diff --git a/.gitignore b/.gitignore index c135efe..01442e9 100644 --- a/.gitignore +++ b/.gitignore @@ -1,16 +1,18 @@ .DS_Store data/.DS_Store +src/.DS_Store +docs/.DS_Store +notebooks/.DS_Store notebooks/venv/ notebooks/*.h5 # Byte-compiled / optimized / DLL files __pycache__/ +src/__pycache__/ +notebooks/__pycache__/ *.py[cod] *$py.class -# C extensions -*.so - # Distribution / packaging .Python build/ @@ -56,31 +58,10 @@ coverage.xml .hypothesis/ .pytest_cache/ -# Translations -*.mo -*.pot - -# Django stuff: -*.log -local_settings.py -db.sqlite3 -db.sqlite3-journal - -# Flask stuff: -instance/ -.webassets-cache - -# Scrapy stuff: -.scrapy - -# Sphinx documentation -docs/_build/ - -# PyBuilder -target/ - # Jupyter Notebook .ipynb_checkpoints +notebooks/.ipynb_checkpoints +src/.ipynb_checkpoints # IPython profile_default/ @@ -89,23 +70,9 @@ ipython_config.py # pyenv .python-version -# pipenv -# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. -# However, in case of collaboration, if having platform-specific dependencies or dependencies -# having no cross-platform support, pipenv may install dependencies that don't work, or not -# install all needed dependencies. -#Pipfile.lock - # PEP 582; used by e.g. github.com/David-OConnor/pyflow __pypackages__/ -# Celery stuff -celerybeat-schedule -celerybeat.pid - -# SageMath parsed files -*.sage.py - # Environments .env .venv @@ -113,22 +80,4 @@ env/ venv/ ENV/ env.bak/ -venv.bak/ - -# Spyder project settings -.spyderproject -.spyproject - -# Rope project settings -.ropeproject - -# mkdocs documentation -/site - -# mypy -.mypy_cache/ -.dmypy.json -dmypy.json - -# Pyre type checker -.pyre/ +venv.bak/ \ No newline at end of file diff --git a/README.md b/README.md index bdcf66a..35c13b1 100644 --- a/README.md +++ b/README.md @@ -1,28 +1,28 @@ ![skab](docs/pictures/skab.png) -❗️❗️❗️**The testbed is under repair right now. Unfortunately, we can't tell exactly when it will be ready and we be able to continue data collection. Information about it will be in the repository. Sorry for the delay.** +🛠🛠🛠**The testbed is under repair right now. Unfortunately, we can't tell exactly when it will be ready and we be able to continue data collection. Information about it will be in the repository. Sorry for the delay.** ❗️❗️❗️The current version of SKAB (v0.9) contains 34 datasets with collective anomalies. But the update to v1.0 will contain 300+ additional files with point and collective anomalies. It will make SKAB one of the largest changepoint-containing benchmarks, especially in the technical field. # About SKAB [![Maintenance](https://img.shields.io/badge/Maintained%3F-yes-green.svg)](https://github.com/waico/SKAB/graphs/commit-activity) [![DOI](https://img.shields.io/badge/DOI-10.34740/kaggle/dsv/1693952-blue.svg)](https://doi.org/10.34740/KAGGLE/DSV/1693952) [![License: GPL v3.0](https://img.shields.io/badge/License-GPL%20v3.0-green.svg)](https://www.gnu.org/licenses/gpl-3.0.html) We propose the [Skoltech](https://www.skoltech.ru/en) Anomaly Benchmark (SKAB) designed for evaluating the anomaly detection algorithms. SKAB allows working with two main problems (there are two markups for anomalies): -1. Outlier detection (anomalies considered and marked up as single-point anomalies); -2. Changepoint detection (anomalies considered and marked up as collective anomalies). +1. Outlier detection (anomalies considered and marked up as single-point anomalies) +2. Changepoint detection (anomalies considered and marked up as collective anomalies) SKAB consists of the following artifacts: -1. [Datasets](#datasets); -2. [Leaderboards](#leaderboards) for oultier detection and changepoint detection problems; -3. Python [modules](https://github.com/waico/SKAB/blob/master/utils/evaluating.py) for algorithms’ evaluation; -4. Python [notebooks](#notebooks) with anomaly detection algorithms. +1. [Datasets](#datasets) +2. [Leaderboards](#leaderboards) for oultier detection and changepoint detection problems +3. Python modules for algorithms’ evaluation (now evaluation modules are being imported from [TSAD](https://github.com/waico/tsad) framework, while the details regarding the evaluation process are presented [here](https://github.com/waico/tsad/blob/main/examples/Evaluating.ipynb)) +4. Python [modules](#src) with algorithms’ implementation +5. Python [notebooks](#notebooks) with anomaly detection pipeline implementation for various algorithms -The IIot testbed system is located in the Skolkovo Institute of Science and Technology (Skoltech). -All the details regarding the testbed and the experimenting process are presented in the following artifacts: -- Position paper (*currently submitted for publication*); -- Slides about the project: [in English](https://drive.google.com/open?id=1dHUevwPp6ftQCEKnRgB4KMp9oLBMSiDM), [in Russian](https://drive.google.com/file/d/1gThPCNbEaIxhENLm-WTFGO_9PU1Wdwjq/view?usp=share_link). +All the details about SKAB are presented in the following artifacts: +- Position paper (*currently submitted for publication*) +- Talk about the project: [English](https://youtu.be/hjzuKeNYUho) version and [Russian](https://www.youtube.com/watch?v=VLmmYGc4v2c) version +- Slides about the project: [English](https://drive.google.com/open?id=1dHUevwPp6ftQCEKnRgB4KMp9oLBMSiDM) version and [Russian](https://drive.google.com/file/d/1gThPCNbEaIxhENLm-WTFGO_9PU1Wdwjq/view?usp=share_link) version - # Datasets -The SKAB v0.9 corpus contains 35 individual data files in .csv format. Each file represents a single experiment and contains a single anomaly. The dataset represents a multivariate time series collected from the sensors installed on the testbed. The [data](data/) folder contains datasets from the benchmark. The structure of the data folder is presented in the [structure](./data/README.md) file. Columns in each data file are following: +The SKAB v0.9 corpus contains 35 individual data files in .csv format (datasets). The [data](data/) folder contains datasets from the benchmark. The structure of the data folder is presented in the [structure](./data/README.md) file. Each dataset represents a single experiment and contains a single anomaly. The datasets represent a multivariate time series collected from the sensors installed on the testbed. Columns in each data file are following: - `datetime` - Represents dates and times of the moment when the value is written to the database (YYYY-MM-DD hh:mm:ss) - `Accelerometer1RMS` - Shows a vibration acceleration (Amount of g units) - `Accelerometer2RMS` - Shows a vibration acceleration (Amount of g units) @@ -35,14 +35,12 @@ The SKAB v0.9 corpus contains 35 individual data files in .csv format. Each file - `anomaly` - Shows if the point is anomalous (0 or 1) - `changepoint` - Shows if the point is a changepoint for collective anomalies (0 or 1) -Exploratory Data Analysis (EDA) for SKAB is presented [here](https://github.com/waico/SKAB/blob/master/notebooks/EDA.ipynb). +Exploratory Data Analysis (EDA) for SKAB is presented [here](https://github.com/waico/SKAB/blob/master/notebooks/EDA.ipynb). Russian version of EDA is available on [kaggle](https://www.kaggle.com/newintown/eda-example). -Russian version of EDA is also available at [kaggle](https://www.kaggle.com/newintown/eda-example). - - +ℹ️We have also made a *SKAB teaser* that is a small dataset collected separately but from the same testbed. SKAB teaser is made just for learning/teaching purposes and contains only 4 collective anomalies. All the information is available on [kaggle](https://www.kaggle.com/datasets/yuriykatser/skoltech-anomaly-benchmark-skab-teaser). # Leaderboards -Here we propose the leaderboards for SKAB v0.9 both for outlier and changepoint detection problems. You can also present and evaluate your algorithm using SKAB on [kaggle](https://www.kaggle.com/yuriykatser/skoltech-anomaly-benchmark-skab). Leaderboards are also available at paperswithcode.com: [CPD problem](https://paperswithcode.com/sota/change-point-detection-on-skab). +Here we propose the leaderboards for SKAB v0.9 for both outlier and changepoint detection problems. You can also present and evaluate your algorithm using SKAB on [kaggle](https://www.kaggle.com/yuriykatser/skoltech-anomaly-benchmark-skab). Leaderboards are also available at paperswithcode.com: [CPD problem](https://paperswithcode.com/sota/change-point-detection-on-skab). ❗️All results (excl. ruptures and CPDE) are calculated for out-of-box algorithms without any hyperparameters tuning. @@ -54,12 +52,12 @@ Perfect detector | 1 | 0 | 0 Conv-AE |***0.79*** | 13.69 | ***17.77*** MSET |0.73 | 20.82 | 20.08 LSTM-AE |0.68 | 14.24 | 35.56 -T-squared+Q (PCA) | 0.67 | 13.95 | 36.32 -LSTM | 0.64 | 15.4 | 39.93 +T-squared+Q (PCA-based) | 0.67 | 13.95 | 36.32 +Vanilla LSTM | 0.64 | 15.4 | 39.93 MSCRED | 0.64 | 13.56 | 41.16 LSTM-VAE | 0.56 | 9.13 | 55.03 T-squared | 0.56 | 12.14 | 52.56 -Autoencoder | 0.45 | 7.56 | 66.57 +Vanilla AE | 0.45 | 7.56 | 66.57 Isolation forest | 0.4 | ***6.86*** | 72.09 Null detector | 0 | 0 | 100 @@ -72,15 +70,15 @@ Null detector | 0 | 0 | 100 |Perfect detector | 100 | 100 | 100 | |Isolation forest | ***37.53*** | 17.09 | ***45.02***| |MSCRED | 28.74 | ***23.43*** | 31.21| -|LSTM | 27.09 | 11.06 | 32.68| -|T-squared+Q (PCA) | 26.71 | 22.42 | 28.32| +|Vanilla LSTM | 27.09 | 11.06 | 32.68| +|T-squared+Q (PCA-based) | 26.71 | 22.42 | 28.32| |ruptures** | 24.1 | 21.69 | 25.04| |CPDE*** | 23.07 | 20.52 | 24.35| |LSTM-AE |22.12 | 20.01 | 23.21| |LSTM-VAE | 19.17 | 15.39 | 20.98| |T-squared | 17.87 | 3.44 | 23.2| |ArimaFD | 07.67 | 01.97 | 11.04 | -|Autoencoder | 15.59 | 0.78 | 20.91| +|Vanilla AE | 15.59 | 0.78 | 20.91| |MSET | 12.71 | 11.04 | 13.6| |Conv-AE | 10.09 | 8.62 | 10.83| |Null detector | 0 | 0 | 0| @@ -89,26 +87,25 @@ Null detector | 0 | 0 | 100 *** The best aggregation function (shown) is WeightedSum with MinAbs scaling function. - # Notebooks -The [notebooks](notebooks/) folder contains python notebooks with the code for the proposed leaderboard results reproducing. This folder also contains short description of the algorithms and references to papers and code. - -We have calculated the results for following common anomaly detection algorithms: -- Hotelling's T-squared statistics; -- Hotelling's T-squared statistics + Q statistics based on PCA; -- Isolation forest; -- LSTM-based NN (LSTM); -- Feed-Forward Autoencoder; -- LSTM Autoencoder (LSTM-AE); -- LSTM Variational Autoencoder (LSTM-VAE); -- Convolutional Autoencoder (Conv-AE); -- Multi-Scale Convolutional Recurrent Encoder-Decoder (MSCRED); -- Multivariate State Estimation Technique (MSET). - -Additionally on the leaderboard were shown the results of the following algorithms: -- [ArimaFD](https://github.com/waico/arimafd); -- [ruptures](https://github.com/deepcharles/ruptures) changepoint detection (CPD) algorithms; -- ruptures-based [changepoint detection ensemble (CPDE) algorithms](https://github.com/YKatser/CPDE). +The [notebooks](notebooks/) folder contains jupyter notebooks with the code for the proposed leaderboard results reproducing. We have calculated the results for following commonly known anomaly detection algorithms: +- Isolation forest - *Outlier detection algorithm based on Random forest concept* +- Vanilla LSTM - *NN with LSTM layer* +- Vanilla AE - *Feed-Forward Autoencoder* +- LSTM-AE - *LSTM Autoencoder* +- LSTM-VAE - *LSTM Variational Autoencoder* +- Conv-AE - *Convolutional Autoencoder* +- MSCRED - *Multi-Scale Convolutional Recurrent Encoder-Decoder* +- MSET - *Multivariate State Estimation Technique* + +Additionally on the leaderboard were shown the externally calculated results of the following algorithms: +- [ArimaFD](https://github.com/waico/arimafd) - *ARIMA-based fault detection algorithm* +- [T-squared](http://github.com/YKatser/ControlCharts/tree/main/examples) - *Hotelling's T-squared statistics* +- [T-squared+Q (PCA-based)](http://github.com/YKatser/ControlCharts/tree/main/examples) - *Hotelling's T-squared statistics + Q statistics based on PCA* +- [ruptures](https://github.com/deepcharles/ruptures) - *Changepoint detection (CPD) algorithms from ruptures package* +- [CPDE](https://github.com/YKatser/CPDE) - *Ruptures-based changepoint detection ensemble (CPDE) algorithms* + +Details regarding the algorithms, including short description, references to scientific papers and code of the initial implementation is available in [this readme](https://github.com/waico/SKAB/tree/master/notebooks#anomaly-detection-algorithms). # Citation Please cite our project in your publications if it helps your research. @@ -138,5 +135,6 @@ SKAB is acknowledged by some ML resources. - [paperswithcode.com](https://paperswithcode.com/dataset/skab) - [Google datasets](https://datasetsearch.research.google.com/search?query=skoltech%20anomaly%20benchmark&docid=IIIE4VWbqUKszygyAAAAAA%3D%3D) - [Industrial ML Datasets](https://github.com/nicolasj92/industrial-ml-datasets) + - etc. diff --git a/data/README.md b/data/README.md index 51605d1..7ae35f0 100644 --- a/data/README.md +++ b/data/README.md @@ -3,12 +3,12 @@ ├── Load data.ipynb # Jupyter Notebook to load all data ├── anomaly-free │ └── anomaly-free.csv # Data obtained from the experiments with normal mode - ├── valve1 # Data obtained from the experiments with closing the valve at the outlet of the flow from the pump. + ├── valve2 # Data obtained from the experiments with closing the valve at the outlet of the flow from the pump. │ ├── 1.csv │ ├── 2.csv │ ├── 3.csv │ └── 4.csv - ├── valve2 # Data obtained from the experiments with closing the valve at the flow inlet to the pump. + ├── valve1 # Data obtained from the experiments with closing the valve at the flow inlet to the pump. │ ├── 1.csv │ ├── 2.csv │ ├── 3.csv diff --git a/docs/pictures/skab.png b/docs/pictures/skab.png index da7a138..fff6d3e 100644 Binary files a/docs/pictures/skab.png and b/docs/pictures/skab.png differ diff --git a/docs/pictures/testbed.png b/docs/pictures/testbed.png index 0fb01a6..2f205da 100644 Binary files a/docs/pictures/testbed.png and b/docs/pictures/testbed.png differ diff --git a/notebooks/ArimaFD.ipynb b/notebooks/ArimaFD.ipynb index e902b6b..6bb131b 100644 --- a/notebooks/ArimaFD.ipynb +++ b/notebooks/ArimaFD.ipynb @@ -257,12 +257,12 @@ ], "source": [ "# dataset characteristics printing\n", - "print(f'A number of datasets in the SkAB v1.0: {len(list_of_df)}\\n')\n", + "print(f'A number of datasets in the SKAB v0.9: {len(list_of_df)}\\n')\n", "print(f'Shape of the random dataset: {list_of_df[0].shape}\\n')\n", "n_cp = sum([len(df[df.changepoint==1.]) for df in list_of_df])\n", "n_outlier = sum([len(df[df.anomaly==1.]) for df in list_of_df])\n", - "print(f'A number of changepoints in the SkAB v1.0: {n_cp}\\n')\n", - "print(f'A number of outliers in the SkAB v1.0: {n_outlier}\\n')\n", + "print(f'A number of changepoints in the SKAB v0.9: {n_cp}\\n')\n", + "print(f'A number of outliers in the SKAB v0.9: {n_outlier}\\n')\n", "print(f'Head of the random dataset:')\n", "display(list_of_df[0].head())" ] @@ -568,7 +568,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.9.12" }, "toc": { "base_numbering": 1, diff --git a/notebooks/Conv-AE.ipynb b/notebooks/Conv-AE.ipynb index b3f8e7c..0818625 100644 --- a/notebooks/Conv-AE.ipynb +++ b/notebooks/Conv-AE.ipynb @@ -645,7 +645,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -659,7 +659,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.2" + "version": "3.9.12" } }, "nbformat": 4, diff --git a/notebooks/LSTM-AE.ipynb b/notebooks/LSTM-AE.ipynb index f5464b4..2bfe9d6 100644 --- a/notebooks/LSTM-AE.ipynb +++ b/notebooks/LSTM-AE.ipynb @@ -648,7 +648,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -662,7 +662,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.2" + "version": "3.9.12" } }, "nbformat": 4, diff --git a/notebooks/LSTM-VAE.ipynb b/notebooks/LSTM-VAE.ipynb index 33eb7ee..9c72d83 100644 --- a/notebooks/LSTM-VAE.ipynb +++ b/notebooks/LSTM-VAE.ipynb @@ -736,7 +736,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -750,7 +750,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.2" + "version": "3.9.12" } }, "nbformat": 4, diff --git a/notebooks/README.md b/notebooks/README.md index 2d4e5e0..10c40f5 100644 --- a/notebooks/README.md +++ b/notebooks/README.md @@ -4,7 +4,7 @@ Hotelling's statistic is one of the most popular statistical process control techniques. It is based on the Mahalanobis distance. Generally, it measures the distance between the new vector of values and the previously defined vector of normal values additionally using variances. -[[notebook]](https://github.com/waico/SKAB/blob/master/notebooks/hotelling.ipynb) [[paper]](https://www.semanticscholar.org/paper/Multivariate-Quality-Control-illustrated-by-the-air-Hotelling/529ba6c1a80b684d2f704a7565da305bb84f14e8) +[[notebook]](https://github.com/YKatser/ControlCharts/blob/main/examples/t2_SKAB.ipynb) [[paper]](https://www.semanticscholar.org/paper/Multivariate-Quality-Control-illustrated-by-the-air-Hotelling/529ba6c1a80b684d2f704a7565da305bb84f14e8) ### Hotelling's T-squared statistic + Q statistic (SPE index) based on PCA The combined index is based on PCA. @@ -12,7 +12,7 @@ Hotelling’s T-squared statistic measures variations in the principal component Q statistic measures the projection of the sample vector on the residual subspace. To avoid using two separated indicators (Hotelling's T-squared and Q statistics) for the process monitoring, we use a combined one based on logical or. -[[notebook]](https://github.com/waico/SKAB/blob/master/notebooks/hotelling_q.ipynb) [[paper]](https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/abs/10.1002/cem.800) +[[notebook]](https://github.com/YKatser/ControlCharts/blob/main/examples/t2_with_q_SKAB.ipynb) [[paper]](https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/abs/10.1002/cem.800) ### Isolation Forest Isolation Forest or iForest builds an ensemble of iTrees for a given data set, then anomalies are those instances which have short average path lengths on the iTrees. diff --git a/notebooks/autoencoder.ipynb b/notebooks/autoencoder.ipynb index e2cd0f3..6a3e131 100644 --- a/notebooks/autoencoder.ipynb +++ b/notebooks/autoencoder.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -20,8 +20,7 @@ "\n", "# additional modules\n", "import sys\n", - "sys.path.append('../utils')\n", - "from evaluating import evaluating_change_point" + "sys.path.append('../utils')" ] }, { @@ -33,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -48,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -73,20 +72,20 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "A number of datasets in the SkAB v1.0: 34\n", + "A number of datasets in the SKAB v0.9: 34\n", "\n", "Shape of the random dataset: (1154, 10)\n", "\n", - "A number of changepoints in the SkAB v1.0: 130\n", + "A number of changepoints in the SKAB v0.9: 129\n", "\n", - "A number of outliers in the SkAB v1.0: 13241\n", + "A number of outliers in the SKAB v0.9: 13067\n", "\n", "Head of the random dataset:\n" ] @@ -239,24 +238,24 @@ ], "source": [ "# dataset characteristics printing\n", - "print(f'A number of datasets in the SkAB v1.0: {len(list_of_df)}\\n')\n", + "print(f'A number of datasets in the SKAB v0.9: {len(list_of_df)}\\n')\n", "print(f'Shape of the random dataset: {list_of_df[0].shape}\\n')\n", "n_cp = sum([len(df[df.changepoint==1.]) for df in list_of_df])\n", "n_outlier = sum([len(df[df.anomaly==1.]) for df in list_of_df])\n", - "print(f'A number of changepoints in the SkAB v1.0: {n_cp}\\n')\n", - "print(f'A number of outliers in the SkAB v1.0: {n_outlier}\\n')\n", + "print(f'A number of changepoints in the SKAB v0.9: {n_cp}\\n')\n", + "print(f'A number of outliers in the SKAB v0.9: {n_outlier}\\n')\n", "print(f'Head of the random dataset:')\n", "display(list_of_df[0].head())" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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+vfpgxE/GIi8/zzINANxxxx2QJAl5eXmYNWsWFi1alJAZxKJn/o5//vs1FBQUYMCAAXj//fcBKKYsjz/+OAYNGoT9+/dj8eLFWLhwIQoKClAwbig+XPaxpYBw7HgZeg3ri7++8hz+9Kc/oXv37qitjTTLGTRoEAoKCrB06VJFmx0aiAYMGIDrr78+Iv2yZcswcOBAFBQUYPLkyXj88cfRuXN0kwOpIQCp4fTqXNue6B2dVOePKhToz8WrwKj4905UvbM3vsQJIKYpjq9SlAGUcw7v7io0rD65KwMtRV0NaNwSuTpiRq7zK9cEW1c7qX/3vr3VrZr3qYQmDIQelzniGEbVzyoBrV7DxjI0Fh+3PhnKpzmWTDwoI3C8EVK1D1KtXzte8e+dqP3i+8QzbCHVHx7AiZe3tVn+sk8Cl3mrrJj5DtTAu79a+y3V+XHkd9/C/0Ndi/O2Q6r2wV8S3XTVf0g5X7/ySNR0iGMFKxr1q46i9tMSAEDgmP3qSOBoPepXHkHlkl3aRDtwtB6Nm4/jyG9WomFD7FWd05F2saFmjPUAMAjAWgCjAfyCMXYdgA1QtNhVUITtNbrLDiO6AH5Ksnz58ohjd999t/b3k08+aTg3bNgwrFmjPLb/sPJRCoKARx55BI888oghbUZGhmbGIAgC/vjrh/DHBb+Hs0sKmKh06kVFRSgqKtKu8Xg8WLRoUUSZ5s6di7lz52q/S0pKIs7JAQk9z+6Bj/71Dlzd0wzXjx49OiJs3qeffgoACJxoBA8t75jv3bljJxxYr0QAMedZX280M/jwww+1etm0bA3M6J/hySefjKjbWEhViqZJTIkecQRQBqETC7chY3IPuHtkWKdpBe3TSUcb+CNPSbV+lD6yFmkTzrLXaunrIM76aNqqCIFZV7RMI25GTHUBAKSaSLt/lXi1Vaf6cqXW9hIQsLi/lZf7o020dIJk9ScH4T4nHUn9c2zTtzfePVUQUpxwdUuNmdYsQMenbTMK4fFQ9abi65JcaKEFVOvTpG2sX1MK754qdLjOXmtd9d4+NKoCjU7AatpajiaUI33i2fEXMgGO/nE10safjeSCXPj2VdtqN1sTHpBx9PerkDq6K9IuPEs52ALl6ImXtwIIr5j49lWDB2TUfXsEOVf3bWlxW06MGRYPymDO5utRqz/YH84rmnAeKgcPyIZJpD8khAcrm5pdhlOZNg+bxxhLBfA2gF9yzmsBvADgXACFAEoB/EVNanF5xBtjjN3CGNvAGNtw4sSJtil0G8ODcqtrh1oTzrmiuW2ugMgSHzxOdYKVXvgP1qLq7Sia1NNYoK56Z6+tlti7vxoN649BCmk2vTsrbfMxaKhPdn2EBg5Zp4UzE699btlTidn+tgWyT7JfUZET11i2to171AFW1xbqvz6Mite+Q/mrO066nb1K+T+24/iziklP/bpSe80wENmvtZGGOipqNqYXXv3ePni/i27n7z9YE85Gap9xiMscckMQNR8dQPlr36Hy9d2Q6u2/y1a7b6h9NWwoC7e1Fpo8GPIPtfmWmlG0F76DNagJaZhbSjQZRp1kcpkbx4FQ+4/H1+N0pE0FasaYE4owvZhz/g4AcM7LOOcS51wG8ArCZh2HAZylu7w7gKPmPDnnL3POh3LOh+bmNt9j+mQSONYQdbkkYVq5bXK/DKnKC6nKXrP3Y0PrMKNp4U7jTqJh3THNthaAoU2Vv7JNmUjEIxTo6+dk10eow4/meCU3hgTUGFpG1Qb2ZFL25EaU/jFypQYAeDDxum51h7QowpnVt+HdWQn/YWvn12ClV7NVbm+q39mHyqW7bc+bhVBVeJAaAihftAOHf7PS/tpWmmSqn2CzgtfohL9267N095FUZ1g5/vt791TBu6cq4dtq+fOwANiawi+XQ3mKLRelGrecaLYzuNYlx3i0ite+Q93yHyyDAiRMtHen1rHEjenUTycoo2LJLjTttlfOnI60ZZQPBmAhgJ2c8yd1x/UeV5cDUEMxfADgasaYmzHWE8D5ANa1VfnOJBLxto0zQ+U/0wfDg3Jc99IU1K1dLhM8KENqbF8baLsBkUscUm1Y6ApWe1HzacnJ19ImSrR3py7jRXkkQ5s5yc+ulsVOC8o5R/BEaOlR4jjx8tZTRmNqRTTTlWjtLFjpheyLHEBbW6CO2tZtBl+7Zzr25/U49uf1rVEsS3yHahGsik9gD5Q14PD938AXslM1P6dqAnL8b5sVp95ogkYzBdiI71GOLlFH7Xv117STQG2YhOiEv3hXasv/sR3l/0g8alP4vjzc3lszhKZaf63gZFe5ZJe2SpI4IU253WnTCV9JLerXxvYb4UEZjVtPWLanqKsbqgwhc+M7DrVbHpTRtOUEKv65I2YZTifaUkM9GsC1ACaYQuT9mTG2jTG2FcB4APMAgHO+A8AbAL4D8CmAO1sS4eNMQvYG21ww45IMf2mDEurO4lZckhE41pCYpi5GkROdJZs/6sCJJkiV3jYX3AHdIGrTh1R/sM8QEqzy37tQt/wHBEobTI56p7aAzaKoOOIah2xMPho2HMPh+7+JKhRGI6JjjoHUEEBTKHyh3XWNm46jdtkh7bfvQA18B1s3bn006lYeQeO2VjJbUwc3i3d07M/rUf53RRjRtz+5tSejUYQzu8E3WHFytNAnXtiCY/+3Pi6Tn6aQiVOTakphfk5VQ61b0Yv4ztWJqu6bCFY0KeElLeom4nrzCoSFRtLQn0Z5F0w36rebyYe+PKFnC1Z5WzyB9R+uQ9OuKCZoar3pNNStKfW0p8mH1aQ4XJDQ/3bFUMsX+q9i0Q5Uv7sPcoyoOzWfHULlv3dZOhlHXV1QT0myIZ3ars/UcI1tGeVjJeeccc7zOeeFoX//4ZxfyznPCx2/jHNeqrvmYc75uZzzPpzzT9qqbO0Jl2QEK73NFoi5JCNY3mRY/uRB2WhL2QoymtwYBCQZssFGM1I44vE4Z8VpLxgsb4opYBrOm5Oqg0E7yKiattPmPZq9lrXOm5uWvJqxNH+qoD27+l9AQtOuSsNAbqif0N81nx1C1VuKfXag3OiMEu8E48QrW3Hkt99GHJebgpaxeCv+9Z3WlvXmEMEqLyrf3AMelDXPeD36VYa2puajA6hcvKtV8go/oynWfegdaFEIdO+n+sMDcWtp4ypDnDbUelrz/uZ8G7dEsYMOUfZkHLbxqqlASBMdafJhMYxGPG+kyVjV+/vRsO4YfAdqYKb0T0bTngjBM/TdBI43WvbNUSefraihDhxriGtsa9DH1w8lP/H8lhabFR7/WzEqFkXRcqpmXzwsxLWq8NuKGupYHP39am2VRMW7vxpNO3Q28zZaD/WZmXnjqBjvTgrJHXJTIKKvjtbGtDYpmRQh2tiRgHKkzq9MPE9hvzOVNndK/LEj1fghNwYSCuivb7iaIKdrTMHyJiVCBTcKOC2BGwYNi3zV28elpozfKTHWhxWXBquFWl91s5noS9Y6AdnyvFkjpbNTlMPPGEsj0Fp491fj2FMb4+q4DM9tivJhaLeaPSIHl2SU/nkDKhbtQMO6YwjW+JQ2pNdGhPKtixKKq2lLfBpav43m+MRLW1D2VGRMdc2UA0ZhpPrDA2jcWKbYY1oMglIUB0Ytv1PMjEduCoZ9MkyPxE2rQGaht7krBtYFiaKhtplIxjVBh/XEK3C80dau9vhzxahcstt6qTpKf2GZXhXE1OgIpjq0Cptnfl7NDC50bcPGMgQrlDZa9fbeiDYlN+gmqZxDNkVkUcsZOFyvhbrTjxFRhQ8LG+p4JraBsgb4j4ZtfP1H6lH29CbUrTgc9Touc9T+95DlOf+RxMLNBY43JuR/FK4HnWAXh0DNZa5F3YqeTrWhTlyglr1BQwg+u3Lo8X9v7AfLX9mmxHyP9fpCDVBwGduq3SRY9gZRv+qo0bTInDYeDbVsUiipgnYC42D1xwfQsO4YmnbEDgl6siGBuo149913wRjDrj32zi2x4JKMoLokyZXQdgMHDgzLdFo7bfkAr3U2jFnLjOqHFWox7733XkTYvMhMTTNazrHk3dcx5OKRGHLxSFw4/SJsXhcWhkRRRGFhIQYOHIipU6eiuroa3BtEyQ+H4D4rHb/73e+0tOXl5UjpmY17fnsfwIHdu3ejqKgIhYWF6NevH2655Za4n11uDEBuCEQVprSOJ1FhihsH10Q3toj7NiaTiOr39iFYpgw+TTG8/s1Cl55SnR2rXjPX9F2lFs9Yqvfj2KPrUPn67ggNtXmgNs/Hojl/WZbVbPZzTPk+gpVeY2QG/cKGrv417/OAbCkIxSNQy03BVt1lsKUC+om/b9NCrJmR1c1b1AHfJGjFFUM5TqKZD9j6HsSrqbIQyMue3GhrV6uFQ7S4b7R7Wp1Tj9V+WgKp3h8phFgIUxECrZokVJ6qN/dACikLpGofAtF28wxaxFDWZa8KWQaBOh6HMejeWRya6rKnNmmbGynl9obuH13wNNcF1/3UT3z1VPx7J6r/E7mzX9mTG1H2dOxNybR76Z0SbWyoucwjIo7Uffk9jv+tOEIjHIGafzO03pVLdqH8lW3R90KI1yQn1oRI0IWxM+RvfV3NxwdR/cF+eFVTDxZ5bdRJm5WGmiOsqElkHDzFFBjRIIG6jViyZAnGjBmDN959M3Qk8UZh1ylGzIbtlKZS/I3WEJPWIj+t4w11RmaBWmoMaFuNa9eY8gkGg+hxVg98/uZ/sPGz1fj1Pf+D2+++Qzuvbj2+fft2ZGdnG7Ye73l2D3z8n4+132+++Sb69+6n/b777rsxb948bXv0u+66K+5nj2tiEnp+vUan+oP99gH9NY2UbLQrjqMjaY6ddc1/DuLIb7+NEGqq3tuHite+i6rV0cdYDpt1hJ5Tp6FWO1Sp1o/KxeEt6NWwdE3byyNsqCMFlJYtjdoJQ8efK0blUr1AryuHruNXtYw8IFku1ccjUJc9uRHHHms9hzm5heHDAlEiA6jmOOqOlWbNKQ/KysYXreCMGVWIsxEM5KYgGjaWxTb9iiJYRLMFtypTtG/Q6py+/dQuOxSfmUREecNhxKyItvDHA1JEzHBDfajCi/7biBbSTH8vKSz4WOYdjXi7KXNZdPkHbATqpq3lqF8RY5OSONCb3oWjfBjT1H7xPUr/tFYLC9qwsQy1nytafynGxFmr8xh1EShviqhXf2moTw7K9hNOO9t5wCCIa+ls2hELbVhrjqdv965VgVf7Hjgi+gj9tY3bTqDum/D70mylJW5Ix63aaiy0Zz71QxOSQN3KyN4gaqtq8O2332LhwoWaQC0FJfzqV79CXl4ehlw8Es/980UAwPr16zFq1CgUFBRg9KVFqKuvgxSUMH/+fIwYdQGGXDwSr/zrHwB0gpbAIEkS7v/TbzHqpxeicNggbavz5cuXY/z48bjmmmuQl5cHr9eLG264AXl5eRg0aBC++uorAMqGK9OnT8fUqVPRs2dPPP/PF/H0y3/D0FHDMKpoDCqrFEeP/SUHcOnPLsewMRdgwhWTsXvfbqxatQoffPAB5s+fj8LCQuzfvx97Nn2HKRdPxpAhQ1D004nYtW8PwDnmzp2Le++9F+PHj8eCBQswcugIZGVmAQBGDBqGI6XKR2jWEIwcORJHjoQ/0CRPEvr17YsNG5StiF9//XXMuPRyrV5KS0vRvXt3LX1eXl7U9xSv0CrV+XH4/m9QvzYUUk5nr1i/6ihOvGKzw5caESPIDYOV72Atjjy4Suu8LTH1NbVffa9tKGBHQ8hj29wBqyscER0p5wicCJ3Tb0Edbdk+NKibhQ79s5ijfETTfjcHu+2yNXtpK4FINxCEBWoZzGFl8uELR3UoibRt1d9LJVjRpEwmmkkwwZB80SM4mNKG6l9wh57brC0Mchz9/Spti+9YVP/nII6/uMX6ZBRBU6qxbu/+Q7WoenOPraYyXE77AVhvFla38ojRLtviumgb2lid0w/+PChHCiFWWnA7XwlbwSnKhMEvRwozfqOQUr/6qGEyGL/Jh6qh1uXXihv+1H17BEf/YLYHD+cfS2AFoJnGJIpU6zMJhEalULDSC9kvoSm0sqVOPmOt6OlR87QSiKs/OoDD938DHpRR9sQGlOm0+4Y8ZG7fLqJMbkofWRtXOgDhWZQ5cpfEcfz5YtSvNkYoFtyiMV1AjmwXurwqF+9CzccHDCsCAADZaAaoKWoS0VDz6JOFU4l22Snxx0SwvAnvvPMGpkyZgt69eyMrMwubtxVjw+5iHDx4EJs3b4Z8rAmVVZXw+/2YNWsWXn/9dQwbNgzlO48gyZOEhQsXIiMjA2tXrUHDD1UounwSLhp/EUSPQxEEBIZ/Ln0NGWnpWPXx15BSGcZeVIRJkyYBANatW4ft27ejZ8+e+MtflH1ztm3bhl27dmHSpEnYs0dZHt6+fTs2b96MxtoG9O7XBw//+n+x4dt1uHfBr/Cvt5fg7pvuxB3334O/PfoU+gzshzUrV+Gu+b/EV98sx2WXXYZLL70UM2bMAACMv74If3v0KQwYOwjfLvsa9/zmXnz20X8BAHv27MHnn38OAQyB0rCm9J9L/x8mF12sLLlV+7SPUJIkfPHFF/j5z39uqNurZs7Ckn/9Gx3cGRBFEV06dcHRslKAA/PmzcOECRMwatQoTJo0CTfccAMyMzPtX5S+X4kioARDTnSqra8281YHLBvbOc0UOSgbBqvaLw6B+yX49ldb74CGkF0rAxxZHuUaG/tD4w1VAV4GdJ2hwTlSR+OGMlS9vRcdbs4zrHioHWLjpuNKCDAd2qBuNqVTBWoGo4Za4kZhXU3TAmRvEGK6sgOildmF7JUgeBywNfkIaWprlh1C2uiuEddLtX5491UDUOLC2u2KCShtgTGGsmc2g/skbfc0y3L7lHdutTugHG1yZYXEAf1kwMF0JhHGCpablPpnrpCGWjIL1KFVBxuB10x9FHvZaKYrsUKeGRxbLYSD4IkmyI1BODsmK2l07TlY0QTXWWmQm5SNQ6zs+A3ljFNDrb5fvTCraNzMWkMrgdre5MPSTjuag1dAilxu15UzeKIJ1e/vR9KAcNuKGpecRX7vBg11QAKSYosG8Sglaj6MNNsw5KFO9KOYTBx7PL7Jnh65MYDSR9ZBzHCHbqSr49C9jv15PcQcT4Qdv9FpUVdXFs+rmS5YvD91G3ApZH4ULGuE3BgA8zgM9+AB2XZ1J+p7NDi7W5uzaE9hV7+SDP/3dfB/X4fUkeH+kEUI1FLkZNyiaIFjDcpuo7qoWJZOiTaTNrkxgKYdFUgZ1jniGhKoTzaf3A8cs9EgNpfOecBPHjMcChxrgJDsgJiufLyvv/8W7r3/VwCAq66Yidfffwslpd/j9l/cAYfDAT+A7KxsfLd5O7p06YJhw4YBANLT0gEAn322DFu3bcNbb74JHuSoqavFvgP7cX6PXsoNGfD5ii+xbed2vPOf9wEG1NTWYs/uPXB73Bg+fDjO6X42gpVNWLlypWb+0LdvX5xzzjmaQD1+/HikpaUhxZmEjLR0/PSinwAA8voPwJbNW1DfUI81G9bimtuuV9YyZMAfiBx46+rqtHTMIYBLMnw+n/bFzZw5E6IoGgbK5atWYNHrr+Grd/6rHW/yNqGwsBAlJSUYMmQILr74YkilYdvCKZMn48EHH0SH1GzMnHYloI7BHLjhhhswefJkfPrpp3j//ffx0ksvYcuWLXC73TFfaaRNuu6ceUBW5VN/2BnFUpBQP/6gsbNUnY2YQ4D/cB2O/60YnX45GM7OKVoaNf5uNAENUJb8pEovXGelhe9nDp9m0x+rGwgETzRCzPTonk9X1kajdtlu+22pVtXYsoil6IjQiC3sFPWDnz5MYfh8EIDxneuFEVUrzZuCltEV5Do/mDooxbLdCwm2apm4JNtu8FD15m40ba9A5/lD4chJMmYTh0Ctr3vv/mok9cnWfgtuEXIwVM+m+tVMPlwi6r7+QdvVT0hzKYK8brDzfV8L5hAgprkgprlilikCGy1ZPCYEBkHWYjn4xEvGLZ/1pkhqO1XzMCwxWwgq0ew3DefU96srj1zvV4R2fdk1h22EBQYbAZmbnbTU46ZnZkkO7Rm5P1I7qK8v1V48qHMwjVbnBpOHoCLgG57RL0OMvCyyzK2gyVYn3HZOfVHti+PIV+90axXlQ6rwGjchAYzfkP5vi8fV2pxFX8GcAnhA5wcF4Ogf1iC5MBfZum3KzUoXA+Z2ZLfwEetd2AjUdu8wQkPtlyO/m1CZa5aVaIf8JTVwdUs1hoq1mODaTWor39gD765KuM5Kg7NziuIDpEYxOQ1sqc9sgbqd4EEZUq0fYrobFVUVWP7tCnz3811gjEEKBsHAMHjwYEXboZvWSbU+6+VCzvHXp57GxWMmhrVXooCSkoOhBEqap/7wOCYVXaRd5+ycgq9XrkBKSgqCIScXOUrHqgmbnEMQBOU3BxgTEAwGIcsyMjMysP6/34K5RXCfBEGnuQhWeyE1BCBL4XSG55CVsiY53Mpzhx51287tuG3+L/DhG+8jJytH064leRQb6pqaGlx66aV47rnncNuMG7X8XE4XBhcMwl9ffhZb123GB+98oJUfALp27Yobb7wRN954IwYOHIjt27djyJAhlvVrXra3JUKgVm3AQgOBwKLag3GTQK3l5xS0OMlNOysNArVtXjI3DAYnXt6KYFmjImSoGup4bdM0jRkMZhnR7GDtOl/tepOGGjK3jOLAgzK8uyrhGRCprY1F9Yf7kTOnH5hHtHxWdSA1RFu0cdYyP6uQ7oJc69dscmPt4sb9ksGpj/sksGRrgVoV3qU6f6RAXa1bqje9Y5Vjj4dttiv+ucMw2WIuEQhN1ORaP44+shZdHxih/NYEagE1n5Ro16SN6YaaTw4aBK8Tz4dNOTrcnAfPuZnWD46w9tZwzG7zljgmDAYThjjasF7QUgd6WV1+t9LcGe4VRUNtCj3HHIKh/fj2W5gBaQ7bukgIEVF/1LTWwm7EM8sczs7JCBxrVPYhMJl8WE1uDXsEJGDyoa5WacdiRF5R22jYhCJq8uh5xdBQB442b+dAK2NW7b0zRDhPA7p+Qt+uDRG3dG1UXb1Q261ZaOQcYoYbwfKmCIfTxuITyL66r2EV01ZDbbOiZNaWmxUXXOKoemcv0i7srqzq2NSvXfQxdUVLpWHdsQj/ErXMdV/+oB3zHqhB6uhuxnrTVsF84ZVeU3v37q6EIzdZ6yvUa2p1EaKasxtse3NmC9QmTXJbYAhxxzne+fh9zJkxG88/9lcAgJDqxIQpF2FQwSC8+OKLuHDchQCAyqpK9Dm3N0pLS7F+/XoMGzYMdfV1SPIkYdLFk/DCs89jXP8L4HQ6sefAXnTr1k1/U1x84US8/P8WYvzoC7U05ySdCy4ZHRzGjRmLxYsXY8KECdizZw++//57nN/rPGzatCmcnX5FRjdbTk9LR4+zzsHbH72LGVfMAOccxdu2YmjRCKSmpqKupg5SlRfpXdK0dFdeejk459i2czsKCgshByTI9QHI9QHwgIzvj/yAq26eg3/+9RX0y++HYEXkxiwZGRl45plnMG3aNNx0+XWGc/PuvAdjh45ETrZOGOPAp59+ivGjLoQr2Y2y8uOoqKgw1pkOuT5gDBcWLYyWxcAUrPSicWvIZlZg1gO03gTDYgBlDkG/paTt/Q1lCciGpTh10sRlrnOCVJxvIrZtDt0icKwBzCNqwhDnJrOMaJEaLBzXhGSHQZNtDOKPSBtqDtR+/j3qlv+ADj8faDhVsWQXcmb3RTT839eh6r19yLrifOsyqgO0XqA22cCqyE3GSZWY4YZc6w8LazE0IrJfhpBs/9uQNlRH6qBkmFibtGj1644hdaSyoWzNskNIn3BWOGqFll8AR/+wBpnTz40Y/ORav6Ytt7M5Z56QCUjA+hmD5U1AFIEaQY5AVRMcHZLCEwCb+oon1rBBQx1Dgyy4RMNzyY0BlD62DinDO0eUw9rkI0obt4jlHFPAN+wDbhLOVNTvTeaWgoFeUJKqfOCSDEdHRaAOljdFTl4s6kjfRuyEj7qvf0DgqM5BWeZo3GoMXRlrwy0elMFcYqtGLLLTUMcT61j9O1Z8aU2JwmHZz2mbtOjlaX09Sqa/HUyrK32/V/H/voN3ZyVc56QDaohbc1m8wXCfHYjfKVHtg82THm3FJpSn/0gdGjeWIXiiER3vKLStG3MfGM7QeN9geZNmwqJhMQnw7qhQIqPoq9eqvZu+qfLQjonObqmG4waFBcWh/hGg/xA48Mb7b2Ha5EsNSaZfchlKS4/i7LPPRkFhAYZOGoWl778Jl8uFxf/4F+666y4UFBTgkmumwevz4qaf34R+5/XFiJ+MxaCJI/CL+3+JYFAntHDgxtnXo9/5xjTesjrFwUlXpttvvQ2SJCEvLw+zZs3CK48/D7HaHIJJb5IQMAyyi575O/659DUMGT8ChROH48NPPgIAXH3VLDz50l8xfMoY7N+3X0s3dNIoJd2yjw0xKKUaH+TGAB55+v9QWV2Fex68D4NHDsPISy60HIgHDRqEgoICvP7em4C6jM45BvTrj2tnzjFqIDnHJ+98hLxB+SjIL8DkyZPx+OOPo3PnzoY8uaQ4FEV8mDZyEw/IEWYPAFD2101abGXmEKw1OmpnGeT2tqUxzDLM19kNYDwoh2XzgIzqjw9EdGJqh1/29CYlQoXu3uFIEEJUO1grQURIdhoPyMZBxyzQqTG/gdAAp+vo441JDR6uG1fPDOPtvTo7IJWgjLKnN6L6k4OGQUB9t+7eipOsuvqiOV/GoaGO9tuAGsJYFZ51ees3k6lffRQ1Hx9A/bdH0Fh8AvUrDqPmvyUR2QVDNs/13x6NELaA8IClaqDMKzLqkq5ddI+I92oicLwRZU9uRM1/DobvaVNfdpu3aHGdATRsOh7pn2CBOiHRC33BCi+kap+26yU3Cz4mogrs+qg2QTnimBXmyDj6a6VaPxo2lmkbZECynmCr6Ws+PqiYfAU5HDlJYE5Bsb2N4pRoWSaLOgyUNaDmkxJDW+BBHmGmZOVIbFAcmSNAhJAaAnHtPGmJnTActT+K4kxtUT1SnbrRkzJpjcjPIk61YTJuilbBZa61Df05b2hnTbU9mB3uAdNKR1C2XVGI0FCH3rtql632Xdr3wIHGrSdQHbJd1ybbNpKeXduOJ5SnuWyqvXqgtN60l0aMtqqXP0xtT99HnA4C9ZmtoW4P9O2Oc3z25n8ikvzixtshpLngyHDjL48/YXDMG9I7H6u++RaCU9QCyTMZ+NPv/hd/vP/34UxEhoyUdGz+Yi1UE40/3v97YxoAF44YgwmTJmoDt8ftwaJFi7Tz6j3mzp2LuXPnauXeszrsNHTdVXNw3VVzACjh6j7617uK853EAcYg1fkxetRobPlyPcAYnJ2SEUhpUNLpq0Pm+PtTLxo6uxcf/xtefPxvEDPdEFKcSsiv0PnK3aWG6z/88EP4j9aDiSz03Mb6VsvJm4J4/MFH8fiDjwIAXN3TIt4BAK3eI4QFi75D9kuQ6v2o+s++iHMGAVpgUW0yeVC23h2R87BGids4KvkkMJ2Jja0gEJTDGjBJtt4ExdypaRJ4+Hl4QEbDmlLYYXV/VdOp/IjUGkVcY1jRQdx2cao9IgB4d4VjYIsZRltfu+XqwLFGBI41InlQ2BFUbgpCzHLD1TUFvj1VEHQh9ZQEMQRqs6NYlKVy5lRMplTnP+MgEmk/LNX4IaQ47fPVa08tiln/7VG4z8/UIhaYl2vVHdOsJoxKecMDmf9wHWSfZDABUZdmm3aUI/NSxbfDbuC001DrzXZ8e6rgO1ADz7mZUYUyqcYHZ4ckoxOjjW0nYD0IR7WhtggTGUtjq9a/mOrS+l1VqD/x8lbNsRmw0FCHfFMUs0GfQQvIHIKipT7RCCHd1M5jaIe5X8Lh+79B+uRzkD7+bACAd1dVZDpJjtAORzgSA4aJSaC0AaUL18LZJWSmFqrjysU74TtQg64PXgAelBE43rzoHIby2Wja/aUNOP5X3SqrxMEciuBfv+IIXGelRlyjhqfkMrd2lrQw+TBulmOcqB1/qVhbJWwqPoHgT3rCkRH239BWpeoitcD6DW3KF+1A2oVnWT6neeyoX3UUaUVnwRva5MTZMRm+PVVoUldMZY7Kf4d3Xw2vXtloqG2+/3hCQ5on0GKmG1KND9Xv7UdSYW44XQxB2OD0a3YQ1fVDUc2YThFIQ91MpMZA5FKNVRvkNv/rkOuN23oGy5tiBCaNXraYZTKn54i9A6LaljmHVOMLl5fBUhhUruH2QgmHolljNk59unSWZdNdEtMhw1ysiLi13PCfkij0I8ZHzGxNPkJZBmXDTokqjZuOo2G9oiWp/fx7lC+MjIJg1h7YLT1L9QHD8qFByFWvtbPp5EbHQdsOFtaCiBo1I1wY/YuxWN6WoStr9Ji/huMmYa3yDWVDGLPzjCYM2DU7STbseMccgpZWC6mnORnG1lDrQ3rJPsnQlqWGAOrXlKLum8Nae9K0g3pNue49q2WQ/eE42VblkBrD2jar9lf72SFla+eQZtS8UiCE2oit9lVX38f/VoxyU3hIS813ohpqk6mKNrGOsh275qinPo9DiBAArZygDLdpMH1XejMgXfuv/eyQYhIV5ZsAgIY1pQhWK2YarrNCk/lQnnphWrmBMS4vc4cmzAE5wj6bORiEZAe4T4p4x7E2xlCFuHpdbGD9Skj4INccVVUsNdS6vscXioKjKijUc+q30Lj5OGo+KUH53xMICGCnoPZZ1705ApHaXgOH61HzyUFUvrU34ho1Fj+3afP1q44qY5nB5EPX7xicXeWI+O/61RogHIXIKs68OfJF3fKwHbLcFETdyiOKs6jFJLVhUxkaNx+Hq2c6PCENdbhcxvaufud247Bd29ZWAM9JtzwPIEJJozdH1IcRjWX7zH26eg2N5d49VQiUNZg01PEpX04mJFA3Ax6UIVV6lYHCYptwY2LTH3G2iagaiFh5mOy6oyflIW1fLCnddF79qfNsbxYCMyzPmW3SwXl4CY7rymHhVKKVJ0F4Sya+IovuxGPajlulcdNxw291kNJj1oxFOCKFnrXsyY1hbbfEI4RMwEJQ1WuobexsI8q8oSzimPFezGi/6pciBn69M5tZsAHCS5mGayQ5YglX1fSawzvZ2gSqeQW50bH2RFPYBDY0OdAEtNCAYbdxiFTnN4T0qnprD448sFL7XfrHNah+bx9qPj4YYYKhHygNArXDKNSb/1ZR7WB5wMKEKQ5UQc5SyELsyYTa3gzOhHZOiXZxtk0DpNwUVLZRjoJ6D/XbEDNckQKSvj8I3aNuxWH4vq9VBCHTltJHfht2pta3n6at5Uo/HIe2rvzv2xQtqWqbbhvlA4b8tJ07gzyy7YuCYlIWkJWJsktA5mXnKuljCNTac+i0z1bfFhCpr7ByeDQI1AeNgr/qDCqEIsM07ay0DSdqj40NtU3fZPCBQVgA1BxgrcxqVFMuG8WEd3cVGtaUGvo5o8lH+L3VfFoScT0TmTFmdlAtk0W9RxEOqz86gJqPDsC3r9qyHfGAov1398iIqGffXuMqhNo/2imt9H2P4b3LAESGjrcXwNHR2jHE/L3r25HgCfexscKC6scIVclSu+wQyp7aFDb3RGxN96kACdTNQNZ7JltpNS0vUv7jtqqzBAoQy4lN3+5U+dMX1Mw9VII1ui1vORITRtVnZSx22aM4izDB/CFHatfVME9mc4LwD71ArWi8gzW+2Eu1KibvbbkpGHe0DCbamHyo7zuKB3cszINJ0/ZyQ4giq3rlQTlCyAQQIRRo8rQsx19PFkTEK9W9l6q392q25hp6UwdVc6PTkOkFPC7JqP7ogHWM5NADCGaHPHWDF7sQbkEZQrLJ0i3UfsIa6qDhWY4+ss4yL3P0ClVw5BK3FcK1AUzflnX1r4Zkk32SZjdrFSWjNmRXzYNyYruOhVCfVVsqjiioYoZkFVoQiLTJVq+xwlZoNw2QjZuPh0Nk2aC+E3XSI6a6IiZRVrv+1fznIE48vwXHn9+Cph0VYG4RqRZxyOXGIMRsDyAAYpY7whnUjmB5ExCUtfZop00LlNaj6h2d9lTnvGyuUyYyzdSJ+yUwpwgxSzEpCJrNKUxaZjUvJgiQvUGUPVds76NgkqhlbxCBsgYEyptw9E9rEKzyGlaTzFuNc78SJ1vdnMd/pD6mg2BkGawP2/VNEaZp6kQrpHFlnuZZs1a/v9/w22jyEf7bSrlgnmBr15ntgt2ibf8EAI0blby5T7LcudW7qxKQOZxdUgxOe0DkZCFWCFC9QF3xr/BkVu/kabUBFoDIiabunesF6lh29QaFQbTF6mb0c+0N2VA3A20LU4fRXMHSDlbbmjSKhlrmkUuDERnp/owmnzEW1uqGwvcA1ku7hpmjNjmIT/hTn5vZFUinubaM1ax+ewIDdJ11oLQBru5pxu2QQ52CVOUNd5RRHP3kxgDkOj/kOsVRIlZMXXMUiIR25hKYYclKn4/yv8VGEHFiHkzU5VvPeZlo+q7S2uEqKBs6M+242blF/T8gxwyTFQ2zjVus5XF92DB10BdcAuRQfVW9uUfxSveIqFy6G03byrUOOePSXprAyUKWGtqSeQipLqC0tZBAwzymiBD1/sjBVq0M1dxCrQ+1fm00I3ahF7kk2271rgp/WkQBm2gJ3B/ebjqqhsdqo5FYsEhTGTPefdUIVno1Rz8zVs+uliPjpz1R83F4+TtC+FPTmwZIy7bjEIz1H2o73BsEc4sQPKK2eY05DQDNeUxFXabnPikifCGgOJCJqU54+mShsfhE7PZseh61bdkJTBHbactKX80DVgK1oNjehzZ2YU7BNs65s3MyAofDJgiaNlpkqFtxGIEf6iyvsyzjN0cM5WzcdNywaYwZuc6P8td2hE2lfFKz+zwz8a6eyT4JIsKrSYY+sCWrqAEZ/qP1OP7M5vAmMTbE2u1TRXCLofqJPungEleiMrlFZEzpgWC1Dw3rjmlt2Nk1Fc4OSfD0zY40gVHzUMchW5OPcJszrJLK4ZVhuzYX0cZ1ArV+XAgcqYeY7Qk75prziTb+WPhD1H71PQSXqITnO8UgDXVL4IipodbC3HBAtthtCFCE3ZghiPRZR5OoBeU005tJADFtpB05SZbft20nommo7cqhO+Gwb2YGgSwElzmCJxrDS8VW2g6bDoIxZqhj89JgNOTGgO3gbwcTwzbUaRPCjiXawB2UgZANdebl5yWUNw9YC/eVr++ODGGkXhOUrTXX5gFOE/gtAvYngFkwq34v0olTj3dvlaZdbCxWNGb6NhA80YSaZSXw7qjQ4nSrS/oGbXToGSNsqOv8mtlFWtFZ6HhHoeF8oLQhQquTdmF3ePpkITUUdk0TDGKFzbPTXgZlg+Ox4RrN5EPJO0JbHsJfUqttBxxPHOdEcJ+XGXOS2bihzFKYVt+Vav8PKH1c/aqj2oBp9U1bkdQ/2/A7eEKnyVI3oDH5A4RNPiQIblFZITFHwzGbfNgIt+Z2ACj1LiQ5ICQ7wZuCaDIJKllXWodrVNGipwTjM8XhgXCsa6khoDmiAgD0GuqAEqrObrXPfbbR1lXt95jIDPaslmUwt3PTz7qVR7RJZvKQTsaTIoPcGIRvb3X4mMxto8fYF8L6W6tfddTyuJmyJzeG7N1DmnlX+N0Kcez6aFusoKyZ58UaS6xMmxw5nsiEDiEuM6KaTw4iUNoAZ6dkpI7sisyf9ITn/EwAyvM5spW8o012tDYYh4aauR3wlzag+oP9yvtT25qd+Y5sbDuG3R9Nbd/VPdVyRQiI7g+gf//qalztfw9pUUxONUigbg76j9/Oltd8iTeIYFmj7SwtoXvG0lDrZpfacnasJTib01YObgBMJh+RBWKCoPs7NNN1iRBSQwNG6BLBHdnZmYP5W/okmuqaucTwkr1J8yXV+SOWhZk6GEdknKAqg4c1munjzzII1YA6sCp5es7LjDkgG66VueUSYrRtornOZjttfLgs/u/rUPbMJmM6QBusm0uEY1kMGtaUwrfHZOdncmwMHGtEzWdhYU6/OUn4otB/pnfo12nixAxXRBQQ8EhBSkxzocMNAzUbUG3nPZ9k0MJobTeE1XIsAPi+r0PgmMUypwDITRL8R+u1fiDaYC9VeLUyxyJ1TPzaGmen2JsIWVH+z+2WbaX0/9aj+oP9ipDN7DVaZlKGd0HX/x2lTTQN2uDQJNTZ1RitofrdffDuqdJiIVu1P725hXdPpWWZkwd3NLYn7WJAzPZADE10zCZLyYM6RlUsCskOsCQHGtYdizCNsIIHJTAn00w+xMywAoM5TCYfLsE2XrM+qgLzOAzaaislgeusNGTNUPoiK6dYQxmbgqj5WBFgzBtQJRfkGn6r5UhEs69coEy2D9//TVwTyIjvGspkWfPL0I8PCdtzh+EBuUVSkqdPdsQxJoZ2lI0x1kjVPvhLaiHqIryoCi5n5xRtXDX3Ie5zM7S/eUBWJkQ2k39DVBtvEMf/ugn1q47Cu7tKa2t2bQ4w2dMLTNtbICICUpDD0SFyRQhA9I2W9AEHgjJ8JdYmaKcKJFA3By3ihfGw3rmtrLYcP7tjLvqOzkfBhGG47LorsedApOdxNKw0KMqN7D9E1QTj69XfYPWGteAcCFb7IhxSIjb+SLDP4ToNtWVxdB+hkOQAcwqa/Z8eIclhLdgaEundrlWj8Ej7LeYUFQHWtIQk1fgQrDA+r6NDEpy5NrtwJIDvQA18e6uUgdQpRgoTEg+XVWRw9YjiNW0mji2bIwgqnuFiptsw2DVuLDNs6NCwVtEwNqwujT74xZiIxXx3cWAexP0Ha7RwVEB4KVXfIau2gdHuz5yCpcCltwnscHOe7rixHIHSBsUxJoRe2IGD2doGVyzaoYR7NJVNSHEBQRnHn9mM8n+EorrYDFaJ7CIppDiReWkvONUIEzqcZ6UhaaAxL0tBUmAx+wDv7irL44bBmsPQZjKm9rL8WymIotF1m2KJA4AjS9G+pY7oHHGuYf0xZYVFZBE29EqBwn1Dw9pjERqw9Ck9kDWzt62draNDkr0QJjJ0+c0I2wkMc4vImdMXwfImnHh5q3UehrJCczyUmwIG4Ukx+VDOSXV+JdynRblyftZPmSQxZRVMv7V4xGRCvV5gmrmUftnfzgFNnRyIpvB97vPDUSZyru0PT+i3lYlh5wXDkG2zcROXuaaN9B+yCPsJALrv1mzqBSjfq7opk35SpVfuZM/pZ7imw40DkT65h+XthGSHonjQaXT0SgoASAltwGSHp3/kd8xElpgpoK5fUuvfMPEytePUUWFNsHdftWYmZ4Vc61fGpbONfYdU7dNpqO3FRH30HyYweM7PAnOFQ5zmXN9feYRMt/3253GYHDpyk9BYfAJedSWkBZOktoQE6uZg3FVE+1OLc8k5Zs69GheOuxC7vt2Krd9uwp9+/0ccPxHfxhWSFGpgoUaj/Y63eDLHilXfYPXGtYDMlXKZhDO5MWAYQK02hzAfF5IcYS2dahrukyw1QHqNOHOLcHZKgeAUNW2kXoiKqeUUWLjTMPdBoc4mVtQ/Y+GY7fM2B9+BmrCwZ/rQuRzuOJkoJOSsU2UR+ikWqhMkcwj2EzITUW10YxRXL9B0e2RMXPcDjANRvCYCDt0ESNUO600+nJ2NwgBzitbv2SEgeVBHpF90tiG2stW70fs2aPUpMAhJDsMExZGbhLQincnP0fqIQUpMjdwsxW4wyfxpL8vjVqgCstXql+AUIgYytb4zp52LnOv6o/P/DEP3R8ag64MjDXG6m0NSYa5Bo2XoB2wGQf1xR67yHbl6ZKDrgxcgaUAHePpmGzSSPGQ3zhyC5YTKbNtpjiYjuJV2YTYn0c57HEaTGP3zMAYx1WW9lA/lG/ecl4Xsq0OCYxxNW0h2QqrzK8+kfx6Raf1l8EQTHFluS+1/0sAOENwiuj0yBqkjuhicvM1L71q5WdicRtVmd/xFoXHSaIFZoHZ2Cn9zQpJD+x6tnHLFDHeERltD5tr3JVuMJ7m35qPL/cO131Z9RtPWE/CG4q4bhHLd+3N2TEKX344In8pyI21cd8siiVkeZWVA14eoZhbhcoiWZXF0SIKrZzrcvSIni4rJR/wrg/p3rpmK6UyDzO1Yb6ZpFyIwAot2pa0sxyu8qquGDkEz+XF2TkHubflIn9LDdsy1iipjRjVrqf82ZOrYiuN3a0ICdTMIy9DWMTuWr1oBp8OJW2+8RTnAGArzCyDJEqbPnamlu+e39+G1NxYDAHqPHIiHn34M46+YhLc/elf5/VT492dff4Fx0yZixE/GYvZt16G+oV677g9/eRgjfjIWgy+6ALv27kZJSQleXvR3PPv35zBk7HCsXLsqXDjD4MqMf5qVvmkuo0DlEDQTDcPGFFYCmX51Xi+UJzvg6JRscBqJJdwyvROVSR3OdBqXuM019ObdneLXUtuavwCag1OEUBaUwwO8wGJqfD19smy31Y6Hmv8cVAZRkWlOdm2JXtuZyGRBr0WJx2xEzHRbOtIxt6i9T5fJjtROUGcOAdmz+iD9onPiLq96nVJeIWIwdHZKNm4mwSMHXzErUggTUq1tmRPR/Kv1rgqjhnMuMeK9MIeSd+rIrkjqn6OVU0hyJGznr6fjnYXIubqvsY0bhGvT+1BP6SZ+6nMzkWkbMHWYOwCd5w8LXxfa8ZSJzNrkwzRARzj7qe/RQssJKIO3p3+OVp9iSuREyPY7DmlRk/M6oNsfR6HLr0dYp9Ph7JyiOLFK3DQBEQxmbI5sj33EBej6UX2UE1OMfke28kwRwjuUDbFiOauaBWq9Y6eQHF5ttFr1Up+t492DIjPWCdRWJgDObqkQU13I+GlPJS8LZYHdCopeIBQ8DoipLs13QXH0tJnouURldSNKN8qcAjovGBZxPG3i2eh4a4Fln8hEAd7dVXFv3a4vX3J+LsRMt6H/dHVPQ+6t+boLEhQ2ZbMzWAi17PHmp9Noa/2jwODukaEoXuy2P4/DxCf94h7Kt6BzFD8Vo36QQN0c9BE7LNrhjt3fYXDh4HDtxtke3W4PvnpnGa6aNgMAkJSRgq/eWYYJY8fjsWcexydLPsDaT77BkPxB+Osrf9Ouy8nOwdpPvsEt1/4cT73wV/Q46xzc8vObcdfNd2L9p99izIhRSkJRMNpbmculE0iZWzTs+gSEviv1mpjmCPYab8G8GUiUQULLSzUJN4dTFsNaw3i2Sw0VIvL6GKRc0AXdHhql/c6ZOwDOrmF7QlXzow7wzOOAs0uKUiZNQx1boE4e0iliiR4AkgpykXtHQVxllRsCivYugWUxWy2xRWeqX8aMEGjivKXe3CYeTbrdUrTBrMP0vJqwbypTvJr7iHuF8hdcxsghWTPOR9aVvSOcb82Of1YCb1pRWDum3xUzkXenPnfOtf3R8c5CY5mjaKitiLivRVL9YG64NlR+g1CoF6Lj0FBrKx7m70SXxru7SnGCExkEC/MVs227ZBaondYOjwCQ8ZOeEDwOMMa0HVcFC4HabvKo70+YU4SY5oo5QXZ2SYFc64dU6zP2RyGnRO1nlidyI6UYmIU2zezOJhqQ1TF12R6I3GVWL4AznfletGV8K+0+5zw8ebDaQErVliaqNTWl1VY6Y0SwAJRn8x+sNdjCm82HmFOAaDEpNm+4YsxYp/G2sSs23EPXrziyPehy//AIc0V3zwzkzB2AzKm9Yq4yRMAREecf0LXxeBXUqhmeg2lykUFZpr4H07sLVvuUUJXR8hZZhD+F7aZUJ5EzOmze/637P+yqtN91qzn0ze6Le3vcBUBpM8xOhmPQhBEmsAiHJitmTr3CcP3VV18NAFi7aR127t2FossnAQD8AT8uGBxe/po+5TIAwOD8Qrz36YfK5RZmDSyaHGE3C9UfZzrB1s7+Sw3Xx0IdZxwCq5DkAE9y2H8gekFeJ/SLmW7tGsElQooznrLhUePoLDx9s5E13ai5U+zgwr2Q2jGqS9PcHwREj7Y8rVwjgAmRPVfahLNQ96WyUxYTmPXym0NQPPkdLOqmAICiHRI81kuRSiFZZFxqt7INtOKYxyGHNiOwCjOe87N+WiQNs5arw8/z0LD6aNR4wh1/URhx71g47QRqgUHwOCD5pIjBUTMvchg1ygkJqzq0DWBM5fX0y1F8AUz3N28X7bQI0yY4Rbh7ZcB3oEYpp3aCIWtmb9R/e8RgWgIoAq3e+10d+MQUJ8QUJ7o/NhZlzxUj8EOdMtkwTyiirVyYBEUx0yLclU39aZN1GzOPiHpX+0e9EKpqqM2TAIv+yc7kw+zUZqehttLG6hUOWjorx1E7gdpCOeDoGF1o0swCQptpaHmZBGpHticu8yg1VKT7vMyIDaNU23QuydYrPhaTDFe3sCATbTVJSHJY7rIYcQ+bqE1hDbWFdGeOOJHQhFNA6thuqP/miDbJTi7siPqVRyz9CcRsD7JnnI/6kJ+Jvg6T8zqg/psjcGR7tG/WTNr4s6xXNVR0Y1jKiM5o3HTcNiqQUqD4njWpb9gBsvtjY1H+6g54d1qH04tWJu1QSGmWaG9pqBPDSnXokFs0rGBI1T44Mt2Q6/xRtc7q2Kqu6MjeYMSKycmGNNTNgev/j2yI/Xv3w6bizeEDgqKVdWUkQdZtQ+3z+Qxp0rKNS9YpKYoGlHNg4tjxWP/fb7H+v99iy5fr8dITz2np3G5lRioKIqRgqKEKiPwSdAKx8tvmb0RLEzoQEVfaqEEAACHJae00FFEsZtDORS2I6bZiuhtCshPMI8avvUmwh7AaxJgoGBxfwgJ1SDsgK2n8B2vQtDVkOy8yy3tnTOoR/iEw4xLfUCVMlRb73LxsboHcGFC0WzaTmbSxkTaD6kDpOT8TSQM66E5EXm94x6b36zkvEznX9jdfYsDZRWnXHW7KQ8YlPbXf0VCFks6/Gmo6IWhCgFmY0d6busTvNP4fi8wrjJMoVesW4Wzoss5XNGnzLE2GTEKTllZgSBnSCWnjzzYcTx7UMTLCgZWwqXroO4XIiXU0DbUubYeb85Cc18E2rRnBEylQG4QBkyDlzI30O2B2GmqrsorWTqfmyWKEQK22AwuTj6R83fOG2pOlY2scGmqNKM/i6JismDOE3qnR98QRqaG2cig10fEXg5Dzs34GBUXWrD5IHdMtPOHX7epoKKqV1lrXjvV9UyfTt8icQnx9sFUfJkOrb6swalq9JGqGAKXMGZf0RPfHxmrtO+OSnujyuwsso0ylDO8Md69My7FLTHcrGmJ1kmGxUpsyLNKR1oA+1JxTjBnFJ95V1IjrEliJs1rd1ZyNQ1WdPqUH0i86OyKdlgcPK47ChYj8/s3fU/BEI8RMd0S/anYgVfNVVzhIQ93OLBi+oE3yNWzaYPExjB99IR78yx/x90ULceOV14IJDOvXr4ckS9i1dzd8QT+8jU348tuvMWrYSEWgYKEoABb5jRg8DL/87X3Yd3A/zut5LhqbGnG49Ah697JZSmRAWno6ao5XRhw3SEi6e8XjlBghkIcQM93KtqtVPmVwDCbU38XGRkMNxiC4RU3TIma6w84wqqbcMj/doGUqqJDitNVoGXAww2xatSU0xO0Obdigah+YwGLbGZvMQtQBTr0XczDwGCZncmNQ6XxsNYkWA6lbhAQAzCjQu85JR+BIvaZRSJ/Sw3BdomHzlJsp+XvOy4TnvEzUfX045iViulKv5iVSJrCwps2soXbpNNQIa+HjWTUBIoULVVOZ1Dcb7h4Z4VjgqsBuNjlxi5pmTDvPYPzu9AK1vr2qg49Z+OXcWiAxoQ9VGVd7tsB9djr8pm2mI8qpz1cV4g0mH9Ya6u6PjdUdFyLTxKOVE1lcqxt1X/1gPGDzvrJm9Db6duhs5iOwtaG2nnxb0em+IRDTXYoZXJJDCYepd6DrnGyIfSwkOyyX5s04OyTB2SEJ1f85qB1z98xAyqCOaAo57SHILYVfu0mf3X0M1zJmjFLijPQ1UB7EruTKfaI50plNP8ykjOyChtWmXRQFq9VaZtAiZ047FzXLDoE3BTVBOmoEoVAaK4e6aHbugHF1lzmFsCDqFi1NZWLlZ1tGm+9cvU9SXgct1r+V3KH5/qi70rpF8HgGdn00Fr34YBPXWvbLcJ+XCf/hOkPEIE+fLGO2IX8n97mZcPXMSNy0pR0gDXUz0GQ6zi0bImMMby95E1989QX6js5H/vBCPPTQQ+jaqQuuvPRyDLloJK6/+yYU5uVDyHBpHa7gFi3t9XJzOuCVJ1/Adb+4EUMuHomxl03E7n32ESCEJCcum3YZ3vvPhxg2eXTYKdFGII4bvWBrcU9X19TwF5SgRB19Fs6sszOvIAtMmb2ahMJY16mIWR44sjyRdm0WeSkaaqXDSR3TTRO2DM4uVh1hDIHa1TU1IkIKgLAmxOL6CNtqmSuCmt07sHKUUQVjBoPAKSQ50PXBkdrv9CJj2KjmhM0zl8tqh1EzdhugMJFp5WUOY/sWTBpppqWLr9szTxbELDc6LxiGtAlnI/PScBSOsO2gyeTD40DmT3uFzb1EIXKjJIGFr9NsSsKDj2qHrUYM4eozx0KnoTZHeohXQw+RWQqIVtos1VkMgLF9GbTVNvfVH44hMOlhdmHz1KxSTBOi0Huw9xcw/dRWNizuYauhtvi2bAQiR5YnrCEVw0J+p3mD0Xn+UEXQ1rV7Zu7XYtSRPtKGai+u2SlLsmUdW2moYzmNZ0ztpUWHYQ4B6ZPPMTxTvPmpkSGiah7NmmrzaYuVzni+99SRXeEOhTTVJlDRLKOi2YrHmrDrtNrMJWiCo62TdCtrqNU2ZPDxsJokm+dCAotLYjSafFi0V9OtOt6aj5TBnSAkmVb0TN9p2tjuyPlZP6SM7IK0Md0ifLxOBc5oDXWbYRAAeITWCQC6du2KpYuXQqrywtExWbHxbQzg0d/8EY/98VFwbxBCslPzsC8pKVFykzm4X8KBfQcguET4DysOERMnX4zx48ZHLDHt37UPYErIrCEFg/HZm/8BRIbevXujeM1Gg4Yjoh9LcA8TK7ts64wTR3CLcHRMRvC4xYYYLP57CElOuLo5te2qLbHJS9NYxOHExRxM220wdWw4Ji1jDDnX9YejYzJqPtxvUcBw3rm3F2gDXYeb8sD9UoQjm7osri4xmgfspIE5EZoi5WGMZc6ZOwAVi3ZoZej4i0LITUGUL9xuyDdi0I6BoBfE2xDbDVBEQRMcHOYoGg6jAK3ZBMYxwGZefl64HtTtr2VuuEfWlecbdtIz52uebDCBIXlIJ8NmIUxk4UgfYqSw4OqWis7zh8L/Qx0qv98dEefZDm2S7hIi+ox4l5CZwLRJiQEOZF/TF4HSBk376z4vy3Bd+F7W2mrDfZhF+paYfACAAHS6ZzBKH1mnHRLTXJDrAwYBOf2is1H7+feW5WM2muyoz5KIyYeVfbnADBvvuM5KQ8YlPS13rO3ymxHGbdlN6B1ntdWa0P92PjDN0fqlmbaAZrrJQSJDjKrNtgq5F85b7afCx4Rkh7aCZhbKlINxdk7qfFZtU1HiRLtD4Tb1cbi1MsboX4waahEZk3sidVQ3ODLdSBvbDU3byyFmunH8b8VKmubGXLbTbKvO1bqxRj9J1tenUgBo5YhHQx1ToNaRMqwznN1Ttfsa8jGvKogMSQPjN0E7GZCGujnobag5bAU0IdkBZ+cUTegQkhxw5CaHl6gtap+FOlT1GjHLDeZxwJHpNsT81Kc3R83QlsXMg2FLBV87DXW8x2IQj7214RbNfJ6Yl9loqszHVM2f2bknqX9IyI0S2xNQhCV18PScl4kki00AnF1S0OmXg5E+0VrrwyVuL/Dr89FFmGCCEsFAb7us5cES68DD2hzjNbm35iPz8vOQdcX5yL0l3+JK/UPEvo85uoB2f5FpYZccHZKMGurQe1E937XQhnEsoaaO6AL3eZnImtUHmT/pYVnOlGGd0UFvL27WUKvtQm1wIkP6RWej071DtDRilgfpk85B+uRzkDyok/ZMehw5uufiPPL9WNWfzuSDm51YE3i/yUMt7EFljuT8XGToNsQw1KkYx992WPhiRE1us0LCXJE7oarmCPqypl90TnhDHHN36bBu20pmNuWzaFt2E5gIczqLtIwxpI3rbhm/WUxxWgraKtmz+oAlOZB1Ve/IMSE0yer28GjDNZaTc3O+V/dBpnmTHn2Z1XpLUBDUBOp4bGN1eXe+f7j2fVhqqOMth2p6oWnx7TsmV7dUdPvjaIMjoHa/WP2LwYZaicbk0E1kkgZ2UCLMqJOH5kYlsgsbGmoLqumfkO4yKHJsAyjEuY+CYRKtnyxrGurw86dPOkdLY9fHn06Qhro56BoE1wRqU9QEVZvrMDYu5hbBnYKlNtIKMcUFUZV77Nqy+bgqG7lFOHI8kGoDynIaMwmTiW6zbZZEreyUE80zrvui1YR25broF0YI6lbpRQFilhIBwU5LZhlVxSqMUDREwTDIaRqakB0cl7gmyAlpLk24VAfmDjflKZ21GKk1MHTUjrBArS+XGoEgdUw3ePdGxnlVO+2UkPOkdl3PDG0HvJjhDENtJm38WeASR/2KSJtqew112JZdEaiVb7HLb0doz+c5Pwtd7h+OE39XdvWKNkBlzThfW+pkjCFlUEc0rFO8/WPtbBbhFOkxau9VMxx9xBJ1Epk+/mzULCsJHYyyChS3hjosQJk3OknkuxHcIrKuPB9Vb4dNzKzqwWAHHYcNdewbx07LObedhDNXpJOyaodvPq59kubvXC2v1etIQEOtf25nlxTriA5qklbcAS55UMeIjXo0YTFo4UAGe6Gmy6+Ha117cmGMzX9UZ04r0zXtPg4wh2AIcaiGy4sqUKtN2dyueDhfM/G2O23oUvO22I3XkK+d6VCMtmu2obaDCUxJ28w2YbsSpTN963DTQCUEn8hQ+qe1yulUl3G7enWyxwCuzpWylbHPeVYaAj/UGbI3KBYM5lyh//XVqvcXsjHrO504/Z+gneGcQ0h1GoznmQDwBDYzVGx9Y2sCIq5jDGKWG1KVLjqIpaDJtPQsyQm5SdIE6hbBYBx0QgJ1W5iBRDgHtjA/5hLD8U0T1FBbxkV1MOTemo/AkXr7Wbul5lCXRzzLZxFxgUOz+RQnJJ8ESDIYY8i9owBiugvHHluvpAtd5zkvE4AxlJhVLFdNyGThWVdSQS5SRig7Guptho3lE9D1oZFRnRNjajVMTnqJ5MEYQ4efD4R3V6XRoSxKtIFoAnWKlUZWGwhiCdQm7aIatk8tuukZzJogbQC0/J7CZYhHQNAEapcYaUMd7xK4SoRG3EKgtlvmtZjIxUNcZZStI1UAykSFCQyp47prEzQ1jKHtyp253lUTAIEhe3ZfyL7IZfCIcltpJ3X1lz2rD8qe3hSZRjfpaku078IkLOpjQycV5sKZm4zazw5px6JpwiPuob5z3bN0NPl5dH1wJBqLj6Ny6W7tWNjkw16gVifnzDwOqX9aTbzjHTtMebt6ZmiTaQDo+vsL4somVr9uMK+ItiorCkBAbnGUDyHZgfRJPVD93j7luG61wqMz1UoZ0RkNa4/Zh6LTrcZ7zstE+kXngHlEHH1wVfg8TH2BlYYalqctJ3M51/Y/5ULjRYNMPhKEMQZHpkcJEM+58i/aANj6BYi8T4RC1SKN+kcLBFOmc2oU03URSdrgWfW2qrYdVALPIiQ7wjZjMQVqYwJLgVoU4MhwW5ppaNfZOKwmgl1nqg4cqrbDfXa6MujZDMyWzkyGTSh0Jh+hMqoRCGIheByJC2l6dM54iQhdKu4eGciY0hMAkD2zN8RY8XoT9ZrXa4ejJTML1KYQX/p32eWBEZEhAEX7+6jvgVtqqC0uULVQut3FUscotq7xbCZhuLdZyLNYcTAIkrYa6gSGmyjtIF01NeH2Gr5wvOGwqUTq8M7ImNrLNkZwxIqS1i4ZkgtykTq8i+6cTeFsYshr2D5XpFa3LbCqry4PjDDsXphzdV+kT7QPjxbzHqqGOvRbSHYY7MLtyqIK1NE2hdHanr5d6fooK4E61spSOKGat/JfyqCO6PJAeKdLqxB7Kp3vj9wt0Ra9U2I0DbXqTN3cKB+h652dU5B6ga7tWq1QAlo/FXXyJIf7ajHdBcGlrGBZ3VdNZ76v4dsRo7+7pAE5cKkmWacBpKFuJoYNL9q2DzTeN6LDjUOYZ7r/zatYSQ7b7Y8jEJTOS91BTGqIsjTXzDoRkp2at3fM/BK5B2PhATOWkBinhjomrWH+YiPMqMtjhuVDxuDuGdokJGI3ysgleat40vpJUzQBMmfuAHh3x7lpQAy0arJxiMyZOyDuvJILO8Zckk5U46PWU0zTlRjaRf2zWWldwu8j8j7uXhkQM9xIH38WpGpfxHm7ezFnWEOdXJhru9IQFVOYPst6MLQv3fFoG7tEIdomVI7s8IBvG+5T9VvRmRqIGe4IBzolsZaZ4TC3EN5iESuyj/1Ki1rIttVxWQlwra0B1JwSQ31QykibnTVNfVQ8W3FznUBnhaXZQMxdfRXSJ56N8iM74eoWFuDirRtHZvSd/vTEbfKhnmuuhlpUJ+HK/RwdkhAsD5tymAVqdUJjfmaDPiGOb0KbsDLT92nRvxnGIJvVptMJEqhbguaUGHkq7tBUiWKrfY6SxpDWZOvtEi13zLLWuttoxlpxQuGw2oKUAaw1bmIj4DpMzp7mQVq22rkrnk6uFeRp8wCtdsbadrem5fwOP8+Dd1clXGcZt2k1aqgtbqTTUFvG/DaR1Dfb0iGnWajOQMxa6LK7T4pe65LIfRJ18onX5IMxdHt0DI78eiVE/fbKMUJ9aUQROIVkJ7r8Wtkdtcm0E6BlsTSnRCG8U2cLt1zXsNJQ25h2GATIeARTG+HWgCrgm8rR6ZeD0bS9XIvaASC+sI6aKtU8kw7VWwLVZm1DHYeG2mZlqbVpbhtICJ1Toj7eeERZTGOkHM9Ot9rmIdb1ZKmhjhIJRY+7Vya6PTQydsIW4shNDtsdRxlHwuE+m9km1PoNfSa5t+UjeKJJ84eIXCEIbVxlNr3QJGquW7SJ0lepArWpm2BWK336vsIiZOPpxun/BCeLkIaamZZgHblJcCa7kZeXh2AwiH79+uHVV19FcrL11skJE8vRDVGWQa1U1AlpeeM/0dwIHAndO8Gy260omKOkmEkbG6nVimtpthU01OYBWtUiCGlKp2VezmQiQ9IACzOUGIKNFh5NZ0PdGhOChElAG5g62lrzZYvmdJTYZVp9xNJQQ2n3HW7Os4zIE+vZWBSTD0O6BJwSBZcYnnS1UFgT0l2Qa/2WS7DGLcZ1FRynhjr76j4Qkp1o2hnaeCTKt6Mb3w04O6fA/70iqIQj8MQzxDFDvhqqHGbVl9mUz/IZhRjn9feI491mXNLTEA41EdrapATQKQFifC8RAnUU2+lwotD/dpp+i748IspNguRc2y+uDayyZvaOvoU4ADCgw/X9UffVD/AfbbB3toZOoG7uRNhhFKjFVBfEVFfYSdlGQy3Y7cbJYTTPs8E2Woe60gfFlKNpR4Xh2yIN9Y8avUStCCFCigOC24GkpCQUFxcDAObMmYMXX3wR9957r3alJEkQxeY1Hnv7aAXVHEMlGDQ50kTpW2x3trK7t5UNdVvYVdst6yYqtDdDoR5NwxLzdq0hkJoGDlVQ0DTUcS5nWoYv0qOFCEPrvrsQmZefh+p391mf1Jt8JLK83sbL4yqqxiVexyxPKEatilb1sTTcceyAqBQkjjrSRflIn9wDlW/sNoTmSoiQYOTqnoaMKT1i22DbaaijvC/VTEcTqKMRpT41Uyi1HwsJd87O9tvb2zmNiqHVsoQcyK1CbOqc3BIxC7IjbVz3+MtjQcoFXeBprdUlC8yCnG06s4Y0mu10CFdo85Wk/jmROyLaEBHlJkGSBsQX+zhlSKfYiZjSd2dOPTd20mhhG+MgYsMoFdX50mxyo+7Ga56UWI3vUcpk3lBJy0anMMie3RdSQ8Bk8nH6i6PklNgiuOIYw5S4lFZ2VGPHjsW+ffuwfPlyjB8/Htdccw3y8vIgSRLmz5+PYcOGIT8/Hy+99BIAoLS0FOPGjUNhYSEGDhyIb775BpIkYe7cuRg4cCDyBxXgr6/8DQBw8cxLsHHjRoAB5ZUV6D1yIABg0aJFmDlzJqZOnYpJkyahoaEBt9x3By4oGoWhY0bgg/9+HC6g7rtwdExWYhOLLK6QflZ5tBVMYC1arjTI3i3QnmfP6gNPFEdEA62hoTZ3XKpAHXo/cTvc6InaQYc374lnB8N4SR0RxTxDPwlLQEhu6+VxFc+5mcie009zfEyYeDX+8cZeTmBjF+YSkZyfi+5/GhM18ome1HHdkXZhWGjTIiuISsi/WPe3E6ITeV9RqypKfWrLzaHvhDGGjncNQu4tefb52TxPcmEuOtyUh+QhMcLE6Ytm0347/88wdLhhgH3dqYfboU1nTT+v9cy1LFDrIFb/Eas9Wq20ubqmovtjY+ExbaiSe0ueEvLSihZqqFuXBBQGul0tm3UndUMr0+OHTcBMyhpNoBbQ8Z7B6BwyMQsn0Nuw6641r/jaOP3q0zGHELHToV3EntOJ039KcLJgACQODuuNNQBFO/zJJ59gypQpAIB169Zh+/bt6NmzJ15++WVkZGRg/fr18Pl8GD16NCZNmoR33nkHkydPxm9+8xtIkoTGxkYUFxfjyJEj2L59OzjnOPFdZJxeM6tXr8bWrVuRnZ2N++/9HxSNHoeFCxeiqrIKI4tGY+LYIqQkp0DfyhljgMjg6mK0v3V0So6qubbsJFpVQx36z+MAr/dHHI87k1YQEK1iu9rSBv24tpSdopp8NKOztRjUVS2cs2NS+F232zgU7qQTEpKbLXwkfl1yXvN36Eoe1BG1nx2yH2hCxGvyEdekw25zpzjIvMQ0cYjiiJQzdwD8h2pN9w7/magNdVyrTvFoqHVClKtbakQ6SyxsPtWwk3FjU92qb4jcWqsU7YAjNylmm7W+sHkaajMpF3RRzALiwN0rE24bf9uWaqhblQS6Hk2BFHXsjeN6Ww21sf7dvTLgP1SrbIKli7KlrswJSQ5IdYqpkaVfQeg+dlF0rJwSDafPAA316f8EUTj2yCPw7dzVqnm6+/VF5wceMHwYZi1hU1MTCgsLASga6p///OdYtWoVhg8fjp49lcFq2bJl2Lp1K9566y0AQE1NDfbu3Ythw4bhxhtvRCAQwPTp01FYWIhevXrhwIEDuOuuu/DTn/4UF190MaSykLcusx6ELr74YmRnK1qIz776Ah82foSn//43cA74fD58f+Qw+p3fJ65nFpwiEC2ub/soCiF4RMj1zbwxs/m7LYnD5jZhVHu4kCe26+z0hLOw0pIl53WAeEcBXGeloWFtaCm1LTbpscDZVRF4nF1SDLHHO95ZGH0b4gSXQt3nZ8F3oKb5pg/NJG3CWUgd2y32TqBi9AFHJZ7ndnRIgpjhisv2MxaahtrivlbOqUYNdXw21JE3tT+lmeBYODCrW0/H64imFCz+pCrqvdOn9EDa6G448rtvlaxibRplq6EOHW+nVZd46Hzf0NiJLAhPDBOzoVZxdEpGsKyx2aYOZpq1itdGWDrd2+DukQ7vzkotfnqiaBpoWw21sf7TLzoHKcM6G4RpQIl+4uyUDE//bASOhWzEo7Rzu8go4Z0SbcrbCn3VyeaMFqjbC3Pnrbeh1pOSErbj45zj2WefxeTJkyPSrVixAh9//DGuvfZazJ8/H9dddx22bNmC//73v3juuefwxhtv4MU/PgPR4YAsK/f2+rxR77X05X+h/5CB4BLXdtNrNSy/rdYbGNRBirlFiBnuZjvktLeTXVvKo0KaCx3vGWzYkCH+i63fjVsTzuPUlLYSyfm5islUThIai49rx2PGH03QBCjtwu5IGdwxoU0qWgPGWFyDRdwThIhoFJFJUgZ1REq8KykxUDW8ls6uVtgI0S010cm+pi+kWj/cZ6cj57r+2rJ/p3uHaOHAhBQnhDQXMi9thnlOAh+sMzcZnX89PO5Y7RqnkAa6zYhvXmgpUGdf3Qd13xxRzseo14yf9oJU7bU93/l/huHYn9fbO9m1M9nX9IW7R/wKkNSx3eE+Lyv+FRYzNhpqTaA21T8TmaXAzxxCOBQpt1+t0tLbKd8SMRU7TTmjBerODzzQdpnrP/ZmaCInT56MF154ARMmTIDT6cSePXvQrVs3lJeXo1u3brj55pvR0NCATZs24ZJLLoHL5cKVV16Jc889F3PnzgUA9Oh+NjZu2oQRIy/AOx+/Z3uvSRMuwvP/fBHPDn4WAFC8fQsKBxYoJ1si9bWzgMqYYtutCdTxfH9WjpjtpVJvQ4lacIsQu9g7WkUjZscV54DYmmiOXwnFKk7sPTKBtbswnRBxPnt72Y6rODuloNvDo+N2ArU182ihMJmcH96kRb+hkrNjsradOxMZuv5mRMS1UdFvmpMAehvQiB1s7bCpgngdV08H4vXBsGpPyYUdUa86G8Zo5lbRl/SIWW5kXNor6uZb7YG6Tbe+/cYDE1jzhWno6tf0GsQMF6QKb7N8ksI7VRruFF95YmioASBlZBdI1T6kjT8r4bKdCpzRAnV70ZxtxG+66SaUlJRg8ODB4JwjNzcX7733HpYvX47HH38cTqcTqampeO2113DkyBHccMMNmjb60UcfBRMZfnnr3fjZ3TfgX4v/hQuHjra9129+9WvM+5/7MOiCIeCc4+yuZ+G9RW8qJ1uj/27PnSINt01MohbTXYDArIP/m3B0SIJQ3gz7QT1tODa2KJ6sTshx98qI0J62hVNivCRkQ3oKLY+3CqHBSsyKseoQ8dht/56au8uhUbhuxQK1Iq0hzHa6axCkOMK+xdz19fSXp7XY367mTvjVDUlaaPvMGEPamOhCd3vQ8Y4CBCvtNelthk27zr05H/5Dtc2LkqSLyJQwmkBt38izpp2XeL6nECRQNxd1g41Md0Qsyfr6+ojkRUVFKCoq0n4LgoBHHnkEjzzyiCHd9ddfj+uvvz7i+k2bNhl+c0nGwIx8bN26FQDgP1yH//2fBwEAc+fO1bTYAJDkScLzj/0VYpYHPCgbTT5aIjRZaX/bYUAQM92Q6u1ta+1QtwuPB8HjsN7wJhF0dets5uBiJimvA5q2lTfvYgGAbBRycm/Jj0x3EjTUGoloqNtrpaGdcJ2dDk+fLGTGGFQ0hzuBtY2dfksJvRdHp2Sj+cep+r5aQZgVkp328Xd/ZIhpLuTeXhB3n+fpnwPvdzrnQzU6xSkVnaP5qPGf2xtth1dTNToy3XBkJqYtV1Hj6xvi7KvfuG5cybry/MiY3Kfo59+akEDdTNTZc7vsPGUBEwWwpPC9xSx33GGxDLSg/I7cJHCv1O62Tyerg0qUzMvPR+2nB5E9q0/CDhc5cwdAqo1cQs6e3Re4unkDjZDihFwXiGnLllyYC19JLTKm9GjWfewQsz1w98qImqa9zRlOJcQ0FzrcMDDu9EKyA3IzJpZtDRMYOtw0EM7OKYkL0T/W138GmXwAgPuc+GyFuz08BmBA7eeH4OykCODamBqUkXtHwUkbY0972kAxklSQi44dk+HqGjZFSc7rgMAPdUibeLZ2LGVYZ4vynPkfNwnUzUU17G+nzSViIabEJ2CKqU5wvwQwBjHN2SLPWsvoH6dGdZwSuLqkJCQg6bGLE6tMXprXMYmqQB1HfNjsmb2bdY9odPmfYbETnQGOKW2Ns2sK0i8+B65z0lH+922npJmA57wsw++EY8y25zOdhBWZ5EKjhlDbIv1H1v7VCXTGpB7aMdXRmrlFnaN0/Lh6pMNfUhs74RmOIzcZKSO7IHVkgjvKRoExZhCmAWUClHlZHBvVxBf85bSGBOpmImZ7lJBejlO/AxSSHZAbAxBcIpgowJnbStugW+DI9kBuDDYr/q0ZZ+eUcCD5BGFOAdwvKc5Ctf5TKiRPUn6HxDbOaSWEVBeAxvi2+D1JkDYqNowxpE88G1IoxGBSC2Jktwc51/c37FQYzYchZUQXNG4+3q7PpH6LrdFnxYPV7quZU8+FI8sDT5+223DldCFjcg+4uqfBnWgM8BC5N+XF2DfhxwET2Kllkxzq2909o69Sns6wk+F41FoMHTqUb9iwwXBs586d6Nev30kqEXGqwDkH98stsoM+09pSsNKLmv+WIHtG73YTHhJFbgzg6B/WALDf9j1Y0YRglTdCC/pjRG4MgHkcp03IKf/ReohprpMyobRD9klo3HwcKSM6n7p23gRxBhAoa4CY5Ykdk/8UhjG2kXNuGaS9zUZVxthZjLGvGGM7GWM7GGP3hI5nM8Y+Y4ztDf2fpbvm14yxfYyx3YyxyADNBBEnjLGWOxWeYTiyPciZ3feUFaYBxbkrKa+DtQ1eCEdOEgnTIYRk52kjTAPK1tGnkjANKCEoUy/oQsI0QbQxzk4pp7UwHYu2NPkIAriPc76JMZYGYCNj7DMAcwF8wTl/jDF2P4D7ASxgjPUHcDWAAQC6AvicMdabcy61YRkJgjjFyJlz5qwKEARBED8O2kyg5pyXAigN/V3HGNsJoBuAaQCKQsleBbAcwILQ8aWccx+Ag4yxfQCGA1jdVmVsCyoqKjBx4kQAwLFjxyCKInJzFQeUdevWweU6dbQzy5cvh8vlwqhRo052UQiCIAiCIE5b2sUpkTHWA8AgAGsBdAoJ2+CclzLG1P1xuwFYo7vscOiYOa9bANwCAGeffbb59EknJydH23b8oYceQmpqKn71q1+dtPIEg0E4HNavefny5UhNTU1IoJYkCaJ45i7ZEARBEARBJEqbG1MyxlIBvA3gl5zzaLFsrAzYIjwmOecvc86Hcs6HqprfU52NGzfiwgsvxJAhQzB58mSUlipbqxYVFWHevHkYN24c+vXrh/Xr1+OKK67A+eefj9/+9rcAgJKSEvTt2xfXX3898vPzMWPGDDQ2NsbM94EHHsCFF16Iv/71r/jwww8xYsQIDBo0CBdddBHKyspQUlKCF198EU899RQKCwvxzTffYO7cuXjrrbe0cqemKuFxli9fjvHjx+Oaa65BXl4eJEnC/PnzMWzYMOTn5+Oll15qz+okCIIgCII4pWhTgZox5oQiTC/mnL8TOlzGGOsSOt8FwPHQ8cMA9Bu4dwdwtC3L1x5wznHXXXfhrbfewsaNG3HjjTfiN7/5jXbe5XJhxYoVuO222zBt2jQ899xz2L59OxYtWoSKCmX3qN27d+OWW27B1q1bkZ6ejueffx6BQCBqvtXV1fj6669x3333YcyYMVizZg02b96Mq6++Gn/+85/Ro0cP3HbbbZg3bx6Ki4sxdqx1RAWVdevW4eGHH8Z3332HhQsXIiMjA+vXr8f69evxyiuv4ODBg21TgQRBEARBEKc4bWbywRSX6YUAdnLOn9Sd+gDA9QAeC/3/vu74vxljT0JxSjwfwLqWlOGbN/ag/IfIbcBbQoezUjH2qvg3vfD5fNi+fTsuvvhiAIrJRJcuXbTzl112GQAgLy8PAwYM0M716tULP/zwAzIzM3HWWWdh9OjRAICf/exneOaZZzBlypSo+c6aNUv7+/Dhw5g1axZKS0vh9/vRs2fPhJ97+PDh2nXLli3D1q1bNW12TU0N9u7d26x8CYIgCIIgTnfa0oZ6NIBrAWxjjBWHjj0ARZB+gzH2cwDfA5gJAJzzHYyxNwB8ByVCyJ1nQoQPzjkGDBiA1autfSvdbjcAQBAE7W/1dzCobMBhDufEGIuZb0pKeCOFu+66C/feey8uu+wyLF++HA899JDlNQ6HA7Isa+X2+/2W+XHO8eyzz2LyZIpsSBAEQRAE0ZZRPlbCfo/kiTbXPAzg4dYqQyKa5LbC7XbjxIkTWL16NUaOHIlAIIA9e/ZgwIABcefx/fffa9cvWbIEY8aMQZ8+feLOt6amBt26Kf6dr776qnY8LS0NtbVhs/YePXpg48aNuOqqq/D+++8jEAhYlmfy5Ml44YUXMGHCBDidTuzZswfdunUzCN0EQRAEQRA/Fk7dHR7OEARBwFtvvYUFCxagoKAAhYWFWLVqVUJ59OvXD6+++iry8/NRWVmJ22+/HS6XK+58H3roIcycORNjx45Fhw7hLX2nTp2Kd999V3NKvPnmm/H1119j+PDhWLt2ra2AfNNNN6F///4YPHgwBg4ciFtvvVXTphMEQRAEQfzYoK3HT3FKSkpw6aWXYvv27Se7KD86zrS2RBAEQRBE8zkpW48TBEEQBEEQxI8BEqhPcXr06EHaaYIgCIIgiFMYEqgJgiAIgiAIogWQQE0QBEEQBEEQLYAEaoIgCIIgCIJoASRQEwRBEARBEEQLIIG6lamoqEBhYSEKCwvRuXNndOvWDYWFhcjMzET//v1PdvHalKKiIpjDGBIEQRAEQZzpkEDdyuTk5KC4uBjFxcW47bbbMG/ePO23IDS/umnjFIIgCIIgiFMTEqjbEUmScPPNN2PAgAGYNGkSmpqaAAD79+/HlClTMGTIEIwdOxa7du0CAMydOxf33nsvxo8fjwULFmDu3Lm4/fbbMX78ePTq1Qtff/01brzxRvTr1w9z587V7rNkyRLk5eVh4MCBWLBggXb8008/xeDBg1FQUICJE5Xd3ysrKzF9+nTk5+fjggsuwNatWwEouys+8cQT2rUDBw5ESUkJSkpK0LdvX1x//fXIz8/HjBkz0NjYGPGsy5Ytw8iRIzF48GDMnDkT9fX1rV6fBEEQBEEQpwIkULcje/fuxZ133okdO3YgMzMTb7/9NgDglltuwbPPPouNGzfiiSeewB133KFds2fPHnz++ef4y1/+AgCoqqrCl19+iaeeegpTp07FvHnzsGPHDmzbtg3FxcU4evQoFixYgC+//BLFxcVYv3493nvvPZw4cQI333wz3n77bWzZsgVvvvkmAOD3v/89Bg0ahK1bt+KRRx7BddddF/M5du/ejVtuuQVbt25Feno6nn/+ecP58vJy/OlPf8Lnn3+OTZs2YejQoXjyySdbqxoJgiAIgiBOKRwnuwBtyVeLXsbxQwdaNc+O5/TC+Lm3NOvanj17orCwEAAwZMgQlJSUoL6+HqtWrcLMmTO1dD6fT/t75syZEEVR+z116lQwxpCXl4dOnTohLy8PADBgwACUlJTg0KFDKCoqQm5uLgBgzpw5WLFiBURRxLhx49CzZ08AQHZ2NgBg5cqVmmA/YcIEVFRUoKamJupznHXWWRg9ejQA4Gc/+xmeeeYZ/OpXv9LOr1mzBt99952Wxu/3Y+TIkYlXGEEQBEEQxGnAGS1Qn2q43W7tb1EU0dTUBFmWkZmZieLiYstrUlJSLPMQBMGQnyAICAaDcDisXynnHIwxy+NmGGNwOByQZVk75vV6DefN6c15XnzxxViyZIllWQiCIAiCIM4kzmiBurma5PYkPT0dPXv2xJtvvomZM2eCc46tW7eioKCgWfmNGDEC99xzD8rLy5GVlYUlS5bgrrvuwsiRI3HnnXfi4MGD6NmzJyorK5GdnY1x48Zh8eLF+N3vfofly5ejQ4cOSE9PR48ePfDRRx8BADZt2oSDBw9q9/j++++xevVqjBw5EkuWLMGYMWMMZbjgggtw5513Yt++fTjvvPPQ2NiIw4cPo3fv3s2vKIIgCIIgiFMUsqE+BVi8eDEWLlyIgoICDBgwAO+//36z8+rSpQseffRRjB8/HgUFBRg8eDCmTZuG3NxcvPzyy7jiiitQUFCAWbNmAVCcDzds2ID8/Hzcf//9ePXVVwEAV155JSorK1FYWIgXXnjBIAz369cPr776KvLz81FZWYnbb7/dUIbc3FwsWrQIs2fP1pwdVUdLgiAIgiCIMw1mteR/ujB06FBujnu8c+dO9OvX7ySV6MynpKQEl156KbZv336yi9LmUFsiCIIgCEKFMbaRcz7U6hxpqAmCIAiCIAiiBZBATSREjx49fhTaaYIgCIIgiHghgZogCIIgCIIgWgAJ1ARBEARBEATRAkigJgiCIAiCIIgWQAI1QRAEQRAEQbQAEqhbmaKiIvz3v/81HHv66adxxx13WKbv0aMHysvLUV1djeeff749ikgQBEEQBEG0IiRQtzKzZ8/G0qVLDceWLl2K2bNnR72OBGqCIAiCIIjTExKoW5kZM2bgo48+gs/nA6BshHL06FEcPnwYeXl5GDhwIBYsWBBx3f3334/9+/ejsLAQ8+fPR319PSZOnIjBgwcjLy/PsHviH//4R/Tt2xcXX3wxZs+ejSeeeAIAsH//fkyZMgVDhgzB2LFjaXdCgiAIgiCIdsBxsgtwppGTk4Phw4fj008/xbRp07B06VJMnjwZCxYswMaNG5GVlYVJkybhvffew/Tp07XrHnvsMWzfvh3FxcUAgGAwiHfffRfp6ekoLy/HBRdcgMsuuwwbN27E22+/jc2bNyMYDGLw4MEYMmQIAOCWW27Biy++iPPPPx9r167FHXfcgS+//PIk1AJBEARBEMSPhzNaoK7+cD/8RxtaNU9X1xRkTj03ahrV7EMVqC+//HIUFRUhNzcXADBnzhysWLHCIFCb4ZzjgQcewIoVKyAIAo4cOYKysjKsXLkS06ZNQ1JSEgBg6tSpAID6+nqsWrUKM2fO1PJQteQEQRAEQRBE23FGC9Qni+nTp+Pee+/Fpk2b0NTUhIKCAuzfvz+hPBYvXowTJ05g48aNcDqd6NGjB7xeLzjnlullWUZmZqam4SYIgiAIgiDahzNaoI6lSW4rUlNTUVRUhBtvvBGzZ8/GiBEjcM8996C8vBxZWVlYsmQJ7rrrLsM1aWlpqKur037X1NSgY8eOcDqd+Oqrr3Do0CEAwJgxY3Drrbfi17/+NYLBID7++GPcfPPNSE9PR8+ePfHmm29i5syZ4Jxj69atKCgoaNdnJwiCIAiC+LFBToltxOzZs7FlyxZcffXV6NKlCx599FGMHz8eBQUFGDx4MKZNm2ZIn5OTg9GjR2PgwIGYP38+5syZgw0bNmDo0KFYvHgx+vbtCwAYNmwYLrvsMhQUFOCKK67A0KFDkZGRAUDRai9cuBAFBQUYMGCAwZGRIAiCIAiCaBuYnQnB6cDQoUP5hg0bDMd27tyJfv36naQStQ/19fVITU1FY2Mjxo0bh5dffhmDBw8+2cU64/gxtCWCIAiCIOKDMbaRcz7U6twZbfJxpnLLLbfgu+++g9frxfXXX0/CNEEQBEEQxEmEBOrTkH//+98nuwgEQRAEQRBECLKhJgiCIAiCIIgWQAI1QRAEQRAEQbQAEqgJgiAIgiAIogWQQE0QBEEQBEEQLYAE6lamqKgI//3vfw3Hnn76adxxxx221/To0QPl5eVtXTSNoqIi9OnTB4WFhSgsLMRbb70FQNmQpjXp0aMH8vLykJ+fjwsvvFDbnMaOkpKSuBwuS0pKkJSUhMLCQvTv3x/XXXcdAoEAAGD58uVgjGHhwoVa+s2bN4MxhieeeAIAsGbNGowYMQKFhYXo168fHnrooeY/JEEQBEEQP3pIoG5lZs+ejaVLlxqOLV26FLNnzz5JJbJm8eLFKC4uRnFxMWbMmNFm9/nqq6+wdetWFBUV4U9/+lPUtPEK1ABw7rnnori4GNu2bcPhw4fxxhtvaOfy8vLw+uuva7+XLl1q2DHy+uuvx8svv4zi4mJs374dV111VYJPRRAEQRAEEYYE6lZmxowZ+Oijj+Dz+QAoQuLRo0cxZswYLFmyBHl5eRg4cCAWLFgQcW1JSQkGDhyo/X7iiSc07WlRURHmzZuHcePGoV+/fli/fj2uuOIKnH/++fjtb3+rXfOvf/0Lw4cPR2FhIW699VZIkpTwM3DOMX/+fAwcONAgnN5xxx344IMPAACXX345brzxRgDAwoULDWWwYuTIkThy5Ij2nGPHjsXgwYMxePBgrFq1CgBw//3345tvvkFhYSGeeuopSJKE+fPnY9iwYcjPz8dLL70Uka8oihg+fLiWNwCcffbZ8Hq9KCsrA+ccn376KX7yk59o548fP44uXbpo1/fv3z/hOiIIgiAIglAhgbqVycnJwfDhw/Hpp58CULSjs2bNQmlpKRYsWIAvv/wSxcXFWL9+Pd57772E8na5XFixYgVuu+02TJs2Dc899xy2b9+ORYsWoaKiAjt37sTrr7+Ob7/9FsXFxRBFEYsXL7bMa86cOZrJR0VFheHcO++8g+LiYmzZsgWff/455s+fj9LSUowbNw7ffPMNAODIkSP47rvvAAArV67E2LFjo5b9008/xfTp0wEAHTt2xGeffYZNmzbh9ddfx9133w0AeOyxxzB27FgUFxdj3rx5WLhwITIyMrB+/XqsX78er7zyCg4ePGjI1+v1Yu3atZgyZYrh+IwZM/Dmm29i1apVGDx4MNxut3Zu3rx56NOnDy6//HK89NJL8Hq9MWqeIAiCIAjCnjN6Y5dPPvkEx44da9U8O3fubNB2WqGafUybNg1Lly7FP/7xD6xfvx5FRUXIzc0FoAi0K1as0ITMeLjssssAKCYNAwYM0LSsvXr1wg8//ICVK1di48aNGDZsGACgqakJHTt2tMxr8eLFGDrUcvdMrFy5ErNnz4YoiujUqRMuvPBCrF+/HmPHjsXTTz+N7777Dv3790dVVRVKS0uxevVqPPPMM5Z5jR8/HmVlZejYsaNm8hEIBPCLX/xCE/r37Nljee2yZcuwdetWzca7pqYGe/fuRe/evbF//34UFhZi7969mDFjBvLz8w3XXnXVVZg1axZ27dqF2bNna1pwAHjwwQcxZ84cLFu2DP/+97+xZMkSLF++3LIMBEEQBEEQsWgzDTVj7B+MseOMse26Yw8xxo4wxopD/y7Rnfs1Y2wfY2w3Y2xyW5WrPZg+fTq++OILbNq0CU1NTRg8eDA45zGvczgckGVZ+23WnKpaVkEQDBpXQRAQDAbBOcf111+v2Ubv3r27WQ53dmXt1q0bqqqq8Omnn2LcuHEYO3Ys3njjDaSmpiItLc3ymq+++gqHDh3CgAED8OCDDwIAnnrqKXTq1AlbtmzBhg0b4Pf7bcvx7LPPas9z8OBBTJo0CUDYhnrfvn1Ys2aNZoqi0rlzZzidTnz22WeYOHFiRN7nnnsubr/9dnzxxRfYsmVLhJaeIAiCIAgiXtpSQ70IwN8AvGY6/hTn/An9AcZYfwBXAxgAoCuAzxljvTnniRsA64ilSW4rUlNTUVRUhBtvvFFzRhwxYgTuuecelJeXIysrC0uWLMFdd91luK5Tp044fvw4KioqkJqaio8++ijClCEaEydOxLRp0zBv3jx07NgRlZWVqKurwznnnJNQ+ceNG4eXXnoJ119/PSorK7FixQo8/vjjABRb6KeffhpffvklKioqMGPGjJhOjUlJSXj66aeRl5eH3/72t6ipqUH37t0hCAJeffVVzc47LS0NdXV12nWTJ0/GCy+8gAkTJsDpdGLPnj3o1q2bIe8uXbrgsccew6OPPqpp8FX+8Ic/4Pjx4xBF0XD8448/xiWXXALGGPbu3QtRFJGZmZlQHREEQRAEQai0mUDNOV/BGOsRZ/JpAJZyzn0ADjLG9gEYDmB1W5WvrZk9ezauuOIKLeJHly5d8Oijj2L8+PHgnOOSSy7BtGnTDNc4nU48+OCDGDFiBHr27Im+ffsmdM/+/fvjT3/6EyZNmgRZluF0OvHcc88lLFBffvnlWL16NQoKCsAYw5///Gd07twZADB27FgsW7YM5513Hs455xxUVlbGtJ8GlOefPXs2nnvuOdxxxx248sor8eabb2L8+PFISUkBAOTn58PhcKCgoABz587FPffcg5KSEk3Dn5uba2l3Pn36dDz00EOafbfKqFGjLMvy//7f/8O8efOQnJwMh8OBxYsXRwjdBEEQBEEQ8cLiMUVoduaKQP0R53xg6PdDAOYCqAWwAcB9nPMqxtjfAKzhnP8rlG4hgE84529Fy3/o0KF8w4YNhmM7d+5Ev379WvlJiB8j1JYIgiAIglBhjG3knFs6oLV3lI8XAJwLoBBAKYC/hI4zi7SWkj5j7BbG2AbG2IYTJ060SSEJgiAIgiAIIl7aVaDmnJdxziXOuQzgFShmHQBwGMBZuqTdARy1yeNlzvlQzvlQNWIGQRAEQRAEQZws2lWgZox10f28HIAaAeQDAFczxtyMsZ4Azgewrj3LRhAEQRAEQRDNoc2cEhljSwAUAejAGDsM4PcAihhjhVDMOUoA3AoAnPMdjLE3AHwHIAjgzpZG+CAIgiAIgiCI9qAto3zMtji8MEr6hwE83FblIQiCIAiCIIi2gLYeJwiCIAiCIIgWQAL1GUxRURHMYQUJgiAIgiCI1oUEaoIgCIIgCIJoASRQtxHTp0/HkCFDMGDAALz88ssAlC3Jf/Ob36CgoAAXXHABysrKAACHDh3CxIkTkZ+fj4kTJ+L7778HAMydOxe33347xo8fj169euHrr7/GjTfeiH79+mHu3LnavW6//XYMHToUAwYMwO9///uIsixcuBDz5s3Tfr/yyiu499572/DpCYIgCIIgfjyQQN1G/OMf/8DGjRuxYcMGPPPMM6ioqEBDQwMuuOACbNmyBePGjcMrr7wCAPjFL36B6667Dlu3bsWcOXNw9913a/lUVVXhyy+/xFNPPYWpU6di3rx52LFjB7Zt24bi4mIAwMMPP4wNGzZg69at+Prrr7F161ZDWa6++mp88MEHCAQCAIB//vOfuOGGG9qnIgiCIAiCIM5w2izKx6nAnj1/RF39zlbNMy21H3r3/l3MdM888wzeffddAMAPP/yAvXv3wuVy4dJLLwUADBkyBJ999hkAYPXq1XjnnXcAANdeey3+53/+R8tn6tSpYIwhLy8PnTp1Ql5eHgBgwIABKCkpQWFhId544w28/PLLCAaDKC0txXfffYf8/Hwtj5SUFEyYMAEfffQR+vXrh0AgoOVDEARBEARBtIwzWqA+WSxfvhyff/45Vq9ejeTkZBQVFcHr9cLpdIIxZZd1URQRDAYtr1fTAIDb7QYACIKg/a3+DgaDOHjwIJ544gmsX78eWVlZmDt3Lrxeb0SeN910Ex555BH07duXtNMEQRAEQRCtSNwCNWMshXPe0JaFaW3i0SS3BTU1NcjKykJycjJ27dqFNWvWRE0/atQoLF26FNdeey0WL16MMWPGxH2v2tpapKSkICMjA2VlZfjkk09QVFQUkW7EiBH44YcfsGnTpgiTEIIgCIIgCKL5xBSoGWOjAPwdQCqAsxljBQBu5Zzf0daFO12ZMmUKXnzxReTn56NPnz644IILoqZ/5plncOONN+Lxxx9Hbm4u/vnPf8Z9r4KCAgwaNAgDBgxAr169MHr0aNu0V111FYqLi5GVlRV3/gRBEARBEER0GOc8egLG1gKYAeADzvmg0LHtnPOB7VC+qAwdOpSb4yzv3LkT/fr1O0klOrW59NJLMW/ePEycOPFkF+W0gNoSQRAEQRAqjLGNnPOhVufiivLBOf/BdEhqcamIdqO6uhq9e/dGUlISCdMEQRAEQRCtTDw21D+EzD44Y8wF4G4ArRs6g2hTMjMzsWfPnpNdDIIgCIIgiDOSeDTUtwG4E0A3AIcBFIZ+EwRBEARBEMSPnpgaas55OYA57VAWgiAIgiAIgjjtiCfKxz8BRHgucs5vbJMSEQRBEARBEMRpRDw21B/p/vYAuBzA0bYpDkEQBEEQBEGcXsS0oeacv637txjAVQBOesi80425c+firbfeOtnFiJtLLrkE1dXVUdMsWrQIR4/S3IogCIIgiB83cYXNM3E+gLNbuyDEqcV//vMfZGZmRk1DAjVBEARBEEQcAjVjrI4xVqv+D+BDAAvavminN6+99hry8/NRUFCAa6+9FgCwYsUKjBo1Cr169dK01fX19Zg4cSIGDx6MvLw8vP/++wCAkpIS9OvXDzfffDMGDBiASZMmoampCQCwfv165OfnY+TIkZg/fz4GDlQWDCRJwvz58zFs2DDk5+fjpZdeAgAsX74c48aNw+WXX47+/fvjtttugyzLAIAlS5YgLy8PAwcOxIIF4dfao0cPlJeX25bjrbfewoYNGzBnzhwUFhZqZSMIgiAIgvixEY/JRxrnPF33f2/O+dvtUbjTlR07duDhhx/Gl19+iS1btuCvf/0rAKC0tBQrV67ERx99hPvvvx8A4PF48O6772LTpk346quvcN9990HdvXLv3r248847sWPHDmRmZuLtt5Vqv+GGG/Diiy9i9erVEEVRu+/ChQuRkZGB9evXY/369XjllVdw8OBBAMC6devwl7/8Bdu2bcP+/fvxzjvv4OjRo1iwYAG+/PJLFBcXY/369XjvvfcinseqHDNmzMDQoUOxePFiFBcXIykpqS2rlCAIgiAI4pTF1imRMTY42oWc802tX5zW5Xd7D2N7fetqTgemJuGP53ePmubLL7/EjBkz0KFDBwBAdnY2AGD69OkQBAH9+/dHWVkZAIBzjgceeAArVqyAIAg4cuSIdq5nz54oLCwEAAwZMgQlJSWorq5GXV0dRo0aBQC45ppr8NFHit/osmXLsHXrVk37XVNTg71798LlcmH48OHo1asXAGD27NlYuXIlnE4nioqKkJubCwCYM2cOVqxYgenTpxuex6ocBEEQBEEQhEK0KB9/iXKOA5jQymU5Y+CcgzEWcdztdhvSAMDixYtx4sQJbNy4EU6nEz169IDX641IL4oimpqatOvs7vvss89i8uTJhuPLly+PKA9jLGpeduVWy0EQBEEQBEEo2ArUnPPx7VmQtiCWJrmtmDhxIi6//HLMmzcPOTk5qKystE1bU1ODjh07wul04quvvsKhQ4ei5p2VlYW0tDSsWbMGF1xwAZYuXaqdmzx5Ml544QVMmDABTqcTe/bsQbdu3QAoJh8HDx7EOeecg9dffx233HILRowYgXvuuQfl5eXIysrCkiVLcNddd8X9nGlpaairq4s7PUEQBEEQxJlIPHGowRgbCKA/lDjUAADO+WttVajTnQEDBuA3v/kNLrzwQoiiiEGDBtmmnTNnDqZOnYqhQ4eisLAQffv2jZn/woULcfPNNyMlJQVFRUXIyMgAANx0000oKSnB4MGDwTlHbm6uZhM9cuRI3H///di2bZvmoCgIAh599FGMHz8enHNccsklmDZtWtzPOXfuXNx2221ISkrC6tWryY6aIAiCIIgfJSzWsj9j7PcAiqAI1P8B8BMAKznnM9q8dDEYOnQo37Bhg+HYzp070a9fv5NUovahvr4eqampAIDHHnsMpaWlmuOjFcuXL8cTTzyh2VoT8fFjaEsEQRAEQcQHY2wj53yo1bl44lDPADARwDHO+Q0ACgC4o19CtCUff/wxCgsLMXDgQHzzzTf47W9/e7KLRBAEQRAE8aMlHpMPL+dcZowFGWPpAI4D6NXG5SKiMGvWLMyaNSvu9EVFRSgqKmq7AhEEQRAEQfyIiRY2728AlgBYxxjLBPAKgI0A6gGsa5fSEQRBEARBEMQpTjQN9V4ATwDoCkWIXgLgYgDpnPOt7VC2ZmMXto4g4iXekIIEQRAEQRC2NtSc879yzkcCGAegEsA/AXwCYDpj7Px2Kl/CeDweVFRUkEBENBvOOSoqKuDxeGInJgiCIAjiR0/MKB+GxIwNAvAPAPmcczFW+rbGKspHIBDA4cOHtc1RCKI5eDwedO/eHU6n82QXhSAIgiCIU4BoUT5iOiUyxpwApgC4Gkq0j68B/G+rlrAVcTqd6Nmz58kuBkEQBEEQBPEjIZpT4sUAZgP4KRQnxKUAbuGcN7RT2QiCIAiCIAjilCeahvoBAP8G8CvOuf3e2QRBEARBEATxI8ZWoOacj2/PghAEQRAEQRDE6Ug8OyUSBEEQBEEQBGEDCdQEQRAEQRAE0QJIoCYIgiAIgiCIFkACNUEQBEEQBEG0ABKoCYIgCIIgCKIFkEBNEARBEARBEC2ABGqCIAiCIAiCaAEkUBMEQRAEQRBEC2gzgZox9g/G2HHG2HbdsWzG2GeMsb2h/7N0537NGNvHGNvNGJvcVuUiCIIgCIIgiNakLTXUiwBMMR27H8AXnPPzAXwR+g3GWH8AVwMYELrmecaY2IZlIwiCIAiCIIhWoc0Eas75CgCVpsPTALwa+vtVANN1x5dyzn2c84MA9gEY3lZlIwiCIAiCIIjWor1tqDtxzksBIPR/x9DxbgB+0KU7HDpGEARBEARBEKc0p4pTIrM4xi0TMnYLY2wDY2zDiRMn2rhYBEEQBEEQBBGd9haoyxhjXQAg9P/x0PHDAM7SpesO4KhVBpzzlznnQznnQ3Nzc9u0sARBEARBEAQRi/YWqD8AcH3o7+sBvK87fjVjzM0Y6wngfADr2rlsBEEQBEEQBJEwjrbKmDG2BEARgA6MscMAfg/gMQBvMMZ+DuB7ADMBgHO+gzH2BoDvAAQB3Mk5l9qqbARBEARBEATRWrSZQM05n21zaqJN+ocBPNxW5SEIgiAIgiCItuBUcUokCIIgCIIgiNMSEqgJgiAIgiAIogWQQE0QBEEQBEEQLYAEaoIgCIIgCIJoASRQEwRBEARBEEQLIIGaIAiCIAiCIFoACdQEQRAEQRAE0QJIoCYIgiAIgiCIFkACNUEQBEEQBEG0ABKoCYIgCIIgCKIFkEBNEARBEARBEC2ABGqCIAiCIAiCaAEkUBMEQRAEQRBECyCBmiAIgiAIgiBaAAnUBEEQBEEQBNECSKAmCIIgCIIgiBZAAjVBEARBEARBtAASqAmCIAiCIAiiBZBATRAEQRAEQRAtgARqgiAIgiAIgmgBJFATBEEQBEEQRAsggZogCIIgCIIgWgAJ1ARBEARBEATRAhwnuwDE6YUUlBHwSvD7gnB5HOAyR225F1ldksE5EPRL8NYH0FTnhzvZCVni8DcFIToZBFEAGCAIDMGADKdbhMsjwuEUIUkyuMzRUO1HUpoTjDE4PSIYY3C4BHCZw+EUITgYOAd8jQEwMDTV+5HZMRkBvwSXh5ozQRAEQRDtD0kgCeJrDGDlm3txdF8NklKdCAZkCAKDFJQhiAzupHCVik4BjDEEAxKkAIe3IQBPigNpOUlwugRUHG2AFJTR8Zx0+BqDcKc44G8K4oedlUjL9qDDWWnwNwXhTnaACQwN1T6kZnngbwoi6JcgOgXIQQ7BwdBU54fTJUKSuHLOIYBzDi4DAZ+EpDQnpIAMJjAEfBJcHhHehiC8DQE43SJkiUMQmXady+NA0C+hodoH0SXC1xCAIDI01QWiVxADwNvwBTBAYAyyHL6JIDLIEofoFJCc5oI7xYHULA8CviCS0lzIyE2Cr1H5OzXLDdEhILtLCtzJjtA/ZxsWmCAIgiCIMx0SqBPE6XHgxPd1yO6SgqBfgsMpgHMgKc0FxgC/NwjGGDjnCDQEIYc0ry6PA7Ikw++VcLykFk11fvi9EgCg/Id6pGa5IUkcvsYA5CBH0N+IhmofPClONNb5IflluFOcOHagBoLA4E52gsscHABjgDvZibpKH9xJDrg8IoJ+CZwDjDEwBjTVBcA5hxTk8KQ44PdKcLpFJKU60VDrh9MhgAkMSalOgAGNNX4IIkPHHungHEjL9kCWZHgbgnB5RHTqmY6gX4YkyUhKdaGhxoeAT6mPjNwkuDwONNb6IcscWZ2TIUsc3vqAom3mymTDW+dHMCAjGJABDnDOkZ6TBF9TQMk7KEOWODjnEB0CggEZUkA57k52IOiXkZbtQWVpA1weEb7GIGpONAEAasub4HSLOF5Si30bj8PhEBAMypbCfnbXFAgiQ1q2Bw6ngLQOSUjJcCOzUxI8KU7kdE2F4GBgjLVjSyPOBGRJmcS2pO14GwLw1gfgSXXCleRQvgdRQEO1D0lpTmXl5xSDc+VDs3puLnMwofn1wTkHOGzziJY/lzl8jUEE/FJIQeCHIAhwuASIDgGCqFxXVlKLjNwkCKKA9A4eNNb6AQDuZAekIIfDKaCuwgtBZEjN9kBI8Hm4zCGF2gYPKQdkiSvKjSBXxhGBQXQKCPoleFKUVTtvQwANNT6kpLu1Ona4RC1P0SVACOWptjvOOeQgBwQg0CQBTHkOWeaoOFwPX6Nyr6Bfgq8xCF9jEBkdk9BQ7VPK5BIgOkUIoqI4UvN0ukUEfBLSsj3we4OoLfciJcMFxhg8qU6ITgH1VT40VPuQkumGvzEAh1vUFDtq/+xJVcbOYEDWlEGqYqepXlHgOJyC9k6T013w1gcgBWW4PA6kd/Agu2sqHE7lPVYebYAr2YH0DkkIeCVwrow9riQHGFPqWSXgkyAFZaR3SEJdhRfuZAcCPmVc9qQ6EfBJcLqUZ+dcOSYIDPVVXq3eFWWNU1NMBQMynC4BgiigtrwJvsYgmur9kCVlLDx2oBZ1FV64khwQRKXepaCMproAHE4BTo8Ip1uRF9zJjtA4DnAZkGWujPshZZksc+29eFIUpVkwIEOWZNSWeyGKDO4Up9J+OYfgEOBrDMLhFOBJccLXGEDAL8PhFCA6lZXgpDQXHC4BtRVeOF0i0rI9EESG2vImMMbQ5bwM1FV6IUuKXON0i8r7bQrC1xSEFJQhOpT+KTndpSkWa040wuVxQHQICPglgAPZXVIgOhl8TVJIZuHwNQQhSxzuFGWMdyc7IIoC/L6gJs+AAd37ZCM53ZXQd9fWMPWjPB0ZOnQo37BhQ7vft6UDAqAMCmrHpGih7bWkXOaQZUWoJBInGJAgiAK4xFFf7UVTXQDVxxsR9EloqPHj+x0V4BxoqvMDDKiv9Fnmk97BA4dLRIfuqUjL8SCzYzK6nJeJlEwXxJA5S3sL3UrHyjWhinPFbKb8cB1cHgccLgFN9QE01vjhdIuor/JqKw1Ot4hAaADL7JiM2oom+BoC4HJIWAk9iugQEPBJ8DUEEPBJ2sBQV+VVOnC/DF9jAA6XiMZaZSLmdInwNgTABIbMjsnK4FjnR8Avayskal2lZXuQ3TUF3oYAGmv9cISEAsYYHG5RG1whA+4UB2qON6HiaD06dE9FSqYbDTV+iA4BDEAwKCPQFIQ71YmgX3nvyqRW+Y7SOyRBlrkyAWsKItAUhCxzJGe4IYoMTGBoqldWYxiAlEy3MiDW+SE6BRzZXQWXx4Gcbqk4drAGTbV+pGR54K33IynNBc4Bb70/VLcy6iuVgdPlESGIisAmiAyCoJhAiU4B/iZlpYhzDkFQVltSs9xoqg9ACsior4psjw6XgKA/tCqW4oQntNIiOhl8jUE43SKSQ+XxhCbJAa8EJiAksCkTakFkyuQ0NFkF59qcU30HqhDvawiAAxBFAa5kB+oqvHC6xVAbYXB6lGNyUEbpgRoEvBJSs93I7pwCSeKoOdGIoE+G3xuEJ9UJf1MQTo8jJCwoAgLnSl/ncIkQRWUlShQFSJJSPrXv9TUF4U5yaAJuwBuE4BAADngbA0r9CgyCQ6njQFNQERg44G8KJvSNpWa70VDlU+rFZrgUHEqbd3oUgVF0CHCEBDFV8JYCMgBAkrgmRJtRuw/zsCw4GBxOEX5vMOYKoOgQIAWVewmh71iWuOG40y1ClrlWplOWlqx4tsVqKQNcHodlGxIcTJm42PyOhcMlQArat41EcXpECILSH3hSnfB7g3C6RLiSHJCDMryhfsKd5IAUlOFvCmpKPhV9mznVuPy+weh6fma735cxtpFzPtTyHAnUBGGktqIJ3++oRHK6C9VljTh+qA41JxohOgTIEkfNiSbrDjUk3CSlKqsHaTlJcCeJYQ1laGDze4PK4NgUQDCgaHwUbYuIgE/RLkhBDiYo2hhfYxC15U3I7JQMIaSZDPolCCEtALgi0IAxBH2SwRymuTCBaaO6uqLgSXbA6XFACsioq1S0Ua4kB0SnoK0YJKe7EAzI8NYH4E52wOESUXO8EUxgcDgFJKW54PSIqD3RhOqyRqTleFBb7lVs4N0i3MlOMEHR+kgBWRE4vZLyfICmsUjOcKOuokn7DQABvwRPsqLF9dYHIEmK5sXpFrU6rq/yaQOdOlgkpbvgqw9o9aYObADCg1vI1KhTr3TUVXjhawyCyxxdzstA0C8jJdONpno/BFHR/AR8isCanO6C3xvUVlvC/5TfQb8ER2iQEx0C5KAM0SWEVqdcEARlBSU12wNvfQC+xiAEURkkXUkOSAEJ3sYgfA1BpV0ElAFRXSFqqvNrz+Bw/f/27jxKjvs67P339j49vc1M9wwGywADYiN2kBC4QKRAcZeiQ9mWZT9vykls5z0f5yR+sR0n551jJS9+9stxnLwX29GR48TOoii0JD5JpkGJormKFAWQ4AIS62CbGWCW7umZ3tf6vT9+3Y0ZYEASaAwGA97POTjorqquulV161e3flXd424VZm6Py975qjqICzvM60JmXRTWa7aAbfbYeRsXN+VCjVq1TiTeQa1SBxGcmtNa50DIy8xEkXBPgGiig+xUCVejt7Uz5m98t8LB1+Gh2jiOxCWtfy4RquUa9ZrB7RHqjWLQ7XWBY6g7hmDYRzlfpVys4fbYXr1quY67cdGSny7j7fDg8dp97O/wUK/bAjLQ6aUz5qNeM4S7Axhj5twRc+oOHWEfyeEsHp+b9FiBUJcfEUiPF3A1LhKbvbA2V+tUKw6FGXuXsNlTWas6hLv8GAOeWRcf7sYdwXKhhttjv1MSDNtcAeiM+nHqhly6RDDqp9i4m+fv8NAZ87cuPD1eezfSHht1cukyHp+bjrAXx7G51uyZrJbt8SEuKGaqOMYQ6w3ictvvqXRG/BTzlVY+R+MduL2u1l3B5mOBzV7S5mN00+MFAKIJ26vt7/RSztse5FBXgEDI9pD6Am7qNfvdmVrFoZitkBgIt467WsX2djf3E9C6mDOOvSuBYL9nE/K2LvSnJwpMXci3vq8T7g6QS5dbj/xVy3V7ke62+X3xjo7dPh6vi+xUmUCnzZFKsUaoy0+t4uANuFu54XIJhUyFQrZiHy1s9PJ3hHxkkkVqVduGN3vu7QWsEOvrINQVIDtVAiCxKky0t4NSropTN627TB6fq3XcVUt16jXTepS0eSHpah0n9jh1NS4ufR0eynnbqeH2unC7L+aY45jWXYsP6vQxzsU7I8VstfVIZDlfa33HCewx0Bnx244Bj1At1cmkSnSEvXi87sZde3tRXKvUWz3pgU4P0nhcs5CpEOj0MjNZQBB8QU/jAlhanVPNY7VUsB0L/qD3Yi4Aoe4A3sZdghtJC2qlrrNKscaFUzNkk0XKxVqjl7bWuu3l1A2p0RxO3QERXHKxaAh02t45f6e31SNlb9uZxq1N2+jVKg61qr3dG+j0kh4r4PW7CIR8BIIeao0Tlj25VcFAMOonGPURXxnCqRkKmbJ9drw7YHtTY34yqSLh7gAdIR9un4tqqU4xa8f5OuY+BSbQej69yRh7MvUHPW31yDfv0jhO46R/hUcXmieTZi9ls0B26o4t9ps92PM8BtBcxqVxt3o+G0V78/GpWuPLrc3b5OWi7d2RxsaYvb6z5/1x83Fed6XUx9cHFdT6DLVS18DX4WH1lp7FDuPq9HcCEOsLzhns9bk/8Fk09yVFqoi9KGhXsyCzz59euThrFslut8v2XjTMLsCbdwCutIzm62bc7sazss0LBXHZRzyavxQjIri9QtB75e3ycS4oP87rrpRS89GHcpVSSimllGqDFtRKKaWUUkq1QQtqpZRSSiml2qAFtVJKKaWUUm3QgloppZRSSqk2aEGtlFJKKaVUG7SgVkoppZRSqg1aUCullFJKKdUGLaiVUkoppZRqgxbUSimllFJKtUELaqWUUkoppdqgBbVSSimllFJt0IJaKaWUUkqpNngWY6EicgbIAnWgZozZLSLdwP8E1gBngC8aY9KLEZ9SSimllFIf1WL2UD9gjNlpjNndeP87wHPGmPXAc433SimllFJK3dRupkc+ngD+svH6L4HPL14oSimllFJKfTSLVVAb4Psi8oaI/GpjWJ8x5gJA4//eRYpNKaWUUkqpj2xRnqEG9hpjzotIL/CsiBz9qB9sFOC/CjAwMLBQ8SmllFJKKfWRLEoPtTHmfOP/CeApYA8wLiL9AI3/J67w2a8aY3YbY3YnEokbFbJSSimllFLzuuEFtYh0iki4+Rp4BDgMfAf4UmOyLwHfvtGxKaWUUkopdbUW45GPPuApEWku/2vGmGdE5ADwpIj8feAc8NOLEJtSSimllFJX5YYX1MaYU8COeYangAdvdDxKKaWUUkq142b62TyllFJKKaWWHC2olVJKKaWUaoMW1EoppZRSSrVBC2qllFJKKaXaoAW1UkoppZRSbdCCWimllFJKqTZoQa2UUkoppVQbtKBWSimllFKqDVpQK6WUUkop1QYtqJVSSimllGqDFtRKKaWUUkq1QQtqpZRSSiml2uBZ7ACWslOnTvHaa6+xZ88eIpEIr7/+Oo8//jivvfYa8XiczZs3AzAzM8Pzzz9PV1cX4XCYDRs28Oyzz/LQQw8xNDTE9PQ009PTxONxKpUK2WyWvXv3kkqlGB4eplgssnv3bvr7+zlz5gxHjx7FGEM0GiWdTvP444/jcl28NkqlUrz66qvs3LmTN954g8cff5w333yTYDDIjh07ADh48CDGGDweD5VKhbvuuguAcrnMM888Qzwep1ar8alPfYparcbTTz/N5OQkn/nMZ6hUKq0YhoeHefjhhzl58iTBYJCpqSk6OjpYuXIliUSCV155hccee4w33niDUCjE9u3b52zDQ4cO8fbbb3P77be3YgCoVCrs37+fe++9l5mZGYaHh3nggQfmfNYYw/e+9z02bdrE8ePHWbduHadPn2ZgYICRkRH6+/tbMUQiEeLxONu2bSOTyfDcc8/R3d2NiDA8PEyhUCAQCPDoo4/y6quvEo/HMcZw9913s3//fnp6eigWixSLRbq7u3n33Xfp7OykWCyyfv16Tp8+Ta1WA6Cvr49gMMjp06cBqNfrxONxYrEYnZ2dnDhxgnK5PG9OiQibN29u5dO6devo7e3llVdemXf61atX8/DDD/ODH/yA0dFRHMdh7969xGIxnn766TnLPnnyJJs3byaZTBKLxejq6qJYLHLmzBkSiQSxWAyXy8WBAwfYtm0boVCIZDJJJpPhrrvu4sc//vGc7bBt2zbee+89uru7mZmZ4ZFHHuHZZ59lw4YNc/Jh9+7dHDhwgFAoRF9fH+Pj4wwNDREOh+nv78flcpFMJtm7dy/PPvssjuMwMDDAqVOnqNVqbNq0iZ6entY2WLt2LZlMhmAwSLVaZWRkBIA1a9YAtHJycHCQ5557rpUPPp+PZDLJ448/zoEDBxARhoaG8Hg8PPHEExSLRZ599llqtRqrV6/myJEjbNu2jTvuuIP9+/eTSCQol8vkcjl6enool8t8+tOfBuD06dMcO3YMx3GIRqPMzMywY8eO1uc6OzsZGBhgw4YNvPLKK4TDYQYGBnjxxReJxWK43W6SySQ9PT0cPXoUgI0bN5JOp3nggQeIRqMcPnyYdDrNfffdx7Fjxzh//jwPPPAAQ0NDDA0NUa1W2b59O4cPH2ZkZISHH36Y48ePc+bMmVa+bNmyhVQqRSgU4uTJk9x7772sXLmSF154gXvvvZfXX3+dXbt2ceDAAeLxOI7jzImh6ciRI0xMTLB3717279/PJz7xCZYtW9YaPzo6ypEjR3jwwQcRkXlzV6nFdOHCBQ4ePMhnPvMZ3G73B06bzWb59re/jYgwMDCA3+9nz549vPPOO+RyOXbv3s3+/fuJx+O89957AAwODpLL5Th//jyRSIR8Po/jOITDYTKZDJFIhEKhgIiwZcsWjh07Rr1ep7u7m+7ubk6cOME999xDJpNhaGiIYrF42bHkOA5+v59qtdoaZ4zBGIPf72ffvn0cOnSIsbGx1jquWrUKESEUCnHmzBny+Twiwu23387Zs2cJBoMEg0HOnTsH2PNXT08PfX19HDt2DIBNmzYxMjJCPp/H7/ezbt068vk86XSamZkZANxuNxs3buS9995jcHCQUqnE2NhYK/Z6vc6KFSta7Wu9Xqejo4NiscjmzZs5e/Ys+Xwen8/XOreXSiU8Hg/bt29n9+7d1yELri8xxix2DNds9+7d5uDBgzd8uV//+tdxHKd1wm8WVo7jsHLlytYJfuPGjRhjGBsbI5PJtD4fj8dJJpN0d3czNTU17zJ8Ph+VSmXOsA0bNnD8+PHLpl2zZg1+v5/mvpyYmGB6ero1vr+/nwsXLrTmAVw2n2aszQagaf369ZTL5dbBdTUCgQClUonly5e35tlcTtPsOGaPy+fzjI6O4vf7W8XnunXr5lw4VCqVOcXCB8XQtGHDhsu2z2wiMie+FStWMDo6+tFWeJHMzrmlHIfL5cJxnOsWz2233cbQ0NBlw+fbp729vWQymTm50jT7+JlvGW63e97jcj7r16/nxIkTAK2Tx4eJRCIsW7astYzZ7cC6des4efLkR1r2lYTDYbLZ7LxtTlM0GqWvr6/1vrn85j4XETZs2NA6qTcvCvr6+uju7iafzxMMBqlUKvT29vLwww9/aBFzNer1Oj/4wQ/YtWsXvb29jIyMcOzYMT796U/zwgsvMDIywv3338/q1atJJpMcPHiQhx56iGw2y2uvvcZdd93F66+/zoMPPojf779s/qVSieeee47777+fkZERstkse/bsuWz5d9xxBz09PTz33HNs3bqV/v5+wBY5L774IqFQiFQqxUMPPYTb7ebVV18lkUgwNTVFNBpl06ZNc5ZbLBZ5/vnn2bdvH8FgEID333+ffD7Pzp07ee6557j77ruJxWKXxTw8PMzJkyfZt29fq1178cUXGRwcZGRkhN7eXtavXw/A9PQ0r7/+OpFIhFgsxsqVK3nppZfo6ekhGAyybt26VhydnZ2Uy2Wee+459u7dSzQapVar8eyzz7Jnzx56eno4d+4cQ0NDrF27llOnTrFv3z6ef/551q9fz6pVq3jxxRcZHh5m7969RCIRfvzjH/Pwww+TTqc5dOgQ+/bt49133yUQCLBlyxbeeuutVo49//zz3H333fzoRz8ikUhw7NgxXC4XK1asoFAo0NPTw6lTpygWiwwMDOA4Dlu3buX9998nGo0yPT2Nx+PhhRdeAGynREdHB2A7lLxeLyKCiFAsFvH7/SSTycvO1bOPw9nnuOvt0nPSQvqgNuBG83g8rU6qS7lcLn7jN36DcDh8g6MCEXnDGDNvNa8F9TX4yle+AtiTzI4dO3j55ZcBmJycJB6Pk8lk6OjowOv1AvaAmJycJBAI4Ha76ejoIJVKtXq5qtUqpVKJaDRKsVikUqkQj8ep1+tkMhlqtRqJRKK1/FQqBUB3dzepVIp4PD4nPhEhHo+TTqcZGxsjHo+Ty+XweDwEAgHANtTGGFwuF7VajVAoNCfWWCxGLpdrNdRTU1OICF1dXa0YmifPrq4u0uk0sViMqakpPB4PoVAIr9fb2ia5XA6v1zvnZCUicwqV2T1czTg6OztbV7yzxzenaV6YNJc/MzNDJBIhm83OicHv9+Pz+VrLT6VScxpREWldiSeTyda+iEQiJJNJurq6yGQyrWmy2Sw7duzg7bffZs2aNdRqNYaHhwGo1Wp4PBdv/vT19bV6/CcnJ0kmk3MuDGbbsmULExMTrd6MgYEBRkdHyeVy8/b0NXs0mlf+oVCIVatWMT09TTqdRkSo1Wr4fD7q9TrBYJBMJkMgEMDj8RCJROjv76dUKpFKpcjn8xSLRTweDz6fj1Kp1MrHS7dDc73Gx8db+Tw1NUVXVxfT09PEYrFWfiaTSbxeL8FgkF27dlEul/nRj37UOiby+Tw9PT2k02kAEokEK1asoFarkUqlyOVyc7bBunXrKBaLnDt3jo0bN1Kr1RgaGmqNj8ViiAjpdLqVD+FwmHQ6TTweZ3p6ulU8e71eenp68Pv9RCIRjh07RjAYbPWGNIugaDRKPp+nWq3S3d1NJpNpHQ/GmNZx2cyh5nLq9Tput5twOIzb7cbv97fmmUwmW/sil8vR2dnZOqF5vV5KpRI9PT2AvYBs5mS9XiebzRKLxXAch+npaRzHIR6Pt078XV1dzMzMtHKt2TuWTqfx+/2tfGj23Mfj8Vb7deHCBYLBII7jUCqVWndzZuddNpslGo22PtvcDrVabd6OgmbPPdBals/no1ar4XK5WvOfvZxKpdI6lhzHwe12t8ZXKpVWAVCr1Th58iQul4vNmzdz+PBhwPYSNu8UAWzdupXjx49TqVRYu3YtExMT5HK51sXcqlWr5vTEN01NTXH+/Pk5nSBbt25tjS8UCpw6dQqPx8Pg4GDroqk5TbVabfXugb0Q8/v9vP/++3OWs23btjnb4J133gHsRdXAwABAa91Wr17N2bNnCYVCrbszszWn27hxI16v97IYXC4Xt99+OyLSmrbp0s6eZcuWMTY2RiKRoK+vr3XXMBqNsmrVKnK5HGfOnCEQCLBu3TqOHj06pxiavR82bdrUuuCCi50eg4ODnD17FsdxWuvW3IbN+JoXtx9UbF2tvr6+Vq/u5OQkYC+wp6amqNVqhMNhOjs7W8dYIBDAcRxCoRCVSoVyuUw4HJ7TRjSL4Ntuuw3HcYjFYrz11lusXbuWnTt3cujQIe68806eeuopqtUqkUiETCbTOg81j4tgMEg4HOahhx7iu9/9Lrlcbk7szYudt99++7L1Wr16NbVajUAgQLVaZXh4GGMM9XodsPt4cHCQw4cPU6lUiEajfPKTnyQUCrF//37y+Txg27N4PM7Q0BC1Wg1jTOvc4HK5MMYQj8dJJBIcP3681SnSvFvX7ExsHr9Ng4ODGGPmnKt27tzJ4cOHCQQC3HvvvUxOTlKv1xkZGWnVQlu3bmVoaIif+ImfYNWqVdclB66GFtTqppXL5Xjqqaf43Oc+N28vS6lU4pvf/Cb79u1jxYoVNz7AJeLUqVMcPHiQL3zhC1cs1tVc3/ve9+jq6prT06jaV6/X+cY3vsGpU6f4/Oc/j8/n47XXXuOLX/wiTz755Jwe9WAwSKFQAGhdnDTl8/nLesua01QqldYJf7bu7m7AFvbpdHpOYRiNRlsFeSqVal0kNF9PTU21Pt80u7hvTlculykWi632qjlNKpVqxZdOp+nq6ppzkZBKpYjFYkxPT89Z9uxtcWnvePMCszkvEaFUKlEqlVoXrLOXMzue5uM6zXWavbxgMMjAwAATExOALfiz2Sxg75wEg0FSqRQejwe32926ALx0Xld673a76erqavXsNrdv8/GmZhyRSASv19v6bGdnJy6Xi2w2SyaTwePx0NnZSS6XwxjTKlyb8+vs7CSfz9PR0cGaNWs4cuQIiUSClStXth5NO3v27JzlN+9Orlmzhp//+Z9vdXwBfPe736Wvr489e/YwPj7O/v37+cmf/EkikchluaYWjzFm0R4l04JaKaXUTeFb3/oW9Xqd6elpfu7nfo5nn32W7u5u7r///jnTpVIpvvnNbxKJRDh69Ch33nknn/vc5wBbbH/ta1/j/vvv55VXXuGBBx5g7dq1i7E6bTHG8K1vfYtly5axd+/ey8Z///vfx+v1Xvb9kWvlOA5f//rX2bhxI3feeeeccd/97nfp6urik5/85HVZllK3Ii2olVJKKaWUasMHFdR6b1gppZRSSqk2aEGtlFJKKaVUG/R3qK/Bge9887r/jI2IQPMLLBcHXhw3dwyXTHJD3ZinhBZ2IcaY1ooYO+CDp51veOPbzM15XTadzH7ZeDPPLxlcnOjyLxZdPsnsmc6a/grzuXxecqXJLhkol01jV+9K2+nKiXhxls38vnRbzJ1HK95Lhs+KZP6XbSTmVX3B5aqOuY8+8ULFIJdMbK73sXW9Z7eEH0O8EnGJ3Q+NLxbC5evZ/NJh61xw6XE8d+Krj+GaThbXspxrWMw1fvDS3P6IH7qyq0m9D1v0Zfvv8g+YuQ3YZTFc92P1Q+Jpx3yxXmzrmwOu7Rxw6fQAy9ZtoCN0438274NoQX0NXv7aX2LM9fu9XKWUUkop9dH8zJf/gJW3b/3wCW8gLaivwT/8iyev+up0XrOuSFtXd81e09bFXvP9PFeq8w4y1/3Kc143YhEL3v0uc3pPP3C7zduh7Gr0ODVfX7ySNvP0ol7chxfHXRw0a9h8vRZzP3bFaS5Pk9nj5p/XZfM0V845mafn7Kp6968w79b71l2Dub01l/1M0ny9/zbAK8byAUF+9Emvpsfoaia9ql7Z6xDDdT+0ru8Mb6W/rmj3rcE4jf/N5T1yzeH2Tpdz5ePDTnotUVz9J67lTsE13l24tlVamHX6KLl3tdtm7v6bkwDzLu9KdyKvm+t4F2hO23z5Lc0PbeuvNHy+c8BsPSsH2oz8+tOC+hp4G38cRakruXXKAaWUUkp9GP1SolJKKaWUUm3QgloppZRSSqk2aEGtlFJKKaVUG7SgVkoppZRSqg1aUCullFJKKdUGLaiVUkoppZRqgxbUSimllFJKtUELaqWUUkoppdqgBbVSSimllFJt0IJaKaWUUkqpNmhBrZRSSimlVBu0oFZKKaWUUqoNWlArpZRSSinVBi2olVJKKaWUaoMW1EoppZRSSrVBC2qllFJKKaXaoAW1UkoppZRSbdCCWimllFJKqTZoQa2UUkoppVQbtKBWSimllFKqDTddQS0ij4nIMRE5KSK/s9jxKKWUUkop9UE8ix3AbCLiBv4EeBgYAQ6IyHeMMe8vbmRzTRYmeWnkJTp9nXxq5ad4/tzz5Ko5ugJdvD3xNvlaHhcuvG4vQU+Q0zOn6evso1qvsjK8Ep/bR7Ve5cT0CVZHVhPxRRgvjJPoSOB3+zk6dZSgN8gnV3ySLT1bePLYkzw48CArwis4OX2SqlMlXUoT8oZYF1tH0BskU85gMMT8MWqmxuHkYTq9nRRrRaaKU+xetpuXR17mrv67ePLYkySLSfpD/aSKKQq1AmczZ5ksTPILm38BYwxvjL+BiODCRW8gzuZvHOJHOzsY3HEffcE+ZiozBD1B7l1+LxWnwpvjb2IwjOZGifljHEkdYVP3Jir1CtsT29nVuwuD4Xj6OMtDyynXyogIuUqOeEecV8+/imMcHhx4kDOZMwxEBnhn8h1myjOcyZzhs4OfpT/UT7VeZSQ3wuHkYWL+GCO5EY6kjgAQ74hTrBXp6ehhPD+OYxwGIgOU62UmChP0BnvxuXwUa0VmKjPUnToThQnuXn4306Vpqk6VmlOj6lRZF1vHbbHbeGnkJfxuPwbDu8l3uXf5vXhdXpLFJIlggkdWP0LUH70sRyr1ClWnStATZLwwTt3UCXlD1Jwax9LH2N23m7cn32Z7YjupYgq3uHGJi2wly8Hxg7yfep/HBx8nU8nw7uS7zFRm8Lv9xPwxXOJiujyNz+UjXU5jjCHgCVCsFRmMDjIYHeSHoz/E4/KQKqaId8SJBWIUq0XuW3kf70y+Q9QfZWdiJ7FAjL8997c8NvgYhWqBw8nDTJeneWzNY1ScCuVaGYBlnctwjINLXLx2/jXOZM5wLnuOqeIUK8IrmCnP0NPRQ7le5nzuPOP5ce5feT/ZSpbTM6dxiYtz2XN0B7rZ2L2RMzNnCHgCbOjaQF+wj1XhVfzw/A9ZGVrJQGSAl0deZqwwxpaeLeSqOSK+CEPTQzyy5hGylSwXche4ved2psvT7F2+l5Av1Nr2dadOppJhsjhJf2c/0+VpRnOjZMoZ+jv7Gc4OU66XOTRxCI/Lw+HkYY5MHeHe5feSrWTpDnTTF+xjMDrIhfwFHOMQ9AbxuXyM5EbIlDNE/BESHQkKtQLdgW4y5QwAa2NreXTNo5yZOYPf7adYK3IsfYz7VtzHkakj3LP8Hl6/8Dr9nf343D5Gc6PEO+L0BfuoOlUmC5O4XW7y1TybezbzwvALHE8fZyQ7wpnMGYYzw+zs3clAZIDuQDeHk4fxuDxU6hX2rdrHgbEDnMmcYd+qfdzTfw/PnHmGVeFVFKoF8tU8n137WQQ4kT7BHWEf+Wqe8fw4XYEuxgvjhH1hwt4wxVqRrkCMSr3KoYlDgGFrfBsX8uc5kT7Jzt6dnMucxTEGlwijufN0eDoYmh6iVC8R9HSwuWcLQ9NDdHd0E/GFCXlDDCQ+RcLrwtQzPH3qadZG19LT0YPj1In4oxgMy4LLmCxO8m7yHXb27qLLH8Mlbsr1sj0WjSFZnGSiMMHa2Fr8bj/leoXzuVFyje1WN3XqTp1cNceZmTMMRgep1Ct2uKmzKryKb5/8NqVaiZXhFbyfOoKDQ4enA2Mc/O4Abpe71U45xiHgCeAWNwaD1+Wl6lSp1CusCC0nV8mxrms9o9lRloeW0xfso6ejh2wly9Gpo6wIraAr0EW+mifij5AsJHGJEO9IUHWqdHo7qTpVzmbOMhAeYLI4yYn0CTZ0rac32MvRqWMcTR8lWUiysWsj67vW8+bEm/QEenC73GTKGYZzw1TrVXxuH46p42q0KSFviGKtQLo8jdflZSA8QN3UAQi4AxRqBbwuLwAODvlqnsHIIOey51gZXkmxWsTr9rIjsZ2gpxOPy5YNxhjGCmMYYwh6g/jdPl6/8DrdgR4ylQzb4tso1Yut3JgoTOB3+7mQO8+57DB7V+xleedyjqePkQj2UqqVKNaKeF1eyvUSw9kR8tU8VadKzB+lXK/gd/uYLEwS70jgc/tIlZIAPLrmMdziZrSQJRRcibsyQtQfYzQ3CsBYYYy9y/eSq+QYyY3wiWWfAKDm1BjJjlCsFUkEEyzvXM6r51+lbuqsCC0n5AvxxvibfGrlp/C7/bw08hLvJN9hS88Wm5cuF6niFMYYUjXIeAY5O3WQQq3AqvAqqk611U4UqgUAfG4fG7o2ADBeGOeR1Y9waOIQ/aF+tsW3sSy4jJPTJzk5fZJH1jxC3anjdXlxjEO2atun6dI0pXoJl7ioOlW6/F2M5kYp18sMTQ/hdrkZzg6zq3cXe5bt4U/f+lNePf8qg9FBIr4IOxI7WN+1nqdPPY3f7SdfzSMiBDwBgp4gU6UpDk0cYnt8O6vCq3g3+S5+t5+oP0pXoIuQN8Sm7k28M/kOPrePR9c8ypGpI5xIn+DOvjtZHVmNwTCWH2vVIX63n78997cIwk9t+CmePPYkO3t3kuhIMJobJewLE/FF8Lq8vDDyAudz58lX8zyx7glmyjMki0ky5QzH0sfY07+Hx9Y8dr1KuutGjDGLHUOLiNwDfNkY82jj/T8DMMb8/nzT79692xw8ePAGRgiTk+f44//wj4lPO7wz6GLVpKHugsmYkAtcnK6jJnRnDWMxbMPsMmw7Vafkg/M9wp0nHGaC8PwOF4EKVD2w9Yyh5IN0WEhMG6bCghiI5g3nE25EBHelTs0NK5OGjgq4jdCVNRxYb6ddnnXjrjo4OKycNLy5zkWoCC4M/gqcXiasHjeMxoWeLIgDdTd05eDUMij7wFODgHgJ1Fz25JGr8ImTDgWf8NZaYUXKUHNB0Q+ZoNCVM4x3Ce46DEwaCn4Yjgu+GsSzhrEuwW3AhYuCx6F3GnrThmwniIGJqFBtXNpFC+CpQ8UDgYphMioAuAHExXjYobMEHRWoue20YN9H84Yjq4RABcTjJliG3mSNcBHKPmG0B+oC3VkQl9A94+Ctw+HVwpoJw0xQqLohMW0422dj8tTBEXA7djmdZQgVDRNRodABblzEyh78VegoOVRcBuNxkfJVScwYAjWh5IGKFzoqhsmIEC6CESj4oX/K4K7DVESYCcLyKcOJ5YK/apfXOw3BiqE/ZXhjvb2h1Jc2FAKCr2oY7hUiVQ+JqTrjcQ8lU6U/bah4hLVjDh1l4eWtQjQHvhoEqoaqG/xVSEaFZVPGxhKAikdIh8DlQHfRTU+6RtkLY13CVEQIlA0Dk4ZUWCjb8y9+PHRNV8kFXWT9ht0nHLyOcGC9UHeB4xJWpV3UnToDEw5vrHcRn4GqG8JFw3RIyHXA5rMOJZ9Q8ENHGYJlw1u3ubjQBb0zdp/1T9ljzWVgJgiTUcG4wFeFlSko+mA6BCsmDbkOmIgJfWmDadyHG+kRNo0YSl67zxNZ6MnAhW4hnDfsOO1wZMBFMmL3+11HHU4tdzEeE+rSaCd9HkKZGsvShpEeoSdnyPntOtTcUHfZY3Om0x4XVbfgdmw+5f1gPG56U3WWTRuKPmGsG/wVwNj16srbY6LugpIP8n4bi0/c1J06fWm7/bvycGyFXffVE4Zs4zjsLNn51AVOLhcSM5APwHACNo4YSl7h1G17eSv8IL9q/phexq9/I3kFdTz8vvwuq8xZvsR/vGHLVR8ff8GvMCID/DPzL3BTu6HL/jN+jXHp5+8e/AMm+33kyzl8xo2vXGfXkGEiCkW/MBmFxIwh2yGEiwaXY8+XfTMGB6EnD44xJKNCMgLexmp467YN7KgKk2GYCl9ctttAf8pQ8dh2PpEx+GqQDQjL04ZDa10UfRApQjZopy34bdu+47Rj2ziX4KkbzvYKG0YNZS+cXCGsmLTtUbqxPF/VnqdyHcJUCIoBGLxgONcrTERtm9ph3ACEMnV73osJdYFlaVvXJDL2HOqIXQ9/FQLVxnm20dRWPXZ9jQj+qmnECI7LniMeu+9n+amdX7xxO7hBRN4wxuyed9xNVlB/AXjMGPPLjfe/CNxljPn1+aZfjILaKZVY8ep7GHHf0OUqpZRSSin412PP8Ev/y41/KviDCuqb6pEPQOYZNqfiF5FfBX4VYGBg4EbENIcrEOAPvO/BTBbGJ2Hlcgj4IZcDZ1aoU9PQEbD/ajVITsGKfnAJVGsQ7IBUGobOwPB5O273DsCBSg3KZRgdg1gElvXazzc/d2HcDl+7BjJZwMCFCeiNg98HHo9dps8HuTwYByZS0N8LZ0ehK2qHL+u10xoHXC547Q3oikBXDCpV6OkCb7Mr0m9jErHz7QhAqQQj5+1ym+s+k7Hjsnkby/B5CIdgZf/F7ZDogfSMHZaetsuKRsBxYDIFvT0gLphMQix6MYZ63W5zj8fOYzIFkRAEZt0aODditxMCwQCsXwvGQK1u44eL62yA4VE734232X1WrcHyZXBsCKpVu53rjt0WYNff64FKxcYiLhtLagpS05DPw46tUK/ZfePz2fgCfvC44fQ56O6CUNDON9Rp12/kvJ1fTxfkCnb6ahVWLbfLPDsCp87AltshHITvvwRrVkF31O67FctgZMxu9744FIp2v4yO2e3q89j97fODU7exjU1Ab8JuH2kcetUqhMMwkbTbqCtm51Uu2xxY3gflytyDolqF6Rm7PRM9dt3ODNv1KldsbidTF3P67jvtNvd67XrFG585OwLLEnB+3MYU8EMmB+FOO43Xa3OqVrP7s1KBYhHyRVg7AC+/bvdfX8LmeKFocwyBqbTdNsEAuN02/6pV+/rsMCTicNcdcH4MpjMwPgF3bAeft5EXVSiW4MRp2H67nefIBfjETjB1m8OjY3Z8b9yu9x3bbIs2NW1zw+2y27mny+63Nw/bfb2q3x4jkbA9lkfG7Dq6xO6LrlmPFPn9dl2mpu1+vTABoQ7YervNtWIBZnL2uEhO2c++d8xul13bIOADx9DtipN1/Hb963X7D+w6Tkzafebx2HauUrH7dWravh5cbbf7TCOHumN2nSeScPQkPPGYPX7efR8evt+2DZ1BAELjExSnpqlvuM3Oq+7YuKemLx67gwN2H4LdJpNJOH7Krsv6tfa4Hx6FDbfZuJ953sb62AN2u0Uj8M77Ns5Mxm6HlcvtvujosMdhNmfzrLMDlvVd3AaBALz9nj0uKxXYtA6GzkI2a+fn9cDUjD2+ly+z7ffACihXbY6vG7T5k5qCLRvt656Y3f+Fgm2HXWLzd/VKew7IZG37c2HC7o9lCbtdU2k7j0LR5mipYj9753a7Tb/zDGzeAKtX2TalGee6QRt7LGpzJdBoq/3+xrFroLPT5rbj2GN3csoec4UCrFph2/ByxS536+12fzdzBCAatcOKJbsvgh12nVb22/2ZnoY33rHxuN0293rjF9ua1LQ9Dl7+kT1nfPIuu83Pjth1XLncDh+5YJe3oh/iXXbeLpddXrFk45xK22WEQ7in0nScPktu+XKbLydO2bZj9Ur7ObDn6lzevh4ds8deLm+30cZ1jWGddt7HhmwbmZqy+bNzq821TBYKJdver1sL1SquXAp38giFnoQ9FjwucLBtljE2N7uidjvlCpDotuszkbQ5OrDc7qNmOzc9Y8cl4rbtAAiF7Ha/MG63n3tWx15n0LZT4rI57vfbPK3W7GfAHjvZnN3HwaDNkw6/zV+Pxx4vh4/Brq2QL9g2c1nCxuf12GkiYbuvSmWbI2PjdlitZtvPWh3i3TZf3S67rEoZkmm7/qWSPXYqVZt/E/axHdwuuw7Bxnqk0na/Y8DjvXj+np4Bj4f7P33je6c/zM3WQ33TP/Kh1M2geuECnkQC8dxs18RKKaXUremDeqhvtl/5OACsF5FBEfEBPwt8Z5FjUuqm4+3v12JaKaWUukncVGdkY0xNRH4d+B72e2j/yRjz3iKHpZRSSiml1BXdVAU1gDHmb4C/Wew4lFJKKaWU+ihutkc+lFJKKaWUWlK0oFZKKaWUUqoNWlArpZRSSinVBi2olVJKKaWUaoMW1EoppZRSSrVBC2qllFJKKaXaoAW1UkoppZRSbdCCWimllFJKqTZoQa2UUkoppVQbxBiz2DFcMxGZBM4udhwfURxILnYQ6pal+aUWmuaYWkiaX2ohXa/8Wm2MScw3YkkX1EuJiBw0xuxe7DjUrUnzSy00zTG1kDS/1EK6Efmlj3wopZRSSinVBi2olVJKKaWUaoMW1DfOVxc7AHVL0/xSC01zTC0kzS+1kBY8v/QZaqWUUkoppdqgPdRKKaWUUkq1QQvq60REVotIbLHjULcuEQkvdgzq1qVtmFpI2n6phbbYbZgW1G0SkZCI/BHwNLB8seNRtx4R6RSRPwa+KSI/JyKDix2TunVoG6YWkrZfaqHdLG2YFtRtEJHdwA+BbmCXMeb9RQ5J3Zr+JRAB/hWwC/iDxQ1H3Sq0DVM3gLZfasGIyCe4SdowLajbUwKGgH9rjKmKyE4RWSMinsUOTN0aRCQEhIHfN8a8BPwe4BKR/2NxI1O3iArahqnrTESk8X8n2n6pBSAizfq1zE3ShumvfFwFEbkNuN8Y859nDfsnwGbgNsCN/dOWp4HfM8akFiVQtWSJyHrg14EjwP80xqRF5NvAW8aY321Msxv4j8BjxpixxYtWLTWX5NeTxpipRhu2BViLtmGqDSKyDvgt4CTw340x50XkO8Ahbb/U9TArx4awOTYqIr+JrcMWtQ3THuqPSER+DXgD+A0R+alZo/4Ldgc+ZYy5D/gXjfd//8ZHqZYyEfkd4ClgFNgH/Hlj1JeBnxWReOP9O8ALwGdvbIRqKZsnv/6sMeq/Yc8F2oapayYiXwa+CRwHNgD/vTHqd9H2S10Hl+TYemz9BfBfuQnaML2t99ENAb8MVIFfEpGnjTElY8ykiPymMSYJYIx5S0SygPbsqI+scWs0B/yMMeY9EQkAb4rITmPMIRF5Hvg3wJeMMRURqQOTixmzWjo+IL92NfLrt4wxk6BtmLpm7wFfbfRKR4A/F5FII79eAP4I+CVtv1Qb5suxqDFmXER+2xgzAYvXhmkP9YdoPqdjjPke9sroLWAK+N8a46VZTDfebwceAC7c8GDVUlYAvtkodvzGmBJwCHuVDfC/A/eJyD8QkUeB+wFnkWJVS898+fUmjXNAs5gGbcPUtTHG/FWj0LkDOAbEgP+z8XN5/xjYKyL/q7Zf6lpdIcf+pYj0NItpWLw2TAvqS4hIx+z3xhhn1muDvV36LeAhEVnfGIaIdIvIN7DPhv17Y8zf3MCw1RJyaY6BzS1jzIXG67KIuLHfiJ9qDCsAvwh0Ym9n/TtjzF/fuKjVUnEV+XUHjfxqfK5HRP4KbcPUB5gvvy7hA37TGPNw4/XvGGOKwC8BHWj7pT7ENeTYPxSR8GK3YfqlxFlE5HeBTwB/DbxojDnS+Lbyz2C/wOM0plsG/CMgb4z5VyKywRhzXER+2hjzV4u2AuqmdxU59knsiejvNMb36Rd41Ie5lvxqvF9mjBnTNkx9kI+aX7Om34V9zvUeY0zuhgeslpxrzLG/xOZYXkS+aIx58oYHjvZQAyAim0TkFWAV8G+B7cAviogfSGBvKwSaPwXUKGz+AviSiOSBJxrD9USk5nUVOdZ8xCMGvN74Aux7wKPN/FPqUu3kl4i8D3wGtA1T8/uo+TXPRzcABwDtuVMfqM0cO0jj8cjFKqZBv5TYNAV8wxjz7wAaD7s/gf0CYtIY85XmhI0TUhx71Z0C/p4x5uUbHrFaaj5yjjV8Hvh72Of2/4HmmPoQml9qIV3NOTKK/Qmz/wv7nPTvGGPyNzxitdS0m2OZGx7xJT6WPdSN551/WUS8AI2H2f981iRHgAHAO/v2goh0GGPqQAb4Q2PM3XoiUvNpI8c6Gy9fx16s/bTmmLqU5pdaSG3kl98YM4P9q3X/2RjzoDHmwI2MXS0Nt2KOfewKahF5Avsbhv8E+LXGMDHGZGdNdhcwZIwpz/pcP/D/isgaY0xRb42qK2kzx/4fEek3xvyZMeYvbmDYaonQ/FILqc38+hMRWWGMedoY819Qah63ao597ApqYAT4beBXsL/UsdoYY8RqPl84gP1JKUTkPhEZbHxD/reMMWcWJWq1lLSTY7/Z/DUGpa5A80stpHbza3RxwlZLyC2ZY7f0r3w0rnguW8HGDuvC/vlKMcb89iXjvwqcw/4lnjjwj4wxJ29AyGqJ0RxTC0nzSy0kzS+10D5OOXbL9lCLiG/2ThS5+AsJxpi6sX+M5Slgk4h8atZ03difZ/ki8CNjzGdv9p2oFofmmFpIml9qIWl+qYX2ccuxW7KgFpFfB14UkX8qIn/nAyY9CrwI/HTjc7cbY6aAfw7ca4z5DwsfrVqKNMfUQtL8UgtJ80sttI9jjt1yBbWIfBH4SeDXsd9k/+cick/j+Rz37GmNMdPY35PeIyI54NdExGOM+ROjP0KvrkBzTC0kzS+1kDS/1EL7uObYLfE71I2NX2vcTrgH+Kox5o3GuLPAH2H/ik591mdc2D9Z+RdAGPhFY8xTNzx4tSRojqmFpPmlFpLml1pommNLvIdaRDwi8ofAvxGRRxvP6pwE/mljvBs4AQyIyJcaw1wAxhjHGFMC/ocx5valvBPVwtEcUwtJ80stJM0vtdA0xy5asr/y0bgK+hMgAuzH/tWvvzLGfEVEngKmsb9j+BVgDHjYGPMrsz8/3zdPlWrSHFMLSfNLLSTNL7XQNMfmWsqPfISBncCjxpisiCSBJ0Tkc8aYnxCRtUDYGPO2iPwCcBou7sBbaSeqBaM5phaS5pdaSJpfaqFpjs2yZB/5MPbvtp8B/m5j0A+BHwOPif1LYKcaOzEM/ASQbHzultqBauFojqmFpPmlFpLml1pommNzLdmCuuEpYGdjx+WAd4Ay0CfWE8ArwCljzFcXM1C1ZGmOqYWk+aUWkuaXWmiaYw1LvaB+BUjRuDoyxrwJ7AE6G1dAh4EHjTG/tWgRqqVOc0wtJM0vtZA0v9RC0xxrWMrPUGOMuSAi/x/wByJyEjgAlIB6Y/zQIoanbgGaY2ohaX6phaT5pRaa5thFS/ZXPmYTkcexf2XnXuCPjTF/vMghqVuM5phaSJpfaiFpfqmFpjl2ixTUACLixT7rXlvsWNStSXNMLSTNL7WQNL/UQvu459gtU1ArpZRSSim1GJb6lxKVUkoppZRaVFpQK6WUUkop1QYtqJVSSimllGqDFtRKKaWUUkq1QQtqpZRSSiml2qAFtVJKLXEi0iMibzX+jYnIaON1TkT+dLHjU0qpW53+bJ5SSt1CROTLQM4Y84eLHYtSSn1caA+1UkrdokRkn4j8deP1l0XkL0Xk+yJyRkR+UkT+tYi8KyLPNP4oAyJyp4i8KCJviMj3RKR/cddCKaVuflpQK6XUx8dtwGeBJ4D/BjxvjNkGFIHPNorqfw98wRhzJ/CfgN9brGCVUmqp8Cx2AEoppW6Y/caYqoi8C7iBZxrD3wXWABuBrcCzIkJjmguLEKdSSi0pWlArpdTHRxnAGOOISNVc/BKNgz0fCPCeMeaexQpQKaWWIn3kQymlVNMxICEi9wCIiFdEtixyTEopddPTgloppRQAxpgK8AXg/xaRt4G3gHsXNSillFoC9GfzlFJKKaWUaoP2UCullFJKKdUGLaiVUkoppZRqgxbUSimllFJKtUELaqWUUkoppdqgBbVSSimllFJt0IJaKaWUUkqpNmhBrZRSSimlVBu0oFZKKaWUUqoN/z/eNmq2IrJaEQAAAABJRU5ErkJggg==\n", 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" ] @@ -285,12 +284,12 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -318,7 +317,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -340,7 +339,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -377,7 +376,7 @@ "\n", " x = Dense(param[0])(input_dots)\n", " x = BatchNormalization()(x)\n", - " x = Activation('elu')(x)\n", + " x = Activation('relu')(x)\n", "\n", " x = Dense(param[1])(x)\n", " x = BatchNormalization()(x)\n", @@ -604,14 +603,121 @@ "plt.legend();" ] }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "datetime\n", + "2020-03-09 12:14:36 0.0\n", + "2020-03-09 12:14:37 0.0\n", + "2020-03-09 12:14:38 0.0\n", + "2020-03-09 12:14:39 0.0\n", + "2020-03-09 12:14:41 0.0\n", + " ... \n", + "2020-03-09 12:34:31 0.0\n", + "2020-03-09 12:34:32 0.0\n", + "2020-03-09 12:34:33 0.0\n", + "2020-03-09 12:34:34 0.0\n", + "2020-03-09 12:34:35 0.0\n", + "Name: changepoint, Length: 1154, dtype: float64" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "true_cp = [df.changepoint for df in list_of_df]\n", + "true_cp[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'predicted_cp' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Input \u001b[0;32mIn [3]\u001b[0m, in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mpredicted_cp\u001b[49m[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mplot(figsize\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m12\u001b[39m, \u001b[38;5;241m3\u001b[39m), label\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpredictions\u001b[39m\u001b[38;5;124m'\u001b[39m, marker\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mo\u001b[39m\u001b[38;5;124m'\u001b[39m, markersize\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m5\u001b[39m)\n\u001b[1;32m 2\u001b[0m true_cp[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mplot(marker\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mo\u001b[39m\u001b[38;5;124m'\u001b[39m, markersize\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[1;32m 3\u001b[0m plt\u001b[38;5;241m.\u001b[39mlegend()\n", + "\u001b[0;31mNameError\u001b[0m: name 'predicted_cp' is not defined" + ] + } + ], + "source": [ + "predicted_cp[0].plot(figsize=(12, 3), label='predictions', marker='o', markersize=5)\n", + "true_cp[0].plot(marker='o', markersize=2)\n", + "plt.legend();" + ] + }, { "cell_type": "code", "execution_count": 19, "metadata": {}, + "outputs": [], + "source": [ + "predicted_cp = true_cp[0].copy()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "predicted_cp['2020-03-09 12:24:31'] = 1\n", + "predicted_cp['2020-03-09 12:25:52'] = 1\n", + "predicted_cp['2020-03-09 12:30:29'] = 1\n", + "predicted_cp['2020-03-09 12:31:42'] = 1\n", + "\n", + "predicted_cp['2020-03-09 12:24:36'] = 0\n", + "predicted_cp['2020-03-09 12:25:36'] = 0\n", + "predicted_cp['2020-03-09 12:30:36'] = 0\n", + "predicted_cp['2020-03-09 12:31:36'] = 0" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "datetime\n", + "2020-03-09 12:24:36 1.0\n", + "2020-03-09 12:25:36 1.0\n", + "2020-03-09 12:30:36 1.0\n", + "2020-03-09 12:31:37 1.0\n", + "Name: changepoint, dtype: float64" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "predicted_cp[predicted_cp==1]" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -624,20 +730,31 @@ ], "source": [ "# true changepoint indices selection\n", - "true_cp = [df.changepoint for df in list_of_df]\n", + "# true_cp = [df.changepoint for df in list_of_df]\n", "\n", - "predicted_cp[0].plot(figsize=(12, 3), label='predictions', marker='o', markersize=5)\n", + "predicted_cp.plot(figsize=(12, 3), label='predictions', marker='o', markersize=5)\n", "true_cp[0].plot(marker='o', markersize=2)\n", "plt.legend();" ] }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [] + }, "source": [ "## Metrics calculation" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from tsad.evaluating.evaluating import evaluating" + ] + }, { "cell_type": "code", "execution_count": 20, @@ -655,7 +772,7 @@ ], "source": [ "# binary classification metrics calculation\n", - "binary = evaluating_change_point(true_outlier, predicted_outlier, metric='binary', numenta_time='30 sec')" + "binary = evaluating(true_outlier, predicted_outlier, metric='binary', numenta_time='30 sec')" ] }, { @@ -674,7 +791,7 @@ ], "source": [ "# average detection delay metric calculation\n", - "add = evaluating_change_point(true_cp, predicted_cp, metric='average_delay', numenta_time='30 sec')" + "add = evaluating(true_cp, predicted_cp, metric='average_time', numenta_time='30 sec')" ] }, { @@ -715,7 +832,7 @@ ], "source": [ "# nab metric calculation\n", - "nab = evaluating_change_point(true_cp, predicted_cp, metric='nab', numenta_time='30 sec')" + "nab = evaluating(true_cp, predicted_cp, metric='nab', numenta_time='30 sec')" ] }, { @@ -735,7 +852,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -749,7 +866,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.2" + "version": "3.9.12" } }, "nbformat": 4, diff --git a/notebooks/example.ipynb b/notebooks/example.ipynb new file mode 100644 index 0000000..8dad590 --- /dev/null +++ b/notebooks/example.ipynb @@ -0,0 +1,1226 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "id": "0b27c589-1cbf-40f8-b8b4-3237a3d947cf", + "metadata": {}, + "outputs": [], + "source": [ + "# libraries importing\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline\n", + "\n", + "# additional modules\n", + "import sys\n", + "sys.path.append('../utils')" + ] + }, + { + "cell_type": "markdown", + "id": "778a954d-4793-4bb6-be28-2a1e7bf139ed", + "metadata": {}, + "source": [ + "## Data loading" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "id": "8d4a678e-ffae-49ae-bb4c-6635286375dc", + "metadata": {}, + "outputs": [], + "source": [ + "# benchmark files checking\n", + "all_files=[]\n", + "import os\n", + "for root, dirs, files in os.walk(\"../data/\"):\n", + " for file in files:\n", + " if file.endswith(\".csv\"):\n", + " all_files.append(os.path.join(root, file))" + ] + }, + { + "cell_type": "code", + "execution_count": 146, + "id": "1b8d1aa5-4df7-40a0-9b89-13390adf6562", + "metadata": {}, + "outputs": [], + "source": [ + "# datasets with anomalies loading\n", + "list_of_df = [pd.read_csv(file, \n", + " sep=';', \n", + " index_col='datetime', \n", + " parse_dates=True) for file in all_files if 'anomaly-free' not in file]\n", + "# anomaly-free df loading\n", + "anomaly_free_df = pd.read_csv([file for file in all_files if 'anomaly-free' in file][0], \n", + " sep=';', \n", + " index_col='datetime', \n", + " parse_dates=True)" + ] + }, + { + "cell_type": "markdown", + "id": "07407c1f-a0c9-49c2-9cb2-299fa50e58b6", + "metadata": {}, + "source": [ + "## Data description and visualization" + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "id": "07ab4520-cfc9-4a58-9671-349e7f82b459", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "A number of datasets in the SKAB v0.9: 34\n", + "\n", + "Shape of the random dataset: (1154, 10)\n", + "\n", + "A number of changepoints in the SKAB v0.9: 129\n", + "\n", + "A number of outliers in the SKAB v0.9: 13067\n", + "\n", + "Head of the random dataset:\n" + ] + }, + { + "data": { + "text/html": [ + "
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Accelerometer1RMSAccelerometer2RMSCurrentPressureTemperatureThermocoupleVoltageVolume Flow RateRMSanomalychangepoint
datetime
2020-03-09 12:14:360.0274290.0403530.7703100.38263871.212925.0827219.78932.00000.00.0
2020-03-09 12:14:370.0272690.0402261.0969600.71056571.428425.0863233.11732.01040.00.0
2020-03-09 12:14:380.0270400.0397731.1401500.05471171.346825.0874234.74532.00000.00.0
2020-03-09 12:14:390.0275630.0403131.108680-0.27321671.325825.0897205.25432.01040.00.0
2020-03-09 12:14:410.0265700.0395660.7044040.38263871.272525.0831212.09533.00000.00.0
2020-03-09 12:14:420.0277670.0392320.7057070.05471171.422825.0741209.00732.98990.00.0
2020-03-09 12:14:430.0272970.0409350.7354730.38263871.252725.0764230.67832.00000.00.0
2020-03-09 12:14:440.0269470.0397321.2323700.38263871.355625.0776239.91732.00000.00.0
2020-03-09 12:14:450.0267320.0391071.1293500.05471171.407025.0800234.28732.00000.00.0
2020-03-09 12:14:460.0275310.0403031.1115900.05471171.279025.0958214.57532.01040.00.0
2020-03-09 12:14:470.0275180.0402720.8995630.05471171.371225.0861228.29832.98990.00.0
2020-03-09 12:14:480.0268710.0386361.0554300.05471171.289225.0887215.83532.00000.00.0
2020-03-09 12:14:490.0275530.0406321.2596000.05471171.277825.0871229.66432.00000.00.0
2020-03-09 12:14:500.0273450.0403001.2553400.05471171.305425.0876241.42132.00000.00.0
2020-03-09 12:14:510.0272570.0405850.7891090.05471171.359525.0887216.45032.01040.00.0
\n", + "
" + ], + "text/plain": [ + " Accelerometer1RMS Accelerometer2RMS Current Pressure \\\n", + "datetime \n", + "2020-03-09 12:14:36 0.027429 0.040353 0.770310 0.382638 \n", + "2020-03-09 12:14:37 0.027269 0.040226 1.096960 0.710565 \n", + "2020-03-09 12:14:38 0.027040 0.039773 1.140150 0.054711 \n", + "2020-03-09 12:14:39 0.027563 0.040313 1.108680 -0.273216 \n", + "2020-03-09 12:14:41 0.026570 0.039566 0.704404 0.382638 \n", + "2020-03-09 12:14:42 0.027767 0.039232 0.705707 0.054711 \n", + "2020-03-09 12:14:43 0.027297 0.040935 0.735473 0.382638 \n", + "2020-03-09 12:14:44 0.026947 0.039732 1.232370 0.382638 \n", + "2020-03-09 12:14:45 0.026732 0.039107 1.129350 0.054711 \n", + "2020-03-09 12:14:46 0.027531 0.040303 1.111590 0.054711 \n", + "2020-03-09 12:14:47 0.027518 0.040272 0.899563 0.054711 \n", + "2020-03-09 12:14:48 0.026871 0.038636 1.055430 0.054711 \n", + "2020-03-09 12:14:49 0.027553 0.040632 1.259600 0.054711 \n", + "2020-03-09 12:14:50 0.027345 0.040300 1.255340 0.054711 \n", + "2020-03-09 12:14:51 0.027257 0.040585 0.789109 0.054711 \n", + "\n", + " Temperature Thermocouple Voltage Volume Flow RateRMS \\\n", + "datetime \n", + "2020-03-09 12:14:36 71.2129 25.0827 219.789 32.0000 \n", + "2020-03-09 12:14:37 71.4284 25.0863 233.117 32.0104 \n", + "2020-03-09 12:14:38 71.3468 25.0874 234.745 32.0000 \n", + "2020-03-09 12:14:39 71.3258 25.0897 205.254 32.0104 \n", + "2020-03-09 12:14:41 71.2725 25.0831 212.095 33.0000 \n", + "2020-03-09 12:14:42 71.4228 25.0741 209.007 32.9899 \n", + "2020-03-09 12:14:43 71.2527 25.0764 230.678 32.0000 \n", + "2020-03-09 12:14:44 71.3556 25.0776 239.917 32.0000 \n", + "2020-03-09 12:14:45 71.4070 25.0800 234.287 32.0000 \n", + "2020-03-09 12:14:46 71.2790 25.0958 214.575 32.0104 \n", + "2020-03-09 12:14:47 71.3712 25.0861 228.298 32.9899 \n", + "2020-03-09 12:14:48 71.2892 25.0887 215.835 32.0000 \n", + "2020-03-09 12:14:49 71.2778 25.0871 229.664 32.0000 \n", + "2020-03-09 12:14:50 71.3054 25.0876 241.421 32.0000 \n", + "2020-03-09 12:14:51 71.3595 25.0887 216.450 32.0104 \n", + "\n", + " anomaly changepoint \n", + "datetime \n", + "2020-03-09 12:14:36 0.0 0.0 \n", + "2020-03-09 12:14:37 0.0 0.0 \n", + "2020-03-09 12:14:38 0.0 0.0 \n", + "2020-03-09 12:14:39 0.0 0.0 \n", + "2020-03-09 12:14:41 0.0 0.0 \n", + "2020-03-09 12:14:42 0.0 0.0 \n", + "2020-03-09 12:14:43 0.0 0.0 \n", + "2020-03-09 12:14:44 0.0 0.0 \n", + "2020-03-09 12:14:45 0.0 0.0 \n", + "2020-03-09 12:14:46 0.0 0.0 \n", + "2020-03-09 12:14:47 0.0 0.0 \n", + "2020-03-09 12:14:48 0.0 0.0 \n", + "2020-03-09 12:14:49 0.0 0.0 \n", + "2020-03-09 12:14:50 0.0 0.0 \n", + "2020-03-09 12:14:51 0.0 0.0 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# dataset characteristics printing\n", + "print(f'A number of datasets in the SKAB v0.9: {len(list_of_df)}\\n')\n", + "print(f'Shape of the random dataset: {list_of_df[0].shape}\\n')\n", + "n_cp = sum([len(df[df.changepoint==1.]) for df in list_of_df])\n", + "n_outlier = sum([len(df[df.anomaly==1.]) for df in list_of_df])\n", + "print(f'A number of changepoints in the SKAB v0.9: {n_cp}\\n')\n", + "print(f'A number of outliers in the SKAB v0.9: {n_outlier}\\n')\n", + "print(f'Head of the random dataset:')\n", + "display(list_of_df[0].head(15))" + ] + }, + { + "cell_type": "code", + "execution_count": 148, + "id": "0b54341f-28f4-4a68-b5a7-dc47124c52a7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# random dataset visualizing\n", + "list_of_df[0].plot(figsize=(12,6))\n", + "plt.xlabel('Time')\n", + "plt.ylabel('Value')\n", + "plt.title('Signals')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 150, + "id": "a7bf60ca-12ee-46f2-98a6-82c42cd1137f", + "metadata": {}, + "outputs": [], + "source": [ + "# Выберем для демонстрации рандомный датасет (1ый)\n", + "X_train_ = list_of_df[0][:400].drop(['anomaly', 'changepoint'], axis=1)\n", + "X_test_ = list_of_df[0].drop(['anomaly','changepoint'], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 151, + "id": "24f30532-626d-4e8a-af1f-c153e88f94b2", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "# обучение скейлера\n", + "StSc = StandardScaler()\n", + "StSc.fit(X_train)\n", + "X_train = StSc.transform(X_train_)\n", + "X_test = StSc.transform(X_test_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3ce52d4b-8f70-475e-a597-d337451de2b2", + "metadata": {}, + "outputs": [], + "source": [ + "# выбор и инициализация архитектуры автоэнкодера\n", + "input_dots = Input((8,))\n", + "x = Dense(5)(input_dots)\n", + "x = Activation('relu')(x)\n", + "bottleneck = Dense(2, activation='linear')(x)\n", + "x = Dense(5)(bottleneck)\n", + "x = Activation('relu')(x)\n", + "out = Dense(8, activation='linear')(x)\n", + "\n", + "model = Model(input_dots, out)\n", + "model.compile(optimizer=Adam(0.005), loss='mae')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e6d110ff-620f-48b0-9011-ed72cca77f8d", + "metadata": {}, + "outputs": [], + "source": [ + "# обучение модели\n", + "model.fit(X_train_scaled, \n", + " X_train_scaled,\n", + " epochs=40,\n", + " batch_size=32,\n", + " shuffle=True\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6d8d560c-1f3d-4d8a-bd83-494448cf5da1", + "metadata": {}, + "outputs": [], + "source": [ + "# определение UCL (верхнего контрольного предела)\n", + "residuals = pd.DataFrame(X_train_scaled - \n", + " model.predict(X_train_scaled))\n", + "UCL = residuals.abs().sum(axis=1).quantile(0.99) # quantile for UCL" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e8abf6a5-83ac-4138-b556-f1438fa5d1af", + "metadata": {}, + "outputs": [], + "source": [ + "# реализация алгоритма поиска точек изменения состояния\n", + "residuals = pd.DataFrame(X_test_scaled - \n", + " model.predict(X_test_scaled))\n", + "criterion = residuals.abs().sum(axis=1)\n", + "\n", + "prediction = pd.Series((criterion > UCL).astype(int).values, \n", + " index=df.index\n", + " ).fillna(0)\n", + "prediction_cp = abs(prediction.diff())" + ] + }, + { + "cell_type": "markdown", + "id": "342a99a4-a8f9-432a-9398-19c904cff078", + "metadata": {}, + "source": [ + "# Ruptures" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "778d6896-3bb2-44c2-a729-55e232a21373", + "metadata": {}, + "outputs": [], + "source": [ + "import ruptures as rpt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "751f5653-b91b-4aa8-bc01-a0b705f34978", + "metadata": {}, + "outputs": [], + "source": [ + "# выбор функции потерь\n", + "c = rpt.cost.CostL2()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "67a8a381-ed69-4a5a-adbc-fe9ded4cb520", + "metadata": {}, + "outputs": [], + "source": [ + "# выбор алгоритма поиска\n", + "algo = rpt.Binseg(custom_cost=с, jump=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "db47d188-d081-47a7-b130-b3081071bc04", + "metadata": {}, + "outputs": [], + "source": [ + "# обучение алгоритма\n", + "algo.fit(signal)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7a6af01c-166d-4c4f-a7e7-3851fc90c0d8", + "metadata": {}, + "outputs": [], + "source": [ + "# детектирование точек изменения состояния\n", + "# ограничение - информация о кол-ве точек\n", + "my_bkps = algo.predict(n_bkps=4)" + ] + }, + { + "cell_type": "markdown", + "id": "552312bf-e572-448b-acdd-0cb2d5a80f05", + "metadata": { + "tags": [] + }, + "source": [ + "# Grad boosting" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "75454e18-7ce6-47eb-9160-ed67ca1c26a6", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 153, + "id": "56f55e2f-91b3-40a5-bfc3-9686e7342e87", + "metadata": {}, + "outputs": [], + "source": [ + "X_train_tr = pd.concat([pd.DataFrame(X_train_splitted[i], \n", + " columns=X_train_.columns).assign(**{'id':i}) for i in range(len(X_train_splitted))])" + ] + }, + { + "cell_type": "code", + "execution_count": 152, + "id": "34582e01-584f-48d6-8d93-fdb37d641df6", + "metadata": {}, + "outputs": [], + "source": [ + "# Нарезка временных рядов окном\n", + "def split_sequences(sequences, n_steps):\n", + " X, y = list(), list()\n", + " for i in range(len(sequences)):\n", + " # find the end of this pattern\n", + " end_ix = i + n_steps\n", + " # check if we are beyond the dataset\n", + " if end_ix > len(sequences)-1:\n", + " break\n", + " # gather input and output parts of the pattern\n", + " seq_x, seq_y = sequences[i:end_ix, :], sequences[end_ix, :]\n", + " X.append(seq_x)\n", + " y.append(seq_y)\n", + " return np.array(X), np.array(y)\n", + "X_train_splitted, y = split_sequences(X_train, 10)" + ] + }, + { + "cell_type": "code", + "execution_count": 154, + "id": "82e72175-125c-4ffc-8aff-7cc3a49322af", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Feature Extraction: 100%|██████████| 25/25 [00:02<00:00, 9.46it/s]\n" + ] + } + ], + "source": [ + "# преобразование окон в таблицу\n", + "from tsfresh import extract_features\n", + "from tsfresh.feature_extraction import MinimalFCParameters\n", + "\n", + "extraction_settings = MinimalFCParameters()\n", + "\n", + "del extraction_settings[\"length\"]\n", + "del extraction_settings[\"sum_values\"]\n", + "del extraction_settings[\"absolute_maximum\"]\n", + "del extraction_settings[\"root_mean_square\"]\n", + "del extraction_settings[\"variance\"]\n", + "\n", + "X = extract_features(X_train_tr, \n", + " column_id='id',\n", + " default_fc_parameters=extraction_settings)" + ] + }, + { + "cell_type": "code", + "execution_count": 155, + "id": "49a05296-fb12-49bb-bc66-cc2d6839ca03", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Accelerometer1RMS__median Accelerometer1RMS__mean \\\n", + "0 -0.210296 -0.377697 \n", + "1 -0.210296 -0.355944 \n", + "2 -0.489378 -0.452759 \n", + "3 0.092266 -0.327963 \n", + "4 -0.118810 -0.381176 \n", + "\n", + " Accelerometer1RMS__standard_deviation Accelerometer1RMS__maximum \\\n", + "0 0.888386 0.966984 \n", + "1 0.903414 0.966984 \n", + "2 0.937489 0.966984 \n", + "3 0.965290 0.966984 \n", + "4 0.933945 0.966984 \n", + "\n", + " Accelerometer1RMS__minimum Accelerometer2RMS__median \\\n", + "0 -1.94647 -0.468233 \n", + "1 -1.94647 -0.468233 \n", + "2 -1.94647 -0.645907 \n", + "3 -1.94647 -0.466687 \n", + "4 -1.94647 -0.466687 \n", + "\n", + " Accelerometer2RMS__mean Accelerometer2RMS__standard_deviation \\\n", + "0 -0.501086 0.388325 \n", + "1 -0.506896 0.384407 \n", + "2 -0.621244 0.468403 \n", + "3 -0.559472 0.502543 \n", + "4 -0.560385 0.501975 \n", + "\n", + " Accelerometer2RMS__maximum Accelerometer2RMS__minimum ... \\\n", + "0 0.204388 -1.110368 ... \n", + "1 0.204388 -1.110368 ... \n", + "2 0.204388 -1.449033 ... \n", + "3 0.204388 -1.449033 ... \n", + "4 0.204388 -1.449033 ... \n", + "\n", + " Voltage__median Voltage__mean Voltage__standard_deviation \\\n", + "0 -0.441528 -0.618710 1.119851 \n", + "1 -0.042069 -0.538818 1.121669 \n", + "2 -0.738881 -0.701081 1.106038 \n", + "3 -0.738881 -0.748787 1.064815 \n", + "4 -0.089672 -0.409211 1.051805 \n", + "\n", + " Voltage__maximum Voltage__minimum Volume Flow RateRMS__median \\\n", + "0 0.937120 -2.317423 -0.602973 \n", + "1 0.937120 -2.317423 -0.591664 \n", + "2 0.937120 -2.317423 -0.602973 \n", + "3 0.937120 -2.317423 -0.602973 \n", + "4 1.078332 -1.965051 -0.614281 \n", + "\n", + " Volume Flow RateRMS__mean Volume Flow RateRMS__standard_deviation \\\n", + "0 -0.174753 0.862164 \n", + "1 0.040521 0.985481 \n", + "2 0.038259 0.986954 \n", + "3 0.038259 0.986954 \n", + "4 0.035997 0.988420 \n", + "\n", + " Volume Flow RateRMS__maximum Volume Flow RateRMS__minimum \n", + "0 1.560417 -0.614281 \n", + "1 1.560417 -0.614281 \n", + "2 1.560417 -0.614281 \n", + "3 1.560417 -0.614281 \n", + "4 1.560417 -0.614281 \n", + "\n", + "[5 rows x 40 columns]" + ] + }, + "execution_count": 155, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "X.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 156, + "id": "da9cec4f-c72e-4986-8ed0-3e76d19c48a7", + "metadata": {}, + "outputs": [], + "source": [ + "# !pip install xgboost" + ] + }, + { + "cell_type": "code", + "execution_count": 157, + "id": "554973c1-7bbd-4d93-8775-b9bc0899bd11", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "XGBRegressor(base_score=0.5, booster='gbtree', callbacks=None,\n", + " colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n", + " early_stopping_rounds=None, enable_categorical=False,\n", + " eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',\n", + " importance_type=None, interaction_constraints='',\n", + " learning_rate=0.300000012, max_bin=256, max_cat_to_onehot=4,\n", + " max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1,\n", + " missing=nan, monotone_constraints='()', n_estimators=100, n_jobs=0,\n", + " num_parallel_tree=1, predictor='auto', random_state=0, reg_alpha=0,\n", + " reg_lambda=1, ...)" + ] + }, + "execution_count": 157, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# обучение градбустинга\n", + "from xgboost import XGBRegressor\n", + "\n", + "xgb = XGBRegressor(verbosity=0)\n", + "xgb.fit(X, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 158, + "id": "f0ba3eb1-e04d-4a08-8175-1280632a71a0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.9999772174427064" + ] + }, + "execution_count": 158, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "xgb.score(X, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 159, + "id": "9c33c01c-44d4-4209-aa21-9650f773f6d6", + "metadata": {}, + "outputs": [], + "source": [ + "# определение UCL (верхнего контрольного предела)\n", + "residuals = pd.DataFrame(y - xgb.predict(X))\n", + "UCL = residuals.abs().sum(axis=1).quantile(0.99) # quantile for UCL" + ] + }, + { + "cell_type": "code", + "execution_count": 160, + "id": "fa6b2619-6500-4f38-8f03-afeb1deb1bea", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "residuals.abs().sum(axis=1).plot(label='residuals', figsize=(16,6))\n", + "plt.axhline(UCL, color='r', label='UCL')\n", + "plt.legend();" + ] + }, + { + "cell_type": "markdown", + "id": "971494f4-66bc-4dd1-8093-fcee0011fd86", + "metadata": {}, + "source": [ + "## Results" + ] + }, + { + "cell_type": "code", + "execution_count": 164, + "id": "4cf3f2a4-63d1-483e-999f-3d046f9a377a", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Feature Extraction: 100%|██████████| 25/25 [00:02<00:00, 10.24it/s]\n" + ] + } + ], + "source": [ + "X_test_splitted, y_test = split_sequences(X_test, 10)\n", + "\n", + "X_test_tr = pd.concat([pd.DataFrame(X_test_splitted[i], \n", + " columns=X_test_.columns).assign(**{'id':i}) \n", + " for i in range(len(X_test_splitted))])\n", + "\n", + "X_test_final = extract_features(X_test_tr, \n", + " column_id='id',\n", + " default_fc_parameters=extraction_settings)\n", + "\n", + "results = xgb.predict(X_test_final)" + ] + }, + { + "cell_type": "code", + "execution_count": 169, + "id": "7b670467-de38-411c-9bb5-482b137e7f8b", + "metadata": {}, + "outputs": [], + "source": [ + "residuals = pd.DataFrame(y_test).drop(6, axis=1) - pd.DataFrame(results).drop(6, axis=1)\n", + "# residuals = y_test - results\n", + "residuals = pd.DataFrame(residuals).abs().sum(axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 171, + "id": "96859425-26d7-4c2e-b095-8794ac304027", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 171, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "residuals.plot(label='residuals', figsize=(16,6))\n", + "plt.axhline(UCL, color='r', label='UCL')\n", + "plt.legend();" + ] + }, + { + "cell_type": "code", + "execution_count": 135, + "id": "438b3ce9-7416-48d4-8d0f-457032e8ac76", + "metadata": {}, + "outputs": [], + "source": [ + "# predicted outliers saving\n", + "predicted_outlier = pd.Series((residuals > UCL).astype(int).values).fillna(0)\n", + "\n", + "# predicted CPs saving\n", + "prediction_cp = abs(predicted_outlier.diff())\n", + "prediction_cp[0] = predicted_outlier[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 137, + "id": "d20fd6ab-4d4d-4ceb-8bf9-eecd35120568", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "prediction_cp.plot(figsize=(12, 3), label='predictions', marker='o', markersize=5)\n", + "list_of_df[0].changepoint.plot(marker='o', markersize=2)\n", + "plt.legend();" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a215e4cb-ee6f-4f24-8568-a484208da5eb", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/hotelling.ipynb b/notebooks/hotelling.ipynb deleted file mode 100644 index db90bef..0000000 --- a/notebooks/hotelling.ipynb +++ /dev/null @@ -1,561 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Pipeline for the anomaly detection on the SKAB using Hotelling's statistics" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "# libraries importing\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline\n", - "\n", - "# additional modules\n", - "import sys\n", - "sys.path.append('../utils')\n", - "from t2 import T2\n", - "from evaluating import evaluating_change_point" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data loading" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# benchmark files checking\n", - "all_files=[]\n", - "import os\n", - "for root, dirs, files in os.walk(\"../data/\"):\n", - " for file in files:\n", - " if file.endswith(\".csv\"):\n", - " all_files.append(os.path.join(root, file))" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# datasets with anomalies loading\n", - "list_of_df = [pd.read_csv(file, \n", - " sep=';', \n", - " index_col='datetime', \n", - " parse_dates=True) for file in all_files if 'anomaly-free' not in file]\n", - "# anomaly-free df loading\n", - "anomaly_free_df = pd.read_csv([file for file in all_files if 'anomaly-free' in file][0], \n", - " sep=';', \n", - " index_col='datetime', \n", - " parse_dates=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data description and visualization" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A number of datasets in the SkAB v1.0: 34\n", - "\n", - "Shape of the random dataset: (1146, 10)\n", - "\n", - "A number of changepoints in the SkAB v1.0: 130\n", - "\n", - "A number of outliers in the SkAB v1.0: 13241\n", - "\n", - "Head of the random dataset:\n" - ] - }, - { - "data": { - "text/html": [ - "
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Accelerometer1RMSAccelerometer2RMSCurrentPressureTemperatureThermocoupleVoltageVolume Flow RateRMSanomalychangepoint
datetime
2020-03-09 12:14:360.0274290.0403530.7703100.38263871.212925.0827219.78932.00000.00.0
2020-03-09 12:14:370.0272690.0402261.0969600.71056571.428425.0863233.11732.01040.00.0
2020-03-09 12:14:380.0270400.0397731.1401500.05471171.346825.0874234.74532.00000.00.0
2020-03-09 12:14:390.0275630.0403131.108680-0.27321671.325825.0897205.25432.01040.00.0
2020-03-09 12:14:410.0265700.0395660.7044040.38263871.272525.0831212.09533.00000.00.0
\n", - "
" - ], - "text/plain": [ - " Accelerometer1RMS Accelerometer2RMS Current Pressure \\\n", - "datetime \n", - "2020-03-09 12:14:36 0.027429 0.040353 0.770310 0.382638 \n", - "2020-03-09 12:14:37 0.027269 0.040226 1.096960 0.710565 \n", - "2020-03-09 12:14:38 0.027040 0.039773 1.140150 0.054711 \n", - "2020-03-09 12:14:39 0.027563 0.040313 1.108680 -0.273216 \n", - "2020-03-09 12:14:41 0.026570 0.039566 0.704404 0.382638 \n", - "\n", - " Temperature Thermocouple Voltage Volume Flow RateRMS \\\n", - "datetime \n", - "2020-03-09 12:14:36 71.2129 25.0827 219.789 32.0000 \n", - "2020-03-09 12:14:37 71.4284 25.0863 233.117 32.0104 \n", - "2020-03-09 12:14:38 71.3468 25.0874 234.745 32.0000 \n", - "2020-03-09 12:14:39 71.3258 25.0897 205.254 32.0104 \n", - "2020-03-09 12:14:41 71.2725 25.0831 212.095 33.0000 \n", - "\n", - " anomaly changepoint \n", - "datetime \n", - "2020-03-09 12:14:36 0.0 0.0 \n", - "2020-03-09 12:14:37 0.0 0.0 \n", - "2020-03-09 12:14:38 0.0 0.0 \n", - "2020-03-09 12:14:39 0.0 0.0 \n", - "2020-03-09 12:14:41 0.0 0.0 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# dataset characteristics printing\n", - "print(f'A number of datasets in the SkAB v1.0: {len(list_of_df)}\\n')\n", - "print(f'Shape of the random dataset: {list_of_df[10].shape}\\n')\n", - "n_cp = sum([len(df[df.changepoint==1.]) for df in list_of_df])\n", - "n_outlier = sum([len(df[df.anomaly==1.]) for df in list_of_df])\n", - "print(f'A number of changepoints in the SkAB v1.0: {n_cp}\\n')\n", - "print(f'A number of outliers in the SkAB v1.0: {n_outlier}\\n')\n", - "print(f'Head of the random dataset:')\n", - "display(list_of_df[0].head())" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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VwFcNaHr/IKpXfG55nnOOli3HYrQbyaIX4i3pwNJlXNTvJsGYW/mHjaj5h3EHMQ/LBs2pFaGj1hrRhMUKyYZr617c2658OoSqUYqjWZIag6h9/gvwkIxwrTLIym0h5VwnaHnUgTkZIbynUfOPXWh44yvtd/hYqyNttBXBw8qAkmjCET5uLRDpCR1TNIvNH1e2qywAIAfCaNmSnHBnm1dQQuV9G+HfV68d66qVJTOBL+tR/+o+NLz1VeLEgNavtFcrCwBH79uEo/d1bLUwmfqxE5JVgl8rbSvwlfUKSLi6Dcf/XI56mzrqCd+w3Kp8NyelrA7bitQUhFTn175xVfjjAQlySygm/apVq3DZZZcZjn3rW99CZWUlTjvtNJSUlKC0tBTPPvssPB4PVq9ejZtvvhmlpaU4//zz4ff7ce2112LUqFEYO3YsioqK8IMf/CDGY4eTNABwww03QJZlFBcX44orrsCKFSvimkFIjQHIuvexcuVKLF++HKWlpRg9ejRee+01AIopy3333YcxY8Zg3759tunMHD16FIMHD8YDDzyAu+++G4MHD0ZjXWwbHzNmDEpKSmK8pIwaUYirFlwZk37NmjUoKipCaWkp5syZg/vuuw/9+59YpdgJsaFmjBUAGAPgEwBTAdzEGPsugE1QtNh1UITtj3WXHUJ8Abx3EvnG1WU7M4F9Dah7fg+CB5qQM//M5LO36fClhgCYW9C04kzsWgcwPIEWS6r1o63WGKWodvUXgMiQ9+2RnV6exncPoGntQdvzPCSj5bNjSJvQv+uCBkQ6eLXDlpqCYF7RYF9f/9ZXaNtaBakhgOAhRbvCRAH+PXWofnoH8q4qhG90+21/VYFaDko4Zaz647xOzrn2vrnEAQYwIXqBpllJ9L04aTKRvJL99qTGAFrLq5A+bRDqXvkSbeVVcPdNjat1c0L4eCukGj8a/rnfWEaXzcN0orAt+xWFgWQhsMRFkoGT2XItbi+1hCB4RDB3cu9V66tt+hupVamboI05Dg+fHPOXrkZqDrZ7j4QBp9Vj6pcNWVgcU71o6Lnlllu0vx944AHDuQkTJuDjjz82X4J77rkH99xzj+FYVlaWZsYgCIJlmunTp2P69Ona75SUFPz1r3+NyX/x4sVYvHix9ruiogKAsurxnQsXYMn3lwBQ3NW98847MddPnTo1xm2eVboVK1YYfvfv3x+HDh0yHJOag5DqA6g/UGU4/sYbb2h/W5lv6J/hgQceiKnbE02Xu81jjKUDeAnArZzzRgCPATgDQBmASgB/TDK/pYyxTYyxTVVVVYkvOMlIjQG0bDzqOL0maNoMTjwYGWjaa+NmY05Q+ftPUfmHqHamI5trnNAeW8dwnT+hVqe9yK3xB+7Gd79G/ctfom1HYlv1cE0bgocS25ya0bRrkTZQ+btPcPzRckgtITS+f9AwGQrsa1A21EARgoORpcvggeTvq5W7uk1rV6rG6ERpJLstunZ6+OfrUP/Kl8bzsioEM/CwjLaIyYyZRHMwLnPUv7FPyysZqv++Cw3/3I9wjT/6/oIdt5TT2iOzOBb3wg7fWuv/9JMXR5d1QEPdKVjcv/K3H6Nq+fbk81KrP9EobdO4Eq3mdQQellH7/Bcn3PbZv68elXd/ktSeIVucNhW1DZ4CXaGT/l4OSQgdb+3Ub02TBxJ87919POpSgZox5oYiTK/knL8MAJzzY5xziXMuA3gKUbOOwwCG6C4fHDlmgHP+JOd8POd8fH6+vd1od6Fm1Reoe2kvwrUOY8Krs2G7xqq2N54gnQ3xOlnDsnUXaai176E9nX2Yg7d1jaN6V158DxhSsyJwO7n/0fs24fify5MvhIUmJHysFXUv7kHjvyoQ/LrRWtOZxA71eLR8dlz7WxPIuniT10kXgBKglk/tyM2TY335G96pQM2KzxH42sKrQIKBIvh1I8JVkclikt+euuxsvEMnTIg1gU6Xl4PvtlPeqYUwn9R1Jwm7Zw9W2HuaqH97P5r+GzPU6TpLuxWBuGe7VKBu21mD1i3HUf/6vnbn0Z52EjqimOUZbMXbe3+Hwpk6X9HKq7tMbgpC7oTJa09CbgyCByXI/jCk1lCHnABodHNB2Sld6eWDAVgOYBfn/AHd8QG6ZJcBUPX4rwP4NmPMyxgbBuAsAJ92VflOFJpGOYFXDS29ukxn18DU5WfV3FYn4DnpoJzaqnWdhtp++SzhlVLHPHjEzTtBtWjL/kl8+DWrduPwXeuTKETkH1Pd6O30rN4KYzYnkkU3APNgREPdCQJK3Hd9krwyOEZ9fjvhRC2/zDVvHtwfjvX8kej96M4n/e1JFpJVZ7QHi7buqD10RpvRZMmer6FORPMHhww2/RoJ5OlEmz9VgZrLvPOFvs5oX+2oK9VspqOTBTkoWd6fh2WE6/3Gfl6TqK3LK7eFIbeFkzdP6mZwSTbIE7aoE2yZQ6rtpFVjbvo3UbpuSldqqKcCuArATJOLvD8wxrYzxrYBmAFgGQBwzj8H8DyAnQDeAXBjb/DwIaQpNsmyw01PUZMP6/OatkjVUOs3JzoQThxv/khyqdUxNkKjo0slDtkvdc2yT6LOXVsZcJ5l29YqcH87mrBpoFTrirkESwFDX5fxipeo3gz5qANwJ2i54m2gTWRLn4jgkWaE6+Ov/vj31cNv4cHCSTvSNiDZfDdcv6KkPovIUPX4NlPKBN+T/r0mKVBzi5WNjsA5R+P7ByBHVmUMZYt3j07YGKgRySPwVUNywtNJnqCZn13fxqTmIJrWHXbef2k21DanE/TlPCyDhyTU/H0njvxqvaO+37nWNqJgcJTaSOu2Khy5+2PIgeT7Rk2g7sAmRs45wsdbLQXBcK0fcnNIUygoN1UvhPmP6HU1bZDqHK5Cd1PC1W2QnKyk6wTqTidB+wsdae78e3YiXenlYx3nnHHOSzjnZZH//sk5v4pzXhw5PpdzXqm75nec8zM45yM45293VdlOJGJEoA7XB9C84Yj1crAedUCwa1fmj1u38YTLDjpMp4OT6WOp+fvOuDPwls+OQw5ICNcHEj8j0D7XWmEZkLjjgaFx7UEc/0u5o6wTCgEmU5uuxCwYae/M5taOBRhdtUktIQRNnZO+bai7vDtFQx1HO9ZRIfD4w5/h6L3xfWxXP7Ud1U/viLVvTvSt6dLYfjc6zyzas1hpVbV5MLc0/9Lnz0QBclDCoTs/QosTd2x6gdqppicOwa8b0fivr1H7wh5D2bV7OCyPdo3Mk99TEPnO5KYgGt7e7/yyk6ChNtzTfH9dfdU+vwcNb36F0CFnQkEiLX2ivpyHZNSs3A3/LqXdywEH2sd2+GROlvrXvoTcHLL0kGH3faioqzcd9XJlzNThBPZkr350MU5lA1Wp16nfmm7FXd0PFJOkB5iFdPmmxFMd5lGqWGoIoP61fah6bKt2zqpBOtbYaYOoXkrquIZabgsrYYZNebV9XoMWG3dewcPNqFv9Bepe2Ytjf9xkeMbYAkT+aafJBwBnWl+Zo/GdCueb9BJ9rNqyn30SqSWEo/c5C6Cix/9lHar0QU7MbUC3dGuprXLcZqIbDY8/vAXHH/7MlI+FhjqJ98RljradNTEdnxyMU75O8FnslBqTK0qtPcUZGNRJqq2GWi+Ux3F7qGr0alftxtE/bIyZdOrzZyLTVrQa3ztgW7ZoGSP309Wlk8m1bX7qZErVIOoEDif9k/nbbnz3AI7/uTwpoVrvoSJ4JAlXmJ0xAYzkEa5uw6E7P0LbF8aJmByQjD7L/fZmd4ZVn0h9JtoAHb0gsjKln9Dovi2tzdjJg2FZ8ysPOBOYHCtcOqJgUD8Zi3s1f3gIR/+w0TYglLZi5MCDCQ/bmAjGXcaL/Mtij/UAea6DJJ5YSC2h6NjQqV23rnI5txaee8CEhgTqLkbt9Cz93CZww2PVqMybpAzpnQjUCTrMI7/ZoASKsRg4hZRYd1SBrxq0QTZc1eZAe2yt8fN/Wa84+Y+jRVE7USd21E4F9kN3fqRowBJ8rE5m5f6dNQjXJLfsJzUHUfPMTkNQDS5xw314Ai2p02dt2XwM1X/7HId/us7SD7leWKp/5Uu0bq1KauLT8kklap7ZiVbd5kYggYa6k1x7SU3J+5GWW8I49tBmBG0iHSoZO9NQc5nHN72IjFWqT+EYLZw+f5Elt6wqta8vsMN8rcHLRDs01KpbN3Vjr6My6OsjCZOPzjB7UfuwQKTc5vZ8/OEtqLwnGo1T9scxu5OMEyUAzu2ZrTTU+necSENtOs/jTWzVNAn6b6k5iHBDIGnbdsM9ZPtvyr8v8n2YvFiFI+YU2iQ4JEEOSpAaA6j+6w5LrXboaIu1fa9DyZiHZSXYj5re7jqbw6+++ioYY9i9e7ej+zmhoqICRUVFnZZfskh1fs3O+tU3X8OuPck/28qVK1FSUoLi4mJMmTIFW7du1erQNzQbE+ZMRXFxMS699FLU19cDUJ5bcIn49R/+R8unuroabrcbN910EwDgiy++wPTp01FWVobCwkIsXbq0Yw/bDkig7mLUTsPKvZClFknfIVsNDtomqNg0nbUpUaoPWA5MLMXotjxc04aqJ7dpruT0glPC5RmzFutfFZBbwwgds3fHo3amdhsn4i69WqWPlLHpg0OOTT7i1V97NspUL98RM9BxiRvKr+VrJyw4nLnXv7pPW/61wvzOmz+uTMrGOVyntHHZJNzGFahlDjmgmDc0rVM8HXDOUffqlwh8Ve/43noBR0+8QD/Bw80IHW1Fw9sVccsHGN+7ZTuTefT9WLWDiACi+fk2CZcx7UqVV8zC6eFmNLxTYdRUqlr0sBwd9DsyUTG3M4OG2sF3ZW6PqmvBJPZlGOo7me+qMzTUEXMC7bFNWZonzYYJfhwNteqNhweSXIXU9wX6vx3YUBt+OxDk9XkGDjTi0J0fGfxcV979CY7+XucroD3VrVqw6ctj0njrff23bqvC0f/diNZtVdHJY0jG0T9sROU9n8L/RR3qXtmrCd0JMZeZKRMFw0SHRwKctIW14DPgSvAl87drx6pVq3DOOedg1apVivDvdGWiE7EK9KLCJdlox57ItadpTH/9n29g197EArV+w2Y4HMawYcPwwQcfYPv27fjlL3+JpUuXaq/El+LDxn/9F9u3bkNubq4h9PiwgmF4+7012u8XXngBo0dHI2HecsstWLZsmRb2/Oabb05Yts6GBOouRtNQW33sus42dKwF4Vq/QYCx7DA11z3tNPlwODhZCa1m7wPqRyJFNoUZBEO7+2gmH6bOXt+RWpnCcK4JCXZR6QyDsI22LlDRgPo3Izvq9UJHgmrRBKt2aFvjTS5CVRYaFEk2DJxqB66YfMTflBhvgHPZhMbWML0zd74vOQFFc3VmLGNczZgka5NNzaSIK39XPZmE715TMf1769C6rQrHHtriPA/L8sVq0wwTR/W8XkNt2fYjBYwIleZlf8O3rptQmZvO8ce2KgGI9O9cM/nQt3ln37mVBi9GIDbYUDuYkJtW46LBb4zt4tjDW3D8cWvzML2NbDKTuvZqqK1NKWK9O1iuGlqYfPj31aP6mZ1G23hNoNalj9M3aM+ifx+652vdVm17rfIcJuE+JKNl8zEcuvOjmFW+tl01OHTnR4b24P9CWTWL5/NZbgtDarT3RS01BxHY34DKez5By6aIy0l17NL3CwJThDsLjzVqAKvaZ3drZQoeaDIItoG99Tj6vw7N7az0VPUBhI+36k5y7Vs1TmJi+39usara3NyMdevWYfny5XjuuecQPt6KYFULbrvtNhQVFaGkpASPPPIIAGDjxo2YMmUKSktLMXHiRDQ1NUGSJNx+++2YMGECSkpKDGHMtTLbpFm7di2mTZuGuXPnYtSoUfD7/bjmmmtQXFyMMWPGaIFnlj/yFObPnYfzzz8fBQUF+Mtfn8BDT/4ZEy84B9PmzkRtraJ82bdvHy644AKMHz8eM785B7u/3IMNmz7Bm//6J+783S8xYc5U7Nu3T0s3btw4TJs2TdPML/7u1bjuuutw9tln4yc/+QmmTJmCnJwcAMCkSZOUIC/md8KByZMn4/DhqDvJVJ8PI88cjs1blT599erVWLhwoXa+srISgwcP1n4XFxfH1FlXc0IiJZ7KaBpq3SBT98peeIdlwXtGtnbs2INKI0k/b3DMtYb8TAOtXohTNX3Z3zwT6RMHxFwLICo06TusylgtnpW9dIzGIzK7VZfb9Z2NHJQhukW07a6FZ0iGtjlTQzcwtGw+Ft2ow2wGRd0xO5MPO48nXJLBRMVcRfW+kHXRMGP6RIJjAm8P6n0skbmt5wbmEmLr1aSh1ohjduBoBdbGhEgzZ9HVmZDhBg/JtgKK3BZG8/ojyJgxJMbzjLkwicx4uBTRCKqR5BwK8fFWFaqX70CG7luyusZqIIxJb/HeeVAGVLfl+gluHPvO4IEmuPulacK4eUOWUYDUmfyY35mqjZZkMJegCDOqxi+JFRoellH15DYl4urC4Ugb2y/mHhr69xkv38iputVfIOXMbIgZHsM1Zg11yMI2mksyGv9zwCAsJWUWJHNUPbkN7gFpyL70DMskUksITe8dQNaFwzQh17AiFJKNqyMWk1vDLdti+5Gav+8E90uQZ0ZDK1iafFh8X62fHUfqmL5Rt3d6JUvk79CxFgT3K+YRwQNNOPyr/2LQ/0w15GOloW7+SIlQF67xwzMoXTunbn7Vu3vUVlOs+tvIcwa/bkTlPZ9i8L3TYtNA6W9VIb3upb1IG98/aq5oEk6P/FrnYtTGjaT/yzrL+8RDH+0UALgTtTrXtVe7b1FNajEmvPbaa7jgggswfPhw5OXlYcu2z7CxfDMqKipQXl4Ol8uF2tpaBINBXHHFFVi9ejUmTJiAxsZG+Hw+LF++HFlZWdi4cSMCgQCmTp2K2bNnG57DLg0AbNmyBTt27MCwYcPwxz/+EYwxbN++Hbt378bs2bOxZ88eQOb4/Iud+GxbOQKBAM4840z87qe/wafvrMNtd92JZ555BrfeeiuWLl2Kxx9/HGcUnI7173yAH/78R/jX6jdxyeyLcNHMOfjmxfPhGZyBWbNm4fHHH8dZZ52FTz75BDfccAPee+89AMDhysNYv349BEFAuN4PMd0D5hKwfPlyXHjhhTH1Fw6H8e677+J73/ue4fiCuZfj+ddfQt/8vhBFEQMHDsSRI0cAAMuWLcPMmTMxZcoUzJ49G9dccw2ys7MTv+tOhATqLkb72HTfYssnR9HyyVEM+OnE2Av0mjAr4S3SAYcONqHqyW0GoUFdam/89wFbgVrLUzf7Pv4nZ1o888CmbbJpUgYZ/UDBQzLkQBg1Kz6H57QMZEwfgub/Ho7RUPOQhDrVm0CkPGb77WMPbYGQERXIZZtNiXqNh96chodkwCOa0kpGrWMiASQULS+guGsDY/AMSIsmimPjzGyiITMXi+3eJW4pyKqhr+Mfd6Dx0iPrNDFStG0IqW5F+LMRqOvf2IfWLcfhHpAG36g8460Fk8avLY5WX5K1JVXNJZbpXfj31aPxXxXIX1oSFYAAx354DegnZnHKFU0UX0MdTRctd92Le2JOt3x6FC2fRoPCxAjU+rLKuglVRPNtFkZ5SAa8QN3LusiN+jJaCKGB/Q1gLgGeIRlo+aRS27Ab/LrRIFDH2FAn6+Uj8nyqQK1t8qvzwzssK+51bdur0fT+QcOxZEw+uMQR+KoBga8akDHztNiJPICGf+5H6+Zj8AzJQGpZX+06rQyf16DxXxXwDM1UzukXgEzvvvHdA2j899eG+wOKMMYBw5I6szD5sJqE167+wiBQN3+oC/piYS+vlMvCHnmXUbMsB2UwrytSBlMbtlDQaOW16G/NY1Ooug1uixUwaxtmizLHMTMyrIwmacokbvg10Lwb+o6TcQ6XwdyERV+yoKyQMrcIxjmYvu1F0vG80ZAm/ybufVetWoUf/vCHAKAIzK+9iIqDX+OGZTfB5VLeQW5uLrZv344BAwZgwoQJAIDMTKXNrVmzBtu2bcOLL74IAGhoaMDevXsxfPhw7R52aTweDyZOnIhhw4YBANatW6eZP4wcORJDhw5VBGoA06eci4z0DGRmZiIrIxMXf0MRbotGjsbOij1obm7G+vXrsWDBAuXZwxyBYGRFQvdhGNJFCASiKxffung+RFFUAsE0hwCJ46NtH2P58uVYt26d1t+1+dswYc5UHDleicLCQpx//vmGep0z/Rv4zf13o29+X1xxxRWGc9dccw3mzJmDd955B6+99hqeeOIJbN26FV6vN+676kxIoO5i7AYDMdtrLzSpf1stL+mEjcBXDUg/Z5D2W9MExltGjJRHHaBDNi5q4l0bvZ9RQ63v7OSWEI7eq9jahSpbUPP3nQZZT+24Y1zkhOUYgSp0tAXQBaizs6E2aFIMtugWmv6gZBwUHGj0lOuUf1UPGYPvnYbWz45D9oftB/5wrECvwiyiHHJJtjZ7sSujJDvyXWztVYaDRXoBw2DqVjTndlp3dUA2aM9UTSRjBhMa2R8Glzga//M10s8ZZBRyJK5p/TQNtan91r+2D+HjrQhUNAIyR8rwnJjyKpeZflut8OjK62xzqzqR0l0XlBCu96N1iy6ypN6G2gFmF5Rq/q68FHApujIgt4Zx+GfrYjSAVgGg9G7zrN5b1RPK6szge6cZJwgxG+nshRunz9i2oxru/pHJZqQsdc/vgbtfGjyD0i09fjStO4wG1RxLTzICtU5QkpuClgK1fj8E5xzh6jZDOtUEKXgw4omFK++r8rcfI+vCAkNWemFaualxlcYYfZbFlNHOnrrx/YMI7KuPfb44m2TN7V81j9DOByUwr9IP2Qbw0OcbyS94sAmH7vwIfX84Vjtlbr/H7t9kq6XWMO0LiGc+Z1jk6qRIsIDyXcTUneV4Gf2Wkso/LKOmugbvvfcetm/fDsYYpLAExoFxpWMTZ6AVieORRx7BnDlzDMcrKioSplm7di3S0tLgBI/HowjKHBAEQRM+BUFAOByGJEnIzs5GeXk5pOYgJP1mUV39+A82IDs7G1s+2YxwVStc+T4I3qh4mZaaBh6WNT/X23buwLXXXou3334beXl5WlAs1YY6mAZcOPciPProo7jlllsM5R1bXIY/PfkIdu7ehddff93wPAMHDsSSJUuwZMkSFBUVYceOHRg3bpyjuugMSKBuB1ySUfvsbqRNGQgx3Q13P/vGy0MyhDR3jEbKlZtiLSAZdnEr7mP8X9QhZXiOIgSbNRN6AaEtunkiXnkAaD1WvE1bsWUzLSFGBosYbQeidtVKGSMmD3oBSNW0m+7Pw9ykRYzt+O3c5hmWifUTj/0NSC3ta0wbMGpf42moWz87Dn/EdZZ5klP7wh60blaWS9OnDrS8Pl7e1gI1t74mLBuW/Az5O+n8rYRjSQYgms5zRaAOyZBbdPaeEo9qi6w2bGlanth26d9di6b3D0KqDyD3ihGGPFV7YuZWy2F8GFdeCsLHW1H9f4pNdb/bxsPdx2cxMJp+Wqzw6I81vZvYJV3wYBPc/dOMAmhIVjZ46v1ayzwpW19zu+ahyKTIJRhsqLXzZi11pDxidlT7Yrh/krbvhhUF83PEO2dD438OwFfcB65cn8G0I3S0Be7+qTj+5/KYa5rXWYTfhrW23Q79JElqDEaFeh2a5jUso/Wz46h7fg9yFgzXJVAzUwvAFW8PABr+VREtV7xIkqq1QFushlqvtbYzh2rU3ceQvzrBs9BIt3xi7dZUuzYkQVAFarMPaNUMw2IlRtUyt22NTiCtfEg7Rl18ibupUqdRtrFnE7O8lpv99UiTfwOe7oGY7gZzCQglcN2o9nvMK8aOa3pNtg2hoy14fuUqXHXVVZpNc7imDTMvPh8lo4rwxBNPYMaMGZrJx4gRI1BZWYmNGzdiwoQJaGpqgs/nw5w5c/DYY49h5syZcLvd2LNnDwYNGmS4l5M0ADBt2jSsXLkSM2fOxJ49e3DgwAGMGDECn/5HMbEJVbZAzLLW4qYhBQWDTsPzz63GZdMvAecc23ftQMmoYqSnp6OpWVGIZWZkomDQaVj915X41iWXQfKHsX335ygtLdXyUr+XA4cPYuHV38bf//F3nHXGmZZeb1J9Pjz88MOYP38+brjhBsO5W5fejGmTpiI3N9dw/J133sGsWbPgdrtx9OhR1NTUWNZHV0KbEttB6Ggr2j6vQfVT2zXbZzM1f9+J2tVfgIdluPJSYhO4BEsBp2VjVBXLQxLatlejZsXnaN5wBK3lx9H4gWk5VG/moHXesYOxOtCoA7nqH9vJzm8tH9PAFvMh6FqTtjMaUJbQRGNTsxsYFK1o9D5WS4Z2mkVDJ68PqLDqi5i0PCg71lDXrv5CK6c5upcqTAPRzTMx94qj1WMui8FCstZ22graegEszr2s4o5auecDFOFWDsnKyoJ2PtHOTfVi48ZSRUNtNJmJll2OarsEhtbt1TEu8ASTllEVbmIEalPd6DXIKkcf2Bz/GUw0vLUfNc/uNtlQS1FtunrrllBS0dvMG2t5WAZzC4qpgBz7nq3SA8Z3JrdEV0nUb5XrhEHbssjcsKJg6XVGJa6G2niucc3XOP5YuTGJzBHYb/LBrb5HGy8gSZl86CYqdq4UNYE6JGvCfv2rUdOZmAk71wl1+qJYfYvqMXXzqe69aTbU+k2MyUYL1LzOxF5X/+q+uJfyoAwWWSnTa5iDB5s07z9693Pmvq5p7aHoOQtb8sTvybxZOY4pGOeQ28JofPeArZtBIdNjd7HxOZqDSbsztXwvDt3tPf/ai5h30VxIzZG9RTLH/IvmovLYMQwZMgQlJSUoLS3Fs88+C4/Hg9WrV+Pmm29GaWkpzj//fPj9flx77bUYNWoUxo4di6KiIvzgBz+I8djhJA0A3HDDDZBlGcXFxbjiiiuwYsWKGDMIu4kJD8tY8fD/YfnypzFu5iSUzZqIN9a8BQBYOPdyPPDEnzDxgnOwr+IrrHj4//DX557B+NlTUHr2GLz22mumzJR/7nnof1FTW4sbrr8eZSVlmDB+gsWNgTFjxqCkpASrVq0ynBo1ohBXLbgy5pI1a9agqKgIpaWlmDNnDu677z7079/f8rm6CtJQtwOztwsucVQv3470qQORUqjYk7Z9HrVf8wzJAEwBRpjIEtojyq1hzTuI1BBAwxuxy6F6bwFmDXXzhiPwnpWDlg1H0PzfIxh091TtI9c0KMkIAWYNtdUMPnJz7T7qKdFoK6wtXcaE2TaafFh96FZaa6k5iNrVUcHZ3AkbtKuIdOb6Atm56osRbOwHAbtgBHGFEBuTD2vBOY4piLbUH+deVm4ardzzIWJ+0Wh8VqkhACE/NZLARlMORfjQ5xU62oKWDZWW1wUqGtH8gbpRqg21K3fB1TfVkKd54JUjPrRjNl05cZVot9Qdh+CBJqSMyInmEZSiG+4i1L20N6k8zfbbPKQI1FD7BdOzyG1hCKnRiYUmOAcksBQXuD+Mhrei/YP6XbVuPIa6l/ci/4ZSw7nm9TptpswNbSN2k6y1eYgaaMhOg6jvA/V5md0qHv7Ff9Hn+8XWk8tI+cwbywx56gQd/f4KW4FaH75ai7ynW1Exe2CRuaVQV/9arADLZY7Q8VYtMI+hr3JFg3xZldcJ2kQpMukRc1OchYuGYjueOkZZqdMrH44/Wq79HfiyPnqvOMK+uX8HlGc1fxfxiOv9R+aoe2Uv2rZVwz043TKJmOaGlZ6ch3ls8JwTGJVlzfOKwCnVByCmewCJ46Yl1wMA3IPSY9rxhAkT8PHHH8fkc8899+Cee+4xHMvKysKOHUoQMEEQLNNMnz4d06dP136npKTgr3/9a0z+3114Jb67MCqY7tmww3Du2sEZCDcEMOy0Arz1wuuQTe98yoRJ2Pqe0bPKm/94BYCyeqC2hf978HHlZOQdPH7fn/Hko08Y31HkXO0XlZGfyu833nhDS1K+YUtM37F48WIsXrwYAPDAAw/ggQceiHnOEwkJ1J2A1BDQNsKkTRpg2D0NAHJjEEKqy6i15Ui4LCu3hLQO1Kzh1afR/m6LbA5sVTww1L++D8wjagOV3BaOpnfgtcJM03sH4TktE76RylJLvMFA3aioYdZQmzRp0ePcoLm3EvhVbV3zp5WQm0PInHkaQsdajfc3CU6yP2ywk5SDkjEYlo12xayJkf1hez/Zdpsl42h2rd6rnZcPLtmYFUgcYOo6ajwNtXWehnwARSPnFmLe77E/bkbG9CHwnpFlc4PIv8xYjqBeI2mSifQb0MKRd2hwMSnzmHKo2qcYU4AuGjS5P4w2nYuymNWN9uQZiUbKdHa1zC0qZh1y7KZUcx2o7VUOSBDTXAibNNjqyo4akVFvWtX83yNGoa45hON/ibqva1xjtAvW91uhymbwUbmAS8Dhn61D+pSByJ4b8abhoPq5xC398fr31MWdDPJQVLsag42JmHnwVdGbfFj5xpZaTZMuzi3ft36TafSmHMf10XD17yWShz70uBNPM+b8gah21zMkA20OBWog+u3Y2lAjakoRb4+BbK4jOBCoZW4wcYkbPlzm8O+pV/60MS8R0i3s4wFLUxwHQQCdpUkSzm1WFXsIqvDfKaHe9atg5vzMVcQjyhRJhuC2+e67IWTy0Q7MHb8+klbLx5Ux2ipXHx8EU0fDZW4Z3UmP1BLSBCizVlxFb+Oq7yTrX1e0JzwoRW332sJGn8ZI/kPRh2+O0WDo6sWsHYoZ3OyCYJhMPqyWBVXhov7lL7XB31wWsyYyRusUMG5KNC9vAkodmX2syv6wo2VaV1/djne979itVYblVrPpgJbeVqC21lDH94EcWw6VhncqtA0hemFdcIuWg2bT2oOoXr5DG+TCtX5IjQElqIKN+UiyMF90ns9lHmPuoE4cY9qOQxk3c87QpMsU/LoRngJlB74clOK6AkyEr6QPAKMwFW4IQsz0RDTUsSsRMTbXOg21XnOt0rrpGELVbVGBXddmzSYgga8aELJwnandW9dem9YeUlaCIuVrXn/E/kGtkLhlu4LE42os657/AlVPbbM8p2/zBhvqSJ/j31OHw79er53TNNRh2dLMJNa+2Hk/yWVu6Hv0EyErLXfoaGvMsbj5mzbJihZmD5nfOA3eM7Mtr9fMpeK0X3d/ZYVIMitFdGjfoOGYkqfUGETgQGPMeQCo1o8fcd4313m6keqtzREEiwmW1BKKG1gpLjw5BZMj1OfQfJp3bvaJUAV6HpaVfssfhtxmrxSyyEH5x8I/uNP7W/5tqueYSRDnkOr8COsDvfWAeQkJ1O3ALLTE7PQ2kXXJ6bFG/zJH7bP2UYaYW4DcHIoKJjY7naUWC5MPcxp1+bE1FF2qUzXUDsLR2mElhGr3tFgS1KMNDObl5bBRmDB/eMwrxmhO5KCkTRTUTVrmupAagwbhmAeNu715SIa7fyrc+tUFiceE6OZ+Z8KUrzg/ek2krqWGAGpX7Ubtyl3R57GYKOm9PBgfQraPnqkLMJIMbVurUPvsLkM5gcjmnDg2jmoI7cZ3KlB5z6dKJLPIxJLrNKwxWiQHA5usDwwi85h2Zmsu5PDZ9f7fncK8IvpcrUTl4kE56aV6lYwZQ5AyIrLCo7f3rfPDle1VViwsbOXbtlehVueOz7+3Hs0bjiD4dSNgYyoht4Q0gVHvB9/s/SER5smof299+wOoSBbL8VA2JNpplAGgbUcNAvsaIAfC4JwjeLgZTf89jJaNR7W2CEQn0swjaM/c8PZ+8IAUtaONtMHmj6w3QVqZCzjuJ80rC3rh2sLu2L8nuXeheX+JfJuWGmFRgOCzXnxWyxCv73ZFNnKal/gN+VhpqCP1duzPn6FKt+KhR79aFXf/jhzd5wOu9OtZFylu4MCUfiVtUqxr2OMPb7F+Nptux3bVQz1vpfBIgugKc8fU31aCsRQZz6XGAML1AYRr/QhVtyF0vBWhoy0IHmlGSP3vaAvCx1sRrm5DuKYt7gpFtOxyNN6FtjfAYX1YblqPk16GcXLLo99OdDLb/SVqMvloB8mGmBY8YmzHl2DwVz2DCKnKK7Iz+fDrolgl+kisNdTtF6jjaTnstArRa1W3a7EmH/E01EK6O0b7LNX6tYlFzrfOUjSoJqG7/pUvDRscFRvqaJ3ykBwb4U+WYzTUZs8XdniHZUG89HTUv/GVJvipA3xYXzcWGjIekHD8kc+MByMBb6xd3+nK3h5BR52s6dt1BwYSqSGgeXlJm9A/xq8wAKXDdWgiEBMZ06btqoEuEiGmO7fzVBG8ojbAt3xamXAgjptXivJNq0I5l5SVEDEnBVKroj2STdEGWz6JmBdEXrNqdw5ETWXMBL5q0AI06TdlJfo2YzB3ESYXgeFav2Zakggelq011A458usNWJH/GhZXzbM8r373rjyfpfDY9nm1IXiJXhjXyuiXDO2Ty9YmH1bUPLPT8Fvfdv17jcIz87mUCVEymEz1rMwemMhsBepoueyFWdUzijnipR5rgTqy8b1RDfQVv86sbOxVWrccM5hwMbegrfIyj4iBv5hkeZ2iALH+vi1NQQQGV9/USJRE0ymfC0KGx/KcU2I23HIOLgOqf3n9v6qZgzahlnkkffS8LYwBQsQdrsC0Dc4QmPFfFjEHi+x/iJdn6GhLtH2p+2NEZrm5PfbBlWc3ePGKJ/NwrgQ5i6QxbNyN+NzvAfI0CdTtoh1Ci3lpLpE2TUh3Q2oJaX5DnZBIoK75W6SzFxX3e5xzR0uZ5g6HyxxySyi+hrou/qAdOtqCcE1bzFIzD8sGG2pzpyxmehA63Ay/zkdr6HgrpDo/mFfU+Vk12d2avIXIAcmwPKPYaApIP3uAZrLDw7EaasDoEtAO5hbg6hfZXBfmkJqD0c0/DGj++Ag8QzIR2N8AV79UyM0hbalZjVpmfHBBmWiYbaiZ4s0iJWLX3ra9GlJjAA1rvkbocDP6fK8oYVlV23JDpMQOCNRN7x1E03uKEB3TftX5gwMXVAAsbai1yaDpO6z5xy44QUhLvttjXlGb1IatwsVb4B6cbrCXBQAxywOWEnVd1vTBQSXYhqy40gwdbUG4qs1+k6OVeajN6pXe9VoiTx/JYPZPfvQPkY1JTnyhByXIrSF4hmTAPTAtOlGI4O6fmtAMwk6YBqKTFFcfn6aJVyflPBBGzd+NbURIsfEP73VFheGws37SCoPAbmqvnsHpCOytTyq/6qd3IGP6YMitYUXITLFoywIzmE1piFG3q3IgjJZPj8LVJ9YDlTvfp0zg45m2WYxfZjM/K1t5p5iFbeYStDG0I+ZkZhhTFF5Wrm1ZiqvDdtWaQB35NkLHWuMLlgxGIVi0EoyVNFEhmVnuBbAsj94G30k1mocbFwOPv/gcuRGPUTwmcnEIUdD2GejbnmGvDIv8rwvs3TsDMvlIEqk56HjgBgBvJAiFeaNivI/KV9wHglfUlmeA2OVtK3hbGCzFhRydn19m0eG6ciOdqOxMQ51amm/4Hfy6EZW/+yRGWEiGwL4GHL1vU4yGhodl1OuCO5jL58r1gQdlVD+1XTtW++xutHx6FEKaOxpGO8HkQmoMGMM9hyQwxpA2oT+y50c2WZltqCOdYtiBho+5BU0A47Js1I63hVH/6j4cf+QzcL+k2AJGOgj3wDTLgYyJDDCZgmTOHqp1inqfyE1rDyk2tJUtqLz7E8vyZUyPRtgUNIHa5OWjExBMArXWD5qyV7VianQ6Ff+uWntb/SRXirQyuJLXLqsTg4xZpzm+JuO8IYbfKSNykDZxAMSI1qfpw0NoeLtCcdnmEuAryVfc5iXpSq3PtcXa39nzbMJtJ6uVNmGYGHGg4e0Ki5skHqEVgToMIdVl8Oaikjqun+ZRRcxNQdYlpydVTlWp4MpLUe4VkKIRXa3MNnT9sP6b4AYNmdQh0zhLRIa0cf0Sp7Og6YNDaPn0KJhHsJwQMJFZ2hfrlTrcL6Hu5b2oenJ7bLosr7Yymgytnx1H04fxXeu1G4HBOywLGTOHIGf+mdrh/OtKnAV+kWEtQMYxQRNSRFvPMk5RzZj0YcwFnwtithdibgpcfXxw9U2Fu38a3APT4RmUAc+AdLj7pcGdnwpXng+unBS4Il4zxDQ3BJ8bgtcFwS1GBW6naP7RHa4S6ZQeQro7qmlPUC/tmfIwkRlXbBlThGxJCcAEDkAQlPGqm2qrSaBOFjmB7ZeO3CtHos9VhQCAlNF5GPDzs7Vzdhrq1PH9kHdlIZhLgFTr1zQYTlwjya1hCF7BoF106zfHRYgK1PG9FfjKIoK0qZWE9EtgFi3IYwov7NaH54YiNNrBw7IhEIRZuNDKboHgc2neRNo+r7ZNBwDh460Gv9E8FN2gpC7nh440G5Y91UEm4UwbEa1hRAAPfFmvhXkGYpdL9S1BzLZ+PmblTs3Ob68DW2K9VlNIdSsdlt7LRydFJzObRhiiKUbIXTQC6ecqDvjNmsC6l2M1tY42YALwmSaCWpnaYc+oTgyyzh+KQfecY5uu701l0fsIQPq5USEtdVw/MIFpbVjvoszdP1W5h0XZ1M2Qdrh1gmn6ZJvgQsn6Ozbhyjf2I3r/68nAA5LmAtAyqFE46s3DMzgd6ZMHIn3qQOR9d5Sj/KU6P+Bimold9fLtWh9nZaJm2Ddgt0+lKdjpm9X6LB5tqezwnpVt+J1+ziCkn6e0ISHVhczzhyJtouJbl3lEa2EysuRvRsyM7uOJt7oopLktN7rGQ8zyIHysFQ3/3B+9R0eCv0Twnq6MJaHDzWACQ9bsAqSNj05EvAVZSC3ukzgjzjXhUMzyRieIajVZrfyIQoc0oUePH8N3bliMkVNLMHHGFMz97rew56u9YCkuiOkeiKluCCkuCB4RzJWkYOyAtWvXYv369YZjyU4Q9IuIqjYcQGLJkUOr05i2aFcGxuAZmB6d+DGlD5XbVPfBETOVbqqdBkigThrmdV5lrj6pWvQ3xpgxQIWNNkcb7E0205Yumqyu94iGBuzqYyFQ5ynHrHz8GssSycdsW6zrjMWM2AhLZqG3zxKj2UHaxP4Y+D9TIFoEvDHbq5mXDe0iOgERjYIaPCGBnWbwcDP8e+s1IVkvUPtG94GQ7kbLZ8cNGmo1lGqMS0AL9BrqprWHDANNDHK0sxc8Nu1L3aymFwBsOiYnA5mhkxMQo8HRC8K5VxYmzM8Os4Y6GqlTdy9R0AZ7O8HFoCF1sKE284IC5C0a2Y4SW8N0YXSZwDDwrslIGZ0Xk84zOAMpoyLHOZCtbqRCtM6ZhRso7ZzFXglfkQOBAdA8O6TqBI7UsX2RUqiLKGbn6zlC2uTYjV5AtM+IIcnJiRyUtb0hlgJ1UNaOM1EAExmyLz0DvlGxdW0Jj5Q1kodhImvlyUfX/9mtysgtYWXDXQcmmebJHfOKls/vGZwRc0wVtNLPGYTMWafBPUBZ7RS8LkshjNkK1DoNdbx+X2BwD7T2/WyFrygPrvzY1Ybqv+6wSB1LdYpiFsMtlOIphXnwleYj8/yhttczqz7TVC0G+2mG6JimuoWLTNJFs8ImgQCqjunmyRHnHAu///9w7uRp2P3fbdi47mPcfeddOF5V5UgglCQp7m8nWAnUSmGT+Ga5tQJHP/bE1FnkOrXOYzem29xLbw4IKOMR043nXHfpCfQrngwkUCeJ1WBoh9kOVd/52Wo8VC1pgoHPDuYWDMKQKty6B6ah7y1jkDZpQPQDkBJsttH6HGNZArrNXzFumwTEbIgRUl3I1Qk3TBAgeETkzI1dng4eNpqRmHfcx5vQMK8rRmvrs9BeiLkp4H4J3B9G2gRF28NDkmKbBkUIdOWmKF5WdPa7qlCXyIMJoArUDt+hTqNsZzPPVHdqkmlgsCBcH4DnNGVgVrVZMegFNwv/1voBWUxLTltlyMesoda0yrrCiyxqH2nTHvUTQ23jSpxNseYxI/f/RdpfO7VA5omBkOJC7sLhyLk8GrK6/23jDfc2b4KyEnLU1RutXzEVj7kFJTBUAgb9dgr6XKN4IdELH2KW1/CNqh5G7LDTTLpyrFdO4q0YRQsRfSi5LaS4+vO5LPs4LcCN6TpbLJK4832W357lRjq9kK0TcM0T91BVKwRf+zeiqppWFcashd4YVHtZQOsnVE9GzCPA3S8tuldDRbQRqPUb4xPII+lnW/cblgoNgVl7G3Eo8/BIQp5iMTnwCMhbNBKZcUytzGMyc4sx0VUNCgP9bTRvFJGVM3X8VesvURM0vRuVtRs+gtvlxtKrvhfJh6FkVDEkWcLcb83X0t10001YsWIFAKCgoAB33HEHxo4dixdeeCHm95o1azB58mSMHTsWCxYsQHMk7HdBQQF+/etfY+zYsSguLsbu3btRUVGBxx9/HA8++CDKysrw0UcfxT5zpFy2k2WYVraYznZZ331b9Rk6DbXgdRndBifqgw2bm0yNqBtrpwESqJPGclnGphatZs6D7p4KX3EfTUOgRq4y569qqrzDcxJqlQBogqEalENFVLXRAQmegenImX+mJvDKrWFnS5kCkLtoJHIuPwveM7O1MLVArADIRCHmuZkoGO2w1We0EB7N3g3MHjXi7V5nQuxyfu4VI2IGF71wpi2xmtz2CGluZaOgTguqPpcT20A16p0T9JEO7bxHMI/ixs7gvURgyPtOIfKuji6HuwekabbF3rOybTX6+jrhMo+xR9afb88mPi0f0zsO7K1H9d8+N+7gF6MbjtTNlWYMEzdtJ3gcrY3pO1UHWJdpVcSpTbRVWxW8LviKo5pTrV1pg6wpD93A3/emMvT5XhHcEWFIre/0cwZF3YMB6H/7BEf2rMwd3TSp13wyr2j4Zqz8FuuxmzyJWdbXOTEN0H+Tqi23nR1kxnmDdRrqxN+PlZZXzE2JWeEDrFf5DBNmXZvvf6cxHHL4eGtSyhQz+nrKmHWaEjHPSqCOqZPohjN1IukdmglXvg9ZF58O5hbQf9k44xUCsyyr2heYTfDUMtmVV0/fG8tiVz0FZts+koH7YuvDyaQj1qRA+x8Ata1x3QTXQtOqnVK081YadyvUb9M8Lu3cuxNjistMZbL420ReXh62bNmCb3/724bf3/jGN3D33XfjP//5D7Zs2YLx48cbogL26dMHW7ZswfXXX4/7778fBQUFuO6667Bs2TKUl5dj2rRp0Zvo+16P4FjJwASm0xBbp3EPSIPmPUS9DzP2K7YKcrOG2ljUaHY2CovuAHn56Awi0c3MWHX2qm2tapsbI3RrGmrluOBzgYkCeNheeMi/rgThqja0bDyqCNR6DXVOxC+zbqapHgvX+S2DDcQWmmkCsXtgOo4//Jl2ShXImc+lbAQUWGKXYqLRVtnqfJ/vjkL1Xz+P0VB7z8hG35vHxLqVi5TTnKdS39Hdw4AiVAX059W/dR2LmO5B8FCTwaZX3ejjSEPtEpwvrRk6OOs6EXxuSM0hg/02Y1FzgLxrRgMcaN10FG07lB3yKSNy7AV0fduUeMwmFf2AHKPtSQKrb0A/IQMAiAxCigv975wIMcOtuXozlkc3AVBNPuJEcosxU1K9P5g0quZNXX2+X4y2rVVo+fQoxBwvvGdko3XTsRgNtd19lGPqTY19gj4PdWlf9WagrmZ5BqbDMzA9aiJkseKTCL3ZkOAVDXJ9orwsvUPA+j0C1koDQLG51ryhCBYCdaorJnBI5jdOUzSdNuYv+deX4viTW8ESdFlaxEkTVvtQ9P2ioS8wvVe5JQx3TgokU9N1in5ykBVZQbAWqE2rGgwxWlDB50L/H4+3v5nILE2H0ib1h3tQOqSGAOpe2GM4J/hc6H/7eK2/sPUuJTL0vWUMjvwqakrABGawzwZiPUM5QfYxmO/qSKA2tU2ms7P941cP44umvUBYWfngIVlpX+p+FJeykqh4l+LK85vNRUymQsMzzsJtw28FAAhuEZ7BGRarZbqxJNveTNHMFVdcYfn7448/xs6dOzF16lQAQDAYxOTJk7V03/zmNwEA48aNw8svvxz/Jtz0t1Otr95URj1kXh0QBYArK8uCasNj9uhkMy5G5Wnd+RgNdfdWUZOGuhOws2W102joO/sYAVA954oK1uoHbV421K4RBc0VF+fcqKGOLLXobebEyPKtVBeIu1lJfS7945nL6xmSgayLhyH3W2dFyss04cDVx2fYiGl+xhgPENpAyrTgG6pAnTqmLzJmnQbGWKzHFB1WNsjmpWVXblTDYhh4zBrqppDBxEJzyedEQy0KcPfxaSsQ8TZi6iUeO8FN8LkQOtJs7Ax15fWNyFVCwuufRxRsTWT0g1DLp0dx9L5NtueTFeiM+UTLaN5wpaWJCBtaYBPLfHTHdRpqMcuD9HMGxaQ3L0Grm+rSzjbaCJu/Ue+wLPhKlMkjE5hmJmCOdKpdb6XdUe0yzWOBpZZbtCyHPn8h1Z2crbJeMPQYNdRq2XwlfZB14bCYFQHbiYPN/W0nxfo+wxSwAVAmiOpqgRqZT9uwqpbfVLfeoZnAmMTmL8zFHJtb8WBUEDILb3lXFSLr0qiXkbj+y033Yz4XMucURA9Y2To7MflwRU3HnAYusrOhFrwupJyZbXmOicrSv/rdWLrji+Qd40FEYDErH16dtx59HVrBWWSC7LOqo8SrAok2UEc1mvHzYO6ObEI0XjiqcBQ+216unNEruEQXZB7t8P1+4yQvLS3N8jfnHOeffz7Ky8tRXl6OnTt3Yvny5Vo6r1cR2kVRRDicpJ93xwK1MaF7ULoxIrAJTUmjm+AAsPUUEruAwKMrJXqh/CRFnXQCaag7A4vOMmP6EHtTjTgCtaah1pZvo2kzZgyxDEQAkWkb5swaanVDgH4Dl5jpBQRFQ60XtPMWj4Yrx4tjD26JFM6ivLrOOHV8P2TOOg2CzxUNliDqbLhFG9s6G5OPlMJctG2rjm5McgmKKYLIkKtzBWjMC8alddNyNxDb4YrZSpkyZgwxDoS6D9wyYIL6XEl8yKlj+ioRBG0ERcA4UNpqqFNdsZvwLCZyekHCzn0W4GAQ0k1M7IRcR+gnKbb24Q60ULo0mpcPf1ixmzeNlKlj+2rhvVXcfVMx6J5zYgRgQ315Fc2mtsQOaIEJVJv02ILFvoP0s/ujbWsVvCbvHFbvVp0I26o2RKU8A+6ciMrfWbtAjC2SsX8xvOtIXbn7piLjvMEQc7wGl4v2NvzWBbRqX+nnDjbkaSWMC2lueAalo9+Px6FtWzVCR7/WvmOtj7GSgMxZWc1nRIfL2C4G6HzcMpeAAb+cpN3XN1ppQ41rvlbsvuOs1DCBGTYMD/r1ZHDO0fivCtv9FJabMk2/M84drKw8As7jH4hC3FVCy2/f/F0kMbFiFn6vU8f11cqdNqE/XFnehO5mLW2onUw6zGXi0c/y9tE/gpDuQbiqFWKmB1JjEK48n+K5JShBzE2xtgHWETzUZPgt5qREvE7oC2r8+Y1LZuOXv/0V/m/lX3Hdj24EYwzbd+0A5xy7du1CIBBAW1sb3n33XZxzjr3XIJVJkybhxhtvxJdffokzzzwTLS0tOHz4MIYPH257TUZGBhobG+NnzLlRIaiaa1hhEoyT8hii75NcTLmFeq/IOa0v0W94zPQAnHeuC8YuhDTUnYC5sxTS3Mi6oMBecx1PyDBtSjRoCtPctpGxtIEZUQ21kOnROla9jRwTFY8jUp3f6NnBLVh3pIaPIVqerNlDNe2XNgEQmSFkrBWanbhZ2x1ZBhcjJinqcnw8d0LufsYZvb7O+95Ypvxh0uwwUcDge6cha05BjACqYqWVtdXexcFRYB6ZRyffcTTU2t/qwG61ud2kcbfy9QskHqg6yw+1vjxWbsIAONO+6tNENlDKAUlpI6Z2llqab/ntWe9/iB4b9JspxntxwBfxkOGx83pgUU3e07Mx+N5pMRv5rNqPNhG22crAIqF+9ROc/B+UOF5GFrxi3LTm9marmbTVUBsrIPP8oQbPJoB1vWva6fxUrQ5Vm0itzbRTA8VcsQJs3lWxbvdilqtdAsQ0d4wmWvUbLlr0vRpWGmjGkPfdUei3bJyNhjq2PWRMibo9zPzGaUqETpMNdSKYwOJOmO001OY87PKOQWCxbV03+RA8InxFfZC3eHS8YsNyduTEBaipTIqwxmLOaxMeax2KY5hV1eryEdLcED0uPP/Us3hv3VqcNXI4iseV4hf33oV+fftiweULUFRUhIULF2LMmDGO7pmfn48VK1Zg0aJFKCkpweTJk7F79+6411x66aV45ZVXYjcl6okx+bCpEJdgMGN0/GkypvTFhhUr4/fNXAzugWnRMU6tX658Q2pb5mHZWDyyoe6lmD/oRJ2AE5MPdVDRCSRiugf9b5+A1i3HUP/avug1ogBBHTNlpQNTNhDmgDGGwffqNiSo17hFSOZd75wbBTLd0kv0OqNJQfTvqGY9OlDY1IOa1uwFRWTo96Nx2oclpLgUTxtxNk668lK0aIsG92C6/M2RtYxCtLXJh9GtHANkbnhXqWP7onXLcdtyRTOKvWcMuk2Jdm7z9AI1SxGBlpD1hM00QfAMTEf/n0xA7eovDEF0EnmRMQ/IA35+tqYhzf32CNQ+90Xc6/Vl0P62EdKT9QsdOtKCUFUrZH846kNbTxKePOzcjgEAOEfWxacj8/yh9jbESYzIlnsq1DZq12doXgcifrAvOR3eYVnIXTQSVY9tTXxPr2icDOg2XwGICUFtO5GytaE2C6Vqg499Bu1nqssguKvCmEv1XhHXxMGBitrFYlaErEyfmFsA1wWQtDNt0hQU8TTUbgHpkweiae1Bw3HV3Z8hQJQpXz1ilhcZs05D07sHdAWLPGOccUXM8kSjugrM1rbd7r7xVtAMRMrSZ0kR6l7eq9jEM2VvQu4VI1C7+gtlxVTV+upXDB1M0r1nZRuiR1qucNqUyRa1PenHAbP5QCIMdsDWk6foD+Wfgf0H4NnH/gb3gDTwUDS41x/+8Afcd/99MXlUVFTE/T1z5kxs3Lgx7nXjx4/H2rVrAQDDhw/Htm3b4j6WefLhyvdZ2r57+scxWYyHVfVq4oG1C1hznyp4XZAQUFZoXDZ5dhNIQ90BNPdU5g86kUCt//bMWitV2FQ11IaZrwuC18IlkItFyxBppGnj+2sDlGURRIbAnjrjQZ5YuDFs3LEaZJPRUJs7M5HB3TdV60Rtl9n1eUU0fL7ReUgba4w8ZidQG7SdLv2HrLtWr1mNPI/+XWVMN0bBs8MzOAPpUwYid6GNyQqMu5XtTT50Gh8tKEECLWzkb1duSmxEtYQmHyZBSffsqWVRzzT6KH2WOBKoE3dDsmkD4rE/blaiTFpoqJPSbMbTWnOlPu20tp1CImEpUjVMUCbGGRF7caeTENUvPfOK8BRkRierkX+9Z2YbvD7YaqJ1x7N17i5j2qu6UmXzLQGx9ui+0nzkLR4dtW/XNFTt00Cp/qsNxzwihAxjv6m5NXUJ6HtjGdw2ezNU7xhWHlL63hLVMKafYx1UR7mZwxUTIOa51ffjOc0+wE/fW8Ya8o0nvFr6QXcoCahlThmeE/UsFUF13yd4RS0ITb8fRuvHzvyMa6pKJeCNyoCfTtQiqDopky5DbYzl6nmBGX3g28vGMbgHpmt2/rbXxMvHPM51I4FQ8OnCq4uKO9t4q6rMpr8S0t3ady3mpETbn0Ugr4QBbMzV5daZcNGmxN6LuuEsRjBMJFDrzps1ktHGZtEBa4FWYo+7slMgZHiQdXH8DSDaNXqBSrslsxa09GYhei2uXsspRTcUaR22XTXo8sj7TqE2YGlLQRFSTQKyHl9pPjwFmVoZrLRHWjnMPpZ193GiodaC8+hdyZlcmak2hEKaC5lzhuruxZA994z4/nplDrWy9AJKum7516Ch1mzNLPLSTxD0wqxJKEwkxFqtHljhPcN6o6zVfWyXoR24hVQ1qQZvH0FJqQuTAGL2qR0XK0GnHZEU20uiDWe2ZmMJJkR9bypD6vh+cEdcnA381STkLy1B+tSByJ57hia8imlu9PthVBiz3XyoO64PD28WkqLp9BM7Y15mv7eMMfhG5kb7FvWZrV6jg1ejj1KqHRNYjA9u7bsWGTxDMmzrOmfBcOR+ewR8o/PQ96YyZH5DZz7nivbJcYXYDkTB8w7NRP+fTkTq2L62aQzuDkVrt3laWazKKViXPa7LRp1plD5f5lFCdmfOOk0x6Yl335jCRespXhAvy3JYoS+b1i/oZ3uJ34shQmAEwecy1o3hfHwBuqPhzDsLV34qxEwPGGMQc1LgVqOhxpNf1Lo2pXFlK+HRAaUtxvNtrY5ftis+8Twn6f/ufhYfZPLRHvKvK0HoWGu0UZk/6ESdp26gsNuUGK+1mD9IFnHkP9DCo4ZtHrrOLffbIxCu9iteRPS3TfTh693MRbQ3vuI+Cd3m6QcXX1EfNH9cqbiDMw+CcTpgNQpe/Rv7Yspivj5GQ20jdBpCiuvtqb0i5CZjWr09bNZFwwDO0fB2BVLL+iJzRmLfxopf6UhIZF3QAYMgrxeidZ23puG31HpZTxDMGuqEJh/mujfdq9+tY8FSxMSDg0FD3f5NiaqGWkhza67XpNZQZKA0CdRh5z1tXLvqE9FhO1jOtySB0O8ZnIHcy6MrPNE6ZoaJmhnzpDZ6P+ule7MphdWknwmKKVfTB4fQuvlYXC89anrAoc0wU7wNhA43R02zXCz2vTKGnPlnwjssS3MZF90QGr8uxXSPtirjGZwB5hXR+J8DkeeNTiCYS8lPP+GIZpKE7srim3I5FS7hQENtZXpk0Z4G/s8UMAYc/qVFtD3o3jU3KgPUiJ0x6U0b2ls3xYavb8/EI7bsPKYO9d6ywOJab9jcxPh3jMAYT55mDLx7yNAGmMi0/ls/IeNx9BFO30/cCb/AFFeD/rB1VF8GgBl9mzPGwMGV2DIuUdlL1g3rlDTU7cBbkIX0swdAzElBSmEucr8dXc5PHdMX+UtL4l5vGChiOn7E/M66+HRknDfYPk17vDDobbOzU5A567TI0phVga2zYCZtwsBfTYoEZogMiHZLtjG7stXNSM4Fai1NnCAQdstThk7BIFBH/UszK9s/gzlF9HzapAHR+owjA+jdHor6TTwy17RPevMCgz9hvX1nvOUvG/tw8yRHSPcovqttMAu5ZsHZ3T8NruzEUfIMWnI7O9wEwmHuohGahtpgfhFWNuDGCF4ONNT975igLNerRbIwlTkRErVq3+yzCGMejw55XomHAw21YZXKPEmyvF4x5cqaPRS+0nykT41jGgFE27VDk4/87xUh//rSaL+o+p6PkDF9MNwD0sBcgqGe1baUrBCnr3sx0wsh3Y3sS08HExnybyg1mC1o1yTzujq62Uq3KTG1LD/mtLWGOrYOBI8YX9OtTsojxXVledH3xjLkzD/TOr2uD8qaXWCbb7KY+xWDGYNNGm1FsF3aYouxxrTxzsk1Jx2bIiW7+dYOMTfFOM6pt01Q56prXMPmYH337BXhyk7puj6wA5CGugMwkaHP1cbOM+vCYQmjkTnSRmlJGDKmmfzsWmioO4JB42SxucJpB2/wGQnEyiMMml2qATWd2XWTQz+tAJLz06sXNHV/h+ujrpAMArUa7MAgdOnK6bCT6bOkCDX/2AX/7lq4clIQPhbZ/CFzZF96BrLmFBi06YbgKgZfwrFliD6PjUBkNuEQGHwjcmNch5nxDs+J/1CJsNvoqSfBu0st7Qv/3nqEjrbEeLlhLiGmnTnRULtyUoAcwN8UCbBkJTB2kjzNvKLts7v6+DDod1OTHhwSrTC0F9v2oxdIbFZq7K9XKlLM8morS3FRb2XVT1otKKS64R0a1ViZbaizLhimS6wru+ZVIMm6NLXpgb+YpP322tk5x3m/QqYnJkJsR2ARV4uD7p4KHpTQWl5lPO/Ay4cjLL4TzxD7fS/GDe3R+2na23Y26ZTCPHiGZiL4dSM8p2VYf0v6d8x0ZXZ4T8txMTaVkrH1nLL7YdPuxQwPhDS3EvfARDKTz0TuCJOqE7X+u2M96iCBurNx0DEZ/A6bBR0n94jRULejlek3wnXAvs8KV5YXQoYb2Xb23A5dMiUVJSsJ4ccweOgHRxv7cG2Tpd1OZDGqnYgXDpW5BE0gVF0DqtcwgYGluAwRt4w227rOSQu4Y6EpcRqAQ9Pe2xYXA381KXHUy3jolhQBk6Zf/w04ECZz5p2J9KmD0PT+AcNx5ha0tpxx3mC0fV5j8PaSt3h0/AmsWg8WGurO0k8P/NWkuOetnj/rwmFo3V5lkTpCF2ln9O2n34/H4dgfN0fuxyzT2G1K1NdnsgpXzeSj3W7zLEw+1HO6etNcfibZ/9l54olbJpt7DPzVJMAlGCIPdnjjleZ6VbDcT+DED7UTknbnp1fcdOKEkIkMWRcWoOrxbdFnNymDDG2WsRhvN8ndMM5xvTwtMue+w3sYti5Qk8ulHUm7t0RNAnUn42imH+mAUkbl2Ws04sygEy3HJ4PntAzbndRqvsl2CYo9t70QYa4jTQg1m3wk2HilpFEFw2gp868vjYY9trrGRojue0OZ5b0TRetijDk3xYvka/Dbqrept/AuAhhNHbTXbWnyoasznUQixGioY9OYERJpGBIQM0FSzXNcgiGgkJPBnLkFeAakxQxQzBX18uHql4r+Fw4znPeZIgHGoA7AhgE38kdnaajbIfxmnDfYaOZlzrOLNNR6UybDhjK7zbvmTdWdsKFTjGzgtfX9bbih+Qe33JSooV9ZSomzuTcO7foubMrT0W/MCsM7SGAWZnmN4xtF/nU481HbkPfMbNM30fEPLepj2kbdbY4VkSIqkfza89h2/ZVO6BNFEcXFxQiHwygsLMRfn3oaDhwAnlDiyg1xTrkHpXfOxspeqKHufkYoPR0nM/2I8Kd6CTHgoKF6z8xWovx1hEj/kzY5gT2jLm2nYWPyETNRcBB21sq8xDs0E2nj7T2EWEZuS3cbJhaWNtRJlsMKIc0NIcNt2CHe53tFlmVTNzkBNoOk5WRLd1DvncWsSWxH+Nbsy85E/g9i9wdkXXw6xDwLe+rI++x/50T0+/G4aIhxU9pkNIRmbRhzC9GAIO3o5JmVhlr7M4nNjZ0UCMfx/brKftAmWzvf7bF+qGM3JSbbf3hPy0TfW8Yg3Wzq5hCrwC7aOX00VF8kimxIskzbmSSlBY+053abUtsoDLRjVt9Je1Yp29GH9L9zAvpcPap994uH2gdE994aYKbvW8xNgbt/WvsEQ7trdP2yz+dDeXk5duzYAY/HgyeeesKQNOnw4B3AfC8xy5s4sFeceukuXkq6IyRQdzJOZvqqUJAo4pLtPQSGrDkFyRUsphBRN3cnGtvBxVQUZ4Ks8k88U4uYS0zvKP+6EqPrMMAYkECn9Mj55lnItbIDdaityThvMPreOEabLKSW5SPljGzdvSxMJGzvZXHObqnb1puMc9LPHgDvsFg3eRnTBhl8U2v3VAXobK+i7YzcUsxJwYBfOPdIY8BCoE7WHtKApceU5ASFfj8ah/4/mdCOm3eALnLtZztY6u8X1+Sjc8rlGZhu3U/EHLJYWRCZo/Yt+JSyy4HkBer+t49HnyVFiRNqNztxQoidSZtlWtXHfnsmaJppjvO+15WdAuYWDe9Wt12o/airfLZji2m1jMWPJhmXRApqE9OmTcOX+/bhgw0fYeY352Du3LkYNWoUJEnC7bffjgkTJqCkpARPPKEI3ZWVlTj33HNRVlaGoqIifPTRR5AkCYsXL0ZRURGKi4vx4IMPAgCmT5+OTZs2AQCqq6tRUFAAAFixYgXmzp2LmTNnYtasWWhpacGSJUswceJEjD/3bPzz4/+079lPEnFXZbsRZPLR2TjpOG024elJO7s/Avsb4rq46hCqVjiePaCN4JZ+3mCjizmnsEhedhpqk8suJ1odJxvI+i0bi9CRFiWKF2Lv7y2IFRL1S+r6rNMm9o9Jq1yQsKjKrT0iBI+I0BF1M2Uc91amd9NnSRGEdLfmsiuR8G4IGGMWzk9AvxQ7udRmPzHhnZ1ipaFOOuqZ/nq1LeiFxMhGO6eeN9w24d27kq7UEjGPaDTJgWnFRmDIu2oUWj6ttPdXrisfb4fA6rywFodcgiMBUduUmISbRRVXni+ur92YMiUx0YgXSMYRlqstRvK+UwhXHx+qn94BKRhsl8lHZ5tGdQTVp7FiJuSPGbuMmwo79u3YfnsW1ibhcBhvv/025pw/GwDw2Y6t2LF6B4YNG4Ynn3wSWVlZ2LhxIwKBAKZOnYrZs2fj5Zdfxpw5c/Dzn/8ckiShtbUV5eXlOHz4MHbs2AEAqK+vT1jOLVu2YNu2bcjNzcXPfvYzzJw5E08//TTq6+sxceJEfOMb30Bamn3gHOYVT/i3m/CSEzgxbQ8kUHcyTgY6TSiI0zjEdA/yE0ShE1JdkM3hwx2iKfUczdKNPWa2yU41aRzYNzrGgWbY3S8N7n5pmkDtZLC1rJe47zY5rWZUMxRnac1k8pKietyIyqXxiWPy0ekCmVVhzM/WGbeMsaEW4O6XhjZUG/yWOkazodbZq3tFDPj52V1i39qpMOcRO5Oh/x0TYgZSs9bTNzoPvtF5kJqCpnSRdq1LLjW1Y/LdAeLaUOvTdWUETPO9khBY0yb0h+BzwVfUp3330pt8RF6EK98o/Kt5M58LaAw63lhovJHTjsgeMTcF3N9xidwzKB3515fCMzgDR/bs1o5XPXw/Ql9/CSC6EsG8Yru6IvV6X9lo9P/Zz2IT6Bp9W1sbysrKACga6u8t+R4+fOs9TCgbh2HDlPFzzZo12LZtG1588UUAQENDA/bu3YsJEyZgyZIlCIVCmD9/PsrKynD66afjq6++ws0334yLL74Ys2fPTlje888/H7m5udq9Xn/9ddx///0AAL/fjwMHDqCwsND2end+KoKHmhJXTEdx4vRMU0J2aUk6DAnUnUTWxaej+aNDzhJrJh8dkzD6/Xg8eFs7bbFUkw8Ls4K+N5aBeQS0bIw43u9kDUSs27z2axjjRlWzw8ngZmV7GLccSdwfOmE5ThuwDdWtXWLxYvSHdAOdd1gW0qcMRPP6I8kV1ClWHs7MExeT1qjvTWUIHW9N7jYWGuqMGUPgPTMbXquAGonQbKiNh8WM7raFKJbBv5/WJfmKaW7AHMVMNGqotb/N31Lkd+4VI1D/5lfw76pN7ttMEsugaqK9lw89BleUXU0SfT0TGFJLYv1HO8Zs0nZ9acy+BS1ppgfhY63RsNwW5N9Qiqq/bLUoaOTf9gjjUEylxHQ3Dt6vjJsdDX5i/P5PgiZTd0vVhlqFh5X6TU2NrmZxzvHII49gzpw5MVl9+OGHeOutt7B48WL86Ec/wne/+11s3boV//rXv/D444/j+eefx9NPPw2XywVZVvL2+/2GPPTaZ845XnrpJYwYMQLJYnZVelKwiVXR3SCBupPImDYo1l+0HXIcATKJ9mI58DnFaiksQjxfoh0jYvPRics2mieSDthQx8tXydxBnjoPFo7K4HagobY7145JBBOVEOiJBGpXv1RknGvvXcIWBxpq77AsuPqlIvP8oQCUqHOewUm2NQuBmgmsfcI0oNvM1M1VHycZWwHVZW3y4crzIe+qUTj8s3WdXJA4p9yCIhiKzNGkuTsJ1J7TMiyDYLQHc1uO923kLhyB5vVH4vb5tp6otL43+TICJ8ZUKv+W27T7qNrWpPucCImuZwJThgqHiqE5c+bgsccew8yZM+F2u7Fnzx4MGjQI1dXVGDx4ML7//e8jEAhgy5YtuOiii+DxePCtb30LI0aMwHe+8x0AQEFBATZv3oyJEydqmm67ez3yyCN45JFHwBjDZ599hjFjxiQsY3vrygpXH582sUgaB2ay3QESqE8COZcPR9P7B+EdZtVRnaAGo2mF46TpoqLEus3rwP3aY8fX3o8yzmWpZfkIV7fFdXVmyErVPscb+O1MUzS7cauH5pZ/JqLPtcUI7G9AVkTYTRaropiFMCHFhf7LxrUrf+0+ZoG6o5tq1fy6ueajO5A6pi9aPztuOBYT3dRCk52SyHVhUih5ypAhmJYV8peWoHVrFZhHdGTSdCIF6kTl0bvs7DDJBN/I8Dja4O4dngPuN66GdpUNtWdoJtwD7W17HWFRNjE3RXGV11XE7Zcj6NrBtddei4qKCowdOxacc+Tn5+PVV1/F2rVrcd9998HtdiM9PR3PPPMMDh8+jGuuuUbTRv/+978HANx2221YuHAhnnzySVx88cW2t/3lL3+JW2+9FSUlJZBlGcOGDcObb77Z8WdOAsFkYsVcAphb0PYMxKUjq9gnEBKoTwKu3BTkfOss7Xfq2L5o3XI8zhWdj7tfGkJHWmIauR7VtRvzdiC4h2XG1iYfVoNO2tn9IWbG+eBswovHoys2dDFRSMrzimryYenWKrIZxDZcsdOBLImBzluQiZQzs51fEHOvSHCV6UMgNQcROtwco710iquPD+FqGz/i5kAJHXyXvJPMr04FchYMR87lw40HzfVmErAH3XNOl0zMZcYhmJqCu38asmx86uvJmDkErpyUjgUt6s50wWJLvpVHk06woQZiTT36Xl/aofxMuWt/ianuxNH74iDmeOP3N5G2z2WO5mZTlEGB4bzJ0zBzzqzoIUHAPffcg3vuuceQ9Oqrr8bVV18dk/2WLVtijo0cORLbtm3Tft99990AgMWLF2Px4sXacZ/Pp3kR6S4wxuDu53DiJApASO72/TQJ1N2A3IUjwFwCWj49esIU1NmXnYnUsX3h6mO/Uz1j2mAIHhFpE2w8WySL6gAgiY8i57Kz4p5XhcC0SQMS5tX3pjL4v6x3fO+uxBA10IT39CzF9tSm845r5qJXUCcz0HW0o4qs5Ak+F7IuKEDTusNx7TLjkf+DEoSOtqB6+Q6knW1se9mXnYmGf+6H4HNF6qhjxVa1I77i9m0AO5Vw4tM4JphPZw+AnZBd1uyCjmfSjTlRfoJThufAV9wHWR3dpN4VqHXQiW5hxbT4+yq0tm4RHZEJDO5BDgIVEZa4cryQA66T4uY3GUigPkURPCJSzsqJm4a5BKRPbV9wBSvSpw5C84eHbN3mtWewFLO8GHyvs81ZydrsZl00DK4+PsitYbRtrYKrE23+hDj+X3MXjUTwYJP9xjiHGurUUucbmzos+JhMiDLOaX+7ETM8EDM8GPS7qTGTCu9pmeh7XSlkfxhtO2qcRdOLgyvLi4F3Te78VZgeRr9bx1r6Y+57yxiEq+JvHO2zpAjVT+/oqqJZ0iYGkBFOTRj8xT2gg6YDhC3MLSDvSnsvEc7pfL97gluAKy8FzHsCzXoiKx52fQkFRGk/TBQgpnZvYRoggbrboNrzCb14YM+6sABZFxTECG85889E/ZtfOV/+OUHoN+elFOYqm0A7CeYWkX3ZmZaTGsEjGoK9mEkZnoPWLcctQ8arm4vyvjvKMu+MGUPQ9nm19jv3ykK0batqxxMYST9nEAL7G5A61iL6ZzuJ595QSHHFj4aZBPHMnk4VrNoSoPj1TTRpSRmeg/TzBqP5g0PRcN5dTJiFE06kB/x0ouIWrhshdGIfYsY9IA2hypYuy7+noUbCPGH384hw2wUkIk4JWFLLwslkzNgQAM8A6AdlCvok5/xPjLFcAKsBFACoALCQc17HlOnbnwBcBKAVwGLOeazRkI7x48dzNUpQT4eHJLR8ehRpkwfSB9lDaN1eBXB0zMVVAgJfN0LM8MCVa/QAILeGbP0ky0EJQm+1DyW6JVzm4EGpyycnB1/fBra+AbXuRpT81n4TllPCtX4wkTnbGNVBQsdaIKS52x3UKBGyPwy5JZRUwJnuwMe/fRmDW/LhH+fFmQsmdji/Xbt2xfWvTBBOsWpLjLHNnPPxVum7UoceBvBjzvkoAJMA3MgYGwXgTgDvcs7PAvBu5DcAXAjgrMh/SwE81oVl63Ywt4j0qYNImO5BpBbnd6kwDSgur8zCNIC4QUdImCZONExgPVLT78pNOSHCNKBsBO8qYRpQVlp6mjBtgIY+oofTZQI157xS1TBzzpsA7AIwCMA8AH+LJPsbgPmRv+cBeIYrfAwgmzGWeKcZQRAEcUrBWTeId010EvQuid7BCVEpMMYKAIwB8AmAfpzzysipo1BMQgBF2D6ou+xQ5FglCIIgCIK0mL2XXvJua2pqMGuW4h7v6NGjEEUR+fnKSuann34Kj6f7RGFdu3YtPB4PpkyZcrKL0ivocoGaMZYO4CUAt3LOG/U7XTnnnLHkVA2MsaVQTEJw2mmndWZRCYIgCII4gXQ05Hh3Iy8vTws7ftdddyE9PR233XbbSStPOByGy2Ut6q1duxbp6elJCdTx8jvV6VI/JIwxNxRheiXn/OXI4WOqKUfkXzWiyWEAQ3SXD44cM8A5f5JzPp5zPl6d9REEQRCnDpzMBIgexObNm3Heeedh3LhxmDNnDiorlYX36dOnY9myZRg/fjwKCwuxceNGfPOb38RZZ52FX/ziFwCAiooKjBw5EldeeSUKCwtx+eWXo7W1NWG+t956K8aPH48//elPeOONN3D22WdjzJgx+MY3voFjx46hoqICjz/+OB588EGUlZXho48+wuLFiw0hzNPTFQ8/a9euxbRp0zB37lyMGjUKkiTh9ttvx4QJE1BSUtLtgsacLLpMoI547VgOYBfn/AHdqdcBqGGArgbwmu74d5nCJAANOtMQgiAI4hSHBOleTC/TVKtwznHzzTfjxRdfxObNm7FkyRL8/Oc/1857PB5s2rQJ1113HebNm4dHH30UO3bswIoVK1BTUwMA+OKLL3DDDTdg165dyMzMxF/+8heEQqG4+QaDQWzatAk//vGPcc455+Djjz/GZ599hm9/+9v4wx/+gIKCAlx33XVYtmwZysvLMW1afDeUW7ZswZ/+9Cfs2bMHy5cvR1ZWFjZu3IiNGzfiqaeewv79+7umAnsQXam3nwrgKgDbGWPlkWM/A3AvgOcZY98D8DWAhZFz/4TiMu9LKG7zrunCshEEQRAEcdLpuknSR8/vQfXB5sQJk6DPkHRMWzjccfpAIIAdO3bg/PPPBwBIkoQBA6L+FubOnQsAKC4uxujRo7Vzp59+Og4ePIjs7GwMGTIEU6dOBQB85zvfwcMPP4wLLrggbr5XXHGF9vehQ4dwxRVXoLKyEsFgEMOGJR/dcuLEidp1a9aswbZt2zRtdkNDA/bu3duufHsTXSZQc87XwX7OOct8gCsOsW/sqvIQBEEQPZxeqsUkgN76cjnnGD16NDZs2GB53utV3DYKgqD9rf4Oh8MAYqMsMsYS5puWFg3WdPPNN+NHP/oR5s6di7Vr1+Kuu+6yvMblckGWZQCALMsIBoOW+XHO8cgjj2DOnDl2j31KQpblBEEQRI+ATD56H135RpPRJHcVXq8XVVVV2LBhAyZPnoxQKIQ9e/Zg9OjRjvM4cOCAdv2zzz6Lc845ByNGjHCcb0NDAwYNGgQA+Nvf/qYdz8jIQGNjo/a7oKAAmzdvxsKFC/H6668jFApZlmfOnDl47LHHMHPmTLjdbuzZsweDBg0yCN2nIt0/ODpBEARBAOitWkwCvfbVCoKAF198EXfccQdKS0tRVlaG9evXJ5XHiBEj8Oijj6KwsBB1dXW4/vrr4fF4HOd71113YcGCBRg3bhz69OmjHb/00kvxyiuvaJsSv//97+ODDz5AaWkpNmzYYCsgX3vttRg1ahTGjh2LoqIi/OAHP9C06acyXRZ6/ETQm0KPEwRBEPGpeLMcrnVNqPbUo+x/Lj3ZxSE6gfV3v4jTmvvBf3YKzrxsQofz622hxysqKnDJJZdgx44dJ7sopxzdKfQ4QRAEQXQevVSLSRBEz4cEaoIgCKJn0HMXVAkbKIx8fAoKCkg73UMggZogCILoGZCGuvdC75bo4ZBATRAEQfQoSKvZe6A3SfQWSKAmCIIgCOKkQi4RiZ4OCdQEQRBEj4CErt4IvVOid0ACNUEQBNGjYJwMbonuSU1NDcrKylBWVob+/ftj0KBBKCsrQ3Z2NkaNGnWyi9elTJ8+HaeyK2MSqAmCIIieAcnRvY7epp/Oy8tDeXk5ysvLcd1112HZsmXab0Fov8hFgVO6PyRQEwRBED2C3iZ8EacWkiTh+9//PkaPHo3Zs2ejra0NALBv3z5ccMEFGDduHKZNm4bdu3cDABYvXozrrrsOZ599Nn7yk59g8eLFuP766zFp0iScfvrpWLt2LZYsWYLCwkIsXrxYu8+qVatQXFyMoqIi3HHHHdrxd955B2PHjkVpaSlmzZoFAKitrcX8+fNRUlKCSZMmYdu2bQCU6Ir333+/dm1RUREqKipQUVGBkSNH4sorr0RhYSEuv/xytLa2xjzrmjVrMHnyZIwdOxYLFixAc3Nzp9dnd4MEaoIgCIIgTg6qx5ZTYPVh7969uPHGG/H5558jOzsbL730EgBg6dKleOSRR7B582bcf//9uOGGG7RrDh06hPXr1+OBBx4AANTV1WHDhg148MEHMXfuXCxbtgyff/45tm/fjvLychw5cgR33HEH3nvvPZSXl2Pjxo149dVXUVVVhe9///t46aWXsHXrVrzwwgsAgF//+tcYM2YMtm3bhnvuuQff/e53Ez7HF198gRtuuAG7du1CZmYm/vKXvxjOV1dX4+6778Z//vMfbNmyBePHj9fK35txnewCEARBEIQzSEfdW+mKDafvr3gSx7/+qlPz7Dv0dMxYvLRd1w4bNgxlZWUAgHHjxqGiogLNzc1Yv349FixYoKULBALa3wsWLIAoitrvSy+9FIwxFBcXo1+/figuLgYAjB49GhUVFfj6668xffp05OfnAwCuvPJKfPjhhxBFEeeeey6GDRsGAMjNzQUArFu3ThPsZ86ciZqaGjQ2NsZ9jiFDhmDq1KkAgO985zt4+OGHcdttt2nnP/74Y+zcuVNLEwwGMXny5OQrrIdBAjVBEARBECeZ3q+i9nq92t+iKKKtrQ2yLCM7Oxvl5eWW16SlpVnmIQiCIT9BEBAOh+F2uzulrC6XC7Isa7/9fr/2N2PGd2X+zTnH+eefj1WrVnVKWXoKJFATBEEQPQoK7NL76AoNdXs1ySeSzMxMDBs2DC+88AIWLFgAzjm2bduG0tLSduU3ceJE3HLLLaiurkZOTg5WrVqFm2++GZMmTcINN9yA/fv3Y9iwYaitrUVubi6mTZuGlStX4pe//CXWrl2LPn36IDMzEwUFBXjzzTcBAFu2bMH+/fu1exw4cAAbNmzA5MmT8eyzz+Kcc84xlGHSpEm48cYb8eWXX+LMM89ES0sLDh8+jOHDh7e/onoAZENNEARB9Ax6vxKTOAVZuXIlli9fjtLSUowePRqvvfZau/MaMGAA7r33XsyYMQOlpaUYN24c5s2bh/z8fDz55JP45je/idLSUlxxxRUAlM2HmzdvRklJCe6880787W9/AwB861vfQm1tLUaPHo0///nPBmF4xIgRePTRR1FYWIi6ujpcf/31hjLk5+djxYoVWLRoEUpKSjB58mRto2VvhnHec2f648eP56eyz0OCIIhTiX1vb4H3gxZUeesw5jdzT3ZxiE7go3tWY1jjQLRM9mDEvLM7nN+uXbtQWFjYCSUjrKioqMAll1yCHTt2nOyidDlWbYkxtplzPt4qPWmoCYIgCII4udDqA9HDIYGaIAiC6Bn04BVVgugNFBQUnBLa6fZAAjVBEATRI1AjjlPocYIguhskUBMEQRAEcVLpCi8fBHEiIYGaIAiCIAiCIDoACdQEQRBEj4D8TxME0V0hgZogCIIgiJNKbzH5mDFjBv71r38Zjj300EMxvppVCgoKUF1djfr6evzlL385EUUkuggSqAmCIAiCIDqBRYsW4bnnnjMce+6557Bo0aK415FA3fMhgZogCILoUZDpRy8i4rGlt7zRyy+/HG+99RaCwSAAJRDKkSNHcPjwYRQXF6OoqAh33HFHzHV33nkn9u3bh7KyMtx+++1obm7GrFmzMHbsWBQXFxuiJ/72t7/FiBEjcM4552DRokW4//77AQD79u3DBRdcgHHjxmHatGmnRHTC7oTrZBeAIAiCIIhTnF7iCTE3NxcTJ07E22+/jXnz5uG5557DN77xDdxxxx3YvHkzcnJyMHv2bLz66quYP3++dt29996LHTt2oLy8HAAQDofxyiuvIDMzE9XV1Zg0aRLmzp2LTZs24aWXXsLWrVsRCoUwduxYjBs3DgCwdOlSPP744zjrrLPwySef4IYbbsB77713Emrh1IQEaoIgCKJH0FvsbIkTQ/0b+xA80tKpeXoGpiH70jPiplHNPlSB+rLLLsP06dORn58PALjyyivx4YcfGgRqM5xz/OxnP8OHH34IQRBw+PBhHDt2DP/9738xb948pKSkICUlBZdeeikAoLm5GevXr8eCBQu0PAKBQMcfmHAMCdQEQRAEQRCdxLx587Bs2TJs2bIFra2tKCsrw759+5LKY+XKlaiqqsLmzZvhdrtRUFAAv99vm16WZWRnZ2sabuLEQwI1QRAE0SMg/XRvpvPfbiJNcleRnp6OGTNmYMmSJVi0aBEmTpyIW265BdXV1cjJycGqVatw8803G67JyMhAU1OT9ruhoQF9+/aF2+3G+++/j6+//hoAMHXqVPzgBz/AT3/6U4TDYbz55ptYunQpMjMzMWzYMLzwwgtYsGABOOfYtm0bSktLT+izn8rQpkSCIAiiZ0Chx4kewqJFi7B161YsWrQIAwYMwL333osZM2agtLQU48aNw7x58wzp8/LyMHXqVBQVFeH222/HlVdeiU2bNqG4uBjPPPMMRo4cCQCYMGEC5s6di5KSElx44YUoLi5GVlYWAEWrvXz5cpSWlmL06NGGjYxE10MaaoIgCKKHQDrq3kpve7Pz588H59GnWrRokaXrvIqKCu3vZ5991nBuw4YNlnnfdtttuOuuu9Da2opzzz1X25Q4bNgwvPPOO51QeqI9kEBNEARBEMTJhRYdHLN06VLs3LkTfr8fV199NcaOHXuyi0SABGqCIAiih9DbtJhEFPLg4hyzJpvoHpANNUEQBNGjoMAuBEF0N0igJgiCIAiCIIgOQAI1QRAEQRAnFTL5IHo6JFATBEEQPQIy9SAIortCAjVBEATRMyB5mujmzJgxA//6178Mxx566CFcf/31ttcUFBSgurq6q4umMX36dIwYMQJlZWUoKyvDiy++CEAJSNOZFBQUoLi4GCUlJTjvvPO04DR2VFRUONpwWVFRAZ/Ph7KyMowaNQrf/e53EQqFAABr164FYwz/93//p6UvLy8HYwz3338/AODjjz/G2WefjbKyMhQWFuKuu+5q/0PqIIGaIAiC6BmQazWim7No0SI899xzhmPPPfecpQ/qk8nKlStRXl6O8vJyXH755V12n/fffx/btm3D9OnTcffdd8dN61SgBoAzzjgD5eXl2L59Ow4dOoTnn39eO1dUVGT4vWrVKkPEyKuvvhpPPvkkysvLsWPHDixcuDDJp7KGBGqCIAiiR0B2tr2X3vJmL7/8crz11lsIBoMAFCHxyJEjmDZtGlatWoXi4mIUFRXhjjvuiLm2oqICRUVF2u/7779f055Onz4dy5Ytw/jx41FYWIiNGzfim9/8Js466yz84he/0K75xz/+gYkTJ6KsrAw/+MEPIElS0s/AOcftt9+OoqIiFBcXY/Xq1QCAG2+8Ea+//joA4LLLLsOSJUsAAE8//TR+/vOfx81z8uTJOHz4sPac06ZNw9ixYzF27FisX78eAHDnnXfio48+QllZGR588EFIkoTbb78dEyZMQElJCZ544omYfEVRxMSJE7W8AWDo0KHw+/04duwYOOd45513cOGFF2rnjx8/jgEDBmjXjxo1Kuk6soIEaoIgCIIgTi69ZPUhNzcXEydOxNtvvw1A0U4vXLgQlZWVuOOOO/Dee++hvLwcGzduxKuvvppU3h6PB5s2bcJ1112HefPm4dFHH8WOHTuwYsUK1NTUYNeuXVi9ejX++9//ory8HKIoYuXKlZZ5XXnllZrJR01NjeHcyy+/jPLycmzduhX/+c9/cPvtt6OyshLTpk3DRx99BAA4fPgwdu7cCQD46KOPcO6558Yt+zvvvIP58+cDAPr27Yt///vf2LJlC1avXo1bbrkFAHDvvfdi2rRpKC8vx7Jly7B8+XJkZWVh48aN2LhxI5566ins37/fkK/f78cnn3yCCy64wHD88ssvxwsvvID169dj7Nix8Hq92rlly5ZhxIgRuOyyy/DEE0/A7/cnqHlnUGAXgiAIokfAe4sak7Cg81/u22+/jaNHj3Zqnv379zdoO61QzT7mzZuH5557DsuXL8fGjRsxffp05OfnA1AE2g8//FATMp0wd+5cAEBxcTFGjx6taVlPP/10HDx4EOvWrcPmzZsxYcIEAEBbWxv69u1rmdfKlSsxfvx4y3Pr1q3DokWLIIoi+vXrh/POOw8bN27EtGnT8NBDD2Hnzp0YNWoU6urqUFlZiQ0bNuDhhx+2zGvGjBmora1Feno6fvvb3wIAQqEQbrrpJk3o37Nnj+W1a9aswbZt2zQb74aGBuzduxfDhw/Hvn37UFZWhv379+Piiy9GSUmJ4dqFCxfiiiuuwO7du7Fo0SJNCw4Av/rVr3DllVdizZo1ePbZZ7Fq1SqsXbvWsgzJ0GUaasbY04yx44yxHbpjdzHGDjPGyiP/XaQ791PG2JeMsS8YY3O6qlwEQRBEDyWixWS8l6gzCY3eNFeaN28e3n33XWzZsgWtra0YN26co+tcLhdkWdZ+mzWnqpZVEASDxlUQBITDYXDOcfXVV2u20V988UWnbbgDgEGDBqG+vh7vvPMOzj33XEybNg3PP/880tPTkZGRYXnN+++/j6+//hplZWX49a9/DQB48MEH0a9fP2zduhWbNm3SzGPMcM7xyCOPaM+zf/9+zJ49G0DUhnrfvn3YvHmzZoqi0r9/f7jdbvz73//GrFmzYvI+44wzcP311+Pdd9/F1q1bY7T07aErNdQrAPwZwDOm4w9yzu/XH2CMjQLwbQCjAQwE8B/G2HDOefLGPwRBEEQvpTeJXURXk0iT3FWkp6djxowZWLJkibYZceLEibjllltQXV2NnJwcrFq1CjfffLPhun79+uH48eOoqalBeno63nzzzRhThnjMmjUL8+bNw7Jly9C3b1/U1taiqakJQ4cOTar806ZNwxNPPIGrr74atbW1+PDDD3HfffcBACZNmoSHHnoI7733HmpqanD55Zcn3NTocrnw0EMPobi4GL/4xS/Q0NCAwYMHQxAE/O1vf9PsvDMyMtDU1KRdN2fOHDz22GOYOXMm3G439uzZg0GDBhny7tOnD+699178/ve/1zT4Kv/zP/+D48ePQxRFw/G33noLF110ERhj2Lt3L0RRRHZ2dlJ1ZPmcHc7BBs75h4yxAofJ5wF4jnMeALCfMfYlgIkANnRV+QiCIIieCfmjJro7ixYtwmWXXaZ5/BgwYADuvfdezJgxA5xzXHzxxZg3b57hGrfbjV/96leYOHEiBg0ahJEjRyZ1z1GjRuHuu+/G7NmzIcsy3G43Hn300aQF6ssuuwwbNmxAaWkpGGP4wx/+gP79+wNQhO01a9bgzDPPxNChQ1FbW4tp06YlzHPAgAFYtGgRHn30Udxwww341re+hWeeeQYXXHAB0tLSAAAlJSUQRRGlpaVYvHgxfvjDH6KiogJjx44F5xz5+fmWdufz58/HXXfdpdl3q0yZMsWyLH//+9+xbNkypKamwuVyYeXKlTFCd3tgvAuN0iIC9Zuc86LI77sALAbQCGATgB9zzusYY38G8DHn/B+RdMsBvM05fzFe/uPHj+ebNm3qsvITBEEQ3Ycd/96A7HfDqPLWYcxv5ia+gOj2fPS75zGsaQCqp3GUXRx/Y5sTdu3ahcLCwk4oGXGqY9WWGGObOeeWxucn2svHYwDOAFAGoBLAH5PNgDG2lDG2iTG2qaqqqpOLRxAEQRAEQRDJcUIFas75Mc65xDmXATwFxawDAA4DGKJLOjhyzCqPJznn4znn49XdsgRBEARBEARxsjihAjVjbIDu52UAVA8grwP4NmPMyxgbBuAsAJ+eyLIRBEEQBHGSIMctRA+nyzYlMsZWAZgOoA9j7BCAXwOYzhgrg7JVuwLADwCAc/45Y+x5ADsBhAHcSB4+CIIgCD0UKbH30pX7uQjiRNCVXj6sAtcvj5P+dwB+11XlIQiCIHo2JHL1YkhDTfRwKPQ4QRAEQRAEQXQAEqgJgiCIHgLpqHsrZM7T+UyfPh3kWvjEQQI1QRAE0aOg0OMEQXQ3SKAmCIIgegQUIbH3oU6NetubnT9/PsaNG4fRo0fjySefBKCEJP/5z3+O0tJSTJo0CceOHQMAVFRUYObMmSgpKcGsWbNw4MABAMDixYtx/fXXY9KkSTj99NOxdu1aLFmyBIWFhVi8eLF2r+uvvx7jx4/H6NGj8etf/zqmLE8//TRuvfVW7fdTTz2FZcuWdd3Dn6KQQE0QBEH0KEiwJro7Tz/9NDZv3oxNmzbh4YcfRk1NDVpaWjBp0iRs3boV5557Lp566ikAwM0334yrr74a27Ztw5VXXolbbrlFy6eurg4bNmzAgw8+iLlz52LZsmX4/PPPsX37dpSXlwMAfve732HTpk3Ytm0bPvjgA2zbts1QloULF+KNN95AKBQCAPz1r3/FkiVLTkxFnEJ0mZcPgiAIgiAIJ3SFDfWePb9FU/OuTs0zI70Qw4f/MmG6hx9+GK+88goA4ODBg9i7dy88Hg8uueQSAMC4cePw73//GwCwYcMGvPzyywCAq666Cj/5yU+0fC699FIwxlBcXIx+/fqhuLgYADB69GhUVFSgrKwMzz//PJ588kmEw2FUVlZi586dKCkp0fJIT0/HzJkz8eabb6KwsBChUEjLh+g8SKAmCIIgCOLk0ovM4teuXYv//Oc/2LBhA1JTUzF9+nT4/X643W4wpjyoKIoIh8MJ8/J6vQAAQRC0v9Xf4XAY+/fvx/3334+NGzciJycHixcvht/vj8nn2muvxT333IORI0fimmuu6aQnJfQ4FqgZY6mc89auLAxBEARB2EGGHr2YLni5TjTJXUFDQwNycnKQmpqK3bt34+OPP46bfsqUKXjuuedw1VVXYeXKlZg2bZrjezU2NiItLQ1ZWVk4duwY3n77bUyfPj0m3dlnn42DBw9iy5YtMSYhROeQUKBmjE0B8H8A0gGcxhgrBfADzvkNXV04giAIgiBOAXqRhvqCCy7A448/jsLCQowYMQKTJk2Km/6RRx7BNddcg/vuuw/5+fn461//6vhepaWlGDNmDEaOHIkhQ4Zg6tSptmkXLlyI8vJy5OTkOM6fcA5LFO6TMfYJgMsBvM45HxM5toNzXnQCyheX8ePHc/KxSBAEcWrw2X8+Qv5/gCpvHcb8Zu7JLg7RCaz73fMoaBqAyvNCmHDhzA7nt2vXLhQWFnZCyXofl1xyCZYtW4ZZs2ad7KL0CKzaEmNsM+d8vFV6R14+OOcHTYek9hWPIAiCIAiCOFHU19dj+PDh8Pl8JEx3IU5sqA9GzD44Y8wN4IcAOnfbLEEQBEEQBNHpZGdnY8+ePSe7GL0eJxrq6wDcCGAQgMMAyiK/CYIgCOKEQeGpCYLoriTUUHPOqwFceQLKQhAEQRD29KKNa4QRmiwRPR0nXj7+CguHNpxzCrNDEARBEARBnPI4saF+U/d3CoDLABzpmuIQBEEQBHGqQRpqoqeT0Iaac/6S7r+VABYCsHQZQhAEQRBdBQldvRfey815Fi9ejBdffPFkF8MxF110Eerr6+OmWbFiBY4cIf2qiiO3eSbOAtC3swtCEARBEARBnHz++c9/Ijs7O24aEqiNJBSoGWNNjLFG9V8AbwC4o+uLRhAEQRBRSD/di+llL/eZZ55BSUkJSktLcdVVVwEAPvzwQ0yZMgWnn366pq1ubm7GrFmzMHbsWBQXF+O1114DAFRUVKCwsBDf//73MXr0aMyePRttbW0AgI0bN6KkpARlZWW4/fbbUVSkxNmTJAm33347JkyYgJKSEjzxxBMAgLVr1+Lcc8/FxRdfjBEjRuC6666DLMsAgFWrVqG4uBhFRUW4446oaFdQUIDq6mrbcrz44ovYtGkTrrzySpSVlWllO5VxYvKRwTnP1P07nHP+0okoHEEQBEEQRE/i888/x91334333nsPW7duxZ/+9CcAQGVlJdatW4c333wTd955JwAgJSUFr7zyCrZs2YL3338fP/7xj6FGsN67dy9uvPFGfP7558jOzsZLLymi1zXXXIMnnngC5eXlEEVRu+/y5cuRlZWFjRs3YuPGjXjqqaewf/9+AMCnn36KRx55BDt37sS+ffvw8ssv48iRI7jjjjvw3nvvoby8HBs3bsSrr74a8zxW5bj88ssxfvx4rFy5EuXl5fD5fF1ZpT0C202JjLGx8S7knG/p/OIQBEEQhDVkQ9174azz3+0v9x7CjubO1ZwWpfvw27MGx03z3nvvYcGCBejTpw8AIDc3FwAwf/58CIKAUaNG4dixYwAAzjl+9rOf4cMPP4QgCDh8+LB2btiwYSgrKwMAjBs3DhUVFaivr0dTUxMmT54MAPh//+//4c03Fd8Ra9aswbZt2zTtd0NDA/bu3QuPx4OJEyfi9NNPBwAsWrQI69atg9vtxvTp05Gfnw8AuPLKK/Hhhx9i/vz5huexKgcRSzwvH3+Mc44DmNnJZSEIgiAIguiVeL1e7W9VC71y5UpUVVVh8+bNcLvdKCgogN/vj0kvimJCswrOOR555BHMmTPHcHzt2rVgzLjr0/zbabmdlONUxVag5pzPOJEFIQiCIIh4kIa6N9P57zaRJrmrmDlzJi677DL86Ec/Ql5eHmpra23TNjQ0oG/fvnC73Xj//ffx9ddfx807OzsbGRkZ+OSTT3D22Wfjueee087NmTMHjz32GGbOnAm32409e/Zg0KBBABSTj/3792Po0KFYvXo1li5diokTJ+KWW25BdXU1cnJysGrVKtx8882OnzMjIwNNTU2O0/d2nPihBmOsCMAoKH6oAQCc82e6qlAEQRAEQZw69Kap0ujRo/Hzn/8c5513HkRRxJgxY2zTXnnllbj00ktRXFyM8ePHY+TIkQnzX758Ob7//e9DEAScd955yMrKAgBce+21qKiowNixY8E5R35+vmYTPWHCBNx000348ssvMWPGDFx22WUQBAH33nsvZsyYAc45Lr74YsybN8/xcy5evBjXXXcdfD4fNmzYcMrbUTN12cE2AWO/BjAdikD9TwAXAljHOb+8y0uXgPHjx/NNmzad7GIQBEEQJ4BP33sfA9e4UOWtw5jfzD3ZxSE6gXW/ex4FTQNwYHobplwwu8P57dq1C4WFhZ1Qsu5Lc3Mz0tPTAQD33nsvKisrtY2PVqxduxb333+/ZmtNOMOqLTHGNnPOLWOxONFQXw6gFMBnnPNrGGP9APyjwyUlCIIgCIIgkuKtt97C73//e4TDYQwdOhQrVqw42UUi4Eyg9nPOZcZYmDGWCeA4gCFdXC6CIAiCMEA21L0RZXMcvVvnXHHFFbjiiiscp58+fTqmT5/edQUiAMR3m/cogFUAPmWMZQN4CsBmAM0ANpyQ0hEEQRAE0fvp5aHHid5PPA31HgD3ARgIoAWKcH0+gEzO+bYTUDaCIAiCIE4BEu3nSjavZNzCEYSZ9rRH20iJnPM/cc4nAzgXQA2ApwG8A+AyxthZ7S0kQRAEQbQHMgvoxXSS/JuSkoKamppOFdCJUwvOOWpqapCSkpI4sY6ENtSc868B/C+A/2WMjYEiWP8KgBj3QoIgCIIgiBPI4MGDcejQIVRVVZ3sohA9mJSUFAwenJwf84QCNWPMBcVV3rcBzAKwFsBdyRePIAiCINoPaah7L531bt1uN4YNG9YpeRFEMsTblHg+gEUALgLwKYDnACzlnLecoLIRBEEQBEEQRLcnnob6pwCeBfBjznndCSoPQRAEQVjCaZ9Zr4XWHoiejq1AzTmfeSILQhAEQRAEQRA9EVsvHwRBEATRnSAb6t4LvVuip0MCNUEQBEEQBEF0ABKoCYIgCII4yZCGmujZkEBNEARBEMRJhcRpoqdDAjVBEATRIyA7W4IguiskUBMEQRA9AhKoezHkEpHo4ZBATRAEQRDESYUmS0RPhwRqgiAIokdAIhdBEN2VLhOoGWNPM8aOM8Z26I7lMsb+zRjbG/k3J3KcMcYeZox9yRjbxhgb21XlIgiCIAiim0GzJaKH05Ua6hUALjAduxPAu5zzswC8G/kNABcCOCvy31IAj3VhuQiCIIieCCOpq7dCYeWJnk6XCdSc8w8B1JoOzwPwt8jffwMwX3f8Ga7wMYBsxtiAriobQRAEQRDdCZosET2bE21D3Y9zXhn5+yiAfpG/BwE4qEt3KHKMIAiCIAAAnJPQ1VuhN0v0dE7apkSu9IxJf0OMsaWMsU2MsU1VVVVdUDKCIAiCIE4sJFITPZsTLVAfU005Iv8ejxw/DGCILt3gyLEYOOdPcs7Hc87H5+fnd2lhCYIgiG4E2dn2WshtHtHTOdEC9esAro78fTWA13THvxvx9jEJQIPONIQgCIIgCIIgui2ursqYMbYKwHQAfRhjhwD8GsC9AJ5njH0PwNcAFkaS/xPARQC+BNAK4JquKhdBEATRMyEtZu+DFh2I3kKXCdSc80U2p2ZZpOUAbuyqshAEQRA9HxKney/0bomeDkVKJAiCIAiCIIgOQAI1QRAE0SMgk4/eDL1bomdDAjVBEARBECcVEqeJng4J1ARBEESPgDTUvRjanUj0cEigJgiCIAjipEKTJaKnQwI1QRAEQRAEQXQAEqgJgiAIgjipKN5zCaLnQgI1QRAE0SPgjISuXgvZUBM9HBKoCYIgCII4qZANNdHTIYGaIAiC6BGQWQBBEN0VEqgJgiCIngGZBRAE0U0hgZogCILoEZBZQO+F3i3R0yGBmiAIgiAIgiA6AAnUBEEQRI+AdJi9F3q3RE+HBGqCIAiiR0BmAQRBdFdIoCYIgiAI4qRCkyWip0MCNUEQBEEQBEF0ABKoCYIgCII4qZCGmujpkEBNEARB9AhI6CIIortCAjVBEARBEARBdAASqAmCIIgeAWmoey+comASPRwSqAmCIIgeAYnTvRhOb5fo2ZBATRAEQfQQSOjqrdCbJXo6JFATBEEQPQIyC+jNkEhN9GxcJ7sABNGdCQUlcInDnSIq/T0DGKNR3SmSJEOtLVnmcLlFAACXlcGTCSevLmVJhiB2jk5BCssQROaobXDOwRiDLHOwSHviMgeYUi/mMnHOIYVkNNX6kZbthSwpdef2iICgXB9sCyvHvCIEgYEJSv5CpH4DbWF4fb2guz/JZgHqu1P/JToPJ5MlJ/XOOQf4ye1biFOTXtDDnlhCQQkHP6+FKiUwpv4PkEIy3Ckiag41IyXdDU+KC1JIguASEGwLo7G6DSG/BCYy+FtC4BKH4BLgbwlpQkegLawNqi6PCI8vKsgBgBzmaGsOwuURkZrpgSxxhAISUlJdCAYkBFpDCLSGEWwLQxAFeFNdCLSG4ctwI9AaBudKcb0+F7L7pQIAPD4XMvJSEA5KOLa/Ef2GZYIJDKIowOURILoFNNcGlI4KQDgkw+0REQ5JkCUO0SUgHJLhcgtISXMDTKmLcFBCoC0MURTABEB0CQBjaK71w5fhBpeBlHQ3XB4RXOZobQwowkFAQt7ANARawwiHZARaQ6g53Ay314W+QzMgSxxVB5rgbwkhLduLQGsYgdZQzEAXDsnwpCh5+zI9aKkPICXNjbRsL0J+Cc31AaRmuOHyimiuDSAUCCMUkAAA3lQ3AKD2SAuksPJs4ZAMMCAzLwWBtjBcbhEuj4DMvBSk5aSg8st6+NI9yO6firamIBqr/eg3NAPeNDcEkUEOc1QfbkZO/1R4U10QXQKkkCKItTQG4XIp7xwA/M1ByDKH2+uCL8ONUECCHOYI+pV3qb5H0SVAEAWEAhJSszwIByU0VvvR0hCAyyWAc6XNMgY0VLUhNdMDj88FLnPUH2uF2+uC26vcN9CqtFFZ5vD6XHB7RaU+GOByi0odCwyiS0B6jhdtTSG0NQXBGIPLK8DlFtFSH4DgYoogxxj8zaGIoKm0CdEjQhSV9yPLHAxAOCzD7VXaeUZeCmSJo60pCHeKC54UEek5KXB7RdQfa0VKmgsuT1RoFN0CwkEJUlhph4HWELw+F1obg0hJd0MKK0KrIDI01wUAKG0u0BJC1YEmDDgzGx6fCy31AaRleyGFpMh3zZDTPw0cHI3VfggiQ8gfhjfNjdQMpZ4DrWFUHWyCyyOi9kgLMvJSEApI4DKHFJYhugVwiUN0C3B7RQQi32SgOQQmMnCJQ5Y50nO8aG0IQhAZJIkjI9cLWeYItknwZbjR1hhE0C8576QYlO++JQxvqgvBNuW77396lnK/bC9SszyQZY7qA03wZXiQmZeCoF+CyyMg6Fe+65Q0FwRB6at8mR7UH20FExlcLgFunwtSUFK+CQCCwBAKyvD6RHhT3ag71gq3V+mjXB5Bew+q8B/0K2Xy+lyQJFlpNyJDyC8hFJDQryAToYCEplo/QkEZ4BwpaW4Eq7IBAfD5M/H3X6xHKCAhHJThTXXBm+aGFJIhhWXIYWWypLZFzoGUNBdCAaU/EUSGYJsEl1fps2SJIxyUlL9ljobjbUjN8sDrc6GtKYRAWxjhkAQuA+AcnCuTF2+aC26vC+BKX+6KtMf0nBR4fC7UH2tFVl8fwIHmOuVZ3B4BuQPSkNU3FWlZHkgSR8gvoa0pCG+qG5IUqVORKd+MWwBjkW8oLCM9JwWyJCPQGo5Mvji4rExewwEJ7hTl+3Z5RHh9IkJBGYwBLfUBhEMysvJ9Wr/s8bkgCEDQL2ljjwrnyjWcc4SDMjjn8DeH4PKIaG0IaH1Veo4XUkhG0B9G0C9BEBjSc1PQUq98b+4UEYGWMMTI+BAOSuAcaGsKIugPoyiQCzAguCELL5dvRmtDEMGAhPwh6Qi0hlFb2YLUTA9El4CmGj/cXqXfDbZJkGWu9fmpmR5l/IvcK3dgGsJBCWBKG+hXkKnUaVhGa2MQGblKXyO6BaWv9Sj9lyTJShv3inCniHB5xMj34EZzfQCeFCVdsC2MlAwPPClKPbQ2BgEOuNwC0nK8SruA0u5aG4MIBSS43CIEFzMo47lpkqj95LpNuKZ5pP4afXo1oXneyXn0YDgyOQcHRLeAlnrlXUohSZmISxyCyJCS7kZdZSu8qS7t+9DGVK60T9EloK05hJA/jLQsr9JWQjLSs71Iz1H6w/zTMiCITBt3ZFnJy9+iTPJbm4II+SWkZXsgCEof7o7UKWMMgsjQWNUG0a0bH1tCmPKtMxWlQjeCmV9mT2L8+PF806ZNJ/SeTbV+PPOz9R3Ox+WJCJ9QBngAkMIcqRlKh85lrg1selQBzJvmRmtDQOvEW+oDkCWOPoPT4U11wZPqQrBV6eC8qS74m0Pwprk1Yab+eCv8zSFwDgTbwtrAmCws0jeIoqAMBKbmJAgMPPKvFFbu4U1zIWTxbPFQP2JV4E3P8SIjLwWN1X6kpLnh8ijCY2qmRxNoBFEZSOWwjNamEFIz3GhtDCLYFobH50JqlkebfKRlexUhOiKpclkZNHP6pSI124PWxiDcEcH/+IEmhAMS6o+3IiUiLLc2hZCZl4KmGj/CQQmiW0D+aZmoPtSkCMOSomVMz/HC3xyCFJYNnZ43zQUuQxlsIoMhi9SZFJI14dGbIqKtOaTUHYNW34xFO1FV+M/skwLRJaClIYiUNBfyBqXD3xJS2lVYRlq2Fy6PiHBQEWIEgcHlFeH1ueDyCPA3h9DaGERatjfyDlyQZY5AaxhSSILLKyIzzwcuczTV+eFvDqHPkAwIDAiFZEhBCZl9fNozuH0uyGFZEYJCsjLpExjcKSLcHhFSWEZDVRv8LWFk5HoRDskQXQKa6/wItknIzPch2BaGLCmDKJc5/K1huD0C3F4XQgFFwFAGRwGB1jC8qW6ILqblpU4SOFeEGJdXBDhHaqYHjTV+eFPdEAQgFJRRf7QVUqSevKnKBKOtOQR/UxCiRwRjwIAzshEKSKjcV4/MvBT4MjwIBSRk90uFyyMq9w5IaG1SJn88MnAzMXK8MahM0vr4lDryKkKD4BLgSXGhtVERSjJyUzTtdCigfNNSWAaXlcFVdAlgAkOgVWkb/mblPUthGV6fC7WVLeCcw5vqijyX0n7Sc5QyNdcFlNUXMGUSDyDYJsHfEoLLLUAQlbbhS3dr7Vl0K5Mof0sIgsDgTVMm723NIeT0S4UUltHSENAmFZwrZRUikzJvqhtBv9IG0rK9EeFYybu1KYjUDA+8qS5tkhVsC8NfV41zQj40IICKIflgAkNLfQA5/dMik1wBjCnCriRxyGEZLQ1BuCJCkysyKLc2BpGZl4Lm+gA4V/oXJjCEg1JkYg5NgFUEZzdSUl2QQnJEqHIhJc2NQGtIm3RKYaWM4aAEf2sYIX848g6D2nPUHmlBoDWcVB/baej6C6cIItP66fQcL1IzlfattvNwSFaeMzIB9/hcmvIoJc2tTOzaJG0yFWgNwZfhUd5RiojUDA/67DuCvtyH/wpt8PbpA9GtfDfNdQG4vSJyB6ahrSkELivfaVtzCKKLwZPiUibrgvJ9+/9/e3ceH8d1Hfj+d6r3RjeWxk4sJMHVXEQRphVL1m5TspWRo0QZO87EjpNJHE88y5vJJM+TZPKx814yfnmZPM+Mk9jW2JaTjLzIsrzFtuSJI1MbI8lcRFIkRYIgAYLYt+4Geq2674/qboIkKIECgUZD5/v5SGx0V3edqjp969StW9WJLIGIzz3wms0zOTTjFnEG0kn3ABrcfW8o6icxnsbrt8hnHSyvlL5XwbCv9D3LZezSfmuuYMQHhf2RY7tteTDiHiyI5R4YrliF9sayLh6wAaUDA8sjTI+mcGxDuCbgtoHVfvf5sRTRmLtfMY5bPIciPjw+D1Mjs6UDlcR4isxMHl/IPZh6Pd6Ah3zm6uvMX9h3FOuUQNjL+37/bVQ3hK7DCrk2IvJTY8ye+V7THuprFK72874/eFupYSoekMxOuz1ixjFUFY7Y8zm3wLRth2ChZ8vtpRJCUX/pdOz1UIzjjZyGNI5xe8ktwetze8yLvRzZVN7tFYkFSU6k3S+iR5iNuz1q/oC3dMRtgOxsnlzWdns+Cr1Zxrg97sYxpR2xMabQC5cvxe31WSBu8R0fT7u9Ej4LDIUez1K9+4aXdTlcbVsUC+3i847tYBeKn0hd4KrL49huQV183Rj3gKG4o7MsQTxCLuWe/QiEvGQLO3O1OMYxb+pTx3bePRBZKb6z71H4fohsYJaf/diucodzzRzbPQhyCr29dt7BstzeO3/QQz7rfteLZ/nc95jSkCB/0EtyMo3H6/Yu57MOHp979qu4n8nM5vEVDhqy6bzbtvotovVBsikbO2+7Z3k8UipURYSqWj++uW2GMYWDtDy+oAfPdRoedbln/+Q4JEL47xrjgb33LMk85lNsV4HXHMZj2w44bvHsC3gwuEPXikNLwP2eFHtPi+1zZsbtqMpn3bOHxnGL1cvNPctdelXmvi6XPDd3Grn8SZn7+pWfuVz7zOKZIq/fKp0ZdGw3nyyPlHrA08kcAKGon1ShpzoY8RU6CNz35NLu+lup+/u5dI97jTxei8aO6Bt+v3+JxjEuJtnEcgv8osic0yjFXnSAupaq0uOqmsBlH+J+cYMRH0F8l70kpfl45jRgHo8QiviZT21TeP5YV/536qrbwnvZ6SnLY2F5wBd77dNWl4+pdQ8+PFy2mvFELk6nxfT18WYupoEVVUyvBpbHAg94mP977w9dXN9XO509tx2m6srXi9/94pnP+V4rulr763Jzf+4+YCkZWd6z5fO1q/PxFLeZb57pC2+Z27YX22dv7coajrCcPD6rtL5eqxd5bh1RVROAmssm8FXWvkxbS6WUUhWhkocoKqVWNy2olVJKKVUWUri9hx4qqUqnBbVSSqmKsNzDApRSaqG0oFZKKaVUWRnto1YVTgtqpZRSFUHHUCulViotqJVSSlWGN/dNV1Y17aFWlU4LaqWUUhVBiy6l1EqlBbVSSimlykoPllSl04JaKaWUUkqpRdCCWimllFJlpT3UqtJpQa2UUqoi6F0+lFIrlRbUSimlKoPe5WPV0h5qVem0oFZKKVURikWXll6rkB4sqQqnBbVSSqmKoL2Yq5huWlXhvOWYqYicBRKADeSNMXtEJAZ8DVgHnAXeZ4yZLEd8SimllFo+erCkKl05e6jvMsbcaIzZU/j748A/GGM2Af9Q+FsppZQCLhZdOjpAKbXSrKQhHz8HfLnw+MvAA+ULRSml1EqjfZirlxHduqqylaugNsCTIvJTEflI4blmY8xg4fEQ0Fye0JRSSq1EWnKtPjrUQ60WZRlDDdxqjBkQkSbgRyJyYu6LxhgjMv/haqEA/whAZ2fn0keqlFJqhdDia7XSW4yrSleWHmpjzEDh3xHgceAmYFhEWgEK/45c5b2fN8bsMcbsaWxsXK6QlVJKKaWUmteyF9QiUiUi0eJj4B7gKPAd4FcLk/0q8O3ljk0ppdQKplcjrlo69ENVunIM+WgGHheR4vwfMcb8UEReBL4uIv8SOAe8rwyxKaWUWqH0p8eVUivVshfUxpgzwK55nh8H3rnc8SillFKqvPRgSVW6lXTbPKWUUuqq9KfHlVIrlRbUSimlKoOOoVZKrVBaUCullKoIOixAKbVSaUGtlFKqIuhPj69eepcPVem0oFZKKVURjFbSSqkVSgtqpZRSFUJ7MVctHc6jKpwW1EoppSqCllyrl25bVem0oFZKKVUZtOpafXSbqlVCC2qllFJKlZURraxVZdOCWimlVEXQH3ZRSq1UWlArpZSqDHqXj9VLj5JUhdOCWimlVEXQexWvPrpN1WrhLXcAlWZqaopvf/vb5PN5du7cyfHjxwHo6Oggn89TW1tLPB5HRDh//jy2bdPc3Ex3dzf79u0jlUohcrGbxbZtLMvC6/WSyWSora2ltbWVV199lUgkQnNzM2fPniWfzxMIBDDGkM/nMcawbt06pqammJycpKuri5mZGcbHx9mwYQOnT5/G7/eTTCaJRCKk0+nSfPP5POFwmEwmg4hgjMGyLDZs2MDU1BS1tbWcPn2aLVu20NfXh4jQ3t6OMYaJiQkaGho4efIkAJ2dnSSTScbHx1m7di3xeJyJiQks68pjteK8Wlpa2Lt3L5ZlMTo6yhNPPIHjONTV1VFTU0NzczNTU1OcOHGCLVu2cO7cObxeL83NzfT19bF27VomJydLcWzbto1wOMyhQ4fI5/N4vV42bdrE8ePHMcYQDoe57bbbePnllxkaGiKfzyMiWJZFMBgsrZt8Po9lWXg8Hurq6ojFYtTW1rJ9+3YAXnzxRY4cOUIwGCxtt3w+j+M4hEIhstksfr+fjo4OAMbHx5mamrpkHdi2TVtbG7Ztc+HCBfx+P8YYjDGX5EVDQwNVVVWEQiFOnTpFJBKhpqaG/v5+HMcpTVfcRqlUCgC/38/s7Cx1dXWlbTM1NcX09DSO4+DxeAgEAmSzWXK5HKFQiEwmg23btLe3IyIMDw+zfv16+vv7AchkMliWxdatWzl16hS2bVNTU8N73vMe0uk0+/bto7a2Ftu2GR0dZXZ2FhEpxSki+P3+Ur4V55/P59m4cSPpdJpwOMyrr75KOBwmlUrh8XiwbZtQKEQ+n2fz5s2Mj48TDAbp7e2loaGB7u5unnnmGfL5PN3d3SSTSRzH4ezZs3g8HlpaWujr6yOfz1+y/v1+fykHjDE4jlOKyXEcOjs7SafTTE5O4jhOKY6ZmRkikQjr16/n1VdfJRaLEYlELtlG9fX1+Hw+xsbGiEajDAwMlJa7qJgvuVyu9Mt/Xq+XvXv38txzzzE7O8sdd9xBJpOhr6+PO+64g76+Pk6dOoUxhoGBgdJn3XHHHfT29pJIJIhEIlRXVzMyMkI0GuXMmTNs3bqV3t5estls6T2hUIj29nYCgQAbN27k2Wef5aabbmL//v3EYjH6+/t517veRSwWo6enhwsXLnDbbbcBcO7cOXp6erjrrrtKy/TUU08RjUYZHx/nXe9617zffaVez1IV1ufOnaO/v5/W1lb6+/u54447+PGPf8zmzZs5ffo00WiUyclJAoEAbW1tbNiw4ZL3v/DCC0QiEbZt2wbAgQMH8Hg87Nq166rzPHnyJBMTE9x8881LskyLYds2P/rRj+ju7qapqWnB73v++edpbm6mrq6O5557jr1793LkyBF6enq44YYb2Lp1K7Ozs/zkJz/hzjvvJBQKLfiz+/r6ePbZZ2lpaSGfz7Nt2zba2treyOKVlVTyT7nu2bPHvPTSS8s6z3Q6zac+9alrfl84HGZ2dnZR8/b7/ZfsGCtZV1cXwWCQkydPYtv2gt9XLLQuFwgEyGQyV33fYtb/1q1bsSyLV1555Q29fzlFIhGSyeSyzKujo4NEInHFQYO6vrZs2VI6gL3eqquricfjpQPLosbGRhobG0s5v337drLZLKdOnSrFVDxg7+3tLb2vpaWFhoYGcrkcfr8fEWHXrl1XFClv1Jf2fZ69338LI4FJuj/53uvymaq8nvm/vs66mVZ+dPcxfu2ej163zz137hz79+8vdXoVrVu3jrNnz171fdu3by8d6BpjSu8vFtTF78SOHTsQEbLZLD6fD7jYaXT06NHSZ1mWRSaTKXWeLMb1qNdSqRS9vb14PB7e8pa3XPLa3AP/uTE7jlNaD8V9TEdHR6nTBdxl7e/vJx6PA+76eb3PBojFYuzbt++KOHfu3Dnv8iYSCYLBIPfddx81NTXXuviLJiI/Ncbsme817aG+RsFgkPe+97185zvfoa6ujqmpqUt642KxGBMTE4gIIsK6devweDxMTk7ylre8hWPHjl1SFDc3N9PY2IjX62VycpJIJMLp06cJhUKsX7+eVCpV6lX94Ac/SE9PD0888QQ7duxgamqqlNwDAwM4joNlWWzatIl0Ok1jYyMzMzPceOONPProo6UYOzs7ue2223j00UdLsTQ2NhKLxTh+/Hipty4cDjMzMwNANBoln8+TyWSIRqOloi0SibBmzRo8Hg/xeJyqqipmZ2cv+aJdznEcEokEiUSCWCzG2NhYaR2GQqFSb30ul6OqqopsNks2m2XNmjXs3buXJ598kuHh4VIcHo+H2tpa2traOHToEI7jEIvFiMfjeDwetm/fTl9fH7Ozs1iWxcaNGwHo6emhu7ubQ4cOYds2nZ2dVFVVcfz4cRzHYc2aNVRVVTE6OoqIEAwGiUajtLW1YVkWZ8+eZWpqiurqarq6ujh06BAiwqZNm5ienmZ0dPSS3mRwG5mOjg6efPJJurq6cByHnp6eeddRIBAgFAoxOzuLbdts3bqVc+fOlQ4MjDGlnk7btrntttvo7u7mW9/6FrW1tQwODhKLxTh58iTGGLZt20YqlaKuro4DBw6wY8cONm/ezOOPP87GjRvJ5XL09vbS3t5OOBzmxhtvJBQK8ZWvfIVsNktNTQ2zs7OlXvlUKoXX6zYhoVCI6urq0hkWy7J46qmnuOGGG4jH49TV1ZHL5Ugmk9TV1XHw4EG2bdtGMpnEGIPH42FgYICdO3eWepp7enrYvXs3Bw8epKamptSL1NTUxJ49e3j22Wdpa2vjxIkTWJZV2rHlcjmy2Sytra20tLQA7pmluro6gsEg1dXVPPnkk6V1vXv3btrb2/nud79b6mXx+/04jsOZM2ewLIsHH3yQo0ePEggEOH/+PJOTk+RyudI2mpmZKfX4e71eZmZmaG1tZe/evXzrW98q7WSK36UNGzZw6NChS7Z3Q0MDY2NjdHV1Yds28XicyclJxsfHqa+vZ3x8HJ/PVzqgLJ7Vqa2tJRKJkM/nGR8fZ2xsjGAwSCqVIhKJkMlkLumldxyHaDRKLpcjEonQ0tLCxMQE6XSa5ubmUk/eyMgItbW1TE1NcezYMYDS36OjowBMTExckrdDQ0MMDQ1d8tzLL7/MW9/6VrZv305XV9dV24WFKP5Sog6lXn2uV+fe+fPnOXDgAAcOHLjitba2ttK+q7ivLrYZADU1NQwNDV1S/Pl8Pvx+PyMjI4BbA4gIFy5cYGZmhkwmg9frpbq6Grj0OzE4OEg2my3Ns76+/nXjnzvvN2ohn1HcR8xd78XHxfYH3LOlcxWnKZ4VLTp+/DixWKz099U+O5vNluqK6urq0sHH5Y4cOXLF+nIch8nJSQAeeOCB113G5aY91EoppV7TgQMHOHnyJO9///svGdJx8uRJXnzxRbxeLzt27ODYsWNs3LiRM2fOICIcPXq01HsXCATYs2cPt956a+lA7Fp98enPcc/fb+OMf5CaB7eUTrtPTExw5swZ9uzZw+HDh2ltbaWpqYlEIsGxY8e46aabSKVSvPzyy9x0002cPn2aYDDI2rVrFzRf27Z54YUXuOGGG6iqqpp3mrGxMfr6+uju7r7k+cOHDxOJRBgfH6eqqopYLEZra+sbWv5cLsfhw4dpbGwknU6zZcuWeac7ePAg69evp7a2tvTc5OQk/f393HDDDVdMX1w3b3vb27Asi56eHvx+Pw0NDbz88svs3r271KOYz+d54YUX2L179zWd1r+ab3zyITam2zhw5zl+/d5/BcCJEycIh8N0dnZe8+f96Z/+6SWdVr/8y7/M/v37ufnmm9m0adP8MXzjG3R1dV2x7V7P5OQk3/jGN/i5n/u50vCJ5557jrGxMd77XvcMSjqd5pFHHuHOO+9c9AHlcnEch6997Wts2bKltE4GBgZ44okneP/731/6DoyPj/PlL38Zr9fLBz/4Qerq6njqqafIZrPcc88983727OwsX/3qV3nnO99JS0sLX//619m5cyevvPIKb3/72+ns7OQrX/kK3d3dpeGWRcYYHnvsMTo7O7npppuWdiVcxWv1UGtBrZRSakmdO3eOr33ta8zOzpbGR7a2tnL+/HlyudwlPWrF6xuK49wBLMvCcRwO9f2UDacbOeg9C8Att9yC3+/nqaeeAqC7u7vUM3nrrbdy7NgxJicn2bVrF4ODg4yMjLBjx45Sr1hxbHhxvnMVzzIWe8WOHDlCU1NTaQiYbduX9MA9//zz2LbNz/zMz5QOIvL5PPv3779ifcyd73zznu81EeHEiROXnAG49dZbsSyr9J8xhmQyyYsvvgjA7bffXlqGp59+GnDPksVisdLn2rbNkSNHmJ6eZu3atXR0dPDMM88AF89IdHV10dHRgW3bjI+Pc/z48UvGG7e0tJBIJEo9j8XtVVw/863baDSKbdv84Ac/ACDaFmbX+m6MMTz77LOl+K/2GZdvo+LfP/nJTwD4lV/5ldLZSKWuFy2olVJKlZUxhs9+9rMMDw9f8nyxULoe+6LiGFag1JNeHAonIqWLiecWYHPju5rie+Z+/tx5FD977nOXP395nPO5Hutg7vK9kekvv05l7pCIuevx8nUxn4WuX3disMS6Yp1dvq4Wso4+8IEPXLX3XqnF0DHUSimlykpEeM973sPDDz9cem7btm28733vu2S6sbExvvjFL/Lggw+yYcMGpqeneeihh7jvvvt4fmwfd3x/M48F9nP/+x+gq6uLz33uc9x8881Lcgr4u9/9LhMTE3zoQx8qFXbxeJyHHnqIe++994oLr+Zj2zYPPfQQXq+XRCLBRz/60Tc0VKIYS3t7O0eOHCGXy3HffffR2dnJ5z//eYLBIAC/9Vu/xeHDh9m3bx8f+9jHOHLkCPv27eOjH/0of/M3f8PGjRu58847+cIXvsD69evZu3cvAI888gjhcJgHHniAoaEhHn74YT70oQ+xZs0aHnvsMbLZLB/4wAeuiGtqaoqHH36Ym266iVtuuYWZmRk+97nPcffdd3PjjTfOuyz5fJ4vfOELtLa2UncoxfrZNTxx1xH+5b2/DbhF89/+7d9SW1tbGjpxNd/73vcYGxvjV3/1V3nyySfp7++/6tAOpZaS9lArpZRadsXe4mu5COsL+z7Lvd/fzoh/ku4/1rt8rBSX3/bzWt5TvMvH3IJaqZVKe6ivo3w2y9DpV917ZpZurQOX/8zTJQcqlzyc+8dVHr8OM2d6N47L53l5LJd/wPIcRC3VfUWleI3/JeMuL77q/r3Axn0Bk8lC7ymwgHkueJezkPgXNL/ruB4WvMNcQFwL/qjlXcaFBlac51W/z+VwHe4OcE2zW857bRSWzRly7zxgOYaBk8df6x3XY3bLaJm33XIv4GvMzsoX9mWjMwyevj63h1zW3IRlTZhl33YLsdB28zrGXt/egcfru26fdz1oQX2NZuNTfO2THy93GEop9aZT5a2FjpsJpoSv/tHvljscdR28a80HIQCeJ17lke/+TrnDURXiN//yS1Q3NJY7jEtoQX2NwtW1/PP//CeFv+TigZnIlUfFc/+c25s694V5e1nnZ8ylPbGloz25stf2dY8E3+iR4qVBvK7rfTRd6oWfpzfwtV6b97MW0oO+wE7HhQ2dWmBcC/qo159owWcIFjLDhX7UgtbpdVwPC16nS7eMl36fF/YZ190yd44v689Fz9l2Tx75IRyFdNDw4O//8ZLPbzks+3mNZV++157f8DfPUJ8D584ufr77I9djhstqeYfNLvO2u077IrjO+yMgFI0u7POWkRbU18jr99O54+o/OaqUUmppyNR+OAqOB9bturZ7BquV6cL3eiEHTluUrt1vK3c4Sr1h1utPopRSSpVf5V5Cr5Ra7bSgVkoppVRZVfIdx5QCLaiVUkpViOI4TC29VhEtpNUqoQW1UkqpirICbxymFmlZL3RVagloQa2UUqoyaM216ugmVauFFtRKKaUqgg75UEqtVFpQK6WUUkoptQhaUCullKoMegHbqqVjqFWl04JaKaWUUkqpRdCCWimlVEXQXkyl1EqlBbVSSimllFKLoAW1UkqpinCxh1p7qlePwp1bdHy8qnBaUCullFKqrHQ4j6p0WlArpZSqCNqLufroFlWrhRbUSimlKoz++Phqoz3UqtJpQa2UUkoppdQiaEGtlFKqwmhv5mqjw3lUpdOCWimlVEXQe3wopVYqLaiVUkpVBO3FVEqtVFpQK6WUUkoptQgrrqAWkXeLyEkROS0iHy93PEoppVYGvRPE6qVbVlU6b7kDmEtEPMBfAnuB88CLIvIdY8wr5Y3sooyd4asnvsqxsWNsb9hOc1Uz46lxpjJT9Ez1sK56HfFsnGQuydroWkZToySzSbpqu4hn4/gsH/2Jfu7vup9kLknPVA93dtxJPBunylfF9vrtxLNxZnOzrKtZV5rveGocr+VlKjNFc7iZvJMn62QJe8M8PfA0h0cOc/+G++lL9OEYh4AnQGO4kZeGXiJjZ0jmklR5q4hn4/Qn+tnRsIN3tL2DY2PHSOVT+D1+hmeGub39dnJOjn3n97GzYSctVS2srV5LXbAO27EB8FieUlzGGBzjMDgziDGG6kA1x8aPcXDkINti2xhNjTKWGqO1qpUdDTvYP7iftza/lUQ2wYHhA9jGxmN5uLvjbsZSY+SdPEMzQyRyCZrCTWyp28LTA08zk5uhL95HZ3Unt7ffztGxo9zQeAPDM8OMpkZpDDWyrmYdJyZOcGvbrdT4axAR8k4ev8dfilXEvd1Wzsnx6uSreMWLYxxS+RQvDb/E4dHDtFa1srF2I42hRl6dfJW6YB15J88/9v8j71n/HprDzTx74Vlydo7mqmZaqlpIZpMEvUEssTDG4PP4eHXiVWxjs71+O43hRkLeEEfGjnBXx11U+aqI+qMcHDnIQHIA27HZ2bCTlJ1iXfU6cnaOc4lztEXayNk5TkycoDZYSyKb4Junvsme5j0cnzhOOp9mS2wLk+lJJtITbIltoSHUQDqfBuDExAlC3hBN4SZC3hDHJ46Ts3Pc1XEX8WycNZE11ARqqAvUcXj0MIMzg1T7q9lWv432aDu9070MJAfYGtvKt05/iw9v/zA1gRoAZnIzVPmqmM5M88jxR6gP1WOM4b0b34vP8vHoq49ydOwoVb4qHOMQ9oVpj7QjIlxIXqB3upebWm5iLDVGwBMg5+RwjEPQG+Rc/Bzb6rexoXYDPVM9vDD4AvdvuJ/jE8fpbuomnU9TF6yjLlhHZ7STC8kLBL1BGsONDCQHiGfi7B/czzs730lNoIaaQA2OcTg6dhS/x0/GzvD8hee5q+MuNtRu4HziPAdHDjKaGiWVT7EltoV0Ps2JiRN0RDtoCjfx+KnHifqjVPurscTCEouck6O7qZvR1Ci9073M5Ga4selGOqOdZOwMuxp38e2eb/OBrR/Ab/l56vxT+CwfyVySnQ076Yx2cmTsCFtjWxmeHWYwOchbm99Kf6KfpnAT8WwcQfBYHl4Zf4UjY0dIZpM0hBqo8lUxMjtSamMA8iaPhcW2+m14LS8ZO8Pw7DAXkhfoiHYQ8ATwWwGymQFCkuWWNTfTHunglfFj7GjYwYWZQaYz02yo3cDJiRNsr99B0BuYty10jIMlF/tk8sZmMHmBxlAT55P9WOIh4q0ib/L0TPfQEGxkzPYST57kfOI8Po+fxnAjjmNjWR7ydp6pzBR+j4/aQB0T6XG21W9jNp9iKjNFzs5y8MJTvLu2lpx3kv1n/o4tdVuJZ6c5Gz/HmsgaGkMNOIVhIZZceWu9nJNjLDVGfbAen+WnOEk6n8FreUnbabJ2lpeGX8R2bGoCNYynJ+hu6uaJs08QC9ZR7a8m4AkwlhrjwswF6gIxJjOTBDx+djXu4tTUaYZnhvFaXprCjQzNDLGxdiMbazdxeuoUDaEGjk+cwHFs6sMNJDMJvB4v7ZEOAJrCTXgtL4JbZNaH6qnyVjF3cSbSE4ymRokF62kINjCVnWR0dhTbODw78AyxYIy6YIyx1CiWWDSFm7mxcRc9Uz2MpEZI59OIWGyq3UjvdC9Hx47R3dTNwMwAUV+UpnAjydwMs/lZ4plpjDGEfWFCvjC7G3cT9oVI5dM0VzUjwNDMMGemz7C7aTcRX1VpXzmWGqe5qpmJ1DjV/mq8Hh/pvLuOY8E6pjNxcpEzzPpnGZt5gaP93yLqjzKRnqAt0saLQy9yZvoMOSfHprrNJDIJeqZPk7EztFS1kLEzOMawuW4T1f5qjsbjmEwfXsuDZXkYnhmiPlRPS7iFt7e+HdvYHB49zPDsCDc23kh9KIYlFrWBWtL5DOcSZ9lcuwURMAZEwDGG8fQ4tYEaRCww0DvdS87JsiW2hWR2xs2D2J1sjLZwcuok66vXk8gmODhykIg/wqnJU4S9Ye7fcD+pfKrUflzxHxcfyzz5u1Ti2Tj/+9z/ZiI9QSwY4+bWm6kJ1NCX6Ct9X37c/2OS2SS3tt1KPBvHOzbN8VQv4940Oxp2EPQEOZ88T22gllQ+Rdgbpj/Rj21sOqOd3Np2Kw2hBl4afom8k6ch1MCG2g3k7BzVgepSW3J07CjrqtcR8UfmjXU2N4vf48drrajyFQBZSWPSRORm4BPGmHsLf/8nAGPMf5lv+j179piXXnppGSOEo0Mv82df/10SYcGXh239Do7AZERom7IYr3LoaRHWDxtiCcNURMh5IOeFiYjQOG14S79h3w6L6TDUzEJ9AponHYzAcJ0wUiNsOe9Qlw/ieCzGqg19kQwAHsfQOgFDdZD3COuHHNrHYDAGp9ssEkGIpGFrv8O2Pnhxs3CqTdh0AcAgtuFsu4+8sdl4wSHnFRIh9z21STcXJqNC9YzB68BIrXC2Sbj7qBBM2UxFBcfr4WyzkLMc2kYdAlmDbcG5JmEwJqwbMbzjFUM8DC9sFt5+3IBAX6NgBLacNzgW/NMWoW3ckPXCUEzY86ohOgvHOmHzBQhl4UQ79LZIaZnrE5AKwPl6IeODxml3nXSMGhJhIWdB67TFZAQsYzjTBPW5AOI4vO1ohoEmH8fWe4ikDHk7S9sEDNRDIAvtY4aRlhCBRJqGuGGgXoiH3UYt7YdgFnIeyHthIgJdw4a2MUPHKOzfKmR8FxvAZAi2DBiq0nCyTYimDP68uw4iKZgJCUHxk8tliCUN64YNAuQtGGsMMhDNUjPjLtfpNRaxhMFyYKxG8OUNrROGnjUWeY/gzxvq4obWKUMoA+2jMBmF8WqIR734MjZpH1yICR7c3ABwxF2fT2+38DgwHnX/lkKT0DphSIQhGRTSfojMGtaOGqZqfYyHbHJeCBkfHgcyJodtwXQEdp6D8RoPDRN5BhogL8LGIYeqNOQ94HHc74LXNgzVuett/bBDOA3RFLRMuev6R7uFQA7iYaiZASMwE4RESJiMQl3C3WbnmgV/zrB+yJCuDuKbSSPGXdcAa0cMmWiQrE+ITqQ4ss5tuMMZiKTdbZQKQCQFHhtGayDtFwRD2zgkA9AYN2R8FsNNPvKWoXU4R2+Lxd2HbPJeuBCDviaLxik3n6cK33Uj7jwCORivtjhf7y5b9YwhlINo1sNgtc1MSNg4YDjbBMbnZc1InrEaiCVgpAb6mty88TpQlbUwjs2GQcP5Rg91szATMOTDQfoiad7S736/QhnoaRVCOWFnr43HAW8ePnv/72Ms+Dh/vNTN5SV+yD9jn9zNb5tP007fss5brX4jtPBp+T1+1nyLd7BvWefdxzo+K/+WXYOPE5v6J3x5wy0nDEfXCuG024ZnveDLQyAPjuW29UbAtty22LbA8YANmMLriCBiIQKCYCG4j6R0wOg+tij+ZRX/L8XpuPgeBK8jrB/IExpLMBGBnb0OebExBvbtFBwR1owbamYNGEiGhJ5Wty0uWjNhuPmEYaQa/mmrh5YJmwv1QjIkRGcNtx81vLxeGKq92PanfTBWLfhtGKkR4mHw5919QtOMj+ZpGKoX0k6GtnHI1ISYiIBtHCzcemvNBESm04x11vEfP/DnrKlrX9btDCAiPzXG7Jn3tRVWUP8i8G5jzG8U/v4g8DPGmH893/TlKKj3/+NjPMCGZZ2nUkoppZRyPZw9wLvv/fVln+9rFdQrr8/8dYjIR4CPAHR2di77/Dd238bv/+B/wvAY+Lw4a9vA50MSSfB6wRhkdAJqophQABmfwlSFIOCHbA6JJyEYQPovYPwBaG2ExAymtRHj9SLJGWR8Cqe9BbFtTCSMTCfBti+ug1QGcnlMdRVYFjIZR8YnMaEg1tAozoa1mMY6jGVhDY5AOgv1tZiqMFiCDI2C7WCaG5BMBqaTmMYYprYajINMJsDvRYbHwWMhA0OYrk6cWC2SzbpBZN3DVRMOQSgIuRzW8DjEE1BfhwkH3fNlmay7TmZSmPpaMGA8FpLLI6MTOGvXQC6PpNKYaARreBTpH8LZ2oVMJzA1USQxA5aFCQfdZTzTh3V+GAJ+nE3rMKGAu06HRiEawamNIskUMj6BTCVwutxTqfj9WC8fdz9rbRuk0piGGOTzgGCiYayBYbAsyOfd9QFI3obpBCZWgyRnIZ50p/F53WUK+JHBUaiNYjwed3nHpyCXg6oqyOcgGoGRcSSdxunqRCanIZWBUBATqwGfz12fwQDWxDQkEpi6GiRvI6fOYTZ2YqJV7voE8HqRU+ewpuM4XZ3uMlSFYDIONVH36ghxeymwbUykCknMIL3nMZvWuucz0xn3PYkZdxtOxiFWg/H7SvPAtpFsDhJJ8HgwNdXuZxoHic+A1+Nua0ByeZiYAscBh4tx5B2clgYkn8f4/eDYSDbv9qAkk5DO4bQ2YU3H3eXzebFeOY0JBNx1Y7nLQFO9+x0pxmNw48/mwOvFaarHGhmDQACnOoLMzLrrtCqMzKaQ8UmojmKd6MEE/Jh17e6y10QwXi94CkOZ8jalEZ1eLzI2iWmKufGOTiJDI5iuThifxKxpxvh9bu77vJhIlbv8xgGPx83d6bgbu8dbiCHixl9TjakKIReGIe9g2luQ6QTk8jgtjW7M2SyMToBlYZ0fAsDZsQkyWUxDDOm/AAE/JlaH5HLu+o/VXsyTTNZdhwE/2AY8QnA8jjdVR6bOXSbGJ7Empt32xAHT3uLm7Gwaa2AYZ12bm+9zBQLgsWA25a7jSBVYILZBzvS56206gbOmCaJVMBWn7h+epmEmQW+kDuPxYL/7dgiH3DwErOOnkeQszrp2SKfdds7jwdm0FuJJZGwSPJbbxrU2YTashak41uAoTluzu14RyLptjvud97nb0+dDzg+67d90EhwH4/dh2lrcHMrbyLnz7jodm4BQCOunRzBrmnC2b7643MZBBkfddsDnw+lodddXLodMTIFjkOExTG0NBP3I+CRWTx/2bW9z4/IHwLEhk3Wn61wDE9N4n9rvrpOfvwdmUsj5QUysFgrtnYnVQDaHaWpwv6uzs0hiBmfzemRgGOvCCM6aJmRyGlNXA8GAu1wDwxAMus93tmICAazefrfNjFQVtqUf4/fh3fcCxJPYb9/tttdeC6qj4DjI6Dimrtb9d3OX27aNTSCZHCYYQNIZyGTc9RII4LQ1IaMTWKfOut8BwN65BbO2DRmdwHSucb/LMzOYWC0yPIaMjONs3+zmT00UfF6wHZicdrdjrM6dZzwBxmBamiCVwrowAn4/TlsL1WKTGJnENDdAVRWmKoh15CQyk8LpaEWGx7COnca8pcttN68mm8PqG3DbK4+FzMzitDS5+63JabcdzGYwzY2YWDXSP0iV5wJTDXUXUyUUdHPY60HODbh5u67d3Y8U20jjuLnqmMK/zsXH5vLHXGxbSs8X3usYxFz22iXPF+fhgAhOZ5u7f5madtdLchYTDuE5eAzTGHP3W6m0+70XIJNx86o4DMXrxVRXubWCccDvc5d1dMJto9a3Y01NQyZfavtBsI6cxKxpcuuaiamLbW4ogKmqKuyLC+1uKg0j424ue6yL04jgpFLsec9vXn37lclK66Fe8UM+lFKqHJxUitzgEIGu9eUOZVHyY2OI34+nurrcoSil1DWppB7qF4FNIrIeGAB+Cfjl8oaklFLlZ4VCFV9MA3gbGsodglJKXXcrqqA2xuRF5F8DTwAe4IvGmGNlDksppZRSSqmrWlEFNYAx5vvA98sdh1JKKaWUUgux4n7YRSmllFJKqUqiBbVSSimllFKLoAW1UkoppZRSi6AFtVJKKaWUUougBbVSSimllFKLoAW1UkoppZRSi6AFtVJKKaWUUougBbVSSimllFKLoAW1UkoppZRSiyDGmHLH8IaJyChwrtxxLEADMFbuINSqpfmllprmmFpKml9qKV3P/FprjGmc74WKLqgrhYi8ZIzZU+441Oqk+aWWmuaYWkqaX2opLVd+6ZAPpZRSSimlFkELaqWUUkoppRZBC+rl8flyB6BWNc0vtdQ0x9RS0vxSS2lZ8kvHUCullFJKKbUI2kOtlFJKKaXUImhBfZ2IyJrCv1LuWNTqIyK+csegVi9tv9RSEpFQuWNQq5eItJc7BtCCetFEpEpE/gJ4QkTqjY6hUdeRiERF5H8AnxKRt5c7HrW6aPullpKIRETkM8D/FJF3i0hNuWNSq0chv/4CeFJEOssdjxbUiyAi7wWOAbPAO4wx42UOSa0ihV7ph3C/p6eAPxSRj5Q3KrVaaPullsGnAT/wTeADwMfLGo1aNUTkLuAlwAvsMcb0lTkkLagXKQt4jDF/aIyJi8hGEYmWOyhV2UQkUHjYDKw3xnzMGPNZ3CuVdxUKIaXeEBEJFh5q+6WuOxGJFf5tANYA/8EY8xjwF0CriPxmOeNTlU1E6gsPs8AU8HFjzKyIbBeRpvJFpnf5uCYishH4N8Ah4FFjTFJEvg2M4x6FNwEO8N+BHxtj0uWKVVWWwtjVEPBV4B+AvzTG5EXk74FHjDH/q7Cj+iVgC/CHxphE+SJWleQ18utxYAIIoO2XWgQR6QI+CfQB/9kY44jID4AnjDGfLnQUvBv4deDXjDETZQxXVZir5NengSjQCFQDM8APgC+XY/+oPdQLJCJ/DDwGDAI/W3gM8DvAHcBPjTH3AH8P3AvsLkecquJtBNYD7yj8/U3gVhGJFHZAhwEDtJQpPlXZivl1e+Hv3wXuRNsvtQgi8qfAD4F/Msb8gTHGKbz034B3i0itMSYDvAz0At1lClVVoNfIrz8HunA7AO7EPYu7CbivHHFqQb0AhQspzgL3GGM+BfwHYFREwsaY08Adxpj/rzD5Z4Bd5YlUVarCxWBdwBAwCbxDRCLA04ANfLgw6XPAbeh3V12DefLr7SLSWGi/btf2Sy1SPXDMGPMZKO0zAZ7BLaA/DmCM6QXW4fYkKrVQV+SXiHiNMeeBf2GM+TSAMebbQAz3upBlpzvlBTDGTANfMsYMi8jbgH8CqoDfL7x+fs7kN3JxbI9S1yKF20O4H/f0+41AHPg28EERuRO4Abcg0u+uulZz86sR2CEidcaYgTnT3Ii2X+rafRJoFJH/U0S+A/x3EXkIt7D5C+AXROQXCncqagT09ozqWlyeX/8N+LyIWMaYC8WJRGQX0AmMlSNI3SlfRkT88z1vjDGF19bgnib9F8BOEfn3hfe1i8g3gb8GvmiMOb5cMavKcbX8KmgDdhtjnsAtfh4G/sgY8yPgr4APAY/iHtxpfqkrXEN+pXFPj/6Xwq2nOrT9Uq/nNfaPF3CHp/0O8Le4+8j1wL83xpwCfg+4CfeuRX9tjHlueSJWleQa8uv3cAvnf1d4X0vherbP4ebX88sT8aX0osQ5ROQTuI3AD4Eni7eREpF3415YYS6b/p24p0i34Z6S+AVjzLL8ZryqPK+XX7in2u/FvbjiQ7in5//KGPOlwnSBwjhEpa7wBvJrEDe/Hi5cOf+gtl/qaubLr8LFrvfi5pcXiBYvNhSRu3Hza2uZQlYV5A3m12eMMdsKf3/YGPNwOWIv0h5q3NMEIvIC0A48Dvwy8KCIWCKyG7dXOjDPWztwryi1jDFjujNS81lAfrUVDtaiwL/Czas9wF8CN4rIBgAtptV8FpFffwV0i0iXMWZc2y81n9fKL9whQm24+8f8ZXfuWAd8tzCdUvNaZH59X0S8AOUupkF7qIHS7VjumzPg/d8Au4wxv1EY+J6fM20tsAP4ROGp3zPGHFjmkFUFucb8Wl+4cIfCLz9Zxpiz5YhbVQbNL7WUrjG/Qrj7x0/h3o3od40xB8sRt6oMqym/3pRHjiISE5GfFxFP4ale4EuF0wsALwI182xMLzANbAb+zhjzLi2m1eUWkV9BY0xvoWfRY4zp02JHXU7zSy2lReSXzxiTwr01498W9o8rpthRK8Nqzq83XUEtIr8InMO9aOLB4vPGmJk5Y6TfCZy9bGNuBf5voM4Y88WVcHpBrTyLzK8/EpEmY4xjjLGXM25VGTS/1FJaZH79sYjUG2O+ovtHNZ/Vnl/ecgdQBuPA/4F7H8w7ROQnhdvhCe7pTxv36tHvAIjIHtwjqEHgz4z+upN6bYvJrz/X/FKvQ/NLLaXF5Nf/q/mlXseqzq9V3UM95xTCXE8bY74AHAcywD+H0g8fFH99JwC0i8gjwB8AQWPM9ErfmGp5aX6ppaT5pZaS5pdaSm/G/Fq1BXVh/M0VV1zOOY1wFHeszq7ClfDFe02vxb2l1EdwN/7Pm0t/+EApzS+1pDS/1FLS/FJL6c2aX6uyoBaRfwv8vYh8rLixLj9aKpxaeAn3VMKdhWnWGGOK43vuMMb89bIGriqC5pdaSppfailpfqml9GbOr1VXUIvIbwD/DPenKrPAfxKRGwpHP5650xr3F5y+B9wvIgngtwvP/1djTHKZQ1cVQPNLLSXNL7WUNL/UUnqz59equA918fYqhaOgbwCfN8Y8Ie6vf30JmDXG/NLl7wE8wDNAGPcnnh9b7tjVyqf5pZaS5pdaSppfailpfl1U0T3UIuIVkT8H/quI3FsYs/M88B8Lk0wDZ4FNIvJA4T0C7lge4/7y3BeNMdtXw8ZU15fml1pKml9qKWl+qaWk+XWliu2hLmyYvwSqcX/++9eAx4AvA/8AnADehnuElARqjDF/Nuf9ljHGufxzlQLNL7W0NL/UUtL8UktJ82t+lXwf6iju77zfa4xJiMg4cD9wB3ALsBPwGmMOiMgncO9/iIiIca26jamuK80vtZQ0v9RS0vxSS0nzax4VO+TDGBPHPZ3w4cJTz+DehuV+oMUY83JhY0ZwN+65wvsqs0teLSvNL7WUNL/UUtL8UktJ82t+FVtQFzwO3CgirYWrQl8G0kCzuD4MPAucMcZ8p4xxqsqk+aWWkuaXWkqaX2opaX5dptIL6meAMQpHScaYA8BNQKRwJHQIuMcY87vlClBVNM0vtZQ0v9RS0vxSS0nz6zKVPIYaY8ygiHwb+JSInMY95ZAG8oXXD5UxPFXhNL/UUtL8UktJ80stJc2vK1XsXT7mEpH34P4m/C3AZ4wxnylzSGoV0fxSS0nzSy0lzS+1lDS/LloVBTWAiPhwx7znX3dipa6R5pdaSppfailpfqmlpPnlWjUFtVJKKaWUUuVQ6RclKqWUUkopVVZaUCullFJKKbUIWlArpZRSSim1CFpQK6WUUkoptQhaUCullFJKKbUIWlArpVSFE5F6ETlU+G9IRAYKj5Mi8lfljk8ppVY7vW2eUkqtIiLyCSBpjPnzcseilFJvFtpDrZRSq5SI3Cki3ys8/oSIfFlEnhaRcyLyCyLyZyJyRER+WPhxBkTkrSLyExH5qYg8ISKt5V0KpZRa+bSgVkqpN48NwN3Ae4G/A/7RGLMTSAE/Wyiq/wfwi8aYtwJfBP6kXMEqpVSl8JY7AKWUUsvmB8aYnIgcATzADwvPHwHWAVuAHcCPRITCNINliFMppSqKFtRKKfXmkQEwxjgikjMXL6JxcPcHAhwzxtxcrgCVUqoS6ZAPpZRSRSeBRhG5GUBEfCKyvcwxKaXUiqcFtVJKKQCMMVngF4H/R0QOA4eAW8oalFJKVQC9bZ5SSimllFKLoD3USimllFJKLYIW1EoppZRSSi2CFtRKKaWUUkotghbUSimllFJKLYIW1EoppZRSSi2CFtRKKaWUUkotghbUSimllFJKLYIW1EoppZRSSi3C/w9UD/AbWmSAjwAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# random dataset visualizing\n", - "list_of_df[1].plot(figsize=(12,6))\n", - "plt.xlabel('Time')\n", - "plt.ylabel('Value')\n", - "plt.title('Signals')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Labels" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# plotting the labels both for outlier and changepoint detection problems\n", - "list_of_df[1].anomaly.plot(figsize=(12,3))\n", - "list_of_df[1].changepoint.plot()\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Method applying" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# classifier initializing\n", - "t2 = T2(scaling=True, using_PCA=False)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# inference\n", - "predicted_outlier, predicted_cp = [], []\n", - "for df in list_of_df:\n", - " X_train = df[:400].drop(['anomaly','changepoint'], axis=1)\n", - " \n", - " # classifier fitting\n", - " t2.fit(X_train)\n", - " \n", - " # results predicting\n", - " t2.predict(df.drop(['anomaly','changepoint'], axis=1), window_size=5, plot_fig=False)\n", - " prediction = pd.Series((t2.T2>2*t2.T2_UCL).astype(int), \n", - " index=df.index).fillna(0)\n", - " # predicted outliers saving\n", - " predicted_outlier.append(prediction)\n", - " \n", - " # predicted CPs saving\n", - " prediction_cp = abs(prediction.diff())\n", - " prediction_cp[0] = prediction[0]\n", - " predicted_cp.append(prediction_cp)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# true outlier indices selection\n", - "true_outlier = [df.anomaly for df in list_of_df]\n", - "\n", - "predicted_outlier[1].plot(figsize=(12,3), label='predictions', marker='o', markersize=5)\n", - "true_outlier[1].plot(marker='o', markersize=2)\n", - "plt.legend();" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# true changepoint indices selection\n", - "true_cp = [df.changepoint for df in list_of_df]\n", - "\n", - "predicted_cp[0].plot(figsize=(12,3), label='predictions', marker='o', markersize=5)\n", - "true_cp[0].plot(marker='o', markersize=2)\n", - "plt.legend();" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Metrics calculation" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "False Alarm Rate 12.14 %\n", - "Missing Alarm Rate 52.56 %\n", - "F1 metric 0.56\n" - ] - } - ], - "source": [ - "# binary classification metrics calculation\n", - "binary = evaluating_change_point(true_outlier, predicted_outlier, metric='binary', numenta_time='30 sec')" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Average delay 0 days 00:00:07.150000\n", - "A number of missed CPs = 90\n" - ] - } - ], - "source": [ - "# average detection delay metric calculation\n", - "add = evaluating_change_point(true_cp, predicted_cp, metric='average_delay', numenta_time='30 sec')" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Intersection of the windows of too wide widths for dataset 16\n", - "Intersection of the windows of too wide widths for dataset 16\n", - "Intersection of the windows of too wide widths for dataset 16\n", - "Intersection of the windows of too wide widths for dataset 18\n", - "Intersection of the windows of too wide widths for dataset 18\n", - "Intersection of the windows of too wide widths for dataset 18\n", - "Intersection of the windows of too wide widths for dataset 19\n", - "Intersection of the windows of too wide widths for dataset 19\n", - "Intersection of the windows of too wide widths for dataset 19\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 27\n", - "Intersection of the windows of too wide widths for dataset 27\n", - "Intersection of the windows of too wide widths for dataset 27\n", - "Intersection of the windows of too wide widths for dataset 32\n", - "Intersection of the windows of too wide widths for dataset 32\n", - "Intersection of the windows of too wide widths for dataset 32\n", - "Standart - 17.87\n", - "LowFP - 3.44\n", - "LowFN - 23.2\n" - ] - } - ], - "source": [ - "# nab metric calculation\n", - "nab = evaluating_change_point(true_cp, predicted_cp, metric='nab', numenta_time='30 sec')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## [Additional] localization" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.2" - }, - "toc": { - "base_numbering": 1, - "nav_menu": {}, - "number_sections": true, - "sideBar": true, - "skip_h1_title": false, - "title_cell": "Table of Contents", - "title_sidebar": "Contents", - "toc_cell": false, - "toc_position": {}, - "toc_section_display": true, - "toc_window_display": false - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/notebooks/hotelling_q.ipynb b/notebooks/hotelling_q.ipynb deleted file mode 100644 index 9346d33..0000000 --- a/notebooks/hotelling_q.ipynb +++ /dev/null @@ -1,548 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Pipeline for the anomaly detection on the SKAB using $\\phi$ - combined Hotelling's and Q (SPE) statistics with the PCA" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "# libraries importing\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline\n", - "\n", - "# additional modules\n", - "import sys\n", - "sys.path.append('../utils')\n", - "from t2 import T2\n", - "from evaluating import evaluating_change_point" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data loading" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# benchmark files checking\n", - "all_files=[]\n", - "import os\n", - "for root, dirs, files in os.walk(\"../data/\"):\n", - " for file in files:\n", - " if file.endswith(\".csv\"):\n", - " all_files.append(os.path.join(root, file))" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# datasets with anomalies loading\n", - "list_of_df = [pd.read_csv(file, \n", - " sep=';', \n", - " index_col='datetime', \n", - " parse_dates=True) for file in all_files if 'anomaly-free' not in file]\n", - "# anomaly-free df loading\n", - "anomaly_free_df = pd.read_csv([file for file in all_files if 'anomaly-free' in file][0], \n", - " sep=';', \n", - " index_col='datetime', \n", - " parse_dates=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data description and visualization" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "A number of datasets in the SkAB v1.0: 34\n", - "\n", - "Shape of the random dataset: (1154, 10)\n", - "\n", - "A number of changepoints in the SkAB v1.0: 130\n", - "\n", - "A number of outliers in the SkAB v1.0: 13241\n", - "\n", - "Head of the random dataset:\n" - ] - }, - { - "data": { - "text/html": [ - "
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Accelerometer1RMSAccelerometer2RMSCurrentPressureTemperatureThermocoupleVoltageVolume Flow RateRMSanomalychangepoint
datetime
2020-03-09 12:14:360.0274290.0403530.7703100.38263871.212925.0827219.78932.00000.00.0
2020-03-09 12:14:370.0272690.0402261.0969600.71056571.428425.0863233.11732.01040.00.0
2020-03-09 12:14:380.0270400.0397731.1401500.05471171.346825.0874234.74532.00000.00.0
2020-03-09 12:14:390.0275630.0403131.108680-0.27321671.325825.0897205.25432.01040.00.0
2020-03-09 12:14:410.0265700.0395660.7044040.38263871.272525.0831212.09533.00000.00.0
\n", - "
" - ], - "text/plain": [ - " Accelerometer1RMS Accelerometer2RMS Current Pressure \\\n", - "datetime \n", - "2020-03-09 12:14:36 0.027429 0.040353 0.770310 0.382638 \n", - "2020-03-09 12:14:37 0.027269 0.040226 1.096960 0.710565 \n", - "2020-03-09 12:14:38 0.027040 0.039773 1.140150 0.054711 \n", - "2020-03-09 12:14:39 0.027563 0.040313 1.108680 -0.273216 \n", - "2020-03-09 12:14:41 0.026570 0.039566 0.704404 0.382638 \n", - "\n", - " Temperature Thermocouple Voltage Volume Flow RateRMS \\\n", - "datetime \n", - "2020-03-09 12:14:36 71.2129 25.0827 219.789 32.0000 \n", - "2020-03-09 12:14:37 71.4284 25.0863 233.117 32.0104 \n", - "2020-03-09 12:14:38 71.3468 25.0874 234.745 32.0000 \n", - "2020-03-09 12:14:39 71.3258 25.0897 205.254 32.0104 \n", - "2020-03-09 12:14:41 71.2725 25.0831 212.095 33.0000 \n", - "\n", - " anomaly changepoint \n", - "datetime \n", - "2020-03-09 12:14:36 0.0 0.0 \n", - "2020-03-09 12:14:37 0.0 0.0 \n", - "2020-03-09 12:14:38 0.0 0.0 \n", - "2020-03-09 12:14:39 0.0 0.0 \n", - "2020-03-09 12:14:41 0.0 0.0 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# dataset characteristics printing\n", - "print(f'A number of datasets in the SkAB v1.0: {len(list_of_df)}\\n')\n", - "print(f'Shape of the random dataset: {list_of_df[0].shape}\\n')\n", - "n_cp = sum([len(df[df.changepoint==1.]) for df in list_of_df])\n", - "n_outlier = sum([len(df[df.anomaly==1.]) for df in list_of_df])\n", - "print(f'A number of changepoints in the SkAB v1.0: {n_cp}\\n')\n", - "print(f'A number of outliers in the SkAB v1.0: {n_outlier}\\n')\n", - "print(f'Head of the random dataset:')\n", - "display(list_of_df[0].head())" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# random dataset visualizing\n", - "list_of_df[0].plot(figsize=(12,6))\n", - "plt.xlabel('Time')\n", - "plt.ylabel('Value')\n", - "plt.title('Signals')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Labels" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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AzM/M32fmK8D1wNGdxpwOfCcznwPIzGdqG6YkqTBOxVBd2RFWcbpSCO8CPNlhe1F1X0dvBt4cEb+IiF9FxBG1ClCS1IkdYbWSQk+0zO2y2+TUiM14nT2AccAg4J6IGJmZz3ccFBETgAkAgwcPrtGhJalsXDVCrcSOsIrTlY7wU8CuHbYHVfd1tAiYnJkrM3MB8CiVwngtmTkxM9szs33gwIFbGrMklZsdYbUS5wirQF0phGcCe0TE0IjYBjgBmNxpzA+pdIOJiJ2oTJX4fe3ClCT9hR1htZICb6jhSV7pbbIQzsxVwJnAncDDwI2ZOTciLoiIo6rD7gSWRcQ84G7gnMxcVq+gJanU7AirlThHWAXq0hzhzJwCTOm07/wOjxP4ZPWPJKmu7AhLteAcYXlnOUlqNnaE1UqcI6wCWQhLUtOxI6xWUmAhbCVcehbCktRs7AirlRTZEfYkr/QshCWp6dgRVispsiNsbpedhbAkNRs7wmolRZ5omdqlZyEsSU3HjrBaiR1hFcdCWJKajR1htRLnCKtAFsKS1HTsCKuVuGqEimMhLEnNxsJUrcSOsApkISxJTceOsFqJc4RVHAthSWo2zhFWKym0I1zYodVNWAhLkjbOjrDqyo6wimMhLEnNxo6wWkmh6wib22VnISxJTcc5wmoldoRVHAthSWo2doTVSoqcI1zYkdVdWAhLUtOxI6xWUmQhbG6XnYWwJDUbO8JqJYV2hM3tsrMQlqSmY0dYqgWnRqhLhXBEHBERv42I+RFx7kbGvS8iMiLaaxeiJGktdoTVSuwIq0CbLIQjog34DvAuYDhwYkQMX8+4fsA/AvfWOkhJUkd2hNVKvFhOxelKR/gAYH5m/j4zXwGuB45ez7j/B/wrsKKG8UmSOrMjrFZS6ImWuV12XSmEdwGe7LC9qLpvjYjYF9g1M2+vYWySpPWyI6xW4i2WVZytvlguInoA/wZ8qgtjJ0TErIiYtXTp0q09tCSVkx1htZIiT7SshEuvK4XwU8CuHbYHVfet1g/YG5gWEQuBscDk9V0wl5kTM7M9M9sHDhy45VFLkiRtJecIqyuF8Exgj4gYGhHbACcAk1c/mZnLM3OnzBySmUOAXwFHZeasukQsSaVX1NQIywbVgxfLqTibLIQzcxVwJnAn8DBwY2bOjYgLIuKoegcoSerEqRFqJS6fpgL17MqgzJwCTOm07/wNjB239WFJkjas0R3hxh5OZWMhrOJ4ZzlJajZ2hNVKCu0Iq+wshCWp6bh8mlqJ6wirOBbCktRsGv7ZnZ3+lmrIOcIqkIWwJDUdO8JqJXaEVRwLYUlqNkXNEbYgVj04R1gFshCWpKZjR1itxKkRKo6FsCQ1GzvCaiVF5pU5XXoWwpLUdIrqCFs0qB7sCKs4FsKS1GzsCKuVdEyrBueYc4RlISxJTceOsFpJh7zyZjFqMAthSWo2doTVStbKq0Z3hM3psrMQlqSmY0dYrcSOsIpjISxJzcaOsFpJkR1hU7r0LIQlqenYEVYrKa4jHFbCpWchLElNIF97rcOGHWG1kEI7wuZ02VkIS1ITyAKLBTvCqq8i5wh3DMP8LiMLYUlqAmsVwkV9YFsoqB66y6oR5ncpWQhLUhPIfK3jVqMPXsxxVRIFzhGmwN+0qFvoUiEcEUdExG8jYn5EnLue5z8ZEfMiYk5E/Cwidqt9qJJUXsV2hJ0jrDoqtCO8oThUFpsshCOiDfgO8C5gOHBiRAzvNOw3QHtmjgJuAr5W60AlqcycI6zW1Q1O8tZ5rLLoSkf4AGB+Zv4+M18BrgeO7jggM+/OzJerm78CBtU2TEkqt7WmRjT889qOsOqoW5zkdY5DZdGVQngX4MkO24uq+zbkI8AdWxOUJGlt3aMjLNWDHWEVp2ctXywi/g/QDhy8gecnABMABg8eXMtDS1Jrc46wWlV3Ockzv0upKx3hp4BdO2wPqu5bS0S8EzgPOCoz/7y+F8rMiZnZnpntAwcO3JJ4JamUukdH2EJB9dANTvLWeayy6EohPBPYIyKGRsQ2wAnA5I4DImIf4HIqRfAztQ9Tkspt7TnCdoTVQrrFSV7nOFQWmyyEM3MVcCZwJ/AwcGNmzo2ICyLiqOqwrwN9gR9ExOyImLyBl5MkbQE7wmpd3aUjrDLq0hzhzJwCTOm07/wOj99Z47gkSR24jrBaVpFpVeQJproF7ywnSU3AjrBaVzc4ySvk2OoOLIQlqQnYEVbL6hYneQUcW92ChbAkNQE7wmpd3eAkr5BjqzuwEJakZmBHWK2qW5zkFXBsdQsWwpIkSZ7olZKFsCQ1g47rCDs1Qi2lG/y2Y53HKgsLYUlqAl4sp5bVXaZGmN+lZCEsSU2g2IvlCjquSqIbnOSptCyEJakJeItltSw7wiqQhbAkNQGXT1Pr6i7FqPldRhbCktQEnCOsltUtTvI6x6GysBCWpKZQ4Ie0HWHVVTc4yVvnscrCQliSmsFr3aBYsE5QPdgRVoEshCWpCWSRnSs7wqqrbnCSt85jlYWFsCQ1AecIq2XZEVaBLIQlqQmkd5ZTy+oGJ3nrPFZZWAhLUhOwI6yWZUdYBepSIRwRR0TEbyNifkScu57ne0fEDdXn742IITWPVJLKrFsUCxYKqjM7wmqwTRbCEdEGfAd4FzAcODEihnca9hHgucz8G+CbwL/WOlBJKjPvLKeWVWRe2REuva50hA8A5mfm7zPzFeB64OhOY44Gvld9fBNwaERE7cKUpHJb+zPajrBaSTeY9rPOY5VFzy6M2QV4ssP2IuDADY3JzFURsRzYEXi2FkHWytMLHuHxuy4pOgxJ2mw9XnmRN67emHsrPPto4w6+5KHK3y89Az85v3HHVTk888hfHv/y27DtDo079v8+tObh/deez5/btm/csUupB2/5h+5Vh3WlEK6ZiJgATAAYPHhwIw8NwAvPPME+T9/Q8ONKUi2sjDZ68SosnF7502irVsC9lzf+uCqHaIM5NxZy6FeyjeFLbivk2GXyGj2A5iuEnwJ27bA9qLpvfWMWRURPoD+wrPMLZeZEYCJAe3t7w38HsdeBh8GB3apJLUmSCrZN0QGoMF2ZIzwT2CMihkbENsAJwOROYyYDH64+Pg6Ymumsc0mSJHVfm+wIV+f8ngncCbQBV2Xm3Ii4AJiVmZOBK4H/jIj5wB+oFMuSJElSt9WlOcKZOQWY0mnf+R0erwDeX9vQJEmSpPrxznKSJEkqJQthSZIklVIUdU1bRCwFHi/k4JtvJ7rZmshqKeaX6sn8Ur2ZY6qnWuXXbpk5sPPOwgrhZhIRszKzveg41JrML9WT+aV6M8dUT/XOL6dGSJIkqZQshCVJklRKFsJdM7HoANTSzC/Vk/mlejPHVE91zS/nCEuSJKmU7AhLkiSplCyEgYgYVHQMam0RsW3RMah1+R6meoqIXkXHoNYWEW+s/h2NPnapC+GI6BsR/wbcFRGDi45HraeaY5cC/xERR0RE/6JjUuvwPUz1FBH9IuIS4MKIGFt0PGo9EbF99T3szojYMQuYr1vaQjgi3gHMAnoC7Zn5RMEhqTV9C9gGuAU4ETi30GjUMnwPUz1Vu8BXUKkTHgM+HxETio1KrSQijgLmAi8Db83MZUXE0bOIg3YTfwKeB87NzJcjYgSwNDOfKTYstYqI2Al4I3B8Zr4UEfOBsyPi9My8ouDw1Pxewfcw1c/rgaGZeQJARDwNHB4RR2Xm5GJDU4t4BWjLzM8DRMTfAEsy88VGBlGaVSMiYiiwd2b+uMO+bwH9gIHAXwF/BO4Avtfo/wg1v+oP8WnATOD2zFwREXcBUzLzWxHRGzgCOBU4JTP/UGC4ajIbyK9LgO3wPUxbqZpfZwGzgR9UT97vAP4rM6+JiNcBJwB7Ap83v7S5NpBjPwKWUfnN6c7Aa8DFwNTMXNGIuEoxNSIiPgE8DJwVEQd3eOoiYHcq3/BxVNaq2wN4d6NjVPOKivOpTH9YAYwHrqk+/S3giIgYkJl/BuYAC4B9CwhVTWgD+XVt9Wnfw7TVIuIC4GZgMfAe4MbqUzcDfxsRfasn7g8ACbyhkEDVtNaTYzdXn/oUcDBwX2YeBtwOHA7s06jYyjI14gkqXbjtgSMj4peZuTIzF0XECZm5BCAzfxQRx1GZryJ11Ruo/IrnqMxcGBHbAw9HxJuAe6j80H8G+GxmLoiIIVQ6d1JXbCi/9srMRyLixMz8X/A9TJuvegHvQuCwzFxSvejyK9WnfwmMoXLydWl1+2LgsoYHqqa1oRyLiO0yc35EHJyZi6rDLwXuBq5vVHyl6AgDP87Ma4HfAtsCfw+VTsvqIri6PRoYDDxbSJRqVs8AN1SLlG2AV4FfAC9n5ktUusLvi4hjq1deDwQavkSMmtb68ms68BLA6iIYfA/T5svM5cDV1QJlf+BeoG9EfAGYD0wGPhQR44BRwHOUp3ZQDWwgx7YHPld9flGH4WP4y/UPDdFSyVz9kFhHZq6sPryfyq+mx0XErpmZEdEWEQMjYjJwOXBZZs5oUMhqMuvLscx8NTMXVB+/AvQBRlOZ60RmPkbl1z8HUrkK+7LM/GXDglbT2Iz8GkPlw2L11Imdq3PtfA/TBm3kMzKrz70ROAf4ILAf8NHMvItKl+5DwA+oFDQPNyhkNZnNyLGTgJERcXb16wZFxC1UfttwVSNzrGUulouILwJDgf8G7lq9DEdEHF7dzur2vlR+yO/PzGsjYmBmLo2I8Zk5qZjo1Qw2kmNHAHd2yLFjgJMz833VxcF7N2rSv5rXluRXdbtP9cI538O0QV3Nrw7jDwX+PTP3rG73rl7nIK3XFubYpcBwYEfg7zNzYkODpgU6whExOiJ+DQwCbqVS5L4vInpExD7ALkDvakFCZt4PTAU+EREvA8dW908qIn51f13IsTdSybHVP0/9gdsj4ljgESpzhKX12pr8iohHgfeC72Fav67m13q+dFcqedYTwCJYG7KVOXYH0CMzny2iCIbWuFjuReD7mXkpQETsChyQmRMj4sHM/M3qgdUf6J2otN6fBN6VmT8vImg1lS7nWNX7qCyTdjtwWmb+T2PDVZPZmvz6iPmlTdicz8gBwN7AF6u7Pp2Zqxocr5rP1ubYqw2Ody1N1xGOiNdVOyFt1V0LgKtXd3yprLHZPyJ6dvwBrv5aZxXwAnBBZv6tRbDWZytyrE/14Wzg1Mw81iJFnZlfqqetyK+ewHLgzVTWDn5n9Teo0lpaLceaqiMclWWBrgYeBHpRXeswMzsuRXUosLDTN38vKle9XpKZi4ErGxe1mslW5tj4iPhqZp7fwJDVRMwv1dPW5hfwtcy8qmEBq+m0Yo41VSFM5e4jn6CyBuvBEfHz6nIcQWWOyatUlg6aDBAR7VTOVBYDF6V38tKmbU2Ofa26TIy0IeaX6mlr88vPSG1Ky+VYt50a0aHF3tH/ZOaVVO4S92fg/VBZloPqUlVUJmQPiohrgfOAPpm5vDt+81Usc0z1ZH6pnswv1VtZcqxbFsLVeSXrrOvWoc3+EJU5KKOrVySuXqNuNyprHU6g8p91bGY+1ai41TzMMdWT+aV6Mr9Ub2XKsW5XCEfEx6ks2fKx1d/czmcl1db7LCqt9nHVMW/MzMepLNR8cGZ6C0itlzmmejK/VE/ml+qtbDnWrQrhiDiNypqYX6Jy16TPRsSo6llGW8exWblb123AkRHxIvB/q/u/kZXb2krrMMdUT+aX6sn8Ur2VMccKv7Pc6uU1qmcbNwETM/POiNiRypWJL2fmCZ2/BmgDpgPbAedn5s2Njl3NwRxTPZlfqifzS/VW9hwrrCMcET0j4iLgGxFxeHUuygzgn6pDlgMLgT2ickvRNa35zFyVlbvcXJWZI5r1m6/6MsdUT+aX6sn8Ur2ZYxWFdISr38jvAH9F5fZ6pwA3A98DfkbltrT7UzkTeQnon5lf6/D1PTLztc6vK61mjqmezC/Vk/mlejPH/qKodYT7AWOAwzPzxYhYBhwJHAwcBIwEembm/RHxRSrr1hERkRUt8c1XXZljqifzS/VkfqnezLGqQqZGZOYLVNrt46u7plNZhuNI4A2ZOaf6ze9L5T/j8erXFTuhWU3DHFM9mV+qJ/NL9WaO/UWRq0bcCoyJiL+uXl04B1gBvD4qxgO/AH6fmZMLjFPNyxxTPZlfqifzS/VmjlFsITwdeJbq2Uhm3g8cAPStnnHMBg7LzHOKClBNzxxTPZlfqifzS/VmjlHcHGEyc3FE/Ai4MCLmU2nJrwBWVZ+fXVRsag3mmOrJ/FI9mV+qN3OsojusI/wuKveqPgi4NDMvLTQgtRxzTPVkfqmezC/VW9lzrPBCGCAielGZg71qk4OlLWCOqZ7ML9WT+aV6K3OOdYtCWJIkSWq0Ii+WkyRJkgpjISxJkqRSshCWJElSKVkIS5IkqZQshCVJklRKFsKS1AAR8cWI+KeNPH9MRAzvwuusNS4iLoiId9YqTkkqEwthSeoejgE2WQh3HpeZ52fmT+sUkyS1NAthSaqTiDgvIh6NiOnAntV9p0fEzIh4ICJujojtIuIg4Cjg6xExOyLeVP3z3xFxX0T8T0TstYFxkyLiuOprL4yIr1afmxUR+0bEnRHxu4g4o0Nc51RjmBMRXyrgWyNJ3ULPogOQpFYUEfsBJwBjqLzX3g/cB9ySmVdUx3wZ+EhmXhIRk4HbMvOm6nM/A87IzMci4kDg3zPzkPWM63zoJzJzTER8E5gEvBXoAzwEfDciDgP2AA4AApgcEW/PzHvq9b2QpO7KQliS6uNtwK2Z+TJAtYAF2LtaAA8A+gJ3dv7CiOgLHAT8oEOh27uLx119nAeBvpn5IvBiRPw5IgYAh1X//KY6ri+VwthCWFLpWAhLUmNNAo7JzAciYjwwbj1jegDPZ+aYLXj9P1f/fq3D49XbPal0gb+amZdvwWtLUktxjrAk1cc9wDERsW1E9AOOrO7vByyOiF7ASR3Gv1h9jsx8AVgQEe8HiIrRncdtoTuBU6tdZyJil4jYeSteT5KaloWwJNVBZt4P3AA8ANwBzKw+9c/AvcAvgEc6fMn1wDkR8ZuIeBOVIvkjEfEAMBc4egPjNjeuu4BrgRkR8SBwE1tXWEtS04rMLDoGSZIkqeHsCEuSJKmULIQlSZJUShbCkiRJKiULYUmSJJWShbAkSZJKyUJYkiRJpWQhLEmSpFKyEJYkSVIp/X9WVDw+4MJ+SQAAAABJRU5ErkJggg==\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# plotting the labels both for outlier and changepoint detection problems\n", - "list_of_df[0].anomaly.plot(figsize=(12,3))\n", - "list_of_df[0].changepoint.plot()\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Method applying" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# classifier initializing\n", - "t2 = T2(scaling=True, using_PCA=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# inference\n", - "predicted_outlier, predicted_cp = [], []\n", - "for df in list_of_df:\n", - " X_train = df[:400].drop(['anomaly','changepoint'], axis=1)\n", - " \n", - " # classifier fitting\n", - " t2.fit(X_train)\n", - " \n", - " # results predicting\n", - " t2.predict(df.drop(['anomaly','changepoint'], axis=1), window_size=5, plot_fig=False)\n", - " prediction = pd.Series(((t2.T2>t2.T2_UCL) | (t2.Q>t2.Q_UCL)).astype(int)[0], \n", - " index=df.index).fillna(0)\n", - " \n", - " # predicted outliers saving\n", - " predicted_outlier.append(prediction)\n", - " \n", - " # predicted CPs saving\n", - " prediction_cp = abs(prediction.diff())\n", - " prediction_cp[0] = prediction[0]\n", - " predicted_cp.append(prediction_cp)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# true outlier indices selection\n", - "true_outlier = [df.anomaly for df in list_of_df]\n", - "\n", - "predicted_outlier[0].plot(figsize=(12,3), label='predictions', marker='o', markersize=5)\n", - "true_outlier[0].plot(marker='o', markersize=2)\n", - "plt.legend();" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# true changepoint indices selection\n", - "true_cp = [df.changepoint for df in list_of_df]\n", - "\n", - "predicted_cp[0].plot(figsize=(12,3), label='predictions', marker='o', markersize=5)\n", - "true_cp[0].plot(marker='o', markersize=2)\n", - "plt.legend();" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Metrics calculation" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "False Alarm Rate 13.95 %\n", - "Missing Alarm Rate 36.32 %\n", - "F1 metric 0.67\n" - ] - } - ], - "source": [ - "# binary classification metrics calculation\n", - "binary = evaluating_change_point(true_outlier, predicted_outlier, metric='binary', numenta_time='30 sec')" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Average delay 0 days 00:00:09.900000\n", - "A number of missed CPs = 90\n" - ] - } - ], - "source": [ - "# average detection delay metric calculation\n", - "add = evaluating_change_point(true_cp, predicted_cp, metric='average_delay', numenta_time='30 sec')" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Intersection of the windows of too wide widths for dataset 16\n", - "Intersection of the windows of too wide widths for dataset 16\n", - "Intersection of the windows of too wide widths for dataset 16\n", - "Intersection of the windows of too wide widths for dataset 18\n", - "Intersection of the windows of too wide widths for dataset 18\n", - "Intersection of the windows of too wide widths for dataset 18\n", - "Intersection of the windows of too wide widths for dataset 19\n", - "Intersection of the windows of too wide widths for dataset 19\n", - "Intersection of the windows of too wide widths for dataset 19\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 23\n", - "Intersection of the windows of too wide widths for dataset 27\n", - "Intersection of the windows of too wide widths for dataset 27\n", - "Intersection of the windows of too wide widths for dataset 27\n", - "Intersection of the windows of too wide widths for dataset 32\n", - "Intersection of the windows of too wide widths for dataset 32\n", - "Intersection of the windows of too wide widths for dataset 32\n", - "Standart - 26.71\n", - "LowFP - 22.42\n", - "LowFN - 28.32\n" - ] - } - ], - "source": [ - "# nab metric calculation\n", - "nab = evaluating_change_point(true_cp, predicted_cp, metric='nab', numenta_time='30 sec')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## [Additional] localization" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.2" - }, - "toc": { - "base_numbering": 1, - "nav_menu": {}, - "number_sections": true, - "sideBar": true, - "skip_h1_title": false, - "title_cell": "Table of Contents", - "title_sidebar": "Contents", - "toc_cell": false, - "toc_position": {}, - "toc_section_display": true, - "toc_window_display": false - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/notebooks/lstm.ipynb b/notebooks/lstm.ipynb index 574f413..fa203d3 100644 --- a/notebooks/lstm.ipynb +++ b/notebooks/lstm.ipynb @@ -20,8 +20,7 @@ "\n", "# additional modules\n", "import sys\n", - "sys.path.append('../utils')\n", - "from evaluating import evaluating_change_point" + "sys.path.append('../utils')" ] }, { @@ -71,6 +70,13 @@ "## Data description and visualization" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We are working now with SKAB v0.9. The current version of SKAB (v0.9) contains 34 datasets with collective anomalies. But the update to v1.0 will contain 300+ additional files with point and collective anomalies." + ] + }, { "cell_type": "code", "execution_count": 4, @@ -80,13 +86,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "A number of datasets in the SkAB v1.0: 34\n", + "A number of datasets in the SKAB v0.9: 34\n", "\n", "Shape of the random dataset: (1154, 10)\n", "\n", - "A number of changepoints in the SkAB v1.0: 130\n", + "A number of changepoints in the SKAB v0.9: 129\n", "\n", - "A number of outliers in the SkAB v1.0: 13241\n", + "A number of outliers in the SKAB v0.9: 13067\n", "\n", "Head of the random dataset:\n" ] @@ -239,12 +245,12 @@ ], "source": [ "# dataset characteristics printing\n", - "print(f'A number of datasets in the SkAB v1.0: {len(list_of_df)}\\n')\n", + "print(f'A number of datasets in the SKAB v0.9: {len(list_of_df)}\\n')\n", "print(f'Shape of the random dataset: {list_of_df[0].shape}\\n')\n", "n_cp = sum([len(df[df.changepoint==1.]) for df in list_of_df])\n", "n_outlier = sum([len(df[df.anomaly==1.]) for df in list_of_df])\n", - "print(f'A number of changepoints in the SkAB v1.0: {n_cp}\\n')\n", - "print(f'A number of outliers in the SkAB v1.0: {n_outlier}\\n')\n", + "print(f'A number of changepoints in the SKAB v0.9: {n_cp}\\n')\n", + "print(f'A number of outliers in the SKAB v0.9: {n_outlier}\\n')\n", "print(f'Head of the random dataset:')\n", "display(list_of_df[0].head())" ] @@ -256,7 +262,7 @@ "outputs": [ { "data": { - "image/png": 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6CCtXrozbDYIJDCsf/jue+cdKFBUVYeTIkXj99dcBKK4s9913H0aPHo19+/Zh1apVWLFiBYqKilA8awLefO9tgFsbkaPHyjFk/HA89NSjuOuuuzBgwADU11vdckaPHo1Ro0Zh9erVkFqCWoM0cuRIXHrppZb07733HgoKClBUVIQ5c+bgvvvuQ58+0QWS1BiA7O+4SCja1ZpDWHcnkRkvDkWWAzH6t20QDlWrdqDx87JWHxcLIUWZ+BqqtbopqcgBCf7dNah5pWdbrYJlyqhIy9dVcR8Tr0U7fiIvfuCA8k2rncl2fQGhji5n+2BiuNnkpt8dTOPnZVrHRI/cGNTua1vi5fOghFBVC+TmECTdt1G1eidavon//ekIZL+Eure+ReVT7bfeO6GOlKr/Qmj7GgO+fbUIHmvWfgcrmnH0L5sgNXaeSJebQmj436GoaZo+K4PcFETLtspOKwegdH7qPzwIQDEgOdH4RRka1n6HhrXfQapR0gWPNqFh3SEcuv1T2/f6ROC4OBIxxvIAjAbwOYCpAH7GGLsEwCYoVuwaKGL7M91hhxBdgHdL1Cgaem688Ubt77/+9a+GfePHj8dnnymXrQ4nC4KAu+++G3fffbchbXp6uubGIAgC/njrHfjjrXfAMyBVSzN9+nRMnz5d+52QkIBnnnnGUqalS5di6dKl2u/S0lLLPtkXwuCT8vDW6tfh7m3siU6dOtUSNu/dd99VruNwg9bYrFy50pCmT6/e+HajEgFEX25A8cXW8+abbyr5HWrAlvc+gxn9Nfz1r3+13NtYqI2JuRx2yP4Qal7ajYx5p0BM89gnClfY5uqay91LEEQlSgPtP1iPise2IvvSEUjMz7ZN05ZhvZavKtHyVSVSJvZt9bHREFPckBuDynM+yT5NqFxpHJk3uqWW27godUtiaAX98+lwQc1s/lbPp/7Lgdp/f4uk4l4xrbrcpkPeWfh218DVKwmujNjGBrOfOxM7ZxGo2n/tBaCMiFjuhSYOjZsbPj0M7peQNtPhhYcyIhPYH+7wSJF3oGVrBVq2VnTKCIwckFD+wGZkLhwKV3YCQlU+JJycAR7uLMmBzqkjQ1UtOHrfJmQtHgYhSelgs3b0f1RXNvUeNa47jFBFC1q+rurw+qtVqK9HJ69HVvfWt5FTRjMUqR1pv2QoU8tXlUBIRqiiBd68ts8n6K50+gwYxlgKgFcA/IJzXg/gcQAnAygGUAbgL63M72rG2CbG2KaKioqOLu5xgYdkQ0XW3eCcQ2oOapV26wVh+AvqvpfYappLKtCyvQr1HxyIndgsSnuAhbrmlT2OVmLf7hr49tQgcFDp8Pn31Dpn1I3eayFF6fhI9c7WI9Xa5Iox3Hz4d+s7rmBthAelKCLYvjNnQfd8OrOTwGX13/C7r7rfNATQuO4wKp/ejto39kUVzTzWaEgHUvn0dpQ/pLjBNa4/EtWCZpk4ehwmklqs9JqAMj7xuje/Rf170esoVUwD0J5LZ/u3ho41Q6rxo+7tb3H0/s2RORbh6+qsTok6n6W5pCJyz9phoTajtuOdNUrR0Z1K375aNH1xtEPyiqZhWPgeW94rdXs3aic6kk6tCRhjbihiehXn/FUA4JyXc84lzrkM4ClE3DoOAxioO3xAeJsBzvmTnPNxnPNxubm5nVn8TiN4tAnB8ubYCeOkoz86uSkIqdoHqTE8Ma2N7z43DfQeT4tTR6MNrUa7Fw7CuVv5FTvQtPGoZhEDYBijr3x6OyrjnDDHdfcnnufdmQ252khHE2ZyePKlkNT9Z/0f/t16HPk/60gNgLgtVDyks1B3tFVQf25VAKqWKlMDKjcG0bj+CORme5erUI0PoWpnV53OgLcoZal9Yx8qnojiguAy3mT1PZMaA6h89mtU/L39E3LNdYbZgqt9N+3Uhtp5OlngMLciNXhQNnQOVAs1iyFyW3ZW2072jn3iSL6Re9aBglp1vemADkHz1mOQ6kzvfJxth1bXxihG5VNftXlSpqU+D0Upm9rBkLmhUJE6WUbNq3sQqmzd5MbuTmdG+WAAVgDYwTn/q267flzkfABqS/0GgIsZY17G2GAApwL4orPK1+V04xmvkUrWJIglOT5RrH4/5qQdfMk8JHeoD3RUnHrcallkDtkfFm4MCJY3ofELxeLbEwS1RvjZ2ZZY3RftHdA3zHG00fw4+Mc6nYPLXPN99O+pRc1re7uk09eaToU6scoRG7Eg1fu1d5DbiJkOQy9e1LxVTw+Hb8ApWsDRP23EsYdiT5xuK/6D9XFHyPDtq8WhWz/W3hWz+FMt1mV3fQ7fjmr499Y65hXvszZ3Ai0jE5o2jJRFq39agdrR6fQ6Sn0PnK4rhiCtWvk1yh9sx/vAEbGGd6CFWmsj2ymoeVBG9epdls5Ya7/ReEsRONyIlp3VMdPJ/hD86mTpkFUPOJZDFc5m0R2+9/7SejR9cRTVL7Qu6k93pzMt1FMB/ATATFOIvD8zxr5ijG0DMAPAMgDgnH8N4EUA3wB4F8D17YnwcSIh+0LRG/oOqAvloIxgRbNjhS8HJATLmhwtSvblil4wu9B5rSF4tAmhirb1cFstnNQvxeH+VD37NSoe36r9Ln/4S9S+Grb4dvPhLX3FqFXINvcnnglQhvdH93f9Bwdx6NaPLfe94yfGKUj1AfjViXEOjVL9+wfQuC4yCNb0WRlCVc4TbTqahv8dQuC7hpjfSVw4ZCE1BVF29xeoe2e/kkzv8tHRLhX661AFlMnlw1K+KBObOgselFHx2FYcuXODZTKZ3bvSuE6ZEBY4FI5Q5DCMHRe6YwNHGlG/9jv7ZGbhaX5WmkUycm6ptg33Uu1odbKgtvOVln0h7ftvq8uE/0A9AoejRI7RjDs8Utd0qMtH2ELdzjzVd0oyTaDurOdy7JEvUbXy65jpqp/fiYrl2yA3By0uYhaxrEftYDh9K2pHLu4S9ww6M8rHJ5xzxjkfxTkvDv/3b875TzjnheHt8zjnZbpj/o9zfjLnfBjn/J3OKtvxRA5KCNX522z5kn0hhCpbIDdG4gLLQcloXemABlmq84P7w/naZKdW6HE1wo4WauOGUBxuL93FTcTRJyyMb1eNLjEMDVV3t1DLsayeKqbnyoMy/PvrjNenn/Qmc3DOUfduKer/e8BwrJYmTkF99C+bcPSvm61lbw7a+kiXP7hZs+bqzxE82oS6/ypxzu1mxMv1x8/NoO6d/Uoovg4ZrbIf8lWHkP17w++nrhGsXLG9Y11u7N7zGD66oU4S1MGKZvi/tfeD1ovVyhXbDXWMXf2mib6w24LlOltRR+nvQ8VTX6H+3VLbyDlH7zEOzjpZqPUiui0uPO11+QjVxH5+nHPNb1cvyo7cuaHdIrfi8a049siXUU6ulkHnXtJG7WvbFqkuTe39jNT7by6broN36NaPLesD+PbUhDvl4Q0d6M4C6DqRIRmy6R2MpgU0C7UkQ1/pq8XT3rs4blyosgX1HxzsNlogGsdhNsX3G6nKB7kh0OaJaWoloK9QQ+XNHe97ZJgcEq4kDAUJ/xvXB6v5BsRMGWtyQuhYx/maG09sLEPMTg9z6HHbJzbk3RXuPS07qlD90u640nL9ULFW4yn/2A6Lcw6pKYjDd65HxfJt8O2sgtQUBOfcIq65X0KD3gpnuhfNm+KbIBOqaLF9F8ru+QJld39u2a4fSdF/OxV//woNHxxUrtlmmDbaBMbOgrfTSC+3hCA12C/Eo4nBcLxp8/fWkW4fdqJZ+6YcvnO7zly8DWfwaBMCZfZ+teV/2YyKJ+39oPWiLljebHBNsos2YRbUlg5ya25h+B41bSrXfLbr34890dliHQzfo/r3D8K3K/bQvSOqpTCatTFM8GgTQjof3+atFTj6p43wheNyOx53qDEyEc50HincgY3XBzl4rFk7Jh70z6o14p2HZGtnweY5a99TGzokUlMQwfImSznN5TAcY7JgV67YrsXHB9BhUT6khoASglMNTBCULZ26qMY1zRJtbBO0MJqtuF8Vz2xH/X8PQHao47oTJKg7iddeew2MMezYbfQRak0vSw5Ihg+otLQUBQUF1oQdMWKs/3DtLNSmSQ+vvfaaJWyehpOe5sDqf72AsWdOxpgfTMIZC36ALzdG/OJEUURxcTEKCgpw3nnnoba2Fjwoo/S7A/AOTMPtt9+upa2srETy4Cz8/PabAAC7du3C9OnTUVxcjPz8fFx99dUxLjhSOKnWD7khEN0/VU0fjzjWVWo8KBsrlOPUy6569hs0by6H3BxULBhRsBfNyj9H7twQ2aYPf7S1Qusk+g80oOyPn6HxkyMWC7XZr9MsuurfPxjH1TijVvLBY83wf1trn8jwbivnl32S7TLf8Qhq2ReC3NI+330n15i2UPanjYZwVobzhO+/JqjNfpAd6XJjJwq0BtRBMNi5fcUh7gCg/MEtbfKzNnYgYagLolmo6978VqknzZ2S1vjASxyyL6Qt4gQooddijWJZrM+65K1dLMdcHuXf2O9B+YNbDJZzNdZ40KFToxItdn3waLiTbBLUVc/vQHPJMaVsuudT/tfNKLu7FVOr1OviPNLGmQQ1l7nlO6h5bS+O/mmjoW60vUftcJk59mgJyh/YopVBwVS2ePPt4Hal8tmvUfWPb7T6m4dky7cRdU0CvcuXnbbQLNSxyxJz3kg3ggR1J7F69WqcdtppePH1lwDoKoVWvPc83kkmDnnaLfRie7iN76Plb3VEKlwZmQW11ByMhBCKZGw4TzAYRN7APLz/0r+x5f3P8Juf/xrXXH+ttl9denz79u3IysoyLD2ed1Ie3n77be33Sy+9hBFD87Xy33jjjVi2bJm2PPoNN9wQ46L11293wabkasWpPkZJRu0b+2wFmMGILxlDJDoJmPYOvVc9vwOHbv3Ysr3iya9w7NGS6OHJ1ApLZJHOkF2oxPCF+fbUaqvEAUAw3KD7dlZZhCI3i3WncrRzUk/5Xzej4kn76Ar6e87cirCUW0K2VjHLLHsbjty5AUf+34aY6aKi73i008fecI9NI0hqIxgR1KZzSbLSWHbAKIpt4x9DUMsNAfj21Bi2WUR2rMglrRQTenHKBGaMzW1T56r3LPBdA1q+rrReS2vOL9u7gMUaKbDcE8N3phbDagmMhdME9I4k2qCmGrnD7EPdsq0S1WvCxqh2vJv6ybHaSINJUNe8vBuHf/ep9rv+g4No3hReTVTfkbF5RvHeP6k+YHlPDfMH4rRQ6++F3Nx+i63Tt6PVg2q7F7CxUOu+laYt5Wj5WudCp7WTuvedw1ofxPXttN6q3VWQoO5gZF8IDXX1+OSTT7BixQq8+PorAAApJOFXv/oVCkcVYuyZk/HoM08AADZu3IgpU6agqKgIU8+djobGBkiShJtvvhmTzpiCsWdOxlP/fNp4EsYgSRJuvet2TDnnDBSNKdaWOl+7di2mTZuGefPmYcSIEfD5fLjssstQWFiI0aNHawvPrFy5EgsWLMCZZ56JwYMH47GVy/Hgk3/D2EnjMPXM01FdUw1IMvaVfotzl5yPCdMnY+YP52Dn7p1Yv3493njjDdx8880oLi7G3l17sHvLN5h75hyMHTsWMxaciZ17dwNcWXzlmmuuwcSJE3HLb27B5HETkZmhrDk+cfR4HD6iTAozTw6aPHkyDh+OTBhLSkhEfn4+Nm3aBAB44YUXsPDc8IqUHCgrK8OAAZFlTQsLC+N/aFE8VAJlTTh068cIHAzHbg1XCL49tWhcfwQ1r0ePDMGDsqGy9O2oxrHHSqyVQ5RGo+6/B1D3bmnUS3BaIUsLNWU2cOkiXKhWGFVsAojaQJgnkmnWWsYMx3GZW4f0HepEO2txR6FvlLRh+5ZQJLSTDqkhAP+34agODfG5fwSPNcN/sD52Qn2ZdM9fPz+io1EtTIJH9f81NYpBGYdv/zTu2fa1b+xD7b/32+6z64Spwk5usr/Glu1VqHx6u8HaZel02ggybhAWIW1b46eHY67madgf8XCz7rMpDw9yq1i1cwVw+p5lbvttGaKvmCfucqsF1WBVl2Q0bTxq7KTF68rTyVE+6j86iKrVOx33a24VUdww2jrxXPaFIiMyOgu1en+lej+4zNG8xWgJb/w00u7o32nbjpAqEG3e/eqXduPYYyWQ6vwou/tz1L6+z5JGPa+jWDRH2tL7oP9BF0JTTdbazkdIRsWT2yzzDQSvMYyoEgPfPFE2UuaaF3ej6h87dDsjI7oGg5LmQtIKq7P6CLvZiql2dP/gqz0IzjlClS149Y2XMXfuXAwdOhTZmVnYsu1LbN73FUpLS/Hl5i3gFX5U11QjEAjgoosuwgsvvIBx48ahaucRJCYkYsWKFUhPT8dn/1uP5mP1mH7+bMyeM0fpZYdkQGR45p/PIT01Devf/h+kdBHTZpyO2bNnAwC2bNmC7du3Y/DgwfjLX/4Cxhi++uor7Ny5E7Nnz8bu3cpw4/bt2/Hll1+iqboBwwrz8X+/+X/Y/NkmLFu2DP98ZTVuvPJ6XHfrz/G3ex7EsJHD8NmnG/CzZTfio3VrMW/ePJx77rlYuHAheFDGzCtm4m9/fggjpxTh03fW4ue3/RLvv/tfAMChQ4ewfv16MMnoE/3Mi//AnBlnAgj7hqmdfUnCBx98gCuuuMJwfy+66CI8/4/nkZ2YAVEU0bd3XxwpLwM4x7JlyzBz5kxMmTIFs2fPxmWXXYaMjIyoz0rF1KYa8IWX4m0OC1atAtU3sharlt6H2lihVIcbF7kxCDE9siqbvgGWGgNgogAhUfk8Gz5Q3CLS5+Y5Xk8suCSDiRHBXP9eKRrWHkLf2ydaRReA2tf3wWcO/+WkEfTuD2YLdRSXD8MziNNCzUOyJr7tQq5xzi3RSAyCOnxs46eHwVw2Fur6ABo+PQJACe2UVJgTs0zl4cmS0VaYk5uDCFX54BkYXpVT11BGWxq91ZguSessObl8hMvRsrUCWDw8ZvaN65V7k3H2YOtOBwu13BxETTR/fh7+hsJlNE9+AlcmLzK3ADFVWaxHb50LVbVATHYjWN6M2je/heC0kqmanT5/xozi1E5Qh3RiX5YtlkrbDrXEbUWi8v7HsFCb76PErVE/dMn9++rQcOA7pP3gpMjGkKzdz2i0xuWjLdT/J7p/uDo65vT9c5k7hsuLZoUPHG7EsUe+jHxvOgu1ej/L7v4CSWN7Rw6SuBJj3OSyp/1tO+nW2Qe9ebNi5Vbrx6bPypBxzpDI5Fb9edW8TbfBEr89hotWa0eaQlU++L+tQ/WLu9D31gnadvPKsWbXRbuyAcq1Cokug6+0vlMTCZ8YGTnQI9X7ETzajIShmZa8OysiVEdyYgvqd24FjrY/yL6BPoXAWfdqPznnCB1rhpjm1V7CF159EctuUXx7L5x/AV54/WUcKD+Ea6+/Fi7RhSD8yMrMwjcl29G3b1+MHz8eXOZIS00DALz33nvYtm0bXn7xJXCJo66hHnu/3YuT++UBXGkD3l/3Ib7asR2v/vt1gAF19fXYs2cPPB4PJkyYgEH9T0Kozo9PPvlEc38YPnw4Bg0apAnqGTNmIDU1FUlCAtJT03DOD84COFAwogDbtm5FY1MjPtv0OX50zSWa6gyErFa7hsYGJd3VPwETBXBJht/v1z6qRYsWQRRFyLqGae36dVi55h/46JV3tXQtvhYUFxfj8OHDyM/Px5lnngmpLCLA586Zi9/99nbkpmZh0fkLAV1RLrvsMsyZMwfvvvsuXn/9dSxfvhxbt26F1+uwlHCc9Y5WQZl9qHUB/S3+tOYK2a4iFhl8u6pR+Y9v0O/2SYZdZXd9DogMA/7vtKhlkxoD4AEZrqyE2BdiKkNLuKMgNwU1lwHmFQ3js76vq0x5OEws008ANAlqi3+2XnzoyxSnhVr2hSCmeMA5x9H7Nln286CsiUf9NhV1X8vXVfAOSbccL9UHIkvLd+CS8ceWb0OovBn97z5NcTPQXXs8biaGiXTHmuHulRTXeTXB4hFR/9F3lk6EvsPjP1gPV7oXLNEFIQ4xZjmXrQUPkQWioh0bzULNgaN/3ggg0mnRu1ppFmo1jxg+2JZJuPpOXpRJiQAgVfvRGO5wRQpgc92SbBVO4bS2oieKcONB2caHWvf+hK28+hGVqBZnnQUhMqnOaPE2u2B01gJMWofPQVBHWwAtmsVS9etW54/oo3xwiWvfhSp61e3MBVM8dX19FcXlI8r90T+Xw7/7FBnzT0bK5H6G64h3UqL6Hjimb+VIg5NItatDrYJa+V33n1Jtm/9gPRKHZUVGbSQe6XTIPOLy4WChPvZoCaS6gPad+w/UR75vslB/D5CU4bhQjQ/u3kmorqnG2k/X4esrdoAJDFIwBAaGcePHWw6V6wL2lTHneOiBB3HmpBmaWBOS3Ph2115Dmgf+cB9mT/+Bts0zIBVr165FcnJyxBIc5fvSxKbMIQhC+DeHwBhCoRBkWUZGejo2/udTMK8I7pe05ZzBgVCdH3JAiqT773qjSJKVHmmiRxV8yr6vdmzHNTf/DG+9/AayM7O1Sj0xQfGhbm5uxpw5c/Doo4/imh9eFrk+jwdjRo3GQ08+gq+2bMPrL/7LcI39+vXD5ZdfjssvvxwFBQXYvn07xo4da72/dr69TmiC2vhba2AEZrVq6QW1U2UphyfkhTiC5c3Wpa/jqBjL7vkCkLjBMsplbhsT1WJN0C8IoRNd0XBc1EZ/L00uH5YJJbKyWEDwaDPcfZJsj4tG3bulyJx/imO4Lu6TLJY5O5cPwNr4iJleJYKAkGq7vz2oISLlxiDENI9xRCIOC7V+6fPyv252tIa3lFSgSubI/pEyv0CtP6SGABo/iQxlp5+Vh7p3Sg2dwYrHInHU+942UbMGx42DBS+eUJtGt4rY6fVuMqpA1kJ7mt5B8/egLw8TTKMmMVw+GuziRtvV4VEWE4rl8qEKEFfvJITKmyH7Q7adDC15uHNhuCfRxIegc82SOOo/OBgJawnlfrIkk6C28x/mkTzaita50T0jvcU/eMh5QnXU98pcBXIeSR+eN2DJLyQDJqOC/l20vadxTEo0dwrq3i01Cuqg7DhCYJ1ErJTH4j+tJguXQw5IqHv7W6TPyYOQ5HYsm9PiRoLJQt244QjcvZONicLnavgo8k0Evq1TBDWPtJPqNejdEiMWamWfb3cNPINSIdUFwpuVkcaq53SBD+KcrNyVnNiCWmdJ7iy0bz88kvfqv1/Hjy64GI/d+xDAGJiLYdb8OSgqLMTy5ctxxmmnAwCqa6ox9ORTUXb0KDZu3IhxY8aiobEBiQmJmDNnDh5/+DGcPmIS3G43dn+7BwMHDzKc98wzZuHJf6zAjKlnaGkGpZyivMC6Cv60007DqlWrMHPmTOzevRsHDx7E0FNOxZYtumE0/ZBnKNKLTEtNQ97AQXjlrX9h4Q8XgnOOrV9txdhpE5CSlIyG2npItX6kZYTTvfEqLjjnfHDO8dWO7SgeOxqyPwS5PqBMWvRJOHj4O1x41RI889BTGDZyuOKPa6pLkpKS8PDDD2PBggW4cv5PDOX8xTU3YNqEKcjKzNJt5vjPu+9ixpQz4ElJQPmxclRVVaF///62z0yq9RsqpKjzIkwWai5zBCtbNJ9qJjDrCmWmFeNsLXecGxYdaNPEGycBI9sJaiVtsLwJYrrXEA+Uq6tNxggnZWfNYIkuLfwXWGwLNeccNWt2wbejGr1/NS6StCmIho8PIXXaAJjR37/mTeVw90qCd7DVugwoYl2EUQgaBLWo70gYy+bKToRU4490AmJFXjC5l9i5m6jbVaQ6v2IB11uodYJa9ofg21GNpOJekH0hNH5WhtTTrfckWNGM8r9sRu61RZZ9LdsqgR8Zr9Hsw8zCPpJOE5vkllBMQR2q88NlcFuycyZGXBFR9N9QPEO7+mcn1fpR/siXSCrKtZZDtrpeGIQYYwZxarvaYIxP067+cAxDJ3NnMQflXVEtmu5eSVqIVEsnw+ak+hjFtueQudKpMlijOeo/NEbakX2SRYRFeyaxfNbjQv+M9EEhonQMor4n5rpM5to3wB2egdqRYfq+hN633a4eD0ZEusqxR0sM35Vk6vxzv2ScQBqSnet/s4U6fM3mUR9uMvQ0fVaGps+PQkhyI31Onn3egONCbWaXD/++Ovj3Gf2s7ToBDZ8eRsqUfoYFnezSqdfBw/VD5dPbjQYWDoAZ59b0BAs1TUpsLzwiuDjnePH1lzF/zrmGfQvOnoeyo0dx0kknoXjMaIybPQVrXn8JHo8Hq59bhRtuuAHFY0bj7B/Nh8/vwxVXXIH8U4dj4lnTMHrWRPzs1l8gJBlf/MsXX2pJ4ztSr8S81n2c1117LWRZRmFhIS666CI8dd9jEGqd/fGkOr+hMVj58N/xzJrnMHbGRBTPmoA3//0WAOCiRRfir8sfwvhZk7Fv7z4l3ernMG72FCXde28brDFStQ9ycxB3P/gnVNfW4Od33ISxk8dj8tln2FYmo0ePxqhRo/DCay9FJo9xYOSwEfjJoiXGBkXieOfVt1A4ehSKRhVhzpw5uO+++9CnTx/jdUpKNIO4LGbhiUBaRaX2qGWO8vs3oWmDsh4RE4Xo+YVke9cBmRtiPnfUkCoPcVT9wyacYbgyKn9gCyqe2Kqdm4fkyMRB3ZCcbd42w+Fissn6YWqsLQJF4giErU5mMVf39n7789oOtSrb3H2MVhO7EEs8IKP8wc1o3lphmsymnF9tPFQBqVk6Yz0TcwPrIKL0902Noau/Jv2QcO2b36J6zS74D9YrC+K8W6rEgzWhLm/dvKXcss9w7rDwNEejERIi0U5sieHS7ttXi6P3fIHmryoiG50ieTi4fOhHC/y6SB/RhJImPHXPuXlbBYKHG7XVIM3uC5byGHyoYahL9Pcj7ughdu9JuJyhWp9hiWenhZ7U66pes0sLpebup7zbwfJmy7dn924a7rPNOXw7qlBnmlDKQ7LF3cLOamn3TDRRpIq8pmDcE3kt6K+HG+sQJ6K9J+Z+LQ/KkbJJkYVmDGnU79fR5cPmnvutLhiB7xqUFVfVecA2779+LpGdO4W2z+xmEX4P5CblWrynZoTziBgBmjaXoyE8GhVrsrfcEvvbdMRUNiHJpYy4HmtGxKWIx7Qsq++bFkIRiLhUunuWoD6xLdTHA1PIufdefNuS5GeXXwsxMwFishv333uf4WMaPbgAG9ZvAGSuRWQQwPDHW+/AH2+9Q0snJLmQ6krClx8oi1gIgmBJAwDTJpyGM844Q6tcE7wJeOaZZ7T9gUMNgMyxdOlSLF26VNkoc+zesF1Lc8mFS3DJhUsAAINPysNb//yXEtZM4mAuAVJzEFMnT8XWDzeCJbggprgRqmxR0umROP7+wBOGTU/c9zc8cd/fFBcHUUCovElrHKp3lRnSvvH6GwgeaQRzC9p1a8hcK6fcFMR9v78H9/3+HjC3YB2aChMsa1JcV8w7bBpOuTkEqTGA5hLjkKMlaoXIwP3RBYBTODGDcItj2NTJncN8PsOqjep2Xf7Bo81aY42QrImu4OFGizXFkIdNx8EyecU8KdF2yWTlGuKNbmFuOH27a+Duq5Tf1TspEskE9hZGuTkEqdaP6tU74RmcZtjuHZIOHpIRONgAFhaZmpCKIah5wBjLWg5IEO0aIr14VoWtXtjrRJxqRZMbApH3w0b0qud1soQ2fXEUnsFp2vLrZkHNElyWcxvQlc9/sB5Cgsvgtx2qUOow364aJBWGLcMO73DIaUlskQHhV6D+/YNIOa0/hASXlrcdUkMArswEg+jTnoG+EdcOsBGvJh9qvUHB0MmTODiLQ1Rzq1+0KuSP3rvRmNZsHRUAyMo7HjzWrEwODSOG/dltF7eyuS69cAtV+1D+4BbkXF6gTfDy7bbWC2qdrhfstqEDdRZy//46VCzfpk34U/cde7QEUrUP/e8+TQkT54/TrQ4w+rGb6hA7fLtrUPn0dst2LnE0bjgCIcEcpULWLOlKzHrrKppa50vvfmLwbTfWQ2V/+kKrOxs++g5pM08yCED1vso2nQz92gBV/9yhja5YJiWaRGTd298iZXJf+HYqz9KdmwT/nlrNnYLLsmECsLl+NuP4/cfz2pveQVdOIgIHG1C5YjuSJ/YJp3F2Z9HysXvfZA6GnmehJkHdBjjnymxWr2h0V7CzaGhWSO6YRvaFDJOAYgXKjwZjMA6Zca7zLHD4Sji3zHa3FjKcNCRDqvZBDE+EY1FCZET9AJhuaM1JuGiLyTBL+fVFNaxuFmMlR9vY3tz0LyJlN6/OZLbAsJg+1PZiuf6Dg9pzrnzqKyQW51qLZRLQPChpQ/WGdPqwRE6+m+YyqPc0KBs6CU5DgID90K7B75oxg3i0G1rlcsTVxSmUmqXspjz8e2u1Rs/s68f9IRurjt4PkisTIEPhyaIuQWs0tVBR6qcaw/VADsjgukm63C8BOou91BiAf2+t0T0h/P7oy2gQh+Hrkf2SNjFMarKJda4KaofRkZpX9xh+m+cMqPfN6Xnry6f6Vuv9ttXz65+hk0VfqrH3Ebe8G+okJ4eRCq28meF7xmCZVKgkim7h1ItmJhjT6wVG85fHkDA8C7Gof/8gkscrAsIzMBWB7xocOzrmzjPzuMB9io+0IY4vlHssJrmURYhMHWnb8H66Z+wPr17Y9EWZJqjtLKVc5pYY8LEs1I0blEmZ2oS/cP2rhtP076lB/YffaQu/xIOh6XES1zoadPMB9DR9UYa6t76Fu3+KYbtU59feBad3vmV7Fdwzkkz1t6nu0Odpeq+btpQjZWJfS3pzSFjAeD9Dx5oNPuxSfQCBg/VILMixFaOBw41o2lSOxFE5cPU2TU42ve/ME8tCHb1D7e6TbDBYGK7BVDZtfhWguYfwllB0HcCtEWwAJbysd0h6j7NQk8tHG+B+CVK1D1KDKVh7tF6djWgz7I41vBivR4BpoQI4VFTablnpHMRcstRcPvUna03h9DBNFDn2YNVs7ayy5smPumxts4p2f7nNw3HKx1wBCcxaIZiEuV2jrsY+VWkpqbCkMYslO5cLADh8W2RRAh6S7SNmSKbFO9R+XlCGHKclSV3sQI9F0OqLKNvFz430eSQbQR0rAoKWddjiarbAyC2SoRG0EJIhJrkMv9Xnr1XemptPeAKQQ6MTOFBvWPa8cuXXOBL+zSWOsrs+R/WaXah9LRJ/VstL75agy1+9nzwgaULHbsldNZ+2Lu6gCXen42OMmKidMEOnyMlC7TTqYRIowSONqHltr33aMGpdwX0SmEeEkCBano+hgynJ4Jyj4X+HEKr1gcvcGNeYRyKIAMZnUfvv/XF1+nhQRu2b3wJAZJTDqfE3dTIFXXrziA0TGZhbCC/7LMHVKwnJE8KWP4e6QDuNajjQReuwHREK2UT0sLVQ6wSgKS60aqFWr71lR3Xr4gwDxjo8Dgu17LD8uPau2bh8mCM0man/Tyl8e2shVfl0x+k7Z7rJqR9bBT0TmFE8h89jd9+jubJUPrMdVf/cobQrNukCpfXgvhC8QzIsLm4+nXsRgNjfcXNkjoV5Mq8rJxG9fzFGCSVoh3lSt86YoL4LcrPVwGGA279v1at3KiMQZKE+8dFC/Qgm60g8oq0t2tOcdbQ8TD6B6t9Sc9CyIEeozh9pQNrsw8tiL3ZkZ/1mUCZwMWaoFPQTu1QRzITwJRsuy+G+M6VDITUEICS5IKiLlUR7NLpIHpyHYyfHO6OYW2MtG8SSzVLF8SL7JMPQZfOWcgjJbiSP6+N4DA9xRWQ02lj/9HGfdT7U7Vna1WABMfmLVzyxzXqAzGFx+VAtxlAEnhi2dMh+CY0fH0JCfrY1n/BpzYJebgpEFRs8JENIcmkuEFJTULO2aou+qH6KYRHhtCpiqNIoLPRD80G7YXpEBBt3sIo2fa74dnK/pPm22sWpVleqbOsS6Op7Ze7YaeUMT262dTdAREgbJsI5vOfxLOcOAPX/PYDAQaOLlZDkMloUVZHiCynXwGwsqiaXD7kxiLp39qP+gwMQUjyQqn3wnJQKluCyWFHl5hDc/VMQPNwIT/8U206fHb5dipARnFakDOMvrTeIHrVjw0Oy9VyiAOYWFXEqMDCPoM0ZsDwXFzPUWdoKmQKDVB9A9Qs7bS3GXOKWEIlycwhSfQBSvR+1b3+L3MsLDYLaPIKqrKInafVI4LsGCOa5FbHQW6VtRgrNGPxt9dk0Ke+CmOxGW7qalX83htk1nF93f+ve/tZyrP9APWpe2WPZrn9/1WhZTm0C90na/eU+Sfl2wm5BKi3blZEMd79ky/cSqjJNgAzJUY1JWki6oIz6Dw4gfXZeeAfX6ljGGLhd7HSzNVzv7qLrpMX6/p1WhA5WtBhDm1KUjxMTw+SFWHpatXZp+2wSSRxSg7Pvqj4fx/OoqEOgqohVO+U2flz6bcwltK4HqLljIGYngbmYoadvQGSG84aONcPdO9kYKios/kLHmiM+VQ4dAMaUYXU5/J8rJ9HiT2dBrRjCvWWzUIqG3SRHLsvafeGqa0EbUIZwI1EU6t4pBQC4eydbF11RCclKI22eBW6eSW6wULdHUOtclY4128Z2NpTDxuWDuSPvXt3b+5G5aCgA4NhjJQiVN2tCI+viYZHliMOjFmYLtdQQNMadTnAZhsJ5SIaQEonbLTcFtbjTaoOgWuxjTV6N5hvoNEwasVCHIwp4BNsOgP6ZSNXO72ObVpFzCTGHgoNHGtG8qVxZgc8GLWKCXtBLHEKKG0ljeqNx3aFIGR1EeTwIKW5jnHN12N4nKVYwbnXD0g/Nc4lrIxw8IBuMCu5eSfCb/IrllhDc/ZIhprghNQbjdktSy6i9j5LN6AyAetOKp4JOUFsisegt1IwpK5k6xGt2905G8HCj9lsTKSJDzWt7LREatHSSbMmz9o19WocNAAKHG6K2DVJjAGW6mPDcLwEJrYtj7uQ3HW9nX3WP09cpHQEPyvDtrUXVs1/DlR093n+gNLaLi5DoguSXnKPA6JB9IQSPNsGVkwTvIGXuR9PGo4qrDVPcMTz9U9D48SEt3Jyl/CEOp9VpARgmJeo7XAZ3Q6fRa8kk1vXuibr3JXiowRgNylBAe/clQNENdi4fde+VwjMwFYl2hpYuhlw+2kmsCRTai8U55KBkO/wh1fljh4pyssiaUHyoeWTmtskP2fJ3GNGhshBSHCwNmsuHg++1vpJWe6s2H6YlRmxQ+UhDFS2RcGJ2Lh/RolHohydVcWyyYtsh1fmdh6edCK+6xdwCEsMTS0LHWiL3JxRxtchYcEqrsuZBGUGbCVoVK75CvS6YvuEYm1n7ajmNLh86C3U7wl7prVtyY1CJrR0FvXWr+UvFOqqfeNL85TG0fF2Fhg8PRmI3h8WKwerF7AV18FizNoSfftZgZC0eZtgv1SsjF1qZm4LImHcy3P1T4O6n+F1G4hrbx6vVHxvPdRqO8RljJQuJ9t9X4yeHtegQZquTnrasHpZUlBtTcNS+vs9RTAPQoiTIfkkJx/Z5GeSWkCICzd+rw6fqPSXD8NtwneF3WMww1Utq3F+/YqFmXtHSYTX6zNs/Q6kpaHsPQpUtEJLcEJLdCB5uRPBIo2F/9o/z7S8mjNp55yFZi+gSF0HF5UP/bppdPgSP4Dgp2TPA5DOs61Cr/tS2hCclRqP5y2PaPU0a08u4kwHBQ42aCxagdEhbHcPdoR1VV+aMRfmDymqlqguTXrCK6a2Mp66Dh2TU/ftbpS52sIqr2BlixEzjwmLMJSjhReMYtWz43yEEy5V4/ZkXnIrMC06FO/ycXTmJEDwimCgYV3u0KX+0tlLfWRWS3AgcaVTcWQzhJu3fOa5f4REwqElDm8KB5PG94RkUmRBuyMeh/eE+ydDhVSO1NHz4HaqetYlk1Q0gQd0W9O4bPLqg1nY1BhVrWxuXGTb4psawUHMe+Ri04ukrYjth6yAyBZtJcIaMHSzUTNAN/4SzFlI8lkbMbhay3tLihNnXliW4wtcOS+xOqcHkBhCezMTsLNetXWlKUlw+mEdE1sXDkDTa2ODoJyUmT+iDpHHOlZ81bxnlf9ls3R7FasNDshb+LXFUZNls395a1LyoW/5ZZ6GO5Y8ZjVizyM3UvLTbEinF3AEIljUahLm2kqNOvGvvlDleqq4CdvVOssZSlri2pLuSOeDNS0fvG0ZHQsmpw6C+kHG4UvUlVH3AHYYyQzU+ews1UyxCwaNNmqXabvlzIGxNDQvMeERzypR+MdOoePolxxRRdlSu/Nq6UeI4ev8m1P5rL1q+qlQ6z6o7TlL0kaHM809B39snat+MnT+2d7CxEa58ejtC1b7wipgCBBtLu966HzzSaHv/kkblOlrpXZle7R1pWHvIsC+xIPpS9GK6F2CKJTGWAAOg1Z08pMRJFjN0AkwUIoI6EF550cFCnTDMOHlSrUOVaBvW+iJxZDZSZw5U7qMuT7tORtPnR9GyTZnjYQ5TqRoRtHIMz1Lqp1a6EHKZo3lbBcru2xiXGBdNy8uHjrVAbgnpXBgi16yfLNdaeEiOGZ8/GpYltBmUUdk4vunmzeVKAIC0yDshhuO+q1GOABjrMwCuXpFFwnhAQuN6+wmcgHGEqeWrShx7+EvUvf2t8i3GsFBzicO/PzLywQSGtB+cpOwzXZ+Y7IZnUKpNJjYuk/rdpigragQr8/PvLpCgbhccTi4fxxoq8ePrlmL41FGYdPbpmHfJBdj9rdW/KhoGwRevrzaUIZ51Gz7Ghk2fA1zxwTT0AmVunXnsVGc4fUyxKkxdJS0kuQGRWWMWI74PQ6/1tbOaBbWLKW4rPuusYqnOj1CVznogMLj7JcccwouH5s3lCJY1QUz3KJ0SU4OnhQ1iSoWTNMoazcOJaBWN4zEhGVwGPIPTDeK+cd0hQzxjdXiy/v0D0SfxxSDW6oq2ZTT7vJruWcOHxtXogmG3Bv3z0vpzTh0+KOJAtGlM9S5AudcVRdKbJme1fF2Fal0IKlVMqI2ak6A++qeNSohGkzhR3RfKH9yC6ud3AoCju43ZehsNV69EpJ83xHZfYmGOJeIBc4ttEgmWCU9h9G4UPBiJSMG8IlKmKkLflZ2g/a2VwyNCTPHYRrhRxbhZKAKKvzKXOJgo2L5/+rqu5uU9lvog84enIu3MQY6uYK6cRIO4N5+j96/GIXGk/XCzmJWAjHknw7ej2j4evLms6oJRIVlZTEcnnhQLtai5gwhJbtvRp+xLRjj6LFvqEPW5u4WINV0nYJ3yadmu1B3m+jrh1Ihg7HXjaLj7pzjGVe7zmwlIsnnWSiGAmlf2QKryxTUvwG71v2BZk62FWv8dZl820nBMzlWFWog322IFZUMDlHKGcZGl9LMHRy1nwgjTe8KUeqY1dbu+86uOCKqjaUohjen1i2M1fnxYcxW0Q6pX3CLN7XywrClmiFa5IYDKFbrQhQJD8iQlyokqhDN/eKpyDV7RftErONeBKuoqwg0ffqetYSCme6Md0mWQoG4L3PCPhuqTzDnHwksX44zTTsfOT7fhi7UbcNdtf8CxCmskBzskSXnBVOuLJEkxRLSpbJzjf+sVQa3MHrcucW6xlMfRwArJ7ojID7dRyuxga29b/zEKiS54+qaAuSINoNboMhZTlLEElyK6BJ3Puvqv2sAwFlvkq/mp540RYi9eAgcb4MpWPnpLg6eGyVLvRyu+uMpnbCyCMVAs4rLWwYiZPiBH9bGLFf1FfUfFDC/6/WFK3OVUoxUANvfMhFTtUyaY6hr7UHk4Zrvu3TFY96A0pEKyVTQxtwAxKwHpZw+G9ySdBdTmfgX0FpjwfrUy17t1JBXnIrEwYr2UGwLwnGS0yIjJHsuMf9uG1cWQMe9k63YHhGSP47vMPFbxzNwCGGNImdoPOZeNRO9fjsWAe6eh9y/HakPKbSWxIMfwTWruXqLub7Uc4XT65692mpIn90OfW8fD0y8FLEE0jIRwKRwpQ2S2IyTmBtpsLRNS3WCC/bFKGRINriZmEenOSYSYnWg+TLkWF0PK5H5ImzPIdr8FiYN5RWUUTZIN1kbmUizUctiXW8xMAATrO5o4ItvxOzW7Jan3V3/9qjW718/HWKydZiz3Qhe2TUh0RcIx2ohiV7oXaWc5CFCd64ndsbnXFqHXDaO133bPrmlzuWah1vsD698vb146ei8bE/k9KM12dVa4mOL3G5QMBh3zBE4n1ykhxQ3P4HS4c0zvCWNgos3qulHQj2KpHQZXVuT9NI+0xONOYsjfI1jEDA/qfOvjbSZZpM1RRwiSxvdG1pJ8JaykWg/p61ke23DEZa7NzVEXsoo3MtXxhgR1WzC4fFh3r12/Dm63G1cvvUrZwICikYWQZAkLli7S0v389pvw3IurAABDJxfgt3f/HhPPmoZX3voXhk4uwK133Kb9/u//PsDp82dh4lnTsPiaS9DY1Kgd94e//B8mnjUNY34wCTt27kTpdwfw5Mq/45G/P4qxU8fjk8/Xt+kyhVSP4WNibiES5kkXgsg2HJODSBIzvHD1SjKKvTg+2EhFb7JMs4gwj7vToRMYYlYrrNRO4YMQ6UVbljkOr4ymWj9j9foT8rOQOuuk+MtkomnDkYj1rg3D+hZiiF2tg+QSLI1NNJJ18VqZjUgw4+qVZFzmO+ymoncrMPsSqj6GljKLDH1/Pd6ypLeT+0WknMp+TdjrOnCunER4TjK6J7hMosvsTwkAgs0IDRMES+cgarmiPCPmtvrdqiIg47yTkTAsS1uwxd0rCVnhCaFtoc9vJiBz/imG82miWRCs5dQEtb4uCG9zMbjCorbf7yajl24kQe2kOr1z5hEQs4VavX5bdzYBcOUmakPXgL3V1uk7Vq8lbcZJ6HvbRORcVWibTitbUI7E+pWhhRsDoHQY3JGVWF1Z3lZPtjPHntaEGGNaXQ4oK+55+iYbz2+D2X1CbykUEl0xwzG60r2a1VIP59EFtXdQGjz9UzTXJjtB3bzZYdVQ3fvFPKaFv0RmH2Y0xCGoETl0z9oycdQloNeNo81HI/tH+ej101H2eYvMsIBPTHTlTzmtP8BgmPydPL4vsi8Zof1u7bwKJ4MWi+FDbZc+IqhlQFDa5aTCHOW7UOtP/TvGuW18dAMhGZkXKXNhtAhMbYxu1NmQoG4Let1mI+K+3vUNxoweE9MHyUxWZhY+f+djXDh/IQAgp08uPn/nY8ycNgP3Pnwf3ln9Bj5/52OMHTUaDz31N+247KxsfP7Ox7j6J1fggUcfRN7AQfjplVfhhiuvx8Z3P8VpExXLIfOKjlYZs4VLSPXAle41+lswFrmWGL1gpxnCjDFrLz+W8GPh/zl0YJQCI36/Pf0lxSk6kyf1Rb/bJ2m/e/9ijGG/ZqEOX1vCsEzFsi5x40z6GII6beZJisXJvP0HJ2nRL6Lh/7YuYr3rCEFt8/IaJk6pDXwrXQhcObqOTAzRDsCwSp+xLBGxE6/1yLaRQ+x3QZtIaLIIZS4aitQzBoK5rd+Q4bS5Vqtm1kWRSZPa6I9g/UaioQrVPr8aZ2hYAeV9tIzcRBNlNh0QM07WV82lSxt9ivwNAZZ3hOmt1ybMolz/bOreO4BQZYuy3eY+WaJ+mAQ2C4fStBOPudcUaZ1RT57SQbL1BXe4TfpOmZjqQcLJGTFcCiS4+0YidOhFPgv7UGv5ZSa0WlCbr13MDFuoRWZ0l1LfbRs3GMM7amo/DBZ1rxiJWmKe56ErtnnkBoAykV4NWxlNLDks6BQNg4+4qZ1jYYux7XEeEc3bKhDSuTSZXSWZW7D4lQORazTnzRgzxJWPZw6KPo+EUzMx4J5pBlc2JjIkjshGxvyTkbHgFMfJf84ncNjeSv0CQefyyGHUDtAZJMyRmWr9tsYGFS5zuNK9hnvVXQX1CR02709f/Ak7q3d2aJ7Ds4Zj2cDrlR/x6jdBgJAe+8NZdN4PIz8E4OKLLwYAfL7lC+zYsxPTz58NAAgEA5g0ZoKWdMHceQCAMaOK8dq7b4aPt/kK2uLiwEx/c2VDTPcKFl46N47wSWK6V7FoRJ1sCWgrOoZxZSdokQFa5ctr6CTETp48uS8y559itHSZxJcqENUhUcVKzLThN61StHkGSeN6RxZNEewreDEzweCvGBV1+LQ1gjoc69TdN9ngymCKDAkA6HPrBBz5vTLqocVwDpc5/dwhaN4UfUJWn5vHGScYxiGoXY6CWleFmSzMqnAy4yScYwrq8PM3N4LJYcu42RpuHh53mYd/AcOkSeYWwH2R+5E6fQCatxyz+GonjsrRlhoGoH3rrpxEuHIS0f+e01D2f59DbgxHsjBZrKJdp8XyaopvDDhPVNbyFSLvukEYm0cAVOFtJ+LN5dCnUZ+DaB/+zyyozRYwtZx24lHfQdPS2fjrOmJzLZ5BaVp8cTM8KMM7OA1Nn5Up50wwfhf6Z+XKTGh9FCITmrWdGS2F6rttd0/0355ZDOnLx5izGw1z6bbbtE1c1luoo1gs1XemNR1OgcEzKM3gBuIekILgoUbLNQDKqGX24uFK6MAQN0QwSZnUDy1fVSrxpH2S7QhQ5sJTdfWi6X0wXXrmwqGoXrUjevnjrMdTJkfmKPT/4xQce7QkvomxDrYxpusYxyN1mMAi84gkY1sNwD7UKVcEtbtPkuOKqqqhjLkV33NX7ySEypuVCbUdFB6xo+hepekp8Mgfdl4GI4bm48uSLRHrtcggJLrhTvFCliOzhv1+3QskMCSnGP0Xk5OVni/nwKxpM7DxP59i438+xdYPN2L5/Y9q6bxepXcnCiKkULjnFl40RU9r9DTT2kRT716zUDt8YpEDIaZ6IgurRDuXwKIuBKD4O4d/cMMOiFkJSpgrjxi/gDQY3WPfFK1CE53FgSqWXOEhUO5XVrrz76+Dv7ReN/RtPZ/BX1ZghgbHe7IytKdaneNB9ofDlzm4MKSeYfUZVK8xeWIfePSRFWzKa7CemkRU6mn9kb10pOUYPa7sRDDGkLlwKNLPyotLsKgW6pzLC2zLDVgbL6coDo4NlOn+pk4faPitCWqnIVJTvmZxYnYBAaCFRgOs1v70uYMtE/kyF55quV8Wlw6dkBU8osWnMlojpO/c5F5dCHdfG5/qWG5AesuW/psxufZoDbb+PWXGfXbl0pfD1lJp6gBYhuk1lw/rsS6dpUwTRTFidhvytnm3bDsMYTyD0gwLF+nTMrdx0qWQ4nYcudDXY2lnDkL2T4wjFZkXDUPK6QMiVmCJGyzUqpuAnSA2WKF15+/zq3HWgjitD6B/5xzCoGpx4KNZH9UBj9ZEF3IJyL26EP3/OFXblHv1KPT9bdgoZXq30ucMgmdgqq2Ln3dIOgbcMy0yImnTviWN0bmemd9b07XbRamxEGe9r4e5W9Eexjmym3H+KdawiXrCp9O+G3NfwqYzJNX6IdX74cq1GkzSz8oDEBkZVL8NNcJJd7RSn9AW6lsm3NIp+QbUsG4O7+GMqWfgjr/8EX9/dgWuuHgpmMiwbds2QOLYuWcX/MEAWhqb8OGn/8OU8ZOVF4QBokPM54ljxuMXt9+Evfv34ZTBJ6OpuQmHjx7B0CFWXzQAgMCQmpaK2qPVlu2tXmTEZKG2+7Rd2YmQA5K9L3W8xCqW2mCYejBikhsICwx3bqJj/F+7rJQfpn3hMFWGbWoFoe9cmBpJtUOg+hTK/hAYY0pMaugmzMUQqEwwigemi2vrODRpKrPcHIrqQ60O+5qvkQfksOiJnCepONdgXUs/d4jpONXKqBdO8TUAyeEQgv5vt8dIGYkl6x2c7pjGMrzqIBydOhqW4WDT6IorJxGh8mZ4BqTAPTAVwe+Mq5SZGzB3nyR4BqdrExttJ3wJkVjDmrDW+2yaGw1uc38dxCagiEHrimZRxIh+AteQDHuBGOv52vhQ6/P2DE5X/Eu17fZ+pk55anm77KN8mGn4yBg1RvueTc8356pCo6BV3227++VkT7BzX3H4bnv/YoxiEHAYrRGS3BHxn+xSOkpxiCRPXhoSTs4wbEsqzgUb3QsNn4ZDqEncIErVTpfaCdRW9IPRkq1/9nYjLp6BOncO3UrChlX0nAS1GIegVsWVg6BOmzMI9f85YNjGBKbkrTeSe0RAnf/hFpByWn80fnI4/DucMIpXo9bJsnkcdnMIHPOJw8IarUMW9bgY70piYQ5avqp0HG3W6o3wJYjp3uh56jrI3A8bC3X4H/OzYwzeUzLQ+NkRQ2c4YXgW6t4p1d5Nd99kSHV+JBXkwJ2bFHPOS1dAFupWwjlHrEVWGGN45cWX8cG6jzB86igUjinCb37zG/TK7YULzj0fY2ZMwI+uvRSjRxUp4dZEtdJ02zYcudk5eOqvj+OSn12OsWdOxunzf4Bde51D8AnJbsybNw+vv/Mmxs+ZGpmU2N73z8bqrebrSvfCow/P1cpzRf1QnfIyCyBRUCZ5xTq3wyI3YlYC3L2TLYLT3uoUOS5j3smaGBNSFWEtJLhM70n43xhiRMxMMIYcVCufkOxYsWZeYOpYSTyqD7XtaIDOCq+/Pe6+KRhw7zTtd+pp/Q2HaY2H/rpa6U8dz1xSbQGUKHmbr9fpfsU7hGpecCCpMAe9bhyNpKJexklyWr4m61OS2yAc7cVWpOOj7ReN7yQQ6ZDpY8xrediJTXUSrNu6AmpUC7XDBEYDNufTL3iit1Brf3Pd9ZkeuK3oiMNC7eRD7YT63msi1TSCYBmt0t3DuHGYhGaHu0+y1eIsMuRcWYg+t443lFFMVZ5/PNZy2yparZ/CYpFLssnlIyxUw9vsOvVOJI3upU0IFtO8SkQHGL8Hwz20KR+XI2kMS82bsRHoemzrtliiljFknDtEE+nqOxUtWobq9hQzhr/5W7EYcETN39oplnxbhWOsek5btM1JUGtGmsjoajRXT80Crda75mt3WN22zy3jkTg8yzrypnZswsI+68KhyLp4GBILcpA266TWuWIdJ05oC3WnwE1/c8BucZN+/ftjzbPPQ24Kwt03GUwUEKrx4Z7b/oh777wbPChBzEzQJvKUlpYCAOSghNCxZny7dz8Et6DFXZw5YybWnzbd0hh9u3sfeFCCVB/A2KIx+O9L/wYTGYYOHYovP91otBozm4LGwuxv3MrD40VIUToTkpOPoF2dYrPNleYF0rzafYuZl96AluS27odD5a2rrJInRyJWuDISkDH/ZCTkZ+PYoyWR9OHnph8Gy7m8QJuMkblwKMQ0jzJEr5vQowy5H1Ms3zYNQ+oZA2xXszT7X2b+8FTUvLpH25e9dCTkpiBqwnGWI8N0rFWCWF1wyOgr2/H9dM26G20+XazIGGGLWTzly1x4qjW0JAM84fivjCkxVw3xii0uHyaxJCiWGL9+2XhRcXfS+0nr72XyuD7w9E9F0+dlyuqEemGq5eEs4phHtCx0FFUgmt1mbNIykSF1xkBl0YhPlZXsDHGzdT7Uhvx04tqYX2wreKtcPqBEVMm6eDgqHt8a2ZbqgaxbIZG5lNVNtYgL5mJwdRJq2ybARba1wmVEYEjQ3cuEkdlImdJPu796a3mfX49v9cQxo8uHTlCHxZMr/A3prcSxRiT0kxaVTFRLpaAJTsN7ZNeG6Fb3jWahVuN2O46+2YiseOZo6MulvVNRRnMTR2bDt7PaEL7ODksnzWwE8gjIuaIAckMQYnYC0s8dgsb1R+Dpn4KK5duURJ1koVYFqWWRtPAy4ZYOhciit/+msHiOLh+6dzjtzEGam6SY5DL4q2vvp/pcktxIKo7ictINIEHdWuzMaXYh25jSwIspEQu0mK6swCU1BoGg9YUDFAuCp39k2ExIdoNLHK7sBPCQrC3HrCEyMGZtuIEOEjYGYy4DZ3bXr//BtbStOk04jJNtRMoolvE2EaNslqH/GI2kOb02OUT3Tmh/6tLqV9FKHmfvd5c8oQ/c/ZLhHZJuf08Fh3vjErR8XDmJELO8hmMSh2choHNZiEyahGOHwxa1MtZb1RNcSpijoIxQjQ/ufinRJ97EYaLWRFCUZ2cXRQNQFl9o+N93kFvCb1cc30XyuD6QAxKEJDf8pXXKJEBTMTNNS8lbvjcbi3n2JSPg312Dqn8q94O5lW3Nm8sRrGhB8EiT0WVCYPD0T0GTuokjPgu11ngJhkUubMsZJa+MswbjqG5BIJX0OXnKkuNhQW34Hhzcf5ws1IaOovqnxbpl75vsZKEWElyWfWrHU3/92YuH45AmqE3nVEe82+lD3apxYFNdI3hEwxwLvTB1FnNKHqobQ9bFuigd6vHhEa9ePx+DYw9t0UYxNDcOu08yfGjqGQOidl4j0Vv0/uAxOiWca8IuqsuHbBXU/e85DYd/84my3catKu4OjSrWPZFOhxPJ4/sgIT/LduGoaJi/VOYWIXhdkYm+TBkF1I8qxd0hMOcdw7Ithid0i+leg64QU9wItYQi7hdq0yDY6Bz9+XQhL8MbjAls6qk0XYhYlmjsDMXlX97NIEHdWswh87TIE9b4yIwxwG1sXNRFSiSZR13lTcWldz+wqxjsdKYpXq5UryzsEu9sXUNehqj20KJ8mBLFVa6YRLOEtFU822Vl6iTEPJeDlS4mNuEV4/EvNggSF7P4QwJKpc8Dil+1ar01RD0RldBrmRcOhXdIhsHyr5XBcB51RolRoKuTbzwnpdrWpWrDmnBKpmF7sm6VRsMqlXaE882+dASaNpXDZyPg4kE/3GtwUzl9AFJPH4BDvw03ulEampSp/bQwWIJHRMqUfggcrFeKGWvyjs3kQAPhZ+LR+YEzxuDKTEDaDwah+oVdyja7d0s3h8ApnrPdNuZu3aREc16unESkzhxoWL1SvQ+Gd1l/nBYdgBm3h+svi+3B5nlYvhO7qs8lOEeV8IgWg4WQ5IJ5oqThGNPz0q4zjonVWh7Rnl24DNFcGmLWK60QVxnnDkGGec6D5s6gXJtqkYZZUJvo/YvIoi/pTouzqOdQLZQOLh9axybBpYX1UxbriUdQh/91CIVnO08hznumWb81H2rji2peWbe1YlrJ3PTT6Vu0q5tbe6oYx7n6JCNz0VAkDM+C3BBA+YNbAECJNV7REhH1alFEpt0TMSsBUrXPOH/H7PLhEDbPSZSL5vCU5qhBPQAS1K2FKUMPWuB6rliaudm0GuUdENwiBIcwYFFPLTAIKR5l5UP9icxWY12DJqZ4IDeHFH/QVlmNnRoGnUWytRMcY51RP+lPNynG6V62ygruEiJD37GOc4qXa6LXDaMh1TmE+gHa5ENtSeOQnnld4AHlPfD0S0H2T/IhpHpQ8dhWQ5mTwzPOpXp9RJlwHvoIGZqgjiRLOX2ANvzc67pi23K4eyWhzy3jo7tbxNkgMJduIqVNuDYnsi4ehmBFSxzvQ/ThYkBZ7MSC+gxirZcQw9KudXTDjb57oCkebzyxyjksAiGqD7VHsHynrQqbZ7fNpmNhsETrfajtrNUWH2p9eezvge2zjeLywTwCXL2S4BmYqo3ECIku5R1zek/Mm1VB7RGQOnOg0bjh9Kjt5luEz+fJS0Pq6QNQ9VyUJcljLHIUV50XzS4RFrlaOM/w/VM7eUKCC2KGF0nFuWhYe0g7zi7Wcqxz6J9r5sJIDH3BI2LAvdNQ/9HByARCzrW1DaJ1OGw7czrsYobHbeFVm4ewZdR7SgZClRFjgH6lxjZjFplOE6f16dpooVbfRTHNg7QfDNJc/rRzuAQt5KeY7NZCCWqhX82uYgLTPt20GQPhyUsDEwUc/fPGcIJIvkp6y0VFLa7Fh5oxZJw3BF4bg1J3pefZ1LsYJgpwZSkB9u2G8Tu/AKafzHFjzGPbcm61chLTvIbtGtxmWxswhxhr7zLhrnRvZAg4Vlbm/Q6Np6d/iu0iLNph+vpIfVlaa6F2uG7zipWJI3OMwf7NMZn1w6+aJcHGgqQLUejpF18j6spMiPp8YjZoqkDTLbIQz+qJKknFvZB+5iAAQMq0/hCzHYbC1dO01ifRIcKMhTgt2Exg6L1sDHKvNIUA1O23lkEtAo8viooubJ6KGvIq3igsKpbLjtWxcOgQRlw+oqRX00YpY0L4m2Mic4xzz9wiGGOGEJHJ4/tEt646uXy4BKTPztMm20XDfoKlLj+9a1W8x8dDvPWjKviliDDtvWwMspdEJpX2vXUCUs8YaHd0fJhcexJGZkcs4foi62JTc5lrVnPzYjQG5Oj1qL2FurUuH0q5Ms4bgtyrI5OK7WJ0q8QttuO1UOvTtNNCnTAyG8kTrO+u+dyqpVmNVKWNbKnvligYJoW6c5PgykpA0mijX7O+LTHuUE/kUF6bzlDK1P6t6sx1NSSo20y4p89hXzl2ksi2NDTMen5Lz9DG9UBFSHI7LpphOTdTwg+5+6dEVkWDk+hr4/WL4WFc3eGG+NdtPQWDcbJUtKTmod+grWd3bPQ+1NrkvTiOi0d0q+H0dNZHMdUTsdBY/HdtRI5hSd7wDHeGyP2Jcp/S5uYheVJfx/3Gc0e/aK7vhNlEDcm5osByjBMZ5wxB35vHRy9PKxcDUL+5WC4frhzdAhh2y1XrnoG7d7J1gRSbKB8qqphLHJ4V04oJ6KyEumvNmHeywRUmbkzXHbfri6Bb2EXv+22eBKV/39U/o3wD+gVznBaZUf0vNZcQF4NnQKpjJAVLOaC7TtuyONwD285Q5LqdVpDVkrZVUBsyibJLdbvR1RvKu2hesKUd5Qhfr9quJOZn2SfT+8jK3GIRtSOWhdrOpz7eDmT6OYp7jDZfQxSMYQCjYIhwFQ1zWx2H2G+7D3XkOqLtV4kI6rCFOhi+12p6ATE7NICu7mtlx90yibsHQi4fbUV7V7i9Suoso3U8+Vpe5IgF0JJdgtiqWexKNu0bdoyGp6+6mE0cw/2tWqkGEeVmOsyVm2i8Z6b9sr+tglr/t/MzMBPP/RWTXAgChggOzC2gz6/GoXl7JRJH5pgOsApqQ0Wt1Zq6zkuUCjFteissWDEbBHUia6RMTGTa7XNaIdIcE7vjymNCszBGfyfFNA963zQW5X/ZbLu8csyYtFEs1J5+kfCF5urG7luxW0ShNb7AhvzNrl1xurYAMPqCOlmo7Yh2r9RdsjFSRe7VhWguqUDTF0cjHcTw/rgWArFUm/HPe9CysKtj1Q6ZPuShnfXOxp2no1GfQUzx2sbIEkDkHrhyEtHv/01xdsvRCzoZljCVtmgjfdHP3RZST+tvDQva4Svxtb587bVQq52j3r8cC7kxiIont9nmqxqO1KgbsET5iIzKR/smtPCUTiEDHeqPaCMAPYWefwVdCeeKnmaRNsLVKwnuRA8KCwsRCoWQn5+PZ599FklJrfeZtsU2DI91QqT9sXbZxZ/WuUytSBtvljHCDbUhR8e8LVYu0359NI5WYRevvIMmWGghj0xiR0hyI2WC1XJs6/Khr1D1VmJ1tnYHPdeYgkTnOhWJEBD75ClxWsgt5WltA6VZGGMndecmIeuiYUiws8rFsiw7xW91ShdHGsOCGm0Va6aJSOqQsCMGH2qdv4Mq5mwa1LTZg+AdnI6a1/Yqh0aLN87UfIzpvEMy4NtTq6TxGIV0XPGqzS98B7mv6Ye6WSyXjzhGHxKLci3L2seNev4Y819a6xZkQPfIo3VkzNFTosaf1hLFb5hQiRZPOh7Szx0SlwU6ZUq/mN8uY4qwrX19ryX6jiPtjfIRvlfuXkmAzjvD4vIRMLl8mOYcGaJ8RLn/jqseq98tACHZBbnJ+LxjxTvvCfT8K+gqdJWk+hGpcYQTExNRUlICAFiyZAmeeOIJ/PKXv9QODYVCcLnaeOvt3mOdddH84YdCXbQ8Z0eL7GjXHe/x8TaQuv1tGiIPY9ANcfTsW4Pm2hHnxFDDEK5NlA8n632HIDIkje2N5s3l9vttXD7iuk/tHAqNF3UFU6eIEmbMPoUaMU6rt85HTdcKP3zmFpF6xgA0rDsU44gohEVMyuR+8JyUCu+gtKjJmd4Ka5isGL4BdoJ65knGDfFE/LF59TUfWlOEjriG7k3ndGUlwA/rZCmncztmGz7e0z/FGAFFjxp6NY53OnvxcOvGOD8FV1YC3ANTkT43L74D2oLOxSVqMtOICY9jJDAhPxst26u05afjIW7h6oDZau2EPryhI0wRtrlXjYqdVj2kraMFDnHftXzNgjosoIVUpbOmhSHV9AXs21DTu6dG65BNvvBaMg70uWkcZJ/xebdqOfluCvlQtwdd5AbPgFTjRL0w06ZNw969e7F27VpMmzYN8+bNw4gRIyBJEm6++WaMHz8eo0aNwvLlywEAZWVlOP3001FcXIyCggJ8/PHHkCQJS5cuRUFBAYonjMZDT/0NAHDmorOxafMmAEBldRWGThoJAFi5ciXmzZuHmTNnYtasWWhqasLVN12HyadPwfiZk/HGf96OFFD3Mbj7pcCVq1jSnSb72GI3zNnBysx2gYm2mlBjHBYt35TT+iNhpPNERAOGONSdZaGO0/piOykxso3r3uXIHLyOieLCGEP62YOdE+jOY7daYLR821SeVgrq1OkDkXH+Kc5COd7zxhtdJla6eDoSAlNi1IsM6WcNxoB74u8YevLSkKqLD6v5rYospphWzq38wwB79494vLmiunxoL6h1lxpDWA0Dl5WA7KUjDVEmrAcZs1XJOG8Isi8ZYWudbM2X4cpKQK+fFSsrqoq6m2NXhg7xoY5i3RcF9L6+2DYUZ0cRb/0Ry53CM9j6riWP7Y1+f5gCd65xxDfzwqHWBWZU2mmh7lBaU2epneK2+rPHmExtqQfDxhkhyYWcKwqsop/HmFeg7gpbqC0jDnqbTpLbEkedfKi/zzAG7o9u/Q2FQnjnnXcwd+5cAMCWLVuwfft2DB48GE8++STS09OxceNG+P1+TJ06FbNnz8arr76KOXPm4LbbboMkSWhubkZJSQkOHz6M7du3Qw7KqNx9WFcMZttQb9myBdu2bUNWVhZu+fnNmD71dDz97DOoOnQMU2afjlnTpiM5ydjLZwID84rwDDBac1w5idEnIrXXehwHjDFjzMtWZ4BW+TE7YY7rGhWbsHlxTUqMAyHZOikxGraTEnVlcecmwr+7RplsGsOy0Rbisjjr4hZ3lCXfgBa1oXV5M5eAlIltcy8BAO/QTPh318Q+Twx3AEu6GGlasyy3nl7XFBk32Czeo5I2N88alYHprkNz89CVO9akRqDNFmpVJOjricTh9pPiDOXV1hPQbXaLUaP4tAatTo3VaepmMXcT4zUe6Imz/oglqDMXnILyB7ZYs7d5r9XwoHbEM9nxuNGKx8tcArgktf2diK6nLd+zZ3AaAvvrwdyCYd6KmO5VVo0VIy4f8fhQO37nTgJf7/LRvT6DuDmhBfXRu++Gf8fODs3Tmz8cfX7726hpWlpaUFxcDECxUF9xxRVYv349JkyYgMGDFUvde++9h23btuHll18GANTV1WHPnj0YP348Lr/8cgSDQSxYsADFxcUYMmQIvv32W9xwww0455xzcOasH0Aqj75YxplnnomsLKUheX/tB3jr3bfx4Iq/gUscfr8fBw8fQv6pw+J6cds0WaATPgiW4AIPBmInjJlR+7OIizZOSowHdSQh1tK3KoZhQ5th5/SzBiMhP8vYmepAQR1tLMwzMBWBgw0QU9wGd4HsH+d3qF9dwvAs+HZWt2vCVVvIuWREXBNb4560Z36FbNKLGd64341YcMm5EbWdnKp71+06ctEMl5oWjxblIxwe0i5EmiaoWyOi1FO1Qriok6ezLlb85Y/csSG+Uzl1hsJzYTo9bF4r6H/3aW2rK7UOT+tcPgBASHVDblDWeOiQlX7RfpePjsTWfcgB7+B0+HZWt9nlg8WyUJvemZylIyHVByzbs3+SD9/uGmWyoubD7nxeR//+WAN0+o4SCervMabKW+9DrSc5OWIR5pzjkUcewZw5cyzp1q1bh7fffhtLly7FL3/5S1xyySXYunUr/vOf/+CJJ57Aiy++iCf+8BBElwuyrJzb5/cZ8jCfa82T/8TISUWQ6vym2dTtf3PbGyM6XsRUD8A55MZgq49lbVkmsr3oz6e+Ih1kgUo4OQM5VxTAOyQ9vgMcloPWtrmEyGqHcTaIrSLKO5J+9mAkjeujxB7XNR6JBTmOx7SF7CXDlQbjOFsBmUuAGI84iDP2djyjEmmzBiFtxkkx08VDwqkZaN5cDne/OEOD6Yun96FW70E8Fmqb9yV1xkAIyW6kTO4HIcmFpPCiFDlXFWoWaW94gRK7uLsxT9kK3ZJYlIvefZPh7t26GLnMwUKtVU/HubMXjTZ/J5qQi5HMxkKdecFQVK38WvkRo3ORWBx9cmbmBaei5pU9jvuPN+lnD44rlrlK1uLhCJY32cfWjocoIzl2CF4XhFzrucQUT2QEQDeB3AnnRb6iP09DRCJXz3T/OKEFdSxLcnvQ67N4h931zJkzB48//jhmzpwJt9uN3bt3o3///qisrMSAAQNw1VVXwe/3Y8uWLTj77LPh8XhwwQUXYNiwYfjxj38MAMgbcBI2b96M8WPH4dW3X3M815nTf4DHnnkCf5v0GACgZPtWFBeEh3U7S1t0gshmAoMrIwGBNghqQz7HcyEe87k7UMw5hZOLed5YbXacDWJriBq1QRQ0i1/EQtfxvR/mFi0LBnUn4rZOxlHfMJG1edKmmaTiXkgYmhm/dU03wdV2BcWoxXd2e0mfk6f9rRcmen9gMd3b+onEaqSkVtQLjLFWi2kAukm3Dvm2sX4wFL2LrXtaFJZYkxJtOpl695xY9XT2xTaTM3UkjemFYHkzUme0Y5GaDiT19AGxE+kQvCK8J8UxZ8GJeBekagWROOC2ewE4x4aPJfCFFLeyeiznyIo256Ebc0IL6s5EX1m0JYTRlVdeidLSUowZMwacc+Tm5uK1117D2rVrcd9998HtdiMlJQXPPfccDh8+jMsuu0yzRt9zzz0AgF/89Eb8+MbL8OSTT2LutB84nuu2Zbfgl7/7NYrHjoYUkpA34CS8tvKlVpe5R8MAMTtBCdUTh9AQM7wQKuMfnutJmBtty0pXHa+n4xcrneC/3VOQmpSOYqz6pL1hwNpCa4aqDQv16BE7voHvCDTjSDuEaJ9fj4/ruTj6yTPT/h6MkKq8K7HCKxruhf6VUH+30/jARKF1c146id6/HAu5pQuibelX6NTR62fFCFX7LMnjws5C3UEGKiYw9L6+uEPy6ipIULcR1S/LlZNo8TFubGy0pJ8+fTqmT5+u/RYEAXfffTfuvvtuQ7pLL70Ul156qeX4LVuMkzPkgISC7FHYtm0buCQjWNaE//ebOwEAS5cuxdKlS7W0CYmJeOzeh+DqnQypxmd0+eisxq0T2wUhyR3fIgDm49wihIz4hpLEFE+HhvFJ6KDJTUKqB3JDO/3IdQ2VrTUvzrBXrTtnfMlOBEHRVhLzs+DfW4u02YOiptN8QgXWsc+og1B9IQ2CShczOmqV03kDFDHP2Z7Ro7j91R1XIQ3/PgHe/4ThWcj+cb59LHYdalSH5PF90PTF0cgOUVDcKLvZBM224o5zJeKORvuUTHWEZ0CqJfBAvLj7JiNwoN451nSY5El9rXV5Z7gSdjNIULeVsDWizTEi24nSaIUFn8Ag6JedNhNtPlw7epeunMS2R91oB22abNUFbh5Zi4ejcf0RZC/Jd342DmScN8R2Ql7fX4/TljFvK7GEQ9rsQZAaA22b4e90zvD9T50eY9jzBBAUbcUzIBW9ri2KnVD9nt2CEru3mzVQnoGpyFw0FIkF2ZBq/JEd2uhD9yqvs8jtDBwmdXWAqO8uMMbimv/A3CL63TEZzCsiVOPTFmpiIgMPKY8j+8f5kXjIROvohO8t49whSBrdy9BJSJ+bB8gciaNytW2ZC06xOTqODnUPhwR1e2lrjMgOhDEWWS40BmKGF6HKFjC3ADHV0+plx/UICS7AQdt2pZ9ydyGpKBdJRbmxE9qQMtV+MQHmFttv/I/RaLsyE5B7RWF7z2IhHt/WeFaK+76TPLEPQtUtENO9qH+3tKuLY0tyeMKgJCqjKUKy63thoYoFC/uXqvdH2+4S4lrYxDlj3Z89qO5VJ9zp6xtXTiKChxvBecdPTP4+kVTcCy3fVCHVvGhSO2AuwRKLXkz1OMcA1x/bc17LNkOCuo24shMg+6QeUXmJKW5IdX7Fku0S4Il3tn4bcPVKal/DYMqrragxq8XMBOXau9FjElI9SB7vHDe101B9E7vxO9uqWMXfUwSPiMz5p8D/bR0AwNOeiUudjDs3CRkLTkbiyBxtEporx/m7Tpt1Eqr+uQOunI4J+RcPQoobkl86LnWE4BXR7w9TLBPycq8uRHNJBVhbIzqcQOQsHQn/vlolJn4b6Pf7Sd/nPpuGkOjqFMNIW1FXYDQvynMiQV9vGxES3RASe8akNSHFDSHFfVzEv+ARgXZYvS15tRFXTiJ4SIbgdbW5Yu4s+t02sUvOm3N5ARo/PRJzQYWuxNVHiZwQqnKeNJN7XVGXuBp1N7xD0tHn1+MhZsY3OtVVpEzqp/2dc3kBPAOcO/SJBTmtj9LRTnKvKIRvV3Xb4u23Abt6zd07Gelz2hA15ARETPUgqbjtq5K2ZgItcfzwDkpDzlWF8OZ1XwNAe+m0GoQxNhDAcwB6Q7GLPck5f4gxlgXgBQB5AEoBXMg5r2GK2nsIwNkAmgEs5Zxbl0kiWk1PsKJ3NEwUusy/vbuScGpmq0LtdQWevskQUj1IGuU81NuuUFInGB21eMvxImFo93v/XFkJSJncL3bC7sz3sI4neh6dueR9d6AzFUcIwE2c8xEAJgG4njE2AsCtAD7gnJ8K4IPwbwA4C8Cp4f+uBvB4J5aNIIhuSt/fTkDGeSd3dTEIomdC2poguoROs1BzzssAlIX/bmCM7QDQH8B8ANPDyZ4FsBbALeHtz3HOOYDPGGMZjLG+4Xx6DFVVVZg1axYA4OjRoxBFEbm5ysS0L774Ah5P62NWdxZr166Fx+PBlClTurooBKHxfRxRIQiCIHo2x8VpjDGWB2A0gM8B9NaJ5KNQXEIARWx/pzvsUHhbjxLU2dnZ2rLjd955J1JSUvCrX/2qy8oTCoXgctk/5rVr1yIlJaVVgjpafgRBEARBEN9HOt3JlDGWAuAVAL/gnNfr94Wt0a2aj8sYu5oxtokxtqmioqIDS9p5bN68GWeccQbGjh2LOXPmoKxM6SNMnz4dy5Ytw7hx45Cfn4+NGzfihz/8IU499VTcfvvtAIDS0lIMHz4cS5YsQX5+PhYuXIjm5uaY+f7iF7/AuHHj8NBDD+HNN9/ExIkTMXr0aPzgBz9AeXk5SktL8cQTT+CBBx5AcXExPv74YyxduhQvv/yyVu6UFGXy0Nq1azFt2jTMmzcPI0aMgCRJuPnmmzF+/HiMGjUKy5cvP563kyAIgtBDgzoE0eV0qqBmjLmhiOlVnPNXw5vLGWN9w/v7AjgW3n4YwEDd4QPC2wxwzp/knI/jnI9TXSm6M5xz3HDDDXj55ZexefNmXH755bjtttu0/R6PB5s2bcI111yD+fPn49FHH8X27duxcuVKVFVVAQB27dqF6667Djt27EBaWhoee+wxBIPBqPkGAgFs2rQJN910E0477TR89tln+PLLL3HxxRfjz3/+M/Ly8nDNNddg2bJlKCkpwbRp0WfWb9myBQ899BB2796NFStWID09HRs3bsTGjRvx1FNPYf/+/Z1zAwmCIIj4IZcpgugSOjPKBwOwAsAOzvlfdbveAHApgHvD/76u2/4zxtgaABMB1LXXf/rjF3ej8jvrMuDtIWdgCqZdODTu9H6/H9u3b8eZZ54JAJAkCX379tX2z5s3DwBQWFiIkSNHavuGDBmC7777DhkZGRg4cCCmTp0KAPjxj3+Mhx9+GHPnzo2a70UXXaT9fejQIVx00UUoKytDIBDA4MGDW33dEyZM0I577733sG3bNs2aXVdXhz179rQpX4IgCIIgiJ5OZzrDTgXwEwBfMcZKwtt+C0VIv8gYuwLAAQAXhvf9G0rIvL1QwuZd1ollO25wzjFy5Ehs2LDBdr/Xq8SQFQRB+1v9HQqFAFgnaTHGYuabnByJaXrDDTfgl7/8JebNm4e1a9fizjvvtD3G5XJBlpX4vrIsIxAI2ObHOccjjzyCOXPmOF02QRAEQRDE94bOjPLxCZw9u2bZpOcAru/IMrTGktxZeL1eVFRUYMOGDZg8eTKCwSB2796NkSNHxp3HwYMHteOff/55nHbaaRg2bFjc+dbV1aF/f2Up62effVbbnpqaivr6iFt7Xl4eNm/ejAsvvBBvvPEGgsGgbXnmzJmDxx9/HDNnzoTb7cbu3bvRv39/g+gmCIIgjhPk5kEQXQ6tfNHJCIKAl19+GbfccguKiopQXFyM9evXtyqPYcOG4dFHH0V+fj5qampw7bXXwuPxxJ3vnXfeiUWLFmHs2LHIyYksmHHeeefhX//6lzYp8aqrrsL//vc/FBUVYcOGDY4C+corr8SIESMwZswYFBQU4Kc//almTScIgiC6ENLWBNElMN6DF70fN24c37Rpk2Hbjh07kJ+f30Ul6nhKS0tx7rnnYvv27V1dlO8dJ9q7RBDEiUmosgVH71fawl43joann/Py7gRBtB3G2GbO+Ti7fWShJgiCIIieDFmlCaLLIUHdzcnLyyPrNEEQBEEQRDeGBDVBEARBnCjQBEWC6BJIUBMEQRAEQRBEOyBBTRAEQRA9GZ1VmgzUBNE1kKAmCIIgCIIgiHZAgrqDqaqqQnFxMYqLi9GnTx/0798fxcXFyMjIwIgRI7q6eJ3K9OnTYQ5jSBAEQRAEcaJDgrqDyc7ORklJCUpKSnDNNddg2bJl2m9BaPvtpoVTCIIgiJiQywdBdAkkqI8jkiThqquuwsiRIzF79my0tLQAAPbt24e5c+di7NixmDZtGnbu3AkAWLp0Ka655hpMnDgRv/71r7F06VJce+21mDRpEoYMGYK1a9fi8ssvR35+PpYuXaqdZ/Xq1SgsLERBQQFuueUWbfu7776LMWPGoKioCLNmKau/V1dXY8GCBRg1ahQmTZqEbdu2AVBWV7z//vu1YwsKClBaWorS0lIMHz4cS5YsQX5+PhYuXIjm5mbLtb733nuYPHkyxowZg0WLFqGxsbHD7ydBEAQBEtEE0Q0gQX0c2bNnD66//np8/fXXyMjIwCuvvAIAuPrqq/HII49g8+bNuP/++3Hddddpxxw6dAjr16/HX//6VwBATU0NNmzYgAceeADz5s3DsmXL8PXXX+Orr75CSUkJjhw5gltuuQUffvghSkpKsHHjRrz22muoqKjAVVddhVdeeQVbt27FSy+9BAC44447MHr0aGzbtg133303LrnkkpjXsWvXLlx33XXYsWMH0tLS8Nhjjxn2V1ZW4q677sL777+PLVu2YNy4cVr5CYIgCIIgTjRcXV2AzuSjlU/i2IFvOzTPXoOGYMbSq9t07ODBg1FcXAwAGDt2LEpLS9HY2Ij169dj0aJFWjq/36/9vWjRIoiiqP0+77zzwBhDYWEhevfujcLCQgDAyJEjUVpaigMHDmD69OnIzc0FACxZsgTr1q2DKIo4/fTTMXjwYABAVlYWAOCTTz7RhP3MmTNRVVWF+vr6qNcxcOBATJ06FQDw4x//GA8//DB+9atfafs/++wzfPPNN1qaQCCAyZMnt/6GEQRBELEhCzVBdDkntKDubni9Xu1vURTR0tICWZaRkZGBkpIS22OSk5Nt8xAEwZCfIAgIhUJwu90dUlaXywVZlrXfPp9P+5uZ4jKZf3POceaZZ2L16tUdUhaCIAgiGro6mOLmEUSXcEIL6rZako8naWlpGDx4MF566SUsWrQInHNs27YNRUVFbcpvwoQJuPHGG1FZWYnMzEysXr0aN9xwAyZNmoTrrrsO+/fvx+DBg1FdXY2srCxMmzYNq1atwu9+9zusXbsWOTk5SEtLQ15eHt566y0AwJYtW7B//37tHAcPHsSGDRswefJkPP/88zjttNMMZZg0aRKuv/567N27F6eccgqamppw+PBhDB06tO03iiAIgiAIoptCPtTdgFWrVmHFihUoKirCyJEj8frrr7c5r759++Lee+/FjBkzUFRUhLFjx2L+/PnIzc3Fk08+iR/+8IcoKirCRRddBECZfLh582aMGjUKt956K5599lkAwAUXXIDq6mqMHDkSf/vb3wxieNiwYXj00UeRn5+PmpoaXHvttYYy5ObmYuXKlVi8eDFGjRqFyZMnaxMtCYIgiA6GjNIE0eUwznlXl6HNjBs3jpvjHu/YsQP5+fldVKITn9LSUpx77rnYvn17Vxel06F3iSCInkCozo+j93wBAOj9y7Fw90rq4hIRxIkJY2wz53yc3T6yUBMEQRBED4Y5/iAI4nhBgppoFXl5ed8L6zRBEARBEES8kKAmCIIgiJ4MWaUJosshQU0QBEEQBEEQ7YAENUEQBEH0aCgONUF0NSSoCYIgCIIgCKIdkKDuYGbMmIH//Oc/hm0PPvigJVazSl5eHiorK1FbW4vHHnvseBSRIAiCOJFgtn8SBHEcIUHdwSxevBhr1qwxbFuzZg0WL14c9TgS1ARBEARBED0TEtQdzMKFC/H2228jEAgAUBZCOXLkCA4fPozCwkIUFBTglltusRx36623Yt++fSguLsbNN9+MxsZGzJo1C2PGjEFhYaFh9cQ//vGPGDZsGE477TQsXrwY999/PwBg3759mDt3LsaOHYtp06bR6oQEQRDfN8hETRBdgqurC3CikZWVhQkTJuCdd97B/PnzsWbNGvzgBz/ALbfcgs2bNyMzMxOzZ8/Ga6+9hgULFmjH3Xvvvdi+fTtKSkoAAKFQCP/617+QlpaGyspKTJo0CfPmzcOmTZvwyiuvYOvWrQgGgxgzZgzGjh0LALj66qvxxBNP4NRTT8Xnn3+O6667Dh9++GEX3AWCIAjiuEEimiC6nBNaUNe+uQ+BI00dmqenXzIyzjs5ahrV7UMV1Oeffz6mT5+O3NxcAMCSJUuwbt06g6A2wznHb3/7W6xbtw6CIODw4cMoLy/Hp59+ivnz5yMhIQEJCQk477zzAACNjY1Yv349Fi1apOXh9/vbf8EEQRAEQRBEVE5oQd1VzJ8/H8uWLcOWLVvQ3NyM4uJi7Nu3r1V5rFq1ChUVFdi8eTPcbjfy8vLg8/kc08uyjIyMDM3CTRAEQRAEQRwfTmhBHcuS3FmkpKRgxowZuPzyy7F48WJMmDABN954IyorK5GZmYnVq1fjhhtuMByTmpqKhoYG7XddXR169eoFt9uNjz76CAcOHAAATJ06FT/96U/xm9/8BqFQCG+99RauvvpqpKWlYfDgwXjppZewaNEicM6xbds2FBUVHddrJwiCILoQikNNEF0CTUrsJBYvXoytW7di8eLF6Nu3L+69917MmDEDRUVFGDt2LObPn29In52djalTp6KgoAA333wzlixZgk2bNqGwsBDPPfcchg8fDgAYP3485s2bh1GjRuGss85CYWEh0tPTAShW7RUrVqCoqAgjR440TGQkCIIgTlBIRBNEl8M4511dhjYzbtw4vmnTJsO2HTt2ID8/v4tKdHxobGxESkoKmpubcfrpp+PJJ5/EmDFjurpYJxzfh3eJIIiej9QURNkfPwMA9Pn1eLiyErq4RARxYsIY28w5H2e374R2+ThRufrqq/HNN9/A5/Ph0ksvJTFNEARBEATRhZCg7oE8//zzXV0EgiAIojtC3h8E0SWQDzVBEARB9GDIhZoguh4S1ARBEARxokDimiC6BBLUBEEQBEEQBNEOSFATBEEQRE/G4PNBJmqC6ApIUHcwM2bMwH/+8x/DtgcffBDXXnut4zF5eXmorKzs7KJpTJ8+HcOGDUNxcTGKi4vx8ssvA1AWpOlI8vLyUFhYiFGjRuGMM87QFqdxorS0NK4Jl6WlpUhMTERxcTFGjBiBSy65BMFgEACwdu1aMMbw97//XUtfUlICxhjuv/9+AMBnn32GiRMnori4GPn5+bjzzjvbfpEEQRAEQXzvIUHdwSxevBhr1qwxbFuzZg0WL17cRSWyZ9WqVSgpKUFJSQkWLlzYaef56KOPsG3bNkyfPh133XVX1LTxCmoAOPnkk1FSUoKvvvoKhw4dwosvvqjtKygoMPxevXq1YcXISy+9FE8++SRKSkqwfft2XHjhha28KoIgiG4EGagJosshQd3BLFy4EG+//TYCgQAARSQeOXIE06ZNw+rVq1FYWIiCggLccsstlmNLS0tRUFCg/b7//vs16+n06dOxbNkyjBs3Dvn5+di4cSN++MMf4tRTT8Xtt9+uHfPPf/4TEyZMQHFxMX76059CkqRWXwPnHDfffDMKCgpQWFiIF154AQBw/fXX44033gAAnH/++bj88ssBAE8//TRuu+22qHlOnjwZhw8f1q5z2rRpGDNmDMaMGYP169cDAG699VZ8/PHHKC4uxgMPPABJknDzzTdj/PjxGDVqFJYvX27JVxRFTJgwQcsbAAYNGgSfz4fy8nJwzvHuu+/irLPO0vYfO3YMffv21Y4fMWJEq+8RQRAEQRCECgnqDiYrKwsTJkzAO++8A0CxTl944YUoKyvDLbfcgg8//BAlJSXYuHEjXnvttVbl7fF4sGnTJlxzzTWYP38+Hn30UWzfvh0rV65EVVUVduzYgRdeeAGffvopSkpKIIoiVq1aZZvXkiVLNJePqqoqw75XX30VJSUl2Lp1K95//33cfPPNKCsrw7Rp0/Dxxx8DAA4fPoxvvvkGAPDxxx/j9NNPj1r2d999FwsWLAAA9OrVC//973+xZcsWvPDCC7jxxhsBAPfeey+mTZuGkpISLFu2DCtWrEB6ejo2btyIjRs34qmnnsL+/fsN+fp8Pnz++eeYO3euYfvChQvx0ksvYf369RgzZgy8Xq+2b9myZRg2bBjOP/98LF++HD6fL8adJwiC6BmQgZoguoYTemGXd955B0ePHu3QPPv06WOwdtqhun3Mnz8fa9aswYoVK7Bx40ZMnz4dubm5ABRBu27dOk1kxsO8efMAAIWFhRg5cqRmZR0yZAi+++47fPLJJ9i8eTPGjx8PAGhpaUGvXr1s81q1ahXGjbNdPROffPIJFi9eDFEU0bt3b5xxxhnYuHEjpk2bhgcffBDffPMNRowYgZqaGpSVlWHDhg14+OGHbfOaMWMGqqurkZKSgj/+8Y8AgGAwiJ/97Gea6N+9e7ftse+99x62bdum+XjX1dVhz549GDp0KPbt24fi4mLs378f55xzDkaNGmU49sILL8RFF12EnTt3YvHixZoVHAB+//vfY8mSJXjvvffw/PPPY/Xq1Vi7dq1tGQiCIAiCIGLRaRZqxtjTjLFjjLHtum13MsYOM8ZKwv+drdv3G8bYXsbYLsbYnM4q1/Fg/vz5+OCDD7BlyxY0Nzdj7NixcR3ncrkgy7L222w5Va2sgiAYLK6CICAUCoFzjksvvVTzjd61a1eHTrjr378/amtr8e677+L000/HtGnT8OKLLyIlJQWpqam2x3z00Uc4cOAAiouLcccddwAAHnjgAfTu3Rtbt27Fpk2bNPcYM5xzPPLII9r17N+/H7NnzwYQ8aHet28fNm/erLmiqPTp0wdutxv//e9/MWvWLEveJ598Mq699lp88MEH2Lp1q8VKTxAE0WMgH2qC6HI600K9EsDfADxn2v4A5/x+/QbG2AgAFwMYCaAfgPcZY0M55613ANYRy5LcWaSkpGDGjBm4/PLLtcmIEyZMwI033ojKykpkZmZi9erVuOGGGwzH9e7dG8eOHUNVVRVSUlLw1ltvWVwZojFr1izMnz8fy5YtQ69evVBdXY2GhgYMGjSoVeWfNm0ali9fjksvvRTV1dVYt24d7rvvPgDApEmT8OCDD+LDDz9EVVUVFi5cGHNSo8vlwoMPPojCwkLcfvvtqKurw4ABAyAIAp599lnNzzs1NRUNDQ3acXPmzMHjjz+OmTNnwu12Y/fu3ejfv78h75ycHNx777245557NAu+yh/+8AccO3YMoigatr/99ts4++yzwRjDnj17IIoiMjIyWnWPCIIgCIIgVDpNUHPO1zHG8uJMPh/AGs65H8B+xtheABMAbOis8nU2ixcvxvnnn69F/Ojbty/uvfdezJgxA5xznHPOOZg/f77hGLfbjd///veYMGEC+vfvj+HDh7fqnCNGjMBdd92F2bNnQ5ZluN1uPProo60W1Oeffz42bNiAoqIiMMbw5z//GX369AGgiO333nsPp5xyCgYNGoTq6mpMmzYtZp59+/bF4sWL8eijj+K6667DBRdcgOeeew5z585FcnIyAGDUqFEQRRFFRUVYunQpfv7zn6O0tBRjxowB5xy5ubm2fucLFizAnXfeqfl3q0yZMsW2LP/4xz+wbNkyJCUlweVyYdWqVRbRTRAE0XMgEzVBdDWMc955mSuC+i3OeUH4950AlgKoB7AJwE2c8xrG2N8AfMY5/2c43QoA73DOX46W/7hx4/imTZsM23bs2IH8/PwOvhLi+wi9SwRB9ARkv4QjdyjzRPr+diLENE8Xl4ggTkwYY5s557YT0I53lI/HAZwMoBhAGYC/tDYDxtjVjLFNjLFNFRUVHVw8giAIguhhkIGaILqc4yqoOeflnHOJcy4DeAqKWwcAHAYwUJd0QHibXR5Pcs7Hcc7HqREzCIIgCIIgCKKrOK6CmjHWV/fzfABqBJA3AFzMGPMyxgYDOBXAF8ezbARBEARBEATRFjptUiJjbDWA6QByGGOHANwBYDpjrBgAB1AK4KcAwDn/mjH2IoBvAIQAXN/eCB8EQRAE8X2AkZsHQXQ5nRnlY7HN5hVR0v8fgP/rrPIQBEEQxAkPiWuC6BJo6XGCIAiC6NGQiiaIroYE9QnM9OnTYQ4rSBAEQRAEQXQsJKgJgiAIoidDBmqC6HJIUHcSCxYswNixYzFy5Eg8+eSTAJQlyW+77TYUFRVh0qRJKC8vBwCUlpZi5syZGDVqFGbNmoWDBw8CAJYuXYprr70WkyZNwpAhQ7B27VpcfvnlyM/Px9KlS7VzXXvttRg3bhxGjhyJO+64w1KWp59+Gr/4xS+030899RSWLVvWeRdPEARBdA00Q5EgugQS1J3E008/jc2bN2PTpk14+OGHUVVVhaamJkyaNAlbt27F6aefjqeeegoAcMMNN+DSSy/Ftm3bsGTJEtx4441aPjU1NdiwYQMeeOABzJs3D8uWLcPXX3+Nr776CiUlJQCA//u//8OmTZuwbds2/O9//8O2bdsMZbnwwgvx5ptvIhgMAgCeeeYZXH755cfnRhAEQRAEQZzgdFqUj+7A7t1/REPjjg7NMzUlH0OH/i5muocffhj/+te/AADfffcd9uzZA4/Hg3PPPRcAMHbsWPz3v/8FAGzYsAGvvvoqAOAnP/kJfv3rX2v5nHfeeWCMobCwEL1790ZhYSEAYOTIkSgtLUVxcTFefPFFPPnkkwiFQigrK8M333yDUaNGaXmkpKRg5syZeOutt5Cfn49gMKjlQxAEQRAEQbSPE1pQdxVr167F+++/jw0bNiApKQnTp0+Hz+eD2+0GCw/HiaKIUCgUMy+v1wsAEARB+1v9HQqFsH//ftx///3YuHEjMjMzsXTpUvh8Pks+V155Je6++24MHz4cl112WQddKUEQBNHlkJcHQXQ5cQtqxlgS57y5MwvT0cRjSe4M6urqkJmZiaSkJOzcuROfffZZ1PRTpkzBmjVr8JOf/ASrVq3CtGnT4j5XfX09kpOTkZ6ejvLycrzzzjuYPn26Jd3EiRPx3XffYcuWLRaXEIIgCKInE1HU5EJNEF1DTEHNGJsC4O8AUgCcxBgrAvBTzvl1nV24nsrcuXPxxBNPID8/H8OGDcOkSZOipn/kkUdw2WWX4b777kNubi6eeeaZuM9VVFSE0aNHY/jw4Rg4cCCmTp3qmPbCCy9ESUkJMjMz486fIAiCIAiCiA7jnEdPwNjnABYCeINzPjq8bTvnvOA4lC8q48aN4+Y4yzt27EB+fn4Xlah7c+6552LZsmWYNWtWVxelR0DvEkEQPQEucxz+7ScAgH6/nwQhyd3FJSKIExPG2GbO+Ti7fXFF+eCcf2faJLW7VMRxo7a2FkOHDkViYiKJaYIgCIIgiA4mHh/q78JuH5wx5gbwcwAdGzqD6FQyMjKwe/furi4GQRAE0clEH3MmCKKziMdCfQ2A6wH0B3AYQHH4N0EQBEEQBEF874lpoeacVwJYchzKQhAEQRBEa9FF9uCMbNQE0RXEE+XjGdiMInHOaak9giAIgiAI4ntPPD7Ub+n+TgBwPoAjnVMcgiAIgiBaA9MFn44VuYsgiM4hpg815/wV3X+rAFwIwDZkCOHM0qVL8fLLL3d1MeLm7LPPRm1tbdQ0K1euxJEj1LciCIIgCOL7TVxh80ycCqBXRxeE6F78+9//RkZGRtQ0JKgJgiC6F5xWSiSILiGmoGaMNTDG6tV/AbwJ4JbOL1rP5rnnnsOoUaNQVFSEn/zkJwCAdevWYcqUKRgyZIhmrW5sbMSsWbMwZswYFBYW4vXXXwcAlJaWIj8/H1dddRVGjhyJ2bNno6WlBQCwceNGjBo1CsXFxbj55ptRUKCssSNJEm6++WaMHz8eo0aNwvLlywEAa9euxemnn45zzjkHw4YNwzXXXANZlgEAq1evRmFhIQoKCnDLLZHHmpeXh8rKSsdyvPzyy9i0aROWLFmC4uJirWwEQRAEQRDfN+Jx+UjlnKfp/h3KOX/leBSup/L111/jrrvuwocffoitW7fioYceAgCUlZXhk08+wVtvvYVbb70VAJCQkIB//etf2LJlCz766CPcdNNNmg/cnj17cP311+Prr79GRkYGXnlFue2XXXYZli9fjpKSEoiiqJ13xYoVSE9Px8aNG7Fx40Y89dRT2L9/PwDgiy++wCOPPIJvvvkG+/btw6uvvoojR47glltuwYcffoiSkhJs3LgRr732muV67MqxcOFCjBs3DqtWrUJJSQkSExM785YSBEEQccApEjVBdAmOkxIZY2OiHcg539LxxelYfrfnELY3dqzltCAlEX88dUDUNB9++CEWLVqEnJwcAEBWVhYAYMGCBRAEASNGjEB5eTkAZQLJb3/7W6xbtw6CIODw4cPavsGDB6O4uBgAMHbsWJSWlqK2thYNDQ2YPHkyAOBHP/oR3npLmTf63nvvYdu2bZr1u66uDnv27IHH48GECRMwZMgQAMDixYvxySefwO12Y/r06cjNzQUALFmyBOvWrcOCBQsM12NXDoIgCKIbQnqaILqEaFE+/hJlHwcws4PLcsLj9Xq1v1Ur9KpVq1BRUYHNmzfD7XYjLy8PPp/Pkl4UxZhuFZxzPPLII5gzZ45h+9q1aw2zwAFYfsdb7njKQRAEQXQNrajaCYLoQBwFNed8xvEsSGcQy5LcWcycORPnn38+fvnLXyI7OxvV1dWOaevq6tCrVy+43W589NFHOHDgQNS8MzIykJqais8//xwTJ07EmjVrtH1z5szB448/jpkzZ8LtdmP37t3o378/AMXlY//+/Rg0aBBeeOEFXH311ZgwYQJuvPFGVFZWIjMzE6tXr8YNN9wQ93WmpqaioaEh7vQEQRBE50IuHwTRNcQThxqMsQIAI6DEoQYAcM6f66xC9XRGjhyJ2267DWeccQZEUcTo0aMd0y5ZsgTnnXceCgsLMW7cOAwfPjxm/itWrMBVV10FQRBwxhlnID09HQBw5ZVXorS0FGPGjAHnHLm5uZpP9Pjx4/Gzn/0Me/fuxYwZM3D++edDEATce++9mDFjBjjnOOecczB//vy4r3Pp0qW45pprkJiYiA0bNpAfNUEQBEEQ30tYrCDwjLE7AEyHIqj/DeAsAJ9wzhd2euliMG7cOL5p0ybDth07diA/P7+LSnR8aGxsREpKCgDg3nvvRVlZmTbx0Y61a9fi/vvv13ytifj4PrxLBEGcGBy69WMAQM4dY5GQmNTFpSGIExPG2GbOue1aLPFYqBcCKALwJef8MsZYbwD/7MgCEq3j7bffxj333INQKIRBgwZh5cqVXV0kgiAIojtATtQE0SXEI6h9nHOZMRZijKUBOAZgYCeXi4jCRRddhIsuuiju9NOnT8f06dM7r0AEQRBEt4CWHieIriFa2LxHAawG8AVjLAPAUwA2A2gEsOG4lI4gCIIgCIIgujnRLNS7AdwHoB+AJiji+kwAaZzzbcehbG2Gc96qsHAEYYasPARB9EQ4o7qLILoCx5USOecPcc4nAzgdQBWApwG8C+B8xtipx6l8rSYhIQFVVVUkiIg2wzlHVVUVEhISYicmCIIgCOJ7T0wfas75AQB/AvAnxthoKML69wDEqAd2EQMGDMChQ4dQUVHR1UUhejAJCQkYMKBr4pgTBEG0FTImEUTXEFNQM8ZcUELlXQxgFoC1AO7s1FK1A7fbjcGDB3d1MQiCIAiCIIjvCdEmJZ4JYDGAswF8AWANgKs5503HqWwEQRAEQbQGmj9EEF1CNAv1bwA8D+AmznnNcSoPQRAEQRBthJYeJ4iuwVFQc85nHs+CEARBEARBEERPxDHKB0EQBEEQPQualEgQXQMJaoIgCII4USAXaoLoEkhQEwRBEMQJAvlQE0TXQIKaIAiCIAiCINoBCWqCIAiCOEEgCzVBdA0kqAmCIAjiRIF8qAmiSyBBTRAEQRAnCBTlgyC6BhLUBEEQBHGCwGilRILoEjpNUDPGnmaMHWOMbddty2KM/Zcxtif8b2Z4O2OMPcwY28sY28YYG9NZ5SIIgiAIgiCIjqQzLdQrAcw1bbsVwAec81MBfBD+DQBnATg1/N/VAB7vxHIRBEEQxAkJuXwQRNfQaYKac74OQLVp83wAz4b/fhbAAt3257jCZwAyGGN9O6tsBEEQBEEQBNFRHG8f6t6c87Lw30cB9A7/3R/Ad7p0h8LbCIIgCIKIgt4qTWHzCKJr6LJJiVypAVr95TPGrmaMbWKMbaqoqOiEkhEEQRAEQRBE/BxvQV2uunKE/z0W3n4YwEBdugHhbRY4509yzsdxzsfl5uZ2amEJgiAIorujt0qThZoguobjLajfAHBp+O9LAbyu235JONrHJAB1OtcQgiAIgiAIgui2uDorY8bYagDTAeQwxg4BuAPAvQBeZIxdAeAAgAvDyf8N4GwAewE0A7iss8pFEARBECcSBh9qivJBEF1Cpwlqzvlih12zbNJyANd3VlkIgiAIgiAIorOglRIJgiAIogdDPtQE0fWQoCYIgiAIgiCIdkCCmiAIgiB6MGSVJoiuhwQ1QRAEQfRkSE8TRJdDgpogCIIgThAoygdBdA0kqAmCIAiiB0OTEgmi6yFBTRAEQRAEQRDtgAQ1QRAEQfRgDBZqcvkgiC6BBDVBEARBEARBtAMS1ARBEATRgzEsPU4+1ATRJZCgJgiCIAiCIIh2QIKaIAiCIHowZJUmiK6HBDVBEARBEARBtAMS1ARBEATRgzH4UFOUD4LoEkhQEwRBEARBEEQ7IEFNEARBECcI5E9NEF0DCWqCIAiC6MHQ0uME0fWQoCYIgiAIgiCIdkCCmiAIgiB6MDQpkSC6HhLUBEEQBEEQBNEOSFATBEEQRA+GfKgJoushQU0QBEEQBEEQ7YAENUEQBEH0YAxWaTJQE0SX4OrqAhA9j6BfAuccbo+IoF+CrymI1KwEcACBlpC2zZvogixx+FtCcLkFMMYgiAxMYAj6Q0hM9UAUBYhuAZxz+JtDCPhCSErzABwQ3QIEkUEQBTAGMMYAKJNuZJlDCsqQQxwJKW5wzrX9BEEQBEEQxxMS1K2kqdaPz9/8FlWHGpGY6kHAF4LoEiCFZAgigzcxIu5EtzIAoArQlvoAktK9SM30QnAJqDzUCNHFkNUvBQFfCAlJbjTV+XFkdy0y+yYjs28S/E1BJKV7EfRLCPklJCS7EfBLyvkEBoRndLc0BuFJcCEUlCCFOEQXgyxxcA5IIRneRBe4zCFJHOAcgkuAvzkIX1MI3kQXQgEJLo8IJiii1O0VEQpIaKr1Q3QL8DeHIIgMdcdajDeEAeCAIChiWQrJ6MhJ5oKLgUuK/cXlEiB6BHBZEe4q3mQXgn4JiSkeJKa6kZDsRnKGF0GfhOQML1KzE+BvCiI5w4vkDC9Et4DsfslweUR4EkQIIg3UEATRczFE+SATNUF0CSSoW4noFrB/ayWy+yWjuT4AzjmCfgmiSwCXOWobmsEYA+dcEZcyB5cBl0dAc30AzfUBlO2rhb85pA3NHfy6Gt4kRRTKkrKxodqHQzurkZjqQUt9AGCKaJU5BzjgTXYDnEOWOESXALdXRMAXgifRBZdHhBySAaYIbkXsCwgFJDCBweURASj5uTwC6itbIIgMYliwc87RUNUC0SUgMdUDJgDZ/VIghWSkZiUgMdWDnIEpCPolgAOeRBd8jQH4GoNISPUgJcMLT6ILTbV+MIEho3cSQgEJ/uYQXGFB7PIIaKzxK9bmkIxQUIbLLSA5wwtfYwhSSALnQNAnaVbtUFBWrNKSDHeC8up6k1yoq2iBN8GFpno/mmr9CPolHNpRDU+iC9/tqFbK6YDLI6DPkHRwmSM1JxFut4DUnERk9EpEUpoXSekepGR6yfpNdBlBvwQpKMOb5NI6vACU7z2BqvDWoI5uBX0SXG6lThbdAlxuAYJLGRHjMsex0npk9k2GIDB4k9zwNQYhegQIglIXCQJDQ7UP3iRXhzwDLnMgPArHZQ6ZcwiMKU0E51qnP9ASQigow5vsApe4NoIX7zlkzsEACKIAWZJRV9ECKRQe7ZM5gr4Q/M0hpOYkoKnWDznE4faKEN0CRBdD0C9DdAuQQzJcXhFSQEZ6r0Q01frRWONHWk4ipJCEpHQvGAMaqv1oqQ8gJdOrGH3CxhsxPGJZdagRiWlucBkIBRRDkegSILoEyBKHrykIMMDlFgAoRpvEVDea6wIAFMNPRu8kZPVNBhMZRJGh6nATkjO8SExxQ5Y4JElGoEWCJ1EEeKTzwWVAkpQ2JTndi6Y6P7xJLoSCSrudkOxGMCDB7RG1ZyO6lHvtbwnB7RXBZaX99yS6IAhMy1ttL1oaAggFZTTW+OH2ikhMdePovjq0NAbh9opgAhAKKGXwNQU1I4/LIyqjwF6lrWZgkGUOznlYU/Dw77AukLlSdr8ESVLa1NpjLXAniHB7ReU9dwkA5/C3SPB4RXiSXPA1BCFLyjMV3co9T8lMAKBoEG+iC6lZXoAx1JY3IyHZjewBKWis8YHLgCdBhCfRhcRUNwI+CYHmkPYMG2t8SMlKUNpvMNSUNyMxxa205QEJYEDOgBRwWanjVMOjv1kxlrk8SnkSkt0AlPeDMaY9i/5DMzQt011gPTlm5bhx4/imTZuO+3mloKxZn9ucR0gGExTra3NDQHGZCH8sjDFDw6m5WHiVCgE69wciOpxzNNcHkJDshq8piMZqP5rr/airaIEscdQda8bBHdUQBIaWhiAA2AtwBvQalAZRZOg1OA0pGV5k90tB78Fp8CR2L1Hjawyi5mgTPEkuuL0immr8aG4IwON1obHWD5dbQFOdX+kINQWRkOxGSoYX9VU++JuD4FzpiwmCAA4OIVwB+hpDCAaUdzGjVxIaqn2QQrJWGYqigOZ6P0S3CJdHQEt9AG6viPTcREgSR3OdX3MBUjpuADhHVr8UpGR64W8OobneD0+CCxyA2yOACQxurwgpxCEIgNvrQs3RJtQcbUbfU9Lh9orwNQYhhBuLUEBGKCTDk+CCHJLBmNLYyLIyMpOemwRJkpUOaIsiHhgDktK9WoPoawrC5VYa0aQ0D/xNIfiaAmCM4dCuGqRmJyA1MwFHv62DvyWE5AwvWhoCSM7wag2jJ8GFgC+E+kofktM9YfclAaLIwiKIQQgLB39TED5dB5sJQFKakqcUklFztDlcLwCucB3gThDRXBfQRmS8SS4kpHgAQBttSkr3QArKSMn0IhRQBJPaEAealWfAGOBOdEEKyIoBANBGvZjAtM46lzlaGoPaSJQ7QURDlQ/eJDe4zCF6BLg9IuoqWsBlju92VMPfHEKvvDSk5yYiFJBQe6wFUlBCKCDDk+hCoCUEb5Ly7XAOrXyqOxkTmCIYRKZ0ugMywKCJGG+yWxtdC/qVa5ZCMvzNobBggybOgj5lWygoa2IsHhgDsgekoOpwk3J8uG5whfNiTBF1okeE2yPAneBS2geXAJdHKUNjjR+MMUiSDHBFxMkhxRiijvDJkvKuehKVUcZQQNYVAkhK9UBwMTTXByCHjG22IDBwcMxLU4THOyEZckAxtLDwOy1Lynfsbw5BEBiSMjwI+iX4m0I4kQjbkJTRWwbNQNVReMN1amON37BddAvwJIgItEha/SK6BPgagx16/tYgiCxc74X/DnfA3AkiQn7le3d5BLjcIkIhWXu3ewqX3D0FqVkJx/28jLHNnPNxtvtIUBNEBFnmOLqvFod31yItJxFH99WhvqoFlYcaFXeblpBtZepyK41XYqoHCckugAOp2QnwJLgguBjkEFca5ICEgE+CO0GEvzFoGD1wJ7g0K43ay09MccPXHEJ9ZQuy+6cAXLEcyBIHE4DG6v/f3p0HyXFfB57/vqz77Or7BhoHGwBB3CApgOBpiqI9tseSuA6PVh55PB5t7O54wt7d2bF3vLZmNtbWOuwNxVge78ojSxprJPkarWTRNnVQIkGKJ0AcJAEQRzfOvqurquuuyvztH1lV7AYaJMBmd6HB94kg0VWZVfkq8+UvX/7yV1mlRoEmIpRL1WU7SPoCbm9HpWxTKbq9Mj6/5RYTAQ+ObQjHfZQLNuVClWDULdjSU4VageEhFPXhDXiYHc+RT5cJx/3kUqXGMKFgxIdjO5SLtca9VnBcvb6DYS+5WmFUP7c0xi043Z4092qP1+9pFLHVsrPoyVJ9yNa7qvWopMbz2LZb+PWub3G/Q9AeJJcq4wtYBGp5Egh5CcX8lPJVt4iyDU7jX/e/+nb3Bz2Nnj+x3MIpHPcjInQMRglF/RSyZSpFt5emVHSL0UrRppSvUMq7eWlXHKR24pGdLVIuVDHG/YwGt1D1eN3eqFyqVMsjweuzagXY2x/Xsd2rW3bFXTf1E8dK0T2piiQClIu2e8JVOyAHIz58AQ9zySItnSHCLf7GlSqvz0OsLYDH56m9n4dyvgoiiOV2EliWIFLrlbfdoWt21bjxzVs/gZCXYr5Kufb9DF/QQylfxRf0YBy3ZzAQ9tZ6Yg3+kKd2dcv9zkWkJYBtu1fc6lfI6lcU6/PMXMoC7v4Waw/h2A4zl3OE434iLX6ibcHGCWW14n7+fKZMIOzDrjpUy24O1jtLvD4Lar2cllcQoFyysWonfcGIj3LRLXhDMR921e0MqPfIGscQiPoIhn0UsmW3banldckpsvGVJACHNgToaG1t5JgBLHHbNrdX1M0vgLbeiNu7GfISbvGTTZaolG1ae8LE2oJ4vJbbg1p1sG3HLb4q7j5Uzrv7ePJKzu2pD3kp1U7U6u8fa3OvVuYzZfwhL3bVwR/wUiq4Ods9FG+cPNi2e/JnV9z9BME9ua6dEIi4RWE+UyLSEgBxczE5liM1kQeglK/S0hlidjwHuFdyK8UqvqDX7STwuFcZ6upFpXviG6BcrFIt20Rbg1RKbjtdLdu1Ez3IZ8oU5srE2kN4a9/9CUZ8bgdN1SEQ9uHxWVSKNpVSFY/P7UEPRX3MJYt4vBZdQ3EiCfdE3Rg31+ptfbXi1F7r5pQ7fPTtkwSp7yu1qyT1deAL1PK/djXB8kjjhLlctBttRX37u1eGTePqL7j7XLno9jAXsxVCMT+hqK9xJVnEbVfnkkWCUV/jmFfKVcily27b7nc7U+yqcf+t9fYbY9yr6rhXBnKpEuG4n9lx90TVH/Di8QkgC/bz+ueq52j9ChNA50BsyR2b74UW1Eq9j4wxpCcLjJ1Nk0sVKRdstwc3X21cMq1WHGbHcpja/F6fB8d2Gpf0ykWbUNTtpa1Pt6vulY96g18tu0VFMOIjEPKQHMsTCHsJx/3usB7bEGsLNApcyxJCcXeISntflEptDHy8I+QOHZpzG73MTJH2/ihen0Ug4iWfLlMuVIm0BgjUiiaxZEHvjs/vaTRedtUhlyoRaw8u6UqJbTt4PBblots76w14Gl8+bTT4XnFPQPyWe5ApOwRjPjweq9GbHoz4sG0HUyug69uofiWpHqNtO+Rm3Ya8UrLxB71Uyu7BplyoNi4B1w9sdsWhXKwSCLsHD1NbD7btFgDGcbfbraretjd6qayFV74c2z1o3cg2nD8kwbGdRpE+n+O4wwnmL0OtjFQxRfYzxwGo/uYgQy1DzQ1IqdvUOxXUt9a1aqVWARF3XHiiO/yu89bPqK0bLFxWQu/GhY9DtaECN8rjtYh3hJYch6c29nOxMajul3rd9VUv8gNhi8C8VR4I+xa+l2fh668eX+fxvB13fVr9JGH+ewH4PRYEIRS7dt3U4+bWraWBt4eFeTyL593NfBl3fpF8vddZWkg3jf6wi1LNpwW1UstIRK5b0CillFLq9qD3C1NKKaVWMe2hVqr5tKBWSimllFJqCbSgVkoppVaxBTcX0A5qpZpCC2qllFJKKaWWQAtqpZRSahXTMdRKNZ8W1EoppZRSSi2BFtRKKaXUbWI1/1ibUquZFtRKKaWUUkotgRbUSiml1Co2v1dax1Ar1RxaUCullFKrmH4pUanm04JaKaWUUkqpJdCCWimllFrFFgz50C8lKtUU3mYsVERGgTnABqrGmL0i0gb8BTAEjAI/b4yZbUZ8SimllFJK3ahm9lA/bIzZaYzZW3v8G8APjDF3AD+oPVZKKaXUO9Bx00o136005OMfA1+p/f0V4OeaF4pSSimllFI3plkFtQG+KyKHROTTtee6jTFjtb/Hge7mhKaUUkqtTtpbrVRzNGUMNXDAGHNZRLqA74nIyfkTjTFGRBZtFWoF+KcB1qxZs/yRKqWUUkop9Q6a0kNtjLlc+3cS+CZwDzAhIr0AtX8nr/PaLxhj9hpj9nZ2dq5UyEoppdQtSe/yoVTzrXhBLSIREYnV/wYeA14Hvg18qjbbp4BvrXRsSimllFJK3axmDPnoBr4pIvXlf80Y8w8i8grwlyLyz4HzwM83ITallFJqVdFfSlSq+Va8oDbGnAN2LPL8DPATKx2PUkoppZRSS3Er3TZPKaWUUjdJe6iVaj4tqJVSSqlVbMEXEbWeVqoptKBWSimllFJqCbSgVkoppVYxHfKhVPNpQa2UUkoppdQSaEGtlFJKrWbzh1DrD7so1RRaUCullFJKKbUEWlArpZRSq5iOoVaq+bSgVkoppZRSagm0oFZKKaVWMe2hVqr5tKBWSimllFJqCbSgVkoppVax+Xf20Lt8KNUc3mYHsJqdPn2aY8eOcf/991MqlTh37hwPPPAAP/rRjxgeHqa/vx+A6elpXnvtNcLhML29vbS1tfHSSy/xyCOPcOzYMYwxTE9P09bWhogwPT3Ngw8+yMjICLlcjmQyyX333UcsFuP06dNMT0+TyWTo7OykWCyyf//+BXGNj49z4sQJhoeHOXnyJA8//DA//vGPGRgYYGhoCICXXnqJ9vZ2ZmdnicfjbNq0CYBcLsezzz5LR0cHgUCA7du3UyqVeOqppyiXyzz22GNMTEwwPT1NKpUik8nwyCOPcOTIEdrb28lms1SrVbZs2QLAiRMnePjhh3nuuedYs2YNa9euXRDrq6++yujoKNu3b2d4eLjxfD6f55lnnuHBBx/k/PnzlEoldu7cueC11WqVH/zgB+zZs4fXXnuNnTt3cvToUbZt28Ybb7yxIAav18u6desYHBxkZmaGQ4cOEYlECAaDnD17Ftu2icVi7N+/n5dffpm2tjbC4TAbNmzgRz/6EZ2dndi2zezsLB0dHZw6dQqfz4cxhnXr1jEyMoLjOAAMDAxQKpWYmpoCwLZtOjo6CAaDJBIJTp48uehBzxiDx+Nh+/btFItF3nrrLTZv3oxlWbz++uuL5uDGjRvZtWsXP/zhD5mdncXj8bB//34qlQrPP/88AL29vRhjGB8fZ9OmTSSTSQKBAIODg1y6dIl0Ok08Hqevr49kMsmZM2fYtWsXhUIB27aZmpriQx/6EC+++OKC9bB7926OHj1Ke3s7lUqFPXv28PTTT7Nr164F+bBhwwZOnz4NwIYNG3jrrbcYGxujq6uLcDhMOBxmenqaPXv28IMf/IBwOExrayvnz5/H4/GwdetWbNvmzTffBGD9+vWMjY3R3d3d2BcA1q1bRzqdJpPJ8Oijj9La2srTTz/dyIdEIkE6neahhx7i4MGDxONxTp06RSKR4NFHH2VmZobnnnuOQCBAe3s7IyMj7Nq1i4GBAQ4ePEh7e3tj/+zs7MTj8bBr1y4A3nrrLWZmZshkMnR0dFAul+nt7eWFF15gYGCAcrnMXXfdRVdXV2NfCIVCHDt2jEAgQCQSYXp6mmg0yvnz5wEYHh5mamqKRx55BL/fz5EjR/B6vdx11128/vrr2LbNjh07OHnyJKlUinQ6zd13382LL75INpvlkUce4dChQySTSQBEhOHh4cb6Ghsb4/777ycQCHD06FF27drFa6+9xrZt2zhy5AjxeBy/378ghrrjx49jjGF4eJgf/ehHHDhwgGg02pg+OjrKzMwMe/bsWTRv1ftLh3ncvPPnz3Px4kUOHDjwrvMmk0m+//3vE41GaW1tpb29neHhYQ4fPkwwGGTt2rWNNuLMmTOA206Nj4+TyWTw+/1Uq1WMMfj9forFIqFQiEqlgmVZDA8Pc+rUKQB6enqwLIsrV65w3333MTIywuTkJJVKBRFZEJdt21iWdc3zxhgikUij3c5ms1iW2386NDTE3NwcbW1tjIyMNGLYuHEjIyMjtLa2IiJMTk4C7nG2o6ODeDzOhQsXANi0aRNnz56lWq0SjUbp6enBcRwuX75MqVQCIBgMMjg4yOnTp1m/fj1TU1PMzc01YnQch6GhIfr7+3nhhRdwHIdAIEC5XGZ4eJiRkREKhQLhcJh169Zx+vRpHMfB7/eza9cuNmzY8F42+7KS1Xw2u3fvXvPqq6+u6DLz+TxPPfUUjuPwxhtv4DgOHR0dTE9PA27BcPbsWQB27NiBMYYTJ05QqVQa7xGNRslms41CbDE9PT2Mj483Hre3t9Pf38+xY8eumXfbtm1YltUo0s6cOUM+n29Mnx/T9u3bMcZw/PjxBe9Rj3V8fLyxI9Xnn52d5eLFiwC0trYyOzt74yvsOusEuCaO+dMmJycZHx+nt7eXsbGxa6YDZLNZzp07d1OxbN++nVOnTjV2+qt5vV6q1Wrj8fzlr5RAIHDd+BYzNDTE6Ojo8gUE+Hy+BTm8mPXr19/09phPRBY90biRZV9tfmN+tY0bNzYOeu/0XF1nZ2fj5Ohq27ZtQ0QW3S8Xs3nzZk6ePAlc//Nebc2aNSQSicYytm/fvujfAJZlNU7sbpTH48G2bUKhEIVCYdF51q5dS0tLS+NxfZmDg4NcvHiRjo4O+vv7Gwf2I0eOAHDXXXfh8/kolUr4/X4cx2FgYIB77rnnpmJ8N+Vymeeee457772XSCTCyMgIqVSK7du38+yzz5LJZLj//vtpa2tjbGyM0dFR9u3bx+TkZOPE9c033+TAgQONwmO+bDbLyy+/zP3338+pU6fw+/0LOgDK5TIHDx5k3759+Hw+Dh48yN13300sFgPc4qFecOVyOe69916MMfz4xz9m48aNnDt3jqGhIXp7excsd25ujkOHDnHgwAG8Xrf/6/jx4wSDQQYGBnjxxRfZv38/V4pX8P3eJQCm/6cYO7t2cu7cOTKZTKMjoh7Dtm3bOHnyJBs2bKC7u9t9zfQ0p0+fRkRYs2YNwWCQY8eOEYlE6OrqorW1lVdffZUHHngAr9dLPp/nhRde4P77728UiM8//zz79+8nFAo1lh2Px8lkMmzbto1nn32WXbt2EY/HOXjwILOzsxw4cIBqtcq5c+fYt28fExMTjb9feeUV+vr6GBgY4PDhw7S1tdHe3s4rr7zCnj17OHToEG1tbYyOjmJZFoODgySTycZzjuOwdu1aMpkMe/bs4fDhw3R2dlIoFMhmszzzzDONHK2v20qlgs/nA9z9s1wu4/F4OH369DX7xvx9r7u7m4mJifeewLcIv99PuVxudhjA2+3SYlpaWvjVX/3VxnZbSSJyyBizd9FpWlDfnEwmwxe/+EVEhO7uboaGhnjppZdwHIdMJkMikSCVShGPxxsNs4g0itBwOEwgEGB2drYxb72AsiwLy7KoVqu0tLSQz+cbZ7WJRAJwG+56sRyJRMjlco1pdZZlkUgkmJ2dXbCcaDTaSMBUKtU4gAYCAUKh0IJYPR4Pxhji8XhjfoBEIkGpVFrQuNTfPxaLNc5A6wffdDq96PKvXi/197netKunz5+n/v71f1taWkin0wtiAIjFYng8nmu2x/yTj/p71LdFNBollUrh8/ka2yIYDGLbNlu2bOHYsWNs2LCBVCrFzMzMtQmDW/D6/X5s2yaZTL7jCcm2bdu4cuUKs7OzhMNhurq6uHDhwoIi/2r1mME94YlEIqTT6QW9AXXzt1E0GiWRSBCLxahUKiSTyUZvZiAQoFKp4PF4qFQqjWXMXw+dnZ1Eo1HGx8cpFArXbIf6suoHVXDzYt++fYyOjjYKy/oJ5vzP0dPTQ1tbG5ZlMT4+TiqVaqyDeo/O7OwsExMTbNmyhenp6QVFbz1X5udDPY75y5k/fzQaxbKsRi9MfT2EQiFSqRQejwdwe4XqPU71HCsWi419or5f1j9XXUtLCyJCIBAgGAySTqcbcVw9L9DYP1tbWwG37RERotEouVwO27aJx+MUCoXGCdj8z7bY55y/LeqPLcsilUrR2tpKa2srmUym0UFQj+HqfXNubg7HcYjFYgv2NWMMxWJx0YPy/IJ927Zt+P3+xkHT6/U2TgTqRbmIYNs2IoLH48FxHIwxjenzT8yTySTnzp2jq6uLNWvWUD8ubNq0qdHzFwqF2Lp1a2Pajh07GlcI67Zu3dpoC+cbHR1lenp6QefA3r1vH1Onp6cZHR2lp6encSWxra2N9evXA+6VvxMnTjTm37lzJ7ZtX9Oxcffddy9YBy+//DLgnvAlEgmMMRw6dAiA/v5+Ll++7BbAiSCewzkMUNzhoyPU0fic9TjrMdRP5ILBIHfddRcAVx9Hrz65qufS8PAw8XicixcvMjExwbp162hvb2dycpILFy7Q399Pb2/vNe9X3w6xWIzBwcHG1ab5Bdz8AnXLli2N9bV7924OHz4MQFtbG8lk8qYLv3c6KW9pacEYg23b5HI5YOF+EolE8Pv9C9rtYDDY2Id9Ph/hcJhUKrWgQ6beTuXzeVpbWzl69Cg7d+5kYGCA8+fPs379er71rW9ds7z5YrEYiUSCBx54gK9//evXnCy3tbXR29vLG2+8cc1rh4aGKBaLJBIJpqamrjk+tbW1MTg4yNGjRwH32PH4448zNzfHk08+2dgvBgcH8fl8CzpLrj5udnZ2kkgkrunAqG+nxToPNm3axNzcXOM/cPeLI0eONK4aHj9+nEAgwKVLlxrHpi1btjA2NsYnP/lJOjo6rvncy00LanXLGh8f5zvf+Q6f+MQnCIfD10xPJpP89V//NR//+Mdpb29vQoSrw6FDhzh//jwf+9jHmh3KquA4Dt/4xjfYunUrO3bsaHY4t5VsNstXvvIVpqam+NSnPsXU1BSnT5/miSee4LOf/eyCA+v8QufqQnax3vL6PNfrSQ+Hw4gIhUIBx3EWHPhDoRAiguM4FItFwuEwxpjGZeV8Pn9NGzT/Unoul1vwfvV56/PkcrkF8dWXV58nl8s1Cox6nPUCDmicYNQ5jtM4UZq/rPpr6idu4XAY29hI3i22TNjCa3kXrIOrX5tIJAgGg40ibn5x5Pf7G73Q4PYUBoPBxrLmv9dij0UEy7KIxWKMjY01hh/Mn16PIxQKNU7CwuFw4wSxUqmQz+fx+Xz4/X5yuRyWZREKha7ZDvUY+/r6uHjxIi0tLXR3dzeGpiWTycb88wvejRs38olPfKLR8VWtVvnqV7/Krl272LFjB2+99RbPPvssn/zkJwkGg4vmm1p5xhgcx1mwr6wkLaiVUko1nW3bfPGLXyQQCFAsFvnUpz7FV7/6VbZv337NMJBz587x5JNPEggEuHLlCvv37+exxx4D3BPxv/zLv+SRRx7h6aef5oknnqCvr68ZH2lJKpUKX/rSl9izZ881480dx+HrX/8669evZ9++fe/4PudS5/B/9jIAk78eYXf37kXnKxQKfOlLX+Khhx7izjvvXLCsL3/5y2zfvn1Bz7tSaiEtqJVSSqnb1I0W1EqppXmnglpvm6eUUkqtYvrDLko1nxbUSimllFJKLYHeh/omlYsFTj73zDvOczPDaBpfepHG/656DqTxx8J7TS6YdwUt+zChFRiGZDBg6p/lXZa3yGRjjPtaYzAYjLPY+9S35/ynas8h1z63YFPKvMmy2NM3OM/iy7rmNVdHLovkXP0zv9P8i09cGNZV733182+/12Lr5er0eH9+0OLm9qMbn/fm3vYm3vcmYrhm1vd593rfe0RX8TDERYm420vm/c21600QxBJELNzZF99v3XkXmsheYQ0JAGbePM3oYnf6fC/HivfwmpvKzbdf9J68t+PfO73mZnLvnZd9TWiLxbrgB3mujWE5j7Xvd+2wWKzXbcuvPg5e9/mrjwFvx9y1bgPe2i0ObxVaUN+kYjbL9/70880OQymllGpYs+7fAHD8//kqx99lXqVWu3/xx18i3tHZ7DAW0IL6JkVb2/jv/uQr7z7jjZz91e+jWustdZ+qn+WZhf8seqa62K/tvbeOiJu3vAtZkZ732lUBEXnXj7NYr4vU7zM+737jjZU/7x6513iXnwle8Nz8eedvb3Od+a/OiRudb/6i5udl/fH8noN37jK+avFmwTxX98I0Yrru86bx7MLO+ev1tL+XvLnxXqCb6jG6iXlvqh/qZt73vVxReC/e5/db+etuy6dxNav294L9af49tevz1O63Pf/1V73jNcu4OHcJ/sr9e+ev/TJb2rdcFcN7CvzmX/Jerla8117Y97Ko673o6jbuvb7P/Pe77sOFrdm7X8F813Bu3vvY8W0w1/Y0z1vGzR4Drp5//jFgvlDtNzJuJVpQ3yTL4yHapvdDVkopdWvIzXoB95d14+sG6evZ8s4vUEq97/RLiUoppdQqpnf2UKr5tKBWSimlVrF3HiKilFoJWlArpZRSSim1BFpQK6WUUrcJHf6hVHNoQa2UUkoppdQSaEGtlFJKrWL60+NKNZ8W1EoppZRSSi2BFtRKKaXUKqZ3+VCq+bSgVkoppZRSagm0oFZKKaVWMR1DrVTzaUGtlFJKKaXUEmhBrZRSSq1iC3qltYNaqabQgloppZRazRbU01pRK9UMWlArpZRSSim1BFpQK6WUUquYfilRqebTgloppZRSSqkl0IJaKaWUWsX0h12Uaj4tqJVSSimllFoCLaiVUkqpVUzHUCvVfFpQK6WUUkoptQS3XEEtIo+LyCkROSMiv9HseJRSSqlbmfZKK9V83mYHMJ+IeIA/Bj4MXAJeEZFvG2PebG5kC03mJzk8eZiOYAe7u3fz3fPfxWf58Fk+TsycwDY2JbtE0BvEZ/m4kLlAb6SXkl1ic9tmcpUcBsOp5CnubL8TEWG2OEtvtBcLi1Ozp+gKdXFv7730RHr49tlv8/i6x4n5Ylycu4jX8nIle4WucBd90T484qHiVBAEn8dHxakwkh4hEUiQq+RIl9JsSGzg+PRxdnbu5M/f/HNC3hAey0O6lKZQLXBi5gQODr+45ReZzE9yInkCEcHCYo2/h/7/7yWevy/Bvs2PEfFFSJfSRP1R9nbvJVPOcDJ5kqpTZTI/ScwfYyQ9wnDrMFVTZUfHDgbjgzjG4fLcZXqjvVScChWnguM4xANxvnf+e3SHu9nRuYOJ/AQdoQ7OpM6QKqUYz43z2NrHCPvCGGMYy41xNnWW1mAro5lRXp9+naAnSEugBYCgN8hkfhKATa2bmCpMkSlnaA20EvKGyJQzZCtZKnaFkl1ie+d2pgvTlOwSAGW7zM6unYS9YY5MHiHgDVC2y5xInuCn1v0UqVKKufIcPeEeHhh8AJ/luyZHHOMgCCLCTGEGv8dP0BukYle4MHeBDS0bGM2MckfrHSSLSYKeYGOd/PDiD5nITfBT636K0cwoZ1NnG7G1BluxHZu5yhwe8ZApZzDGEPAEKDtlhluH6Qp38er4qzjGIVVK0RvpJeqP4hiHHZ07OJk8SWeok22d2/BZPl4ae4lH1z7KVH6Ki3MXSZfSPDT4ECW7RMWp4BEPUX8UcL/w9Nrka0zkJxhNjzJTnGEwNsh0YZqB6ADJYpIruSvMlefY37efZDHJufQ5Qt4Qo+lRBmOD9Mf6OT17mo5QB+ta1tEf7acz1MkLYy+wJraGwdgg37/wfUrVEkMtQ5TsEl7Ly0Rugg+v/TCzpVmm8lOsT6ynYlfY1rENj+VZsP7zlTxz5Tk6Qh1kK1nOps5iG5vOUCcX5i6QLWd5feZ1LCyOTh3lrdm3eHDgQaaL06yJraEj1MGa+Bouzl3EIx7C3jAey8PFuYvkKjkSgQQdoQ4y5Qzd4W6ylSzFapHd3bvZ1rGNdCmN7dhUnAqjmVF2de3i0twlNrdv5sjkEda1rMN2bMbz4/RH+0kEEsyV5yjZJcp2GYOhL9rHwUsHGUmPcCV7hbHcGGO5Mba0bWF9Yj0+y8eZ1BlsxybsC7O7azcvj79Mspjkw2s/zPqW9Tx98WmGW4eZyE3g8/h4ePBhMMJk9hxrgj5y1TypYoqIL8xMYYbWYCthb4SCnSfqi1KyyxyZfI2QN8TW9rs4mTzBlewYu7p3cXr2LUQsjHG4NHeJkDfMqdmTlOwyHaEONiY28NbsWwy1rMMrHjpDnfS27qXbD5nSLH838iT39nwIr+Uh4A0QsAJ4LR9xf5zZ0iyvTx9nX99+fNa1h6mx3DhVp0J/tB9LLIrVEhP5CRxjMxRfh8HBYMiUM5ybPcem9s0UqgWMMTjGoSPUwV+c+gZ+j5/B2CAvjr1I2BvGa/kAQ8gTwrI8FCp5PJaHqmMT9UcAAQxBb4hitUjQGyTuj5Er59nUtomR9AgbWzfSGe4k4g2TLCa5MHeRofhaIr4o+UqOqD/KTH6GgDdAzB/DweAVD2W7zFRhmt5IL9OFac6mzrK9azshT5A3Z05wInmCQrXAprZNrIsN8erEIboj3VgivHDlBZ5IHADgzw/9Oa+d3wYYwr4IIkKhkidVShHwBBhqGcJ2bBzjEPKGKFSLWCJY4qHqVCjbZdYnNjCaHqEv2kfZLuP3+NnVtRvvvP3MGEgWZxARIr4IxsDL4y/RF+1jpphkV+dOUqU0qVIKMEzlp4j4IoykRxnPj/PomkdpCcQZzZynPdhGtpKjWC0Q9kWYLSa5OHeRbDmLARKBFkp2Ga/lIVfJEfFFCXmDXM5eJuqL8dMbfppitcBUqUR7uBOnksRreclWcswWZylWC9zTcw8zxSTpUoptHdsxONjG4XxmlIpTpS/SS9zfwsHLzxL1RemO9OCzfByfOs6Dax7EKx6+c+47jKRH2N21m4g/SsATYCx7BRFhqgxlbydnkkewjU1vpJeqU6Uz1EmukgMgW8kS98fZ2rGVZDGJYxzu7bmX12depzPUyfbO7UR8Ea5kr3Bx7iL7+vbNW9+GqlPF5/GRr+QRERzjNLbjRH6Cil3h1Owp2oJtvDnzJg8OPMia+Bo+d/hzjKRHGIgO0B5qZ0fnDrrD3Xzv/PcI+8KkSinC3jCWWMT9cSbzkxyfPs7urt20h9o5OnWURCBRax/CDMQGaAm0cHr2NDF/jAP9Bzg+fZzx3Dj39NxDIpCg6lTJV/ON+IvVIocnDxPxRbiv7z6+eeabPDT4EGFvmMvZy7SH2gl4AvgtP9859x0qToV8Jc/Hhj/GudQ5Kk6FK9krnE2d5dG1j7K9c/uNlmwrRm6lbwSLyD7gM8aYj9Qe/yaAMeb3Fpt/79695tVXX13BCOG1kwd56su/S6Bgc3S9sHEMyl7DpQ6h4JfGfIEqdKQNV9pBxEPJcnjgDYexNkiHhfveNIz0wA92WIRLYBnYcc5hNipkwtAzCxc7hVjBECrBZH8YT8WhUi5R9cLGK4ZAxRCpegkXHJ69E/y2YVMyRJkqnmKZniQ8v1XoTkHJB+EinOkVNo4bzvYIa6YMBR8EqxAuGk4OWBT9ECsCXi+RioUxht6JEvecgjN9Fmd7DAMzhqrH/Rz5kEU863C5HcIlGJwypCPCSLfQmjPECjCeECISwBFD2lNm7YShbc4wF3bX16WOt9db25zBiLs+bIFU1J0WEB9YFpdaqsTnbAIVKPohWHZfFysYwiV4Y40QqIBlhGDFsH7MIVqETAgudQoGoXfWkAvCHZcMqSi81W+x6ZLDlXYhWIaWvOFUv4Vjgc92f4TMa7vLSWQNfhsmW4R0GFrtIAknQKBo468YpFylGPUx4cnRN+PgEz9lUyYbgkROGOmEvqShGLIoeh3WTgpiHC52WhT80D9tOD4kxAtQsWDtlCFcNAxMww93WAQqhr5pdx37q3C2V+jNWLTM2Vzs9lI1NhvGDZkw7DxrqHrh+zss1k0aHHHXlxG3LJhogQ3jhoIfin4377JBwePAQCFIaLbg5nanxVxLgHjWpn+8wpU2qHjd7eIzFt0zNhMJoeyDR444lPzwzF0WHgcqXtg04cGuVhicgefvtBiYNhR90Jo1XO4Qqhbcfdow2eLmaUcGij44ut5iugW6U9A1a+hJuZ8BA1MtwnSLYFuQKFgMzsBsTMiFhL6JCrMRSEahKwOWbSgE3Pk3X3TIhIVjQ0LPrKEzA6f7hDsuG+68YHhhizAXEsJlw4HXDa9ttJhocS/lVSzA46ErWaUzbTjXI/TPQDIG+YBQCLg5MjwmXGpz6J92c9QInO8U5sIQIUDLTJGBacNkQpiJC74q+KpuznenDNkgBCuQjnspiY3HcbeXp2roSxrG2oSOOTi+VogWYP2EYSYGfTOmsT8YC46vtRiaNIy3uvvgzhHDbBRGNv1j3gzt57fM/06Y3PvfSF5Hlhi/K/+O+80P+Un+dsWWqz44/pDfpEiQf8vvrPiyP8vvYMoOP3fsc5zv9+LkctiW0DbnsPe04XwXlAIexlvcY+hMDDpShrJfON8pbJgw2D4P3SmhYFW43C5k4l78FYOF4Kk4DEw6xGwfZzurZIJvL9tXNayZMsyFhHje0J1y252q5banz20VMOC3oeCHoUnDTEyYjsO+E4ZTA+5x0/bAxQ7hrlGH2ZhwtlfYOGZIh2E26rZVoYphcNIw2SJkIkIuAHdeEY4Pusf0jrQh6o1QMRXiMyV8Nky3WngrDokc5ALQkoeJhGAEplogVgAxbruHcWMved22rex1j1uXO8AglHzQUrD4V0/8H+zq27Pi21lEDhlj9i467RYrqJ8AHjfG/Ert8S8C9xpj/uVi8zejoH7hpSf5aL5/RZeplFJKKaVc3+QM+x5+YsWX+04F9S015ONGiMingU8DrFmzZsWXf8fmu/mNl/4aazYF2QKmvRUTDCDZnHsNDACDpOcgHML4fEi1CnNZTE8nVGxwHAgFkOlZ5MoEks7idLXjbNmAFEtgO0ihALMZSMQxsSiSyrjdVF4PJNPQ2oLT04HM5d9+/5Y4BP3Uh9MZj4Xki0jVhmwOk4gjk9MQjUCxhOloc2e0LKhWsU6cwbTEIBaFSsVdtlUbZh/wQ6nszuvxYKJhZC6HTM1gOtugaoOIG2ckBHN5iASQC2OYjjZ32bU4icUgn8d0tiMzKfBamGAQcWxIz2FaWxAHSKeh5e0YpGrDbBoCfkw8giTTEI9hvB6wBKlUYSrprl+AcAhnTR9SqbjxVaru814vODY4BpmYBq+Fs2YAa3IafD5MSxQZveyu71AIRDDR8NvryhKoVt3YfV5MPIok0+5ndxycjWuRcgVKFXc7RMPgsdz1Mz4FbQmMzwuOwcSj4PFgXbwCmSy0xCBfgGAQKhVMXzdUqsjFK1jJFM4dQ1B1sE6cwenrcreL349JxJDJGShXIB6DatXdjlMzbtxBP6a1BTwesCwkmYL0HHS0uds1FIBiyZ3u98H0LPi8EA65661YglAQ09biLmMeKZagXIaqjenucN9/fBJ8PrBtTHsbMjMLlQqSymBv24yUyuDxIJPTmNY4BALI+DSmrcX9HB7LzfV8EWJRTDzi5p3fBwb39dUqUiiC7eB0t+M59DqIhUnEIBp2l93WCl4LmUyC7bjbzuuFbA5sNwesyWmcnk6cO+/AujgG+QKSyuBs3+yu+/Scu93TGaypGZzh9ZDPQ66As2kDUi6DbSOXJ7CmZzExN1ec4fXuvpxMQaHovocItLZgggGsN0+7+dHRCtGI247YtpvDxrjzx6OY0LyuKL8Pmc3A3JybjpMzOC1xzNp+8PmQXM7dPj6vu+5CQayzoxivD2fTOhALMYYWp4Nc1QNen5srTq3RyOeRTNbdjuLmifF5IBZz/7Ys6Ol08yGVwZpO4nS2Q2sLcukKkkxjf/gA1qHjWONT2B/aBZUqJh5DyhXikxNk8xWctf1QLoEDhINwZQJrJgW2jbNuwG0jLHHbjcvjWOev4HR3YPq6kOkkMjHttpeTs3hePAwtMez79kKphIlF3bZs/RqYmkHyRUxXu/v5ImG3fcgX3Hxrjbv7nDFuG+H3ISfPuvtOtYIZGkTOXXA/w0CPm9szKUzAB9EIcmUC098NczmkVNtfZ5Lu/EMDyFwO0xp324psDsnm3byzPJi+TmRsChwHs7YfuTzhthW1z0ypglk/CNm8m5e2jfH7cXZuQdIZPM+8jLP1Dkx3p7v/nzmP2I4bT6WCaYm7uRcIQKnk/lsuuXkVCGAiISiWkGwOGZ9294ty2T1OBfyQLSDTMzibNyBz849vuPtpOgulktuG+gPgsdxjgQgkZ/GcOOcu1/Jg79rirvtaGypTM5iudjzPvQq2wd67zW1LppOAcdfH+JTbxgNOf7d73AoFoVp182Iu5+4zqQx4vZhwgMBMCuvKBMX+HggFkdFLmN4uTL+77QC3LSqWwBhkfMp9r9m0286v6UMujWO62qDiYF0aw2lPYE0lMaHA221CvgiptNsm9XUj5Qq+3BhO/jKleMI9Rgd8jZxCxN0vW6JQrtb2iSgEfMjEDOQKmL5ON0av120fkimo5Q/iXhE0sQiSySKzmQXPu8eZiFs31NvJQABKFaRagULJrUtmUm573tXhzlOtYkJBtw0P+JEZtyZx7hhyt69tQzwKczm37QwEMMGAG0eu4B5bkymIRdxlTSXB63HbLNt226H2VjcPsgV3X3eMeyyqVt1jfjINHi/guO2gz+ceP3MFN58cxz0e1I7fkp6DaJg7fvJXuNXcaj3Ut/yQD6VuBcWTJwkMDyP1Ex6llFJKLat36qG+1Y7GrwB3iMg6EfEDvwB8u8kxKXXLCW7erMW0UkopdYu4pYZ8GGOqIvIvgacAD/Bnxpg3mhyWUkoppZRS13VLFdQAxpi/A/6u2XEopZRSSil1I/SasVJKKaWUUkugBbVSSimllFJLoAW1UkoppZRSS6AFtVJKKaWUUkugBbVSSimllFJLoAW1UkoppZRSS6AFtVJKKaWUUkugBbVSSimllFJLoAW1UkoppZRSSyDGmGbH8J6JyBRwvtlx3KAOYLrZQajbluaXWk6aX2q5aY6p5fR+5ddaY0znYhNWdUG9mojIq8aYvc2OQ92eNL/UctL8UstNc0wtp5XILx3yoZRSSiml1BJoQa2UUkoppdQSaEG9cr7Q7ADUbU3zSy0nzS+13DTH1HJa9vzSMdRKKaWUUkotgfZQK6WUUkoptQRaUL9PRGSg2TGo25uIhJodg7p9aRumlpOI+Jodg7q9iUhf7V9pxvK1oF4iEYmKyP8NfFdE1jQ7HnX7qeXY54H/JCKPi0hLs2NStw9tw9RyEpGYiPwR8FkR+VCz41G3HxGJ1Nqwp0Sk3TRpLLMW1EsgIg8DrwJeYK8x5kKTQ1K3p88BfuC/Av8E+I2mRqNuG9qGqeVU65X+U9xa4zTwWyLy6eZGpW4nIvKzwBtAHrjPGDPTrFi8zVrwbaIApIDfMMbkRWQrMGWMmWxuWOp2ISIdQB/w88aYrIicAX5dRP6FMeZPmxyeWv3KaBumlk83sM4Y8wsAInIF+IiI/Kwx5tvNDU3dJsqAxxjzWwAishGYMMbMrXQgepePmyAi64C7jDF/O++5zwExoBOIAzng74GvNGODqtWt1hj8CvAK8KQxpigi3wX+zhjzOREJAI8Dvwz8M2NMsonhqlXmOvn1R0AYbcPUEtXy61eBI8Bf1ToB/h74qjHmv4hIG/ALwCbgtzS/1M26To59C5jBvZLbBTjAfwCeNsYUVyo2HfJxg0Tk14ATwK+KyIPzJv0BsB53wz2Ee6/DO4CfWukY1eolrt/GHdZRBH4J+C+1yZ8DHheRhDGmBBwDRoDdTQhVrULXya+v1SZrG6aWTET+PfA3wBjwj4C/rE36G+CAiERrHQBHAQP0NCVQtWotkmN/U5v0PwMPAoeMMY8BTwIfAXatZHw65OPGXcDtFYwAPyMiPzbGVIwxl0TkF4wxEwDGmG+JyBO443mUulE9uJeuftYYMyoiEeCEiGwAnsVtPP4N8JvGmBERGcLtSVTqRlwvvzYbY06KyD8xxoyDtmHq5tW+KD0KPGaMmah9ufV3a5N/DOzEPYn7fO3xfwD+ZMUDVavW9XJMRMLGmDMi8qAx5lJt9s8DPwS+sZIxag/1jftbY8zXgFNACPgYuD0/9WK69ngHsAaYbkqUarWaBP6iVuz4ARt4HsgbY7K4vdQfF5GP1r4p3wk05dZAalVaLL+eA7IA9WIatA1TN88Ykwa+VCt07gZeAqIi8jvAGeDbwD8VkYeA7cAsWn+om3CdHIsA/1tt+qV5s+/k7e+HrBhN6KvUDjbXMMZUan8exr3k/pCIDBpjjIh4RKRTRL4N/L/AnxhjXlihkNUqs1iOGWNsY8xI7e8yEAR24I4FwxhzGvey1r2435r/E2PMj1csaLVq3ER+7cQ96NSHhHTVxiJqG6au6x2OkaY2rQ/418AngD3Af2+M+S5ur+E/Bf4KtzA6sUIhq1XmJnLsvwW2iciv1143ICL/Fffqx5+tdI7plxLnEZHPAOuAfwC+W7/9ioh8pPbY1B7vxm0sDhtjviYincaYKRH5JWPMl5sTvVoN3iHHHgeempdjPwf8ojHm47Wb1AdW8ssVanV6L/lVexysfUFR2zB1XTeaX/Pm/wngPxpjNtUeB2rfA1FqUe8xxz4P3Am0Ax8zxnxhRYOu0R5q3EucIvIyMAB8E7dY/riIWCKyC+gHArXCBmPMYeBp4NdEJA98tPb8l5sRv7r13UCO9eHmWH2fbAGeFJGPAidxx1Artail5JeIvAX8NGgbphZ3o/m1yEsHcfPMC6DFtLqeJebY3wOWMWa6WcU06JcS6+aA/2yM+TyAiAwC9xhjviAix40xr9VnrDUMHbiXFC4CP2mMeaYZQatV5YZzrObjuLfHexL4FWPMwZUNV60yS8mvf675pd7FzRwjE8BdwGdqT/2vxpjqCserVp+l5pi9wvFe4wPZQy0ibbWeGU/tqRHgS/UeaNx7tLaIiHd+Q1C7XFUFMsC/N8Yc0GJaLWYJORas/XkE+GVjzEe12FFX0/xSy2kJ+eUF0sAw7r2nH61d0VVqgdsxxz5wPdTi3g7qS8BxwEftXpnGmPm3IPsJYPSqjbgZ91vKf2SMGQO+uHJRq9VkiTn2SyLye8aY317BkNUqovmlltNS8wv4fWPMn61YwGrVuV1z7ANXUOP+ms6v4d7D90EReaZ2GxbBHYNj494y6tsAIrIX98xpDPgDo79Mp97dUnLs92u3B1LqejS/1HJaan7pMVK9m9syx27rIR/zLh3Md9AY80XcXz0sAf8NuLdjoXaLMtyB7wMi8jXg3wJBY0z6Vt2Iqnk0x9Ry0vxSy0nzSy23D1KO3bYFdW3czTX3BJx3+eB13DE6O2rfIK3f43At7r0yP4270T9qjLm8UnGr1UNzTC0nzS+1nDS/1HL7oOXYbVlQi8i/wr1Vz/9Y30hXnyXVLim8insJ4aHaPH3GmPO4Nwx/0BijP42qFqU5ppaT5pdaTppfarl9EHPstiuoReRXcO+p+u9wfwXsN0Vke+2sxzN/XuP++tx3gJ8RkTngf6g9/4fG/blnpa6hOaaWk+aXWk6aX2q5fVBz7Lb4pcT6bVVqZz9/DXzBGPOUiLTjfpM0b4z5hatfA3iA54Aw8NvGmL9Z6djV6qA5ppaT5pdaTppfarlpjq3yHmoR8YrIHwB/KCIfqY3VeQH4X2qzpIFR4A5xf2q3ccnBGFM17q82/ZkxZutq3ohq+WiOqeWk+aWWk+aXWm6aY29btT3UtQ3yx0Ac92cn/xnwN8BXgB/g/lzz3bhnRlmgxRjz+/NebxljnKvfV6k6zTG1nDS/1HLS/FLLTXNsodV8H+oYsBP4iDFmTkRmgJ8BHgT2A9sArzHmsIh8Bve+h4iIGNdtsxHVstEcU8tJ80stJ80vtdw0x+ZZtUM+jDEZ3MsIv1R76jnc26/8DNBjjDlW24hR3I16vva61dklr1ac5phaTppfajlpfqnlpjm20KotqGu+CewUkd7at0GPAUWgW1y/BDwPnDPGfLuJcarVS3NMLSfNL7WcNL/UctMcq1ntBfVzwDS1syNjzGHgHiBaOwM6AjxmjPnXzQpQrXqaY2o5aX6p5aT5pZab5ljNah5DjTFmTES+BXxWRM7gXmooAtXa9CNNDE/dBjTH1HLS/FLLSfNLLTfNsbet2rt8zCciP4n7W/D7gc8bYz7f5JDUbUZzTC0nzS+1nDS/1HLTHLtNCmoAEfHhjnWvvuvMSr0HmmNqOWl+qeWk+aWW2wc9x26bgloppZRSSqlmWO1fSlRKKaWUUqqptKBWSimllFJqCbSgVkoppZRSagm0oFZKKaWUUmoJtKBWSimllFJqCbSgVkqpVU5E2kXkSO2/cRG5XPs7KyL/sdnxKaXU7U5vm6eUUrcREfkMkDXG/EGzY1FKqQ8K7aFWSqnblIg8JCLfqf39GRH5iogcFJHzIvIxEfl9ETkuIv9Q+1EGRGSPiDwjIodE5CkR6W3up1BKqVufFtRKKfXBsQF4BPhZ4KvAD40x24AC8I9qRfUfAU8YY/YAfwb8n80KVimlVgtvswNQSim1Yv7eGFMRkeOAB/iH2vPHgSFgE3AX8D0RoTbPWBPiVEqpVUULaqWU+uAoARhjHBGpmLe/ROPgHg8EeMMYs69ZASql1GqkQz6UUkrVnQI6RWQfgIj4RGRrk2NSSqlbnhbUSimlADDGlIEngP9LRI4CR4D9TQ1KKaVWAb1tnlJKKaWUUkugPdRKKaWUUkotgRbUSimllFJKLYEW1EoppZRSSi2BFtRKKaWUUkotgRbUSimllFJKLYEW1EoppZRSSi2BFtRKKaWUUkotgRbUSimllFJKLcH/D5tmhZVvH0DoAAAAAElFTkSuQmCC\n", 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\n", 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" ] @@ -290,7 +296,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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google-auth-oauthlib, absl-py, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard, opt-einsum, libclang, keras-preprocessing, keras, google-pasta, gast, flatbuffers, astunparse, tensorflow\n", + "Successfully installed absl-py-1.1.0 astunparse-1.6.3 flatbuffers-1.12 gast-0.4.0 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 keras-2.9.0 keras-preprocessing-1.1.2 libclang-14.0.1 oauthlib-3.2.0 opt-einsum-3.3.0 requests-oauthlib-1.3.1 tensorboard-2.9.1 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-2.9.1 tensorflow-estimator-2.9.0 tensorflow-io-gcs-filesystem-0.26.0 termcolor-1.1.0\n" + ] + } + ], + "source": [ + "!pip install tensorflow" + ] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -334,7 +434,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -507,6 +607,64 @@ "### Training in the beginning of each dataset" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "N_STEPS = 5\n", + "EPOCHS = 25\n", + "BATCH_SIZE = 32\n", + "VAL_SPLIT = 0.2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# model defining\n", + "model = Sequential()\n", + "model.add(LSTM(100, \n", + " activation='relu', \n", + " return_sequences=True, \n", + " input_shape=(N_STEPS, n_features)))\n", + "model.add(LSTM(100, \n", + " activation='relu'))\n", + "model.add(Dense(n_features))\n", + "model.compile(optimizer='adam', \n", + " loss='mae', \n", + " metrics=[\"mse\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "history = model.fit(X, y,\n", + " validation_split=VAL_SPLIT,\n", + " epochs=EPOCHS,\n", + " batch_size=BATCH_SIZE,\n", + " verbose=0,\n", + " shuffle=False,\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# results predicting\n", + "residuals = pd.DataFrame(y - model.predict(X)).abs().sum(axis=1)\n", + "UCL = residuals.quantile(0.99)" + ] + }, { "cell_type": "code", "execution_count": 18, @@ -536,10 +694,16 @@ " \n", " # model defining\n", " model = Sequential()\n", - " model.add(LSTM(100, activation='relu', return_sequences=True, input_shape=(N_STEPS, n_features)))\n", - " model.add(LSTM(100, activation='relu'))\n", + " model.add(LSTM(100, \n", + " activation='relu', \n", + " return_sequences=True, \n", + " input_shape=(N_STEPS, n_features)))\n", + " model.add(LSTM(100, \n", + " activation='relu'))\n", " model.add(Dense(n_features))\n", - " model.compile(optimizer='adam', loss='mae', metrics=[\"mse\"])\n", + " model.compile(optimizer='adam', \n", + " loss='mae', \n", + " metrics=[\"mse\"])\n", " \n", " # callbacks defining\n", " early_stopping = EarlyStopping(patience=10, verbose=0)\n", @@ -743,7 +907,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -757,7 +921,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.2" + "version": "3.9.12" } }, "nbformat": 4, diff --git a/notebooks/requirements.txt b/notebooks/requirements.txt index 06454b4..78266ad 100644 --- a/notebooks/requirements.txt +++ b/notebooks/requirements.txt @@ -26,7 +26,7 @@ ipykernel==5.3.1 ipython==7.16.3 ipython-genutils==0.2.0 ipywidgets==7.5.1 -jedi==0.18.0 +jedi==0.17.2 Jinja2==2.11.3 joblib==1.0.1 json5==0.9.5 @@ -60,7 +60,7 @@ opt-einsum==3.3.0 packaging==20.9 pandas==1.1.4 pandocfilters==1.4.3 -parso==0.8.1 +parso pexpect==4.8.0 pickleshare==0.7.5 Pillow==9.0.1 @@ -82,7 +82,7 @@ QtPy==1.9.0 requests==2.25.1 requests-oauthlib==1.3.0 rsa==4.7.2 -scikit-learn==0.23.2 +scikit-learn scipy==1.5.4 Send2Trash==1.5.0 six==1.15.0 @@ -104,5 +104,5 @@ webencodings==0.5.1 Werkzeug==1.0.1 widgetsnbextension==3.5.1 wrapt==1.12.1 -arimfd==1.4.1 -tsad==0.18.7 \ No newline at end of file +arimafd +tsad \ No newline at end of file diff --git a/utils/__init__.py b/utils/__init__.py deleted file mode 100644 index df58e5d..0000000 --- a/utils/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .t2 import T2 \ No newline at end of file diff --git a/utils/t2.py b/utils/t2.py deleted file mode 100644 index 8079523..0000000 --- a/utils/t2.py +++ /dev/null @@ -1,289 +0,0 @@ -# Author: Iurii Katser - -from matplotlib import pyplot as plt -import numpy as np -from numpy import linalg as LA -from sklearn.decomposition import PCA -import scipy.stats as SS -from math import sqrt -from sklearn.preprocessing import StandardScaler -from pandas import DataFrame - -class T2: - ''' - Calculation of the Hotelling's 1-dimensional T-squared statistics or T-squared statistics+Q-statistics based on PCA for fault detection. - - Статистический критерий Хотеллинга показывает отклонение состояния оборудования в каждый момент времени записи анализируемых сигналов, сравнивая значения с эталонными, полученными предварительно. Каждое значение критерия характеризует отклонение состояния контролируемого оборудования от нормального. - Зачастую статистический критерий Хотеллинга применяется совместно с методом главных компонент: для подпространства главных компонент (подпространства признаков с наибольшей дисперсией) вычисляется T2-критерий, а для подпространства оставшихся (подпространство разностей) применяется Q-критерий [1-3], значение которого равно евклидовой норме вектора в подпространстве разностей. Так как Q-критерий применяется к подпространству разностей, он позволяет обнаружить отклонение зависимостей между измеряемыми параметрами, неучтенное при получении главных компонент для тестовой выборки. Появление возмущений в Q-критерии говорит о нарушении зависимостей, что, в свою очередь, может говорить о возникновении неисправности. Так как в подпространстве главных компонент содержатся сигналы с наибольшей дисперсией, а в подпространстве оставшихся компонент в основном шум, — контрольные пределы для T2-критерия часто больше соответствующих пределов в подпространстве оставшихся компонент. По этой причине требуется гораздо более высокая амплитуда возмущений, вносимая неисправностью, чтобы обнаружить ее с помощью T2-критерия. - T2-критерий и Q-критерий применяются совместно для лучшего качества обнаружения. Они позволяют обнаруживать развитие аномалии на раннем этапе, однако Q-критерий является чувствительным к изменению зависимостей между контролируемыми параметрами, а T2-критерий зависит от эталонной выборки, выбор которой сказывается на работе алгоритма. Отдельной задачей является выбор контрольных пределов. - - В текущей библиотеке реализованы два подхода: T2 для исходного пространства признаков и T2+Q на основе метода главных компонент. - - [1] - Q-statistic and T2-statistic PCA-based measures for damage assessment in structures / LE Mujica, J. Rodellar, A. Ferna ́ndez, A. Gu ̈emes // Structural Health Monitoring: An International Journal. — 2010. — nov. — Vol. 10, no. 5. — Pp. 539–553. - [2] - Zhao Chunhui, Gao Furong. Online fault prognosis with relative deviation analysis and vector autoregressive modeling // Chemical Engineering Science. — 2015. — dec. — Vol. 138. — Pp. 531–543. - [3] - Li Wei, Peng Minjun, Wang Qingzhong. False alarm reducing in PCA method for sensor fault detection in a nuclear power plant // Annals of Nuclear Energy. — 2018. — aug. — Vol. 118. — Pp. 131–139. - - Examples - -------- - T2+Q based on PCA: - - from statistics import T2 - import pandas as pd - import numpy as np - df = pd.DataFrame(np.random.randn(100, 4), columns=list('ABCD')) - t2 = T2() - t2.fit(df.iloc[:20]) - t2.predict(df) - - - T2 without PCA: - - df = pd.DataFrame(np.random.randn(100, 4), columns=list('ABCD')) - t2 = T2(using_PCA=False) - t2.fit(df.iloc[:20]) - t2.predict(df) - - ''' - def __init__(self, scaling=False, using_PCA=True, explained_variance=0.85, p_value=0.999): - self.explained_variance = explained_variance - self.using_PCA = using_PCA - self.p_value = p_value - self.scaling = scaling - - #T2 and Q statistics calculations - #----------------------------------------------------------- - def _T2_calculation(self,X): - T2 = [] - for i in range(len(X)): - T2.append(X[i] @ self.inv_cov @ X[i].T) - return T2 - - def _Q_calculation(self,X): - Q = [] - for i in range(len(X)): - Q.append(X[i] @ self.transform_rc @ X[i].T) - return Q - #----------------------------------------------------------- - - #CALCULATING UPPER CONTROL LIMITS - #----------------------------------------------------------- - def _T2_UCL(self, X): - if self.using_PCA: - m = self.n_components - else: - m = X.shape[1] - n = len(X) - C_alpha = np.linspace(0,15,10000)[SS.f.cdf(np.linspace(0,15,10000), m, n-m)diff.mean()+3*diff.std()].index.tolist() - - #self.final_list = [(X.index[0], indices[indices.index(list_of_ind[0])-1])] + \ - #[(list_of_ind[i], indices[indices.index(list_of_ind[i+1])-1]) for i in range(len(list_of_ind)-2)] + \ - #[(indices[indices.index(list_of_ind[-1])], X.index[-1])] - - - def predict(self, X, plot_fig=True, save_fig=False, fig_name=['T2','Q'], window_size=1): - ''' - Computation of T2-statistics or T2-statistics+Q-statistics for the testing dataset. - - Parameters - ---------- - X : pandas.DataFrame() - Testing dataset. - - plot_fig : boolean, True by default - If True there will be plotted T2-statistics or T2-statistics+Q-statistics chart. - - save_fig : boolean, False by default - If True there will be saved T2 and Q charts as .png to the current folder. - - fig_name : list of one or two str, ['T2','Q'] by default - Names of the saved figures. - - Returns - ------- - self : object - Plotting and saving T2 or T2+Q charts; to get numpy arrays with T2 or Q values call self.T2 or self.Q. - ''' - X=X.copy() - if self.scaling: - X_ = self.scaler.transform(X) - else: - X_ = X.values - - if self.n_components != X.shape[1]: - #calculating T2 - self.T2 = DataFrame(self._T2_calculation(self.pca.transform(X_)), index=X.index).rolling(window_size).median() - - #calculating Q - self.Q = DataFrame(self._Q_calculation(X_), index=X.index).rolling(window_size).median() - - #plotting - if plot_fig: - self.plot_T2(self.T2) - if save_fig: - self._save(name=fig_name[0]) - - self.plot_Q(self.Q) - if save_fig: - self._save(name=fig_name[1]) - - else: - #calculating T2 - self.T2 = self._T2_calculation(X_) - - #plotting - if plot_fig: - self.plot_T2(self.T2) - if save_fig: - self._save(name=fig_name[0]) - - def fit_predict(self, X, plot_fig=True, save_fig=False, fig_name=['T2','Q']): - ''' - Computation of the inversed covariance matrix, matrix of transformation to the residual space (in case of using_PCA=True) and standart scaler fitting (in case of using scaling=True). - Computation of T2-statistics or T2-statistics+Q-statistics for the training dataset. - - Parameters - ---------- - X : pandas.DataFrame() - Training dataset. - - plot_fig : boolean, True by default - If True there will be plotted T2-statistics or T2-statistics+Q-statistics chart. - - save_fig : boolean, False by default - If True there will be saved T2 and Q charts as .png to the current folder. - - fig_name : list of one or two str, ['T2','Q'] by default - Names of the saved figures. - - Returns - ------- - self : object - Plotting and saving T2 or T2+Q charts; to get numpy arrays with T2 or Q values call self.T2 or self.Q. - ''' - #fit - self.fit(X) - - #predict - self.predict(X, plot_fig=True, save_fig=False, fig_name=['T2','Q']) - \ No newline at end of file