diff --git a/Build_Week_2.ipynb b/Build_Week_2.ipynb index 5094dc2..85acb54 100644 --- a/Build_Week_2.ipynb +++ b/Build_Week_2.ipynb @@ -43,7 +43,7 @@ "colab_type": "code", "id": "5nv2QG_RYDpt", "colab": {}, - "outputId": "33a0fa64-5b83-435b-fd0e-b9c13274d439" + "outputId": "8308718b-753f-476f-e03a-3fd3ce01c5f0" }, "source": [ "import pandas as pd\n", @@ -59,38 +59,38 @@ "output_type": "stream", "text": [ "Requirement already satisfied: eli5 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (0.10.1)\n", - "Requirement already satisfied: jinja2 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (2.11.1)\n", - "Requirement already satisfied: graphviz in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (0.14)\n", - "Requirement already satisfied: six in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (1.14.0)\n", "Requirement already satisfied: tabulate>=0.7.7 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (0.8.7)\n", - "Requirement already satisfied: numpy>=1.9.0 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (1.18.1)\n", - "Requirement already satisfied: scipy in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (1.4.1)\n", + "Requirement already satisfied: six in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (1.14.0)\n", + "Requirement already satisfied: jinja2 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (2.11.1)\n", "Requirement already satisfied: scikit-learn>=0.18 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (0.22.1)\n", + "Requirement already satisfied: scipy in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (1.4.1)\n", + "Requirement already satisfied: numpy>=1.9.0 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (1.18.1)\n", "Requirement already satisfied: attrs>16.0.0 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (19.3.0)\n", + "Requirement already satisfied: graphviz in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from eli5) (0.14)\n", "Requirement already satisfied: MarkupSafe>=0.23 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from jinja2->eli5) (1.1.1)\n", "Requirement already satisfied: joblib>=0.11 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from scikit-learn>=0.18->eli5) (0.14.1)\n", "Requirement already satisfied: category_encoders==2 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (2.0.0)\n", - "Requirement already satisfied: statsmodels>=0.6.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from category_encoders==2) (0.11.0)\n", - "Requirement already satisfied: scikit-learn>=0.20.0 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from category_encoders==2) (0.22.1)\n", - "Requirement already satisfied: numpy>=1.11.3 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from category_encoders==2) (1.18.1)\n", "Requirement already satisfied: patsy>=0.4.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from category_encoders==2) (0.5.1)\n", - "Requirement already satisfied: pandas>=0.21.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from category_encoders==2) (1.0.1)\n", + "Requirement already satisfied: scikit-learn>=0.20.0 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from category_encoders==2) (0.22.1)\n", "Requirement already satisfied: scipy>=0.19.0 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from category_encoders==2) (1.4.1)\n", - "Requirement already satisfied: joblib>=0.11 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from scikit-learn>=0.20.0->category_encoders==2) (0.14.1)\n", + "Requirement already satisfied: statsmodels>=0.6.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from category_encoders==2) (0.11.0)\n", + "Requirement already satisfied: pandas>=0.21.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from category_encoders==2) (1.0.1)\n", + "Requirement already satisfied: numpy>=1.11.3 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from category_encoders==2) (1.18.1)\n", "Requirement already satisfied: six in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from patsy>=0.4.1->category_encoders==2) (1.14.0)\n", - "Requirement already satisfied: python-dateutil>=2.6.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from pandas>=0.21.1->category_encoders==2) (2.8.1)\n", + "Requirement already satisfied: joblib>=0.11 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from scikit-learn>=0.20.0->category_encoders==2) (0.14.1)\n", "Requirement already satisfied: pytz>=2017.2 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from pandas>=0.21.1->category_encoders==2) (2019.3)\n", + "Requirement already satisfied: python-dateutil>=2.6.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from pandas>=0.21.1->category_encoders==2) (2.8.1)\n", "Requirement already satisfied: seaborn in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (0.10.0)\n", - "Requirement already satisfied: pandas>=0.22.0 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from seaborn) (1.0.1)\n", - "Requirement already satisfied: scipy>=1.0.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from seaborn) (1.4.1)\n", "Requirement already satisfied: matplotlib>=2.1.2 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from seaborn) (3.1.3)\n", + "Requirement already satisfied: scipy>=1.0.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from seaborn) (1.4.1)\n", "Requirement already satisfied: numpy>=1.13.3 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from seaborn) (1.18.1)\n", - "Requirement already satisfied: python-dateutil>=2.6.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from pandas>=0.22.0->seaborn) (2.8.1)\n", - "Requirement already satisfied: pytz>=2017.2 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from pandas>=0.22.0->seaborn) (2019.3)\n", - "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from matplotlib>=2.1.2->seaborn) (2.4.6)\n", + "Requirement already satisfied: pandas>=0.22.0 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from seaborn) (1.0.1)\n", + "Requirement already satisfied: python-dateutil>=2.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from matplotlib>=2.1.2->seaborn) (2.8.1)\n", "Requirement already satisfied: cycler>=0.10 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from matplotlib>=2.1.2->seaborn) (0.10.0)\n", + "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from matplotlib>=2.1.2->seaborn) (2.4.6)\n", "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from matplotlib>=2.1.2->seaborn) (1.1.0)\n", - "Requirement already satisfied: six>=1.5 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from python-dateutil>=2.6.1->pandas>=0.22.0->seaborn) (1.14.0)\n", + "Requirement already satisfied: pytz>=2017.2 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from pandas>=0.22.0->seaborn) (2019.3)\n", + "Requirement already satisfied: six>=1.5 in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from python-dateutil>=2.1->matplotlib>=2.1.2->seaborn) (1.14.0)\n", "Requirement already satisfied: setuptools in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from kiwisolver>=1.0.1->matplotlib>=2.1.2->seaborn) (45.2.0.post20200210)\n", "Requirement already satisfied: xgboost in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (1.1.0)\n", "Requirement already satisfied: scipy in c:\\users\\terrence malone\\anaconda3\\lib\\site-packages (from xgboost) (1.4.1)\n", @@ -1019,7 +1019,7 @@ "metadata": { "tags": [] }, - "execution_count": 36 + "execution_count": 2 } ] }, @@ -1286,10 +1286,10 @@ { "cell_type": "code", "metadata": { - "id": "bcFDJRZkyXhA", + "id": "RXgB6P9kEzTY", "colab_type": "code", "colab": {}, - "outputId": "111a9014-1575-4f95-e0b9-247220d19e46" + "outputId": "fc942607-a315-46c3-ddaa-9fac19c87469" }, "source": [ "import seaborn as sns\n", @@ -1330,10 +1330,10 @@ { "cell_type": "code", "metadata": { - "id": "3jsPwJHUyXhC", + "id": "X4T4aAX2EzTa", "colab_type": "code", "colab": {}, - "outputId": "fc31234a-14c4-4aed-f001-35c343bc9795" + "outputId": "d35827f2-390e-4417-9047-7612d664ff8c" }, "source": [ "sns.barplot(x=df['NA_Sales'], y=df['Genre'])\n" @@ -1344,7 +1344,7 @@ "output_type": "execute_result", "data": { "text/plain": [ - "" + "" ] }, "metadata": { @@ -1355,7 +1355,7 @@ { "output_type": "display_data", "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -1370,10 +1370,10 @@ { "cell_type": "code", "metadata": { - "id": "58zj6AM9yXhE", + "id": "vgy0udWiEzTc", "colab_type": "code", "colab": {}, - "outputId": "39071730-cd99-4483-d6ea-c191bc861490" + "outputId": "f96dc9d6-6740-4276-e51b-e7a7dda7d368" }, "source": [ "plt.scatter(x=df['NA_Sales'], y=df['Genre'], color='red')" @@ -1384,7 +1384,7 @@ "output_type": "execute_result", "data": { "text/plain": [ - "" + "" ] }, "metadata": { @@ -1448,10 +1448,10 @@ { "cell_type": "code", "metadata": { - "id": "ZAnrRLSLyXhI", + "id": "ntSvnKKBEzTg", "colab_type": "code", "colab": {}, - "outputId": "31b5a1c3-1dc0-430f-f9d2-da777ffb2a9a" + "outputId": "9abe618b-bfd1-4101-fd15-39d909e751b5" }, "source": [ "df['Year'] = pd.to_datetime(df['Year'])\n", @@ -1480,17 +1480,17 @@ "metadata": { "tags": [] }, - "execution_count": 54 + "execution_count": 12 } ] }, { "cell_type": "code", "metadata": { - "id": "lHPgt4BZyXhK", + "id": "poRsFmE_EzTi", "colab_type": "code", "colab": {}, - "outputId": "b32493dc-823f-4071-c2b7-2fe373d162ee" + "outputId": "f0c8538a-15ce-42f3-eb44-d940db108e8a" }, "source": [ "# Holding out test set before preforming training & validating dataset.\n", @@ -1513,7 +1513,7 @@ "metadata": { "tags": [] }, - "execution_count": 55 + "execution_count": 13 } ] }, @@ -1535,16 +1535,16 @@ { "cell_type": "code", "metadata": { - "id": "K4C9M2gYyXhQ", + "id": "JoFKSKjQEzTl", "colab_type": "code", "colab": {}, - "outputId": "6b2487e7-c9ae-4a71-cd6d-eed7802f701d" + "outputId": "61a689f3-bdb2-4293-fd5f-2d75fbf463f6" }, "source": [ "import plotly.express as px\n", "import plotly.offline as pyo\n", "import plotly.graph_objects as go\n", - "fig = px.scatter(df, x='Genre', y='Year')\n", + "fig = px.scatter(df, x='Genre', y='NA_Sales')\n", "fig.update_traces(marker_color='green')\n", "fig.show()" ], @@ -1559,7 +1559,7 @@ }, "data": [ { - "hovertemplate": "Genre=%{x}
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5B2bkHWymgJm8+3LGd7eTZ5c9s1btnkOflE3W2zRSkfFQAQJmqJT9OQKmvWnoRgJmqJT9OQKmvWnoRgJmqJTtOQKmradmGwFTo2V7loBp66nZRsDUaNmeJWDaemq2ETA1WpxdV4CAGfk8NFPAXENVbu2XtrJIV3c5Uo9xrQABUytmd56AaWep3UTA1IrZnSdg2llqNxEwtWI25wmYNo5pthAw06jZzBAwbRzTbCFgplGzmSFg2jim2ULATKPGTCJAwIx8DpoxYI7qKEtnW1kWLe+J1GNcK0DA1IrZnSdg2llqNxEwtWJ25wmYdpbaTQRMrZjNeQKmjWOaLQTMNGo2MwRMG8c0WwiYadRsZgiYNo5pthAw06gxQ8Ac9Ax0dfXIGefOrf7Zs06eKZ2d7dX/+/qbb5PT57zy5/fZa0bNXyNg8jdSngIEzDy1a69FwPSzJ2D62RMw/ewJmD72BEwf9+SqBEw/ewKmnz0B08+egOlnT8D0sy/6lXkH5uo7uCZe3nTLnTWR8u4HHpPzLrlWLpp9gkwcP1bOu+y66sSJRx5Q/f8JmEX/W6BYr5+A6Xe/CJh+9gRMP3sCpp89AdPHnoDp407A9HNPrkzA9PMnYPrZEzD97AmYfvZFvzIBc/UdTMLklptNrv7RnX9+ZO27LNf8+f333qP61wYHTQJm0f8WKNbrJ2D63S8Cpp89AdPPnoDpZ0/A9LEnYPq4EzD93AmYvvYETD9/AqafPQHTz77oVyZgitS8qzL5uPiagJnc3OQj5TPetL2sCZjz5j8vp83+lpw963DZauoU3oFZ9L8DCvb6CZh+N4yA6WdPwPSzJ2D62RMwfewJmD7uBEw/dwKmrz0B08+fgOlnT8D0sy/6lZs+YCbB8m/Pvrj2I+FDBcwD9t1Tpu88rXqvBwfMZSt7i/4MqF9/a2uLtLaUpKunXz3LQJxAe1uLlKQk3b3Yx0nqpzvayzIwUJHevgH9MBNRAskPDuvtq0hfP/ZRkCmGR3e2Vv9Znzz7fOUrkPwHqxVd/VKpYJ+nfKlUkjGdZVm+qi/Py3ItEWlpKVU/yryyC/u8H4jWcou0tZZkVTe/v8zbvq21pfrsd/PvVXnTS0dbWSpSkZ5efn+ZN37yz/q+gYr0NeG/V40d3ZY394i6XtMHzOQj4ldcfVPdTU1+WM9px31Kzr7gytd8ByYBc0T9/dDwvxgCpt8tImD62RMw/ewJmH72BEwfewKmj3tyVQKmnz0B08+egOlnT8D0sydg+tkX/cpNHzAH38B134GZ/BRyvgdm/SOexITOtrIsWt5T9Oe/cK+fj5D73TI+Qu5nz0fI/ez5CLmfPR8h97HnI+Q+7slV+Snkfvb8EB8/ez5C7mfPR8j97PkIuZ990a9MwBx0BwcHTH4KOQGzkf4mJ2D63Q0Cpp89AdPPnoDpZ0/A9LEnYPq4EzD93JMrEzD9/AmYfvYETD97AqaffdGvTMAcJmAmfzmJmqfPmVs9mXy0/KyTZ0ry7szki59CXvS/BYr1+gmYfveLgOlnT8D0sydg+tkTMH3sCZg+7gRMP3cCpq89AdPPn4DpZ0/A9LMv+pUJmJF3kIAZCci4SoCAqeIyPUzANOVULSNgqrhMDxMwTTlVywiYKi6zwwRMM0r1Ij5CriYzG+AdmGaU6kUETDWZ2QAB04xSvYiAqSZjYLUAATPyUSBgRgIyrhIgYKq4TA8TME05VcsImCou08METFNO1TICporL7DAB04xSvYiAqSYzGyBgmlGqFxEw1WRmAwRMM0r1IgKmmowBAqbNM0DAtHFkS5gAATPMKYtTBMwsVMN2EjDDnLI4RcDMQjVsJwEzzMn6FAHTWjR8HwEz3Mr6JAHTWjR8HwEz3Mr6JAHTWjR8HwEz3IqTtQK8AzPyiSBgRgIyrhIgYKq4TA8TME05VcsImCou08METFNO1TICporL7DAB04xSvYiAqSYzGyBgmlGqFxEw1WRmAwRMM0r1IgKmmoyB1QIEzMhHgYAZCci4SoCAqeIyPUzANOVULSNgqrhMDxMwTTlVywiYKi6zwwRMM0r1IgKmmsxsgIBpRqleRMBUk5kNEDDNKNWLCJhqMgYImDbPAAHTxpEtYQIEzDCnLE4RMLNQDdtJwAxzyuIUATML1bCdBMwwJ+tTBExr0fB9BMxwK+uTBExr0fB9BMxwK+uTBExr0fB9BMxwK07WCvAOzMgngoAZCci4SoCAqeIyPUzANOVULSNgqrhMDxMwTTlVywiYKi6zwwRMM0r1IgKmmsxsgIBpRqleRMBUk5kNEDDNKNWLCJhqMgZWCxAwIx8FAmYkIOMqAQKmisv0MAHTlFO1jICp4jI9TMA05VQtI2CquMwOEzDNKNWLCJhqMrMBAqYZpXoRAVNNZjZAwDSjVC8iYKrJGCBg2jwDBEwbR7aECRAww5yyOEXAzEI1bCcBM8wpi1MEzCxUw3YSMMOcrE8RMK1Fw/cRMMOtrE8SMK1Fw/cRMMOtrE8SMK1Fw/cRMMOtOFkrwDswI58IAmYkIOMqAQKmisv0MAHTlFO1jICp4jI9TMA05VQtI2CquMwOEzDNKNWLCJhqMrMBAqYZpXoRAVNNZjZAwDSjVC8iYKrJGFgtQMCMfBQImJGAjKsECJgqLtPDBExTTtUyAqaKy/QwAdOUU7WMgKniMjtMwDSjVC8iYKrJzAYImGaU6kUETDWZ2QAB04xSvYiAqSZjgIBp8wwQMG0c2RImQMAMc8riFAEzC9WwnQTMMKcsThEws1AN20nADHOyPkXAtBYN30fADLeyPknAtBYN30fADLeyPknAtBYN30fADLfiZK0A78CMfCIImJGAjKsECJgqLtPDBExTTtUyAqaKy/QwAdOUU7WMgKniMjtMwDSjVC8iYKrJzAYImGaU6kUETDWZ2QAB04xSvYiAqSZjYLUAATPyUSBgRgIyrhIgYKq4TA8TME05VcsImCou08METFNO1TICporL7DAB04xSvYiAqSYzGyBgmlGqFxEw1WRmAwRMM0r1IgKmmowBAqbNM0DAtHFkS5gAATPMKYtTBMwsVMN2EjDDnLI4RcDMQjVsJwEzzMn6FAHTWjR8HwEz3Mr6JAHTWjR8HwEz3Mr6JAHTWjR8HwEz3IqTtQK8AzPyiSBgRgIyrhIgYKq4TA8TME05VcsImCou08METFNO1TICporL7DAB04xSvYiAqSYzGyBgmlGqFxEw1WRmAwRMM0r1IgKmmoyB1QIEzMhHgYAZCci4SoCAqeIyPUzANOVULSNgqrhMDxMwTTlVywiYKi6zwwRMM0r1IgKmmsxsgIBpRqleRMBUk5kNEDDNKNWLCJhqMgYImDbPAAHTxpEtYQIEzDCnLE4RMLNQDdtJwAxzyuIUATML1bCdBMwwJ+tTBExr0fB9BMxwK+uTBExr0fB9BMxwK+uTBExr0fB9BMxwK07WCvAOzMgngoAZCci4SoCAqeIyPUzANOVULSNgqrhMDxMwTTlVywiYKi6zwwRMM0r1IgKmmsxsgIBpRqleRMBUk5kNEDDNKNWLCJhqMgZWCxAwIx8FAmYkIOMqAQKmisv0MAHTlFO1jICp4jI9TMA05VQtI2CquMwOEzDNKNWLCJhqMrMBAqYZpXoRAVNNZjZAwDSjVC8iYKrJGCBg2jwDBEwbR7aECRAww5yyOEXAzEI1bCcBM8wpi1MEzCxUw3YSMMOcrE8RMK1Fw/cRMMOtrE8SMK1Fw/cRMMOtrE8SMK1Fw/cRMMOtOFkrwDswI58IAmYkIOMqAQKmisv0MAHTlFO1jICp4jI9TMA05VQtI2CquMwOEzDNKNWLCJhqMrMBAqYZpXoRAVNNZjZAwDSjVC8iYKrJGFgtQMCMfBQImJGAjKsECJgqLtPDBExTTtUyAqaKy/QwAdOUU7WMgKniMjtMwDSjVC8iYKrJzAYImGaU6kUETDWZ2QAB04xSvYiAqSZjgIBp8wwQMG0c2RImQMAMc8riFAEzC9WwnQTMMKcsThEws1AN20nADHOyPkXAtBYN30fADLeyPknAtBYN30fADLeyPknAtBYN30fADLfiZK0A78CMfCIImJGAjKsECJgqLtPDBExTTtUyAqaKy/QwAdOUU7WMgKniMjtMwDSjVC8iYKrJzAYImGaU6kUETDWZ2QAB04xSvYiAqSZjYLUAATPyUSBgRgIyrhIgYKq4TA8TME05VcsImCou08METFNO1TICporL7DAB04xSvYiAqSYzGyBgmlGqFxEw1WRmAwRMM0r1IgKmmowBAqbNM0DAtHFkS5gAATPMKYtTBMwsVMN2EjDDnLI4RcDMQjVsJwEzzMn6FAHTWjR8HwEz3Mr6JAHTWjR8HwEz3Mr6JAHTWjR8HwEz3IqTtQK8AzPyiSBgRgIyrhIgYKq4TA8TME05VcsImCou08METFNO1TICporL7DAB04xSvYiAqSYzGyBgmlGqFxEw1WRmAwRMM0r1IgKmmoyB1QIEzMhHgYAZCci4SoCAqeIyPUzANOVULSNgqrhMDxMwTTlVywiYKi6zwwRMM0r1IgKmmsxsgIBpRqleRMBUk5kNEDDNKNWLCJhqMgYImDbPAAHTxpEtYQIEzDCnLE4RMLNQDdtJwAxzyuIUATML1bCdBMwwJ+tTBExr0fB9BMxwK+uTBExr0fB9BMxwK+uTBExr0fB9BMxwK07WCvAOzMgngoAZCci4SoCAqeIyPUzANOVULSNgqrhMDxMwTTlVywiYKi6zwwRMM0r1IgKmmsxsgIBpRqleRMBUk5kNEDDNKNWLCJhqMgZWCxAwIx8FAmYkIOMqAQKmisv0MAHTlFO1jICp4jI9TMA05VQtI2CquMwOEzDNKNWLCJhqMrMBAqYZpXoRAVNNZjZAwDSjVC8iYKrJGCBg2jwDBEwbR7aECRAww5yyOEXAzEI1bCcBM8wpi1MEzCxUw3YSMMOcrE8RMK1Fw/cRMMOtrE8SMK1Fw/cRMMOtrE8SMK1Fw/cRMMOtOFkrwDswI58IAmYkIOMqAQKmisv0MAHTlFO1jICp4jI9TMA05VQtI2CquMwOEzDNKNWLCJhqMrMBAqYZpXoRAVNNZjZAwDSjVC8iYKrJGFgtQMCMfBQImJGAjKsECJgqLtPDBExTTtUyAqaKy/QwAdOUU7WMgKniMjtMwDSjVC8iYKrJzAYImGaU6kUETDWZ2QAB04xSvYiAqSZjgIBp8wwQMG0c2RImQMAMc8riFAEzC9WwnQTMMKcsThEws1AN20nADHOyPkXAtBYN30fADLeyPknAtBYN30fADLeyPknAtBYN30fADLfiZK0A78CMfCIImJGAjKsECJgqLtPDBExTTtUyAqaKy/QwAdOUU7WMgKniMjtMwDSjVC8iYKrJzAYImGaU6kUETDWZ2QAB04xSvYiAqSZjYLUAATPyUSBgRgIyrhIgYKq4TA8TME05VcsImCou08METFNO1TICporL7DAB04xSvYiAqSYzGyBgmlGqFxEw1WRmAwRMM0r1IgKmmowBAqbNM0DAtHFkS5gAATPMKYtTBMwsVMN2EjDDnLI4RcDMQjVsJwEzzMn6FAHTWjR8HwEz3Mr6JAHTWjR8HwEz3Mr6JAHTWjR8HwEz3IqTtQK8AzPyiSBgRgIyrhIgYKq4TA8TME05VcsImCou08METFNO1TICporL7DAB04xSvYiAqSYzGyBgmlGqFxEw1WRmAwRMM0r1IgKmmoyB1QIEzMhHgYAZCci4SoCAqeIyPUzANOVULSNgqrhMDxMwTTlVywiYKi6zwwRMM0r1IgKmmsxsgIBpRqleRMBUk5kNEDDNKNWLCJhqMgYImDbPAAHTxpEtYQIEzDCnLE4RMLNQDdtJwAxzyuIUATML1bCdBMwwJ+tTBExr0fB9BMxwK+uTBExr0fB9BMxwK+uTBExr0fB9BMxwK07WCvAOzMgngoAZCci4SoCAqeIyPUzANOVULSNgqrhMD1rNgbcAACAASURBVBMwTTlVywiYKi6zwwRMM0r1IgKmmsxsgIBpRqleRMBUk5kNEDDNKNWLCJhqMgZWCxAwIx8FAmYkIOMqAQKmisv0MAHTlFO1jICp4jI9TMA05VQtI2CquMwOEzDNKNWLCJhqMrMBAqYZpXoRAVNNZjZAwDSjVC8iYKrJGCBg2jwDBEwbR7aECRAww5yyOEXAzEI1bCcBM8wpi1MEzCxUw3YSMMOcrE8RMK1Fw/cRMMOtrE8SMK1Fw/cRMMOtrE8SMK1Fw/cRMMOtOFkrwDswI58IAmYkIOMqAQKmisv0MAHTlFO1jICp4jI9TMA05VQtI2CquMwOEzDNKNWLCJhqMrMBAqYZpXoRAVNNZjZAwDSjVC8iYKrJGFgtQMCMfBQImJGAjKsECJgqLtPDBExTTtUyAqaKy/QwAdOUU7WMgKniMjtMwDSjVC8iYKrJzAYImGaU6kUETDWZ2QAB04xSvYiAqSZjgIBp8wwQMG0c2RImQMAMc8riFAEzC9WwnQTMMKcsThEws1AN20nADHOyPkXAtBYN30fADLeyPknAtBYN30fADLeyPknAtBYN30fADLfiZK0A78CMfCIImJGAjKsECJgqLtPDBExTTtUyAqaKy/QwAdOUU7WMgKniMjtMwDSjVC8iYKrJzAYImGaU6kUETDWZ2QAB04xSvYiAqSZjYLUAATPyUSBgRgIyrhIgYKq4TA8TME05VcsImCou08METFNO1TICporL7DAB04xSvYiAqSYzGyBgmlGqFxEw1WRmAwRMM0r1IgKmmowBAqbNM0DAtHFkS5gAATPMKYtTBMwsVMN2EjDDnLI4RcDMQjVsJwEzzMn6FAHTWjR8HwEz3Mr6JAHTWjR8HwEz3Mr6JAHTWjR8HwEz3IqTtQK8AzPyiSBgRgIyrhIgYKq4TA8TME05VcsImCou08METFNO1TICporL7DAB04xSvYiAqSYzGyBgmlGqFxEw1WRmAwRMM0r1IgKmmoyB1QIEzMhHgYAZCci4SoCAqeIyPUzANOVULSNgqrhMDxMwTTlVywiYKi6zwwRMM0r1IgKmmsxsgIBpRqleRMBUk5kNEDDNKNWLCJhqMgYImDbPAAHTxpEtYQIEzDCnLE4RMLNQDdtJwAxzyuIUATML1bCdBMwwJ+tTBExr0fB9BMxwK+uTBExr0fB9BMxwK+uTBExr0fB9BMxwK07WCvAOzMgngoAZCci4SoCAqeIyPUzANOVULSNgqrhMDxMwTTlVywiYKi6zwwRMM0r1IgKmmsxsgIBpRqleRMBUk5kNEDDNKNWLCJhqMgZWCxAwIx8FAmYkIOMqAQKmisv0MAHTlFO1jICp4jI9TMA05VQtI2CquMwOEzDNKNWLCJhqMrMBAqYZpXoRAVNNZjZAwDSjVC8iYKrJGCBg2jwDBEwbR7aECRAww5yyOEXAzEI1bCcBM8wpi1MEzCxUw3YSMMOcrE8RMK1Fw/cRMMOtrE8SMK1Fw/cRMMOtrE8SMK1Fw/cRMMOtOFkrwDswReS8y66TK66+aa3Md86fJdN3nrb2j6+/+TY5fc7c6h/vs9cMOevkmdLZ2V79YwImf0vlKUDAzFO79loETD97AqafPQHTz56A6WNPwPRxT65KwPSzJ2D62RMw/ewJmH72BEw/+6JfuekD5qIly+TbP/w/OeaQD1Wj5Lz5z8tps78lZ886XLaaOkXufuAxOe+Sa+Wi2SfIxPFjq7Ez+TrxyAMImMt7iv78F+71EzD9bhkB08+egOlnT8D0sydg+tgTMH3cCZh+7smVCZh+/gRMP3sCpp89AdPPvuhXbvqAOfgGJkHzmFlfkxOP+nj1XZhJsNxys8my/957VI8ODpq8A7PofwsU6/UTMP3uFwHTz56A6WdPwPSzJ2D62BMwfdwJmH7uBExfewKmnz8B08+egOlnX/QrEzAH3cEkUJ529uVy6ZyTZMrkDeSMc+fKjDdtvzZgDn6H5j8WdhX9GVC//s6OFulsLcviFb3qWQbiBMaMKkvyL1fLVvbFLWJaLTBudKv0DVRkZVe/epaBOIEJ67XJqp5+6e4ZiFvEtFpg0vh2WbK8V/r6K+pZBuIENprYIS8v7pYK9HGQyulSSSQJ9y8t6lZOcjxWoLVckvHrtcmCJXzCJ9ZSO9/R3iKj2suyeDm/t9faxZ4f3VmW1paSLOX39rGU6vmxo1tloFKRFav4vb0aL3Jgwpg26errl67u5vu9ffIfqPlKL0DAXG2XhMnPnvJVef7FBbLme2B2dfVUA+YB++659ntiDg6YyT/0mu2rJCVJ/l+lCX/t3ve6ai8iFWm+587dPvm32gr2HvchifbJP2547vPXxz5/8zVXxN7HPvnf2eQf9834+zsf8X9dFXu/O4C9rz3/XuXjz79X+bgnVy018b9XJb+/4yu9AAFzkN26HyHfaduthn0HJh8hT//wMakX4CPkejOrCT5CbiWp38NHyPVmVhN8hNxKUr+Hj5DrzSwm+Ai5hWK6HfwQn3RuFlN8D0wLxXQ7+Ah5OjeLKT5CbqGYbgcfIU/nxpQIAXOIp2Dd73vJ98CsBxrVUZbOtrIs4of45P7PEAJm7uRrL0jA9LMnYPrZEzD97AmYPvYETB/35KoETD97AqafPQHTz56A6WdPwPSzL/qVmz5gJh8Jv+X398qRn9q3ei/XfJT87NOOqH5snJ9CTsBslL/Ju/u75E8v/k4qlX55y+R3yujWMY3y0pridRAw/W4zAdPPnoDpZ0/A9LEnYPq4EzD93JMrEzD9/AmYfvYETD97AqaffdGv3PQBc833ubzpljvX3ss13wNzzZ+4/ubb5PQ5c6t/uM9eM+Ssk2dKZ2d79Y/5CHnR/xYoxut/YuGj8q6r31zzYn/60Vtl+iZvLcYvYAS8SgKm300kYPrZEzD97AmYPvYETB93AqafOwHT156A6edPwPSzJ2D62Rf9yk0fMGNvIAEzVpD5EIHXXTRRegbqfyLqc8etDBnnjIEAAdMAMeUKAmZKOIMxAqYBYsoVBMyUcJFjBMxIwIhxPkIegRc5yjswIwEjxgmYEXiRowTMSMCIcQJmBF6TjxIwIx8AAmYkIONBApteMHrIcwTMID6TQwRME8ZUSwiYqdhMhgiYJoyplhAwU7FFDxEwowlTLyBgpqaLHiRgRhOmXkDATE0XPUjAjCZMvYCAmZqu6QcJmJGPAAEzEpDxIIFpl20sy3qW1pwtl8ryzLHLguY5FC9AwIw3TLuBgJlWLn6OgBlvmHYDATOtXNwcATPOL2aagBmjFzdLwIzzi5kmYMboxc0SMOP8YqYJmDF6zT1LwIy8/wTMSEDGgwReWP6cvOU7r685+9uD/yyvnzgtaJ5D8QIEzHjDtBsImGnl4ucImPGGaTcQMNPKxc0RMOP8YqYJmDF6cbMEzDi/mGkCZoxe3CwBM84vZpqAGaPX3LMEzMj7T8CMBGQ8WKC/0i/zlj4slcqAbDVuJ2ltaQ2e5WC8AAEz3jDtBgJmWrn4OQJmvGHaDQTMtHJxcwTMOL+YaQJmjF7cLAEzzi9mmoAZoxc3S8CM84uZJmDG6DX3LAEz8v4TMCMBGVcJrDeqVZJ/uVq6slc1x+F4AQJmvGHaDQTMtHLxcwTMeMO0GwiYaeXi5giYcX4x0wTMGL24WQJmnF/MNAEzRi9uloAZ5xczTcCM0WvuWQJm5P0nYEYCMq4SIGCquEwPEzBNOVXLCJgqLtPDBExTTtUyAqaKy+wwAdOMUr2IgKkmMxsgYJpRqhcRMNVkZgMETDNK9SICppqMgdUCBMzIR4GAGQnIuEqAgKniMj1MwDTlVC0jYKq4TA8TME05VcsImCous8METDNK9SICpprMbICAaUapXkTAVJOZDRAwzSjViwiYajIGCJg2zwAB08aRLWECBMwwpyxOETCzUA3bScAMc8riFAEzC9WwnQTMMCfrUwRMa9HwfQTMcCvrkwRMa9HwfQTMcCvrkwRMa9HwfQTMcCtO1grwDszIJ4KAGQnIuEqAgKniMj1MwDTlVC0jYKq4TA8TME05VcsImCous8METDNK9SICpprMbICAaUapXkTAVJOZDRAwzSjViwiYajIGVgsQMCMfBQJmJCDjKgECporL9DAB05RTtYyAqeIyPUzANOVULSNgqrjMDhMwzSjViwiYajKzAQKmGaV6EQFTTWY2QMA0o1QvImCqyRggYNo8AwRMG0e2hAkQMMOcsjhFwMxCNWwnATPMKYtTBMwsVMN2EjDDnKxPETCtRcP3ETDDraxPEjCtRcP3ETDDraxPEjCtRcP3ETDDrThZK8A7MCOfCAJmJCDjKgECporL9DAB05RTtYyAqeIyPUzANOVULSNgqrjMDj+37BlZ1D9fNmp7vWw0ZmOzvSwaXoCAObxRVicImFnJDr+XgDm8UVYnCJhZyQ6/l4A5vBEnhhYgYEY+GQTMSEDGVQIETBWX6WECpimnahkBU8VlepiAacqpWkbAVHGZHH7HlTvLvMVPrt31nqkfkO/te73JbpYML0DAHN4oqxMEzKxkh99LwBzeKKsTBMysZIffS8Ac3ogTBMxMngECZiasLH0VAQKm36NBwPSzJ2D62RMw/ewJmPna3//iPbLPdXvUXfTBw5+RSZ0b5PtimvRqBEy/G0/A9LMnYPrZEzD97AmYfvZFvzLvwIy8gwTMSEDGVQIETBWX6WECpimnahkBU8VlepiAacqpWkbAVHFFH770/vPlrNtPrdtz/Ud/Jbtt8vbo/SwYXoCAObxRVicImFnJDr+XgDm8UVYnCJhZyQ6/l4A5vBEnhhYgYEY+GQTMSEDGVQIETBWX6WECpimnahkBU8VlepiAacqpWkbAVHFFH777hT/Kh3/8nro99818WjYaPTl6PwuGFyBgDm+U1QkCZlayw+8lYA5vlNUJAmZWssPvJWAOb8QJAmYmzwABMxNWlr6KAAHT79EgYPrZEzD97AmYfvYEzPztd7liS3l51UtrL/zmjXeTGz72m/xfSJNekYDpd+MJmH72BEw/ewKmnz0B08++6FfmHZiRd5CAGQnIuEqAgKniMj1MwDTlVC0jYKq4TA8TME05VcsImCous8OPL/yLvNT9lGw+egfZcvzWZntZNLwAAXN4o6xOEDCzkh1+LwFzeKOsThAws5Idfi8Bc3gjTgwtQMCMfDIImJGAjKsECJgqLtPDBExTTtUyAqaKy/QwAdOUU7WMgKniMjvcUirJRhM75B8Lu8x2sihMgIAZ5pTFKQJmFqphOwmYYU5ZnCJgZqEatpOAGebEqXoBAmbkU0HAjARkXCVAwFRxmR4mYJpyqpYRMFVcpocJmKacqmUETBWX2WECphmlehEBU01mNkDANKNULyJgqsnMBgiYZpTqRQRMNRkDqwUImJGPAgEzEpBxlQABU8VlepiAacqpWkbAVHGZHiZgmnKqlhEwVVxmhwmYZpTqRQRMNZnZAAHTjFK9iICpJjMbIGCaUaoXETDVZAwQMG2eAQKmjSNbwgQImGFOWZwiYGahGraTgBnmlMUpAmYWqmE7CZhhTtanCJjWouH7CJjhVtYnCZjWouH7CJjhVtYnCZjWouH7CJjhVpysFeAdmJFPBAEzEpBxlQABU8VlepiAacqpWkbAVHGZHiZgmnKqlhEwVVxmhwmYZpTqRQRMNZnZAAHTjFK9iICpJjMbIGCaUaoXETDVZAysFnANmOdddp3846UFctbJM6sv54xz58pNt9wpUyZPkkvnnCRbTZ3S8DeKgNnwt2hEvUACpt/tJGD62RMw/ewJmH72BEwfewKmj3tyVQKmnz0B08+egOlnT8D0sydg+tkX/cpuAXPRkmVyzKyvyYlHfVym7zxN7n7gMbnuxt9WY+ZDj89b+393drY3tDEBs6Fvz4h7cQRMv1tKwPSzJ2D62RMw/ewJmD72BEwfdwKmn3tyZQKmnz8B08+egOlnT8D0sy/6lV0D5mnnXC6fP/rA6jstk3djJl8nHnmAzJv/vHzl4mvk7FOPkInjxza0MQGzoW/PiHtxBEy/W0rA9LMnYPrZEzD97AmYPvYETB93AqafOwHT156A6edPwPSzJ2D62Rf9ym4Bs6urp/qR8QP23VO22XLTundjnnfJtXLR7BMImA34hI3qKEtnW1kWLe9pwFc3sl8SAdPv/hIw/ewJmH72BEw/ewKmjz0B08edgOnnTsD0tSdg+vkTMP3sCZh+9kW/slvATOCSd1p+9pSvyvMvLpDDPrlP9d2Xaz5aPn3X7ap/3OhfvAOz0e/QyHp9BEy/+0nA9LMnYPrZEzD97AmYPvYETB93AqafOwHT156A6edPwPSzJ2D62Rf9yq4Bs+h4yesnYI6Eu1icXwMB0+9eETD97AmYfvYETD97AqaPPQHTx52A6edOwPS1J2D6+RMw/ewJmH72Rb8yATPyDhIwIwEZVwkQMFVcpocJmKacqmUETBWX6WECpimnahkBU8VldpiAaUapXsRPIVeTmQ3wQ3zMKNWLCJhqMrMBAqYZpXoRAVNNxsBqAQJm5KNAwIwEZFwlQMBUcZkeJmCacqqWETBVXKaHCZimnKplBEwVl9lhAqYZpXoRAVNNZjZAwDSjVC8iYKrJzAYImGaU6kUETDUZA40QMNf8IJ+bbrlTpkyeJJfOOUmmTN6g+sN9Zrxpe9l/7z0a/kYRMBv+Fo2oF0jA9LudBEw/ewKmnz0B08+egOljT8D0cU+uSsD0sydg+tkTMP3sCZh+9gRMP/uiX9n1HZjnXXadbLnZZNn73TPkKxdfIwfvv5dsNXWK3P3AY3Ldjb+Vs06eKZ2d7Q1tTMBs6Nsz4l4cAdPvlhIw/ewJmH72BEw/ewKmjz0B08edgOnnnlyZgOnnT8D0sydg+tkTMP3si35lt4CZ/LTx0865XD5/9IHVd12uGzCTn06e/PHZpx4hE8ePbWhjAmZD354R9+IImH63lIDpZ0/A9LMnYPrZEzB97AmYPu4ETD93AqavPQHTz5+A6WdPwPSzL/qVGzJg8g7Mxn6sRnWUpbOtLIuW9zT2Cx2Br46A6XdTCZh+9gRMP3sCpp89AdPHnoDp407A9HMnYPraEzD9/AmYfvYETD/7ol/ZLWAmcNfffJvc+edH5NTPHSwXzP1J9SPkEyeMlWNmfU0O2HdPvgdmgz5dBEy/G0PA9LMnYPrZEzD97DcY3y5LlvdJb/+A34to0isTMH1uPAHTx52A6edOwPS1J2D6+RMw/ewJmH72Rb+ya8BM8JJ3Wx56/Owax++cP0um7zytELZ8hLwQt2nEvEgCpt+tJGD62RMw87d/aeU/ZLfvbCc9A93Vi5/9zq/LZ3Y6Mv8X0sRXJGD63HwCpo87AdPPnYDpa0/A9PMnYPrZEzD97It+ZfeAWXRAAmbR72CxXj8B0+9+ETD97AmY+dtvesHouov+6qC7ZPtJO+X/Ypr0igRMnxtPwPRxJ2D6uRMwfe0JmH7+BEw/ewKmn33Rr0zAjLyDBMxIQMZVAgRMFZfpYQKmKadqGQFTxRV9eOGqBbLTFZvX7dlnmw/LZR+4Ono/C8IECJhhTtanCJjWouH72sotMmFsm7y8+JV3fvOVnwA/hTw/68FXImD62RMw/ewJmH72Rb9yrgEz+cnjyfe3fPDRecO6vXG7reSi2SfwU8iHlcr/AN8DM3/zNVckYPrZEzD97AmY+dov6V4s218+pe6i+7/hQPnm++bm+2Ka+GoETJ+bT8D0cU+uSsD0sydg+tkTMP3sCZh+9gRMP/uiXznXgFl0rKFeP+/AHIl3tXF/TQRMv3tDwPSzJ2Dmb7/FhWOlv9Jfc+G7PvOYbDZ2i/xfTJNekYDpc+MJmD7uBEw/9+TKBEw/fwKmnz0B08+egOlnX/QrEzAj7yABMxKQcZUAAVPFZXqYgGnKqVpGwFRxmRzu6l8le/9wd3l84aPS2tIq137k57LbJm832c2SMAECZpiT9SkCprVo+D7egRluZX2SgGktGr6PgBluZX2SgGktGr6PgBluxclaAQJm5BNBwIwEZFwlQMBUcZkeJmCacqqWETBVXKaHN5zQIYuX9Upv/4DpXpYNL0DAHN4oixMEzCxUw3YSMMOcsjhFwMxCNWwnATPMKYtTBMwsVMN2EjDDnDhVL+AaMOfNf14+e8pX5fkXF9S9Mr4HZuM+rnwPTL97Q8D0sydg+tkTMP3sCZh+9gRMH3sCpo97clUCpp89AdPPnoDpZ0/A9LMnYPrZF/3KbgGzq6tHzjh3rsx40/ayyw7byFXX3yKfP/pA6exsl/Muu07esdtOMn3naQ3vyzswG/4WjagXSMD0u50ETD97AqafPQHTz56A6WNPwPRxJ2D6uSdXJmD6+RMw/ewJmH72BEw/+6Jf2S1gJj+R/LRzLq9Gy+TrKxdfI2efekT1p47f/cBjct2Nv5WzTp5ZDZqN/EXAbOS7M/JeGwHT754SMP3sCZh+9gRMP3sCpo89AdPHnYDp507A9LUnYPr5EzD97AmYfvZFv3JDBMyJE8bKOd+8Sk793MHVgJl8tHzdoNnIyATMRr47I++1ETD97ikB08+egOlnT8D0sydg+tgTMH3cCZh+7gRMX3sCpp8/AdPPnoDpZ1/0K7sFzHU/Qr7/3ntUPza+5WaTJfm/r7/5Nrnzz4/wDswGfbr4Hph+N4aA6WdPwPSzJ2D62RMw/ewJmD72BEwfdwKmnzsB09eegOnnT8D0sydg+tkX/cpuAXMwXPKR8mNmfU0efHSeTJk8SS6dc5JsNXVKw/vyDsyGv0Uj6gUSMP1uJwHTz56A6WdPwPSzJ2D62BMwfdwJmH7uBExfewKmnz8B08+egOlnX/QrN0zALCokAbOod66Yr5uA6XffCJh+9gRMP3sCpp89AdPHnoDp407A9HMnYPraEzD9/AmYfvYETD/7ol/ZJWAmHxG/+Ls/q3mXZfKDew49fnbV80unzKx+lLwIXwTMItylkfMaCZh+95KA6WdPwPSzJ2D62RMwfewJmD7uBEw/dwKmrz0B08+fgOlnT8D0sy/6lV0CZvL9LpOvE488oPr/r/sTyadM3kDOOHeuHLDvnjJ952kN70vAbPhbNKJeIAHT73YSMP3sCZh+9gRMP3sCpo89AdPHnYDp507A9LUnYPr5EzD97AmYfvZFv3LuAXPN97o88aiPrw2Uybsvr7vxt2t/aM/gP25kZAJmI9+dkffaCJh+95SA6WdPwPSzJ2D62RMwfewJmD7uBEw/dwKmrz0B08+fgOlnT8D0sy/6lV0C5mnnXC6fP/rAtT+kZ/A7MufNf16+cvE1cvapR8jE8WMb2piA2dC3Z8S9OAKm3y0lYPrZEzD97AmYfvYETB97AqaPOwHTz52A6WtPwPTzJ2D62RMw/eyLfuWGCZhbbjZ57fe9JGA29mM1qqMsnW1lWbS8p7Ff6Ah8dQRMv5tKwPSzJ2D62RMw/ewJmD72BEwfdwKmnzsB09eegOnnT8D0sydg+tkX/cq5B8yurp6a73E5+I8T0OQj5Oddcq1cNPuEzN+Bueb6N91y59p7+Z3zZ9V8/83khw6dPmdu9a/vs9eMtR91T/6Yd2AW/W+BYr1+Aqbf/SJg+tkTMP3sCZh+9gRMH3sCpo87AdPPnYDpa0/A9PMnYPrZEzD97It+5dwDZgKWBME7//xINQQ+9Pi8ulg5+CPlWSIn35Pz2z/8PznmkA9JZ2d7NZ6edvbla39C+uCYOvi1ETCzvDvsHixAwPR7JgiYfvYETD97AqafPQHTx56A6eNOwPRzJ2D62hMw/fwJmH72BEw/+6Jf2SVgJmhJCLzi6puqfuu+4zEJhoceP7vmz+WJPPiHDCWvc92Ptw8OmgTMPO8O1yJg+j0DBEw/ewKmnz0B08+egOljT8D0cSdg+rkTMH3tCZh+/gRMP3sCpp990a/sFjAbFS75/punzf6WnD3rcJkyeYPqx91nvGn7mu/PueavbzV1Ch8hb9QbOUJfFwHT78YSMP3sCZh+9gRMP3sCpo89AdPHnYDp507A9LUnYPr5EzD97AmYfvZFv3JDB8zk+1Ne9L2fyX984gOZfy/M5Eau+X6Ya4LlUN+fc93AmQTMld39RX8G1K+/taUk5ZaSdPcNqGcZiBNoK5dESiK9fZW4RUyrBdpbSzJQEenrx16NFznQ0dZSde9PbgBfuQp0trdIT+9A9dnnK1+B5AfmdXX3C/T5updEpLOjLKua8Pd3+UrXX62lJNLe1iJdPfz+Mu97kfy+vrVcku5e7PO2T9yTZ7+H39vnTS9trSVJ/ke2l9/b527f0dpS/X19XxP+BnN0Rzl375F0QQLm6ru5JlZuvNEkOfHIA6p/dnDQTP7c4IC5uAl/EndbW4u0lVtkZVffSPp7oRC/lo72srRISVb1YJ/3DRvV0SoDAxXp7m2+/2iRt/Xg6yXvTujpG5Be/qNJ7rdi7Og2WdnVL/0D/Ett3vjJu76XruyTSoWEmad9qVSScaNbZcmK3jwvy7VEpNzSIqM7y7JsJfZ5PxBtrS3S3toiK/i9fd700tFWlpaWkqzq5vf2eeOPam+VAalIdw+/t8/bfnRnq/T2D0hvE/5HkwnrtefNPaKuR8BcJ1SuGy/X3GW+B2b98568K6SzrSyLmjDeev/dz0fI/e4AHyH3s+cj5H72fITcz56PkPvY8xFyH/fkqsl/HJ8wtk1eXtzt9yKa9Mqd7WVJ3hW0cFlPkwr4/bL5CLmfPR8h97PnI+R+9kW/ctMHzKHeZbnuTeWnkBMwG+lvcgKm390gYPrZEzD97AmYfvYETB97AqaPOwHTzz25MgHTz5+A6WdPwPSzJ2D62Rf9yk0fMJOPhH/2lK/K8y8uqLmXh31yn7UfJb/+5tvk9Dlzq399n71myFknz5TOzlfe+stPIS/63wLFev0ETL/7RcD0sydg+tkTMP3swLBEYwAAIABJREFUCZg+9gRMH3cCpp87AdPXnoDp50/A9LMnYPrZF/3KTR8wY28gATNWkHmNAAFTo2V7loBp66nZRsDUaNmeJWDaemq2ETA1WnZnCZh2ltpNfIRcK2Z3nndg2llqNxEwtWJ25wmYdpbaTQRMrRjn1wgQMCOfBQJmJCDjKgECporL9DAB05RTtYyAqeIyPUzANOVULSNgqrjMDhMwzSjViwiYajKzAQKmGaV6EQFTTWY2QMA0o1QvImCqyRhYLUDAjHwUCJiRgIyrBAiYKi7TwwRMU07VMgKmisv0MAHTlFO1jICp4jI7TMA0o1QvImCqycwGCJhmlOpFBEw1mdkAAdOMUr2IgKkmY4CAafMMEDBtHNkSJkDADHPK4hQBMwvVsJ0EzDCnLE4RMLNQDdtJwAxzsj5FwLQWDd9HwAy3sj5JwLQWDd9HwAy3sj5JwLQWDd9HwAy34mStQMO9A3PRkmVyzKyvVV/lRbNPkInjxzb0PSNgNvTtGXEvjoDpd0sJmH72BEw/ewKmnz0B08eegOnjnlyVgOlnT8D0sydg+tkTMP3sCZh+9kW/csMEzLsfeEwOPX521XPK5Ely6ZyTZKupUxrel4DZ8LdoRL1AAqbf7SRg+tkTMP3sCZh+9gRMH3sCpo87AdPPPbkyAdPPn4DpZ0/A9LMnYPrZF/3K7gHzvMuukyuuvmmt43fOnyXTd55WGFcCZmFu1Yh4oQRMv9tIwPSzJ2D62RMw/ewJmD72BEwfdwKmnzsB09eegOnnT8D0sydg+tkX/couAXPNx8QffHRe1S+JlttsuWn1o+MnHvVxAmaDP1WjOsrS2VaWRct7GvyVjryXR8D0u6cETD97AqafPQHTz56A6WNPwPRxJ2D6uRMwfe0JmH7+BEw/ewKmn33Rr5x7wHy173G55s8TMBv/kSJg+t0jAqafPQHTz56A6WdPwPSzJ2D62BMwfdwJmH7uBExfewKmnz8B08+egOlnX/QruwXMzTfdSM46eaZ0drZXDQmYxXmUCJh+94qA6WdPwPSzJ2D62RMw/ewJmD72BEwfdwKmnzsB09eegOnnT8D0sydg+tkX/cq5B8x1Y2XyEfI1P7Bn4oSxfIS8IE8TAdPvRhEw/ewJmH72BEw/ewKmnz0B08eegOnjTsD0cydg+toTMP38CZh+9gRMP/uiX9klYK6Lxg/xKd4jRMD0u2cETD97AqafPQHTz56A6WdPwPSxJ2D6uBMw/dwJmL72BEw/fwKmnz0B08++6Fd2D5hrAO9+4DE59PjZ1T/cZ68ZNR8vb2Rkfgp5I9+dkffaCJh+95SA6WdPwPSzJ2D62RMwfewJmD7uBEw/dwKmrz0B08+fgOlnT8D0sy/6lRsmYK6BfLUf8tOo0ATMRr0zI/N1ETD97isB08+egOlnT8D0sydg+tgTMH3cCZh+7gRMX3sCpp8/AdPPnoDpZ1/0KzdcwCwaKAGzaHes2K+XgOl3/wiYfvYETD97AqafPQHTx56A6eNOwPRzJ2D62hMw/fwJmH72BEw/+6JfOfeAueYdlskP8Hmtrzdut5VcNPsEmTh+bEMbEzAb+vaMuBdHwPS7pQRMP3sCpp89AdPPnoDpY0/A9HEnYPq5EzB97QmYfv4ETD97AqaffdGvnHvAHA5szQ/1IWAOJ+X31/khPn72BEw/ewKmnz0B08+egOlnT8D0sSdg+rgTMP3cCZi+9gRMP38Cpp89AdPPvuhXbpiAue4P8fnO+bNk+s7TCmHLOzALcZtGzIskYPrdSgKmnz0B08+egOlnT8D0sSdg+rgTMP3cCZi+9gRMP38Cpp89AdPPvuhXdg+YXV09csa5c+WmW+6Uwz65j5x45AGFMiVgFup2Ff7FEjD9biEB08+egOlnT8D0sydg+tgTMH3cCZh+7gRMX3sCpp8/AdPPnoDpZ1/0K7sGzOtvvk1OnzNXpkyeJJfOOUm2mjqlcJ4EzMLdskK/YAKm3+0jYPrZEzD97AmYfvYETB97AqaPOwHTz52A6WtPwPTzJ2D62RMw/eyLfmWXgDlv/vPy2VO+Ks+/uEC+dMpM2X/vPQrr2IwBs6+0Qlpa+qXUN1ZKpVJh710RXzgBM/+7VpGKHH7zgfJ/826sXvz46bPklN3OyP+FNPEVCZh+N5+A6WdPwPSxJ2D6uBMw/dwJmL72BEw/fwKmnz0B08++6FfOPWCu+Snkm2+6kZx18kzp7GwvtGEzBcz+Sr/scPmmsqxn6dp79ruD75NtJm5b6HtYpBdPwMz/bn3k+r3kT8//oebC/z3jTPnPt5yS/4tp0isSMP1uPAHTz56A6WNPwPRxJ2D6uRMwfe0JmH7+BEw/ewKmn33Rr+wWMB98dN5r2vFTyBvv0UrehfbzeTfUvbDnjlvZeC92hL4iAmb+N3bTC0YPeVGe+/zuBQEzP+vBVyJg+tkTMH3sCZg+7gRMP3cCpq89AdPPn4DpZ0/A9LMv+pVzD5hFBxv8+pvpHZibXTBGko/TDv76+7HLpaXUMtJubUP+egiY+d8WAmb+5oOvSMD0uwcETD97AqaPPQHTx52A6edOwPS1J2D6+RMw/ewJmH72Rb8yATPyDjZTwNx17lby0sp/1InxTrTIh0gxTsBUYBkd3euaf5NH//lwzbajdz1B/uft/2t0BdYMJ0DAHE4ou79OwMzOdrjNBMzhhLL56wTMbFxDtraVW2TC2DZ5eXF3yHHOGAp0tpdldEdZFi7rMdzKqhABAmaIUjZnCJjZuIZsJWCGKHFmKAECZuRz0UwB86nFT8geV+5SI3bELp+TM3f/cqQi46ECBMxQKbtzA5UB2fdHe8r9L95TXfqJ7Q6R895zid0F2DSsAAFzWKLMDhAwM6N9zcWVSkXWn9Aii5dWpFL/wQefF9UkVyVg+t1oAqafPQHTz56A6WdPwPSzJ2D62Rf9ygTMyDvYTAEzoXp55UvylT99QRaselmO2OW/ZMYmu0cKMq4RIGBqtGzPjh/TJn39FVnR1We7mG3DChAwhyXK7AABMzPaV138syevk2N+8Zm1f/2U3c6Q46fPyv+FNOkVCZh+N56A6WdPwPSzJ2D62RMw/ewJmH72Rb8yATPyDjZbwEy4RnWUpbOtLIuW8zGTyMdHPU7AVJOZDRAwzSjViwiYajKzAQKmGWXQoq6+VbL1JZPqzt5z6JOyyXqbBu3gUJwAATPOL2aagBmjFzdLwIzzi5kmYMboxc0SMOP8YqYJmDF6zT1LwIy8/wTMSEDGgwUeW/AXOefO/5EB6ZeT3nKG7DL5LcGzHIwXIGDGG6bdQMBMKxc/R8CMN9RsuPcfd8l+P3pX3chZ7zhXDtv5GM0qzqYUIGCmhDMYI2AaIKZcQcBMCWcwRsA0QEy5goCZEs5gjIBpgNikKwiYkTeegBkJyHiQwM1P/UyO+PlBNWfP2fN8OWTHI4LmORQvQMCMN0y7gYCZVi5+joAZb6jZ8NSiJ2SPq2q/13Qyf9kHrpJ9tvmIZhVnUwoQMFPCGYwRMA0QU64gYKaEMxgjYBogplxBwEwJZzBGwDRAbNIVBMzIG0/AjARkPEhg0wtGD3mOnwAfxGdyiIBpwphqCQEzFZvJEAHThDF4SUUqssWFYyX54WHrfs0/Zqm0trQG7+FgegECZnq72EkCZqxg+nkCZnq72EkCZqxg+nkCZnq72EkCZqxg884TMCPvPQEzEpDxIAECZhBTpocImJnyvuZyAqafPQEzf/u+Sp+c8buT5Y8v/Fa2X39nOfc9F8uo1qH/I1b+r27kX5GA6XePCZh+9gRMP3sCpp89AdPPnoDpZ1/0KxMwI+8gATMSkPEggT2u3EWeWvxEzdmJnevLw4c/GzTPoXgBAma8YdoNBMy0cvFzBMx4Q+2GxxY8Inv9YLok78ZMvq7a7wbZc4u9tGs4n1KAgJkSzmCMgGmAmHIFATMlnMEYAdMAMeUKAmZKOIMxAqYBYpOuIGBG3ngCZiQg40EC3f1dsu1lG0tv/ys/+b0kJXn0yBdkbPu4oHkOxQsQMOMN024gYKaVi58jYMYbajb0DfTJ1Ivq/7n+6BEvyLiO8ZpVnE0pQMBMCWcwRsA0QEy5goCZEs5gjIBpgJhyBQEzJZzBGAHTALFJVxAwI288ATMSkHGVQLmtV0oi0tfbpprjcLwAATPeMO0GAmZaufg5Ama8oWbDAy/9Wfa+dve6kS+/65vyqR0O06zibEoBAmZKOIMxAqYBYsoVBMyUcAZjBEwDxJQrCJgp4QzGCJgGiE26goAZeeMJmJGAjKsE1hvVKsm/XC1d2aua43C8AAEz3jDtBgJmWrn4OQJmvKFmwyMLHpL3/mC3upGvvedS+fh2n9as4mxKAQJmSjiDMQKmAWLKFQTMlHAGYwRMA8SUKwiYKeEMxgiYBohNuoKAGXnjCZiRgIyrBAiYKi7TwwRMU07VMgKmisv0MAHTlHPYZclPH9/8wvXqzv31qH/yg3yG1bM5QMC0cUyzhYCZRs1mhoBp45hmCwEzjZrNDAHTxjHNFgJmGjVmEgECZuRzQMCMBGRcJUDAVHGZHiZgmnKqlhEwVVymhwmYppxByxZ0/VP2unq6vLTyRRndOkZ+ceAfZKsJrw+a5VC8AAEz3jDtBgJmWrn4OQJmvGHaDQTMtHLxcwTMeMO0GwiYaeWYI2BGPgMEzEhAxlUCBEwVl+lhAqYpp2oZAVPFZXqYgGnKqVq28fqd8tKibhmovPLTyPnKR4CAmY/zUFchYPrZEzD97AmYfvYETD97AqaffdGvTMCMvIMEzEhAxlUCBEwVl+lhAqYpp2oZAVPFZXqYgGnKqVpGwFRxmR0mYJpRqhcRMNVkZgMETDNK9SICpprMbICAaUapXkTAVJMxsFqAgBn5KBAwIwEZDxb49oOXyBm/P1kqlYqcMuMM+c+3/HfwLAfjBQiY8YZpNxAw08rFzxEw4w3TbiBgppWLmyNgxvnFTBMwY/TiZgmYcX4x0wTMGL24WQJmnF/MNAEzRq+5ZwmYkfefgBkJyHiQwDfumSNfvvPMmrOH7vRZ+d93fi1onkPxAgTMeMO0GwiYaeXi5wiY8YZpNxAw08rFzREw4/xipgmYMXpxswTMOL+YaQJmjF7cLAEzzi9mmoAZo9fcswTMyPtPwIwEZDxIYNMLRg957rnjVgbNcyhegIAZb5h2AwEzrVz8HAEz3jDtBgJmWrm4OQJmnF/MNAEzRi9uloAZ5xczTcCM0YubJWDG+cVMEzBj9Jp7loAZef8JmJGAjAcJEDCDmDI9RMDMlPc1lxMw/ewJmH72BEwfewKmj3tyVQKmnz0B08+egOlnT8D0sydg+tkX/coEzMg7SMCMBGQ8SODgG/aT3z5zS83Z7TbYUW458E9B8xyKFyBgxhum3UDATCsXP0fAjDdMu4GAmVYubo6AGecXM03AjNGLmyVgxvnFTBMwY/TiZgmYcX4x0wTMGL3mniVgRt5/AmYkIONBAhWpyPt+MEMeWfBQ9fwW47aU2z/9kJRL5aB5DsULEDDjDdNuIGCmlYufI2DGG6bdQMBMKxc3R8CM84uZJmDG6MXNEjDj/GKmCZgxenGzBMw4v5hpAmaMXnPPEjAj7z8BMxKQcZXAmM6yJP9ytWxVn2qOw/ECBMx4w7QbCJhp5eLnCJjxhmk3EDDTysXNETDj/GKmCZgxenGzBMw4v5hpAmaMXtwsATPOL2aagBmj19yzBMzI+0/AjARkXCWw3qjWasBcurJXNcfheAECZrxh2g0EzLRy8XMEzHjDtBsImGnl4uYImHF+MdMEzBi9uFkCZpxfzDQBM0YvbpaAGecXM03AjNFr7lkCZuT9J2BGAjKuEiBgqrhMDxMwTTlVywiYKi7TwwRMU07VMgKmisvsMAHTjFK9iICpJjMbIGCaUaoXETDVZGYDBEwzSvUiAqaajIHVAgTMyEeBgBkJyHiwwGMLHpEv33W69Ff65MTpZ8guG705eJaD8QIEzHjDtBsImGnl4ucImPGGaTcQMNPKxc0RMOP8YqYJmDF6cbMEzDi/mGkCZoxe3CwBM84vZpqAGaPX3LMEzMj7T8CMBGQ8SODn826Qw28+sObsl9/1TfnUDocFzXMoXoCAGW+o3dDb3yPvvWaGPLnoserombvPkSN2OU67hvMRAgTMCLzIUQJmJGDKcQJmSjiDMQKmAWLKFQTMlHAGYwRMA8SUKwiYKeEMxgiYBohNuoKAGXnjCZiRgIwHCWx6weghzz133MqgeQ7FCxAw4w21G6ZdtrEs61laM3blvj+Td019r3YV51MKEDBTwhmMETANEFOsIGCmQDMaIWAaQaZYQ8BMgWY0QsA0gkyxhoCZAs1ohIBpBNmEawiYkTedgBkJyHiQAAEziCnTQwTMTHnrlvcN9MrUi8bX/fkdNnij/PLAO/N9MU18NQKm380nYPrYEzB93JOrEjD97AmYfvYETD97AqafPQHTz77oVyZgRt5BAmYkIONBAntcuYs8tfiJmrMTO9eXhw9/NmieQ/ECBMx4Q82GVwuY20/aSX510F2aVZyNECBgRuBFjhIwIwFTjhMwU8IZjBEwDRBTriBgpoQzGCNgGiCmXEHATAlnMEbANEBs0hUEzMgbT8CMBGQ8SOCTN+wnv3vmlpqz0yZtL7cedE/QPIfiBQiY8YbaDUN9hPz7+/5U3j31fdpVnE8pQMBMCWcwRsA0QEyxgoCZAs1ohIBpBJliDQEzBZrRCAHTCDLFGgJmCjSjEQKmEWQTriFgRt50AmYkIONBAnyEPIgp00MEzEx5h1ye/BCfva7ZTf666PHqX//C22fLkbv+Z/4vpImvSMD0u/kETB97AqaPe3JVAqafPQHTz56A6WdPwPSzJ2D62Rf9ygTMyDtIwIwEZDxIgIAZxJTpIQJmpryvuXz9se2ysrtfunr6/V5Ek16ZgOl34wmYPvYETB93Aqafe3JlAqafPwHTz56A6WdPwPSzL/qVCZjr3MHzLrtOttxssuy/9x419/X6m2+T0+fMrf65ffaaIWedPFM6O9urf0zALPrfAsV4/d+458vy5Tu/WPNiP7PTkXL2O79ejF/ACHiVBEy/m0jA9LMnYPrZEzB97AmYPu4ETD93AqavPQHTz5+A6WdPwPSzL/qVCZgism6g/NIpM2sC5t0PPCbnXXKtXDT7BJk4fqwkkTP5OvHIAwiYy3uK/vwX6vXPffBi+cLvPy+VSkU+v9vpcvz0WYV6/UV/sQRMvztIwPSzJ2D62RMwfewJmD7uBEw/dwKmrz0B08+fgOlnT8D0sy/6lQmY69zBod6BOfjPDQ6avAOz6H8LFOv1rzeqVZJ/uVq6srdYL7zgr7avv1eeXvEXaSt1yNSx06QkpYL/ior18gmYfveLgOlnT8D0sSdg+rgTMP3cCZi+9gRMP38Cpp89AdPPvuhXJmC+RsDs6uqRM86dKzPetP3ad2XOm/+8nDb7W3L2rMNlq6lT5OUl3UV/BtSvv6OtRTpay7J0FRFNjRc5MLqjLKVSSVZ09UVuYjxU4P4X75X3/eDtNcefOPoFmdAxMXQF5yIFxo9uk1U9/dLTNxC5iXGtwMSxbbJsRZ/0DVS0o5yPFJg0rl0WLe2VAcE+klI1/viCR+S5lU/I68buJK+bsLVqlsNxAq0tJRk7plUWLeP3l3GSKaZLfdLaOiB9va98iyy+8hMY1V6Wcrkky1fxe/v81F+5UhKPk0+2Jd9nna98BcaNapPuvn7p7m2+39tvOL4jX+wRdjUC5jo3dPC7LdcEzAP23VOm7zytenJwwOxtwn+hbmkpSakk0t/Pv1Tl+c+DpxfPkzN/9wXp6e+RM/b4gmy3wfZ5Xr5pr9X+v+W6X/vU8VvKk8c91bQmef/Ck9/YVyoiA0S0vOmltdwi/QOV6m/w+cpXoK21RXr7B4R+mZ/75l+fIi+ueHHtBWds+la57dDb83sBTX6l5D/QlltK0pc893zlJrDjxdvLEwsfX3u9B496WKZN2i636zf7har/XiVS/d9avvIVSP55k6jz+8t83ZOrNfPv7ZPf3/GVXoCAGRAwX+sdmHyEPP3Dx2S4wG+fuUUOvmG/moHz3/st+di2nwxfwkm1QBJtNrtwzJBzzx23Ur2PgXQCfIQ8nZvFFB8ht1BMt4OPkKdzSzt19wt/lA//+D114/fNfFo2Gj057VrmFAJt5RaZMLZNXl7cfJ9uUjCZHv3mvV+R2X/8Qt1Ofo9jyvyay/gIeX7Wg6/ER8j97PkIuZ990a9MwHyNgJn8Jb4HZv0jPqqjLJ1tZVnED/HJ7e//zS4YI5Uh3obDbzCzvwWbXjC67iITO9eXhw9/NvuLc4WqAAHT70EgYPrZEzDztb/0/vPlrNtPrbvo9R/9ley2Se23Ecn3lTXP1QiY+d/rd1y5s8xb/GTdhf929GJpK/Nx8jzuCAEzD+Whr0HA9LMnYPrZF/3KBMxhAiY/hbz2Ef/70vly5u0ny+LuhXLULifJe1+3d9H/HijE6x8qoiUvnICZ/e375dM3yX/cdEDNhe485FHZfNzU7C/OFaoCE9ZrlVXdA035fXK8HwECpt8dIGDma3//i/fIPtftUXfRBw9/RiZ1bpDvi2nCqw1UBuSmeT+Wvy9/Ut4xZW/ZacNdmlAh/1/y2763o8xfOq/uwk8fvUjay3yftjzuCAEzD2UCpp/y0FcmYDbaHSnO6yFgisj1N98mp8+Zu/auTZk8SS6dc1L1h/QkX+v+9X32miFnnTxTOjtf+a+SzfQR8kcWPCTv/cFuNU/3QdsfKue++6LiPPEFfaUzvredJPF43a+x7ePksSP/UdBfUbFe9uKuRXLL338mneXR8t6p+0lHubNYv4CCvtqFqxbIrt9+nfQNvPKN7ffZ5iNy2QeuKuivppgvm4Dpd98ImPnbv+HSjWRF7/K1F95y/NZyx6cfyv+FNNkV+yp9MvXCcTW/6ndPfb98f9+fNJlE/r/c9/zgLfLYgkfqLjz/mCXS2tKW/wtqwisSMP1uOu/A9LMnYPrZF/3KBMzIO9hMAXO7yzeRpd1L6sSePXZF9Sdj85WdQPIvVNteOrnmY+TJR5iTjzLzlY/A+DFt0tdf4SfA58NdvcpQ3zoh+Q8myX844SsfAQJmPs5DXYWAma/9Xxc9Lu+8ate6iyb/oTD5D4Z8ZSdw3p/+V776p/+tu8BTRy2QztZR2V2YzfKLp/8/mXnTx2skOsuj5KmjF6CTkwABMyfoIS5DwPSzJ2D62Rf9ygTMyDvYTAHz1T7G/Mwxy6TcUv+TmiNpGR9CoLe0tPoT4FsH+JepvB8QAma+4r39PbLlxRPqLvqG9beT33zy3nxfTBNfjYDpd/MJmPnaX3bfN+SLd8yqu+hPP3qrTN/krfm+mCa72idv2E9+98wtdb9qfoBSPg/CV+76knz97nOqF9t4zBS545CHJImYfOUjQMDMx3moqxAw/ewJmH72Rb8yATPyDhIwRf5+7HJpKbVESjIeIrDeqFZpKZVk6crekOOcMRQgYBpiBqzqr/TLFheOrTv5po3/TW782G8DNnDEQoCAaaGYbgcBM51b2qlfz/+lfPrGD9eN8z2P04qGz/3w0e/JibceVTcw/5il0trSGr6Ik6kFSuU+aS33S28P3/cyNWLKQQJmSjiDMQKmAWLKFQTMlHCMCQEz8iFopoB5/K8Olx89fnWNWElK8uxxKyIVGQ8VIGCGStmfI2Damw63cajvzfWrg+6S7SftNNwof91IgIBpBJliDQEzBVrEyLKepTLtso3rNjxz7DIpl/iUSQRt0OhbvvN6eWH5c2vPnrn7HDlil+OCZjmUXqAiFXnb93aQZ5b+be2SWw+6W6ZN2iH9UiZVAgRMFZfpYQKmKadqGQFTxcXhdQQImJGPQzMFzOQ3OTO+u508u+yZtWr3HPqkbLLeppGKjIcKEDBDpezPETDtTYfbmPwzZ9ZvPidX/eXbsl77WPnev18v/zblbcON8dcNBQiYhpjKVQRMJVjk8av/8h35/G+OqdvyiwP/KDtusHPkdsZDBJb3Lpa+liUyurSxtLfwTsAQs9gzyUfHk4+QD/567riVsauZDxQgYAZCZXCMgJkBauBKAmYgFMfqBAiYkQ9FMwXMNVTl1n5pK4t0dfOOhMjHRz1OwFSTmQ0QMM0o1YvWH9suK7v7paunXz3LQJwAATPOL2aagBmjp5+99P7z5azbT60bTL5lRfKtK/jKXqCt3CITxrbJy4u7s78YV6gK7HHlLvLU4ifqNJ4+epG0l4nIeTwmBMw8lIe+BgHTz56A6Wdf9CsTMCPvYDMGzFEdZelsK8ui5T2ReoxrBQiYWjG78wRMO0vtJgKmVszuPAHTzlK7iYCpFYs7f8l9X5cv3XFa3ZKf7n+rTJ/CD/GJ0w2bJmCGOVmeOvCn/y6/f/bXdSv5/vaWyq+9i4CZn/XgKxEw/ewJmH72Rb8yATPyDhIwIwEZVwkQMFVcpocJmKacqmUETBWX6WECpimnahkBU8UVfXjugxfL6bedVLfn55+4Q9644a7R+1kwvAABc3gj6xP/WPG8vPnb29Ss3XvrD8nlH/yB9aXY9yoCBEy/R4OA6WdPwPSzL/qVCZiRd5CAGQnIuEqAgKniMj1MwDTlVC0jYKq4TA8TME05VcsImCqu6MMX//lr8v/+4f+p2/OT/W/he+9G64YtIGCGOVmf+ueql+Ws20+RF1c9L4fueKx8cKv9rC/BvtcQIGD6PR4ETD97AqaffdGvTMCMvIMEzEhAxlUCBEwVl+lhAqYpp2oZAVPFZXqYgGnKqVpGwFRxRR++/dnfyCd+uk/dHn5YYTRt8AICZjCV+cHO9rKM7ijLwmV8eyhz3GEWEjDzFv/X9QiYfvYETD/7ol+ZgBl5BwmYkYCMqwQImCou08METFNO1TICporL5HDfQG815tz5/O0ytn2c/Hjr/6HzAAAgAElEQVT/X8oOG7zRZDdLwgQImGFOVqcqUpHXX7KhrOr7109f3nL81nLHpx+yugR7hhEgYPo9IgRMP3sCpp89AdPPnoDpZ1/0KxMwI+8gATMSkHGVAAFTxWV6mIBpyqlaRsBUcZkcft1FE6VnoPYnAd83c55sNHpjk/0sGV6AgDm8kfWJJGLe8reb5aGFd8lbJ+8lb910D+tLsO81BAiYfo9HEjBHdbTIomW9fi+iSa9MwPS78QRMP3sCpp990a9MwIy8gwTMSEDGgwX6K/3y5OIHpCID8vpxO0truS14loPxAgTMeMO0GwiYaeXSzS3tXiLbXb5J3fDHt/u0fO09l6ZbypRagICpJose+OIds+Sy+76xds+X33WBfGqHmdF7WRAmQMAMc7I+tc+175D7X7q3urYkJbn/sL/JBqM2tL4M+15FgIDp92gQMP3sCZh+9kW/MgEz8g4SMCMBGQ8SeH75szL9O2+oOfvrT94r266/XdA8h9IL9A30ybuufrPMW/xkdcn7X/fvMnefa9MvZFItQMBUk0UNLFj1T3njFVvU7fjA6/aVK/b5YdRuhsMFCJjhVhYnn1nyN3nr97evW/XkUS/L6NYxFpdgxzACBMz8H5HZf/yCfPPer9Rd+Lnj/vWtFPJ/Vc1zxUqlIgt7npcB6ZX12zaXcku5eX7xDfArJWD63QQCpp990a9MwIy8gwTMSEDGgwS2vXSyLO9dVnO2pdQifz92edA8h9ILvP37O8nfljxVs+AzOx0pZ7/z6+mXMqkSIGCquEwOb3rB6Lo9N33897LLRm822c+S4QUImMMbWZ649P7z5azbT61b+bOP/lresskMy0ux61UECJj5PxpJtE/i/eCvvx71TxnVWv+/A/m/wpF7xWU9S2XaZbXfluWWA/8k222w48j9RTfYr4yA6XdDCJh+9kW/MgEz8g4SMCMBGQ8SGComJIP8F/IgvtSHkv8yvtmFQ7/zBvvUrOrBzs4+6ektyUA/70xQ46UceGbp3+Rt39tBku8JmHydstsZcvz0WSm3MZZGgICZRi39zJm3/7dcfv836xZ8999/LHtt+cH0i5kMFiBgBlOZHXy1gPnUUQuks3WU2XVYVC8w1H8g5/f2+T4pBMx8vde9GgHTz77oVyZgRt5BAmYkIONBAltdvL5093fVnSWiBfFFHSIeR/FFDf910ePyzqt2Xbtjm4nbyu8Ovi9qJ8M6gQ0mtMuSZX3S2z+gG+R0tAABM5pQteCoX3xabnzyx3Uz57zzfDlkpyNUuzicToCAmc4tZupt39tR5i+dV7fi6WMWSXtLR8xqZocReLXfXz577AoplUr45SBAwMwB+VUuQcD0sy/6lQmYkXeQgBkJyHiQwOCQkwzd8LHfyJs33i1onkPpBQ6+YT/57TO31Cw4c/c5csQux6VfymSQwFC/uZ8144vyubd8PmieQ/ECG07okMXLegmY8ZTqDQRMNVnUwH//+ji58pG5dTsuef/3Zd/XfzRqN8NhAgTMMCfLU8f/6nD50eNX16189rgV1R/ow1d2AskPy0t+aN7gL96ckJ35upuXdS+VXz7zEym3tMr7pn6Y73WcD/vaqxAwcwYfQZcjYEbeTAJmJCDjQQKPLfiLvOcH02vO/nj/X8qMKbsHzXMoTuCkXx8t1zzy3eqSM3f/shyxy+fiFjI9rEBvf49sefGEunO8C3NYOtMDBExTzqBlXf2r5OCffUjuev4O2XbS9vKjj/xCJnauHzTLofQCj/7zYdnrmn+rW/DoES/IuI7x6RczGSxAwAymMjvY1bdKtr5kUs2+L+3xVZn5xqPNrsGioQWS76+efIx83S/+g0k+T8udz98uH73+fTUXu/Wgu2XapB3yeQFcRQiYPARpBQiYaeVWzxEwIwEZDxKYetF46RvorTvLf6UN4jM5NH5Mm/T1V2RFV5/JPpa8tkD/QL9scdHYukNv3mQ3ueGjv4EvJwECZk7Qqy+TfM/RzS6o/767849ZIq0tbfm+mCa82uB3RG07aTv59UH3NqGEzy+ZgOnjPlAZkIcX3CPL+xbJDhN3k/Ed9f/x0OeVjfyrrupbKTc+9UPpHlglH9zyANlg1IYj/xfdAL/CoT7h01Zul78dvbgBXl1zvAQCZnPc5yx+lQTMSFUCZiQg40ECfB/GIKZMDxEwM+WtW9430CdTLxpX9+e332An+dWBd+X7Ypr4agTMfG/+EwsflXddXf+T3i96/3flQ68/IN8X02RXe+ClP8ve19Z/quHhw56ViaN4B2wejwMBMw/loa/R2V6W0R1lWbisx+9FNOmVx3S2Smu5JEtW1L9RoUlJMv9l8+9VmRMPewEC5rBEHHgVAQJm5KNBwIwEZDxIgP+hDWLK7NDCVQvkl/Ovl87W0fKBLffnJ3NmJv2vxUN9rC35q1PHvU7+cMhfcngFXCIRIGDm+xzc9sytctAN+9ZdNPkJ8MlPgucrO4H/uvVIue7RK+sucP5el8vHph2c3YXZvFaAgOn3MBAw/ewJmPnbJ/+BPPkP5et+Jd8qJPmWIXzlI0DAzMd5JF6FgBl5VwmYkYCMBwnwEfIgpkwO/XzeDXL4zQfW7E4CWhLS+MpO4NW+B+aW47aWOw55KLsLs7lGgICZ7wPxh2d/Jwf89IN1Fz15t/+RE6aflu+LabKrHXLj/nLr/P+r+1Wf+raz5Lg3ndxkGj6/XAKmj3tyVQKmnz0BM3/7eYuflHdcuXPNhe+bOU82Gr1x/i+mSa9IwGzSG2/wyyZgRiISMCMBGQ8SSP6lKvmXq3W/5rz7Qjl4+/8ImudQeoGh3v06oXOi/OXw59IvZXJYgeR7cm1+4Xp159644a7y80/cMew8B2wECJg2jqFb7n3hLtnvx++qO37628+Wo3b9r9A1nEshcMKtn5VrH/1+3eQF7/u2fOQNn0ixkRGtAAFTK2Z3noBpZ6ndRMDUitmcT96BOX/Fo9IiLTJ1ve2kpdRis5gtQQIEzCAmDg0hQMCMfCwImJGAjAcJbH3xJEl+Mu26XyUpybPHrQia51A6gUqlIptdWP8DNZJt/ACldKahUz393fK6iyfWHd96whvktk/dH7qGc5ECBMxIQOX4vf+4S/b7UX3A/OLuX5HDdzlWuY3jGoFv3DNHvnznmXUjP97/lzJjSv33xtTs5myYAAEzzCmLUwTMLFTDdhIww5yyODVudJsMVCqyfBU/oDML39faScDMW3zkXI+AGXkvCZiRgIwHCfA9MIOYMjk0lD3fhzET6rqlQ9kn74RK3hHFVz4CBMx8nNdcJfmJtNtcskHdRe885FHZfNzUfF9Mk13t1d79ev9hf5MNR23UZBo+v1wCpo97clUCpp89AdPPnoDpZ0/A9LMv+pUJmJF3kIAZCch4kEDyLsDk3YCDv3gXYBBf1KGH//mAvP+at9bsSL7Jd/LNvvnKTqBvoFeS7/06+It3YGZnPtRmAma+3snVfvjo9+TEW49ae+HPvfnzMuutX8z/hTTZFRd1LZQdv7VZ3a/6mWOWSbml3GQaPr9cAqaPe3LVpb3/lP7SShnbMkVaW1r9XkgTXpmA6XfTCZh+9gRMP/uiX5mAGXkHCZiRgIwHCfAOzCCmTA4lP4F8pys2X7t7bPs4efjwZ/kNfiba/1r6au9E22LclvLHQx7J+OqsXyNAwMz/WfjKXV+Sr999ztoL//s2+8ulH6j/6dj5v7KRfcXP/XKmXP/ENXW/yHPfdZEctMOhI/sX3yC/OgJm/jeiv9Iv21y8gfQMdK+9+Pf3/Ym8e+r7838xTXpFAqbfjSdg+tkTMP3si35lAmbkHSRgRgIyHiRAwAxiyuTQVhevL939XTW73zrlHfKj/X+RyfVY+opA8i9VW1w4to6DH+KT7xNCwMzXe1nPUpl2Wf1PQf3dwffJNhO3zffFNNnVPn3jR+TX8+v/uZ68+zV5Fyxf2QsQMLM3HnyFM247Wa548KK6C/MJn/zuxeiOsrSWS7J0Jd+HMT/1V65EwMxb/F/XI2D62Rf9ygTMyDvYjAGzs72l+r1yFi/vjdRjPFSAgBkqZXuOH+Jj66nd9v4fvlUefvmBmrFbD7pHpk3aXruK8ykFCJgp4VKO3f3CH+XDP35P3fQX3j5bjtz1P1NuZSxE4Et3nCaX3Pf1uqNX7XeD7LnFXiErOBMpQMCMBEwxvseVu8hTi5+om3z6mEXS3tKRYiMjGoEDfvJB+cNzv6uObDxmitz1mUeltaVNs4KzEQIEzAi8yFECZiRgE48TMCNvfrMFzE/f+GH59fxfVtXGtK0n9x/2tIxuHfqnNEfSMr6OwNSLxknfQP1/meW/kGf/mAwVj5PfXM4/Zkn2F2/yK/z3b46TK/8yt0bhocP+LuuPmtTkMvn98gmY+VknV/rLPx+U910zo+6is/f8hnx6x8PzfTFNdrXkJ5AnP4l88NcPP3yT7L5Z/U+GbzKeXH65BMxcmGsu8rGffED++NxtdRd+9rgVUpJS/i+oia540q+Plmse+W7Nr3jTsZvLnz7zeBMp+P5SCZh+/gRMP/uiX5mAGXkHmylgnvH7k+WKB2o/ZkLIiXyAAsd5B2YgVAbHzvnjGXLBvefWbOZfaDOAHrRyoDIgm1+4Xt2F+Ph+9vb/f3t3Hm81cf9//HPvZRXZxKpfXLgiiqKC2oK4ISpfcaMuFdQqiyggqLWotZZWW2lL1br8rBZwQxFX8OuOW3FDBaqtFhcERQERq1ZlR0Au9/eYA0Nzs5yTOZmc3Jy8zj8KZGaS5+Qkk/eZJM4WCDBL6/3G5zPk5Ee8s/2uPPRPMmy/i0q7MhlrbegzZ8rUjx/1bPUfD79RBu07LGMayWwuAWbp3Y96sKvM/fp9T8PqR1pmAsbbH0Fj+8/OXy0VFYTH8epvqp0AsxTK/m0QYCZnn/aWCTAj9mCWAsygE+3i81dJZUVlREmK5xMgwExu/+gwfltRL5Rxfg7ZqadMPunp5FYqAy1/V7Mm92IB92eXltUysz8v8SnVLkCAWSrpTe18suwjOezeLp5Gbzn6Ljl5j9NKuzIZa+3n04bKlLnelyXdfPQEOWWP0zOmkczmEmCW3v3I+38o8779wCfAXMHLCmPujp1uaSa1UutphburYoZ3VE+AWTprd0sEmMnZp71lAsyIPUiAKbJoBIOciLtRweIEmAWJYlmAZ2DGwhqq0u9r1kv1uFaeZatb7CavD3g3VB0sFF2AADO6oUkNPAPTRMvusmc+8WN5+dNpnkov7fobGXngKLuNUZuvAAFm6XeMnvcdIB8tnesTYDIDM+7euPf9O+WXL11Yp5lj2veRO497KO6mqX+zAAFmcrsCAWZy9mlvmQAzYg8SYBJgRtyFQhUnwAzFZH0hAkzrpEYVthvXUjbU1H1Z2PhjJkmfDj8xqoeFixcgwCzerpiSc7+ZI0c98CNP0WuOuFnO2vucYqqkTEiB0x8/QV5d/KJn6REHXCy/PvgPIWthsSgCBJhR9Iore/CkfWTR8k98AkwmJxQnalbqvjl3yeUvXSjqsTlD9rtAfneo9zm8ZjWytIkAAaaJlt1lCTDtemapNgLMiL1NgCny6YiVUlVZFVGS4vkECDCT2T8IMJNx162qZ2CqQb3zw8tMStMn6ra2cW/dKE/MnyzVLTvINT1vkZaNvTNiS7M22Wnl/+Y9ID/7mzeoPKPTILnuyLrPoM6OSmm2VL2BXL2J3P159rQZsu8P9ivNSmS8FQLM0u8A3e/ZSxavWORp+L1zP5PWTbYp/QplsMVmTRpIg6oKWb667g+2GaQo+SYTYJacfEuDBJjJ2ae9ZQLMiD2YpQBzp782ExXouD+8qTDiThSiOAFmCKSYFvGzb1jVSBYOXxZTi1SrBNbVrJX247wXT+1a7CozBnhfOICaXYFuEzvKkpWL61Q6b9iXsnXD5nYborY6As8teEoGT+3nUTm783nyhx43oBWjQNAb4N8/d4m0atI6xpapWgtsqF0rlY3WSu265vwwXqLdIijA/Oeg+bLD1m1LtBbZbeab776WsW//WdbVrJFB+1wgHVp3zC5Gibd89ldvyQ1vjJYGVQ3lsgNHS8dt9irxGmS7OQLMbPd/lK0nwIyiJyJZCjCDQjSegRlxJwpRnAAzBFIMizADMwbUkFWu2bBadh//A8/SO7doJ7MGeF84ELJaFgshsGr9Sul42/aeJQd3Hi6/73F9iBpYpFiBRz58UC58frCn+OmdBsr1R44rtlrKhRC49V83yejXfuVZ8tFTpkm3tgeHqIFFogj0fuggee8/s7dUMa73PfLj3U+NUiVlQwgcNKmTfLp8oWdJxvYh8CIuMnPJq3Lqo73r1HLBDy+VXx00OmLNFC8kcO/7E+SXL11QZzH17FH1DFI+8QqoZ9wfem9n+Wzlp7mG1ONx1GNysvRp26ZpljbX+rYSYEYkJcCU3Ew0NSONT3wCBJjx2Raq2c++oqJCPjt/daGi/HsEgfUb18muY72znpiBGQE1ZNH/rPlK9ptQ7Vn6yHa9ZVKfR0PWwmLFCExb+IwMfMr7jNch+10ovzv0mmKqpExIgSc+fFiGPz/As/Tr/d+V6pa7hayFxYoRCHp0Ao8oKkbTrExQgPnxed9IkwZcZJtpmi3NW8jNvGwuzXWVTU2zuva5YydZuvbbOoV+c8gfZfj+I80qSvHSBJjROo8AM5pfpmZgBp1oVZCjAh0+8Qlwoo3PNl/NzMBMxl21qp7BqI457s/hu/SS+3/8RHIrloGW1XNH1fNH3Z8Jx02W3u1PyIBAcps4Y8kr0vfRYz0r8LMfXSa/7P675FYsAy1fMf0SmfCOd5Yrs3Li7/xeD3aTD75+z9PQzAFzZJcW3h9T4l+j7LQQdAs5j06Ifx8IGtsvPn+VVFZUxr8CGW6B66pkOj9ofFlVUSWfnr8ymZVKoFUCzGjoBJjR/LIVYAY8A5MTbcSdKERxTrQhkGJYJOhEq5pacsGaGFqkSi2wYeMGaTe2hQekXYv2MmOA90IXOXsCa75fLbvf6r19n7cx2zMOqukv/7hWrpnlDSqZ/Rq/ff8nT5YXFz3naUgFxypA5hOfwNEPdhf1DFL3Rz0uRD02hE98AkEB5tuDP5HtttohvoapWRjbJ7cT7H3HjrJs7dI6K9C+1e7y6ln/fYxFcmtXvi0HTU5oVNlYFoyo2x/lqyBCgBmtdwkwo/llKsDseOv2sup7768jzMCMuBOFKM4gJwRSDIvUbKyRXcb6v7SEADMGcEeV6sH2ne/cxdMIz8CM113V/tWaL2X/Cbt6Gjqi3f/KvX0ej38FMtzCve/fKb986UKPQJ8OP5Hxx0zKsEz8m97vsePk9c9e9jQ0bL+L5MpD/xT/CmS4hac/flyGPHOGR4AfyOPfKYICzNnnLJJtm3p/yIp/jbLTQtDYnuuq+PeBletXyF63/U/ubh/1aVDZUOYN+0KaVPHYhLj1/fb7HZvvLG8MnBd30/WmfgLMaF1BgBnNL1MBprqlUM1Ic38IciLuRCGKE2CGQIphEW4hjwE1ZJXql3H1C7n7Q4AZEjDCYutr1smu47zPHz2nywgZfdh1EWqmaCGBed98IEc+8EPPYtf0vFnO2uecQsX59wgCfR87VmZ89oqnhrP2HizXHHFLhJopWkhAvczhwIl71llM3UKrAkw+8QoEBZjTz/yX7NZ6j3gbz3jtu41rI2trvuO6KsH9oEHD9VJbK1KzgXc5lKIbuLNtkzIBZrS9jQAzml+mAsygEI0HfUfciUIUJ8AMgRTDIpxoY0ANWeWXq/8tB9zlfXEGAWZIwAiLBc3A5PmjEVBDFn3io4dl+HPeF8lk8S2dIcmsLXbqo8fIzCXTvQFmp8FyzZEEmNagfSq68PnB8siHD3r+Zc6Qz6Vl41ZxNp35uoMCzJfPfEt2b103VM48lmUAZmBaBjWsTv1Q/shH90hlRZX8ZI8B0ryR97FFhlWyeAGBoOuqrL0clQAz2leFADOaHwGmiMwb9qVs3dD/NtuIvBTfLECAmdyugH0y9guWz5dDJ3X2NE6AGX9/rN3wnew2vo2noYu7/Vou6fbr+Fcgwy38beHTMuipUz0Cg/YZJn/seWOGZeLfdPXyJPUSJffn7M7nyR963BD/CmS4hbOn9pXnF0z1CLx7zmLZpqn3WJRhKuubHhRgzuw/R3ZpyQuUrIM7KuQlPnHq5q/b77EVj53ygnRte1ByK5WBloOegZm1GfcEmNF2dgLMaH4EmCLy4dCvpFkj7xtrI9JSPMQgh9v3491NmIEZr2++2oNmARJgxt8nQbeQD93/Z/LbQ66OfwUy3MKE2ePkilcv8Qgc076PqLdh84lPICjAHNxluPz+sOvja5iaZeizP5Wp8x/zSHww5N/SonFLhGIUCAown+73mnTZ7oAYW6ZqZmAmtw/42WdtFmAS+szA3KROgBlt7yPAjOZHgCki75zzqbRpum1ESYrnE2AWYDL7BwFmMu6q1a/WfCH7T2jvWQECzPj75L3/zJbeD3lnIfAG+PjtR73yc5n47m2ehg7e8XCZcvIz8a9AhlvgGZjJdf4h9+wrC1d87FmBV858Wzq07pjcimWg5aAAc9ppb8heP9gnAwLJbSIzMOufPRND4u2ToHcLVFVUyafne18UHO/aJFc7AWY0ewLMaH4EmCrAPPdTadOEADPirpS3OL/SxqkbXHfQTDRVgkFOvH3yxarP5Yd3dyDAjJfZt/YPv/1Ajrjf+yKZXVt2kNf6v5PAGmWnyUteHC4Pzpno2eCDduwhD5/8bHYgEtjSoGdg9tuzv9zY69YE1ig7TQaFaPf1eUJ6tuuVHYgEtjTI/tFTpkm3tgcnsEbZaTJobL/wvGXSsAEvlYlzT2BiSJy6wXUzMWSTDQFmtP2PADOaHwGmuoV82FfSrCG3kEfclYoKMAnR4lQX4S3k8frmq33Bsvly6L08AzOJHvi+Zr1Uj/O+OOMnHc+Qv/zvnUmsUmba/MWLI+T+OXcTYCbQ4wSYCaBvbjIoRHvgxCelx85HJbdiGWg5yP6uE6bI0dXHZ0AguU0MCtE+HbFSqiqrkluxDLRMgJlcJ/vZN63aSuYP/zq5lSpxywSY0cAJMKP5EWCKyFtnfyzbN/ufiJIUzyfAiTaZ/eP7Deulerz/G1AJj+Ptk0XLP5GDJ3lvX+MW8njdVe0ffTtXet7vffZZdYvd5PUB78a/AhlugRmYyXV+UIB5eqeBcv2R45JbsQy0HBSiTTzh/6RX9bEZEEhuE4PsHzpxqhy68xHJrVgGWibATK6Tua5Kxn7Dxg3Sbqz/296zdF1FgBlt/yPAjOZHgCkiM/q/J+1aep9VF5GW4g4BTrTJ7A6caJNxV60uXrFI1IWV+0OAGX+fqDcxqxeaYB+/tbuFkdOGyeS5kzwNcwt5/H3BDMz4jYNaCArR1Iur1Aus+MQnQIAZn22hmoPG9guGL5VGVY0LFeffIwhwXRUBL0LRdTVrpf24bXxrIMCMAJuxogSYETv882++i1hDeooHHexn9p8ju7SsTs+GpHBNeQZmMp3GiTYZd9Xqv1cvkR/dtTshWgJd8P7X78jRD3b3tNyuxa4yY8D7CaxRdpokwEyurwkwk7MPCtFuOfouOXmP05JbsQy0HHgL+fFT5OhduYU8zl0gaGz/yXnfSuMGTeJsOvN1E2AmswsEPaJIrQ0BZjJ9ksZWCTAj9hoBJjMwI+5CoYoHvqlwxCqprKwMVQcLmQvwEh9zM1sluIXclqR5Pf/84u/y44e9tw4y+9Xc0rQEAaapmL3lCTDtWZrWFBSiXXfEWDlj70Gm1bG8gUCQ/a2975UTdj/FoCYWNRUgwDQVs7c8AaY9S5OauLNtkxa3kJvsNd5lCTCj+XELuYi8cubb0qF1x4iSFM8nwAzMZPaPVetWSsfbt/dtPEu/FCahP//beXL4/ft7miZEi783Jn8wSUa+MAz7+Kk9LRBgJoC+uUkCzOTsg0K03x16jQzZ78LkViwDLQfZ33z0BDllj9MzIJDcJgaN7T8c+pU0a8TLUePsGQLMOHWD62YGJgGmjT2PADOiIjMwRZ7p97p03s4bNESkpbhDIPBB38NXSlUVbyqMa2dZuXaF7HnHDgSYcQHnqffFRc9L/ydPIkRLwP6B9++WS18agX0C9gSYCaATYCaHvrnloBDtF92ukJ93+1Xi61fOKxBkf1OvO+TUPX9azpue+LYFje3nDv1Cmjfyf9FJ4itdJitAgJlMR363YY10GL9t5q+rmIEZbf8jwIzmxwxMEXn05GnSbceDI0pSPJ8AAWYy+8c3a76WzhN2yfyJNgn9qfMfk6HPei+emIEZf2/c/c6t8uvpIwkw46f2tECAmQA6AWZy6AUCzMsOvFIu6np54utXzitAgJlc7waN7T8Y8m9p0bhlciuWgZYJMJPpZALMTe4EmNH2PwLMEH6PPD1drrh2Qm7J43t1l9GXDpYmTRrl/swMTJFHTv6bHLjjISEkWaRYgaAT7aLzVkiDBg2KrZZyBQQWL18k3Sd534StinELeby7zyPzHpQL/zaYEC1eZt/a//LmNXLN36/CPgF7AswE0Akwk0MvEGBe2u03MrLbqMTXr5xXgAAzud4NGtvPOedzadm0VXIrVuYt19bWyk5/bea7lYzt4+38dRvWSvvxvIWcADPafkaAWcDvzdlz5Ybxk2Xs1SOldcvmcsNtU3IlLh7alwBzsx0BZrQvYZjSQYOcBUOXSqNGjcNUwTJFCCxYNl8Ovbczg5wi7KIWeXju/XLRtHMJ0aJCFlH+xjfGyHVv/AH7IuyiFiHAjCpYfHmegVm8XdSSQSEaAWZU2cLlCTALG8W1RNDY/u/958pOLf3v/olrXbJUb01Njewyrjlj+wQ6/d+rlsiP7t498/YEmNF2PgLMAn4qsKzeaXs55bgeuSXdgSYzMJmBGe0rGK500CDno8H/ka228lrW1MMAACAASURBVP8VMVzNLJVP4J0v35Zjp/jPLuZX2nj3HQLMeH3z1U6AmZw9AWZy9gSYydkTYNY/e56BGX+fBI3tXzj9Tdlz273jX4GMtvD9+vVSfZv/DFfG9vHuFEEv6FStZsmeADPafkaAmcdv7dr1cuV1E6T7AZ22BJifLPpcRl19h4y5/Fxp366tfLNiXbQeSFHpbW9s4ru2T536gnTfmVvI4+zKIPuPB38hLVtym0lc9v9Y/IYc8/CmHy/cn69Hro2rWeoVkclz7pcRz3lvId+lRTt565x5GMUo8OdZf5RrZv7e0wL2MaJvrvrC54bIA3MmeRo6ZKce8njf5+NfgQy3cOKUo+X1z6Z7BM7o1F9u7n17hmXi3/QD7uwon65Y5GnolwddIb/o/uv4VyDDLQTZj+09Qfp14iU+ce4aQWP75/u9Kgfs2DXOpjNd94oVy6X9ndsztk9gL5j12Qw5YcqRmbdv04K7J6PsfgSYefR0gNm3T0/p2mXP3JLuADMKftrKVlxV4bvK0wdOl8OqD0vb5qRqfYPsl160VFq1IsCMqzNnLZwlB008yLf62t/WxtUs9YrIpNmTZMBjAzwW1a2qZcFFCzCKUWD0K6Plty//FvsYjYOqPvuxs+Xu2Xd7/rlndU95aeBLCaxRdpo8YuIR8vLClz0bPKjLILnrpLuyA5HAlu56066ycNlCT8tX9bxKrjz8ygTWKDtNBtnfc9I90r9L/+xAJLClQWP7mQNnSvfq7gmsUTaaXLZsmbS+qTVj+wS6+7VFr8lhd/tnBlxXJdAhKW2SADNPx4WZgbnu+40p7Xrz1W4ypsq30KtnzpSu7bqZV0iJ0AJB9mtH1YSugwXNBRYtWigd79vNtyD25p4mJSa/+5AMeNI7+6Ndy2qZd/7HJlWxrKHAmOl/kNGveQNM7A0hi1h86FPnyD3veAPMw9v1lOfOfKGIGikSVqD3fUfJK4u8AeaAzoPkthPuDFsNyxUh0PGvu8mi5d4A88pDr5JRPX5TRI0UCSsQZD/xhPvktM6nh62G5YoQCBrbzzvzY2nXrrqIGikSVoDrqrBSdpf7x6I35dD7/MP5LF1XNW5YaRc2Y7URYBbocJ6B+V+gnW/ZWjaKN7DN0jMrkjo+7HRLM6mVujP+KqRCPrtgdVKrlJl2/Z5RhH1put/Pvl3z9jJj4HulWYEMt+Jn36F5R3ll4NsZVinNpvvZ993hLPl/p95WmhXIaCs/f3ioTPniXs/WM8aJf4c4fOL+Mn+l99Eg2Mdvf/DEfWTRyk/Y7+On9rTgN7ZXC7Hfx98ZXFfFbxzUgt8Yp1IqZfEFq5JbqRK3zDMwo4ETYBbw4y3kdYEOnri31FZslIqKCqmtFZk5YE60PZDSoQVy9pWbA+TaCuxDy0Vf8KB7OklFxaYIuWJjpcwY+H70SqkhlMAme5Ha2lqpqMU+FJqlhdSLNSorK6SmZqM0ksby6sDZlmqmmnwCZ9zVRxZUzZfKCpGajbWytTSXFwa+CVoJBI6a2FVWyUqpqqyQjbUiu9Z0kAfOfrIELdPEYRO7yHpZJ1VVlbJxY63MGvABKCUSYGxfImifZvTYXj2kq5axfUk7Qo0vpWLz5JCNFTJzINe0peoAPbbfWLtRKmurMnddRYAZbU8jwAzh98jT0+WKayfkljy+V3cZfelgadKkUe7PWXoLuaZq2rhKmjSskqWr1ofQYxGbAls3bSCVFRWyYs33NqulrhACLZs1lA01tbJ67YYQS7OITYFtmjeSNetqZO16Hplg0zVMXT9o1ViWrfxevq/JzuNSwriUYpkdtmkiXy1dJxvVr4V8SiagzrHbtW4sX3zLi9pKhr65oYZVldKqeUP5z7LsvCCz1MZB7TVpVCVbNa6Sb1cyti91nzRr0kAaVFXI8tWM7Utt32Krhrlz7KrvGNuX2r711o1k7fc18t267I3tCTCj7W0EmNH8CDAj+lHcTIAA08zL5tIEmDY1zeoiwDTzsrk0AaZNTbO6CDDNvGwtTYBpS9K8HgJMczNbJQgwbUma10OAaW5mqwQBpi1J83oIMM3NKLFJgAAz4p7ADMyIgBQ3EiDANOKyujABplVOo8oIMI24rC5MgGmV06gyAkwjLmsLE2BaozSuiADTmMxaAQJMa5TGFRFgGpNZK0CAaY3SuCICTGMyCmwWIMCMuCsQYEYEpLiRAAGmEZfVhQkwrXIaVUaAacRldWECTKucRpURYBpxWVuYANMapXFFBJjGZNYKEGBaozSuiADTmMxaAQJMa5TGFRFgGpNRgADTzj5AgGnHkVrCCRBghnOKYykCzDhUw9VJgBnOKY6lCDDjUA1XJwFmOCfbSxFg2hYNXx8BZngr20sSYNoWDV8fAWZ4K9tLEmDaFg1fHwFmeCuWrCvADMyIewQBZkRAihsJEGAacVldmADTKqdRZQSYRlxWFybAtMppVBkBphGXtYUJMK1RGldEgGlMZq0AAaY1SuOKCDCNyawVIMC0RmlcEQGmMRkFNgsQYEbcFQgwIwJS3EiAANOIy+rCBJhWOY0qI8A04rK6MAGmVU6jyggwjbisLUyAaY3SuCICTGMyawUIMK1RGldEgGlMZq0AAaY1SuOKCDCNyShAgGlnHyDAtONILeEECDDDOcWxFAFmHKrh6iTADOcUx1IEmHGohquTADOck+2lCDBti4avjwAzvJXtJQkwbYuGr48AM7yV7SUJMG2Lhq+PADO8FUvWFWAGZsQ9ggAzIiDFjQQIMI24rC5MgGmV06gyAkwjLqsLE2Ba5TSqjADTiMvawgSY1iiNKyLANCazVoAA0xqlcUUEmMZk1goQYFqjNK6IANOYjAKbBQgwI+4KBJgRASluJECAacRldWECTKucRpURYBpxWV2YANMqp1FlBJhGXNYWJsC0RmlcEQGmMZm1AgSY1iiNKyLANCazVoAA0xqlcUUEmMZkFCDAtLMPEGDacaSWcAIEmOGc4liKADMO1XB1EmCGc4pjKQLMOFTD1UmAGc7J9lIEmLZFw9dHgBneyvaSBJi2RcPXR4AZ3sr2kgSYtkXD10eAGd6KJesKMAMz4h5BgBkRkOJGAgSYRlxWFybAtMppVBkBphGX1YUJMK1yGlVGgGnEZW1hAkxrlMYVEWAak1krQIBpjdK4IgJMYzJrBQgwrVEaV0SAaUxGgc0CBJgRdwUCzIiAFDcSIMA04rK6MAGmVU6jyggwjbisLkyAaZXTqDICTCMuawsTYFqjNK6IANOYzFoBAkxrlMYVEWAak1krQIBpjdK4IgJMYzIKEGDa2QcIMO04Uks4AQLMcE5xLEWAGYdquDoJMMM5xbEUAWYcquHqJMAM52R7KQJM26Lh6yPADG9le0kCTNui4esjwAxvZXtJAkzbouHrI8AMb8WSdQWYgRlxjyDAjAhIcSMBAkwjLqsLE2Ba5TSqjADTiMvqwgSYVjmNKiPANOKytjABpjVK44oIMI3JrBUgwLRGaVwRAaYxmbUCBJjWKI0rIsA0JqPAZgECzIi7AgFmRECKGwkQYBpxWV2YANMqp1FlBJhGXFYXJsC0ymlUGQGmEZe1hQkwrVEaV0SAaUxmrQABpjVK44oIMI3JrBUgwLRGaVwRAaYxGQUIMNkHEEAAAQQQQAABBBBAAAEEEEAAAQQQQKC+CzADs773EOuHAAIIIIAAAggggAACCCCAAAIIIIBAhgUIMDPc+Ww6AggggAACCCCAAAIIIIAAAggggAAC9V2AALO+9xDrVzYCnyz6XEZdfYeMufxcad+urfF2qfLDLrtePv/yG/n9ZYPllON6GNdBATsCN9w2JVfRxUP72qmwjGqJup/no7BVN/1nd4dbu3a9XHndBOl+QCeOSxZo35w9V24YP1nGXj1SWrdsbqHGbFaxdPlKGXH5jXLxef2ka5c9s4kQ01bHdQyNcoznOGSnszn+mDuamD3y9HSZ9dYcGX3pYGnSpFHBxqJ8JwpWnvIFTC1TvrmsPgIIbBYgwMzYrqAO9ldcO6HOVt990+WxDO6zeNLVF0zvfPDJFmMdNpp4uE/KDMyL+6Jqt6nTZm2poPNe7SMHA3FdvBW3lfZL+e3Hx/fqHmrAbbKf+625re9QPpVy7z+17fkcbe8xHJ/CiaqL3EEXXe35AUqfl/W5wuRiOFzL5buU84c9vZXn/PT43I9LcQWYcdVb33pJHSfvvH/qltVqu30bufXaS3I/wMZ1DDU5fzBO8u4xQceYoH3Lb1/m+OOv5TeeVEuq481hB+4b+kenQqGb+7tl8p2ob8eQYtZHOy9e8lXBsXohy2Lad5cpRRs21jOOOgpdC9g4D9ioI45tp876LUCAWb/7x+ra+Q1K1Ilx2qv/lKFn9bHalqosayddZ2igZ3zog3/fPj1lv707hJ6B6T5hZuWCyfZO6BesqJPlF199EyqMs70+aanPvb9pxx22a1Nw1mnU77277WK/Q2mxjms98znanr1NgBmuF9U5+Prxk6V1y61lzK+G5GZXqn4a9afbZenyVdKvT09msIajzC3ld15U++LYex6Xs087JrdMHDMws3A+9rtoV/uvChVsHz+cXW5y/shysBD0NdFhQNgxThb2ZYNDSt5FbZ3nCu23WQ901DFg/KQnZOWqNTL4jOPyTrApZGmj70vRho31tF1H0P5+271PSq/Dfmjth6ys7++2+y0r9RFgZqWnRQr+Yq4Hjif0Okj+dPN9ORk9k0EzOX+Rd/6bPsA3b7aVPPj4izKw3zHy9bfLxDnzTc307FC9Y+6CQs9QDDurKy3d5DcYVDYLP/tSTup9SJ0A0z1zRHu6/77THu1ymz/nw0W5/7pnQegZEvn6Q/2bbn/vPapzfaT7V/1yrGYF+fV3WtyD1tPvBOwO8t2zkt0zkp3/rmdv3vXQs7km1SyfMN8bdxs2ZoHG2TdB+7HztifnfurcJ/0uQJ3bX+g7b/Idcv86rOv+bt06T3DhXK/Hnnt9S//pOo7vdZBMnPxs7hEN7nVMW/8FhTv6WKTCHXewo47t1TttL8cd2T13O7jz2K3qU98LFV64Z/CrY8uIASd6biHXM4FU2fq+v8f5XXLWrUymPPmydN5rN9mqaeNcEKT6ZM136+SdDz7ecgu+yTHK7/iUldvOC80UM/1uu7/3Qcc498xEPXPWfTzS5xL3eqh9Qs9kLNW+Z9JOmKDGedGpj61hxxbuQECV//O4B3Oh/tJlK4saJ6ljzI1XXSA33Da5zqMsgs49Yc7bJmb1YVm1n6mx+/ABJ8q1Yx+QXww/vc7jitz7p9pv1djUOctW/d3OO25XZzZh0H6ttlntB6tXfycrV6/JnTOcY4H6YGJzHfJ9L9zHonx3QLivl/T5VT3mwnneVH+vjkln9ztWrrpx4pbHTxUy95uVHteddjZ9dV3KR3/U/ul+VJP7+KuP2+qHKz0uV/9191fQfpzvWOC2VMeZMaOGyKgxt9d5NIkeP6lzurs+Pf5R6+S8/q3vfVLoxyS/fVX11cjf/lX0eFqf6/71/vw6Y0e97X51qEcrqI9zHOp8bFrQd+uIQ/bPO+4v5tFtcezf1GlHgADTjmMqatEDuaCDpj5QH3tUd9/br5yDTn1w0TOy/Or2O/g5D/KqjvsemSbHHXVg2Tznyy980QN9d4D53Mtvyu677pgbYGp7dWJUg5gwMzCL6Q/1DM3hA0/MXTi7+7vQySoVO7lrJYNmYOpBjvr3h6e+Iqcef3juWUTKVAUM+tlz7j+/P2+BNG3SWJwBWKHvjTpBq8GOvmAtdNFdH5yDZmDqZxy6/925jWr9nc96dRu6jwHu7TX5Dql21Ud9Z5wzNXUw5Bz8Oi+4nf+vy6mLNufASW9rGvtPmeRzzBdgumdXBc0+cB4v2m6/bZ0A022mg9OsPzNWB5gjh/SVG2+fIuq/Dzz+opxx4pG5Pzv3Of0MTBXo6HBHBZPK/aMFS6R3z66e45U+PmVloO4+9gYdS/J9t53PGnXOznf/COLcp1u3au65UHIff5yhnL5w1esR5rl3SZ8HlMUzL8wKDFrdAabJ2MIkwDQZJ7nP9+5zrbN/P//y69wzxYPGu0n7F9O+2t5X//5ubvzuPs+6909l9cqs2dJt/z09+7LTrWnjxnWO7e6xqns/KefZamEDTG2mr4/c5dzXS377qTOIc4/N85nr45a660udy9M2w1ZZqfPdmaf0yn0FnOc+9We/Mbr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