diff --git a/README.md b/README.md index b581532..ba81d55 100644 --- a/README.md +++ b/README.md @@ -1,21 +1,79 @@ -# Benchmarking Stochastic Approximation Algorithms for Fairness-Constrained Training of Deep Neural Networks +# humancompatible-train: a package for constrained machine learning [![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) [![Setup](https://github.com/humancompatible/train/actions/workflows/setup.yml/badge.svg)](https://github.com/humancompatible/train/actions/workflows/setup.yml) -This repository provides a tool to compare stochastic-constrained stochastic optimization algorithms on a _fair learning_ task. +The toolkit implements algorithms for constrained training of neural networks based on PyTorch, and inspired by PyTorch's API. + ## Table of Contents 1. [Basic installation instructions](#basic-installation-instructions) -2. [Reproducing the Benchmark](#reproducing-the-benchmark) -3. [Extending the benchmark](#extending-the-benchmark) -4. [License and terms of use](#license-and-terms-of-use) -5. [References](#references) +2. [Using the toolkit](#using-the-toolkit) +3. [Extending the toolkit](#extending-the-toolkit) +4. [Reproducing the Benchmark](#reproducing-the-benchmark) +5. [License and terms of use](#license-and-terms-of-use) +6. [References](#references) -Humancompatible/train is still under active development! If you find bugs or have feature +humancompatible-train is still under active development! If you find bugs or have feature requests, please file a [Github issue](https://github.com/humancompatible/train/issues). -## Basic installation instructions +## Installation + +Use + +``` +pip install humancompatible-train +``` + +The only dependencies of this package are `numpy` and `torch`. + +## Using the toolkit + +The toolkit implements algorithms for constrained training of neural networks based on PyTorch. + +The algorithms follow the `dual_step()` - `step()` framework: taking inspiration from PyTorch, the `double_step` does updates related to the dual parameters and prepares for the primal update (by, e.g., saving constraint gradients), and `step()` updates the primal parameters. + +In general, your code using `humancompatible-train` would look something like this: + +``` +for inputs, labels in dataloader: + # inference + outputs = model(inputs) + # calculate constraints and grads + for constraint in constraints: + c_eval = constraint(outputs, labels) + c_eval.backwards(retain_grad=True) + # depending on optimizer, update dual parameters / save constraint gradient / both + optimizer.dual_step(c_eval) + optimizer.zero_grad() + # calculate objective + loss = criterion(outputs,labels) + loss.backwards() + optimizer.step() + optimizer.zero_grad() +``` + +Our idea is to +1. Deviate minimally from the usual PyTorch workflow +2. Make different stochastic-constrained stochastic optimization algorithms nearly interchangable in the code. + +### Code examples + +You are invited to check out our new API presented in notebooks in the `examples` folder. + +*The legacy API used for the benchmark is presented in `examples/_old_/algorithm_demo.ipynb` and `examples/_old_/constraint_demo.ipynb`.* + +## Extending the toolkit + +### Adding new code + +**To add a new algorithm**, you can subclass the PyTorch ```Optimizer``` class and proceed following the API guideline presented above. + +## Reproducing the Benchmark + +The code used in [our benchmark paper](https://arxiv.org/abs/2507.04033) is not migrated to the new API yet (WIP). + +### Basic installation instructions The code requires Python version ```3.11```. 1. Create a virtual environment @@ -30,13 +88,19 @@ source fairbenchenv/bin/activate python -m venv fairbenchenv fairbenchenv\Scripts\activate.bat ``` -2. Install from source (*as an editable package*). +2. Install from source. ``` git clone https://github.com/humancompatible/train.git cd train pip install -r requirements.txt +pip install . +``` + +If you wish to edit the code of the algorithms, install as an editable package: +``` pip install -e . ``` + __Warning__: it is recommended to use Stochastic Ghost with the mkl-accelerated version of the scipy package with Stochastic Ghost; to install it, run ```pip install --force-reinstall -i https://software.repos.intel.com/python/pypi scipy``` @@ -48,8 +112,6 @@ after installing requirements.txt; otherwise, the algorithm will run slower. How -## Reproducing the Benchmark - ### Running the algorithms The benchmark comprises the following algorithms: @@ -74,7 +136,7 @@ The results will be saved to `experiments/utils/saved_models` and `experiments/u This repository uses [Hydra](https://hydra.cc/) to manage parameters; see `experiments/conf` for configuration files. * To change the parameters of the experiment, such as the number of runs for each algorithm, run time, the dataset used (*note: for now supports only Folktables*) - use `experiment.yaml`. -* To change the dataset settings - such as file location - or do dataset-specific adjustments, use `data/{dataset_name}.yaml` +* To change the dataset settings - such as file location - or do dataset-specific adjustments - such as the configuration of the protected attributes - use `data/{dataset_name}.yaml` * To change algorithm hyperparameters, use `alg/{algorithm_name}.yaml`. * To change constraint hyperparameters, use `constraint/{constraint_name}.yaml` @@ -84,35 +146,12 @@ This repository uses [Hydra](https://hydra.cc/) to manage parameters; see `exper ### Producing plots The plots and tables like the ones in the paper can be produced using the two notebooks. `experiments/algo_plots.ipynb` houses the convergence plots, and `experiments/model_plots.ipynb` - all the others. -## Extending the benchmark - -**To add a new algorithm**, you can subclass the ```Algorithm``` class. Before you can run it, you will need to follow these steps: -1. In the `experiments/conf/alg` folder, add a `.yaml` file with `import_name: {ClassName}` (so the code knows which algorithm to import) and the desired keyword parameter values under `params`: - -``` -import_name: ClassName - -params: - param_name_1: value - param_name_2: value -``` - -2. In `src/algorithms/__init__.py`, add `from .{filename} import {ClassName}` (so the code is able to import it). - -Now you can run the algorithm by executing `python run_folktables.py data=folktables alg={yaml_file_name}`, or by changing the experiment config files. - -**To add a different constraint formulation**, you can use the `FairnessConstraint` class by passing your callable function to the constructor as `fn`. If you use `run_folktables.py`, you can add a new constraint function by following the steps: - -1. Add a `.yaml` file with `import_name: {FunctionName}`, along with the desired batch size and bound (*to be reworked for more generality*), to the `experiments/conf/constraint` folder -2. Import it in `src/constraints/__init__.py` as in step 2 above. - -Now, to run the code with your constraint, use the `constraint` field in the main config. ## License and terms of use -Humancompatible/train is provided under the Apache 2.0 Licence. +humancompatible-train is provided under the Apache 2.0 Licence. -The package relies on the Folktables package, provided under MIT Licence. +The benchmark part of the package relies on the Folktables package, provided under MIT Licence. It provides code to download data from the American Community Survey (ACS) Public Use Microdata Sample (PUMS) files managed by the US Census Bureau. The data itself is governed by the terms of use provided by the Census Bureau. @@ -134,9 +173,9 @@ For more information, see https://www.census.gov/data/developers/about/terms-of- ## Future work -- Add support for fairness constraints with >=2 subgroups (limitation of the code, not of the algorithms) -- Add support to datasets besides Folktables -- Move towards a more PyTorch-like API for optimizers +- Add more algorithms +- Add more examples from different fields where constrained training of DNNs is employed +- Migrate the benchmark to the new API ## References @@ -164,5 +203,4 @@ Facchinei & Kungurtsev (2023) Stochastic Approximation for Expectation Objective Huang, Zhang & Alacaoglu (2025) Stochastic Smoothed Primal-Dual Algorithms for Nonconvex Optimization with Linear Inequality Constraints, arXiv. [4] -Huang & Lin (2023) Oracle Complexity of Single-Loop Switching Subgradient Methods for Non-Smooth Weakly Convex Functional Constrained Optimization, Curran Associates Inc.. - +Huang & Lin (2023) Oracle Complexity of Single-Loop Switching Subgradient Methods for Non-Smooth Weakly Convex Functional Constrained Optimization, Curran Associates Inc.. \ No newline at end of file diff --git a/constraint_demo.ipynb b/constraint_demo.ipynb deleted file mode 100644 index d45ed76..0000000 --- a/constraint_demo.ipynb +++ /dev/null @@ -1,41 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "1efc20cc", - "metadata": {}, - "source": [ - "This notebook will demonstrate the `FairnessConstraint` class and how you can use it to **add a constraint formulation**." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "58feeb34", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "humancompatible", - "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": "3.11.12" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/examples/_old_/algorithm_demo.ipynb b/examples/_old_/algorithm_demo.ipynb new file mode 100644 index 0000000..cdfa46f --- /dev/null +++ b/examples/_old_/algorithm_demo.ipynb @@ -0,0 +1,604 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "1efc20cc", + "metadata": {}, + "source": [ + "This notebook will demonstrate how to use the **constrained training algorithms** implemented in this toolkit." + ] + }, + { + "cell_type": "markdown", + "id": "790ccbc7", + "metadata": {}, + "source": [ + "To train a network, instantiate an algorithm, passing to it the model, the dataset, a list of `FairnessConstraint`s and the algorithm's hyperparameters." + ] + }, + { + "cell_type": "markdown", + "id": "5bfe05ba", + "metadata": {}, + "source": [ + "Load and prepare data from `folktables`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "58feeb34", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading data for 2018 1-Year person survey for OK...\n", + "Protected attribute: RAC1P\n", + "Number of subgroups considered: 6\n", + "Size of subgroups: [10685, 794, 1213, 259, 315, 997]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\andre\\miniconda3\\envs\\hc-mkl\\Lib\\site-packages\\pandas\\core\\computation\\expressions.py:73: RuntimeWarning: invalid value encountered in greater\n", + " return op(a, b)\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.preprocessing import StandardScaler\n", + "import torch\n", + "from folktables import ACSDataSource, ACSIncome\n", + "\n", + "device = 'cpu'\n", + "torch.set_default_device(device)\n", + "\n", + "# load folktables data\n", + "data_source = ACSDataSource(survey_year='2018', horizon='1-Year', survey='person')\n", + "acs_data = data_source.get_data(states=[\"OK\"], download=True)\n", + "features, labels, groups = ACSIncome.df_to_numpy(acs_data)\n", + "# split\n", + "X_train, X_test, y_train, y_test, groups_train, groups_test = train_test_split(\n", + " features, labels, groups, test_size=0.2, random_state=42)\n", + "# scale\n", + "scaler = StandardScaler()\n", + "X_train = scaler.fit_transform(X_train)\n", + "X_test = scaler.transform(X_test)\n", + "\n", + "# make into a pytorch dataset, remove the sensitive attribute (RAC1P)\n", + "features_train = torch.tensor(X_train, dtype=torch.float32)[:,:-1].to(device)\n", + "labels_train = torch.tensor(y_train,dtype=torch.float32).to(device)\n", + "dataset_train = torch.utils.data.TensorDataset(features_train, labels_train)\n", + "\n", + "c_batch_size = 128\n", + "min_subgroup_size = c_batch_size\n", + "# For each subgroup, FairnessConstraint needs a list of indices of samples belonging to that subgroup\n", + "group_indices_train = [\n", + " np.nonzero(groups_train == group_id)[0] for group_id in np.unique(groups_train)\n", + " if np.count_nonzero(groups == group_id) > min_subgroup_size\n", + "]\n", + "\n", + "# repeat for test set\n", + "features_test = torch.tensor(X_test, dtype=torch.float32)[:,:-1].to(device)\n", + "labels_test = torch.tensor(y_test,dtype=torch.float32).to(device)\n", + "dataset_test = torch.utils.data.TensorDataset(features_test, labels_test)\n", + "group_indices_test = [\n", + " np.nonzero(groups_test == group_id)[0] for group_id in np.unique(groups_test)\n", + " if np.count_nonzero(groups == group_id) > min_subgroup_size\n", + "]\n", + "\n", + "print(f'Protected attribute: {ACSIncome.group}')\n", + "print(f'Number of subgroups considered: {len(group_indices_train)}')\n", + "print(f'Size of subgroups: {[len(g) for g in group_indices_train]}')" + ] + }, + { + "cell_type": "markdown", + "id": "4feed165", + "metadata": {}, + "source": [ + "Let's say we want to add an equal loss constraint on the model.\n", + "\n", + "We can do that by using the `FairnessConstraint` class, which will handle sampling (if possible, sampling an equal number of samples from each relevant subgroup in each minibatch), and passing it the function that will calculate the value of the constraint." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c3a2ead3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of constraints: 15\n" + ] + } + ], + "source": [ + "from itertools import combinations\n", + "from humancompatible.train.fairness.constraints import FairnessConstraint\n", + "from humancompatible.train.fairness.constraints.constraint_fns import abs_loss_equality, tpr_equality\n", + "\n", + "# the protected attribute is \"Race\" (RAC1P)\n", + "# we put a pairwise constraint on each combination of subgroups\n", + "constraint_bound = 0.01\n", + "constraints = []\n", + "for gr1, gr2 in combinations(group_indices_train, 2):\n", + " c = FairnessConstraint(\n", + " dataset=dataset_train,\n", + " group_indices=[gr1, gr2],\n", + " # subtract bound from absolute loss difference to bring constraint to form $c \\leq 0$\n", + " # also implemented are fairret wrappers, e.g. equal TPR\n", + " fn=lambda model, samples: abs_loss_equality(torch.nn.BCEWithLogitsLoss(), model, samples) - constraint_bound,\n", + " batch_size=c_batch_size,\n", + " device=device\n", + " )\n", + "\n", + " constraints.append(c)\n", + "\n", + "print(f'Number of constraints: {len(constraints)}')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d6ed01b9", + "metadata": {}, + "outputs": [], + "source": [ + "# helper function to analyze model performance\n", + "\n", + "def model_stats(model, features, labels, groups, constraints, constraint_bound):\n", + " with torch.inference_mode():\n", + " gr_ind = list(combinations(groups, 2))\n", + " vals = []\n", + " acc_dif = []\n", + " for i, c in enumerate(constraints):\n", + " idx1, idx2 = gr_ind[i]\n", + " val = c.eval(model, [(features[idx1], labels[idx1]), (features[idx2], labels[idx2])]) + constraint_bound\n", + " vals.append(val.cpu().numpy().item())\n", + "\n", + " logits1 = model(features[idx1])\n", + " logits2 = model(features[idx2])\n", + " outs1 = torch.nn.functional.sigmoid(logits1).cpu().numpy()\n", + " outs2 = torch.nn.functional.sigmoid(logits2).cpu().numpy()\n", + " preds1 = (outs1.T > 0.5).astype(float)\n", + " preds2 = (outs2.T > 0.5).astype(float) \n", + " acc1 = np.mean(preds1 == labels[idx1].cpu().numpy())\n", + " acc2 = np.mean(preds2 == labels[idx2].cpu().numpy())\n", + " acc_dif.append(abs(acc1-acc2))\n", + "\n", + " print(f'constraints (should be <= {constraint_bound}):')\n", + " print(np.round(vals, decimals=3))\n", + " print(f'c mean: {np.mean(vals)}')\n", + " print(f'c min: {np.min(vals)}')\n", + " print(f'c max: {np.max(vals)}')\n", + " print('---')\n", + "\n", + " logits = model(features)\n", + " outs = torch.nn.functional.sigmoid(logits).cpu().numpy()\n", + " preds = (outs.T > 0.5).astype(float)\n", + " acc = np.sum(preds == labels.cpu().numpy())/len(labels)\n", + " print(f'accuracy: {acc}')\n", + " print('accuracy abs. difference:')\n", + " print(np.round(acc_dif, decimals=3))\n", + " print(f'acc abs dif mean: {np.mean(acc_dif)}')\n", + " print(f'acc abs dif min: {np.min(acc_dif)}')\n", + " print(f'acc abs dif max: {np.max(acc_dif)}')" + ] + }, + { + "cell_type": "markdown", + "id": "ea06f697", + "metadata": {}, + "source": [ + "---\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "b26213fe", + "metadata": {}, + "source": [ + "For comparison, let us first train a model **without constraints**." + ] + }, + { + "cell_type": "markdown", + "id": "7ec89642", + "metadata": {}, + "source": [ + "Define a model:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4c957562", + "metadata": {}, + "outputs": [], + "source": [ + "from torch.nn import Sequential\n", + "hsize1 = 64\n", + "hsize2 = 32\n", + "model_uncon = Sequential(\n", + " torch.nn.Linear(features_train.shape[1], hsize1),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize1, hsize2),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize2, 1)\n", + ").to(device)" + ] + }, + { + "cell_type": "markdown", + "id": "6409a977", + "metadata": {}, + "source": [ + "And start training:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8793a889", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 0, loss: 0.46349757064932157\n", + "Epoch: 1, loss: 0.4295002950488457\n", + "Epoch: 2, loss: 0.4227255582809448\n", + "Epoch: 3, loss: 0.4194903533040945\n", + "Epoch: 4, loss: 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0.3927339928756867\n", + "Epoch: 28, loss: 0.39265128787207815\n", + "Epoch: 29, loss: 0.39145034085959196\n", + "Epoch: 30, loss: 0.3911734277249447\n", + "Epoch: 31, loss: 0.39005530682126327\n", + "Epoch: 32, loss: 0.3902694277265774\n", + "Epoch: 33, loss: 0.3899349652430309\n", + "Epoch: 34, loss: 0.38934317380855127\n", + "Epoch: 35, loss: 0.38934725685976446\n", + "Epoch: 36, loss: 0.3888395121986313\n", + "Epoch: 37, loss: 0.38758641937082366\n", + "Epoch: 38, loss: 0.3866228824813983\n", + "Epoch: 39, loss: 0.3872190235249166\n", + "Epoch: 40, loss: 0.3865409423929772\n", + "Epoch: 41, loss: 0.38718925948653904\n", + "Epoch: 42, loss: 0.38601168897002935\n", + "Epoch: 43, loss: 0.38557462982966434\n", + "Epoch: 44, loss: 0.38449275343944983\n", + "Epoch: 45, loss: 0.3835361286266042\n", + "Epoch: 46, loss: 0.3837257699841367\n", + "Epoch: 47, loss: 0.38322850596159697\n", + "Epoch: 48, loss: 0.38279763529343264\n", + "Epoch: 49, loss: 0.38252385719014065\n", + "Epoch: 50, loss: 0.38216987398586105\n", + "Epoch: 51, loss: 0.38258736544022603\n", + "Epoch: 52, loss: 0.381573615063514\n", + "Epoch: 53, loss: 0.38164684093291207\n", + "Epoch: 54, loss: 0.3804648918698409\n", + "Epoch: 55, loss: 0.38036493870562743\n", + "Epoch: 56, loss: 0.3794036984576711\n", + "Epoch: 57, loss: 0.3797108101924615\n", + "Epoch: 58, loss: 0.3796296337885516\n", + "Epoch: 59, loss: 0.37813905576643136\n", + "Epoch: 60, loss: 0.37894386132912977\n", + "Epoch: 61, loss: 0.37890936424290494\n", + "Epoch: 62, loss: 0.3780763379763812\n", + "Epoch: 63, loss: 0.37740884787802187\n", + "Epoch: 64, loss: 0.37799342365802396\n", + "Epoch: 65, loss: 0.37659537815488875\n", + "Epoch: 66, loss: 0.37684703967534006\n", + "Epoch: 67, loss: 0.3764669771439263\n", + "Epoch: 68, loss: 0.3760061870395605\n", + "Epoch: 69, loss: 0.3761867823944028\n", + "Epoch: 70, loss: 0.3747647256324334\n", + "Epoch: 71, loss: 0.3744730817353619\n", + "Epoch: 72, loss: 0.37441441598015707\n", + "Epoch: 73, loss: 0.3742638121226004\n", + "Epoch: 74, loss: 0.3730027308421476\n", + "Epoch: 75, loss: 0.3727368223148265\n", + "Epoch: 76, loss: 0.3718348775125508\n", + "Epoch: 77, loss: 0.3718047884758562\n", + "Epoch: 78, loss: 0.37228686126348165\n", + "Epoch: 79, loss: 0.37233117039847585\n", + "Epoch: 80, loss: 0.37078445783949326\n", + "Epoch: 81, loss: 0.3705418659706733\n", + "Epoch: 82, loss: 0.37155885764929864\n", + "Epoch: 83, loss: 0.37024217863966313\n", + "Epoch: 84, loss: 0.37042985863185357\n", + "Epoch: 85, loss: 0.37004580155813266\n", + "Epoch: 86, loss: 0.36969783486399266\n", + "Epoch: 87, loss: 0.3688722074231399\n", + "Epoch: 88, loss: 0.3681897620470928\n", + "Epoch: 89, loss: 0.3689138336173658\n", + "Epoch: 90, loss: 0.36889166102212456\n", + "Epoch: 91, loss: 0.3685122812499425\n", + "Epoch: 92, loss: 0.3678717091679573\n", + "Epoch: 93, loss: 0.36827987069929286\n", + "Epoch: 94, loss: 0.36637745135729866\n", + "Epoch: 95, loss: 0.3662173674841012\n", + "Epoch: 96, loss: 0.3667734933218786\n", + "Epoch: 97, loss: 0.36630333584201125\n", + "Epoch: 98, loss: 0.36586450858573827\n", + "Epoch: 99, loss: 0.3652148133675967\n" + ] + } + ], + "source": [ + "from torch.optim import Adam\n", + "\n", + "loader = torch.utils.data.DataLoader(dataset_train, batch_size=32, shuffle=(device != 'cuda'))\n", + "loss = torch.nn.BCEWithLogitsLoss()\n", + "optimizer = Adam(model_uncon.parameters())\n", + "epochs = 100\n", + "\n", + "for epoch in range(epochs):\n", + " losses = []\n", + " for batch_feat, batch_label in loader:\n", + " optimizer.zero_grad()\n", + "\n", + " logit = model_uncon(batch_feat)\n", + " loss = torch.nn.functional.binary_cross_entropy_with_logits(logit.squeeze(), batch_label)\n", + " loss.backward()\n", + "\n", + " optimizer.step()\n", + " losses.append(loss.item())\n", + " print(f\"Epoch: {epoch}, loss: {np.mean(losses)}\")" + ] + }, + { + "cell_type": "markdown", + "id": "ec6ebc1d", + "metadata": {}, + "source": [ + "Let's now analyze how well the **unconstrained** model does in terms of constraints:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bd84ec11", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "TRAIN\n", + "constraints (should be <= 0.01):\n", + "[0.097 0.015 0.062 0.183 0.055 0.081 0.035 0.086 0.041 0.047 0.168 0.04\n", + " 0.121 0.007 0.128]\n", + "c mean: 0.0777715116739273\n", + "c min: 0.006703734397888184\n", + "c max: 0.1832037717103958\n", + "---\n", + "accuracy: 0.8240424195911533\n", + "accuracy abs. difference:\n", + "[0.063 0.004 0.022 0.102 0.023 0.059 0.041 0.038 0.041 0.018 0.097 0.018\n", + " 0.08 0.001 0.079]\n", + "acc abs dif mean: 0.045657815374404734\n", + "acc abs dif min: 0.0006777088020819555\n", + "acc abs dif max: 0.10155016303823039\n" + ] + } + ], + "source": [ + "print('TRAIN')\n", + "model_stats(model_uncon, features_train, labels_train, group_indices_train, constraints, constraint_bound)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "101e001e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "TEST\n", + "constraints (should be <= 0.01):\n", + "[0.079 0.057 0.112 0.03 0.075 0.137 0.191 0.109 0.004 0.055 0.027 0.132\n", + " 0.082 0.187 0.105]\n", + "c mean: 0.09223249951998393\n", + "c min: 0.004368424415588379\n", + "c max: 0.19137758016586304\n", + "---\n", + "accuracy: 0.794921875\n", + "accuracy abs. difference:\n", + "[0.022 0.016 0.011 0.083 0.043 0.038 0.033 0.061 0.021 0.005 0.099 0.059\n", + " 0.094 0.054 0.04 ]\n", + "acc abs dif mean: 0.04521909230893753\n", + "acc abs dif min: 0.004741402801242578\n", + "acc abs dif max: 0.09864360424289464\n" + ] + } + ], + "source": [ + "print('TEST')\n", + "model_stats(model_uncon, features_test, labels_test, group_indices_test, constraints, constraint_bound)" + ] + }, + { + "cell_type": "markdown", + "id": "e16c4fa0", + "metadata": {}, + "source": [ + "---\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "a3dbc50a", + "metadata": {}, + "source": [ + "Now let us train the same model with one of the **constrained** training algorithms:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8564545d", + "metadata": {}, + "outputs": [], + "source": [ + "from humancompatible.train.algorithms import SSLALM, SSG\n", + "from torch.nn import Sequential\n", + "\n", + "hsize1 = 64\n", + "hsize2 = 32\n", + "model = Sequential(\n", + " torch.nn.Linear(features_train.shape[1], hsize1),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize1, hsize2),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize2, 1)\n", + ")\n", + "\n", + "optimizer = SSG(\n", + " net=model,\n", + " data=dataset_train,\n", + " loss=torch.nn.BCEWithLogitsLoss(),\n", + " constraints=constraints\n", + ")\n", + "\n", + "history = optimizer.optimize(\n", + " max_runtime=180,\n", + " batch_size=32,\n", + " seed=42,\n", + " device=device,\n", + " ctol=1.0,\n", + " f_stepsize_rule='dimin',\n", + " f_stepsize=0.1,\n", + " c_stepsize_rule='dimin',\n", + " c_stepsize=0.1,\n", + " verbose=False\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a329bf12", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "TRAIN\n", + "constraints (should be <= 0.01):\n", + "[0.008 0.01 0.002 0.009 0.01 0.002 0.01 0.001 0.002 0.011 0.001 0.001\n", + " 0.011 0.012 0.002]\n", + "c mean: 0.006037203470865885\n", + "c min: 0.0006375312805175781\n", + "c max: 0.012136995792388916\n", + "---\n", + "accuracy: 0.7662038652061676\n", + "accuracy abs. difference:\n", + "[0.05 0.026 0.071 0.121 0.037 0.024 0.021 0.071 0.012 0.046 0.095 0.012\n", + " 0.05 0.034 0.084]\n", + "acc abs dif mean: 0.050338703671629736\n", + "acc abs dif min: 0.011668145409021724\n", + "acc abs dif max: 0.12120685429061662\n" + ] + } + ], + "source": [ + "print('TRAIN')\n", + "model_stats(model, features_train, labels_train, group_indices_train, constraints, constraint_bound)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "372e50f9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "TEST\n", + "constraints (should be <= 0.01):\n", + "[0.005 0.001 0.021 0.007 0.014 0.006 0.026 0.012 0.009 0.02 0.006 0.015\n", + " 0.014 0.035 0.021]\n", + "c mean: 0.0140508770942688\n", + "c min: 0.0007504820823669434\n", + "c max: 0.03483313322067261\n", + "---\n", + "accuracy: 0.7642299107142857\n", + "accuracy abs. difference:\n", + "[0.056 0.002 0.006 0.06 0.041 0.054 0.05 0.003 0.015 0.004 0.057 0.039\n", + " 0.053 0.035 0.018]\n", + "acc abs dif mean: 0.033019134885242975\n", + "acc abs dif min: 0.0023696482327177915\n", + "acc abs dif max: 0.059619158525802796\n" + ] + } + ], + "source": [ + "print('TEST')\n", + "model_stats(model, features_test, labels_test, group_indices_test, constraints, constraint_bound)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "hc-mkl", + "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" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/_old_/constraint_demo.ipynb b/examples/_old_/constraint_demo.ipynb new file mode 100644 index 0000000..25efc25 --- /dev/null +++ b/examples/_old_/constraint_demo.ipynb @@ -0,0 +1,126 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "1efc20cc", + "metadata": {}, + "source": [ + "This notebook will demonstrate the `FairnessConstraint` class and how you can use it to **add a constraint**." + ] + }, + { + "cell_type": "markdown", + "id": "790ccbc7", + "metadata": {}, + "source": [ + "**Fairness constraints** typically involve working with numerous **protected groups** - as such, **sampling** data to evaluate them can sometimes be tricky. Ideally, each minibatch should **contain samples from each of the protected groups** ...\n", + "\n", + "`FairnessConstraint` provides the functionality to sample for and evaluate user-defined fairness constraints." + ] + }, + { + "cell_type": "markdown", + "id": "5bfe05ba", + "metadata": {}, + "source": [ + "A toy example: we have a dataset of 10 samples with 2 groups. We want to add an \"equal loss\" constraint on them." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "58feeb34", + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "from humancompatible.train.fairness.constraints import FairnessConstraint\n", + "from humancompatible.train.fairness.constraints.constraint_fns import abs_loss_equality\n", + " \n", + "# the toy dataset\n", + "features = torch.arange(0,10)\n", + "# encode group membership of each sample\n", + "group_membership = torch.repeat_interleave(torch.tensor([0,1]), 5)\n", + "labels = group_membership\n", + "dataset = torch.utils.data.TensorDataset(features, labels)\n", + "\n", + "# For each subgroup, FairnessConstraint needs a list of indices of samples belonging to that subgroup\n", + "group_indices = [(group_membership == gr_idx).nonzero(as_tuple=True)[0] for gr_idx in group_membership.unique()]\n", + "\n", + "c = FairnessConstraint(\n", + " dataset=dataset,\n", + " group_indices=group_indices,\n", + " fn=abs_loss_equality,\n", + " batch_size=2,\n", + " seed=42\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "581e2463", + "metadata": {}, + "source": [ + "The constructor creates a `DataLoader` for each of the subgroup. Now, when you call `sample_loader()`, it will return a `(features: torch.Tensor, labels: torch.Tensor)` tuple for each subrgoup, with specified batch size:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "058dfa79", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[[tensor([1, 4]), tensor([0, 0])], [tensor([5, 7]), tensor([1, 1])]]" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c.sample_loader()" + ] + }, + { + "cell_type": "markdown", + "id": "58ff4a55", + "metadata": {}, + "source": [ + "When one of the dataloaders runs out, it is reset just like during normal PyTorch training process." + ] + }, + { + "cell_type": "markdown", + "id": "b284acab", + "metadata": {}, + "source": [ + "What about the constraint itself?\n", + "The constraint formulation is defined by the `fn` argument. When you call the `eval(net, sample)` method of a `FairnessConstraint`, it just passes those arguments plus kwargs to the constraint function and returns the result. It is expected that the constraint function takes the **model** and the **minibatch** in format specified above as the arguments." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "hc-mkl", + "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" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/constrained_training.ipynb b/examples/constrained_training.ipynb new file mode 100644 index 0000000..9e095f6 --- /dev/null +++ b/examples/constrained_training.ipynb @@ -0,0 +1,1159 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "1efc20cc", + "metadata": {}, + "source": [ + "This notebook will demonstrate how to use the **constrained training algorithms** implemented in this toolkit with **PyTorch**-like API." + ] + }, + { + "cell_type": "markdown", + "id": "790ccbc7", + "metadata": {}, + "source": [ + "The algorithms implemented in the **humancompatible.train.torch** subpackage share a similar idea. Before the training, you initialize an algorithm like you would a PyTorch one. Then, during the training process, you:\n", + "\n", + "1. Evaluate a constraint and compute its gradient\n", + "2. Call the `dual_step` function to update dual parameters and save the constraint gradient for the primal update\n", + "3. Call the `step` function to update the primal parameters (generally, model weights)" + ] + }, + { + "cell_type": "markdown", + "id": "8d3224eb", + "metadata": {}, + "source": [ + "Let's try the Stochastic Smooth Linearized Augmented Lagrangian (SSLALM) algorithm on a constrained learning task." + ] + }, + { + "cell_type": "markdown", + "id": "af7f86ab", + "metadata": {}, + "source": [ + "Let's train a simple classification model, putting a constraint on the norm of each layer's parameters.\n", + "\n", + "In the canonical form, the algorithm expects equality constraints that are equal to 0; however, we can easily transform arbitrary inequality constraints to that form." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "48b9577d", + "metadata": {}, + "outputs": [], + "source": [ + "# load and prepare data\n", + "\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.preprocessing import StandardScaler\n", + "import torch\n", + "import numpy as np\n", + "from folktables import ACSDataSource, ACSIncome, generate_categories\n", + "\n", + "# load folktables data\n", + "data_source = ACSDataSource(survey_year='2018', horizon='1-Year', survey='person')\n", + "acs_data = data_source.get_data(states=[\"VA\"], download=True)\n", + "definition_df = data_source.get_definitions(download=True)\n", + "categories = generate_categories(features=ACSIncome.features, definition_df=definition_df)\n", + "df_feat, df_labels, _ = ACSIncome.df_to_pandas(acs_data,categories=categories, dummies=True)\n", + "\n", + "sens_cols = ['SEX_Female', 'SEX_Male']\n", + "features = df_feat.drop(columns=sens_cols).to_numpy(dtype=\"float\")\n", + "groups = df_feat[sens_cols].to_numpy(dtype=\"float\")\n", + "labels = df_labels.to_numpy(dtype=\"float\")\n", + "# split\n", + "X_train, X_test, y_train, y_test, groups_train, groups_test = train_test_split(\n", + " features, labels, groups, test_size=0.2, random_state=42)\n", + "# scale\n", + "scaler = StandardScaler()\n", + "X_train = scaler.fit_transform(X_train)\n", + "X_test = scaler.transform(X_test)\n", + "\n", + "# make into a pytorch dataset, remove the sensitive attribute\n", + "features_train = torch.tensor(X_train, dtype=torch.float32)\n", + "labels_train = torch.tensor(y_train,dtype=torch.float32)\n", + "sens_train = torch.tensor(groups_train)\n", + "dataset_train = torch.utils.data.TensorDataset(features_train, labels_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "834e083e", + "metadata": {}, + "outputs": [], + "source": [ + "from humancompatible.train.algorithms import SSLALM\n", + "import torch\n", + "from torch.nn import Sequential\n", + "\n", + "dataloader = torch.utils.data.DataLoader(dataset_train, batch_size=16, shuffle=True)\n", + "\n", + "hsize1 = 64\n", + "hsize2 = 32\n", + "model = Sequential(\n", + " torch.nn.Linear(features_train.shape[1], hsize1),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize1, hsize2),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize2, 1)\n", + ")\n", + "\n", + "m = len(list(model.parameters()))\n", + "\n", + "optimizer = SSLALM(\n", + " params=model.parameters(),\n", + " m=m,\n", + " lr=0.01,\n", + " dual_lr=0.1\n", + ")\n", + "# bounds for the constraints: norm of each param group should be <= 1\n", + "constraint_bounds = [1.]*m\n", + "\n", + "epochs = 10\n", + "criterion = torch.nn.BCEWithLogitsLoss()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ea8758f7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 0, loss: 0.5559760332107544, constraints: [0.91737795 0.30318373 0.9765759 0.51893866 0.91513544 0.16496846], dual: [0.14526425 0. 0.16194636 0. 0.18826969 0. ]\n", + "Epoch: 1, loss: 0.451104074716568, constraints: [0.99989265 0.74805677 0.9999066 0.68494964 0.9997819 0.30124232], dual: [0.20154439 0. 0.23898543 0. 0.2657407 0. ]\n", + "Epoch: 2, loss: 0.4313131868839264, constraints: [0.9995655 0.99329156 0.999513 0.7401734 0.9993561 0.30543154], dual: [0.24007902 0.03688543 0.29564866 0. 0.32183442 0. ]\n", + "Epoch: 3, loss: 0.4230686128139496, constraints: [0.9993245 0.99980736 0.999204 0.7695187 0.9990042 0.29860938], dual: [0.27040952 0.04574572 0.3421067 0. 0.36567575 0. ]\n", + "Epoch: 4, loss: 0.4171927869319916, constraints: [0.999209 0.99974847 0.9988674 0.7896771 0.99875087 0.29188126], dual: [0.2937199 0.05142263 0.3789018 0. 0.40203938 0. ]\n", + "Epoch: 5, loss: 0.411997526884079, constraints: [0.9991832 0.9997038 0.9986903 0.80403227 0.9985356 0.29104593], dual: [0.3148753 0.0556339 0.4104012 0. 0.43517974 0. ]\n", + "Epoch: 6, loss: 0.4084599018096924, constraints: [0.9992076 0.99964964 0.99854374 0.81644124 0.9983635 0.28951004], dual: [0.33437052 0.05873958 0.4407348 0. 0.4652856 0. ]\n", + "Epoch: 7, loss: 0.4049149453639984, constraints: [0.9992023 0.9996763 0.9983643 0.8254219 0.9982158 0.28898498], dual: [0.35126206 0.06172189 0.4677158 0. 0.4927429 0. ]\n", + "Epoch: 8, loss: 0.40224578976631165, constraints: [0.9992311 0.99960256 0.9982846 0.8321669 0.99801767 0.29036668], dual: [0.36736622 0.06378309 0.49475437 0. 0.51823753 0. ]\n", + "Epoch: 9, loss: 0.3998371958732605, constraints: [0.99921805 0.9996137 0.9980073 0.8389309 0.9979264 0.29086685], dual: [0.38295138 0.06551965 0.51818824 0. 0.5431031 0. ]\n" + ] + } + ], + "source": [ + "for epoch in range(epochs):\n", + " loss_log = []\n", + " c_log = []\n", + " slack_log = []\n", + " duals_log = []\n", + " for batch_input, batch_label in dataloader:\n", + " # calculate constraints and constraint grads\n", + " c_log.append([])\n", + " for i, param in enumerate(model.parameters()):\n", + " norm = torch.linalg.norm(param, ord=2)\n", + " # convert constraint to equality\n", + " norm_viol = torch.max(\n", + " norm \n", + " - constraint_bounds[i],\n", + " torch.zeros(1)\n", + " )\n", + " norm_viol.backward()\n", + " # for the Lagrangian family of algorithms, dual_step requires the index of constraint and the value as arguments\n", + " # to update the corresponding dual multiplier\n", + " # in a stochastic-constrained setting, this estimate needs (in theory) to be independent from the one used to update dual parameters\n", + " # in practice, it makes little difference \n", + " optimizer.dual_step(i, c_val=norm_viol)\n", + " optimizer.zero_grad()\n", + " c_log[-1].append(norm.detach().numpy())\n", + " \n", + " # calculate loss and grad\n", + " batch_output = model(batch_input)\n", + " loss = criterion(batch_output, batch_label)\n", + " loss.backward()\n", + " loss_log.append(loss.detach().numpy())\n", + " duals_log.append(optimizer._dual_vars.detach())\n", + " optimizer.step()\n", + " optimizer.zero_grad()\n", + " \n", + " print(\n", + " f\"Epoch: {epoch}, \"\n", + " f\"loss: {np.mean(loss_log)}, \"\n", + " f\"constraints: {np.mean(c_log, axis=0)}, \"\n", + " f\"dual: {np.mean(duals_log, axis=0)}\"\n", + " )" + ] + }, + { + "cell_type": "markdown", + "id": "30a4e546", + "metadata": {}, + "source": [ + "The model is now trained subject to the constraints we set." + ] + }, + { + "cell_type": "markdown", + "id": "ea06f697", + "metadata": {}, + "source": [ + "---\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "bd2f190b", + "metadata": {}, + "source": [ + "It is also possible to train a network subject to **stochastic constraints**. One of the main use-cases for that is **fairness**. Let's train a network on the `folktables` dataset without constraints first, so we can identify some biases:" + ] + }, + { + "cell_type": "markdown", + "id": "7ec89642", + "metadata": {}, + "source": [ + "Define a model:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4c957562", + "metadata": {}, + "outputs": [], + "source": [ + "from torch.nn import Sequential\n", + "hsize1 = 64\n", + "hsize2 = 32\n", + "model_uncon = Sequential(\n", + " torch.nn.Linear(features_train.shape[1], hsize1),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize1, hsize2),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize2, 1)\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "6409a977", + "metadata": {}, + "source": [ + "And start training:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8793a889", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 0, loss: 0.4347502906876172\n", + "Epoch: 1, loss: 0.39616607425111366\n", + "Epoch: 2, loss: 0.3803682842677656\n", + "Epoch: 3, loss: 0.36906123785641\n", + "Epoch: 4, loss: 0.35617675897269874\n", + "Epoch: 5, loss: 0.3407004922434713\n", + "Epoch: 6, loss: 0.32453690413740727\n", + "Epoch: 7, loss: 0.3077362470128662\n", + "Epoch: 8, loss: 0.2909023775355939\n", + "Epoch: 9, loss: 0.27703681499237254\n", + "Epoch: 10, loss: 0.25923273601105995\n", + "Epoch: 11, loss: 0.24734333765118396\n", + "Epoch: 12, loss: 0.23562498148865643\n", + "Epoch: 13, loss: 0.2216183516476142\n", + "Epoch: 14, loss: 0.21393390793790734\n", + "Epoch: 15, loss: 0.20235857262348342\n", + "Epoch: 16, loss: 0.19367398184129364\n", + "Epoch: 17, loss: 0.18549755612789176\n", + "Epoch: 18, loss: 0.17622195665972337\n", + "Epoch: 19, loss: 0.17113913496894895\n", + "Epoch: 20, loss: 0.16546863001624793\n", + "Epoch: 21, loss: 0.1577721542313185\n", + "Epoch: 22, loss: 0.15047499655759644\n", + "Epoch: 23, loss: 0.14970412313719433\n", + "Epoch: 24, loss: 0.1444376527208545\n", + "Epoch: 25, loss: 0.13948282646024113\n", + "Epoch: 26, loss: 0.13189793694390617\n", + "Epoch: 27, loss: 0.13196727598255326\n", + "Epoch: 28, loss: 0.1282071336502335\n", + "Epoch: 29, loss: 0.12355432915780293\n", + "Epoch: 30, loss: 0.1198987612153054\n", + "Epoch: 31, loss: 0.11910682175911078\n", + "Epoch: 32, loss: 0.11250700417492716\n", + "Epoch: 33, loss: 0.11242990967761503\n", + "Epoch: 34, loss: 0.10754635257826538\n", + "Epoch: 35, loss: 0.10808734387594947\n", + "Epoch: 36, loss: 0.10446399722273983\n", + "Epoch: 37, loss: 0.10137819896590687\n", + "Epoch: 38, loss: 0.09824282584325755\n", + "Epoch: 39, loss: 0.09761354314009757\n", + "Epoch: 40, loss: 0.09629385479537075\n", + "Epoch: 41, loss: 0.0980458986942506\n", + "Epoch: 42, loss: 0.09241889443527279\n", + "Epoch: 43, loss: 0.08775029779491787\n", + "Epoch: 44, loss: 0.09480425191157296\n", + "Epoch: 45, loss: 0.08960090783067486\n", + "Epoch: 46, loss: 0.08645440529421625\n", + "Epoch: 47, loss: 0.08848531700701591\n", + "Epoch: 48, loss: 0.08257072548864597\n", + "Epoch: 49, loss: 0.08516274812671665\n", + "Epoch: 50, loss: 0.08246131248908278\n", + "Epoch: 51, loss: 0.08108251444005035\n", + "Epoch: 52, loss: 0.077191001967496\n", + "Epoch: 53, loss: 0.0829771353439806\n", + "Epoch: 54, loss: 0.07923281729589933\n", + "Epoch: 55, loss: 0.07383052453275467\n", + "Epoch: 56, loss: 0.0772944877691194\n", + "Epoch: 57, loss: 0.07454561611126437\n", + "Epoch: 58, loss: 0.0742188997714782\n", + "Epoch: 59, loss: 0.07355393029622771\n", + "Epoch: 60, loss: 0.0697388788985484\n", + "Epoch: 61, loss: 0.07458990502004269\n", + "Epoch: 62, loss: 0.07110446929254989\n", + "Epoch: 63, loss: 0.07200490791683478\n", + "Epoch: 64, loss: 0.06962692059076966\n", + "Epoch: 65, loss: 0.07062180563546375\n", + "Epoch: 66, loss: 0.06986464381293794\n", + "Epoch: 67, loss: 0.07094456208266448\n", + "Epoch: 68, loss: 0.06910460650539003\n", + "Epoch: 69, loss: 0.06356872942972283\n", + "Epoch: 70, loss: 0.06500895586004048\n", + "Epoch: 71, loss: 0.06496120100553573\n", + "Epoch: 72, loss: 0.06516535142350358\n", + "Epoch: 73, loss: 0.0625493444946909\n", + "Epoch: 74, loss: 0.0643912013601416\n", + "Epoch: 75, loss: 0.0650474983162311\n", + "Epoch: 76, loss: 0.060230221252792614\n", + "Epoch: 77, loss: 0.0630991333682761\n", + "Epoch: 78, loss: 0.06679340553298452\n", + "Epoch: 79, loss: 0.05962247319382759\n", + "Epoch: 80, loss: 0.05913202169742904\n", + "Epoch: 81, loss: 0.060647026409740734\n", + "Epoch: 82, loss: 0.058496695048014934\n", + "Epoch: 83, loss: 0.058554264080446734\n", + "Epoch: 84, loss: 0.05841069125057187\n", + "Epoch: 85, loss: 0.055307874043951155\n", + "Epoch: 86, loss: 0.05863243487901814\n", + "Epoch: 87, loss: 0.05677493428852676\n", + "Epoch: 88, loss: 0.058535073186499316\n", + "Epoch: 89, loss: 0.0591084572531721\n", + "Epoch: 90, loss: 0.05810895870381086\n", + "Epoch: 91, loss: 0.05616463630724945\n", + "Epoch: 92, loss: 0.0571854826372277\n", + "Epoch: 93, loss: 0.05417437522650802\n", + "Epoch: 94, loss: 0.05881660859306018\n", + "Epoch: 95, loss: 0.05910663971227885\n", + "Epoch: 96, loss: 0.05401602186099406\n", + "Epoch: 97, loss: 0.05149090717909237\n", + "Epoch: 98, loss: 0.05482359819341903\n", + "Epoch: 99, loss: 0.054031581708226376\n" + ] + } + ], + "source": [ + "from torch.optim import Adam\n", + "\n", + "loader = torch.utils.data.DataLoader(dataset_train, batch_size=256, shuffle=True)\n", + "loss = torch.nn.BCEWithLogitsLoss()\n", + "optimizer = Adam(model_uncon.parameters())\n", + "epochs = 100\n", + "\n", + "for epoch in range(epochs):\n", + " losses = []\n", + " for batch_feat, batch_label in dataloader:\n", + " optimizer.zero_grad()\n", + "\n", + " logit = model_uncon(batch_feat)\n", + " loss = torch.nn.functional.binary_cross_entropy_with_logits(logit, batch_label)\n", + " loss.backward()\n", + "\n", + " optimizer.step()\n", + " losses.append(loss.item())\n", + " print(f\"Epoch: {epoch}, loss: {np.mean(losses)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9fd521be", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor([0.3648, 0.5193], dtype=torch.float64, grad_fn=)" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from fairret.statistic import PositiveRate, TruePositiveRate\n", + "from fairret.loss import NormLoss\n", + "\n", + "preds = torch.nn.functional.sigmoid(model_uncon(features_train))\n", + "pr = PositiveRate()\n", + "pr(preds, sens_train)" + ] + }, + { + "cell_type": "markdown", + "id": "e16c4fa0", + "metadata": {}, + "source": [ + "---\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "a3dbc50a", + "metadata": {}, + "source": [ + "Now let us train the same model with one of the **constrained** training algorithms:" + ] + }, + { + "cell_type": "markdown", + "id": "6ef60dce", + "metadata": {}, + "source": [ + "Here, to make sure each batch contains representatives of each protected group, we can use the BalancedBatchSampler from the `utils` subpackage - a custom PyTorch `Sampler` which yields an equal number of samples from each subgroup in each batch." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b0e2bd5d", + "metadata": {}, + "outputs": [], + "source": [ + "from fairret.statistic import PositiveRate\n", + "from fairret.loss import NormLoss\n", + "from humancompatible.train.fairness.utils import BalancedBatchSampler\n", + "\n", + "\n", + "\n", + "dataset = torch.utils.data.TensorDataset(features_train, sens_train, labels_train)\n", + "\n", + "sampler = BalancedBatchSampler(\n", + " subgroup_onehot=sens_train,\n", + " batch_size=128,\n", + " drop_last=True\n", + ")\n", + "dataloader = torch.utils.data.DataLoader(dataset, batch_sampler=sampler)\n", + "\n", + "criterion = torch.nn.BCEWithLogitsLoss()\n", + "\n", + "statistic = PositiveRate()\n", + "fair_criterion = NormLoss(statistic=statistic)\n", + "fair_crit_bound = 0.3" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1b5d4833", + "metadata": {}, + "outputs": [], + "source": [ + "from torch.nn import Sequential\n", + "hsize1 = 64\n", + "hsize2 = 32\n", + "model_con = Sequential(\n", + " torch.nn.Linear(features_train.shape[1], hsize1),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize1, hsize2),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize2, 1)\n", + ")\n", + "\n", + "optimizer = SSLALM(\n", + " params=model_con.parameters(),\n", + " m=1,\n", + " lr=0.05,\n", + " dual_lr=0.05,\n", + " dual_bound=5,\n", + " rho=1.,\n", + " mu=2.\n", + ")\n", + "\n", + "# add slack variables\n", + "slack_vars = torch.zeros(1, requires_grad=True)\n", + "optimizer.add_param_group(param_group={\"params\": slack_vars, \"name\": \"slack\"})\n", + "\n", + "epochs = 150" + ] + }, + { + "cell_type": "markdown", + "id": "894ed813", + "metadata": {}, + "source": [ + "As the constraint, we use `NormLoss` from `fairret`, which penalizes the model based on the ratio between the value of a statistic for each group and the overall value: $\\sum_{s\\in S}{|1-\\frac{f(\\theta, X_s, y_s)}{f(\\theta, X, y)}|}$." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8564545d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 0, loss: 0.5964877009391785, constraints: [0.04701327], dual: [0.00181583]\n", + "Epoch: 1, loss: 0.4189867675304413, constraints: [0.1951957], dual: [0.18362688]\n", + "Epoch: 2, loss: 0.39733222126960754, constraints: [0.195305], dual: [0.331285]\n", + "Epoch: 3, loss: 0.38910675048828125, constraints: [0.18657973], dual: [0.49074867]\n", + "Epoch: 4, loss: 0.3847562372684479, constraints: [0.17641279], dual: [0.64988726]\n", + "Epoch: 5, loss: 0.3822310268878937, constraints: [0.1629196], dual: [0.77936023]\n", + "Epoch: 6, loss: 0.3778993785381317, constraints: [0.16089187], dual: [0.8648878]\n", + "Epoch: 7, loss: 0.3771510422229767, constraints: [0.16208908], dual: [0.93879974]\n", + "Epoch: 8, loss: 0.3745404779911041, constraints: [0.1560387], dual: [1.007343]\n", + "Epoch: 9, loss: 0.37269678711891174, constraints: [0.15407917], dual: [1.0742816]\n", + "Epoch: 10, loss: 0.36955833435058594, constraints: [0.16355389], dual: [1.1565105]\n", + "Epoch: 11, loss: 0.3666114807128906, constraints: [0.15231781], dual: [1.2088367]\n", + "Epoch: 12, loss: 0.36505863070487976, constraints: [0.15350686], dual: [1.2767298]\n", + "Epoch: 13, loss: 0.3611990809440613, constraints: [0.15531769], dual: [1.3377378]\n", + "Epoch: 14, loss: 0.36214250326156616, constraints: [0.14783621], dual: [1.3907313]\n", + "Epoch: 15, loss: 0.3562532067298889, constraints: [0.15379377], dual: [1.4235057]\n", + "Epoch: 16, loss: 0.35390418767929077, constraints: [0.15776344], dual: [1.4756509]\n", + "Epoch: 17, loss: 0.3535971939563751, constraints: [0.15685916], dual: [1.5177106]\n", + "Epoch: 18, loss: 0.3471146821975708, constraints: [0.15370088], dual: [1.5513668]\n", + "Epoch: 19, loss: 0.3475930690765381, constraints: [0.1474714], dual: [1.586608]\n", + "Epoch: 20, loss: 0.3460840582847595, constraints: [0.14250916], dual: [1.6197054]\n", + "Epoch: 21, loss: 0.3429458439350128, constraints: [0.14190581], dual: [1.6456172]\n", + "Epoch: 22, loss: 0.34112831950187683, constraints: [0.14478178], dual: [1.6845007]\n", + "Epoch: 23, loss: 0.338951975107193, constraints: [0.14300168], dual: [1.7155722]\n", + "Epoch: 24, loss: 0.3365129828453064, constraints: [0.14208852], dual: [1.7364867]\n", + "Epoch: 25, loss: 0.3343072831630707, constraints: [0.14276032], dual: [1.7592628]\n", + "Epoch: 26, loss: 0.3313661217689514, constraints: [0.14373988], dual: [1.7783875]\n", + "Epoch: 27, loss: 0.32905271649360657, constraints: [0.14391356], dual: [1.7997092]\n", + "Epoch: 28, loss: 0.32559558749198914, constraints: [0.14232083], dual: [1.819667]\n", + "Epoch: 29, loss: 0.327927827835083, constraints: [0.14654839], dual: [1.8411492]\n", + "Epoch: 30, loss: 0.321808785200119, constraints: [0.14310653], dual: [1.8547634]\n", + "Epoch: 31, loss: 0.32212570309638977, constraints: [0.14388805], dual: [1.8718505]\n", + "Epoch: 32, loss: 0.3176101744174957, constraints: [0.1381243], dual: [1.8878857]\n", + "Epoch: 33, loss: 0.317004919052124, constraints: [0.145917], dual: [1.9084262]\n", + "Epoch: 34, loss: 0.309824675321579, constraints: [0.14643095], dual: [1.9242992]\n", + "Epoch: 35, loss: 0.3082379698753357, constraints: [0.14121831], dual: [1.9382846]\n", + "Epoch: 36, loss: 0.3035806715488434, constraints: [0.14091176], dual: [1.9536991]\n", + "Epoch: 37, loss: 0.3061775863170624, constraints: [0.1483007], dual: [1.966921]\n", + "Epoch: 38, loss: 0.30338165163993835, constraints: [0.1401922], dual: [1.9825641]\n", + "Epoch: 39, loss: 0.29926785826683044, constraints: [0.13897325], dual: [1.9931812]\n", + "Epoch: 40, loss: 0.2985864579677582, constraints: [0.13982335], dual: [2.0051253]\n", + "Epoch: 41, loss: 0.3025634288787842, constraints: [0.14690428], dual: [2.0209005]\n", + "Epoch: 42, loss: 0.2959322929382324, constraints: [0.14241821], dual: [2.0312753]\n", + "Epoch: 43, loss: 0.2915193438529968, constraints: [0.14137688], dual: [2.043062]\n", + "Epoch: 44, loss: 0.2895781099796295, constraints: [0.13996492], dual: [2.052078]\n", + "Epoch: 45, loss: 0.29019805788993835, constraints: [0.14758688], dual: [2.0599484]\n", + "Epoch: 46, loss: 0.28346332907676697, constraints: [0.14723331], dual: [2.0699785]\n", + "Epoch: 47, loss: 0.282205730676651, constraints: [0.14151676], dual: [2.0788229]\n", + "Epoch: 48, loss: 0.2858007848262787, constraints: [0.13964847], dual: [2.0868034]\n", + "Epoch: 49, loss: 0.2787598669528961, constraints: [0.14851792], dual: [2.0965524]\n", + "Epoch: 50, loss: 0.28025394678115845, constraints: [0.14295687], dual: [2.1033878]\n", + "Epoch: 51, loss: 0.28168436884880066, constraints: [0.14666698], dual: [2.1118765]\n", + "Epoch: 52, loss: 0.2783763110637665, constraints: [0.14728773], dual: [2.1210885]\n", + "Epoch: 53, loss: 0.2756488621234894, constraints: [0.14001457], dual: [2.1283817]\n", + "Epoch: 54, loss: 0.26900428533554077, constraints: [0.14261566], dual: [2.1323845]\n", + "Epoch: 55, loss: 0.26862695813179016, constraints: [0.14055779], dual: [2.1365182]\n", + "Epoch: 56, loss: 0.2692442834377289, constraints: [0.14318149], dual: [2.1423361]\n", + "Epoch: 57, loss: 0.26916006207466125, constraints: [0.15178545], dual: [2.1502285]\n", + "Epoch: 58, loss: 0.2659660577774048, constraints: [0.14420068], dual: [2.1559668]\n", + "Epoch: 59, loss: 0.2642906904220581, constraints: [0.14652895], dual: [2.1605902]\n", + "Epoch: 60, loss: 0.25864848494529724, constraints: [0.15069722], dual: [2.1651785]\n", + "Epoch: 61, loss: 0.26272860169410706, constraints: [0.14011948], dual: [2.1683803]\n", + "Epoch: 62, loss: 0.25607120990753174, constraints: [0.14674106], dual: [2.1716883]\n", + "Epoch: 63, loss: 0.2573090195655823, constraints: [0.14621599], dual: [2.1768246]\n", + "Epoch: 64, loss: 0.25697386264801025, constraints: [0.14576429], dual: [2.180749]\n", + "Epoch: 65, loss: 0.25918692350387573, constraints: [0.14535215], dual: [2.1840749]\n", + "Epoch: 66, loss: 0.25922897458076477, constraints: [0.13461945], dual: [2.187466]\n", + "Epoch: 67, loss: 0.25659751892089844, constraints: [0.13869996], dual: [2.1908526]\n", + "Epoch: 68, loss: 0.2454579919576645, constraints: [0.1536644], dual: [2.1942308]\n", + "Epoch: 69, loss: 0.24609331786632538, constraints: [0.14740591], dual: [2.196441]\n", + "Epoch: 70, loss: 0.24420279264450073, constraints: [0.14055099], dual: [2.1986299]\n", + "Epoch: 71, loss: 0.24194061756134033, constraints: [0.14601841], dual: [2.200429]\n", + "Epoch: 72, loss: 0.2456093728542328, constraints: [0.14273079], dual: [2.2033453]\n", + "Epoch: 73, loss: 0.2373281568288803, constraints: [0.14385772], dual: [2.2047284]\n", + "Epoch: 74, loss: 0.2415442168712616, constraints: [0.1400674], dual: [2.2067454]\n", + "Epoch: 75, loss: 0.23711906373500824, constraints: [0.1392258], dual: [2.208614]\n", + "Epoch: 76, loss: 0.2385871410369873, constraints: [0.15111162], dual: [2.2106266]\n", + "Epoch: 77, loss: 0.23665224015712738, constraints: [0.13679147], dual: [2.2122114]\n", + "Epoch: 78, loss: 0.23727214336395264, constraints: [0.14756472], dual: [2.2137735]\n", + "Epoch: 79, loss: 0.23571041226387024, constraints: [0.14845511], dual: [2.2153444]\n", + "Epoch: 80, loss: 0.23159131407737732, constraints: [0.14601612], dual: [2.2169511]\n", + "Epoch: 81, loss: 0.2346397191286087, constraints: [0.14555117], dual: [2.2188866]\n", + "Epoch: 82, loss: 0.2340419441461563, constraints: [0.14760321], dual: [2.2206213]\n", + "Epoch: 83, loss: 0.23143181204795837, constraints: [0.14760313], dual: [2.2225103]\n", + "Epoch: 84, loss: 0.22536739706993103, constraints: [0.150007], dual: [2.2236059]\n", + "Epoch: 85, loss: 0.22689326107501984, constraints: [0.15151397], dual: [2.2252765]\n", + "Epoch: 86, loss: 0.23241053521633148, constraints: [0.15168461], dual: [2.2270362]\n", + "Epoch: 87, loss: 0.2280157059431076, constraints: [0.14710415], dual: [2.22825]\n", + "Epoch: 88, loss: 0.21915465593338013, constraints: [0.14353297], dual: [2.2293699]\n", + "Epoch: 89, loss: 0.22162611782550812, constraints: [0.15810521], dual: [2.2308097]\n", + "Epoch: 90, loss: 0.2232014238834381, constraints: [0.15162558], dual: [2.231541]\n", + "Epoch: 91, loss: 0.2240859866142273, constraints: [0.14621147], dual: [2.232426]\n", + "Epoch: 92, loss: 0.2200152426958084, constraints: [0.14163853], dual: [2.2333605]\n", + "Epoch: 93, loss: 0.21871152520179749, constraints: [0.15136827], dual: [2.2341821]\n", + "Epoch: 94, loss: 0.22239236533641815, constraints: [0.14794702], dual: [2.2351263]\n", + "Epoch: 95, loss: 0.21425533294677734, constraints: [0.15009786], dual: [2.2358263]\n", + "Epoch: 96, loss: 0.21236008405685425, constraints: [0.14431676], dual: [2.2364988]\n", + "Epoch: 97, loss: 0.21712376177310944, constraints: [0.14312749], dual: [2.2372472]\n", + "Epoch: 98, loss: 0.2115909904241562, constraints: [0.14728952], dual: [2.2379458]\n", + "Epoch: 99, loss: 0.21050243079662323, constraints: [0.15252361], dual: [2.2387273]\n", + "Epoch: 100, loss: 0.21029923856258392, constraints: [0.15522177], dual: [2.2394524]\n", + "Epoch: 101, loss: 0.2144780158996582, constraints: [0.14657014], dual: [2.2400439]\n", + "Epoch: 102, loss: 0.21160098910331726, constraints: [0.15675975], dual: [2.240746]\n", + "Epoch: 103, loss: 0.209450826048851, constraints: [0.15010435], dual: [2.2413888]\n", + "Epoch: 104, loss: 0.20099897682666779, constraints: [0.15731794], dual: [2.2418349]\n", + "Epoch: 105, loss: 0.20690873265266418, constraints: [0.14877451], dual: [2.2424757]\n", + "Epoch: 106, loss: 0.21406854689121246, constraints: [0.1602774], dual: [2.2430935]\n", + "Epoch: 107, loss: 0.21242424845695496, constraints: [0.15046977], dual: [2.2434857]\n", + "Epoch: 108, loss: 0.20496298372745514, constraints: [0.14981384], dual: [2.2438796]\n", + "Epoch: 109, loss: 0.2084779292345047, constraints: [0.14728351], dual: [2.2443502]\n", + "Epoch: 110, loss: 0.20824851095676422, constraints: [0.16428857], dual: [2.2449615]\n", + "Epoch: 111, loss: 0.20649243891239166, constraints: [0.14855409], dual: [2.2453547]\n", + "Epoch: 112, loss: 0.20473264157772064, constraints: [0.15185581], dual: [2.245726]\n", + "Epoch: 113, loss: 0.2079596370458603, constraints: [0.15176682], dual: [2.2461061]\n", + "Epoch: 114, loss: 0.20911486446857452, constraints: [0.14733893], dual: [2.2463815]\n", + "Epoch: 115, loss: 0.2022322118282318, constraints: [0.14419109], dual: [2.2467177]\n", + "Epoch: 116, loss: 0.19850262999534607, constraints: [0.14425563], dual: [2.2469835]\n", + "Epoch: 117, loss: 0.201682910323143, constraints: [0.15393361], dual: [2.2472632]\n", + "Epoch: 118, loss: 0.19376477599143982, constraints: [0.14403272], dual: [2.2475638]\n", + "Epoch: 119, loss: 0.1972176879644394, constraints: [0.15170129], dual: [2.2478926]\n", + "Epoch: 120, loss: 0.20545555651187897, constraints: [0.15377723], dual: [2.2481735]\n", + "Epoch: 121, loss: 0.20293855667114258, constraints: [0.14233474], dual: [2.2484584]\n", + "Epoch: 122, loss: 0.1967054009437561, constraints: [0.14865485], dual: [2.2486722]\n", + "Epoch: 123, loss: 0.1904909908771515, constraints: [0.14646], dual: [2.248861]\n", + "Epoch: 124, loss: 0.1894625723361969, constraints: [0.15409784], dual: [2.2490542]\n", + "Epoch: 125, loss: 0.19265057146549225, constraints: [0.15408646], dual: [2.2492945]\n", + "Epoch: 126, loss: 0.1863272339105606, constraints: [0.16410109], dual: [2.2494981]\n", + "Epoch: 127, loss: 0.2021758109331131, constraints: [0.16046663], dual: [2.249748]\n", + "Epoch: 128, loss: 0.1971173882484436, constraints: [0.15370535], dual: [2.2499228]\n", + "Epoch: 129, loss: 0.18836602568626404, constraints: [0.14775909], dual: [2.2500918]\n", + "Epoch: 130, loss: 0.191558375954628, constraints: [0.15483183], dual: [2.250291]\n", + "Epoch: 131, loss: 0.1903645396232605, constraints: [0.16307046], dual: [2.2504704]\n", + "Epoch: 132, loss: 0.19536878168582916, constraints: [0.15230502], dual: [2.2506273]\n", + "Epoch: 133, loss: 0.1905580461025238, constraints: [0.16486068], dual: [2.2507963]\n", + "Epoch: 134, loss: 0.19633212685585022, constraints: [0.15917125], dual: [2.2509418]\n", + "Epoch: 135, loss: 0.19853660464286804, constraints: [0.14616182], dual: [2.2510946]\n", + "Epoch: 136, loss: 0.18865327537059784, constraints: [0.15255734], dual: [2.2512093]\n", + "Epoch: 137, loss: 0.1936325877904892, constraints: [0.14925405], dual: [2.251307]\n", + "Epoch: 138, loss: 0.19147324562072754, constraints: [0.15401727], dual: [2.2514274]\n", + "Epoch: 139, loss: 0.19009578227996826, constraints: [0.15572309], dual: [2.2515285]\n", + "Epoch: 140, loss: 0.18249237537384033, constraints: [0.14649434], dual: [2.2515988]\n", + "Epoch: 141, loss: 0.1841551661491394, constraints: [0.15948216], dual: [2.251726]\n", + "Epoch: 142, loss: 0.1866031140089035, constraints: [0.15603144], dual: [2.2517989]\n", + "Epoch: 143, loss: 0.18284974992275238, constraints: [0.15177317], dual: [2.251889]\n", + "Epoch: 144, loss: 0.17810754477977753, constraints: [0.15401429], dual: [2.2519746]\n", + "Epoch: 145, loss: 0.1783520132303238, constraints: [0.15827942], dual: [2.2520578]\n", + "Epoch: 146, loss: 0.18537741899490356, constraints: [0.14877283], dual: [2.2521193]\n", + "Epoch: 147, loss: 0.18220528960227966, constraints: [0.15156275], dual: [2.2521803]\n", + "Epoch: 148, loss: 0.18182533979415894, constraints: [0.16411862], dual: [2.2522485]\n", + "Epoch: 149, loss: 0.17791171371936798, constraints: [0.16872206], dual: [2.252326]\n" + ] + } + ], + "source": [ + "ep_c_log = []\n", + "for epoch in range(epochs):\n", + " loss_log = []\n", + " c_log = []\n", + " duals_log = []\n", + " for batch_input, batch_sens, batch_label in dataloader:\n", + " # calculate constraints and constraint grads\n", + " out = model_con(batch_input)\n", + " fair_loss = fair_criterion(out, batch_sens)\n", + " fair_constraint = torch.max(fair_loss + slack_vars[0] - fair_crit_bound, torch.zeros(1))\n", + " fair_constraint.backward(retain_graph=True)\n", + " \n", + " optimizer.dual_step(0, c_val=fair_constraint)\n", + " optimizer.zero_grad()\n", + "\n", + " c_log.append([fair_loss.detach().item()])\n", + " duals_log.append(optimizer._dual_vars.detach())\n", + " # calculate loss and grad\n", + " loss = criterion(out, batch_label) + 0 * slack_vars[0]\n", + " loss.backward()\n", + " loss_log.append(loss.detach().numpy())\n", + " optimizer.step()\n", + " optimizer.zero_grad()\n", + "\n", + " # slack variables must be non-negative. this is the \"projection\" step from the SSL-ALM paper\n", + " with torch.no_grad():\n", + " for s in slack_vars:\n", + " if s < 0:\n", + " s.zero_()\n", + " \n", + " optimizer.dual_lr *= 0.95\n", + " ep_c_log.extend(c_log)\n", + " \n", + " print(\n", + " f\"Epoch: {epoch}, \"\n", + " f\"loss: {np.mean(loss_log)}, \"\n", + " f\"constraints: {np.mean(c_log, axis=0)}, \"\n", + " f\"dual: {np.mean(duals_log, axis=0)}\"\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "993899e3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor([0.4127, 0.4717], dtype=torch.float64, grad_fn=)" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from fairret.statistic import PositiveRate\n", + "\n", + "preds = torch.nn.functional.sigmoid(model_con(features_train))\n", + "pr = PositiveRate()\n", + "pr(preds, sens_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4ac5a57f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor(0.1331, dtype=torch.float64, grad_fn=)" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fair_criterion(model_con(features_train), sens_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "170d5dbf", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from matplotlib import pyplot as plt\n", + "\n", + "window_len = 5\n", + "c_mavg = np.array([np.mean(ep_c_log[i:i+window_len]) for i in range(0, len(ep_c_log), window_len)])\n", + "plt.plot(np.array(c_mavg).flatten(), lw=0.05)\n", + "plt.hlines(y=fair_crit_bound, xmin=0, xmax=len(c_mavg), colors='black', ls='--')" + ] + }, + { + "cell_type": "markdown", + "id": "c31520f0", + "metadata": {}, + "source": [ + "---\n", + "\n", + "Now let's see how the **Switching Subgradient** algorithm deals with this task." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d1b0abd5", + "metadata": {}, + "outputs": [], + "source": [ + "from fairret.statistic import PositiveRate\n", + "from fairret.loss import NormLoss\n", + "from humancompatible.train.fairness.utils import BalancedBatchSampler\n", + "\n", + "dataset = torch.utils.data.TensorDataset(features_train, sens_train, labels_train)\n", + "\n", + "sampler = BalancedBatchSampler(\n", + " subgroup_onehot=sens_train,\n", + " batch_size=128,\n", + " drop_last=True\n", + ")\n", + "dataloader = torch.utils.data.DataLoader(dataset, batch_sampler=sampler)\n", + "\n", + "criterion = torch.nn.BCEWithLogitsLoss()\n", + "\n", + "statistic = PositiveRate()\n", + "fair_criterion = NormLoss(statistic=statistic)\n", + "fair_crit_bound = 0.3\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3af4f40c", + "metadata": {}, + "outputs": [], + "source": [ + "from humancompatible.train.algorithms import SSG\n", + "\n", + "from torch.nn import Sequential\n", + "hsize1 = 64\n", + "hsize2 = 32\n", + "model_con = Sequential(\n", + " torch.nn.Linear(features_train.shape[1], hsize1),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize1, hsize2),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize2, 1)\n", + ")\n", + "\n", + "optimizer = SSG(\n", + " params=model_con.parameters(),\n", + " m=1,\n", + " lr=0.05,\n", + " dual_lr=0.05\n", + ")\n", + "\n", + "epochs = 150" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c03fa9f9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 0, loss: 0.6001204252243042, constraints: [0.04241562], \n", + "Epoch: 1, loss: 0.4303379952907562, constraints: [0.13826096], \n", + "Epoch: 2, loss: 0.40842941403388977, constraints: [0.15191562], \n", + "Epoch: 3, loss: 0.39816904067993164, constraints: [0.14719616], \n", + "Epoch: 4, loss: 0.3904563784599304, constraints: [0.15606072], \n", + "Epoch: 5, loss: 0.38553640246391296, constraints: [0.15684228], \n", + "Epoch: 6, loss: 0.38166555762290955, constraints: [0.15871304], \n", + "Epoch: 7, loss: 0.37914013862609863, constraints: [0.15415388], \n", + "Epoch: 8, loss: 0.37259629368782043, constraints: [0.15696371], \n", + "Epoch: 9, loss: 0.37085652351379395, constraints: [0.15705763], \n", + "Epoch: 10, loss: 0.36701878905296326, constraints: [0.1616243], \n", + "Epoch: 11, loss: 0.36691004037857056, constraints: [0.15857347], \n", + "Epoch: 12, loss: 0.36154231429100037, constraints: [0.15565112], \n", + "Epoch: 13, loss: 0.358410507440567, constraints: [0.16360183], \n", + "Epoch: 14, loss: 0.3602617681026459, constraints: [0.14829725], \n", + "Epoch: 15, loss: 0.3550925850868225, constraints: [0.15702702], \n", + "Epoch: 16, loss: 0.3498671352863312, constraints: [0.16079595], \n", + "Epoch: 17, loss: 0.34986379742622375, constraints: [0.15130001], \n", + "Epoch: 18, loss: 0.3486783504486084, constraints: [0.15111124], \n", + "Epoch: 19, loss: 0.3418213427066803, constraints: [0.16165802], \n", + "Epoch: 20, loss: 0.34027335047721863, constraints: [0.15793627], \n", + "Epoch: 21, loss: 0.3385888636112213, constraints: [0.15608813], \n", + "Epoch: 22, loss: 0.3377761244773865, constraints: [0.15792396], \n", + "Epoch: 23, loss: 0.3353097438812256, constraints: [0.15518718], \n", + "Epoch: 24, loss: 0.3309491276741028, constraints: [0.15695738], \n", + "Epoch: 25, loss: 0.3253192901611328, constraints: [0.15083658], \n", + "Epoch: 26, loss: 0.32598230242729187, constraints: [0.15099859], \n", + "Epoch: 27, loss: 0.3208489716053009, constraints: [0.16029301], \n", + "Epoch: 28, loss: 0.3170267939567566, constraints: [0.15626481], \n", + "Epoch: 29, loss: 0.3147437274456024, constraints: [0.16268557], \n", + "Epoch: 30, loss: 0.3153856098651886, constraints: [0.15580469], \n", + "Epoch: 31, loss: 0.30903345346450806, constraints: [0.15850964], \n", + "Epoch: 32, loss: 0.30615678429603577, constraints: [0.15670682], \n", + "Epoch: 33, loss: 0.3001261055469513, constraints: [0.15726967], \n", + "Epoch: 34, loss: 0.2994067370891571, constraints: [0.16355504], \n", + "Epoch: 35, loss: 0.2924099266529083, constraints: [0.16540035], \n", + "Epoch: 36, loss: 0.2943499982357025, constraints: [0.15614382], \n", + "Epoch: 37, loss: 0.29126882553100586, constraints: [0.15444685], \n", + "Epoch: 38, loss: 0.2871687114238739, constraints: [0.16269149], \n", + "Epoch: 39, loss: 0.2830827534198761, constraints: [0.16923334], \n", + "Epoch: 40, loss: 0.28494855761528015, constraints: [0.15809905], \n", + "Epoch: 41, loss: 0.28078603744506836, constraints: [0.16276498], \n", + "Epoch: 42, loss: 0.274924635887146, constraints: [0.1645166], \n", + "Epoch: 43, loss: 0.2728683650493622, constraints: [0.16999877], \n", + "Epoch: 44, loss: 0.2695772349834442, constraints: [0.17991635], \n", + "Epoch: 45, loss: 0.2688858211040497, constraints: [0.1679903], \n", + "Epoch: 46, loss: 0.26256781816482544, constraints: [0.17445401], \n", + "Epoch: 47, loss: 0.26931947469711304, constraints: [0.16366511], \n", + "Epoch: 48, loss: 0.260123610496521, constraints: [0.1618341], \n", + "Epoch: 49, loss: 0.25645551085472107, constraints: [0.17065683], \n", + "Epoch: 50, loss: 0.2579772174358368, constraints: [0.17052301], \n", + "Epoch: 51, loss: 0.25344526767730713, constraints: [0.16339976], \n", + "Epoch: 52, loss: 0.2516031563282013, constraints: [0.16678933], \n", + "Epoch: 53, loss: 0.24834021925926208, constraints: [0.17403643], \n", + "Epoch: 54, loss: 0.2521849274635315, constraints: [0.16434238], \n", + "Epoch: 55, loss: 0.24604232609272003, constraints: [0.16597489], \n", + "Epoch: 56, loss: 0.24173328280448914, constraints: [0.16767609], \n", + "Epoch: 57, loss: 0.24055714905261993, constraints: [0.17164708], \n", + "Epoch: 58, loss: 0.24090471863746643, constraints: [0.17076605], \n", + "Epoch: 59, loss: 0.23778022825717926, constraints: [0.18025442], \n", + "Epoch: 60, loss: 0.24030300974845886, constraints: [0.16894374], \n", + "Epoch: 61, loss: 0.23452314734458923, constraints: [0.16566513], \n", + "Epoch: 62, loss: 0.23426228761672974, constraints: [0.16813052], \n", + "Epoch: 63, loss: 0.227885901927948, constraints: [0.1719063], \n", + "Epoch: 64, loss: 0.22985109686851501, constraints: [0.17722311], \n", + "Epoch: 65, loss: 0.23049235343933105, constraints: [0.17205983], \n", + "Epoch: 66, loss: 0.22204948961734772, constraints: [0.17392887], \n", + "Epoch: 67, loss: 0.22441013157367706, constraints: [0.17864915], \n", + "Epoch: 68, loss: 0.22410380840301514, constraints: [0.17491257], \n", + "Epoch: 69, loss: 0.22257471084594727, constraints: [0.16604825], \n", + "Epoch: 70, loss: 0.22120976448059082, constraints: [0.16821927], \n", + "Epoch: 71, loss: 0.21636255085468292, constraints: [0.17073152], \n", + "Epoch: 72, loss: 0.21456964313983917, constraints: [0.167203], \n", + "Epoch: 73, loss: 0.21102654933929443, constraints: [0.16702595], \n", + "Epoch: 74, loss: 0.2134944349527359, constraints: [0.17733093], \n", + "Epoch: 75, loss: 0.21377742290496826, constraints: [0.17411009], \n", + "Epoch: 76, loss: 0.21092282235622406, constraints: [0.17359538], \n", + "Epoch: 77, loss: 0.21036960184574127, constraints: [0.16934926], \n", + "Epoch: 78, loss: 0.2074458748102188, constraints: [0.17163914], \n", + "Epoch: 79, loss: 0.207858607172966, constraints: [0.17177738], \n", + "Epoch: 80, loss: 0.20861825346946716, constraints: [0.16990473], \n", + "Epoch: 81, loss: 0.2030610889196396, constraints: [0.17243704], \n", + "Epoch: 82, loss: 0.20613326132297516, constraints: [0.17382218], \n", + "Epoch: 83, loss: 0.2028989940881729, constraints: [0.15758233], \n", + "Epoch: 84, loss: 0.19834107160568237, constraints: [0.17925738], \n", + "Epoch: 85, loss: 0.20002301037311554, constraints: [0.17489548], \n", + "Epoch: 86, loss: 0.19448336958885193, constraints: [0.17440994], \n", + "Epoch: 87, loss: 0.194872185587883, constraints: [0.17601796], \n", + "Epoch: 88, loss: 0.19620059430599213, constraints: [0.18545204], \n", + "Epoch: 89, loss: 0.19517451524734497, constraints: [0.17471902], \n", + "Epoch: 90, loss: 0.19876201450824738, constraints: [0.16699634], \n", + "Epoch: 91, loss: 0.19627507030963898, constraints: [0.17622223], \n", + "Epoch: 92, loss: 0.18928897380828857, constraints: [0.17300513], \n", + "Epoch: 93, loss: 0.18830154836177826, constraints: [0.17588054], \n", + "Epoch: 94, loss: 0.1902553290128708, constraints: [0.17699304], \n", + "Epoch: 95, loss: 0.18733958899974823, constraints: [0.17398354], \n", + "Epoch: 96, loss: 0.19297413527965546, constraints: [0.17043888], \n", + "Epoch: 97, loss: 0.18849952518939972, constraints: [0.1697199], \n", + "Epoch: 98, loss: 0.18984360992908478, constraints: [0.18074665], \n", + "Epoch: 99, loss: 0.18471331894397736, constraints: [0.17432813], \n", + "Epoch: 100, loss: 0.1805119812488556, constraints: [0.1784166], \n", + "Epoch: 101, loss: 0.17839719355106354, constraints: [0.17319294], \n", + "Epoch: 102, loss: 0.18190599977970123, constraints: [0.17842196], \n", + "Epoch: 103, loss: 0.1793074905872345, constraints: [0.18058061], \n", + "Epoch: 104, loss: 0.1828930824995041, constraints: [0.17665594], \n", + "Epoch: 105, loss: 0.18111839890480042, constraints: [0.18076078], \n", + "Epoch: 106, loss: 0.17935657501220703, constraints: [0.17311536], \n", + "Epoch: 107, loss: 0.17501302063465118, constraints: [0.18673999], \n", + "Epoch: 108, loss: 0.17864742875099182, constraints: [0.1753304], \n", + "Epoch: 109, loss: 0.1793893277645111, constraints: [0.1809412], \n", + "Epoch: 110, loss: 0.17605699598789215, constraints: [0.18122667], \n", + "Epoch: 111, loss: 0.17391279339790344, constraints: [0.18559144], \n", + "Epoch: 112, loss: 0.17210640013217926, constraints: [0.17572801], \n", + "Epoch: 113, loss: 0.17481662333011627, constraints: [0.18654998], \n", + "Epoch: 114, loss: 0.17524538934230804, constraints: [0.18040747], \n", + "Epoch: 115, loss: 0.16929590702056885, constraints: [0.17937525], \n", + "Epoch: 116, loss: 0.17002621293067932, constraints: [0.17657284], \n", + "Epoch: 117, loss: 0.16743944585323334, constraints: [0.19249756], \n", + "Epoch: 118, loss: 0.17469194531440735, constraints: [0.18850104], \n", + "Epoch: 119, loss: 0.17302443087100983, constraints: [0.18805781], \n", + "Epoch: 120, loss: 0.16703085601329803, constraints: [0.18518359], \n", + "Epoch: 121, loss: 0.16685180366039276, constraints: [0.17915714], \n", + "Epoch: 122, loss: 0.1626531183719635, constraints: [0.19132323], \n", + "Epoch: 123, loss: 0.16841277480125427, constraints: [0.18636912], \n", + "Epoch: 124, loss: 0.16606149077415466, constraints: [0.17718854], \n", + "Epoch: 125, loss: 0.16884854435920715, constraints: [0.17879555], \n", + "Epoch: 126, loss: 0.164825439453125, constraints: [0.19273966], \n", + "Epoch: 127, loss: 0.16576161980628967, constraints: [0.18063454], \n", + "Epoch: 128, loss: 0.16752099990844727, constraints: [0.17885307], \n", + "Epoch: 129, loss: 0.16117583215236664, constraints: [0.18633077], \n", + "Epoch: 130, loss: 0.15898703038692474, constraints: [0.17882477], \n", + "Epoch: 131, loss: 0.15817241370677948, constraints: [0.17668184], \n", + "Epoch: 132, loss: 0.15675686299800873, constraints: [0.18428492], \n", + "Epoch: 133, loss: 0.15573503077030182, constraints: [0.18639444], \n", + "Epoch: 134, loss: 0.1597144603729248, constraints: [0.18333471], \n", + "Epoch: 135, loss: 0.16342280805110931, constraints: [0.18398987], \n", + "Epoch: 136, loss: 0.15673507750034332, constraints: [0.18879395], \n", + "Epoch: 137, loss: 0.15465138852596283, constraints: [0.1829467], \n", + "Epoch: 138, loss: 0.15301258862018585, constraints: [0.18021822], \n", + "Epoch: 139, loss: 0.15087264776229858, constraints: [0.19219053], \n", + "Epoch: 140, loss: 0.1533176749944687, constraints: [0.18319076], \n", + "Epoch: 141, loss: 0.15874679386615753, constraints: [0.18259482], \n", + "Epoch: 142, loss: 0.1605692207813263, constraints: [0.1885766], \n", + "Epoch: 143, loss: 0.15094277262687683, constraints: [0.18244334], \n", + "Epoch: 144, loss: 0.14904795587062836, constraints: [0.18745018], \n", + "Epoch: 145, loss: 0.15477216243743896, constraints: [0.18989369], \n", + "Epoch: 146, loss: 0.1521841585636139, constraints: [0.1802065], \n", + "Epoch: 147, loss: 0.15173102915287018, constraints: [0.17840846], \n", + "Epoch: 148, loss: 0.14991548657417297, constraints: [0.19002107], \n", + "Epoch: 149, loss: 0.15738952159881592, constraints: [0.18855303], \n" + ] + } + ], + "source": [ + "ep_c_log = []\n", + "for epoch in range(epochs):\n", + " loss_log = []\n", + " c_log = []\n", + " duals_log = []\n", + " for batch_input, batch_sens, batch_label in dataloader:\n", + " # calculate constraints and constraint grads\n", + " out = model_con(batch_input)\n", + " fair_loss = fair_criterion(out, batch_sens)\n", + " fair_constraint = torch.max(fair_loss - fair_crit_bound, torch.zeros(1))\n", + " fair_constraint.backward(retain_graph=True)\n", + " \n", + " optimizer.dual_step(0)\n", + " optimizer.zero_grad()\n", + "\n", + " c_log.append([fair_loss.detach().item()])\n", + " # calculate loss and grad\n", + " # batch_output = model_con(batch_input)\n", + " loss = criterion(out, batch_label)\n", + " loss.backward()\n", + " loss_log.append(loss.detach().numpy())\n", + " optimizer.step(fair_constraint)\n", + " optimizer.zero_grad()\n", + " \n", + " ep_c_log.append(c_log)\n", + " \n", + " print(\n", + " f\"Epoch: {epoch}, \"\n", + " f\"loss: {np.mean(loss_log)}, \"\n", + " f\"constraints: {np.mean(c_log, axis=0)}, \"\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3f4e4383", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor([0.4195, 0.4931], dtype=torch.float64, grad_fn=)" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from fairret.statistic import PositiveRate\n", + "\n", + "preds = torch.nn.functional.sigmoid(model_con(features_train))\n", + "pr = PositiveRate()\n", + "pr(preds, sens_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d25cb25b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor(0.1609, dtype=torch.float64, grad_fn=)" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fair_criterion(model_con(features_train), sens_train)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f25ef130", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from matplotlib import pyplot as plt\n", + "\n", + "ep_c_log = np.array(ep_c_log).flatten()\n", + "window_len = 10\n", + "c_mavg = np.array([np.mean(ep_c_log[i:i+window_len]) for i in range(0, len(ep_c_log), window_len)])\n", + "plt.plot(np.array(c_mavg).flatten(), lw=0.5)\n", + "plt.hlines(y=fair_crit_bound, xmin=0, xmax=len(c_mavg), colors='black', ls='--')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pypi-hc-test", + "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" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/fair_loss_constraint.ipynb b/examples/fair_loss_constraint.ipynb new file mode 100644 index 0000000..0b17570 --- /dev/null +++ b/examples/fair_loss_constraint.ipynb @@ -0,0 +1,691 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "2d334db6", + "metadata": {}, + "source": [ + "In this notebook, we will expand on the **SSL-ALM** experiments from the [preprint](https://arxiv.org/abs/2507.04033): *Benchmarking Stochastic Approximation Algorithms for Fairness-Constrained Training of Deep Neural Networks*.\n", + "\n", + "Specifically, we will train a classifier DNN on a dataset with a binary sensitive attribute, with a constraint on the absolute difference in loss on samples belonging to those groups." + ] + }, + { + "cell_type": "markdown", + "id": "0cf1c517", + "metadata": {}, + "source": [ + "$$\n", + "\n", + " \\min_{\\theta\\in R^n} \\quad\n", + " \\frac{1}{|\\mathcal{D}|} \\sum_{X_i, Y_i \\in \\mathcal{D}} \\ell( f_\\theta(X_i) , Y_i) + \\mathcal{R}(\\theta) \\\\\n", + " \\\\\n", + " \\textbf{s.t.} \\\\\n", + " \\\\\n", + "-\\delta \\le \\frac{1}{|\\mathcal{D}[s_1]|} \\sum_{X_{i}, Y_{i} \\in \\mathcal{D}[s_1] }\n", + " \\ell( f_\\theta(X_i) , Y_i) - \\frac{1}{|\\mathcal{D}[s_2]|} \\sum_{X_{i}, Y_{i} \\in \\mathcal{D}[s_2]}\\ell( f_\\theta(X_i) , Y_i) \\le \\delta\n", + "\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9eaa9623", + "metadata": {}, + "source": [ + "Start by loading and preprocessing the **data**:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "06b2a4ce", + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "from folktables import ACSDataSource, generate_categories, ACSIncome\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "data_source = ACSDataSource(survey_year='2018', horizon='1-Year', survey='person')\n", + "acs_data = data_source.get_data(states=[\"OK\"], download=True)\n", + "definition_df = data_source.get_definitions(download=True)\n", + "categories = generate_categories(features=ACSIncome.features, definition_df=definition_df)\n", + "df_feat, df_labels, _ = ACSIncome.df_to_pandas(acs_data,categories=categories, dummies=True)\n", + "\n", + "# binarize the RAC1P attribute into \"White\" and \"Non-White\"\n", + "df_feat['RAC1P_White'] = df_feat['RAC1P_White alone']\n", + "df_feat['RAC1P_NonWhite'] = df_feat['RAC1P_White alone'] == False\n", + "df_sens = df_feat[['RAC1P_White','RAC1P_NonWhite']].to_numpy(dtype=bool)\n", + "df_labels = df_labels.to_numpy()\n", + "\n", + "# remove protected attributes from data\n", + "df_feat = df_feat.drop(columns = [c for c in df_feat.columns if c.startswith('RAC1P')]).to_numpy()\n", + "\n", + "# split\n", + "X_train, X_test, y_train, y_test, sens_train, sens_test = train_test_split(\n", + " df_feat, df_labels, df_sens, test_size=0.2, random_state=42)\n", + "# scale\n", + "scaler = StandardScaler()\n", + "X_train = scaler.fit_transform(X_train)\n", + "X_test = scaler.transform(X_test)\n", + "\n", + "# make into a pytorch dataset\n", + "features_train = torch.tensor(X_train, dtype=torch.float32)\n", + "labels_train = torch.tensor(y_train,dtype=torch.float32)\n", + "sens_train = torch.tensor(sens_train, dtype=torch.bool)\n", + "dataset_train = torch.utils.data.TensorDataset(features_train, labels_train)\n", + "\n", + "features_test = torch.tensor(X_test, dtype=torch.float32)\n", + "labels_test = torch.tensor(y_test,dtype=torch.float32)\n", + "sens_test = torch.tensor(sens_test, dtype=torch.bool)" + ] + }, + { + "cell_type": "markdown", + "id": "b681af52", + "metadata": {}, + "source": [ + "To make sure that each batch contains representatives of both groups, use ```BalancedBatchSampler``` - a PyTorch-based ```BatchSampler``` that does exactly that." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5e64d8d1", + "metadata": {}, + "outputs": [], + "source": [ + "from humancompatible.train.fairness.utils import BalancedBatchSampler\n", + "\n", + "dataset = torch.utils.data.TensorDataset(features_train, sens_train, labels_train)\n", + "\n", + "sampler = BalancedBatchSampler(\n", + " subgroup_onehot=sens_train,\n", + " batch_size=64,\n", + " drop_last=True\n", + " )\n", + "\n", + "dataloader = torch.utils.data.DataLoader(dataset, batch_sampler=sampler)\n", + "\n", + "criterion = torch.nn.BCEWithLogitsLoss()\n", + "\n", + "fair_criterion = torch.nn.BCEWithLogitsLoss(reduction='none')\n", + "fair_crit_bound = [0.005, 0.005]" + ] + }, + { + "cell_type": "markdown", + "id": "8669da5d", + "metadata": {}, + "source": [ + "Define the **model**:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "38f040d1", + "metadata": {}, + "outputs": [], + "source": [ + "from torch.nn import Sequential\n", + "hsize1 = 64\n", + "hsize2 = 32\n", + "model = Sequential(\n", + " torch.nn.Linear(features_train.shape[1], hsize1),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize1, hsize2),\n", + " torch.nn.ReLU(),\n", + " torch.nn.Linear(hsize2, 1)\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "58ae3247", + "metadata": {}, + "source": [ + "Now, let's set up the **optimizer**.\n", + "\n", + "In theory, the SSL-ALM algorithm requires two independent samples of the constraints to calculate an unbiased estimate of the gradient of the Augmented Lagrangian function (speifically, of the penalty term).\n", + "\n", + "In our experiments, we failed to notice it impacting optimization or generalization performance; however, it does make the code unwieldier.\n", + "\n", + "Let's test it: the ```use_two_constraint_samples``` variable switches between using one or two samples in the training loop. Feel free to run a training loop with and without it!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "852924cd", + "metadata": {}, + "outputs": [], + "source": [ + "from humancompatible.train.algorithms import SSLALM\n", + "\n", + "m = 2\n", + "\n", + "optimizer = SSLALM(\n", + " params=model.parameters(),\n", + " m=m,\n", + " lr=0.005,\n", + " dual_lr=0.01,\n", + " dual_bound=5,\n", + " rho=1.\n", + ")\n", + "\n", + "# add slack variables\n", + "slack_vars = torch.zeros(m, requires_grad=True)\n", + "optimizer.add_param_group(param_group={\"params\": slack_vars, \"name\": \"slack\"})\n", + "\n", + "use_two_constraint_samples = False\n", + "\n", + "epochs = 300" + ] + }, + { + "cell_type": "markdown", + "id": "aa36b41f", + "metadata": {}, + "source": [ + "We also do not directly constrain the absolute value of the difference in loss. Instead, we split it into two constraints:\n", + "$$\n", + "L_1 - L_2 - \\delta \\leq 0\n", + "\\\\\n", + "L_2 - L_1 - \\delta \\leq 0\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b461c303", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch: 0, loss: 0.6666577134216041, constraints: [ 0.0149 -0.0149], dual: [0.0123 0. ]\n", + "Epoch: 1, loss: 0.6340173221471017, constraints: [ 0.0359 -0.0359], dual: [4.7523e-02 6.2589e-06]\n", + "Epoch: 2, loss: 0.6087080407560918, constraints: [ 0.046 -0.046], dual: [0.0943 0. ]\n", + "Epoch: 3, loss: 0.5955117674250352, constraints: [ 0.0603 -0.0603], dual: [0.1573 0.0006]\n", + "Epoch: 4, loss: 0.5834381943731978, constraints: [ 0.0647 -0.0647], dual: [0.2254 0.0015]\n", + "Epoch: 5, loss: 0.5787962766592962, constraints: [ 0.0781 -0.0781], dual: [0.3087 0.0003]\n", + "Epoch: 6, loss: 0.570171995121136, constraints: [ 0.0746 -0.0746], dual: [0.388 0.0035]\n", + "Epoch: 7, loss: 0.5649299069977644, constraints: [ 0.075 -0.075], dual: [0.4678 0.002 ]\n", + "Epoch: 8, loss: 0.5621515572593924, constraints: [ 0.0817 -0.0817], dual: [0.5552 0. ]\n", + "Epoch: 9, loss: 0.5548800849600842, constraints: [ 0.0738 -0.0738], dual: [0.6337 0.0033]\n", + "Epoch: 10, loss: 0.5500588529465491, constraints: [ 0.0738 -0.0738], dual: [0.7121 0.0063]\n", + "Epoch: 11, loss: 0.5412227108813169, constraints: [ 0.0689 -0.0689], dual: [0.785 0.0049]\n", + "Epoch: 12, loss: 0.5380150380364636, constraints: [ 0.0704 -0.0704], dual: [0.8596 0.0038]\n", + "Epoch: 13, loss: 0.5266943100774497, constraints: [ 0.0604 -0.0604], dual: [0.9227 0.0071]\n", + "Epoch: 14, loss: 0.5217762257446322, constraints: [ 0.0621 -0.0621], dual: [0.9878 0.0056]\n", + "Epoch: 15, loss: 0.5131124799188814, constraints: [ 0.0581 -0.0581], dual: [1.0484 0.0063]\n", + "Epoch: 16, loss: 0.49931377643033076, constraints: [ 0.0458 -0.0458], dual: [1.0949 0.011 ]\n", + "Epoch: 17, loss: 0.49188399785443354, constraints: [ 0.0434 -0.0434], dual: [1.1387 0.0112]\n", + "Epoch: 18, loss: 0.48182949188508484, constraints: [ 0.0294 -0.0294], dual: [1.1665 0.0195]\n", + "Epoch: 19, loss: 0.47439154015298474, constraints: [ 0.0242 -0.0242], dual: [1.1883 0.0203]\n", + "Epoch: 20, loss: 0.4686823591851352, constraints: [ 0.0121 -0.0121], dual: [1.1964 0.0202]\n", + "Epoch: 21, loss: 0.46680148965434026, constraints: [-0.0036 0.0036], dual: [1.1866 0.0254]\n", + "Epoch: 22, loss: 0.4629088499044117, constraints: [-0.0258 0.0258], dual: [1.1514 0.0494]\n", + "Epoch: 23, loss: 0.460015277590668, constraints: [-0.0455 0.0455], dual: [1.0939 0.0956]\n", + "Epoch: 24, loss: 0.4627277644579871, constraints: [-0.0568 0.0568], dual: [1.0235 0.1547]\n", + "Epoch: 25, loss: 0.451113771451147, constraints: [-0.08 0.08], dual: [0.9266 0.2402]\n", + "Epoch: 26, loss: 0.4417062838349426, constraints: [-0.0794 0.0794], dual: [0.8304 0.325 ]\n", + "Epoch: 27, loss: 0.4354692849150875, constraints: [-0.0568 0.0568], dual: [0.7599 0.3841]\n", + "Epoch: 28, loss: 0.4215463927963324, constraints: [-0.0458 0.0458], dual: [0.702 0.4306]\n", + "Epoch: 29, loss: 0.4036286536015962, constraints: [-0.0371 0.0371], dual: [0.654 0.4672]\n", + "Epoch: 30, loss: 0.39904324814938663, constraints: [-0.0073 0.0073], dual: [0.64 0.4698]\n", + "Epoch: 31, loss: 0.3923772513343577, constraints: [ 0.007 -0.007], dual: [0.6423 0.4561]\n", + "Epoch: 32, loss: 0.37287182347816333, constraints: [-0.0062 0.0062], dual: [0.6295 0.4575]\n", + "Epoch: 33, loss: 0.37809186742493983, constraints: [ 0.0212 -0.0212], dual: [0.648 0.4276]\n", + "Epoch: 34, loss: 0.37492166433418006, constraints: [ 0.0252 -0.0252], dual: [0.671 0.3932]\n", + "Epoch: 35, loss: 0.3639962979053196, constraints: [ 0.0137 -0.0137], dual: [0.681 0.3718]\n", + "Epoch: 36, loss: 0.3638203083945994, constraints: [ 0.0198 -0.0198], dual: [0.6978 0.3436]\n", + "Epoch: 37, loss: 0.3614213249662466, constraints: [ 0.0196 -0.0196], dual: [0.7145 0.3155]\n", + "Epoch: 38, loss: 0.363957455545141, constraints: [ 0.0238 -0.0238], dual: [0.7359 0.2826]\n", + "Epoch: 39, loss: 0.36355829905522496, constraints: [ 0.0228 -0.0228], dual: [0.7562 0.251 ]\n", + "Epoch: 40, loss: 0.3606017247626656, constraints: [ 0.0142 -0.0142], dual: [0.7667 0.2291]\n", + "Epoch: 41, loss: 0.36354573057931766, constraints: [ 0.0179 -0.0179], dual: [0.7815 0.203 ]\n", + "Epoch: 42, loss: 0.35959367532479136, constraints: [ 0.0013 -0.0013], dual: [0.7772 0.1959]\n", + "Epoch: 43, loss: 0.3621970229504401, constraints: [ 0.0028 -0.0028], dual: [0.7747 0.187 ]\n", + "Epoch: 44, loss: 0.35769858668770704, constraints: [-0.0114 0.0114], dual: [0.756 0.1943]\n", + "Epoch: 45, loss: 0.3610085123463681, constraints: [-0.007 0.007], dual: [0.7423 0.1966]\n", + "Epoch: 46, loss: 0.35518218746833635, constraints: [-0.0126 0.0126], dual: [0.7223 0.2052]\n", + "Epoch: 47, loss: 0.3598756233328267, constraints: [-0.0003 0.0003], dual: [0.7162 0.1999]\n", + "Epoch: 48, loss: 0.35468775256161106, constraints: [-0.013 0.013], dual: [0.6957 0.209 ]\n", + "Epoch: 49, loss: 0.3535344723546714, constraints: [-0.0093 0.0093], dual: [0.6794 0.214 ]\n", + "Epoch: 50, loss: 0.35023506560869383, constraints: [-0.0135 0.0135], dual: [0.6583 0.2237]\n", + "Epoch: 51, loss: 0.34921581350397646, constraints: [-0.0081 0.0081], dual: [0.6434 0.2272]\n", + "Epoch: 52, loss: 0.3464623947154012, constraints: [-0.0054 0.0054], dual: [0.6315 0.2277]\n", + "Epoch: 53, loss: 0.3472256660461426, constraints: [ 0.0031 -0.0031], dual: [0.6294 0.2185]\n", + "Epoch: 54, loss: 0.34514825032991275, constraints: [-0.0006 0.0006], dual: [0.623 0.2135]\n", + "Epoch: 55, loss: 0.3467897498293927, constraints: [ 0.0025 -0.0025], dual: [0.6201 0.205 ]\n", + "Epoch: 56, loss: 0.34341168861117277, constraints: [ 4.3987e-05 -4.3987e-05], dual: [0.6145 0.1992]\n", + "Epoch: 57, loss: 0.341829227250919, constraints: [-6.8447e-05 6.8447e-05], dual: [0.6087 0.1936]\n", + "Epoch: 58, loss: 0.3398057529539393, constraints: [-0.0007 0.0007], dual: [0.6022 0.1887]\n", + "Epoch: 59, loss: 0.3419647437700054, constraints: [ 0.0068 -0.0068], dual: [0.6043 0.1753]\n", + "Epoch: 60, loss: 0.34227307166969567, constraints: [ 0.0051 -0.0051], dual: [0.6043 0.1639]\n", + "Epoch: 61, loss: 0.33772281452751995, constraints: [-0.0013 0.0013], dual: [0.5971 0.1597]\n", + "Epoch: 62, loss: 0.339414491857353, constraints: [ 0.0057 -0.0057], dual: [0.5978 0.1477]\n", + "Epoch: 63, loss: 0.3366526556119584, constraints: [ 0.0019 -0.0019], dual: [0.5943 0.1399]\n", + "Epoch: 64, loss: 0.3326363094281732, constraints: [-0.0071 0.0071], dual: [0.5805 0.1423]\n", + "Epoch: 65, loss: 0.3349878023329534, constraints: [-0.0007 0.0007], dual: [0.574 0.1375]\n", + "Epoch: 66, loss: 0.33689139966379134, constraints: [ 0.0027 -0.0027], dual: [0.5713 0.1289]\n", + "Epoch: 67, loss: 0.3349499860615061, constraints: [-0.0022 0.0022], dual: [0.5632 0.1258]\n", + "Epoch: 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constraints: [-0.0042 0.0042], dual: [0.4092 0.0475]\n", + "Epoch: 89, loss: 0.31894694739266444, constraints: [ 0.0021 -0.0021], dual: [0.4059 0.0401]\n", + "Epoch: 90, loss: 0.321976481953211, constraints: [ 0.0092 -0.0092], dual: [0.4107 0.0254]\n", + "Epoch: 91, loss: 0.31670211451618296, constraints: [-0.0009 0.0009], dual: [0.404 0.0214]\n", + "Epoch: 92, loss: 0.3124247920094875, constraints: [-0.0072 0.0072], dual: [0.3901 0.0249]\n", + "Epoch: 93, loss: 0.31092367491178347, constraints: [-0.0048 0.0048], dual: [0.3789 0.0258]\n", + "Epoch: 94, loss: 0.31208012684395436, constraints: [ 0.0046 -0.0046], dual: [0.3785 0.0174]\n", + "Epoch: 95, loss: 0.3088887731234233, constraints: [ 0.0001 -0.0001], dual: [0.3729 0.0125]\n", + "Epoch: 96, loss: 0.30491270503976886, constraints: [-0.0058 0.0058], dual: [0.3606 0.0151]\n", + "Epoch: 97, loss: 0.31138403648347185, constraints: [ 0.0111 -0.0111], dual: [0.3676 0.002 ]\n", + "Epoch: 98, loss: 0.30208034604264977, constraints: [-0.0111 0.0111], dual: [0.3492 0.0157]\n", + "Epoch: 99, loss: 0.30879467438187513, constraints: [ 0.0062 -0.0062], dual: [0.3506 0.0055]\n", + "Epoch: 100, loss: 0.30859838661394623, constraints: [ 0.0077 -0.0077], dual: [0.3536 0.0053]\n", + "Epoch: 101, loss: 0.3056953073593608, constraints: [ 0.0028 -0.0028], dual: [0.351 0.0103]\n", + "Epoch: 102, loss: 0.3015175284000865, constraints: [-0.0041 0.0041], dual: [0.3406 0.0123]\n", + "Epoch: 103, loss: 0.3068383385737737, constraints: [ 0.0071 -0.0071], dual: [0.343 0.0131]\n", + "Epoch: 104, loss: 0.3075912688907824, constraints: [ 0.0126 -0.0126], dual: [3.5170e-01 1.0116e-04]\n", + "Epoch: 105, loss: 0.3112845603834119, constraints: [ 0.0166 -0.0166], dual: [0.3649 0.0067]\n", + "Epoch: 106, loss: 0.3029771448488821, constraints: [ 0.0006 -0.0006], dual: [0.3599 0.006 ]\n", + "Epoch: 107, loss: 0.2998065826924224, constraints: [ 0.0004 -0.0004], dual: [0.3547 0.0072]\n", + "Epoch: 108, loss: 0.3055445349268746, constraints: [ 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dual: [0.37 0.0071]\n", + "Epoch: 139, loss: 0.27492620077049523, constraints: [-0.0035 0.0035], dual: [0.3603 0.0115]\n", + "Epoch: 140, loss: 0.2749708477865186, constraints: [ 0.0019 -0.0019], dual: [0.3568 0.0052]\n", + "Epoch: 141, loss: 0.2731585808490452, constraints: [ 0.0013 -0.0013], dual: [0.3526 0.0042]\n", + "Epoch: 142, loss: 0.27314889234931844, constraints: [ 0.0034 -0.0034], dual: [0.3508 0.0008]\n", + "Epoch: 143, loss: 0.2707426738843583, constraints: [-0.0064 0.0064], dual: [0.3378 0.0075]\n", + "Epoch: 144, loss: 0.2672206844415581, constraints: [-0.007 0.007], dual: [0.3242 0.0113]\n", + "Epoch: 145, loss: 0.2703603911295272, constraints: [ 0.0038 -0.0038], dual: [0.3228 0.0043]\n", + "Epoch: 146, loss: 0.27642640379960076, constraints: [ 0.0167 -0.0167], dual: [0.3362 0.0021]\n", + "Epoch: 147, loss: 0.27226450372683375, constraints: [ 0.0075 -0.0075], dual: [0.3391 0.0044]\n", + "Epoch: 148, loss: 0.26695823362260535, constraints: [ 0.0043 -0.0043], dual: 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0.22531977701082564, constraints: [ 0.0006 -0.0006], dual: [0.3726 0.0098]\n", + "Epoch: 210, loss: 0.22370301736028572, constraints: [ 0.0072 -0.0072], dual: [0.3751 0.0011]\n", + "Epoch: 211, loss: 0.2233023525852906, constraints: [ 0.0031 -0.0031], dual: [0.3729 0.0096]\n", + "Epoch: 212, loss: 0.22535847950922816, constraints: [ 0.0043 -0.0043], dual: [0.3721 0.0041]\n", + "Epoch: 213, loss: 0.2253161285137921, constraints: [ 0.0012 -0.0012], dual: [0.3678 0.013 ]\n", + "Epoch: 214, loss: 0.22243571242219523, constraints: [ 0.0056 -0.0056], dual: [0.3686 0.0035]\n", + "Epoch: 215, loss: 0.21969630124798992, constraints: [ 0.0057 -0.0057], dual: [0.3694 0.0092]\n", + "Epoch: 216, loss: 0.2134861308885248, constraints: [-0.0105 0.0105], dual: [0.3517 0.0225]\n", + "Epoch: 217, loss: 0.21454969349137523, constraints: [-0.0046 0.0046], dual: [0.3407 0.0228]\n", + "Epoch: 218, loss: 0.21505965972155855, constraints: [ 7.6633e-05 -7.6633e-05], dual: [0.3351 0.018 ]\n", + "Epoch: 219, 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0.2073735931332697, constraints: [-0.0003 0.0003], dual: [0.3239 0.006 ]\n", + "Epoch: 230, loss: 0.20747139396374686, constraints: [-0.0044 0.0044], dual: [0.3131 0.0074]\n", + "Epoch: 231, loss: 0.2057261406852488, constraints: [ 0.01 -0.01], dual: [0.3188 0.0048]\n", + "Epoch: 232, loss: 0.2078207094679799, constraints: [ 0.0123 -0.0123], dual: [0.3271 0.0044]\n", + "Epoch: 233, loss: 0.2046592582605387, constraints: [ 0.0044 -0.0044], dual: [0.3264 0.0091]\n", + "Epoch: 234, loss: 0.20093572969760812, constraints: [ 0.0083 -0.0083], dual: [0.3302 0.0062]\n", + "Epoch: 235, loss: 0.20259714191942885, constraints: [ 0.0045 -0.0045], dual: [0.3296 0.0016]\n", + "Epoch: 236, loss: 0.2054771974421384, constraints: [ 0.0129 -0.0129], dual: [0.3386 0.0072]\n", + "Epoch: 237, loss: 0.2018039358551042, constraints: [ 0.0036 -0.0036], dual: [0.3371 0.0125]\n", + "Epoch: 238, loss: 0.19745886012127525, constraints: [ 0.0029 -0.0029], dual: [0.3346 0.0087]\n", + "Epoch: 239, loss: 0.20315554345908918, constraints: [ 0.0164 -0.0164], dual: [0.3476 0.0083]\n", + "Epoch: 240, loss: 0.1933904096745608, constraints: [-0.0072 0.0072], dual: [0.3337 0.0162]\n", + "Epoch: 241, loss: 0.19948938756919743, constraints: [ 0.018 -0.018], dual: [0.3486 0. ]\n", + "Epoch: 242, loss: 0.1980541079844299, constraints: [ 0.008 -0.008], dual: [0.3521 0.001 ]\n", + "Epoch: 243, loss: 0.19506375040662915, constraints: [-0.0014 0.0014], dual: [0.3448 0.0054]\n", + "Epoch: 244, loss: 0.20454701813950874, constraints: [ 0.0159 -0.0159], dual: [0.3573 0.0193]\n", + "Epoch: 245, loss: 0.19644319984996528, constraints: [ 0.0072 -0.0072], dual: [0.3598 0.01 ]\n", + "Epoch: 246, loss: 0.19297016032955103, constraints: [ 0.0017 -0.0017], dual: [0.356 0.004]\n", + "Epoch: 247, loss: 0.19187981295481063, constraints: [ 0.0018 -0.0018], dual: [0.3524 0.0043]\n", + "Epoch: 248, loss: 0.19423297675032364, constraints: [ 0.0014 -0.0014], dual: [0.3483 0.0104]\n", + "Epoch: 249, loss: 0.19275162460511192, constraints: [ 0.0085 -0.0085], dual: [0.3522 0. ]\n", + "Epoch: 250, loss: 0.1944455024051039, constraints: [ 0.0097 -0.0097], dual: [0.3576 0.0022]\n", + "Epoch: 251, loss: 0.19691978100883334, constraints: [ 0.0063 -0.0063], dual: [0.3591 0.0127]\n", + "Epoch: 252, loss: 0.1969348237964145, constraints: [ 0.0117 -0.0117], dual: [0.3667 0.0042]\n", + "Epoch: 253, loss: 0.19600529622351914, constraints: [ 0.0078 -0.0078], dual: [0.3699 0. ]\n", + "Epoch: 254, loss: 0.19358875628626138, constraints: [-0.0053 0.0053], dual: [0.3582 0.0078]\n", + "Epoch: 255, loss: 0.19389238437278228, constraints: [-0.0017 0.0017], dual: [0.3505 0.0081]\n", + "Epoch: 256, loss: 0.1890965906020842, constraints: [ 0.0012 -0.0012], dual: [0.3462 0.0054]\n", + "Epoch: 257, loss: 0.19321208179258464, constraints: [ 0.0061 -0.0061], dual: [0.3474 0.0051]\n", + "Epoch: 258, loss: 0.19156005070136303, constraints: [ 0.0052 -0.0052], dual: [0.3477 0.002 ]\n", + "Epoch: 259, loss: 0.18688981097779775, constraints: [-0.0022 0.0022], dual: [0.3395 0.0089]\n", + "Epoch: 260, loss: 0.18719216468825675, constraints: [ 0.0094 -0.0094], dual: [0.3445 0.001 ]\n", + "Epoch: 261, loss: 0.1865738462983516, constraints: [ 0.0073 -0.0073], dual: [0.3472 0.0035]\n", + "Epoch: 262, loss: 0.18351293949965844, constraints: [ 0.0042 -0.0042], dual: [0.3463 0.0082]\n", + "Epoch: 263, loss: 0.17924926580305686, constraints: [-0.007 0.007], dual: [0.3326 0.0131]\n", + "Epoch: 264, loss: 0.1829595665136973, constraints: [ 0.0081 -0.0081], dual: [0.3361 0.0046]\n", + "Epoch: 265, loss: 0.17863105989077635, constraints: [ 0.0037 -0.0037], dual: [0.3346 0.0034]\n", + "Epoch: 266, loss: 0.180980353697873, constraints: [ 0.0065 -0.0065], dual: [0.3363 0.0027]\n", + "Epoch: 267, loss: 0.1832564435245698, constraints: [ 0.0123 -0.0123], dual: [0.3446 0.0066]\n", + "Epoch: 268, loss: 0.1827907262925516, constraints: [ 0.0131 -0.0131], dual: [0.3538 0.0056]\n", + "Epoch: 269, loss: 0.17370059975145155, constraints: [-0.0018 0.0018], dual: [0.3461 0.0113]\n", + "Epoch: 270, loss: 0.17583516220513143, constraints: [-0.0075 0.0075], dual: [0.3319 0.0161]\n", + "Epoch: 271, loss: 0.17501422612552056, constraints: [ 0.0042 -0.0042], dual: [0.3311 0.0067]\n", + "Epoch: 272, loss: 0.18721152855116024, constraints: [ 0.0043 -0.0043], dual: [0.3302 0.0094]\n", + "Epoch: 273, loss: 0.18629865975756393, constraints: [ 0.0168 -0.0168], dual: [0.3437 0.0034]\n", + "Epoch: 274, loss: 0.18125144686353833, constraints: [ 0.0121 -0.0121], dual: [0.3517 0.0006]\n", + "Epoch: 275, loss: 0.17437999362224027, constraints: [ 0.0028 -0.0028], dual: [0.3493 0.009 ]\n", + "Epoch: 276, loss: 0.17577237400569415, constraints: [-0.0118 0.0118], dual: [0.3302 0.0207]\n", + "Epoch: 277, loss: 0.18086074828578716, constraints: [ 0.0115 -0.0115], dual: [0.3376 0.0043]\n", + "Epoch: 278, loss: 0.17971792764831007, constraints: [ 0.0109 -0.0109], dual: [0.3443 0.0051]\n", + "Epoch: 279, loss: 0.17249665990994686, constraints: [-0.004 0.004], dual: [0.334 0.0167]\n", + "Epoch: 280, loss: 0.17116934629647354, constraints: [ 0.0044 -0.0044], dual: [0.3333 0.0071]\n", + "Epoch: 281, loss: 0.1730455894415316, constraints: [ 0.0087 -0.0087], dual: [0.3375 0.0096]\n", + "Epoch: 282, loss: 0.16227583430315318, constraints: [-0.0066 0.0066], dual: [0.3243 0.0179]\n", + "Epoch: 283, loss: 0.1658750383281394, constraints: [-0.002 0.002], dual: [0.3163 0.0155]\n", + "Epoch: 284, loss: 0.16941813895838304, constraints: [ 0.0169 -0.0169], dual: [3.2984e-01 2.8997e-04]\n", + "Epoch: 285, loss: 0.16954091707603974, constraints: [-0.0002 0.0002], dual: [0.3239 0.0027]\n", + "Epoch: 286, loss: 0.16594577051307025, constraints: [ 0.0057 -0.0057], dual: [0.3247 0.0041]\n", + "Epoch: 287, loss: 0.16670144519262148, constraints: [ 0.0101 -0.0101], dual: [0.3304 0.0024]\n", + "Epoch: 288, loss: 0.16459978763994418, constraints: [-0.001 0.001], dual: [0.3236 0.0064]\n", + "Epoch: 289, loss: 0.16546874362648578, constraints: [ 0.0027 -0.0027], dual: [0.3209 0.0011]\n", + "Epoch: 290, loss: 0.16458163573815113, constraints: [ 0.0034 -0.0034], dual: [0.3191 0. ]\n", + "Epoch: 291, loss: 0.16169988723439083, constraints: [ 0.0008 -0.0008], dual: [3.1434e-01 2.2433e-04]\n", + "Epoch: 292, loss: 0.16944028901164992, constraints: [ 0.0123 -0.0123], dual: [0.3227 0.0016]\n", + "Epoch: 293, loss: 0.1649960491218065, constraints: [-0.0004 0.0004], dual: [0.3165 0.0043]\n", + "Epoch: 294, loss: 0.16720790350646303, constraints: [ 0.0104 -0.0104], dual: [0.3227 0.001 ]\n", + "Epoch: 295, loss: 0.16445957496762276, constraints: [ 0.0117 -0.0117], dual: [0.3303 0.0087]\n", + "Epoch: 296, loss: 0.16385822442539952, constraints: [ 0.0037 -0.0037], dual: [0.3288 0.0061]\n", + "Epoch: 297, loss: 0.16593966587332257, constraints: [-0.0033 0.0033], dual: [0.3193 0.008 ]\n", + "Epoch: 298, loss: 0.1635957213870266, constraints: [ 0.0058 -0.0058], dual: [0.3203 0.0051]\n", + "Epoch: 299, loss: 0.17047755662025066, constraints: [ 0.0046 -0.0046], dual: [0.3199 0.0034]\n" + ] + } + ], + "source": [ + "from itertools import combinations\n", + "import numpy as np\n", + "\n", + "\n", + "avg_epoch_loss_log = []\n", + "avg_epoch_c_log = []\n", + "for epoch in range(epochs):\n", + " loss_log = []\n", + " c_log = []\n", + " for batch_input, batch_sens, batch_label in dataloader:\n", + "\n", + " # evaluate constraints and constraint grads\n", + " c_vals = []\n", + " c_vals_raw = []\n", + " \n", + " if use_two_constraint_samples:\n", + " c_inputs, c_labels, c_sens = batch_input[::2], batch_label[::2], batch_sens[::2]\n", + " else:\n", + " c_inputs, c_labels, c_sens = batch_input, batch_label, batch_sens\n", + " c_sens_norm = c_sens.div(torch.sum(c_sens, axis=0))\n", + "\n", + " # calculate loss for each group\n", + " c_loss = fair_criterion(model(c_inputs).squeeze(), c_labels.squeeze()) @ c_sens_norm\n", + " c_val_raw_vec = []\n", + " # in our setup (2 groups) we only have 1 combination\n", + " for (l1, l2) in combinations(c_loss, 2):\n", + " c_val_raw_vec.append(l1-l2)\n", + " c_val_raw_vec.append(l2-l1)\n", + "\n", + " for i in range(m):\n", + " optimizer.zero_grad()\n", + " c_val = c_val_raw_vec[i] + slack_vars[i] - fair_crit_bound[i]\n", + " # retain_graph in all but last iteration to calculate grads\n", + " c_val.backward(retain_graph = i < m-1)\n", + " # update dual multipliers and save constraint grads\n", + " optimizer.dual_step(i, c_val)\n", + " \n", + " c_vals.append(c_val.detach())\n", + " c_vals_raw.append(c_val_raw_vec[i].detach())\n", + "\n", + " # use two constraint samples to calculate gradient instead of one\n", + " if use_two_constraint_samples:\n", + " with torch.no_grad():\n", + " c_vals = []\n", + " c_inputs, c_labels, c_sens = batch_input[1::2], batch_label[1::2], batch_sens[1::2]\n", + " c_sens_norm = c_sens.div(torch.sum(c_sens, axis=0))\n", + "\n", + " # calculate loss for each group\n", + " c_loss = fair_criterion(model(c_inputs).squeeze(), c_labels.squeeze()) @ c_sens_norm\n", + " c_val_raw_vec = []\n", + " # in our setup (2 groups) we only have 1 combination\n", + " for (l1, l2) in combinations(c_loss, 2):\n", + " c_val_raw_vec.append(l1-l2)\n", + " c_val_raw_vec.append(l2-l1)\n", + "\n", + " for i in range(m):\n", + " c_val = c_val_raw_vec[i] + slack_vars[i] - fair_crit_bound[i]\n", + " c_vals.append(c_val)\n", + "\n", + " optimizer.zero_grad()\n", + " # evaluate loss and loss grad\n", + " logits = model(batch_input)\n", + " loss = criterion(logits.squeeze(), batch_label.squeeze()) + torch.zeros_like(slack_vars) @ slack_vars # SLACK\n", + " loss.backward()\n", + " \n", + " optimizer.step(c_vals)\n", + " optimizer.zero_grad()\n", + "\n", + " # slack variables must be non-negative. this is the \"projection\" step from the SSL-ALM paper\n", + " with torch.no_grad():\n", + " for s in slack_vars:\n", + " if s < 0:\n", + " s.zero_()\n", + "\n", + " loss_log.append(loss.item())\n", + " c_log.append([c.item() for c in c_vals_raw])\n", + "\n", + " avg_epoch_c_log.append(np.mean(c_log, axis=0))\n", + " avg_epoch_loss_log.append(np.mean(loss_log))\n", + " with np.printoptions(precision=4):\n", + " print(\n", + " f\"Epoch: {epoch}, loss: {np.mean(loss_log)}, constraints: {np.mean(c_log, axis=0)}, dual: {optimizer._dual_vars.detach().numpy()}\"\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4a1f1774", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from matplotlib import pyplot as plt\n", + "\n", + "avg_epoch_c_log = np.array(avg_epoch_c_log)\n", + "\n", + "f, ax = plt.subplots(1,2, sharex='all')\n", + "ax[0].plot(avg_epoch_loss_log)\n", + "ax[1].plot(avg_epoch_c_log[:,0])\n", + "ax[1].hlines((fair_crit_bound, [-1*b for b in fair_crit_bound]), xmin=0, xmax=epochs, color='black', ls='--')\n", + "\n", + "f.set_figwidth(20)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4dddd8b3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train loss difference:\n", + "tensor(0.0074, grad_fn=)\n", + "Test loss difference:\n", + "tensor(-0.0125, grad_fn=)\n" + ] + } + ], + "source": [ + "loss = torch.nn.BCEWithLogitsLoss()\n", + "\n", + "train_samples_w, train_labels_w = features_train[sens_train[:,0]], labels_train[sens_train[:,0]]\n", + "train_samples_nw, train_labels_nw = features_train[sens_train[:,1]], labels_train[sens_train[:,1]]\n", + "\n", + "train_logits_w = model(train_samples_w)\n", + "train_logits_nw = model(train_samples_nw)\n", + "\n", + "print(\"Train loss difference:\")\n", + "print(loss(train_logits_w, train_labels_w) - loss(train_logits_nw, train_labels_nw))\n", + "\n", + "\n", + "test_samples_w, test_labels_w = features_test[sens_test[:,0]], labels_test[sens_test[:,0]]\n", + "test_samples_nw, test_labels_nw = features_test[sens_test[:,1]], labels_test[sens_test[:,1]]\n", + "\n", + "test_logits_w = model(test_samples_w)\n", + "test_logits_nw = model(test_samples_nw)\n", + "\n", + "print(\"Test loss difference:\")\n", + "print(loss(test_logits_w, test_labels_w) - loss(test_logits_nw, test_labels_nw))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "hc-dev", + "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" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/experiments/algo_plots.ipynb b/experiments/algo_plots.ipynb index 3a0bb74..9ccb5cc 100644 --- a/experiments/algo_plots.ipynb +++ b/experiments/algo_plots.ipynb @@ -7,14 +7,14 @@ "outputs": [], "source": [ "import pandas as pd\n", - "from utils.plotting import plot_time, plot_iter, plot_trajectories" + "from utils.plotting import plot_time, plot_sep, plot_trajectories" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**Read results:**" + "**Read results**" ] }, { @@ -23,25 +23,37 @@ "metadata": {}, "outputs": [], "source": [ - "import os\n", - "\n", - "\n", "TASK = \"income\"\n", "STATE = \"OK\"\n", "DATASET = TASK + \"_\" + STATE\n", - "lb = 0.005\n", - "constraint = \"eq_loss\"\n", - "\n", - "algs = ['SSLALM', 'ALM', 'StochasticGhost', 'SGD', 'fairret']\n", - "stats = dict.fromkeys(algs)\n", - "results_dir = './utils/exp_results/'\n", + "DATASET = TASK + \"_\" + STATE\n", + "loaded_models = []\n", "\n", - "for alg in algs:\n", - " filename = os.path.join(results_dir, f\"{alg}_\" + f\"{DATASET}_{lb}.csv\")\n", - " try:\n", - " stats[alg] = pd.read_csv(filename)\n", - " except:\n", - " print(f'{alg} not found in {results_dir}')" + "experiments_to_read = {\n", + " # 'SGD': {\n", + " # 'unconstrained': 0.05\n", + " # },\n", + " # 'SSG': {\n", + " # \"loss_equality\": 0.005\n", + " # },\n", + " 'SSLALM': {\n", + " \"loss_equality\": 0.005,\n", + " \"abs_diff_pr\": 0.05\n", + " },\n", + " 'StochasticGhost': {\n", + " 'loss_equality': 0.005,\n", + " \"abs_diff_pr\": 0.05\n", + " },\n", + " # 'TorchSSG': {\n", + " # # \"abs_max_dev_from_overall_tpr\": 0.03,\n", + " # # \"abs_diff_pr\": 0.05\n", + " # },\n", + " # 'TorchSSLALM': {\n", + " # 'loss_equality': 0.005\n", + " # # \"abs_max_dev_from_overall_tpr\": 0.03,\n", + " # # \"abs_diff_pr\": 0.05\n", + " # },\n", + "}" ] }, { @@ -50,562 +62,34 @@ "metadata": {}, "outputs": [], "source": [ - "stats_train = {alg: s[s[\"is_train\"] == \"train\"].drop([\"is_train\"], axis=1).dropna() for alg, s in stats.items() if s is not None}\n", - "stats_test = {alg: s[s[\"is_train\"] == \"test\"].drop([\"is_train\"], axis=1).dropna() for alg, s in stats.items() if s is not None}" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plots w.r.t. time" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### SSL-ALM" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Train**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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LEEIIIYQUEQoaFbPz589behMIIYSUUaNHj+ZBnYkTJxpd9/bbb/Pr2DKFZdiwYbh3716hrY8QQgghhJQsFDQqZllKJT6YMdPSm0EIIaSMqlSpEjZt2oT09HRxXkZGBn7//XcEBAQU6n3Z2dmhQoUKhbpOQgghhBBSclDQqJgtXfsXVv36KzIzMy29KYQQQsqgJk2a8MDRtm3bxHnsMgsYNW7cWJynVquxcOFCBAUF8eBPw4YNsXXrVoN17dq1CzVq1ODXv/zyy3j06JHB9TmHpz18+BD9+vWDt7c3HB0d0bx5cxw4cMDgNoGBgfjyyy/x5ptvwsnJiW/XihUriuCZIIQQQgghL4qCRsXMx78iqtasI9aDIIQQUgpoNEBWqmVO7L7ziQVk1qxZI06vXr0aY8aMMViGBYzWr1+P5cuX4+bNm3j//ffx+uuv4+jRo/z68PBwDBw4EH369MGVK1cwbtw4fPjhh7neb0pKCnr27ImDBw/i8uXL6N69O799WFiYwXJLlixBs2bN+DKTJ0/GpEmTcPfu3Xw/TkIIIYQQUrSsinj9xAS1RoMnT57wI7GEEEJKAWUa8L2jZe773RRA7pCvm7Dgz+zZsxEaGsqnT548yYessULWDMt2Zdk+LAuodevWfF6VKlVw4sQJ/PLLL+jQoQN+/vlnVK1alQd4mJo1a+L69ev4+uuvzd4vy1ZiJ63PP/8cf//9N3bs2IEpU6aI81lgiQWLmFmzZuHbb7/F4cOH+X0QQgghhJCSg4JGFuBTKdCg1gQhhBBSmLy8vNCrVy8+fEyj0fDLnp6e4vUPHjxAWloaunbtanA7hUIhDmG7ffs2WrZsaXC9NsCUW6bR/Pnz8d9//yEyMhJKpZL/3uXMNGrQoIF4mRXn9vHxQXR09As9ZkIIIYQQUvgoaGQB1ja2fGedEEJIKWFlL2T8WOq+C4ANUdNm9yxbtswouMOw4I6/v7/BdTY2NgXe1OnTp2P//v1YvHgxqlWrxmshDR48mAej9MnlcoNpFjhiNZYIIYQQQkjJQkEjC5DKrcUhA4QQQkoBiSTfQ8QsjdUTYsEaFpDp1q2bwXV16tThwSGWAcSGoplSu3ZtPqxM35kzZ3K9TzYMbvTo0RgwYIAYnMpZPJsQQgghhJQeFDSyAFdPX4TmSNUnhBBCCpNMJuNDzLSX9bGuZSwriBW/Zhk+7dq1Q2JiIg/6ODs7Y9SoUZg4cSKvZzRjxgxeBPvixYt8uFtuqlevzju1seLXLFj1ySefUAYRIYQQQkgpRt3TLMDN2w+ZOVL1CSGEkMLGAkDsZAorUs2COqyLGssqYplJbLhaUFAQvz4gIAB//fUXtm/fzotbsy5rrHh2br755hu4ubmhTZs2PHDEMpyaNGlSJI+NEEIIIYQUPYmGVci0MFZrYdGiRXj69CnfMf3hhx/QokULk8t27NhRbAesj3ViYTu7DHtI8+bNw8qVK3lr+7Zt2/IuMOwIaF4kJSXBxcWFH3U1t7NdUBdD4/HXjt14cnE/1q3VtUMmhBBScmRkZCAkJIQHUGxtbS29OeVebq9HUf5mk/yh14IQQggpe7/ZFs802rx5M6ZNm8aDPJcuXeJBI3Zk0lwXFZb2zjqyaE83btzgafdDhgwRl/nf//6H77//nh8VPXv2LBwcHPg62U5nSWBr74CExCRLbwYhhBBCCCGEEEJIyQ0asVT28ePHY8yYMbwwJwv02NvbY/Xq1SaXd3d35615tSfWpYUtrw0asSyjpUuX4uOPP0a/fv14W9/169cjIiKCp9iXBC4eXggPp5pGhBBCCCGEEEIIKbksGjRiXV1YYc0uXbroNkgq5dOnT5/O0zpWrVqFV199lWcTMSx9nQ1z018nS7tq2bKl2XVmZmby9Cz9U1HyqOCLyIiIIr0PQgghhBBCCCGEkFIbNIqNjYVKpYK3t7fBfDbNAj/Pc+7cOT48jXV10dLeLj/rZEVAWWBJe6pUqRKKwpJ9d/H2xku4GJYItdripaQIIYQQQgghhBBCSu7wtBfBsozq169vtmh2Xs2ePZsXgNKewsPDURSS0rPwNCkDf195AnlQUx4wI4QQQgghhBBCCCmJLBo08vT05EWso6KiDOazaVavKDepqanYtGkTxo4dazBfe7v8rNPGxkZsS5xbe+IXVcPHSbxs1X5cnrKpCCGEEEIIIYQQQspd0Mja2hpNmzbFwYMHxXlqtZpPt27dOtfbbtmyhdciev311w3ms3a8LDikv05Wo4h1UXveOova0GaV0KyymzAhteLd3wghhBBCCCGEEEJKIosPT5s2bRpWrlyJdevW4fbt25g0aRLPImLd1JiRI0fy4WOmhqb1798fHh4eBvMlEgnee+89LFiwADt27MD169f5Ovz8/PjyliSXSfFe1xri9Karzyy6PYQQQgghxHLYAdDQ0NAXXg/rJhwfH18o20QIIYTos4KFDRs2DDExMZg7dy4frtWoUSPs2bNHLGQdFhbGO6rpu3v3Lk6cOIF9+/aZXOfMmTN54Omtt95CQkIC2rVrx9dpa2sLS7OTy8TLW+8rsdiiW0MIIYQQQizh0aNHPEOeiYuLg5tbdjZ6Hu3du4/X4Rw3bixeeeUV3hjGzt4Bvj7eJg+4EkIIIQUh0Wg01MYrBzacjXVRY0WxC7u+0cXQeHx/8D6O3ovh04++6lWo6yeEEPLiMjIyEBISwv/QlYQDDuVdbq9HUf5mk/yh1yLvbu5fiTkfzsJ91MTtS2dw8+ZN1KlTx+AA6bVr1zFkyGCz6xg8ZAj+2roVbFfe3loChQpQqYXrWBa/fndhQgghpKC/2RYfnlYeta/mKV6+F5Vs0W0hhBBSdowePZoP0544caLRdW+//Ta/ji1DCLEc5Yl5qHvtLfzzWjwmDu8kDlPTat68Bf+8Dh06xOTt165dh+9+XIZo/5dgX/slzP9wKtIWAmlfsjINwjJXr14tngdDCCGkzLP48LTyyN5G97RvPh+OT3rrjiwRQgghL6JSpUq8u+i3334LOzs7MVPn999/R0BAgKU3j5ByS61UQPqdjcHO92sO/2DXgGFQKBR8+uTJk7hw4bzZdSgf7sb8O+zgoydgC3j1nYluLrOh0kghl6kxvQNwwqo3HBwciuEREUIIKQ8o08hCKrna8PNVJ0IsvSmEEELKkCZNmvDA0bZt28R57DILGDVu3NigW+nChQv5kC8WXGrYsCG2bt0qXq9SqTB27Fjx+po1a+K7774zuC+WtcSaTCxevBi+vr68OQXLkMjKyiqmR0tIKaFW8oARv6iRIDBmJz95pN5Efdc4pCULRaz75WjakpaWxs8PXAlGyzl/YPGGzUarHp64EFVjdyAodidm9XRGi0498fXXXxfLwyKEEFL2UaZRcUoIRo2jowDHTqhhXRXhEDq/qdQayKTZ+cSEEEJKHFYzJD1LZbEGCmxYWX68+eabWLNmDUaMGMGnV69ezbuSHjlyRFyGBYw2bNiA5cuXo3r16jh27Bhef/11eHl5oUOHDjyoVLFiRWzZsoUHg06dOsUbTLDg0NChQ8X1HD58mM9j5w8ePOANLlhTi/Hjxxfis0BI6cVqC/1aexVYFdEvU9/EyvSB4nUs0IMKQIVDK6Byr4oMnwZwt32ENk3rIyomnn8+PVv2x9x/bwNwxvJ000PWtJo++x3jWniiYkCg0XXsM8o+2zkbzBBCCCG5oULYxVXIkT3Nf7QGIs/yyUS1Axo+E44WbXqrFVpVEQJIhBBCSl7h5TSFEnXm7rXIttz6rBvsrfN2jIdl/rCuoawILss2YsV0mVq1amV3WRoHV1dX/PLLL3B3d8eBAwfQunVr8fbsepbZwIaymTJlyhTe6VSbkcTujwWiHj58CJlM6A7KAkrsTykbIldYqBB26UCvhWm96kiw883sAFEejbP7Gx87ruKXWUZSfjU6Og7bTj4RA0Sb/9yCV4cNxZMnT+Dn55fv9RFCCCm/v9mUaVRc2FHiHhsQe2g+0pNj4ZT+CHgmXHXq4TMKGhFCCCk0LFuoV69eWLt2Lc+SYpc9PXVNGFhGEAsOde3a1eB2rK6K/hC2ZcuW8SylsLAwpKen8+tZFpG+unXrigEjhmUdXb9+vUgfHyGlgVKpROyxb7HjTSmCYnfk67a/pg9AgtoRba1NF7Q+7T4KFaTxeKiqiHceDcVNaX1YOen2JRM7fYqkxzfhGlCfT7/xupB1yDIKX331VRQ3NtyVfX9o66wRQggpPShoVJzcqiG02Q+4+zQZtR//jKZPbuGisg5iE1MsvWWEEEKeM0SMZfxY6r4Lgg1RY5lB2uCPvpQU4Xfnv//+g7+/v8F1NjZC3RWWKTR9+nQsWbKEZyM5OTlh0aJFOHtWyJjVksvlBtNsKB0b2kZIeabIzMT8nrZ4qXNrTEwyDhg5SLKg2vYuGnQbiHP2hsFbra2ZXflJ66DbBGzw+RFTBnaH06GuSJZ7o3bv7zBocCimNPGA7a0PsdRvJV82ROWPte80QHi7JfgnNghBdRrh3tXzOHPmLM/W69atW7EGcBYsWIADBw/i+LFjxXafhBBCCgcFjSwkxTYAvW1286DR/Yg4S28OIYSQXLBASF6HiJUU3bt350f22bazP4j66tSpw4NDLIOI1TgxhXVxatOmDSZPnizOY8PQCCHGlCo1lGoNroYnQCqVIOHQEnzQ3RlNn31ksFzMP1/j8al/4Obmhs/sb2De3E8AfAfVIgkUkMNWojA7HK2q1RNM7N4aHk62QL8/YA1g8NCn2LxpE8/kad3gR3xUfRW+SB3Ll99T7wfceRYESABl93kY1eUiUpKeYPq4Aaiy7lvU7DJJDBIXtdOnz+DE8ePFcl+EEEIKV+naAy5jQSM/WQy/fD4i09KbQwghpIxhQ8Zu374tXtbHsoZYFtH777/Ps4LatWvHx7SzQBEb1z5q1CheHHv9+vXYu3cvryX022+/4fz58/wyIYQFQk7z4ZrLFk7Aj4phOa5tk33SqX1rFfb8vYIHjJi5n3yMoUMG88y/mGMD4a0J5/NHVclEpG0A9t2K4tNdrU9jhfMXuPDUDs28vQ3WyQJG2s/4uZuP0bWRN9BdCBrdURl+Vj28/eGdvA+/zmZXvo93fvsbo2d8g5iYGB5kLkqhYWFwcHAo0vsghBBSNChoVIxYXYlfvv0K7lXqo22DSvCUpIrXqdUafmSKEEIIKSy5FTb8/PPPee0j1kUtODiYF8hu0qQJ5syZw6+fMGECLl++zLuhsWyl4cOH86yj3bt3F+MjIKTkYpl4Dt6V4TnacPinKaGL+2PsvLm8KL0+cbrmKfy9Yh4Gz1gNtWYQft59CR1r1kdKYgKOz+6NpRWBveltsOc597Nx33W0+Oa8yevcK/hgpvSkOD0p4Bh6v9IMIXHCPmpRiYiIwJ3bt+DhoaurRgghpPSg7mnF3P0jILAKwkND8OeJ6+hzuglqxf7N55/7qDMqsHRjQgghFpdbty5S/Kh7WulQHl6LGzdu8DpgzuHbINs/Du2e/YrHap9cbxO5dioUUQ95Z0P2/OSGZf5NfnsKEqXO6P3GJJz470+kht/Cgs8+RUBAQJ62cdzi33EgVrgfayig4APZdK56DMPkpNmoZ/UAsx3XYv4+YP7evP8dGDf+LXww7X3Url071+XYkLkWLVuhapUgbNmyBZ5eFRATLWRPEUIIKT2/2UIfTlJsNqxfy89TlGzceha8pUILtTuRyRbeMkIIIYQQYg7LuKtfvz7a1nbH0z2zee2hnAGjPjZH8a797/xyoJMGoV/3hn3mM9SoWeu5ASNGKpWia5fOyExPw+utA7Fvyzq8OnRIngNGzOcjXob/fxOw4uV0vK1Zb3R9w2ebcTKrEX5JH8wfw9rGO5Fwd7/JYvn6WE0z9hys+nUlzpw5I85ntdFq1qplVAA/MjISly5e4AEjJjYmmndtJIQQUrpQ0KiYvfTSS3ipYyfcviT82Eaphfaou288tfCWEUIIIYQQU7TBjsb+wK0ZwOSkDw2u/yX1NTzy6o0fnBdhpOc1Hiw6+nEfXnT+8ePHuHjB9JAxU9zd3fH3mh/45eC7N/Ndb8jX1xd3o7JwTxGAj7/bjkrS5+9jDlgfgsxMocYmq3HE6p6xwQjsxDKkWNfEatWqics/fBgsXu7WvQfu3b2L9PR0g3V++CErnqRTu34jXpyfEEJI6UJBIwvo26cXFk0bjXQrd3HeH+fCLLpNhBBCCCHEGMu6adykCb+84aOuSNXY4qqypni9YvfXsB/yD74N64b3DgfB7c2T+OWXFfy6mzdv8gLQjo6Oeb6/jh07ipfbtmvHs4/y61lMNN7p2xIpmcA7MR8g2LNPrsuHqPxxfZYtPpkzCxUqVODzatSsye+bFe5mRfL1xcTGipfv3b3Dz48dOybOY8MdNm7cIE7/djIYtvb2FDQihJBSiIJGFjB40CB+rtJI8ZotFRQlhBBCCCmpFi1ezDNpJn78FWqlHkDd2K3idVNaeqCCVRrav9QR73+3B0t3BkNm64y33hoPpVJZoPtjQ8AOHz7MM3wK2qb+888XiJd3Kftjk/wd+Et19YQkaXFwtTXsqjjYdic+9/gfvzykiQ1sU+6L123YIASAmrTrjKlf/syHqF27dg0/LlsGzwpCR7eePXuKy8fHx/Pzhq1ewsxv10Eqk8HKSo6srKwCPR5CCCGWQ93TLKBy5cro0q0HwvEMI+x24feMHnw+dVAjhJCShXpFlAz0OhBL+uzTT/n5927z8HnyOIPrzu3Zgs56mUH6ZDLDoEx+6GcbFcSHH87igZuOHTvgwOEj2HQxHduaLEBqZiZOuk3G2Cmf4mFGBm7cvoa+vz0Rb9cgdhOW/PQU34cKQ9H6Rf4HZUYq/vtzPToNGIFR0+bjWVQkL3Ldf8AAhAQLw9Sm/e9XfDNzHM/KYllVbIhb607dMOVLIeOKSUtN5cGnWbNmvdBjI4QQUrwo08hCalSvDoUiEzVkumFpNyISLbpNhBBCDP/s0VCKklVPRi6XW3pTSDnDgh+VAqvi4O7f8FtqN6xJ7ydeN7CmPc7s247JkyehpLGyssKSJYvRp08ftGjaBP/+9jPqfRyC281W4YP5v2DmrFl86FmDuo0MbpekcRQDRkzb/q9BpREOaL7UazCs5Nbw9PFHxaBqPBOKcXTzglQm/KXYu3evWBzbyc1LXE9Glgp3QyPw4YeGtaAIIYSUfJRpZCGVAwLwINERDd1U4ryENErZJYSQkvKHy97env9hZIGKgtQUIYWTYcQCRtHR0XB1dX2hzA1CCmLd+t/wcvsmeHphAz5LfUec36CiC359vw+SExMQFBSEkkxbSDs2FXh38geIiQyHq14nt03e3+PVqHdN3nbZ2UTUa9ofUc12wDl+GE7HrUCk+8to0bE7tq35EZVn7eTLyQMrofeItxCbXevo8LETqFS9nli38/qTRPi/tQIpNw4VwyMmhBBSmChoZCHVqgYh/nAS4AY0t7mH85k1cD86BS/V0B2VIYQQYhmspgjrQBQSEoLQ0FBLb065xwJGPj6Grc0JKQ7Xbt7CjEaP0Cd6nsH8Yc0q4d/EBLRr377EB5U9PDxw8eJFNG3aFPM//hANGjRA9erVxev9B63AG9NfwW9VvjF5+xvxcrTAb8LEUWBul1jYNB0A73Q/cZntVyLQumJl3oGN1S1a9v1STF++A3P+vm6wLsd6nYrqYRJCCCkiFDSykJo1a+LMLqFIYIBtMs5nAqcfxmJsu5J9tIoQQsoLa2tr/seKhqhZFsv0ogwjYimHDuyHvOJocdreSo2P+zREckIcf28e1+sYVpI1adLEbG2wSgGVUbHzNHifPowon5efu67PDkTyc9vKDcR5aQoVL3Sdce8//PlDKLxHfI0tIaaDaRHRz+BXwQMvauKkt9GoYX1MnDiRPzYW7CeEEFL4KGhkIYGBgVj1JBOoDdhJhD8kN8OfWXqzCCGE6GEZBLa2tpbeDEKIBSTEx+H1us+wSdFCnDe7ew1+PrF7Y5QlLBspdudEPJq9ROzw2/LZOsRq3PK8jr3KOvjD/zfEpGfAtuJMs8t1/uwv3Fk2oUAF7tltBg8eguHDX8Uvy3/i84YOHcq3nwrmE0JI0SjZ+bRlmIODA4LDY/jlVqqj/Dw2lWoaEUIIIYRYnEoB19Ue8Gw9QJw1tvIjyOR2SHwm7L/du3cPZcXgwYNx83E61qW9gUdxQPcVarz76A088uqNDS4foYI0bwc2hycuxLvJxgGjna5Txcvpjv7oMmgAdq1dkOft+3rRYgQEBKBr167Ytu0vjBgxgs+3tbNDXFxcntdDCCEk/yhoZEGJGcJ5ffkDfp6lkUKhVFt2owghhBBCyrnMgzOg1EjxY9qr4ry69VpCrVZjSt+WfFq/LlBZwLIqR32yHoFfaLDrpgKjNgGS6cCuA1dx2n0MhnlcM7rNa7a7c13nRw6rcMdzAOpYBRvMv19tLH564IQbJ//BnTt3nrttH86cgfDwcBw8eJBPa4cNZ6SnY9WqVfwye20IIYQUPgoaWdDWI3f5eSVplDjvcbzQVpgQQgghhBQvNsTp05mTIL/2A6rF7hDnT7HfhNjETPw0byrUKhWWLl2KsozVa8rIyMD8+Z9C0vpjWM9Uo+FLI3Cm2kKefcROlzxewxeOy3Dfsx+k0HUD1rro8RrG2/8NW0kWpBINBtkcMLj+hrIals0ajPf61wbUxrfX0mYS+QYIdT9rNGjGzytVq8XPv/rqK35+6dKlQnwGCCGEaFHQyII8/KsjUwn+Q+pjJwxN23HiqqU3ixBCCCGkXPr+++9RK3I5xid9YjD/A/sNmNCnHU7v34GqVati6lTdcKuyysbGBvPmzYV3BS+os8sFBXsPFq93lyaB1Z6WS1QI9urHg0fibZEJD2mSwfoWOX1ndB8f93XDnvGA6sY6s9uxY4cQvPvfHwfx7pc/YdqiX/n0l+t2YdEmIfOorA0XJISQkoSCRpYkkcAmuxS5pyyZn28/8/wUXUIIIYQQUvjee+89DG0IHNQrfm17aCFkMwE/f3/88ccf2LlzJ8qTVq1a8fNrZ44gya6a2eVY8Gi63Vp4pj1Ag92DjK5nB0lZhpK+c1l1+XnyySU4d+4c0tKMM+4TEpMxdOJ0SGUytOzUC04uQnFuNu0XWA2jpn+Kjn2G4vr1G1j63fe4fPnyCz9mQgghOhQ0srAIxzb8vLo0RJjOsrPwFhFCCCGElD/Hjh2DlRT4OnWUOM/vyRHcPX8SrDHXk8eP8eqrr6JWLWFYVHnRooUQQPv6vVHQSHR/He4lOhkt+878rbj4w3vYfgNYeUaY99Fu4I3fdcvc8BgiXg5R+UOtkcA6NRQtW7bEBx98YLTO/3b9B0+figbz+o9+W7z8yuDRaN21H55EROD996aiSZMmYs0jQgghL46CRhZWobJwhKWJ/WN+rrB2sfAWEUIIIaSkW7ZsGQIDA3nxYvZnm2Vp5GbLli082MGWr1+/Pnbt2mVw/ejRoyGRSAxO3bt3R3ly/sJFvD95OJan64IapzcsxvJffin37dyPHz+OqtVr4K91K8V50tdO42g1YagY8+oGYNKkSfxyxNNovLUV6LK7M748CNQdshBr7L7CrP+Ay1W/Fm/zfdpwVIn9F2kaK9hbA8uXLze67wP79opBI8+kC+h1sTM+6W24v+zo6obIqGhxOjExsZCfAUIIKb8oaGRhVlVe4eedFNvFeams0BEhhBBCiAmbN2/GtGnTMG/ePF78t2HDhujWrRuio3V/mvWdOnUKw4cPx9ixY/nQnf79+/PTjRs3DJZjQaLIyEjxxIZilRcqlQrTP5iGGy5txXlPlo/Fgi++xIS33kJ5165dO7Rr3x6rftuOERuB8z4zUa1WXXToNxadlwuZRAM//IPXevptwwZ4eXnx240aNUrsbDZm8ix8+FccWvcVAkv6ZiVPRUNf4PWRI41eF8bd2xdNgj/FK9cGYU7UIPzviqPBci5unoiN0b3/MzMzC/Q42fu+oLclhJCyioJGlubgy8/8pDGwlwk/jCfvPLHwRhFCCCGkpPrmm28wfvx4jBkzBnXq1OHZGfb29li9erXJ5b/77jseEJoxYwZq166Nzz//nA/h+fHHH40KH/v4+IgnNzehdkx5cPPmTTi5eeKWMpBPuysj8f5bI/HRnNmW3rQSw99X2Gf9/TKgqjpAnF/zlbex4RJQOTAINWvWxOsjRvD5Dx8+xNChQ7F27TrMnDmTz2PvKSsrK+yboqsZxcSqXWBtBYSGhhkFcSpXq4k2in9QK2I1UtR2+C+zPc5kNUBUYhoc00PhlXgeLu6efFmtggZ+/Pz8ynxnPEIIyS8KGlmaX2t+xrtPSIXU5+MXDY/8EUIIIYQwrFbLxYsX0aVLF3GeVCrl06dPnzZ5GzZff3mGZSblXP7IkSOoUKEC/+PPhhk9e/Ys121hf8yTkpIMTqUVy9aqMlgIbDBVj72PL774wqLbVNJkKXSBGPYe0fppmRB8bN68ucHyVapU4YHIUaNG8kCRwXU+bgj7dqg43cH6Et7+5GtYya0NlktJSQEGLcGQSy/huKIR6j3bIl733aGHeHdPEo6cOgTXzGBERUaI18XGxhb4cZoqxk0IIeUZBY0sTSJFgkd7fvElB6FV6O77KRbeKEIIIYSUROzPMBuy4+3tbTCfTT99+tTkbdj85y3PMpHWr1+PgwcP4uuvv8bRo0fRo0cPcXiQKQsXLoSLi4t4qlSpEkojbb2iBPc6/NwaWWgzeCbkcrmFt6xkGTx4MNasWcufr5xZaNNnzODBy7xiQSRlejImdqgi1jZysJHi8IF9PDNp/mef8dO7Mz8Wb/NG4gKT69qY0RMVn+0zmJfb+5ZZt24duvfowbOhtDWbfvr5Z3758OHDeX4chNy+fRuVAgIsvRmEFCnDsD+xCCcHW+AZ4KsJB1AHGiV1fCCEEEJI8WFdwbRYoewGDRqgatWqPPuoc+fOJm8ze/ZsXltJi2UalcbA0d27d/Fynx4Izp5e4fI5mk0+auGtKpld1LSd1HJa9L//5Xt9LMjkYqfLLMp6fJyfjxkzGp36v4baTVohxMovT+tKUkgRVLMu4mKi0K5rL5Pd01iwixV4Z+/TCxcuYO+ePahWrRqfv3btWnF4JwsgEZJX7P30OJz9hyOk7KJMoxJAVm8MP++CQ/z8mcwdanX57tJBCCGEEGOenp6QyWSIiooymM+mWR0iU9j8/CyvHVrE7uvBgwdml2FDj5ydnQ1OpRHrLOfYoKs4HRuVAkdHw0LLpGi0reYhXl6d0AHL//iLX67ZsDnavNIPWTW65Wk93912x7HXglGrohOs5HJkZWUhPT3dYJlOnTpj/vz5PCuOZRppseGeiaV4aCWxrOdltRFSFlDQqCTwb8PPGsrvirOuh+deR4AQQggh5Y+1tTWaNm3Kh5Fpsc5UbLp1a6FOYk5svv7yzP79+80uzzx+/JjXNPLNLn5cZmWlo6vmT1xT1uCTA1NWwqrDV5beqnKjvr+LePmqsiaqJO7EiHc/QsPWHc3epoP8Ana4vodbnoPEedVl4XCyk+L7SU1hZSXnmUasOPxLL70kLnPkyGF8+umn/HJycjI/r+QKDO/eDElJQmkIVzcPePv586ATIXnBvn8JKesoaFQSOFbkZzYSpThr67FrFtwgQgghhJRUbEjYypUrebYEq6fBilanpqbybmrMyJEj+dAxLdYGfc+ePViyZAnu3LnDsy3Y8JwpU6aIxYZZZ7UzZ87g0aNHPMDUr18/PnSHFcwu0w5ORqzMVZxc+usB1Klb16KbVJ6w4WJVks6K0+NDBqHna2/BydUda/YcM3mbRV7r0ED+APaSTIy03cnnbcrohobPNmPoo9F44NwYT548MRhqNmrUKIxvCWgWC6dP5k3EuGmTEPYxcO9DQP3kFF9OAw0q+PgbdGIjJDcUNCLlAQWNSgKpTLzYxj2Onx+6YdhylBBCCCGEGTZsGBYvXoy5c+eiUaNGuHLlCg8KaYtdh4WFGfzpbdOmDX7//XesWLGCdwnbunUrtm/fjnr16vHr2XC3a9euoW/fvqhRowbGjh3Ls5nYH242BK0s0zz4G1OSPxSn27dqxp8DUnx+m/OWwXSaQomHMSm4n64rtj3V/neMrafBgv714KqKFufHqA0LcjMJdn6Yu/BrfrlTl1f4+X9b12PFEOH6G1lVsD6jN/bLe+F8llD8fExDYXhaUkI8vCsF4dy5c0XxUEkZHp5GwSNSllHQqIQIThWOctXRXOfnTyReFt4iQgghhJRULEsoNDSUt70/e/YsWrZsKV7Hilezwr76hgwZwgs+s+Vv3LiBnj17itfZ2dlh7969iI6O5sN6WLYRCzDl7LhWFt1OdRcvt43fjK+/oqFpxc2/YkV0qpAgTiemZ2HViRCDZbq4hqNq9QaQSiRYdk8I9DBfOC0zuU7bYd9j7SgnJMTF8umJo4WIUbrGBr0TvheXm5I0C6x5nrs90KRNR14U2yegCs/cIyQvtMGijIwMS28KIUWGgkYlRIRK6A7RSiV069AoDIv3EUIIIYSQQpSVjp7xP4iTjarVR6tWrSy6SeXVrx2E4A7zwyHj4uthty+Il8NTbMXL7tIktJVfMbnOeT5/ILXTDBw6dAhpCU/5vLqxfxosE6X2wHdpw9GjFtCiS2+079Ef6elpGD16dKE8LlJ+gkZsmC8hZZXFg0bLli1DYGAgbG1t+VGy56WDJiQk4O233+aFGVnKNEsh3rVrl3g9G6fPxkfrn2rVqoWS7rp9H37eQn6Dn0us7XD19j0LbxUhhBBCSNl0c1FDg2lW14lYhtS5MipIjZvANLW6hRDP3vh4h+5gaobMcEjaRteP0c/miMn1ZsickJCcBk38A+zPbAE1dCUhtJamjeDn7XsOwcR53wES42UIed7wNMo0ImWZRYNGmzdv5sUc582bh0uXLvFx9qzgIkuPNoWlTHft2pWnTbPx+CzNmhWC9Pf3N1iubt26fCy/9nTixAmUdAH12uNxhjOcJGnivP9OCQEkQgghhBBSiFKjcEldTZy89GF7i25OuWfrimi1h9HsKfab8eejAFyJ0GV1bPxrv3j96E3C+QJH08PUmB82bkTPqslYmPpmnjal6+CRBh3WCMmNNsNIGzwipCyyaNDom2++wfjx43m3jzp16mD58uW8Pebq1atNLs/mx8XF8eKNbdu25RlKHTp04MEmfVZWVvDx8RFPnp6eKOnq16+P82EaSCSAq1QIHO28Em7pzSKEEEIIKXOUG1tjedpgcdrd1dmi21PuuVZDXSvDYWnBnn3wss1FjFgudEKLDAtGanIiklLS0ez3xpgZNR3rLgDpahs4SdPxp8ssrHaejy7WZwzWM6J+BroGpiBYJXQrNiVe7QSpWsgUcXIRMpnmzJlTBA+UlDVJSUJwUanUdcEmpKyxWNCIZQ1dvHgRXbp00W2MVMqnT58+bfI2O3bsQOvWrfnwNFackXX9+PLLL40iu/fv34efnx+qVKmCESNG8C4iuWFFIZOSkgxOxS0gIACHQx345SZWQobRw4hYXpCPEEIIIYQUEpUC8YnxeKIWCn1/Pai+pbeIOFXEHy6GQZqnSRqMPtIEvn5CsGf60Jdx67wwemDvvv3o3r0HvyyXZPHzFtY30cnmAlY6L0Ab+VVxPQtSxyFTY2Ww7jqamwbTbyV+DPvMp4b3/9RwmhBTHgYH83PKNCJlmcWCRrGxsfzDlbMzB5s29yUdHBzMh6Wx27E6Rp988gmWLFmCBQsWiMuwukisYwhrPfvzzz8jJCQE7du3zzXFdOHChXBxcRFPlSpVgiUERwrb+Er2ERK76q14hxNCCCGEEFI4bv71MYYl6Lqk9azva9HtIQK1IgO73N5BgDQSS50WI+AL4FSo8N+AqV6vMULuXMcPP/wADw8PdOrUCRs3boSVxLDVOcva/931I4N5HyRPM5juH/wh/nN7R5w+r6wL34RjBsvk9cAtW279+vX5frykbMhSqXkNXco0ImWZxQth5wcbx1yhQgXeBrZp06YYNmwYPvroIz6sTatHjx68rWyDBg14fSQWXGLFs//807Bbgr7Zs2cjMTFRPIWHW2ZYWKS0Cj/vYXNSnLd5n+4yIYQQQgh5MREHF8FTGi9OO9nKLbo9RCBxqog6ViE45jEe/W2PQKUGIkIfolZtoaFNWkoS/t3wCxo1aiTepmrVqmbXN9puh3h5Z+ZL4uWI1VPwwwkN6lqFGCyfJXM0mM5reYvU1FSMGjUqT8uSsicrKws2tnaUaUTKNIsFjdgXsUwmQ1RUlMF8Ns3qEJnCOqaxbmnsdlq1a9fmmUlsuJsprq6u/DYPHhi379RiXdicnZ0NTpaghLDT4iJNRSNH4Xk5FE5fQIQQQgghhSL+AV6uLsW5LGFI2poxzS29RSRbnE9Po3mpSYkIDAjgowuePHrI57Vr187gf4Ap3xwFPp2/wuR1WTGPcOMpYDUT0JxaI86XqnX/JSbPXQI3N8MubeZcuHAhT8uRsilLoUBGehquXtUNiWQo84iUJRYLGllbW/NsoYMHDxpkErFpVrfIFFb8mgV/2HJa9+7d48Ektj5zFe0fPnzIlynp6tVvgCMQxmdXzrrNzyNsAy28VYQQQgghZcTq6rih1HVNa13FuGMXsQw/P8N99dGjx/DzjIx03jDHFP0DvYl2VfHIqy+epQIrsmthq1J0GWX6WBOeCt6+eHrvijgvNi4GC3fdxsXQOFjZ2CE9IzNP282a9Oifk/JFkSUEG8eNG8fP2f9UNipGLqcMRlJ2WHR42rRp07By5UqsW7cOt2/fxqRJk3iKJ/siZ0aOHMmHjmmx69kX8tSpU3mw6L///uOFsFlhbK3p06fj6NGjePToEU6dOoUBAwbwzKThw4ejpPPzqYDoTHt+ub/NEXF+uoKyjQghhBBCXsT9c7v5ef+Eb/h5++qesJXrsteJZWk8GhhML1z4pdiwJresn1nXOuDwA2Dp0944VfMH9D7UGXdjgGkfTEfEmikGyyZd2MEb3rCOzBEREVCl6AI9U+52RHKmEn9deoKXHc5jw4pv+WiE58nIELqusXIYpOS4c+cOPxW1mJhYtO0+AH37D+DT7H01YcIEfpmGrJGywrCVQDFjNYliYmIwd+5cPsSMjVFmBay1Be9Y1zPWUU2LFajeu3cv3n//fV6zyN/fnweQZs2aJS7z+PFjHiB69uwZvLy8eArrmTNn+OWSrlq1avhjfzCGtgI6WutSXbefvonhHQx/SAkhhBBCSN6l752Ci3KhPg7TsKKrRbeHGJL7NDTKImJNcCpXrswLDbMaphMnTjS63RN1ADrx8qbfAZ9/x+exDs1NmjTBN0sWw+rBYdhWbYnwI5swsXNdODk5ibcd1r8nTFUPfVnxJ2I/A6KSFTgzrwbuBs3BqNGjTW43+8/BsAPWrHMzKRkGDxnCgza3b90q0vvJVGShXvP2uH3iP2E6U5ehtn37dgwaNKhI75+QMh80YqZMmcJPphw5osu20WJD11gQyJxNmzahtBo0cAA+/XwB0Ero/OBsDSQpgC1nHlLQiBBCCCHkBbhmhWFo+q/i9LSuNSy6PcSQzC0Igze5Yk3/BEg6fwdHe3sEBQWJ1w8cOBBJJroh29raGs1zd3cXL5/+eRb+/ns7JvxvG97d9r3Bcku//RbNl5wzun2GxgYuSIW3E+CN+/jmlxlmg0bnL12Bo7MrL4hMSg42vDAlKanI74cNR3P1rACpVMazzc6ePSteN3jw4Dx34SOkJCtV3dPKOlYcPPJxmDhdzTGNn197Rl82hBBCCCEFlZgQjwAXJZ6qhY5YVbwcIJVKLL1ZJIfFWy7DZkYmHFu9a3QdGzUwY/p0o/lfLPjcaJ6VlXBcfMuWLXz/unp1oY4V68Ksz9ywt8zs5jRalW1jzW4zG45UrU59ChqVMA4ODrC1Mw4oFkUhbFs7eygyM/Hm2HEYMWKEwfU0RI2UBRQ0KmG69+iJSKWwQzNIvoufK6XPH09NCClcf/yxCZGRkZbeDEIIIS9KlQWXVe7I0OiapnzS23RhZWJZgYGBZpvbmMPKWrzz7lSTQSOW6cGGtrFuykzO4sRsuVl1DDs5M4tSRxpMN69k/v7v3r4N30qBFDQqYeTW1uLQwaKUlaWArb0jL9jOSqvos3dw5DW0CCntKGhUwowZPQrBaUJKbW/lFnH+7qvhFtwqQsqf114bjn379ll6MwghhLyg6D8G8/PTCt1Q/5eql/xalyTvvv9uKc/o0GZ15AwO2dsLjWZMmfSSPxY5fYvtrtPEef9mdjBYJsBM+SvWVp0NP1JmZfG6q6TkcHJyRmpKSpHfT8jDh3Bx80BYaCgaNW4szv9+xxmkpaYYDJUkpLSioFEJTKVc+0AYv+0iTRXnbz9sPN6aEFK08nu0kxBCSMly6+p5VIjawS+vz+glzpfR0LQyhzXPYaeQkBB4eHjk/fdcao0htgfRSH7P7CKtKgNx0RGIjo42mP/jjz/iyeMw7N++Cb/88suLPwhSaFjnO23G2Q8/LsOyZcuK5H4cnJzg4OwCF1c3eOo1XnJydkP1mtXx75vA/d3/K5L7JqS4UNCohGHjte/F6l6WcS4H+PmBu+bHUhNCikZeWu0SQggpueocaCFePqxozs871zKsa0PK3hC3nGQymfkbKIyLazO3c4xae7+Xv9jhWSv88WN+PmravAJtKymYZBMF0XOSymQ8E+yzL77Eu+9MwcaNvxfJtrDsNqlMCE6plEp+/tvc3uh+fww2vSEFGwlb/Zau0zchpREFjUqYihUrIvjePcTb1+bTjdQX+LlSIucV+QkhuWvTpi1CQ0MLZV3aI1SEEEJKoZhr4sWDmULAiJnZvZaFNohYSq6/536tkaaU4VGiNVztdMPaHjo0M1hsYD3Dm7FaSawIMtOx32uoU486HRcH1q3M2dmZX2Z1pNjrcOPGDaPl9uwUMgy/WbIEg9+ahu7duxfZ9rAMN7YdSUnJeP9/K/G68074JJ5CE9u7RXKfhBQ3ChqVMOwIBhuHfTloDp9uZX2dn0ucvbHjlHCZEGLe6dOnCi1oREUtCSGk9FKdmCteHpuou1zTx8lCW0Qsxc/PD0+fPjV9pb0X7nQ4iPbrfDGunS5LaUr6fIPFMoQkEoPaRVbZtZOs5Na8IDIpevHx8eLlw4cP8/P69etj9+49YgMT/Tb3Xt6+8KkUxIM7LVu2LPSD8CxYpL3PFct/grW1jdnsKLZMaqqu/AghpQUFjUoYlj4b8zQCIXKhkJqnNFG87p/rMRbcMkJKD3bEpzAUVvCJEEJI8YsKFjKNjkg6sX92/PJXA+tbeKuIpeQcWqbPwc0Hj8NC8U4Xwyy0dI0uAFDVA+hXF/ht1c9YsmQJn/ftN9+g6+CRfL/j/t07PDBBilZsrK5kR7du3cTLPXv2wB9//MEv//bbb+L8lOQkSKUyPozs3LlziIkpnP9TLAA0dNgwPLx3h08rlcKBxvot2ptc/vvvvuXvk6AqVQrl/gkpThQ0KoE6dHwZ184dQ5iHkEZZy1oYL30xnuqrEJIX2u4pBaXd6VMoFPj999+pIwohhJRCfgjh55/GDBPndaljPnBAyq+aNWvy88GDBxnMrx37F+anvAWWuNKsErB9DNDF8SSmT58uLlO1rq5jFh1sKnrBwcEG003avixe/uCDD/j5wcNH+blfpcq8sx0L1mj3DQsj04ftJ7Js9C1//inOCw0Rtqth2GKTt4l4KAyhs7Oze+H7J+XD2rXr8OzZM5QEFDQqgfr06oGrJw8hxlkYfz/B4R/xujRFdm4sIcSsFz3SxwonMg8eBmPKlCn43/+o6wUhhJQmtnJdd7QQjT8/71LbG56OdACO5J7xH/3XZwbz1qb3xU1lVXF6dN1Y+LsA2gZ87boP4Of1m7ZESjG0eC/vevbsaTDNsohyOnbsGL796zgvhi21soJEJsPixYv4dYmJulEcBdW16ytYvNg4OPRS9/6o99h0l7ad/2xB5aCqePL4MWWkkef6449NGDNmNNatW4eSgIJGJVDfvn1x6cQBRLm05tM9ZfvF6w7eNmz1SQgp/EwjbdBIpdbwsfPa8eqEEEJKvlu3biHQTbh8SqErTvztsIaW2yhSaoJG6Q/OGc3vnfAdzzbSevwJoFoENK+kq2nj4e1HmUYW4BtUw2jYGKsfVME/AOmpqZDJrKBWKsU6lWlpaXla78OHDxEeHi7WTnr06JGY6XTo0EEcOSJkM32waJV4G5mV+S59NjIgJjoKtRo0wV9//VWAR0rKk9deG87PS8p/EAoalUC+vr6wtbVFRJYXn7aRKCGB8Eu19aIwVI0QUvSZRtrgU2GNfyeEEFLEVFlYMbUNlo3w4JNzU98Wr3Ky1XXGIsQUV1dXs9eFqn2N5p2byqMU/LJ7BV+DAsyk8Ok/v2PeHMvP+7w+0WAZNvzMzt6BX34WE4XI8EeIj40ym6lkzjtTp+KlDh345U6dOiEoKAj//bcLTZo25fP279/Hzz19K+rdSlsUG3ii8jIINNpbA2mpKWjf9zXs3L0nvw+dlFPqEpKVRkGjEqpZ8+a4d1vXPrKJrRDdvhQWZ8GtIqTkZQUVxTpZ0EjOOqFkFzWsXbt2IW0ZIYSQovRkaU0s7Z6IzhWFOhAPlMLQNCfbXFquE5JdYLlDdpBg5WDjYsXHFY1M3s4j5YrYSY3VQiTF8wd67ZrVCKpRBw7OLny6cjWhiPnChQvh6uFpeLvs/cLK1evw87i45/+fSk1JNRrK1rt3LyTqdV+zspKjUlWhHpY2K+Sh0h9BsTvRNm4NZqe8I17nKcSxUMG3UnZoiZDnK4zhlIWBgkYl1PBhw7DqixkITxKOis2z/Y6fJ2eooFbTUQxSdlhZWRX6EajCyDSytrWFUpFl1J2DEEJIyaRODIV/dvFrZlbmx+LlXe+a7mhEiJaHhwfkcmG/u1NjwyFPzHrVGyZvJ1cmC+fW1hQ0KmLsoGC1WnXF6ZZd+oqXJ87/DrZ29jh2/ARk2fuWXQa+zs9bdO7Fz30CqoivdV7uixXQzu019fKtaDB8iO2Hdo7/RZzelKHbf6wUEMDPpTJpqf4vR9l0xSs9IxMlAQWNSqg3Xh+BZ7ExqDTmXz5d20q3ExQc++JV/wmxtDt37hT6OF1tsOhFM40yMjL4uVJFhecJIaS0CN0ySby8rcU57EhvK05Xcre30FaR0sTa2lqsbfToq16Y1lUXPLqf7owjacZ1sfzjDgm3sZJj3759ePr0aTFucfnC9u8kUqmYVeTsrgv+sEyveSv/xonjx8T9y+6vjsW0/62ARwVhaGHnAa/l+b7i4+N40Gjbtr/NLqMNQmnZOgpZT/oCY3bicGYzdO8gZKpJJLpObqURe04ocFR8tKMeLI2CRiVdYDckS9whl+i+XDaepSJ7pPSLiIgo9HVqf4RfNNOIdT+xtXNAxJMnhbRlhBBCipp99HF+HuXcCgkST6RnCb8J3X3SLbxlpLRwdHQ0mG6mraiebXTqF7iYJQQstGpGruHnzp6+WLt2LebOnVsMW1o+jX7zTdy/dR1u2UEgbfBi4W974FMpSByqduXsSX7uG1AFTV/SZfu4efngs1XbxeBgbjIyFIiJjsbnCz7n0yPe1WUuMjO/XYeR0+bj7tMk/HjoPuRegfBq0cfkusYkzUcz+7uwloEHvUpKnZqCStAbokeKho9/Jbzx/jw8ixWGWlsaBY1KgSPe8w2m15wU6hsRUpq5u7sX+jq1P8IsU4gVK9y8eXOBg0/+lYOgogMphBBSKmjUanjbCO3Ob1ecgOuPdXUg3mhX3YJbRkqTNm3a4Nq1a7rpqp7ImRQ9KMG41bpDRjiCagmd+tLTKUhZVP7ctEmsJcQ4uwqZRgHVa/MMGHsHJ7O3rdu0NV+evU6BVao+97602UqPszuoNWnfFf/rDZycAh78adi6I+/Qtu50KCISM+D35o84GmW+5EJV3MVbrYRMndIeNKL3eNFh/0HYkEhbOzv4BVbDht/WoySgoFEp4BHUFPMv18M8B90Y2fC4vLWLJKSksrOzK7JMI9ZO9auvv8LUqVMLvB4bO3uxcCIhhJCSLfj2JfFytHML3IwUgkZZIefRoqFQ/JaQ52E1jerXr28wb0AjoZh6bqpGbYa1jS2/7O3tbXDdv//+i3r16hXylpZv3pUqi/WB9Glfg+lLVhvdZs6yTXB0cYVUJsvT8KrMzAyxGxsbeuhTKRAzOgJtAoG9Kwu2fzm7pwvPNCrNw9MYyjTKG/beGTlqFPJj/qefolKlSvxynSat4JSdPWdpFDQqBWrVqoWfDjxDDy8h0s18sPmyRbeJkBeV2w/2gi++xLFjx/K9zszMTPHoECuwrZ0uSCFsVkxRoRBu//jx4wKthxBCSPGIvHdWvJyiscO9KCHryDbisljcmJCCmNdHV3hZS6ExzCixUqXymjrMkiVLDK67desWbt68yfd7Tp4Uhk2RFzN4/HS+n+bqUcFgPiuAPefH39GoTadcbx8fF8dfk+RkoYi5KVWr10C12vVROTAIHy37Q5yfobHG94/r4uDtqHxt8y1lEPxsEiGVSKHW5C/TaMeOHejTR1f029IKsl/cpElT/PKLLgGiPIiMjMRv6/OXKXT79m1ER0cj/tkzWMmt4e0jDMW0NAoalZJhPFmKTByvtw6BMqEOjDwz2tKbRcgLyS0195OPP+I/kPm1fPlyMejD/iRkZWUVvHuajS3ingnjiK9ev1mg9RBCCCke3qFrxcsXHunaaf/x3WcW2iJSVrjYyxGysCfeaCVktzDfpI7AdM1SRKiE1u6pNhVhpVcn59dfV4mXWVFtJj4+Hu3atUNwcDAVEn5BrMPtqsO3EVjTOIOrbrO2z220wjrdseyvNWuEelSmHD10ABX8KuJZbCzPPtfamdkOl1L9cPBONCISzA/TauRrYzDdM/4Hfs4ynfKbyX79+nXs3Ck0RyoJ9h84mO/bXL58CRMnTixX7/3IyMh838bTSwiE1qgnFE5/cO8Ovv9hGSyNgkalhLOLK27cuo/pXvv49Mmn1uXqQ0fKbtCIZQTldn1+tNPsxJVpgFSZyseMs7TQgmBpwzKZFd+pYKdn2cEjQgghJZOrQtdl9kyIEDSyViShRRPjbleE5BcLQnzeXxegWJ4+BFtjq6Fz/ApxHjvYVL1+E355/Phx4ny2P6Lf5r1q1aq4f/++uL9x5cqVYnscpV2lwCr4bHX+DyrmlJeO995+Ffl5YmICPLz9UCHxDNI1NpiePE1c5tcTwWZv/3pjVwR6OJh8L+V3HzcvhbuLuwNyQcXGxqK8UBfgv4xUJmQs3r56UZw39d0psDQKGpUSKcmJ+GzCYHh5C2McmfWnqYsaKb20QU+WXpzb9fnxku1pNPQD+qQvgZ2Z9eY104iNk5db28DR0QmRkYXf6Y0QQkjhUGakwEsmBPev+b+NuFQFv9zKnYq1kqKVrrFGpsYKNso4DLjSGf/Nqm20zF9//WU0TxtIOn/+PBo3blws21oW/oCz4TpV67x4IDgq4rFBIM8Uth+pyMzk+6mVpWHocn0Ypie/Z7BMRpbpoMBDz77QyGzw1ktVjK6TSjT5DibkrJNlSfYODoiKjinw7Qt6QNeU0NDQEl1CIqsAIx4yFZmwd3RGWmqywXNuaRQ0KiXOnzvHz5PtdW0+D1wzH90mpKTT/mCaCw69SCZdBc3jFzoqk5KSwg4F4eG9O4iPewY7+4IHoAghhBStsEPfiZc3ZvQUL3/9Vj8LbREpT/7LbI/aj1fAKSMU1Z9uROPWHfj8Tz/9lJ+fOnXK6DZOTkKXL9YlieTN3r17EXK/4Bkupjg7O5ucf+/ePTx6eA9qtYoXrq6QKNRMu60MytN6ZRI1sqxMFzDuFfdlnmpufvTxJ5gyZQp/j4zKZzHlwvD06VOTw/ycXFwRHx9X4GLeBX3Pmwq0vf7GSLz55psoaU6ePMkPQF+9ejXfQbDTJ46junMSzr2jgv+zfUXWPCi/KGhUSlSpIkSqv16xHSNtd/LLxx/RETRSeum+/DUmW3fmN2ikvrXR5PwdO/7FgwcP8rUu9mOu0vttUipLd5cLQggpyyKv/Cde3vFQt2vrW8F8FgEhBeF/03hfY1ryBwjO0mWCvLdolbj/Ye5PY0yMkKlR2luvF6cLFy4U2rpGvj8XdRq34H/sTWEd7xi1SsmzwlQyoStbsEoYsvY8WzP64OaFE/yye8ojg2LYtdIOIy38+Y/lwIH9WLZsGbZt2wZLyMgQusflZG/vgAf37mLI0KFG17FA0h9/6IqGm2Jqn/952H48qw0WFWVYfPzE8WOF+r4oLO3atcPZs2cxffr0fN3ujZGjcfvWTRybIkPTikCH2+OxYt81VA6qCkujoFEpMnr0GBzYtRstPHTpagol/diQ0unu3bv8vIKPv9HRiga+gIvMfEcLU6S7Xzc5v1+/vmKB7LxiAStHFzeDaUIIISWTQ6rwe/LAtQfSs4Tfk8aKGxbeKlIW2WclonuQYYFjpmv8zzifVYdftrKSo1LVmrh06SK6du1qcj1Pnjzh5/7BP+DS+2wcS+EN2SmrXF1dC21d3YaNRf3mbUxmy+zfvx9SjQKaxcDlISfRqHYAwlQVEBgjHLR/nqbKMxj3zWks/+wDPu2n0HW//jD5HX7+eRfTARl9NnIrvFwNOHPoxWs4FYQ2Yz8uTtdYgMvOPjp/7rzRbVix99dee81kAEpbw/SDD4TnJT8SEhL4+aNHugDczA8/FO+zJJIXoGtnbKwQTHa21r0vJVJJifgfQkGjUmTNmtVo0KgJNl/Tpahdu5+/DApCSorhw4fzc1ZoWv/L8MLNO7AevR5dvS4X2n0dPnw4z8uyo37sB0gi0X09FjQFlxBCSBFLfYpG7sKfmpXJPcTZvdnRB0IKmZVcjiouQEflBaSHXDK4bkjC/5ChkcM15RbeWbDMIKMoJ20dlurx29DYn7XHWl0MW1+6BQUFoeugNwptfazhyZAhQ4wyVV555RUcXD1HnF7yXjd8cJ69SDoOkjSD6a+DdPuZzVL3QaVSIjMjXSzIr3VNWYMHnzpVTs215TrTvXIsDk0Ehtv9YbCPWpBMnYLQZmGlpRk+Vmby/KXo2bu30Xxt5lzODJutW7fy9bF6VDVq1Mj3ttjYCIFa7bC+P//8E4u+/holWVYB6hlJsjstGsyTSEtERiIFjUqZ8ePexIZffxWntx8reSl5hOSVp7cvLzat/2U4+LeHiFG7443EBS+0blZoUOvSJcMdu9z88ccmTJr+MatSKc7TlIAva0IIIcY0pz8XL2+PEYbyq2ND0K+3rrYRIYWF1XiZO6YvDv79O9IfCPVG9c1Ifg+db7zKO6mZwoaatOrSm9d1+Ut/2FFW/rKryyO2r2jv4Fho63sWLbRD371793MzfnKaYr9Zdz0y0dThCWY4rEMX6zNYs+0iUhITkJqUKGy3yngI3OJnfXnNoJzSzi2D8x91oH56CQOqRPN5LQOADzsB0zuyQJcMbm66TPiipC1YnZgoPA59bl4+2LrlT3GavZ8PHTokBpqWLFkiBnnYddp1dez7aoGCRtqhctp6SOeya/1q9e3XP1/7+sUhMw91q3KysxVqqKqhCx7JNFlsyAMsjYJGpcyUt9/G+Lcm4CW58ME4dP662fG4hJR0rLgg2wErirRLK72gUX4cDE6B/8RVeGqnK3ZImUaEEFIypYed4edxdjWhhjBsIuPSP/D09LTwlpGyyMvDnWeQPA6+hyaNGhhd/29mB9goE1HBKgEBbkDYx8AnPR0wb4XQQc3B2QX1mrXlfyjHjRsn3i4j8nqxPo7SGjRi+42FpXqD5nB0duVBGBaU0A/iOHkFiJfTbIyzFvvYHBMvL3ZaColGhbftt2BSnXTcjzbcZ4yPFYI/+n5Uv4XgYF1Do85duvDglf3xKfB3AdL/GYHaLsKwK6VGitOtViCs3UIMaQhMb5dZLAcztdlw9erVM8huylIo+L573DOhYyVz5coVdO7c2eg/6Ztjx+Htt98WA0+8PlQ+96nZf4QWLVoYBI203Qe1/t3xD06fPo1bt27B0m7cuFHgoJFaI7yumTKhUD5jp4yl4WmkYFq1bInmaiHCGuHZDitXrrT0JhFSIOxHh33xazONcqZfvsiXpBQFC/QcSRF2Dp7oBY1Kwpc1IYQQY/KEm/z8gMtbyFIJ39VzxlDXNFI0ateqKV5Oca5sdrnGyVvxVU+gkivwWadUnlWtJbex4UEKe5WuFosyk2oaPc+mTZsRF22cnVNQrbsNwNBJM3kQY+nSpWjatJkYHHm3h4+4nFoiR317w8CPVXocLnsMxyaXD9Hb5jj84w6aDBQkxsVCbmU85ChnoemLJw/i+2m67EiHFF2XuLNZ9fFI5cfP//eaLxb0AF6uISvyzntJSbphdd988424zSwwlJmhG7LGHrO25hC7rlHLtvCqIBSGZ0P/WDBMG9CXSGX5DhrpB/O2bNkibIeJgAzrNNetuzBEefXq1SYzuV7UkydPMGHChFyXqV+/Pj9ft26dOG/Tpk15Wn9YqFCzSQLd/yE7VXyJ+B9CQaNSaPDgQYgO1kVS35n5cYGimYRYmiIz0yDTKGfQSKU2/pLctu1vo24kpt7/1pICtvTUq2VECCGkBMtKh1wjfP8fSa7Gz1VR9/HW2JLXgpmUDXVq1xIvd/U1n+nPhpQ4mx6hxvd5nj6NwrQOunkpksIr8lxWbd68CcF3Cjcjix24ZIEOVuw5IuIJ35+s06gZWst1w59aPpgFW4nhfubn+1RwkyajlfUNXhfaVinUVfNNOWuwXMida1CrVPiySwWD+W6SRHHf9dix4/h5ELBbl3hmQKk3VOlqVnV+7udsXDNHeF8VXqBEvwC2NpjGgkbuXt6ws9dlwsyYORPdunUTtlWphJ2DE2Kio3D9+nWo1SoeaHFydESdpq0hlT0/aNS4cRODLCxt4xxm+z//8POs7K7GDk4u6NJnML/8xfpdeBwexu937Nix2LVrFwrblHfewYoVK/K07ObNmzFw3PsGw/Vyw14/qVSGz1bvgBS6/z8uGWEUNCIF4+zsjEO3dB+4ykM/xsGDQoSbkNLE07ciDxppg0U5f0iU+n3vsw0aNBA///yzOM2KVtvaGu+ZWWkKFjSSKp/f0YIQQkgJEHVRvBiqEOp8yNPjYG8v1IUgpLDp72+8OcB0Z7QsjQzJtoFoW03XuEZ/WJWDsxucJIn4QD9oJPUoqk0uE3bs2CF2pitMUpkV3/d0chKCIL369OUFsvXJVSmQKoRMGi1zzavZ0MScmUZKZRaaVHTCN0Mbws9JCABJoUZERAS/PG7cWAxvbH4bRyV+Jl5mGUdMfDpw5MgRg+VCQ0Ph61t4DQDCwnVd37744gt+zrKbWFe1mo2ai23gY2NjxeVY0IjVXWIaNGgAVzcPsSB8847d8zQ87cqVy2J3QUY/OObq5s7Ptdcv33sFB3cKQz8rBlUX77eg3cueJ6CSbthiXlSqItRv8vHRZa6Zw55bqZUVLxZurUrGtoyXUTXmHySlxIvD1iyJgkalVNNOAzHFXkh1c6ngg6Xf/2DpTSIk39iPh36m0YHbUQbXK8z8sOiPmZ45a5bJZVRZuuCPi5mjfaZYK3Q/+FM+X4alf5/M+40JIYQUG1WccAQ6TWODmxHCUIq6DjTMhxQdbRcn7T6M64Vf0T5AFxxiMjXW0EisoHbSddzyC6iKKZ99J97uziVdTRxOnf9OS+XJw4cP+Xlhd5HSZr54eHjg9amf4NSJ41BkGncnY0PDtNRrh5sNGp236YE+/frjyy+/5NPJCXFQZmXxAMbAJhWxcZgQ1FForMVMoyDJ/Txvr59M6MbHnoaTJ0/i+x9+wLx587Lnqc12OyuI5DTjg6hsm63k1vyyzEoIrulnwSQnJxtMs318baaSvZUKAbIIfPrpfAwcJGQHmaPfdVAbNGrdpTcS4oXsJ1X2QWX2WWrQ8qXs7TEMEjk6Fl7RdK1aepmGObOyIiOFwur6tM9VhQqGmWamsOfI08sbtooYpGpsMS35A6ggwzu3WlGmESk4V2dnDJYIUfc4jTNOnbtU5GNbCSlsLu5e/Ogb+6FLTM/C25sM047vR5nuJqJ/1CEqyjDQpJWSJPywzOkMxLGDNMGGaarsyz0kJMR43dbO4uVabV6Bl2/FfD4qQgghxSHyglDfYhneEef9NP89C24RKeu0BXhXrVqFKlWqQBP3GKd/fB9uCbohNJmQQ6LJgo1G9+fd2tYWrV/pL6xDJjMqGBwV8QSdOnfBiRMniu2xlCaZCmG/T1PIGRey7Ndi9569PAhSuUp1ZOrVGsrJ794GhEclw0QiPDfhsy04fPAAZs6cidGjR+OPHxfi9JH9sMoOsNhkZ7+w94i2ptGWkXnf3hClPy5n1eBD2c5sWYip774rDpfSvqfM7Rfnl0qpMgrEsDpHOUtCVKxYySDwIZXrAqvhYaHi/AkuWzDL9mt0DFLh721/Gd+fSoXLly8b1Xti+/x9Bw3E8nFB6FBdblRvqdfrEwwCVFpF0ShKmT0sLqd33p2KAQMGGg0PVGRm4N0vf4Kfn5AhZs6DBw94Vzn2fPvFHUTd2K0G11PQiBTYyDdex7n7SfCVCpHYyi1e4RFnQkpr97R0hfEX8eSNV3DifiyG/XIaD2NSTP4Q5PyR0LKzEX5YvujBdvLYoPGZBtcPe/VVtGzZ0uh2KivdEcOUTOpMSAghJVVGhFDf7nJ6oDivUiXdHxhCChv788f2O4YNG8bPvbw88PD2NSSf2ACZVCJmGtko4+GQKQw/MhV4ss0xcmbnv9tx+NBBtG/fXpzHDgbnrFtTXmVkHxhnNXIKE6shk5KSgp3/7oCLhxcP6OW8j2tZQr00xv6x8F/LVKZRhE09REVG8PWxYNSgQYPE6+zshH1LG2sh80QBa6SnZwAJD83WvjLlp/ShGJDwDS6rauHQRGBCayA66qnBvnHO4V+sq5j+ELK8YuvrO3ISajZsjqbNmmPt2rW4efMmPH38DPa/ExJ1AZyuXbvi/vVLeOuj//Hpp5ERaNWhM54+jURD69t83riWQIeOLxvd36+rVqFJkyYGj4Vhn4FBVaLR4PEPWNtXeBzP9Oot6ReZr9+indFzXpiysj+PrPD3P9n1lZioqKc4e/aM0fBAlUoJKyvr5wby2OvDsqv8qtZAqwcmRlBQ0IgUVLVq1XAvBnCUCEcxHOp35sW5CCmt3dOy97UMRCVn4vVVZ3E2JA6dlxwV5+el80KdQC/DGVmGQxZYoEo/4BSZmI7Fe3VHCpm7ZjKdCCGEWBb7U3E/VPiz9DBLSP1v6aj7I0FIUahatSrfZ3FwcDDIAEiKixGbdyRqHGGTpeuMlr2gQaBiRB3D2jdNTSQ19+rVC8OHDy+CR1H6aLNb7OwLd8gR2wfVtpaXy234fqFMYvgH/ZOUSeLllFhhCJK7u6fRuiIiDIcndenShZ9PnjxZHJ4ktxKCRszny38HsofYmnNOUdf0/Cxh/vJBgGoRjIJGL73UQSxk3aZNGyxalL1QPrCAR63GLfHOgmWIiY3FmDFjeLA0Pcfwt+gYXWc5tg1PH4eiUrXawuO1tuZBnS1//ikuU8MLcPc0fv5Cww3rGLHgG2t8k5iYiHoOwnWutsbROi8/3YECVjdJ6/793If9sSDNsWM5hok+hzL7OV64cCH69xcyBxltJhkzf+U2fv7aO3PQslNPuFfwwcXLV3Jdb1hYGD9v08B0R0Y1BY3Ii5i++ioG2h7il+PlXrh18ya+XSqMlyakNJDwTmVCplE4q+qXR/pH3sxlGhl1XsvRFe3E8eMGt/169x38ePiBwTJxqTTkkxBCSiKWzv9KDSBDY40ohVD4ulfdHAcLCCmmGkdsGIp2j6J//BLEKwxTiazUuj/aLJuld1XDwspP9GJI2kAUq+Oj30WqvHfbfXXyhxj/cf6DH7lhhYd///13NG3bCY3bdUbwvdsIsjbMELuqrKmbkAvBwg8+FgpD62vm8YyfBwYGikXT2Wu5bNkycRknO13QqFLlACiSc+929lHKZJPzN6T3MpqnHzQ6fvwYz4bR1oLS328OqFw5TyVN2PpYgNPW3gFhj3TlHGwcnAzep4mJhgdY67dsL16XpVAgOckwQNrYH5DrfR609OtVsfv+8ccf0ahRIz40MVOj+zydO7gNt29cE6edXT0wfs5XYpBKa9q0abk+vsWLF6NDB71q9Hnw7JnwGu/Zd8BgfuXKwmvu6OyK6vWbYuWB6+g1YgKvaVSpas3nZhpdyg4q1atouomDxtby3RUpaFSK2fo2QBu58KHJUgMy5wqY9v57lMpKSmWm0aCfT+X5dtu2CVH8XOVIL87IHg+f8/61tl8xTiO/Em64U0cIIaRkOLB3F2RS4O8M3TCH1/oIR/YJKS7rVq/i56lJiXC119arscGwe0MMlmsQKrTcdk67j04KXdaF1tT2gJejYTa1fqOQ8uzjT+bi15UrULlmXVQMErpRFRZ3L6GrlZu3MOywau0GmPeGrpWZQmPYSW3j78Jr59ZwMN74Hei0XHfdH0I5HnjlUvRYIrNGDZlQ56epvxo/ns3A0ISFvPAx887fQIzaVUxMu68ynXnyRJ3jPtQq8X2jPWeBl/DsDmj676PwsDDcvi0MFcsNWw/rJGdtYzh+rlO/1wyXy97f1i43YMxUBNaoC7/KVYTHLBG6qRncJkWXnWQqaMT+y86ePZtfTktLh4eNLsilThayjr5Y9x8/Z7WoOvYVMvKksrx1TGMBtfTM/B8YzsgSAnOJiQkG2UVW2bWqtEEre0ddfVQWOGLLp6aab9LwJPIpAmvWg4ur7nb6FK/MgaVR0KiUq2OvG6P66ufrUL1OA1y5knsKHCElBfuBzu9OUd36DeDs4iJO/7N9u8nlNFDBQXfAAbbp4SbvnxBCXsS9e/cwfvx4DBw4EPPnzxePRJKiw34z7m75gF/+PUMYjiBPiTLYiSekOHh5CdltrK16pl6hG3WOv1i1IlahRsQa9LjcCx0VQgH3nBb2gFg0WLuPUtjdwkqjLxZ8jqTERNRq2KLQ1639cz9y2qf8fP6qf+BQUxd8jlfr/sTLoELVWkI7dwcnF2y4BLAEddsPgYFrgUnZtZ03bthg/g71ghpV/BzwfXBlnMuqjz7xS5GeBWxyn4Hmzzbgy9Q3cT1LaGlvSh0rIYNIlPoU8fHxBu8f1slMW7i9IAdfeaaRlUzskqZVrZ4QVFMoMvHxxx8jNUWoOerk4sbPs7Iy+W0atGivK46dY3c7UK4biqal/17X/x0NDQtFOnSBK+XTq3hlwGs8yJKTq+fzu5Qxffv1xw/fLX3uclOmTDHo5JaRng7fSoEIDQmGs4su+ychO9uKdcozpWa9xrkG6v7dsR3TFv2KB8k2+DxlHKpnBxZLEgoalXKSBuPwhu1OfvlEhAotX+mPQ4eEIWuElHQsRTu/O0WsjoCtrVDcLtdgk0qJnj1MH3XW3i4vQaOMLBXoOB8hxBwWLGrRogU/KsqKYPbo0YN+h4sY24nv01D4HbiurM7PKztQ4wJiWWl6DT0qSY2HHTULng+ZxrDzlD4PYeQTNm3aJDYLITDK5ihMFfwD0HXg62JghAVZMuVC8GNu+vvoniR0JmNWZI4CHITMJFbomunbty9Yz5S/bwCJ2Q2/qlcXvpNMkjsiRSN8dz1OzX7BWYNfVUVsj6gMhzrCcKmV6QPRJ8F8yZEW8puGMzQqseOYtsnLxYsXjTqIsULWzGeffWbQgcyUJ0+MAzv6Yp4+xRdffIHY7JpGaalC4MSnUhA/V2Xft5ObO9xy1KRe/HKEUX1S/ek9e/eKl3/8/jtUstYlSfy3ZRUkpgqh6mU7Pc/xY7o6qblhQwvZgSGt6OhoJMQJ2+Lm7mGQbeXs5oHkxBy1zLJ5V6yMR48emcx4Ytw9K8DV0wdfXvfGqvT+ZjPMLMni30bsxWBjP9m4T/YmP3fuXK7Lsyf37bff5jtmbBwxa0+3a9euF1pnaWYV0BE9bXRd0+r5AlevG7YtJ8SS9CP0poI27Is/P5lG7Ida+8OS61BMjQqd+psuIJnzh0qds/6RHnbkkNLDCSHmsH0NlmnUvHlzTJgwATt37sT7779v6c0qs9j3sbe3N+p5q5Ci1v0TaWRj/FtDiKVUtwpDktp0fRJz2mY3AXz33XfF93rOFt7l/UBjoa9TKsXomYb1iaQaIdixPqUz4pW6IES/n4Q/+Pr7hKwxkb7ndimTSOCeJmQJJVgZFoOeba+rfZTTA8++BtNnFTmybNRKMcNIi01r52m3uV493e3Wr1+f66ay2qAu2QW/vXyNK7VnZmbkCNQIgRxPH39+Xr1BU7wyeCQvhJ2zWyDzp15xbP4Qsg8gB1SpjjOnTxtcZwVd8Ku+j/mAql12vaWhE2eg7Ut5r1fEag6xLnP62UB//SWkjjk5CetkUtPSodEe6NY78Mz+j9RslEsmnEaDIUMMh6wybm5u/DVa2P4xWp7XddvTekl+UbirGMOaq+UuaLR582ZepGrevHm4dOkSGjZsiG7duvEonimsaBdr5ccidVu3bsXdu3excuVK+Pv7F3idpV5QD8CpljjpkHEH16/fsOgmEaKPdYzIWXBPmy7LCmFLkL9MIzb8QJ0d9NH/cY5JEZqTrEvvjctZNXDx3GmDtNykTN2Xu3Z7tJlGTxLMF+FWqig1nBBijP2xW716NV5++WVesFPLw8PD7JAA8uK0hYH9HBQ4rGgmzh8/YrAFt4oQQ4cULdDg2Z/IzFETJ6ebKboW3aymEUugYBkj7E++l6enmD1Cio9H8lWT8z9bKNSlMlUIXbythy77xBwXKyHbTG6d9yCYlUQNp1hd8efbKqFekEijMgowvvfee+jduze/HBurG+41sD5Qxxt45zldt1lwhLWLZ77csMfschnpaXjjvU/QrscAg/ltewzCqOmf88s2Jj4Gr71mWBtJ+1+gcnXd/1r9oYHi/SmFDoSm2NgJBxLcvf1gm8esI/ZfYtKkybzLXJ06dcT5gwcPNgoSatRqzPh2Hb7bbliHlRX87vHqWHy2ekee/0tou9vduHEDw+qk4t8EoeOcPjdpyenibNG9mm+++YYfnWMt/NiLtHz5ctjb2/OdMFPYfPYEb9++HW3btuXZRKzqOQsMFXSdpZ5Egkr9vxEnF6eNRE+vm5QZQUqUnOmxWizLiB0tyOv7lS3HfiiUKmF9Fy5c0K1LAuzI7IB5KRMxIOEbyCSsfaoVjiqaYHziR1hxU0gpZr777juD1NucrSyH2+6Gh0Q4opSlos8SIcRY9+7d+QEp9j3C9jVYK262g86O5GpbLZPCxw4YjhwoHEHenqkrgl2zpl6HI0JKiLvS+rlen+jWymB61su6zAUHR8fnDiEiha/6U9M1iXIGOY4ePSpmhTHOzqaLGOd01qodP79o2zFf2+V6YxNG2f5r+kq1ErHx5pu3bNy4AWfOnMFLVYC/RgE3Zzz//rKUWeKwPVYQ25wn4WHo/uo4dBn4hsnra/pY40zu8SnhIWgLeGcJB3bnrfhLlxQBXfCkdWUg6rHQoj4nbZDL1s5eHFUQGRmZ6/2ePXsWl69kVzE3QX9UgyJLwTOptNlUWlFRT/nwtKp1dDEJfXVbGb/W2mFvmZlCEPGh0jibK16dneVUAmqwWixoxI70s7GW+jtW7Mgcm2bpYabs2LEDrVu35sPTeGpyvXr48ssvxTdFQdapfbHYl7L+qTSpWLEi7O/tE6dndrPH4+xq+YSUBDmHg2mxLKPU1JQ8f+ZYqmxKSrIYhLpz547euoCpybpfQdZVx9raBqMSP8N+RWvsdhyBnTuFTgs5W9hGJRnWGJjtsAYKCLm0qQqlUVCJEEJ69uyJDz/8kLdrZkcKWVr7ggULeG0jOnBTdO4/eIBONYTd11i10BShnruFN4qUa9rMQmu245HDvwG5F9t1cbTF+nsB4vSXPYVz1mlJPzuEFC+Wta4v/ug6owzSl156CT4+PgblUfJCifwV7PeRCln1yRmAvcRM5plaiTu3dfvEphz9eRyOTtZNj3ptYK7Ls+wZbR0pbfBo7bF75rczIAh9Xp9gMM86Kx6rG2wVOwPmRptpxDrMscylGg2ETFK7HEPbYlIBFy9vk+vQdi+rUqch/78QFhYGPz+/XEc0sIM9j0JCDOZpAznMW2/pHhMr+i2X63XZyXb/3j2TQ/i0mrbvikqVAw0Ofnz62WfCfWUIox12KYRgor7uNkJGk6QEVFe1WNCIpYKxP5Is+KOPTZsbv8v+6LFhaex2rI7RJ598giVLlvCdtIKuk1m4cCFcXFzEU6VKlVDajG2rK5jF0rVVh6ieAik5/v3X9JERlmXkUcE3z3+wTp89j4vnzyE9LY1Pf/qp0O2CyVkTz0pq2L0kw8oVffr0NlkL6WZEoni5vew8nCRpSNYIBQrjUhRIjIsTu1IQQogpoaGhmDp1KkaOHInFixdbenPKrIuXr8LTRRiCcFUpZBe90a5w23ATkh+sbIaLmzvuf9kTdTMNhzatvJAMlcb8362zGdWQaKcLGmm5u7vj6pXL8Kto/o9oeWCp7nEsa13fnP5NebkFU1g5FKaoDha8kr4HazPHIS1LgwQb3f+9y6oGyNDuzmpUUD4+Cc1i4H968a5+IyehcdtO/PKsBobFs/v43s/1fmOioyGzyg4ayaww7sOFvD6ROVZWcrw6xbA1vH9c3ptCqDXZQSOplGcuadnnCBqxMqSN2nQ2uQ4HZ1fM+u43WMmscOHcWVSuLDxfx44dy9M2eHp68deRdZ7TunxZeH2ZiCdPYGOfXcBco8Hhw4f5RVd3D1iZCCZpsXIY+kW6WZLLnt27+WVlZjr+yhBeo5wcJUJASe1ZDX/vNKwBVdykpe2Lg31gV6xYgaZNm2LYsGH46KOPeFr4i2BHBRMTE8VTeCnM0mnRojlkkUIB7AOZLRH4bBugEFogEmJpc+fOFS/r/6iyoWbsh8jc8LWcliwVjtjZOwiHLPTH+rPMTU+JLrDDDvjdS9KNeZbqFdHTPzLE1PbVpRR/IfnUIAt0z82nqFKzDtUVIITkimU7nzhxwtKbUebdvXMX1Z0S8VgltDpnOtU3/tNNSHFm/CfGC/VJjm1ZY3T92CTdPpAW2xWakDgHn4W1xBLWs90MZ2chm668WvDFF/nqilUU3JDCS52Y07hxY8z6cDaaNdPVWMvNuj7m19WldgWELuqPJumXYPXgCOa8UgUhygBI/NvxxIh2VXTvhzBNIM+64dRK/D1Q+P86Q28k1OAJM/D+QtMZULUdInLdzqwsBR/mpQ16vNzfcHheXkRkOeDj5EmIUBkW/TYlMyMDL/d7FT1H6DJ77B2d4KlrMsf5+FdC7aaGwzq1WDZYg5YvGRVNZ8PJTanXvK3BdGxsDD74YDqqVNHVjPL20dUds3dwgE12B2dWKqNTJ9PBnuexzs6IYt55awQ+SJ5mcL29XIIpLRxgJdGN1LgfKXzHlLugkaenJ++CxKqV62PTOf/QabGOaaxbmrbNIVO7dm2eRcR21gqyTm0RMzYOVf9U2rRq1QpxZ//ml49nNeaF97KOfWTpzSLlVN9+/XgXIS39oJB+0MjWyQVSKxliUxS8BlFunSIYbeaQtvCg/hEodvtYjZvBtBq674pkG92Xfp26dU12T1PEhCIsx5Dw5oFuBh3bCCGEWAb7/bhx/Srkdk5Yrzd8xMvJ/NFvQoqatqkG06xlG6Prjyia8U5/36W+isCYnfg1rR++Sh2NvQrdsgozBbPL+1DX4IdCOYGVByzXGbqJ5sFzmxt8tfBL/p80L9q0MByG5Cd5isc/v4lzH3XGr6Oa8wCQa3IInB4dRVZaCtQqNd/vZTV/kivp9o0fSGqLBaaTooSObFpse3u+Ohb1In7BqxeaopmJQTR/nsl9+KOdNqMmFz1fG49R0+bp7ledCbtM3eieD877Y0NGLwxL+Mrgdqk2/qhaw7Dg9bo1q9GyU28E1tDto3+0bBMcciTweHhVgH12lzRzcmZE6Q8309e2uzBEr3YTXRDq4MGDBplGTi66QB37PGo/76HBwnM+cOAgPpQvP/SDkB5ywySPObUeYHbPugjw1h0Yyfk9U66CRizCxrKF2Aujxf4AsmlWt8gUVvz6wYMHBn8UWREpFkxi6yvIOssKuVyO+n5OsJVpkKqxx/msupBf/d7Sm0XKKVag+vr16yaDRtrPb7UATzz064RbVV7FlAMsfdu4U0RO6WqZwZhlprY34GILOOU4CCWRyeCTdkWc7u8itK00tROm0k5r1LiT3WhxhO0u4b6spPzHl4JGhJRvEydO5B1b2fdbzo6QpHjMnPUh0lJTYCXVYEW6cXtiQizNzcX0n9nxSR/j27TX+eUFqePxS7pht78zWULB7Ewl+5PqBn//ihYdnlVS1G/QEIPf+iDXoT9FqYqXA983LMyOmKwLsL63ZBvw1htDUSF7R7Z6jRo8gcHNzRXJCXFQqZTibdRSa9hkH2W9i7rwzI49rF33m8E6bWzkGPHeXDQK/RpydRo+72a8HbaOrma3kZVxeBbz/M7jAdVq45Whb4rTL90ej/7nW8EpzTCIFa72wdr03jy7Llltx59TFgTRf3/b2NgaZRAF1qwHeY5GaRI8/zNhaybg9eeff+KNkaP45bfmfCW+rv1HC5W6WSDr2jXdENMv1u8yG7j1dRZGNfz99zZER+aetZXbe+CTHH0zmjrHQSaVQCkzfAw5y3AUtwJ9AtjwrcePH4vT586d42392LCx/Jg2bRrfAVu3bh0vIDlp0iRe+I11PmNYXQA2dEyLXc+6p7GaASxY9N9///FC2Kwwdl7XWZY1rF8PLllC6tp/mdlR7ExdrRZCiovQ5Uz39aIfcNFe7t2nPdI1+Ts6HOHbnp/Ls8dYs5aht2YAJz9whtF+lXdt1Ev8R5z0zO6GxrAfqVeGjEaLVm3FAtvChquhyN5UbdE59lvB0lwpaERI+cYC4Wwfo0WLFnBycuJDEsaOHYuffvqJd6Vh+xqkaP3993Z06DUEvvFHxXmTOuRoPU2IBbGsEFNOZ5nuqqS1Kq0fP991W8goePLksVhXpjxjQ4DcPE3XEioSGjUS1bo/611re/N9xsIMGrHXt+Ket1FBKmT6NMNF3u1X69jRo/jss8/4sKjMzHSo1SoeZNAWTM7MPsqaCTnOZ/8dl2UKxbK1ulQ3DHS4mxgRJ4XaqManFpvvW0lXuNmcnM+LX/xRvv/c7u4Uo2Xnp0zk2XV/ZnTlgZ/EhHie0dO5SxfehdTZ1Y3XRcrJOkcSniS79tHzjPrgU8PbSSS4desWNvy2ngeHOvQdzgNyjLO7J2o3bmEQIOo66A2DrCd9HsmXETEXOPsuMKQh8M/ITDR/kPcRPvr/KU5Z6+ozfeu0GA+9hwkTEsPn1tL90/JXvl2v5eBbb72FN954gw8N69q1K+rWrYuNGzfyaf36JblhNYliYmL48ux2jRo1wp49e8RC1qziuf6bkRWo3rt3L95//300aNAA/v7+PIA0a9asPK+zLGvTqiXO7L4O+LXFHxk9sNBpGbLOfQt5+/mW3jRSzmjUwhEELVYrTEt7VIFlB+VXqoMfP7e1E8YT/z5CmF/Xzbj72t4aX2Gv3uz9ipaAVGjfyX4U2Ph4bdE9bXc0tt3aSP4RRVN+fuhONCpS0IiQcu/kyZP8u4N1PWGFT7Wnv//+GwkJCSUifbysYn9gXnt9HB4+CMHcNfsRdfwINCrhuX6jZRWwZFb9g/e5JYKxlyi7IVC+l2X/r8yNFiqqZRm95Np8Lcuel9wSVfKzLNte7du7qJZlP7O5/dTmZ1n2ftD+hSieZYUXVJkF+DraIyIxHZCyoSzCtfw1U5v/fjiibsaXsZJpny9hfRKprdF7lFXp0FbqYMvmVhayoMuybTETT8j3suz50n4+87tsSEgEVM5+/HnNiT23+p3gTS2T32UrJJzFJ4mTxGkHGysos1hGjJXJ74oCf+4lVjji8hZS1XZwkWZAlm4nrt/d3Ycvy4akJcbFQq1UQaOxQka6EopMtfjdp1FbIU0hh0IJ1LHVdf/KUlnB2VrOH6NCKRebw7DlGGsr4cE7OtgjLi4Jbm4eRtuakcH24w2zu1h8xfCxyfnzon0u9Z9fp6S7sE+4K26rvguZdTFcfRoBVWojLS0Nhw4ewYMHYVCpZSZfFyu9VajUUiiUUrOvH9sG7WeuXvMO4udIXJecBQTliIyIFj4P2W/GikG18OH3WzCqfTXxNs069OX38/BeMB4+DEHVqkGIfhoJtQqo82Axf27r+wAbhmev/PFmnK30CSC3Fb8j2LLa7z+NRi6+xuz5Zffj5OqKDc5C8yr23HaTncZWjSOQ/fgUSivdc2jh/YsCBY1Ya1l2pE2b5lWvXj2+M7Vv3z6evp3XoBEzZcoUfjLlyJEjRvPYMDN2RK+g6yzL2rRpgzcmTkXFSUL2xGlFfdQ99T8KGhGLZxr5+fuLl7XBlx2y/iZv64F4jLEXuq2pD38H6ctTjZbhf8yy0tHQT/8+c98m1mXHpc0wcfv06xSJBwZZumz2xSdq3ZEtidSKgkaEEP7dU6tWLX5iB9D0u7uybiiXL1+26PaVVSzDfc/uRgCC8M9aZ2x4uByJWWznHljxvQ2qVwdGZB9EYBYtMv/HNDAQGD1aN836K2Q35DTi58faLeumWUft7PigES8vQC/xHSz5PibG9LKursB77+mm16wBIsyMbmClL2bO1E1v3Mi6dZlelv0h/UjvYPfmzcD9XBokzdfbPdy2Dbh1y/yyc+bogkw7dwJXdKO/jcyYAThkJ2vs3QucP29+WfY8sOeDYdUlTgkdpk2aPBnQNrA6fpz9TzC/7PjxgHbXg/1t2L/f/LLs/cDeF8zFi8AuYXS6SexjXyO7WR8bhb99u/YaoWvUvetNUMumEVRJGWj8Ugr2RgotyrNiHZF2V1dbMSf76lHY4fISetY9h0YRY3Fij5AaolZ74MsvDZft2ZM1wBEuh4UBa9ea396uXVl5D+FyZCSwcqX5ZTt2FE4Me+/+9JP5Zdu0AV55RbjMjgtm9ykxqXlzoFcv4TL7rLHPpzmNGgH9s3cP2Wf4woWusHH3Q0KscUFw/6AstOqi+/D+s9Z80XCfSllo21237M4NzlApjf+E+8bbYmfGQKC+MHLDw8Eaty62RGKIF3KUzH2h7wilRoI1Z8ciJkWoW3M2ta3B68w+E04O9tCwOkZJCTh8OBDKrBnY/LMVnt12h5WjOy5bp0OSNAfnw9NQwXERkL1PvPHSCNx6WhXpa10QHKbrZrbjJiCXZeGjLsIdWctl2LAhC6x8D9svZnV/bG2FI7oZGVZ4FqPrYMacP2KPJyG6IIynzzLcvdoB0U+E573faN0B4p23e2P/6WQkxtQzeh6uyGRI672Rl1YRhnp3w8iRdxAXM9bka/hK1z6sDzO/fPB+ZxyM6IcHl02/1l0GJcPFXdipj45gH+o5sLV3REaaUDfo350N+DwrmRsSYmW8aPb7X/2M+zesceMcOyAtPF+sTN6j3Ta4f0WY98MP/2Dp0vfg6e2LkDvWuLzrTThlGHdwu3nXBa16qOAbIETowh7KcfGo8FmOf/aW+BrfuVOVr1eRqfuyYd8R7z3ag2cPdI8t8+lnSEzIrstc8TQsSVrQIz7aQrQHDhxA375CUS62ExXJvpGIRbC2gu52Mvhmp3CwdpHOVunQpOVe6IyQwsayibRH3Flwplr1mgbXMXES4yMbzBLrrzDFIbut5L39aPt4E9IeCnucbol6e79pukJ7zIks9ocidw51O+mCWlZWvKgg3ya9mkbaTCNfqS7VN8WvKQWNCCFmsU4rQ4YM4UPmSeELCAhAj8EjMODNqZCrUqA0UzSYEEupWKmyuH8hl0lRyc1eqIeTD1OTZ+I42iMrM5MfwKpYpSYk2YeyDh85Ui7/Y6mUSoMGSEWN1ZFpZX1NnGb7shroih8XluQkwwx5NzddIxctVtfoxO5t2Lftd0RHR8PNzR1JcbFi6kqWGgiVBCFLYwUfN2sMS1iIZalD+HXtAtWo+Gxvrtswrs4TqLMyxISQ7777zqCJVGxU7nV6Xuo1FG6e3maP3kqSw0zezk2axIeYsdIP2pEIYWGhZu+nWbscHcryWBte23GvVefeaN1ViFXExgj79tp9ei+/SmjWsad4G23trAmtgBrKi/BIFqLjjo6OBkPXnDJMb69Uk7f/Cuy/kLWNHd6c9QXcVLohqM+cDP/LsBpWWrHxug7RllCgX102FI21ue/Vqxf279+Pzz//nM+PiIiAh4fpP4KkeLB2hX7Kp4iEKx6pfJGqscWzfz5AwPBcDkMQUsi03QVYjQ92+c5t3eHL5xV1lOpVenulBmDj4oyMc5dhX7U5ZPrjD3L8OL2RuOC52yV3che3TyazwtXLF/kPx7Hbwo6YjX9tjMgO8L9muweL00byy/E+zQ2KeRNCCCk+rJ7Hm1M1iE5Ohnf8Ccw9oYSL+gEGVbfGnNE1xKEA+pku5uT876ef8fO8ZVmWQG5DT/Sx7IO8LsvKbua1SRbLqMrrssOG5T40TN/AgboMD1P0h+D07i1ku+Rl2W7dhGyXvCzbubMu0+V5y7ZvL2S7mKO/u9CqlZDtkpdlmzYVsl3ysmz9+kCdOsLlPfvW43H4SQTVegP9Rjfm86Qy4APvGliy/x7knilwcX9gtD4fZ1s8TcpghVr49JvRU/FFsy/Rq/NFHG/yF6a8/Tlmz34bn376Cl7p+gVmzJghDgtjAgKELDBz9Jf19c37siwrJq/LsuZSuS2r//lkmXN5XZa93t6+a9C87yhUr+v83M+RfqbL85bt/bpxWQOmbvg+HLrzFGcyh6FlkLDPWKPBCXRtWhNvvNG40L4jrBw98VarFdBoJNh4CWj2Rhsxc0u77IIvrXDh2D7hsfWLQ1LqDuzeOQ4B01l6WwJYhaMQeGEFvLDA5SrOptTH2az6uN+kP15rnLcgVx/3aagyehu+++4Qtm37BHPmCCVfunRhWUasdpyuyHXzjmloxkZ85VAxdg/cU6/jtuxdxKud0PjZH3CpkIwET2e4wPg939T2MNylj3Hn7GM0bMgeH3szCamA/Ubr7k/LJVp4rRQyJ3SufhCN6kdgT2OWfWRMf4hcrUaZaNnpKka8+xqsbT1ha3sfUcEsY+k6UlMAV09dMfpmgVcw2HYrLv23HS7ydHzRQ5eqeia0HVxde/OhbNXcVahSMw1DOps+QPRvk85IdxQCyExA1SxUDBLel1eOrcCcOcJIqG++3QuVYwzavFITj/8+j3hUwDtNr8C/QZDB+u6FqXDzsvAcVnEQalqVqqDR119/jQEDBmDRokUYNWoUGjYUirvt2LFDHLZGLON/X3+FpT8vBbrPhwLWWJvWB29HrMPy5a0xcOAAVNDm9RJShFhgKDY2FikpKajXpAVSEnTZbtraH+boH835dSgw55kLIBGOdsQ66H+ZFqANrUyI2POihtl7PH/8/js23hR2DBj77KB+f9vDYtAoL9tNCCGk6LADwKxGqq0kEVGSAEhkGrRvFGRQl0fL1Dxz8rOsftCiNCybo0lTiV9Wv05OaVs2PY1lAbCCNgrIrHSZKawDK8MnZYb7LR1xHR+MmYQ+P54wmD/CWxij1yRyCcJCbmPLlo183Wp1htH7lQVZ8voezs+ybHtLwrKRkWHwrODJP/vPk5dlnresiyoMyzLf4JdZxhgjlWTxbc7Lduf182nj4Aq5TDgYufo8cPC3jkbr1++w9eqrg3D0BAviZPHvvpweqoRue8J25/0gZ63kvwFr9j5mGTJZuHnzMm/ywN5rYmEdEwEZfZ0eTuDnKS61eMCISZQ4mdxO5resXvhc8jNeawz8eJLNYfetMvu6eKQKmV8KKxc4qpLhmXU3T681C9q+OW8JHj1LQ00HGzi7OuLwzUsmA5TtH06Fa9o9hEw3Xs/kvoGIYQXJLy7F/qEPcDf0M7EuVE52sjRkSg23gZ2YpMRoyOXCd0P4kzAE1KjFtyFd7sofvqM0zehxPcm0Fp/HRNZ1rrQNT+vYsSP/Q8hOq1evFuez4tgsA4lYDus4F/0kFE0DhDTHRWlCW8Ef5k/Eli1bLLx1pLxgGUHx8Qk80MJSPSV638xszLSVu+7HLbdMIy3n5vqHP/WrShaMtqYR0zD6R5PL2Ehy/FiqzBS9IIQQUrQyE+EWexw+8cew4bIum6B7o+d39yGkOGiHrjwNC8brrXXvSycb81GzXxdMh6Ot+eutlcJ7/VR2oSc2oqO8iYx4AvcK5mtBFTa53r7eiQfCUCZFZmahdk9jrORyvLzWA29uBk6EsICUcUTKSmbFh08xLNDg5mq+ZtNtpe6gakF2j7Xv38nZRZfMtZk3cUPxokOmrrN6Xvg4GU7PWrre5HJyZTI/t80SDkBLNUqDDpq52XbpMTacDcWV8AReVJzfb0VdJpAWCxiZ44Qk3s1OclYY0VAzcp35O8yls5u9gyP/D8Skp6fBwVko5nZfJWyPc6pxAbqENF319UOppju5FZcCfQLS09P5g9aOvwwNDcXSpUt5RxHKZLEsO9ZVSqNBLR/dOOrDmU1xdboMB3KrAkhIIfLyqsDbpLKgkY2tYWScDQdzaTnI7G1zpvpWwgOkP7wgTlv7VEVCAjui96JBI2FHrT7OoYos3GgZe4kwzlvLL3Jzge+PEFI23bt3z2JDV5ctW4bAwEBeuLRly5Y4d+5crsuzA0es9iRbvn79+tiVo9ov+15kjUx8fX35vkSXLl1wP7cqysWF7YSvqY0m54ag0803sD+1vniVnXXx1TohJC/UaqXBUPyctXDq+7tgQA1b1Lq5gmeSBHmar3skVwl/lh20VcXLIUcnF8PSBEVMKRFq9jJ2cuH7RaVIz3sQJY9Ya/kjN55hTS5F4tn7Qy63xq+//sqnJ4w3LEytjw1L07qorJ3rfT91aW04IytVvHjmtFBsOS+PV65MhH/cQXGaBXPyiq3eNSBvQRC5Sti+KL3tbnk/lzHIeu48FT5DFx7FwUcej9szgVdbGQ915Mtk1cbBTONxrN4Vg3jB7oxUYV25kcB80MjZ1S278LfQIZ4FDh/F6p77e5nGnd5fqZtdBJsFLy1cy69AQaN+/fph/XohGsj+FLKdlSVLlqB///74+eefC3sbST5VqVYdNvG61ho/pg2DlUSFoS67LbpdpPywtrGBna0dL5rv7O5pcB37g2VXtZnZ27KSg/omeWyBzc1tegtIeSBKlVtv1bzUXNI7ahSj1g1PYx5WGAKHHEEjl+SrBb4/QkjZVLt2bd45rbht3rwZ06ZNw7x583Dp0iVeJqBbt268WKopLFNh+PDhGDt2LO/wxvbX2IkVP9X63//+h++//55njJ89e5b/UWXrzMgw/C4sdhIpULUP0u0qIsKOdb4RfN7Bsqn6hJiSkd2KT2OmmFRtX2f42bM24s+vOWOniMErg0eiatWq+cv+KEMKuwD188QnCl3TmJGthQwQ1jTFx0f3570wyOVWfF+Z+euvv0wuw4Jlz6IixKLN2uFq3jJdoMGUwQlCe7pLWTXxZ3pXTE2aji9ShFpBuzLb4kqmYd0cKDMQn6PI8vPqj0rUWehz8WV0uD1WnFcnPJd2ezmoIUXtesad1UxRSYXnKdVG1zLZXmGilV0uIpMy8Hb1G6hVAfi21XXMXb7F5PM2NmkewlWGwRsN+w0C4CzU1c5VboWwdd3i2GFvCZxdPbDiuG7/4RmE/0vLPpmCyLBg/hqoU3XvR7WNcbH0Eh80Yjso7VkFOgBbt26Ft7c3zzZigSS2w0Es6+UOL+H8kd3oxD4ZPOJchxcmG95AgeCz/1h680g5wH7i2ZfdrVu3kJKcZPCjz3/8sr+ATbG21h3l0To+RXf7N6bMgourKzIz8/9HpqO1kLGUrpLgpLwJXNoKLbP72Bzj5xPstmJ7rb+gYOOLWRte39vibdX52VdLj0PCv5PwUj2hlSohpGyy1J+4b775BuPHj8eYMWNQp04dHuixt7c3KBmgj3XF6d69Oy+iywJdrIFJkyZN8OOPP4qPg2WMf/zxx/zAYIMGDfg+HRsOs13XU9xyOi7F0TYnMdd2OTSqLH4a2LEN3wFnp5zZXtr5pk7sYEZBl2XTxb2s9k9GQZZlz0thLav/Xi+qZdn+QWEtq/+ntziW1c5/dP+O8DopMsR573WuDo1GDVupGnW97fj+i/5t+XtarfuzmaKyhkIJJEnc4RsQJA5p0b72+t1c2X3ktr0FXZY914W1rP7nM7/LsudNmaUweWKd1Qzew2aWy7lsYnoW7kXEmVxuUNg70KiEZQPchVbpGekpPGBTqJ97jZoPe2NYEylTy8okrG+bBq6urnxa+/7v4/RI/B7UngbZHNCtWqXk758Bz77CjMTJ2J7WFitS+uBaRgAmxU/HxPDXdM+ZClCkp0DGu4ZJ4BJUFxkZmTh79ozB4+Lvd6VSfJ5sk+9Bmv6M34/2ZKU3tI+9n7XbttjuK6PtVWikaKk+iAXdhfb22vW7xp5C5bC1UCoyxftCdvZeutwLKrXu/vyfbIEkLcbg9dP/jmDBPu39sc9QkF2ceNvqtWsbfJYVKom4bLuY5QjNdMdrz+ZiesJkZKqAVgF6z4PeNlzxHoc/G50Up5V6n3vtNmi3TSqzQnJyMpKSknjjKral7P2tVbNqDb7cqf3/4nHwfRzftRVTerfQPW+2hgfhi1uB8pzS0tLg5CQMRNy3bx8GDhzIx3q2atWKB4+IZbVv1xaL+vbFb2/PxqE7wlHHSUmzscl1Dqqc6A+0LH9HKkjxYlk8rI39hAlCcTzm6dOn/EgN2yGQW1uLCZxe0jiDTB9vyVOj9VWRPREvs2Fl7EeBjQcWfs6f72OHX7EgdRyUGiHV+IfHlXhky7Xda8jU/IkH2QUEnaWpeKzyR3WJUImureQM1qJ2vv8cavaNh+uDbdj7ep5vQgghecL+UFy8eBGzZ88W57F9MDac7HT20IKc2HyWmaSPZRFpA0IhISH8O5qtQ8vFxYVnkrPbvvrqqybXy3bEtX9oGbYzXCTkdvh95ffYcTW7potGg0VfC62QmerVq2MEayuWjTVqyflnTosN6Rs9erQ4zYJlbL/WFD8/P16vU39IoLmmCF5eXng7ux4Is2LFCsTExJhclv0JfE+vbduaNWvM1qthwcCZM2eK0xs3bsSjR7ps8pxHsj/66CODjLTchhjOnz9fvLxt2zZ+oMecOXPmiHVXdu7ciStXdM9/Tiw4qR1StXfvXpw/b34MDnse2PPBHDx4UKzfY8rkyZPFMhjHjx/HkSNHzC7Lgqr+/v788pkzZ3i3Z3PY+4G9Lxj22co5dFPfa6+9hho1avDL169fFz9DMdlZfqrsgMOO9T+jzSv9ULFKDVRwtsXbjexw9uB/2LHuEGKePsbTB/fw5ZdCB6a+mkxckVZHOIQMh68ed4HVnV3ItHqGa0nH8fSmXDxoz27Ts2dPsfEQG+aydq35Dsldu3ZF27Zt+eXIyEisXLky15q17MQfT0wMfvrJfOZImzas25fQ7ou1TWefI3OaN2/OO24z7LPGPp/mNGrUiGdBMizLMTw0BP+sXWZyWf+g6mj4Ug8cvReNlkEeOPS76eUYn0qBaNt9AL/89Z47SDy1GfX9HHmlAwcbGeytrXA/OhmJcWmwcvGGY/0u4gHPa+dOYfNmN5Pvt4J+R1SvVh2H9u/j3+OHDh3C4cOHDZZlnwn2XldksOLn1vw74sEDoYvWiaNHkJjdCp6RyG3wV0tdJ7DUW0fwZRaQmPanwTrnW8uRpNwGlzbD8Ef9oxh+vQM2XwUuzf0UG66mwqWt8D3fe+wHwg2kMoTEpqKyhz2kEgnOH9mDJyHC90m1pxtw1TDujDmddZfTH5yDIjoY79hvwg1o4Gfli4jgO0j0FLKLknpYwVsai4+6AHdjgN8uAqcP/Av7fdsh0WgQXOEqUm2FSE3LBpk4paiPCddewpDH+6GOyM6QPTgdcQ518MRD13auy6A34JI9wuHOlXNIPK1LlnjHOhD+0hie5SM9MxQ1xqyGu7dQL+tIqDUSrwrPlzUUaCdph2SN8Fh/PRyPNZ10j+3iY2DXbUABGf6Wq+HnuhGX411ho0zAwxtb0ahvBfgGVOHLhj28g4tHhQ544Y+CeTOxNWvXQu3kDc0f65Dl1gzWXkJGmzJdIb7Xzx7ciZsXhO/CxNPZr2N/3fus1GQaVatWjX9JhoeH8x8D7ZcGS4t2djY9TpAUnz59+sCrgjeunjoEDwfhB/5MVgNkaITLmttCZXtCigr7A6MfaWcd1LQ/ohPfGm8wPv2c+0hMthO+EOMO/YpMGGcasd9tZ0mKcFkqha2DE6KePjU5zreD3U14SgzTbH2kQvG7E1nG7VKzNHKcyx4L/iDLHxkZabBTCDt/Eltd0UGl2nSKNAsm5dwh1jwWMpfs8tHJgxBC8oI1IWFH+VmWtz42zQI/prD5uS2vPc/POpmFCxfy4JL2VKmSULS1KEQk6rJLU+8YdpsipMTJ7TiTBnB0cBQnPRxt8MPwJuL0mox+YiFsFrjQHrRKt/RQUQsEyJ1dch+S8/l/t3DsfiwW7btrdhmWrZOepeJFhS+G6vYPrz1OwLUnCTgdLBRYDoszHTzOSEvlAZ/C5OXpwc9ZQMjcEDxWf067DKMtxi23ksFGlXv79VCV8XC6Qwpdh/PZh3T1eS7cuIHM7IOqfDpUGBLl0nooVh4PxvF7xsFvO4WwX61PpTF+HDJocP0py1JRQZOle/+ezdLVM2qkG3XGA0aMjVL3Okk0KoxO/BTJSjmWpQ81WL976q1cX/ecj/+3jF7YkNET9in34Zamu+1jla4mM+s+nqwxrCOWkKb7v/FE5YkotRt+ShuKyMR0/p76L60ZYtUuRiU29Dk4OfP/RhrXinCo2RY3ow0/z1KZ4Z+GpHjD59jSKR8FyjRihRJZpP39999Hp06d0Lp1azHriLXpI5Y3b+4nmDLlTXy+4xp+PRnG501JmoVfXT6HZNdrQO3hlt5EUoaxHzZt2i3j5uklBpGqqK8i0yoE15TCkTr2WznDYT1apO7Gy+djoBxY1WQ4W5bdjpMFjdw9vQ06FESrdTsVk9z2oVXWQVzNqo6RiZ/hN5dPEKHW/djfzS6Kp5Wl9zX4t6ILJqtUiHOshyrRWw3GJv+e0BwmOnHyceDsiJ9+JpI0w/jHlBBCyhp2lFw/g4llGhVF4GjFsYe479sFLtlNlDZ9PJLvf2rl7GzEMl3MyfkHTT/j53nLsiwBc1mnOZdl2Qd5XZYNM8xrNivLqMrrssOGDXtubRItNmpAm+FhLotJq3fv3jzbJS/Lsow2lu2Sl2U7d+4sZro8b1lWJoNlu5ij366cjYRg2S55WbZp06Y82yUvy7KC8mx4KLP1r7/4/oA2w63X62/BzkHXHsovsBr6jRayTG6eP4WEe2d49pYW7+i6SciqtnLzxZyqQKJdVURGdUGQo4b/x7p75w7fNraNWgEBAQbryUnbKZZhRe7zuiwLkuR1WRYwzm1Z/c8ny5zL67J8O3x8xectJ4lEih3/6soImFtuz82nOPgwDof26gJLzi0HGizTr189XPhHW+NNgjdrCgcqGTcPTz50tzC/I06f4r3mzT4XbNk9e/aI73v2HZGSksIzVdh3QPjJeMTbmu4q51CnIw6hA8z3WhNcyaqBYQ3v4buKE+CiFoJYWokn/+BBI2bvrSi0rOKBKs1fRrMOQqLIqyeNM8sy9IuIV2uBz+tfRex54EI4MPiNnjixexsCBv6PX/9OuhX6OvXhl1tlNzNr3aUP5ij/5pfPV+mAh75C9qjLreM8kMPYVm6IObr4Krepre51l1nJEZuSiY1nQ1HHJ1B8DDn1d7mEYJkEfxw6jSDfCvjH+Ue4tDb/XennwrK8zqNe7J/ItJcBjdUGzy/rc/gvgF86JCPWQ9c9MaBqLVQMqs4vp8RF8tdur4ved6dU9zmycvLk7+Ftq5YisGY9nN6/Q3j82Y/B0jXNChQ0Gjx4MNq1a8fTHFnxRf0v+wEDhNQ/YlnsS+vq9Ru4uWcjqlXtgQfRKTigaMmLe1WSRSHl3M9wbDHJ0ptJyiB2BPx89ljofv0HQOJWEfGRj8Tx76zF5r/ZASMt9jva0Vs4kuErM31UWwXhi5UfDWFH3vR2hG0kumEIWdlHSxrK7+OqpxAcjc7UDX87eP6SwXpTNbrKdq3k16BSNYZaInw1elnpWjtHKUwXXTXVOYkVzZNkB7XY9fo7mYQQ8iI8PT35H7aoKMNCoGzaXLFWNj+35bXnbB77Y6m/TG5/oG1sbPipqO2/FQVJ9lFYp6t/oPrET022qNbK7boXWVY/aFEals3Pb09JWJa9r/WDEaVpWXbOHqs2aCSVyoT9lOwgCAuGSKXZGf9Qw87O1ux7jwVDrK0AqY09MlJTMedLodU3w4Yo6W8fW29e38P5WZYFLSy9rFDOwAZWvN7O80WnquDnaryvdiokERK9P+d8O3JkdcRlqA3mtfZVQZtfE/8sNs/bnNfPJ6tLx/5D57Ze7ZBJtk52cnQUstPYuU/KeSTZ+UItNb4/SXZ34Of5MGUq9ri9jfa2N/BXZhcT69Gte9Heuzxba1rXGvC1zeDvz5y2pncQLz+q0I/v20t2g9ch1Wb96K+THdxl++qy7Djh2UP/wTr7WAB7vNrXXabXkYy9jjnvu23IHES4v4xwT2EI5Df77/HzqKRMo9dZSy2zxrprmbib5YXriWnZ7w/zn/sJKfNwz7Y/D14JZVlNLyuXSQ0Cn1KZjJ+YuJhoPqRVIgsy7pJmfRrvDfgCG88IZX7++FEYuqr/nFk606hAw9O0Oxgsq4iNwX78+DGfx462s3aupGT4eM5sHN6+EaPb6CKeHyQLR9Qcj08G4ktAK11S5rDaAVoOjg4IqlWf7zxpj3YqzQTy07LHRuv/OOhL0jiKmUbsC1m/eJy+GtbGHRWS9NJMd9zSBYKYDI3uD898x1940Tp1dk0jW+hSR9PUpv8YPXmiq7ck0jsawOpEEEJIYWF/MlimAav/osW+X9m0NvM7JzZff3mG1XjRLh8UFMT36/SXYVlDrIuauXUWp/r+rryuxrh2QXh66SAqVhTq0BFSUrAcEv1gzh8/LMCPn0wxuWxmRjrkVrkHF1hJCZXUFkq9gtOmMnHKMhaAyxmEUak1ULJKxLxBieHf6A1nQ5GlUmPO39f5KSUz7y3gE9N0Bx+DPftAbaUbPujmbpiFUxhYltrzOm+yAwSM9jlg5yzbhAXqZZmJqHZv0wttQ7hKyMK3leQoTgSgcTPdUDaGBYyYq+EJkCt1WVj6bimFOj6MNqmKdYZ7pVt3XDyyB37+ht/bhxVCJ2Xty5iRpOsU5pZ6W7ziWmzuQdyq0VvQ/s5k5Ees2g13s/L3O7Ixvcdzl7HJEGIiplw4cRjvvPOOyet+cf7iudlEOd/vxa1A3zxs5+Szzz7j6YiVK1fmJ1awi3XjyGsaLCl6LGU1KuIxDvy1Hu2qCV88rHaL+J5bbZjtQUhh0P/C+33DBv7LoV/jKPu3XvSpUB8Ov18GOlQFHKSmx2nXtRIKAGog5Ufh9DONNHrjqK2kxl+q9aweipc7ehnWO+oSv1y8fC8yg3dv0GQHjSrH67pRhCs9sWbNWty5I3RGEW9zTziioU9/TDNrc00IIYWJDQljBW3XrVuH27dvY9KkSUhNTeVDGJiRI0caFMqeOnUqH+qwZMkS/h3GCiBfuHABU6ZMEY/+s2FaCxYswI4dO/jRULYOVuQ1tyFLxWVunzqY27sOgjwdoMjMKJbsJkLyS1vQm7VSD3twBzfOma69lZGSBJnUuP6Lp61uv2Zm8ruokHQePV4dZ7CMqfo3rOi3/gG7siI9PR0qvZ3GNIUSn/xzA3N33MThu9H4eLt2OJkgIS0L83bcFKe3X36CiITca/9orTmlKy4vlWgQ7yAMO2Rk2lSYQsReRxasz422jpKpQGHSs2ho1EoMqaMLbuXXRPu/eXa+q9SwbAMTm2ocSGIcNEmoEWm68HpLueHrcfCxB8+WGj5sKJxcXHnwze/2ZvH6pWnC8DOfgCoY2wJ4t4GumVb1pxtQIeksv/xmkq5gvxb7q3E4symGJ3yBwJid/CRLNz5obM4BvfpOefVpqq65jzlqRarZ69y8DGsG6rvlJAxZS0/TBeSq1aor/qYzFo4ZFSxoxDozsDatX331FS5fvsxPrJr/Dz/8gE8++aTwt5IU2O7du7F52Vdo5Kn7kdmraG1Q3I2QwsKO/rI6AzmxII+pTKNOkqNIzz644+UAHMllxKQcSt3QL4kEar16QwkapxzH+wzZ6B1FSVDphqPl5Ocs4Z1PpBqFwX0y11AXb745Bn/+adiNQpsuzJoCxMUJR0nSsjs+MK1KwFF6QkjRmDVrFm+XXNxYrZrFixfzGpNs+BjrZMWCQtpC1qyjEishoMVqv/z++++8oxcbErF161be0KRePaGTDcM6dLGjoKwWD6v/wupnsHVqi7GWBKlJifDL7ohFSEmjDWY6O7vwDGul0nQHPxYEMFVYef8Q3f7LjsyOUEPGG4f0eWOiwW1z+vXXX3HsmNCA43lYy29znQVLGlaE395JqBxz4kEsFvx322DI6vPcikzCnacF6+iozh5KyLLPLZXdpR3aWaWKLoNHG5xk7zW2v1rN4/kB9ArWuhqj+pakjkD12H+wLG2Y0XUquWEhaK0mT75DnScrTF53SakbbVTza2DaYT/eaZDVsUqMi0VaWio0St229LAW6jo5WSnw61Dg9SqGmVdB0X+ZvB+1RoKg2J0Yk/QpTmfpyuTM2iM0sckL9vkqCrZxV81mDPUf8y5c25tuq5yeKAyGPLVH6MbIOLsIr3NJCRoVqNAGO7LFvqD69u0rzmvQoAFvbcnaYX7xhZBiRSyve/fuaN26FTZ8PQPoILRsnZj0EUI8ewt1ZGo74vQjtdnK/YTkh8mhWnxImUQMGnn4VtYV/7T6E/9kB5G89eM+JlzJ/jE6HGUN1BgBRZbux+GYQleAn7XSzMlfqlv27wdWpuJKXGPnaGxKTkJ6JaGLgqmPRc4fAu00+6yxI//jxo1DhkIJ++zrcysWSggp3Vj3MEthWULaTKGcTLWGHjJkCD+Zw/YDWBY5O5VEWQogPCQEfn6BUOQ4CM7+0+mXzsl5vT72va4/4iU/y7L/2uZ23ItqWUa/7El+lmUl93IbAJCfZdn2an8Ti2pZNhIrx2isAi/L3g/a//rFsaxazd6A7AmVw8PTDxKJNVR6R8nYc6DOXjZLoeHL67/32Mg2Nw8W9I0WXl+1BFlZUqgUKljbsWYfwhtGpZLx+5RI1Dyw6+jIulbLIZHYmHwvs/VqR82xbfD3D0JychIyMxW5Lsu2IbfYUn6W1f985mfZhw+D4ejqAxZ7++8Kq3eZY6eM1czRyy7XqIx32qLiFcJ8CeDhJEdcdgaNqWW1slS6LxMWmJFJ7cx+TxT1dwT7T80OBugvy9477H2gzFKhiY8TNKo4SGQaWCMLCsiNHls3PxnWP9TNY8tqaVhnYBPbYGfjiCyVxGhZK6UKCqXpoZV7M3QHSR+nuQEPnkAud4BUaovkxFQEBdWClYMbItj2STXwlQmBEqkyCwqV8TozVDb8tWePW/u5Z5UpnmW5mH39LjzSjSbgVSxMdHQTSTUG6825rJudDPHpqjwtqxWl9MLD6FSsOhmMNlU90LOun/j9V71+Kzim1zDcdqkG/7lNxcXLbESEBGsWfar3WZdiyJAR+HfbE8jsnNC6avEfoHrhoBE7mm6qdhGbpz3STkqOFb/8gh59B2BwE39svST8qd+Y0QOv2+3GmXeBI0eP5tqtgpAXoVQoINXLNIrL1I1N3nsxRhyu1lCv5WZefHTZFftsgJ/TBuHrVF36pqlIj5VEDUdJGlI09qgvf4gLSl2rT30yiRpqtQqa7C9sU9jR/Xnz5pkMImVmd4xjY+q1+zbaAuCEEEIK7vcVDrh90xvSjCn4UlcjlKtenXUV000vWmT+jymrLTt6tG566VIgzXSnbfj5sS5ouully4CEBNPLssSRt/WaN61YAcQYd6rm2Cgm/aZta9YAERGml7W3Z1lguumNG4FHupE0BtifzI8+0k1v3gzcz6V85Xy9UR+s/N4t892rwZo8aYNMO3cCV66YX5Y1r3PITlTYuxc4f978sux5yB7VBVZS69Qp88tOngxUyO6Mffw4C46aX3b8eBYgES6zkVv795tflr0fsmsO4+JFYNcu88u+9hpQI7u6w/XrwPbsxIDo6HG8RTwQh4QEf95+XKXSvVkiHslx9qBwOCnkTms8cbJGql6yPxsF2qg+Kzq/D8p4B6Te8sMA+UbY33dGyP3e2QEp4MCBFmjXDggN/YsPS7tyhd3HHBw/3h5Ll/6K8eMNh7OxxnVt2wqXWfJhcrIQaM75GWLYXwHt3wH23v3pJ/PPA2tc94rQSAuJicLnyBzWuK6XUKOYf9bY59McVndfOyKWBUeehL6Kf9a6IPFONaNl5R4pcKity6hMPG28zE0HaySmesHKLRVNuqeJQaOks1WFgIkJP1WfC6/sms6sZEF8wiiTz1dxfEdou6vpf0c8feqLkHsDEPrgNtbV8MboCjVw+smHUN7eh+Hd6mL2qdlQJuoKgp8JsULiUyFzngXZXNoI5R6Y1Nu+/P2Wk33MCKSdrgbXdrovkLS7PtiRPBQPrAw7ET5zbACPlGuo1fwRIljr+pCTUGt6wlreHAsXShAWFoSrZ9qieo1aSLiRDEVENTi3CIYNhC/pU7eb4ny4cXdDtt4Id2dUdYlAsFz4k5AR6om5lz5FYobxa81syQiFLPvhZD52R0aY+UCLY8MwWDkJ++2ZEW7IeOSJJlZ3eMZUHV9neDtZo+ajf/kIHcf6j2HlIgx1VDx1QXpw9hdRDm+cnonAlrE87nPq4TPUs62Mi0e1h5GbIvmOYYacfc1IVPMKw7+83GptdniHzw+oWhNPn6Ri796msD4YhYjkZMz7XDdk0hIKlG/HUpvZ8LSc2DyWcURKlqpVq/LW4e6ZkajgJKS5fZzCWkIK14953fyRR0IKqvfrQjq1k5s7L17NgkYNGjREVJQu62fnA2eost+HdjniNLt0Wcgm3UsSdqAMAka5GGEr7AWaCxhpqZVKg5pEdnrFsBl2ZM9geb1DqGz8fc5AEtV5I4SQwqHISIOry/MaSRNS/Fg2iI+Pr65LWS7DOtP/z95ZgEtRvWH83bzdQcO91KUb6ZAUJETAolXAQEoxQEkJFUQBlT8ggoSESoMg0t3deYkL3O7Y+j/fmZ2dmY0b5AXO73n22dmZ2dnZmnPOd97v/VKTnSv87So97WGpNxYUKxWBll16KwfUsbFIpGiNFXrN27dvKvoflF5KhvZPK9R/os9JNGG+H8QgEaHV5JxV0UK/Hya1OMgHkuJjFR6a+QH6TMTvmSYmvdx1+HfW99i68xSS3ZSijmIBnsi09k3zQlqROi4rGd8zBzBVv0nthjNF30ecd2W2rbA6ht1nZpmQkZYCT08hcOXrS2o4wSi+66uvQJ0mCExyyrbKUrkhMS0LmRZlhblrpjzOMufATN/x+MBjGd5y34DG+iNI3rcMhfw8hAqIJayRURnB3m7QZpOyqJX9t7NcVf+RQcEzZ9Xo6Dum71pjNiDz1jn4uOe+cuajQGXJzqbbBdu3b8fLL7/MjJbFqhp79+7FjRs3sH79eqeeJk8TdIElk2+6GIs/9KedL78aiRtpGvjX7oBVx4RQdV+PvzHCey7GbdHhkz8T4eHhvKQ4h5Nb5J2gMXNWYtS7r2DkzD9xcPMKjBj8Pho2bIjPBnXCEvd32D5T6hixZfIr+OlVx2OFTwBOjioIbwNJksFM7uy5GNyR5WPL2RXxA4rGCQbWg1YCP74CxOlK4svIllivbZ/t+V8LaQfVJ8BLdcKwoaswlft7+ssYmfI+XlTtwrxJk9g6+WWTfEE6depke0zb0id7wEMlBJu+SvgK48blz3QPDudZ4Flss59WHuV38c/xu5g24Sv07PQSXn1V2Wjw9DTn+/L0tMe3L00aUftP/4FXX3sDep8g7N28Aov2XVOkp5FB9ld92mH69BnMP8w+3atQz6nQFyrL0tOIn1/MRKxvTbbcq1FpzJjxE957ry/mzp3Nnm8yWaDR6DFv3nz07t0LqalpNi8cNzc9tm3bgiZNGtrOgfalI2c8Belp8+b9jrV7z8G/Tmf8e9aJh1Eu0tNEGpUJwrFbCbaKajpo4OWmRbxYutfKxeBXcNn3RRytMZs9Pn1oNyL3b8Gvc4TH+eEacebMGQwY9iV2b16Lq1evsYIFbm7Cex/67RykhFTDzfgMvFylELzdtDiy8z+MV32ACrF/5To9zXYeGgs6u23GX5ktFPsO8liMTkWjsbPCbPinnEaDo2+gRsJidt4JuxYjcfdSdH3tLSxc8DsLbFEAqVPnrvjfLz+j3odTYQivzfZdH/ARyqoiYbY4BmEqx/2FDLPGITWsTKAeF2Nd/IhySCPr5H8KKxKsXn5qC7YF9kO49jZMZjVM9Fr0v/kcmL9TUmOV39YWXZK/sR23dYWCqFksEF+vFYy/iyMGN9QFnJ5DYV8P9G9UCnN3X8O1WEla6OehQyKZuqotuB7aDt9vBz5eQ0+SGrKAoFCcP3saPd9+F/+sXQWL1W/1SbXZ96U0atKkCasYRAOlhIQEdqMG/PTp01iwYMH9njfnEdK2zUtYPW866oRLMr3fM9rDZFHj08ZGZlJWo4bQKHE4D8pr7w9DyQqCOR2ZOMrT0054S6mQHu56BDv32kOGAUh0pfG1Eq8wwBY4UeITpOlDMeloKUzfDTT9BQjodwTnM7M3T/VRCQoiLy8vbNh3FbMOuinMsI0q59m88gBS8+Yt2H2KWZql4kojDufZhibKfv/9d1t6KufRoNMDt66cRKlSxViwQ36TB4wI++3ym10F7zztS48f977ywE5e96XP5WHtKxfGPKp9KQjxsPaVCwEex75+fh7w9/dE8eIFodGYoGIFOCzKYIgO+KpPawoBsEG+/LhiACbQz5u9TxqsM5+aW+vZ89xVKRgytD88PDTWgI3GdlxfdwOio6nUtwFarVn2/Rqg10uWALTvnz0NuDzcAFNGtMN7E8+BoHPI7nPIy77y/2de9rVYzNBpLdh84Y7t81Dc7KrlOt3HevN017DqiyIjO5bHJ23K4KUqBWz7TC28AHqtAbeuSlVy01NTEBrqn6+uESxApMpC6bKlEBZWmK2b8v33aNykKfvMmpQPQbf6xeDvrWW/HZMpDV66DKwLGogPih7GSxULSp8ZBTis77+f918OnxvRUH/MYd+ZWZ1xt2BLdnydzoyaiULAiPCrT8baJnh6aNi50W+Wfos+3jp4emphKlDKtm/b+OnQakxIV+vZZ5+g9kKWWguDRoNMKnxDryf736vUQKZKozhHrcYoPbbbl9Z97feTbXu30IMYW2yDbV8KGBEatZm9Pt3oXDf88Qt7b3QrWihQcVxvdw28PTW4Oa0rbkx9BSUMl1DxyOdOz+F2UjouxSbjekKK4py71SuG/mVu4u+AT9h+QjFF+rwN+Pjjgew+PvYW3N3V7HpCj580920HT1FNMuf666+/2I3KtMbHx+PXX399uGfIeShQ5RSaeUhNTsSg5mXYukyLDrsM1eCmtaBGEeDo0SO47SqpnsPJAyTpFKtNUNBIboR93STIt4miRYrgDUrhdwIpitPSpNSw3h6rHfbZkulYMjPBqzxWvnAQXyy6zGZltl8GVO5+uOxVI9tzNlsvh2JHrNGoo+j4G6BTGWzvg6D/kdynSHxfOp0O//23mQWRsixSa889jTicZxuqqHjz5k2mpBw6dCibVOM8IixmlC7t3MuCw8kvCBNllmwnjsS+hj1VZdWOid2xwey+xcmu+LbgTxjzyTuYNm0aTp06hZfJAmWKColfAw1S5jrtc9i/TucqQHggcGDZeId0+/wGfXbqXJS7/7JteUzoJKRIucJdp0GZUKk8vUatglqlYkockVdMQjn49HSp75mSEAs3/ZNNC7KH+tdU1U3O0CFDULlKVcRHOyqykhOEtLFKustoVNIHDUoHo1k5R08eyj5xRgc3x8p8WdAjSyukCqe5KSdljfHCWLJr1y6K9SHBIawPbfEKVKyfmvoWqsYuZRkFL8QuRKXY5diS6ehxJP4zMgzK/1SQOgGF1NGuxS76w7bljMBaaOp3FfsDe+JcsJQlYM+Sn4XMAmJ7uNKEKzlDmEwODQlibVL07RvQJ0W6PNaCfdcd1rnp1Bie3B81dUKAMikTeOONN2wxFvl3nV+KVT2ZGoKcJwKpIE4d3IUCvu6oQy0GSV0TxyLLosWqcS3Rvtu7mDdv3pM+Tc5TjJ9/gENJWI1GKzRw1o5TqkVS4QQGBmKwMrvMRpYJkKcCf+ipLHVPXDRJpe1zolzqfsXjPh7KF94a2E/RwSpfvjzadX4TOggN87asWuw+rHQEK1lrrzQi3yZRok5ycZHevkuffJ1MDofzyChUqBC++OIL5h9SoUIFpsJu1qzZkz6tZ5Lrly/CxyeHUpscTn7wnLH2eXZvlEpo5yZoVNFT6UFkykiAf+pZBKaegVZtQbPSwKBBgzB16lSsFTL9GfV8zjkNGinKxcv6Ikvm/oiPP/4Y+Rl6LyqVGrVKCH1LZ2wJ6AdPWeCHkCtpRNy0avjamWfqjIlo4XEMwap4VNWeh1olfD6378bi28E9bN9lCDlY5yPot2OxBiXlLF+6BPMmf+W4vwoYefU19FhMNgydWMCsRXlZOhWZsweT2TqwyG+Ek+ebUb2Y1a1eRqZWWJepUwaBDk3uxfrGZGUjR6/XswnWlJP/Kdb/mPaWw7E/Sv7MYV14iKAUi05Rqnqn+EzFcn+hWkAhP8FL7FW3Lfg34H12K665i7Hev2Cyz/dYOPlzFEjYiwKaOLhbJ4WzY9nPk/Bm87pw3yxVSs2wemx5+/jgpZc7wGzMgrdZ8hfLDV2OCCmjIvt0L7N+hOhFLMKDRpwnQru2bbBxya8sOl0rTPqDd034BkXj/kXzzr0xYcJErozg3DfuVuNHChSJqLUauHl6o0fP3k733+RiUp6uyfI2LUStTFUL90jDr+nWEhu5oEzWScVjqpAgJ9R6/I5i2Q4AZ2+mQmMNGpXU3MKCPVfh6+evSEMRg0YeHkIwbOjHH+PePcnsu5zbVSCBSmlyOJxnEfIBqFOnDj766CMcOHAAbdq04RVJHwGnjhyAm5ubza+Fw8mv0CQSpQkRM8cMUag/PL28sw0auWtUCMgUvByJu+YgFEiQSsppcxi52SubFK9jlgbJZO1DXrT5Fcpi6d+/H/ssjbIAybuNwjHYmjFBaFXSmKV1xYIoHeLttDS5qDRqXj4UPeqWYOu67quCNhd6Y09QH6z0lwJouy6bcHzfDmaCbTRQip9dLucThgIJ+7ZtxKULyn6sq2sjBZiCyzbAwayqihzPEW3LY4jnQhwJeoutTkwHfGKOK577pvsGdh8W5OglYbHaNtjbI7syf/bz82XnHr/1/rKSYlOUnj4BuiwcCH0XjfTHUFQTjT/rHMLHjUKYP+n3vt+jjPYGuxE9Pdahi/sW3E0G3I2uK70nmH2ZZ5TezR3Xzp/Cqt9/YevPH95t26dpRKji/2XIykRUEljgMbe4s/RViVSD2vZflU+MKIK+T5j8cyacR063bm/h/InD2Lh8Hor4S6bXx40R7L5t2s+oVLs+Nm/ejIwMZcUozvNJamqqQ2OQHbaS8zJnUS9vP3R89xN0fv9zh/1pAOAKJ5MoClIMjjt84eUore3YsSO711qUwVBPq1G1PB3uWFBf/DZXOsbCZatRUBPLlk1Qs4u3Tq9XBI3EDlp6mmBwt3/ffkdPQWvnkcPhPHssWrQIRYoUYbOBPXr0wOTJkzFy5MgnfVrPFHFxcfjm0/fw9dfjnvSpcDg5QgNwecWtAe2FVPrkxHikpaZkm7ZWtkxpBFz51/Z4U1Y9nIyXghZhrkU3DHHiV+y7yQedO1bOsi1b/aDzLYcPCylFpDQSzatJQVQy2Bv+ntLn4a6S+mNNyobg7Ybh0GnUeL+JpNYgaB1do5uXK4DyhZSGv3qVUeFDc1no9uH9NjVgNObPoJEzQgoIwYyEWGnikn5naxbPZv1tI7nSyyAj8LeD9iJQLajb6s0AKigFSJjo8xO719tFK1Uww6QWPpeTt5Qqm+KBUkaBYn1xITvAnJ73in6veOwUjKNlZKo8sLn+PlwL7iCck8UCjTl7b0Gt81gtI9oYgL91Q1imQYGChTCil1IpVfXuRoztUJEFIK9dOI3LF4QgUUZ6GihjbqbvhFy/H3dI46QP/wZ2/7fBFjQib1URWqeyJeY9RUEjMrvO7jZkyJBHd6acB4YulpR+duPiGfZ4WCshWETsyaqCsOhVKF6mPF566SXUqu2YS8p5/vD29sbWrVtzte+mTZuQEC9E7739JBmrmi54KhW05GJqBxmw3y8p1pxiORrfYg7rqLoZQeU/5VAQqIxGyjP2Hg7cK6zMvx4ybDi0VqWR0SJczOm9yMvcih2zLGugLMvgWN1AnHHkcDjPHu3bt8eKFSuYz+OGDRvQvHlz/PKLMDvJeTiQZ2aL5s3R9913n/SpcDi5GtRfOadUNxP7/l2jSGt1RpUqVbB1teCtIzL6YjVbZpmd2MJl0Eic3BIHonv27MEXn3ykmJjLL2kvzhDVFmq1Cleihf6bp9XUmwIYH/muxCeev9tU4vYUC/TE0BZlbY/F5xJlb/+GuheGunxteUAt5s6tfBc0cqVS+3PZMnj5+ODDl6UxXELMPcTcuc2CRia7oBFhlhV5CSzTSDFhW18nqY58PJQqJgvU7EZcj02zrb8x7S2Xv6ugIEkB5rXne+SFiQG/opQ1PU0kjXwsKBWUHK9ZIMsEtcV50Oj3Q0CcuiA2ngdOeSuDQaJtxjfRb0DtH8aWaYLYntXzyLRbeK0RPduy+3WrV+DAtk0wmoCCamu0MRfIg533UsC+GzEYWLBgQYV6LL/8T/MUNKKSbNndSpQogZ49ez66s+U8MF27dsWh7f+wH2eAlx7lCgoX5bcSJ0BrTEXZCOECe+sWN8R+3rF5EKVKJSKzY9euXbbl29eldCwxVU00kvZRCcd722Mla/jut7qYWe1oTHg8tJfL/a8nKC93epUBQ7wWZ9sQN2vVTgoaqYTXCwnwxu2b1x2CRiTeW9IdqF8w3kElZciuviyHw3mqoYkWqqBGk2fr1q1j6anTp09/0qf1TEEeD1ShjsN5GkhNTkbsPSnFzNkEkiuldWioo0ExER6zFp8mD8QXzcifx/Vri32qtDRhIC8ORKfPmKFIbcspze1Jcz0y0lZYRexT+bhLb/x9n7UY4OXodSlHHigiTyORWldGo+Q9ofy8MzJlwvRrZ44pPGbyA66URlQkILSAMhj5UYc6Uuqak8wBlew3ueSPxdBrgQV+X7LiM7/5jZL2c6J2ydALJu1ZJukY+mzKwsvT51JSc19t9FBQN3YG7atKBtFKhM8jIOUUNGbh9ePTgGk7pT16LQEmmseD7JC+/3Wd4tmD736M0NHAlCm/2MYBqSmSd6mc7av/wNmjSo9UgjLyKLYzM3hart6TViV9ZmI2n/i9UjylcxdpEju/BI3ylBj+22+/Pboz4TwWSNlRtXpNXDp1FBHVaqN8QV+cuyP8MZrHz8T3Vc5BP2cl/pg2BjNnzmQzFv379+ceAs8honImt2ogeSMmVxWJwSIKnIS8MhzJFi9FehhdDA2eRaFLo3Kxucegduxw3YhLQ72SQUwqas/ZGGVAqInuCKuYNsBzCaprz6OFk6ARvY9pF6oAoYDBooHeEI8l9Tcg5eJZoE07RdBodCvg9Wp0uw37QgkGA9WZ4HA4zyI//fSTbfKMTD45HM7zTfkKFXDk0AGH9fJ0f1fqFbEfMst7NPqljFZsW5bRCt/6TMPUDsBAJ/7a1YtISqOEBEGBQ5UdyaB/186diPDIXZpOfuB/M2eye/KLgWCXCZ0i0pXzhKOHXsO8eMi4WJ7SlhMUcBC5evEcauez7IvsfG4SE+Jty/I0NXrOtcsXcOPyeRQrFaFIMxMpWrQo4jRFmUcQ3eS46xxf02Tt2ZJX1OHrwuuS0tYV8rFkgq4gcsi0tBGsTmQV5wPsvkNR+OCZKQgdMnTBCEg9bbOc+GID0KB2ecxae1Z4r9bPbeERYO7r0nFiYhNgFbPZgq5Vq1XHpihJQFE2IgIXzp/HnEnDUa6aY+Vmqzc2aupy9jWa5TvO6XPDwsJs5uFeVu+z/BQ0yudxZs6joGH9ehj7XhdkZWSgpiw5+oqpKHbfMqN0peroNmgU/li1AQMGDMCJEyee6PlyngyitPnTzxwrGDhDflHTanUKpVF6lgmx8IZnRH3b+mCr4ojQdduN0ZuUx2vU5EWH1/jL/xOU01xly2Y49niqFBHKf8bddaKUs5tg2R8pVIT4xGshmrsdZOvKlSvn0MBlWL2T4s3eKBL5O3RqM0INF/HBhx8qGpgC0vUdVo9FG1xpxOE8u9AsdHBwMK5du4YmTZo86dPhcDhPGFcqIjFmtHTpMuabkl3Q6M+1h5xuN1tUeL8+YC0SpWDe67B5kooqcbGPQsEjnazbRFXYbt26hfyIXIF+ZI9kkRDqY33TFjM8s6SAiDMKxW+Hf9pF9G0UjgHNSrOKYbnldpKgICUCAoOy9d98EoiTuc6CR3ExQun5nev/wr7N6xx+VzO+FPquIio7v88zQc4V+4FejkG3FacFq4YjkVKgavny5S7HCNROihjiXP/23GS/0xd0Upqn1u47rFFcGMPe8xOCOBpLls3TqKg/pa8B39/thFn7hHQzs1WyJgZpROQFoDp37iy8lnUCqJk1CBZeUlCbFSxaHGeO7GPLVDH1u+++Y8vtOr7K7kOM1/F7hc1svGLPnJonmUl3KzelUul8tDTmWLt2LVtOkAX/eNCI88SYMP5rFC1WHH2aRmDvxpUY17GSbdt391qxmZCSFauj/+jpeK3fUPz5l2sJJ+fZRexwHLGaEYrGhKICyR75RU2M5hNHbyVj3Loz2BGnLJN8xyzzH/Itjt8vllRs37l9K1bYWQLU1J3DGG9h9skZbjoNjIYsDHvDcaZDHa+U/7SeDcyxU5jK84gJIX3OaioJNd480QxlYlaxxzN/+VlYb+0FyuXM9hgz011v5HA4zwR0bZSn6XI4nOcT1+p8ob/w2mtdmTLRGWIg4Nht4HiQTA5hJdUiBE6alnZ8bpXC0gA4PV3od5D5sbhOLhbpURPINOQPN+xRo0YjJibG9njSt8JAnIjoLFU1KxPzN7tvfVwwPnZF4bj/8OLpnnjxdA/WN1Xfx6B77ty5qFqjFqs4nd8Qg0bZeY4e27MVJqPBIWiUnKj0gJIrjYisIs2cHo+MxO3Zc03IVLlwV/IM9fCQydnsJk9J8SaSfslRiSeqh6Y212Kc98+opruEyeHbpHO1+x7N1v632WrIrTGlQ22tECiOH9JSklGxUmUUDyupMKeXYyQ1G6X3lY1gXq7y/2GLlq3YfZLVy7REKcknq3Xr1rbPlapEixRR32bjleZ65XssmeE8EHwpBrbgk8jlS5el7AceNOI8KehHOH+ekGr48+jBOLV/O0bUlbaPWHnKtly7eTvMmzc/TxW0OM8Gotlz+fLSRb5WrVpo1Uq4gNrjLBLe/YspWHXCMa9feIJSKUSzADF29kkjNzo+zUNmHmePMSvDpUeS/WxKq/avYbWgYs2246c2Or7eqowm8LSKqXLz38hKyL9lbTkcDofD4Tw8nPWHsjIzsGDqmFw/Ny4N8FO79pS08wSWXsc6sZd5+yj61wPMhnRbQMY+Q8vf33ng6nEzduwYREVF2R7HxsahTjPBaPhIvKRcb3jlc3hm3EJQiqPJuBy/tAvs3jPrjsLHJyj5GEISBWV5TpBp8/Ejh3An6la+DUq6MsQW+6YZ1qq+2e0b51VZuLem5LlKsb6fwJsc+euXjSjntKqwt5sG3eqUgAUa9PBYjz8Dv0CWXlATHS/hqNwpEST8CUwq4YddIHEv1FZPJdHMPDEuBuUrVGSfh6uiNDvWCeqowEDJqHvtSiFAefv2LYVHmD3k5bx9+3YkQ/ov6YxCEM1XpSzAk6WVigSJnIvVO71m0GPRS4srjThPlGbNmrHB9caNG7F1xQJ4FRIuGiLDV5xkf7DCJUrB08cfJ09mf4HmPJtKIw8vb7Rr316xni6OIiSDbtGypUN+vhhI8SrfJNdG1tSgUPUBOZ9/MtjheSFqSbIpUqmIHzKjLuD6/o25Mtb+8uXyWLxoISjNecp2YMDGEJcNc0rUJYf1g5KHwceqVqbXa96pGzPXc8WVC1IglsPhPJ289957mD17Ng4dOuRSccnhcDhioOLFF6U0+6T43FdWkg96m+iU6oRbZsEo21l6GiFemxpdfg8zOwNetzdi8R9/sHUl7ExkqhTIPyoaeR/y1u3baPDSqw5Vd6kwiVdmzkEco0aKqOlMQnl3jSkDrY93RMuTyiq5zqA+bH6rmCZHDCI4O0eq4Dnpm29RrlptWMySkkxUziTGRWO6LEXtaPhwrD+nRpffpaCRyaIMUqTDtbdpqrzUXC4RA1PecdLM7Ur/ofjipQiWRihWQ9Oa023pZmZrMZoOVQujchE/fNyyLPw8xHGEcL7emTeZyTlh0UifjZhq5kw1tuUSGdcLvxFnle3FzzozM0MxvnnnnXdswcXGjRtj936p0lxQ8lF2vyJTUm29Wr0IMnRSUErk4B1Pl+pE8bV50IjzxKEfYdOmTXH++CEYjQZcDO6o2H5+20wWCW7Urium/vDjEztPzpOBKgDRhVYehPm8GbCeKh6bhE5JSkoK/tu8mS3Lc5XFDlMcJRS7IMWilLBqNGpbBQERTw/HBlE00Jbz1gvFcef3ofjtmy8w5eM+tvUlrTnIIjd/7oPolRPxdoNw1mhdvnwFn6wBThsrIzbWsUNHjYFe74Yi6rsO29x8/W0NiE6nx5vVXb5VlEvgKZ4cztMOTZ4MHToUL7zwAisHXb16ddZx/Pnnn7Fv375cV5rkcDjPNqR6JuhaQdRt0BD7/1NWbMoJMvIl5vsrzbBfiv+J3Xdt42jGSyQnK6s+XdjyK4YOGcKWE+26T+6y6mJPGnlfk/pjIYWKYv7Oi4p9aOysthhwx6+B9DwnQ1mxFDwhBh18MgQ/zLxCFcnyK84K1ZAXk6+vj6KEu33gYd9mwTeHSPEIw4jjL+DnNYJZNPWNV10vatt+9BYw8roQaKtY2Nfh9VjZeyup53Kbni2MEUqfngZ/VRLe8ViJaroLUKmF36M8uBIevUIRNKpbMghvvlAcQd6Sz1SSp2N1O0+t8HtKTohjthX0Wch/YysT6+PsXaDTPClgExIkve6LzYSAj8laGe6rkSOFx0YhSDZs2DDF6+3etcO27JUlqObe85D8nWqWCGC/XXuMZjEo5XrmmQeNOPkCilIXLlIUK379AVurLsMvvhNs235PaIjhK0+jVKNXMO+3uQrpKOfZh/LhfQOCYbJ6+sCYiYltgTblgIwTC6xST0n2e+fePRQtWRZtXu+DcjWEEp/ZEaDNdFAakXGdnObNqaaZEvds0tMI0aCOOH5cqv5Ap2pKjkba+d1QW830wsPD2T09DgwMdDiW4GlkwS1zAYdtbn7CbB99BlQhLjCbInPBxivZnjOHw8n/7N69G0lJSThz5gyrJktVYq5evYovv/wS9evXR926sjxvDofz3OLuLsiAxowZwwIg+3bvwuLp4/N0jPh0YNhaYN1ZoITasbhHwSDBQ8WkUpo02w8+Ke3I10/oXNl7QRtN+cd6Qj6gv3v3Ljx9HAMUhMacARWkQIWaPHnsbALKRv3uUFJea3KeXpQT+bm4gSvvLKYWMhltnpw1a9ZibZQrqA8bECDI0MjTJzlGslT4ejMQaRT8Pt+oXRzDWpXBwIK7bdtvJUifa6A2d0Vf3nzjDXbvm3kLR4K64SvvOTiQJc28Zmn9csxOkJOmL+Sw7p/4asLzzGYULVKEBY1O7t+BDh06olaDplie0BQVvgOSMgTfLyJANg7oai15L/4u33rjDZSvVAVpqSl4++23baljImXKSl5HIu97/olCfu5oVaEAC/xUiZzqsM/tu/FOrS46dOyAV155hS3nk5gRDxpxgA7t22HlbzNwS18RVQp64FxwJ8X2OXtvAhodRo9WznZwnm3u3LkDv4AgqSE/Pc+2rX+/d1mahriNBk5UMa31a2+j+5DRqFhTaJzu2E9rySiiT3EI0NwWbJQYR44cga+vY8OhR+6lsKKhHVHBRaUSeQfPWYNscpHu5t6wj+1Cby+htueWRipvyuFwnl6o40dVFt966y1MnjwZW7ZsQVxcHC5duoSlS5fis1xWm+RwOM8uVIFp4jffsqpbziakcsvkbUCPxUAVnVJxQ4iBkzv+DRXrWb9MNgAlBXe9Bo3Q78vvHLJv1Jb8YYQtGiWLA2c3N3e4uTs3VPbOiHQIEtmbOfunnXfws6Rg0/2Qnn5/z3scuPIfMpvMSE1KgK9fIAs8HDp0UJkNYIfRYLQFoCIiIlCkkDApSpD3Z2hhoXANpY4FeLkjqWQ32/Zlh27alnfO+ipX5z18+HDh/DUUyBS+y9/Tuko7WNPT5OiNsgGCHQatrHyxlVf6j0eFihVxZOe/0Gm1uHD2NLatWYrVq1cxQ+xCxUuhVq3aDt6q8v/wggULFSltwUFBSEqIZyoj+4Ddlv/+YwFeOeRJ9lGzMmgaIX2ecuYdBGbbFeQRGf/115g0aRJb5kojTr7hm0kT2f3ciZ9hrmoQpnrPxviaUhUDotznK7BkyVKsWLHyCZ0l53ETn5gMnZs7pv3wA3bu3Imk09J3n2UE+vfvbwsaRUZGMgmnqOARuRnvfGbHR5UClZ0RNs0CFJbFiCj1Qx5e//aiMNtzv9fOv/760+W29evWuQ4amUwOHRJ2HoElWHqe2pSO3kWlCnNyEj2EmYgryb62ThGHw3n2KFmyJLp27YoJEyS1LofDeT4hL6PPP1Wmr4j07dcvz4qjj7wdU9y1JiEd1qhRBldINbFxg9SnKVKiJAxGA/Ru7g79p6z4SOQX3u3bFyVKlGCBI1K4q9UaRMY6pvwaNN4OaT4lolfBJ/2q06InYnAtJy+kG76NQJlI9wIkH6qAgECnZe3zC67MrYODg6DVqGGBBe3atcvxOFRlTR6AcvOVghxqrZ6lZF05ewJnDu8V9reWrlcQH4mQAOfqMHvEIEipAtJvV+tpZ7hlR4p7CZfbMrWOgdnWrVuhn/W/tmzZUtv6kJAQ9vtSqVUOKjK9Vvo8Q0ND0b17N1vlQSI4JARZmZlOfxNFixZFg26uje5V1qpuhMEEqIcBfZYC1x1tWh2fy4NGnPxEdHQ0Th/chZFvd8Dw93vj+E1ga4Vf0Uh3hG1PNwLm4jXx6qudeCW15wTqZPgFCgbRO3bswPb//rFtE1OJxaCRkMZltuUji5BZnTM6uO2Ayv6i6+x3pZEUQK99LimdcoN92c/sTA3lZUAdzbnNaOsmSXF9VEInJsHii79XrkLA9T/wSoCUEueM48eOoEaNmgizpsNxOBwOh8N5/pj1v//luE/v3r3h6ysNwP10jhNXYoUmk1qplLZkxOP8LKmAiYd3IDIzMlC6Ug10eXeQYl9KAxNTc540Rw4fxo0bN1ihgaMH97NB/cwdUmr/lgAhAFA4fitCkoWxiUj9C0PQ6GxftuyXKqmMCLU1iCRW2HLFTe96KDwWuFh2lG0dKXTGj/8aTxvU36U+OSmOXKWwyTGajIqg0T5jfdxJAsb+CzRv0RK3rl3CV33aY/yHQlpZ6VBHZQ8oEJPH4AYZXYt4ePkotm2utMSlT5XD+TtRGhFicOf69et2p2qGxWxh278aOYophQlPu3ED0bRJE7z9Dpm5CkqkrMx0l8E6fx+vbN6rNIm+77rjkCe7sTUPGnHyFSRb/HrcWNvj74b2xubQLzDHT1oX9PJQFC9fAwsXLnxCZ8l5nJAqRmsNtNAF66rMJzramlkmRuDFoJF99P34TUlOGqySwumnjKUdlEZ+fk4CTMGVsOFaEP5NqKrY/offF7ZlHZyrd27dyn2ZVDKxdYZonCcvm5lskRqFq1GX8UrgHpfHFXPpw8NK4OjRI/Dyct6wcTgcDofD4RDkmRYfH2+r0GSBCjsD37Ztz7Ro4Z0p+M6YVcqgQJnYpRjYCIr0tNdC9qFTzAhmkCyHhBWkmM4PiIPmUVYrDFIaFfaXAmLhGsHXqUSMc2W4f5qQwqexllwXEZVHzkyIiQn/AXP2A6cCuuBeCqB381QoSIsXL478yNy5v6FgQcFryKlK3mhkvkauAhxyDFlZiuBSkrYwCo0FRm0U+v/2lf90GifhA3XOwSk5/fr3x+5r0mOLtb8scs9P6REoVlRzRax3Vdm+GkWwpUULocqzCHk9mS3CmGXsmNE2f6KYGGWWDUFqo1/nzGbLep0e8bExLi0toFH6i8nRmqQ0R52HN4YM/RhPGzxoxLFB6UZXrlxh5Tq7vPY6tq1fBa1ahYNB3W37BHT8HPN+X/BEz5PzeDAYsuCrFS5yqalpOHtP2kZ5yM6URvKg0aYzdxTHOxjUw7b8rscKZNnNbjmVAKtUaDn1DpqPOaJQChXWRNuW1wUoZ84IkuOKpn5yfv3tN6xZs0axbsmSJawSkjOowSEj7E+8hN98L/c16O2x2rb9anL2qjtxBjDy2hV2/s7OicPhcDgczrPLwIGO/ZScoD5Rq1atbBNQRdRSvyfF4gmdNT2NgkY7y/3Clo0WNcomKfs4SYnxGFgvA8UTtyEk8YBiW4UCwgTbo84gqFpVMCV2hvja2sCi0PoXwoEDB2xBo2rFpD5TrsQWFgtUdj5N2QWNyEHhxz1u6LscyLBWAataVQo+5Gf69OnNPLOyCxqlp6YogkG//y4ZhItcPHUEl8+fVezn4ykpbtavW4ttq5WqH6e45y41TeR/M2di6w0fVr2s5ASlEbqzL1wMBLki0bOMbdkQJPzeVFYXr3//3aTYl3yKyNfIftyRk4WEyWosXqRIEec7FG/usKrDwQaodnWCwpOJ1H3i23NWAS+/woNGHBs08KdqUiRR7NWjO84d3o2d5WchRJ2APh6r2D4JFk+cuhHLU9SeA1722Iy/XvgLrcpS0CgVWtnVQlyWX+SZ94/sArztvNTB8VMlswtkfd1xpjhqqj+EAgWUFcnod/fPOcfzoIaMLuzyxrGE5g6GeC7E194/oaw2MtdSzrd793bI73799dez/Rxu3YhEkDoJV4LbY4zP/9i5i6RZnM82xJl98XXKO9jj2ZE9pkkZCsbmF4kph8PhcDicx8ObbwppPfdb7t3TkmgzDLbve/hkXEe0by2pkpgdmRnpTtOBiJJhRdG0aVP8+OOPeJScOHHc5TYaqKt07ijSdyaK9J9tS9uh9LT1J4WqzSU9k3P1OhQwCk1UKsfFwbpn5l3F+t+P6lBykhpjv/nR9jk1fbFZtlYGTwti9bSV839WpB9WqlRJESzKSEvFrxM/Z4/l/dPChQvn+BphQcpgR9atM3k+T3//QKw8BVyNA2aPd+4Blpv0NCLjilTyXt92LruXB4VebNZcEfyxDxoVKSqYfWfH7RvKNDcHgspjb7Ky6I535k1UuPU/hRH7hRi17XvZv19wwn4axtU8aMRxaeJ3+9pF7I8vgjR9KAZ5/mHb5vHKWPww4+en4gfOuX+aeh9m5VlndgFS01IVJeVFpZEo6WS50+RpZJWPmu1+G4P9hKDjQr8vsTuoD3zUlBOsrPowb9481OjgejbOXmI7yGsJuntswJXQzg77PszfZpXqNdm92GEbs0KS6R4wSA2wnE+SB2NOeid8eFaoatKm3EM7HQ6Hw+FwOE8RVapUua/n1ahRA917v43b6pKK9ZNSe9uW47wrw2JNUbOrRWJTGomozcrUrd4RN1lKzoULF/C4oGq7cnNhGjx7RjSQdnDztimNRK6kOVeD2xOQegbVrn9nt1b4UDQyTxnCYFIjJUsaBpMyx/8ZUYNnZmZi458LHJQs8r7x6Hc74Z1mFXDjstIDyt4T1NVkp9puvddFpZonN6z4WzJ4T4iVJpqdkVN6WlaiLB0ipIrDucdaU8/69OkjeBpZBE8jkd27dmLKlCnZvoaPj4/LinUiRpXzyWS1LG1yxOo0m6kRBfL+N2sWq3Lnivwy4ZwvgkY//fQTwsLCWI5gnTp1bNJEZ9DAkj48+c0+t5AM5Oz3eemllx7DO3l28PLyQsOGDTFz9CB8mTYG/uoUzPaV/I2+Xn8e27dvf6LnyHk86DXA8RMnIPe9E4NGItQBYOlp1jzne0mZiu0pKh9b4MVNJUTXtXYXXqpoEFpPMDK8YSyS64vmsTDJ3+hRoNYo87SvRCnz/+emdcCQpKFMFi6yJesFxT7F/IHCvvnnws/hcDgcDufx8EApKBZgheEVpOuEwiTEuszG0maV2sHXSI4hU1IXFUhyXt/7UfZNxECFqEwnnyC5jyQpjXyqtbE9NlnTkNS58OKxJyTJsZKtWD3NrFL2Oa/Hm1nASjw/VkFMm31A4GkawzkjtxOq8qDR/Pnzne4T6GWnyMpIQl6pWVOYlHXFmSJSpUG5UscZ9uMS+991enoaizWMHz8etyOvOlhqUOW+3CisciIazn2mykQtsi3fSZY8YYl+ffuifHmlQklOfhk7PPGg0dKlSzF06FCMGjUKR44cYbmkrVu3xr17soihHVRRICoqynazd0UnKEgk3+ePPySlDCd3DB44EIM/7I8F34/G32G/oaXbAbTWC6a/PlVbY8aS9U/6FDmPASqAVle3Hz6y1OnqdjGdjIwMdgFUU+fFYsG0LYIhoUglneN/1OAmlfS0EVwRlScDi9LecnoumbW/cliXoZc6Uo/iAnv8sLKTdSdO2XCNTe2HFZnNMCFVMql0xq2RuU3K53A4HA6H8yzx0cCB9/W8gqHBuJnhj+khi5wWAKG0neyCRjTxlxOPMnNADBbJB8kkABChwE3WXaF6FaH1Ewbd93NGYdF/O6wTPY2KxyjHLMdvCuvFdDRSGtlPZj6tNGjQAOFlIhy+29x+zzSJK1e7OcNkfji/mT/+WIL6DQRVvgOyl/BLk34jzggLdFwnDwqRoTl9LmR5EVqwEFKTE517qeYQTAuWfTbOMMP5Hy5c9tvs/fY7CA0NRVhY7ioqO/g9Pa9Bo++//x59+/ZlcjEqez1z5kwWkZ87V8hHdAYNCMkxXrzZe6MQ5H8i34cb0OadBg3qY9CgQXj11c5YvVfwjfne93vb9kP+TTB/2coneIacx8W0V4CetYAbpgK4Z/ZHrOC/aKNr165CeppajfhUpfyZaGoWZKubbhXEvxeA17c3hsU9yOlrnboDZKicz8q5NR6LVutcNC6PiIb1aiseZ6XZvXkrc9OdS0sTzdKMz749ux/y2XE4HA6Hw8nvTPvxR6ZyyCtBwcFY8/vP+Omrj2zrWurlk1kUNHId7KiWC/EEeS4+KkRzYbm3zpw5cxTbjUlSapJ3+y8cghLyirnZEZRy0mnQSGdMhG/GVcX60KJhCl9LIymNnpGgkZz69evblr29c1fBV26KLdpQ2FO+UN6Mr13xxhuvo1HDhk6DWmZj7n6XNP4wSDFJpxPIGzZssAUrr166gN++HZHnoNE3kyZhrV0xHXt8/Z2PbeT4+Xjj888/Z1WVc4Mmn0w4P9GgEV2kDh8+jBYtWkgnpFazx3v37nX5PCoPSTKyYsWKoWPHjjh9+rTDPtu2bWNRvIiICLz//vuIjVWWC7TP/UxKSlLcOBIFC4Ri/pRRmFfrHLxUGainkwztRh3RsepSnKefcV+Pd6gsJmdiSm80ivsVL8QuhIeOpJxCg0tQaVihfKXGqcpHXLXhdhhazQIuxaoVjZLj/q4vkCkZTlqGR8hP06c7rKt/8kun+94xOTYWbeMdn58TpNzicDgcDofz7DB8+PA8P6dEsaKIvHQOcdF3kXpGsIVIlRlhU3qaRe062NGpsutjX0r0hKce+HPRrzmeR+8+fVhfL68kJyc7KI3kTPj3KgKa9lGs6zviW0XQqIbuLO4XChpVuS5NeIuUqf6iLZWrbPmKSIi9B5Mp++pZTxMZaWkoVbYcChUqZFtXrlw5NoaW97/JFsZeWCHf7qpCmzxo1Ll64ftKJxQZMWI4U/9QVTM5apPkQ2WxelM5w2w24XZS9mMJCgjajzvS0pQ+VzkRHh7uUnklovXwy/E4fn5+TOHm7++fq9cNDc1e3fRcBI3IfI0uIvZKIXp8546yXLcIBYFIhbRq1SosXLiQRRcpinrz5k1FahqVFfzvv//wzTffMO+dNm3auLxgTZw4kX2B4o2CURyJkV99ibff6Yt1i/6Hc4XfxmK/ESgkK/05cpmyUgHn6f2e5bM/aRY3vJM4EsvSW7LH/0vvYttWrZhGIZeMiCiHQ0ePY2eSPw5ei3P5GgWtMzux96KyDRplF/0v7KrUpZWBgwaxYPLDQlVQqEoicuXKFSTGJTjdt27cfOzJUvbQbplDYbZIDdfatWuzfT2ajZPnk3M4HA6Hw3k+EfsDKUkJ8KrQhC1vN9RyMAg2qPPum3T4ahqSvwYSvqYDOFdRi8yfNy9b6xBXREdHOyiN5Kw+7dhnrN3kJWSZpD6mzupLdD+oYEZElJQOJ9L7nf7YsUOouEX90cz0dJQMkyZDn3ZcTb5SkOzLr8gvQYDGyHFxyu9A3j93dRyNWoVR7Svgg6alUKWwNzQy4/K8QgbTpKijim9ySsdL/eWoAOG37wwKNnX5Hdh5Bei1tkiOY4ni1knv21G38bCJ8amNU4nZq43yqnDy8Xk4qq6nPj0tr9SrVw89e/ZEtWrV0KRJE/z9998s9/J///ufbZ833ngDHTp0QOXKlZkbOQ3SDh48yNRHzvjiiy+QmJhou924ceMxvqP8D1Wtmjjha2xc9hsOFfuMqUb2BvWB3ppTvfBYHPp9v/xJnybnYWKxYHZaJ/yX9QI+TRmEFLMyiLFD/SJu3IhUlLJML14fd7PcsP2CsgLCruD+tmWjtQ/gptcjMNBJAjJVJxs7Dq1atcrVxfZYCccSnT/+8APeeecdPDTsGkKaabgc73zmhXgncZTDukizZIz31lvO/ZqI9PR0rjLicDgcDoeTKx8asRS5WEEt5+MBhw3lWOo81S6xdanis/eMuV9E31l7VcfN+DQ0+naL0+ekWfQwiB1GWfVaOTeCWmf7ugmeZRWeRvaEFiqGRo0asWWNVouYO7dY8OJZwT2bycfBgwZmqySyr1bsCjetBkUDPNkkcm6f4wq1Wuvg3aOXVbyL86mabdDocoIbGv8M/HPGkGPAi+IHREb6w+9vp2eZUHlcLJYcdb49KkmYfM4LAz54DydOnMBzHTQKDg5mP7K7d+8q1tNj8iHKDSQ3q169Oi5dcn2xI6d+ei1X+9Afhsy15TeOEkr1a9euHTav/ANHwkawdQeCeti2b7rnicafzrblLnOeTrzEfOf0aBwzCiZ6RL243xT7LfQZzAyyLZOBXzoLOelZOue50kVVt2zLKUZBQk37u2pgSPFEcllXyJ8X51bK1mCQOd1PP/2MR0FUFcGHYP8d4dpglCmH7EmHY7lNjXWWrEh4aUSUK2dbT4pJmn2jNF3i1c5dMGyYYyCMw+FwOBzO803CniUO60SlUU4lyUX+yaqPzgmTUTV2KUwqKWBguS/r6ZyhyTAiNVWpZPp02RHciJMqu8mZuuUSjNb0NH+N8xSig6VIHuU6YGTQ+GQbNIKsz+rl4YFtKxc+N5kmonfTlO8d0/bkgcrly3MnCKA++IOkpxFaLWUwKL+rJYlCpkNOkAqvhNVUmopr5bh/ipAyGRTkfPL6QRAr18096nxy+Y+jeTeepxgGCWGe66AR5fNRuT1KIxOhKCM9JkVRbqCUs5MnTypyNu2h1DXyNMpuH07O9OnVE6cP7MS5ov1YQ+OvTsFQz4W27ZHqwvhgxqoneo6cB8OWwmnMQJQp2LY+2eIYEFo0sBReS5iIF2pFIDn6GrydNOwjvJR58kkG4SKalZlx37MScqVRpkmYWSNJa4GChfDBB+/jUZBZ5i0U/xpoPFVImk5NScnT8zUQZk8GD34ftV+og8jISGzcuIkpIRcsWIBatWqxvP+9e/ewKpKEs6qQHA6Hw+Fwnk8yb55h9xW1lxyURtlVUJMzPkWq9Kop08C27MrCQw55GuXVNFtUj5CXjvTCOuy5mpjt86KTM4VdLY6T0XTIDL2TCryyz8SiEvqY7oYY5zvppX7tvxs3YM+unayoy7NCdt6gYtBo6JAh2W7v0kWypciOjLRUpLsoEpNbKOhkkaUkEr0n/otX5wHtdrR3+pwVc6bCkJWJzPQ0ZpNBAZt+/frZtickOreS6N2r9yMrZa8WxygqoSqfPbFpgLu74+Ty08ATT0+jiODs2bMxf/58nD17lplWUzSaqqkRlIpG6WMiY8eOxaZNm5i0iwZX3bt3Z4Ord99913ZRopn6ffv24dq1aywARf4mpUuXRuvW2UsZOdlDcr4ju7fi719/wNL659m6gV5LcDToTds+/971wNYJtbF62gBMmzbtCZ4t535YtnQpfvnlF8BixjlT9qUgBxq+xgFDZbyaMAXnDmyC1t9RHdjDQ+nfYzAJF+h7UbfznNMrUqhgIQxYAczaB9z0qm3r7JC8+FFBasQbCUCWtU8VEOCP0d4zc/38ZIsw81DHso1dr+ia99JLwvWIrlNicJvyyMX0NEqzXbZsGbstWbIk25Q9DofD4XA4zx4KVYJViWGyyCbdbEqjnCfibppCcFOWLh9lkgx2DVk5ZwrQhD75wN5P0EgekAl5JftqaCE+blh8QLBAiDUrjYWTM4DQ0dm/JqmufNKFFKCQpJwrVFFVsbJlyz5witXTQnaeomKGTl6KQiXGRaNsWSk74X4gTyR7T6NMI7DiFLBu9RoWHJKTnpqCP+f8wFRGn77ZAseOHmExALmp99Wryop5Ih06CEGo+x2HZIctEKVx/hn/dvDRvO7j4ImfNZU6nDx5MkaOHMl8io4dO4Z//vnHZo5NM/JRUVGKKHffvn1Rvnx5tG3blv2o9+zZgwoVKrDt9IenvD/yNKILAHmbkJpp586dLh3gOblXhlFg76/ZU7Hyt2n4o8Fltj5AnYyRXrNs+/VJGo2oxCgMHTLokURxOY8GsbH84IMP2DxNTiRapNzvttW8cN3sWNfVXaXshNy9J/gdGQxZ9904jxkzGgtP+aP/n4DZ2pkym4zQurhAPwzsy5RSkKqtfneun/9nRnN2n+lfAevXrmHpefVKACWDpMabguU6rY4VCCCOHD2Khas348/N+/D3lgP4999/8yxp5XA4HA6H8/RCvq0iFosQgJFP6uXF0+i4UfD5EfFXC2k6RHxCPOtjbNni3GeIKBMMWJKkwkN5CRpdvnzZVknNs/QL2T6noK9zJcbE/4DaPwK+hZXvwxE1ErwEK4Dw6L/zdL7PAzQ2yykoJPd3oj5wixYtodPrHSqcEZkZ6fD0eDD1TGpKMtKsaWPOyEhXZjNEXhIq6hmtyjf71DYiKTF7NdujGKPWri1MZsenO4ZYlh8XPI2eVh7dKCsPDBgwgN2cYW9ePXXqVHbLrsrAxo0bH/o5cgQoEEfpgJRi07HPQGytOB/h9/5GqeB2mH98JHoljmX7TUx9Gz++fx0DfjrMnPlF0zFO/sXL2wdJVinn1StCQDC3/FfFsax8qDrWYZ1JVj3jfoNGYr4wITZeuzb89UiVRvbmiBS7CdVkX3q2T4Mw/LZbUBEtyWiFEd5zUSt5KXvsbbiNPR8J+31wOcqmNFKp1cjIEHL8P/txIcpVkzpWezetZEFzMhBfsWIFli3/E38sXvRw3+hzwq5du5haNShIqHBBkxSUIsjhcDgcTn6CzJppoolShswZKYp+iDDmFQa+7lnKIiTOcLMWsBH5KuUD9PBYbz2ehSmdmzdv7nSC6ssWwLiXaImq7M62rRfPzRVyc+OcUts0KhVMFgtMVj8je4ZvAMsyadK0aY5Ko0IJu/A8QwERe2NpOXkx/T516hTrJ1WtUZMFiDy8lBOp1BfPbfl4V5QqXRpGYxaSE+KgUqnh7ac8niFTqTTS6oT0L1GBVKtmTad+vOWtohJ7vvn2O9Stk33w8n4oWrQo/AMDofag81eOg/Ra+q8+vZO/T1xpxHn6qFSpEipXrYY5Ez5FVEBT7ImYhltBrRDVdCmaFpUivd95j8Hw72bggwHW0TEnX+OuU+HTF4GqhYEff/wxT8+9B8fc8iV+jvLjTJm89EHkmW7WfGCaWaBA1Pwpo3OU2z4MpkyZwu4t1oZ4S4CUO21PeJAXIgr4KDyhLGqhkSuskxqSI8eOs/s1a9aw44plad09lOVzCxQuhkxro0lBjyV/LH6o7+1564T36tULk6bNwpzla9GuQ8cnfUocDofD4ThF7N8Y46QS4TfMQkaG3iioKe74C5XAcuOv6BSLMsBjjxAwcp6FkF0RHPGYPXv1ZirtKrWde9bGrJmMlhWE93TGiRwjKkX4DChrpEBBQdl+IF7wqt1nbGj3Vvjw1pCVhfhYF35OeaREiRLMh8fLy9upoofSyh504pZUTEaDAbPGDsGciZ8ptpWJKIe01CSnKqH42HsujzlhwgQcP3bM6bZPh32Cxo0b41Gg0+qg9xYmJeWIhbae1iwc/q/i3BdjR43EtjXLsG31H7Z1ZrUerWpXU+y3KCYMKbE32CCXk7/pVtWAb14GlvXU4ESBtk73KavJvTmzm11qGtGyRUuWK008SO74PxvWo3TZCNYZEWcZbkZef2wycXEWLlxzG+3dtqOR7gjaVFR6OmnUKpy/q5TaxvrWYGZ//27ebFsnVpyYO3cu7tyJYoGhmvWbICyikuK5NJMnztLlxrCSkzPNXu2Jru9/wb5PMVjH4XA4HE5+xGKUJt6GJwsZGskeJdj9/jKTcnz+HbPjQFbEoPNzGTRKTHBuKCxCSmlX0DHLVK7BJgr3798PldbRKkRnSsPV17Zh98U7DtuWhs9n98vPC95GcquRUQfLoPcSYJdJsAAQCU5xHihIzZuH91PN9auXER/nqPh/EKjf7uw3Qkojqn72IFAf12Qw4PaNa7h3S/CzEokoVx6pScpUMzHTwF6BZH++2angHhUarRapmWb8lf6Kcr016vK09uF50IhzX5CJL3lHzZ7wOauEJWdUe6UUUNVzISZ+1h1pac7LZnLyB3WKCYPmL7Vf44qquNN9BnpKQcKc0DsJGn366TBMnz79gYNG1atXR6EixVijQf5IxI3HEDQSZwcoyLDoCHAvBehw5zt0jPsZ9w6td7qviMGiYaVfX+7aE+kZUs+lZlCcYj8KGmXZGf6pzRnQ8qDRQyExMdGmclOphe8oMCQ025lSDofD4XDyE4U10QovI/tqYqeLvo8of6WSItLkWLBEhDwiXQWNMpKdK1bECbQ333zL5XHJszYzPR3zfpvL/GYNBSs67KPRqBHiDSQ7CepUMB5k9+nJCQq1Br329XvpmH8IWPTnauQGa5PPuU+o7yQq7UUObtuA1OSkB1b70/NJaaSmtDqrd5c8zcxoVPbRRNPs5ETBKqJ///7IL2jUGjYReUb1Am6YJL9XSu0jHjSV70nBg0ac+6Zy5coIDg7Bmt9/Uqx302owrqNSJXG60U/Ytm3rYz5DTl7INAqNP1VEc8bmgPfgqVIGCLNDb5c7bx9MedDoP3UyqPGi/GeiXTvnJTkfBQkJ8ei+GCg8FuiyxBddf76D1Qv/57Dfu40ks8o4sx/UFiPUdN6yfaY3Ou3wvJOH9tmWQxIP4I09Efi21hFbYIMCH5z7gzwbKtesq+jwmk1mVtXucUKBTw6Hw+FwcsPMmcqKrbdMQpDI7KJq2vGwz7GvzGTFOvs+XBt5QQ+z66CROfWu0/Vin2T/fqnPYg+1rbH3pLS61LJtHPbJgGA58GMZpY8tkW4NhkXGmVibTYrvzMwMNml49thBvPfee4iNVSpqft0P3PMVDInl6Pio94EgZbx9etoPn7+HiycPP3AxGvKziouOYt9xijUQFFKgIJskpRTI9Ytm4a9ZgkWEXGm0b/MatH6pDSuOlV+4dTMSJ48fg06nxfSYVxUpg8TTWqWP/304D8Tu3bvw7/L5DqZ5lJoztW2wYt0HO4D0pIeTX8t5+OjdBYPpytqLDtvedP8HpbU3oSnp2Ni7wr5zkgU3W5WwhxFpNxlNLDWNbp27vobVq1fhcZGaKphRklejWLnRmCjlVYcHC59lyWDJLDAdbkxpdDvyGisjKqdkhOPMm0jpO4K6q17IPVw+tV94LVM2vgScbKEOiNpuRuzCmZOsIufjhCqFcjgcDoeTG+zVy7sN1WC0qLOtmmay+igSxwxl8XdmM8X2/QZpgpfUHa6CRqYsQSFhj6uS5vZYrMbWnhENst2vRervLrdVrNPCtnzj+jX8+5ewb5UqVVjAopIsPkZi4hnnhOppcrTVBR/K1Y5zdc8korL/YaFW0WSto5HzxmW/YcmS3GciOKNo0SJQqzWsj6a1BlV8fP2Yuknv5oZje7bi77nTbPvThDGlKpI6qcJj7r/lFk93N1xN0OFEomBtsfa8/oE9XZ8kT+dZc/JVNTVypp/33Qjcvn4Z/yyZgxRrBa50t0KY0EmpWpnyy3dP6Ew5OaIWOh4njWUcNu35dysKjAauF+uV7SHckInV/oOZQbROZZdCpRIuNw0bNsSoUaMe+HS9vDwxaWA3/Pf3IqZaepzGcpkZUkBs2jRrI2YyWCuZAA1KSb4BXnqh8cuw6OGfdh5pqclIlMXTLkQDFaorKzgM+WaWbdmklhRZmihhVpCnp90/JBkm6fCTNCN0VpmGw+FwOBxXOEuhXpTRlk1GucKk9rAtv5LwPa6aiii2x1kEnyCClNsug0YG5yrza9eECrE5Qcelal1uxZwr2QNVgnray+Boaqy2CO/bTa9Up0ffvsHuO3fujJ69esEg+xh83YC1Sxc4vlDF3mg9CzheeCieB8QKsQ/X08j5761wocIPfGxKOdNq1FBbVUtiH00j0+eL/ac71y8gIiICmelpzEQ7PzFu3DibgThNbM+MewXdFgFrrwliCh404jy3LF64ALvW/41JA7tjwQ/j0L91VSz75Rvb9v81kRzv58Q3dllKk/Nk8dU7Tyfz3/QJduw5zfx7RvRUyj8neCtnMV5y24squksoqZWkyCI0g0AULFgQo0ePfuDzpePERd/FiX3bmN/P4yTYaohNeHhInbIB9QuxlLQKhaWOWGqW0MCOSekHk9odiXGxMMr6ZfR3yEhPw8yNx+Du6QU3nQrNwjOhMQkze6luRW37ak2CsbYpmwonnOyhgJvGathoH7x5XMEc8XV48I/D4XA4ueHXX391WDcq5T2kWxyNpUVMGvecj5vWAQeyKsISfwmDhwxxfhw7n8W8tpkZaSlC0MvOq0Zka6DzSrQriv+A4OSjbNnbW1nmnTxuypYrz/xuRo8aicDC4QrD6zRnptc+xbDpAnAt6vlI8X/YwQmVWm1LC5NTonQEJk6c8GDHVqnw08iB0Or0cHOX+tVEsCz4lZYsjClVFgtKlSrFfIIofS0/UaVKFdv44E7kFSRrQrH4KGC2hl140Ijz3EJ/2nnz5yH2rhQoOHtIypOODWyAQUGbbI//2rjhsZ8jJwcsFrQNE3KIX3ffqNh0/Og52/LNKxfQWr/H9vgtD+W+DfSuU27U2ocb2Dl18gS7j466+ViqI6xatRpt2gjpeRMmTMSSJUvw88+/2BqrOvUbwVNjUaSkydlrqIqglOP4qo0bXq8nNYDlQsGMr338AvC/TcdxYNEQtIv8CJUjv2fbVbIZlsxMIbDHK33dP/TZiQFMEZ1Onyep/YMidrTJ9JzD4XA4nJygkufO2JFVw7ac6qZUEhEXCvXI9rjjUvuhe+I4pCbHY/GiRU73SUxwbi0hKpOKlwhDTlAhD1Oq0M8Uqao9zyrQ+qkF2wJ7qqfLKs3aDbQNmRm2tps4dUXyNSLVUZSyeC1OU2E2H2ESzt3ddaDtWeJhq6mZl6iTQCGliD1o4ObqlSu2czabjBjYsS5uXBf6ZHIFnKh0oiI4FEiMvHgm3xVaat26NbZv345ChQrB3c0NOjc3vPbaazBZrSUetgLsccGDRpyHwuuvvYakpCRm0BsfH49b1y/DaK1qRRSt39e2/Ol2rjTKd5ilIITB4pgfHyi7wDW6ozR8vhbSDsO9fkU7tx3o4vafy5dQZyo7Cw/KzUipJOfjMJXr0KG97ULf99138Prrr+P999+zdeS0Oi2M1moO2dGv1Bl88oLStPEFX0HirdXqUMUaLKpwS0hRU8lm5tatWcHu795xLEtL1Qzf//AjbN3KDedzVBpptPj4uzkIixD8HPTWWS17M80HYcaMGS6l/iIP8/U4HA6H8+xC6V00SC5wRTnxeilG8hs6l+A4aXWo5FjsCxuT7bGzoIfF5LqCqFumXdpYpqD2oABCxZr1Ub9hQ5fPVWndEFSzDSxad2h9pL7kYr/hWBXwMab7Oret8NApAx72kz27N66yVZQlUqwKFPaaKsAruJhi/9+EImxYsGAhBg8ejOeB5GS7yNkDonahNEpLTXngoFFcnFDUho5/89plxN6NQpZ1Yi05Jdmhatrpw/ttE8aVKiqrdj9p3Nzc0LhxY1vKHQXVWrZsyfqfYWHh+arSW17gQSPOQ23QqBQmGRw3aNQEJw/stG0zaH0xvNRx2+OaYzdxX498xJHDB2zLBjgGjTZtlBRFv2+Pxe9+X+FP/2G2df08V2CG77dQq5TfaVylz/CnIAiCoZljdbEHIS1NmpkK8pfSwR43RYoUsRkzXjp15L6O8V1t1wotjVnqEM7sTB9kOoJChGoiN2/etG37fdEf2HXwGMZPmHhf5/BcKY00atRo1NImgfby8VWYtD8IR44cYcHFjz76CKPHOO+oi9e++fPnP/DrcTgcDufZhyYhaBBaSKMMBOyTKWxuXTnv+ESVGkmqAMUqP53jBNc3k8a7fG2Vya5tzEqSzkmrgdnoOtW6cMeh8G7xIUI6jbB5ZxI+quzbW/tKZ2q1MohEE9OlS5V0+lzyjSQVUpyXFEzYLghZ0L17N5Qp4+jd+axRu3ZtpnR5mBiNJmRmOpqix8fcc0gfzPuxjba0Q3vSZUoiCrxQYOncicMs00VU9uRHtFotCxolx8ew/wqdd/ESxVlQ6WmEB404j4R3+/TC5I/fVqwrWLq+bTk2zYDwL9bj8uXL+O23eU/gDJ9f6DO/cuUKBr/7GhbOmcHWXb18ybb9mCHCttxCvw9z5/6GmjVrKmS/jfVHUUt3NsfXCqzZHWuyXkGzmYCmcp+H+j7kclTyN3pSUCfuxo0biLx2FdOGf+CgLilpraRGnDFKOff2+KZdRKXIHx3WV7hlF2zbP96mrDp+XArE0oxbnebtkJnlerbwWYOCPHkNPickJCAj3XklmEiZeu1+WbRokW3GbNzYsU73Ec+5WDHlTGh+hT6X06efk3IzHA6Hk29VshrorMbQzrjjQliy855yQP92qWiHfQwZzttFhr1q1pQlCxrpslXVaksLFdM8wqoitLDUV9OrnCuzu7r/K9yXV9oOFFY7emWWi5D6q8SIDcC1OGDIgutIT0tlPpIi6c9P14ixf//+h16G3tvTA0aZuktOyZLOA3i5RVQwRd107IfJFWVmo9GWoubp6Yn8jIaMw03kZGRh3lsJCfFPtWCCB404j4SOHTuy+60rpfzoFI9wnA7uotiv/vDFePvtPiyHNSoq6rGf5/NI9x49MeS9Hvih/HJ0T/yIrbNY09OiTEG4YRYa9V7uazDb92v06dNbYfhMBoO5JrgSmrRsj62XHr6nkbyT8qQbjqJFJbPq88etGmgrHatJHgMfJH3h8hhBySdsqWnZErXfFjTavFnK9yeTSR//AFy9chnPCzSztWmT5JeWG+hz8g8p6GDuSFDw72HMLOWW27cdO8H5kYGDBqNq1ao8nY7D4XCecNDImYluaiYNpM2Y8B8Qqy2Gg6WE6k0ia28plUapRsd2SqN1PSSkymrKk8kCUu8gct4rKOOXApOLilr2pIdWsy2X1jhvbyd5T8cnrSJQvYBSWRSqisq2ve36+uvs/YeTH7NvcXh4eMJirdpLZCOGeiZ5FNVh/QMCXFZPc+W5lVuy8+ps2rSp7f0ISiOzYuIt3cVEYH5RGqWlJLMxFAWMvL2kieSnDR404jwSKLe1TJmymDNpOBtEz/vuS6QkJeJEgf7YGyiVbfcIr5Hn0p2cB4MGfmFaqbE+efIkTEYhb7henJQu84L+FG4EvGR7XNAqcz0kZUQ5YFI9vipm4eHSrMbjMMLOLSa7srgBntK5XTMVhsHi3H/phUufOazzynCifImUAkU//PCDYibG08cXmjwELZ4FLl2SVHK5gcyn9W7Kzo3Yt8rIzEtE1Dm5+S2KM01jrWVZ8zs0O0YdtVGjRj3pU+FwOJznkuyCRuPXn8XdxDRcjwfmhPyKi4V6KrbHG5TtkrsWyIq+rlhXpYgOOifdE1KmX5ap0RnmLGDncHzUEBhb40yO/n32eCIdGpXz59D6QC+9ws+RSFP5ZRs0WrZkiWIblWEPTTpke/zlyAev2vu8IwRBpKCRM3+j++WTYcNcVhV74403mE8kYTIaHJRGok1EfkOj0SArIwP//LWIjYvpf+Ln9+TsNB4UHjTiPDIuXDiPiHLlMLZ/F/z71wIsm/kdGvb6EYU0sfjL/xPbfiU+W4sXuw9mDVNOUHWjs2dzToviuIai9c1KSIaBB/6cgPN3UxAWvVax3/HILFwqIZVfVVtnbGi8W0uKVSiI9ZFmkUQelRRzzZrV+SI9TWTkKKFDorYz5dZqlJfZE0Yplz5NL3gTERonkvOq1yc7fa3RJVfhq5bUkL6pMDzUanSKaiLPA3lVKFLQSKdX5pOroHpo1czsf4sUlHX2nyhboTLr1Oa1s/0kuHnrFrvnSiMOh8N5skEjmuWQV1UV2XfFaiScC9XPhih/m8JWZGATLRa+5bjv8OHDsWb1KuXK+AtIPiEEaSL8UxTpQ7nhM++c/fxUFuX7OKR/OU/KXvu+58vthQwIzoMrZ0SyMjMe2rFfbtvGQTwg7z+JfSuqmGy2BhRFddODqpwe5eeVbvVfFScUn1Y/I4IHjTiPlNmzZtkMX/9bsRBmC+A31gc1dVIZd+JKkRYYcdIfM6ZOUshgNy6fjaaVQ9CiZUv2+MuvRqJChQqsUhTn/oNGO84m2h6/47sEc+MqOux3LskPnt6CQTBRvnw52/Jhmdponiwby4JHX8VMRDTAI1zNTjxOBg8ayO6dKX0qFJI+Rzn7yzgPCon4pzoPkFYJzcTY1kDp0pLa6t69e6ys56OQJD8pqNOXnWT5fgI9d+7cgdruOxI/sz/+WIwHISMjwyFdrnefPk7PgeJUhYoUZ+ly+Z0Qq/H60xDg4nA4nGddadSxmGO7oVXlXv2RCh+Y0qR+IJEFHV6rKizL2yVapibyw6TP0Dh2Nps4NCXfRlpa+n1P3hRQ5zwBoYKyvcnSZK80Ehk/frzTqroBgSF5OkeOC48eWZ6fIevBJ9rk2CuGKlaUxiadOnXC91N/wMLvR2LPhr/zTd8/JwuFi2dOKIJGD1pl7kmSvz9tzlNPw4YNmW9Hz549mSkbNXpJScm4aS6Kc8GdHPaffLcyEqf4AVNUOD27K1pH9sO23jG4cGgza5QWL1rI9iN/jV9//dVmOMvJPTEx0fDIRQaTW1YcqlSpYnv8/ffO/XZuJEpBCo0lE1ka5wGSh428s5CYqOz8PAmoaqAzpRHRoHSwbTnFIshpzSotovwbZ3vMVLfsJbeWLKnTRh05H//AZ2pgP2HCBHTuovRBsycpSVLN5YbIGzfh7ReoXGkNGt18QE8jUkuuWbNGse70qVOKx3TNqlajJiq/0BgZ6WlISUlBfsfPX/DDyCmAx+FwOJxHw9dff41p06axgbKfzrGdT80Srs+56QOM71QZ6ZeV/ouRpoJOC41Q+2jSemBdZiNEmgtheWYLWFKibGndhKdX3ipnldIofQ7kE5Fm6+Sj2k5pZLaoc0wHp/dOyij2HuzbVt3T6yWTX9BolEqj5ARhDPawUtftg0DySVBaHjJ4EKZ8Owm3rl5g64KDpb51fg0aaaxjAqouTpQuXRpPKzxoxHmk0J9cLPn4wgsvsAvCO/3645fkbnBXGXA5uIPDc6rFLsGI5A9QPvEvzErrhF/TOqB7DWD0aCkfmcplv/vuu6hZq/ZjfT/PAoWLFEV4ILA9qwZ+SeuMVItzWWewKUphMB0WFuZ0P4PJgtXWwkoXC3ZDZHDbx5KeRr8lGsRu3LgRLa1KtCf9W3+zey8hemNHWJD0OdLWWO8qWF73JOuM7Yr4yeUxM3RCg2ixpk/ZE33nOlavFtL0UlNSWAn5K5cuPBWBiNywfv0G/JuD0bXOzp8oJ+7FxCEguIBiXdW6TdCicw+Ur1gZD4LYOahSt4lCCSX+B+h+2LBhKFupOl7t/ykir17Gl19+ifxOlNWw+/btKDbrTFXrOBwOh/P4aNWqFSsyQ30NaktKhyoDNSeiUnOVnjbYYzFeLBeKGtWVdgKL0tvYluUTstS3uF2whe3xiowXYTFmKnolrgJVrvp/ZWS+msRrC4D5p4XJHDVMzM9RbVaqWPwCghyOo1arXAYZChYurNzZXZjY4zzYZK38u87MSEeX115XjM8eBl5eXiha1Hl1WUpFo994vYaNmRKJrBnyMyar8s/Hx4eJKD7++GM8rfCgEeexU7VSRew7ecNmeHctpB02BXyg2GdRRluUjFmDCanvYFxqPxSq0xazZs1Cz6GjMfTb2fhg9A/oMfirPKsMOEB6RgZijV7olTgW36T2wetxgpTXnpd6j3TaGNOFT05UEtB3hTuGHGuMa6Gv4lyRvkjMVOGARVDRPMrykjRIp45UQICyMsiTLq9pD312wd6CJDXN4gHvjEiYNEIgKTKkncvjWVSCmirBq7zT7Sf2bmSdSBrIX71yCZ7ewnfTvXsPPAtkGQxOjaW//OorW2BMq9VgwYKFuHv3brbHok4wlY6/eTMSPnadz26DR6HXx2NhND5Yqpj4Wy9dsToGfi2YNgYGhbAgC83cUqBz7ty5KFpWCk6dP38+3/u0pVt9CyywYPr06Wz2jMPhcDiPH2pHyMbBU+/cDiCn9LSyugR2P+S9txXr/85sbluWTzxRG3WlaGfb49umEMAspKyJyM2R5RjJkyIXXIkF/HyldqXjoUYIv/eXYh+5ipvS8YmIiAiXxzx2+OBzWzntUUH9rayMdBgNWeyWlpoMrzyqzPIyKewK+o1rrH6hT0t/RK/XMxGFfdrk0wQPGnEeO6QK2bJyMb4NXYXNFRZgY9VVUPuXxpXg9i6fM8X8AQoFuqGpejMa1yoFS9RetOjSG3p3dzYQ5OQeD08vHAt+xfb4lNl5o1uxilTZTs7OnTvZ/RsLgdn7BE+j4MIlsTtSD4tKgyTP0gj80gLPl1wraJ5VWNDIbMKhHY7qmJgUwShyWuobSPCS/KGyIyTpALu/61cPaXqlOoYwZQgdO1Kr0Cyc1mqCnVMA5WmB/KE8ZGo3kfFff43169ez5cOHDqFnzx7Ys2dPtsdq27YtSpQogX/WrWWKLPugHuuIP2CAU+w4hxYtgTot2rPXKVSsBK5fv64oCevtK3kz0PWLfNryQ4qlHPosbIE5jRC8TEpMeqrz8TkcDudph4qS0PW5dphdmrWV5MR4l8/12jYex1UN2PLLlYUsgJy8An39/GDSSIpencoIs8mgVBq5CBolpTtOxAzxFGwm7LkRr2x/i8VudJm6JBofF7ZXE9lx0mq1NHNftrtxcsm6Nasw/csPMfG9V9nt758noEb16g/9dUg95GoSj/prpHZSWYvzPC24PcUG2CJP1yfOeSYoV64cQkML4LOeHdGybQ8s23QcZd7bAs0wC8rt/BSVT010+jx9378wRvM5Bm1Mw9cnC2LkmrOo16oj/v33X9s+pLioIDNOe5JcvHgxX8omjQYDEvXZN7REkJebQ0CEUgLJT4rYcjsUH2/0Qd0GjVCvXj2kJ0uD3vAy5VCpUqVcNerPEtSpiblzC1M/7etynyB1Ii4WzJ0SyC/9Mrs3q3QsuGpPGWs696pVq3Dz+lXb+mfFe0aU4TsjOjqa3e+yBjHlqZTOiI+XOtIeno9mZkr83L2sBvJzt51DgSLFWWUZ+XciVm8LLlgEpUoL1fTOnDmD/MTIkSNtqkI6dx+/AIQWCHVQGnI4HA7n8UEKH4vFjCL+yskPEXkxmRlffYiLp4/bHp87fspWYVWjVuH6N86Vzh06SNYRFcpXgEktTRawym0mJ0ojs2O/45fVuxzWDfISqq6tPQMcuQn8Za1rM2WNMmXtnm8dl0EjcTm7gTidU68lwA87gDio0hQAAIa4SURBVNHK+BPnPqHCHvPmzcPZUydst4EfffhQX4MKirz3wYd47733XO6TkpgAw0Os3PY48Myhj/o0wINGnCfCtWtXsXjxH6xk+O5/ViC0UGHcunULr737CTb9exCHP2uA39v5Y2O37E3OMgqVQ+aVrTTNwR5TkObsmTNo+/LLqF37BdvA8n4rM90v//23BWXLlsXUqVOR36CGtHJw9hfb08FdoNLoHQbws2fPZstHjx5FuNXjiDxnqFqFXDosL8P58ssvPzNBjJxQa9S4e+s6W75zQ1k6tF0VYVZvt6EaDri1wK6L0Zi04Swu3VP6D90OkPxwRMxqLdLdCmFF7f2K9X1qA3dHA0GZ52EwSCVvn5XPmzqG9+7edSjD6uw97tmb/VTihQuCcSLh5qLxVph/PoDSSC/zWaL0OgoayavR3LgkVI98f/QPCAkRKrrUr18f+Yn/tmxRvK+Pp8wFVOqnRgrO4XA4zyIqlp5mgbtO43JiUGTvv2txeOdm22OL2ehQcUyVGsPuW+n3svtFbwF/dY6y9aur1agBjUnq0100lWDHkSuNgt3SkfiNB+4sUJa1/276/1y+j98OAi8vKYguvwuP0+yEJTqTctI1JiZGOmdrxCon5evRW8DJkL6IfbCmnWPli88+Q69evR7pa1Ag8OcZ0zFu3DiX+xzauRkFrX65TwPLli1zarXwtMGDRpwngoeHB9588w0sWrQQ508exb2o20yR8nafPkwWGxTgj8YNGyCich2sb3jU5XHOmMLxrelNnPq2LLWGtkZlw/r1OHToIFMhlS5TRihxbceihQvRun55p8bFD8ov/xMaStEEPL9An61XxnW4q7Ivk6mHAVC5zrutVq0aBgwYgE8//ZTJhOkiL0pJY+/eVlRXIJ7mHN68YDIaEHdP0EPP/WY4q44l4u0mddSm/XcR60/dQVKGEXN3X8W6TEEuTpwr7KhSIqURkaFXBlFblAXIC/Obl6V1hcNKo2SpkngWcLN2CJ0Fc/buFTq4RKsuvfKk6lOrnf8eDVmGB0pRo0BWiw6vodILDRWqIvrfyYNcoqcSpa8dO3YM+ZEXm0nGp4SvfxB7L2Jnfd06IT2Qw+FwOI8Plp5jEdREI9tVcNhun9azdvEc27LFZHAMtFiDRseMZdn9WzWAejQneEfwBDIZjSh5d4PiKZrEiwqlUQOf0/DTG1HwnlCYw4YT9ZEIWTL5B0gpdjF29RU0dkbY8hRvsR3KTcpPuqwfxnk6kBuau9qm0z494wrLI/R2fZzwoBHniSsJuuRQUrtCO2V1oUo35jvs0y5hGg4c2IXpOyIBjTDALhJWGt26dcPlS5fw22+/OTzH6942/Pf6JaQvk424HxJq6zn4+UneJfmBqd+MQaXAFKRanMuaRXQqE+BTNNt9evToYav8RBF0k0HoHKQmJaJOnXp4HilerJhNZXX60G4c2y2pNTIMrsvg/mF+3bacqfNHlkZIbxJxN8QojLHtaRgO/NIZrOLImwOGs6Dps0ARF9UziKVLl9qW9e4ezDTbGTdv3nRQJdmXdc0wCDOqbh4eD2SuHxsbC5Nd5RqLRosmTZowJaXIC82EKjXFS5fH6VMnkR+Jj5eq5xAFzdcwt/YGhN4VBgXt2j386yaHw+Fwsoe1X9ZBKKmNGpcR1KoiM8cMUTzWessKhZhMttLfIpY0IXXbV+W8Kubde/egtQvgREXHw9tdjcOGcsiw6KB1MZo0Zwn9oWBvN/QuHYcDgT0UQaJixYuz5TLlK7G3dE3W7Kgtknp61j7ngQPyKXRFufLlHYJNnGeH76dMwdOAXq9HYKBz/7GnDR404jxxli9frhhQOWOpzygM9/oV0wstxftv9cKfFf/FV+5Ko+XXViRjzaVMlPhkBUp8thaDZqywbdu129Ek90XNP+ze46ZyBuVhEBV1G41e6phvGisyRqZUPb05Erdb/4zlGUKJendIkuNzwa9iqd9n6Hp+ALyGUyQo9/m3FDQSZ7eiblyBXuc8uPGs4+Xphb2bVqO4tSPk5SMFDWuWcF3h7ZK6Ai6HdkWUf2PEe1XE33UOK7bHeUQgJVMIfJisqiN73qsH1Lwyhpks55ff3YPi5e0Nd09PRYnXVaukmczug75i9/Tby8xwrp4rVqwY/vrrLzRs0tSp0mjZoRsYu/YMNp6+g+DQgiyV7H6hz93NSxkoLlW5FqZ2AG79r6FtZtbHL9Bm9E1UqK70bsgPnD8vpPPRZ1/R/SrejOyJYv5AwzTHoD2Hw+FwHg+sspRskqRsASlluNA7P8GtmFCdc93Cmey+cdtXZc+2OKTJmKIFP8SrpiLKF7I2WGeOHURWcWX69K0EE35Pb4fOCZMxKbUP5EXSDu7biQMHDuDw4cNQWYsoFPJzR8uCCQjVSN6C3bp3t70PCgK5e3hifeBY6X2ahW3brrnji/VCWyRCKXZUbj07Ffu6tWuxYsUKlCjuevKJ8/TytKR7xcfHo3lzqTLh0wwPGnHyBTmZJR8OfBf9R65A4YaDmEdOsVZfYNiMg2gP1wGfn3ZeR432PdlytDVtjVJYRHNdf9Ntxf60TSzj+aBQiW0f/2AWrNm9e7diG6kOHgevdpZKpL7VrTveebcfpmW8iUsmIaBBVNFdxCDPxZjlOw7uqiz4hdXF1NXXULZCtTxfvO9FCYG/9NQU1Kiet+c/K3h5CgounVX+TWaVImQ66QpfDy32l52MrZUWMN8Ys9V00mRR48+MZnhjfzVMWH8WF+4mY2XtfbgR2NrpcYrGbUbZKrVQsnTEMyGHpYos7u4einK+/fv3ty2XrixU+DNmZSLyhmMVRdEkPyEhAadPWt02qYNqLdVqtlhw7IZQfnj7hWhodTqF91BuoedQwGjr1q3wCxRSz0R89WYMbgy8VhV4p2dn/L7rMvwClWmGRpMRBQoVzldeVFs2CxUAs9ISsbrX/QfSOBwOh/PwOHP6FKYMe8f2+NwRKVVbH1wCBd8SislsWyOocc3WiI4pNcFmDyFCqiMqnU7U0ApeezasfYiG+l24iNKKTbeibmNsaj+2PC+9A5vgEVkxcwRGjJ+C9h07AWqtrf/jniV5EhEFCxVmlhJ0DtRfKVO+IgqHCSlyhLshlt1P2ZKBuDRlig8FjU6dOpXt51SyZEm88soreOONN1j1VM6zgS097SkJGnl6emabbvc0wYNGnKeCHt27oXKVKjYpaoECQvnxGd/8hJG+y10+L7bCayhZqSauW41033zrLXZfOkT503+vvgpDPx6KSuVKPZTzVZmNKFasIGJjY9CwYUOFemHHjh3ZDkypQb99WxnQyis0I7Pi779tj69evYpr8Y7m1297rMYQr8Vo5SYYLB8pORImM2xKmdxCF8SgkFC2HH3ziqJT8jxRrJiQ0pdkLZ9uHwR4wUWJ3At3U5jShYhJycSfh2/iSMCb+COjNT5JHmrbb96ea8jUB+NioWyqr1nMMBgy810J9/v9HWu0OsUMo5uHZDKt0Wjx0bjpqN/6FcVMp0irVq3YPc16xsfFKUoWE4l25YCpI3o/QaNhw4axa9OMGTMcysCGaIWOOtHBb69NXSTHw8sH3n4BbGY2v2Fc3+dJnwKHw+FwrNhXjVo2XVLnyEmKE4I0WRqhzdR4+aNK1aqKogs00eGjEvopWbAbhOuFQNC7dYBwjTIbQGXneWnykuwMmr35AfoM/w5hZcsz025CrVLBN/2S4jnUfleoWAEtWrSwTRLJi0h4GIRCNl5WCyZ5PyAv1K1bF+vWrbuv53LyH6KS/mkJGj1LPJ85JJynDirzfOK4VDaUiI8VGsR3RszHxUn/oVPCFEz3/Qbz09tja1Zt236ml8cgfeMM1G/QAHv37EFRP+DyF8rjz2SinDmYPQJIvbIDHmENHXxPckvKufU4/NYRCsHgZIwHvlMJRr5y88H9+/ezYJKzUpN0Gz58OCtrKRIXF8fSy7p2fQ0//vgDXnzxxWzPQQwY0OtSlJtmaGICK8O+zkSBjEuA1Ufwj+M6wHpK77wjzWLllmuXL+L29cvQaTTZ5pk/y5ApOPH5559j/T8bmTG2nA7VCqN0qDcWH3BUxZDSJchLj7+p3AcpxdANfirn5s7peiFA54zWx19BjR4xiI25B39/fzzNkMJIq9UplEY6rdRRoABM3ZYdEHsvCps3bmC/c2czOvbpemJ6muhlRPh76liA6n6VRmKlxtAiyt++N6nPrDZJ7YvfxmK7577xweeo26Iddq1bxkyxKfe9YMGCT7S0vbxz7n1j1RM7D86zC/2n7+e/xuE8Smggmt8Ld4iTpiJ+3s6tBFKShYYnOrCqogBMcLCkdK1RowZ+nTMLPX49gEyLfdDIF4Yzy1DEDyiacFeRvpahUVbRLODpqEbdu3UT/BoKE7UFUg6hsGmrYju1t/PmzmXtTbVaddg1Qe/mOOFYp1wBLD12976DRpxnC7HdEPvbnMcHDxpxnlrENDOikCdwUiuYCTfVH8ERQwReTZBM0gJbD8Cx+YNwfChQJftMOHitaIKFBRage/fu93Ve+g1vsPvjhjIIDYhDiYB0NmilAbyoONqxY6fToFHnLl3Z/fz58zFhwgRb2l5QkJTyMmvWLJdBo8jISFapSTQ6JGNeChqx8yrnmBY3Y2MMfn1NWB64KQg/fghUqVnH6bnlhpVzpyEoKPC5nQFo3LgxDh48iOrVq+NOdCwSkiSViTjbVqmIHyZ0EjwHJm86j7hUqbMlBoxEEi3OAwf2VdTkBKUcR5A/cDb+Orkd4GmGfr8UA5J3FuUSdXFZrxcinyR1F0vYy7EPJKmt6WnTt0gznykZRnjdp2lmWHi4bdleSVQ0LBywZsaZLI4BrfY932f3pIj8Z9NqfDP8PQx6rS4G/bybpSrmBUrDW79+A9566008CHQNkT5XR6+oQE+wdAEOJ6/Qf5aqmdJvlcPJj1BfjQL3+TWlhM5NjslqNi1nwxKhYtrr3Xpgn7vkp+hsIklvbQ/PmcJZSrxGZbb9V3UbhH51mkU5QF/hoSy7btCTivoKW1ZBaq91AUIfNiDtArw0QmVZEWq+aeAvBgGonXeTKY1Eftx4N9eV0jjPPqKC/3kdZzxJeNCI89Ry7tw5lgZFsxNe2khkLHsZ7pYUtq2G7jya6Q9gS9YLtv1De/0Ilf8gAJdzPHbPnj3uP2hkTsaApE+xNrMxe1w8qDOqVKmCP//8E2XLCoN4UZVgz/p1a23LrmZVlixZgkWLFjlVQo0ZOw6LFi7ApUuXFKXKr127Bmfan8QMi4Nyy2Qy3vfFePfGlez+ndc74nmEOkC1atViy6HBgbh2UUg5c0X/xiUxcYOdj0AuyNS6NtUWib9Nv4GWzFeL0hNJov3UodbALyBQoTRyk80u2cruenjagkzOgkbi/0B6nuN/x2i2IK50W+ZtllfkgSx7vyKVzNfqQrDkM2ZPgSIl8O3ff8EymR7tw8mVE1C505csiFW0aFH23nJi27Zt6NbtrQcOGpHasWL1Wtb89UMO22d3BTpzP2zOfSAGjEJDQ58prwfO0w9dx6mtEL0tCxUqhPzIhPHjMX/+77bH8XdvQVkPDdi14W8U+WAe9vko2yNn7eO9ZGliYGlGS7zlsZEtZxmymBDdYNHgsLGC4jmHdA1sy8GqeGjVFqdtnlg9zT57PMOkha5QdcU6KmgR7OT8IhOAEydOICwszGEb5/mDK1SfHDxoxHlqEQMwAmFwH5qMqLF6FPISLijf+vyIWrGLFM9pn/AjWuj34zOveSijvYGDJcciOPkowqOlSmtE1iRg3759CA8Pd5AC50S6xc0WMCKq166DnYt3sNQTStvy8w/EDz9MxdSp3+eYYkaDRZFSpUrj8uVLtoums1mXmNhYphIQI/E3btxgxxArWIh4qdLwum49xp4Clh4Ddl8DTEYj6zRlpKUxb5cHwX6Q/jxSvlw5LF/7L1KTEuHp4+t0cOTjrsPnbcphUh4CRyazBXeSMrE1sxZedHMc0IsMG/wBdnd8H5MnT8Hkyd/hwoULKFOmDJ4m1qz4k91PmDARa9asVgRT5++8CK1OSLgkH4RmL3eyKWTs/aQMBiOavvwqtq0TfL7UGg0MZN5lR3pAqTybUR86dAifffopW6bKdcVKlVNsV0EKeGl0ruXU9BspL7vUZFzbDkAIGlF6KgWN5IpDMUhEqkMKdHl7e7MB+cMy8qfAmqvx/KuCUM6Gq7RADkcOBX/FgJH9b5nDyQ+IfowUOKLfaX5MVQsICEDBIlLfUCNT9shTsLV2ASPCWb+RFNAihdTS5EStapVxcggwMElo31wRYwmA4fYxwHpKotKoQo06uGvte5bQSG3TyWKD8O3q2+hbV5r8SkqIx92oW4iIiADWS8c2mIWMgsqV7RodznNLfioY8rzBjbA5zxQZ7ddhfyRw4jYQrE7Ea+6b0EhH/kISm7PqoGX8Lxhe/ABOhnTH3ogfHI6j1QCDX6+H999/H92698Bnn32W42tfvnwZCxcsxOgUoaKEyLmzZ9j94MGD2eCuUk1B/ZST2TVtp8by8y8EAyYxYES4KgseGxeviMSTwiS8x0QU/1gyxSZOBL2BkX7zmOn1GwuB6buE9fO++xKXL5x9YNnn8+ppZF8l7+T+nejXqgr2/+fahNHXPefPunsd6fM8eC0OP229hD5Jo3HO6PpzDvAQFGZp1lL09lX88gOjRo9hyrmcWLt2jfTAquoRA0Yiejc3ppARkSuGqDoZdaIjqtTEhAUbWIAjOcN5x0MeeMqJr0aNYv/rT18Evu8ANG3XFe6elOQmobJIQSO1bNke34Ag7PtIepxkdFf8l7t06eLwHDIxZfsmCd4VpCp7GJAS0s3DCxqr91N20Pndr/8b5/lC/C2LKdMcTn5E/H3mZ0VDQmws6x/SJIpciStWbRV9++S8GOA8JbRxWSm4dN5UgjWxpwwl4V+lKdKNamzIklRFruhVW+WgNPps2iL4BQszITpIn2WW1g+xGXpFQI4CRoR9W6JTW1CunHIihvN8w4NGTw7e0+M8U4RXb4m604BmM4XH3/pMwwL/kbga3M5h38WH72Hs2jMYu/Y0tpVkOSEK9g0EmmEFzmxdyFLLcmL58uV4u08PqO2EuFkaD9QsKpTc/mXmL9i7TSgD/uabzlNIdHo3tOvWjylDqDPwzaRJtm0+fv7ZBo08vbxtFaAK+AAn4zXwLFvPYT8xZ50dU2a4e/64oFx5kNk1Pz8/1Kvn+JrPG6T8SE8XFFc/j6a0SNeQz1F2+HpIyi+xyhpx2STNNh40VMDyjOa2x8OaAqNHj2aqmvzqBzB2zGj8LavyR51geYcgvHQEu5cHMUMKFGDVxpwpsMjTSIRUN9920OHnV0m1l8B+0yNn/Y0SZSqw10nNdN7xuHpVqLSYG36dPYcF4755GRjSGCiqVXo2ECXvStcOlSX7zs51IebLaKTaqBi4kKpIDik2xo4VquaIPkxTvs9evUjQez958mSOSsEfGl/E1leEqorZIQ/UZQd9rytXrnQY4HDyDinPunXrxrzryKOEChekpAip2dl9Tx9++CFT+NC1qXPnzg5BRgqm2t9yE9TNK1yVxsnPPA2/T72bHkZDFswmI4KtlWtFSCVqaDfO4TnxFudVbUnxLDIptQ9qxy5Au4RpuFHlI8zP6qTYt2WyfSkHgV/S5JMa1okdKmJRSFAIpcs8kTTmdJjNplwp2iPjgX79lBOxnOebh6Wo5uQdHjTiPHPQoGjP0fMoPVFaR32Ay8EdnO6fYTCj9/5y2FBN8hMSGdAAODoU+Kr2FTQMz74jERMTC50GSLIoZ1E/a+uPQ4OBpT2Ao+t+YWVFiYsXLzoco2SZCMzZchohRYqzGST5ALp4ANCsYY0c1RAvlTUiYVYN3BkFrI7LObVuwIABtuUsaynX++k0nTlzJt8qWp4U4oCrcs3s/YQ6V5eqkrzXpBS6UpTRyuu1iqGAr9ThyjRKAb/JqT1ty10TvsWw5CHYkil4KjUpBXhqsjDjx6nscX6tPCKfWZw0aRLavvyywifosx8XoMMrUsc1NLQAvvzZcSDr4e2neI+p9y5iWGMD3q8PpF7bZ1t//k4yRqw8hV+2S95mL1eWvCs+X5JzoMSZlxHxS5V10BqVg/fwaCko5p15I9vjyU4DepUBU76fqggQk/rwU2sq3PXrZHQuIHpwNGnWMsdzpn3JYy077ty+iYZBN+Hn5vo3o1YJnh+vvvoqcsOOHTvQqVMnljLLeTAoYHT69Gn8+++/WLt2LftscxpYDRkyBGvWrGGTG9u3b2e/JWff3W+//YaoqCjb7ZVXXnmE74TD4dwPBQoWgoEFjcwILVAAGSc25Pic3PbrKN1MHkSSk5rhPOgfa/Z36mkksiBDaNcJs0rPvDNzEzSidoY8PDkcET7x9OTgQSPOM+t3lK6XAiZ3/eoydc254E4oV9B5RarjWaWwrLTzWZTetYFdUmzFKXdj4qBTU9U0ZcWq9zInwmgR/mqd6hfDF9MWoUm7rnj9daEqhQgNeGPu3WWzM6JaSAwauWuB6yOAlS9uwd3RAA47VxQE6NKw5m2gfjHXQaVu7rKEcQCffPKJbbAdH30HAwcPxoN4TNlX9nieEavceXlnXz7dTafB8LblMbBZGRQP9ET14gGswhrdqhbzh85a3cQeKoG7Fu0xL11S0r2dRD8QgX9W/mFbzq9Se3mgh/yB/t20iS3Tb58qkfn4BUAlk9rTQFblJB3K3cNDEWCJvnzYtkwxOdHDaP5eRyVRg9KSPN/3hU65Pu87d6IcfH9K3xU+8wyDCddjU2GWVUxTm50rBAmV2fH7uXDxokI9RUGC7777ji3/OO1HrH8X2D2A/MiE/7shK8tlqtiWLVuyVSnKuXrpbI77lAnVQp12BzVMmxHkmfPs35UrV5wG2jh54+zZs/jnn38wZ84c1KkjVLqcPn06C1C7Snkmf7xff/0V33//PZo1a4aaNWuy4NCePXuYd5+zylHijZc15nDyH1QQwpiVxRQ7Or0e5cuUyvE5rQvlfO13Bhldi5gznBeK+D1D6oOInkaZRmlwr5Ip8Mnnjwb+uVG0F/UnP8+c3xvn+SEvFgKchwsPGnGeWW5H3UWDGcA/5RbgWNjnMKu0uFzsXfSsF8YG45+0ElJfRGZuv4xP9/qiUZpQAcwZtauUwZw5v6J69Rr477//bKaxNJC7dvUKqod54KbZMWjyWsI37D497hYKhZVClbpNWRqXHCrVnpQo5JyrNVrMmDHDljrWvqK0X6g3UPjCFKfnF+qWaltek9HI6T4DPJfalskLJTAwkM1AkbkiKY1092mCTYNVMlrmBqfKSiW///57rmZGvN20KOiX9wHagOj+GJ3ynmLdtymCAmmQ9SdQtW6jfJsHrrN6Ex05ckSRqsYM3Q0G5l207b/NtuASpW96etvXihE8juQBkfHjhNQtokwwsG3NMqev3yXi/ppBOl9CowJWZTTByoymOGMMx+Irgbh4Lxm/7rqK/+24glcSpjBzfMKgcR089MmQlEMi3UO2sfdUoGgJvNqlq+07pMCLKeY82pQD6ocB7omCyi8pKdFpyWIy0W7evHmuO1x3z+9VPN6bVRlL01tiV8QM27ql3YxY9w5Yat4nTSW1U07woNGDsXfvXhbYEas0Ei1atGDX3/37navkDh8+zILGtJ8I+YQUL16cHU8OpbAFBwfjhRdewNy5c3P8vuj3RO2I/MbhcB4t9L/89895SIi5x4IvFSsqq5s5I9D9/tLu5MqjOx45+wuJPn4HrsbZ1hVSS5Mfmbog7Ny0Ntc2COPGOabacZ5faJxRqVKlJ30azyU8aMR5ZiGfhz3XgBtuVRHrUx1/1j2B42Gf27YHeukxtKVSFUTcSNUiLHotusR/g0Sz0tT2YK9LiDj6Lm5ePIrZc+YAxgwcGuYN8/ZPsWvHNoR1+cTpuRwxlhcWVIB/YAhTUNj7ScgVFxqNFkHGq7gyXKhUtKwHsDWzJjPZzrC4Nk72UEmD5o+SHc27u7r/i0KaWKd+RuKMs+iBk1co8EQ+TBzlZ9KoUSMmxX5QRrS1/oZywc/pr7H7V6ztarFSEbke1D9uFi8WpOf2iofJU6YgIT4OWp0OMTHRrIP5xx9/ICsrk82s2kPqPNHbh6hTXird+2UL4OyngMaUDo2dNKiLh2Am7e8p/a++/PLLHM9bHBxr3dwxKHkYBid/grbx0/FnTFn8tvsabiUI53LCWBblY/5iyxqz64AN+TzY08jvLHtPIQWLsEGC3vq+qcJP52KSMf7d6+fZ/Z2oKGRkpCuClBs2bHBqEO4qwABjJr6rLKi9CIoZvJk4EZ+lDMLCe1JHrWphoJo1q/LzZrmXjPOg0YNBii6q6mT/26fgvyu1F62n3w4Fm+RQZVD5c8gja9myZUzRRp5HH3zwAVMxZcfEiRPZBIh4K1asGJ5VKLXy7bffRuHChdnnSQUfBg0axIKyBAXmqGgGVXry8vJi+/Xs2dNBAUalw+29oyg1l8PJLSHBQfj712k4c2QfK1hQrHj2xUdMqfGsMMaD8KHnUiT65aYfYrGpbUXe91xuW74W0oFNCIkTjPbq2IUYqHj8oIVZOM8W1C7l5MvIeTTwoBHnmWX8+PFsoCn69Bg1ygAQEezthtdqSf4xcg4ZK6JqrKTKEWlUEvioIRAeXhID2oYz75jPXgSC2g7CVkMd236byBnXShEIncYCXmYWMHL38EJSirIsPXUcKX9bVBqtfRsIDwT+6iWs65M0BvPSO+Cz5EGKlBc59UKFwICz7b3cVmGs90xJiVVU8sORN8y5yTPn5B76PE0PQeXj5abFl3kIHFFw0b1ABH74exeqN2qNoydO5mtjX/lg80ZkJG5tGI0I7xj2f5EHkrIyM6HVKoNGGlMGviowH8UuS2mbXzeWZjaJcqFAofjt8HJTBkW91EJa2KvVpevA+AkyQzQXiOb4PnWVaabZUSBJCIxRqpyQuiYFUHzShQ69we46NXfub3Bz90BCfALuRcfY1B3uWinIvGTuNFvKQpnylZj6kaD7tm3bKlITxQHsL7/8gkuXpMCTiCVDmh0mzpjCbcv/XHBttrxq1SoM+zTnKpMc53z++edOjajlt3Pnzj3Sc/jqq6/QoEEDVK9enQU/yD9LTId0xRdffMHS38Tbs+pZRemVpO4iL0IKXtN/Z+bMmUxxTIUf6BpGBvKkQKTPUVROnj9/Hh06OPopUoBO7h310Uey0okcTg6IVXlNRkOuJvo0XgHZFi0YWM5x0sKeQFUiQjOFNOPscDcIQdTCsZtt6wqopXbFrHZH6bLlWFCVnZtGw1SNIjEaqc0heNCIw8kf8KAR55mFZlFp9vvbwT1xYt92l/tVoaTpbEg2O1aceCHcHWmpqfAzC7O0NPbzrqw0oS1bwAfL+gtVxG6hMNrG/4iwQOEv5xsYhEy7Btw99iBM3wFv7SqBL3RjWfUzkXiz9GBVZlOMTe3r1Ng40yQEixZltFGsH+f9M36bNht7LmWiw1yg6hTgVom+Thvm3JTZ5uQe+lzT05QBwvvF003LfI9yAxlTmj0LIKRwMXj7+SMz48nlgdMgK7u0KBpsGoxmqPTCf6138xKY3RXY3B+KSmlUFSYuNoapj+RV01bsPYEWSbPwlWUYPhryMftDeugsSJVVbCEsKjWSMpQBPPJXIEqQMY8VXYjzWdsffpyOWbNm2YIuhOcLXXP1GYiBXDdDLFYcvcVS11YcuWVT3oieDzqTlGJK7Fj/B0KLhiE6JhqffDzUtn7/HSlFz896iaLrnd7NjQ1giY8//thWaY29f4uFDRwCgkMxf/58p+qG1GRZCTcAf8sq8mUHmSxP/u7bHPfjSiPn0HdFfkXZ3UqWLMl8huxVg5S2SN+5Kz85Wk9pjuLvQITUrtl50JFn0s2bN7P971JVRqriJr89i1DaHqmLNm3ahCZNmrDUvjZt2mDz5s24desWRowYwZRWpNJ67bXXEBERgbp167I0c0oPjIyMVByPVL5y7yhSJnE4uaVDO8FDKD7mLgu6UPuZHRaTMdsU9QL+3jm+ZmSKO/yQsy9SgYTdbCLnTJJ0TDerCt6otrbJdvOa5LNWIizMqfKIB404nPwBDxpxnmmookzkpXP4ZnBPxN69jbULfnEYtJzatw3vVvFEywoF8Glrpc8RUTlWktWKRIRYsGTZciRa4z5RZslIlwg+Ppvda8nwxMoZYynow2qwAa2Xjx+OHz+meE61c5Ikt7BWGhRkWrSoHisZGhOkOHrppZcczstNLQyAp2UpK150dv8PNxKAFv8D1pwBTkQBBrPy7y+mvoSGKN8L58EgCfa1izkbC+cW8j0iTy5ndKkhqWUaxP0Gn/SrbFnv5s7Kzj8p3nrrLVy+LFUrs4cGtGOOaFB8yHIEvvQRKhUEDhvKoVLSWkzcchO+dbtK1V/UGsRnUhDGgsi4NOZFti9aiJrcMQdj/s6LGP/+S/g740VUjPkTzeOE4A6RCMcBrc5oTTMTZX70/+vjPCXnp5+ms0EgUTSPaTglY9aw4LJ7VjSO0Z+RvGYi43H8ZqLw3ixChz7KvxH2lRY80Ih9A4HQIsXZcxWfmWyQQB7fa9euY0EjCrKJKUdilTRRXUTG7AcOHIC7p9CZJ3Nk++DzwX3K6oe/piurZx0Nfcfp++PpaQ/uf0Y+Q9nd6BpNqhYK/lAgQm5yTt8jBXmcQQMyGniJPnwEKWAokEHHc8WxY8eY1x0Fhp5nKCC3ceNGlhZBqaFyKOBD1eyWLl3q9LdNAXG6btmnBlLAltoGUnWRmiu/es5x8iftrEGjVfNmsJRksdCDK1QaLZo2bepyu59fzsHeRSnNoElVKlEHqf9nWxZ//sVj/0HV69/Az0NSCZ+J98Zd9/LYVe4XXDh+EJfOK1WT1FZduyr0V+wDqPbpuBwO58mQL/JQfvrpJ9ZoUke3atWqLIeeTBidMW/ePPTpoxwQU4dGLrukhnvUqFGYPXs261yR3Jpmhck8i/N88b///Q8vv/wyOnbsiIEdhc5xmcq1EFGtNlvOSE/DN0N6o9krb+Gdz4WUFBqQR12/gulHpBn//5n7or9aCAQR4X6Z+G3RXPhtp0DPBYyUGRHX1p7Gn/+sYssRcrkQdSAt3lBbshBUoDAuXbzAyh/TrOTx48cRlAgUUXpjM2akveH0vdGMpj3/BPbBgvgARBulju2V4PZQqxw7s/ZVccSGmlc/e/jpaUWKFWeDOleVrR4WBeyMtFel1WMTehRIeNKeRs6qt5UsUw6FioexoFGiQQja+FRtjax9v6JzwmTbfgFNeiFp33IhMFGxDaZvu4KqRf1sARc5gS36497udpjtv5Y9vmwqhs2ZL6CF2wEkGRybPI+su07LEX/78zx82KurogNLA2/xfdRr0Ag7tNXz9BkcMlZQVJEh/jt9Cx/H90OBJMFjyKLS4FroK6h76TNb5URDViZOnzyueJ7FLAVpCvkC7du3Q2iBQrhy8TxrI0mZIg5URcURlVqnW+lK0nmTkoRUE1S6nQYidyIv2rbdMEkVKEU6nabqcp2wN7CXwh8tp0GvOKDmQaMHo3z58mzCoG/fviw9in6PAwYMwBtvvGFL9yDlCxmfkwk/9aVIAUMef0OHDmXeR6QGonQoChiRGkZUipHyiB5T20Dty4QJE1h1zUcN9dHi45UKt0cJBcJ271YGR7ODUtLod0ufvTNoPZ1/dHS0YoBL/VJK83vzzTcVCqyBAweiRo0a7LugCnaU4kcpalTdjsPJDeIkH3Hx3Dm0rlgQ8/c6FlOQQ5UTXWF0YXkgxyNyF1L9lQGdYEhp4LsNVdFQL7RT5W7PRTE3yTPUL/E0FtXajoKBYRjTNnv/JZaqLpvjsm+bORzOcxo0otkZ6shQ54dmyX744Qe0bt2azYK5ii5T40vbRRw6+99+i2nTpjH5fXh4OMsvp2OeOXOGl499DiE/ATKTFWcIp3/1IWasOcCWL58R1D4au8H8gqmjkVa0KTxLCcGlibEdoX9pCBpfH4FSMSvYugIJe+GjjmGm2XJeM/6NYVaTWfKhkbPXUAW1zRkwa4WZ26NHj7J7Cmr+UlrYhxQW/2W+gMFei3HZVBTTXQSN7Nm+7zA2ZtV3WO8sYESSeuq0yhEHx6VLW0+E81A7eDTwJ2+ahwWp4tadjEKbSoWw5GAkQn3cUNjPnQWJxG98RFxPTKDv1sfP5nPzpHAVtLoam44/t5FqQjKuPlhuuMN+Kq0bUxdZyglpoM4CRiKrGij/k+8mjcS1kHb4cq+kmHjdfSPauO2GSS1I4u35fvc9fPahNxuUiz5f5Bl0zFo17eqdeLjXyd5jalXIl+gY/bXtcdeEbzHTTEEnqc2KTTfbAkYEVXkkz4d0XTA8DDEI8QZGaX6DqRqw9BjwxbRFmDiwG6JuSd4xI1sC6QZg0pYo9Pp4DG4eFwbEYoDL3gvHNyDYwdC7ffv2bOImY+93QG2gVPQqmOA6VbVe3HxcDW4HsfkVzYDljBw1Gh8N+JCpaER40OjBWbRoEQsUUWCIAtFkWk19HhH63qmPRB47IlOnTrXtS+lm1Cf6+eefFQFRmsAbMmQI+46oHaAgBgWnHjV5CeA8SXL67coH8vQd0IQQPUdMZRWhPq9cYUHP69+/PzMVf95VXZzc2y+IqDVq1C8djLUfNUS76bts6xe/WwdvzXFR8MCOQt452xJok28hw03pAepjkXzukizKFLcFssIJi46oUb6J48SR09fhvpocTr7kiaeniZ0SmhmtUKECCx55enoqTNHsoSCRPBdcfvGkBpoCT1T9htQl1CDTbBvJ81eudF1KnfNsQ8FC+m38+OOPCC8rlSZNiothaSY+/lJJUaPRgOP7tiP6zzGKY4z55wqan30H0WZ/nDeWQOUr4/Gv2tHvo8VnGxRKuRPDrXXPASzLaIVhayJxJzEDA8bNwKlTp9h6+t1TGlqbuGlMYUHVr6rGLEGbeKnEtT32ky/dv3U07R7pJfivyMuWUnpK48aSSbc9vMF++NBXFX/PeWWj+8XfU49udUqwKoAfNC2NLjWLsWvj6A4VFfuZ06LZYJEGivLqYg+LnCqyiAMtZ74oFo0eutbDMP+WFFQgYvyrOez76U/L4VldkOTfD+8nfqF4/I3PdDTVH7GlhRG1i0mzqO7FhM/xlVek9Kxq1aVAq1rnenB3KbgD/iy3HBFapY8JsedWDoocldB5vxr6qm1dWY8oLOkOlAoCylSpKby+ivyGXkStmAXIsOgxsa2wb5nKNREQFMiWY2KUZuAiOr107lTpSaxEQu1un9rASUOpbANGIluzpLLvzip3jRs7hqU4cR4upFBZvHgxq4RH6U/0vXl7eyuqc9H/Tp6OQm0gBYUo1YoCyGTSLFeVknqJJjHomCkpKex7o0DGo1ZHPg1QAI2uraTecwatp8CoqOwTA0bXr19niq2cfJ5owpSUeg9a3Yrz/CAPLkaUFRQ9leyk6hRIyi1quw4ltWH2qNRqZKQkwnfH94hZ+z1uTHsLpdWSuqmwOtrl8TfeCM51QRDuYcTh5E+eaG+AUhIoL79FixbSCanV7PHevXtdPo86NFTqlCSMFBg6ffq0bdvVq1dZ51V+TJJmU6Ps6pg0mKHZVvmN82xCv4s7kVeRFC/Mis/46iOUKF4chizJ3O/ODSGvmqhmkhRtIrVjF6J1/E8oG7MS36VaS5vZSd/l0Cxi1j3pmMS0LRdZ2XDVlTWwTAa7RcSsxFlTSds+6XBUxS3wk0qB1ymu3OZetJzD/oU1QiNu1HqjSBGhPnbt2rVdNsqUukLeGZyHS9ly5ZCR/niUPjqNGgMaSbOBv+8VAheFipZQKA8eBnQtJjWnM5WJiPiaJ08KAVIFmtx3Di+n6XE7xHnacm7YkNXA6fqgFCmoMVWjrP5F/ej169fZHvv4SIO/DNHQ08pf/kIaTyv9XmhVZpTKOAi1xQi11Whb5Pezju/5ntnf5gdhsaqQkt1KsHV0S7MIA4QfOgJvHquHxiVJHQkMTf4YMZYAlIv5m20nVZJGo4XBIHTOI2/dRue+kqqB0Bcqi7vlOkPjI5Q7JubMmcPuhw8XFF7tE35EbthlcAzu2dOqVSvFY6404jxtkPdQy5YtmTLLPvBO/U1SfvXu3VsRMKKUNlL0imXFs4MCdNT35d4tnNwi78NREPlBsc/YoDbMniqVK7PX9XLXIfX0FpjTk+Dn7QEflaA2StdLv98sjTJQGhhSCClJufNVpInLvo5WohwO53kOGtEsKHlUyJVCBD12NmtJUEUKmlWj8r4LFy5kPiH169dnvgyE+Ly8HJMkwRRYEm/y0s+cZwsKnNy+cQ3vt6mBsf06s3U9e/bE2aP7naZO3j60CfXCnBgNuUCziZKBnFTPuiqktMi5pS2MVUp7rhwprpF+w++92w7IsPpApETB4OnoP3LEIASAtG0XsHLBgwYNzvb4pEDiszwPHze9HtG3H18p6sLBUuDyQpKQMkFVtR520IgGRgT50LlCrOR102rGTJA6goIHRt9CuX6tg3eyn6V8UX8w18fSQ5LJ+2REwjPjJlRmA4qmHsBEb+m9HBkMHB6sYpVniOk/CJ4jzIOpWnfbfp3ctqCm7hyWW97E/3zHs3UBqWeYf9nWwP45ns8LsQsxJrUfCxA1PjcAw1ecxOv7qyI8Zi0+Sv4UFWL+wn+ZtVE5oiA2pVTGxr5AkdbvKo5xzFAW90YD7uosNqNLPmm/zp7F/NvmbjuHl7r2ZPsV6vk9LN4hKPrBfPQYMpqtK1pUCjJeNgrB5dwgn1mmwPfL5YXPhiCVhTN40IjzNEIG+GJa344dO3Djxg38888/LJhUtmxZjBw5kgWMunTpgkOHDrFAEvVvqd9JN/F/QZOXpIan/+eVK1fYfpQS2L17d4cJJw4nN4pw+ZhFrAKaclIod0/ef8SaAQ0f+DU/blcRZpNZoXIvpr+LZGta2lqD5Jl0B0pvzFMnjmPSwO6s2ltOUB+UsurKTgJmuXOfLw4nv/DU6Y7JuJEG+dWqVWNlT0liTbJgMjy+X8iEkAYx4o06A5xnEwoKHrF6kpw/cQg1a9dBxYoVcen0MfwyaiALQs7+ehi6vPYGgoODcXDbRrhd3opO1bIfSPnpjMxAW5XqqLigcqht6zpWu9p/T6k0yIllfp+hgFqqXDEq5T0Yfy2HL/q0wE/ffeX0Oa3drOo6jY6lofzww9QcX4fz8KlRtQpuXb3wWF+zilZ6PfICohsZ3T5MKL2SOpAv3huD5H+cByTJDJZm0eVG2JTGQR5z6saSgfyD8JvvKHzoucxhfb0Yx5RNIgvKwOgrhxrglYOCUX6QWpoNpb999SIW3L5yQrH/pk1KE/qpvkLHtnZosqJDrTVnoITmDn5ok/NMMFVEXJLR2mH92kwhlfSdpFHol/glBiZ/iu8z+zhUNXsl4Xvmr/bDCTWSNT74auRIpKakoGCxcOalFRhaANVbt1c8p8Wr3di1ITolC/VadkCAB/B+kqOfFNu3vGNQWqdSqqjWviOoFcUUKaJSlaqKfXjQiPM0QoVUDh48iJIlSzIlEand27RpwwJG5MlE6YFkQL569Wo2iUl91EKFCtluZHgtphUtWbKE9V+p7zF+/HgWNJo1S0ol53ByQpzco98aFRIS2fZJU7yhO4TY9T+wxys+aICzY19CZWvwKDsS9ixh91UNgufnBx5Smzo+YwjUodVhMhmhUjkfOh5OFYz4iXGJ3WzL3mk30b5DB/bcG5cEf72FCxe5PA8xJfZiDGDWPDwfSA6H8xQHjWhQTgNq+4EMPc5tBSe6cFLJ0kuXLrHH4vPyckxqxCnnXH7jPLvQ70UkPjbaVhFl18ZVSE1OZAEkmsURy1XTzErt8ECMtfOKURwzyNGvRc6iiUOy3X7RmH01CaKa7jzcVVIaHZGSloaJlf7DvN9+dfocUj8wUh9usICTNypWrIA71y/j6jnBO+ZxMNpbCqSfupWIQsXCXXrc3C/RMXFoXhpoUgrwOe08pYm8Onz9Ax2qax24lLPH0wp/ZWqVM2oGZ+JFt8MIUDmmFaemS8a0OeFhEFQz1WTBtgyL0DG/fP4UC3aElSqLshUq4397JdVUbsjUBaJXgDBoFGmgc/T6+SLlo2yPc94kBGJmpQsqSVdcK/u6bdnDU/BpMmTGI66aUvWUaVaj1IC5WJZZDSklGsKz7Re4YHJ+LWpWLhQfNi0NLZkpWVmd0ZgFqoYkDbWl11GqTa/ekoTy/Nkz7J5XT+M87VAglCr4knKIJphIXbRp0yacOHFC4SXl7Cb6S1EBin379rHKvpTqRsFzmrjkBtic+wkakXqeJkPlaWZaizRBo1ar4KHP2Z+OUtwSdy1G1IKP0T5aaMsHeS22bX/nTx00bl4wm024cUWqsCnnXJakWDVaJCWUPiMOv8+fj0JFimLxD4K6tWNHR88kEbk/G/dU43DyD0/030heLzVr1sR///1nW0cNMT0mRVFuIPkvmXjSTA5B/hoUHJIfkzyK9u/fn+tjcp59yAh0+Igv2QwNNZY0mK5QqTL2bBTM0uPjYlhQk/DxE1RAWo0aX7Qph9phAVjpPxSzfMfZ0lxeC09hBtp5LQ26JkMwyT5qiMh2v/c8luN2vGN6zi2zYCA8/03przzYcxH6NSqJ5YVlsl5WsYnzpKDBxM6Nq/Bl73ZIiHVeRexhE+onmTpfj0uDT3BBW7W+hwWpiPzkE4EmZVCToGCR3t1doTQivj3gmCrXw11Z9ayq1nnnVM7IwpvYfYjasWS3u1bZxIUHeyHExw1Tql2C2YXRc5Baqsr2asJk7MiqDtWxGfj1119x7fIFXDhzEidN0oxqbjBpPBBlVKoJG+sdU1YfJv7mKBR6oS0mb7uBpAwDDgQplUnE+PVnYXQXUmKSgipAW9q579PA5mXYfZEAD4ztWAluBsHD4rBRKCqwIrOZzTOK2uTf58+zPbdYCcmnjcN5lhgzZgyrWkdBIOq7cjiPCwqsrF2rbC9F7ue3SAo6WMzIun0epjShDXRTSX1OlVbHJvlNRhNuXruc4/HkVXsLXVvNxntXL1/CmZPHWb9BHhiyR17lmgdTOZz8wxMP4VLp0dmzZ2P+/PmsAsX777/PBvRUTY2gVDSahREZO3Ysm9mhXHBKM6I8cPJOePddwd+BBu2DBw/G119/zWTCFFCiYxQuXFhRBYfzfEMV+sZ/PQ6vvipUKCKzyiZNmuL374VZkAnjBV+SEV+NtJlmEz7uOnSqXhR/b7uKVm77cSGkEyvlPXLCTPzwWX+kZ+MZU/baCpTU3EQZjeT18VHyZygTvQKT0wS/EWKe30jb8tjC+9H30jto7nMF4zZLASSRl+OnY3ZaJ1zwlaqh9fP8G2HBXihgkFViKSNVYuI8fuQqx3u3HCtqPQqOR3xjW957ORaFwyNw9Zpzn5n7JSMzA21lvulpsZHOg0Zu7sjMUgaN0k2Ozc+r7lscOp4jvJyr6IiwIC/4GwTVj5cqw2G7h10hwL6NSmJIi7LIDO+EJQ2cd3w1MgPQM8ZS6Jk4Dn7JR1mVzzIVq6F6A8m3gSivuYLc0N9nveJxL481eBi877fB6fpr/jWhf/EDZBjMmLTBqjjMA8NaS4Fsfw9lOl9KkmOA7oMkoZ22V5QlJSYoqk5xpRHnWYL6qtTn5IoIzuOExjovv/yy020UuH8QzsuKoIWoBEuEzDuXWNCIlEYlSpZy+rzSIYKfElFNKxWRUaVEM2UUBYAoWJRTIEhUUZF32FtvvfVA74XD4Tw8nngr9/rrr2Py5MlM5ks54CRtJ3NB0cg6MjISUVFRtv3j4+NZ551Sitq2bctURJQrXqGCVEb9008/xUcffYR+/fqxSlFU4YeOKY9eczj2hIcJ5cjIJ4sk5ESFchGIvq0cCO9YuxTjNhrQ59gb2IuW+PxEY6QkpQAZifhqxAiXx9cl38GWwPfwb+CHivUGO38VKgN+Nbgd1rj3R7cPvsKi8wWwxNQL2y7TDBLgqVKmwo1PfQeDk4XKTcSNwJfYvR4y1YensqQ55/FCajaxo3Tj8nncufHoSyunuhVGcbV07bwDf8TF5656SW45sP8A3pYVNDt9/LDDPhREcHNzx/Ili/HXX39j924hTSt++3x2r9eoUPrvdiz4WkErBWCa6A6x+3c9VuBAYA9bFbLFfl/gF98JaFg6GD8VWYQSMULwZcwmM27P/QipZ3fYjuHn7Yn23tfxUsWCTCWoIBtVoH3Fs4vWoGz56i+gSfvXkBUtfH+VtRexzF+quDZ7n+vPyjtYmfblrjKw97zc/1P09lit2Eb+aLkhWBWPxpDer5zIIu1wv1TRXUKApx6964ehR90ScNcpVVlRv7tOG/zqK8lfrVbjVvDw9UOjRoKikuBBIw6Hw3l03K/qTeyj7MusgRvpQsrbu8ZFaBy7DpbMVGbbYDaZoLbzNBLbryIBXvi3suCDNCtFCmgZjGaFcXdOiEEj8gvjhVk4nPzDEw8aEQMGDGBqIapMQWlkderUsW3btm0byyEXmTp1qm1fyitft26dwqNGjMCTIom2kwySyp7SxYfDyY4WzZuzewpEilAg8+YlaZaciL8rVOqb/dsC1Pt4EybN345zZ8/gyKGD6N+/n8vj//TTDFSzZoxRapszhnkKA+m604GFGT2g0epgyMrC1M/74Uos8EPC2zgXlX3j+9P1uuz+llEof5qUxRvd/IDW2vmZ+81wfNy1ySN/PaPWG909JHXLrmg9PHSuK5CROWvxEiWwYMHCPL0nEzS2kvBrV//teB5GI4qXisDL3fpjx65d2GU1hNUFC0HaykX8Ud5aqVcuh//Ac7ktthOqicfuwLexyG8E6utPoo3bHrwaoUbFKKFUPFHMD+jRvhli1n6P5CNr0VRzHqdPn8KMrz5E47IhTCVoT6y30qRZxD517ePkoRjYMRx3Aqrgsmd56AIEY/xPvebDRy2U4P7nHNDvT0AzTHmsy6Fd2b1H1l1M8p7m8Fq1dWdQv35rdK8jBJWGtRIUPhQUywk3VRbq6k5iqGfuv7PcoLP2DMoW8EH5QkqPP6oCaMlSlh2X46mn1Akfttx72Nfo0u8T9H77HaQY1SjYYwo2Xkp+qOfK4XA4HAkPD4/7CraI3lwJqUYU/yoR2k+BsBZDUDBICCCR0iglOdHBhkEDs21CwKwSXlesqCaSF+sGMcDE1XscTv6C/yM5HCsUfKSS9PIgJJWipkZSDhlj//nnn3maOSHId+u41T+XUtuc8cnEVQgbDxyIpApNG9k6GshbzGY0bNgIlZq8jjM3MqBXO5+tV6fHY/Z345CVmYHJVxrj5z3AxPP183SenEfDv5v+Zd4Xg4dkb4r+MOkYolQ0mUtWB7IEPxqR1WvWskomb775Jm5ERuKLLz7P3cEtZtQrk4VS0atYSfjNmS/g2OH9zpVG7h6o9EJDtnzgwEH0/mQcTKlCilNKphF661/JYAYGeC5Ba/0eFkyRU0gTiwb647bH3hlKBWBCBjB69CjAbETcvzPxyZutcOK4tL8z9pWZnLv3CmBVuem46xmGE7eSmb8DccUkGH/uKDkZby8DQkILoFt3KdWUOBr+Jbu/kOiD1903YXjRXVjrP8i2fW2NzYjxrYUKhX2ZwijASzDvbl0x52IQTfRHEBnyMgZ6LcFIr1moqVV+Zs6Qp7e6ooC3a+PU69Ygun/yVYdtZIpdt6QbChYugi59h8LHP4BF/U6eOIltcb5wKxyBGfsdU9s4HA6H83Cganz3418o9mkNBkGlbjILgRtRuUSG21kZ6eya3volQdFOaKzKXLMFsKgc2w5NHkea5H9EUGVsDoeTf+BBIw5HBpWkF6umET4+Prh+6TySE+PxYbva6Fa3BPZt/QdeXpLJcF6kv+TDlR0ZGVm4bh1TTbaWUS1WVBiY3rgRyYJY29f9iSaezqs3xR/fjIz0NJw6uBsrFvwPH/4NnIrLudQq59FTr15dpqL8epygMqPA3qPG3axUdew2VEPWPsnriPj+++8xcKBUtYvKRsfFCT4G2XJ+OWbrpFTLd5NGolKooxH2vXv3kGUwsFlKMsO+c/ceytesC5278B+qZdmHb61K9oWHgYDzf+F/fhMURprOqHlljOJxhy/XKTqZEREReDMHP4RErwdToDbWHcFd3zpo8uoniEoCPL280K9fX9t2o9oNWTrBAHvTyuVMNdXC7xIq6SQ/pXS9Yyl7QqNWsSBSdqlqI3zn4XRR4Tt423M15hbOuWz3UK9F6OC2Ldt93i96yuU2tVqDoR9/jIgUx+pvhFfJGrh04RyatH8dWp0elWo3xLZtW5Bh5t0NDofDedQEBASgYkXX1X5dIaqT5Oln1G4HBwrFEqjfazELAaJ/NgheeqkFmkItUxpZrM91h9C/IU/CTJMqz56jD7toB4fDeXB4L47DyQZRUvvzqEFIiBGqXt28eum+/bFIxZTcNxFew4Edge8wb5ZDHu1w/dsOODdaSI8TvbuaNWummHUhA3jy8iLmfNUfN39SKhqIpINC9bcpn7yNzPR0Nks0htQXnHwlHSfmTvr8ofq7rF3wM1KTlKq4ZI9w5pkj558jgkJk/fr1SExMZB1F+r3JIS+5nLh6TGnszI4dMQn952xn6iERUhcFhBYSUi0NBqg1Gnh4esOvujBTWTj1kG0mMikD+Gyl69QnOUEpJ23LZScB4dVb2DwZFi/+g72vQQMHssfZfc5bK8yzpZCJzPEdm6tzCNfeRoEkSV2VkZ6O0NBQfGL1uD4SLpnaZ1ltktSWLBZMIo6GfQGDVpn+5QwvWcnkPqGnmRcS3TbW3oYE74o4WWwQDpT62tZhFzkb3FlhvE/P0auMmOY7GVeC2+Ny6KsY06Eigr3dUL2ID84Fd8Kl4A4ITL/k8lySE2Lh5u6OSmXDcWvOe6gLyfCUOF1RyM/zDQhk9+4enihWIhzcyYjD4XDyL3L1vI+v0C5RH1KsTk394auXLuDyBamwQnylT7H3qhA02nM5Fjftso8raS8hMknow+YFsobgcDj5Cx404nBywYl929GjRw+8/sabaNa8OZo2bXrfx6LGOC0LOHH+LvNmmb5bSPWRB6L8/f0dcsDJl0u+rv87vRTb33DfiN5vdHFQeYim3pz8AXXCipcIx84NK5ip5MPij5++wT070/brIR1YmhcFC0SWx0YAhnRWeYUCR7rbW9GxImCZLNwK+gD16+ec0jjmjmPlllhVEDZeSkGlUUJqpdlswd5Ld3EoqAWOJehhMhphNBhgVmlgMAlhhDPGcNvzqUhXbBrwS/lD+MXzW5yUfLxdEmf2R89B41hwlf4fFy5cwJtvvqGYOTUZlZXb5EQFvoj9ZZVpauHFw1gAZVPlJRjUKPs0sUSz4N9D3L0Txf6nny+/hyaLw3GpYDdb0Mpg/apDEw9AbRbO52po7qoadq4heChVKeoHb09JObhvrxCwOlliKC4V6gGPrHtY7Dcc9XXHsSewNzxUmcx4nwJELNAUB3T9XXguKbk0liw0ujwMnzcNxYqsJsycW6syQ290nUJmysyAl4cHRnzxBcYO+wjuxhSUCJSq5pjUevQcOpqpjOQcPyEF+TgcDoeTvyBVEUHtaGhoAds6Z31RUZVsCaqE7ZetSiMqzLIPyLDokAGhP2vmw0wO55mB/5s5nBwgg2CCUl+W/LEY/23e/MDHvHLlCt5aokODGcDXm8FM24msrCwsX670HFkw/zfFY6ruRlw6Jxl0t1ZtgWXHdJQIC0NCglAhi1KhgoKCHvhcOQ+f2bNmsntjNsGMvJCRlsrux70nBA3j7t1B5KVziPFxnK3baaiBWwuEYEVGShzW9zFgZR9p+4qhZZCeno6//vor29cs7y6ry+uEsM/XoeTw9ViZLJTnPRGvgSo1EkaTESmyt33aWNq2HFqiPJo2b8VS926jBKpMAV6anf17N1nUihK+ZcqUcVB12ZeBl7Nr/Z/4Z4lkqG1WaXEs7AucKvUlTpb4GAWCs/dVWBTf3GF2NDgkBDeT9TZ1zTeDujO/B8Iz645Nzm9W5W4GdtP0z1AjZT9eq1UMCQjEvINgfmXffTZAsV+cdyXU15/AYv8RKKyJsa0XU/3qzAlB0TBlueSS9/5El/1KQ3Cz2vV5ZWWmo0iRIiz4GeDvh/jou+jbuKT0WjDB3VOZvpuclASVNu+zzRwOh8N5PNBk5ZTvv0fk9au4fOkiW0fXefug0bBhgpq0cOHCTJ2kDwlTbE8ySybYHqpHn4bP4XAeDzxoxOHkAHmjEKQ0eliEh4ejbsNmyAquhYuXLqNAgQI2ZUSXLkq1EFUAlNOpUyd2v2njP1g9oAES9y7D7Ck/4dutwInjx5hZYYGCBRGbG18azhOhVatWqF7rhWwVMHmBjCtrvVCHTfVRwGXTsl/xRffWSHUXKpQR7d2225Yz7wh+NJ8OUQYdiLo+QmfR/ndoT7o1UPWij+tUJntaVnNHcOFQzD4gpHoSS/y+sC137Er/MQsS42JgMgmBno3K7Ccst/O2nhHdURE0kkOB3qo1a8NkcP0571i3HKvm/4xTxQRfp0MlxyJTF4gLhXuze2dl7gmq4kbEaoqhb1/Bx0gepL1y8Tx+HjUQS2ZMwMkDu3DMakMmn3k1q3NX4Wb/lg1Y8dM4qFUqZorfZymYXxmRScakVgwa16lu+yNJeRgNjc75ZyVHZ3Rd4SzuXpQtZTasRAlkpCax8xrn/TNbV0AdhwYvCdcokXt3bsMjjKcbcDgcTn6FrutDhwxBly5SujYpjeRVzE6ePIl33nlH4Z/kWbae4jhxFqkdqq61a8A5HM5TCw8acTg5QOoBSi952DnWS5f8gf/++w8lS0qz9M4g9ZC8opvI+++/jypF/fH36N6wGDLZuvHjx7P7AP8AZGUK6zj5E51Oz1K1HgYUfHJzc0dmZgZmjhmM4IJCOpOcnhFScGFU+vvsXvsALUByoqCO8zUK97lha1ZtnC3zrmJdQU2sbVkVcwolihdHZkaaInXPFFDBtly0sxCcIE4X/QCX00NsQQxnGLKykJaSlK2xMwXa9vm/jXXVN+FSQUfz7J99J9qW9wb1xmr/wVjgO4I9zjIYWQoomXfKFU2tW7fGnk2rsWbh/9jjSGvGl6gyYu/L6m2UW+h93L4umWiToikpTlIUUeBL9EuyZ8qJMhg5ciSGfTw0x9eJ95I+b3tUFhMCA4VgWoUKFXB09xbE3r2NGO+abF2UOQSFo/62exLvanCefm7cuIG3336bKSzomlOiRAkMGjQIsbGya5hK5fT2nbWwBREWFuawfdKkSU/oXXE4SuRBIvuy95UqVVIoj8hWwTNJ8s0jXor/yba87ixYYQQOh/P0w3tyHM4TgmZofK1mg9lx/tw5HDp0SLHuzJkz+OknoWGmDixx9epVmyqqctUqKFZMUplw8h9mswkpiQ+n/Dh5BZFKbdy4cVDBgiyZOu2P+pfwT9U1uFRSChbsNNRE5xblnAaNTCo39PtS6fFTs1YtbN26VbHur0whLetIppRelhP/Zb2Q/Q6B5eAfEICE2Gib0qhFixbQ+AhGnIS6YA1oPwWWFf4ZJ4sPRvTtGyhY0LXvUOkyZXAv6obL7Sq1mqX39W1dHYleEaycsD0hFV7CWv9BOB70OnQqE6roLkGjEoI/CfFxbDa2Tt16KFasmO05vXopPcfavSFVVROxqCTj0dzQt0Vl/PbtCEycOBETJk5EjVovIOauIGGiCo8J3hXwZ90TiuekZAJHwkYgxqMCU48VCJeqQ7riWugrrjdahOo2BFVzjL5zG2P6vYr/1gvVdIhfjgE+aVJwa3QHofoOUcCLdzs4Tx+UUl6rVi1cvHgRf/zxBy5duoSZM2eyiZ969erZKk5GRUUpbnPnzmWD7M6dOyuON3bsWMV+H30kVbDkcJ4k8qAQtW32hTLs8cxGmfrDzod6ahwO5wnCe28cTj6HUm/sZ3uoiprYsNNsp/ye+OWnn7Bs2dLHfKacvBBWojg+7y5UEHsYQSOtTodXX30VJw/uwZGdm9h6UutY1DrE+VSBRaVBy8JS5+5QzcnQatVoFvcLwqLXYkOmYH6tsWSi6cudUKqMEIBMSkrCkcOHWTU/ClbaE6DNRN8bAxGgSsQs33EK023iN9+cq/fdTgKWn/cFqg9AkUIFcPrALsyfMkpKx2w4HvFpwEcrhHRRkxmI1JSDWe2GHf+sQunSrgNXRQoVRHK8MlVz76ZVyEhPU5hlE4YsQZ136+pFhdLpdkBTVNJdhp9aSMmTQypESi/9c/kyzJgxw7Ze/H+++ZagXPrqq5FINUj/46xsUsnk0HmGly4LvZtklE/BqS8+/xxhYSWw+a/fYTRk4b3W1di+KxfMwZe7CsFoAktj8xkBnC3Sl/lnsfcaVBFxWR64p5YCXHL+rbwcd/0auDwfCuaJVXbE61Ls3SikXZUC24eNFWDcPwnp1pJxXzSUqvrdTTUjVVZdj8N5Gvjwww+ZuoiqmDZp0gTFixdHmzZtsHnzZmYIPGKEoDykALb8tmrVKrz44osOimIfHx/FflTOnMPJD8j7m/SbT0sT2kpXZLr5u9wmevlxOJynHx404nCeoYoXIuStIiqQOPmTFs2bsbSyr9/rioRYyeMnr9y8egFDOjfC9WtXmXotNTkJ7V9qyar07dm0UrGvl16pbCnZ9xdcMQnBg/eThmNBehu2XDBhF6Lv3UVKSgpeflkKAh04cIDdm8wWBKmFlK8IzR3cvHoFR4O7oZWbUM3rWJBQvayvx9940e2w7bErmv4MDN9eCHAPQLWqVXHq0C6mIPryyy/xwQcfAIXqoPXqWphz2J2ZdRIULGHnYjSwIKorihYpytLdRH6fMhIzRg7E7WuCF1NwSKht2+Uzx3HnxjV8+mYL3Llx1bY+Q+faDPvKxQtswEcpW+QnJkJG9OPHT0AR6/+Q/pNeOrMi2ERpcTnRv2UVVuZYvi8NWtl7N5mwb/NapCQJ5vdXzhzH0l++w/iVUaj+WylmmE0kxkWz1DkW7NF5YuTNnhif+gmOhA23HbP1LKDGVOCeb22naisRCqaJ1xw55+1+wkMSBmLcujPYd0VK3SEqaK/Ayy1vCisO50lCKqKNGzeya5Fori9CAZ9u3bph6dKl7D8t5+7du1i3bp3CA0aE0tHomkCp55S6lp1ZP4fzOBH7kmXKlmWFJVq2bIlvvvnW5f7B0UdcbvPm9Q84nGcG3nPjcJ5ySD1AqWmcp4v+/frhvf79cfbYASz6cRw+HDv9vo6TliwEb8pFlLUFLb6ZNBHffjMJv4wZil8nDcdv2wUzyjQtedFI3kaXLUrvo69SPsTr7v/ixdO9kJQozIYTQaEFUfvFlxCbamBV0QQEpYzZkIVEu9iHvzpFoTiix854xU1IebsYA5QJVttUNKRcIW7evGnbd8vWrWxGX2TjsnlITUpAifBSToMYIhQoiYmKlJ63fL5iNtXDS6j00rRZc/z5vyk4e3QfexwddROFw0ojNTkR4/p3wesfOD/+mePHkOnEP4zM7ocP/wLz589H3Xr1HAab/2/vPuCbKrsHjp8CLZuyKXvvvUEEQUCGImX8GaKyZCMiG14BcYCKIqIo4stWKEOGgiLIFGQPQTYIFGWDlNkW2vw/5+mbkDQdaWmbjt/38wlJ7k1ubi637ZOT85yTNvSOfDy0u4z5YpFEN43Rnk4T1GlhyvN/7/vNtvXN9fsDHgfndu79Q9avXy+v9eotA56v6ZBVlS17brl8/4Ecz99bzqz9XC5ceyAjvlxrpgLe/veGeGfPGen+aKDKmmkUPltsUaZpMuruIIflP/xxUeplamS7/58XwvYFsKpXr160U2DikgbXt2/f7vLjdUqaBoQiC07rct3/a9euSe7cj4PQ+rOvv0M1A9TeoEGDTB00DTT//vvvMnr0aDNFbcqUKU/wroC4Ye3Ae/JE2LhBA5sR1dW0KpDuoUQ2Ar1NaU0g2SBoBCQDWlgTSc+sWbOlZ88e4ukVs4LI4aem9erdV76e8aX5htD6bbdOa9Rghmao6OXBvbvSqGxeWXf6ryi3V+r6SlmXrb8U8PaXbBlEDl8SyZ7bRwoUKyU/Xn2cSWMV+O8VyVlX6/V8E+V2vT3uSIAlLAildCpbQ699tvunjh8z19ZOgtY6IlaZMmWy1ezSzJ579+7JtrWOmVQRKVG8qOw6Hlao85fFs2zLD+3cIkVKVzDHTxUvUUI2zwwrWq2mjx8kM9cdkvMnj8qFv07KYakmmW/ulyLhGqpdvqPd6yIvaK61jaydF//18JFslseFw4/s/T3a/c9fqIhcOPf4ODRo0MB228cn7FhFlLGkx8jX11e6d+9uW2Y9trnz5JEL526YjKJZ11vKhNFvmsyo51q+YIptRxU0On3ssEPQ6MyZM1K8eHH5z1tvSaf070m2VLelz+23HJ4z4W5v222v9I/bMQMqJgEcdwqfSRRe+IL8Ws9Is5C0WLC9IUMe15erVKmSeV6fPn1MrbLIOkECCUX/dpQuU8blx4f/QsQqgzyQwLjp9QEgEWB6GgC4SY8e3WXFihXif/q4qTkTU3u3rjOFkTWDxH56otJvsPXba3Vk73bp37K6WFKnNxlAZ3M61h0K77l/v5RaAz+UQ0NF6hYWebHbIPHyTCvngpzrbuz79QfxbRf19DO1KXsfx9dIu0sCgx7JlH9aOSzX4JBVnTp1ItzWiBEjJCYDWmutoo3Lv7UtX/xVWLp9aGiobNmyRUqXKuXwvHuaamWXvTNsZ3kpNknkUSrHD4Bankfrm0TFmtWUrVRD27Kzd1yrYZIxU2Z5fdCgCOtN2O/z1q1b5fr166a4vn03J51aM3LUKJk1a5btw2u6dGnlTsAtebtXG7lzO8AWBNJjFRT4OBMtvKsX/eXc6RMOU2mstVoOHzost4NSSVOvsCmK9jw9Hj8+VRRT34DESGum6e/XY8fCAtvh6fJcuXLZps6q3377TU6cOCGvvebYLTIiGrDVn6lz587F6X4DsaFZymt/ftzYIDqpIumOOT/rOHkYImZqJ4Ckj6ARALh5asbZ44flwmnHtrSn/zxgC3ZERgs6/3PutBw48Dhjx0qnP2i9jfIVK0vAjWthCz1SydYyM+RG5iqmE5hVE6+wKVn29j0qLyGWVNKohEi1pxtLai/HYInS1vNHLwVJw4YN5Vb19yPcx3uZwrKDsv+vBpIanOE7c73hlMjpwAIyYtQo2bNnj8MUqgkTJphucBGx70z28SefSFQ0UKKZQl3qFJa/z4dl7Lz55pvinS27Q2Hn3Dmds2vs29uvW7ZANNHgcJbHncUafJNJRo0aFWXqvoOMj7OonvnMuai2Pd3f/b/9aqanffJxWDe78G25O3bsKPv377dNkdEaKQEBAWbai5Vp5z1pkmkVbj/IP/Pnfjl1eL8cObDbNr2vYP788teRg5Hu099nTppr++2rr2bMkGHDhsrEP6vKP6mKy8RMjlMt7TPMLJF8wAASK/250rouX375pTx44BhUvXz5snz33XfSrVs3h+UapK1evbpUrlw52u0fPHjQBIPtp7YB7qIZqTHJXtdzt4b3PcmVyTFLrnqaY3LgYtgXMwCSPkZvAOBG+g11jhw55a1uL8gnQ7vJitnT5Oo//jL+NV8Z8HyNKJ8bEhgWeLh29X9BoQhoVsnJQ2Gdrc6dPCJ/52wh66qsMp3ArFlHLxZPIx++6NyB7Iv7HeRslroyZsVh2fwgrI6OqpnmiHmetp6vWaeeGTRmbThGMo4Rab+ulhwp9aGsOeYhD/vfEY8XFknvpSKZxoh8n3WYCSi8kSGsjs+CP9KaVPgPJ00y7aztaX2m8NM9rKydAkuVKiVD7aZ6REQDZ//8dfLxMQsJMbVDdPta1FkvGjQqUyYsuGXNHMiaPYec/GOPbQqJ1QebUsmhQkNkTdX1cvRmRlOPxGW1RsuvF3LIM1+K7D52SXL75DUdzyKb9vLJ8J7y6OEjE9TRLASthWJPA0L6oVS7tuWMIOgVmcKFC8n1y2H1oQL+vWnLNKpTq4bcvf2v3A0Iq2kR3r5Nq2XBggWmXpM9rc1Vv359eZS/kbRdVVTylG1qzq3wwSOVJjXDDiQ9+jOm032bNWtmsvouXLgga9euNcEk/T00btw422O14+TSpUsjzDLasWOHTJ06Vf744w8z/VYDThrEfvnll02tJSCp0b//xdMHyptNHbN1NalU/7TpzwOApI/RGwC42cyZM831/u2bZNnMT0w3NKWd0CKj09nOnT5uOpp9//2ySB/XxtdXtqxeam4f3rnVtvxPCcuOOX5VpE33tyUkdXr5rM4Vae71uL7Ip/dflt9LhbWSvv3ocbHpJVlH2hpslSxe3Lb8frDI9+t2S/lWI+T5/4aKZ/pMkiF/VVl6IpvcCxY5sP+4tPP8RWbvFun7vcjb83bLyJEjI9xva8ZRZBb5+cnKlS7UNCpRQq5dvug0vUunfd27e9sEkTQoYx900W/8M2fOIudOHDbtsrUzktWlf4Plz0JvyKwFq0yRW50O5rKMeWTGxcYSmr++CWZ5e2eVno3Kmq5nkfnr1HGzzxooi6h2hK7TduAxodvRDDVrYV/rMcmQIYNcu/i39Gn2ODvCOl3tr6MHZfNPK6Rz585RFnffu3W9vDM7rFZTi7SONZs8QoIlS7qo/1+BxEi7SGk2pE7H7NChg/l5bNGihQkYaU0m+2m1fn5+JhAc0c+K1izS9doBsXz58vL++++boJH1bwCQ1OjfD4sl8myi4ODgBN0fAPGDoBEAuFnbtm2c6lnoB5GiJUpFWORY070/eL2LXLt8ScqUKeOQCRNerlxhwRCdQuX35ePpTYO3lZE3/AfJ9Va/SaglbJtZvUJlhvekaPfXvixN6VIlbbfnzp0nY8aEBZnsZf5fYKXXUpFc40U+P1lZvt4RlsETWYaMfe2eiHTq2DHSbkaRBZ/ss4I04PPg3h3Z8OMyEzTSgIlq/3//Z9ZdOH9W1n//rXz00UfmGFuzgW5c/tv8n6yY+4Wc++u0xJTfwu9k3f9qPPj6tjbXdwISrnOU0oCVev311821tSaTHoONq8KywI7u2yFvdW0pPRqWkWVfT5YFU942y6PqVKcfrNXWn5aba28Px655efbNjPb/FUisdMrO3LlzzZQ0/X2p2UXr1q2TQ4cOOTyud+/ecv/+fVs3y/DThnfu3Gk6VOlUt6NHj5rfSxTARlKVKpWHhIY4Bo3ypboqRy67VkAeQNLA6A0AEgH95lpbNuu3cqdPn5annnpK8uX1kakje5kPKLs2rDaP+23NEtn8g58cO7BLGjdubKZ3RSX7/6Y8zJkzx2EAt2fTz/LSSy9J/fpPm/sz3x0qd9KHFTWOyuiMs223153LLO3bt7fd79r1VXn//fecnjN/3jz58MMPze07QSKTJ0+O9nX0vcUl7To2ceJE230tWhv6KMQW7MibN6/8888/snTJEodAU8WKFR1aaGfLkUMePQyWQoWLSIGCBWO8HzoVzJoxVKdWWPt57WxnL74H2dasiJYtW5oPsNb71ml/at3SuXL2xBFze9W8L+Xknweizf5SWtC3TPmKcjJbK0nlYZG0ElaXK0+qGyIhwQSNkGxo3bVp06aZnyHqtiCl0i8SQsNlGl0MzS0h6XKZTOg2bdq4bd8AxB1GbwCQSGjWjX4w1xbmav0va+WPnVvl7dd8Zdp/BpgPJjPeHS6zPhgtr77aVX799ddoP4RbC1pas3KGd3xWtv+ywnyzrV171JEjR+Svw3vMVLUDRUbLvhwvOWyjWppjklpCpFjqC9I7fVgWiXpjdTopUOBxraPINGz4jEPHM2vr98hoC3tr1kpc0EwADfjYS50mjdy9fUsyZ/G2Bd7y5cvn9Fz7DADt5mYJCZFHDx9KvvwF5IK//xPtlwaq1B87Npmi58u/mWLqCd28dtlsP75oJpXS/zvrOaCswayKFSvJns1rbcutH4i1losrHyC0UPaMay3N/RO52pn6Rj8XmiyW0FCCRkhWunfvLoMHD+a8RsqenhYuaFrb87DkKVZFatas6TB1E0DSFVb9EgCQ6OiH+D59+8rCRWE1dQIfPO64de9+1N23rKpUqSIbN260FZW+5P+XfDl+sMNjypUrJ882aSp3bv0rh8v3kHtpcsm50y/IYc86kjnwvBRJfclpu/+xfCEPPT83xZhjE7SIKpvGWpg5rthnC1l5pvGUqaN6S84cOSJ8jratD98lTDux/b5xrbTpM0KCouls5wprcPC3n76X9Bkyybpl86RGwxZy4cxxKVGypKz7Za0cOnRY4pq+j4immuk0tTNnzpi6LXrOaLZX//79TdcoZd9SPCoNnq4nH4zqJ1M+tnvNh9clNDQHH64BIBnxiCBoVCHNGfH05CMmkJwwegOAREy7Y1lr3nw4sJMUKFTI1Dua+fXXLj1fAzBazFmNGDkq0selS59eggLvy7TRfaW+7xDxe+qUHK69WHbW3+z02A9u9JaLV2Jeh0eLTruSaZQQNNPo3+tX5ejRsClY4YUPGClrRtKKWVPlwN6wzmpP2srbSgNG6sux/eXLtwfLlUuXTKHczp07SfwULnUO2mkAUANG6tlnn7UFmGrXrmNuu1p3pUL58uZ6453HBbX9c7Y0xVJjE2QEACRO9n9PBjYqIT3Sr5SRGedKeo+wJgoAkgfCwACQiFkzM27evCn+/v5m6lb49vSu+vCDSTJq5AjZsmWL7NrtGPTInSO7HP1jty0wsH/HVqlSr4mEpgrLSrF6lMZbCldsJKNf6iyVKleN1XuxFp12p+1bNzlk3bjCGkj6fd0PMmXKlCfeB830+fPPP6VChQrmvhbP1WXa2juiTmkJ7fz586YNuGaGbdq0yaWpiKpNG19p266deIQctS27l7aAhIaeINMIAJIR/Z1uncKcL2t6eSnTf83tYE+KuwPJCaM3AEjE2rZpI2vWrDEf3jXrKLYBIyvdjq+vr0ya+L7D8rp1asuKOV9IcOA96devn/zx+0bbuiV1j8rWMjPklzPpJHXnLdKpU0dp2LChHDywL8avn1g6qdy5fVv69u0bo+fYZ8lYp/s9Kc0mstYK0kCRbleDNHE9RS82dLqatf6RZqu5UgjbGhTs8H//J+duPLItO5uhjtwJuEXQCACSXaaRcyH4VJaHbtkfAPGD0RsAJGK5cuUyXa7iW7169aRGzVqyd/sWadu2raz7/jvpUqewXL/8jzxKnVHOZW0i//ddWvHIXdkETzTzJClPNbp+/brpfBRTFy5ckMqVq0iTJk3ibF/q169v2m8nJwULFpQJfqfk6l2RGxkryLjR4+X08SMEjQAgGfHy9JTf1iyTNd/OMJcboWEdWy15n3L3rgGIQ+7/KhMA4HZa5HjZ0iWm25rWs3mh1Yuy+scfZN7HY+XQzq2SNn0GKVy4kCQXsZ0ip1O0Dh48EOf7E5NpckmBdus7/69IwYle8qHfV3LtUgezPDFkUAEA4kbf3q9J4YL5ze0TJ05Iz1VZpX72f2VwvyHu3jUAcYiv/AAARuHChU1dHc0G+fGHVXLgwAHZv22DPHr0UO7dCZCHQU/eMQwpg06D1PpbzZ5vJZt/WCylKlSWFStWiLe3t7t3DUh0Nm/ebDI3b926Ze7PnTvX5W6FgDvlzp1bunbtai4tWrSQQ9fTy7AfRVJnCMs4ApA8EDQCANjYF2CuUqWKfDzlU1m3bp0sXrJEFi/2c+u+IWnRrKIc2bLJqrlfyO8b1kqlSpXcvUtArHTr1s0EdSKqgzZgwACzTh8TVzp27CgnT56Ms+0BCUF/DkJDQqVM2bLu3hUAcYw8cQBApIa+Odjdu4AkrESJ4rbbxYoVc+u+AE9ap8vPz08+/fRTW3A9MDBQFi5caIrGxyXdfmLooAjEOGgUGiK16zRw964AiGNkGgEAgHgxYthQ6dajp7t3A4mRdlJ8eM89l1h0caxWrZoJHC1fvty2TG9rwKhq1aq2Zdp+fNKkSVK0aFET+NGul8uWLXPY1k8//SSlSpUy67Uz4blz5xzWh5+edubMGWndurXkyZNHMmXKJDVr1pRff/3V4Tlaj27ixInSo0cP0/VQ92vmzJkxfp/AkwSNQh6F0PAASIbINAIAAPHC09NTxr31H+nQvp27dwWJzaP7ItMyuee1B90V8cwY46dpQGbOnDnSpUsXc3/27NnSvXt3U5PISgNG3377rcyYMUNKliwpW7dulZdfftl0wnzmmWdMB0btUKnT2nr37i179+6VoUOHRvm6d+/eNV0033//fUmbNq3Mnz9fWrVqZQoP22c5ffLJJ/Luu+/KmDFjTKCqX79+5jVLly4d4/cKxCZoZLGEJunOqgAiRigYAADEG8240AKpQFKnwZ9t27bJ+fPnzWX79u1mmVVQUJDJ9tFgUrNmzcyUTK11pI/5+uuvzWO++uorKV68uAnwaDBHA1DR1UPSbKU+ffpIhQoVTCBKA0O6jR9++MHhcRpY6t+/v5QoUUJGjhwpOXPmlE2bNsXT0QAcaYbRzWtXJDgo0N27AiCOkWkEAACAhJUmQ1jGj7teOxY0W+j5558308csFou5rYEZq9OnT5sOlE2bNnV4XnBwsG0K27Fjx6R27doO6+vWrRttptHbb78ta9askUuXLsmjR4/kwYMH4u/v7/A4+2Lzmu3h4+MjV69ejdV7BWJX0yhUStrVsgOQPBA0AgAAQMLSKSyxmCLmbjpFbeDAgeb29OnTnYI7SoM7+fPnd1in08pia9iwYbJ+/Xr5+OOPTRaR1kJq3769CUaFnw4a0Yd4ICHo+fYwOEi8vLzcvSsA4hhBIwAAAMAFzZs3N8Ea/YCsU9DslStXzgSHNANIawlFpGzZsk7Tynbu3Bnla+o0OJ3C1qZNG1twKnzxbMDdrLWMCBoByQ9BIwAAAMAFqVOnNlPMrLftadcyzQp68803TYbP008/LQEBASbokyVLFunatav07dvX1DMaPny4vPbaa7Jv3z4z3S0qWsdIO7Vp8Wv9YD527FgyiJDoWLumETQCkh8KYQMAAAAu0gCQXiKiRao1qKNd1DSrSDOTdLqaFoRX2u3s+++/l5UrV5oC19plTYtnR2XKlCmSLVs2eeqpp0zgSDOcqlWrFi/vDXjSTKPcuXO7e1cAxDEPi1byg4Pbt2+Lt7e3+XYoskEBAABwP/5mJ43/i8DAQDl79qwJnqRLl85t+whEhfM09g4ePGgKvmsWnDWABCB5jJ/INAIAAAAAxJo1UETACEh+CBoBAAAAAJ64phGA5CdR/HRry9IiRYqYNNDatWvL7t27XXqen5+fiWb7+vo6LNcOE7rc/qJzygEAAAAAAJBEgkaLFy+WIUOGyPjx42X//v2mKKAW+Lt69WqUz9NWo9qhon79+hGu1yDRpUuXbJdFixbF0zsAAAAAgJSLjn5A8uX2oJF2hOjVq5d0795dypUrZ7pIZMiQQWbPnh3pc0JCQqRLly4yYcIEKVasWISPSZs2rfj4+Ngu2nUCAAAAABC3CBoByZdbg0bBwcGyb98+adKkyeMdSpXK3N+xY0ekz3vnnXdMO8eePXtG+pjNmzebx5QuXVr69esnN27ciPSxQUFBpnq4/QUAAAAAED0acgPJl1uDRtevXzdZQ3ny5HFYrvcvX74c4XO2bdsms2bNkm+++SbS7erUtPnz58uGDRvkww8/lC1btkiLFi3Ma0Vk0qRJpt2c9VKwYMEnfGcAAAAAkDIQNAKSrzSShNy5c0deeeUVEzDKmTNnpI/r1KmT7XbFihWlUqVKUrx4cZN91LhxY6fHjx492tRVstJMIwJHAAAAABA9pqcByZdbg0Ya+EmdOrVcuXLFYbne1zpE4Z05c8YUwG7VqpXTL6g0adLIiRMnTHAoPK17pK91+vTpCINGWv9ILwAAAACAmCFoBCRfbp2e5uXlJdWrVzfTyOx/4ej9unXrOj2+TJkycvjwYTl48KDt8uKLL0qjRo3M7ciyg/7++29T0yhv3rzx+n4AAAAAIKVhehqQfLm9e5pOC9PpZvPmzZNjx46ZotX37t0z3dTUq6++aqaPqXTp0kmFChUcLlmzZpXMmTOb2xqEunv3rgwfPlx27txpspI0ANW6dWspUaKENGvWzM3vFgAAAElJt27dxMPDQ/r27eu0bsCAAWadPgZIyapVq+aQCAAg+XB7TaOOHTvKtWvXZNy4cab4dZUqVWTt2rW24tj+/v6mo5qrdLrboUOHTBDq1q1bki9fPnnuuefk3XffZQoaAAAAYkyz2f38/OTTTz+V9OnTm2WBgYGycOFCKVSokLt3D3A7/fL+2WefdfduAEiOQSM1cOBAc4mIFq+Oyty5cx3u6x/yX375JU73DwAAAHE7leXBw4i72sa39J6pTXZQTLMotLbm8uXLpUuXLmaZ3taAUdGiRR3KLGjn3pkzZ5ovQ0uVKiVjx46V9u3bm/Xaybd3796yceNGs16f379/f3njjTds29CsJf3i8+mnn5ZPPvlEgoODTZOXqVOniqenZ5wdBwAAkkzQCAAAACmHBozKjXPPl3xH32kmGbxiPgTu0aOHzJkzxxY0mj17timnYP8F56RJk+Tbb7+VGTNmSMmSJWXr1q3y8ssvS65cueSZZ54xQaUCBQrI0qVLJUeOHPL777+bIJLW3ezQoYNtO5s2bTLL9FobuWhmvmbj9+rVK46OAgAAriFoBAAAAERDgz9aZ/P8+fPm/vbt282UNWvQKCgoSCZOnCi//vqrraGLdvDdtm2bfP311yZopJlCEyZMsG1Ts5R27NghS5YscQgaZcuWTb744gtTdkEbwTz//POmXgxBIwBAQiNoBAAAgASfIqYZP+567djQbCEN3mhpBJ1ep7dz5sxpW68ZQffv35emTZs6PE+nl1WtWtV2f/r06SZLSet2PnjwwKzXLCJ75cuXNwEjK8060g7CAAAkNIJGAAAASFBaUyg2U8TcTaeoWetwavDHnnbwVWvWrJH8+fM7rLM2Y9HMpGHDhplaRZqNpB2AJ0+eLLt27XJ4fPjaRXq8dGobAAAJLen9tQYAAADcoHnz5iYzSIM4zZo5ZkqVK1fOBIc0g0inokVEp7Q99dRTpvi1lRbYBgAgsSJoBAAAALhAp4wdO3bMdtueZg1pFtGbb75psoK0+1lAQIAJFGXJkkW6du1qimPPnz/fdPrVekYLFiyQPXv2OHRgAwAgMSFoBAAAALhIA0CReffdd03tI+2i9tdff0nWrFmlWrVqMmbMGLO+T58+cuDAAdMNTbOVOnfubLKOfv755wR8BwAAuM7DopX84OD27dvi7e1tvh2KamAAAADci7/ZSeP/IjAwUM6ePWsyatKlS+e2fQSiwnkKIKW4HYPxU6oE2ysAAAA8kZs3b0qXLl3MAE+zWHr27GkrwByZmTNnSsOGDc1zNLvl1q1bcbJdAACQ/BE0AgAASCI0sHPkyBFZv369rF69WrZu3Sq9e/eO8jnaBl4LOFunSMXVdgEAQPJHTSMAAIAkQAswr1271hROrlGjhln2+eefS8uWLeXjjz+WfPnyRfi8wYMHm+vNmzfH6XYBAEDyR6YRAABAErBjxw4zdcwa2FFNmjSRVKlSya5duxJ8u0FBQaYmgv0FAAAkLwSNAAAAkoDLly9L7ty5HZalSZNGsmfPbtYl9Ha1Q5gW0bReChYsGOt9AAAAiRNBIwAAADcaNWqUKVAd1eX48eOS2IwePdp0XbFeLly44O5dAgAAcYyaRgAAAG40dOhQ6datW5SPKVasmPj4+MjVq1cdlj969Mh0PtN1sRXb7aZNm9ZcAABA8kXQCAAAwI1y5cplLtGpW7eu3Lp1S/bt2yfVq1c3yzZu3CihoaFSu3btWL9+fG0XAAAkfUxPAwAASALKli0rzZs3l169esnu3btl+/btMnDgQOnUqZOtw9k///wjZcqUMeuttC7RwYMH5fTp0+b+4cOHzX3NJHJ1uwAAIGUiaAQAAJBEfPfddyYo1LhxY2nZsqU8/fTTMnPmTNv6hw8fyokTJ+T+/fu2ZTNmzJCqVauaoJBq0KCBuf/DDz+4vF0kLw0bNpTBgwfH+XY3b95sanBp5lpiNHfuXNMpEADgOqanAQAAJBHa0WzhwoWRri9SpIhYLBaHZW+//ba5PMl2UzLN1Hr//fdlzZo1JpNLO81VqVLFBF00yJYQtOaVBmJWrlwZJ9tbvny5eHp6uvz4c+fOSdGiReXAgQPmvQMAUg6CRgAAAEAkwZJ69eqZ7JTJkydLxYoVTTbXL7/8IgMGDEh0Xe1031wJBmmQEAAAVzA9DQAAAG4RHBz55dEj1x/78KFrj42p/v37m+lWWuupXbt2UqpUKSlfvrwMGTJEdu7caXucv7+/tG7dWjJlyiRZsmSRDh06yJUrV2zrNdNLM3QWLFhgssG8vb1Nzag7d+7YHrNs2TITlEqfPr3kyJFDmjRpIvfu3TPPnTdvnqxatcrsi150GpgGtPT24sWL5ZlnnpF06dKZaYY3btyQzp07S/78+SVDhgxmm4sWLYpyepru08SJE6VHjx6SOXNmKVSokMP0RM0yUjqtUV9Tnx8VrYtVqVIls0916tSRP//802H9999/b46jdt/T1/7kk08c1utrhM+q0sCdTi9T1veuGVONGjUy77Ny5cqyY8cOh+fo4/W96Po2bdqYYwMAiBkyjQAAAOAWEydGvq5kSZEuXR7fnzzZOThkVaSITuF6fH/qVBG7sk420czSc6CFwteuXWumpmXMmNFpvbU2jnaZswaMtmzZIo8ePTJZSB07djTBHaszZ86YQMjq1avl33//NYGlDz74wGz/0qVLJtDz0UcfmeCGBpN+++03M9Vw2LBhcuzYMbl9+7bMmTPHlil08eJFc3vUqFEm6KIBHQ3SBAYGmi54I0eONAEsnVb3yiuvSPHixaVWrVqRvl/dxrvvvitjxowxAax+/fqZYFTp0qVN0Eyf++uvv5pgj5eXV5THbvjw4fLZZ5+Jj4+P2V6rVq3k5MmTJgtKu/Tpe9dgmB6j33//3QTnNFCm0/Bi4j//+Y98/PHHUrJkSXNbj6EWfE+TJo3s2rVLevbsKZMmTRJfX1/zfzl+/PgYbR8AQNAIAAAAcKLBBw3aaIHwqGzYsMF0pDt79qwULFjQLJs/f74JruzZs0dq1qxpCy5p5otm8igN5OhzrUEjDTa1bdtWChcubNZrhpCVZh8FBQWZIEx4mjGkz7OngSar119/3UynW7JkSZRBIy2ArsEbpQGnTz/9VDZt2mSCRrly5TLLNbAT0T6Ep8GZpk2bmtuaJVWgQAFZsWKFCRZNmTLF1IIaO3asWa/ZW0ePHjXT/2IaNNL3+fzzz5vbEyZMMMdc/9/0/0yDVtoVcMSIEbbX0QCVBo8AAK4jaAQAAAC3GDMm8nWpwhVRGD488sd6eDjej4vGYOELikdGs4A0WGQNGKly5cqZTCRdZw0a6TQsa8BI5c2bV65evWpu69QqDaRooKhZs2by3HPPSfv27SVbtmzRvn6NGjUc7oeEhJipZhok0sLdwcHBJuCkU7SiotPJrHTqlwaHrPsXU3Xr1rXd1qwoDTzpsVB6rZlZ9rRu1NSpU82+p06d2uXXsd9nPZ5K91mDRvo6mrUVfr8IGgFAzFDTCAAAAG6hs5wiu6RJ4/pjw9d+juxxMaFTnjR4ElfFrsMXqNZta/aR0kDJ+vXr5eeffzYBp88//9wEWjR7KTrhp85pxo5m2Wi2kGYKHTx40ASiNHgU2/1LaPra4YN2WuQ7qn3W5yh37TMAJFcEjQAAAIBwNENGgy3Tp083BanDu3XrlrkuW7asXLhwwVysdLqVrtcAkKs06KEZNzrNSlvba90gndKl9LZm4bhCi1BrJs/LL79sMpiKFStm6gk9CWsNI1f3wb5IuNZv0tfX46T0Wvcx/D7r9DFrlpFOh9Mpe1anTp2S+xEVqYqCvo7WNYpsvwAAriFoBAAAAERAA0YaKNFaQNrxS4MXOu1p2rRptilY2uVMp5V16dJF9u/fb4pGv/rqq6aIdPipY5HR4IZOKdu7d6/pxKZdwa5du2YLtOjUtkOHDsmJEyfk+vXrEWbd2GdIadaS1u/Rfe3Tp49DJ7fYyJ07t6mrpFO7dFsBAQFRPv6dd94x9Zq0a5rWKcqZM6cpRq2GDh1q1mnRbQ0mac2jL774wqEO07PPPmuWafBMj0nfvn2dMqGiM2jQILO/Wihb/990e0xNA4CYI2gEAAAARECzdDQQpG3dNdhRoUIFU+BZgx5fffWVLUNo1apVpv5QgwYNTBBJn7d48WKXX0e7nG3dutUUo9aMm7feest0M2vRooVZ36tXLzNdTYNQmoUTPlPHnj63WrVqJkuqYcOGpjaRNWATW9qNTANlX3/9teTLl8+pJlF42hXujTfeMF3cLl++LD/++KMtW0n3Test+fn5meM5btw4E2SyL4Kt711rRNWvX19eeuklE1CKriZTeHXq1JFvvvnGTNXTjKt169aZYwMAiBkPi6tV/lIQbWnq7e1tvkXRP+IAACBx4m920vi/0DbwWp+naNGipi08kBhxngJIKW7HYPxEphEAAAAAAACcEDQCAAAAAACAE4JGAAAAAAAAcELQCAAAAAAAAE4IGgEAACBB0H8FiRnnJwA4I2gEAACAeOXp6Wmu79+/7+5dASJlPT+t5ysAQCSNu3cAAAAAyVvq1Kkla9ascvXqVXM/Q4YM4uHh4e7dAmwZRhow0vNTz1M9XwEAYQgaAQAAIN75+PiYa2vgCEhsNGBkPU8BAGEIGgEAACDeaWZR3rx5JXfu3PLw4UN37w7gQKekkWEEAM4IGgEAACDB6AdzPpwDAJA0JIpC2NOnT5ciRYpIunTppHbt2rJ7926Xnufn52e+tfL19XWalzxu3DjzbVb69OmlSZMmcurUqXjaewAAAAAAgOTH7UGjxYsXy5AhQ2T8+PGyf/9+qVy5sjRr1iza+e7nzp2TYcOGSf369Z3WffTRRzJt2jSZMWOG7Nq1SzJmzGi2GRgYGI/vBAAAAAAAIPlwe9BoypQp0qtXL+nevbuUK1fOBHq0o8bs2bMjfU5ISIh06dJFJkyYIMWKFXPKMpo6daq89dZb0rp1a6lUqZLMnz9fLl68KCtXrkyAdwQAAAAAAJD0ubWmUXBwsOzbt09Gjx5tW5YqVSoznWzHjh2RPu+dd94xRRR79uwpv/32m8O6s2fPyuXLl802rLy9vc20N91mp06dnLYXFBRkLlYBAQHm+vbt20/8HgEAQPyx/q3WL43gXtb/A8ZPAAAkn/GTW4NG169fN1lDefLkcViu948fPx7hc7Zt2yazZs2SgwcPRrheA0bWbYTfpnVdeJMmTTJZS+EVLFjQ5fcCAADc586dO+ZLIrj3/0AxfgIAIPmMn9IktTf0yiuvyDfffCM5c+aMs+1qppPWVbIKDQ2VmzdvSo4cOUyh7biM5ulA6sKFC5IlS5Y4225yxLFyHcfKNRwn13GsXMexcv9x0m/IdHyQL1++ON0uYk7/D/T/OHPmzIyf3IRj5RqOk+s4Vq7jWLmG45T0xk9uDRpp4Edbrl65csVhud738fFxevyZM2dMAexWrVo5BHhUmjRp5MSJE7bn6Ta0e5r9NqtUqRLhfqRNm9Zc7GXNmlXii/6H8wPiGo6V6zhWruE4uY5j5TqOlXuPExlGiYOWGChQoEC8bZ+fM9dxrFzDcXIdx8p1HCvXcJySzvjJrYWwvby8pHr16rJhwwaHIJDer1u3rtPjy5QpI4cPHzZT06yXF198URo1amRuaxSuaNGiJnBkv02N0GkXtYi2CQAAAAAAgEQ4PU2nhXXt2lVq1KghtWrVMp3P7t27Z7qpqVdffVXy589v6g6lS5dOKlSoEGFGkP3ywYMHy3vvvSclS5Y0QaSxY8eatCtfX98EfncAAAAAAABJk9uDRh07dpRr167JuHHjTKFqnUK2du1aWyFrf39/k+4cEyNGjDCBp969e8utW7fk6aefNtvUoJM76RS48ePHO02FgzOOles4Vq7hOLmOY+U6jpVrOE54Epw/ruNYuYbj5DqOles4Vq7hOCW9Y+VhoUctAAAAAAAAElNNIwAAAAAAACROBI0AAAAAAADghKARAAAAAAAAnBA0AgAAAAAAgBOCRglo+vTpUqRIEdPFrXbt2rJ7925371Ki8/bbb4uHh4fDpUyZMpLSbd26VVq1aiX58uUzx2TlypUO67WevXYgzJs3r6RPn16aNGkip06dkpQoumPVrVs3p3OsefPmktJMmjRJatasKZkzZ5bcuXOLr6+vnDhxwuExgYGBMmDAAMmRI4dkypRJ2rVrJ1euXJGUxpVj1bBhQ6fzqm/fvpLSfPXVV1KpUiXJkiWLudStW1d+/vln23rOKcQG46foMX6KGOMn1zF+cg3jJ9cxfko+YyeCRglk8eLFMmTIENMyb//+/VK5cmVp1qyZXL161d27luiUL19eLl2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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "alg = 'SSLALM'\n", - "os.makedirs(os.path.dirname(f\"./plots/{alg}/{DATASET}/\"), exist_ok=True)\n", + "from itertools import product\n", + "import os\n", "\n", - "f1tr_time = plot_time(\n", - " stats_train[alg], lb, round_step=0.0005, f_ylim=(0.4, 0.77), c_ylim=(-0.12, 0.12)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "./plots/SSLALM/income_OK/train_time_income_OK\n" - ] - } - ], - "source": [ - "f1tr_time.savefig(\n", - " f\"./plots/{alg}/{DATASET}/train_time_{DATASET}\"\n", - ")\n", - "print(f\"./plots/{alg}/{DATASET}/train_time_{DATASET}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Test**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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EhFw/T8YYY4wVDzw8jTHGGCshqPZQjx49sGDBAqSmpprddu/ePfz222948cUXzeb/+OOPaN68uRgC9SCnTp0SAYzAwMAC33YmiY6Ohk6nQ9myZc3m0zS9htbQ/LwsX1DDESnjzNvbW/mrWLFiHp5p6XYv7CaOHD5gEWybOm06evXujZ07d1kECU+fPo20tDSR7figbELGGGOsoHCmEWOMMVaC0JCkdu3aiUyT6dOno2rVqjh//rwYulSrVi1MnjxZWZYOVqmA8uzZsy3WQweshw8fFkOYKMBA05R1Mnz4cDFsjhVfBTUckbKhTO9D7ycOHOVCegJcfq4Dp6h0DP5yENb+uRZnz54Vn88pn0wWAaGtW7agZctWOHLksLgLZXuNaaWDgxoI8ADKVaqJl5ZcRXJyMhwdHZEScRneQTUAB/PXlDHGGHtYHDRijDHGSpCaNWvi6NGjmDJlCoYOHSqKJ9NBKGWV/PLLL3Bzc1OWpawSuo2KKGdHQQK6ndZDQ5Ao+ERBo+zDoFjB8vf3h0ajEUPITNG0rVpDND+3yxfkcER6j3Btq7z57bcVuLTsOUzrDTQpD+xYuFbMp453VH/KPzAInds1xP/8tyIu/Th2LHwNbYe+j7LuOizMqlmuN6hwXOuIyu9txGMfLUfPhPWYUXerdOPbnIHEGGOsYPHwNMYYY6yEodbpy5YtE8OT9Hq9yC7aunUrzpw5Y7bcSy+9hJSUFDG0KLtmzZrh0KFDuH//vhjqduHCBZFZwkGCwkXZPTRccMeOHco8eg1pum3btlbvQ/NNlydUCNva8jwc0b7GvSQFjI5n1sFtXVlETdNg7vq94rYDe3fi0z5O+KP9VvSsDQxrpEO3lIVwW1YZDSt7iGVi9F6oFv03htz/QkxHO1WCd8VyyDA4gEasnfv5JWzYsAF37tyx6/NkjDFWcnCmEWOMMVbCffrppyKQREGgVq1aiUAAK7oom+uFF15AixYtxOs1Z84cMQxJ7qY2YsQIlC9fXgwbI+PGjUOnTp3EMMMnnnhCZIgdO3YMixcvNlsvD0e0j5CQEFGLaNlnYxA9FfgvvQVGJUwRt630fh+9Lz2D14e0xNym1rO/KLPIsf8sVImqYvX2halDxB85bRiGRYuXYNhhIDWTs44YY4w9PA4aMcYYY6WAHHBgRd+wYcMQFRUlMsQoW6xJkybYvHmzUuw6NDTULPBHNaxWrFiBjz76CJMmTRJDFKlzWoMGDczWy8MR7aN9h45Qp9zD0Y8CUCVqo9ltT8fPkq5UA+7EXcJJbR00driMv3zfVpYZl/gOzmZaDxhl1zhmFX594kNM63VaTFOWIGWv0ZBHxhhjLD9UBm6/YIHOxFGqfnx8PLy8vOy9OYwxxh4xygq4ceOGOHDOXiyYFa3Xg3+ziw5+LcwlJSWJItX0nt0x3hejnH7J9X3d1JlY32AdAuKPoOmtr/L82CH+/ZD+SjyefvY5ODs5Ys2aNXleB2OMsZIrL7/ZnJ/OGGOMMcZYHo0aPRpXrlyBSqXCl18ZAzuzPv9C1AB77eXRaNqsORo2b5angBFJ0Tui55mh+NxjrtXbQz57HDc+boVf6+1EkO6exe3fpwzGsrdaYOPfG/Dnn3+KDDPGGGMsPzjTyAo+U8YYY6UbZxoVLZxpVDyUtteCgkWy8uUr4M6d28r8319wwdMN0/DurQFY7fY/s/t5ODtg+ahWaFbJR0z3m7cfZ8PiH/h4O31fgv7pvahQvjKcHSyHmy3cfg6fb7+lTC+I7ovhG8rC08MDVy9dEMPUqBteZmYmXF1dH+q5M8YYKz2/2VzTiDHGGGOMsXzqN+IV3L50CjsPHsN9nROcy9fB0w0v4bYu0CJgdHl6b4uAz99vdMDatWux8Le1ePHdz/Dh+nNWH8c7sAb8KlezuR2vdm+Afy/G4UxYgpg+E18GXqN+FNcPhUTi6sGtuBpyVRTE37VzZwE8c8YYY6UBB40YY4wxxhjLQ62iffv2iesvffQlmrXrgJm7+2LkXxFiXtDwr9A4OhHxBk+z+4W8mAYHKxlCpEyZMti+9je06dEfMwa2xsW7CfjlkJQ1ZEiKQeiCkXBJSnzgtq1+tR1qf7RZXF9Ufbkyf8TPp3Hr89Fo0aIljh07KoqnHzhw4CH+FxhjjJUWXNOIMcYYY4yxXPL09MTjjz+OPs+OQdNuAzFzd4zFMtkDRvNTXoBDncE219mpUycMGToM018dipSkBNQt54UZAxtiat/aCJ3/AmKio+Dm5vbAbbM2bE1m+Ap4pepRcf3gwYNi2OdPPy3DozBr1iwkJyc/ksdijDFWsDhoxBhjjDHGWC6kp6cr1/uNeA0bT0t1jHLydS8/NH3/zAOXGzFihLi8ftG47I3L59D+sU7w8/PDw9IZ1BjdGqjpD2weA+yd1QU/fzYSv/y0GIXp9u3b+OCDD3D48OFCfRzGGGOFg4NGjxh12WCMMcaKo127dokiv/fv3xfTy5Ytg4+PVMyXsdIgIiIC3n5lMHHOL1hxOg7n7lpmzwSrI5XrE4KvYVCXtggODn7guvs+0Qfu7u6Y+cZzOL5nG1bOm4GzB/7D0MGD8rSNq3qmKtdne36tXK8evQFVojbin9e9sDZoEs6pq2Hnq0D0+pdFQVTTgFhBat++vbjs1q1boayfMcZY4eKg0SM2YMAAe28CY4yxEurFF18UQZ1XXnnF4raxY8eK22iZgjJs2DA+GcJKlU3//IMGLdoh0qs2bsWmKPP/8H4PNwP6ir9dfi9haH0vhM4eiFGjRuVp/TuzClTfvHIef//6Pf5cOhedO3fO0zpadxmkbMtgl/8sbu+eugJbMtrh25RnRRCpdZtG6NCxIz766CNlmf/+24kvvvgCOp1OTEdFRSl1nPLi2rVrItOIMcZY8cVBo0fMYDAgJcW4k8EYY4wVpIoVK2LlypVITTVmG1DtkhUrVqBSpUoF+ljUtjswMLBA18lYUUWtiV979VUMG9gDOy8bs4lIK6fz4jJTB3T4TotN376H2jVrwsPDI0+P0bJlS8xfsABrf/hGmdeoUaO8bahKjZGrgN3XgB8OA16qpBwXfzZ+BnTe/vhrw19ievPmzejWrSvee+89ODg4YP/+/fj555/RsWNHZGZm5mlTFi4q3KFvjDHGCh8HjR6xhs1aoWq1aiJ4xBhjjBW0Zs2aicARtfCW0XUKGDVt2lSZp9frMXPmTFStWlUEfxo3bow1a9aYreuff/5BrVq1xO1dunTBzZs3zW7PPjyNsgr69++PsmXLioNlOgDevn272X2qVKmCGTNmiAwMKihM27V4MR9YsqKNhm/RH+kZP1uZ38LhvMjo+TvhMVSdAXxwexTe+OwXXDh+EB99OClfj/XsM8+Iy+nTp+PQoUP5Woe64Wh0XgiMWQ08n/gjLvnbLsJNkttNwKSmV3H06FFR5LtlRaBsVi3vgQMHQqvViuvr16/P03a4ubujU98h+HY9d2pjjLHiioNGj9h7M+bAzdNb2fFgjDFWDFCgPzPZPn/5OMlAAZmffvpJmV66dClGjhxptgwFjCh7YNGiRTh//jzGjx+P4cOHY/fu3eJ2GlIyaNAgPPnkkzh16hT+97//4f33339gK/I+ffpgx44dOHnyJHr37i3uHxoaarbc7Nmz0aJFC7HMa6+9hldffRWXL1/O8/Nk7FGg4CllGZGli2ehV9x85bbnW1dC6xUN8eSnu7Hq38MYN3EKnnvuWXFbv3798vV4FIilIM2HH36I1q1b52sdc+d+Jy4pO+h8SiW8m/bVA+/zfAs19uzZg8bBwJFxwO5x7njuzQ/F0DT5s5/XINa8ud+iVqMW8A8qj/KVKufruTDGGLMvBzs/fqnkW8Yf0dHRyg4IY4yxIk6bAnyXt2EmBebNJMDRPU93oeAPdSu6deuWmKbhJTRkjQpZEyp4S9k+lAXUtm1bMa9atWqiZsn3338v2n8vXLgQ1atXFwEeUrt2bZw9exaff/65zcelbCX6k02bNg3r1q3Dhg0b8PrrryvzKbBEwSJCQ2C++eYbUcuFHoOxombcuLegUqsxbekG7A27bnbbsTtqePlLRa5btWqlzF+9erXIpMsvjUbzEFsMuLm5iWxCqmP2zZxvMWH8G9j/YTB2OfbCm24r4a5Kxcs3/ofL3q1wSx+sFMoO3voO5g+mc8p61PZJRt8+I/D3L4uQEBeDrgOexddffy3+Tpw4YZa5aEtcbCwatOoorhv0ehw7dkwEjBljjBUfnGlkBy7uXoiJibH3ZjDGGCuhAgIC8MQTT4jhY5RxRNf9/f2V20NCQkR9vR49eohhZPIfZR7REDNy8eJFiywHOcCUU6bRO++8g7p164psCVonrSd7ppFpjRY6qA0KCkJkpHmNGMaKAtpfCwm5iqfGTIA6oBr+S6im3PZj9XXY9Mt8DH9WGk5m6qmnnoK90WeLtGopBWl+/i8ckzx+goc6FWcy62Px/CV42WG12X2aPtkPrSsBs5JewK6MZigXtwcfzF0hbhs58TNlOQr+mKKTodZUrVFLZBmR8Du3xZBVxhhjxQtnGtmBn3+gWYFSxhhjRZyDm5TxY6/HzgcaoiZn98yfbxxOIwd3yKZNm1C+vHRAJ3N2ds73plLAaNu2bfjqq69Qo0YNUQuJDp4zMjLMlnN0dLQ4uKWsCMaKmsOHD6Nm/Sao1XUovt9jzDIa5H4Q664G4uTBH/HUtn9QlFHwl7on0vfADX11BOuvoe4TfUA5gUOf6IFJ64zLbkp/TPyRRalDsCFhEypX74bfDklZiwNeHIv1y+bj2jXj/8Wo/43BTz/+ID7npp9tmr4fF6dMBwZXQGT4nUfzpBljjBUYDhrZgZOzM59RZYyx4oTO2OdxiJi9UT0hOmijgEyvXr3MbqtXr54IDlEGEA1Fs4ayhWhYmakH1TOhYXAvvviiKJwrB6eyF89mrLigul6UpffK5Nn49YT5flunDt0woGtXZShYUUYd0ObNm4fqNWpCr9OKYXQNGzaUbqvzFC7510GdaGPhfFO3r5/BM2HVEOHVBjqNM074SkNIw+/eVZZZn1V0n7KyKGtQmb9+Pbx8fJXpd79ejnef7lZoz5Mxxljh4KCRHTi5eeHevXv23gzGGGMlGNVEoaFh8nVTVGuFsoKo+DVl+HTo0AHx8fEi6OPl5YUXXngBr7zyiqhn9O6774oi2MePHxfD3XJSs2ZN0amNil9TsOrjjz/mDCJWbMlF4V0r1AWuGd/HIWWfwmfXpCFblMEjDwMr6sa/Nc5ypndV9F9fB9/WGYhx/iYpR1nGJnyAZM85GGLYLmLnX5XfjQoLvsP4197ErJkzcOPGDaSrpOwiqklG3yOEhr8OGzYMzR/rqawruEoNeHn7iGC2k5NTYT5VxhhjBYhrGtmBV5kARERG2XszGGOMlXAUAKI/a6hINQV1qIsaZRVRZhINV6tataq4vVKlSvjzzz9FtgAVt6Yua1Q8OydUINfX1xft2rUTgSPKcGrWrFmhPDfGCtvzzz+PRm06Ya1JwGin70vY0GIvPn1pMBo1biIyeIq7Vl364enlmTZvn5j4FqpGb0SVqI1I0rvirZQ3UdUPeKxzFzz3930EjPkRPd+aLToDy0Fi6rhGnn9rMvQGA07cisM/Z++ifJUaXNeTMcaKGZXBkI9evgWMxlh/+eWXIvuGdkznzp1r1oHCVOfOnZUzP6aoEwvt7BJ6Sp988gmWLFmC+/fvo3379qILDJ0BzQ360aPOZnS2xNbOdn4dvxWHlX+uhy7sHL7O6kjDGGOsaElLSxNn0CmA4uLiYu/NKfVyej0K8zeb5U1Jey0CygZh1uq9mPbPFWXexmZb8OvdFvj8rRdEF8KSkjEzZ84cdGtRHct+WoAFW2/Bt+frcAqobHXZvX6jMCHyJRxMqQ4HrwAxzwF6XPu8nyiyT10Xz21djEN/TAOG/InpO40nSh1SonFt7otiX50xxljx+M22e6bRqlWrMGHCBBHkofadFDSiM5O2av5Q2vvdu3eVv3Pnzom0+yFDhijLfPHFF/juu+/EWVEqYOju7i7WSTudRYGDgxNCb3MhQMYYY4yxooj2MR2dnPHjAWPnv0v+A7HlXmURMCIlJWBE3nrrLTTs8CRm//gvkm+dw7JnpNpF1nSMXYqjDm2UgBHRQo3KNesoJ3ZTjn+H6f6LzAJGYjk3f7Ni/A+DAskUfKK/I0eOPPT6GGOMFdGgEaWyjxkzBiNHjhSFOSnQQwUFly5danV5Pz8/UWRP/qMuLbS8HDSiHw46W/LRRx+hf//+oq0vtRAODw8XKfZFgV9gENLS0u29GYwxxhhjzIrTp0+jdr16CL9vPOHoosrE++PfQXD58iW6C65arUaPbl3xRNK/uPV5X3iqchfgad//eXGC9uKmLzA0/nOby33YyxmRZzfnaZveePNNMSqBXL9+HZmZmahWrRpWrFiBO3fuiA5xjDHGSmDQiArhUWHN7t27GzdIrRbTBw8ezNU6fvzxRzz99NMim0g+60DD3EzXSWlX9GNia52UXkzpWaZ/hcnTxw/nz58r1MdgjDHGGGP5o4o8gTtNX1am53p+jmd+Bdq074h33n67xA9bpeLe8+fNEydjh7scQeewbx94n/2axvgitDIe31s/x+XKtBuMivuG4cKFC7nennlz52LixIniOg1/27Fjh7g+fPjwXB8zMMYYK4ZBo+joaOh0OpQtW9ZsPk3nprsYpaLS8DTq6iKT75eXdVIRUAosyX8VK1ZEYfhp/w1M/fs8biZrSvQZKsYYY4yx4oi6fr07cSJW7DuLTEhdwUhf5734Zu1Z7N2zR3QdLE2StO5Y/us2dK0TaHFboPrBRa2fdtmCf3zfUKa/TXkWp3W10bRRzsElmVxeokbNmkhOTjYrtC0XLJdPAjPGGCuBw9MeBmUZNWzY0GbR7Nz64IMPRAEo+e/27dsoDCGRSTh9Jx4rj96GQ1CtQnkMxhhjjDGWP7/++iu++vJL7PYbrsz73ONb0W4+qHJdlEZDh0olILrXLYslXVNxM6Cv+NvvNxL7/UbhJ69PrN5vmMsWsdwsz7moo7lpdttT97+EfyWpU+ODbN4sDWULuXoVI0eOEtevXr2KJq07YMSEKWLkAtm3b99DPU/GGGNFMGjk7+8vilhHRESYzadpqleUEzrTsHLlSowePdpsvny/vKzT2dlZaUucU3vih1XVXxpCRzTtR4mzWYwxxhhjrGh4+eWXMX3iMGX6DbeVGOa6DRE13wTUGpRGdILW3cMTcdERyHDwVuaX10TBUaVDF+fjCPHvhxEuG83uN7BpBegh/Z+pVQb0d95ldrvj0LlmXdTo/940g0h24+YttOvZT1xfvfoPcTlt2jScOrwPvYaOVJbLzSgFxhhjxSxoRF0nmjdvroxLJnq9Xky3bds2x/uuXr1apKHSWGZT1I6XgkOm66QaRdRF7UHrLGxPt6oEb1cp1Vnl7mf1h5ExxhhjjD1658+fF5dLVM8b5524CrxyF2X7PbimT0mWnJSI1/u2Qkqq9U7EDio9PvVYpEz/6fMOrgc9jSjvlsq8aR4LLO6XmqlTri9evNjqCV46SRxUqboyXaeJNMLA2dVNXP6y/zqee+MDXLlyJd/PjzHGWBEenjZhwgQsWbIEy5cvx8WLF/Hqq6+KLCLqpkZGjBghho9ZG5o2YMAAlClTxqJwH7UNnT59OjZs2ICzZ8+KdQQHB4vl7cnD2QFzhjVRpjccv2HX7WGMMcYYY5KjR4+i2aBXlenKySfx9bLNgHvO2e+lyY59p2GASlyvNQtIcCyv3EZD+K7598NV//74M1I6URvhaexq9u+ZFNzw72u2vq0rPsPp38ZT+2Pl5HF2Rw4fQt2mrUVwaOzUbzH6g1li/uJtZ8SlWqNBcNVaIiOpzxNPFJluyYwxVlI42HsDhg0bJjJuJk+eLNJKmzRpIsYuy4WsQ0NDRUc1U5cvXxbjlrdu3Wp1ndRdgQJPL730Eu7fv48OHTqIdRaFThdeWZlGZPaRZLwxyK6bwxhjjDHGAJw6cxYpNbop07MHN4aPj49dt6mooKYxdBL3+1kf4we1FOPRG4Cxy8Pwy7PG5fw+1oOqMWR47sG0AWlYH90IZ44DZ1174Itft2H4Skf4NZwN155vi+U1YTvQ2GUv5o89YPVxqWEOqVijjggOtetpPAHs4GDcp/YNCMLJiEhs3/Iv/v3nH1ECwtXVtfD+QxhjrBSxe9CIvP766+LPml27zMc/k9q1a5uNgc6Oso2mTp0q/oqiRhW8ceZOvL03gzHGGGOs1KN9ynbtO+DQ4SOo/G5XMe9l1zVo0elHe29akUEneeXMf51JMtDvp2AWNEpIk/6qlXHC8T1bMe9juWvaNvGvVpuJyJM7UTkraPRG4nvYldEcjpfnWH3cyMhIBFeqAk9vX7P53QaaPCgAH78AhJk0sklMTOSgEWOMlZThaaVRr/rGNOdI+mVljDHGCsCLL74oTpy88sorFreNHTtW3EbLMMaMDh48iEMHD6D71DXKvHHuvwMq3k02rRk6ddo0Zbp9+w5KAEkeUXbnvnRZp25dhIXeNAkYmatRo4bZ9J/p3XE7sBva9uyHxzpLQTsZdTWuXKOOxTpGvTfTbNrLzx/347M2ABB1TxljjBUM/jW0A183J+X6iiOhdt0WxhhjJUvFihVF4djU1FRlXlpaGlasWIFKlSrZddsYK4rkrParicYEfMfqT9hxi4qmie++i6SkJNStVw9lywaKDC36q/QZMGcP8ObJ7ug/YAB27dyJ9DTj909gYKDZen7//XdkxoaZzYuv3AuPP/0/7Nn1H95++20R4G7UtDnq1q2L+NjoB24bLR95764yzUEjxhgrOBw0shNXVaa4XLqPi2EzxhgrOM2aNROBo7Vr1yrz6DoFjJo2barMo4KzVKeEMghoGEfjxo2xZs0as1oio0ePVm6noeHffmveQYqylqjJxFdffYVy5cqJ5hSU0ZSZKf3GMVYcJCQlY+CEL5TpmR5z4diIM/Kyc3Z2hru7Ozb/+y/mzZunzN959ArS2s7E4mW/Y/26dUpdUtnu3buxfv1fOHPmDG7duoUWLVrg8CfmQbnKrgmoWK22uP7111+Ly/FzVqD3U8+jTrN2ZsveiknGjehki+1zdfdQrsfExBTQs2aMMcZBo0cpMwXBZ6fBN+kc6gZK2UYJadoc6zMxxhizP/qeTsnQ2uUvP78Ro0aNwk8//aRML126VOlKKqOA0c8//4xFixaJVuPjx4/H8OHDxQGeHFSqUKECVq9ejQsXLoiGFZMmTcIff/xhtp6dO3fi2rVr4pI6oS5btkz8sYczf/58VKlSRTTxaN26NY4cOZLj8vQ61alTRyzfsGFD/PPPP1aHLpr+9e7d22yZ2NhYPPfcc/Dy8hIFoCloSJklJd3pM2cR51NTmR7mshWo3NOu21SUUQCagsSymjVr4v3334e/v78yj4JDGRkZuHHjhnhf9u/fT7wv5WxHdzc3RMzuiwCVFNxx1KfCSx2PSfNWKOtwdnHF8+9Mx+CXpPpHRKvT4/s917Fk73Xx/WgqoFwFiwLajDHGSkgh7FKBdvrX90O50B0oh29QU1sB3bFI3HQ1Mgm1ynraewsZY4zZkJqpQ73JW+zy2Bem9oKbU95+rin4Q0Vr6cCN7N+/XwxZk4fh0NCNGTNmYPv27WjbVmqNXa1aNdGZ9Pvvv0enTp3g6OiITz/9VFknZRxR7RcKGg0dOlSZ7+vrK7IONBqNODh84oknsGPHDowZM6aA/gdKn1WrVmHChAkioEcBozlz5qBXr16ie2z2oT7kwIEDeOaZZ0QgsG/fvmIoImWAnThxAg0aNFCWoyCRaTCRMkdMUcDo7t272LZtm8gWo0AjdaKl9ZVk586ehVNDqRPXsy7/Qq0yAA7m/zcsb+TgEAU+rXFwcECaFog7uwdoMBDr07vgieSr8A+qKG5v3LaTsuwXmy/hfmompjxZH3+euKPMX3n0NvzcnNClTiC8XR3h4eUDv8AgtOvSWwSsGGOMFQwOGj0qKhXQ8l2kxYXCkBaHGjD+6P179h4HjRhjjBWYgIAAEbyhjB/KVKLrplkAISEhoiV1jx49zO5HB1qmQ9go24WylEJDQ0WNJLq9SZMmZvepX7++CBjJKAPh7Nmzhfr8SjoankNBNzk7jIJHmzZtEq8FZXRkR8MGKSD07rvviulp06aJwA8F8+i+pkGioCBjMw5TFy9exObNm3H06FExfIjMnTsXffr0EcMPg4ODUVIlJSXDOyuh7wnnffbenFKBgtLk3q2b8M+Ka56OcULZKuXF9Y59nhKXGVq9CBiRKX+fN1tHSKSUBXfkZixmDGyIYa+9h5TkRFw4tIuDRowxVoA4aPQoVemF870O4/K9RNS58z0CYmIRpfdDUhr/sDHGWFHm6qgRGT/2euz8oCFqr7/+uhL8MSUPOaJARPny0kFa9uwTykx65513MHv2bJGN5OnpiS+//BKHDx+2evAno2FPNLSN5Q8d7B4/flxpb07UajW6d+8uMr2sofmUmWSKMpPWr19vNo8yzShTibLDunbtiunTp4s6VPI6aEiaHDAi9Jj02PSaDxw40OJxKWPNtOBwQkICihsKknm1lQIUpI3jWeDVCLtuU2lAmUZEG2csiH0uRo3gGg4Y+vLbqNusjZh36V7u31NV6zYWl5eP7RPF//ODhnXSZ5Ay9RhjjEk4aGQ3KvzPdT1mJo/C+dBIOldr7w1ijDFmAwVC8jpEzN4o84QOfmjbKYBgql69eiI4RBlENBTNGhrS1q5dO7z22mvKPKpdxApXdHS0qMeSvZgwTV+6dMnqfe7du2d1eZpv+n4YNGiQGGZIryPVp3r88cdFsIgyxWjZ7EPf6MDez8/PbD2maDic6RDG4uji9iVQNeivTN/tuRUV3CyHALKCRe85ymSrUaMGXtkl1R/aFe4MqiTVf+SbZkPQcuN6dBKq+WcVwlZrcOeOMaM/L0aP/h98fX04aMQYYya4ELadJLhVR3k1BYuAE2GWHSAYY4yxhz0ooyFHVMTadPgYoawhyiKi4tdUvJqCCFT/hg7iaFoubnvs2DFs2bIFV65cwccffyyyMljx9PTTT6NfP6kYMR0Qb9y4Ubyecp2r/KBsqPj4eOXv9u3cHeAXJZXSjMPRPnT/ERUadbPr9pQWFMymTEgKZroiVZm/7IB5V2EP59wF638+cFO57le2vOjimJ9i2BoHDQ9tY4yxbDho9AhRXYlP3xmLrat/QopzMDzVKWJ+mk7FHdQYY4wVOOqCRX/WUN0bCgRRtkjdunXFwRsNV6NMFPLyyy+LzJRhw4aJYszUwto064gVDqo9RUG+iAjzIVI0baseEc3Py/Jy4XN6LKpvJa8jMlI6mSXTarWio5qt9VC2mvwey+m9VlQd2f0PXkz/UpnuXoszjOxhs9MzyvUrEUnKPvHZsHgkpZt3SCNrfN7FzYC+uOHfV5nXK8CYDRdQvrK4TExMzFcwi4LovF/OGGNGHDR6hOiH6PSxQ1g+ewq0ajc0criq3JZo5UeRMcYYywsqfJ29jo0puo2WkX+Txo0bJ4Y80Zl1ChhQIeTHHntMCQhQp6379+8jLi4OCxYsEAGmU6dO5fh41OnrYbJXSjsnJyc0b95cdKCTUY0ompY73WVH802XJ1QI29byhIbvUCBQbp1Oy9JrTfWUZP/99594bAoaljjaNLQ8+oTZrCpDF9ptc0qzyt7m+8AxSRm4HZuC34+EWiz7m/eHaOF4Uekx84zLZnH973tlMWndWWj1etRr3g51GzbBN998Y1ZfjbpFvvHGGxbrpOCojGp4kfzWRGKMsZKIg0aP2M4d2+Hk7IwYrTt81Ylwy0rJvRHFQ9QYY4wxBlHUesmSJWKoIA0xfPXVV5GcnKx0UxsxYoRZoWwK/lHAj4qWUxBwypQpYmihXAidCp9TZ7VDhw7h5s2bIsDUv39/UU9GrnclZ5tR17YjR46ImlZ0fxrWVhI7p2k3PI27emNHwX9ebyMCqezRC413wEYfYx2jdJ0eC3eb10/b5PuGyC5q73TabH603ttsevJf57Fk73VcPHsKU6dORXh4uHLbM888IzoKykEiOZuIivlTkOjGjRtwcpIaAZw/b96pjTHGSjMOGj1ilA7etVsPnDp6GDqVM7zVUgebfSHR9t40xhhjjBUBNCSQ2txPnjwZTZo0EdldFBSSi11TAfO7d+8qy1PB8hUrVmDx4sVo3Lgx1qxZIzLAGjSQepnTcLczZ86Imka1atXC6NGjRTbT3r17lW555LfffkOdOnXQrVs39OnTBx06dBDrLIkcbvyFf9PbKdP1Kkhd5NijtyWmPho4Xlem5++UhkyaqqYxBn9MTfb4wWLezZgUVH5vI3RfqlBhVUUgM0UpMk8oIDp4wky0GDJWdEsjgwYPRseOj8HN3V1M07BMxhhjEpWBB+1aoJax3t7eoqhjYYzPp7MclB5r+AqoErVRmX9zlnmaNGOMMfuQzzpTfR8XFxd7b06pl9PrUdi/2Sz3itVrMVuFLrHf44auPJpV8sHa19rbe4tKrcT4OHj+4IfaUX8iHcYgpuwLzzkY6rLd5v3rRa1GClwt5geqY/Cnz0SU6/wO9HVfwNnJgfgvBJi0tyzKv/KjWMZx7VisfOIWvtoF/HFGLbLNqID2ypUrRfCWMcZKqrz8ZnOmkR0MHTpUXMY5VkBltfUzJ4wxxhhjrBDEhSBEW0EEjMhrnWvYe4tKNU9vX0TWGmc1YPS152yLgNGqsEbosKmHMn0hYIjV9Ubqy6Bj7I84snszvnuzK5pXAN7qpEGtV75TlpkwrJ6Y//twqZ6Ro6OTmM/n1BljzIiDRnYQGBiIvv0GQKfVYZqnsegi/0AxxljRwt/LRQO/DqwgGfa8h2fjP1OmO9cOsOv2MCAwqAKect5mNm+O51fo57xbmT5YfRb6nRiFC54DEB+fgEUHjTWoVngba3xlp9ZGoLJaqpHU//7XSIY0BI18njkW8XppmmodefuVwXNj3zMrjs0YY6UdB43spELFiojM9EZTh0vKvDtxUlFsxhhj9kU1YAh1FWP2l5KSohSsZexhqULWwk2VLq47alRw0PDusN2pHTDdc4HZrAEuu+CgkrqfRSUBH/98DueOHULDhg1x7sRhvPqnAcFTpWXbOJ6zuerT2loYUi8VF7VVcEFb3eL2UfGfKNe1mRlQOzggMzOz4J4bY4wVcw723oDSqmb16rgXtwv1vFPNgkYV/dzsul2MMcYABwcHuLm5ISoqSgQq5DbM7NFnGFHAKDIyEj4+Pkowj7H82rJyLnoagJs6qSPcnGFN7b1JjAS3g4sqE3v9RmN0yud40eF3s5t93QCNgwNuXLkgvp9ldxOkS7XKgHNlhiDe4IGz2hp4JeFDZZkwXaC4nJE0yupDH9fWU64nJSaK9XPQiDHGjDhoZCfVqlbG7es6wBuo6XAHV7UVEBqbjLbVuXsHY4zZGxVDLVeunCi+fOvWLXtvTqlHAaOgoCB7bwYrAa6tfhM3W0kBI9Kmmp9dt4dl0aWJi4qaCGz1fNHi5mTHIPgFBFlkgL469nXoDfNF0MhDnQoPpKK8JgqnyjyNJjErxTI/p/XFVM9F2JvZLMdNqFGvEUIunBHBKR6exhhjRhw0spO6devi3z8TxfVazvdE0Oj4rTgMa1nJ3pvGGGMMgJOTE2rWrMlD1OyMMr04w4gVlOByZTEqwTgcqYyHZfFlZgeBOWd8HfV5CasXzxTX27Zti89mzoK/nx/S09OgzrCseeajTjKbTjHk/DpH673h5uktricnJeGdd2bgtddey8cTYYyxkoeDRnZSqVIlOOqknFpfJx2QDJwOjbX3ZjHGGDNBw9Kyt3hnjBVPmRkZ6FslCm9FS13TWBHi5Il7CUCQla7PSc2nID6mAXTaTBFArlixIia9/564bfny5bh7U4NyHjqz+5wKAz7yXYLpyWPEdL3oP81uX+A1E68lGItnf578Ivq/2A6d+z2N6HvhSE1NzXN2KhfsZ4yVVFykwU5cXV2x72K8uB6guS8uw2KT7bxVjDHGGGMlk+NcZ/yd/pgy/eer7ey6Pczc/bpv4FqcI+J0nth53QGf7wQyRt6AR+dP4OwsZQpdumRsIEOuX78Ovc48YERqBQCZp/6y+jieZ39BH+f9uBnQV5m3Oq0H6jVuhtbd+qLrgGfztN2cjcoYK+k4aGRHyVm/MR21W8VlkpbPUjDGGGOMFTidVNh4apKUeUKaV/a14wax7GoNnYP6X2kw6vyz+OpmT7y/CXDyqyJuk2ua1ahRw+w+ffv2hcrKutycgDfXW3+c89v+gsHFspaVo1YaAeDq7iEuFy9enKvtTk7mk76MsZKNg0Z29Nuf/4jLeg7XlXmRiVILWMYYY4wxVjDOfNtJXMYZpLo1zSr52HmLmLXhwOUrVYYuMwONGzc2u83bW3rdsmvZsiUcHKwfzmj1wMeuP1rMN2SmQZUhBYjed/9JmV/u/h6z5bZs2ZKr7T5//ry4TEuTinkzxlhJw0EjO/Ks1kFcUotR2YnrEXbcIsYYY4yxkkd/5yC0BuNu7/A2le26Pcy661cv4+/ff0KfPn1w+/ZtZT41JbCVjR/orleunwiTLs/dA6ZMmYLBdS3zkO7cuQOMOCuuh981ZgmpDVqLOkW5IdZHIwaSzItvM8ZYScFBI3ty8kRG1u9TeTdprNrmQ9KPGGOMMcYYezhUb4YO/puUB27qgpX5fRqWs+t2sZyVL18eFSpUyPP9uixSY8jPQOvvgE8++QQ+nu5Y5zMBjR2uiNur3f1PrBtl6gBvGxDn30W5b7pOg01nwnGZKnIDuS6Gfer0GXF58eLFPG8vY4wVBxw0sjMHR0dx2chFOjWy7VKMnbeIMcYYY6xkCAsLw6LB0vXFqYOU+S6OGvttFLPp519+FZceHlJdobxKSNVjzRlg/LsfSjM6zEBN/RV0Pz8BobMH45cZE8yWf7JTS+X6C4drYf+1GCw/eAsePn5ScAnArytWYOXKlTYfMyIyChWr1cpzxzXGGCsuOGhkZ/oqvcVlZUh1jVKcuCgjY4wxxlhBWPHFq3i5rXT9j7Se9t4c9gDPD38OvXs/nqeg0eJTUlHrn84HKvOmT58uXfGsgNTR4fAZ9DMM2nSUKVPG7L51a5kX1pYNHTsJPj5S3atPp0zBjBkzbD7+nbAwePn4IjPTWG6CMcZKEg4a2ZmDfz1x2VWVVXxPreEOaowxxhhjD+v+NXxYQypmnGaQMrvJa52r23Gj2IP8++8/cHV1zfXyf8e3R6PZwP+WRYrpe/fumd0eULacUljb2dnZ7DY3Nzer6xzltQ5l004hNDRUTOe0b67WaODlWwZarXlNJMYYKyk4aGRvFR4TF41Vp5VZF8Lj7bhBjDHGGGPFX+ZpY+esf9PbK9dfbC+1cWclQ4f27XH2LqDPiuuULVvWYhknJyerxa3lbKLsKiEEb1fehpWvVUbI1as5Pr5Wq0N6WiqOHj2a/yfBGGNFGAeNikjQyFmlhbNa6v5w+lpW6wfGGGOMMZYvZ3b+rlyfkTRSXFYLcEegp4sdt4oVtDFjxuDAgQPi+vr1660u45hVQzQ7jUaDxi7GLm2yEK1UhHtiF4BijCkpKTYfX6fV4sT+nfjss8/y+QwYY6xo46CRvTl5IMVRGoPd0kP60Vq1/7KdN4oxxhhjrHhzyogWl9d0FRFlkGrZPMFd00ocPz8/tGnTBmq1Gi1bGgtb5yZoRNY8E4Q+TvvQ3OGCMm9kwqfK9X2vA5mxUu3RpKQk6HQ6s/trdVo4OXMgkjFWcnHQqAhw8K8rLoMM4eLyXlySnbeIMcYYY6z4mjBhAhqWkfanJsW9qsx/plUlO24VKyw07IyCOcHBwXm+r6OTCxZ4z8KfvhNtLtOmsnTZqnUbzJs3zyLTaNL831E2iAOSjLGSiYNGRYBT05fEZVscFJcRavPODowxxhhjLPfmffeNcv2woZG4rFLGDcE+uS+wzEoOb29vdOwolYSwoJHqHeWkvBeQkZGBixfOY/fu3Wa3UQHswOBK8PblDsiMsZKJg0ZFQfmO4qKdo7EYdnwKt+1kjDHGGMuPHm3qiMs0gzEg8PlgKXjESmfQaM8e82CPQm8+3MyanvVdlc5robfNayDFxkTD0ckJ+mzD1hhjrKTgoFFR4FleXJTTxCizDlzmYtiMMcYYY/nhr78lLtdm9FLmtarqZ8ctYkWWizFDqHaAsTbR6Sjjdb02zXhdb0CdOnUwbtw4MZ2ekQFXd0+EXLksah4xxlhJw0GjokBlfBmqukndGf7cbyzGxxhjjDHGHuzatWu4uOI1LB+cKqYnJbys3Ja93TpjQtnmWBDSBE+vC0L/ZlnFiwD0xxrlOu2p960HhLwPdK6mxeXLl/Hdd99h1ao/EBZ6S3lvRURE2OUpMMZYYeKgURFxJU4aY19XHSIud9+SdnYYY4wxxtiDUc2ZQd2bou7dhRa3lXF/cN0aVkqpVGg1egk2nkmBl6t5lzWDQbp8vI4Bf48CqvsD4+tfVG7//IvPleudevXF/fv3H912syIhJCQEtWrVtvdmMFaoOGhURNzRBonLNtgvLjM13LqTMcYYYyy3Nm/ejBOvJSrT73msUK7/M06qH8mYNZQplJyYgG8njjKbf15b3WLZip4ZyvWUFONJXo2jC+7du1fIW8qKmoSEBFy9esXem8FYyQ4azZ8/H1WqVIGLiwtat26NI0eO5Lg8RfDHjh2LcuXKiYJ0tWrVwj///KPcPmXKFPHFb/pH446Luv9SO4jL9o6nlHk6nd6OW8QYY4wxVnzs3LULGpM92y33jN1oy3rxyThmW7NmzcRlQsQdZNw5r8zve/9bTE36n5JxlN2dO8ai2D7+gdDred+9tNFxAXRWCtg1aLRq1SpMmDABn3zyCU6cOIHGjRujV69eiIyMtJl23KNHD9y8eRNr1qwR44mXLFmC8uWlQtKy+vXr4+7du8rfvn37UNR5lW+IeK0rKmmMZyh2HDF2U2OMMcYYY7ZpIo8p1w/XmIn7qVIn2mY+6XbcKlYcyDWJ6Bgietsis9uWpg5AiK6i2bwnnntJXDo5Goc9Ojg6imMVVrpwoJCVBnYNGn399dcYM2YMRo4ciXr16mHRokVwc3PD0qVLrS5P82NjY7F+/Xq0b99eZCh16tRJBJtMOTg4ICgoSPnz9/dHUdewYQOcjA+Co8oYrd50TKpvxBhjjDHGctbB+ZBy/YDLk8r1QY0D7bRFrLihY4jMyBsW83vEGetkZard4Osvvafi4mIxaf7v4rrGwRGZmVKgkpUenGnESgO7BY0oEn/8+HF0797duDFqtZg+ePCg1fts2LABbdu2FcPTypYtiwYNGmDGjBkWH9arV68iODgY1apVw3PPPYfQ0NActyU9PV2MRzX9e9Toufx5XOqc1tDhqrjcc96Y8soYY4wxxqy7ceMGmlWQxhCFlumDM+HJym19Wtez45ax4hY0suWOLkBcOupTsLjqAmweA3z2OFChai3lvpcuXbLLcQSzH/k41GBrDCNjJYDdgkbR0dHiQ0bBH1M0bauI3PXr18WwNLof1TH6+OOPMXv2bEyfPl1ZhuoiLVu2TBRDXLhwodiJ6NixIxITjYURs5s5cya8vb2Vv4oVzVNQHwV6zPsZUseGmhopWBTtEMApj4wxxhhjD3Dr1i1U8tKK61fLDcflCGm/L+P8dvj5+dl561hxsGbNn2IEA/n5qUoWt18zGaLmqo1Fr9rApG5AkLuUXaRxcsGnn36KyZMnP8KtZkUlaKTVSt8/jJVEdi+EnRcUQAkMDMTixYvRvHlzDBs2DB9++KEY1iZ7/PHHMWTIEDRq1EjUR6LgEhXP/uOPP2yu94MPPkB8fLzyd/u2fTJ8tp+VzkwMc9kiLjUefjhw5LhdtoUxxhhjrLiIiwxTrt91qovw+2niejXHeDtuFStOBg8epAQYa5a3LG3xQ8oAq/fzTLslLstVqamcGGclU1RUlBihYi1olJpq7KTHWEljt6AR1RnSaDSIiIgwm0/TVIfIGuqYRt3S6H6yunXriswkW4XnfHx8xH1CQmzXB6IubF5eXmZ/9lCmfDVx2dLxgjJv2X9n7bItjDHGGCs+3WVXr14tusXS8g0bNjTrLEt1Vt577z0x393dXQzhHzFiBMLDw83WQY+XvQPtrFmzUBzcDTEWwT5p0k9l/dJv7bNBrFgPTwsICMClab3RsLy3ctvezGaI0VseI3inSO3Wy5avLC49PDwe2fayR6tp02aYN2+e1aBRUlKSnbaKsRIcNHJychLZQjt27DDLJKJpqltkDRW/puCP6ZCtK1euiGASrc8a+gBfu3ZNLFPUadRqHPJ8FmqVAd2cDot5h2KsPy/GGGOMlUx57S574MABPPPMMxg9ejROnjyJAQMGiL9z586J21NSUsR6aFg/Xa5du1Z0oO3Xr5/FuqZOnWrWgfaNN95AceCXaSxefPhmrLh00KbA38fTjlvFihs6kSwHj1wcNXi+jRQIkr2VONHiPi2vfSzdJ6uTGgVvWclDQfSwsDsW38PycSkPT2MlmV2Hp9EO0ZIlS7B8+XJcvHgRr776KpKTk0U3NUJnwWjomIxup+5p48aNE8GiTZs2iULYVBhb9s4772D37t24efOm2IkaOHCgyEyinamirkHDRohIkl6SOg43xWWSo6+dt4oxxhhjRbm77LfffovevXvj3XffFRnY06ZNQ7NmxjPiVK9x27ZtGDp0KGrXro02bdqI26ghSfZmIZ6enmYdaCkzqahLS0tD/cS/lOk7cdIwkaqwHmRjzJbsWUIDmpY3m96b0QQ3tMEW9/NMuQYHR6k26fjx4wt5K5k9ZS94HRMTIy65ixoryewaNKKaRF999ZUoGNekSROcOnVKFLCWi2PTjgyd5TItFr1lyxYcPXpU1Cx68803RQDp/fffV5a5c+eOCBDRThHtHJUpUwaHDh0SaaZFXbmyATiYVFtcH+ayVZl/N57HyDLGGGOlQX66y9J80+UJZSbZWp5QDUc6c07D+E3RcDTad2ratCm+/PLLHM+eF4Xus+Ts2bOolHWO7ZZDXWX+O0OkosaM5RYN3ez9+OPKtJOD5aFSl7jFFvOqRG1QMo3I4336FOJWMnvS6cybFIVnHauafldSAImC9YyVFLb7Sj4ir7/+uvizZteuXRbzaOgaBYFsWblyJYqr6tWrY922fUA7oJLGWOtp5d4LGN+3uV23jbHSZtmy5ejevRsqVKhg701hjJUiOXWXpXbe1lBtx7x0o6XMHKpxRCfZTOs40sk4ylCiYsCUrU3Z3nTyjjKfbHWfpW5R9rZ/579o6SJd/0JnzPLo2aq+/TaKFUs1atTAvyb1wMjHfeth2kZjvVFrnLWxcHZxxRPP/A+bfv8Bm//9t5C3lD1KpqVR4rN15I69LwXL6Xs7Li4Ox44dEwEkCqLT/Sjoz1hxx+/iIuSpwYNw/uheZTrYVWrh+ffJO3bcKsZKp5EjXzSrucYYYyUBFcWmTGwaYrFw4UKLsgGdO3cW2dyvvPIKZs+ejblz51p0Cypq3Wc1N40H+bvvS8OJ1GlSJhVjD2t0h6pw1Ji/l/QG8+kk54pQazR4dpxU34iVLPT95uNXBk8+/4oIumf/TqXAEAWN1q1bh549eypZR7YaNTFW3HDQqAihIXTht28hyUkq2t3SSTqjeDOJd3oYswdbBfYZY6wodZel+blZXg4Y3bp1S9Q4elC3WOraRgc/VCeyKHef9Uy9Ji4zDA5IypDqjTzmGWWXbWEl0+Vpj6O2t7GWzaHMhuIyyrOZuDSojIM3mrbrLC6p7IYpCtT+9Zex9hYrHqje7ttvv437sTFo13MA7mbrOknfq07OLiJoJAeqKeOInDlzxi7bzFhB46BREdOlazdcSZQG5j+j+l1c6lUaZGjNx88yxh5dFxXGGCvK3WVpfvbMSAoKmS4vB4yuXr2K7du3i7pFD0IHvXQGPTAwEEWZp1pqdb1YbSx30L6aea0mxh6GWq3Cm42Nh03Pxs9AlaiNWJ/cRkyrYCyCPP6LH8Xl9M8+E5cUTKBMFcpQoa6GrPig123Shx/hp59+EtP+5cqL5k2mxbB1Wi2cnJ3F60wBfyLX5KWu34yVBBw0KmJefmkM1kY0ENebO5xX5q84bP0sH2Os8FDLXcYYK+rdZakpCDUSoeFkVPdoypQpoq6GXDOSAkZPPfWUmPfbb7+Jgxuqd0R/8vAJKpo9Z84cnD59GtevXxfLUReo4cOHw9e3aHdyHVxPGi6yIbmluDQkROCxdtLBPGMFxdlK9vFnEVLBa5XBGDTSZO07XL92XRRpp66HVHCePoeseKHX7btv5yjTbh5ecPP0Fq+rLFObiYT7caJxwAsvvCDmyU2aqNETYyUBB42KYKvPo6FS9NpRZfwB2nfCGEBijNl25MgRi3ao+cU7eIyx4tBdtl27dlixYgUWL16Mxo0bY82aNVi/fj0aNJBOQoWFhWHDhg2iwyytr1y5csofFbyWMyupmUinTp1Qv359fPbZZyJoROssyqL3L1CuX0uRhselXtyDWrVq2XGrWElEXZytidZ7Q2XQwz/hGFzTpc/lx4tW4+TJE+jffwASswonczet4s3dS3r96jZpKTI25X3EhHipEPbvv0sjRBgr6OLrRQEHjYoYShdPSU5FqmOAmP7I/QdxueuqNDaWMYYH1uCIiYkpkHVR3Q/GGLMHyhKi7yAqQn348GHx3WbaXXbZsmVmyw8ZMgSXL18Wy587dw59TFp+V6lSRQTTrf1R4WtCXdOoO+39+/eRmpqKCxcuiGymoj5M1/fI2+IyxeAMXVZx4nLacC6CzQqls9qTKsuuaPsymsIv6Qx6nhmM7meHiXk+ftJ+fHh4mEX3LH5vPhr0HUaZmgW1Dzj1B6kelYubm8jcXLBAClgnJCbhqZcmKMsFV6yS78dkjPz999+oU6dugZ0ELwgcNCqCZzFCr13GqSpSWmNdhxviUutWRjlTwRjLWfbOFnklf0lz1wvGGCvaNPqsoWl+0n6TKj0J33851c5bxUoiqlfjePpPi/mLUwciOG6nuO6ZJgUaHF1cxCUFcSljL7vY2FhxSdkqkZGRhbzlpdPAQYPw9NNP5/v+FGw3pXF0FJcGtTRM8V7W60Z7jJVrSVmdpGqtOtg0GjjzoS9gMmyRsdxKSEjA1atX8Mcff6Co4KBREUOdTuhH6WbgQDHdzFHqoEa++8e8CwNjzDqq/fEw5FapNznTiDHGii698YDsv4xW4jIz5jbXEWGFZs1FN3z7uDcaBLkp8y5oq8MhK3gp8/TOuQ6YfCKYhn/Kw05ZwUpMTEJs3P0CWVfT9l2V4WmePr5mw4e02UoZZCbGoE9doKFvHO6e3ymKqDs5SQEnxnLbUZ3cvn0bRQUHjYoYChhF3g1Dalo6bgQMhKsqXbltT4h0VoIxlrOoqKgCCRqlpWeKISBFbVwxY4wx6mt9Rbl6Lk4aRueckQCXrCwPxgpaQnwconS+aOwUYTY/Ri/V05KLYlML9pxwzcTC51emDBwdC6ahybiZi+Dm7imuR98LF5d7du3CH3+sxvVrIXA2+c5RG4xZ6ruWjIP+S+D6e9J+JWO5Qc0qCA0VLyo4aFQEde7SFVfOHEOKc7CYHuB+UFxeTuROTozlxsPWC5CDRhQsom5F589zIXrGGCtyoqUORnqDCuHxUqaHT+bDnTRgLCf1GzRCekoKEmKjkXhikzK/ecwKXNBWFdcbhn5t8/7Dx32sDFsjlStXLvRtLq0cHB2RkfFwwbnKNevilwM34OhkrO2m00rrpBpww4YNxbWrl+Hk4irmnZ/XBQeHnVaWndZbuqzgY1znL7/88lDbxEo+vV4PL98ySvCoKOCgURHUo1sXnDnwH+74dRfTzzqsV24Lv190Io6MFVUPmxlEQSNqmUttVInc5poxxljRoY84IS7/VfVV5o3p1dyOW8RKOkdHR2i1mdDTwZzG/GRun7i5iNL7oMHteUoHNeLgYByaVK1eY3F579490QFx9OjRj3T7SxMXF1eE3bmd79qWru7ueP+73ywKmfcaNhrPvP6B2byWmuNInwXUS5NqW9lCtTJHjBiRr21ipYdOpxNDXO+ESVltRQEHjYqgnj174sKx/Yh3ry2mWzkZsxwOXiuYrlCMlWQPG5mnoJGzswt0mVLG0UsvvVRAW8YYY6ygpF7fJS6PGoyBotEjX7DjFrGSjgJAOq1WnJzKuGscHil7J+EtcRkQf0QZzlSpZh3l9jJlg5WGHU/264eqLpGYOxBITzAf7sYenoeHh9mwsbzuRwZXqCyyPbILCK6IvsNfQeXqNZV5fWKmw+kBA0IoUPhTtq6XjNl6/5WrVBU//rBEKZpvbxw0KoLq1q2LsNAbSMowDrEJcJQyjBbvuW7HLWOsaJOHlRVI0MjFRck0YowxVvTcj08Sl/8l1hKXblEXRCYIY4U55Emv0yLxfgwcA6ThaKZ2Z7YQl9Ui/kAd/0z8PQroUtHY/dg/qDwGjxwrCtxevnQJh94EXm8PpO+f+UifR2ngQBnjWV1wqdZlREREnjPOc+Lm5m7ztuvaYExImIBr2vLKvLFjx+KVl18W14vSsCNW9Oi0GXiyngGVfIHffvsNRQEHjYqolq3b4tbl89CppJ2f7prd4jIkUtpBYoxZiouLK5Dhaffv3xf1BqIipdoYXAibMcaKnvJaKRM7VicdvLWs5m/nLWKloWYidcui0olqR6n1ujWZDl5ofm8e+tYD5vaMwvPjpyi3efgGiOFPZuuNvVCo210qqVTK/tuzzw3P01BAChqp1Zocl7EVVIrXu6Nr3GKsTe+KbnHfK/OdwneaDVNjzJayyccxucZ23PpQGipZFHDQqIga0K8fvp86DtP2Sm0dX3WTxkXrDAZk6vgAlrGcPOwZHLp/1dr1kZLVtYDPCDHGWNGSmpIsLjMMDkjSSgd3rSrYPvPPWEFwdXbCyf07cPfmNcRsmW9zuVSnQDFETdwHyajTpKVym4OjkwgamB4MJur5vZsXNLzP9ESfNVs2/a10Udu+basI+B0/fhxXrhiHFdK8v/76y+K+tN+nccg5aCQHldyzxQ4bx6wym47TS8MUf39KOrFJrl/nkSPMNo8MYy0uV7319/ejxkGjImriu2/jXtgdTFl7V0xXUEcqt50Li7fjljFWsJKTpR3/gvSwmUG0s+Dq5lZg62OMMVaw4nbPEpf7Mpoo857o3NqOW8RKgwoVK+KPRV9ix18r8ViH9laXoViQXuUEndrFLFBk3tWLgkbGE1L6rJEFLJdFql1dleCRr68vbt26ha9mf40zZ84o9YNkfgFBeO3Tb9GyZSu0aNECtWtLNWNlmzdvtj48LVuh8+w0Dmp80w9Y+L+K+DzpBcTqvawu1zTmd2xObyuud6kBuDhADE9kJV9YWFi+3t9b/9urTNfVH0VRwEGjok6lxnLDW1CrjGcjpvwltZhlrLijH2UqVFhQ5LN2BVPTyBWZmVL6MGcaMcZY0ZJyTRrqsS2jjbjUJ0SiCrcvZ4WsXNlA5Xrbtm2R9sc7eKZVJbNl0uEIlUGqsSgrX7UmZv8hFW53dHJCQkICgt2M2TJpDn6Fvu0lRUyMsSnQjh07xGWVKlXw7jtvY/ny5WL6zTffVJZJSU4SWUHHjx+zur6kpCQsWbIEv/++Mk/D03pXjMVbjwHrfN/EwtQh+DL5eSTojSccTb2S8KG4/O8VIHUWoNal5Ok5s+J5UrxChQp5vt9HH3+MqHvGYFMHw0YUBRw0KgZcKrTG2nsN4AZpqMzpMGNBPcaKK/qR9vHxKZR1F0SmEQWN5JRnzjRijLGixfHefnG5JbODuPQzJNh5i1hpULuWsWOWp6cnIm5cQr1y5hkmGQZHqKCDe4Y0WkAeBhVUSSqcrTcAiUkJuPq+8T5FpGxJsQsa9e3b1+y2r7/+WlxeuHRZXAZVqCT+b9UatahVaQ3Npy65zz77jDKPMsG0D2iGMqON9BgntHXF5e9pj6NRzB+5eg6eiedytRwrvpo0MWbB5sXSpUvR1Fg/vcjgoFExUDYoCLNPVcIS7+nKvMPXjV+YjBXXH/2CHpqWlJiImv7UdUCLlJQUcSYvP8QZJo2Dkrn09ttvF+h2MsYYyz/6bvdzkw60Y3VStmodD+sHhIwVJNPsaLVaOoxSq4CP+kiBA5IBR/gm2y5s7e7phQCVsewEMejNM5PYgzvlypq172KxDA1PW7ztjOiglpqaDLVKjcxM8/vJxahPnTptNp86rX377bdwdrORCW8woNGtLx/qObim8fC0ki4kJEQ58Wyr7pY13j6+uFcE80M4aFQM1K1bF9cvnkX1Msbx0NM3cZcFVrzllL3z2fuv4r9/1+V5nbFbP8CV94Gqd5fhjTfH4emnn87XtokCiBoNXFytpxkzxhizn9W/LYWnMxBlMGar1nDnoBErfE5Oxn1xPz9pSJlOp4WbswM0FD3KyjTSqm0XtqZhTxXitprN02QWwaPEIqpBgwZm02qNxmL/kvbh3D29xbSPXwBUGg3u3jNmfiUmJoqTixT4u3rVvDB2YGAgZs+eDY2N7njlYnfi3JUrOJ1ZE+G63HdslAtii21KlbKUWMl38uRJUXcrtzw8vOBoEqH59TiKBA4aFQNly5ZFanISdjVcgZ5OB8U8LwMXw2YlNGiUeAcfBixC1wuD8rzOFilSl8Gm6RsREnIVR45InUvySh7LfvPa1XzdnzHGWOGgg70VX48X1/dmNFPmN29sfiDJWGFwdHRUhkXRkKaqNWqK7Gaip3Fn9B41uMMjLdT8jibjz1QqNfrVMM88cM4wzzxiuefhXcZsmrLYXd2lAM2dm9dxK+SS2Ke7dPGiEkhq3qKl2Ndz97BevJq4eVovoXAtPALvJ72J/ve/QYiuos37964fZDbdP04aOkd803n/0t4yMzMRGVk4n7uUlBSrnf5yw8nZCY45l9OyCw4aFRNlAgIQFxePV9zWiOn94SpkaLnOCiv+QSNnF2N3ESFcCow+LEpJph+E/IiNjRVFsLkANmOMFS03b95Eo3LS9T2Zxjbmffr0sd9GsVIXNFq5cqXISvH29oEuq/aNHBbakdESAffN92VUMO6zU30dXxfzffh0dcE1BSlt2vUeYDEsyMNLCg7JYiPvipIDjz8zWkxfC7kqgkZlAsuKaapjacFKoSm1PgNhYdeU6X/T29ncrq+HNTabDtWXM64ng2uw2RsVP6fRPIUhIiLCImhkOs+Wu3fv4s65PejXqY4yL9CvaHw3cNComIi4G44pYwbCJbi5Mu/73dJYScaKc9DINNVbUEnp3QWxY5ffoBHtCLp6GlNJm7dsVSDbxBhj7OHQAWGjxvXF9VNaace6qlMinJ2d7bxlrDRo1aqV2H9xd5eGnzk4OiqZRt6uUkDpi+QXsTh1oNn9qkb+qVy31pXrXjjXuMkNudYk+eeff1CtZm3Uby4Fbj747jdx+dZbb4kTh8S/nNS9KjNDGr7q6OSMyd+vQc1atbOCRkEY//liDBr1hsVjpSRbDhl0SbmBn1L7K9NU/NoWNycHnJ7cU5l2hTHjxFOTAnAdK7sKuXZNnCQuDPHxxhFBN27cEJfXrhmDjdlRdlxYWBh2796NixOB8pmXlNt6Vk3CihW/w944aFRMzJ83H5Hht5Ho3UiZ9/3mIjLIkbGHCBo5OEg7WQ8re1cMKi2Qmpqa721zMAlmpadxrQzGGCsKboWGooKv9LtxSxsgLttWMc8qYKww0YklWWZGBtJSpKYeck0j8nnySLP7tAyRWq7bChpdOHsat29z4CgvpQ2eeOIJREXcU6Z9/APFZWJSMjQaKWjU4jEpaFOnSSvltfMLCMLlSxfFfqPGwQEtOvVC3xFj0WPwcLHMSx99aRGgkn20Syqe/SDPOx0Vl95uxn3cVGTLrE+4ldunzWxYvWYN/v777zzf79SpU7gTFo7CkmYyJG3MmDHiMqft/PLLL9GqVWtAlwH3bOfSL2irYuff83H54gnYEweNiokRI54Xl/tvqvCqq1S3JUljexwuY8Xlh59+sE0lZwJ/pT2GBH3eilBTdN6Ur7ex4GBeu/IcOnRI1ByQxcRyt0LGGCsKTp89h/LuadAZjN/RA9pzPSNmHwEB/gg5fxL3bt9EbLLtgILGkGE2PG35MfPbqYZJpUqVcO4ct2J/0L5j9dpSpiFp2Lqjcp0CQl+u3IGTJ45DldXZrmWXx/HsGx+gap2GYjq4Sg2UKRusdFgzDQB2fGIIXp/6Hdp0fxITPv8eQ16y7JyblMsEdgeN9UPscN9Oxon03A9Ru3jxIn5atizXy5cWL40ZgylTpuT5fv369cfqVStRWNKs1DGaNWuWzeVp6Fp4eBimfvSOxW1r0rphW+UP8Ne+/NVpLSgcNCom5C+1t996D08471XmJ6flLuLNWFENGtFZOlNfHXfEuMSJeOp+3tqZVon9y2xao5LW//yIF/Dnn8a08AdZvny56JqhNjlj6O5eNMYTM8ZYaXfrVihU7v7YmdFCmde8pjQEhbFHzdXVDfM+fgPLZ082m9/VyfIAzzP1OpwzotFQux9yAkqKk1QsuV0VY3BA9t5772Hq1KmFuv3Fcd/RdP+sTjNjTSEnZxd4+kgd7Y4f2K1kGD3x3CvKMi5uHqLbWssOXfDuxIk4vHu7clv1ek3Qtmd/Ud+oeafeKF+1Zr63k7qyyYa3qaRc31p7GRLUUoYkDDnXzQwNDcXGjRvF9bVr12LUSPPsNXvZtm1bnhoX0NCrwkKt7E+cyHsGzu3b2QrVF7B79+7B09s3z8dEhpQoi9sMKJiyHQ+Lg0bFSFJSkri8Uv41Zd66PfZNVWMsv+QvSFd3D7MuAz9dkDKPrugqA7rc1ySqFbbAbNpJLa3/119+xoEDB3K9nusJBpQbORcJTlk/6jZSlBljjD160dHRcHc0iGLDMtNhQYw9SilZQ9MS4swzkt1VqRZ1lJ883gWDjzTHoOTZGCLXSM46SCzjBrSqBMz+2thha/Xq1Vi/fn1hP4ViRdSKUalQLSvbiAJFZOmuSwgIrihqFuXEt4w0hI0KYEdHx6D3sFE2ly2TeBIVo/8RBbF1egP+OhVmc9mGDsZuaDUdYqDRGIcgdq0jPSa5EZ0MvSorw/4BNY3mzp2LJ598UtS6kQuwFwU9exrrND3I6P+NUYZnFbTxEyagqDIYDOgx5EU0bNleTAdVrJrj8nLjHWfzwRdFCgeNihEqukcfvqdeMKau/fi7NFSNseKGCsN16t0fvmX8zcaomzKkmbekzQsXtRRw8nEFDNf/yXXBwX8iPOEUWBWX3aVUZsYYY0VDTEwMzp46gQpJB5UCtA68J8vsqHxwOaU7l6m/0zthwP2voTfkHNC8dE86WCzjDhx+E8i8fcjsdj5pZa5s2bK4euEsXDzMS3TI3c/kepRyXSJTL334OfzKSq9XcnIqrl65jMZtO1t9HJeMKPQ6PQAdL72KwPiDmPnvRRy+Ybto8s8VlijXvfRJZsPeOtUyBo1O3Y6j8Ym5yjS6fOWKuNy6dSvK0HablE2wN9OTvdlt2bJFGZ518eIFrFu3rsAfn4Isi7//Xlzv2av3Q60rLi5OrC+3dVATEy0LpGeXkZEBRycnvPP1Mvyy/7oovp7zNkjHOy45BI1M31P2UHTefSxXPpn8sThzMdhZSqdM0ILPQrBiaeDAgbh89iTUKrXNnaIMnfVgUm6oVdI6978OfN3hEnB8Tq7ul+5m/HFnjDFWdIwcJbXLVpu0Lx/TWmqZzZg9LP3hB6uZRuS0thZWVl+R4/3Tsp3P+u+VonOQWJS5uknd6zx9zIcAUQFsv8AgNGptUjsoS6cnn1Yyk1JTpQwxW5lJAQlHjdcTjyMlwzzAM8Z1rXK9fqAjtjVcjSHNK6BDDX+snTkWsSa1ME0zIU/ficfshCG5Chr5lfGXrji6YNpFP1SeuMFif5mGQdlDTkPOevfujT179ojrFStVEgEkOZOmoCxcuFAJXNFjZPfFF1+I4X25HeL26aefom3bdg8c6nb79m14eXnlKmhEjX4cHJ3EcEhvP39UryV1+7QmPavbczkrq+bhaSxfKlasiDnffocODtKbOqZ8V3HwbStTg7GiLJO+JFUq5f2b/X2cps3/j4wm6zu2nnw8cXlVntfx2pQ5mL3avMA2Y4wx+zh1+gxe+2Q24vXSASMZ0clYFJexR810GFLqzZMWt193aoQ4t7o276/Pds7Mm7Kj5cCASsWZRjbItYuQ7YCaAm1zNxyGb0DOwWR91klJW0Ejndo43wDLbncndv6nXO/TtBq0Dh5oWskXfRpKmUy9evWy+di/JHXD3owmtBE5bmPVqtKQpjW7jO+rBl3644tZnynT5cqVs8sxYPaOxdaaylB9Lq1Wr9RBqlqtGt5//4MCeXzTYBkNHcyO6oHltvZStWrVMG3aNJw+fQrNmzfPcdkpn36a6+wlhzwMKbxy+ZIohr/uReO8Zal9USVqI45l1hPT9g4dcdCoGOrYoT3i7t5Rpl0q1lciuowVJ1TMkIoFyjtF2X/4krKfgstHppEil2m9zimRyvX2vQciqGJWdUrGGGN2O8Hw7PARuH3rBrp3bY89Gc2U24K8s7WxZsxOojd8Cd8U8+yGWzEp8Ei/bfM+h60kQ8hZGRQA4aCRdUNfmSguXbIyjvJK7qBWqYb1gJ5ObfxeSXYOhpezeeAohWor/fkuZgxsCF838x7p1WrWRvfu3XN8/Ofjpz+wbIIckPxv+1ZlXr86yRiV8RGQHq/MW7Ei52y2whAba3uoHnn++edRr149qLM6JB85cgQ3b9zA55/b7iCWE61Wi717jY2gXFyMr8+yH41DA00VRh2oFi2MDRhykpiSataF+UGuXrmCqnIcNMuUJCnt8Jy2BoqCIlxuidnStGlTfHb4LtBDmq4xbBJ+WrYcnTtbH5fLWJGlUomdIgoW0Y7RO2vOmN2cmctMo3379qFD9pnZ036zfXkvW7YMkZGRmDhR2vGQaUw6XiSkZsLLtegUH2SMsdIoPDwc//xLw/Id4Zx4B/vSGsGgk867ZmbSyQcg69hEyNaU0wyN+DE9lsjLspQca+sYvrCWJVllWvK8rFZLJ2MKZlnaXnm0VGEtS7GSnEax5GVZej/IP+eFv6z0YupTU1E2OQyxzpWlBdQGbLsQgdQyemigglZvediVkgFkaGnfQwdNVgOPtLQMODnRsk5ISEizeI9SLEFOcKL/W/o/tiW/y9J7LGvEzEMva/r5fPhlpf9rd68AzNt4Aj5ljEfa2hzWS+8bjcl//1MvT0L/Ue9CrXGxvJ8KCLpvDFBkaJ1QRRuC07pqxu108kNyUpr4/zT97qFpg8HR4jWTv69UGuOHNzNDD4OV758LFy6gfv16MGjTsGAQ8FXl96DNun9gYBC8nB2RceoX6BtTYyRHPP/8KAwfPrxQviNq1qqC8+fOwcPDw2RZR1y/fgd16jSy+flMS6P/VEckxFOdIEckJWWgUTlH9KgFJN5PgIe3V56+I+j/5LHHHoNWaxCfOWdnT+W9QGbM/BqDBw1ErVpVlfVqNE45fL/TfbWoVrchrl+kYw/6UEtvaGv3ccj63EtDRtVITzfYHD5Ky6anZ8DLr4JIJpOfm7X3hen3SbCXChla6c30VdJw5T1TVHDQqBiiN6mmak+87fYLZqc8DycPH6xbvA5Lf/zBLE2WsaIuIy0NKrUUNIpMTMf6U+aFJJccisD0ilUQl5IJP3cnpaZF82ZN8frrr4vpqKgodOzYEYavzNet0mth1lAnI8Hs9h+XLhWR/exBoxQXf+MPb1b6MtcVYIwx+ylTpgw6dNsHvYMzVq+4h2thvRGvrQEvpGLGDKBmTeC554zLf/ml7QPTKlWAF02GAMyZQ0VdrS8bHAy89JJxev58qn9hfdmAAGDsWOP04sX0+2R9WR8f4K23jNM//USBMevLurkBpj9Tv/0G3Lxp++Dqww+N06tWAVeNTZ0sTJlivL52LR2Y2V520iTjwSZ1AT91yvay775LzVuk61u2AEeN5WEs0P8D/X+QHTuAnJqdvvYaHTRL1ynpYNcu28tSw6by5aXrhw7R8Bjby9L7gd4X5Phx4J9/bC/77LNArVrS9bNnqa4oXZuk3H7tZDvEu0krc6t9F04BSWgbuwx/aKdg9emsWjYmjsQEYsaOSAxosB5Nyp8W8/744wRCQzsgPn4skhITxXvcVJ8+QKtW0nUq27Jsme3t7dEDaC81cMLdu8AS60kZAp17ls8/03t3gXlTWjPt2lEXLek6Jd3Q58iWli2BJ56QrtNnjT6ftjRpAgwYIF2nz3D25y7/X/+1zBvlq7qhTXfjh5fm2RJUMRPtexuX3b62HHRa6/t2/uW0eNbvJ2V69YaGuHFNj3i9ccjbxdBXER+biQWfnMSrn9RThrltW+OJsNvPWWz3C66PY/6h8/BsdktMuyEVi3+vg9CUVDHUSh6KRhk1n332B774YhIe02xHp3bA51FeSDpVAbokFxxy6ol4h5rY9VMK2g3SZv1/pIjhYs7Ozrn6jvDxXYCGDRqIIExO3xF0Mjf01i1R+JmCRsbviEmYOVNl8R1g+h0B9KVXE6dOuMPHrz+2bq2ATtUmwcMJmD7uFCYveCxP3xHy8e327QYcPKjCwYP0AZiEdj0H4MDW9fhwUgJW/HYcj3X6GV98/rZYNjKytpX3j7K1dJSB7oOfx+Lp7wJoQ58WeHn5KPe5fv06KleuLB77xazviMxM+j9vjnffjcPZs2fRqVMnq98RGRnpcHR0Rug1Rxzf7Sbmx8W8ZLE9Q4YA9esD/oH03iqDGTuk74g5Kc9arFdVx3bG4qPAw9OKqeq1G2KE60ZxPSbVgHLV6+FKVpV9xooLao+qgpR+be2n+7cTMfhm2xU0m7ZNaXX66y8/m41Tnvjee1bXbTDoUCFrR1SIMd8bpkAVDY0zLm/Atagks2XOhknpv5wezhhj9kMHLH4BgXB184Ban4kzWumovZyX+bAQxuyNTlhll2xwg9Zg/ZDLwaui2fSZcOCTTz4R191cXQu8gHBxRvti3r5l0GvoqEJ/rDt+xrbyQff3Q59tL5UCKa7u7ji8YxNmvmFygG8wwM3KkDkqx6BKM568dFOlAUnhIvDw88/LlfkZcaHoSdk4sRHo5GIZQc3MyveIT0xBPEXrssjvmQehDPvXx47Fi6aRcxvkkhGi/mg2Ybai3NmkpiTD08tHDNXyk2In0CQbS6zklkNWOldYWJjZNrm6U8aR5Pz5c1i4YD6efvoZMS0H0bKT9+lrNmgOtWn6majFZDwr8MsvP4v/L1ParFS9H3/8Ebt27bS5vbExsUonv9xQqzUYOlo6GV5UqQx8NGS1eJe3t7f4MOamQro90NCabtdGYpDuZ0Tp/VAp5hiSTmzACTpFwlgxQNk7tRu1gLurM/7560/A1RutZ+zI8T43Zz0Bd3d3kVm0efNmMa9f//74e8MGi0yjl3Y3xn8HTiNErrmn0gATjDtzbdu1w+3QUNy5I/14Ld13A1M3mgeWWlX1w4Am5TH5+Z4IuXKpYJ44Y6zU/WaXFoX5Wmw+HSEyUhtd/wz9z/YX8yZ3DsTzPVrw8DQby/LwtEezrLOzk9K5q/ewkTgbnJVWo6YhLNLV0c7r8K7rL8iEBs4qaV9EZ1CjX8qvyLjwF/5rvUIMT1t/Dhi4TIX0dD3atGuPk8ePiqEupkrr8DT6XqlQsRKWbD9rdchZXoan5bQsxYdGHKpsMjzNETWjjZ2qj/oNR4+5SVBX6ohTh6mmrBa/HZIyiFKS0vD1uGdx6sQxi9U6OzvCwS8I5ccsgpcqCcf738W3+9R49913kJaWjkOHDqHtISlz5X5QLwRGS8kBVAxZHqrU3ekwOjiewqa1/+Klr7bi1XHjcf3SeTz1VH+sXr06x+8IKs4cFEQZLdKTpxBATp9P6pDm5+eBd955B19++aVYNjU1Hf4BgWjarDn27DIWAzf9fErZ+fTmoA+KCu269ELNysFYXGepWC7MvQ2qjN2Tp++Iq1evoEG92tiybTfat39M+czN33gcY/s2h6urO16e/A3mfDBSud+BA4fRvHlWSl6WX375BQsWLUJsXDw+Wboeh//biEWfjsdHC9Zg+mvPwMvbF1GREVmvl/QYp06dRsOGdcV788uvZmPiuxNRu25DXL54weKzSej92/6xx9B3zHuoXLOh8tw+HdUXF8+dsfp9UrVGbayZ+RQaXpfS8Ezfb7I369zG26Nfhr1+s3l4WjE1YsQIfDdwJPwaJCAKfvBs0Bl7f5iCTZs24Qk5B5SxIs7Dxw+GjBTxw3X3Po17fjAnZ2fExBhbmdoeOmbcWSM6gzxa2XgGxfS+2QNG5MiNWBE04uFpjDFmX45OgIMj8NvdSkpdkKceq2sW+JDl4QRvnpbNS13VorCsaSCtOCxrGogoXstKB+FSHaIMs7o1sh/TB+KcvgYOZzbEMu/JUIefxgj3ddKNNZ7GzP9+xUfdqbYRzTDg6tXzOHPqMMr4++X4HqUDzty+h/OyLO32FLVlly9fgoz0BPE9YI2t+Q+7LDQG5TUd57YCgU5xOHMXaF6VootSFO7k/h1o2r4b0tPiYTCk2XiOWhi0UpAhw+AAR1Uq1KJLWya02hR07txOOQHqH/2vuEw3SB8g+fF36FqJv36NIpCWlgBPL8pqyjTLSLP1HaFW07Zm5vrzmZIiLfvVV19h1qxZcHDQwGBIR/lKwYiMvP2A15G2Ryc6iLl6OCMlJQ5ODtL6UkL3m+2fZ98GyuJycnIyyxRyiTyItJlA+PXpcOpChcGldfn4e6NZ2zY4c/QgGtOYSRNXr15C27bmQaPY2Hs4cewAylesBCdnJ+iyooeZmXQMkgl3DyeT5yXddu3aRTRuLBVMl7K79IiOCoObm+my5qh0RlDFqlBrIP6ISpVpdXmR0aVSwcmQrPwfWfsOsfeRCA9PK6ZoWE311v0wwEVKjbsUkSwu+/bty6msrNhQazTivUxfmIMW5lDIwISjgyPSM3I6RSSpWtbd7Av295PmX7cUqDIdnpYTTshkjLGiYXVcE+W6t2f+OicxVpCoGQdxdHIS+wudagVYXY4CRuTF+KkY4f6X2W2XY6UD5MpZw+rHvPyK2J/39DQOvyntHtTmvbD8ntZbuT7IxZhdo9MZ07ai70rDptJSklGeiqFZMee7uUrHtAw4ikLX8hAwyuoxpRZBF2q73s/qujxqtBAdzFzcPcT0zl27kZaWhj/++MPm88jr8aE8FIvMp4JuWcPCPLy8ceNaCNatM8+GqVe/Pi5evGi+jsxMePmWQegtY5vA+mX1OaZL1m/QAG+ZFn0D4HvtRxH0rHBfKk9BGWcyDy8fsa0O2SKB1ur8ulKROBEQk05U67KeI21jlVr14Zb1/2mKAliylDTpPRgTHQ0fvzKwhQJemmzRsJRsr7Hp60LL+ieeQFHGQaNi7Mn31uAxJ+kNptMb8NpXv6BscAXcuHHD3pvGWK5Q0EZuKZvbuIyvnx8yTcYTJMSbF7iWObt6mhXCDonS5VjTyJb0XHZwY4yVPFQrcMyYMRg0aBCmTJliluVY2GgnvUqVKqK1cOvWrUXL4pzQ0IQ6deqI5Rs2bIh/slXzpe/ZyZMno1y5cnB1dRUtoa9mq4BKByHPPfecSFP38fHB6NGjkZRkXuvtkaMzwJueQ5d/K+DZfcYhIy3S9tt1sxiTtcqqSk0ntfQ6HXrWK4u3utVEnwZBuV5Hom89cRmUNULk4H4pEOXi6loYm1ws+fsbG5U8Sj+ZBG6C1cbq9vRaywwwGIMk3tYLco9743UM6PekdF9oEBFyFO9S1XjaR716GVWytVwnC1Isi6eTFWmPY80XI9E8fYv0uFotQkNDMWzYMJvPQw5QkaDgrCrxOaAglEyun0RBI8oeIs8/b+zYdvr0aVy8cEEMY5O16NhVXDq4uEGXka3bQEaizcel0hH0W2TqwDFpSKJgMMDP3xiY3bPlb+VEtK2glyz87j1x6ZpVd6pFp16YNG+FCBh99vM/SEu17IpgeqyQYXL8Qb+jttBj03BVU3qD3uz+Mgq0Xbt0HpkadxzOqI+p6mko72Nl3XYe9cBBo+JM44j6DsYAkb5sXXR4fLAYosZYcUCF8ejP9IcsN8PTIqOkwnR0P1uF6PR6ndn3q1knNUB0JMnNsLP0TPNhbIyx0oOCRXRA+MEHH4hgy+OPP47//jOv41AYVq1ahQkTJojipidOnEDjxo3Rq1cvi6KcsgMHDuCZZ54RQZ6TJ09iwIAB4u/cuXPKMl988QW+++47LFq0CIcPHxb14WidpgcGFDA6f/68aDawceNG7NmzBy+Ztg+zBwcXIDUaaoMW57VShyEyfuBjdt0sxrJnNMTERIvsk0snDyPQywX1gm1388oupJwUmIjJloxAzUKYpEKFCnhyeMHWdLHKYL5PelNnzBxygA4vrQZatGhhlrmzepE0rkybmQFHGktrwxczpyvXD8QYa8hcXtwXN4xN+BTxBtuZZhtHA/MHAR1rOsPHx1cJbpgWyDZlur3uHh4WQY7svy+mWUPye5yCHpTR06h1R3Tp1l25felSqV7RT9QKMouPvxQ0dffwgirT/ARvbJx5UMhW4WuSkpICR61J28rEUCVwRWhbZCPGT1auWyv2LbfdkbPEvP38Ub9Fe5PADrBmzRqbmUbp6emo2bAZGrWx7JqW/f86exCrjH+g1aLiy5cvx9f9gODorRgW/zmWRjRFWFbJjqZ+Nlp7lsagUV7PpN2/fx9jx44VO2+U+lWrVi2Ls2l5XWdxlunXEKNcpfTAf8/dQ7kqNXHmjEk0lrEijIIxcqZRblFkXz57YO0AKlrvjUwDjbs2DxrRT4Wpy5cvKz+w0Um2U5619AvCGCuVaD+CMo1atmyJl19+WQRSxo8fX+iP+/XXX4vHHTlyJOrVqycCPW5ubsqOeXbffvstevfuLc5a161bF9OmTUOzZs0wb948cTt9x86ZMwcfffQR+vfvj0aNGuHnn39GeHg41ks9w8UBAjUY+OGHH8S+U4cOHTB37lysXLlSLGc39EXefQEONV+NN/TzYNBlir+WbbuKAxj6y35GWZ5v7S/7TntelqXpR71s9jPTeVmW/l8KalnT3+nCWpYOtApqWdOTUYW9rOn7LzLsNqa/NkwED7xdjAeNBoNeee9a+0txkjIn6hq7ugt6g+X2mB780/bktL35XZb+rwtqWdP/n4dZVgxPo+LNmRniTx5apLzXsuZb+8vLsoYMY3ZlvN7d7HVqOxdYchiYOXMmzp809olPSUpAfGw01v/0Ha6FXLX5ua9WqYJyn2sXpOO1GkHOeK5eAjK0UP4ydeYjuAw6rdl21MJVZdmZn02Cs4uL8n8XERFh9fFNTxBk/3xS4KJSpUpmy98KDbVYloppp6Qko/fT/xPH4vKyAWXNs+qm/vQ3khOlQJHaQYPYyHCz53ct5IrN7wiZPE3768lZs3V6YN+mn3HiyCF8tHCVeL36vTBWeU0pu6eMSUZa9v+D1BQpCBMRfsfss0xZY3T/u3dCMWTIELPtoOX0WcvevRuOp156BxO+WGLzvTx//gLExcaI4xt5vfSnUmtE5m727xMKyI1/DEjQuVp8L2gzja+7vdm1ELZ8Jo12hmgHhXZo6KwXvTkCAwMtlqf/3B49eojbKApYvnx53Lp1S6RQ53edxZ2m2Vg8HvEdlqYOENOBFapg6zbzCClj9kTDOcqUsT7ul75Q5ZpGuUXBYoeslM+jR40/2PcSgGS38ugW9z3qaG6gdcJSkV0UpgvA3oymcHE/YFF/QD4bk5JuOQTNQ5WCJIMbMnV65UeGMVY6vPnmm2jSpAm6dOkiAi+vvy61wqXvstzWQssv2tc5fvy4yG6S0WPScLKDBw9avQ/Np30fU7TvIweEaNj6vXv3xDpk1DGF9pPovk8//bS4pP0pOoMuo+XpsSkzaeDAgRaPSwdxpnVGqBNLofCpjgWrF+LEaSl45WzIwIwZp5Sba9asKbKkZDREwtoZXUInFU3PQNN+Ip3JtiY4ONgs04pOStLJS2sCAgLESU3Z4sWLRTFUq0/Hx8esZgednbcVmKNg4cSJE5Xp3377DTdv3rS6rKOjIz788EOzfeLsQxBN0ZBL2dq1a3HhgmVDCNmkSZOUM+4UPD11yvj/nx0FLymTjWzZssXstzo7+n+Q9+N37NghsuZsee2115R9+b1792LXrl02l6WgKx0nEOpKRdlzttD7gd4XhD572U9Gm3r22WfFCWtC7dLlz5gsNETKzli3dC7a9ngS7/Ssja+2XkZm9G2kXJb2Paxxq9lWFEd2UmlFLoQcL4iOisKMGTPMlu3Tp48yJI6GJFFHZVvouKl9eymT4u7du1iyZInNZTt37iz+CL13FyxYYHPZdu3aoWfPnsq+FH2ObKGgu9ykhz5rpkOYsqPvXcqSJPQZNn3uly5dwpVL1/HXMqm+TvmqNdGme1/ldnm+NUEVq6B9b+N32MZfv7cIJMnqeEQBFYEQbQWcyKyLhGN/wZCZjnLqKFzLGqG8c6cxy50yPI+cOoff532GY7upSDMsXjPT74hyiMJdBGDPlTRUatYOUa6V8d72v+CtShHd9W7qyqGhewTGdDQOUUo6ux26JOPw6AyHy5iRlQDjtvcTALWVoNG6deuQmmrZXIYCPtnJ3xH0/U/f5abbfcykIzf99tF3BH1GExPicXDb37hz6YSy/P4DB+FfrgKi70odieMi70KlVqNx2844eWA3yjhnwLRBcpfGxsCcte8IOnaQ1928eXMl327HVeDX//4U188c2oMLxw4iLTVZef0pgyrN5Llnfx0OHDAOa74fHQm/QCnYdfXcCZw7sk+MfqAALw3lNu24VqtWLfEdkZGpQ+L9GGxYLgWGrL3On376qXI99NolHM96T8RERYii4vJ3I6EAFQXrkA4sudME8SfNa1LdcMtEfIqUVaWqK302S2WmUV7PpNF8GuNIX9D0BUgvXqdOnUTadn7XWdypy3dACwfjj3zK/as4e+a0XbeJsexj0E0j9oSGeBCRuqnKfaFpWk5E7rOCTKbDxtRqFWYkjxbXL+mqIjriLoa98g56xC7A+0lvIrJyX4zJ2vn/91+pK4V8UJGRrTjg0TLD4Qxpm5PTtdDpua4RY6UJZe1QJmNYWJjYj6hevbpoNNGgQQOzwEthiI6mIS46lC1rnnJA0xT4sYbm57S8fPmgZbKfXKMhAn5+fjYfl862U/BJ/qtYsSIKS2SiMTjVvprxZCFjRQUFWI3FkaX9GkdN7oeX/ZjaX1w+1QgY3xEo7wUkJtiu/VLa0HcyZWwUNq/U6+Kye9wiTEwap8x/ymWHyHSRA7Smx55Uy+jWlfO5Wn8CpKCBQaVBvKtUp+3X1D7icn7KUGxK74gvkl9E85gVyn26Riw0W4fWrB9w1rysoJGtE7Hyvnb5KjVytd9Nv0NdBz6H8pWrKYFSCvrR8DTa/75x/bqy3PZtWy2G5QVVrIbq9ZqgjctpPF4n27qzusjZ2kb6LNHvDhUIp+dVz+Sn6174bWUZ4uzqhi79nxHXqaB09qLi2UtTuLrbHvJHxezl5ykzrRWso1pFeWq9l/37wfJ4wt9HKs59KKtQvqkMfdEZnmq3TKP8nEnbsGED2rZtK6K0f/31l4jYUsT/vffeE6ld+VnnIz1TVhj862N7nT+g2qeHAWr8fq8mPNxdRDTZ19fX3lvHmEBf+KZjgmkIhJJplIeaRpk6gzhzQcXkslOpDNiRYWytGRV5D82r1EDKRelMzR33Rlj1zSQsWbxYGSstP+5/l8yHuXmpkhBjkA5KEtO0SsE8xljpQGfy6U9G+xeUhXHmzBnxxyS0v2Wa4UT7T4UROFpz/A4ulu0G76wDh29ebyqGRsiyZ3/JxWWtyV6jLnuXnpyWpf1PWwdb2ZelDKXcLksnOnN78oQyqnK7LBXFze3vK9XvkjM8rDE9SKYAqunnI6dlKeONsl1ys2y3bt2UTJcHLduxY0eR7ZKbmiht2rQR2S65WZayGijbJTfLUsF5OkEtZxd4eHggIatWy5PPvwInFzfltXb0rwhvv6E21wuVGp8nj8Qo17+wcrgWWj0wqBHw5Ap3keVlqysUZSlkv93WsvSZye2ydIyV22UpYJzTsqafTzqRn9tl6fU2XZb+j8tVqob+L0oZfZQVYkqeb032ZfvmUBup1l0vINR43OjVQgrmfez/O349BsSlSpl3tD10DEoZ8FptJkJDLovlKKnB2nOU3wt+qgQkG9zQqGE1nHU1vicm+a/BT9HytPl3xJpTOgS/0gMOHtKxHYVNJvkbM6eWhhiUoBFldVFThOx+/fVXcTlxzs8YN6AdfvzxR7zwwgviO+Kbb77B1q1bxYmRfv2k+lrTp3+G8Ew3uDg5KN8Rhw4fQbOOPVC1TmPs2bRaPE/Kvpw+fTocsvbzXd080LR9NzRp10VMP73fMgvtsIPK6ncEBYqmTp0qhkfT5SuvvCL+f12yPnbdagKxKbHYdoZe79ctvvtP7N0uLn39AxEXHWnxOhw4fAxatbPILPLxN54kqdmgGarXa4xbV87i+N4d4vubhmeT/fv3S9lAYl8gHVXrNESzDt1wavc/IsuVvjdNv5tMM40qVa+DClVriuuXT+wXtQdNk13o++TaQWmE0AnvPvBuax5U6hSciK3hUpBLpbJe07DEB41yOpNG6YfWXL9+XRSgpB9MSh0NCQkRqaqULUDFIvOzTvlMmekLXNx06zMYqtlDYWg9Ukz/+Jyz2LmV01EZszdbbT6lQti5r2mkpY5nNoJM2WPxNDTtXoaLMi1nDpnu9MnD5uqVMxar/MnlHTirjCnLG06Hi50j0RLTSvtOxljJR0Phx40bh927dz+S7Ez6rqG6FKZoOijIejcmmp/T8vIlzTMNttC0fIBMy2SvE0cHIZThbetxaWee/grb+pNhUGmknfK0/xYieMY6s5307ExPUjxIXpbN6TGL4rKmAY7isCy973P7O1sUlzV9L1E2gukBrQhaaMwPcLdPeAw/H7wl/mS1o9fjZkBfOKmB+sGO8C0TINZ77NgxcYBKARpT9Bi5fQ/nZVnaNytKy1JRfjmrxMFGoWlb8/O6rM7FvKSC/N1DsZMzIXdx/spNZbvo+5Q+k1ez6hNl325r3CHVFnIoUwmqdOPn+ePUN5THsubeLxNQ8XUp8CNvj8zVQS+GmuX0On8yZQraVQFeuDUE+xsD//vf/1C5cmVlGDL5/PPP8dRTT4nr8UnJ0Lh7iiwqCgzRZ/lOWDjqdB6IlKx6RfQ48u9GcOXquB1yCR8uWGnWbt50O2V6babV7wj5ekxsnEjooN8gEQxzofd9vPgIUdBOrNfZuI8vkwNB/V58HXdO7xfbRyd6qI4fuX8/TgxTDAyuYPb5pJEP9Pf69AVYPOUNi+HN6qxlw8PuwCXrPUijEIYPlzrIfTV7Nnx9fDFqlHQsnn29pFzFylbfG/739yIVzla/I6p5G6CKyHpP6GzXXy0VhbDzgg4UKXWaxonTmQA6g0Jjtyl1/GHPlNF4XPnv9m0p7a24oDdy6wpSahtJ9KqG3f9J4ycZKwpmzZpldb5KrRI/BtbGXq/2MdZwkGVqDUhNTVGCRj/9tMxmdzSaToXxByVUbzxQorOBRN7Zk383MqJD0VBtHmBuUslH7PzZqo/BGCv5KNNIroVW2GiHkvZxqHaEjL7zaJqyra2h+abLE6rhIi9ftWpVEfgxXYaygqhWkbwMXdKBAWVsy+hEHT021T6ypwxKu6CTZHUCkR5yME+BE8YeFdOD0NycDKsR6ImnW0oZDNY4u7gq2SmUKWXamaq02b5dyiAx5KEGZn5Rp0aqL5Xd10f94ekXJDLXSOs2bUTWSPZsF8qmyomDSnoO8TAPAK5K65Xj/a6cPoYvPL61epufi07Uy7F2opZ+Cyj4HxsTg1l9AO/MMKx6XrqNki6IXKuNCjXL6C3s6e2HrWtXiCwjsnrV7/ApE4D6LaQsP2q6IGd2tuvZH5Vr1hWZOA/y9/fWs83o98bNwxPLs+p00f8tHScEOxs7wlFc5fEhI6ze38NbysSioXLx8fdFsJVeI/m4gWqEdewzGK9NlbKIsqNAFN3X9P+hRm1j1pZOp4e7p/S63bp+TZn/0YcfYsZMy/pGpijQZO1YYvd/O1A3WqrTZKpTrQC4643POyLc+HilKmiUnzNpFM2lMZWmUX3qEkKpbLRDl591EjpL5uXlZfZX3AwdNBBeidKYy83p7fCCbnqeigszVpio+441opWsxkF8iWqyRX1aOloW5IyJTxBB3ZSs8cp//73BZF3Z1q0CHEy+4Ro4hCjX5e8QF1dp6JryUTHo4ZT19fK0yxZx6eakgV6vMxvCyhhjhYmGfFHBWupoQ13NXn31VVGngYYxkREjRpgNxacsKBr2O3v2bJFZTQWOaWdZLuBNB540DIuGENBQfyrgS+ugQs/ykCTan6JaTlQXkrrOUko+3Z+KZNNy9vTHK22xaHgztKvsiSCTTCnGiorAskEWnb+s6VwrAI8Hp6PJVfmg2PY63Qzm5TJsFWwvDSiARqhIcWFTGbSoFW1e4Pzz4PVYctb8WPLQwYMWwykpcPOgOrrn9NXE5V/peStsTN/jf0TWt3qbRm18v1Hh/Pc/+ED8ZlC5EipY/sUXX6Bth46oF2wecJePmeU6PaYjc7K3jZf3g8uUDYaLmzt8/cqIgtF3wsLE/Cbtu2LGL1L5iQf5qrNlggaNGBr9v/+hbuPmiImJNgaNstWxyqlMmFxXiQI7x44cVoalyp3jqMQFZavlSKUSv5HWPssaBwfl/8TL21hbj7YzMiLCYuixqd2bN+DJJ580m3fnzh24ZjsH0riCN97rXQe96gfBNcMY06jglFj8gkZ00EZPUkY7F7QzQhlAhXkmjYZb0ZA002DIlStXRDCJ1pefdZYUNK46+uA6cX1PRnP4eThix2rzommMPSp//rlWjI2WZW/5Krsf0BD3WryKQX/chS4Xre0//vxbhN8x/tBQsMlRYz3T6JOhleBgkmFeVSP9qBG5c0GjJs2k7cv6QXDV6JXOGA6Qdv7oJvoxtdaqlDFWMlDdBArSUKAle+F+e6BMajr4oB1yGj5GnaooKCQPv6eOSdQJSUa1XVasWCH2w+isKnWYpaYhVJ/C9EDijTfeELUaaEeazqTSOl1cXMw6c1EtDKotQzVrqK5EXvbtCpOjRo346AizzjOMFRVU08ZUemoKkhOlLIG21Y3DnVpV9YO/oxb+fn5iumag7aK85PrVSzh37py4XhS+m+wlM2s/MrflDB6GZ5pxuKDsgwWHcOmC9Drk5O2331Y62xWUe8uNddd23zRGGOL0nlYDKbT//fmsWSIgRKVd5P3wgMCySHGXAlbE3ckYTHHL+l51yQrOSffRigBJt4HPIiAwUOmAJw8Lk4egncsKsFCBbGtiHGxn05lauWoVtm7ZArVaY5YRm3TfvAslZRr9u/rnHIcd+mZ1RZPJjXAi7oXnGNghe7b8bdYJ09byaVmjJOj4Y+voNPz6lBTUefdr690MU5OTRFc4U1QDsEN186y2oS0qwjsrkhTm102Z72znChn5qmlExadpp+P5558XWT5UvKp+/fpiZ4OmTdvUPehMGhXgovau9AGjdo3Zz6RRu0yqOUToTBu1vqUzarTjQy0CqdUdtcbN7TpLqho1akB/7xJcHYBUrSO2pbdGw/NUnNJ2UTjGCsub495EpYoVlXas1oJGAfVaIC7AdrFJaw45Ssv7ZO1sBXoAFycCmy4C3vQ7Z8wmxfPx0xARJw1DI47QKUOFaWhDo9YdkZm1A6bPCljVDdSjaVb9+J0ZUtvpfVej4eXhxZl7jJVgdFaR9mFof4G+H6i4bbNmzcSJKLrMPvzgUaAsHzlTKDtrrcapdS/92UI7vlRYlP5soU5pFHwqqu7evo7q1Y0HPYwVFW6ubiad0yDar8fcC8ek+SvRt2E5VPf3QJC3C3zcnHBHq4Wjk3RQmD3L2lSCK73Xr4tW56S4lc8oSHLA7FEMT6t/ZwG1Q1CmAzydcezygwNGhVH3snLKJXTs3haNGr8iphOOrIV7vU7ieqrBGb6QAhWmmfUy2vc2Lf9wLSQEFZtIxbrJ002Av65L2UN/rlktLgPKBplnGlFDqUEjoE+IxN69Ul0pawaOMh6LZ+ell7KGHiT8nlQbyfT3loZktm8hFZuX0b58qy5SF+bs5EBW2fJSVzrZit9+wxuvvw5Pr7x13hwxfjL2b5JqRWVHRbFJDX+gfWXpfUkFuytWr52rddOQQXIpxQ8wKXNkGqRKd/Kn00QoCvIVNKKItxxF/eOPP8SZLEpjpsgmna3LbdCIzqRFRUWJ5SnYRGfTsp9JM33jUDRuy5YtGD9+vChoRQElCiBR5frcrrMka9e+A26qtEiFA35LexyrfPZAp83Md2tAxvKLzgSZfnZNU7blANLjLcoiryVldRpns/TTl9sCfm7A880tl43QmxcynJ3yPCpWOyJNqFRwdHZVdkLkLCcNjDsjsXppzHKGTg+VRhpTzRgrmWgfhr63Ll++jBMnTih/69atU2o9POjsJCtcNEIhMjwC9eo0QvaEC/q5Ma23nFNCBr2MpiWR8rIslaOwlehQWMsS07qpeVmWfrZyOsbOy7K0vfJHoLCWpd0DG30z8rwsvR/k3ZBHsaxe7wCNKGIsvbCRd+7i+qXTyndHnSAv6HUAJSSlp9HBuLPy3jPoVDQmihqoZa1XBZ3BAcmii6sj7t6l7ARHaDS030LBCelPelzp/9iW/C5L77GcSjnmZVnTz2d+ll23bj3CwyjbxBE6vYP4PyT0XtCYfO6zJXuZycuymTrzw+Oxj9XEyKzXNfv3helnmYal5eZzrzvxJzTNBkuvuxWJp7YgbvsClKtYHmV79cfAgQPw5JODkJSUjI9ffwlL4qX7pWqdkWGQHry8ZwZ2vAKsOwvM20/br8KVKzezGhU4QqtVo4afChlaRzg5SE/+h6HAf/N9xXM6dvSU9B5zcFOeI11S1o+njx9iY+OQkUFvdkfl/y46koIe0uOXCaoqnrfy+dRK/w+qxFCsju+Ens4H4KU2Dq9M0asgh2/k7wjaRrE+lRO+XnMIiz59C1fOHocuJU6pQaHTq2HQa9B1wEirr6GrhxdeeHsKnETGFK3PGMhr2/Yx6fGy7kcJTfJnmT6bxu8p6Tn5lAlEt0GjsW/jWnEbLXs/LlZZ1snZCxnpqeJ5ZmR9rgIC/eHtVxbvzF5qsd7h46fj128+Vf5/z5+/Kl6n7zykEzm0nnGda5k9L12myub7pFgEjWhIiNwtgwqTya35KKXZNF26MM6k0TCzQ4cO5XudJVmTRg0RFnUbcKuKw5lSEbIDW1ah4xNSZXfGHhU6E2R6gCUfdBE5Y8czsLzV+w40bMAoX2mI6V6/URgQ/TVi1NJPi1onfdM6UdDIYMBUk5qBKboHd83QdHtH2j6DAR5e3khOllLH9Vm/8GqToJGXOhmpeikF94VOnlDdD6HIde7/ExhjxYo4sKtTR/xRRrWM0vupOPTJkyftun2l3YrF7jh9vCWi/DwxI1u90Zo1qRW9cfrLL20fmFapArz4onF6zhyqFWN9WSrllDWqQZg/n37PrC8bEACYjGgAjeqLMh9VofDxAd4yjjgB1TcOD7e+LNXUnWjSF+K334CbN60vSwekH35onKZmSlfpuMSGKVOM1ymZ5YJlKUEFda6Wg0wbNwKn6BjTBqqLK48i3LIFOHrU9rL0/0D/H4SqSxw4YHvZ114DArO6ZO/dS8cJtpcdMwYon7WbQYcN27bZXpbeD/S+IFQH/p9/bC9LXw21aknXaVTO+qzSNwkJr8PFhY6NoqDROCAmshx0OmOx3fCbjji8Q6qlEn6rPpBcVnkf98rsgo3xx+BUVqphdC6mHtadfAqZGsqWfhKXLlHrcl8cP95c3KdPH0AeARUaCmTVDLaKOpnLzZTpEG3JEtvLUnkeuUQPvXcXUMKNDe3aAVnJ5IiPlz5HtlBZmayRTeKzRp9PW6iZY1aZNfEZpuf76af0ZiuLgHIL4RdQGX8tk07qla+aiTbdjR9eeb41QRUz0b63cdmNv3pBp7V+MK5Peg7Iej+QLauo1q1UuDn7d4/pdwTtW+bmO0J/YbsIGiWdrgRdivm+a/KlfdDGUMr7WFSofEbsM1MGk/QdQR+qiUg7eA7pcMKn6vfghxgEe6VgVMN5aBUMdK1BQSP6MqyCyZPT0KBBDbHt9Pq0rfssvtR3wofdjU+iUaPPsp6T9Pzux/krz/HUyd6o0joTzm5uCLtD2S5UDLueyf+zsZh12I0h0Gl1kPMUTu53xa0rTjh4tQxSdHNQ3+EaejgdVpYf2W6uEjSSvyP27+so1hl2qyb2/VsH92PpP/YWosMjgazP8o6r3XA8ZQTunOmJK2cs/4+7D05EzyHy6CJaX2f0qAnEpAAnsqpUyNvfpX8S/AKlqO/Vc044d8TV7Hl16vsG/lrmgOtXB+P33/fjuefaw8XVHTcuOeHUAVdoM99BUMVKcPNUY8YOqUh1UqIrou46o2l7aVhZ6DVHHN8tfe7T00bRu1r5/w0Lq0BjHBDpQJdAZrQH9v0ZgNshF1G2YlU4O7vi8j0V4u/TawhEPmHfmsv5yremoWjUsWzv3r2iIjsVTiTh4eFKC2v26HXs0B73j0h1jcjhjPqIWp1VHp8xO2Ya1W8otbo0zTTaqJGCzdkNct6Nho7Sl29FTSTapR5C/EEpbVYu9u7s6gKkxZndb17q0w/cLpesjhb0I0xnISgbkdyNl8Z0h+iMQaHHnfcr17/SvgzvCznsETHGSqxq1aqJYV80HJ7ZV2pSEjw9c64Bw5i99nvkVtoOWSlRehspSxnpaWYn1oJ9XLHpzQ7KdLguQFw66pLQuE1npY7Xo6jnU5S16NwbtRtLhY0flYFNrZ/gzG7mzFmi9m5uNG1qXpqhteNZ9NFthPPp36GNMR+KRO+h7MPe5Kz4mAxXyOVAy3lYppAFBASYlVawVjvUId320DG6r1qjhpOTs+g6lhNHJymZJLsUnbTt57XVcUMXjH0ZTaCHCmq9ZVRffn/Ln42GraXMoDV/mA+ZVucwpNPUq1O+RRVfoF0V4Ml6QJkH1L82VbNhC2Wom2mBcKespBl5e1UqNWIijcWqtRmW3aBlzi5u8PGj4WbAjRs38MMPSyyGFVKDoGO7tyA24i6unj2O2zeNHdP2pNaFPakM+fgGogyggQMHiuJUVD9IrhI/adIk8Z8qj70truh5eXt7Iz4+vlh1UqNsDl9fX7Scvg2RiemopbmFrX5jcWPQddFul7FHJTAwUHTi2b17NxydnNCjZ2/8s3GD2eer8nsbrd73N5d30N7T2L3hpcv/Q1JqBA6Ufxne8SE4s+gt1KhVB1eP/AP8YKxtUSXK+vqyuznrCfy4dCnW7zyKyJCzOHxwH6q8v8l4e0BfcRmqK4vHYn9U5l+oOx1uLxzM0/8DtbO2d6tqxkq64vqbXRIV5mux+XQEJo4egoXfzlY64sh4eJr1ZXl42qNbtlKlyqhSpQoOHz6I6rXqwNXLH+eO7cJvh6S0MPo/oKEqZN+/axCkScFHH32krJfiAtU/lPZFHnM4hh88PxPXx0R8guZVymDcuDfxwgsvisL0pW14mrOz9EZduvOS2YF8YQ1Pa7XnMfROmC+uv9+7Dvb8+Qt+nzcDZcsGidIpD/u5p+/HPk18cOcp6fWudewTbN8lDWWU1atXH+5+vgiuWhMvPzMA3bs/rqy37ocboIUDXk6fi/4u/6FmGQPuJWlRyUdaoP6vrXHh1AnUqVMXly5dVNb5x0v+6F8tWhmeRsbsaIT5608r/8dVa9TGpfNSYeuBTw1FmwHDUa1eYwxvS6lXGgRXqYWZWR3SXugoZcCQ5XtDxP9v9uFpH/9lWQvqU/dFeMHjb6hevgN4lle+IyZ+8CG+/fpLdOjxJMZM/kZ5jLaVM3Hgjaz16tVI0gThr1bW98dNtyEjPROnP6qLz7Oy3Ejr74Dxq0JyHJ4296OxaN21L1p1leomvTu0Cz6e9DZef/01VK1ZB9OWbxXL0rY1f6wnUi5txakJWQHBb4AP1oXYGPYGTBnVF5fOncHq1asxfPhzeKWtFuFdv8JpbW3x/zXtyYZivW/NWoI574+B2jMAFV6W0gNruYRj27T/wV6/2fkankbtBaktHj0QBSlkVBzbLetMPnv0fHx8EFyhItpV88X60/dwU1cOKQZnrPl+Koa88gkqV67MNRnYIyHHoqkAnzYzE+Hhxs5lpkWxraniLBXCkyWe/gNN+gzEgVQg3tv4A5XjXnMuto/O3Oj0OtHO2hoXlVTgTqY35O2zQ2do2rRpU+rPDDLGWEGgUclqVSZq165qFuyw5kG353dZ04PD4rCsaSCtOCxrGogodsuqMqDR0P5NJtzdHAENRWeMv/90ECkfSKpVWvj4uNl87+3RtlAO7B0dVVCp6Hom9h/YBa02BU5OxmMtWmdu38N5WZYOF4rOstL/hZOLRgkIWJOXEq45Lft2ynjluoujBrcunxDbsGfP9gdue24+nx4eHsjUAbO8v8N5bTWciDhu9l4hLVs2xoVrobhx8Sw8PIabrdfXMQHRel+EpzlB45oJJwcDypsc7wcGB+PCqcO4dMl8/NaQWpYlZM5dOINvv6Xxgpno0v8Z3Lp4UnmO8QnRIoPIeOyow6S5y03+77JeF2dni/9POUCn0ljuA19HefE6Gq78AVXz8cp3hPw+1zjozR7DyeQ7RKPWI82rUq5eaydnRxiy3f/QODX+tHJfEUDK+iyP/1wKGMq6DhwClcqg7M8bl5W210FjfIwGzVoon/Ps65Wfo6OjAe7utBGZ6FkL2KSWRk78r0Zk1vOS/g/oUp8Yrvwf2vtoIl/D0+hAMD09XQkY3bp1S3QpowKSlGHA7EeXmYmL6+aJ6xlwwi+pTyAodJnINFpFg9sZewSohSe1c6bAcsPmbURxehm1m1S72B5eEKczj3Q3D0zAr2nGLhYqJ3nMcf6/PkXKrYODSPuN//ctVDJYtld1hXnQyN5f1owxVtrFREWIAy7GippUk8JYdBBNRXRt0eulrlS5QcOD5JNtIVevikwjuaZsm7ZtUZo8khPfBgMi9VKHXuKoUaFOE6mAVEF999BrH5UMPOO6BdM9F+LgTWkP88yZM+KYmri4uCA68h60melo3Lix2f19PKT95GNxZVEn0HLv1NND3k8GXmwJXHgX6GvegAwZGmkdjhrgyBGpSUzdpuaZ8VQE283TfJ/c2dW4btmPO42jA0zZOml6TCsNs4oON9/3lofS0efDlGP2j0oedsh7DxlhNu2s0cMp00bRKRs8fXxF3ENnZagg1Uet08BYguPFtz/NcV1qGraq1ytDTrvUANINTsp7TWHl/46G9RW7oFH//v3x888/K0OiaPjF7NmzMWDAACxcuLCgt5Hlwfbt23Dr4ik0ryQF9GYmjxKdpdr2eBIHcqouyFgB8vD0FCnE1E6Sdp5cTTIQqQuZR6MeNu+rUZt/Ub7TGfjI/Qdl2rFMVt2hh8jgkQoLOiA6OgptDFtxTxVssYyn2jguuabmltm48NzYSJVCGWPF1pUrV7hrYhGjzcxQGrEwVpRQA55Ro0aiTZu2UKnVObZf1+uk4sY5yTRIt/tqEswytOXvpJCQEBx+QGMglneOugQMd/nHLFDlkJUKI9eseli0zkUrNuOzSx3Rf21l3M/a3WzYsCEqVaokrqekpODGlYu4feOaxeNqHKUmLTq1CzZddlDa0Mu7xRtaGWsA/TQMqFsW+JtqMJtIcS4nPV+1NAIgoGw5tO890GzfWksduLNShuo2lQJnru6WJ31tBUCp+7A1KSqpEPXC7xfj2LFjynx5P9uQLTxRXSoDpFCZNK15kAYeltlVdcO+R15QF/Lff/9dDNe7dtnYLaDFYz1Qo0FzvD/mceO2GXLetvS0NNFQTA6oxaYARzLrWwTHrl2w7DRgKI5BI2pD27EjVSQH1qxZI9rZU2SUAknfffddQW8jywOqI3P3zi3ULWf8UO/NaIIPXuyA9X9JNWUYK2yUjZicnCwyjaS2l0b04+TVijowWFfR0Xx4GmntZDkmGg/4YramvaP0JUxf1inOZXAv68RgJyfpR6unk/kY6eHB0rjnq7rK0Nn48bOGfvgouC4/FmOseP6eUuc0Zn/0nfrbgtkWnTkZKyo+++wzjB49GgcPHnjge3TH+t8fGDS6ppM6KvVw3Y8LJm3t5HU/6P4sf6rfWwl91uFx66pSfy+9QS9G1Pj7Z4tePIRevXohyrMlTke4wDVb9k7fJ/uhdu3a4npiQrxF0OjGfWlY2N2Alhjrtx7/prdDot4VnWKXYEqSSbtHG6I9msAn5bK4PqghRBMr/yDjyVN5v5XKS8g1pMZ/IZ28zf7eHvqqSWvHbFIzrJejaO0jjT5wRqpZfTr6fidevuZNtbTZVqMy5FzmwtT5tPKYnjQaCXrjyev6d3JoC2hF2I2rIrh15rx5RtVbny9B1wHPoM69n4zbhpy3zdXDUxwbyYFgT2cgHdKJkPhM42d6/U/GzovFOmhE0U+5e8XWrVsxaNAgEWWk+h1yWh2zD/oRcXdzRxVv40v7duJ4PHn3PRjS7pu1PmessND3g4uLq4ime2f78n9QTSP5x9qUC4yVSvWpiUhKSsxTfmpzB2mHS511duKvSD+cd2uE4FHzoDWo4aVKFvMbOFxDjIOxg1pN1/h8fVmnxoVhRAvAw5na1ubccYIxVjRxwLfooO/Ro7v+xc7/dth7Uxh7IOqAZCtwtOPPn3HzynmrQZ/ulBKSpXecVFfFOTNWaThkmtVhmt3x559/4s6dO7nePj4WsM1Zex8XtVLzIMesLBuDXqqDWdAogykjIx1PPfUUXn8jq9Iz7aOuXyeaS9nK5JFjMQ4e0jC6VxMmYVVaT4Tqy2FZqrEz8aR55l3HZO7pxjqjNDyNyMEhet/Kv320Dy/PlzOOTL379U/oMdi8S7dH4mUs2nIM8/67ii+2SIGp7LbHUVFtoGGQ+Xw504gye0y5ZcXMtGrnPGcafXa7PX5IHYjvUwcjvx7rO1Rc+vibDzmVP+N3/HrmOqDl5e0r/l/lY6GfVcOV264mSBlksqat28Hb1y/ftVWLRNCoRo0aWL9+PW7fvo0tW7agZ0/pPysyMpI7lxQBjZo0wdUzx9GxphQRj9SXQazeC9ffSRDdrBgrbPTjotVpkZGRIWoHmaIvSpWD7RTfTJX5lyYJ0sQo1z18fEWLSx21ZrAh+w/KCFdpqJgWGiAzBZdSpLHEJB1O2JrRJut+Biz2W4RLwaPFdIDGuGNlq3WuNU6bn8Hyp4GlQ6VsBcYYY/lHmavUzpq/T1lxYHrgnZYinZSSLf3yY5tDeuY929Rinp9Dktm0fD85iEGPQ0GHX375JdfbZ9rEqKijxkuPUqbGHVszpFpRMUlSbUuDQZ/rGlR5odZokJGejhEjRmCuyUgdeqy8ZlTe0RsDjsTVzR31W7S3umy0Z1NcKP+yuF41KyYhv5/oseXgTVxsrBLAMe1aJ2vSrivcsuoryd7cnoHQFGeEx6fZ3NYYrZRZFWH+1lYe16+sMevJydkFraURe9Cqs/bd83BChwJp5FBGw1wtXzvsR7S9/BZUBuMxhrOrlKXk6m6jppVKnevhafR5pcxBOhZqEATMTXlauc3FIefnVSxrGk2ePBnvvPOOaC3ZqlUrtM0qxEZZR02bWn7hsUerfZvW+O27aehZzxjCfSfxLTiqDUi9uNau28ZKB0dHR2RmZOLNN9/E4V1bce3KZZGOSa5du2b24/OL90fonDU8LPH0FmhspHZ6qyi7CBgwchx8/PzE2RkZBUVl3wX8gBsB/TDOTTrDMs1jAZxU0pf/wczGSA/512y9WoMGiQbph2B+yhAxDE2vkravWpTx8/JXsnmL5+wHNGbP/95+cTmkMURdJ8YYY/lXrVo1LFq0yN6bwViuSAGGrC6yydmOjLNYy1yhTl2mbumCUN/lJrq2a4RqZYDHqknt2sPCwrB582blsQY3AnwN97Bz506UNB99LAXZnFwsTygWBo3e2I7+dlyqsXlKIQSNKNMoKSFO7DM/rLs686Fz3q4quKfdtrrsqaofwFEn7bdGZr095Uyiq5cuYNeuXeJ6amoKnLNKTGTP/ikILtniUDQMcMykz9F9kDF7adK83+Cd9dI76pJylWkUEH8U3c88Bb/E08q8u3rz/58qkdaPh5vfmIqqUetQIWarMk+tBIVUVu9jml30oEyj4wf3iGQbChp986x5qlXfismIi4owzjAYxElyZbI4Bo0ooh0aGirG91Gmkaxbt2745ptvCnL7WD70798PYTdCoFYBvtT2E8B/Ga2QZnDC044/Iy76nr03kZVwDo6Ooljj+fPnERNxF5Wq10R4eLi47ZlnnkEV/TVl2Y5OpzDX83M0OvsZ4rZ/bzNopMn6kXBwdrHoVJJpMP7ylNFIPyrj3Vfgmn8/PO/6DxxgPGOw6Yr52Y8MGH8I0+AiCq2qs84w+KiMO3ty/SNrcuqoMfG992zfkTHGGGMli0mWyKEdf+PaBePBqyw3w526xUqB0hHtPbH7VWD3a8DqhZ+gcuXKSkfkXrWBNSOAV5y/Q9euXR+4Tup0XZxkpEvlCX7Yfv6RPJ5X8kXlepBXVrTCYCiUoBG9B6gwstxJ62FEmHR8i9N74u4HSeh/rIPFcplqNyS6VkOsh1R8uX5ZaTs0Dsb347170nGiu4enkvFEz/+XAzdQUChZqKWxGoQSnAssX1lkYMlqNmyhBJfi3WrlKjDTKuQ9BCYcRdsr45V54XrzoWXtroyHZ4rxWIQcuh6DjxJfFcPA/JLOKvNVdEANILhyNTRqJdV0Ji4ZEdDo0qA2GAONuR06R0OuI51qmM3zcdJj25/LlWm9nt53KrR0kN77Qz3t29Aq35+AoKAgkVVEB4LyOFrKOqpTp05Bbh/Lh0aNGsE/IBBLZkzE4GZSIT1SJ1qKqt6dZ966kbHCOHtiOnyscvVaStopBZNuOEpDDNRZASLqVBYUcxAGbYbNH4P4rGygdIMDnN08cO+esSOCRmW8j6faGBTSqLLGR5t8ie8IzbZevTHg84PXVCTF34deJf1geaqNGUQZsD6k7kE1mnjILmOMMVZ6mI4s+nXONEwe1c8iWJSboJEW0tGyh6c3Kkg1mcWBtul+R588HnYVt+O0ho0ai2LL1oZHFYazmdWV64ObS8dQ+kIKGslDGCtUMB6rZc9inzjR8sTj+PbmARBySmt8XW/rzIeqmcnKXJH3tcuULScFjbIyjfoPH4OAgACxrx4dGZGrLmn5oYMaNfyBPnXpPVlX1ET+cfH3SmaTqbSsw4lUp7JKKYmceKdeM7u0NiqBuGaa1xzdcDocv6Y9gb/TO0KXVT9JPF7W/1nT9t3w3ne/iutuaXcw8EhrdDs7DK4ZkbkenuZfthygdsBfV1LwFV41u81DF4VylaX3X9uuvcVxU2x0FH7yniJGZYz1NWY/2UO+Xn16ElOnToW3t7eIdtOfj48Ppk2blue21Kxw7Ni+Dbv//gNeOmMhXxKp80U9z0ikRxavMw2s+KAfmnNnTuP6tWuiA0S/F8aajZF2Nclw1VONoSzzBgIX3gU81NZTeuQMJIq6lwkIMuueZjrOt4KT5XAwN5UxkBSfaZ5i+1LCh8r11MibIj02yaWymDbNUArJlMZFW+sURyirKi0tzaJdKH8nMsYYY6XH/9k7DzAnqi4Mf2nbe6MuC0vvvXcEKVKkiCIoKjZEFNQflKaCgBSlCAiINEFBikrvvffee1vY3kvq/5w7mcxMMsnuUndhXp6QZDKZTLLJzL3nfOc7NObZvnqZw3JqYc5HlJwlnMK0UjU0qR5KleKMgwkPuyqhLBd5K1KJXLp06aESXnlpTOnrL6honjSfXmtnu+1vHbBSV68nETRKt1obUBdyOby8vDBu3I8Oy18p7+hJVUnLdfsluiWOd/qafIlTlo77TI3QMd8ofixLwTn6zMmsuVC48L1zRe0rQ9HhSFPojJwNhT0DvbhAixjmMUrq/z6kfrvArBwKhxdDyYrVHNbVWj/6LF3AQ3dPJmand8b0tNeYFQXhqZcGxXimpb8uCf7wf/sMUalpuXtzWfAqJPUECidw5XyEd5ZrQ/pxf21F4Y5f4JyuDOIt/pLHNGY9zEZu3kEli+SlRfioM1hVhjabzmxPmof6BQwdOhTTpk3Djz/+iOPHj7PLmDFj8Msvv2C4tfZU4dmrjSZNnoz/5k3FmM6VEeTNqSQGpX7Ort3/KJcrIzEFhZyyf7/Qtr5c+fIoWaEqi9LzwRPy+ZHDTQuIGoc4UFbLdWa0qDRQqdW21pxsmUXt8rAWqk4QtqORymuvmQR9rI+3J0xGgy3DoBMdoPc5MdHjA0WVKlViHUzsg1hKByYFBQUFBYUXh7RUeR+jg1vWwGSdFDoLFIQEStUQ67Iaouo9oUV4YT/5CXVOjaTDA4DqRYBt27YhPxAfH8csDx4n1Ar+voxR8/FbwlhRzJMywk5N4YIsuTW9ltsXvuObWBl/3lgc67MaSNZzM3H+oEYNp7JXW/T4+++/UaREaXafVEcUNGJNa6xlWdlR+v4i+GbeQHjsOsf9CumKz72X4KsGPvj8Je41CJMoacy/bqY1cGVPWEHO+8es0uWorT1PnJ2yaGbGa5iQ3hsT0nrjlqmAJMErppjmAaKTUvHLtsuYseMKMo3cOD6iTAXbOgFp52yqLurCzMN7ojrDw8sburJNHJZ39dmLm6EdYTDo4enpiV0bV+PcyWPISzzUL2DBggWYM2cO+vbty4ITdPnkk0/w22+/Yf78+Y9/LxUeio8+/BA71y6HQZ+F8gV92bId+lq2WFHmPMW0XOHxQgEScZBk4vhxLKvmTGlURC1IOu0pP14+O2JRqVnQyGwWThrHRLJcetyeELXQBS09wXkWoEHgXUwd8gnmTOW82dSq7AM++/YJNcbpVp8lsS+TojRSUMifDB48GMHBwc96NxQUFPIZpUoJJU6VagsdrNJSBSWGu7tQ/iKmVqQ0mHTCWFZy32Q3pLDzzpa1CxCz91PgyOeAW6ZQ4p+XSUnLeOylaeM2XsDUbZdxJyEdyZkGGK3jtGVH5ceHNI7LbWAnJ1SrWhVFisiXprmCxtTplw9KltkHYYi2CdPQN3kIXo6fjslpPdiyM4aSSEjTw2QNwLhZDbF9AkOt2+aCRjkx/yaj7eCU407LvdgyFde0JqhACXirDLJepAS9pl+AvKKsSERxJJm9sSK+AquYCUi/jIBULmgjR7LZCz+k9mFzXmc8MAcz/6HEdD2bt9xLFAJWW/V18Mm1DohKysSdhAxM2s15svry+2exQJdwFm8ljkTj+N/xWfIgbMuqhUSzD4JTTuBhKNO4D1N/pSbEomfPnnly/vBQQSOSkMnVxNIypVNQ3oEilZTRmP3DV2hcmjsYEPsNnGLCI+EkkHL3Ge6hwvNG4cKF0bRpU4flXJCHO/hlCRVfGKyZgp92ym/rThKQpRb8hs4YOcO4XbGeuFT2LWQauO1RjGqnvqb41Ry29SAuDb4q7sSotztRiXGDkRkS/r7pBkYeDEecmzDwI0jmbd8pTTwgo5MekWESImN57aCvoKCQM8aOHasEjRQUFHKNh8iXxaDnjJwZoqSam5u8T2LfpoJihNCJyuSJCqKYUvEg4FP5ruo2JN5JFgtTGlEsINiSP8b/eoMefgHOj8M02R/yz2lmYpzjbRq5cdmMHVfx4/oLGPGfo8l2zSBhrPekytM+/PBDnDrlaJKeHSwRm8kphpwhFrlfMkVgcnpP3DaFoX3iFEzYdBFmNTdOLeSRwlrau0dUY+qrJI8wZBpM1qCR84ik2pyFV461ROuTr9qWVbjhuhnWxROHbLerxS2RPEZVSzeuyFunkP/S1ymf4dd7NdA76Xu2rN7lL1Ekbgu0RkdV3ztJ32NORmd8mfKF033RW3TYc0+D8RsvYui/ZzBtu1Dex/unyqExpcNgNKBm3J/YbajBlq3TN8J7yd+x9+SXcQ0Pg6+17lSn1aJQIakdxtfbgpBlVAHtHMv8niYP9QuoWrUqK0+zh5aR6kgh70DKh32bVuHSIUGG+mbSWNvt1GWdn9GeKTyP8B0X7FGrVLbgSUBBoUa6kP4qYuRV3NBLx0kOfHWYqwUuEbsGSzJbu1xX718e3T02s9tHDIK81B5KJLEBllqLUf9EYfbFSIfA+KxZsyTLxEEh3iOADP5sj9unBRUUFBQUFBSeW8QBhosnD9tui5XYztqsh/pJjYDt9c6xorzV9SHO94Efj4gTW6+0qGO7bTA92/bdOYW6i+mcqLIIfrJPJsbOuPQghQWW+IscJrP0k+4eKXzQ5GXzJIJG9LcJCsq9XxPtiyGWs2xwxui0Pg7LThgE1Vqip1Aq1rJFDexK8GPqq/NeVbH0qgozZ83C2eOHkSbO9Iqg4IjWLC3xS7dYu81Z6ebOjbt3Wv2ovZx0iaOSy/fff9/pe6Gg0Xo9Fx09b+LG5UFp59D0fB9UuyHMaXmOGblmO66INQdg8fUQ5BRdaAkWpDq66Vd8u8a5L7Bea/VdcgKZqruCLDLEKsT33nsPvx1xR+npRYGiQue2Z8FD/QLGjx+PuXPnokKFCujTpw+70G0qTZs4ceLj30uFR1IbkUH57tVL0KFqYdvyfzKbsWufhMOKEkLhiUNKI34AE5shZC5WnDDC5OT4aRUSOeVmqlbWlosvYxMTFhaGiwncyeqmWfgduMrKkWpo9ZrNGOL9O7vf0u0AG/ClpEizO+JBIP9bMlmE96j8vhQUFBQUFF4ceM/FkJAQyViAHy6kpqaidu3aTscgt37uJvFhITNsnr4NgG45yM/bjI1FSqPEG0eE28lS1XRe5fr169Bqc+ZpJJ6Qi8dm8/fdyPa5V6KFsd1Mv9Eo4K2SdOJ9EkGjh4X2JfnoaiTscG4JQ0obexbdq2i7/edJ4f3+6/uBZL1TKV5Yu2YtCr//K0avO48zd6VNlYiGFz51WLYuq5Ht9png1zDBdwq7PWgtt4zsUsTs0XMmp42k4joHfDOkXqRiytyXqm/cDTmreCITa7H/aHYUfu8XFqT6O/Nll+sZnE1q+Ne9L/wGeQJF5vc0V/LwEIJvDRo0QHx0FG7fvo1nzUP9Aqj8hMo0OnfujMTERHbp0qUL6x70xx9/PP69VHgkPvjgA1y7eAa1i/nBx53LOAxM+cp28to695tnu4MKzzUqkKeRhg2Y9uzZg7saoX570RGTQ30+D30/3c1OZEhWsqxmf9IXlAkaBfkhJStnh7u2bYXOGbcTAV9VuiQLtXz5crv9FE4QfGBMHLhSgkYKCgoKCgovDnzwonhxQVmdmU7jGW45lcE788ih5RaDVMHxSfLXkvvL3s5+H2wei6KgkUY0DPI05byc61mSlZWFkEJF2G2DyWxTC9Fte27FpbPPnh6nkqP4NFFpYDaIlUZt3PdLDI0NegNrQ59XoK5qMBlRwzMO7ct65fh5B33b226fuJ2IG6Ed2W2tybFrMY1tdcFco5g/D91yeNw/Q1rORZwxCpYO1PGLvuIUr+OfnhATJQl07dJz5V0FONvdhyY8dq0tsFQ8+p8cPWefoSpSLTn/7Ig7puy/A/pshvzbTzmqlCaWOSDpsChWGt28ySnK3EWBpGeF+lG8S0aPHs26BdHlhx9+QEJCAn7/ncvKK+QdqENDxQoVcf7oATQsKdQFT0p/k11nHfzpGe6dQl7mUVqyDp/JtZv18vWzeRo1btwYDwpyKjdi6u/LnAaNiBhfsVeRI2eN0vIxeybuoKANpURGwqRxLm/muRnSFYsWCYHvDAOgVRltbUmJM2fOOA0arVq92sE3SQkaKSjkX+iYtXDhQjZxUVBQUMgJqVZFcs2awhgmMTYaf0zi/FhyywZraU5OOzQRvMes2DtJI4pT6c2P11z6SXHl8iX4+Adi6/kH+HaV4D30y7YrDiVls3dfw5bzQhv11SfvyQaX5Fh0UBoYkQaNMiXqj2cNVZEQI0d+j5IFAh96O7dTuYBit8CjDo/Zj123XYjG73uuufw86+kcS/+yTEKoIS7qNjKuCx3BZmd0ZddTrbZI9Vt2kN3uPqt3kBybsupi9oFY9N+QyryY3I3yHfDsyc7WQo4FGfL7JybFyP3ejE4+py3pji2kg3VCkPjfhbPw4IHwHb5z506e6cScd7R2Ck+UVzt1xNmj+9CkjBAlnZ3ZnUle25cz4eqlc3niC6mQt6B66927d+f6ed37/g9lKte0bUOtEoyw4SeUh3m46WD1I5SFb69J/OAzXbb7gT03Q7jMydbLwP/WAMZ+SUBYNdx3d61//dP/G1wt+pEk+5dh5Myxid1G+S4M4hMrP7EUS8mVoJGCQv6FWhHToK1Ro0b44osvmMpaQUFBwRVpaaksWBMXx6l5mrd8GacO7srdNg5JVc3lY5bj+1RpGZErMjMzJUqjzZs3S5RGZpPQySovExAYzMrTtl6QdtuNTc3C8P+kSTxix0Whg9fFByk4eP3hGjSJvWnu37nJ1GF5Bd4Pi/62bStzKqyHYU4UF8Aw6xwVN/ZzQgrGXY1Jw9GbzoMyvKdREbUQ9Aj358bA+sxMxNy9QbWbtseauwl+X0ST9q/Jbve92IEOy6iLWpO43/Bh8nCbIfXINedgFNlDPG5+y+iS7TrpJi3ryjdi1VmsPuXcZ0uMDtxv8c71S7Zgc9HwcEmAMC+gBI1eEDp2aI89a5exCfFHTTh1RqZZi216rqb6z88q5ql6XYVnD3/CIAVhbtFotFBbByoarQ4qtWCEneYlnOCKFSsGNxfH91NHBMlmR3dpmzU1LPgk2bG08nKhnthb6if0tjZmcPPyY9flk6TBr1C1dCBRSn8aKrWQWfrf//6HdL1QAhcO+Xpi8Yl1/759MisoQSMFhfwKdTH55ptvsGHDBubdSGX5LVq0eNa7paCgkIfRqNXw9fOzTfi2b9mUa5VR7HapX00GPDAvo5OtBH7WxpMOHo6BnkBycrKkPI3n97lzJUojiymbbiN5hEdNaGdk11XFCUnegml0fPR9VKwo+AE9a/j5GgWNyhUNQS0tp8CyJOauI95OA5cM9YBjGV9Gpry6Nk1vhMosH3CcbK1guWsWWvxttFZjZaSlQKuhMbbwJSyjcTTzrn79B7Q5/opsVzQe+krUif8Dt8zSLmPEq8db4lkyJboRU2UR+6/mrARUY01OD+7RCpGly6FTp054/wMuQOznx81hzI9Q+fG4UKIELwilSpWCt5cX4qKjEBHsjRrFODnj+8kjYLKo8XlT7qugZFEVeAwGg1A7nUOCrTXf4gAkBY9Ye1AZxY2/vz9eq+pie6KX9lNLB0BFPTiTRzF1dadhVrvjvG9r2Pv2FfKXlqcVVsdK7jeaxnkJ8IwcORKdXu2Mo+C6FZggb25tP6Ch+wkJibb7A0IW0dHe+ZtUUFDIs9CArW7duujfvz8OHTqEtm3bolkzocRWQUFBwZ4/Fi7Apo0bn5hKIMWzOHz8/JiZr5ix7WBTN9l3s02Ij5cojeb+Pgf5Awtuxzt67uSUK9FC8KF6eEDOX1Ul8oLSaCRlfnkFpn5SqXBryfcIvLwS9/8dL7uePlreSPpLrz8wM70rZmR0d3js/MULss9x12rgbhTGuGJKaByVNWTzQGRlZcBg0MOcJTZgd/T1Kn/3NwSlnUGxuHXcGhbH8bMeD19aWSLEUTH2udefttuTfCeipOY2untswsqAL/G6x8Zcbf+4vjSyRCUUGXph/7MMwu1xPlNYd7kxPr9AZTHb5hU0h6C5CP0jWrVqZVv+rMnVp05m164gQ2yFvEvbV17BmUO70bR9d1QvFoBjtzgFyUfJQzHHfxSGfNod06bPwNQpk5/1rirkAfhSqylTpqBly5xF7t103EmVjK+lqiMdvhosNXIkyOztp51AA8ErUkINwTPbgXSj4wH0dY9NyMSbuHv9ssNjGpV0/WC19Hh1OVYaNKL69eIlSiApLoZq1GC2xtgjy5RnmbyAAG7wYR8M6/XWWxgqatBW1C0aSLgEBGffAlRBQSFvsXjxYtYtlo4Nb731FvM4UlBQUHBFcHAwu4hNqB+G21N6IPzzvyTLUs2e8M24Aa3JsfsZxUT4hJ9YLU6G3Js2bUL7CsK62idXxfNYoTHWhfuceuphiE4RFDNqJ+bjYihYYE9iwsOVuD1p+O/Xu1/9hE/69sW4ceMQWKsERm+SBomi5n2GiMGc56aYn9Lfkt2uO7IQ7CcfJNOqVdCYHZO2RAE1F7Ds6cEFfAid9XuWEPMARoMB7kbhe6sBF0S5xFcUiv4+ajP3d1ObDUyRdMkUYXvsiokr3copRQI8cTeR2+dO1Qpj8hZhjrAl8GOU0t7BQG8hcNTZY4ftdgXtNSy18z+qrr0AN5UBBw2VZV/veqzwHrdeeIB2lQth2L/SUsrquot43XMzu33MYxguneK6ql2/wkmz+PkIKZvbtu+IjevWIF8pjUgV4OoSERGBt9/OgaW/wjOhR/dumP3D/5CalIiSoT625Vv0ddn1kNI78Ntvsx0krQovdtBozZo1OT6xJ1hPrCaR7NnD0wsd3huIyk1ecXgOBWZWOvrm5Qi92XHEQyVrxHfvO7YavW8uKLkffecuRvnMkCyz72YybeoUHNnOnfxIwfTD/DUICAySmOLyAzPymH/wHVD8/mLYeTMCmXlzwKGgoOCaDh064J9//mGNP9avX4+XXnoJv/7667PeLQUFhXwAHTcuXLhgG1vo3NxQuXKVHD/fnCm0Reeh4YXGYoBPFmeQK4bK/fmgUXDyQczqBsRHXbUtE5enfVQPeR6j0YiE+DhsF/kU5Rax6kOfA1PsMT7TcDfwJckyHx9hzpSXIM9Qou/HH9sChO82LSezZu5UKllwh1rn7jRo5GGQKvV5fKzdho0iZf5iq+81lVfFxTxASFgB1C7KqX2SLNznmiRqFnjOWAKXjRQUUrHgy6+7byHGLFWInTaUztX7aVEuzHbbz0OH3UHv2e5TwMgVHioDglTS0oX6ulOY5Cs0kWpW1nlXtX1X43DqTpJjYE4llARmuBXAqI/l/ZwIOn7kBX/UXCmN5s2b9+T2ROGJ07x5c3a9/q/ZeO3jQRjYsgwmbeHK0Y4ayqEmLqBO007YuHEjy6aGhIQ84z1WeJbExnInhTJlhLpuV8yZMweZGVwkX2tVHBE6d3d4eHkjqAAnv/FTpSLZ4oOq2ovw9HzZ5TYT0oFAJ9VxerNjxmg3msBZv7UslVQm/k1jH1SO3YG/Mlujqe4YvpYJGjVs1AipCVzNtQlqlChXmQ365IJGX7cAwnyA0W2Bc4IHILeOMUNGhKugoJDXadOmDdLS0tiFuknSwO2XX35B3759n/WuKSgo5HECAwPZhSb3FLgpVjwSp06dzPZ5jRo1RmpqKiIjS8CxrxVHQNp5dq3X+MLNxAWXfNyFoFGz+AloVg84H7cBcXGN2DJxeVo9QbiRZ6H3UqBwuIzjTu6hiT1N4HkK+nmwTmBxadKta1Vmh+50ebE0TRw04gkKCoJWo0bSgeXwr9cNYZm3cXT24IfbdukmsstJrSWnciN26TlD6mIaoTTysNUOlFRG0fduo1yFSkjJ5BLLizPboa7uDDwzOJP4Xbt3YUnJX5jSab7lIn7bfc26FX/J62zXyzemcUZEsBf8PLRwo9I6rRrhmmgcDu4Ff5Vz3yQxfwcMRsuEmbb7fuo0FNbE4o24SQh/YzoCfTzRKvgOhu6TD7T9fcTRE9Xdan5tVHvigX99h8fF8xHqQJ0XyBt7ofDUoE5Yty6fY7dDfd1RtoAvu901cSIzFmtdTs3KECtVkpfcKbw4UOcNCv507dYtR+vzbSGJuAdCXTMZYbNrjRaBLT9iASOitft+1gHi11+FA7E9JrvkSIhKMOXOhOPBOSOiA4xGeYO+9HTpSa5+ly+YT9K6wM8x2GcBW1a2rDRANu7HH1GlBqfEy7C4w2g2g9TASaJSXD767y/qxlqhgN37uJ37DnQKCgrPnunTpzOl0cGDB3Hy5EmcPn0a585x51AFBQWFnFCsWO4iNLt378Lx48fQvXt3RC+XGmgfN3JKEp2RCxTxASM+EMQHjXg8sqJY2TwhKjLgyAM+Ka6g96LVaW0+rI+Ch1aDCoU4U2Gif4tSGNiqDLrXEnwQxle+4OBnRGM8+4RiXkFc/nj27Fl88skn7HbizvmocncVKqjuoXaV8pg1a3buN16nt+zi9Ft7sXzvGdw0FUSaWyFsq7gIJyO+wiF9Rdw0c8nh1ZmOASfyNAoJDYO7hyeuJQiJ189SBiEjsBwKdP4G90p2simdehx0rsjzVmXaKWDkzc4998/CO7ULwMtNiy9alWV/c/pbprsVRKg6EW4q+efx6ihnaiQ/VSoOlxyFcXO2IiXqBlvm75G7ek9SGv1bax8WllqDmAzXGp680qgqb+yFwlOjYcOGOH/8EDLSuOhqKZJGWOmaOAEvRXAnH4PRkCdMtxSerdLI3cNDIok8fPiwRGXj7KBG7VHFJ7W0LCOiDTr41exgW17IakT98ccfOd2HGLskwJ7g9zDY27ni8dzWZZg98kvZx8zJUnmz2r8YRoj87aj0JCxMkLBy70MLk9loayU64r+z0NTvgUIH3retQ7+Tei3buxT/ag+OdPGogoJCXqVkyZJMdXvjxg00bdr0We+OgoJCPmT+/HkoWb5Srp9HHWYzrkrbkr+dNIpd66zBoljf6pLHqURJPH7XqzywdcsWdtvdfl4bbTc7fkbs3bsXer1ePmik1bGSKJ5aEY4BpJblw/DDq64/XzetGpEiE2QKHpBqRmwnUNwzVSZoZILGTtGTVxD/nam7JzPGFo/JVSq89957+PDDD1AjQH7snhNeLiVI/tfFRmC9viE+SBoOo8YL9wMb425gC3RPGmdbJ8YkKIN+nsT55E4b9ikXfLNYIKoYZHyGifAo0zDb/fD35OYWx6yBU7GX0geeK233W7ntR8V9A+GdGYNCvjrb319nldrdDZKWH9rDq6Oc4aYywKTiEtd8opoS47nhQrF+SPcogik/jMDvPzp2ghbDm2I/a5Sg0QsG/WCbNm+OTcu4Vp51I4Nsjx0zlsetNAt++nsHipepyFqOv/7GG8iwlhwpvFiQNNrd00sIGqVGwbiwDoZ2KsKW0Qmernft4mSl4kyMRlSeduJeOkavO4+dCdKa5FIa4ahsbvsH7BTCjOEbHWuLa2rlOzoQ965fwblj+2UfMyREOSwrUb6mpAxFNotjp1y6ZS6MI7FabN2y2XbS9vbxQx4oN1ZQUHhC0PFuz549z3o3FBQU8iHh4eHw9HTs2pQd9evXR4+3eqOoxtHTJyCdM8w1qaSlUxQsECfxqENyparVULFmA2TZNaIyG6SKjWdFo0aNcOaM1CiYDxrROCzeOkBsViYUnasXkazzqvt2NC0Tlq3JNZUlUeDAntKi5LnOwn0eZlHQyGQ0QidKhOYVaH5GpY/OsJipI5fJVsI2vlsVBFzZgMpF/CXvWUxHd8EAWkw5k2NJJRlT+2dcZbftu/i9f/9/ttsDB3yO3r3fQUTpctDp3BAYGIBiXvIKn+xIsrZiy7JI/x7t3XdjsPd8FFFHY5j3b/jNfzRuxLux7s1yrepJaeQKUhpdjVPhTpDQBOhvf6HM7yrzXOIwWecIFmjYa+cUoydXkhB1+wbi7t+1Lf/www+5xw3CpCivKN2UoNELyOvdX8PfMydwgSOTEd93rGh77H8pA1EwPAI9vxiFG0lG/L10KZPlK7x4REdHIziskBA0OjIR9YsDE1vFYcKECWjX7hU8ePDAln0XD1L4A5zWvwDWnJU3MBSfZNQVesFvqPTxajVq4pRj90542clSJdvMSEBCbLTsY1mZQvBTZ3WD7NSJk8I6g062Wr2jgd3HyUPxTjfOj4k+H41OhzekyT4JGcUdjbkVFBQUFBQUnn+8vLyQnvpwHcAoaFJWe8thOd+K3CfzloN5tNi7aN2GzQgPj0DDtl0c9ArTZ+QdU385s2kKGpGY5k4iZ7Ds46Fl48thrwjdaAd6L4bGqkTilURD2jl2q/XQaVCxsD/KF/RF20pc0MA78xZK6E/gm7bl8F2HivDN4LqOqUVt3ikoQH52eY0lf/0FPz+h3M4eChiZTWSpoLGN0T1iL6JHnWJ41S7wRpwP6YqpfhNlt9XO65Ds8iwtnwyWBo1SPUpw1xbu7/Hmmz1QrGRZpsopXLgwKro9XHMYvrwwyhwqaV3/hfci5kW1N/g9vO/1H7duhUrQqDXsc7DnciHXTbuo+dnLy8vgcMkxtmV13M7abpfV3oRZrbN5NRFmtRavirquZYdaLa9MmjVrFrumBmM8StBI4Znxzttvo0rValjw07cY+fFrTPbZt3Ex2+ND/j2LguHF0eX9L/DWgOFYvWbtM91fhWfD/ZhYaN3cYbIGje5d5tpBEqdPn8LWrVtkA0ViyWyxZq873f5+QwPJ/TLlRL1gSaF07Khk4JNu5A7QoWrB14jn46Yl0bt+BCzpgteQPdTdMXbtzzDfv4CDQ7jsgUqlzjZoZDGb4Ctjlufmy50s6fHqga47exjU3pg8eTK+/U7qTaCgoJA3+Pjjj/Hbb7/hyJEjsmUST5P4+Hj07NmTTQgCAgLQp08fpvzMzoOuX79+rM03Tb66du3Kgvo85MfUo0cPq+LBE+XLl8eUKVMk29ixYwc7jttf7t8XTE0VFBRyD3WK9fCQNuPIKTTO+tTnH4flOiN3TIj1k5oC0yT2pVLC/ei4JGY5Qduxn3tG3eSa4eQF5Cwx7t69C627BzIN3Dg0wFqeJFYVqSHIvN9vHIkxnSvDx12Lvk1LSrZFKiMKLr1Vvzgal+aCDi+d7oGXT3VDcf1p9niWLpgt15mEAN+da5cQGpr/GgNxjRsEpREdy0l9RAR6ubHPSYyniitf2xf0jsO2ykX/hXq6Uw7Lj0Z+K/va747dgLlnC+Jm1Z9tRuKJcbHw8/VDWEgwlk8Z8VDv6VyUNPBaUXuFta13l/EmWr5sKac0kikD0OsCbOVlrhArzoiBvsvR3O8aWvpfxZ2gVmzZoikjcf/2Dfy5cDFC1EnwRPbqvS+9/sC+revZ82KiOJVRQHAIxo4dK2+ErQSNFJ4lWzZvYgPMq2dP4L/5vyA8ROpMP+Sf0ygcuxm1m7fDr7/OyBOt/hSe/gknICSM/e3pcmQ/V4ZG+Go41Y74eyGupeap2eYNp9u/aZYaQ8p9x3Si47WXlovme1hPbGKKBXmhsIcRZpNzyStNCEu5JSNrwwQEeXNybmNBrmPBJScxH+bHlJyMFKt5txhtAJepKpp1DD+WWQdXRMfEYODAgRj5/Xcu11NQUHg2kMH1F198gTp16sDX1xfVq1dnwZoZM2bgwIEDrHva04ICRmRqunnzZqxZs4aVAPOSdWfQ8WX16tVYtmwZdu7ciXv37rGmFjxHjx5lnm2LFi1i2x46dCi++eYbTJs2zWFbFy9eRFRUlO1i7/WmoKCQO2gsYZJRPOQEs9GI4rjhuE0zNxaiTl/iMpr2lzpio+hwQY2qqMSKutiKrIEYge7PNkCe3Rjw+vXrCAwrZLtfOpEba1GAJ0Cd4jSRSIQHeeGLlmVs93k/GzE+WZzBcetTnSWfaaKXoFRKT01B1arOTZnzKhmpqYiJuiNRGlnsFEFftiqDlm4HsDuoj20ZdQUTU0TNJR/aezlWnVisXeYOpwrlWkRIoD/emxuFiq24LyIFro7t3YbgkBB8/NGHKFC4CFrZd4zJhpl+ox2W3VKVxLkiHyLaLnDKY9BnITUpAVfOHMeq+b9IHtNYsvd4Mtp1af7cYz5avdQJq2rthlHLNZK6cfEsTh3ciSULONuX2f4/uNxmObe76O+9FLs3rcPl01xvxOSEOFSv2wjt2rWT/T0o3dMUnimhoaFssHj+/Hmc2ruVLVtX/g/JOkeO7kAZr2iUrVSdDZoVXixI4qzTuWPxoj+wZMkS7BWNWXZt5LJevGQ3PT2drW8fFXdlDu2uMWebZRr81Re227cDWkuyIfb0a18bV8+fdvp6dNI6eewIokXZd0twJTScBry5UpC6iqFMf2YmJ4u2x6f5x+w6MmsfssOgNyCsQEHUqVsv23UVFBSejRFrcnIy64w2b948vPTSS2zCMmzYMDRo0AD16j2d3y6dkzds2IA5c+agbt26zOvjl19+YcdgCgTJkZSUhN9//x0///wzWrRogZo1a7L3sG/fPtu5m8xQSVlE5cSRkZHo1asX3n33XaxcKZiH8lCQqGDBgrZLXuncoqCQX2FNNYzGh2owExlZAkkWPywP+J90m+Y0W9CI/FScQaOxuNhYRFaoijf7Sw13I3xy1nL8aSCfnFbBL1gILrwU8xMrKSOl0bqwb3Ai+A3mdekMDzfhc/EUZyHlsFigtnDbMqkFn6jkhFh4uIva4+YD1q5dix1rl2PLP38yFSpBx3H7zzjYxx2jInYhXCOMi+3ZEcQFfg4Xl6qKVDAjQ8eNna/ECvYPhQ/PcNgGlaQR7u7urGsyEeqTvdKHPUdlwLmQrmjjvt/W8ZsnxaDCiRJDEZZ8xG65Fq1bt0F40aKs8dPJ/TuwdKZ86R0R51PVYRl5Id2PT0e0Xx3bsrUpVrNuO+WPUa9nZZQGtRfq6ZzPQ3rVLYYN/lzzHzJgd7N+r2Lv32UqMPG5lhTDvGeVojRSyBOUK1cOCbEP2I/qRNlxrDaUZ1r6G/hoiwZlWr6OSZOlMnaF5x+u1amODTYmTJyIeFHshD/W80EjmmjdvReFui+1xzdTF6F5R05hFJfqPJIfqZNmh5KSEnHazqs6MEBQwF0LeY1d65y01qQBmT3r1q13+R6DgoKw7wYwe8kG2cepjIMCZ3K4+XD7dv36TafbT/Tislw7d2xD9AOlxENBIS9DAzM6J7755puYOHEitm3bxkrFrly5gqVLl2LwYMEI80mxf/9+VpJWq5aQOW3ZsiUbTDrzFyQVER2vaT0eeh/UeYm25wwKNtEx0J5q1aqhUKFCaNWqFQumuYK6aVKwTXxRUFCQQmqPKxfO4tplzrw6N3h6eOL16bcQAaF5SJrFA576aJvaQ9zty546dWqjqf9ZtEiZAzc36Xgmw6TL00EjGmPe8RJq7XxV6fDKeoDglBMobLqBALXroJeXmwZuGq4sjUrWJFjMDkGQ0CSuU116psiEGBb4+0mDFXmdsmXLOnhFMaWRzGe8q/xsp9tp7bYPOhU3zg/1lX53LFQYaPX1SSE5m5WwAKHTGg+dT/gyNRZANRmRpndeGVBYLXiTkum1lyoL10M745XKgurMFX8ltkKvXj3Z+Y1eS87XyFUZGlG6TBk2r9hS+W/bsgyL1HQ+KJgrW4yL5iYvOnM6+7wWNbiM0TLd/CoU9keSJ1c2aRF5rZatWAU7NqySrEtJnQsXuMY/eSVxkzf2QuGZ4uPtjS+6NWGRU4/GI/B3DaEMiThoisSKf/5jLYcVXhxIOaS1dkHz9vKW+Avx597ixYuzazoJUO1wo7ZdUKlOYwSGcpmhOwnOO++p7KTCBr0eK0QBeioRafFSC+Fxq+FebgLubds6dkQTw9d6U/bD2UDPaDShrZswceL9jciILy3LiJhYqZRXDN/W0+q7nWeyBQoKCjmHlDmvvfYaxowRTDGfFOQfZF8ORscpGvw68xai5TQYp2CTmAIFCjh9DqmQKBAmLnujgf3MmTOxYsUKdiH/o2bNmuHYMedtucmDgQw7+Qs9R0FBQcqjTPq8vTxw6BYQ+Z0QIEm3eMBL/8A24XUVNEpOSsLUDlmoGDUHISnHJY+ZLCpM/WUadu/ejbwYNKJlDzwEz1U3lREqiwGtT7puYsJDiqRPm5fCJ81KwlOkOiJ0Jq68jcfdEI80j6Ls9tXDm22lQzNH/S/PTNpzSsmSJVGidFnJuJOuzTJKN5PGE7eDOCU/z9fe8xCpuYPRvtNty+TGr2YVFzQqEij4dXm6SwMrbJkn97jBoGfns4y0NNy/LZ9wray9jH3B79nul/XkxthJXmXg7yUNcobZBbJ4ovU+bPyusSr8tqyQVtLYI/79/HCCaw7F+SGZkJkhZMwvpnCeVzyBwcFo3a4DTFnSioRGlweyz6u1TAme2sIFyxIzAH1WJurWF/xdKfnDQ4osfiyQV6YO+etXoPBEmD5tGqunvHb+FNI8iuFKRD8MaC4cpIkiH/+OUaNGPbN9VHj6GAwUNNIJ3ThEBy13u/GJuDRNTMXC8p0d3vJY42BCTdtYdBQwmoANF7iJkEdAUeFxTe7b1eYUZ50xWEbEbLbVzhNif6NZO68ySaocq2tuh0HDvf/eVtGAEjRSUHgx+frrr2VNpsUXPqv4pKHW1tQ58ttvv8XLL3NdIPns9EcffcTK26gkb+7cuex60qRJTrdFvkikWOIvt28LaggFBYVHP/fzpT1i4XasWQgQ+2TdllVK8GSJSuzdjNJmIRqVBZ9/1h9//fUX8mrQSIwbDNBYcufDFOLrjkL+UhPygNSzKHd3jmRZl0O1UDR+M7u9bt9VfPdBF4miMr/DAl9OBqwHykyAUS2U4H3stQLbgj5mxs48WRmOvn4GC/e9IzUXew1YEBLi3DS8cKGCbFx9/fIF/DtJXrn7uz/XMOZb71kooYvBr8X/ZfdJ1USNm8S8XIHzFj1WYphkOZV+UdCIBahSU5Ca7LxJjn3Q6Fws9znQ8+n7N7Z/D5QcC3ScCwybtFx4jsXCAlL0uVLSW45Td4XPr1IRf0nXQ6OZ8zLS6dxw8SxnMu6sCUdemTsoQSMFtGnTmskXf/32M0wY8Bb6d6iDYB9v/PxKAbzkxrVZ1HgH4J+ziVj855/PencVnhLR0YI89MyZ0xKlkYfOscOFPYnpehy/LX+gPmyoCJVaOsghtc/VOKDoD0DHeVyLWvgXx3tLgSk3mknWXRPwue12Y53zLHhOoGx76dKlZR/jZLQmfOjJ+X7U1Z3G+55CF5Otxy/j9Wry283UBMBiDYyddV4urqCg8ALw5ZdfMr8iVxdSNJGHkPjYywfUqUyOHpODltNgMzFReryl7mn2z6FSYvJrIoUR+TVlBxmDU3meM+i4Td5v4ouCgsLjQ27C2D95kO12gnclJHkJ5Uj2kLrDhl3MwMNdl2cmpTkJGmlUZnhl2fkYPATNzr2DyrenOn08wyr4mDasn9N9y/NYA0QVKlQQPI2cJEgNWn+MuO282zFx+7xUpUbMPMWNcf87yfntmaGyKfjl8PXxtRlz66McO/etDPgSYWruPPau12psD3gX/pnXuW2rtA7fU97YO9kzUrLcaLaw1yG1Dl8C5go3g3DuTEriksT0/L0b/8WVsydxLQ7wrNJD8pzNyxfgxrWrbD0y3JYjLlX47bWvUshWBkmYzJyCSFzpIFYaickrSre8sRcKz5yUlBREFC2CEwd2IT7mAd5uVBJp6iCJW71fs/fQ+6PPHsrITyH/4afTo2nhRGjVQPHIkpKuG82knUzx6quvOjx//EZp7f6FkC6SLIa90ujEiRMYP348HqQABtF5bd5hYMedANSoUcO2rKCou8M0v3Gy+9+r11s5eZvo3r27TTprD8s0mEwoob2Hk8Gv40//oWigEU6cWelxss87YSiD7zdH4Z80TnZavQi3/MD+7E2zFRQUns/mE+Qz5OpCJWb169dnwR/yKeIhbyWatJAxthykDKLB8datXFMLvgParVu32PZ4qGta8+bN0bt3b4we7diJRg46LvN+FAoKCnmDKyahGsCiUuFSobedrhsXEy3x5xGTkpyUZ4JGcnML2UCSSitrXJwTVBYjVGYDvKx+UM4gFQixf8sap/uR10lMiEfJMuVQvnx52984KTHe6frL1h3EcWNN3M3izJft0Rodm8KcjeEG6yaS9vDruQgaqdQqpwGQn3x/Rg2dnOcX99lrzI6t7PmvjEElLVMzmbigkUajhd4aNPL0lHotkWk18cC/HgLTBZVvUhr3Ohq1BqsWTHeoSDhzcBfzMFrwE2cMrtaoobcGjTaZue5nJmvZXvOyQpMdP2u2nb6DbB0zcHDbOklnNLGXoRgqY8sLKEEjBRs//zQBDRs1Yh1YiDOH9+BOWCccDxaiq0Xf+wV//OG6NlTh+eCz4jsxqOAyVlp188Z1hIiqw9L0ZAAnre11hbcqHR4qPapoL8FHlY4mbscclEZFihSxmbKGFRDqgHv0eJNNlmhCVWcKsPI0mGT2L/9vsDrgc/irHSWzHTp0wB9/LMSjQidZnYY7K9HrUJarqE4IWF3JCoHRomamlGJeTfwZqXozFp4TBmJ++av5hoKCwjOABvht2rTBBx98gEOHDjEj6k8//RRvvPGGrUyFlJ0UZKLHCfIS6tOnD7744gts376dBZzIRJMCRnzXNypJo4ARlaPRelT+S5eYmBjba0+ePBn//fcfUxbR+gMGDGABq379uGy7goJC3sAdWRJDYqPWBwaNUDovRtw0zNvaYp6nQnDGMw8a8ZNxOZsAuWBNeNxGGDWekiBSTqCyoO77yqH9MaFhgDNO2YmZ3nnnHeQ3eJNmHhpD+/g4N/S+f+8eqg8+gtCv5H3wUuIcl3vqHL83O3fscPoaxSMiJN+1ETW5xgnF1FHo4r7NttxsDU8ke5RgRu9ElpabH1QpypV5FQnwRLlC3PtJcJdmsg0mFQsa0d+cN6m2Z2+56bgV3AZ7y/4iWZ6mDkarl19mfkhiTNbv58T/vY+Z3w+0LV+1cjkO7+TKGi9lcpYa9FusfHMS2oVcR7EgL7StVBBqcxbCEvfbApZUiXD7ygXcuSV4O3l4yE8UihaxZp6fMTn7pSm8ENDgco/VDI+UF//t2I4DAyaiR0wkPvBcid8yugCefpi94i+8/bbzrIZC/oS63tABi04sRGU/7sA29VXg90MpGCY6z3rqgOCgYMTHcUqbatVrSLJEZBAt5isvLtC4LGAQMi3uLAAjjq7z8BmIiIgI27I//1zMrtPT03H4NvDOEqBLZaC+m/O2ls54pX0HRJbgzLtzSnyU1KzPnCkNUvVJGoG9hmrYF/QuwjTSjnBiyK/Pzc/RFE9BQUFBzOLFi1mgiMrI6JjYtWtXTJ06VSJhJyURHRN5yHeIX5f8N1q3bo0ZM4TWx8uXL2cBokWLFrELDx1r+SYXVOJGZXQUlKLy4CpVqmDLli0s2KSgoJB3aO0u7orIjZuc+RqJm4b5ZVyTPNYgLMalL+XTgH/tzz//HAcOHLAtp26Rv8z8DXhZ2uqdfIdSPCKcdkFzhl/6VWgsBvhmZt/U54ZIkFOoSBFmLJ3f4buWOaOgNSnBzwHs0cgEFjMMFhhJMiPi8GEumSFH0aKCTykR6ZOFKyEdoVVJt7Gv7FQ0uvgp/Kg0zSqyMWi5oOgbtYuhey0LMznnSVNLm0BEJWSyoFFYWCiuxHKB0QyRoTVxL6gFu4jJNAAFCxXE+nXr8HpPabVCsrUzaGBIKM4f476n9BriYOecmbPx6ReAhzEBlW9PRgXVr0hrypXhtTn2MgLSBSWVSk0/TD0aN2qIC+fPSeY99niSXUceIE8ojaZPn866MNGElRQFfPZMjvnz5zuYR9pH5igibL8OZe4Ucg4NOLf/txRpaWlYX20NPvVaanvsTvkeSKVflsJzRes2bZipqT3XZNSsTSOBy5e5A6GXjx/q1avPRM/8Mfz0kY2S9dUqLqDkrjLalEGBgY6tnitV4lpUHpY5BvAnMpEKVtLWnuebIUNZyZkc//6zkmXTc0O0QerRseQyd2Ll2WmoBSO0qBMvr8Azqrj9pvK+gKAQxFkDbQoKCgpykOLyzz//ZGXjZC5NhtR822SCxksUpKfOZjw0DqKxFHkf0Xl75cqVEj+j7777jj3H/iLuijpo0CCmMsrIyGDHKVItKQEjBYW8g2/MGXZdQC0MzHjvRAvkg0bihJ8999K5yajOSaDgaQaNKEgkhjo4Pohsa7sfoOIm7YRvppDMU1P5Ug5sM+y7peWU1m2Efcj3QaMcBgdf+cNRkeRMjZamF4ImGdeOIDBQvrxNrlOxhz7GIWBEmNWO30fx91scMCIy04TOgkRMdCxKlSrF9pnMpomQMC5pm54qfI9sz9dwQae9sYUwxTpH4L2XeOKtY/fI0uVsSfIlS5bYHg8LKyCx1mDbsHCKQL/0K5KAEfcmuGgu33H0448/hjNaNG2K/p8JXq4vbNCITGhJKk1dPKita9WqVVnAwt4IUgwZLUZFRdkuN286tu2jIJF4nbzQGSA/UaJECbzcpi0ObFmL+9pSuFh6KBb5D7U93nHcqme6fwqPnwP79+Py5csOyysVFDx5eKLTpSJFylB7Zd5BWcsppGekYlW0tPteJa2jkapW53hSqF27ti3j5LC+Vsuy7a92EbyRiEOlfpTcHzP6B/Tq1Uv2PdI2cmsoV6hMLehF59nvpi7L1fNP6LkMVY/qQIEi4ZJykEGDBzt0JqKT0Q4X8l4FBQUFBQWF/Acp+XILmdH/9DM3TjB4cJNbpvy3YoHKoQNUTtl+gVNh/CJSMj5tnJn/UsWDV6k6tvt7gvq42EpOgkbSwEJ2HD9+PE+ZED8qfGOXnPDagKk5DhpdiRY+V1NqgsR/1B77QMzs9fJNFkxqaXCJ4MvUJMuswZuMtFREWG36qKJx1I9TUKZMGbbPpK566+3eCAgMQvS9W/igZWWH7SwpPAtD1gEb9O3Z89i2zdLPqlHjRtwN0edAyl7yYiXate9g88Kyx8Mg2FrwJGZx76d9+/bIjlatWmLqlNwlvJ8Ez/yXQP45VLtP9ffk8D5z5kwmi6bMmjPoS0AZNP5SQOR/Io5mitdxFflUkKdi+XKYP2EohvRshUvBndDI7SQ6uO9kj13L8MCMlduf9S4qPGacSSCPWct3J6b1wqrMJvASZb3NZhNTHX0YsBTvYzJ84wUDV54aWsdW0mRQ5wxnJ6f+/fsDdgOjWL+aeJIkxsfjhrjqzLeYxOdLzH+ZTWCySA+r3RInsOtxrwB7t27Amz17Mp+QwV9/jXlz5zIPEfsAnJLdV1BQUFBQeH4YOmw43n///Vw/j0p6vhg4gN3O9JWW90iURnbNRXICrwJ/0ly65Ngpy15ppAsOx/VYafl/8lHOiJrwUTvvgsW3MXcFqVpyg7NulfkVV93T7PH2FpmYirj/5zeoV8AoaZK07rTgGVTdL42JQZxhb5I9b9ZsrKi03mE9o9rx9eXKL3vVL460lCQMf7cDbiUAZX8vB89vKCktdAU8c3gv8ye6cvE8bl1xnIsQcaowjN0G3E8QvmPVqnJm6+XKcUbiUydPRpUatSSqNr6aifD183NQGgn7rnMsgbzPKZ6qV6+eb4KTz3QPaXJEho0tWwraSfrQ6P7+/eJ6XSmpqams9o8kXZ06dWIdQeyhTH1YWBjKli2Lvn37uiwJofp/qlUUXxQ4xQZlAKhk6MzxY9hUZQUm+gqqiPGH0nE73tFNXyH/QmUJzmgT/wumpb+Bz1IGwcNdUAn5BQZj966dKB4EnDFEwi3ZsfsBHwP67nC5HAWNXB081VZJ59PizKkTzI/Ihs4Tq8/JZ/Q+TxmE3zM6OSxPMAtS3+PHjmHz5s0YP24cy/rQeyXfED5jkh+7dCgoKCgoKCg454dRI5mB/aOgS5OrwlA/tNKIuuMObAKMfsIVWDQXcxU0Url5ovD7v6L5xB22TlzLlq+AxcAZ2oR7ODY8EaNC9sGQnBpm8/AlwXJePvkRCm7cuHoJx/ZscXiMFDjXrJYTROfOnR3WWTR1NLJun8b7FTKhEX3eGdZIibfGjAg/NYJdNMmR66yWIfIj2u/VDdsrLoRR42gIrbZ2HePhA0BZGRlIT+NKDy+dvwCqluNfh95z3P27Nj+jVfOFbmhiDHo9uxZ7s8ZEP2DXtevUsW1LoxY8jMh3kKhWrRo6dnoVK5cvcxo0Utn5bs0WrLtsuPrc8grPNGgUGxvLPnx7pRDdp64ezg48c63ZeTJzpAlWgwYNcOfOHUlp2sKFC1n72XHjxmHnzp1o27atU1ne2LFjWfcR/sLXF77o8BHUEhHF8PvYrxHrVwtpPuXQ1V044DQevx0GOxM0hfzL6lWrsGfPHnY71eyJXomjsCiDG01cMJWwrRdQROoj5KYBjhrKoX3iVAy8ILR4JurpTtlu+4RXwepzwIm4AGR6C9uzx1UnD62o9p5aZT5prl27xgZWYjZfccwa8IxJc5RQp1g4BVfXD75g19QKm6Cg7PXr19GqVStbsDqn8mEFBQUFBQWFFwfve0fYdQnNXdsyXmHkoXcsgXEGdX0laGzzc0dgyEuU3XK0J3gaUNDIq0wD2/2kDK5c7fy5s/Cv143dvp0pr3zhUeXA00htMTxU0EhNhpT5FHEQhGfuuCEOy+aPHyJJWIqDO+l6YMQZYVyf6hkBLflI2WEwWZCa4tw3avfu3bIt5TNV3kiHD4wm4KB7B0QFNpX15/LUc0EcnqwMLpBoNHABHzE6kdKIWGq1qMnK4hLjM7/nlHs88TId1m5c5/z+LGazzYspPS0FifGcCGXYsGHsmoQu//37D+7euY1Ux12xIv28RDZQNm7fvo28Tt7XQtlBLWSpcxdF9po2bcrMHkNDQzFr1izbOtSatmPHjqhcuTJeffVVrFmzBocPH3bqE0Lmv2Q2yV/ywx/uafJZ/08Re/8uzhzeg+0VF+Anv8koqxHMM3/ZJl+TqpC/4NU9ZKIKsxGzM7pgj6E6hqX2w32TNAI+MuE14Q4ZspYEVmc1kd3uYn/uwEq4e/qi41ygx9pImJyYNor3RY7hw0bYbp8t0hdPw98r1K6T7ZU0RxNvV2isJ4xy1biMBe/ZFlaggM2IljoWUQDJWcBcQUFBQUFB4cWE5jxBQVwbdQ9wBrtiT6MUT+fdl8RcMRZFqdhVKB6zBipRQMSsd+35s379eqf+Q7nBPjH24MED+FQWKk5SM43Ys2dvrrapNac/1qARjcV48mvIiI2jZYJGZplE//3bjt7APF+tAUbNF6p/0t0LI6OmY+Ap4fxeLF3i3D+4UaNGtoY2pcsIyjPaxZ9NQ1BzMpBo8nFaahnvU0VyX6PlAkMGfZZtrM4jVhqJuXOVq4TYvf4fFlCLe3CP20YWp2hLTEx0CDz9+usMm3dymbLlkJWZgTNnzsha46QKP0uX5ZPVi3ng7d7vSJY9qgrxuQ8ahYSEMFMsOmCIofs5rSWlPyrVA1LHD2dERkay13K2DkUQyVxbfFEQoPI0ihCvWTANWW4h0Gv8sDHoU0SouR/b1K2X8d0qxxJBhfyFjy/3vaeDeuzNMzhjFFqM1otfIFn3QHpJuLtp4VGsCusAkKYHbpoKOWyzke44NKLOCInp3Elbq9E49Rlr2qwZC/g6o0RkpO02L2N+2iRk5G4YYbQGyAJDuZPM+fPn2fW1q1cRGBRsC9Z16NhR1gRcQUFBQUFB4cXlww8/hMmkl6iXGdYJ9o1Qx5IiOSalvyk8tZhgNG0iqYcL2rVrx5TXucW+9J4m9KdOCQp0SpypzELpUUqWAaNGjwbUOS+305icWyvwaE3W3u0iEiGfAKQOlWIrlfzI5QvncO2Ko5dUUnwM5o0f6rDMnhn7gBvxwJ/HHLedGCDjJZqLv5e463nM/Tv4b+12nIoC8yeSCxodvQPE+0qDRjwJsdIYglzQqO8n/RzWib57C5914hRUBoMeTZs2w/Dhw22Pv/32WxgyZAhTnPEBIq1Ox4JUcolt+s76+PnL7qPKTmnUMDwTxUsI37ENGzYwu528zjMNGtHktGbNmqyMjIcOKnSfFEU5jVifPn0ahQo5Tlh5qHSNPI1craPgGooQ371+CeePHcCKeifYstWBgrxv/r4bqPHt6me4hwqPikbDHQ4okEvdAKLNrtU0bd/9AAV6jEFwuwGsb0WaxbEGeZjPHMn9BL0nuzYaDQ5dFHi2b9uGt956y+VrX48HMg1ArHtZpxLcx4n5Ve67ffwBt/+UqBnvm/NOBndNYey6YNEIFClekqmKeAoVLmw7TtFy/jFJM4CkG9i7hzOhV3h0xo0fj1fat0ev3u+yy8hRPzzrXVJQUFBQUHAKTYAPbd/Ibt8xC4l1i3Uqdy7ccWJsj8GiwVqRKjxKIxhrZ1kVG67GU336vJ9r30Xe6FqsMBL7Z56IU8G9OGcGTLwydQ+KFSuGl7q+ne22s7ScH45/urS0TmNKR82rI1AgkbNbIPwyrkrWuZkAjNdMzPY1YmJyXvaXX9iycpHkvrePL/p/9plkWb+VQIkxQKbFsZOZHBrvQNRvIJQZukKsADq0bR2O7NrMbht5byG7SoT3ZLy1qSsae45V/SbeZpEiRSTLZkyf5nRfyM+JPI3atm2DunXr2paTrc1oCl7aCVX0WfJBo2FDhiAhIVH+/dr9pqLSdJL9pa7x1C0wr/PMy9O++OIL/Pbbb1iwYAHLvpNpNWXcqZsaQaVoVD7GM3LkSGzatIlFu48dO8Zaa5NsjO9IQCbZ//vf/3DgwAEWvaYAFEXvSpUqxf4oCg/PuB9/xJGd65nZ3rJ6p+CnTkc3d+6HTsRnqVH92zWYO3eeZPKrkD9QW7MEJIHWalQ4Yyzlcv3jAa+w6/TAkqB40yGDozqonFYqeTVYxxokcZYzxMvOz4jnrY2VUHIskK7m1FHUEaJYRHF2THgSqCNfQYuZwMkIaxbCYkFrN+dm/fZMtmb2iiTuQI160jI+D+uJYvXq1eyERMb8RJ8+fVCzTj183qksMKcEtMuaPb439ILz9eDBWLd2LTLdg1C6SSdMnzHjiQceFRQUFBQUHhbWPjw13mF5brqmrc9qKLmfmCVMzslXkcZmruwB9u7dk+txFl/SJg4aDRhgbckL4I9rjkGJhMRk1Gjysu3+xsB+LkvOmp97BwGp52zLS0T/g7JRC/DSmZ62ZVk6qbqd/Jwy9VJz5QcpwOmCnMExsWjxYnz00Yd43ilRqiy++fpryTJeDcaXadlTvqDQ4IXwMqexpG9OKB5RzHabD/oQZqthdJZOsMS4lwSmQspIk5ZP8p3gMqwm2PzcYd68eQ6eRkSnV1+VPt/MPX/T3/Oxcs6kHAVDdVod+z47S3rn1Kj9XqouX/qXPvOg0euvv46JEydixIgRzKfoxIkTTKbFS8HIMDYqSjCoSkhIwAcffIDy5cszqSQd5Pbt24cKFSqwx+kPSV908jQqU6YMN/GqWZOVV/FGVgoPB5n17lj9N5P0GbT+WFNjMyb6TcGFEEESm5Clwm8bdrEWoXR59733nuk+K+Qc8UEwwD93JZrpkcLJ3RUmM3cAf3D3ttOgUU5YsPRf3EsWThqUcfDz97e1rnzsqFTYfgXQ+nMm+RRg8FenoY7utNOnDH+lAnw9uPdYRM15GPmnX4LJeqIi83AiIz3DdqKLiY62+R19OeF39B07BwM7cJnAusWA9AQuEEsB9j//dF47rpAzipepiNKVarDaeD4bqqCgoKCgkNegCbAxWSgjyrToXLaSvxfomGhKs0jVDPGi8ixKm+TkPOisHbsz+DGNeJJ84ACXdLtMURoZLl28gIBgQU1VUiPvNaszCV3VisWuEfYxS2iOxPv6+KVLlUZF/MlMWfBCoiRkwe+Bm/6CwKDnm2/ilVe4BOnzCgVjjuzf7RAc4m0inCVy/TztgknXD9g8i7KjXTvhM00WlcaRiocwaAUj0VXWWKDJ7rvJj//PHNoj2c+qVava1lGJHKnsYwD89tYv+Z359pIfcnao1WpkpKe5DKyui6mUbfc0vUllSxDnJ5550IhvW0dqIfoADx48KJGHkXn1/PnzbfcnTZpkW5cMY9euXSuZKJK8a+PGjewgRXWopDaaPXu2rGGVQu6IiIjAwM8HYGDXxrh8+iiSvcrgRmhHeKgMWBHwlW29qMhuaPA+pw6bP28eLl50bMGukPcQDxb0Mt0IXBFbUyprJRb4j3B8DasBX2pK8iMFjUqWLIm6DRrZ5Kl08tA8wvZyC2VDXpoJ/Oo31uk67jo1dNaSv3+yWrBrT30M7t68Bh93IG6UGjv6kq/RZdm/g5uHB7x8/GByFzIuWde2s+vff/8dPXsKvgQKD4eX1ccrICgo3/oWKCgoKCg8/9Ck2KIXyro2ZnE2Himegs+jmB0VpV6UREE11/mJ529je+GO2ZIjtQVrlpILUqwdteyVFUdvxqPVpF2yz9H5BsPd28ehmYg9SZ6CIl4c2kh3EwJOOhPXmbZY3DqH52dmpOOq9SM549ESxSIi8NJL1Eru+eAva9cwV5w+uMulosgZ9p6iqvibOaoUIMTqLXEAZub3nALNohLG8x/WBWrWqc+UQfPGDYHealpNPkT03ERr0KlKlaoO70O8P/bfbbLJ4AmPKCEx0naGt5cH8zRyFTgtEi41pC+QuBdeWZwHME96WhpMj8FU/oUMGinkH8aMGY3vvvseP33FtRXfV/YX/NXwKi4234j5Zdfa1rsb3BAT153C2wO/xTvvObYgV8h7hBUsBJ1V/bJgnshP5yGJ1IgyPVZSU4XBxqMEjRgqFa5fOI2YqDvsZKLVPL2g0b27d0BNA9+ck4zaV35C/eAs9G8hLedTq1SIJ4dwK3z1E51wWpUGfNzMaFoS8BINjNjjBgO83YCI0px6Ms0jXNhGKnfiya2ngII8/GDl/KkTGDpMMEBUUFBQUFDIS3ATYGGivjSTU8SYRRPs7DC76AVGybCcjC0o0Z8b+M5T9kGjEf85b6AT13AADBZhX53FItQWcbJH+GzIRoNHY9ZT33TZ5ycnxKHJDBXeXQps8+yFevUa5AtvmZziShHDwwdhnI3JnZXu5zRA5IqgkBCorR38GjdpYns9cUCH3oKbm46N87f8sxj6TG5/b108zZpmkVqs7yefYOHCBQ7vWS5o9NZbnFdWWrLgPyR+PVdorNt2JUSx/w29dOZN1LkqNR6PTweCg6VdqfMDStBIIdd8++0I1vnq4snDkojwvQpfY37hWbb1ftl5C8279sb5c+eYya9C3qZMKKAfB9weroGpzUjZdf7n5Zi5coY7DC4zVI8aNCK55/iBvbF4yih81Loa1LmsMX4UyDSP2HQJWL5iOwoYo22qImekWjyhMWciPiba5u1EJMTFolLNerb7nctnIXk0UC1zg8M2+OYm+bEWOi/7eBFTJk96qq/ND6QVFBQUFBSyw36SHqTmO005H0sl26mQThpLO13XrPZ06e33ZnVg2dtATLRjtypX8Cpesfk16YLOkseAC8xWOwMflVBCJsag9oJv5i3REmHfy0TNl4wVy96b5/D8A7c1OH9sP2IzdJh/mDw3Naw71vNEToJGc3782qXSyNl3IjI0d2WK9oSGhiIwMAhuHlyQ7sF97nt16/JZ7Fm3AvetX4/ef7ux8T0/7uW9iGAyMPsZCiL5+fnb1D9iqw3xb6bnmz0xbtx4jB79A2o1bMa292ZPzvMq6m7O5qhRUVLFkBzlyjr/jfHMvxSRo79NXiP/7bFCnuCTT/pi5EfdcPUs10mNJ6HacJTWCJOh71afQ2iVZggPD8+X9ZsvEm+V5bzD+pknwFykhuw64ZqcDxbcVI5BI721OweRWyM5e8qVK8+ub1w6y5WnPcWgkTiTULtOHUTduoYb54UWsmJfI55kiw9UFiMat+2Cuu0Ec8b6xQHfAMFXYEZnMyjxUvcKV+KpsggBovVr/pUZfCk8jFT+WSNu6augoKCgoJCboNEma3maWaSqsWdv2amS+2pRYMUeo9rNpdJocU+gWxVgdFPOoyin8NsUJw0DGvfK9nk3k7jxotEivD+Pr4Ez97nbe8rNkKwfnCKMwQJE3dTIhLjmdcdE6LHYIJw9ss/mw0Nqk0dWwOcxcqIGMljnZnLvvXfvd1CwoHzn8ZKhgkq+R51itu3kFLKRKVYi0qYc4oNT04Z9irnjhqL+NKDTPODPYyZo1Bps//dP9jhvS0GeRF5eXsjKypB4KTkLGnXp0hmDBv2PPU6BJ4vZjNCQ0Fzts8lkyjbY41nQsSmQmOr/NEdYhZdYR/eQkBDkJ5SgkcJD8cWAz9GvXz9MGy7taJDhXgC/lV4vWWao3wdl3/4B+/fnvNuUwtNHo+JO7CeNZWQfPxTcC6qCtXK8PQ+V4wkkOFg4QD7qyfnypUvs2mw9gRzYuxtPEl9fX9sBvnGTprbllStXwd8zJ2BS/262ZdXDuTawnm4aeOi4w2ymxQ1qiwmv9hmAOi93sa27vg+wf+s6TFtziN33t1NGqy2C19SJI9xvKDlF2kVCIedQwK1qba4trMVuAB0TI28o+rhROrUpKCgoKDxKAEAPHfbqq0rGCPakuxeW3A9QS5MmLd0O2G7TaclZ0Eic9H2jkrzyJ7vznXgb/g1ed/mc1NObsfEC1ykuE4KBcZYRqDwRUH0FRAU1lzynYNJedu2TcUOyXJx4E8P7YPLd3ahUzeKkjC2/kpTEqdGcsX/zKtttuWDI/PnzEBQcZGthL8bHXYsh7coza4bKRfyRlpr7hNztG9exffXfLPkaViCMLUuIjWaBoRvxwKqzFMwzMaVR1K3r7HH+O0pBPiolTIyNlqiknAWNxI9Topm+l/zj3333XY7212w2Z2/2rfPKZisqhIYEs+7vl6zzmPyCEjRSeCjoBzpt2jRE37uD3etXSh7bV3461lf7T7Iss1A1LNqw7ynvpUJuMFqlwJW1UmNmoqfHOhhSEpFe9t1st/Oq+3aM8J7NDNIP2FXgUAkQmdk/jnroy5c4g3XjUzIwpoBCmzZt2O3ly/7GtWvX2O0NG4QgaZNSQXDTqtG2ciGH7g2XTBG29rBmlXCCoyAReUl5evviQ6FKzUbFO9Ntt1uVeXy15C8qZDRuX8qoc+MGpbdvy3doeVIowSMFBQUFhZwgd95fmtkKXllCh2l7TCphgmu0qJFolrZJ91MJ6h91ZqzToFFivNRAOzfw2+zZq1fOlb4y6qmJO4TbwaHOPWXcjQk5ChqVCFJJyuf0mRkoEJq/lB+u6NHjTdZFXMzx48dttynoMm14/2y3wwdXmjWTBun4wFEha6Yz6GE8eqxjoCmTJ8PTWqaWZfVYsg/0kB8oYTYa2T6tXDCTLU9NSkDxiGK2dZ15Gom3ZTKbWYCQ1n2zZy907do1R7v7v6++wvz52dh0aF0HjUjhRAop2g+yeslPKEEjhUdi2bLl+G/uZIflx0sMw+6yv+BLrz9sy7agKizJirdRXuTWrVtIsA4KTtvVvKthQrXM/ag6swBMOq7blDM6u2/DZL+f8J4Xl734jKumskHGb0WLci3kH/VgmZbGqW2SErj9ftJGxuJ2nWFhYcyAj5j2yy+25U0j/fFdh4rsRMqTYeAGLH2Th9gGLxaV9NBLXlLBqljMEsRKspTjEjEwWbvQibl8+TJGfPsdDh3iFEsKzuXFGt403TpgCQgOfaiuMI8aLOIznHmdHTt2YuXKf571bigoKCi8sMglGVZlNcMNT0EBfieoleRxo0YoISoVuwqT04XSeOKySZhsa7LinQaNLGn3ne7TkiVLXO43v81TJ0+67FKaees0Uo5zHc5UMo1NxGX8Glceknafk7Og0ctF7kk+1/TUFAQFCa+R3/nzz8Vo1KiR0+/QlTNCAMkVvXq9hb59+2L16lUoGuG8w9jDJDMzMzNs3bn5fSMVkD30WGJctO37RIEXvpMyUbUq1zktp0EjCymNzBa27uJFf6BSpUo52t/GjRvj9de7Z7OW62QgvZf8WgapBI0UHolu3boi6vZNbFjyOxJiH+Dork22aPDhUqPQ33spengISozqP3LyUYW8BZUOplvP5W52BtYHgnvjtd5fsr+rfYeB8yHS6LyvnWHhYZFww6zlTOrq1auHAQMGPPJB036C/8MoefPuJwUvUeVPWnyNtSvCkg6ya5XM4K/90RYOy/zTODUVT6LVysjEGwGKmP37PCz9dy2GDf82p2/hhVUaabTSLCY/sLh79+5T3ZdMay1/XmfUD6PYQMnVgF9BQUFB4elzLEvcudVubJHNRF6cJLSYjU6DRuZMrlTMHio569Gjh8vXEG/T2fZ1FgMe/PUNDAmcasq7PNdJS4zeJLwXp74yFgvCkrlxltjTyBWjR49m17evnpckB59H+MBMaFgBmzdQdnz+WX8MGTIEPj4+uHPzOi6cOPTYlNP8OJ6sH+Se7+HhgfHjx8NNp7F56NJ+82bY9DghLhkTB4qclqeZzaxb4BMxow4WvEzloNd8mh6sjxMlaKTwyCxcuBCLpozCpr/n4udBH+CdJmXw37ypyHQrgD8b3cRYX6G8JtHsgwfJ+WOi9CJBB9AuVu+2zh7bJI99sigRKPsGSpQshfSUZLx8ZZjtMU9VFi6FvGq7/6W3oCwjVq0S6qVVGu6gTkojvkQtP8Mf9Pla6tr1G+boJBweuw6BaY6tZjXW0jUx1a9zgxkeNy0wfMS3uHfzCuwTbVl6PRq364qMfBKIeKbladauafwghR9Y3LuXfWeM7KBBNG2HtpmeLu/9wL/uLyKVWl4mOTmZfW6jRo161ruioKCg8ELCn6dUx5ZJlidlCmOHDDerHFlEope8T6UDLoJGuuijssudneMkm7Vus2LFSmx9cbdYHoO1ZN+vTmeHx0YW5hLPsRlcovHUqVPw8ZGW2fEEpJ1H9Rs/SpZR9zRXE3h/f39u+zcu4uWXX8bzjOAvlYkx/VwH+5yRKmpV/6jUq1cfgwYNYkEfuaBR308+wf/+9z+JH2pWRrrtO0Vm0oTY0yhnQSPOCPuJBI2CymKx5n+yD03dDZzYtz1br6m8ihI0Unhk3nrrLXz5v0FYtXCmbdmJvVttt7dWWozNgX1t93/6c81T30cF11jMJhSzVosZLNK2myuoIYVag8sXzmPMpz1w9OAJvOmxHp97cZ0M3FRGXAnpiDPBr0HvX07yXLFkVKV+vHJM/kT/LLlx44Ytw6HTuWWrNDLrU9D4Ql/UvcK1OM0OL73Uq8DXHdi2dSNWdziB/f2B2NhY22MGvZ7Jt69dvfJQ7+VFK09r0q4LQgpypZIqaldHg+/kR++sNnnyZJtpJN8C1h5+cOTn57rcM6+QbP1crl/njCgVFBQUFJ4utgnwbWlZ0eqTQrLjbNF+SPAqh4OlhMDJ3rLTcN+3ttPtDk7pj41Z9VwqjSxZdoECvqTLGjQ6c+aM0+3T+a505Rq4e/cOypYtC4REOn+TRkc1azMfzmfTZI0puDIi5s2wxbgb5YMcv10qLXm/J44dyXGZUn6FH3ski4IWw4cPx59/cuP5nODp7SO73YcpT/tn5QqMGTOG3Sbljz2RJbhyOHFlws3L52x/N3ul0erVq1GgQIGcGWE/qaARgMAyzTBHKnhjjNzMXUdFOfchy8soQSOFx8IPI7/H8uXL2YmDzGTv3rxqm0A/CGiE21XHoo0bdzD/+4YnkjLyh5fHi0JivBB80EMrG5xJT0/D7asXWfeKMb7TMdBbOMloVWb4qDOQqZOaCEo6LgSXf6z7LFYxPSuoDjs0lPPDSU5MwIO7ds7fpNyqJnwGyzJb5mr7qR4R0tcLBDoWu4cQLwtqhwOvvyaUB5I/jpePL3TPubxaDGWZDhwQur/k3AhbjY9GTEJQWEGJWbm4u8vDIg7kZUd+kcKTlJ1QjLsVFBQUni0qo3M1cbpHUayvsRFXCwoqkiTvsjhdsI/T5yzNbI2Pkoe5VBoZRN5IDOsEn28IQrYDrtuUa5CYmMidY93kkylE+H3HLrhqa2dfs7VZC503KRggdz5Smx3P4RbIlwKdTeD8i6pVq4ZXOzsqnJ5HSOn/WnepJw91DsuuxJDn3fc/tI2XxFAQRvUQARj6W/Kq/c8/+1y2azHbvvV7WblKFVvARxw04ucp7du3lwSY5MZ09PiDqLuse+6TChpZLBb8ISPOi7MK88TKqPyEEjRSeCzQD5/c5ytWrMgOSjVq1salU0dsj98PbIx3CgqZiKrfb8LVGKVteF5BqxFOAkcNQnCni/s2xMdLa9ld/dmMGm+keIiMFTUatJwFbCfxS0tBifY4qFKlCvICpBb58suvcObUCfzQ19Egr2p4gO32d6kf52rbGW4FHDqgfFBJyFAc2r9L4o+j1bpBK2Mg+bxy//79XAcPaeCamWE1h7LLRp0/f+6R9yknXl38YPejjz5CfsDHOnBTgkYKCgoKzwa+FOf+vdx7791Nyf7Y7UpplJqSLF1gNkp8+Vw1kXjvvfeQksR1NFPp3JFSoZPTdX1UjgEx3siazvevv/EGM6u+fPE8S2LaU+3mBMfnw4R0a9neVVFOxzuoMLtu2LAh/lkp7QL9vEINXP5eulSyLDeBE760yx7qRKaxlv0/LJ07C1YX4iQfQSo1omOHjsxb1d7TyJlqOz0jXXaMFhAUbDPCflIYXFtp5UuUoJHCE+H9d3vjh09elyxTFWmAFm6CgdpLP+1ElvE5/FXlcUb9MBo//vgjO9lTBog4fowL8O3TV0aUmaoLY+0AAJ8ASURBVFPOfOq1BD/7/exwUI12ETRyMyYg2q+uZNmXU9ahxczHrzTisxPvvPseDh8+jGfJxInCQOXaearnE3DTSj+/K0auJCpncAO4NA/hORZf4fa7b3ax3b518ya0+TR78Sjwg4qcQoqsgFBOYWTDGjRa9d9/j7w/OVUPlS5fCUHB8uaPeY2LFy6wa2cTCgUFBQWFJwu16SaKFXfsYJWdV+ji61IVeM1QmfOmi6CRyt5g2xrI4devVbuOy9dPTohjahC/Wo6BAaJfM66hiKenY7tylXUcROVpS/76yxYg2LVW6u3kFDI8tu7vUVG8zdPv+emU9rTsHfjSLnvMJvMTMXfublVFUaKPAkRFihZhVSz8986ZBQBPXBzXXdkerUaDzPTUhyqpyykGF8Ol/DDuk0MJGik8Ebp143qH798kTMJuhnTAXH9ph6tGY7dg5qxZT33/XmT++OMPLFq0CAPfaIA54//Hsjd/LV6Ey8ZwvJk01rZeJe1Vp9sIELywJZhVOlws0gcG6LA9kesgkJLy6D4xcvDBrHlzf0etWkLL2WcNmYW7IskiyLzJe+BCYeeycd+MG+w6zqeabVmwgVtG+GiE+n+1Rgu/oBBk5MCY8nkiOpprw5pTSK7s5s5lp3h8/QJQvGwlFCwsKqd8SIoXLy65//U3Q5x7GgUEsiBWXsfbqjR68OABMyGlTicKCgoKCk8PvlRHTs06Zetl3Ip3fu6/kyH1AWpcyNE7SJd532mHTL4cyF5pROeyUpWqo1LlbJTfFgtbV+0lH6woHOAp/zoiI+vGTZtLd0EmeCEHBZ14tZJY/dGj17tYtmw5XkRebt2GXff/7LNcPY/8IOWURrTsYcrTsgts8d95UgVRoIi8i4wGA/ue1KpTL9vglzMF3NVLF/DbmMFPVGmUalcZ998ZoF6Dhuz24MGDkR9RgkYKTywjQu0Zp434jLVnnDN6EBJSDVhW/A/cCG2PWlque1RMmhHfLDnIor137nDyQ1fQpCUn6yk4hw6SoZ56/Nr4OD5ym4Tp06fDs87raJXwq2Q9dxhwO1RQsniJIvpJTpJaWbogJHqXxyjtTCxLaP5E24o/yYP9w9Cz11vsWi2TbXmDDIisZFoEJUqMXy0cixzhdJsFk/bZOqLEigJHPEVChQ4iGRnpLBhy7+5t9jt5UbDI1Ne74r///kPsfWmXtA+G/4R+30+B7yMaU9+8eRPvvvuuZNmcOb85NY308PLKF0Ej3p8uJTUVV65ccZq9U1BQUFB4MtCYmg8adazoGLg/dcd5V6sMk3RcEi8zLJs8dTqOHTvGbjsojizyQSNaj29h7goyOaZzncXO6Jq8Tvt4/gtPQyxOfQl0L8S1Vef5X+uytoCPxW7KKhdgkoNURnId1EqWrYRu3QRfyBeJub/PYddTp0x5CKWR42dJnYOpI9vjpGVLwQNUq1GzMT+9dkpCLAtSubm7ZasUogYxrnhSSiOVSgX7GK7ZAhS2+ryWKZPDjoZ5jLw161J4rqCWgpElS2LUx69h++qlWDJjHLp3ews9z3+EBQHf2tbzr9sVEYPX4Nh5x8488TdPo2WTumjfoQO7/+33IxEeHs7MthUe/mBWq4AQfV/42y9wr88FPMT8fSUYlqY/2+4XKGBX0iOD2sINJOKSUm31zU/qoPwkpLCPwpTJk2yZGHvKFhCCO2JR6tnw/g7r8rX3YsxqHYwaR9l24s1jKBbBmWVfPH/O1tWix5tv4nlg5cqVGDduvMPydevW4fJlrqOKf0DuZNYzZ87EyYNSs81CxSJRuHipHA9CncF3kilduaZtWZwLY+wLp09i7ty5yC8lgMHBwU9MOaigoKCg4BzePFej1aJSAU8U9pcqZnNT8bLwkuN4QqPVsI6wcgbC5FnjrDyNTK6zCxplpqcxFZM/hK5dnsjETP+xGO4zBy1PvYbKhYC3ip60Pa5VqxDo5WYrT/P3F/whudc24Ujkd4jOki9ROnOf31dSGnHnMJF9J6CRfn4vEq460LlCrVYhPTVZVmEf8Bg6GpcrV97WQEc8NqJxHtlpFCxYgAWQSHlEcwzeYsMZzpJynTpzCfF7UdIE4uPCYrEgxU5pRD/P+HyecFOCRgpPDIoKz/39d3abyqF2rFrCTNiWL1oAvXcEmuoEo2zis63J+PsIFwxiB4KEywhaXgVbOh3C5vVrWFeiWb/OYI8XK1YMW7duRYadoa1C9uizshAbLRwohzYWTuJitIk3bAEJoqi4E5qIvaJYn28Gd8eoz0RoSDC7/cYbb+DqVeelbs+L0igggBvQUGcue9x1GhT14UZ0GSKlUYa7YyDuQOmfHJaZVVpoTY7S8wKGS5jY9BYuH9uOoJAwW9lVRvrz8buYOnUqvvtOCDDzvPLKKzhyhDt+nD51CocOHcqxYqddh474bPR0PAn47yTflY1HLPmnfW3ctBmgUtuUT3kdmhB888tiREaWRKlSpZ717igoKCi8sBN9anZByo57dpLv3LikhHkYkX7ob8my7jV0LNmbo6CRqDwtO6WRLqwEQnv8CG3h8mgQKSTVFol8DvwyHZPGRpJm0Dgnydoh1XrOtO2CxYITfl1R7mfHANifxwC+STMFnXRmbvwkGZ5pHi5w8jzwsN273LTygRoyOg/LQWI5O44cOcwU2/S9Eptb03eMkle03/RdYyVyKlW2npaUtPb05EofxYRaS+z5RN+TIMMAbMxoIQnqPo4Ovc+SvDXrUnjuaNKkCTsA9OzZE+fOncO9e/egz8rE5OiuWBDwHeb5fSdZf9DyU/h+WG+UCtPi/tJetuWvlAdGjBDKeIqXqcCki/UbNHiq7+d5IDMrE2VCgGSzF64ZC6NHHccDKqHVS4NJ3bu/JrveVuqMZiXBpyK7XjTlB5tBHR3kIyMj8bwHjeik1r7jqzZTZXvupHLLd+hrIca3BpY0EDp/ZGqDJB3o7HE3xCPF09H88v26FnSvCiQsex337915aHPovEpaeobTbmQxMTHsesf27ahbty527tyZ7fa4sjA1AoId1VzEowah+cFUmSq1MGsjlzEtHF5coozcvWcfvAsUx6djOS838hTLi5w8eRIvt25tu6/TuSMjMzPfGjgqKCgo5Gdo8nv37l1bybBYwUycvSefAJTj126R0BSrIVl2O0ljKz12mNy6KE8jP0UqP3NGge4j4VGkPAq++SMCAwRPRx1cj1MKWZVUmTouAWlSS5VB5JlKXZoT4rixgBgyzearqPzTOVUy4SmOlTxBE+S8DgVT+FLE3ECd6+Qw6LPg6f7oQTiaN8hVEXTp3AWDBn9t696WlpwEQ1YmChcujL6ffOJ0e8OGDZMdGyYkcF2hs56QfQbPAUsLXDZy85+lJ5+cx+vTIm/NuhSeywMTqYKI8uXLs/ufDfgCdzO5E0dz9yPYGfS+5DnzjN1h+WANRt5rgeIxa9jltdZV8euvv+Ktgd9iwJgZGPrr3+j8bn/cvHnrmbyv/EzRYsXh56lClbi/0SJhNial95Rdz8dTegKwbw++0RrzmHcYaDID2JVcHmeL9mPL0lNT0LXrk60Vp6BRXpvA+gcEZmvOuCSzNfwyrsIsGgBtqLaaXWdpAxDnUwV7y0jrzJO8SjNfI2fUCYnBx3UNcDMkPldBIzJWdOYzZP+3zy6ISEGmzz//HGtX/QutE2n2o3YH44NGwWGF4OMfgM/GzEDpilWYGSOpjXr0eBNffTmQBZVoHcLb6lOR1/jpp5+xedMmdluvz2Kd+ah0Ia/95hQUFBReFGiSrFYBSfExDp1ZUzJzdt7/xPNv1KxUGaZkabDFw12L363VAQkJCZLHHEq3s7jHO3fuzMb1cj43PBrvQNvtiyrBy8VdJa8O7uq+hV23KBeGAol74WHgAlmJKukYKCMtlQUP5HDXAlodd573MAgl4ruuOd3NF47q1as/5Ljb8W9N415ebf8kePvtt/Dj2DEsiUivtfXfRfDx9WVBrBnTnSvHyc6kdu3aDssrVazErgMDhe/m46ROnToYPnw43N3cMDO5B95YFY5lJ4HUlORsO77lZZSgkcJTp2zpkjh1YBf+rn8OO8vPwYUaM7Gt/O8Y6s2drHjW6RvZbo/Wch2IMpNiUbvFK/Dy9kW3j76Cu4eHYoydC/76awkO7d+LgwGCwfXcDPkWqO8Mmia5z3sTvf5GD3Y9+FAV+A4FbsQDB++4YdLtl2zlViXLlHPoIvUiwMu0qb2sPTWKcScnNcy46lYLiw/exJB/TmP50TtI0BbCnw1vYEXdE7CodbgZ9qpDV7po/7ouX/vnV/SocusnvNSlF2rUFDx18jPM+NBJIGfAgAGS+zt37XK5rUaNGuGXX35htykAIgcF2x5FrswH6/jrui1egZu7O8vapqamYsmSv9hyWkYMmfYn6zoTFBzstGvNsyKyVGnb7aSEBPj4B7LyR/7v8bwEJhUUFBTyE2SmS+OxioUfrnHDIJ+F7DpUIz3X+Qdzih57pdH8+QuwevV/GJv6Dj5IGsotNKRJkjs59QO8oqtsu11SI+9NOt53Kv73cllULOSHl84I/owWtWOyhz8fLTW+I1keEUjla9yYtVjsOtvym9JYmMLDBI1k/tZULkleW08azojbhC0rFuH0KcH/Krd8++2IJ1qxEBoaipEjR8JNp8GN+ynYf4dLEgf4Bzwxn9engRI0UnjqtGnTBod3bMCm1f/hqldDxPlWx5R7rTB+6j9422ON7HNS4Y2fh7+BcuEmHN+zjE229504jgZtOmPjxo229Wgi81r37k/x3eQPLl68yIyDjxw9yu7HeAoTQjledd+OksUFPyOCP9At+etPbhuxcaylJNUd0yU1kZN7EkZj3u8I9aROaMnxsejbVir7JkqHcYoSA3Rod3Mgzt7jzASP3UrA3itxnFRadDIxqIU6fbPaDfcCW+B48W9cvn6ZqIWoUq+prTNGfodO6A/u38+2G1yrbm8jNVW+tSpPrMiAkPd+sodKyR4laMQrjUpWrGpbpnNzZwEhcZCFlrH98PBkXm0J8fEoUcKx/PBZwk8ayCsqrFARBFkeYGy5dfB/wKmPwsKcK98UFBQUFJ4MNBYjxWexIEcvn+ygMfYf3DAQn3/KKcN5Vhjb2W6vXs2pn4lVq/7Drag4zMrohs36+lib1RAwZuYoueMKrUr+ORqVGYHeblBbpIkUiwsPorumopL7JQv5gkmySM2bxZX0EStPA9P2Ar3/fjhPnxcdOYX/yf3bmdH502hOQ0ojClBVrFYTy/6WenLlBn4+86QDOMWLF4cFFpvNQmhYKPIzStBI4alD/jb16jfA7z9+gz7Ny2PBhKGYOuQTZHoURd3a7RG2YxRC3R1PJlP0vbAwsz2WxZRj99dc16JCuC+uXb5gWyc5ORnLly1j7c87dXr1mbaGnjR5Cs6cOYO8AMkz33rrLZshnKfKtXfLj76/AHZZHTohnD9/nt2m7gbu7u7sgLtlyxZMnz4d+kxush0XHcVkwy8iZIJ95zpXP2//GSSmO1eSXI52rHPeUH2tRGlEAaXLhRy73NkTVpgrB30e4E/ovH8RHwDlGT5zmS1Yoze4VuqIu1ZQtxeeDL0Jm889QFwqV4KVU0NtOSgw1LJjd8nfgF7r7Nmzku3yQavQQkWxdvUqdpv83vIScXGcpJ8CdrVCEtD75muoWRSodnuMbPmCgoKCgsLTm7gHeDkGUaLv3XKY1JNhNE/W4SX49B/uts6uvG2FQfCwo9IaGyoVbhVsY7u7NONlICvR9jqse5oLTyM5BngtznYdN6O0S5dJ5eE0gPH5gC8kj4XoUlDCnzvnprpzAaVrcWSuDfT/B+g+wvohKOQK+szJT+u/eVNty8YPfAcXThyCVqt5amp+d3ePx9K2/kl7o3p4eCA26jYiSpbBhg0bkN9RgkYKz4T9+/bi+vXrWLx4MS6eOIQChYswJQx1RTp04AAOf98Bv7fygM+C9mjpZu2cIMOirEZo5LcPFyZxpTt8kOjPxYtYdmT9+vWsY1tUVJTDc/ft24dvhlqlto+Zvv3644uBA3Dw4MFcP5e6Qj1u35CAgEC2zeQU7iQc6u56YuwGA+Du2D6zXDkuYEclgYULFYKPjw8LSNWoUQPRd2+yx9KSEtGgYWO8iJBsNiGGMzbesnKR5LE6JYKdP8/aJUSMUS3UPScgELfj02VNsu2pXEiFtnUingvvmcKFuY594gzWq9ZWqYTO6llAn3tWZs7Lu8RBo1Frz2H7xWj8tPkSywY9StkVmZTqjVJPq6AiJZgfmJzSiAy5s2sZ+6xYuWIFu6ZuOt+3cK3iUni8xMfHs+YRpOAkn4g+ffqw8kZXZGZmol+/fggODmbHZfKUs1foURDW/rJkyRLJOjt27GDHc0oKUKe8+fPnP5H3qKCg8GhKI+IV6lMvYmCXxoi+e8vp+GLCFj2SrSKhrpQFyOHrXS4inHdvmwvCcmsbzIk3MLEDUNI/I9dKo/Jax25p9mhN0vOORStt2kKfgclowM8//wyNl9SbJtO3DK7Hc0knnyzOwmLzJaBy5Srsdoi1e5ZC7oMs1Mzo71nSLr9UskZd/Z40NBZMjIvBsYN7H7oDnDix//rrr+NJUqhQIViMBmbeTf6++bk0jVCCRgrPDJLt9ejRAzevXsKDe3dZRNa+89ry7efxfYjrltR9k4dgfEIbmJNus1IPnqKRZZi6hgbO1Lrbnt27d2P13DGIf8DVVZPD/grrROlROXHyFFp27uG004ArKAgzceJEPE6YUaHZjLR0brQQ6OOYERjnw5kvf+s9C2O2WgAf6WDEHlIb8Sdemty4e3An9Hs3r8LLU77853knLDQE+kxOxbVk+licObTH9pinm/MszO0ER+UXGV+fC+yMgfpR6L/HH7/uvIojZCCVDW1PtMOa124i5t4N5HeCrd8vcWAlNVVQZVEN/eApC1GzycuIiYmW3cZ77/VhAWJ7RRiRZRfg0Wi0j6Q0ogBLaOFw6XsoWATlCwDTvhUM/719HQOyeY24WE7dFXh+Msr6SzO+Ck8WChiROm3z5s1Ys2YNdu3ahQ8//NDlcwYOHMhKSpYtW8bOZaRc69JFmOjxzJs3jyVR+Murrwr+aZTIocRN8+bNceLECeYb9v7770tKwBUUFPKOr0zDUo7BD/uEkUl8n1qVW/Hz0OH2VMEzqJzmOqoVhuz2mNrZynVTEUTHp+LCrHb4sinwTaWTuQ4aaeB6fe/M21BZTC5VIbRfiTFRtvd7I03k8aTSoE5RaQJIb6Jxv2vvQwXXaDRq2WYvG5bOxYb165/469NcIy2ZUzk766ybUwZ8/hkaNmyIJ4mbmxubf5E6i09+5ueErhI0Unim0I+JSpvkoCgyKVuK9FqOib4/2+qxb4S2x+6gPpJ1t+nrIHLsKfT4Lx4Rg9fg1Qlr8e3vq+DpzfnIHD/haJhWL/AWznwFWDZxXcFGjxmDbt26PZb3ZTAa4Onp5di2NIc8rK8KvR51anLYXkY6O1AFB5rR5pvJrIMXoRW1PH3dczP7bDWpCRieAxUlddkgVRT/tzJZJ9vJCbGoXk3wdHmRIJO7vRv/ZQE1gmqvxbjyICCfLuLSgxR2+05iBkYZB+GfJKHDxcrjd7G73K+45KJMTW0xslL+tNj8HzSigbF/YLAkaORmVenwiqEqdZuyMq9kJ55G8+bNxbhx4yTLqEUwkZYlHfw8bHna9u3bMW78eKYIIZ8iMe5aNY4PBCZU3oJA60POurc9KvQ5Xb169bFus/DN58MfK79AJcAkY58zZw7q1q1rM3AnRZCzEkYKVtLxmDLuLVq0QM2aNVlwiIKlBw5IlbqkXCL1LX8RJ2tmzpzJvLV++ukn1u30008/ZefESZMmPfH3raCgkENIaQRh4mm17rFBqgYxBuo/b8Vikp7fzBnJ0Dzgxh41deexva/jyyUnJcEksito67YXFy+cRUUdZw1RNTgZSYlc59ac0tyNGzs6o+rNCVDBPqnjmHiLuXcLERGc/2bxwkIATaV1PMdSrsjfP+8nbPIynH+VvDr6wgXOvuJJ4uUljKFJDZvX0ViNu02kxNJqFaWRgsKj8sknn7jOUgSVQTePbSygMdJ3JtBiGla5/w/tU52rgo7HWvDDhiuoUP8ldj821tHbqEQyFxkJjl7PvJAeVeooxmgwwN3Ti3mx7N27V/LY7Nm/OX3ejh072bV9rW5OOyt99b//odtrrzksj42JQXJqOv5WdcJ5cynb8mrai6z96q9+nE+JGRpsvh2Eb75xbbhMUAkEr6Siz44vv0lLiMnXLSUfBTc37jtEXf34riJietcvjuZlOSO8Qv4eCPSSfucW7r+B+fu4YM+MHVexn4rw7bgd0g5HSv6Q7b4k3r3Erk+ePImfJ01GfoSCIBTIER8fxFmaLKuPlpePL7ZtdlRDrF271pbtkctYHhR9vqG+7qzEh0qDcgOV83Rs2wLjvx/M7nt4Sr/7XhoDa/9LdOjwMgaOm41CxSIl63w6ahp0bm5c5jQxERcuCD5tuWHbtm2spOhRya5kzv/FFBI+Ffbv388CO7Vq1bIta9myJfvOOit3Pnr0KAt20no8lHAhOTxtTwyVsJFClFoCz507V/J7onXF2yBat27tsA37RAWdP8UXBQWFp9fBqpu1zEyn4Sak9pN68u2zIeM9pDJwyU0jNAiQ5jwY6ekZMGmEg/5ZY6SDCig9Uz5BapIpvefNrl0RmHoGKrt9FY8DZs6cheKlymLnun+ECoOGo2yPu7s7Juh0yoz38XgayYwPihQvieXLlz/x16fAiyErC1WqVc8XQSMtM+42MaUR3e7YoSP69v0E+RXlJ6SQJ8gu+hpfpDN3Xe5zoHo/FC9VDudvp2HCy34YWfqE0+fF1vwAtZu1we07QmtPyrzSQLkIBCUGZR+y9FwGpkCBAo/0XihQpDFnIdgLeHD/HssUi4M+H330ITIy5I2omzdvxq6H2nkt0cFx0SKpR44cVJZw0C6zfO7cOXYdUbW+4+thB2u/2tadK9/5t85+LPprFS5d4gIOOYUm5UbeiNhiRtGiOauVf94oYe04FxPNlUqZ7ZRGVKLWqkJBjOlcGf1blHYwsrxw39EQ2xlmlWtp7oD+H7PrmbN/w5dfDGTfjXwZNNLqJIMUD6uZe/e+/0N4Sc5jS2v1NrL3fWnfvr2sjFltzVjuviKUs8akZMG7SNlceQytWrUa//77L1JGA3EjAR93ICBE2lWsVLiQ/SzgpUetpq0lx7vFB26ifqsOKFupKpv8T/15HNo2LG/73WbH/fuchxZx8ybnK/ao0PGpVjgwpF2A7OML3ngsL6Pg5O9p35mOvr8UoBf/re2fQ8dgCjaJoXOZ+DnUAvjvv/9mZW/keUQJG1Ixibdjf/6j+xQIcnbOGjt2LDt/8pfwcGl5poKCwpPzNCL8PHU2RVFY95F4kCo9h/HraizceKRps2bS7SVzCkZ38rKUIbxYOEpohA5kt8yFSLIkWcdNp8Ow4SMcEh4Gk/Pg0NLb3PlbDv+Mqw6BKXEy8q23etmSc5TAZJTrIaxc8W2Hbd5I5MYBI0aMYEpKhYdUGtmNawmNWo3AQKmv1JOAzoVZWZnw88sfijENrzQyceVpn3zSFxMmjEd+5cm7VikoPAaC3ljJBq1B1gkjye9P7HsXv1osaP/2pxjh/RNGpsl7PuibD0TihX7w9fVlk8pQH+CDusDotsI6mz4E3lp1it3uVT4auLMHKNroofa1WeUwHP4c8HI7jQtx7hij4srNxGoH6gBVrVo1p9sgbwmavPKdAggy0yWPpv/++w8dO3aUfd7du/fgzZ9ArVSsWJFd39Y5Dua3HriOfqLPIdONmzCULl06V++ZlEbxsdFITojD0b070Kd7B7yI8JkP8h+hEo/sTJXfa1gCw/97uA57VIbmijKhwMqVK5lPD3HrltQcMz/AGdtbZJVGnXp/altGqj7eiLps2bK25W/XAgr4AOdSU+EXEIjkxAQHI2wx1yJeyVVJKZXv3L59C5MnCsGUk3aDmUBfIRs2svxurHSyrRpN2+LA2t8xwn8mRgwBlmyejwoVxkves1xwnYwWKVBN6pHszJL5bZFfTqVKlZyuQ4orOoYB8iUHnZw/VcEJX3/9tUOZpD18d8onhbgjUvXq1Vkp84QJE/DZZ5899DZJlfrFF0LnIgow5SRwROe3R/EPU1B4EtBY5mm0Dn/cbc95PEvUwIorRtSsLCzjz568cmfggAGS96s1JLNwUZpFXkJas2ZteGRsx8/pvYTn2X1EVH4z+odRqFSxgq1hCvGAd90WcSCoN7s+efoCXndyqMjUBkJtFzTiu/8KwQsTQkLD8MYb1iyGSoUZmnH4feJgHP3yY6yeNQQdSgpdPvt8yCXSvv/+e/kXVcgW/nO3h8a69oruJxU00mdlMT/L/IBGo2EBo6P7dj2yB1NeIP+/A4UXBvEJg7wY1Co1tq9ehsr1myPiyircqMK1ria+C16B+Re4yVpiugGFek/G3VnvY1jLVIwSOofaaFUG6F/tPobyyvyljYEvc2dWduzYMazfsBG9agAeOhVGpfZBFe/LCPHeyQJelAXmVQybNm92GTQqW7EKoqOj2YSQ7whHk7xDhw4xxZGzoJF/QCDSrEbBb/bsiT8XC21NM4vWdli/YIbQvrzfxgJo2AioUrMOvvzyy1y9d5rMenn7YO6Pg3H90jlZX6UXASr5INN18rahmnp9NpMijVrFVEe8n1FOoMxdbGoWVup6o4thgdP1qPKNypX42v7HWX751FBr4B8YJFH/iGX5PB6eXmjycntpGWfafZsipuakNajZsCu2r12Bz8bMYAOfpAz5vw11Bswp9kHBLpUBn6DbiEU92zKVKLjnoXGuYioUUQqfGkfa7pc2CCVBX375FY2HWSBSDl4FQmbI2UHHlcqVK7s0Y0yMuYec9Jahv8uff/7JgtkKrqFj6jvvvONyncjISHZuo7+R/feMyibpMTloOX33qbRRrDaiJhDOnkOQZ9KoUaNYoJQC3rSufcc1uk/mo+Lzrxh6Xm7KBOh7R4om2lcFhbwI7/uVV/1H7JVG3m6up3IJadx50Wj1JRKXoJJx/vfzloPOICuyWuInTEaVek0Rc1vwxjPJeNiQskQMn9ixVzuuOuHow1ZQw41p41xYd3oYE+Bh4Jox8Ij/HnQOp+NicGioJMin9QrAMasoavXJNHQoKTw/spSQUFJ4OMhyQU6NnZQQ91TGmHzQKL+YSWs0GmRmcF/0vB6MzglK0Egh3xIbww1upw75BHuKAF25TpqMb2O7YgmWIxNC5qTIR3PwCctwOPrEELaAkRUyI23TRibC5ASS/A8bOgSWiUDxmNW25cWD9+Lll1tj9uxZzGOCSIgXsh9y+AeFsIE1BY34bCzfNpVO8s7w8/dHeloqdv3aB7+W/xM75lo7oKnkK1HvJgkH3mWnNWhoPfk/zMH/zs3rSLIqOUip8CJCao/+/fuz214e7oh6IG9caw8ZWTop/Wf0qhuBRQe50qOdl2Kw7QJNKl+DqnJ5dL7/texzprwKVPtjD/M0Ih6llfyzYvU/XI38sGHDsHXrVnY7wIkE2tPLW/q9uyoEkYv4A6nWUjAelUneJ4wm9r17c5nQ7EhLdwyORhjPIhaCr5jYzPOqR12n2/LxD5QcmlKNbraA0KRJPzM5vX3QiA/OkhEyqTtatXkFmzdwPk7OyIk/WmqSdLAuR5ly5ZGQkIC3335bCRrlgNDQUHbJjvr167OACpUqkqKWoOAvHZcpyCMHrUfHbPqNUNkZr2YldSFtzxnUIY1KCvigD627bt06h/Oaq23kFj5gRCV4ZGqaVyfmCi8eNBElVTgftKXxV16EEqbi5Ak1W3DFxrP3nZZ5UafEtaeuYlMaUEPLKR0HlDuHH+KDJZ6Ys7SCyogI00iDy7z6hMrTxONmV11jXY15iEq3pjrtnsZav+uz4O0pVfaKJ+bJ6XbnOnU+TJzlMbhgnWPCLS0l+ZGtPXIaNKIAldbe/T2PotVqkRjPDewUpZGCQh5h2rJ9UDVowAI2BI1DNwd9gsbxcyXr1Y9fgFfcd6O/1xKU07r2//i0V1tsO3aTDWz51vKuuHWHS2/cNkn9KGrWb4iZS3bi8OHDLHvl7umJH38ci7FjOfNpe0qUrQj/oFCkpHCKIT5odOTI4Wz3gSYOD+5HoUrcXPh7As0SuEmmSueYCW6r24X/BKsnxNznAhxk2PawGYOUJC57XK+eoLR4USlXtgz2r1jHBlO8h44z2lQqhHWno5w+7iUaeB0QmTcf8myHpt5/ICjtLE4bSuKOuYDNn4q4f40LGIVHlsmTpSDLli9HsfBwp5NhHpo08xQpGo7RCxwDIyRXFptYmy0Wm2nfB/WAjnNX4P3hPzNT0F2XY7DrEk0MuIEH/c+PX90KiFKTLqBOVtRVxn7s4pch7V4mNvPMCnauLvQLDJYEjTJuH8aSpUvRuBFXJivXLGD++M/QqARsqg0aMNu3JbYnJ+V3muij2a5z7dJ5pz43Cg8PBQdp0vXBBx+wbmb0u6UySCrBKFy4sK0M86WXXsLChQuZupG8hEjdSGVi5H1EyiAKXlOwhz8Wr169mqmG6D51TKNg0JgxY/DVV1/ZXvvjjz/GtGnTMGjQILz33nvsd0ceSLyh/KNCGWo+YBQcLExKFRTyCryijgJH9D3Ni+oAlV33NB21BXNBdIrzYz4dK1pVKYpN+6mMjTuZvVspBj/sDWIG+AMGDISPjzdQW+qDFI8wROAeHpiCEKaOZ+en8gWAoYMHYoCo/C3L6Fxd65HNDDQkVfAr3XgRUBeXBo3iYx7A11tqeC3+e63gHCcEVHnvb5nfoL9AYoy8t97T8DLlExz5pZohICAAd29ee26CRooRtkK+hRQUV65cwY0bN9jgOCpKOukuqo5GaY1jYGhtVmO0SZiOxVkd8UfFbXCmcuxdizrQlGHZYTpJZ5cRTUrm/ETGp0lVCufOcp41VMZBk6zq9Zqw+7dviyI2VopHlsKwmcvh4x+Aa9euscxX8eLFHdZzJs3kD6jiDhhF+y9GsYFSddKZ4NcwzvMnRCUDZccBBa0l3huWzsX50yce6eA2ceJElCyZs4n380yDBg2wecUivP9SBRzbw6lknNGwpDCB+rZ9BfRvIXTAer9RCRTle7VTlxJRJ5S9V2JxNrwfu90hcQr6Jg/BXn1V2+MUUCBCChbOk0qjHm+8IVHPLF++AiNHCh1QSljl5OLv4/37UVxU2A6zSiMJjOkTBePODhWAlb25UrFxGy8wtZbFOkAmhrevYLtd6J0pOdp3OvYQ9kEjg0bqKSY183SeWg3w95XcbxOZgs1bttmOE/ZdqegY0M9vLnb3AzQZXGZcb9CzLmz20LrUjp3gg9F79uyR3xGLGZUvc53gXEGfKb+NP/74I9v16XU//exzlslXcM3ixYuZLwgFhtq1a8eaKcyePdv2OH3PSUkk/iwnTZrEjN9JadSkSROWoCBPMx5KBEyfPp2dK6k0etasWew78e2339rWKVGiBAsQUUCpatWq7Lc5Z84c1kHtccD/PsVtkxUU8hr89zMvJloIOv2JlUaugkb2Y8WxY390WMfbgztn6KFzGMMcOnQQQbFC0oZHrdHi38xmqBu/EFPT30CkbwrO/Q/YJ1gNMiaPH8uuC6lj8JPvzzgS3NNlF867mX622/f9SfvO0W8lp6jlofF4Rno66tSuJd0vUdLEaJ9n8ZBv7KCQc0h9Z+Kb3liTzDxPQzXKv8bBA847euYl3N3dbd9JStbkd5SgkUK+pUqVKiw4ERHBdayiQXJMABeQEdRG/XAjtD0uh3RyeP7Q5A8xfEc6SsSuQZxZOFHxDG8F3B8qzdBQS0m6rFmzBuvXr5dMIE+dPO4wgSTMHgEoHgRoHhzEqlWrcO3iWbb8zTffdFiXFCnkz6Lz9mMTArEq4H/NgAGNudvOJl7UaUrM/Iz20Hg5dhnwUWfAz52bzF6KAR5Ym3ZtX7WEXT9KbTJNchRg+15mZWbi12+Zq7DLEyF5G41+tRLcdRoU8vdk9+kSGeoDrZNB4a34dOzXNMdEX6EDUs+k0bZA6NfNuety1ergzFnue5eXIOWBeKCx8p+V+PbbEZLB7uDJC9GpcxfbOjo3D3j7On6nff0DJaVXHkeE4BPRuTJQKGEn9A4jSfIgk2YgK1QQgkjO4FU29JsnA1HeRNTdwKmdUjINOHsvCe5ZQlauaPwWp9sLskjl/vykhX9PFBSnz4vvhnVX5L3kmcKVFVy5dIl93+w9B8gom/cpI4UU0alTJ0lQwUamo9cM/SnMFhUOlJ5gW7byHW6fCCpRo8/DWXcvgpSW03+Z6uDXo+AIqYUoyUCBNpoozZ07V+gQRMmF4sXZ76OZqAsSDUgpKERqO8rC0t9W7GdE6qXjx4+zbZJhOpWmUXMFe2UabZPWo3PP1atXs/VhehiUkjSFvExe/36Sr4w4/6DVyO/v5C2XMPRfaaMNubfm68UlG88ZS8oGm14pDzTWHZM85/LlyxiQwqkUJ6X3QiS4rmlVOTGkjQfRXKlzDd0FdPXYhhC1EPixNzM+FeuDfSlc4xZCbeGCdu8uBa7GCYpa7n1wbyQkWFoFQMfG0qXL2O5P3CF6MFDxNHpUyOz68K7NtvsGfc4bh7yomK0BXkVppKCQxwjtsxNlfgQ++1e6XKcy4VLIq06fVzPuT9nlfh5AW1FX0Ndee41dOnTogF69hBrv2rVr4/TJE6yjhIdKWkddvG4LXB8C7P0U+GvqN4i+x032SEnkDF+/QDZhbPdKe9tJe3x7YFIn4LWqQFzUdfknmk2STM93qVy3CGeMGPEtfvvtN9v9TKvk81EGTTnx7XhR6NWL83opWJTzssqOh/ncZ+y4imnXrJIiK6PT+rBr32rdsHDPVVSq2xS37+bMX+lpw79nCkAs+/tv23JSRtGg0jcgCCpRtzPyMdDKBDVp2Y4dO/BGD8dgLI/O5NhdbFr5vQ/VxYqOAXygt0HcPFSMXY7JaT1Q9+owLNh3A+M2XMDig7fw1r7SuGfiBrapHs6/BzqTo9w6XHdfUgJGPmu8z8bZk0K56pp/OSWhj68vSpWrKAkqU0t1PmNOEwHaXmBIGAsurFghEzQyOpacUWA9MnY1rvhao5BWxEGn8ePHo1495943vN9UfjGwVFBQUMir50yzqOxZ7WTcYF+WlnHjpK3EVYwFwvn1ipErMZr6EqfULRsKvFMbyLBILQ6SdNJxnlOLGeu5WyPy9uOp30DoUKz6Cui1qTyuuDdyCBrxPSvkSgXtl5HK8tIlrsHL2++8i6FCbhfwUsamj4p9QvlZBY2otFrh6aMEjRSeOy7FWPD1X7cw64D0LOamMuJCSGdULyBf1zzbZyQuGDl1iJjV7wFbp77OWpjbZ4MJ8ongMyBTV+7AssxWkvV2e3fCSQPXwr5Lw6Lo++0kNOv4Orp37+70Pai1GpYt3r6NK2taw8UAGH+/BXgfEUoKxIR7J6O+YzWbhLc81thuf//9d3j99ddtqikae7zd+9Eyy2SsqsBB3lVEoRwGjVzxXQchA5cdczI6s+tAww0WeHHz8ERWZt7MCJlM3OB3xYoVkhK6Dz78EFcunIVW54blS/+yBU8Mej1bJjeYoQ6GS5f8hQYN5IMXNDgOpLZyIoroOPP2jpIUqfwI+JshQzF69GhuP6yBGK1/CJIsXGnZ5HROen/xQYrE5LNB/Hx2rTY7/xv4ZjgGkT8vvhPnznMZXPs6/q2zOMN14uBRzrvKYDQwOTQZVBOkKqF26rxikdQrly5fhrsnZ4T655+LHVWLJqmJ/X2TUDo5bKNUSZR4VQi4kenyzZs3nL4/PlikBI0UFBQUHh6mDnyI42jWvfOyKvLYLGEquFnP+Qu2L52GUiHAP9bh4BGjdPxxJqCt5L7Yi3v/nu3Yt28fDh48aEv4aGWCRrctJRwUGUUiBLWT2sydY3lxsNy5w5V6Y8G8ucgyWtB1AdCL8sLezjtJKuRcaSQmLVlQjj1NcqIGV3j8KEEjheeSwkXD8fVa4QRj0HCTJA+VAa81qMDKfoaRfEfEmOs1mNdR8Zg1yLQIJ1aqDGqhX4qLg4FfZwr+K/wEl5+gEZlOOhO9ljieXXub4lCmSi1UrtOEGRCKoTKUa5e5DIlGq8PQoUPZ7XJVanCvZ1Ej2szVZAffXenkBy1kn35Je112nU+9BDUH4evra+t2ERN1ByEhD2dQSpNG8r/Ii8aRzwoy0nz33XdhkjExzi1uWjW+75jzwFGWRYssHfe31Lm5IyYmb5YFLV/OqWTsM6AL5nOBFl5VRD4TM2bMQHJykkMZZnyaHne0hREVUJndb+51QPa1LCq1Q3laSCZnXF2lqFDyVrJiVaf7unTpUna746tcyVzwe7/n+L0Gp3LOnInpeuy6FINMgzCQtsiYdIZ5pENvMKB5px7o2q27bYBcukwZBIUWcBiwm4wm1oWN934YOHAgu46NjWXXe/fuxdAhQ1h3RnHpmjgIfniXODULRJmdHw/OfAXWfGBCe7BSppxItJWgkUJ+hfzFyCCcjlU0eaIS5M8//xxxcXG2QPLgwYNRuXJl1qGK1qPSTb4kVFxCw/sk8pcff3T0mlFQcKo0cjGmIJvsGBnza61PkGyQJbhoJdvtMppbttuUzyFz67smR4XOP0apz1kNkQfy8jljMPKn6ejy2us2pZFOJSSE4nyqYoW+M6JUxVHgO8CPG+qypiHUBZUnKI0rrTM9ZNCIZ+VpYLG0uk7hIRGXSdN3UJ/FJZkWLFjw1PahZ89eKFs2f5UazpkzB88DStBI4bmlU/e38cdR4Ib/SzgT/hlbluglHGi83LQY0k4aOOIpF/sPCx5FibLsRE8j1wI0snxlZsB9+MBu3J5UHiOt58+fD+tlzY15g8Hk1AwEhRVk6g9SKInZvXu3rZuEWq1BiSAuy9O0rCcytYHom/wN6sQtklVD8VjMwiT0p3THNth9PP9FAY3QYUoMtUqVqzPPKdTymzr4KAhQVm/EiBEwPyYTajK8HNhSqNd3RZw5AAUTdts6c4n9APIaZPLMMqAq7pR06eIF5inWppwaV5Ms0Phyv6U5v89liine7NlgMuPQ9XhM3HQRV3UlYKrUHm3rFGQ6oRumQuiWMA5nDELm0ggt0kRG4mwbOj8HX6P00i/jk379HPx3aKLIq3bIdDo3UBCPStA0pkzM23sDG87ex8g152A06pnXkm8Gp9KJ9a0ued5P40YzDydSEUVb/SGuXL6MFFGGz130kz24a6ute03FihUlgaGzVl8rCizxHDp0iA3GKfhNZXkeuwQFE9E5kTPQ5tlZXihn5fmqWfamsUqwSCE/Q+XktWrVYl4uf/31F/MxpO52W7duZebiVO5Jqj1SOw4fPpxdU/kmGZZ37NjRYXsjR45kJbn8hbrdKSjkBFLdHtsj9cerTcaZVqjJw6QtlxyfqNbKKo0alRESEB8lcxEcdrjWcT59ryWOy3afunD5GkbbHu/j7UFjUbZydWgDOHWPRpTQvBnSHluymrCAT2y6Gnx8i3U81cjsX2POq1QuUJaTBh/lypW3dcVTeDTEXS8z01NhMOjRo9dbLDj+tFi06A/WKCI/4e/v6MOZH1GCRgrPLaNG/YC3/wI2FJ2AS4XexomI/2FvWcEwmPBx1+K9hlKJrJj68dLouW/mTaztAyTcOI3qdRpg3EdN0KoMZ5pd7Kt/JOvO6FkT3npOhRSo4cpKKI5EKiIvH18kp0rLQoJu/YWMH4GisRtYnfCK3sCrlYCZdfdCa0jCZj1XckNqKKeBI2udu8EiVS24IwvBp+fB5zin3nAlO30ezNryEvR5Go2PrwtLqK87M8yWo3stId3XMv5XpHlw993cPfDg/n2X2clnCWXqxx0HIgatgn+DN/Bll/KIqz8Y5zutwror6Sj6Cfc7JBWbpmA5TN5+HefuJWPs+vP494TQJY0413wOTBagWfxvTFLfPlHohhZnknY2E/smiH0h3Mo2wcw581GgQAGJktDb2weXLnGD8cSkZEBmgOuMsrH/Qm/RwjfzOmJShSzw+VN70fzs26hyiwvO6LX+MKqFAe4fXRLh6e3DlDxjx3LljoTYHF3cuviVnh8i1Vpyxg/wqKsWsWvXLu65ovI+KpMl3yPi8wEDUJmzTHLKqugInDWWyPXgXSlPU8jP9OvXj50jN23ahKZNm6JYsWJo27YttmzZgrt37zJlME0MqPMc/aYoE16vXj1MmzYNR48eZUpce4UvGZXzF1ImKSjkhBPHjmDrykW2+1fPnYTGWsrlirQzW2WDRhqRIRElVo4byjAfO/M7y3HaUBL3zGEut2vvV6Sy3k+Mj6NID7udYhE6JlLyxGwysn0Rj0lIaURd2ew5ePiY03NHTsY0Hp6ekqYACg+PuANYVmYGm6u4u0n9rhQceV7GPUrQSOG5hZQvxKRB7+PowQM4F/4pkrwdJY0lQ10P1g7ppSVBJE6a+/VLSEvPQDmratdkUUNlN4H099Jh2rtcu7MEkzdTLnn7eDNpMWX6s6yyTp7q8VyZS5MLH+GDQrtQvYjw2PwMznSXhwJH9oNQwpLCyeBnpL8mWT7CYzqOrVuBL/4zIj5L5zJopBGZDis8nqCR/d/6UXFmmB3iI5y80+GJTfHFbesXLBrOuiY9K2kub4QsB5Vm3knnTkcBjXuhQKECWJtlbRUogt6HqUlfVo626OBNZBrkB4wxRaXSefrtEefuS02eq2svIChV2l2GJ6BhDxaMqV1NCNBVrV5d4o8UYRcozo6jhvIsCyxmwy2pR4BZpcOqWjtt91uXBd4qehw6nRtu3bopWlEI0ni5qZh/UcyDKNR9qT2Kl4hky/nuZvYkxXPKI3dPbiDPl9ds3rTJts6vlo9sn5uYFRf0eCXhFwxJ6SdZzpfAOUMpT1PIr5CKaOPGjfjkk08cFAs0Ge3ZsycrW5X7blOpKB23AgKk7b6pHI2CutWrV8eECRNypJhQUCCKWce2PN9/2AXnjjo2dLAn8+bJHCUFxerSHklCooJoH8hZKIgxiYy0CZX1d3D8wG6bPWAxjeCHZ9R4Iv7BXQd1anpaKkuq2tO0KjcYlvt95aR5CCV/QkNdB74Ucob4+Df5f+9i4YQhCAx4PlQ0TxLLczLuUYJGCs81TZo0xaXTxzDhi3dx9/pljPq4m4Pqg046ozpVwpt1iuHbDhVQL1KQ+RLdkxyluTXDteg7cip8i3BBqGumItIysOsfsuvQIOlAUVe8FtP9UtDoxPHjTve7dqYwWTtlKIUf0j5wWKdBw4YOyzx9fJFucbcZIfPUyRL6jgZ2+4tdXwnpId03awYqLFTawlTh0SCvmKvn5QMTj8KAlzhz9R51OJPtMF93FAmQTmgGpXyGoBTOR8fHx8/R9Pgp8cEHH7ByDnsiS5VF+QatcCNO2jlse3WpIpDQevsjwy1nJutbCjmWelD2dO41YeC4O6gPlgZ8DT8ZA2rCr05nXBgMbO51zxagiborqJoyNc7l7uUDuUzr9rDPJcvZANwoLWtLsEi9zcwqDTLdhHIBooPnVlyxdoThsYgyrGVCLAgO9IO3jx8zSTWZuNe/EyUtgeVp8sprGL1gLT4bPcOmeuC5n8yVJoyLlQaq7fkzs63NY42oHOhY/jh79mzm78L2V1EaKeRTqCSNvrfly8uXs9NyUiTyZaA8FCgnj6MePXpIPAzJnH7JkiXYvn07PvroI9YJaNCgQU/8fSg8H9irhWgMm2JNBDjFetzlu2/mlFSRQogIVssbHyeYfR2URuy2VTnkqxLGHiqLCTq1CiVLlpQ0XiF7BfLds6dNx+5Ozx1BQdmPCeb8NhtLlnDjXoVHg4KOFOyjseTxQwdw5sQxTBifffnii8yyZcvx0ksv4XkgTwSNpk+fzowBSfZWt25d5rHgjPnz5zsYCIrlcvyBhXxE6OBIUdGWLVuyk77Ci8fOnTuwatUqdntQj5a4cOIwDm1bJ1nnwKb/cPvyWVQq4g93rQYdqxZhRtli3kn6TnK/QNI+hBUuhu4tuKBRv+SvbY+96/kfxv7DKX4qFJJOCE1QQ23JQnBYIVy7egW///47y/J76JxnS35Jlze0vnvnjsP3/mSlQWga/xtSLIJ66kZoe+b9QlBnJVWZrvAfBlwIlrYm5yeORYpIA2AKjwYpuIqEF3vspWFhfh7se1q5iD+7HtCyDDse2ptlhz7YYGsN/yx9jcSdv3gsGh3SG3+Oj1ZJFTEmjXSgSpQp7ImUhp8+9Ovbe/OEax6wjops2/fmwSfjBrYEfixZJyIQzFvMnMZ5G61ds9pmiHv21AnJuh96rrDd/rJaOishDHNzVFdNOeY6aEImpsTpcM6XiKd9qRR2/emoaez6wb1b+DqlP1MDtW9QFPpxwOfV7kCj0bKOdHv37sO0KZMwdPoSm1l2v4ZA+WK+iNYVQNHSFVCtQXOUq1yN+as1bteVreemBRrH58y08Y8MruyN+LElV8YnnjjThPjMGS5gqgSLFJzRsGFD1g3naV3o9R6G7L7D4s5CNLGiMjV6zq+//ipZ74svvkCzZs1QpUoVfPzxx/jpp59YiSjvl6ag4IpSJUtJ7vv5B9gaRjjDC5kORsYPg8FLvhPs7HSuMQQfFOJRu3FjUS0EJZ1R48XGQxT8WjB/nm15ZkYG3njjDYdtpxV9xenvr0GDBtnuc9GiRVGihHMbCoXcB45obk3fJboozW9c061bV4kXVH7mmQeNSNJLJ9Bvv/2WGQdWrVoVrVu3djAgFUMZG7GB4M2bIsk+gPHjx2Pq1KnMpJBaPlKtOG3TVXmEwvNLhw4d2GCsZCnuRLvwJ6FdfVpKEn4Z8Rk2LBVOXMS9m1fhc/eg7f4OfS18lDQE141chyc3Uwo8s6KQoQ1ik7ZLJsFjqMqtefh3zUZ2W61W4cMGQhBmenp3aE1CiQypL0JCQpjXEU//5P+xbcaYA9A1YbzNyyg7pv+xHA+0xRBjliqliAoFyONpFO7f5yTCyZlcSZCc7DQykittUXh8ULCOar+fBmSW3a+5MKicd4kbtHn5+j/ToBGZXTtgNdrMCWldHl/3CfL4ElPr2nfoeLQpSmnvoKb2nMP6d24ISQdS8pCPSUhDaTB3gPef6OazD7/5jUTLMz3gaYiFymJkJXBiLiU6nnZXZLZArJmTeBuo653RxBRHNEamS5LZG3/14krVupWOQ7OSwMyuwJJMrgyvZcJMdv11Cy44SN4QY3/kygoKFYvEwj1XMez1MpjWGUjv8ReOpwdi0mbOmym0YGFMnDgRGWlc6WKQF3DHnDP/By+VcCy7YfXXX758uey6SnmagjNIXXDu3LmndpFTM7iiVKlSLCBPRvFy0PLQ0FBbCRofMKKxKXkc2XdKtYeSpVSeRs01FBSyY9SokQgtKCiGzGaLTdHjjHSVp62j66NwNVP++VdNRR3K0yLLVYZXWS6oIx4jXw/rArPZ5FAqFx8Xy8o17QkpUBRt2rZlvxN7lPOJgsILFDT6+eefWekCtaWmDBAFeqi18ty5c50+h/lziAwEqV5VfACZPHkyhg0bhk6dOrFMzsKFC1nL03///fcpvSuFvAZlAKnj0D///IMylYWT0o2LXBbcR1SeQcwbNwRnF42SLNuob4DmCbMxKe1NfJH8BbKiTqDfJUfJofbVlXj55Zdt9z9pwvnKEFdN4fhqzR3Wbrv/D9PZ4HVUG+Ds/8ACUhQsWp3VlK1bO24RjhorSLZdRC1fbkKM2eLocfSTr6CuoN8EP6glD4VGjRo5DXAoPF4sFjMSYpz/7R434jK1NVlc55GgsEI4dYorVXucVK1aTVZFZD+oExtK2/CVlmE9LB95Lsef/t/keP0sOP+O9/VyDHpYjk6xtbEvHB6BPXv3wb2i8NvfE/QuvFRZ6JnwI1q5c0rZyAd/s4zr4oCh8M/mJ/VlyhdoHT8dRosaLS72xferz6HT0ebMjPTD5KGoGrcUG7LqY+47AdBeW4ltHwO9k76XbGN6+msswGSyqFh5GgW3CA8vb9YR8bVGRSWtkxPSuTJdo9VXgkwtyVt7Tnon2X30Fbdos0LvmScujfs7k7dS30/6MVWw5DNUytMU8imUJW7VqhVmzJjBOleJoUTM4sWL8c4770gCRqRup+ByTjLMJ06cYL/XR53QK7wY0BjNx1cIRKYkJdg6j2aHsy5i937/JNvnVopdhZhMeVX8JlFyky9PG2JVuRKbs4SAj0HrD5PRmOOmK75+fli/bh1T59mjnE8UFF6QoBEpHairBJWP2XZIrWb39+/f7/R5ZOYaERHBjI4pMMS3ESauX7/OTuLibVJHC4pQO9smqVAoCy6+KDyfVKtWDUf3bMP+TVwA8dKpoyhTtiybWPGkp6Xg3LED7HZrf8G8j2dK+ptYmdUCXx8viutZjvXULVq0cAhYpV3YI1lG7bZNOm9UMO7GMOtXlQJS2bE4YJjtttpL6pdEE0N7vEVKADFfffWV7ACVMp35rZVlfqBsufLIzHAeWHkSlNAI/jsmswVFSlfCzVu3H+trkBn7qVMnXRps8z5KBw46lh2bm/R95H3wddfgG5/58JH5rrc9LTVrFvNXw6uyy4tqhOAeBXGIhHPrbAHXOzevY+G/G+yew5VkFfUTShDdjIlQW4wssDK6mSde8T3h9O9DxFkC8L3mR4f94ZWGHycPxdspY9AzaTQGp36GXYaakvUmpPVmQaZZpzKxJ84Tbm7uqFq/Geu8RlxVl0bDeKmiki03BaLw+7+iyRufwjeyqqx/GjGoTTlUKixVTNDnc9+dO170rAFUrNWQKSZm/jqDJYKIiEhO9aYEjRTyM9QFjcaKpFqnLoRUorphwwYWTCpTpgyzRKCAUbdu3XDkyBEWSKLgLY1H6cIre2kcSonNkydP4tq1a2y9gQMHolevXggMzJlnm4KCGPqeaXOg2q1Zs6YtmWCPxZC9Erog7jsNGkk3xp0HxeNqvhRcvM98WdP/Bg12uTmx557DSynnEwWFFyNoRN1W6MAhVgoRdJ8vo7GH2piSCum///7DokWLmOSdalrvWP1d+OflZpvUxpgCS/yF77ql8PzBt92cNuJzpCUnYfnsnxBetCgMolKt+GjBXyXl3lV83Tb7IAr5kJQO84Fm7QiH1rlUt21KtdZuiDitD2ElJjmlh8d6uEPYz+Ldv8G3331r8wzRhEnr3PluTey1Qjlj7uygYGxOulEo5A7yXYuPlj/+PCn6lBOCKOdv34e3rz8uXHTsfPIo8ObWrrw4qPMQkSEqD969ezd2Xcz+8zgS3DPbdSZW5cqsCmocu3fd9eVUVvZUCw+ARSWf5YwUBXOOGCogy6JFtQLc++vQ8wO88clgFHmfKwezJ1RkF1Hh7mwWNCLMKi3Udl3TCqi5jmVi/nggVRbac8XE+Un8nSkoGeWgDnSUTGnQujNSMjklUf8bUmNrN60aC/ffgGeDt6ELDsea+17w7zpadnslQrxZW+Y360ZwXk0G7hg5Ku1D1LszkSkkMy1u+F8LLTsvi6FSOZowP25PLwWFp0np0qVx+PBhVr5NSiI6V7Zt25YFjEgxTN4ed+/eZR6KNB6lBBX5avKXffv22VQiZILdtGlTVKxYEaNHj2ZBIzKNV1DIKfZBeJU++86oZMDujJx8/24l6+Cnyt7mQwXuWH8+SkjA62Bg58H9pSey++LytNE/SFX9uSGnaiUFBYXnoDwtt9SvXx9vv/02OyHTSXflypWslnzWrFkPvc1vvvmGlR7wF8ogKTy/k3e+lObDl6tw1x9+iDWLZ9u6qlnMFhQqVJgFJjcvXwh9YjSGtJPvmsLjqTHj3YYloNKnyZ7Ukg87tua+JTrHnzNmb9I32HsBCoommqYCFfGBaSQOjqmFBQsWyD7nbc+17LpyRdf7r/BkqVC2DG5devwd1FyhKiZIuRPuXYRfYDDU2fge5JYTJ0+z63KlIjB/7u+y61A5B6ngxC2lmzRpgnfnH3VYt4O70GqeCFEnoYqWCwrJ4aZRI0DDKZn8VI6/PU+tNFBDJuEfNYlE1xqc/4JZ5hQozoi+kfQjysb+C7NFBQ8t+QVpUbWBVEkoZv5h6X2difuRW1QalPaQBrX6ey3FkyQjMwPrMkpi7PoL+GmTY7BQbzTjwn3OXFuO6uGCkrF7LSGRQkHlaJ1jB5456a+id9hOB98XL79ApsJQlEYK+R1q2EJll5SApCAofa83bdpkK/ulx+n7LXfhS2tq1KiBAwcOMH85OjaSxxKNQZWycIXcQIpXKvEymYzw9fWD292jMNwVqi6ImFUTJPedqYyInJRG3glrgYtbsu9C5pPJWSVEkXmmlW4eW7G0wSVcL/Aaux8fE+004HPdwnWGzQ6qLKE5oYKCwgsQNCIDYJInUucWMXSfV4RkB6k4yDiNz3jzz8vNNulkTUaF4ovC8wt5ZjVrzk38atSqzQZ6RO9GpVjg6OueL6Nx02YsGBl7/y4Obl0LH3ct61BVu7i8fLx7CeeTL5pkGZPkjd0zLVzHiwcmR/Nqe+Iy3VHlJ+kys28B9KmZZfNTsIc6RDH8BF8lhadPtapV8OD2dayaP+2pTZrV7sJxbP39YGh1bhJF3eOAyjF83YGbQ4EalwfKrkNqUr+AILauGJ3a8XP4xGuZw7Jf/MbjY09h+RTf8fjWexYqFvbDsPblEZbEGdZ7qAzwu7VN8lwPNzc0CeVUQg1LBjOT8IhgTjVDnA3vn6P3ud9QBRQ3DgsvgWKlpMrDFQFf2W5/u0n++QaND1733CxZ1tDtJPo5CRyFB8r7Tsgx0kfamclG919sN+PScv9371qzKMoU8EHJUG/4UsRMRGSCY8BvYvrbstu5ePoYxo0bpxhhKzx3fP/996zpCgWBFCWdwtOkXIVKMBj0TMnp6eWJE7s3w7Kd66zJk35xT46DRnqh4ZlTfDLvIe6AYwLUnoq3Z8A34xoz6OZp7HGaJU949m5eY5tr2QePNqJ79jtjDdIqyngFhRckaEReL1Rju3XrVtsyOvHS/ZxGj2lCcvr0aSb/JaitIgWHxNskjyLqoqZEpBV4tm7hJnD+vj7MLJ0nKT7WdnKlTn6ETpQB7FStCD5oVAJnQ7rhYsirGO8zBe97/oMmRbgBo6sTWGDqNYdl5WL/QarZE6PS3pd9TvvEJTjm0wk3Qttj4p12uJFArVOFsqNocxAzvzVMEH7K1Db8u3aR2B0qmhBrlSzms4SOS7vW/4OlMycg6pbj9+BJQAO0IlqhLNLvxgJ8Xsq5Vxwxd948TJkyJcevkZmViTeqcWVZVUJSbF4GYkhh5Obu4RA0quXNdXLzcwM67GnPvuOlNYKZOx9QidDcx9c+C1hw5mvveejgvhvveq1Gz7oR0KrVKBHD+ZOZoMXpv37G7alvQmdMR9viGlY26pd+lwV8X6nCdT4Uc7mQfPmbr0oq9X8raSRW9AZ8/Dj1jTGG63L0q98Y1NQJ3dFuJQBFZZT2el0gtpx0LJ/7n/cf2F96PD5qLFUa9m3mWGoqR4gqAfV1j9/cvL37bqhVKrzToAT6NIpkt8X4p3Pl4K4oVKwEXu72NirU5M67itJI4XmEvLsGDBjgckKuoPAkVPPUkZWOpyGhnEoo6q5dlYRZGglyNT4t4pd923Tdrf0O5/iKWi5hL8bNlIzaV4YiJVNQ7fpppftSsnRZW6c02i9x1810dfZJVAUFhafPMz/LffHFF/jtt99YeQ3J2vv27cvKh3gTTSpFI+kuz8iRI5kcmAwEjx07xswDqa3p+++/bzv40An8hx9+YLXlFFCibRQuXBivvvrqM3ufCnkLGuCRESWVNdLJl4KVrdu1x/KZnJzXTathiqQmzZrbJorseSoVSoT6wFuVCXeVEd09N2OYz+84l1YwW8+aYve247+AgZjvP0KyvFLcMlwzCeUf10PaY6H/cMzz+w6VSxRE3T9KYXH9y7iTrEGWEXjP6z/but0SJ6BK3FKMShXMa4tqouHu5o5Us8gYUWYyr/B0VZX2gcmnQQ9fodxrXHIPlAvJAu5La6iOHz+OPXu4jOSvv/7Ksuc5JSY6BrM5tTmj//tvygaN3N09kJaewX5nfNDgzE1OfVcs0BNu1kTj7VThO9vWjfMA4aHgzMdeK6BWCUGHOpcH2W6bGo5h1+aMZBQ4tQBvlPeEh7s7ju/Z4nT/M90K4IF/PYflKRaRORErY9OgX/JgrIwvjCH/nIY2lFPuuUEIhN3mYmC4mwSIVPk23DLuY3sg5y1WSM0ZZxMHS41FRIgPhr1SHu2rFGIldETTMkKnM2eQ0b0hoh3m+n2HnNLSjTP5d8UFdSWXj9++7jhRIPYZa9huD5m2BL2/GoWPhv+EQoWLsKyze3glpGTlIKWtoKCgoOAUOo9+2a0prpw9Djd3dwwa/HW2z3EV2LRPDPzpP8RhHblR5GifGbbbxw1lbLcLJu3DkZtCx9RA0z2X+0aeYDnZTwUFhWfHM/9lvv7665g4cSKrDSefImo9Sh0peCNr6s4TFSUYE1Pb5g8++ADly5dHu3btmIqIDAYrVBAMRAcNGoT+/fszr5ratWuzzj60TQoOKCjwkMKIzC35YGOJiAjsWreC3f/xx7HsuvXLL7MSNTG71/6NV0T2LZuKT8HkEV9i/sThMOilagoxN69dR1H9ZTRzO+Zyv+jcXV97CvHRSej16XfQubnjzo3rWLNkPgwmqVEvkWLxxoJMweTWQ6WHBRomWxZWyl4ZoPDkIPUj71mx/Z/F+HuGY5esJ0H7MOHYSbxDbdoX15Eso8Hm62+8wTr6HDl8mB1jL11y7iMkJj7dgHYJUzA4pT9izAHYvkkIaIqDRj5+/vhv5XJ8+/33+GXadLb81uVz7Nqs1kFnPRNR1dgU3wn4ymshKunku5vx+KddRKkHQnmXW9U+ttt7N69lkveVK5Zh36ZVLrezp+x0bK+4MNv3ujarscOyWDMXUL5csCe6/yEs93Z3zOieuAeU0N7D6vJLsDtIUBZmunFZYi83LRqUDGEldESrCgVsvk2eOvkscMeC93Aq4gvU8buPf8N/xnDfudm+j+99svf/+y7SsdOdmKN7t8Pr+GKH5W8mjITGNwR1WrRDYCi3/yEFi8BkMuNUkg4F3/wR/dZIv5MKCgoKCrlDn5WFtJQkxNy7DY1ag7RUziKBkg/E/cVcRzJfdy4jE/3PaOahldMOZQ3cHBWsFuuU0cPCbaeIOho3TYLtR5RZmuioUUywczD5RLhUPXl6CiXZStBIQSFvkids5z/99FN2kWPHjh2S+5MmTWIXV9DBiBRJdFFQyCkVK3BeJX/99Zet3LFihfJYu32OZL34+7ex7jywvcY2LFm2HFtnzcDVyxeB86fxzrvvOd3+5MmTULRVc2T8CFbeVjFWkOPy7LROJl+eZUKdbl3R1dubTbonfiVsN+bkbiDyS6evc/IendwBH7OQ5YG3o3GtwtOFzCoLF/bBXmtgpfsn2WcGH5UHQdLuYRdNZNQKqBKv4WqcBcWKcd247t29yzr4iLubUVeg7NgX+gpgJCP3ktilr4HCBR0VL/T9LVqiFF55+xMk3TyJHTt3o8krXXFG78Yeb5z2N755hVv3eoo3OhUS1FGvLQTq1a2GL8tK29UTAelCWRjDI5CZ13fq1Mnmd1e0aDhiYgRVjxxZbiGIcmsqWdawqAZ772SviOnisQ3RfrVwuNQYHLjJBVEqV66Cq5FtUeb6OHZfr/HF5dNHbZ4R3uoMqCk6ZgHW1NgCs5r7HOQyv1RWR5C6SUyYOg4fea6AT61xMKk9sLrmDlaO2PX4yxglslcrpYnFFZOgcrsU8ioz+iY143ldDRysuRwbz93HgWtcGSMplqikL9xcEEKhoBR9Fiej6tGoAqYe2oES5asiWi1MDnzKN0aZypUkkwJff3/8e/QmUKgy4jMUpZGCgoLCo3D65HF2TclB8oZt3LgxyELo/caRcLu+B73vcKbYh4e1hG9oERiTHuDmzdZOt0edqQF5BSmP2tqh7V+8Bm1gURTVPIDRIkwjQ1RWua2VQC+drYxa7+F6DNqoUSObQIAUyTuvAk1LZvMhKCgoPFWUcK6CghVSsBHiLk+kRkqxlhNRpwrCbDKzttLNmzfHrBnTceXSBVuHlHlOOkgRdevWBV/iTeVtcjQZF406U4AdV4Fly/62qVRiozilUIGCBVE2PBDveMqrJ4KM91FvKlj26VSMl/BApHVWrvDM2LVrJ9asWWPrtCNRgj0h0t0KYm2g1Oz5qLE8cGAkSpUqhbVr1yLqfhRIyGKZyF2K+oOV++7atcvltuPtzJUpy3gvLgnRcVywkjpRHjlyhP2e1GoNtFo35mukUmvQ9YMv4VuD+076m4SyzhuxBrRdUQopmhAc0TTD8lPAV785BoyIhhft2gerVOw3xhMcHIwZM6bn2kcn1rc6Wtcoh7frR2BQ67III6dvJ+hUJoQlH8ESq3KscJGi2L17F4IaDcTQ9fT5h2F/mcn47oMu0Ft/+xqzHmoLdydLF5yjfSrgKez/nAKzcSi4N/p4rbIFnCxqHaCi07kKDXXc51VJewVbgt7B7mLD0dV9C3YHvccCRsc82zE1YwXjMZRI2YGOVYtgXMeSzFOqhfsRNHc/Cu8s56UEpw/uZtfDhw/DiNbFUc4oVYQFNO+Dui+1lyzLzMxASkr2LaEVFBQUFLKHt+2gcalKrWZVGzOmc0bY4oC9h07DAkY5OQ9aTMLY1x7qYuoTxTWdCPEGSmnvsOYTPmpBveQlGtdmaQOw9QJXgh5rCZSYYHM7Kb1L6iK+WVG5cuVw0FnWQkFB4ZmhBI0UFKxQ+RD5HHXp0sW2jE5iD+5yZ6+3G5VEz3oROLhjI5uQ5hYqj5xmLc0h3vXkFCdfe8xm18PblMKteDMOW70Mv/qSUxOVKimkW+7cvo1GXT7FcG+p+omnVsp6Fpga2LUxjp67KTygzt7kUOHJQiW1VEZL18TaxdmXCeUGUoDYDwrvBzZGRe11FhDgmZveCRnXOTVPSkoKYmPjMVAkSFoyqDa7btpUqr6x55dVgiKIJ7X7ItSZsA/frTrLyt2oPPjoqbO4Vqg5og1c0MhoMEBjTrM9Z6++mu12bFwi4i2hGOc2DSvU70vUc66Y5/0zuxb/LiMjI22KQWpL7Iy71y/h+oXTrEQtzqcyjkR+D61GjXIF/RDg5YYBLV0rrtLci2D1Qq6DmcFogL+/Pzy9fTBmK+D9WTQ69uJ8l3ilUdG4jbbnmlRcJjY7LswfApUxCx2rFsZtN8E3yKKyFwurMNVvPGb7jcKqAE45Fp5xHD/5TUa4hhvAfz9jnW3t2leHo9KtKXh9P/edFPbLeaBMo9Xg/+3dB1hTZxcH8MMURAUEFRFRcVPcW+vEXbd+auvW4m7dVq17oW2d1Tpq1dq6raPuVfceteLCiRtQEBCQne85b7jZgYBgAvx/zxOzbsLN9SZ5c+455x2ZnJXGPaNCg17S1xqNvPMXVJ+p9G1wMD6DAAAySLNmzRTfbZxpZEjDa544KCWhR+Tj0y/N5TOkfZN7i+K+WXlWiCxU1jf55osqQ0wWrtILMMFC5aAlEYWFqWS+p4JLyzFdAoDpQdAIQAVnFnEDbNU66+DAV3Rgkzyww54/fiBm/ksr/iIfNmwoJbbbQy/CiKbl+VX8mK8X+Tc9nd+G+jcso1YeNGjQoOR1kK8PT0/KX6bm1UbQH1eTqMnpzlp/4/guZU+ZZWeJ7r13prCqKNM0Jfx/WLpsOdryy/wMzTbq17Cs1sxs2kEFogNxn9Od5AaVPElAAdsYquamvL9sbsN6zsiC/9N73/rzAXQmwomKfbePFj8vSrF2hehYsC0lxsdSQmIC5Qr3VyybqPI1xLOwVateQ8wKoxroSekAaVySOTm6lFCbupfLmvn9Jg2mOVClz8Yls2jZlOH02rEhHa68j0LzymdNNNSueOUEC2+CgrT6M0S8CxHn3MSeWciUGVr6StM0RQT4UcCCzlTbw4kem5cn75VEdf8oRuvmqzcrtY0LJCfzCGqe65Jaw3DV2d24L5rELvYlVXwmD7hpzn6jz4eoSMqV3B+wTJnSFBr8ijyc84gSBFbO4onWY2JjPpC5FXoKAgBkBKlH4h+LZiiy4DV7AvEBDFWtWrVK8TmrOsSJ2UdH2clLrYerBI3iVbqZ7L9L1PAXorYaLfSmxI3X6n8k+e+y+sytKWU9cWk5JtkEMD0IGgEYYOPSOTRu3DiaMmWqyJ5o0qRJup/LonQ7KjqbqNEKoqP3iTr/TrRz5y7xI/e75BkwuL5b8+iR1KjQ3Mae+m0l6u2rzFhgX+e9To/fJIjSOZZo7UDlpr8hh8ZT0r2ukDnat++QajAjLaTg09nkRu48IJNuO11uFUXmcqN6bspBn71jXlrbjURZmt/QEOqqEidxTnxB3h17pvo3S9rI+xc0sdbdNPmhlXr2CevgfodyFS5Bs+/JZx9jq/LNUVwOjstHNja5RPDr+SNlYOl4pLzsbIX6hGrC7UCZoqG92BZJSYosqSJFipCNjS0lJujfzvx/EBURnuJrLWIp7/nD9jqMEA1AjznJy/78A7WzmHjQzjOCsipVq4nzGSu0m4QnmevP6NHlfVgoBT5/Qg9i3enCf0/p2C71ZtSheeQ9kPSZFzqYPEqVSvXvhNrJZ3DTJfLdW7JJDppXq1aNLhzbTzfOHadxdvJm4vcStf/fmU2xiqn+XQAASJ00WRB7cF/5XamaacSTWqiqW7duis+5Zs2vYvbR+ER5xMaaGxYmi5OpZ8Wefkz0NoooorAyEOWQKM9mZW8T1QNWCUmGl4nzwZ/l5/i7nOhWkjITGQCMC0EjgFR4eVVQpPbOnDmDLl9OeWYhQyxYuEg0+mu+mqh2q17UsWMHxaxtqn1Z2OZNfyimRlc9EtNIpXyo87PvKW+efOJyjx49yKWwKzmpTPMOpuXH+b5UuVoNSkhQ7wuUXh+i5f1i9vwuTy8/uGk1zfDpKC6/cG5Jf9c4R82qcKNLuW8ixlO/GkSOyoQYhSQyp37jZ1Mxj5S7UN4ieWAhv1nKARdVgZZF6Xnp7mq32ZsrS9VGjp9M1SpXon92baQty30VU/GOWXWBKi4gGsFxlxrKo5ls8K5cipI/zdR8vly6XDmRHaOfjN6Hv6PpX8u3ly6jGrqSBSXSYNvtVMHqEZ1z6k+lzOUZNZbWNoq/2aKFstFo8eLFqWChQlSxgnz6+jyu6tPYc4NsQxUsVJhsbHPT+C+9aY3vBKpZU15CyFQDXkkplJX9+86JBg8eQlFJyhICfZ4WkDcT14UzwKQG6nZ2duL8xzH9afu/ysDc4zfq2/vnfR//mQkAAKSWVcukmdMk0veR6ndhmzZtDH5OWXxs8uOV9zmZh5ONjmrqt1VmKy5fj1MevJkf3kVx2cPiBTnYEMXHxioO7JiLHnz61+NFONFC2Rxy7qkspwYA40LQCCAVw4cPE+djknsMZYTRo0ZSkSJu4sjPhg3q031fvHhR7Tp/wbICBZTTmcbFyYMNfZMOUJMz/6M1u/4T/Ze++VbeHNgpf36KjdHdbBtMg5WVtVZaeXrx89Su+7m4fPyvDWKw+PCOevmYtaXy4/5uogetjO5MpZzlpV+aBwD58eHv3qk1hde09Yk8SPkvN9Y2kG+U/tkFmVWYv5i17WWAchaXPn36iNGr3+vk0qq6M+h2cu/sxSHdKNSqeIpT9PL7jBvDq1Ld7tY28sjZg1vXFdlZmkdEzW0c6FGB9jQhjzx7SFV8QhL9/PPPIjNQel+yBg0a0OtXrxR9lRySS+iUdPed0HTz0imKjo6imA/RFPFOnvHk7e0tzr0qVqbQN8pG4nfcBisuv9d4+y+96ymCzT8tWpLi3zvutZECHeT7ki5hb4MUJbyqP0ocQ5UNy9ecfUJJKtvQPn9BxWUPC/X/C4Cs4vnz59S/f39ydXUVJerFihWjESNGUEiIvARVek/oOv34449qAWXN++fNkzfTB0hr0KhqVWWfO6Yro2fFCnnfvZRI2e0WKl+nG+yn0Pw8S6is5VORmazJzEY5c6aqGFkutQNRefIXoplft6UpvVrQ1N4tqYhbkVRfW59+PuSS/P0JAMaHoBFAKniQ+PLlSzFQzEiLlyymKVNSLx3r0uV/olxNl2btv6J15z9QRAyJJstLl8h/EJb3LC+mGwcTZibvD5MROAjCP2IqVqxEV04ekk/proO3h7KvzLyofjS5Xz0q8XafOK2Jlme7mZM8SOnqXlwxBW6ZsmXp9m35FL6abMxiqMqduYrrV5zUS9va5Tpp+AuxcRQlZRLep3195RlHCpY25PUTkdlYolG+W8XshSkpUbwYhSfPgMg4MMRN7V89lc/6ZW/voLjvbdBLcd6zTnF6Gyi/zGJSmOWMZ4njJvelSpdW9JmQcDBr2LBhdOjQYa3mpCn1DVI1f0RvinyvviyXyPIsfDxNMpes8Y+E29fO0xv7mrS7+nnqFfAd5ZtMVNKXKCae6GyphXT/XW4RNHJyKab3b13xmElBHDDS00iVyRLi1Pq+Scw+qE+3PGvfHXrxLlpctkxQZkO9SdL9IwPAlD1+/JiqV69ODx48oM2bN9PDhw9p5cqVdPz4capTpw6FhsoDuvyZqXpau3ateO937qzeg3DmzJlqy33zjfoslwCGBo2436WqDx+UM5qxRYsXqx10TO05VYNGDaz/pW62R8XlVSvks7OpUm2jULpgHvIv3Edclppms29zb6Ymbb6ixw/86dH9u/T4wT06cUz+nLpI35UODsrvZgAwPgSNAFLBP7QyOmDEunTuTC1btkx1uV9Xr9I7/Xm9evXo1Cn5LFZ81FPyy/LltH37tgxcW8hopTxK0NQB+suA0iIhPo4sraxo3bq1ZGlhQa+SM3U0jzgmWajXo/0Zr+xHMDvqa5oTKc8Eso5/R47OhSgwMFAERR7cv09eXl7iSLumYbm3Uxm7WHri3EY0di9gHkYHHYeL+9zNX9PSfD/RLofRKa7/hP1EF1/bEVUbpTZQLFGihKKXF/dnuH//vuIHl6HcirhRbIw8eMHW/iBvHh0XIx9YO+RXBoSObFtPC8b0E5elgB7PSndkh3aGkSQxPkE0vt6+bRstSQ7aqv19Nzdq0aK5zsee/HtzquvvXFDZu4KdP39e/HitUKECOTk70Zxh3UXj8LnDvqTwkDfUs20r2r5Gvh6PQ4gqrC9P9TuMpof3bsl/FOQrRn88LkWbg9XLYJustqaanaamuj78W0D1/4j7vLGmLVqrLRabkES/nHxES47fJ5to5X4Tq3IEGiCr4OAvB+aPHDkieqZxiSY3Fj527Jg4qPT999+L5TjjV/W0Z88eaty4sZjNURV/rqkuJ5V6Ahg6LpVwCbcqKYApGTlihNYBDV2kANCuAN3jXScHZZ+i5cuXKx4TcfVvcbmIgy09LdBOXC5FymzhTjYnyCLK8AxTqYG36msEAOND0AjAxEnp6/qULFlS62gTH1XiH6tguup/Xk9kiYzsWI+CXz5L9/NER72n/y6eEgOsggUL0r8XT1Pg47uUz8GBXgY8UFvWwU49aHQuXr3J5K8fOlGMzJoqPFtEX7n5Ee1uSwWclAGCA0eOU/EJ+8VJ4m4eSE16z1BLTilvGSCCSKedfMT1KlbyYI+mmXnkKfPzTxB131mIG/8oZh5r4u1Ns2cr+yVwoEJqeN2vnzyww7g0LCXW1lb05uVTRanniT1b1AJqUknalz160ZEdG+j6uX/E9Z2/LRbnoUGv6fcF02mz/UwatpNjJurvxbehoeL9xkEcLq1LSYybMkh8KMCBfp0rb3yfEucC6kGj2rVrKy4nJcqzwu7/d1Wc/73hF4p6Hy5KUx89eiT6sEUnB7+CX78U+wd7WfRrOmn9PzpfZpEoY6uxhOjEfXlpXWrNSrmnkepRbu7zxsLeR9N9Z+VMcpKgiFi6fvmI4noBc8OnXgYwBfwj/PDhwzR06FC1mREZB3y4j+DWrVu13jtBQUG0f/9+GjBggNZzcjmak5MTValSRZSupVQKDKBJ+gxet24dzZ8/P8VMI0NxxiybdVDee0hLknwf7dq1q9hvFY+Ryb+HkrjUPfln5cskeWZTbkpeF3PDA0Cq3y8AYDoQNALI4rhniuqPaMgahgyW95958/oFbfpZGRxJqxeP/GndD9/TscMHFVk5fv/doIiwMPruy2b01+qfFMvWKOFEDjYpf+yXe7uT/nkUST5er6lG/iD6ojxRQdei1KR9d9rH2UAalp+MpHr1lU3ZJZpxThdzZYkYO+E4kHrb7qf99+UD1TdB8t48UoC0zRdfUOXKumdOkQKixYoXp+HD5VlN+pT0UPYS2rFK2Vdk2gB5gCMpKVH8gCtV0kNtlrXL/8gbcP4wWp5uv/3CG/rlvHravbh95yERnDGETe2xissLnzdLcdn1P3yvCCbeuKHsF6QaQM6bR14m5vttD3F+aKtyDmTObODyuFcv5Ed4OVtStaws+OVTqtduFJVY6kJNe05UZHFFqJTyGRI0kiQ4VyNrswT6x3Gg1n0XY5RN2BNIR2MMABPGJWkcEFJtuK+Kb+dMyDdv3qjdzjMo8mdyp06d1G7/9ttvacuWLXTixAkaNGgQzZ07l8aPV2/wD5AS/iwfMWIk9e3bV3HgULMPZlpxhk88zyYal0Sjkif7HL9PZYEi9cQZf/5HRcknsODApyw5aCSCpskNrvfHNhDn0ZQcZE1exhAIGgGYJrwzAbI4/mHIfRMg69mw4Q/q3bsX5bHPn+7n4AFig4YNRT8rHvQ9eSKf1Uuyc+3P1HHAKDJPTj0f30o+69mkXX56n3N+VD9x4nKz/LmJ8lu6kEf5CnQ0UkcvmzzFRHr8lENEs1KotjzsOIwqhWxVXC9h+Yr2+OemZ16+5OAwjUppTAWfWmr65KlTqWH9+pQazgyICAulAU08KSY6Si34Ic4TEkXPsH9VAjMSLlELeiHPUtq1Vp7R9CreiVyt5I1vnzpxed9Bik2eFSZVxbyp9HI3evjkBYebUlz06M4/ye/KOcpjZ0ufffYZ+QwcRN27dVVbxlGj58OQIUNEw9Pynp6K27j/ypdffkk9eyp7TdnZ5abHt28oShu7de0qsriat25DUZERZO+kv/8FZzdpDur5h4a4bcEC8rB8pfWYaJmyl1ZxG/WZfgC4zFpzevDM5OjoSOfOnUvz41LLwuPyNVX8vcxZSFIGh2T0aGW5bsWKFcXjOHjE/dsMKSMC4M/bxYsX6bwvvUEj6XnNzS1o8RmiA/eI7r8hWnOJqEAeIv8xpalps2ZUqVIltfdCyZKliA818C1SppGWeGWJeGpU+yQBgOlA0AgAwEh69epJzs5O1Lp1a/py+ESyy6vsGWAIbtZ86/IZ8vT0EgM5aWYetnXbNipXtqy4/emDO7Rq5miat0nZfHKz1zH68lZTcXmq3WqaG9WfEjS+EmJllvRb1wS6mdeVNr6MJdKIjfyabyadSy6f2n1LO2gUVOUHio0MoZjLS8nOXBmwmZ5npThvW9OVqP9w6tmrl9YPrtSCRrNmyMuiDDki++SenyJg5O3dlMaMGU09e/UWA1/ONOKBcvly5RSP2bVrF3Xr1p2unlaWVUlWPfSkGeXPiMtbP/C0wgdFiYqhrPNwgPCFCO7MnjtPrIO+8tPA50/Io3Q5MYhevUq+zVT17t2b/Pz8aPv27aLfFGcdcgDsq6++UizTvXt36tatm9rj+IdqwAP59gt/F6oIAllb56LIcP0/3nldj+3dQRazJqvdrhlEOpN/AHUL86VXScnlcEnKErsx7bSz0iBnS08A51PigDa/R+/evUsdO3bUup9v5xJV1V5fZ86cIX9/f1G2lppatWqJ8rSAgADR3B7gYxia+Zpa0IYDRsy9TCX67z/5bKwH9u8Xn/dHjyrHEtK3F8+YKdP4LitmnnwQoXjzNP99ADAtKE8DADAinpqdPb1/R+3oHZetpXbEcM/6ZbRr7VJ6+jRA676u//ufCA6wF08e0PPH6n2FLtp2oqfz24iT09ODdMVduzyiasgm2h7jTe0e+9CzJOXR8pIWz0XPoma5LlMhV/ksfcs2HVPc3+VAJXrmfYQKNRlHRb6YQ2XnfCC3WUQHHL+hZXnnUV9bec67efudIlOOj/xrNoLVbBybXtxr6PFdZVbVkSOHRQNbF1c3io+NFRlHPEhVnbWNMx8cnZwpJJAzgojWr1+vuG+ffy76q9a/tKleAK1btYImTpwofvQZyjY562Dw4MH08vlTMVPbswd39S7PM83oCypx83tpKmUuE+DXoRow0tcXjbd1xLsQqlatmtog3d3NlfxvXNa/LndvGtQzo6hFEJ136k9r803Xuo8btQNkJfzeatasGf3yyy9a+z5PFrBx40ZRJqTqt99+E+8vKZifEi4/5c9BqecYwMf4mEwjxvtitRo1FddVD+jwwRz+LuHvHuk7U5qs9fyjELqVHGhyMJPP+Dk5zxr5DV7ySTYMERcn768HAKYFQSMAACPiH/DuxYqJWbCm9mtL21f9pGiQvXSSvO+RPrGR8qnMr1+/pneZmnXq0cvkgBE/r0S6zOUQX//tSF2OVKP1n7+k446DFMtEyXLTuPejxOUL8fIAFDviOEzRs6hJO3nZU7ESJanKQqJu2+xpx/Eb5F5Z3rNHBGSSexBtOPyEbJ6dpQo/ETnzpFsFKuhc53379pG3tzdlBM1pe3lAzJKSEuh9eCjFxcaKI6eqJST8f8Izkl0+to927NhBffr0oeDgYLFOcTFRFGuVXzRtev30UZp7kSxbuoSOHTsuLn87Ul6m8u5t0Ef9oOXyOM0GvYZsE6kXGs9Sx+rXqyv6OulbnwB/P/rsMy9FMFJLz6sU5txIcbWm1W21u60+hFA+W8yIY0jjZS5r4skN+P+KGylHRsobmusTExMjZvji/YHLRXmKd27ELOHApxQ81Dzxvs1Onjyp834OjOR0y5YtE++zFi1aiNlMObPv0KFDIpjEDfCnTlXOPBgRESGy/77++mut57lw4QItXrxYZG48fvxYBJxGjRolykc5eA5g7KBRWNg7Ck7+7GjWvDn973//o8FDhqotwxlxL1680OpXtPyGeklyXrNoehFhQWSlXdquT1q+ywDg00HQCADAyP7asUOcP77nR7vX/UyDW8pnJrly8nCKj4sKD6G//vqLfl+vf0r4yhW96MLRveLy2UO7FLdHR0aI4Mi2bdvo9i0/8r92lsLfvqaSli9TXV8LM+Ug0cOzuqIs7srTeFpx8LHW8lw2Jc2S1mw10bItJykkhRYHX3zxhSK487GkDBue+Ug1k8vNrSglxMfTzSvnxfpxo2huTsv9ebikLTTkLT195K8IXnH5Cc/UZu8g/2G3+ec5lNfeXisolRqe/czbu4m4XKdWDXEeFxsjzjlQxWI+GN7/gWmW9qVG6pvCDXxDQkIUATN+3Y/u/EfD2yiPMkt43Q78sYL++muHWkNtNYWqkUOfEzT3mjxLzM5MPSuj4M0/UXpgAA4Y3b59W5SAcACVgxQDB2o3GFfFgYe9e/eKYMWpU6fo1atXag2YuUTx9evXaicOgPD08ZoZLlxWpbocMmBI9Py6cuWKyIDk2aM404IzFjlgxOV1qtOe8+cIf9ZwLzFd7z2+n7c79yqbM2eO+L9bvXr1J35FkF19bNDIpZALPX8m7+W38c8/ady4cbTil+V6l4+xVi+r5xlY48haMfHB5oeuafr7+fPnF9/DAGBaEDQCADCy6tWra5U9cE+MkmXKKaaE17R3wwq6ceUiNWnShFq00N8vgKfGfRv4Qvzw+3PxTMXt108foYGDBlO7du3EfU2aNqO30fKvhIG2f+l9vrG5N+jtPcQZOzzg0xUUu3PnjuI6zygkzb7yKbRp206rF4mFpaXIqnFydqZChQqJwAv/sNbsz6MaFOIjoA/v+lFcTAzt27iaXugoC0wLDlSxR7dviP/nvg3KiMbbEe/eUuHk+zKDFGTiH7yq/1/8Wq+flWdBRb0Pp83L5opeWP9dOEm///g9Bb56YVDPlTA3ebCC43WT7H4Tl3vZ7qfEpMQMCwZmV9wfhzNY1qxZI8oeuUcVBys50MCBIF3Cw8NFOdTChQvF5wGXRfFU3OfPn6eLFy8q9l3uvSWdOHj3zz//6JwOnj8PVJfF/xkpAuOcscWZV/zDnLOLjhw5Qjdvyss2JRzgi46OFhMTaKpatar4PwkLCxOf+fy5yCWuaIANphI0qlZdfiCIGRLkD8+rnKGUvUlSfmeak4yeRuZL8zpgBjUA04N3JQCACeBsDy5/4B9oDx8+pHLlypGlhTkd3r6eWnUfIAIV1jY2oqlzbMwH2vLLPPE41SPcuuRNvp9/RHIGj+TKyYM076iy0bONrS09iS9Cb+Ly0KQ868jdIpAmRw4T9w213Ua/fOhK7uavaVjubWl+be7u7vJ1yZuX3r9/L4ITerNVMsHev5PnD9YIdnHzWX0zInH2gFtyWZ2Ef3gHvXxOTx/eIU+vCuTokLbG5ZqkqZL3/rGC3EvLp/P+EPWeln4/hIJevaIFCxbQEZWGoxmF9xl+/ZqvT8oIY4OaK2fIuXbmmAgiGapixcpEyZVRA3PvEqcEc1s6klQLmUap4PIlfn9wIFnStGlT8blw6dIlnY2Yr127Jo7M83IS/vzg9x0/H2e3adqwYYN4D3bpws3c1VWuXFl8Fnl5edH06dNFjy99eDnV2QO5NCunmDFjhggkcRCoZs2aCK6BSWjcuDFFf5Bnr6aH6me0IZ/XdomRFGWhHIf0C1f2sqtldYu2WuouQweArAXfcAAAJoIzQPgIG//gY4cO7BfZQb/5TqB+jcqKH/GT+7ahWYP/R7Vr11FOdW5AYILLIdiYLg3p+K4/ydrKShz1ljjnd6T7d29Tx2N16Nh9op62BymgQBua27ECjc+zQVw+7eSj6GXEHr1LW38aLoVS7aFjTJaWVrRl2Rx6/EC9Qbikbt26imCXhEvU2JtXz8ne3oHOnpHPopZenOEkWT71W3G++7dFFPTimWJq7oMHDlBG47JEXc1GuR9O/foNRM8V1WCaFDDavXu3Qc/frl1buhGiHlCzTPpAiUlJ+GGdCs5i0SwHkzL49PUW4tv5s0OzVJL3L32P4cwkbpqu2j+Eg4YrV64UJa98Klq0KDVq1IiuX7+ud315mnjOqJFO/JichPuCjRw5Evs1mAw+OPTL8mXpfvzOv+Tl8oYGjYrFyUvZJA8Tkw8SmUWJUvZH4ehRBJAd4FsOAMBE8VHs/3XtSif+3qLW+4YVKFjAoBRunr1nzZrfFLOTBb4IoLXzv6fgIPUfk5/XrUPbVy2khEQZ/fmmIW1/6Um7q58X9x2svE9kirCzT4iufyhPV54TyXr9m6bXw9ktixYt0jsb2KfE2+6/i6fpwYMHBj9G+mH4z65NdNvvZoasA/erUS1JnDN5vAjOPH0qH4h/ym3FgYnTp0/RiBEjaPSYMeK2Dh06qE09bghu4Hyr3BK120LtPEUJXk7NNJowYYLeRtTS6d69e59kXTj7iMvgNEvTuPRw0KBBoryNg6Zr164V5/ye1YdLq7g8Tjpxg2gAyLoSk0viOQhsSL+8t1bygyma3svsqN9WokIlkGkEkB2gPA0AwITxkf7t2+QlYevmfSfOjx8/rshGSg1nEgwYIJ/u9vvJU2jO7Fk6l6tRowblzZePLp06RtMPHhRNXmlRXVq88yyRawXaVvce9ahdTCwrkyn7E6UVH5U3BXdu3UxTIETSrHkLOnrkMHl6embIetSvX180I+fmuty/xlQs+OknWrhggehpwzOm3b59K02z2rgXL0EhAURO8lglJYQG0L+X7uTYoNGYMWO0pmXXxE2WeXtLs5lJuIySZ1Tj+3Th2zlzjPvkqGYb8expuh7D/ZK4BI2DQ6nhsquzZ8/qvZ978aAfD0D2w58nhsgt018KFxBK9BlmQwPIFhA0AgAwYVJ2i5+fH129epV8vuoimt2mx+xZM2nWzBmiB4ffrVtapVdHjxwR/U/4+RctXkITJ3xH21f9RGEhwWSdSz7D1qRJkyg7CHj8iNq0aZOu6YjZ2LFjM2xdeHp0xfTFJoSzoHiWqBUr3Ml33jy1crrUcD+c+dOJ5ie30dp7W96cNacGjfj9JZU3pqROnTrixxr3KZKCOtywmpvbcmNsXXg5zuLjYDLvS9IMaM+ePRPPpyoyMlIEKbmszBA3btxQ63UFAKCqRNIrCiD1Um5Joow+uvcfAJgGBI0AAExYh/btxRS4/COcTx+Ly2D4h6Tmj0nGP0qPHTsmUtJHjviW2nzRWkw1rWr27NmUHQQEBKSrGfeihYtoz57d1L59+wwNDBYpUoRMDWdBSSZOmJDmUrdZK/8m2ttOXH9vU5wWLPDR6rsD6sqXL08tW7YkHx8f0V+I+5YNHz6cunfvrpht7+XLl+Tt7S2aWXMmEJeRcKkZ98Di7c7lgd988414j2s2wd66davIXOrZs6fW3+ZeVtxvjKeCj4mJERlJHLDiGcIAIGfgMYK+CSJ0sTdTn/lVlaU5kddnn2XQmgGAMSFoBABgwri8pEOHjAtQpIZ/jEq4dGve/B/J67PyFBgcTOXKlDGJfkQZwZCsD13q1asrTpA6a+cyisur99+jPRPaZpv9JzNt3LhRBIr4vcgBRc4eWrp0qeJ+DiRxJhFP6y7hvkPSsjybWYsWLeiXX37R2QC7U6dOOoN3XOLGZXQclOKAasWKFUUQmWdjAoCcoWWrVqLnmaFSagIfEiWfGRYAsj4zWVrCyTkETxnLR+64qSMfsQMAAIC0m9k2L715F0nLznEvrMwZbuA723Sk9H/B2UtPnjwR2Uz4IQmmKqfvp/fv3xdlrKqzq6Zk7PgJtMNcmZUqKWAeShFretNPv/1Nbdu2zYQ1BYBPOX7C7GkAAACQKabufU9WteQzsQEAgGkrU6aMwQEjZmZuTlVsQ6lgXvWG+LscxlBsQs7tYweQ3SBoBAAAAJlm0sQJdP36dWOvBoDJOnnypCjdlGasWr9+Pfp/QZbA5Wnu1pE0sqmyHJm5WbyhsA8IGgFkFwgaAQAAQKZxdnamKlWqGHs1ANKtb9++IqgzePBgrfuGDRsm7uNlMkq3bt1EmRBAlmicnaS79JgzjVLqeQQAWQfeyQAAAAAAKShatCht2bKFPnz4oNb/ZtOmTeTurnvK8fSytbWlggULZuhzAmQGDgrJZElqt+WiWHEenyTvmQIAWR+CRgAAAADwaXFj9Pgo45zS0ZSd+7xw4Gjnzp2K2/gyB4xUM+mSkpLI19dXNFLm4E+lSpVox44das914MAB0TuG7+fZ6QICAtTu1yxPe/ToEbVv354KFSpEefLkoRo1aoiZ7VQVL16c5s6dS/3796e8efOK9Vq9enWaXydA2oNG6u8nO7MYcZ6YJJ/tEQCyPktjrwAAAAAA5DAJ0URL8xjnb38bSWRll+aHcUBm3bp11KNHD3F97dq11K9fP9GTSMIBoz///JNWrlxJpUuXptOnT1PPnj2pQIEC1LBhQ3r+/Dl16tRJlLUNHDiQrl69SmPGpNwsnmezat26Nc2ZM4dy5cpFGzZsEDNS+fv7q2U5LViwgGbNmkWTJk0SgaohQ4aIv1m2bNk0v1YAQyQmxFPE+1C120Jl9orLCBoBZA/INAIAAAAASAUHf86ePUtPnz4Vp3PnzonbJLGxsSLbh4NJLVq0IA8PD9HriJdZtWqVWGbFihVUsmRJEeDhYA4HoFLrh8TZSoMGDSIvLy8RiOLAED/H33//rbYcB5aGDh1KpUqVou+++070Eztx4kQmbQ0AIne3Ipw2qHZbM+sLissJCQlGWCsAyGjINAIAAACAT8sytzzjx1h/Ox04W+iLL74Q5WNcksOXOTAjefjwIUVHR1OzZs3UHhcXF6coYbt79y7VqlVL7f46deqkmmk0ffp02r9/P71+/Vr8EOfeSs+ePVNbrmLFimoNil1cXCg4ODhdrxXAELlz56a4WHk5Wl4bS3ofk0B1rW6K69bW1uTt7W3kNQSAjICgEQAAAAB8WmZm6SoRMzYuURs+fLi4vHz5cq3gDuPgTpEinIGhxGVl6TV27Fg6evQo/fTTTyKLiHshdenSRQSjVFlZWald58AR91gCyCw2NjYUHvJGXP6mSWkqf64zfW51Q1xv1apVhjeJBwDjQNAIAAAAAMAALVu2FMEaDshwCZoqT09PERziDCDuJaRL+fLltcrKLl68mOLf5DI4LmHr2LGjIjil2TwbwFiZRhZm8vK0PLksqb61PGDEELAEyD4QNAIAAAAAMICFhYUoMZMuq+JZyzgraNSoUeIH8+eff07h4eEi6JMvXz7q06cPDR48WPQzGjduHH399dd07do1Ue6WEu5jxDO1cfNrDlZNmTIFP8jBJNjZ2WnNnmZo2SUAZB1ohA0AAAAAYCAOAPFJF25SzUEdnkWNs4o4M4nL1UqUKCHu53Kdv/76i3bv3i0aXPMsa9w8OyULFy4kR0dHqlu3rggccYZT1apVM+W1AaQFB05lOgKYIVEkZggEgOzBTKYvPJyDRUREkL29vTg6pG9QAAAAAMaH7+ys8X8RExNDT548EcET7oMCYIqwn6bNmTNnaM6SVdR7nDzw+dXZYuL8TSRR3u8+YBsCZJPxEzKNAAAAAAAAIM2ZRrpKJXNby5tkA0D2gKARAAAAAAAApD1olJiodfvdIKOsDgBk56ART1lavHhxEZGuVasWXb582aDHbdmyRTQE7NChg9rtPMME36564ppyAAAAAAAAyKhMI2XQ6ITbTHr0lmj0XqOuFgBkt6DR1q1bafTo0TRt2jS6fv26aArIDf6Cg4NTfBxPNcozVNSvX1/n/Rwkev36teK0efPmTHoFAAAAAAAAOTFopGyP+6hAJyo1j8hn+h9GXS8AyGZBI54RwsfHh/r160eenp5iFoncuXPT2rVr9T4mMTGRevToQTNmzCAPDw+dy+TKlYtcXFwUJ551AgAAAAAAAD6eubm5WqYRJc+v1KtXT+OtFABkr6BRXFwcXbt2jZo2bapcIXNzcf3ChQt6Hzdz5kwqWLAgDRgwQO8yJ0+eFMuULVuWhgwZQiEhIXqXjY2NFd3DVU8AAAAAAACgP9PoQ1Sk4jpPyl21Ri2jrhMAZLOg0du3b0XWUKFChdRu5+uBgYE6H3P27Fn67bff6Ndff9X7vFyatmHDBjp+/DjNnz+fTp06Ra1atRJ/SxdfX18x3Zx0Klq06Ee+MgAAAAAAgOyL+9HGRiuDRiQj0UsWALIXS8pC3r9/T7169RIBI2dnZ73Lde/eXXG5QoUKVLFiRSpZsqTIPvL29tZafuLEiaKvkoQzjRA4AgAAAAAA0I0PtqsGiTjTiKtGACB7MWrQiAM/nNYYFKQ+LyNf5z5Emh49eiQaYLdt21ZxW1JSkji3tLQkf39/ERzSxH2P+G89fPhQZ9CI+x/xCQAAAAAAAFJna2tLUZHv6d1b+W85WZKMzAiZRgDZjVGDRtbW1lStWjVRRtahQwdFEIivDx8+XGv5cuXKkZ+fn9ptkydPFhlIS5Ys0Zsd9OLFC9HTqHDhwpn0SgAAAAAAAHIOnryotEcJ2vzDeAoPDyNb+wIUEf7O2KsFABnM6PmDXBbG5Wa///473b17VzStjoqKErOpsd69e4vyMalu1svLS+3k4OBAefPmFZc5CBUZGUnjxo2jixcviqwkDkC1b9+eSpUqRS1atDDyqwUAAACArKRv376iBGfw4MFa9w0bNkzcx8sA5DRcinZw/146e+oELV+6hD5ER4rfXACQvRi9p1G3bt3ozZs3NHXqVNH8unLlynTo0CFFc+xnz56lqTaWy91u3rwpglBhYWHk6upKzZs3p1mzZqEEDQAAAADSjLPZt2zZQosWLRIlOSwmJoY2bdpE7u7uxl49AKPj4GlSQgJZWVkZe1UAILsFjRiXoukqR2PcvDol69evV7vOX+SHDx/O0PUDAAAAgIzDDXM/xOue1Taz2VpZpHmGp6pVq4remjt37qQePXqI2/gyB4xKlCihWI7bLPDMvatXrxYHQ8uUKUNTpkyhLl26iPt5Jt+BAwfSP//8I+7nxw8dOpRGjBiheA7OWuIDn59//jktWLCA4uLixCQvixcvxg9yMFn8nkpISCALcwtjrwoAZMegEQAAAADkHBww8pxqnIN8d2a2oNzWaR8C9+/fn9atW6cIGq1du1a0U1A9wOnr60t//vknrVy5kkqXLk2nT5+mnj17UoECBahhw4YiqOTm5kbbt28nJycnOn/+vAgicd/Nrl27Kp7nxIkT4jY+54lcODOfs/F9fHwyaCsAZELQKD6OLCzx8xIgu8G7GgAAAAAgFRz84T6bT58+FdfPnTsnStakoFFsbCzNnTuXjh07RnXq1FHM4Hv27FlatWqVCBpxptCMGTMUz8lZShcuXKBt27apBY0cHR1p2bJlou0CTwTzxRdfiD6dCBqBKQeNOJOOZ7QGgOwF72oAAAAA+OQlYpzxY6y/nR6cLcTBG26NwOV1fNnZ2VlxP2cERUdHU7NmzdQex+VlVapUUVxfvny5yFLivp0fPnwQ93MWkarPPvtMBIwknHWkOYMwgMkFjRLiETQCyIbwrgYAAACAT/4DMz0lYsbGJWpSH04O/qjiGXzZ/v37qUiRImr3SZOxcGbS2LFjRa8izkbiGYB//PFHunTpktrymr2LRJPhpKRMeU0AGYH30diYD2nuFwYApi/rfVsDAAAAABhBy5YtRWYQ/zBu0UI9U8rT01MEhziDiEvRdOGStrp164rm1xJusA2Q1fFs12GhIZQrCwaDASBlhs9lDwAAAACZJjQ0VDRZzpcvHzk4ONCAAQMU2Sv68CxdjRo1Eo/hQAbPupWe57158ybVr1+fbGxsxPTyP/zwQ4a/vuyAS8bu3r1Ld+7cUSsfY5w1xFlEo0aNot9//10Eg65fv04///yzuM64OfbVq1fFTL/3798XM6tduXLFSK8GIOPIs+ESqaibm7FXBQAyGIJGAAAAACaAAzu3b9+mo0eP0r59+8TMWzyzVkq4hw5nv0yaNCndzxsREUHNmzenYsWK0bVr10S51PTp00VACrRx8I1PusyaNUsEgngWtfLly4v/Gy5X44bXbNCgQdSpUycxG1qtWrUoJCRELesIIGv3NEoga2trY68KAGQwMxl38gM1PHiyt7en8PBwvYMCAAAAML7s8p3N2Stc3sRZJ9WrVxe3HTp0iFq3bk0vXrwgV1fXFB/PM3g1btyY3r17J7KJ0vK8K1asoO+//54CAwMVP/gmTJhAu3fvpnv37mXI/0VMTAw9efJEBE84mwnAFGE/TT8OOPNnzKJFi2jkyJHGXh0AyMDxEzKNAAAAAIyMp13nYI8U2GFNmzYVfUI0myRn9PPyMg0aNFDLEOB+Pf7+/iIIpQ9PMc+DTtUTAORMUgNsZBoBZD8IGgEAAAAYGWf5FCxYUO02nro6f/784r7MfF4+L1SokNoy0vWU/jaXYPFRSunEvZAAIGcHjVQzHQEge0DQCAAAACCTcJkX/5hK6ZSWEjBTMnHiRJHWLp2eP39u7FUCACMHjbp06WLsVQGADIY5EQEAAAAyyZgxY6hv374pLuPh4UEuLi4UHBysdntCQoKY+YzvSy9DnpfPg4KC1JaRrqf0t3l6eT4BAKA8DSD7QtAIAAAAIJMUKFBAnFJTp04dCgsLE81kq1WrJm77559/KCkpScyylV6GPC8vw42w4+PjycrKStzGM62VLVuWHB0d0/23ASDnBY0AIPtBeRoAAACAkUnTs/v4+NDly5fp3LlzNHz4cOrevbti5rSXL19SuXLlxP0S7jl048YNevjwobju5+cnrnMmkaHP+9VXX4nsgAEDBtDt27dp69attGTJEho9erRRtgUAZD0IGgFkXwgaAQAAAJiAjRs3iqCQt7c3tW7dmj7//HNavXq14n7OBOIZzaKjoxW3rVy5kqpUqSKCQoxnQePrf//9t8HPy02sjxw5IqYa52wkLqmbOnUqDRw48JO9dgDI2mQymbFXAQAyiZkM73AtPGUsD6C4qWO+fPmMvToAAACgB76zs8b/RUxMjAhKlShRgmxsbIy2jgApwX6afv/99x9VrlwZwSOAbDh+QqYRAAAAAAAApBv3SQOA7AlBIwAAAACAHKRRo0Y0cuTIDH/ekydPit423HzdFK1fv54cHByMvRrZEjKMALIvBI0AAAAAAPTgZuPffPMNeXh4UK5cuaho0aLUtm1bOn78+Cdbh759+1KHDh0y7Pl27txJs2bNMnj5gIAAEQziJusAuiBoBJB9WRp7BQAAAAAATBEHS+rVqyeyU3788UeqUKGCaEh++PBhGjZsGN27d49MCa+blZVVqsvlz5//k6wP5BwoTwPIvpBpBAAAAABGERen/5SQYPiy8fGGLZtWQ4cOFRk2ly9fps6dO1OZMmXos88+o9GjR9PFixcVyz179ozat29PefLkEQ1Fu3btSkFBQYr7p0+fLpoE//HHH1S8eHHRfLR79+70/v17xTI7duwQQSlbW1tycnKipk2bUlRUlHjs77//Tnv27BHrwicuA5Oyf7Zu3UoNGzYUjZt5pryQkBD68ssvqUiRIpQ7d27xnJs3b06xPI3Xae7cudS/f3/Kmzcvubu7q82wx42hGc/Mx3+TH5+Sc+fOUcWKFcU61a5dm27duqV2/19//SW2I2du8d9esGCB2v38N3bv3q12GwfuuLyMSa+dM6YaN24sXmelSpXowoULao/h5fm18P0dO3YU2wYyBzKNALIvZBoBAAAAgFHMnav/vtKliXr0UF7/8Uft4JCkeHEu4VJeX7yYKDpae7np0w1ft9DQUDp06BDNmTOH7OzstO6XeuNwhoUUMDp16hQlJCSILKRu3bqJ4I7k0aNHIhCyb98+evfunQgszZs3Tzz/69evRaDnhx9+EMENDiadOXNG/BAfO3Ys3b17V8x0s27dOkWm0KtXr8TlCRMmiKALB3Q4SMMzgFWrVo2+++47EcDav38/9erVi0qWLEk1a9bU+3r5ObhkbdKkSSKANWTIEBGMKlu2rAia8WOPHTsmgj3W1tYpbrtx48bRkiVLyMXFRTwfl/Pdv39fZEFdu3ZNvHYOhvE2On/+vAjOcaCMy/DS4vvvv6effvqJSpcuLS7zNnz48CFZWlrSpUuXaMCAAeTr6ytK+/j/ctq0aWl6fjAcMo0Asi8EjQAAAAAANHDwgYM25cqVS3E57m3k5+cnpmrnfkdsw4YNIrhy5coVqlGjhuJHNWe+cCYP40AOP1YKGnGwqVOnTlSsWDFxP2cISTj7KDY2VgRhNHHGED9OFQeaJNyPicvptm3blmLQqHXr1iJ4wzjgtGjRIjpx4oQIGhUoUEDczoEdXeugiYMzzZo1E5c5S8rNzY127dolgkULFy4kb29vmjJlirifs7f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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "f1t_time = plot_time(\n", - " stats_test[alg], lb, round_step=0.0005, f_ylim=(0.4, 0.77), c_ylim=(-0.12, 0.1)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "./plots/SSLALM/income_OK\n" - ] - } - ], - "source": [ - "f1t_time.savefig(\n", - " f\"./plots/{alg}/{DATASET}/test_time_{DATASET}\"\n", - ")\n", - "print(f\"./plots/{alg}/{DATASET}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ALM" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Train**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "alg = 'ALM'\n", - "os.makedirs(os.path.dirname(f\"./plots/{alg}/{DATASET}/\"), exist_ok=True)\n", + "# names = product(alg_list, constr_list, lb_list)\n", + "alg_states = {}\n", + "full_eval_train = {}\n", + "full_eval_test = {}\n", "\n", - "f1tr_time = plot_time(\n", - " stats_train[alg], lb, round_step=0.0005, f_ylim=(0.4, 0.77), c_ylim=(-0.12, 0.12)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "./plots/ALM/income_OK/train_time_income_OK\n" - ] - } - ], - "source": [ - "f1tr_time.savefig(\n", - " f\"./plots/{alg}/{DATASET}/train_time_{DATASET}\"\n", - ")\n", - "print(f\"./plots/{alg}/{DATASET}/train_time_{DATASET}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Test**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "f1t_time = plot_time(\n", - " stats_test[alg], lb, round_step=0.0005, f_ylim=(0.4, 0.77), c_ylim=(-0.12, 0.1)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "./plots/ALM/income_OK\n" - ] - } - ], - "source": [ - "f1t_time.savefig(\n", - " f\"./plots/{alg}/{DATASET}/test_time_{DATASET}\"\n", - ")\n", - "print(f\"./plots/{alg}/{DATASET}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Ghost" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Train**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "alg = 'StochasticGhost'\n", - "os.makedirs(os.path.dirname(f\"./plots/{alg}/{DATASET}/\"), exist_ok=True)\n", + "for alg, con in experiments_to_read.items():\n", + " for constraint, bound in con.items():\n", + " FILE_EXT = \".pt\"\n", + " dir = f\"./utils/exp_results/{constraint}\"\n", "\n", - "f1tr_time = plot_time(\n", - " stats_train[alg], lb, round_step=0.0005, f_ylim=(0.4, 0.77), c_ylim=(-0.12, 0.12)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "./plots/StochasticGhost/income_OK/train_time_income_OK\n" - ] - } - ], - "source": [ - "f1tr_time.savefig(\n", - " f\"./plots/{alg}/{DATASET}/train_time_{DATASET}\"\n", - ")\n", - "print(f\"./plots/{alg}/{DATASET}/train_time_{DATASET}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Test**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "f1t_time = plot_time(\n", - " stats_test[alg], lb, round_step=0.0005, f_ylim=(0.4, 0.77), c_ylim=(-0.12, 0.1)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "./plots/StochasticGhost/income_OK\n" - ] - } - ], - "source": [ - "f1t_time.savefig(\n", - " f\"./plots/{alg}/{DATASET}/test_time_{DATASET}\"\n", - ")\n", - "print(f\"./plots/{alg}/{DATASET}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### SGD" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Train**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "alg = 'SGD'\n", - "os.makedirs(os.path.dirname(f\"./plots/{alg}/{DATASET}/\"), exist_ok=True)\n", + " filename_state = os.path.join(dir, f\"{alg}_\" + f\"{DATASET}_{bound}.csv\")\n", + " filename_full_train = os.path.join(dir, f\"AFTER_{alg}_\" + f\"{DATASET}_{bound}_train.csv\")\n", + " filename_full_test = os.path.join(dir, f\"AFTER_{alg}_\" + f\"{DATASET}_{bound}_test.csv\")\n", + " try:\n", + " data_state = pd.read_pickle(filename_state).reset_index()\n", + " data_full_train = pd.read_pickle(filename_full_train).reset_index()\n", + " data_full_test = pd.read_pickle(filename_full_test).reset_index()\n", "\n", - "f1tr_time = plot_time(\n", - " stats_train[alg], lb, round_step=0.0005, f_ylim=(0.4, 0.77), c_ylim=(-0.12, 0.12)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "./plots/SGD/income_OK/train_time_income_OK\n" - ] - } - ], - "source": [ - "f1tr_time.savefig(\n", - " f\"./plots/{alg}/{DATASET}/train_time_{DATASET}\"\n", - ")\n", - "print(f\"./plots/{alg}/{DATASET}/train_time_{DATASET}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Test**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "f1t_time = plot_time(\n", - " stats_test[alg], lb, round_step=0.0005, f_ylim=(0.4, 0.77), c_ylim=(-0.12, 0.1)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "./plots/SGD/income_OK\n" - ] - } - ], - "source": [ - "f1t_time.savefig(\n", - " f\"./plots/{alg}/{DATASET}/test_time_{DATASET}\"\n", - ")\n", - "print(f\"./plots/{alg}/{DATASET}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Fairret" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Train**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "alg = 'fairret'\n", - "os.makedirs(os.path.dirname(f\"./plots/{alg}/{DATASET}/\"), exist_ok=True)\n", + " alg_states['__'.join([alg, constraint, str(bound)])] = data_state\n", + " full_eval_train['__'.join([alg, constraint, str(bound)])] = data_full_train\n", + " full_eval_test['__'.join([alg, constraint, str(bound)])] = data_full_test\n", "\n", - "f1tr_time = plot_time(\n", - " stats_train[alg], lb, round_step=0.0005, f_ylim=(0.4, 0.77), c_ylim=(-0.12, 0.12)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "./plots/fairret/income_OK/train_time_income_OK\n" - ] - } - ], - "source": [ - "f1tr_time.savefig(\n", - " f\"./plots/{alg}/{DATASET}/train_time_{DATASET}\"\n", - ")\n", - "print(f\"./plots/{alg}/{DATASET}/train_time_{DATASET}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Test**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "f1t_time = plot_time(\n", - " stats_test[alg], lb, round_step=0.0005, f_ylim=(0.4, 0.77), c_ylim=(-0.12, 0.1)\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "./plots/fairret/income_OK\n" - ] - } - ], - "source": [ - "f1t_time.savefig(\n", - " f\"./plots/{alg}/{DATASET}/test_time_{DATASET}\"\n", - ")\n", - "print(f\"./plots/{alg}/{DATASET}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plots w.r.t. iteration" + " print(f'loaded {alg} | {constraint} | {bound}')\n", + " except FileNotFoundError: \n", + " print(f'not found {alg} | {constraint} | {bound} at {dir}')" ] }, { @@ -614,68 +98,71 @@ "metadata": {}, "outputs": [], "source": [ - "alg = 'SSLALM'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Train**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "f1tr = plot_iter(stats_train[alg], lb, \"iteration\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Test**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "f1t = plot_iter(stats_test[alg], lb, \"iteration\")" + "import numpy as np\n", + "\n", + "\n", + "def explode_column(df, col, names, m):\n", + " df[names] = list(\n", + " df[col].map(\n", + " lambda x: [np.nan]*m if np.all(np.isnan(x)) else x \n", + " )\n", + " )\n", + "\n", + "def aggregate_stats(live_stats, after_stats, constraint_bound):\n", + " \"\"\"\n", + " live_stats: states of the algorithm evaluated during run\n", + " after_stats: statistics evaluated on full set after run\n", + " \"\"\"\n", + " live_stats.columns = live_stats.columns.map(lambda x: str(x) + '_live' if x == 'c' else x)\n", + " after_stats.columns = after_stats.columns.map(lambda x: str(x) + '_full' if x == 'c' else x)\n", + " # combine into one dataframe\n", + " stats_joined = after_stats.set_index(['iteration', 'trial']).join(live_stats.set_index(['iteration', 'trial']), on=['iteration', 'trial'], how='inner',lsuffix='_full', rsuffix='_live')\n", + " for col in stats_joined.columns:\n", + " if col == \"time\":\n", + " continue\n", + " # change [list] into list\n", + " if isinstance(stats_joined[col].iloc[0], list):\n", + " stats_joined[col] = stats_joined[col].map(lambda x: x[0] if not np.all(np.isnan(x)) else x)\n", + " # \"explode\" ndarray column into separate columns\n", + " if isinstance(stats_joined[col].iloc[0], np.ndarray):\n", + " if len(stats_joined[col].iloc[0].shape) == 1 and col in ['c_live', 'c_full']:\n", + " m = len(stats_joined[col].iloc[0])\n", + " \n", + " explode_column(stats_joined, col, [f'{col}{i}' for i in range(m)], m)\n", + " for i in range(m):\n", + " stats_joined[f'{col}{i}_corrected'] = stats_joined[f'{col}{i}'] + constraint_bound\n", + "\n", + " # add norm for ndarray columns\n", + " stats_joined[f'{col}_norm'] = stats_joined.apply(lambda x: np.linalg.norm(x[col]),axis=1)\n", + "\n", + " stats_joined.dropna(axis=0, how='all', inplace=True, subset=[x for x in stats_joined.columns if x not in ['cb', 'time', 'constraint_name']])\n", + "\n", + " # convert one-element ndarrays into floats\n", + " for col in stats_joined.columns:\n", + " if isinstance(stats_joined[col].iloc[0], np.ndarray):\n", + " if stats_joined[col].iloc[0].ndim == 0 or stats_joined[col].iloc[0].ndim == 1 and stats_joined[col].iloc[0].shape[0] == 1:\n", + " stats_joined[col] = stats_joined[col].astype(float)\n", + "\n", + " stats_joined.reset_index(drop=False, inplace=True)\n", + "\n", + " return stats_joined\n", + "\n", + "\n", + "data_train = {}\n", + "data_test = {}\n", + "\n", + "for name in full_eval_train.keys():\n", + " print(name)\n", + " data_train[name] = aggregate_stats(alg_states[name][['f', 'c', 'time','iteration','trial']], full_eval_train[name][['f', 'c','iteration','trial']], float(name.split('__')[-1]))\n", + " data_test[name] = aggregate_stats(alg_states[name][['f', 'c', 'time','iteration','trial']], full_eval_test[name][['f', 'c','iteration','trial']], float(name.split('__')[-1]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "**Trajectories:**" + "---\n", + "---" ] }, { @@ -684,67 +171,63 @@ "metadata": {}, "outputs": [], "source": [ - "alg = 'SSLALM'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Train**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "traj = plot_trajectories(stats_train[alg], lb, \"iteration\", alpha=1)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Test**" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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oExIQc9edfPzw8BHIm/kUDo8cBTjsCL/4It/GlXnApv8iIUyL6GM/iXmdxgBhCdD26snFoQN7jmL5VbfCeacoMNK1ZDAPqb13sR3D16g9m0oqA3J1hXx83f5FWLZ6NTL2FGPt/KM8rfrVRQfw+LxdiAvTYkTnaEztk4hQrQodIoVvEDNifuG3/dyviHGNK9KJMdwsXqeARRsRBEEQ7QoSeZoYyZP9gH8PIoJoj5E8VHCDIAiCCHY+Xit8bJJtShh+yePjb9w9FD/dPxo6tWyu3CVKC6hl8WTBZDtev1bCKJMJmHN+k14r7uGHPePl80UZdElrh3rds74Nl78I/P4kZp68E06HiKBxXvM5H0Ze4RKTrr4EyXs3+6wWXZsMvVfydKeJRTBrwtGlbBif7lgyEid/WYZFs3dj1x+Z6Dbzd3y0+rjHfPm7e0bhw5uH8OlwvW+UzosL9nMRKdZR57LfCezPpQqyBEEQ7Q0SeZroyUMQfyUokocgCIIIduZvz8akLrG40StCJblbVL12lqNHAasVL9ygRO6YWnw1SINZBUXcdBm1JUDuTmDrp/IKhQeBXd/5bEOhUqH7VlGty010txpgz/dATbE8UynEpdjao5gkbUOOMwZvrinG0cIqqFOEB483IyzL+PCa3U+hpzHWI/PoY6xYd85rPm1NNeM945fVylW3PrxpiG9fFQr0SPC9fnXLPls1Ns+8jjYl9wsiCIIg2hck8jSCMiSktbtAEC1OXU2HInkIgiCIYGb90WIcK6rBwG01nnk3vjjSb1vzcRHxk5GgwCNjw+FQKjB62MPAdd+IBh+NAxY8Anx7IzBvOvD+COCnu4F17wrBZ78rckenQfoFhYjrX4nul+ch9qmXxPolx+QXY6KRixHKgzjo6Ij3Vx7DxHdWo9Jog/3ZVz3Lj/caBn3WdoRECsFmY8cXUTnhNnR5ZgocXgVw00KWwCzJ75PR3Sohxq7AjIndMbVvYr33/OWdw7H8sXGe6YsShPiVo7Ij9DzR/toaLWqN1qZ83ARBEEQbgkSeRmBVFcIvvpiPszKaBPGXMF6uV2+LIAiCIIKH3TkVGGOVU7BufmUUIuMNfiNTSz7/DLnRQK1OhK0kGBKgO28G0KNORa2DC4B98+Xppc8Kwef7m4E9PwDf3gBthA2xvash3b8U6HWpaHdsuRjabUD+HiCyo2cT/7Nf6Bl/f+VRXLxbg+unPoc7JzyJX7RpUGadRM/lctWumj7jsSp3CMptSXy6X+58GG/4P+R1fQlVmjJI8RbsTBavd3uVDtLvIk2tLvFhOnSJC/VMm4uF987Pz0/A2B5xnvmvfrUbZ4OCmgI4nHQdTRAEcTYgkacJhE2axIdURp1or9SVdG6Ys6mVekIQBEEQjbPuaDFG1Ipol6tnDEV4jDAb9qaougDb77gO5j17sba3EglOJd7vcy8WXrFQNGC5Sk+dBK7yStUKxI93AEeXivHh9wCpw4CQWCCyE2CqAF6IBl6KASqygNGPAFGdedNtju6eTeg1IpWrXBcGQ5d07IgXyyKqTqDbkXl8/ODuGhw+3gHflrzHp0Oy9mBK5RFcMfYOzB3yPGZ3eQKbUxd4tmmukdOvDm3K5+XWdy3P8sy7qL8Qi/pGhSI6OQSGcA3S+sVg6EVp4rXtLZ+vlV+Tj4k/TMSDyx+E1UGRQwRBEC0NiTxNQIqK5ENbaWlrd4UgWgTy4CEIgiDaCpkltRi5pQZKJzBwYiriO4lKqHX5v8+vgmG9iFTZ1AtYes1KjB36ALSS7OEDfSTQ9wrg3CfE9MO7gWu/Ap4r9//iLMXrwn/K09pwYNOHgFOYLHMiUoCHd/JtLH9ysscf539rRNrYO9cMwJHCahQZZP+g1JyVqDFm1ns5nakY2ffdj2Fxo/Ds13Y88YMdETV2VGqFD5DaYMXq7NV8fNmn+/lw7bwjnvVn3zAYOx8/D4pj1QiNFO9bKSkx4pJ0VCuciHQoYLM3HmHjsFiQ/dDDsObl4UDvPjjQsxe/dlh6cin6fd4PVZbAD0J3Fu7kwzU5a3DNb9dg0fFFjb4eQRAEceqQyNMEVNHRfGgvK2vtrhBEi0AePARBEERbwOFw4pVFQsxgdB2S4LfdlvwtiD0uHs4dTQRePe9xKLxElXowkeeOpUBUJ6DXJSLK5+ks4B/FcvpVSBzQU06/4vhzLg5L8ixLjTZgyd/ORZ/kcFSbRdQNK3n+9AU9+fjdU/6OL3tOxi2T/459ka71XAzoq4DSleJ0ZMq16HvSiWFHnPjvf+yYvHo2Ykr2wVqrxrEnN/MIHm+O7yzyjM99ZiMfJnUTDy3dxCQYEO5QoLTGwoUze3UNnFb/kTbmAwdQ9ccfyPvHs+xLEPOOHMGSE0v4eE51jt8HRiXGEjyx2iWgse+i/CieWvMUjDaj39chCIIgTh8SeZqAFBHBh/aKitbuCkG0DG1I5CnNq4HdRnn9BEEQfzXWHilG+sxF+HNvAZ9O7R2N+LT6VVBtDhvuXTAdDywUvxUFd6Wg38BbGt64SgukDvedpwsHJDXwyB7giePAY4frr3fHH2IY1wu44E0xHt6hXrPHp/TwjPdJjsCto9LQMdqAO68dg697TuZRPUaXXpShElFBnfrFBuyuwViIjpnitWvDB3vmaw0ihe33D/fUW2foBSJFy41GrURfqwo3P78S5775Jw4PHYqcx2VBxpuyr7/mw5q1az3zSj/5FOtz1/Pxq3+7Gp/vE6Xivdld5N/zZ+6BuQHfG0EQBHF6yNb9RECUJPIQfzHj5WB+gvvNC5vQb1wHnHu9fMFMEARBtF9YhEjnGXKKT29JVKMaNa0LLxfuzb7ifXh81eMYu1f+Xbvz2oWe0uanTEiM//lqPfBMIeCwi/GeF/ltmx4rqrUO6hiJ6BDR/9VPnsffG5ue1DsB+06UYe/GPOgNwANX9uNtrCv/hOXECWTeNr3eNqMqjiKy/AjKI7t55p17XXcs/USOdKqttPDhsORsZFx9DTrP+96zrCpLVOwaY1KhzCYif6qWLIHTbodCkj8v1kdbSX3Lgoqff4YjTcLUfU4sG6jAhrwNuK3vbZ7lvx77FX9f+3e5v9oolJlFVLxPyhxBEARxRqFIniag1GigMBhgLw+Qn00QbZy2IfEAdqt4KluUVd3aXSEIgiDOEiNedVWvAvDQ+V3xzJhuUKmViOvoG8Uzc81MXLfwOtgys3DPYvF70fPaXEAlRJUWg0UBaQwidSuifhQPo1NMCJb+7Vx8fadvmXcmUl0yIBk6tYQh3WJx68398JJL4GGoExMRMnIkeh08gC5LFvN56Xd1RNgFU/n4zwNEuhTjjqfS0bmDHUNShWDjdDjx67vCD0f94wcw7dkDc0aGJ61KHy4+F4OlGp//8aqPeONN4T/f5BE82t69oEr2TSm7e7EDty91YMp2JxJDElFtqcZz65/j6VveAs/vV/wOvUo2x3b7CBEEQRBnHorkaUbKFkXyEO2VtmK87BZ5/FkgEARBEO2TwiozH+56djJKj1Zg0fu7EZUkImMYrGLThO8neKJE3vuvSHcKTTZB8VzwFM3o5jJgPlU0nTqh11tTgazN6PDWW6j42wN4McSKFX/PQ0TFMWRc8ABvZ4ofAvS+He/f/6dnXZ1ZPKg8fsGFvGqsad8+DCw142CPG1ERngYnFFC4Hvnk/f0ZRF55pef6oPRTUX0sZMRIxD/xOJxmM/buXAr19Kcw6qBYJ7LaiZjQFMzaPgvzj8z3EXQYKWEpqLXVeqY35m3k264biUUQBEGcPhTJ00Sk8HA4SOQh2iltxXjZ5hJ5QNeEBEEQfwkqaoUR8CMTu6Emt4YLPAxzjZi/OW8zJs2bxAWetHwnvn9NLimeMqb09NO0go2IVKBgLxR7vkdk5S6kR3TG9thXMGD3+54mNknX4Caqli6FNTcXelMJOmYtg0PSwqTzNaXOfaovHEUnUb1yJZ+Ovv12xD/+GBRKJZR6PZaoDvm0D68F3tvxHr479B2f/jNTCEydIzrj1t638vGpaSL6yM3xiuOn9VEQBEEQ/iGRp4lIYWGwV1GKCNE+cbaRhC27zatELUEQBNHuOVwoSnNP7ZvoEXgYVz45hA/v+OMOlJhK+PgLv8i/EanjS6Boj1e5aWPE8Od7gR9uh3bD++jasytUdpOnSWLBZp9Vxqx7CsnPPYkOs2ZB28PXzy6kJo8PC+KH8WH8/cJTp+IXOw6NnQrzISHmXBb+OWwKuejB9oLtuPkxWUBLKfa9jsityeXDX6f9iseHPc7HZ4yYgVXXrsIrY17xRPMQBEEQZ572+PPXIijDwuCorGztbhBEy9DWInkIgiCIvwQrDxVCpVSgY7ge5lob4juF4YEPz0d4rB6ZlZmedrN73ol4g1yWO+Sfu4Fn5DLi7YYUIcZ4WP4CQuITPZPaaedDclhx3soHkJq1HD0PzYXGWg3FxucRPnUKFCpfpwatK8XtePql+OmGW1CdtxgVCbKHUdGsd/mwRq/wqZ6lVCpxbrfJ6LZ+HULOHYv4SgUGHXVg2OHAv9NKhRLRumhc2uVSPmT+PQRBEMSZh0SeJqJOToYlU76YIIj2RFtJ13KLUU7SegiCINo9x4uqMfvPY7A5nCjNFBE9o67o6ll+1W9X8eGrY17F8EMnUZWth37QQHTftBGK8MSWN1xuDZiHTYpvqffR2z7AS9cpcf2TEi7rtRoHU5m/DtDt2Hw8ff0m/G+yEtnxNcDqtxB/yyVQRejQ46pcdLmoAFHpNUjUZfDtROSOwIKyf2DbuT39vvTJypN8yLx0WGl0g8oAVXQ0wqdMRUSNEzPmOfDEjw4MOSJ+pJdfLRtm1yVME4YaY0Wb8QQkCIJoS5DI00Q06Z1hyc7mZSUJ4q+QrhWMF16shLog+PpGEARBnFmOFdXgHKMKT5Tr8cssUSWKRfK4idBG8OElXS5Bxqu/8/GYu+/mxTLaNdfNBaLTgYiOfHKI2Yx96SrYJWFY98EF8uW9SavAH0OU+CYiDAfXvo6QHQ+h2wXHUaZRQgqzY894C+aky+XpGXuVvWBSy9P/nSq29/PRn2G1W9H/i/58ekTSCD5Ud0j2Wf+JX0Q/IrWRAd9ChyoNLrjtU5R9+dXpfhoEQRBEHUjkaSKq+HjAaqUKW8RfJpInKKN73JE8wdg3giAI4oxy1xdbMcIspxdNvrMPNDqVx7Q3vyYfb577Jhy5B/m8iAExCDvvPLR7QuOBh3YAV33smbX++vWe8bwYBbZ1UWDJYLlKwc9hobi6QxLGduyA30IMGN8pBQM7d8RjCXHICT+CDR1/8bTV2UJxy+Py554TK2/nkh9l8+RYfawn2t0bSVJjy41boJECR1IN3idS62q3bz+lj4AgCIIIDIk8zTBeZjiqKX+YaH/4i9qxB6HK4+6nMwj7RhAEQZx5ahVOJHQOx/3vn4duQxM88xceX4jzD6jQe/YyGBd8xOdFPvo6/lKkDgfO+T8+GlKZjz9SrsDak1l8+o1rJHw8RcJXufk+q5RLEmbGC3HGg8KJXR1WeCaTK+WUOEaCyoJ3dd34eI6xkA+ndZ2GQfGD+Lg6UfYEYjitVuhUDVf4iq4Uv+NHc/c07z0TBEEQjUIiTxNRhgqRx14lcsIJoj3hLzLGEYThMm4vniDsGkEQRKPMnj0baWlp0Ol0GDFiBDZv9q2CVJd58+ahZ8+evH2/fv2waJFvWs1tt90GhULh8z91qm+Z6raKze5AhEKJcKcSAyakQqGUo0lMNhM+2v0R7v3ZhJoFC1E2/zdIGgf0Q0fhL8e4p8Tw34ORtGYWIhxOPFcsqo09VVKGAWYLknR1RJ0A/NznXdgUFhis4fi137v48nwlTB2s+LexAOcfWI54m1ye/qXRL3mEHIXGN2KHlVhvjL5/uvx9MnN85luyc2AvL29SfwmCIAj/kMjTRKTQED50VNe0dlcI4ozjTzQJ6kgeUnkIgmhjfPfdd3j00Ufx3HPPYfv27RgwYACmTJmCwkIRGVGX9evX4/rrr8cdd9yBHTt2YNq0afx/7969Pu2YqJOXl+f5/+abb9AeOF5cg+E1okR3Qlq4z7L3dryHO5bIHolVJ1Qw9OsKhSSX9P7LoJU9ijj6aET1uISPRrh8JD+f8D7u6neX39UfH/o4pqSch8VZOSgIO44/u87l86squuGVJ/6LQXeP4l7PjFjX9hIMckSVG4VWy4dRN1wPVUL95W4qfvsNpV984ZmOrvPs9NjEici45tqmvHOCIAgiACTyNKOEOsNRTZE8xF/DeNkehEKKu0tUXYsgiLbGO++8g7vuugvTp09H79698eGHH8JgMOCTTz7x2/7dd9/lAs4TTzyBXr164aWXXsLgwYPxn//8x6edVqtFYmKi5z8qKipgH8xmMyorK33+g5XfduZgoEX4wrBy6W6YyP/l/i8xZbv4QYjpLa7LQi+4vJV6GmTctgDje9+AF4tKMKWmls9Kiu6BhwY/xMcTQ3xTq27tcyvemvAeKsfMhu34/dhX24/PV2slKDqPARL6eNrG24TI86/x/6r3smnffYvE55+HFBMDRwP7Ve4TT6Lg1df4+Kq+Cmjs4EVNCt74Jw707MXnW1k128pczzq8mtefWaittJzWR0MQBPFXgUSeJqIMDeVD87Hjrd0Vgjg76VoUyUMQBHFGsFgs2LZtGyZOnOiZp1Qq+fSGDRv8rsPme7dnsMifuu1XrlyJ+Ph49OjRA/fddx9KSkSqjj9ee+01REREeP5TU1MRrBzfK97HpY8M9Jn/0saXeLluhjpShdhxKUic8TjCr7wRf1mezgSu/Qq4608uykghcbi8ugY8iarfNWxn85gzL7h8AZ4b9RySQpKw+MrFnk1IvS5GraUjrDV94FQAdqvraUqHIZ42rxeV4JW0aegb2xdWuwOvLNyP/TkVsBht0PXsiajrroUUFg57E8XDvZ1EiJDDaETpp5/6LKt+Qv7eK4qMWPPdEXz65FrUVJhP66MiCIL4K0AiTxNRarVQd+wI405RwpMg2hP+/HeCUOPxqFGk8RAE0ZYoLi6G3W5HQp00Fjadn+9rjOuGzW+sPYv0+eKLL7B8+XK88cYbWLVqFS644AL+Wv6YMWMGKioqPP9ZWcKkN9gwWe2w5NbCaZCQ0kOOTGLVtOYdnoeLNju4WXDauGwo+1+KqFvvaJIPTLtFFwH0ugToMFhMx/UARj8CPHEcuHKOp1mYJgxaSYurul+FP676Ax1CO3iWRRrkmulOpQI2t8jTbRIwIwerrj2AEKcT5xeXw2q04pNFhxH5Wz7+fGkb5vxttc9DUafZjNKvv/bt47p3gU8v9Jk1rq9IK3vs7cn13lLWqhjUbBSCpqna6pmfc7jsVD8lgiCIvwxyfUSiUULPPdfzg0MQ7Ym3/jjUNjx53GlapPIQBEHguuuu84wzY+b+/fujS5cuPLpnwoQJ9dqz1C72H+x8vvAQBtZI0EepuJn0rG2z8PFeUS68Y6ET0zY6Ed7JCJXeAaSOaO3uBh9KCZj0QrNWiQuV9wul3Yl1PxzFwIkdxQxtKHbk5GIci2jf/ic+X7q23vp2uwOSpISuT28+XfjmWwifOhWq6Gg+7fj9ORTtZdYHIjKekds9Cn0BTF4hhBtd374ImzgBRbPeFdt4/XV0/vkXWC2yaKnW0q0LQRBEY1AkTzNQxcXBXlTc2t0giDPOoj3yk+EucS6T8SAUUtx9CsKuEQRBBCQ2NhaSJKGgoMBnPptmPjr+YPOb056Rnp7OX+vo0aNoq5RUm7FzeTYfHzxBpJO5BR7Gc3tEee/Y3tXAxf8CutYXs4jmw8S0m0d28pln8xJX3CncC8qe9bv+/jXCQ0fXowcfOo1GnLj6Gs/ykkOhKD0oCzyMCd0u4r48nV27edLsDxF26518fN2ol7EnbDyObiuE1ST3w2mnCwCCIIjGIJGnGUiRkTzPmBnEEUR7YlR6jGdco5KCNpIHnhLqQdg3giCIAGg0GgwZMoSnVblxOBx8etQo/2W/2Xzv9oylS5cGbM/Izs7mnjxJSUloq6w8VIQYhxLGJC2PJCk2FkOlVGFY4jBclH4RYnJLEdm1BtpL/gYMvb21u9uueOqCnjxta4leGByXFwrjZsahgirkOaNR7fBfjn3H4fpeUNacHPR9dB6q3+oPh1UhHw9paTBrwrHq2UL07ncfbJIOR9Mvx8fP7cL//rYauwfdD7M2ClkhA7Bkzl4c3SqLnRazXMadCB4W781DDX03BBE0kMjTTJGHhRA4qqjCFtG+6J4gP13TqJRBK/KQuEMQRFuFlU+fM2cOPv/8cxw4cICbJNfU1PBqW4xbbrmFe+a4efjhh7F48WK8/fbbOHjwIJ5//nls3boVDz74IF9eXV3NK29t3LgRJ06c4ILQZZddhq5du3KD5rbKkZPlSLIrcf5oEcWzInMFP/ezik6vDJgJS04hdJFWYOxjrd3VdkeoVoVXL++Hg6zkFYATu+Xo9bxyI24wPxNw3d/3e0UEL/0DTihgUYdi3qJngSP5cNhkkSfth3lI/HERH9+T1werx76NzI6yyXhxhFzRi1FwQjZytm759rTfJ3Fmqai14t6vtuPF3/a3dlcIgnBBia3NFXnYzW95uWecINoDP2wTofEMraQM2nStIOwSQRBEk7j22mtRVFSEZ599lpsnDxw4kIs4bnPlzMxMXnHLzTnnnIOvv/4azzzzDGbOnIlu3brh559/Rt++zMUEPP1r9+7dXDQqLy9HcnIyJk+ezEuttwXfHX8wMWf/riIwl50ew8Tn8svRX3g1pwhtBGrW/AZW+skwqB+g/gsbLbcgGkkJiwLQRGtRcKIK7/xxCDGhWsQeN2KKsbOnXbn+EG659zocKK/Bls8PQu31+6xJTcXaPjfBGjcS41c9xE2UGfnxQ7G/93Q4dpTDHi4bPTdGZbHJM249uetMvVXiDGG0ClEwv1L+ngiCaF1I5DlFkYcg2hM1Xnn3Kkk8baNIHoIgiDMLi8JxR+LUhZkl1+Xqq6/m//7Q6/VYsmQJ2gvs/N55xiKcZ1RDE2FASIQWBTUF2F28G2+MfQOw1ML8yd1QKCOguf6d1u5uu6VDlBDP8lQORFVZ8N6KLITbFbjbKAuH50W/jlWKeKT2uA8Zh23QOxQYYVajusyEPatyMOKSziiL7sstlm0qAzRWEQHPBB7GyrmHsVxvwQRR5L1JpEceQmFlFKxO3Rl/z8TpUWOxBe11I0H8VaF0rUZg1QIsJpuPyGMjkYdoxyhcEdUUyUMQBEGcLZ79ZR8fJtuU6NRdlE3fWrCVD4fEDQReTULB9kheZVGRLKKZiDNPr6RwGDQSTpYbUZBRiSm1atxTpYMCcrpVHiSkKgv5+JBOUSiTxHXy6m8PY/vik9jxZzZqNEIsqujcm6duMaJqMzzbMDjk7TUFnfkE1EoTLApWoYsIJiqNosS9zeEugUoQRGtDIk8jzHt1Czb+cpyPS1EUyUO0T8J1KqiU4oJL6VJ57EH4W+10PyUisYcgCKJdsXBXLm6o0iDZrkRiejiftzhjMfrH9UeCscLTTp0qvHqIlqPWK7q3v6V+0H+ZUkJnhfDgCdGqcHf4y3y8slSk65zYVYgwhSiLvif5FhxLn4bY22+CuqNsCM7Mtb3ZkbwMy7p+EbBPGoUR1fY4HKoZAzh8C6Cwgii20lJ5miJKWpTsslp8sPKYJ7p63VHh3RQTIqK9Kk1WpD29EH8eFEIgQRBnHxJ5GsEQoUVtuZmPKzUaKAwGEnmIdkdUiAap0QZPGdWgDbsNwi4RBEEQpwe7WextVqKDXVR3jEsNQ1ZlFtbmrMWFnS8ECvbBXCmWxdwhSmwTLYtF4f8Hd4fGhoPOjuimkm/gI1WifLqxuoYPO+R+Ao3S6Fle3rkLoh6bgfJKOT2ru1WC3etHvVJXAotKXseNwiGiRJI0B2B16mF2hgFWueoXo+C113HknNFwVhXi6JZcvH//nzDXivWIM8+YN/7EG4sP4p2lh/n09sxyn0ierFLx/fyxX66KRhDE2YU8eRohJEKDsnz5x0SKiIC9Qn6iRBDtASbo6LXiAloZxOla+9bm8GHw9YwgCII4VU6U1CKuUpzZh16YhsQuEfj3ji+gV+txacZOYPNHqCkQDyLCL5jayr1t/0QZ1Cgzy+G8JztpcNGwFIR1jcCbH67HtTBA4zACNguw4iWEKkugVVSjtkxU6jQ6wpGGUmRDRF1V2jtj24EiWCy+z5ZNUi1uiXgJ1Y4YfByXjZjqdD4/I2o39sX9gdc+K4VkN8EuaRE/KgPJHWzIzVWhMr8M4Z3ktK2yr77iQ8fr3bGkZL7oQ5UVWkPTzZ2J5pNTZsTcTSdhtonIqkqjSNszuiLBWNofQRCtA0XyNEJIpBY1rkgety8PRfIQ7Q2HwwmtWvwYu7PkgzGSJ3OfCMdWupUogiAIok1jstpx3lsrkWhXos/5KRhxaTqPKD1SfgT9onsjbPNHvJ25TA1tr178YRvRsiz527m4/IrununOaZEYNzENITrxbPjieFdp9a+uANa/B4XCCbNTCDwMkyMcFocBXaO2Q99DXFts/Y/wXLog8nVs11bzcYfSiETNIXTVrYcKDiic4re9TF+A7OhMaC0VUNnN0FoqeYWujqWbxMu+fsRvv+1m+bbG+9qdaBnm78jB33/ai5JqiydNi0XxXPXhBj5NIg9BtB4k8jSCPkwDY7Uc8ilFRpDIQ7Q7mJ7jLp3uJvgkHmDI1E58KKno1EUQBNEe0rS+3ZyJzlYlQp0KqL0E/AMlB9DD7dvS9yqYI8ZA27Vr63X2L0R8mA7ndo9DtStla0gPUQI9PS4EN4/shL6TRZUsnFjjd32jIwxmZwiq4/uhV5cUn2VhUgGsSnFd7VDKJbfH1RpREHYCexJXYWeH5XIVCC8qqlzRvC4xyJqXB4dJ3obNJF8b/DJrx6l/AERA3FE73lS5CtQUV5tx6yebPfMNmrOXMLI+Zz0czJWdIAgO3Sk1gi5EDbvVAasr9FAVFQV7GYk8RPvC7nSC/TFULrEnGNO13FApdYIgiLYP8/R4/rf9GGgWN4M9Rgpj3o15G1FQW4Be2buB+N5wXDwbxh07oEkTQj/R8iRH6j2Rvb07R/OhWlLipWl9EdVrXL32l0Y9z4fhUh6MjgjU2GNgZ0a8de67I6R82F3izrA0kYLHeKWoBD2sRqzrPJ978+y5dQ/UKb4C0V7jXs+40+HA0fPOR+6jD3vmWSxymXe6TGgZ3ClZ3uSUCy+lgkozjhcLXyaG9iw9kGOC8D3L7sGALwbg832fiz5V52B19uqz8voEEYyQyNMIulCRz2tyRfM47Q7UbtzInfwJoj2la7nTszSuH+Vgu0DKOVyG8kLhj0WVMwiCINo+/15xlIeNpjkkDJ7aCbEpocirysZdf9zFl4/NPQgMvgXVa0TESMiIEa3c478OrGpWpxThe6MPb8TbZvLLSNXuwvWx/4dtGjvK7SmwQYsu3ZNg86rUxdAoTXhG+z4fT9GekOcD6GMWKVZPDXuKDzv/NB/H5jzuaTNhh6jYFWqwwu6qplW1Qr6Rt9pkkYdR97WJ06OoyoznfxVpd03hbKX9253y9/zW1rf48PoF1+OB5Q+cldcniGCERJ4mRPIwTDVC5NF0TuNDS0ZGq/aLIM50JI/d9VvsTtsKtmiZn9/ZgWPbi/h4kHWNIAiCaCZuc9YIhwIqB5DcLZJPr/nzH3x4b1kFQtnJfujtKP9+HjTp6TAMHdqqff6rcdH9/TH+xh6Q6qRz+zD8bmDkA/gIV+ABx61YoYr1LErr3gHdhyfWW6WXZi9ujL0fPQtegs0Qh/+zPMjnh4YLo+akEBHRJYWFYcCAyZ71lE4HSjVbERFmhL2yqt52rXZRvUupFOFDGbuLkX+8IuiuZ9oiP+3IxrBXlmHhnjw+/fVdjQuuFvvZSZ9SKnz3T6PNiDKzEAQJ4q8KiTzNFHlibrtNTB861Kr9IogzHckT4jLIiwkVF0nBfElEkTwEQRBtm51ZIvX9oaEiBSu2Qyhs27/Aq6VbMMhkwgPlFcDEF+B0KlG7eTPCL76olXv81yM0Soc+Yzv4X3jeM8DE54EL32SqCuZHTscGRx9USvLvc0SsHglp4aicmsCnpYFCyGNEqvK47Y5CbcAhpxB3bBWZ4nU1solzrEEWjRhaWwhyCsJR/fyoel2qyBWRR5cMXAGNXoU9K7Px4z+34eAGIUwQp86M+Xt8pjvHhvhML/i/MZ7xaQOT+bCgUvZLakksdmH87Gb43OFn5XUJIpghkacR9HXStVh1LYVaTb48RLuCaSbje8Th3esG4tphqR7hJ1ihp3IEQRBtm60nShGmU6FfiIE/UDOEq/Hpqr/DrlDg8qoaoNNoYNSDMB85AqfZjJCR9W/qiVZk3BPAmL95Jl+8rG+9JirXw6Orz+mE/4ab8HpGfbFFodLgsDMVTihhje3G54WqZZFHr9KjfP4sOJPi+bTaKUygs+xyGzfVJULkkSylsBhtyDtawafL8kWqN3HqWGy+UTmReg2ev6Q37jlXlL3vmRiGI69cgAMvTsWs6wbhgr6JOFIgqqi1NFaHXCCnLlmVWWelDwQRbJDI0whqncTLNbtFHoYyNBSO6rNz4iKIswHLm5aUSlw2sAMfMoJZRqECCgRBEG2Xy99fh7eXHuY3hiXZ1YhJCYGi9DjeixaRHhfesR6YvoiVUoRx9x5AkqDr3au1u000wJBOUZ4Ijv1qGzr1E2IMQ6+RUKl0gjk5/zb2Z+Q5hZEzQ2ERRr3fXrADtjQRDaJS+lZlGtV7Crp++TUfj82fz4dGkxB0GB9PdhWMkMSDWVXeRp/1S3NlM+DmwHwAM3YVUTl218NAb9h3etvozphxYS+ceP0iXrSDGXOz+YwKoxUbjpeg8CxE81jtgUWeC3+6sMVfnyCCERJ5GkGhUEAbqvakazGU4WGwlwnDN4JoD7BKWpKrjIa7mgZV1yIIgiDONCdLarAjU0RD90oMQ/ahMiR1jURe7hY+b3qXK6CNEv6HjNpt26Dt3h1Kna7V+kw0jqRU8AiO6aPTMOy6brj4gQGeZSxiy02RNg3nOz7wTCuqcmHQSKixONA9qjufF6WLqrd9TUoHKCLC0T27UqyXJXv9mNTAryMUqIgSKUQqhQVXXidXgXIXbWguc5/diEUf7MFv/96JvzJWL2+dJ6b0wOwbBje6zpWDRWW0rDJReasl+eHIDy3+GgTR1iCRpwmwMGJvkUfXvQdMhw63ap8I4kzCBB0WscZQsiR5RhDrKKTxEARBtE3+2FfAh5/cNhSPjevG02pYVa2t2aKC1vQhcklsBvPjCR0zulX6SjSf5y7pwyM8vAnXqXnpdXeEh1atBB49IBaOehA6tQSzzYHre16PRZcvQrxBpGbVRRkZCUNtPh836uI88yUHYFYDhipxcSApLNCXyNE8FYVGWEz1S383lZKcU4sEai/kV8jROA+c1xUX9RfG2A0xtrvwUiqr8fXLaQmWnlzKh7tv2d3ir0UQ7VrkmT17NtLS0qDT6TBixAhs3rw5YNvx48fzaJi6/xdddJHPU/lnn30WSUlJ0Ov1mDhxIo4cOYJgQRei8hF5VImJsBWLKj8E0V7StdzijlvjCWJLHjJeJgiCaKP8eagQE3rG4/yeCagsEBEWkfEGbMtZj65OFaL0ciqPrbQUtoIC6Pr0acUeE2eClEi9x4xXq1IC4cnA8xXAlFegUym5yMPuD1JdFbb8YT+ZCcllslsZ3hHP3KzGsoEKbOypQI9s4FD36/kynaIa2l0f+qzLxETClxPFTROv8rxEnqYSZRBFPErPgsjTIbQDJnWaxPcff1D0N/FXpNkiz3fffYdHH30Uzz33HLZv344BAwZgypQpKCws9Nt+/vz5yMvL8/zv3bsXkiTh6quv9rT55z//iffeew8ffvghNm3ahJCQEL5Nk+nsuLI3hj5U4+PJo4qNhb2ouFX7RBBnCvbjxzQTFmrNkAN5gvdHkX6wCYIg2h4mqx3bTpZhVBfh15KxowihUVpEq7KxC0YM1CX4tj8goj10PXu2Sn+JM0dUiLjpz6808cgdb7Qsksdqb9J2FK5rk+yU8xHtnIiPLpAQI9lQMgAw6UX0iDo6AVqFb4qWzdI8M7+yfF8BxNbE/rUVNhwrwfi3VmLFwQLcMGcjMksCp7TllouUq1VPjG/y9pk/T6RBjeKalvczqrJUoU9MfSF4MkT6ntlOnkrE6Xk+nff9eVh+cjnatcjzzjvv4K677sL06dPRu3dvLswYDAZ88sknfttHR0cjMTHR87906VLe3i3ysJu1WbNm4ZlnnsFll12G/v3744svvkBubi5+/vlnv9s0m82orKz0+W/xSJ66Ik9FBRyWllenCaKlceslLo3H8yQkmINlyHiZIAii7bH9ZBmP2BjdVdyMZ+wpRvqgOFg+HIEMtRq9kkf4tDcfPAilwQB1x46t1GPiTBFlUHtSf3gkjxdsmu0XjRF2wVSf6eRaIRZ2s1jRTS37/ijsFigUTpzbewcm3CYMu23W5l047Fwqyrm7Wf/jMbQnFu0Rlc5eWnAA64+V4Nw3/wzYNrfCiAi9Gp1ifMumN0Z0iAZfb8r0iEQtdQNeaalEjF7sC0qF2LeWXbUMl+ZneEQggjhVKiwVKDYWe/attkKzemuxWLBt2zaeTuXZgFLJpzds2NCkbXz88ce47rrreLQOIyMjA/n5+T7bjIiI4Glggbb52muv8Tbu/9TUwKGdZwJdHeNlVYJ40mQrpJQtou1jd6k8nnStNhAtE8x9IwiCIPxH8dzz1TZ0iNSjR0IY90ipLjUjPqwY+zUaXjq9b8+rfNYpfPMtKPR6KFxVH4m2S0yolg8P5lch1jXu7dlzvLiG+7c0VI2pw1tvoXbZZ55pFhD0Y/pNeLmoBAaFiBRiFEMIOv1SjyImWZRaP7ixfvn2hjDX+qZ3VZa0vIHw2eTLjSf5UOV+wueHjcdLuBjERJqkiOYbn0cbNMguM+L+udvRUhQaRSZJtE6kef55zZ9YcfUKJIQkINT1tLLKSiIPcerk1wgfsHBtONoSzfrVLC4uht1uR4JL5HDDpplQ0xjMu4ela915552eee71mrPNGTNmoKKiwvOflZWFlkTLjZflk7060SXyFDT+ngmiLfjxMNzpWm6xJ5h1FPLkIQiCaFv8uisXVSYbnr6gJzf6L86u5vMjS/7ADp0WekmL7rFymXRrnrgp17Twgzzi7BCqlSNt3JFcbuLCtdiRWYZRry/H8FcDp0QoJAmJkaJqE0MVm4TuY59CWJeJyNP8jc+rlLahUu0SfOxmGCLEeOGJ5kX9S8wc2gunvX1edxwpFMfhkE71K5pd99FGLtDM3ZTJxdnmonKVbfWuznWmWZezjg97RffyiD1xBmHKHeYQr0uRPMTpsKd4Dx+mhrWt36Kz+miERfH069cPw4cPP63taLVahIeH+/y3dHUtZtjmcJ2kmPEyw9oEYYsggh23mNO2PHlauwcEQRBEc/hhWzbO6RKDSwYk8+lj2wuh0UmIzfoCO+LS0T9+IFRKWQg4et75fNjhX++0Wp+JM0tcmIjgGZkum2szRqXHoNZih8mVUvXKwv0BI3ZVCnkfCTuQhrXfH8G+Tu+iIEdUfJq6+msYxz4vGuz9ESER4jXzjlZgw0/HmvyQSB8uxKG+4zrwodXSvjx56uK+BnRj8xJm2Fdh8BLpmkq1WTwgTwhvOAqIiUCzlh1GlcmKpfsL8NuuXB751xQ+dBlsu4Udb9wiT7VFCFkEcSoszljMh4Gq/rULkSc2NpabJhcUiPKXbtg089tpiJqaGnz77be44447fOa71zuVbZ4t9KEij9gdzaNkqWaSBEcVKcNE+0nXcnvxeESeIBZSKJKHIAii7cDScDZnlOKKwXIURmWREUmpChx1VGKlvQxD4od4ljldN2dSdDTUSY2XaybaBptnTsCyR8/FkE6+Ik+IVvJEFTPmrMlAVqn/9Ki6N1q7VmRh5dxDnmmd1YRf3/0HCiWXubOpAjEpImVr+5KTqChuWtqV1WRHfKcwHnV2KsbNbQ1vUYfBjldv1A2kdQXivnFd+XDFwUIUVwc2Pz6QV4lZy47gPyuO4q4vtuL/vtmB8W+ubDQCiAmBRcbA1hlukefeZfdifc5690rAscD+QwThjdFmxPbClks3DBqRR6PRYMiQIVi+XA6ldDgcfHrUqFENrjtv3jxumHzTTTf5zO/cuTMXc7y3yYyUWZWtxrZ5tmCRPAy3+TK7GVaGhsJRTcow0fZh5UwZkseTJ/iMl+uKOsEsQBEEQRC+vLRwPx8OTI30zKsqNSNEW42ZcTEIURlwbc9rPcsqfvmVDzu8Q1E87Ql2/dw1Pqze/BBN/SgRyZXq428blqlHYVcELolulYBNepfvT8lRTLill99S6na7A6W5/suIW002qHUqdOgu0piKMqtQktM+rvvd4kmnGINn3vbMck/kTU65ETf8b5PPOp1jm2e6zLiovyzQvrboYMB27ggu7+gdVoWt299/ryc+eVNjbbgEvMHrYvGeZfdgVdYqYM8PKJl7BRZsfKvJ74NoP/xy9BeM+rphfYFVY2PiDsPqkD152xrNTtdi5dPnzJmDzz//HAcOHMB9993Ho3RYtS3GLbfcwj1z/KVqTZs2DTExwv3c+2T9yCOP4OWXX8avv/6KPXv28G0kJyfz9sEAM15meJsvSyEhsBb4LxtPEG2JCW+v4kPJdTZwP6wJJnNjR51ceLvNgf3rclutPwRBEETTYDdp87fn+Nwost8XdsOcXbEWh7UavHveux7jVIZp3z4+NIw4vfR+om0Q4icVyNHAk6aimBP4s+vcgMtjq4DcscKjB8tf8vjyMGor5cq4G348hm9e3MSvKepiMduh1kq8+pubb1/ajPZASbWlnujKOFwgMhRK/ETd3Du+yym9VqIrVevH7dkB29RYhLh0IL9+hkSFMfBN9oHSA826yX1wxYO46+DH+HtcDGYc+pxX5iL+Wry/831UWxsWa2/7/TaPEGRzBBaTg51mJ1hee+21KCoqwrPPPsuNkQcOHIjFixd7jJMzMzN5xS1vDh06hLVr1+KPP/7wu80nn3ySC0V33303ysvLMWbMGL5Nna75Tu4tGsnjJfLoBw1C7batrdgrgjizyOlawRfJ4+8C7M8vD6L3aOHtQBAEQQQnO7LK+fCVy/t6fD82/XqcD3dJh/lwSOJQn3WsWVkIHTfO83tEtG8MGldqlReH8quQGi1HmnhTYiqBRQqc/nPebieWlFSIieN/QusQ+2BdkSdjt0j1sVnskOqUdWfpWqFRvlXA2gtFVWYfca1LXAiOFdVgV1Y5BqVG4tL/CDNjxoc3Dcao9Fio3U8Cm8nXd43A+a6HiUy4c6e/eVNrtvtNEWOU1Fg8ldnqLTOW8OGaa9fUX2j1X6VtozEHMAgTae/S60TwUlVq4hF4MR1E2uXp4HBV3mMROmqluL+vy96SvXxYaiqF2Rb4PBPsnNIR++CDD+LkyZM8/YqlVbFy525WrlyJzz6TyxsyevTowZ/aTJo0ye/22I/4iy++yEUjk8mEZcuWoXv37ggWtAZVPZFH260rbPm+PkIE0ZZxp2vJv7/OoBZ5CIIgiODnYF4l1JICVw+RK5Oc3FvC/d/WxB/EQ9FDfQyXGZasLKg7dmyF3hLBEsnz4DeBfTCeHPYkRneqn3IRVyqq4DDGzfyFD1lQ8pFR4z3zjVUWT6pWZbEQAiym+ia/Fle6VnuksEq875gQEeF019h0Pnzht/2e0upuJvRKQITB/81wU0iPC8X1w8WxbA5wLeeO5HGT7FWufX+u/6po7L5y9bEsbjHgt7R1uXgf3+eIKn3+qLC4hEB/fVq/3uMNRrQuX8xcf8ai6BxOV2qgzb8I6M2478Zh8o+T+fj0PiJjqS1xVqtrtVWUkpILPW5PHj4vPBz2ysqgSmkhiOayJ1v+gfNU1wpCTx4SeQiCINom+/Oq0CUuFBpXpASLpCjOqkanpG9QKykwpu+NPu2tOTmwHD8OXY/gedhHnP1InoboEtkFdw72veli1+mX/+d6JL38Ep/WMeFm0M3I2+SbkrR5QQaWvr8F+1dmeeaxqlt1YZE8Gq3o15mIIAgmssuMXHiNNAiRR+tVLv6z9Sd82p5qBI8347qLlLdAFbNqXV5Abr67ZxRiXdE7ZbVy5JU3B/Or8NOhJbwSrFLh28d/LT2MD//Yxcd7WayYkOjfg6XS7F9AMu7dh8zb70DJf/+Ls8GRrQVY9qnwLSOaR3Pvw52u9sx3h7G3eC+yquRzQSDOTTkXbQ0SeZqIudbm8yMgRUQANhscNbWt2i+COB0+3yD/mLtDaN2/lcGkX9ptQdQZgiAIoskczK9EryT5SXtFobhuOhyZixhI6JEmSqW7qVq+Agq1GmFTLzjrfSVah9BTKM+tqRNlM/WeflDHx8PglV1g7nwTKk6IlC+ly0DVYXPi8O4qrJ4nX9NX+qm4xT15dELkufrpoYhODkFUUvPNh4ORzNJapEYZPJHbSq+0yONFspnxd3ePPCOvp3OJSNM/24INx0SKlTd1hSWWprf1mYlIitD5rcpVUFOAj/f/C6pQuaqaN+8uP4IVezM907YA5rkVZv+RPNYssW7Ru+/hbPDH//bh0Kb8s/Ja7Qkm2HSesQifrM1o8jp2p93nu79+4fW4d+m9niif9hS8QSLPKSKFR/ChozJwqB9BBDvemdHuH3v3PEcQnegcjZTRJAiCIIIP5sHBvFV6JckVldwlrNdqsjA6vGu9p/BVS5fyG3UptH3cUBONY/CqrhUfJiI4xnSNbXAdtwDjxn1zpkmV0wJLv5nvGR+/+hEk5m/0u61OfWPqVfQ0V1uhdxVekdRKpPQUVbbaA0arnafIuSO2mcjDfHm8+fmB0RiRfmb8aqJdaWE7s8oxY/7uessLKv37nvRPicCiPfk+N9611lpM/GEilmT/4Hed77eIqAydQo4AUlrFOWf6H3Z8/5oN4TXOBtO1iufM8Yw7Lf4jiVqC9iQwtARbFmb4GLKz/ZixcE/glLxAn/FDKx7ypG5lVmXy+QO+GID/7PwP/GGxn7394ExBIk8TcZ/c3TuHFClEHnu5bOZGEG0Nb09L2ZNHDIPppybQ7x79IBIEQQR3xECtxY6eiV6RPEVGaDVGHNY7MTZV9kphWPPzUbtlC8ImTmiF3hKthTuVj/HN3SO5J0tvr+gvf2j1sjA0eEpHT6lzxpZXrubD8p9+81mny/Ff623H6jBjb6bvtbyx2spvJg0RsuGvWiNxg+b2gMlih14tyfc0SgX+7/xuPm3qVt46HdypV3UFPTdD06I8/kBju8ni3oX9kpBRXIPfduf5mG4HIrfciCd/FCKSDvJN+TMHNmCQshMu2Cbe76BjTv5A81/b/gW7o/53qunQQWyjTx8c7D8A1auEcXRLY3UZUP8VqakwN3p8bf4tA/nH5GO12iTS/DTNSCm0uyJ5mLDjLpPOPOHW5Qqz8Y92f+R3vVHJDZddD0ZI5GmEDbkbkF+Tj16jk3wOQClKlPq0lZa1av8I4nRw++/4pGsFYQn1QIpTQyVWCYIgiNZld454Ut7TK5Kn8EgBSlWipPqovjf5tGdePIyQUW3vgpo4PVhqDoNdeuRWmPDeiqMNtld5+fiMnNbFp2pTj3Mu8ruOO2XLB6cTJYd8RZ6CE8KrJSRSFidUWqnd3ISzCAidRsLVQ1NxxeAOOK9HPKYN6uBJqzrTxITKJew7xDhwzW/X4GSlbPC85kixp1S6u+Q6I84V1fXQNzu4WXS1pRoXzr/QZ9tJpv/zW25dB3k8XOqNGa/I6Xl3ZVUjttyJYmMx1ueur9ffqqXL+NBWJKqvZd0j0nlaCve+y6xB/oqwaP3PnlqH+W/VN1uvey9irLIi/3gFn1/l8nJS16mM1xCVFtmH6ZPti/lQK2lx37L7GlyvLVZ6JJGnAVgY16ubXsVti2+D2mW+5j7Bq2JFCKO9pLhV+0gQp4P3OUtZN5IniPQTZqznD5ZbTxAEQQQnC3bl8pSL+DD3DbwT+Rk1yA7LxJVpFyFC5xstULt9Bx+qk5Nbpb9E63Hf+C7N9ucZemEaBk3uWO8GLFIb2SSRZ/iWl6GWdNCbnLB5mQLvWi5SfqISDD4eQKziVlA9ADsNkUevViJCr8Y71wyE3iWYvXfdoBZ5Pa1KFuQ0IZk4UHoAPx75kU+bbeJzt7ke2kV7CUKsf24KKsyYuXZmvW0fzZWQ9vRClFSbPdW7FE4H7ps/H7nMdLv3ZbBW+KbaaHYbMPsD8bo7i3YG7LetsNAz3pKVtpQqsf/W1unnXwW3uFWUWcVTJb0pzZU9ohgrN2Tjx39uw7KFx7wieZomwFRbqn2mPzr4vEfkqUu3KN/ItrYIiTwNwPLEHx78MHKqc1DtrPS47fNlOh2UISGwFQcOGySINpWuVeds4GgDkTxUdYsgCCI4YTdvf+wvwKReCZ555QW1sFiVOBp1CBf1uNKnvdNmQ/F/hB8CM14m/lrcPLITVj9xHhIjdE0WekZcmo5zruhab35dkWd9L9dDLIccKRFanY3QGjkNyGIU1/fVZWbkHBJR+hqvlDBWvYs9WLJZ2/51h9GVrlWXcT1EFayW4MTrF/G0rSX7c/k0S5Oa/edR9HhGRFMw7hzTGdcPE+XWGWFatY85s7VWZFW4MRVcBIdZnF9OlNTCtmkjJp7cgm7l2XxeRYYBNqcW9uoA5bKdTmzJ39Kk/tsrzrwHq1swDHGlBf7wxtaz4kGZWZmJHYVCUA8GvCPkHHbfC352PHpj2iOi7hasy8Jls9c1qwLc/COyR5c3paZSz7hBJYTduRfOxcprVvLxvjF90RZpvp39X4x+sf34MNPEnN8VXMV3o4qNha2ERB6iLaMIGMnTFjKh6v4YEARBEMHB678f5MPeyb5+PHwYkof+cf192levXs2HMffec1b7SQQHLBqnY4y4wZo+Og0/bhM36qdCQkgCtiQr0SVX3DDnuPyDFXAiWV+IXGM8uh2Z57OOxWiDIVyDoqwqv9vUhQjBwVxj5f48bRlWytwdvRMo4qYlYJWyVGHiOzHZTPhunVwV6fUr+uG64ULg2V20mz9gHxorKu+pIzfip31pUIUVQOvSoYzZN2BK5ylYWJrnEZWjnvkbHqvzmvO2FmBilX+RR3IAPTXCfqMxnKYAQtEpcmJPMRbO3o1xN/TwnBcZh7cUoOdIXzHrTHPpz5dyb5o9t+5BsIk8druDG527cd93fxxmwh1VciofWPSPHs0SeZJDRYRoquIyZDl/8dtm4w0bPZGBepUev1/xe8DIwGCHInkaId4Qj1B1KPIdIn+8tlIOpZOYyFMs8jUJou1H8ogJlWtoC6KKVoGCiiiShyAIIjjJKRM3Lszvw015bj4csOP8qLh6IfLZ9z/Ah7H3tqz/BRH8aFVKWE7zIc7HN8pRKb8Nl293ItWH60X1eKeMWF0+H/X6ZFC1G98U7snjJ5KH0SnGgK7xoS3yui9c2gdQiBv60toaFFfL91Tn95LPEzcuuhFPrn4SsaEansanS/oZ+o7/AxTis7efeA5Pn3ut5xzDcKdq1cVhlVCTLUeDaMLllD2VHaiqbZrthsN45kSeqlITF3gYe1eJ+0s3pmr/5d7PJG7z4WAyXQ708LbCVXmtTOlEmVL+jrubJYQ4mify7Czc2WCmwp1hF8Be5uu1mxKWglBNyxwPLQ2JPI3A1LxYfSxKlQX8hrimXN4RVTExsFO6FtFO8ETyKBVQSwpYgkjkcedr9R3XAcMv6eyZS5E8BEEQwQdLQ9ieWYYHzvM1xN2xbw1qNZW4ffCDftfTDx3C0+GJvzaSUgn7aXqgmKNkPx2TVt4Hra4KPmqb8ProdeBzTyQPb1sthudc2TWAyNPyN+GtKfIse3Qcfn94bIu87q3npKFLvDi+f9+fBSmECW4OfH77cI9vV917sIcnpokJpwSF0oIuEd1gMul5JFKtRRbcpn/qP+2q/7LDsBTaoY20ouul+XDa5X1BbQOMdlko8od+wADx8uYzJ/JUekXumKotUHp5ykjNMBFuDtkHS1GQIZsOM/xVFmsNqkt9RR5moP2Pn/eitKgWm74XBuxOBbystAX3VIp9ZuPxpt2Lf75fHOs6e7rf5ZNn/oYj43wrPrZlSORpjE8vRGx5NorMRdAa1DDVeCnAsTGUrkW0abyuvT0ij7scoSWIomTconvPUUlI6hLhmX82cpcJgiCI5mGyOjCpdyLGdZefzsNYjsziEkiaSnROn1CvdDoj6trrznZXiSCEPZh3G/GeKjqVDusfm4BDb9/hMz9dt4kPtWbm7eFEbIlIWTG7RB4m4rC0rUGTZG8Y72pev767q81HERstDr+ePO6oiKZGRpwKNklkQKjDd8PQ8ROkpBzGuO5y1JW7rLWbYxWiKpbDEg0orTCaldxOwGpzoMYrzadbmTDLrovK5oDd6ERUlxqoDQ5Ya2SnkglVRhjzdgHVssGy+75O202IfKp4cQ5znMl0La9r75oKC1Re6Ukt8fAy+1AZfpm1E4s+ENFDbsrMwVEh2vt4Yu//i/Un8OXGk1i9XqRsVirE8miHr8Gy5Pogc8qNPpXVGiPE0QfqzDd85j0237UvWdu+iOuGRJ7GOLkOcbUVvMyeNkQFc43NN12LRB6iDSN5CTvudC2GhodKB9FFjOs3j3XX+4mHnaprEQRBBB3sKftrV/TD8M6y34X52GrElp4Dnb5+6Ltx5y4+DDmHSqcT7kie0/t9Zz4aszSr8I9i8fTeTVfdBlxaMxuSwwp1iB0qm4mVTvKK5LFCF1rf+Nt97cFuSL2tG9qsJ08Aked0+HjPx9hVJI7l97a/x9NjWMlqb3PjQuUi35X0h9Dv835YlbWKTw6fO9yzKKMiA1UW4ZHktBugUFiRXy5uxvMqTJh942BP2/dWvRu4Y04FVMmpQLpvlIbB5oSRXfuueQcoFhEjmXfexYdSlDh3KcPDxCbOoMjj9qAJi9H5CIgMo1cKG3uQWdd4+FT45V/CZLnufvvW1rcQfCKPPG6ptsEOJ+aEi89A5a2O+dmnGzO47hbVDTf0vAHrjpbAYpNgrRS+u4wRh9rf/QSJPI0R2x2xdjuKa4u46ZrJK0xTFRMLe2kpnPbgCHcjiObiHUbvHdWjDrJIHm+8S6VSJA9BEETbYN2mFXyoNfpW8LGcOIGcRx7h41J000xQifYN8wY83UierpH1q25VjunDh9Vb9vNhaAcTN2OW7GbutXNyXwl2/5ntSc3yRvKKbvEYxW7/AtgwG20JdsPL07XOsHk02+6s7bNw37L7kFedhzl75uDm32/G6G9G4/Ylt/PldUtYMypUG/jw3R31RZo7l9yJo2VHPXEbLJLHZhffzeBOURiYGom9L0xpUv9UxuOALgK6/rLhe4jNCZNCCWz6APjPEB42bj4qXk9pEOl+Ulj4GY/kce8/fcYKI2CVRonuw0WVsG2/n/S0W/fDUXw+Q1SQ8iZzXwkvN36qdI/qzocLjy/0CCDBFMnjvsyvKDWiUumEO4BnocGCKoX//ta60jDrsjZnLfp/0R8FNQWw2C1Ysld4MKXFGmDKvRbnJV2B9gqJPI0x5VWPyMPStbwjeVi6FhwO2MtFOTeCaMuRPN6CT2GVGbOWHUEwCjwKiuQhCIJoW1QXIiNLGIxOe0R++m4rLsaxqRfw8YgrrvAR8Ym/Liyy+HQjeTqEdvCZvmaGCneOPeQzTx9tRfzACkg2E6/is+Dfu3wqaXmjVMn7ps19Q/nr/wFLZqItYbU7+Wd7piN5qq1CwGHFaib/OLne8rkH5uKXY/4rGjHKTfXvpQqNhXhjiyutxqnkkTx2uxpXDk7BlD6J4vW0Khx+WZxDGkKhcgKSBh0/+QQp7wthLiJxKmD2OuccWYqQYcP4qH7QID5UhorIw5fn7zxjDz+tJrH/hEaJSB6ms0y6XQiQ3mQdLPN5oJm5vwQrvjyA3/69C9+/2rTS7w6v48i9Xyu8ImKKjKdYQOibG4A9P+BM4J2iJkQe0T9jpQXVLlHnppEd8d7TY/BhhAnHmGO2V1U23jaAyHPfsvv4cG/JXpysPIm8CuHF9ciE7oBThQuS7sFPl/6E9giJPI2RNABxdjuqbCyXU+HryRMT47lIIYi2iHeKlrfg407ZCha8nzR4i1EUyUMQBNEG2P45iiw9UGsoRVyKXFK9+P33PeMJM9vWzTLR8iLP6UQZsPLHflHKAk5EmhFKyQml04bti+UICn8v650q7l3yua3Bypgzov0IWacDi5hgqJT1o6AYLI1rT/EeaBAOc/G4esvdYkNauMtouQ7qiJ1QhR6B0x4CrZeHTd3r1T/PkUVkb9j3jEv/DSk0BOoOKXzeiHdWYsZHXte+pcegG9AfquQkqGJEVKEUIXwgS0oqUFpzZtL0WEoWM1hWu6KpqkpElFC3YSKap+41rs0qhr+9twsH1omS8U3FLUgmd4vkvlNOhxMlJtlqxJ0OF5Af7wQ2feQ7jx0ghxaKZWcAu+v9MYxe1e1M2bWoVQJzbhmKl6f181R9q1XKB+jIdHEvXlDVcKTV3ANz+VAKOc6HyZHi/FBrcaBrlG/Un7Od+PIEz11csBIaj0SbOEBsKPdx1XebcdkKZcMugmhLeD819TZevrh/EoZ2ikLQoZArYDAcFMlDEAQR3Bz+A+Y/X4bR3BXV0b4PxUyHD0M/eDCS33yT33wRhPcDqNMJ5tFKWv8L1AZ0fOJSbOvZg0/aVSpeTt074sHfAySlv3StNkh+pbgZTooIIIKdIqzkOcPh9P/wjYkJWVVZiFL0h9MmfG7qsrtIGAPf1uc2XJx+sd82TlsIvt6UWW++duBAPrwvdQG6XZbPK2n1OnjAs1wRGgOoxXtWaGSBS+e+rYvpBpRnAjYbFJIKjhoR8SFFRcGhUEJjt3rSiE4Hlma18efjPEXJe59jRCeHQB8m962iUJhQz3lkNa+OdTpRMuExOi7wjPrfWO4zG8jouh575gG/P+E77yOXt5HUuFBYVGWGrZEHsu6Kd4wn5u2E2WpHqAMIcSrQwyphbLdYz3Im9GzSyvcBCTo1YkO12Haivon0ouOy/5NOElFT1goRodUhSs8rCbMKbU5XJT9liPgNqvzjD7QHSORpAh3UQsU1OUu4IZsbVVwcd4IlkYdoqwR6SsY8eWxBVJ7c3U32AxubGga1Tjz9sFMkD0EQRHCz4d/4LDQGMbUd0KNnJ5/fH/ORowg9dywiLvF/Q0f8dT15GLbTKKNutsuGtTtu3oFbe98qokTUeujToxDZT9zcKlUsksdXtPFXxto7ithmaZvXHkxU+Hz9CT4eaTizkTyNiQbrctehxlIDhVMLySD6UJclJ5bAZDfxymh9Y/v6baNQWvHmVbKvjhuVBghLNfLrRJXeAXVcjEfE4+tpZdFPqdHU33CHwcDRZXDa7FCoVLBXifQzKSwUJkkNjd0G6ylcc3pfZ5fm1fikWdW9Bme+T4Gqa+1bm9vs1+av4RKSDOXb+VBjF15Dfr8vYxOrbeXtrBcV5w/2eQ17ZRle//1gg+2YIbRSL67rTxTWosZih57VTGeebToldF6phQsfGoMNr04BOho8x+LgjpHYkVW/7//Z+R/PuNNVwcVaPgIpUXpE6NUwaFT8tdym2tF33M6HkitFr61DIk8TSLhrFVTMMMxZAGON1XNQKtRqSDExsBYUtHYXCeKUCJTzzi6wrKdxcXXG8XRTwXOKb3n5HD5FkTwEQRBBjqTBblUPSE4J5w+Wq2exB2SOigpou3Vr1e4RwRvJw65RWBTA9R9txDtLDzdrG5d1vQwvjX4J22/azlOIDGoDaq21XOSxm6txsbSRt1MrLVA4GhB52DW/qdJneVuN5Fl6oAC/7BRiQaTej9BxBig1iYiT8am+lazc5dBHpSdiQLivqPvqmFf5cHX2aphsJh51EUjkgcKKMV6RHW6c+Qeg8DblPf8ffGBTu3xovCyIFHVEHh4XkjwYjpJMVPz6K9sB4ahypTGFhELhdCLKXMX9jJrLhw+uxC+z6le3OufKrp5o+qEXpnlSApkB+JI5e+tt59i2UwsocEcLSdmiepnk8PVi+r8V/8eHy/61GN8/MQ+oEGXLmwRT1hrgRLGIhlpx0Lfv7HOoqZBF2NoKCyRXRbshqZEorDThPKOYnnqv736gVUlc9Ln8mp6edLQeiWE4Vihey5uCmoJ66YRwqPDJbcM85xnNd1/g0OAhfFqdLIyws+65F+0BEnmagBSayFO2yh35/KbS++Suio+DrYAieYi2ibfG41a5Gapgi+Rx9c0dKus2QKRIHoIgiCDG6URh/i4ch3gyGhIpQuYZ5sPC3J9EHqIuKqW4PWE31ceKarDheAneW34ENV5+HU1J15rWdRrUrpQSg8rAoxZ26g2w1wqTX6tk4Df/zJPHm5SeXunqJ9cDr6cCc6/BFY8N8jVedlOVj2CGpczMWnYY93y5zTNPV8fX5kwzInGEZ/ye/vd4xuNDQ/HNLdf7tHX78JyoPMG/IxbJMyBuABZevrDedp22UESHaPxf0HqnU0V35oOywSLqR1md5VnkHdXDuHnwJKbsoeygGvaSEliOHoN+gFjPmZwCvd2Ca478CZvJJfwcWFBP+AsEi8zJdhkou0uZMwacn4LOA2IxeGonDJnaycf36ei2QpQX1Pq+71O8JHdnz6kUQmBSOoXI4/5sa6w1/PUOHdKgyNYVKHFXM2Mn6frV0HyifdSBU2wX7s7DpH+t5uPaOibfnz65Fp89tQ5bF2WIPpSb4dArPdf1RQW16GQT66R5ebh54/YzYpE8bH9gaYiPfS+M090MiB/gZ00JOpVYl3ksddkgp2ap2ll1RxJ5moJSiRSnhGK7MAXzFnnU8QmwUSQP0UZxeP1qeP+AsDzVUwlLbTGc/kuZOoK0zDtBEATBHtGWYKXCCL1ViDw619NahvnIESj0eqhThAkqQbjRuiJpzDY7L/ft5nSuS5gRc5W1Cjdrq7CkUqSP1ET35oa8Cq90rTveHoveY8QTfU6RK9XkyBIkGTJ4ujgv+fy2iCTg/Le+kXAw8dKC/fUqpp7pSnYhdW74z0051zP+4KAHPeOZVZlQKpR44ZwXPPOSQpNwaZdLPWl2zLuH0TG8I14Z8wrWXrcWCy5bhtqTd8BSMp5Hc/hLS2LV0D1ECeGo5qIJ6HF1LhQXvuZZpNTJYjOj7MhBOGxyahMj/MIL0WPbVjgi5Rv/lPmXs9JYwHc3Ap9diFPl6hlDuccTixgbNa0LVC7Bwru4z9bf66e0aQ0qlIXUFxR/OvITCmv9Bxw4XFH5KojIGckp0tdSw1I9bdbP9xJ2jGWoKjUJkWnuVfL8kmOApRYol8UyxAYW6Bftzat3PNd9j5t+dYk8lRaYNaJNRK4ZmUWyuKQLkFbIys67/XyiDEL0+3F7dpPM12NCZZGwSB/pGVeG+veKaquQyNNEOqgMKHCU+pS+Y6gSEsiTh2gXIo93pS32FM12muVLWxL30w57EEUbEQRBEHUo3I81eh06qzpBpZarybhFHm3XrlC4ojYIwk2oTtyIVptsPqat5tN4sMPStdycrBI30HZtJBRM5HGla41K2wDdm7EiIOSXB4C3egBWL8+SOefxh0x2JjxVeVU5qg7uSJ664tiF/UT58TPFkbIjPCLEmyhdFL656Bu8M/4dn/kRGuFzekW3KzzzonXRPHKH0aHYiTFRQz3LmPgToY1Ap8gE2GuZqOC/9LvTXCOna107F4jsyEcrk8/FHY4n4BjulYLjSuFy8685dhya/jaMRb4RQsyI12J3oFwjBCx96X7A7WGTv8fTjkV2ffTwKuQdrV8G3pv4TmHoPToJ8Z38R6ckdZUFh0Mb8xESqcX0f45BaLTWc+17Ikp+3S//sQHFeZV4dt2zeGzlY02L5HGlazGRL0wjRA2V1kvwqy3Bl89swNznNgKZG+T5/x4MvJoE/HesmA5PAVyfiz+qTHJ03M4s+XP5+LE1Pu0s7Bg327E6W9xjp1QDCV6HnMLr3sQbtzDGPvtBHeXPzZtqSzV6R9cvTR+ilSvAlelkYUdp0MMwfDjin6hjNN1GoV/WJpKui0cmKuq5gLN0LSuJPEQbheW7p8eF4K2rByA12uATydOYG/7ZxKNFKeSTPvsPZFBHEARBtDIOB5yfX4KdOi3StT2h86oawzAfPkypWoRfQl03YdVmZnYr/86bvUote2Oy2pH29EJ8tPpYwG12ieziGa9xpWdVdL2MR/IYXNWGDGUuU1xzFbDjKyHe/PF3n+1IKgXslgBpY7k7gS+m8X0/mGCfjzevXVHfuPh0uOJXIdgwMcZNqDqU++pM6jTJp+1Tw5/yjH914Vd4YOADPLKHiUJp+U4uuMRcInxi6vLLrg/xrzC51L0bh8kEU4kGdosSuGEe0Ev2/AnVq/GnfRBqvD6DQFFMprL6USNM5FnacRg0Ya7vnEXy1KG6zMyzPPauyUEgmJ+rscoKnVcUSV1SekRhzDXyOTEsWgdDuAbRSaEe8++tyUuQGbmfT1cWGfHdC1vRN/9c5Nf6Fxrd0UkzE8Q2epgdeDy0Nx9/efTLfBiTJl//OysLPOtYHQ147oQnAXavkvKWGuC9wUChqGhm9SPIvvPWpnrz9q0WHlFV3mXRTY2bgrsjeVi6VkfX/cvwNN90q47bRqJ37UhUH30CtVm3ofrwP3Di9Ys8y/82sTu0NotPhFenLz5HjMuAua1DIk8T6RHRGbUqc/10rYQEnr/ptMrhZwTRVmDncXYxddUQ33B5FU/XCiIBxW127pVwLUkKETJNEARBBB8Zq3BSpUK5JCHClIjIeK8bCbsd5mPHoO1OIg9Rn4RwkU6TU2bE4YIquZpzjnjY6s9zhvHqosBVfHrH9EZiiIhgsbsvJfpcAcV1n8JQK6JytArXa614KeB2lColHLY61/zxrmiBpf8Ajv8pR3sECcx7xJuW8uOpMFcEFFJY2tW9A+7lJthuWPQOm+cuvZ5Q3vB1pybjKHrOnV1vvnmb8H6pLgwHuk/2WaZ3+cGYAgiE3ijV9dswscIsqeGwud7PB6Lwhzc2l4Ck8kpLWvn1IXz2lMvsF8AXf1/P06C8U1b9MeB8OY3KXejHHb3OUrzskhU7k1f4rDPy5CVIUCbz9nUrdrmNl21Ksc9qlaG4Vd8RFbvWo+A3Ba7Z+QTyti73tF+3Nd4z/suRpwN3NDTBV+Rh3lWlx4DtX4rXqyN0MhFWe7S+ObI7VSxXJbcPdVXWmnJXAPPtOpE8bF8b3jmaV81yU3iyEonZPRD7Z384rTGwV/eE0+4beXR7igPDCg95bVTeN9sD7evdtCCdonvAmi1KxrGwMu90LXYDaisq8rhyE0RbgZ38lX6eaIh0LUcwFteqc6EVREIUQRAEIfPlNGzVRcJhU8FWokVorxBYXPcElpPZsBqtPpE87mX+YD9T3hkWzWnLnsEFMi1tqbYM7wI+zWlrszUcCNKctqy/7p/4lmprt4v/M9GW3WOx7L24MC0MKgnfb87FioPM91Js4P4vd+DIK0lYfbgIPZJDkRotbupYX50u5cbfvuHebpeILsirKoTZpobFrkZiqAE2bTRi87YhIrYYSbF74HAqoNz8kdiuUwGbw/dWyQkFTLUOvr6ksEOKTeOpW46lL8JmtAJ2NeCVquJGksS/u7/sMw7EqbZl+5i/Z84qSOLzUQjfGuZpE6itG/Z5ue95G2vrtEtQSHYMjh+MbQXb4bSr6n0PU1OF5w57L9730p52Ng1qlWpYXPlFbD7zSlIp7LwalsNigcWpBux1vuMT62HZuxRWpwrpL/2t3nZVTvHeK2vsiHD5LbP9MX3hAlSvXIXCN9/k67Lv1VIhDvCU997zrF9jcsDBrjdd+5e1uhJOuE4Er/cFrpyDamsv2OwKOJUSDwRgn/G+1Tmws3mufbe8iG1QAaVG7dl2oHPElHsHYOHs3SgvtvC2BZlCHHF7Dplh4a8no0W/1Zfjvd9XIjYlFDc+NwzLP9/P32jfcam8rRFmmB12DK9JhKUwC5/9JITRKGUKonKOoCaFRfcrsO1oV89WC7Q9UJYTgpBE0WG10iqO5cR+sB3bAAczn64x8op12DxX7PuaOMAiTNM9+wf7Stmx5NNnGUnpRLUSiO0ZicL95fy4Y3TsF19vP3Ifyyz9lx0btTUO3oZVbzSanZ72FWVW/iDbpDP69MF7e1n3PgQr26cGDkZUfCQP3GjOeaqx47NOEbezDok8TSQxohPiHOIg862uJRRP5stDIg/RFj15/KW7MuGnoNKMfbkV6JMsh9+2Gq7fCm89iodMB1FKGUEQBOHCLq56P1z1N1jD4/HjySQkn4zCGpf3q/m4HVFVF+BvXiLPm28GvpFMSwNuu02enjULqPUtPuOBXYrdfbc8PXs2UB7AKiMuDnjgAXn6o4+AIlFjox6RkcAjj8jTn34K5IpMg3oYDMCTT8rTc+cCJ+r7qHpEkL97ZQR99x1wxNcj14fnn5fH588H9ovMDb/MnCnfaCxYAOwUzyr9wmwoQlwPupcsAba4Mpf8wT4H9nkwli8H1q8P3Pb++wHXpTLWrAFWrgzc9q67gA4dxLimLB6L1obDbPM1Q73kjmJsyihDzKB9OPZvUaZ75w4FKjaIm9NXXnHWiyK54Qage3cRXWLK6obVG8fgiupUDGWlsiu6o6TwVmA5EFcwBFf3/hl94kVE0IGiHpi3f5rPtvaiA8L2q7Gy7DFM67kQA/t1Bfb9hKO//oyv91wNYJzrZtf3vV14ITB8uBjPzAQ++yzw5zBpEjB6tBjPywPmzAncdvx48c9g++7779dvs29zB1RUxkDboQz6ziI1raJCHEeBGDYMuMiV2cKONXZ8BqKqdBzCh6xArD4Wv1yyCG+8JuFVURW9Hr17A9dcI0+72zmd42FYOAMflRRBm56O8FeB6HVfYlLWG+h18AAclZX4pPR22JwqRD5cCHWCa6dauQqW6niEVl6MxzuKKlXe54jc8hBUbO2KWW9JiAllXjFW9EhX4+67u8C4R/jbfFN2Ayod8n4Wt2E84LKjsapVUCqdcFiUuDM2Hl0X3IoqowFqhasE+NY8lMcNwOEdaThuC8WBNasQHisi0TYcSkJFrW8lr+NSOKL+bPgcYaoJx+4dwjg6+1Vg24p4TB18EpXFJqAbywochSW7xfJ67ABGX16MgxtE+lZGdRqWsL7lXIlFJSlI2z8Re9S7sKVKrD9l0Ak4FSpEagqw6lAfZJfIn0NExXGcjHgJFZoYJKgP4anRsxCiqQXUBizZNwRbcgcDa2YB/a4Bqu8BMnoAhROA1UCl1/5vOhkLS3YUlphllTypSwTyjonIr3P7MMNkI/pP7ogPVwBHckV1u7JXA58j2LGcWRqJDz8LQeIq4NC2ZChUCrx6XLQry9chploHTWwVksxq5BWE44K4oT77ZdHeS/hQm9Ud9740GQpX99hu8fPPCMjVVwN9XMF7Bw4A8+Y1fq5uDShdq6kk9kOK3SXyeCn0bpHHSmXUiTaI3en0MVx2k1Murp4/Wu06W7Y69R+BsrBVqq5FEAQRjDiBy95HaWQHxGhiYbc5odHJhqm2khIo9QaomMpCEH5gZY79GS1vyhAGrd7LmL+gZ7yBkCmJ1UtnD7igwF6HKLGt0MopHtYaL1PfAJV5JEspbN6pP2kuI1pvvKp1BQPeURVz75RLm59pxqeO51WbkkOb/9Cb3bTrcsV3y8qZM0z79vFhzqOPonrVKk/b8nnfo2rFinoftzJCiAPeqFzXuKyYyImSGny8NgNZpeIa11YYQNGt611ZIbx2kvdosL36ahysnQAHixBiESeSBqZaq6cUOIOLMQHQhzUe3qELEWpDeIxvFTA3FqnhdMCF7+/2jFczrxwexMJKzDu5AF83Ss/BUugU9RV2FklVqe2MLMsAFNvE8eLxrPJmz/dAhku9dQizdHeK4DVDhR2Ed5LaPrWNR+K4qVKIDsWF+wpijSGpJe7NyVLUEvOsMJTLx53ddX7Q1mpxU7UOU41aTxpoXZzGwN9XW4YieZpKVBrSkvrCsr8aNYUl7FDns6WICB6zZS8ra+0eEkSzYddC/gzoalzm4jEhzTvhthTuazbvvrJIHjJeJgiCCEIkNTDoRoRcPAFXxd8AfK/GJQ9FIqWHWJz9+HdwRhb7nNMbKmhS92fKO6KmsbYsUqehFCxvWARQU9tOn95wCpY3N97Y9LbXXtt0394rrgCm+Qaa+OCdXnbxxSKapCltp0wR0SRNaTthghxJ0ljbsWOBc+pbmnjwTuOJ71KFPE1gI1t4GbX27GtHxCjh7fHYE+kI0Sr9bpcLCalHUBShhDO7G490cjpCcPAnkZ6FSqBnTKYYtxnR6+Y7MFOfCHSfCrwmrvuXlDtgThqPS41v83QtGGL4/K7RxzFz7Nti3XumATvmAuc/A6jFjaU7pYrRsaOIsgqEd9ukpKa3ZZqpv7ZL3zoOW5mR3+QPTB3C57Hbl4a26130jkWdBGprdVjxw9er8NSwp3BJl0v4ft7U7TK82x5ZOg+24mKgFIi0X43KsN/5/MpFv/P/26O9dqYCoOdTO6Cwv43yDD3yayMhRd5f7xxxrMiGhbOO4qY7Y7E9swx/6o5ixBQWrSJ7hF0f9TXsCoVnl+o1Uy75vjnDiJObhGARVeXEmF65rseOw9Bb/wfGnb8avx1LQbamzNtRgDOqR57PI8rzb+mJHiPUTTpHlN+RAEOEBhod8EGOa590ETpqAaZgAprCL4rbMW3Q31DV72uMP6rDWOUa9DcsxBdFwzypUnlJo6A1laNvpxL06cjucQUp2WvRsZ+E9WUKqBRh0Ktc4ZOF+zGlTz4mdfmz3uvlDNNh/Jp86F3H4CMTu+O7zSsQ26EUU6rEsXA83Ijc6FxM0YsT3VGtzXN8dk0sR3pCBS5/bDAS0xs+R/ToVI1uw0oxcGIoPs4VYVC9Otdi/PU9sXNVMTb9YILSKES1kd2suKHOfnnwpy/gNJmgS+uNrl1FOiGjXz8RcRYI7z706tXw/t6akMjTDNJSRmO/rgQFmWyH6cfnsdKfTOixB4oFJogghj2hkPyIPG7jNlZlKyjwc3HMDehI5CEIgghKSk2lKLcVIsWRinzJiYSOBk/qkPP4QYQMH3HK/gXNaVunWnLQt22O92cwtPX2hDmTbbUaJS9v3lhpcLWkhFPh8LRVSI6A+wdLJ1IoHVDqKnh70U4JjVcUg71WCSlMPOhS6kOhGei6+bt9PvD5JTCoamHJ2wVNjGsdlau8tcIJjeSat+czYNuHQKcBQH+WwlVf6PDbx7KTQFSnprX1A7uc89fW7LChT0oYusSHespHB2rbnO0yVpxYzv14fs/4HTf1vqlZ22V4t1WW5EHjuuysnfc1VHUuQb2/J0b1t18iRrJC5VDzz14RlVJvu+EhzC/ICZvCDjvz95GcCDGInVDnupO3a3VYf84bGLjzXUSXH8bhogpc99FGbJo5AU6lA9cNWI3DR5Ng1GoQ4bVPZtmGQWPYgYr8Kqj87KtSnXmRMdqAn03dc0R8qixChUaoYKqW3zv7vP29nj80ChVv69DWQlLZIUWlQWFW11vfrIhEWG0uakOSxHqWSji1BpiP50MVy9pqYYUBWgihR3X7z8B/z633ekaTOLZMNjuu6p+MFW/vRLJDAbWCFXVxVe1SObGnqhpTJREtpzonBtdqVFzkYfu7Ek4kpoU0uh9pdRIcFisUkD+PIxtyMfnWnrDaTT52FImdw3y2x+5zNA4TnAorYi+d6iM+Nuc81Zzj82xD6VrN4Jzul6NCV4ysDN8UFhJ5iDbtyePnLGBziSfs4ilojZclBaVrEQTRppg9ezbS0tKg0+kwYsQIbN68ucH28+bNQ8+ePXn7fv36YdGiRT7L2YXqs88+i6SkJOj1ekycOBFHGjJ0OUuwfr2/U5iDxDs68NB8VgqY4TAaYTlxkiprEQ2i8apUtPyxcX7bLNtfUC9dq6HKoE8MfQJKqOC0+0/bYBTs8PIh1NX3JFQx01tm1upG6UfBc7jSRhzNqLzLyq+/2x84uBBnmlqLHVcM7oB/Xz/ojG9bpRCiUZW1TgrPaaIMC4N+4MAG21gyMvjQYVNCyUpq+3lo6a6uVWu2YdYycW7Uuq5tQ8eMRvrvi3Dw1cf4dEmMqOb07ZZMVJttyCiugcXmgE0loSTegTCzb4nuaFUWoAmBxWjD4Dg5nYzRR78EWmWl37LfzeWG5wKn2GmGVcLsjrDxQ0xtsqe6FhOsHF2nwOL0n4o4YI9s6BRSkwuLNgLmYrliWqHVdc4eejugc5ly1cFudXkVsWgxG1BRZMQwsxoj48PlNq6v6ccQM///1w2D8cZV/T3G0gypCfcfsalhyM+o5BW26mI0yv3gr1mnUIujpoZXxk5++y3ETPcyfGtHBMcdXBshNbIzKnRFqLCJEoxupMhIEnmINmy8XP9H0X3BpPTnytyaJdR9jJeVPA+6brlIgiCIYOS7777Do48+iueeew7bt2/HgAEDMGXKFBQW+vf0W79+Pa6//nrccccd2LFjB6ZNm8b/9+7d62nzz3/+E++99x4+/PBDbNq0CSEhIXybJlPrewx8d+g7jE4ejcoMO6+G6E7NMrH+22zQDzrzN5xE+6Hay/+yS1woQl0RKN5YXMUXvIWdj1Yf4zfo/jCoDYjTpkEVchxKrf9UMFV6f16JJ397OGyG+kKkpLDA7nQ9ur/lV49/jF/szRB5KrJdbrCBy8CfCuwayWi1w6BpmeSNKJ3wwXlymJeL8CngrJOjqAwLhb2iAtqePQOuU/7993zosCqgrJOiV1fkWX9MTkPyvmrUdu6Mc9Im+Szpd/x/+Fj9BiI+64rN+57Ha9rhqNEroLfLkUKMHEs/ZGbruIDgrJW3z9AoayDBdz9k58GSajO2nnB5DzURt4+PJkS8x84Rsj+ONKIUv454J+C64SaRTmhVmuGAA06nBMvwR+u1S8leCb1J7pfOVAa7pIVRL5dU/7XM5SQcngzo/Ys8/Y54CUVK8dmPTovGuRG+BuqM42oHHImy4OqdvusuG98QMR1CUFlshM1S/4GvqY7I423vYK+sRP6LL/JxVYz4fNojlK7VTOwhVQixRsJaUQa1y+BLioqCrax5ByxBBAPsN9WfyDOsczSWHyyE1utJWnCg8LlwObypAHGpYRg4sWOr9oogCKIx3nnnHdx1112YzsxcWOWpDz/EwoUL8cknn+Dpp5+u1/7dd9/F1KlT8YTLrOall17C0qVL8Z///Ievy86Bs2bNwjPPPIPLLruMt/niiy+QkJCAn3/+Gddddx1aC3axvuTKJYiQIvC/79fyeRZX7drq4xmwsAcMKb43TO7lgban9spnaE5bqzXww4CWasvQeMXwN6etzcaMUR1npC3rr/vGqaXa2u12/n8m2qpUrJKRuO7YmVnqqnssvm8WCFblMrjlKCVuwnzZwA6wWG1wugSVj1Ye5k/xn720j9/t5huPckFBqc707EdRM2eg4BVRdkc16jJY9q5F2eFQ2N7/GPEvviQ2YmHl0Z1wOkww2ZWw2J2QOo6GlLPZ89DME1xstfG2WDgD6Hc9nyVJEv/nbR0O/hn74F7HYoVktzfc1gvv7bJ9jO1r3pisdjhsVqhZupLXdv219YZ9Xuxza6yt2WyG0+5Ex7COzd4uw/0d2MrK+HkhbPJkVP3xByw5uTwSIWbaNJgPuoSv9M6wHPPNpsjZFYri/aFQ1BFU3NtVOJx83/hinfBsYhzKK8PorrGeaWONCTa7FVnhNvx4pYQ5ZZ9iTkQ4HoqKh6JiDRQdFBiiV6FTkR4Hwm1weslEP63qxb48JEjbYbdfCskl+mkURuiRj0p7GCY9PAAFe0oQkaDBZe+vw8H8Shx55cJmnSNuf3MMjlUdxXtLgVAplPeX991khEPJzI7lz1wlqRExtQYVi0OgM4fwZVaHGYkh8TCbTajuOh42uzC1lpQiTYqZL9vYPuzajsNaDTMkmLVazzzWVixk0U0hAX0x+bGoVEEPBdghwQrUH9uWx5eNnJYO50rx2ozLByTw9836oFAq4HDY4XA6YLX534e8j2WNXkJNlRHVFbU+7/9w0WH8cuA3pOh6YLNGi3RjJJKsVs8+UThnDkp++ZWP20NC+Xzv7TbnPNXQ8en9/bYGJPI0k3Gdu8F0GKg4cRKxA6I8FbaMe2Qnc4Jo69W17h6bjtd/Pxg0njzunxFvPcr9W5i5r4REHoIgghp2Eblt2zbMmDHDM49dJLL0qg0bXLV668Dms8gfb1iUDhNwGBkZGcjPz+fbcBMREcHTwNi6/kQedkPG/t1UVvqmE5xJWIWdZ//xLLbuOInIBAPKXhXvs2bTJphMRoz8+WfcyNxGXbz55psBbw5ZitttXjXUmbhVG6CGenJyMu72qqHOUuTKA0Rbx8XF4QGvGuofffQRigLUUI+MjMQjXo7Pn376KXID1FA3GAx40qs+8ty5c3EiQA11JoL83auGOov4aijl7nmvurzz58/H/gZqqM+cOdNzo7FgwQLsbKCGOhMTWSQYY8mSJdjSQA119jmwz4OxfPlyHnUWiPvvvx/xrkq0a9aswcoGaqgzEbSDq4a6vvw48vcLAeXVV3fiwPIjPjfBof0mYsMxER2wb/cOVGwQUR2MpRlhUO0V3iKMG264Ad1ZDXUmemQZUbm9Et1C9+BVVz1llrZRXCJKi1+XcRzDXdcaRwqL8T93zWXml7PLjBzLFhRay5AZYsa0vXsxMEYIf0dLHfh6j2v/PbgSKGLHmRlwiPUvvPBCDHfVUM/MzMRndWuoFx8B9pqB7OWYpBuL0a4a6nl5eZjTQA318ePH838G23ffr1ND3Wixo2LDMfxSsxYR5ZMxefJkPr+iooIfR4EYNmwYLnLVUGfHGjs+/ZFRkYEqexWka4R4xI5h9+fqj969e+Marxrq7rZVy5bDVFKMsMJCmNQqWPPz0UmjwS1hYcL4xOHAFwoFKl3fkyeTYo34nDuo1ejv9Tre54jqTUd8Uvqe2BOD2xf/2zP9xTcfY+eOY7CFHsPh6lK8WmXG+5FMECiCKkyFmIkxyFY7kKbSY+2BBag2ySlM/PNRVyJbtwMZ5l9wXv8r+TyNogYFJ17C7NJJyPxqNcJ0aqx6g5VDP8Irfc2adbjZ5wirKzqlcH0hPix7FNO6XI4dH21Fbnku/sj42nNdfNHQW7HKshgDcSWqtlZjSdnXKCgqwB8186DZrkLEWj0ydonPccqgG7go1OnkEqysrsbB/TNRUcCia5woj8yFzlIOU/ZJ3nbiANf35rCJc8S2MKC2mAs6bJ6bCtv3CB96GSSbk4s8f65YgeMF+3hp+bItSajYcNjTdnlxHK4f+Hd+jmDX+Efz9+BI7i7P70VD54jDmXuwZMd32P/q78g6KBdAWveiESd2lUDXIwz7Q1PRx6nC0ZP78eqrC8T+sHo1jK79KObruVBqtT7niD179nh+Z/1x9dVXo4+rhvqBAwd4WnVj5+rWINge0wc9CYniyVPxyQOeeawEqC3ARQFBBDPsgslfRhZL04o0qPkPUVDgpxtSkAhQBEEQjVFcXMyfDLIoG2/YNBNq/MHmN9TePWzONl977TUuBLn/U1NT0ZKYa8WFf1K6lx9DaRmkcHmaIPwx/ZzOvpWK0uW0igEpQmBinikM7xt4RlOikDvHyukjCrUa2eMvgUml5Z5RrgAiOP08odcqamB16mF3+/K4G3tTJN8jWE6cQOlXcxvtj+cp1hm+7GLm1IyWemjHDJe9y9OfbrqWMsTABR439soK6PoKrxxtulxuyTBsGP+umrbx+rNqKy34/b97YK61eop48GgSLkvUxyoBNpUOams1TH1PIk271Wd5nsr3/ducOuilShSp7Nh6wrsCs/gedmQ23+bDaBPvV6fS8fQrrV7Fq5upJTWShutwPHonjsRuxcfDnsSm2jX11mfvrzSvxiPweKMziz5Gq/MRVX4ITpdBjknjJy3LLegMvgUY9X8B5QT22XoTGlm/Yq/3g2YWydMcQqLE9qx1PHkkuwpKpwSbZIXToUWPpHCU5Fbzf2Zg7fBKZ2YCT3uFInmaSUpyN5xEGXavL0FPl+G+OikR9qJiHOjZC12WLYWmTggyQQQr7MJIFcDcTKVUBE/1Kk8oD+rl65IlD0EQRNNgkUTe0UEskqclhZ7p1z2AJZV7ccuz5yAkQgt7dQ0Ofz8PUdddi2RWK9wLd1qaP7y9GhjeETWNtWWROg2lYHnDIoCa2pal3TXVE45FLDW17bXXXttgqpQ3V1xxBfdpCoR3etnFF1/Mo0ma0pZFjE1qoIa6d9sJEyZ4Ikkaazt27Fic00ANde80nhEjRyBin/jMZs6U+2222aFVSej2jyV82mZ3oEuv/ogYJUeHTDk3HU9M6el3u7pUHbQdtLjx3BsxoZNchvrrTScRnnkSXUNC4bz4F2DxXegaEYEx7vrIzBj54x9x0pyIRWU34Oa4VcirjsXurHweQdI1WomZY+vfMB7fUQKzJKH3gAFwOpz8RrZjx448ysqHw0uB734Fzh0PKfsjID8cSOzHTdXrtfXCnX7ljkyr2/ZIQRV+dKzBPXePxLD0OM98JvI2tF13Ooo7Ms1fWxbFM+/XefzYULlSedj33dTtMtxtS9M6o+C119Drww9xYJ2IDGMtwy+4AKqoKBR/+F88/tBDOPbHUoRNnAh9v74oPJ4BhAqxrq484H2O+Nq8GGafQh0KbF98Esd3FKFj72hcffHNSDYdgS15NWyJpZiZW4t5aeKzYrIPo2ueE5ZwPc5PPwdfnmvCrIfuwQcfCCPmMn0Bhk0bgGPfyPt2qLII0weq8ZbpcpyABlkdE/DBTUPwvXUJaix28HdoNQFLnwXOf6ZJ5wi3yNP3/L7ISMvAjJtmYN5X86CEErdNvBkblq0F2xusKjlac0DnsejTeSTeuXUo9m4YgZxD3oKTnIKlgBPjQ0OROi4JJ/PykHnOOBxX+VbP8qRrpY/DlI5j5HPESx/x6ltu9oRehQsrv4Va+TSYHXePDoPQLXkAhl2UhqEXdkbvC7Ox/UQ5vtmSiUsv7cP3W7mEej+kJ/bBfTPPa/wcMXwEpgyyoeeoRBzcIAuDOePWIjlkGMAqbjnUUKmUSInqBoezC1ABnJ94HI6SUoSMHImOrv3Pe7usyAGLOAuEd9tevXo1uL+3JiTyNJOUWHYxVIai8t7i7lKhQPiFFyLv7894DAVJ5CHaCuzhl78S6m51naVzBQPu/Gfvi+y6F9wEQRDBSmxsLL8ZKygQ1YDcsOnERN9iDm7Y/Ibau4dsHrsR9G4zMEBVGq1Wy//PFrVlNugNOkTGhvJztrk0ExqHA7EXXuhzodxc/4LmtPUWGdpC27qfS7C39faEOZNtY8P0UEjqet+3e1ThijTYnFHKow7cbRkGnS7gPtI/9Drsqf0OTl5CXW4TatDDptah8vvvETZGpEopHA65Tdpw4OYfoP/0BZ7eIk1fgpVvi7ST/u9kQPnPztD4eWvKsjJoFAqse+Vn7CuMwwMfns+Fjnr9Y8clf3hlBg78DBhLgNsW+G8bAHaM1W1rAyshrkZ4iMHns/fXtjnbZRSYC7iZsHckT3O2y3C3Vdus0EVE8Om0t99G7uOPI/KaaxB2nrjZT/3wA9irqvhnGX/tNXDUGvl4Y9tlRIQaUFQlCx/RdgV2rcji46zy36afTvDvVKHWodCghEpSeN6Xm84FwL5oHXROG6rtu6EZ/DWidR+h0toVOoUeBkO6x4/nT9shnPfrcdSO0mNs0kEsdwzB8sOlvE+SSgOFXUTCWI6vgmbzfwFDNNTj6/uy1cVkExEoCzMX8v4dqDjg6eeI1BH1+syQlBIuj3oBqRF/w0GJlU4Xx0m4vhKDav6HnKx0FEQKE3wV8x0LT4RGkQ9NiAoqm2gblWhAWb4rPXZGNqAN8xUQ3FFiif2B/N340TgdUAMrpYdQkBqK+LRw7F+TC51eHJfXDE+HRp2Db7fnweqUTfnZIa1USggJC3z8eqPRiPdjNQofIjc7CndhqOJCGKUqwC5Bo5X4dpVcAgOsWYVIvOpKJP7971D6eZ3mnKeac3yebShdq5nEGGJgUlfDyQy+ykTpPqXeqxRdkNwUE8TplFBnMPGnbgh0q+GnG80N6yQIgmgt2EXgkCFDuH+JGxatwaZHjRrldx0237s9gxkvu9t37tyZCz3ebVhkDquyFWibZ5uKQiMi4vVyZa19wnBT06VLK/eMCHYSwkXVnbHdZINcfzzy3U7Y60Q+ldZYkF/hv8JcV80lfGhxWOqVbI8yiTLgBS+97P86o/tkSAqRglJcLXw5OYZoYGYeMECYLHvjdJm9Hs4TfkcBozXc5dbNrlLkKu0ZK5/O0PtToE4TZpDrRuld//pUtmUyQ6kT33nExReh5949SHrxBZ82UlgYeh08gNBzz4UULX/+8bdeiPRFiwJuOylCbPeZi5hJMnBHlVzRqbxQTvkqdX01C0MMfrfD0rVUNhPUrmylrnGz+VDhVCL+/n952r209j0e/1N+LAQfa94O2K+sGpdUkrsDTcEdyROrF8fEnuI9fDip0ySolWrc3Ptmv+vplDVAz0tgNctpTTa7CtLqY+h4fClKncJvqcIAOPTi4UGU5Kr2xl4vJRSjr+oKtVbiAk9A9F7HBDvGsvaLlDKTeN2yPJFeyRiZHoOYEA0u6Cs/oHD/TuhCmiaKuyP6T+7xrWymdKogOVWwK8UX1SEp1Gd5aWg6VINHQmnw/z23FyiSp5mwHbA6LRPKk3HAzq95iB2j86+/IOPSy1C9bh0PLSSItlxC3e15Eywijz/jZffFF+mqBEG0BVia1K233oqhQ4dyA1ZmDFpTU+OptnXLLbdwQ0nmm8N4+OGHMW7cOLz99tvcAPXbb7/F1q1buTmw+3qEpSS8/PLL6NatGxd9/vGPf3Dj4YZSeM4mRTlGhMSEwF0Mq3zrbiC9BxwhUayKOrwDRhoomMXP/d7BMM1py7ycA/1OtFRbhvfD3ea0ZZ9LQ9lazWnL+uv+3WyptqwITQOFaJrVlu0P7gdPUXoNJvdMwv3ju/r9vl3B9Dwi2WRhFZTkC4Qv1mXyf1bBqO52zRYFHFY1ao02n+0qHEpE11TB4VTA5jLqdkCq99rWYQ/BtkiBBe/v456G7u06VAbYJr0DbP9BbqyLgtmqQGbyRJgVBv5k3WZ1QFJJ/DP24St2g64GNn0JSaGEVCSihNj30EBxLbCAA3fQAftMvL3Lq0xWZJeY+GejgsQ/+0Bt68Lel/v4DNS2tLoaDhurzuT0pGs1Z7sM9vky4Sv33//1TAtUUDZwjrDaJVhcvkhhl0yBItXXw8m77a6TzGBegfToMP5Z2O0KSCyVh1e5d/BpNlVmk/j7KXdo+ZDB9qqPinLx8N1xuGWzHqrackhmFd9+jZNVtVKgQqqErcYOTXUBbOFyyXGrQwWLXQ0n3+cVMJqcqKxlE2Jf1WSKyoM4vLhJ5wgWyaNX6fGvc/+NGxfejH0FR3g/Xxr5Bu+P5NDzaaVK3mHsDgUccb1hcWhQXWHl/WVUGkP456eGFa63ipAaCcbCCj6/j24BcsOuxMkCPY+UszuUPhYOPucIu/geyuLGIeqoSLVTK62wVpRCbd+Ncktf/rpOST6eovU6bHhqks+xzHRCtk1Jpwl4jvc+lp2spprXce9GadEBVg1sehsSw3WIidLx7bJjm7Gv6w0o3AJcdYn/7TbnPNXQ8dnaAT4k8pwCulA9FA69cNp3z3M5clf88COSXxZPAAgi2GEiTkCRJygjeeS+BopAIgiCCEaY1wqrfvPss89yY2SWUrV48WKPcTKruOPtV8G8S77++mteIp3l/DMhh1X86OsyIWWw6ixMKGJeMqyC1JgxY/g2da4n4q3N17/GILZjGLbmixu58u+6QBU/CmGvAt26Ma8auS0r3hPo5jAtDfAqrgVWFChAcS0kJzNvHXl69mwgQHEtMCsIr+JaYPpZoDoarJiUtxXQp58CAYprgT0g9iqcg7lzgQCFc7gI4lVcC999BzRQXAveBVvmzwcaKK4FZhXhvtFYsABooLgWmCWSq7gWliwBGiiuxT8HV3EtsECyBopr4f77AVdxLaxZAzRQXAt33QW4Cudg0yYFkk8Mxs+fAf7q3Ngr9VBFsMgGJw7vU6FiQ9d6bdxFnm64AXBdpiP/hBbF6+7BDzu647BsUYND+SGILr4TU8KWoJtClNs+nB+JT+oUiqoovhKHdgj/jwFpRUiJrebjR48CX3+lA9Y8JjcOS0ZRbg0yVBegT3Ex0uKrsGVBBpIHd0Xd4lre601K/xOjlZsAUyXySsLRQHEtMDsktyUS23e9i2u9v/IkLNyLpiven6XGeecCruJaqKgQx1Eghg0DXMW1+LFWt7jWsfJjWHIik31r0Hc8BMXN4vqMHcMNFNcCszrxKq7F2zrtDhSXiIM2zmvdhs4R1rxklJfcDV2UFWH/64m0gYHPEbFHB6Iivxbv7baic/RQbMgpxZje4uDdsTQTq/eloNaiRtlRFYoiIvFzrRFFBpGloQorQ3ivWciLUaAsPAx79nVA7qL78HKpExnrp+OQVUJemAIVJXcjZHkOrnotA1ghXndewVUwrwlDtS0ddkh4+h9Wz36qUNuRGiJHfs39IBcnSpMbPEewSB6dpMPG3zuh6Le78K3KALvzQbyZJUSW/SUTUJQlIeHyDzzr7sqIQ/7B4dCUA9tXJnOR0c3hkrtxd8xHuNIQDxNysLJ6PE6uuQbG0iGIlaYjZ1sucosk7CgJhSFCi+4q+Rrc5xxR9CdQXYgd640YZBf78SMjP4DVqYOh5iQKlGOxZEcMihM6Ye2rgc8RLDDsaH4kthSm4sCrjZ8jtmxTYsmONM+y7YYyDK6NQsHRO7DeFI/eo6MQGqmCpFIiszgM+zLlqEBmR3rY62fS+xyxZw/QQHEtXH014CquhQMHgO++dcBitEMX6huB1MrFtShdqzFu/WQz3lxy0GdeWKgBkk0Pe2mG7/wLpvKho6FHTAQRbJ48ygY8eYJE5HGHN/uL5DnjpSgIgiBaiAcffBAnT57kZcxZWhUrd+6GlZauW1aZlWo9dOgQb7937956xrksmufFF1/kopHJZMKyZcs8ZWBbG4vJBovZDl2I6wm/yQRbaSnUHci3kDh97hgjIjc6xYQ061rFxqMRlLCL8AoPJqsde2Pk6k2M2q3b6q0fEi5Us7BoP0Jq3Ydm7DXqppLlyikrjeJVlvpUEAKPQHWGn4wdLJXvjbpGdeUVn04VZ0NhEwFgFdEYksYBqBtOu7mwXxK6WyVYSsyI0DeUCiS+P5vX99jPbIGaXYM6FVAqE6B0WKF0Onj1WUtoHE5E7YVZJdQkyW7Fxi2+94yMlHA1ogyahivWZm1q7C1zkYdF8mglkcpXa6v12Y8TDbK/G2vnRqkQ+5HDKxJHqZDXC0mWPdyMu3ZDqdFCoTF4Hqay6C/2W+NwOP2mG/5WEINV9v7YavY18Wcij1phQteewIDzU7jY0hCGcA0GTeqITn3kSnoN4Z1OOWhyRzgk8T4Tq9Khghp6ZQeEalWwHheibWh1jqe9q+jcGYFVK9u9UqS3ZewqwvFdwVFxmyJ5GoHtPwfyXPmxLtLjO+EYTDhQmQ/5eRoQde11qPp9MazZOdCm+4YNEkQwwk7YgXzrmMhzqiXUTQcOwGE0wTBYmLmdMfyKPARBEESwUVFkxJRBJ3D5Y9FITAdKPvsehTEfofMzk6DrUT8as4HiWvV+pxoorlWvLYvUaSgFyxsWAdTUtizLrqnpwiwaoaltWdGxJhbXwhVXAA1l5nmnl118MdBAcS2ftlOmAA0U1/JpO2GCHEnSWNuxY1mEWuC23qk5I0eKaJLAbTtjd0UuUqL0SEszI2KUuJHzZubM7vW2G55Si8SLv8TkgcBd/eVrlIV7avFINNDl12OeeV00xzC1XuEcCT+x6I44HY5uFlE8rGpW164KzPw7yx9zebD0ugT2nIU4dKQKqwb1gVIhdgBTjRUdkhyYObPOAWCXvVsk9w24wwbmqd5Q8R5vf1gWmebd9tMa8Zmwy6Vn/t7N53OIiGh4u97HJ4tMq9s2e9lC1OZtgEFlwJIb1/HXcH/fTd0ug7W1lVThyI8iDbXXzAcDtvU5R8y9D1XG9QhNNEPx9N1Q6Bo6RyjwQZ4IpdOPikO5qhBp/WJwwuXlcm6fHM/jwo9GzgH71FiQ10d5hRhuNqHY4US34iF8+ajeBcju/188+vCdWHzEgb07RZjVnccUkCxWqJfLwtyVMT8ibWwJFN2G4pM9Vlx2swELlOI70cI3IOBG3Z1wzry8SSLPTder8ZZVvC7z4pl5o4iCyq02YflPYn5ySDKGjQ+F3VGEu+LfhDTzMXyQI4IThl6YhqScb1D173k8XUsR2xnfPTEEV/5zJc4NXe36Hu7Ejv+dwMYdEoZNToIhLhxrv3GgstiEiDi9zzni07/vBCvKrkoBaqVSvKz+VKRrVTORx4hzBxzAhKu7NOkccfP9sY2mSrk55xwF/43pOjQBk6ZLyP/xEPqvECJqjbYC5vA4hOlUqFyyAB1jz8PIzquQnSKfrO6b2dnvdvv1ExFnTelDr17A+X2OoTLBhOvvSMA3L+51bdt/dbCzCYk8jdAtIQy/783znRffBcewDztsQF9LDaAR8a3qZGEeZSvIJ5GHaDOePIGrayn58lMh4/Ir+JAZ5LWY8bK73xTIQxAEEXQw02WV5ER8ikH4SSxbBH1cBML6dvf7cKE5/gXNaduMwlZB0bYZha2Coq23J8zZbhuuU8PMPFXghFLFogwa30+YSbNKpYBdafRZPm1wEv42b4dHjAmbNBFVS5dBrXJAUUdt0OoApc3iESGWfbYfk27vI7YnufKJYpJhProbkkrBjwM3BRmV+OjhlbzKlg+hoYDRt7w13uoG5cO7oYnqhKbAjivv96RwvS4zXdZqFQ22bc52OZKFe7/otZLP/tKc7TJYWwUs0LgMrRta12fZyT8Q4w4cCatvBlx3O57vIKsKaqUTHXpEeUQetz8PY1jeRGxLXczH4xRmqCUbYuyA1iaihVg/9SwyRmmDTW1HuNIChaSFWmWHZPWNvJJCk6CR8nFOmg6f7rfg7q+3wFWEDGOVu33aquM6AY18bjxdS6WDWs2qf4nX0qjUnvcaYdB75l/c5WIMC7ejz77p0EtGvm33ZzD68s4wf2fGcddnrlCpsSGiCNdycVEoLGybzM+HrWMwKBARpebf7Z5V2Rhzla9g6N7PGIcVKdCwY2DiC7D+lAQ1NkKqzoKkOfPnCHYcXztjMGI6hEKtASStCftSViCtrC9CnRGohJNH8jhCIqB0Ajpnjc+xGGhfa04fuMeU5OT/TpvNs/3W9uNhULpWI3SNC0VWqZGHcboxhAq5OEOK8PHlUbny6q35viVPCSJYYZGbAT15lDjlSJ6WM172LqHuWhYcXSQIgiC8KC+ohTZExX0KWIi/5dgxxNx2q895nCBOB51aCZPNztO11E1MR7LaHVAq1LC6q1m5YPsliwpyI50rRBinH6MoSVKi9qAwRmYc3uznul8pwWGxwu5KrWmUaN9UMQ/75uN00TaSJnMq2JwukaGpd+8N4K5AlvKh7CXTKN1dRW6imvZQPa6jEIKkCDU0UECllXjlP0ah0gFNmnhgPyxbLp5zr/0NPmTv8Ppe1/HxnofmQm1zosxUDpPThsl7DDh3vxoOP9HlluwCGEvViHSV43pY+hEndDfg8kEdUO10pZh1Hgd0Gg2kNBC25sJkF8bL3rgNrxnulLkOoR0wvc90KMyVCJHKgL+JqobeMEHCjUIloXNk/c+xc2clEvM3ocfACKT1j/VUvaqttMBYLb6zuqmSnfqPBa74HzDyPlihh0phBhY/zXLF0BIkpkeIql8MpRlGVTUiTHGQzBoY7XaEMJFHL757vcm3CtcZI0h/00jkaYQu8aLs2kerj3vmsXJwjG3qSFgP/uaZr9RqIUVF8UgegmgLsAtvZUBPHl8n/VbFj5ITqN8EQRBE61OcXYXIeHEjYysogKOmBpp0Kp1OnDl0aok/hGVlwlm0yr+uHYDY0MCiCiur/uehIiihhsVe3z9Tw55uuXji1wM+AoQ37Noo19RwaXco1bBW2GHSNc1fBLYAfp7GAK7hzaCstoFyV6eI3XXTfjpePG4qflvAh2q3Q3dT0LhEkmu/bFLz6CQh4pgOskpbgEov4cbnR8J+eQd8Hm7GbwW+UVQ6ZRjybcLh1wgdUnQdYVM6oTOXQ2MDTlRmwGw347pF1bj150o41P5DP078EQe9KzXrDpUo8/7opO64T/WraHDRO0DpcWD3t42+B6NVRPIwZp03y5Ou5emzpEOoOhQzhs+ApJSAHV+JBYb6+6Czl5znqQwPx0ODHqrXJixcjd4Hv4BKyawdFIhM0MNca8OnT67FJ4+LymD7cit81okN0wH9r4ZT0vDS6RqFq0R9WQDn+TOIE2ZEGeWS7BabiOTpkmhEcu4axBduxbCtonrlmaSySLzHbYtb/j02BxJ5GqF/SgQf5lUY5fOKS+SxOUNxvNA33E6KiYatpPQs95IgTqe6lv9lKma8HCRhMu5u+DdeJgiCIIKNvGMV6NBdlGCyuEpLaTrLlVAI4kxEqJisDtRabAjRSLh8UArSYgw+voNumBg08rXlYsIpweKoL6qovUQeq7skuB+RJ+dQnbQqP8xbNgAHas/BtsGPe+YZJHPgFZjo1Psy4N51QB+R8n4mzJdbCrfhr9sE+HSwHBcP0rU9ejR9JSYypZ8HJPZrYnNfoyuNTsWvIw0GIZKYXGl6bvRSOI9mv9EyAxebX4LFaIPZFVeusQKlpjKYrPK9oas6N04MSULXy/KRNFzeR7QQ3zursMUIVSswXtrlWhgmaoc3Ae9InrEdxkLpcKLXSfl9MSFmww0bMC51nJhxwCUkqV3rXNsdXQa5Ssqp5ONEFR2NbpHd6r0ei/Dh781lkqM1qGGu8RUMv9hw0vdzc4ldVrOdGz3rlC5f2+qWz3JxKszIiDzkma42WbknD0ud6nn4W0gOG0KrhUFyUsqZz6eqLDb6Pfe0FiTyNAI74Y/uGoMKo7xTaw3ixK+x6XE8czUvG+dGFRUNeymJPETbEXmYmBP0JdTd+BF5/Dn9EwRBEK2H3ebg0ZZRrqfnlowMbvSiSaHKWsSZjeQx2xyoMYu0DIZ3xdAvN8o3oCdLXPW0uRGxCrVWedqNWqXAb4++g9smzYBVkqvCecPSt8Ki6wsb1kL5XoBRWBaKrWq5RLbGUgmpzNfj08OSvwPFh0TqUWJfbtp8JkSefh3Eg+ozjcPpwJ7iPXy8qPb0KwkpI8Kh7dULiqYaofBOMF+cpptHWS2+Io/kSvExaMQ2rHUuhdVKHa9Ots7RD8ecHbBt8Uno1aLt335xwJRxFH0+Xedpr6kwImSoAZWdw6DWO6AOl9+LwrWv2Vy33XqYfCOSxj0lLnDtDUdcsX3WLfKwCJ4r1jnx8CfFsObIVaMaov95KZh6jxDFnDYvG5IhQ6CW/BiHub8PV2oXu/9lkTxujBY7ftgmRJMhnaI8KZR8WZV4LzqliJzCsT8Dd6yqAPjPcDE8DWwwoVwtF0syWx38tsE75ZJNxxXtgNJL0D1TMGErkKjYGpzSO5w9ezbS0tKg0+l4+c/Nmzc32L68vBwPPPAAkpKSoNVqeXnPRYtEyBrj+eef5+qj93/Pnj0RTL48B/PlnUalUfI880R7BxyTFMAJEbLGcDocqFy4kG48iTYBE3FYWlawl1B3m/IovFQe9zHWEidqgiAI4tRhpXJvfW00eowQJX3NGRnQpKZ6yh4TxBkTeax2fLIuwyPueIs8z/26DzuzRLqT2eumthrHsChDvg/xfrBbEt0BBSExKDBE83mWk0IoYjfSmffcgxM33oSh8++CZPeNyjl6Xh0j5ToM2/o6JH2A1KYN/0G2uR/Kal2ijLfI08iNf0O01DWct0D2wjkvnPb2nLW1ULISXs2BRfI0UeRh14sndrP6TzKSTggYeo24hrTUEXkKzXKVtRcvFaWWeg2S08kUBw6h41q5DYuqsUsSN2Y2O1VQjBIVrxhhhdtwk7QUcQoheGirTuKAIxU/2UeLSJ5Q5unqBGp8+1iXcnM5IrUiOpLdKw+0CC9Yh59os8b2G7fw0fHzzyFFim0+cJ/kY/KscLkreyJ5QtS8OpybXs8u9vhYVZnE/K7xwv+mqlQIWWGS6z2t/iew9Dn/nTm+Uoice3/E6WC01sLhVVOqWulEXoUJTosVUkQEum1YD223rlA6bDhTh0ZNhdmvkOhdrr61aPbd0XfffYdHH30Uzz33HLZv344BAwZgypQpKKyjYLuxWCyYNGkSTpw4gR9++AGHDh3CnDlz0KGDyHN006dPH+Tl5Xn+166VhZPWZkBqJI4X1aDCldPKDqywaB3inSnINIQBBaJcGsOWl+cTekgQQR/Jw4TKYBd53Hh11X0CZTcTBEEQRPDBrpfYDZZx1y5ougQwliWI00jXOl4sSia7H8Z6izyMabNFtAWLyvh/9s4DTG7q7MJH0rTtvbr33sGAjQGD6SX0XgOEDgmEmp9AEgIkQCotEHpooYZqik21TTHGuODe7V1v8fYyTdL/3HtVrjSa2V23XeP7Po89MxqNRjOrmbk693znc/P5ZtYumhd5SDAzoZ6cfJNxUgMTieqefRatn32O8KJFkKBTN4ADru+zpieOS0gH3lRCxv/qf48X3h/PbvCuik6W8nhhvpadTWuMvefnjjgX0/vueKtobXtEHlIuRnJnOsGWlYm5RmTCnhA3xpIVCnuvmn2JDq+8ECvt6TOCCX+UDVVoDjnHyJqsIIQoglIccsgW9EqWPEbbiptIzZXIktoRKDC6pmUa4lGr97k0L/LkhZhjhrBPITtetv3734nmgrDhoElC69y59DLQ3y6h7TtsH+v65Ocno0Vtd7h+iJOnroL97U0yAj4cPrKElk0STNGHlLfRx8gt9spzWI5QAqFsdkk6VncR8rqPfu1ofFX5FeJog6rbx8Qyv4q8jAA9J08bPx6+vDz4ysog6Sq0nfTRILlDJsVGuDehtSFFaeZuosvfHH/5y19w6aWX4qKLLsLIkSPx6KOPIj09HU8++aTn+mR5XV0d3nzzTUydOpU6gA4++GAqDvH4fD6UlpZa/woLkweaRSIRNDU1Of7tSky744+V9vNk5AaR11yG7wJ+aHXrrOW9H3mYXkY3bdql+yQQ7AxipJWo3PNFHrO2VfIUeUQ2j0AgEPRUIitWIPzDImRMmdLduyL4CTp53LhFHpMHPrS7YZlcNesqx+28dD/eXlRBr7f72Il92/cLqYtHznS26R666hUMW/GC53PF9cRyLkWREGtsdggbncK3fZk3G7a1YlU1O8Hmc4p2Bq1xdjJ+WN/Ddsr2tNbtcfJ0vlzLbNRx9OV2fo8SMsq0jLEkydSZH4zDF2Jn/0eVXWav6zGpuO9HPyKf0y8IcVlBJoxcFldWUZ3ChR9vmIPeUi10v3FMBQ2RI2IfH16QsPCAbGfJ6NWr6GXja68jtnGjc+Vw6sBuEoRP8JfY7qTpfZyCXatmvBaVCTYhI7+Ip6KhnYYbm12oc411SMkuQUljJbspMV1Hro53naEx0ojNLZtx6YeXYmXrF5DT7PdBl1jINRFqzQ7YGQdMoU4ec/92lDjXfXvDErt71wt3fo09SuQhrpzvvvsOM2bMsDcgy/T2vHnzPB/z1ltv4YADDqDlWiUlJRg9ejTuvvtuqJziTVi1ahXKy8sxcOBAnHPOOdjoPlg57rnnHuTk5Fj/+vTpg11JL0OV3NpkByoV9s5EsC0L1ZKKRU22XS84eDB5UxDbKEQeQc+EBBQe8/cvsHFbG+0QkUzkIcvjO0vq3kF0LbE0y5yFEQHMAoFA0HOJbmDjueyj7dbEAsHOwKs1OJ+hyTNvrX0CNkg+x3OdqYMLuZN+tu36557D6sNmQM5i3XZNfGoYvSrnIK9+uSOygRDTE8uyZEVHc7pdxWCWgSHmzPxJYDvjH+43RK0z9umDT2/ccbeNu8sTIcPfiRP4XeXkoSJP55w8quFoyi/n9tcYO/Jupxh0KBr7uw/MHG0tr5vDsmKi4Tiqbr4r6fMQkaevxNw4bmdNvroN76v7gqbEzP0nW8cM/w5mdsrJEtfijpbpeoVdSQIjQ8q6b/GraFibBv3kJ5O+58TdwkNCtB86wY93b5rKtmHEOWgR5kohUSVumiOk9ElH1Hgf89IDTpHnem4fk9Fet92lif9ZZnQQM9CNAG1dZpU4RAjWWlqsz2/+hReg9MTD0dLs8bkiXc6+egSIuNS7FMQiPeM8aYdFntraWirOELGGh9zeutW7bfjatWtpmRZ5HMnhuf322/HAAw/grrvsDwnJ9Xn66acxc+ZMPPLII1i3bh2mTZuG5mZvRfPWW29FY2Oj9W/TLnbNkFCunDQ/reszyS5IgxaW4NdlrGhYA8TZB4CGhmkaqu6+e5fuk0CwvSzZ0kRdac9/vQF1bdGkmTysNWnP+PIyA8z4tukHnTmUXekZZiOBQCAQeBDbvJmewJm5DwLBrnTytEbinpNbPEHZW1AwOwOZVHKtp2ObWMCsm2CEtZCuLJmMLTfcgLCWgZrYoIT1co8/HoW1Rkclgjn2+vTu1DqOvn3jsJhxkm0G4e6Kcq3uFXk6l8nT1hTFW39bSK/7uL8vESbcZXxkSaAtHSf1ORXl6XZ5aePyRstBXnD4DISTOMifz6jHkiwmEISGszGqHLTXjcCP1SHbTRTXjPsCxvv45pVJXwcRjUhHOCryzP4j8PovHMfNtisPwZYrzsfmX/6K5u20vvgAKr/JQ8MSj7we8ppefx3tC9n7wos8n43SsbiMiS1Rmb03G846G5E1a+DXvAXJ/y2swJEjWf5aeoC9x1rcmJw1bjuoXGSdN1OqbaE02WtPlnX7r0X/ctzWJGYiCWf74DfOGdSWFiiZmVYJceGYgTRbKGKUlFG+eRz4xwRg5i3oCvGo07TSk9jlYRaapqG4uBiPPfYYJk2ahDPOOAO/+c1vaJmXydFHH43TTjsNY8eOpfk+RAwiYc3//e9/PbdJwpuzs7Md/3Y1ZTkhbOVEnlCmn34bDJF7Y2XAD6z7IuExXm0XBYLuxix5WlfbSkWcT1d61wBnBBW0eAyWurVci8sPSstkswVrF+54ZweBQCAQ7BralyxGcOhQOrgWCHYmZJzixnTi8GxrcY7HBxd7C44BlzPovQH7W9ejSSoMIkEW6bBsxAVofn8mnqj+D95t+I3Hiu0IhW03kdpmVAe0VEP3Oh27ZgG7NFqVdxUzaHpXfO5MkSfdn969Th6pYydPXYXtylD89nuxub4N+9z1EeasYcHApOSo0HDxnJt5GYK+xNIkNaZhTO8cx3saKc5BPMTWbZFV/Ds3GwjlQhp+DAqvusqhQ0V1P+KK7fKaH9iXXQkYTp625MHLb65+k16ub1zPQowXvQxdtfejYaUPTZ98i+aZMxFe8oM1ARr36PistduVKTwhH9u3BdXs2Pu+ZZl1X91zz6HqV9d6Pu5n48tx10mj8eXN0633hnZY9LFmSs4nV4F/TQPev8leZpapJSnXenDhgxj77FjrNhF8xj07Du+vez/xtUlMmFJ10lhGQtWf/gx12zbIGbYTLy2L/b3CLdzzvfdr+7rprOpiRy0eh2tsTxB5SE6OoiioqnK2OCO3SY6OF6SjFummRR5nMmLECOr8IeVfXuTm5tLHrF69Gj2F0pyQw8lDRR4AQ3InY2UwBGywg6J7P8xyeWJJ3E0CQXdift1WNbHj+fuNDUkdbO7Zr+6C5u9ITiePQCAQCHo+4R9/RNo4e4AuEOwsMoz21zxeAcs1LbZrYNYNB+OQIc7mL3zwMk+Ln8U1ELQk+Z+y0Va7IyRdp/9M4m3GPumat8hTMAgoHbtdTp4731qKT1bUOJwVOxMSAEzIDmTvPJEno4siDyltMh0wSVi/uBb/M1w8fKZOnazhq7V1qG2J4lPjffripuk44TzWRYuMN32cyz2rlB0H/cdyuToGGQUl8BmdpYobdISJqJHTh86oSn6fFTdACCMAVWZCysrsKZjXVm48nwRMvc4WezxY28ga+jQ2buCOPW93i1a1AarRE14KBBLvb/EuR3ILMtE0+9hueOllZDev93zcb44ZQT87vfPsvyEReawMo9y+9sqqce6/9A2g6kd23XDDmdk/JHvoxeUvWu6dxxY9Ri83NzM3XVVbFTRdSyjVIpzYj2Up1bZGEYSGuqeMwGuf/TlQDEcXEe083gXsqJOnbHAOMvOSdNLrqSJPIBCgbpxZs2Y5nDrkNsnd8YKELROxhqxnsnLlSir+kO150dLSgjVr1tB1egpuJ0+aIfL0Cw3GqmAA2ja7m1agT296Ga+1FXuBoKdgfocHuS+8nVmulcxSuaMijxB4BAKBYM+C2ORjGzYiOHxEd++K4CdIRtA+CX3m55MTWqWbzFtjj8cHFmYgzR/0bAt+84Ij4Mta4inykA5xJkXXcY6GiLcrwqREXo6rSk+iUQ45jWsS3RRq1FvkIZBcIOJ86CJPz7VPxmeMdEZs7Ay2tm1FQagAAcX7PK6rkBDgLjt5wo1AyGg5n4R3H1rkuO3zyxhy9iC8mBnBfR+scNxHujAdum85PccnHZP4UsDMzACG7V+KnCJjH7lhbmurPRn6+lQZETLITjc6YCmKw4jVjDSoPnZMKYEQGoyuzZRQLhBtSZpLoxobkrhua5LsPd5Wl81GpNFvx4i4MLOj3PChzgQt5PycKFocB49zip1psTC2TZ6Azdc4XT7RsAq/6bRLM7qSEeeVKfKQv98jB7icPOy9JALP3V/fjf+t+R9eXv6ytc2jXz/aClsmLKpx/n3fOekdHN3/ePYaQUqF7TiXAJffS44D+j55hi937RzmoycNoYojmO7HxqXbsPhT7xLPHluuRdqnkxbozzzzDJYtW4YrrrgCra2ttNsW4fzzz6eZOSbkftJd67rrrqPizrvvvkuDl0kQs8mvf/1rfPbZZ7TN+ty5c3HSSSdR589ZZ52FnkJpdprDyWOWipTJfdAKHRWr3qFf4ASlgCm98W3JbXcCQffBxJJkrdP54OWudtciAk/z+4n2yZ1RriVEHoFAINiziCxnWQuhkULkEex8+LyZsUYn3KZwogOZP6EnboWI6mxvvLV1K6a+xMJmfdm2mNPKiTyO5x1rO9OKatj6AcPd4sbnM07adQ3FtT9gxPLn6M14m+1o0EkbIC/ICX0XnTz8RBtpbT2xr91ye2dBBLGsgLPb2PYSXrkSeiQCX7Hd5alDom1ASxWQUZT0PXjnQS7/CMCFf5pKm3dk9cpEWzJNTZLgCyi0BCfNcEBN7p+PeFSjy+0nsK82GS4eQswnIUz+ZsZ7I/n8jr9ts54O1SzXUgJo510g1T/a2TBJXhN9GNcaXY16vxBt3XxL5NEiHjk6xvlqn8eceTbjipydryN6YsWNFHN+do5dzxovNX/0kfOxbTEqdlDOfhkYdRIrPYy7trnsbWDtp8Z+sfeyJcacRrfPuR13fZ0YdN0e9xZW+2b1Rb5xfh6VAKWRfSYHvPU/ZE6bZq2n1LH3Or4Tc0fHHWaLSI3VrHNe5RrDobSniDwkU+f+++/Hb3/7W4wfPx4LFy6kgclmGDPpilVZWWmtTzpfffDBB/j2229p5s61115LBZ9bbrGDjTZv3kwFnWHDhuH0009HQUEBvvrqKxQVeX94u8vJU9sSsWygwXQf7epTAPaltJK4ktrYTAENF1QUqNsS6yAFgp7i5IkbAs4j50z0XE/eDpGn/bvvsOX6G3a6q4c6eTxEqYJena+bFQgEAsHuJbxsOSS/H8GBdoipQLCz4MurzNbN+w9MLKlxQwJmeWZvnE07FzHsE7+okpjLQlAyMjDw/fcweNbHOPjNvyCneR3yGlZZ3Yh4ZLATeTmdndz7o8y1EA9HLJcO7+SZ8+oqu8SHdI/qosjDdxebMqjj92J7ICfZaYYjZUfZcN759DI0ogtCMBF4iCOkeLjn3cvmVjraWRPM0iGS05IKcjd5y80yN5LtQrJbglzpko9zwmgZTrGLOnl6T6LXJZ8PkPzAyJ/R243IgGa+b74A2mMqftjUYAtX9LUZUR9NFUCFXWr2/LLn2TbXfW4tU6MSQnlRz3IsTWPHm06Os4QVjP13uXwK0pzHCymbctO24HvnprjyJlJ2Zz22LW6/Z1mlwODD2fWYvQ5l5Uz7ulGuRUqxUnHDZ/Z5BuHI/kfifyf+j4p0ZUXp+Dgtio/SovAZ2zNDl018711HL+NeuaO9jZykTtJ/bCF6Dc3FAScP6nG5PNsVvHz11Vdjw4YNiEQi+Prrr2l3LJNPP/2UdsriIaVcRLQJh8O0DOu2225zZPS89NJLqKiooNsjgg+5PWhQ4pvVnZTksA9LdTNTRInAQ0q2mtbHkevPZOHLxgdTkmX4S0sRXbeuW/dZIPDC/DqOGx2rBhR5fwkpkkR/3LpquXUu2D6VXAuHUf/KK5ZIRAY8fOiyyeBJxVaAmkAgEAh6DvHaWlT98Y/EykCFHoFgV4k8Bw4utPJEHj9/EmbfcHDKx00tn4qS9BKMLBjpCJwlSEZwKyGWpEW3lJaO4IAB8PfqBV9uLkJFedBkH3Q/287kqZnIbmIlU7LETiTzzzwZ6Qfsj+AAlk+itkdoeC5B407HFn68CS0Nke128tRzJUAkTHhXEI6HHe/ZjhA0zvd8SbJdPTFbjSdxE33yXGK3JlvkSVx/EDcOJud3ZOxpdlojY+XWhggy82xhcFt/I0uHmBsu5wKEaUcqkq/zK7YtkskTjwO9WSlhq56GAaVMSBm05S16+cBHrNU9TEFxzt+B+g3Ag/sCj9nHsW7Yh0oN4YLuW5sCf0ZiOZ/a0gZNZ44W3cPJY5ZrkfNVNx+dajtywmoYOSef7Hx9y+0wZjcxzuQRi6rwh7jPj5lA7RZ5CofZ1w0nT0cTxNVtzoYxB/Y6EANzBlpRFN8HVbTLQL7PaNriiodR2tn5utri4b4b17UqIur6yg44qg2Ouox1UFO8DrbdSPc++x4EcfIQ+Fye7MI0tNZHMDRnEHPyNNtBy6GxY2jYoEDQ09BdHShIWZYXpJzL7Gq13WynyFP70MPYevtvEVm5KmUmDy1X39F9FAgEAsFOp30Ry0vwd6UMQyDoAn5j8icnzRYRyUnewKJM/PmUsbhquveEMRGEpveZbrl3HNkynMijGvkn7pNEOd3pYmmOBVFTNAGNuez5skIxlFfOYY81nEFkU/2eegq9brvBFnlIqYrLyWPuH7vSdSdPOGaf9HdUlr89kLbb4Xg7QlyXqB0hbcwYBAYOhBxMzEnqWOTpvFNCMdqeF2Um7vddJ45xiDzkxN108uiqTseZvGDh/8dt1vXmbA+3lCGeUCePpkEffARQNh7/uO2XKAwwIUMzOpP1yzdyfo59wH78pm9YPo8HlzSwci2ig5ByLSWUeHxokTjihpaipXLyeIiYpRm22PbCshdQdNedjvv9Rmc1k3af/XcjrdtNaIkbV06JeiMnasNc5xOajydd6ojoqespnTx6Y0XCsliSrlz5xsdW4o+tbWugSMyhpM66hy0zhbPhxwGTLkRXIMdKIKg4QqvzyzIQzPDtkozSriBEni501yKsqbE/dL2G5WLr2kYMLRyJr0IhZq0zCA4ejMiqVd3+BxYI3JiiyOItrFZU8VDyCbIkWSVdncV9vG/v8a821JtboP9rqkZrqd2QH+MuZqQJBAKBYDcQNzqx9n3qye7eFcFPFLMDkleX8NP37YMbj3SW8yz/w1HcY32WyJPp58s5NFqyc8TIEsjGGCb7uOMc25HTXKVKxlipKXcwvQwgAtkI0G3XjHBgo/RF+YZ14I031wGrPqTXdd05viFjHs/g5c3fAU8fx87wkxDhwmSlLnYK6ojWefOw/syzUPbdpp3m5NFjUc8OUCkxBZAkIk+Ad5AYmGPIstxQQslWwOwCZbTVnv/eemxdakRumBOiXBBzefEgz/c7ASLykNeY2x+47DMgswiIsTwZ+aL3aN5Pq1kylFFoP05J7sDy5fVnV4pHA7rkqQHG22XEm9jxpoc9nDzG8UXH0CkgYc+vrnzVsSyrdQvKK76ErEZpiHlxkR1+rXNds4n4YQUvs51ilx//zvkk5DNIuoqZHba2LIDGlUy6mffoBMftS8dcihMGneBYNqSYfZ7PnVjqFHlIwHO0BT6JfTbjDUa38LjxHpHcoCTuvWTEwnH4PRxzZGK6uyehhcjTSbKCPhRnBfHeYtutk5Ufot+zvVqGo1mRsWrLV9Z9wSFDoDY0QN0mOmwJehZnPW4fp6mcPOT3cIe/oNSud4Ug6DHjR88YyCQLXibKeXd/iQoEAoEgkejGTfD37Qt/uV3aIBDsTExxp6OcFXOsw3dM8st+KvJ8U/kNnl5qx0xMHZKPtfcci1uOHo64ccKn5OU6tuXuBLVfX6P8I8TKh+TaCkSN9uJVMaMcJc4cFXIrK2lRSWCvITK5nTxW1x/yAvmz+M/uBdZ/ATTaXYPcrNjKnB4DizIwZbB3Jk/r3LmIbdmCrhJescIqqd9ZIo8W3R6RJ7WTJ6swDf3GFODcP+zvWeJnVmeYBDmRx2TzInb+JhljTF/AXqcsswyXXqvguotO8ezmZoqHJHiZwjlcMOwYdpnXH9lpPkdws4XsR0tlELFW+zlHppXajpgp10A7jzU5SS9MzM1p2mgfn1rEw8ljHlMenbfcmG3LeTJbNkNTAvjDwN64tCjiKfKQ1uKOsOopRvctU8zZ91IWIEHEUFLKZWYVVS1OOUF8WanTGXrV+KsSMrY+uv5grL/3WOQoRrmWWS58T2/gvRuhgL3nqu53fDbRhWM6Go7joctno35rm7MsjTs/sbK1ugkh8nQS8scibQg/W1ljZZkMP4C1eC/fxr7A16ybZZ2UEpGHQNw8AkFPwizTMkk2OCIOn65m8rhp+eKL7XqcbohD5g8GKdfyyuQhwk93f4kKBAKBIJHoxo0I9GX5IwLBrsBsDkGcx8n45YwhnqVLiqxQp8LFH16M76q+s5ZXtVahPlxPXULrssvQetWvUXT11Y7HSsS9zzHwynPoZXuQdbJqfvAB6O59Mpw8stZunSSaJBN5WiUJn8S4Ji7E8WC2n07Cza8tppfPXDQZxVneJ60bf34x1p1+BrqKbrR9b/WpOy14mQggEsk13S6Rx7v5RjyiIr80w2557oIv76O7YDqnONZ9X0MvDxrAHDZ86RERFT65/HsgcDgiHh2anlj8hF2uRd43kstjMvwY4M5GIC0P2SE/fqxoss4rTfSXzsGmzwqw6fMC67wyK9yCo1qM171hHhXaCHy51sBjnFk1cnY2tGajPblXuVaSz82cs1ipIaGmrQYVrgZtkiESLfxwI6pb072dPFENfl7kcbe7J2HMxIpPXDQkj+iXRjv05iqrXbwJcdpdMe4Kz30ln+Nk6JEodfHwpVTY9DUkiXziYlDlTKB6me0y6oLI01Jvi1uhzMTjl2Y7CZFnz2GoYf/6dn29FeJVMiAbelhGgS8DC0iN35rZ9D4ysCEHFuksIRD0ZJI6eSS7A1encYlCZqZOlzF2ibTVJBC3juIh8mxHJqFAIBAIdgPRNWsQ6Nevu3dD8BOmd146pg4uwNWHsjKpVOHMZmmXiSzJ2NKS6GZZ37Qe0/87nY05JAltR56AOjhzSNyBtf5M5iSISuwkUVEjCETtVte8W0BR2Qnlt3Us9NkdvExQY2wsdTe24droatqy3LmtRPeGSWk224eMDkKXt6fSwHSFRLRIgnuisxCXRuO771r5LVokCjnQxW0RJ5Pspx2qeGo2NtPtk9BfH18q5GJphfNv08fMxXGx5M4jcN6+TKh2l+QQJxhxhnmVa1Uabi0SvJwg8nCkBxVUNIZx/4dG+LKBGmHHgxYznC7k2Iq1IGCOsSddCN3oZCUrOu2wpRQUIDhxOsomm3EHQKBPH7TOmZPw/FbwchInT7bhQiP8UPMDfnm5D6ffar9+iRNhop9+7HBlOZ083HFNxJi8AfbtjCK7hIr8LTOLgcKhQKQJesxZYvbIjEdwUO+DHMv6hzruwK0Tl5hZquX6zASkdkTifuDh/YF24z0Legd5E0i3NlKC5kVeabr3+Uk3z0ELkacLnLVfXyp6bqxrdah3pH7z6L6H4aOMdGgLnrM+OKHRoxFeurQb91gg6JjkTp6ul0KFFy9xbiPflv9JftUPs5NbjHlM1Z38+FtOniTlWiL3SiAQCHoWpJUuOcFJ34e1EhYIdgUkS+X5S/bHoCJvRwc/xnGPdYjIkwziJDAnwIhb6Oy3SGlJckgXHVnSEFVZULIEHaVV39L7LBPBlu+AV38OvY2JK206d2KoO/dNNZwdVUb7dbezwcoQMfnyb8yRAOBn48uRnxGg/zrYaXQVPcoEh+a2ehSnJwaqE+dCuNU7BNckvPRHVNzwa6yadhAdv5GurHJGF1tN160FCplDixd4/nv3t1jx9Vbq5HG4SJJAMmWW/u5IFBoinRspoiHazgQSEqTrRVVTYuYNEYCSOnk4Asbf4PuNtjBDiLUqtkvHcJlE1AiC5nh34CGIGyKdr7gE/Y+oxZAvPgfOfRXKDLu9eNoEll8TXs7K7BKdPB3LABWtdt7sQ8fKaPGFsKjAFmskozSNvs5oFA2vvYaamZ+ieVsY1RtcQqfRSp6SbpQSznsQaK6wRZZwI1RX63byWTVL4AgnN7fgPysW4OXSI1Puux6NQAoan4MPbnXcl6VUo1k1hKI6oxt2gXdQ+8pvtuKdB3/At+96d80Opic6eUQmzx4GSewvyw5hTQ0n8mT4EWmL4ajhp6PWp+Cz9TOtD4+/pNj6EAoEPYWRZbZC7zW7xX9BdbVci9jzk812vfbn7/Dlfzvp7DF+eMgXNL0k3bU8nTzdb4cUCAQCARIySwa+/TayjrKDbgWC7sAUa3ydEHkmFk+0rteEyXhGx0fLqlDRYp/ojkjSQton64j70iGbeSzurhDvXg8seQ1KOwt7DRhlWySjRfvZI57lWqb2Y3UPWvq6sYIrZ+XjO4BnT6RXibOkKIloQbepu3JKuoDpro5HwigIJeb9LPpkM5644QtLGPHE6GREckuj69ZDa2npusgTbgJyejsXGa3j6ypaWeivkZNy7h8OwHHXjPPeTExN6Xgir4Oc45nne24WbW7E7OXVuOzQX+MPlxzhCPVmV3zOnMkkWEJg/2lsfc20s5M/vlHeJ8kImIeUPx3xmlr2FNfMhvSbSnu8XW4HE2dOP8Qxlk4IXu5ii+/Pxso47bi7UJXGhS2TDnDm9WgMlb/5P6z83d/p7aD7PeM/c1xXLgsi8kSaoXGCDn0YJAzIsYWleWkh5Gg6RjY7xTEv55ks68C9/YDvn3fcFwrEENEznEHeQef5kUldZWvCMUBELGtbHgKgyOTZA9mnfz6+WWfXx4bSmZNnXNE4DEYQs0lbRRKMRl0MBSJ4WdDj6F/otBV6lUGZAyIyFuiSEu0ShciP93Zh/OKRAUXLZ58hVlfvGbxMM3n07e/iJRAIBIJdhyMLQSDoBsy8HreTR+FOTk0yuYyXs94/BVkjbsXLSz8EJBUvHiSj1z/+kfR5fIqOuD/dKmUxXRRucnxM5OnT9A2WtU7HavUM6H0OcKyjGjkvqlG7HjNKdizMoFgeLY5NdW1YtLnB0S0qmVDTVZGHhDXXP89OlBWNEzI4qtYz50ZjrSFgeaAZuT5sJ8CcPJnJnVhY9TFw/zCWw2N2Gos00RPy1sYI1i5k2TkSV1ZDhoR5JWysm1OUhn6jnILUq5ez97s1mro5SKQtjpn/Yg71QFpyMWhjdinWZdhjaz/JmOGDl+Pe7iZNd2VKnfcGuzSGtJEmP2CU6kUlyS7X8gURr62lf0O5oAgI2M8dGjvWuu4rLLQENQdmzkGSSd5UkHLAvCxOoPH5UHzjjWyzYfa3VWXmnjnwNKfbypGvwIs8OX2MZWns2HY514iTLSeYg291tl7IPC9Z4uz85ZnJ07YVCDfYuTsGcd2PNeGpUHUF+J+RueUq/3P/jvEVBcTZY5JVwPKpTrh2PE6/bV9rXSHy7GGMKs/GyiqiMrI/XCjTZ1kTx/SfjtUkPKyFBV/5CguEk0fQY4MKO8rkMX90uuLm0Y0f4PI//4l2VFGbbZHHS6RJilWuFcGmyy5H40ezvFs9mpMdQuMRCAQCgUDgwgxcdgsfXk4er5wZf9YiUpOCN6bKSDuMOSO8IJU3qhKErKsovPIK9Hv2maTrZsSroMdVzG6+Fh98mY3oFtspRNDibFCj+0NOJ0/BkOQij65i2p8/wYKNqUUeU2TpqshDwppNfKq3SGZCyqWSPj8/+adp3k4eUhHxw0vscs7fgJatwN3lwDu/soOnQ9l4+58/4P1HWdB0a2PUcvIQCvtmpZywJ+w/kF0mo3JNY8ox7K1HD7eup8c5cUVigpDkU1KWa+lukUfxo234qdaYVlcl0qMbqF2FiASrXKsxrmDz5mrIWVkJQrq/2C6jU3JZV7jNV16Ftu++SxD6uiLySG1jjH0F8vJsUY6cUlCRTpKw9fd/YMsMAdDRXcst8vCftSP/SC9W/X0Zts2pQNB4/6yHGcd7KBbGKU0tuLumc+fWeiSCZIdpZTvL8aqL90sQldy0t7DPX7JMHvPY6DMyH0XGccdEHnQrQuTpIsNKs9AWVfHt+jrLuhVujUNTNfTLH471wTToDSx3RMnPh1pfb3UKEgh6Au4mAqkyedj6XVBQVA0ZU6ci54QTIJOMKiMYjiAbnQnMWvOUGD9kZicHYgfV65g11euLVTh5BAKBQCAQJBvLuNtke4kUnmHCMhEP2BgjqiUPPG5uN07sNRVSMGSJKGnZARYsy28Scahcp1O1pS2hXIt0+dpihDRbIo8pTPEij5mvYl52ELq8vU4ePsOHiDxyCoEgHk0c58Xr67Fs+Ai0fPGlvevtYcQqKhJFniWvAW9cBvw+j7WMN1nwDBN6DCcPXzLTWM3eQ6J5ZBeGEEzhvCF8c9th+PuZ3m4rk7mvraaXvYYyscRNOidijCsZgVEFo1xOntSZPOYkKq/TTFp6GrbpXNnQp3cDL5zhcPJc/+gn2Pj6O3aocBJk7v7Gzz5Ha4Ttx+ZrrvUMEOd5+qinccmYS6zbejoT0ypbaqEG7C5UpE+VFAjQf1ZHXEPkUXzeHebcTp5ofQTrzz0X8cYoqmfX4P1Ns50Pa6liYteW73DntjqM5gKeU6HHopCMNupu8nLZe6Hl9AVCucBIVu7oRbgl6iij7AzkrTWdWt2FEHm6CFF/Q34Zj3y2ht4u7JNF7VjVG5vRP6c/WqBhWw0LW/YVsNZ30XXeQU0CQXfg/tJRpJ0n8lAnj1njq/iIomPdZz4LCVHucDvGF3jdsyzIXFP8kNx2Zc462d2WSIFAIBAIBD0Pc4wTMFwVbicPHyDsJfJIkn2CHnUFwnpByrVIJhXhmCvH4pQbJwFpTpFAhgpNt0/BNNdkMDmZnPHqDFSpTLiIPXEkbS1t1fHwmTzzWbtuRGzXyecra9DeHHW0ad9RJ0/mwQdb12m5lsttQffTeD7S3coNyd8hNLz8srWs/rln2ctpbHA+hnstCcx/Emipoe+pWdZGt9/OHk+GuAkOEg+Ks0O0O1ZnOOxCuxMaT5B7/C8PG4oj+xtBwOaQ1BJ5vCf7w8b+txjiC6E9puK9+GR7pWVvI9a0BY2yjHzjODnltb9iUFNFYhmWC14EenfhZoy64wN6nRgQ6H4ZHc68mFQyCScPPtm6XRo/nW3TX4+w3y5r0iUi8vipyGMtM0Ued+YPbZsO4Ip5DpFn66OvoX2+4TTSgRrjuLe29/olwDPHo6toJJMnKzE7inDMNaysKhongpUO9LLzuNyYDp6unGvIigytC6LQrkCIPF0kM+jDVYcMxnfr62nJVn45U58bq9vRP7s/vb4+WkeDo9L32x/w+9HyOadCCwTdQM1DD6Hd6HzlFnmSlVFZIk9XlGhVg0TaJBozBGb5Fk9nviRNkUdtbqaXUX8Wgr7EwYo5qdXdlkiBQCAQCAQ9DyWJ49cUeXpn2gG+IZ/tULCQ9C6JPKRcKzR8GL0+YGwhsgvTSMKtcx3EocFeZnYSNfM83I6BWLgOWPup1U7b4eSp/jFhH/oVpOPJG7/Eq/fOT+rkiW3e3OFrcTwuHkPmjMMQTw8mLdeKGIHLn724IuE1eIX8miX964um4bFrP0M8ZowZOxp3xlqBohGO54hwgpaSolyts8g+yWr4kZXvcVy44g5IidxFoy9CeUa55bzqKJOHCDqExnbn/R+q7Dgwqddj0CQJRYbIkxlpc7jdX/h6Ix7/fG3C9nnhpaLeKZwQiNuedPZqNMKl3QQ5IabIx8q1JElFLGi/H6uGnEYFQ9O1RLcr+eh7545ZiE2+HH+ZfgXa8vs7RB4pxDJtvOgXi2EE+Xxs/sZ7BZKnQ46Xt64Fqpdbi3VVRdNbbyNulFq5Sc9nZVXheJDlPQWcbrKqdU2oXM1ENNUonzSjWkgWlMn4GUaekAsSxkwqfboTIfJsBxP65qE5Esfa2lYEQj6a4N7WFEWfrD7EtIb1fh9QvwFKZgYC/foiVlnZ3bss2Mup/eeD2HjBBV1y5pizX10KXiZ2YdPS6/M5gsf1JE6e1oYIXvvzfGtwwIs8Si5L8I/70hAgU0cuzFpk4eQRCAQCgUCQTORZvpVNGrlFHl7Y+WzTZwmP92Wu6FS5lgkp10rf13mSDmPyyyHycE4Yzei+RHdJ4jQO0l5LB2JkrPPGL4D6dYkiD+dyHlCYgRPGleOtqw6kt+u3tqUOPu4KxI2iKGhFBD4y1HO9Jp62xijW/eAqsfdwjbfMZmU5q9eyFxwn48A3LgfWfNLx/vhtYYCMAWPcGJJEaGwvZYNzMGZ6bwSCPjpezSlOLkDwcQdm5VNACVhioORPXa5185Es06fA1e5e4WYuybEQNZ7GLNcigo99v47b3liMP76X2PVN4krsZE44k7NZOZheVo6THp6L37zJSrHcmM62sYVjEY8bL1BSEYa9v23ppUxM4kq/NFlJLNUC8EnFF3hq/bt4deWriEkylhoilJKZmJ+UrmnYrz2MdzZXIjOV6Pf9c6wMjJTykQ52BrEKlnMVrU1scY/BM+APKpAkHZGoj4aWgwtd37alBa/+aT5ev38Bez1mtzvj/OXpm+dY644/vK/nboUyAwi3dq6sbFchRJ7tYExvduJJEuwJ6dkBtDVG6Ae7V0YZNhDldiv7wKh19ah/jpWcCATdiWbWynbSmWP+eMW7VK5FnDzscZGVK9H80cdomTPHtY5zeyu/qcLWtU3Y9GOdo46WXoaNgYwk0S/jZCJPl4QogUAgEAgEewXmWCbDVcJjOlH4Eq3RhaNTbsvKxkkBKcVKXKh4lGv5HF2czDENDeE1xmlnff8bnLnwNiby8MTDniJPcziOIcWZyElPXoplhe52gdjWrbS7Funypcokk0f3LNcyHQ+EDx5f0unnNR+nbl0G/PAisOLdjndKsYUGMgbkJwq3bWHhy9vDyb+ehIPOGIpAmtKhK8gKTOYmRkkej+3kSS3y9C1Ix+n79EZc1bD1979HdMMG9jhrWpQ51c2/v99YHOM6m73yXeccWaes/gw3zWfd0fy9eyHnxBNRb7RCJ13ZvNA0Y/8BfLveKKGTNBxxxFDn+0BFHvu9IJk8pFzJTX3YKBODjn8ufwFn9ipFMznms+1yRj3EBJX/VFThsa2skZGDnz2UuMwjzkFN1fioeAQ9Vwn444iGNTvM22DFV1ud2zJFHo9zDSIWeTHpqH6Yeqqru9huRog820FOmh/lOSGsqm6xRB4z1b1f7kDm5HnzcnpbrWMnrtHNW7pxjwUCMiiId83JI2+HgEKspMZgRg+zQUhk1Sp2n7Ed9/bMH1K+dtwSpMzgZRCRJ/HprFIzofEIBAKBQCBwUdPMxIUbjmAlVAlOHsV28tw77V5cO4GF0nqR0MrcA8mrftxV2qRIceic8BOLaPbElWw7eXIiRcgNlySKPPx+cCVktS2RlKHLaNgE7Sk7Z6Wz1BmT1ZElSxBXjO5aHk4ed4kWcUSY8I043MSNx6lRD9cFz2lPJxV5opzIszPwh9j7aJZsdeTkMa/7Zb/l+DJFntYv7bBpN6TMS2pvR/0LL2Ljb+9kj+MmY0mHrXrjvTadPItK2bHc6+WXablVZ5m++XsqKMU2bkJwyGBEjPf9h82NaAonHtsH/ekL6LqEnOgMwBAln7poIvYfW46DvrjBXpE492ts55Yu+SF7lDbe9fVd1vWNbcxpUw8Z9S/brdDDA9jjsjUN8i8SnXXILk9cttZ0fnFCUzs7f+h/RA33BvyfsYPsfQwGVER0w8HDddtTAvZ1cm5ihqR7nQ8ly38q6JWJoj7JO7ztDoTIs50MKs7Eqir25ZVTlGalupNcnvVmreLGrzH4E2ZFbJ3rdDMIBN1FZzUbU0DpWgt1LaHummT01G5uRjzmrYSbX5BxLnTPDIOzBgUk2M3j+czvZOHkEQgEAoFA4KbW6Iyzr9E2O8HJ4wtiv7L92DJZcXQUctOZTB7N69TKw8mjyrZIYWbRkDENEXpICY5ESrUMpDVBLHup3C7jIuUl1gsJJGSHJmXNLOhm7k0XUHKY06K9roaKPKR6nrgx3LiDZpd8bk9wRzdstK4XXnWVYz21tdmRTUTh3Cr2jnDB2D4u6FfVEQ3v3E7GgVDHocxeIk9ADthioCHybPv3E8m3IUlYWcEqQxZuqEss11IlXFBewrZtvOf96zejzRdEZOAwtHJtvaPc+591pBEC7aI1GqdjazkjExEuuPpvHxkTshzNYRUty+9BW/0okqZMl8WNY09Rw57ZP4Qt5QeiPSKn7C4dMMTVC/LLrGXBIgVR47jPIvEPua5SqKu/A/pNBcaf41z+8rkJ29cMkcefzu2DKwA9GN2KsGZk8Uy6MGlWqXlck3MNvkMwzW1KkmvaExAiz3YysjwbSysaLbWurqKVnrwOyBmAzT4f6Mf7ySPgL2VJ4lt/e0f37rBAgK4JImagXLwT3bC8nDwWiozaTS1Jn9+eoOK+KI1OBHoHTh6ru5ZooS4QCAQCgcDFldMH4bfHjcToXtmeTh5yUv7ojEfx3bnfOcrAHRjl4h9v/LjD54uE8hIXblvteu44VC541nTAkDENrdYi3as0+8S5ai07EbXO/XmRx9jO3PbDcWJrwNGpKQFdgxqR7VyWFe+jM9T85S/0sj0AkGgW4uSpaeMcEiTzaF5lQgZQKMPvmQWk5OQ4unvFSQ0YKQn6ghN5crhA2yFHAFd94xS0uOtv/GUBGqqSO4W2B78xAcmPX93w3WktkYdk8phOHu41uqMLTJ6ZtwF+4+8ZM48DbkyrqfZz+A+6GfqVX2NkzVqkxyPY948f460fmCOG8PzXrNxr+JLF6PVX9jdz01bfSPMzSdv6CNf1q641eTldXWsUum5MyBr7WnjJxeizyfg8cN22mjN6IRpkZWAbjCxQkzQfyze6f/79CBhZWKEI/3lTEYcEn64jbcbvHeHMmHwZUDiYLTvxYe8d5f4em69kQqLMt1BPN4Re44MU8EUQ01knPBht79lj+MwjrlxL1RGP2iLPcVePQ09GiDzbyaS+eahsDGNtTQtyitOpS6FpWzv6ZfejmflbzJTx3+VCznQmdgsE3UlnnTlW8PKOOnkUEm7Gr5Nse7w91an+0xaNHrNGooW6QCAQCASCZGSH/Pj5gQMSxBtT5PHJPvqPnJyb3DPtHse6ksRO7F5c/mKHz6dDxgXvX4BHFj6SdB2yvXDQdhaZrcCJK4CMa8jElWLkoRCs00rT3cOLPCRwluTPNl6JITEF5bnenaDY43VEW9l2pWgL8OKZzhDnDnjuUJk5eVTgqAFHOe6b9Uxi8K/jZDkSgZKfj/wLzkfOCcdbbebZ62Mn2JvWc06goB2Ei7NeBoqGOdw7vACQSojZXsy22alwBC+buTmy3xJC+I5Tmy6+xAoD5jl5Qi+E4oYoBB1+NY4zVs5yOHlM0kedCi1gtCH34ItVtdbzkg63hMCAAY51Gg49iO1vRgYWbLRbsG+qTx7Iva0lArhEnsCgwchsMZxaAftvsWgMiyshWG3RDY4beJx1PSvASpmuf8N+n2sycqDFJGSrOqSp1zqdW/tc5NypwzpnnpB4kSfNJfL0GYNt8X6Jj+H+ruT8wnSJkfOhSKtd1pZDOuf1YITIs52M68MsX+QDUtKfzQ5sXdNot1E/wj74is4+krZSJyfAAkF301Emz3uPLMK7Dy+yy7VSrL9wUwPW1LSkdvIQgcbxhdmZnXTNRNHg5cTVzGXCyCMQCAQCgaCzlGWwMpEt5olqkpNRghZngsNhfQ/reMOShAXVC/DwD0ncBuSEWpqMcFphYmCxZJRrkUoVv+0ICuk6Vg/8GZ6vM7ap2a3G61enY/kiOzD6yFHJRQCyYXMMZp2TbPwq6ep1zz+P6Ea7zGrOKJkGL/et0dH2/ofoCF5Y06tWQI7Xo+Tmm6Hk5kLKsEUek7QAJzgZDWwoZuemQjvwt0VnJUw82YUpBK4uEjVEHrOtvReyVyaP4re7a3EiD6Hx7XcStnH6lq/x5Mf3su3pGo7Y8DWGNNrHpC4HMWG1hv2rc1CaNwBqCxtzN7hafhO8XFxSmvd7QkSe6iZWcjVlUAHW1yaGVWcZuUTbSJcoksmjS2iLM8cUmdA1HUf+PnZZVSTkLIvkiaiRhHLJ3kY+8spyoCLeiKI1fpz9nvF5UHzJy/emXQ/c2Wi7bcwWZO7XL3M3goabz/gQrFsRRV28L5rUIudjXN3LzMxQ4uQJGyIPOS6yhcjz06Qok6mLv37lBzz3/SZau9nWFENxejG1o20IpQO9J9N1/K1LgFgM8VpXO0GBoBvga3a9IG0v1y+qtcq1Ujl5TnxoDg57wA5Go4OGBCeP7Oi44G6h7oXOWUitci2P9YSTRyAQCAQCQVcxO2lN7TXV8/73Tn4P5408j16X5M63Qk45GikbD+xzccJisxyEOnlocy0deb4C634SuLux7xFo0gwB5+tHACIEbF2ErfNzsa3CPkn1LDcz0VTomlnmbix79gTPVeM1Naj6w12ouvdP1rIsfxbys4oxYjNQccOvU71Sti/ccHDba7MQa9Kt0jXZcH+U3snChgnDStfYD9jPdoTYO1AKXPA2cOMafP/RpoS7j79mPA49fwTO+L/kwkxnGX1QL3qZX5a8GsMcJzu6a8mJ3bVMav76V+t604cfouH1N5Dz2N+4NSQEeJcW+Tud9y5ufUXD9U8wNUSPsm3ftZ+dIWPS2JYYnpw2yrtjnORTqIhD2rcfPrLEEojauXzMXKNLGwtoliEjDb+b9zss3bbUyMw0zie49ump4DOtVN05zr/jXAXGoYmDlnp8ijyCvimDD6dC58rXy6ASm1kqZGM/Xec17aozq4c/pyDlWZpxDsMHfJtNY3oyQuTZTsgX8S9nsNZo97y/HGlZAbQ1R+mXa++s3nhuxUvQL2Yqt7+WparHKyu7dZ8FAoKZpk/49NeHdDhDYbZQf+mbjZizujah9tcBbaHu+uKTFcx+dlnyTCAPN45uzlKZt2kaocc+Gj+qfI2sQCAQCAQCQSrS/emYd9Y8nDnsTM/7+2T1wbiicQ6RR3WNTXimnzucrZvKrkyEi+P+gkK/7Y6h2zVOIlkmDyvX8ut+x0SXSWuVUbLUsAFoYucVKlfWkjKjMNJsO3liqV3QaiNzScS22K4SMondJ38gOgvv4rZoZK9dIp2IidgBlt9C9ynMApgp5ROAi2YCx9zvfPyAg4CMQiz6JLF1OOl2PGJKGQp7Z+0UkefKh6dD8XfcQv2AgQXWmJlm8phihkvk4dly7XWovO02x7K4rEB2/VG2Pf2s47YeY9uOeYgexHFz3hNfU5e9ScntRkcpF1J2DsIxjXb3Iv+iqob/LdyCEb+dSbu0eaFJzMVz5jtnsngGY195UaTvCPb3PHDOzfQysmaNp5PHFHm+HyihbcpYqIoENVWIcYAr3+M54zm0VbPjX4v70PLFlykCnyV24fqMqpIzOJqfjOY7/5LPacw430jWVasnIUSeHeCXM4ZiUr88qoKSL5b2JvbBW9ewDlVtVVhetxw48h74M9jBFhMij6AbcP/gR7jOCn5f8q8Ac1aCBC/PWlaFW15fjMv/Y9fX/v1jO4m//y3vsuciAyCXk6dtgbMml/wYLPpkE6o3NBm3PZ7c5eQhX8xeX/0xY8Zh3hvOUEOBQCAQCASCVGQGMlM6X8ySkmTuA54B4wo93RvODTLhptcw26VDiJsiDylNN1qo81ks/Chu46fGY4mwE29PFHlSOZujLQjX2Se0LRVc5omLqrvvppeRFSvs3ZeV1K/Phee+GPkz8LH3Yvl6Lpy5jhO/SEZSvwOAyZemfI6BE2wXUyCt8/u23SIVh1miNazUFpUcLdSTHFtqExv/umHCjfM9a54503HbdPLEXccmgYgzJJfnnvfsiVXZ1fnKZN//rMGDn6xmIo8i02Pug6Vb6X0NbTE6IbuZy+k5aQJzNlloRHpk+1q5phFRPxNhsvNDyGzZjECMlZW1fP6Fp5Pn1ZWsbXooqiNmdDKLpdJNMou9l/tCkIxg9KYfm7Hp0kvR8Opr3uuawcuFzKTRexgriYz6nOVaNRttsTFm5PGQY6u1IYK4UcbnDwqR5yfP2ZP7UuU0mBNAcx2rbXxoxkP0koo8+18B2a9D8ulC5BF0Dy5Fm6j1Jql+v8wfr09XVOPiZ+bT682cos1bOgnz19eRaS7LyVN84430stH1ZUt+OL54eRVeuWd+0kGAd/ByohpkOngaqpMHxgkEAoGblStX4tJLL8XJJ5+MO++8E9u2GcEAAoFAYLCxeWOnRR7ZmDST01Pkwhjjo0GHTPR0Dpgt1CPxCOoMJw2BHyVZ3YLUCCLr2P6pXGh0qpJ40qI80mCLKhZ35gDrWdWBSevceQmrVbY6z2P0eGIGzKV/OwjHXcMcUF+9udbcKYTyosgd1ErCU9hr9fmoQ2n1enMgqkEzwn2NF5r0daxZUG1dD3TjybY5huYDmB0t1JNQzZVt8cRkX4KTx40eM0Qe1/vDd48L+p339frH37Eqt7djmVmeFTScPIT3Fm+1Xk84rjqcXqPKs/Hc0c9xO0KUSLbCO//8AQvHXk2vq6qOYO9yDP7sUyhFhdDa2zydPKSkrWybTkv/on72/tXYpq7OYwijhOoPWQlfZDWb+C07ZTiQw7VhJy3Zr5jLOnUBOPqKMWz9gT9zhKCvXViTIPKQMi0i/hBBiyCcPHsBQ0qYcqmmK1b7vinlU2gA8wfrP2AH3+nPwJ8eR2yj8WUnEOxOXIHfEaOLA2819cL80Vq/jR3XIUSwPnS2NRBwd+m6/8MVLAzQcPLknHyS53bdoo5VvsWXa3kEL3tVulttR1NPtggEAoEDIu5MnjwZt956K8rKynD00Udj9uzZ3b1bAoGgB8GfrAfljJTlWorRSUpLVa5l3FfYx1lOFDOGPIpPpuOZDQ0bEIyzYGJd1tC3wh7kSLIxFoqHseH3zyY4eRJK4lOIMg4zyPL3ku83gPtOkRPGlNX3P5CwXiDkQz/9U+fCbx5jIzjyMjiRJ2600SZkyrVQwTlxUryPq76tsq5POLIfzvztZFzyl2nY3fiN8W6Yc8iTci0zk8eLhtdeQ8OLL3ne17s4x7OTrJfIQwQhk2lDCnH82HLrNhFueLKPOALzi4dZt9MmTbL31ycnrB9TNTS2O19DesCH8cXjuR2xnTyEViPInIg8gcI8+EtKaAc1nWb3JIo8hAs+Zn9j1ShB07ZTlWivcwmXxsfFl60wYecXnwFn/IctLBllZfOQY5V85lpL7UD11kbnPkZdYdaLP92cELrdUxEizw4yqIiJPI0+oK0pagUyjSwYiRX1hsWxdAz86Sri623Lo0DQbeVaXCaP+QOVSuQxH14oGfbSb/+NmUsq0eZy8ny1tg465+Qx2ze6cQ9ATNHHsZ+c24jeBwkK127T3Z5zZ1t0BQLBT5tQKESdPPvuuy8uu+wyvPPOO/jVr37V3bslEAh6EPlmy2VyYqxkp3TymNktRJRJoO8Uh6qi+JwuAFN78flltDXHUD/HB79quHMU1/aCRhBwPAKtLZIo8qRw8pgCQYIriPDVQ47OpnnnnutYd8Egs9GFvT+tc+da18nJ8rQzhgBL3wRe/TmGZXyJssGGNWP1LNqZSeJEHiI48fvtlyL4vvVk/NBqdDZLIagF09mY7/J/HkKDkQvKMxE0QoJ3J6RMqygriFMm2S4ZPniZ0Pfppx2PqbzDDpp20++HOThlld3MpDMiz4LbD8czF0223DiEkMvJQ0SbvIhdgtTvP7YjJzvkdzzWbNDyi2edUQv9C11jcCLC8eN2Y7aVGPHJcUyQ09KhtbUnFXlUYzdjYH/rsYXMWePg2L8Ap3MOIg+iTc6/vdbEXqssxYnlBigfD4w43vOxZLJ43htcbpBxHm+yZgFz9fQa6gxn3hMQIs8OkhFkH7KH56+nl4017GA+pM8hqG2vRWOkEcgfiEBRFiLLfxS9ngW7H+4HmbYC5AQUvyGSpBJ5zPVjpo1WjeEvH630fhBtoW58rSQRedxOHvM2L/54lWsltFUnofoTix218AKBQJCKa6+9Fk8++SSmT5+OBx980FpeUECCM8WQSCAQ2Jwy5JROizykzOqoy0Yj7zQ2IRZSuLKtIYezS9N9obhOwuOk5ESCTLJRjLFQQauRgeK2KvuMts3xsHUWx5drPXHDF6ha55350rqMleOYJJyS1LNzGbqrrtbbJBjXPaZM33dfa2xJTpaJ0INXLqDL/HozokapC9JymRmbZKeYIk84jLj5WswTcgBfNl/cochD3CJEQEoVirw7IGLKt7+ZgYl97Xb3fAt1r/fRUvSSkB2znS9emMHLZrlWZtBHXSVBTjjMcJUStUVU5EZYRg6hlZukLcwMIuA6Hsm4f/EWu1yQ0CvX2S6c/M35GAUzHJyEE9PjgL72NKMLl7ndKE4YZHdzixkfh7ghio3KH5n4gve9GBjp3QEuGY1vvkkvJSrypCif9MCsEHC7xkoGbE8tWfciRjQ7iXrDPmmKPINyB9HLNQ1r6Bd0qHc2ovUqtP9d3637KdgL4X6QeRcPwa3eewUvR90hyGrM8WNiUtxWh3hdHW2ZntA707E79qjilXu+tXbPIf64fwQlGXokMe2fDIpI6Hln2rILBALBUUcdherqamzZsgWPPvooBg0ahOOOOw6jR4/GjBkzunv3BAJBD0LmxjGV4RWYW2E7V7wYNKEYei4bq8R1bhzjN06Qg1mW09kftYWY9pgvQbAYu9XofqoDa/t6BCTHI1ZDCtJenefVP7HMQ0otyyfRWltR8cIP9HrBSMPV4TYdceJEZWM6mjL70Ou3XqB4dz81SqrMMZh5ck+QoUKPxbHl9GnQFr5ivG6FjiEJmYceikgg17G+gxSCmhbXLCd3T8Pt5DGdT0pu150gGVMMB5hX8LIh8pjjeN6Yr7omU2Oahto0JlJcPONmHHKfXU43oiw74Vyg1VWixJsaLhx1of235FRCs3SLin2mkyc9HVq708lTkl5i3W43tEk9HEkIOe8KmQce4LlcrpgHNKfOw83MZ58t0gyGCFfk2PIiu7BrYlFPQIg8O4F7Tx6DsEQEesmq5SOZPIQLZjJFO3Doz+ll7DNnKzyBYFfDW2t5Fw+BJOp36OQxvvAUczSgRhPqdwnPfHg3tOZmKyzPEnvc+8MJMtUbSDtPZwtGtaUFetQeaND7yEAr4h2uTD53buVdIBAIvDjmmGNwyy234IUXXsCSJUuwbNky3HXXXTSbJ2XrYYFAIOigjTohrsUT19vnYuCEf7L23wRFwQFf/w5T5rH21o2REHxJJt0kXXJmK5rfU/EwNFfZvCfzn2D7wwU5B7PZPur9DSHJhBMnvqwehvn73EKvr2FxKw6Rgbi1iYhDt22OE7nXQFwesfp6NC2qRXttgO02cTLF2XlS0XXXovhPf7LWlyX7tai6D7U1yUUcIiopKcav3YmjhTr395Kz7WBkgq+ce1OTEBwyOEW5lrskS086oUu65P571PG49uDrUJFZ5GiR3q8gPUHkWVNtu35MiGOIUJhWiEx/JnJPPw05xx5j75ch0pDgYsvJk+508jREGhDinDW12exv/OPkEvjIscH9Bnfl91iXvCMbJGLAqEkdlTLxiH70kjSDWfH1Vqgx9ryHnGNnGBGGT7H/XkP2tYWqnkzP/ITsYVDDgwTUqyrN5TE/5PkhVsu7rX0b/PuyD0K0RQHCTgucQLBL4QYHDc/9B1f9YHe7Stk61FWupZg/wFocwRQWWUvc6WQmz7aKFsdurtxn34S6cfohS2JxJTbVVDmHAoFAkIwNGzbguuuuw/nnn4/777+/u3dHIBD0cH72P7sTTyqRR4duhzCTXJCJ59ulV7IMnxpGIGqfD/gCScZVOiBzJ/BKTo7RPt0WErKaNmBk2gfejzfEgOimzfYinzG5Rk4Dr+C6aHmUxVO4sSJxBNH9LSqygpwbP/2c3dlm577E9QCao2nQTDcUEavIuNAMXiYi0dI36PXphU85nm5u8A94+bUSxJKIWKRca09x8qSNG4f8i3+OwiuvcKxXevvtHW+rN3NS8Zjj4/OnDcbH1x9sr8u9HxGXA59k8kR8AazKS9xeTpo/YcLXLRIRzMld4m4jZYtyKITcExM/C+HWGIJGTiZz8jCR5/VVr6M93p6Qy1OfAawcHDJEHiQcZ51CVeHPSDx2JXKcG+65ZPDHUfO2sCVYhjLsnJ9JR/dziIpmJlRPR4g8O4GfjWd1s60y0NpgH7yvnfAa/bC/v+59+IqLIfn9iLX4gNpV3bi3gr0NR0jeA3/GcesS22KmEnnmrN7mdPLQL/sUtkrTyZNEQHJn8iybU2ktT6bc01rfuHe3AvI8YgZeIBBsD9FoFF9+6WwdLBAIBCa3Tr4VofB+ODT7D/T2hqYNKdfny7SSuX7M8ZHEzVDxLhh6X8isZZcc4kv65H1ZzgjJ5DHQSSffZF2Z0lheTGyD3eFXCZrbVoASLgfFoyvU7efa4717p90LraXFyluJrF0DLRLBlptuY8+x2s5rXNp+FL2szxuOcIOfmjT4ci36/rSxE/kR5escz1ntm0wvF8z0fq81VbNa1vc0gkqQOnnMcamkKCi58Ub48uzcHjkzE1LAzlFKhhQKJs3kyckMYXAxa/5DGN+Hbb8wM2A58HmRh3DieLsDl8mY3jkOJ09xVtBT5DGPWVJWZR7X7nH+7EMeQl1FKzILmFtHSkuDbgQvf7LpE7b/3Hj97MGnI64AX1V+RcUjvqSt5u//SPneON4TTYMSSNxnWemayENej+VK4yazSTSE8/n2jHOOnvkJ2cMgwVsPnzMRjbKGFV9ttQ5gYmkbljcMy+uWs/rbPr0RbVWAqqXdvcuCvQkPAeSEcYlf9G7c7dUtkUdKbLfo6eRxBblZu6Mlt9+6y7Q6JfIQJ8+e8X0rEAgEAoFgD+LsEWejt3oR4lGjq1UH8C4ORy6PB0QosWiud5wA6xFjDKY7G2yRLqbUGUQyefwS9EwfNFmBLCUZXBmhzFqzXYITyDLcRkRA4uEEGJMVfex1jh14rCXyRNevR/iHRdDb26EZgdL1j/8r4fGk3D5Gzn3ISyPjQ66USY2rkBGHFEiDVGiXJpmBzVtW1CcdL/ZUJ0+aL406XTY2b3Qsfye6wLpectttdOI/FS3l/Ty71BInT1T2we+abCWdvpb/4SgcMKgwsVzLECXcosxBQ4tody1zTD+8NIs69UlL+JMnGsHfLojIYznUkpwKpGexY05Oz7DKtVpjhgOMa/2ejgAVeQjN0WYUXHop8s45h96ufy51Ry0HqgrZr3uXawVsIcyLmo3254L2eDEEMR8XXj16mvO9ECLPXsb4PrmoMloRtjbYX2AkgJmGL5Mv1b79EK4LAG9fCzQ4P/wCwa7CrJnmue2YEVh/77EJy+sqbXukz6Vcy+YskSSjOezapqONYtfKtaxNaDrCS5bQ6zFfOhryh9LrcdKhIkl3Lfp0UtdqdwUCwd7D5Zdfjscffxzz58+nrh2BQCDoKn5FhqyldgSYfLzh44TSrc6IPFp1FRVOLEwBRpfAd2WnTgNa2qLS4GSdjrVkmoGT168VBb1dJ7VmRlBrS0Lr9C3P2sIDZeVMbFlZj/aWxO/KgMxO3LOOPNK5+WjUEnlkLQ49nU0iEvGG7j4kRJt90NMKmNObE3logLIUA3xBSOl2u3ozyJkf221d14jl8yrtcN8emsljZs4c94bRCt7gjxVPWtdzTz4Jcgonz7d9x2POrX+H7m58YoQUxxQffB6vn5gOiGATSeLkcXP25L6OvB1N16lTnzyeTPRO6me7j0wUWaHiJTUwJNn/UKbf7q5lBC/Xh5lgRzxndxxwB547+jn4VB0q9zKUzAyU3s5yqroCdfKQMkYXEtFp/K7W7+51uOf3BxVocXbMmW3gCRm5TkfVHqLxCJFnZ1Gem4aNIfZXn/3cMqfI07iGflGl7zMJ7XVB1hVw5q3duLeCvQk9Ylt6O+qq9crd3zqybnh+73uaXjaEVXy5utZbACLPZ9RomzMG7u/CZAo4EX/iNTX0+uJRl2LB2Ovo9WXDmKrfsrHKW8whzyMyeQQCgQeLFy/G9ddfj8mTJyMrKwsTJkzAxRdfjIcffhhfffUVWrtS9y8QCPZKSGaJpndcXkNYWb+y0yHNOT/7GUbKbHJLJg6gJNmDWW32eCyuyezslQgqpBuQ4WghIk/vtAgQc435jAky04FD1zUyeRKY9yDe/Mv3ePfv31iLchUmvhzW9zB6WfaH32PY97Y4pLW0QiUZQeQ16HHEa7bSzCCzJTo5i26tDCFe28gc3pzI0xJOQ1xPY+Vn3JAzHmPvGz/k++iJpZj1zDI6huzpTp5OkcLJ44eGKHG3G3+7pqJ0a30yTq4PZiGQ5PV/t6Ge/jvt0bk474mvHaHM/CNuO2Y4jhpdSq9nhXzWeiE/EYlUxFUtYbKX57S3T0Ok3ft4TcsMJAQvk9Blug+ShFOHnorxxeNJIrTl5OEJDBiA9P32Q5ecPCMPR/4wZ2C0RHbfFVCdikhbnImoJD4qxfElnDx7IfecP4FexrhvJSLykKCpytZKpO+zD5X/Io1+YPk7QFNFN+6tYG/Bq/V4MpEnHuPqw11f7gcoPyYk+JvIXA2WW1SinbE64eQhyyUf+6EJkxkfYwZIH7s/ux6NovmjjxKfW2azDwKBQOBmzpw5aGpqwo8//oinnnoKhx12GNatW4f/+7//w5QpU7D//uz7RSAQCJJBQm1jcQ37lOxDb39X9V1SB3FeMK9T5VrDfliI4ht/jUBRviXy6Kq3KJRplm6R8pLWBsRkGVp7mE5wqSTAWGJOHmnjHOjb7Owd3smjcU6eZD03SFgyoaHGFmIGB4bTy1GFo9hjFYU6NDKmsLbV8aqtaE1nYkEoXAc1SkQoyWqJvmbgCfbzygq2NQQRi7D7alqNLkU+p1OipY6NW3OKbcGkpZ4tC7fFmMjTQzN5QsR97sIsb7r/vCz0+tvf6PVk5VqBfv3w0YSjaa5O7imn4OPjemHFUcOBWIwec/GGBjQGMqi7zIt1tWzi4tv19fhiFZuQbWhjf880owTpsfMm4RcHDbIeY7qCTpnYizl5YhqWVDQh6Fdw3NgyTBtSaK3Ldw5rarA7Z/GkZfnt4OXmZmy9+240hBswYbWGg8/4OxWqlg0fgfoXXvAUeYKDB1mZRaQ8Lb6NZYOmzB71B1AyLQ25U4c475Q7CEk2PsYkg6expt3q3JaqMc2eUj3QMz8heyjDyrOxwaeimSuPGZLLDjZiawsOZeUnTb6j2Z2rEk9YBYKdjRZOFHn4FP5kJFPw24z2goTTV87CoRu/g8KFO/NBzwyXyOMhErHH6ZYLiFh+CYMXLoIUsH/8E7puWU6ePeMLVyAQ7H7IYG348OE4++yzaQet2bNno66uDqtXr8bLL7+Mm2++ubt3USAQ9GBIpsmSLY04ecjJ9PaFMy/Em6vf9Fx3QM4AS+hJ5eSRg0GauRLIzbJcMMlEHn6ybOnW5fhnmoTN/zKCbMlYzRR5SE8vd86OKfK0OF2L+cNb4C+xg24J7R4labn+PMw6bRbOHnwy8L+rgbY69vgLLqCXGy/6OeK+dMhqFIFYCzSVZCiGLZGnzRCACDElDS99fihmP70Y+OEl+KU29Aospk4er5Pq4r5223FT1GlvJiKP1nOdPP5EJ495HCzuD2QfxcrdvMq1Bn0wk/6rLB9EO9uSY+Tzg/PskGZVpUHXMZLJ04VytcpGNvl601HDcf4B/XDwsKKEdUiEw9WHDqHlXiurW7C6ugWfr6zBg2dPxHMXe7tqysZ651Qd8c4MXDP7Ghq8TKh/9jkqeB68hI3Vm7gJ26Jsj1byZMLXcDERgWjV1ANTv0BVZaHeoVyUncbESIsOnDz7HjcA+xzTHwPGFaKljnXXkn2SFbZc3C/xM7GndPQVIs9OpFduGvSggkZDbSaUZpSiPKMc3279liqagcGDEI3mAH32B1Z92K37K9g72HTppQnLqq66itZRp8LdUtFkVY09ULjox/dx44IXofDfeJzeEi/th7gxQzPjItbBgfw4J3PymCKORGrNyYAgojoUc68QOpbJk/KlCAQCQQIDBw7Eaaedhrvvvru7d0UgEPRgiCOiojFMO+aaVLR6u/FJDo+Zy0ICeDvCn2mLAno0ho8HP+uxlj328fmmYosioc3ofJqmt1PXMxN5NNaogscIgtaMTlaUC9+Dkh6AFnEOnsIayzXhDdmK5kNxejH8G78Gvn8O+PpRulxqWG2ts7HPDGhGwLMeN57fY/KtRmLukdXf12HTSw9Di8URlFpYuZYH/KSgzxJ5olDjxG3RQ0UeJS1lGLeJl5OHuHjopSJZHbJIy3HFz97b6gf+ArW93cjk8X79NxPXDwcZQ3+7vg5pfoW2S//9z0an7JBLRJ7aZnYee+qk3gn3981mOT4ELRijAombVjTh002f0vNeL+qefsa6XhRPXEdSfFaeaMOLLyWf5LVeo8ZCvdNygfYG98aQCtIqfb8TBtKgZSLwmKWAis8og/SY8A6EOl8C1p0IkWcnE8jxA41MZSYQZXpc0Tj8uI2VumRMnozYxk3A0COANZ/QdHyBYFeiNjQkfgF/9hnU2lrHj8Dnmz93rOPO5LHW9fjayA5I+HHYuWjMHuBY/vnwm/DdhBvodTIRRQQZ8uPsuV3aXSuW0vWjGa0YeUQLdYFA0NMhzqFzzjkH2dnZyM3NpblALVxGhhfhcBhXXXUVCgoKkJmZiVNOOQVVVVUJ33/ufy+9xAbFAoFg58J3BrI6DHmc0JM22smcPK+tfA1fbP7Cuu1PMx0dEiKRVqwu+i7hMaRFuklTwSH4gQQnk85BhqvAKteSiMgjIydkd6Uy3UEOJ0//qVCOvwtqSysbP53xH7p4TvOFCc8dMScEzddrOIP40OhIyC5Ro06eU56Ar7WZ3i7Ytti670vf+db1t+rvhAo/FDN42WPIqXHOcF/Q7eTpmaewfiVRvJm1cRa9JG3C7RXZeukeJcMkUuGlbzeh/y3v0vIoxc+Op7qnnkL4m2+okyfZROzRRs6Oyezl1Xh9wRa0GzlHHUHCm7c0sLH2ZQcNTLj/wF4H4vdTfk+vt8XaEkSQYI5ihf/IaU4BZ3g+E6BiG+3mQ9E1rDkRD4lucLva1JYW1D7yCGr+4dFaXdUsJw/Cjej/+H0on9reuXItAyIakvMTM9Tb7K7l5TCbcrLdCa4n0zM/IXswGf2y4IvrWL2g2lo2vGA4LdciPwj+Pn0R3bwZ+uAjANJObv2X3bq/gr0X/gt0ftV8XDXrqs49zmPZ/x09DFvLDsDSkRdZX+4rvt5KL9vTWc01PQFRpKROHr5cy5yJom3VzSeUFejRRFFUtFAXCAQ9HSLwLF26FB999BHeeecdfP755/jFL36R8jG/+tWv8Pbbb+OVV17BZ599hoqKCpx8MisX4SFZQ5WVlda/E088cRe+EoFg74UXeZKVYhGRxwzfjemJ7oM7592JK2ddaW8zZIsCb6/6n+c23dmGNVTQMW5opFxLgqTTFEM6fmoM26KLbnbXMgJwTeSsbBr0TCcCRxxPl22Jjkl47pU1q4wXZohEXzwAfPM4lBy7jCWzeRP6DGRuHL14AjDmVOs+RUkuLqi6KfI4g5dNyBjwi5dXorkubIk64ZaokcnTM508JcaY14SIaLd9eRu9TvxWJma5lu5xHJm5mYGiD7ClZYsl8tD129pQ0N6YtFzLnae5tSmx+UoqzHbqpuDjxcgC5sy/6+u74Ctw5k5NvN4+Lla0OPOh8ufYjYl4fjnxl/j1Pr+2boeXLUP7ggWOCVyS7VPz93+g9uFHEid2yXtI3g9SKhdvR9qsc5DTxxA6p1zTiVfNygHJ+Yl5bCnG+8BrPGMO7oUJR/RFIK1zwlF3I0SenUxOEfti/+iJH1G7manYYwvHoi3ehkU1ixDo05t+QFVfKZDdW5RsCboNU1AhtJo/3p2gWGrAacqnjmVpxo+KJvks1Xv9YmcHLrKctGSkyfUdlGuZ36o0wd74Mqdijkc7SVquJTJ5BAJBD2XZsmWYOXMm/v3vf2O//fbDgQceiH/+85/UcUOEGy8aGxvxxBNP4C9/+QsOPfRQTJo0iYo5c+fOpV3BeIgzqLS01PoXCnmXPggEgu3j3pOZ+KFwpR9ETnFDhB9HuVYH3bWcIo+OjQ3rPNfRXSUn/jgZ+3BOHqOFOhF53GqJOdbTXJ0ElWx2Mr7qgCloePVVYLK36OzTDIEhHkVtrD8LZ/74TviLc+FPNybmJBnZhemWk4eE6pqTdcG8OPpOd44HTWJ6EApMJ0+iaPPN2+uw6JPNmPPqasSj7L1ct2gbDWHumRIPKbUK4IZJNyDLn5UwvuZfo1mutbU58TfAdOkEC1nuUllOL8f9wxo2we/rnMjDC0ud2n9uu+5tmaT70q0A8hejj+HYq8Zabcebo+zcl3Dft3+y9yPFOP3iMRfjglEs44kQWbGCXupG+3VCdJ392VDrbacaQYtE2ftJPnd8hcx+VwD9WEB4RxBRx+HkMVuoc2/BQWcN22NcPAQh8uxkxgzOR63MTmKXf8WcDKRci/wwrGpYRZ08hOimzaxka+VMESgi6B44kYefneqI8fIa3Od/zLHMbwTsaWQ7KRLpmZMneXct0kErmZNHkyTUNG9N3KYo1xIIBF1g5cqViCdpVbwrmDdvHhVi9iEdNg1mzJgBWZbx9desxa2b7777DrFYjK5nQsKj+/btS7fHQ0q6CgsLaZv4J598MuX3YSQSod3G+H8CgSA1ZvchCT7PLlom+/xnH6xvWm+Xa+mdF3lkTYWWJHhZ47KACME4oPr8mLvf79AU6o1YIBNalLVR13TXqZ1ZrtXqLHeXM23HRfPHs4Bj7nPcX7r1a+ikLXsDaxqjx6N4edtf8XnTpfS8RdLiKBzNTuhVJQA/mkigIvTNP9Bl/TaySWxNVxA64TrP17UtPgDZSjVzYKSADCvjRkeujUtZFhFx9/RUyJja7KzGix5mudYbq95AVYwFWLdG7LLd+769D5d+eCnaleWO7YWCzoDjT3pPgD+JAONumnLbG3a5XGfg83rKckIdhkvPXD8T+WVs/8gvT3PMfr1tAXtffJ2rFmPbn8C6Vdc9/7y1bNNll1vXq+66y7oe27qVln/5S0pYl7YYd5wrydvUe5VrUSdPnHVuUwLsb9VraOLnfE9BiDw7mYOGFuHZrIgjCZ7UZ5ZllGF943oEejM1NrJyJTDgYKB+PfD2td26z4K9u1yrKdqUtLa8s/jMQYRrIMKj1tbQnJ941Pu5Vs+vRltLFL6iIvj79beFH+N8JabH8czipxIeR34zhcYjEAg6y4gRI7B2ravN8C5k69atKC4udizz+XzIz8+n9yV7TCAQoOIQT0lJieMxv//97/Hf//6XloGRzJ4rr7ySuoSScc899yAnJ8f616dPnx1+fQLBT50aI4h20SZbFHXkqxiYJ/ZFaUWeTh6vsZaZySPpcahGRyE37rFVVlRCW1oJwmmFWFN2LHX6LG86hGYsk5wbHlIORE6E1foGTycP3T6ftGwwbOULiMoNKGlh47GlS5lwVRElpTo6zeaRfWzwpSlBBPxxSIqOxgr22kur56O4egF1+ShD9kfOdXY5Dk+a3ASMPDHV/CAi7XFEw873ctQ0p7ulx4k8RplclKhvBjJkuvy3c3+LI95knZa/nlpg3f/sj8/iq8qvUIH3Ifnsv1d+pvP345uSEZ128nQVs1xrVHl20jbiZjmiiT/IhCHiqm+MNFrL15VJmDeS3VeSGA9KKbvnnoRlBRf/nF7WPPAXz8c0vfe+dX3zdYaASE4EiJOnaYu9opLYwSwZ5JxdjWlQVY2GLhM3zwX3TKXdt/ZUhMizCzhsVAm2KCrWbmh01C8StVMyOmy1L14E5BiDqwXPAlsSg9YEgp2BUlToudxMrp/64lTPPB6+BOrPpzIrZjICixdyTh5zxsu1vbZWWnIVTxH+trIym7ZcNJ+bL9fSZAmKhz4knDwCgaAr7Kzvi1tuucUz+Jj/t3y5c0Z2Z3P77bdj6tSpmDBhAm0Ff9NNN+G++5wz8jy33norLQUz/23atGmX7p9A8FNgYx3Ls1lWaefapJocyzOCiE3Rx8Q88ecJFrA24fl1y6EbIk/ascytYj2Xy23dq12GL419j9VlsDFea0YZ7WilknIqDrLNrb//Q8Lzyllca2g6oUa2Z383ylocDQH7+6uuVrOd1mTdL/8GJcCWaYEg/L449LiM9go7h8gXjEEiooEShDr9JM/3Sj7lYaBoaEoX+KYfmeuFJzPPzqnpaRAB0HRx8X9zUsZnlW9JEk6/1YcfxmUmPD5TLoMk2+JQcZazzXjYF+h0Jk9XMcu1+GweN6ZTzXpMus9y369tcE6gfDuIHVN/+bdz7G+2V8863HarWveFUju7CHGjZCs0jIU5Zx93HHPytHDNCfwdb8eECDuqqkMjLdSN95YcY8ma0OwJCJFnF/Cv8yYhFlJQW2XXYR494GhUt1Wjqq0K/l69EK+pAUpGAv2nsRV+fKv7dljwkyY4eLDzx9wkyYyRdTdnGz5oCJuZ4Xn9yin2czzydzhaaHlB7L1U5Ek+MEpDK+RQyDoJc5ZrkVae8Hby7JgRSSAQCLrMDTfcQPN2Uv0jbdpJTk51td2MgUDKxUjHLXKfF2R5NBpFg6s7IumulewxBJL5s3nzZlqW5UUwGKQdvvh/AoEgNcRVTFAkLng5RSmWWQLvFnW8WmkXDO+DI/PnoXzrPGjGuEzuz8SkIQPZeEqVmXBTlTbfeHIf2kJsXNYcYPkog1e/BjUsQdV9CU4ezRW6TPcxzy5DUfLyaJkKPz1HrumSDklny0qrWAeuwSGjXHTDl0griiJzrIQ4gmhvThxTBtKj0MippiQh5nLiWM/tEXBLCGb4Uras7snht+TvT0TAqtaqBJGHL99KltukyDIkv/3dL/mdr7XVF4I/SQv1HXfyKClDl70iHojrhZCVH8K8Smc5cXbioUcp/MWlGDzrYyiZiSKXnN6xOLNqylR6KQWDCA4ZDF9BAXPy8AQSt50MIuwQgYcIPWb79D0dIfLsAsjsXU5BCLFm+8t8dOFoerm4djECvXojvGgxUxgvfAcYPAOoNdLrBYKdDAkzJl+CbprbGzFny5wUj7N/eLx+Myb2scsINNK6sAMkXaOKOLFDJsOvtrN9NYUda3aJDDbIzFLiDLxw8ggEgu6gqKiI5uSk+kdKrg444AAq1pCcHZPZs2fT9sBElPGCBC37/X7MmsVa7xJWrFiBjRs30u0lY+HChcjLy6NijkAg2DmM7ZNDLwsyQp1y8viN8ir3CXxE9RZf+994pSOcdt/yfXDVo4eiXx/TyWyIRgo7r5i46T4s6M0ySkI6OyHObt6A5o2hhHItxCLQGmoSnlMKBDBi+TIoYyfh/ciRWLcoMRxZk3QMjRrBzTBKcuiOsNwTMvRTBxqicyQx30vJKYFOHqdrSZtu2CfUzoFmRo79HeYu1SL4jRbXPRGzlG/GqzMcwl5ICWFD0wbPYyLC6SbrYx8gve+TjpbiPLXpuUmdPD7Ze/n71xmmgg7IMEqv5q5xusk6YtqFA1F0Rjs2NW/C4f0Ot5YPrUgyPvf5qOnBCzLZ2yG6Dl3ToEcikILG+sTJwxNwtnDvMHjZcvIIkUeQgl69shCM6Wg3vhxLM0oxMGcg5lbMRdrEibRlodpsqLn5A4GqJSJYRLBriMU9vzBvnH09Lv/YDjJzo3GdrDzrcrkBDt/5QTJ/eNyPMUSeZJk8bBXi9pFd5VrmcwCKx0eEdddKukmBQCDo9gygo446CvRx2yUAAQAASURBVJdeeim++eYbzJkzB1dffTXOPPNMlJeX03W2bNlCRSFyP4Hk5Vx88cW4/vrr8cknn1CB6KKLLqICz/7770/XIe3VSceuJUuWYPXq1XjkkUdw991345prOtcyViAQdI5TJvaml8VZ9kkjcWSQTEMvFGPiy12u9cD8BxLW/Xbrt/i88kt6vbKlgnYuGlUwit6WDJFIM7JFokqiSBSUmKgj6Sr86URQYGOwEeVr6KW+6kP4mpYmfW0bsyYgqgfwweNLEu7TZB0+w8lDApTp9sxg531YbsrC9pPp5aiyxNJUSVGYOESc3Elc3smcPKMPShQA0rJsAYs4w3sqfBe2+nC9I8vGPe4mItDt5yn45WXJRasEkSeUk1TkSaLxYERZ51yb2Va3t87z+ebPcc6K4/FWzauW0+fi0RfT669P8d4hMtZPRmfKtQhqYyP0SNieyHY7eUJMnO0MRGwkAg+pNlC48Om9TuR56KGH0L9/f9qmk8xCmYOSZJAZLNL9oaysjM4uDR06FO+9994ObbOnU1qeAQUSVq+17XbD8obh1ZWv4nt5M70dM1unkpKthg1A9Y/dtbuCn7iTJzBoYMLyWCzc6Rbrnr+lnLIiTbRno/N/zn74PR5AS6uSzeawTerQFQWtjdEEJw95lOLh9qU/9EIgFQgEPZjnn3+eijiHHXYYjjnmGNpG/bHH7C6FpJMWceq0cWUVf/3rX3HcccfRQOWDDjqIlmm9/vrr1v3E6UPGTkT4GT9+PP71r3/Rlut33HHHbn99AsFPGbOldYwbvzy19CmaaWjCO4p9RlmX28nz1prEaIaff/Bz3PzlrfQ6ac4bVe0slnjVVkfwclxOLPfi3dLBbC4Px6hv1+BDKN/ephs9zaOc36AsHmMZPGqcbsfcHjKKST09UDoWWyIkiJlMwjm7d9HXU9AXWkY50P9AM64xcR0z+4UbZ+aXZyCUmSg2nHm7t/OxJ4s8Ne01SbNsCOTvvaK3hG3Zybpl+YkC4VgWU/xJy7X8HuLJh786qNP7HjRah5vHfDL2Ld3Xuv7jNnb++uUWJlZm+jMth9ImV9pD4ZXMtZb0gKAuM/tv3/+V/yZdb/2ZZ6Lxf29BDga8nTx97ViJzpRrkY9wPKra7dP3cLr8Kl5++WU6s0QGEQsWLMC4ceNw5JFHJtSbm5Ca8sMPPxzr16/Hq6++Sgcxjz/+OHpxFq2ubnNPYOSYIqjQ8f5H66xlfbJZ0PLt61jni9gWQ+QZeAi7fGQK0JpolxQIdgQi1vjy8hOWd9TOkCjaKWt8OZFH5jrAeNXXElo/+xwSdPoFmvQ5NR3NPvsXQefarZPJI1+S4GWzXl4gEAh6IqST1gsvvIDm5mYaeExanWdy35VkkoucJB5yyCH2JGQoREUckt3T2tpKBR4+j4e4g77//nu6zZaWFlqqddlll9HW7AKBYOdBXMikNXWOrw/uOOAOFITsjkheGT2mk6czLdQJmvGRlXWnc7rxpZfoZe4fWcvoqFGulUzk4Se8/JFKerms7TDoqgR/ZhxZfdpRct0vnM+d7hR50toruPGVBp2cKqoRqzU7zfxprQYWPOOw3/iQKPIE0wOIKAW0rotkLHoRNEJ7zS2dctMknHzjJMvh49g3D+GnJ2L+/QkPfv+gdV3ngq07KuEzuWzkTQmZPKlEGK+g4OKszpfvmlk8180YknK9J4980lPUMssV51SwOAhdkhylaFZGaAonlpLL8qL6PP440saMQXCI977ENmxkm8rJ8RZ5MhPzRJM+p1E2GGlXoeytIg+ZJSKWY2IbHjlyJB599FGkp6fTAYsXZDkZoLz55pu0AwQZyBx88MFUyNnebe4J9CvNQqWioXmzHb58wagLcN3E69CYAcSCCiJrVrM7QtnA9N+w64tf6aY9FvyUnTxewctkMJGK5s8+t76DOyrX8vqxcf+gt8//hrZRN508w1a8kPCYtoWLHF0kiHiTXchsm6q2HkV2wzr7dShS0sGDQCAQCAQCwY5CymPimo5Th55KA3RNZrwyAzE15shemVQyiV6SfJJUmO2mjYooOi7jW7OTiTF6aZRKRX3JHTmkXKvON8i67WtjVQPzW0+FpkqQFR29p9Yj/7xzHI+Lys4Sl7J1f8JBX1xv7A8ReSQgHrGcPEvbj7JXDtuDMr+emLAbTFMQaY0ldGz16pJV3N/oMlaWgWCaz9NNQZzbB505FJOO7oc90clD2qO78QrjNtFiOZhWdrSjXKvmFib4+VI4be44nrmr3B2zOsMBgwowsW8uTp7YcYv6A3sd6LmciFkPHfaQdTtoFAYEhw9HznHHQs7IQNaMxK5aJkpmBs2LypzGtj/wbdsBV3jlFQnr+woKu9wy3Y3ZUSvaHocvsBeKPMSVQ+rCZ3B/GDJjRG7Pm+dM0zZ56623qJWYlGuVlJRg9OjRtGbc7NyzPdskXSOampoc/3oipb0yIbXFEVPZSW12IBuXjLkEY4rHYV0x0L5ihb3ywTcBfQ8ANiZ+AQgEOyzyGK0Kebw6VfHUPf+iVfPrXa5l/2BrHtvSjOOeX1+Kx1C5mg0KslrYAMSxCmk7zFlQiciTW5yO3JJ0NPtXILstcZBABgKpOnYJBAIBD2k1XkA6cQgEAkEnIeUx5nh+S8sWaznpmkvyNr+v/p7efuDgB2gGJ+HP3/6ZXla2VOL5Zc87tlcXrsNdX91ldQ81y7X4QOfQUNPBwBwsEX8qkUcDcnsnCESa7qNOHskMNfQ7w2g3NjhzS/pXx+Ez3CWVflLCIhsij0dOSf1666qsJ0YA+IOKlcNoOq7P2/cFnJR/G73eb3QB0jLZifk+R/fHuX84wOqaZZVxGRx4GnsvxhzSG/v/zBazerrIY5buHdz7YM912+PtKEkvwZXjjTImACXRs9kVXUFc1Wm2ESE0ahSaJrLg/WTlWoSLpg7AuN723zVZfk+yTJ7Xr5yKspyOc3H6Z/enl2+ufjPhvj5ZffDY4XZJMiFjyhT4ioow7Lv5CPS2j9XOIPmN7KlAopATGsHaqO9IQGfI6ObWUheGL0VnsZ+syFNbW0vFGSLW8JDbW7eyulE3a9eupWVa5HEkh+f222/HAw88gLvuumu7t3nPPffQUELzX58+rAyqpzGgXw4y4hJ+2ORsgUqsnltyNWxb7Qo5638gsOpDIJZoeRQIdqRcyx3ahiT5Njyk84st8qR28rjLpVRVQ1uTczBCBxxcfbov3oZDP73KuU3agl1xlGuREgYyUIj6gEA8SSK+EHkEAkEnIWMIIfIIBIKuQMZDsSSu4atnX43LPrqMrSf7aXgyz8srXsa939zrWNYQbrCyTBzlWkbhkhaNIrp8Gb2+cBZzBLUFUos81RG7I5I82Mxh0Z0iT7DzbaWJx4SWa81/wgpeJmyKjPFY2SOTx++zshVNx3VWejt8EnsdWQUhh0snpygtadmR36ON+p5QrpUdZA6lnGDyEOBjBh6D6X2ms8dKCnRSEkeRqHsMPiZwKAX5ltDYkXDzn0v2wxc3TcfyPxzVJZGnK6yqX+XZUp243QjjiuyqHYrqMYjvqsjjTxR5iDNoR8nMY8ciDV7eW8u1ugo5USwuLqYBg6Ql6BlnnIHf/OY3tCRre7n11ltpTbv5b9Om1HbI7mLYkHxk6hJmfWMr/oSheUOh9yuHf+UGxOvquAccDcTagIqFu39nBT9Z9GiUhpiV3/dnzDvqvE47eYiGY2bx0MvhxzlXqLK7NWhx58Dn4yd/RNU6l8NOJ0MFLqzZFUhIVyFfSS4nDzEMEY2JijwerlbyZZwqzFkgEAgEAoFgRyAnytFOjDX8it9xkp8sd4Xk9Wxs3mi5mE2RJ91w2jR/8AECUeZ8bqppd7RQ90TX0WqsT+g/jJ34jkibbZVreeFTdATD3LkIh2KWa0kKdQSZvFX/e8d6E0vnADUr7QVGLpgS8NljOdI9lWxqxbuWYJSqVTVxcPMEQomTlXuCk4c4togIwju03BBhz3T8kHK9I0caLhddQlzV4CsuQuG116D87rstobEj4SYr5Eef/HQrY2dXQCJICLlBO5fzd1N+R89zCeaxfNcZbF+1th0wMRiT1V5OHi1suMhGnQxMZfvUVXgRca8MXi4sLISiKKiqqnIsJ7f5MEAe0lGLdNMij+PbiRKXDinV2p5tkg5d2dnZjn89kdIBbL8yZ9v1mCZ5J55EbZmrXvq3vbB4FBDIooq5QNBZNjaxQYIXWiQCta4OvqJi5Bx/PBryirsg8mhWHS8df7jdPE8eYV1tiTm/dNcsSAxNJ04e0z5MkPmQQr8MWY1Cl2Q2oDD3X9PoDBCZ4Yn6Uzh5Ohp4bZgH3JkDtHkPZAQCgUAgEAiS4ffZ5VqpcLsaCF4n+HwXLbqOLNHzggw/E2cqbrwJ/liLY5247O3kKR+ZjbqMWmixBfZ+BGQUFEssPJl38rhQNYmVenkgkR0i4kNmMVQEk1btZ7UtAiKNCJSxk/2ck06kl2YGPJkIJE4eVo6vW6VfZg6KF+nZAVz4p6lWl6091clDb0sKtrXbLis3xP1lHjdk3Ul92FhdJ+VaVByTUHTllfAVFtJjkEy8ejZE2c0MzhtML1u447QwzcjH4WhJM9xp7Tsg8pjnIB7HTHCg0UHYHwIOdwqQnYVUDJjslZk8gUCAunFmzZrlOAkjt0nujhckbHn16tV0PZOVK1dS8Ydsb3u2uaeQU5QOPSCjVdahuspZDhl/Er4bLGHLGy/bbRfJwTn4MGDNbNESWtApfqj5Ace+cSw+3/y5Y3n74iVofPsdaEZelZLHkurj3Ee+Q5FH1VCQwcQbah9OcUwukJ1tCj1X1Z0iT/HhZcgZwIL6+gzPg6YEsKX8QGhmAqFVrmU6eST4t7dca+kb7LLO7nYnEAgEAoFA0PlyLTbWOG7gccnXM9qdnzX8LMvRwHfZMsuxrpxlZ7AQ4n6ZTmQR90PUqFBwiy/JRJ68gQGoZHgXt900ik+BpPhopg5z8iQ+jrhr6BjLeJ4xS/7luH9a+TBoZNwYa0NcdpbEkMd97rubXqcu7XAj+t9xFgZ/+gmKrrkGWUcfhUApi+J4/f7v8PlLK5nre+TPWIeuDpw8hIycIMItzL3k1W2rp+LuNkWcXMThlYwDyg+wRR5ZQYALEKblWhyxuEY7vfUEzJDw5miztawozdnR6uj+R+P0/S6l19UGZ3xJV0j2iocvWYy0sWOdC6+YB5z2TJe27w/Yf7M96VhLRZdfBWl1TlqgP/PMM1i2bBmuuOIK2tqTdMYinH/++bScyoTcT7prXXfddVTceffdd2nwMgli7uw292R6H1iKoAYsq3S2BSrPLMfXEzPQa1MbwkvtsheMPR1o2wY0OUu8BAIv6tqZM2VFHRfiDWD9aaeh4sYbaR4PX8vKl5O7RZ4hW5w/JMRe+9czxuPUSb1ZwJuHckOWaFwniFS4nTyBdBmyX8P0H2/DkZeOpsvaMspYyB+3D1TAibZamTwkpK7L3bXMgVLP+F0UCATdzLRp0/Dss8/SRg4CgUDQEaSLqFkq05ErgxBSQlaZVn243rp/RMEIq4zHsf2IigtmafjztD9DNSbo3EOWoUVJWkkjRnN9iPHGhJRnyYEQFWmSOXlMF3QowvbFH7UdGbdcn4c8MvlMJt7iYUThzPKZW/w0lmxhr6XEz8QlJTsP/tJS+q/3X/8KJY25f2o3cY6k4/6GnEufpVd7DbXLfDpkD5r8NkWe4jTbPT+xeKLnuv889J+0G5sp8hDhpCHCxBAlVEXLtXjIMZisfXqPEHnSnSLPnw/+M84++Bp6Pevww7f/yTyyQTMPPdQzcxQlI4FRJ3Zt88QdZYg7Pk7w2ZPp8lFCMnXuv/9+/Pa3v8X48eOxcOFCzJw50wpO3rhxIyorK631SSjyBx98gG+//RZjx47FtddeSwWfW265pdPb3JMZ3D8HPkhYsS6x9/NxF/wOER+w5OOX7YUlo9hl5Q+7cS8FeyqZAfaj+/XWr5N21uJFnjj3JekWefKbE0WeEWXZmDZhPf5vzv95ptavHXACPj34n53bWeLk4b6jZSlObwfDtfBF7QGTo1xL1bHq2yps3axaIs/CamdmFbH/uoOfE5/b3Heh8nQXn66oxn53f4zWyPYH7wkEO4v//ve/2Lx5Mw488EA60UQmoQQCgSBlJo9xwn32CKP7kQemCyPoC1qTUryg0yszdWvqvq0h75alAH4z1Z5E54nqEagSy/QxUWipFZlakxGu9xG7TsLjzM6kvSq+xISFf0Nu01p6u7Kfiv9d+DHtdkyn51QNy5udju2Fi+0gYTNIGenOQHtPp056PrIHDsTlDx2CviM7H4DfaxhzpO8JmOJHXsje54tGX4RXj3/Vsd7nZ3yOQ/ocQq/z5Vp9s/ta67jDvmOkKUoPcZrIhozAl2vlBRP/TpIs05boeWecvv1PZp5AGGJf+Z/uRe+HHsTORDe2HdiDSgNTsV1HydVXX40NGzbQGbCvv/4a++23n3Xfp59+iqefftqxPim7+uqrrxAOh7FmzRrcdtttjoyejra5J9N/CDvY1y9PzAIpze6Fynxgwfx37YU5fYGy8cAHtwHt229rE+wdpPlYJ4JI3Hs22nLyBEwnT/JyLTIL5OfUeBiDGSLwvLXmLcO342RDvyMTnzPJbItE5pO4ADjFp0PyB1Et+TDmtcOQ3bQOxdULHM/CO3RIJo+fOJ5dsxoKdfJ0IkWabTD1eoJdxoVPfYuqpgiWVrgCuQWCboCUjBPXMZlQGjlyJE466SQceuih3b1bAoGgJ7dQN5wv/Em4m+wAy+MMKkHLyRPTYilPgnm2XHsdaVHqeV8olJiLQ4hLMagKkM0ZnUkeTvX6JixrPxxxPYhwXWJgbbiV7Vf+jGnIa2CdkghLpkdIajIkkpOoSx3mHiqmyJM/wLk8heMk1X1ekFyaPQVTsDFdXabwMyx/mHX7zwf92SECmeuS9UhXqnsP/CtaVt2aEPcRi+sp26d3h5hFmNZrGh6d8WhCHtFOw/j761Hjs6T4dvoxoRnnHHttuZag6y3ZwkEJTVtaE+4jH+K27CAOmt+OeH29/a18+jNAwyY7R0QgSIIpqPD13p5OHsPOyHsoEkQeCchrWAnFmHlKcMe4nDxJnpLWeCfZWcg+I2xPjUKRVRqgFjXcNUqcpOPrCC9lLUUJsaj9JMTJQ5e9/WvHZklwn/nFXPfMM6h91FlT7th3+hyC7iSDC7cTCLoL0rCBTCZdc801+Oabb3D00UfjkEPYjKpAIBCkyuQZmDMQ/5j+D8/1zFbZpFyrMdKI11a+hrgWT3Bgm5wx7Ax6+clYNhaSQiHa+MKLZBk2uqwh4pew3wp7/KX47TKWqD8LuQNZBiJPSx0bExUecbBjOS3tUnz0nIQ4eSKR1CfTPsk48eZEDa/9PemGCdgbMMUP829tdqEiHNrnUPx6n1/j6AFHOx7DO3nYetOhx3MQdx0Li7c0Jgg/3QURWcyMqQnFEzC119Rd+WT0IuOA/WmnrfSJu+5YUn4i3bX2nH50ezBqtg8FlRHWBs+lXBdlkpK0jah/638ouuBCtjCvP5BVCrzzS2D5u8BBvwb67t89Oy/o0WhGS3J3To2JqXhb5VpcuRIVeWgYMmvfSUQeGgloqDcJYo3LoRMPe38JxpPM+LA8HraNYStfhDyI1IjLtIZcIV0XoNPuWnxNVzyqJYg88dr1iZk8xr5W3XMvvUzfbzLSJ3A/AAuMADaPNqaC3Uu8o/wkgWA38Pzzz+PJJ5+kg9TzzjuPZvQIBAJBMki3Ub50xquLECHdx9pGh3whennnvDsxOJd1ITJP4vtk9cGmZhauXJZRRi+tPB1ZQu2DD3lum5RP8VRnbEBxaz+EtXZEXEadsfN/g8vxd3qdjK98M64DpjoDahuq22kVe0G/XPC1A8QVRB+nMCfPrG/t/fdCgeHkcYULy5wjYtCEIpQb1Q0/dUyhhuSvfnTqRyhJt+NH/n4o+5u4Ic4vU0Ak+AyBzF2u9fEyZzfqnvBa43rcOt53FWnjx6Nl1iyEhg/HiCWLd+lz9RvV+TLCnsxPQ6rq4aSVpkMhuTwbEsuvsu69k17WVrI6WIsp17LL1R8BTx65RwWOCXa/kyecxKGix91OHltAIQOKPz6j4qm/MlGHdGYgYo/ZZSEhgse1oCWe7/mcMa7TlUMN13VoTEmCL94OiRSPywoVmwIxUi5OXouE4GgWwkz3N5Lo5ImTwnNXWJo7eHmbl5uHPtjuTPG/v32PTT+Kluq7m860oBUIdjXHH3883njjDfzxj3/E+++/j8MOOwyPPPJId++WQCDYAzJ5+HJ5N2YJiVmqRWiNtVoOn31K9qH5LCamy2f+EMPVnJ2D1rlzPbdtOmMkTUWw7mHEFDameWHl84gkb97EJth6TwCGOd0jpLGFzydDyXS6i7KNgGdSDh/Ws7Gpio33Cvs41zPxSRFvkYdz8mxvmO1hF4zAyKlMCNvTnDzE5VKaUdqpsiLi5Hn26Gdx9zTWsczsoKVyTh53CHNPwHxtpki1q+h1/30Y+P572B1IPaR72Y4iRJ7dwOGHsxrVdWsSRZ4RvSdgcX8J4Y8/RfOnn0KLGieh+18OnP6cvSLpuCUQuNANZwxR0TsTvMxrIT5Vx5BKID1iZ/IQJ42ismMw0Q3qXBBR2WxVSpGH+4EnM0mqzn7kg9EmUNOOIiOvFThqAe3TRUWmwICBnuVa5sxS1g/O2QLyHKTVOk/LZ5/ZdmdeIOXEsM3L6/HRU1xnO8Eu4+Mf7ZknfpAsEHQXRx11FHXvnHzyybTrZ3V1Nf75z06GyAsEgr0OkoPCn2SnyuUhHNnfzixsibbgxEEn4j/H/AdTek2xAmv5cvuvh8tY1F+C7MrdCRbbt1tjbKzXHKvG6/sut8ZlmqR2IPKQyT57BVVTsaVlC83aIZNxcrpzPLf/Mey7MCfXObY67qpxGDElUXCxNIwU5VqdbMSawPADyjD9PNbFa08bm3cVUvJUnF5siSeKLDmcPM3heI99rXzb912BnJaG4ABn5pMgNULk2Q0M7J+NOHQ8/+GahPuIvS3Nn4HQ5hpsvvwK1PIziSNPAC79hF2vd5aoCAQEzXDXaEnqt2EEL8P4cY9xTp48rqMlgXTJ1CUfFGP2KbiPK/zcFVocTSLyRGOqo/OVCamfJeHLBFmLQQ6S+5lyc9ZnmuXk0cIRa3AQN0Se8RmvWVbmrDWBxEweTU8IfNaajRBpNYp2LQvNagG9zhNu7Xk/mD9FLnl2vnVdlGsJegIPPfQQdfKQRg8//PADFi9ejB9/tPPABAKBIDGTx/798jqpzfJneZZzNcea4Vf8NIvTHVjL5/XEZXtyjjD4k9lYUmdn6dw7axVmpkWx+sAh2FRsj69UWTVK7r0hHbbMyT7CQwsfwlGvHYWNDZtoSZW7DfXIgpH0Mi3deZqYnh3AwAnOFtkOUjh5firuiM6QrAFJVyFuHj5/55XvWIlfT4I/fgU9CyHy7AYCAR/aAhLSI7pnWFb76P7W9XjlVuedBYPY5cvn7vL9FOy5Ik8yJ4/pDLMyeYiSY3DoIvtY9Md02l1Tk2T4VMPtkpbh2Na3cWdXpNnq9Z7PGeXcN2284ENqyY0fPjKg8GfKtFzLRgdCacg4mAUAyqQlaEMlvT6/YCUVoQhKTELLF19w22V3tH5rCwkEtcnY31g7nqv5F56t+bfl5DF/gJOGRAt2GaJcS9ATGDRoEAoLC7F+/XocbHznCAQCQTICrnItr5KtayZek/TxZrCuW+Q5Z8Q5jvWavuRKtRQFH6Tbk1ON7VEsDqrYf5hTaCFOnn1WsfFMRsuWhOcmLm2JC2KeUzGHXr618m0oPqf4knvaqdZ1fzCxPN4t1gyZlJ9U5OE7aO1NIo/JjnZ/isQ1GrRs8qPRnfTJC/dBT8PMlhL0HITIs5vo1ScbeZqEiobEgNzmM4/E1ZcraDlqf7R//73zzhCr4UVzJdAm8kMEqcUeN7rhijFbqPMiD09GhGX06CQjx3DyNM/9ChsvvsRa5+e+bWjlfrBa4T2bY7YYJchRTkQhP/aGuOIrKqCuHo3UiBFhSCGZPBqCw4bRenS6r1oAq5ax52tQZFrWaLLp0l8kzBStv/Bi53vSbnzW4hHEdGMgZraaF9pOt+EOERQIupNoNIovv/yyu3dDIBDsQd21TL455xtcO8HI0AQwsXhi0sf7pESR55oJ16AgzQ55nbhWh9RuO3eI27mdO1ObvbyaXuZn+BNEnnzDnb3Pgj/j/YHOLqSkVop38pitu/tnDrTaRX//66PRkK2g9M477dfs0Q2T1y1OumEiDr9gqL3A5W7inTzlg3Oxt2CWMJmdp3aEV7/bTC/DMRVvLqyg1w8dbgc59xT2K3O5/wXdjhB5dhNFZRkYEFewan1iLs/Zo85BdZ6EOYV1iG7YALXF1W79vDfZ5brPd9PeCvY0cSdZC3VT6LCCl5OIPOTniOQga6Rcy3C7aLIfrXPYbI/Jffkdd0aIcR2x+GeTuVkcUmIFLQ7dCNqJkd3Tyc+ilMTmqtORxWaPwHtzEKEb3QzcncUcJVqRpp1qpRV0HeHkEQgEAsGeht8nef5+mQ6d2/e/HcPyhyV9vFeGD2mznhJXNy3TfCwbSovOiTy/upSNgRRaPuMsTadNNQIBa9y4sWkjvZ4hZ1oiz4IhMm68Ptcqo6evOZTYhJkXLsj4S+KFnYRyLXv/h+1Xir2FghAbrE4sSS76dZX121znhgJBBwiRZzeRbnyJrpzJvljdds9RBaPwYZBl9rT/sNC5wqDpTB1/5QKgVQQwCzxEHldejokeNkQeYwbH+bNvU1oPnPMJCT5WaLkWcdW0pSU6dRoyOhZ5Kuvbkw9WjP2lFlYyEDEGMERgYi3WSTCQx+s0xhRhf1dEHuPV8i6n2XexRULj6TbiyfKjBIJdwOWXX47HH38c8+fPp64dgUAg2G4nT1xPKvKYbbOTwWf4NEebHY6a545+Du+d9B7+dMAFjseQMvdjxyaWwZBAXh5VjmNLoYQt/2Rl9JlhHfc+aZfx06YaWSwvaMYrM6z27RoJXjbOTz5Y/wEaI43O1xz0GnRxrz3gLrtHUifP3kRRehHmnjUXxw08boe3lRVkx1eaf/u6kwk6z+EXj8TBZycXavc0hMizm5gwgyn48U1tnjkgg3IHYVMREPVLiK5enbiBYiNZ/p3rdvm+CvYcTEdKUidPm9PJkyyg+aZXVfSrYeVaJBQ5TW9C3KM9qJrJUv8JQ9SPHfcpYAOKm175wVr2oz/umNExxRXSVYuIPIFCNosVUwwnj+7tslEN5SfKjTd0VXXMFJFBjLfI4/HeCJGn2/AaJAsEuwoSqHz99ddj8uTJyMrKwoQJE3DxxRfj4YcfxldffYXWVjE7KhAIOpfJk8qJSoKVU2GGLhPa42xslu5jDSzGF49Hn+w+CAedWYikS6jXyb0iSbhl8i3WbU1i+5WXySbnLv1QwkC7qSWdBJONNuk17TX24+KwRJ6S9BLa3t3xPMFAypwZH9m3FLkze6vIQ8gK2CHc28tJE3phRHm2w73V0yDi5uXjLsdPgaH7lmL0Qb3wU0GIPLuJ7MI0fNZLouG2M59N7ODxm/1+g/45A9AS1FE316Ms6+cfsMtlbwPtiSVfgr0Ts+6XiDwxLYYVdSsSy7XID4Oi0Hreqnq71psndwCrqdbIQID86kfDCaIJu9/+kQnpjZC5UqjiIKsVV5LVIFMxxlR52OgiZyybxVpfQgzAOrUUe7lsVMvJY29baw87BhGaazZJjxn75iFs8UJStAe2pPwpc9Nri7p7FwR7EXPmzEFTUxPtnPXUU0/hsMMOw7p16/B///d/mDJlCvbff//u3kWBQLCHOHncwcsE0/2SF0x0Ol88+mKa2bP4gsWObltmRyLFNW5RXW4gJTubNmz5V1YYj2YbTTFImVXQ5xBkNIltzxdg7dbLa9nklq/5DXpJSuGVgsR6d13VofhZmXxUjWJ04WjH/ZI/cbKP1xqokycFe7PIszMI+mREjZzLnupAX3j+Qlw1/qru3g2BB0Lk2Y2cfvRg1Mga1s6vRpzrOkRI96fjocMeosFpsc/mIrJunfPB5Iv2MkP8+dHI6BHs9Vgt1HUN93x9D059+1RHO0NSrkVKtcjMy6qqFshJApp9ugxV9qMto4xm8ci09Tr7eshqs39ZItyvjK7L8Mda4IuxmXAZhrOG264zk8cOXqb5PFockuLDxkLAp5LuXhoQaQVet0OVTcxXFOEnlYwStaTlWvWVSZ08/G9lLOLtghLsPMpzQhheas9qReLiPRfsPsj33/Dhw3H22Wfj/vvvx+zZs1FXV4fVq1fj5Zdfxs0339zduygQCPbA4GVCQ4RNvOaHuC5TBr+c9EtcOvbShOWm+5rvuEWIcArKoJnv03ycuKajSdGhZNrrpgcU6hwy83FIudaLx75oiTwmgbZl9DLn1FM9Oz3pqkSdPH/69k+oj9RbziILn729405WE508gdQlRHx3LcH2iTxkgpagGePnR8+d1M17JdhTEJ++3cip+/TBOxlRkn6LTSvqE+4vzyzHvaeyP8mKf/0lcQNl44DyicCXfwMirJ5XsHdjOnmIyDOvYp51nS/XMku1iMaiJBF5SN331lKWjF9bMAbx3HRLNBm41ZZEalQ7b0fTZSrMUHGGOng0K1/H2i7/HFx3LdpKk4hRkgLSYMtHf8N06OEm6B5fS6qx0ajPo1zLqE1PKNf64h/GjnKCgo+Vh/Elk2pMZMTsakIBBdOG2LOYrUJYE/QABg4ciNNOOw133313d++KQCDYA4KXTVcFjzmxlhvqfPcoy8njmpxqNTqOEgL9+9NLTdPp7+clBw6w7ksjIo/sR0BlY5qwr5W6cBSfs7xKMZ3Mfrb8u6rvrPv2L9ufzoERkefN1W8m5AaxJ7cnDfvtO4ReCifP7iM/I4htrcyVrhrj5/yMxBI6gcALIfLsZo6f1hcadMz+ZkvCfUTRP+/Sv+Oz0RIa5n9lZ4q4Q5jr1wH39N49Oyzo0fCCTlhlVt5Yq9FHk1xvabJCl+/7YAXqgqy21034xx8RDrJZqGCkHrpPhmaIJm0BbtaGWIuN0sEIaJCOEZhMvkyMUGXS4lxhJ/HfB1WHkCRZIg/L5EHhYJCGX0TkIfeRe02z0Oi0963HLgwFE4OXjcGLncnjHCxteZuFlOvcIGVrZFDCa48LkWeXQwapfHe1FlEiJxAIBII9iKyQH83hOP094/nlxF/ipn1vQnlGeae35eXkISVTcY8Q43cXV2JjXRt8xlhnXJ9cjCrPQUAOYHnxV3TZLyZdQi/9AWe3roBZ6mPkBbUazusDyg5AcXoxEJfg88tUMOJbu1ukMeEqQ64FQjn2JJ2BmeeTDH5dQdcpyAxgW0uEHhtmzIB4SwWdRYg8u5k7ThgNLSBj0/waz5KFGf1mYEOxhKLNLVhx6PTEDUw4z77euHkX761gTxJ5zB+A6mt+ZS37bvGHgCHyfLqiBrXpubjgegWL+yX+SsT8LPBP1lWo2UHLGePjNJDSQC7Qd3/g4FsQJSIPGaiYqowxaJGMDJ3l/jjaSQiVgaTY7dEjixcD9etp1zjSOatPLX010HUiGbHnlST+88EelylrCU4ef5CtbwZF50wdmVTEea0msbuWcPLseojd3MeNTLxyDQQCgUAg6KkUZQbpb1l9m3MCljh4zht5nmc5VDLMjqi8k4f8Lm7KKvFcf8O2Nus3dGJfJryQcq2lpV/i0QOuwxXjrqDLfH6nyBOKGr+1PjYOzPSz8OVfTfoV6sJ1iLTH4Q8pVslZgsiTPxAXFF2MMwt/CXhMEjpec3pi5o9gxyBleURTJMeGqS125TgT7N0IkacbKOyfDaLdf7GSntkmMG78EfRSr62DHos578wfAFyzgF3//vldvq+CPaNci78e+dEO9h62Lgq4jqH2oFnF7cR02RBvjuaTEBo/gd4meTmHt7bRfzErOJmUXplByqbIYzt5JGNplHuipspqq9sXEXQoso+KPH6VBCcHUNNqDxJMZxD/2vwKJw4YIk/Tb1nL0Pa0QvR+8J8ov+F8+3Gahm2VHo44TuURTp5dD5n5JN1ATEQbdYFAIBDsSWQEmSDT7srU3B7KMllb9NwgE2xI1g85JzAd1CZmHsuJ48upwET4eBlrm0WcPG4y050lY2kRs1zL7ygTI2LPl1u+hF8Nojq+1Vq/d1ZilUBmaQlCcqvVKt1TZLhoJnD5l0lfL+/kFXQes7NaOKrRAG6CIt5LQScRIk83MGG/MuRpMn759HzrQ8tzxiUPoKWQuSq+/uDpxA0UDAKyewGf3g3cmQOoovRhb4XvEkVmZf7vRRV6s12uRVAbWecH3kkhexx3EhdQrEs6fMVsRomUUp3X2ISArnMiD3HlkB8f+2Q9yyjrMp+FrBnhnDz4ao4lCJmCEnXyyE4nkeXk4UUeYztqgBO1DDdIZO6XkLQY9KJeyJoxAwiwmSq6fsU6hNtdAzKjVbu1zk4YsAlSQwanCinRM2+rPbRNhEAgEAgEHgR97IQ74pHL01XOGn4W/nPMfzAwdyC9/fAna3DJs/Md6yzZ0ojqpgi9fsqk3laZ8zGjy5K2bM9Jd3b4yggbk2/pmQ6Rh5SJPXnkk/BrQVSE7aqAw/oelrizF7wF/OJT66ZH41Wg3wFAdvJyteFT2T4LukbIFHniqhW8LDQeQWcRIk83MGAsCyC9qCmExz9fk3A/ySvJfPNZtAWAd975m/dGDrRLcvC/q4A4+yEQ7L3lWmlhHWPXJz95vmgqC/EjjNyUeL8ZoExT9SQNmiHX5LePREv7aPiJyMOvw/qgI5IuWWVe9C66LbZaYY5tHbaEHYpx3RdElmHuKa5mDrUvmlhtuSR5BBx6dNeim4mH0dYax0OXz8a6VfbzrDvzfPt1mc9MHsftinDy7HrI4IRvsmHOSAoEAoFAsCcQ8ssOd82OQMqixhWNs25vaWhLWOe4f36Jq15g46KS7BBOGF+OY8eU4VeHD6XLzBwdHsUIWDbJtEQeNokW122RZ9/SfSHrMhZuW5h6ZzOLgXLm7OadPJn5zk5eyfjFPw7GwWcN69S6Am+Rpz2qWpOTsijXEnQSIfJ0A2lZ7Es4BAlvvrUaWxrsjkUmIwpHItKvBOd8quHx7/+VuJF9fs7skYRFLwF3FQOz/uAMGxH85CFSjAlfyZSMvqVNKe5lx87XY1fTwyhiDA6GtFyBRdW3M5HHej7JKNfSOHdOYrnW3Nv4WSEtUfCRZJTXsauyMcOkgn0+tnKBfma51oLMgCOTx8zlUdQIwkFW6rViGZDdjw2Y4qTk0VUapMXJj6XortW9Th7xngsEAoFgz3PynP3415h+v+1s2Rnwv488i7c0WnlAQ0uy8NA5E60T/4T8HILRTdXEmuRS2PKYFnMEPku67Cj77xSGxpBb7Gq3ngR/QBHlWtuJ3+hORkrczcoPIfIIOosQebqJn99/IL0cE1WwvNL7xLuglmWJzH3VaAXNQ2pjiT3yirn2si/uB5a8tov2WNDTILbbfy/6t3W7o6/9mKqjKZsJhrVZ3uukt1Vh5eCFwJYMbFnlPC79OjgnDxkYsHItc4AgG23OTZGHtM3meXLkMfa+mttR7bwc2Rh8mLyXYZddhXQVV9Q3oo2fOFJVaG1MzJH1uBUUTTadWWY727xFHvu2cPLsesjghHfykGNRIBAIBII9zcnT2B7DulrWpSoV1c1h/FiRamLNJthBl6rc9ETXjhfEZRN3bMrormUEPPPlWnR90uzCwzXd0XPQbbjGeIKdjymOkXkxq1xLnLkLOok4VLqJtMwAeg3LRY4u491FlZ7r9HvqSXp5wDIdjRGm5idQMgq4sxG4bhG7/drFwBNHArFEd5Dgp8XcirlYUb+iU06epbVL8W3Lv6w6qj+cpSB69nGOdYhIImlxtMRb0OpPPN580BE3c3sUPzQ6A6RZXbUU4yx+2uAiKvJM7OesDQ87rMXGSb4awxejJE+RR9G51qIAsjUNYa6dO8nk0VrZQKstrRjVJfvQ62tXy9BIey/zeVdvdGxXjcWFk6c7WqiL4GWBQCAQ7OFOns5y6P2f4Zh/fNGpdctznV2xIlxrdVJq35WOSmbOIT+hRhpqeIk8JLy56yIPu/QFxCnkrsbM0iQTZWaVO9/EQiBIhfiEdiMDxxcjV5cwe3k1PQlyExo+HPJJx2DcOh2vrnw19cby+gHH/ZVd3/QVsPiVXbTXgp5Cuu78oneLPFvy7eu3fHELNsY+gSrV09v77XcSxv32PvR78QWnyAMdTdEmLC77DHF/BJGgbflhmTyGyEMFG9ZdS9ZYxtSS+sVsP4zdSrSUmsMMbkmf/bGlwBR5nAHiMjdSIV26AjN+53TyaKol8riTAFXVvt22bK3jvvrKVkcmj9dnT7BrW6iLTB6BQCAQ7El05LZx0xLpfFMU3t16zSG/xM8Pv9W6XcZlG3YGxR9M7JoqeYs8PinQ5XKtUAabsOs9zDmRJ9j5mONoJvIYbnkh8gg6iRB5upHMvCDJt0W0NYZFRt2tm7JDjkR2OzD/27cc7gNPJl4ITLqQXf/mMZHP8xMn7bmTHbdlTuSpzgHuOtOedVrftJ5dMZw8U3tNZbcdxwhpi842ospxyHE/1gz8mbNcyxRiFJ/t5DGoRI25FZAm7e4abFLYld20jl7vPbUG9QUTsSG/txXSrGjOVucy7d7FIMaczMwybOXGFLyTx01c49Qg1w9iQ3W742VronRoNwUvS3j5F/vT26K7lkAgEAj2JMwsnF0B/5t46AkHoS4tp8O8nmQEAnzDCzYxZ5azWyKPZDiFSBlQF508GblBnHfXARgxNXk3LcHOwWyXruq6NSEp4o0EnUWIPN0s8hCyNQn/nb/J260xeV96ecGDKzH22bH4pvKb5BskPwTH/x3Y91Jg62LgiSOANiPVVvDTQlOp8MFDWp2bbM2TnK4XFxm+DCvXxmRLr2loyepLr8flGO26sLXkAKeTxxR5ZL/R6tx+/JyR7Pqy9tfZ/piWHgPiEhq47h38rO065PZqw7Z2Hce/eTwqDMdRgpOHK9ciSlB2MBvD03OtRWpDQydFHud9DVVtDsFUd7lKyHYb//c/z+0Kdix4eUgJc4aZM1ICgUAgEOwJBLro5OkK/G9iRsAZnsy7YDsDP74xnTwRNWaJPIqk2G4QnQhAXS+fzi5ME2HKu7VcS7PLtcT7LugkQuTpRgrKMyH7JBxSmIMVW5s91/Hl5SHWvww5bYA/ruOzzZ91vOGj/8wuN38DvH8zy+cRGT0/LaKtnIeGYeQeU0i1El+X7WZg7kDLDeNFRjQ7YRmRdVrj7WjbWgFdJgk9CnTThkOe0xB1WtQKqqv4+KRdQ+Qh/zINx4/Zon3eiGSZPPasGbETZwey8deT3rCWxSq2IF5b673/A2zBSK9wtgddMLvacTvcGqP/TCp/ewcqbr4FWrv4zOwMyOwTGWeSw8GsJRclcgKBQCDYkyAn12a3o10h8hRmBvDEBfsgzyiHMknrooNIj/FjKTbGqw3XWy3UzVItui75fe5qdy1B9wYvi3ItQScRIk83ovhlZOYG0T89RNskhmOcFYNj8D0P0MtetcCahjUdb5g4eq78ml1f/F/gj6Xs37ZOPFawZxBrh4rkmTxaCpEnK5CFXpm92A2jPEtzZdpszP0x4XGkXCvQEsGGQw7DtlnfUycPX67V7jddNRJKsoLISeugGwTpEEdXl1CZ5xR53hz1F0e5FoGIPEXpRfj4ZCbg6JEoKm68iV4/7oqRjnV1fwBZfUyRhr1PRxxmu9pm/ovlBxHmv7ceT9xghyNqLc0eAyXB9kJsxgTi5DEPM6HxCAQCgWBPw++avNpZkBP4tICCw0aUWK2yTU6aaIzXOgk/djGDl1kLbhXrGtdZIg9x/JCf5/w0Vgc/PH/4Tnglgl0VvHzOv9l5nXDyCDqLEHm6GX/IB/XHRmRGdBrA7EVwyFB6ee+zOr7dPA914U6UYBUPB6Zc41z2z4nAl3/bKfst6GZirdBc3/MKpxGSFppc9rCDLH9WQnvx9sMvcKxTk5lYPkjKtdLD7PryZSuh00weezDSGKqil6TMqzgrCMn1QzTAv5Xd7zODAO0dJEt4kUeVNUg6f79OxSnC24OYeFT1xz9a95cMLnA8V1wPQPYbXSWM7fQbYL9B1Rs8nHMr3geWvU3zhgiRNUIU3RmYA1YyNjZnoES5lkAgEAj2NHbVCTZxavAhuyaT++d3XViKs4mwXv/8B53iUuJhxKIaHlv8GF5e8TJaY2xCzvwZvnjsxXj1+Ffx8GEP77TXI9g5eB0TXS3fE+y9CJGnm/EHmFthUsSHK59fgPpWZ/gsQcnMgK+8DLKqYdQGHbM2zurcxg/gRJ7CYezy4zuADfN2zs4Luo9oGyp9zrrtySs1p5Mnye+AI5nf+OHwlxQ51uHLsExCZNbHeGirGsO2zHFQ08Z4PIat5HaUXn9oFcom1yOrD1OKqps5p4wE+GMt9m5JGlQ55tg2yeQhVHq0MSXdHs774wE467f70dtxPYjMsgi70zQMGeJNUl48E3j5XEgKe8CGs85Ovb6giyKPbAUGCpFHIBAIBHsau+oEmzYn8JgEOWgo616ajEvHXIr/2+//PO/zl7FgZF+8DdGwjmXbljnuN/MIM0MZGJY/jDqlBT0LM9vSdEQThJNH0FmEyNPNHHvVWHo5OC+dXs5K4uYZ9M479HJ0cw7u//Z+fLHZLi9JSlYJcGcjcEcDcDzn4HnmuJ2y74JuJNaO3xTZ7pV9S/fFKXPtH4EDluuJKouBzJdmGVZet+vGi0yNuGvY9b5fGd26OExXz/Q1Z6N2U4tVTHbyryfS45zUsucObLd2yxRT2GOJA4gTqSQNrQG+45wOP23bDgx2lTWGxrLPUHZBGnxBo4OEHkC2ISYpAaPtZCATmbJ3hg+hWTUGU5yIRPJ5Ylu2YNEnm7F8XmWH75EgEbNdOhkcCyePQCAQCPZUutrpqrOQnDpzbGRGJd536lhcecjglI+7duK1OGP4GZ73yWkhBI84FL54O9Sojk82feIp8oiW3D0XU/gjwcsm7rxLgSAZ4kjpZogDYeSB5egfCKA0O4Q3v9/iuZ6cno60CRMwbkUUbfE2XDnrys4/CfmS6DcFuH4ZMOY0gHQxWv/lznsRgt2PYbdN6JbVCUhnBetxBxyA/AsvRPaRh3dK5PGlaMLgk50ZPaZto2xwLvrnbwBiYedL4KxGTx4l49shEtp9zM2jSyq+7f2+5/P8qsnejlJYiKzphyQ444iTh+5CQIZm2I+kYDomZrDOX140q0UJjp+G//4XtY8/ji9eXolZzzhnwQSdI2KIciE/cfKYwcvdvFMCgUAgEOxGJ8/Dn67Gf7/17qRLnBqmQ8OcBMlND+xQBys5FIIkyZB1Fd9UzE+432rJLZwhPRbzbxONcyKP+HsJOokQeXoA+WUZ1PkwvX8BVlY1O9of8uScfBJ6r2lCZpuRadLV2fDscrvz1ryHdni/BbsP8mP80Cer0RoxukZF2xz3x/TkIcHusi1+1kby+1Fyy83wZTAnGU84WOG4PTAWc4Q7m/xn4p2YPeouyFw7doJsdqGIR4DHDwU2feW4P8rt2LC8dtx3qoK4bJcrqoqzXMuESDCfjTYeSwIGfT4sqlmEV1e+imCGH7Kso1Ut4L7hjK+5QBoUKfn7pOr+BIcRQclK7DQm6DztlsijiHItgUAgEOzx5TPbw59nrsBNry3yvI/8JJqTIOS3ktAS2bHmD1J6OnLOPQs64ohz5f1D8obQS001nDxCNOixmIJOOGYPvkW5lqCzCJGnB5CeE6CXQ9dFUN0cwcwlW73X22cf2ib76PgIevvSjy7djifLB0aeCKx4D2hmQbmC7qf/Le/ij+8mdrQy+bGyCfd9sAKnPDKXLYg5RZ6LR1+c9LHm6bSisQ4KTZGmpLMFpOObiSI7nTdFqoYjSqclPLYlWI+V2TVUTJK4rxRrdkhNzJmiL4ETeQLGSf/yYtY9QNYU5MtB7jVwIo8kYUOxBGSkQ1dVKspc/tHl+N2831HTWlqahnq1F9aH96HdnHTTyUOavndC5IFL5BHsGObghLSBNQcnQuMRCAQCwZ7Grgte1i2R5+jRpcgM+rBv//wd2iZx8mRMnISV5eQ32B7X5ARy2HMav83+oBjz9FTMcbQ5WUYQTh5BZxEiTw+g/1iWBdK2qRVZmoQrnl+Aj36sSnDqBPr2hRQI4KpslqnzdeXXiHEdiTrNwaztNCq+3wl7L9hZPP7FuqT3kdaahOVbja5QcacAQzJ5kmGGJUNnMznbwtsS1rFcNwD+MPUP9LIthwkuhECUCUOXDj2HbcpYHo19aK3j9PHwIo/3MapxLeBPMtqWf9/rI3w05GnUpVciwJWVHa6nWdcVSIiTu6JRaC0tkDZ/i+YYe3xcj8On6FjcdizebfgNDXS2yrXKJ0JGCpEH3k4e+9UKdtTJY7rI+BBBgUAgEAj2BDZssyfYllUmTpiZ8N2QVlV5dPN0r6/rMON+ynPTsOR3R6K3kdXZZYwxjBQMwif5oMkqFGP8R5cbv8PhVjYe8nGTe4KehSnotEftEbZw8gg6i/hk9wBIjsiY6b3p9TOKmXJ/6bPzcfWLThGGnHwGBg1CdPUa/O0QFqS8sHph15+weCS7fMvVYl3QYzFrpwcUGtk7sXbnCg3edd6EWrPaSE8xW2P8Zow+uBdOHHwi9mkPo7HQ7uIm6ewHRo+rjgfEYQeF667wPklJ7eRRua+foHHSTwYjawq/p5sPROxuW6WSPUDxQUKMvJQYK11r/vIb675PNn4CxWjRTvdJ5lQuRYaS5swuGrd/KNHJ4w5W3IsFCRLy/l3Vdzu0jbpW1uUsL505Fsn4RJRrCQQCgWBP5ui/J2+Awmeo/OyhOR1ui0zqmiG7Owopw6eXsgxFVqBJKmRdsfIYe2X2opdzXlvNnnunPKtgV2C6u3gnjwjKFnSWDnoKC3YXB50xFCvmVSJvdRvSsoF2GXh3USUGF63Erw4faq2nZGSg4ZVXsP+pJyMnmEO7bKVycXhCviAyioHWaqBmBVBktFcX9FhM58O6WiNwOR5Gmqaj3VT0/zaazP8kPO6PZ8jYWGT+IKT4YTB+5UdMKaOXfuiI8bMFxvPrYSbY6EaHLpXUDyaho3KtOLc/6dysl0mABIR7zFz4TCePgdpu//jd8NkN+G3sdgCF1n7qhphEfhh5/WZY6BMcuP4f+AFv0NvtWo6nqNPl7KufEM/8+AxeWfkKvj7HdnV1ldpm9vcvzDRFHgkef26BQNCDUVUVMZKBJhD0MAIBElDcs+asY1x3gbaoig3bnM0yvJw/O+vkPe/MM1H39NP2tqU4FM0HTdcwtnAsbp18K12uGBNxwXRxKthTMce+ZgMLgaAriE92T8L4gv/fGftgXUjHZc99h/eXVDpEnrR9JqFt/nxsPOMs/OyPR2Hm+pn41aRfdf3H4drvgQeGAz+8CMy4c2e/EsFOJm4E5NkLwjguouKVtNQf4R8G8gOfxDPr5rownr1tLqaeytp0mseRXyciDIckoer7bKRNjrhEHhXFgRxUR/l2564SMK5c65FcZiu6oqEJUU7kyfBotxTI7e8QduzrMqKG6YZ3OZko4WpL5NEUH83kkYxiMpkThw7JeRQYdCiO+tlozPzXEjSpxWydkO3uETjzkLaHSFyFX5Gstp9E/NubhTOBYE+CfFa3bt2KhoaG7t4VgcATIvAMGDCAij09BdU1Zjv4vk8dLp+AzylKkbbpO6sMp/jmm1B8043WbeKQ9sUD9Lf8oN4HId3PysD6jirA+sXbUNQna6c8r2Dno3g4eQSCziJEnh7E2Xfsh6dvmYNPnl2Oy/5+MO47dSxN4m9sjyEnjZ3VFl19NbY9+i96/YgXVuHZEyqxqXkT+mb37dqTBTOBcWcA3z0DHHYHc1vUrgJyegFpLKBX0HNIKG+JhaFxmTVumuwIG4uoqoLrDk6p3cRqxTctq6OXplbo03VEOeGQuGHqVmSiPOwWeXSMzOqP6m0/JDyf1bGBdNcyeDgv1xJ5Ytz20zxO+n9sq8BBHkFzPgmoy+JuZxKByR6kBGV7xkzzBQyRx9kqNKBE4JOiQFo+Bk0oRlHfLKg17DOmqw55S3iZd5CoqsNvCDz0dlzD2prUs5oCgaBnYAo8xcXFSE9PF6UCgh6FpmmoqKhAZWUl+pLcyl18fJ42qTde+W5zh+vFU9hVyeTtz8azkqldUq5FtsNtS5VIJg8bLwaVoGOCjG+2Ieh5mGPWeWsTszQFgo4QIk8PIiOXffnGIypUVcPkAfm0cuSV+ZtwybSB9D7J50PpnXdi6513IrB0DUoPCeK9de/h8nGXd/0JB88Avv03sGEusPwd4KuH2fI7Ghw/EILuhw/xo8TDUKktxXbASOkqVuQqeGOKjE2Fyf9+plWXd8FsXFrncvLoaOHsz9FgDr6afDuOaghDUyTUZrP74rKK7EB2l8u1mmQJf+m/nl7fN2siFGxM+fp9XO92nxpHa9D+6nrnQOe62YrdnU6T/dBZMI+xT2y5pDn3SfHJVvCy3u4SIDiXERmIiZOcrhFTE2ctn567HneeMKrb9kkgEHSuRMsUeAoKCrp7dwQCT4qKiqjQE4/H4TfyaHYV7t+yZKTKneNDdPmS/F01tNCkOGSNjZmCPq5rKenoJUJ89wiWbGEh3y9csl9374pgD0JIuD2Mk2+cRC+r1zejbz6zVN717jJHiFvemWegz+OP0ev/eCiChxY+hGiS3JOU5DPhCE8fA9RxnZ0aNuzYixDsBidPOzSj9oi4bgiSrGNpPwnfDZFRnZf4wy1JzKHSP9sug9LcZWDGw8gwKewacbSll6JibTOaizIRM7o3qLKGs3sd5rnPunnIenTXmpmRYeUh/3z4MSlfO90fXuRpr2PBywafZTltS37J7jxGy7UgQzIsTOaAxnT2mOKP4pes4GU97Oxcxmf0VK1L3k1D4E0srjmcPAKBYM/AzOAhDh6BoKdilmkRUXJX01ljbyonj5ewEo6ptAPlroCU1ZPgZbeTh4zRLMe1YI+gJEfECQg6jxh59zCK+mbSdobrF9VSx8ARI0vo8oc/ZSn4JpnTpiHvHNbOesgWHV9VftX1JysYAmSWsusr37eX/30cUL1sR16GYDdk8hAnz9icQZi3gVmHdU2CmuoTLTORhw8odIs8pkuFCEcRj2ml1m++oXYYzdhGbkYeRpVPxnijjIvHyl1RE+/L4QZjAT8TacZF+yXddT+3zwrJC+I8iH3iThFpW9zejupLgx7MhWQIYlbHL3OotuQ14LP7EKmux9YICyDXwnaLVMe6AF67b8c6Te2N1LVFHSJ1UneaQCDokQj3oqAnszuPz87mybkzeXhIWdZDn6xGS8QuDW+NqMjkHMo728ljtlB3lmtpwsmzhxEQE2aCLiCOlh6Gz6+gdFAOGqvZieY9J4+hl3/7eBX63/IuDvzTbOtHpuSWmwG/HyNqArhq1lWYWzG3a09GTpwves++fdhv7esP7w+s/WxnvCRBB/DBwQs3NaTsrmURJ5k8MtJ86QiZ9+lkxsb+wb67upaKKaWS0WlKZTMAZhtNwurv7BboBHOsRMq1wh4//npbOzKqIlgz8h56uzAeBPL6YWEomELkSXSZZXGvx2cMOg5tsx1GbnxGBpCVF8SNhb7KcM5sVEZHWNd/6P1zqKqMuCEyyBn5xuu0n1/76I+orZfQrDNBVW93tqfX+MA7oUt0mafmrKe5Ym68hB+erY1hbKpzC24CgUAgEHQPRVmdc1LEPZpJmNzwyg+474MVeHC2PXnbHIkjI7hrnDzDC4dB1pI5eXbJUwp2EcIVLegK4mjpgeQUpaGxlp1oFmQG8fj5+1j3ba5vx5R7Z9Prkt+P4ODBmN7A2l5fO/varj9ZwSDg9GeBQ28HDrweOPT/7Puqlu7waxF0zdZLTmy94McLVBRSo1AlGbLCt5kiGTT2zeNb2/Dlxi34YO33aF17LbQwO05IDLEJcYzxmNbdNlnGhiS17eEQE0oImbUtHb9Aj3It3lStGqJToDV5GK+PE6bIXjlaqLu+xfbP/4t1vT1QgFVpB1nijJzXx7jHfs/j7TLKK75kS8l72N6G7GOPtbcf3zu7GuzqDlhR0k4kBfvfMwvT/vzJLt0HgUAg6G4+/fRT6kbpSgezQw45BL/85S936X4JErl6+uBOOW4641QleXUmrZE4MoO7Jk9oRNHwpMHLolxrz6KzmVACAUEcLT0Qf8iH2k0taKlnJ/yHGyVbJpWNYTS2sRPnnOOOQ6/5m1AcCSKiRlDRUtH1Jxz5M+CgXzMbx0E3AtcuZMtjYhZ9d+AV0Ed+8B/5dI3l8uFnhairR41DkyTIMjco0L3LtWTo0CLlVuCOYpQukXBvN6aT593MjCR7S5pw2oOCol4s16nYI8Pdcihx3bWs18BtI+zzIy75kNte0SmRR9F1RyYPec3njjjXuv14qbOde9SXiSH7ss+QlFVEL9s1u4PcmndLEAqzzgXb1mdDa2uHksu6gBEiGzZhb0SzQpV2jP4F6bjsoIG2SfCcifSyvnU7csQEHfL122vx0OVsIkAg2Ns7g11zzTUYOHAggsEg+vTpg+OPPx6zZs2y1nnssceoYJKdnd1loSUVd955J8aPH9+pdadMmUK7Q+Xk5GBni0cTJ06kr33w4MF4+umnd+r299aT7Peundbhegnu6w5gIs+ucfLIigzZKNcK+Wwnkghe3vPwW5EDAkHHCJGnBzJoAjsRXf6V3SXojSun4KGzJ+K5iyfT25+vqqGXuaecTNIR8eCDURoQ+9KKl3Z8B/IHAGXjgeofd3xbgi7O+LDrj362Bn+auRwLN7MBZ7BpHUZJ6+z1tThUSYKisMBBipboavFCNvy5W1c7xRBG6h8Qei/n7+37s9Pp5eNjr8XN2+q9RQIPkSfOPU2/nAFo8eWjVGIdvkyeP+o567pPtkUkn8vJQ9xLmYFM63Z1KHFwVdKfdQCLpvX1fF21hePo5TocCK09DDk9DX2e+Ddd1vqdIXruZewskafdFSi5toa5vw65/9Me4Sj6qbH4k47b+woEP3XWr1+PSZMmYfbs2bjvvvuwePFizJw5E9OnT8dVV11lrdfW1oajjjoKt912W7eFW5Pg4NLS0p2aLbNu3Toce+yx9PUuXLiQun4uueQSfPDBBzvtOfZWynJDXc9R9IDXV1rCcWSGdk0mDzmuzAp14eTZ85h1w8HWdVGuJegK4mjpgZQOzMGAcYXYssI+aZ7QNw/Hji3DtCFFKMoKYuZSJgARx0HuWWcC0RjOrRyITU07yXXQe18WSrtlwc7ZnqBTgwFT72kOs0C+sNFq84B3j8C7wd9wIk+MljwpnPhBnDyax+/1a6rZY5zdKRsf+w+fSCzHM/Wbe6qdZVw8OjcQ9YfYYGdgeinObWp2rKfqRplTa3Xiaza2Me+seeib3ReS7MMQyT45nVo+FWOKmfDCdxCjz0muc/sQ80k4tM+hOLeRdb6KZ9kuHZP6xx6F1tqK4nLvmTLTndS8KYTY1lpIaWnInDqVLjO7mO1tmH+/HRVZiGGMn306cpQR9t5JJvzhI0dulSA1svFeC3FMsDdz5ZVX0pPbb775BqeccgqGDh2KUaNG4frrr8dXX9mNKoj4ccstt2D//fffac9NHDO/+93v8MMPP7ATbEmyXDTk+iOPPIITTjgBGRkZ+OMf/5hQrrVt2zacddZZ6NWrF+1sNmbMGLz44otd2odHH30UAwYMwAMPPIARI0bg6quvxqmnnoq//vWvO+117q105kTbnLxLVdplinoLNtbTTB55FwVIs+1KHpk8wsmzJzCoyJ7EFMHLgq6wXUfLQw89hP79+yMUCmG//fajP6LJID9s5o+c+Y88jufCCy9MWIfMrOzNFPbOxLYt3nknw0qy8OHSrdaPSNkddyDQvz/2WxLFxxs/RnvcGRy7XZRPYJePT9/xbQlS0hyxM2tqW5jrxXQ+tBkiT0KGj2o4ebgyJlrF5f5El42DpjsXyktfB2pX02Ms2aAjLckJoi7J2DLjVOu2P2gMGDzS+9JLjGVtdUB2L2CgfSzFJKdDJydSgRzJLg989PBHHbOa2rrPretK78nI5bpzZejAiIIRiBnrxz0cKGpVBaIbNkD2sedLl5lryFw1r2ElexnGduU01jJYzs6Gzr3He9PJc2edPJV33ImGV19Ner/q6uAxpCSrS+9lQ1sMNcbnQtAx5ucmHts5TizBzqGurg7nnHMOLQvKzc3FxRdfjJaW1JlmnSkl2p7t/tQh7wlx7RDHDhFS3JD3aVdyxhln4IYbbqCiEinDIv/IMr6U66STTqLuop///OcJjw+Hw9SF9O6772LJkiX4xS9+gfPOOy/lWNvNvHnzMGPGDMeyI488ki4X7Djn7NcX5SnaWZtZi3wHrYyAcyxh/iq+sWCL4zE7G+LWMbMY3eVawsmzZyFEOcEuFXlefvllOhNyxx13YMGCBRg3bhz94aiuTpytNyGDD/OHjvzbsGFDwjpE1OHX6eqsxU+N/PJMtDfHULEqcVB36UEDEVN1LDJKeQgkKLbkuw0o26bjkg8ugaqpO0fkIdyZA4SZS0LQdV78ZiO+XssyX7zgOw/99n/MXWOK9auN0hYes1xLg2SVXiXN5AlkYbS8DjNku/W3PPefwIOTUBxin8M+I+0gZVNXSfbFQDp61bcNsrflN2apXELIq2Puw6ON9xv7pRF7AXD+m9b97cZ+m/lAseIxVt4O2ntb6wVLH8VXfd9CJi84jDsD5XF74BQ0o3+MQUycC1WWjMfJWhzrTj6Ftpk/r/AynFXIAiu16XfRy34bmYVdMtwrchpr6x4aPhwa75YC8Nbf7fKtdx9ehE3LnWVmPzknTwctxRpefhmV/3d70vvJwNWXZGDSUfhyZztxCRKdPPHI3hkY3lMhQszSpUvx0Ucf4Z133sHnn39OT95T0ZlSou3Z7o7SHlWxZEvjbv9HnrczrF69mgrIw4cPR3eQRpygmZnw+Xy0DIv8I8tMzj77bFx00UU0K+j/2TsL6Ciut40/6xL3kKDB3d2tpU7lKzXaUnd3+1Oh7i0tdXcXWihFi7tbkBAk7sm6fOe9d2ZnZiVGaAPM75w9a7Ozs7uzu3Of+7zP27p1aAkxOXjuuecelulDy1CuEO0H3377bYPyiNLSlHmOdL2yshL2oA6SKg0nKcpY6z9juKzFVol88khOTnEN2iVzIfKSweHLyZtG+A918pBDVvy/UGn+BIuEKip10eAC0JdffhnXXnst+4MSLaE02/Dhhx8yy2ukHxj6k6sNCoara5mTiYyOfKbpp5fW4+ZZ4xT3dUzlDowbPl+HVQ/xmZrocWNRPHMm7v3Bi7uu24xFBxdhfJvxjd+AtG7AjSuAt4fy6zlLgS6nN359JzEP/riFnec8K3VskhOuvbROUFue/XMnzl3+Lex/J6HthBJFuRaVZolOHnY84QfOr6lGWoUG42yCK8ZoRVftQbxvfAlXm/qA5gG1wrGHb9dcxOpGQOONCnEBMLGFRN3eT+PRPDN2F97Fn0ejQ9dOwAb+kqARRR6tUhaqMpVim9h5K0yfTofwPHoNf7yu31Rgzn1Ym3MQ93b6ILDcJZq/EG+yon8r2b6n1eMQc+TwbWTzUjt+xyi7HT/ERsOiNeLChwZCv+5tfD2nD/xUoObjolDhhz8izSgJ0j5hlk3ndULrc8NmTeVPEcUPxvwuV4iT59DOMnjcXugNOtadjBx3l88Yhtrwenwoy7eFdU81dyfP0WbzsAPJCDZ0Eqvr0ajkmM1wnoiIM7NupxcWyTSl8h+yY8cO5ixZs2YNBgzg3TLfeOMNnH766XjxxReRkUHB+KGI3ZOonKep1ut0OtlJhAb9DWVvUTXOfIN3JPw3+f3WEeiRWXc48bF0W37xxRe4/vrrA9f//PNPjBxZdxCvHPGzioTX68XTTz/NRJ3Dhw/D5XKxz4xKt1SaBzqtttYOWmIZ/kfTBrImGqv388mgLukx2JnPS9vfWbKPnUTMet0xzOQJV64lHfOpNG/WPjIB8ZZj031N5cSlQSIP/dGsW7cODz74YOA2rVbLLKG1WUDJOtymTRv4fD6W9E9/XmRjlUMHMampqUhISMC4cePw1FNPISkpKez6muIgpbljjTUiuVU067LlqHHDHCV9uTPiLbh2ZDt8sHQ/S+SPMulh6d4d6dOnkw8Y7fL8+Hnvz0cn8ohCzy3rmOsDVC6jijzHhEq75EoREf94z89eiNJts+mvmV2PgU0KXha+fwxhHN7T5cTIUmGW7pQZwK4/Auts5c7FanN0wCLshw5aWou8xXmQk6fMWoBYk3QQQIKHLpWEEC6U6ETLUZCI49G54PWJByz+kPvLdVroyEAsvE5tdErgB8ktdIEgrH4/LqiqAc57V7aNOlTqaN0eycnzzaUgKXRSdQ2KrUaktI4Bsp3wCSKST2g1X7VyI9JGUQd6DSr2W2HbywdPSR0rYbUVwGXkAc0iiVdNQ+FDL4R8PuSyi0nU1XtAsfS7bGxdfBg3zBwjvWfHiZPH7QsVIVfmrUS5sxyT2tZdVhvOyXPxoFb4avVBuMmhIx1zRuR/v27Dp1fx0PljSU2Fk81sWqJlgebHqZ3b41LdT80FOj6iEiH54J6Om+j3e9WqVax0599a7zPPPMPyYo42I4IEl/8ym6I2OnbsyP5bdu7c2eTbQFk6FFMgd900lHAlZHIoKPq1117Dq6++yvJ4aHkS/OgYvL7QpGlBQYHiNrpOznq5q0ilcdDfeG0ij3hfh5RovDqlD4Y9yzseDu+QHBB5/q3OSXIhJ8og7Xuqk+f4ITm6HgdKKipBNGi0UVxczGYYwllAyRoajs6dOzOXzy+//ILPP/+cCT3ULvLQISlklWyon376KWtr+dxzz2Hx4sU47bTT2HOFgw5SqNWkeKK2mCcip1zNhbDdq0Pf20k90llI78fLcwK3xZ5+Gjt/4ksfFucuxPIjy49+I5I7AH2nAnvVlryNweYShAh95K9apSN0EC06HyYdUNbgzzPdK7VQh5TJ4xdmaTSt+gPJnfjCBjMTgwLrFMQIr/Cf7vProNF4uQuIcnFSLDBZBGeNTLiw6KVyJFa6ZJZmEwPaTZCI49V44PELz82cIMoDiffi46CV32aVSsbCNqXQywbdWh1mFEnlb2aPdOCba9BjrU34bZF1Hosv38POowb0YufF22NQsCEOVWt4Fk9C/xTm5vFq+WOsAwey89hTToEmhs8cd2glfU5eed5JPSaNi3KrQh/XzJE7eMod5Qqx59q/rsW9i++t53r8IcLWKd3S6yzXirdKwvaS3byb4LHm4/uX4aN7/32HwrFw8pQcOblzWZoTdHxEk1hyqJQnMTEx4rHTsVovTdJVVFQETgcPNrxZg8WoY46af/tEz1sf6PVTjADlR9bU1ITcfzRt0mNiYlg7cvEUSTChjlmRjmHrYtmyZTjnnHNw2WWXsUgEKtnavZv/V9WXoUOHKlrFE1TSR7erNJGTp5YJHo+P/7fpdRrFJMfdpwjHZ2EEnmPlqtFp6GiLr9soOy5imTyqxqOicsJyzKeU6Q/l8ssvZ7XFo0ePxo8//oiUlBS88847gWUuuugiNjtCMxaTJ09mdeVkP45kUW6Kg5TjgYT0KOZIKMgJdSq1SeJq/AtzdwXKfXSxsTC2aQOTy4+xm/x4Yc0LTWNbbjMMKN4FONVBQ0P5cws/0I6ppTUmubGCRSDx4MGmV6r36ZoyeL1iC3WpHbr4MWtG3AoMu41fIUFGNlAXn4HEIWKL7TTUeJMgHItg5EWdAgNEXXybwOP0sqOA3Z0ugqNKGuwHQvtEYSlwB1gAuJtcQqwbVuhPjVu0H7EnsShKeAJc9iNwvlS+Jb6us6trsH2CA6+co+XdtgQyPfyg2kPi1tCbArcbXVxk0Ql2d41YsyausjoHWq8LXp0J0e30MMhKRz02BztP+uEZ9Fv/ErvssLlhq+TiUn2+YlSudby5K+S5XiO/GYnpy6c3aj3k5BHLDw/ffQ+qFiyAUdjfa8vaER8jItrdjzXHe6623sjf2x3L8/7rTTnhoRL14KYRwadj4SY5Gqg0ntwc8tOJCAk8JLIMGjQIP/zwA7Kzs1l52+uvv64QOkgMoxbjlONDUBgyXafw5qOBmpNQG3NaF02Qyt3n9XEikSCzfPlyts1UHhbsyqmLG264Afv27cN9993H9sG33nqLlX/deeedjXg1KmGdPLW0SRczeeh/THRX0k1WY/hjQX1QyXuTBy/7NciMVrrOVCePisqJTYN+VZKTk6HT6cJaQOubp2MwGNC3b9/AH2o4aNaCnivSMifLQQrRsnMCdq8qQEWRPcS69+ftI5kK/+cW6WA+40VeWnLDnz7kH8nGgcrQkOsGEyN8thWS+0qlftz93SZ2Xlwd2WZNHbSsQTOUYstoCjoOxkOzgx47k0gC3bXEsTKVMQnuHSqtKqyU9hu9cDwScPLAAJc/KjCo1cmEJq1FctZQUZecw7vLpPvEx9A+0jo0l+a5Nc8FRJ5aBUehnIptn6g6ER3GAz2lbl584/hBUll7D1Z002KzWRLCJtTwLCKX1wWYpEASreAqKvn6V3gcWmh1ym3Rmb3MyeOjenXRgSTgEQQovccOrVDC9MNz6/DRfUsDs2F1IYo7B3ccPyHNwVk8C3MXsvOGdO+j/Zg+dnEms3L2bBy65dZAC9ranDzBwZU5JaEz8irhS32JzE7HtoOQClgHJRqE13ai4xk6PgpuTuHxeJiQcDRZhMdqvScC9L5Tc5CxY8eyz6lHjx6YOHEic7dQC3MRypWkY1LKmiRGjRrFrv/6669H9fzUtp1c6vT8NLHZkGYijzzyCIs2IDcSdVejz5ImQBsCtU+nvEwSi8gNRK3U33//fbZOlX/BySMIQDqtJtBG3SFMQv2bpVqE6BASu5mKqN21VFRObBqUyUP2U2rrSH+S4h8OlV/R9VtuuaVe66CZFZopoWDASFApV0lJCVq0aIGTnay+KdgwLxdrZ+/H+Cu7Ke7r2iIWA9sm4sW/dmHKwFbsh9zSsycSpk5F2Wef4cPXvLjAMhmfDHkD3bs0LBhQgVXIRpo1HHgscpcolcZ13iI3ltkQ3skTDuecR4HyXHhTE2ROHqFcS6cPiDzlDh/yym1IFVatE+qKgg8zxLG8XOTRGaMAQZfSuWswsG0x1uQkh2yLYhaIhJUgdpTsALStWNuuQPlWHSJPnSG7lgR2Ntxux2tQDmRNwvs2N2cuTs+SfmMSLrkYZV/yg2zK49EIipfGoIMxysGaf8UkVaGsMh0JnZSvw2XgYpHBXR2S2UOIjp5IUABuVSl3A238OxedB6cfV5k8IuLnt/LIynqvY6XQVU7R9tPnCxzQumsReYLzDmorefy32D9lCqIGDULq3Xc36vHO7GzkXHwJOiyYz5yXx4Lj0TV2vEKDdzrVBTlHqESIMg3pGIpYsGABO36S57s0lGO13hMFOoZ888032SkS1M6cTk0NTUZ+//33IbeHm+wgIUd+O5Wb/fyz1I0yHJGc7sHr3bBhQ723WaX+0F9Ybccq4v8XOXTMBj4ZV1uGj0lY5ljAy/+DurEKIo/akltF5cSlwUfN1D79vffewyeffMJmqW688UZW8yx226LSLHkw8xNPPIG//vqL2UZpVoVqjKmF+jXXXBMIZb733nuxcuVK5OTkMMGIapGp1lmdcQDSs+LQYUAqdq7Mx65V+di5Mo+1bZ55wwJs++cwzujZgrlE5EFuqXdJdtz7v3JBO/k67P3+k8ZvRKogLpF4IHdZqNTJNSPahbhzwnXecgRltYjL+mW5NeIxoHHPHL6M3xtarkXdGYQym//9vgtaWUkUlTiRKyfL7VaUpIjPpdNLzyUKQuLlXuf2DlwvL5ScHHJhCK5QpwVrkS5012IlVBHRhMyA1SU6dnW58UnmWfj0iJQ9YRRe2GPLH8OD/0i/Q+mPPSY9Ez1VDM/x8ru9gdItc5QDFQkdEJ2utNVbxoxjnbe0fl+gJXsw+fsrIm7uu7cvDmTxpLSKOW6dPKKDp9IllY/2/4wPLMPx9/YCXPL+KnY5OHhZLNdye2qzuyuvN4cuII5Nm1Hy3vuNfnzFL7/AV10N565dOBa4HB4c3sXzRjzHUf7TiU7Xrl2Zq4PcIqtXr2aZKzQxRqXqYgcs6qJELb/p/vqWEtVnvSoqKk0P5cyFO6YTEQUgnTCh8dz5PfHxtMjNA0S3z7FAQ5k8finDUWT36gIc3t34fCoVFZUTTOSZMmUKa8352GOPsZwdOuCgFp5iGHNubi7y8qTyobKyMnYAQgcj5N6hTlhUZ9ytGxcOqPxr8+bNLJOnU6dOuPrqq9mM1D///MNmQlSAvhNbs/OFn+/E/I93sLbNxD/fZDMHj1GnxSphxpzQWixoP5cLAT0O8D8a1yPPYuuEMdjRpSs7lXz4Efz1FWzIZTHlc375uyua+NWd2Ih/8ITN7cXBUhsTdsIdHFwtCEI0oxd2xke4qQq8fIhEk4D9lvqp8yeEP57vL4f9ydDKxJrOLjc27s9BHJXQyL76YrmRwskje3q6bO7cOWT5ECfP/30UuJhi4bPbXITy10PkkahttouhZ03TgYy+6BfVEn2drhAnD7GuYJ3iYck33yxsvwZ+mW3aL9Sv7bBPZI4ot1v5/Jqo2IC4owlyt4gU7FfmZn33zBp88b+VzMUjJzrh+PlNC3byhMPlC3UxkQhEWUwHSnnpHBE8W0i/WezxtQSTBpdr3fbVhrr3jebOMRaqbBXS5+FxNS70VeXYtd4mEWf8+PHsWGjEiBF4912pa6Db7cauXbtgs9kaVEpU13pVVFSaHsraqZ+Th//mTxnYGh1So/8TkYf+fzVhnDwqKionNo36VaGZokjlWcEW0ldeeYWdIkGdCebOnduYzThpSG0Ti24jMrB96ZEQW77G40efVvGY/tt21n1iQFuepUIBzAmXT0XZp5+hxqxBlMMP3SEpS6nw+efh3LMHGU/PqN9GtBnOz3NXNOErO/GRiznULvqp2dsxd1sB7pjQESlBLRG7Z8QGckrClWs5K/Uwx3vghDHgtJA7ebLbn4cFnzkx+eERuNL5PLL9LRUijxy5yCM5eaTbTEL5F7u9lvZRCidPalec1vNzOOx+fCeIInpqYc6cPJraRR7ZwcfqnFJsyC1D39YJkZ5UfBDrtCVHdPKwxTQ6nH17H1SV8FKp6DGjUTxzJiryWwAdKHjzb3a7s4KXivWy/obNtrPg8hhgIAFUCEL0G4zQCNuukYURyxFFjPICGxN3RIJFnq1LDmPgme2Y7uW0e2COksrUmhvhygpIvInkqKHl6b7hXw1Hr+ReGB3zROC+SE4eVy1OnnCCjt3tPSYHw2vz14bkFQTjb0D74rpokkD8Wkq1CNXJ07ygEpwvv/yy1qDe4P2iPqVEda1XRUWl6RH/03wRSp7E/y+xU6qc3i3jsOmQ0v0bnMvYlIj/2cFOHhUVlRMbVdY9TujQX2qTevVLIzHqIt7N6OeX1+P2CR3Y5QtmrUBehVRKk3LTTUi56y70mf9P4LbKWGlQWfHjj/CFaS8aFmpxfd77QE0RcHh9U7ykkwL5TA9dtgh113aXFz9vPKxYVrzP4fKFdfqUZfOOaoO1OwMiT6CFug842Go8u7xpbi4TeIivvWPDbhe1Tw9cFg9GqFxr6SvA9DgkHtkYuD8oo1hBcGeGrLQ8dEvZAvIKKcq1UIfIk9JFcfXDZTmRlxVbgIaZlTJmSOVD9NytuiYygZQtrueD+JINXvijebmWnPZnncbOHb5ovp/T51TlwoadRt46XqOBtZtyO0XE/JOig1LZJOF2Kl+zvcqN3G2lWPHTXnxw9z/HbLB/rJw81e7qQCvWYD7e9nHg8ubizYp9n46B5a+1McHLhKeW5YOpsLnr7fyZNncarph9Za3LeIS2y1qhQ1vjOLZOHp9Q6miy6lUnj4qKisoxQhR2Irl5gp08cr6/cdi/nslD5VpyJ8/2ZcpJYxUVlRMPVeQ5TsiQdUoxmnXoOYYP4osPVgObKvD+5QPY9XeX7Assp4uPR/J110KflISuO3fg9VdH4NqbfHjh9pZIvYcHh1b89lv9N6LHebyz0aavArkvKrUjH2TSoNUizNZUOtworZGcASkxpsB9Nrcn4OSRGWrg82jY2y5qJX22uHH6Ze+jZEeUYkGPW/psPvGeiraOL7Fw4DuK7fKBP9cpcS9CHMvrdv0C/M1njeNqSurl5AlxddD+UbQbPjcXG9lBhdBdSxR5pvXg+V3Kx0k/RQPaJKDSLrVpD11WECrpueX74WU/wjROyt4JnrXSGCSB0y9rZ9t6HC9/jO3IS0hLPG2AykOKNtQ+nRHGdu2gT4gLu0lesfwr6K1y1IQKW5XFdhamTjht9Sthaw6ZPES5sxwPLX0o7PJzt/6kuC4Xg9juLCvNcn/5GT+vpYV6uGPn9blSZ7faIEGp9xN/4bk59Wtfrfcacd2ql2tdRhTENRZeLnlUHCNtzyuIYFzkUZ08KioqKseCchs/fttbVB32fhJ/6BAlnMuHJjnaJln/tcYC/DhNmcmz8LP6/TeqqKgcv6giz3EU8tauN+9upBVmwc+8hYfhbpyXi1FZSbh0cGt8v/YQiquVwbEij4yYDr9GgzXWfFRfOBFRw4ayjkM+2YC3VsiVQQP11e8CTyQC9voNuE5m5CIP/emLJVpnv7kMX6ziA33i1Sl9Ah0YyOUTzrDgc2ux749U7Po+AzaNBp12coGgcFOcIkhZE+ZgwWlND1uupdN4pBmnOVJgt1weqc3JE1aAqc6Hz8UPfNhBhd8Hr0aDU344hd02ImMEO48N06mK6JQeoxDAInfi0ig7enUYD2O85NAJ7SQhvak+l7TPGyxcfIhK4IN3t98CCCKV3HhhbJUJoya8KOMVyo6CHVgLPt0RsuySr3cHLjuqaxGzmqGTZ31BZBefX5YlEq4lrF8m8thef6VWJ8/hcntYF85VH6+tx5YDNsHF8v06LtbVhcUdOStBpGbpMnaukQmSjcbvh9/T9AKfT9gPjRbVyaOioqJyrFi1n4efz9suxSDI8fp8YV08In/ePupfE3noWIgmXYZlhjqIOg3meaoqKionHqrIcxwx6boeuPxp6Ue6TY8k9D2ldcDRc0r3dFQ5PRjw1N9hy30yozORZuU/6LM2zYK5Zy84d+9GwTPP1H8jWsv+JLb+cFSv56Rz8vj8eH0B75JC7C+uUdhpxUExPYaWtbgd6FZ6QHq8RwN3DS85ejUhHkJTqECYcFIx79SVu46XGsnRBnJslOVaGnjhEYKGDRqeXRNMg0zEQkaOTRgIiyKPTXasQ2VUb457E9+c+U3YVdDBjlMWjBy6QaKTRwt4lSKJSWdSOFEW5C4IXDe25t8Vml7zy8KaRSFHE5XEOox5/YaAyCN3o2gr91KudVjE7lnB5VelR2ovh6RysOPJyeP2RRal8mz5CiFHXm7FLoURNSK1UH/yt+04Gkqq+ftaq1hYC/M/3q4IGCcKZgj5ZZF2gvogON+8lRXY2aMnyr77Dt7q8DPBR+XkYSKP6uRRUVFRORY4BMe0WGYfDB3HhcvjESHn9pw7RmJMZ96kwkSdUY8R5CaifMQbe98Ycl9GB6lKQEVF5cRCFXmOI8jBE5ModBYSGHxOFjv/6aX16JcqtWeetWRv2HW8Me4Ndv77vt+xpJeQAbNla/03YtofwN1C+9/Zd4cMslVqz+SJxJCsROgEYYRKteh0QbYyxNznlg4YClJ7Qysfw1EHLCefWQqHJmhgKjp5tBpf4COky+HQBfqzK2+/4AFeIqiEL+sRg/6Y6OOHU3awQwG3o1uNRssYXnIYDB3sOGsp41GUaxnMEUWew9WHcfvC2/H+Ft7yWms2I+m662DIzGTlWqZuXZF0w/UwXPUxcD8X0/QGLTwUbL2WdwqTm4HiesbycJlaAm8jdFiPiK0ZizzhnDwlDqmML5gZn3ixY4QkArsoGF5XBY2umjnN5AIQw+9ny4SjTbLSyn750DYN2vaSmnq6EyOwc2U+yguVziSRpnDyeCt46Gb+o49h94CBOCZOHlnZpoqKiopK03HxID5plBEfvnyXjvdqc/IQXdJjA8vUBOX3NSlCuVa47lqaOrZRRUXl+EUVeU6AMi6RVT/tw84nJyHBasDzc3aFdfN0TeqKr8/4ml1+/NC70N52Feuy5atv5xj6s4hJB8YIuRzfX9VEr+TEhHVeEP5DI4XAUrcgqpkW/+yv+WQtKzMx+JV/+nqLNCD+pyQhxMkj/zpnubWIFVqDE7pAiROn1MMFFpfPiq5tai9pEeWh614djS7DWgRuT2sbptxqn1KY4k4eP+xBIk9ENFoYdRocKLFh62Fl9wlpBSbe7W3iE0CWECw9bQ47M4qhzDJeW/+atHqDAX63m4k8hhYZSL3jDmi6nQ1Y+GyW1qDlTp5ds/nysu2O7hADjUaLdh6ly8SoqYGtkn9/wgUpG8yRZ+gqi8K7p5oDO0ukmn3R0VRs5/lF4UiuAjRlUit5EnCiO81AdKen2PVgkSfNURaxXKtNIg8Zv3NCJ6TGmHDRwNZS6WFtLi+BMiEvob50LaRua0oiOWHcR440PjBb2J9oHzwW+FQnj4qKisoxZ1C7xLBlySJ0vKerh4Dy945Cdj5nWz6OJZH+s4IdqyoqKicOqshzAnDjzDGBQFfKdZncN5Nd/30LD40Npntyd/wzhXfcurfyEzbgdWzhpT71pvcUfr7jV+DXW/nlFW8Bm79t/Av5+3HW2QlzH5YyUY5zqHzOatQrgvqCaSu4FkRr76Ey/tp9QV9PjUzVcbi12CvoLZZMM3dKyASJ82tMuLRacrVoglqNl3ja8cdqyzG88lbc/FRotykRbVp3dm4w6RAVx0WU4Rfwjm4heJQOCh687INcykgwRWiNfuc24J5sLN7Ny83OfGNp+OXodZKjrNUgIL0HML0CaMMH6UZtqMijeCiJPC4Xy+TRmkKX1et18Kb1AzL68huKpfwc2MtZQHQrj1RyR7QybUR1WWTnSGYn/nq7DmuBFh2Uwc2FByRRpDnh9Drx1CouzhAPDn6QnZfYIzt5gql2S04Y1m0tqFwrweuMGLxMZVzUZv32CR2x+uEJSIySPqtqR90zno4GtA+nVvb9DvO8KDm1ZdpUzf0LR0Od7dirCoB9i4GXuzco5F7MhlIzeVRUjh8WLVrEJhTKhQ5+9WHMmDG44447jul2qUTGIDg6Izm0mZNHNglbFzTZd6xgh4YRtJxm3OBTRUXlKFFFnhOkjKvfqW2Qt7cCs9/ajEfO6FZrIBwRb47HyMyRyEkD7EZg84LvUGQLzXKJSFwroD1v2Y31nwI1xcDcB4Efr2XdlRrFUqG7zYo3eSvvE4B9RdXokh4TaHFf25+7PmhGaEq2LE8m1g2fR/q6ev16FMfy5Y0DTwH+7wuFyENEyf68tUalpTiq2xB2nmrYKwkYETBZ+IyV3NmSmMGdFiHIg5BZJkoBL8sRHifPhQohriUQlYxzBZGyMfDysMgYMlrAW1YG24qV0BhNoY8nJ482KvB++PdzoamVcSMXHrUaxHqVZXH2fT54HIKTJ8wBH82g3fjWWIyd2oU5LIjMTvEsSN1lb57dtaqF4GyRXsm92Hmli4tS9wy4p851ODyStBeuXCvW54zo5CEXkFF2gJwULRN56mFrl7t96nTdRLg/2Alj6igJm+68PJR++ik7bxDCV9TvqsXJQ6LOS52AT8/mXd5kYll9nTy8XEt18qic3OTn5+PWW29FVlYWTCYTWrVqhbPOOgvz588PLPPuu+8ywSQ2NrbBQkttTJ8+HX369KnXssOGDUNeXh7i4sJ3b2wMtL5LLrkEnTp1glarVQWhJkY8Xosk8vjq6eTp04q7iFNjQ49HmgrxuC3cf6E2ghNJRUXl+EcVeU4Qeo/nToyczcXsQ6Uyh982HcGS3UW49tO1uOmLdVi5r0SRgfH6uNfRPrEjDicB69b8iqvmNqD0igbTU38Exj7Mr7/QXrpvpixjorow8ky0VzZYk3U+YhQeXfBqc6HM5q7zz1sM3It0QBA3qi0siW74TDygj+HXBzJ5/G4vcm+8PeTrLP87t8SmKN/6JC4E6jTCYDNMmMzjsb3wRFEJb4seVL8dMXtGCPj57Ai3Hq8sXMcWdgsHGTPHz6xTiLlyeDu0S+Yi0oGS2oOLG4qlb1/ptZjCiDx6LbwaM1C2H7CVwmvgB906jQs4tJqVa/lJ0BQ6k51S/gi0Pi881TaFk0KBnwcf0oGWVuigQa4eU5SBuUiaI2K7e2LeBfOYOEesK1gHs9OP03zc3aWpxert8EpuPFoquJtULDl5vOEf7xKcPPKWsz/fPJxdrrDzfSy/whGxk6DcyVOXqyeSBiTP5PFW18CZLTm4tFYrCp5+BofvurvWdSuex+sNBH6Te1KOc98+qWQ2WNSRfRZ1Ie5/5Lrz1ZZrpaJygpOTk4P+/ftjwYIFeOGFF7BlyxbMmTMHY8eOxc033xxYzmazYdKkSXjoIaEE/V/G7XbDaDQiPT1dUR58tDidTqSkpOCRRx5B7968E6vKMRB5IkxUkPijq8fn+e31oaXCTY64GWH+68K1eFdRUTkxUEWeEwRrrBH9TuW5FZUldlwymF++/MPVzNHzx5Z8XPTuSrz3zz5FNsoHp36AkhgNxm32I79of8OfeNS93NUTzM4/gOI9wIsdgTUfhC/reTKJl2fRKOv1oIOQ0hwc79BMDpVoiW3TI3HFMB4qqzggkI08Uya1BwXwKIQVjTuQyUPOFPYQ4fEakzbk/zzGYgAu/FTaNj8XbihmmCFzXYicF9sZ51bXAImSgCcGf5us+lrLtfo4XRhsd8BC5VNbvoWYGW0QQ5Pr4MbR7et0o9WXfqn9ApcNLaWwZ41eH97J4xV+Fp9vhygbb4E+IuZDfhtZtAt34Ya0C3D9+SuRiBxofR54hYwV0UlBJKRbQ2bPnDV8udgUK4xmHVyO5llSI++iRb8TcmHujp99KPm/qfy+WnQEh6x0j70HQSJPjNcZMXiZbg/OOsgUAi5J3Jm/owBDnpnPOgnaw5QlOWWhw9+uPVjbS43o9JGX4Ln2S7+bROFzz7Fzn7P+mUq7+vZD6UcfhS3X2nf6GSh6WXAvBpeqNiDcnu1/GkBvpP1Y9eGrnLzcdNNNTDRZvXo1zj//fOZo6d69O+666y6sXLkysBw5XB544AEMGcLdrU3Bxx9/jMcffxybNm1i20Anuo2gy2+//TbOPvtsREVFYcaMGSHlWiUlJbj44ouRmZkJq9WKnj174quvvmrQNrRt2xavvfYaLr/88iZ1CKkElWtF+J2tbyaP+D93LKUW8dBSvqXmaH4sRo5iFRWVExNV5DmB6DuxDbNe7t9UjJQYEz6eFtq1ZcVeZaZGojkRBWP5rPxHr3gbHihK/x53buUZJlEpwKXf89u/vhhYLgTe/nkvUMgHywGKhA5dxJwHgfJcfvn+HKDVYKBgS4OyKJojlQ43yOhAn0VtjOvCy5fEA4L+BTsxc6FQukYDaY2Xd3mSfTQpln1o43kDFbHtAp16xI5ZfqcvfElYrCRweP06aPV08CncEK4khMq0pv0JnCJls3QZmo5z7+6L9KwIB40ycSDN44Hd58JGkxFuofyn1tBlGWf1zmDnyXUIZOF4e8Lb+OL0LwLXXbISMjqQznyd75d+V6gLpPhgFbbvTcLCipswM/8H+Kt4KGKMrghI6si7a/lJkPNCY+Qijsbvhs9uA0r3B7psET3H8Pe7plx6frGEJi7FwkpqXMeBk4eEORagLdCmSNgR/X7oa/mKOmXCYfsUS0i5VowncrmWmMkjJ1YodcstteHqT9YGbp/28eqQxztkn0McCZy1EeEnz2lzK5w7cnw24fvSgNBKubATbt9z7d8fQeSpX4h0VamDOXkojJ850jy+xgdEq6gcx5SWljLXDjl2SEgJJj7+2LaNnjJlCu6++24mKlHZFJ3oNnkp17nnnsvcRVddFeqgdjgczIU0e/ZsbN26Fddddx2mTp3KBCuV5gE5YOhwwB3sQldk8tQt3YjuLXIwHztElUf6P6BOogNObwuTtX4TbyoqKscfxy7pS+Vfh5T51t0Ssfr3/eg2IgOjO6VgyoBW+H3zEZzWswWzlS7dU8IO/OW24Ltv+wrZ7/SEzg8sPbwUI1uObPiTX7cotASLsnpENn4JnPKkdL1gm3R51dvSZUsCMPh64OAqLjyYpLbwxxtiWUmrROUAkVh87xgUVDrRJkm6TzwguG7Lr2hNZW4CGlcVNBo/HIekkN70Ci4MlcV3QOIh4cAvyBosH97Fmg2ARpqxEQeDAQ4sC30B1KmqjdQSmz+FBhkdIwQnE2e9BvxGpWNAroEfPMyNsmKo19kgJ4/ZoGUHUPXJXwlmROYIRaYMtVKXo4vlApXPETrQ9gmzctvtE9n5gkoeKq6Bj5XNVPz8C+AV8mHSe8Hn0UDj96MG8cBXF8PbRpptpYE2UXJY2pYR/9cRq3/bB0uMAUbz8SHykDAnF+fcgt5j9AC6WkSecq8g3ALokGaFf6+yM1eU1xExeDk4k0c+cxosDK3cp8xIIsjdQ+KO+B2sjUg6iNMmvQd+IeMn89VXcViebdFIEaX0E9lvY3D5YCNEnooiOz5/dAWSW0UzoZ9y2ugHgDKi9mwoRHyqFSmtj9/fUpVmhsumDKX/t0juBAjiem3s2bOHHed06dIF/wUWiwXR0dHQ6/WsDCsYysqZNm1a4Pq+fUqnIDl47rlHyj2jXKG5c+fi22+/xaBBg47x1qvUF5qYC9fFlvD56+fkIXKePQPHErFzuvzviiacyLmsoqJy4qKKPCcYA89sh5xn1uKzh1fg6pdG4rkLerETQSUOP288wtpTtxUyTwi9Tg9D61Zw5x7E2vw1jRN5RHR63u2IyrAiUZYDLH4OiGkBGKOAEmW3Ihij+fkLHYCB1wCdTwPajsDxhpg3khbLS5xErhuVhTZJUewkRyzX8gqDWcJnMgNuR+BPWuT2X93Y3JNKtHSSkydI5BHzc4hosx6wtgE6nw7s+gMet5+VdARY/V6YV9CIAWz3cwMij1E4ovg8LhZzmMNHU2+Rh8SkpGgTCiob12I8WtyHaHdzlmF/xX60i+MzZbo43vrd76h/BzdNp1OAwp2A6EZJ7gzEZsDn1rLPgLDV+BU5KMGfGUEOqLNv57lAFMLsdnrZQWJzq4v3+CM7ecRqNrOLVRFGZLfv/cDlcmc54uUCMDl5XDbkRwpe9lK5ljbszKmzloydoioncwDZ3V4kWLnI8/qC7EDHwXBEcrvInTx+D79saCW54Rh1uA2L33sPxpYtET16dK3LsecQ961gV13Q+xYOezUXgooPVsMcZYBOL/yWeP34630uqN88a1yd61FRqRck8Lxb9z7d5Fy3GMioO8z4WDrYvvjiC1x//fWB63/++SdGjmzYMdOAAQNqvd/r9eLpp59mos7hw4fhcrlYxg6Vbqk0H0jEidhdy+uHvpn8rwe2IkjkITePiorKiYsq8pxgpLaJRUySGVUlDmbfFzNUiMFZSez83u834bsblA4Na99+qMg9iL8WfYgb+9wEs14pTDSYQdcBq98Fup8HOCuV5VqvCfk7WWOA054HZgozU48I7hUSfggq96BOW3Qi4eg4g2qyCRp0fnntYFzy3ip2vZuvAkcefhgtnnwSGpmgI876yFunZ33+KXDwM2i0UoYAYRM6VPkVSoLyD9uk12LGuT2YqyEwoxTP83/cLj8MJPyIdJwI7PhN+QIac6AsEwNuLSvHVAufxSwWnt+gq781mMKXqTSnsSy8cCHGfjuWXZ78y2RsunwTu6xP4SHU3rIGdFHJ6Afkb0XUqJGoWfIP/FojNDojfG4NEsp24UCbU1nLankOSl3OCSrXItwOT7OzTLtlOTDk4tHIEgM8OknkSVQ24WKQsylYcJz4/USs7vel4raxm+bh0ynXhDz+101H8OmKA4HwbTnUktYh65wVzMAZfyM1xoRTu6fDYtQjI84Mm7N2ISZciHhUvFHh5CmZNYu/Nr3ycwrXTU1O0Uu87DJqRN0itaeoqNFOHrlISI5O0UXmVTtsqRwrRw0JLv/F89aDjh07somCnTt3NvkmUJbO4MGDFa6bhhKuhEwOBUVTns6rr77K8nhoecoOIrFHpflAE3PicV4wXp8P2iYM0j4qxO5agspDIqjX5YXeWHsTDBUVleMbVeQ5AZl8V1/m5DmwtQQ9RmWGtOpek1PGMi/kM+Vpjz6Kil9+wcvvezHBMgAXDLkGt/W7DYW2QqRHhdqN62TSc1xQ6DcVWDETWPshsHchYJDNRJ3xMhAttNPuexmgNylFnn+DvM2AvQzIavpZSfHPnw4E5K6dzM/eQsWmNUi7/37oYrmrhNALgo/cyaNPTcWn875EktmELNm697Q/L0TkCXHyaDS4dDAXdQKkdGZnLq8JRtLxxLG8jYc3B62g4S9aFtDbW+gkJKe+mTxEeqy50U4eItmSjBhDDKrcVfDJRvK6pCToEhOROO3K+q+MttvvRdxZZ3ORR2OCRksdjDTQCjlENa4oRSZPcssYnHdPP8SmKNvXi1DwMlF0sBotO9dSAvcfO3m0QZYkUeTpbG6NcfOP0B6ruJ+6vnnDHDsGd9cigl059J257asN7DKFlgdj0GrgCBO0XFbjQkIUL6MrrHIyJ4/VqMNZvdvgncX7kFNcgy2HKwJZT0Fbprg2a+jteMj9Orx5kqBTNe9vdq4ROuEFHul0wl1QCENaKmrDtmYN6sJnqwkv8lCnwfQetT5WXn5LTh6xi5tYfqjYZtbPXun0U1FpEFQyVQ9HzX9FYmIiTj31VMycORO33XZbiKhCAceNzeWJiYlhp7qgjlnkyGkMy5YtwznnnIPLLruMXff5fNi9eze6deNdMVWaBzR5FknkqW8mz79BIHhZ2FT6X6DLqpNHReXERv2Gn4DEJlnQsksC1szeD4fQzUfk+tFcKjjnzWXsYN8hdKHRRUsHQRcv9uGDrR9g+FfD2Qz8K+teQYWzgU4aEiqG3QKY43hZVk0R8Nlk4MNT+P0j7gKS2gOmaODG5cCZr0qPlZXaHHPeGQl8enaDOtjUF6rJFg8E5LZd0b3jFzoy0Ww75baI2o5PNqjWb56FF5ISsDlMu2+2Dplzxh/UnyGsRtP/SuDm1XBro2GQz+KQ2yqERhygiNsT34Y9+jTqziVDr6m/yEOhy5S3klvSeDePkXKFgjdRo0Gn5csQM358yH1THomQd0AfjqMCGh/fFhJ5kJgFX3KfgMjzY+H/AuVaCS3496lFh3hExYX/7GKTufjzyysbsOpXZSZDc8nkub0fL72TI2byPN/zYfQ0hYZF6iKZR4JEnpLEdGzPq8S4lxahRsheOlIuCRzOMHk95OT5ak1ot6zgDlrkXrMYdCzXh7LILn1/FW4VxKNgqpyhdiSvxhMQSOSBycEd2dyHDmHP6NGoXrqs9pKRWlxxrd5/H+aePeGrEL6DniCR50j47Y70VY2KN0EnDC7koqPIvA+3462bFmLXqvy616uicpxCAg+JLJRh88MPPyA7Oxs7duzA66+/jqFDpbbV+fn52LhxI8vxISgMma5TePPRQN2t9u/fz9ZVXFzMyq3qCzmR5s2bh+XLl7NtpvKwgoKGd5qk56ZTdXU1ioqK2OXt27c3eD0qtYg8/tq6azWTIVZQC3WxAYSayaOicmKjfsNPUAafnQVbhQsf3P0Pfn1NGiRM6s5dOTS4avfgH+jy6By8MT+bzZ6nzlvA7huWx0WWajcf/Hy49UPc+PeNIc/hs9th37iRXbZt2IDc66+HP1ynAbPkVgnQ5xLpclp3+reRrouOHjnvjsExZfbdTb5KcYaHLLsKkUe0zjq4S2X5T3vw9ZOryT7BrlfJgiU1236o/xMGh8CEU3notpTObABL3bVqF3nQeCePUO4n9z1Qrou8FXddVDu5eDLqhYWNzlh4YvgTDVo+uWU02vfl5VwiHaMFF4bHAc3vt7CLtiNeeKuq4NXGsBbqIjSoTmsXiykPh3a2CyY+Tfqc1/6Rg/8SckzZXJ6Qcq0z2oUGQsYKGkThiy/Bt3VnvUUe+r0gMl58EYlXXwWdz4ud+VXYV1SDHXl8/yMHjki4rANqNytvuy524MqrUDq+9hZVw2LUsftrXN7Aaws367r00FLF9UlrffBpPQGBxFtToxB5jG3bhqzDuSv0fRBFXHa5ljILS58+iJ10KnzC70GIk8dRt8AuLxurKXdI5VphRJ7sNXyw+PdH6mBP5cQlKysL69evx9ixY1mnqx49emDixImYP38+a2EuMmvWLPTt2xfXXnstuz5q1Ch2/ddffz2q56e27ZMmTWLPn5KS0qAW6I888gj69evH3Ehjxoxh4c2TJ09u8DbQ66DTunXr8OWXX7LLp59+eoPXoxIeEnHkJdpy6L+m2WTyiMecwnEUlZYTarmWisqJjVqudYJCAa+UzeCoduPgjjJsmJeLvhNbo2/rBKx6aDwGPz0/sOxL83iXjIW7CvFr9+7Atm2YmDIG84qkwU+cSQpSzq9wwLB2JQpv5sJPhyWLcfCGG+GrqMCecePR4e95yhnvrucA570PUIelX27mt8XUUgJmFbpAjX2ETz0snMFns/O3AOk9cUzI/qvJVykOUrmTRxvyh1u1aBG0Zgs2L+C2cXsFHwiWmrgoVhGXjAotDX79KImlx9QudFC5VosOccjbU1FntRUTeeQHII7KpinXEoUm4bFrzaZGlWoR8tbzxdWuOlvRh2NUy1ENfkzwgc/4J24F/uDijpZa0AE49G0u4pxPw2+zQyd0DiNK82wwGHkL6/pAXbbsVU3vImso9HswvEMSvrhmiKJcS/6ZPfyVF3MGaJAhTHB78vLCrmvqAh8+mqCF26CB/cj/ITrtW8z41IuyLnyQEz16FGsXrpcFCosds6iMNECY3V3+Pfr+hqG4YNaKgEhFjh0REo86pcWwc6JMCFGutLsDZV0iCaYEFMpKzq6a58Pq/n74RSeP2C6ddmuLBWkPP4yDwoBQxLFN1i1Q3HxRtAnC1KkTnLv5b277OX8yF6XGZJaWDw5erofIIy/Lcjm8gXKtcCKPisrJQosWLfDmm2+yUySonTmdmhqTyYTvv/8+5PZwExYk5Mhvp3Kzn3/+udb1L1okdDT9jwKoVejYDnU4eZqbyANFVptarqWicmKjfsNPYK5+cSSueYUPcrcsOhT4w5d3e8pKkcq0qigAdhoPQn3oYF/MO3IJ5hdPw+ntTofD48DBUhucHi+GPDM/IPAQRa+8ygQewpOfj/LvvgvtuNXr/3juzm0bgQs/rb01OjlZKGh59L28u5aIvQFBuQ3FU38rdQibvwOWvFhLuRYC5ROERshCKnjyKeQ9/LD0AGGg5hHcLolmHSqFAV95VN1ZHD6tgZUGFcdoQu4LN/PPysau/puX08mdPPXsgBVhgxRXa2Tuovp21hK5dVxHXDq4Nbu8Yl8J/i3kXcdaGTdCa7Hw3Cb6LM3SoJkyrHxOJ0wuab8szKmE1sOFhfpwwf21d1n5NxB/F1bvl8oT3EIJmlzk6Z3jx42zpdfvLRdet0H5uU7Y6MeYLdRpzIonx1+GaDuQlQ9UC4MSrdUKjdEInUzkoU4k7HllYoUYEimHcnZEyKkjQk4gR5CgQR3lxDIwkfIwLdXDlhDq/AGBxCcTefSJiWTNC1m88o8/Q24LOHNkpD34APTJgohN70UcF8+1FjNz/rAOW+TkkWeX1eO3SV6WS9/tQHctNXhZRUVF5ZhAkw61ZfKIHVP/a8SyrG1LDsNp98DjUkUeFZWTAfUbfoJDbZrPurU367b11o0LUVnMSwH+unMU7j21M368cRhO75mO9y/ng807DnIXSdErr6Dsk09R8t57iP52D9YWrMUpX12KsS/9BUNQS9+Kn35SXM9//InIM0iJ7YBu59T/BVgTgcwBUretY4W9FFj1buMe++M1wIInIwcva7VK2641qtaSC594YODzwtOGZwfkJ0Q4WDCaFCIPlWBV2/nnYzBFtuKytt0kPLUaCCS2B8SSo2sWAKc9h6OGSvBoG2QDdafM8VIfzAYd7j6FB0XP2RreNVIfRmTW3dlIjt7A37c+1p9xduLjXCxrzbvR6WUijxi8qw1qz6Q/vByoFjrF1QHl8sSl8myef77ZHSil+TcRs28owyY4kydYmLOG+Qi7btnMM4uCwpe1ehsy4mOgD8oe1eh00BgMCpFn5b4SJtTI3Tjhjp0pp0mE8nZEWNhyUCBzu6QomIOCksvChDm7hNK02PE2DFnFZ/S9GnfAHeOTlWtF3LAwhHPyaKOi4HPxNzHzlZehT+CB2yR6ESXvfyCIPLKw7j3zgC2hjgA5s2dulp7XT44z/t6IB/MqKioqKk0L/e1F7q7VfIKXRTFnxU97sXnBQXiEsmi1XEtF5cRGFXlOAlp1SwxcXvQFz46gUoabx3ZAvNWIty7tj7FdeHeYVklR0KVIM83EBX9vR/9sH/TRe1CVfh9OqfiY3V797Osw9+4VWM4gayXqaURIYEQuFZxBtqMLQqyTNe+zsz+35GF/cdDArhGQkELQbI5c5KHWmnL0ghgjDirTawTXiscLbzTPhzmQFv5gQePg26mNiYG+XQf4tBosMfNBqzXOGHnbvD4u8rAHy34GWvYHup4NJHUAupyJRnHDUuBsbo83yMQ+0R3SEBKjjBjULvGoWpF2S+qGFlEt6r28KLpos0YAk57lN468G+h8OjRCuZY8eDcYncYFOOvv5hHbp29eeAh/fbDtX7fYi2WF8qcNdvKI26QP0gzE73xwIHF8jR/aylZMiDGFNtVibh69yxEQyN5atBenvfaPwsmTIhN0RJJjpH3aatLjrom8pbLN5Q2EyMtfV6zQpl4kuGPXVzu/whMruECb2ToJWg9vY+7zOANZC3InD38z+DZHjxuH2qiazzPOkm+6KXAbK8uyc/HHTKWx4u1mc8AdxkQefVBHth+urvW5FJvnl5w84sE8QaW7KioqKirH3snTnMq15GJORaFdDV5WUTlJUL/hJwHkRLhhJg8upnyeI9mhZU/0ZzSyYzLyKuzouGgROq5Yjs6bNmLv5MvZ/fd/78PNv3nx7TMe3LJkJ4pigY3JLeDJkzq0dJj/N9r/NbfeLYMb5OahIF9y2zQlQY4kapNNToIbv1iPR3/eCpTuA6bH8XMZD/64GW0fmM1FnI1f1Tl4Jg1F/mfvrwoSAEQHz+afcL/+K0QJjiWa6fdEEEaMTv4ZagTHhbFNG/hMVvi0QIHej8SeiWHbJ4fN5HEFCVokLN26DoitvzCigHKTqOSu71Tom0CvaBlvYTlQjYXKcbx+b73Fk+hEsyR4DRHKEulD7Pl/gUye2tjjGMlLCz86Azi4pkGhuYRLcGL9W4gHqWJ5odzJEyjXitAKOPP118IGC5+/3I8HvvWz4OOL2p4b8jh9agq0fj/igjpbiZk8z5zXE59fM7hWJ0+0UY/bxnfEK1N6s+sVQaVY9F2+UxCBRJZmK8v+nls+Ay+9x1+bSW+GTVi9zVYa6JQmijwPXsEPlMVw+XABzHJKZs1i55b+/QK3aQx6pE//HxKnTYOhVavA7TETJrBzc4/uPJOHnDwJta9fjsnKP6duIzJwytXdAwfvciePms+joqKi0nTQIVStLdSbi8gjE3NI4PGq5VoqKicF6jf8JEGn06LbyAx2+aeX1oddhv6Qlu8twcqcclZGoDWZ8Gm7MZgxcCq7f/RW6c9sQ3sNVhUuRubMNxTrMLZuDevgwSElXBW/z4aniM+SNwpLYtM7efKlEgeGVgfX4pex2XQNth+pAH6/k99+WPl+fbWat2surnEC/7wUcfViIB8JPPJ8HI1HORgVs0d8qz/EjfrfoPd54TztHESle+CJJCIJWTdiC3VyUnjdXviFbzT9edcl8mjEA5CqY1QidM6b8NQWsF1PrCadoutSQ6GOXl6fF2O/HYu3Nr5V70weeY4SI71nSAMzIu788zBg3XNo6ZftJ1V5wIGlwN91B3oGi09VpUeRD9UIxINU6kIlus9EkYc6ogV3ipKjFcqMwtGnKIc5ef6v1dmhj4vmHfwsQXkzB8u4oDK+Syo6pPJl5FiNkjMnSnDAiSVZ5UK4cr/W8QHBiJZvL8sdc3iU+1GUg+J3+Ods1BngEla/pWA9+47QZyOWa+VysyOs/frB1LEjEi6RdQgMQ9wF5/PX2JuLUOL31NKzJ9Luv0/5m6DRIOaUU+AtLgmUa/muXwV7cf1yrChkv8/E1hh7WRektokNlByKXVSIQzuPsRNSRUVF5SRz8oTrAik6to/GgdyUyBtBOGpc2LuBl5Or5VoqKic2qshzEjH0nPYR3QPEE+f0YOcXv7eSOVV+2nCIhbGuSesSWObvVv3Z+Zz+6VhVNQuD11+KM895CjMf+hjXfboW83cUwNKrF1y5B6Xn8npx5J57sOfUSahZuTLigLFON0/xLuDLKcDCZxr0UBqo5e0JE9ostPkOkL8Z1iVPIlZjw1DfemCf0L3CzAeNwRwqs4e4YCpsbnR8+A+WLyIv15KTbA76Y3Xzga7Xz0eYJPJoDXogex48QccIvr7d4NaRMCR0SxBUB0OvfqgsdgTyfIwmHdxBGSWK94SsxKKIQYLEMcIpdGkiYo0876mhUFbM0Yg8Wo0WNo8NJY4SvL1Jap0bibS2seg5OhO9xklOC0ZyR+C050OWp/05tioXujzuEmlp3Ci9p0FZNeEIFuOqy45h9lQY5DORS7KLAiIP5fGIQkRwiLCxA/8toWyd2jAs/CvUuSYThwyy9vPEwz9tZeemoCydYK4c1hZ6IXeGspvkTp7z+rXkr0sQz2LMBkW4vBzSd6grHdsmrRY+4SvhF/bboppiPL7gIXg1YN+7y/64DIXaGmT99iuMLTNZO3gStUXRSo4+KZll8Oiio2Hq0qXO94tyefweTyB4ufCFF5Hzdwp8wT8CYaCAZfmsrOjkmfeh1Cb97493hDxO7b6joqKi0jjIDS13wMqhjqAJ1siTIP8mgdJ8mrPcVY5t/xxhl1Unj4rKiY36DT+JoNne3uP5wHXfxlBXTatEKyZ1l5wXd327iZ3fNKknaxusv/5mnPHlLHTZvg1FSbK8jKjD+H17Mf7aXoBrvpwLf2I8yypxCG2CvZWVgVbEuVdOQ84ll6Lyzz+l7jwynPv3w1stlXAcuf8B7B45EohvDeyeC+yeAywWclLqyfalR/Dji+tReCCoTbhYCiXvZCMwEzIhSRb4LAo3BHUbU3Sl8vuxM7+S5Yr8svEIcul+wclDzLtzFNY/OhEIErlEwcYHPljV+0nkMfDyMZlAdNH9OpQ/fwdePE8LtzAzQyJP+7lzsMowll13C66g2HgTbJWhIbNE9toC5O2tgEb84/c3XkCpC+rKJnJtT2Xb6fpiMeqZeEZtshtbrmX38MDx+mA06zHq4s4wR4UZkEeloNWoErS+4xRp+TZt2LnJzLevl/UP4I97+J2CE6b25+PLXPjQQHa+f1NxvbaTypEOlNQ0qcgTbdIHMnnknbUOXHqZ4jHmTp3rJWL5ZzwGbxnvTCZHDBo2BpdMCgRn6QTTp5UkvMaY+bIP/MideaM7peCaEe1w3cj2ivuJ3zYdweLd0m+flr10/j1oEZ2OBHOC7Hbgx2V/wOICHLS5Gg02FW3CpmL+u0jEnXkGK7UKJ1yTYCNmFWU8z8PMzT24kB4OCqRm3bU8dpRusqPsiy/q/fUkQVfeFU4vm7mV72fyjB5C7b6loqKi0jjI/R7JyVNc7URabGiu3H8t8sjRyf4zVFRUTjzUb/hJxqCz2rHzgzvLsHXJYcy8YQE7iVb+WVP7Y90jE9C7ZVwgiHXq0DZInHoZOt55C7JSolnr7aEZUl6Gtc170BoLEdP1AUR3eAFPbP+a3b7/bN5FK3iQ59iyBYfvvAuH7hDKoWTsO+107B44KHCdgki9RcVAt8kN7q61fG8xXpm3G78vOsCuBzVBkloTp0vh0WGhmfUgJ0AMbJgweyTgkmWK+LzYXcBdC6TNPP7bdkWJSce0GBYkTPklGqskLPmFcpE9jhHw+I3MycNm/LV6yIdkFKq8rmgDNnTQwmngj8ltfQr0LVshby8XmxzCAUdsrAkep1R+I+ev97exc7EDT4A43q68KemeLIXLykWDhpASY0JJjQuDn57fqMcHP+/C3IVoNJYERGc4YezGHW0Mrw9RI0dCK3MtBdCS7coPOIIERhkdB6YFLNUU+kwd8Db8lcvCsWvj+bm7MPqFRYqOVI3BIwsCF3OayMkjf99c+5S5VDpqJc6EjLoVCPeRUKeYxmQK6+QJ3B/B5i6GlptlM5D0vRK/mwlWAzLjLXjkzG6IEwKtYwUnj7jKKz5cLb0Or+SG02n1iLNwkcfs4ev0/tQKFqcfdtmxukYQhQLXDYYIIo870F7e3KkTuu7cAX1SUtjXxTdAx7OP3HYUL5V+M31kI6qF/P0VcNZIbXEJ6rIXjMvhRXVQKaDafUtFRUXlKJw8tWXyBB9j/UcESvPDxDioqKicuKjf8JMMcin0HNsSOZuLsfjLXYHbF34hXU6KNmF051SpU44l1NHw4oQHUbP/Fjjyed5GVPuXA/ftzuBWUMLndIZ17BC2lSvDb6SfZ2HUrJIGY35h8BWAApFXv1fra31+zi68Nj8be4u4EOMNHgwXZ/PzCXXkpshcIGKmxzLTrYhyK0Nc4XXhyO/P4An9RyyQT0Q+IGWvxe2GPl5eAsYXznaMxMqqS5nI46aBp1aHA0HlHe9t4a9ZI/vq0uBNxCkoWVGCE0IMjw1HiFX3jqCMoiZg5viZuKk37y5E4ceN4bQekrss0gFVbUQZlC3rb1t4GxpNu1HAtQuh7XuuwrGhi4lBfA0XEy3aCml5cvKsfAt4tpUkKgbRc3RLnH9ffyRmRCG9XRwO7SzD8h/34O2bhXLBCGw+xL9Xn6/kz9tY5M3e5Jk8we3T5aTeeQfSHnkExnZ1hwMXz5wZ0clDIs/T5/as97aKZXvyEiyrLFdgYrc0KVBcYNV+LmC3Tgx17Ol8QHV0S0kEEku3xHAr+v66ALvMdR/sCmOvxefjpVYy3AcOwFtcP1dWwMnj8yHvtxx4bdK6/HWIPHvWFIaU+UUSyeZ9tF25jbWUdKqoqKioNM7J05y6a0Vy8qioqJzYqCLPSUiXIemoKXfWOuCfOoSXoBDBgybCpDPh+iGj4S4bBr9XmW2Tn6jB2tSO7PL+JasCTp6o4cPRYcniiNslz4fwVVfDtoPncxBuQ1boA8SSmAgEd2QSOwoEOLyWn6d1BzL6Rl5RVQHbNvuWLYE2zbGaMOU/bhvuN3yNy/XzFLP98gEXlWM4s7Phs9tDyrWIQ66esMV1RGJcFBN5nkzmjolgNIL7h70umZDj8vuZqCQGr9bWUUcexidsKJoaElg6JHRQhPk2FOqodMNoXnpTHtRBqb7b0GSQMyezH8taEYm/4HzWwj6xeh+mpVyJdONu5fL7l/DL1HErwixbelYcu2yso0xJjngAOV1wjEXKXiJnUH2dPOIBa3C5VjD0+hMvuzSimFAX8nKtbhmx+OHGYfV6nN3lQ7TLFigrIwyy2cgHTusa1jYfXLZFr6/Xx71w5u4Z2NGFB8vTaxFnPHU+aVlLkMhjo+5X8tei4ft1wM1DOV2z70bFL7+iQdDrcNpRvkHp+qrLyeMWfpMMsveEMEWFfn6FOcp1y4OZVVRU/hsWLVrEfn/KI0yIhWPMmDG44447jul2qdQO5S1GdPJ4fc2mu5Yq8qionJyoIs9JCHVfiU/js9oTr+6G0Zd0RumRGnzy4DJUltgDJTI7npiEhffw1uvhoNIIIsN9ReC2UxOeYudPjzqVnbtuvZ6JGkSrd2bBkJqqLHOQDTDlJQ+511yDaodUCuWtbHj2iClIuKoSuu8Q7/+zDyVeKy9RMscC1ywIuw7SJfJffAOVP/+InP+7EPalyyI/YaEy2DQjLijYmbbhr7/4BY8LCZ2qoY2NCnTKIko87bCvy5WIirawcq3htvADdLmTRy7kUB4QlYfphHINryey80UMZz3WaIVtFbuINYbxXfl+U0odzRpItCE0FPdooZJF64AByHz1FdZRThcbA69HD6uuAuh0mrTgrj+AciGEvHQf+9wZv9wCrP0oZL2G4FDuWtDVI9T54I5SfPbIChzJjjx4kAdH1tfJo3i8z4+i6FrKkMIgd/IYdBqF821cF+k3Ipi4nF347o/HYHrw9rD3UzlkML2F/J6JXSVHWKWzEjqfASZvjLRN7O3kG1JtyAnczjN5NAqBSPFatn7Lzv2V3FHjW/sFdt43Gw1Fo9XBX3Eo5Pa6nDxUlhnuQH78Fd0Cl8UstqSW/Ltw/v283HDninw1l0flhCU/Px+33norsrKyYDKZ0KpVK5x11lmYP18q/X333XeZYBIbG9tgoaU2pk+fjj59+tRr2WHDhiEvLw9xcVzsbwp+/PFHTJw4ESkpKey1DR06FHPnzm2y9asABVUO/LjhMGtU0qydPM1kO1RUVP5dVJHnJOXSx4fg+jdGo9PAdCS34gf+1WVOfPbwCsz/hDsDLEYd2iVHdkGIWRhH8loj0ZyIewbcgwcnjmC3uS3V2BOXyS4XvfoaOxdDSPUZLQKijrdEKnnyybrwODZthuNVqROSp7QUmF4B3LaBXfe6NCjeHg3/73crN2rl28CBFeyiKcip8ulSKVfkqdk78PeG3YBZOKiKMGCuOmxGWXYUjjz4CH9dh6SuYSF4paBjp8eLTukxOLU7z1sJvEZBtNHotUjvV4lEoa19MI7tO5jIEyuvpZFh0EiD2a2LDiuel7pRiS6d2pw8AfdWuL7gTYhYpkUByI1FHLxTx4qGEmUM3Yd9IQFNDafN558hdtIkdlkbFQ2fUxBLolOUCxbyDCR8NAn45lLu9NjwGfD7HUD+lrAhzPUhWmghXhvVgmOvtvbZcru52JEqOJMnXGctkeV7SzBt3H1oCPLuWtSG1inbT5+aHD6c2L5xIwYs/I5d9q9dHdIZqrPwexTM9zcMxcoHx+PyoZI7sdpdHZKt4yktC7jZRpMDS6BlkZ8HL8tFHlnGksbBS7KK3/uQ31/qqFOYCQt1FAszK1zXuqgEl0hto3z9ctGndbdEpl+Rs4sCmpMy+W/++rkHsPp3Zd6SisqJQE5ODvr3748FCxbghRdewJYtWzBnzhyMHTsWN998c2A5m82GSZMm4aGHHvpPttPtdsNoNCI9Pb3RzshwLFmyhIk8f/zxB9atW8deNwlcGzbwYyiVo+dAidLVGZLJ00zElZD8RRUVlZMC9Zt/EiOW9CS2UA6CaXa3Pm2cx3ZOxeNnd8fHV47A4imLcUX3K5jYY9FbcEEXN144UxpURZ/GB8NE26++Quq9vNRq7xln4sgDD7Iw4uzhXCCSUyMEnuY/+yyce/fCH88zQIq3xqBocywccz6RFiaXxJwH+GA6TBvmiiouEIiDwza+g0CCtI3hkI31GJqZrzBPSlj+/p/CZbFoVxFKZKIEZRM5hY5jGqF9j79IOcgXYeVcGh0LXtb6/egQ30HaJp8Wflnb7Q3zcqXXaHOzcq36iDyBcq1LvwP6SW6sYyXy6ILfzAaWbIUrwWuskyfYjXG0aMwm+N1COVosz3gJS/ZfgFMW1p2rzKWKTbLU+zkpYJhIjYncwUMsx1kzW3Km1NZdS16uFc7J0/aH79H+998Vt+l1GniDPtv0J5+on5PH62HlYt0zYgP3RWo7m3PRxWi3XyrhrPjp58Dl1Q+PxzfXDwn7OCrnSo8zIyHKiMuGtEantGj8sXU/NLLcHcI+f25A7O373WYYXVzIySzVI7lCeo/cVfk8Y2nP3/y1gO9LpZ9zR4/XLR3Yt/nsU36Buoi5a993NZWH4bPJ9o16lmuZrHom3HQaJDmVCJ1M5KFOekaTDvZqN/veG2Q5RiTuq6icaNx0001MNFm9ejXOP/98dOrUCd27d8ddd92FlbI8QCp5euCBBzBkSPjfj8bw8ccf4/HHH8emTZt4GahGw24j6PLbb7+Ns88+G1FRUZgxY0ZIuVZJSQkuvvhiZGZmwmq1omfPnvjqq68atA2vvvoq7rvvPgwcOBAdO3bE008/zc5/++23JnudKpFhTp5mIq6oTh4VlZOT5vELpPKfQjPBQyZnISkzCh0H8FKJX1/bWK+Q2yuGtcWAtlJuDB2oDIgZjFbzhmFsuSTanNlrHraVcEeDIS0NsWedxS77KitR8fPPOHDltMCyvwyW/pA8wljEcyAX+844E2Wff445pz6C7VY+a126OwqoEcJNn5IcFLTtWw7zAFxxbaIw4i7Pw+nalYiFDYjhriI5450vSK9H7KUsoPN5YYE0KPJ1Px+46Et+RebKmLV4Lztfe0DqknNg6lSUfvJJYNBFksAaWbaLnJQ7qBzFz1qoD3e48dpY7oYizjt4KyKxLqcMe4tqAqVYtYo8opOnwwTg7NdxrNAKTiGzPrR8rb7EmvXMzbPxYMOt9CQ8itzWl4cuu71NK/JoTSb4xLKXzH61L+yQvQaDUtRJaCGFA0cn1N5+VXQ1dUyLXI7mlAX4RtwcWVttX12ZPNT9KQjRkv7wsGsDt1lqaRXO0OtZVyty8tDBMAUpi7OewUHlkch76CG48/PZ5dQYM+IjiENyoox67C6oxgt/7VTkWrHn1blpZw1c75jNXUM+rQ7vnMZ/iDKjM/FW9jdYYzYBh3iml6ZUCq0n/F5p+w0ZglPv03OAGUpXXzCanEXwOLSRnTw+L1AttX8XcTm9iE0OFQe1Micj/S5T3pOj2q24ndi9ugAuoWugisqJQGlpKXPtkGOHhJRg4hWND5qeKVOm4O6772aiEpVh0Yluk5dynXvuucxddNVVV4U83uFwMBfS7NmzsXXrVlx33XWYOnUqE6wai8/nQ1VVFRKFzogqxw6aSGxOTh463lRRUTn5aHz9hMoJRf9JbdmJyF67AGX5NhbSKQbCNoSWGh6SnFrTBjszAauLt/++6PeLsPrS1ThSfQSV3nLIh/z29esDl38frMXqzsCMT70wualbF9BJaNi18Le3MP3MGpydoMFl8MMY4wVeaA9MVDoHxFbnhF7QaSqqXViyuwjD/rkabxmX44AvFT69OUTp3OvPRC/HezhTtxKn9u6K1CVS5zDC4pdm5B1nz4K1SNmVyhc0eBRxZu8JXKZyrdnRUfjNFYe+YSppDC1aAAU18Go00MWksaBromfeaCQfCRNCLVApiFJiqYavtkye4ODlY8T41uNxR787MLn95Eavgwap5PYoqmq46yDBnID5/zcfyZZkLDzI26e7fA0v+6p1+4wmZvDyn/IsNC3qyGHYKavfDyqVi0+11rvz0Yq9vNRx2Z4SFFY5mNARDLXWrit4cX+xZDnfkVeJ8V3TeLlWmPK64A5ShEsQEtendJJelkm5LTEt7fi4jRUdO1eAopHZ7Lbfh9s2/YAumU+yZUZ0TGbut4aULOQ/8SRavRXavSsSlFfFN9CnKNdKKN3BqqXk5VJawYHm0+rx431r2fJ9PuOf7VNJifiFRBcWbq3cXr9TytEyaOkzygQOLK1749w18HtCxRpfi4GAeQuwcAbwz0vAY2WK8lK3wxO2zC94FplEHnLtyB0+IrnbStGhf+QsJBUVOdRhbn/F/n/9edvFtWNO4brYs2cPG2h36dIF/wUWiwXR0dHQ6/WsDCuYSy65BNOmSRNb+/YpSybJwXPPPVJjCcoVojydb7/9FoMGDWrUNr344ouorq7GhRde2KjHq9Qf8W9EzeRRUVH5L1FFHpUQOg5MQ/aaAuxYdqRRIk+0R5olmzvi/7AjjcKKeSjpP4f+wd2LeY7OZ0u+QuwNT8BJ+TMyqs2ARnhatw5M6BEp81AJhQ5WIf/E5xH+vOY9Ji3Uehi8Qi7PM2d3R+mn/ADK7/Hj8g9XY08Gnw1voy1Eod2PwNCmx/nYuzcbcACViMI3/gkY6ZTybkSm7FgA9AOec1+EG2iAF+R40Gr8SEAlyiCVoASj0WtQodXCLeQUhdxPrdMXPAlPWgqsGf0CLpjhOeeFXT460YSSSidyDT6FgPPDC+twwxtj6tdC/RhBjpCre1591OtJijIirxHlWkSqlX/KSWYeEFxsL1Y4fI4WUfxwtz4LRkMdjqX5j0uXg9qq6406nHJNd9YRa+XP+2CvcsESE+pQIfdLkdA1ihg0Yz72Pn164KBy2z+HUVZgg1MIG/d5/WzQE05Auee7TYHLL/61G7eM6xgxk8fUSRJy5DlQDNm6tSblNkdnOPDncCsyKjRAdSEQLQtgFx731qX9UFgZXsSjcs5waM0Nc4eJ7dY18CrKtZJLtgKantBGS7P+GqEbnF+jD3kv2LdMFIHE3yAAjy57FPc5Zdv0zkjgf/Vzn3kcys/G26M3dFs3wRfVGvBvAvb/Iy4IGGVioMMLg6xzmIhc2KP9icq62O1hxF3K6lFRqS8k8Ez5XXKm/Ft8c+Y36JYkBYpHIjivqyn54osvcP311weu//nnnxg5cmSD1jFgwIBa7/d6vay8ikSdw4cPw+Vywel0stKtxvDll1+y8rFffvkFqbLmFyrHBrFjZXNx8qioqJycqCKPSggTr+qGksPV2L4sD5ldElg4c32gUoCcrcUwbk1jWTJEz4IxSHMNxo9dHmDXp6+YHlh+6p9TseGDJcgeKrVPfuUcLbw6Dcqj/NjeyYLMqdNgeOWtwP3Dd/iRm+pD371CWYlNx0ocdCYfH2PGtwZylyMx9ywY8QlaWIwoDXL0aCulDjaxG98DJs/gVy74EONlXRKoRChqZWg3rQ5l3Fa0zd8Gbq8P0IUOwn83PYzhzjcivlexvdJh8OeiMMEg6l+hIg8d7GloNsgQcPJEwmX3osbMB28jOyZLmTy1dM75t5w8TUVilAk/bzzCOlnsfuo0GBux/W1ieQbT7H2zsT9pP05ty7vAHS2eEl4yWDXvbyRdfmn9HximbKzjgDSWiUUiz4GtJegytEXYEit5lg6xcl8JhndIZpcXfcFLiNr24tfFgXywbZuynzrqHMj2KsUSlsmjkzJ5dImJSLziCuiio8O2NQ9GY1Lur/TdtPr9sJFz6cWOwq0ZIS6btsnh/5JKP/s87O2mzp3RECrs7rBOHg24ACYGQhNaPxd5ku6SZtRFmK4jliEm8c/BYQB+3vMz7nGeG/kzpsFnOKdSwTZU7FV+BtmHy9Bab+KB9IZKwFkVVuShci3K2wlGK3TYI+JTLTAJ3RDF7z2V6NI+RtDvPYn7wVD5njoLrBLOUUOCy3/xvPWBsmfo+7xz584m3wbK0hk8eLDCddNQwpWQyaGg6Ndee43l6lAeDy1P2UEk9jSUr7/+Gtdccw2+++47TJgwocGPV6kf8kkUsV9Gc3HyEGfc3AuzZ24OTPBNvquOsnIVFZXjHlXkUQmB/qhOvaYHvnpiFeZ9sB0tOydiyde72UBhyGRlZx15ackH9wgzzYpCLMDssOKP8/7Aub+ciyqX1EGLqLFq8dwT3aE/UoQ1cSWsrGvz5ZuRU5mDllNbsoHmesoeee79wGMuXiwNKqsOWtiJSOhQg/Szk4ByHkRshhNGWfjycM1O7EIytB6pnGKW5wzcIVyWD5q3PX4qbnz4U6RsXhXyWrekt8P5WA4PdGFFnnKtFpPaREG77wh6pXaDc99+1hlITuKo1tBnr4JDLB8Jwr93IRuCeozRLLDYGPQciRlRrO29iMvuQYXeC0QD70ztD2913Rkb/1YL9aYiM0Gy6R8ss6F9SsNbo8ebuMvsw628E9KAtAFIsjSs/Xc4kq65BsWvv8E7yMnEkTrxhneuRCeYkZBuZSWT4UQesQuWHCrZCoacPD74oSXvitcfEiR+6I478PriJbjzhnewM1/6bgaXa5FTSRMUZB4snFw3KgsQs5B1Qctq/bD6/LDJDnoTLr0EZV98ybrsiaJmJDyFBWFv91WHBhXXRuCgm0QeWZkV5QP5PV4pPJsFnPPL0ZNOC9z20OCH8PSqp1FD5VKCu8cYp4O5Sw0OFfGBm69G+l4Gd93DkQ3hM5veHobUPlEo3Cg5J41eN0lPKFm0EUkTqU2h4Hh0U3ldokJcj7Z6eDZZlCTqJaRJQlBGxwRsWcxdiTpB/KHyXFHkWTfnQNjf9i2LDmHDX7m44plhTdr5R+X4hkqm6uOo+a+g3JlTTz0VM2fOxG233RYiqlDAcWNzeWJiYtipLqhjFjlyGsOyZctwzjnn4LLLLgvk6ezevRvdujXsPaewZsr8IaHnjDPOaNS2qNQPyuAxCJMokpOn+Rxjte2ZjJZdEnBoZxnS28chrV1kp7mKisqJQfP5BVJpVpCIkNWHBxn/8Pxa7F1fyAYCkZwhc96Rut4EE2v3Q5cfExhgX9pVcjq8su4VrLPvwqqEUibwEDSYoBk70UnQb9rd2PToeYFOW5Eo2xMFjOWtzonN5uuQtYgH7RLdNIewxnyT4jEfeE4PXLbLAmijTHpctOYHxbJRrRyw64zoncn/HD1+HTwU5hw0qM828uv62M2Y3CcDR+65h4XEytHAhyeSk6Dzhx/c+g7zEhqWyaPRBcKLRWKSzBhwbTd8GS0LgZY5Iurj0vm3yrWaiitkLbAjlfXUBe1bLaIk0eS19VKg9dFADhBTx46B7mmYXgE8Vgokdwau/AM4k7qyBWGOAw6Giogi1lgjHEJwMs0SiqVXRLhQdLYvhgleJoGHOLI7tGyoZjkva0zUA71bxWNcF27lDy7X4iKPPqLIE2cx4KHTKW2Ho4uLg1VWkkDiktXv404eAVNHLirs7NkLdeENEnM6rV4FU8cO8FYrReO6uHFMe3x+9WBA44FJ1gXLl5QOv8sJn0MSyjRC5g6VuonEkKhLvzU6HQ56bNhXsY+5c7JdZrQsAdoU+OE8XBQq8iQJ7qX3xgK28O3sTXFKYZYEniiPA94Sj6IkjHXpylnKy97o/S+yI37nm8ArPULa5l776ihc9uRQdl0v/CY0xMFXXmBjZV6qwKNyvEECD4kslGHzww8/IDs7Gzt27MDrr7+OoUP5d4LIz8/Hxo0bWY4PQWHIdJ3Cm4+Gtm3bYv/+/WxdxcXFrNyqvpATad68eVi+fDnbZioPKygIL3TXVqJ1+eWX46WXXmLOI3qddKqo4A0pVJoW+f+vOGHYnJw8hPgzXltGn4qKyonD8TXKU/lXOe2GnohLtaCyWBr4HNwhHfhQR5bDu3j3KHEAeuHDA9k5zRjI2b6rBJ+d9hl+m/wb7ht4X+D2H7KVQkokBp1xNabdpceCXrKciaD8Ra3RB3ScAO/UXwO3mQukUGS3V+mGWezthSpYAwNmm0saZNGgul2BFIbY+YI8tBpaCovXhbaH+e3k5HExJ49SqJH5A9jsjs8mBduyberZk3XKSa5uiXO33hn29XotfLDtikoOtLI+M+vMwP16gw4D+qbhsN4XeEJ5p2VqqSwSqUtaUmbDnTD/JXqdFusemaAsu2kE1/W6LnA5xSp1ZDta9CnJStGBlI1bVgNthwO9LwZG3AncsAy4Zj5w8xogpQvvmBQBKq8Rv1dv3bgQ79/1D9xOvnxwqRbB9sUgyOUh8vubmxTZK+6CQsDN77dofWidaIVdCHsud5YrWqiT2wYR3DaiyBN4H1q0gKZ0L1qkSaWPGl2ok8dbXFjvDI2KH35UXNfFxkKXkAhfAwcsZoOOBTxbMr+C0SN9R7wGK3wOJ/wOB/QZLRTlWvIOdSaH9HynH/4J5/x8DhNxzJV8Xbf+6oXXE1RSQblLftlnUyGVi8oRF0nuwVu3f99RytJSijw24OMzgE8no/BAJXPxGbU2QOZQlHdOjEvhP5Q6IY+orgP8FT/twY8vrONP5fAGsnxUVI4nsrKysH79eowdO5Z1uurRowcmTpyI+fPnsxbmIrNmzULfvn1x7bW8O+CoUaPY9V9/lY4jGgO1bZ80aRJ7/pSUlAa1QH/kkUfQr18/5kYaM2YMC2+ePLlhjQveffddeDwe1mGsRYsWgdPtt1PnTpWmxi3WaAmunuaYySOK9TQBoKKicuKjHr2p1MrIKZ3w+xub0L5vCvZuKMKmBQcDOR80aMzbU4ErnhmOgv2VsMQYkNIqBpdMH4yYRDOcdg/WbMjHtq/3Ir/SgX6aVnB53MyVsmHqBvT9rC9bT9fErthRyksRXhr9UtjtyIrPwpenf4nFcy6mYReeP18Lgxe482fpj9Xn4n9c87IrMEm4zeuXdnGbXbJY/+XtjxeMNwNuwOHxMveLOMD9aNpAeMuVrgetGOhDA8UtW4DuXORhszexUrbIKn836P28fbpG44cvzOBVa7Gwwf2InPMjvu9eweFjN1oQZeBW86dHPI23vuDdoQxGLZslSo42wl+jgcbth8GvHNyJeFzewHW6TEy4sivM0Q0oK2omiGLC24v2YFKP+mVFBXNBpwvw+AoefhxrbDrLsjY6Br7KCM4SapU+QcqjYsS3ASpDg71FjFY9avKUs78k8hhMurDlWq/9nY1LB0tuJ8JW6cIKkxtDnfx9qypzIDaJD/qLXpa+axaNH1m71iJ17Rr0NPHBTtvYtpIAQyVVdTh5iKzffoUuKQk48Kdc7YSWiTw+2GWOEL9DEiX8Nhs0QSUVh269FZ6yMrT9PHwej7F9FuxruRjRUDRaNwyyVuduvRV+ZxVz8sSdcSZK3nsvUK7llXWos4YL6/Z78eUwHW7/1YfWxRTBEyRAbvw8ENLM+PUW4PolIavRm30BR0/XnTuw6IHZuH/dl+w2n4cEaoeUyUOUH8CGebw0tdqbVG/nntzJExVvQk25M1ByazDqsH4uX2cgk0ed9VU5TiFR480332SnSFA7czo1NSaTCd9//33I7eEEbRJy5LdTudnPP4u1r+FZtGjRUd2v0rTIP9aAk6eZ/XZqBNFJzVlTUTk5UOVclVpp0z0J054fgYlXd2clXFTPKx6MkMBDfPIgDye2V/HBTUJ6FOsSFBVnwpgxbeCEHz+vPoR+T87D6BcWYdGuQkUpyCenfRK4PCJzRMRt6ZnSE6c8OBPl/dpjS1sNVnTVoiqouY7b68ZeuzRY9Mp0zIO6Qdjp4SUiBxOH4d7zhrPLNkH4KKnhM/DpsWZ4i4vh0+jZ4K/juXmK5/DFRMNeapAyeWR8qT8XWuqlTaUdqOFOHpcztFOQzwOdL7LI4qUBsNYAm8cOq4Fna8hLJuj9JWj9dsFp0M6jw5XD+MBcLPdh65KV2Dlq+Gdkjg4Niz5e3DzEpkMVqJCVLzUWChhuKrQx0Q0rH6JyLQd3bYSDHBS2ChdzzImIIp04afj0uT0D9xVWObGvqBp5FUpHR5nWjxzKaxLKtxRt38VN0QGTvn4ZF+wRc7WAA5UHhCflj9EYQvcZEgG+Wp2LMhv/7lDJmj4xETCYFfnCGr0fFgpelmUUyFuNB5djiSHWYUUcQWzSGk1wZmejZuVKNAajzB2jK8xF+bffMiePxmxSdNeSO3mGJPGSqCF2aduvSU/Fsu4yV5CH71OtRvMW91jwFFCWIz1xntDN7JvLgP1LAs4eS5IbWacVIrZVaLaSV/jcGS4x80cWrKxX/kaFg8TBYJFniuC8JA5uDy1PYWHdaqmWioqKSghyrUQu0n2/7lCzdPKIxw+i2KOionJio4o8KnVCYgENDMQAWCodoUBOcu7IOfu2PmEf79D4YZLNcpQLg/Pb+92OzOhMFuIYeC5B0IhEp16jMfTL35GV3g390/rj/Ula1mZdLFf64MXLMfi5R/Fp9QQ8oLkDDkEFap37FzufX/wiO0/U2WERhBLRwVNCAc9UxhRthKekBFu7TcM/I17A4iSpTApZGmirqpHzVwpalhSGiDy5xvbS0EvjZ2G33nJlSQkLYfZ7ofPxwardJBsACnidLsBghc1tg1Uf+p6IBxT0XsoLfm4bL3YuAsZO7cLOK0ukQaNY7iMO+I5nduZHFkjqYtGFixBtiG5SkUcXExvZyRMOcywgK/8JhmbbqkodeO8OyfVBbgtCdPJEB7XOHvfSYgx9ZoHiNqfWj78s/HU6BZGPIRu8t80VQn1l+AWxUmwPHy4cObeUlyKO7BhU9ka5Mxq/wsljSOqA1RZzYH+NGd4vfIDy3oVAEe8OJi8BIwwZGei6dQu77BEyMyrnzEFjEJ08GZ01aJfDS8vIyaM1WxTlWlQOJaKDH6dWK4OVV1mUSrPX4YQlyYXoFrVkcNDnt+M3LvS80j0kl8cj/K7MGDg1tFxL3Gc0WlhijNCbdOhs5g6/2sr/KMeLvS7Z7DI9PrDdMjFLRO2upaKiohKeyX0zwzp5Xpi7q1lm8hwWcvlUd6aKysmBKvKo1JtuI6SyJOq2JTp3RIJzeETaZcRgUkeeMUNYBXHlmp7XYM75fID24akf4p4Boa2KI/HtWd9i+tDpzM1z6X16vH26Fjo/MPqjjYgqL8OPpSOwydsGuWv44DClWJg9p0Gbz4x4rQ0Wgy7Qjlp+Trd7S0tRIszaf5d6BzCFl4xsS70a+al89tvkdMEdFHbrNcTAIwyedfDCZNDyPJNgmJOHD9D9WhOuSLkGp+y7Ax32cHu3vbAQPoMFla7KsCKPPAzWKFxcbnLDJJulF1smH9wuOApo8Ci4euSZPccbFw9qxc6v+XRtnVkukaCOWlSqRc6v/8zJY6pd5Ok6LLSrlsfpU+QsxVsMGC+EJUeiWuNnQivhqJEEi+JKyY0y/vs3Ij5e3H/Fcq33luzD3iIuylQ7+fouGdRa+aA/7lE6eXR+rHTz/K65UXx/tnRohXa//BIq8nw2GZg5KOiFC9stcwLpqSyMbjIF2fnqIK86Dz1yfMio5ILoF7ty8U0Hnn9D7crJydP6448R25OLpH/O4qISX8ALk5/ez9Dvz7aB/H3y7C/mgti570TeiPWCezHC519qc+HecgsSYnkotaNUJrDZBceNhjJzPEhO1UrvtU36rgcjZvMEO3ZOv5G7wcg1Jof2MebkUQcEKioqKiG8cEHvwOVwpfnNqbuWHFW4V1E5OWiev0AqzRKTRY/Rl3RW3Db2si7oODANZ9zUK6IFNC7ZgsqtZVhyDx9I7SmqDggqIgPTB+KK7lc0aHvSotIClx1BlSSxsQtR5DZhU+9b2HWrTepMsb7mfBj8bhbCKu+q9edWXvJg0uvgc7mgE9pbz99WgMez27HLBea+2N7tSna5GpbAjLuIxmiFOIzu2zIGVw5rB4MQ5CqHun74hYG3RmNFtK4EVlQivWAN36biYnwdxctGDlVz6688NFc+E2MSvEP5ep9C5EnPilWIPYTH5Tsu26fLeWoyH5RWOTwoFtxXjYG6t3kEt8Z/4uRJbAc4K4Dyg2Hvjpe1wA62W4s1/wadFh9cORBRgnAajiKdH04NOXOkgHRidz2dUAEnj9A1bsYfO3DlR6uVwqhcNFw5i58HZfIYzLy7XiB82WOHLoaHf3srI2+Lz26HX2hFbOkldeJKvpl3yjN1Vv4m1cXNr0/EI19r0Kn8/9h1l1aPpZnSerVmM6KGDEb7zz8KfbDfC7Pfj62m0NI1ezL/bvlLbLDla4DeFzG3TVh+CxN+2u2cwMXiKr5fd/HyfUDeWj3QnUuj5RlNTlnXHWfk/Y/a5lIuz4SrlG2Y2/VOYQKQmM0j4vP41HItFRUVlQjInTrh+ls0t5/OgWfwcn5VuFdROTk4fkd6Kv8JmZ34QE3u7jnl6u6BMOZwtO7OZ9zXf8YtrM/P2YXrPlvHZoojdX6qD/Iyr+wM5Z9WrG4vBtjzA9f1HgfGF/2PXV5XcwF8HmfAUUTlWuQI+WNLPkweF+zz5jL3gijyWH0afLT8ADZ4eZ4P4dXqYdOY8eMGZXAulYC5hX/21olGGPVa+G3KjBRjmzZw+lzwavngWevl26HR+gPP6bbZcdDAnRPk5hFbJYuIgtqErpLQpfVLmTVsGY2GhStTALaIRxiUU8Dq8Xxg9cx5XOgJzp9pCHqNHi5qb91EaGNi4Hc6mUBYLxK4cAhbcdi76fObOkNq9Ssv13LY3czBJR5kvnu51K6cOKTzQmfSYsTdvXjXNRJ59JpAuR6hR2h5Tl1OHvH7WiOsxyE4w0gYDbDuY+EFSN9tzdh7cFp7XvYYCAh3O6BPTmZHwp5DB4B8mWNGhqeklIUQWYcMQYunZwRu14pBzbWUKIWjZbEfPlkmmEurg1PRIU/6LWnTIwlte8pCjX0+JvKIbj05VleY3zJ5V626OOetwEUx4ygs9jKZyOODPloWHu5QBsbL0em0uP6NMWjfN9T5RQHM1UEiD5VvqcHLKioqKpHJiONO0nCuYjEKoLlgMAl5dqqTR0XlpEAVeVQaBIUqX/PKKNzw5hhc8/LIej2mZWdexlV4QJplXrK7CFkP/cFORyP0PDfyOZzT/hwUx2mwuIf0xzV0hx+3z3k/cF0DP7zbhcERlTalXox4K5+N33akEk4hj+KKHX/iyJ13wX3wEAxeLiDE+/h6HZBEJa/OAo9GFwjYEyF3kOuUJ9llrZCOS04Ekaw//kCbr79CpdcGj5YP5DQ+SeTRUkaM34ftHi9KBavvpLa8V5g8gFcaePmRTW3GWHmYJmx4rxi2S7PyTqFc53h28hCndOPi1sHSxos8mTGZ2F+xv8m2yZTFRZuapTyIvF7By0QtJVvUCevUa3ugwwA+MJ89czMT7ebPWI+bKswQNT25g4ugPSGmfSx0MhcXzd4FWrBXVSE2X+qiVBt+t5TJ49n8HdJRAieJhaX7YXPx+0RXHF+Qb4tcB9G2G4Jb+97KLrvE2/M3Q2M0QhcfD8+it1HxwETknDo45Pm9ZaWs213MuHHMZSM9jZaVb/k9DTuQvvEPH/waSeRxa3VwyUQeuTOIsqvEEkf+ZvByrXBoo5SCzq5SZa4QkjsDNy6PvGEm7moiSoUQeGJHcpZyuRVCpyBbCXN2KfKw/7gXjSE6wYTqMgf2rJPa2lNXMdXJo6KiohKZGcKEU7jDWLGpR3NBq1e7a6monEwc3yM9lf+sbIuCmOVlQLVBZSfUgt0aY8SSa4chK0XZKnnLYT7IXfDpDiz5ZneDtuX0rNPx5PAnsfSipZh5ljTQ7LfPj7w05YBRK2tjfOGQoUiM4qOjJ37fjhohWyTBZUdlTBu4KypRHZWpEHkssll5j94MX5hSDMrzsel5mZVemN2Rizymdm2hT0hAuYd6jvklJ4+eD17ZM2m0WOHsiz90fGZ9UDrPJyk5LAW+6mWD6gNC56RwX2b6jMQSnZW/7MXc97Ye904egj671olWLNsb3gVTH1KtqaigcqkmwtK7N2AwwJUTGqQdMXiZsEd2XxAd+qdiwpVSiU3OZv6aDdBAKwzA5SJLoleDTK8OjjIX674mUuXxBsr1cq+6Gun5QvesOvC7BTHSXQ3jz9fiPsM3aOk9CLzeB7pt3zNHnPhdYugEAUWeyWONhVajhRlauETRYD5vY6+Li4O3pBBHVibAfoC71jwOaW+umjuXnYd7XzU6XaCcrCH4tNL75dDqYNfJOo11l95ryq4S3zP+ZvhgjiBK+1PdeGWytN0fbP1AuUDb4UBad6BNmA6C58yU1tOiDxbslMSWf1r1jWivp0weg/D9Z3hcjQ7Xp26Jy77PDtxGgdM8eLlRq1RRUVE54RH/g8XjOXlXrbbJtTcS+bcRW7qr5VoqKicHjTp8mzlzJtq2bQuz2YzBgwdj9WqezxCOjz/+mM0Eyk/0ODk0EH7sscfQokULWCwWTJgwAdnZ0sGmyvFPXKqFlRv99sIGfDSpJ64ZIZSqAHj0l62oLLZjx/I8bFmodMZQy++ZNyzA4V2SCycY2qfiTHHIisvCVy+cG7h9f7sz2Hnv0j8RPXo0tFYuNhF/vrBBsQ6x/ARpY7G2/31YvFPqFmTwa2D2AVvLbg7c5tFbcHqPNLQXBCvfZbPxzz/9kVpVDJvYsYnKSKjURcgTYbw1hJ1l+2zQ+oWWxj4Daq5fAm+vswOLtSnnHXeo1bxOGJCSCBbcKSfGbAgcWsiqYwIYzTq4Hfz5s9dIA0fdcRy8LH7m/VrHY2l240WeGEMMqt2hrbuPCrcbhc8/X//g5TqcPCIkqvae0CrwmYpoBFeJ3MlDIg9hSDYpMqOcfj8TBSgs2bFlS0gJYTBRYp92MZPHzQWYdJQiysfft/iyLUiwGpVdRLSGgDNNegJ+sGvUm+AURZ7YTGB6HEhfEaoUGaSlum3Sa6xevJg/14U8Q0cBBRx76xZ5DlYeRLlQyrR0gBV+jbR+u06HGqMFl536KLrs2K5wrpCYKpY4UnkZNn/DyrVErpV1zqP3i4LgH79Yi3uv0iHepCxtRd/L+HkLKawz5L5792Hfmd/jJ1kZqENrgN9LrprQh7lramDQC3dQ5lF7nnvWUKgLIFFdJn0QRQercHhXefMLllBRUVFpJoi/jnLtv1tGLM7rl4ku6bJS2maAVrD+isKUiorKiU2DR3rffPMN7rrrLvzvf//D+vXr0bt3b5x66qkoLJQGkMHExsYiLy8vcDpwQDmD/Pzzz+P111/HrFmzsGrVKkRFRbF1OhxS62eV4xtztDTT//sbm3BJyxTsfJKXIQ1rn4wdK3jocTCbF/BQ2p9fUYoy4fhl8i84t7dUruAw8yyN7q9PR/S4ccxRQ2KTnOln8Vn7XQW8lCxRcFWUJfDOOgRteZJPiwqv1F3Mo7PArJXEIZcvFcmH89B/2a+w+bnI4/I6Ay6e1AfuR/szC4Cinex6deVB6P3c8ZDdYjWG/HEBvi9TiqVanw7JFinrqPOQdHZ+xs290F3odDb9rO44px93HN02tkPIe6I3yspNNMp8juOd9DgLa+H955Y8PPrzVhwU2nnXlyhDFKpcDQhKbmpIvDPFATWRfzvlDDiTC6N/vC0JNDV59pBMnOFt+X6v65MQcPIkRxtRbQDKi+yYuXBP6MrDHPR9cYRnWgW6w3n5++uDBnqhEXqbshUhpWIQSp+03XkGD8PARZ5oYxwqLQlARl+gkgsZWk8RvHbpCJnahbtrpNfjzN7DRChzly4RnDyRLfGfbPsE/T/rj9N/Oh33vnkmdnTpihFrbVg+9KnAMg7BeVRiicOmQxWY8s6KQJaCTu7k+eclljckF3nkrp4Y4fZtbbU4kKbBVzu/kjYkpgWQ2V/x/oQlKglVPuX9NUJpmU8Q7+R4HC7os3+VnqOW4OXa6CL8tsjZ8Bcv5yvY33RuNxUVFZUTCVEwEWMHqCnC5kMV2H6kfo0N/otyrcZ2JVVRUTm+aPBI7+WXX8a1116LadOmoVu3bkyYsVqt+PDDDyM+hmZG09PTA6e0NCksln5sXn31VTzyyCM455xz0KtXL3z66ac4cuQIfv7557DrczqdqKysVJxUmjeWaOXAhbUldvoQbzVg1uK9sAuOA71JWUa0ZnY9S1+CHTkynDFV8FKnKj9l3kiz/pQ30SqRDz6v/XQtOze5lAMaD/ws4DZ4eEXlWh0W/IRLF34Ep8fLWybT66RyLzcfDLt97oDIY8rKwsZkPQ5SG2qPE3l6PbQ+LUx9q7Gs/Q9smR972hA1UirlMHhNzJ0ksmslH3S37ZkcCF6Osxpw3iQu7gweIolQcgeI2JFJ5iY+IbhxDA/CvvGL9fhs5QGMfH4ha+9dX6KN0ahxSyVwTYm/vuHL6T0jBg4H8+Xag8iVl+Yw3UVw2Qg7aKe0aJzXswV88GP9oXJ4BIfGkKwk+ExaOKrdiBbCF+UoSqGEA8B2bg/8XrfUXeuPO/g56Qkavo8nOw6wcHEFYqixz4OotkbEtrEFRJ6UqDQU9TgbiJb+A3Soglem5x9cnITDyxKVq4yJCfueUBh0beVaszbNgsvHP4u73g/fXtwjvHed02Lw3dqDWLW/FLsF0ZfKGgNOnv1L2Nke4btOyPN5EmWOvSHR3BnlfLQQeDgfuH1zaAv0CLC8I/l1QRTyj3gImPSc4j7WXUsjvHmWeMDZOGeaOSpUeBLLPCuL1ckWFZVjyaJFi9hxcnl57aW7csaMGYM77uC/ySr/HaKJVfwrIKcssTP/P5xAioCY5aiWa6monBw0SORxuVxYt24dK6cKrECrZddXrFgR8XHV1dVo06YNWrVqxYScbdu2Be7bv38/8vPzFeuMi4tjZWCR1vnMM8+wZcQTrVeleZOUyUNFqQtXphDEXHyoCuU2N3R+YNscPmtMLX5FqkqVgwtvULvycNS4PJhy2uO46nYdCqMOIC9mHyZ+PxEv7X6H3e+ukfJx8vdXhgx4D2eODlw2OstRTK2f/RrWuUqxLXoL4ndvxei8HXj5z50Bt0PLzSvw/nbeXSjXUQyf0FlLW3MQV7dIw9ktWwBuOz6Ki0W8Ix06nS7Q4aksRoPW770XeA69z8iEorqg9sc3zxqH+NTQ+m/KFKEuOcE14ycCcRZDiIvk9fn1L/OMNkTD6XXC7a37PW4o3up6DrbjWgJVshbYtbArvwr7hdKc6JZR8FKYuCDyJAiZOPed2hlLv8mGFhrY3F64hZIrKuuz+f0oyq2CVwjfFlnXWfkd6LdHyIqigX5FgdRdS3irdRof2mi4+8gNQ6CdO6O6CMj5h182x6H1BSnIHFoeKNciYc1GIqjsPdfpbHCWy8qnSkLbk2uFVuvBeMvKUPTKKxHfM7HUUY5PVqpFvHFpP1w3KgsOEmuFY9+CSkcgoNwrOuEOrmRnJTIXXJpM2IkXfp8eK7dh2pCH+LL2EsBgoS+i9ISi2+a894EJjwM3Kx18Ygh84LrwWF/PS4BYpZDr9hlg0Dqkcq1GOnmscaHvuSju9BzNnYIqKscbdGx56623IisrCyaTiR0rnnXWWZg/f35gmXfffZcJJuQ4b6jQUhvTp09Hnz596rXssGHDmMudjmebiqVLl2L48OFISkpiMQhdunTBK7X8Vqo0DrG8Vzy+okk/4o2L+6K5ITq4xWweFRWVE5sGiTzFxcXwer0KJw5B1+nPNBydO3dmLp9ffvkFn3/+OXw+H/tDO3SIZ6+Ij2vIOh988EFUVFQETgcP8pIeleZLSusYXPr4EEy6rgc7EY4aD2ad2QNXV0qhp+Q0EK2kviBRp2B/7Y6t/cU12HyoHJWmKPxy+T/waN2oNPHMlm1uLiJV5xYFls9eUwBPvqw7U5AGQm3XXYKTJ3io6NGZ4IcG/4x4Ac7VRVixU1ZuJmz/6pqDKC3jJSmaP2/nj6MDAo8TBh9/zTroQ8QXq5bP9Bt8RnRO6HxU9loSzajchAaq1aXKFsknAsED4swEZTlebSRZeFlTfk3435nG0Prjj9h5+bff1T982VU/NxEJOQlCCHjZoWrUaPwBwYbEypxnz8CgNGmQMGfnLuwRHCkp0UbUCKEumuXFKKCSKQC33qDD9kzle/jA99J1R8lBmcgj5P/AjSjw7022LwPZhTJBa99C6fJpzwPtx/PLgpPHorPATl3rOkiivs7gh88TJsS8bQKSe/DvvEYMc46AN4KbUycIOj33S6/JZVS6gk7pmc7Ksw6U2OAUBJ11uWWB749bHrwM4I4yPghs5XYrnDxJXi8278/F/3kMgX2r2B4mM8ojfA9b9AJG3AGkSN28wu3TDtHJQ65Ap/Q6vX49fH4dDBphffTbkj233vuTHMoe6ntK67D3jbpYuX0qKscDOTk56N+/PxYsWIAXXngBW7ZswZw5czB27FjcfLOUr2ez2TBp0iQ89BAXZv9t3G43jEYjc7k3ZSc7ij245ZZbsGTJEuzYsYO55elEopZK0yF+ZOJch/gfQll1zdXJI2bzqKionNgc82/60KFDcfnll7MZjdGjR+PHH39ESkoK3nmHOysaA83I0KyL/KTS/KEuW6wrl0XPwmOP7C5Dztf7Eefnu2FlEh/MfPbICiZq7F7NHQ4TpvHcnJ9eXB9x3Td8tg5jX1yEmQv3susp1nikmdPh1/A/3IwWfKAS/+urgdKELYsOYeOnUjcvixDgGl/O3SA6nxNuDQ9eln9RjP5qaNIzURPFcyx8JS48/xvvWkUYZEYJezUv/9LqZSJN2X7ovfwAIK5daJnEJz146/chycNxe7/bWbmI6MYZd3loLkltkBOBMnmKDzVxwHAz4Rmhfelvt4zA42d3x96iakXYcG20j+PlXvsq9sFLIdlNSNmXX9ZvQZ0REJxcdVHpIFGBH6TNtrpQoyVnGhdgygtsrDPdkq+k/Tm64zOYf5B3pkqOMaFIyNHRVLlh8Hnwef8sFCRoYAp6+i1tpIGGcdmLUgt1IdnbSP4djSdwuWOqzGUjd85Q+dDo+1mYsHi7WW+Gw+MAht4kvQWm8J+XNr0DLElCvlVQjptI4rRp7Hz3oMEofDl0lpo6ehGPfi0TeQxKkYcGVofLuWglBh7nltgCmVZelxf+hc8Glm8hzNSSwCN+1e9ucybom8zeOZ1RISAW2oIyl3qcD5DIFhOagyOfCRY5cwDPYvJRRl1PKXza5uPBznqxXKutUOpZ1TjRUu6iVFE53rnpppvYd5sag5x//vno1KkTunfvzjIlV67krjyCSp4eeOABDBnCmyI0BdRw5PHHH8emTZsCDUfoNoIuv/322zj77LOZEDNjxoyQcq2SkhJcfPHFyMzMZHEIPXv2xFdfyTK+6kHfvn3ZOug1U6OUyy67jGVd/vOP4LRUadpMHkHwF0V6UzP8PRXL/EWxR0VF5cSm9unRIJKTk1l5SUGBsryArtMsRH0wGAzsz2fPHh7+KT6O1kHdteTrrK/VVeX4gv5oWnVLxJbFUgcZYlONDSNhQFWJA/s3FWP1b/vZ7QnpUhkSiT/hZrvmbFMObGgZq84KnzB4327gA620NtHo92B3vPfIxpB1nNomBthGDh4+wLN27oihCVGwVbmwvVjK0TDrq+Cy++AycteEC17oZVk/VidQYaB8Hz+OfP4haLin0UmDzOz98xHn4V+9KIuy0xzh0fJR98i0UWxQTN3FkjJ5Fy+tvItRPWfovUwkaloRo7lw8aDWOLNXC1aOVFJDpVd+5FU4AllLtSEOxG9ZcAu6JXXDN2d+c9TbYx3E293HniULHa4NnQGeaid0bncg1ykSVQ4PFlncKNf6kG3wobvLD2e1m4mVS76WxB1iq5Xnz2zzvI1o04uIMuqRLwienjgDE3ncwq9/cqXSJXaEvy0MuzUDRtHJI+g3sQYfjEL2lVXnxYRuaaF5PIFzLQsTFgmIPIq3ILzIo4mKhTlOuE/eoU5G8vXXofSjj0JyhZx798JXXR1w8sg5mBY6KfDs+T0xaMb8QFC1XcjFoXJHOnb3LXoB4nExvbI0axpuKdiK4XYHplRW4YIMKvN8S3hBRiSYEpjAdPfiu9lNW66Q5S71vICfIiDOBIvoy7k7jeV76SXXY56LC74JOuF3tM0wYQVNlwUx6qJOTbYulRMH2hed++qff9ZUULad1lK3W7O0tJS5dkhAISElmPj4oM53TcyUKVOwdetWtg1///03u01eikWlXM8++yzLo9Tr9dgX9F5S0xFyId1///1sEnP27NmYOnUq2rdvj0HCf0xD2bBhA5YvX46nnpJC51WaMpOH/3c4hP+OkIYEzQDKoSRUkUdF5eSgQSIPWUrpj4fqmSdPnsxuo/Iruk620PpA5V5kmz399NPZ9Xbt2jGhh9YhijoUpExdtm688caGvyKV4wJymASz3uTBSAcf6B7aKbVMN8jCmKnsiGbX64VPC5+G/+GWucphHD8ajvmLseu0iXAOehwmLxcCXj2lGygG5Nx4P77algO9EJystVqQEG9GcY0Xlw5qjepFXNw0ZnSEJy8HXqFVNGUKpdtKlSJPNHDBUh+SVm1nt+VYpK/aeTlfIwFc0LSYlSIPOUrcOl5+YRDcPkTJ4ZpG2WxpkEpOHq9bGsiPv7IrTiRI4CFEYWf2ljzcMJq7dGrDSC4age0l/HM6WjRaLUxdurDSGjroq1myBFGjRkW24euMyP7Yhbjyx5Dx7DO1rrvS7kaV1o8lFi4o1mj9sJe7QgSeFh3i8LJjPUSZy6DTwGrUoVznR3SSGYWxWhi9bniEThuzB2oxbrMkoojZznt8GYjy6+FauFDh5GkRrYVBCJfM8Begc8VS6s/EH7TybX4+9aewr8GsCxV5NHKXmwyt2QydngtMiZdOCbuMTjZYM2RIeTX7zuAiW8GDyr+43RnA12PiMZYb/gKkxphD3mv2Xhj4b43Hb4ROcC8Rf//f36z9O/FIVBeg46lA5gDg8FomxFAWkE/W83zCdxPwxrg30DWp7u8ezQTLtVx/sZD5IHabHPsIc0nZv1vEXDxJhlxg1H2ASRCvGttha2gLFnR/6RND8MVj3OmQ0enYDoZPJkh4oHyY3377jWUZkrvktddeQ3R0+LwpgkprvvzyS9bJtKqqCmVlZSECBbk0gjuWUm4huVOOFSTw5JwfWag8VrT94XtYunevczmaRKTfX8qh+S+gDBz6XEnACTcBeskll7DmJSLBIg85eO65557Addpv5s6di2+//bbBIk/Lli1RVFQEj8fDxKVrrrmmUa9JJTzif7tYriVm1BmaYUmUT2jEQL8/KioqJz4NEnkIsrpeccUVGDBgAPuzoZmImpqawB8WlWbRHxQdZBBPPPEEs8F26NCBWVGpNpoOSMQ/GvqBJLsszS507NiRiT6PPvooMjIyAkKSyolH12EZTMi54P4ByN9bgcIqB1x/bUXN2S1gnF/I3AkiPosO3UZkYPvSIyxfJljkUQS/UolgZjy2LjkMjV8Dn1YaaM3PX4KRtNNX2QICD3H42/0suPjAX+vYdaObD5Ly9lQgtXUs62AzqHUiFkAQecx6eDRG+ASRR+/3I9leoRB5iBhZ3M8F7ZSZUyYPn420BNVt2zw2eIXBZJIxJaLdtr6IwbHyTJ8uQyTH3IlEa0HkefbPnbhyWFuYhQH6v43WaoXrQC5yplwEx+bNiJ8yBS0enx64n1qtHnr2eSSNHwur4Hip+PnnOkWeKocyIDrOp0HpkfD5KxpB3CTKbG60iBdmv01a6Ko8MPi8cAlvz8FU5T4llhtq4Ie26ghKv9usCF7WVxyABVLXtwl7qeOTMHDIFcLyW4YfiND+vbdiLxN6zJOeBeY8AE087Y9OJJ/RE/aKONQsJdEIMLRIh6Ya6HLhEWgmC9k+4V8sy8ESO9nVRkmsBhZ3NExWPSwxRlbmFo71ueWsPI5EUsLjN8EEYdneFysXvmoOP+8+mYs8gnhIbp8CG//NoPOvd32Nx4c9Xuc2Lt9bHBgwyEvOPDXC84++l515v10KHYR9YtzDgIvu1wDlNOCnX7qGEZvMA9yJrL4p2LehiP3WqTQNl156KQvXnTdvHsthoWOm6667jok4kRDzYuhEWYSRoOMs6noqEhOhG11TOmpIcPm3oeetD8eyRfQXX3yB66+/PnD9zz//xMiRDfu+0fFzXZOhTz/9NBN1Dh8+zJqeUFdZKt1qKFSeRc1PqESNhD86FqcyLpWmQZy/EXc5sWxLLONqliKP6uRRUTkp0DfGhkqzAo899hgLRib3DVlSxeDk3NxchUpMM0908EHLJiQkMCcQWUap/brIfffdx4QiOuAhIWjEiBFsneYgl4PKiUPLzgmY9hzPkIhJNKMd5aj8tRVvLdmHU9wG9BZ2TZ9Ri/7PzMf8SwczkedQYQ06RCtnMqe8wweWmfEWPHVuD1TNO4LFX+6CzgT4EqXB7oJeGozcFv7gb0v3Pvhn+POszCT9kvORu1RooWzWoSyvBtlr+WDtrNt6Y/PCQ6jRGOATBnM0Vo5z1cBuoAGkH4nVfhTqLPBppQG4P0iciXHy4NvoROU+Ti29fVq+zfEGvoychv45i8HLx/CYt9lAM2f3T+qC5+bsxJqcUozsGCqSBXNxl4vx1U6edTD+u/H4+oyvkWKt+3G14TqYC29RMbTCDH35N98oRJ6X5u3CmZ9+jJpPP0bnF8+THnfgAIxteOvtSOVa4Vp/E12Ht0Byyxj8881udiA3vEMC1ssMM2mxvMzH0ioKxtVF7MhULNdSbLueuroBWT4t2mvzgEN5KIXgkJG1mLtELwUsmz3ybjQaoNOp9MUJ+xp+zP6RnW8s2oghQ24EhtwI3YO9+eqNRrR87VW4CwpQs3wF4s8/D1hUBM2qWcAb/YDpkpAqJ+u3X3Fg2jT47OEFG/nOP7efBrHuaCbwnH9vf9RUSmHkIzokY+meYtw6rgPeWLAHz/yxEzd3ywyIPAHOncXPB1wNtJQN1oxCWYjwu3DPwHtw72IuyLCbZaVjX+/8GulR6RjTakzI5v6+OU8ZAi+IPHl33gljchKsAwey6770/tDtcwOJgmuNOpiZ44CaMGHPDWTw2VlIbROD6ATZ61ZpNBR8S8c0a9asCQzw33jjDeZofvHFF9mkVjjEFtmU2VIbJOrUt2S+KaCSqfo4av4raMKQJhB37tzZ5OumLB3q/ipCk5oNJVwJmRyaDCWXF02iUh4PLU/7Aok9DYUmTglaD8UgkJtHFXmOXSaPKNA3cD7uX0EUP8M56VVUVE48GvVNp9IscuPQzAKVVcn/8OhgRAyYI6hlo7gsCT1UW0yZPHLoz5hmouh+qkWmGmYKyVM5edDrtCxbhXAJZSHESxYulLy3jnfHumqm4BSQsfYAL+364MoBGNs5FZUFfEbf6wQ6Vw7A/3XiYaXb2mqR+nD4Dhr/DH8BGqG8ovdk3v2rZZeEQKnYwe2l0Oo1aN0tic1ul6f1RH47PutNwcxdS3OwtS1QYQVOX+OD1RgLXS0xOHrqrqXxw2xWOnmo3bvo5PELsy5yGpXJ4/GFdCo7Ubl+VBZrrf7AD1vw/j91Z0aQ20KEAnKXH1l+1NsQf/757JwyYURcQjdBd2EhZi7YI92+RnCBkJclu/b27+QsuW1cBzx4Gi9BcA+QREAKNI9P424dEvXO7ad0jlkEV5Mu2US7HdyGGLj1GnRK6IIuiVJJQ3GKCcN2+PHKFr4uuTg43Xs57nVfF7JdB1L49yDQLUzMhqmFtza+JW2bMQfpA8qRcP1t0EZFsdn6xMsu5dkbFNxcB6YOHWDu0hU+Gxd57Ju580jE4AXceiveOEuL7W20sHiiYYk2wBxtQFKGVCrz0bSB2PnkJAzJ4hlCUUZdwDVI5VqMkTxjh3Hmy0CfS6TrViF7yFERKE2TIzpy1uSvwYxVM3Drglsjvib5t9yaZsGBGP55ln3zbeD2VXt6wOZLlEQn9mbEAKvfAyqP4GhIbBGF/pPaNmm3n5OZFStWsDIruYNjwoQJbEKMjqGOFsp3oVbZdGxFAgGV5kSCjsWoJF5+OtFITExkIcMzZ85kE4jBHE2bdBLUyA0jnqg0K1K8ATlyGsOyZctwzjnnsLDk3r17sxbwu3cry3IbA8Ur0Oev0nSIh2SiyCMKKc3xt7N931TWRbHLkH9PEFZRUfnvUOVclWbDK1P64IMrBrBQ2QDC/+R3O/JYq3EqUQm2Yov/pZ1SuUW9okgq2xgypAfuGSDVtudV8pDS1rk8DFHETxka1BWnZCuM0RZc/8ZonHVbH0UekM8j1FqbdfB4NSgz8Rk8arHeofww1rfXoNoMdM8Fhq23Iy6CsYCtw2uERg+YyG4UhE8IyPV6/SGvtaFOHnHGhtrVE73GtcSJDIlg5OihbklPzd6BGiE7JhIjW44MKSc6Wlir6yByLr4YNStWYM+o0ehVLAXClFZIAvmhW26Fp4QHJkdy8sRaDBjeIZldN8lKaUjksQpunZLD1fAJnbSIywa3ggUOxMCGUjs/wHeYE9ArKx7xplic1u40PDstBnvGdUB5MhcmnH9U4IsDE1CSJwlJbo0B29POBszcSfeO5wzM9/aFyS+zDLntgXbp4biz/53sfEPhhsBtmsS2SOhgg9Yc5nHCc9UFCUJ+G3/fcy6U8ns0fj/iaxLxz4gXYPX1Y13tOhcNYiVzwdB+QyV+9P7GmPRo5T0APRxKJ48lMfJGJLTl5zU85D34u+2hsGuvG1fNvSpwG32/cyu5gE3sEdrRJ/iU3/NHh14DV3wSNEYuNpXlywauUXx/CLiJKg8BX18aeTtV/nVoAis1NVVxG+W1kBhB9x0Nt912G77++mssXLiQlRFRmQ+5oyNBpfQUAiyeWrVqhRMREnhIZKFYgR9++AHZ2dnMUfX666+zrq8i9P5v3Lgx0AyEMiPpOmUoHQ2UlbR//362ruLi4gaJK+REorI+cr3TNtPnGtzwpD6vn/Kf6HXT6YMPPmCuMRKOVJreySOVa4m3o9lBx4PDzutQ/1xLFRWV4xpV5FFpNtAga3zXNCDZBJvWj0OCFaZVogVeDVCl4SLP/uIaVNjdGPfSIjzww2aY9To8cFqXsC6XQWe1g9VgxTMjed7JpdbP2bnFHv6ASSN0ySIHDK0vnK3VEPQHGWM0QAs/CuMBr7D4xT+Xod9e5UAy3iQNWPU+A8wmgyL8V9oIP6vQoLIbUVgK3NWIci1iwac72PmgM7l1+0SGWqmL3PFNaBc1OZ0SOmHz5Zux8hIeNPv0qqdhE4K3G0vMqaeG3OZ3ulDxy6/s8thD6wO3V8yRyp6I7OFCG+wgqC28zeVFrNmAGEHcccrcWVWlDiS2sLKsmbFTu2BPueQWykw0wPj2IGwxX4PD3/DStHX97gXleuu1ehj8wI4MH5Zf3AN+WY5RvxXbUbREmqX2a/SYfdtIoN/l7PpBfyqqYUGcVhB5vG7eDt4QufvN2FZjQ2889x1+HhdGgJQHRIp2eJ8f1WXKAZN90ybULF+O/f93oeJ2swsYHs+dRUnOEYi384F2wf7a3QuD2iXiig0XQb/gYXbdA6Oya1g49OLr1gQ6icn5IfsHXPCbMqz25XUv44yfzmCt1gn6XSP+dwp3V0UnmhBr0qPImoCyjLbwVlSwHKYvp8vcH4mynBKx+1ZJULK0yjGBMk7EFtmRTseiZCg4J3HMmDHo1asXbrjhBrz00kusFCySqEDZPhUVFYHTwYMHcSJC7hcKrB47dizuvvtu9OjRAxMnTmRNPqiFucisWbOYA0rMNBo1ahS7/uuv/Pe6sVCwNmUp0fOnpKQ0qAX6I488gn79+jE3En22VIrX0IxKcu3QZ02RCuQgI9HnueeeY655laZHKtdqvpk8KioqJxdqqqJKs2NSj3TMLNvPxkrk7MmIt+C01/5BtQ5o49Fh5sK9LGR3X1ENOxGFQrYGDXbliMGhWkHP9AlCULl+OQauzYXG78XqgY8EltcHlU/JadsrOeCakON2U0StBi0T28Fipll8ZXebNR35c8YYY1Du5DZxnc/AZlOiDOFr8+k5qMxq9WzeRl6EykwaQrBI1dDg5uORM3q1wLNzLDhYase87QUoqnIiJSZytggNxKx6yUVy+8Lb8d4p79X6HHaXF/f9sBmPnNEVabHKwbxZljfW8s03UPrZ59CYTSxcmZh0YHWDX1ON0LKcBB6LIDK6PD5Muq4H5ry7FW6Hh3Veu+blUcif8TRSVn8OnMeXu2hQBjQL89jl1PIc+FMAnccOu9bLSooMu/+C2+uA8/C6Wtu4Xze2M78gCKHbfW3QU7MfMfmLAGc1YBc64kVHtoKTGy+E1kMi5u0oIPHNGIXVv+3Duj8P4MaZYwLd5qh1feVvv8GxZYvy++IELILwoYUFGuF3YGAdYmfnFDOQAxgOkOPvErh8wv4RIWuIoVcKQeFcevsqlCWEH2/jpc2ljlKW0UP7FXHoB94O3hpjBDUfS4oywhMdj1+95wFP1FLek7eJnzvr8X6qHDUkHlx55ZV1ig00SC8s5A4vESqpIrdIU2fpUPk8rTsnJwedOwvfWRkmk4mdTgZatGiBN998k50iQRk1dGpq6D3+/vvv6xUKTUKO/HZyeP0s/F9Eoq6cJurIRSeVf9vJo4o8KioqzQPVyaPS7BjZMZkJPB1So5mzp2uLWOx9+nRkeLTI8Grx95rD+GCpcrDUIzMWNRVOfPpQ+EyVU9qeErj8wJU6vHCBDjHVhxBdwwe/IkVRHRTXxf/pURd1wuk39mSXKZtHREfBPxoNvDojqjUueNJ5OcehjJGwm5OwtY8HL5zPv2ZGrREfjn2Dhar2P3wqqkqdzMnz4akfom9q3xCRZ/eqfKyfo2yNG53QsDDyYEHqZOmqsOTesazDFrE2p27bPQk9SWaeqbIyj7t6aoMCen/bdARfrpJKbeStvwlDZiZiJkyAoVVLeAqUAzw5pnaZMETXXlZW5eQOj2iznrl5iNN6pCOrTwr6ndoaYy7jzo+qRYtQ9tlnGLJLGjD8uk8aLGxJaY+0gtWIsuWjSuNEtDEahv1L4NFoYCvbBwgiD4mWcpJ7VMJkEvc9fp8bepybKIiQm78ByoX3IjZy97Yofe2Bo7VSdkDhwnHZpZK0xMu5uygYiwuoruLLW7Qx6BDLv9/t+9Uert3GxIVaq7YMPi1Q7hVeUxr/DZBDIiIr/xKdO1pdRJFH5IJOSkfPV1u/QX5lPmpcyv2AAqI9bh/0Og2KDGo78+YGOTSoTXdtJ8pmofIgyoFZt453cCQWLFjA3BbyTMOmgMqDKOsnuDxMRUWl6RHNpiU1ToXYo2o8Kioq/zWqyKPS7BjTORUL7h6NeXeOCtymkzlQzH4KofWgY2o0E4R6Zsbh3D6Z+Pj+ZYr1RMVJrhwqSxHZ10IDmzn8P7BXG+zk0QQcMIEgPdlEHBN56HE6M2o0Tuy+fgISr7wSuztdhE09b8Kw7iVINMayZah19MDWY6D3KZ9jYPpAVjYkQmIDiTGFB5SOIILKcRpC8PINDW4+XqHPavrZ3ZGVHIVn5+xkrpe6uGvAXez8tLan1blsfgXPf/lw2X4s2V2ECpuyvXnXnTvQYT7PfdLHx8NZS8lGm29+RPszBRcMC9z2RuysFW3Ss9yYnGfPwHn9WrL9cui5HRCbxEuF3EdCA3f1dilkVOv3IarmCGyWFJTpncxJJnp3qrVaRFV7cKDVBPwz6kWF5yalRzUSYwSBZtQ9LID4txk3wThEaNtsigXWvM8vx4bvFESkRaWx5zyvo9RVrE4u+Iif23jXKDFPwGFzS7PfQfv1g1fwZawOHdL28g5WcaYETB8yvV7fg9YaLsrRV96grYLdFw/0uRRo2V+xnNPjxcAZf+PVv3cHumqJIo8YtByO/w39H9rHCV2xAKR/NRofP7MQDrf02ZOYbI4yMEdfQaUT/9iPQiBT+U/p2rUrK92hkqDVq1ezYF1qYHHRRRcFOmtRq2wShej++ubFUKAzdWDatGkT9u3bx9p733nnnSx3hbqZqqioHFv0wn/JVR+vxUXvroBLKKM+WY61VFRUmi+qyKPSLMlKiQ7pTkClKUQ8Ta3TxL7Njc+uHozvrxmCjX9LuQIULtxzbEtMvqtf2HW/PvZ1vDr2VXw3gq9/9MUdA/dldlbOlmd2ig+0fBc5ki0bNAsiz7JhT2PQ1v/BEJeI1Pt56KXbGI1MrxfPDn5MsU7K4wmmTazUOvv9U94PlKEQcalSxklDOzaktOJh1IHHn2QHHpcMbo0DJTbklIR2WAnm7PZno09Kn/A5SUFUC+VTJL5c/uFq/N87kbty2bdsjXifxmKBLjYWGoMRGUP5wM1XFSruVQsB0mIeTyS0ZmlfGSiEBVsXPRe4LcFbBYPbDo/eiu32HJYbE+XzodeRMShwdUVMuRMHW46FR2uGvYWypCnQRcaaCIx/jIsZfafy2368ht/OFqx9cNk5oTNclN1TX7KENuOCWCWGoX/x2MpANo0+SehsJVAuNM1qUdkGehf/DpBwSmHm/HLtf32JRklsSdEcht0bB8QqWyXf+90mTHh5Mbv81/YCyckT1xo/PL8OuctDP0c5NR7lPhlTloZDs3ZB5wfr/EX5WTq9Bl43HzS4xbwdGb07BuWu3LcfGHoLv1zBO7qpNA9IgCERZ/z48ax1+ogRI/Duu+8G7ne73di1axdsQpe4+uTFUEkQhS6PHj0a3bt3x4wZM5jII1+viorKsUN01hIr95XiUCn//p5kh1oqKirNEFXkUTluyOqbAmucES0ohRnAp1cNYuerft6L5T9KQbMj/q8jRk3phPg0Zbeebkk8K6V/en/mlvluhBZT7tdB26MKXYbxcoxRFykzDGKTLbh51jjFuuQ6S5eeUgtmwr8kNdC5x22IBh4phNuk3I5R6aNDXtslXaRWzB0SOrDBnci5d4cXq+pDsKjTHNt6HkvGdeElCz+uPxw2CyEYEnhcvroFiGBn0O4CqV16MOYeUhD0ulTJsbVs2DnosGA+v2JNgt4sdFUrk1w9ItUBJ0/4zBx3QSEcu3bB75YcRVG2Mph8Pthk+0C6vxR66iCm0cJuMTGxJTauLYYdOBeTt90Od4wFei/PtSqN6Q6nMZaVbpV7WoTvmiUPWSYnT3poOVMwSZYkFNu5K6demGJR400AvuWCksEo/W2VF9ioZzwM6elo89eCwO1lwtdy6kLp/aCu0juW5dVdtuj1oNNCqVW8RVsBmy9O2cWKOv6tO8Ryn9j66HtltAJnvgpc+Cny91Vg6y/FzK3z7ZnfYssVW3BZV97VZtYE3vL8tbGvhX36KI0PPo+PCVE6g445edhmBYmPvTa/hR5tgsRLEtoGCN27io++5bJK00E5K19++SWqqqpY4PGHH36I6OhoRTcm+o2ifBYRyoqh24JPYg4QhfOuXLmSlYLZ7XZs376dhe2eLJk7Kir/NdTxUk5pDf/PUTN5VFRU/mtUkUfluIEEivSsOIyKi8G7U/ujWwYvg/LIBtyXTB8cUch4a/xbeGn0S4g1xqJ7cnem1vi1Guwu2422PbgTwBJTd7CxJdYYEF/atVE+l3uPhXXFCqA3ISNKWb7y6MD/hZRS6bQ6Fvb7+emfhzgNxOVikhqWx6MCZCZwEWLW4r34dm3dXWQMOkO9XCYurxfGOtwgIqm33470/z2GvRddj8eGXB24fd7gc6AXSyrMcdCZ+H78+KvvhwhSZTa+TbGWUCeP3+PBntGjsf+cycj/H9+3iHydHlF+P/YZDNhv4I+zuh3wWfj+a/BaMbnDZEQHCraA7dePg9XKRZ7dGadhe9crcThjJL4ofgu/fOPDzBsWMAEjQLDrKX9L3e+HNbVBIs+G+UfwcdGHOOLqyq7rBSdPgKdSsOfHX/DR0ztgvfAceMcPZQHrJYM7wqvlg93E0u1wOX3IXlNQt8hTfiDQZU8Ueey+OOS4YrG7ILw7h8q2GAOmAVGSq+jnyT+jaxLf7tv63YZHhzyKYRm821fXRH57MFExu5jjiIReCk6nTJ4BbRIQJdMVW+f+haTSbeyzJ675ZA1e+muX1Mr9lnVAW6ncVUVFRUWl6aHyaTkeH/+hVjUeFRWV/xpV5FE5rsjoEA97oQPjO3OHRtHBKoVbJT41jNtA5iAQA5gNWgOeHvE0u0wDzvb9Ulm3Hkt03aU6Yy7tgjNv7Y2MjvEwRCuFF7+Hmg9Jo7HDu8uYM+fP8/7E2svWKsq9aB1yhrQYgt4pvRWD0CGTs1g79+CSscZwMopEJr0OVwzlpXALdkYOPxZJsaRgfu78QEvr2pw8LRMs6JKuLIcLh8ZoRMLFF+PA6DPh0+pQZopGQVRSIGeHodVCZ+T7TXLVYbR78A/FOg6V2ZEcbYTVGCryeIK69ohc/IsGWj/wbWwMzm6ZAZ9bg6G7t8Gq4SJOy4rO0HuMyDlyduAxe/QlMEdJIpffYoI2i7/GQzlcyNi1UvbeNOJIlrrMVbkkseTbXd9iyaElEZcXXXqV3vSwYeIfFHyCuX/xbYz2zkblZT1gdcXCMeU+eIUSqvjyPfC4JeGsVpHHVqK4atWWw4YknPNbLGY+tRIb95Wi7QOzFcvsLapR5OmEw6K34MLOFwZEaDrvmNAR03pMUyx32cF+rESLhF69UQuPy4ez+2TAaRLK4Sg4et8vLC3M7+Kzxn/vKMQbCwQ3I5XRJXegN6rW7VFRUVFROXpmXSZltbnFkmBV5VFRUfmPUUUeleMKsWzq74+3w+f14dsZa7D9nyOBrI6GZM6c1f4sVk4hugrqyukQMVn0aNOdz9ZrZTP+hN5Mrc+lweTPL2/ArFsXYfPnpfDWaOB2erHw852B9USi9Agvw4iK406EqTOGYvQloe1wG8LUp4biZOSxs7rj6hHtMHdbAab/uq3WZeNNPINp4vcTsa04/LIVdjdyS20w6rUw1HOfIdxCIOMVpzyCH25/CbsKqgK3UdcmUeSZks/LjmyyTkvUdSlGVvsvx+dQ5rI42nExpOs+DYr10iyjvYQ/3pTP23OP3XsJ5j6Wg30F0gFqdlk2PF7peczxHhi4YS6AR2jzHZZ2oaWIwcQYlCLPkyufxM3zb67zcTpw8UnhlKPX65c2MNfVB46SXeh36BTs+tWFyphWgN8Hk1NZAldrKCa1apdBTp5KTzyy3Dp0cuvw/Gtrwj5s/YGyenVyk/Pj2T/irv488Nup46VfcgxGHXu/zXodiqMS4YUPI5fexwQebXQ0K8+rT6i4ioqKisqxQd4YxCMGL6sij4qKyn+MKvKoHFektOYz9jS7vWO5sv35GTf1avj6rCkotNXt8IhE7JiRiuvJmTHYslgZeEqz8vs3FeOj+5Zi9sxNgdspXLUuxHbt1D0p2MFQXyiwesDpbU+6PB75AdjFg1qzyx8vz8H8HbxkJxzybKSLZl8Et0/ZNYu457tNTDDamV+Fcrvkehn34qJa3RyioOPW6TGkczq8Pj/u/2EzEwY6r5yA8d6X2P0V+6IwRrsB5RVSWZTT7YMpwufvq1HmshiKlEJDlJ2LIhpB78lNkoLDg4lxxMEt0y1rPPEocPO24yI7V+YzsTLA3UKZEHG+0GGrDiePzWODx+fBqjwenFwbae24iLPbOY6dy51ywSyvmobHS9ajRwH/XpYndYHBXYOuLyvDz8XwZgXOKiBnKcvkCRZ5dOCuKKKNR/ocKBfsrok8Z+mS91fhglkrFI+tTw4UYTTrsCdZaq9NMKegSQe3w4vSeYfRzq0DbZlBCGzWmM3w2e249av19XoOFRUVFZWmRz5n4BEyGdXgZRUVlf8aVeRROa6wxhoRm2xGYgsrFn0hDS5bdIhDZiPKmZItySixK8szGoLeqiyByttVibWzuVMiHId3lyMpk7dCpvbIkYhL4VkyYmedo4FK0QafnYWTmQ6p0Xj2PB4KfPUna6UMlSBaRPMAbpEaV2hXLrmQc0G/VoHL+4prWEv1SPy2SRIl2yVFBQKhF+0qghNG7Pe3wL7UDJji3PjY+AJi5twWWN7pCS/yOHbuhH2TJBwSumpJeEqq8OOjV70Yup3CfPlR5xtnhQocxdbDfLt2dITbL+3TVZ5kFLqlsGiRDfNypStWIYMmvg0Qzcsoa4MysYhqVzWeXf2s4r6aCifW/rEf2ftycWBPAbxeX8C5k+PoB1/hHpZXQ2LvZU8OCbv+lkek2yui2yGlpQ5xHaXPqV3v5PCuvZ9uAD4+A9i3kF+/9PuAyEOMc/BSzkpR7QEwvEMyrh8d+btlq6xfFzGXw4szu5yuuC2xRRQTeSjI3ZtrQ5ZHB49Gg6UZPZF47bWso5ht5UomOAZ3YVNRUVFR+XeQu3akTB5V5VFRUflvUUUeleMOg1mPQ7uUboSqEp4z0lCiDFGocdfdXjsSDf0jJ1eCJcbIhJfaHjvp+h4scDkpU9m9S6XxUK7JuX15G+zsWrph/XzOz4HL8rIieTeNFnFmrHhwHG6f0BE3jmkfuO/5Obuw7UgFiqqUJVQbcstYiZdI98w4dn5ev0yFeLM3NoOqixgxe3+HM2cVNh4sx1erc8OWhu2ffC4KnnpKcVvxmJTAZauwGf32+vG1hbvgqmUNsUS+7/08SqxH0KqsEyq9SqErHIqSLZ0BGHk3cNmPdT5u6ffZOPCBLvDexh1qiXO33Bm4f8nXu7Hq1/346/k9+P3Fbdgw9wCcNslNZf/tf8zJozdoA6WMwVCnMDlHCq2KkPP+k9qG37gDy/n5ijf5eXovlLQ9E1d7lKVkelYsBVw/Kou5xCj3SZ7JcPe3kuhmr6pb5CnL578/KbHKNvDhHEde+DFj0BUYXNQZ7uRU2NauRY9yLrj9fddoRJvUHB4VleONRYsWseMB6pJWX6gL2x133HFMt0ulfsgP5TyBTJ7/bntUVFRUCFXkUTnuIJdLYU5loOQpq08KJl4ltaluCFa9FXZPaBbGsYLKzMiZIG+RHo7kljG45uVRSG0TFIii0mgotPipyT3Y5UW7IpfotY9vj1/O+YVdnr5iuuK+yz9cjdmb89C1RSxaxFkCg/07J0hulzNeX4qHf1J2mTr3LUFAEKDBOLmLyMmzbK/UacptioeryoBfyoagpsCIb77+GJNnLmP3VeVFLjMTSb7pJuSPtOL74Xz/MghajMUFHLBzhw4ZUn4d/BL2dp7JrmvhxkC7A5WmYnjdabWuf8KVvCOU0xbkGBn/GA/7rUMY2vT3QdgLuYqVV5OHHjsmIq26La5a9RwKC8qUnbtIHNuQjcpiBzq04YMfu13HnDxUxqg3KgWQdqZV0GmU4poIlTrStk97fkSg/CuEYNeWwYK4qZ9hQP/uisBmyuX58LQeePD0roGSrFO6puLXW4az6z+sl8o1nfJw7QjYKrgQ1La3skW7zW0L6SRGZWMi+UMnsPMXFr2OVokWtj+pqKhI5Ofn49Zbb0VWVhZrK9+qVSucddZZmD9/fmCZd999lwkmsbGxDRZaamP69Ono06dPvZYdNmwY8vLyEBfHxf+mZtmyZdDr9fXeHpXGZ/KowcsqKirNBVXkUTnu6D2uZeByq66JOO2Gniy/ojGY9eajEnnkTo9zHuLlQCJTHhkUsrzT7maB0dpG5uuoHB1RJj1GdkzGW4v21hpY2zaOuz1W569mLdUPVfGB+9IDW6CL3q4I2I23GpmjJylK6swWqZPXw6d3xXuXD2AHhXrhwHDlPmldfZz8cZ3m5iJ3YTJaVvHw5xGHN+HVbx+CY9fuiNvcZfs2pNx2K1zVhTiYytf9v718wKL3AJcs5q/Xq9PgiDYXnTWrcWXKVZiaciOeKC5BS5OUCSOKC92sf0EvdOMiOg9pgbY9k5C7rUSRN1NRZGOlVcFUlzlYCZbo0pHz9qa3offx98zoM+O7/20ICB4iroPcmRIVzZ/LXuGA1+ODLoyrKdO4FR6/5GRJjeLlcanJ9sC2U7lnRLorHUDkUNLrtHjqQinrK6EFL7Pb8dVeVBbz9S7+chfevnkRsqIsmDJAKgsj/vig9qBvInc7Lxc94lbmP+0o3RHi5InySwOH6tZSmdgQ078nVKuoHA/k5OSgf//+WLBgAV544QVs2bIFc+bMwdixY3HzzZI7z2azYdKkSXjooYf+k+10u90wGo1IT08/JiU+JFpdfvnlGD9+fJOvWwUhgo5XKNdSRR4VFZX/GnWkqXLckdExARc/Nhhn3NwLoy4KzQtpCHGmOFQ4K+D0hncA1MXKvJWYNfR2dkrJjMUpV3fHiAs74qa3xyK5ZejMenWpE/n7Kmtv4axyTLl5bAfYXF68uSA74jJajfTT2P/z/jjtx9Mw/8BCRGW9CmurT1HlU4Z+E5cM5uHO8vBFQi4mdc+MxcRu3C0jL98SyR6hzGXpuOIgC2FuX8Ezc9xH+Hk4NFotE6SeNbth9XJxwPJPjMLRI6er04UoXRmidSVo6QWuHcJLjqxmNy7532Bc8MAAjL35FFx/5UHF43QGHarLnNi1irdSp8yYzx9diWXfCy28ZXzy4HJ8fD93IpXmSU4Zk9bEnDwGQeSpi76T+bbZ9WmsXCucSGrU1EAD/rqHxXyMyT1/wVltP8T/DVS2o2ds+R6wBXXCCj4o1/LMLOrY135kCwy9tBMGn9UucLfoZtomdPf79OHlmDq0DSDLWnaVuerM1aoo5ALN3jLl/rCzdCeK3ZEdZ57U/2/vPsCbLLs+gP+796C00FLaAm3ZpewhshGKyLIoSxTlQ0VwoYDIxhfBDSLDV1/BgaAi4AbZQ7bsKSCzQIGWlkJ3m+86d8hsWtoSaEn/v+sKTZ48SZ7eJM2dk3OfE4TgWR+r81UvnSzwMYjKmhdeeEEFTXbs2IHY2FhUr14dderUwYgRI7Bt2zb9frLk6Y033kDz5pZrfBXHggULMHnyZOzbt08dg5xkm5Dzc+fORffu3eHh4YGpU6fmWa6VkJCAfv36ITg4GO7u7oiKisKiRYuKdSzPP/88+vfvjxYtymZ3zXvB+K0j69Z7P2M8RFTSuICf7kt+lTzU6U5F+EYgMzcT8TfjEept+JBeWPKhWsfRzhGRTQpe7qJjKROB7o1GYdoC3R+vPYERnfJvS/9h2w8xYr22vbV4Zb2hEHJkjU0ABuVZDmYsOTULPu5OquW6ToMQQ3FwCTSZ82jbFlhgKEZ844IrRqcuQtwVbZ2cnCTT5UzG3tnxDr458o32sV1Muzo55WhwKFQ6Mxm2hRtnjji6wr3Ty8DydUjPdoaXn6s6Ae2B8PZomxmHa/HaIMSDj0Xi5O7LWLPgCGo0C0TGTe39HFh3Hq37GIKu5kuvjNuWezp6Iu5G/gErc27BYVLaGjlwRUpiBgJCtQHU2lUuwPH6CUQOeRW7VvYA9mr3r+ayDU6n4xFavQtw07AcTslKA34cDFRpBQz6VdZbSV92INWsALu9IYsmZoB2aVbihZsmy8+M6wVpcjWoGegFd7OGWm8tO4hxsXVVVpAlWZm5aqnWrI3/otutbSuq/w+nd+yHT1oA+mGc2tZ7dGO1TK1ywnW8vHgvDsYlo0fXh3DUzQt+KcUvHk9UVFmZOUi6lDdIfbf5BrrDyWyZpiWJiYkqa0cCKBJIyXM/vsXL/C2sPn364ODBg+oYVq9erbYZL8WSpVzTp0/HjBkz1DKqf//91+T26enpKgtp9OjRahnZb7/9hoEDByI8PBxNm+bNEM7P/Pnz1X1/8803+I9Z7TayHgfjwstsoU5EpQSDPFSm6Tr9JKQnFCvIk55tWMriYPSh8Lb4/l9ipIDx5O51MPHnQ1i84yz63mqvbu6hsIew5rE16PBD3jT3iIp5i/42r+Zncnnj8SvoFl0JJy5rizx/M7gZ3Ar4gPLHy61UkCDtu8U406ev4YoVuQiGNiCSc+2afrMm51aQyN4eDr6++gCPSKjjD/ygzbQRQc4BSNKkwt5VAi+OiLlxE8G6DmN9FgL+1VXGSoUwL9R+sFKeY6vTSluwWniWM/zuX4/dikeGR+fZPyk+FT+++3eeD2gXT2oDP8lpKVJgpkBfN5yAgbunqPPXM5ORixwcSktA6s0M+FSoACScRDun/wCVvICqk7Am5SIiIMEgqOwkOLoBHv7A5cOmd5xxq+j2rYK9DDbHAAAwaUlEQVTF2DYXWDkGCDL7PSxM0qWzn0786et56gLlZuVi2HXTytb7tl7AT+F+iG1kWGaaeDMTRy5eV8+RclduIs0ZOHojBd2gve3p8vvVzywHQ4ahrpZQjxAvFeT5bNMp9GpQGVc9yyN69fdI/Cocfk8+WfCgElmBBHi+f3vnPX/cx99sojrr3c6JEyfUctKaNWuiJLi5ucHT01MFcGQZljnJrHn66af1l82DPJLB8/rrr+svS12hlStX4vvvvy90kOf48eMqQ2nTpk3qOOjuMf4CQzphCt1ybCKiksK//FSmVXDXtnx+8o8nsf/J/SZr4i+nXkbP5T2xpPsSVPLM+8FX3MjKv0uTsdDafqjbJhi/z9UW5M1MY6vjktSvaSje+vUw3lh6AI81DjEpnGj+/HivzXtYd/QSfo//AGnnB6BzkwRsjFuhurJJdzb5MHEu5RzK3Wolbu96DrkZgXhx0R4V5PnjoHZpV2RF0+V77WoEYN2xK/rLUsxZuEdHo9cjU7Hs17F5jifn2GYATyPr8mVcfuddtS34ww/hHdMZ+NJQE8rZ0RCMED7nklAhIgJxGm3np5Bso+dfrUf0Zx8b06RQ4ycFjOeP2oyUxHSTZViyNEm2LZxoWA4hMtKy4Wi0xKqRf2PcPGwIkNg5AEf9tiOm1kPYtG8n/G9Wxk2XZHze9HW4ZLvjgeuzkGOfgx9dXdE2IQtOp1YA20drb5yiHV+XqlnASeCs72E42GUDDh6ARwAQZxRs+n0kcOWo9rwuKLvnVnDsolEr+mBDtyxjxkEdS8vTEuIMY+EV7oWUkynomOaMj1YcU53ddB8Ghny1C3+f0QbsnrrugvOOuYC7pHI5IqppIHArdpxtX3B3rvPXUhHv7oeqOI34t6cxyEP3hARsJeBSEo9bGMb1wqxt4cKFeO655/SX//jjD7Rq1apI99G4ceMCr8/JycHbb7+tgjpxcXHIzMxERkaGWrpVGHJ7CSTJkjFZpkZ3l/H0Yf2xK+r7AePADxFRSWCQh8q08m6GtsWHEw6jjr+hk86qM6uQkpWC1WdW48k6lj883a79+sD/tFCFYssFeqgPuhZbUNM95+xojw8ej1YZEXPWncCLHSLz3bdTaGd8sHQjUi5PR+9GldG5+mVsvLgCzb9trjLBUrNTkZ2bjaWP/AHYZcGjqrZrVcqRt1Ur9XOJqWha1Q8VvU0DL/97qokq3xL+Zt6aMUfe64WjZkEeN/9MpG1bB1y/gKuz5uH6b7+p7faenqoTk7Em5evCt28zJC3+TrshKwsZR44gt6n2eecZ1QfY+N/iDp8qYBw7qpHK1jnyl7YmjUhNyVQnHamb9dvs/fj81Y0mt6+d0QQup7WFg6PaBMOuUSLmbv0WtWr74tfMObC7lerWJTIGv/z7iwrCPm03DQ4aR2RnaeB4erU2KGIkvfw1fNdyFL4+cwqQl1rX94F/12uvPPwzUPMRYIfR7yyRJXHZQnFkz7zfvhekSj1/nN5/FfGnDEvUQuv549BJbWH2zGsZ2HMuCTUCvdQ3vGcSDH83pCpRpp32Q2nviU21z5MvtddlOmijPe7ltfWBzMVfT8fhcqFofmY3HAL8kfzLr/Du3Al2zoWrdURUHLJkqjAZNSUlMjJSfWFz9OitgK4VSS2dZs2amWTdFJWlJWTGpFD0zJkz1XIuqccj+0vtIAn2FEZKSgp27dqFPXv2YPjw4Wpbbm6uCn5JVs+ff/6J9u3bF/m4yTLzpVl3McZIRFRoLAxCZV6zQO2EbdmJZerniWsnMHLDSEzfoa2N8t6u9wrVXcsSb383FeARjs72Jq3UqWR1j66kgj2bjpvVbDEjS2qO31py9f5j0XioykP6665nXlcBHvHLqR9g72IoyGznlIQmU1erbJ0gH9MAj5Bv+iSDKKZOIOYPMv1WXD6gpE/9UH85/OUoOLnnIDXeBVdG9Ufy8uX66xw8PbBr5asmtx/aYDh8uukqvBjkeGhnnwFhrXGn3Ly0gYSzhxP13bikDk92hjaQ5OblhLC6hiCqMZc1hs5QddtWhpevdpnSnH1z1FLGyS0nq8vRAYYlVLl2OXDJkteSHRzDGloMuDZ0C0SYZCnJ0qt6jxvWRa57GzhtGmhCwnEgrejtkqPaGZZd6bQdUAPlgz3VMjX5f5WC8E3bhWCTq7Zmz4PpToiduwV1J65EzfErcPWG4cOas8YOmXbawKMuEDjlgSnqJIcvRd0bvGz6gXrXOG37dHluLQttjpToJsi5chUXRo7Ete9/KPLvRGRL/Pz80LlzZ8yePRs3b+b9IuZO2qR7eXkhIiJCf5KlWZZIxyzJqCluy/MePXrgiSeeQHR0tGoB/88/+XdWNCd1fKSb2N69e/UnKcBco0YNdd44SEV3jvV3iKg0YpCHyrzPO3+u76i04tQK9Pq5F1acXmGyT1auaXtj4w+WzvbO+KXnL4Uqtqz7MBzRSLtMjEqOBFKkNs+O04lYechQv8bcz/u0mSrGLdLndZyXZ7/5h76AR9U5+sv2zobgUZCP5Q8C6r4GNkK7mnmfDw1iu6DWgd2o1fcCnONXonwtbUDx6vp4aIyKJmf7eGJYwhb95Zcrtoa3bxjcGuYNhES3G4VXwx5R9Ybwf2uAV83q1RSB1KeRQI7o+FQt9c3+n58fwi+ztMue+k9sXqiWwB6+LnB2MIztiw1eRM+Invik/SeIrR6r366xz0VQijY45O8aB4Q9eOuX6q/vdLfm5hnttrRbtYs63yo2euWIIXPH2PKhlg+qgAw9KS7dsLO29o+Oo5M9fCu44dqlVNVtTJZ1SSHuxTM6q+vDsw2P7ZoLRGc46LtwOWu0mTzGXdh6RfbS/h/dIjXDjPl7ausirT16Gdn2jrCLNC0gnnboEFJ37873dyCydRLgkSCL1LD58ccfVY2aI0eO4OOPPzbpNHXp0iUV+JA6PkIXHJHizXeiSpUqOHXqlLqvq1evquVWRclEWrVqFbZs2aKOWZaHxcfHF/r29vb2qFu3rsmpQoUKcHV1Vedvl0lERcMgDxGVRgzyEEk3Hp9qWHR0EUZuHGnx+qbfNEXUrZonuZpcXLp5SV+Tp3FgY1TxqVKox3luZhsMm9ceNVtouyVRyZIsGjFjdd526jm5Guw9l4Slu+PUcqtVI9ror/N387/tfTv57tCfDy7nXLw6EU5uQJ1H1Vlnb8t1nFIrGLI8+kfE4v9itMvFJMBSfcd2VN+1C5XefUcVEvZ9+Ck803YaXKVmT+XGgE/RlxroyP0/814r9XwOb1hB1Z0yOXRXbWCjWXdD23Ep7GzO2dUBrg6GTKcGFRqo+24T0gaO9o4YGq0NxLjbeSIoJVyd9zn7LZB0BhgTB/T4BLP3an/nln51tXfiequTjVs5oMFAoFJDYLMhM0ov0bTgKYas1f6MKzhA0qJXODz9XPQZes5ujvCp4I6EuBt5svYkIGTnaAeHW//9ktXTKc0ZPW86w9XeHo7QZvKY83T2xBtN31DnE9Lyds96tKHh/66Cn2Fc7RzscTq2N870H1Dg70BkyyT7Zffu3WjXrh1ee+01Fdx46KGHsGbNGtXCXGfevHlo0KABhgwZoi63bt1aXf7555/v6PGlbXtMTIx6/ICAgCK1QB83bhwaNmyospHatm2rijf37Nnzjo6H7h57fpIiolKINXmIbtXm+TfZ7AOfkWxNtr6b1vITyzF1+1SsiF2BG5k31Icxuj+V83DGi+0jMGvtCfzflzsx74lG2HziKnadvoazian6LJ4PHouGn1Emj7ujtiBMiFcIHqj0ACq6V8THez5W22r51VLtwZtHBWPEE+3QY/HrePfYG/jgHwcs7bFULQUc2WQkmgc1L9xBxn4OHFqq6gRX/2stksbGwj7lFDyD05Gd5oArH9UGQrSFwce0nGRyUwdvbTFnn+7d1elu8g5wM6nZ43Cr0HJonfLY/vMpdH2hHipF+mLJO7tUxouOBHSMa2M1CTRduvZcvefQtVpX/Lr1pLqcY5eNT8t5YVjSOcDFUwXP5u3TZlb1DGkP/P27NrijIwGfC/kEbcJaagsxd/0QiOoNuHjnaZ+en37jm+FmcoZ+OaZPBTdkpGbrM3t0whsGYPfKMwjMsUecYy6yb9Xficx2QGSi9nE61q6IF5vnrQM0oNYAfLb/M4tBHt0SQC8XR3iHVoJuRHOSr9/22InKgqCgIHzyySfqlB9pZy4na3NxccGSJUvybLcU7JdAjvF2WW623GhJriXr19+qN1ZId+v3JGbyEFHpxCAPEYBBdQZh5yVDS9j/PvRfPLvqWdQpXweHEgyFWVstboVu4dpaJ/E343E25Sw6hmrrY9D9aUCzMBXkWX3kMh77dCv2nDWt11ClvDtC/Eyr/AZ5BqF7eHc8Vv0x1K9QX20bUk/7TbAYtmYYMnMz4Oqahgz3TWpbjiYHPZb3UOdfXvsytg/YXrgDlIDDs+uBczvhUD4I5edtAb7qCfy7Dk7uuUiz0y6Z+jbsMZSkavUDcGrfVVWAuHlPQ82dCmHeKttHJ6S2nwryNOoSpu9A4uPig0CPQNQtfysTx4iDvQPCvMNQbdApfPrXF7jk9S/snLwwLDRGXS+Fr3XK6TKs/I06ylw+kv9BH/kF8KsGNBls2CYFmuvfPgtGsnfkpOPibjjv6GQIEvmHeMHe0Q4PpjniO69MtA4tj7TjpoGYh6pXQN26lrP7JEvweNJxpGWnwU3awt/i6qh9jDB/d/jGdoJbVBTOv/QSUlatUtvtCtmJh4iIio9BHiIqjRjkIZIP7R6GD1jSFrtRRW0L5YerPmwS5EnPSYeLg3aZxpJ/lqiMjWq+hg+0dP8J9HHF2tfaoP0HG/IEeIQs1TIny4imPjg13/uUJX0bz29En4Q+Fq93sFQfpiCVGmhPOr2/AN6tCoS2QFq8tkW4a72+KEmuHk4qW+d2mnarpgoyh9Y2Lcq8MnZlgbeLadYGlcPLY/ymN+AAX7wZ4I+pGg0S0w21M+pV6ww8/D5QX1unR5FxO7nG8p3evKw9Geu7EMXhdKvelnAwWq4lgSypwZW7PR5jW0Ug4N80nDW7ba0HggpcSvrDPz+obn8TW0xE7+q91farN7Q1PsL8PFQ2lGuNGshJSkbWGe29e7a58+LaRERUMHZLJ6LSiCtJiWTpRLlIfNH5C0MxZQdnbO+/HQNrD0Sr4FZ4qcFL+n1PJZ9SP6W1s27JDt3fqgV44pmWhtoxm0a1g6+7E5Y83wJTeuTNLrmdzXGb1c/4VMvFMo2XJxWLux8w8l9g0G+40W+x2uSlW2pUyrm4OeYJ8OgKn8spPxLIiAqIwsmUs/gn5Yx6/V1Nu4qP/v5IXf/9I9/DzckdaDoEcDYqLNpmtOG8jNVr/wCDV1v5t5Igj+E7k+xM0646rR7XZhZVTwbOHkpEjWamS7N0S9ssMV6+NnnrZIzdPFadbxmhzVp6vo22TpFwDg3Vny/Xt98d/DZERFQYuoxUIqLShEEeIrMPU7rlV+5O7uqD5ZyOc9RSnPHNx6vtf134K8837XT/eyTakE0hy7P2TuiExlX84Gq09KawekX00p+v6lMVix/RBmJ0dVYk0+eOeZRXS7mu52ozOryd748gz50ybqsudbQkw0Xkm1HnaKilhJBmgFdFIKQJECUt1q3Hx6gmUeUa5fJkOYmDG+PUz+ysXAyY3DzPMi9LulTtgqaBTfWXfz75s+r216lOIE5P74qoyj6GrLQJE/Tn3eobxomIiO4OLtciotKIy7WIjOwZuCffpTS62ivGpMvSHWdlUKnQMLQc+jQOQaMqph/Qi2NKyylYdmKZOj+7w2yTbC95zlzPtF5xXLkvRztHk3ottmxBzAL8Z9t/8OPxH/F/f/6f2tanRh/9MsrbZkDpxEwDPAKA4Lyt5otDik3LMrQbSRmwdyj4+5Pg6r7wreiOF+a0Q45R6/T8zGo/S2UsSX2e6TumY3f8bjQLapZnP7eouvDu3g2pO3bC3qUQ40FERHeEiTxEVBoxyENkVmslP5U9K+fZJstFyHa80/v2NWUKK6ZKDFacXoEAtwCT7ZJxk5KZorqpSKbYnUjNSsXqM6vh7eJ9x/d1P71GJz0wCUcSj+BwwmG1rXHFxgXf6KU9sobKdJuHPxDztlWPrcvzUbDLZ8bf/aX6OLL1IhrFhMGvknY5mezr6Hz7TDHJKhzbfKzqsiVBnpm7Z+Lbrt9a3LfSO+8AWVl3+JsQEVFhMJOHiEojLtciKiT5oKXTIbSD+jm4rlFXHiIj77Z+Fxv6bICro7bV9cx2MzGnwxwV5JFOWy+tNdR5KgrpsqRrtys1WrZf2l5msniMVXCroD9fq3ytgneWDloVat71Y5LaOvnVZ5CuYp0G10H5YM9iB+Qka9DTyRMHrh5AVo7lQI7ct52z0RI1IiK6a1iTh4hKIwZ5iIpgSbcl2NRnE2a0m4H9T+7HK41eKelDolJKPmz7uRqWB7UPbY9WlVvpa+esP79eLTdKz04v9H3KB/umC5ti3r55+po0wio1fu4zod7aIsOjm4xWLdbLCqnRI04knchznWQ2SXYXERHdG4zxEFFpxCAPURHU8KsBX1dfdb6sLI8h66rjX0d/fvvF7WiysAnOXjdvqm2ZrpbPnH1zsO/KPmTnZuuze8qaYfWH4esuX+OJ2k+gLBkSNUT9vHDzgknwb+P5jejzax+M3mTUTYyIiO4qB84FiagUYpCHiOge8nHxwYGnDphs67qs621vJ0u05IO8zhO/P6HP5riRdQNlcfmkpWLotq6iR0WVufTn6T/VZXlONPymIYatGaYu77+yv4SPkIjulrZt2+KVV6yfQbx+/Xr1xVVSUhJKowULFsDXV/sFW2nDL/yIqDRikIeIqASMbz7e5LIuKyc/2y5uw4QthhbZxia2mGjVY6PSy97OHg0rNMTvp35Hq8Wt9MEdncT0RGTmZKossbK4jI9I59KlS3jxxRdRrVo1uLi4ICQkBN26dcOaNWvu2TEMGjQIPXv2tNr9LV26FG+99Vah9z99+rQKQuzdu9dqx0AFL9d6oW14SR0KEZEegzxERCXg8RqP48/YP1G7fO1CdWrLr+36m83eRM8I632IoNIv0CNQ/UzKsPyte6NvGql6T5LtIxlgcl66chGVFRLcaNSoEdauXYv33nsPBw4cwIoVK9CuXTsMG2YaGC0NsgrZEc/Pzw9eXl53/Xio8BzMojyjYu5+kX8iotthkIeIqIQEeQZhasup6vzjvzxe4L5bLmyxuN3VQdu9i8oODbTd1cQvPX/BhBYT8GKDF7G8x3KT/cZsHoN6X9VTWT0LjyxERk5GCRwt2aLMzPxP2dmF39c8tpHffkX1wgsvqAyWHTt2IDY2FtWrV0edOnUwYsQIbNu2Tb/f2bNn0aNHD3h6esLb2xuPP/444uPj9ddPmjQJ9evXx9dff40qVarAx8cHffv2RUpKin6fJUuWICoqCm5ubihfvjw6duyImzdvqtt++eWX+Omnn7Rd7+zs1LIoXXbNd999hzZt2sDV1RULFy5EQkIC+vXrh+DgYLi7u6v7XLRoUYHLteSY3n77bTzzzDMq+BMaGor//ve/+uurVq2qfjZo0EA9pty+IH/99Rfq1aunjql58+Y4ePCgyfU//vijGkfJjJLH/uCDD0yul8dYvtz075Ass5LlVkL3u0tGkgTc5PeMjo7G1q1bTW4j+8vvItf36tVLjU1pxeVaRFQaOZb0ARARlWW6zlDXMq5h7+W9FuvMfH7gcyw9vlR/Wbp2fdH5C/T8qSeaBDa5p8dLJS82MhZ7Lu/BjLYz4OnsiSo+VfTXSaBHOrgN/GMg4m7Emdxu2Oph+Lzz5yVwxGRr3n47/+siI4EBAwyX33svbzBHp0oVWdJkuDxjBpBqoUHcpEmFP7bExESVtTN16lR4eHjkuV5X2yU3N1cf4NmwYQOys7NVlk+fPn1UMEbn5MmTKnDx66+/4tq1ayoQNH36dHX/Fy9eVIGZd999VwUjJPizadMmlUH3+uuv48iRI7h+/Trmz5+vz8S5cEFbNP2NN95QQRIJwEhQJT09XWUfjR49WgWcfvvtNwwcOBDh4eFo2rRpvr+v3Ics4XrzzTdVwGno0KEqeFSjRg0V5JLbrl69WgVnnJ2dCxy7kSNHYubMmQgMDFT3J8vb/vnnHzg5OeHvv/9Wv7sEr2SMtmzZooJpEtiSZWlFMXbsWLz//vuIjIxU52UMT5w4AUdHR2zfvh2DBw/GtGnT1FI3+b+cOLH0Lkk2TuSpGcgsKyIqHRjkISIqQU4OTni67tOYf3A+Vp5eqYI8yRnJOJ9yXt+Ja+bumfr9e1fvra/BY17AmcrOcq3PO1kO1oT7autBPFLtEXy6/1N1vnt4d/x88mdsv6St0yN1fYhslQQLJMhSs2bBy2akNo8s4zp16pSq1yO++uorFQzZuXMnmjRpog8GSWaJbpmUBF7ktrogjwSHHn30UYSFaQP2koGjI9k9GRkZKmhiTjJy5HbGJDCkI/WEVq5cie+//77AIM/DDz+sgi1CAkQfffQR1q1bp4I8AQEBarsEYiwdgzkJpjz00EPqvGQhVa5cGcuWLVPBnQ8//BAdOnTA+PHaenKSHXX48GG1HK6oQR75Pbt21TYcmDx5shpz+X+T/zMJMsXExGDUqFH6x5GAkgR7SiP7W5k8jcPKYcnQB0r6cIiIFAZ5iIhK2IhGIxCXEodvjnyDB4MfVEtrNsVtwpZ+W+DhZPgmemj0UHUiup3hDYarNvO6pQTtQ9vjlXWvqOyeEC/tB1qi4nrzzfyvszeLIY4cmf++5itdrNE4SgI8hSFZNhLc0QV4RO3atVWmj1ynC/LIsiTjOjhBQUG4fPmyOi9LjSTwIYGdzp07o1OnTujduzfKlSt328dv3LixyeWcnBy19EqCOnFxccjMzFQBIlmyVBBZXqUjr3cJ5uiOr6hatGihPy9ZRxIokrEQ8lMyn4y1bNkSM2bMUMfu4OBQ6McxPmYZTyHHLEEeeRzJijI/rtIa5DGvyUNEVBrw6zwiolLgmbrPqJ/Pr35eBXjEA4seQPRX0er87A6z8UJ9bZ0JosIwfq6EeoWqn7P3zi7BIyJbIat+8js5OhZ+Xyenwu1bFLIESJ77R48etU62pdlByn1Ldo+QwMaqVavwxx9/qADRrFmzVGBEsoNux3wpmWTESBaLZONIJo50xJLAkQR7int895o8tnmQzVJRaeNj1v2dKqljtha+NRNRacIgDxFRKSBLs6Tblo55x6yq3toCmkTFEVkuEl93+RrDoktfZyEia5IMFAmOzJ49WxVANpeUpO1KV6tWLZw7d06ddGT5kVwvAZvCkiCFZLTIsqM9e/aoujeyxEnIeclyKQwpeiyZMk888YTKEJLW71IP507oavAU9hiMi1JL/SF5fBknIT/lGM2PWZZT6bJ4ZHmYLGHTOX78OFItFVkqgDyO1OXJ77hKa3DH1anwmUxERHcbl2sREZWiblvrHl+nuiAFewar9ujSGUlOlb0ql/Th0X3OUlFvIlskAR4JvEgtmylTpqjlQVI7R7Ju5s6dq5YESRcsWWY1YMAAteRIrpfaNlK02HwpVX4kGCH1eWSZVoUKFdTlK1eu6AMjstRL6uocO3ZM1cWR7lwFZSBJ4WSpPyPLvaQGjnT6KkrAyZwck9QFkqVOUl9HCjwXdAwyVnKcFStWVAWR/f39VfFj8dprr6klbFLkWQovS0esTz75BHPmzNHfvn379mqbLK+SwJJkJZlnGt3OSy+9pP7vpDCzBL1k/ErrUi3h4uiAid1qo2uUdtkZEVFpwEweIqJSxN/NXwV4hJujG9qGtMXopqO5TIuIqJAkC2b37t2qTbcEJ+rWrasKCktARoI8Qv6mSntzCai0bt1aBX3kdtLavLCkC9bGjRtV8WPJaBk3bpzqdtWlSxd1/ZAhQ9TyLQkaSZaLeSaMMbltw4YNVRaStDqX2jq6AEtxSbeqjz/+GJ9++ikqVaqUp6aOOeka9vLLL6suX5cuXcIvv/yizwaSY5N6QYsXL1bjOWHCBBUUMi66LL+71Dhq1aoV+vfvrwos366mkDlp3f7ZZ5+ppWuS0fTnn3+qsSnNnm5ZFRW8XUv6MIiI9Ow0ha1QV4pJe0r5ZiI5OVm94RIREVHpxfft0v//IC29pbZM1apVVQYIUWnE5ykRlRXXizB3si9uGqykoMof02bNmmHHjh2Fup1E/+WbE/NvJuRbANlufJL2iUREREREREREVDhFDvJIGuuIESMwceJElQorqZSSWnq7do2nT59WaZuSwmmJBHWkWJvutGjRoqIeGhERERERERFRmVXkII8UgpM1xk8//bQqBjdv3jy13vaLL77I9zZSfE0K20nnAVnvbImLi4taf6w7yRppIiIiIiIiIiK6C0GezMxM/P3336o4nf4O7O3VZamynx8pzCYV/gcPHpzvPuvXr1f7SIG6oUOHIiEhId99MzIy1Jo04xMRERERERERUVlWpCDP1atXVVaOtFY0JpelCr8lmzdvxv/+9z9VKT8/slTrq6++Ul0P3nnnHWzYsEF1JpDHsmTatGmq6JDuJJX8iYiIiMi6bKA/B9kwPj+JiPJyxF2UkpKCgQMHqgCPv79/vvv17dtXfz4qKgr16tVDeHi4yu7p0KFDnv3HjBmj6gLpSCYPAz1ERERE1uHk5KR+pqamws3NraQPhyjfVQbCwcGhpA+FiOj+DPJIoEb+iMbHx5tsl8tSR8fcyZMnVcHlbt266bfl5uZqH9jREceOHVPBHHNSt0ce68SJExaDPFK/R05EREREZH0y3/P19dU31pD6i9L9lKi0kM8UV65cUc9N+VxBRERaRfqL6OzsjEaNGqllVbo26PIHVi4PHz48z/41a9bEgQMHTLaNGzdOZfjMnDkz3+yb8+fPq5o8QUFBRTk8IiIiIrIS3Rd4t+ugSlRSpDZoaGgoA5BEREaKHPaWZVJPPfUUGjdujKZNm2LGjBm4efOm6rYlnnzySQQHB6u6Oa6urqhbt67J7eVbIaHbfuPGDdV1KzY2Vk0mJPtn1KhRiIiIUK3ZiYiIiOjekw/O8oWbNMbIysoq6cMhsvgFtAR6iIjoDoI8ffr0UamREyZMUMWW69evjxUrVuiLMZ89e7ZIf2wlHXj//v348ssvkZSUhEqVKqFTp0546623uCSLiIiIqITJXI01T4iIiO4PdhobKEsvhZely1ZycjK8vb1L+nCIiIioAHzfLh34/0BERGR779nMbyQiIiIiIiIisgEM8hARERERERER2QCb6DeoW3EmKUxERERUuuner21gxfh9jfMnIiIi25s72USQR1qyi/xashMREVHpfP+W9eVUMjh/IiIisr25k00UXs7NzcWFCxfg5eWl2n1aO2Imk59z586xKOEd4lhaB8fRejiW1sOxtI6yMo4y9ZBJinTUZPvjksP5U+nHcbQejqX1cCytg+NoPWVhLDVFmDvZRCaP/JKVK1e+q48hTxZbfcLcaxxL6+A4Wg/H0no4ltZRFsaRGTwlj/On+wfH0Xo4ltbDsbQOjqP12PpY+hRy7sSvz4iIiIiIiIiIbACDPERERERERERENoBBnttwcXHBxIkT1U+6MxxL6+A4Wg/H0no4ltbBcSRbweeydXAcrYdjaT0cS+vgOFoPx9IGCy8TEREREREREZV1zOQhIiIiIiIiIrIBDPIQEREREREREdkABnmIiIiIiIiIiGwAgzxERERERERERDaAQZ4CzJ49G1WqVIGrqyuaNWuGHTt2lPQhlSqTJk2CnZ2dyalmzZr669PT0zFs2DCUL18enp6eiI2NRXx8vMl9nD17Fl27doW7uzsqVKiAkSNHIjs7G7Zu48aN6NatGypVqqTGbfny5SbXSz30CRMmICgoCG5ubujYsSOOHz9usk9iYiIGDBgAb29v+Pr6YvDgwbhx44bJPvv370erVq3UczgkJATvvvsuytpYDho0KM/zNCYmxmQfjiUwbdo0NGnSBF5eXuq12LNnTxw7dsxkH2u9ptevX4+GDRuqDggRERFYsGABytpYtm3bNs/z8vnnnzfZh2NJ9yvOnwrG+VPxcf5kPZw/WQfnT9bD+ZMVSXctymvx4sUaZ2dnzRdffKE5dOiQZsiQIRpfX19NfHx8SR9aqTFx4kRNnTp1NBcvXtSfrly5or/++eef14SEhGjWrFmj2bVrl6Z58+aaBx54QH99dna2pm7dupqOHTtq9uzZo/n99981/v7+mjFjxmhsnfyuY8eO1SxdulS622mWLVtmcv306dM1Pj4+muXLl2v27dun6d69u6Zq1aqatLQ0/T4xMTGa6OhozbZt2zSbNm3SREREaPr166e/Pjk5WVOxYkXNgAEDNAcPHtQsWrRI4+bmpvn00081ZWksn3rqKTVWxs/TxMREk304lhpN586dNfPnz1e/3969ezUPP/ywJjQ0VHPjxg2rvqb//fdfjbu7u2bEiBGaw4cPa2bNmqVxcHDQrFixQlOWxrJNmzbqfcX4eSnPMx2OJd2vOH+6Pc6fio/zJ+vh/Mk6OH+yHs6frIdBnnw0bdpUM2zYMP3lnJwcTaVKlTTTpk0r0eMqbZMU+cNuSVJSksbJyUnzww8/6LcdOXJEvYls3bpVXZYXnb29vebSpUv6febOnavx9vbWZGRkaMoK8zfW3NxcTWBgoOa9994zGU8XFxf15ijkD5LcbufOnfp9/vjjD42dnZ0mLi5OXZ4zZ46mXLlyJmM5evRoTY0aNTS2Kr9JSo8ePfK9DcfSssuXL6tx2bBhg1Vf06NGjVIfboz16dNHvbGXlbHUTVJefvnlfG/DsaT7FedPt8f5k3Vw/mQ9nD9ZD+dP1sP5U/FxuZYFmZmZ+Pvvv1WKp469vb26vHXr1hI9ttJGUmAlzbNatWoqXVPS44SMX1ZWlskYSipyaGiofgzlZ1RUFCpWrKjfp3Pnzrh+/ToOHTqEsurUqVO4dOmSydj5+PiolHfjsZO02MaNG+v3kf3lebp9+3b9Pq1bt4azs7PJ+Era47Vr11CWSEqmpGvWqFEDQ4cORUJCgv46jqVlycnJ6qefn59VX9Oyj/F96Pax5b+t5mOps3DhQvj7+6Nu3boYM2YMUlNT9ddxLOl+xPlT4XH+ZH2cP1kf509Fx/mT9XD+VHyOd3Bbm3X16lXk5OSYPDmEXD569GiJHVdpI2+asn5R/vBfvHgRkydPVmtuDx48qN5k5Q+6/PE3H0O5TshPS2Osu66s0v3ulsbGeOzkTdeYo6Oj+iNovE/VqlXz3IfuunLlyqEskPXjjz76qBqLkydP4s0330SXLl3UH3IHBweOpQW5ubl45ZVX0LJlS/UGKqz1ms5vH3nzTUtLUzUUbH0sRf/+/REWFqY+5Em9gtGjR6tJ79KlS9X1HEu6H3H+VDicP90dnD9ZF+dPRcf5k/Vw/nRnGOShYpM/9Dr16tVTkxZ50X3//fc28eIg29C3b1/9eYnsy3M1PDxcfTvVoUOHEj220kqKA8qHjc2bN5f0odjsWD777LMmz0spEirPR5lIy/OTiGwX5090P+D8qeg4f7Iezp/uDJdrWSDpXxKhNq96LpcDAwNL7LhKO4lQV69eHSdOnFDjJGnbSUlJ+Y6h/LQ0xrrryird717Q809+Xr582eR6qRovXQ44vgWT1Hh5jcvzVHAsTQ0fPhy//vor1q1bh8qVK+u3W+s1nd8+0pnD1j7c5DeWlsiHPGH8vORY0v2G86fi4fzJOjh/urs4fyoY50/Ww/nTnWOQxwJJqWvUqBHWrFljkjIml1u0aFGix1aaSctEiaJKRFXGz8nJyWQMJZVO1pzrxlB+HjhwwOQNYtWqVeoFVrt2bZRVktYqf3yMx07SB2V9s/HYyZuFrPPVWbt2rXqe6v7YyT7SHlPWARuPr6SH21p6bFGcP39erSmX56ngWGpJ3UV5U122bJn6/c3Tq631mpZ9jO9Dt48t/W293VhasnfvXvXT+HnJsaT7DedPxcP5k3Vw/nR3cf5kGedP1sP5kxXdQdFmm28BKtX4FyxYoKrHP/vss6oFqHGl7rLutdde06xfv15z6tQpzV9//aVa1UmLOqmErmsXKG3v1q5dq9oFtmjRQp3MW9x16tRJtcmTtnUBAQFlogVoSkqKausnJ3kZfvjhh+r8mTNn9C1A5fn2008/afbv36+6G1hqAdqgQQPN9u3bNZs3b9ZERkaatK2Uav7StnLgwIGqFaE8p6VdoC21rbzdWMp1r7/+uupeIM/T1atXaxo2bKjGKj09XX8fHEuNZujQoartrLymjdtSpqam6vexxmta17Zy5MiRqrvE7Nmzba5t5e3G8sSJE5opU6aoMZTnpbzOq1WrpmndurX+PjiWdL/i/On2OH8qPs6frIfzJ+vg/Ml6OH+yHgZ5CjBr1iz1gnR2dlYtQbdt21bSh1SqSKu5oKAgNT7BwcHqsrz4dOQN9YUXXlCtE+WF1KtXL/VCNXb69GlNly5dNG5ubmqCIxOfrKwsja1bt26dekM1P0m7Sl0b0PHjx6s3Rpksd+jQQXPs2DGT+0hISFBvpJ6enqot4NNPP63elI3t27dP8+CDD6r7kP8jmfyUpbGUNwX5Iy9/3KV9ZVhYmGbIkCF5PmxwLLXtUy2d5s+fb/XXtPyf1a9fX/3tkDdn48coC2N59uxZNSHx8/NTz6eIiAg10UhOTja5H44l3a84fyoY50/Fx/mT9XD+ZB2cP1kP50/WYyf/WDMziIiIiIiIiIiI7j3W5CEiIiIiIiIisgEM8hARERERERER2QAGeYiIiIiIiIiIbACDPERERERERERENoBBHiIiIiIiIiIiG8AgDxERERERERGRDWCQh4iIiIiIiIjIBjDIQ0RERERERERkAxjkIaIiadu2LV555RWUJnZ2dli+fHlJHwYRERGRRZw/EdG9YqfRaDT37NGI6L6XmJgIJycneHl5oUqVKmrCcq8mLZMmTVKTkb1795psv3TpEsqVKwcXF5d7chxERERERcH5ExHdK4737JGIyCb4+flZ/T4zMzPh7Oxc7NsHBgZa9XiIiIiIrInzJyK6V7hci4iKlW4sP8+cOYNXX31VpfvKSWfz5s1o1aoV3NzcEBISgpdeegk3b97UXy/fYL311lt48skn4e3tjWeffVZtHz16NKpXrw53d3dUq1YN48ePR1ZWlrpuwYIFmDx5Mvbt26d/PNlmKd34wIEDaN++vXr88uXLq/u/ceOG/vpBgwahZ8+eeP/99xEUFKT2GTZsmP6xiIiIiKyJ8yciulcY5CGiYlm6dCkqV66MKVOm4OLFi+okTp48iZiYGMTGxmL//v347rvv1KRl+PDhJreXCUJ0dDT27NmjJiNCUphl4nH48GHMnDkTn332GT766CN1XZ8+ffDaa6+hTp06+seTbeZkMtS5c2eVfrxz50788MMPWL16dZ7HX7dunTpW+fnll1+qx9VNeoiIiIjuBs6fiOhu43ItIip22rGDg4OaWBin+06bNg0DBgzQrzOPjIzExx9/jDZt2mDu3LlwdXVV2+WbIpl0GBs3bpzJt1Wvv/46Fi9ejFGjRqlvlTw9PeHo6FhgevG3336L9PR0fPXVV/Dw8FDbPvnkE3Tr1g3vvPMOKlasqLbJJEa2y+9Qs2ZNdO3aFWvWrMGQIUOsPFJEREREWpw/EdHdxiAPEVmVpAPLN1ALFy7Ub5P67rm5uTh16hRq1aqltjVu3DjPbeVbK5nQyDdEkh6cnZ2t0pGL4siRI+obLt0ERbRs2VI9/rFjx/STFPlGSyYoOpJ2LGnKRERERPca509EZC0M8hCRVcnk4rnnnlPryM2FhobqzxtPIsTWrVvVN1iyblzShX18fNS3UB988MFdOU7pcGFM1qXLRIaIiIjoXuP8iYishUEeIio26eiQk5Njsq1hw4ZqTXhERESR7mvLli0ICwvD2LFj9dukMOHtHs+cfNMla8NlbbluIvTXX3/B3t4eNWrUKNIxEREREVkb509EdDex8DIRFZus+964cSPi4uJw9epVfYcHmXBIob69e/fi+PHj+Omnn/IU7jMna8/Pnj2rvn2SdGNJO162bFmex5OUZblfebyMjIw89yPfZsm69aeeegoHDx5UhQFffPFFDBw4UJ9qTERERFRSOH8ioruJQR4iKjbpDHH69GmEh4cjICBAbatXrx42bNiAf/75R7UBbdCgASZMmIBKlSoVeF/du3dX7URlMlO/fn010dF1jdCRjhPSeaJdu3bq8RYtWpTnfqR96MqVK5GYmIgmTZqgd+/e6NChgyoSSERERFTSOH8iorvJTiMVvYiIiIiIiIiI6L7GTB4iIiIiIiIiIhvAIA8RERERERERkQ1gkIeIiIiIiIiIyAYwyENEREREREREZAMY5CEiIiIiIiIisgEM8hARERERERER2QAGeYiIiIiIiIiIbACDPERERERERERENoBBHiIiIiIiIiIiG8AgDxERERERERGRDWCQh4iIiIiIiIgI97//BzNLKLnq96V+AAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "traj = plot_trajectories(stats_test[alg], lb, \"iteration\", alpha=1)" + "from utils.plotting import plot_sep, groupby_time\n", + "from matplotlib import pyplot as plt\n", + "\n", + "experiments = {\n", + " (\"StochasticGhost\", \"abs_diff_pr\", 0.05),\n", + " (\"SSLALM\", \"abs_diff_pr\", 0.05)\n", + "}\n", + "n_constraints = 1\n", + "\n", + "n_rows = len(experiments)\n", + "n_cols = n_constraints+1\n", + "\n", + "\n", + "f, ax = plt.subplots(n_rows,n_cols)\n", + "for n, (alg_name, c, cb) in enumerate(experiments):\n", + "\n", + " alg = f\"{alg_name}__{c}__{cb}\"\n", + " data = data_train[alg]\n", + " if 'time_r' not in data.columns:\n", + " _ = groupby_time(\n", + " data = data,\n", + " round_step=0.01)\n", + " print(alg)\n", + " \n", + "\n", + " cb = 0.05\n", + " if isinstance(ax, plt.Axes):\n", + " ax = [ax]\n", + " for i in range(n_rows):\n", + " ax = f.axes[i\n", + " +n_rows*n\n", + " ]\n", + " if i == 0:\n", + " plot_sep(data, plot_col='f_full', x_col='time_r', idx_col='trial', ax=ax)\n", + " else:\n", + " plot_sep(data, plot_col=f'c_full{i-1}_corrected', x_col='time_r', idx_col='trial', ax=ax)\n", + " f.set_figwidth(30)\n", + " f.set_figheight(15)\n", + " for i in range(n_rows):\n", + " ax = f.axes[i\n", + " +n_rows*n\n", + " ]\n", + " if i == 0:\n", + " ax.set_ylim(0.4,0.72)\n", + " ax.patch.set_linewidth(2)\n", + " ax.patch.set_edgecolor('black')\n", + " if n == 0:\n", + " ax.set_title('Loss')\n", + " else:\n", + " ax.hlines((0, cb), 0, ax.get_xbound()[1], ls='--', color='black')\n", + " ax.set_ylim((-0.01, 0.01*30))" ] } ], "metadata": { "kernelspec": { - "display_name": "humancompatible", + "display_name": "hc-dev", "language": "python", "name": "python3" }, diff --git a/experiments/calculate_iteration_values.py b/experiments/calculate_iteration_values.py new file mode 100644 index 0000000..e439a1e --- /dev/null +++ b/experiments/calculate_iteration_values.py @@ -0,0 +1,310 @@ +from copy import deepcopy +import importlib +from itertools import combinations +import os +import timeit +import warnings +import hydra +import numpy as np +import pandas as pd +import torch +from omegaconf import DictConfig, OmegaConf +from torch import nn, tensor +from torch.utils.data import TensorDataset, DataLoader, SubsetRandomSampler +from humancompatible.train.fairness.constraints.constraint_fns import fairret_stat_equality +from utils.load_folktables import prepare_folktables_multattr +from utils.network import SimpleNet +from humancompatible.train.algorithms.utils import net_grads_to_tensor, net_params_to_tensor +from itertools import combinations +from humancompatible.train.fairness.constraints import FairnessConstraint + + + +# @hydra.main(version_base=None, config_path="conf", config_name="experiment") +def run(cfg: DictConfig) -> None: + warnings.filterwarnings("ignore", category=FutureWarning) + + print(OmegaConf.to_yaml(cfg)) + N_RUNS = cfg.n_runs + FT_STATE = cfg.data.state + FT_TASK = cfg.data.task + DOWNLOAD_DATA = cfg.data.download + DATA_PATH = cfg.data.path + + if cfg.device == "cpu": + device = "cpu" + elif cfg.alg == "ghost": + device = "cpu" + print("CUDA not supported for Stochastic Ghost") + elif torch.cuda.is_available(): + device = "cuda" + print("CUDA found") + else: + device = "cpu" + print("CUDA not found") + + print(f"{device = }") + torch.set_default_device(device) + + DTYPE = torch.float32 + + ## load data ## + + torch.set_default_dtype(DTYPE) + DATASET_NAME = FT_TASK + "_" + FT_STATE + + ( + X_train, + y_train, + group_ind_train, + group_onehot_train, + sep_group_ind_train, + X_test, + y_test, + group_ind_test, + sep_group_ind_test, + group_onehot_test, + _ + ) = prepare_folktables_multattr( + FT_TASK, + state=FT_STATE.upper(), + random_state=42, + onehot=False, + download=DOWNLOAD_DATA, + path=DATA_PATH, + sens_cols=cfg.data.sens_attr, + binarize=cfg.data.binarize, + stratify=False, + ) + print('Groups:') + print(len(group_ind_train)) + X_train_tensor = tensor(X_train, dtype=DTYPE) + y_train_tensor = tensor(y_train, dtype=DTYPE) + train_ds = TensorDataset(X_train_tensor, y_train_tensor) + + print(f"Train data loaded: {(FT_TASK, FT_STATE)}") + print(f"Data shape: {X_train_tensor.shape}") + + PATH = + + ## prepare to save results ## + + if "save_name" in cfg["alg"].keys(): + alg_save_name = cfg.alg.save_name + else: + alg_save_name = cfg.alg.import_name + + saved_models_path = os.path.abspath( + os.path.join(os.path.dirname(__file__), "utils", "saved_models") + ) + directory = os.path.join( + saved_models_path, DATASET_NAME, CONSTRAINT, f"{BOUND:.0E}" + ) + + model_name = os.path.join(directory, f"{alg_save_name}_{BOUND}") + + if not os.path.exists(directory): + os.makedirs(directory) + + ## run experiments ## + + histories = pd.read_csv(cfg.checkpoint_df_path) + + #################################################### + ### CALCULATE STATS ON EVERY ALGORITHM ITERATION ### + #################################################### + + loss_fn = nn.BCEWithLogitsLoss() + constraint_fn_module = importlib.import_module("humancompatible.train.fairness.constraints") + constraint_fn = getattr(constraint_fn_module, cfg.constraint.import_name) + + print("----") + print("") + + exp_iter_indices = [ + histories.loc[exp_idx, :] + .index.get_level_values("iteration")[histories.loc[exp_idx]["w"].notna()] + .to_list() + for exp_idx in histories.index.get_level_values("trial").unique() + ] + exp_maxiter = np.argmax([ind[-1] for ind in exp_iter_indices]) + longest_exp_indices = exp_iter_indices[exp_maxiter] + longest_exp_indices.extend( + [ei[-1] for ei in exp_iter_indices if ei[-1] not in longest_exp_indices] + ) + longest_exp_indices = list(set(longest_exp_indices)) + longest_exp_indices.sort() + + index = pd.MultiIndex.from_product( + [longest_exp_indices, range(N_RUNS)], + names=("iteration", "trial"), + ) + full_eval_train = pd.DataFrame( + index=index, columns=["G", "f", "fg", "c", "cg"] + ).sort_index() + full_eval_test = pd.DataFrame( + index=index, columns=["G", "f", "fg", "c", "cg"] + ).sort_index() + + loss_fn = nn.BCEWithLogitsLoss() + X_test_tensor = tensor(X_test, dtype=DTYPE).to(device) + y_test_tensor = tensor(y_test, dtype=DTYPE).to(device) + X_train_tensor = X_train_tensor.to(device=device) + y_train_tensor = y_train_tensor.to(device=device) + + save_train = True + save_test = True + histories.dropna(subset=["w"], inplace=True) + + for exp_idx in range(N_RUNS): + for alg_iteration in histories.loc[exp_idx, :].index: + print(f"{exp_idx} | {alg_iteration}", end="\r") + + w = histories["w"].loc[exp_idx, alg_iteration] + net.load_state_dict(w) + net = net.to(device) + if cfg.alg.import_name.lower() == "sslalm": + x_t = net_params_to_tensor(net, flatten=True, copy=True) + lambdas = histories["dual_ms"].loc[exp_idx, alg_iteration] + z = histories["z"].loc[exp_idx, alg_iteration] + params = { + "x_t": x_t, + "lambdas": lambdas, + "z": z, + "rho": cfg.alg.params.rho, + "mu": cfg.alg.params.mu, + } + + if save_train: + if cfg.constraint.import_name == 'abs_max_dev_from_overall_tpr': + data_c = [[ + (X_train_tensor[g_idx], y_train_tensor[g_idx]) for g_idx in group_ind_train + ]] + elif cfg.constraint.import_name in ['abs_diff_pr', 'abs_diff_tpr']: + data_c = [ + ( + (X_train_tensor[g_idx], y_train_tensor[g_idx]), + (X_train_tensor, y_train_tensor) + ) + for g_idx in group_ind_train + ] + else: + data_c = [ + ( + (X_train_tensor[g_idx_1], y_train_tensor[g_idx_1]), + (X_train_tensor[g_idx_2], y_train_tensor[g_idx_2]), + ) + for g_idx_1, g_idx_2 in combinations(group_ind_train, 2) + ] + calculate_iteration_values( + alg=cfg.alg.import_name, + full_eval=full_eval_train, + index_to_save=[alg_iteration, exp_idx], + c=c, + loss_fn=loss_fn, + data_f=[X_train_tensor, y_train_tensor], + data_c=data_c, + net=net, + device=device, + add_negative=cfg.constraint.add_negative, + **params, + ) + + + if save_test: + if cfg.constraint.import_name == 'abs_max_dev_from_overall_tpr': + data_c = [[ + (X_test_tensor[g_idx], y_test_tensor[g_idx]) for g_idx in group_ind_test + ]] + elif cfg.constraint.import_name in ['abs_diff_tpr', 'abs_diff_pr']: + data_c = [ + ( + (X_test_tensor[g_idx], y_test_tensor[g_idx]), + (X_test_tensor, y_test_tensor) + ) + for g_idx in group_ind_test + ] + else: + data_c = [ + ( + (X_test_tensor[g_idx_1], y_test_tensor[g_idx_1]), + (X_test_tensor[g_idx_2], y_test_tensor[g_idx_2]), + ) + for g_idx_1, g_idx_2 in combinations(group_ind_test, 2) + ] + calculate_iteration_values( + alg=cfg.alg.import_name, + full_eval=full_eval_test, + index_to_save=[alg_iteration, exp_idx], + c=c, + loss_fn=loss_fn, + data_f=[X_test_tensor, y_test_tensor], + data_c=data_c, + net=net, + device=device, + add_negative=cfg.constraint.add_negative, + **params, + ) + + net.zero_grad() + + fname = f"AFTER_{alg_save_name}_{DATASET_NAME}_{BOUND}" + fext = ".csv" + if save_train: + fname_train = fname + "_train" + fext + save_path = os.path.join(utils_path, fname_train) + print(f"Saving to: {save_path}") + full_eval_train.to_pickle(save_path) + + if save_test: + fname_test = fname + "_test" + fext + save_path = os.path.join(utils_path, fname_test) + print(f"Saving to: {save_path}") + full_eval_test.to_pickle(save_path) + + +# helper function to calculate relevant values on full dataset (e.g. constraint gradient, AL function, etc) +# used to calculate those values at different points during algorithms run +def calculate_iteration_values( + alg, + full_eval, + index_to_save, + c, + loss_fn, + data_f, + data_c, + net, + device, + add_negative, + **params, +): + c_val_vec, c_grads_mat = [], [] + + for i, c_i in enumerate(c): + cv = c_i.eval(net, data_c[i // 2 if add_negative else i]) + c_val_vec.append(cv) + cv.backward() + cg = net_grads_to_tensor(net, flatten=True, device=device) + net.zero_grad() + c_grads_mat.append(cg) + c_val_vec = torch.tensor(c_val_vec) + c_grads_mat = torch.stack(c_grads_mat) + full_eval.loc[*index_to_save]["c"] = [c_val_vec.detach().cpu().numpy()] + full_eval.loc[*index_to_save]["cg"] = [c_grads_mat.detach().cpu().numpy()] + + X_tensor, y_tensor = data_f + outs = net(X_tensor) + if y_tensor.ndim < outs.ndim: + y_tensor = y_tensor.unsqueeze(1) + loss = loss_fn(outs, y_tensor) + loss.backward() + fg = net_grads_to_tensor(net, flatten=True, device=device) + net.zero_grad() + + full_eval.loc[*index_to_save]["f"] = loss.detach().cpu().numpy() + full_eval.loc[*index_to_save]["fg"] = [fg.detach().cpu().numpy()] + + + +if __name__ == "__main__": + run() \ No newline at end of file diff --git a/experiments/conf/alg/alm.yaml b/experiments/conf/alg/alm.yaml index cd6db8c..c38f97b 100644 --- a/experiments/conf/alg/alm.yaml +++ b/experiments/conf/alg/alm.yaml @@ -1,13 +1,16 @@ # name of the algorithm class to import form src.algorithms import_name: SSLALM -save_name: ALM +save_name: SSLALM params: - batch_size: 8 + batch_size: 16 epochs: null - lambda_bound: 10 + lambda_bound: 50 mu: 0. rho: 1. tau: 0.01 - eta: 5e-2 - beta: 1. \ No newline at end of file + tau_mult: 1 + eta: 0.05 + beta: 1. + use_unbiased_penalty_grad: True + save_state_interval: 50 \ No newline at end of file diff --git a/experiments/conf/alg/fairret.yaml b/experiments/conf/alg/fairret.yaml index e88bece..3c35e8f 100644 --- a/experiments/conf/alg/fairret.yaml +++ b/experiments/conf/alg/fairret.yaml @@ -7,4 +7,6 @@ params: lr: 0.05 epochs: 10 pmult: 0.5 - batch_size: 8 \ No newline at end of file + obj_batch_size: 16 + c_batch_size: 8 + save_state_interval: 1000 \ No newline at end of file diff --git a/experiments/conf/alg/ghost.yaml b/experiments/conf/alg/ghost.yaml index 9c345ae..52a1d03 100644 --- a/experiments/conf/alg/ghost.yaml +++ b/experiments/conf/alg/ghost.yaml @@ -3,10 +3,11 @@ import_name: StochasticGhost params: alpha: 0.4 - beta: 10.0 + beta: 1.0 gamma0: 0.02 rho: 0.8 lamb: 0.5 zeta: 0.001 tau: 1 - stepsize_rule: dimin \ No newline at end of file + stepsize_rule: dimin + save_state_interval: 1 \ No newline at end of file diff --git a/experiments/conf/alg/sgd.yaml b/experiments/conf/alg/sgd.yaml index 43ac6e9..9314b18 100644 --- a/experiments/conf/alg/sgd.yaml +++ b/experiments/conf/alg/sgd.yaml @@ -4,4 +4,5 @@ import_name: SGD params: lr: 0.005 batch_size: 8 - epochs: 10 \ No newline at end of file + epochs: null + save_state_interval: 1000 \ No newline at end of file diff --git a/experiments/conf/alg/ssg-torch.yaml b/experiments/conf/alg/ssg-torch.yaml new file mode 100644 index 0000000..7ae9300 --- /dev/null +++ b/experiments/conf/alg/ssg-torch.yaml @@ -0,0 +1,14 @@ +# name of the algorithm class to import form src.algorithms +import_name: TorchSSG +save_name: TorchSSG + +params: + batch_size: 32 + epochs: null + save_iter: null + ctol: 0.1 + f_stepsize_rule: const + f_stepsize: 0.05 + c_stepsize_rule: dimin + c_stepsize: 0.5 + save_state_interval: 500 \ No newline at end of file diff --git a/experiments/conf/alg/ssg.yaml b/experiments/conf/alg/ssg.yaml index cd8bb5e..1eb7b7c 100644 --- a/experiments/conf/alg/ssg.yaml +++ b/experiments/conf/alg/ssg.yaml @@ -2,11 +2,13 @@ import_name: SSG params: - batch_size: 16 + batch_size: 32 epochs: null save_iter: null + ctol_rule: const ctol: 0.0001 f_stepsize_rule: const - f_stepsize: 0.2 - c_stepsize_rule: const - c_stepsize: 0.02 \ No newline at end of file + f_stepsize: 0.05 + c_stepsize_rule: dimin + c_stepsize: 0.5 + save_state_interval: 50 \ No newline at end of file diff --git a/experiments/conf/alg/sslalm-torch.yaml b/experiments/conf/alg/sslalm-torch.yaml new file mode 100644 index 0000000..69c733e --- /dev/null +++ b/experiments/conf/alg/sslalm-torch.yaml @@ -0,0 +1,16 @@ +# name of the algorithm class to import form src.algorithms +import_name: TorchSSLALM +save_name: TorchSSLALM + +params: + batch_size: 16 + epochs: null + lambda_bound: 50 + mu: 2. + rho: 1. + tau: 0.01 + tau_mult: 1 + eta: 0.05 + beta: 0.5 + use_unbiased_penalty_grad: True + save_state_interval: 500 \ No newline at end of file diff --git a/experiments/conf/alg/sslalm.yaml b/experiments/conf/alg/sslalm.yaml index a3884d9..26cb9c2 100644 --- a/experiments/conf/alg/sslalm.yaml +++ b/experiments/conf/alg/sslalm.yaml @@ -1,12 +1,16 @@ # name of the algorithm class to import form src.algorithms import_name: SSLALM +save_name: SSLALM params: - batch_size: 8 + batch_size: 16 epochs: null - lambda_bound: 10 + lambda_bound: 50 mu: 2. rho: 1. tau: 0.01 - eta: 5e-2 - beta: 0.5 \ No newline at end of file + tau_mult: 1 + eta: 0.05 + beta: 0.5 + use_unbiased_penalty_grad: True + save_state_interval: 10 \ No newline at end of file diff --git a/experiments/conf/constraint/abs_diff_pr.yaml b/experiments/conf/constraint/abs_diff_pr.yaml new file mode 100644 index 0000000..7c1d678 --- /dev/null +++ b/experiments/conf/constraint/abs_diff_pr.yaml @@ -0,0 +1,6 @@ +import_name: abs_diff_pr + +c_batch_size: 16 +bound: 0.05 +add_negative: False +type: "one_vs_each" \ No newline at end of file diff --git a/experiments/conf/constraint/abs_diff_pr_mean.yaml b/experiments/conf/constraint/abs_diff_pr_mean.yaml new file mode 100644 index 0000000..b2bf86b --- /dev/null +++ b/experiments/conf/constraint/abs_diff_pr_mean.yaml @@ -0,0 +1,6 @@ +import_name: abs_diff_pr + +c_batch_size: 16 +bound: 0.05 +add_negative: False +type: "one_vs_mean" \ No newline at end of file diff --git a/experiments/conf/constraint/abs_eq_loss.yaml b/experiments/conf/constraint/abs_eq_loss.yaml new file mode 100644 index 0000000..838d87b --- /dev/null +++ b/experiments/conf/constraint/abs_eq_loss.yaml @@ -0,0 +1,5 @@ +import_name: abs_loss_equality + +c_batch_size: 128 +bound: 0.05 +add_negative: False \ No newline at end of file diff --git a/experiments/conf/constraint/abs_eq_loss_torch.yaml b/experiments/conf/constraint/abs_eq_loss_torch.yaml new file mode 100644 index 0000000..97ea1dc --- /dev/null +++ b/experiments/conf/constraint/abs_eq_loss_torch.yaml @@ -0,0 +1,5 @@ +import_name: torch.loss_equality + +c_batch_size: 128 +bound: 0.01 +add_negative: False \ No newline at end of file diff --git a/experiments/conf/constraint/diff_loss.yaml b/experiments/conf/constraint/diff_loss.yaml new file mode 100644 index 0000000..f687764 --- /dev/null +++ b/experiments/conf/constraint/diff_loss.yaml @@ -0,0 +1,6 @@ +import_name: loss_equality + +c_batch_size: 16 +bound: 0.005 +add_negative: True +type: "one_vs_each" \ No newline at end of file diff --git a/experiments/conf/constraint/diff_loss_mean.yaml b/experiments/conf/constraint/diff_loss_mean.yaml new file mode 100644 index 0000000..244c5cb --- /dev/null +++ b/experiments/conf/constraint/diff_loss_mean.yaml @@ -0,0 +1,6 @@ +import_name: loss_equality + +c_batch_size: 16 +bound: 0.005 +add_negative: True +type: "one_vs_mean" \ No newline at end of file diff --git a/experiments/conf/constraint/eq_loss.yaml b/experiments/conf/constraint/eq_loss.yaml deleted file mode 100644 index be83500..0000000 --- a/experiments/conf/constraint/eq_loss.yaml +++ /dev/null @@ -1,4 +0,0 @@ -import_name: one_sided_loss_constr - -c_batch_size: 8 -bound: 0.005 diff --git a/experiments/conf/data/folktables.yaml b/experiments/conf/data/folktables.yaml index 1f16b21..3e8b630 100644 --- a/experiments/conf/data/folktables.yaml +++ b/experiments/conf/data/folktables.yaml @@ -1,4 +1,6 @@ task: income state: OK download: True -path: .\utils\raw_data\ \ No newline at end of file +path: ./utils/raw_data/ +sens_attr: ['RAC1P'] +binarize: [1] \ No newline at end of file diff --git a/experiments/conf/debug.yaml b/experiments/conf/debug.yaml new file mode 100644 index 0000000..748fd89 --- /dev/null +++ b/experiments/conf/debug.yaml @@ -0,0 +1,30 @@ +data: + task: income + state: VA + download: True + path: ./utils/raw_data/ + sens_attr: ['MAR'] + binarize: [null] +alg: + import_name: TorchSSG + save_name: TorchSSG + params: + batch_size: 32 + epochs: null + save_iter: null + ctol: 0.1 + f_stepsize_rule: const + f_stepsize: 0.05 + c_stepsize_rule: dimin + c_stepsize: 0.5 + save_state_interval: 500 +constraint: + import_name: abs_diff_pr + c_batch_size: 240 + bound: 0.05 + add_negative: False + +run_maxtime: 90 +n_runs: 1 +run_maxiter: null +device: cpu \ No newline at end of file diff --git a/experiments/conf/experiment-workshop.yaml b/experiments/conf/experiment-workshop.yaml new file mode 100644 index 0000000..3c48b2a --- /dev/null +++ b/experiments/conf/experiment-workshop.yaml @@ -0,0 +1,16 @@ +defaults: + - _self_ + # REMOVE + - alg: sslalm-torch + - constraint: pr_dev_mean_separate + - data: folktables_MAR + +alg: ??? +constraint: ??? +data: ??? +model: + +n_runs: 5 +run_maxtime: 60 +run_maxiter: null +device: cpu \ No newline at end of file diff --git a/experiments/conf/experiment.yaml b/experiments/conf/experiment.yaml index 56aad2e..cb65c20 100644 --- a/experiments/conf/experiment.yaml +++ b/experiments/conf/experiment.yaml @@ -14,3 +14,4 @@ n_runs: 10 run_maxtime: 30 run_maxiter: null device: cpu +save_checkpoint_df: True \ No newline at end of file diff --git a/experiments/conf/experiment_noc.yaml b/experiments/conf/experiment_noc.yaml new file mode 100644 index 0000000..469a452 --- /dev/null +++ b/experiments/conf/experiment_noc.yaml @@ -0,0 +1,13 @@ +defaults: + - _self_ + - alg: sslalm + - data: folktables + +alg: ??? +data: ??? +model: + +n_runs: 10 +run_maxtime: 30 +run_maxiter: null +device: cpu diff --git a/experiments/model_plots.ipynb b/experiments/model_plots.ipynb index 2f012cd..9271926 100644 --- a/experiments/model_plots.ipynb +++ b/experiments/model_plots.ipynb @@ -13,19 +13,12 @@ "\n", "import torch\n", "from torch import tensor\n", - "from utils.load_folktables import prepare_folktables\n", - "from src.constraints.constraint_fns import *\n", + "from utils.load_folktables import prepare_folktables_multattr\n", + "from humancompatible.train.fairness.constraints.constraint_fns import *\n", "from fairret.statistic import *\n", "from utils.network import SimpleNet" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, { "cell_type": "markdown", "metadata": {}, @@ -49,7 +42,6 @@ "outputs": [], "source": [ "TASK = \"income\"\n", - "# TASK = 'employment'\n", "STATE = \"OK\"" ] }, @@ -57,30 +49,67 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\andre\\miniconda3\\envs\\humancompatible\\Lib\\site-packages\\pandas\\core\\computation\\expressions.py:73: RuntimeWarning: invalid value encountered in greater\n", - " return op(a, b)\n" - ] - } - ], + "outputs": [], "source": [ + "sens_cols=[\n", + " \"MAR\",\n", + " # \"SEX\",\n", + " # 'RAC1P',\n", + " ]\n", + "\n", "(\n", " X_train,\n", " y_train,\n", - " [w_idx_train, nw_idx_train],\n", + " group_ind_train,\n", + " group_onehot_train,\n", + " sep_group_ind_train,\n", " X_test,\n", " y_test,\n", - " [w_idx_test, nw_idx_test],\n", - ") = prepare_folktables(\n", - " TASK, state=STATE, random_state=42, make_unbalanced=False, onehot=False, download=True\n", - ")\n", - "\n", - "sensitive_value_0 = \"white\"\n", - "sensitive_value_1 = \"non-white\"" + " group_ind_test,\n", + " group_onehot_test,\n", + " sep_group_ind_test,\n", + " group_order\n", + ") = prepare_folktables_multattr(\n", + " TASK,\n", + " state=STATE.upper(),\n", + " random_state=42,\n", + " onehot=False,\n", + " download=True,\n", + " sens_cols=sens_cols,\n", + " binarize=[None],\n", + " stratify=False,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "group_onehot_train.sum(axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "group_codes = {\n", + " \"MAR\": {0: \"OTHER\", 1: \"Mar\", 2: \"Wid\", 3: \"Div\", 4: \"Sep\", 5:\"Nev\"},\n", + " \"SEX\": {0: \"OTHER\", 1: \"M\", 2: \"F\"},\n", + " \"RAC1P\": {0: \"OTHER\", 1: \"W\", 2: \"B\", 3: \"AI\", 4: \"AN\", 5: \"AIAN\", 6: \"A\", 7: \"PA\", 8: \"OT\", 9: \"TW\"}\n", + "}\n", + "groups_sep = [[int(g) for g in gr.split('_')] for gr in group_order]\n", + "group_names = [\n", + " [\n", + " group_codes[sens_cols[i]][c]\n", + " for i, c in enumerate(gc)\n", + " ]\n", + " for gc in groups_sep]\n", + "group_names = ['_'.join(g) for g in group_names]\n", + "group_names" ] }, { @@ -102,54 +131,16 @@ "y_train_tensor = tensor(y_train, dtype=torch.float, device=device)\n", "\n", "X_test_tensor = tensor(X_test, dtype=torch.float, device=device)\n", - "y_test_tensor = tensor(y_test, dtype=torch.float, device=device)\n", - "\n", - "X_train_w = X_train_tensor[w_idx_train]\n", - "y_train_w = y_train_tensor[w_idx_train]\n", - "X_train_nw = X_train_tensor[nw_idx_train]\n", - "y_train_nw = y_train_tensor[nw_idx_train]\n", - "\n", - "X_test_w = X_test_tensor[w_idx_test]\n", - "y_test_w = y_test_tensor[w_idx_test]\n", - "X_test_nw = X_test_tensor[nw_idx_test]\n", - "y_test_nw = y_test_tensor[nw_idx_test]" + "y_test_tensor = tensor(y_test, dtype=torch.float, device=device)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "w, nw, total\n", - "train\n", - "10680 3653 14333\n", - "tensor(0.3081) tensor(0.2078) tensor(0.2825)\n", - "test\n", - "2670 914 3584\n", - "tensor(0.3075) tensor(0.2068) tensor(0.2818)\n" - ] - } - ], + "outputs": [], "source": [ - "print(\"w, nw, total\")\n", - "print(\"train\")\n", - "print(len(y_train_w), len(y_train_nw), len(y_train))\n", - "print(\n", - " sum(y_train_w == 1) / len(y_train_w),\n", - " sum(y_train_nw == 1) / len(y_train_nw),\n", - " sum(y_train_tensor == 1) / len(y_train_tensor),\n", - ")\n", - "print(\"test\")\n", - "print(len(y_test_w), len(y_test_nw), len(y_test))\n", - "print(\n", - " sum(y_test_w == 1) / len(y_test_w),\n", - " sum(y_test_nw == 1) / len(y_test_nw),\n", - " sum(y_test_tensor == 1) / len(y_test_tensor),\n", - ")" + "len(X_test_tensor) " ] }, { @@ -165,55 +156,58 @@ "metadata": {}, "outputs": [], "source": [ - "# directory to load models from\n", + "from itertools import product\n", + "\n", + "constraints = {\n", + " # \"loss_equality\": 0.005,\n", + " # \"unconstrained\": 0.005,\n", + " # \"unconstrained\": 0.03,\n", + " \"abs_diff_pr\": 0.05,\n", + "}\n", + "\n", + "dict_alg_names = {\n", + " \"StochasticGhost\": \"Ghost\",\n", + " \"SSLALM\": \"SSLALM\",\n", + " \"SSG\": \"SSw\",\n", + " # \"SGD\": \"SGD\",\n", + " \"Adam\": \"Adam\",\n", + " \"fairret\": \"SGD-Fairret\",\n", + " \"TorchSSLALM\": \"SSLALM\",\n", + " \"TorchSSG\": \"SSG\"\n", + "}\n", "\n", - "LOSS_BOUND = 0.005\n", "DATASET = TASK + \"_\" + STATE\n", - "constraint = \"eq_loss\"\n", - "DIRECTORY_PATH = (\n", - " \"./utils/saved_models/\"\n", - " + DATASET\n", - " + \"/\"\n", - " + constraint\n", - " + \"/\"\n", - " + f\"{LOSS_BOUND:.0e}\"\n", - " + \"/\"\n", - ")\n", - "FILE_EXT = \".pt\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "StochasticGhost_0.005_trial9.pt\r" - ] - } - ], - "source": [ "loaded_models = []\n", - "directory_path = DIRECTORY_PATH\n", - "file_list = os.listdir(directory_path)\n", - "model_files = [file for file in file_list if file.endswith(FILE_EXT)]\n", - "for model_file in model_files:\n", - " model_name = model_file\n", - " model = SimpleNet(X_test.shape[1], 1, torch.float32).to(device)\n", - " print(model_file, end=\"\\r\")\n", + "\n", + "for constr, cb in constraints.items():\n", + " DIRECTORY_PATH = (\n", + " \"./utils/saved_models/\" + DATASET + \"/\" + constr + \"/\" + ((f\"{cb:.0E}\" + \"/\") if cb is not None else '')\n", + " )\n", + " FILE_EXT = \".pt\"\n", + "\n", + " directory_path = DIRECTORY_PATH\n", + " print(f\"Looking for models in: {directory_path}\")\n", " try:\n", - " model.load_state_dict(\n", - " torch.load(\n", - " directory_path + model_name, weights_only=False, map_location=device\n", - " )\n", - " )\n", - " except:\n", + " file_list = os.listdir(directory_path)\n", + " except FileNotFoundError:\n", + " print(\"Not found\")\n", " continue\n", - " model_file = str.join(\"\", model_file.split(\"_trial\")[:-1])\n", - " loaded_models.append((model_file, model))" + " model_files = [file for file in file_list if file.endswith(FILE_EXT)]\n", + " for model_file in model_files:\n", + " if model_file.split(\"_\")[0] not in dict_alg_names.keys():\n", + " continue\n", + " model_name = model_file\n", + " model = SimpleNet(X_test.shape[1], 1, torch.float32).to(device)\n", + " print(model_file)\n", + " try:\n", + " model.load_state_dict(\n", + " torch.load(\n", + " directory_path + model_name, weights_only=True, map_location=device\n", + " )\n", + " )\n", + " except:\n", + " continue\n", + " loaded_models.append((model_file, model))\n" ] }, { @@ -236,8 +230,7 @@ "metadata": {}, "outputs": [], "source": [ - "from utils.stats import make_model_stats_table\n", - "from utils.stats import aggregate_model_stats_table" + "from utils.stats import make_pairwise_constraint_stats_table, aggregate_model_stats_table, make_groupwise_stats_table" ] }, { @@ -251,440 +244,62 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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AUC_MIndSpInaSfWd|Loss_0 - Loss_1|Algname
meanstdmeanstdmeanstdmeanstdmeanstdmeanstdmeanstd
Algorithm
ALM_0.0050.7998530.0096890.0559310.0122910.0579950.0120940.2471640.0099970.1956770.0131600.0025090.0007250.0213760.016707NaN
SGD_0.0050.8430000.0010480.0962980.0053920.1306090.0072880.2036140.0015910.1116640.0092550.0073860.0002920.0633240.001281NaN
SSLALM_0.0050.8031560.0100000.0546020.0088080.0481020.0172010.2359590.0099200.1935130.0119460.0022760.0007200.0214260.018033NaN
StochasticGhost_0.0050.7681990.0384000.0477920.0198690.0568090.0319540.2836950.0477870.1910890.0241910.0009250.0005820.0245610.014830NaN
fairret_0.0050.8497180.0010170.087340.0132400.1190110.0179740.2029440.0033560.106020.0098140.0065160.0014890.0724280.005458NaN
\n", - "
" - ], - "text/plain": [ - " AUC_M Ind Sp \\\n", - " mean std mean std mean \n", - "Algorithm \n", - "ALM_0.005 0.799853 0.009689 0.055931 0.012291 0.057995 \n", - "SGD_0.005 0.843000 0.001048 0.096298 0.005392 0.130609 \n", - "SSLALM_0.005 0.803156 0.010000 0.054602 0.008808 0.048102 \n", - "StochasticGhost_0.005 0.768199 0.038400 0.047792 0.019869 0.056809 \n", - "fairret_0.005 0.849718 0.001017 0.08734 0.013240 0.119011 \n", - "\n", - " Ina Sf \\\n", - " std mean std mean std \n", - "Algorithm \n", - "ALM_0.005 0.012094 0.247164 0.009997 0.195677 0.013160 \n", - "SGD_0.005 0.007288 0.203614 0.001591 0.111664 0.009255 \n", - "SSLALM_0.005 0.017201 0.235959 0.009920 0.193513 0.011946 \n", - "StochasticGhost_0.005 0.031954 0.283695 0.047787 0.191089 0.024191 \n", - "fairret_0.005 0.017974 0.202944 0.003356 0.10602 0.009814 \n", - "\n", - " Wd |Loss_0 - Loss_1| Algname \n", - " mean std mean std \n", - "Algorithm \n", - "ALM_0.005 0.002509 0.000725 0.021376 0.016707 NaN \n", - "SGD_0.005 0.007386 0.000292 0.063324 0.001281 NaN \n", - "SSLALM_0.005 0.002276 0.000720 0.021426 0.018033 NaN \n", - "StochasticGhost_0.005 0.000925 0.000582 0.024561 0.014830 NaN \n", - "fairret_0.005 0.006516 0.001489 0.072428 0.005458 NaN " - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "res_df_train = make_model_stats_table(X_train_w, y_train_w, X_train_nw, y_train_nw, loaded_models)\n", - "\n", - "train_df = aggregate_model_stats_table(res_df_train, \"mean\")\n", - "train_df_std = aggregate_model_stats_table(res_df_train, [\"mean\", \"std\"])\n", - "train_df_std" + "loaded_models.sort(key=lambda x: x[0])" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": null, "metadata": {}, + "outputs": [], "source": [ - "**Test set**:" + "full_data_stats = make_groupwise_stats_table(\n", + " X_train_tensor,\n", + " y_train_tensor,\n", + " loaded_models\n", + " ).drop('Model',axis=1).groupby('Algorithm').agg('mean')\n", + "\n", + "groupwise_stats = []\n", + "\n", + "for group_ind in group_ind_train:\n", + " groupwise_stats.append(\n", + " make_groupwise_stats_table(\n", + " X_train_tensor[group_ind],\n", + " y_train_tensor[group_ind],\n", + " loaded_models\n", + " ).drop('Model',axis=1).groupby('Algorithm').agg('mean')\n", + " )" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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AUC_MIndSpInaSfWd|Loss_0 - Loss_1|Algname
meanstdmeanstdmeanstdmeanstdmeanstdmeanstdmeanstd
Algorithm
ALM_0.0050.7954300.0081410.0546230.0147880.1146490.0188880.2502790.0070340.2207890.0113920.0031630.0007800.0287640.022415NaN
SGD_0.0050.8346900.0008980.0936610.0041710.1729960.0106140.2189730.0037450.1866640.0144640.0083470.0004100.0455240.002327NaN
SSLALM_0.0050.7985970.0087170.0562450.0116840.1137720.0138140.2448100.0055820.2337480.0174830.0029060.0006840.0189430.010466NaN
StochasticGhost_0.0050.7586560.0417950.0530020.0244740.1069330.0234880.2869700.0453980.2083750.0297230.0012170.0007650.0248040.015357NaN
fairret_0.0050.8358640.0023910.0973060.0127680.1901080.0250920.2157370.0045350.1752510.0151560.0075520.0016480.0446690.007357NaN
\n", - "
" - ], - "text/plain": [ - " AUC_M Ind Sp \\\n", - " mean std mean std mean \n", - "Algorithm \n", - "ALM_0.005 0.795430 0.008141 0.054623 0.014788 0.114649 \n", - "SGD_0.005 0.834690 0.000898 0.093661 0.004171 0.172996 \n", - "SSLALM_0.005 0.798597 0.008717 0.056245 0.011684 0.113772 \n", - "StochasticGhost_0.005 0.758656 0.041795 0.053002 0.024474 0.106933 \n", - "fairret_0.005 0.835864 0.002391 0.097306 0.012768 0.190108 \n", - "\n", - " Ina Sf \\\n", - " std mean std mean std \n", - "Algorithm \n", - "ALM_0.005 0.018888 0.250279 0.007034 0.220789 0.011392 \n", - "SGD_0.005 0.010614 0.218973 0.003745 0.186664 0.014464 \n", - "SSLALM_0.005 0.013814 0.244810 0.005582 0.233748 0.017483 \n", - "StochasticGhost_0.005 0.023488 0.286970 0.045398 0.208375 0.029723 \n", - "fairret_0.005 0.025092 0.215737 0.004535 0.175251 0.015156 \n", - "\n", - " Wd |Loss_0 - Loss_1| Algname \n", - " mean std mean std \n", - "Algorithm \n", - "ALM_0.005 0.003163 0.000780 0.028764 0.022415 NaN \n", - "SGD_0.005 0.008347 0.000410 0.045524 0.002327 NaN \n", - "SSLALM_0.005 0.002906 0.000684 0.018943 0.010466 NaN \n", - "StochasticGhost_0.005 0.001217 0.000765 0.024804 0.015357 NaN \n", - "fairret_0.005 0.007552 0.001648 0.044669 0.007357 NaN " - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "res_df_test = make_model_stats_table(X_test_w, y_test_w, X_test_nw, y_test_nw, loaded_models)\n", + "groupwise_dev = []\n", "\n", - "test_df = aggregate_model_stats_table(res_df_test, \"mean\")\n", - "test_df_std = aggregate_model_stats_table(res_df_test, [\"mean\", \"std\"])\n", - "test_df_std" + "for group_stats in groupwise_stats:\n", + " diff = group_stats - full_data_stats\n", + " diff = diff.add_suffix('_dev')\n", + " diff['Sp'] = abs(diff['tpr_dev']) + abs(diff['fpr_dev'])\n", + " diff['Ind'] = abs(diff['ppv_dev']) + abs(diff['fomr_dev'])\n", + " diff['Sf'] = abs(diff['pr_dev'])\n", + " diff['Ina'] = 1 - group_stats['acc']\n", + " groupwise_dev.append(diff)\n" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": null, "metadata": {}, + "outputs": [], "source": [ - "**Plots:**" + "import pandas as pd\n", + "stats = pd.concat(groupwise_stats, keys=group_names, names=['group'])\n", + "stats" ] }, { @@ -693,47 +308,78 @@ "metadata": {}, "outputs": [], "source": [ - "for model_name in test_df.index:\n", - " alg_name = (\n", - " \"sslalm_aug\"\n", - " if model_name.startswith(\"sslalm_mu0\")\n", - " else model_name.split(\"_\")[0]\n", + "import pandas as pd\n", + "con = pd.concat(groupwise_dev, keys=group_names, names=['group'])\n", + "con" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from itertools import combinations\n", + "import pandas as pd\n", + "\n", + "bin_dfs = []\n", + "\n", + "for group_idx_1, group_idx_2 in list(combinations(group_ind_train, 2)):\n", + " X_train_1, y_train_1 = X_train_tensor[group_idx_1], y_train_tensor[group_idx_1]\n", + " X_train_2, y_train_2 = X_train_tensor[group_idx_2], y_train_tensor[group_idx_2]\n", + " table = make_pairwise_constraint_stats_table(\n", + " X_train_1, y_train_1, X_train_2, y_train_2, loaded_models\n", " )\n", - " os.makedirs(os.path.dirname(f\"./plots/{alg_name}/{DATASET}/\"), exist_ok=True)" + " table.index = table.Algorithm.apply(lambda x: dict_alg_names[x.split(\"_\")[0]])\n", + " table.drop(\"Algorithm\", axis=1, inplace=True)\n", + " bin_dfs.append(table)\n", + " \n", + "df_train = pd.concat(bin_dfs, axis=0, keys=range(len(bin_dfs)), names=[\"constraint\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train_df = aggregate_model_stats_table(\n", + " df_train, \"mean\", agg_cols=[\"constraint\", \"Algorithm\"]\n", + ")\n", + "train_df_std = aggregate_model_stats_table(\n", + " df_train, [\"mean\", \"std\"], agg_cols=[\"constraint\", \"Algorithm\"]\n", + ")\n", + "train_df_std.drop(\"Algname\", axis=1, inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "train_df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Plots:**" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from utils.plotting import spider_line\n", + "cr = con.reset_index()\n", + "cr_alg = cr[cr['Algorithm'] == 'TorchSSLALM_0.05']\n", + "cr_alg.index = cr_alg.group\n", "\n", - "\n", - "f = spider_line(train_df)\n", - "f = spider_line(test_df)" + "f = spider_line(cr_alg, yticks=[0,0.1,0.2,0.35])" ] }, { @@ -749,116 +395,77 @@ "metadata": {}, "outputs": [], "source": [ - "predictions_0 = {}\n", - "predictions_1 = {}\n", + "predictions_by_alg = {alg: {} for alg in set([model_name.split(\"_\")[0] for model_name, _ in loaded_models])}\n", "\n", - "for model_name, model in loaded_models:\n", - " preds_0 = torch.nn.functional.sigmoid(model(X_test_w)).detach().numpy()\n", - " preds_1 = torch.nn.functional.sigmoid(model(X_test_nw)).detach().numpy()\n", - " try:\n", - " predictions_0[model_name].append(preds_0)\n", - " predictions_1[model_name].append(preds_1)\n", - " except:\n", - " predictions_0[model_name] = [preds_0]\n", - " predictions_1[model_name] = [preds_1]\n", "\n", - "for name in np.unique([name for name, _ in loaded_models]):\n", - " predictions_0[name] = np.concatenate(predictions_0[name])\n", - " predictions_1[name] = np.concatenate(predictions_1[name])" + "for i, group in enumerate(group_ind_test):\n", + " for model_name, model in loaded_models:\n", + " alg = model_name.split(\"_\")[0]\n", + "\n", + " preds = torch.nn.functional.sigmoid(model(X_test_tensor[group])).detach().numpy().squeeze()\n", + " try:\n", + " predictions_by_alg[alg][i].append(preds)\n", + " except:\n", + " predictions_by_alg[alg][i] = [preds]\n", + "\n", + "for alg in predictions_by_alg.keys():\n", + " for i in predictions_by_alg[alg].keys():\n", + " predictions_by_alg[alg][i] = np.concatenate(predictions_by_alg[alg][i])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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", 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", 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], + "source": [ + "pred_dfs = {}\n", + "\n", + "for alg, pred_dict in predictions_by_alg.items():\n", + " preds = []\n", + " groups = []\n", + " for group, group_preds in pred_dict.items():\n", + " preds.extend(group_preds)\n", + " groups.extend([group]*len(group_preds))\n", + " \n", + " pred_dfs[alg] = (\n", + " pd.DataFrame({'pred': preds, 'group': groups})\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import seaborn as sns\n", "\n", - "for model_name in np.unique([name for name, _ in loaded_models]):\n", - " # predictions_0 = torch.nn.functional.sigmoid(model(X_test_w)).detach().numpy()\n", - " # predictions_1 = torch.nn.functional.sigmoid(model(X_test_nw)).detach().numpy()\n", + "fig, axs = plt.subplots(nrows=1, ncols=3)\n", "\n", + "for i, (alg, predictions) in enumerate(pred_dfs.items()):\n", + " ax = axs[i]\n", + " predictions.group = predictions.group.apply(lambda x: group_names[x])\n", " sns.kdeplot(\n", - " predictions_0[model_name].squeeze(),\n", - " label=sensitive_value_0,\n", - " color=\"blue\",\n", + " predictions,\n", + " x='pred',\n", + " hue='group',\n", + " palette=sns.color_palette(\"husl\", 5),\n", " fill=True,\n", + " alpha=0.1,\n", " bw_adjust=0.4,\n", - " ) # ,clip=[0,1],common_norm=True)\n", - " sns.kdeplot(\n", - " predictions_1[model_name].squeeze(),\n", - " label=sensitive_value_1,\n", - " color=\"red\",\n", - " fill=True,\n", - " bw_adjust=0.4,\n", - " ) # ,clip=[0,1],common_norm=True)\n", - " plt.xlim(-0.1, 1.1)\n", - " plt.ylim(0, 22)\n", - " plt.xlabel(\"Predictions\", fontsize=20)\n", - " plt.ylabel(\"Density\", fontsize=20)\n", - " # plt.title(model_name, fontsize=10)\n", - " # plt.title(alg)\n", - " # print(alg)\n", - " alg_name = (\n", - " \"sslalm_aug\"\n", - " if model_name.startswith(\"sslalm_mu0\")\n", - " else model_name.split(\"_\")[0]\n", - " )\n", - " plt.savefig(f\"./plots/{alg_name}/{DATASET}/dist\")\n", - " plt.legend()\n", - " plt.show()" + " ax=ax,\n", + " clip=[0,1],\n", + " common_norm=False)\n", + " ax.vlines(0.5,0.,10, ls='--',color='black')\n", + " ax.set_xlim(-0.1, 1.1)\n", + " ax.set_ylim(0, 10)\n", + " ax.set_xlabel(\"Predictions\", fontsize=20)\n", + " ax.set_ylabel(\"Density\", fontsize=20)\n", + " ax.set_title(alg)\n", + "\n", + "fig.set_figwidth(30)\n", + "fig.tight_layout()" ] }, { @@ -883,7 +490,16 @@ "metadata": {}, "outputs": [], "source": [ - "select_by = \"auc\"" + "df_train.index.get_level_values('Algorithm').unique()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "select_by = \"AUC_M\"" ] }, { @@ -893,13 +509,11 @@ "outputs": [], "source": [ "best_models = {}\n", - "algs = res_df_test.Algorithm.unique()\n", + "algs = df_train.index.get_level_values('Algorithm').unique()\n", "for alg in algs:\n", - " alg_df = res_df_test[res_df_test.Algorithm == alg]\n", - " if select_by == \"auc\":\n", - " model = loaded_models[alg_df.AUC_M.idxmax()]\n", - " elif select_by == \"wd\":\n", - " model = loaded_models[alg_df.Wd.idxmin()]\n", + " alg_df = df_train.xs(alg, level=1).reset_index()\n", + " best_model_name = alg_df[['Model', select_by]].groupby('Model').mean()[select_by].idxmax()\n", + " model = [(name, model) for name, model in loaded_models if name == best_model_name][0]\n", " best_models[alg] = model" ] }, @@ -921,68 +535,15 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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XflizZo06ePCg/rtBgwaO25jluA8FQRAEQRCSzi3oJuvXr9fvhQsX9lv9msrY9m0FQRAEIV4hzOXQsRNu7UypYycNEPFKvvwFVbYow4MiRcSVH/bt26ff09LS/G5ToEAB/f7vv/8G3NeRI0f0yxBse0EQBCF1cVUEefapVK/h89WKrW6MP5Yam/sJ1SD7GhXPHLznL5W/wGkx+W4RV1kAgfFPPPFErA9DEARByEJBE3sR5CaWyqdOGgnyqyNxKax2qiKquNqj4gERV34wrsADBw743cYkES1UqFDAfT344IM6V5bdcmVcioIgCELmu6kCiSc+euXIRWrVtvgRNPkyab81ShVSH13XSGXLFs6nLJX3w04q+/blGdYcvH2VUrnyq1hy7Nhx9f3MmWr58t9U757dVYUK5T1uwVgh4soPlSpV0u979+7VLkKnuKuNGzd6beuPPHny6JcgCIKQCVYly1J5Puyocmxa5HcTtEQgCaDnfOdVyc9epdRLLu2r/Hkqf+FSKkyl5iq7du1SY8aMUTt27ND/37P3X1WjVmxcgXZEXPnhzDPP1PmsmDG4ePFi1apVqwzbsBzq168fgyMUBEFIfldbcDeZpYqqf9WSvP6FleASpeoq1W/KKTGFxSqGwmrZsmU6ZdKxY8d0fHT37t11/sl4QMSVH3Lnzq0uvvhirYg/+eSTDOJqw4YNat68efrvbt26xegoBUEQ4lNIZU3sUMbA6nMPv6kOqjwRucTy5cqhS50JfoixmLLnoZw8ebL6+eef9f8rV66shZWZZBYPpLy4ev311/WrUaNG6oMPPvBa98ADD6ixY8eqUaNGqR49eqj27dvr5VizrrvuOnXixAm9XLKzC4KQSmSOkDoVMB2yMDp2UOV/7ZSwOlGusZpzVS+/AkDEU3KwevVqLay4li1atNB1f6OtyOI2SSWufvrpJ3XLLbd4/k8NQBgxYoSaOHGiZzkZ1UuXLu3x13KhSpUqlWF/uPteeuklHYzesWNHfRFLlCihCzdv3bpVuw6HDx+eJb9NEAQhHtx24QqpWqULqTE3nR/Y4BFCzFTQWKF71qocacVUfhFPSU+dOnXU5s2btWEjWMxzrEgqccUsvIULF2ZYvmnTJv0y2HNOBePOO+9UdevW1SJr0aJFevZghQoV9AxAXv4SjAqCIMSzgMoMa5OTdemktShIn8ssv0DCKhjlz1MqrVhcuKwE98ENOGPGDNW8eXOVL18+bbEynqR4JZvFnSdkuQg87bTT1D///BM0jYMgCEKkFqfMjHuqVaqgmpA2SOXY7HIg+T1rlcqdPyFjgQT32bZtmw7P2b17t6pZs6bq3bt3QozfSWW5EgRBSDYyO1Dcy20XRkkTLFbZBrssrMQCJdja/ZIlS9SUKVN0fDNC5rzzzlOJgogrQRCEOB1cDh49EaaQcg4KDzRLzuO2Q1iNaq/UtoyJIjPF2uSEWKAEdTJ0Z8KECeq3337T/69evbrq2rWrTo+UKIi4EgRBiDMrVSjWqQyB4oGCwt1MHOmLWJsEF9m1a5dOf/T333/rGYBt2rRR559PO0+s9iXiShAEIQ5iprSgenOeWr9tZ4YSKCEFikcbFO4vUWQwxNokuEhaWppKT0/XcU09e/ZU5cqVU4mIBLTHAAloF4TUIfSYqYwJMSMmGjediCUhBrMBc+XK5bFOUcqGmfjMDIw3JKBdEAQhIYLPT8ZJ5VdH3BFW4qYTEojNmzfr2YAkAjWl5MgnmeiIuBIEQYhB3igdM3XjeSrvRw5xUmJ5ElLgPlqwYIGaNm2adgPy9znnnBN3mdYjRcSVIAiCCy49M0vPyZHhN2bq2N6McVJieRKSnEOHDqkvv/xSrVlz0lJbq1YtdckllySNsAIRV4IgCBHO2INsKl1NzP2wqp19g/+NQpmtZ6xVYnkSkpiNGzdqNyCxSzly5FDt2rVTDRo0SLjZgMEQcSUIQsoTrqDypEFQlsr7biuVfXsAYRUKYq0SUoB///1Xvf/++zopaJEiRVSvXr0c6/omAyKuBEFISUITVJaqVyqP/zQIRw8qtf2/pJtFqip14+zIBJJYq4QUoFChQqpp06a6lE2nTp1Unjx5VLIi4koQhJQUVj2Hz1dLNvwdWrB5KAk4EVZ5Crh+rIKQyGzYsEEVKFBAFS1aVP+/RYsW+j3Z3IC+iLgSBCHlZvZRVsZXWNkznp8MNg8jKSduvdxpbh22ICQ86enpau7cuWrmzJmqZMmS6rrrrlM5c+ZMelGV6eJq3759atOmTTqF/fHjx1Xz5s0z66sEQRAiLnC8+JG2Kn/uHP+5+vx0/MFSI4hbTxA87N+/X40fP16tW7fOk7cKsZVK5HRbUA0fPlx9/PHH6tdff9WdHdBhIbDskIF18ODB+u+6deuqq666ys1DEQQhhUhPt1SnoXPDKHB8kgYVT1dF03IrLYuwVNkhnsqAsBLLlCAEZf369WrcuHFaYJF1vWPHjjp/VarhmriaNWuW6tOnj9q6dav+f7CqOijZ6dOnq59//lkVLlxYXXrppSp37txuHY4gCClUkw9htX7XgdAKHNvQ1ir+eLedUhsXZtJRC0Lyg2Vq9uzZWgtA8eLF9WxA3lMRV8QVftX27dvr+kB0fliqatasqfbu3esRW07ceOON6qabbtLbfffdd+riiy9243AEQUhR61TlYmlqYv+mDjP7ArjsjuwPLKyIp8LtJwiCXxj7165dq/+uV6+e6tChg7ZcpSpRF24+fPiwqlatmtqyZYv+f9++fdUzzzyjSpcurfr376+GDRumOzbyWvjCdEwC3TiEAQMGqFdeeUWlAlK4WRDCT5cQyDplLFQIq+zZ/QgpduLr+mPZiOZK7fnDf2yVxFMJgl+MQQUwlJAktG7durE+rMQv3Dxy5EgtrDi5N998s3r99ddD/ixTM6tXr65T4P/000/RHoogCEnk9vMXkO5knQpqoWJnwVx/pepKIk9BCMMNOGPGDH3Ptm3bVi8jxIeX4IK4mjBhgn4vWLCgeu6558L+PDWFVq9e7TEnCoKQetBBkx4h2Oy+oNYpfxw9EFxY3RBhAlBBSDGw3nzxxRfqr7/+0v8/66yzdBy14KK4Wr58uX5aJNUCicLChRT4xpwoCELqESyWKkP+qXAFEFarUe1P/V9cf4IQMb///rtOs0DxZSahde7cWYRVZogr4qagbNmyEX3edJSplgNDEISTFitfYeU7uy8iQXXqC5Q6sEupbf+VqBHXnyBEBHHT33//vZo3b57+P3HVPXv29BhIBJfFVVpamrY6oWIjYdu2bfrdpMYXBCF1YqtwBRphZWKpSOjpShZnpzirflNEWAlCBPfrp59+qv744+TEj0aNGqkLL7xQZ1wXnIn6zKBeycK+YsWKiC7YggULdEdauXLlaA9FEIQELpSMsErL42Jn7RtnJSVqBCEiGKOJq6LqSpcuXXSqJSEwUfdkzZo108KK2X5//vmnqlSpUsifJSBu165d+sK1bNky2kMRBCFBg9XJlI7FKoov8U6zYFIs2OOsxB0oCGG5ATGcFCtWTP8fcUXapfz5JedblogrMrCOGDFCd6DktTKzB4NB+gZyWwHi6vLLL4/2UARBSKBg9agD1UNNsyBxVoIQFoiqsWPH6lmBJPom/AdEWGWhuGrdurVq0aKFTnn/zTffaLFFfcFAMVQTJ05Ut9xyi463okMlKI6UDIIgJHfiT0dB5ZTcMxyoARhIWEmKBUEIGTxRX3/9tTpy5IjKmzevnrRmxJWQhRnaAT8sAW7bt2/X/8+TJ49q06aNXr5s2TLdgWKlQkwx04DlwFdXqVJFLV68OKUSj0mGdiHV3H9+g9VDSe4ZDr5pFiTFgiCExPHjx9W3336rfvzxR/3/cuXKacMHY5UQ/vjtiriClStXqh49eqhVq1ad3HGADs18Ze3atbVCTrVgdhFXQqoEqQdN/EnQ+TNl3DkYAtavldmAghAuWKdwA5rZ+02aNFGtWrVSOXJEEQeZpGRZ+RsDswewQL300ku6nuCOHTv8bouV6o477lB33323mBsFIQmD1COKp3JK7hkOYqUShIj44YcftLAipqpr1666LJ0QHa5ZrnzNiwit+fPn68B1FB4iiiLNjRs31qqYzK6piliuhESGLqPn8PlqyYa//YqqkHNV2S1XD22RVAmCEAOIr5o8ebKOoZYxKc4sV147zZlTnXfeefolCELyJf60CyvXZv0JgpAlkAJp6dKluuAy9ytx0lisBPeQ9KqCIEScUmHxI21V0bTckc/6Y6afIAhZBpPMJk2apI4dO6ZDdBo2bBjrQ0pKXEnFAN26ddN5rsKFtA2jR4/WnfP06dOjPRxBENziP7GExarHm/PV+m3/qny21fUrnK6K5jqmsh07fqo4sqnhJwhCXHH06FHt+vv555/1/0n4XaNGjVgfVtIStbiaOXOmFkZ16tSJ6PPUKjL7EAQhTrClSODOHM+yvD7bMGflWeXeTD8C0gVBcB0mmDEbcOfOnXqsJTcl1VWyZ88e60NLWsQtKAhC8Lp8oULSzkiKI8tMP0HIFH777Tf15Zdf6olmBQoU0CmTwilTJySouEpPT9fvkk9DEOIE4+L7j3MPv6kOqjzaDfjRdY0CW5lFJAlCXMGMNuoEVq1aVYfvSPqjFBFXW7du1e8oakEQ4sRq9V/s1G/pFdVuVUgtfuTCU4HrgiDEfWoFZgBC+fLl1bXXXqvKli0r928WElOHK2VwpkyZoi84ZXAEQYgtVnq6Sn/3lNWq19GBqlbp00RYCUICwOQTcky+9tprXom8KWUj928cW65Qv/5gpl+g9XaYArp582a1cOFCdejQIX3RSbUvCEJsM65f+eYMNX7vKasV7sCTOaykYxaEeLdWTZgwQcdYwZIlS1SHDh1ifVgpS1ji6r333nPsZOmYqSlo6gqGS8GCBSNK4yAIgrs5rPKrw55ZgVitGlQsorOtC4IQvxBew2zAPXv26BmApEi64IILYn1YKU3YMVf+quVEWkWHBoAJs0KFChF9XhAEGydOKDVnDr2tUqVLK9WsGbNFAhZcRlit33WApWpM7ie8EoTmSyskVitBiFO4j3/88Uf17bff6qB1yrIwG5A4KyGBxNWoUaMyXFhcgXS+bdq0UX369Am6D7bNmzevKlq0qM6NRb1BQRBcYNw4pW6/nWDGU8vKlVPqtdeU6t49SG1AS9UrclzVPrjh5H9L1VX50wrJzD9BiGNwAZIYFM4880zVpUsXlS+fPdWvkLCFmzFBIphuvfVWNWTIEPeOLImRws1Cpgirnj1PplGwY8TR2LEegXXgyHFVe+BU20aW+ibtKVXrxMpTix7crFQemcErCPEMqYw++eQTVa1aNdW4cWOxMidT4earr75aX1Ap0iwIMXQFYrGyC6tc5g/rpMC653ZltW+jDp5Q2mqVj9gqpdSc+1qp/NmOqPyvrfTOlp5bcuEIQryBLYTagHh9cubMqY0beIxEVCWh5UoIH7FcCa4yc6ZS9tm2/fIrVSHC56Z71iqVVkzcgYIQZzCznkzra9as0cWWO3bsGOtDSkn+zSrLlSAIsTVarZ6+VdWyW6wiFVZYrERYCULcsXHjRj0bkIGdaibFihWL9SEJQRBxJQgJHr9edVNpNdNhvfXiPp2nqueVL6o/Ty+tl1UqmqbG3nS+Tq+QwZUgpWsEIa7AsTRv3jydR5K/ixQponr27KlKMxNYSC1xRQNYsWKF+vnnn9WuXbvUvn37PPUDg/HYY4+5fTiCkPTx61tUM7VRlVNl1WaVTVnKyKPul76glpao6flM5aL51aS7W6rs2UVACUK8c/DgQTV+/Hi1du1a/X/irDp16uQpayOkiLgi6/qLL76o3njjDU+9wHARcSUI4cevp6vs6rZcr6mP1JXq33tLqbJqt16+qkRlz2dq5U9XE0VYCULCcPToUV0ijsD19u3bq/r160vgeqqJK7LCXnjhhdpaFUp8PA3Edzs3G82YMWPUsGHD9KwKGijTVJlRceedd6pcuTzTqELiwIEDOsXEF198oQMJCSokR1eDBg3UDTfcoDp37uzacQtCKJAj9FQqK0uVvmauWlYyt/ordzVVO/sGT+maQyqPqrVnoxpzYQmVv2c36ZgFIc5hXDT3aeHChXVCUCqYSD7IFBVXvXv3VkuXLtV/lypVSnXr1k0XjyRzLA0FixTuwQ0bNqgffvhBbdu2TS9PS0vT+bFIKuoWd9xxh874jtqnBECBAgXU999/r+6//35dd4lMtqEmWdu9e7dq3ry5dnOyH7LJ0+Ax006aNEm/BgwYoL9PELKKU4bhk8Iqd8l/VT51xCOs1h8rpZ588X71xn1pqsMb/1PZckpopSDEO/v379ezAUlrhEEAzLuQgFhRMnXqVCtbtmxW9uzZrUaNGln//POPXn7bbbd5lts5ceKENXbsWKtChQp6Xb169awtW7ZYbjB+/HjMYVaBAgWsJUuWeJbv3LnTqlu3rl539913h7y/AQMG6M+ce+651u7du73WTZo0ycqZM6deP3/+/LCOk3PE58y5EoRwmDEDs69lZct1zKp4/0T9qnrDZMsaWEi/0nL9q9eznSAI8c+6deuswYMHW48//rj1yiuvWMePH4/1IQlRjt/ZoxVnn332mefvkSNHBs3bRNIzTJ1YtkjXj+vusssui7g2oZ1nnnlGvz/wwAPaP21g2iqxYPD666/r/BShgMULsHoxS8MOOUZa/ZdbaP78+VEfuyCECuUCy5U7abUybPvo/FMbZMuuKC3GdoIgxC9M9po5c6b64IMPtOWqePHiOoSFdAtCYhO1uDLConbt2no2Q6jQiD766CMtqubOnavjpKJh8+bN2g0JV1xxRYb1TZs21cUsjxw5or755puQ9hmqu1JyjghZBffL4ePHValrZ6lcRSi2rNTR7YWUdcy7M371Vcd6zYIgxAmEynz44Ydq1qxZ+v/nnHOOuv766/XYKCQ+UYsrEz9Vt25dr+X24FkEjRNYlwgMh48//jiq4zAxX1iYKlc+NUvKjvkus20wOnTooN+ff/55HbRvB4E2Y8YMHWMmQe1CVmAKLlMXcOeRk8LK+jdNbX2vKXecZztuJVudZkEQ4gysVCNGjFB//vmnnmRFnDJFl8OdcCXEL1FHujKbDgj0tkOwumHv3r1+Zztg7cJFuHz58qiOY/369fq9QoUKfrfBcmXfNhi4AxctWqSmTp2qKlasqJo0aeIJaF+yZIn+P65QUuELQmZz8OgJtWTD357/1ypdSH01qKn6oXc2tWOzUur3k8u7iNYXhLiGCVLVq1fXaYtICirej+QjanHFNFHE0+HDJwvBGk4//XTP3+vWrfMrrsznsIBFa2L1FXVODRooIRAK7IsZhg899JB66aWXtMgykI6hbdu2qmzZskH3g+XObr0L9fsFwZCebqlOQ0/FWC1+pK0qmpZbW4hbtsQ3SNBhTA9REIQAmNI1ZowytQHFWpWcRO0WxKIDO3fu9Fpes+apzNBzSMzjBwLaIXfu3Cre4KkC69TQoUPVU089pUUi5lysWeeee6564okndCyXEXb+ePbZZ7V1y7yMBU0QQnEFHjhyXLV5eZZav+uAx2JlhNV/Gyl19GBsD1QQBL/8/vvvavjw4Trjupm8hagSYZW8RC2uzjrrLN1YVq5c6bWcXB1mxgONClHiC3FWfI5BgpmD0VrQ7G5KJ8wxBJvRaOjbt68Okh80aJC2XhHLxVMHFcknTpyo48wQh4MHDw64nwcffFDPUDQvinAKQijWqouHzNUxVkZYVS6Wpib2b+otrN5tp9RgyYcjCPHGiRMn1Hfffac++eQTnYCa8Yl3IfmJWly11D6Jk64/e9kbZjyQsh/hRfJQknGOGzdOK3gECYKFmRGG7lFG4FaqVEm/BxIuZp3ZNtjsQ24KuPzyyzOs54kDXzlMmzYt4L6oBYWgs78EIRRr1Yqtp1zIWKym39XCu4TN0QNKbVx46v/lzztZgFkQhJjCg/R7772nCy8DD+XXXXedyp9f7s9UIOqYq4svvlhbqMjXgcnzlltu8axjlh3CgxI0CKpevXo57qNKlSo6U3s01KtXz5NVnYB1pxmDBM6DPQeWP/766y/P3/7EkAlk951JKAjRxlbZRZWxVuXPncO7hA1Wq1HtT/3/nrVKpRVjqm4WH7UgCHZWr16ts60TU8zDNTPKa9WqFevDEhLJcoWF6uWXX1b33XdfBkVOY6KBIU54Gnd6nXHGGTqtgQk2j5Ry5crpJwPABOsLubSwXNHQTSBhIOyB6gsX2iwDNhYsWKDf/aV+EIRw4H7wFVbGWpWWJ+fJZAtYqszrwC6ltv03y7ZUXRFWghAnrkDKrCGsypQpo2688UYRVilINtK0Z/aX7Nq1S7399ttq+vTpasuWLTpLO9aqSy65RMc1uRXMjpAjXwhCjcRsxkKFNYts6qR7uPvuu71ipLC2EROFmOL47DRq1EjHXBGcjwC0uxNJgHr11VfrAZFEcFdeeWVYs0awemE2FhehALSj3QeOqgZPTXO2VpnYKrsL0M6Dm5XKE90DiiAI7kCIDONNmzZtJNt6khHq+J0l4ioruf3229WQIUN0TBQNmwB0RBPpIpj5RxyVvXAzPvF+/frpWY8kdLPz66+/alGGOCRbO0H65CMhCP+3337T2yCqKF3g5a4JgogrwSk5qD2H1W9PtNPWKg9H9iv1rJ+0H8RZXTtFrFaCECMYEwhUDyXkREhsQh2/o465ijdee+01LaKGDRumAwmPHTumqlatqusN3nnnnWFZyUhwisB65ZVX1OTJk7UVi3xV5PBq166duvbaa1Xv3r0z9fcIqWGxsgurBhVP1xYrba06dvDk+4jm3rFVuW0ueALYRVgJQpZz/Phx7QJkbMBCRXhKiRIlYn1YQhwQF5YrMp4//fTTatSoUSoVEMuV4M9i5UkOyn+c3IDEVt04R8SUIMQYJjJRE9ckwL7gggtU69atxQ2Y5PybCJarVatW6eScn3/+uZ5tmCriShCcytlgsfIkB8UN6CSsbpgtwkoQYgweDap3MBOeMBNifSlnIwgxFVcE+iGqvvjiC8+swXBilgQhUaGtHzp2Qnv6/JWzcUyxgBtQ3H+CEHOY3IQb0NSy7dGjh3ggBPfEFWkIZs+erWf/MeWU2oEEfF900UV+zaIEgT/66KPq66+/ziCqQqnRJwjJ5gZ0LGdDmgVJsSAIcYkRUs2aNdNJtJn9LghRiyvq6pG345dffnFcT7oCytogtAzM1CMFArPqcP/Zw7wIACTYnMy1gpBKgetGWGUoZ2O3WvWTWYCCEGuYyESORGDCFLkNxSAguCauSMRJSRumnDq58lhGdnRm0pGZnaSeZEWntA3lZOyiitQH5JciDYIUrxSSze3nvUypXsPneyUHxQ3IjMB8uXKcSg6q3w96W61yp2Xl4QuCYIPZ5rgBGb/+97//6dnmjHsirATXxBWNjKSZBw8e9IgqBhLSEhDQRy4ogvtg3759qn///jrR5oUXXqij6w0ofoogkzw0Z86kywQhpDD+3H6+eAWuB0oOKlYrQYgZO3fu1LMBeQcMB2eeeWasD0tIEEJ2FlN0mSSbRliRM4r/k/1806ZNav/+/WrKlCnq7LPP1usJ+CMDO9MVGXRI5kmZHGYI4gIUYSWkgtvP1wVIctAxN51/yupLHisnYUViULFaCUJM7uWlS5eqt956SwsrKn5gWBBhJYRDyAqHaaeG5557Tt17773eO8qZUwezN23aVDVo0ECLqDVr1njisBBe1BEUhGTriEmp4M/tZ0e7AANZouzJQWVmoCBkOXhfJk2a5IkppkybKakmCJkirlDyplAzVit/ULwZt5+pu8dgQu09EVZCqrgBvdx+4YCwEmuVIMQMKnEgrLh3KX2GsUDSBAmZKq7IQksjY6ZEMJceNf2A7Skhw2cEIdmTgOL2w+XnKbYsCEJCgaBirGPiFpOuBCHTxZUJSiefVTDs29SoUSPSYxOEuCU93fKfBFQQhIRJsUAIi4kVJofVDTfcIPexkHXi6sSJE7rBhRKIbk+qJkUshWQUVm1enqXW7zrgnARUEIS4Z+vWrWrs2LG6RiApFmrWrKmXy30suEGmT9mThioks7CqXCzNOwmoIAhxHyvJbPZvv/1WGw2wVknAuuA2kg9BEKIQVtPvaqGyZxdhJQiJAKXaKL+2cuVK/X/SK3Tp0kXnahSEmIorEoT+9ddfmbI9RTAFIV6fdomxclVYkUCUjOyCIGQ6ZFnHDUg5NkJX2rZtq8u0idVZyAyyWfaaNAGgMYbTCM1uQ/0M2x0/flylAkwOOO2003SCVammnhgcOHJc1R441V1h5ZuZ/aEtkopBEDIJrFWjR49WhQsXVj179pQSNkKmjt8RuQVD0WN2URWifhOEuIT2S5JQAzFWUbsCqSVoF1ZkZCdxqCAIrmGvgUvAeufOnfV73rx5Y31oQpITcvkb01BDFUpmWxFWQjLkszLZ15kZ6Jt5PWy4J0a1987Mfq3UERQEN6Es2zvvvKNDUwz16tUTYSVkCSFbrihaKQipbrXyqgvo/0Mnawb6gzirbctP/l2qrlJpxURYCYKL9+y8efPU999/r9LT09X06dNV165dY31YQooRsriSbLVCKhK21coplioQ/cRiJQhucfDgQfXll1+q33//Xf+/du3aqkOHDrE+LCEFkVQMghCt1cpuqcIqFaqwIs5KAtgFwRWYlc5sQNyAOXLk0CVszj33XJkNKMQEEVeCEI3VKj1dqbean3Lz2SGWimLM/iCAXTp+QYgaLFWffvqpfiAqWrSong1YqlSpWB+WkMKIuBKEEGoHOlqtsFj5E1ZYpSSWShCyBMJWihUrpkqXLq0uvvhiXc5GEGKJiCtBsMGTLxYre8JQv1Yr0ikYYVWkqlI3zj4lpsQqJQiZXhsQ6xQPPYipfv366ZmA4gYU4gERV4LgY60yrsCAtQN90ykgrPJIfTJByGyYATh79mz9atOmjWrSpIleLiVshHhCxJUgONQNNBYrvwlDj/mkU5DAdEHIdPbv36/GjRvnSQ20Z88er0ShghAviLgSUh6nuoGIKlyBIXXakk5BEDKddevWaWF14MABlStXLh1bdfbZZ8f6sATBERFXQspz6NipWYEh1w20Vx4QYSUImeoGnDlzppozZ47+f4kSJVSvXr10ALsgxCsiroSUx66TQqob6BtvJQhCprFr1y6dcR3q16+v81dhuRKEeEbElZDS+KZc8GuE8k0Uao+3koLLgpBpYKkiy3qePHlUnTp1Yn04ghASIq6ElMU31ooA9ny5coRX0kbirQTBVU6cOKHdgLVq1dJ5q4BM64KQSGSP9QEIQrzEWjmmXAAsVk7CSsrXCIKr/PPPP+r9999Xc+fO1aVsjh8/HutDEoSIEMuVkLKEFGvFRrgBnUraSKJQQXCN1atX66LLhw8f1i5AcljlzClDlJCYZFrLpXjmpk2b1N9//62fPpo3b55ZXyUImRNr5eQORFiJtUoQXHUDTps2TS1YsED/v0yZMro24Omnnx7rQxOE+BBXCKrhw4erjz/+WP366686pgVwtfiad3fs2KEGDx6s/65bt6666qqr3DwUQQg5YajfWCtfdyBuQAleFwTXOHTokB4vNm/erP/fuHFjdeGFF6ocORzuR0FIRXE1a9Ys1adPH13vCYywCjQDZPr06ernn39WhQsXVpdeeqkU2xRiljA0aLJQ3IFSiFkQXIVagObVpUsXVaNGjVgfkiDET0A7wYfkHkFYGVFVs2ZNz0wPf9x44416+71796rvvvvOjUMRhIBQlDnshKHGHSjCShCiBi/GsWPH9N881HTr1k2PBSKshGQianFF8OFll12mjhw5ooVS3759dazVb7/9prp37x7wsz169FDZs588BHzugpCZ0D57DZ8fesLQINZXQRDCg1qA7777rpo8ebJnWVpamvZeCEIyEbW4GjlypNqyZYt+ArnlllvUqFGjglqsDEWLFlXVq1fXf//000/RHooghGy1Is6K2oF+kSzsguAqPHCPGDFCezhWrVqlY3QFIVmJOuZqwoQJ+r1gwYLqueeeC/vzJIpjCu7atWujPRRBCNlqNeam873jrOwZ2EGysAuCK+ACnDp1qlqyZIn+f4UKFbTXgjFDEJKVqMXV8uXL9SBFqoUCBQqE/fkiRYrod+KuBCGzhNXuA0f9W60CZWAHycIuCBHXBSQZ6Pbt2/X/mzZtqlq1auUJBxGEZCVqcbV79279XrZs2Yg+b6wHVD4XhMzKZ2WEVQarFcLqwC7/wkqysAtCRNCnk2aBB+f8+fPrGNyqVavG+rAEITHEFcGI3DzkK4mEbdu2eeKvBCEz0i7YhVWDiqefslo5WazsGdhBsrALQkRgnerYsaOaN2+eFlbiBhRSiajFFcHrZGFfsWJFRIMfWXmxIlSuXDnaQxGEoLUDEVYeq5VTklDJZSUIEbNz507177//eixUTFiqVq1a8DxygpBkRO34btasmWe2359//hnWZ7/44gvtk4eWLVtGeyiCELB2YFqenP47eSxW10pslSBECgmh3377bR1jZY+hFWElpCJRi6tevXp5rFD9+/cP+XOkbxgwYIDn5rv88sujPRRB8Ds70Kt/18WYD3gXZJYkoYIQEUePHtUFl7/66is9M5DagFJwWUh1ohZXrVu3Vi1atNCD2TfffKPFlgly98fEiRPVeeedp+OtEFYU6SQlgyBkVk4rT+1AE2f1TBmlBleL7UEKQoLDLECsVcuWLdN9OTMBKYMWycxxQUgmXHm8+PDDD1WjRo30jTZu3Dg1adIk1aZNG52p3XDnnXdqMUVwo305sVYUexaELMlp5RtnBVKQWRDChlAQMq1TzoZgdXJXVaxYMdaHJQjJI67KlSunizBzc5F5l5I4WLHADGpDhgzxbG/qD9auXVt9/fXXUvpAyLqcVnbMzECZESgIYUOmdYQVAetdu3bVM8cFQTiJa45xCjUvXrxYvfTSS2rYsGFqx44dfrdFTN1xxx3q7rvvlhtScFVY9Rw+Xy3Z8Lf/TOx2EFaSw0oQwrrHzP3Url07PVu8Xr16ErQuCD64GnVIorhHH31UPfjgg1pozZ8/Xweu//PPP1pElSxZUjVu3Fg1adJE5c6d282vFgSdesEurLxyWgmCEJWook9fs2aNnnxEDiuC1uvXrx/rQxOEuCRTpnRw0xGwzisWjBkzRlvPCLJkJgtma4IsifvKlStXRPtkJgxFqhctWqQru2N9Y7/t27dXjz32mOu/QYgu9cLiR9qqomm55YlaEKKEMA9qyJpchr/++qs666yzYn1YghDXJF2BJ9yNvXv3Vj/88IMOskf8/PXXX+r+++/XMxvDzSSPOGN/xBRMmzZNx4kxu7FOnTrqjz/+8IolE+IniN0rWaggCBGB5+Gtt97Swgpr1UUXXaTq1q0b68MShOS3XJEI9JJLLokLNx+5Vl577TU9DXjWrFkekzWJShFWc+fO1W7LwYMHh7zP66+/XlvCEFdMOS5WrJhX7SwsWUJ8ZWP3Sr0gCEJEDysLFy5U3333ne7nTjvtNP1QyeQlQRCyKIloqVKl1I033qhmz56tYskzzzyj3x944AGvWAAE0RtvvKH/fv3113UMWCgwA/KDDz7QVqrRo0d7CSvgSS5Wrk/BPwGD2AVBCAqiaurUqVpY1ahRQ/fvIqwEIYvdgoiVd955RyeQI2/VI488olauXKmyks2bN6sff/xR/33FFVdkWN+0aVNVvnx5deTIEU+aiGAMHTrU42qMNFZLyPp4K9FVghAd55xzjsqbN6/q0KGDDovIly9frA9JEFJLXFGYExOyeRHf9Oyzz2prT4MGDbSbLlBaBrdYunSpfi9SpIjfItAcj33bQJw4cUJbrqB58+Y6Aeqrr76qbr75Zi223n//fbV//35Xf4PgTryVIAjh30PEVxlKlCihbr/9dh23KlZgQYhBzNXq1au1xeijjz5Sn3/+uZeQQsTwuvfee3XG9quvvlrHLmXGU9D69ev1e4UKFfxug+XKvm0g1q1b5xFPCxYsULfccksGMcXv+uyzz3Q8VyCwlvEyUDVeiFG8ld3EJQiCOnjwoI5XZYJOv379PO4/LFeCIMTQLdiwYUNtoeLJh3IIpD0gr5WxZpHF99tvv1VXXnmlznWFyMKnbzK1u8G+ffv0e6CkpKbeVSjixl4f8brrrlPnnnuuFpF8D9XfO3bsqHbu3Km6dOmifv/994D7wpJHQKh5GZEnZHG8Fe1tVPusPiRBiFvwNIwYMUL3Ydw3pJkRBCHOUjEQ4E3WXmoNUmcQaxY+e/JeGaGF9efjjz/WKRJ4QsL6g1iJN+zCr2zZsjq4E7ciAu3ss8/WZXtwffJ7nnvuuYD7IqkqcWnmtXHjxiz4BalDSPFWbHRgl1Lblp/8f6m6Uk9QSFno3+bMmaPee+89/bBZtGhR9b///U/yVwlCvOe5Ils7geUUcSbYHMsW/nswQovaVC+//LK2CkWbO4XCoXDgwAG/2xi3XqFChULeH1xzzTUqT548Xutz5MihZ9AA+a8CwWf5TvtLcIf0dEt1Gjo38EYIq3fbKTW42qll/aZI5LuQktBH8oD7/fff636YvpeUM8z6FgQhgZKIFi9eXPXv31/HLmF+JqM52c3tQstk/42USpUq6fdAViGzzmwbbH/GvVSlShXHbcxyRKIQG2HV5uVZav2uA/7jrYzFauPCU8vKnyc1BYWUhZncxFfhUSBHYbdu3TI8PAqCkGAZ2qtWraoef/xxNWPGDNWjRw/X9kvxUBMr5S9gndpYEEo9LNx/Z555picJqRNmuYnlEmInrCoXS1MT+zf1jrdysljds1apa8VqJaQueArIz4e1ir5QZgMKQoKLK4LBR40apWcOYhkaN26cazc28VsE1sMnn3ySYT3Z2bFc8YRGMHqoCVIDuf0Iygfj7hSyBiyduALtwmr6XS1U9uw+benYwYwWq7RiIqyElIJwCGJEzYxl+lxiY0m3IAhCgoorZgpS9JhEdMwUJGhy5syZOo+UcQmSm+qmm26K+rseeugh/U6A+U8//eRZjjWLVApw22236Rl7hvHjx+sMxAg+XwYMGKBOP/10nXSUGTV2SMFA3ILZTsgaaC+7Dxz1pF7wElZYqo4esL0OnvqgWKyEFISUMsOHD9cpcaZMmRLrwxGElCHqPFf+wFLEbMGxY8eqv//+O8MMPHKodOrUSadnwJKE/z9ayKGF0KGYMmZvBBOpGUgGunfvXtWkSRM1aNAgr88we49cXVR+94VyN+Tu6ty5sxZ/ZGyvWbOmjlcwiUipVRiqJUyIDtpPz+Hz1ZINJ9sT4Ar0CCtcgHZLlZ3c+UVYCSkDZWt4iGVGIGClov8TBCEBxRWBkggq3HLkT/EVVJijyXaOoMLllhmz5piVSCcybNgwNW/ePHXs2DEd50W9wTvvvDPsAtMXXnihWrZsma5biHsQKxzHjaAigzFV4oWs4eDRE17CqkHF01X+3DmcXYB2cAdK2gUhRSC1AiEXGzZs0P8nrorUN1LCSxCyjmxWlJk8mSmHmMJFhggx2Hdbu3ZtLahILirFP092frgmsZpJWobIAtgXP9JWFU3LfSpmDzfgM2VOuQCxVBkQVmK1ElKATZs2qU8//VRnXedBEu9AtGluBEEIf/yO2nJFtnEjpOyCqnTp0uryyy/XoooioILgZsoFL2HlC8JKUi0IKUjhwoV1MmdyVvXs2VMnBxUEIevJ6YZv30BKgu7du2tBRbyTTPEVMmNmYIaUC4KQwhw6dMhTr5U+mPJiTMRxI45VEITIiPru4wYmLglBlVlFmYXUjrNynBkoCIJas2aNLrpMmTHj/iNpsyAICS6uKG0jN7OQWVarXsPnZ5wZ6Lxx1h2YIMQYUtkwwYaqF0DqGWqdikVXEJJEXImwErLCakWclWdmoJOwGtU+aw9OEGIEaWVIccODLTRu3Fi1bdtWhJUgxBHilBcSoiDzmJvOzzh4IKpIwUCy0G3LTy4rVVfSLghJy6pVq3Q6GPLykSuwS5cuOgmyIAjxhYgrIe6D2B2tVv6ShvaTLOxCcrJz506d1BjKli2rZwMyO1AQhAQVV9dee63nb6wHI0eOdFwXDb77FVKXQ8e8g9gdZwc6JQ0lWaikYBCSFEIwLrjgAv3wwWzsHDn8uMkFQUiMJKLkTbEPbgRT+lsXDfb9JjOSRDQwB44cV7UHTtV///ZEO5WWx+EZwClpqCQLFZKMFStWqDJlyngsVHTXElslCEmURNRoMKcbO8ok7373K6QevjMEHZuFLtBsK8osSUOFJIOC91OnTlWLFy/WVS2uueYabamSflIQEoOQxNWoUaMiWicI0c4QzJfLx/VB0tq3mp8KYBeEJGP37t1qzJgxavv27fr/lSpVElElCMkorvr27RvROkFwdYYgFitfYSVFmYUkYvny5WrixInq6NGjKn/+/Kpbt26qWrVqsT4sQRDCRGYLCvE/Q9Ap5UKRqkrdOPukO1Ce6oUE59ixY2ry5Mlq6dKl+v8VK1ZUPXr0UAULFoz1oQmCEAEiroT4niHoL+UCwipPgdgcrCC4DG19y5Yt+u/mzZurFi0o85Q91oclCEKsxFXr1q31O+br/v37h/354cOHq9GjR+vOZfr06dEejpAEeJW5kZQLQhJjZv9Ro7VXr156BlKVKlVifViCIMRaXM2cOVN3DtS1ioQ//vjDsw9BAL9NQVIuCEkCMVXffPONTrHQsmVLvaxo0aL6JQhC4iNuQSEunt6ZJRgUSbkgJAE7duzQswF37dqlXX/16tXTeXMEQUgeYi6u0plar5RkG05hYdVz+Hy1ZMPfwfNZCUKCt3UC1glcJ48Vwerdu3cXYSUISUjMxdXWrVv1e4ECEpycimCxsgurBhVPP5nbyl8guyAkIEeOHFGTJk3SqRaA9Apdu3ZVaWliiRWEZCSm4mrTpk1qypQpOt5KgjhTD99s7IsfaauKpuU+GX9HeRu7sJJ8VkKCgnWeZMskBaVtMwmoSZMmEmcqCElMWOIqUJFmZvqFWsSZnC6bN29WCxcuVIcOHdKdTKtWrcI5FCEJs7F7hJVTIHtaMQliFxIS4qoaNmyoZs+erXNXVahQIdaHJAhCPBRuDlSkOVDNwVDg8xQ//OWXX1Km05HCzSev+8VD5nrEVYYCzfbCzA9tkUB2IaE4fPiw2rdvnypevLinvTNDME+ePLE+NEEQsmD8DjtLHZ2E/eVveaivCy64QFu9UkVYCRmThnplYxeEBIdkoG+99Zb6+OOPtWXePHyKsBKE1CEst6BvkWbEEa5AOo42bdqoPn36BN0H2+bNm1fncyE3VsmSJcM/aiHhsdtLvWoI2kvdCEICQX+4aNEi9e233+o4K55usV7ly5cv1ocmCEI8iyunIs0mzqpGjRpSxFmIKJDd41GWGYJCgoKF6uuvv1arVq3y9IedO3cWYSUIKUrUswWvvvpqbXU477zz3DkiIeVcgjr1AvjOEASZJSjEOcx6Hjt2rI7BIC71oosuUo0aNZLZgIKQwkQtrt577z13jkRIbZcgC0e1P7VCSt0ICcK8efO0sDr99NNVz549VZky/03EEAQhZYl5ElEhtUhPt1SnoXM9//foJuKstp1MsKhK1ZXUC0LCcMkll+gkyOSvIp5UEAQh7NmCghBNrBXCav2uAxldgnb6TRFhJcQtf/31lw5aN7Oliavq2LGjCCtBEMKzXH3wwQcZ4qz8rYsG+36F5E4aWrlYmprYv6lzXIoIKyEOQUz98MMP6vvvv9d/lypVSp111lmxPixBEBI1iag9eSjvFB11WhfVgfjsN5lJxSSiAZOG0gQP7FJqcLWT/5ekoUKcceDAAfXll1+qtWvX6v/XrVtXXXzxxZK7ShBSjH9DHL9DjrkKpMHCSPIupCi+pW48SUMl/YIQ5/z5559q3LhxOmdVzpw5VYcOHVS9evVkNqAgCNGJq0D5qyS3lRBuXiuvpKFSoFmIY6h/OnXqVN2GixUrpnr16qVKlCgR68MSBCEZxJVvZvZQ1wlCwFI36elKjWh+akMp0CzEGdQGRFidffbZOmg9d+7csT4kQRASAEnFkGAQl5ZosWlHjh5XZQueFFQf9aunjhw5ctId+HkfpY4eVapAeaWKnaFUjgJKsU4QYpxt3WRWJ2cVVSgQWZS0oSCzIAiJQ/bs2VWuXLmy3I0fUkC7EPuA9oMHD6pdu3bpwNpEI92y1Ja9JwelMoXzquw6aWi6Uv9sOrlB9lxKFSwlFishptAVIvx5kbcqRw4pJi4IyUCuXLlUwYIFtWs/2vva9YB2IXYcPXpUbdy4UTeQ0qVL6xlKiRRMeyLdUsd37NN/VypRUOXInk2p9BNK7frPSlXsTKWyy0AmxI4TJ07oTvPYsWP6/2lpafolCEJiPzCdOHFC7d+/X+3du1dbpcuXL58lD05ZKq6WLFmiJkyYoLZv366DQpl1IzUJg7Njxw7dGCpWrJiQT9OIq2w5TwopEi16xFXO/wQiyRdFXAkxAlcfMwHpiHmA4ak0f36ZVCEIyUKBAgX0fU0CYDxAJUuWjH9xhRocMGCA/puEevfcc4/jdnfccYcaOnSo17KnnnpKXXnllerdd99NSNGQFdDh4xKkblkiniOOf+2O/bE+DEFwbJuIKp5qgTQLRYoU0e+CICQX+fLl02487nmMO5nt/Ym6F/n666/VRx99pA+0TZs2jtuMHDlSDRkyxHEdn0VR+luf6uCmwKxpAmwTUVgdOX5C/59SNxitBCEe4KHFCCssVfRDieRuFwQhPIi7wiDEuJrZM3+jri04c+ZM/Y5VpUuXLhnWM8Pm8ccf13/TcdWpU0fdddddOl8M/2cAfvPNN9WqVauiPZSkhPMHiWi1SrdOpmGAPDlzqGolCpwcvJhDsev3WB+ekOIgqIhfxCpcuHBhEVaCkOTk+G8cNeNqXIurX375Rb/XrFlTd1C+TJ8+XW3evFl3XE2bNlWLFy9WgwcPVp9//rl67bXXPD/UzRqFyUiid/xewir9uFLHD51ckTOfUtmkfriQ+fAgh6XKTJCmPeIGTESrsCAI8T2ORj2qMYuNA65Ro4bjerIbGx5++GEvU9wNN9ygOzeYO3dutIcixBEMYOt2+sRaGYvV9l9PLStWXVIwCJkOueEIZGVGIDEXyfLQIghCfBK1uKKzAiOSfJk9e7Z+J5DMNyYLocVsQQbiNWvWRHsoQpy6BD2xVuS2OmbL05UrTaxWQqbD9OudO3fqOAvEFDMCBUEQMpOoRzbju3TKRUqn9vPPP+sOrUmTJo5xQ6VKldLvJOQSkpMqxf9zCdopWcd1q9Xvv/+ubrvtNlWrVi2do4i0D+XKlVMNGzbUy7/44guVSLz33nv6vF1zzTVZ+tlkgT6JfuXvv//2pFm4//77dawV5ydVziezuTl2XqTCCQS/L5Tfac5HpUqV/G6DmKU8WteuXVWFChW0+5VzX6VKFdWzZ0/18ccf6xx+8cq0adN0ySMST3LseGfwvphJEJFYT9944w0dHkOcH+2RfWN0eP/99x3jgCgabq6dv9cDDzzgwq8V4m62IBapPXv2qK1bt2ZY98MPP+gGRQO44IILov0qIZnSL2CxclFYjRs3Tl1xxRU6u3bRokW1mKdkCQMrAn/YsGHqs88+Uz169FCJDh1u5cqVdd4z/hYyQr/DtbcnBaWvohRGKl0L7gdEjIG0N5dcckmmf+9PP/2kBdT69et1/09txkaNGunzz3n68ssv9cMOYmXFihVxl1fslVde0ROvOPZmzZrpvEhz5sxRzzzzjD5uwlgQRuFch4suukh7cvDYILDonwirmTFjhvr+++/1OaEfc3JV0345n06ce+65Uf1WIU7FVbVq1XTl+AULFuiUAXbr1Pjx4z1/00D9JcgEp2B4IfGIRfoFktL27dtXd2B33323zp+G1co3ge3YsWNVItGtWzftNidFQFZ+NlnaIQKLwZy+xbc9pMr5pA/m4ZcaiTwAT5w4Ud8vmZlEEWFFf0+qi06dOuk0OwhQO7hpETAvvfSStl7Fk7haunSp7kcYy7D0kewa+D2dO3fWk7RuuummsPoTLFYIK0Q471jyDEzyat26tRZXTPS67LLLMnweIReutVWILVE/xjVv3ly/Eyz68ssve7loPvzwQ/03HZK/TOzMNkSpYyoWEh+/6RcyEQYMTPUMIMxEdRpIebp79tlnVSLBfYMrgpJHWfnZRMUemoDLBdcLg1K0wiqRzyc5BuH2229XLVq00IIzM2dmYykkzQ5CBHfgV199lUFYAVYbrEBYgEiHEU/QT9CW+vXr5xFWgADkfCLYsV6Fkz4IyxTceuutXsIKGjRo4BFU8+fPd+13CAkurqgYb6xV+H4RW7heGjdurAc8Btarr77aMYh0w4YNOh09YDYWkousEFbAk7jpsCOBAeedd95RLVu21BMz6OwZEG6++WZttnfK7cbvYnsGk+eff17Vrl1bx2XgkuzevbtauXKl43dhQbv00kt1LBjuAVxVPFhwzzAQBYvz4W8zWHH/+MZfBPrsiBEj9LL27dv7PRe7d+/Wv59jw7pgBzfbwIED1TnnnKOT8THY1K1bV1sKGUwzi/r16+vjxiLia/VmoGMdlSF4wMN6aSBehn7HDGy+4LK66qqrdNwnv7lq1arqkUce8dqHG9fCfu379OmjB1e+j7bWrl079c0336jMAPcbVhYyztMHX3fddR7XYGbxySefqHXr1un2Q/7CYG5Y4iHjKRUGVrRJkybpvwkz8AXLEyEHvp6ZYIQq8MNxNQpJLq7OPPNM7Tc3T43EWWHeNAHqmJ9Z74TdrGoarJCkZGLiUPMk+Ouvv+rBJByYln/hhReq66+/Xg9+lHDC9M/gN3z4cFWvXj3tJnACYcUA/uSTT+pjuPjii3VsBJ0uMYa+MTgc2/nnn69Gjx6tO1GS7rZt21aLQjp0gn+DQayGiRvju3CH2l+B4OmYgey7777Tuef8DY4MMMTl2MUqcTE8APFbETUcB8eOAHv00Uf1/ZtZk1L4HhNgbIf/m36HlC9cD46BZUymmTdvnv69Tn0LcXiIROJosOjwUIjb7Omnn3Z0y0R7LcjpR8wR5xcBThtDkCPUaTecV7dBRHEuaKMISI4VCxwWF85NZmAeEBCNZrJSIsGsdfOggEXJCbPcX7/ghLGAEftpDAoG+h3iQWmriH0nDhw4oJ577jntjuzfv7969dVX1erVq0P+fiEGWC7x6quvWsWLF7eyZcvmeZ1//vnWihUrHLdPT0+3qlWrprfLkSOHtWPHDrcOxRo9erTVokULq3Dhwlb+/Pmts846y3r++eeto0ePRr3vSZMm0ZvrV5s2bSLaxz///KM/z3swDh06pM8h7/EO13TV1n+tZRv/1q/jJ9JPrTxx3LI2/3TytX0lG7v2vfv27bPKli2rzyntqWXLltagQYP0tQrWrq644gr9uU6dOlnbt2/3WvfKK6/oddWrV7eOHz/uWT5jxgxPG6hXr561detWzzquU7t27fS6G264wWt/rVq10ss/+uijDMexd+9ea/78+V7LRo0apbfv27ev1/L169fr5RUrVvT7u/x9tk+fPnr5s88+6/g5fg/rJ0yY4Fl28OBBq2rVqnr5I488Yh05csSz7sCBA9bll1+u1/Xr18/xOMN9ce/amTp1ql5+4YUXei2/5ppr9PKaNWvq675q1SrPdfL3Gc6H+Z6HH37Y67ouX77cSktL0+vmzZvn2rWYMmWKPr5ixYpZs2bN8lr3yy+/WOXKldP7mDlzpuUWJ06csMqXL6/3++WXX3qW33jjjXrZtdde6/g5c358f6cv5nz4/m7znU8++aTlNvb7LpxXsN9i5+uvv9afYezwx8svv6y3adCgQVjX4+qrr9afy507t9W6dWvrsssus5o0aaLbBmOUb5sLdg/xuSuvvFL3f0JouDGehjp+u1ahFJ8+0915KiL3Vfny5bXrwx88YWKCNxWrI3XpOBWI5ikRUzhBguwbtwBTsAlO/PbbbyM2Q+MWwcJhyvbEA/op/b8Yp1gfxx87D6jD/x1L3lw51OFjJ2eKatJPKHXsv6nGRSordeyEDnZ3w23INcYqhLWAyRVYA0xZJsBCceONN+prZ59wgevu008/1bFaWBRwdfm2Jaw8uG0mT56sg3PtcOxYm+xP6Jj/n3jiCW1J8bW0GPcllgRfAsUluglufGaP4ebyncK9bNky/TTO77G7Dpkm/scff+jfP2jQIK/P4Bp866239PknxpIAZWKdzHUJZk1zwjchMcHRWBKJz8Flx99YqTi/9DEUf8c6zrFjSQdz7o3VyykGj99ib3+U5sJygMWSz2NldANcqdwf7NfEqBpwqxKr2rt3b13YHiuaG9DP4dLGc4BlzIBrEPcw1lP6Sa6RmxhXMoVx3YZ2GUl7wsIYKibBLJZIf5hzZnI8hgLuUe45LOMPPvigl6uae4h2ilvaF9o6/RYzBUkxg9UTdzazCrFkUZsXS/KUKVMkIW6c4Wr5dwYuTN2hwAyeSG6UQOCONB3GrFmzdKwGEIuB0KJzxoVB0HMkYI5lgMQ0SzxBPICwqvXYqSz4icE2/e+KJ9up/LndaYIMqsxYXbRokXaxIbKI0aGzxwVE/BRBqKwzVQIQTQx6mOx9hZWBuCq2w43iK65wBTrFClIKCnxdb7iFcK8Rd/PQQw9pMcVDQFbSqlUrnZsIlwLBs3YBYdySxOfYj8vEoBAr5gT3G64SztOPP/6op5y7OcOJhyHcrExZ5x5GgHB9N23apONicLEhrhB4xqUXTFxxLZ0GI3/XLlLoe2iT/AZ/KRBoY+Cmq44YQqdrSYwTIhIXOjPTTBxWIoDoTtQZcwixyy+/XD+k8dBGf1S2bFkdn0YAPQKb/gk3NYYJAxMoeHixg8jixX3GfYGQxh3LBAIhfkiq9NjMPgGeyI2wMp08U2Hh9ddfjyg2hDganvjJfcIgKcQnXBssRzzJIYSJZ7APuKaeJdCxATOA/CXou++++/Q2vsHd4Dvrx0CQOvgGRtOJ0i7pYLHGsB1P1Vhw/QXAu409KNse44UlyORDYpaUHXOesOr4O08mKNvpPLkdd8VDnJlVhWBBLDAgGUFFUD6Cmqd8YuacCHbtDh8+7MpxY2UwMWBYIZzOnbHyuHXu2M/XX3/tsVT6YpY5BbYbwRnMMm+vz2jHeCBMip1EwzxkEePkD5NE1LSVUCC1A/cIogohVb16dW2xou1y3xGjxqQI480Jta8zgj1Yclgh68nax+ZMhCdNnpr9zfJgEKMDxlROI+cpIpynT6xVWEcIPCX4MF7AtYYFKNacSLfUyq0nzeQ1SxdSOXyTW+EWNDUFyc6ePYc+9syEjh8xg+uPIFUGHKyb995778lD+i8jMm7DYLNVmf3qS7gJKXFrkNMGqypCgMkfWGB458EA8YX7OrNBXCFAjWsIqwqdM+0ca5qvW86cJ1yFwfIjMZvKwP6YxRcufL+vy9JYd3DTcp6w8nD+mYxgxBdice3atdpiyeCPtdqfq8TtZKL+MOcO615WJbDFPYtYxmL1v//9z6844BwSxmG/3sYdFkhc2Pfh61bE3Uofa/piN+FYcYWFC32/03lwwmSc37t3r3YROlm0zQziQNnp7ZD/0aQl8jfuMGY5hRIEA0srfRpWXCHJxRU3JfErmPDp5OhgTSPFgsRgR6dHY3IzcZyZucH0Zqe8KoDrghuDbcMRVzxt8Dvwc7uRM8dNGDzccq1FK66IswKOx0tc8ZRLAqxc/w1oHG/2zBVWvmBCR1xxHQ3G/M5sMiyaWYFJ4WDEAhYSXB3kv8FVSGyFU+yFmyCAuAdxo9GmcVMad4uTpYPzxMCGC8lflmh/AzDxWuGC28+IK0QSwphjJi6NexfLDDF1iGKsU3ZxxeBkUjb4cwlmJaaNcd2xFGWFqDO5rUgxgnAPtu2LL76YwaKHSA0EeQzt2xuYActgj1BwO1nptm3bImpPEKq44gGacYk2x4MQbnRfWA5270ggsOIZK7Y/a5dJTkvC13DASgv+whqE2OHqnc70UAJMsfLgz+cGpLHwFMU7/2c5wcX4m+0uGjfM74HM/faOzmwbClipSBlBvJWki4giBYOxWmXKVwSfXGCmP9snWZjp0Ygut9xA4YJY534h0BUrB0l1g2Fixhg8I8WIKEQVgyCuSixYTnFV5jxh6QoHnuy5NuG+zGQEzgcWBNz4iBMsECx74YUX9HJjtQLqs7ENlq1g8VZuEuxaMFmCa8sDJq7qzAZ3KXF9uCBNTUWnl3HjYlGxHzuiG2iH/gQW/blxO5rtDQh1rjvpPHgodaqXZwe3PS7TUOCBJJL2FE6cFtfTTADASOALrjsTG0fW/lDgAcAkSsVS7QTxouDPMODPkGHcgRKqkqTiihuIrLz4lU2eGfOyY1/OdsQv8Tk3Zt5lxiwPnpSwKGBJMPFckcBTC99pf6UMVrpSx2wuhlxpJ+sKugjxdEyOcAoIpm1hnTGWKXsOI+JxcNVgzSTxp1NtODowYiLMTL9oYCKFb44bwCpkLAF2t5o/iGthEKB9hvuka+D3MqmEWUvkdmKA5Vw4PVnfcMMN+rjGjBmj3ZbmXrPDsbz99tvKLRjAsTKagZcncyPyzLW0iyssJMSvIBp4eGKQyoqqD6FcC5Ksmlg2p9gY2iiDLoHJTslqw5kFZqxWWJAClRTDkoubmnZNhQO7dR+hyjExC9O3ZizXA9GEyOC3+wbEk7QVEc5DA3GqBFk7Pcxyrkx+NKekrbEEq6mZCWwXxFiz+L24+bhXfN3nTFxgme9y2geTLoDf7PsAhQUZw4RTSAvB7E6JjDmnXGOuD9fZyeIsxBjLBe68806dcyN79uz6nXxXAwYMsD7//HNr4cKF1q+//qrf+f/tt99ulSxZ0pMLi8/cddddUR/D008/rXNPkDfEHw899JDe5qKLLgppn5dccok+RvKrOOV4CTXP1cCBAx3zlCRLnivyW63Z5pDfilxW5LQy+a2OH3U1v5VvPipetD2uL/mrOnbsaFWqVMmzjpww5Jux8++//+rraPLPNGzY0Ordu7fVq1cv/TfLWLdy5coM+XZ88zHZMd9p57TTTtPLatSoYXXr1k0fIzm5cubMqZeTByeU3ErQs2dPvY68QuSZuu666/QrlM8abrrpJq/2+P333/vdlnvYnEtyADVv3lwff9euXa1atWrp+4T72o22tH//fmvz5s36tW3bNuvw4cN63erVqz3Hmi9fPs9yez9k1l9//fUB8zhxfpzwd96iuRbw2muvea4z+f0uvvhiff7Iw1WiRAm9/P777/f6zPTp0/VyPhcK5DsqUKCA/gw53oJBv2tyvNkhb1vdunX1urx58+qcTORHY7uiRYvq5UWKFLFmz57td9+LFi3SObBMPqb69evr88S91bhxY53bkHVVqlTRedTiDZPLyuTN47hLly6tl5155pnWzp07A+bh8mXTpk36t7KO3844xT7JlWU+w3n27efPPvtsfQx16tSxunfvrnNjcf7y5MmjP8P18M2dJsRHnquoxRUHys1vhBXiicSCgeBmMoKMV65cubwGr0gYMmSI/sHnnHOO320QfGzDTR6M9957T2978803Z1gXrrhiEOBCmNfGjRuTSlwhpoywQmQxQGZ24lBfgUSixP79+1uNGjXSSRlpUwzAJL9kwJs8ebLfzyO4PvnkEy3GEAh8lk6LDo3EmOPHj/dKQBupuCJ5KPtjvwxOdJAMQB06dNDf4TlvIQzou3fv1gkhK1SooI/X9/tCEVcMgOZzCCff73c6zy+88IJODozA4nsZcBCh9957r2MSxHDhWiCoEFa7du3ySvJpT1LpmxzUN8EvD3JZJa6CXQt7klISy5KUFtFCgmMGXJLO0n/xm+1wrtkP+w6FkSNH6u1LlSqV4bw58fPPP3sGe9/vpo8eOnSoFhbcC/TxhQoV0klmH3zwQa/Euf4g2ew777yjH1JJ8kt753dXrlxZ98GffvqpK4mdM4vvvvvOat++vede5brx27kPnAgkroDPPfXUU/p+4Vxy3tk3/ciIESMcrxnXFBHGAxnbch2499gHD+2+iY+FJBJXdKrGAuX75BWMBx54wPNZ9hMNJrMuHYE/sBawzT333BN0f126dPFk4aXx2188uZgneLMslM4mGTO0O1qtGKQRVliqjLji/4IQAgzKWGGCib1kp23btlqAhdO3CIKQJBnaTfAos/R8szcHg7QGJLvD/x7uFFRfTD4bZk+YmItoZ3nYP+MEQbVMq4dYBUTHGiYBmgzxpFbQkwQJYLfHWQmCH8xsQD3r9b/Zw8SomEDxVIXYJhKmEseaiDX6BCHViTqymGA7OkamrBLMGA5sz+foYJ2C9sKBWWBkH/Y3y4OOiu9g1oZT+RFfmE7sb/aJSb5oAj95hZrzJJngd6/beTLfDVQpXkBl8w1gz6QgdiHxYSIMM9qY3MIrmtmPyQYzNxFYJhheEITEIuoRz8wcMvXEwsV8zmkGUriQJwhINGdy3Rhr1i233KL/pv6hySkCzGhhdgdCSXDBamWHZKGlzlKqWHUS/cTkGIX4hKn65KsyFl9mA9rrPgqCICQyUbsFcQcynddpinkoGIsV+4kWpv0OGDBADRkyRGeaRjCRmoGprrjwmPbr67rkiZk6a6nq1nMLbbVCQNmzamCtyuJkoUL8WztJb2HSkSCoeMBKdTegIAjJRdSWqzPOOEN3mMQehVsbi+3J5M6gzH7cgMSkJCqlIC15j8h7g8sQaxY5fTC3C+67BAUhlDaDG9AIK3IhmTxRgiAIyUTU4op6Y0AiOBKZhRo3QSI2ShKYBHImQaAb9O7dW4s9rFIEyy5fvlwnP3TqxKmzRqfvlEDSH+Yz0QbhJ7VLUBB84CGKeneAax6LVVbV+BMEQchKou7Zrr/+ek8ME1YiyiEEK+Hx66+/apedyQxMVmj2IyRwILvEVAl+2goPUgZiq7BW4a6XNiMIQrISdcwVdZNeeuklbYWis6RQKGkRKKp6wQUX6LIZdKTEWRCXhavOFFmm4+UzL7/8sisxV0KMrVamjqAg/GedJtaRWYEUbTelXMKdVSwIgpBy4gpwB5Kr6sEHH/Q8pf7888/65YSpJUgwK7FQ1NwSksBqRRqG4/8VYc2ZT9IvpDC4+4mvQljRPpgdaIrXCoIgJDuujX733HOPjnNq1qyZ/n+gKuXQvHlzNXv2bJ0kT0hCq5WkX0hJuL9Jq0L6E4QVMVZYrURYCYKQSrhiuTLgBkRgrVq1Ss8CxP3HjMD9+/erAgUK6FgLXIbEZZ155plufrUQA8RqJTi5Ac0kFWbmEo8pQeuCIKQaroorA0k5eQkpglithP9yxiGsENyIKlPORhAEIdWIWFwRoD5nzhy1bt06nbeGzpR6frgFCWAXktPls3aHQ24rsVoJ/836xRVIXyBB64IgpDJhiyuE1MMPP6wLLhOk6gu5pJg5SCb0woULu3WcQpwIqyPHg+S2EqtVSrkBsVQZC5WJrxIEQUh1whJXlLkhP9XKlSs9gen2XDUso7N94403dDZ0ys5IRffkC2TPkzOHqlZCclulMpSLMmkWiKki27ogCIJwkrD8N6RMWLFihdcy31mAZhlB7ZJiITnTL8SzsOJYKX/UvXt3Vb58eT3okwmcvGv33XdfxDUwo+Xxxx/X54z3eMbkogp0frFek3qFc1y2bFkduG4+F8or1O+KdypVqqSPP5zqDtEQ6flq2bKl/tzMmTNVVvPee+/p76aqRThwTvkc5ziRYKbsQw89pCdscV9gyb344ou1sSFSMGZw/ujP8AyVLFlS33vkjAwEfd1tt93mORb6QkJ3+vbtq5YtWxbx8QguW67mz5+vpkyZohs8HSyFkSkpwwxBBi9y2sydO1e9+OKLasGCBXqbb7/9Vn+OOn9CYsJ1PJ5uJUSpmy1btqhu3bqpRYsW6XZ67rnn6mLdlECiHdI2KepN0ttbb73Vte9l0GrVqpVq0aJFTAawrHQDcp+bcIALL7zQsSbo+++/r9/btWsnlmvBdRBcGzZsUOvXr48r8bVjxw4dc7xmzRpVunRpdckll2hvz+TJk/WLurf9+/cPa59UMaGc26FDh7QwYp+bNm1SX375pfrqq6/UW2+9pa677roMn1u4cKG+PxF7PABddNFFOq8kuSc/+OAD9cknn+hXr169XDwDghdWiNx2221WtmzZrOzZs1u9evWyjh8/7rjdiRMnrB49eni25XOCN//88w9mPv0ejEOHDlkrVqzQ71lNenq69fv2fdayjX97XsdPpGfc8MRxy9r808kXf8eAPXv2WFWqVNHntV69etavv/7qtf7YsWPW4MGDrRw5cuhtXnvtNde+e8aMGXqfLVq08LvNzp07rZUrV+r3eIbf4dQt0P62bt1qbd682dqyZYt18ODBoPvgvETyXYlCxYoV9fGvX78+S74v0vNFuwzlemQGo0aN0t/dt2/fsD539OhRfb+sXbs25uc9VLp06aKPq02bNtaBAwc8yydNmqT7HcbDZcuWhby/bdu2WQULFtT7vPPOO73G3MmTJ1t58uSxcubMqccHX8466yz9uRtuuEGfS/v4/Mgjj+h1hQsXjsm4EkvcGE9DHb9DdgtijQLMi2+++aZWwU4QfzFixAi9nVHQQuLGWR08eqoQd1runHFrtcL8zcxVnu4wwdeuXdtrPcHWJKzl6dEkvcXcnlXgHiA9SaIGfBNbxYtZgOSrM/e3IGQGtDPul6pVq6pEgHAZLEmMiyNHjvRKQ9KxY0ft1uP+efbZZ0Pe57vvvqstT9WqVVMvvPCC15jbvn17dcstt6jjx4+rZ555xutzJPA19X2feuopr5m7jM+EJnD/EjOZlX1gqhGyuMIMi6uladOmup5gIFiPeZSHrayKRxAyl5qlC6kqxeOz2C6i6rPPPtN/Dx48OOAsVTqks88+Wx07dkx3WP7iomjvV199tTbvE6uA+4vlmOd941lwCQIJdO2xRXaXhb+YK3tMCnmi7rrrLv05vrN69erq+eef150ybN68Wd1444069oKM58RSDB061PF3cvx8loS9FSpU0NtzXrh/efgx+wyEPY6SwYLPIw4Rqm7zxRdf6GMjnQOpXHDnUgg+WKwTAxq/kdqkvnFFuDAHDhyo4+0oGM1vqFu3rh5wcBX7wjnBzcJ381sZlEqUKKHbC+6cQH0ZSZNxvRAiwcBVv3597X7xB99P6S+2M8fGA8EjjzyijztcNm7cqMuQmfZK22FWt297DQXaoKn56kutWrX0ukaNGmVY9+STT+p1jz32mN/0PZRIQyzQHnEZE/9Duw4l5srcK7Rt4EHKfr/5uuQJE+C31KxZU59fznPDhg3V66+/rkWJm4wfP16/03aop+vLFVdcod8nTJig+55Q+PHHH/U74QZO91zbtm31O/eA/feEUw0hUR/2EoJQTWG5c+fWZk3MjKHAdrgG+ZyQeG7BY8fSrQ+/OGA9N3S/9c7ofdaRow7uQEhPt6ztK2PqFnz11Vc9Zm7cf8HAPcj2RYsW1a5Pw8CBA/Xyq6++Wq8rWbKkdoF36tTJSktL0+uaNGnidS2effZZq127dnod2+P+MK+77747w755d3Kb4FKoWbOmVaJECe1Wv+iii6x8+fLpdbjWcY+UKlXKKl++vNW7d2+rVatWHhfnc889l+E3Dho0SK+rXLmydlNcdtll2j3E/cjy7t27e/12X9cTbr/t27f7df8HIly34GOPPab7Cs7tpZdeap199tl6OcvGjRvn1y3EeeG9QYMG1uWXX65/3+zZs/U2v/32mz5XrC9durTVvn1765JLLtHXiGXnnHOOtXfvXq/99uvXT6/Lmzev1bZtW71Prm316tX18vHjxzsex6OPPqqP9dxzz9Xn+bzzzvP8tldeeSXD8e/evVt/P+sLFSpkde7cWV/zYsWKea6Zk8vLn1sQ9xntxvxW2mzHjh11+zn//PP1Kxy3IG4stu/QoYPXclzC5hgYC/7++2+v9c2aNdPrZs2alaF9d+3aVbuquEe5DrR3c8ycR99rwe836wxz5szR95W5Fzln9vuN82DgGE4//XS9XaVKlfQ55lqaZdxfdndZtHAs7Peuu+4K2Ofzom2GwoUXXqi3v++++xzXL1y40O8+zbUI5Bb0vb6pwKEsdAuGLK5MDFX//v3DjtESEktcffGFZZUrh1PQ8rz4P8sDxlshshwG7Mzmqquu0ucTwREKdLymU1q3bl0GAWTEjj2uaOPGjdYZZ5yh1z3wwANhx1wFE1e8GHTssRpLlizRMRXcQ7Vq1bJuuukmL/H45ZdfegZo++dg0aJF1vLlyzMcBwOkES+jR4/OsN4cC9vx8h30MkNcMeAuWLDA8Xxxzn0xogZx+dVXX2VYz3WrWrWq3oaB5MiRI551nCdEE+sQU4YNGzboZeXKldOxZb5wD7KN03HkypXLmjBhguN1Pe200zLEpyEgWde4cWNr165dnuX79u3TAx7rLrjgAr/ny5eGDRvq5Yhuez/B8ZrzEI642r9/v/5NiBj7uXv//ff1fkw8zxe2DsH+Gftgbm/fiBt7n0ecpBGZzzzzTFBxFWrMFdePhyPGnzfeeEMLCgPnu3Xr1vrzTzzxhOUW9evX1/vkQc8f3KdsM3HixJD22adPH719z549Hdd/+umnnnPru89Vq1Z5YlDLli2r+zMeqBDuPGDRZ4Yy/iQbh0RcJTfxLK7oL7NloyP3Flcs45VBYMVBMDtWCc4nVoNQoOMxnRJPf74DOk/8TgMsA6gRM/br4Ya4KlCggLYU+cITN+srVKjg2Abq1q2bwVoQjKlTp+rPYOGwg3CziyuElZN1y21xNWTIkAzrDh8+rIUJ6//66y/HwfXaa6913O+bb76p12NxdAIRg9UE4coAb8Qon+F8h4o5Dn/Wiho1auj1xppmBA99In2jU3Dzpk2btOWMz/3www9BxdXcuXP1MkSNXagZsLaFK67slo+ZM2dmeIgxli3EfjBrl2nfHB8TIXz57LPP9HoEj1vi6v777/dYNp3gHCMEixcvHlH7dsJYN99++22/25QpU0Zv88knn4S0z5EjR3r6I+5HX1q2bOm5tk77pD/BQme2MS8e1Nh3KnIoHgPaheTnxAmlbr/dxNp4x1aZ8Js77ji5XSJjjyVygtgZpxQCnTp10vGE5Hn66aefXD0m0kYQ3+MLsTNAXJdTok6znvgSX0joS4wHMTA33XSTzjtHbBcxV7B69WrPtsTmUGTdQAwTZWyyIsaO6eW+EDdSpUoV/bdTTA707NnTcfmkSZP0+6WXXuq4niLyDRo00HEqJq6F4Glicojzevrpp/U0/2iOH4j18T3+2bNn69guCtifddZZGT7DtHlSWJg4rmCYOCMCnJ1iYbt06aKvY7iYeJ5p06Z5lpEUmngpArTLlCnjtc78bT7nC+ebeLBQzlG0BLv+nGPuG9r777/baqLGGcRpcZzcm/RJXOv9+/frHJLEg/J/E4vlWxz9hx9+0PGFv/76q065sG3bNp2bzsR8kb7BKYWDEOeFm4XEZM4cpTZt4i/nARVNsnHjye1atlRxgwnKJKdMqPloDMx884VAWX8QYMtsHHLNuAlB5/6EQKD1CAKTMd13di+DS6CkqYhEE1zNzCE7WZlx3d9vI7jd6bcZ/OU4YoIDXHXVVfoVCCMoOY+jRo3SApSgcl6IAfL5IVwY6My1iOb4jYgI1MbMDLlQBIdph/72Z4LCw00aiUhiMgCiiVJmzIZDwN988816PZU6PvzwQx1cTgB3MHEV6TWOBHP9mVQVDK6/U642O+RvpNybL127dtUv+31I0L4/EEb23xwM7kHEPgL5t99+80ycAUQV+fqYfbhr1y79MGTgXibfH8vJ79e4cWOvB0QmJSC8mI145ZVXeu1XiKG4GjZsmH6FYyXwl7bBtxNwewaHEB5bt7q7XVaB1eejjz7S1iTaULDZbCQZBZ70I01CGMz6FS6+T57hrreDWKLTR2wiFhgQsTjQqXMvkuSQmYbmN9CJszxW6RXC+W12/B2vmQmJKCKbdSDsM7t69OihxcHXX3+ti9Lz9M8sMF5Y/7777js9KLl1/PEMswFpL1j2mMVqxBOJKYHzhLjinHTu3FlbSLC8Op2frD5H5vpj2WTmaSCCzXyHtWvXehLj2qHvMOKKv+l//D3M8CBjHmbC6XO4bxHGWJzIyM61QKjy22i7VJ0A+3nHcodoRKTbhZUBizDLsYxyXUVcxZHlKpSBxV6qwe2BSMgcHKz2UW2XVeCWIYcVHQ/Tkhkk/UFbZFAwT3FObq9ALiEzHb9cuXIqXsH1hLBimj9Pp774ukIY+LDgJYtIIFUFrhPcHv5ch/7AhWa3eJHigDQMtCtyqZFuIxpwSdmtK06YdWbbUPYXKE2ESV0QDjygkAKAQd0MwghwMxDb3YakOeC+wpoVD6lauP60cSqI4I6MFlzpwcr3cK+NGzdOLV682HG9WY7YC2Ypc7oWWKJ42cFNS9WEOnXqeIUxGIEXyEJmXMW4CoXMIaze1LeGYCjbirBKHLCilytnqWzZnK8Z/Wb58ie303Btd8U+ZoEnNEpEwL333pvBxWWHouIk2KPDYlsnKNtkdx0aMNHjEsQFgLXMQL0viBfLq+kwnVwxPNUbwWW/N5NFWEGHDh30++jRo10ZqJ944gn9N6VDoqV58+b6XLMvJ1fd1q1bdZkxCMWigAACPuM0UGKFC3Q/BMIIKEq3ICoRKiaHHDFXxEsxwGO9sm+f2QS739y8/qFiLFhYO52sV8Q9mQdBe1LPaCCnH/iW1DGCmwcMHjh9IebKxIwGck8L0RFyj8rTS2a+oilsKbgD3ttXXjn5t6/AMg+kr756cjuNla7U8f+SFObMp1S22A3QuKoxt2N1IqkkMQp26IhJing7EftK6QSbvlncDQSQ4kqzJ2Ak3gTrGBAcbo9JMlYsnpZDTRCYmZggYQY+e6F1jo1zYBIeJis33HCDdpmMGTNGWy/Icu0LAb5vv/225/9Lly7VBb+dkm5ivQGn5JDhguClnhvCloSwiHUD8TocO/FH1GzlFQziirCaEM9DvUwmMRiwulGJIFKMWCIZKi4t4xK0ryeuxyTwzSpxZe4333vcwEMTIpC2TlySqYVph36CUAK3oC8hNgpLEhZTeztCnJIAFVFNElVfCE5nQgXJTX1BgPvGo+H2R1AhqEla+r///S+DuMRCxjFcf/31nlgv4FzceeedWgAi8sK17AqZ4BY0T0hC8kKHf3az/WrwiOzqhYH51Patp0z89GcIq+7d/Xy4WPVTCiwGENBJ4ClPkJjgiUHgSRurlincTBwCT710uEZkOUFnR8FUYhMYvOjcEP8MfhQhN5YM+4DJd9m/F/FFoD1ZuLMaZqLR0ePK4m+yyOMiwFryxx9/qAEDBugyQPHgwskMGFiIO8HtSxZ+sq4zM49BmbZAzBllP4gRYvAxrrPLLrvMk10dixWCfPny5XpWJe3GN6N/NA8CWBUoDUb7xEKFJRXrEG0Ua8LHH38c8v5wc3ONETm4hMl0z++kzfK7aYe0/3Ah8BkLlZmJ6iSuqBDA/cGsNn9B626D258HcoKxTVZ8I6qIJeQ6m/AAxCXXDdcZExSw5HDtuQ+IO2IfbkE742EGVynXlb4DCzjXlb6Ve85phihChzaGUPWFSQVcR9okx8+DArFXZPEnLg7LpK/VGRf/8OHDdbwlDxjMKiQzPWKKPoqJEnyGIvZmRq7gPjJbUPBAZqtDx06oth1OqI4Xp6utqwuobduy6RgrXIEhzEuIKZjDGbBwBzDQEIzLkx9CB6sDoom4mWABpQxudEKUD6FjoyNj4GDGGJYQp0BqyrfwVEqnjwWEgZnvjIW4AjpVOnOsDohOxAFlXJhdhOAyNRaTFSwJuH8ZZLDU8TcCA6HB4Muga49hYVYg1wpxwuCLJQvBw7ZYhLAUMHC7AUHUDJAMbrQV3NC4a2l3iD2OzQiGUEUQ7ZWBGCvJl19+qY+bYyYQn9QJkWJmBSJYebCwg6DjHNHWs8pqBViVERlYnnDVG8sOQslcI9yvWLawBiG06Quw6iGouZfZNlBsZiSwb64D9xj9AQKP80ZqDa4p5zJcmPHL70Pk037ZHw9wffr00RYyf5PF+H1s9+qrr+o2jRUbgYdA47M8YDmVMBLcIxvJrlzcnxACmNgJKOQpKti0XG4sTNh0vJk5PZ5msGb7fnXk+MkkVrXLnKZyBKvSnH5CqW0nC4SqUmcplT3O1VcQqPuHVYpByrcGYKKCG8A8ERMrRjqBZLVYCYIgZPZ4Gur4LZYrIYOwypcrhwqmq4TEAIsVHQEWhnAKugqCIAiRkzxThISIhdXaHaeEVZ6cOVS1EmLdSFRwLzE7zB5YjytBhJUgCELWIeIqxTFxVkZYnVEyRGEVJ2kYhFMgqHABEsxMnJh4/AVBEGKDuAUFD2FZrOIoDYNbEGeViLFWiCgElclpw0ygrKoLKAiCIGRExFUKw6C8buepHCgRE+M0DKmMcQOaGVO4/8jxE0rJKUEQBCFzEHGVwthdgmEFsYtLMC5gCjxJKElcCMxcIb5KLFaCIAixRcSVoKlSPLVdgokI1iljoSIvkikLIgiCIMQWEVdCePharcQlmOVuQFMUnReiivdkqg0oCIKQ6EiPnKJEHG8lVquYJgSlPApJ7AxYrkRYCYIgxBfSK6coEcdb2RGrVZYJYYqvkmaB+CqC17FgCYIgCPGJuAWF8OKthJjOBqRkA7MBxVolCIKQouLq0KFDOpkhs5qyqmK6kInILMEsdwNy/5jZgOSuyp8/vwhhQRCEVBJXuC/Gjh2rPv74YzV37lw9MACDAQLLDi6O0aNH67+rV6+uLrzwQjcPRQiAxFslhsVqz549+p24qiJFiqhcuXLF+rAEQRCErBRXq1evVpdeeqlavny5/n+w0htFixZVr776qvrjjz9UqVKl1MaNG8XVkUVIvFX8Y7Ks4w7kXe4NQRCExMGVHnvlypXq/PPP18IKUcWLZIa8/IE16+abb9bbbtu2Tc2cOdONQxFSON7q999/V7fddpuqVauWbnvEJ5UrV041bNhQL//iiy9UPHPkyBH9Mnz++efaYnXttdeGva/33ntPX9drrrnG5aMU4gGuK9eX65wq7WLAgAGeFCQTJkwI6fwE+53mfFSqVClgzc5Ro0aprl276vCWfPnyafd8lSpVVM+ePbWnBhd+vDJt2jTVsWNHVaxYMX3sNWrUUA8//LCeJBMJeKHeeOMN1bRpU50KBos6+27Tpo16//33HSfbbNq0Sd13333aQ8W5LliwoK4mwfm87LLLtKcr2YhaXBEP0r17dx10i1Bq3bq1mj9/vtq3b1/Qht27d2/P399++220hyJkJlgicQvGKePGjVN169ZVw4YNUzt27FBNmjRRPXr0UGeddZbavHmzXn7jjTeqeIT7hvuFbOv2GCt//Pnnn0EHBEEIh3hvUzx0IGIM7777bpZ8708//aTOPPNM/YDz9ddfa4/LxRdfrDp16qQFxZdffqmuvPJKdcYZZ+j6nvHGK6+8ogXNlClTVO3atdUll1yia5A+88wzqkGDBjo8J9zrgIi69dZb1Y8//qjq16+v+1nO0YwZM/SYz/8tH8/VqlWr1IsvvqiWLFmiH3jbt2+vBR8ilYfIZs2aqRdeeEElFVaUvP/++1a2bNms7NmzWz169LBOnDjhWXfbbbd51vmjSpUqen2bNm2sVOGff/6h5en3YBw6dMhasWKFfneD9PR0a822f61lG//Wr+Mn0kP5kGXtWG1Zm3869Tpx3IoXtm3bZhUoUECf07vvvtvxXC1evNh64IEHrHjj+PHj1q5du6zNmzfr1549ezz30N69e62VK1daW7Zs8frM+vXr9W+tWLGi3/36+6yQHPTt21e3gVGjRoX1uWjaVCz59NNP9fGVKVNGjyk5c+bU932w88N7IDh//n73kiVLrPz58+v1nTp1statW5dhmx07dlgPPviglTt3buvvv/+24omffvpJn6scOXJY33zzjWf5gQMH9HjL72LMDoeXX37Zc742bNjgte7HH3+0ChYsqNd/+umnXuu4VkuXLvXSB4ZPPvlEHyM6gLEuM3FjPA11/I7acjV+/Hj9jgvmzTffDDs2pE6dOlrl4tIR4jDeiieQ9ONKHTtwalmutLgKZp84caI2cZcpU0YNHjxYt0Vfzj33XPXss8+qeIKnQJKC8o7VgBQLmNnNPUSsFSb80qVLh73vaD4rJC+J2i5Gjhyp32+//XbVokUL7Zr64IMPMu37cAX26tVLW6NwB3711VeqcuXKGbYrXry4tgLh1sLNFU/Q3zG29uvXT3Xo0MGzHGsR55N+hlAJrEqh8v333+t3LFe+GQCwhOHig/nz53utK1mypDrnnHMc9cHll1+urynuRFyYyULUIyRmPgYG/K80tHDBtAq4RIQ4i7cyqRe2/3pqWck6cRfMvn37dv0eSfsDOup33nlHtWzZUsc40UnSkRITyEQLX4gP5LyxPZ3w888/r03uxDPgNsBNThyiv/uFiR9ly5bVcQfMlCVe8ZZbblHfffdd0PgY/jad/IYNG7xK4divpdNnR4wYoZdhkvcH9yG/nzqFCD87uCwHDhyoO0mOnU4aV+xTTz2V6S4R3FUcO+4r3A8XXXSRFqKcc1wTgQZaju25557T25nj5no98sgjnhnN/lxkDE5vvfWWFufE8SFO+G7fwSMU+H72i6vJDm5sBh3WEZfiC6EWrDMDmy/r169XV111lZ4YxLWrWrWq/m32+D032pS9Dffp00cPrnwf90y7du3UN998ozIDrsf06dNVzpw51dVXX62uu+66THcNfvLJJ2rdunX6PgjFaEBcJ20xXiAGbNKkSfrvK664IsP6ihUr6tAJu4EkFJweXAON66HCtYV4E6gxFVemA47UV2+ml/umahDiAGKsfC1W2XPGlbAC8wT166+/6k44HIh1Iibh+uuv14MGMVqdO3fWN/nw4cNVvXr11NKlSx0/i7AibuDJJ5/Ux0AsBgMwndUFF1ygBwU7HBtCihQkDEgM0gg0BsXJkyfroNlg8BBDTAPwXX379vV6BYKnSgYARBxxaP4GFTpmYjPsYnXFihXq7LPP1r8VMcBxtG3bVt//jz76qO6oieXIbBhQifkgTQUiEaHH9eG3M/vYF7bj2B588EE9MxmhwjXjNzz99NNaNPleJzs89TMZAqsicTZcK85fq1at1MKFC8M6ds4X+D6d838To+K7jlyB8+bN09fNDIZ2fv75Z30O5syZo5/+mzdvrrZu3ap/m7EiuNmmXnvtNdWoUSPdTniQ4F5BqPLAQfunfWTGNef8cN04/xwrIheLC+cmM8BSBYhGvjPRWLNmjeeBB4uSE2a5v/7NCWMBI4b1r7/+8lpH//nZZ5/ptnrVVVeFvE9EIA9MCDf6xKTBipLTTjtN+0r79euXYV0oMVfdu3fX25QqVcpKFVyNuSIe6sj+kF/HD+2zflm3Wb/4O+D2h/6xrD9/OPk6+LdlHQ6yfbgvjt0F9u3bZ5UtW1afU9pSy5YtrUGDBlmTJk3SMRGBuOKKKzwxFdu3b/da98orr+h11atX17FRhhkzZujlvOrVq2dt3brVs47r1K5dO73uhhtu8Npfq1at9PKPPvpIxx4cPHjQKxZm/vz5jvEgvnEjocTH+Ptsnz599PJnn33W8XP8HtZPmDDBs4zjrFq1ql7+yCOPWEeOHPGK37j88sv1Ot8+wBxnuK8WLVpkOC5+K+ty5crldWz230pfZD+ncOmll+p1jRs31rFt9jbToUMHve6CCy7we9x87+rVqz3raAfXXnutXnfRRRdZ4TB16lT9uQsvvNBrOeeN5WeddZZuvzt37gz6GRNTxOvhhx/2ap/Lly+30tLS9Lp58+a51qamTJmij69YsWLWrFmzvNb98ssvVrly5fQ+Zs6cabkF90n58uX1fr/88kvP8htvvFEv41pkRsyV+c4nn3zScht7/xHOK9hvsfP111/rzxQuXDho/FSDBg3Cuh5XX321/hxxZq1bt7Yuu+wyq0mTJrpt0IZ925wvN998s/4txHvVrVtX74tYrbFjx1qZTVbGXEWd5wpfKk//kcZMLVq0SJuey5cvH+2hpCbHDir1TJmQN8+hlKqr4oSHtiiV23+6jlApUKCAtgrxlI01gadoe2oPnuyZKYh1ioScBlx3n376qY7V4kkcl5GdO+64Q1spcHdgWcJyYYd2i7XJ/mTL09cTTzyhpk6d6rFCmNmAW7Zs0f/nCRw3g92NwJP4eeedpzIbZj0x6wr30AMPPOC1btmyZfoplt9jdx0yvRqrD79/0KBBXp/BxYbbjPP/4Ycfqpdeekm768x1CWZNc4KYIH/0798/w3XArYVrFkvG4sWL9cwj4Ml6zJgx+jpxjFhaDBzb22+/rapVq6atH7ywNvoydOhQPRPMQPvBKoQ1ZdasWdp6GWpyV44LiyjxObjsjAuEc4ebhjZKLAv/x3UMpg0Zq5cvWN64Jnb3HXGsWA6wvPJ5rKVugEuYtsx+sZDZwT388ssv6xngnDOsaG7ALHJc84wzWMYMuAZxc2MFxprG9XQT45EpUaKEchvur0juCyyMoUJ/A4HSIZlzZi8EHwz6LfoOLPxYg+2uavoC2ilu6UDQ19qt3FjIaVOEUyQTUYsrblyEFdMyiX3hJggV456gY/C9WQUhHJgKvGDBAi3WMTMjsohtoZPEdUL8FMGbrCOOAhBNDBaYun2FlQG3Hdsx+PoO6rgCcZX5UrNmTf1O2yatAnE9uNrYlmS7xKs89NBDWkyZWIOsAncWLnyOg7gh+8Br3JLEtdiPy8RumAHfqZPGxcB5oh8wpn3iLsLNwxQM3JVOcM4RV3Z35+zZs3WQLLFODAa+EPeG2wcXEG4JX3HFOXCKT2NwREByXYlRC9VthJjmO/guBBbuTdw3iMD//e9/Xm7DUMUVbdIpLsreBt2AKfvcW/wGf9eAewXcdNURC+nUJolxQkQSCsBUfhOHlQjw8OD2fZFVIMQIQOdhk4dP+lXuI+LTCKBHYNPPzpkzx6/BhLRNxmXP9WNCAK5e3NgfffSR1wNwIhN1z85MCoJJeYJDyYYaZIiyJimcgZkZQgTkyn/SAhQCCIk/dh7wzBasVbqQyuFvuqAJZjflbghkz57D/WN3GeJBeJnfiyWG/CrEAjBQ8ZR777336vV0CMDMGTMbyR++wd3gr15moUKFvGYDMsAzABJUvXbtWt0x8TLB2AxKCC4zIGYmJpj58ccf12LKiCvuX5NHiDgjO+Y8YQ0JFkvhdJ7cJNg5NwWu7cLCaZaXwTxlO4kQZtT5s0rxfYgr+/fdc889jnmD7AMpIglxRVtEXBnxRNwfFjIGJLMM4caDARY3Yv+iPR/RQNA89xMxYMGCjt1qA+yH3FLglEiXZXfddZcec3zFlRGcwSqFmPW+AhVrChYzYvMSEfOweOCALWbWB5NE1LSVULj77rv1QxQTcBBSBoQu/QdtFqv9I488oi3egSDuFKMKFl0EO300cYXEOCYDrogrnshxKXAyCfxkEDHWASfI5M6TCE/PNGo6mcaNGyu3wBVAwB3HhMUA0z+D15133hlWfTYGZpKv0dmhsFHaPKXTkFDZN9xwQ+zrvdEphOhaS0+31EF1XKlc/6VhyENKBT/iKv2EUqzKle9kHcE8BeMukD0YtC3EC64/gjvpqEn6Z8SVySSM29DJAmXHqX36m0Fk79D5DtoIlg6evHFb4U6iTf3www/awsY7T288+d1///0qs0Fc4bo0LhVEHhmvEQZY03zdcuY8YcUJZpnGvWVgfwiOcOH7fV2WhqwsAxTud1FXldl2wcQV2bGx2nO9aQd8D32gWY/oRYRjeTWJmf3N6s2q82HaAP2fCX7PbHAzI/q5b7Ds+RMHWMqwWtrbrXGHBRIX9n34uhVxtyKusMS6DcfKGBmJW9DpPDhhJphhJcKQ4WSZNzOhQ52MhhWeawJYr5xgZqI9JCKcBz4s5EwGEnFlA1GFAuUi0lljpsV/irgxsJwyNwwk3AxmAMJ1EMxqEA6YKvkubkg6JW4a/MIMWgwg+PBDmTLL7EUGZmAfmKEZWEjjjzsFsz4WOxoSgjLRijUHTMNgrFaGOEu9EAm4qhBXdsuCMVvztPT666+79l3G7G06eZ4Mzbk2KRyMCwXLAoMvsTa4CimnESxmIVoQQNwbxPaQ2Z4HDyMAnCwEnCcGBKwDHF+oMHAFe3p1gngdf+IqHHBX2C1vTph1ZttoCDTr0ID7lP6CBzcsM1ixEPcmHsyIKwYnk7LBn0swKzH3Cu0XS1FWiDozLtAXM24E2xYLta9FD5EaCBMr7GsB7NKli34Qo38PN9wlGIyDkdwXEKq4IkyCGCgeKnmgIxzAF5aDGeeCgRXPpPfwZ+0idhT27NmjwsGI4US1FDrhyh1CPAMDF6ZUUyuQ2kPcEGZQwXxLenuW8RTEdpjdUatuBbNzM5jgRiwC3Bj4f7mBCLhEEDFtPFR4euHpngEZgYYFBF8yHSPHTgwCvyupkoeapKHGHYjVKo4ShjoRzPQPZtowpRd8pxXTdt1yn/gGkdLZBMolRgD8TTfdpO8h7otffvkl6P6NVTia9CVGRCGqGDyMm9IprsqcJ+6FcDB5osJ9uVVnlAc+RACuNfuDnoGUBVimwWnwyQw4Hr6La01/iBDHJWjAgkV7wbIVLN7KTYK1KSZ90EZ5gDbnLDPhAZb0H7ggcb/6aysmtxYWFfux8/AA3E/+BBZWMeN2NNsbeOCg/eL5IK7IqV6ebxoCXKahwINVJPdFOHFaXE8zAYAAcl+wsJrYuG7duoW0Tx4AjEvYXxoS4l6DueKdMCl07JNHEh7LRUhxz9TYPHny6GmZ/l5Mp2b6sdulORo2bKinSD711FMZ1s2ZM0ev49iY9h4tH374od5fvnz5rKNHj8Z9+RvK3AQteRPnZW788frrr+vpwT/88INjuZ8vvvjCU8birbfe8lrPdGCWMy2f6ei+7N+/X6dOsJfaMFOpTcoAvuPw4cNenzPTp+28+OKLGUpGAOVIzNR5Sm4EmzZPe2MaNCUjdu/e7XhO/H3WQHtimjZpUvr376+3vfLKKx235RyYVAj33Xef9e+//2bYhnQUvufWTcz3O12jQOVg/KVi4DeRfiNQKoZAaQmCHU8ghg0bpj+bN29e/T5t2jSv9UxPN+sqV64c1u8Ndv2jaVNmen+JEiX0375wHyxYsECnj/CXeiBUrrvuOr197969A25HCgrS+LDt+PHjvdaZEi9ce9+xhpQd5juKFy/uWLpm0aJFnutwySWXOJa/4VyRnoRxJd7K39CXmPI3kydPDrn8zcKFC60zzzxTv3zp1auX/lzJkiWtZcuWea2jHZvzNWjQIK91I0aMsFatWpVhf7Q71qEJ+BzpPpIlFYOr4spAnhZqCw0YMMDq2bOnztHStWtXnZvk3Xff1TXU3GbTpk2eG9jpJrDnLqGWUbT8+uuvnu8LVyTGrbhCSNmFFULLpVxUmYnJR2U6SvIPkb+qY8eOVqVKlTzrEA++ta0QCqajYXBBoNOh04nwN8tYhwByElfHjh3TubRo0/b8T06DCXmYWFajRg2rW7du+hjJyUWdNJYjEEMVSNxXrKNNk2eKgYJXKJ813HTTTV55dL7//vuA7d2cS0RZ8+bN9fFzX9eqVUt34nS48SauEFRnn322Jw8Wx8u5o50Y8eK7z8wWV+TNMuechzNfYX7nnXd61l9//fVh/d5IxVUobQpee+01T3utVq2adfHFF+t2QB+P6GL5/fff7/WZ6dOn6+V8LhTIQWZqhZKrLhh33XWX3hax7Cv4TR4lBn1yMpHnje2KFi2qlxcpUsSaPXu2330jsMy1po3Xr19fnyf6CEQbwoV11Mj1zbEWD5hcVib/H8ddunRpvQzxZM+pFooYZpzlt7KO305+K/ZJrizzGc7zIZ/xir6SdeTL69y5s24z9LtGGPOQ5y/3npskvLiKBSQWNDeLPxjQ2Obee++N+vt4SjIDsm/nmBTi6vjRhBBWRiCRYBALTKNGjXQyQ56EGLi4mRko7E9uviC4ENyIMQQCn6XzrVOnjrawcq3t1knT+TRr1kwLa4QV7/Zr5NQ5YQFjf+yXdsrTLh03VjO+gyf/UAdCnph5WKlQoYLnqc/+faGIKwYO8zmEk+/3O53nF154wTr//PO1wOJ76agRodxTwZIHxkJcmSd1Ou5zzjlHWzAZaGvWrGk99NBDulC2L5ktruwPer7JQQFBYa7L559/nmXiKlibsicpJUEuyXU5l5xTBlyS5w4ZMiTDwzNthv2w71AYOXKk3p6B154c1R8///yzZ7D3/W4Ez9ChQ7Ww4J5G4BUqVEgny6Xgsj0BsD94aHrnnXe09Ypkxdy3/G6EOUILQ0K43ous5LvvvrPat2/v6XO4bvx2Jwt0KJZGPod3iPuec8l5Z98IKKxQTtds0qRJus3woMODDdeBxKG1a9fWSUV9rWDJIK6y8Y9KAkhcR2oHUw7DCYp+DhkyRAflMqMwUjhlBEETF0DgPnFd4eYKIRaHRGrBpsESC8Q0aHzYodZ1cjretTv2e2Kuapc5zTkFAzMEt/0X81PqLPdTLyQJnE+uoZmJRHwDQcpZnbNKEBIBYsqI7yERbSKWkhGSh8MujKehjt9JMxpkVkZaJ5jGjrBif6FMqWWGhb2IarTf72owO9qaGoL678BBm8LJgF8CbAmGBdoA05wDFsAWhBSFIG8mEpEfSYSVkEokjbjKKki/QHFSZv0wJbl69epBP0M+GwRZPOCVgsGkXLAXZxaCPvkgrLj+WKsiffoRhFSAGaihzqIThGQipxtiwy1ILBpvGWnt4Eo0U9ipSxZqVnky19tTNmC5yqpair75rbxXpjsLq1xpcZ9+IVZgGWVaNu/JUqZBEARBiDNxRWZVN1wi7CMacWWyzJqss06Em5HWDskWyT7LwErBUKdki/4gN0iwkhExz29FeRsjqHgXN5cGKxUuZ6xUWKtop5GKc0EQBCE1cMU8EW4yNH+fiQZTe4vaRgSsORFuRlp7clLK3ZD+/80331TXX3+9SkQCZmVHUBHAzkuElYbsxiSQxRVoYvoEQRAEIdMtV3379g1pOyw+RNdTV9CIH+JVcK25UUqBzNuUqKEWFBlpqd9lh6BKLFdYkDp27BjyfimZ07t3bx3IjLC68cYbVVLgW+JG8GqruG4RV2Y2oG/tMUEQBEHINHFFHaxwwYJEWgRm3FEqh1gmN1wt1GYjlT8z+CjZYSxUWLOo4g0UhTT1j4BCkcREUVvMpOA3UFqBtA0Iq+HDh+tCzUkD8VYJVOImK92AzAY0pTSI5UNYyWxAQRAEIa5nC1K8dPbs2br2ETW0iLXC9RYtXbt21bmuyGV13nnn6TpdBB4jmqjhRW6qQYMGeX0Ga9rq1asz1JajgCQ5rKgthVWMPC2mFpMvgwcP1gWoEwZ7+oUkKczsBrQBU8cMa+rpp58es1g5QRAEIXGJWSoGZlq98847qlq1atr1RsA4YiZaKNyMiBo2bJgWQ1giqlatqh544AF15513egqUBgOXkMlNtWnTpoBVzB9//PG4FFeOMwUl/YJfcuXKpS1UJimozAYUBEEQIiHmGdqxLs2YMUNbsRBZqUBWZWg/kW6p37b845kpWK1EAZUt/bhS23/1TruQwpYrJinYRRTuQP4vbkBBEITk4nAWZmiPeaANViVYtmxZrA8lqalSPE1lw2JlF1akX0hRYcUzBTnRcP/akxxSwkaElSAIghANMRdXJtaJQU7IRHwThmKxyp4zJYUVswGJreLJA5HlG28nCIIgCAlb/oZBjsB2sM/gEzIZLFYpKqyYoICwwh0ImHUD1aMUBEEQhIQSV4888oj666+/tBsm3MSeQhSkYAZ2LFRMUsBaBcRVMRsw1AkOgiAIgpBlbkHEUaivdevW6SSf1OVr2rSpev7558NORipERvbda1WqiKjPP/9czzylfiNBi4ioc845R917771q8+bNelnx4sWzVFgxo5SHCN7jGY4x1Jizli1berYP5xXJd8UjlNHi+P/8888s+b5Iz5e5TjNnzsyU40oF3nvvPX0OKfcWDrQNPhdJybVYQX5H+qlLLrlElSlTxtPumDUfaZ88aNAgnYPyzDPPVEWKFNEzs0uUKKEuuugi9dFHHzlWaKG9htqnoC+SznJlOphoIGM65WWEzCG7slS2FEgYumXLFn0DL1q0SLfJc889V6flwGJFwloy7L/77rs6LxnJZN2CTqBVq1aqRYsWKTWAtW/f3nHQMGlL2rVrp0qVKhWDIxOE+Id7Z8OGDXr2WjyJL2roGgu/G5w4cUI99thjOmdg3bp1tcDKly+f/u3Tpk3TuS5Hjx6tE3rbZ27TdwQyutDPr1y5Uk+K40E6ad2CkWR0IFHjzTffrF566SW3DkMIRpLODiSOqlmzZto6Sp3JDz74wDPdlhuWFAvkQLv//vtV//79dbwfCWezCsQcDxDxmA8tUsgd54QRV6zHaiIIqQqVPxAAWGoSBaz+1atX16E6vLAwRUOOHDl0uiUSe/umP6AcXtu2bXUaJvJe2svL1ahRQ1sM/VGrVi39fu2118alBTxqcVWhQoWQfxgNjABiVHrjxo3VpZdeqj8vZC5Vs21RyQ7iBWGFoOJpCHj6Is1C0aJFdYqFu+++W9/cbHvPPfeoCy+8UNWsWTNLjg9RlUzCShCE0MY8REIigXXfTbJly+b3IQtLFv0xlq1vv/025Nq9eCIQrQi3cF21WUXU/iF8ypg1Q3mtWbNG1xUcO3asjn8RYZU1LsF82Y4mtUsQUfXZZ5/pv6krSVZ+k14B87MdakyeffbZepsXXnjBb1wUJmvKMpUuXVoLsjPOOEMvt+fEAjoNXIIwa9YsrzgAu6nfX8yVPZYDMXjXXXfpz/GdPD0Sl4iVDYgXo/PBBI6JHfP60KFDHc8Jx89nW7dure8ztifrPLGOI0aM8OwzXvjiiy/0sZnZm7hzif0IFuv01Vdf6d9IHIdvXBHWzIEDB+p4O2pE5s+fX3fmTz31lKcotx3OyVtvvaW/m3Nl4kJoL1g7A8VW8WRO/AjxfbQ5nvixnvqD76etsp05ttq1a+tJPhx3uFCUnid4015pOxSv922voUJ75HzSPum7r7rqKu2moR3hhuE4TQULJ7gfSRDNdeEzFStW1MfHGBDsmoZ7Lv3BvcQ+X375ZUerB+saNWqUYd2TTz6p1zHgO0F+POrRUl2E32bcV9yfocRcmXueexR4ILT3G76hBYQ78Ft4EKSd0F4aNmyoXn/9dU8N1EQmZ86TNp5wSo0ZAUhoAnFhcQkZ2oWs5Z9//sGHqt+DcejQIWvFihX6PVyOn0i3lm/cY1mbfzr5OnE8jA8ft6wZMyzrk09OvvP/OOXVV1/V57Nw4cLWhg0brM2bN1vbtm2zjhw54rj94MGD9fZFixa10tPTPcsHDhyol1999dV6XcmSJa1evXpZnTp1stLS0vS6Jk2aeF2LZ5991mrXrp1ex/Z9+/b1vO6+++4M++bdzqhRo/TyLl26WDVr1rRKlChh9ejRw7rooousfPny6XW33XabtXbtWqtUqVJW+fLlrd69e1utWrWycuTIodc/99xzGX7joEGD9LrKlStbbdq0sS677DKrRYsWVu7cufXy7t27e/12A+ui7RbMPmbQbkLY7rHHHrOyZcumz+2ll15qnX322Xo5y8aNG5fhcxUrVvScF94bNGhgXX755fr3zZ49W2/z22+/6XPF+tKlS1vt27e3LrnkEn2NWHbOOedYe/fu9dpvv3799Lq8efNabdu21fvk2lavXl0vHz9+vONxPProo/pYzz33XH2ezzvvPM9ve+WVVzIc/+7du/X3s75QoUJW586d9TUvVqyY55qtX7/e7/nyZeXKlbrdmN9Km+3YsaNuP+eff75+hXI97NB++cztt9+uj5HfSrvjvJh22bVr1wyfo01x/7A+Z86cVuvWrfU5OeOMM/Sy/PnzW5MnT87wuUjPZSAmTZqkP9ehQwev5fQPZp/Zs2e3/v77b6/1zZo10+tmzZqV4T7lN5911lm6r6E9cd+ac89v8G1TXEezzjBnzhx9fk2fwrW39xtcTwPHcPrpp+vtKlWqpNsKbdIso584evSolZmYc7Vx40bX97127VqrXLlyev+ffvppSJ85cOCAVbBgQf0Zp/4hs8bTcMfvqMXVsmXLPK/jcTwAxxNxL66++MKyypXT5Z09L/7P8jjkyiuv1Ofzggsu0B3nnj17rBMnTvjdng7LdBjr1q3LIICM2Dl48KBnHR2LGSAeeOABr/0xaLGcwd0fwcQVLzprOg7DkiVL9ADFAFCrVi3rpptuso4dO+ZZ/+WXX3oGaPvnYNGiRdby5cszHAfnx4iX0aNHx4W4YqBasGCB4/ninPsbiBGXX331VYb1XLeqVavqbR555BEvkc15QjSxDjFlQJSzjI5+69atGfbJPcg2TseRK1cua8KECY7X9bTTTvNqR4CAZF3jxo2tXbt2eZbv27dPCwHTlv2dL18aNmyolyN+7P0Ex2vOQ6TiitfDDz/s1bfTrowwmDdvntfn3nzzTb0cobh06VIv0WWuKdd7x44drpzLQOzfv1/vj2O1t4H3339f7w+RxPsXtn7N/hm7aLHfp4gbe99Nf2PE8jPPPBNUXPn+ZichDbRDHvIQm2+88YZXn0a7Qbjy+SeeeMJKFHH12muv6bbFPdi0aVN9D9O/+fapgXjvvff08SBqwxWWCSWuuPCcHJ62hPgRV3Rma7b9G764oqPJls1bWPFiGa84FFjGcoQgonN0ssjYWbVqlafDWLhwoWe56fx5MncaYOn0jZixXw83xFWBAgWs7du3Z/gcT6qsr1ChgmMbqFu3boan7GBMnTpVfwYLRzyIqyFDhmRYd/jwYT2Ysv6vv/5yHJSuvfZax/2aAR6LoxOIGDpmhCsDoxGjfIbzHSrmOO666y7H9TVq1NDrjTXNCB76S/pNHkh92bRpk7ac8bkffvgh6LWZO3euXoYYsAs1A9a2aMQVFiSn+wmhz/onn3zSa7kRc07XlP0YQfP0009HfS5DwVihZs6c6Vl21VVX6WXGssVvCWbtMvcp53nLli0Zvuezzz7T6xE8bomr+++/32OhdYK2ghAsXrx40D4vXsRVly5dPPszYhpBGo5obt68uf7sPffcE/b3Z6W4ijoAx8yCYCaAED+kW0odOnYyC3nIkLX89ttPyilfzLI77ji5XYz578FA/20mVOCzJ14n2ASLYDNbifdwSiHQqVMnHRxP4c6ffvpJuQlpI5xm5RA7A8R1ORUaNeuJy/CFmBhm4RA7ctNNN6l+/frpWBpirmD16tUqHiCfji9cyypVqui/nWJZoGfPno7LJ02apN+ZMONEgQIFVIMGDXS8Cnn3gKBjYlmI83r66ad1nFE0xw9msoT9+KlIQWwXM1rPOussx9llpLAAYo+CYeJziD2hbfrSpUuXqKpf0Oad7ien30YepD/++EP/7TSFnv3QBgP9tnDOZSgwEw3MJBeYPn26jpciBRDxOvZ15m/zOV9oN8S1uXV8gQjWjmkr3P87d+5Uv//+u0oEvvzyS09d119++UXdcMMNOn7v/PPPd+zDfFm7dq2nqgsxfPFM1LMFGYS4qeiwhARnzhx6SP/rESUbN57cLoZT7MmbsnfvXj0A0+7MLDw6mVCw17EkmagvBJj6g8DU3bt3R5xQzx/+JneY+8rfegQB+NZHXLBgge6UAyXXQyTGA/5+m6k476/2o7/cQExwAIKweQXCtBnO46hRo/TgT2fPi0GUh0aEC7l//PVx4Ry/GXwDtTFTzD6Ugdq0Q3/7M8HUy5YtU5EQyW9D5Jn14f62cL6Pqftz587NsC0pQMwMPUQSkxoQTSSyXLFihR7ESQEEBN1/+OGHOricoPtg4irSthoJph2TYiYYtGMm3QSCc8U586Vr1676lZXk/29yCUH5nPf77rtPp8ZhslsogeyIsaya6R0zcUUjZqaKmfkgxB6eDNbt3B/+B7dudXe7TABrDLOpePqnTiA3KVYfsvxiTcIaYWafBEo+ZwaBSJP3RZLXLVjOt2jW+85Eo7Pcvn27FgsMJDypMwAwdZkZW8w0dPs3REo4v82O70xQg5kJiSgqWbJkwH3QsRt69OihB9Wvv/5azZkzR/3www86sSEvrH8kO2RAcOv4E4Gs/m3hfB9iweRUs4N11ogrZgPS7rFQMhvXiCfSsADXG3HFte3cubP69ddftQXZ6TqHe3zRYtoxFtpg9U+drJZOVh+n80UfmNXiyg59FOIKKzsPzvZEonZYZ2aNXnfddSreiVpc9e7dWzdMGjpP9KFcZCHrXIJ5c+VQKlQvnoO5O6rtXAQhsH//frVv3z79fwQUU7Xp7HAlkMOKzpOp+QySgfZDZxrI5RHIJWSm45crV07FK5jNEVZMYXfKWZMoLoRIIVXFqlWrdAfsz3XoD1xodosXD46kYaBdkY+HdBvRgCvHbpVwwqwz24ayv0BpIrLqwdccC+MAVlEn61U4vy0YpDQIlGTS9BNUTmDgxhWJuGLwNulT7G5DHtToH7BmxUNSStox9yqJj3FHRguiMx5zQqX9Jxx5WMYj4U9DTJ06VVs8sSD7c5XGE1HL8D59+uicIZhDb731VneOSnCNysXyh74x5mdEg7+OheWUGQjBTO0mPLHQYRthRSeIK9DE++FqQOQD+dO4Qf3xxhtvaF8/nS7bOkEyO7vr0EA8DseBCwlrmcHUKIyXnDN79uwJ6MLAypfMdOjQQb9TUsONAe6JJ57Qf//8889R76958+b6gYB9Obnqtm7dqqZMmaL/NgIgEAgH4DPmutvBChfofnATHjiM289J9CBczPJQfptbGAE1efJkLY4RKuQxA2KucC8Rh4WRwL59ZhOs33CzHccz06dP1++IKvKi+WPkyJH6nb4+EcKQohZXBNniJ6UTGjNmjA4S9JcoTohzMMe+9trJv30Flvn/q6+e3C4LTeO7du3STzU8TdIp8vI1zw8bNkybt7E6kVTyt99+81pPB0YywdsJ2FdKJ9gkaaMTJF7ElWZPwEicBtYxIDjcHlxurFg8ZZKcNNaYWAQ6LWJM7JAkk8LWyQxBsrj76I946jei3M62bdt0AXnD0qVL9XlxSrqJ1cPXhRgpCN5evXppoUFCWMS6gSBfjp0H1QsuuEC/gkE8DhZKrLo83NoTe2J1oxJBVmK+j/gmu3jk95K8FVHJ/Xv99ddn2TEZsYRLCYuacQna19PHmETEWSWuTL/h21cZePjjXNFvUSKOPtAX+rt4eVjC4oc7Fje6nYkTJ+qJF05hCN9//70n/o024c9iyPUx92EiuATDcguStdb4sIll8F2Ov3r48OHadEfnzkwYnu4JGPYXG+GLv4y4QhbSvbtSBBUiQuxB23QECCvWZyGIKMzGxBHhBvRXo4snHlzTxA5QBYCYCZ5QeZI2hZsJ+uRpkY7KiCwnyMxOh8BsNQYvBjs6AQY/AimNJcM+YPJd9u9FfGFdIwt3VsNMNGaJ4crib7LIc34Y2Jgh+NBDD+kZcckK7YWZVrh9ycKPoKQ/YjCjLfDwR+kMYmvMII/rjNqPJiM4D4sIcmqfcc5oN74Z/SOFBwHclgsXLtTtEysOllSsKrRRgtM//vjjkPeHm5trjDjAJUyme34nbZbfTTuk/WcFCMZ58+bpY+I+wLLGeSYekvPI+f3kk08cJ5JkFnhWsFCZ2WhO4opKB9znzL7LqsohhC/gqrzyyis9GemNqCImkvZqwhwQrbS/OnXq6IkWhEDQhpmdSSk59uEWCGMzU9EOY7yxtnGP4AWww7FwH/kWfV68eLHuM7nm9Ee8Y03lYdQYYrp165aheoUd2hMProi3UB46EkpcmfIdPB3ZxZVZbgeFiuuFVziIuIoTEFBdupycFUjwOjFWuAKzyGKFGxCLlRFSDJahpFggjoMBCzM6Aw1BrDw9I3SwOiCaiJsJFsTO4EaHQPkQBigC6OlwmTGGJcTpYYHyLZTEoLPEAsLAzHfGQlwBVhsKVfO0jujkHDDYDRkyRA8gySyuAKsk/Q8PfDxJ8zcCA6HBoMVgRYduYFYg1wpxwqCFJQvBw7b0ecRdMeC5Ae4PBAjXgraCG5r2TrtD7HFsZqANVTzQXpkVh+uL6e4cN8dMn4o3IavgHqXN4dJC1C5ZskQ/lDCrnHgfZvK5dR7DwcwKpB/hAckOwpRrzT2bVVYrwGKDVRXLEyEHZqYhQsmcI9zIWLaYVYfgoU/DOolgpU9i20AxppGASKIf9YV7wuCUFsYfPXr00BZh+iF+C1Yo2gkiERcf8Y08CAWCmbyJkH7BTjaSXYVqQTDiik7BvtyVA8mWTQ+qqQCmaQJnUfj+piwbuOEw/dLxhtqgT6Rb6rctJ58eapcuoHJsX35yRamzlMqedS69SOD38lRDe+AJJytn5/CgwBMWg1SgpyhBEAQh8TgcwXga6fgd9WxBBiIhfsm+e61KBND4PMUROwJYrXiaT+Zp7oIgCEJyIuIqicmuLJXt+H8BujnzKZUtPoUK5nhcbyYYHNM9TwTxMB1aEARBELJcXAkJQrHq/lMsxNhMi7DCcmVmA4Y6AUIQBEEQ4hERV0LMMDWmeMcNSBBvsOzqmQlxVhJrJQiCIESLiCshZhhLFQKLxJziBhQEQRCSgfgMwhGSFqbk2vOgUIpC4qsEQRCElLZckTOG4pZuw+Bq0uALyQeuP6awYqWCPHnyRDwVVhAEQRCSSlyR5dZkunULE8wsJCe+swGpC4W4EgRBEIRkJGxxFWLOUSFGcH3W7TyZKype3IAkBeW4yFlFjJVYrARBEIRkJmxxRW1BU61biD/SLaUOHTuZ6b5a9q0xPRbcgCYpKDWpmA1IjJUgCIIgJDMRiStJHBr/5FQnVF51JKYJRE2RT9yAMhtQEARBSBUkFUPSYamq2baotGz/CassTiBKfUhjncL9R4HRWOauEgRBEISsRlIxJBtWurewypWWJVYr6gASW7Vjxw4dwG4QYSUIgiCkGjLyJTEnStRWOXLkynSrFbMAmQ1oRNXRo0dFVAmCIAgpi1iukhksVpkorJgBePDgQbVr1y4trJgNWLRoUZU/f36V1VSqVEnHdNlfpHsoV66c6tKli5o4caJKBGbOnKmPvWXLlioZWLhwobr55ptV7dq19UxR4vBwFbdo0UI99dRT6q+//krY3//nn3/qY6XtOTFhwgTVrFkzT5JcXvw+MP8XBCE5EfOCELEbkEzrpFoAhAyDZ6xnAzZp0kRVq1ZN/83xLV26VH399df6deedd6qXX345pseXKiC6//e//6lPP/1U/79UqVKqadOm6rTTTtNifNGiRWr27Nlq0KBB6vPPP1ddu3ZVycTPP/+sevTooe+T1q1bq9KlS2sxxXkQBCH5EXElRASZ1o2wYiYgMwLj4UmcAf2aa67x/B+LGqLq9ddfV6+88oq6/PLLVcOGDWN6jMkObuJ27dqpuXPnalExfPhw1blzZ69tuC5Ue3jooYe0BSgRKVu2rFq5cqUuOu7Ll19+qc8Dv+/pp5/OsJ7PCYKQvITlFpQEooLBZFnHDRjPaRaI/XrxxRe1a8a4aoTMBWsUwgpL5g8//JBBWJnr0qtXL21ZxEWYiCCqatSooapWrZphnXF3Vq9e3fGzfI6XIAgpLq7Wr1+vX0888UTmHpEQMYjf9bsOZsq+cW/s27fPI7ARUwirRChjQ0oIM8ht3749w/pp06ap/v37q3POOUcVK1bME6t16aWXqh9//NFxn48//rg+B7zv3LlT3Xrrrap8+fI6poh39sfsSX988MEH2oJGfFqRIkVU+/bt1Zw5c4L+FtxpvXv3VmXKlPHEL11yySXqu+++c9weKx7H+d5776nVq1fr38Rn0tLS9Pd/9dVXXvFRCKHixYurfPnyqfPPPz/sep+0kddee03//dhjj6nKlSsHFen16tULad+RXCfa7VtvvaXdxYg9BBG//+yzz9b78rWabd26Vd1+++3qjDPO0O2G68P1bNOmjRo8eHDQmCvTLkaNGqX/369fP098lT2OLFDMFVa9d955R29P2+B3ch6JXdu4cWOG7e1xarhjOe81a9bUx+4vHkwQhDhxC1asWDFzj0RwJTv7YbKz/yeZs7tkTWL2H7MByWEFWKoSDbLFQ8mSJTOsu+mmm/SgRdA1gzBWlVWrVqnRo0ercePGqc8++0zHzzjB5+rXr69dQHz28OHD2lqDGxKxwt++biMG7yFDhugJAMQhIZR++eUXPTgy4Pvj7bff1seKYECQsP2GDRt0sD4vBnZ/CX5/+uknddttt2kxglDgc/Pnz1fdunXTv5PfjGirU6eOXs/vX7BggRZ9M2bM0McZCmzLuWawv/rqq5WbRHKdcBMjdBBK/AaE4549e9S6dev0NeK3GgGybds21aBBA107tUKFCvq38zn+TwzVkiVL1D333BPwGBF+ffv21Za7P/74wysGMBRLFeIUgYtgQniee+65+piXL1+u3atjxozRQtpJkNL2aBMrVqxQzZs31wJy9+7dYZ5lQRBcwRKynH/++Qfzj34PxqFDh6wVK1bo90AcOXLEOnjosLV03XbryJ+LTr4OHdTLjx07lmFbf6+jR496tktPT7f27Nlj/fnnn/q1ceNGa9++fY7bAv8PZb+ZQcWKFfU5HTVqVIZ1nL8cOXLo9T/++GOG9ePHj9e/02l5zpw5raJFi1oHDx70Wjdw4EC9P17XXHONdfjwYc+6v/76yypbtqxe98knn3h9buLEiXp5WlqaNXv2bK91zzzzjGefLVq08Fr3yy+/6GPJli2b9cEHH3it++abb6zcuXPrz3377bde6/r27evZ51NPPaWvqWHIkCF6ebly5azTTz89w37vuOMOvb5t27ZWqDz66KP6M1WqVLEiYcaMGY6/P5LrtGHDBs/v27p1q2O7YBvDE088obe/4YYbvM4T0H6nTZvmtWz9+vV6e9qeL+a8O7VHMNfElyuuuEIv79Spk7V9+3avda+88opeV716dev48eMZzhmvs846y/G3CoJghTyeujF+S0B7kvDss896/j7l6PlG/4tL7IorrvAsxb2BpcWfhRJXkkkKirWEJ2InsLhcf/31nv8PGzZMz9BzgqfvW265RWUlHAvWIyxFWN0eeeQRbZnwxd9MNZYTF8SMNywyHTt2zLANliB+t909atyCDzzwgHZlEURvePXVV/U7ViSm6dt58MEHtRUGK4kvuNpwF3Xv3l1dddVVXuuo9XnDDTdoSwzxZRdeeKFj2SqCq+2uKNxMWLs2bdqkf6fvfjlfHC+z+mgvToHbvuAiBVxvbhPudTIuYCyLTrP0cJ3ZMdtjsfJ12fHbsXJlJgS58xu4rz755JMMFuI77rhDW62++eYbNXnyZNWpU6cM+6ANyIxEQYg9Iq6EoG7ARIIYF152SA/x0UcfqT59+vj9HK6fSZMmaTcToswkRP3tt9/0O/FKTuKKAdcpr5cZuDdv3uxZxj5xF8GVV17peBy40pzElcmPZJ8Jaee6667TAytxW/YSRHYB5isYcKsRy4ObzOm3EVNHzA/rcS/Fw6AdznXCDYdAQYwwY48HjEAxYAjQN954Q4tijEsXXXSRds1lFRwn38u18ud6x+3HdvPmzcsgrhC0voJdEITYIOIqScDqcSI9XR3dtlrly3b05MKSdZTKnkPH9tgJFDdiBmAsVwzQBGqbAsz+tjWwrb8ZpVk1m9Ae44IVBbFBHAtWGix4DKC+MEmDwdefNc8es+ULsTlOmNmJdqsfAsX8398g72+5EWn+1psZa+yf7/G1HPk7TiMe/K1nkEdc+bNeOlkogTJIbhPudeLYibdCbGOF40VqiPPOO09bpxBbdvGE5Q7L0Mcff6xjt2j/tWrV0rFaPXv21PmqMhPiwGDkyJH6FYqF0I4ErwtC/CDiKklAAJ04cVzly52uL6uVM5/KlievY4Z2J7GEKLILoNNPP11v5yvMAhGK2yir81xh3SBoG3cRAdsE+9otTQRC4xpjkMXywwCKW4bZcpwPXGm4XP2JxnDOTywJdpxu/Q4CsIGZxYg8rF9uEOl1QiS1bdtWJ5FFaDPBgPxavJhVh5iqW7eu5xxg4WRfWMfYltebb76pX8zK5HOZlSiXBxoTFE8weiAaN26cYRnnQhCE+EDEVZKSXrSayhGitci4AY2gAmZJJQNkBCcDOC4iZsiRoR0LhoEYJ8AiQtySL7///rtrx2JSVxw5ckRP42fWmy/+EmqSsJLZZ1g3mNHnz+rBdcOVFytatWqlLUZYC0k3QQJXN4jmOtEGsEqZmDJmHBITRxoKYt9mzZrltT3WKl733nuvFmvff/+9tnKRI43f5Ot2dgti9Yz1FQEpCELikhiP3UKmwMCxf/9+XY6EOB1/rq9EB1eVEVQE89vzT+Hy8pdqBNeWv/xRkUCMEwMn4Hpy4sMPP3RcbnIkka/KiXfffVe/E3MTy6LZuEMHDBig/37yySe1BSsQtD8SiQbDzeuEiDH5+pzi2+xgFSOuzkwICbZ9NBBrBVjZQnXDCoIQn4i4SlEQUwxYRlDF2uKR2TBTkbgi3IQvvfRShsBzEk1iwTOwHfmK/M1+jBRmfMHQoUN1ULKdF154QeejcoIZj4gmyqrgurLz7bffqhEjRui/g+Vhygpwt11wwQVaxBKv5JQVn/aHiw03oq/lyIlIrhOiDaulKdNkxxyTXaxhlSKXlS9Y4cyEgszM90fuKtyYWNaYFepkxaTsFMLcKRmuIAjxg7gFUxDcUrgBTYwHbhPikOK1hI0b4I4jZufaa6/VaQ1wVyEmETsMqszAqlKlig52JmCaAZ9zwvbGKuQGxO0Q+E/6BqxMJHskyJokokzFR0SZDOd2iAviMwTm496iTqJxdSLSsELy+5jhFmtwLU+dOlXPYMSdR1JMfiNCCssWsVhkVEfcm+zjwYjkOnFuLrvsMh2LRDoGLFbMLiQhJ7MKOU4ErT2uC6FGLBdxT7jJuU+Iu0K84Y61px7JDAjAR5SSauHMM8/UsVecH64vYmvZsmVaXNJWnBLiCoIQHySl5YosxrhR6Bwp80EHRScaaJZRIHiaJY8OnRkWHjo7YjYyY0ZUZkPHzOCGsMISgsuMc5TMwsqe5oBYGiwR5IMCriUWDtI0EKhMpnMGMHJTsdzEwbgJ8TQIASwVZEFHMCA+KDXjL5cTEGuEkGLmGikJEC6kJCD1ANYrf9nZYwGB51iNyALPcVN6hnxZHDP3E0KF+CniyLp06RJ0f5FcJwTYc889p+PAOF+42zhPZhYsgpZZg4a7775bizhyl2FBpB/hnTaDpZFrldnVCdg/x0ieKwLxqVGIhY+4Lyxw/H7+71TPUBCE+CEbmURVEkHnyJM/woEZRXTydEzGRUHHFc6smrFjx+oOnCdearHRyS9evFgHECO2yFtkpv6HCq44rEU8DZsp+/4g9oK4Fb43WJA5swVzbF9+8u+SdVWOHBkNk1xunsYRUxxDosx2EwRBEIRoCGc8jXb8TqqRlXgUhBWCiszcuCa++OILPZMItwpC6NFHHw15fzzt4iZAWBHTQtFcnsbXrFmjk0AS90Cgazzo00BFm3EDGhcgogqLHpYEEVaCIAiC4D5JNbo+88wz+p0My8RYGIoVK6YzLxuXTKhBypT+oMo85nn79G/cCuS9Qb0SO4I1LG6KNqtTRZsRXLjAcAPym40IRGClghtQEARBEGJB0ogrMlgjdMBeR8+AS5C4DKw4xLiEArEN/vaHdYxAXRMIG29gqUJUIa5AxJQgCIIgZA1JI65MrhxmgPmbfWSK9oaSVwdRsnbtWq/PRbO/rOSwyq127tqtg9cRVbgAeYnAEgRBEITMJ2lSMZhkhf5qpIGZURQssSHYc8z422c4+8t8LJVdpat/VZrarwpgutJB/cRXxUNZGkEQBEFIFZJGXBn3F2kF/GGKtIaSidzsL9A+Q90frkhehkzJhG6lqzOzb1I71clabvnz51OFCslsQEEQBEHIamTkzQIoKEvwu3llRu4kyKHS1enqH1U4x2FV+DSZDSgIgiAIsSBpRl+T3I/yEIHqmEGw3FL2/QXaZ6j7e/DBB/VsPfOivEW4BEv3kD17Dp3bKmfJM1W+EpWJYA/7OwRBEAQhWbGyMG1S0rgFK1WqpN8DCRezzmwbCHsNMbIkkycr0v1R4oNXJBjrE7XYAkGwulPSUEEQBEEQlGcczQqvTtJYriglAqQf8BdgTmZ1sOfA8gfWKJN53Xwumv1FCsHo5NVyKj4rCIIgCEJoEEvNmJoVk7ySRlxRD4zyNEBdLl/Izo6lCQsStdhCoVu3bn73h0twwoQJ+m8q2GcWWKQoTIs7MZj1ShAEQRCEjGCgYDIZIT9ZkZYoqWoLUv4GQcQsvlmzZnksSlizKN66fPlyXZx18ODBXolCiYkqW7asLpzrW/6mevXqOkv7W2+9pa6//nq9HJHTr18/9eGHH2pBR6mdcC5WOLUFgXxVpIYgtQJ5vBCIkrNKEARBEPyDvGG8xmLFuMvYyYQyvEGREur4nVTiCm6//XY1ZMgQbfZr06aNTqOAaKJwc5MmTdR3333nVbj5vffe00KJGCt7bivDmDFjdOFmLlDjxo11fBWZ4LOqcLMBgbdr166AAfuCIAiCIHiDHsBiRSm8aIRVOON30kVAU7gZETVs2DA1b948dezYMVW1alVdb/DOO+9UuXPnDmt/vXr1UlWqVNF1C+fMmaOzsZcuXVrdeuutugg0AisrwDVIMlOKSPMSBEEQBCEwBK8jrrLa25N0lqtEIBLLlSAIgiAIiTF+J01AuyAIgiAIQjwg4koQBEEQBMFFRFwJgiAIgiC4iIgrQRAEQRAEFxFxJQiCIAiC4CIirgRBEARBEFxExJUgCIIgCIKLJF0S0UTApBYjX4YgCIIgCImBGbeDpQgVcRUDqHME1DgSBEEQBCHxxnGSifpDMrTHgPT0dF0U2u3q3ChqBNvGjRsl83smI+c6a5DznDXIec4a5Dwn/nlGMiGsypQpo0vr+EMsVzGAC1KuXLlM2z+NSW7crEHOddYg5zlrkPOcNch5TuzzHMhiZZCAdkEQBEEQBBcRcSUIgiAIguAiIq6SiDx58qiBAwfqdyFzkXOdNch5zhrkPGcNcp5T5zxLQLsgCIIgCIKLiOVKEARBEATBRURcCYIgCIIguIiIK0EQBEEQBBcRcRXHjBkzRrVs2VKdfvrpKi0tTZ199tnqhRdeUMeOHYtof0uWLFG9evVSJUuWVHnz5lWVK1dW/fv3Vzt27FCpjFvneenSperZZ59Vbdq00ec4V65cep/NmjVTw4YNi/i6JQtut2c733zzjU7Iy6tt27Yq1cmMc/3VV1+pzp07q1KlSqncuXOrEiVKqAsuuEA9+eSTKlVx8zwfOHBA9x8NGjTQuZnoPzjXnTp1Ul9//bVKRVavXq2GDh2qrrnmGlW3bl2VM2dOfY8/9dRTUe132rRpqmPHjqpYsWIqX758qkaNGurhhx9W+/fvdzXbqBCH3H777Uw0sHLmzGlddNFFVvfu3a3ChQvrZU2bNrUOHjwY1v7GjBmj98XnGzZsaPXu3duqUqWK/n/JkiWt33//3UpF3DrPx44d05/hVaBAAatVq1bWZZddpveRI0cOvbxRo0bW33//baUibrdnO3v27LHKlCljZcuWTe+vTZs2Virj9rk+cuSI1atXL/35fPnyWa1bt7Yuv/xy3cZLlChhFS1a1EpF3DzPu3btsmrVquXpP9gffXT9+vU9/cqAAQOsVD3Hyuc1aNCgiPf58ssv633QXzRv3ly37VKlSullZ555prVz505Xjl3EVRwyfvx4z022ZMkSz3Iuet26dfW6u+++O+T9bd682cqfP7/+3IgRIzzLjx8/bl155ZUewZWenm6lEm6eZ8TVueeea40ePdo6fPiw17pffvnFKl26tN5fv379rFTD7fbsS58+fbSAvfnmm1NeXGXGub766qv157p27Zph4Dlx4oQ1f/58K9Vw+zwjnPgMfcju3bu91k2aNMnzYJxq5/rtt9+27rnnHuvjjz+2Vq5caV111VVRiauffvpJiyr6i2+++caz/MCBA7rfYN89evRw5dhFXMUhCB0u8lNPPZVh3Zw5c/S6PHnyWHv37g1pf/fee6/+TNu2bTOs27dvn3Xaaafp9VOmTLFSCbfPcyA+/PBDz5P/0aNHrVQiM8/zuHHj9Odp46NGjUp5ceX2uZ42bZr+TJ06dVKu3Wbleeb88hkezpy48MIL9XqsLqlM3759oxJXxgL7v//9L8O6P//808qePbtej5CLFom5ijM2b96sfvzxR/33FVdckWF906ZNdUHKI0eO6DiTUBg/frzf/RUoUEDHUcC4ceNUqpAZ5zkQ9erV0++HDh1Su3btUqlCZp5nzuNNN92kzjzzzJSO+8nMc028C9xxxx06BkjInPNMDGwoECMkRMbRo0fVpEmT/F63ihUrqiZNmniNmdEg4irOICgaihQpogPOnSDg0b5tIKjevXbtWq/PRbO/ZMHt8xyM33//Xb8TCMx3pgqZeZ5vvvlmLbBGjhwZ8uCUzLh9rk+cOKGmT5+u/27evLnatm2bevXVV/V5R2y9//777gYAp3Cb7tChg35//vnn1Z49e7zWIdBmzJihg9vNg7AQPmvWrFEHDx7MsrEwZ9R7EFxl/fr1+r1ChQp+t+GpyL5tIP7880/P3/72Gc7+kgW3z3MgcL8zgwiY+ZNKpS8y6zx/9tlnauzYser222/3PG2mOm6f63Xr1nnE04IFC9Qtt9ySQUzde++9+lq0bt1apQqZ0abvv/9+tWjRIjV16lSPBaVw4cL6wZhZ3vyfh4jTTjvNpV+Reqz/71pwXgsWLJjpY6FYruIMLE3AtF5/4MqDf//9N+T9BdpnOPtLFtw+z4F44okn1Pz58/X+nnvuOZVKZMZ5xoJy6623qqpVq6pnnnnGpSNNfNw+17t37/b8fd1116lzzz1Xu8P4np9//llPZd+5c6fq0qWLxzKbCmRGm2ZfEyZMUPfcc49OyYDI+vzzz7WwKlq0qE4vUrZsWZd+QWqyLwv7fBBxJQiZyAcffKDjgbJnz67effddVb169VgfUsJzww03qL///lu98847Kn/+/LE+nKTFXnaWgZ0BH7cJAxD5nMi9VKdOHW3NSrWHBrfZunWrtk4R40YOJ2M1xJqFqOUBjVgu+8OyEN+IuIozjLmSpxd/GNM8ieZC3V+gfYazv2TB7fPsL8Hgtddeq/9+++23dQLXVMPt80ycD0/4BLKTvFHImr6DJI6+7uwcOXKoG2+80ZOUMVXIjL6jb9++2io4aNAg9dBDD+lYLiwsDRs2VBMnTtQJNJctW6YGDx7s0q9IPQpmQZ9vR2Ku4oxKlSrp940bN/rdxqwz2wYC/73hr7/+0jdpNPtLFtw+z74w85IZKenp6WrEiBEekZVquH2ezSweBiJfcYW7EHClmHXEAxEInAq4fa7ZhmzYWLCqVKniuI1ZjuUlVXD7PDP78LvvvtN/X3755RnWM0uzZ8+eavny5VrEYsUSwsdci71792oLoFPclZtjoViu4gwzZZ94B39BdYsXL9bv9evXD7o/FHi1atW8PhfN/pIFt8+znS+//FJddtllerbVm2++qa6//nqVqmTWeeYzs2bN8npRKsN0nmbZ4cOHVarg9rnG/UeaC/CXPsQsN7EqqYDb55mHXoM/i4kJZPedSSiEDm3ZhBFkxVgo4irOKFeunDYFwyeffJJh/dy5c7W6xkRPQGkodOvWze/+MIPiZoHu3burVCEzzjNwLnv37q2OHz+uhZVxm6Qqbp9nhOt/yY8zvEaNGqW3obajWZZK1tjMaNPGle3P7WcsLo0aNVKpgtvn2R6ovnDhQsdtmK0J/lI/CMEhDc7FF1/s97pt2LBBzZs3z2vMjIqo05AKWVZagfpT/korkKmaukjU/QpU/uatt97yKn9jyglI+ZvozzNlKnLnzq3LK9jLDKU6bp9nf0iGdvfPNeVcTj/9dP254cOHe6379NNPPfUcafuphNvn2WR8r1mzprV+/foM1R3MeebvVKZvCBnahw4dqs8zY5svXCtT/mby5Mme5VL+JoUwtaZy5cpltW/fXl9wUxS0SZMmGYqCmoGlYsWKjvujrIIpINy4cWPr0ksvlcLNLp7n7du363IXrCtXrpzuBPy93CoMmsrt2QkRV5lzrr/99lsrb968epvatWtbPXv2tOrVq+cpovvoo49aqYib53n58uVWsWLF9HrOdcuWLfV55nyb80wd2FR7AF6yZIker8zLnCP6WPvyLVu2eD4zcOBAvU2LFi2CFm7mPFMg29R+lcLNKcLnn3+uq3YXKlRI16Sj/tRzzz2nq9T7EspgtHjxYl25vXjx4trCwra33nqrtW3bNiuVceM887TpVL3d6eX7ZJoquN2e/X0m1cVVZpzr1atX6weDsmXLajFRtGhRq2PHjtbUqVOtVMbN80w/fP/991tnnXWWlZaWpos101e3a9dOf08qMmPGjLD71GDiCr777jstiIsUKaIfiqtXr249+OCD1r///uvasWfjn+idi4IgCIIgCAJIQLsgCIIgCIKLiLgSBEEQBEFwERFXgiAIgiAILiLiShAEQRAEwUVEXAmCIAiCILiIiCtBEARBEAQXEXElCIIgCILgIiKuBEEQBEEQXETElSDEAe+9957Kli2bfl1zzTWxPhwhCigWba7ln3/+6dp+aRdmv7QXQRDiFxFXQkrSsmVLz0AVzmvmzJmxPvSE5vHHHw94fvPly6fKlCmjWrdurR577DG1fv36WB+yEAcPHE6vPHnyqBIlSqiGDRuqW265Rc2ePTvWhywIHkRcCYIQNxw+fFht3bpVzZgxQw0aNEhVq1ZN3XPPPero0aMqmRArVPTQJnbu3KkWL16s3nzzTdWiRQvVqlUrtXHjxiw/Frmegi85MywRhBSDJ99GjRqFtG3ZsmUz/XhSBSxU3bp181p24MABtXLlSrVo0SKKyqv09HT10ksvacH10Ucf6cFLSD0KFiyorr766gxCfMOGDeqHH35Qhw4d0suwLGP1XLBggSpatGiMjlYQRFwJgurYsaN2VwlZS/Xq1dXrr7/uuG758uXq8ssvV7/99pv+/yeffKK6du2qevXqpeIdN+Os7GARSVWrSJEiRfy2ld27d2u34OjRo/X/165dq+/noUOHZvFRCsIpxC0oCELcUbduXTV16lR12mmneZa98sorMT0mIT7BQoX4xgJtGDVqlDp27FhMj0tIbURcCYIQl+CCtc+cxFX477//xvSYhPgkR44c6rbbbvNyLy9ZsiSmxySkNiKuBCFCduzYoZ+Q+/btq+rVq6ddF7ly5VKFCxdWNWrUUP369dPWF7f58ccf9UBSv359dfrpp6ucOXPqWXalS5dW5513nrr55pu1i4QBJhhsQzDwJZdcoipWrKjy58+v41tw2V177bXq+++/V7Hkggsu8Px94sQJ9ddffzluh/vw3nvv1dehWLFieiYZMV3MCn3++ee16yhU+M3XXXedtp5xLTm/nJdy5cqpZs2aqTvuuENNnDjRb5B9oFQMZt3777/vWUY7cZoN5+uqDhQ0PW7cOM+6M888M+TfumnTJi1M+By/c9u2bX63xRL04Ycfqt69e6sqVarodpKWlqYqV66sXbjjx4/XcXKx4pxzzvH6/5YtWwJuT2wf1tDu3bvrc8bv4f4tXry4atCggbrzzjvVihUrAu4jmuuZSOdWiABLEFKQFi1a0FPp18CBA8P+/GuvvWblyJHDs49Ar9atW1u7du0KuL9Ro0Z5tu/bt6/jNseOHbNuuOGGkL6T18MPPxzwO0ePHm2VKlUq6H46depk7d2713IDzrXZL9cgGN9++63Xsfzwww8Zzkn//v2DXovChQtb7733XsDv2r9/v9W5c+eQz+/bb7/tuJ+KFSt6tlm/fr3fdcFevu2SdmHW0V7sHD58WP9Gs37RokVWKDz//POez1x00UV+t5sxY4ZVtWrVoMd83nnnWZs2bbLcwH5PcN6CsWbNGq9j+fjjj/1u26tXr5CuQbZs2aw77rjDOn78uON+ormesTy3QuYjAe2CEAE8FWNJAZ40a9asqZ948+bNq/bu3asDsk0wNpaQtm3b6hlMWFQiBcvMW2+95eU2Y5Yj38usOqwzPGmvXr066L54Yr/77rs9T8OFChVS559/vrbO8Ls4dqa4sx4rDRYgZmVhwclK/v77b6//22Ow+M09evRQX3/9tWcZ1kOOlXem5JPSAQsT1wTLD++3336743ddeeWVXvsiDYSxSGJZYNo/1zWagHWsnFyn6dOnq1WrVullbdq00ZZOX0KdwQq0K4L93377bf3/jz/+2CsGyR9sZ7jqqqsctxkzZozq06ePJ4YJKykWUqw22bNnV2vWrFHz589Xx48f122cdoR1tWTJkior8bVUBfp+YwHFWlerVi1tqcVKiRUPizTHv3nzZt3+X331VXXkyBH1xhtvuH49E+XcChGQBQJOEJLOcjVy5Ehr6NChAZ8kly1bZjVo0MDzPYMGDYrYcoXlK2fOnHo9VhqsMOnp6Y772rJlizVkyBDrnXfecVw/bdo0K3v27HpfuXPntp577jnrwIEDGbZbunSpVatWLc9x3XzzzVZWW64GDBjg2Z7f/c8//zhaXXg98MAD1pEjR7w+v3XrVm2RMdtwDhcsWJDhe37++WfPNgUKFLC++eYbv8f0xx9/WE899ZT19ddfh225CsUK5Y9gn5k1a5ZnfcmSJf1aWwzLly/3bJ+WlqYtd778+uuvVr58+TxWnHvuucf6+++/Hc9J06ZNPfvr0KGDldWWqwcffNCzfa5cuaw9e/b43Za2guXW3p7scG9xfYsXL+7Z55w5c/zuL5LrGctzK2Q+Iq4EK9XFVcOGDa1bb7016CsSkzzuNON6K126tN8BL5i4mjBhgmd9nz59rEg5ceKEVb16dc++xo0bF3B7xAkDtRmwNm7caGWVuOJ8n3baaV5uEQODIiLIrGNg8gcuM66x2bZVq1YZtkEoh+pODUasxBWCwP7dU6ZMCbi/+++/37PtlVde6bgNLm2zzcsvvxxwf4gzuxh3ErGZJa5WrFhhFSxY0LP9FVdcYbkBv8Hss3fv3n63i+R6xvLcCpmPBLQLKQ9m9mHDhgV94RYKF9xYJlEmiTCDBcj6wz5LDjdgpEyYMEH9/vvv+m/yRvkm8fSlVKlSOoAbcF2YXEKZza+//qratWun/vnnH88yAowNTL3fv3+//hsXyZNPPhnQZWbPkYSr0Nd16tb5jSUETeNiMpB01R88WHMO7S5RX5YtW+aZ0IB71LQDfxCA/eijjzq6HDMDXHW4zV588UU98WHfvn16OS65l19+2ZXvaNy4sXb5A64/t4j3cytEj8RcCUKUEKNBPASzj4gRYgaefWYPsUuGn3/+Wc9CC5fy5ct7zQx78MEHdV21cPnmm288f19xxRUhfYaM14a5c+equ+66S7kBIs8+fR4OHjyoBajJ0G5gFpU9gah9FiOzqYhVCQTxLpx3YqaMwLLPqrOf3w8++EBdf/31WR5f5gaIpGeeeUb//eWXX+rz6fQ7qMNnysQgoIkJDNRWOMehZMf3bStuQSb2YN9PjBIPDDwIhROThEDjHv3jjz+0mEe02dueEfjEVnHO7G0lUuLp3AqZg4grIeUZOHBgRBnaEQH333+/mjx5sie4PRi7du2K4AiVDnKlU6dzJxi3du3aeso3KRR4us6dO3dI+yE41vDFF1+oWbNmBf2M3XrkZt02ApAZCAPBoEMA+nPPPec1AC1dutQxXUMgmjRp4hFXP/30U4Ys/VgHEMasw/pBOoaLL75YWxYIdE4EsLKQooPfgGUPgeUkou1WLQZ3p99nbyuIUQROMOyiJKtr/HXu3FmNHDlSB6aHwqRJk7Q1yN6WQrl/3RBXiXZuhfARcSUIEUD+qi5duuin3HAwrotwIf8OeXA6deqkB006edwhvJihSF6e5s2ba5GA2PD3JGyfUfX5559HPXvPbfgtJk9Y06ZNtYBkNqYvdhct+blCgRlY/kQuWb7feecdXb8O9yeDF4KbV4ECBbSApTAwYtY3n1I8Wq+MeMR95CuuaLNjx4712j5YW+EBIpZtxbe2ILPnOD6EEbm6ACG5bt067b4j11kguK5PPPFE2McR6f0bz+dWyBwk5koQwoSB/dJLL/UIKwb3Z599Vpvq6TRxxZAm4L8JI9oyZmB5pDC4E6vBIGN3g1HAlu/GHYQgQZgw0ASzQkUCg5pb8HvMOTIvCvASm8bT/KBBgxyFFZh4K8DiFAr27ZwGycsuu0y7I4lDQ8zav4sB+7HHHtNWLITsnDlzVLxit0R9++23GWIFsdiQkgJIQ4ClKzPaSqjW3HBqC5rX8OHDddqM9evXa2sVohx++eWXDAWeffnuu++8hBXpDUhxglBDdHM/2dsk7dSN+zdez62QOYi4EoQwIZeQ6RzPPvts3aE/8MAD2u1ElnSEj91y5NbTLiA2yAbNgDllyhT1yCOPqFatWnmJLWJIEAhOQb12gYF1w1fcBHtlVlHicMGaZAglE73vdlhCnMAqRUwbcXRfffWVzi3G4GsXW5RV4ZyToygescdQIYZ9LZT2YGh/VivftsI5CbetZEVGcfJUUUkAq6PdEmTPmO4L1l4DnyV/GzF2XHssmL656Ny8fxPp3ArRIeJKEMLEPmsIcUMCzkCEEk8RSefMbDqsOwR3E2zLYG8PlifonUSIduyBvoFKncQ79hl9/kri+GIXhsHcRrgmieF54YUX1Lx587RFg1JHFSpU8FgObrnlFm1pi0fsoskeX4XFCsuV0+xCXxKprfA7uF4GYqmwQPnCdTNxhgTAY3EOFkweavsKh0Q6t0JkiLgShCjiJYLN/KMz58k4s8Fy1bNnTzVz5kxPx01mct/ahsQOGbLiuDIL3HMGxE8o2Lfz5wrzBwKaDO8IWWPZQHDZA5PDIZTZYdGA5dJYRxYuXKhnwgGxVsadTYyeEYtOJFpbQQgbdygxc7gOfeGamZqQzLYNNuOWSSuhTEIJ93om2rkVwkfElSCECU+8BuKrAkHsU1Y+mRKbgnvSsH37dq/1BMQb3n33Xcen+0TAPi39s88+C/o7mGqP+9aAWy8Sqlatqmdq+ju/oWJihMCUPnEThBVpCXytV3YrViCXoG9bwXUV6W/NKkitQdyc3f3nO+HEfu+GYnWkqHlmXM9EO7dC+Ii4EoQwsQdZ22vR+UJclD3xZTTg9gsV+zRt3ydzavFRMw8IHMe1FWr8BoHdocY3ZTbMgDNxV/yOQDO/sFT079/fS1jZc1yFkyIDSyTfZ4gk1xgQ22Pwdd26hb1WIHFWtAvyWxkxYM8b5i83GHUajRBhf8bqEwy2i8WMNtz0RkBhYbbHYpnzbupTEjcZKBUJFqVQxVW41zMRz60QHiKuBCFMmI5vIGbDKRM2weLMMmJAC3U2WyCGDh2qA27p7P1ZwhA/Dz/8sM44D7hILrroIq9tWMY+jPuEOCJyOZEA1R8kPiWfF/l9mJ0VD+Cms2esJg8W//cdoLAIkDKDJK8mAJpr5guB67jJSCBqZtI5CVwCn4244hhCzbHlS506dTx/Ezgf6sAaDgS1E9xuErYi9I2QxnJiL4IdqN0ZEcssO84RbkZ/MJmCOEDSXsTC3cVMWRLOGp5//nmvc4vwIl2JAVcvM0R9oRIB2yGmQ7l/I7meiXZuhfCQPFeC8P/27h8nlSgKwLjEhMKO2FGhhY2JDSUrcAHWdEQjnWyAxBITOyOVnS0LILABEmwsXICbkOK+fDeBjDxlBryiJt8voXmRGefPc86cc++5a2o2mzs3Nzfxjx1lB946aYPAzEEyAizdMu/Kzr8x8JzxIF9FGwYyTZeXl7E8xR90BmZThuCBz5iibIsCZjB+1PCQhy4B1sXFRXx4MLuKmYdMyz85OYlBA+VOtsk+N1n2Zxs6nU5sQcGSPri+vo7HRWaqUqnEwJaWDtnSEKWi7HiXOYIO2ivwIfDkIU1DTrZDZoFsBA+07EOz1+vldob/zOnpafwu2yZ4ZV9kMhhIPx+/Q2C8HByvg+OgTHZ7e7toGvtRVmsV7rHHx8fYeoR7goc/DW25/xi3RhmakiyzKym7flcWbh0E2QRHtE3gHnh4eNhptVrvsluU6zn3THLgeJgRenR0FK8v4+jmLxEE0/w/z2u2u8n1/IvnVmvYwvqF0q9euJnFhNf18vISDg8PF9v46NNoNOLiw9nFij/bV97Czb1eb+W+sp9yuRy63W7uMYxGo3eLOOd9jo+Pw+vra9jWws1FzGaz0G63w+7u7srfnQWgVy2oyzaKngcWCO73+19auBl3d3ehVCp9up/le2WTxYEnk8l/293f3w9vb29hHU9PT6Ferxc+R7VaLUyn07CthZuXnZ2dLb57cHAQ75OswWAQ9vb2Vh5Dq9WKi35n/1aMx+Nk1/Mnz62+n5kraQO85dJ0kOVbGJDKQsC89VKGYQYhY4IoT6RaNuXq6iqOl6J8QIaKZVx462bBYUodvCHztsxAb5ooFulaToaHciBv8UzPp3RGyZFtsh4dsw7J4FD64s38N3Ymp8xHeeX8/DwO0KdNBtkKehPx5s91orxDBiI7LmYZ2yArOBwO43l4fn6OU/DZDvvguwxkJ/NA1mfTsVZZ/M7cK/f39zFrQWaCDEbKHkb1ej3eF9myL/dltm9XEWRgycbSlJT7hSweY5oooTJ7ktYYjGMjK0imlkzQd8+IzMteMTOSc0kWitUN6PY/R6mYDDO94DgmrjXXuVqtxgkhlAsp023jev61c6tiSkRYBX9WkiRJORzQLkmSlJDBlSRJUkIGV5IkSQkZXEmSJCVkcCVJkpSQwZUkSVJCBleSJEkJGVxJkiQlZHAlSZKUkMGVJElSQgZXkiRJCRlcSZIkJWRwJUmSlJDBlSRJUkIGV5IkSQkZXEmSJO2k8w9KIOU7NfdqhgAAAABJRU5ErkJggg==", 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", 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", 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ixeOjEc6UxKDClZK2MFjefffd4v8TDBzLbSg7WqjTTjsti++FjUYLhDUrEm1IigcvKDdiNRH+jvOUx7EDAiVY0GAFIpwSOpHgToToVW4EoRABxDrt+0PYeig/NWueCeTbEs49DsbNN98sn5i/gpm6+C3+QgOpG6wjPCk5nn322YQmdsRPi6hW+PTTTz191dCwkebBtgVqZ7oJlXjTPg++i4S1FgQNGwEXzfMIBBoi+35R1sddfsfCO8vv4tquvfbabH3PjTfe6NPseQnclPGxCWxJLuzvG4fplPXA/UcD6w8+a/Z9tpG0btatWxdyUnP55Zf7tMYEHii5iEQn2lKUREFiRV6BQoUKOX369HHefPNNZ/Hixc6WLVucbdu2OT/99JPz+OOPO2XKlPEl9CPRZ6BSGiNGjJBSHCTUZHEnowSSAdp9L7vsMmfevHnyPVwHiQ3z5s0r20jw6JW4lP25VvYhueGjjz4q18t3knSSUhs33nijc+6552YrEecDDzwg+1DmJFCywwIFCjgPPvigs2zZMmfr1q2SZPWcc86RbfXr1/d9jxu+M3/+/FJi6I033nAWLlwo93jDhg3Ot99+KyVaAiVa5B7axJL8rt9//93Zv3+/7x6Hm0SU++ku93LBBRc4X3/9tbNp0yb5HfPnz5dnS6JWr3v0xx9/OMcff7zv+JNOOskZOnSo8+OPP8rv2LFjh7N69WpnypQpzqBBg5xy5cr59uUexfp50G4qV64s2wsXLixlcn799VdZ/80332RqawMGDMhyfJ48eZx27do5L774orQr7sPmzZvlPpDole1eyTOhQYMGsq1Zs2ZSgmffvn2+50ES1mihJBDtjO+gNNBnn30m10Zb570J9rssdp9AyX25VkpNsU/BggUlySzPb926dc4rr7zilChRQrZRXihQAk/WH3vssbIf+7/66qtyPOfhfPY38D77t1UYOHCg3Mv//e9/zsyZM+VY2tHKlSudt956y2nYsKHvd/CsYnFvlfihwpWStlATjI41VIZkFoQDBjt/GFjq1KkTt9qCCARkhc5ubcHsDuZkEQ/2veeff77z+uuvBxSuwrnH7du3d3bt2hXwumJRW5BBKtR1BLpHDKYIglYIDrXUrFnTef/997OcJxbPI9raguFc/8knn+yZlT5YXc1YZW0fNWqUCI2BvocM7l4Ci//vC1Y5gQlJsLqOCK9MBILBdivkei2cn+/xAuEqnOfAb/3nn38iuHtKMqDClZLWIPCMHj3aueGGG5wzzjhDNA7MOBG6+LtFixbO3XffHbQ4KwMQs2iELPeA4NWxM/tk4ECzYL8LoaVNmzbO8OHDgw4Y7kGe2S6aGDRYXCsle7h+q8HIicEc7c2VV14pgwnXTQFphMV33nkny6DrX4oFDdVDDz0kwg1CR7FixXzXjUbrww8/DDgzZz1aQcrroMVyCzeRCFcWCuiikeF3cA2U5kGDcMUVV4j2L1ThXAr6or3j+zgHzxyNYoUKFeQa0UIiBAf6PbF6HoAwipaEtsC94blQ9JgBmaLTgUBDRRkg2iEaOTQvHFu+fHnn7LPPFi1MsLJPFHTmWdJ28+XLF3PhyhZWp71Vr15d7i/tDQHcS2DNjnAFe/bskfuHdol7QLtEe3nvvfeGXRCa/dif4zie85xyyilyXs4fCITjxx57TNo/fQf3kkkcx3MufjsaLSV3kod/Em2aVBRFURRFSRXUoV1RFEVRFCWGqHClKIqiKIoSQ46UTFcURVGUKCFFQqhM/YESmdoanoqSCqjmSlEURYkJFBem1E6kCwWjFSWVUOFKURRFURQlhmi0oKIoiqIoSgxRn6sEQGkKSkegDrelJBRFURRFSW7QR+3cuVNqzObNG9j4p8JVAkCwOvbYYxN9GYqiKIqiZAPqpVapUiXgdhWuEgAaK/twKASsKIqiKEry888//4hyxI7jgVDhKgFYUyCClQpXiqIoipK7COXSo9GCiqIoiqIoMUSFK0VRFEVRlBiiwpWiKIqiKEoMUeFKURRFURQlhqhwpSiKoiiKEkNUuFIURVEURYkhKSVcLV++3AwbNsxcdtllpmHDhiZ//vwSLvnII49Edd4pU6aYzp07mzJlypgiRYqYunXrmnvuucfs2rUrZteuKIqiKEpqkFJ5rl5++WXz/PPPx/Sczz77rLn11ltFSDvzzDNN+fLlzaxZs6SK+0cffWS++eYbEboURVEURVFSTnPVoEEDc/vtt5tRo0aZpUuXmksuuSSq8/3000/mtttuM/ny5TOTJk0yM2bMMKNHjza///67adeunWjKrr322phdv6IoiqIouZ+U0lxdeeWVmf4frKhiODz22GNSpLF///6mU6dOvvVFixY1r7/+uqlRo4Zor5YtWyamQkVRFEVRlJTSXMWSAwcOiLYKLrrooizbq1WrZpo3by5/jx8/Pu7XpyiKoihKcqLCVQBWrFhh9uzZI383adLEcx+7HvOhoiiKoihKypkFY8mqVavks2TJkgGrX1MZ272voiiKoiQFjmPMwT0J+FrH7D142CQDRYoeZfJE6R6UXVS4CsDOnTvls1ixYgH3KV68uHz+888/Qc+1f/9+WSyh9lcURVGUqASrNzoYs+b7uH91HvySTXKw5/Y/TdHiRyfku1W4igM4xj/00EOJvgxFURQll2qQItIIHdxjiiZAsEo0W0wpU9ZsN8mAClcBsKbA3bt3B9zHJhEtUaJE0HPdddddkivLrbmyJkVFURQleQWe6Mxcjin8TheTd9MikyiN0Cn7XjZ7TCETT+pWKGHevaKpycNFx4GDBw+Zr6dPN4sW/WL69OphqlY91mcWTBQqXAWgevXq8rljxw4xEXr5Xa1ZsybTvoEoVKiQLIqiKEruMpklk5krUn7ION5sM0z+Yy/l1K9Ywoy59nRPAapIgXySeDsebN261YwZM8Zs3rxZ/r99xz+mbv3EmALdqHAVgDp16kg+KyIG582bZ9q0aZNlH9ZD48aNE3CFiqIoKUgOOGJn0j4lwGT2S0Y10/vAA8aJs0bohAJFzZIcEnLiKUAF4ueff5aUSQcPHhT/6B49ekj+yWRAhasAFCxY0JxzzjkiEb/33ntZhKvVq1eb2bNny9/du3dP0FUqiqLkXrKY3BzHFHqns8m3dm5MvyeQ9ilck1m0Zq7jChQ182IgiCSDQJMseSg///xzs2DBAvn/cccdJ4KVDTJLBtJeuHrhhRdkadq0qXn77bczbRs0aJAZO3asGTlypOnZs6fp2LGjrEebdcUVV5jDhw/Les3OriiKEpkghYKq9/A5ZsmG/6Kni5p9Zknh2ApWwUxm5StUMWOuOyOk0KRCTXKxfPlyEax4Jq1atZK6v9FWZIk1KSVc/fjjj+b666/3/Z8agDBixAgzceJE33oyqlesWNFnr+VBVahQIcv5MPc9/fTT4ozeuXNneYjlypWTws0bNmwQ0+Hw4cPj8tsURVFSSZDyOMqMKfhQjjli+2ufMJlNKphfhaZcWkd43bp1otgI5fOcKFJKuCIK7/vvs9rS165dK4vFnXMqFLfccotp2LChCFlz586V6MGqVatKBCBLoASjiqIoqY5XJF14gpSfY/Q1p5k8e7eaos+vlnUZ5RuaWZf3NrEMN1PtU+42A06bNs20bNnSFClSRJ6jtSQlK3kc3g4l7kLg0Ucfbf7++++QaRwURVGSUaCKVIgKFGFWJH9ek2dkx8zRe3etM6ZQ8vjPKIlj48aN4p6zbds2U69ePdOnT59cMX6nlOZKURRFyTntVCQClacg5aU92r8rs2B17GnGFAxcGUNJn3Y3f/5888UXX4h/M4LMaaedZnILKlwpiqIo2dZOBcp3FJYZLiPDmBEt//v/7b8ZU6xMTM2BSu5j//795tNPPzW//PKL/L927dqmW7dukh4pt6DClaIoiuITqvYcOByRQJVtXyYkt1daGrP9SOCRqdBQBSvFEGRG+qO//vpLIgDbtWtnTj+dtpa72oUKV4qiKGlIJBF9/tqpqJzDbZLQA3uM2fhvWZhSNY25eqYKVoohGWhGRob4NfXq1ctUqVLF5EZUuFIURUkxQtXDi9TcF7NIu0ClZ66ZaUyS5SlS4hsNWKBAAWljRANedNFFEonP37kVFa4URVHS1Ok8mFBVtGCUApVXGRu0Vf6ClTqwpzXr1q2TaEASgdpScuSTzO2ocKUoipKLychwTJdh32RLmAo7oi8niiPjvF6wqDEFiqo5ME0nBN99952ZMmWKmAH5++STT066TOvZRYUrRVGUXGjaO7KPEcFq1dbdYUfxuYlakApUZNlLQ+WvrVLn9bRl79695uOPPzYrVqyQ/9evX9+ce+65KSNYgQpXiqIoSSY8Zce0d1yZYmbigBaxcToPBRd4YLcxJP+0TumhNFRuVFuVtqxZs0bMgCTjzJcvn+nQoYNp0qRJrosGDIUKV4qiKLnIlOcFWioEq7x54zBAhWPys6iGSnGBQPXWW29JUtBSpUqZ3r17e9b1TQVUuFIURYmzxipcwSoc0x7ENJrPy8wXzORHfqr+X3gLUKqhUlyQZb1FixZSyqZLly6mUKHYFeZONlS4UhRFiaPJjySdVrDyN+UltNhwJBopi2ZUV0KwevVqU7x4cVO6dGn5f6tWreQz1cyA/qhwpSiKEneTn2OKmP1m4jUtTLE8+wPvdtDEj1BO6P6oyU8JQkZGhvnmm2/M9OnTTfny5c0VV1xh8ufPn/JCVY4LVzt37jRr166VFPaHDh0yLVu66kcpiqKkqGDV7pkZntF7/+GYsQUfMk3yrjDmaZOceDmh+6MmPyUAu3btMuPHjzcrV6705a1C2Eon8sdaoBo+fLgZNWqUWbx4sajGAUkVAcvN5s2bzZAhQ+Tvhg0bmksuuSSWl6IoipIQX6pVW3eJVqp66WJmrJe/1ME9pujzR0LQkxLVSClRsGrVKjNu3DgRsMi63rlzZ8lflW7ETLiaMWOG6du3r9mwYYP83wpWgUCSnTp1qlmwYIEpWbKkOf/8803BggVjdTmKoihxg/5u2+4DZsmGv//TSqG8ejoGGqJ4oxopJRugmZo5c6bIAlC2bFmJBuQzHYmJcIVdtWPHjlIfiE4GTVW9evXMjh07fMKWF9dcc4259tprZb+vvvrKnHPOObG4HEVRlLg5qrtzUqGxEsEqHFRDpKTYu/Hbb7/J340aNTKdOnUSzVW6ErVwtW/fPnPBBReY/fuPOGX269fPPProo6ZixYpmwIAB5sUXXwx4bM+ePc31118vD4UU+CpcKYqSNMKTX1oC/nvx63PNso3ejuqUmC1q9oevlVINkZICWIUKCUF79eolSUIbNmyY6MvK/cLV66+/btavXy8397rrrjMvvPBC2McSmlm7dm1Jgf/jjz9GeymKoijZFqgyZ0V3OZ27GM8/hcM8MYKVFiRWUtgMOG3aNHl/2rdvL+tw8WFRYiBcffrpp/J51FFHmccffzzi46kptHz5cp86UVEUJbFpExxT2vwTvnkvkMkPzZSipGim9Y8++sj8+eef8v8TTzxR/KiVGApXixYtEq0VqRZIFBYppMAH/K4URVHiAbNtknlmLXrsmM+KPWLqH17qW7Nn4LJMglJYiT3V5KekKL/++qukWaD4MkFo5513ngpWOSFckcYeKleunK3jbSeVbjkwFEVJFm2VY+qVzn8kbcIh0iQszaSBKlqyggpKStpDPcCvv/7azJ49W/6PXzU+VlZBosRYuCpWrJhonZBis8PGjRvl06bGVxRFyUm/qszaqn81VbuXZk2boKVdFMX3/rz//vvm999/l/83bdrUnHXWWZJxXfEm6juD9EoW9iVLlmTrgX333XeivTruuOOivRRFURTPfqbX8Dlm/uq/3GuPaKuuOMkUG+rSVFk0TYKi+GCMxq+Kqitdu3aVVEtKDgtXZ555pghWRPv98ccfpnr16mEfi0Pc1q1b5cG1bt062ktRFEXJkosK3yp/wcqnrRpqvFMnqM+UkuZgBkRxUqZMGfk/wlWtWrVM0aIaqBEX4YoMrCNGjJAOjbxWNnowFKRvuOmmm+RvhKsLL7ww2ktRFCXNCVU0ed697U1Rs88UHeKnrVJNlaL4QKgaO3asRAWS6Bv3H1DBKnzymihp27atadWqlQhXn332mQhb1sk9EBMnTjSnnXaa+FshWOEUR0oGRVGUaIsmBxKsmlQ7xpQuVtAULZAvs7bq7vXGXP6FClaKYoxYolCYoAChJnCo8VzxJo8TqghgGGCHxcFt06ZN8v9ChQqZdu3ayfqff/5ZBCi0VAhTRBqwHvjqGjVqmHnz5qVV4jFmA0cffbT5+++/TYkSJRJ9OYqSco7qx5UpZiYOaJFJXpIUCvwx4kxjNi46shLBShN9KooIUl9++aX54Ycf5P9VqlQRxQdjlRL5+B0T4QqWLl0q5WyWLVt25MRBZoH2K0844QQzYcKEtHNmV+FKUaL3p8qcUf0/EKym3trK5M3r0Qcd2G3Mo5WO/F2hoTHXzFKNlZL2oJ3CDGij95s3b27atGkjJW2U7I3fMYujJHoADdTTTz8t9QQ3b94ccF+0VDfffLO57bbbfLZcRVGUUEk/vYQpN/UrlhCNladg5U9/NQUqCnz77bciWOFT1a1bNylLp0RHzDRX/upFBK05c+aI3RYJDyGqfPnyplmzZiIVk9k1XVHNlaLETqhCoBpDAtA8IbKn09Xt3mrMkFpH/q8mQUUR9u/fbz7//HPxodYxKcnMgkr4qHClKNkXqtzCVNjlaOjm3uhgzJrv/1unwpWSppAC6aeffpKCyyHfHSWxZkFFUZSc9KWyQlXRgmEIU/+d2JiDe4w5sCezYKWFlZU0hSCzSZMmmYMHD4qLzqmnnproS0pJohauUCNC9+7dJc9VpAwfPtyMHj1aOsupU6dGezmKoqSo2S9socoKVHyO7PhfZKBFy9ooaciBAwfE9LdgwQL5Pwm/69atm+jLSlmiFq6mT58uHV6DBg2ydTy1iuw5FEVJ97I0MdBU+Zv/3GiyUCUNIcCMaMAtW7bIu0RuSqqr5M0bdapLJQBqFlQUJSH4l6XJli+VV6oFf8GKlAs2MlDL2ihpxi+//GI+/vhjCTQrXry4pEyKpEydkkuFq4yMDPnUfBqKkn5JP91lacieHpUG25oB/WsFqkClpDE4XVMnsGbNmuK+o+mP0kS42rBhg3wiUSuKkp7RfzERrEizYP2r0Fap+U9J49QKVEqBY4891lx++eWmcuXK6n6TLsIVZXC++OILeeCUwVEUJb2KKdukn1ELVv5+VpogVEnTScz8+fPN119/bS677DJTrlw5XykbJYmFK6TfQBDpF2y7G0JA161bZ77//nuzd+9e6VhJta8oSuppq9w1/8JO+mkj/sLBK82C5q9S0lBb9emnn4qPFSBkderUKdGXlbZElESUyAL/jtAent2ZJ8djE164cKGpWrWqSQc0iaiSFtqqobPMqo1bfOuqly5mxoYT/RcohUI4aJoFJQ3BvYZowO3bt8s4TYqkM844Q82AuSmJaCBZLLuJ3mkAzz//fNoIVoqSDoJVu6enm6d2/p9pUnjFfxtQXj2dg1+saRaUNINx94cffjBffvmlOK0z6BMNiJ+VklgiEq5GjhyZ5cFiCkQ6bteunenbt2/Ic7Bv4cKFTenSpSU3FvUGFUVJDegTMANu3LY9s2CVHdwpFMJBowKVNAMTIIlBoU6dOqZr166mSJEiib4sJVLhql+/flnWWT8rMr16bVcUJX0Eq227D4jjeqbu3aZEiBQVlhQlKPXr15eM67Vq1TLNmjVTM2AqRQteeuml8kBPO+202FyRoii52scKwaqo2f/fRgQrdTBXlJhMYKgNiNUnf/784l+FxUiFqhQUrt58883YXImiKLk3IejQWVl9rBRFiRlE1pNpfcWKFWb9+vWmc+fOsl4Fq+Qk4UlEFUVJPIcPGzNrFlFHxlSsaMyZZ1I1IfCG/3JX/W2KmP2iqfIUrHAyx7ynKEq2WbNmjUQDEqlGNZMyZcok+pKUEKhwpShpzrhxxgwcSFLf/9aRc3DMhePMae8f2UAs8N4ChYypVNk4Tz1luqwuZVZt3WXGFnzINMnrJ1S5fazUb0pRotIOz549W/JI8nepUqVMr169TEUmOkp6CVc0gCVLloiT3datW83OnTt99QNDcf/998f6chRFCSFY9ep1JLWUm6Zrx5mmT/UyGcYxewsUNr37PmGWlK95ZON8/tl9RFvlL1hpOgRFiQl79uwx48ePN7/99pv8Hz+rLl26+MraKGkiXJF1/amnnjIvvfSSr15gpKhwpSjxA4sfGqv/BCvH5Clw2OQ1h81j5g6z2xQy54tQVUNMf0XMPt+xiE5fFb3XGDtv0iLJihJTDhw4ICXicFzv2LGjady4sfpXpZtwRVbYs846S7RV4SQTpYH47xfLRjNmzBjz4osvSlQFDZQwVSIqbrnlFlOgQIGIzrV7924zdOhQ89FHH4kjIU6F5Ohq0qSJufrqq815550Xs+tWlHiCK9V/pkDHlO87xxSu8pf872wz1Lfe0/QHVrDSIsmKEhMYF+1YWLJkSUkIetRRR2k+yHQVrvr06WN++ukn+btChQqme/fuZt68eZI5loaCRgrz4OrVq823335rNm7cKOuLFStmbrjhBkkqGituvvlmyfiOtE8JgOLFi0sRyzvvvFPqLpHJNtwka9u2bTMtW7YUMyfnIZs8DR417aRJk2S56aab5PsUJbfhVjCjsbKClRtP058bBKurZ6pgpShRsmvXLokGJK0RCgGwn0ouxImSyZMnO3ny5HHy5s3rNG3a1Pn7779l/Y033uhb7+bw4cPO2LFjnapVq8q2Ro0aOevXr3diwfjx41GHOcWLF3fmz5/vW79lyxanYcOGsu22224L+3w33XSTHHPKKac427Zty7Rt0qRJTv78+WX7nDlzIrpO7hHH2XulKIlg2jTUxxlOngIHnbxF9znV7pwoS4uiXzu7CxSS5fA1xR3ngRJHlqJ5HKeA+W+Z8rnjZGQk+mcoSq5n5cqVzpAhQ5wHH3zQefbZZ51Dhw4l+pKUKMfvvNEKZx988IHv79dffz1kIWKSnqHqRLNFun5MdxdccEG2axO6efTRR+Vz0KBBYp+2ELaKLxi88MILUnAxHNB4AVovojTckGOkTZs28vecOXOivnZFiTctWjim6uVzTNVbJ5tjB0zxrZ9z8Ayz7WBZU9gcMHkr/NtFbDhszB7HmIPGmEN5jKlwrDGtz1KNlaJEAcFe06dPN2+//bZorsqWLSsuLKRbUHI3UQtXVrA44YQTJJohXGhE7777rghV33zzjfhJRcO6devEDAkXXXRRlu0tWrSQYpb79+83n332WVjnDNdcqTlHlNwG792OfQdMnrKZTYH71h5jDh8saG42z5k8/V35qUbuts6RRz6fe+7fRFiKomQHXGXeeecdM2PGDPn/ySefbK666ioZG5XcT9TClfWfatiwYUAHdQQaL9Au4RgOo0aNiuo6rM8XGqbjjjvOcx/7XXbfUHTq1Ek+n3jiCXHad4OANm3aNPExU6d2JTdBAtBzhn5jmjzyn7bq8Nj25s9nzjY7R59oihbYY1bWbmnyVMz3n9YKjZVNgDV2rDE9eiTm4hUlBUBLNWLECPPHH39IkBV+yhRdjjTgSklhh3ai6QBHbzc4q1t27NgRMNoBbRcmwkWLFkV1HatWrZLPqlWrBtwHzZV731BgDpw7d66ZPHmyqVatmmnevLnPoX3+/Pnyf0yhRx99dFTXrijx0lbtOXBYMquv2vqvJso4pnnVouathQfM3pc6maN2ebyHvccY03qHX+p2RVGyCwFStWvXlrRFJAVV60fqEbVwRZgowtO+ff/lwIFjjjnG9/fKlSsDClf2ODRg0apY/YU6rwYNlBAIB85FhOHdd99tnn76aRGyLKRjaN++valcuXLI86C5c2vvwv1+RYkV/5Wr+a/tHVe6qJlS8lGTb91cY5405iivA0kK2q6j+lYpSpTY0jV2jLK1AVVblZpEbRZEowNbtmzJtL5evXq+v2eRUCcAOLRDwYIFTbLBrALt1LBhw8wjjzwiQiLqXLRZp5xyinnooYfEl8sKdoF47LHHRLtlF6tBU5Sc11QdMrv3HzLtnpmRSbCqX7GEmTqgyRHByj+1wl3rjLl7/ZHl8i9UsFKUKPn111/N8OHDJeO6Dd5CqFLBKnWJWnN14oknSvLQpUuXZlpPrg6kdKIhaFTXX3+9T3Nkwc+K4/DPInIwWg2a20zpBYIRhIpotPTr10+c5J988klzxx13+NafeuqpZuLEiSJgIRwOGTJEBK1A3HXXXebWW2/NNINRAUvJSejAew2fY+avzuywflyZYmbigBamaIG8Js8rLf/boBnWFSXmHD58WKLOqQ9oxycSURctqsXMU52oNVetW7eWT7Q67rI3RDyQsp9OnuShJOMcN26cSPAIJIMHD5bICEuPKB1kq1ev7qseHgi7ze4bKvrwq6++kr8vvPDCLNuZcWArhylT/nMM9oJaUAh07kVRcpK9Bw9nEaxEW3VrK1OsUH6T59BeYzYuypxhvWAxFawUJUaQ8ufNN9/0CVZMyq+44goVrNKEqDVX55xzjk9DhcoTDZWFKDsED0rQIFD17t3b8xw1atSQTO3R0KhRI19WdRzWvSIGcZwHdw6sQPz555++vwMJQ9aR3T+SUFGSiXn3tjdFC+YzRQrk8y4z1V9Nf4oSS5YvXy7Z1vEpZnJNRHn9+vUTfVlKbtJcoaF65plnzP/93/9lkchpTDQwhBM0WF7L8ccfL2kN/E2GkVKlShWZGcB7772XZTu5tNBc0dCtI2Ew3I7q33//vec+3333nXwGSv2gKInCnZMXwapowfxHBCs2HNhtzIE9/+2ggpWixNQUSJk1BKtKlSqZa665RgWrNCQPadpz+ku2bt1qXn31VTN16lSzfv16ydKOturcc88Vv6ZYObMjyJEvBEGNxGxWQ4U2i2zqpHu47bbbxEfKgrYNnyiEKa7PTdOmTcXnCud8BEC3OZEEqJdeeqkIiCSCu/jii8O+Tnyu0HqhNlYToRJraJPksbIO7Ese7iDClQhWb3QwZo3fZAHHdUyCiqLEBFxkGG/atWun2dZTjHDH77gIV/Fk4MCBZujQoeITRcMm7BWhiXQRRP7hR+Uu3IxNvH///hL1SEI3N4sXLxahDOGQbO046ZOPBCf8X375RfZBqKJ0gae5JQAqXCk5CRGC9e+f7POzmnRTiyPtE43Vo5WyplrQiEBFiQrGBBzVw3E5UXI34Y7fUftcJRvPP/+8CFEvvviiOBIePHjQ1KxZU+oN3nLLLRFpyUhwioD17LPPms8//1y0WOSrIodXhw4dzOWXX2769OmTo79HUSLlv+mSY8ZcfqLJc/BfE6DbFKjRgYoSNYcOHRITIGMDGircU8qVK5foy1KSgKTQXJHx/H//+58ZOXKkSQdUc6XkfAb2XWZswYdMk7wrvHdWU6CiRAWBTNTEtQmwzzjjDNO2bVs1A6Y4/+QGzdWyZcskOeeHH34o0YbpIlwpSk7ntSpi9gcWrDAForFSFCVbYNGgegeR8LiZ4OtLORtFSahwhaMfQtVHH33kixqMxGdJUZT/4P3ZtvtAprxWdSuUMGaHnwnQoqZARck2BDdhBrS1bHv27KkWCCV2whVpCGbOnCnRf4ScUjsQh++zzz47oFoUJ/D77rvPTJgwIYtQFU6NPkVRQmdin3dPO1M6zz/G2KBYBCs1ASpKTLCC1JlnnilJtIl+V5SohSvq6pG3Y+HChZ7bSVdAWRsELQuReqRAIKoO85/bzQsHQJzNyVyrKEpk4GPlFqyaVC1pSo8+z+TxT7egKEq2IZCJHIlAwBS5DVUhoMRMuCIRJyVtCDn1MuWxjuzoRNKRmZ2knmRFp7QN5WTcQhWpD8gvRRoELV6pKJHD+9R7+JxMmdhLFzho8jzmEqzUv0pRsg3R5pgBGb+uvPJKiTZn3FPBSomZcEUjI2nmnj17fEIVnTtpCXDoIxcUzn2wc+dOM2DAAEm0edZZZ4l3vQWJ/+6775bkofnzp1wmCEXJUXjnqBtotVY2USj5rEoXK2jyHDz03874WlEzUP2rFCVitmzZItGAfAKKgzp16iT6spRcQtjSDUWXSbJpBStyRpGwE4c+m++D6t933nmn1BHE4Y8M7IQrAlnTH374YakhqJoqRYmcjAxH0ixYgcrNmGtPzxoUgq+VClaKEvEEZsGCBaKxYlxj7ML6omXOlBwRrgg7tTz++OPmjjvuyHyi/PnFmb1FixamSZMmkmZhxYoVPj+sL774QuoIKoqSPcGq3TMzzKqtu7Nsa1LtGKkfqChKdGB9mTRpks+nmDJttqSaouSIcPXTTz/5CjWjtQoExZsx+9m6e8ymqb2ngpWiRJsY9IhgdVyZYmbiAEraHNmnSIF8mspEUWIAlTgQrHifKH2GskDfLSVHhSuy0NLIiJQI5StFTT9gf0rIcIyiKNGbARGspt7ayuTN+2+HT5CILW/jX+JGUZSIQKBirCNwi6ArRclx4co6pZPPKhTuferWrZvda1OUtMRLW2Wd1tFYZRKs3uhgjKZdUJRsp1jAheWkk07y5bC6+uqrVVulxE+4Onz4sDS4cCL83EnVtIilokSvrUKowq8qU6ePxiqQYKUpGBQlKBs2bDBjx46VGoGkWKhXr56sV8FKiQU5ngtBG6qiZN9pPYu2KhBa4kZRwtYME83+5ZdfitIAbZU6rCuxRhNNKUoSClYBtVVuXEl5tcSNooSGUm2UX1u6dKn8n7xVXbt2lVyNipJQ4YoEoX/++WeO7G9zZilKOiUERUbyjwbM5LSe9UBjDuw2ZkTL+F6wouRiyLKOGZBybLiutG/fXsq0qXVFyQnyOO6aNEGgMUbSCO1pwz2G/UjYlg4QHHD00UdLglWtpp6eBEoIGpZg5e/EXqGhMdfMUjOgogQBbdXo0aNNyZIlTa9evbSEjZKj43e2zILhyGNuoSpM+U1R0johaFj+Vf5O7AhWV89UwUpRPHDXwMVh/bzzzpPPwoULJ/rSlBQnIuEqEiFJBSpFCd+3iv4/4mSgWjtQUQKydu1aSQp6wQUXmKOOOkrWNWrUKNGXpaQJYQtXFK1UFCX7MOEI6VvlnxTUH3eSUK0dqCie79ns2bOl1m1GRoaZOnWq6datW6IvS0kzwhauNFutokQHiUGtj1VAwUqTgipKttmzZ4/5+OOPza+//ir/P+GEE0ynTp0SfVlKGqKpGBQlTrPp3sPn+P7v6VtFBGC4gpUmCVWUTBCVTjQgEer58uWTEjannHKKRgMqCUGFK0WJs9YKx3XyV2UCrdXIjoGTgvqjSUIVxQeaqvfff18mMaVLl5ZowAoVKiT6spQ0RoUrRYmz1mrMtadnnU3jZ7Vx0X8RgOqorigmEreVMmXKmIoVK5pzzjlHytkoSiJR4UpRcliw2rb7QGCtlXVgdzuq9/9CBStFCaM2INopJioIU/3795cUC2oGVJIBFa4UJQcFq17D55j5q//y1loFcmDXwUFRAkIE4MyZM2Vp166dad68uazXEjZKMqHClaLkoJ+VW7BqUu2Y/7RWCFa7t2YVrNRRXVECsmvXLjNu3DhfaqDt27dnShSqKMmCCleKEgc/q3n3tjelixU8Mgh4aaysA7s6qiuKJytXrhTBavfu3aZAgQLiW3XSSScl+rIUxRMVrhQlDn5WmQQrf40V2ip1YFeUgGbA6dOnm1mzZsn/y5UrZ3r37i0O7IqSrKhwpSg5XJDZ52cVSGOlgpWiBGTr1q2ScR0aN24s+avQXClKMqPClaLEuLyNW7DK5GflnyRUNVaKEhI0VWRZL1SokGnQoEGiL0dRwkKFK0XJAVOgLciMYOXTWvknCVXBSlGycPjwYTED1q9fX/JWAZnWFSU3ocKVokQpVBEViPO6W2OFYFWskOv10iShihKSv//+23z00UdmzZo1ZsmSJea6664z+fPrMKXkPrTVKkoM/auymAK90CShipKF5cuXS9Hlffv2iQmQHFYqWCm5lRxruRTPXLt2rfnrr7/MoUOHTMuWLXPqqxQlKfyriArEed1nCgyEClaKkskMOGXKFPPdd9/J/ytVqiS1AY855phEX5qiJIdwhUA1fPhwM2rUKLN48WIZgICBBgHLzebNm82QIUPk74YNG5pLLrkklpeiKDnK3oOHA/tXefHvu6Aoyn/s3btXxot169bJ/5s1a2bOOussky9fEM2voqSTcDVjxgzTt29fqfcEVrAKFgEydepUs2DBAlOyZElz/vnna7FNJVeSxb/KH39ndkVRBGoB2qVr166mbt26ib4kRYkJeWNxkm+++UZyjyBYWaGqXr16vkiPQFxzzTWy/44dO8xXX30Vi0tRlLg5sYdt5SMFg9uZXcvbKGkMVoyDBw/K32h6u3fvLmOBClZKKhG1cIXz4QUXXGD2798vg06/fv3E1+qXX34xPXr0CHpsz549Td68Ry4Bm7ui5AYn9nOGfmOaPBJme83IMGaEy99QndmVNIZagG+88Yb5/PPPfeuKFSsm1gtFSSWiFq5ef/11s379epmBXH/99WbkyJEhNVaW0qVLm9q1a8vfP/74Y7SXoigJSRJapEAA/xC0uK+0NGb77/9prQoWi9PVKkpywYR7xIgRYuFYtmyZ+OgqSqoStc/Vp59+Kp9HHXWUefzxxyM+nkRxhOD+9ttv0V6KouQomAIjcmJ3mwNL1TTm6pmqtVLSDkyAkydPNvPnz5f/V61aVawWjBmKkqpELVwtWrRIBhdSLRQvXjzi40uVKiWf+F0pSjL7WKG1yrYT+zUzjfnXBK4o6VQXcOzYsWbTpk3y/xYtWpg2bdr43EEUJVWJWrjatm2bfFauXDlbx9tZP5XPFSU3JAoln1XQJKFeTuxqDlTSDPp00iwwcS5atKj44NasWTPRl6UouUO4whmRl4d8Jdlh48aNPv8rRUk2wardMzPMqq27MwlWaK2CJgn111qpE7uShqCd6ty5s5k9e7YIVmoGVNKJqIUrnNfJwk4dqOyYW8jKy0B13HHHRXspihJz53UrWIX0sUKgon4gHPCrI6haKyVN2LJli/nnn398GioClmrVqhV8MqIoKUjUwtWZZ54pghXRfn/88YepXr162MdSoBObPC9e69ato70URckx5/Wpt7YyefMGyb7+Rgdj1nyfdZtqrZQ0gYTQn332mWRXJ2+VTa+ggpWSjkTtVdi7d2/fTH/AgAFhH0f6hptuusn38l144YXRXoqixNTPyoLGKqBgBWisvASrY09TrZWS8hw4cEAKLn/yyScSGUhtQC24rKQ7Ub8Bbdu2Na1atZLyN8xaELaoLxjMh2rixImSEwt/KwQrinSSkkFRks0cGJbzurvU0+2/GVPw3wzsZGLXWbuSwhAFSDSg2wJBRKBGAyrpTkymF++8845p2rSpvGjjxo0zkyZNMu3atZNM7ZZbbrlFhCmcG93r8bVCGFOUZM1lFZHzOoKVaquUNABXEDKtU84GZ3VyV1WrVi3Rl6UoqSNcValSRYow83KReZeSOGixwA5MQ4cO9e1v6w+ecMIJZsKECVr6QMmd5kBrEtS6gUoaQqZ1BCsc1rt16yaR44qiHCFmulsKNc+bN8889NBDply5ciJABVoQph588EGJFNQoQSXXmgP9Ued1JcWxE2Po0KGDOffcc81FF12kgpWi+JHHcb8tMYLZDILWnDlzxHH977//lpevfPnyplmzZqZ58+amYMGCJl0hVPnoo4+W+1KiRIlEX07awyuwbfcBXzHmkNGB/slCH6105O+716tJUEnZd4Q+fcWKFRJ8pD5VSrryT5jjd46EdBApctppp8mSCMaMGWNefPFF8/PPP0skC2rrvn37it9XgQIFsnVOImEoUj137lyp7I72jfN27NjR3H///TH/DUr8Bo1ew+eY+av/iswcqChpAm4e1JC1uQwXL15sTjzxxERflqIkNSk3/bj55ptNnz59zLfffitO9gg/f/75p7nzzjslsjHSTPIIZ5wPn4IpU6aInxjRjQ0aNDC///57Jl8yJfex9+DhTIJVk2rHhBcdiMZKln8ThypKCoLl4ZVXXhHBCm3V2WefbRo2bJjoy1KUpCdqzRWJQLG7J4OZj1wrzz//vBSQJjVE48aNZT1hwghW33zzjbnvvvvMkCFDwj7nVVddJZowhKtXX33VlClTJlPtLDRZSmow7972pnSxgqGjAwMlDFWUFNLofv/99+arr76Sfg4zCJNKgpcURYlTEtEKFSpIRt6ZM2eaRPLoo4/K56BBg3yCFSAQvfTSS/L3Cy+8ILbScCAC8u233xYt1ejRozMJVsBMLlGmTyU2uD0OA5a2CTdhqEYKKikCQtXkyZNFsKpbt6707ypYKUqczYIIK6+99ppp06aNRP/de++9ZunSpSaerFu3zvzwww/yN9Er/pDY7thjjzX79+/3pYkIxbBhw3ymxuz6aim5J/VCWPgnDMWJneVyjRRUUoeTTz7ZFC5c2HTq1EncIooUKZLoS1KU9BKuKMzpTrOAf9Njjz0m2p4mTZqImW7z5s0mp/npp5/ks1SpUgHTO3A97n2DcfjwYdFcQcuWLSUB6nPPPWeuu+46Ebbeeusts2vXrpj+BiWxqReKFAjD18orYSiLClZKLn8f8K+ykE5n4MCB4reqtQEVJQE+V8uXLxeN0bvvvms+/PDDTIIUQgzLHXfcIRnbL730UvFdyolZ0KpVq+SzatWqAfdBc+XeNxgrV670CU/k46Jcj78wxe/64IMPxJ8rGGjLWNyhnEouzMS+e6smDFVSjj179oi/KgE6/fv395n/0FwpipJAs+Cpp54qGipmPpRDIO0Bea2sNou8V19++aW5+OKLJdcVQhY2/Vim2Nq5c6d8Bktmh6N7uMLNtm3bfH9fccUV5pRTThEhku+h+nvnzp3Nli1bTNeuXc2vv/4a9Fxo8nAItYsV8pTEQLvrPXxO+KkXrBP7kFr/rdOEoUoKgKVhxIgR0ocxuSDNjKIoSZaKAQdvsvZSa5A6g2izsNmT98oKWmh/Ro0aJSkSmCGh/UFYSTbcgl/lypXFuROzIgLaSSedJGV7MH3yex5//PGg57rrrrvEL80ua9asicMvUIIlDLVaq7AysZNywe3EjvO6JgtVcvl7MGvWLPPmm2/KZLN06dLmyiuv1PxVipLsea6KFi0qjuUUccbZHM0W9nuwgha1qZ555hnRCkWbO4XCobB79xEfGi+sWS+crOj2fHDZZZeZQoUKZdqeL18+iaAB8l8Fg2P5TveixB+bMNRmYocx154eWWFmnNjVeV3JxdBHMsH9+uuv5Z2g7yXlDFHfiqLkoiSiZcuWNQMGDBDfJdTPZDQnu7lb0LLZf7NL9erV5TOYVshus/uGOp8ddGvUqOG5j12PkKikaMJQ/8LMxcqoYKXkaojkxr8KiwI5Crt3755l8qgoSi7L0F6zZk0p2jxt2jTTs2fPmJ23UaNGPl+pQA7r1MYCdw6sQGD+q1Onji8JqRd2vfXlUpIbt4sfCUPD0lq5M7Crn5WSAmApID8f2ir6Qo0GVJRcLlzhDD5y5EiJHEQzNG7cuJi92Phv4VgP7733XpbtZGdHc8UMDWf0cBOkBjP74ZQP1typ5J6cViEThno5sesgpORCcIfAR9RGLNPu8Y0l3YKiKLlUuCJSkKLHJKIjUhCnyenTp0seKWsSJDfVtddeG/V33X333fKJg/mPP/7oW482i1QKcOONN0rEnmX8+PGSgRiBz5+bbrrJHHPMMZJ0lIgaN6RgwG/B7qekWE4r/0zsmoFdyYWQUmb48OGSEueLL75I9OUoStoQdZ6rQKApIlpw7Nix5q+//soSgUcOlS5dukh6BjRJ2P+jhRxaCDoUU0btjcBEagaSge7YscM0b97cDB48ONMxRO+Rq4vK7/5Q7obcXeedd54If2Rsr1evnvgr2ESk1CoMVxOm5JKcVv7gxK6+VkougrI1TGKJCAS0VPR/iqLkQuEKR0kEKsxy5E/xF6gY0Mh2jkCFyS0nouaISqQTefHFF83s2bPNwYMHxc+LeoO33HJLxAWmzzrrLPPzzz9L3ULMg2jhuG4EKjIYUyVeSaGcVl6+VmRiV8FKySWQWgGXi9WrV8v/8asi9Y2W8FKU+JHHiTKTJ5FyCFOYyBBCLO7TnnDCCSJQkVxUi38e6fwwTaI107QMOcvu/YfMCQ9M9pkDJ93UIjxfK7dJkNqBmtdKyQWsXbvWvP/++5J1nYkk1oFo09woihL5+B215ops41aQcgtUFStWNBdeeKEIVRQBVZREO7GHjA4E9bVScjElS5aUZM7krOrVq5ckB1UUJf7kj4Vt30JKgh49eohAhb+ThvgqiRSs2j0zI5MTe8icVv6or5WSC9i7d6+vXit9MOXFCMSJhR+roijZI+q3jxcYvyQEqpwqyqwo0QhW2XJiB/W1UpKcFStWSNFlyoxZ8x9JmxVFyeXCFaVt9GVWkjXtAoLV1FtbhXZiV5RcBKlsCLCh6gWQeoZap2otUJQUEa5UsFKSOe2CClZKqkFaGVLcMLGFZs2amfbt26tgpShJhBrllZR1YA8r7UKwFAyKkmQsW7ZM0sGQl49cgV27dpUkyIqiJBcqXCkpm4U9Igd2rxQMipJEbNmyRZIaQ+XKlSUakOhARVFyqXB1+eWX+/5G9fz66697bosG//MqSlyzsGsKBiXJwQXjjDPOkIkE0dj58kUY/aooSnIlESVvinugwpky0LZocJ83ldEkorGFJnzO0G98wtUvD3UwxQpFqJQ9sNuYRysd+VtTMChJwpIlS0ylSpV8GirauvpWKUoKJRG1MpjXix1lkveA51WUcNh78D+tVUhzIG0VLZU/Wu5GSSIoeD958mQzb948qWpx2WWXiaZK+0lFyR2EJVyNHDkyW9sUJd5kycLuFqb4e2RHYzYuStj1KUootm3bZsaMGWM2bdok/69evboKVYqSisJVv379srVNUXIatKb4W1kyjUHZcVJXXyslgSxatMhMnDjRHDhwwBQtWtR0797d1KpVK9GXpShKhGi0oJKrBatew+eY+av/8tpozO6t3oJVhYbG9P/C2/SHYKVaAiXOHDx40Hz++efmp59+kv9Xq1bN9OzZ0xx11FGJvjRFUbKBCldKrgWNlVuwalLtGFOkQD5vjRVO6vhSgQpQSpKB2W/9+vXyd8uWLU2rViS/zZvoy1IUJVHCVdu2beUT9fWAAQMiPn748OFm9OjR0rlMnTo12stR0sgU6E4YOu/e9qZ0sYJHfFP278qaVkGj/5QkxEb/UaO1d+/eEoFUo0aNRF+WoiiJFq6mT58unQN1rbLD77//7juHomTHFEiEoE+wsk7rFk2roCQh+FR99tlnkmKhdevWsq506dKyKIqS+1GzoJLr0i74C1aZEoYSGWijAfGtUsFKSTI2b94s0YBbt24V01+jRo0kb46iKKlDwoWrjIwM+dRsw0qkZDIFehHIaV1REqR1xWEdx3XyWOGs3qNHDxWsFCUFSbhwtWHDBvksXrx4oi9FyWWQLDSoOVkFKyVJ2L9/v5k0aZKkWgDSK3Tr1s0UK1Ys0ZemKEqqCVdr1641X3zxhQyQ6sSphEMMigEoSty18yRbJikofR1BQM2bN1c/U0VJYSISroIVaSbSL9wizuR0Wbdunfn+++/N3r17pZNp06ZNJJeipCEZGU6mCEFFyQ3gV3XqqaeamTNnSu6qqlWrJvqSFEVJJuHqzTffDFhbcNmyZbJkB3wPspPGQUkfaGMIVqu27vY5sktOq8w7Za4RqCgJYt++fWbnzp2mbNmy8v/GjRtLRHWhQoUSfWmKosSBvNkZ5NxLoPXhLmeccYZovXQ2pwSDvFa2OPNxZYpljhAEmzh0iJYKURILyUBfeeUVM2rUKNHMA21VBStFSR8i0lz5F2lGOMIUSMfRrl0707dv35DnYN/ChQtLPhdmcuXLl4/8qpW0gnbWe/gc3/8RrPLm9dOgHtidNXGo1ghU4txO586da7788kvxsyIKEO1VkSJFEn1piqIks3DlVaTZ+lnVrVtXizgrOZbbymqtMAcSJZgJTRyqJBg0VBMmTPC5RtAfnnfeeSpYKUqaEnW04KWXXiraqNNOOy02V6QoQSIEx1x7ela/P00cqiQ46nns2LFSugbn9bPPPts0bdpUowEVJY2JWrjCyV1R4mUSDDleaeJQJc7Mnj1bBKtjjjnG9OrVy1SqVCnRl6QoSronEVWUcB3ZPSME/VHBSokz5557riRBJn8V/qSKoigRRwsqSqK0Vp4mQUWJM3/++ac4rdtoafyqOnfurIKVoiiRaa7efvvtLH5WgbZFg/u8ihLSkV1R4gjC1Lfffmu+/vpr+btChQrmxBNPTPRlKYqShORx3MmqAoCTptUY8EnRUa9tUV2I33lTmX/++UfCtPHTKFGiRKIvJ2nZc+CQqX//ZPn7l4c6mGKFAswFSMPw6L9+LnevN6ag1mtTYsvu3bvNxx9/bH777Tf5f8OGDc0555yjuasUJc34J8zxO2yfq2AyWBjymaJEhVoDlUTxxx9/mHHjxknOqvz585tOnTqZRo0aqYlaUZTohKtg+as0t5WSULTkjZKDUP908uTJMoEsU6aM6d27tylXrlyiL0tRlFQQrvwzs4e7TVGiIaRC1Ja8cWdmV5QYQm1ABKuTTjpJnNYLFiyY6EtSFCUXoKkYchn4paWDbxoD2nXvzDeVjzrixL5/3z6TN8OvuaKx+mu9McWPPfL/CicbczgvVXMTcMVKKmVbt5nVyVlFFQqELEraUJBZUZTcRf78+WVJOod2JfEO7Xv27DFbt24Vx9p0IMNxzPodRwaygvnymHIlPMLcnQxj/l575O8SlY3Jq9GESvahK9y/f78s5K3Kl0/bk6KkCsWKFRPTftGiRZPLoV1JHAcOHDBr1qwxBQoUMBUrVpQIpVR2pmWQ+2PrHlOu6GH5f61yR5l8/oWaIeOwMVv3H/m7zHEqXCnZ5vDhw9JpHjx40NcRsyiKkhqTpu3bt8s4etxxx8XFvB9X4Wr+/Pnm008/NZs2bRKnUKJutCZhaDZv3iyz6GrVqqX8bJoX4bfNu8zBPPlMnvz5JCN70SKFvYVJhKv8/64ngaMKV0o2wNRHJCBtjwkMs9JoZ7eKoiQPmPmPOuoos2rVKhlPq1SpkvzC1Y4dO8xNN90kf5NQ7/bbb/fc7+abbzbDhg3LtO6RRx4xF198sXnjjTdSXmjILnT4mASpW5YO9yjDOZI8FArlz2dqlSue0lo6JbHvFkLVrl275P/4ZJQqVSruvhmKouQ8jJ9MnP766y9593N6XIm6F5kwYYJ599135ULbtWvnuc/rr79uhg4d6rmNY/nBgbanO5gpMFlYB9t00FpZVLBSchImLVawQlNFP6TtTVFSlyJFiojvMuNqTpsGo64tOH36dJ9U2LVr1yzbibB58MEH5W86rgYNGphbb71V8sXwfwbUl19+2SxbtizaS0lJuH+Q6lorK1jtP3REa4U50MvNynWAMVt/jdv1KakHAhX+i2iFS5YsqYKVoqQ4+f4dR+24mtTC1cKFC+WzXr160kH5M3XqVLNu3TrpuFq0aGHmzZtnhgwZYj788EPz/PPP+35oLGsUpiKp3vFHbA4kUvDQ3iN/5y9iTB6tQa6EFuDRVNkAadoXZsB00AorimLiOo5GPSLhfc8F161b13M72Y0t99xzTyZV3NVXXy2dG3zzzTfRXoqSS2GwW7klCnNgmdpaH0cJCrnhMAcQEYifVbpMWhRFSQxRC1d0VmCFJH9mzpwpn+SD8PfJQtAiWpDBdcWKFdFeipICWquQ5kBFyUZS0C1btoifBcIUEYGKoihJLVxZ26VXLlI6tQULFkiH1rx5c0+/oQoVKsgnCbkUpUbZ7Dux//rrr+bGG2809evXlxxFhQsXlpDbU089VdZ/9NFHJjfx5ptvyr247LLL4npsqkCfRL9io4MQqu68807xteL+pMv9JJqba2chFU4w+H3h/E57P6pXrx5wH4RZyqN169bNVK1aVcyv3PsaNWqYXr16mVGjRkkOv2RlypQpUvKIxJNcO9YZrC82CCI72tOXXnpJ3GPw86M9cm6UDm+99ZanH9Cff/5pRowYYXr06CGpePARJMEt5ZjuvvtumTQoKSpc2QylGzZsyLLt22+/9ZVqOeOMM6L9KkUJyLhx40zDhg3Niy++KHlMEOZ79uwp6UHw+WP9NddcY1KBP/74I+TAlu5YM6CtaGCzM+fNmzetngXJExFiLKS9iQc//vijqVOnjpQOIqK8dOnS5pxzzjFdunSR5/Dxxx9LGp7jjz9eojaTjWeffdacddZZ5osvvjAnnHCCOffcc0VQf/TRR02TJk2kbUX6HBCibrjhBvPDDz+Yxo0bS//EPZo2bZoIs/zfX0lx0UUXmWuvvVaE4vLly5vu3bvLWEq7e+yxx+TaUGAoyUfUqRhq1aolleO/++47SRng1k6NHz/e9/eZZ57peTwDIXg5wysm7dIvhHnQEYf2fyEpbb9+/aQDu+222yR/Glor/wS2Y8eONbkJOlLM5qQIiOexqdKuELAQpuhb/NtDutxP+mAyU1MjkQnwxIkT5X1hoM5JwYr+HqEJYYo0O2TFdoPGBQHm6aefFu1VMiVt/emnn6QfYSxDqCHZNfB7zjvvPAnSQuCJpD9BY4WLDNonPtHkWQjyatu2rQicBHpdcMEFvm2VK1eW+3TJJZeIgOq+f3369JFofT6XLl2a8hHluY2op3EtW7aUTyT5Z555JpOJ5p133pG/6ZACZWIn2pCZH6piJb2IOP2COwXDpsW+VRMnThJVPQMIkaheA+kpp5wiM73cBO8NpghKHsXz2NyKe9aPyQXTC1qSaAWr3Hw/yTEIAwcONK1atRKBMycjszEFkmYHQQRz4CeffJJFsAIKYaMFIpAJU1cyQT9BW+rfv79PsAIEQO4nAjsuBpGkD/r666/lE82VW7ACNGFWoJozZ06mbQhbJOB2C1b2/tnxlbHW/zglBYQr1L5WYh40aJAIW6g3mzVrJgMegtOll17q6US6evVqsSkDNmQlvYg8/YJjTMYhYw66ilcXKGY2/av9pMPJDgw4r732mmndurUEZtDZMyBcd911Eg3rD7NFrpP9GUyeeOIJUc/jl0EniH8EM0kv0KCdf/754gtGQAdmdSYWvDMMRKH8fPjbDla8P9aXxi7BjsV3g3UdO3YMeC+2bdsmv59r8/fnwHfpgQceMCeffLKUkmCwwRSLpjAnTTuYULhuNCL+Wm8GOrZRGYIJHtpLC/4y9Dt2YPOHUhhoBPD75DfXrFnT3HvvvZnOEYtn4X72ffv2lcGV76OtdejQwXz22WcmJ8B0hJaFjPP0wVdccUWOmwbfe+89s3LlSmk/5C8MZYbFHzKZUmGgRZs0aZLPJOcPmidcDvwtM6EIV8BnMhAu9CF2f69+SsnlwhU2Y5z87KwRPyvUm9ZBHfUz271wq1Vtg1XSk7AEKz+NlSnfQNIwVK1WTf67ePFiGUwigbB8fCuuuuoqGfzw0UL1z+A3fPhw06hRIzETeIFgxQD+8MMPy4CJTwm+PXS61i/CDdd2+umnm9GjR0unSNLd9u3bi1BIh47zbyhwhkUQA74Lc6h7CQazYwayr776SvzQAg2ODDD4mLiF1SVLlsgEiN+KUMN1cO0IYPfdd5+8vzkVlML3WAdjN/zf9jukfOF5cA2sI5hm9uzZ8nu9+hb8VBASZ82aJRodJoWYzf73v/9lMsvE6lmQ069p06ZyfxHAaWMI5AjqtBvua6xBiOJe0EYRILlWNHBoXLg3OYGdICA02mCl3ARR63aigEbJC7s+UL/ghdWA4ftpFQoW+p0PPvhA2irCfrgwmWDCA7lNo5oWODHiueeec8qWLevkyZPHt5x++unOkiVLPPfPyMhwatWqJfvly5fP2bx5c6wuxRk9erTTqlUrp2TJkk7RokWdE0880XniiSecAwcORH3uSZMm0ZvL0q5du2yd4++//5bj+QzF3r175R7ymUrw/Jdt+Mf5ec1fshw6nBH8gMOHHGfdj/8tm5dzEtm0c+dOp3LlynJPaU+tW7d2Bg8eLM8qVLu66KKL5LguXbo4mzZtyrTt2WeflW21a9d2Dh065Fs/bdo0Xxto1KiRs2HDBt82nlOHDh1k29VXX53pfG3atJH17777bpbr2LFjhzNnzpxM60aOHCn79+vXL9P6VatWyfpq1aoF/F2Bju3bt6+sf+yxxzyP4/ew/dNPP/Wt27Nnj1OzZk1Zf++99zr79+/3bdu9e7dz4YUXyrb+/ft7XmekC++um8mTJ8v6s846K9P6yy67TNbXq1dPnvuyZct8zynQMdwP+z333HNPpue6aNEip1ixYrJt9uzZMXsWX3zxhVxfmTJlnBkzZmTatnDhQqdKlSpyjunTpzux4vDhw86xxx4r5/34449966+55hpZd/nll3seZ++P/+/0x94P/99tv/Phhx92Yo37vYtkCfVb3EyYMEGOYewIxDPPPCP7NGnSJKLncemll8pxBQsWdNq2betccMEFTvPmzaVtMEb5t7lQ3HnnnXK+ihUrZnonlZwdT8Mdv2NWoRSbPuHuzIrIfXXssccGrTzNDBMVPBBaml2Tjj/Yp5klogrHSZBzYxYgBBvnxC+//DLbamhmCWg4bNmeZEBm6f+a1nKXrxWmvSPFMyPObYXGKm9+X+JQnjFaIbQFBFegDbBlmQANBZGCPDu30yemu/fff198tdAoYOryb0toeTDbfP755+Kc64ZrR9vknqGj/n/ooYdEk+KvacGRGNAk+BPMLzGWYMYnegwzF2Z8Nz///LPMxvk9btMhYeK///67/P7BgwdnOgbT4CuvvCL3Hx8QHJTxdbLPJZQ2zQv/hMQ4R6NJxD8Hkx1/o6Xi/tLHEHWGdpxrR5MO9t5brZeXDx6/xa0tpTQXmgM0lhyPljEWYEqlzXNe66NqwayKrypOyRS2R4sWC+jnMBVhOUAzZsE0iHkY7Sn9JM8ollhTcrly5UysoV1mpz2hYQwXm2AWTWQg7D2zOR7DAfMo7xya8bvuuiuTqZp3iHaKWTpcaJ/4lwLvXE7XyVMiJ6bl3xm4UHWHAxE82XlRgoE50nYYM2bMEF8Nqz5F0KJzxoRhG2WkDBgwQAZIIkXwJ0gGEKzq3/9fFvzcxOhrTjNHFykYeUZ2St347c+gSsTq3LlzxcSGkIWPDp09JiD8p3BCZZvtiBCaGPRQ2fsLVhb8qtgPM4q/cIUp0MtXkFJQ4G96wyyEeQ2/G3LUIEwxCYgnbdq0kbQBy5cvFydYtwBhzZL457ivy/qg4CvmBe8bphLuE2HmZ599tqzH9BlpPikvmAxhZiVknXcYAYTnu3btWvGLwcSGcIWAZ016oYQrnqVXmwv07LILfQ9tkt+AqTVQG4NYmurwIfR6lvg4IURiQsdZ2vph5QYQumPRnhIBgtiFF14okzQmbfRHRALin4YDPQI2/RNmahQTwVi0aJEEDRCdz5jEeZXkI6UKshF9AszIrWBlO3lCYeGFF17Ilm8IfjTM+Ck6zSCpRA9O7MeXz37SUC94NmiOyE+DIIw/g3vAtfUsgY4NiADyd0a2y//93//JPl7J+vyjfvxzv/k7RtOJ0i7pYNHGsB+zajS4gRzgY43bKdvt44UmyOZDIkrKjb1PaHUC3SfrlJ1TSQ3dfldM4mx0FAILwgIDkhWocMpHoMa3CZ85L0I9u3379sXkunGatz5gaNy87p3V8sTq3nEecktZTaU/dp2XY7t9F0Np5t31Gd1YC4RNsZPbsJMsmx/NC5tE1LaVcCC1A+8IQhWCVO3atUVjRdvlvcNHjaAIa80JBJYh3oUdO3bIe+ruz5TkIr7T5hyEmSaz5kBRHgxidMCoymnkkUj7zD7RVqEdwfEU58NkAZPakoc7mNwAHfLvW3abff+aMU+oVCJHa7txboQZTH84qTLgoN284447ZLvNiIzZMFS0KtGv/kSakBKzBjlt0KoiCBD8gQaGTyYGCF+Yr3MahCsEUGsaQquCyZx2jjbN3yxn7xOmwlD5kYimsnA+ovgihe/3N1la7Q5mWu4TWh7uP8EIwICDsPjbb7+JxpK2hrY6UPuKdTLRQNh7h3bPOr/nNJhnEZbRWF155ZUBhQPuIYO1+3lbc1gw4cJ9Dn+zIuZW+ljbF8cSrvXxxx+P+Dj6fq/74IVNBovwgonQS6NtI/PCTRyLhsmmTQg07jBmebkS+Dvb06YRXNFIop3U2phpJFzxUuK/ggqfTo4O1jZSNEgMdjQQGlMsE8fZyA3Cm73yqgCmC14M9o1EuGK2we8gC3gscubEEl6uogVzh4x8mNwL+CUVyCdCYb44FhHEVIVw5c6sbNXvRJOh0YwHNoWDFRbQkGDqIP8NpkLKgkTie5EdEIB4BzGj0aYxU1pzi5emg/vEwIYJiesLFwZg/LUiBbOfFa4QkhCMuWb80nh30czgU4dQbPP/WOGKwcmmbAhkEownto3x3NEUxUOos7mtSDGC4B5q36eeeiqLRg8hNRjkVnLvbyEClgkMgkKsk5Vu3LgxW+0JwhWumEAzLtHmmAhhRveH9eC2jgQDYchqsQNpu2xyWhK+BrrfXAsRrfgY0tbjNUFQskdMn85zzz0nDqZoebDn0yBoLMyi+OT/rMe5GHtzLFWaqN+DqfvdHZ3dNxzQUpEyAtu2pouIXSb2aGoIep07FDb82R1kYcOjEbpiZQaKFIR13hccXdFykFQ3FNZnzJaWyg5WiEKoYhDEVIkGy8uvyt4nNF2RwMyeZxPpYoMRuB9oEDDj01bQQLDuySeflPVWawWUFmEfNFuh/K1iSahnQbAEz5YJJqbqnAZzKX59mCBtTUWvxZpx0ai4rx2hG2iHgQQs+nNrdrT7WxDUee6k82BS6lUvzw1me0ym4cCEJDvtKRI/LZ6nDQBASeAPpjvrG0fW/nBgAmATpaKp9gJ/UfBSDBBMgmC1fv16EawQMFWwSn5i8oR4gXCww65s88zYxY17Pfvhv8RxsYi8y4koD2ZKaBTQJFh/ruzArIXvdC/pRLYysUcA/nQER3g5BPPdaGesZsqdwwh/HEw1aDNJ/Omfl8pqYvGJsJF+0UAghX+OG0ArZDUBbrNaIPBrYRCgfQaa6YaC30tQCVFL5HZigOVeeM2sr776armuMWPGiNnSvmtuuJZXX33VxAoGcLSMduBF822FPPss3cIVGhL8VxAamDwxSMWj6kM4z4Ikq4CPjFfhZNoogy4Rfl7JaiOZhFitFRqkYCXF0ORipqZdUxLHrd1HUOWaGMj9a8byPBCaEDL47f4O8SRtRQhn0oCfKlnavSaz3CubH80raWsiQWtqI4HdAjHaLH4vZj7eFX/zOYELrPNfT/sg6AL4zf4TKDTIKCa8XFq4dwhWuL3g86iCVe4hJvYk/CqIdLCdAOY/zG68OMxiEHgYpBi8GADRBqEqtQMfxxNOmmwwqDD747dFY8LERwQfl3Ql4kzs2RiIKenBQoeP0EQbRLvBLN4KTQwW/oMBHSj7obnBJIDvFQMzbZPjSE/ALByH82hNHAyy+HvR+RKVhqaI2SgRcAg3+FGEY2pgAKOzRqOKaQyNjm2fNkosFAx+CJqkByAFQCCTIPD+EjFIhB1aI1IvoI1BC8iAgy8I9wfHbNJdRIM1A9qgE5zXERKY+VthCi0j984/xB5NFZFU9u94EM6zwOkeLT2TT/alHittDVMQJk7aGP0hgquNtASr9Qk3ohQzLJYBCBWJzX1lIMe5GoEMIcjy7rvvynUg8CGgEqlJkkqeCZoxAgZwv6Bf9BLgiEikfh4TZ4RJhDfeSc6FYIBghmkNIYV1yVb+hneQ8YjJP2lTMFPTtonkQ9jk2fHe+EO7JQrXC+oDoqUjOITz49toowWtmREtoL+Pop382XsU6B3F7BlJygklDjhRQkKu/PnzO3nz5pVkaAMHDpTEgsEgKeEtt9ziSzZaoEABZ+nSpVFdx9ChQyWx18knnxxwn5tuukn26dWrV8jzvfnmm7LvddddFzCBXrhJRPft2ycJx+yyZs2atEoiSoLQsJOFekGy0E1L/0sgSkJRF//8848kShwwYIDTtGlTScpImypSpIgkvyTJ5eeffx40wd97773ndO7c2SlfvrwcW7p0aadBgwaSGHP8+PGZEtDaZIb+yS7d2ASGbkgeyvk4b6lSpZxChQpJEsZOnTrJd5BYNZzElbBt2zZJCFm1alW5Xv/vC3asZe7cub7jqlevnuX7/eE+P/nkk5IcmCSLfC8JDE899VTnjjvuiDgJYqBnsXHjRmfdunXO1q1bMyX5dCep9E8O6p/g98MPPwyaJJP740Wg+xbNs3AnKSWxLElpCxcuLAmOa9SoIUln6b/4zW6415yHc4fD66+/LvtXqFAhy33zYsGCBbI/SZz9v5s+etiwYZKQl3eBPr5EiRKSZPauu+7KlDg3ECS2fO2115xzzz1XkvzS3vndxx13nPTB77//fkwSO+cUX331ldOxY0ffu8pz47fzHoRKcuoFxz3yyCPyvnAvue+cm35kxIgRns+M/iGcRKmB2rOSuCSiUQtXdKoISAhXZIyNhEGDBvmO5TzRYDPr0hEEonv37rLP7bffHvJ8Xbt29WXhpfG7lzp16viy+Np14XQ26ZihPeJM7KGysyNkhRAClNwNgzJZ90MJe6lO+/btRQCLpG9RFCVFMrRb51HUxP7Zm0NBWgNU59jfg4WghoPNZ4PK2vpcRBvl4T7GC8xJhNVDohyiU97XytYUtJSpnSWBqJJ7sWZAiXr915yGj0q6Z5zGtwlzMabE3FijT1HSnag947AH0zHidIf/QSSwP8fRwUZb1Rv/D2z9gaI86Kis7dqr/Ig/hBMHij6xyRet4ydLuDlP0omY+Fo5GcYc+jeaKH+RI9nZlZQAnyJ8GvHlYYkm+jHVwKcMAcs6wyuKkruIeqSykUO2nlik2OO8IpAihTxBQKI5m+vGarOuv/56+Zv6hzanCBDRgoMxgpISOxA4M1xRoNkTrFRrlaoQJIAzt9X4Eg3orvuoKIqSm4naLIg5kHBerxDzcLAaK84TLUS83HTTTWbo0KESjYHARKQToa6Y8Ihe9DddMmMmwkPNerHPxL7nQJSaCNVapWTbIHLYpiNBoGKCle5mQEVRUouoR6vjjz9eOkx8jyKtjcX+ZHJHo8F5YgEhz4QjU5CWtA/kvcFkiDaLnD6o25WcNwe6BatiBfNH5muFxirj8BHhyqJaq1wP/QRmQCtYkQ7C5olSFEVJJaLWXFFvjJwmJIIjBwdmtnDyspDjhNwcHIdwZRMExoI+ffrIEm6dNVvINlyyc0w6DaArt/yXib1exRImf94IEiFaU+DB4LXNlNwHbcD2DZjmcWDX2miKoqQiUWuuSBpofZjQEpEILVQJj8WLF4vJzmYGJit0tMkHleRzYic6MCLBCtBW+QtWBYqpSTAXC9tMpCz4VqGtwlyvgpWiKKlK1Jor6iaRzRYtFJ0lhUJJi0C2YjL7UjbDZmjHLwtTnS2yTMfLMWQJjoXPlZJcRF0/sHyDI0KVLDoQ5zYQqvB1JCqQjPm2lEukUcWKoihpWf4GcyC5qu666y7fLHXBggWyeGFrCeLMii8UNbeU1DMJRg1CVV6NIMuNYO7HvwrBCoGK6MBkK3OiKIqSU8TM1kJNJJzazzzzTPl/sCrl0LJlS/HVIkmekpomwagThiq5Dt5v0qqQ/gTBCh8rtFYqWCmKkk7ERHNlwQyIgLVs2TKJAsT8R0QgBUWLFy/uK6qLXxbFL5XUJVsmQU29kBJmQLRWQGQu/pgU61UURUknYipcWUjKyaKkX6mbKE6gCUNzOeSMs9G/NhpQURQlHcm2cIWD+qxZs8zKlSslbw2dKfX8MAviwK6kD7GpIahaq9wOUb+YAukL1GldUZR0JmLhCkHqnnvukYLLOKn6Q0JAIgfJhF6yZMlYXaeS6jUE3ajWKteYAdFUWQ2V9a9SFEVJdyISrihzQ36qpUuX+hzT3YMo6+hsX3rpJcmGTtkZreieXkQtWCm5AspF2TQL+FSRbV1RFEU5QkS2F1ImLFmyJNM6/yhAuw6ndk2xkPrEJP0Cbcdd6ibK66H8UY8ePcyxxx4rgz6168i79n//93/ZroEZLQ8++KAInXwmMzYXVbD7i/aa1Cvc48qVK4vjuj0unCXc70p2qlevLtf/xx9/xOX7snu/WrduLcdNnz7dxJs333xTvjvSihbcU47jHucmiJS9++67JWCL9wJN7jnnnCPKhkjZs2ePJNq+8cYbzUknnSQJeLEM0a9dcMEFklPSi4MHD4pi44477jCnnnqqWJAw06PoOO+888ykSZNi8EuVmGmu5syZY7744gtp8HSwFEa+8847JUKQwYucNt9884156qmnzHfffSf7fPnll3Icdf6U1INnfCjDiU36hRiUu1m/fr3p3r27mTt3rrTTU045RYp100nRDmmbFPUm6e0NN9xgYgWDVps2bUyrVq0SMoDF0wzIe27dAc466yzPmqBvvfWWfHbo0EE110rMQeBavXq1WbVqVVIJX5s3bxaf4xUrVpiKFSuac889V6w9n3/+uSzUvR0wYEDY53vvvfd8lUtIxo3VCNP7zz//LBPI0aNHi/sNbjpuiNjn3QTevxYtWogfNIqRTz/9VJarr77aDB8+PFdPbpIeJ0xuvPFGJ0+ePE7evHmd3r17O4cOHfLc7/Dhw07Pnj19+3Kckpm///4bNZ98hmLv3r3OkiVL5DOZyMjIcFZs/Mf5ec1fvuXQ4YzIT3T4kOOs+/G/ZfNyTh7xabZv3+7UqFFD7mujRo2cxYsXZ9p+8OBBZ8iQIU6+fPlkn+eff96JFdOmTZNztmrVKuA+W7ZscZYuXSqfyQy/w6tboP1t2LDBWbdunbN+/Xpnz549Ic/BfcnOd+UWqlWrJte/atWquHxfdu8X7TKc55ETjBw5Ur67X79+ER134MABeV9+++23hN/3cOnatatcV7t27Zzdu3f71k+aNEn6HcbDn3/+Oezzvfnmm87ll1/u/Pjjj1n63qefftrXHqZPn55p+9SpU2UMnjlzZpZzfvDBB74+8K233nLSjb0xGE/DHb/DNguijQJUnS+//LJkV/cC/4sRI0bIfvD999/HSg5Ukiw60GqsoFjB/NEnDaXcTTad2VGdE7lKxCoq+BNOOCHTdmZ8JKxl9miT3uI7GC8wD5CeJLc6fONbxYJ5gXx19v1WlJyAdsb7UrNmTZMbQCv0ySefyLj4+uuvZ0pD0rlzZzGL8v489thjYZ+zX79+ci5yQ7pB23TrrbeKJgveeeedTNvJIzl27FhfQm83559/vs9E+/bbb0f8O5XwCVu4Qg3LQ0XFSD3BYLCdB8sgHC9/BCVx0YEnVDra1CgbZiFeBKqMw/8uhzKnX8ibP1uCFULVBx98IH8PGTIkaJTq9ddfL/4L+CU8+eSTAf2iaO+XXnqpqPfx28L8xfq9e/+9Xpc/CyZBq453+xa5TRaBfK7cPinkiaLT5Di+s3bt2uaJJ56QThnWrVtnrrnmGvG5IOM5fh3Dhg3z/J1cP8fS0VatWlX2577w/jL5secMhtuPksGC4xEOEVRjzUcffSTXRjoHTBiYcykEH8rXiQGN30htUn+/IkyYDzzwgPjb4a/Cb2jYsKF55JFHxFTsD/fklVdeke+2firlypWT9oI5J1hfRtLks88+W1wkEDwbN24cdPDi+yn9xX722pgQ3HvvvXLdkbJmzRopQ2bbK20Hc5F/ew0H2qCt+epP/fr1ZVvTpk2zbHv44Ydl2/333x8wfQ8l0mrVqiXtEZMVAgTtOhyfK/uu0LaBiZT7ffM3yeMmwG+pV6+e3F/uMz5IL7zwgjl06JCJJePHj5dP2g4mPH8uuugi+cQkR98TC6zQxbOPx3FKZITdS9Lxg1fD8cLuZ49TcheUiJw1y5gNG4ypWNEYJkFeykqiA/OFq7IK5l8VRfoFOiwGRgZEHDaDQSd8ySWXiN8Cx9ni4W7w5cBfCyGCMk0MUAyeDz30kJkyZYosNjquY8eO8vfkyZNN+fLl5f++nxSBlorIO3wTKRvDxATHWPLIDRo0yKxdu9bcfPPNInww4OPnSOUDykfddNNNMlDj/+iG2ex9990nAxCCIZ3+hg0bxPcMR1j8IZndBhKI+c1cAxMlq6XOqaSgCED4jvC7mOUTDEOB9y5duojQhR+dF/jOMVA2adJE7juDqb1WNAmsYwBB4LD3Dn887gvnZTAmJ5eFFDIjR46U58n+aOhw3Ed453vQFHj5+LzxxhsisCEo8Z0IBmj6ERw4nmfnhnWci9qrCJMIh1wbwvn//vc/8bVB+xquPxH3C38/fH74rbwDCDLPPvustNtIad++vRxLO0c4sXB/rbZ3/vz50mbdExn2t8f7wzjA8yWghPbdoEEDaYsIoPxu3kf3s/ACoYx7Srvl9/Xs2VMqf1jc/n28G926dRNBlfuIDxKR7Dx/BGXefZzFY5WPjWokQFv0wq7nun/99VcRUqOF8wDPPB7HKRESrp3R+lANGDAgYh8tJXf5XH30keNUqSIhfL6F/7Pe39cqIj8rf/+qKP2sLJdcconczzZt2oS1/4wZM3z+CitXrvStf+CBB3zr8Z9w+xWtWbPGOf7442XboEGDIva5sufm08snheXcc8/N5Ksxf/58J3/+/PIO1a9f37n22mvFd8zy8ccfy3ElSpTIdBzMnTvXWbRoUZbrwGfqpJNOkuNGjx6dZbu9FvZj2bFjhxMpkfpclSxZ0vnuu+887xf3PJDPDb4jn3zySZbtPLeaNWvKPvfee6+zf/9+3zbu04UXXijb+vfv71u/evVqWVelShXxLfOHd5B9vK6jQIECzqeffur5XI8++ugs/mnnn3++bGvWrJmzdetW3/qdO3c6nTp1km1nnHFGwPvlz6mnnirr+/Tpk6mf4HrtfYjE52rXrl3ym4oVK5bp3uGjw3lOPPFE+fyIDsHjGPyl/O8DS4cOHTL1efhJnnzyybLt0UcfzXQN+FOxnnscqc8Vz6906dIy/rz00kviB2zhfrdt21aOf+ihh5xY0bhxYznnc889F3Af3lP2mThxYtTft3DhQukbON+ECRPCPo57Q5vkuKFDhzrpxt44+lypcJUAklm4or/MkyezYMXCOpYxYzJ8ghVCFsJWtoSrQweO/J8lCsEKOnbsKPfzggsuCGv/ZcuW+Tr877//PsuAXqRIEc8BlgHUCjPu5xEL4ap48eLOpk2bshx33nnnyfaqVat6toGGDRvKdgTGcJk8ebIcQ2CKGwQ3t3CFYBXR882mcOXVye/bt883CPz555+egyvOvl68/PLLsr1Lly6e2xFiypUrJ4MTA7wVRjmG+x0u9jpuvfVWz+1169aV7W7HYgQe+kT6Ri/n5rVr1zqFCxeW47799tuQwtU333wj6xBq3IKaZfz48RELV3DmmWdmcZa2kxgctPlE2LfYdQiHXu2b6yMQwsvBmu0IPLESru68807ZHiiYinuMIFi2bNlstW8vateuLd/56quvBtynUqVKss97770X1XfRfhs0aOATWMOF9xtne46j33ALzunC3mR0aFfSwxQ4cOARccofu+6WW4/sl+3izBbK2+TNd2SJcziw25fIC3xnvFIIYKbCTEaepx9//DGm14QZEv8ef/CdAfy6vBJ12u2YbPzBDIL5Ax+Ya6+9VvLO4duFzxUsX748kxkQU6MFHybMNPEI1SZk3R98cmrUqCF/e/nkQK9evTzX2zw+OO96gSkJMw1+Nz/88IOsw3kanxz8vDDNYRqO5voBXx//68dchQkbv5cTTzwxyzHkDSOFBYRj0rN+RpgjvXxhu3btGtLc5oU17VlTH5A7CdMcpttKlSpl2hbMJAjcby8zlNc9ipZQz597zHtDe7cmstwC/lq9e/c2ixcvlvfD35k9GPQBPEPaCaZVcmYpuaxws5I7wcdq7drA25FJ1q7JY36cm9+cenpsHUKjwfo2kVMmHPBNseBX4w9+SoHAfwO/KPygYglO515Yn5JA2xEIbMZ0N/j8MLgES5qKkAj4bOE/4yaeGdcD/Tb8kbx+myWQTxI+UoBvHUswrEDJfcTfCgEUp3IWhAHy+SG44JDs9u/J7vVbISJYG7MRcuEIHLYdBjqfdQrHpykSEJLwhUNowh8OHzYE+Ouuu0624zPGwI5zOf61oYSr7D7j7GCfv1e0nNfz98rV5ob8jZR78wefLhb3e4hPVSB27dqV6TdHCpMBkoeSb5J7jl+eV//lxcCBAyXykICLr776KuRvVhIgXL344ouyRKIlCJS2wb8TiHUEhxIZOK+Hw9ZNebKXMDSHQOvz7rvvijaJNhQqmg2nVmAGl90khKG0X5FCCpNotrtBWKLTR9hEWGBARONAp867SJJDIg3tb0CQYn2i0itE8tvcBLpeGwmJUESQQTDcATo4SCMcTJgwQYIJcPwnCowF7R+DEtGGsbr+ZIZoQNoLmj2c0a3wZJNTcp8QrrgnONCjSUHz6nV/4n2P7PNHs0nkaTBCRb7Db7/95kuM64a+wwpX/E3/E2gyw0TGTmay0+eQwLdv375m3LhxEi2MVjPc4DJS0JA8meADAln8UzsoSaS5CmdgcZdqiPVApOQM4QaPlCnvRGYStOVtYlTixsssQwfCIEBoPoNk4EtxfKp0zHxevyGYSciG41epUsUkK5ieEKyIXiOSzR9/UwgDHzPgVBESGHyIoLviiisCmg4DgQnNrfEi2pDoMtoVudSIbIsGTFJu7YoXdpvdN5zzBUsTYVMXRAITFCIQMSszkCNcIYDbtCNusyFRpLxXaLOSIeM3z582TgRtoOi9SMCUHqp8D+8ags+8efM8t9v1CHuRao0QrC6++GLJyG4Fq2CaTzeU/CKlBu0awSoW90MJj4h6U/8aguHsq4JV7gEtOjJDoP4xTx7HlK+UYRo3jUDDaNMvbFxozKbFJifAjNKnTx/5m3pa/iYuNxQVX7hwoQwe7OsFnZDbdGjBHweTICYAtGUW67uQLJpXQv0DmWKY1VuBy/1upopgBZ06dZJPBqNoYTAjBQeQOiFaSO3BveZcXqY60mVg9gEryAQDAQg4xj53N2jhgr0PwbACFKVbECoZmG3qBXyu8JfChwftlXv/nCbU+xbL5x8uVoOFttNLe0V6DTsRjCT9A+8r+fbI42cFq3ATq5LGhZJfCFY8I3J8KUmoucpOvhQld4H1lgTmTPYRsNxysRW4/u/BvZ75rgKCtso/r1WBYkcc2mMIpmr8jNA6kTcI7ZQ7SzsdMapxZnJAgk3/LO5u525MaZgarekJfxO0Y9Yx1O2TZLVYzJZxOI1V7pzsYp2EGfjwlbE5dbg2MtTbhIepCnXT+J1jxowR7QX+U9YnxrJx40bRytjabeQpwlyKicvf3Mh+EK4ZJhgIvDgkUxuOhLA4X1vTFP46XDv+R+SEYgkFfkVoTTBJUS+TRJsEA1itG5UIsosVlshFxTVZk6B7O0lsbQLfeAlXvG+8a7/88ouYu/1h0sQ1o7HBLIzm0d95m34CQQiNUCygLyF4AA0nGlOEWtuOEE55LgjVJFH1B+EJVwU0oyxuwQqzPoJZpIIVbZ4+zpoCVbBKYuHKzpCU1KZHD2PGjj0SNej22UZ+IGHz8acdjK68DUKVLLE1HxDdhuMpM0hU8Ph+MNOmM7KFm3FepZMl+SQOnoGgsyPBINE4DF4MLDiPMviR6NNqMtwDJt/l/l6ELxztycIdb/CpsB09f5NFHv8ZtCW///67JB5F+EgGE05OgOkFoQWzL1n4ybpOZB6DMm0BIYpkmPgIWeEK0xnOwja7OoMZAvmiRYskqpJ245/RP5qJAGZLSoPRPtFQoUlFO0QbxeQzatSosM/HRIJnjJCDSZgEqPxO2iy/m3ZI+48UhHI0VDYSNZBwxftB9F0gp/VYg9kfQQPByGbFt0IVvoQ8Z+segHDJcyNpKQEKuA7w7HkPmjVrFjPhCmhnTGYwlfJc6TvQgPNc0RLzznlFiKLpoo1t3bo103oS19os/5yPwAIviHRFS2VBsCPiFRA+A/lI0y6oaKHkDBotqHgKWF27Zs3QbvIY80vWiP/gWqsYlLcJF/xPGLAwBzDQ4IyL6QVBB60DQhMzw1AOpQxuCEqUD2GAIsszAwcRY2hCvBypyfjNrJROH60EAzPfmQjhCtDa0JnTOSN0IhxQxoXaZghctsZiqoImAfPv8OHDRVPH3wgYDCgMvgy67szvRAXyrBBOGHzRZCHwsC8aIbQfDNyxAE0VGejRpNJW0CygpaDdIexxbVZgCFcIor0S3YeW5OOPP5br5ppxxCd1QnaxUYEIrEws3CDQcY9o6/HSWgFaZaoHoFnGVG8jDRGU7DPC/IpmCwEFQZu+gNQkCNS8y+wbzDczO3BungPvGP0BAh73jdQaPFNbCzBc3GZe/9I+/ooPt3DlPo7rCeQHRv+kwlXOkYdkVzl4fsUDokawgzOLChWWS8eBCpuON57h8aGKNVNPMGDZG7cDu/WzqnDikZxWSQx1/9BKMUj51wDMrRw4cMA3I8Y0RjqBVNVYKYqi5PR4Gu74rZorJeJizUHTMASrH6jEHTRWdARoGKwvjqIoipKzpE6IkJKjWquVW44kwIOgaRji5MCueIN5iegwnNctmCZUsFIURYkfqrlSYq+1ioMDu5IVBCr8w/CBwRxI7io1ASqKosQfFa6UiAiptYqjA3uswc8qN/paoVkkOgwfACDkO151ARVFUZSsqHCl5AxlaucqwSq3mwFtxBTmP3LbhFNySlEURckZVLhSIvK3UpIHzH9kjKc8BhC5gn+VaqwURVESiwpXSmz8rZS4g3bKaqjIi+SfhVpRFEVJDCpcKWETUbFmJcfMgLYoOgtCFZ+pVBtQURQlt6M9shIQNQkmF0QAUh6FJHYWNFcqWCmKoiQX2isrsTEJ+qdhUGIq5O7atUsyreNfhfM6GixFURQlOVGzoBIbk6B/GgZNGpoj0YCUbCAaULVViqIoaSpc7d2715fUMF4V05UkQNMwxMwMyPtjowHJXVW0aFH1e1MURUkn4QrzxdixY82oUaPMN998IwMDMBggYLnBxDF69Gj5u3bt2uass86K5aUoUaL+VonXWFHdnk/8qkqVKmUKFCiQ6MtSFEVR4ilcLV++3Jx//vlm0aJFvsE5GKVLlzbPPfec+f33302FChXMmjVr1NSRRGgKhsRis6xjDuRT3w1FUZTcQ0x67KVLl5rTTz9dBCuEKhaSGbIEAm3WddddJ/tu3LjRTJ8+PRaXoiTE3yo5nNl//fVXc+ONN5r69etL28M/qUqVKubUU0+V9R999JFJZvbv3y+L5cMPPxSN1eWXXx7xud588015ZpdddlmMr1JJBniuPF+ec7q0i5tuusmXguTTTz8N6/6E+p32flSvXj1ozc6RI0eabt26iXtLkSJFxDxfo0YN06tXL7HUYMJPVqZMmWI6d+5sypQpI9det25dc88990iQTHbACvXSSy+ZFi1aSCoYNOqcu127duatt94KGmyzadMm6YuPO+44qSZRvnx507t3b/Pjjz+aVCNq4Qp/kB49eojTLYJS27ZtzZw5c8zOnTtDNuw+ffr4/v7yyy+jvRQlUSbBJHBmHzdunGnYsKF58cUXzebNm03z5s1Nz549zYknnmjWrVsn66+55hqTrPeb94Vs624fq0D88ccfIQcERYmEZG9TTDoQYixvvPFGXL6XQb9OnToywZkwYYJYXM455xzTpUsXESg+/vhjc/HFF5vjjz9e6nsmG88++6y43HzxxRfmhBNOMOeee67UIH300UdNkyZNxD0n0ueAEHXDDTeYH374wTRu3Fj6We7RtGnTZMzn/46H5WrFihXSH9MXo4lHWK1WrZq4EjVr1syMHz/epBROlLz11ltOnjx5nLx58zo9e/Z0Dh8+7Nt24403+rYFokaNGrK9Xbt2Trrw999/0/LkMxR79+51lixZIp/x4tDhDOfnNX/JsmLjP05GRkbgndm2aanjrPvxyHL4kBNvNm7c6BQvXlzu6W233eZ5r+bNm+cMGjTISTYOHTrkbN261Vm3bp0s27dv971DO3bscJYuXeqsX78+0zGrVq2S31qtWrWA5w10rJIa9OvXT9rAyJEjIzoumjaVSN5//325vkqVKsmYkj9/fnnvQ90fPoPB/Qv0u+fPn+8ULVpUtnfp0sVZuXJlln02b97s3HXXXU7BggWdv/76y0kmfvzxR7lX+fLlcz777DPf+t27d8t4y+9izI6EZ555xne/Vq9enWnbDz/84Bx11FGy/f3338+0jTGkUaNGsu2SSy6Rfs8yYsQIWU8fvmHDBicnicV4Gu74HbWKwUqbmGBefvnliH1DGjRoIFIuJh0l+cgNKRgmTpwoKu5KlSqZIUOGSFv055RTTjGPPfaYSSaYBZIUlE/uMSkWULPbdwhfK1T4FStWjPjc0RyrpC65tV28/vrr8jlw4EDTqlUrMU29/fbbOfZ9mAIxV6GNQsPyySefiCnLn7Jly4oWiAAuzFzJBP0dY2v//v1Np06dfOsxaXI/6WdwlVi2bFnY5/z666/lE82VfwYANGEXXHCB/D1nzpxM2z7//HPz008/SR+HSdFdWP7qq68WbRh9+PPPP29ShahHwvnz58vAgP2VhhYpqFYBk4iSy0lQCgbs+JCd9gd01K+99ppp3bq1+DjRSdKR4hNIoIU/+AfS5tmfTviJJ54QlTv+DJgNMJPjhxjofSHwo3Llyuaoo46SSFn8Fa+//nrz1VdfhfSP4W/bya9evTpTKRy3EOx17IgRI2Rdx44dA94L3kN+P3UKEfzcYLJ84IEHzMknnyzXTieNKfaRRx7JcZMI5iquHfMV5oezzz5bBFHuOaaJYAMt1/b444/Lfva6eV733nuvL6I5kImMwemVV14R4Rw/PoQTvtt/8AgHvp/z+vuXYMZmoGPb//3f/2U5DlcLttmBzZ9Vq1aZSy65RAKDeHY1a9aU3+b234tFm3K34b59+8rgyvfxznTo0MF89tlnJifgeUydOtXkz5/fXHrppeaKK67IcdPge++9Z1auXCnvQThKA/w6aYvJAj5gkyZNkr8vuuiiLNsxx+E6AZGY47wmrsHGdYv9jvPOO88UL17c+GOvEfeOVCFq4cp2wNm11dvwcv9UDUpiyI0pGOwMavHixdIJRwK+TvgkXHXVVTJo4BNAB8CgMXz4cNOoUSOZcXmBYIWj6MMPPyzXgC8GAzAdyRlnnCGDghuuDUGKFCQMSAzSCGgMiszscJoNBZMYfBqA7+rXr1+mJRjMKhkAEOLwQws0qNAx45vhFlaXLFliTjrpJPmtCANcR/v27eX9v++++6Sjxpcjp2FAZZZLmgqERAQ9ng+/nehjf9iPa7vrrrskMhlBhWfGb/jf//4nQpP/c3LDrB8HXGbc+NnwrLh/bdq0Md9//31E1879sg7Gbvi/9VHx30auwNmzZ8tzs4OhmwULFsg9mDVrlmh0WrZsaTZs2CC/zWoRYtmm0Cw0bdpU2gkTCd4VBFUmHLR/2kdOPHPuD8+N+8+1IuSiceHe5ARoqgChke/MbeDfZCc8aJS8sOsD9W9eWA0YflN//vlnpm30nx988IG01UsuuSTTNvsdoa4FC9bu3btNSuBEydFHHy0+U/3798+yLRyfqx49esg+FSpUcNKFmPpc4fO0f1fMlkN7dzoLV66T5dc1G52MfTuDH7P3b8f549sjC39H8n3BfLkiYOfOnU7lypXlntKWWrdu7QwePNiZNGmS+EQE46KLLvL5VGzatCnTtmeffVa21a5dO5OPwLRp02Q9C34Ebj8BnlOHDh1k29VXX53pfG3atJH17777rvhV7dmzJ5MvzJw5czz9Qfz9RsLxjwl0bN++fWX9Y4895nmc9Yv49NNPfeu4zpo1a8r6e++919m/f38m/40LL7xQtvn3AfY6I11atWqV5br4rWwrUKBApmtz/1b6Ivc9hfPPP1+2NWvWTHzb3G2mU6dOsu2MM84IeN187/Lly33baAeXX365bDv77LOdSJg8ebIcd9ZZZ2Vaz31j/Yknnijtd8uWLSGPsT5FLPfcc0+m9rlo0SKnWLFism327Nkxa1NffPGFXF+ZMmWcGTNmZNq2cOFCp0qVKnKO6dOnO7GC9+TYY4+V83788ce+9ddcc42s41nkhM+V/c6HH37YiTXu/iOSJdRvcTNhwgQ5pmTJkiH9p5o0aRLR87j00kvlOPzM2rZt61xwwQVO8+bNpW3Qhv3bHJQqVSrLM3SDr6n9nYsXL3ZSwecq6jxXhFIy+8+uz9TcuXNF9XzsscdGeynpycE9xjxaKWanwxLe0MSJu9cbUzBwuo5wQc2MVohZNtoEZtHu1B7M7IkURDvltvVjunv//ffFV4uZOCYjNzfffLNoKTB3oFlCc+GGdou2yT2zRW3+0EMPmcmTJ/u0EDYacP369fJ/ZuCYGdxmBGbip512mslpiHoi6grz0KBBgzJt+/nnn2WGye9xmw4Jr0brw+8fPHhwpmMwsWE24/6/88475umnnxZznX0uobRpXuATFIgBAwZkeQ6YtTDNosmYN2+eOfPMM2U9M+sxY8bIc+Ia0bRYuLZXX33V1KpVS7QfLGgb/Rk2bJhEglloP2iF0KbMmDFDtJfhJnflutCI4p+Dyc766HDvMNPQRvFl4f+YjsG2Iav18gfNG8/Ebb7DjxXNAZpXjkdbGgswCdOWOS8aMjeYh5955hmJAOeeoUWLBUSRY5pnnEEzZsE0iJkbLTDaNC9TUywsMuXKlTOxhvcrO+8FGsZwob+BYOmQ7D1zF4IPBf0WfQcafrTBblM1fQHtFLN0pNfjfn6RXE8yE7VwxYuLYEVYJr4vvAThYs0TdAz+L6uiRAKhwN99950I6/gaIGTh20IniekE/ymcN9mGHwUgNDFYoOr2F6wsmO3Yj8HXf1DHFIipzJ969erJJ22btAr49WBqY1+S7eKvcvfdd4swhR9JPMGchQmf68BvyD3wWrMkfi3u67K+G3bA9+oYUetzn+gHMHdav4tI8zCFAnOlF9xzhCu3uXPmzJmScwdfJwYDf/B7w+yDCQg/Ln/hinvg5Z/G4IgAyXPFRy1csxHCNN/BdyFgYd7EfIMQeOWVV2YyG4YrXNEmvfyi3G0wFhCyz7vFbwj0DHhXIJamOnwhvdokPk4IkbgCkA/O+mHlBpg8xPq9iBcIPhdeeKFMNpl80q/yHuGfhgM9Ajb97KxZs9JeYRJ1z04kBc6kzOCQZMN1MkSSJSmchcgMJRsUKHpEAxQjDmc4ZsmGIzOH+hVLmHxeqdnxD9n2uzEH/Wzj5RsYk/c/zVBY1x5j8AdhAQQnNDFPPfWU+AIwUDHLveOOO2Q7HQIQOWOjkQLh79wNgepllihRIlM0IAM8AyBO1b/99pt0TCzWGZtBCYHLDog5iXVmfvDBB0WYssIV76/NI4SfkRt7n9CG+PtShHOfYkmoe24LXLsFC68oL4udZXsJIUTUBdJK8X0IV+7vu/322z3zBrkHUoQkhCvaIsKVFZ7w+0NDxoBk1yG4MTFA44bvX7T3Ixpwmud9wgcsVFRcrNoA5yG3FHgl0mXdrbfeKmOOv3BlBc5QlULsdn8BFX9DNGb45uVG7GQxmP+STSJq20o43HbbbTKJIgAHQcqCoEv/QZtFa3/vvfeKxtt9Pfg/Broed0LTSK4n5YUrZuSYFLiZOH4yiFjtgBdkcmcmwuyZRk0nQxKxWIEpAIc7rgmNAap/Bq9bbrklovpsDMwkX6OzY4ZE42CWTkPCWZQQ0oTXe6NTiIFpzUeGY5wC/wYXcF4v4SqDJJcZxhRwRccUKGZMoaOSqmAzbQvhBdMfzp101CT9s8KVzSSM2dBLA+XGq30GiiByd+h8B20ETQczb8xWmJNoU99++61o2PgknJuZ35133mlyGoQrTJfWpIKQR8ZrBAO0af5mOXuf0OKE0kxj3rJwPgSOSOH7/U2WlniWAYr0u0iGSLRdKOGK7Nho7XnetAO+hz7QbkfoRQhH82oTMwdKhxKv+2HbAP2fdX7PaTAzI/Tz3qDZCzQgoylDa+lut9b8FMo52p7D36yIuRXhCk1srOFaGSOzYxb0ug9e2AAzknujyPDSzNtI6HCD0dDC80wA7ZUXRP25XSIsfAfjp78TvP+10M7dfUhuJiY2CYQqzHo8RDpr1LSEoyPcWFhPmRsGEl4GOwBhOgilNYgEVJV8Fy8knRIvDXZhBi0GEGz44YTMEr3IwAycAzU0A8vatWvFnIJaH40dDQmBMm0iBf1L3aCtIreVLMkjWPmDqQrhyq1ZsGprorBeeOGFmH0XHZq7k2cmZgdHm8LBmlDQLDD44muDqZByGl4+C7GEzot3A98eQp+ZeFgBwEtDwH1iQEA7wPWFCwOXe/YaLvjrBBKuIgFzhVvz5oXdZveNhmBRhxbMp/QXTNzQzKDFQri3/mBWuGJwsikbApkE44l9V2i/aIriIdTZcYG+mHEj1L5oqP01egipwbC+wv4awK5du8pEjP49UneXUDAOZue9gHCFK9wk8IFiUsmEDncAf1gPdpwLBVo8m94jkHYJ31HYvn17pvV8B+3ZfmegayE1Taz95xJFTN4Q/BkYuFCl2lqBJArjhbCDCurbJ598UtYxC2I/1O74c8TKNsvLYJ0b0QjwYmD/5QXC4RKBiLDxcGH2wuyeARkBDQ0ItmQ6Rq4dHwR+V1oUa0aoQmOVcShz0tC8+Y+YAhMoWIVS/YOdMVFr0D+smLYbK/OJv9MmnU2wJKw4wF977bXyDvFeLFy4MOT5rVY4mvQlVohCqGLwsGZKL78qe594FyLB5omKdIlVnVEmfAgBmNbcEz0LKQvQTIPX4JMTcD18F8+a/hBBHJOgBQ0W7QXNVih/q1gSqk0R9EEbZQJt71lOwgSW9B+YIDG/BmorNrcWGhX3tTN5AN6nQAIWWjFrdrT7W5hw0H6xfOBXFKxenk1DgMk0HJhYZee9iMRPi+dpAwAI1vEHDav1jevevXtY52QCYE3CgdKQ4PfqZYrv/u93cL+9tIn2GlHKpAxODKEcAaGxhQoVkrDMQAvh1IQfx7o0x6mnniohko888kiWbbNmzZJtXBth79HyzjvvyPmKFCniHDhwICXK37jL3vC3D1ImbF7+X4mbBJa68eKFF16Q8OBvv/02yzbKLnz00Ue+MhavvPJKpu2Uf2A9YfmEo/uza9cuSZ3gLrVhQ6ltygC+Y9++fZmOs2HFbp566qksJSOAciQ2dJ6SG6HC5mlvhEFT1mLbtm2e9yTQsRbaE2HapEkZMGCA7HvxxRd77ss9sKkQ/u///s/5559/suxDOgr/extL7Pd7PaNg5WACpWLgN5F+I1gqhmBpCUJdTzBefPFFObZw4cLyOWXKlEzbGzZs6Nt23HHHRfR7Qz3/aNqUDe8vV66c/O0P78F3330n6SMCpR4IlyuuuEL279OnT9D9SEFBGh/2HT9+fKZttsQLz95/rCFlh/2OsmXLepaumTt3ru85nHvuuZ7lb7hXpCdhXEm28jf0Jbb8zeeffx52+Zvvv//eqVOnjiz+9O7dW44rX7688/PPP2faRju292vw4MEBy9/QV6dD+ZuYClcW8rRQW+imm25yevXqJTlaunXrJrlJ3njjDamhFmvWrl3re4G9XgJ37pL33nsv6u8jF4f9vkiFxFwnXCFE+QtWCFsxylMVLTYfle0oyT9E/qrOnTs71atX921DeHDXvgQEBdvRMLggoNOh04nwN+vYhgDkJVwdPHhQcmnRpt35n7wGE/Iwsa5u3bpO9+7d5RrJyUWdNNvphCsg8V6xjTZNnikGCpZwjrVce+21mfLofP3110Hbu72XCGUtW7aU6+e9rl+/vnTidLjJJlwhUJ100km+PFhcL/eOdmKFF/9z5rRwRd4se8+ZnPkL5rfccotv+1VXXRXR782ucBVOm4Lnn3/e115r1arlnHPOOdIO6OMRulh/5513Zjpm6tSpsp7jwoEcZLZWKLnqQnHrrbfKvgjLbhioEVStIEtOJvK8sV/p0qVlPfmXZs6cGfDcCFj2WdPGGzduLPeJPgKhDcGFbdTI9c+xlgzYXFY2/x/XXbFiRVmH8OTOqRaOMMw4y29lG7+d/Fack1xZ9hju816P8WrZsmW+945zMPFp2rSpr22MGzfOyWlyvXCVCEgsaF+WQDCgsc8dd9wR9fcxS7IDsn/nmBuFK2YWFGnOIlz5F2Y+dOCIsJUkgpUVkEhOhwaGl5VkhmhHGbhIfslA4Z65+YPAhcCNMIaAwLF0vg0aNBANK8/arZ20nc+ZZ54pgjWCFZ/uZ+TVOaEB43ycl3bKbJeOG60Z3+FfIDvYQMiMmclK1apV5Xr9vy8c4YqBwx6H4BS0QPe/9/nJJ590Tj/9dBGw+F46aoRQ3imv5IGJFq7sTJ2kqSeffLJoMBlo69Wr59x9992SvNCfnBau3BM9/+SggEBhn8uHH34YN+EqVJtyJyklQS7JdbmX3FMGS5LnDh06NMvkmTbDeTh3OLz++uuyPxopt4YjEAsWLPAN9v7fjcAzbNgwESx4pxnES5QoIVoUCi6Hoylh0vTaa6+J9opkxby3/G4EcwQtFAmRWi/iyVdffeV07NjR1+fw3PjtXhrocDSNHId1iPeee8l959xMNtFCBXtmGzZscG644QZ5fxg7EbZIJO7W2KeKcJWHf0wKQOI6UjvYchheUPRz6NCh4pRLRGF24ZbhBI1fADZi/LoizRWCLw7lQkKFneILRBg0Nuxw6zplNwXDL+v/9vlb1Sr3b8Fm/Kw2LvzPx6psnaR2XI8HPH+eofUdwL8BJ+V456xSlNwAPmX495CINjeWklFSh30xGE/DHb9TZjTIqYy0XhDGjmDF+cIJqSXCwl1ENdkz0NYo+69glSSFmZMJnGZxsMUZFmgDhDkHc1pXlHQFJ28CiciPpIKVkk6kjHAVL0i/QHFSon4ISSZ0NBTks0EgS1ZyY7HmRM58EKx4/mirclKbqCi5HSJQw42iU5RUIn8shI1YQWLRZMtI6wZTog1hpy5ZuFnlyVzvTtmA5iqZSgMETcGgZALNKGHZfLrrFCqKoihKzIQrsj3HwiTCOaIRrmyWWZvp1YtIM9K6Idki2WcZWCkY6pVsMRDkBglVMiJZtFYBTYJpCloqTM5oqdBWcW9SpTyDoiiKksRJRCNNhhbomGiwtbeobYTDmheRZqR1Jyel3A3p/19++WVz1VVXmVRBtVaBIbsxCWQxBVqfPkVRFEXJcc1Vv379wtoPjQ/e9dQVtMIP/iqY1mJRSoHM25SooRYU2V6p3+UGp0o0V2iQOnfuHPZ5KZnTp08fcWRGsLrmmmtMqpJFa+Vf6iZNoK1iukW4stGAqVKSQVEURckFwhV1sCIFDRJpEYi4o1QOvkyxMLVQm400+0TwUbLDaqjQZlHFG2688UZf/SMYP368+ERRW4xaa24orUDaBgSr4cOHS6HmtMLJyFzqhvqBaWAGJBrQltLAlw/BSk2liqIoSlJHC1K8dObMmVL7iBpa+FpheouWbt26Sa4rclmddtppUqcLx2OEJmp4kZtq8ODBmY5Bm7Z8+fIsteUoUkkOK2pLoRUjT4utxeTPkCFDpAB1SpMGaRhoA7aOGdrUY445Jml95RRFUZTkJWGpGIi0eu2110ytWrXE9IbDeCyKNlK4GSHqxRdfFGEITUTNmjXNoEGDzC233OIrUBoKTEI2N9XatWuDVjF/8MEHU0+4SkOTYIECBURDZZOCajSgoiiKkh0SnqEd7dK0adNEi4WQlQ4kS4Z2Hv1vm3f5HNpPqHS0yWc92tMkMztBCm4hCnMg/1czoKIoSmqxL44Z2hPuRINWCX7++edEX0raEXakYAqaBBEsyYmG+ded5JASNipYKYqiKNGQcOHK+joxyCmJI53yWxENiG8VMw+ELH9/O0VRFEXJteVvGORwbAd3BJ+i5BQEKCBYYQ4E1LrB6lEqiqIoSq4Sru69917z559/isYk0sSeSg6CGx5pGFIINFQEKaCtAvyqiAYMN8BBURRFUeJmFkQ4CndZuXKlJPmkLl+LFi3ME088EXEyUiWHhSoc2bcsN2bTYpNbhagPP/xQIk+p34jTIkLUySefbO644w6zbt06WVe2bNm4ClZElDKJ4DOZ4RrDNQ+3bt3at38kS3a+KxmhjBbX/8cff8Tl+7J7v+xzmj59eo5cVzrw5ptvyj2k3Fsk0DY4Ljsl1xIJFSnIG1mnTh0pvk00PEFnX3/9dbbO98ILL5jzzz/f1K9fX85FZHapUqVMy5YtJbKfqP5AIDuQn9JeC/03DunIDMnsq50/Vh1MNJAxnfIySuJqChpD6oXfjDnoV/i6QLFckzx0/fr1kkR27ty50iZPOeUUScuBxoqEtWTYf+ONNyQvGS9rrGDQatOmjWnVqlVaDWAdO3b0HDRs2pIOHTqYChUqJODKFCX54d1ZvXq1RK8lk/CF//OZZ55pVqxYYSpWrGjOPfdcs2nTJvP555/LQrqjAQMGRHTOxx9/XM5xwgknmGbNmok7BhNd+uVZs2aZd955x0yZMiVLJYzvv//enHXWWSLskej77LPPFqvDggULzNtvvy3VWFio9JJ0OFGSJ08eJ2/evPIZ6ZIvXz7nhhtucPbt2+ekE3///TfpL+QzFHv37nWWLFkin7Hk0OEM5+c1f8myYuM/TsbhQ46z7sf/lk1LHYd1GRlObmD79u1OjRo15L42atTIWbRokbNr1y7n0KFDsv3gwYPOkCFDpM2xz/PPPx+z7542bZqcs1WrVgH32bJli7N06VL5TGaOSNkmJufgvuT0dyWSatWqyfWvWrUqLt+X3ftFuwzneSiBGTlypNzDfv36RXTcgQMH5L3/7bffEt5+wqVr165yXe3atXN2797tWz9p0iTpPxnvf/7554jOOWvWLGfnzp1Z1q9evdqpU6eOfN+gQYOybD/xxBNl29VXXy330nL48GHn3nvvlW0lS5YMe3yMxXga7vgdteaqatWqYWuuUAUisSKlI72iJuR4JQkiBY3Lx6p8A2Py5s9V6RfQRGF2Rl3MDAjwryLNQunSpSXFwm233SYqZfa9/fbbZUZUr169uFwfqvCUSzSrKErIMa9u3bomt7BkyRLzySefiHbo9ddfN0WLFs1kYcIsyvrHHnvMvP/++2Gft0WLFp7rGf+pA0yVli+//FLOa6Fs3cKFR3ItPvLII3IvLVTQwMXi6aefluorS5cuNY0aNTLJRNT2HmzKqDXDWVAzUldw7Nix4v+iglWSghkwFwlWCFUffPCBT/2M/d6mV8BG74YakyeddJLs8+STTwb0i0JdzwuPWhyB7Pjjj5f17pxY1p8FkyDMmDEjk2+RW9UfyOfK7cuBMHjrrbfKcXxn7dq1xS+RqFpAjU7hcHzJKMuDD8KwYcM87wnXz7Ft27aV94z9yTpPJzdixAjfOZOFjz76SK7NRm9izqW2ZyhfJwYCfiP+G/5+RUSFPvDAA+JvR41IBoqGDRtKR22Lcrvhnrzyyivy3dwrOvNy5cpJe8EMEsy3ikTImCzw76PNEaCD2SIQfD9tlf3stWEyIciH644UitJffvnlvvZK22HQ8m+v4UJ75H7SPum7L7nkEjHx0o7ITch12goWXvA+kiCa58Ix1apVk+tjDAj1TCO9l4HgXeKczzzzTJZt+P6wrWnTplm2Pfzww7Lt/vvv9zwv+fGoR0t1EX4b9wX/H97PcHyu7DvPOwpMCN39hr9rAe4O/BYmgrQT2supp54qfky2BmqsoNYu8A7wzPy56KKL5JOE38H8pCKBiS/4lxqLpPRYUk5cs60bU1LGLMjfYgK0JkH+xpyGGeG99458/mteS0aee+45n3oYNfO6deucjRs3Ovv37/fcH/Mg+5cuXdrJcJk9H3jgAVl/6aWXyrby5cs7vXv3drp06eIUK1ZMtjVv3jzTs3jsscecDh06yDb2x2xgl9tuuy3Lufn0Mjegiq9Xr55Trlw5p2fPns7ZZ5/tFClSRLbdeOONYlaoUKGCc+yxxzp9+vRx2rRp4zNxPv7441l+4+DBg2XbcccdJ+r9Cy64QMxDBQsWlPU9evTI9NsTaRa8//77xU2Ae3v++ec7J510kqxn3bhx4wKaU7gvfDZp0sS58MIL5ffNnDlT9vnll1/kXrG9YsWKTseOHZ1zzz1XnhHrTj75ZGfHjh2Zztu/f3/ZVrhwYad9+/ZyTp5t7dq1Zf348eM9r+O+++6Taz3llFPkPp922mm+3/bss89muf5t27bJ97O9RIkSznnnnSfPvEyZMr5n5mUqCvRsMDvRbuxvpc127txZ2s/pp58uS6RmQdovxwwcOFCukd9Ku+O+2HbZrVu3LMfRpnh/2J4/f36nbdu2ck+OP/54WVe0aFHn888/z3Jcdu9lMDBjcVynTp0yrad/sOfExPXXX39l2n7mmWfKthkzZmR5T/nNmKroa2hPvLf23vMb/NsUz9Fuc5vIuL+2T+HZu/sNnqeFazjmmGNkv+rVq0tboU3adfQTbnNZtHAtnPfWW28NOnax8I5Fy6ZNm3zvO32pP/ZZBDML+j/fZDELRi1cYXu1i/VvUZJbuKIDxM8qoHA1ZozjVKkiCRl8C///6CMnGbn44ovlfp5xxhnSceJ/xcsXCDos20GsXLkyiwBkhZ09e/b4tq1Zs8Y3QPj7BoTjcxVKuGKhs3b7OMyfP18GKAaA+vXrO9dee634jlk+/vhj3wDtPg7mzp0rfmf+cH9sZzZ69OikEK4YqL777jvP+8U9DzQQI1x+8sknWbbz3GrWrCn70AG7hWzuE0IT2xCmLAjlrKtSpYqzYcOGLOfkHWQfr+soUKCA8+mnn3o+16OPPjpTOwIESLY1a9bM2bp1q289PikMFLYtB7pf/px66qmyHuHH3U9wvfY+ZFe4Yrnnnnsy9e20KysYzJ49O9NxL7/8sqxHUPzpp58y9Tn2mfK8N2/eHJN7GQx8Ljkf1+puA2+99Zacz/rzfOTq19zHuAdz93uKcOPuu+lvrLD86KOPhhSuwvW5oh0yyUPYfOmllzL1abQbBFeOf+ihh5xY0bhxYzknE9ZA0N+wz8SJEyM+/6hRo6Rt9e3bV66/UKFCPl82r8nwsmXLfL60lStXln6ZiSETECaKl1xySVjjaK4UrqxDOz9WyR3CVRZn9gyXcPXqUzzUzIIVC+tYklDAspojXjw6Ry+NjP8LazvK77//3rfedv7MzL0GWDp9K8y4n0cshKvixYvLLM4fZqpsr1q1qmcbaNiwYZZZdigmT54sx6DhSAbhaujQoVm2EeTCYMr2P//803NQuvzyyz3Pawd4NI5eIMSgbUBwZWC0wijHcL/DxV5HoFl+3bp1ZbvVplmBxwYAeTkFr127VjRnHPftt9+GfDbffPONrEMYcAtqFrRt0QhXaJC83icEfbY//PDDmdZbYc7rmXIeK9D873//i/pehoPVfEyfPt23jgGZdVazxW8Jpe2y7yn3ef369Vm+54MPPpDtCAyxEq7uvPNOn4bWC9oKgmDZsmVD9nnhYrW0r776asB9KlWqJPu8h1UjQgYOHOhrjyy8B7fccksWjZ8b+kU0dO7jWJhwvv766xF9fzyFq6h9rqyT2WmnnRYLK6WSyLI3ZC2//6kj4pQ/dt3NNx/ZL8H8OzGQv+31Y6PHXydUgEWoWuX4e3ilEOjSpYs4x1O488cffzSxhLQR+Pf4g+8M4NflVWjUbscvwx98YvCNwHfk2muvNf379xdfGnyuYPny5SYZINTbH55ljRo15G8vXxbo1auX5/pJkybJJwEzXhDu3aRJE/FXIe8e4HSMLwt+Xv/73//Ezyia6wcbLOG+fipS4NuF8+2JJ56Y5RjCzUlhAfgehcL655AWg7bpT9euXaOqfkGb93qfvH7b2rVrze+//x4wbyHnoQ0G+22R3MtwaN++vXzaIBeYOnWq+EvhoF2pUqVM2+zf9jh/aDf4tcXq+oIRqh3TVnj/t2zZYn799VeTG3juued8JceWLVsmfoHDhw8Xv0ac6f359ttvxU9y8eLFknJh48aNZvv27T6fryuuuEKWZCTqaEEGIV4q//wUSi7k+5+M2RCkxiNCyZo1xsyahSe3SRSUriFChAGYdmedGelkwsFdx5Jkov7gYBoIHFOJYqHNx5JAwR32vQq0HYEA/Osjfvfdd9Ipk4AvEAiJyUCg32Yrzgeq/RgoNxABDoATNkswbJvhPo4cOVIGf5y1WRhEmTQiuODIG6iPi+T67eAbrI3ZYvbhDNS2HQY6n3Wmzm6yxez8NoQ8uz3S3xbJ97322mvmm2++ybLvoEGDfBF6CEkENSA0DR48WAZwJiLXXXedbMfpnhxLOJfjwB1KuMpuW80Oth2TcyoUtGOCboLBveKe+dOtWzdZ3P0JTvuB2LXrSH7EQM84HAr9G5DDM2GS0adPHxHI7WQH6OPJW7h161bJh0WGAbfQT1ACghe5Cy+++GJfYFHKCFc0YiJVbOSDktuSh7rYvDW8k2zYYBIF2hiiqZj9UyeQ6Bm0Pu+++65ok9BG2OiTQJBk1A4C2U3eF0r7FSmEFkez3T8Sjc6SpH0ICwwkzNTpDAmxJmKLji3WvyG7RPLb3PhHglpsJCRCUfny5YOewx0R1bNnTxlUJ0yYIIkNmTUTPcWC9u+rr76SzjxW158biPdvi+T7EBZswlo3aGetcEU0IO2eQZtoXCs8kYYFeN4IVzzb8847TzQkaJC9nnOk1xctth2joQ1V/9RLa+nPb7/95nm/6AOtcMXf9KOBJmVMyOykLFaJT3v27ClCHZkEkCWIhraaO4RGBHK3YGVBs816tKA815QTrpA4aZg0dGb04TxkJXFkOMbsPXjErFekQD6T163xLxdmOKuHWjynQRBgxkSmXkCAIlSbzg5TAjms6DwJzedlDXYeOtNgJo9gJiEbjl+lShWTrGB6QrAihJ1ZnT+5xYSQXeicMTlgLghkOgwEJjS3xovOnjQMtCvyo5FuIxow5bi1El7YbXbfcM4XLE1EvCa+9loYBxiAvTQbkfy2UJDSgCUY9BNUTsCMZAdhJhh2IHabDZmo0T+gzUqGsky0Y97VO++8U8yR0YLQGap8D33GuHHjRNDxwq5H2AulKQsX+nAmSvTtWBWscGUFvGAaMmvyxlSYbEQthvft21fUc6hDb7jhhthclRIXrZXP3woNxtZfjWnWyJiK5QLnuGI9DT8MNXWszYB02FawohO09amAmQ1CPpA/DXVyIF566SVJTEeny75ekMzObTq04I/DdTDLQltmsTUKY51zJrvYjiaQCQMtXyrTqVMn+Rw9enTU56Kjf+ihh+RvSm5EC7XUGEw4l5epbsOGDeaLL76Qv8OZiSM4AMd4DTBo4YK9D7GECYc1+3kJPfQ/dn08tQxWgKJ0C8Ixggp5zACfK/yl8MNCSeDeP6cJ1W/Esh2Hi9VgobX10l7h9wRMaN1JPaNh8eLF0t8i9Fo/S7cAzkSJibM/+FxZ39dgZvZcK1zhZEtSUDqhMWPGiJNgoERxSpJqrZwMYw7tNSZfPmP+d8+Rdf4Clv3/c88d2S9e15yRITZ3TIAIgnSKLP7qeYp/oqZG60RSyV9++SXTdjowkgkOHDhQ/k+CTZI2ekHiRUxp7gSM+GmgHQOcw93O5VaLxSwzVon1osE61zJg+DuJkiSTwtapzNVXXy3mPvojZv1WKHeDYywF5C0//fST3BevpJtoPcArqWKkIPBSBw1Bg4SwCOsW/Fy4diaqZ5xxhiyhwB8HbQNaXSa37sSeaN2oRBBP7PfhS+MWHvm9JG9FqOT9veqqq+J2TVZYIhEpGjVrEnRvp4+xiYjjJVzZfsO/r7Iw+eNe0W+RiZw+0B/6u1hOlugTCYJgQovm1/0+IJwiHNP3kkTVH5IuY44luakbrFq8Q15CJMLRhRdeKH/zXmCNcAuXaMi4BtqL9fUC7sUtt9wiAiBCXqQa6qQyC5K11tqw8WXwX4+9Gq//yZMnS+eOkxqzexyGA/lG+BMoI66Sw1GCbvrdYMzRVYxBCHE7bdMRIFj16BHX6+RF5gXDj4gXL9BsiUzQvMTMvFBd4zPBDJWZtC3cjP2e2SIdlRWyvKCTmDhxosyiGLwY7KgGz+B3+umn+zQZ7gGT73J/L8IX2jWycMcbItHoIDFl8TdZ5Lk/DGxECFLtnoi4VIX2gr8GZl+y8CNQ0h8xmNEWmPxRLgPfGjvIYzqjeLzNCM5kkcFg0aJFcs9oN/4Z/bMLEwFm4xSlpX2ixUGTilaFNsosfNSoUWGfDzM3zxjhAJMwme75nbRZfjftkPYfDxAYZ8+eLdfEe4BmjfvMIMp95P6i/fAKJMkpsKygobIRtV7CFZUOeM+JvotX5RDcFzBV4oxtM9JboQqfSNqrdXNAaKX9NWjQQAIt0OTQhonOxO+Ic8QK3hcmZZhKaZ/0gWiWaJ8IyRRu9op0RdDhGSOo+vt64fuJoEh/xPUjKCEY8n7ZjPAvv/xypuNoI8gUHMtEichYMtMzBtDXEhTB+DB06NBMGq+kIdJ8VgMGDPBc71681oWzpAuJynOVJSs7kB/l0IHM2dll58RlaCdhoTuBHzlcws3jQqK9999/X3JekY+FRHPkpSIfFBnTgxVJdeeiIrkoySbJ6M05atWqJZnE/ZN1uvMXXXTRRZIhm/xJ/rltQuW5ClQQNtBx/vmIOI8b7t9TTz0lv5us2KVKlZJcMV9++WXQ3DuJyHMVacHhcAve/vPPP86TTz4pGcpJXElOIJ4PSTfvuOOOTAkwyWtGpnsym5Ozj3tGuyGXDsXlyY3mT6jrCPRsgHZERmqST/Jd5LYiQ//dd9/ty70Vyf2i/V122WW+9kriRfIk8T3ZKdwc7NrDabfkQGrdurXvvpMtn+vzuo/R3stwsLmt/JODAv2wfWevu+66bP3eQO9UsHeNvoo2cMIJJ/hym3k9J/I8kbmeBJ9HHXWUPF+S3ZJoln5h4cKFTqzhnpAsmbxXJPqk/6DKwZQpUwIeY9uZf1+1atUquX6qStAO+K32N5A4mcSiwZI+L1iwQNoObZpr4VjuJ4lI3XkKky3PVR7+CUcIQ0JE04HqGUnRvT4WcG5UkekAqmkc8Zh9hApnZTaFhM9s1ivPUSQcznDML+uP2K5PqHS0yYfiasvyIyZBS4UTjckbP7Of1+/FR4T2wMwlntE51P1DK0Xotn8NQEVRFCV3sy8G42m443fU0YIMREpuxDFmy4rMglWBYkeKNifiahxHfGOsXR3VL/5WqRzmriiKoqQmKlylK9aJHfIVMqZsnSOCVQJCkPFtIXeVdQbHZ4YZQTKEQyuKoihK3IUrJQVAsEqQKRA1LYIVmisbDRhuAISiKIqiJCMqXCkJA4GKCDw+MQMSLRMqu3pOgp+V+lopiqIo0aLClZIwrKYKAYvEnGoGVBRFUVIB9RZOE4LWFIwjJIRzZ9slK6/6VymKoihprbmiiCnp6mMNgysZpZWcz85etEBek1dSqsRXuCOE1VZbpyp6tKklFEVRFCUlhCuy3NpMt7HCOjMrOU/NPOtNscP7jdmUuGjA4sWLi3ClKIqiKKlIxMJVmDlHlaTDMfnNYVMsz3+1x+KR2wozIElBaTfkrMLHSjVWiqIoSioTsXBFbUFbrVvJJSDYbPvN1M97xCQnlG/wb16rnMtthRnQJgWlNhvRgPhYKYqiKEoqky3hShOH5jKcDJPn4H+ClVOgmMmTN3+OJwxFoLJmQI0GVBRFUdIFTcWQBmDItWLNkoyqpk7pY0y+HBJ0qA9ptVOY/8qVK5fQ3FWKoiiKEm80FUMakOHykytYoIDJmwOCFXUA8a3avHmzOLBbVLBSFEVR0g0d+dKM48oUjbl5jihAogGtUHXgwAEVqhRFUZS0RTVXSrYhAnDPnj1m69atIlgRDVi6dGlTtGjRuF9L9erVRWh0L6R7qFKliunatauZOHGiyQ1Mnz5drr1169YmFfj+++/NddddZ0444QSJFMUPD1Nxq1atzCOPPGL+/PPPXPv7//jjD7lW2p4Xn376qTnzzDN9SXJZ+H1g/68oSmqi6gUl22ZAMq2TagEQZBg8Ex0N2Lx5c1OrVi35m+v76aefzIQJE2S55ZZbzDPPPJPQ60sXELqvvPJK8/7778v/K1SoYFq0aGGOPvpoEcbnzp1rZs6caQYPHmw+/PBD061bN5NKLFiwwPTs2VPek7Zt25qKFSuKMMV9UBQl9VHhKk3SMMQaMq1bwYpIQCICk2EmzoB+2WWX+f6PRg2h6oUXXjDPPvusufDCC82pp56a0GtMdTATd+jQwXzzzTciVAwfPtycd955mfbhuVDt4e677xYNUG6kcuXKZunSpVJ03J+PP/5Y7gO/73//+1+W7RynKErqEpFZUBOI5tI0DIeOCEF7nYIxSxhqs6xjBkzmNAv4fj311FNimrGmGiVnQRuFYIUm89tvv80iWNnn0rt3b9EsYiLMjSBU1a1b19SsWTPLNmvurF27tuexHMeiKEpqEvZIu2rVKlkeeuihnL0iJcf43ankSsoQGZg3du7c6ROwEaYQrHJDGRtSQthBbtOmrHV/pkyZYgYMGGBOPvlkU6ZMGZ+v1vnnn29++OEHz3M++OCDcg/43LJli7nhhhvMscceKz5FfHI+oicD8fbbb4sGDf+0UqVKmY4dO5pZs2aF/C2Y0/r06WMqVark818699xzzVdffeW5P1o8rvPNN980y5cvl9/EMcWKFZPv/+STTzL5RyEIlS1b1hQpUsScfvrpEdf7pI08//zz8vf9999vjjvuuJBCeqNGjcI6d3aeE+32lVdeEXMxwh4CEb//pJNOknP5a802bNhgBg4caI4//nhpNzwfnme7du3MkCFDQvpc2XYxcuRI+X///v19/lVuP7JgPldo9V577TXZn7bB7+Q+4ru2Zs2aLPu7/dQwx3Lf69WrJ9ceyB9MUZQkMQtWq1YtZ69EiS0IQU7GkSVKiP4jGpAcVoCmKrdBtngoX758lm3XXnutDFo4XTMIo1VZtmyZGT16tBk3bpz54IMPxH/GC45r3LixmIA4dt++faKtwQyJsMLf/mYjBu+hQ4dKAAB+SAhKCxculMGRAT8Qr776qlwrAgMCCfuvXr1anPVZGNgDJfj98ccfzY033ijCCIICx82ZM8d0795dfie/GaGtQYMGsp3f/91334nQN23aNLnOcGBf7jWD/aWXXmpiSXaeE2ZiBB0EJX4DguP27dvNypUr5RnxW60AsnHjRtOkSROpnVq1alX57RzH//Ghmj9/vrn99tuDXiOCX79+/URz9/vvv2fyAQxHU4VwioCLwITgecopp8g1L1q0SMyrY8aMEUHaSyCl7dEmlixZYlq2bCkC5LZt2yK8y4qixARHiTt///036h/5DMXevXudJUuWyGcw9u/f/9+yb5+zf90vzv4/5spycPUPjrPuR2fRmu3OocMZmff1Ww4cOOA7Z0ZGhrN9+3bnjz/+kGXNmjXOzp07PfcF/h/OeXOCatWqyT0dOXJklm3cv3z58sn2H374Icv28ePHy+/0Wp8/f36ndOnSzp49ezJte+CBB+R8LJdddpmzb98+37Y///zTqVy5smx77733Mh03ceJEWV+sWDFn5syZmbY9+uijvnO2atUq07aFCxfKteTJk8d5++23M2377LPPnIIFC8pxX375ZaZt/fr1853zkUcekWdqGTp0qKyvUqWKc8wxx2Q578033yzb27dv74TLfffdJ8fUqFHDyQ7Tpk3z/P3ZeU6rV6/2/b4NGzZ4tgv2sTz00EOy/9VXX53pPgHtd8qUKZnWrVq1Svan7flj77tXewT7TPy56KKLZH2XLl2cTZs2Zdr27LPPyrbatWs7hw4dynLPWE488UTP36ooihP2eBqL8Vsd2lOExx57LOC22seWM107tDKFCuQ3efMY88SQIaJpCaShxJRkk4KiLWFG7AUal6uuusr3/xdffFEi9Lxg9n399debeMK1oD1CU4TW7d577xXNhD+BItVYj18QEW9oZDp37pxlHzRB/G63edSaBQcNGiSmLJzoLc8995x8okUiTN/NXXfdJVoYtCT+YGrDXNSjRw9zySWXZNpGrc+rr75aNDH4l5111lmeZatwrnabojAzoe1au3at/E7/83K/uF6i+mgvXo7b/mAiBUxvsSbS52RNwGgWvaL0MJ25sfujsfI32fHb0XLlJDi58xt4r957770sGuKbb75ZtFafffaZ+fzzz02XLl2ynIM2oBGJipJ4VLhKA3Y6RcXf6oSy4UX0+ZsBcxP4uLC4IT3Eu+++a/r27RvwOEw/kyZNEjMTQplNiPrLL7/IJ/5KXsIVA65XXi87cK9bt863jnNiLoKLL77Y8zowpXkJVzY/kjsS0s0VV1whAyt+W+4SRG4BzP/ZY1bDlwczmddvw6cOnx+2Y15KhkE7kueEGQ4BBWGEiL2LLrooqA8YAuhLL70kQjHKpbPPPltMc/GC6+R7eVaBTO+Y/dhv9uzZWYQrBFp/gV1RlMSgwlWKgNbDR8ZhYzYtlj9X5qth9h7KHOUZzG/EDsBorhigcdS2BZgD7Wth30ARpfGKJnT7uKBFQdjAjwUtDU7tDKD+EKTB4BtIm+f22fIH3xwvbHSiW+uHgGL/H2iQD7TeCmmBttuINc7P9/hrjgJdpxUeAm1nkEe4CqS99NJQAmWQYk2kz4lrx98KYRstHAupIU477TTRTiFsuYUnNHdohkaNGiW+W7T/+vXri69Wr169JF9VToIfGLz++uuyhKMhdKPO64qSPKhwlSJkEoAQrgocebSHMvKafPnzmCIF8olJMMu+/4JQ5BaAjjnmGNkPp+twCcdsFO88V2g3cNrGXITDNs6+bk0TjtCYxhhk0fwwgGKWIVqO+4EpDZNrIKExkvuTSEJdZ6x+Bw7YQGQxQh7ar1iQ3eeEkNS+fXtJIougTYAB+bVYiKpDmGrYsKHvHqDh5Fxox9iX5eWXX5aFqEyOy6lEuUxorFM8zujBaNasWZZ13AtFUZIDFa7ShBpBTILWDGgFKiBKKhUgIzgZwDERESFHhnY0GBZ8nACNCH5L/vz6668xuxabumL//v0Sxk/Umz+BEmqSsJLoM7QbRPQF0nrw3DDlJYo2bdqIxghtIekmSOAaC6J5TrQBtFLWp4yIQ3ziSEOB79uMGTMy7Y+2iuWOO+4QYe3rr78WLRc50vhN/mbnWIGvntW+IkAqipJ7yR3TbiVHYODYtWuXlCPBTyeQ6Su3g6nKClTkKnLnn8LkFSjVCKatQPmjsgM+TgycgOnJi3feecdzvc2RRL4qL9544w35xOcmkUWzMYfedNNN8vfDDz8sGqxg0P5IJBqKWD4nhBibr8/Lv80NExL86hCuwtk/GvC1ArRs4ZphFUVJTlS4SlMQphiwrECVaI1HTkOkIn5FmAmffvrpLI7nJJpEg2dhP/IVBYp+zC5EfMGwYcPEKdnNk08+KfmovCDiEaGJsiqYrtx8+eWXZsSIEfJ3qDxM8QBz2xlnnCFCLP5KXlnxaX+Y2DAj+muOvMjOc0JoQ2tpyzS5sdfkFtbQSpHLyh+0cDagICfz/ZG7CjMmmjWiQr20mJSdQjD3SoarKEryoGbBNMDtbwWYpTADWh8PzCb4ISVrCZtYgDkOn53LL79c0hpgrkKYRNhhUCUCq0aNGuLsjMM0Az73hP2tVigW4LeD4z/pG9AykewRJ2uSiBKKjxBlM5y7wS+IY3DMx7xFnURr6kRIQwvJ7yPCLdFgWp48ebJEMGLOIykmvxFBCs0WvlhkVEe4t9nHQ5Gd58S9ueCCC8QXiXQMaKyILiQhJ1GFXCcCrduvC0ENXy78njCT857gd4XwhjnWnXokJ8ABH6GUVAt16tQR3yvuD88XYevnn38W4ZK24pUQV1GU5CAlNVdkMcaMQudImQ86KDrRYFFGwWA2Sx4dOjM0PHR2+GzkRERUTvtb0TEzuCFYoQnBZMY9SmXByp3mAF8aNBHkgwKeJRoO0jTgqEymcwYwclOx3vrBxBL8aRAE0FSQBR2BAeGDUjOBcjkBvkYIUkSukZIAwYWUBKQeQHsVKDt7IsDxHK0RWeC5bkrPkC+La+Z9QlDBfwo/sq5du4Y8X3aeEwLY448/Ln5g3C/MbdwnGwWLQEvUoOW2224TIY7cZWgQ6Uf4pM2gaeRZ5XR1As7PNZLnCkd8ahSi4cPvCw0cv5//e9UzVBQlechDJlGTQtA5MvNHcCCiiE6ejsmaKOi4IomqGTt2rHTgzHipxUYnP2/ePHEgRtgib5EN/Q8XTHFoi5gN25D9QOB7gd8K3xu2kznRghsXyp+LM6qbepVKmnz/qq543MzGEaa4htwS7aYoiqIo0ZCt8TSb43dKjaz4oyBYIVCRmRvTxEcffSSRRJhVEITuu+++sM/HbBczAYIVPi0UzWU2vmLFCkkCid8Djq5JJZ86jnG2LM+06uCBAz4TIEIVGj00CSpYKYqiKErsSanR9dFHH5VPMizjY2EpU6aMZF62JplwnZQp/UGVedTz7vBvzArkvUF6xXcEbVgyCVZ5Du+X/+51CprCeQ6Z7du3yW+2QiACVjqYARVFURQlEaSMcEUGawQdsGHTbjAJ4peBMzc+LuGAb0Og86Edw1HXOsImA46TYfIc2usTrDab0qZoniN+ZipMKYqiKEp8SBnhyubKIQIsUPSRLdobTl4dnJ5/++23TMdFc76cBq3U/o1HzIH7TEGzPU8pUyBPhghVmABZVMBSFEVRlJwnZVIx2GSFgWqkgY0oCpXYENw5ZgKdM5Lz5TQZGYdNIbPf/GOKmV2muMljHHHqx78qGcrSKIqiKEq6kDLCFZomIK1AIGyR1nAykdvzBTtnuOfDFMliyalM6Bkmr9ljjtTNI/cPkQzqtK4oiqIo8UVH3jhAQVmc3+2SE7mTIJ/JMMeYv+U7NBpQURRFURJDyoy+Nrkf5SGC1TGDULml3OcLds5wz3fXXXdJtJ5dKG8RKaHSPeTNm88cLt/Q5C9fR7RWiqIoiqL8RzzTJqWMWbB69eryGUxwsdvsvsFw1xAjSzJ5srJ7Pkp8sGQHq32iFlswcFbPly9lHqeiKIqixBQ7jsbDqpMymitKiQClXQI5mJNZHdw5sAKBNspmXrfHRXO+7IIzOnm1vIrPKoqiKIoSHoyjjKfxCPJKGeGKemCUpwHqcvlDdnY0TWiQqMUWDt27dw94PkyCn376qfxNBfucAo0UZj7MiaG0V4qiKIqiZIXxk3GU8TQeaYlSqrYg5W8QiIjimzFjhk+jhDaL4q2LFi2S4qxDhgzJlCgUn6jKlStL4Vz/8je1a9eWLO2vvPKKueqqq3wPqX///uadd94RgY5SO5E8rEhqC9piy6SGILUCebwQEDVnlaIoiqKEkQNy/36zfft2KWWHG0/BggVNdgl3/E4p4QoGDhxohg4dKmq/du3aSRoFhCYKNzdv3tx89dVXmQo3v/nmmyIo4WPlzm1lGTNmjBRuRqBq1qyZPBgywcercLMFAW/r1q1BHfYVRVEURckKsgCl8KIN+Ap3/E45D2gKNyNEvfjii2b27Nnm4MGDpmbNmlJv8JZbbolYYu3du7epUaOG1C2cNWuWZGOvWLGiueGGG6QINAJWPKBBkMwUyZtFURRFUZTQYPVhiScpp7nKDWRHc6UoiqIoSu4Yv1PGoV1RFEVRFCUZUOFKURRFURQlhqhwpSiKoiiKEkNUuFIURVEURYkhKlwpiqIoiqLEEBWuFEVRFEVRYogKV4qiKIqiKDEk5ZKI5gZsajHyZSiKoiiKkjuw43aoFKEqXCWAnTt3yuexxx6b6EtRFEVRFCUb4zjJRAOhGdoTQEZGhhSFPuqoo2JagBmJGoFtzZo1mvk9h9F7HR/0PscHvc/xQe9z7r/PiEwIVpUqVTJ58wb2rFLNVQLggVSpUiXHzk9j0hc3Pui9jg96n+OD3uf4oPc5d9/nYBorizq0K4qiKIqixBAVrhRFURRFUWKIClcpRKFChcwDDzwgn0rOovc6Puh9jg96n+OD3uf0uc/q0K4oiqIoihJDVHOlKIqiKIoSQ1S4UhRFURRFiSEqXCmKoiiKosQQFa6SmDFjxpjWrVubY445xhQrVsycdNJJ5sknnzQHDx7M1vnmz59vevfubcqXL28KFy5sjjvuODNgwACzefNmk87E6j7/9NNP5rHHHjPt2rWTe1ygQAE555lnnmlefPHFbD+3VCHW7dnNZ599Jgl5Wdq3b2/SnZy415988ok577zzTIUKFUzBggVNuXLlzBlnnGEefvhhk67E8j7v3r1b+o8mTZpIbib6D+51ly5dzIQJE0w6snz5cjNs2DBz2WWXmYYNG5r8+fPLO/7II49Edd4pU6aYzp07mzJlypgiRYqYunXrmnvuucfs2rUrptlGlSRk4MCBBBo4+fPnd84++2ynR48eTsmSJWVdixYtnD179kR0vjFjxsi5OP7UU091+vTp49SoUUP+X758eefXX3910pFY3eeDBw/KMSzFixd32rRp41xwwQVyjnz58sn6pk2bOn/99ZeTjsS6PbvZvn27U6lSJSdPnjxyvnbt2jnpTKzv9f79+53evXvL8UWKFHHatm3rXHjhhdLGy5Ur55QuXdpJR2J5n7du3erUr1/f139wPvroxo0b+/qVm266yUnXe2z8lsGDB2f7nM8884ycg/6iZcuW0rYrVKgg6+rUqeNs2bIlJteuwlUSMn78eN9LNn/+fN96HnrDhg1l22233Rb2+datW+cULVpUjhsxYoRv/aFDh5yLL77YJ3BlZGQ46UQs7zPC1SmnnOKMHj3a2bdvX6ZtCxcudCpWrCjn69+/v5NuxLo9+9O3b18RYK+77rq0F65y4l5feumlcly3bt2yDDyHDx925syZ46Qbsb7PCE4cQx+ybdu2TNsmTZrkmxin271+9dVXndtvv90ZNWqUs3TpUueSSy6JSrj68ccfRaiiv/jss89863fv3i39Bufu2bNnTK5dhaskBEGHh/zII49k2TZr1izZVqhQIWfHjh1hne+OO+6QY9q3b59l286dO52jjz5atn/xxRdOOhHr+xyMd955xzfzP3DggJNO5OR9HjdunBxPGx85cmTaC1exvtdTpkyRYxo0aJB27Tae95n7yzFMzrw466yzZDtal3SmX79+UQlXVgN75ZVXZtn2xx9/OHnz5pXtCHLRoj5XSca6devMDz/8IH9fdNFFWba3aNFCClLu379f/EzCYfz48QHPV7x4cfGjgHHjxpl0ISfuczAaNWokn3v37jVbt2416UJO3mfu47XXXmvq1KmT1n4/OXmv8XeBm2++WXyAlJy5z/jAhgM+Qkr2OHDggJk0aVLA51atWjXTvHnzTGNmNKhwlWTgFA2lSpUSh3MvcHh07xsMqnf/9ttvmY6L5nypQqzvcyh+/fVX+cQRmO9MF3LyPl933XUiYL3++uthD06pTKzv9eHDh83UqVPl75YtW5qNGzea5557Tu47wtZbb70VWwfgNG7TnTp1ks8nnnjCbN++PdM2BLRp06aJc7udCCuRs2LFCrNnz564jYX5oz6DElNWrVoln1WrVg24D7Mi977B+OOPP3x/BzpnJOdLFWJ9n4OB+Z0IIiDyJ51KX+TUff7ggw/M2LFjzcCBA32zzXQn1vd65cqVPuHpu+++M9dff30WYeqOO+6QZ9G2bVuTLuREm77zzjvN3LlzzeTJk30alJIlS8rEmChv/s8k4uijj47Rr0g/Vv37LLivRx11VI6Phaq5SjLQNAFhvYHAlAf//PNP2OcLds5IzpcqxPo+B+Ohhx4yc+bMkfM9/vjjJp3IifuMBuWGG24wNWvWNI8++miMrjT3E+t7vW3bNt/fV1xxhTnllFPEHMb3LFiwQELZt2zZYrp27erTzKYDOdGmOdenn35qbr/9dknJgJD14YcfimBVunRpSS9SuXLlGP2C9GRnHPt8UOFKUXKQt99+W/yB8ubNa9544w1Tu3btRF9Srufqq682f/31l3nttddM0aJFE305KYu77CwDOwM+ZhMGIPI5kXupQYMGos1Kt0lDrNmwYYNop/BxI4eT1RqizUKoZYKGL5d7sqwkNypcJRlWXcnsJRBWNU+iuXDPF+yckZwvVYj1fQ6UYPDyyy+Xv1999VVJ4JpuxPo+4+fDDB9HdpI3KvHpO0ji6G/Ozpcvn7nmmmt8SRnThZzoO/r16ydawcGDB5u7775bfLnQsJx66qlm4sSJkkDz559/NkOGDInRr0g/jopDn+9Gfa6SjOrVq8vnmjVrAu5jt9l9g4H93vLnn3/KSxrN+VKFWN9nf4i8JCIlIyPDjBgxwidkpRuxvs82ioeByF+4wlwImFLsNvyBcAROB2J9r9mHbNhosGrUqOG5j12P5iVdiPV9Jvrwq6++kr8vvPDCLNuJ0uzVq5dZtGiRCLFosZTIsc9ix44dogH08ruK5Viomqskw4bs4+8QyKlu3rx58tm4ceOQ50MCr1WrVqbjojlfqhDr++zm448/NhdccIFEW7388svmqquuMulKTt1njpkxY0amhVIZtvO06/bt22fShVjfa8x/pLmAQOlD7Hrrq5IOxPo+M+m1BNKYWEd2/0hCJXxoy9aNIB5joQpXSUaVKlVEFQzvvfdelu3ffPONSNeo6HEoDYfu3bsHPB9qUMws0KNHD5Mu5MR9Bu5lnz59zKFDh0SwsmaTdCXW9xnB9d/kx1mWkSNHyj7UdrTr0kkbmxNt2pqyA5n9rMaladOmJl2I9X12O6p///33nvsQrQmBUj8ooSENzjnnnBPwua1evdrMnj0705gZFVGnIVXiVlqB+lOBSiuQqZq6SNT9Clb+5pVXXslU/saWE9DyN9HfZ8pUFCxYUMoruMsMpTuxvs+B0Aztsb/XlHM55phj5Ljhw4dn2vb+++/76jnS9tOJWN9nm/G9Xr16zqpVq7JUd7D3mb/TmX5hZGgfNmyY3GfGNn94Vrb8zeeff+5br+Vv0ghba6pAgQJOx44d5YHboqDNmzfPUhTUDizVqlXzPB9lFWwB4WbNmjnnn3++Fm6O4X3etGmTlLtgW5UqVaQTCLTEqjBoOrdnL1S4ypl7/eWXXzqFCxeWfU444QSnV69eTqNGjXxFdO+77z4nHYnlfV60aJFTpkwZ2c69bt26tdxn7re9z9SBTbcJ8Pz582W8sou9R/Sx7vXr16/3HfPAAw/IPq1atQpZuJn7TIFsW/tVCzenCR9++KFU7S5RooTUpKP+1OOPPy5V6v0JZzCaN2+eVG4vW7asaFjY94YbbnA2btzopDOxuM/MNr2qt3st/jPTdCHW7TnQMekuXOXEvV6+fLlMDCpXrizCROnSpZ3OnTs7kydPdtKZWN5n+uE777zTOfHEE51ixYpJsWb66g4dOsj3pCPTpk2LuE8NJVzBV199JQJxqVKlZFJcu3Zt56677nL++eefmF17Hv6J3rioKIqiKIqigDq0K4qiKIqixBAVrhRFURRFUWKICleKoiiKoigxRIUrRVEURVGUGKLClaIoiqIoSgxR4UpRFEVRFCWGqHClKIqiKIoSQ1S4UhRFURRFiSEqXClKEvDmm2+aPHnyyHLZZZcl+nKUKKBYtH2Wf/zxR8zOS7uw56W9KIqSvKhwpaQlrVu39g1UkSzTp09P9KXnah588MGg97dIkSKmUqVKpm3btub+++83q1atSvQlK0kw4fBaChUqZMqVK2dOPfVUc/3115uZM2cm+pIVxYcKV4qiJA379u0zGzZsMNOmTTODBw82tWrVMrfffrs5cOCASSVUCxU9tIktW7aYefPmmZdfftm0atXKtGnTxqxZsybu16LPU/Enf5Y1ipJmMPNt2rRpWPtWrlw5x68nXUBD1b1790zrdu/ebZYuXWrmzp1LUXmTkZFhnn76aRG43n33XRm8lPTjqKOOMpdeemkWQXz16tXm22+/NXv37pV1aJbRen733XemdOnSCbpaRVHhSlFM586dxVylxJfatWubF154wXPbokWLzIUXXmh++eUX+f97771nunXrZnr37m2SnVj6WblBI5KuWpFSpUoFbCvbtm0Ts+Do0aPl/7/99pu8z8OGDYvzVSrKf6hZUFGUpKNhw4Zm8uTJ5uijj/ate/bZZxN6TUpygoYK4RsNtGXkyJHm4MGDCb0uJb1R4UpRlKQEE6w7chJT4T///JPQa1KSk3z58pkbb7wxk3l5/vz5Cb0mJb1R4UpRssnmzZtlhtyvXz/TqFEjMV0UKFDAlCxZ0tStW9f0799ftC+x5ocffpCBpHHjxuaYY44x+fPnlyi7ihUrmtNOO81cd911YiJhgAkF++AMfO6555pq1aqZokWLin8LJrvLL7/cfP311yaRnHHGGb6/Dx8+bP7880/P/TAf3nHHHfIcypQpI5Fk+HQRFfrEE0+I6Shc+M1XXHGFaM94ltxf7kuVKlXMmWeeaW6++WYzceLEgE72wVIx2G1vvfWWbx3txCsazt9UHcxpety4cb5tderUCfu3rl27VgQTjuN3bty4MeC+aILeeecd06dPH1OjRg1pJ8WKFTPHHXecmHDHjx8vfnKJ4uSTT870//Xr1wfdH98+tKE9evSQe8bv4f0tW7asadKkibnlllvMkiVLgp4jmueZm+6tkg0cRUlDWrVqRU8lywMPPBDx8c8//7yTL18+3zmCLW3btnW2bt0a9HwjR4707d+vXz/PfQ4ePOhcffXVYX0nyz333BP0O0ePHu1UqFAh5Hm6dOni7Nixw4kF3Gt7Xp5BKL788stM1/Ltt99muScDBgwI+SxKlizpvPnmm0G/a9euXc55550X9v199dVXPc9TrVo13z6rVq0KuC3U4t8uaRd2G+3Fzb59++Q32u1z5851wuGJJ57wHXP22WcH3G/atGlOzZo1Q17zaaed5qxdu9aJBe53gvsWihUrVmS6llGjRgXct3fv3mE9gzx58jg333yzc+jQIc/zRPM8E3lvlZxHHdoVJRswK0aTAsw069WrJzPewoULmx07dohDtnXGRhPSvn17iWBCo5Jd0My88sormcxmRDnyvUTVoZ1hpr18+fKQ52LGftttt/lmwyVKlDCnn366aGf4XVw7Ie5sR0uDBoioLDQ48eSvv/7K9H+3Dxa/uWfPnmbChAm+dWgPuVY+CcknpQMaJp4Jmh8+Bw4c6PldF198caZzkQbCaiTRLBD2z3ONxmEdLSfPaerUqWbZsmWyrl27dqLp9CfcCFagXeHs/+qrr8r/R40alckHKRDsZ7nkkks89xkzZozp27evz4cJLSkaUrQ2efPmNStWrDBz5swxhw4dkjZOO0K7Wr58eRNP/DVVwb7fakDR1tWvX180tWgp0eKhkeb6161bJ+3/ueeeM/v37zcvvfRSzJ9nbrm3SjaIgwCnKCmnuXr99dedYcOGBZ1J/vzzz06TJk183zN48OBsa67QfOXPn1+2o6VBC5ORkeF5rvXr1ztDhw51XnvtNc/tU6ZMcfLmzSvnKliwoPP44487u3fvzrLfTz/95NSvX993Xdddd50Tb83VTTfd5Nuf3/333397al1YBg0a5Ozfvz/T8Rs2bBCNjN2He/jdd99l+Z4FCxb49ilevLjz2WefBbym33//3XnkkUecCRMmRKy5CkcLFYhQx8yYMcO3vXz58gG1LZZFixb59i9WrJho7vxZvHixU6RIEZ8W5/bbb3f++usvz3vSokUL3/k6derkxFtzddddd/n2L1CggLN9+/aA+9JW0Ny625Mb3i2eb9myZX3n/P/2zi3Epi+O40dqHkSSFxS5xMuIh0keRmpeSMSLW0N5MmF4QQ25Nch1TEpyCckLCo0mTMilkVIyQygJD/KgvIg8kPa/z+q/TuvsOft69jlzTr6fOjXGnn3OXnudvb7rd+3t7Q08X5r7OZhjK8qPxJXw/nVxNWvWLK+1tTXylcYkjzvNut7Gjh0buOBFiavu7u78/69atcpLy9+/f72pU6fmz3Xjxo3Q4xEnLNR2wfr8+bNXKXHFeI8cObLALWJhUUQE2f9jYQoClxn32B7b1NQ04BiEclx3ahSDJa4QBO579/T0hJ6vra0tf+zq1auLHoNL2x7T2dkZej7EmSvGi4nYcomrt2/feiNGjMgf39zc7GUB12DPuXz58sDj0tzPwRxbUX4U0C7+eTCznzx5MvKFWygpuLFsoUwKYUYFyAbhZsnhBkxLd3d37v379+Zn6kb5i3j6GTNmjAngBlwXtpZQuXn9+nVu/vz5ue/fv+d/R4CxhdT7nz9/mp9xkezduzfUZebWSMJV6HedZjW+gwlB07iYLBRdDYKNNWPoukT9vHz5Mp/QgHvUzoMgCMDetWtXUZdjOcBVh9vs6NGjJvHhx48f5ve45Do7OzN5j9mzZxuXP+D6y4pqH1tROoq5EqJEiNEgHoLsI2KEyMBzM3uIXbL09/ebLLSkjB8/viAzbPv27aavWlJu376d/7m5uTnW31Dx2vLkyZPc5s2bc1mAyHPT5+HXr19GgNoK7RayqNwCom4WI9lUxKqEQbwL407MlBVYbladO76XLl3KrV27tuLxZVmASDpw4ID5uaury4xnseugD59tE4OAJiYwbK4wxnGq4/vnSlZQiT3q/YlRYsPARihJTBICje/ohw8fjJhHtLlzzwp8YqsYM3eupKWaxlaUB4kr8c+zZ8+eVBXaEQFtbW25O3fu5IPbo/j27VuKT5gzQa481Hm4E4xbX19vUr4pocDuuq6uLtZ5CI61XL9+Pff48ePIv3GtR1n2bSMAmYUwDBYdAtAPHTpUsAD19fUVLdcQRmNjY15cvXjxYkCVfqwDCGP+D+sH5RgWLlxoLAsEOtcCWFko0cE1YNlDYBUT0a5Vi8W92PW5cwUxisCJwhUlle7xt3jx4tz58+dNYHocbt26ZaxB7lyK8/3NQlzV2tiK5EhcCZEC6lctWbLE7HKTYF0XSaH+DnVwFi1aZBZNHvK4Q3iRoUhdnrlz5xqRgNgI2gm7GVVXr14tOXsva7gWWydszpw5RkCSjenHddFSnysOZGAFiVyqfJ87d870r8P9yeKF4OY1fPhwI2BpDIyY9ddTqkbrlRWPuI/84oo5e+3atYLjo+YKG4jBnCv+3oJkz/H5EEbU6gKE5MePH437jlpnYXBf29vbE3+OtN/fah5bUR4UcyVEQljYV6xYkRdWLO4HDx40pnoemrhiKBPwf8KIsYxZ+H1aWNyJ1WCRcd1gNLDlvXEHIUgQJiw0UVaoNLCoZQXXY8fIvmjAS2wau/l9+/YVFVZg460Ai1Mc3OOKLZIrV6407kji0BCz7nuxYO/evdtYsRCyvb29uWrFtUTdvXt3QKwgFhtKUgBlCLB0lWOuxLXmJuktaF+nT582ZTM+ffpkrFWIcnj16tWABs9+7t27VyCsKG9AiROEGqKb75M7J5mnWXx/q3VsRXmQuBIiIdQSsg/HmTNnmgf6tm3bjNuJKukIH9dylNVuFxAbVINmwezp6cnt3Lkz19TUVCC2iCFBIBQL6nUFBtYNv7iJepWrKXFSsCZZ4lSi9x+HJaQYWKWIaSOO7ubNm6a2GIuvK7Zoq8KYU6OoGnFjqBDDfgulGwwdZLXyzxXGJOlcqURFcepU0UkAq6NrCXIrpvvB2mvhb6nfRowd9x4Lpr8WXZbf31oaW1EaEldCJMTNGkLcUIAzjDjxFGkezmTTYd0huJtgWxZ7N1ieoHcKIbq4gb5hrU6qHTejL6gljh9XGEa5jXBNEsNz5MiR3NOnT41Fg1ZHEyZMyFsONmzYYCxt1Ygrmtz4KixWWK6KZRf6qaW5wnVwvyzEUmGB8sN9s3GGBMBjcY4KJo87v5JQS2Mr0iFxJUQJ8RJRmX88zNkZlxssV0uXLs09evQo/+CmMrm/tyGxQ5ZKfK5ygXvOgviJg3tckCssCAQ0Fd4RstaygeByA5OTECc7rBSwXFrryLNnz0wmHBBrZd3ZxOhZsViMWpsrCGHrDiVmDtehH+6Z7QlJtm1Uxi1JK3GSUJLez1obW5EciSshEsKO10J8VRjEPlVyZ0psCu5Jy9evXwv+n4B4y4ULF4ru7msBNy39ypUrkddBqj3uWwtuvTRMmTLFZGoGjW9cbIwQ2NYnWYKwoiyB33rlWrHCXIL+uYLrKu21VgpKaxA357r//Akn7nc3jtWRpubluJ+1NrYiORJXQiTEDbJ2e9H5IS7KLXxZCrj94uKmaft35vTio2ceEDiOaytu/AaB3XHjm8oNGXA27orrCMv8wlKxadOmAmHl1rhKUiIDSyTvZ0lTawyI7bH4XbdZ4fYKJM6KeUF9KysG3LphQbXB6NNohQjns1afKDhuMDLacNNbAYWF2Y3FsuNu+1MSNxlWigSLUlxxlfR+1uLYimRIXAmRENLxLcRsFKuETbA4WUYsaHGz2cI4ceKECbjlYR9kCUP87Nixw1ScB1wk8+bNKziG33EO6z4hjohaThRADYLCp9Tzor4P2VnVAG46t2I1dbD4t3+BwiJAyQyKvNoAaO6ZHwLXcZNRQNRm0hUTuAQ+W3HFZ4hbY8vP9OnT8z8TOB93YU0CQe0Et9uCrQh9K6SxnLhNsMPmnRWxZNkxRrgZgyCZgjhAyl4MhruLTFkKzloOHz5cMLYIL8qVWHD1kiHqh04EHIeYjvP9TXM/a21sRTJU50qIhKxZsyZ37Ngx87DD7cCukzIIZA5iEaB1i63Kzu8IPCcepFQow4ClqbW11bineKATmI0bggWfmCK3RAEZjMUKHrLoIrDWr19vFg+yq8g8JC1/xowZRjTg7uScvGeatj+VYOvWraYEBS19YP/+/ea6sEyNGjXKCFtKOriuIVxFbryLBdFBeQVeCE8WaQpych4sC1gjWNDcRbOjoyOyMnwQCxYsMH/LuRGvvBeWDALpbfwOwtgvjpPAdeAmO378eL5obDGrVhjMscuXL5vSI8wJFn8K2jL/iFvDDY1LluxK3K7lssIlAZGNOKJsAnPg4sWLuZaWlgLrFu56xp4kB66HjNBp06aZ+0scnd1EIKb5nkcV201zP2txbEUCKtC/UIiqbtxMM+GkvHv3zps8eXL+HMVejY2Npvmw26w46L2iGjd3dHSEvpf7qqur89rb2yOv4cGDBwVNnKNe9fX13pcvX7xKNW6Ow58/f7yNGzd6Q4cODf3sNIAOa6jLOeKOAw2Cz549W1LjZjh16pQ3ZMiQwPfxz5U0zYGfP38+4LyjR4/2fv/+7SWhv7/fa2hoiD1GEydO9Pr6+rxKNW72s2zZsvzfTpo0ycwTl66uLm/YsGGh19DS0mKafrvPiocPH2Z2PwdzbEX5keVKiBSwy6XoIO1bCEilETC7XtwwZBASE4R7Iqu2KVu2bDHxUrgPsFDRxoVdNw2HcXWwQ2a3TKA3RRTjVC3HwoM7kF086fm4znA5ck760ZF1iAUH1xc782qsTI6bD/fKunXrTIA+ZTKwVlCbiJ0/9wn3DhYINy7GD+fAKnj//n0zDm/evDEp+JyH9+BvCWTH8oDVJ22slQufmbly5swZY7XAMoEFI8saRg0NDWZeuG5f5qVbtysOWGCxxlKUlPmCFY+YJlyoZE9SGoM4NqyCWGqxBJU7IzLKekVmJGOJFYruBlT7t+AqxsJMLTiuiXvNfR43bpxJCMFdiJuuEvez1sZWxGMICivmsUIIIYQQIgIFtAshhBBCZIjElRBCCCFEhkhcCSGEEEJkiMSVEEIIIUSGSFwJIYQ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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "\n", - "\n", "# Function to generate predictions and plot ROC curve\n", "def plot_roc_curve_pr(ax, predictions, targets, sensitive_value):\n", " # Compute ROC curve and area under the curve\n", " fpr, tpr, thresholds = roc_curve(targets, predictions)\n", " roc_auc = auc(fpr, tpr)\n", " # Plot ROC curve\n", - " ax.plot(fpr, tpr, label=f\"Sensitive={sensitive_value}, AUC = {roc_auc:.2f}\")\n", + " ax.plot(fpr, tpr, label=f\"group={sensitive_value}, AUC = {roc_auc:.2f}\")\n", " tpr_minus_fpr = tpr - fpr\n", " # Find the threshold that maximizes TPR - FPR difference\n", " optimal_threshold_index = np.argmax(tpr_minus_fpr)\n", @@ -990,30 +551,28 @@ " ax.scatter(\n", " fpr[optimal_threshold_index],\n", " tpr[optimal_threshold_index],\n", - " c=\"blue\" if sensitive_value == sensitive_value_0 else \"red\",\n", + " # c=\"blue\" if sensitive_value == sensitive_value_0 else \"red\",\n", " label=f\"Optimal Threshold {sensitive_value} {optimal_threshold:.2f}\",\n", " )\n", "\n", "\n", "for alg, (model_name, model) in best_models.items():\n", " f = plt.figure()\n", + " f.set_figwidth(10)\n", + " f.set_figheight(10)\n", " ax = f.subplots()\n", " ax.set_title(alg)\n", " with torch.inference_mode():\n", - " predictions_0 = model(X_test_w)\n", - " predictions_1 = model(X_test_nw)\n", - " # Plot ROC for sensitive attribute A=0\n", - " plot_roc_curve_pr(\n", - " ax, predictions_0, y_test_w, sensitive_value=sensitive_value_0\n", - " )\n", - " # Plot ROC for sensitive attribute A=1\n", - " plot_roc_curve_pr(\n", - " ax, predictions_1, y_test_nw, sensitive_value=sensitive_value_1\n", - " )\n", - " ax.plot([0, 1], [0, 1], linestyle=\"--\", color=\"gray\", label=\"Random Classifier\")\n", - " ax.set_xlabel(\"False Positive Rate\", fontsize=24)\n", - " ax.set_ylabel(\"True Positive Rate\", fontsize=24)\n", - " ax.legend()" + " for i,group in enumerate(group_ind_test):\n", + " predictions = model(X_test_tensor[group])\n", + " # Plot ROC for sensitive attribute A=0\n", + " plot_roc_curve_pr(\n", + " ax, predictions, y_test[group], sensitive_value=i\n", + " )\n", + " ax.plot([0, 1], [0, 1], linestyle=\"--\", color=\"gray\", label=\"Random Classifier\")\n", + " ax.set_xlabel(\"False Positive Rate\", fontsize=24)\n", + " ax.set_ylabel(\"True Positive Rate\", fontsize=24)\n", + " ax.legend()" ] }, { @@ -1027,61 +586,8 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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", 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", 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0EvWKuIoAWKzMxSHTsiAIgiAI0c/Ro0e1ccS0494QcRUBjCsQYSXiShAEQRBiC18hPTJaUBAEQRAEwUFEXAmCIAiCIDiIiCtBEARBEAQHEXElCIIgCILgICKuBEEQBEEQHETElSAIgiAIgoPElbhav369evPNN9Utt9yiatWqpZKSkvRwyeeeey6k/c6ePVu1b99eFSxYUOXMmVNVrVpVDRkyRB0/ftyxYxcEQRAEIT6IqzxX77zzjho5cqSj+3z99dfVgw8+qEVas2bNVJEiRdSCBQvUCy+8oL755hu1cOFCLboizfnz5/UkCIIgCEL6ULoma9asYStBF1fiqmbNmurhhx9WderUUZdffrkWQJ9++mnQ+1uxYoV66KGHVJYsWdSUKVNUu3bt9PyTJ0+qTp06qTlz5qg777xTff311ypScCz79+9XJ06ciNgxCIIgCEKskTVrVp1pHQMJ7byTxJW4uu2221L9P72iiv4wfPhwXaSxX79+LmEFuXLlUh988IEqX768tl79+eef2lWY0Zw9e1aX0OEGKVasmMqePbsUghYEQRCEdKBdT05O1qE9hw8fVqdOndIlbZwUWHElrpwWLtOmTdN/9+7dO83yMmXKqCZNmmgX4aRJk9Tjjz+e4ce4d+9efTNwLE6rbkEQBEGIZ/LkyaMuvvhitW3bNu0BIuzHKeIqoN1J/vrrL+1yg3r16nlcx8zHfRgJ5c3xcWOIsBIEQRCEwGGQGjV+jx07pttVpxBx5YXNmzfrz3z58nmtfo0Z0b5uRnLu3Dlt1uTGEARBEARB/evyO68nf8USbTxtKpNTiFvQC6hYyJ07d7omRTh69Gi6+zpz5oyeDL7W94eUlBT9KVYrQRAEQbhASkqyyrJntf47uUgtlSWLb5lj2lHTrjqBWK4yAALjcd+ZyVi8nEAC2AVBEARBacvT5v0Xwnki3Y6KuPKCcQWml+LAJBHFX5seBLsfOXLENTHCTxAEQRCE0MHixKi/ffv2qeRzZ13zM0fQ+CBuQS+ULVtWf3LBcBF6irsyIsms6w1SJDAJgiAIguCsterQoUOuJNqFMx12LYukX0csV16oUqWKzmcFy5Yt87iOmU/CUiF62bBhgxo4cKCqXr26jqHLkSOHKlmypKpfv76eT66yWOKjjz7SZmzKPGXktvEM54PzwvlJlPM5aNAgfexMJEn25/z4+p3mfKTX4aQxHDt2rOrSpYsqXbq0HpTDu5a8gd27d1eff/65ToUTrThZDg3PyBdffKGTVV911VXaC8L5q1ixol/Xw9fUsmVLFc+c/DeJNsKKvJanM+dQ+TNdiJe2knIqlSlyEkcsV17Ili2buvbaa9WECRP0zd+iRYtUy7du3aoWLVqk/+7atWuEjlLwxcSJE3WeMgYUFChQQOcmK1SokO7prFy5Ur311lvqq6++Utddd52KdbZs2aLKlSun857xtxA5ov1a8DwgYgwffvih6tixY9i/97ffftMCihHWNP61a9dWDRo00A0j5+nbb7/VnR3Eytq1a10d3GjB6XJodPxuvPHGgI+jadOm6S6nzULEurdb8eQGPHr0qCtdEu31xfnyqf27j/1nMipYiWCqyB2kFcf07duXcZjWs88+63WdN99806pSpYp18803p1m2fPlyK1OmTFaWLFmsGTNmuOafOHHCatWqld73ddddF/BxHTlyRG/LZ7CcOnXKWrt2rf4UPLN7924rT548+lw/9NBDHs/VsmXLrMcee8yKJQ4fPmytW7fO2rlzZ6r5mzdv1r+1TJkyAW+b6Jh3xdixYzPsWkSSL7/8Uh9f8eLF9TsuKSlJPy++zg+f6cH58/a7eZ/mypVLL+/QoYO1adOmNOvs3bvXevzxx61s2bJZhw4dsqKJ3377zdUeTJ8+3ZH2YOPGjVa/fv10O7Rw4UJr6tSpej8VKlQI+jh/+eUXvY/MmTNb27Zts+KREydOWDt27NDT0aNHrZSUFOt8coq1evtBy9rx24Up+XxY2lN/2++4slzRK7r77rtd///777/155gxY9TUqVNd88moTrkYwKS4fv16VbRo0TT7w9336quv6p4KZuDmzZurwoUL657Krl27tOtw9OjRGfLbhMDhmmOqL168uHrllVc8rlO3bl09xRJm1GlGbyvEz/mkfBfcd999asaMGeqnn35Sn3zyiXrkkUfC8n1YUXr06KEtDbgDsfJ4Kk+GVRkrEN6AaItTDUc5tAoVKmiroYHr4NS1veaaaxwdmR5N5MyZU99ThHi47hMHE4A6QVzFXGEm/OWXX1wTwgn++eefVPPtOad88cADD6gffvhBtWnTRv3+++9q8uTJOr8VIwB//fXXgEzAQsayZ88e1ws7GPDjv//++zoW4pJLLtEPMa6eu+66y+OIT16MuAtYnwf/xRdfVDVq1NAvAlyS3bp1U+vWrfP4XcuXL1fXX3+9jgXDxE3sBS9r3JXcc77ifPibYzMua/fYi/S2pfPBvLZt23o9FwcOHNC/n2NjRI4dXKxDhw5Vl112mR74QWNTq1Yt9dxzz7nM9uGAzg/HTafKvSwUDTfL/u///i/NdsShsOzHH3/0uF9cVjfffLPucPGbaQCfeOIJj++NUK6F/drjGiL+iO/jXuN9M336dBUOcL9RdD4pKUn16dNH3XrrrXq+vZF3GtxUmzZt0vfPO++847PuK/GQ0ZQg2d9yaKbzHimokUeYA5jrGi9uwCNHjrjyUPEc0amJNgFuJ64sVzRqgaavf/rpp/WUHq1bt9aTEFvQWMEff/yhG5NWrVr5vS0jRDt16qQFE2Ia6xYibfXq1dpaSSweortOnTpptkVYYekkJu/KK69U1apVU0uXLtUv3blz5+pySfaAX46NnjDbEYPSuHFjnX1/x44d+oXO3507d/YZg4GVjp4zQfvEtfjLDTfc4OpE8J0lSpTw2DjSwCAQ7WKVuBhEGWITazDHQSFxfu+TTz6pj4dzGA7rDs8k55IAY/ugEv5v3gP87d74cF1ouE1jaIc4PKw5+fPn15bqgwcPqp9//lk9//zzas2aNX41nIFci5EjR2rLOI0G4rRhw4Zq9+7d+px9//33atiwYeqpp55SToKI4vxwjyIgEfAM7MDiwrm54oorlNOYDgKi0ZOXIF7KoeHViEQ5NMPXX3+tjQx0+nl/xdtowOTkZN35iAn8dkoKjhHumCv8zyfOnIvZieN3gmPHjlklSpTQ55pYiauuukrH302bNk3HdqRH7969XbEhe/bsSbXs9ddf18sqVapknT//n19/7ty5ej5TnTp1rF27dqW6Xm3atNHLBgwYkGp/LVq00PM/++wzjzE9ixcv9hjX4h7/4k+cj7dtb7zxRj1/+PDhHrfj97B8ypQprnknT57UsSHMf+KJJ6wzZ86kiono1auXXkZMiafjDHRq3rx5qv3MmjVLz7/66qtTzef7mH/ppZfq675v3z6f25iYIqYhQ4akuq6rV6+2cufOrZctWrTIsWsxc+ZMfXwFCxa05s2bl2rZ77//bpUsWVLv46effrKcIjk52SpVqpTe77fffuuaf8cdd+h5/fv3D0vMlfnOZ555xnIa+3MXyOTrt9j57rvv9Db58uXzus5rr72m16lXr17IvyXYmCvecWz/wAMPWLFOSkqKdfz4cVdsFTGBp0+f9rq+xFwJYefUuWRV/alZKlZZ+0wblStb6LcmFiesQn379tXuYKwB9pgGLAV33HGHuv3221OVEcJ19+WXX+pYLSw27jnO7r//fm3lwW1DvEqHDh1SLcdkzVBzew+d2ACsELNmzUpjTTHuSywJ7mDxadSokQo3/fv316PHcHM99thjqZatWrVK98b5PXbX4ccff6zjGvn9zz77bKptcA2+++67+vx/+umnOnYRa5C5LlyTQHGPY2G0Fm4BRmjhsjMuAr4TNw3X9p577tH/x+UK5tx7s0RjoeS32N13NWvW1G5CLJZsj2XRCXClYkFiv1g47eBWfe2111TPnj3Vm2++qa1oToA1DCsjo9wYDW3AhYR7ePz48dqaZkp7OYVxJROz6jTcl8HcT75G3IWrHFq4wO06b968uHAJpvybFPT06dP6/zzb1PmNpXJvYRNXuGJ4iI05D9++IGQ0DDpYsmSJdlPhYkNkEaPDyx4XEPFTuG9YRjwIIJpo9HDVeSvajQua9XCjuIsr3JG499zBPQi43uwwFB33GnE3gwcP1mKKeJiMhCHbuCoZ3LF48eJUAgKhCDzD9uMyMShGuHhqbHCVcJ6ITyTAFnBZBJpPyhO49nBh4WpFYOH2xX2zbds2ddttt7kEFILIX3HFtfQUF+Xt2gUL8aDck/wGbykQuMfApHxxAmIIPV1LYpwQkby3x40bF1ONM6Lbifsp1jHuXt4nxHrGshvw4MGD2gUIxJ8iamOt1Jujb3CCN1966SXd6yf4zI67uKK3ThI7bgZewJ4CT4XgyJk1i7b+xPLxOw0vHCbgnsMS8/LLL+vgTxpceutmpBQ9QDPqxoy88YZ7cLc91ssdUybJPTCaUUgMlsAKxkSDSwwRjSuCyzTs4cQEZRN/iJgy4ooXncmHxCgpO+Y8YdVhCvQ8OQEiCXHFNURcGfF09dVXq8qVK+vRUmYeQfkIagYXeIqV8+famZ50qBA0z31IDJivoFynzh37+e6771yWSneYR/wXjbS7uDINm6+YVrPcvSEkTo/ONoMNEr0cWrgsPViSIZaEsSeMdYpPrN2m0xtrOCauEFSY4bn53B9AT4oTszQPGmZMerakUHDaFJ2ocL6dcKvFK5wfxAv3LEGqNDgkLzTiyoxIwW3oyQJlhwBkd3yNhPLk1iDbP88CQoAAaixsfDIsHfH16KOPqnCDuMJ1aVxDiDwyd2NlwZrm7pYz5wlXIc9zeuCmM7C/hx9+OODj4/vdXZaIKxJO4qblPHH+OP9m8ALLEYsbN27UFkveTWa0oCcCvXbBYs4d77yMSmCLexaxjMUKy543cYClzD2dgHGHpScu7Ptwf5fjbkVcYcF0Go51xIgRQbkFPZ2HcJdDCwe4exkVjzueASqxRkpKims0Lc8gQeuIK3+fR57rTfuOqwqZdqpowZEWGLfKTTfd5PqR+Ebp+RKPgZneG9zYNCj03mbOnBnQCCdBcAJcVYgrk7YDTG4YRpP973//y5DjMCkcjCsICwmuDmKGcBXybJASIJwggBAexCiR2R6rmXG3eLJ0cJ5o2OgpB/Ls0gCbXnYgEHfkLq6wevO+wRKJZQYrFqIY65RdXCG6TMqGaBj5a+4xrjuWoowQdcYKS5gGwt3Xulh23S16iFRfGcft6xsY7UoHhphDvBa+xHggMLoymPsJ/BVXphwanTE6Qp4yn0eyHJpJo0EusUhYzkLh7NmzOnwIQW5EPCOOAyHFUurMufMqZ+azrtI3mSJY+gZC/naUPAHBiCpeFARpkmCTeAxM8+nBUFHj9+eFLghO4k9aDuJzgPxSBpMgENHllBsoUAiAv/POO9Wll16qe3W4DX1hzOemgGkwGBGFqKIRNG5KT3FV5jxh6QoEevZcm0AnTwkWESU0dJwjQhJ4H9nfO1iweC9h2fIVb+Ukvq4FgyW4tlhB6FiGG+LoiOvDBUlD5u0cm9xaWLnsx25q1HEfehNYWMWM29G9ph1CnetOQ0qco7HceYPcX3S6A0nBE+gUSJyWKYcGDHJxJ5Ll0HB3m1QXseQStCxLd7To2BJf5cnrFSyZIl36xglxxYggXmhGWDH5m9gL0yrxJJxQRiQJgpO8/fbbehSRp4Bg7jmsM8YyZTelE4+DqwYzP3mdPNWG40VALJIZ6RcKZI83Is8OViFjCbC71bxBXAuNAD15AkKDgd+LJYgEm+R2ooHlXHjqDQ8YMEAfFzm/cFuaEVV2OJb33ntPhRMjlsy1tIsrLCQEaiMaiHMiuSfJWcONP9eCJKsmls1T4WTuUdzDuHw8JasNJMDXWK2wIHF907Pk4qbmvrZXtcBCiFDlmPBS0IG2gxBCNCEy+O3ujTyWCEQ4nQZyhZGlnevhDueK/GhYjQNJ9pwRYDU1I4HtghhrFr8XgcCz4u4+Z+AC8/zN2h4on332mRatxBgygjYWSElJ0dfajKzkvmCgS6wFrYfVLWh6Opjhg4kLwdxKYkYTHCsITkFPmpIeTLzwEU08wHQG6MUb0URj4d4Y8AJlPSw33KPEXtEw07iwHZ0BXmikbQjVxUEjS7wXL186G1iKdu7cqUfAmZG2/rgaaMCwBpNIENcYMSWm8K0ZJeYLXnIITdIDkALAm0sQMOFjoWaEHVYjOlpYY7AC0uAQEsD5Yfg91u1wiyusjJw79yH2LOcdY1833PhzLRglSGzbQw89pNetWLGivtdIv4GLk3uMuFTeq2akJRirj78jSrEOMAIQfKUsIM6FDOSkgUCQIYLsjTjHgeBDoDJSk8SxDF7CMoYFhVgZwkQ8CThGJM6fP1+7rhCTiDeeSfaFBRJhhmsNkcK8aMu+HWw5NJ4FRuF6A0uXEatGbBA/ZU/BgvvSmwvTjOb19pxGqxsw+d/RgNzvPBvBCisTb1UpkzMjeR3DCpGiRYvqApHdunVLs2zgwIE6SR7LvUFCRdbJkSOHlShI4eaMgYKeJEq89957rQYNGuikjFmzZrVy5sypk/SR5NJekNtTwsUvvvjCat++vVWkSBG9bYECBayaNWvqRJWTJk2yzp49myYBoHuySzsmgaEdkoeyP/Z7ySWXWNmzZ9dJGNu1a6e/wz2pqrfElXDgwAGdELJ06dL6eN2/L71tDUuXLnVtV7ZsWZ9JXTnPL730ktW4cWOdZJHvLVasmFW/fn3rkUceSZN4MxyYJJXuyUGBpLHm94wbNy6ows3ezlso18KepJT3IElpeQ9S3Lh8+fI66eyoUaN0AkU7nGv2w7794YMPPtDr8662J0f1xsqVK/X6FCh2/24Sx1JkmGSVPAsUfM6bN69OMkvBZXviXG+QbPb999+3OnbsqJP8cr/zu8uVK2d1795dF5W2P1fRxg8//GC1bdvW9axy3fjtPAe+kpx6gmfdV8LToUOHetyWwvPmWsVCMfbz58+nSgrqxHU+n5xsnfznD1fy0JQ968hAGtA+wpFENBP/hCLO6F3Qu8ZFQM0oO/fee6966623tCI1KtUd1DjBePQ4fY1EiRfonaDW6fEFG3xIL924ObA2CIKQGOD2xNXNgKFYLCUjJDbHjh3TmoE20ImBHMnJ51WWPRcs01aW7CpT4WoBx1sF0p76236H/MtMzTAzBDdQTFI+M7pHEARB8AyxTbiLqQUpwkqIBc6cOZNqcASjAnEbh2OEbErByhEPZHcs5ooir0T7BxOQTkwMvnosWwTjCYIgCN7Bwu/vKDpBiIbRgMeOHdMxiCZgPZ6C1tMjZOlo8n1QMd6f4eLugXgmgM996K4gCIIgCLFHcnKyHg1oRhAz+MKpNAupsCyV+UD6uddiVlwxssRAXh5/h89Sw8qUvOHEmySkgiAIgiDEJmiAffv26U+sVLgAKWMTlkS5VorKdP6CJfeUlU2pCCcOtRPykZD/hNw4JicLuVAQTt7ApE0+GoYmY7Xi5BPU7q2mlyAIgiAI0Q0aAEsVKTlSUlK00QRXoElBEm7+toqTPlTFVfkb8raQN4ikh8RQkROoevXqqWIDyOVBQj0Kp5LnwpgIyXNCThVBEARBEGIXU9EiV65ceiRdRtXqjEYcEVeY/ajp1atXL1eJCsQWmOA1UxbB7nclzoqsvdGWLE4QBEEQBN+Y0ndMuP8wnuTKIGtVNOOYrCRLNfUBKaBJRmJv9ZyALNTUdaKsAxl9BUEQBEGIHWjPCe2xl73CFZhhwsqylNp/oTxY3FquDCjXm2++WU+4AHERUsaDZFuUykCANWzYUCfqEgRBEAQhNkcDUsIGK5VJEUK6hQzFSlHKFsyeEkXxVo6LKzskuMvo6uCCIAiCIIQ3roq6qwStm9GAGS6sPASz58yaRWXOlADiShAEQRCE+BoNaKqxIKiIsfK3gLjjLkEsVzbKF8oTVQlKQ465ono507Bhw4Lafvjw4Xr7ChUqhHoogiAIgiCEQViRFNQIK8J8SLMQMWG1f4NSe7ynfIoGQj4zW7Zs0WqR3BbBwAUz+xAEQRAEIbqgfSauihgr3ID8HTGsFKXOnXD994SVPerirUDcgoIgCIIgpLFWUXDZxFMxCpC0SVmyZFHRQnLhGurv3SdVNJI5GkYdQETMi0JCvSjGjRunqwmUKlVK5ciRQ8cLkDaEMkzbtm2LyHE9/fTTulfIZzQTSMHVq666yrV+IFMw3xWNlC1bVh8/FvmMINjzZa6TyU2YkZCKh+++5ZZbAtrOeDk4x7HC9OnT9fPdsWNHVbx4cdf1+ueff4J+lz377LN6wFiVKlV0OiMEUOHChdU111yjPvvss4Dq+PXs2dN1TGwLiKr9+/drj5RpoyGahJUmisrduBNxRWMatYsuuijShyLEKaQD4UW0dOlS/QKpW7euatKkiTp58qROF/Lyyy+rUaNGqVdffVXdc889jn0vjRaFzZs3bx6RBixStG3b1mPjRw48aNOmjR5NLAhOwj23detWtXnz5qgSX9TfJR2RUyB2nnrqKW1FqlWrlhZYuOn47bNnz1Y//PCDTs49adIkn2KIDueECRP0e9EIMiqrMBrQJAdFaEWdqIoBIiquli9frmbOnKkvYOXKlSN5KEKcQi6WZs2aqU2bNulSS59++qmqUaOGazkvjpEjR6pHH31UDRw4UL+4Bg0alGHHx3fecMMNOjg0Xnjsscc8zjfiiuVYTQQhUEqUKKHWrVsX8aH/gYC1vFKlSuryyy/XExamUEDoUBGlUaNG2gJvZ/Xq1ap169ZqypQpuizdHXfc4XU/e/bs0Z1J3ou4/H7++Wfd4eSdGfHRgHFAQGeNcjXeQCWnV7DZzrlz59SOHTu00jbqGHOmIIRDvCCsSFz7448/6mBMO7w4HnroIf2SYt2HH35YXX311bqKQEaAqIonYSUI4YQGv2rVqiqW+PDDDx3dH+2lt84JlizeY1i2qICSnrgaMGCAzrA+duxYV4fyzJkz+jNPnjzamxQ17nnLlnrBLQVD1GIFQKZMmazMmTOnmpjnab4/k9m2ePHi1r59+6xE4ciRI9hf9WewnDp1ylq7dq3+FDzz999/6/uMc/3NN9+ku25KSopVu3Ztve4tt9ySatnQoUP1fD63bNli3XzzzVbRokWt7NmzW5UqVdLzT548mWqb5s2b6208TWXKlPG4bztjx47V8/v27WsdPnzYeuCBB/R2fGfFihWtESNGWMnJyXrdf/75xxowYIBVsmRJK1u2bFblypWtUaNGefydHD/btmjRwipVqpRe/+KLL7aaNGlijR492rVPd8yxh4LZx9y5c/1aD77++mt9bBdddJGVK1cu64orrrCmTZvmcTvOD9tt3rzZ+vbbb/VvzJ8/f5rvPHjwoPXUU0/p650nTx4rZ86cVs2aNa1nn33WOnHiRJr9ck7GjBmjv5tzlZSUZBUqVMi69NJLrYEDB+rv83YcP/74o3X11Vdb+fLls3LkyGHVqVPH+vjjj73+dr5/+PDhej1zbNWrV7eGDBmij9vX+XJn27ZtVr9+/Vz3K/fO4MGD9f1q7lFf18PAPcj6r776appl1apV08vq16+fZtmwYcP0sieffNLj/X38+HHrsccesypUqKDvxyJFilh9+vTR97U7nFP3Z8jsy9vk/vt27Nihf0vVqlX1+eU816tXz3rzzTetc+fOWeHGHNf27dvDsv8XXnhB779Xr15e1+EeZB2eA+AZ4/+cg6hrU1JSLGvvesva8Vua6fz5c9aq7Yf0dD45JUPaU3/b74DFlZNT7ty5rRtvvNHaunWrlUjEsrg6f96yeFd98cWFT/4frbzxxhv6PNOw+fPSfOWVV/T6BQoU0GLLXQDxwmcZL/8ePXpYHTp00Pcwy3g52a8FDWSbNm30MtanETHTQw895Le46ty5s264ChcubF133XXWNddcoxsEltGwb9y4UTecCKWePXtqQZElSxa9HBHlDgKCZeXKlbNatWpl3XDDDbqRpVFjfrdu3VL99kiKK178vCc4t9dff71L/DJv4sSJabYzoobzwicNJg0Mv2/+/Pl6nTVr1uhzxfJixYpZbdu2tTp27KivEfMuu+wyLWbtIE5Yhjhq3bq13ifXFmHN/EmTJnk8DsQEx1q3bl19nhs1auT6ba+//nqa4z9w4ID+fpbnzZvX6tSpk77mBQsWdF0zdyFnP1/urFu3Tt835rdyz7Zv317fP40bN9ZTIOIKUcv67dq1SyNWzDHQmTl06FCq5c2aNdPL5s2bl+b+7tKlixapPKNcB+53c8ycR/dr4UlcLViwQD9X5lnknNmfN86DgWMwgrts2bL6HHMtzTyer7Nnz1qxKq54H9DJYv9ffvmlx3UQrZxvOhRnzpzR84zQTk/4R4zk8x6FVcre9dafu47Eh7j66aefUk08lMZqxUvZfbmniZv7l19+0TeBt15yvBOr4grjT8mS2j7rmvi/D6NQxMDCxHlGcPgD96Z58W3atCmNADJix26l4gWJpYhl9L7t8HwwnxeXN3yJKyYaHbtFZfny5dp6wnOHVePOO+9MJR6x2pgG2t0Ss3TpUmv16tVpjoMG0oiX8ePHR4W4ogFYsmSJx/PFOXfHiBrE5eTJk9Ms57phHWGdJ554wtWwAOcJ0cQyxJSBjh/zaLB27dqVZp88g+6dQ3McWbNmtaZMmeLxumIBc7d2IiBZ1rBhQ2v//v2u+ceOHdOChmVYz7ydL3ewIjEf0W1/T3C85jwEIq6wMPGbEDH2c2esIIgkdyuxfRu7aLHf34gb+7sQC50RmVhhfIkrTxZDT3D96BzRZr399tup2h/Od8uWLfX2WNpiRVyNHDlSC0ju3aZNm+p7n/eC+7vIDh0K1uO6m46UEVeffvqpFVWkpFjWnnX/iarzZ7XYSkk+b/21+6hLWPG3p05hzIgrTxhxde+994a6q4QhFsUV78tMmVILKybmMUWjwOIlwnnGauAPf/75p+vFRwfAvUGnx++pgaUBNWLGfj2cEFe4LPbs2ZNmO3rcLC9durTHe6BWrVpprAW+mDVrlt4GC0c0iCtPrs3Tp09rYcJyXF6eGtf+/ft73O8777yjl2Nx9AQiBqsJwtW44BCjbMP59hdzHA8++KDH5bijWG6saUbwmFCJVatWebQ2YDlju59//tnntVm4cKGeh6ixCzUD1rZAxZXdCkVH2b0TYyxbiH1f1i5zf3N8O3fuTPM9X331lV6O4HFKXD366KMuy6YnOMcIQVy+oTTUGSmu6OyZ/RlBjyB1F+6Gd99913UO6FAhfqNaXCXbrFaIrH+vC1YqI6z+3BWasAqXuAo5ScTQoUN18Fy7du2cCQITog7SnNx33wU55Y6Zd//9F9aLZXzlhmHQhacUAh06dFAFChTQwaG//fabo8dE2ghPo4sYfQSkenAfMWRfThoKdwhaZTQRz+2dd96p+vXrp/MNjRkzRi9fv369igbIC+QOw88plwUMivFE9+7dPc6fNm2a/rz++us9LieIt169enoE6a+//qrnETxNYC+5ip5//nk9zD+U4wczWMJ+/PPnz9eFcBm5demll3ocJUcKC2CkmC9M6g/SYnBvutO5c2d18cUXq0BhJBow5N8wZ84cVbFiRdW+fXudx8m+zPxttnOH812sWDG/zlGo+Lr+nGOem3379qkNGzaoWODbb7/V760TJ06o33//XQepP/HEE6px48Zpnn3uXQbv8BsffPBBlS1bNo/vjqilYCWi+dPMrlg4umoKGpKcEFdCfLNggVLp5btDk2zffmG9aBphb0bhMeTYH/bu3ev6u1ChQmmWM+LQG+TVIeFesIkBvVG6dGmvQiC95SZvHBXs7SxZskQ3LuklTUUkRgPeflvevHk9/jaDtxxHjBqFm2++WU/pQQNrziOjqRCgNFpMiAGGwSNcyGFkrkUox29ERHr3mKm/6o/gMPeht/2ZRJyrVq1SgYBI4p2PaCKR5dq1a3Ujftddd+nlrVq10ulOGAlepkwZn+Iq2GscDOb6k5rFF1x/X+mBFi5cqNMduNOlSxc9ZSSkUmCk4P/+9z993kmMzAjAr7/+Wi+nbE2fPn20CCOfH+9G7ttoFCXxgiSwEHyya5ez62UUWH3IOIw1CWuEr3wtJBkFevrBJiEMJDOyP2TOnDmk5XbIYcNLH7GJWKBBxOJAQ0bunL/++ksnJHT6NwRLIL/Njre6Z1iGAFFUpEiRdPdBA2W47rrrtDj47rvv1IIFC3Q+IFLPMGH9I2kjDZtTxx/NNGjQQN8vWPZIjGnEE+lLgPOEuOKcdOrUSafnwfLq6fxk9Dky1x/LJoWH08OTtc+djRs3unK32eHdkdHiyg7PNuIK6zR5+xBWiF3EIL+bpMkILDsrV67Un1hnEYxUrnjjjTci9AviAxFXgk88WO1DWi+jwC2DGZxGYPLkybqR9AaCgkbBuPk89ejScwmZUiclS5ZU0QquJ4QViQw95d6JFVdIsFD26M8//1S33nqrV9ehN3Ch2S1e27dvV/fee6++r8grNG/evJCODZeU3briCbPMrOvP/tIrwUODGyh0UKg4QMONexJxhTDHPe3uNsSawnOFNSsaLCRcf+5xEgbjjgwVXOmBlu/JCIxwRFSRaR3rq+kwYbmig+ANng+mqMCylNqf9p3Eb9m077hKOHFFQ4ZCRglTm+jYsWOuHkN68PB98MEHTh+O4ABY0dEMeCM8GTV4b7LcD2t7hoIbhbpZX331lXrkkUf0S949iajh7bff1jELNB6s6wmS8uE6dI+BIh4HlyAvMaxlBmIaAKtZNHDw4MF0XTGmrli8QlyoKQ0SqLjy1FAPGzZMiyvT6w+FK6+8Ultx2Beuutq1a6davmvXLl3NAoyQSQ8EELAN1536c3awwtHwBoPJAD5jxgwtKhEq5rki5op4KeKwjAXRm0vQaXw9b1x/xBXX3wlxFa1w7o31jetO28q7kHbYm8glKSnXkg7mTTfdpKICK0Wp86cu/J2U01VHMMVS6tS5CwG+ObNmUZkjr9s94phNlpT5BNPxcGEOxlxOvTbiFTCd+poo5ClEJ5SVGjnywt/uz6b5PxbkaCw/9dZbb2kzPVYnKgysWbMm1XJexK+99pq6j4h9pdSLL76YqjyOHWpu4Urj00C8CdYxIDjcHiBqrFi80KlKEGlMkDAvX2Jl7Lz77ru6zlg8w/sJdx+11LBe0PFzZ/fu3eq9995z/X/FihX6vNivuQGB4e5CDBYEb48ePXSvnKzaiHUD1gaOnfijK664Qk++IK4IC+Xx48d1iROTedtY3ahEECxGLH3yySc6Ps+4BO3L6VjTqbGvH27M8+b+jBvoNCECed5xi2HZcYf3RLR0MugMMqAC97OdqVOn6gELntz3PNu8h6B///4uMYXwjAbrodPB7OULRW/cmCOWK0zP9JQIovQnXsNeJNI+T4heunVTithINIg9Zpv3GcKK5dEIPTcsqcRALFu2TMd+0GulJ2cKNxO8ysuHF64RWZ4gIJQXG6PVaLxo7CipQ+PH6BwsGe4NJt9l/17EF8GkI0aMUBkNI9EYJYa1hb/prXJ+sJYwQnDw4ME65iJewV3CiDHcvi+99JIWlIzMo1HmXiDmjLp1WCZvv/12l+uM2o9YYRArWKwQ5NRw45xx37AvpzoCuGR++eUXfX9iocKSikWBe5Tg9M8//9zv/WGF4BojcnAJN23aVP9O7ll+N/ch93+gVK9eXXeizWg0T+LqzTff1M8HI9O8WUqdBrc/rkosL4zspS6eEVXEEnKdTXgA4pLrVrNmTT1AAY8L1/7vv/9WDRs2dNR6Q+C/GaloByOEsbZxb2E9t8OxcP+5F33mfcK7hkE3PMd8YoWkE8c9bKx0oQhoIQrEFSKpa9euujcEPLQ33nijdqGgohFNxHfQS+RG4SE3w5wZrcDIE6mtFhsgoDp3vjAqkOB1YqxwBUajxco9/oQGC3cADQ33H64XhA5WB0QTcTO+gthp3HixDRkyRDdQWGtpOBgxhiXEUyD1N998ox5//HH90scCQsPMd0ZCXAFWGwpVY3VAdHIOEH1YmWkI41lcAVZJ3L+jR4/WFgH+RmDwDqLxpUHifWZgVCDXivcWjS+WLAQP62IRIu6KhtsJcOMsWrRIXwvuFd6huHK47xB7HJsRDP6KIO5X3rG48Bi2z3FzzHgWSJ0QLGZUIIKVjoUdBB3niHs9o6xWgFWZdgbLE656M9IQoWSuEe5XLFuMqkPw8C7Aqoeg5llm3fRiM4MBkcT7xx3uJUMgKRE4PiypPL/8FqyEtLP8BuJMWc7kK2hfCC+ZSHYV6suaod1cXPKw4MvnweIBpifGfEYs2Fm+fLk2c3Nz8bDzEom1YpyhgCmdAFl6JGbIcaDw4sCEzYs3pnKVxCBPP/207inSSPG3IAhCNEDzjTXSWLcYXIAANxaxmCYlWandv1/4u+ilSmXOon/vxr3HXTFXNYpfrLI4EHQVSHvqb/sdcsyV8Qcjot555x2fw92BoF9UN7EDuBIJOnYyn4kgCIIgxDu0m0ZYIQpwEcaFsPJCrASzOyKuyA2EsMJnHEhgJy4UgthR2pg2v/jii1APRRAEQRASBgQVVQuwoGCxisfcat5SMERzMDuEfCVMJmMzEsm1Y9tF9maVIoEh1itOmhlZIgiCIAiCdzegieZBXDAoJe6yrVuUrk2JWauVI+LKCCf3EhD2/5v8Op4wNdCipZ6ZILhDnBUvM4m3EgQhUjC4gbaUkYH2ElVxJarsyUP3/KG8Ee1WK0fElQnoQk17Kx9AmQBvGH+xva6bIAiCIAgXICcXXiKTr8yf2OaYxUpR6tyJ//6fNbcrgWgsEfIRm2KiJN+zY0/EyLB1b0qcum9AqQRBEARBEC6AxZxEsKRbYNQ9McqkDUmYNAtFanpNIBr34ooCj9wA7hmfyQ9DoB2QU8aTZYrCkAx/xLxHMjdBEARBEJQWU7gBjQuQQWDxPhowDVisYlBYOSKuSBgHpFSwFx0lDwSJzBBemDNJVEjZAWp7kSWX4qlU7jaQBVkQBEEQhAtWK9yBGB9oTyndE8+jAV3xVvviI/465CtFll+jpL+mPooN6rSZjMI7duzQZQjatm2runXrptMwmBEPpHG47bbblFOQ2BTRx3djPqUIKqUOgqnvRmmT4cOHa3FIfFnWrFlV0aJFdQkNEqYKgiAIghPYc3oTV0UbZtyA0R7A7ZiwSj6TplhzLBJyVByC48svv9RuP8qM2OH/s2fP1hYs6g96gnIElCVBtDjB/fffr8t7cGNSqJdRi8R8UZ6EQqtkg/dUpsQTFE/l+HB5sh/SRtB7IECf0glMgwYN0t8nCIIgCKG4ARkJiJAyWcITpvqGZSmVcl6p8/8WSM+SXalCVWLWJQiODDmw1+Jyh8KSFCOlxhq1Bin2iWmT4rfUQXIv+hkK1M5C6CCEKHaKRQwIBkRokRX+ySefVK+88opf+3vmmWe0sCKjPKKMfCIGaldRBJc6YL169dIxZoIgCIIQKIwCpFYpg7yoyUi8ctxbqtxTL9hHCLoJK/cEorFAhoznxG2IAGEKJy+88IL+fOyxx1zCCjCrUnG8WbNmumAnAgsfti/MKEesXnZhZdyhVK0nhozCryKuBEEQhGBGA1Jw2u4KTBhh5WfqhVhLIAqx69B0g5guKpxD79690yxv2rSpKlWqlO4hYHXyB39Nsog3QRAEQQjEDUjoiRFWpCOiLXEqRCZeUi9YMVb2JqrE1dy5c7UVKBRWrFihP7EwUdnaEwSl29f1Rbt27VyB+e5Z5hFoHDfB7Z06dQrp2AVBEITEElaMojejAYnlTYjRgEGkXohFqxVENM0rcUzPPvusWrRoUcj7Il8WlC5d2us6WK7s6/oCdyCFqWfNmqWLUjdp0sQV0L58+XL9/w8++MAvF6MgCIIgAMlA8YwgrnADJrS1KgBixWoFEZHJU6dO1TFKWIYQVvbhp8FiTKvpZa419Q7tdZnSg30xwvDhhx/WKRkQWePGjdPCivI+rVu3TjNC0hO4IvlO+yRkHBs2bFADBw5U1atXd43EKVmypKpfv76ez2CLWII0JrxgbrnllgzdVoh+uK5cX65zotwXjNjm2Jl4X/tzfnz9TnM+ypYt63UdUvuMHTtWdenSRXfqGYWOa4/BWt27d1eff/65Fk92axWTfaR9JN2AjOQndphj4NirVq2qhgwZomPAAoXawCQFZ3+0idmyZdO/j3csqYx87XPPvgNq4JARqlyFijqYv0iRIqpHjx66rY21QPaQxBXFmr/66it199136xuL3FV9+/ZV77zzjh7x4I0ZM2bokXeMsiM+ClFlhJVx2UUTu3bt0tapN998Uz333HM6SSo3CdYsfsewYcN0LJcRdt7g5sK6ZSZjQRPCz8SJE1WtWrXUW2+9pdOFcD1JDXLppZfqOD3m33HHHSoeIN2JrwZBEOLpnqLjiogxfPjhhxnyvZRtq1Kliurfv7/Od0hn+9prr9X5DxErjFy/6aabVOXKlXXdXdpM3ICkWjBtHi7ASLkBX3/9dT1Sf+bMmbpUHSP3qfPLoDDaYkbYB0KrVq3UAw88oENlEJfXXXed3s8ff/yhBg8erCu5bNu2zS31QrKe/lr/p7q09fXqrY/G6/OBpsBTRN5MjDBTv5usN4kll6DGCpBvv/3WKlasmJU5c2aPU758+axJkyal2mbTpk1Wy5YtXetkypTJNTVq1MiaPn26FSqjRo3ijrUuu+wyr+sMGjRIr9O9e3e/9nn11Vfr9V966aU0y86ePWvVqlVLL3/qqafS3c/p06etI0eOuKbt27fr7fg7WE6dOmWtXbtWfwqe2b17t5UnTx59rh966CGP52rZsmXWY489ZsUShw8fttatW2ft3Lkz1fzNmzfr31qmTJmAtxXig759++p7YOzYsRl2T0WSL7/8Uh9f8eLFdXuSlJSkn3tf54fP9OD8efvdy5cvt3LlyqWXd+jQQbdv7uzdu9d6/PHHrWzZsllbt261duzYoSfmnz9/3ookv/32mz5XWbJkSdX2njhxwmrVqpX+Xdddd11A+6R9/+CDD6xjx46luX9q1Kih99miRYsLM1NSLGvvesva8ZuV8s9yq07Nqnr5zddda50/e8a17ZgxY/T8XLnzWHOW/2mdT06xwkUg7Snttj/td0DiCtHEzWuEkbtQMv/nhpoxY4beZurUqVbevHnTrNukSRNr1qxZllN89913+gcXKFDA6zpdu3bV6zz88MM+9/fPP//odZkQQ54YNmyYXn7FFVcEdKz+Xpz0EHHlm/fff9/14k0Eor0hFKJXXMXqPdW6dWt9fC+++KJ11VVXee0MOyWu6FSXL19eL+vSpYuVnJzsdR/nzp3TbdzGjRu1sELApiAsIkyPHj308d92221plm3ZskW31SxHbDvBggULUrelyee1sGKa9skFo0i+iy+yjm367YLwstHyX7HX/577Y05c+W2TJOZowIAB2mdsAsrwjZIklMzlmI2NuRNf9EMPPaSWLVumzYO40swy3DLkhiKh5zXXXOOYBY7jAIa2egtY53jAngPLG3YTJr5jT5hAdveRhEJ0sGfPHv1JsdNgIJnf+++/r0spMQqV+52RqHfddZfavn17mvV/+ukn/WywPs8Ao0wxuRPPgNuAsk/r1q3z+F3EFlx//fU6FszEKxjzOrU4fcXH8LcZJbt161ZXDIqZ0tt2zJgxeh7ufW/wXPH7OTbcG3YIBRg6dKg2/V900UU67gRXLK50XCLhhPcOx477CpcE7xQChDnnPOeffPKJ1205thEjRuj1zHFzvZ544gmP4Q12Fxnvs3fffVeHBxDHx7uA7ybnXaDw/ewXV5Md3Ni4SVhmr8NqIDEyy0w+Pnd4D9588816RDPXrkKFCvq34UpzJ5R7yn4P33jjjTr+iO/jmWnTpo3fqW8ChetBYmpyQ/Xp00fXqw23a/CLL77Q4SE8B4TBeHPrGTdgzZo19X3FPck9EulgbGLAqCziLWWRGbgFkyZNcrRthu20qyQM/ZdJ81bqz06duqg8ZS9Lk4Kh9bXd9N9zZkxVMUcgVgBjncqRI4d2w505858JD9avX2+1bdvWtR7uQ2OpKlmyZBp3odPUr19fK8rnnnvOq3rOnj277kH4AlOuUdvff/+9x3VuuOEGvbxdu3YBHadYrjKGTz/9VJ9nzN+zZ88OaNujR4+6esK4Fps3b67dyVWqVHFZSDGv25k7d67LkkmPGtcBzwMm9lKlSl3ooeXLp60Bdji2rFmz6uW1a9fW34OVtUGDBvp+7dy5s8detb33/d577+nvYX7u3Ln1MvuU3rY8Dzlz5tTPLBbb9Nzu3bp1SzV/zZo1rt/G887v7dixo1WkSBGXm96f5y1YsCzwPU8++aR+z9StW1c/l4QbmOf39ddfT7PdgQMH9LGxHMt6p06d9PkrWLCgnleuXLk018luxeH8cc1wh/Ts2dOqXLmy6/2yZMmSgH7DI4884rK+2Pn8889dv6FOnTqplp08eVJ/F9eNsAN3y8x9992nfxfHyvFxP7Kusbi4E8o9BW+88YbL4sF55R5u2rSp9mIwDyu/03DN2TfXzpyTiy++WM/7+eefw2K5Mt4P7nFvYJ3CNWncgFiwooXVq1e77inecZ544IEH9HIsXE6wYsUK13du3viXy2pl7Vmnn1fm835xB0vVhO8vtNs82+4ux7hxC3KijWj66KOPvK6HP7lhw4apXIW8GLjJwg3izTSG+MUN+/fvd8VHEXtjZ+LEibrB5CXpTaxVq1YtzYuWhpvfx3L+jipxhWn1zPHYnRwynfMwlihRwvVwIpaeffZZa9q0aT7vx969e7tiKvbs2ZNqGY01yypVqpQqfsKIK9MY7tq1y7WM69SmTRu9bMCAAan2RywC8z/77LM0x4EwWbx4sc+G0F8Xjrdtb7zxRj1/+PDhHrfj97B8ypQprnk0ZhUqVNDzn3jiiVSdLeI3evXqpZf169fP43EGOiFwvYkrhI792Oy/lQaXY7Vz/fXX62W8q3g/2O8ZOkue3P324+Z76UwauA/69++vl11zzTVWIOA6YjtiPO1w3ph/6aWX6vt33759Prcx4oFpyJAhqe5PGlZEEssWLVrk2D01c+ZMfXwI03nz5qVa9vvvv+uONfv46aefLKfAHWdEPXHAhjvuuOOCG6l//7CIK/OdzzzzTLrb8ywE6ga0vz8CmXz9Fk/hM3TyvPHaa6/pderVq2c5wfX/PmuXX1rjP2HFlHzeuuSSS9JcQ7u4WrD6v2fujz/+sGJJXPmd52rlygvmO9wWjAxML38H+aFwZxgwzQfrmgkERhkwLJd6f4wyYAQDJntMx4zSwNxJXi07jJBgGClmXHcwL5PcFFdOtWrV9D4ZCcL/16xZo9dhRAim8Kji3EmlXiiuYpbBO5XK5j2lhr+QeoNrz/36yy+/aLcdkwE3FiMFb7/9dn3fGri+FCMvXry4dgPgMnIvDo5rG3cHI2AZIWQH0z9DtHHHGEj/wOhS0nkwBNqT+5JhzO7gSsiI0kqMemLUFe4hykfZWbVqlU68y++xuw4//vhj9ffff+vf7/5c4QrBbcb5//TTT9Wrr76qXSPmuqT3DvEGQ8W9ce+996a5Dri1cM1S25SQAMpfGZf/hAkT9HXiGHHZGji29957T1WsWFGniWEi7MEdRhAzEszA/fP888/rdwZ1TXEL+zvEnuPCjUaoBC47/gbOHW4a7tF77rlH/x/XMZh7iHQwnsBdyTWxu6FwUeEmHD16tN6+cePGyglwCdNRZ78UureDe/i1115TPXv21OesefPmjuVIxDXPkH1G6RlwDeLmHj9+vKvOrJMYl3jhwoVTzT916pSuC2hSAeE2ZAoEnq9gngtGrEcyZVF6fPTRRzp9Ec/HyGEPpilx4+14TFb2nLb5sZbCKCmQm4oH1Z8H0lxs1ifPBQ91RsEDhYhiiD0vRl5yxBrQYDBUNJAbnuNmKCnDVmlESR/By49GglgCGiReGkL0wnDpJUuW6PQZxBogsoht4X6mw0D8FHmuWGbuDUQTDzd52NyFlYG4KtbjHnNv1Ik5qV27dpptEOhACgg7DRo00AXCEekMW0ZMEUeSkdCJIJaIjgZxQ/bnHKEIxLXYj8vEbpgG39NLmuHYnCeeHRNjSQcl0DxMvmAouSc454gr+zmfP3++bgiJdSIlhzvk6eH5JtaNOC53ccU58BSfRuPIu4F4LWLU7OI6PYgP4zv4LgQWncK//vpLi8DbbrvNJaAQRP6KK+5JT/E93u7BYGHIPs8Wv8HbNeBZASeSRRuIhfR0T5r2hvc2jbqJwwoXvCdo9IlJBt4hweatovPg9HMRSebMmeNKc/PSiyNU0wZ1/itxkzkpTSZ2b1nZYxW/3+BGYfpTR8++DsImo0Hw+Ct66N2ml1COnhFBr0wxQ9ZcF6w/sQrH7zAIGCbzQsQS8/LLL+t8bTRUiPJHHnlELydgFci+z5Qe7sHd6VUJMAMj3AOKyYP2+++/awHPZIKxaZQQXKZBDCcmmPnpp5/WYsqIKzonJo9Qv379Um1jzhPWEKZAz5OT+Drndsu0ERbeymTZ31ueREixYsW8NqB8H+LK/n0kIfaUN8jekCKSEFfci4grI57IRYSFjNx4Zh7CjY4BFjd7sHCw5yMUCJrnecJyYyxu4b4H2A+5pYAOrjvMe/DBB7UV0V1cGcHpK3G1We4uUPHAYDFjsAEDXrjWPCOmM5HRnaJAMZ1FIwY9YRJ+ehvI5Q8LFy7U+SwJoMey+eADDyi1+/c0JW44HgaEeTueU7b5oRxPJPD7TqCnx43mT9Iz+w1pN7kLGQTn3wG3WrzC/Yl4wfXHiDFe1CT9M+KKe924DT1ZoOw0bNgwzbxAEwNi4cBthTuJBvTnn3/WFjY+SeqH+MLVHm4QV7gujUsFkUfGa4QB1jR3t5w5T1hx6ISkB+4tA/tDcAQK3+/usjRkZDLGQL+LZIiMtvMlrsiOjbuZ6819wPcgtMxyRC+lt7C80vib0YJOHGOwmHsAYWEPBQknuJkRNAgZLHvexAGWMqyW9vvWuJ/SExf2fbi7FXG3Iq6whiPyuA6ca8qi4foPBY41mE48niJP58ETJhksYTIYTDxZ5s1I6GATx3Le27dvr8/xkMGD1dNPPamUleL1eBBXqRKM2ti96x/9yX1uf4fEAtEtswUhzOCqQlzZLQsmgz7u5f/9738ZchwmhYNxoWBZoPEl1gZXIeU0wm0F5uVFg405n8z2WM2MAPBkIeA80SBgHeD4/IWGi3itQCFex5u4CgRTsspY3jxhlvlT3sqflAG+wH1KA41FlUYbKxbi3nROjbhCdJmUDd5cghmJeVa4f7EUZYSoM9ZkLEd0QHyti4Xa3aKHSPVVMsu+vgFrDB0xrgPWK+4PXMH2mM1g2b17d1DPBfgrrgiTIB6STiUdOsIBQklZ5A6ik87WsWPH1ODHH1fP3d/3P4uVB/gO7mfzne6sWXUh1rtSpUqOx8+FmwQvwS3EM/7UrDQ9JgZqGIi1AkSXU+6TQKEXfOedd+qYIKwDuA19YWLGaHSCxYgoRBWB9sZN6SmuypwnLF2BYPJEBTrZByOEAkHXiABcawTreyp7RVkQ8NT4hAOOh+/iWr/00kvasoBL0IAFCwGDZctXvJWT+LqnGPTBPUpjas5ZOCEekPhEXJC45LzdKya3FlYu+7HTeQCeJ28CC6uYcTua9Q10OOiE4O4iZ5gvYUXuL1ym/kDHKpjnIpA4La6nGQDAYB13sLCa2LiuXbuqQCD2jlhFLawGD1bPP/esUufcLIT/BrIbzHdwvo010QSzw4zJX+tPcgTGGgGLK2IQCAj1NQW6vn0bQXCCt99+W4++8RRIywOMdcZYpm644QbXMuJYcHFgHueh9mR54EVALJIZ6RcKr7zyikezOFYh04P2xyROPAgvT3rAwSa25fdiQSExJaPfaJg4F57iHUgqzHEx8g63pacamxwLo++iCawRFIXlHiDglhgm92TJiGqCzD2NFAwXRiyZe9IurnC7EqiNaCDOiXgxksyGG3/uKZLFmpg8T4WTOc+4uRnh5ynpbiCJNY3VCgsS92l6Fmnc7TyfU6dOTWUhRKhyTIz0RkjbQQgxyAWRwW83MVvG/UmsHZ0JOj/sF3HgKWk15+rJJ5/U1m9PSVsjCdZfM6LZLoixZvF7SRTOM+8eBoB4Yp6nUbtYnjjnBPdfEFbPpUoWqoPYi16qVMFKqQLZ6aDxvqUzQa1ivtsEs3/9+Ufql4XztMXqvvvuUzGHv3kgTM4qfyd7nit/JhI9JgqSRDRjMPmomAoVKqTzD5G/qn379lbZsmVdy2666aY0ZSxIsGfqbJEIkZxnJGMk3xt/m+SI9hIRJk+Np3xMBvOddkziw6pVq+okhRwjObkoNcX8Pn36+JWTCEjeyDLy8ZBn6tZbb9WTP9sa7rzzzlR5dH788Uev65J7xpxLcudceeWV+vhJVFm9enX9DiChaLgwea7c89D5KgdDbisStpo8WBwv5477xJ8kosEeT3qQN8ucc/fkoPbkjky33357QL/X1/UP5Z6CkSNHuu7XihUrWtdee62+D8jDVbhwYT3/0UcfTbXNnDlz9Hy28wdykJlaoeSq88WDDz7oylVnh/xzJu8hCbHJcUieN9YjOTDzyb80f/58/V44dOiQznVnf0csXbrUda25xy+//HJ9nnhHkDuN9oxllMpxz7EWDZhcVib/H8dNEmDmkffRnlPNUx4ud/Lnz+96B+gks336WH17dLwwXd/FlXjWU0mdP//80/Xccb569rzeqnlZXde9QS7KcBPRJKKBiqtAhRifiYKIq4wBgURyunvvvVdnOyeZIckmabhIfklDYWpgeoKX6RdffKHFGAKBbXn51qxZUyd4JGkttcZCFVckD2V/7JeXOpm3eXGTzJLvcE9EmF5DSOZxEimWLl3alfXd/n3+iCsaDrMdwslXIkTOM/XcGjdurF+ufC8vakQo2cfdE1ZGg7gyiU5JmkpGcbLp09CSMHjw4MHWwYMH06wfbnFlT1LpnhwUEBTmuowbNy7DxJWve8qepJQEuSTX5VxyTmksSZ5LBm4yltvhnmE/7NsfKAzM+kWLFvWr+PHKlSv1+ggd9+9G8Lz55ptaWPBM04iT0Z5kuRRcRoDxbCOqTNFl93ctiUKpXEK2dpIV89zyuxHmCC2KStvfD9HGDz/8oCsqmHcO143f7i1ze3riyt+Ep3PnzvW4b873Pffco58fOq75CxS0WrXraC39dZmVEYRDXGXiH38sXOEOVMRMiUkwEcB0SnJIEpgGO7wUt4VxD4Q6SkUQBCGjwe2Jy55EtP7mBMsITGoJ3s9mNCCxVb5STQj65Cm1b71S5/+NM0vKqVShKunmtHInOcVSa3Ye0X/XKH6xypI5/PUYA2lP/W2/A0rFIAiCIAihgnghF9JDDz0UVcKKdo5G0wShI6iI7XJiNGBCCKuU8/8JqyzZAxZW8YSkYhAEQRAyFEag+juKLiPBKmGOixxQBFMHEnCf0MKKAHb76MBCgQsr+0jBWEfElSAIgiD8K6hIxYC7R9yAAUCSULuwypo65YK/2Mve5MyaRWWARzBsiLgSBEEQEhLcgMTbkFgTcP9Rvk2sVUFYrQx+1A70h/KFYttqKOJKEARBSDhIBEoiUgZS0YjjqoRYbtAjHmdFAHuQwsqyLLVxb3y4BEHElSAIgpAw0IiTMJPAdWOtkoB1h+Ks3JKEBiqszpyPD5cgiLgSBEEQEsYNSDZwU9aKYfeMBszIwt9xZbFyIM7KPdYqe1IWVbFwbLsEQcSVIAiCkFBuQCBoPXfu3DHfiEc8l5WDcVYQD8IKRFwJgiAIcQ+iigkXIElBTVFqIURhhcXKIWEVT4i4EgRBEOISYnmMFYSAdf6PK1DcgCGkXEiTJDRzSMLKiqPcVnbkDhMEQRDi0g24f//+VGXVSLkgwsohEFaZs4RssUqJo9xWduQuEwRBEOIGLCHHjx/XwoqEoGRdFxxyCWK5CiPlYzy3lR1xCwqCIAhxAVYqRgOeOXNG/x8XIEV2hTCkXRDSRcSVIAiCEPMgqBgNSLoFQFThBowXS0g8lLdJJOTsCAnjKhg3bpzq1q2bKlWqlO7RMmLosssuU//3f/+ntm3bFpHjevrpp/XLn89ohmP0t5G66qqrXOsHMgXzXdFI2bJl9fFv2bIlQ74v2PNlrtNPP/2kYh3yVh04cEALq6SkJFWoUKEMSbPw0Ucf6e+45ZZbAtqOe4PtuFdihelzFqqnXx2tOg54QhWvfZXKlDmz/g3//PNPSPtdtGiReuSu/uqaBjVUzhzZ9XWrVauWevTRR9XevXuDescULVpUxa3l6o8//lDbt2/XPYnz58+rPn36hOurBCFddu7cqbp27aqWLl2qH7y6deuqJk2a6CzNixcvVi+//LIaNWqUevXVV9U999zj2PfSaLVo0UI1b948Lhowf2nbtq3HRuPjjz/Wn23atImKl58QP5BWAVGVNWtWbbGK5aB1np2tW7eqzZs3R5X46j1wsDpy1NlRfW+99Za69957dee3YpVqqlmTJurEieNqyZIl6qWXXtLidd68eapq1aoet/f2LokGV7Cj4oobghPy5ZdfukoLGNzF1Z49e9SgQYP0Sa1Xr562HgiC0yDumzVrpjZt2qTq1KmjPv30U1WjRg3XcoT/yJEjdS9p4MCBOmaD+zKj4DtvuOEGXSw2Xnjsscc8zjfiiuX0PAUh1NGAiCk6TIgpU3A5FqyeJUqUUOvWrdPHHyt0a9dSVSpXWl1+ZTt1eb36qnDhwiHtb/fu3eqBBx/UGuDZ195WnXr0UjWKX6yyZM6kjh07prp3766+//57df/996uZM2d63Ec0v0scE1cIqjvuuEOdOHFCnyw7nm72IkWKaJMfqnT69Onq7rvvVnny5HHqcATBJV4QVuXKlVM//vijLnVhh97uQw89pN2ErPvwww+rq6++WlWrVi1Djo8GIZ6ElSBk1GhAGmCyrJt2I5asVYgqb9aYaA1m//C1f0MXil56IQVDSLu01Pips9W5s2dV+cpVtbDKnS3JlYbhoosuUkOHDtXiCu9CLOLI3fjNN9+om266ySWsaMDatWunKleunO52t912m/48deqUV2UqCMGCqPrqq6/036+88koaYWUHcV+7dm09dBvrq7e4KKyzWGGLFSumBRn3OPO5h+3Qm8IlCHQg7PEAdlO/t5greywHVuAHH3xQb8d3VqpUSb344ouuwN0dO3bojg2xZNmzZ1dVqlRRb775psffyfGzbcuWLVXp0qX1+pyXpk2bqjFjxrj2GS3wbuHYTKkS3Ll0xnzFOk2ePFn/xksuuSRNXBHWTF7cxNvxEifomRiP5557TruK3eGcvPvuu/q7OVc0jPTauV9waaQXWzV37lx1zTXX6Pg+klhefvnl6pNPPvG6Pt8/YsQIvZ45NiytTzzxhD7uQCE0o3///q77lXtnyJAhae5Xf+F+5Hxyf+K2uvnmm7VbhvuoQoUK+jjNSD1P8Dy2atVKXxe2KVOmjD6+v/76y+c15VzS8eFccv5xCX322WdpOvO+4Flin6+99lqaZdWrV9fLGjRokGbZM888o5c99dRTHvdL+/f444+rihUr6t/Geenbt69+Pv2JuTLPPM8o0CG0vzfcQwsId+C30BHkPuF+qV+/vvrf//6nLfKO1hA0iUOTcoYcyG79W6Q5879WO/aGxap8Ic8xcjHb+bRC5NChQ1b+/PmtTJkyWVmyZLGefvpp6/Tp03rZwIED9fzMmTN73Pbo0aNW1qxZ9fI777zTShSOHDnC20B/BsupU6estWvX6s8M5fx5y5o717K++OLCJ/+PUt544w19nvPly2edO3fO5/qvvPKKXr9AgQJWSkqKa/7QoUP1/D59+uhlRYoUsXr06GF16NDByp07t17WpEmTVNdi+PDhVps2bfQy1u/bt69reuihh9Lsm087Y8eO1fM7d+5sVatWzSpcuLB13XXXWddcc42VM2dOvYzna+PGjVbRokWtUqVKWT179rRatGihn0OWjxgxIs1vfPbZZ/WycuXKWa1atbJuuOEGq3nz5la2bNn0/G7duqX67QaWhfq6MPuYy33jx3pPPfWUfn9wbq+//nqrdu3aej7zJk6cmGa7MmXKuM4Ln/Xq1bN69eqlf9/8+fP1OmvWrNHniuXFihWz2rZta3Xs2FFfI+Zddtll1uHDh1Ptt1+/fnpZjhw5rNatW+t9cm0rVaqk50+aNMnjcTz55JP6WOvWravPc6NGjVy/7fXXX09z/AcOHNDfz/K8efNanTp10te8YMGCrmu2efNmr+fLnXXr1un7xvxW7tn27dvr+6dx48Z68ud62OH+ZZv77rtPHyO/lfuO82Luyy5duqTZjnuK54flSUlJVsuWLfU5qVy5sp6XK1cua8aMGWm2cz+Xl156qX4mOKfpncv0mDZtmt6uXbt2qebv2LHDtU/aJNo2O82aNdPL5s2bl+Y55TdzbLxruJ84RnPu+Q3u9xTX0SwzLFiwQJ9f807h2tvfG1xPA8dAu8t6ZcuW1fcK96SZx3vi7NmzVkjwHti73rJ2/PbflPzf+96cq+3btwe02/PJKdaq7Yes+b9vsi7Ke7Hex0cffZRqnWPHjunfwLIXX3wxzT54plk2aNAgfS8OGDBA3yPcQ8nJyWFtT/1tv0MWV/xwI6CeeeaZVMt8iSvghmQdHvREIWbF1TffWFbJkjqVnGvi/8yPQm6++WZ9nhEc/sALy7wwNm3alEYAGbFz8uRJ1zJeLKaBeOyxx1Ltj0aL+bwIvOFLXDHxsj5x4oRr2fLly3UDxXNVvXp13TGxi8dvv/3W1UDbt4OlS5daq1evTnMcNCxGvIwfPz4qxBUN1ZIlSzyeL865t4YYcTl58uQ0y7luFSpU0Os88cQT1pkzZ1zLOE+IJpYhpgxbt27V80qWLGnt2rUrzT55BlnH03HQcZwyZYrH63rxxRenuo8AAcmyhg0bWvv370/V0CAEWHbFFVd4PV/u1K9fX89H/NjfExyvOQ/BiiumIUOGWOdtnSvuKyMMFi1alGq7d955R89HKK5YsSKV6DLXlOu9d+9er+eSBpj7dM+ePVo4pHcu0+P48eN6fxyr/R74+OOP9f5ok/j8xvZes29jFy325xRxY3+nHzx40CWWX3jhBZ/iyv03exLSwH1IJ4928+23304lJrhvEK5sP2zYMCskEFJ2YYXQsnW8ghFXKSkp1tnzyVpcMU2cOMl1z9SsWdPVAUAkMj3//PMeO3tGXHmaeDfwnot5ccWP5CIXKlQo1Y3qr7jiZLIOPcdEISbFFS+aTJlSCysm5jFFocDCKsF5pofsD3/++afrAf3ll19c883Ln565pwaWBtSIGfv1cEJc5cmTRzcm7tBTZXnp0qU93gO1atVK08v2xaxZs/Q2PJPRIK5GjRqVZhlWcRpTlm/bts1jo9S/f3+P+zUNPBZHTyBisDYgXGkYgZc023C+/cUcx4MPPuhxedWqVfVyY00zgof3JO/CVatWpdnmn3/+0ZYztvv55599XpuFCxfqeTRcdqFmwNoWirjCcuSp0UPos9y9o23EnKdryn6MoKEx9XQusUwgrLAm2cWEp3PpD8YK9dNPP6XpjBnLlt2b4s3aZZ5TzvPOnTvTfM9XX32llyN4nBJXjz76qF5O++oJ7hWEIG2yp2sUlLg6fzaVsApGXKWkpFgb9hxzCSsmrFjLli1LJfbNhOXKfn3s0Dl67733rPXr1+uOEb+Ze7pGjRqudzHtYyTFVcgxV+vXr9d+UkZkBVNlHP85uI8uFKIIanPdd98FOeWOmXf//RfWi2F8xW4QO+Np2G+HDh1UgQIFdJmN3377zdFjIm2Ep1E5xM4AcV3E0nhbTlyGO8TETJkyRceO3Hnnnapfv346loaYK/NMRwMdO3ZMM49YlvLly+u/PcWyAKOMPDFt2jT9ef3113tcTmA0I5eJV/n111/1PIKOiWUhzuv555/XcUahHD+YwRL2458/f76O7WJE66WXXupxdBkxRkDskS9MfA5pMbg33encuXNIw9W55z3Fx3j6beRB+vvvv/XfxCC5w364B9P7bV26dNFtBTFv9sB1T9/nD61bt9afs2fPds2bM2eOjpdq3769Kl68eKpl5m+znTvcN8S1uRPs8aWHr/uYe4Xnf9++fWrDhg3OfGmIxZlNDcGTZ/+LBcudLUmNGf2Oaty4sb5HuWfRAcQJkqKBdAzETRKL5s6zzz6rY7aJeSXejN/MPbJ8+XIdd8a7mPi3mB4tePDgQf0Z7LBMU1QzlkZ6JBwLFvCG9L4cUbJ9+4X1omhYrAmEJO2HP9gT1pGE0B0CTL1BYCpJDENNqOcOQeeeMCOkvC1HEJjkinZ4YfFSTi9parTUYvP22whu9/TbDN5yAzHAAQjCZkoPGiZzHseOHasbf4K1mWhEGzVqpIVL7969vY5yDuT4TeOb3j1GwLh93fQw96G3/Zlg6lWrVqlgCOa30YCa5en9Njo5jAS0dxoYpMGAAH++7/3331cLFy70OGzfjNBDJDGoAdFEQ7127VrdEbnrrrv0coLuSdtCcDlB977EVbD3ajCY+xiDhi+4j30NLONccc7c6XJVPdXlmibKCSzLUpv2/Zcjq1qxvOqXxYt0XkGeJ0YFGrHPOWOAEYMeevXqpVMxIJzSG5Bk73wxYIP1GSTHAKVIpbsIWVxxQmhUGBobDPYHT4hSdu1ydr0MAqsPo4mwJmGNIO1CepBk1NyLwSbvC3Tkki98dToC6ZQwEo2XDmITsUBDQk+dl1mWLFn0iC0aMad/Q7AE2+Hy1AiDGQmJKCIVTHrQoBquu+463ah+9913asGCBernn39WkyZN0hPWvx9++EGPNnTq+GOBcP422hNyWNlHNAbyfYgFk1PNDtZZI64YDch9j4USa4kRT4xGBK434opr26lTJ50UGwOCp+sc6PGFirmPsdAygjY9/GlXN27c6PF8lS2Q/YK4cmCEYIql1KlzFwwpObNmUUmZM7m+E0uhJysqvw9LJ9eH62SujS+MtRALPcW7PVkUY0JcYY7jBwTTA0JVksOCXpQvdS1EEH9vzgjdxOm5ZchhxcPJ0HwaSW8gKHiZpufySM8lZIbjlyxZUkUruJ4QVgzz//DDD9Msd8yFEKWQquLPP/9Ut956q1fXoTd4+dstXrguSMPAfUV+NNJthPoetVslPGGWmXX92V96aSLMkP9wY44F0YRV1JP1yvw2rM0IK54/b1YuX+BG8uRKskNHi8oJuMdxRSKu6GCY9Cl2tyFuJ94PWLOiIUEp9zHPKomPcUeGCqIzTfmelGSldv9+4e+ClUJyCVpuVqvyhfLo82is596uM9cI8cj9YDxk/sB95m7BjwQhy21zM65Zs0b9/vu/F8NPMLcbFwS+VSFKwfyMaPD2gDG/VKkL60URuBp69uyp/37kkUfU4cOHva779ttv6/uXB5p1PYHp2lOtK+JxeKB5kLGWGUwMomM5Z0LEvKC8uTCw8sUz5N6D8ePHO9LADRs2TP+9cuXKkPd35ZVXausH+/LUUd21a5crF6B556YHwgHYxlPDhBUuvefBSehwGLefJ9GDJeaDDz7Qf19xxRXajYNb3psF0imMgJoxY4YWxwgV43oi5goLCHFYWK/s64cbX+8NJ+/j9JKGOkWKm9XKJAo1ovuXX37xuB2xnya3W3rucndMbkOuXyQTk4csrog5MBAcm14COTuYWU3JGxo0kpAKUUqWLEqNHHnhb3eBZf7/xhsX1osyCIzExYfVCQFPJ8AOLzCSCd5HwL5SOsGmvTyOHdwUuNLs7griNLCOmfvfHidirFj0MrHSRhpjLqfBIMbEDkkyKWwdzwwYMEC7+yZMmKB7/cT1eCrJ8d5777n+v2LFCn1ePCXdxOrh7kIMFgRvjx49dC+fhLD23jfJKTl24nYQH0y+IB4HCyXhGsS12N/LWN2oRJCRmO8jvskuHom5HTx4sFq9erW2Dt5+++3aeuXLhe8ERiyR1JVOvrvbieV4ZUxjnVHiyrw33N9VBjp/iEDeW9RDxbLjDu+7oDpLYUgaevXVrVXnqxqoOTOmuqxWYKzHFG6mvqs9HIFOLBZmwKtlt9BhaST43T18gfNAAl6TQNm8lyNFyHcwP7pbt25q4sSJWoFiOh09erSqWbOmx/V5SdFLITCUG5oTTdS/t960ECV066bU119fGDVoD9rmRYCwYnkUQlAkMRjEGi1btkzHTHDP0pM2hZsJ+qS3yIvKiCxPkJl96tSperQajReNHSV1aPwY8WIsGQbuab7L/r2ILxoPXgIZDSPRGCWGK4u/ySLP+cFaQi+RRo4RcfEKLgZGWuH2JQs/gpKReTRm3AvEnFHvjdgaGnnjOqP2o8mujsUKQY4Y4Jxx37hn9A+lI4Dbkvco9ycWKkQGVhXuUXrvn3/+ud/7w83NNUYc4BIm0z2/k3uW3819mFGlRRCMNKIcE88BljXOM/GQnEeeC6xaxsKVEZCNHQuVGVHrSVzRUPOcM/ouo9oowhcQEBgcTHZ/I6qIieR+NWEOiFbuP9pbYosIgeAeZnRmw4YNAzNaGIvVuRP/zbO5BBHGZqSiHWLSjLWNZwQvgJ1Nf/+tn6Pjx1IPlCHWivuCUcoYWszzSKeHZwB9gIjknrHHtCHOH3jgAR03SZUF4sp4PvA8mMFLnBcjziKFI90DRhrQE+bFwMNKWQhuXHtvr2vXrrpXyIschWlUJy95T2UIhCgEAdW584VRgQSvE2OFKzAKLVZ2MD/zsGJGp6EhOJIHlBc6VgdEE3EzvoLYadwQSoxGoYHCZM0LF+stlhBPbgzKtzAkmJclFhAaZr4zEuIKsNpQqJreOqKTc0BjN2rUKN2AxLO4AqySvITpABKQzt+8sxAaNFq8lHlXGRgVyLVCnNBoYclC8LAuFiHirmjwnIBGAgHCteBewQ2Ny4z7DrHHsZmG1h94B3O/MioO19e3336rj5tjJhCfxi2joBPNPYdLi0aUIfN0SkyJGISDN4txODGjAhHedJDsIEy51jyzGWW1AqzjCAwsT4QcmJGGCCVzr+FGxrJFqRsED+80rJMIVt5JrJtejKlHrJTUwipr7lRWKwSbJxcez4TBPS2MZVnqfLL3ATI8h9wTGFy4V7EGc86550k9Qnkf9zhWhDnniHuI5xe3N+ILocw2CDZ/rLvhJhPJrpzYEYqRYZMmv4q3wD/71+GmocGj95xIoMgxgdPLCDZokwcO0y83oac8R4JzUPcPqxSNlHsNQEEQ/AehQqeEuCp/htYLGQTt8t51SiX/6z4uUlOpzEkh57ZKTrHUmp1HXPFWFQv/5xaMJgJpT/1tvx0bP4qJjlgOhldiqvs3+3uaycR+YAKmZ5ZowkoQBCERwZOB+4b4Qxozk+NQiDC0y/vW/yesiLNyQFhZXkYJJgqORg1y4sxwZVyAmNvxZ6PwMLsiwPADBxL5LwiCIMQuuDbp7RPvBcTn4N4k9YEQBeAONAHsWbIrVahKyMIqvVGCiULYhmTgS7fHLgiCIAiJBVYq3IAmrQBD40lZkkgWjKjGPe2CQ8LKnUSzWkH4x7sKQoxDnJXEWglC4G4hgo1x/xFwTIyVxIdGsdXKgbQL3lyCiUjIZ5Lh6yS4EwRBEAQDlgoCf3EDkhRUhFWUE2ImdjspCe4SdERcMYSWoZ/k42BIK8NrBUEQhMTDBKsbEFSkmJD4qsSlfAK6BCGzUwGLjBSkPhFB6zfeeKPOq2IKTAqCIAjxDQHrZDS3x1hBIjasiYy4BB0SVyRXw59uUi3wgJGokSzIJPUikyrJvgRBEIT4g040gopahbQBuAFFUCUu4hJ0SFyRq4paVcRekfoejNCiPhDZhhs0aKCzBQ8fPjzDKrELgiAI4XcDYq0y1TgYCUjuQnEDConsEnTMLUjaBSxUpK+nRAQ1ykwuKyO0qB9FPUFqR5G6n5I55L8SBEEQYg/iaxFWuADxXhBbJWkWBMHhDO0Gah8999xzug4RtcuoAcRDZ0QWJuSff/5Z1/9BlFEZm5pX9IAEQRCE2IB3Nu/07Nmz69GAfAqCECZxZYfiiVR6J1XDd999p3r27KmL2xqhRaFJiqdSYJKK3oIgCEL0Yq8NS5oFJnEDxkkCUSF2xJWBKtcEuBPoToHnDz/80BUIbx5YAiIFQRCE6IN3NG5AkoIagYX7j7Jm4gaMUcKUQFS4QIafTcofkLJh2LBhqlOnTql6Qk4xYcIEddVVV+n6VTz8tWvXVi+99FJIrsfJkyfr48WVyWiYwoULa8vcM8884+ixC4IgRONoQGJk8TaY4HUhjnAogSjt+ca9koYhw8XVX3/9pYYOHaoqVqyomjZtqgWL072e+++/X7sfietilGLbtm3Vtm3b1KOPPqpatmwZ8Ivh7Nmzen9dunRRs2fPVjVq1NBxYjVr1tRxZYyGFKKXsmXL6nvMPhEbUrJkSdW5c2c1depUFQv89NNP+tjpNMQDv/zyi47H5HmiLIrpsDRv3lzHbPLMxurv37Jliz5W7j1PTJkyRTVr1kzlzZvXdU/y+8D8P1rg/bdv3z5XYlCOmdAOQfAkrP7ac1ydOS9pGDKktiDpGL788kv1+eefp8p3ZbdYIVRuvvnmkL+LwPiRI0dq69i8efNcqSEY0YKwIsD+ySefVK+88orf+7z99tu1JQxx9d5776mCBQum6tEtXbo05OMWwk+TJk20qAd64CtWrNBxgEyMdH3ttdcifYgJAXnwbrvtNv1OACzBdLSI3eE55XmaP3++evbZZ9W4ceP0cxdPrFy5UseY8u7gnUSsKWKK8xCNbsCjR4/q/xNThScAESwI3ixWRlhlT8qiKhZO3DQMGisMHD9+3Pr000+tNm3aWFmzZrUyZ86sp0yZMrmmkiVLWo888oi1atUqx763fv36KDbrueeeS7NswYIFeln27Nmtw4cP+7W/2bNn621q1qxpnT171rHjPHLkiN4vn8Fy6tQpa+3atfpT8E6ZMmX0uR47dmyq+efOnbMGDhyolzEtXbrUimbmzp2rj7N58+ZWrMIz1LRpU/07ihUrZk2ePDnNOlyX8ePHWxUrVrRef/31mPz9/M5169ZZGzduTLNs6NCh+ncMHjzY47ZsxxRpeEfu2LFDTwcOHLCSk5MjfUiCk6SkWNaedZa147cLU/L5kHZ3PjnFWrX9kJ7+3HXUSmH/MUQg7am/7bdjlit6YjNnztQWKqwB9FD/FW+udciB0q1bN3XTTTfpXpuTqnbHjh3q119/1X/37t07zXJ6x6VKldIJT6dPn6569erlc59vvvmmy9WYNWtWx45ViDwMsnj55ZfVJ598onvnuGrq168f6cOKa7BGYT3GDYjb3uTCc78uPXr0UO3atVMbNsTmSCbeFVWrVvW4zLg7K1Wq5HG5t+0ymly5cul3OG5A/k5oC0Q84mAwu3u5m4S3WDkVc0XsxL333qvN2x07dtQjAjEnm3QLvCyvvfZa7QZgpODYsWNVq1atHD/5uHmAYcGeXtpQr169VOumR3Jysq6XCCQ93b17t3rjjTd0nAhi6+OPP1bHj0vgXixDUVnTyHFvukOMHff2ZZddpt3BJlbr+uuvdwl5d55++ml9b/NJrMo999yjRT3uFD7ZH2VCvIHYQ+TRoHEvEzO4YMECn78FdxqxgZScMvFLPI8//PCDx/UZVMJxfvTRRzrBL7+JbRgAwvcTD2l/xhnMQS4j4m0aN27sejb85dixY9plD0899ZTXZ9SAa79OnTp+7TuY60Rn8N1339XuYsQegojfz+AX9kXclB3Sydx3332qcuXK+r7h+nA9eZe5hxl4irky9wXvP+jXr58rvsoeR5ZezBXJOkm+zPrcG/xOziPvJDqN7tjj1BBKnPdq1arpY3ePB+NdTXyVgfNBnVgZDZgAhBjMLuVuPBOy5YoXLQ+f+6g/gsmxUN1www2p4pTCxebNm/Vn6dKlva7Dy9C+bnps2rTJJZ6WLFmi7r777jRi6pFHHtFiEitcejDChslg4hiEyGOuBQ2JO3feeadutAi6phGmo/Dnn3+q8ePHq4kTJ+prT/yMJ9iOmD9GqLItAcFYa/73v/9pscLf7tZQGm8GSJCiBEsrQun333/XjSMNvjeIBeRYEQwIEtanzBTB+kw07Awk8cRvv/2mBg4cqMUIQoHtFi9erLp27ap/J78Z0UZcJMv5/TwPiL65c+fq4/QH1uVc867o06ePcpJgrhNxXwgdhBK/AeFImgGee64Rv9UIEDpWdMx27typ3y/8drbj/8RQEUv68MMPp3uMCL++fftqyx0DYewxgP5YqxCnCFwEE8Kzbt26+phXr16tRo8ereNCEdKeBCn3HvfE2rVrdUcRAXngwIFUHUkEP+8o3tUmrsqkyhEEb+jE4La2P5HL3aQhVF+lPY6qQoUKOqZgw4YNVkbz/PPPaz9okyZNvK5DnAPrXHPNNT73t3jxYlc8DnFjxHr8+uuv1rFjx6yVK1da7du318vy5Mlj/fXXX+nuy8RZuE/hjrk6c+aM14nYFn/XdY83C2Rd/h/IuhkVcwWcvyxZsujlXFt3Jk2aZB08eNDj/KSkJKtAgQLWyZMnvV7rW265xTp9+rRr2bZt26wSJUroZV988UWq7aZOnarn586d25o/f36qZS+88IJrn+4xR7///rs+Fp6/Tz75JNWy6dOnW9myZdPbff/996mW9e3b17VPYhTtMRKjRo3S84mLzJ8/f5r93n///Xp569atLX958skn9Tbly5e3giG9mKtAr9PWrVtdv2/Xrl0e7wvWMQwbNkyvP2DAgDSxJNyzxGba2bx5s16fe88dc9493Y9grok7vXv31vM7dOhg7dmzJ9UyYtNYVqlSJev8+fNpzhnTpZde6vG3cn/u3r3bFV914sQJj8clxBnEWIUQb8VzQJzVX7uPumKtmJgXi5yKxpgrStvQs8VKhRUrXrBb4kqUKKFmzZrlKu9Az4+4Mnqjf/zxhxoxYoT64IMPvO7r8ccfVw8++KDr//TgjRUtnFAo2xu4w+yxabg2vOUBK1OmjHYjGXDvmJg6d7C2MMLSQIZ+bzUk6XljEbRbYOz/DxccD9YjLEX02ql5aVzGdryNVGM+cUG4urHItG/fPs06WIL47faSIMYt+Nhjj2lXlj3uD5czYEVimL77/YMVBiuJO1wL3EXEMrqPuCVuacCAAdoSQ3zZ1VdfnWZ7LMzUArX3NnEzYe36559/9O903y/ni+NlVB/3jD/xiLhIAdeb0wR6nYwLGMuip1F6uM7smPWxWLn3yvntWLnCCfVa+Q08W1988YWOXbVDmAJWK2JJZ8yYoRM2u8M9YP+tvN+wxGMRA6x9jAaU2NIEgLaNmKugN7fU3/tOqJNnz6eanztbkrgEbYQsrohF4MGMNOaFQ7yXN4xbjyBNf/cHCAv3ulkMTaY+Io0lDWV6sK3U3YosxLgwuV/Dzz77TN14441et8P1M23aNO1mQpQhZGDNmjX6k3glT+KKBpfYFm8NNwMwDOwTdxHQSfEErjRP4srkR7KLXzu33nqrbliJ20JIupcpQYC5CwaeZ2J5cJN5+m10qIj5YTnupWhIIxDIdcINx/ONGHn++ed1JyO9GDAE6Ntvv61FMQ3LNddco11zGQXHyfdyrdyFlQG3H+stWrQojbhC0NoFu90NCMTRkQpD3IAJVPLmnPd20p8YK7uwIs4KdyDCSlyC/xGyKooGYQUmPsJTYKfBLPOW3M99fyaWrHz58h7XMfMRmNEIFg9vuL9I04sZcX9gsPj4uy4B3d6y8Luva7d4OY09xgUrCmKDXjtWGqx4NKDuUEWAxje9zP7e4ue8xf4ZYW+SMgICxfzfWyPvbb4Rad6WV6hQwfV9fI+75cjbcRrx4G05jTziyv470gMrpcl75zSBXieOnXgrxDZWOCYG5DRq1EhbpxBbdvGE5Q7LECOhid1CoFavXl3HapFQ2FfMZagQBwZYx9OzkNsthHbc33dcM4QVz5+MBkwwsFjZhVXW3CGNFKxWLK9KyhxdiW+jhehQRg5gAjlpQAhY99TYLFu2TH+a5KLpwcu1SpUquidMckNPmPkZ2YsNhEAS/oVr3UDcDOF0SRDAbLfuYN0gaBt3EW5tgn3tliYCoXGNcW2x/NCA4pahl8+LBFcabldvwjFWrAC+jtOp30EANvBs8oxi/XKCYK8TIon6prj3EdoMMKCIPBOj6hBTtWrVcp0DLJzsC+sY6zK98847emJUJtuFq3gxAxWAMARCEtKjYcOGaea5Z1TnPseyx6e4AROYIjWVypwU0EhB9/I2maOsokA0ERstgB8Q42LyFBGX4A5uFyxXuOc8uTo8QbwGeHP7mWHunqweQnSDG4QM4Li3GCHnnqGdGCfAIkLcElYvew/fyRxMCA3jNnZPAWDwNp94QLt1wx0zn9Ft/NZI0aJFC20x4uVMugmnCOU6cQ9glSIlA+5DclBREokYK2Lf3MFaxQhhKkFggeO9gCWQHGlO/iZ3THwm1ldSZ6Q30Ylwh3OOG9CINM4Nv12EVYKDxSoIYSXlbRwUV/QGzeQevGlfFsrkRFAoPUsgwJwh5gZ6yiZQmpcmLxYDPU5iMDx9/6BBg3SQJ7EMY8aMSbWM4d24Ccx6QuyBqwqXkAnot+efwuVlgvndoWH1lj8qWNc6DSeYe8qdTz/91ON8kyOJhtUTH374of4k5iaSLnzcT+Y5odi5r3QoxEf6k4/OyeuEiMHFCJ7i2+wgUHhnmEEhvtYPBWKtACubv25YO7hLGYAiKWASnBAD2e35rKS8jUPiiqBZavXxaQJo3ZeFMnnabzAwOogXOC9m4id4KRETQW+WfDA0YGSJtoN7iGBXcs+4Q84XrBv0+smlQ64frFm4FRnphZKnVqG/ljAh+kB0E1fEffDqq6+mCTzHqmFPrsh65CvyNgIyWBjxZaoCEJRs56WXXkrVWXCPf0M0YU3BdWXn+++/d3UKfOVhyghwt11xxRVaxBKvhMXHHYKt6fDgRuTd4ItgrhOijefaUxF3c0x2sYZVyl4X1UDMnnlveRJ3ToY84MbE8s6oUE9WTAbyIMzNyEZTG9DAPUJCUCHBA9n3/OHI7kRY+cbvrqy32BJfyzIahqYjohgGTyNFr42gXkb6UKA30MKjDF9ftWqVeuGFF7QbgMzV9MIRVDRsjBwSYhfcccTs9O/fX9873CO4zxA7NKpYLRm4gFjnXqLBx+3E+sYq5ATE7RD8z32LlYlkjwRZk0SUofjcaybDuR3igtiGwHxcXK+//rq2xOLq5P7n2eT3RcN9yrNHShNGMOLOIykmvxEhxTOFhZmM6lijTPZxXwRznTg3JDcmFomOEhYrYpDogNHR4jgRtPa4LoQasVzEPWHNPnTokI67QrzR6QrnYAwgAB9RSqoFYkGJveL8cH0RW7yjEJfcK3QKOT4jHokZY16sxAEK0R/ILjgkrgj6DWZZpCBAmckfCHL2NozdQMkLb24XIfYhzQFuQYLayQdFADQNFxYO3IYEPJPpnJQDWCwRKwQyOw0B2QgNxBJZ0BEYxBEyHzyJKyDWiMaW30BsIYIM17fpAHjKbxUpCDzHaoSIRTBwbsmXhduKMjQIlTZt2mgxY+LJ0iOY64QAI3SA70WMsD2WHeI2EbikV0HAGB566CH9PYhVLIiIPwQ4MVi4BRl1GG6rEPFqWCI5d1gosaThikSUIlBJJ4JYRSgyYpD4KmNZ4LeJsBKcDGQXfJOJTKJ+rCc4CLEPNH70ev3JueUJYi/MqEjcloIgCLhVEVeMXMTCFi2pcoQIk5Ks1O7fL/xd9FKlMmcJWFjZ6wfGm1vwdADtqb/ttzx5giAIMQxWKmOZQlQx+hRRFU+NnxA5JJA9OMRWLAiCEMM9bkZF2stRkWJBGj8hHIiwykBxRRApkxnCHCjEt7C9ySQtCIIg+HbV4JYg/gvLFeJKIjyEcKRgEIIjZLcgI1VQsoz0CQZeDmYfgiAIQvowspHRgKbcD8H0xH7IO1RwupagBLIHj8RcCYIgxAikVyAlA40eYooRlu7lbQTBJaxSzgedgkEysse4uGJ0iz4QGdUiCILgFSxVWKxMXJWMBhQCslgFmIJBAtlDI+JPJvW8TB4XQRAEwTMIKvKEYVEQN6CQbnyVp6Shfgor7i+Eld0dKMIqxsQVifBmzpypLxqJOoXAkSBWQYhvNyCiylio6IRKIycEFF8VgMWK9uTvfSfUybPnXfMSwR1ohaEdDUhcUWDZG9QD++OPP/w2b+/YsUOXoTCxA9FQniOWIJ+NOZcScyEI8TkakFGAiCvK1/CeFGEl+B1fFaDFCrBYuQurRLBanTlzRn866WYPaE8UKfV0knkR7Ny5U0/BqEXKVQwcODCgbRMdXriUR+EFLL1ZQYiv0YCMouYTeM4FIeD4KgLX9ZTJ7/Z4077/XIHViuVVSZnjX9AnJyfr541RtxETV+mZz4Ixq1FYtUuXLrooMj0zITA4Z1gA//nnH52OX5IHCkLsuwGPHTum/+ZZJraKQtKmZy0IHkvbnLKlS0jKqRTWpwDbguQUS538t9g3Aeznz55RyXHanliWpUUVzxsGCnLFUaPTSQISV+5FmjlAXIW8BBBJgwYN8rkP1qV2DyUaqOMjBUWDx9Q12r9/vxZZgiDEJrxLedGfPXtW/58eNJ3P48clx5DgA4LXj+y78HfeEhdSgx/ZEvBu9h49rc4mXzCSFM+XQ205Fp/Cyj28huescOHCuhMTMXHVvHlzr8uoYJ/eciF8AouJ2CuT1kIQhNgCF+DXX3+tO0r169dXtWvXlo6n4Bs8RuNuVGr/Xxf+P2C+UtlyBbgLSx0+eU7dNnGR/n+FQnnUmJurxb0XJHPmzGH19oTsYBw6dKj+bNCggRPHIwQJNwmTIAixgxnQAx07dtQuCsqBCYJfwurEfqW2zLnw/6K1lLoof0DuQO6/7qMXq+VbL+RPg+8fbqRyZo94lqaYxzFxJQiCIPgH7r/p06frDOtXXXWVnkeoBJMg+CWsPmyj1PZf/pvXb2bAcVYkCbULq3pl8qtc2S6MRBdCQ+SpIAhCBrJ37141YcIE7QLENVGnTh09IEUQ/ObcydTCqlQjpbLlDmgXWK1Onv0vlGTZE61VgdzZ4t4dmFGIuBIEQcgAaMxWrFihZsyYoWOsSKHSrVs3EVZC4Farsyf/+//DG5XKXTBkdyAWKxFWUSyuiBlYuHChWrlype6ZMayYYY6+4KJ+8MEHTh+OIAhCxCGVwrRp09Tq1av1/ytWrKhHWJNbRxBCcgcSwB6gKMJi5e4OJGGoEIXiioKijz76qPr888/V6dOng9qHiCtBEOINOpdjx45Ve/bs0Z1I0tc0adJErARC4Jw9kdYdmDWw0YEpKZbq8OZC1//FHRjF4mrLli06DQPJLP1JJspFdF9PLqwgCPEIcVWkV5g/f7667rrrVOnSpSN9SEIsQps5tm3I7kCE1eb9F7K5Vy+WV4RVtIorLlbXrl3V9u3b9f8vvfRSdeONN6rvv/9ezZkzR1+0Dz/8ULsHqSXIC+bXX3/V61LhndGGkp1dEIR4Aus977xChQrp/19++eWqZs2aUspGCC2Ifffq/9IuBCisjDtw7a6j+u9yBXOrqfc2FWEVreKKxHerVq3SF6hNmzbqu+++09mFt23bpsUV9O3bN9U2y5cvVwMGDNDBnSNHjtRCrGrVqqEeiiAIQsShxirvRdyBd9xxhy6szvtRhJXgGEGkXXB3ByKsMmcWYRUuQk4BPGnSJP3Jy+Odd97xq/Bh3bp1ddD7FVdcoV2JPXv2DDpOSxAEIRrAiv/LL7/o2FFiUMHUCRQERwlQWHlyB0o+qygXV0uXLtXCCrN3mTJl/N6O3txHH32ka/usWbNGffHFF6EeiiAIQkSgLuD48ePVzJkztcUKSzxWK2qWCUKkIVmouANjTFzt23ehYGS1atVS79hWF8ubVYrhyFivUNVfffVVqIciCIKQ4WB9HzNmjPrzzz/1e69t27baGk8HUhDCktsqiM0N4g6MEXFlhBPB6Xbs/z948KDX7StVqqQ/169fH+qhCIIgZDiLFi3S+f3y58+vbr31VtWwYUOxCgjO57Z6pWIQm1rqxJnzqWKt5NaMkYD2vHnzavF08mRqVW2vkbVx40ZVvHhxj9vzUjIlIQRBEGINCi7TmSR/VY4cOSJ9OEIilLrxI7eVCWA37kATayXJQmPEclWhQgX9uXv37lTza9So4fr7xx9/9LgtsQm//fab/jtXrsASoQmCIEQCRkIzwtnk6sP91759exFWgkPuvxNuk1upm/6+RwqaAHZ3YSWxVjFkubrssst0UPvatWtTzW/UqJEeekz199GjR6u77747TXDnG2+8oTZv3qwvNjlgBEEQohUarJ9//ll3Fvm7aNGiOq+fIISttI07fpa68RTALrUDY8xyddVVV7mCOjdt2uSaTzFSshHzEiLovV69euq1115TP/zwg5o8ebKOTfi///s/1/o33HBDqIciCIIQFk6cOKFHNJO7j3darVq1VJUqVSJ9WEI8CasT+9MXVgGUunEPYM+dPUmEVQaTyfKnXk06HD16VFukzp07p4YPH55KMO3YsUP37A4fPux1e76evFcEhWbNmlUlApwzxCfxZsSsCYIQvVDea+LEiTpnFXn82rVrp+rUqSONlRA+ixXuP6xUdhBWftxztKnXjvrPJbj2mTYqVzbHyggnPEf9bL8dCWj/8ssvdUB6iRIlUi3j/7Nnz9YWLF5Qnrjyyit1fphEEVaCIMQOJAWdNWuWbrAo09WjRw/JXSWEP2A9iNI2nlyCEsAeORyRs9QW9AY9PPK/fPPNN9qkTmkIcsGUL19ej7K5+uqrnTgEQRAEx6E2IMKqdu3aOmg9W7ZskT4kIZ4JohizO3Zf1IQ7G4uFNUJkiK2QF1KvXr30JAiCEM2QVsaMXqYTSKZ1gtcFIez4GbDuDToCPUYvdv1fdFUMB7QLgiDEA6SGmTt3rho1apQ6cOCAa74IKyGshBb2nApxCUYPIq4EQUh4CFb/5JNP1Pz589WZM2fUunXrIn1IQqIIq7FtHdqVpU6eTXb9X1yCkUWGEAiCkNBQQWLSpEnaHUgIQ4cOHXSqBUEIOyQJ3b36wt9Fa/mdasGfbOyiq2JcXNHTCwWC2xlxmC9fPlW6dOlQD0cQBMFvNyAJQUkMCkWKFNGjAe2luwQhw6xW/XxnXve8m7TCql6Z/OISjHVxRRJRp0yPuXPnVpdffrm68cYbVe/evfX/BUEQwsGyZctcwookx23atNF5rAQhIlarbMG1d5KNPY5jrlDOTkzHjx9XCxYsUHfeeaeqXr2615qEgiAIoULyYmqjdu/eXV177bUirISYs1q5I9nYo4eQ3yYkATUXcsmSJbqWoEn6TtK9kiVL6orxlI+gRA6lcIBtqD3YsGFDnd394MGDOvbh/Pnzevn27dt1XpkZM2aoFi1ahHqYgiAkOMnJydpahZUqS5YsesJKLg2REJFSNw5YrczuDHIrx5Hl6qefflJTpkzRyfYYZXPRRRepYcOGqb///ltnbf/tt990XNby5cvVnj17dKHmZ555RsdZsT7ZjsmATOFn0skzYqdMmTJ63wi1Pn366PUEQRCChRJcY8eOVTNnzkxlERdhJWQYqKAzx5Ua00ypVyo6YrVyz2slxJlbEAFEBvZKlSqp33//XT355JOqXLlyHtdFOD3xxBN6vYoVK6qvv/5abw85c+ZUN910kxZk1apV0/PI6I7gEgRBCAYqRIwZM0bXOs2RI4cqVapUpA9JSNT6gcNL/GexMqVuQrBakXpB8lrFqbj69ttv9UQPkBqB/o744wXH+vZ9GPLnz6/effdd1//pbQqCIAQCIQa8O8aNG6dOnz6ta52Sbb1q1aqRPjQhEYPX7fUDcQU+vkOp/s5ZrSSvVZyJq48++kh/EjtF/a1AYP3GjRvrm8Tsx9CkSRNt2WLZihUrQj1MQRASiEOHDqkPP/xQF14G3jP9+vXTKV8EIaLB69QPvGOBUtnzhCSsDpw4m8pqxQhBIY7E1apVq7RaNm68QDG9SPbjDmkZYP/+/SEepSAIiRa8znuDUANqml5zzTU6gF0QMpxzJ1MHr4dcmNlS3UcvVvWem+2aJ1ar6CPk0YK7d+/Wn8EGnRO0bt+PHdyDwGhCQRAEX42OaWAYqdyzZ0890Obiiy+O9KEJgmMpF4izWr71UKqEoWK1ikNxxYuL9ArG/B4opG8w+3Hn1KlT+lMyJguCkB4UWmZQDRaqsmXL6nmEFQhCVBGisHKPs1r2RGtVIHc2sVrFo1uQGlxccFIvfPXVVwFty/rktuLGqFmzZprlpG0wvVBBEARPrF69Wg+A2bVrlw5gN3n2BCHicC+ePenY7txHB4qwimNxdcMNN7j+vvXWW9WECRP82o5e5m233eb6P3ERdnAzEsjOjUMW5UDgGCjLg1uREjoEzr/00kuOuBenT5+uj4mpdevWIe9PEITg4Hkmx97EiRN1eAFpXiQpqBB16RfsOa1C2p2MDkwoccUInDp16rjceIitZs2a6bwyK1eu1OZ65vNJ0Do9zObNm+t4CKrQc3Ncdtllej92pk6dqsvhAPvzl/vvv1/vm5phDRo0UG3btlXbtm1Tjz76qGrZsqXL1RjsCKTbb79dbmhBiDAEq7///vs6J56pFEG+PJIYC0LUZGG3p18gp1XWXEHv0l5DUEYHJkDMVebMmdV3332nS9Tg4oNFixbpyR9INjp58mS9H3frk8nU3rVrV7/2Ra6skSNH6nI78+bNSzXaEGG1cOFCneD0lVdeUcFw77336izz1D585513gtqHIAihQUeNThqWKyzT3bp1U+XLl4/0YQlCaouVXViRfiHEUYJ2xGqVIBnaSc5HYDom+UAKNffu3VsHwlN/0FM8FjFXTEZk+eKFF17Qn4899phLWJmYrbffflv//b///U+X2QmUSZMmqc8//1w9+OCD2iImCEJkuOSSS1TlypV1x4yOjggrIXriq054tlg5IKykhmBskclyOPqTUhMk76PmICVuTKoFyJo1q7r00kt1PFT//v2Dzo3lCUpbGJG2adMmj+V3yB5PQegvvvgiTYxXemD5qlGjho7hwtWJ8MON2apVKzV79n+5Rvzl6NGjenQkIo8ai4IgpA91SnH5kbcKsFqRt8rd4i0IUWOtctBiRTN97aiFLrfg2mfaqFzZQnY8CUHgb/vt+NUhKSjB4wYOgNgpXHXhzDdjsrjTq/VW17BevXpaXLFuIOLqrrvu0gKLwFlqkwmCkDGYCg0zZszQqRWIp8QdQkdNEKIqUai7sHLIYuUp3kpqCEY/YZe+CKqMSOJn0jakV9vQFGw16/oDViqKS9933326JI8gCBkDI4anTZumUy2YWoFYrLJlyxbpQxME72CtypbrQvC6Q/47u39J4q1ig7ixKx47dkx/EuDqDaxnxqznD2SNv+eee3QqCBPPFWwjYc9g7+/3C0KiwrNHp4bgdRoSBqTQuZFGRYhK7OoHYZXNezsUKCkplurw5kLX/+URSHBxhdj5559/dPoCepwMlY41BgwYoI+fnFy5cgU/hHb48OFq2LBhjh6bIMSrG3D58uU6GSj1AYlpuO6669K1SAtCRElJUWrMlWF7HhBWm/ef0P8Xl2CCiisE1ejRo/Wouj/++MOVKZneJgLLPUDVpEQgy/vNN98c0neb/DYnTly4CT1h8mb5E0T+8ccf6wSFxFsRgB8Kjz/+uB5laLdcGRelIAj/wQCYBQsWaGHFiMDOnTuH1LERhLBCG/fulUod/Pu/wswh5LJKL9aqXMHcauq9TcV6m2jiirxSpGKgBAX4GoRYuHBhNWfOHD36Ll++fOr6668PKZbC1BMjYN0bZplZ11fqBfj111/TiCtTZJoetllGbFbRokU97it79ux6EgQhfXhOunfvrp/Vxo0ltkSIgUD23RdiAtUlFZQaMN9Rv529GUVYZc4sz0NCiSuSc5IJnV6nqUxPmoXDhw+7xJYn7rjjDp2nhvV++OEHde211wZ9DCZLPDEaBKx7GjG4bNky/WnPgeULs40nOG5EJZw+fTqIoxaExIb3BR0YOlZUagCsumLZFWKOO+aTVdux3bmXu5F+RmwR8p2AqKDkDQHb3Ax9+/bVsVZr1qzRmZPTg1gKk6cmmHxRdshxVb9+ff03eaw8CUB6w/SM27dv71e2d2/JT8eOHavXIc+VmeePNUwQhNTvDioxkGaBUYHENwpCzOKw+nEv0iyxVgkmrj744AO1c+dOba26++67tfAoVqyYX9sWKFBAVapUSf9taoSFwuDBg/XniBEjUu0PaxbHBgMHDkyVGgL3H7m5EEqCIGQMJP2l/ui6det0B4si6IQHCIIgRZrjgZDdggR9m4ByRE2gVK9eXa1fv95VlzAUunTpogYNGqRGjRqlGjVqpAUTqRmI7cKFx1DuZ599NtU2JDnl+8WtJwgZ02hQKgtLdUpKiq56QIxV8eLFI31oghA1uFutpEhzAoorEvyhqEm1YPJIBQIZ1QHx4wQUbkZEvfXWW7p4NEkHyVNFvcEHHnhAEhAKQgSF1fjx43WJLNOx6tixo1Q9EAQbYrWKD0IWV7jcTPHmYDA3Db1Yp6BEBpM/3HLLLXoKhGC2EYREh2edUcIbNmxQbdq00eWopNEQhPRL3YjVKkHFFW43rE6nTp0KanuT1oD4K0EQ4q8XzrvB5Kpq3ry5qlmzpipUqFCkD00Qoh6xWiVwQDvB67xA165dG3T8BTePt2LLgiDEJiT0ZeTuZ5995koiTPC6CCtB8N4mEm9lEF2VwJarZs2aaWHF6LwtW7YElJKAsjL79+/X4irULOiCIEQPW7du1c83VRuSkpL0iGIpYSPEHT6SZQdTQ9C4BIUEt1z16NHDpbjvvfdev7fjZcvIPkBc9erVK9RDEQQhwhA7OX/+fF0+CmFVsGBBddttt4mwEuJTWI1t65iwavXavFTCql6Z/JLbKpHFFdXqiaNAXE2fPl2LLRPk7o2pU6fqVAnEWyGsGIrNyCFBEGIXandSV3Tu3Ln6fVC7dm11++23qyJFikT60ATBeWF1Yv9/pW9CqCnoXpyZGoJrhrWReKsYJ5PlqwigH5CRvUGDBmrPnj36/2RBJ8cU81etWqVvEKxUiCnSIzAf+Ory5cvrEjOJlECQws0kMiXHlj9FpAUhFqC+JjnjsmbNqqsgmHI2ghBX0GR+2Eap7b/8N+/xHUplDzwVEZw4c17VGDrLJazmPNhcagjGQfvtSG1BSs+QqJNyNuSwISEnViwwypvEngaj52rUqKG+++67hBJWghCvkF6BkYEdOnSQoHUhfjl7IrWwKtVIqWy5HclpJcWZ4wfHqkxSqBkL1LBhw3QuG291+ZgQU08//bQeKSijBAUhNiGmasWKFa7/k229X79+IqyE2AcDACLKfTpzXKkxV/633sMbleo/M+hhfZKJPX5xxHJlIJfNk08+qR5//HEttBYvXqwD1zGfkQ+L2IuGDRvqDOqSKV0QYpe///5bTZw4UZ08eVKXvqpYsWKkD0kQwuf28wRxVrkLBi2szOhAg8RYxRdJYdlpUpIOWGcSBCG+RgMSsL5w4YVGgQ4TFitBiBvOnfRPWA2YH7Swcg9iF6tV/BEWcSUIQnwGcpK7atu2bfr/lK8hzorOlCDEJbj9snkYBcjIwBCsTHZ3IEHsxFqJ1Sq+kLeiIAg+oR7gpEmTdMA6o4EpuMyAFEGIaxBWQQare0OC2BMDEVeCIPiE2CqEFeWuyEt3ySWXRPqQBCEmkSD2xMBvcfXXX3+F90iUUpUrVw77dwiC4H8P27gqSAhKXUBGBYsbUBCcsVpJEHv84vdbsmrVqmG9Cdi3Ke4qCEJkIV8dget9+vTRI32hVq1akT4sQYhpYXXgxFmxWiUIAXdBHUjoLghClJKcnKx++OEH9csvF0ZL/fzzz+qaa66J9GEJQkxDu9l99GK1fOsh1zyxWsU3SZEUVubGEsEmCJHn0KFD6uuvv9a56aBx48a6jJUgJFby0JNhibOyCyuKMovVKr5JCiS/jVPgbhgyZIjO0C7KXRAiz9q1a3UpqjNnzqicOXOqzp07qypVqkT6sAQh+pKHhpgsdNkTrVWB3Nmk7YtzMjQyFVcDogpxBdxcWK3I8Hz//fdn5KEIgvAvK1euVJMnT9Z/lypVStcIpTCpICSMqCJxKBYr95qB5LMKaddpk4WKsEoMMkRcrVq1SpfFmTZtWio3ID3ku+++Wz322GOqQIECGXEogiC4wQjABQsW6M8WLVqoLFnEXSEkuLWK5KEhlLYxnDonyUITlbCKq/Xr16unnnpKZ3U2RZsha9as6vbbb9dWLPLmCIKQsWzdulWVLl1av+hJCnrHHXdIvU8hsaA9OrE/rbDCYuWAsDJfYZBkoYlFWMTVli1b1NNPP60+//xzHatlRBU94ptvvlkNHTpUlSlTJhxfLQhCOpw7d07NnDlT/fbbb6pdu3aqQYMGer4IK0ElusXKlLoJsbTNhd1bOojdHmslBqvEwlFxtWvXLvXss8+qDz/8UL/Ejaiid9yzZ081bNgwSRQqCBFi//79asKECWrv3r36/2RcF4SE5OyJtPFVDlmrTAC7cQeaWKucWcXdnkgkOfXSHj58uBo9erQ6ffp0qtQKnTp10oJLEhAKQuQg7pGYRzo9JAXt1q2bKl++fKQPSxAyHtqnsW0dj68ywqrVa/NcAexGWEmsVeIRkrg6cuSIevnll9WoUaPUiRMnUomq1q1bq+eee87ldhAEIeM5e/asmjFjhh4RCOXKldPCKk+ePJE+NEGIDIwM3L36wt9Fa4VNWJkAdvJZibBKPJKCLeL6xhtvqFdeeUULLLuoatKkiXr++efVlVde6eRxCoIQBLgAsVrxcm/evLlq1qyZrhEoCIJSqt9MhwLXU6dcQFjNebC5BLAnMEmB9oLfeustNWLECO0KtIuqunXravdf27Y2c6sgCBGlZMmSOnC9UKFCqmzZspE+HEGILhyyKLmnXBBhJfgtroinwiJFaQy7qKpRo4Z65plnVNeuXcN1jIIgBNABYjQgpWsQVFC/fv1IH5YgxHV5G0m5IAQtrkj2aTKq81mxYkWdbqFXr17+7kIQhDCyZ88ePRrwwIEDuhNE7iqJ9RCE8JW3kZQLgmMxV+ZlTZHXhx56SE9OwH537NjhyL4EIZHgBb98+XJtsUpOTtblpNq3by/CShDcA9kdLG/Dc9d99OJUBZkl5YIQ8mhBesdgdxEGg90aJghCYFBoecqUKWrNmjX6/5UqVVJdunRRuXKFVhNNEOKaENIv0F4RY4XFyl1YScoFIShxFaqQyqh9CkIiwEjdTz75RB08eFCPAGzVqpWOtZKXuyD4gEzsQTwnnhKEwrInWktBZiE4cTV37lx/VxUEIQPA/Ue+KlyB3bt31yMDBUHwQogdeZNuwV1Y1SuTX4SVELy4IkeOIAiRhQoISUlJesJa1aNHD12zM2fOnJE+NEGInazsDqRbuOACVDrGSoSV4I5kExSEGIEBH2PGjFE//PCDax6WKxFWguBDWJ3YnzorexCB7O7pFnJnT1K5siWJsBLCX7hZEATnwR2xZMkSNXv2bJWSkqI2bNigWrZsqbJnzx7pQxOE2Eu/EGBWdkm3IASDiCtBiGJOnTqlJk+erNavX6//X716ddWxY0cRVoIQbPqFbLn93lzSLQjBIuJKEKKU7du3q6+//lodPXpUx1W1adNG1atXT9wQgpAB6RcQVgdOnJV0C0JQiLgShCgtY/PVV1/pIumXXHKJDlwvWrRopA9LEBIi/YIni5WkWxACQcSVIEQh2bJlU9dee61at26d6tChg7gBBSGD0i94slhJugUhUERcCUKUsHXrVp2zqnz58q74KiZBEMKffsEErvcYvThVLiuxWAnBIOJKECIML/UFCxaon376SadVuPPOO3WCUEEQQuDsCb/TL3jLvC4WKyFYRFwJQgQ5fvy4mjRpktq0aZOrNqC4AAXBYatVOukXPGVeJ3B9wp2NVa5skiBUCA4RV4IQITZv3qwmTpyoBVbWrFlV+/bt1WWXXRbpwxKE+EjBYLdapZN+AVege+Z1EVVCqIi4EoQMhp7yvHnz9ASFChXSowH5FATBYTxYrXgGKWeDgcueHNRkXheEUJG7SBAyGHrEhw8f1n/XqVNHtWvXTluuBEEIwyhBN2HlLb4KVyAWK0FwAhFXgpBBULqGYsuAC7BKlSqqWrVqkT4sQUiIUYL2Mjab959ItUySgwoxJa4o3XHo0CF1/vx5Vbp06XB+lSBEtaiaO3eu2rNnj+rVq5d+gZPHSoSVIIQ/3spKyqlOnjmfJsWCia9CT1HORoSVELXiip4B5To+//xztXDhQi2sgJsWgWVn//79avz48a4RUldffbWThyIIUQGla7755hu1bds2/f+///5bVaxYMdKHJQjxZalCUBnO/ve31W+G6j5mSaqEoHZLVebMIqiEKBdXFJa9/vrr1erVq11CKz0KFCig3njjDd3YUNaDOmrGZSII8cCGDRt0mgUsuFiqKLgswkoQHIR25sM2qYsz2zh1LiVNbUBJsSBkBI6oGUp0NG7cWAsrRBVT7ty59eQNbuy77rpLr7t7926dQNEpJkyYoK666iqVP39+fQy1a9dWL730kjp37lxA+1mxYoUaPny4atWqlSpSpIgOOmafzZo1U2+99VbA+xMSA7Ks//DDD+qLL77QwqpYsWLqjjvuUDVr1oz0oQlCfAmrE/u9CitVqpGyknKlyrQ+bdCF0YAirIRwk8nyZWLyoyGh0cByBS1btlTPP/+8atiwobr33nu1COFGZj13duzYoUqVKqWXP/LII2rEiBEqVO6//341cuRIlZSUpI8lT5486scff9Sjs5o2baq+//57nQXbF7gxzQgu9lG/fn0tsP755x+1ePFi/XsaNGigZs2apfLlyxewq+jiiy9WR44cUXnz5g36twrRCbmrjAWXewSXN/ejIAhhtFg9vFEXZ3alWUjKpTr872dX8PraZ9qoXNnkORRCw9/2O+Q7jfgqhBUCqWvXrjqOyl/3XokSJVS5cuXUli1b1LJly0I9FPXtt99qYYUYIofQ5Zdf7orvQmgRB/bkk0+qV155xa/91a1bVz366KOqU6dOqbJm03C2adNGLV26VD344IPqww8/DPnYhfihUaNGOuM6hZclaF0QHIynssdV2YVVqUZK5S6oUv7NW+UpzQJB64IQM5YrBNXkyZO1NQiRZE+E6MtyBZ07d1ZTpkzRFiwK14YCVoJff/1VPffcc2rIkCGpliGscOchkhi1hfIMhc8++0zdfPPN+nejYAPJUySWq/iCexuLZpkyZVzzcBlL7ipBCF88VSqLVe6Ciobs2lGehZUErwsxZ7lavny5Fk+43ILJMF2wYEH9eeDAgZCOAxcjwgp69+6dZjnHh4AjcH769Ol6SHwokPwRiKnBMkZcjZB4MCKWEbII9ltvvdV1H4iwEoQQwWLlS1j9a7EinwLpFtzL2EiaBSFShCyu9u3bpz/Lli0b1PamEXJP1RAoBJ/DJZdcol2NnqhXr54WV6wbqrhiJBgwCozvFBKPtWvXqu+++06dOXNG5ciRQ5086cF9IQhCcK5AW0oFE0+Vhqy5tMUKYSVlbIRoIuS7Dzfb2bNngx45Z8QZo/BCLYIL6SUrxXJlXzdY8KQy+hA6dOiQKh5LiH/oCDAwwlhKua+uu+66kF3NgpDweHMFIqw8FF/2VMpGytgIcSGuGEF37NgxlyUnUAgKx2RrhE+wcAyQXvoHAt2NzzQUhg0bpkcMsj9/Rjhi2WAyhPr9QuQ4ePCgTvVB+hBo0qSJatGihcqSRV7mghCW1Aq4/rLm8iisWr02L1UpGyljI8SNuCK/FcKKXjxxJ4gtfyEXELFSPAhXXnmligU++eQT9cwzz+gRkYwSJLu8L8iVhSATYh9yuiGscuXKpbp06eLX9RcEIfjUClpYuYklvAf2GoEmxkqSgwpxk0SUBgZwCz7++OMBWZoGDRrk+n+PHj1COo6LLrpIf544kbogp53jx4/rz2BH6GGx6N+/v/77vffe8/uYOS+MLDATcV9CbHLFFVdoaxVJQUVYCUKYgtdNoDquQA9iiQLM9uD1OQ82l+SgQvyJKzKg05P4+OOPdd4nYrDSgzxRWKpMfiwyoJN0NBRMQH16wsUsCyb4nsSQjEKkCO+YMWNcIssfiMlC0NknITZgJCijAU1MIfdr69at5RoKQrjAYtV/pkdRRTtzwkPwuqRZEKINR4ZTIKoQS1ijSOI5btw41a1bN7Vq1SrXOszHnfLzzz+rRYsWuWoPkorhgw8+CPkYTGoEUjoQsO5pxKBJVGqSiwaSnPSGG27Q+Yzeeecddfvtt4d8vEL0w/07bdo0LaywjJI4VhAEh6EtsI8MzObZDYi1qsfoxRK8LsQEIScRNcyfP1/17NlT7d2716dp1nwlOYFIQEqKBCcIRxJREpwyEowRYggr3EGhIklEoxvEFLnQVq5c6bJ00lkwrmdBEBxKt8Dn2LZK7b5QLkozeGeqkYGeRgSCJAcVIoG/7bcjhZsByxU9/X79+uncVaaAs6eJOmu33HKLtiQ5Jaxg8ODB+pMRfL/99ptrPtasu+++W/89cODAVMJq0qRJqmrVqto16Q4NbPfu3bWwGj16tCPCSohuSA1CPB3Cik4CBcDJxC/CShAcDl5/obhSw0ukFlZuIwPNiEB3a9WaYW10EWYRVkLcW67c41Rmz56t0xXs3LlTKzxSJDCSkNgq3CvFixdX4eC+++5To0aN0gIPwcT3zpkzRxduJhCZEYr2ws0fffSRFoSULqF8jwELHDmzSKFQsmRJj+LLQK1Ck2neH8RyFZ0w6pXamIhp0mxgsQw2Oa4gCF5qA+ICfKVi6nlFaynVb2aqAHaaJns5GxkRKCRU+RtPIDSIUWLKaIjtQkRR05DYLlw8FSpUUI899ph64IEHdEZ1fyDbtslNRd044sq88fTTTwckroToBPGPKEdoUzMzvZxpgiA4UBvQS7oFhNWBE2fTjAgUS5WQ0JYrIX3EchU9MAjD7vLDhUw5I+kZC0KInD1xwfXnDVyAHkYF0iR1H71YLd96yDUPN6CUsxFUoluuBCHa4QVO0fFZs2Zp9x9xd1CgQIFIH5ogxB+eagN6SQ6KxcourOqVyS8jAoWYQ8SVkHDg7mUU6Jo1a1wFmI24EgTBoRgr9/QKHmoDXtjEUqfOJetN3VMtLHuitSqQO5tYkoXEE1eUg3GKPn36OLYvQfDErl27dKb9Q4cO6RJGDFSghJMgCBkQY+WGtzQLxmIlwkpIWHFFSgUnbn72IeJKCBf0jsmB9v333+tksPjMcQeGWjBcEAQvJWyCKLxsUi1MuLOxjAoUYhpH3IKBxsTzwEgcvZCRUPpoxowZ+u8qVaqozp07p0rJIQiCg1nW7TFWHkYCkm3dU+FlVsuZVUSVEPuELK769u3r13rU5CO6nrqClKeBHDly6OLHuGcEIZyQs4wca/ny5dOf8vIWhDC6A73EWHlyA0qaBSEeCVlcjR07NuBtyMxOsk+SjFJvkBgYSUkghMMNWK1aNVeqhbZt20b6sAQh/hKDYrGyCysPbkBP1iqQEjZCvBKxPFfEvVx77bU6Y3rHjh11ceREQfJchZdTp07pmpXr16/XGdYpXyPWUUHIgKB13IG5C7rcgMnJ1J211NMLFqutJ/9LryDZ1oVYJcNrCwZKlixZ1Pvvv68zYjMsfuLEiZE6FCHOYquoA4mw4h7DciUvb0FwCBKDehNWWKxswopXOtWjWrVJTiWsSuTKq92AJAWVZ1OIVyKa54qafZSqmTt3rnYvduvWLZKHI8QwGGApd0QdSf4myzpFt4sVKxbpQxOE+LFajW3rPTGoLXAdYdW9+4VNMmX9b5V//tdabTuZTX1bM5OS170Qz0TcV0LdP1i1alWkD0WIYTfgF198oYuFI6xq1qypBgwYIMJKEJyEOKvdq/8rtIyViqB1M/0rrM6ft9R9D55XKum8ypT1vCp2y0LXLlLOkmk9k7r//gsuQ0GIVyKeof306dP6c+/evZE+FCFGwf13+PBhlZSUpIPWL7/8cnE3CILTAez2VAv9UtcEtGdZb/fKYpXlhqOqtNtuzu7Jq6xzF8rYbN+u1IIFSl11VUb9CEFIIHFFeob58+frvwkQEwR/MeMwEFHZsmXTKT2YV6RIkUgfmiDEfwD7v7kKvZWtUR6E1a6PmmqrlWHXrnAeuCAksLh64okn1LZt23QDibVBEPzh+PHjatKkSdqlfMUVV+h5hQsXjvRhCUJ81gd0E1bJJRuq0ynZVI9RnsvW6M325FW7P/+vrNQFi1Vqa7J47YV4JmRxhTjyl/Pnz6sDBw6olStXqo8//ljnuQo0GamQ2JCAlpGlCKwdO3aoOnXqSKZ1QciAVAsnBv2pbvrkD7Vi4xmlnv4+zXJTtiYlRanqlbModR7rVtqvwJtYsqRSzZqF60cIQhyIK/IIhRrf0r59e3XDDTeEeihCHGNcyPPmzdP/L1SokB4NKMJKEMJrqYI1Waqra19a/q/1KVMaQeVetmbkyAujBfmvXWCZpuKNN4iVDPcPE4Q4cAsGk4uUxI533XWXevXVV506DCEOOXbsmLZWbdmyRf//sssu04KcHGmCIITHUnXyvj+VlZRLdR+9WK07cN4lqrwJKjukWfj6a6Xuu0+pf/75bz4WK4SVpGEQ4p0kJ2q2+Wu5ojEkoynWLuq7XX/99Xp7QfDGuXPndLJZsuJy/5DVv3bt2pE+LEGInxGAHoTVrymVVY8XjaUKMgWcVR0B1bnzhVGBBK8TY4UrUCxWQiIQsrgy1gRBCAcIqsaNG6sVK1boEYEFCxaM9CEJQlxaq6yHN6gDZ5NUs5fmqlMqexr3XzA1ABFSkm5BSEQinudKENzBSkX+MzMCECtnvXr1dB4rQRCcL2HDCMCO7/+p1u4+ppTKoecte6K1tlKBN/efIAieCbm1+v33311/16hRQyd0FIRg2bBhg06zQKA6WdazZ8+uX+oirATB+RI2/Qp9qZZsP6VObcRShbC6QL0y+VWB3NlEUAlCkITcYhFczANYpkwZtWnTplB3JyQoycnJ6scff9T1AU1SWaxXiCtBEBzi9DFXCZvk3OXU3O0pLkuVPVjd37gqQRDCJK6IiSF/VaNGjULdlZCgHDlyRH399dfqn3+HFdWvX19dc801Yq0SBCeZOFFZDw1Smf5NKdhh461K5c+UygUo7j9BiJLCzUWLFtWfefLkceJ4hARj/fr1avTo0VpYYaUiaJ00CyKsBME5rG8mqhO9blLdWtzvmrclf3H9WX3P36rArGkqV7YkEVaC4BAht2BVq1ZV27dvV1u3bnXmiISEgdxov/76q3b/FS9eXCcFzZ8/f6QPSxDiAlftv3Pn1U3fb1d/PvCpyqXOpFoHYTX14wdUpjkllOrSWfIkCIJDZLKCyf5p44MPPlC33367DkCmFE6BAgWcOra4Hg1HTBHuMPJ+JTKUsVm6dKlq3ry5DIYQBAfglX7ybPK/xZSPqK+zDVP1Mv+VZr2TL59ROU+e+S/hwty5kjdBEBxqv0N2C954442qevXq2vpwzz33hLo7Ic5Zt26d+v77/+qS4U5u2bKlCCtBCAb6xmdPKOvMcXXy+BF14tgR1W3kbFVv6GS1eddeVUAd9Sis1LbzKpddWAGZPgVBiA63YI4cOXQwctu2bdWECRO0qnvjjTdU5cqVnTlCIS5g0AOiCjcglCtXTlWqVCnShyUIGVe3z/Fdpyjrw3Yq857VWiTl+nf+JJVqAOB/6798TGU696+j4pyHHZJCXRCEjBVXzzzzjP5s0KCBFlLu8zt16qQDk2fNmqWqVaumLr30UlW3bl1dYNff4rpPPfVU4L9AiHoOHjyohffu3bv1/6+44gpVvnz5SB+WIESsbp8TpC6h7IPdWVSmUxyTpx1lulD0j9o0giBkbMwVRZYZSYLrb9SoUWnm22GXwYw6IddRIpBIMVd//PGHmjJlijp79qwW2V27dhWLlZAYlirq9r1SMexfuSaljOpxdqiqUjSv+uzWBp4LKk+ZqVSPHv8do8GsQ5VlqaYsCI61346Md/ekzwKNk5chwPHH7Nmz1c8//6z/pkD3ddddF/diUkhg0rNUPbxRqWy5gh/xZyl10wdL1Z+7j6ZaXhVBdedValnmTOnnqLruugsC6r77lPo3n5wGi9Ubb4iwEgSHCVlcDR061JkjEeIOBBUZ15s2baquuuoqbeUUhLiNp8JS5UlYlWqkVO6C/1mJAhBUF0b82QVVjuAzqSOgOndWasGCC8HrxFjhCpTBJILgOCKuBMdNpsY6xaCGgQMHqksuuSTShyUIGRtPZbdUZc3ll7BKnUIhtYXKsfI0CClJtyAIYUfSYAuOcO7cOTV9+nT1559/qjvuuEPly5dPzxdhJcQlWKy8CSs/LFXGOvXf/z1ZqVILKo+xVIIgRCUiroSQ2bdvnx4NyCds2bJFF/QWhITAPZ7Kh6UKYdV99GK1fOshr+uIoBKE2EbElRA0NBIrV67UFivyWJEQtFu3bjqHlSDENfYBOwirbLn93hTXnzdhFbLbTxCEqEDElRAUpFaYNm2a+v333/X/yVtFmgUp4C3EfTJP9jXmyiA2uxBT1eHNha55y55orYWUQaxUgpCg4mrSpEk6d5HT8EKZM2eO4/sVwgOjABFWXLcWLVroEYHSKAgJl8yzaK0LbkAfpKRYWlTZY6qwUhXInU2eG0GIQwIWVzt37tSTkwSbdFSIHIgp7oMmTZqoMmXKRPpwhHgmVKuTtxQJTgirAfPTxFd5ClZHWG3efyKVsJp6r3RIBCFeCVhcBZocVIgPzpw5o5YuXarFFPmqkpKSVO/evSN9WEK847TVKchknu5oAaWyK3U+BbuUX6P+oFzB3FpUSUyVIMQ3AYsragu2a9cuPEcjRCW7du3SxbmpEUiJIhKCCkKGcPaEc8LKR4oEd4uTN3wJKG8Ya1XmzCKqBCHeCUpcSeLQxIDG5tdff1Xff/+9FlUkB61QoUKkD0tIFFAxY9s6Z3WypUgIJM9UMNhTKRgkWF0QEgcZLSh45PTp07rg8tq1a/X/q1Spojp37qyLLwtChsRNESu1e/V/8U1+lJBJ1/r073ynhJQnAWUQISUIiY2IK8GjG3D8+PHq8OHDOr6qdevWqlGjRtJYCJGLm+o302diTl+lY0IVTO6IgBIEwRsiroQ0IKiOHz+uS9h0795dlShRItKHJMRrqRg/SC7ZUJ0hePzsecdjoMR1JwhCOBBxJWhSUlK0qIIiRYqoG264QYuqHDlyRPrQhFhPvIl7z4+4KePS42tv+mCp+nP3BbF0amN2pYZ+77j1SYSUIAjhQsSVoLZv366Tw1K6pmTJknqeBK4nOGFKvHlSZVMKK5Rf1qfAhL2UjhEEIVoQcZXAYCkg0/qPP/6oLVd89unTJ9KHJUSDhSoMiTd/Tamsejy3gHoMjsc/gViiBEGISXElCUTjh5MnT6pvv/1WbdiwQf+/Ro0aqmPHjpE+LCEaLVQPb1RW1pxpRuG5u+98oZNu+hBWdkElYkkQhLgXV5s3b9af5DoSYputW7eqb775Rh07dkxlyZJFtW3bVtWtW1caskS0VPmwUFmlGqmTSflUj9FL0gkYz+GI5QlEUAmCkFDiKpbqx02YMEG99dZbatWqVers2bOqYsWK6sYbb1QPPPCAypo1a8D7W758uRoxYoSaP3++OnLkiCpWrJjq0KGDevLJJ1XhwoVVLLFjxw718ccfaytkgQIF9GjAokWLRvqwhCiwVJ28789URYh1HNQHq9Tap9MPJvcmokQoCYKQqGSy4szXd//996uRI0fq2nctW7ZUefLk0bFE5Gyi2DDZxgNJhEnZl169eqnz58+r+vXrq3Llyqlly5apTZs26VF1Cxcu1OItEI4ePaouvvhiLdQy2hLI5R43bpzKnj27uvbaa1W2bAQYC9GMz7IsgYzqO3dS5RpZ1XM81FkqL3gXQyKiBEFIdI762X7Hlbgihqhr165aUM2bN09dfvnlev7+/fu10Fq9erV66KGH1CuvvOLX/nbu3KkqVaqk45PGjBmjBgwYoOdTCuaWW25Rn332mRZcv/zyS0CNS0aLq23btmkhiKAChCLuwLhsEJ1KHxAhPJVlSS+uiSs4IdswVSPz1oC/q+7pd9TJf0fupRcPJaPwBEEQElhcUfeQWnjPPfecGjJkSKplWJiaNWumBcaePXv0yfHF//3f/6mXX35ZZyj/4YcfUi0jySZpCzjBM2fOVG3atIk6ccUIQFyZTDVr1tTCM64bxzClD4hHsFQNveRVNeGuKyQflCAIgsPtd9ykYiCWCGEFvXv3TrMcl2CpUqV0Tqfp06drV58vyP3kbX9Yxzp16qQ+/fRTNXHixIDEVUZAsDrHbwYiYKlCbPEZt5w9kbDCKqVILXX65ql+pzmokTWXmpYtSUSTIAhCGIgbcbVixQr9eckll+i4KE/Uq1dPiyvW9SWuECcbN250bedtf4gr893Rwt9//62F1YkTJ3QAP7FVtWvXjv7YodB2rnJ82FZl9hKcHcJuA0o34ARVi+ZVn93aIKCyLJmz5lK5RCgJgiBEBXEjroyFpnTp0l7XwXJlXzc9tmzZ4vrb2z4D2V+4sVJS1InjR9TPi5aoJb8s1fMKFiyoOnVorwoUuESdPH4ksscXZpGSS51Ry3Os1n+vSSmjrn1xud9WHP8IrgyQpCMQBEFIPOJGXGFpgty5c3tdB1ee8Zn6u7/09unv/s6cOaMngz/fHyinTh5TmV6rplarPkplyq0ut35Xbff9pLKOHayiBe1kzYBShb5GvWWUSAIRSoIgCIlH3IiraGb48OFq2LBhYf+e3OqUuk5NVyesXKqmWq8SkeSSDdWymzupgFWQD0QkCYIgCAknri666CL9SZyRNxjhB/6M0DP7M/v0NLrQ3/09/vjj6sEHH0xluTIuRafImesidfLhbarIv/+P1mQE4RYpWST2SBAEQYgwcSOuypYtqz8JWPeGWWbW9TcjPXmiatWqFfT+SP9gckyFi0yZM6tceXynlxAEQRAEIbyYwVUxT506dfTngQMHvAaYk1kdTHLR9MAaZTKvm+1C2Z8gCIIgCIlB3IgrEnqSLR2++OKLNMtJIoqlCQtS+/bt/donSTe97Q+X4JQpU/Tf3bp1C/HoBUEQBEGIF+JGXMHgwRdGxlFk+bfffnPNx5p19913678HDhyYKn6KfFBVq1ZVrVq18linMFeuXGr27Nnqvffec82n/A37o14hgu6aa64J8y8TBEEQBCFWiKvyN3DfffepUaNG6eSZCCbSKMyZM0cLoSZNmugyNvbCzR999JHq16+fjrGy57YyTJgwQSccRVA1bNhQx1eRCT5WCzcLgiAIghAc/rbfcWW5gpEjR6px48apxo0bq0WLFulSN7gMsWb9+OOPqYSVP/To0UMXZsb1h6DC0oXQuueee9SqVasCFlaCIAiCIMQ3cWe5igXEciUIgiAIsUfCWq4EQRAEQRAiiYgrQRAEQRAEBxFxJQiCIAiC4CAirgRBEARBEBxExJUgCIIgCIKDiLgSBEEQBEFwEBFXgiAIgiAIDpLk5M4E/zCpxciXIQiCIAhCbGDabV8pQkVcRYBjx47pz1KlSkX6UARBEARBCKIdt9cpdkcytEeAlJQUtXPnTnXRRRepTJkyOaqoEWzbt2+XzO9hRs51xiDnOWOQ85wxyHmO/fOMZEJYFS9eXGXO7D2ySixXEYALQr3DcMHNJA9uxiDnOmOQ85wxyHnOGOQ8x/Z5Ts9iZZCAdkEQBEEQBAcRcSUIgiAIguAgIq7iiOzZs6uhQ4fqTyG8yLnOGOQ8ZwxynjMGOc+Jc54loF0QBEEQBMFBxHIlCIIgCILgICKuBEEQBEEQHETElSAIgiAIgoOIuIpiJkyYoK666iqVP39+lTt3blW7dm310ksvqXPnzgW1v+XLl6sePXqoIkWKqBw5cqhy5cqpe++9V+3du1clMk6d5xUrVqjhw4erVq1a6XOcNWtWvc9mzZqpt956K+jrFi84fT/bmT59uk7Iy9S6dWuV6ITjXE+ePFl16tRJFS1aVGXLlk0VLlxYXXHFFeqZZ55RiYqT5/nEiRP6/VGvXj2dm4n3B+e6Q4cO6rvvvlOJyPr169Wbb76pbrnlFlWrVi2VlJSkn/HnnnsupP3Onj1btW/fXhUsWFDlzJlTVa1aVQ0ZMkQdP37c0WyjQhRy3333MdDASkpKsq655hqrW7duVr58+fS8pk2bWidPngxofxMmTND7Yvv69etbPXv2tMqXL6//X6RIEWvDhg1WIuLUeT537pzehilPnjxWixYtrBtuuEHvI0uWLHp+gwYNrEOHDlmJiNP3s52DBw9axYsXtzJlyqT316pVKyuRcfpcnzlzxurRo4fePmfOnFbLli2tXr166Xu8cOHCVoECBaxExMnzvH//fqt69equ9wf74x19+eWXu94rgwYNshL1HCu36dlnnw16n6+99preB++LK6+8Ut/bRYsW1fOqVKli7du3z5FjF3EVhUyaNMn1kC1fvtw1n4teq1Ytveyhhx7ye387duywcuXKpbcbM2aMa/758+etm266ySW4UlJSrETCyfOMuKpbt641fvx46/Tp06mW/f7771axYsX0/vr162clGk7fz+7ceOONWsDeddddCS+uwnGu+/Tpo7fr0qVLmoYnOTnZWrx4sZVoOH2eEU5swzvkwIEDqZZNmzbN1TFOtHP93nvvWQ8//LD1+eefW+vWrbNuvvnmkMTVb7/9pkUV74vp06e75p84cUK/N9j3dddd58ixi7iKQhA6XOTnnnsuzbIFCxboZdmzZ7cOHz7s1/4eeeQRvU3r1q3TLDt27Jh18cUX6+UzZ860Egmnz3N6fPrpp66e/9mzZ61EIpzneeLEiXp77vGxY8cmvLhy+lzPnj1bb1OzZs2Eu28z8jxzftmGzpknrr76ar0cq0si07dv35DElbHA3nbbbWmWbdmyxcqcObNejpALFYm5ijJ27Nihfv31V/1379690yxv2rSpLkh55swZHWfiD5MmTfK6vzx58ug4Cpg4caJKFMJxntOjTp06+vPUqVNq//79KlEI53nmPN55552qSpUqCR33E85zTbwL3H///ToGSAjPeSYG1h+IERKC4+zZs2ratGler1uZMmVUkyZNUrWZoSDiKsogKBouueQSHXDuCQIe7eumB9W7N27cmGq7UPYXLzh9nn2xYcMG/UkgMN+ZKITzPN91111aYH3wwQd+N07xjNPnOjk5Wc2ZM0f/feWVV6rdu3erN954Q593xNbHH3/sbABwAt/T7dq1058vvviiOnjwYKplCLS5c+fq4HbTERYC56+//lInT57MsLYwKeQ9CI6yefNm/Vm6dGmv69Arsq+bHlu2bHH97W2fgewvXnD6PKcH7ndGEAEjfxKp9EW4zvNXX32lvv76a3Xfffe5epuJjtPnetOmTS7xtGTJEnX33XenEVOPPPKIvhYtW7ZUiUI47ulHH31ULV26VM2aNctlQcmXL5/uGDPKm//Tibj44osd+hWJx+Z/rwXn9aKLLgp7WyiWqygDSxMwrNcbuPLg6NGjfu8vvX0Gsr94wenznB7Dhg1Tixcv1vsbMWKESiTCcZ6xoNxzzz2qQoUK6oUXXnDoSGMfp8/1gQMHXH/feuutqm7dutodxvesXLlSD2Xft2+f6ty5s8symwiE455mX1OmTFEPP/ywTsmAyBo3bpwWVgUKFNDpRUqUKOHQL0hMjmXgOx9EXAlCGPnkk090PFDmzJnVhx9+qCpVqhTpQ4p5BgwYoA4dOqTef/99lStXrkgfTtxiLztLw06Dj9uEBoh8TuReqlmzprZmJVqnwWl27dqlrVPEuJHDyVgNsWYhaumgEctl7ywL0Y2IqyjDmCvpvXjDmOZJNOfv/tLbZyD7ixecPs/eEgz2799f//3ee+/pBK6JhtPnmTgfevgEspO8UciYdwdJHN3d2VmyZFF33HGHKyljohCOd0ffvn21VfDZZ59VgwcP1rFcWFjq16+vpk6dqhNorlq1Sr3yyisO/YrE46IMeOfbkZirKKNs2bL6c/v27V7XMcvMuumB/96wbds2/ZCGsr94wenz7A4jLxmRkpKSosaMGeMSWYmG0+fZjOKhIXIXV7gLAVeKWUY8EIHAiYDT55p1yIaNBat8+fIe1zHzsbwkCk6fZ0Yf/vDDD/rvXr16pVnOKM3u3bur1atXaxGLFUsIHHMtDh8+rC2AnuKunGwLxXIVZZgh+8Q7eAuqW7Zsmf68/PLLfe4PBV6xYsVU24Wyv3jB6fNs59tvv1U33HCDHm31zjvvqNtvv10lKuE6z2wzb968VBOlMszL08w7ffq0ShScPte4/0hzAd7Sh5j5JlYlEXD6PNPpNXizmJhAdveRhIL/cC+bMIKMaAtFXEUZJUuW1KZg+OKLL9IsX7hwoVbXmOgJKPWHrl27et0fZlDcLNCtWzeVKITjPAPnsmfPnur8+fNaWBm3SaLi9HlGuP6b/DjNNHbsWL0OtR3NvESyxobjnjaubG9uP2NxadCggUoUnD7P9kD1X375xeM6jNYEb6kfBN+QBufaa6/1et22bt2qFi1alKrNDImQ05AKGVZagfpT3korkKmaukjU/Uqv/M27776bqvyNKScg5W9CP8+UqciWLZsur2AvM5ToOH2evSEZ2p0/15RzyZ8/v95u9OjRqZZ9+eWXrnqO3PuJhNPn2WR8r1atmrV58+Y01R3MeebvRKavHxna33zzTX2eadvc4VqZ8jczZsxwzZfyNwmEqTWVNWtWq23btvqCm6KgTZo0SVMU1DQsZcqU8bg/yiqYAsINGza0rr/+einc7OB53rNnjy53wbKSJUvql4C3yanCoIl8P3tCxFV4zvX3339v5ciRQ69To0YNq3v37ladOnVcRXSffPJJKxFx8jyvXr3aKliwoF7Oub7qqqv0eeZ8m/NMHdhE6wAvX75ct1dmMueId6x9/s6dO13bDB06VK/TvHlzn4WbOc8UyDa1X6Vwc4Iwbtw4XbU7b968uiYd9adGjBihq9S7409jtGzZMl25vVChQtrCwrr33HOPtXv3biuRceI809v0VL3d0+TeM00UnL6fvW2T6OIqHOd6/fr1umNQokQJLSYKFChgtW/f3po1a5aVyDh5nnkPP/roo9all15q5c6dWxdr5l3dpk0b/T2JyNy5cwN+p/oSV/DDDz9oQXzJJZfoTnGlSpWsxx9/3Dp69Khjx56Jf0J3LgqCIAiCIAggAe2CIAiCIAgOIuJKEARBEATBQURcCYIgCIIgOIiIK0EQBEEQBAcRcSUIgiAIguAgIq4EQRAEQRAcRMSVIAiCIAiCg4i4EgRBEARBcBARV4IQJj766COVKVMmPd1yyy2RPhwhQXj66add9x1/C4KQ8Yi4EuKGq666ytWoBDL99NNPkT70uGnMmbJkyaL++OMPv7bl3JvtihYtGvZjFeIP+z3kacqaNasqWLCgql27turfv7+aNm2aSklJifRhC3GOiCtBEByFhuupp56K9GHEBWKFCp3z58+rAwcOqN9//12NHTtWdejQQV1++eVqzZo1GX4scj0Th6RIH4AghIP69eurBg0a+LVuiRIlwn48icakSZPUsmXLVL169SJ9KEKCcc8996T6/9mzZ9WOHTvUzz//rI4cOaLnrVq1SrVo0UItXrxYVahQIUJHKsQzIq6EuKR9+/bSM4wwTzzxhJo5c2akDyPh4L5P5Hv/f//7n8f5J06cUEOGDFEjR47U/9+3b5+6//771ZQpUzL4CIVEQNyCgiA4Rt26dVVS0oU+26xZs9TChQsjfUiCoMmdO7d64403VNeuXV3zpk6dqnbu3BnR4xLiExFXgiA4RsWKFVONjMRSIAjRBNYqO/Pnz4/YsQjxi4grQbCxd+9eHfTat29fVadOHXXJJZfo0Ub58uVTVatWVf369dMWGaf59ddf1cCBA3Wgbf78+bX1J2fOnKpYsWKqUaNG6q677lLjx4/Xrg1fsM4777yjOnbsqMqUKaNy5cqlLrroIlWpUiU9WurHH39U4eTJJ59U2bJlczVc33//vaP7P3funPr0009Vz549Vfny5fVvwypRrlw51atXLx3vZVmW3/s7dOiQeu6553R8GOc+T548qkqVKuq2227T18VgH4GWHlu3btXnn2OpWbOmuvjii/U9VKBAAVWrVi19LZcsWeLXyNdhw4a55vG3p9Fw7mk+0gua/u2331zLOK7Tp0/7dY5Yj/XNtvbz4g7nnmvAM1S5cmW9XY4cOVSpUqVUly5d1Mcff6yDzCPFZZddlur/vixXkb6esXRuBRuWIMQJzZs3p0XV09ChQwPefuTIkVaWLFlc+0hvatmypbV///509zd27FjX+n379vW4zrlz56wBAwb49Z1MQ4YMSfc7x48fbxUtWtTnfjp06GAdPnzYcgLOtdnv9ddfr+fde++9rnkNGjTwuu3cuXNd6xUpUsTnd7F+hQoVfP6+Ro0aWf/884/P/f3444/6e73tJ3PmzNbTTz+t17XP98bDDz9sZcqUya9recMNN1gnTpzweS/7mtzvLfv18PQcVKtWzbWc+8Ufxo0b59qmSpUqXtdbtWqVddlll/k8ZvaxZs0aywns95A/TdrZs2dTrf/8889H9fWM5LkVgkcC2gXB1oNNTk7Wf2MRqVatmipUqJDuGR4+fFitXr3aNXwb60/r1q11jzV79uxBf+cjjzyi3n333VQjFxnlyPeS0oAh5GvXrlXr16/3ua/XX39dPfTQQy6rTd68eVXjxo1VyZIl9e/i2BnBx3JiTehNM4IKy5bTDB48WH3wwQfq5MmTaunSpWry5Mmqc+fOIe1zwoQJ6sYbb9SWK8Cyh1WvbNmyKnPmzOqvv/7So7/ouXNd+O1YWIoUKeJxf6zDsHyOEbAaMMq0Ro0aeoQZx71hwwZt/SFPkj9s375dn1/2hfWLCQsHlg6u5YoVK9Tff/+t1/3qq6/U0aNH9bVwt4YRF4SVhGMwViJvI2A5B4Fw0003udy1n3/+uerRo4fPbVjPvr0nsFJiLeU3Ab+ZY8Ziyt9btmzRMXhYwbifr7jiCn29eM4yEndLlbf7I5quZ6ycW8FGCMJMEOLKcvXBBx9Yb775ZroWD3qP9erVc33Ps88+G7TlCstXUlKSXo7F7KOPPrJSUlI87mvnzp3WqFGjrPfff9/j8tmzZ2srC/vKli2bNWLECI+96BUrVljVq1d3Hdddd91lhcNyBf/3f//nml+rVi2Pv81fy9Uff/xh5cyZU6+HJQGLwqFDh9Ks9/fff1tNmzZ17bNdu3Ye93fq1CmrUqVKrvXKlStnLV261KPFJleuXFb27Nn9so689NJL+rrv27fP6zrz58+3Klas6NrXp59+6nVdX1aoYLbZsmWLyxrDvXLgwIF098fyrFmzus79pk2b0qyza9cuq3Dhwq7v7dOnj75n3dm9e7fVtWvXVPfF+fPnrYy0XI0ZMybV+txb0Xw9I3luheARcSXEpbiqX7++dc899/ic/HEduYM7zbjeihUr5vUF5ktcTZkyxbX8xhtvtIIlOTk5lVCYOHGiz5e1cYXRaG7fvt0Kh7iiUc6bN69r2Zdffhm0uMINa9Z77bXX0j2e48ePpxKQS5YsSbPOO++841qOeNq4caPX/XE+3V0vobJ582YrR44cPt2m4RBXcOWVV7rWGT16dLr7s58rhKsn+vfv71pn0KBB6e6P58V+Pb/66isro8QV937JkiVd615xxRWWE4Tzekby3ArBI+JKiBsCiWswE5acYMDiY/bx+++/ByWuPv/8c9fy+++/3wqWb7/91rWfLl26+LXN8OHDXdu8+uqrVjjEFRCvZJZVrlw5jRD1R1ytXLnStU6dOnW8WvfsIOTMNsR/uWO3Pg4ePNjn/lq0aOGouAKsasYadOTIkQwVV++++65PwWRo0qRJukJs79692gLGcjodWAV9sXjxYtc+O3bsaIVTXBFjhfhBJJYoUcK1Hsf6559/Wk4RjusZ6XMrBI/EXAmCl1GDxOSsW7dOjyZjBJ59BBqxS4aVK1fqUUOBwggfw8SJE9Xjjz+uChcuHPB+pk+f7vq7d+/efm3TsmVL19/Eajz44IMqHDzwwANq1KhR6uDBgzomitFMjFgM9vcxYsvXaD1Pv8/OsWPH9Kg5XzFEdlhn7ty5ARy1Utu2bdMxNvxuYvZOnTqV6h7avHmz/mQeGcObNWumMgrirO6991515swZHXfHiDhGlrpDLM+iRYv034wAZYSmO7Nnz9YxatCtWzcdo+iLhg0b6hGePFdO50Lz5/5o1aqVeuutt3QMVTRfz2g7t4L/iLgS4pKhQ4cGlaWa4PFHH31UzZgxwxXc7ov9+/cHcYQXAlcRWATN8uImkJpUDwSu8oI06Qx8QeCq4ZtvvlHz5s3zuY0pAwJ8f7ggqJ7zyQTPPPOMFir+/jb334fAQQj4wt7ouf8+asyZwr0cHyk2fMH1COR4H3vsMbVgwQK/U0IEew8FC6lFrr32Wi3qOUYC1hmE4A7zzW9gfVJVpHd9OLekFAkE03lBEGQEBHt/8sknqnjx4lF/PWPt3Ar/IeJKEP6F/FWMaKM3HwhYQoKBUT7ka2LE2vHjx/UL+eWXX9YTPVTyLl155ZW6lA8NgrceuX3007hx4wI+Dl7A4YQGgZGMu3fv1sLovffeS1P/LT3svw/RG+rvo+yJgZGU/lg6WM8fPvzwQ50fK5A8W6HcQ6GAyEVcQXriyr6+r+uDpSQYawnXyCkBYL+3ENG7du1Sf/zxh9q4caOehyWOjs1PP/2kRwVH8/WMtnMr+I8kERWEfxvc66+/3iWscJEMHz5cv8x4wTFcnxf1v3GK2jJmMFaQYGjevLl2IfTp00enFjAwpJrvfuGFF1TTpk21deXbb7/1aYUKhnAnHSTVg73hfv7557VLxV9C/X3uFkiErP3Y/IHEov5YPe+44w5XQ4wlkjp2uJL27NnjciOZiUSQTtxDwYIliiS55thJK2AH1yluccBixfrhuD5O34PUFjTT22+/rZNu4srj+TGWN6yZuNmMyy1ar2e0nVvBf0RcCYJS2ppiXmS1a9fWJnhcAU2aNNFZ0hE+dguHk5YGes/EIiHwKHRMweMWLVqkEls0DuTKee2119Jsb++V0iDaX/j+TMTVhBsaqdKlS+u/sSQQ7+Iv9t9n3FiBTt6Ekslx5Qt/MuNTt840ZG3atNHXYtCgQTofEbF07vEykbBW2cE1a89xZbdSuf+f9bzlc7NfH+7PYK7P/7d39r7QdGEcnhetaEiUgkiQiFCphdAoUGiUCioJWomoCJVCI6GQaDSIRAiFQqJQicQ2orCFxr+wb67zOPsc+8zHWQaz2d+VCHZnZ2fOObtzz/3xu9Eq+0747OKVxsBCEw24qeEGKsvzWQljK8KRcSVEEASXl5fFvzFuyMWJwyfv5zNfpHyJr66uGpFSRAoRznST5Ul6z+fzkSKIhN6yCBfy5eXl4v9ra2veF6O0z88VBC0dyyheXl7KWkO000nKK/uONVQubqjv4OCg6HHhN/9bpqenI/dRCevPQpjdzVva2NgwXqiszmclja34iIwrIUpyG5Iq/wgzUWH13eC5mpycNLkh9kuWMEZpb0M32fonjuuzEDZBURrILyMPy4e0z6+np6fovcBb+fj4mPgaQkFpriHeF+9oEj75YF8Bzyw9Ge3x24pIjHs8jMDzbBdFpaw/C0a+vXkiRBzlvcrCfFba2Iq/yLgSgg/C+8XWJ1REaOEn7yLJi3EvbqV32iTEuwm4vs14fxqaUbsVnIQ5fJLp3fMjLBjlafCFCytNuaPCYWHs7++nuoZ2dnaKbXzicENPPtuXCxd7V77Dnqd7vjwfZxTgbWVubbI44bYsQ/saZCgstJ8KW1NZmM9KG1vxFxlXQrznPVmOj48jtyMvCu2mNCDs54srJ1CqhTUxMRG0t7ebv/E2zM3NeVc3cefuk0+UFlNTU6bHmr3bX19fT3wN/dfogwgkEROiiktEdmG7MAPO1doit8ZqFIXBenBDRF9dQ/QrXFlZCXwNgXJDmOXihvwwXhkvW0VY+nwY9MO04UXWHcUZtgdeEoQf3erNnwJdt/r6+uKaIjyYxfmsxLEVf5BxJUQQGG0pC2GCME8FCa1U92HopFHavLW1FfT29gbb29uRnjCMH5rs2mavtbW1wfDw8IdteIx98Bt2d3dNZZet9AoD4VO0p9DZijMs0gZvAFpXFoRafcfKJqJfXFyY3Jnb29vI7SkAIHeNZN6wcAp6YtYgZYxpwn13d/fPdoeHh8Zz49Oc211DXLxLw7eAkYahSL6Zzxqyhiicn5+nUj1WCkKayH4AF+6ZmZliPhyP+whtUgFK4QcQHsMg5njjctgIC7Pvz8iHpOENdiUb+PyUalNlZT4rbWzFH6RzJcR7PtDm5qa5KCPHwN06MghUDuLKRyfHqrLzGO56H69LErj58TTxRd/W1ma+fEm4JmSAF4pQgCsdQAWjq+xuwTjgAjE7O2tywtCDovKwq6vL5BgRCiO0wT55z9+8o6XqkYu2q3KfBONCgjVyGZwHhhVaRYxZX1+fuVgSDkVZnwtQkleAfLa9vb1gaGjIeC6enp5MFRg5LowZHi+rxg2U9dtE6KgQ2fz8vAkPMbYo0o+MjJhjY3+8BuP84eHBbMv6wQOJzlkcXEit0CxzhyQHxjVrxB4Hx824fAW8I3Y+EKL19VpZEOQ8OjoymmwYKblczpwjnhfOoampyaxpnuOz9JMGfRQLCwvGaMdzyw9haj7zWZvPShxbkVaTLCEy1lvQtw+bSy6XK7S2tsb2IqTPGs2efXqEJfUW3NjY8O6BSH+xlZWVxHO4urr60MQ56ae7u7uQz+cL39VbMIqzs7N/jiWucbPbZ7C/v9/7/FpaWmL7R15cXBSampoiX19TU2P6I9Kfzj7W0NAQub+bm5tCY2Nj7DHR/5Hm36wJ+xhrJQoafNv+cmE/pWvrM/0IX19fC7W1tR/2W1dXZx4vh+fn58Lg4KD3/DDnrIWfatxcytLSUvF19fX1hbe3t8zN52+Orfg88lwJ8U5HR4cRUkSDiZwT7hDxYDQ3N5tqIcJD9Faz4bc07pzJlyLMhYfq/v7eaE4RmiF8RouSzs5O0yePXIuw3m+loI9FOJCk+9PTUxN2I+TIPhHMpOqQu2UU30dHR01Y8jfgzpvea7QUKQe8hnhYCItwjoT8qOqi1xuhO+7iCYfggeI9BgYGYpOx8fhRLYhniv3hwcILgFeA0CP6XHgS3IRn5iUK3g9vBnlcJycnZn9AWKe/v994iNxwkw8k9HPOrEuEZWmVhDezXNXwOPC64EFxFfDx6pXb65I1Sj882rYgI3J9fW28NORxkZhNzhEVo3gueT9CajZh+zdYXFw044o3lNAe8+bmT2VpPittbKud/7CwfvsghBAiy2AA21w3wkOfacMjhKgelNAuhBAJuInBeLKEECIOea6EECIGkucJYVpdIsKuhFaFECIKea6EEFUJuS70zCPvJewek6pLJDnI3bKG1djYmAwrIUQi8lwJIaoSigds6xcSt0lQJlGZggUS2EkcdiUreA4tLKs5JIQQUci4EkIE1W5cJUEFFoKiPhWbQggh40oIUbUgFEqJPZIVKFsjxIisA2rwyFZQij8+Pl52ub0QorqRcSWEEEIIkSJKaBdCCCGESBEZV0IIIYQQKSLjSgghhBAiRWRcCSGEEEKkiIwrIYQQQogUkXElhBBCCJEiMq6EEEIIIVJExpUQQgghRIrIuBJCCCGECNLjf0J5Bm81s+o6AAAAAElFTkSuQmCC", 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "\n", - "\n", "# Function to generate predictions and plot ROC curve\n", "def plot_roc_curve_nr(ax, predictions, targets, sensitive_value):\n", " # Convert PyTorch tensors to numpy arrays\n", @@ -1098,42 +604,40 @@ "\n", " tnr_minus_fnr = tnr - fnr\n", "\n", - " # Find the threshold that maximizes TPR - FPR difference\n", + " # Find the threshold that maximizes tnr - fnr difference\n", " optimal_threshold_index = np.argmax(tnr_minus_fnr)\n", " optimal_threshold = thresholds[optimal_threshold_index]\n", " ax.scatter(\n", - " tnr[optimal_threshold_index],\n", " fnr[optimal_threshold_index],\n", - " c=\"blue\" if sensitive_value == sensitive_value_0 else \"red\",\n", + " tpr[optimal_threshold_index],\n", + " # c=\"blue\" if sensitive_value == sensitive_value_0 else \"red\",\n", " label=f\"Optimal Threshold {sensitive_value} {optimal_threshold:.2f}\",\n", " )\n", "\n", "\n", "for alg, (model_name, model) in best_models.items():\n", " f = plt.figure()\n", + " f.set_figwidth(10)\n", + " f.set_figheight(10)\n", " ax = f.subplots()\n", " ax.set_title(alg)\n", " with torch.inference_mode():\n", - " predictions_0 = model(X_test_w)\n", - " predictions_1 = model(X_test_nw)\n", - " # Plot ROC for sensitive attribute A=0\n", - " plot_roc_curve_nr(\n", - " ax, predictions_0, y_test_w, sensitive_value=sensitive_value_0\n", - " )\n", - " # Plot ROC for sensitive attribute A=1\n", - " plot_roc_curve_nr(\n", - " ax, predictions_1, y_test_nw, sensitive_value=sensitive_value_1\n", - " )\n", - " ax.plot([0, 1], [0, 1], linestyle=\"--\", color=\"gray\", label=\"Random Classifier\")\n", - " ax.set_xlabel(\"False Negative Rate\", fontsize=24)\n", - " ax.set_ylabel(\"True Negative Rate\", fontsize=24)\n", - " ax.legend()" + " for i,group in enumerate(group_ind_test):\n", + " predictions = model(X_test_tensor[group])\n", + " # Plot ROC for sensitive attribute A=0\n", + " plot_roc_curve_nr(\n", + " ax, predictions, y_test[group], sensitive_value=i\n", + " )\n", + " ax.plot([0, 1], [0, 1], linestyle=\"--\", color=\"gray\", label=\"Random Classifier\")\n", + " ax.set_xlabel(\"False Negative Rate\", fontsize=24)\n", + " ax.set_ylabel(\"True Negative Rate\", fontsize=24)\n", + " ax.legend()" ] } ], "metadata": { "kernelspec": { - "display_name": "humancompatible", + "display_name": "hc-dev", "language": "python", "name": "python3" }, diff --git a/experiments/run_folktables.py b/experiments/run_folktables.py index ec23a13..4d4fe58 100644 --- a/experiments/run_folktables.py +++ b/experiments/run_folktables.py @@ -1,23 +1,27 @@ -from copy import deepcopy import importlib +from itertools import combinations import os import timeit - +import warnings import hydra import numpy as np import pandas as pd import torch +from torch.utils.data import TensorDataset from omegaconf import DictConfig, OmegaConf from torch import nn, tensor -from torch.utils.data import TensorDataset, Subset -from utils.load_folktables import prepare_folktables +from utils.load_folktables import prepare_folktables_multattr from utils.network import SimpleNet +from humancompatible.train.benchmark.algorithms.utils import net_grads_to_tensor +from itertools import combinations +from humancompatible.train.fairness.constraints import FairnessConstraint -from src.constraints import FairnessConstraint @hydra.main(version_base=None, config_path="conf", config_name="experiment") def run(cfg: DictConfig) -> None: + warnings.filterwarnings("ignore", category=FutureWarning) + print(OmegaConf.to_yaml(cfg)) N_RUNS = cfg.n_runs FT_STATE = cfg.data.state @@ -25,13 +29,16 @@ def run(cfg: DictConfig) -> None: DOWNLOAD_DATA = cfg.data.download DATA_PATH = cfg.data.path - # CONSTRAINT = cfg.constraint - CONSTRAINT = 'eq_loss' - LOSS_BOUND = cfg.constraint.bound + if "constraint" in cfg.keys(): + CONSTRAINT = cfg.constraint.import_name + LOSS_BOUND = cfg.constraint.bound + else: + CONSTRAINT = "unconstr" + LOSS_BOUND = 0 if cfg.device == "cpu": device = "cpu" - elif cfg.alg.startswith("sg"): + elif cfg.alg == "ghost": device = "cpu" print("CUDA not supported for Stochastic Ghost") elif torch.cuda.is_available(): @@ -46,32 +53,46 @@ def run(cfg: DictConfig) -> None: DTYPE = torch.float32 + ## load data ## + torch.set_default_dtype(DTYPE) DATASET_NAME = FT_TASK + "_" + FT_STATE ( X_train, y_train, - [w_idx_train, nw_idx_train], + group_ind_train, + _, + _, X_test, y_test, - [w_idx_test, nw_idx_test], - ) = prepare_folktables( + group_ind_test, + _, + _, + _ + ) = prepare_folktables_multattr( FT_TASK, state=FT_STATE.upper(), random_state=42, - make_unbalanced=False, onehot=False, download=DOWNLOAD_DATA, path=DATA_PATH, + sens_cols=cfg.data.sens_attr, + binarize=cfg.data.binarize, + stratify=False, ) + print('Groups:') + print(len(group_ind_train)) X_train_tensor = tensor(X_train, dtype=DTYPE) y_train_tensor = tensor(y_train, dtype=DTYPE) train_ds = TensorDataset(X_train_tensor, y_train_tensor) + print(f"Train data loaded: {(FT_TASK, FT_STATE)}") print(f"Data shape: {X_train_tensor.shape}") - - if 'save_name' in cfg['alg'].keys(): + + ## prepare to save results ## + + if "save_name" in cfg["alg"].keys(): alg_save_name = cfg.alg.save_name else: alg_save_name = cfg.alg.import_name @@ -82,289 +103,306 @@ def run(cfg: DictConfig) -> None: directory = os.path.join( saved_models_path, DATASET_NAME, CONSTRAINT, f"{LOSS_BOUND:.0E}" ) - + model_name = os.path.join(directory, f"{alg_save_name}_{LOSS_BOUND}") if not os.path.exists(directory): os.makedirs(directory) - ftrial, ctrial, wtrial, ttrial, samples_trial = [], [], [], [], [] - - # experiment loop + ## run experiments ## + histories = [] for EXP_IDX in range(N_RUNS): - torch.manual_seed(EXP_IDX) - model_path = model_name + f"_trial{EXP_IDX}.pt" net = SimpleNet(in_shape=X_test.shape[1], out_shape=1, dtype=DTYPE).to(device) + + ## define constraints ## + loss_fn = nn.BCEWithLogitsLoss() + constraint_fn_module = importlib.import_module("humancompatible.train.fairness.constraints") + constraint_fn = getattr(constraint_fn_module, cfg.constraint.import_name) - if cfg.alg.import_name.startswith("fairret"): - fairret_loss = importlib.import_module("fairret.loss") - fairret_statistic = importlib.import_module("fairret.statistic") - statistic = getattr(fairret_statistic, cfg.alg.params.statistic)() - loss_fairret = getattr(fairret_loss, cfg.alg.params.loss)(statistic) - - run_start = timeit.default_timer() - current_time = timeit.default_timer() - data_w = Subset(train_ds, w_idx_train) - data_b = Subset(train_ds, nw_idx_train) - - history = {"loss": [], "constr": [], "w": [], "time": [], "n_samples": []} - loss_fn = torch.nn.BCEWithLogitsLoss() - optimizer = torch.optim.SGD(net.parameters(), lr=5e-2) - epochs = cfg.alg.params.epochs - batch_size = cfg.alg.params.batch_size - mult = cfg.alg.params.pmult - for epoch in range(epochs): - gen = torch.Generator(device=device) - gen.manual_seed(EXP_IDX + epoch) - loader_w = torch.utils.data.DataLoader( - data_w, batch_size // 2, shuffle=True, generator=gen, drop_last=True + if cfg.constraint.type == 'one_vs_mean': + c = [ + FairnessConstraint( + train_ds, + [group_ind, np.concat(group_ind_train)], + fn=lambda net, inputs: constraint_fn(loss_fn, net, inputs) - cfg.constraint.bound, + batch_size=cfg.constraint.c_batch_size, + seed=EXP_IDX ) - loader_b = torch.utils.data.DataLoader( - data_b, batch_size // 2, shuffle=True, generator=gen, drop_last=True + for group_ind in group_ind_train + ] + if cfg.constraint.add_negative: + c.extend( + [ + FairnessConstraint( + train_ds, + [group_ind, np.concat(group_ind_train)], + fn=lambda net, inputs: -constraint_fn(loss_fn, net, inputs) - cfg.constraint.bound, + batch_size=cfg.constraint.c_batch_size, + seed=EXP_IDX + ) + for group_ind in group_ind_train + ] + ) + elif cfg.constraint.type == 'one_vs_each': + c = [ + FairnessConstraint( + train_ds, + group_idx, + fn=lambda net, inputs: constraint_fn(loss_fn, net, inputs) - cfg.constraint.bound, + batch_size=cfg.constraint.c_batch_size, + device=device, + seed=EXP_IDX, ) - for i, ((inputs_w, labels_w), (inputs_b, labels_b)) in enumerate( - zip(loader_w, loader_b) - ): - current_time = timeit.default_timer() - elapsed = current_time - run_start - if elapsed > cfg.run_maxtime: - break - history["time"].append(elapsed) - history["n_samples"].append(batch_size) - - net.zero_grad() - - inputs = torch.concat([inputs_w, inputs_b]) - labels = torch.concat([labels_w, labels_b]) - group_ind_onehot = torch.tensor( - [ - [0] * (batch_size // 2) + [1] * (batch_size // 2), - [1] * (batch_size // 2) + [0] * (batch_size // 2), - ] - ).T - outputs = net(inputs) - loss_bce = loss_fn(outputs.squeeze(), labels) - - try: - loss_fr = loss_fairret(outputs.squeeze(), group_ind_onehot) - except: - loss_fr = loss_fairret( - outputs, group_ind_onehot, labels.unsqueeze(1) + for group_idx in combinations(group_ind_train, 2) + ] + if cfg.constraint.add_negative: + c.extend( + [ + FairnessConstraint( + train_ds, + group_idx, + fn=lambda net, inputs: -constraint_fn(loss_fn, net, inputs) - cfg.constraint.bound, + batch_size=cfg.constraint.c_batch_size, + device=device, + seed=EXP_IDX, ) - loss = loss_bce + mult * loss_fr + for group_idx in combinations(group_ind_train, 2) + ] + ) - loss.backward() - optimizer.step() + torch.manual_seed(EXP_IDX) + model_path = model_name + f"_trial{EXP_IDX}.pt" - with np.printoptions(precision=6, suppress=True): - print( - f"{epoch:2} | {i:5} | {loss_bce.detach().cpu().numpy():.4}|{loss_fr.detach().cpu().numpy():.4}", - end="\r", - ) + net = SimpleNet(in_shape=X_test.shape[1], out_shape=1, dtype=DTYPE).to(device) - history["w"].append(deepcopy(net.state_dict())) - - elif cfg.alg.import_name.lower().startswith("sgd"): - run_start = timeit.default_timer() - current_time = timeit.default_timer() - loss_fn = torch.nn.BCEWithLogitsLoss() - optimizer = torch.optim.SGD(net.parameters(), lr=cfg.alg.params.lr) - train_ds = TensorDataset( - X_train_tensor.to(device), y_train_tensor.to(device) - ) - batch_size = cfg.alg.params.batch_size - train_l = torch.utils.data.DataLoader( - train_ds, batch_size=batch_size, shuffle=True - ) - history = {"loss": [], "constr": [], "w": [], "time": [], "n_samples": []} - for epoch in range(cfg.alg.params.epochs): - for i, (inputs, labels) in enumerate(train_l): - elapsed = timeit.default_timer() - run_start - if elapsed > cfg.run_maxtime: - break - history["time"].append(elapsed) - history["n_samples"].append(batch_size) - - net.zero_grad() - outputs = net(inputs) - loss = loss_fn(outputs.squeeze(), labels) - loss.backward() - optimizer.step() - - with np.printoptions(precision=6, suppress=True): - print( - f"{epoch:2} | {i:5} | {loss.detach().cpu().numpy()}", - end="\r", - ) + optimizer_name = cfg.alg.import_name + module = importlib.import_module("humancompatible.train.benchmark.algorithms") + Optimizer = getattr(module, optimizer_name) - history["w"].append(deepcopy(net.state_dict())) - else: - constraint_fn_module = importlib.import_module("src.constraints") - constraint_fn = getattr(constraint_fn_module, cfg.constraint.import_name) - - loss_fn = nn.BCEWithLogitsLoss() - cf1 = lambda net, d: constraint_fn(loss_fn, net, d) - cfg.constraint.bound - cf2 = ( - lambda net, d: -constraint_fn(loss_fn, net, d) - cfg.constraint.bound - ) - c1 = FairnessConstraint( - train_ds, - [w_idx_train, nw_idx_train], - fn=cf1, - batch_size=cfg.constraint.c_batch_size, - seed=EXP_IDX, - ) - c2 = FairnessConstraint( - train_ds, - [w_idx_train, nw_idx_train], - fn=cf2, - batch_size=cfg.constraint.c_batch_size, - seed=EXP_IDX, - ) - - optimizer_name = cfg.alg.import_name - module = importlib.import_module("src.algorithms") - Optimizer = getattr(module, optimizer_name) - - optimizer = Optimizer(net, train_ds, loss_fn, [c1, c2]) - history = optimizer.optimize( - **cfg.alg.params, - max_iter=cfg.run_maxiter, - max_runtime=cfg.run_maxtime, - device=cfg.device, - seed=EXP_IDX, - ) + optimizer = Optimizer(net, train_ds, loss_fn, c) + history = optimizer.optimize( + **cfg.alg.params, + max_iter=cfg.run_maxiter, + max_runtime=cfg.run_maxtime, + device=device, + seed=EXP_IDX, + verbose=True, + ) ## SAVE RESULTS ## - ftrial.append(pd.Series(history["loss"])) - ctrial.append(pd.DataFrame(history["constr"])) - wtrial.append(history["w"]) - ttrial.append(history["time"]) - samples_trial.append(pd.Series(history["n_samples"])) + params = pd.DataFrame(history["params"]) + values = pd.DataFrame(history["values"]) + t = pd.Series(history["time"], name="time") + histories.append(values.join(params, how="outer").join(t, how="outer")) + ## SAVE MODEL ## + print(f"Model saved to: {model_path}") torch.save(net.state_dict(), model_path) print("") # Save DataFrames to CSV files + c_name = cfg.constraint.import_name utils_path = os.path.abspath( - os.path.join(os.path.dirname(__file__), "utils", "exp_results") + os.path.join(os.path.dirname(__file__), "utils", "exp_results", c_name) ) if not os.path.exists(utils_path): os.makedirs(utils_path) + + if cfg.save_checkpoint_df: + fname = f"{alg_save_name}_{DATASET_NAME}_{LOSS_BOUND}.csv" + save_path = os.path.join(utils_path, fname) + print(f"Saving to: {save_path}") + histories = pd.concat(histories, keys=range(N_RUNS), names=["trial", "iteration"]) + histories.to_pickle(save_path) + print("Saved!") + + #################################################### + ### CALCULATE STATS ON EVERY ALGORITHM ITERATION ### + #################################################### - ftrial = pd.concat(ftrial, keys=range(len(ftrial))) - ctrial = pd.concat(ctrial, keys=range(len(ctrial))) - samples_trial = pd.concat(samples_trial, keys=range(len(samples_trial))) - - fname = f"{alg_save_name}_{DATASET_NAME}_{LOSS_BOUND}" - - print(f"Saving to: {fname}") - ftrial.to_csv(os.path.join(utils_path, fname + "_ftrial.csv")) - ctrial.to_csv(os.path.join(utils_path, fname + "_ctrial.csv")) - samples_trial.to_csv(os.path.join(utils_path, fname + "_samples.csv")) - print("Saved!") - - ############################################################# - ### CALCULATE TEST SET STATS ON EVERY ALGORITHM ITERATION ### - ############################################################# + loss_fn = nn.BCEWithLogitsLoss() + constraint_fn_module = importlib.import_module("humancompatible.train.fairness.constraints") + constraint_fn = getattr(constraint_fn_module, cfg.constraint.import_name) print("----") print("") - wlen = max([len(tr) for tr in wtrial]) - index = pd.MultiIndex.from_product( - [["train", "test"], np.arange(wlen), np.arange(N_RUNS)], - names=("is_train", "iteration", "trial"), + + exp_iter_indices = [ + histories.loc[exp_idx, :] + .index.get_level_values("iteration")[histories.loc[exp_idx]["w"].notna()] + .to_list() + for exp_idx in histories.index.get_level_values("trial").unique() + ] + exp_maxiter = np.argmax([ind[-1] for ind in exp_iter_indices]) + longest_exp_indices = exp_iter_indices[exp_maxiter] + longest_exp_indices.extend( + [ei[-1] for ei in exp_iter_indices if ei[-1] not in longest_exp_indices] ) - full_stats = pd.DataFrame( - index=index, columns=["Loss", "C1", "C2", "SampleSize", "time"] + longest_exp_indices = list(set(longest_exp_indices)) + longest_exp_indices.sort() + + index = pd.MultiIndex.from_product( + [longest_exp_indices, range(N_RUNS)], + names=("iteration", "trial"), ) - full_stats.sort_index(inplace=True) + full_eval_train = pd.DataFrame( + index=index, columns=["G", "f", "fg", "c", "cg"] + ).sort_index() + full_eval_test = pd.DataFrame( + index=index, columns=["G", "f", "fg", "c", "cg"] + ).sort_index() loss_fn = nn.BCEWithLogitsLoss() - - device = 'cuda' if torch.cuda.is_available() else device - X_test_tensor = tensor(X_test, dtype=DTYPE).to(device) y_test_tensor = tensor(y_test, dtype=DTYPE).to(device) - - X_test_w = X_test_tensor[w_idx_test] - y_test_w = y_test_tensor[w_idx_test] - X_test_nw = X_test_tensor[nw_idx_test] - y_test_nw = y_test_tensor[nw_idx_test] - - X_train_w = X_train_tensor[w_idx_train] - y_train_w = y_train_tensor[w_idx_train] - X_train_nw = X_train_tensor[nw_idx_train] - y_train_nw = y_train_tensor[nw_idx_train] + X_train_tensor = X_train_tensor.to(device=device) + y_train_tensor = y_train_tensor.to(device=device) save_train = True - - with torch.inference_mode(): - for exp_idx in range(N_RUNS): - weights_to_eval = wtrial[exp_idx] - for alg_iteration, w in enumerate(weights_to_eval): - if CONSTRAINT == "eq_loss": - constraint_fn_module = importlib.import_module("src.constraints") - constraint_fn = getattr(constraint_fn_module, cfg.constraint.import_name) - c_f = constraint_fn - c_loss_fn = nn.BCEWithLogitsLoss() - print(f"{exp_idx} | {alg_iteration}", end="\r") - net.load_state_dict(w) - net = net.to(device) - - if save_train: - outs = net(X_train_tensor) - if y_train_tensor.ndim < outs.ndim: - y_train_tensor = y_train_tensor.unsqueeze(1) - loss = loss_fn(outs, y_train_tensor).detach().cpu().numpy() - - c1 = ( - c_f( - c_loss_fn, - net, - [(X_train_w, y_train_w), (X_train_nw, y_train_nw)], + save_test = True + histories.dropna(subset=["w"], inplace=True) + + for exp_idx in range(N_RUNS): + for alg_iteration in histories.loc[exp_idx, :].index: + print(f"{exp_idx} | {alg_iteration}", end="\r") + + w = histories["w"].loc[exp_idx, alg_iteration] + net.load_state_dict(w) + net = net.to(device) + if save_train: + if cfg.constraint.type=="one_vs_mean": + data_c = [ + ( + (X_train_tensor[g_idx], y_train_tensor[g_idx]), + (X_train_tensor, y_train_tensor) ) - .detach() - .cpu() - .numpy() - ) - c2 = -c1 - # pandas multiindex bug(?) workaround - full_stats.loc["train"].at[alg_iteration, exp_idx] = { - "Loss": loss, - "C1": c1, - "C2": c2, - "SampleSize": samples_trial[exp_idx][alg_iteration], - "time": ttrial[exp_idx][alg_iteration], - } - - outs = net(X_test_tensor) - if y_test_tensor.ndim < outs.ndim: - y_test_tensor = y_test_tensor.unsqueeze(1) - loss = loss_fn(outs, y_test_tensor).detach().cpu().numpy() - - c1 = ( - c_f(c_loss_fn, net, [(X_test_w, y_test_w), (X_test_nw, y_test_nw)]) - .detach() - .cpu() - .numpy() + for g_idx in group_ind_train + ] + elif cfg.constraint.type=="one_vs_each": + data_c = [ + ( + (X_train_tensor[g_idx_1], y_train_tensor[g_idx_1]), + (X_train_tensor[g_idx_2], y_train_tensor[g_idx_2]), + ) + for g_idx_1, g_idx_2 in combinations(group_ind_train, 2) + ] + calculate_iteration_values( + alg=cfg.alg.import_name, + full_eval=full_eval_train, + index_to_save=[alg_iteration, exp_idx], + c=c, + loss_fn=loss_fn, + data_f=[X_train_tensor, y_train_tensor], + data_c=data_c, + net=net, + device=device, + add_negative=cfg.constraint.add_negative, + **params, ) - c2 = -c1 - full_stats.loc["test"].at[alg_iteration, exp_idx] = { - "Loss": loss, - "C1": c1, - "C2": c2, - "SampleSize": samples_trial[exp_idx][alg_iteration], - "time": ttrial[exp_idx][alg_iteration], - } - fname = f"{alg_save_name}_{DATASET_NAME}_{LOSS_BOUND}.csv" - print(f"Saving to: {fname}") - full_stats.to_csv(os.path.join(utils_path, fname)) + if save_test: + if cfg.constraint.type=="one_vs_mean": + data_c = [ + ( + (X_test_tensor[g_idx], y_test_tensor[g_idx]), + (X_test_tensor, y_test_tensor) + ) + for g_idx in group_ind_test + ] + elif cfg.constraint.type=="one_vs_each": + data_c = [ + ( + (X_test_tensor[g_idx_1], y_test_tensor[g_idx_1]), + (X_test_tensor[g_idx_2], y_test_tensor[g_idx_2]), + ) + for g_idx_1, g_idx_2 in combinations(group_ind_test, 2) + ] + calculate_iteration_values( + alg=cfg.alg.import_name, + full_eval=full_eval_test, + index_to_save=[alg_iteration, exp_idx], + c=c, + loss_fn=loss_fn, + data_f=[X_test_tensor, y_test_tensor], + data_c=data_c, + net=net, + device=device, + add_negative=cfg.constraint.add_negative, + **params, + ) + + net.zero_grad() + + fname = f"AFTER_{alg_save_name}_{DATASET_NAME}_{LOSS_BOUND}" + fext = ".csv" + if save_train: + fname_train = fname + "_train" + fext + save_path = os.path.join(utils_path, fname_train) + print(f"Saving to: {save_path}") + full_eval_train.to_pickle(save_path) + + if save_test: + fname_test = fname + "_test" + fext + save_path = os.path.join(utils_path, fname_test) + print(f"Saving to: {save_path}") + full_eval_test.to_pickle(save_path) + + +# helper function to calculate relevant values on full dataset (e.g. constraint gradient, AL function, etc) +# used to calculate those values at different points during algorithms run +def calculate_iteration_values( + alg, + full_eval, + index_to_save, + c, + loss_fn, + data_f, + data_c, + net, + device, + add_negative, + **params, +): + c_val_vec, c_grads_mat = [], [] + + for i, c_i in enumerate(c): + cv = c_i.eval(net, data_c[i // 2 if add_negative else i]) + c_val_vec.append(cv) + cv.backward() + cg = net_grads_to_tensor(net, flatten=True, device=device) + net.zero_grad() + c_grads_mat.append(cg) + c_val_vec = torch.tensor(c_val_vec) + c_grads_mat = torch.stack(c_grads_mat) + full_eval.loc[*index_to_save]["c"] = [c_val_vec.detach().cpu().numpy()] + full_eval.loc[*index_to_save]["cg"] = [c_grads_mat.detach().cpu().numpy()] + + X_tensor, y_tensor = data_f + outs = net(X_tensor) + if y_tensor.ndim < outs.ndim: + y_tensor = y_tensor.unsqueeze(1) + loss = loss_fn(outs, y_tensor) + loss.backward() + fg = net_grads_to_tensor(net, flatten=True, device=device) + net.zero_grad() + + full_eval.loc[*index_to_save]["f"] = loss.detach().cpu().numpy() + full_eval.loc[*index_to_save]["fg"] = [fg.detach().cpu().numpy()] + + +def sample_or_restart_iterloader(loader): + try: + item = next(loader) + return item + except StopIteration: + loader._reset(loader) + # loader.gen + item = next(loader) + return item if __name__ == "__main__": - run() + run() \ No newline at end of file diff --git a/experiments/run_folktables_torchalgs.py b/experiments/run_folktables_torchalgs.py new file mode 100644 index 0000000..20d4fa6 --- /dev/null +++ b/experiments/run_folktables_torchalgs.py @@ -0,0 +1,956 @@ +from copy import deepcopy +import importlib +from itertools import combinations +import os +import timeit +import warnings +import hydra +import numpy as np +import pandas as pd +import torch +from omegaconf import DictConfig, OmegaConf +from torch import nn, tensor +from torch.utils.data import TensorDataset, DataLoader, SubsetRandomSampler +from humancompatible.train.fairness.constraints.constraint_fns import fairret_stat_equality +from utils.load_folktables import prepare_folktables_multattr +from utils.network import SimpleNet +from humancompatible.train.algorithms.utils import net_grads_to_tensor, net_params_to_tensor +from itertools import combinations +from humancompatible.train.fairness.constraints import FairnessConstraint + + + +@hydra.main(version_base=None, config_path="conf", config_name="experiment") +def run(cfg: DictConfig) -> None: + warnings.filterwarnings("ignore", category=FutureWarning) + + print(OmegaConf.to_yaml(cfg)) + N_RUNS = cfg.n_runs + FT_STATE = cfg.data.state + FT_TASK = cfg.data.task + DOWNLOAD_DATA = cfg.data.download + DATA_PATH = cfg.data.path + + if "constraint" in cfg.keys(): + CONSTRAINT = cfg.constraint.import_name + LOSS_BOUND = cfg.constraint.bound + else: + CONSTRAINT = "unconstr" + LOSS_BOUND = 0 + + if cfg.device == "cpu": + device = "cpu" + elif cfg.alg == "ghost": + device = "cpu" + print("CUDA not supported for Stochastic Ghost") + elif torch.cuda.is_available(): + device = "cuda" + print("CUDA found") + else: + device = "cpu" + print("CUDA not found") + + print(f"{device = }") + torch.set_default_device(device) + + DTYPE = torch.float32 + + ## load data ## + + torch.set_default_dtype(DTYPE) + DATASET_NAME = FT_TASK + "_" + FT_STATE + + ( + X_train, + y_train, + group_ind_train, + group_onehot_train, + sep_group_ind_train, + X_test, + y_test, + group_ind_test, + sep_group_ind_test, + group_onehot_test, + _ + ) = prepare_folktables_multattr( + FT_TASK, + state=FT_STATE.upper(), + random_state=42, + onehot=False, + download=DOWNLOAD_DATA, + path=DATA_PATH, + sens_cols=cfg.data.sens_attr, + binarize=cfg.data.binarize, + stratify=False, + ) + print('Groups:') + print(len(group_ind_train)) + X_train_tensor = tensor(X_train, dtype=DTYPE) + y_train_tensor = tensor(y_train, dtype=DTYPE) + train_ds = TensorDataset(X_train_tensor, y_train_tensor) + + print(f"Train data loaded: {(FT_TASK, FT_STATE)}") + print(f"Data shape: {X_train_tensor.shape}") + + ## prepare to save results ## + + if "save_name" in cfg["alg"].keys(): + alg_save_name = cfg.alg.save_name + else: + alg_save_name = cfg.alg.import_name + + saved_models_path = os.path.abspath( + os.path.join(os.path.dirname(__file__), "utils", "saved_models") + ) + directory = os.path.join( + saved_models_path, DATASET_NAME, CONSTRAINT, f"{LOSS_BOUND:.0E}" + ) + + model_name = os.path.join(directory, f"{alg_save_name}_{LOSS_BOUND}") + + if not os.path.exists(directory): + os.makedirs(directory) + + ## run experiments ## + + histories = [] + + # experiment loop + for EXP_IDX in range(N_RUNS): + + net = SimpleNet(in_shape=X_test.shape[1], out_shape=1, dtype=DTYPE).to(device) + + ## define constraints ## + + criterion = nn.BCEWithLogitsLoss() + constraint_fn_module = importlib.import_module("humancompatible.train.fairness.constraints") + try: + constraint_fn = getattr(constraint_fn_module, cfg.constraint.import_name) + except: + constraint_fn = getattr(importlib.import_module("humancompatible.train.fairness.constraints.torch"), "loss_equality") + + if cfg.constraint.import_name == 'abs_max_dev_from_overall_tpr': + c = [FairnessConstraint( + train_ds, + group_ind_train, + fn=lambda net, inputs: constraint_fn(criterion, net, inputs) - cfg.constraint.bound, + batch_size=cfg.constraint.c_batch_size, + seed=EXP_IDX + )] + elif cfg.constraint.import_name in ['abs_diff_tpr', 'abs_diff_pr']: + c = [ + FairnessConstraint( + train_ds, + [group_ind, np.concat(group_ind_train)], + fn=lambda net, inputs: constraint_fn(criterion, net, inputs) - cfg.constraint.bound, + batch_size=cfg.constraint.c_batch_size, + seed=EXP_IDX + ) + for group_ind in group_ind_train + ] + elif cfg.constraint.import_name in ['abs_diff_fpr', 'abs_diff_pr']: + c = [ + FairnessConstraint( + train_ds, + [group_ind, np.concat(group_ind_train)], + fn=lambda net, inputs: constraint_fn(criterion, net, inputs) - cfg.constraint.bound, + batch_size=cfg.constraint.c_batch_size, + seed=EXP_IDX + ) + for group_ind in group_ind_train + ] + constraint_fn1 = getattr(constraint_fn_module, 'abs_diff_tpr') + c += [ + FairnessConstraint( + train_ds, + [group_ind, np.concat(group_ind_train)], + fn=lambda net, inputs: constraint_fn1(criterion, net, inputs) - cfg.constraint.bound, + batch_size=cfg.constraint.c_batch_size, + seed=EXP_IDX + ) + for group_ind in group_ind_train + ] + else: + c = construct_constraints( + bound=cfg.constraint.bound, + add_negative=cfg.constraint.add_negative, + batch_size=cfg.constraint.c_batch_size, + device=device, + constraint_groups=[group_ind_train], + dataset=train_ds, + seed=EXP_IDX, + constraint_fn=lambda net, inputs: constraint_fn(criterion, net, inputs), + max_0 = False + ) + # breakpoint() + + torch.manual_seed(EXP_IDX) + model_path = model_name + f"_trial{EXP_IDX}.pt" + + net = SimpleNet(in_shape=X_test.shape[1], out_shape=1, dtype=DTYPE).to(device) + + history = { + "params": {"w": {}, "slack": {}, "dual_ms": {}}, + "values": {"f": {}, "c": {}, "G": {}}, + "time": {}, + } + + ## train ## + + if cfg.alg.import_name.startswith("fairret"): + m = len(group_ind_train) + + _fairret_loss_module = importlib.import_module("fairret.loss") + _fairret_statistic_module = importlib.import_module("fairret.statistic") + fstat = getattr(_fairret_statistic_module, cfg.alg.params.statistic)() + floss = getattr(_fairret_loss_module, cfg.alg.params.loss)(fstat, p=1) + + run_start = timeit.default_timer() + + criterion = torch.nn.BCEWithLogitsLoss() + optimizer = torch.optim.SGD(net.parameters(), lr=cfg.alg.params.lr) + c_batch_size = cfg.alg.params.c_batch_size + obj_batch_size = cfg.alg.params.obj_batch_size + mult = cfg.alg.params.pmult + + total_iters = 0 + gen = torch.Generator(device=device) + gen.manual_seed(EXP_IDX) + obj_loader = iter( + torch.utils.data.DataLoader( + train_ds, + obj_batch_size, + shuffle=True, + generator=gen, + drop_last=True, + ) + ) + + constr_dataloaders = [] + for group_indices in group_ind_train: + sampler = SubsetRandomSampler(group_indices, gen) + constr_dataloaders.append( + iter( + DataLoader( + train_ds, c_batch_size, sampler=sampler, drop_last=True + ) + ) + ) + + epoch = 0 + iteration = 0 + total_iters = 0 + + group_ind_onehot = torch.empty(m, (c_batch_size * m)) + for j in range(1, m): + group_ind_onehot[j][c_batch_size * (j - 1) : c_batch_size * j] = ( + torch.ones(c_batch_size) + ) + group_ind_onehot = group_ind_onehot.T + + while True: + elapsed = timeit.default_timer() - run_start + iteration += 1 + total_iters += 1 + if ( + cfg.run_maxiter is not None and total_iters >= cfg.run_maxiter + ) or elapsed > cfg.run_maxtime: + break + if total_iters % cfg.alg.params.save_state_interval == 0: + history["params"]["w"][total_iters] = deepcopy(net.state_dict()) + history["time"][total_iters] = elapsed + + net.zero_grad() + + inputs, labels = sample_or_restart_iterloader(obj_loader) + outputs = net(inputs) + loss_obj = criterion(outputs.squeeze(), labels) + + c_inputs, c_labels = [], [] + for j in range(m): + group_inputs, group_labels = sample_or_restart_iterloader( + constr_dataloaders[j] + ) + c_inputs.append(group_inputs) + c_labels.append(group_labels) + + c_inputs = torch.concat(c_inputs) + c_labels = torch.concat(c_labels) + + outputs_c = net(c_inputs).squeeze() + loss_c = floss( + outputs_c.unsqueeze(1), group_ind_onehot, c_labels.unsqueeze(1) + ) + + loss = loss_obj + mult * loss_c + + loss.backward() + optimizer.step() + + with np.printoptions(precision=6, suppress=True): + print( + f"{epoch:2} | {iteration:5} | {loss_obj.detach().cpu().numpy():.4} | {loss_c.detach().cpu().numpy():.4}", + end="\r", + ) + elif cfg.alg.import_name.startswith("TorchSSLALM"): + epochs = 1000 + avg_epoch_c_log = [] + avg_epoch_loss_log = [] + m = len(list(combinations(group_ind_train, 2)))*2 + + from fairret.statistic import TruePositiveRate, PositiveRate + from fairret.loss import NormLoss + + # breakpoint() + train_ds_sens = TensorDataset( + X_train_tensor, + group_onehot_train, + y_train_tensor + ) + + + slack_vars = torch.zeros(m, requires_grad=True) + obj_batch_size = 16 + c_batch_size = cfg.constraint.c_batch_size + + from humancompatible.train.algorithms.torch import SSLALM + optimizer = SSLALM( + net.parameters(), + lr=0.01, + dual_lr=0.1, + rho=1.0, + mu=2.0, + beta=0.5, + m=m, + ) + c_bound = torch.tensor([cfg.constraint.bound]*m) + optimizer.add_param_group(param_group={"params": slack_vars, "name": "slack"}) + # constr = FalseNegativeFalsePositiveFraction() + # constr = PositiveRate() + constr = constraint_fn + # fair_loss = NormLoss(constr) + + time = timeit.default_timer() + total_iters = 0 + c_criterion = torch.nn.BCEWithLogitsLoss(reduction='none') + + for epoch in range(epochs): + elapsed = timeit.default_timer() + if elapsed - time > cfg.run_maxtime: + break + loss_log = [] + c_log = [] + gen = torch.Generator(device=device) + gen.manual_seed(EXP_IDX + epoch) + from humancompatible.train.fairness.utils import BalancedBatchSampler + + sampler = BalancedBatchSampler( + # subgroup_indices=group_ind_train, + subgroup_onehot=group_onehot_train, + batch_size=c_batch_size, + drop_last=True + ) + dataloader = DataLoader( + train_ds_sens, + batch_sampler=sampler + ) + # c_loader = iter(dataloader) + for batch_input, batch_sens, batch_label in dataloader: + elapsed = timeit.default_timer() + if elapsed - time > cfg.run_maxtime: + break + history["time"][total_iters] = elapsed - time + + # evaluate constraints and constraint grads + c_vals = [] + c_vals_raw = [] + + c_inputs = batch_input[::2] + c_labels = batch_label[::2] + c_sens = batch_sens[::2] + c_sens_norm = c_sens.div(torch.sum(c_sens, axis=0)) + + # calculate loss for each group + c_loss = c_criterion(net(c_inputs).squeeze(), c_labels) @ c_sens_norm + c_val_raw_vec = [] + for (l1, l2) in combinations(c_loss, 2): + c_val_raw_vec.append(l1-l2) + c_val_raw_vec.append(l2-l1) + + + # c_outputs = torch.nn.functional.sigmoid(net(c_inputs)) + # c_outputs_pos_idx = (c_outputs >= 0).squeeze() + # c_overall = constr(c_outputs[c_outputs_pos_idx], None + # , c_labels[c_outputs_pos_idx].unsqueeze(1) + # ) + # c_val_raw_vec = constr(c_outputs[c_outputs_pos_idx], c_sens[c_outputs_pos_idx] + # , c_labels[c_outputs_pos_idx].unsqueeze(1) + # ) + # c_val_raw_vec = torch.abs(c_val_raw_vec - c_overall) + + for i in range(m): + optimizer.zero_grad() + c_val = c_val_raw_vec[i] + slack_vars[i] - c_bound[i] + # retain_graph in all but last iteration to calculate grads + c_val.backward(retain_graph = i < m-1) + optimizer.dual_step(i, c_val) + + c_vals.append(c_val.detach()) + c_vals_raw.append(c_val_raw_vec[i].detach()) + + + optimizer.zero_grad() + # evaluate loss and loss grad + logits = net(batch_input) + loss = criterion(logits.squeeze(), batch_label) + torch.zeros_like(slack_vars) @ slack_vars # SLACK + loss.backward() + + if cfg.alg.params.use_unbiased_penalty_grad: + with torch.no_grad(): + c_inputs = batch_input[1::2] + c_labels = batch_label[1::2] + c_sens = batch_sens[1::2] + c_sens_norm = c_sens.div(torch.sum(c_sens, axis=0)) + c_loss = c_criterion(net(c_inputs).squeeze(), c_labels) @ c_sens_norm + c_val_raw_vec = [] + for (l1, l2) in combinations(c_loss, 2): + c_val_raw_vec.append(l1-l2) + c_val_raw_vec.append(l2-l1) + + # c_vals = [] + # c_vals_raw = [] + # c_inputs = batch_input[1::2] + # c_labels = batch_label[1::2] + # c_sens = batch_sens[1::2] + # c_outputs = torch.nn.functional.sigmoid(net(c_inputs)) + # c_outputs_pos_idx = (c_outputs >= 0).squeeze() + # c_overall = constr(c_outputs[c_outputs_pos_idx], None + # ,c_labels[c_outputs_pos_idx].unsqueeze(1) + # ) + # c_val_raw_vec = constr(c_outputs[c_outputs_pos_idx], c_sens[c_outputs_pos_idx] + # , c_labels[c_outputs_pos_idx].unsqueeze(1) + # ) + # c_val_raw_vec = torch.abs(c_val_raw_vec - c_overall) + # c_val = c_val_raw_vec + slack_vars - c_bound + # c_vals.append(c_val.detach()) + + # c_vals_raw = c_val_raw_vec.detach() + + optimizer.step(c_vals) + optimizer.zero_grad() + if total_iters % cfg.alg.params.save_state_interval == 0: + history["params"]["w"][total_iters] = deepcopy(net.state_dict()) + history["time"][total_iters] = elapsed - time + + total_iters += 1 + + with torch.no_grad(): + for s in slack_vars: + if s < 0: + s.zero_() + + loss_log.append(loss.item()) + c_log.append([c.item() for c in c_vals_raw]) + + # print(optimizer._dual_vars) + avg_epoch_loss_log.append(np.mean(loss_log)) + avg_epoch_c_log.append(np.mean(c_log, axis=0)) + with np.printoptions(precision=4): + print( + f"Epoch: {epoch}, loss: {avg_epoch_loss_log[-1]}, constraints: {avg_epoch_c_log[-1]}, dual: {optimizer._dual_vars.detach().numpy()}" + ) + elif cfg.alg.import_name.startswith("TorchSSG"): + epochs = 100000 + avg_epoch_c_log = [] + avg_epoch_loss_log = [] + m = 1 + + from fairret.statistic import PositiveRate + + # breakpoint() + train_ds_sens = TensorDataset(X_train_tensor, group_onehot_train, y_train_tensor) + + obj_batch_size = 16 + c_batch_size = cfg.constraint.c_batch_size + + from humancompatible.train.algorithms.torch import SSG + optimizer = SSG( + net.parameters(), + lr=0.05, + dual_lr=0.05, + m=m, + ) + c_bound = torch.tensor([cfg.constraint.bound]*5) + c_tol = torch.tensor([cfg.constraint.bound*2]*5) + + time = timeit.default_timer() + total_iters = 0 + + for epoch in range(epochs): + elapsed = timeit.default_timer() + if elapsed - time > cfg.run_maxtime: + break + loss_log = [] + c_log = [] + gen = torch.Generator(device=device) + gen.manual_seed(EXP_IDX + epoch) + obj_loader = iter( + torch.utils.data.DataLoader( + train_ds, + obj_batch_size, + shuffle=True, + generator=gen, + ) + ) + + gen = torch.Generator(device=device) + gen.manual_seed(EXP_IDX + epoch) + from humancompatible.train.fairness.utils import BalancedBatchSampler + + sampler = BalancedBatchSampler( + subgroup_indices=group_ind_train, + batch_size=c_batch_size, + drop_last=True) + dataloader = DataLoader(train_ds_sens, batch_sampler=sampler) + max_idx_log = [] + for batch_input, batch_sens, batch_label in dataloader: + elapsed = timeit.default_timer() + if elapsed - time > cfg.run_maxtime: + break + history["time"][total_iters] = elapsed - time + + # evaluate constraints and largest constraint grad + c_vals = [] + c_vals_raw = [] + + c_inputs = batch_input + c_sens = batch_sens + c_labels = batch_label + c_outputs = torch.nn.functional.sigmoid(net(c_inputs)) + + constr = PositiveRate() + c_overall = constr(c_outputs, None) + c_val_raw_vec = constr(c_outputs, c_sens) + # breakpoint() + c_val_raw_vec = torch.abs(c_val_raw_vec - c_overall) + + c_val = c_val_raw_vec - c_bound + c_max_viol_idx = torch.argmax(c_val - c_tol) + c_max_viol = c_val[c_max_viol_idx] + c_max_viol.backward() + max_idx_log.append(c_max_viol_idx) + + optimizer.dual_step(i=0) + + c_vals = c_max_viol + c_vals_raw.append(c_val_raw_vec.detach()) + + optimizer.zero_grad() + # evaluate loss and loss grad + logits = net(batch_input) + loss = criterion(logits.squeeze(), batch_label) + loss.backward() + + optimizer.step(c_vals) + optimizer.zero_grad() + + total_iters += 1 + c_tol /= np.sqrt(total_iters) + + if total_iters % cfg.alg.params.save_state_interval == 0: + history["params"]["w"][total_iters] = deepcopy(net.state_dict()) + + + loss_log.append(loss.item()) + c_log.append([ + c_val.detach() + ]) + + # print(optimizer._dual_vars) + avg_epoch_loss_log.append(np.mean(loss_log)) + avg_epoch_c_log.append(np.mean(c_log, axis=0)) + print( + f"Epoch: {epoch}, loss: {avg_epoch_loss_log[-1]}, constraints: {avg_epoch_c_log[-1]}" + ) + elif cfg.alg.import_name.startswith("SGD"): + + optimizer = torch.optim.Adam(params=net.parameters()) + + time = timeit.default_timer() + total_iters = 0 + train_ds_sens = TensorDataset(X_train_tensor, group_onehot_train, y_train_tensor) + epochs = 1000000 + avg_epoch_loss_log = [] + + for epoch in range(epochs): + elapsed = timeit.default_timer() + if elapsed - time > cfg.run_maxtime: + break + loss_log = [] + gen = torch.Generator(device=device) + gen.manual_seed(EXP_IDX + epoch) + + gen = torch.Generator(device=device) + gen.manual_seed(EXP_IDX + epoch) + from humancompatible.train.fairness.utils import BalancedBatchSampler + + sampler = BalancedBatchSampler( + subgroup_indices=group_ind_train, + batch_size=cfg.constraint.c_batch_size, + drop_last=True) + dataloader = DataLoader(train_ds_sens, batch_sampler=sampler) + + for batch_input, batch_sens, batch_label in dataloader: + elapsed = timeit.default_timer() + if elapsed - time > cfg.run_maxtime: + break + history["time"][total_iters] = elapsed - time + logits = net(batch_input) + loss = criterion(logits.squeeze(), batch_label) + loss.backward() + + optimizer.step() + optimizer.zero_grad() + + if total_iters % cfg.alg.params.save_state_interval == 0: + history["params"]["w"][total_iters] = deepcopy(net.state_dict()) + + total_iters += 1 + + loss_log.append(loss.item()) + + avg_epoch_loss_log.append(np.mean(loss_log)) + + print( + f"Epoch: {epoch}, loss: {avg_epoch_loss_log[-1]}" + ) + else: + optimizer_name = cfg.alg.import_name + module = importlib.import_module("humancompatible.train.algorithms") + Optimizer = getattr(module, optimizer_name) + + optimizer = Optimizer(net, train_ds, criterion, c) + history = optimizer.optimize( + **cfg.alg.params, + max_iter=cfg.run_maxiter, + max_runtime=cfg.run_maxtime, + device=device, + seed=EXP_IDX, + verbose=True, + ) + + ## SAVE RESULTS ## + params = pd.DataFrame(history["params"]) + values = pd.DataFrame(history["values"]) + t = pd.Series(history["time"], name="time") + histories.append(values.join(params, how="outer").join(t, how="outer")) + + ## SAVE MODEL ## + print(f"Model saved to: {model_path}") + torch.save(net.state_dict(), model_path) + print("") + + # Save DataFrames to CSV files + if cfg.alg.import_name.lower() == "sgd": + c_name = "unconstrained" + else: + c_name = cfg.constraint.import_name + utils_path = os.path.abspath( + os.path.join(os.path.dirname(__file__), "utils", "exp_results", c_name) + ) + if not os.path.exists(utils_path): + os.makedirs(utils_path) + fname = f"{alg_save_name}_{DATASET_NAME}_{LOSS_BOUND}.csv" + save_path = os.path.join(utils_path, fname) + print(f"Saving to: {save_path}") + histories = pd.concat(histories, keys=range(N_RUNS), names=["trial", "iteration"]) + histories.to_pickle(save_path) + print("Saved!") + + #################################################### + ### CALCULATE STATS ON EVERY ALGORITHM ITERATION ### + #################################################### + + criterion = nn.BCEWithLogitsLoss() + # constraint_fn_module = importlib.import_module("humancompatible.train.fairness.constraints") + # constraint_fn = getattr(constraint_fn_module, cfg.constraint.import_name) + # if cfg.constraint.import_name != 'abs_max_dev_from_overall_tpr': + # c = construct_constraints( + # bound=cfg.constraint.bound, + # add_negative=cfg.constraint.add_negative, + # batch_size=cfg.constraint.c_batch_size, + # device=device, + # constraint_groups=[group_ind_train], + # dataset=train_ds, + # seed=EXP_IDX, + # constraint_fn=lambda net, inputs: constraint_fn(loss_fn, net, inputs), + # max_0 = False + # ) + # else: + # c = [FairnessConstraint( + # train_ds, + # group_ind_train, + # fn=lambda net, inputs: constraint_fn(loss_fn, net, inputs) - cfg.constraint.bound, + # batch_size=cfg.constraint.c_batch_size // len(group_ind_train), + # seed=EXP_IDX + # )] + + print("----") + print("") + + exp_iter_indices = [ + histories.loc[exp_idx, :] + .index.get_level_values("iteration")[histories.loc[exp_idx]["w"].notna()] + .to_list() + for exp_idx in histories.index.get_level_values("trial").unique() + ] + exp_maxiter = np.argmax([ind[-1] for ind in exp_iter_indices]) + longest_exp_indices = exp_iter_indices[exp_maxiter] + longest_exp_indices.extend( + [ei[-1] for ei in exp_iter_indices if ei[-1] not in longest_exp_indices] + ) + longest_exp_indices = list(set(longest_exp_indices)) + longest_exp_indices.sort() + + index = pd.MultiIndex.from_product( + [longest_exp_indices, range(N_RUNS)], + names=("iteration", "trial"), + ) + full_eval_train = pd.DataFrame( + index=index, columns=["G", "f", "fg", "c", "cg"] + ).sort_index() + full_eval_test = pd.DataFrame( + index=index, columns=["G", "f", "fg", "c", "cg"] + ).sort_index() + + criterion = nn.BCEWithLogitsLoss() + X_test_tensor = tensor(X_test, dtype=DTYPE).to(device) + y_test_tensor = tensor(y_test, dtype=DTYPE).to(device) + X_train_tensor = X_train_tensor.to(device=device) + y_train_tensor = y_train_tensor.to(device=device) + + save_train = True + save_test = True + histories.dropna(subset=["w"], inplace=True) + + for exp_idx in range(N_RUNS): + for alg_iteration in histories.loc[exp_idx, :].index: + print(f"{exp_idx} | {alg_iteration}", end="\r") + + w = histories["w"].loc[exp_idx, alg_iteration] + net.load_state_dict(w) + net = net.to(device) + if cfg.alg.import_name.lower() == "sslalm": + x_t = net_params_to_tensor(net, flatten=True, copy=True) + lambdas = histories["dual_ms"].loc[exp_idx, alg_iteration] + z = histories["z"].loc[exp_idx, alg_iteration] + params = { + "x_t": x_t, + "lambdas": lambdas, + "z": z, + "rho": cfg.alg.params.rho, + "mu": cfg.alg.params.mu, + } + + if save_train: + if cfg.constraint.import_name == 'abs_max_dev_from_overall_tpr': + data_c = [[ + (X_train_tensor[g_idx], y_train_tensor[g_idx]) for g_idx in group_ind_train + ]] + elif cfg.constraint.import_name in ['abs_diff_pr', 'abs_diff_tpr']: + data_c = [ + ( + (X_train_tensor[g_idx], y_train_tensor[g_idx]), + (X_train_tensor, y_train_tensor) + ) + for g_idx in group_ind_train + ] + else: + data_c = [ + ( + (X_train_tensor[g_idx_1], y_train_tensor[g_idx_1]), + (X_train_tensor[g_idx_2], y_train_tensor[g_idx_2]), + ) + for g_idx_1, g_idx_2 in combinations(group_ind_train, 2) + ] + calculate_iteration_values( + alg=cfg.alg.import_name, + full_eval=full_eval_train, + index_to_save=[alg_iteration, exp_idx], + c=c, + loss_fn=criterion, + data_f=[X_train_tensor, y_train_tensor], + data_c=data_c, + net=net, + device=device, + add_negative=cfg.constraint.add_negative, + **params, + ) + + + if save_test: + if cfg.constraint.import_name == 'abs_max_dev_from_overall_tpr': + data_c = [[ + (X_test_tensor[g_idx], y_test_tensor[g_idx]) for g_idx in group_ind_test + ]] + elif cfg.constraint.import_name in ['abs_diff_tpr', 'abs_diff_pr']: + data_c = [ + ( + (X_test_tensor[g_idx], y_test_tensor[g_idx]), + (X_test_tensor, y_test_tensor) + ) + for g_idx in group_ind_test + ] + else: + data_c = [ + ( + (X_test_tensor[g_idx_1], y_test_tensor[g_idx_1]), + (X_test_tensor[g_idx_2], y_test_tensor[g_idx_2]), + ) + for g_idx_1, g_idx_2 in combinations(group_ind_test, 2) + ] + calculate_iteration_values( + alg=cfg.alg.import_name, + full_eval=full_eval_test, + index_to_save=[alg_iteration, exp_idx], + c=c, + loss_fn=criterion, + data_f=[X_test_tensor, y_test_tensor], + data_c=data_c, + net=net, + device=device, + add_negative=cfg.constraint.add_negative, + **params, + ) + + net.zero_grad() + + fname = f"AFTER_{alg_save_name}_{DATASET_NAME}_{LOSS_BOUND}" + fext = ".csv" + if save_train: + fname_train = fname + "_train" + fext + save_path = os.path.join(utils_path, fname_train) + print(f"Saving to: {save_path}") + full_eval_train.to_pickle(save_path) + + if save_test: + fname_test = fname + "_test" + fext + save_path = os.path.join(utils_path, fname_test) + print(f"Saving to: {save_path}") + full_eval_test.to_pickle(save_path) + + +# helper function to construct pairwise constraints for every combination of provided groups +def construct_constraints( + constraint_fn, + bound, + dataset, + constraint_groups, + batch_size, + add_negative, + device, + seed, + max_0 = False +): + c = [] + + for group_indices in constraint_groups: + for group_idx in combinations(group_indices, 2): + c1 = FairnessConstraint( + dataset, + group_idx, + fn=lambda net, d: torch.max(constraint_fn(net, d) - bound, torch.zeros(1)) if max_0 else constraint_fn(net, d) - bound, + batch_size=batch_size // 2, + device=device, + seed=seed, + ) + c.append(c1) + + if add_negative: + c2 = FairnessConstraint( + dataset, + group_idx, + fn=lambda net, d: torch.max(-constraint_fn(net, d) - bound, torch.zeros(1)) if max_0 else -constraint_fn(net, d) - bound, + batch_size=batch_size // 2, + device=device, + seed=seed, + ) + c.append(c2) + + return c + +# helper function to calculate relevant values on full dataset (e.g. constraint gradient, AL function, etc) +# used to calculate those values at different points during algorithms run +def calculate_iteration_values( + alg, + full_eval, + index_to_save, + c, + loss_fn, + data_f, + data_c, + net, + device, + add_negative, + **params, +): + c_val_vec, c_grads_mat = [], [] + + for i, c_i in enumerate(c): + cv = c_i.eval(net, data_c[i // 2 if add_negative else i]) + c_val_vec.append(cv) + cv.backward() + cg = net_grads_to_tensor(net, flatten=True, device=device) + net.zero_grad() + c_grads_mat.append(cg) + c_val_vec = torch.tensor(c_val_vec) + c_grads_mat = torch.stack(c_grads_mat) + full_eval.loc[*index_to_save]["c"] = [c_val_vec.detach().cpu().numpy()] + full_eval.loc[*index_to_save]["cg"] = [c_grads_mat.detach().cpu().numpy()] + + X_tensor, y_tensor = data_f + outs = net(X_tensor) + if y_tensor.ndim < outs.ndim: + y_tensor = y_tensor.unsqueeze(1) + loss = loss_fn(outs, y_tensor) + loss.backward() + fg = net_grads_to_tensor(net, flatten=True, device=device) + net.zero_grad() + + full_eval.loc[*index_to_save]["f"] = loss.detach().cpu().numpy() + full_eval.loc[*index_to_save]["fg"] = [fg.detach().cpu().numpy()] + + # if alg.lower() == "sgd": + # return + + # elif alg.lower() == "sslalm": + # x_t, z, rho, mu, lambdas = ( + # params["x_t"], + # params["z"], + # params["rho"], + # params["mu"], + # params["lambdas"], + # ) + # G = ( + # fg + # + c_grads_mat.T @ lambdas + # + rho * (c_grads_mat.T @ c_val_vec) + # + mu * (x_t - z) + # ) + + # full_eval.loc[*index_to_save]["G"] = [G.detach().cpu().numpy()] + + +def sample_or_restart_iterloader(loader): + try: + item = next(loader) + return item + except StopIteration: + loader._reset(loader) + # loader.gen + item = next(loader) + return item + + +if __name__ == "__main__": + run() \ No newline at end of file diff --git a/experiments/utils/load_folktables.py b/experiments/utils/load_folktables.py index 4da965a..c168f66 100644 --- a/experiments/utils/load_folktables.py +++ b/experiments/utils/load_folktables.py @@ -1,119 +1,160 @@ import os +import folktables import numpy as np from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler +from folktables import ( + ACSDataSource, + ACSEmployment, + ACSIncome, + ACSPublicCoverage, + generate_categories, +) +import torch # sys.path.append("..") -from folktables import (ACSDataSource, ACSEmployment, ACSIncome, - ACSPublicCoverage, generate_categories) + +ACSIncomeSex = folktables.BasicProblem( + features=ACSIncome.features, + target="PINCP", + target_transform=lambda x: x > 50000, + group="SEX", + preprocess=folktables.adult_filter, + postprocess=lambda x: np.nan_to_num(x, -1), +) RAC1P_WHITE = 1 + def download_folktables( state="AL", - horizon='1-Year', - survey='person', + horizon="1-Year", + survey="person", year=2018, download=False, - path=None,): - - if path is None: - base_dir = os.path.abspath( - os.path.join(os.path.dirname(__file__), "raw_data") - ) - else: - base_dir = path - - data_dir = os.path.join(base_dir, str(year), horizon) - if not os.path.isdir(data_dir): - os.makedirs(data_dir) - - data_source = ACSDataSource( + path=None, +): + if path is None: + base_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "raw_data")) + else: + base_dir = path + + data_dir = os.path.join(base_dir, str(year), horizon) + if not os.path.isdir(data_dir): + os.makedirs(data_dir) + + data_source = ACSDataSource( survey_year=year, horizon=horizon, survey=survey, root_dir=base_dir - ) - - definition_df = data_source.get_definitions(download=download) - acs_data = data_source.get_data(states=[state], download=download) - - return acs_data, definition_df + ) + + definition_df = data_source.get_definitions(download=download) + acs_data = data_source.get_data(states=[state], download=download) -def prepare_folktables( + return acs_data, definition_df + +def prepare_folktables_multattr( dataset: str = "income", state="AL", - horizon='1-Year', - survey='person', + horizon="1-Year", + survey="person", year=2018, random_state=None, onehot=True, - make_unbalanced=False, download=False, path=None, + sens_cols=["RAC1P", "SEX"], + binarize=[False, False], + binarize_values=None, + stratify=False, ): - acs_data, definition_df = download_folktables(state, horizon, survey, year, download, path) - - # group here refers to race (RAC1P) + acs_data, definition_df = download_folktables( + state, horizon, survey, year, download, path + ) + if dataset == "employment": features, label, group = ACSEmployment.df_to_numpy(acs_data) - # drop the RAC1P column - features = features[:, :-1] elif dataset == "coverage": features, label, group = ACSPublicCoverage.df_to_numpy(acs_data) elif dataset == "income": - if onehot: - categories = generate_categories( - features=ACSIncome.features, definition_df=definition_df - ) - features, label, group = ACSIncome.df_to_pandas( - acs_data, categories=categories, dummies=True - ) - sens_features = [col for col in features.columns if col.startswith("RAC1P")] - features = features.drop(columns=sens_features).to_numpy(dtype="float") - label = label.to_numpy(dtype="float") - else: - features, label, group = ACSIncome.df_to_numpy(acs_data) - # drop the RAC1P column - features = features[:, :-1] - - # drop sensitive - group_binary = (group == RAC1P_WHITE).astype(float) - - # stratify by binary race (white vs rest) - X_train, X_test, y_train, y_test, g_train, g_test = train_test_split( - features, + features, label, _ = ACSIncome.df_to_pandas(acs_data) + + for i, c in enumerate(sens_cols): + if binarize[i]: + features[c] = features[c].apply(lambda x: int(x == binarize[i])) + + # group membership (by combination of values of every sensitive attribute) + sensitive_groups = features[sens_cols].apply( + lambda x: "_".join([str(int(v)) for v in x[sens_cols]]), axis=1 + ) + + sensitive_groups_onehot = torch.zeros(size=(len(features), len(sensitive_groups.unique()))) + group_codes = [] + + for gn, x in enumerate(sensitive_groups.unique()): + group_codes.append(gn) + sensitive_groups_onehot[sensitive_groups == x, gn] = 1. + + # groups defined by sensitive attributes separately + separate_sensitive_groups = [features[col].to_numpy() for col in sens_cols] + + features_desens = features.drop(sens_cols, axis=1).to_numpy() + label = label.to_numpy().flatten() + sensitive_groups = sensitive_groups.to_numpy() + + X_train, X_test, y_train, y_test, group_train, group_test, group_onehot_train, group_onehot_test = train_test_split( + features_desens, label, - group_binary, + sensitive_groups, + sensitive_groups_onehot, test_size=0.2, - stratify=group_binary, + stratify=sensitive_groups if stratify else None, random_state=random_state, ) - if make_unbalanced: - # g_train_new = g_train[:len(g_train)/2] - train_w_idx = np.argwhere(g_train == 1).flatten() - train_nw_idx = np.argwhere(g_train != 1).flatten() - train_nw_idx = train_nw_idx[: len(train_nw_idx) // 10] - idx = np.concatenate([train_w_idx, train_nw_idx]) - X_train = X_train[idx] - y_train = y_train[idx] - g_train = g_train[idx] + sep_sens_train = [] + sep_sens_test = [] + for gr in separate_sensitive_groups: + s_train, s_test = train_test_split( + gr, + test_size=0.2, + stratify=sensitive_groups if stratify else None, + random_state=random_state, + ) + sep_sens_train.append( + [np.argwhere(s_train == sens_val).flatten() for sens_val in np.unique(gr)] + ) + sep_sens_test.append( + [np.argwhere(s_test == sens_val).flatten() for sens_val in np.unique(gr)] + ) scaler = StandardScaler() X_train_scaled = scaler.fit_transform(X_train) X_test_scaled = scaler.transform(X_test) - train_w_idx = np.argwhere(g_train == 1).flatten() - train_nw_idx = np.argwhere(g_train != 1).flatten() + group_indices_train = [ + np.argwhere(group_train == sens_val).flatten() + for sens_val in np.unique(sensitive_groups) + ] + group_indices_test = [ + np.argwhere(group_test == sens_val).flatten() + for sens_val in np.unique(sensitive_groups) + ] - test_w_idx = np.argwhere(g_test == 1).flatten() - test_nw_idx = np.argwhere(g_test != 1).flatten() + group_order = np.unique(sensitive_groups) + # separate_group_indices = [separate_sensitive_groups return ( X_train_scaled, y_train, - [train_w_idx, train_nw_idx], + group_indices_train, + group_onehot_train, + sep_sens_train, X_test_scaled, y_test, - [test_w_idx, test_nw_idx], - ) + group_indices_test, + sep_sens_test, + group_onehot_test, + group_order + ) \ No newline at end of file diff --git a/experiments/utils/plotting.py b/experiments/utils/plotting.py index f53e10f..a005992 100644 --- a/experiments/utils/plotting.py +++ b/experiments/utils/plotting.py @@ -7,6 +7,74 @@ def getRoundedThresholdv1(a, round_step): return np.round(a / round_step) * round_step +def plot_qmeans(data, plot_col, group_by_col, q1=0.25, q2=0.75, ax=None, **kwargs): + q3 = 0.5 + means = data.groupby(group_by_col)[plot_col].mean() # .reset_index(drop=True) + q_lower = data.groupby(by=group_by_col)[plot_col].quantile( + q=q1, interpolation="lower" + ) # .reset_index(drop=True) + q_mid = data.groupby(by=group_by_col)[plot_col].quantile( + q=q3, interpolation="linear" + ) # .reset_index(drop=True) + q_higher = data.groupby(by=group_by_col)[plot_col].quantile( + q=q2, interpolation="higher" + ) # .reset_index(drop=True) + + return_fig = ax is None + if ax is None: + f = plt.figure() + ax = f.add_subplot(1, 2, 1) + + ax.fill_between(x=means.index, y1=q_lower, y2=q_higher, alpha=0.4) + ax.plot(q_lower, label=f"Q{int(q1 * 100)}", c="black", lw=0.5) + ax.plot(q_higher, label=f"Q{int(q2 * 100)}", c="black", lw=0.5) + ax.plot(q_mid, label="Median", c="darkorange", lw=0.5) + ax.plot(means, label="Mean") + xt = ax.get_xticks() + xt_ind = xt[1:-1] - 1 + xt_ind[0] = 0 + ax.legend() + + if return_fig: + return f + + +def plot_sep( + data, plot_col, x_col, idx_col, q1=0.25, q2=0.75, idx_is_index=False, ax=None, **kwargs +): + # q3 = 0.5 + # means = data.groupby(group_by_col)[plot_col].mean()#.reset_index(drop=True) + # q_lower = data.groupby(by=group_by_col)[plot_col].quantile(q=q1, interpolation="lower")#.reset_index(drop=True) + # q_mid = data.groupby(by=group_by_col)[plot_col].quantile(q=q3, interpolation="linear")#.reset_index(drop=True) + # q_higher = data.groupby(by=group_by_col)[plot_col].quantile(q=q2, interpolation="higher")#.reset_index(drop=True) + + return_fig = ax is None + if ax is None: + f = plt.figure() + ax = f.add_subplot(1, 2, 1) + + plot_lines = ( + [ + data.loc[data.index.get_level_values(idx_col) == i] + for i in data.index.get_level_values(idx_col).unique() + ] + if idx_is_index + else [data[data[idx_col] == i] for i in data[idx_col].unique()] + ) + + # colors = kwargs.pop('colors') + for to_plot in plot_lines: + ax.plot(to_plot[x_col].to_numpy(), to_plot[plot_col].to_numpy(), **kwargs) + + xt = ax.get_xticks() + xt_ind = xt[1:-1] - 1 + xt_ind[0] = 0 + ax.legend() + + if return_fig: + return f + + def plot_iter( data, lb, @@ -15,7 +83,7 @@ def plot_iter( q2=0.75, f_ylim=(0, 0.75), c_ylim=(-0.01, 0.01), - w = 14 + w=14, ): # save=False, dataset_name=None): q1 = q1 q2 = q2 @@ -28,13 +96,14 @@ def plot_iter( f = plt.figure() - ax1 = f.add_subplot(1,2,1) + ax1 = f.add_subplot(1, 2, 1) ax1.fill_between(x=means.index, y1=q_lower["Loss"], y2=q_higher["Loss"], alpha=0.4) ax1.plot(q_lower["Loss"], label=f"Q{int(q1 * 100)}", c="black", lw=0.6) ax1.plot(q_higher["Loss"], label=f"Q{int(q2 * 100)}", c="black", lw=0.6) ax1.plot(q_mid["Loss"], label="Median", c="darkorange", lw=0.6) ax1.plot(means["Loss"], label="Mean") + ax1.set_ylim(f_ylim) xt = ax1.get_xticks() xt_ind = xt[1:-1] - 1 xt_ind[0] = 0 @@ -49,13 +118,14 @@ def plot_iter( # f.savefig('C:/Users/andre/docs/plots/sslalm/income_race/loss # f_ = plt.figure() - ax2 = f.add_subplot(1,2,2) + ax2 = f.add_subplot(1, 2, 2) ax2.fill_between(x=means.index, y1=q_lower["C1"], y2=q_higher["C1"], alpha=0.4) ax2.plot(q_lower["C1"], ls="-", label=f"Q{int(q1 * 100)}", c="black", lw=0.6) ax2.plot(q_higher["C1"], ls="-", label=f"Q{int(q2 * 100)}", c="black", lw=0.6) ax2.plot(q_mid["C1"], label="Median", c="darkorange") ax2.plot(means["C1"], label="Mean") + ax2.set_ylim(c_ylim) ax2.set_xlabel("Iteration") # ax2.set_ylim(bottom=-0.02, top=0.02) @@ -73,16 +143,26 @@ def plot_iter( ) ax2.set_ylabel("$L_w-L_b$") ax2.legend() - + f.set_figwidth(w) f.tight_layout() return f -def plot_trajectories(data, lb, x_axis, alpha=0.5, lw=1, legend=True, w=14): +def plot_trajectories( + data, + lb, + x_axis, + alpha=0.5, + lw=1, + legend=True, + w=14, + f_ylim=(0.4, 0.77), + c_ylim=(-0.12, 0.12), +): f = plt.figure() - ax1 = f.add_subplot(1,2,1) - ax2 = f.add_subplot(1,2,2) + ax1 = f.add_subplot(1, 2, 1) + ax2 = f.add_subplot(1, 2, 2) for EXP_NUM in data["trial"].unique(): traj = data[data["trial"] == EXP_NUM] if x_axis == "time": @@ -97,7 +177,8 @@ def plot_trajectories(data, lb, x_axis, alpha=0.5, lw=1, legend=True, w=14): continue ax1.plot(x, traj["Loss"], label="Loss - trial {EXP_NUM}", alpha=_a, lw=lw) ax2.plot(x, traj["C1"], label=f"C1 - trial {EXP_NUM}", alpha=_a, lw=lw) - + ax1.set_ylim(f_ylim) + ax2.set_ylim(c_ylim) ax1.set_xlabel("iteration" if x_axis == "iteration" else "time, s") # ax1.set_ybound(0, 1) ax2.set_xlabel("iteration" if x_axis == "iteration" else "time, s") @@ -118,10 +199,43 @@ def plot_trajectories(data, lb, x_axis, alpha=0.5, lw=1, legend=True, w=14): f.set_figwidth(w) return f +def groupby_time( + data, + round_step, + fill="bfill", + fill_limit=None, +): + data["time_r"] = getRoundedThresholdv1(data["time"], round_step) + + time_step_idx = pd.Index(np.arange(0, max(data["time_r"]), step=round_step)) + + trials = [] + + for EXP_NUM in data["trial"].unique(): + trial_stats = data[data["trial"] == EXP_NUM] + # trial_stats.index = trial_stats["time_r"] + # trial_stats = trial_stats.reindex(time_step_idx, copy=True) + # trial_stats["time_r"] = trial_stats.index + if fill == "bfill": + trial_stats.bfill(inplace=True, limit=fill_limit) + elif fill == "ffill": + trial_stats.ffill(inplace=True, limit=fill_limit) + else: + trial_stats.interpolate(fill, inplace=True, limit_direction="forward") + trials.append(trial_stats) + + trials = pd.concat(trials, ignore_index=True) + trials_gr = trials.groupby("time_r") + + return trials_gr + def plot_time( data, - lb, + cb, + loss_col, + c_col, + two_sided=False, round_step=0.5, fill="bfill", fill_limit=None, @@ -129,7 +243,10 @@ def plot_time( q2=0.75, f_ylim=(0.4, 0.75), c_ylim=(-0.06, 0.07), - w = 14 + w=14, + add_lb=True, + sep_figs=False, + plot_loss=True, ): q3 = 0.5 @@ -140,10 +257,10 @@ def plot_time( trials = [] for EXP_NUM in data["trial"].unique(): - trial_stats = data[data["trial"] == EXP_NUM] - trial_stats.index = trial_stats["time_r"] - trial_stats = trial_stats.reindex(time_step_idx, copy=True) - trial_stats["time_r"] = trial_stats.index + trial_stats = data[data["trial"] == EXP_NUM][[c_col, loss_col, "time_r"]] + # trial_stats.index = trial_stats["time_r"] + # trial_stats = trial_stats.reindex(time_step_idx, copy=True) + # trial_stats["time_r"] = trial_stats.index if fill == "bfill": trial_stats.bfill(inplace=True, limit=fill_limit) elif fill == "ffill": @@ -168,58 +285,80 @@ def plot_time( f = plt.figure() # f.set_figwidth() - - ax1 = f.add_subplot(1,2,1) - - ax1.fill_between(x=means.index, y1=q_lower["Loss"], y2=q_higher["Loss"], alpha=0.4) - ax1.plot(q_lower["Loss"], label=f"Q{int(q1 * 100)}", c="black", lw=0.6) - ax1.plot(q_higher["Loss"], label=f"Q{int(q2 * 100)}", c="black", lw=0.6) - ax1.plot(q_mid["Loss"], label="Median", c="darkorange") - ax1.plot(means["Loss"], label="Mean") - ax1.set_ylim(bottom=f_ylim[0], top=f_ylim[1]) - - xt = ax1.get_xticks() - xt_ind = xt[1:-1] - 1 - xt_ind[0] = 0 - # ax1.set_xticks(means['SampleSize'].cumsum()[xt_ind]) - # ax1.set_xticklabels(labels=np.round(means['SampleSize'].cumsum()[xt_ind], 0), rotation=45) - - ax1.set_xlabel("time, s") - ax1.set_ylabel("Loss") - ax1.legend() + if plot_loss: + ax1 = f.add_subplot(1, 2, 1) + + ax1.fill_between( + x=means.index, y1=q_lower[loss_col], y2=q_higher[loss_col], alpha=0.4 + ) + ax1.plot(q_lower[loss_col], label=f"Q{int(q1 * 100)}", c="black", lw=0.6) + ax1.plot(q_higher[loss_col], label=f"Q{int(q2 * 100)}", c="black", lw=0.6) + ax1.plot(q_mid[loss_col], label="Median", c="darkorange", lw=0.5) + ax1.plot(means[loss_col], label="Mean", lw=0.5) + ax1.set_ylim(bottom=f_ylim[0], top=f_ylim[1]) + + xt = ax1.get_xticks() + xt_ind = xt[1:-1] - 1 + xt_ind[0] = 0 + + ax1.set_xlabel("time, s") + ax1.set_ylabel("Loss") + ax1.legend() # f_ = plt.figure() - ax2 = f.add_subplot(1,2,2) + if sep_figs: + f_ = plt.figure() + else: + f_ = f + ax2 = f_.add_subplot(1, 2, 2) + ax2.hlines(y=0, xmin=0, xmax=max(means.index), ls="--", colors="black", alpha=0.5) - ax2.fill_between(x=means.index, y1=q_lower["C1"], y2=q_higher["C1"], alpha=0.4) - ax2.plot(q_lower["C1"], ls="-", label=f"Q{int(q1 * 100)}", c="black", lw=0.6) - ax2.plot(q_higher["C1"], ls="-", label=f"Q{int(q2 * 100)}", c="black", lw=0.6) - ax2.plot(q_mid["C1"], label="Median", c="darkorange") - ax2.plot(means["C1"], label="Mean") + if add_lb: + q_lower[c_col] += cb + q_higher[c_col] += cb + q_mid[c_col] += cb + means[c_col] += cb + + ax2.fill_between(x=means.index, y1=q_lower[c_col], y2=q_higher[c_col], alpha=0.5) + ax2.plot(q_lower[c_col], ls="-", label=f"Q{int(q1 * 100)}", c="black", lw=0.5) + ax2.plot(q_higher[c_col], ls="-", label=f"Q{int(q2 * 100)}", c="black", lw=0.5) + ax2.plot(q_mid[c_col], label="Median", c="darkorange", lw=0.5) + ax2.plot(means[c_col], label="Mean", lw=0.5) + + if two_sided: + ax2.set_ylim(bottom=c_ylim[0], top=c_ylim[1]) + ax2.hlines( + y=[-cb, cb], + xmin=0, + xmax=max(means.index), + ls="--", + colors="blue", + alpha=0.5, + label="Constraint bound", + ) + else: + ax2.set_ylim(bottom=0, top=c_ylim[1]) + ax2.hlines( + y=cb, + xmin=0, + xmax=max(means.index), + ls="--", + colors="blue", + alpha=0.5, + label="Constraint bound", + ) ax2.set_xlabel("time, s") # ax2.set_ylim(bottom=-0.02, top=0.02) - ax2.hlines( - y=[-lb, lb], - xmin=0, - xmax=max(means.index), - ls="--", - colors="blue", - alpha=0.5, - label="Constraint bound", - ) - ax2.hlines(y=0, xmin=0, xmax=max(means.index), ls="--", colors="black", alpha=0.5) - ax2.set_ylabel("$L_w-L_b$") + ax2.set_ylabel("C") ax2.legend() - ax2.set_ylim(bottom=c_ylim[0], top=c_ylim[1]) f.set_figwidth(w) + f_.set_figwidth(w) - return f#, f_ - - + return (f, f_) if sep_figs else f -def spider_line(data, title=None): +def spider_line(data, yticks, title=None): plt.rcParams.update({"font.size": 16}) labels = ["Ind", "Sep", "Ina", "Suf"] @@ -241,7 +380,7 @@ def spider_line(data, title=None): values = data.loc[alg, ["Ind", "Sp", "Ina", "Sf", "Ind"]].tolist() ax.plot(angles, values, lw=2, label=alg) # ax.plot(angles, values, lw=2, label=alg) - ax.set_yticks([0, 0.1, 0.2, 0.3]) + ax.set_yticks(yticks) plt.thetagrids(np.degrees(angles), labels=labels) if title: diff --git a/experiments/utils/run_sgd.py b/experiments/utils/run_sgd.py deleted file mode 100644 index ebe70e5..0000000 --- a/experiments/utils/run_sgd.py +++ /dev/null @@ -1 +0,0 @@ -### util file to run the Stochastic Gradient Descent diff --git a/experiments/utils/stats.py b/experiments/utils/stats.py index 3ca7f0a..7511fd6 100644 --- a/experiments/utils/stats.py +++ b/experiments/utils/stats.py @@ -3,16 +3,16 @@ import pandas as pd import torch from fairret.statistic import * -from sklearn.metrics import auc, roc_curve +from sklearn.metrics import auc, roc_curve, accuracy_score -from src.constraints.constraint_fns import * +from humancompatible.train.fairness.constraints.constraint_fns import * def fair_stats(p_1, y_1, p_2, y_2): - ''' + """ Compute Independence, Separation, Inaccuracy, Sufficiency. - ''' - p = torch.concat([torch.tensor(p_1), torch.tensor(p_2)]).unsqueeze(1) + """ + p = torch.concat([torch.tensor(p_1), torch.tensor(p_2)]) w_onehot = torch.tensor([[0.0, 1.0]] * len(p_1)) b_onehot = torch.tensor([[1.0, 0.0]] * len(p_2)) sens = torch.vstack([w_onehot, b_onehot]) @@ -25,69 +25,133 @@ def fair_stats(p_1, y_1, p_2, y_2): acc0, acc1 = Accuracy()(p, sens, labels) ppv0, ppv1 = PositivePredictiveValue()(p, sens, labels) fomr0, fomr1 = FalseOmissionRate()(p, sens, labels) - npv0, npv1 = 1 - fomr0, 1 - fomr1 + # npv0, npv1 = 1 - fomr0, 1 - fomr1 + + predictions = (p_1 >= 0.5).astype(float).flatten() + tpr = (predictions @ y_1) / sum(y_1) + tnr = ((-1*predictions + 1) @ (-1*y_1 + 1)) / sum(-1*y_1+1) + fpr = 1-tnr + fnr = 1 - tpr ind = abs(pr0 - pr1) sp = abs(tpr0 - tpr1) + abs(fpr0 - fpr1) - ina = sum(np.concatenate([p_1, p_2]) != np.concatenate([y_1, y_2])) / ( + ina = sum(np.concatenate([p_1, p_2]).flatten() != np.concatenate([y_1, y_2])) / ( len(p_1) + len(p_2) ) - sf = abs(ppv0 - ppv1) + abs(npv0 - npv1) - return ind, sp, ina, sf + sf = abs(ppv0 - ppv1) + abs(fomr0 - fomr1) + return ind, sp, ina, sf, tpr0, tpr1 + + +@torch.inference_mode() +def make_groupwise_stats_table(X, y, loaded_models, full_preds=None): + results_list = [] + criterion = torch.nn.BCEWithLogitsLoss() + + for model_index, model_iter in enumerate(loaded_models): + (model_name, model) = model_iter + + alg = str.join("", model_name.split("_trial")[:-1]) + predictions = model(X) + y = y.squeeze().to(float) + predictions = predictions.squeeze() + loss = criterion(predictions.squeeze(), y).cpu().numpy() + predictions = torch.nn.functional.sigmoid(predictions) + fpr, tpr, thresholds = roc_curve( + y.cpu().numpy(), predictions.cpu().numpy() + ) + auc_score = auc(fpr, tpr) + acc = accuracy_score(y_pred = predictions > 0.5, y_true = y) + tpr_fairret = TruePositiveRate()(predictions.unsqueeze(1), None, y.unsqueeze(1)) + pr_fairret = PositiveRate()(predictions.unsqueeze(1), None) + predictions = (predictions >= 0.5).to(float) + tpr = (predictions @ y) / sum(y) + tnr = ((-1*predictions + 1) @ (-1*y + 1)) / sum(-1*y+1) + fpr = 1-tnr + fnr = 1 - tpr + + ppv = tpr / (tpr+fpr) + fomr = fnr / (tnr + fnr) + pr = sum(predictions)/len(predictions) + + results_list.append( + { + "Model": str(model_name), + "Algorithm": alg, + "acc": acc, + "auc": auc_score, + "fpr": fpr, + "tpr_fairret": tpr_fairret, + "tpr": tpr, + "ppv": ppv, + "fomr": fomr, + "pr": pr, + "pr_fairret": pr_fairret + } + ) + return pd.DataFrame(results_list) + + # make table of "deviation from overall rate" @torch.inference_mode() -def make_model_stats_table(X_w, y_w, X_nw, y_nw, loaded_models): +def make_pairwise_constraint_stats_table(X_0, y_0, X_1, y_1, loaded_models): results_list = [] loss_fn = torch.nn.BCEWithLogitsLoss() for model_index, model_iter in enumerate(loaded_models): (model_name, model) = model_iter - # else: - alg = model_name - predictions_0 = model(X_w) - predictions_1 = model(X_nw) + alg = str.join("", model_name.split("_trial")[:-1]) + predictions_0 = model(X_0) + predictions_1 = model(X_1) if torch.any(torch.isnan(predictions_0)) or torch.any( torch.isnan(predictions_1) ): print(f"skipped {model_name}") continue - y_w = y_w.squeeze() - y_nw = y_nw.squeeze() - l_0 = loss_fn(predictions_0[:, 0], y_w).cpu().numpy() - l_1 = loss_fn(predictions_1[:, 0], y_nw).cpu().numpy() - predictions_0 = torch.nn.functional.sigmoid(predictions_0[:, 0]) - predictions_1 = torch.nn.functional.sigmoid(predictions_1[:, 0]) + y_0 = y_0.squeeze() + y_1 = y_1.squeeze() + l_0 = loss_fn(predictions_0.squeeze(), y_0).cpu().numpy() + l_1 = loss_fn(predictions_1.squeeze(), y_1).cpu().numpy() + predictions_0 = torch.nn.functional.sigmoid(predictions_0) + predictions_1 = torch.nn.functional.sigmoid(predictions_1) # Calculate AUCs for sensitive attribute 0 fpr_0, tpr_0, thresholds_0 = roc_curve( - y_w.cpu().numpy(), predictions_0.cpu().numpy() + y_0.cpu().numpy(), predictions_0.cpu().numpy() ) auc_0 = auc(fpr_0, tpr_0) # Calculate AUCs for sensitive attribute 1 fpr_1, tpr_1, thresholds_1 = roc_curve( - y_nw.cpu().numpy(), predictions_1.cpu().numpy() + y_1.cpu().numpy(), predictions_1.cpu().numpy() ) auc_1 = auc(fpr_1, tpr_1) auc_hm = (auc_0 * auc_1) / (auc_0 + auc_1) auc_m = (auc_0 + auc_1) / 2 + # Calculate TPR-FPR difference for sensitive attribute 0 - tpr_minus_fpr_0 = tpr_0 - fpr_0 - optimal_threshold_index_0 = np.argmax(tpr_minus_fpr_0) - optimal_threshold_0 = thresholds_0[optimal_threshold_index_0] + # tpr_minus_fpr_0 = tpr_0 - fpr_0 + # optimal_threshold_index_0 = np.argmax(tpr_minus_fpr_0) + # optimal_threshold_0 = thresholds_0[optimal_threshold_index_0] - # Calculate TPR-FPR difference for sensitive attribute 1 - tpr_minus_fpr_1 = tpr_1 - fpr_1 - optimal_threshold_index_1 = np.argmax(tpr_minus_fpr_1) - optimal_threshold_1 = thresholds_1[optimal_threshold_index_1] + # # Calculate TPR-FPR difference for sensitive attribute 1 + # tpr_minus_fpr_1 = tpr_1 - fpr_1 + # optimal_threshold_index_1 = np.argmax(tpr_minus_fpr_1) + # optimal_threshold_1 = thresholds_1[optimal_threshold_index_1] p_0_np = (predictions_0 > 0.5).cpu().numpy() p_1_np = (predictions_1 > 0.5).cpu().numpy() - y_w_np = y_w.cpu().numpy() - y_nw_np = y_nw.cpu().numpy() + y_w_np = y_0.cpu().numpy() + y_nw_np = y_1.cpu().numpy() - ind, sp, ina, sf = fair_stats(p_0_np, y_w_np, p_1_np, y_nw_np) + ind, sp, ina, sf, tpr0, tpr1 = fair_stats(p_0_np, y_w_np, p_1_np, y_nw_np) + + acc_0 = accuracy_score( + y_true=y_0, y_pred=np.array([y > 0.5 for y in predictions_0]) + ) + acc_1 = accuracy_score( + y_true=y_1, y_pred=np.array([y > 0.5 for y in predictions_1]) + ) a0, x0 = np.histogram(predictions_0, bins=50) a1, x1 = np.histogram(predictions_1, bins=x0) @@ -108,36 +172,20 @@ def make_model_stats_table(X_w, y_w, X_nw, y_nw, loaded_models): "Sf": sf, "Wd": wd, "|Loss_0 - Loss_1|": abs(l_0 - l_1), + "|TPR_0 - TPR_1|": abs(tpr0 - tpr1), + "acc_diff": abs(acc_0 - acc_1), } ) res_df = pd.DataFrame(results_list) return res_df -# def get_alg_name(alg: str): -# if alg.startswith("swsg"): -# return "Switching Subgradient" -# elif alg.startswith("sgd"): -# return "SGD" -# elif alg.startswith("sg"): -# return "Stochastic Ghost" -# elif alg.startswith("sslalm_mu0"): -# return "ALM" -# elif alg.startswith("sslalm"): -# return "SSL-ALM" -# elif alg.startswith("fairret"): -# return "SGD + Fairret" - -def aggregate_model_stats_table(table: pd.DataFrame, agg_fns): + +def aggregate_model_stats_table(table: pd.DataFrame, agg_fns, agg_cols="Algorithm"): if len(agg_fns) == 1 and not isinstance(agg_fns, str): - df = ( - table.drop("Model", axis=1) - .groupby("Algorithm") - .agg(agg_fns[0]) - .sort_index() - ) + df = table.drop("Model", axis=1).groupby(agg_cols).agg(agg_fns[0]).sort_index() else: - df = table.drop("Model", axis=1).groupby("Algorithm").agg(agg_fns) + df = table.drop("Model", axis=1).groupby(agg_cols).agg(agg_fns) df["Algname"] = df.apply(lambda row: row.name, axis=1) df["Algname"] = pd.Categorical( diff --git a/humancompatible/__init__.py b/humancompatible/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/humancompatible/train/__init__.py b/humancompatible/train/__init__.py new file mode 100644 index 0000000..6ad021c --- /dev/null +++ b/humancompatible/train/__init__.py @@ -0,0 +1,3 @@ +# from .algorithms, .constraints + +__all__ = ["algorithms", "constraints"] diff --git a/humancompatible/train/algorithms/__init__.py b/humancompatible/train/algorithms/__init__.py new file mode 100644 index 0000000..c87c362 --- /dev/null +++ b/humancompatible/train/algorithms/__init__.py @@ -0,0 +1,4 @@ +from .ssl_alm import SSLALM +from .ssw import SSG + +__all__ = ["SSLALM", "SSG"] diff --git a/humancompatible/train/algorithms/ssl_alm.py b/humancompatible/train/algorithms/ssl_alm.py new file mode 100644 index 0000000..5ef0b44 --- /dev/null +++ b/humancompatible/train/algorithms/ssl_alm.py @@ -0,0 +1,212 @@ +from typing import Iterable, Optional, Union + +import torch +from torch import Tensor + +from torch.optim.optimizer import Optimizer, _use_grad_for_differentiable + +class SSLALM(Optimizer): + def __init__( + self, + params, + m: int, + # tau in paper + lr: Union[float, Tensor] = 5e-2, + # eta in paper + dual_lr: Union[ + float, Tensor + ] = 5e-2, # keep as tensor for different learning rates for different constraints in the future? idk + dual_bound : Union[ + float, Tensor + ] = 100, + # penalty term multiplier + rho: float = 1.0, + # smoothing term multiplier + mu: float = 2.0, + # smoothing term update multiplier + beta: float = 0.5, + *, + init_dual_vars: Optional[Tensor] = None, + # whether some of the dual variables should not be updated + fix_dual_vars: Optional[Tensor] = None, + differentiable: bool = False, + # custom_project_fn: Optional[Callable] = project_fn + ): + if isinstance(lr, torch.Tensor) and lr.numel() != 1: + raise ValueError("Tensor lr must be 1-element") + if isinstance(dual_lr, torch.Tensor) and lr.numel() != 1: + raise ValueError("Tensor dual_lr must be 1-element") + if lr < 0.0: + raise ValueError(f"Invalid learning rate: {lr}") + if dual_lr < 0.0: + raise ValueError(f"Invalid dual learning rate: {dual_lr}") + if init_dual_vars is not None and len(init_dual_vars) != m: + raise ValueError( + f"init_dual_vars should be of length m: expected {m}, got {len(init_dual_vars)}" + ) + if fix_dual_vars is not None: + raise NotImplementedError() + if init_dual_vars is None and fix_dual_vars is not None: + raise ValueError( + f"if fix_dual_vars is not None, init_dual_vars should not be None." + ) + + if differentiable: + raise NotImplementedError("TorchSSLALM does not support differentiable") + + defaults = dict( + lr=lr, + dual_lr=dual_lr, + rho=rho, + mu=mu, + beta=beta, + differentiable=differentiable, + # custom_project_fn=custom_project_fn + ) + + super().__init__(params, defaults) + + # self.param_groups.append() + + self.m = m + self.dual_lr = dual_lr + self.dual_bound = dual_bound + self.rho = rho + self.beta = beta + self.mu = mu + self.c_vals: list[Union[float, Tensor]] = [] + self._c_val_average = [None] + # essentially, move everything here to self.state[param_group] + # self.state[param_group]['smoothing_avg'] <= z for that param_group; + # ...['grad'] <= grad w.r.t. that param_group + # ...['G'] <= G w.r.t. that param_group // idk if necessary + # ...['c_grad'][c_i] <= grad of ith constraint w.r.t. that group= self.dual_bound or self._dual_vars[i] < 0: + self._dual_vars[i].zero_() + + # save constraint grad + for group in self.param_groups: + params: list[Tensor] = [] + grads: list[Tensor] = [] + c_grads: list[Tensor] = [] + smoothing: list[Tensor] = [] + _ = self._init_group(group, params, grads, c_grads, smoothing) + + for p in group["params"]: + state = self.state[p] + # state['c_grad'] is cleaned in step() + # so it is always empty on dual_step() + state["c_grad"].append(p.grad) + + @_use_grad_for_differentiable + def step(self, c_val: Union[Iterable | Tensor] = None): + r"""Perform an update of the primal parameters (network weights & slack variables). To be called AFTER :func:`dual_step` in an iteration! + + Args: + c_val (Tensor): an Iterable of estimates of values of **ALL** constraints; used for primal parameter update. + Ideally, must be evaluated on an independent sample from the one used in :func:`dual_step` + """ + + if c_val is None: + c_val = self.c_vals + if isinstance(c_val, Iterable) and not isinstance(c_val, torch.Tensor): + # if len(c_val) == 1 and isinstance(c_val[0], torch.Tensor): + # c_val = c_val[0] + # else: + c_val = torch.stack(c_val) + if c_val.ndim > 1: + c_val = c_val.squeeze(-1) + + if c_val.numel() != self.m: + raise ValueError(f"Number of elements in c_val must be equal to m={self.m}, got {c_val.numel()}") + G = [] + + for group in self.param_groups: + params: list[Tensor] = [] + grads: list[Tensor] = [] + c_grads: list[Tensor] = [] + smoothing: list[Tensor] = [] + lr = group["lr"] + _ = self._init_group(group, params, grads, c_grads, smoothing) + + for i, param in enumerate(params): + ### calculate Lagrange f-n gradient (G) ### + + # stack list of grads w.r.t. constraints to get + # tensor of shape (*param.shape, m) + l_term_grad = 0 + aug_term_grad = 0 + # if c_grads[i] is not None: + for j, c_grad in enumerate(c_grads[i]): + if c_grad is None: + continue + l_term_grad += c_grad * self._dual_vars[j] + aug_term_grad += c_grad * c_val[j] + + G_i = ( + grads[i] + + l_term_grad + + self.rho * aug_term_grad + + self.mu * (param - smoothing[i]) + ) + G.append(G_i) + + smoothing[i].add_(param - smoothing[i], alpha=self.beta) + + param.add_(G_i, alpha=-lr) + + ## PROJECT (keep in mind we do layer by layer) + ## add slack variables to params in constructor? + + c_grads[i].clear() + + self.c_vals.clear() + return G diff --git a/humancompatible/train/algorithms/ssw.py b/humancompatible/train/algorithms/ssw.py new file mode 100644 index 0000000..85999ab --- /dev/null +++ b/humancompatible/train/algorithms/ssw.py @@ -0,0 +1,155 @@ +from typing import Iterable, Optional, Union + +import torch +from torch import Tensor + +from torch.optim.optimizer import Optimizer, _use_grad_for_differentiable + +# def project_fn(x, m): +# for i in range(1, m + 1): +# if x[-i] < 0: +# x[-i] = 0 +# return x + + +def _dual_step_func(dual_var, lr, cval): + return dual_var + lr * cval + + +# def step_fn(params, grads,) + + +class SSG(Optimizer): + def __init__( + self, + params, + m: int = 1, + # constraint tolerance + # ctols: Union[ + # float, Tensor + # ], + # ctols_rule = "const", + # learning rate + lr: Union[float, Tensor] = 5e-2, + # learning rate decrease rule + # lr_rule = "const", + # constraint learning rate + dual_lr: Union[ + float, Tensor + ] = 5e-2, # keep as tensor for different learning rates for different constraints in the future? idk + *, + differentiable: bool = False, + ): + if isinstance(lr, torch.Tensor) and lr.numel() != 1: + raise ValueError("Tensor lr must be 1-element") + if isinstance(dual_lr, torch.Tensor) and lr.numel() != 1: + raise ValueError("Tensor dual_lr must be 1-element") + if lr < 0.0: + raise ValueError(f"Invalid learning rate: {lr}") + if dual_lr < 0.0: + raise ValueError(f"Invalid dual learning rate: {dual_lr}") + if not (m == 1): + raise ValueError(f"Switching Subgradient does not support multiple constraints." + "Consider taking the largest violation at each iteration.") + if differentiable: + raise NotImplementedError("SSw does not support differentiable") + + defaults = dict( + lr=lr, + dual_lr=dual_lr, + differentiable=differentiable, + ) + + super().__init__(params, defaults) + + # self.param_groups.append() + + self.m = m + self.lr = lr + self.dual_lr = dual_lr + # self.lr_rule = lr_rule + # self.dual_lr_rule = dual_lr_rule + self.c_vals: list[Union[float, Tensor]] = [] + # self.ctols = ctols + # essentially, move everything here to self.state[param_group] + # self.state[param_group]['smoothing_avg'] <= z for that param_group; + # ...['grad'] <= grad w.r.t. that param_group + # ...['G'] <= G w.r.t. that param_group // idk if necessary + # ...['c_grad'][c_i] <= grad of ith constraint w.r.t. that group self.m: + raise ValueError("SSw does not support multiple constraints.") + + # save constraint grad + for group in self.param_groups: + params: list[Tensor] = [] + grads: list[Tensor] = [] + c_grads: list[Tensor] = [] + _ = self._init_group(group, params, grads, c_grads) + + for p in group["params"]: + if p.grad is not None: + state = self.state[p] + # state['c_grad'] is cleaned in step() + # so it is always empty on dual_step() + state["c_grad"].append(p.grad) + + @_use_grad_for_differentiable + def step(self, c_val: Union[Iterable | Tensor]): + r"""Perform an update of the primal parameters (network weights). To be called AFTER :func:`dual_step` in an iteration! + + Args: + c_val (Tensor): an Iterable of estimates of values of **ALL** constraints; used for primal parameter update. + Ideally, must be evaluated on an independent sample from the one used in :func:`dual_step` + """ + + # here assume c_val is a scalar + + update_con = c_val > 0 + + for group in self.param_groups: + params: list[Tensor] = [] + grads: list[Tensor] = [] + c_grads: list[Tensor] = [] + lr = group["lr"] + _ = self._init_group(group, params, grads, c_grads) + + for i, param in enumerate(params): + + if update_con: + param.add_(c_grads[i][0], alpha=-self.dual_lr) + else: + param.add_(param.grad, alpha=-lr) + + if c_grads[i] is not None: + c_grads[i].clear() \ No newline at end of file diff --git a/humancompatible/train/algorithms/test/__init__.py b/humancompatible/train/algorithms/test/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/humancompatible/train/algorithms/test/test_ssl_alm.py b/humancompatible/train/algorithms/test/test_ssl_alm.py new file mode 100644 index 0000000..dd134ab --- /dev/null +++ b/humancompatible/train/algorithms/test/test_ssl_alm.py @@ -0,0 +1,144 @@ +import unittest +import torch +from torch import Tensor +from humancompatible.train.algorithms import SSLALM + +class TestSSLALM(unittest.TestCase): + def setUp(self): + # Simple model for testing + self.model = torch.nn.Linear(2, 1) + self.params = list(self.model.parameters()) + self.m = 2 # Number of constraints + self.optimizer = SSLALM( + self.params, + m=self.m, + lr=0.01, + dual_lr=0.01, + dual_bound=100.0, + rho=1.0, + mu=2.0, + beta=0.5, + ) + + def test_initialization(self): + # Test if the optimizer is initialized correctly + self.assertEqual(len(self.optimizer.param_groups), 1) + self.assertEqual(self.optimizer.m, self.m) + self.assertEqual(self.optimizer.dual_lr, 0.01) + self.assertEqual(self.optimizer.dual_bound, 100.0) + self.assertEqual(self.optimizer.rho, 1.0) + self.assertEqual(self.optimizer.mu, 2.0) + self.assertEqual(self.optimizer.beta, 0.5) + self.assertTrue(isinstance(self.optimizer._dual_vars, Tensor)) + self.assertEqual(self.optimizer._dual_vars.shape, (self.m,)) + + def test_dual_step(self): + # Test dual variable update + c_val = torch.tensor([0.5, 0.1]) + self.optimizer.dual_step(0, c_val[0]) + self.assertEqual(self.optimizer._dual_vars[0], 0.005) # 0 + 0.01 * 0.5 + self.optimizer.dual_step(1, c_val[1]) + self.assertEqual(self.optimizer._dual_vars[1], 0.001) # 0 + 0.01 * 0.1 + + def test_dual_bound(self): + # Test dual variable bounding + self.optimizer._dual_vars = torch.tensor([101.0, -1.0]) + c_val = torch.tensor([1.0, -1.0]) + self.optimizer.dual_step(0, c_val[0]) + self.optimizer.dual_step(1, c_val[1]) + self.assertEqual(self.optimizer._dual_vars[0], 0.0) # Should be zeroed out + self.assertEqual(self.optimizer._dual_vars[1], 0.0) # Should be zeroed out + +# ADD TEST DEALING WITH CONSTRAINTS THAT DONT USE SOME OF THE PARAMS + + def test_step(self): + # Test primal parameter update + # Mock gradients and constraint gradients + p_pre_step = {} + for p in self.params: + p.grad = torch.ones_like(p) + p_pre_step[p] = p.detach().clone() + + c_val = torch.tensor([0.1, -0.1]) + c_grads = {p: [torch.ones_like(p) for _ in c_val] for p in self.params} + + for p in self.params: + self.optimizer.state[p]["c_grad"] = [g.clone() for g in c_grads[p]] + self.optimizer.state[p]["smoothing"] = p.detach().clone() + + self.optimizer._dual_vars = torch.ones(2) + G = self.optimizer.step(c_val) + # Check if G is computed and parameters are updated + self.assertEqual(len(G), len(self.params)) + for i, p in enumerate(self.params): + self.assertTrue( + torch.equal( + G[i], + ( + p.grad + + sum(_lambda * c_grads[p][j] for j, _lambda in enumerate(self.optimizer._dual_vars)) + + sum([c_grads[p][j] * cv for j, cv in enumerate(c_val)]) + ) + ) + ) + + def test_step_with_none_c_val(self): + # Test step with None c_val (should use self.c_vals) + c_val = torch.tensor([0.1, -0.1]) + self.optimizer.dual_step(0, c_val[0]) + self.optimizer.dual_step(1, c_val[1]) + + p_pre_step = {} + for p in self.params: + p.grad = torch.ones_like(p) + p_pre_step[p] = p.detach().clone() + + c_grads = {p: [torch.ones_like(p) for _ in c_val] for p in self.params} + for p in self.params: + self.optimizer.state[p]["c_grad"] = [g.clone() for g in c_grads[p]] + self.optimizer.state[p]["smoothing"] = p.detach().clone() + + G = self.optimizer.step() + # Check if G is computed and parameters are updated + self.assertEqual(len(G), len(self.params)) + for i, p in enumerate(self.params): + self.assertTrue( + torch.equal( + G[i], + ( + p.grad + + sum(_lambda * c_grads[p][j] for j, _lambda in enumerate(self.optimizer._dual_vars)) + + sum([c_grads[p][j] * cv for j, cv in enumerate(c_val)]) + ) + ) + ) + + def test_step_with_invalid_c_val(self): + # Test step with invalid c_val (wrong shape) + with self.assertRaises(ValueError): + self.optimizer.step(torch.tensor([0.1])) + + def test_smoothing_update(self): + # Test smoothing term update + p_pre_step = {} + for p in self.params: + p.grad = torch.ones_like(p) + p_pre_step[p] = p.detach().clone() + c_val = torch.tensor([0.1, -0.1]) + self.optimizer.step(c_val) + for p in self.params: + state = self.optimizer.state[p] + self.assertTrue("smoothing" in state) + self.assertTrue(torch.all(state["smoothing"] == p_pre_step[p])) + + def test_error_handling(self): + # Test error handling for invalid inputs + with self.assertRaises(ValueError): + SSLALM(self.params, m=self.m, lr=-0.01) + with self.assertRaises(ValueError): + SSLALM(self.params, m=self.m, dual_lr=-0.01) + with self.assertRaises(ValueError): + SSLALM(self.params, m=self.m, init_dual_vars=torch.tensor([1.0])) + +if __name__ == "__main__": + unittest.main() diff --git a/humancompatible/train/algorithms/test/test_ssw.py b/humancompatible/train/algorithms/test/test_ssw.py new file mode 100644 index 0000000..a59fa6a --- /dev/null +++ b/humancompatible/train/algorithms/test/test_ssw.py @@ -0,0 +1,64 @@ +import unittest +import torch +from humancompatible.train.algorithms import SSG + +class TestSSG(unittest.TestCase): + def setUp(self): + # Simple model for testing + self.model = torch.nn.Linear(2, 1) + self.params = list(self.model.parameters()) + self.m = 1 # Number of constraints + self.optimizer = SSG( + self.params, + m=self.m, + lr=0.01, + dual_lr=0.01 + ) + + def test_initialization(self): + # Test if the optimizer is initialized correctly + self.assertEqual(len(self.optimizer.param_groups), 1) + self.assertEqual(self.optimizer.m, self.m) + self.assertEqual(self.optimizer.dual_lr, 0.01) + + def test_dual_step(self): + # Test dual step saving constraint gradients + for p in self.params: + p.grad = torch.ones_like(p) + self.optimizer.dual_step(0) + + for p in self.params: + state = self.optimizer.state[p] + self.assertTrue(state["c_grad"] is not None) + + def test_step_obj(self): + p_pre_step = {} + for p in self.params: + p.grad = torch.ones_like(p) + self.optimizer.state[p]['c_grad'] = [-1.*torch.ones_like(p)] + p_pre_step[p] = p.detach().clone() + + self.optimizer.step(c_val=torch.tensor(-1.)) + + for p in self.params: + self.assertTrue( + torch.all( + p == p_pre_step[p]-0.01*torch.ones_like(p) + ) + ) + + def test_step_c(self): + p_pre_step = {} + for p in self.params: + p.grad = torch.ones_like(p) + self.optimizer.state[p]['c_grad'] = [-1.*torch.ones_like(p)] + p_pre_step[p] = p.detach().clone() + + self.optimizer.step(c_val=torch.tensor(1.)) + + for p in self.params: + self.assertTrue( + torch.all( + p == p_pre_step[p]+0.01*torch.ones_like(p) + ) + ) \ No newline at end of file diff --git a/src/algorithms/Algorithm.py b/humancompatible/train/benchmark/algorithms/Algorithm.py similarity index 88% rename from src/algorithms/Algorithm.py rename to humancompatible/train/benchmark/algorithms/Algorithm.py index c0c555c..f5ffcd8 100644 --- a/src/algorithms/Algorithm.py +++ b/humancompatible/train/benchmark/algorithms/Algorithm.py @@ -3,7 +3,7 @@ from torch.nn import Module from torch.utils.data import Dataset -from src.constraints import FairnessConstraint +from humancompatible.train.fairness.constraints import FairnessConstraint class Algorithm: diff --git a/humancompatible/train/benchmark/algorithms/__init__.py b/humancompatible/train/benchmark/algorithms/__init__.py new file mode 100644 index 0000000..7543e43 --- /dev/null +++ b/humancompatible/train/benchmark/algorithms/__init__.py @@ -0,0 +1,8 @@ +from .ghost import StochasticGhost +from .ssl_alm import SSLALM +from .switching_subgradient import SSG +from .sgd import SGD +# from .torch.ssl_alm import SSLALM +# from .torch.ssw import SSG + +__all__ = ["SSLALM", "StochasticGhost", "SSG", "SGD"] diff --git a/src/algorithms/ghost.py b/humancompatible/train/benchmark/algorithms/ghost.py similarity index 77% rename from src/algorithms/ghost.py rename to humancompatible/train/benchmark/algorithms/ghost.py index d42f84e..75bec90 100644 --- a/src/algorithms/ghost.py +++ b/humancompatible/train/benchmark/algorithms/ghost.py @@ -3,15 +3,13 @@ from copy import deepcopy import numpy as np -import pandas as pd import scipy as sp import torch -from fairret.statistic import * from qpsolvers import solve_qp from scipy.optimize import linprog -from src.algorithms.Algorithm import Algorithm -from src.algorithms.utils import net_params_to_tensor +from .Algorithm import Algorithm +from humancompatible.train.benchmark.algorithms.utils import _set_weights, net_params_to_tensor class StochasticGhost(Algorithm): @@ -83,30 +81,37 @@ def optimize( verbose=True, max_runtime=None, max_iter=None, + save_state_interval=1 ): + self.state_history = {} + self.state_history["params"] = {"w": {}} + self.state_history["values"] = {"f": {}, "d": {}, "c": {}, "n_samples": {}} + self.state_history["time"] = {} + max_sample_size = np.max([c.group_sizes() for c in self.constraints]) n = sum(p.numel() for p in self.net.parameters()) rng = np.random.default_rng(seed=seed) run_start = timeit.default_timer() - - iteration = 0 + + total_iters = 0 while True: - iteration += 1 - if max_iter is not None and iteration >= max_iter: + total_iters += 1 + if max_iter is not None and total_iters >= max_iter: break current_time = timeit.default_timer() - self.history["time"].append(current_time - run_start) + if total_iters % save_state_interval == 0: + self.state_history["time"][total_iters] = current_time - run_start if max_runtime > 0 and current_time - run_start >= max_runtime: print(current_time - run_start) - self.history["constr"] = pd.DataFrame(self.history["constr"]) - return self.history + # self.history["constr"] = pd.DataFrame(self.history["constr"]) + return self.state_history if stepsize_rule == "inv_iter": - gamma = gamma0 / (iteration + 1) ** zeta + gamma = gamma0 / (total_iters + 1) ** zeta elif stepsize_rule == "dimin": - if iteration == 1: + if total_iters == 1: gamma = gamma0 else: gamma *= 1 - zeta * gamma @@ -114,8 +119,11 @@ def optimize( Nsamp = rng.geometric(p=alpha) - 1 while (2 ** (Nsamp + 1)) > max_sample_size: Nsamp = rng.geometric(p=alpha) - 1 + + n_samples_used = 3 * ( + 1 + 2 ** (Nsamp + 1) + ) - self.history["n_samples"].append(3 * (1 + 2 ** (Nsamp + 1))) dsols = np.zeros((4, n)) ################ @@ -176,11 +184,16 @@ def optimize( constraint_eval.append(c_val.detach()) dcdw.append(c_grad) - constraint_eval = np.array(constraint_eval) + constraint_eval = np.array(constraint_eval).flatten() dcdw = np.array(dcdw) kappa = self.compute_kappa( - constraint_eval, dcdw, rho, lamb, mc=2, n=len(dfdw) + constraint_eval, + dcdw, + rho, + lamb, + mc=len(self.constraints), + n=len(dfdw), ) # solve subproblem @@ -194,7 +207,7 @@ def optimize( beta, tau, hesstype="diag", - mc=2, + mc=len(self.constraints), n=len(dfdw), qp_solver="osqp", ) @@ -207,12 +220,12 @@ def optimize( ) / (alpha * ((1 - alpha) ** (Nsamp))) start = 0 - print(f"{iteration}", end="\r") + print(f"{total_iters}", end="\r") with torch.no_grad(): w = net_params_to_tensor(self.net) if any([torch.any(torch.isnan(lw)) for lw in w]): print("NaNs!") - return self.history + return self.state_history for i in range(len(w)): end = start + w[i].numel() w[i].add_( @@ -222,9 +235,16 @@ def optimize( ) start = end - self.history["w"].append(deepcopy(self.net.state_dict())) + if total_iters % save_state_interval == 0: + self.state_history["params"]["w"][total_iters] = deepcopy( + self.net.state_dict() + ) + self.state_history["values"]["n_samples"][total_iters] = n_samples_used + + self.state_history["values"]["d"][total_iters] = dsol + # self.history["w"].append(deepcopy(self.net.state_dict())) feval = self.loss_fn(outs, obj_batch[1]) - self.history["constr"] = pd.DataFrame(self.history["constr"]) - return self.history + # self.history["constr"] = pd.DataFrame(self.history["constr"]) + return self.state_history \ No newline at end of file diff --git a/humancompatible/train/benchmark/algorithms/sgd.py b/humancompatible/train/benchmark/algorithms/sgd.py new file mode 100644 index 0000000..c090b5c --- /dev/null +++ b/humancompatible/train/benchmark/algorithms/sgd.py @@ -0,0 +1,107 @@ +import timeit +from copy import deepcopy + +import numpy as np +import torch + +from .Algorithm import Algorithm + + +class SGD(Algorithm): + def __init__(self, net, data, loss, constraints): + super().__init__(net, data, loss, constraints) + + def optimize( + self, + lr, + batch_size, + epochs=None, + max_runtime=None, + max_iter=None, + seed=None, + device="cpu", + verbose=True, + save_state_interval=1000, + ): + self.state_history = {} + self.state_history["params"] = {"w": {}} + self.state_history["values"] = {"f": {}, "fg": {}} + self.state_history["time"] = {} + + run_start = timeit.default_timer() + + if epochs is None: + epochs = np.inf + if max_iter is None: + max_iter = np.inf + if max_runtime is None: + max_runtime = np.inf + + gen = torch.Generator(device=device) + if seed is not None: + gen.manual_seed(seed) + loss_loader = torch.utils.data.DataLoader( + self.dataset, batch_size, shuffle=True, generator=gen + ) + loss_iter = iter(loss_loader) + + epoch = 0 + iteration = 0 + total_iters = 0 + + optimizer = torch.optim.SGD(self.net.parameters(), lr=lr) + + while True: + elapsed = timeit.default_timer() - run_start + iteration += 1 + total_iters += 1 + if epoch >= epochs or total_iters >= max_iter or elapsed > max_runtime: + break + + if total_iters % save_state_interval == 0: + self.state_history["params"]["w"][total_iters] = deepcopy( + self.net.state_dict() + ) + self.state_history["time"][total_iters] = elapsed + + try: + (f_inputs, f_labels) = next(loss_iter) + except StopIteration: + epoch += 1 + iteration = 0 + gen = gen + loss_loader = torch.utils.data.DataLoader( + self.dataset, batch_size, shuffle=True, generator=gen + ) + loss_iter = iter(loss_loader) + (f_inputs, f_labels) = next(loss_iter) + # lr *= 0.8 + + ######################## + ## UPDATE MULTIPLIERS ## + ######################## + self.net.zero_grad() + outputs = self.net(f_inputs) + loss = self.loss_fn(outputs.squeeze(), f_labels) + loss.backward() + optimizer.step() + + # f_grad_estimate = + + with torch.no_grad(): + if total_iters % save_state_interval == 0: + self.state_history["values"]["f"][total_iters] = ( + loss.detach().cpu().numpy() + ) + # self.state_history['values']['fg'][total_iters] = torch.norm(f_grad_estimate).detach().cpu().numpy() + + if verbose: + with np.printoptions( + precision=8, suppress=True, floatmode="fixed", sign=" " + ): + print( + f"""{epoch:2}|{iteration:5} | {lr} | {loss.detach().cpu().numpy():1.5f}""", + end="\r", + ) + + return self.state_history diff --git a/humancompatible/train/benchmark/algorithms/ssl_alm.py b/humancompatible/train/benchmark/algorithms/ssl_alm.py new file mode 100644 index 0000000..a1ffc40 --- /dev/null +++ b/humancompatible/train/benchmark/algorithms/ssl_alm.py @@ -0,0 +1,311 @@ +import timeit +from copy import deepcopy +from typing import Callable + +import numpy as np +import torch + +from .Algorithm import Algorithm +from humancompatible.train.benchmark.algorithms.utils import _set_weights, net_params_to_tensor + + +class SSLALM(Algorithm): + def __init__( + self, net, data, loss, constraints, custom_project_fn: Callable = None + ): + super().__init__(net, data, loss, constraints) + self.project = custom_project_fn if custom_project_fn else self.project_fn + + @staticmethod + def project_fn(x, m): + for i in range(1, m + 1): + if x[-i] < 0: + x[-i] = 0 + return x + + def optimize( + self, + tau=0.01, + eta=0.05, + lambda_bound=25., + rho=1., + mu=2., + beta=0.5, + tau_mult=1., + eta_mult=1., + batch_size=16, + epochs=None, + start_lambda=None, + max_runtime=None, + max_iter=None, + seed=None, + device="cpu", + verbose=True, + use_unbiased_penalty_grad=True, + save_state_interval=1 + ): + self.state_history = {} + self.state_history["params"] = {"w": {}, "dual_ms": {}, "z": {}, "slack": {}} + # self.history['vars_full'] = {'G': {}, 'f': {}, 'fg': {}, 'c': {}, 'cg': {}} + self.state_history["values"] = {"G": {}, "f": {}, "fg": {}, "c": {}, "cg": {}} + self.state_history["time"] = {} + + m = len(self.constraints) + slack_vars = torch.zeros(m, requires_grad=True) + _lambda = ( + torch.zeros(m, requires_grad=True) if start_lambda is None else start_lambda + ) + + z = torch.concat( + [net_params_to_tensor(self.net, flatten=True, copy=True), slack_vars] + ) + z_par = torch.narrow(z, 0, 0, z.shape[-1] - m) + + c = self.constraints + + run_start = timeit.default_timer() + + if epochs is None: + epochs = np.inf + if max_iter is None: + max_iter = np.inf + if max_runtime is None: + max_runtime = np.inf + + gen = torch.Generator(device=device) + if seed is not None: + gen = gen.manual_seed(seed) + loss_loader = torch.utils.data.DataLoader( + self.dataset, batch_size, shuffle=(gen.device == 'cpu'), generator=gen + ) + loss_iter = iter(loss_loader) + + epoch = 0 + iteration = 0 + total_iters = 0 + + ### initial f and f_grad estimate ### + f_grad_estimate = 0 + pre_loader = torch.utils.data.DataLoader( + self.dataset, batch_size, shuffle=(gen.device == 'cpu'), generator=gen + ) + pre_iter = iter(pre_loader) + (f_inputs, f_labels) = next(pre_iter) + _, f_grad_estimate = self._objective_estimate(f_inputs, f_labels) + self.net.zero_grad() + + ### initial c_val and c_grad estimate ### + c_sample = [ci.sample_loader() for ci in c] + _c_val_estimate = self._c_value_estimate(slack_vars, c, c_sample) + c_val_estimate = torch.concat(_c_val_estimate) + c_grad_estimate = self._constraint_grad_estimate(slack_vars, _c_val_estimate) + + ### c_val estimate ### + if use_unbiased_penalty_grad: + c_sample = [ci.sample_loader() for ci in c] + c_val_estimate_2 = torch.concat(self._c_value_estimate(slack_vars, c, c_sample)) + else: + c_val_estimate_2 = c_val_estimate + + n_iters_c_satisfied = 0 + percent_iters_c_satisfied = 0 + + while True: + elapsed = timeit.default_timer() - run_start + iteration += 1 + total_iters += 1 + if epoch >= epochs or total_iters >= max_iter or elapsed > max_runtime: + break + + self.state_history["time"][total_iters] = elapsed + if total_iters % save_state_interval == 0: + self.state_history["params"]["w"][total_iters] = deepcopy( + self.net.state_dict() + ) + self.state_history["params"]["dual_ms"][total_iters] = ( + _lambda.detach().cpu().numpy() + ) + self.state_history["params"]["z"][total_iters] = ( + z_par.detach().cpu().numpy() + ) + self.state_history["params"]["slack"][total_iters] = ( + slack_vars.detach().cpu().numpy() + ) + + percent_iters_c_satisfied = n_iters_c_satisfied / total_iters + + try: + (f_inputs, f_labels) = next(loss_iter) + except StopIteration: + epoch += 1 + iteration = 0 + gen = gen + loss_loader = torch.utils.data.DataLoader( + self.dataset, batch_size, shuffle=(gen.device == 'cpu'), generator=gen + ) + loss_iter = iter(loss_loader) + (f_inputs, f_labels) = next(loss_iter) + tau *= tau_mult + eta *= eta_mult + # rho *= rho_mult + + ######################## + ## UPDATE MULTIPLIERS ## + ######################## + self.net.zero_grad() + slack_vars.grad = None + + # sample for and calculate self.constraints (lines 2, 3) + # update multipliers (line 3) + with torch.no_grad(): + _lambda = _lambda + eta * c_val_estimate + # dual safeguard (lines 4,5) + for i, l in enumerate(_lambda): + if l >= lambda_bound: #or l < 0: + _lambda[i] = 0 + # if torch.norm(_lambda) >= lambda_bound: + # _lambda = torch.zeros_like(_lambda, requires_grad=True) + + x_t = torch.concat( + [ + net_params_to_tensor(self.net, flatten=True, copy=True), + slack_vars, + ] + ) + + G = ( + f_grad_estimate + + c_grad_estimate.T @ _lambda + + rho * (c_grad_estimate.T @ c_val_estimate_2) + ) + + if mu > 0: + smoothing = mu * (x_t - z) + G += smoothing + + x_t1 = self.project(x_t - tau * G, m) + + if mu > 0: + z += beta * (x_t - z) + + ################### + ## UPDATE PARAMS ## + ################### + + with torch.no_grad(): + _set_weights(self.net, x_t1) + for i in range(len(slack_vars)): + slack_vars[i] = x_t1[i - len(slack_vars)] + # objective gradient + loss_eval, f_grad_1 = self._objective_estimate(f_inputs, f_labels) + self.net.zero_grad() + + # constraint value abd grad (1) + c_sample = [ci.sample_loader() for ci in c] + _c_val_1 = self._c_value_estimate(slack_vars, c, c_sample) + c_val_1 = torch.concat(_c_val_1) + c_grad_1 = self._constraint_grad_estimate(slack_vars, _c_val_1) + + # constraint value (2) (independent) + if use_unbiased_penalty_grad: + c_sample = [ci.sample_loader() for ci in c] + c_val_2 = torch.concat(self._c_value_estimate(slack_vars, c, c_sample)) + else: + c_val_2 = c_val_1 + + f_grad_estimate = f_grad_1 + c_val_estimate = c_val_1 + c_val_estimate_2 = c_val_2 + c_grad_estimate = c_grad_1 + + if total_iters % save_state_interval == 0: + with torch.no_grad(): + f_grad_par = torch.narrow( + f_grad_estimate, 0, 0, f_grad_estimate.shape[-1] - m + ) + c_grad_par = torch.narrow( + c_grad_estimate, 1, 0, c_grad_estimate.shape[-1] - m + ) + G_par = torch.narrow(G, 0, 0, G.shape[-1] - m) + z_par = torch.narrow(z, 0, 0, z.shape[-1] - m) + + self.state_history["values"]["G"][total_iters] = ( + torch.norm(G_par).detach().cpu().numpy() + ) + self.state_history["values"]["f"][total_iters] = ( + loss_eval.detach().cpu().numpy() + ) + self.state_history["values"]["fg"][total_iters] = ( + torch.norm(f_grad_par).detach().cpu().numpy() + ) + self.state_history["values"]["c"][total_iters] = ( + c_val_2.detach().cpu().numpy() + ) + self.state_history["values"]["cg"][total_iters] = ( + torch.norm(c_grad_par, dim=1).detach().cpu().numpy() + ) + + if torch.all(c_val_1 <= 0): + n_iters_c_satisfied += 1 + + if verbose: + with np.printoptions( + precision=3, + suppress=True, + floatmode="fixed", + sign=" ", + linewidth=200, + ): + print( + f"{epoch:2}|{iteration:5}|{tau:.3f}|" + # f"{loss_eval.detach().cpu().numpy():1.3f}|" + f"{_lambda.detach().cpu().numpy()}|" + f"{c_val_estimate.detach().cpu().numpy() - slack_vars.detach().cpu().numpy()}|", + # f"{slack_vars.detach().cpu().numpy()} | {100*percent_iters_c_satisfied:2.1f}%", + end="\r", + ) + + return self.state_history + + + + def _c_value_estimate(self, slack_vars, c, c_sample): + c_val = [ + ci.eval(self.net, c_sample[i]).reshape(1) + slack_vars[i] + for i, ci in enumerate(c) + ] + + return c_val + + def _objective_estimate(self, f_inputs, f_labels): + m = len(self.constraints) + # breakpoint() + outputs = self.net(f_inputs) + # if f_labels.dim() < outputs.dim(): + # f_labels = f_labels.unsqueeze(1) + loss_eval = self.loss_fn(outputs.squeeze(), f_labels) + f_grad = torch.autograd.grad(loss_eval, self.net.parameters()) + f_grad = torch.concat([*[g.flatten() for g in f_grad], torch.zeros(m)]) + + return loss_eval, f_grad + + def _constraint_grad_estimate(self, slack_vars, c): + c_grad = [] + # breakpoint() + for ci in c: + ci_grad = torch.autograd.grad(ci, self.net.parameters()) + if slack_vars is None: + c_grad.append(torch.concat([g.flatten() for g in ci_grad])) + else: + slack_grad = torch.autograd.grad(ci, slack_vars, materialize_grads=True) + # if torch.sum(slack_grad[0]) != 1: + # breakpoint() + c_grad.append( + torch.concat([*[g.flatten() for g in ci_grad], *slack_grad]) + ) + slack_vars.grad = None + # slack_vars.zero_grad_ + + self.net.zero_grad() + c_grad = torch.stack(c_grad) + return c_grad \ No newline at end of file diff --git a/src/algorithms/switching_subgradient.py b/humancompatible/train/benchmark/algorithms/switching_subgradient.py similarity index 65% rename from src/algorithms/switching_subgradient.py rename to humancompatible/train/benchmark/algorithms/switching_subgradient.py index ff9f9bd..9cad4f1 100644 --- a/src/algorithms/switching_subgradient.py +++ b/humancompatible/train/benchmark/algorithms/switching_subgradient.py @@ -5,8 +5,8 @@ import numpy as np import torch -from src.algorithms.Algorithm import Algorithm -from src.algorithms.utils import net_params_to_tensor +from .Algorithm import Algorithm +from humancompatible.train.benchmark.algorithms.utils import _set_weights, net_params_to_tensor class SSG(Algorithm): @@ -22,21 +22,26 @@ def project_fn(x, m): def optimize( self, + ctol_rule, ctol, f_stepsize_rule, f_stepsize, c_stepsize_rule, c_stepsize, batch_size, - epochs, + epochs=None, save_iter=None, device="cpu", seed=None, verbose=True, max_runtime=None, max_iter=None, + save_state_interval=100 ): - run_start = timeit.default_timer() + self.state_history = {} + self.state_history["params"] = {"w": {}} + self.state_history["values"] = {"G": {}, "f": {}, "c": {}} + self.state_history["time"] = {} f_eta_t = f_stepsize c_eta_t = c_stepsize @@ -57,6 +62,7 @@ def optimize( ) loss_iter = iter(loss_loader) + run_start = timeit.default_timer() while True: elapsed = timeit.default_timer() - run_start iteration += 1 @@ -64,18 +70,17 @@ def optimize( if epoch >= epochs or total_iters >= max_iter or elapsed > max_runtime: break - self.history["w"].append(deepcopy(self.net.state_dict())) - self.history["time"].append(elapsed) - self.history["n_samples"].append(batch_size * 3) + self.state_history["time"][total_iters] = elapsed + if total_iters % save_state_interval == 0: + self.state_history["params"]["w"][total_iters] = deepcopy( + self.net.state_dict() + ) try: f_sample = next(loss_iter) except StopIteration: epoch += 1 - f_iters = 0 - c_iters = 0 iteration = 0 - _ctol = ctol loss_loader = torch.utils.data.DataLoader( self.dataset, batch_size, shuffle=True, generator=gen ) @@ -83,8 +88,8 @@ def optimize( f_sample = next(loss_iter) self.net.zero_grad() - if iteration > 800: - _ctol *= 0.97 + if ctol_rule == 'dimin': + _ctol = ctol / np.sqrt(total_iters) if save_iter is not None and total_iters >= save_iter: eta_f_list.append(f_eta_t) @@ -94,61 +99,49 @@ def optimize( c_sample = [ci.sample_loader() for ci in self.constraints] # calc constraints and update multipliers (line 3) with torch.no_grad(): - c_t = torch.concat( + c_t = np.array( [ ci.eval(self.net, c_sample[i]).reshape(1) for i, ci in enumerate(self.constraints) ] - ) - c_max = torch.max(c_t) - self.history["constr"].append(c_max.cpu().detach().numpy()) + ).flatten() + c_argmax = np.argmax(c_t) + c_max = c_t[c_argmax] x_t = net_params_to_tensor(self.net, flatten=True, copy=True) if c_max >= _ctol: c_iters += 1 - - self.history["n_samples"].append(batch_size * 2) - # calculate grad on an independent sample - c_sample = [ci.sample_loader() for ci in self.constraints] - c_t2 = torch.concat( - [ - ci.eval(self.net, c_sample[i]).reshape(1) - for i, ci in enumerate(self.constraints) - ] - ) - c_max2 = torch.max(c_t2) + c_max2 = self.constraints[c_argmax].eval(self.net, c_sample[c_argmax]).reshape(1) c_grad = torch.autograd.grad(c_max2, self.net.parameters()) c_grad = torch.concat([cg.flatten() for cg in c_grad]) if c_stepsize_rule == "adaptive": - c_eta_t = c_max / torch.norm(c_grad) ** 2 + c_eta_t = c_max / (1e-6 + torch.norm(c_grad) ** 2) elif c_stepsize_rule == "const": c_eta_t = c_stepsize elif c_stepsize_rule == "dimin": - c_eta_t = c_stepsize / np.sqrt(c_iters) + c_eta_t = c_stepsize / np.sqrt(total_iters) - x_t1 = self.project(x_t - c_eta_t * c_grad, m=2) + x_t1 = self.project(x_t - c_eta_t * c_grad, m=len(self.constraints)) else: - self.history["n_samples"].append(batch_size) f_iters += 1 f_inputs, f_labels = f_sample outputs = self.net(f_inputs) if f_labels.dim() < outputs.dim(): f_labels = f_labels.unsqueeze(1) loss_eval = self.loss_fn(outputs, f_labels) - self.history["loss"].append(loss_eval.cpu().detach().numpy()) f_grad = torch.autograd.grad(loss_eval, self.net.parameters()) f_grad = torch.concat([fg.flatten() for fg in f_grad]) if f_stepsize_rule == "dimin": - f_eta_t = f_stepsize / np.sqrt(f_iters) + f_eta_t = f_stepsize / np.sqrt(total_iters) elif f_stepsize_rule == "const": f_eta_t = f_stepsize - x_t1 = self.project(x_t - f_eta_t * f_grad, m=2) + x_t1 = self.project(x_t - f_eta_t * f_grad, m=len(self.constraints)) start = 0 with torch.no_grad(): @@ -158,10 +151,30 @@ def optimize( w[i].set_(x_t1[start:end].reshape(w[i].shape)) start = end + if total_iters % save_state_interval == 0: + if c_max is not None: + self.state_history["values"]["c"][total_iters] = ( + c_t + ) + if loss_eval is not None: + self.state_history["values"]["f"][total_iters] = ( + loss_eval.cpu().detach().numpy() + ) + if verbose and loss_eval is not None and c_t is not None: - with np.printoptions(precision=6, suppress=True): + with np.printoptions( + precision=3, + suppress=True, + floatmode="fixed", + sign=" ", + linewidth=100, + ): print( - f"{epoch:2} | {iteration:5} |{_ctol:.5}|{loss_eval.detach().cpu().numpy()}|{c_t.detach().cpu().numpy()}", + f"{epoch:2}|" + f"{_ctol:.3}|" + f"{iteration:5}|" + f"{loss_eval.detach().cpu().numpy():.5f}|" + f"{c_t}", end="\r", ) @@ -174,6 +187,6 @@ def optimize( np.arange(start=save_iter, stop=total_iters), p=np.array(eta_f_list) / np.sum(eta_f_list), ) - self.net.load_state_dict(self.history["w"][model_ind]) + self.net.load_state_dict(self.state_history["params"]["w"].iloc[model_ind]) - return self.history + return self.state_history \ No newline at end of file diff --git a/src/algorithms/utils.py b/humancompatible/train/benchmark/algorithms/utils.py similarity index 82% rename from src/algorithms/utils.py rename to humancompatible/train/benchmark/algorithms/utils.py index 4684a14..f3dce02 100644 --- a/src/algorithms/utils.py +++ b/humancompatible/train/benchmark/algorithms/utils.py @@ -35,17 +35,18 @@ def check_same_sample(sample1, sample2): ) -def net_grads_to_tensor(net, clip=False, flatten=True) -> torch.Tensor: +def net_grads_to_tensor(net, clip=False, flatten=True, device=None) -> torch.Tensor: param_grads = [] if clip: torch.nn.utils.clip_grad_norm_(net.parameters(), 0.5) for param in net.parameters(): if param.grad is not None: # Clone to avoid modifying the original tensor + device = param.grad.data.device if device is None else device if flatten: - param_grads.append(param.grad.data.clone().view(-1)) + param_grads.append(param.grad.data.view(-1)) else: - param_grads.append(param.grad.data.clone()) + param_grads.append(param.grad.data.to(device)) if flatten: param_grads = torch.cat(param_grads) return param_grads @@ -57,4 +58,4 @@ def _set_weights(net: torch.nn.Module, x): for i in range(len(w)): end = start + w[i].numel() w[i].set_(x[start:end].reshape(w[i].shape)) - start = end + start = end \ No newline at end of file diff --git a/humancompatible/train/fairness/__init__.py b/humancompatible/train/fairness/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/humancompatible/train/fairness/constraints/__init__.py b/humancompatible/train/fairness/constraints/__init__.py new file mode 100644 index 0000000..9c01824 --- /dev/null +++ b/humancompatible/train/fairness/constraints/__init__.py @@ -0,0 +1,15 @@ +from .constraint import FairnessConstraint +from .constraint_fns import ( + fairret_stat_equality, + ppv_equality, + acc_equality, + tpr_equality, + abs_loss_equality, + loss_equality, + abs_diff_tpr, + abs_diff_fpr, + abs_max_dev_from_overall_tpr, + abs_diff_pr +) + +__all__ = ["FairnessConstraint, loss_equality"] diff --git a/src/constraints/constraint.py b/humancompatible/train/fairness/constraints/constraint.py similarity index 58% rename from src/constraints/constraint.py rename to humancompatible/train/fairness/constraints/constraint.py index 5683f79..2a043e4 100644 --- a/src/constraints/constraint.py +++ b/humancompatible/train/fairness/constraints/constraint.py @@ -1,24 +1,16 @@ from typing import Callable, Iterable import numpy as np +import fairret import torch from torch.utils.data import DataLoader, SubsetRandomSampler -def _dataloader_from_subset(dataset, indices, *args, **kwargs): - data_s = torch.utils.data.Subset(dataset, indices) - loader_s = torch.utils.data.DataLoader(data_s, *args, **kwargs) - return loader_s - - -def _make_dataloaders(dataset, group_indices, batch_size, seed): - g = torch.Generator() - if seed is not None: - g.manual_seed(seed) +def _make_dataloaders(dataset, group_indices, batch_size, device, drop_last, gen=None): dataloaders = [] for idx in group_indices: - sampler = SubsetRandomSampler(idx, g) - dataloaders.append(iter(DataLoader(dataset, batch_size, sampler=sampler))) + sampler = SubsetRandomSampler(idx, gen) + dataloaders.append(iter(DataLoader(dataset, batch_size, sampler=sampler, drop_last=True))) return dataloaders @@ -30,7 +22,9 @@ def __init__( fn: Callable, batch_size: int = None, use_dataloaders=True, + device="cpu", seed=None, + loader_drop_last=False, ): self.dataset = dataset self.group_sets = [ @@ -40,11 +34,14 @@ def __init__( self.fn = fn self._seed = seed self._rng = np.random.default_rng(seed) + self._torch_rng = torch.manual_seed(seed) if seed is not None else torch.Generator(device=device) + self._device = device + self._drop_last = loader_drop_last if batch_size is not None: self._batch_size = batch_size if use_dataloaders: self.group_dataloaders = _make_dataloaders( - dataset, group_indices, batch_size, seed + dataset, group_indices, batch_size, device, gen=self._torch_rng, drop_last=loader_drop_last ) def group_sizes(self): @@ -52,16 +49,29 @@ def group_sizes(self): def eval(self, net, sample, **kwargs): return self.fn(net, sample, **kwargs) + + # def eval_fairret(self, net, sample, group_id, **kwargs): + # if self._fairret_results is None: + # statistic = fairret.statistic.TruePositiveRate() + # loss = fairret.loss.NormLoss(statistic) + + + # return self._fairret_results[group_id] def sample_loader(self): - try: - sample = [next(l) for l in self.group_dataloaders] - except StopIteration: - self.group_dataloaders = _make_dataloaders( - self.dataset, self._group_indices, self._batch_size, self._seed - ) - sample = [next(l) for l in self.group_dataloaders] - return sample + self._fairret_results = None + samples = [] + for i, l in enumerate(self.group_dataloaders): + try: + sample = next(l) + except StopIteration: + sampler = SubsetRandomSampler(self._group_indices[i], self._torch_rng) + l = iter(DataLoader(self.dataset, self._batch_size, sampler=sampler, drop_last=self._drop_last)) + sample = next(l) + self.group_dataloaders[i] = l + + samples.append(sample) + return samples def sample_dataset( self, N, rng: np.random.Generator = None, indices=None, return_indices=False diff --git a/humancompatible/train/fairness/constraints/constraint_fns.py b/humancompatible/train/fairness/constraints/constraint_fns.py new file mode 100644 index 0000000..d067796 --- /dev/null +++ b/humancompatible/train/fairness/constraints/constraint_fns.py @@ -0,0 +1,244 @@ +import torch +from fairret.statistic import ( + TruePositiveRate, + FalseNegativeFalsePositiveFraction, + FalsePositiveRate, + PositiveRate, + Accuracy, +) +from fairret.loss import NormLoss + + +def tpr_equality(_, net, c_data): + statistic = TruePositiveRate() + loss = NormLoss(statistic, p=1) + + return fairret_stat_equality(net, c_data, loss) + + +def ppv_equality(_, net, c_data): + statistic = FalseNegativeFalsePositiveFraction() + loss = NormLoss(statistic, p=1) + + return fairret_stat_equality(net, c_data, loss) + + +def acc_equality(_, net, c_data): + statistic = Accuracy() + loss = NormLoss(statistic, p=1) + + return fairret_stat_equality(net, c_data, loss) + + +def fairret_stat_equality(net, c_data, loss): + g1_inputs, g1_labels = c_data[0] + g2_inputs, g2_labels = c_data[1] + + g1_outs = net(g1_inputs).squeeze() + g2_outs = net(g2_inputs).squeeze() + # if not (1 in a_labels or 1 in g2_labels): + # return torch.tensor(0) + + group_codes = [0] * len(g1_labels) + [1] * len(g2_labels) + group_codes = torch.tensor( + [[0.0, 1.0] if x == 1 else [1.0, 0.0] for x in group_codes] + ) + + return loss( + torch.concat([g1_outs, g2_outs]).unsqueeze(1), + group_codes, + torch.concat([g1_labels, g2_labels]).unsqueeze(1), + ) + + +def dummy(_, net, c_data): + r = torch.zeros(1) + r.grad = 0 + return r + + +def loss_equality(loss, net, c_data): + g1_inputs, g1_labels = c_data[0] + g2_inputs, g2_labels = c_data[1] + g1_outs = net(g1_inputs) + if g1_labels.ndim == 0: + g1_labels = g1_labels.reshape(1) + g2_labels = g2_labels.reshape(1) + if g1_labels.ndim < g1_outs.ndim: + g1_labels = g1_labels.unsqueeze(1) + g2_labels = g2_labels.unsqueeze(1) + g1_loss = loss(g1_outs, g1_labels) + g2_outs = net(g2_inputs) + g2_loss = loss(g2_outs, g2_labels) + + val = g1_loss - g2_loss + return val + + + +def abs_diff_tpr(_, net, c_data):#, stat): + tpr = TruePositiveRate() + g1_inputs, g1_labels = c_data[0] + g2_inputs, g2_labels = c_data[1] + g1_outs = torch.nn.functional.sigmoid(net(g1_inputs)) + g2_outs = torch.nn.functional.sigmoid(net(g2_inputs)) + + g1_pos_pred_mask = (g1_outs >= 0).squeeze() + g2_pos_pred_mask = (g2_outs >= 0).squeeze() + + if g1_labels.ndim == 0: + g1_labels = g1_labels.reshape(1) + g2_labels = g2_labels.reshape(1) + if g1_labels.ndim < g1_outs.ndim: + g1_labels = g1_labels.unsqueeze(1) + g2_labels = g2_labels.unsqueeze(1) + + g1_loss = tpr(g1_outs[g1_pos_pred_mask], None, g1_labels[g1_pos_pred_mask]) + g2_loss = tpr(g2_outs[g2_pos_pred_mask], None, g2_labels[g2_pos_pred_mask]) + + val = abs(g1_loss - g2_loss) + + return val + +def abs_diff_pr(_, net, c_data):#, stat): + pr = PositiveRate() + g1_inputs, g1_labels = c_data[0] + g2_inputs, g2_labels = c_data[1] + g1_outs = torch.nn.functional.sigmoid(net(g1_inputs)) + g2_outs = torch.nn.functional.sigmoid(net(g2_inputs)) + + if g1_labels.ndim == 0: + g1_labels = g1_labels.reshape(1) + g2_labels = g2_labels.reshape(1) + if g1_labels.ndim < g1_outs.ndim: + g1_labels = g1_labels.unsqueeze(1) + g2_labels = g2_labels.unsqueeze(1) + + g1_loss = pr(g1_outs, None) + g2_loss = pr(g2_outs, None) + + val = abs(g1_loss - g2_loss) + + return val + +def abs_diff_fpr(_, net, c_data):#, stat): + tpr = FalsePositiveRate() + g1_inputs, g1_labels = c_data[0] + g2_inputs, g2_labels = c_data[1] + g1_outs = torch.nn.functional.sigmoid(net(g1_inputs)) + g2_outs = torch.nn.functional.sigmoid(net(g2_inputs)) + + if g1_labels.ndim == 0: + g1_labels = g1_labels.reshape(1) + g2_labels = g2_labels.reshape(1) + if g1_labels.ndim < g1_outs.ndim: + g1_labels = g1_labels.unsqueeze(1) + g2_labels = g2_labels.unsqueeze(1) + + g1_loss = tpr(g1_outs, None, g1_labels) + g2_loss = tpr(g2_outs, None, g2_labels) + + val = abs(g1_loss - g2_loss) + + return val + +def abs_max_dev_from_overall_tpr(_, net, c_data): + stats = [] + st = TruePositiveRate() + for input, label in c_data: + out = net(input) + pred_sigm = torch.nn.functional.sigmoid(out) + pos_pred_mask = (pred_sigm >= 0).squeeze() + tpr = st(pred_sigm[pos_pred_mask], None, label[pos_pred_mask].unsqueeze(1)) + stats.append(tpr) + + stats = torch.cat(stats) + all_inp = torch.cat([x[0] for x in c_data]) + all_lab = torch.cat([x[1] for x in c_data]) + all_out = net(all_inp) + all_pred_sigm = torch.nn.functional.sigmoid(all_out) + pos_pred_mask = (all_pred_sigm >= 0).squeeze() + all_tpr = st(all_pred_sigm[pos_pred_mask], None, all_lab[pos_pred_mask].unsqueeze(1)) + + val = torch.max( + torch.abs(stats - all_tpr) + ) + + # val = torch.max( + # torch.abs(stats/all_tpr - 1) + # ) + + return val + + + +def abs_max_dev_from_overall_fpr(_, net, c_data): + stats = [] + st = FalsePositiveRate() + for input, label in c_data: + out = net(input) + pred_sigm = torch.nn.functional.sigmoid(out) + tpr = st(pred_sigm, None, label.unsqueeze(1)) + stats.append(tpr) + + stats = torch.cat(stats) + all_inp = torch.cat([x[0] for x in c_data]) + all_lab = torch.cat([x[1] for x in c_data]) + all_out = net(all_inp) + all_pred_sigm = torch.nn.functional.sigmoid(all_out) + all_tpr = st(all_pred_sigm, None, all_lab.unsqueeze(1)) + + val = torch.max( + torch.abs(stats - all_tpr) + ) + + # val = torch.max( + # torch.abs(stats/all_tpr - 1) + # ) + + return val + + +def abs_loss_equality(loss, net, c_data): + g1_inputs, g1_labels = c_data[0] + g2_inputs, g2_labels = c_data[1] + g1_outs = net(g1_inputs) + if g1_labels.ndim == 0: + g1_labels = g1_labels.reshape(1) + g2_labels = g2_labels.reshape(1) + if g1_labels.ndim < g1_outs.ndim: + g1_labels = g1_labels.unsqueeze(1) + g2_labels = g2_labels.unsqueeze(1) + g1_loss = loss(g1_outs, g1_labels) + g2_outs = net(g2_inputs) + g2_loss = loss(g2_outs, g2_labels) + + val = g1_loss - g2_loss + return torch.abs(val) + + +def fairret_constr(loss, net, c_data): + g1_inputs, g1_labels = c_data[0] + g2_inputs, g2_labels = c_data[1] + g1_logits = net(g1_inputs) + g2_logits = net(g2_inputs) + g1_onehot = torch.tensor([[0.0, 1.0]] * len(g1_inputs)) + g2_onehot = torch.tensor([[1.0, 0.0]] * len(g2_inputs)) + logits = torch.concat([g1_logits, g2_logits]) + sens = torch.vstack([g1_onehot, g2_onehot]) + labels = torch.hstack([g1_labels, g2_labels]).unsqueeze(1) + + return loss(logits, sens, label=labels) + + +def fairret_pr_constr(loss, net, c_data): + g1_inputs, _ = c_data[0] + g2_inputs, _ = c_data[1] + g1_logits = net(g1_inputs) + g2_logits = net(g2_inputs) + g1_onehot = torch.tensor([[0.0, 1.0]] * len(g1_inputs)) + g2_onehot = torch.tensor([[1.0, 0.0]] * len(g2_inputs)) + logits = torch.concat([g1_logits, g2_logits]) + sens = torch.vstack([g1_onehot, g2_onehot]) + + return loss(logits, sens) \ No newline at end of file diff --git a/humancompatible/train/fairness/constraints/torch/__init__.py b/humancompatible/train/fairness/constraints/torch/__init__.py new file mode 100644 index 0000000..37a86c7 --- /dev/null +++ b/humancompatible/train/fairness/constraints/torch/__init__.py @@ -0,0 +1 @@ +from .constraints import loss_equality \ No newline at end of file diff --git a/humancompatible/train/fairness/constraints/torch/constraints.py b/humancompatible/train/fairness/constraints/torch/constraints.py new file mode 100644 index 0000000..6c54145 --- /dev/null +++ b/humancompatible/train/fairness/constraints/torch/constraints.py @@ -0,0 +1,36 @@ +import torch +from torch import Tensor +from torch.nn import Module + +def loss_equality(preds: Tensor, sens: Tensor, labels: Tensor, criterion: Module = None, diff_to_overall: bool = False): + """ + A constraint that penalizes the sum of difference between the loss of each group and the overall loss if`diff_to_overall`is`True`, + and the absolute difference in loss between the two groups if`diff_to_overall`is`False`. + + Args: + logits (torch.Tensor): Predictions of shape :math:`(N)`, as we assume to be performing binary + classification or regression. + sens (torch.Tensor): One-hot encoding of group membership of shape`(N, S)`with`S`the number of sensitive features. + `S`must be 2 if`diff_to_overall`is`True`. + labels (torch.Tensor): Predictions of shape`(N)`. + loss: (torch.nn.Module): The loss function to calculate. + diff_to_overall: (bool): Determines whether to penalize the sum of the absolute difference between + each group's loss and the overall loss if`True`, or the absolute difference in losses of two groups otherwise. + """ + if not diff_to_overall and sens.shape[-1] != 2: + raise ValueError(f"If`diff_to_overall` is`False`, expected`sens.shape[-1]` to be 2, got {sens.shape[-1]}") + + if criterion is None: + criterion = torch.nn.BCEWithLogitsLoss() + + sens_t = sens.T + group_losses = torch.empty(sens.shape[-1]) + for group in range(sens.shape[-1]): + group_preds, group_labels = preds[sens_t[group] == 1], labels[sens_t[group] == 1] + group_losses[group] = criterion(group_preds.squeeze(), group_labels) + + if not diff_to_overall: + return torch.abs(group_losses[0] - group_losses[1]) + + overall_loss = criterion(preds.squeeze(), labels) + return torch.sum(torch.abs(overall_loss-group_losses)) \ No newline at end of file diff --git a/humancompatible/train/fairness/utils/__init__.py b/humancompatible/train/fairness/utils/__init__.py new file mode 100644 index 0000000..19a6faf --- /dev/null +++ b/humancompatible/train/fairness/utils/__init__.py @@ -0,0 +1 @@ +from .balanced_batch_sampler import BalancedBatchSampler \ No newline at end of file diff --git a/humancompatible/train/fairness/utils/balanced_batch_sampler.py b/humancompatible/train/fairness/utils/balanced_batch_sampler.py new file mode 100644 index 0000000..61a5994 --- /dev/null +++ b/humancompatible/train/fairness/utils/balanced_batch_sampler.py @@ -0,0 +1,65 @@ +import numpy as np +import torch +from torch.utils.data import Sampler + +class BalancedBatchSampler(Sampler): + def __init__(self, subgroup_onehot=None, subgroup_indices=None, batch_size=1, drop_last=True): + """ + A Sampler that yields an equal number of samples from each group specified with either one-hot encoding or indices. + + Args: + subset_indices (list of list): List of indices for each subset. Defaults to None. + subgroup_onehot (tensor): Tensor of one-hot-encoded group memberships of shape `(N, S)`, where`S`is the number of subgroups. Defaults to None. + batch_size (int): Number of samples per batch. + drop_last (bool): If True, drop the last incomplete batch. + """ + + if subgroup_indices is None and subgroup_onehot is None: + raise ValueError(f"Exactly one of`subgroup_indices`,`subgroup_onehot`must be`None`") + + if subgroup_onehot is not None: + subgroup_onehot = subgroup_onehot.numpy() + subgroup_indices = [ + np.argwhere(subgroup_onehot[:, gr] == 1).squeeze() for gr in range(subgroup_onehot.shape[-1]) + ] + + self.subset_indices = subgroup_indices + self.batch_size = batch_size + if drop_last is False: + raise NotImplementedError('drop_last=True not supported yet!') + self.drop_last = drop_last + self.n_subsets = len(subgroup_indices) + self.subset_sizes = [len(indices) for indices in subgroup_indices] + self.n_samples_per_subset = batch_size // self.n_subsets + # Check if batch_size is divisible by the number of subsets + assert batch_size % self.n_subsets == 0, ( + f"Batch size ({batch_size}) must be divisible by the number of subsets ({self.n_subsets})." + ) + + def __iter__(self): + # Shuffle indices within each subset + shuffled_subset_indices = [torch.randperm(len(indices)).tolist() for indices in self.subset_indices] + + # Calculate the maximum number of batches per subset + max_batches = min(len(indices) // self.n_samples_per_subset for indices in self.subset_indices) + if not self.drop_last and any(len(indices) % self.n_samples_per_subset != 0 for indices in self.subset_indices): + max_batches += 1 # Include partial batches if drop_last is False + # TODO: randomly permute the batch as well + # Yield balanced batches + for batch_idx in range(max_batches): + batch = [] + for subset_idx in range(self.n_subsets): + start = batch_idx * self.n_samples_per_subset + end = start + self.n_samples_per_subset + subset_batch_indices = shuffled_subset_indices[subset_idx][start:end] + batch.extend([self.subset_indices[subset_idx][i] for i in subset_batch_indices]) + + # Yield the global indices for the batch + yield batch + + def __len__(self): + if self.drop_last: + return min(len(indices) // self.n_samples_per_subset for indices in self.subset_indices) + else: + return max((len(indices) + self.n_samples_per_subset - 1) // self.n_samples_per_subset + for indices in self.subset_indices) \ No newline at end of file diff --git a/humancompatible/train/fairness/utils/tests/__init__.py b/humancompatible/train/fairness/utils/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/humancompatible/train/fairness/utils/tests/test_balanced_batch_sampler.py b/humancompatible/train/fairness/utils/tests/test_balanced_batch_sampler.py new file mode 100644 index 0000000..58e44fb --- /dev/null +++ b/humancompatible/train/fairness/utils/tests/test_balanced_batch_sampler.py @@ -0,0 +1,78 @@ +import unittest +import torch +from torch.utils.data import TensorDataset, Subset, DataLoader +from humancompatible.train.fairness.utils import BalancedBatchSampler + +class TestBalancedBatchSampler(unittest.TestCase): + def setUp(self): + self.data = torch.tensor([[i, i+1] for i in range(10)]) + self.labels = torch.tensor([0, 0, 1, 1, 1, 2, 2, 2, 2, 2]) + self.dataset = TensorDataset(self.data, self.labels) + self.subset_indices = [ + [0, 1], # Class 0 + [2, 3, 4], # Class 1 + [5, 6, 7, 8, 9], # Class 2 + ] + self.subset_onehot = torch.tensor([ + [1, 1, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 1, 1, 1, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 1, 1, 1, 1, 1] + ]).T + + def test_batch_size_divisible(self): + with self.assertRaises(AssertionError): + BalancedBatchSampler(subgroup_indices=self.subset_indices, batch_size=4, drop_last=True) + + def test_onehot_init(self): + sampler = BalancedBatchSampler(subgroup_onehot=self.subset_onehot, batch_size=3) + self.assertListEqual( + [i.tolist() for i in sampler.subset_indices], + self.subset_indices + ) + + def test_iter(self): + sampler = BalancedBatchSampler(subgroup_indices=self.subset_indices, batch_size=6, drop_last=True) + batches = list(sampler) + self.assertEqual(len(batches), 1) # Only 1 full batch of size 6 (2+2+2) + self.assertEqual(len(batches[0]), 6) + + def test_len_drop_last_true(self): + sampler = BalancedBatchSampler(subgroup_indices=self.subset_indices, batch_size=6, drop_last=True) + self.assertEqual(len(sampler), 1) + + def test_balanced_batches(self): + sampler = BalancedBatchSampler(subgroup_indices=self.subset_indices, batch_size=6, drop_last=True) + batch = next(iter(sampler)) + # Check that each subset contributes 2 samples + self.assertEqual(len([i for i in batch if i in self.subset_indices[0]]), 2) + self.assertEqual(len([i for i in batch if i in self.subset_indices[1]]), 2) + self.assertEqual(len([i for i in batch if i in self.subset_indices[2]]), 2) + +class TestDataLoaderIntegration(unittest.TestCase): + def setUp(self): + self.data = torch.tensor([[i, i+1] for i in range(10)]) + self.labels = torch.tensor([0, 0, 1, 1, 1, 2, 2, 2, 2, 2]) + self.dataset = TensorDataset(self.data, self.labels) + self.subset_indices = [ + [0, 1], # Class 0 + [2, 3, 4], # Class 1 + [5, 6, 7, 8, 9], # Class 2 + ] + self.subsets = [Subset(self.dataset, indices) for indices in self.subset_indices] + + def test_dataloader(self): + sampler = BalancedBatchSampler(subgroup_indices=self.subset_indices, batch_size=6, drop_last=True) + dataloader = DataLoader( + self.dataset, + batch_sampler=sampler + ) + batch_data, batch_labels = next(iter(dataloader)) + self.assertEqual(batch_data.shape, (6, 2)) + self.assertEqual(len(batch_labels), 6) + # Check balance: 2 samples from each class + self.assertEqual((batch_labels == 0).sum().item(), 2) + self.assertEqual((batch_labels == 1).sum().item(), 2) + self.assertEqual((batch_labels == 2).sum().item(), 2) + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 7fd26b9..6551352 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,3 +1,28 @@ [build-system] requires = ["setuptools"] -build-backend = "setuptools.build_meta" \ No newline at end of file +build-backend = "setuptools.build_meta" + +[project] +name = "humancompatible-train" +version = "0.1.0" +dependencies = [ + "torch", + "numpy", +] +requires-python = ">= 3.11" +authors = [ + {name = "Andrii Kliachkin", email = "kliachkin.andrii@gmail.com"}, + {name = "Gilles Bareilles"}, + {name = "Jana Lepsova"}, + {name = "Jakub Marecek"}, +] +maintainers = [ + {name = "Andrii Kliachkin", email = "kliachkin.andrii@gmail.com"} +] +description = "PyTorch-based package for constrained training of neural networks" +readme = "README.md" + + +[project.optional-dependencies] +benchmark = ["fairret", "matplotlib", "pandas", "folktables", "pot", "hydra", "omegaconf"] +ghost = ["qpsolvers", "scipy"] \ No newline at end of file diff --git a/requirements_benchmark.txt b/requirements_benchmark.txt new file mode 100644 index 0000000..06e1f9e --- /dev/null +++ b/requirements_benchmark.txt @@ -0,0 +1,68 @@ +asttokens==3.0.0 +certifi==2025.4.26 +charset-normalizer==3.4.2 +colorama==0.4.6 +comm==0.2.2 +contourpy==1.3.2 +cycler==0.12.1 +debugpy==1.8.14 +decorator==5.2.1 +exceptiongroup==1.3.0 +executing==2.2.0 +fairret==0.1.3 +filelock==3.18.0 +folktables==0.0.12 +fonttools==4.58.0 +fsspec==2025.3.2 +hydra-core==1.3.2 +idna==3.10 +ipykernel==6.29.5 +ipython==8.36.0 +jedi==0.19.2 +Jinja2==3.1.6 +joblib==1.5.0 +jupyter_client==8.6.3 +jupyter_core==5.7.2 +kiwisolver==1.4.8 +lightning-utilities==0.14.3 +MarkupSafe==3.0.2 +matplotlib==3.10.3 +matplotlib-inline==0.1.7 +mpmath==1.3.0 +nest-asyncio==1.6.0 +networkx==3.4.2 +numpy==2.2.5 +osqp==1.0.4 +packaging==25.0 +pandas==2.2.3 +parso==0.8.4 +pillow==11.2.1 +pip-system-certs==4.0 +platformdirs==4.3.8 +POT==0.9.5 +prompt_toolkit==3.0.51 +psutil==7.0.0 +pure_eval==0.2.3 +Pygments==2.19.1 +pyparsing==3.2.3 +python-dateutil==2.9.0.post0 +pytz==2025.2 +pywin32==310;sys_platform == 'win_32' +pyzmq==26.4.0 +qpsolvers==4.7.0 +requests==2.32.3 +scikit-learn==1.6.1 +scipy==1.15.3 +seaborn==0.13.2 +six==1.17.0 +stack-data==0.6.3 +sympy==1.14.0 +threadpoolctl==3.6.0 +torch==2.7.0 +torchmetrics==1.7.1 +tornado==6.4.2 +traitlets==5.14.3 +typing_extensions==4.13.2 +tzdata==2025.2 +urllib3==2.4.0 +wcwidth==0.2.13 diff --git a/requirements_mkl.txt b/requirements_benchmark_mkl.txt similarity index 100% rename from requirements_mkl.txt rename to requirements_benchmark_mkl.txt diff --git a/setup.py b/setup.py index 74c3da2..f26a755 100644 --- a/setup.py +++ b/setup.py @@ -1,7 +1,7 @@ from setuptools import find_packages, setup setup( - name="constrained_fairness_benchmark", + name="humancompatible.train", version="0.1", packages=find_packages(), ) diff --git a/src/__init__.py b/src/__init__.py deleted file mode 100644 index b7a800d..0000000 --- a/src/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -# from .algorithms, .constraints - -__all__ = ['algorithms', 'constraints'] \ No newline at end of file diff --git a/src/algorithms/__init__.py b/src/algorithms/__init__.py deleted file mode 100644 index 2f0e059..0000000 --- a/src/algorithms/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -from .ghost import StochasticGhost -from .ssl_alm import SSLALM -from .switching_subgradient import SSG - -__all__ = ["SSLALM", "StochasticGhost", "SSG"] diff --git a/src/algorithms/c_utils/constraint.py b/src/algorithms/c_utils/constraint.py deleted file mode 100644 index 337e192..0000000 --- a/src/algorithms/c_utils/constraint.py +++ /dev/null @@ -1,80 +0,0 @@ -from itertools import cycle -from typing import Callable, Iterable - -import numpy as np -import torch - - -def _dataloader_from_subset(dataset, indices, *args, **kwargs): - data_s = torch.utils.data.Subset(dataset, indices) - loader_s = torch.utils.data.DataLoader(data_s, *args, **kwargs) - return loader_s - - -class FairnessConstraint: - def __init__( - self, - dataset: torch.utils.data.Dataset, - group_indices: Iterable[Iterable[int]], - fn: Callable, - batch_size: int = None, - use_dataloaders=True, - seed=None, - ): - self.dataset = dataset - self.group_sets = [ - torch.utils.data.Subset(dataset, idx) for idx in group_indices - ] - self.fn = fn - self.seed = seed - self.rng = np.random.default_rng(seed) - if batch_size is not None: - self.batch_size = batch_size - if use_dataloaders: - g = torch.Generator() - if seed is not None: - g.manual_seed(seed) - self.dataloaders = [ - cycle( - _dataloader_from_subset( - dataset, - idx, - batch_size=batch_size, - shuffle=True, - generator=g, - ) - ) - for idx in group_indices - ] - - def group_sizes(self): - return [len(group) for group in self.group_sets] - - def eval(self, net, sample, **kwargs): - return self.fn(net, sample, **kwargs) - - def sample_loader(self): - return [next(l) for l in self.dataloaders] - - def sample_dataset( - self, N, rng: np.random.Generator = None, indices=None, return_indices=False - ): - if rng is None: - rng = self.rng - - if indices is None: - indices = [] - # returns len(group) points if N > len(group) - for group in self.group_sets: - indices.append( - rng.choice(group.indices, N) - if N < len(group) - else rng.choice(group.indices, len(group)) - ) - - sample = [self.dataset[indices[i]] for i, _ in enumerate(self.group_sets)] - - if return_indices: - return sample, indices - else: - return sample diff --git a/src/algorithms/c_utils/constraint_fns.py b/src/algorithms/c_utils/constraint_fns.py deleted file mode 100644 index 4cdcf1f..0000000 --- a/src/algorithms/c_utils/constraint_fns.py +++ /dev/null @@ -1,48 +0,0 @@ -import torch - - -def one_sided_loss_constr(loss, net, c_data): - w_inputs, w_labels = c_data[0] - b_inputs, b_labels = c_data[1] - w_outs = net(w_inputs) - if w_labels.ndim == 0: - w_labels = w_labels.reshape(1) - b_labels = b_labels.reshape(1) - if w_labels.ndim < w_outs.ndim: - w_labels = w_labels.unsqueeze(1) - b_labels = b_labels.unsqueeze(1) - w_loss = loss(w_outs, w_labels) - b_outs = net(b_inputs) - b_loss = loss(b_outs, b_labels) - - return w_loss - b_loss - - -def fairret_constr(loss, net, c_data): - w_inputs, w_labels = c_data[0] - b_inputs, b_labels = c_data[1] - w_logits = net(w_inputs) - b_logits = net(b_inputs) - w_onehot = torch.tensor([[0.0, 1.0]] * len(w_inputs)) - b_onehot = torch.tensor([[1.0, 0.0]] * len(b_inputs)) - logits = torch.concat([w_logits, b_logits]) - sens = torch.vstack([w_onehot, b_onehot]) - labels = torch.hstack([w_labels, b_labels]).unsqueeze(1) - # print(logits.shape) - # print(sens.shape) - # print(labels.shape) - - return loss(logits, sens, label=labels) - - -def fairret_pr_constr(loss, net, c_data): - w_inputs, _ = c_data[0] - b_inputs, _ = c_data[1] - w_logits = net(w_inputs) - b_logits = net(b_inputs) - w_onehot = torch.tensor([[0.0, 1.0]] * len(w_inputs)) - b_onehot = torch.tensor([[1.0, 0.0]] * len(b_inputs)) - logits = torch.concat([w_logits, b_logits]) - sens = torch.vstack([w_onehot, b_onehot]) - - return loss(logits, sens) diff --git a/src/algorithms/ssl_alm.py b/src/algorithms/ssl_alm.py deleted file mode 100644 index 747a34f..0000000 --- a/src/algorithms/ssl_alm.py +++ /dev/null @@ -1,233 +0,0 @@ -import timeit -from copy import deepcopy -from typing import Callable - -import numpy as np -import torch - -from src.algorithms.Algorithm import Algorithm -from src.algorithms.utils import _set_weights, net_params_to_tensor - - -class SSLALM(Algorithm): - def __init__( - self, net, data, loss, constraints, custom_project_fn: Callable = None - ): - super().__init__(net, data, loss, constraints) - self.project = custom_project_fn if custom_project_fn else self.project_fn - - @staticmethod - def project_fn(x, m): - for i in range(1, m + 1): - if x[-i] < 0: - x[-i] = 0 - return x - - def optimize( - self, - lambda_bound, - eta, - rho, - tau, - mu, - beta, - batch_size, - epochs, - start_lambda=None, - max_runtime=None, - max_iter=None, - seed=None, - device="cpu", - verbose=True, - ): - m = len(self.constraints) - slack_vars = torch.zeros(m, requires_grad=True) - _lambda = ( - torch.zeros(m, requires_grad=True) if start_lambda is None else start_lambda - ) - - z = torch.concat( - [net_params_to_tensor(self.net, flatten=True, copy=True), slack_vars] - ) - - c = self.constraints - - run_start = timeit.default_timer() - - if epochs is None: - epochs = np.inf - if max_iter is None: - max_iter = np.inf - if max_runtime is None: - max_runtime = np.inf - - gen = torch.Generator(device=device) - if seed is not None: - gen.manual_seed(seed) - loss_loader = torch.utils.data.DataLoader( - self.dataset, batch_size, shuffle=True, generator=gen - ) - loss_iter = iter(loss_loader) - - epoch = 0 - iteration = 0 - total_iters = 0 - while True: - elapsed = timeit.default_timer() - run_start - iteration += 1 - total_iters += 1 - if epoch >= epochs or iteration >= max_iter or elapsed > max_runtime: - break - - self.history["w"].append(deepcopy(self.net.state_dict())) - self.history["time"].append(elapsed) - self.history["n_samples"].append(batch_size * 3) - - try: - (f_inputs, f_labels) = next(loss_iter) - except StopIteration: - epoch += 1 - iteration = 0 - loss_loader = torch.utils.data.DataLoader( - self.dataset, batch_size, shuffle=True, generator=gen - ) - loss_iter = iter(loss_loader) - (f_inputs, f_labels) = next(loss_iter) - - ######################## - ## UPDATE MULTIPLIERS ## - ######################## - self.net.zero_grad() - slack_vars.grad = None - - # sample for and calculate self.constraints (lines 2, 3) - c_sample = [ci.sample_loader() for ci in c] - - c_1 = [ - ci.eval(self.net, c_sample[i]).reshape(1) + slack_vars[i] - for i, ci in enumerate(c) - ] - # update multipliers (line 3) - with torch.no_grad(): - _lambda = _lambda + eta * torch.concat(c_1) - # dual safeguard (lines 4,5) - if torch.norm(_lambda) >= lambda_bound: - _lambda = torch.zeros_like(_lambda, requires_grad=True) - - ####################### - ## UPDATE PARAMETERS ## - ####################### - outputs = self.net(f_inputs) - if f_labels.dim() < outputs.dim(): - f_labels = f_labels.unsqueeze(1) - loss_eval = self.loss_fn(outputs, f_labels) - f_grad = torch.autograd.grad(loss_eval, self.net.parameters()) - f_grad = torch.concat( - [*[g.flatten() for g in f_grad], torch.zeros(m)] - ) # add zeros for slack vars - self.net.zero_grad() - - # constraint grad estimate - c_grad = [] - for ci in c_1: - ci_grad = torch.autograd.grad(ci, self.net.parameters()) - slack_grad = torch.autograd.grad(ci, slack_vars) - c_grad.append( - torch.concat([*[g.flatten() for g in ci_grad], *slack_grad]) - ) - self.net.zero_grad() - slack_vars.grad = None - c_grad = torch.stack(c_grad) - - # independent constraint estimate - with torch.no_grad(): - c_sample = [ci.sample_loader() for ci in c] - c_2 = torch.concat( - [ - ci.eval(self.net, c_sample[i]).reshape(1) + slack_vars[i] - for i, ci in enumerate(c) - ] - ) - - x_t = torch.concat( - [ - net_params_to_tensor(self.net, flatten=True, copy=True), - slack_vars, - ] - ) - - G = f_grad + c_grad.T @ _lambda + rho * (c_grad.T @ c_2) + mu * (x_t - z) - x_t1 = self.project(x_t - tau * G, m) - z += beta * (x_t - z) - with torch.no_grad(): - _set_weights(self.net, x_t1) - for i in range(len(slack_vars)): - slack_vars[i] = x_t1[i - len(slack_vars)] - - if verbose: - with np.printoptions(precision=6, suppress=True, floatmode="fixed"): - print( - f"""{epoch:2}|{iteration:5} | {loss_eval.detach().cpu().numpy()}|{_lambda.detach().cpu().numpy()}|{c_2.detach().cpu().numpy()}|{slack_vars.detach().cpu().numpy()}""", - end="\r", - ) - - ###################### - ### POSTPROCESSING ### - ###################### - - G_hat = torch.zeros_like(G) - - f_inputs, f_labels = self.dataset[:][0], self.dataset[:][1] - cgrad_sample = [ci.sample_dataset(np.inf) for ci in c] - c_sample = [ci.sample_dataset(np.inf) for ci in c] - - self.net.zero_grad() - slack_vars.grad = None - # loss - outputs = self.net(f_inputs) - if f_labels.dim() < outputs.dim(): - f_labels = f_labels.unsqueeze(1) - loss_eval = self.loss_fn(outputs, f_labels) - # loss grad - loss_eval = self.loss_fn(outputs, f_labels) - f_grad = torch.autograd.grad(loss_eval, self.net.parameters()) - f_grad = torch.concat( - [*[g.flatten() for g in f_grad], torch.zeros(m)] - ) # add zeros for slack vars - self.net.zero_grad() - # constraint grad estimate - c_1 = [ - ci.eval(self.net, c_sample[i]).reshape(1) + slack_vars[i] - for i, ci in enumerate(c) - ] - c_grad = [] - for ci in c_1: - ci_grad = torch.autograd.grad(ci, self.net.parameters()) - slack_grad = torch.autograd.grad(ci, slack_vars) - c_grad.append(torch.concat([*[g.flatten() for g in ci_grad], *slack_grad])) - self.net.zero_grad() - c_grad = torch.stack(c_grad) - - # independent constraint estimate - with torch.no_grad(): - c_2 = torch.concat( - [ - ci.eval(self.net, cgrad_sample[i]).reshape(1) + slack_vars[i] - for i, ci in enumerate(c) - ] - ) - x_t = torch.concat( - [net_params_to_tensor(self.net, flatten=True, copy=True), slack_vars] - ) - G_hat += f_grad + c_grad.T @ _lambda + rho * (c_grad.T @ c_2) + mu * (x_t - z) - - x_t1 = self.project(x_t - tau * G_hat, m) - with torch.no_grad(): - _set_weights(self.net, x_t1) - - current_time = timeit.default_timer() - self.history["w"].append(deepcopy(self.net.state_dict())) - self.history["time"].append(current_time - run_start) - self.history["n_samples"].append(batch_size * 3) - - return self.history diff --git a/src/constraints/__init__.py b/src/constraints/__init__.py deleted file mode 100644 index e67a82c..0000000 --- a/src/constraints/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from .constraint import FairnessConstraint -from .constraint_fns import one_sided_loss_constr - -__all__ = ["FairnessConstraint, one_sided_loss_constr"] diff --git a/src/constraints/constraint_fns.py b/src/constraints/constraint_fns.py deleted file mode 100644 index 4cdcf1f..0000000 --- a/src/constraints/constraint_fns.py +++ /dev/null @@ -1,48 +0,0 @@ -import torch - - -def one_sided_loss_constr(loss, net, c_data): - w_inputs, w_labels = c_data[0] - b_inputs, b_labels = c_data[1] - w_outs = net(w_inputs) - if w_labels.ndim == 0: - w_labels = w_labels.reshape(1) - b_labels = b_labels.reshape(1) - if w_labels.ndim < w_outs.ndim: - w_labels = w_labels.unsqueeze(1) - b_labels = b_labels.unsqueeze(1) - w_loss = loss(w_outs, w_labels) - b_outs = net(b_inputs) - b_loss = loss(b_outs, b_labels) - - return w_loss - b_loss - - -def fairret_constr(loss, net, c_data): - w_inputs, w_labels = c_data[0] - b_inputs, b_labels = c_data[1] - w_logits = net(w_inputs) - b_logits = net(b_inputs) - w_onehot = torch.tensor([[0.0, 1.0]] * len(w_inputs)) - b_onehot = torch.tensor([[1.0, 0.0]] * len(b_inputs)) - logits = torch.concat([w_logits, b_logits]) - sens = torch.vstack([w_onehot, b_onehot]) - labels = torch.hstack([w_labels, b_labels]).unsqueeze(1) - # print(logits.shape) - # print(sens.shape) - # print(labels.shape) - - return loss(logits, sens, label=labels) - - -def fairret_pr_constr(loss, net, c_data): - w_inputs, _ = c_data[0] - b_inputs, _ = c_data[1] - w_logits = net(w_inputs) - b_logits = net(b_inputs) - w_onehot = torch.tensor([[0.0, 1.0]] * len(w_inputs)) - b_onehot = torch.tensor([[1.0, 0.0]] * len(b_inputs)) - logits = torch.concat([w_logits, b_logits]) - sens = torch.vstack([w_onehot, b_onehot]) - - return loss(logits, sens)