diff --git a/README.md b/README.md index 6fd33adcc..e67501ab9 100644 --- a/README.md +++ b/README.md @@ -23,11 +23,11 @@


-Concrete ML is a Privacy-Preserving Machine Learning (PPML) open-source set of tools built on top of [Concrete](https://github.com/zama-ai/concrete) by [Zama](https://github.com/zama-ai). It aims to simplify the use of fully homomorphic encryption (FHE) for data scientists to help them automatically turn machine learning models into their homomorphic equivalent. Concrete ML was designed with ease-of-use in mind, so that data scientists can use it without knowledge of cryptography. Notably, the Concrete ML model classes are similar to those in scikit-learn and it is also possible to convert PyTorch models to FHE. +Concrete ML is a Privacy-Preserving Machine Learning (PPML) open-source set of tools built on top of [Concrete](https://github.com/zama-ai/concrete) by [Zama](https://github.com/zama-ai). It simplifies the use of fully homomorphic encryption (FHE) for data scientists to help them automatically turn machine learning models into their homomorphic equivalent. Concrete ML was designed with ease-of-use in mind, so that data scientists can use it without knowledge of cryptography. Notably, the Concrete ML model classes are similar to those in scikit-learn and it is also possible to convert PyTorch models to FHE. ## Main features. -Data scientists can use models with APIs which are close to the frameworks they use, with additional options to run inferences in FHE. +Data scientists can use models with APIs which are close to the frameworks they use, while additional options to those models allow them to run inference or training on encrypted data with FHE. Concrete ML features: @@ -154,6 +154,8 @@ Various tutorials are given for [built-in models](docs/built-in-models/ml_exampl - [Health diagnosis](use_case_examples/disease_prediction/): based on a patient's symptoms, history and other health factors, give a diagnosis using FHE to preserve the privacy of the patient. +- [Private inference for federated learned models](use_case_examples/federated_learning/): private training of a Logistic Regression model and then import the model into Concrete ML and perform encrypted prediction + - [Titanic](use_case_examples/titanic/KaggleTitanic.ipynb): solve the [Kaggle Titanic competition](https://www.kaggle.com/c/titanic/). Implemented with XGBoost from Concrete ML, this example comes as a companion of the [Kaggle notebook](https://www.kaggle.com/code/concretemlteam/titanic-with-privacy-preserving-machine-learning), and was the subject of a blogpost in [KDnuggets](https://www.kdnuggets.com/2022/08/machine-learning-encrypted-data.html). - [Sentiment analysis with transformers](use_case_examples/sentiment_analysis_with_transformer): predict if an encrypted tweet / short message is positive, negative or neutral, using FHE. The [live interactive](https://huggingface.co/spaces/zama-fhe/encrypted_sentiment_analysis) demo is available on Hugging Face. This [blog post](https://huggingface.co/blog/sentiment-analysis-fhe) explains how this demo works! diff --git a/docs/README.md b/docs/README.md index 4ef70a86e..0a4a44f09 100644 --- a/docs/README.md +++ b/docs/README.md @@ -4,10 +4,13 @@ ![](.gitbook/assets/3.png) -Concrete ML is an open source, privacy-preserving, machine learning inference framework based on Fully Homomorphic Encryption (FHE). It enables data scientists without any prior knowledge of cryptography to automatically turn machine learning models into their FHE equivalent, using familiar APIs from scikit-learn and PyTorch (see how it looks for [linear models](built-in-models/linear.md), [tree-based models](built-in-models/tree.md), and [neural networks](built-in-models/neural-networks.md)). +Concrete ML is an open source, privacy-preserving, machine learning framework based on Fully Homomorphic Encryption (FHE). It enables data scientists without any prior knowledge of cryptography to automatically turn machine learning models into their FHE equivalent, using familiar APIs from scikit-learn and PyTorch (see how it looks for [linear models](built-in-models/linear.md), [tree-based models](built-in-models/tree.md), and [neural networks](built-in-models/neural-networks.md)). Concrete ML supports converting models for inference with FHE but can also [train some models](built-in-models/training.md) on encrypted data. Fully Homomorphic Encryption is an encryption technique that allows computing directly on encrypted data, without needing to decrypt it. With FHE, you can build private-by-design applications without compromising on features. You can learn more about FHE in [this introduction](https://www.zama.ai/post/tfhe-deep-dive-part-1) or by joining the [FHE.org](https://fhe.org) community. +Training on encrypted data provides the highest level of privacy but is slower than training on clear data. Federated learning is an alternative approach, where data privacy can be ensured by using a trusted gradient aggregator, coupled with optional _differential privacy_ instead of encryption. Concrete ML +can import linear models, including logistic regression, that are trained using federated learning using the [`from_sklearn` function](./built-in-models/linear.md#pre-trained-models). + ## Example usage Here is a simple example of classification on encrypted data using logistic regression. More examples can be found [here](built-in-models/ml_examples.md). @@ -86,11 +89,11 @@ This example shows the typical flow of a Concrete ML model: To make a model work with FHE, the only constraint is to make it run within the supported precision limitations of Concrete ML (currently 16-bit integers). Thus, machine learning models must be quantized, which sometimes leads to a loss of accuracy versus the original model, which operates on plaintext. -Additionally, Concrete ML currently only supports FHE _inference_. Training has to be done on unencrypted data, producing a model which is then converted to an FHE equivalent that can perform encrypted inference (i.e., prediction over encrypted data). +Additionally, Concrete ML currently only supports training on encrypted data for some models, while it supports _inference_ for a large variety of models. Finally, there is currently no support for pre-processing model inputs and post-processing model outputs. These processing stages may involve text-to-numerical feature transformation, dimensionality reduction, KNN or clustering, featurization, normalization, and the mixing of results of ensemble models. -These issues are currently being addressed, and significant improvements are expected to be released in the coming months. +These issues are currently being addressed, and significant improvements are expected to be released in the near future. ## Concrete stack diff --git a/docs/SUMMARY.md b/docs/SUMMARY.md index fb668d389..330483b41 100644 --- a/docs/SUMMARY.md +++ b/docs/SUMMARY.md @@ -16,6 +16,7 @@ - [Neural Networks](built-in-models/neural-networks.md) - [Nearest Neighbors](built-in-models/nearest-neighbors.md) - [Pandas](built-in-models/pandas.md) +- [Encrypted training](built-in-models/training.md) - [Built-in Model Examples](built-in-models/ml_examples.md) ## Deep Learning diff --git a/docs/advanced-topics/advanced_features.md b/docs/advanced-topics/advanced_features.md index cc9fccbe7..d30180a9b 100644 --- a/docs/advanced-topics/advanced_features.md +++ b/docs/advanced-topics/advanced_features.md @@ -6,25 +6,25 @@ Concrete ML provides features for advanced users to adjust cryptographic paramet Concrete ML makes use of table lookups (TLUs) to represent any non-linear operation (e.g., a sigmoid). TLUs are implemented through the Programmable Bootstrapping (PBS) operation, which applies a non-linear operation in the cryptographic realm. -The result of TLU operations is obtained with a specific error probability. Concrete ML offers the possibility to set this error probability, which influences the cryptographic parameters. The higher the success rate, the more restrictive the parameters become. This can affect both key generation and, more significantly, FHE execution time. +The result of TLU operations is obtained with a specific tolerance to off-by-one errors. Concrete ML offers the possibility to set the probability of such errors occurring, which influences the cryptographic parameters. The lower the tolerance, the more restrictive the parameters become, making both key generation and, more significantly, FHE execution time slower. {% hint style="info" %} Concrete ML has a _simulation_ mode where the impact of approximate computation of TLUs on the model accuracy can be determined. The simulation is much faster, speeding up model development significantly. The behavior in simulation mode is representative of the behavior of the model on encrypted data. {% endhint %} -In Concrete ML, there are three different ways to define the error probability: +In Concrete ML, there are three different ways to define the tolerance to off-by-one errors for each TLU operation: -- setting `p_error`, the error probability of an individual TLU (see [here](advanced_features.md#an-error-probability-for-an-individual-tlu)) -- setting `global_p_error`, the error probability of the full circuit (see [here](advanced_features.md#a-global-error-probability-for-the-entire-model)) +- setting `p_error`, the error probability of an individual TLU (see [here](advanced_features.md#tolerance-to-off-by-one-error-for-an-individual-tlu)) +- setting `global_p_error`, the error probability of the full circuit (see [here](advanced_features.md#a-global-tolerance-for-one-off-errors-for-the-entire-model)) - not setting `p_error` nor `global_p_error`, and using default parameters (see [here](advanced_features.md#using-default-error-probability)) {% hint style="warning" %} -`p_error` and `global_p_error` are somehow two concurrent parameters, in the sense they both have an impact on the choice of cryptographic parameters. It is forbidden in Concrete ML to set both `p_error` and `global_p_error` simultaneously. +`p_error` and `global_p_error` cannot be set at the same time, as they are incompatible with each other. {% endhint %} -### An error probability for an individual TLU +### Tolerance to off-by-one error for an individual TLU -The first way to set error probabilities in Concrete ML is at the local level, by directly setting the probability of error of each individual TLU. This probability is referred to as `p_error`. A given PBS operation has a `1 - p_error` chance of being successful. The successful evaluation here means that the value decrypted after FHE evaluation is exactly the same as the one that would be computed in the clear. +The first way to set error probabilities in Concrete ML is at the local level, by directly setting the tolerance to error of each individual TLU operation (such as activation functions for a neuron output). This tolerance is referred to as `p_error`. A given PBS operation has a `1 - p_error` chance of being correct 100% of the time. The successful evaluation here means that the value decrypted after FHE evaluation is exactly the same as the one that would be computed in the clear. Otherwise, off-by-one errors might occur, but, in practice, these errors are not necessarily problematic if they are sufficiently rare. For simplicity, it is best to use [default options](advanced_features.md#using-default-error-probability), irrespective of the type of model. Especially for deep neural networks, default values may be too pessimistic, reducing computation speed without any improvement in accuracy. For deep neural networks, some TLU errors might not affect the accuracy of the network, so `p_error` can be safely increased (e.g., see CIFAR classifications in [our showcase](../getting-started/showcase.md)). @@ -63,9 +63,9 @@ clf.compile(X_train, p_error=0.1) If the `p_error` value is specified and [simulation](compilation.md#fhe-simulation) is enabled, the run will take into account the randomness induced by the choice of `p_error`. This results in statistical similarity to the FHE evaluation. -### A global error probability for the entire model +### A global tolerance for one-off-errors for the entire model -A `global_p_error` is also available and defines the probability of success for the entire model. Here, the `p_error` for every PBS is computed internally in Concrete such that the `global_p_error` is reached. +A `global_p_error` is also available and defines the probability of 100% correctness for the entire model, compared to execution in the clear. In this case, the `p_error` for every TLU is determined internally in Concrete such that the `global_p_error` is reached for the whole model. There might be cases where the user encounters a `No cryptography parameter found` error message. Increasing the `p_error` or the `global_p_error` in this case might help. @@ -78,7 +78,7 @@ Usage is similar to the `p_error` parameter: clf.compile(X_train, global_p_error=0.1) ``` -In the above example, XGBoostClassifier in FHE has a 1/10 probability to have a shifted output value compared to the expected value. The shift is relative to the expected value, so even if the result is different, it should be **around** the expected value. +In the above example, XGBoostClassifier in FHE has a 1/10 probability to have a one-off output value compared to the expected value. The shift is relative to the expected value, so even if the result is different, it should be **close** to the expected value. ### Using default error probability @@ -162,7 +162,7 @@ $$t = L - P$$ Then, the rounding operation can be computed as: -$$ \mathrm{round\_to\_t\_bits}(x, t) = \left\lfloor \frac{x}{2^t} \right\rceil \cdot 2^t $$ +$$ \mathrm{round\_to\_P\_bits}(x, t) = \left\lfloor \frac{x}{2^t} \right\rceil \cdot 2^t $$ where $$x$$ is the input number, and $$\lfloor \cdot \rceil$$ denotes the operation that rounds to the nearest integer. diff --git a/docs/advanced_examples/LogisticRegressionTraining.ipynb b/docs/advanced_examples/LogisticRegressionTraining.ipynb index ef2acb7a3..9c721c9f7 100644 --- a/docs/advanced_examples/LogisticRegressionTraining.ipynb +++ b/docs/advanced_examples/LogisticRegressionTraining.ipynb @@ -6,13 +6,19 @@ "source": [ "# Logistic Regression Training\n", "\n", - "In this notebook, a logistic regression model is trained using stochastic gradient descent.\n", - "First a Scikit-Learn model is trained as the baseline, then a Concrete ML quantized model is trained, and then a Concrete ML model is trained on encrypted data using Fully Homomorphic Encryption, first with the simulation mode and then in FHE." + "This notebook shows how to train a logistic regression model on encrypted data using stochastic gradient descent (SGD). During this process,\n", + "the training set remains encrypted at all times and the gradients and loss are encrypted, thus unaccessible by the server performing the training. \n", + "\n", + "The result of the encrypted training is a set of encrypted model weights that can only be decrypted by the training set secret-key owner. In Concrete ML the `fit` function encrypts the training data, trains the model producing encrypted weights and then decrypts the weights. The model can then be used in on clear data, or on new encrypted data.\n", + "\n", + "Training on encrypted data is especially useful when multiple parties collaborate confidentially, meaning they provide encrypted shares of a training set. \n", + "\n", + "In this notebook, a Scikit-Learn model is first trained as the baseline. Next, a Concrete ML model is trained on encrypted data using Fully Homomorphic Encryption." ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -40,14 +46,17 @@ " Z = Z.reshape(xx.shape)\n", "\n", " # Define red and blue color map\n", - " cmap_light = ListedColormap([\"#FFAAAA\", \"#AAAAFF\"])\n", - " cmap_bold = ListedColormap([\"#FF0000\", \"#0000FF\"])\n", + " cm_bright = ListedColormap([\"#FF0000\", \"#0000FF\"])\n", "\n", " # Plotting the results\n", " plt.figure(figsize=(10, 6))\n", - " plt.contourf(xx, yy, Z, alpha=0.3, cmap=cmap_light)\n", - " plt.scatter(X[:, 0], X[:, 1], c=y, edgecolor=\"k\", cmap=cmap_bold)\n", - " plt.title(f\"{title} (Iterations: {n_iterations}, Accuracy: {accuracy})\")\n", + " plt.contourf(xx, yy, Z, alpha=0.3, cmap=cm_bright)\n", + " plt.scatter(X[:, 0], X[:, 1], c=y, edgecolor=\"k\", cmap=cm_bright)\n", + " plt.title(\n", + " f\"{title} (Iterations: {n_iterations}, Accuracy: {accuracy})\\n \"\n", + " f\"Learned weights: {clf.coef_[0][0]:.3f}, {clf.coef_[0][1]:.3f}, \"\n", + " f\"{clf.intercept_.reshape((-1,))[0]:.3f} \"\n", + " )\n", " plt.xlabel(\"Feature 1\")\n", " plt.ylabel(\"Feature 2\")\n", "\n", @@ -78,16 +87,17 @@ "\n", "\n", "# Load the Iris dataset\n", - "X, y = datasets.load_iris(return_X_y=True)\n", - "X = MinMaxScaler(feature_range=[-1, 1]).fit_transform(X)\n", + "Xfull, y = datasets.load_iris(return_X_y=True)\n", + "Xfull = MinMaxScaler(feature_range=[-1, 1]).fit_transform(Xfull)\n", "\n", "# Select petal length and petal width for visualization\n", - "X = X[:, 2:4] # Petal length and petal width\n", + "X = Xfull[:, 2:4] # Petal length and petal width\n", "\n", "# Filter the dataset for binary classification (Versicolor and Virginica)\n", "# These correspond to target labels 1 and 2 in the Iris dataset\n", "binary_filter = (y == 1) | (y == 2)\n", "X_binary = X[binary_filter]\n", + "Xfull_binary = Xfull[binary_filter]\n", "y_binary = y[binary_filter] - 1" ] }, @@ -95,19 +105,19 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Sklearn Clear Training\n", + "## Baseline Scikit-learn Training on Clear Data \n", "\n", - "Training of the typical Scikit-Learn baseline." + "Training of the typical Scikit-Learn baseline. A Logistic Regression model is trained using SGD. " ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -139,18 +149,45 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Concrete ML Clear Training\n", - "Training of the a typical Concrete ML model. This handles quantization so that FHE compilation is possible." + "## Training on Encrypted Data with Concrete ML\n", + "\n", + "Training over encrypted data in FHE using SGD. Compared to the equivalent scikit-learn class, two new parameters need to be set: `fit_encrypted=True` and `parameters_range`. " ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Compiling training circuit ...\n", + "Compilation took 2.8851 seconds.\n", + "Key Generation...\n", + "Key generation took 5.9258 seconds.\n", + "Training on encrypted data...\n", + "Iteration 0 took 3.9328 seconds.\n", + "Iteration 1 took 3.3114 seconds.\n", + "Iteration 2 took 3.5336 seconds.\n", + "Iteration 3 took 4.1602 seconds.\n", + "Iteration 4 took 3.9363 seconds.\n", + "Iteration 5 took 3.9606 seconds.\n", + "Iteration 6 took 3.7548 seconds.\n", + "Iteration 7 took 3.9216 seconds.\n", + "Iteration 8 took 3.9122 seconds.\n", + "Iteration 9 took 3.9069 seconds.\n", + "Iteration 10 took 3.7588 seconds.\n", + "Iteration 11 took 3.9522 seconds.\n", + "Iteration 12 took 3.8692 seconds.\n", + "Iteration 13 took 3.9916 seconds.\n", + "Iteration 14 took 4.0708 seconds.\n" + ] + }, { "data": { - "image/png": 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b+pOWgurVq7Np0yYiIyNxcXF5qTbyBUUIMyIiIhRA6dChQ7q2P3PmjAIogwcPNln+4YcfKoDy559/Gpf5+PgogHLw4EHjstDQUMXW1lYZO3ascdmkSZMUQFm/fn2yxzMYDIqiKMq+ffsUQCldurTy7Nkzk/Vly5ZVWrRoYdxWURTl2bNnSqlSpZRmzZoZl02fPl0BlKCgIJPHuHHjhqLRaJSvvvrKZPm///6rWFlZJVv+ol9++UUBlL/++kuZM2eO4uzsbIzx7bffVho3bmx8Ptq0aWOyL6AMHz481fbN6d27t1KgQIFkyxcvXqwAyowZM5KtS/r8AMrkyZON/x40aJBSpEgR5eHDhyb7BAQEKK6ursbjiYuLU6Kjo022efz4sVK4cGFl4MCBxmVBQUEKoLi4uCihoaHpOiZHR0elX79+yZZPnjxZAZQePXokW5f0Wki0cuXKZNdd4jlKeu7Te30mXnv79u0zLmvYsKECKMuWLTMui46OVry8vJQuXboYl33//fcKoGzcuNG4TKfTKX5+fsnaTFSuXDmlVatWyZYnlfg6HDZsmMnynj17vvS5fdlrx9XVNc1ruF+/foqPj4/x3xs3blQA5X//+5/Jdl27dlVUKpVy7do1k8ezsbExWXb27FkFUGbPnp3q4yaeu6JFiyqRkZHG5atXr1YAZdasWYqiKEpMTIzi6emp+Pv7Kzqdzrjd1q1bFUCZNGmScVnDhg2Vhg0bpnmMia+BAgUKKGFhYcblmzZtUgBly5YtxmVVq1ZVihQpooSHhxuX7dq1SwFM2lSU5Nd8TEyM4u/vr7z11lsmywFFrVYr//33n8nyy5cvK4Ayf/58k+Xt27dXSpYsaXKuXxQbG6uoVCqT10eixNfpgwcPjMvatGmTLH5FUZTly5crarVaOXTokMnyBQsWKIBy5MiRNI9DUdL/XKT03vLi+0JoaKhiY2OjNG/eXNHr9cbt5syZowDK4sWLjcvS+x7QoUMHpVKlSske+0WA2esqNX/99ZcCKL/88ovZ9R9//LEyfvx4ZdWqVcrKlSuVfv36KYBSr149JTY2NkOPldR3332n2NvbG19TV65cUQBlw4YNJts1aNBAcXZ2VoKDg02WJ73G+vbtq6jVauWvv/5K9jiJ2yVeWy9K7X19x44dybY393nRokULpXTp0sZ/h4eHK87Ozkrt2rVN3gtejLtu3bpK7dq1TdavX7/e5H098fl+8TvHixK/m4SEhCRbV7NmTaVOnTqp7t+uXTvFzc3N5D0uMUZA+e6778zuN3z4cLPPa1K//fabAignTpxIdbv8ToYLCrMShxA4Ozuna/s//vgDgDFjxpgsHzt2LECye7cqVqxI/fr1jf8uVKgQ5cuX5/r168Zl69ato0qVKmZ/uX+xJ6Jfv34mXd1nzpzh6tWr9OzZk0ePHvHw4UMePnzI06dPadKkCQcPHsRgMKR6TOvXr8dgMNCtWzfj/g8fPsTLy4uyZcum2OtgTrdu3dDpdGzduhWtVsvWrVszfaggwKNHj8z+crVu3ToKFixo9mbZlHp1FEVh3bp1tGvXDkVRTJ6DFi1aEBERYRz6pdFojL8sGgwGwsLCiIuLo0aNGibDwxJ16dLF2Fv4qszdf5b0WoiKiuLhw4fUqVMHwGw8L0rP9ZkSJycnk1/9bWxsqFWrlsm+O3bsoGjRorRv3964zM7OjnfeeSfFdt3d3dO8fy/xdfjBBx+YLE/slUqUkXP7MtcOgJubGydOnODOnTupxvxi/BqNJln8Y8eORVEUtm/fbrK8adOmJr0Pr732Gi4uLuk6TwB9+/Y1eY/r2rUrRYoUMT6Pf//9N6GhoQwbNszkXp82bdrg5+f3Svekdu/e3eS1mni9JcZ+9+5dzpw5Q79+/XB1dTVu16xZMypWrJisvaTX/OPHj4mIiKB+/fpmr/eGDRsma6NcuXLUrl3bZHhXWFgY27dvp1evXqme67CwMBRFMfvekxFr1qyhQoUK+Pn5mVyTb731FkCy91xzxwEZey7SY8+ePcTExDBq1CiTe33feecdXFxckl0H6XkPcHNz49atW2aHiCalKEqm92JNmzaNr7/+mm7duhEQEMCSJUv46quvOHLkyCtNa7BixQratGljfE2VLVuW6tWrm1xTDx484ODBgwwcOJASJUqY7J94jRkMBjZu3Ei7du2S9eIk3S6jSpUqRYsWLZItT3q9RERE8PDhQxo2bMj169eJiIgA4kdHaLVaPv7442T3/SWNp2/fvpw4ccJkKPWKFSsoXry48d60JUuWoChKmtMwJFZvNlccy87OLs3qzkOHDiU8PJzu3btz+vRprly5wqhRo/j7779N2n8Zia/1zLynPC+SJEuYldj9q9Vq07V9cHAwarWaMmXKmCz38vLCzc2N4OBgk+UvvrlC/Iv28ePHxn8HBgbi7++frscvVaqUyb8Txxr369ePQoUKmfz9/PPPREdHG988U3L16lUURaFs2bLJ2rh48SKhoaHpig3iv6Q3bdqU3377jfXr16PX6+natWu6988IxUw1p8DAQMqXL28yrjstDx48IDw8nIULFyY7/gEDBgCYPAdLly7ltddew87OjgIFClCoUCG2bdtm9nl+8Xy9CnNthYWFMXLkSOM480KFChm3S+u8Q/quz5QUK1Ys2ZeAF/cNDg7G19c32XYvvn6SUhQlzS8Xia/DF4c9JR2TDxk7ty9z7UD8PZ3nz5+nePHi1KpVi88//zzN5Cc4OBhvb+9kP+5UqFDBuD6pVzlPQLKhMiqVijJlyhjv5Uh8vBefPwA/P79k8WTEi7EnfmlJjD2xbXPDeczFs3XrVurUqYOdnR0eHh4UKlSI+fPnZ+j117dvX44cOWJ87DVr1hAbG0ufPn3SdUzm3nsy4urVq/z333/Jrsly5coBJHvPTek4MvJcpEdK14GNjQ2lS5dOdh2k5z1g/PjxODk5UatWLcqWLcvw4cNN7hfObqNHj0atVrNnz56X2v/ixYucPn2aevXqce3aNeNfo0aN2Lp1q/GH28T3gNQ+2x88eEBkZGS6P//TK6Xr5ciRIzRt2hRHR0fc3NwoVKiQcQqUxGsmMWlKK6bu3btja2trTCwjIiLYunVrmj9UmJOY/L14PyKQrqIdrVq1Yvbs2Rw8eJDXX3+d8uXLs23bNuOQzFcZGpr4Wn/ZhDe/kHuyhFkuLi54e3tneMK59L7gUqrc9LIf0i++2ST2Uk2fPj3Z/UCJ0nqDMRgMqFQqtm/fbjbejL5B9ezZk3feeYd79+7RqlWrl76XIzUFChRI9xfMtCQ+h71796Zfv35mt3nttdeA+OIg/fv3p2PHjowbNw5PT080Gg3Tpk0zW1gjMys6mWurW7duHD16lHHjxlG1alWcnJwwGAy0bNkyzR5MeLXrM7Ov7USPHz9+6fHzL8rIuX1Z3bp1o379+mzYsIFdu3Yxffp0vvnmG9avX2+8L+VVZdVz/TJUKpXZx9Xr9Wa3z8zYDx06RPv27WnQoAHz5s2jSJEiWFtb88svv5idPiKl119AQACjR49mxYoVfPLJJ/z666/UqFHDbFKXVOK8TK/63mMwGKhcuTIzZswwu7548eIm/zZ3HBl9LrJCes5thQoVuHz5Mlu3bmXHjh2sW7eOefPmMWnSJKZMmZItcSZlb29PgQIFCAsLe6n9f/31VyA+WRs9enSy9evWrTP+gJNZUvq+kdJrztz1EhgYSJMmTfDz82PGjBkUL14cGxsb/vjjD3744Yd0fV4k5e7uTtu2bVmxYgWTJk1i7dq1REdHv1Qlx8SCY3fv3k127d+9e5datWql2caIESMYMGAA586dw8bGhqpVq7Jo0SIA448XLyPxtZ703niRnCRZIkVt27Zl4cKFHDt2jLp166a6rY+PDwaDgatXrxp/dYb4m+vDw8Nfar4RX1/fl55VPPGXfBcXF7OV9pJK6Y3a19cXRVEoVarUK70ZJerUqRPvvvsux48fZ9WqVa/cnjl+fn6sWLGCiIgIkyFGvr6+nDhxgtjY2HSXzU6sTqfX69N8DteuXUvp0qVZv369yfM5efLklzuQJDL6S9njx4/Zu3cvU6ZMMZkwMWklJUvz8fHhwoULyXqnrl27Znb7uLg4bt68aTK8MKV2DQaDsfcp0YtzUWXk3L7MtZOoSJEiDBs2jGHDhhEaGsrrr7/OV199lWKS5ePjw549e9BqtSa9WZcuXTKuz0wvXhOKonDt2jVjgpn4eJcvXzYOWUt0+fJlk3jc3d3N9tS9bG9XYtvmrtsXz+e6deuws7Nj586dJkOLfvnllww9poeHB23atGHFihX06tWLI0eOpGs+KysrK3x9fQkKCkrX46T2nnv27FmaNGny0r+QZ+S5SO9jJL0Oks4hFBMTQ1BQUJqvoZQ4OjrSvXt3unfvTkxMDJ07d+arr75iwoQJ2TY9RCKtVsvDhw9fahi3oij89ttvNG7cmGHDhiVb/+WXX7JixQoGDBhgfP5S+2wvVKgQLi4uaX7+J/b+hoeHm/xomZHX3JYtW4iOjmbz5s0mvcsvDk1N/E5x/vz5VEccQHyPcIcOHfjrr79YsWIF1apVS7NgkjmJPxD//fffJgnVnTt3uHXrlrFgS1ocHR1NvsPt2bMHe3t76tWrl+GYEgUFBaFWqzPlu1FeJsMFRYo++ugjHB0dGTx4MPfv30+2PjAwkFmzZgHxc0EByT6QE3+RNFfdLC1dunTh7NmzZksWp/Vrb/Xq1fH19eW7777jyZMnydYnLbGaOK/Si6V4O3fujEajYcqUKckeT1GUZOXA0+Lk5MT8+fP5/PPPadeuXYb2Ta+6deuiKIrJ/BcQ/1w+fPiQOXPmJNsnpedSo9HQpUsX1q1bZ/bDLulzmPjLbdK2Tpw4wbFjx17qOJJydHTM0ETR5mKB5NemJbVo0YLbt2+zefNm47KoqCh++ukns9tfuHCBqKioNCt9JiYvL1asfPHYM3JuX+ba0ev1yYZmeXp64u3tbXboS6LWrVuj1+uTPdYPP/yASqXKtB6wRMuWLTMZEr127Vru3r1rfJwaNWrg6enJggULTOLevn07Fy9eNHlf8/X15dKlSybP3dmzZ196CFiRIkWoWrUqS5cuNXkud+/enWzKA41Gg0qlMvkF/8aNGy81iXefPn24cOEC48aNQ6PREBAQkK796tata7zXIy2Ojo5mh+5169aN27dvm30d6HQ6nj59mmbbGXku0vve0rRpU2xsbPjxxx9NrvlFixYRERHxUp9vL35+2NjYULFiRRRFMSntnd4S7ukVFRVl9jaAL7/8EkVRaNmyZYbbPHLkCDdu3GDAgAF07do12V/37t3Zt28fd+7coVChQjRo0IDFixcnO67E51atVtOxY0e2bNli9ppK3C4x8Uk6sW5iWf70Mvd5ERERkSwpb968Oc7OzkybNo2oqCiz8SRq1aoVBQsW5JtvvuHAgQPJerHSW8K9UqVK+Pn5sXDhQpPref78+ahUKpNbDiIiIrh06VKaQ2KPHj3K+vXrGTRokMkPsRl16tQpKlWq9Ept5AfSkyVS5Ovry2+//Ub37t2pUKECffv2xd/fn5iYGI4ePcqaNWuM84pUqVKFfv36sXDhQsLDw2nYsCEnT55k6dKldOzYkcaNG2f48ceNG8fatWt5++23GThwINWrVycsLIzNmzezYMGCVGe1V6vV/Pzzz7Rq1YpKlSoxYMAAihYtyu3bt9m3bx8uLi5s2bIFiE/IIL60cEBAANbW1rRr1w5fX1/+97//MWHCBG7cuEHHjh1xdnYmKCiIDRs2MGTIED788MMMHVNKQ7PM+fvvv/nf//6XbHmjRo2M80G96M0336RAgQLs2bPH5Jf3vn37smzZMsaMGcPJkyepX78+T58+Zc+ePQwbNszs/DgQP5nhvn37qF27Nu+88w4VK1YkLCyMf/75hz179hiHlrRt25b169fTqVMn2rRpQ1BQEAsWLKBixYpmk9yMqF69Onv27GHGjBl4e3tTqlQpateuneL2Li4uNGjQgG+//ZbY2FiKFi3Krl270v0re3Z49913mTNnDj169GDkyJEUKVKEFStWGH+9fvEX9t27d+Pg4ECzZs1Sbbdq1ar06NGDefPmERERwRtvvMHevXvN9pCl99y+zLWj1WopVqwYXbt2pUqVKjg5ObFnzx7++usvvv/++xTjb9euHY0bN+bTTz/lxo0bVKlShV27drFp0yZGjRqV5hxMGeXh4cGbb77JgAEDuH//PjNnzqRMmTLGAiTW1tZ88803DBgwgIYNG9KjRw9jCfeSJUuaDIsaOHAgM2bMoEWLFgwaNIjQ0FAWLFhApUqVXnouomnTptGmTRvefPNNBg4cSFhYmHFupaSvqzZt2jBjxgxatmxJz549CQ0NZe7cuZQpU4Zz585l6DHbtGlDgQIFWLNmDa1atcLT0zNd+3Xo0IHly5dz5cqVNH/drl69OqtWrWLMmDHUrFkTJycn2rVrR58+fVi9ejXvvfce+/bto169euj1ei5dusTq1auNcxylFX96n4v0vrcUKlSICRMmMGXKFFq2bEn79u25fPky8+bNo2bNmi81FKx58+Z4eXlRr149ChcuzMWLF5kzZ45J4QjIWAn3OXPmEB4ebiw2s2XLFuMcee+//z6urq7cu3ePatWq0aNHD+NEtjt37uSPP/6gZcuWyV7PicUZXpwzLKkVK1ag0WhSTDbbt2/Pp59+yu+//86YMWP48ccfefPNN3n99dcZMmQIpUqV4saNG2zbto0zZ84AMHXqVHbt2kXDhg2N5fzv3r3LmjVrOHz4MG5ubjRv3pwSJUowaNAg448CixcvplChQulOTJs3b46NjQ3t2rXj3Xff5cmTJ/z00094enpy9+5d43YuLi788MMPDB48mJo1axrnZjx79izPnj0zSeysra0JCAhgzpw5aDQaevToYfKY6S3hDvG3PLRv357mzZsTEBDA+fPnmTNnDoMHDzYZNbRhwwYGDBjAL7/8YvxeFhwcTLdu3Wjfvr1xKpMFCxbw2muvMXXqVJPHCQ4OZvny5QDGxDbx+4ePj4/JfZmxsbEcOHDAbK+leEEWVi4UecSVK1eUd955RylZsqRiY2OjODs7K/Xq1VNmz56tREVFGbeLjY1VpkyZopQqVUqxtrZWihcvrkyYMMFkG0UxX7JcUcyXQH706JEyYsQIpWjRooqNjY1SrFgxpV+/fsay04mlmNesWWM29tOnTyudO3dWChQooNja2io+Pj5Kt27dlL1795ps9+WXXypFixZV1Gp1stKq69atU958803F0dFRcXR0VPz8/JThw4crly9fTvV5S1rCPTUplXBP6e/LL79Mtb0PPvhAKVOmTLLlz549Uz799FPj+fHy8lK6du2qBAYGmjxu0jLciqIo9+/fV4YPH64UL17cuF+TJk2UhQsXGrcxGAzK1KlTFR8fH8XW1lapVq2asnXr1hTLV0+fPj3VY0jq0qVLSoMGDRR7e3sFMJZcNlcaOtGtW7eUTp06KW5uboqrq6vy9ttvK3fu3El2fCmV+k3P9ZlSCXdzZZlffB4URVGuX7+utGnTRrG3t1cKFSqkjB07Vlm3bp0CKMePHzfZtnbt2krv3r1TfpKS0Ol0ygcffKAUKFBAcXR0VNq1a6fcvHnzpc+tomT82omOjlbGjRunVKlSRXF2dlYcHR2VKlWqKPPmzUvzedFqtcro0aMVb29vxdraWilbtqwyffr0ZCXESWGaAx8fH7NluZNKPHcrV65UJkyYoHh6eir29vZKmzZtkpWVVhRFWbVqlVKtWjXF1tZW8fDwUHr16qXcunUr2Xa//vqrUrp0acXGxkapWrWqsnPnzgy9Bsydo3Xr1ikVKlRQbG1tlYoVKyrr1683+7wtWrRIKVu2rGJra6v4+fkpv/zyi9kS1yk9b0kNGzZMAZTffvst1e2Sio6OVgoWLJjs/cnc6/TJkydKz549FTc3t2Tl6GNiYpRvvvlGqVSpkmJra6u4u7sr1atXV6ZMmaJERESk6zjS+1yk9N5i7n1BUeJLtvv5+SnW1tZK4cKFlaFDhyqPHz822Sa97wH/93//pzRo0MD42eTr66uMGzfO5BgTjzO9JdwTy5Sb+0s8lsePHyu9e/dWypQpozg4OCi2trZKpUqVlKlTpyoxMTHJ2ixYsGCqpcJjYmKUAgUKKPXr1081tlKlSinVqlUz/vv8+fPG92g7OzulfPnyysSJE032CQ4OVvr27asUKlRIsbW1VUqXLq0MHz7cZLqQU6dOKbVr11ZsbGyUEiVKKDNmzMjQ+7qiKMrmzZuV1157TbGzs1NKliypfPPNN8apK168BjZv3qy88cYbir29veLi4qLUqlVLWblyZbI2T548qQBK8+bNk61Lbwn3RBs2bFCqVq2q2NraKsWKFVM+++yzZOcq8ZiTlu0PCwtTOnTooHh5eSk2NjZKqVKllPHjxycr6a4oz98Tzf29eP1t375dAZSrV6+mK/78TKUoFrhDWAiRZa5fv46fnx/bt2+nSZMmlg5HZMDMmTMZPXo0t27domjRokD8dASvv/46//zzT4pFXITITKNHj2bRokXcu3fPOHFpenz55Zf88ssvXL16NcXiDyL3uHDhApUqVTI7obVI3dmzZ6latSrLli1Ld3XO3KJjx46oVCqzt3IIU5JkCZEHDR06lGvXrrF7925LhyJSoNPpks3nVa1aNfR6PVeuXDEuDwgIwGAwsHr1akuEKfKZqKgoihcvTtu2bTNcOOPJkyeULl2aH374gV69emVRhCK7zJ07lxUrVnD06FFLh5LrjBgxgqVLl3Lv3j3jfd95wcWLF6lcuTJnzpzJ9BL7eZEkWUIIYQGtWrWiRIkSVK1alYiICH799Vf+++8/VqxYkSUTVQuRmtDQUPbs2cPatWvZuHGj9JwK8RK2bNnChQsXmDhxIiNGjEhxOgKRP0iSJYQQFjBz5kx+/vlnbty4gV6vp2LFinz00Ud0797d0qGJfGj//v00btwYT09P4xdEIUTGlCxZkvv379OiRQuWL1+ebGJ1kb9IkiWEEEIIIYQQmUjmyRJCCCGEEEKITCRJlhBCCCGEEEJkIpmMOA0Gg4E7d+7g7OycbIJQIYQQQgghRP6hKAparRZvb2/U6pT7qyTJSsOdO3coXry4pcMQQgghhBBC5BA3b96kWLFiKa6XJCsNiZVhbv79Ny5OThaORuQJjx9z94kTj51KGBe5u1swHiGEEEIIkS5PnkRSo0bxNKtHSpKVhsQhgi5OTrhIKU6RGWJjeaI4E+vkYlwkl5YQQgghRO6R1m1EUvhCCCGEEEIIITKRJFlCCCGEEEIIkYkkyRJCCCGEEEKITCT3ZAkhhBBCCJEDKIqCwRCHougtHUq+pVJpUKutXnnqJkmyhBBCCCGEsDC9PoYnT+4SF/cMmZrVchQFrKwccHIqgkZj89LtSJIlhBBCCCGEBSmKgfDwIGxtNXh6emNtbQNIppX9FGJjY3j06AHh4UF4eJRFpXq5u6skyRJCCCGEEMKC9PoYwEDhwsWxt3ewdDj5mp2dPVZW1oSEBKPXx2BlZfdS7UjhCyGEEEIIISxMpeKle01E5lKp1K88ZFN6soQQQgghhMgD1GrQGGJR2VgblykxsejV1hgMFgwsH5IkSwghhBBCiFxMpQIrVVz8Pzash7Vr4fFjcHeHrl3RdOmCRg1xihWKYtlY8wtJsoQQQgghhMilVCqw0hhgxy5UAwfC/fum69euhcKFURYvxqplS+L0aoskWra2Klav3kCHDh2z/8EtQAZ+CiGEEEIIkUtZqeJgxw5U7dsnS7CM7t+PX79jx/Mer0x07949Ro16n/LlS+PsbIuvb3E6dWrHn3/uzfTHehmKojBlyiR8fIrg6mpPy5ZNuXr1apY+piRZQgghhBBC5ELqhG/yqoEDQZ/GBMZ6PapBg0z2yww3btygbt3q7N//J19/PZ1Tp/5ly5YdNGzYmJEjh2feA72C77//lrlzf2T27AUcPnwCR0dH2rZtQVRUVJY9piRZQgghhBBC5EIaQyysW5dyD9aL7t2D9evj98skH3wwDJVKxZEjJ+nUqQvlypWjYsVKjBo1hkOHjqe43yefjKdSpXK4uTlQvnxpPv98IrGxz+M6d+4szZs3pkABZwoWdKFOneqcOvU3AMHBwXTq1I7Chd1xd3ekatVKbN/+h9nHURSF2bNn8vHHn9G+fQcqV36NxYuXcffuHTZv3phpz8OL5J4sIYQQQgghciAbm7S2sI4vcpEBqrVroVs3Umo6Jib9bYWFhbFr1w6++OIrHB0dk613c3NLcV9nZ2d+/nkJRYp4c/78vwwb9g5OTs58+OFHAPTr14uqVavx44/z0Wg0nDt3Bmvr+KqJI0cOJyYmhr17D+Lg4MjFixdwcnIy+zhBQUHcu3ePJk2aGpe5urpSq1Ztjh8/RrduAek/4AyQJEsIIYQQQojc6vHjrN0+FYGB11AUhfLl/TK874QJnxn/v2TJkly58iFr1vxuTLJu3gxhzJhx+PnFt122bFnj9jdvhtCpUxf8/SsDULp06RQf5/79ewB4ehY2We7pWdi4LitIkiWEEEIIIUQOlFavko0N8WXaMyJh+4z0WKVEeYUyhWvWrGLu3B+5fj2QJ0+eEBcXh4uLi3H9yJFjeO+9waxYsZwmTZrSufPb+Pr6AjB8+Ae8//5Q9uzZxVtvNaVTpy5UrvzaKx9PZpJ7soQQQgghhMiFlJhYlK5dM7ZP164oMZlzT1aZMmVRqVRcvnwpQ/sdP36Mfv160bJlazZs2MqJE6f5+ONPiUmS+U2c+DmnT/9Hq1Zt2LfvT6pWrcimTRsAGDhwMJcuXadnzz6cP/8vdevWYO7c2WYfq3BhLwBCQ03vWwsNvW9clxUkyRJCCCGEECIX0qutoUsXKFw47Y0BvLygc+f4/TKBh4cHzZq1YMGCuTx9+jTZ+vDwcLP7HTt2lBIlfPj440+pXr0GZcuWJSQkONl25cqVY+TI0fzxxy46duzM0qW/GNcVL16cIUPeY/Xq9YwaNZbFi38y+1ilSpXCy8vLpJx8ZGQkJ0+eoE6duhk84vSTJEsIIYQQQohcyGCI/6+yeDFoNKlvrNGgLFpksl9mmDVrLnq9nnr1arFhwzquXr3KxYsXmTPnRxo0MJ/ElClTlps3Q1i9+ncCAwOZM+dHYy8VgE6nY+TIERw4sJ/g4GCOHj3C33//hZ9fBQDGjh3Frl07CQoK4vTpfzhwYJ9x3YtUKhXvvz+Kr7/+H1u2bOb8+X8ZOLAvRYp40759x8x7Il4g92QJIYQQQgiRS8UpVli1bImyeXP8PFj3zBRz8PKKT7BatiROn7l9LKVLl+b48X/4+uuvGD9+LHfv3qVQoUJUq1ad2bPnm92nXbv2fPDBaEaNGkF0dDStWrVhwoSJ/O9/nwOg0WgIC3vEoEF9uX//PgULFqRDh85MmjQFAL1ez8iRw7l9+xYuLi40b96S6dN/SDHGsWM/4unTpwwfPoTw8HDeeONNtmzZgZ2dXaY+F0mplFe5Yy0fiIyMxNXVlYhLl3BxdrZ0OCIvCAvjjtaZMGcf4yIPDwvGI4QQQgiLiouLIjIyiBIlSr3UF3+VCqxUcfH/WL8+vkz748fg7h5/z1bnzvGPo1gh3/zTFhUVRUhIEC4upbCyMj0fWm0kfn6uREREmBTqeJH0ZAkhhBBCCJGLKQrEKlao1aDp2Am6dXu+MiYWPVaZOkRQpE2SLCGEEEKINCiKwoUL5wgLe0jRoiUoXbps2jvlYHq9nnPnTvH06RNKly6Ht3exl2onMPAKd+7cpECBQlSoUBmVSpXJkYqMMBjAgDWYlGe3Bkmwsp0UvhBCCCGESMXu3Vtp1Og1mjevSkBAU+rXL0f79vU5c+YvS4f2Ulas+ImaNUvTtm1tundvQq1aJejTpx3BwdfT3capU8dp27YeDRqUJyCgKc2aVeGtt6ry55/bszByIXKPXJVkHTx4kHbt2uHt7Y1KpWLjxo1p7rN//35ef/11bG1tKVOmDEuWLMnyOIUQQgiRN2zZsoYBA9oTGOgN7AQCgTWcPv2Mzp0bcfr0SQtHmDFz5nzNRx8N4f79+sBh4BqK8hMHDvxH27b1uH07JM02/v77GF26NObs2RhgLfHPyXauXi1E375t2bFjY5YegxC5Qa5Ksp4+fUqVKlWYO3duurYPCgqiTZs2NG7cmDNnzjBq1CgGDx7Mzp07szhSIYQQQuR2sbGxfPLJByhKZxRlO9AcKA10xWA4TGxsBSZPHmvhKNMvNPQe3347CRgP/ArUA3yBQej1x4mIUPP991PSbOezz0ah17+GwXAI6EL8c9ISRdkJtOXjj98nLi4u6w5EiFwgVyVZrVq14n//+x+dOnVK1/YLFiygVKlSfP/991SoUIERI0bQtWtXfvgh5RKPQgghhBAA+/ZtJyzsHvA5yb8y2WMwfMypU4e5du1y9gf3Etav/xVFsQI+NrPWE71+OOvX/4ZO9yzFNi5dOs+//57EYPgEeLEKngZFmcyDB7c4eHB3JkYuRO6Tq5KsjDp27BhNmzY1WdaiRQuOHTuW4j7R0dFERkaa/AmRJbSRaLWg1Vo6ECGEEObcuhWMSmUL+KewRQ0Abt8OzraYXsWtW8FoNGUAtxS2qEFsbBSPHj1IsY3nwwlrpLBFNUDFrVu54zkRIqvk6STr3r17FC5c2GRZ4cKFiYyMRKfTmd1n2rRpuLq6Gv+KFy+eHaGK/MTDA2/u4KG7g7MuFHTPCA6GsDBLByaEECKpAgUKoSjRQEr3KV0zbpcbeHgUxGC4CUSlsMU1VCo1rq7uqbYR72oKWwQBSpLtRHZSJ3yzt7F5/pd0ucg+8pS/YMKECURERBj/bt68aemQRF7k44O3Zxz+9oH4EAK6Z4SGQrD88CeEEDlG06Ztsbd3Br43s9aASvU9pUtXpFKlqtkc2cvp2LEnen04sMjMWh0azRyaNWuPs3PKE6xWqVKD4sXLolJ9D5ib1fY7HB3daNKkdeYELdJFpXqeSG3YAG+/DU2bxv93w4b45Wp1/HYie+TpJMvLy4v79++bLLt//z4uLi7Y29ub3cfW1hYXFxeTPyGyhIeHMdnyIQRP4nu1Ll2SXi0hhMgJHB2dGDt2IvAjMApI/OH1AipVAIqyg88+m5pr5oYqXbosPXoMRqUaBUwFHhGfKB1DrW6FRnODsWMnpdqGWq1m4sRpKMpWoCdwKWFNCDACmM+4cZOxt3fIsuMQplQq0Ghg1y4oVgwCAmDtWti7N/6/AQHxy3ftit/OUperra2KTZs2WubBLSBPJ1l169Zl7969Jst2795N3bp1LRSREGZ4eJj0ankSauzVkmRLCCEs6733PuSzz77F3n4xUAK12h6ohJvbQebNW0mLFh0sHWKGfP31fAYOHI6V1RSgECqVPfAG3t63WLlyB/7+1dJso02bLsye/StubnuBCgnPiQ8ODsuZPHkGgwePzOKjEEmpVLBjB7RvDy/0LRjdvx+/fseOrEmy7t27x6hR71O+fGmcnW3x9S1Op07t+PPPvWnvnA02blxP69bNKVKkALa2Ks6ePZPlj6lSFMVcX2+O9OTJE65dix//XK1aNWbMmEHjxo3x8PCgRIkSTJgwgdu3b7Ns2TIgvoS7v78/w4cPZ+DAgfz555988MEHbNu2jRYtWqTrMSMjI3F1dSXi0iVcnJ2z7NiEAOKzKq2W8zpftDihwwF7e/DxsXRgQgiRvz15omX37i08evSAYsV8eOut1tgk3vCSCz169IA9e7by5ImWsmUr8OabTVBn8Mad6Oho/vzzD27fDqFgQU+aN2+Pg4NjFkWct8XFRREZGUSJEqWws3uxamPKEk9ZsWIpJ1hJeXlB4p0wBsNLBGrGjRs3aNy4Hq6ubkye/AWVKlUmLi6WXbt2smjRQv79N76309ZWxerVG+jQoWPmPHAGrFixnBs3gihSxJuhQ9/h5MnTVKlSNcXto6KiCAkJwsWlFFZWpudDq43Ez8+ViIiIVEe8WWVW8Nnh77//pnHjxsZ/jxkzBoB+/fqxZMkS7t69S0jI85tTS5UqxbZt2xg9ejSzZs2iWLFi/Pzzz+lOsITIdh4e4OGBf3Agd3TuhOGBVudEcLADzs7xq4UQQmQ/JydnOnXqaekwMk2BAoXo3n3AK7Vha2tLq1bpm1ZHZA2DIf6eq/QkWAD37sH69dCxY+bF8MEHw1CpVBw5chJHx+dJdsWKlejff2CK+33yyXg2bdrA7du3KFzYix49evHpp5OwtrYG4Ny5s3z44ShOnfoblUpFmTJlmTv3/6hevQbBwcGMGjWCo0cPExMTg49PSaZNm06rVubvBezVqw8QnxBml1yVZDVq1IjUOt6WLFlidp/Tp09nYVRCZAEfH7zDwvDWxidbwboShOoc0GqlV0sIIYTIL9LTWbp2bcbaXLsWunVLeX1MTPrbCgsLY9euHXzxxVcmCVYiNze3FPd1dnbm55+XUKSIN+fP/8uwYe/g5OTMhx9+BEC/fr2oWrUaP/44H41Gw7lzZ4wJ2MiRw4mJiWHv3oM4ODhy8eIFnJyc0h94NshVSZYQ+UpCr5Z3WBiEhhh7tS5dcsDTU3q1hBBCCAGPH2ft9qkJDLyGoiiUL++X4X0nTPjM+P8lS5bkypUPWbPmd2OSdfNmCGPGjMPPL77tsmXLGre/eTOETp264O9fGYDSpUu/ymFkCUmyhMjpPDzw5nmvVhgehIZ6otUiQwiFEEKIPCytXiUbG3BPeVozsxK3z0iPVUpepbTDmjWrmDv3R65fD+TJkyfExcWZ3OM0cuQY3ntvMCtWLKdJk6Z07vw2vr6+AAwf/gHvvz+UPXt28dZbTenUqQuVK7/2yseTmfJ0dUEh8owk5d797QON5d5lbi0hhBAi/4qJga5dM7ZP166Zk2ABlClTFpVKxeXLl9LeOInjx4/Rr18vWrZszYYNWzlx4jQff/wpMUkCmzjxc06f/o9Wrdqwb9+fVK1akU2b4if9GjhwMJcuXadnzz6cP/8vdevWYO7c2ZlzUJlEkiwhcpOEZCtpuXd0z6TcuxBCCJEPqdXQpQsULpy+7b28oHPn51UJX5WHhwfNmrVgwYK5PH36NNn68PBws/sdO3aUEiV8+PjjT6levQZly5YlJCT5r8blypVj5MjR/PHHLjp27MzSpb8Y1xUvXpwhQ95j9er1jBo1lsWLf8qcg8okkmQJkRsl6dXyIUR6tYQQQoh8KLEM++LF8RMNp0ajgUWLTPfLDLNmzUWv11OvXi02bFjH1atXuXjxInPm/EiDBubnpi1Tpiw3b4awevXvBAYGMmfOj8ZeKgCdTsfIkSM4cGA/wcHBHD16hL///gs/vwoAjB07il27dhIUFMTp0/9w4MA+4zpzwsLCOHv2DBcvXgDgypXLnD17hnv37mXeE/ECSbKEyK2SDCFM2qt16ZL0agkhhBD5haJAy5aweXN8T5U5Xl7x61u2jN8+M5UuXZrjx/+hYcPGjB8/ltdf96dNm2bs27eX2bPnm92nXbv2fPDBaEaNGkGtWlU5fvwoEyZMNK7XaDSEhT1i0KC++PuXo1evbrRo0YpJk6YAoNfrGTlyOFWqVKBdu5aULVuOH3+cl2KMW7duplatanTs2AaA3r0DqFWrGj/9tCATnwlTuWoyYkuQyYhFrpAwibGxMAae2NtLYQwhhBAiN3jZyYgTqVTxfxA/D9batfFVBN3d4+/B6tw5fp2iZH6SlRflu8mIhRApSFLu3VsbyHkdaHVOMreWEEIIkQ8kJk9qdfxEw0nnwUqsJZGZQwRF2mS4oBB5iRTGEEIIIfKtxEQqJub5X9LlIvtIkiVEXiSFMYQQQgghLEaSLCHyKimMIYQQQghhEXJPlhB5nYcH3sTfq2UsjBHqiVYrhTGEEEKInCK+IIVUpcgZlFcuECI9WULkB0l6tfztA429WjKEUAghhLA8tdoaAJ3umYUjEfD8PCSel5chPVlC5CcJVQj9g5/3aml1TgQHO0ivlhBCCGEharUGGxs3HjwIBcDe3gFQWTaofElBp3vGgweh2Ni4oVanMcNzKiTJEiI/8vExlnu/o3MnWFdCyr0LYWHXrl1ixYqfuHbtEo6OTrRu3YVWrTphbf3yv6QKePgwlC+/HMehQ7uJi9NTpowfEyd+R7VqNS0dmhAmnJy8ePIEQkPjEy2V5FjZLnGIoI2NG05OKczsnE4yGXEaZDJikeeFhXEn1Cq+VwsndDjg6Sm9WkJkp5kz/8f06RPRaAqi19dDrb6LwXCSsmUr8/vvO/Dy8rZ0iLnS9u0bGDIkAIMhFngTcAH+BKLo3XsI33yzwLIBCmGGwaBPuGaFJajV1qn2YKV3MmJJstIgSZbIF8LCQKt9XhgDT+ztpTCGENlh48aVDB/eE5gEfALYJqw5hUbTgQoVvNmx4wQq+Vk7Qx4+DKVq1eIoSllgE+CbsCYSGAks5ZtvFtC79xCLxSiEyH3Sm2RJ4QshhBTGEMJCFEVh9uxvUatbAVN4nmABVEevX8L5839x7NgBC0WYe3355TgUJRbTBAvie7N+BsowY8aXFolNCJH3SZIlhHguIdnytw/Ex1OHp2d8b5bMqyVE1njw4D6XLp3BYOifwhZNsLIqyp9//pGdYeUJhw7tAephmmAl0gADuH//TvYGJYTINyTJEkIIISwkNjYm4f9SGo6uApyIiYlJYb1IiV6vJ77XKiVOyJxEQoisIkmWEEIIYSGFC3vj4eEFbElhi8vExV2mSpUa2RlWnlCmjB+wj/h7sMzZhL19akmYEEK8PEmyhBDmhT6A0FC0WtBqZcigEFnBysqK/v3fRa1eDOx/Ye0z1OrhuLt70qZNVwtEl7tNmvQdEAW8D+hfWPsrsJe33+6Z7XEJIfIHSbKEEMklKYLhrHteBEMSLSEy34gRE6hTpz4qVVNUqq7AXOAzNJpyWFsfZ+HCVdjZ2Vk6zFynSpUa9O37HrAcKA98BfwINAH6ULJkWb76ao4lQxRC5GFSwj0NUsJd5HvBwVLaXYgsFhMTw2+//cQvv/wfQUEXsbNzokOHrrz77tiEYW/iZa1cuYjvv5/C3bt3AAP29i68/XZPvvpqDmq1/NYshMgYmScrk0iSJQTGebTORxRHa+OBDgfs7cHHx9KBCSGEEEJkH5knSwiReRJLuxcLx4cQ4zxawcEyhFAIIYQQ4kWSZAkh0s/Dw3ivlg8hEBFunLBYki0hhBBCiHiSZAkhMiahV8vbM466rheNvVpSGEMIIYQQIp6VpQMQQuRSHh7g4YF/cODzwhihnmi1UhhDCCGEEPmb9GQJIV5NknLvnjG3jL1awcGWDkwIIYQQwjIkyRJCvDopjCGEEEIIYSRJlhAi80hhDCGEEEIISbKEEJlMCmMIIYQQIp+TwhdCiKwhhTGEEEIIkU9JT5YQImtJYQwhhBBC5DOSZAkhsp4UxhBCCCFEPiJJlhAi+0hhDCGEEELkA5JkCSGylxTGEEIIIUQeJ4UvhBCWIYUxhBBCCJFHSU+WEMKypDCGEEIIIfIY6ckSQlheYq9WWBh3Qp8QhgdanRPBwQ7SqyXyladPn3D37i0cHJzw9i72Um3o9XpCQoJQFIUSJUphZfVyH/V3797m6VMtRYoUw9HR6aXaCA9/zIMH93B3L0DBgp4v1UZO8vBhKI8fP8LTswiurm4WiyMuLo6QkCBUKhUlSpRCo9FYLJa8do5F1oiKiuLWrWBsbW0pVswHlUpl6ZCynPRkCSFyDimMIfKpR48e8NFH71K5cmEaNqxAzZrFadWqDnv2bEt3G3q9nvnzp1OjRinefLMs9euXo0aNUsyb9y16vT7d7ezd+wetW9elRo1iNGxYgcqVC/PRR0N4+DA03W1cv36Vd9/tzmuvedKoUUWqVClMQEBL/vnnRLrbyEn++ecE3bu3oEqVwjRqVJHKlQvx3nsBBAVdy9Y44uLimDv3G2rUKEn9+uV4882y1KxZmgULvsvQOc4MgYFXeOedt6lcuZDxHPfo0YqzZ//O1jhEzvb06RO++OJDXnutCA0b+lGnTikaNXqN9etXWDq0LKdSFEWxdBA5WWRkJK6urkRcuoSLs7OlwxEi/wgLA62W8zpftDihwwFPT+nVEnlPWNhD2rR5g9u3w9DrPwAaAfdQq+djMOxnxozFdO8+INU2FEVhxIg+bNq0EkXpD3RPWLMalWoJ7dq9zdy5K1CrU/9tdc2aZYwe3R+VqgEGw1DAG9iPRvMj3t5ubN16JM3eimvXLtGu3Zs8feqMXj8KeB24ilr9IxrNJVas2E69eo3TfmJyiMOH/6R379bo9X4YDCOBMsA/aDQzcXTUsmXLYcqU8cvyOAwGA8OH92LLljUoygCgG6AAq1CpltCxY09mz16WLT0EV65coH37+jx75ppwjqsBV9BoZqFWX+X333dSp06DLI9D5GzPnj2lS5cmnD//HwbDMKAVEIFKtRhF2cz48V/xwQefWDrMDNNqI/HzcyUiIgIXF5cUt5MkKw2SZAlhYcHBzwtjxLhi72orQwhFnvLppyNYvnwlev1JwDfJGgUYjK3t75w+fTvV4Wl79myjX7+2wEog4IW1a4Bu/PLLJpo3b59iG5GREVSrVpSoqK7AYkwHu1xHo6lFz55v8/XX81M9nm7dmnP8eAh6/THAPcmaaNTqVhQpEszx41fTTPhyAr1eT506Zbl3rxQGwx+AbZK1YWg0dalbtySrVu3M8lh27tzEwIEdiT+fXV9YuxLoybJl22jSpHWWx9Kly1v89dc99PqjgFuSNVGo1S0oWvQuR49eyhXnWGSd2bOn8e23UzAYjgDVX1g7EZXqKw4fvkrJkr7mds+x0ptkydUvhMjZkhbG4IEUxhB5SlRUFKtWLUOvH4ZpggWgAr4iJiaGDRtSH1qzfPlCNJoaJE+wAN5Go6nF8uU/pdrGhg2/ER0dDUwl+deD0uj1w1mz5ld0umcpthESEsSRI7vR6z/DNMECsMVgmMrt29c5fHhvqrHkFIcP7+XOnSAMhmmYJlgAHuj1n3L48C5u3ryR5bEsW7YQjaY2yRMsgAA0mtdZvnxhlsdx/fpVjh/fh14/EdMEC8AOg+Erbt68yrFjB7I8FpGzLV26EIOhJ8kTLIAJqNVurFy5KLvDyjaSZAkhcr6EubX8i4XjQ4hxbi25V0vkdg8e3EOn0wL1U9jCCyur8ly/fiXVdq5cuYxen1IboNc34OrV1Nu4fv0KVlZliB8iaE4DoqKeEBp6L8U2goKuJvxfSrHURqWyTvN4corr16+gUtkANVPYIn5I3PPjzjpXr15J5Ryr0nWOM0Pa57geoMo151hkjdjYWO7evUHK14kDBkPNPH2dSJIlhMg9pDCGyGOcnBKHmtxOYYtYDIZ7SbYzz9XVNZU2AG6lOqwFwMXFFYMhFIhJsQ0AJ6eUh847O7sm/F9KsYSiKLFpHk9O4eTkgqLEAA9S2OKWcbuslhnnODO4uKR1ju8CCs7OueMci6xhZWWFjY09KV8nCmr1rTx9nUiSJYTIXRJ6tbw946jretHYqxUaKomWyH3c3T14440mqNXzgDgzW6xCr39Eu3bdUm2nY8duqFQbgZtm1t5Crd5Ap06pt9GmTVf0+jDi7+95kR61eh516jSmQIFCKbZRpUoNvLx8gNkpbDEXGxt7mjZtm2osOUXTpm2xtrYD5qawxRy8vUtRpUqNLI+lY8e3UavXY/5Lawgq1SY6dkz9HGeGatVqU6hQMVI+x3OwtXXgrbey/t4wkXOpVCrat38bjeZnwNwQ4/3o9RfSfG/LzSTJEkLkTolDCBN6tTwJlV4tkSuNGTMROI1K1QMISlgaDSxBrX6Xli27UKFC5VTbCAgYiKdnYTSaZsAh4otmKMBhNJrmFCxYiICAQam24efnT+vWb6NWDyO+8EV0wpogVKqeKMrfCbGmTKPR8NFHk4HfgVFAYtn3SOAbVKqvGDJkFG5uL96vlTO5u3swZMhIVKr/Ad8C2oQ1ocBIYBUffjgpW+ap6tFjMAUKFESjaQ4c4fk5PohG0xxPzyIEBAzM8jisrKwYN24SsAIYw/Nevkji7+f7mqFDxybp8RL51bBhH2Fl9QC1uh3wX8LSOGA9Gk03qlatS8OGzS0YYdaSJEsIkbslLYwRc0sKY4hcp27dhixYsApHxz2AL9bWvmg0hYEBtGrVljlzlqXZhpubO2vX7qVkSSugAVZWRbGyKgbUx8dHxdq1e3F3T7sk548/LqV163bAIDQaT6ytfQFfHBx2smDBqnSVXu/efQCTJ8/A2vr/UKmKYW1dBrW6CCrVJwwePJKPPvoyzTZykvHjv2LQoA9QqSagVnthbV0m4bgW8vnnP9C9e/9sicPDowBr1+6lRAkFeBMrq2JYWRUFGlKqlDVr1+7JtgmSe/V6h4kTv8Pael6Sc+yFWj2J994by9ixn2dLHCJnK1++EitW/IGb2wXAH2vrUmg0XkAXateuyvLlW/J0BUop4Z4GKeEuRC4SFsadUCvC8ECLE9g7SLl3kWs8e/aULVvWEBh4CQcHJ9q06ULZshUy1IbBYODw4b3Gym516jSgfv2mGf4ic+3aJbZtW8fTp1p8ff1o1+5tHBwcM9TG48dhbNq0ktu3QyhQoBDt2wfg7V0sQ23kJLdv32TLllU8evSAokVL0KFDj3QlrpnNYDBw6NAejh07gEqlom7dRrz55lsW+bIaFvaITZtWcufOTQoU8KRDhwCKFCma7XGInC0mJoYdOzby33+nsbW1o2nTtrz2mrmKg7mDzJOVSSTJEiKXSZjE+I7OneAYL3Q2btjbI8mWEEIIIV5Znp0na+7cuZQsWRI7Oztq167NyZMnU91+5syZlC9fHnt7e4oXL87o0aOJiorKpmiFENlOCmMIIYQQwsJyVZK1atUqxowZw+TJk/nnn3+oUqUKLVq0IDQ01Oz2v/32Gx9//DGTJ0/m4sWLLFq0iFWrVvHJJ59kc+RCiGxnrjDGrWgpjCGEEEKILJerkqwZM2bwzjvvMGDAACpWrMiCBQtwcHBg8eLFZrc/evQo9erVo2fPnpQsWZLmzZvTo0ePNHu/hBB5SNLCGDyQwhhCCCGEyHK5JsmKiYnh1KlTNG3a1LhMrVbTtGlTjh07ZnafN954g1OnThmTquvXr/PHH3/QunXKczdER0cTGRlp8ieEyOUSe7WKhRt7tdA9k14tIYQQQmQJK0sHkF4PHz5Er9dTuHBhk+WFCxfm0qVLZvfp2bMnDx8+5M0330RRFOLi4njvvfdSHS44bdo0pkyZkqmxCyFyCA8PvAnDWxsYXxgjwotQnRtarRTGEEIIIUTmyTU9WS9j//79TJ06lXnz5vHPP/+wfv16tm3bxpdfpjxHx4QJE4iIiDD+3bx5MxsjFkJkOSmMIYQQQogslmt6sgoWLIhGo+H+/fsmy+/fv4+Xl5fZfSZOnEifPn0YPHgwAJUrV+bp06cMGTKETz/91OycEra2ttja2mb+AQghchYPD/DwwD84vlcrDA9CQz2lV0sIIYQQryzX9GTZ2NhQvXp19u7da1xmMBjYu3cvdevWNbvPs2fPkiVSGo0GAJkeTAgBmBbGiLklhTGEEEII8cpyTU8WwJgxY+jXrx81atSgVq1azJw5k6dPnzJgwAAA+vbtS9GiRZk2bRoA7dq1Y8aMGVSrVo3atWtz7do1Jk6cSLt27YzJlhBCGHu1wsK4E/qEMDzQ6pwIDnaQXi0hhBBCZFiuSrK6d+/OgwcPmDRpEvfu3aNq1ars2LHDWAwjJCTEpOfqs88+Q6VS8dlnn3H79m0KFSpEu3bt+Oqrryx1CEKInEwKYwghhBAiE6gUGTeXqsjISFxdXYm4dAkXZ2dLhyOEyC5hYaDVcl7nixYndDjg6SmJlhBCCJGfabWR+Pm5EhERgYuLS4rb5aqeLCGEyDbmCmPcckWrtZVeLSGEEEKkKtcUvhBCCItIWhiDB1IYQwghhBBpkiRLCCHSkjC3ln+xcHwIMc6tFRwsc2sJIYQQIjkZLiiEEOmVWBiDUM5r7UBu0xRCCCGEGZJkCSGEECLPMhgM7Nu3gz///IPY2BgqV65O5869cHR0yvZYHj16wJo1SwkMvIyjozNt2nSlRo26qFSqbI9F5G2KonDy5GG2bVuHTveUsmUr0rVrXzw8Clg6tHxDqgumQaoLCiFMJIwPPK8tAc7xVYWkCIYQOdPt2yH07t2OK1fOYWVVFnAmLu4MTk4uLFiwksaNW2ZbLL/+upDPPvsAvV6FWl0ZuEtc3C3q1WvGzz+vwcXFNdtiEXnb48dhDBzYmZMnD2BlVQLwRK8/h5WVmm+/XUC3bv0sHWKult7qgnJPlhBCZJRWC7ootKFSBEOInCo6Oppu3VoQGBgJHCEu7jJxcaeAIJ4+rceAAZ24ePHfbIll164tjB//LrGxAzAYbhEXd5K4uGBgI8ePn2To0J7ZEofI+xRFYdCgrpw6dR7YRlxcEHFxf6Eot4iN7cmYMQM4eHC3pcPMFyTJEkKIjEgsgmEfKEUwhMjBtm9fz40bl9DrNwJvAIlD8kqgKOswGAqzcOGMbIll5sypqNWNgHlA4nAtNdABvX4h+/f/wfnzp7MlFpG3/f33MU6c2IdevwRozfOv+oWAn1Cp6jBr1jSLxZefSJIlhBAvI0lpdx9CTEq7S7IlhOXt2LERtboOUMXMWlv0+v5s3bo+y+MIDb3H2bPHMRje5Xmil1RnNJqCbN++IctjEXnfzp0bsbLyJj7BepEag+Edjh/fR3j44+wOLd+RwhdCCPGyEiYs9g4Lg9AQwvBAq3MiVOdgXC2EsIxnz55iMBRKZQtPoqOfZUsc8VKKxQq12gOdLutjEXlf/PVWkJT7UTwBiIrSAe7ZFFX+JD1ZQgjxqjw88PZzMRlCKL1aQlhW+fKV0GgOAzqz61Wq3fj6VsryOLy8iuLo6ArsSWGLIGJjr1K+fNbHIvK+cuUqodf/B9xJYYvduLoWpECB1H6AEJlBkiwhhMgsSYYQJt6rJYUxhLCMXr2GYDCEA5OBFwsp7wI2M2DAe1keh52dHT16DECjmQ/898LaWFSqD3FycqVdu25ZHovI+zp37oWtrR0q1YeA/oW1Z1Crf6ZPn8FYW1tbIrx8RZIsIYTITFIYQ4gcoWRJXyZO/A6YjlrdGFgCrAP6o1K1pVGjVvToMShbYhkzZjK+vj5oNHWBUcBGYB4aTQ3U6s3MmvULDg6O2RKLyNtcXFz54YfFqFSr0WhqAQuIv95GoFa/SYUKFXj//U8sG2Q+IfNkpUHmyRJCvLSwMNBquaNzJ5gS6HDA3h58fCwdmBD5x65dm5kzZzqnTh0GoEiRkgwcOJR33hmdrb/mR0ZGMHfu1yxf/jMREQ9RqVQ0btyGDz6YQM2ab2RbHCJ/OH78ILNmTePQoZ0oioKbmyd9+77D8OHjcXKS77OvIr3zZEmSlQZJsoQQrywsjDuhVvGFMXBChwOenlIYQ4jspNVGEhsbg5ubB2q15Qby6PV6wsPDcHBwxN7ewWJxiPzh2bOn6HTPcHPzQKPRWDqcPCG9SZZUFxRCiKzm4YG3B3gHB3JH504YHoSGeqLVgrOzJFtCZAdn55S/DGUnjUYjRQdEtnFwcJShqBYi92QJIUR2kcIYQgghRL4gSZYQQmQnKYwhhBBC5HmSZAkhhCUk6dXyIcSkV0uSLSGEECJ3k3uyhBDCUjw84u/XCguD0JD4whg6J0J1DsbVQgghhMh9JMkSQghLk8IYQgghRJ4iwwWFECKnkMIYQgghRJ4gPVlCCJGTJAwh9E/Sq6XVOREcbH4+HenpEkIIIXIeSbKEECIn8vHBOywMb21isuWdbBOtzopQnYMMKxRCCCFyGEmyhBAip0pSGMNb+1/y9fZwXucrxTKEEEKIHEaSLCGEyOkSki1zkg4rDL3lilZrK71aQgghhIVJ4QshhMjNTIplPJBiGUIIIUQOIEmWEELkdh4e4OODf7FwfAgxViaUiY2FEEIIy5AkSwgh8goPD2Ovlg8hEBFu7NWSZEsIIYTIPpJkCSFEXpLQq+XtGUdd14sm821JoiWEEEJkD0myhBAiL0ocQpjQq+VJKKG3oqVXS2Qrg8FAZGQEcXFxL92Goig8eaIlKirqlWKJioriyRMtiqK8dBtxcXFERkZgMBheKZbMoNM9Q6d7ZukwRBaSc5y7SZIlhBB5mRTGEBbw4MF9Jk8eTYUKBalQwY2yZV0YM2Yg169fTXcbcXFxLFr0I2+84Uf58i74+trz9ttN2b9/Z4Zi2b9/J2+/3RRfX3vKl3fhjTf8WLToxwwlfoGBVxgzZiBly7pQoYIbFSoU5PPPx/Dgwf0MxfKqFEVh7drlNGtWgzJlHClTxpEWLWqxYcNvr5Q8ipxDURRWr15K06avG89xy5a12bTpdznHuYxKkTOWqsjISFxdXYm4dAkXZ2dLhyOEEC8vLIw7oVaE4YEWJ7B3kHLvItPduXOLdu3e5MEDLXr9YOB14Coazf9hZ/eE9ev/xN+/WqptxMXF8c47b7N79xagG4rSFtCi0SxBrz/OV1/NpX//YWnGsmTJXD79dAQaTR30+v6AMyrVFmANzZu3Z+HC1VhZpT6bzb///kOXLm8RFeWCXv8uUAb4B43mZzw9Xdi8+RDe3sXS89S8EkVRmDx5NIsWzUKtbo3B0A1QUKtXYTDs4L33PmTixOlZHofIOoqi8Omn77N06VzU6jYYDG8DBtTq3zEYdjFixMdMmDDN0mHme1ptJH5+rkRERODi4pLidpJkpUGSLCFEnhIWBlotd3TuBMd4obNxw94eSbZEphk4sDN79vyFXn8UKJ5kTQQaTRNKlYpm//5zqFSqFNv49deFfPzxUBRlM9AmyRoFGIVKNYdjxwIpXrxkim2EhATxxhtlUJT3gR+ApI+3FWjP9OkL6dlzcIptKIpCw4aVuXHDHr1+L5D0C1UIGk09mjWrxaJF61JsI7McOrSXgICmwFzgxQRzFjCKdesOUKdOgyyPRWSN/ft30qtXS2AB8O4La78HPmTjxsPUrFkv+4MTRulNsmS4oBBC5CcpFMbQauVeLfHq7t69za5dm9DrP8M0wQJwRa//hmvXznPy5OFU21m8eD7QDtMEC+ITpamo1c6sWPFTqm2sWPETarUzMBXTBAugLWp1WxYtmpdqGydPHiYw8D/0+m8xTbAASqDXf8KuXZu4d+9Oqu1khqVL56PR+ANDzaz9AI2mPEuWpH48ImdbsmQ+Gk1VYIiZtaPRaMqwdOn8bI5KvCxJsoQQIj/y8ABnZ/w9Q3G2j0M66kVmuHr1AopiAJqnsMVbqFRWXLz4b4ptKIrClSvnUJSU2nBEr6/PpUsptwFw8eI59PoGgIPZ9QZDC65eTbsNlcoaaJTCFi0wGPRcuXIh1XYyw7//nkOvb0HyhBFAhV7fgvPnUz8ekbOdP38Ovb455s+xGr2+Bf/+K+c4t5AkSwghhBCZws7OPuH/UuoWjUBR4rC3t09hPahUKmxt7VNpA9Tqh0keK+VY1OpHqWzxCBubtNtQlDggIsU2gFSPJ7PEP0bqx5MdcYisE39Npzak4CEODnKOcwtJsoQQQgiRKapWrYW7e2EgpaF8i9BorGncuFWq7bRs2QGNZgkQY2bteQyG47Ro0SHVNlq06IDBcBT4z8zaGDSapbRqlXobjRu3Qq3WAItT2OJnPDy8qFq1VqrtZIY2bTqgVq8FHptZ+xC1egOtW6d+PCJna9OmAxrNaswn9aGo1ZvkHOcikmQJIUR+ptXiobuDNvR5aXe5N0u8LBsbG0aMGAf8HzAdSJzbKg74FbX6UwICBuLp6ZVqO0OHfgiEoFL1AO4lWXMKjaYTJUqUpXXrLqm20aZNV4oXL4NG0xH4J8mau6hUPVCpbvHuu2NTbaNw4SIEBAxErf4EWAHoE9ZEAd8CCxkxYhzW1taptpMZ+vR5DwcHa9TqdsD1JGuuoVa3xcnJnt69zd3LI3KLfv2GYWenSjjHQUnWXEGjaYuzs1OqhVpEziJJlhBC5FdJimAkTlicOI+WJFriZb377piE5OUjNJqiaDQNsLIqCfShVasOfPnlrDTb8Pevxk8/rcHWdicqVXE0mjewsqoM1KB4cStWrdqJra1tqm3Y2dmxatVOihe3AqpjZVUZjeYNVKoS2Nnt4qef1uDvXzXNWP73vx9p1ao90BsrKx80mgZoNEWB8bz33ocMGTI6zTYyg5eXNytXbsfV9SpQBo2mJhpNDaAsbm7B/P77DgoVKpwtsYis4e1djN9+246LyyXAF42mVsI5Lo+7+21WrdpJgQKFLB2mSCcp4Z4GKeEuhMg3goO5o3MnDA9C8ZTS7uKVXL9+ldWrl3D7djAeHoXo0qU3r71WPUNtRESEs3btMs6e/RtbW1uaNGlD06Zt05zbKqm4uDj27NnK3r3biI6OpkqVGnTt2hdXV7cMxXLu3CnWrfuVsLAHFC3qQ/fuAyhVqkyG2sgMOp2OzZtXcezYflQqFXXrNqJdu25yP1YeotM9Y9Om3zl+/CAqlYp69d6ibdu3sbOzs3RoApknK9NIkiWEyFcS5tE6r/NFixM6HLC3Bx8fSwcmhBBCWJ7MkyWEECLjEoYQ+tsHmgwhlHu1hBBCiPSTJEsIIURyCfdqJSZbifdqSbIlhBBCpC39g5qFEELkLx4e4OGBd1gYhIYQhgdanROhOgfjaiGEEEIkJ0mWEEKI1Hl44O0B3sGBzwtjhHqi1UphDCGEEMIcGS4ohBAifZIMIUxa7j042NKBCSGEEDmLJFlCCCHSTwpjCCGEEGmSJEsIIUTGSWEMIYQQIkVyT5YQQoiXI4UxhBBCCLMkyRJCCPFqpDCGEEIIYUKGCwohhMgcUhhDCCGEACTJEkIIkZmkMIYQQgiR+5KsuXPnUrJkSezs7KhduzYnT55Mdfvw8HCGDx9OkSJFsLW1pVy5cvzxxx/ZFK0QQuRTUhhDCCFEPpar7slatWoVY8aMYcGCBdSuXZuZM2fSokULLl++jKenZ7LtY2JiaNasGZ6enqxdu5aiRYsSHByMm5tb9gcvhBD5jRTGEEIIkU+pFEVRLB1EetWuXZuaNWsyZ84cAAwGA8WLF+f999/n448/Trb9ggULmD59OpcuXcLa2vqlHjMyMhJXV1ciLl3Cxdn5leIXQoh8LTj4eWEMPLG3l8IYQgghchetNhI/P1ciIiJwcXFJcbtcM1wwJiaGU6dO0bRpU+MytVpN06ZNOXbsmNl9Nm/eTN26dRk+fDiFCxfG39+fqVOnotfrU3yc6OhoIiMjTf6EEEJkAimMIYQQIp/INcMFHz58iF6vp3DhwibLCxcuzKVLl8zuc/36df7880969erFH3/8wbVr1xg2bBixsbFMnjzZ7D7Tpk1jypQpmR6/EEIIjEMI/ZOUe9fqnAgOdrBYr9aFC+fYu3cbsbEx+Pu/TpMmrdFoNBlq48GD+2zduoZHjx7g7V2ctm3fxsXFNUNtREVFsXPnRq5du4SjoxMtW3aiZEnfDLWhKAonThzi+PGDKIpCnToNqFOnASqVKkPtCJEf3b9/l23b1hIW9pBixXxo2/ZtnJxy7yimoKBr7NixgWfPnlK2bEVatOiAra2tpcPKN3LNcME7d+5QtGhRjh49St26dY3LP/roIw4cOMCJEyeS7VOuXDmioqIICgoyfmDOmDGD6dOnc/fuXbOPEx0dTXR0tPHfkZGRFC9eXIYLCiFEZgsLA62WOzp3gimBDodsHUIYHv6YoUN7cvDgDjQaF1Qqe+Li7uPl5cPChb9TvXqdNNswGAxMnz6JuXO/xWBQodEUQq+/h62tHRMnfkP//sPTFcuuXVsYNWogEREPsbLyxmAIR1F0dOrUm+nTF2JnZ5dmGyEhQQwc2JWLF/9Bo/EAVOj1j/Dzq8bixWvx8SmdrliEyG8MBgNTp37MwoU/oCga1OqCxMXdxc7OgS++mEGvXu9YOsQM0el0jB07mE2bfkOtdkStdiUu7g7u7p78+OMS3nqrlaVDzNXy3HDBggULotFouH//vsny+/fv4+XlZXafIkWKUK5cOZNfJCtUqMC9e/eIiYkxu4+trS0uLi4mf0IIIbJAQrl3b884k3LvoaFZX4FQr9fTu3dbjhz5C/gdvf4hcXH3gL8IDS1KQEALrl+/mmY7s2b9jx9//Aq9/hMU5S5xcbdQlGCiovry6acjWL16aZptnDx5mMGDOxMZWRe4SFzcbQyGByjKPDZuXMOoUQPSbCMyMoLOnd/iypUIYBd6/QP0+gfAbq5efULnzm8RERGeZjtC5EfffPMZ8+d/h14/GYPhHnFxt4AbREUF8NFHQ9i06XdLh5ghI0b0YcuWjcBCDIYHxMXdBv4jPLwG/ft34NSp4xaOMH/INUmWjY0N1atXZ+/evcZlBoOBvXv3mvRsJVWvXj2uXbuGwWAwLrty5QpFihTBxsYmy2MWQgiRDh4eePu5mMytldXl3vfv38np00fR69cA3YHE4kg1MBh2EB3txP/93/eptqHVRjJ79rfAOOBzILH7rSgwF3ibb7/9PNX7gAG+//5LoDKKsg7wS1jqALyHwTCPLVt+58qVC6m2sWrVL9y7dxu9fjfQjPiPdxXQFL1+N/fv3+H33xen2oYQ+VFY2CP+7/9+AD4FPgPcEtYUBxYC7fn668nkkoFfnD9/hh071mEw/B/wDmCfsKYiirIB8GPmzK8sF2A+kmuSLIAxY8bw008/sXTpUi5evMjQoUN5+vQpAwbE/8rXt29fJkyYYNx+6NChhIWFMXLkSK5cucK2bduYOnUqw4enb/iGEEKIbJSNhTE2b16FRlMZaGRmrTN6/QA2bEj91+u9e7cRHf0UGGlmrQr4gLt3b3DmzF8pthEe/pjDh3eh1w/jeaKXVC80Gg82b16VaiwbNqxCUdoDpcys9UFROrJhQ+ptCJEf7d69hdjYaOB9M2vjX8chIVf4778z2RvYS9qyZTUaTSHifzx6kQ16/VD27duGViuF3bJaril8AdC9e3cePHjApEmTuHfvHlWrVmXHjh3GYhghISGo1c/zxuLFi7Nz505Gjx7Na6+9RtGiRRk5ciTjx4+31CEIIYRITTYVxoiMDEevL0H8lyhzfHj6NAKDwWDyuZJU/PA7NeCdYhuJj5USrTbCZNvkbFCri6TaBsDjx48B86M6EtsPDz+bahtC5EeRkeGo1fYYDMnnW40X/9rMLcNtIyPDUamKYv5HG4j/0UXhyRMtzs5yS0xWylVJFsCIESMYMWKE2XX79+9Ptqxu3bocPy5jT4UQIlfx8cE7LAxvbXyyFawrQajOAa02cwpjlCxZBo3mV/T6GMDc8PEjFC3qm2KCBVCqVBnAAJwAzBXJOJJwKClXCCxYsDB2do5ERR0mfpjfi0KJi7uCj8+QFNsAKFOmLLdvHyGlkYkazRFKl85YpUIh8oOSJctgMDwDTgPVzGyR+DrOHYVj4o9nMfAIKGBmiyM4OLjg4VEwmyPLf3LVcEEhhBD5SBYWxujZczB6fSjwg5m1p1Grf6dfv9QritWr9xbe3qVQqycCLxZTikSj+YpatRpSunTZFNuwt7fn7bf7oNHMA14cF6kAk7Gy0tC5c+9UY+nT5x30+pPAejNrN6HXH6NPn9xVIU2I7NC4cUsKFSqKSvUpEPvC2nA0mmnUr9+CYsVS6m3OWbp27YNarQBTiH8PSSoIjWYBAQH9pJR7NpAkSwghRM6WBYUxypatwIgRE4CPgR7ATuA48BkaTSMqVKjMgAHmR00k0mg0fP/9QlSqA6jVbwArgL+A/0OjqYmd3U2++urHNGMZO/ZzChd2RqOpDXwDnAQ2oVK1Ahbw5ZczcXdPveuuadO2tG7dFZWqOzAcOAAcBEagUnWlZcvOtGjRIc1YhMhvrKys+P77hajVu1Gr6wMriX8dz0ejqYG9fShffmnux5icqUCBQkyZMgOYjUrVFthC/HvKNDSaOnh7ezBq1ETLBplP5Jp5siwlMjISV1dXmSdLCCFygoS5tc7rfNHiZJxby+clfmRWFIUVK35i9uxvuXUrEAB7e2d69OjPRx/9L933K/z11xG+/noix4/vA0ClUtOkSVs++WQq5ctXSlcb9+/fZerUCWza9HvCTfhQvnwVPvxwEq1bd05XG3FxccyePY1Fi+by+HH8dCfu7oUZNGgYI0ZMwNo6pXs0hBDHjh3gm28m8ddfB4H413Hz5h345JNplClT3sLRZdyWLWv4/vsvuXr1XwCsre3o3LkHEyZMo1ChwhaOLndL7zxZkmSlQZIsIYTIgYKDnxfGwAnsX74whsFg4Pr1K0RHR1OqVBkcHBxfKqQ7d24RFvaAwoW9X/pLTEREODdv3sDR0YmSJX1RqVIqzJGymJgYrl+/AkDp0uVkyhIhMuD27Zs8fvwQL6+iFCyYUjGM3EFRFG7cCOTp0yeUKFEKFxdXS4eUJ0iSlUkkyRJCiBwqoVfrjs6dYEoYe7UyswqhEEIIkVR6k6xcV11QCCGEAIzl3r3DwiA0xFjuPVTnYFwthBBCWIIkWUIIIXI3Dw+8PcA7ydxaoaGemVbuXQghhMgoqS4ohBAib0go9+5vH2hS7j34xcroQgghRBaTJEsIIUTekTC3VtJy7+ievVK5dyGEECKjJMkSQgiR9yTp1fIhxKRXS5ItIYQQWU3uyRJCCJE3SWEMIYQQFiJJlhBCiLxNCmMIIYTIZjJcUAghRP4ghTGEEEJkE0myhBBC5B9SGEMIIUQ2kCRLCCFE/iOFMYQQQmQhuSdLCCFE/iSFMYQQQmQRSbKEEELkb1IYQwghRCaT4YJCCCEESGEMIYQQmUaSLCGEECKRFMYQQgiRCSTJEkIIIV4khTGEEEK8AkmyhBBCCHMSerW8PeNMerVCQ00TrYcPQ/n224nUqFGK0qWdqFevAvPmfcuTJ9p0P9SzZ8/44IO++Pq6ULSoFcWK2dKkyWscOrQ3Cw4sdcHB15k48QMqV/bG19eZZs1q8OuvC4mNjc32WETO9eSJlnnzvqVevQqULu1EjRqlmD59Eo8ePbB0aELkCCpFURRLB5GTRUZG4urqSsSlS7g4O1s6HCGEEJYSHPy8MAae2NtDePh1BgxoxIMHjzEYegHlgNOoVKspW9aP9ev34e6eeuWMJ0+eUKdOGR4/DgVaAW8B94DFQATTps2mb9+hWXxw8f7++xg9erQkOtoWvb4v4I1KtR9F2UqDBi1YunQTNjY22RKLyLnCwh7RuXNjAgOvYDB0A6oCV1CrV1CokAcbN+6nRIlSFo5SiKyh1Ubi5+dKREQELi4uKW4nSVYaJMkSQghhFBYGWi3ndb5ocWLQiOZcuXIfvX4/UDTJhv+h0TSkffuWzJnza6pNBgQ049ChfcAfQPMka7RAa1Sqk1y48CDVD/PMEBMTQ82apQgLK43B8AeQ9DNvD2p1G8aM+ZTRoydlaRwi5xs+vBdbtuxKuO4rJVlzC42mEVWrFmHz5kMWik6IrJXeJEuGCwohhBDplaQwhvbqDi5ePIJePx3TBAugEnr9p2zevJqHD0NTbC4qKorDhw8CgzBNsCA+yVmIosTw7befZuphmLNjx0YePryDwbAA0wQLoCkGw0B++WUBcXFxWR6LyLkePLjPli2r0es/wzTBAiiGXv8tp04d5r//zloiPCFyDEmyhBBCiIzy8eHGnbOACmibwkYd0etj+e+/Myk2c+HCWRQlBuiQwhYVgFL89deRV4k2Xc6cOYmVlS/Jvzgn6sijR3e5e/dWlscicq7//juDXh9HytdsO0DFmTMnszEqIXIeSbKEEEKIl2Dl6gooQFQKWzwDQKOxSrENGxtbk22Ti29fo9G8XJAZYGVlRfyxpHQXQdrHI/K+5+c/pWs2/hqKv56EyL8kyRJCCCFeQtP69VGp1MDyFLZYhqOjK6+/XjvFNipWfA1ra0dgSQpbHADu0rZtt1eKNT0aNmxBXNxt4E+z61WqZfj6VqJIkReHRor85PXXa+Pg4AIsS2GL5ahUat58s2l2hiVEjiNJlhBCCPESShQtSrd27dGoxwN7kqxRgN9QqWYwYMAwHBwcU2xDrVbTvXtvYBswFUhaJv080AdbWyfee29sFhyBqTfeaETFitXRaAYC55KsiQW+QVE2Mnz4h6hUqiyPReRcjo5ODBw4DJXqe2Alz3s+FWA3avXHtG8fQNGixS0XpBA5gFQXTINUFxRCCJES7ZMntOnWg0Nn/0GtrobBUB6N5h/0+iu0bx/A7NnL0xw2ZTAY6NKlISdPHgYKEV/C/RZwBCsrezZs2Jdqb1hmunPnFt26NSco6CJqdX0MBm80mkPo9Xd4//1PGD/+f5JkCWJjY3n//T5s2bIKjaY8en01NJrL6PWnqVOnMcuWbcbR0cnSYQqRJaSEeyaRJEsIIURq9Ho92zdvZvn6DYQ8fIJbYV+atxpC7doNKFky/QnJ5s2rmTnzS+7evYuNjTUtW3bgk0++xtXVLeuCNyM6Oppt29ayZcsatFotZcuWp1evIfj7V83WOETOpigKx48f5PffF3Pr1k08PT3p0qUPjRu3zJZ7CIWwFEmyMokkWUIIIdItLIw7oVaE4YEWJ7B3wNk5vvK7EEKI3E/myRJCCCGym4cH3p5x+NsH4kMIRIQTGgrBwfHzGAshhMgfJMkSQgghMlPChMXennHUdb2IJ6Gge0ZoqCRaQgiRX8gkBkIIIURW8PAADw/8gwO5o3MnDA9Cb7mi1drKEEIhhMjjMtSTpdPpOHz4MBcuXEi2LioqimXLUpozQQghhMinEnq1/O0D8bMJMvZqBQdbOjAhhBBZJd1J1pUrV6hQoQINGjSgcuXKNGzYkLt37xrXR0REMGDAgCwJUgghhMjVkgwh9CHEOIRQ7tUSQoi8Kd1J1vjx4/H39yc0NJTLly/j7OxMvXr1CAkJycr4hBBCiLxDCmMIIUS+kO4k6+jRo0ybNo2CBQtSpkwZtmzZQosWLahfvz7Xr1/PyhiFEEKIvEMKYwghRJ6X7iRLp9OZzFqvUqmYP38+7dq1o2HDhly5ciVLAhRCCCHypIRkK7FXy5NQQm9FS6+WEELkAemuLujn58fff/9NhQoVTJbPmTMHgPbt22duZEIIIUR+4OODd1gY3tpA7uBOsK4EoToHtFrw8bF0cEIIIV5GunuyOnXqxMqVK82umzNnDj169EBRlEwLTAghhMg3pDCGEELkKSpFMqNURUZG4urqSsSlS7g4O1s6HCGEEHldWBhotdzRuRMc44XOxg17e2RuLSGEyAG02kj8/FyJiIjAxcUlxe0yNE+WEEIIIbKYFMYQQohcL933ZAkhhBAiG3l4gIcH/sGB3NG5E4YHobdc0WptpVdLCCFyOOnJEkIIIXKyhF4tf/tA/GyCjL1awcGWDkwIIURKJMkSQgghcjopjCGEELmKDBcUQgiRa02bPZvNu3ZhY23N+OHDad2kSYbbOHP+PHOXLCE6JobmDRvSu0uXLIg0bYqicOjECS5du4aToyOtGjfG3c3NdCMPD7xJKPeucyc4wotQnRtabd4tjLF+/Qr279+JjY0t/foNpXLl1zPcxr17dzh4cDexsTFUqVIDf/9qWRBp2hRF4fjxgwQGXsbJyZnGjVvh6upmkVjCwx+zb992nj59QpkyftSuXR+VSmWRWDLD3bu3OXRoT8I5rom/f1VLhyTyuZeqLrh8+XIWLFhAUFAQx44dw8fHh5kzZ1KqVCk6dOiQFXFajFQXFEKInOfXtWvpN3ocBkNMkqUqnBycOLd3F6VKlEizjbDHj6nTrgNXg64Dzz8KHeydWbtwHq3eeivzA0/Bsb//pt+oD7kadBVQAQq2NvaMemcgX40fj0ajSb5TQhXC8zpftDihwwFPz7yTaB04sJtBg95Gp4tIslSFj08Ztm49iodHwTTb0OmeMWHCCNatW4bBoDcur1q1LrNnL6V06bJZELl5f/11hFGjBnPjxiWM59jWgSFDRjFu3Bfmz3EW0Ov1fPPNp/z004/ExOiMsZQqVYFZsxZTvXqdbIkjszx79pSPPx7Ghg0rTM5xtWpvMGfOMkqW9LVgdCIvyrLqgvPnz2fMmDG0bt2a8PBw9Pr4C9rNzY2ZM2e+dMBCCCFEevx5+DB9Ro7FYCgGbABigHBgJk+exVK+fiNiYmJSbcNgMODXsDFXg24B3wNhQCywmWe6IrTpO5C/z57N2gNJcO7CBZp070FgcEFgHxAH3CU65kO+nTufkZMmm98xYQihv32gcQhh6K3oPDGE8N9//6FXr7bodIWATcSfm8fADwQH36RBA38MBkOqbSiKwqBBXVm3bhUGw/cJ+8cCG/n33zA6dmzI/ft3s/pQADh//jTduzcnJKQAcID4c3yH6OjRzJnzNVOmjM2WOAAmThzJvHnfERMzDribEMs+goPd6NatKRcunMu2WF6VwWBgwIDObNiwDoPhB+LfB2KADZw794COHRsSGnrPskGKfCvDSdbs2bP56aef+PTTT01+dalRowb//vtvpgYnhBBCvKj3Bx8AdsBhoCNgDbgCHwBriY2LZvgnn6TaxuzFi3nw6AGwEhgNuBM/gr4dcAhFceC98eOz7BiSmvTdDGJii2Ew7AEaEf/R7AV8gcJ3zFu6hKCQkJQbyIOFMcaPfxdFSTzH7Yk/N27ASGAVjx/f56efZqbaxuHDf3LgwHYMhpUJ+7kltNMBvX4/4eE6fv459TYyy/TpnxMX54PBsBtoQPw5LgL8D0X5msWLZ3PrVtafsBs3Alm2bB6K8h0whfjrTA00wmDYTWxsUWbM+CLL48gshw7t4fDhXRgMq4H3iX8fsAY6otfvJyxMy6JFP1o2SJFvZTjJCgoKolq15GOZbW1tefr0aaYEJYQQQqTk7v0woD/xX1Jf1Booz++bNqXaxvxly4BSxCdpL/IEBnPq30uvFGd6RERGsmX3LvT6EYCDmS3eRa12ZsX69ak3lMcKY5w7dxYYCBQ2s7Yd4Mvy5QtSbWP9+l/RaPwStn+RF3p9P37/fdkrx5qW8PDH7N27Fb3+fcDezBZDUakc2LhxZZbHsmHDb6jVLsAQM2sd0etHsHPnRrTayCyPJTOsXbscjcYfaGVmrTd6fR9WrVqe3WEJAbxEklWqVCnOnDmTbPmOHTuoUKFCZsQkhBBCpCIO8EthnQqoSHRMXKothEdEABUStjenPBBLXFzq7byqxxERCfeRpHQ8DqjVxQl99Ch9DXp4GHu1fAiBiHBjr1ZuSbYMBgOKEkv8OTAn/hxHRkaksD7ew4eh6PXlSe0cP34c+vKBptPjx49QFAMpH48TanVRHj7M+lgePQpFrS6O+YQeoDwGg56IiMdZHktmePAgFL2+HJY+x0KYk+HqgmPGjGH48OFERUWhKAonT55k5cqVTJs2jZ9//jkrYhRCCCGSsAL+SWGdATiFg71tqi0UKlCA+w9PA3rAXMGB06hVNlhZZW0R3oIeHlhb2xIbexpoZmaLcPT66xT37pT+RhMmMfYOC8NbezG+MIbOiVCdg3F1TqZWq1GrbTEYzqSwhR74hwIFUi98UaRIMTSaXQn3jps/x4ULF3+1YNOhYEFPNBpr9PozgLliKmEYDMF4e2d9LN7exdHrrwMRxA+te9FprK1t01VUJCcoWrQYGs0B9HoD5vsNsuccC2FOhnuyBg8ezDfffMNnn33Gs2fP6NmzJ/Pnz2fWrFkEBARkRYwm5s6dS8mSJbGzs6N27dqcPHkyXfv9/vvvqFQqOnbsmLUBCiGEyFKlShQBVgBXzKxdAYTwbp8+qbYxbuhQ4m/6X2Jm7XVgCfVqZX2ZbydHR7q1a4OVZg5grrfqe1SqWHp37pzxxnNxYYxateoAS4FrZtYuB27z7rsfptpG9+4D0OtvJGz/omuo1Svo3Xvgq4aaJmdnF9q27YpG8yPxBVZeNB2VSk/nzr2yPJbOnXsD0cQXe3nRIzSaOXTo0B0HB8csjyUzBAQMRK8PBH4zs/YyavXv9Oo1ILvDEgLIYJIVFxfHsmXLaNq0KVevXuXJkyfcu3ePW7duMWjQoKyK0WjVqlWMGTOGyZMn888//1ClShVatGhBaGjqXcE3btzgww8/pH79+lkeoxBCiKy1cdEi4nus3gDmACHAf8BHQH8c7B2Z+vHHqbbR9+23KVuqNPH3pnwInE9oZx5QFyuNwqLvvsu6g0jiiw8/xNn5GRrNGyQmEPA3MAj4H5NGj6JIYXP3JqVTLiyMMWPGL2g0KuLP8Vyen+NxwCB8fHzp1q1fqm28/nptunTpi0o1OGG//xLamYtGU5/ixYszYMD7WXocicaN+wJHxydoNPWI/yHgNvAX8fcWfs2HH35OwYKeWR6Hl5c3o0dPBL4k/vr6OyGW5Wg0b+DsHM3YsZ9neRyZpUaNN+jQoScq1QBgPHABCAZmo9E0wMenJP37D7dskCLfyvA8WQ4ODly8eBEfH5+siilFtWvXpmbNmsyZMweIH7ddvHhx3n//fT5O4QNVr9fToEEDBg4cyKFDhwgPD2fjxo3pfkyZJ0sIIXKeI3/9RbOAHuiiong+x5WGYkU8ubh/P05OTmm2ERMTQ7OAAA6eOEX8fV4AKooU9mLHr8t4rWLFLIo+ucvXrjH0k8/Yd+SQcVmhAoWZNPp9hvfvn3mTxIaFcSfUijA80OIE9g45dhLjS5fO07NnK+7fv83zc2xF7dp1+f33PdjY2KTZhl6vZ8aMKfz002yePg0HQK3W0LJlJ6ZNm5stiU2ia9cuMWHCCI4e3WtcVrCgN2PGfEbfvu9l20TAiqKwZMlcfvhhKo8ePS9hX69eM6ZNm4Ovb7lsiSOzxMXF8d13k1m8eC5Pn8bfp6dWW9G6dWemTp1DgQKFLByhyGvSO09WhpOsRo0aMWrUqGwfdhcTE4ODgwNr1641eex+/foRHh7OphQqSU2ePJlz586xYcMG+vfvn2aSFR0dTXR0tPHfkZGRFC9eXJIsIYTIgXYfOMCytWuxt7Njwvvvp2sS4hc9DAtj6erVPNXpaP3WW9SoUiULIk2fwBs3uBwYiJOjI3WrV8fa2jrzHyRhEuM7OneCY7zQ2bhhb0+OTbb+/fcf9uzZiq2tPQEBA17qfiGd7hl//32M2NgYKlasgpeXdxZEmj5BQde4fv0KTk7OvP56naw5x+kQGxvLqVPHePr0Cb6+5XP9pL3Pnj3l1KnjxMbGUKlSVQoXNld9VIhXl2VJ1urVq5kwYQKjR4+mevXqODqajtt97bXXXi7iNNy5c4eiRYty9OhR6tata1z+0UcfceDAAU6cOJFsn8OHDxMQEMCZM2coWLBgupKszz//nClTpiRbLkmWEEKIPCUh2Tqv80WLEzoc8PTMmYmWEELkFOlNsjJcNimxuMUHH3xgXKZSqVAUBZVKlVDFx/K0Wi19+vThp59+omDB9P/qNWHCBMaMGWP8d2JPlhBCCJGnJFQh9A8O5I7OnTA8CL3lilZrm2N7tYQQIrfIcJIVFBSUFXGkqWDBgmg0Gu7fv2+y/P79+3h5eSXbPjAwkBs3btCu3fNJCA0GAwBWVlZcvnwZX9/kXeO2trbY2qZe+lcIIYTIM3x8Esq9B3IHd4J1JQjVOaDVggVuvxZCiDwhw0mWJQpeANjY2FC9enX27t1rvCfLYDCwd+9eRowYkWx7Pz8//v33X5Nln332GVqtllmzZknvlBBCCJEoydxahIbEF8bQOREcnHMLYwghRE6W4SRr2bJlqa7v27fvSweTljFjxtCvXz9q1KhBrVq1mDlzJk+fPmXAgAHGxy5atCjTpk3Dzs4Of39/k/3d3NwAki0XQgghBPGJFgm9Wjp3giO8CNW5odXm3MIYQgiRE2U4yRo5cqTJv2NjY3n27Bk2NjY4ODhkaZLVvXt3Hjx4wKRJk7h37x5Vq1Zlx44dFE6YPyQkJAS1OsPzKwshhBAiUZJeLW/txfjCGDonQnUOxtVCCCFSl+HqguZcvXqVoUOHMm7cOFq0aJEZceUYMk+WEEKIfC04+HlhjBhX7F2lMIYQIv9Kb3XBTOn2KVu2LF9//XWyXi4hhBBC5HI+Pnh7xuFvH4ifTRDonhEaCsHBlg5MCCFyrkwbW2dlZcWdO3cyqzkhhBBC5BQeHsZky4cQPAkF3TMuXYqfbksIIYSpDN+TtXnzZpN/K4rC3bt3mTNnDvXq1cu0wIQQQgiRw7xYGCPGi9BQKYwhhBAvynCSlVg+PZFKpaJQoUK89dZbfP/995kVlxBCCCFyIimMIYQQacpwkpU4oa8QQggh8rGEZMs/OPB5YYxbrmi1UhhDCCEyfE/WF198wbNnz5It1+l0fPHFF5kSlBBCCCFyCSmMIYQQyWS4hLtGo+Hu3bt4enqaLH/06BGenp7o9fpMDdDSpIS7EEIIkU5hYdwJtSIMD7Q4ocMBT0/p1RJC5B1ZVsJdURRUKlWy5WfPnsVD3kWFEEKI/MvDw9ir5UMI9jHhxl4tqUIohMhP0n1Plru7OyqVCpVKRbly5UwSLb1ez5MnT3jvvfeyJEghhBBC5BIpFMbQIoUxhBD5R7qTrJkzZ6IoCgMHDmTKlCm4uroa19nY2FCyZEnq1q2bJUEKIYR4dRevXmXukiXsPngMRVF4q14thvfvT+UKFSwdWq729Nkzlq9dy69r1hAaGkqJ4sUZ0LMn3dq1w9ra2tLhWU5CNuXvHMp5rR3IiHshRD6S4XuyDhw4wBtvvJFvPjjkniwhRF6wcuNG+nwwEhUFiNN3BtRYaTagN9xj0fffMaB7d0uHmCuFPnxIky5duHDtGm1UKsopCqfVav40GGhUuzbbVqzAwd7e0mFaTsIYwfPaEuAcf++C9GQJIXKz9N6TleEkK6moqChiYmJMlqX2YLmRJFlCiNzu8rVrVHqrCXp9T+AnwCZhTSwwHJVqEad37qBKpUqWCzKXat2zJ6cPH2aPXk/SZ+8g0Fqtpm/v3sybNs1S4VmeJFlCiDwmywpfPHv2jBEjRuDp6YmjoyPu7u4mf0IIIXKWecuWocIdWMjzBAvAGpiHRl2E2b8ssUhsudnla9fYfuAA019IsAAaAB8bDCz5/XfCIyIsEV7OodXiobuDNvSZFMEQQuQbGU6yxo0bx59//sn8+fOxtbXl559/ZsqUKXh7e7Ns2bKsiFEIIcQr2HvoBHH6DoCtmbVWxOm7sPfwiewOK9c7dPIkAF1TWN8N0MXE8PfZs9kWU47j4WGcR8uHEDwJNc6jJYmWECIvS3fhi0Rbtmxh2bJlNGrUiAEDBlC/fn3KlCmDj48PK1asoFevXlkRpxBCiCyUfGIOITKRhwfeHuAdHMgdnTtheBAa6olWC87OMoRQCJH3ZLgnKywsjNKlSwPx91+FJfwU9eabb3Lw4MHMjU4IIcQra1K/NhrNRiDazNo4rDTraNqgTjZHlfvVr1ULgDUprF8F2NvYUKNKlWyLKcdL6NXytw/EM+aWsVcrONjSgQkhRObKcJJVunRpgoKCAPDz82P16tVAfA+Xm5tbpgYnhBDi1Q3r2xcIB97BNNGKBYaiN9xlRP/+FogsdytfpgytGzVinEbD+RfWHQC+VqvpHxCAW5IpTwTGIYT+xcJNhhDKvVpCiLwkw0nWgAEDOJswvvzjjz9m7ty52NnZMXr0aMaNG5fpAQohhHg15cuU4dfZP6LRrMRKUwIYCgzHSuODWrWYxd9/x2sVK1o6zFzpl1mz8CxdmipAO5WKsUBjtZpGQO1atfhu0iTLBpiTeXgYe7V8CDHp1ZJkSwiR271SCXeA4OBgTp06RZkyZXjttdcyK64cQ0q4CyHyikvXrjF3yRJ2HTiKoig0ebM2w/v3x9/Pz9Kh5WrPdDp+XbeO5atXGycjHtirF13btMk3c0q+srAw7oRaEYYHWpzQ4YCnp9yrJYTIebJtniw7O7uX3T1XkCRLCCGEyCbBwc8LY+CJvb0UxhBC5CxZNk+WXq/nyy+/pGjRojg5OXH9+nUAJk6cyKJFi14+YiGEEELkb1IYQwiRR2Q4yfrqq69YsmQJ3377LTY2zye19Pf35+eff87U4IQQQgiRzyQWxnC9KYUxhBC5VoaTrGXLlrFw4UJ69eqFRqMxLq9SpQqXLl3K1OCEEEIIkU8l6dWSwhhCiNwmw5MR3759mzJlyiRbbjAYiI2NzZSghBBCCCHw8IivQhgWBqEh8YUxdE6E6hyMq4UQIifKcE9WxYoVOXToULLla9eupVq1apkSlBBCCCGEkYcH3n4uxl4tT0KlV0sIkaNluCdr0qRJ9OvXj9u3b2MwGFi/fj2XL1/m/9u79zgZy/+P46+Z2fORicWy1iHa5JhTlEoISY6hEL4OiVTUt/SrqCid6ITqq4P6poRKoiSkEqmvQ5FDLNZhrU3L7uzusLsz9++PZbNrZw/M7Ozh/Xw85lHu655rP/dcuzvz2eu6P9cHH3zA8uXLPRGjiIiISPYSwqQkIm2x7EjOwIaVRHsQNhtER3s7OBGRfxR7JqtXr158+eWXrF69muDgYKZMmcKuXbv48ssv6dKliydiFBEREcl2rjBGrVMqjCEipVaR98nav38/devWxWQyeTqmUkX7ZImIiJRSSUlgsxFvr0wctbETpL21RMSj3L5PVoMGDfjrr79y/j1w4ECOHz9+aVGKiIiIXKyzs1qREVm5ZrUSEzWrJSLeVeQkK++E11dffUVaWprbAxIREREpFhXGEJFSptj3ZImIiIiUSuftrRWRcSTX3loiIiWpyEmWyWS64H6sinZ/loiIiJRyKowhIqVAkUu4G4bB8OHD8ff3B+D06dOMHTuW4ODgXOd99tln7o1QREREpLisViLJLvceb69MnL12Trl3FcYQEU8rcpI1bNiwXP8eMmSI24MRERERcRurNTvZSkqCxEMkYcVmDyHRHpTTLCLiCUVOst577z1PxiEiIiLiGVYrkVaIjMue1UrCSmJiBDZb/qdrpktELlWRkywRESn7Tp46xS/btmEYBq2bNeMyL36S3L5rF3FHjlDFaqVNixaYzarFtO/AAfbExhISHEz7Vq3w9fX1dkjlS3Q0kUnZSwh3JGdA4IV73NjsPjnLCqOj3R/C/v172b//T0JCQmnZsp3GWKScUpIlIlIBpNvtPPT008xfuBB7RgYA/r6+DOnXj1eefpqQPPfXetKGX3/l/sce439//JFzrH6tWsx4/HFu79mzxOIoTfbs28e4yZNZu3FjzrHqViv/N3Ei944YoUJT7nR2CWHjpCSwHb6gOZ7KOcsKd+8OIiLCPbNae/fuYvLk8fz883c5xy67rAaTJj3GsGHjNMYi5YySLBGRci4rK4ueQ4eyadMmHnM6GQSYgCWZmUxftIjdf/7JmiVLcgobedLG//2PTrffTjOHg2VAK2AfMPPIEQaMHcsHZ84wtH9/j8dRmsQePMh1t93GZampfAh0BI4BbyQlcd8TT5B06hRTJ03ycpTl0NlkK69zM13x9srEZVQnMbHSJRfL2L9/Lz17Xkd6ejXgI+AGIJ6//57LY4/dS3LyKe6//7FLuRoRKWVMRt5dhiWXlJQUwsPDSd69m7DQUG+HIyJSbJ988QWDxo1jLdkf4M/3M9AOeG/WLIYPHOjxWK699VYyf/uNH51Ozk/pDGAo8E14OEe2bi2RhK+0GDphAt9/8QVbHQ4uy9P2BPCcxcKhX3+lRrVq3giv4kpKApuNHfb62AjBzsXPao0bdyfLl2/A4dgKVM7T+igWy0w2bz5M1aoaY5HSzmZLISYmnOTkZMLCLlxyfI4WwIuIlHPvffwxHczmCxIsgGuArmYz7y5Y4PE49uzbx4atW3kkT4IF2TNrTwAnkpNZvnq1x2MpLVLT0li0bBn35pNgATwE+BkGH2p7lJJ3br+twNic/bYSj5wp9n5bNlsKy5cvweG4jwsTLICHMQwLn33m+Z9BESk5SrJERMq5I0eP0tzpdNnewunkSHy85+M4dgyA5i7arwACzeac8yqCE0lJZGRl0cJFezhQ12LhcAmMj7gQHU1kRBaNA2OJCU8Aezo2W9ETrRMnEnE4MnH9nV8Zi6UOx44dcVPAIlIaKMkSESnnIiIi2FNA5b7dJhMRVat6Po4qVQDY46I9DrA7nTnnVQTWSpWwmM3sdtGeDhx2Oom4LL95LikxViuEhhIZaiM0MIvi3D1QufJlmExmXH/np+JwHKZKlQh3RCoipYSSLBGRcm7ogAF863SyNZ+2ncCXwF0lcD9W45gYml1xBS+ZTDjyaX8RCAsK4rabb/Z4LKVFWGgovW6+mdkWC2n5tL8J2JxOBvftW9KhiZtUqlSZTp1uxWJ5ney0Oa+5GIadPn3uLOnQRMSDlGSJiJRzd/TqRYsrr+Rmi4V3yf6YZwc+ADpZLMTUq8ddt9/u8ThMJhPPT5nC90Avk4n/kV3wYh8wFpgDPPXwwwQHBXk8ltJk6oMPctTXl85mM2sBJxBP9j1q/zaZGD9sGHVr1/ZukJKLq02MXfn3v5/CxycOs7kLsI5/RvkxYDIjR95HzZoaY5HyREmWiEg5FxAQwKpFi7juppsYZTIRDAQBw4CrO3Rg7Wefldg+WV1vvJHP332X7RERtCb7TagBsCgkhFeffpr7R40qkThKk6aNGrF60SJS6tShE2ABagKz/P15ZPx4Xnn6aS9HKED2kkGbDas9nlB7IomJFLkIRuPGzfnkk2+Jjj5Jdo3P7FH293+V++77P6ZOnenh4EWkpKmEeyFUwl1EypPYgwf5YdMmDMPgutataVi/vlficDgcrP7xR+KOHKGK1Ur3jh0JDAz0SiylhWEY/PTrr+zau5eQ4GC6d+xIpfBwb4cleZ0r7Z4chc3Pip0gAgMhOrrwpxqGwaZNPxIbu4eQkFA6duxOWJjGWKQsKWoJdyVZhVCSJSIiIhdISiI+0YckrNgIgcCgS9qwWETKBu2TJSIiIuIpVmtOafdoDoE9vVhLCEWkfPPxdgAiIiIiZZLVmp1sJSVB4qHsWS17CIn2oJxmEamYlGSJiIiIXAqrlUgrRMbFEm+vTBJWEhMjsNnQEkKRCkrLBUVERETcITo6ZwlhRMaRXEsIRaRiUZIlIiIi4i5WK0RH07jWKaI5RASJYE/XvVoiFYySLBERERF3U2EMkQqtzCVZc+bMoU6dOgQEBNC2bVt++eUXl+fOmzePDh06ULlyZSpXrkznzp0LPF9ERETEbc7OakVGZOWa1UpMVKIlUt6VqSTrk08+YdKkSUydOpUtW7bQrFkzunbtSmJiYr7nr1u3jjvuuIPvvvuOjRs3EhUVxc0338zRo0dLOHIRERGpsKxWImPCcma1IkjUrJZIOVemNiNu27YtrVu3Zvbs2QA4nU6ioqKYMGECkydPLvT5DoeDypUrM3v2bO666658zzlz5gxnzpzJ+XdKSgpRUVHajFhEREQuXVIS2GzsSI7C5mfFThCBgRAd7e3ARKQoyt1mxBkZGWzevJnOnTvnHDObzXTu3JmNGzcWqY/09HQyMzOxFlBLdcaMGYSHh+c8oqKiLjl2EREREUCFMUQqiDKTZJ04cQKHw0G1atVyHa9WrRoJCQlF6uORRx4hMjIyV6KW16OPPkpycnLO4/Dhw5cUt4iIiMgFVBhDpFyrMJsRP/fccyxcuJB169YREBDg8jx/f3/8/f1LMDIRERGpkKzW7GQrKQkSD5GEFZs9hER7UE6ziJRNZSbJqlKlChaLhePHj+c6fvz4capXr17gc1966SWee+45Vq9eTdOmTT0ZpoiIiEjxWK1EWiEyLpZ4e2WSsJKYGIHNBqGhSrZEyqIys1zQz8+Pli1bsmbNmpxjTqeTNWvW0K5dO5fPe+GFF5g2bRorV66kVatWJRGqiIiISPGdLffeODCWiIwjuZYQikjZUmZmsgAmTZrEsGHDaNWqFW3atOGVV14hLS2NESNGAHDXXXdRs2ZNZsyYAcDzzz/PlClT+Oijj6hTp07OvVshISGEhIR47TpERERE8nV2CWHjpCTiE1NzlhDGxQVpVkukDClTSdbAgQP566+/mDJlCgkJCTRv3pyVK1fmFMM4dOgQZvM/k3NvvPEGGRkZ9O/fP1c/U6dO5cknnyzJ0EWkDEqx2fjw009Z/u23nDlzhuZNmnD3kCE0rF/f26FdlHcXLuTexx7jzOnTAPj5+zNr6lTuGTasyH2cOXOGxcuXs/jLL7HZbDS8/HLGDBnC1U2aFLkPwzD4cdMm3l24kLhDh6hSpQqD+/bl1s6d8fEp2belI8eOMfHJJ/n+p59wOhzUrVuX5x59lE4dOhS5D4fDwYo1a/jvp59y/K8k6tSqwYiBA7mxfXtMJlOR+9m2Ywf/WbCAP/6MJSwkiP49bmHgbbcVeB+xlGNWK5EkEWnLXkIYZ69Noj1ISwhFyogytU+WN6SkpBAeHq59skQqmO27dtFt0CCO//03nYBKhsEai4Ukp5PXp09n/PDh3g6xWFp1787W33/HB+hG9lrxlUAGENOgAX+sW1doH0ePHePmAQPYuX8/HcxmajqdrLdYOOJw8O977uH5xx4rNKnIyspixAMP8OHnn9PAYqGVw8E+i4VfHQ6uvfpqVixYQHgB+46406JlyxgybhwOw6AzEA6sApKBO3r35qM5cwrtw5aayi1Dh7P+l41YLFfjcFyBj2ULWY49DOh5Gx++/hq+vr4F9mEYBo8//zzPvv46PpZIshzXYzYdw2l8T/3o+qxd/DG1a9Z0xyVLWZWURHyiT/asFiHYCSIiQomWiDeUu32yRERKit1u55Y776TqyZPEGgbfGAafAIcdDiYYBvc+9hhrfvzR22EW2XOzZ7P199/pAhwDvgA+P/v/twK79+7loaeeKrAPwzDoO2IEtrg4fgN+cDr5GDjgcPAS8OIbb/DOxx8XGsu0V17h46VL+QDY43DwEfCLw8H3wB+//ca/HnjgEq606E4kJTF03DgaGQYHgW+ARWS/JvcCHy9dyivz5hXaz6iHHmbj5j+A1Tgcm4GPyHLsAj5m8fKvmPLSS4X28d8lS3j29deBGWQ5DgIf4zTWATuIO+Lg1rv+hf4eWsFZrUTGhOWUe48gUeXeRUo5zWQVQjNZIhXP/E8+YcSkSfwJNMjTZgCtLBaqd+jAigULvBBd8fnVqYNfZibHgLy/xexATSDFYiHr0CGXffy4aRPX9+3LKqBLPu23m0xsr12bXT/95HI2y263U6tFC4bZbMzKp/1dYJTJxN7166lfp04RruziDX/gAT5YvJh9QL08bU6gGfB3lSrE//abyz7ijhyh7jXtMIw5wNh8zniEkOA3Sdi2meCgoHz7MAyDqzp2Yfe+BhjGF/mcsQ7oyOqFC4u1hFHKsaQksNnYkRyFzc+KnSACAyE62tuBiVQMmskSEblI33z/Pe3M5gsSLAATMNTh4JsffsDpdJZ0aBcnM5P+XJhgAQQCgwCLw1FgF9+sW0d1Hx9cbeV+l2GwJy6OuCNHXPaxeft2kmw2hrpov4PsN6Vvf/ihwFjcYfWPP9KeCxMszsYwHEg4caLAMV6zfj2G4QSGuDjjLlLTUti0ZYvLPhISE9m1dxeGcZeLM27AxyeKlUVYzikVhNUK0dE0rnUqZ1YLe7pmtURKGSVZIiJ5ZGVlEVhAexDgcDrLzBIuExR6PYXJcjgIONtXfs71n5WV5bqPs22uYvEDLGe/lqc5nc4CrzuQ7FnLgpKs7OsxAa4KU2R/hYKu55/Xy9WrYsJEYIGvq1RQVmtOufdoDuUq965kS8T7lGSJiOTRpkULfgJOuGj/3Gym1VVXYbFYSjKsi5ZpMrEUyO9juhNY4qLtfG2aN+dgVha/u2hfClSrXJnoWrVc9tEkJgZ/X1/yWxQHZwtxGAZtmjcvJJpL17RRI74HXH0W/QwIDwwssNphdpwG8KWLMz7Hx+JL86uuctlHZPXqVKtag+xXMD87ycz6k7ZXX+2yD6nAzs5qRUZk5ZrVSkxUoiXibUqyRETyGDFwIBZfX+42mcjI0/YBsNLp5N5Ro7wR2kUZcOutJACTyU4JzjGAJ4E4oPMNNxTYR88uXYiqVo2xZjPJedrWAm+bzdw9fHiBlfQus1oZ3Lcvz1ks5L3T6RjwoMVCmyZNaF0CSdbMKVPIIvtOqsw8be8Ba4A7b7+9wD6aN25Mu5Zt8LH8G8i7THIHFsuzDLitJxFVqrjsw2KxMGHEUMym+WSX3zifDbN5LFUvq0bf7t0LvyipuFQYQ6TUUeGLQqjwhUjFtGzVKm4fPZrqhsEQh4NwYIXZzA9OJyMHDWLeSy8Vaw8kbwuPiSHFZiMGuJPsv7AtBHYAQYGBpO3bV2gfv2zdSteBA/E5fZqhDgeRwA9mM8udTrpcdx3LPvgAf3//Avs4lZxMp/792b5rF/2AVobBPmCB2Uyo1cr3S5dyed26l3q5RfLIM8/w4ty5RALDyC7h/gWwAbjy8svZ8d13ufZezM+BQ4e4tnd/Ev9KxuG8E2gIbMFsWsKVDRvww6efYK1cucA+MjIy6P2vUXz93VrM5u44nR2BY1gs/yXA/zSrPvov7Vu3dsclS0WgwhgiHlXUwhdKsgqhJEuk4vp9505effttvly5kjOZmbRo3JhxI0Zwe8+eZSrBOueGfv1Y//PPOUsYnECr5s3ZtGJFkfs4cOgQr73zDouXLiUlLY2GdesyZtgwRgwcWOh+UOekpafznw8/5J3//pe4+HiqVK7MkAEDuHfECKpVrVr8C7sEi5Yt47Hnnyfu4EEMICw0lOF33MGLTzxRaIJ1zl9//83s997j3YWf8vfJv6lZI5K7hwzi7iFDCA0JKVIfmZmZfLBkCXPmf8ie2H0EBwYzqHcP7h850uOVFqWcyrO3FoFB2sRYxA2UZLmJkiwREREpk87OasXbKxNH7ZxZLSVbIhevqEmW6zt6RURERKTsslqz79dKSoLEQ9mzWvYQEu1BOc0i4hlKskRERETKM6uVSCtExsUSb69MElYSEyOw2TSrJeIpqi4oIiIiUhGcLffeODA2p9y7zaYKhCKeoJksERERkYri7LRV49BEdtgCQLebi3iEZrJERERERETcSEmWiIiISAVls3k7ApHyScsFRURERCoamw2rPR44TaJdRTBE3E1JloiIiEhFcl5p90hbLDvsqLS7iJspyRIRERGpiM4mW43PL+1+JBybzV+zWiKXSEmWiIiISEUWHZ0zqxVPZeLstUm0B7m8X0sJmEjhlGSJiIiIVHTnLSEk8RBJWIGAC06z2X20rFCkCJRkiYiIiEg2q5VIsme18hPP2WWFiSqWIVIQJVkiIiIi8o+zs1r5ySmWkZyBDWvOssLo6BKOUaSU0z5ZIiIiIlI0VitER9O41imiOUQEiWBPJy4OkpK8HZxI6aEkS0RERESKx2olMiKLxoGxRHMI7OkkJqJkS+QsLRcUEbcyDIP9cXEk22zUqVULa+XK3g6p3Ig7fJgNmzdjrVSJLtdfj9nsnb+TGYZB7MGD2NLSiK5Z86LH+I89e9j2xx/Ui46mXcuWF9VHWno6e/fvx8/Pjyvq18disVxUP1K+ORwO9sTGkpGRQYN69QgOCvJ2SOVDPsUytN+WSDbNZImI23y5ahWtunTh8muvpWW3blRv1ow7x43j0NGj3g6tTPt9504ub9+eetdcw53jx9Nt8GDC6tVj4tSpJR7L0pUrubpzZxpcdx1Xd+1K9WbNGDx+PEfi44vcx/LVq4ls1owmN93EkAkTaH/bbVRu2JBX5s0rch+paWk8MGUKkc2a0aJrV67q2JHL27Zlzvz5GIZxMZcm5ZBhGMydP5+611zHVR070qJrVyKatuD+KVOwpaZ6O7zyw2olMiYsZ1YrgkTNakmFZzL0blSglJQUwsPDSd69m7DQUG+HI1Jqvb9oEcMnTqSTycS9hkEt4EdgpsUCVisbV6wgqmZNb4dZ5vyxZw+tunQh2OHgYaAjcByYC3wN3N6zJ4vefLNEYnl34UJGPvggXUwmxhsGNYEfyB5jS5UqbFyxgpo1ahTYxxcrV9J/5EiigIeB1sA+YBbwKzD1wQeZOmlSgX3Y7XZu6tePHdu3c5/TSU8gDZgPfAhMGjOGmV5IQKX0eXj6dF584w1gMDAcCAW+xGJ5jeaNLueHzxcTFBjo1RjLnaQksNnYkRyFzc+KnSACA1UYQ8oPmy2FmJhwkpOTCQsLc3mekqxCKMkSKZwtNZWazZvT127nPcB0XtsxoJXFQqfevfngtde8FGHZ1bRTJw7v3s1WoM55xw3gPrKTrR3r1nFlgwYejSM5JYWaLVow6PRp5pF7jI+SPcbd+/fn3VmzCuynaqNGVE5O5heg0nnHs4DbgDUmE8n79hEQcOH+POfMeustJk+bxk+GQes8bS8Dk4Btq1bR7Kqrinx9Uv78vnMnzbp0AV4EHsrTuhmzuT3PP/YID40d64XoKoCkJOITfbKXEBICgUEq9y7lQlGTLC0XFJFL9smyZaTZ7Uwn94dvgBrA/Q4Hi5YtI8Vm80J0ZVdKSgo7d+9mPLkTLMh+nacCFuDRZ5/1eCwfL13KmTNneJoLx7gmMMHh4OPPPitwCdYPP//MieRkHid3ggXZNwhPBzIMg+dmzy4wlnkffEA/uCDBArgXiLRYmPfRRwX2IeXf2x9/jI+lOnB/Pq0tcTpv54339X3iMSqMIRWckiwRuWT7Dh4k2teXWi7arwXOZGZyNCGhJMMq83bt24eD7NcvP1WABsD+Q4c8HktsXBx1fXyIdNF+LXA6M5Njx4+77GPTli055+bnasAP2L5nT8GxHD7MdS4WYfgCbR0OYg8cKLAPKf/2HTxIlqMt2d8V+bmWg0cOlmBEFdDZcu+REVm5yr0nJirRkvJPSZaIXLJKYWH85XCQ7qI97ux/w7XktlhqVKsGgKsUKpPs5ZglsZS5UlgYx51OTrtozxnjApZOFHY9x4EM4LJKlQqOJSQk5+vlG4vFQqVC+pDyr3J4OBZLgd8phIaEl1g8FVrewhiBKTmzWiLllZIsEblkt996K2mGwXv5tDmA2WYzHVq1IrJ69ZIOrUyrXbMmEVYrr5OdfOT1MXASmDh6tMdjGdCzJykOB+/n05YFzDGb6XjNNVSrWtVlH4N69SLQYuEVsu8py+t1st+UHr333gJjGdi3L/MtFk7l07Ye2OJwMKhXrwL7kPJv4G234XBsI7s8S17J+FjmM6TvbSUcVQUXHU1k4EmsoZlERHg7GBHPUpIlIpesfp06jBgwgEkmE68C5+7K+RMYaDKxyTCY+lDeG8+lKJ6ZPJmdQG9g59lj6cBbwBggqnp1+vXo4fE4GtSrx7D+/bnPZOJ1sqv5AewBBphMbAamPPhggX34+PgwatgwlgGjgMNnj58EngaeBdq1bk3dQsqQTRozhszAQG62WPiZ7IQtE1gM9LFYaNOkCT06dbq4C5Vyo0enTrRu1hKLpS+wiOzvEgPYhMXSlYAAO5PGjPFukCJSbinJEhG3eOO55xg2aBCTTCaqms1E+vhwBbAuNJRFb71Fpw4dvB1imTRq8GCefOghVptMXAVEAJcBY4GatWqxbfXqEovlrRdeYOjAgdx/3hjHAD+GhbFk3jxubN++0D5emzaNof368T4QTfb1RABPAm2uvpp1S5YU2kfd2rVZs2QJSTVq0A6o7uPDZWYzA4Cr27Xjq48+wsfH5xKuVMoDi8XCygXvc9O1TYGBWMyX4eNTHbiGmtUT+G7xQuqprriIeIhKuBdCJdxFiufQ0aN8umIFKampNKhbl77duxdYjluKJjU1lSkvvcTWHTsICQ5m4ujR3HTddV6J5eDhw3z+9dekpKbSsF49+nTrVuwxjk9I4PEXX2T/wYNUrVKFqRMn0jgmplh9OBwOVn3/Pb/+9ht+vr5079hRZdslX7/v3MlXa9eSkZlJq6ZN6XrjjVgsFm+HVTHlKe1uJ4iICJV2l7JD+2S5iZIsERERETc6u2FxvL0ySVhJJILAQLSPlpQJRU2ytJ5CREREREqO1ZpdcTApiUhbLDvsYLOHkGgPymkWKeuUZImIiIhIyTubbDWOi/1nVutIODabv2a1pMxT4QsRERER8Z6zGxY3Dowlxu9AzobF2kdLyjIlWSIiIiLiXVZrTrIVzSEiSAR7Ort3Z9/CJVLWaLmgiIiIiJQOViuRZN+rlbOEMDECm02FMaRsUZIlIiIiIqWHCmNIOaAkS0RERERKHxXGkDJM92SJiIiISOmlwhhSBinJEhEREZHSTYUxpIzRckERERERKRtUGEPKCCVZIiIiIlJ2qDCGlAFKskRERESk7FFhDCnFdE+WiIiIiJRdKowhpZCSLBEREREp21QYQ0oZLRcUERERkfJBhTGklFCSJeJl23bs4L+ffkrCX39Rq0YNhg8YwJUNGng7LK/6cMkSJs+YwcnkZAIDA7l78GCe/ve/sVgsRe7j0NGjPPj002z5/XcsFgu3du7M9IcfJigoqMh9nD59mqdmzeKzr78mMzOTJjExzHrySerXqVOs61nw2WfMfOstkk6dolrVqkydOJFbOnUqVh/Hjh/nvU8+YefevYQEBdGvRw86XXcdZnPRFyTY7XYWffkl323YgGEYXH/NNdzRuzdBgYFF7sMwDNZt2MDi5ctJSU3linr1GDFwILUiI4t1PSIiHqPCGFIKmAzDMLwdRHHMmTOHF198kYSEBJo1a8brr79OmzZtXJ6/ePFinnjiCQ4ePEiDBg14/vnnueWWW4r89VJSUggPDyd5927CQkPdcQkiAGRmZvKviRP58PPPqeHjQ0PDYCfwl8PBuGHDeH369GJ9gC4PHA4H0W3acDQhgTCgKbAfiAeC/Pz4c8MGataoUWg/T82axbSZMwFoBaQCfwABFgtLP/iArjfeWGgfP/36KzfffjvpmZnEAJWA/wFO4P7Ro5n15JOF9pGamkrjjh2Ji48nAmgA7AROAk2vvJLNK1fi41P437re/OAD7nv8cXwNg5YmE8dNJv7MyuKaZs348sMPqVKETwybf/+dnkOGcOzvv2llsWAGfnU4qFKpEkvnz6d969aF9nHy1Cl6Dx/OD7/+Sn0fH2oaBlsMAzvw4hNPMHHMmEL7EBEpcXFx/8xqZYQTGK7CGHLxbLYUYmLCSU5OJiwszOV5ZeoT3CeffMKkSZOYOnUqW7ZsoVmzZnTt2pXExMR8z9+wYQN33HEHI0eOZOvWrfTu3ZvevXuzY8eOEo5c5EIPT5/OJ0uX8i5wKCuLdQ4HRxwOXgPeeP99pr/6qrdDLHEtu3XjaEICzwAJwI/AIeATwJGRQaPrry+0j8+//pqnZ86kO3AY+BnYAfwGRDkc9Bo6lBOFLNBPT0+nS//+VMnM5BdgF7AROArcDrwybx7vfPxxobFc26sXR+PjmX/2ueuBY8ArwPZdu7hl6NBC+1ixejX3PPooYxwO4p1OfnA42J2VxRpg/44d9B0+nML+VpZ44gRdBw4k6uRJ9pKdXG1yOIgFYlJSuGXwYI7Exxcay6C772bHli2sBPZmZfH92ZjudzqZ9NRTLFm+vNA+RERKnApjiBeUqZmstm3b0rp1a2bPng2A0+kkKiqKCRMmMHny5AvOHzhwIGlpaSw/743/mmuuoXnz5rz55ptF+pqayRJPSDp5kpotWvBYZiaP59M+CZgfEsLRbdsILMZSrrIsNTWVyldcwWBgfj7ts4H7gKXvvsttXbu67KfhddeRduAA+wH/PG17gSuA4YMG8e7Zma78THrySV6eN48tQIs8bVlAI+B09eoc2rzZZR97YmNpdP31TAcezaf9PuBNIHHnTiqFh7vsp8Ntt2HeupV1TiemPG1fA7cA65cu5doCZqKeefVVnnnpJeKcTqrmaTsF1Dabue/ee5n+yCMu+9j8+++06t6dT4G+edoMoLvJRGJMDJu//RaTKW+kIiKlRFIS8Yk+JGHFRgh2goiI0KyWFF25m8nKyMhg8+bNdO7cOeeY2Wymc+fObNy4Md/nbNy4Mdf5AF27dnV5PsCZM2dISUnJ9RBxt1U//MDpzExGuWgfBZxMTeXHX34pybC86sU33yQLGO2ifRjZv7CmFTLDd/DAAf7FhQkWZC/X6wB8vXp1gX18vnIlzbkwwYLsG1lHAUcSEnA6nS77ePXtt3GePTc/o4BMKHBG7O+kJNZv3syofBIsgK5ALR8fvvjmG5d9AHzx1Vf0zifBguxlkAOcTr5YsaLAPpatWkUVi4Ve+bSZgFGGwdZduzh67FiB/YiIeJXVmjOrda4K4blZLVUhFHcqM0nWiRMncDgcVKtWLdfxatWqkZCQkO9zEhISinU+wIwZMwgPD895REVFXXrwInnYT58GwNUfzi7Lc15FcCo5Gfjn2vMKAXzJLkZRECeuX1eAqkBWZmaBfWRkZLiMA7JjNICsrCyX56SlpwNQuYA+AGypqS77KOz7xHy2/8K+T+x2e4GvyWVnzymwj9OnCTebcVV6pCJ+z4pIGXVeuffGgbE55d61hFDcqcwkWSXl0UcfJTk5Oedx+PBhb4ck5VCzRo0AcDX/sPLsf5vExJRIPKVBvx49MPHPtee1HjgNtGvZssB+QgID+dpFmx1YDURHRxfYxxX167MBcDWP/RUQ5OuLn5+fyz5ubNcOgFUu2s9dZ5cbbnDZR/WICCIqVXL5fXII+CMri6ZXXumyD4CmTZqwymIhv3k3A/jaYqFpkyYF93HllcRmZrLXRftKoFJwMFGqMigiZcXZZOv8WS178hnNaolblJkkq0qVKlgsFo4fP57r+PHjx6levXq+z6levXqxzgfw9/cnLCws10PE3a5u0oQ2TZrwfxYLeX+PHwOesljo2qED9QpJBsqT66+5hqCAAJ4lu6Lg+Wxk36fmC8x+5pkC+xnQpw/fAp/lOW4AU4BkYEY+93Ce74XHH+c08G+4IDH5BlgK3FLAfWEAwwYMINTfn4fJriZ4vqPAk0A1q7XAe6l8fHwYfdddvGM282uetkxgoslESFAQd/TuXWAs9wwbxl6Hg5fzaXsT2O5wMHbYsAL76N+jB1XCw3nAbOZMnrbfgDcsFkbceScBAQEF9iMiUuqoMIZ4QJlJsvz8/GjZsiVr1qzJOeZ0OlmzZg3tzv7FOK927drlOh/g22+/dXm+SEl699VXORYcTGOLhanAQrILJDS1WMiwWnnjhRe8HGHJW/b++5wCmgEPkv2aPAPEAFuBR+6/v8DZI8hOwmrXqEF/oD/wIfAW0A54CejdtWuBs0cArZo1Y2j//vyH7BLwc4EFwB1AD6Cq1cr7L+eXsvzDbDbz3uuvs+ds/E+dvZ7JQGPgL7OZT999t8A+AB6dMIFmTZtyvdnMaOBj4GWgucXCMrOZD2bPJiQ4uMA+rmvThkfGj+ch4GazmXfJLi5yi9nMOOC+f/2LLoVUbgwICODDuXNZY7HQzGJh5tlY7gHam800aNiQJx98sNDrEREplc5bQnhuVgt7Ort3a1ZLLk6Zqi74ySefMGzYMN566y3atGnDK6+8wqJFi9i9ezfVqlXjrrvuombNmsyYMQPILuF+ww038Nxzz9GjRw8WLlzIs88+y5YtW2jcuHGRvqaqC4onHTh0iOfnzOHDJUtIO32a8OBghg0axCPjxhFZwIxrefbz5s30GTWKE4mJZJH9l6Dg4GBmTp3K6MGDi9RHRkYGd913H1+uXEn62fuvLgsLY8Lo0UydNKnIsbw4dy4vzZlD4qlTAARaLHTt3JkFs2cXeVPjdRs2cM+jj7J33z4cZBfOaNK4Me/OnEnzIv4eSrfbefk//+Gt+fM5nJiIxWym18038/D48bS9+uoi9WEYBouWLePlN99k0++/A9CyUSPuv/tuhvTrV+SKgFu2b+f52bP57OuvyXI4iKxShdF33cWDd99NaEhIkfoQESnVkpLAZvtnby0iCAxEe2sJUPTqgmUqyQKYPXt2zmbEzZs357XXXqNt27YA3HjjjdSpU4f58+fnnL948WIef/zxnM2IX3jhBW1GLKWOw+EgLT2dkODgCrcBsSsZGRkcPHyYqMjIiy5j73Q6OZGURICf3yUt/U1NTSX99GmqWK0XPT4ZGRmcSEoiokqVIm1AnB/DMEhNSyPA3x9fX9+L6gP+KXJxKdsDZGVlYT99mpDgYJVsF5Hy6WyytcNeX+XeJUe5TbJKmpIsERERkQosLu6fWa2McALD/TWrVYGVu32yRERERERKnApjyEVQkiUiIiIiUhAVxpBiurgbA0REREREKhqrlUiSiLTF/rOEMDECm02FMSQ3zWSJiIiIiBTVebNajQNjc2a1tIRQzqckS0RERESkuM4mW40DY3OWENqTzxAXpyWEoiRLREREROTiqTCG5ENJloiIiIjIpVBhDMlDhS9ERERERNxBhTHkLM1kiYiIiIi4iwpjCEqyRERERETcT4UxKjQlWSIiIiIinqLCGBWSkiwREREREU9SYYwKR4UvRERERERKggpjVBiayRIRERERKSkqjFEhKMkSEbdLS0/n+F9/kZWVddF9ZGRkcPyvv7Db7W6M7OKk2Gz89fffOJ1Or8aRlZVF4okTpKaleTUOdylNYywiUuJUGKNcU5IlIm7z8+bN3HbXXYQ1bEj15s2p1rgxDz39NCdPnSpyHwmJidz72GNUadSI6s2bE3bFFQwYM4bfd+70XOAurFi9mut79SI8JoaIpk2Jvvpqnnn1Vc6cOVOicdhSU/m/GTOIbNqUas2aEdqwId0GDeL7jRtLNA53iU9IYNyjj3LZlVfmjPGgsWPZsXu3t0MTESl55xfGCE8AwGZTolXWmQzDMLwdRGmWkpJCeHg4ybt3ExYa6u1wREqt5d9+S9+RI4kB7nY4qAX8CLxtsVAzOpofvviCywpZbH4kPp7revYk7a+/GOtw0BqIBd6wWDjq48M3CxdyXZs2nr8YYPZ77zHh8cfpYDYzwumkEvAV8IHZzPXXXMPyDz/E39/f43Gk2Gx07NOHP//8k385HNwEJADzLBa2GQYLZs9mYK9eHo/DXQ4dPcp1t97K6b//ZqzDQStgH9ljfMzXl28/+YR2rVp5O0wRkZJ3NqvaQeOcQ7pHq/Sx2VKIiQknOTmZsLAwl+cpySqEkiyRwp0+fZpaLVpwrc3GEsPA97y2PUB7i4WBgwczd8aMAvvpP2oUm1atYuPZJO2cdKCb2czRGjXY+/PPmM2enYQ/dPQo9a65hnudTl4GTOe1rQO6mEy8OHUqD4we7dE4AB555hnmvvkm651Omp133AEMNZn40t+fo9u2lZnfT31GjGDLmjVsdDiIPO94GtDVbCaxZk12b9jg8TEWESl1lGSVCUVNsvQuJiKXbMmKFfydksLMPAkWwBXABIeD/y5aRFp6uss+EhITWfrNN0zOk2ABBAEvOJ3sP3qUb3/4wc3RX+jtjz4i2GRiOrkTLIAbgf7Am++95/E4MjMzeefDDxmTJ8ECsAAvGQb2M2dY8NlnHo/FHY4eO8ayb7/l//IkWADBwHNOJ3sPH+a7n37yRngiIqWDLQWbzdtByKVSkiUil+yPP/+kjq8vl7to7wyknj7N4fh4l338uX8/DqeTTi7a2wLBZjM7//zzEqMt3B9//sk1TichLto7GwZ74uJwOBwejeP4X3/xd0qKy9ckErjKYmHn3r0ejcNd9sTG4jQMl9dzLRBgNpeZ6xERcSurFWw2rPZ4Qu2JOdUGdW9W2aQkS0QuWXBgICedTjJctCee/W9QYKDrPoKCcp2bVwpw2jAK7MNdggMDSSxguVoi4O/r6/Elbeeu1dVr4gROUPDrWpoUNsangDNOZ5m5HhERtzu/tHvGEZV2L8OUZInIJevTvTvJDgeL8mkzgLfMZlo2akRUZN5FYv9oftVVRFevzlsu2t8FMJno2aXLpQdciD7du7PN4eCXfNoygHctFvrecgsmU97FhO5lrVyZG9u2ZZ7ZTH7F45cD8VlZ9O3e3aNxuEvLpk2JiohwOcZvAz4WCz06uZrrEhGpAM6Vdq91Kqe0O/Z0zWqVMUqyROSSXXXFFfS5+WbGmc0sIbsoA0AScB+wyunksUmTCkxKLBYL/zdxIh8Bj5M9cwWQCbwHPGo286+BA4msXt1zF3JWzy5daNqwIf0sFr4nO1EEOAwMMJk4ZDLx0D33eDwOgEfvv5+NhsEo/pkBcpKdYI2wWOjUrh1tWrQokVgulY+PD48+8AAfAFOBc7ccZADvAI+bTIy6806qR0R4LUYRkVLDas2Z1YrmECSf0hLCMkTVBQuh6oIiRZOalsagu+9mxXffEenjQySww+nEaTbz8lNPMW748EL7MAyDZ159lSdnziQQiDGbOQQkZmVxZ69evPvyyyVSNh2y93LqOWQIW3btop6PD+HAb1lZhAQFsWDuXG4tgRm1c95ftIixDz+MMyuLJhYLicDhrCw6XnMNn77zDpUrVSqxWC6VYRg8/fLLPD1rFkEmEzFmM3GGwV8OB0P69OGdWbPw8/PzdpgiIqVLUhLxiT4kYcVGCHaCiIhQ9UFvUAl3N1GSJVI8v27bxifLlpGSmkqDunUZdvvtRFSpUqw+jsTH8/7ixRw8coTLKldmcJ8+NLnySg9F7JrT6WTN+vV8+e23nDlzhhaNGzO4b19CQ1yVxPCcv5OS+O+nn7Jz715CgoLo16MH7Vu18viSRU85fPQo7y9eTNzRo1SxWhncpw+NY2K8HZaISOkWF0e8vTJJWEkkgsBACA1VslWSlGS5iZIsERERESk1kpLAZmNHchQ2Pyt2gggMhOhobwdWMWifLBERERGR8kaFMcoEJVkiIiIiImWNCmOUakqyRERERETKorOzWpERWbQL35Uzq5WYqETL23y8HYCIiIiIiFwCqxWsVhrHxf5TGCMxAptNhTG8RTNZIiIiIiLlwdlZrcaBsURkHMmZ1YqL83ZgFY+SLBERERGR8kKFMUoFJVkiIiIiIuWNCmN4lZIsEREREZHySIUxvEaFL0REREREyjMVxihxmskSEREREakIVBijxCjJEhERERGpKFQYo0QoyRIRERERqWhUGMOjlGSJiIiIiFREKozhMSp8ISIiIiJSkakwhttpJktERERERFQYw400k1UB2O12lqxYwY49ewgKDKR31640u+oqb4clpYzT6WTt+vV8t2EDhmFwbevWdOvYEYvFUqx+9uzbx5IVK0i22WhYrx4Db7uN0JAQD0UtIiIibnVuVispifjEVJKwYrOHEBcXpFmtYjAZhmF4O4jSLCUlhfDwcJJ37yYsNNTb4RTb8m+/ZdiECSTZbNTz9eWk08lJh4OeN93Eh3PnlslrEvfbHxdH72HD2L53LzV8fLAAR7KyaFC7Np/Pn89VV1xRaB+nT59m1IMPsmDpUsIsFqqazRzIzCQ4MJA3XniBwX37ev5CRERExH2SksBmI95embiM6tj9KhEYWLGXENpsKcTEhJOcnExYWJjL87RcsBzbtGULfUeO5LrUVPYCsZmZHHc4+Aj4/vvvGTB6NMqxJcVmo3P//pzev591wNGsLA5lZbERCDx6lM79+5N44kSh/Yx+6CE+XbaM/wDHHQ72ZWZyEOhltzP0vvtY+d13Hr0OERERcTMVxrhoSrLKsWdffZUrgCWGweVnj/kCdwDzHQ6++fFHNm3Z4r0ApVT4YMkSDh07xjcOBzcAprOPa4BVDgcpp07x1n//W2Aff8bG8uHnn/Oa08loIODs8SjgfaCDycS0mTM9eBUiIiLiMef21jpb7j2CRJV7L4SSrHIq3W5n+Zo13O1w4JtPey+glo8Pi778sqRDk1Jm0dKl9ADq5tNWDbjd6WTR558X2MeSFSsItVgYmk+bGRjndLJh61aOHjt26QGLiIiId6gwRpEpySqn0tLTcRoGNV20m4FIICU1tQSjktIoJTmZmgUsG61F9pLCAvtITaWK2Zwzg5VfH+fOExERkTLs3KxWrVM5s1rY0zWrlYeSrHLKWqkSl4WF8aOL9iTgd6eThvXqlWRYUgo1bNiQHy0WXKVZ31ssNLz8chet2a6oX5+4zExc/SHreyDA15daNWpcSqgiIiJSWlitObNa0RyC5FNaQngeJVnllMViYeSQIbxtsbAzT5sBTAGcZjPDBwzwQnRSmowZMoQdDgfv59P2BbDe4eDuYcMK7GNAz56EBgcz2WTCkaftEPCaxcKdffuqlLuIiEh5osIYLinJKscevfde6tSrx7UWC4+TPZuwGLjZbGYO8PJTTxFRpYp3gxSv69ShAyMHDeJfwDDga2AVMAbobzLRr3t3+nTvXmAfwUFBvPXiiywCrjebWQD8AEwHWlssBFWrxjOTJ3v2QkRERMQ7VBjjAtonqxBlfZ+sk6dOMeWll3h/4UJsdjsAra66iv+bOLHQD85ScTidTl575x1efestDp4tTlGzalXGjxzJv++5Bx+fou1b/u0PPzBt5kx+/N//AAj08+OOPn2Y/sgj1KhWzWPxi4iISClxdm+tHclR2Pys2AnK2VurPEhNTaFdu8L3yVKSVYiynmSdk263cyQ+nqDAQGpFRno7HCmlHA4HBw8fxjAM6kRFFTm5yuvY8eOk2GzUrFGDkOBgN0cpIiIipV5SEvGJPiRhxUYIBAZ5OyK3SEtLoUuXwpOsi/sEJWVOUGAgDevX93YYUspZLBbq16lzyf3UqFZNM1ciIiIVmdVKJElE2mKJt1cGAr0dkVvYKLji8jllJslKSkpiwoQJfPnll5jNZvr168err75KiIsb6ZOSkpg6dSqrVq3i0KFDVK1ald69ezNt2jTCw8NLOHoRERERkQrGas1OtpKSoIjJSWmXYiradjRlJskaPHgwx44d49tvvyUzM5MRI0YwZswYPvroo3zPj4+PJz4+npdeeolGjRoRFxfH2LFjiY+PZ8mSJSUcvYiIiIhIBWW1ejsC9/H1LdJpZeKerF27dtGoUSN+/fVXWrVqBcDKlSu55ZZbOHLkCJFFvMdo8eLFDBkyhLS0tCLfa1Je7skSEREREZFLk2KzER4TU+g9WWWihPvGjRupVKlSToIF0LlzZ8xmM5s2bSpyP+dejIISrDNnzpCSkpLrISIiIiIiUlRlIslKSEggIiIi1zEfHx+sVisJCQlF6uPEiRNMmzaNMWPGFHjejBkzCA8Pz3lERUVddNwiIiIiIlLxeDXJmjx5MiaTqcDH7t27L/nrpKSk0KNHDxo1asSTTz5Z4LmPPvooycnJOY/Dhw9f8tcXEREREZGKw6uFLx588EGGDx9e4Dn16tWjevXqJCYm5jqelZVFUlIS1atXL/D5NpuNbt26ERoayueff45vITer+fv74+/vX6T4RURERERE8vJqklW1alWqVq1a6Hnt2rXj1KlTbN68mZYtWwKwdu1anE4nbdu2dfm8lJQUunbtir+/P8uWLSMgIMBtsYuIiIiIiOSnTNyTdeWVV9KtWzdGjx7NL7/8wk8//cS9997LoEGDcioLHj16lJiYGH755RcgO8G6+eabSUtL45133iElJYWEhAQSEhJwOBzevBwRERERESnHysw+WQsWLODee++lU6dOOZsRv/baazntmZmZ7Nmzh/T0dAC2bNmSU3nw8ssvz9XXgQMHqFOnTonFLiIiIiIiFUeZ2CfLm7RPloiIiIiIQDnbJ0tERERERKSsUJIlIiIiIiLiRkqyRERERERE3EhJloiIiIiIiBspyZIyJT4hgW6DBxNYuzammjXxq1mT5l268NOvv5Z4LB9++il12rTBp2ZNzDVrElavHiMmTiQjI6NE48jMzOSN99+n2Y034hMVRXiDBoyYOJEdu3eXaBzukmKz8exrr1G/dWsstWoR0agRD0yZwuGjR4vch2EYfLx0Kdfeeit+tWsTVLcuff/1L698n4iIiEjFo+qChVB1wdLjQFwcTW+8kYyMDO4A2gIHgLcBG/DxW2/R/9ZbSySWfz/9NDPfeotoYCRQGVgBrASiatRg74YN+Pn5eTyOjIwMeg0bxrc//kgvoJNhkAjMt1g4bjaz7IMP6HL99R6Pw12STp6kY9++/LlvH3c4nbQBYoH3LBbMoaGs/fRTGsfEFNiHYRiMfeQR/rNgAZ3NZm5zOkkDPrRY2Ol08vZLL/GvQYNK4nJERESknClqdUElWYVQklV6xHTowLH9+1kPNDnveBLQEdjn64tt/37MZs9O0O6JjaXR9dfTH/gQ8D2v7TOgP3BHnz4smD3bo3EAPDd7NlOee46vDIPO5x0/DfQ1m/k5KIjDW7cSHBTk8VjcYcQDD7Dss8/4weHgqvOO/w3cZLFg1KvHb999h8lkctnHomXLGHjPPbwHDD/vuBO4B3jHbGbfhg3UiYryxCWIiIhIOaYS7lKuxB0+zN79+3mE3AkWgBV4FUjPzOSVefM8Hsukp57CAswhd4IF0BfoCXyxfLnH43A6ncx95x2G5kmwAAKAOU4np1JTWfjFFx6PxR2STp7k46VLeThPggVwGTDT4WD73r2s/+WXAvuZ88473Gg250qwIPuX3SwgxGTiPx9+6La4RURERPJSkiVlwjfff4+T7AQmPzcAQcCan37yeCzbd+2iHVDFRXsvIC0zk9TUVI/G8dfff3M4MdHla1IXaOrjw/9++82jcbjLH3/+yZnMTJfX0wkINJsLvZ7N27fT0+nMty0YuMnh4H/btl1KqCIiIiIFUpIlZUJQYCCQfe9Vfs4AmUCAv7/HY/H18SGlgPZzMXr6niw/X99cXy8v42xbSdwb5g6FXY8dyDSMQq/Hz9fXZR8ANpMJ/xL4PhEREZGKS0mWlAl9u3fHz2Rivov2T8hOssYOGeLxWHp07sw2YHs+bU7gPSDCavV4clO5UiWuadaM+WYz+d1YuR7Yn5VFj06dPBqHu7Ro3JhqlSu7HOOPAQfQ7cYbC+znli5d+K/FQlY+bYeAtYZBj855F1iKiIiIuI+SLCkTgoKC6NKpE/OA2ZDzAdoAVgMTgJpVq9Llhhs8HsuzjzxCgMVCX+D8IumpwHjgN+Dh8eM9HgfAwxMmsNbp5FGyZ3rO2QoMsVhoHhND5w4dSiSWS+Xn58fEe+7hLWAuucf4G2CSxUK/bt2oX6dOgf1MHDOGg4bBcODUeccPAH0sFiKsVgb37evu8EVERERyKMmSMmPpO+/QJCaGCUAtsu99agx0AXxCQtiwYkWJxBESEsKy//6Xw2YzVwLtgVuBasBbwNB+/Xhw7NgSiaVP9+68+MQTvGAyUdNi4TagrdnM1UBIdDTLPvjA49UW3enf99zD2LvuYjxQ12KhN9DEYqEb0LJ1a955+eVC+2jZtCkLZs9msY8PNc1megA3mkzUB45VqsTKhQsJDQnx6HWIiIhIxaYS7oVQCffS5+OlS5nx+uskJCYSGhLCiIEDmXzvvfj4+JRoHEknTzL52Wf5au1asrKyaFCvHi88/jjtWrYs0TgA9h04wLyPPuKPPXsIDgqib/fu9Onevczcj5XXlu3beefjjzl4+DCXVa7M4L596XL99cVKGI8dP87bH33Er9u24evnR7cbb+TOPn3KTDl7ERERKX20T5abKMkSERERERHQPlkiIiIiIiJeoSRLRERERETEjZRkiYiIiIiIuJGSLBERERERETdSkiUiIiIiIuJGSrJERERERETcSEmWiIiIiIiIGynJEhERERERcSMlWSIiIiIiIm6kJEtERERERMSNlGSJiIiIiIi4kZIsERERERERN1KSJSIiIiIi4kZKskRERERERNxISZaIiIiIiIgbKckSERERERFxIyVZIiIiIiIibqQkS0RERERExI2UZImIiIiIiLiRkiwRERERERE3UpIlIiIiIiLiRkqyRERERERE3EhJloiIiIiIiBspyRIREREREXEjJVkiIiIiIiJu5OPtAEo7wzAASElN9XIkIiIiIiLiTedygnM5gitKsgphs9kAiGrVysuRiIiIiIhIaWCz2QgPD3fZbjIKS8MqOKfTSXx8PKGhoZhMpgLPTUlJISoqisOHDxMWFlZCEUphNC6lk8aldNK4lE4al9JJ41I6aVxKp/IyLoZhYLPZiIyMxGx2feeVZrIKYTabqVWrVrGeExYWVqa/ecorjUvppHEpnTQupZPGpXTSuJROGpfSqTyMS0EzWOeo8IWIiIiIiIgbKckSERERERFxIyVZbuTv78/UqVPx9/f3dihyHo1L6aRxKZ00LqWTxqV00riUThqX0qmijYsKX4iIiIiIiLiRZrJERERERETcSEmWiIiIiIiIGynJEhERERERcSMlWSIiIiIiIm6kJOsSJSUlMXjwYMLCwqhUqRIjR44kNTW1SM81DIPu3btjMplYunSpZwOtYIo7LklJSUyYMIErrriCwMBAateuzX333UdycnIJRl3+zJkzhzp16hAQEEDbtm355ZdfCjx/8eLFxMTEEBAQQJMmTfjqq69KKNKKpTjjMm/ePDp06EDlypWpXLkynTt3LnQc5eIU9+flnIULF2Iymejdu7dnA6ygijsup06dYvz48dSoUQN/f38aNmyo32UeUNxxeeWVV3Le46Oiopg4cSKnT58uoWjLvx9++IGePXsSGRlZ5M+169at4+qrr8bf35/LL7+c+fPnezzOEmXIJenWrZvRrFkz4+effzZ+/PFH4/LLLzfuuOOOIj131qxZRvfu3Q3A+Pzzzz0baAVT3HHZvn270bdvX2PZsmXGvn37jDVr1hgNGjQw+vXrV4JRly8LFy40/Pz8jHfffdf4448/jNGjRxuVKlUyjh8/nu/5P/30k2GxWIwXXnjB2Llzp/H4448bvr6+xvbt20s48vKtuONy5513GnPmzDG2bt1q7Nq1yxg+fLgRHh5uHDlypIQjL9+KOy7nHDhwwKhZs6bRoUMHo1evXiUTbAVS3HE5c+aM0apVK+OWW24x1q9fbxw4cMBYt26dsW3bthKOvHwr7rgsWLDA8Pf3NxYsWGAcOHDA+Oabb4waNWoYEydOLOHIy6+vvvrKeOyxx4zPPvusSJ9r9+/fbwQFBRmTJk0ydu7cabz++uuGxWIxVq5cWTIBlwAlWZdg586dBmD8+uuvOce+/vprw2QyGUePHi3wuVu3bjVq1qxpHDt2TEmWm13KuJxv0aJFhp+fn5GZmemJMMu9Nm3aGOPHj8/5t8PhMCIjI40ZM2bke/6AAQOMHj165DrWtm1b4+677/ZonBVNccclr6ysLCM0NNR4//33PRVihXQx45KVlWW0b9/eePvtt41hw4YpyfKA4o7LG2+8YdSrV8/IyMgoqRArpOKOy/jx442bbrop17FJkyYZ1157rUfjrKiK8rn24YcfNq666qpcxwYOHGh07drVg5GVLC0XvAQbN26kUqVKtGrVKudY586dMZvNbNq0yeXz0tPTufPOO5kzZw7Vq1cviVArlIsdl7ySk5MJCwvDx8fHE2GWaxkZGWzevJnOnTvnHDObzXTu3JmNGzfm+5yNGzfmOh+ga9euLs+X4ruYcckrPT2dzMxMrFarp8KscC52XJ5++mkiIiIYOXJkSYRZ4VzMuCxbtox27doxfvx4qlWrRuPGjXn22WdxOBwlFXa5dzHj0r59ezZv3pyzpHD//v189dVX3HLLLSUSs1yoIrzn69PjJUhISCAiIiLXMR8fH6xWKwkJCS6fN3HiRNq3b0+vXr08HWKFdLHjcr4TJ04wbdo0xowZ44kQy70TJ07gcDioVq1aruPVqlVj9+7d+T4nISEh3/OLOmZSuIsZl7weeeQRIiMjL3hzlIt3MeOyfv163nnnHbZt21YCEVZMFzMu+/fvZ+3atQwePJivvvqKffv2MW7cODIzM5k6dWpJhF3uXcy43HnnnZw4cYLrrrsOwzDIyspi7Nix/N///V9JhCz5cPWen5KSgt1uJzAw0EuRuY9msvIxefJkTCZTgY+ifiDJa9myZaxdu5ZXXnnFvUFXAJ4cl/OlpKTQo0cPGjVqxJNPPnnpgYuUE8899xwLFy7k888/JyAgwNvhVFg2m42hQ4cyb948qlSp4u1w5DxOp5OIiAj+85//0LJlSwYOHMhjjz3Gm2++6e3QKrR169bx7LPPMnfuXLZs2cJnn33GihUrmDZtmrdDk3JMM1n5ePDBBxk+fHiB59SrV4/q1auTmJiY63hWVhZJSUkulwGuXbuW2NhYKlWqlOt4v3796NChA+vWrbuEyMs3T47LOTabjW7duhEaGsrnn3+Or6/vpYZdIVWpUgWLxcLx48dzHT9+/LjLMahevXqxzpfiu5hxOeell17iueeeY/Xq1TRt2tSTYVY4xR2X2NhYDh48SM+ePXOOOZ1OIHvWfs+ePdSvX9+zQVcAF/PzUqNGDXx9fbFYLDnHrrzyShISEsjIyMDPz8+jMVcEFzMuTzzxBEOHDmXUqFEANGnShLS0NMaMGcNjjz2G2aw5h5Lm6j0/LCysXMxigWay8lW1alViYmIKfPj5+dGuXTtOnTrF5s2bc567du1anE4nbdu2zbfvyZMn8/vvv7Nt27acB8DLL7/Me++9VxKXV2Z5clwgewbr5ptvxs/Pj2XLlukv9ZfAz8+Pli1bsmbNmpxjTqeTNWvW0K5du3yf065du1znA3z77bcuz5fiu5hxAXjhhReYNm0aK1euzHWvo7hHccclJiaG7du353ofue222+jYsSPbtm0jKiqqJMMvty7m5+Xaa69l3759OUkvwJ9//kmNGjWUYLnJxYxLenr6BYnUuUTYMAzPBSsuVYj3fG9X3ijrunXrZrRo0cLYtGmTsX79eqNBgwa5SoUfOXLEuOKKK4xNmza57ANVF3S74o5LcnKy0bZtW6NJkybGvn37jGPHjuU8srKyvHUZZdrChQsNf39/Y/78+cbOnTuNMWPGGJUqVTISEhIMwzCMoUOHGpMnT845/6effjJ8fHyMl156ydi1a5cxdepUlXD3gOKOy3PPPWf4+fkZS5YsyfVzYbPZvHUJ5VJxxyUvVRf0jOKOy6FDh4zQ0FDj3nvvNfbs2WMsX77ciIiIMKZPn+6tSyiXijsuU6dONUJDQ42PP/7Y2L9/v7Fq1Sqjfv36xoABA7x1CeWOzWYztm7damzdutUAjFmzZhlbt2414uLiDMMwjMmTJxtDhw7NOf9cCfd///vfxq5du4w5c+aohLvk9vfffxt33HGHERISYoSFhRkjRozI9eHjwIEDBmB89913LvtQkuV+xR2X7777zgDyfRw4cMA7F1EOvP7660bt2rUNPz8/o02bNsbPP/+c03bDDTcYw4YNy3X+okWLjIYNGxp+fn7GVVddZaxYsaKEI64YijMu0dHR+f5cTJ06teQDL+eK+/NyPiVZnlPccdmwYYPRtm1bw9/f36hXr57xzDPP6I91HlCcccnMzDSefPJJo379+kZAQIARFRVljBs3zjh58mTJB15OufocdW4chg0bZtxwww0XPKd58+aGn5+fUa9ePeO9994r8bg9yWQYmicVERERERFxF92TJSIiIiIi4kZKskRERERERNxISZaIiIiIiIgbKckSERERERFxIyVZIiIiIiIibqQkS0RERERExI2UZImIiIiIiLiRkiwRERERERE3UpIlIiIiIiLiRkqyRESkTBg+fDgmk+mCx759+9zS//z586lUqZJb+rpYP/zwAz179iQyMhKTycTSpUu9Go+IiFwcJVkiIlJmdOvWjWPHjuV61K1b19thXSAzM/OinpeWlkazZs2YM2eOmyMSEZGSpCRLRETKDH9/f6pXr57rYbFYAPjiiy+4+uqrCQgIoF69ejz11FNkZWXlPHfWrFk0adKE4OBgoqKiGDduHKmpqQCsW7eOESNGkJycnDND9uSTTwLkO6NUqVIl5s+fD8DBgwcxmUx88skn3HDDDQQEBLBgwQIA3n77ba688koCAgKIiYlh7ty5BV5f9+7dmT59On369HHDqyUiIt7i4+0ARERELtWPP/7IXXfdxWuvvUaHDh2IjY1lzJgxAEydOhUAs9nMa6+9Rt26ddm/fz/jxo3j4YcfZu7cubRv355XXnmFKVOmsGfPHgBCQkKKFcPkyZOZOXMmLVq0yEm0pkyZwuzZs2nRogVbt25l9OjRBAcHM2zYMPe+ACIiUqooyRIRkTJj+fLluZKf7t27s3jxYp566ikmT56ck7zUq1ePadOm8fDDD+ckWQ888EDO8+rUqcP06dMZO3Ysc+fOxc/Pj/DwcEwmE9WrV7+o2B544AH69u2b8++pU6cyc+bMnGN169Zl586dvPXWW0qyRETKOSVZIiJSZnTs2JE33ngj59/BwcEA/Pbbb/z0008888wzOW0Oh4PTp0+Tnp5OUFAQq1evZsaMGezevZuUlBSysrJytV+qVq1a5fx/WloasbGxjBw5ktGjR+ccz8rKIjw8/JK/loiIlG5KskREpMwIDg7m8ssvv+B4amoqTz31VK6ZpHMCAgI4ePAgt956K/fccw/PPPMMVquV9evXM3LkSDIyMgpMskwmE4Zh5DqWX2GLcwnfuXgA5s2bR9u2bXOdd+4eMhERKb+UZImISJl39dVXs2fPnnwTMIDNmzfjdDqZOXMmZnN2zadFixblOsfPzw+Hw3HBc6tWrcqxY8dy/r13717S09MLjKdatWpERkayf/9+Bg8eXNzLERGRMk5JloiIlHlTpkzh1ltvpXbt2vTv3x+z2cxvv/3Gjh07mD59OpdffjmZmZm8/vrr9OzZk59++ok333wzVx916tQhNTWVNWvW0KxZM4KCgggKCuKmm25i9uzZtGvXDofDwSOPPIKvr2+hMT311FPcd999hIeH061bN86cOcP//vc/Tp48yaRJk/J9Tmpqaq59vw4cOMC2bduwWq3Url370l4kEREpMSrhLiIiZV7Xrl1Zvnw5q1atonXr1lxzzTW8/PLLREdHA9CsWTNmzZrF888/T+PGjVmwYAEzZszI1Uf79u0ZO3YsAwcOpGrVqrzwwgsAzJw5k6ioKDp06MCdd97JQw89VKR7uEaNGsXbb7/Ne++9R5MmTbjhhhuYP39+gft6/e9//6NFixa0aNECgEmTJtGiRQumTJlysS+NiIh4gcnIu9BcRERERERELppmskRERERERNxISZaIiIiIiIgbKckSERERERFxIyVZIiIiIiIibqQkS0RERERExI2UZImIiIiIiLiRkiwRERERERE3UpIlIiIiIiLiRkqyRERERERE3EhJloiIiIiIiBspyRIREREREXGj/wcpTSVvA06yrwAAAABJRU5ErkJggg==", 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xyp47d46qVavi7OzMyJEjsbW1ZdWqVbRo0YK1a9fSsmVLIGnfP9G1bt2ac+fO8fnnn+Pi4sLDhw/ZtWsXt27divOX/pCQEGrVqsWVK1cYOHAghQsXZvXq1XTv3p3nz5/HSkbe5boKMHDgQLJmzcqECRO4dOkS8+bN4+bNm4aEDCJvHCdOnEi9evXo16+fodyxY8c4ePDgW/fm+Pbbb9FqtQwbNozAwEC+//57OnXqxNGjRw1lfvvtN/r06UOVKlX48ssvuXbtGs2aNSN79uwUKFDAUC4oKIhff/2VDh068Nlnn/HixQt+++03PD098fPzi/XIwuLFi3n9+jW9e/fG0tKSggUL0rJlS1auXMmPP/6ImZmZoeyff/6JUopOnTrFuS/h4eEcO3YsUV32Zs6cyeeff46dnZ3hxj3qezY4OJiaNWty9+5d+vTpQ8GCBTl06BCjRo3i3r17sZ6Fjrkf2bNnT9SxyJUrF/PmzaNfv360bNmSVq1aAfDhhx/GGXdy39dNmDCBadOm0atXLzw8PAgKCuL48eP8888/hkHl7t69S4kSJejWrVuyP+Po7++Pra0tYWFh5MmTh88++4xx48a9U++ko0ePcuXKFRYvXoyFhQWtWrVi2bJlRuMmAOzatYumTZuSL18+vvjiC/LmzcuFCxfYsmWL4TP+77//Ur16dczNzenduzcuLi5cvXqVzZs3M2XKlLeKL+Y9QNR1KLHfYRMnTmTChAlUqVKFSZMmYWFhwdGjR9mzZw8NGjSgS5cu/O9//2PHjh1G40/cv3+fPXv2MH78eAC6du3Kvn37UErFG+/JkycBjO5jIPL7QKvVcvLkyXhb4kJDQ7G2to613MbGhrCwMM6ePWv07HlS3hPly5dP+kBMKh0LDAxUgGrevHmiyp86dUoBqlevXkbLhw0bpgC1Z88ew7JChQopQO3fv9+w7OHDh8rS0lINHTrUsGzcuHEKUOvWrYv1enq9Ximl1N69exWgihQpooKDg43WFy1aVHl6ehrKKqVUcHCwKly4sKpfv75h2fTp0xWgrl+/bvQaN27cUGZmZmrKlClGy8+cOaOyZMkSa3lMixcvVoA6duyY+uWXX5S9vb0hxrZt26ratWsbjkeTJk2MtgXUgAED4q3flM6dO6scOXLEWn7s2DEFqMWLF8daV7NmTQWo+fPnx1oX/ZhG6dOnj7KxsVGvX782LOvWrZsqVKiQ4d/Xr19XgMqRI4d6+vSpYfnGjRsVoDZv3mxYNn78eBXz4wAoCwsLdeXKFcOy06dPK0D9/PPPhmVeXl7KxsZG3b1717Ds8uXLKkuWLLHqjCksLEzlzp1blS5dWoWEhBiWb9myRQFq3LhxRvsHqEmTJhnV8dFHHyl3d/d4X+fFixcqa9as6rPPPjNafv/+feXo6Gi0PLGvs2fPHgWoQYMGxXq96O93QGm1WnXu3DmjMpcuXVKAmjdvntHyZs2aKRcXl1ifL2dnZxUUFGQot2rVKgWoWbNmGZY1adLE6D0QZenSpUqr1SpfX1+j5fPnz1eAOnjwoFLqv2tI//79jcp17NhRAWr8+PGx6o5u5syZClCrVq0yLHv16pVyc3NTgNq7d69huan39bRp05RGo1E3b940LBswYECc76OYdYSFhanSpUurOnXqxBunTqdTDg4OasSIEUqpyPOVI0cO1bZtW2VmZqZevHihlFLqxx9/VFqtVj179sywbczjENe1K6psYj5DpkR9fk39RT+OUe/X+P6iX8fiqxdQhw8fjhWLhYWF6tevX7zxbtiwQQHq+++/NyyLiIhQ1atXj3Xdq1u3ripTpozR9Uuv16sqVaqookWLGpYl5vsnan+i6n/27JkC1PTp0+ONt2bNmqpmzZqGf0e9d729vQ3LwsLCVOXKlZWdnZ3hs5eU66opUd9J7u7uKiwszLD8+++/V4DauHGjUiry+9jCwkI1aNBA6XQ6Q7lffvlFAer33383LCtUqJDq1q1bgvsYdS0pUaKECg0NNSyfNWuWAtSZM2cM+507d25Vrlw5o3ILFy5UgFGdERERRmWUijwHefLkUT179jQsizpuDg4O6uHDh0bld+zYoQD1119/GS3/8MMPjV7LlCtXrsT5eerWrZuytbU1WlaqVCmTdU6ePFnZ2toqf39/o+UjR45UZmZm6tatWwnuR2KPxaNHj+K8nsb8Lk6J+7qyZcvGut+JKWo/Tb2v4rN69epY16joevbsqSZMmKDWrl2r/ve//6lmzZopQLVr1y5JrxPTwIEDVYECBQzXhZ07dypAnTx50lAmIiJCFS5cWBUqVMjomq6U8Xd2jRo1lL29vdH3UMwyMe+3osR1L2XqHkCpxH2HXb58WWm1WtWyZUuja0H0mHQ6ncqfP7/65JNPjNb/+OOPSqPRqGvXriml/rvXTMiAAQOUmZmZyXW5cuVS7du3j3f7MmXKqGLFiqmIiAjDstDQUFWwYEEFqDVr1hiWJ/U90bt3b2VtbZ3gPkSXrrtxRnWDtLe3T1T5bdu2ARh1QwIYOnQoQKxm15IlSxpamCDy1+gPPviAa9euGZatXbuWsmXLGn5pjS5mU3W3bt2MMvlTp05x+fJlOnbsyJMnT3j8+DGPHz/m1atX1K1bl/379yc4oMi6devQ6/W0a9fOsP3jx4/JmzcvRYsWjdVVJD7t2rUjJCSELVu28OLFC7Zs2ZLsXTghsoUuvr7McbG0tKRHjx6xlkc/pi9evODx48dUr16d4ODgRDXHf/LJJ0bxRJ3z6Oc5LvXq1cPV1dXw7w8//BAHBwfDtjqdjr///psWLVoYPUzr5uZmaEGNz/Hjx3n48CH9+/c36r/epEkTihcvbrKrQMxnIatXr57gvuzatYvnz5/ToUMHo/eRmZkZlSpVMvk+Suh11q5di0ajMfxiFl3Mz0bNmjUpWbKk0bJixYpRqVIlli1bZlj29OlT/vrrLzp16hSrjq5duxpdC9q0aUO+fPkMn/v4rF69mhIlSlC8eHGj/Y/q8x61/1F1DRo0yGj7xA74sm3bNvLly0ebNm0My2xsbOjdu3esstHf169eveLx48dUqVIFpZThV8WERK/j2bNnBAYGUr16df755594t9NqtVSpUoX9+/cDcOHCBZ48ecLIkSNRShkGGPD19aV06dLvNPBKQp+hhPTu3Ztdu3YZ/ZUtW9aojJWVVawyUX9JqXfXrl2x3qcA2bJlS7DlcNu2bWTJksWohcXMzIzPP//cqNzTp0/Zs2cP7dq1M1zPHj9+zJMnT/D09OTy5cuGLtxJ+f6JYm1tjYWFBT4+Pia7RcYXf968eenQoYNhmbm5OYMGDeLly5fs27fPqPy7XFch8vhH/9W6X79+ZMmSxfAZ/PvvvwkLC+PLL780evb9s88+w8HB4Z2e1e/Ro4fR82UxY4+6Lvft29eoXFQX3ejMzMwMZfR6PU+fPiUiIoIKFSqY/By2bt06Vq+PevXq4eTkZHQtPHv2LP/++2+Cz/E8efIE4K2+c6NbvXo11atXN7zXo/7q1auHTqczXCvi24+kHovESIn7uqxZs3Lu3DkuX74c5+u6uLiglEr2Vr3ffvuN8ePH06pVK7p06cLGjRv57LPPWLVqFUeOHHmrOiMiIli5ciWffPKJ4bpQp04dcufObfSeOnnyJNevX+fLL7+MdU2P2u7Ro0fs37+fnj17UrBgQZNl3oapewBI3HfYhg0b0Ov1jBs3LtY4GFExabVaOnXqxKZNm3jx4oVh/bJly6hSpQqFCxcGIrtyqwRa9SCyp0Ncz6BaWVklOAtA//798ff359NPP+X8+fOcPXuWrl27GroFR98+qe+JbNmyERISQnBwcIL7ESVdd+N0cHAAMDpx8bl58yZarRY3Nzej5Xnz5iVr1qzcvHnTaHnMNzJEHsToX5BXr16ldevWiXr9qDdTlKgLialuPFECAwPjvUhfvnwZpRRFixY1uT4pzf65cuWiXr16LF++nODgYHQ6ndFNaXJKzIcpJmdnZ5MfrnPnzjFmzBj27Nlj+AEgSmBgYIL1xjzPUcc7MTdCCb1HHj58SEhISKz3HGByWUxR78mYIzMBFC9ePNZ0GVHPxcUVT1yi3otxPdAb9VlLyutcvXoVJyenRD2rEPOzEaVr164MHDiQmzdvUqhQIVavXk14eDhdunSJVTbmZ0Cj0eDm5hbr+TBTLl++zIULF+LsWvvw4UPgv2tI9OQETJ8fU27evImbm1usL0VT29+6dYtx48axadOmWOcvMe9rgC1btvDNN99w6tQpo+dXEvOlXL16dSZMmEBISAi+vr7ky5eP8uXLU7ZsWXx9falfvz4HDhygXbt2iYolLom5zsanaNGiRs//mmJmZpZgmbepN4pSKsFjevPmTfLlyxfruamY5/7KlSsopRg7dixjx441WdfDhw9xdnZO0vdPFEtLS7777juGDh1Knjx5+Pjjj2natCldu3Ylb9688cZftGjRWDdTJUqUMKyP7l2uqxD782xnZ0e+fPkMn+e4ro0WFhYUKVIkVjxJkVDsUXXHjNHc3JwiRYrEqm/JkiXMmDGDixcvGj0zZOq6Z2pZ1I3qvHnzDAOTLVu2DCsrqwQH+4jyNt+50V2+fJl///03wWtklLiu6Uk5FomREvd1kyZNonnz5hQrVozSpUvTsGFDunTpEm9X0pQ0dOhQFi1axN9//23UtS+xdu7cyaNHj/Dw8DB69rR27dr8+eeffPfdd2i1Wq5evQpA6dKl46wrKimOr8zbiOv8J+Y77OrVq2i1WpPJYnRdu3blu+++Y/369XTt2pVLly5x4sQJ5s+fn+R4ra2tCQsLM7nu9evXJrtoRte3b19u377N9OnTDc89V6hQgREjRjBlypQEn6+N7z0R9VnPNKNxOjg44OTkxNmzZ5O0XWIPQPS+8dG97UUz5smParWbPn16nFMNJHTC9Xo9Go2Gv/76y2S8CW0fU8eOHfnss8+4f/8+jRo1SpGh0nPkyJGkX5SjmPrwPH/+nJo1a+Lg4MCkSZNwdXXFysqKf/75h6+++ipRUy28y3lO7vfIu4ornoREHaelS5eavOGLOfrZ275OXOK6MLZv357Bgwcbni3w9vamQoUKiU6uEkuv11OmTBl+/PFHk+ujP4OTGnQ6HfXr1+fp06d89dVXFC9eHFtbW+7evUv37t0T9b729fWlWbNm1KhRg7lz55IvXz7Mzc1ZvHhxnA/mR1etWjXCw8M5fPgwvr6+hl/Dq1evjq+vLxcvXuTRo0dGv5K/jfT2GXobz58/j/P5uKSKOrfDhg3D09PTZJnE/FAUny+//BIvLy82bNjAjh07GDt2LNOmTWPPnj3xPneYFOnpvMb1na/T6UzGmZyxe3t70717d1q0aMHw4cPJnTu3YVCVqJvr6OK6Fnbt2pXp06ezYcMGOnTowPLlyw0DbcQn6rnXt/nOjU6v11O/fn1GjBhhcn2xYsWM/m1qP5J6LJIiOe/ratSowdWrV9m4cSM7d+7k119/5aeffmL+/Pn06tXrneJ8G1HfP0+fPn2r7aNa7+L6YW7fvn1G02Alh/g+c6aYer+863dYTCVLlsTd3R1vb2+6du2Kt7c3FhYWb/WDZb58+dDpdDx8+JDcuXMbloeFhfHkyZNETZUxZcoUhg0bxrlz53B0dKRMmTKGZyhjfp5iiu898ezZM2xsbBJMOKNL18keQNOmTVm4cCGHDx+mcuXK8ZYtVKgQer2ey5cvG36NBHjw4AHPnz+nUKFCSX59V1fXJCeb0beFyKQ1oV+Q4/rguLq6opSicOHCCb45EqNly5b06dOHI0eOsHLlyneuz5TixYuzbNkyAgMDjb6o3qYLgI+PD0+ePGHdunVGg0Rcv349WWJ9V7lz58bKysrkSG6mlsUU9Z68dOlSrFa3S5cuvdV71pSo92Lu3LmT3AISX507duyINcBKUmTPnp0mTZqwbNkyOnXqxMGDB+OcFD1mlxulFFeuXDH6NTa+z9Hp06epW7duvO/DqGvI1atXjRLOS5cuJWp/ChUqxNmzZ2O1BMXc/syZM/j7+7NkyRK6du1qWG6q22Fc8a5duxYrKyt27NhhNE/m4sWLExWrh4cHFhYW+Pr64uvraxhVs0aNGixatIjdu3cb/h2f9DgdQXK6e/cuYWFhRt8pphQqVIjdu3fz8uVLox/hYp77qJYhc3PzBD+L7/r9M3ToUIYOHcrly5cpV64cM2bMwNvbO874//33X/R6vVHrXlRX+eS6FkW5fPmy0Q3oy5cvuXfvnmHuw+jXxuitaWFhYVy/ft3o2GXLls3kqKc3b9402RKXkKjXvnz5stF1OTw8nOvXrxt1I16zZg1FihRh3bp1Rp8FU93b41O6dGk++ugjli1bRv78+bl161aiJnAuWLAg1tbWif5OjO8a+fLly3f6fkjssUjKNSMl7usg8runR48e9OjRwzAI1YQJE9Ik2YtqTXub+UNfvXrFxo0b+eSTT0z21Bo0aBDLli2jdu3ahvuAs2fPxnmeoz4vCV134vvMJVZiv8NcXV3R6/WcP38+wTmau3btypAhQ7h37x7Lly+nSZMmb9XFOep1jh8/bjQf6/Hjx9Hr9YmeKzpbtmxG81v//fff5M+fn+LFi8e7XXzvievXryf4fRRTun5mD2DEiBHY2trSq1cvHjx4EGv91atXDUPGRp2QmDeLUb/mJ3ZEvehat27N6dOnY434BAn/Cuju7o6rqys//PCDyeFUHz16ZPh/W1tbgFgfnlatWmFmZsbEiRNjvZ5SytBfP7Hs7OyYN28eEyZMSLE5eSpXroxSihMnThgtj2sf4xP1K130fQ8LC2Pu3LnvHmgyiOo+tmHDBgICAgzLr1y5wl9//ZXg9hUqVCB37tzMnz/fqAvDX3/9xYULF97qPWuKp6cnDg4OTJ061eTQxNHfi4nVunVrlFKGyXGjS8ov5F26dOH8+fMMHz4cMzMz2rdvb7Lc//73P6Mu3WvWrOHevXtGz0ba2tqa7ALZrl077t69y6JFi2KtCwkJ4dWrVwCGumKOThtXAhpT48aNCQgIMBo6Ojg4mIULFxqVM/W+VkrFGv46ap8g9ufGzMwMjUZj9EvqjRs3jEYWjY+VlRUVK1bkzz//5NatW0YteyEhIcyePRtXV1eTU94kJr7MIuo6ltCI0I0bNyYiIoJ58+YZlul0ulg37Llz56ZWrVosWLDA5LDu0T+Lb/P9ExwczOvXr42Wubq6Ym9vb3IKkOjx379/3+hHwIiICH7++Wfs7OyoWbNmnNu+jYULFxpdi+bNm0dERIThM1ivXj0sLCyYPXu20b7+9ttvBAYGGl0bXV1dOXLkiFG3qy1btiRpeqLoKlSoQK5cuZg/f75RnX/88YfJzyEYn4+jR48mOLG2KV26dGHnzp3MnDmTHDlyJOq5b3NzcypUqGA03U18bG1tTX5W27Vrx+HDh9mxY0esdc+fPyciIiLBuhN7LKLmz03MNSMl7uti3jfZ2dnh5uZm9PlIytQLiRUUFBTrM6iU4ptvvgGIs6U/PuvXr+fVq1cMGDCANm3axPpr2rQpa9euJTQ0lPLly1O4cGFmzpwZ69hHnbNcuXJRo0YNfv/9d27dumWyDER+5gIDA/n3338Ny+7du2fyWhWXxH6HtWjRAq1Wy6RJk2L1eol5HezQoQMajYYvvviCa9euxXrmNbFTL9SpU4fs2bMbXc8h8jplY2Nj9L57/PgxFy9eTPAZupUrV3Ls2DGj55Df5j3xzz//JHqGgijpvmXP1dWV5cuX88knn1CiRAm6du1K6dKlCQsL49ChQ4ahoQHKli1Lt27dWLhwoaH7n5+fH0uWLKFFixZv1Yw9fPhwwySZPXv2xN3dnadPn7Jp0ybmz58fa6CA6LRaLb/++iuNGjWiVKlS9OjRA2dnZ+7evcvevXtxcHBg8+bNwH/De48ePZr27dtjbm6Ol5cXrq6ufPPNN4waNYobN27QokUL7O3tuX79OuvXr6d3794MGzYsSfsU3zOEMR0/ftzwpouuVq1aRr9WRFetWjVy5MjB33//bfSrqKurK1mzZmX+/PnY29tja2tLpUqV4u3LX6VKFbJly0a3bt0YNGgQGo2GpUuXpqsuYBMmTGDnzp1UrVqVfv36odPp+OWXXyhdunSCc3OZm5vz3Xff0aNHD2rWrEmHDh0MUy+4uLgwePDgZInRwcGBefPm0aVLF8qXL0/79u3JlSsXt27dYuvWrVStWpVffvklSXXWrl2bLl26MHv2bC5fvkzDhg3R6/X4+vpSu3ZtBg4cmKh6mjRpQo4cOVi9ejWNGjUy6jIRXfbs2alWrRo9evTgwYMHzJw5Ezc3Nz777DNDGXd3d1auXMmQIUOoWLEidnZ2eHl50aVLF1atWkXfvn3Zu3cvVatWRafTcfHiRVatWsWOHTuoUKEC5cqVo0OHDsydO5fAwECqVKnC7t27E9VKC5GDR/zyyy907dqVEydOkC9fPpYuXWq4uYlSvHhxXF1dGTZsGHfv3sXBwYG1a9ea7IoVdW0YNGgQnp6ehoS4SZMm/PjjjzRs2JCOHTvy8OFD5syZg5ubm9EXcHyqV6/Ot99+a+hiApHJyAcffMClS5dMzl0WV3wxr11RSWB69c8//5hs5XJ1dTXqRbJr1y4KFiyYYPdHLy8vqlatysiRI7lx4wYlS5Zk3bp1Jn98mDNnDtWqVaNMmTJ89tlnFClShAcPHnD48GHu3LnD6dOngbf7/vH396du3bq0a9eOkiVLkiVLFtavX8+DBw/i/CEFIgdMWbBgAd27d+fEiRO4uLiwZs0aQ2t7YgdKS6ywsDBDnJcuXWLu3LlUq1aNZs2aAZE3naNGjWLixIk0bNiQZs2aGcpVrFjR6CauV69erFmzhoYNG9KuXTuuXr2Kt7d3rGdvE8vc3JxvvvmGPn36UKdOHT755BOuX7/O4sWLY7UUNm3alHXr1tGyZUuaNGnC9evXmT9/PiVLlkzyPGodO3ZkxIgRrF+/nn79+iX6mfzmzZszevRogoKCYj1/HZO7uzvz5s3jm2++wc3Njdy5c1OnTh2GDx/Opk2baNq0qWGqglevXnHmzBnWrFnDjRs3EuzKnNhjYW1tTcmSJVm5ciXFihUje/bslC5d2uRzYilxX1eyZElq1aplmLPs+PHjrFmzxug7K6lTL0TdJ0XNW7t06VLDM/djxowBIq85HTp0oEOHDri5uRESEsL69es5ePAgvXv3pnz58kZ1ajQaatasiY+PT5yvu2zZMnLkyBHnzX+zZs1YtGgRW7dupVWrVsybNw8vLy/KlStHjx49yJcvHxcvXuTcuXOGRH/27NlUq1aN8uXL07t3bwoXLsyNGzfYunWr4Z6mffv2fPXVV7Rs2ZJBgwYZpnIqVqxYogfjSex3mJubG6NHj2by5MlUr16dVq1aYWlpybFjx3BycjKahzJqrt/Vq1eTNWvWWD8GJHbqBWtrayZPnsyAAQNo27Ytnp6e+Pr64u3tzZQpU4x6M/3yyy9MnDiRvXv3Guat3L9/P5MmTaJBgwbkyJGDI0eOsHjxYho2bGg0jU1S3xMnTpzg6dOnJucojleSxu5MQ/7+/uqzzz5TLi4uysLCQtnb26uqVauqn3/+2Wj46vDwcDVx4kRVuHBhZW5urgoUKKBGjRplVEYp01MNKBV7qGallHry5IkaOHCgcnZ2VhYWFip//vyqW7du6vHjx0qp/4ZzXr16tcnYT548qVq1aqVy5MihLC0tVaFChVS7du3U7t27jcpNnjxZOTs7K61Wq4gxlPnatWtVtWrVlK2trbK1tVXFixdXAwYMUJcuXYr3uEWfeiE+cU29ENff5MmT461v0KBBys3NLdbyjRs3qpIlSxqmJYgaLrxmzZqqVKlSJus6ePCg+vjjj5W1tbVycnJSI0aMMAxVHXMIdlNTL5gagpwYwz7HNVywqaknTA3zvXv3bvXRRx8pCwsL5erqqn799Vc1dOhQZWVlZXKfYlq5cqX66KOPlKWlpcqePbvq1KmTunPnjlEZU8NoxxV7XPbu3as8PT2Vo6OjsrKyUq6urqp79+7q+PHjb/U6ERERavr06ap48eLKwsJC5cqVSzVq1EidOHHCUCau4xhd//79FaCWL19uMmZA/fnnn2rUqFEqd+7cytraWjVp0iTW0NAvX75UHTt2VFmzZlWA0fshLCxMfffdd6pUqVLK0tJSZcuWTbm7u6uJEyeqwMBAQ7mQkBA1aNAglSNHDmVra6u8vLzU7du34xwqPKabN2+qZs2aKRsbG5UzZ071xRdfqO3bt8d6v54/f17Vq1dP2dnZqZw5c6rPPvvMMC1B9GH6IyIi1Oeff65y5cqlNBqN0Tn47bffVNGiRZWlpaUqXry4Wrx4cZLeD1u3blWAatSokdHyXr16KUD99ttvsbYxdRziunYl5TMUU3yf3+jier9GjzcpUy9Ej0un06l8+fKpMWPGxBtDlCdPnqguXbooBwcH5ejoqLp06aJOnjwZ65wqpdTVq1dV165dVd68eZW5ublydnZWTZs2NRqSO6rO+L5/Yk698PjxYzVgwABVvHhxZWtrqxwdHVWlSpWMpgNRyvR33YMHD1SPHj1Uzpw5lYWFhSpTpkysuJNyXTUl6jtp3759qnfv3ipbtmzKzs5OderUST158iRW+V9++UUVL15cmZubqzx58qh+/frFGjZeKaVmzJihnJ2dlaWlpapatao6fvx4nFMvxPyujnkMo8ydO1cVLlxYWVpaqgoVKqj9+/fHqlOv16upU6eqQoUKKUtLS/XRRx+pLVu2JOn7KLrGjRsrQB06dCjectE9ePBAZcmSRS1dutRouanPxv3791WTJk2Uvb29IsY0Ei9evFCjRo1Sbm5uysLCQuXMmVNVqVJF/fDDD4ZpMuLbj8QeC6WUOnTokHJ3d1cWFhZG7xtT16/kvq/75ptvlIeHh8qaNauytrZWxYsXV1OmTDGaCiSpUy/Ed02Jcu3aNdW2bVvl4uKirKyslI2NjXJ3d1fz5883mtZAqchzAcQ7xH/Uee/SpUucZYKDg5WNjY1q2bKlYdmBAwdU/fr1lb29vbK1tVUffvhhrKk7zp49q1q2bKmyZs2qrKys1AcffKDGjh1rVGbnzp2qdOnSysLCQn3wwQfK29s7SfdSSiXtO+z333833Cdly5ZN1axZU+3atStWuahpmXr37h1rXWKnXoiycOFC9cEHHxju7X766adY5yoq3ujf71euXFENGjRQOXPmNOzbtGnTYk1NkpT3hFJKffXVV6pgwYIm18VHo1Q6aiIRmca1a9coXrw4f/31F3Xr1k3rcNJEixYtEhzeWUQaPHgwv/32G/fv34/VCubj40Pt2rVZvXp1io0eK4QpGzZsoGPHjly9ejXB7qxCJIeWLVty5syZRPcmiPLpp5/i7++Pr69vCkUmUtO2bdto2rQpp0+fNvS6EImzceNGWrRowf79+995gLH0JDQ0FBcXF0aOHGnUOpgY6f6ZPZExFSlShE8//ZRvv/02rUNJFTHnXLl8+TLbtm0zNOmLuL1+/Rpvb29at24dK9ETIi199913DBw4UBI9kSru3bvH1q1bTU49k5Dx48dz7NgxDh48mAKRidS2d+9e2rdvL4neW1i0aBFFihSJ81GjjGrx4sWYm5vHmgM5MaRlT4hkkC9fPrp3726Y/2nevHmEhoZy8uTJOOdIfN89fPiQv//+mzVr1rBhwwb++ecfkyNcScueECIzu379OgcPHuTXX3/l2LFjXL16Nd45EYUQsa1YsYJ///2XadOmMWvWLAYNGpTWIaUb6X6AFiEygoYNG/Lnn39y//59LC0tqVy5MlOnTpVELx7nz5+nU6dO5M6dm9mzZyd6KGMhhMhM9u3bR48ePShYsCBLliyRRE+It9ChQwfs7Oz49NNP6d+/f1qHk65Iy54QQgghhBBCZELyzJ4QQgghhBBCZEKS7AkhhBBCCCFEJiTJnhBCZCATJkxAo9GkdRjUqlXrrUebrVWrlskJlIUQQgiRvCTZE0JkODdu3ECj0fDDDz+kdSgiBQUEBDBhwgROnTqV4q+1c+dOPv30U0qXLo2ZmRkuLi5JrmPTpk2UL18eKysrChYsyPjx44mIiIhV7vnz5/Tu3ZtcuXJha2tL7dq1+eeff2KVc3FxQaPRxPp7m6G3o7wv+5kc8cfl6tWrdOzYkdy5c2NtbU3RokUZPXp0rHK//PILJUqUwNLSEmdnZ4YMGcKrV6+MykRdy0z9rVix4p33VQghZDROIYQQSbZz584Uf42AgAAmTpyIi4tLio/Wunz5clauXEn58uVxcnJK8vZ//fUXLVq0oFatWvz888+cOXOGb775hocPHzJv3jxDOb1eT5MmTTh9+jTDhw8nZ86czJ07l1q1anHixIlYI/iWK1eOoUOHGi0rVqzY2+0k789+vmv8cTl16hS1atXC2dmZoUOHkiNHDm7dusXt27eNyn311Vd8//33tGnThi+++ILz58/z888/c+7cOXbs2BGr3g4dOtC4cWOjZZUrV363nRVCCAAlhBAZzPXr1xWgpk+fnqZx6PV6FRwcnKqvOX78eJXRL901a9ZUpUqVSrDcsWPHFKAWL16c4jHdvXtXhYWFKaWUatKkiSpUqFCSti9ZsqQqW7asCg8PNywbPXq00mg06sKFC4ZlK1euVIBavXq1YdnDhw9V1qxZVYcOHYzqLFSokGrSpMlb7E3c3pf9jEti4zdFp9Op0qVLq0qVKsX7uQ8ICFBZsmRRXbp0MVr+888/K0Bt2rTJsCy9XMuEEJmXdOMUQmRaoaGhjB8/Hjc3NywtLSlQoAAjRowgNDTUqNzixYupU6cOuXPnxtLSkpIlS5r8ld/FxYWmTZuyY8cOKlSogLW1NQsWLMDHxweNRsOqVauYMmUK+fPnx8rKirp163LlypVY9Rw9epSGDRvi6OiIjY0NNWvW5ODBg7HKHThwgIoVK2JlZYWrqysLFixI1H7Pnj0bMzMznj9/blg2Y8YMNBoNQ4YMMSzT6XTY29vz1VdfGZbp9XpmzpxJqVKlsLKyIk+ePPTp04dnz54ZvYapZ/Zu3rxJs2bNsLW1JXfu3AwePJgdO3ag0Wjw8fGJFef58+epXbs2NjY2ODs78/333xvW+fj4ULFiRQB69Ohh6Nr2xx9/AHD58mVat25N3rx5sbKyIn/+/LRv357AwEBDHY8fP+bixYsEBwcneMycnJwwNzdPsJwp58+f5/z58/Tu3ZssWf7rMNO/f3+UUqxZs8awbM2aNeTJk4dWrVoZluXKlYt27dqxcePGWO9NgLCwsFjd/97W+7Kf7xq/KTt37uTs2bOMHz8ea2trgoOD0el0scodPnyYiIgI2rdvb7Q86t9xdc989eoVYWFhSd0tIYSIlyR7QohMSa/X06xZM3744Qe8vLz4+eefadGiBT/99BOffPKJUdl58+ZRqFAhvv76a2bMmEGBAgXo378/c+bMiVXvpUuX6NChA/Xr12fWrFlG3Qu//fZb1q9fz7Bhwxg1ahRHjhyhU6dORtvv2bOHGjVqEBQUxPjx45k6dSrPnz+nTp06+Pn5GcqdOXOGBg0a8PDhQyZMmECPHj0YP34869evT3Dfq1evjl6v58CBA4Zlvr6+aLVafH19DctOnjzJy5cvqVGjhmFZnz59GD58OFWrVmXWrFn06NGDZcuW4enpSXh4eJyv+erVK+rUqcPff//NoEGDGD16NIcOHTJKJKN79uwZDRs2pGzZssyYMYPixYvz1Vdf8ddffwFQokQJJk2aBEDv3r1ZunQpS5cupUaNGoSFheHp6cmRI0f4/PPPmTNnDr179+batWtGCW7UM1PRj2tKOHnyJAAVKlQwWu7k5ET+/PkN66PKli9fHq3W+OvXw8OD4OBg/P39jZbv2bMHGxsb7OzscHFxYdasWSm0FwnL6PuZlPhN+fvvvwGwtLSkQoUK2NraYmNjQ/v27Xn69KmhXFQia21tbbS9jY0NACdOnIhV98SJE7Gzs8PKyoqKFSumSjdpIcR7Io1bFoUQIskS0/Vp6dKlSqvVKl9fX6Pl8+fPV4A6ePCgYZmpLlmenp6qSJEiRssKFSqkALV9+3aj5Xv37lWAKlGihAoNDTUsnzVrlgLUmTNnlFKR3T6LFi2qPD09lV6vN3r9woULq/r16xuWtWjRQllZWambN28alp0/f16ZmZkl2I1Tp9MpBwcHNWLECMPr5siRQ7Vt21aZmZmpFy9eKKWU+vHHH5VWq1XPnj1TSinl6+urALVs2TKj+rZv3x5rec2aNVXNmjUN/54xY4YC1IYNGwzLQkJCVPHixRWg9u7da7QtoP73v/8ZloWGhqq8efOq1q1bG5bF1Y3z5MmTsboImhLV5TX6aydGUrs3Tp8+XQHq1q1bsdZVrFhRffzxx4Z/29raqp49e8Yqt3Xr1ljvLS8vL/Xdd9+pDRs2qN9++01Vr15dAYbz+q7el/18m/hNadasmQJUjhw5VKdOndSaNWvU2LFjVZYsWVSVKlUMn+kTJ04oQE2ePNlo+6jPkZ2dnWHZzZs3VYMGDdS8efPUpk2b1MyZM1XBggWVVqtVW7ZsSYa9FkK876RlTwiRKa1evZoSJUpQvHhxHj9+bPirU6cOAHv37jWUjf4LfGBgII8fP6ZmzZpcu3bNqFsgQOHChfH09DT5mj169MDCwsLw7+rVqwNw7do1IHJwh8uXL9OxY0eePHliiOnVq1fUrVuX/fv3o9fr0el07NixgxYtWlCwYEFDfSVKlIjztaPTarVUqVKF/fv3A3DhwgWePHnCyJEjUUpx+PBhILK1r3Tp0mTNmtVwzBwdHalfv77RMXN3d8fOzs7omMW0fft2nJ2dadasmWGZlZUVn332mcnydnZ2dO7c2fBvCwsLPDw8DMcqPo6OjgDs2LEj3i6aEyZMQCn11lNEJFZISAgQ2eITk5WVlWF9VNm4ykWvCyJHjRwxYgTNmzenZ8+e7Nu3D09PT3788Ufu3LmT3LuRoIy+n0mJ35SXL18CULFiRby9vWndujWTJk1i8uTJHDp0iN27dwNQvnx5KlWqxHfffcfixYu5ceMGf/31F3369MHc3NzodQoWLMiOHTvo27cvXl5efPHFF5w8eZJcuXLFGrBGCCHehiR7QohM6fLly5w7d45cuXIZ/UWN8Pfw4UND2YMHD1KvXj1sbW3JmjUruXLl4uuvvwYwmezFJXpiBpAtWzYAw/Nuly9fBqBbt26x4vr1118JDQ0lMDCQR48eERISEmvEQoAPPvggUftfvXp1Tpw4QUhICL6+vuTLl4/y5ctTtmxZQ1fOAwcOGBLSqPgCAwPJnTt3rPhevnxpdMxiunnzJq6urrHmAHRzczNZPn/+/LHKZsuWLdazgaYULlyYIUOG8Ouvv5IzZ048PT2ZM2dOrHOVWqJ+LDD1HNrr16+NfkywtraOs1z0ukzRaDQMHjyYiIgIk89AprSMsp9Pnz7l/v37hr+o90VS4jclan2HDh2Mlnfs2BGAQ4cOGZatXbuWsmXL0rNnTwoXLoyXlxft2rXjo48+ws7OLt7XyZ49Oz169ODSpUtpktQLITIXmXpBCJEp6fV6ypQpw48//mhyfYECBYDIObPq1q1L8eLF+fHHHylQoAAWFhZs27aNn376Cb1eb7RdfDeEZmZmJpcrpQwxAUyfPj3OqQTs7OxM3owmVbVq1QgPD+fw4cP4+voakrrq1avj6+vLxYsXefTokVGyp9fryZ07N8uWLTNZZ65cud45rigJHauEzJgxg+7du7Nx40Z27tzJoEGDmDZtGkeOHCF//vzJFmdi5MuXD4B79+4Z3ldR7t27h4eHh1HZe/fuxaojallC0yFE1R/9GbHUklH2s1WrVuzbt8/w727duvHHH38kKX5TomLOkyeP0fLcuXMDGP1Q4ezszIEDB7h8+TL379+naNGi5M2bFycnp0RNKRF9/1P7/SyEyFwk2RNCZEqurq6cPn2aunXrxmpBim7z5s2EhoayadMmo5a5+LosvktMAA4ODtSrVy/Ocrly5cLa2trQEhjdpUuXEvVaHh4eWFhY4Ovri6+vL8OHDwegRo0aLFq0yNDlLPrgLK6urvz9999UrVo1wVaOmAoVKsT58+dRShkdb1OjkSZWfOcNoEyZMpQpU4YxY8Zw6NAhqlatyvz58/nmm2/e+jXfRlTifvz4caOEISAggDt37tC7d2+jsr6+vuj1eqPBS44ePYqNjU2CiUBUN9fkTLwTK6Ps54wZM4wSr6gkLSnxm+Lu7s6iRYu4e/eu0fKAgIA4Yy1atKihhf78+fPcu3eP7t27J7gPaXmehRCZi3TjFEJkSu3atePu3bssWrQo1rqQkBDDEO9RLUzRW5QCAwNZvHhxssfk7u6Oq6srP/zwg+H5n+gePXpkiMnT05MNGzZw69Ytw/oLFy6YnJDZlKhR/f78809u3bpl1LIXEhLC7NmzcXV1NbR2QOQx0+l0TJ48OVZ9ERERRiNdxuTp6cndu3fZtGmTYdnr169NHv/EsrW1BYj1ukFBQURERBgtK1OmDFqt1qhVNClTLyRWeHg4Fy9eNGq1KlWqFMWLF2fhwoVGQ/HPmzcPjUZDmzZtDMvatGnDgwcPWLdunVGcq1evxsvLy/A82dOnT2MN6x8eHs63336LhYUFtWvXTrZ9MiUj76e7uzv16tUz/JUsWTLJ8QcGBnLx4kWjrsHNmzfH0tKSxYsXG7X4//rrrwDUr18/zpj0ej0jRozAxsaGvn37GpZHfeaju3v3Lr///jsffvih0edTCCHehrTsCSEyrN27dxueAYquRYsWdOnShVWrVtG3b1/27t1L1apV0el0XLx4kVWrVhnmymvQoAEWFhZ4eXnRp08fXr58yaJFi8idO7fJbmjvQqvV8uuvv9KoUSNKlSpFjx49cHZ25u7du+zduxcHBwc2b94MRA7Fvn37dqpXr07//v2JiIjg559/plSpUvz777+Jer3q1avz7bff4ujoSJkyZYDILmcffPABly5ditXCULNmTfr06cO0adM4deoUDRo0wNzcnMuXL7N69WpmzZpldEMcXZ8+ffjll1/o0KEDX3zxBfny5WPZsmWGATkSaqUzxdXVlaxZszJ//nzs7e2xtbWlUqVKnD59moEDB9K2bVuKFStGREQES5cuxczMjNatWxu2/+WXX5g4cSJ79+5NcJCWf//915CoXrlyhcDAQEMLYdmyZfHy8gIib8RLlChh6BoYZfr06TRr1owGDRrQvn17zp49yy+//EKvXr0oUaKEoVybNm34+OOP6dGjB+fPnydnzpzMnTsXnU7HxIkTDeU2bdrEN998Q5s2bShcuDBPnz5l+fLlnD17lqlTp5I3b15D2Rs3blC4cOFYMb3P+xmXxMa/fv16evToweLFiw2fk7x58zJ69GjGjRtHw4YNadGiBadPn2bRokV06NDBMC8kwBdffMHr168pV64c4eHhLF++HD8/P5YsWWLUg2DEiBGGruROTk7cuHGDBQsW8OrVqzSdZkMIkYmk5VCgQgjxNqKmXojrb+nSpUoppcLCwtR3332nSpUqpSwtLVW2bNmUu7u7mjhxogoMDDTUt2nTJvXhhx8qKysr5eLior777jv1+++/K0Bdv37dUK5QoUKqSZMmseKJmnoh5lQAUXGamjqgVatWKkeOHMrS0lIVKlRItWvXTu3evduo3L59+5S7u7uysLBQRYoUUfPnzzdMJ5AYUcPcN2rUyGh5r169FKB+++03k9stXLhQubu7K2tra2Vvb6/KlCmjRowYoQICAgxlYk69oJRS165dU02aNFHW1tYqV65caujQoWrt2rUKUEeOHDHatlSpUrFet1u3brGmAti4caMqWbKkypIli+FYXrt2TfXs2VO5uroqKysrlT17dlW7dm31999/G22blKkXFi9eHOf7qVu3boZyUec0+rIo69evV+XKlVOWlpYqf/78asyYMSosLCxWuadPn6pPP/1U5ciRQ9nY2KiaNWuqY8eOGZU5fvy48vLyUs7OzsrCwkLZ2dmpatWqqVWrVsWq78yZMwpQI0eOlP1MhMTEH3WcYn529Xq9+vnnn1WxYsWUubm5KlCgQJzbly1bVtna2ip7e3tVt25dtWfPnlixLF++XNWoUUPlypVLZcmSReXMmVO1bNlSnThx4p32UQghomiUSuTT8EIIIUQSzZw5k8GDB3Pnzh2cnZ3TOpxMae7cuYYWopiDh2Qm78t+CiFEcpJn9oQQQiSLmPOUvX79mgULFlC0aFFJ9FLQ3r17GTRoUKZPgN6X/RRCiOQkLXtCCCGSRaNGjShYsCDlypUjMDAQb29vzp07x7JlywxzkQkhhBAi9cgALUIIIZKFp6cnv/76K8uWLUOn01GyZElWrFjBJ598ktahCSGEEO8ladkTQgghhBBCiExIntkTQgghhBBCiExIkj0hhBBCCCGEyITkmb0E6PV6AgICsLe3f6tJgYUQQgghhBCZg1KKFy9e4OTkhFab/tvNJNlLQEBAAAUKFEjrMIQQQgghhBDpxO3bt8mfP39ah5EgSfYSYG9vD8Dt33/HwcYmjaNJISdOAPDNlfbg5gaAu3taBiSEEEIIIUT6ExwcRM+eBQw5QnonyV4CorpuOtjYZN5kz9Iy8j/mdmDpAEBm3VUhhBBCCCHeVUZ5vCv9dzQVQgghhBBCCJFkkuwJIYQQQgghRCYkyZ4QQgghhBBCZELyzJ4QQgghhBDpgkKrjUCj0ZFBHgnLVJQCpczQ67MAmeMESLInhBBCCCFEGtNqw3BwuIe1dbAkemlIKQgJsSEoKB96vUVah/POJNkTQgghhBAiTenJmfM6dnZmZMvmRJYsFmSWlqWMRREREcazZ4+wsLjOw4dFyehPvUmyJ4QQQgghRBoyMwsjSxY9OXMWwNJS5r9KSxYW1piZmfP69U3MzMLQ6azSOqR3krFTVSGEEEIIITK4qG6bGk3y3JprNKDVIt1B31LUecgMx09a9oQQQgghhMjgNBowNwdLs3DMLM0Ny3Wh4YTqzAkPj3weTbxfJNkTQgghhBAiA8uSBWytIiL/sXYdrFkDz55Btmxo27TBunVrrC3g1essRESkbawidUmyJ4QQQgghRAaVJQvY2uhh+040PXvCgwdG6zVr1kCePKjff8e2YUNeBWvTJOHLlk2Dt/d6mjRpkfov/h6TZ/aEEEIIIYTIgDSaNy1627ejadYsVqJn8OBB5Prt27G1ikj2Z9EePLjPiBGfU65cEfLksaRUqQK0b+/Fvn27k/eF3pJSiqlTx1G8eD7y5bOmRYt6XL16Oa3DShWS7AkhhBBCCJEBmb95NE/TsyfodPEX1unQfPqp0XbJ4datG9Su7Y6v7x4mTZrOwYNnWLNmO9Wr12b48AHJ90LvYNas71mwYDY//jifXbuOYmNjS+vWnrx+/TqtQ0txkuwJIYQQQgiRAVmahcPatXG36MV0/z6sWxe5XTIZOrQ/Go2Gv//2o1mz1ri5FaNEiVIMGDCEXbuOxLnd+PFfUaFCMZycbChXrghTpowlPPy/uM6cOY2XV20KFLCnYEEHatVy5+TJ4wDcunWT9u29cHHJhrOzLZUrl2Lnzm0mX0cpxfz5Mxk2bAyNGzendOkPmTfvf9y/H8DWrRuS7TikV/LMnhBCCCGEEOlQ1qwJlTCPHIwlCTRr1mDWrh1ZLU2vf/488XU9e/aU3bu3M2bMFGxtbWOtd3TMGue29vb2zJnzB/nyOXHu3Bm+/PIz7Ozs+eKLEQD07t2JDz/8iBkz5mFmZsaZM6fIkiWySXL48AGEh4exdet+bG1tuXjxPLa2diZf5+bN6zx4cJ9atepFi8sRd/dKHDt2mNat2yd+hzMgSfaEEEIIIYTIqJ49S9ny8bh27QpKKYoVK57kbYcNG2P4/4IFXbhyZRjr1q0wJHt3795i0KDhhrpdXYsayt+5c4tmzVpTqlQZAFxcisT5Og8e3AcgV648Rstz587Dw4f3kxx3RiPJnhBCCCGEEOlQfK1sGg04OgLZsiWt0jflAwPffd499Q4VrFu3kgULZnPjxlVevXpJREQE9vYOhvX9+w9h0KBerFy5lJo169GiRVsKF3YFoE+fQQwd2o89e3ZSq1Y9vLxaU7r0h++2M5mUPLMnhBBCCCFEBqNU5ITpqk2bpG3Xpk3kdskwwbqra1E0Gg3+/heTtJ2f32F69+5E/fqNWbFiC/v2nWTo0NGEhYUZyowcOYHDh8/RoEETfH338PHHJdmyZT0AXbv24uTJa3zySRfOnz9DnToVWLjwZ5OvlSdPXgAePTJ+rvHhwwfkzp03SXFnRJLsCSGEEEIIkQGF6syhdWvIkyfhwgB580KrVpHbJYNs2bJTp44nv/02h1evXsVaHxj43OR2fn6HKFCgEMOGjeajjyrg6lqU27dvxirn5laM/v0Hs27dTpo2bcWyZYsN6/LnL0DPnn1ZunQdAwYMZcmSRSZfq1ChwuTJk9doGoigoCBOnDhKxYqVk7jHGY8ke0IIIYQQQmRAUYNXqt9/BzOz+AubmaF++81ou+Twww9z0Ol01KvnwaZNa7l69TKXLl1gwYLZNGhgOpkqUqQod+7cYu3aFVy/fpUFC2YbWu0AQkJCGD58IAcO+HDr1k2OHDnIyZPHKFasBACjRn3J7t07uHnzOqdP/8OBA3v54IMSJl9Lo9HQt++X/PDDN2zbtolz587Qr19X8uZ1ei8meJdn9oQQQgghhMiAlIJXr7Ng27AhatOmyHn07psYdCRv3shEr2FDXgVrk6ULZxQXlyL4+PzDjBlTGDNmKA8e3CNnzlyULevOjBnzTG7TuHEz+vUbzIgRAwkLC6V+/SYMHz6Wb7+dAICZmRlPnz6hb9+uPHr0gBw5ctK0aStGjZoIgE6nY/jwAQQE3MHe3oG6dRsydepPccb4xRcjCA5+xeDBvQkMfM7HH1djzZrtWFlZJd+BSKc06l2erHwPBAUF4ejoSOCKFTjY2KR1OCnDzw+Asf5doFgxADw80jIgIYQQQoj3R5Ysr8md+zoFChTGwiLpCUiWLGBrFRH5j3Xr0KxZEznqZrZskc/0tWoFRCaGERHJGXnmFBb2mtu3r/PwYWEiIozPR3BwEO3bOxIYGIiDg0McNaQf0rInhBBCCCFEBhYRAUGvsmBuDpbNW2LWrp1hnT40nNCwLEQb+0S8RyTZE0IIIYRIgFKKGzf+JSjoMblyFcTJqWjCG6VjOp2Oq1dPEBLyEmfnYuTMmf+t6rl715/Hj2/j4JALF5cyaDSaZI5UJJZSEBYGYZijeR05NYNSoFTyDMYiMqYMlezt37+f6dOnc+LECe7du8f69etp0aJFvNv4+PgwZMgQzp07R4ECBRgzZgzdu3dPlXiFEEIIkfEdO7aFxYtHcefOWcOyDz6oRu/eP1K0aMU0jOzt7NixiD///IanT2+9WaLB3b0JffrMIm/euCenju7ixSP8+utQ/P0PGZYVKPAhPXt+i7t7oxSIWiRFZJKX1lGI9CBDjcb56tUrypYty5w5cxJV/vr16zRp0oTatWtz6tQpvvzyS3r16sWOHTtSOFIhhBBCZAYHDqxm8uRm3L3rBOwArgKruXw5mJEja+Hv75fGESbNmjXfMmdOb54+rQ4cAK4Aizh58hzDhlXl0aNbCdQAFy8e5uuva3PlShiwhshj8hd37uRi0qSmHDmyISV3QQiRBBmqZa9Ro0Y0apT4X4vmz59P4cKFmTFjBgAlSpTgwIED/PTTT3h6eqZUmEIIIYTIBCIiwpk/fxDQCqVW8d9v5EXQ65sA1Vm0aCjTp/umXZBJ8OzZfby9xwFfAd9GW+OKXu/Fy5cf8eefExk06Ld461mw4Et0ug9Rah8QNXhFEZSqD7Ri3rzPqVixKWZmGeo2U4hMKUO17CXV4cOHqVevntEyT09PDh8+nEYRCSGEECKjOHHiL4KC7gMTiH3LZI1eP5JLlw5w586l1A/uLfj4eKNUFmCkibW50esH4OOznNDQ4DjruHnzLFev+qHU1/yX6EUxA8bz7NkdTp3alXyBCyHeWqZO9u7fv0+ePHmMluXJk4egoCBCQkJMbhMaGkpQUJDR33vB39/wH39/w2wMQgghxHvr0aObaDSWQOk4SlQwlMsIHj68iVbrBmSNo0QFIiJeExj4KM46/uvmWSGOEh8BGh4+zBjHJLPSaECrjfyveL9l6mTvbUybNg1HR0fDX4ECBdI6pJTn4QHFiuERsJ5iAXsh4C4+PpLwCSGEeL85OORCqVAgrufYrhjKZQQODjlR6jbwOo4SV9BotNjZZYu3jkiX4yhxHVDRyonUotGAhQVYW4OjIzg4RP7X2jpyuSR+76dMnezlzZuXBw8eGC178OABDg4OWFtbm9xm1KhRBAYGGv5u376dGqGmPQ8PvEaUZLLTfDrjTS324uMD3t6S9AkhhHg/VazYFEtLe2CGibV6NJoZODmVpEiRcqkc2dupWbMjev1zwNQzeSFotb9QsWIzbGzinijaza0CefIUJfKYmBru8QesrbNSoULjZIlZJE6WLGBrG5nUbdgAbdtCvXqR/92wIXK5rW1kOfF+ydTJXuXKldm9e7fRsl27dlG5cuU4t7G0tMTBwcHo773SuTNetV4y2Wk+tfivlc/bO60DE0IIIVKXtbUdHTqMBWYDXwJRPwCfB9qj1Ha6d5+aYeaWc3IqSv36vdBovgSmAk+ITNgOo9E0wszsBh06jIu3Dq1WS48e04AtQEfg4ps1t4CBwDw6dhyPpaVNSu2GiCFLFrCxgZ07IX9+aN8e1qyB3bsj/9u+feTynTsjy6VVwpctm4atWzekzYu/xzJUsvfy5UtOnTrFqVOngMipFU6dOsWtW5HdK0aNGkXXrl0N5fv27cu1a9cYMWIEFy9eZO7cuaxatYrBgwenRfgZh4cHdO5s1MpHwF1p5RNCCPHeadlyGN27f4+l5e9AQTQaa6AU9vb7GTbsTz7+uHlah5gk/fvPo2nTAZiZTQRyvdmfKuTMeYeJE7fj6vpRgnVUqdKaIUO8sbPbDZR4U0chLC2X8umnP9Ks2RcpvBciikYDVlawfTs0awYxOrQZPHgQuX779sjyyf37xIMH9xkx4nPKlStCnjyWlCpVgPbtvdi3b3fCG6eCzZvX0apVA4oUyUG2bBrOnDmV1iGlGo1SGWfKRR8fH2rXrh1rebdu3fjjjz/o3r07N27cwMfHx2ibwYMHc/78efLnz8/YsWOTNKl6UFAQjo6OBK5YgYPNe/grlZ8f+PuzOaA83nQmAGecnKBYscicUAghhHgfBAe/4NixzQQGPiJ37kK4uzfG3NwircN6a4GBjzh2bAshIS/In78EZcvWRatNWhtAeHgox49v49GjWzg65qZSpWZYWdmmUMSZW5Ysr8md+zoFChTGwiLmKKdxs7CI/MufP+5EL7q8eeH2bQgLi/xLDrdu3aBhw6o4OmZl1KhJlCxZhvDwcPbs2cGSJQvx84ts/c2WTYO393qaNGmRPC+cBCtWLOXWrevkzevEF198xv79JylTplyc5cPCXnP79nUePixMRITx+QgODqJ9e0cCAwMzRA/ADJXspYX3PtmL4ufHZh87/PDAn2IE4EytWpLwCSGEEEK8q7dN9qytI5/Ja98+8a+1ciU0bw5xDEyfZG3bNub8+X/x87uEra1xsh8Y+BxHx6xA7GRv/Piv2Lp1PQEBd8idOy9t23ZixIhxmJubA3DmzGm+/vpLTp06jkajoUiRovz00wI++qgCt27dZMSIgRw5coDw8DAKFnRh4sTpNGgQ/7Oit27doGzZwu9VsiePaYrE8fDAywO8vOezOaA8fnjg41Mbf39p5RNCCCGESAlZsyZcZs2apNW5Zg20aweWlqbXP3+e+LqePXvK7t3bGTNmSqxEDzAkeqbY29szZ84f5MvnxLlzZ/jyy8+ws7Pniy9GANC7dyc+/PAjZsyYh5mZGWfOnCJLlshEcPjwAYSHh7F1635sbW25ePE8trZ2iQ/8PSLJnkiazp3x8vPDy38+YwPAP6AYPgHO+PtD585pHZwQQgghxPvl2bOULR+fa9euoJSiWLHiSd522LAxhv8vWNCFK1eGsW7dCkOyd/fuLQYNGm6o29W1qKH8nTu3aNasNaVKlQHAxaXIu+xGpibJnkg6Dw/w8GBytFY+/4BieHs7SyufEEIIIUQyia+VTaOJnEcvW9zTIpoUVT4wEN71Ya53eRps3bqVLFgwmxs3rvLq1UsiIiKwt/+vW2T//kMYNKgXK1cupWbNerRo0ZbChV0B6NNnEEOH9mPPnp3UqlUPL6/WlC794bvtTCaVoUbjFOlMtGkaOuNtNE2DjNophBBCCJFylILQUGjTJmnbtWkTuV1yjNrh6loUjUaDv//FhAtH4+d3mN69O1G/fmNWrNjCvn0nGTp0NGHRRo0ZOXIChw+fo0GDJvj67uHjj0uyZct6ALp27cXJk9f45JMunD9/hjp1KrBw4c/vvkOZkCR74t28mabBq9ZLo2kafHwk4RNCCCGESEk6HbRuDXnyJK583rzQqlXkdskhW7bs1KnjyW+/zeHVq1ex1gcGPje5nZ/fIQoUKMSwYaP56KMKuLoW5fbtm7HKubkVo3//waxbt5OmTVuxbNliw7r8+QvQs2dfli5dx4ABQ1myZFHy7FQmI8meSB4eHniNKGk0N5+08gkhhBBCpJzw8Mj//v47mJnFX9bMDH77zXi75PDDD3PQ6XTUq+fBpk1ruXr1MpcuXWDBgtk0aFDZ5DZFihTlzp1brF27guvXr7JgwWxDqx1ASEgIw4cP5MABH27dusmRIwc5efIYxYqVAGDUqC/ZvXsHN29e5/TpfzhwYC8ffFAizhifPXvKmTOnuHjxPACXL1/izJlTPHhwP/kORDolyZ5IXtG6dkZv5fP2TuvAhBBCCCEyF6Xg9Wto2BA2bYpsuTMlb97I9Q0bRpZPzonXXFyK4OPzD9Wq1WbMmKFUqVKaVq3qs2/fbmbMmGdym8aNm9Gv32BGjBhIjRrlOHr0EMOHjzWsNzMz4+nTJ/Tt25WKFYvRs2c76tVrxKhREwHQ6XQMHz6ASpVK0KZNQ1xdi/HDD3PjjPGvvzZRo8ZHfPJJEwA+/bQ9NWp8xOLF85PvQKRTMs9eAmSevXfg7f3fAC4UAycZwEUIIYQQIqa3nWfvv+3B6s1m69ZFTq/w7FnkYCxt2kR23YTIRC8iIhkDz6Rknj0hEiPaNA2bA8rjHdDZME2DJH1CCCGEEMkjIgJevQJz88gJ09u1+29daCiEhUX+ifePJHsiZb2ZpsHLzw98vA3TNPgEOBtWCyGEEEKId6PUfwnd69eRUzMolbxdNkXGI8meSB0eHnh5gFe0ufl8fGpLK58QQgghRDKTJE9EkQFaROqSAVyEEEIIIYRIFZLsidT3Zm6+6NM0EHBXpmkQQgghxHspqhVOxk1MH6LOQ2Y4HZLsibQTrZWvM95GrXyS9AkhhBDifaHXm6PXQ1hYcFqHIog8D3p95HnJ6OSZPZG2ZAAXIYQQQrznlDLj5cusPH78EAALCxs0Gk0aR/X+UUoRFhbM48cPefkyK0olMFN9BiDJnkgfZAAXIcR77s6di+zYsYg7dy5ibW1HlSqt+fjjlmTJkvF/WU5Lz58/ZPHi4Zw6tQu9Xkf+/MXp0eMHihWrmNahCWHk5cvIGdEjIh6ilb53aUavh5cvsxrOR0Ynk6onQCZVTwN+fuDvz9iAvvhTjACccXKCzp3TOjAhhEgZK1d+w7JlY9Fqc6LXV0WrvYde70eBAmWYNGk7OXI4pXWIGdLhw+v59tv2KBUOVAMcgD3Aazw9ezNgwPy0DVAIEzQaHVptONKwl/qUiuy6GV+LXkabVF2SvQRIspeGvL0NrXz+FAMnZ2nlE0JkOvv2/cmMGR2BccDXgOWbNSfQapvj4uLETz8dlS5dSfT8+UO6dSuAUkWBjYDrmzVBwBfAEgYMmI+nZ+80i1EIkfFktGRPGolF+iUDuAghMjmlFGvWfI9G0wiYyH+JHoA7ev0fXLt2jLNn96VRhBnX4sXD37ToRU/0ILJ171fAjT//nJwmsQkhRGqRZE+kb2+mafCq9dJomgYfH0n4hBAZ3/PnD7h58xRKdY+jRF3MzJw5fnxbaoaVKZw+/TdQFeNEL4oZ0IOnTwNSNyghhEhlMkCLyBhkABchRCYUERH25v/s4yihAeyilROJpdPpiGzFi4sdIE+yCCEyN2nZExlLtK6d0Vv5vL3TOjAhhEi67NmdcHDIC2yOo8QldLpLuLlVSM2wMoX8+YsDe4l8Rs+UjVhapv/nbYQQ4l1IsicynjddO6Oe5YtK+uRZPiFERmNmloXGjfug0fwO+MRYG4xGMwB7+9xUrdomDaLL2D799AfgNfA5oIux1hvYTZ06HVM9LiGESE2S7ImMSwZwEUJkAm3bjqJ06epoNPWANsAcYAxabTHMzY8wcuRKLCys0jjKjMfNrQKNGvUFlgIfAFOA2UBdoAt58xalT59f0jJEIYRIcTL1QgJk6oUMws+PzT52hmkaAnCmVi15lk8IkTGEh4exc+citm5dQEDABSwt7ahevQ0tWgx90x1RvK1du35j+fKJPHkSAOixtHSgTp2O9OnzC1qZuVoIkUQZbeoFSfYSIMleBhNtbj4fauPkJAO4CCGEEEKI5JHRkj35SUtkLjKAixBCCCGEEIAkeyIzkgFchBBCCCGEkGRPZGIygIsQQgghhHiPyaTqInPz8IickN3PD3y8IwdwCSiGT4CzYbUQQgghhBCZkSR74v3g4YGXB3h5z/9vABef2vj7ywAuQgghhBAic5JunOL9IgO4CCGEEEKI94Qke+L9IwO4CCGEEEKI94Ake+L9JQO4CCGEEEKITEye2RPvNxnARQghhBBCZFKS7AkBMoCLEEIIIYTIdKQbpxDRyQAuQgghhBAik5BkT4iYZAAXIYQQQgiRCUiyJ0RcZAAXIYQQQgiRgckze0LERwZwEUIIIYQQGZQke0IkhgzgIoQQQgghMhjpxilEUsgALkKIFBQS8pI7dy7y+PGdt65Dp9MREHCFgIDL6HQRb13Pkyd3uXPnIiEhL9+6jpcvn3H79gWeP3/41nWkJ8+fP+T27Qu8fPk8TePQ6SIICLhMQMAVdDpdmsaS2c6xSBlhYa+5c+cSDx7cQCmV1uG8V6RlT4iketO1c3K0Vj7/gGJ4eztLK58Q4q0EBj7C23sMe/Z4Ex4eDICbWyU6dBhLxYpNElWHTqdj48Yf2bjxZ549uw1Atmz5adbsc1q0GIqZmVmi6jl+fBvLl0/mypUjAJib21C7dic6d/6GrFlzJ6qOgIDLLF06hsOH16HXRyacZct60rnzRD74oFKi6khPLl06irf3OE6f3gmAVpuFKlVa07nzNzg5uaVaHDpdBBs2zGDjxp95/vwuANmzF6R5889p1mxwos9xcrh715///W80R46sR6nIhLNcuYZ06TKZokUrpFocIn0LCXnJn39OYMeO3wgJeQ5A/vyladduJLVqdUrb4N4TGiXpdbyCgoJwdHQkcMUKHGxs0jockd74+YG/P5sDyuNNZwJwxslJunYKIRIvKOgxQ4dW4dGjp+j1g4BawH00mnko5cOgQb9Tr16PeOtQSjFjRhf27/8T6A588mbNKjSaP6hatS3Dhi1Dq42/Q8+ePf9j5szuaDQ1UKof4AT4oNXOJmfOrPzww8EEE747dy4yfHg1QkLs0eu/BMoDl9FqZ6PRXGTixL/48MPaCR6X9OL06T1MmNAYpYqj138BuAH/oNXOxNr6BdOnHyB//uIpHoder+eHHzpx8OBqlOoBtAMUsBL4g5o1OzJkyP/QaDQpHsutW+cZMaI6r187vjnHHwH+aLWz0GovM2nSDkqXrpHicYj07fXrV3z9dV2uXTuHXt8faAQEotH8jlKb6Nx5Cu3afZ3WYSZZcHAQ7ds7EhgYiIODQ1qHkyBJ9hIgyZ5IFD8/NvvYRbbyUYwAnKlVSxI+IUTC5s8fyPbtf6LX+wGu0dYooBfm5itYsuQudnZZ46zj2LGtTJ7cFPgTaB9j7WqgHaNHb6RSpWZx1vHqVSDdujkTFtYG+B3jJz2uodV60KBBW/r3nxfv/owZ04CzZ2+h1x8GskVbE4pG04icOW+yaNHlBBPP9ECn0/HZZ0V58qQwSm0DLKOtfYpWW5kyZVyYPHlHisdy5MhGpk5tQeT5bBNj7Z9AR8aN20qFCo1TPJZRo+pw4cJ99PpDQNZoa16j0XiSO/c9Fiy4mCHOsUg5q1dPw9t7IkodBNxjrB0LTGHBgsvky+dqYuv0K6Mle/IpFCI5eHjgNaKk0dx8Mk2DECIhYWGv2b37f29+9Y55w6MBphAREca+fcvirWf79oVotRWInegBtEWr9WD79kXx1rFv33LCw0OBqcS+PSiCXj+APXu8CQ0NjrOO+/ev8++/u9Drx2Cc6AFYotRUHj26xunTu+ONJb3499/dPH58HaWmYZzoAWRHrx/N6dM7efDgRorH8tdfC9FqKxE70QNoj1Zbnr/+WpjicQQEXObcub3o9WMxTvQArFBqCg8eXObs2X0pHotI37ZtW4hSHYmd6AGMQqvNyq5dv6V2WO8dSfaESE4ygIsQIgmePbtPaOgLoHocJfJiZvYBAQH+8dZz69Yl9Pq46gC9vga3b8dfR0CAP1qtG5FdN02pQVjYS549ux9nHffuXX7zf3HFUgmNxjzB/Ukv7t71R6OxACrGUSKyq2JAwOU41iefO3f84znHGvT6Gty5k/LH9b99jSuWqoAmw5xjkTIiIsJ58uQGcb9PbFCqorxPUoEke0IkNw8P6NzZqJWPgLvSyieEiMXGJqoL0N04SoSj19/H2jr+rkJ2do7x1AFwB1vb+OuwsXFEqYdAWJx1AFhb28dbR6S4YnmIUuHR9jt9s7FxQKkw4FEcJe4YyqU0W9uEz3FqxJHwOb4HqATfsyJzMzPLgrm5NXG/TxRa7R15n6QCSfaESCnRWvk6423UyidJnxACwN4+O2XK1EWrnQuYmiZhJXr9E6pVaxdvPTVqtEOj2QDcNrH2DhrNemrWjL+OqlXboNc/JfL5r5h0aLVzKVWqNo6OueKsw82tAjlyFAJ+jqPEHMzNralYsWm8saQXFSs2JUsWK2BOHCV+IWfOwri5pfzokzVrtkWjWYfpm+dbaDQbEzzHyeGDDyqRLVt+4j7Hv2BubpMqzw6K9Euj0VCtWlu02l8BU12/fdDpzid4bRPvTpI9IVLSm1Y+r1ovjVr5fHwk4RNCROrQYSxKnQQ6ANffLA0F/kCr7cPHH7fGxaVMvHXUr9+TrFnzoNXWB3yJHNxFAQfQahuQNWsu6tf/NN46ChUqTeXKbdFq+xM5QEvomzXXgY4odZwOHcbGW4eZmRmdOo0HVgBfAlFzrwUB3wFTaN78S+zsYj7Plz7Z22enefMvgG+A74EXb9Y8BL4AVtKp07hUmfKgfv1eODrmRKttABzkv3O8H622Admy5aNevZ4pHoeZWRY6dhwHLAOG8F+rZxCRz3t+S6tWQ9+0RIr3WevWIzAze4RG4wWce7M0AliHVtuOokUr89FHDdIwwveDjMaZABmNUyQrb2/D3Hw+1JZpGoQQABw6tJZZs3oREhKImVlhlHqCXh9IlSrtGDx4MZaWCX//BARcZvLklty9ew4zs3yABp0uACenkowdux5n52IJ1hEaGsLMmT04eHAlWq0DGk1OdLrrWFk58MUXv1K1qqnBQWLbuPEnliz5Gp1Oh5lZQfT6eyj1Gi+vL+jRY3qqzgf3rnQ6Hb//PowtW2aj0Vih1eZDp7uFmZkZ3bpNo3nzL1Mtljt3LvHNNy0JCLiAmZkToNDp7pE/f2nGjFmHk1PRVItl/foZLF06Gp1OYWZWAJ0uAAijRYvBdOv2nYzEKQA4e3Yf337bnqCg+5iZuaDUC/T6J5QpU4+vvlqBg0OOtA4xyTLaaJyS7CVAkj2R7N7MzTc2oK9hmgYnJ+jcOa0DE0KkpdevX3Hw4Gru3LmIlZUdVaq0pkCBEkmqQ6/Xc/r0bs6dixwJsVSpGpQtWy/JN9537lzk0KG1hIS8IH/+4lSt2hYrK9sk1fHixVP27/+TR49u4eiYi+rV25MzZ/4k1ZGePHp0mwMHVhIY+IhcuQpSo0YH7O2zp3ockef4b86e3YdGo6F06Vp8+GGdNEmugoKesH//nzx+fBtHx9zUqNGeHDmcUz0Okb6Fh4dx9OgGrl49iYWFFRUrNsXNzdQInRmDJHuZjCR7IsVEa+Xzpxg4OUsrnxBCCCFEOpbRkr0M18Y+Z84cXFxcsLKyolKlSvgl8ODTzJkz+eCDD7C2tqZAgQIMHjyY169fp1K0QsRDBnARQgghhBApKEtaB5AUK1euZMiQIcyfP59KlSoxc+ZMPD09uXTpErlz545Vfvny5YwcOZLff/+dKlWq4O/vT/fu3dFoNPz4449psAdCxODhETkhu58f+HhHtvIFFMMnwNmwWgghhBBCiLeRobpxVqpUiYoVK/LLL78Akf3WCxQowOeff87IkSNjlR84cCAXLlxg9+7dhmVDhw7l6NGjHDhwIFGvKd04RaqSAVyEEEIIIdIt6caZQsLCwjhx4gT16tUzLNNqtdSrV4/Dhw+b3KZKlSqcOHHC0NXz2rVrbNu2jcaN4577JTQ0lKCgIKM/IVJNtK6d0adp8PZO68CEEEIIIURGk2G6cT5+/BidTkeePHmMlufJk4eLFy+a3KZjx448fvyYatWqoZQiIiKCvn378vXXX8f5OtOmTWPixInJGrsQSfKma+dk7/n/DeASUAxvbxnARQghhBBCJF6Gadl7Gz4+PkydOpW5c+fyzz//sG7dOrZu3crkyZPj3GbUqFEEBgYa/m7fvp2KEQsRjQzgIoQQQggh3kGGadnLmTMnZmZmPHjwwGj5gwcPyJs3r8ltxo4dS5cuXejVqxcAZcqU4dWrV/Tu3ZvRo0ebnJPG0tISS0vL5N8BId6GDOAihBBCCCHeUoZp2bOwsMDd3d1osBW9Xs/u3bupXLmyyW2Cg4NjJXRmZmYAZKBxaYSITPhGlDS08tVir7TyCSGEEEKIeGWYZA9gyJAhLFq0iCVLlnDhwgX69evHq1ev6NGjBwBdu3Zl1KhRhvJeXl7MmzePFStWcP36dXbt2sXYsWPx8vIyJH1CZCgygIsQQgghhEikDNONE+CTTz7h0aNHjBs3jvv371OuXDm2b99uGLTl1q1bRi15Y8aMQaPRMGbMGO7evUuuXLnw8vJiypQpabULQrw7GcBFCCGEEEIkQoaaZy8tyDx7Il3z8wN/fzYHlMebzgTgLHPzCSGEEEKkkIw2z16GatkTQsQgA7gIIYQQQog4SLInRGbg4YGXB3hF69rp41Mbf39p5RNCCCGEeF9lqAFahBAJkAFchBBCCCHEG5LsCZHZeHhA585G0zQQcFemaRBCCCGEeM9IN04hMqvOnfHy88PLP7Jrp3dAZ3wCnKVrpxDivaLX6/nnn+0cP76NiIgw3NzcqVmzE9bWdqkeS2DgI/bsWcLdu5ewtranSpU2FC9eGY1Gk+qxiMxNKcX58wc4dGgtoaGvKFCgJLVrd8XBIUdahyZSmYzGmQAZjVNkCn5+bPaxixzAhWIE4EytWpLwCSEyt0ePbjFhghe3b/+LmVlRwB6d7hTW1g6MGPEn7u4NUy2W7dsXsnDhIHQ6DVptGeAeOt0dPvywPqNGrcbW1jHVYhGZ24sXT/nmm1ZcuLAPM7OCQG70+n8xM9MyYMB86tbtltYhZmgZbTRO6cYpxPvAwwOvESWNunZGPcsnXTuFEJlReHgoY8Z4cvduEHAQne4SOt0J4DqvX1dlypSW3LhxJlVi8fPbzNy5fYiI6IFSd9Dp/NDpbgIbOHvWj++/75gqcYjMTynF1KltuHTpLLAVne46Ot0xlLpDRERHZs3qwcmTu9I6TJGKJNkT4n0iA7gIId4Thw6t4969i+j1G4AqQFRXyYIotRa9Pg8bNvyYKrGsWDEVjaYWMBeI6kanBZqj1y/k5MltXL16MlViEZnbxYuHOXduL3r9H0Bj/rvVzwUsQqv9mFWrpqVZfCL1SbInxPtGBnARQrwHjh7dgEbzMVDWxFpL9PruHDy4LsXjePbsPleuHEGpPvyXcEbXCq02J0eOrE/xWETmd+TIBszMnIhM9GLSotd/xrlze3n58llqhybSiCR7QryvorXydcbbqJVPkj4hREb3+vUrlMoVT4nchIcHp0ockeKKJQsaTXZCQ1M+FpH5hYa+AnIS9y1+7jflQlIrJJHGJNkT4n32ppXPq9ZLo1Y+Hx9J+IQQGVvBgqXQag8Apm9qNZpd5M9fKsXjyJHDGSsrR+DvOEpcR6e7TMGCKR+LyPwKFiyFTncOCIijxC5sbXPi6BjfDyEiM5FkTwghA7gIITIdT8/e6PXPgfFAzIHHd6LUJpo06ZvicVhYWNGgQQ+02nnAuRhrw9FohmFt7Ui1au1SPBaR+dWs2QkLCytgGKCLsfYUWu2vNGzYiyxZzNMgOpEWJNkTQvwn+gAuT9bIAC5CiAwrXz5Xevb8AZiORlMb+ANYC3RHo2lK+fKNqF//01SJpX378Tg7F0KrrQx8CWwA5qLVVkCj2cTgwYuxsrJNlVhE5mZr68iXX/6ORrMKrdYDmE/k+20gWm01XFxK0Lbt12kbpEhVMs9eAmSePfHe8vZmc0B5w9x8ODnLZOxCiAzn6NFNrFkznUuXDgCQI4cLTZv2o3nzwanauvHqVSBr1nzL9u2/8urVY0CDu3sT2rUbRYkSVVItDvF+OHt2P6tWTePUqR2Awt4+N40afUarVl9hY2Of1uFlaBltnj1J9hIgyZ54r/n5gb8/mwPK401nAnDGyQlJ+oQQGU5wcBAREWHY2WVHq027jk06nY6XL59iZWWLpaXcV4iU9fr1K0JDg7Gzy46ZmVlah5MpZLRkL0taByCESMc8PCKf5/PzAx/vyFa+gGL4BDgbVgshREZgY5M+bsrMzMxkcAyRaqysbKWL8HtOkj0hRMI8PPDyAC/v+YaunT4+tfH3l1Y+IYQQQoj0SgZoEUIkXvQBXKJN0yADuAghhBBCpD+S7AkhkubN3HzRp2kg4K5M0yCEEEIIkc5IsieEeDvRWvk6423UyidJnxBCCCFE2pNn9oQQb08GcBFCCCGESLck2RNCvDsZwEUIIYQQIt2RbpxCiOQTfQCXJ2tkABchhBBCiDQkyZ4QInlFDeBSZrUM4CKEEEIIkYYk2RNCpAwZwEUIIYQQIk3JM3tCiJQjA7gIIYQQQqQZSfaEEClPBnARQgghhEh10o1TCJF6ZAAXIYQQQohUI8meECJ1yQAuQgghhBCpQpI9IUTakAFchBBCCCFSlCR7Qoi086aVz6vWS6NWPh8fSfiEyAz0ej2vXgWi00W8dR1KKYKDXxAW9vqdYgkLe01w8AuUUm9dh04XwatXgej1+neKJTmEhgYTGhqc1mGIFCTnWCQHGaBFCJH2ZAAXITKVZ88esHbtt+zatYSQkGeYm1tTo0Z72rYdhZNT0UTVodNFsG3bXDZtmsODB/4AlClTl9ath1O+vGeiY/nnnx2sXTudM2d2A5AnTzGaNRtA48b9MTNL3G3Q3bv+rFnzLfv3ryA8PARr62w0aNCdVq2+Ilu2PImO5V0ppfDx8WbDhllcv34CgCJFKtKy5ZfUqNEBjUaTarGIlKGUYs+e/7Fhwyxu3jwJgKurBy1bDqZ69U/kHIsk06h3+YnrPRAUFISjoyOBK1bgYGOT1uEIkfn5+YG/P2PPtMU/R2UCcMbJCTp3TuvAhBCJ8fjxHYYPr8azZy/Q63sB5YHLaLULsLR8ydSpe3B1/SjeOnS6CKZNa8uxY5tRqh3QFHiBVvsHev0R+vadQ+PG/ROMZevWOSxYMBCt9mP0+u6APbAZjWY1Hh7NGDlyVYIJ39Wr/zBqVB3CwhzQ6/sAbsA/aLW/ki2bA9On+5IzZ/7EHJp3opTi118Hs3nzLDSaxm+Oi0KjWYlS22nZchg9ekxP8ThEylFKsWDB52zbNgeNpglKtQX0aDQrUGonrVuPpFu3aWkd5nsvODiI9u0dCQwMxMHBIa3DSZAkewmQZE+INOLtbWjl86cYODlLK58QGcCUKa04duwYev0hoEC0NYFotXVxcgplzpx/422h2L59IXPn9gM2AU2irVHAl2g0v7Bw4VXy5HGJs47796/Tp48bSn0O/AREf70tQDMGDlxIgwa94qxDKUX//mW4d88avX43EP3G7hZabVU8PDz4+uu1cdaRXE6f3s3YsfWAOUDMRHcW8CVTp+6jdOkaKR6LSBn//LODCRMaAvOBPjHWzgCG8e23ByhZsmrqBycMMlqyJ8/sCSHSJxnARYgM58mTu/j5bUSvH4NxogfgiF7/HXfunOX8+QPx1rNlyzw0Gi+MEz2ITNimotHYs3Pnonjr2LlzERqNPTAV40QPoCkaTVM2b54bbx3nzx/g7t1z6PXfY5zoARREr/+ao0c38uRJQLz1JIetW+eh1ZYG+plYOwit9gO2bYt/f0T6FnmOywG9TawdjJmZG9u2zUvlqERGJ8meECL9kgFchMhQbt06j1J6oEEcJeoAWbh580ycdSiluH37X5SKqw5b9Prq3LgRdx0AN278i15fAzDdK0cpT27fTrgOjcYcqBVHCU+U0nH79vl460kO1679i17vSezEFUCDXu/J1avx749I3yLPcQNMn2MtOp0n167JORZJIwO0CCHSPxnARYgMwdLS+s3/PQUKmygRCERgYWFtYl0kjUaDubk1YWFP4ynzGEvLgvHGYmFhjVYbQNwDZz7B3DzuOKLqUCriTdxZTdYRVS6lRR7bJ/GUeBLt+IuMKPL8xf2+h8dyjkWSScueECLjiNa1s9aTNUZdO4UQaa9oUQ/s7fMAcXWx/A2t1hx390bx1vPxx80xM/sDCDOx9ixKHaFSpebx1lGpUvM3zw2eM7E2DK12CR9/HH8d7u6N0GrNgN/jKPErDg55KVYs5X9xqlKlOVrtGuCZibWP0WrXU6VK/Psj0rfIc7yKyB8XYnqIRrNRzrFIMkn2hBAZy5uunZPLrDbq2inP8gmR9szNLWjTZjiwAJgORM2NFwF4o9GMpl69nmTLljfeelq2HIZSt4AOwP1oa06g1bYkT56iVKnSOt46qlZtQ+7cbmi1LYB/oq25h0bTAY3mDi1bDo23juzZ81GvXk80mq+BZYDuzZrXwPfAQtq0GU6WLObx1pMcGjbsi6WlOVqtF3At2poraLVNsba2xtPT1LNeIqNo3Lg/FhaaN+f4erQ1/mi1TbGxsYt3QCEhTJFkTwiRMckALkKkSy1aDKFFi6HACLRaZ7TaGpiZuQBdqFy5OX36zEqwDlfXjxg5cjUWFjvQaAqg1VbBzKwMUIE8ebIwefIOzM0t463DwsKKb77ZQZ48WQB3zMzKoNVWQaMpiLn5TkaOXE2RIuUSjKVPn9lUrtwM6IyZWSG02hpotc7AV7RsOYzmzQcnWEdyyJHDiUmT/sLW9jLghlZbETOzCkBR7OxuMmnS9lSd808kv5w58zNp0l/Y2FwEXNFqPd6c4w+wt7/LN9/swNExV1qHKTIYmXohATL1ghAZgJ8fm33sDNM0BOBMrVryLJ8QaSkg4DK7d//Bw4c3cXTMRa1anXFzc09SHS9fPmfv3v9x5cpxzM0tqVChCRUrNk30ZOgQOWffsWNbOH58K+Hhobi5VaB27a7Y2WVNUixXrpzAx8ebwMBH5M5diLp1e+Dk5JakOpJDaGgIBw6s5MwZHzQaDaVL16JatXbyLFcmEhoazP79Kzh3bj8ajYYPP6xD1aptsbCwSuvQBBlv6gVJ9hIgyZ4QGUi0ufl8qI2TkwzgIoQQQojkk9GSPenGKYTIPGQAFyGEEEIIA0n2hBCZiwzgIoQQQggBSLInhMisZAAXIYQQQrznZFJ1IUTm5eEROSG7nx/4eEcO4BJQDJ8AZ8NqIYQQQojMSpI9IUTm5+GBlwd4ec//bwAXn9r4+8sALkIIIYTIvKQbpxDi/SEDuAghhBDiPSLJnhDi/SIDuAghhBDiPSHJnhDi/SQDuAghhBAik5Nn9oQQ7y8ZwEUIIYQQmZgke0IIIQO4CCGEECITkm6cQggRRQZwEUIIIUQmkuGSvTlz5uDi4oKVlRWVKlXCL4GHa54/f86AAQPIly8flpaWFCtWjG3btqVStEKIDEcGcBFCCCFEJpGhkr2VK1cyZMgQxo8fzz///EPZsmXx9PTk4cOHJsuHhYVRv359bty4wZo1a7h06RKLFi3C2dk5lSMXQmQ4MoCLEEIIITI4jVJKpXUQiVWpUiUqVqzIL7/8AoBer6dAgQJ8/vnnjBw5Mlb5+fPnM336dC5evIi5uflbvWZQUBCOjo4ErliBg43NO8UvhMig/PzY7GMXOYALxQjAmVq15Fk+IYQQ4n0THBxE+/aOBAYG4uDgkNbhJCjDtOyFhYVx4sQJ6tWrZ1im1WqpV68ehw8fNrnNpk2bqFy5MgMGDCBPnjyULl2aqVOnotPp4nyd0NBQgoKCjP6EEO85Dw+8RpQ0tPLVYq+08gkhhBAi3cswo3E+fvwYnU5Hnjx5jJbnyZOHixcvmtzm2rVr7Nmzh06dOrFt2zauXLlC//79CQ8PZ/z48Sa3mTZtGhMnTkz2+IUQmUDnznj5+eHlP5+xZ57gT2V8Apzx94fOndM6OPG2rl//l+PHtxIREYara3nc3RtjZmaWpDqePXvAwYOrCQp6RM6cBahatS22to5JqiMs7DVHjmzgzp2LWFvb8fHHLcmXzzVJdSilOHfOl3Pn9qOUonTpGpQqVQONRpOkeoR4Hz19eo9Dh9YQFPSYXLkKUbVqW2xs7NM6rLcWEHCFI0fW8/r1KwoWLEmlSs0xN7dM67BEKssw3TgDAgJwdnbm0KFDVK5c2bB8xIgR7Nu3j6NHj8baplixYrx+/Zrr168bvrh//PFHpk+fzr1790y+TmhoKKGhoYZ/BwUFUaBAAenGKYQw5u1tmKbBn2Lg5CzTNGQwL18+4/vvO3Lq1Ha0Wgc0Gmt0ugfkyFGIr75aQfHiHydYh16vZ/nycaxZ8z1KadBqc6HT3cfCwooePb6jSZMBiYrFz28zP/3Uk1evHmNm5oRSz9HrQ6hZszOff74QCwurBOu4f/86U6e24caNf9BqswMa9PonFCr0EaNHryFv3iKJikWI941er2fJkpFs3PgTSpmh1eZEp7uHhYUNn332I56en6V1iEkSGhrC7Nm98PVdjlZri0bjiE4XgL19boYM+QN390ZpHWKGJt04U0jOnDkxMzPjwYMHRssfPHhA3rx5TW6TL18+ihUrZvQLbYkSJbh//z5hYWEmt7G0tMTBwcHoTwghYpEBXDI0nU7HhAlN+fffY8AK9PrH6HT3gWM8e+bMuHGeBARcTrCeVau+YdWqKej1X6PUPXS6O8BNwsK6smDBQHbvXpJgHefPH2Dq1FYEB1cGLqDT3UWvfwTMZf/+1cyc2SPBOl69CmTUqDrcuhUI7ESvf/Smjl3cvv2SUaPq8PLl8wTrEeJ95O09hvXrf0CvH49S9998jm8QFtaeOXN6s3//irQOMUlmzOjCwYMbgIXo9Y/Q6e4C53j5sgKTJzfn4sUjaRyhSE0ZJtmzsLDA3d2d3bt3G5bp9Xp2795t1NIXXdWqVbly5Qp6vd6wzN/fn3z58mFhYZHiMQshMrk30zR41XppNE2Dj48kfOndyZM78Pc/hF6/GvgEiBrEqwJ6/XbCwuzYsGFGvHUEBwexZs33wHBgApD9zRpnYA7QFm/vCfE+Jw7w55+TgTIotRYo/mapDdAXpeZy4MAKbt06H28df/+9mKdP76LX7wLqE/n1rgHqodfv4unTAP7++/d46xDifRQU9IQNG34CRgNjgKxv1hQAFgLNWLp0PBmkIxzXrp3iyJG16PULgM8A6zdrSqLUeqA4K1dOSbsARarLMMkewJAhQ1i0aBFLlizhwoUL9OvXj1evXtGjR+Svnl27dmXUqFGG8v369ePp06d88cUX+Pv7s3XrVqZOncqAAYnrViOEEIkiA7hkOL6+K9FqywC1TKy1R6/vgY9P/L/mHzu2lbCwV8AXJtZqgEE8eXKDy5ePxVnHy5fPOH16J3p9f/5LOKPrhFabnQMHVsYby759K1GqGVDYxNpCKNWCffvir0OI99GxY5uJiAgFPjexNvJz/OCBP9eunUrdwN7SgQOr0GpzEfkjVkwW6PX9OHFiK8HBMgDh+yLDDNAC8Mknn/Do0SPGjRvH/fv3KVeuHNu3bzcM2nLr1i202v/y1wIFCrBjxw4GDx7Mhx9+iLOzM1988QVfffVVWu2CECIzkwFcMoxXr56j1xck8mbOlEK8fh2IXq83+l6JWUfkb6ZOcdbxX7m44gg0KhubBRpNvnjrAHjx4hlgupdLVP0vXpyOtw4h3kcvXz5Ho7FGqdxxlEj4c5yevHr1HI3GGdM/HkHk/ihCQl5gYyOPKr0PMlSyBzBw4EAGDhxocp2Pj0+sZZUrV+bIEembLIRIJR4e4OHBZG9vNgdcjRzAJaAY3t4ygEt6ki+fG1qtN3p9GGCqW/9BcuVyjTPRi6oD9MBRwNRgLgfflIt7RM2sWfNgYWFLWNgBIrtfxvQQvd6fvHl7x1kHQP78RXn06CDRnlowotUexNk5aSN7CvE+cHJyQ6lg4CTwkYkSkZ/jjDLAUb58buj1vwNPgBwmShzE0tIBB4ecqRyZSCsZqhunEEJkGDKAS7rWoEEv9PqHwE8m1p5Eo1lB48bxj8D34Yd1yJmzMBrNWCDmoF9BaLVTKFmyJk5OReOsw9LSmjp1uqDVzgVuxlirgPGYmZlRq1b8TcMNG36GXu8HrDOxdiN6/WEaNsxYIwoKkRrKl29I1qzOaDSjgfAYa5+j1U6jbFlPcueOq/U9falduwtarQImEnkNie46Wu186tfvJlMwvEck2RNCiJQiA7ikWwUKlKBNm1HASKADsAM4AoxBq61F4cJlaNLEdC+SKGZmZgwatBCNZh9abRVgGXAMWIBWWxELi9v06TM7wVg6dJhA9uz2aLWVgO8AP2AjGk0jYD69e8/E3j57vHVUrNiUypXboNF8AgwA9gH7gYFoNG2oVKkVlSo1TzAWId43ZmZZ3nyOd6HRVAf+JPJzPA+ttgJWVg/p3dvUj0Lpk6NjLnr1+hH4GY2mKbCZyGvKNLTaj8mZMzuffDI2bYMUqSrDzLOXVoKCgnB0dJR59oQQ7y7a3Hw+1MbJCenamYaUUuzYsYg1a77n4cOrAFha2lO/fnc6d/4m0c+znD9/kKVLx3Lu3F4ANBotFSo0pVu3qRQsWCpRdTx9eo8lS0axf/8KdLrIuV4LFixLx47jqFKlVaLq0OkiWL16Gps3z+HFi8hpiuzt8+Dl1Z82bUaRJUtcz/AIIc6e3cfSpeO4cGE/EPk59vBoTrdu08if/4M0ji7pDhxYzZ9/Tub27TMAZMliRc2aHejadRrZsuVJ4+gytow2z54kewmQZE8Ikaz8/MDfn7Fn2uKfozIBOOPkJAO4pCW9Xk9AgD/h4aHky+eGlZXtW9Xz+PEdAgMfkT2701vfTL18+ZyHD29gZWVHvnyuaDRxDSATt/DwMAIC/AFwciqGublMNSREYj16dJugoMfkyOFM1qxxDdqSMSiluHfvKq9fvyRPnsLY2jqmdUiZgiR7mYwke0KIFOHnx2Yfu8gBXCgGTjKAixBCCJHeZbRkT57ZE0KItODhIQO4CCGEECJFZbipF4QQItN4M02Dl58f+HgbpmnwCXA2rBZCCCGEeFuS7AkhRFrz8MDLA7y85/83gItPbfz9ZQAXIYQQQrw96cYphBDpRbS5+Wo9WWPUtVMIIYQQIqkk2RNCiPTkzdx8k8usNpqbT57lE0IIIURSSbInhBDpUbRWPhnARQghhBBvQ57ZE0KI9EoGcBFCCCHEO5BkTwgh0jsZwEUIIYQQb0G6cQohREYhA7gIIYQQIgkk2RNCiIwkagCX1qdlABchhBBCxEuSPSGEyIg8PGQAFyGEEELES57ZE0KIjEoGcBFCCCFEPCTZE0KIjE4GcBFCCCGECdKNUwghMgsZwEUIIYQQ0UiyJ4QQmYkM4CKEEEKIN6QbpxBCZEYeHnjhh5d/ZNdO74DO+AQ4S9fOFPD8+UO2bPmZ3bu9efHiETlyFKBBgx40atQPGxv7RNXx+nUwc+f25dChDYSFBaPRmFGw4Ad8+ulPlCtXN4X3wNj9+9fYtGkm+/ev4fXrFzg7f0CjRr2pV68HWbKYp2osIv0KDn7BX3/NY+fOxTx5cht7+1zUq9eFpk0/x9ExV1qHJ4R4Q6OUUmkdRHoWFBSEo6MjgStW4GBjk9bhCCFE0vn5sdnHLnIAF4oRgDO1aknClxzu37/GV1/VIjDwGXp9J6AYcBKNZhX58xfn22/3Ym+fPd46goNf0ru3G0FBD4FGQB3gPvA7EEjfvj/TuHG/lN4VAC5ePMy4cQ0JC7NEr+8KOKHR+KDUFsqV82Ts2I2Ym1ukSiwi/QoKesKoUbW5c8cfpdoB5QB/tNplZM2anW+/9SFv3sJpHKUQKSM4OIj27R0JDAzEwcEhrcNJkCR7CZBkTwiRaXh7/zeAC7VxcpJWvnc1fHg1Ll9+gF7vAzhHW3MOrbYm1ao1ZNiw+B+aHDu2PqdP7wW2AQ2irXkBNEaj8ePPPx9hY5OyNxXh4WH07FmYFy+KoNdvA6K3Sv6NRtOEDh1G0779uBSNQ6R/P/zQiQMHdr5535eKtuYOWm0tihbNx/TpvmkUnRApK6Mle/LMnhBCvC9kAJdkdfXqSS5dOohePx3jRA+gFHr9aA4cWMXz5w/jrCMs7DX//rsf+BTjRA8ik62FKBXG//43OlljN+Xo0Q0EBgag18/HONEDqIdSPdmyZT46XUSKxyLSr2fPHnDgwCr0+jEYJ3oA+dHrv+fSpQNcv346LcL7f3t3HhdV2f5x/DNnkE0F9wWi3DK11FwaIzUxLbd4tKzUpMysHltssc0WNTPTditN2/0Z5fpkqZXlhmZZlFuWC7kviLsgoixzzu8PkMRYhWGY4ft+vXiV5z5zc525Ubi4zrluETmPkj0RkfJEDVxKzN9//wbYgBvzOKMPppnOzp3r85xj584NWFYa0DuPM5oC9dmy5afihFoocXGx2O0N+fcP8Gf1ISnpAEeO7HN5LFJ27dy5HtPMIO+v2UjARlyc/kERKQuU7ImIlEcOR3aVL4roHFU+JX2FY7f7ABZwJo8zUgAwjLx7oVWo4Jfj3H/LnN8w7BcWZBFkXs+ZrM+Zm5RzzpPy6p/1z+trNvNrSF8nImWDkj0RkfIqq8oXGZGco8oXE6OErzCuvLIrNpsBfJbHGdPx9w/mssva5TlHvXot8PGpCEzL44wVwAE6dLitWLEWRqtW3XA69wPLch232aYTGno51auff8uqlCeNG7fDzy8ImJ7HGZ9hsxm0bNm1NMMSkTwo2RMRKe8cDiKfapZd5Ytguap8hVCz5sV06NAPw3gaWHLOiAV8gc32Jjfe+AD+/hXznMMwDLp0iQK+AV4G0s8Z/RO4gwoVKtGnz+MuuIKcmjePoH79NhjG3cAf54ykA69gWV9xyy1PYLPZXB6LlF0BAZW48cYHsNneAGbwTyXYAhZjGCPo0KE/NWuGuS9IEcmmZE9ERDKpgUuRPfjg+zRt2ga4HsNoDQzAMJoAA2nf/hYGDnyxwDnuv/89mjbtADxHZqOX/kAHoDl2+1FefnkJhuH6b9c2m42RI7+iTp2KQEtstmuB/hhGPWAEt976LNddN8jlcUjZN3Dgi7Rv3xe4HcNoSubXfRvgBpo2bctDD73v5ghF5CxtvVAAbb0gIuXSeXvzERKqbRry4HQ6Wbv2O5Yt+4wTJw5Tq1YY119/N5dffm2RqmCrVs1m5syxHDlyAF/fCrRr15tBgyZQqVIV1wWfi/T0VH76aS6rVs0hJeUkYWGX0a3bfTRocGWpxiFlm2VZ/PXXShYv/oRDh/ZStWotOne+g9atu2O3u/4ZUxF38bStF5TsFUDJnoiUW7GxEBfHgvjWRBNFPKHam09ERMo1T0v21CpJRERy53BkPs8XGwsx0ZlVvvjGxMSHZg+LiIhI2aVkT0RE8udwEOmAyOipLIhvTSwOYmI6ExenKp+IiEhZpgYtIiJSOGrgIiIi4lGKlOydPn2aVatWsWnTpn+NnTlzhunT89pzRUREvELW3nxj+27IsTeftmkQEREpewqd7MXFxdG0aVOuvfZamjdvTqdOnThw4ED2eGJiIoMHD3ZJkCIiUsY4HNlVviiic1T5lPSJiIiUDYVO9p5++mmuuOIKDh06xNatW6lcuTLt27dnz549roxPRETKqqwqX2REco4qX0yMEj4REZGyoNANWn7++WeWLFlCjRo1qFGjBgsWLOCBBx6gY8eOLF++nIoVK7oyThERKavUwEVERKRMKnRl7/Tp0/j4/JMb2mw2pkyZQmRkJJ06dSIuLs4lAYqIiIdQAxcREZEypdCVvSZNmvD777/TtGnTHMcnTZoEwH/+85+SjUxERDxP1t58Y2NjWRCzPXtvvujoUFX5RERESlmhK3s33XQTM2bMyHVs0qRJDBgwAMuySiwwERHxYGrgIiIi4nY2SxlavpKSkggODiZx5kyCAgPdHY6IiOeJjWVBTKXMKh+NiSeUiAhV+URExPOkpCTRv38wiYmJBAUFuTucAhX6Nk4REZELogYuIiIiblGkTdVFREQumBq4iIiIlColeyIiUnqy9uYb23dDjr359CyfiIhIyVOyJyIipU8NXERERFxOz+yJiIh7ZG3TEBkbCzHR2ds0xMSHZg8XZPbs8cTGzqdCBV/69n2atm17FjmMHTvW8803k0lPT6VVqxvo3DmqyHOUBMuy+OuvH9m3bwsBAZVo06YHlSpVdUssZUlMzOesXfs9FSr40aPH/TRq1LrIcxw9Gs/69YvJyEijUaO2NGzYygWRFixzjVeyb99WAgIqZ61xFbfEkpx8nDVrvuP06WQuuqgJl1/eEZvN5pZYSsLRo/tZv34JGRlpXHrpVTRocKW7QxIpEy6oG+dnn33G1KlT2blzJ6tXr+aSSy5h4sSJ1K9fn969e7siTrdRN04RkVISHf1PAxc6ExKSdwOX5cujmThxCJaVds5RG/7+lXn33fXUrl2/wE+XlHSMp54KJz7+b+Cfb4V+fkGMGDGTNm16FP+aCmnLltVMnDiE+PjNgA2wqFAhgP/852GiosZht9tLLZayYt26xbz88q2kpiaec9RGnTqNeP31nwkKqlHgHKmpKUyZ8hDLl0/HspzZxy+9NJzHH/8/QkIudUHkudu06SfefvseDhzYwj9rHEifPo9y++0vltoaO51OoqOfY/78d0hPP50dS0hIUx599BOaNLm6VOIoKWfOnOK99x5gxYrPc6xx48bX8Pjj06lbt6EboxNv5GndOIt8G+eUKVMYPnw4PXv25MSJEzidmX+xqlSpwsSJE0s6PhERKS8K2cBlw4ZlvPXWYCzrImAekAacACZy5kwaQ4c2JS0t7fzZczBNkwceaEZ8/G7gDeAYkA7MJzW1DmPG9Gbbtt9L/BJzs3PnHzz//PUkJFQBlgMZwAHS05/gf/97jY8+erRU4ihLtm1bywsv3Ehqak3gazLX5jjwFgkJe3nggSswTTPfOSzL4uWXbyEmZhaW9UbW69OBr9i+/RhPP92JY8cOuPpSANi+fR0jR97AwYPVgRVkrnE86emPMWfOBD755PFSiQPgww8f4csvXyc9/UngQFYsy0lIqMLzz3dl584/Si2W4jJNk3Hjbmblyv9hWW+R+e9AGjCPbdsO8/TTnTh+PMG9QYq4WZGTvXfffZcPP/yQ5557Lsdvodq2bcvGjRtLNDgRESlnCtHA5c03owB/YBXQB6gABAMPA3NxOlN5//0H8/00Cxe+S1LSQWAG8BhQlcwnGyKBH4FAJk8e6oor/JcvvniBjIxQTHMJEEHmt+Y6wIvA63zzzWQSEnaWSixlxXvv/RfLOrvG/yFzbaoAjwCzSEo6yPz5E/Od448/lrFu3XeY5oys11XJmqc3phnDyZOnC5yjpHzxxQs4nZdgmouBa8lc47rAS8AEFi58l0OHdrs8jgMHtvPtt+9hWa8DY8j8OjOACExzMRkZocyc+aLL4ygpGzYsYcOGHzDN2cAwMv8dqAD0wTRjSEo6yYIF77g3SBE3K3Kyt3PnTlq1+ve97n5+fpw6dapEghIRkXIunwYux48fAe4i84fl8/UELuPHH2fmO/13300B6pOZLJ6vFnAP27e7vsJx6lQisbHzMc2HgNweFfgvhlGZFSs+d3ksZcm2bRuAu4HauYxGAg357rup+c4RExONYTTJOv98dTDNQSxZMr3YsRYkOfk4v/++ENMcBgTkcsb92GyBrFw5w+WxrFjxBYYRBNyXy2hFTPMhfvnlK1JSklweS0lYvvwzDOMKILdbrkMwzTtYsuSz0g5LpEwpcrJXv3591q9f/6/jixYtomnTpiURk4iISHaVLzIiOUeVL/O2syZ5vMgGNCM9Pf/bOE+dOgE0zTo/N5cB6WRkZFxY7IWUnHw86zmjvK4nEJstjMTEQy6NoyzJvD0zncw1yE3mGqekJOYxnunEiUOY5mXkt8YnT7r+fU1KOoplmeR9PZWw2UJLZY0TEw9hs4WR+y8WAC7DspwkJx93eSwlIXONG+PuNRYpy4rcjXP48OE8+OCDnDlzBsuyiI2NZcaMGYwfP56PPvrIFTGKiEh55nAQ6YDI6KksiG/NbHyAtXmcbAJr8PPLrYLyj6Cgmpw4sQ5wArk1xliHzeaLj49rm1YHBdXAbvfD6VwHXJ/LGScwzR3UqDHIpXGUJYZhYLP5YVnr8zjDCawtsEFLjRoXYbf/kNVbIPc1rlo1rHjBFkKVKrUwjAqY5nrgulzOOIZp7qZGDdfHUqNGGJa1A0gk85bH863DbvcrVPObsiBzjVfgdJrkXr9YR7Vqrn9fRcqyIlf27rnnHl555RWef/55UlJSuP3225kyZQpvv/02/fv3d0WMOUyePJl69erh7+9Pu3btiC3khkwzZ87EZrPRp08f1wYoIiKukVXlqx9YAfgciMvlpM+BPfTo8d98p7r55rPNKablMroDmEbTpu2KF28hBARUokOHWzGMScDRXM54A5stnYgI92wH4S7Nml0N/B+wLZfRz4D93HTTE/nO0aXLYJzOXVnnn28bhvE53bvfXdxQCxQYGET79rdgGO+Q2QjofK9hsznp1Gmgy2OJiIjCslLJbEp0vqMYxiSuvbYf/v4VXR5LSeja9W6czu3AF7mMbsVmm0m3boNLOyyRMqVIyV5GRgbTp0+na9eu/P333yQnJ5OQkMC+ffsYMmSIq2LMNmvWLIYPH87o0aNZu3YtLVu2pFu3bhw6lH+JfteuXTzxxBN07NjR5TGKiIgLORx8NX48mdWda4BJwB7gL+Ap4C78/CoRFfVyvtNcd92d1K3bmMxnl54A/sya5z0gHMOwGDbsY9ddxzkGDhxDYOAZDOMaziYy8DswBHiJ/v1HUq1abs8neq9HHvkUu91G5hpP5p81fhIYQu3aDbnuuvyrnZdd1o6IiDuBe7Je91fWPJMxjI7UqhXGjTcOc+VlZBs48EUCApIxjPZk/kJiP/Abmc+eTuD221+gSpVaLo+jevUQ+vcfCYwl8+vr96xYPsMwriEwMJUBA15weRwlpWnTa7j22tux2QYDTwObgN3AuxjGtdStW4+ePfNv1iTi7Yq8z15gYCCbN2/mkksucVVMeWrXrh1XXXUVkyZNAjLv6w8LC2PYsGGMGDEi19c4nU6uvfZa7r77bn788UdOnDjBV199VejPqX32RETKnp82beL650dyOiODf/bIsxMQUJdhwzbToUOlAudIS0tj9Ojr+euvn8l8DhDARtWqobzwwjfUr9/CRdH/2759W5ky5SE2blySfSwoqC79+z9Lr14PevRm1xdq164/eeGFHhw7tp9/1tiHZs3CefHFJfj6+hY4h9PpZObMMcyf/y6nT58AwGazc/XVN3H//ZNLJcE6a9++LVlrvDT7WHBwCAMGPE+PHkNLbY0ty+KbbyYzc+bLJCX9s/VEixbXc//9kwgNbVwqcZQUpzODL74YzYIFkzlzJvM5TsPwITz8ZoYOnURwcE03RyjextP22StyshcREcGjjz5a6rdDpqWlERgYyNy5c3N87kGDBnHixAm+/vrrXF83evRo/vjjD+bNm8ddd91VYLKXmppKampq9p+TkpIICwtTsiciUgYtXreO6XPmcOhwAJde9CiHAzoRTygREblvxp6bpKQjLF36f6SmnqJt2540atTWpTHn58CB7ezfvxV//0o0aRKOj08Ft8VSVmzbtpbff1+Ir28AXbsOvqDnyVJTU9iyZTUZGWnUq9eS6tVDXBBp4cTHbyM+Po6AgMpcdtnVblvjjIx0tmxZzZkzyYSGXubxm4+fOXOKrVt/ISMjjfr1ryx31XApPZ6W7BX5yfMHHniAxx9/nH379tGmTRsqVsx5X3eLFq75TeiRI0dwOp3Urp2zDXPt2rXZsmVLrq9ZtWoVH3/8ca7dQ/Myfvx4xowZU5xQRUSklFzfqhXXn90OKDqaBfF7icVBTExn4uKgceOCk76goBrcdFPpbWqdn7p1G3r8D90lrVGj1jRq1LpYc/j5BdKyZZcSiqh4QkIaERLSyN1h4ONTgSuuuNbdYZQYf/+KZWaNRcqSIid7Z5uwPPzww9nHbDYblmVhs9myul6538mTJ7njjjv48MMPqVGj8L8FfOaZZxg+fHj2n89W9kREpIyLiiIyNpbIuKmM3HiUOMKJiQ8lLg6iyld/ExEREeACkr2dO3e6Io4C1ahRA7vdzsGDB3McP3jwIHXq1PnX+du3b2fXrl1ERv6zmWrm3j3g4+PD1q1badjw37899fPzw8/Pr4SjFxGRUuFwgMPB2NhYFsRsJxYHcfGNiY4OLVSVT0RExJsUOdlzR2MWAF9fX9q0acPSpUuzn9kzTZOlS5fy0EMP/ev8Jk2asHHjxhzHnn/+eU6ePMnbb7+tap2IiDdzOIgks8q3IL410fFR2VU+JX0iIlJeFDnZmz59er7jd9555wUHU5Dhw4czaNAg2rZti8PhYOLEiZw6dYrBgwdnf+7Q0FDGjx+Pv78/V1xxRY7XV6lSBeBfx0VExAtlVfkiY2MhJjq7yhcTH5o9LCIi4s2KnOw98sgjOf6cnp5OSkoKvr6+BAYGujTZ69evH4cPH2bUqFEkJCRw5ZVXsmjRouymLXv27MEwirxPvIiIeDOHg0gHREZnVvmK2sBFRETEUxV564Xc/P3339x///08+eSTdOvWrSTiKjO0z56IiBeJjYW4OEZuvJW46uHEE0pIiBq4iIhI4Xja1gslkuwB/P7770RFReW5DYKnUrInIuKFYmNZEFMp89ZOGkOIGriIiEjBPC3ZK7F7Hn18fIiPjy+p6URERFzH4SAyIpmxIVOJIhri9xMTA9HRmcU/ERERb1DkZ/bmz5+f48+WZXHgwAEmTZpE+/btSywwERERl1IDFxER8XJFTvbObntwls1mo2bNmlx33XW88cYbJRWXiIhI6VADFxER8VJFTvbObkwuIiLiVaKiiIzN3Jtv5MajxBGevTefGriIiIgnKvIzey+++CIpKSn/On769GlefPHFEglKRETELRwOiIpibN8NRBFNBMshfr+e5RMREY9U5G6cdrudAwcOUKtWrRzHjx49Sq1atXA6nSUaoLupG6eISDmVtU3DgvjWRBOVvU2Dbu0UESm/PK0bZ5Fv47QsC5vN9q/jGzZsoFq1aiUSlIiIiNupgYuIiHi4Qid7VatWxWazYbPZaNy4cY6Ez+l0kpyczNChQ10SpIiIiNuogYuIiHioQid7EydOxLIs7r77bsaMGUNwcHD2mK+vL/Xq1SM8PNwlQYqISPFt3ruXyd98w+L1m7Asi+taNuXBnj1pXq+eu0PzDHk0cNm06RS1a3/GiqXTSDxxkBq16tHlhnvo0OE2fHwquDtqEREpx4r8zN6KFSu45pprqFChfHwD0zN7IuINZqxYwR1vTcRGdTLMvoCBj/1LnOZBPh72EIO7dnV3iJ4lNpYFMZVYnnYp0zY+TeLp7fQELsNirWGw3DRpfnlHRr2wCD8/fe8QEfEWnvbMXpG7cXbq1Ck70Ttz5gxJSUk5PkREpGzZum8fd7w1Eac5kAxzL/AeMIkM524sawhD3p3Ehp073R2mZ3E4iIxIZsvuB/A9vYM/sFiAxevAMtNkBbB988988snj7o5URETKsSIneykpKTz00EPUqlWLihUrUrVq1RwfIiJStrz33XfYqAp8APieM1IBeA+7rQ7vLvzGPcF5sK0hIXx38CCvY3L5eWPXAs+YTpYt+ZTk5BNuiE5EROQCkr0nn3ySZcuWMWXKFPz8/Pjoo48YM2YMISEhTJ8+3RUxiohIMSzdsIkMsw/gl8uoDxnmLSzdsKmUo/J8P27KfM9uyWP8NiA1PZVt234vtZhERETOVeRkb8GCBbz33nv07dsXHx8fOnbsyPPPP8/LL7/M559/7ooYRUTExXLZUUdKyNKl7o5ARETKqyIne8eOHaNBgwYABAUFcezYMQA6dOjAypUrSzY6EREpti4tm2E35gGpuYxm4GOfS9eWzUo7LI/XsVnmezYnj/FZgK+tAlVTQ4iOztyjXUREpDQVOdlr0KABO7Me5G/SpAmzZ88GMit+VapUKdHgRESk+B7o0QM4AdxLzoQvHbgfp5nAQ716uSM0j3bZRRfRs1UrnjQM/jxvbAUwwWZjSIOLudtnAcTvJyYGJX0iIlKqipzsDR48mA0bNgAwYsQIJk+ejL+/P4899hhPPvlkiQcoIiLFc9lFFxE9/DHsxhf4GGHA/cCD+BgXY9g+4ZOHh9Gifn13h+mRPn3sMWqFhtISiLTZeBzobBhEAO2aNeP1CROIjEgmimgiWJ6d9CnhExGR0lDkffbOt3v3btasWUOjRo1o0aJFScVVZmifPRHxFlv27WPyN9/ww7q/sCyLLi2b8mCvXlxxySXuDs2jpaSmEr18OZ8tXcqhEye4uFYt7r7hBm5p354KPj7/nBgdzYL41sTiIIbOhIRA48bgcLgvdhERKRpP22evWMnemTNn8Pf3L8l4yhwleyIiUmJiYyEujpEbbyWuejjxhBISAlFR7g5MREQKw9OSvSLfxul0Ohk7diyhoaFUqlSJHTt2ADBy5Eg+/vjjEg9QRETEazgcEBXF2L4bctzaqWf5RETEFYqc7I0bN45p06bx6quv4uv7z+a8V1xxBR999FGJBiciIuKVHA4iI5IZGzKVKKLVwEVERFyiyMne9OnT+eCDDxg4cCB2uz37eMuWLdmyZUuJBiciIuK1sqp8auAiIiKu4lPwKTnt37+fRo0a/eu4aZqkp6eXSFAiIiLlhsNBpAMio6f+08AlpjNxcWrgIiIixVPkyl6zZs348ccf/3V87ty5tGrVqkSCEhERKXeyqnxjQ6YScXRujls7RURELkSRK3ujRo1i0KBB7N+/H9M0+fLLL9m6dSvTp09n4cKFrohRRESkfHA4wOFgbGwsC2K2E4uDuPjGREeHqsonIiJFVuTKXu/evVmwYAFLliyhYsWKjBo1is2bN7NgwQKuv/56V8QoIiJSvpzfwGXjH2rgIiIiRVboyt6OHTuoX78+NpuNjh07snjxYlfGJSIiUr5lVfkiY2Mh5jtiOUpcfGNi4kOzh0VERPJT6MrepZdeyuHDh7P/3K9fPw4ePOiSoERERCSLw0HkU82yq3wRLFeVT0RECqXQyZ5lWTn+/O2333Lq1KkSD0hERERyoQYuIiJSREV+Zk9ERETcJGtvvrF9N+TYm09VPhERyU2hkz2bzYbNZvvXMRERESll5zdwOafKp6RPRETOKnSDFsuyuOuuu/Dz8wPgzJkzDB06lIoVK+Y478svvyzZCEVEROTfcjRwic7epkENXERE5KxCJ3uDBg3K8eeoqKgSD0ZERESKyOEg0gGR0VNZEN+aWBzExHQmLg7tzSciUs7ZrPM7r0gOSUlJBAcHkzhzJkGBge4OR0REJG+xsRAXx8iNtxJXPZx4QgkJAf1+VkSkZKSkJNG/fzCJiYkEBQW5O5wCFbqyJyIinu94cjKxcXFYlsVVl15KdTd+o9q4axe7Dx+mRuXKOBo3xjDUM2xbfDxb9++nUkAA1zRpQgWfIn6bzrq1c2xsLAtitmff2hkdHaoqXxkRH/83+/fHERBQmSZNwvHxqeDukETEiynZExEpB1JSU3nik0+YtngxpzMyAPCz24nq3JmJ995LpYCAUovl582beWTqVH7fuTP7WMOaNRk/eDC3duhQanGUJVv37eOB995j2Z9/Zh+rExTEs/3781CvXkVviOZwEEkskXGZt3ZGb+xBTHwL3drpRnv3bua99x7kr7+WZx8LCqrLgAHP0bPnA2p6JyIuoV+jioh4uQynk8gxY5j+/fc8l5HBNmA78KLTyexly+g+ahSp6emlEsvqLVvo8txz2HftYj4QD6wErjh8mNtefZXPli8vYAbvs/3AATo8+ST7N20iGtgP/A70Skri4Q8+4MWZMy9s4qxtGiIjkomq/l32Ng0xMerYWdri4//mySc7sHlzAvAFmav8G0lJ3Xn//YeYM+dlN0coIt5Kz+wVQM/siYinm/Xjj/R/7TWWAZ3PG/sFCAc+feQR7urSxeWxtH/iCdK3beNH08TvnOMWcAfwfcWK7Js+Hb8K5efWtjveeIMVP/7IOtOk+nljI4EJhsGeTz6hbrVqxftE0dH/NHChMyEhqvKVltdeu52ffvoZ01wHVD1v9BkM4w0+/XQvVavWdkd4IlIEnvbMnip7IiJe7tMffqCjYfwr0QO4Guhms/HJ99+7PI6t+/bxc1wcT5+X6AHYyExsjpw6xcLffnN5LGVF8unTzF61iodySfQAngB8geiYmOJ/sqwq39iQqUQcnZtjbz5xnZSUJH76aS6m+TD/TvQAnsKy7KxY8XlphyYi5YCSPRERL7fv8GGuNM08x1tZFvsOH3Z9HEePAnBlHuOXAQE2G/uOHHF5LGXFkaQk0pxOWuUxHgzUt9nYW1LvSdatnWP7biCK6OxbO7UZu+ucOHEI00wn76/8qhhGPY4e3VeKUYlIeaFkT0TEy9WqWpWt+TR/2GKzUatKFdfHERwMwNY8xncDpy0r+7zyoFrlythtNrbkMZ4C7HXFe+JwZFf5oojOUeVT0leygoKqY7MZ5P2Vn4xl7SU4uFZphiUi5YSSPRERL3dHly4stizW5TK2CVhgWdx5/fUuj+OKSy6h5cUX87rNhjOX8deAID8//tOunctjKSuCAgPp3a4dkwyDU7mMTwVOmiYDO3Uq+U9+bgOXc6p8auBSsipVqkrbtjdiGO+Smb6f7z0s6zSdOt1e2qGJSDmgZE9ExMsNuPZaWtWrxw2GwSdk/rh5GpgOdDEMmoSGcmfn3J7oK1k2m41X7r6bFUBvm43fyWzMsg0YCkwGxkRFUdHf3+WxlCWjBwxgv48PXW02lgEmmV1KRwJPAg/26kX9OnVcF4DDQeRTzbKrfBEsV5WvhA0cOAa7fTeGcT0Qwz+r/BwwghtvfJiaNS92Z4gi4qXUjbMA6sYpIt7gaFIS97zzDl/HxnLuP/o9W7Xi08ceK5XbOM+a/+uvDJsyhT3HjmUfqxoQwAtRUQy78cZyud/YL1u2MGTiRDbFx2cfC6xQgUd692bswIHY7fbSCSQ2FuLiGLnxVuKqhxNPKCEhEBVVOp/em23e/DNvv30P8fGbs4/5+lakT59Huf32FzEM/f5dxBN4WjdOJXsFULInIt5k+4EDrPzrLyzLokOzZjQODXVLHE6nkyUbNrD70CFqBAXRo00bAvzO79FZvliWxU+bN7N5714q+fvTo00bqlSq5J5gYmNZEFOJWBzE0RhCQrVNQwmwLIu//vqR/fu3EhBQmTZtelCxYvl5RlXEGyjZ8zJK9kREpFzKqvItiG9N9NEexFdvob35RKTc87Rkz8fdAYiIiEgZ5HBkPs8XGwsx3xHLUeLiGxMTH5o9LCIiZZuSPREREcmbw0GkAyKjp7IgvjWxOIiJ6UxcnKp8IiJlnZ4GFhERkYJlbdMwNmQqEUfn5tibT0REyiYleyIiIlI4WXvzje27IcfefNqmQUSkbFKyJyIiIkXjcGRX+aKIho1/aG8+EZEyyOOSvcmTJ1OvXj38/f1p164dsfl8V/nwww/p2LEjVatWpWrVqnTt2jXf80VERKSQsqp8kRHJRFX/LrvKFxOjhE9EpKzwqGRv1qxZDB8+nNGjR7N27VpatmxJt27dOHToUK7nx8TEMGDAAJYvX87q1asJCwvjhhtuYP/+/aUcuYiIiJdyOIh8qll2lS+C5aryiYiUER61z167du246qqrmDRpEgCmaRIWFsawYcMYMWJEga93Op1UrVqVSZMmceeddxbqc2qfPRERkULK2ptv5MZbiaseTjyhhIRAVJS7AxMRKRmets+ex1T20tLSWLNmDV27ds0+ZhgGXbt2ZfXq1YWaIyUlhfT0dKpVq5bnOampqSQlJeX4EBERkUJQAxcRkTLFY5K9I0eO4HQ6qV27do7jtWvXJiEhoVBzPP3004SEhORIGM83fvx4goODsz/CwsKKFbeIiEi5owYuIiJlgscke8U1YcIEZs6cybx58/D398/zvGeeeYbExMTsj71795ZilCIiIl5CDVxERNzOx90BFFaNGjWw2+0cPHgwx/GDBw9Sp06dfF/7+uuvM2HCBJYsWUKLFi3yPdfPzw8/P79ixysiIiJkVvkcEBk9lQXxrYnFQUxMZ+LioHHjzJxQRERcw2Mqe76+vrRp04alS5dmHzNNk6VLlxIeHp7n61599VXGjh3LokWLaNu2bWmEKiIiIufLqvKNDZlKxNG52VW+6Gh3ByYi4r08prIHMHz4cAYNGkTbtm1xOBxMnDiRU6dOMXjwYADuvPNOQkNDGT9+PACvvPIKo0aN4osvvqBevXrZz/ZVqlSJSpUque06REREyiWHAxwOxsbGsiBmO7E4iItvTHR0qKp8IiIu4FHJXr9+/Th8+DCjRo0iISGBK6+8kkWLFmU3bdmzZw+G8U+xcsqUKaSlpXHLLbfkmGf06NG88MILpRm6iIiInOVwEEkskXGZt3ZGb+xBTHwL3dopIlLCPGqfPXfQPnsi5VdSSgrRMTEsjI0lNS2NKxs25L/du9M4NNTdoV2QTxYv5qH33yc1LQ0A3woVeHPIEO7v2bPQc6SmpzNn1SrmrFrFyZQUGoeFcV+3brRu2LDQc1iWxY9//cUnS5awOyGBGlWqMDAighuvugofu73I11Uc+44c4bGPPmLFxo2YTif1Q0KYcOeddLnyykLP4XQ6+eb33/lseQwHTyRRr1YNBnftQkTz5thstkLPs37HDj74/nv+2rOfoEB/brkmnH4dO+Lv63sBV+ZBYmNZEFMps8pHY+IJJSJCCZ+IlE2ets+ekr0CKNkTKZ827tpF95EjOZiYSBebjSqWxVLD4Jhp8u5//8uDvXq5O8QiafvYY6zbvh0foDuZD2wvAtKAJmFh/DV5coFz7D96lBuee45N8fF0tNkItSxW2e3sczp58qabeOWuuwpMbjKcTgZPnEj0ihVcahi0NU22GQa/mSbtL7uMb154geCKFUvgigs2e9Uqol57Dadl0RUIBn4AEoEB117LF088UeAcJ1NS6PniOFZt2ojdaIXTbIKPsYYMM47bOnQkevhjVPDJ/yYay7J4Pjqal+fMwceoS4bZCcMWj2mtpGGdi1g2bgwX16xZEpdctkVH/9PAhc6EhKjKJyJlj6clex7ToEVEpLScTk2l5+jR1Dx5ku3A95bFLGCvaTIMeOj991m6YYOboyy8CXPmsG77dq4HDgBfA/Oy/v9GYMvevTzxySf5zmFZFje/9BInExLYAKy0LGYAO51OXgdemzePjxcvLjCWsbNmMWPFCqYDW02TL4BY02QF8Nfff3P3xInFuNLCO5KUxB2vvUYzy2IX8D0wm8z35CFgxsqVTPz66wLnuWfSe6zesgtYgtNcC3xBhrkFmMGcn1Yz6vPPC5zjs+XLeXnOHGA8GeZuYAamtQL4k92H7Nz44suUi9/LqoGLiEiJU7InInKeWatWse/4ceaYJpecczwAmAi0NgzenDfPPcFdgFFffEEAMAeods7xKsBMMitaE+fPz3eOVZs2Ebt9Ox+bJuduYOMDPA7cArw+d26+Scnp1FQmzZ/Pw8AdwLk1wGuBN0yTeb/+yvYDBwp9bRfqiU8+Id2y+BIIO+d4APA2cAXw6ty5+c6x+9Ah5vy0Cqf5KtDlnBEb0B/LGs6kb77n1Jkzec5hWRYT5n6FzRYJjAAqnDN6ORnmNDbu3s6yP/4o0vV5rKy9+cb23UAU0dl782kzdhGRC6NkT0TkPN+vXUu4YXBpLmM24A7T5Pt16zBNs7RDuzBOJ7cAlXMZCgD6A/YCruX7deuoY7fTNY/xO4GtCQnsPnQozznWbN/OsZQU7shjfACZ35QWr1+fbywlYcmGDVwDNMhlzADuAhISE/Nd46UbNmBZJhCVxxl3knwmmV+3bs1zjoTjx9m8bxeWNSiPMzrhY7+IRWvX5jmHV3I4sqt8UUTDxj+yq3xK+kRECs+junGKiJSGDKeTgHwqVIGA07I85tY6G5lJXV4K8zRyhtOJPzmrcecKOOe8/OY499zz+QJ2my3fOUqKaZr5XncAYGWdd26X53NlxmkD/POYJfMzZOSTMP5zrXm9KzZs+JfKe1LmZG3TEBkbCzHfEctR4uIbExMfmj0sIiL5U2VPROQ8jsaN+Qk4ksf4PJuNtvXrYy/lzpEXKh34CsjIZcwE5uYxdi7HpZeyy+kkr5sJvwJqV67MJbVq5TlH80suwc9uJ68n4RYBaZaFo3HjAqIpvhb16rECOJbH+JdAsJ8fPvk0V8mM0wIW5HHGPHwMH66sXz/POUKqVaN2lRpkvoO52US6cxvtSuE9KbMcDiKfapZd5Ytguap8IiKFpGRPROQ8g7t2xe7jw3/J7FZ5runAIsviof/8xw2RXZjb2rcngcwnws6tRVrAC8BuoGurVvnOEelwEFa1KkMNg8TzxpYBH9ls/LdXr3w7T1YPCmJgRAQTDIPz29scAB43DBwNG3LVpbndQFuy3hgyhAxgKJnJ8Lk+BZYCt193Xb5zXNmgAeGXXY6P8QSw77zRP7Eb47itQ3tqVamS5xx2u51hN3bHsE0js03MuU5iGP+lZnB1bg4PL/CavJ4auIiIFJm2XiiAtl4QKZ/m//ort06YQB0gyukkGPjGMFhpmgzp2pUPhw0r0h5q7hbcvz9JKSk0AW4n8zd9M4E/gUBfX04V0IwEIDYujm4jR+KTmsodpkkIsNJmY6FlcX3LlswfNQq/ChXyneNEcjJdnn2Wjbt309eyaAtsAz43DCpXrsyKV16hUUhIcS+3UJ6eNo3XvvySEGAQmY1qvgZ+BpqGhvLn5Ml53sJ51s6EBNo//RyHElNwmgOBxsBaDNtcmoZdxMrxY6lWObenJf+Rlp5On3ET+G7t7xi27pjWdcAB7MZ0/Cuc5ocXR3FN06Ylccne47y9+QgJ1TYNIlIqPG3rBSV7BVCyJ1J+/bFzJ28vWMCCX34hNT2dVg0a8EBkJLe2b+9Rid5ZnZ55hlV//ZV9S4cJtL30Un59441Cz7EzIYF3Fi5kzsqVJJ0+TeOQEO7r0YPBXbsWuJ/cWafOnOGD77/n40WL2H34MDUqVyaqSxce6tWL2lWrFv3CimH2qlU8N306uxMSsICgwEDuuv56Xhs8uMBE76zDiYlM+uYbPlkSw9GkREKr1+S/3bvw327dqFzI7xvpGRlMX7aMyd/+wNb9+6joF0D/a8N5JDKShnXrFuMKvVhsLMTFsSC+NdFHexBfvYX25hMRl1Oy52WU7ImIiJRh51X54gklIkIJn4i4hqcle+rGKSIiIp7L4SDSAZHRU1kQ35pYHMTEdCYuTlU+ERE1aBERERHPpwYuIiL/omRPREREvIPDAVFRjO27IXubBuL3a5sGESm3lOyJiIiId3E4sqt8UUTDxj+0N5+IlEt6Zk9ERES8j8ORmfTFxkLMd8RylLj4xsTEh2YPi4h4OyV7IiIi4r3UwEVEyjHdxikiIiLeTw1cRKQcUrInIiIi5YMauIhIOaNkT0RERMoXNXARkXJCyZ6IiIiUP1lVvsiIZGY1H5dd5YuJUcInIt5DDVpERESk/Mrq2jlWDVxExAupsiciIiKiBi4i4oWU7ImIiIiAGriIiNdRsiciIiJyLjVwEREvoWf2RERERM6X9SxfZGwsxHxHLEeJi29MTHxo9rCISFmnZE9ESpRlWexISCAxJYV6tWpRrXJld4fkNXYfPMjPW7ZQrXJlrr/ySgzDPTdnWJbF9gMHOHn6NJcUY43/2rOH9Tt20KBOHcKbNLmgOU6dOcPf8fH4+vhwWWgodrv9guYR7+Z0Otm6fz9pGRlcGhJCRX//wr/Y4SDSAZFq4CIiHkjJnoiUmAWxsbwQHc3aXbsAqGAY3NK+PRPuuouLa9Z0b3Ae7I+dO7n55ZfZefAgZtaxij4+3NuzJ2/dc0+pxvLVL78w5vPPWb97N5C5xrd26MArd93FRTVqFGqOhb/9xn3vvENCYiJW1rEq/v6MHjiQR3v3LtQcyadP83x0NJ/+8ANJqakA1KtenSduuYUHevbEZrMV+drE+1iWxZTvvmPC3K/YeyQBgEC/QO65oQsvDRxI5cDAwk8WFUVkbCyRcVMZufEocYQTEx9KXBxERbnoAkREislmWZZV8GnlV1JSEsHBwSTOnElQUb4piJQz/7d0KXe9/TZdbDYesiwuAn4E3jAMCApi9RtvEKaEr8j+2rOHtg8/TEXT5CmgM3AQeA/4Dri1fXtmP/10qcTyyeLFDHn3Xa632XjQsggFVpK5xvbgYFa/+Sah1avnO8fXv/7KLePGEQY8BVwFbAPeBH4DRg8YwOgBA/Kd43RqKtc9+yx/bt/Ow6ZJJHAKmAZEA8N79+aNIUOKebXiDZ769FNemzcPGAjcBVQGFmA33ubK+iGsnDCOQD+/ok8cG8uCmErE4iCOxhASqiqfSDmRkpJE//7BJCYmEhQU5O5wCqRkrwBK9kQKdjIlhdBBg7g5NZVPgXNrKgeAtoZBl2uvZfrw4W6K0HO1GDaMvbt3sw6od85xC3iYzKTvz8mTaRoW5tI4Ek+dInTQIPqnpfEhOdd4P5lr3KNzZz555JF856k5YABVT50iFqhyzvEM4D/AUpuNxDlz8Pf1zXOON7/6ihGffspPlsVV5429BQwH1r/9Ni3r1y/09Yn3+WPnTlo+8gjwGvDEeaNrMGzX8MpdA3nippsu7BPExkJcHAviWxN9tAfx1VsQEqJbO0W8nacle+rGKSLFNmvVKk6lpvISOZMAgLrAI6bJ7B9/JCklxQ3Rea6klBQ27d7Ng+RM9CDzfR4N2IFnpk93eSwzVq4kNT2dF/n3GocCw0yTGStWcDKfNV75558cOXWK58mZ6EHmMwUvAWmWxYS5c/ON5cPvvqNvLokewENAiGHw4fff539B4vU+WrwYH6M2kNsvINpgWrcy5dvFF/4JsrZpiIxIZlbzcdnbNMTEqGOniJQdSvZEpNi2HTjAJXY7F+Ux3h5IdTrZf/RoaYbl8Tbv3YuTzPcvNzWAS4EdCQkuj2V7QgL1DYOQPMbbA2cyMjhw/Hiec/waF5d9bm5aA77AxqznAfOM5eBBOuQxVgFoZ5psP3Ag3znE+207kECGeTWZXxW5ac+uQyXwdXJ2b76sbRoiWK5tGkSkzFCyJyLFVqViRQ5bFnnVdM7+6B6sW6GLpG61agDsyWM8nczbZEvjFvMqFSty0LI4k8d4Yda4btWqQN7XcxBIA6oX0N2zSmAg+aWDuw2DKpUq5TuHeL+qlSpiN3blc8ZuKgeU4NdJVpVvbMhUIo7Oza7yRUeX3KcQESkqJXsiUmy3tm/PKdPk01zGnMAkw6BjkyaEFNC8Q3K6uGZNagUF8S6ZSdD5ZgDHgccK2cGyOG7r0IEk0+T/chnLACYbBp0vv5zaWQldbvp37EiAYTARyO1h8XfJ/Kb0zC235BtLv06dmGYYnMhlbBWw1jTp37FjvnOI9+vXoQNOcwOZbYTOl4iP8SlREXnVmS/Q2Spf3w3ZVT7i96vKJyJuo2RPRIqtYd26DO7SheE2G28DyVnH44B+wK+WxeiBA90XoAcbd8cdbAL6AJuyjqUA7wP3AWHVqtH3mmtcHselISEM6tyZh2023iWz+yXAVuA2YI1lMer22/Odw8fHh3t69mQ+cA+wN+v4ceBF4GUgvGlT6tepk+88w3v3Jt3PjxsMg1/ITBzTgTnATYaBo2FDel2V2xN9Up70atuWqy5tgt24CZhN5leJBfyK3bgBf98Uhvfp45pP7nBkV/miiIaNf+jWThFxC3XjLIC6cYoUTlp6Og9NncrHS5bgC1Q1DA44nVSvWJH3hw0rlYTEW704cyYvffEF6UBN4CRwBmhQqxa/vfkm1UqpG1hqejoPTpnCJ0uW4G+zUSVrjWtUrMiHjzxCn6uvLtQ8d775Jl/ExGCS+dzhcTIrwI7GjVk1YQI+PgVvAbt2+3ZuGz+e7YcOUctu57RlcdI0uaFFC7546imqe0CHNHG9YydP0v+1N1m8fg12oxI2WwAZzsNcXLMu/xvxBG0vvdT1QZy3TUM8oUREqGOniKfytG6cSvYKoGRPpGj2HD7M/37+maSUFC4NCeHm8PB82+hL4SSnpDDqiy9Yt2MHlQICeKx3b65r0cItsew6eJB5v/xCUkoKjUNCuOkC1jj+6FGe//xzdhw4QM3gYEb3788V9eoVaQ6n08kP69fz299/4+vjQ482bbTdguTqj507+XbNGtIyMmjbqBHdWrXCbreXbhDR0SyIb00sDmLorG0aRDyUkj0vo2RPRERESkTW3nwjN95KXPVw4gklJASiotwdmIgUlqcle3pmT0RERKQ0qIGLiJQyJXsiIiIipUkNXESklCjZExERESltWVW+yIhkZjUfl13li4lRwiciJafglmciIiIi4hoOBzgcjI2e+k8Dl5jOxMWpgYuIFJ8qeyIiIiLullXlGxsylYijc7OrfNHR7g5MRDyZkj0RERGRskANXESkhCnZExERESlL1MBFREqIkj0RERGRskYNXESkBKhBi4iIiEhZpQYuIlIMquyJiIiIlHVq4CIiF0DJnoiIiIgnUAMXESkiJXsiIiIinkQNXESkkJTsiYiIiHgaNXARkUJQgxYRERERT6UGLiKSD1X2RERERDydGriISC5U2RNxs/U7dvDZ8uUknDjBRdWrc1eXLjQNC3N3WG4VvXw5I6ZP53hyMgG+vvy3e3devP127HZ7oefYc/gwj3/8MWu3b8dut3Nj27a8FBVFoL9/oec4k5bGmBkz+HL1atKdTppfcglvDhlCw7p1i3Q9n8fE8MZXX3EsOZnaVaowun9/erZtW6Q5Dhw7xqdLlrBp714qBQTQNzycLi1bYhiF/53d6dRUZq9axfKNG7Esi2svv5wBnToR6OdX6DksyyJm40bm/PQTSSkpXBYayuCuXbmoRo0iXY+IuMDZKl9sLAtithOLg7j4xkRHh6rKJ1JO2SzLstwdRFFMnjyZ1157jYSEBFq2bMm7776LI59/vebMmcPIkSPZtWsXl156Ka+88go9e/Ys9OdLSkoiODiYxJkzCQoMLIlLEAEgPSODu99+m+gVK6hrt9PYstgEHDZNHujRg3f/+98i/SDvDZxOJ5cMGcL+Y8cIAloAO4B4INDHh7gPPiC0EEnFmBkzGDtjBgBtgWTgL8DfMPhq1Ci6tW5d4Bw/bd7MDc8+S4rTSROgCvA7YAKP/Oc/vHnPPQXOkZySwhXDhrH78GFqAZcCm4DjQItLLmHNW2/h41Pw79ymfvcdD7//PhWANsBBm404p5OrGzViwQsvUCMoqMA51mzbRuSYMRxITKStYWAAv5kmNSpV4quRI7mmadMC5zienEyfsWNZuXkzDe12Qi2LtcBpy+K1u+/msd69C5xDREpJbCzExbEgvjXRR3sQX70FISG6tVOkuFJSkujfP5jExESCCvH919086ifJWbNmMXz4cEaPHs3atWtp2bIl3bp149ChQ7me//PPPzNgwACGDBnCunXr6NOnD3369OHPP/8s5chF/u2pTz9l1sqVfALscTqJMU32mSbvAFO++46XZs92d4ilrs3w4ew/doxxQALwI7AHmAU4MzJo9sADBc4xb/VqXpwxgx7AXuAX4E9gAxBmmvR+8UWOJCXlO0fKmTNc/+yz1HA6iQU2A6uB/cCtwMT58/l48eICY2n/9NPsP3yYaVmvXQUcACYCG3fvpueLLxY4xze//cb9U6Zwn2kSb5qsNE22OJ0sBXbs2MHNL71EQb+zO3TiBN1GjiTs5En+JjPJ+9U02Q40SUmh5+jR7DtypMBY+r/yCn9u3coi4G+nkxVZMT1iWQz/+GPm/vRTgXOISClRAxcRwcOSvTfffJN7772XwYMH06xZM6ZOnUpgYCCffPJJrue//fbbdO/enSeffJKmTZsyduxYWrduzaRJk0o5cpGcjp08ydTvvmOUZTGYf+6n9gWGAY8CE+fN43RqqrtCLHXJp0/z186dDAKeBQKyjtuB24DXgZNnzjD/11/znefpadOoA8wFzr3ZsgXwDZBmmjw1bVq+czwfHc1pp5OvgKvOOV4LiAYaAWO++CLfObbu38+fu3fzIjCIf9bYD3gEeAiIWb+eE8nJ+c4zYfZsrrXZeBcIzjpmA64DppkmP27Zws+bN+c7x4c//EBKSgoLTZNG5xyvD8w3Tcy0NKYuWpTvHGu2beOHDRv40DTplhUDQGUy16abzcbLM2cWmHiKSCk7uzdf1jYNESzXNg0i5YjHJHtpaWmsWbOGrl27Zh8zDIOuXbuyevXqXF+zevXqHOcDdOvWLc/zAVJTU0lKSsrxIVLSfli3jjMZGeR1I+A9wPHTp/lx06bSDMutXvvySzKAe/MYH0TmP1hjZ83Kd55dBw5wN5lJ1fkuBToC3/3+e75zzPvlF64EWuUy5kPm+uw7ehTTNPOc4+358zGzzs3NPUA65FshPJqUxKqtW7nHsrKTq3N1Ay6y2/m6gAT4659/po9lUTOXsSrAbabJ1wVU5ebHxlLDbie3GzVtwD2Wxbrdu9l/9Gi+84iIm6iBi0i55DHJ3pEjR3A6ndSuXTvH8dq1a5OQkJDraxISEop0PsD48eMJDg7O/ggr540yxDVOp6UBUC2P8epnzytHlb0Tp04B/1z7+SoBFchsmpIfk7zfV4CaQEZGRr5zpGVk5BkHZMZoFTDPqTNnAKiazxwAJ0+fznOOgr5OjKz5TxfwnpxOTc33PalOwV9rp1NTCSaz0prXHBQiFhFxo7NVvr4bsqt8xO9XlU/Ei3lMsldannnmGRITE7M/9u7d6+6QxAu1rF8fgO/zGD97Q13zevVKI5wyoW/79tj459rPtwo4A4Q3aZLvPJX8/Pguj7HTwBLgkjp18p3jstBQfgbyqut/S2bDGF9f3zzniGjeHIAf8hg/e53Xt8qtfpipTtWq1KpUKc+vkz3AX04nLQr4OmnRsCE/GAa51SEt4DvDoEXDhvnPUa8e251O/s5jfBFQJSCAMHXlFCn7HI7sKl8U0bDxD93aKeKlPCbZq1GjBna7nYMHD+Y4fvDgQerk8YNbnTp1inQ+gJ+fH0FBQTk+REpa64YNcTRsyLOGwbHzxg4AYwyDbi1b0qCApMSbXHv55QT6+vIymR04z3USGE5mZW/SffflO89tnTqxGPjyvOMWMApIBMbfcUe+c7w6eDBngCfhXwnS98BXQM8C2tkNuu46KleowFNkdt88137gBaB2UBDt8+mC6WO3c2/PnnxsGPx23lg68BhQyd+fAddem28s9/fsyd+myVu5jE0FNpomQwvoUnxL+/bUqFiRR202zq8BbgCmGAaDb7gB/3wSYBEpQ9TARaRc8Jhkz9fXlzZt2rB06dLsY6ZpsnTpUsLDw3N9TXh4eI7zARYvXpzn+SKl6ZPHHuNAQABXGAajgZnAM0ALwyAtKIgpDz7o5ghL3/yRIzkBtAQeJ/M9GQc0AdYBT992W77VNMhMBi+uXp1bgFvIbKjyPhBOZiORPu3a5VtNA2jbqBF3dO7MB2Ru3fAe8DkwAOgF1AwK4v8efTTfOQzD4NPHH2drVvxjsq5nBHAFcNhm43/PPZfvHADP3HILLRs25FqbjXuBGcBbwJWGwXzDYPrw4VQKCMh3jg7NmvF03748Adxgs/EJMA3oabPxAPDwjTdy/ZVX5juHv68v0U8+yVLDoKVh8EZWLPcD1xgGl158MS8MGFDg9YhIGaMGLiJezaP22Zs1axaDBg3i/fffx+FwMHHiRGbPns2WLVuoXbs2d955J6GhoYwfPx7I3HqhU6dOTJgwgV69ejFz5kxefvll1q5dyxVXXFGoz6l99sSVdiYk8MqXXxK9bBmn0tII9vdn0PXX8/TNNxNSPb+nxrzXL1u3ctPLL3Pk+HEyyPyNVEV/f94YMoR7u3Ur1BxpaWncOXEiC1avJsXpBKB6YCDDevdmdBESkte+/JLX//c/Dp08CUCAYdDtqqv4/PHHC705e8zGjdw/ZQp/79uHk8wGL80bNOCThx/mygYNCjVHSmoqb339Ne9/8w17jx/HbrPRu107nurbl3aXXVaoOSzLYvaqVbw1bx6/btsGQJv69XmkTx+iIiKw2XJrAfNva7dv55W5c/ly9WoyTJOQ4GDu7dGDx/v0obL+jRTxbFl7843ceCtx1cOJJ5SQEIiKcndgImWHp+2z51HJHsCkSZOyN1W/8soreeedd2jXrh0AERER1KtXj2nntFWfM2cOzz//fPam6q+++qo2VZcyx+l0cio1lUr+/uVuI/W8pKWlsevQIcKqVyeggMpVXkzT5EhSEv6+vsX6+5uckkJKWho1goIueH3S0tI4cvIktYKDC7WRem4syyL59Gn8fX2pcIFzwD/NWAL8cutZWjgZTienU1OpFBBQ6ERRRDxEbCwLYioRi4M4GkNIqDZjF8miZM/LKNkTERGRcieryrcgvjXRR3sQX70FISEo6ZNyz9OSPZUQRERERCQnNXAR8QoXfh+QiIiIiHg3hwMcDsZGT2VBfGticRAT05m4OFX5RDyBKnsiIiIikr+sKt/YkKlEHJ2bXeWLjnZ3YCKSHyV7IiIiIlKws9s09N2QvU0D8fu1TYNIGaZkT0REREQKz+HIrvJFEQ0b/9DefCJllJI9ERERESkaNXAR8Qhq0CIiIiIiF0YNXETKNFX2RERERKR41MBFpExSsiciIiIixacGLiJljpI9ERERESk5auAiUmYo2RMRERGRkqUGLiJlghq0iIiIiIhrqIGLiFupsiciIiIirqUGLiJuoWRPRERERFxPDVxESp2SPREpcafOnOHg8eNkOJ0XPEdaejoHjx/ndGpqCUZ2YZJSUjicmIhpmm6NI8Pp5NCJEySfPu3WOEpKWVpjESlFauAiUmr0zJ6IlJhftmzh5dmz+WbNGkzLolpgIINvuIHnbruNqpUqFWqOhOPHeWnWLKYvXcrJ1FR8DIObrr6a5/v1o0X9+i6+gpy++e03Xpkzhx+3bAHgoqpVGdqrF0/cdBN+FSqUWhwnU1IYP3cuHy1axOHkZAC6tWzJM/360emKK0otjpISf/QoL82ezWdLl5KcloaPYdD3mmt4vl8/rrjkEneHJyKlIetZvsjYWCLjxjEyfihx8Y2JiQ/NHhaR4rNZlmW5O4iyLCkpieDgYBJnziQoMNDd4YiUWQt/+42bx42jCfBf0+Qi4EfgI8MgtE4dVr76KtWDgvKdY9+RI3R48klOHT/OUNPkKmA7MMUw2G+38/3YsXRo1sz1FwNMWriQYR98QEfDYLBpUgX4Fphus3HtFVew8IUXSiXhS0pJofOIEcTt2cPdpsl1QALwoWGw3rL4/Ikn6Nexo8vjKCl7Dh+mwxNPcCYxkaGmSVtgG5lrfMDHh8UvvUR4kybuDlNESlt09D8NXOhMSIgauEjZlJKSRP/+wSQmJhJUwM81ZYGSvQIo2RMp2Jm0NC4aNIj2KSnMtSzOTYG2AtcYBv26deO9++/Pd55bxo/n119/ZXVWsnhWCtDdZmN/jRr8/eGHGIZr70Dfc/gwDe65h4csi7cA2zljMcD1Nhuv3X03j/bu7dI4AJ6eNo33vvqKVaZJy3OOO4E7gAW+vuyfPt1j/n266aWXWPv776w2TULOOX4K6GYYHKpZky3vv+/yNRaRMig2FuLiGLnxVuKqhxNPKCEhEBXl7sBE/uFpyZ6+m4pIsc396SeOnjrFG+clegCXAcNMk8+WLuXUmTN5zpFw/Dhf/fILI85L9AACgVctix2HD7N4/fqSDT4XH/3wAxVtNl4iZ6IHEAHcYllM/eYbl8eRnpHBx99/z33nJXoAduB14HRaGp/HxLg8lpKw/+hR5v/2G8+el+gBVAQmmCZ/HzzI8o0b3RGeiLibGriIlDgleyJSbH/t2UM9u51GeYx3BZLT0th75Eiec8Tt34/TsuiSx3g7oKJhsGnv3mJGW7C/9uzhassir6cMuwJbExJwFqMBTWEcPHGCo6dO5fmehACX2+2l8p6UhK379mHms8btAX+bzWOuR0RcRA1cREqMkj0RKbaK/v4ctyzS8hg/lPXfQD+/fOc499zzJQFnTDPfOUpKRX9/DtnOr+n94xDg5+Pj8lsNz15rXu+JCRwh//e1LClojU8AqZZFoK9vaYUkImVVVpUvMiKZWc3HZVf5YmKU8IkUhZI9ESm2m8LDSTRNZucyZgHv22y0qV+fsBo18pzjyvr1uaR6dd7PY/wTAJuNyKuuKn7ABbjp6qtZb5rk9vNEGvCJYXBzeDi2fBLCklCtcmUimjXjQ8Mgt00fFgLxTic3h4e7NI6S0qZRI8KqVs1zjT8CfAyDXqWwxiLiIc7e2plV5Ytguap8IkWgZE9Eiu3yiy/mJoeDBwyDuWQ2DwE4BjwM/GBZPNe/f77Jkd1u59l+/fgCeJ7MSh5AOvAp8IzNxt1duxJSvbrrLiRLpMNBi7Aw+hoGK8hMWAH2ArfZbOyx2Xji5ptdHgfAM/36sdo0uYd/KmImmYneYMOgyxVX4GjcuFRiKS4fu51n+vVjOjAaOJl1PA34GHjeZuOeG26gTtWqbotRRMqorCrf2JCpRBydm13li452d2AiZZu6cRZA3ThFCif59Gn6v/IK36xdS4jdTgjwp2liGgZv3XsvD/TsWeAclmUxbvZsXvjiCwJsNprYbOwBDjmd3H7ttXzyyCOltr9d/NGjRI4Zw9pdu2hgtxMMbHA6qeTvz+dPPsmNpVh9+r+lSxk6eTKm00lzw+AQsNfppPPll/O/554r9B6GZYFlWbw4cyYvzpxJYNYa7wYOO51EderExw8/jG8p7mEoIh4oNpYFMZWIxUEcjSEkVNs0SKnxtG6cSvYKoGRPpGh++/tvZv34I0kpKVwaEsKg666jVpUqRZpj35Ej/N+yZew6dIjqlSszsFMnmter55J482OaJks3bGDBb7+Rmp5OqwYNGNipE5Xd8G/B0aQkPlu+nE1791IpIIC+4eFc07Spy28ldZW9hw/zf8uWsfvwYWpUrszAiAhtqC4ihZe1TcOC+NZEH+1BfPUW2ptPSoWSPS+jZE9ERESkjDq7N1/8UOJoTDyhREQo4RPX8bRkz8fdAYiIiIiIXBCHAxwOxkZPZUF8a2JxEBPTmbg4VflEQA1aRERERMTTqYGLSK6U7ImIiIiI5zu7TUPfDdnbNBC/X9s0SLmmZE9EREREvIfDkV3liyIaNv6hvfmk3FKyJyIiIiLeJavKFxmRzKzm47KrfDExSvikfFGDFhERERHxTmrgIuWcKnsiIiIi4t3UwEXKKSV7IiIiIuL91MBFyiEleyIiIiJSfqiBi5QjSvZEREREpHxRAxcpJ9SgRURERETKJzVwES+nyp6IiIiIlG9q4CJeSsmeiIiIiIgauIgXUrInIiIiInKWGriIF1GyJyIiIiJyLjVwES+hBi3lwOnUVOb+/DN/7t5NoJ8ffa6+mpb167s7LCljTNNk2R9/sHzjRizLon3TpnRv3Rq73V6kebbu28fcn38m8dQpGoeG0q9DByoHBrooahERERdSAxfxcDbLsix3B1GWJSUlERwcTOLMmQR54A+sC3/7jUFvvMGxlBQa2O0ctyyOmyaRbdoQ/eSTHnlNUvJ2JCTQZ+xYNu7dS127HTuwz+nk0tq1mTdyJJdffHGBc5xJS+Oed97h85UrCTIMatps7HQ6qejnx5QHH2RgRITLr0NERMRlYmMhLo6RG28lrno48YQSEgJRUe4OTEpTSkoS/fsHk5iYSFBQkLvDKZBu4/Riv27dys3jxtHh9Gn+BrY7nRw0Tb4AVqxbx23jx6NcX5JSUuj67LOc2b+fGGC/08kep5PVQMDhw3R99lkOnThR4Dz3vvsu//vxRz4ADpom25xOdgG9U1O54803WbRmjSsvQ0RExLXUwEU8kJI9L/by7NlcBsy1LBplHasADACmmSbfb9jAr1u3ui9AKROmL1vGniNH+N406QTYsj6uBn4wTZKSk3l/0aJ854jbv5/oFSt4x7K4F/DPOh4G/B/Q0WZj7IwZLrwKERGRUqIGLuJBlOx5qZTUVBb+/jv/NU0q5DLeG7jIbmf2Tz+VdmhSxsxeuZJeQG5PcdYGbjVNZq9Yke8cc3/6icqGwR25jBnAA5bFz3Fx7D96tPgBi4iIuJsauIiHULLnpU6dOYNpWYTmMW4AIWTewiflW9KpU3l+nQBcRMFfJ0mnT1PDZsuu6OU2B4WYR0RExKOcvbUzq8oXwXJV+aRMUbLnpapVqkT1ihX5MY/xY8AfpknjkJDSDEvKoMZhYfxoGOT19OYKw6DxRRflMZrpstBQdjud7M5rDsDfx4eLqlcvTqgiIiJlU1aVb2zIVCKOzs2u8kVHuzswKe+U7Hkpu93OkG7d+Mgw2HTemAWMAkzD4K4uXdwQnZQl93Xvzp+myf/lMvY1sMo0+W/PnvnOcVuHDlT292cE4DxvbA/wjmFwe0SEtmAQERHvpQYuUgYp2fNiz9xyC/VCQ2lvGDxPZnVlDnCDzcZk4K1776VWlSpujVHcr0vLlgzp2pW7gUHAd8APwH3ALTYbfa++mpuuvjrfOSr6+/P+sGHMttm41jD4HFgJvARcZRgEVqvGuDtye6JPRETEy6iBi5Qh2mevAJ6+z97x5GRGff45/7dkCSdTUwFo26ABz/brx03h4W6OTsoK0zR5Z8EC3v7qK3ZlNVEJrVKFByMjefLmm/Ep5Mbqi9etY+yMGfy4ZQsAARUqMKBTJ16KiqJutWoui19ERKRMOrs3X/xQ4mhMPKFERGgzdk/mafvsKdkrgKcne2elpKay78gRAv38uKhGDXeHI2WU0+lk16FDWJZFvdq1C53kne/AsWMkpaQQWr06lQICSjhKERERDxMdzYL41sTiIIbOhIRA48ZK+jyRkj0v4y3JnoiIiIi40dkq38ZbiaseTjyhhIRAVJS7A5Oi8LRkz2Oe2Tt27BgDBw4kKCiIKlWqMGTIEJKTk/M9f9iwYVx22WUEBARw8cUX8/DDD5OYmFiKUYuIiIiIoAYu4hYek+wNHDiQv/76i8WLF7Nw4UJWrlzJfffdl+f58fHxxMfH8/rrr/Pnn38ybdo0Fi1axJAhQ0oxahERERGRc6iBi5Qij7iNc/PmzTRr1ozffvuNtm3bArBo0SJ69uzJvn37CCnkXnFz5swhKiqKU6dO4ePjU6jX6DZOEREREXEJNXDxOLqN0wVWr15NlSpVshM9gK5du2IYBr/++muh5zm7KPkleqmpqSQlJeX4EBEREREpcWdv7cyq8kWwXFU+KVEekewlJCRQq1atHMd8fHyoVq0aCQkJhZrjyJEjjB07Nt9bPwHGjx9PcHBw9kdYWNgFxy0iIiIiUqCoqOxbOyOOzoX4/dlJn0hxuDXZGzFiBDabLd+PLVn7dRVHUlISvXr1olmzZrzwwgv5nvvMM8+QmJiY/bF3795if34RERERkXypgYu4QOEeXHORxx9/nLvuuivfcxo0aECdOnU4dOhQjuMZGRkcO3aMOnXq5Pv6kydP0r17dypXrsy8efOoUKFCvuf7+fnh5+dXqPhFREREREqUw0EksUTGTWVBfGuiN/YgJr4FcXHam0+Kzq3JXs2aNalZs2aB54WHh3PixAnWrFlDmzZtAFi2bBmmadKuXbs8X5eUlES3bt3w8/Nj/vz5+Pv7l1jsIiIiIiIu4XBkJn2xsUTGjcts4BLfmJj40OxhkcLwiGf2mjZtSvfu3bn33nuJjY3lp59+4qGHHqJ///7ZnTj3799PkyZNiM2qcyclJXHDDTdw6tQpPv74Y5KSkkhISCAhIQGn0+nOyxERERERKVhuDVz+d1S3dkqheUSyB/D555/TpEkTunTpQs+ePenQoQMffPBB9nh6ejpbt24lJSUFgLVr1/Lrr7+yceNGGjVqRN26dbM/9ByeiIiIiHiMcxu4ZD3LpwYuUhgesc+eO2mfPREREREpM2JjWRBTiVgcxNEYQkL1LF8p0j57IiIiIiLiGg5HdpUvimjY+If25pM8KdkTEREREfEkWc/yRUYkM6v5uBy3dirhk3O5tRuniIiIiIhcoKyunWOjM7dpiMVBzP9aEBdXXbd2CqDKnoiIiIiIZ1MDF8mDKnviUeKPHuXud95hxYYNnDFNKgDN6tdn8tChtG/atFRjiV6+nOejo9l3+DAmUMnXl74dO/L+/ffj6+tbanGkZ2Tw0Q8/MPWbb/hr3z4q+vlx8zXX8PhNN3HFJZeUWhwlJSklhUkLF/LxokXsOnqU6hUrcnvnzjzepw9hhdiXE8CyLGauXMmkBQv4bds2fOx2urduzeM33UT7Zs1cfAUiIiJucLbKFxvLgpjtmQ1c4hsTHa0GLuWZunEWQN04y46dCQm0ePBB0tLTGQC0A3YCHwEngRlPPcUtHTqUSixPfvIJb3z1FZcAQ4CqwDfAIiCsenX+fv/9Ukn40tLT6T12LIs3bKA30MWyOARMMwwOGgbzR47k+latXB5HSTl28iSdR4wgbt8+BlgWDmA78KlhYAQGsmz8+AITWMuyGDp5Mh/88ANdbTb+Y1mcAqINg02myUfDhnH39deXxuWIiIi4R2wsxMWxIL410Ud7EF+9BSEhKOkrAZ7WjVPJXgGU7JUdTYYO5UB8PKuA5uccPwZ0BrbZ7Zz83/8wDNfenbx1/36a3X8/twDRQIVzxr4EbgEGdOrE548/7tI4ACbMncuozz7jW8ui6znHzwA322z8EhDA3mnTqOjv7/JYSsLgiROZHxPDStPk8nOOHwWuMwyskBA2TJ6MzWbLc47Zq1bR79VX+RS465zjJnA/8LHNxrYPPqBe7dquuAQREZGyIyvpGxk/lDgaE08oERFK+IrD05I9PbMnHmH3wYP8HR/P0+RM9ACqAW8DKU4nE+fPd3kswz/+GDswmZyJHsDNQCTw9U8/uTwO0zR5b8EC7jgv0QPwByZbFidSUpi5cqXLYykJx06eZMaKFTx1XqIHUB14wzTZuG8fqzZtyneeyQsWEGEYORI9yPzH7k2gks3GB99/X2Jxi4iIlFlZXTvPbtMQwXJi/ndU2zSUI0r2xCN8v349JpmJVG46AYHA0j/+cHksG3ftIhyokcd4b+BURgbJKSkujeNwYiJ7jx/P8z2pD7Sw2/l92zaXxlFS/tqzh1SnM8/r6QIE2GwFXs+a7duJNM1cxyoC15kmv//9d7FiFRER8Shq4FJuKdkTjxCY9fzbyTzGU4F0wL/C+bW2klfBbicpn/GzMfr6uLb/kW/Wteb1nlhZY76l8J6UhLPvV17Xc5rMNS7offW12/OcA+CkzYafh7wnIiIiJeZsla/vhuwqH/H7VeXzckr2xCPcHB6Or83GtDzGZ5GZCAzt3t3lsfS66irWAxtzGTOBT4FaQUEub9BStVIlrm7UiGk2G7k9eLsK2OF00qttW5fGUVJaNWhA7cqV81zjGYDTsujeunW+8/R0OPjMbicjl7E9wDLLotdVVxUvWBEREU/lcGRX+aKIho1/ZFf5lPR5HyV74hEC/f25vk0bPgQmQfYP8hawBBgGhFapUiqdJ1+OisLfMLgZ2HLO8WTgQWAD8FTfvi6PA+CpW29lmWXxDJmVr7PWAVGGwZWXXELXli1LJZbi8q1Qgcduvpn3gffIucbfA8MNg77h4TSsWzffeR7r3ZtdpsldwIlzju8EbjIMagUFMbBTpxKPX0RExGNkVfkiI5KZ1Xxcjls7lfB5F3XjLIC6cZYdGRkZtH7sMTbu3k1tMrde2AZsAqoGBLB+0iQuLuQ+bMW1eN06IseMIdU0CSezScxyMhOuqIgIpg8fXipxALw+bx5PffopVQyDDqbJQcMg1jRpFhLCorFjC703XVlgmiYPvf8+U777jovsdto4nWwzDP4yTTpffjlfjRxZqL+Hs378kTvffBMf0yTCsjhls7HSsqgTHMx3L75Iy/r1S+FqREREPER0NAviWxOLg5ijLQhpXl3bNOTB07pxKtkrgJK9smfGihWMnzuXhOPHqRwQwOCuXRnRty8+Ln5G7nzHkpIYMX06365ZQ0ZGBpeGhPDq4MGEN2lSqnEAbIuP58MffuCvPXuo6O/PzeHh3HT11R7zvN751m7fzseLF7Pr4EGqZ1Xirr/yyiJtq3Hg2DE++uEHfvv7byr4+NC9dWtu79TJY7ahEBERKVVnt2nYeCtx1cOJJ5SQEIiKcndgZYuSPS+jZE9EREREyo3YWBbEVCIWB3E0hpBQVfnO4WnJnp7ZExERERGRTGrg4lWU7ImIiIiIyD/UwMVrlO5DTiIiIiIi4hkcDnA4GBs99Z8GLv9rQVycGrh4ClX2REREREQkb1lVvrEhU3NU+aKj3R2YFETJnoiIiIiI5C/r1s6xfTcQRXR20qdn+co2JXsiIiIiIlI4auDiUZTsiYiIiIhI4amBi8dQgxYRERERESk6NXAp81TZExERERGRC6cGLmWWkj0RERERESkeNXApk3Qbp4iIiIiIlAyHg0hiiYzLvLUzemMPYuJbEBfn7sBKRnq6uyMoGiV7IiIiIiJScrKe5YuMjSUybhwj44cCoe6OqkSkkuzuEIpEyZ6IiIiIiJS8cxq4eIsk0nnN3UEUgZI9ERERERFxnagod0dQclJSYN48d0dRaGrQIiIiIiIi4oWU7ImIiIiIiHghJXsiIiIiIiJeSMmeiIiIiIiIF1KyJyIiIiIi4oWU7ImIiIiIiHghJXsiIiIiIiJeSMmeiIiIiIiIF1KyJyIiIiIi4oWU7ImIiIiIiHghJXsiIiIiIiJeyMfdAZR1lmUBkJSS4uZIRERERETEnc7mBGdzhLLOZnlKpG6yb98+wsLC3B2GiIiIiIiUEXv37uWiiy5ydxgFUrJXANM0iY+Pp3LlythstnzPTUpKIiwsjL179xIUFFRKEUpBtC5lk9albNK6lE1al7JJ61I2aV3KJm9ZF8uyOHnyJCEhIRhG2X8iTrdxFsAwjCJn7UFBQR79ReyttC5lk9albNK6lE1al7JJ61I2aV3KJm9Yl+DgYHeHUGhlPx0VERERERGRIlOyJyIiIiIi4oWU7JUgPz8/Ro8ejZ+fn7tDkXNoXcomrUvZpHUpm7QuZZPWpWzSupRNWhf3UIMWERERERERL6TKnoiIiIiIiBdSsiciIiIiIuKFlOyJiIiIiIh4ISV7IiIiIiIiXkjJXjEdO3aMgQMHEhQURJUqVRgyZAjJycmFeq1lWfTo0QObzcZXX33l2kDLmaKuy7Fjxxg2bBiXXXYZAQEBXHzxxTz88MMkJiaWYtTeZ/LkydSrVw9/f3/atWtHbGxsvufPmTOHJk2a4O/vT/Pmzfn2229LKdLypSjr8uGHH9KxY0eqVq1K1apV6dq1a4HrKBemqH9fzpo5cyY2m40+ffq4NsByqqjrcuLECR588EHq1q2Ln58fjRs31r9lLlDUdZk4cWL29/iwsDAee+wxzpw5U0rRer+VK1cSGRlJSEhIoX+ujYmJoXXr1vj5+dGoUSOmTZvm8jjLIyV7xTRw4ED++usvFi9ezMKFC1m5ciX33XdfoV47ceJEbDabiyMsn4q6LvHx8cTHx/P666/z559/Mm3aNBYtWsSQIUNKMWrvMmvWLIYPH87o0aNZu3YtLVu2pFu3bhw6dCjX83/++WcGDBjAkCFDWLduHX369KFPnz78+eefpRy5dyvqusTExDBgwACWL1/O6tWrCQsL44YbbmD//v2lHLl3K+q6nLVr1y6eeOIJOnbsWEqRli9FXZe0tDSuv/56du3axdy5c9m6dSsffvghoaGhpRy5dyvqunzxxReMGDGC0aNHs3nzZj7++GNmzZrFs88+W8qRe69Tp07RsmVLJk+eXKjzd+7cSa9evejcuTPr16/n0Ucf5Z577uH77793caTlkCUXbNOmTRZg/fbbb9nHvvvuO8tms1n79+/P97Xr1q2zQkNDrQMHDliANW/ePBdHW34UZ13ONXv2bMvX19dKT093RZhez+FwWA8++GD2n51OpxUSEmKNHz8+1/Nvu+02q1evXjmOtWvXzvrvf//r0jjLm6Kuy/kyMjKsypUrW//3f//nqhDLpQtZl4yMDOuaa66xPvroI2vQoEFW7969SyHS8qWo6zJlyhSrQYMGVlpaWmmFWC4VdV0efPBB67rrrstxbPjw4Vb79u1dGmd5VZifa5966inr8ssvz3GsX79+Vrdu3VwYWfmkyl4xrF69mipVqtC2bdvsY127dsUwDH799dc8X5eSksLtt9/O5MmTqVOnTmmEWq5c6LqcLzExkaCgIHx8fFwRpldLS0tjzZo1dO3aNfuYYRh07dqV1atX5/qa1atX5zgfoFu3bnmeL0V3IetyvpSUFNLT06lWrZqrwix3LnRdXnzxRWrVqqU7EFzkQtZl/vz5hIeH8+CDD1K7dm2uuOIKXn75ZZxOZ2mF7fUuZF2uueYa1qxZk32r544dO/j222/p2bNnqcQs/6bv+aVHP8UWQ0JCArVq1cpxzMfHh2rVqpGQkJDn6x577DGuueYaevfu7eoQy6ULXZdzHTlyhLFjxxb6llzJ6ciRIzidTmrXrp3jeO3atdmyZUuur0lISMj1/MKumRTsQtblfE8//TQhISH/+iYtF+5C1mXVqlV8/PHHrF+/vhQiLJ8uZF127NjBsmXLGDhwIN9++y3btm3jgQceID09ndGjR5dG2F7vQtbl9ttv58iRI3To0AHLssjIyGDo0KG6jdON8vqen5SUxOnTpwkICHBTZN5Hlb1cjBgxApvNlu9HYX8wOt/8+fNZtmwZEydOLNmgywFXrsu5kpKS6NWrF82aNeOFF14ofuAiXmLChAnMnDmTefPm4e/v7+5wyq2TJ09yxx138OGHH1KjRg13hyPnME2TWrVq8cEHH9CmTRv69evHc889x9SpU90dWrkWExPDyy+/zHvvvcfatWv58ssv+eabbxg7dqy7QxNxOVX2cvH4449z11135XtOgwYNqFOnzr8eBs7IyODYsWN53p65bNkytm/fTpUqVXIc79u3Lx07diQmJqYYkXs3V67LWSdPnqR79+5UrlyZefPmUaFCheKGXS7VqFEDu93OwYMHcxw/ePBgnmtQp06dIp0vRXch63LW66+/zoQJE1iyZAktWrRwZZjlTlHXZfv27ezatYvIyMjsY6ZpApl3MWzdupWGDRu6Nuhy4EL+vtStW5cKFSpgt9uzjzVt2pSEhATS0tLw9fV1aczlwYWsy8iRI7njjju45557AGjevDmnTp3ivvvu47nnnsMwVPsobXl9zw8KClJVr4TpqzsXNWvWpEmTJvl++Pr6Eh4ezokTJ1izZk32a5ctW4ZpmrRr1y7XuUeMGMEff/zB+vXrsz8A3nrrLT799NPSuDyP5cp1gcyK3g033ICvry/z589X5aIYfH19adOmDUuXLs0+ZpomS5cuJTw8PNfXhIeH5zgfYPHixXmeL0V3IesC8OqrrzJ27FgWLVqU41lYKRlFXZcmTZqwcePGHN9H/vOf/2R3tQsLCyvN8L3Whfx9ad++Pdu2bctOvgHi4uKoW7euEr0SciHrkpKS8q+E7mxCblmW64KVPOl7filyd4cYT9e9e3erVatW1q+//mqtWrXKuvTSS60BAwZkj+/bt8+67LLLrF9//TXPOVA3zhJX1HVJTEy02rVrZzVv3tzatm2bdeDAgeyPjIwMd12GR5s5c6bl5+dnTZs2zdq0aZN13333WVWqVLESEhIsy7KsO+64wxoxYkT2+T/99JPl4+Njvf7669bmzZut0aNHWxUqVLA2btzorkvwSkVdlwkTJli+vr7W3Llzc/y9OHnypLsuwSsVdV3Op26crlHUddmzZ49VuXJl66GHHrK2bt1qLVy40KpVq5b10ksvuesSvFJR12X06NFW5cqVrRkzZlg7duywfvjhB6thw4bWbbfd5q5L8DonT5601q1bZ61bt84CrDfffNNat26dtXv3bsuyLGvEiBHWHXfckX3+jh07rMDAQOvJJ5+0Nm/ebE2ePNmy2+3WokWL3HUJXkvJXjEdPXrUGjBggFWpUiUrKCjIGjx4cI4fgnbu3GkB1vLly/OcQ8leySvquixfvtwCcv3YuXOney7CC7z77rvWxRdfbPn6+loOh8P65Zdfssc6depkDRo0KMf5s2fPtho3bmz5+vpal19+ufXNN9+UcsTlQ1HW5ZJLLsn178Xo0aNLP3AvV9S/L+dSsuc6RV2Xn3/+2WrXrp3l5+dnNWjQwBo3bpx+aegCRVmX9PR064UXXrAaNmxo+fv7W2FhYdYDDzxgHT9+vPQD91J5/Rx1dh0GDRpkderU6V+vufLKKy1fX1+rQYMG1qefflrqcZcHNstS/VpERERERMTb6Jk9ERERERERL6RkT0RERERExAsp2RMREREREfFCSvZERERERES8kJI9ERERERERL6RkT0RERERExAsp2RMREREREfFCSvZERERERES8kJI9ERHxCHfddRc2m+1fH9u2bSuR+adNm0aVKlVKZK4LtXLlSiIjIwkJCcFms/HVV1+5NR4REfFsSvZERMRjdO/enQMHDuT4qF+/vrvD+pf09PQLet2pU6do2bIlkydPLuGIRESkPFKyJyIiHsPPz486derk+LDb7QB8/fXXtG7dGn9/fxo0aMCYMWPIyMjIfu2bb75J8+bNqVixImFhYTzwwAMkJycDEBMTw+DBg0lMTMyuGL7wwgsAuVbYqlSpwrRp0wDYtWsXNpuNWbNm0alTJ/z9/fn8888B+Oijj2jatCn+/v40adKE9957L9/r69GjBy+99BI33XRTCbxbIiJS3vm4OwAREZHi+vHHH7nzzjt555136NixI9u3b+e+++4DYPTo0QAYhsE777xD/fr12bFjBw888ABPPfUU7733Htdccw0TJ05k1KhRbN26FYBKlSoVKYYRI0bwxhtv0KpVq+yEb9SoUUyaNIlWrVqxbt067r33XipWrMigQYNK9g0QERHJhZI9ERHxGAsXLsyRhPXo0YM5c+YwZswYRowYkZ1ENWjQgLFjx/LUU09lJ3uPPvpo9uvq1avHSy+9xNChQ3nvvffw9fUlODgYm81GnTp1Lii2Rx99lJtvvjn7z6NHj+aNN97IPla/fn02bdrE+++/r2RPRERKhZI9ERHxGJ07d2bKlCnZf65YsSIAGzZs4KeffmLcuHHZY06nkzNnzpCSkkJgYCBLlixh/PjxbNmyhaSkJDIyMnKMF1fbtm2z///UqVNs376dIUOGcO+992Yfz8jIIDg4uNifS0REpDCU7ImIiMeoWLEijRo1+tfx5ORkxowZk6Oydpa/vz+7du3ixhtv5P7772fcuHFUq1aNVatWMWTIENLS0vJN9mw2G5Zl5TiWWwOWs4nn2XgAPvzwQ9q1a5fjvLPPGIqIiLiakj0REfF4rVu3ZuvWrbkmggBr1qzBNE3eeOMNDCOzN9ns2bNznOPr64vT6fzXa2vWrMmBAwey//z333+TkpKSbzy1a9cmJCSEHTt2MHDgwKJejoiISIlQsiciIh5v1KhR3HjjjVx88cXccsstGIbBhg0b+PPPP3nppZdo1KgR6enpvPvuu0RGRvLTTz8xderUHHPUq1eP5ORkli5dSsuWLQkMDCQwMJDrrruOSZMmER4ejtPp5Omnn6ZChQoFxjRmzBgefvhhgoOD6d69O6mpqfz+++8cP36c4cOH5/qa5OTkHPsG7ty5k/Xr11OtWjUuvvji4r1JIiJS7mjrBRER8XjdunVj4cKF/PDDD1x11VVcffXVvPXWW1xyySUAtGzZkjfffJNXXnmFK664gs8//5zx48fnmOOaa65h6NCh9OvXj5o1a/Lqq68C8MYbbxAWFkbHjh25/fbbeeKJJwr1jN8999zDRx99xKeffkrz5s3p1KkT06ZNy3dfwN9//51WrVrRqlUrAIYPH06rVq0YNWrUhb41IiJSjtms8x9EEBEREREREY+nyp6IiIiIiIgXUrInIiIiIiLihZTsiYiIiIiIeCEleyIiIiIiIl5IyZ6IiIiIiIgXUrInIiIiIiLihZTsiYiIiIiIeCEleyIiIiIiIl5IyZ6IiIiIiIgXUrInIiIiIiLihZTsiYiIiIiIeCEleyIiIiIiIl7o/wH+mLoOYInyZwAAAABJRU5ErkJggg==", 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" ] @@ -160,24 +197,41 @@ } ], "source": [ - "sgd_clf_binary_clear = SGDClassifier(\n", + "parameters_range = (-1.0, 1.0)\n", + "\n", + "sgd_clf_binary_fhe = SGDClassifier(\n", " random_state=RANDOM_STATE,\n", " max_iter=N_ITERATIONS,\n", - " fit_encrypted=False,\n", + " fit_encrypted=True,\n", + " parameters_range=parameters_range,\n", + " verbose=True,\n", ")\n", - "sgd_clf_binary_clear.fit(X_binary, y_binary)\n", - "y_pred = sgd_clf_binary_clear.predict(X_binary)\n", - "sgd_clf_binary_clear.compile(X_binary)\n", - "y_pred_fhe = sgd_clf_binary_clear.predict(X_binary, fhe=\"execute\")\n", + "\n", + "# Fit on encrypted data\n", + "sgd_clf_binary_fhe.fit(X_binary, y_binary, fhe=\"execute\")\n", + "\n", + "# The weights are decrypted at the end of the `fit` call. Use the clear weights here\n", + "# to evaluate accuracy on clear data\n", + "y_pred = sgd_clf_binary_fhe.predict(X_binary)\n", + "\n", + "# Evaluate the decrypted weights on encrypted data\n", + "sgd_clf_binary_fhe.compile(X_binary)\n", + "y_pred_fhe = sgd_clf_binary_fhe.predict(X_binary, fhe=\"execute\")\n", + "\n", + "# Check that the same result is obtained when applying\n", + "# the decrypted model on clear data and on encrypted data\n", + "# Linear classifiers are 100% correct on encrypted data compared to execution on clear data\n", "assert np.all(y_pred == y_pred_fhe)\n", + "\n", "accuracy = (y_pred == y_binary).mean()\n", + "\n", "plot_decision_boundary(\n", - " sgd_clf_binary_clear,\n", + " sgd_clf_binary_fhe,\n", " X_binary,\n", " y_binary,\n", " n_iterations=N_ITERATIONS,\n", " accuracy=accuracy,\n", - " title=\"Concrete ML (clear training) decision boundary\",\n", + " title=\"Concrete ML (training on encrypted data with FHE) decision boundary\",\n", ")" ] }, @@ -187,28 +241,63 @@ "source": [ "## Validate Encrypted Training using Simulation\n", "\n", - "Training over encrypted data using FHE simulation." + "FHE simulation is a way to test an FHE program on cleartext data, providing a fast way\n", + "to determine the behavior of an algorithm over encrypted data. Inputs and results of FHE simulation are not encrypted\n", + "but the the results are quickly obtained so they can be analyzed to show if any errors are introduced by the execution\n", + "of the algorithm with FHE.\n", + "\n", + "### Get a different dataset that has more features" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "\n", + "X2, y2 = datasets.load_breast_cancer(return_X_y=True)\n", + "x2_train, x2_test, y2_train, y2_test = train_test_split(X2, y2, test_size=0.3, stratify=y2)\n", + "\n", + "scaler = MinMaxScaler(feature_range=[-1, 1])\n", + "x2_train = scaler.fit_transform(x2_train)\n", + "x2_test = scaler.transform(x2_test)\n", + "\n", + "perm = np.random.permutation(x2_train.shape[0])\n", + "x2_train = x2_train[perm, ::]\n", + "y2_train = y2_train[perm]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Configure the FHE training algorithm and simulate" + ] + }, + { + "cell_type": "code", + "execution_count": 6, "metadata": {}, "outputs": [ { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" + "name": "stdout", + "output_type": "stream", + "text": [ + "Sklearn clear accuracy: 97.08%\n", + "Full encrypted fit (simulated) accuracy 91.81%\n" + ] } ], "source": [ "parameters_range = (-1.0, 1.0)\n", "\n", + "sklearn_sgd = SklearnSGDClassifier()\n", + "sklearn_sgd.fit(x2_train, y2_train)\n", + "accuracy_sk = np.mean(sklearn_sgd.predict(x2_test) == y2_test)\n", + "print(f\"Sklearn clear accuracy: {accuracy_sk*100:.2f}%\")\n", + "\n", "sgd_clf_binary_simulate = SGDClassifier(\n", " random_state=RANDOM_STATE,\n", " max_iter=N_ITERATIONS,\n", @@ -216,183 +305,33 @@ " parameters_range=parameters_range,\n", ")\n", "\n", - "sgd_clf_binary_simulate.fit(X_binary, y_binary, fhe=\"simulate\")\n", + "# Train with simulation on the full dataset\n", + "sgd_clf_binary_simulate.fit(x2_train, y2_train, fhe=\"simulate\")\n", "\n", - "y_pred = sgd_clf_binary_simulate.predict(X_binary)\n", - "\n", - "sgd_clf_binary_simulate.compile(X_binary)\n", - "y_pred_fhe = sgd_clf_binary_simulate.predict(X_binary, fhe=\"execute\")\n", - "\n", - "assert np.all(y_pred == y_pred_fhe)\n", - "\n", - "accuracy = (y_pred == y_binary).mean()\n", - "\n", - "plot_decision_boundary(\n", - " sgd_clf_binary_simulate,\n", - " X_binary,\n", - " y_binary,\n", - " n_iterations=N_ITERATIONS,\n", - " accuracy=accuracy,\n", - " title=\"Concrete ML (fhe simulation training) decision boundary\",\n", - ")" + "# Measure accuracy on the test set using simulation\n", + "sgd_clf_binary_simulate.compile(x2_train)\n", + "y_pred_fhe = sgd_clf_binary_simulate.predict(x2_test, fhe=\"simulate\")\n", + "accuracy = (y_pred_fhe == y2_test).mean()\n", + "print(f\"Full encrypted fit (simulated) accuracy {accuracy*100:.2f}%\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Encrypted Training\n", - "\n", - "Training over encrypted data in FHE." + "### Evaluate accuracy evolution during training" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Compiling training circuit ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Compilation took 3.1515 seconds.\n", - "Key Generation...\n", - "Key generation took 4.0054 seconds.\n", - "Training starts\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 0 took 3.7323 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 1 took 3.8028 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 2 took 4.3082 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 3 took 3.6551 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 4 took 2.4843 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 5 took 2.3454 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 6 took 2.2775 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 7 took 2.2840 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 8 took 2.6507 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 9 took 2.4483 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 10 took 2.2989 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 11 took 2.2665 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 12 took 2.5625 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 13 took 2.4625 seconds.\n", - "Starting iteration ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Iteration 14 took 2.3384 seconds.\n" - ] - }, { "data": { - "image/png": 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", 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", 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" ] }, "metadata": {}, @@ -400,48 +339,44 @@ } ], "source": [ - "sgd_clf_binary_fhe = SGDClassifier(\n", + "# To measure accuracy after every batch initialize the SGDClassifier with warm_start=True\n", + "# which keeps the weights obtained with previous batches\n", + "\n", + "sgd_clf_binary_simulate = SGDClassifier(\n", " random_state=RANDOM_STATE,\n", " max_iter=N_ITERATIONS,\n", " fit_encrypted=True,\n", " parameters_range=parameters_range,\n", - " verbose=True,\n", + " warm_start=True,\n", ")\n", "\n", - "sgd_clf_binary_fhe.fit(X_binary, y_binary, fhe=\"execute\")\n", + "batch_size = sgd_clf_binary_simulate.batch_size\n", "\n", - "y_pred = sgd_clf_binary_fhe.predict(X_binary)\n", + "# Go through the training batches\n", + "acc_history = []\n", + "for idx in range(x2_train.shape[0] // batch_size):\n", + " batch_range = range(idx * batch_size, (idx + 1) * batch_size)\n", + " x_batch = x2_train[batch_range, ::]\n", + " y_batch = y2_train[batch_range]\n", "\n", - "sgd_clf_binary_fhe.compile(X_binary)\n", - "y_pred_fhe = sgd_clf_binary_fhe.predict(X_binary, fhe=\"execute\")\n", + " # Fit on a single batch with partial_fit\n", + " sgd_clf_binary_simulate.partial_fit(x_batch, y_batch, fhe=\"simulate\")\n", "\n", - "assert np.all(y_pred == y_pred_fhe)\n", + " # Measure accuracy of the model with FHE simulation\n", + " sgd_clf_binary_simulate.compile(x2_train)\n", + " y_pred_fhe = sgd_clf_binary_simulate.predict(x2_test, fhe=\"simulate\")\n", + " accuracy = (y_pred_fhe == y2_test).mean()\n", + " acc_history.append(accuracy)\n", "\n", - "accuracy = (y_pred == y_binary).mean()\n", - "\n", - "plot_decision_boundary(\n", - " sgd_clf_binary_fhe,\n", - " X_binary,\n", - " y_binary,\n", - " n_iterations=N_ITERATIONS,\n", - " accuracy=accuracy,\n", - " title=\"Concrete ML (fhe simulation training) decision boundary\",\n", - ")" + "# Plot the evolution of accuracy throughout the training process\n", + "fig = plt.figure()\n", + "plt.plot(acc_history)\n", + "plt.title(f\"Accuracy evolution on breast-cancer. Final accuracy {acc_history[-1]*100:.2f}%\")\n", + "plt.xlabel(\"Batch number\")\n", + "plt.ylabel(\"Accuracy\")\n", + "plt.grid(True)\n", + "plt.show()" ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can see that the final accuracy is on par with the accuracy obtained without FHE simulation." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/docs/built-in-models/linear.md b/docs/built-in-models/linear.md index bdb85286e..d8cf7b4a1 100644 --- a/docs/built-in-models/linear.md +++ b/docs/built-in-models/linear.md @@ -20,6 +20,8 @@ Using these models in FHE is extremely similar to what can be done with scikit-l Models are also compatible with some of scikit-learn's main workflows, such as `Pipeline()` and `GridSearch()`. +## Pre-trained models + It is possible to convert an already trained scikit-learn linear model to a Concrete ML one by using the [`from_sklearn_model`](../developer-guide/api/concrete.ml.sklearn.base.md#classmethod-from_sklearn_model) method. See [below for an example](#loading-a-pre-trained-model). This functionality is only available for linear models. ## Quantization parameters diff --git a/docs/built-in-models/training.md b/docs/built-in-models/training.md new file mode 100644 index 000000000..0bd1f29d0 --- /dev/null +++ b/docs/built-in-models/training.md @@ -0,0 +1,47 @@ +# Training on Encrypted Data + +Concrete ML offers the possibility to train [SGD Logistic Regression](../developer-guide/api/concrete.ml.sklearn.linear_model.md#class-sgdclassifier) on encrypted data. The [logistic regression training](../advanced_examples/LogisticRegressionTraining.ipynb) example shows this feature in action. + +This example shows how to instantiate a logistic regression model that trains on encrypted data: + +```python +from concrete.ml.sklearn import SGDClassifier +parameters_range = (-1.0, 1.0) + +model = SGDClassifier( + random_state=42, + max_iter=50, + fit_encrypted=True, + parameters_range=parameters_range, +) +``` + +To activate encrypted training simply set `fit_encrypted=True` in the constructor. If this value is not set, training is performed +on clear data using `scikit-learn` gradient descent. + +Next, to perform the training on encrypted data, call the `fit` function with the `fhe="execute"` argument: + + + +```python +model.fit(X_binary, y_binary, fhe="execute") +``` + +{% hint style="info" %} +Training on encrypted data provides the highest level of privacy but is slower than training on clear data. Federated learning is an alternative approach, where data privacy can be ensured by using a trusted gradient aggregator, coupled with optional _differential privacy_ instead of encryption. Concrete ML +can import linear models, including logistic regression, that are trained using federated learning using the [`from_sklearn` function](linear.md#pre-trained-models). + +{% endhint %} + +## Training configuration + +The `max_iter` parameter controls the number of batches that are processed by the training algorithm. + +The `parameters_range` parameter determines the initialization of the coefficients and the bias of the logistic regression. It is recommended to give values that are close to the min/max of the training data. It is also possible to normalize the training data so that it lies in the range $$[-1, 1]$$. + +## Capabilities and Limitations + +The logistic model that can be trained uses Stochastic Gradient Descent (SGD) and quantizes for data, weights, gradients and the error measure. It currently supports training 6-bit models, training both the coefficients and the bias. + +The `SGDClassifier` does not currently support training models with other values for the bit-widths. The execution time to train a model +is proportional to the number of features and the number of training examples in the batch. The `SGDClassifier` training does not currently support client/server deployment for training. diff --git a/docs/deep-learning/fhe_assistant.md b/docs/deep-learning/fhe_assistant.md index 9f44584a5..12a3111d8 100644 --- a/docs/deep-learning/fhe_assistant.md +++ b/docs/deep-learning/fhe_assistant.md @@ -55,7 +55,12 @@ concrete_clf.fit(X, y) concrete_clf.compile(X, debug_config) ``` -## Compilation debugging +## Compilation error debugging + +Compilation errors that signal that the ML model is not FHE compatible are usually of two types: + +1. TLU input maximum bit-width is exceeded +1. No crypto-parameters can be found for the ML model: `RuntimeError: NoParametersFound` is raised by the compiler The following produces a neural network that is not FHE-compatible: @@ -100,46 +105,53 @@ except RuntimeError as err: Upon execution, the Compiler will raise the following error within the graph representation: ``` -Function you are trying to compile cannot be converted to MLIR: - -%0 = _onnx__Gemm_0 # EncryptedTensor ∈ [-64, 63] -%1 = [[ 33 -27 ... 22 -29]] # ClearTensor ∈ [-63, 62] -%2 = matmul(%0, %1) # EncryptedTensor ∈ [-4973, 4828] -%3 = subgraph(%2) # EncryptedTensor ∈ [0, 126] -%4 = [[ 16 6 ... 10 54]] # ClearTensor ∈ [-63, 63] -%5 = matmul(%3, %4) # EncryptedTensor ∈ [-45632, 43208] -%6 = subgraph(%5) # EncryptedTensor ∈ [0, 126] -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ table lookups are only supported on circuits with up to 16-bit integers -%7 = [[ -7 -52] ... [-12 62]] # ClearTensor ∈ [-63, 62] -%8 = matmul(%6, %7) # EncryptedTensor ∈ [-26971, 29843] -return %8 +Function you are trying to compile cannot be compiled: + +%0 = _x # EncryptedTensor ∈ [-64, 63] +%1 = [[ -9 18 ... 30 34]] # ClearTensor ∈ [-62, 63] @ /fc1/Gemm.matmul +%2 = matmul(%0, %1) # EncryptedTensor ∈ [-5834, 5770] @ /fc1/Gemm.matmul +%3 = subgraph(%2) # EncryptedTensor ∈ [0, 127] +%4 = [[-36 6 ... 27 -11]] # ClearTensor ∈ [-63, 63] @ /fc2/Gemm.matmul +%5 = matmul(%3, %4) # EncryptedTensor ∈ [-34666, 37702] @ /fc2/Gemm.matmul +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ this 17-bit value is used as an input to a table lookup ``` -The error `table lookups are only supported on circuits with up to 16-bit integers` indicates that the 16-bit limit on the input of the Table Lookup operation has been exceeded. To pinpoint the model layer that causes the error, Concrete ML provides the [bitwidth_and_range_report](../developer-guide/api/concrete.ml.quantization.quantized_module.md#method-bitwidth_and_range_report) helper function. First, the model must be compiled so that it can be [simulated](#simulation). Then, calling the function on the module above returns the following: +The error `this 17-bit value is used as an input to a table lookup` indicates that the 16-bit limit on the input of the Table Lookup (TLU) operation has been exceeded. To pinpoint the model layer that causes the error, Concrete ML provides the [bitwidth_and_range_report](../developer-guide/api/concrete.ml.quantization.quantized_module.md#method-bitwidth_and_range_report) helper function. First, the model must be compiled so that it can be [simulated](#simulation). + +### Fixing compilation errors + +To make this network FHE-compatible one can apply several techniques: + +1. use [rounded accumulators](../advanced-topics/advanced_features.md#rounded-activations-and-quantizers) by specifying the `rounding_threshold_bits` parameter. Please evaluate the accuracy of the model using simulation if you use this feature, as it may impact accuracy. Setting a value 2-bit higher than the quantization `n_bits` should be a good start. + + + +```python +torch_model = SimpleNet(20) -``` quantized_numpy_module = compile_torch_model( torch_model, torch_input, - n_bits=7, - use_virtual_lib=True + n_bits=6, + rounding_threshold_bits=7, ) - -res = quantized_numpy_module.bitwidth_and_range_report() -print(res) ``` -``` -{ - '/fc1/Gemm': {'range': (-6180, 6840), 'bitwidth': 14}, - '/fc2/Gemm': {'range': (-45051, 43090), 'bitwidth': 17}, - '/fc3/Gemm': {'range': (-17351, 13868), 'bitwidth': 16} -} -``` +2. reduce the accumulator bit-width of the second layer named `fc2`. To do this, a simple solution is to reduce the number of neurons, as it is proportional to the bit-width. + + + +```python +torch_model = SimpleNet(10) -To make this network FHE-compatible one can reduce the bit-width of the second layer named `fc2`. To do this, a simple solution is to reduce the number of neurons, as it is proportional to the bit-width. +quantized_numpy_module = compile_torch_model( + torch_model, + torch_input, + n_bits=7, +) +``` -Reducing the number of neurons in this layer resolves the error and makes the network FHE-compatible: +3. adjust the tolerance for one-off errors using the `p_error` parameter. See [this section for more explanation](../advanced-topics/advanced_features.md#approximate-computations) on this tolerance. @@ -150,6 +162,7 @@ quantized_numpy_module = compile_torch_model( torch_model, torch_input, n_bits=7, + p_error=0.01 ) ``` diff --git a/docs/deep-learning/optimizing_inference.md b/docs/deep-learning/optimizing_inference.md index 93e02de34..98d030f9a 100644 --- a/docs/deep-learning/optimizing_inference.md +++ b/docs/deep-learning/optimizing_inference.md @@ -21,6 +21,6 @@ Reducing the bit-width of the inputs to the Table Lookup (TLU) operations is a m it is possible to leverage some properties of the fused activation and quantization functions expressed in the TLUs to further reduce the accumulator. This is achieved through the _rounded PBS_ feature as described in the [rounded activations and quantizers reference](../advanced-topics/advanced_features.md#rounded-activations-and-quantizers). Adjusting the rounding amount, relative to the initial accumulator size, can bring large improvements in latency while maintaining accuracy. -## TLU error probability adjustment +## TLU error tolerance adjustment -Finally, the TFHE scheme exposes a TLU error probability parameter that has an impact on crypto-system parameters that influence latency. A higher probability of TLU error results in faster computations but may reduce accuracy. One can think of the error of obtaining $$T[x]$$ as a Gaussian distribution centered on $$x$$: $$TLU[x]$$ is obtained with probability of `1 - p_error`, while $$T[x-1]$$, $$T[x+1]$$ are obtained with much lower probability, etc. In Deep NNs, these type of errors can be tolerated up to some point. See the [`p_error` documentation for details](../advanced-topics/advanced_features.md#approximate-computations) and more specifically the usage example of [the API for finding the best `p_error`](../advanced-topics/advanced_features.md#searching-for-the-best-error-probability). +Finally, the TFHE scheme exposes a TLU error tolerance parameter that has an impact on crypto-system parameters that influence latency. A higher tolerance of TLU off-by-one errors results in faster computations but may reduce accuracy. One can think of the error of obtaining $$T[x]$$ as a Gaussian distribution centered on $$x$$: $$TLU[x]$$ is obtained with probability of `1 - p_error`, while $$T[x-1]$$, $$T[x+1]$$ are obtained with much lower probability, etc. In Deep NNs, these type of errors can be tolerated up to some point. See the [`p_error` documentation for details](../advanced-topics/advanced_features.md#approximate-computations) and more specifically the usage example of [the API for finding the best `p_error`](../advanced-topics/advanced_features.md#searching-for-the-best-error-probability). diff --git a/docs/deep-learning/torch_support.md b/docs/deep-learning/torch_support.md index 732eceaae..578a8e9fc 100644 --- a/docs/deep-learning/torch_support.md +++ b/docs/deep-learning/torch_support.md @@ -6,6 +6,10 @@ As [Quantization Aware Training (QAT)](../advanced-topics/quantization.md) is th The following example uses a simple QAT PyTorch model that implements a fully connected neural network with two hidden layers. Due to its small size, making this model respect FHE constraints is relatively easy. +{% hint style="info" %} +Converting neural networks to use FHE can be done with `compile_brevitas_qat_model` or with `compile_torch_model` for post-training quantization. If the model can not be converted to FHE two types of errors can be raised: (1) crypto-parameters can not be found and, (2) table look-up bit-width limit is exceeded. See the [debugging section](./fhe_assistant.md#compilation-error-debugging) if you encounter these errors. +{% endhint %} + ```python import brevitas.nn as qnn import torch.nn as nn diff --git a/docs/index.toc.txt b/docs/index.toc.txt index f9362e2e5..a9cbab77a 100644 --- a/docs/index.toc.txt +++ b/docs/index.toc.txt @@ -25,6 +25,7 @@ built-in-models/nearest-neighbors.md built-in-models/pandas.md built-in-models/ml_examples.md + built-in-models/training.md .. toctree:: :maxdepth: 0 diff --git a/src/concrete/ml/sklearn/linear_model.py b/src/concrete/ml/sklearn/linear_model.py index b97b98ba0..ae5049036 100644 --- a/src/concrete/ml/sklearn/linear_model.py +++ b/src/concrete/ml/sklearn/linear_model.py @@ -508,7 +508,8 @@ def _fit_encrypted( X_indexes = numpy.arange(0, len(X)) if self.verbose: - print("Training starts") + mode_string = " (simulation)" if fhe == "simulate" else "" + print(f"Training on encrypted data{mode_string}...") # Iterate on the training quantized module in the clear for iteration_step in range(self.max_iter): @@ -533,8 +534,6 @@ def _fit_encrypted( to = time.time() # Train the model over one iteration - if self.verbose: - print("Starting iteration ...") weights, bias = self.training_quantized_module.forward( # type: ignore[assignment] X_batch, y_batch, weights, bias, fhe=fhe )