diff --git a/assignment/assignment_programming.ipynb b/assignment/assignment_programming.ipynb
index 87d73f2d..20ba9ebb 100644
--- a/assignment/assignment_programming.ipynb
+++ b/assignment/assignment_programming.ipynb
@@ -26,6 +26,277 @@
         "4. Rank the jobs you picked from best to worst, and briefly explain why you did so.\n"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "source": [],
+      "metadata": {
+        "id": "MEa5FpNrDAbq"
+      },
+      "id": "MEa5FpNrDAbq"
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import pandas as pd\n",
+        "\n",
+        "jobs = [\n",
+        "    \"Software Developer\",\n",
+        "    \"Web Developer\",\n",
+        "    \"Computer Programmer\",\n",
+        "    \"Database Administrator\",\n",
+        "    \"Computer Network Architect\",\n",
+        "    \"Computer Systems Analyst\",\n",
+        "    \"Computer and Information Research Scientist\"\n",
+        "]\n",
+        "\n",
+        "df = pd.DataFrame(jobs, columns=[\"Job Title\"])\n",
+        "df"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 268
+        },
+        "id": "X6faQRDd6U20",
+        "outputId": "8b2ac9c0-26f1-402f-ef93-e9944981cf9a"
+      },
+      "id": "X6faQRDd6U20",
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                                     Job Title\n",
+              "0                           Software Developer\n",
+              "1                                Web Developer\n",
+              "2                          Computer Programmer\n",
+              "3                       Database Administrator\n",
+              "4                   Computer Network Architect\n",
+              "5                     Computer Systems Analyst\n",
+              "6  Computer and Information Research Scientist"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-3d92acc9-12b3-4900-9315-8a50063eb9d8\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Job Title</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>Software Developer</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>Web Developer</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>Computer Programmer</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>Database Administrator</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>Computer Network Architect</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>Computer Systems Analyst</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>Computer and Information Research Scientist</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3d92acc9-12b3-4900-9315-8a50063eb9d8')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-3d92acc9-12b3-4900-9315-8a50063eb9d8 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-3d92acc9-12b3-4900-9315-8a50063eb9d8');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "  <div id=\"id_58303ba6-9e4f-43d3-bb17-22e615e64b70\">\n",
+              "    <style>\n",
+              "      .colab-df-generate {\n",
+              "        background-color: #E8F0FE;\n",
+              "        border: none;\n",
+              "        border-radius: 50%;\n",
+              "        cursor: pointer;\n",
+              "        display: none;\n",
+              "        fill: #1967D2;\n",
+              "        height: 32px;\n",
+              "        padding: 0 0 0 0;\n",
+              "        width: 32px;\n",
+              "      }\n",
+              "\n",
+              "      .colab-df-generate:hover {\n",
+              "        background-color: #E2EBFA;\n",
+              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "        fill: #174EA6;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate {\n",
+              "        background-color: #3B4455;\n",
+              "        fill: #D2E3FC;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate:hover {\n",
+              "        background-color: #434B5C;\n",
+              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "        fill: #FFFFFF;\n",
+              "      }\n",
+              "    </style>\n",
+              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+              "            title=\"Generate code using this dataframe.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "    <script>\n",
+              "      (() => {\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#id_58303ba6-9e4f-43d3-bb17-22e615e64b70 button.colab-df-generate');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      buttonEl.onclick = () => {\n",
+              "        google.colab.notebook.generateWithVariable('df');\n",
+              "      }\n",
+              "      })();\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "df",
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 7,\n  \"fields\": [\n    {\n      \"column\": \"Job Title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"Software Developer\",\n          \"Web Developer\",\n          \"Computer Systems Analyst\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
+          },
+          "metadata": {},
+          "execution_count": 2
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "1. Software Developer – Good pay, lots of opportunities, and flexibility in what kind of work you can do.\n",
+        "2. Web Developer – Creative work with flexible environments, especially with remote options.\n",
+        "3. Computer Programmer – Focused on writing code, but with fewer opportunities than other development roles.\n",
+        "4. Database Administrator – Important role handling data, with steady demand.\n",
+        "5. Computer Network Architect – High responsibility role designing and managing networks.\n",
+        "6. Computer Systems Analyst – More business-focused compared to other technical roles.\n",
+        "7. Computer and Information Research Scientist – Very interesting work, but usually requires more schooling."
+      ],
+      "metadata": {
+        "id": "ag8x2lSNDCqO"
+      },
+      "id": "ag8x2lSNDCqO"
+    },
     {
       "cell_type": "markdown",
       "id": "7e9d65ad-3740-43d3-a944-b3653fbeb80c",
@@ -36,6 +307,14 @@
         "Depends on student opinions."
       ]
     },
+    {
+      "cell_type": "markdown",
+      "source": [],
+      "metadata": {
+        "id": "hmiYhiM2DB0k"
+      },
+      "id": "hmiYhiM2DB0k"
+    },
     {
       "cell_type": "markdown",
       "id": "7cfa75b2-aaef-4368-a043-93437887879c",
@@ -67,15 +346,100 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 3,
       "id": "9c05ee86-06dc-4ae9-896d-0cb70c4d6c3d",
       "metadata": {
-        "id": "9c05ee86-06dc-4ae9-896d-0cb70c4d6c3d"
+        "id": "9c05ee86-06dc-4ae9-896d-0cb70c4d6c3d",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "outputId": "1e8722d5-0651-49fc-afcc-17be1b72b96f"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjUAAAHHCAYAAABHp6kXAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQAATz5JREFUeJzt3XlclNX+B/DPMMqACAMqCCQCoqmIxnW9WuYShubavWVpLpRZrjfTFpcKbRFNM8qMUgvNpTLbNA1zicyl7Kfi1VALRS3FXQdEAWHO7w/ujA4zwzwDsz0Pn/frNS/jmWeeOTyS8+Gc7zlHJYQQICIiIpI5L3c3gIiIiMgRGGqIiIhIERhqiIiISBEYaoiIiEgRGGqIiIhIERhqiIiISBEYaoiIiEgRGGqIiIhIERhqiIiISBEYaoiqoHv37ujevbu7m+GRZs6cCZVK5e5mKJpKpcLMmTPtfl1mZiZUKhUyMzMd3iZ3O3HiBFQqFZYtW+buppAbMdSQwy1btgwqlQo+Pj44ffq02fPdu3dHXFxcla79/vvvy+ofraioKPTr18/dzfBISUlJUKlUFh8+Pj7ubp7bbdy4sUrBxREM/w9bekydOtUtbTJYvXo1UlNT3doG8ly13N0AUq7i4mLMmTMHCxcudNg133//fTRo0ABJSUkOuya5j0ajwdKlS82Oq9VqN7TGs2zcuBGLFi2yGGxu3LiBWrWc/8/3q6++iujoaJNjVf2FxFFWr16NQ4cOYdKkSSbHIyMjcePGDdSuXds9DSOPwFBDThMfH48lS5Zg2rRpCA8Pd3dzrBJCoKioCL6+vu5uSo1Tq1YtDBs2zN3NkB1X9WT16dMH7du3d8l7VRd7+Ajg8BM50fTp01FWVoY5c+bYPDc9PR09e/ZESEgINBoNYmNjkZaWZnJOVFQUfv/9d/z000/GrnBDXYu1Og5DN/qJEydMrtOvXz9s2rQJ7du3h6+vLz788EPJ7XC00tJSvPbaa4iJiYFGo0FUVBSmT5+O4uJik/P0ej1mzpyJ8PBw1KlTBz169EB2djaioqIk9VzNnz8fXbp0Qf369eHr64t27dph7dq1ZuepVCpMmDAB33zzDeLi4qDRaNCqVStkZGSYnbtjxw506NABPj4+iImJMd5HRxFCoEePHggODsb58+eNx0tKStC6dWvExMSgsLAQwK2fgSNHjmDw4MEICAhA/fr18cwzz6CoqMjkulLvueFnZceOHejYsSN8fHzQpEkTfPLJJ2ZtvXr1KiZNmoSIiAhoNBo0bdoUc+fOhV6vN55jqPuYP38+Fi9ebHz/Dh064LfffjOel5SUhEWLFgGAydCPQcWampMnT2LcuHFo3rw5fH19Ub9+fTz88MMmP/eOZq2up+LPo+H/wZ07d2Ly5MkIDg6Gn58fHnzwQVy4cMHs9d9//z26desGf39/BAQEoEOHDli9ejWA8qHrDRs24OTJk8Z7EhUVBcB6Tc22bdvQtWtX+Pn5ITAwEAMHDsThw4dNzjH87OTk5CApKQmBgYHQarV4/PHHcf36dZNzN2/ejHvuuQeBgYGoW7cumjdvjunTp9t/A8kp2FNDThMdHY0RI0ZgyZIlmDp1aqW9NWlpaWjVqhUGDBiAWrVqYf369Rg3bhz0ej3Gjx8PAEhNTcXEiRNRt25dzJgxAwDQsGHDKrXt6NGjGDJkCJ5++mmMHj0azZs3l9wOR3vyySexfPlyPPTQQ5gyZQp+/fVXpKSk4PDhw/j666+N502bNg1vvvkm+vfvj8TERBw4cACJiYlmH9jWvPPOOxgwYAAee+wxlJSU4LPPPsPDDz+M7777Dn379jU5d8eOHfjqq68wbtw4+Pv7491338W///1vnDp1CvXr1wcAHDx4EPfffz+Cg4Mxc+ZMlJaWIjk52e6/k4sXL5od8/b2RkBAAFQqFT7++GO0adMGY8aMwVdffQUASE5Oxu+//47MzEz4+fmZvHbw4MGIiopCSkoKfvnlF7z77ru4cuWKSRCRes8BICcnBw899BBGjRqFkSNH4uOPP0ZSUhLatWuHVq1aAQCuX7+Obt264fTp03j66afRuHFj7Nq1C9OmTUNeXp5ZDcjq1atRUFCAp59+GiqVCm+++Sb+9a9/4fjx46hduzaefvppnDlzBps3b8aKFSts3sPffvsNu3btwqOPPopGjRrhxIkTSEtLQ/fu3ZGdnY06depI+ruoSKfTmf39NGjQoErXmjhxIoKCgpCcnIwTJ04gNTUVEyZMwOeff248Z9myZXjiiSfQqlUrTJs2DYGBgdi/fz8yMjIwdOhQzJgxAzqdDn///TfefvttAEDdunWtvueWLVvQp08fNGnSBDNnzsSNGzewcOFC3H333di3b58xEBkMHjwY0dHRSElJwb59+7B06VKEhIRg7ty5AIDff/8d/fr1Q5s2bfDqq69Co9EgJycHO3furNI9IScQRA6Wnp4uAIjffvtNHDt2TNSqVUv85z//MT7frVs30apVK5PXXL9+3ew6iYmJokmTJibHWrVqJbp162Z2bnJysrD042xoS25urvFYZGSkACAyMjLMzpfajm7dullsR0WRkZGib9++Vp/PysoSAMSTTz5pcvy5554TAMS2bduEEEKcPXtW1KpVSwwaNMjkvJkzZwoAYuTIkTbbUvF7KykpEXFxcaJnz54mxwEIb29vkZOTYzx24MABAUAsXLjQeGzQoEHCx8dHnDx50ngsOztbqNVqi38XFY0cOVIAsPhITEw0OffDDz8UAMTKlSvFL7/8ItRqtZg0aZLJOYafgQEDBpgcHzdunAAgDhw4IISQfs+FuPWzsn37duOx8+fPC41GI6ZMmWI89tprrwk/Pz/xxx9/mFxz6tSpQq1Wi1OnTgkhhMjNzRUARP369cXly5eN53377bcCgFi/fr3x2Pjx463eRwAiOTnZ+LWln9vdu3cLAOKTTz4xHvvxxx8FAPHjjz9avK6B4f8bSw9rbTCIjIw0+Xk0XCshIUHo9Xrj8WeffVao1Wpx9epVIYQQV69eFf7+/qJTp07ixo0bJte8/XV9+/YVkZGRZu9ruLfp6enGY/Hx8SIkJERcunTJeOzAgQPCy8tLjBgxwnjM8LPzxBNPmFzzwQcfFPXr1zd+/fbbbwsA4sKFC2bvT56Bw0/kVE2aNMHw4cOxePFi5OXlWT3v9noWw2+H3bp1w/Hjx6HT6RzerujoaCQmJrq9HRs3bgQATJ482eT4lClTAAAbNmwAAGzduhWlpaUYN26cyXkTJ06U/F63f29XrlyBTqdD165dsW/fPrNzExISEBMTY/y6TZs2CAgIwPHjxwEAZWVl2LRpEwYNGoTGjRsbz2vZsqXF+2qNj48PNm/ebPaoOGT51FNPITExERMnTsTw4cMRExOD2bNnW7xmxR41wz0y3Gup99wgNjYWXbt2NX4dHByM5s2bG+8FAHzxxRfo2rUrgoKCcPHiReMjISEBZWVl2L59u8k1H3nkEQQFBRm/Nlz/9mva4/a/25s3b+LSpUto2rQpAgMDLf79SrVo0SKzv5uqeuqpp0yG0Lp27YqysjKcPHkSQPmwTkFBAaZOnWpWG1OVJQLy8vKQlZWFpKQk1KtXz3i8TZs26NWrl/Hn4HZjxowx+bpr1664dOkS8vPzAQCBgYEAgG+//dZkWJE8B4efyOleeuklrFixAnPmzME777xj8ZydO3ciOTkZu3fvNhvD1ul00Gq1Dm1TxRkd7mrHyZMn4eXlhaZNm5ocDw0NRWBgoPEffMOfFc+rV6+eyYdjZb777ju8/vrryMrKMqkdsfSBcXtQMQgKCsKVK1cAABcuXMCNGzfQrFkzs/OaN29u8QPDErVajYSEBEnnfvTRR4iJicGff/6JXbt2WS3srtimmJgYeHl5GetLpN5zA1v3AgD+/PNP/Pe//0VwcLDFNt1eD2Tpmoa/w9uvaY8bN24gJSUF6enpOH36NIQQxueqE8Y7duzosEJhW9/zsWPHADhudpXh79EwtHy7li1bYtOmTSgsLDQZvqysjQEBAXjkkUewdOlSPPnkk5g6dSruu+8+/Otf/8JDDz0ELy/2EXgChhpyuiZNmmDYsGFYvHixxTUujh07hvvuuw8tWrTAggULEBERAW9vb2zcuBFvv/22pN+IrP0mV1ZWZvG4pQ9ER7Sjqpy9WN3PP/+MAQMG4N5778X777+PsLAw1K5dG+np6cYizNtZm1J9+4elq2VmZhrD2MGDB9G5c2dJr7N2b6Xecyn3Qq/Xo1evXnjhhRcsnnvnnXfafU17TJw4Eenp6Zg0aRI6d+4MrVYLlUqFRx991OU9Ctb+n/PEn6mKbLXR19cX27dvx48//ogNGzYgIyMDn3/+OXr27IkffviBSxF4AIYacomXXnoJK1euNBbc3W79+vUoLi7GunXrTH5T+vHHH83OtfZBZPiN6urVq8YuYgBmv3VXxp52OEpkZCT0ej3+/PNPtGzZ0nj83LlzuHr1KiIjI43nAeVFq7f3Ml26dEnSb/dffvklfHx8sGnTJmg0GuPx9PT0KrU7ODgYvr6++PPPP82eO3r0aJWuWZm8vDxMnDgR999/P7y9vfHcc88hMTHReF9u9+eff5rco5ycHOj1emNRqNR7bo+YmBhcu3ZNcq+TFPYE3bVr12LkyJF46623jMeKiopw9epVh7WnoqCgILPrl5SUVDrMXBnDcOehQ4fMetFuJ/W+GP4eLf08HjlyBA0aNDArMpfCy8sL9913H+677z4sWLAAs2fPxowZM/Djjz869O+fqob9ZeQSMTExGDZsGD788EOcPXvW5DnDbzcVu8wtfeD6+flZ/Ifa8A/i7bULhYWFWL58ueQ22tMOR3nggQcAwGx2zIIFCwDAOCvpvvvuQ61atcyml7/33nuS3ketVkOlUpn8Fn3ixAl88803VWq3Wq1GYmIivvnmG5w6dcp4/PDhw9i0aVOVrlmZ0aNHQ6/X46OPPsLixYtRq1YtjBo1yuJv+Yap0AaGxR/79OkDQPo9t8fgwYOxe/dui9/71atXUVpaavc1DR+4UoKJWq02uxcLFy602mviCDExMWa1QosXL67ye95///3w9/dHSkqK2Yy+2783Pz8/SUNqYWFhiI+Px/Lly03u4aFDh/DDDz8Yfw7scfnyZbNj8fHxAGC2HAC5B3tqyGVmzJiBFStW4OjRo8apsACMv333798fTz/9NK5du4YlS5YgJCTE7Le+du3aIS0tDa+//jqaNm2KkJAQ9OzZE/fffz8aN26MUaNG4fnnn4darcbHH3+M4OBgkw/dytjTDnvk5OTg9ddfNzv+j3/8A3379sXIkSOxePFiXL16Fd26dcOePXuwfPlyDBo0CD169ABQPnX9mWeewVtvvYUBAwagd+/eOHDgAL7//ns0aNDA5m+vffv2xYIFC9C7d28MHToU58+fx6JFi9C0aVP897//rdL3NWvWLGRkZKBr164YN24cSktLsXDhQrRq1UryNUtLS7Fy5UqLzz344IPw8/NDeno6NmzYgGXLlqFRo0YAyj+whw0bhrS0NLPi6dzcXOM92r17N1auXImhQ4firrvuAgDcddddku65PZ5//nmsW7cO/fr1M073LiwsxMGDB7F27VqcOHHC7qnQ7dq1AwD85z//QWJiItRqNR599FGL5/br1w8rVqyAVqtFbGwsdu/ejS1bthin3zvDk08+iTFjxuDf//43evXqhQMHDmDTpk1VnvIdEBCAt99+G08++SQ6dOiAoUOHIigoCAcOHMD169eNv6C0a9cOn3/+OSZPnowOHTqgbt266N+/v8Vrzps3D3369EHnzp0xatQo45RurVZbpS0oXn31VWzfvh19+/ZFZGQkzp8/j/fffx+NGjXCPffcU6XvmxzMTbOuSMFun9JdkWEab8Up3evWrRNt2rQRPj4+IioqSsydO1d8/PHHZtOxz549K/r27Sv8/f0FAJNp1Xv37hWdOnUS3t7eonHjxmLBggVWp3Rbm2YttR32TOmGlamxo0aNEkIIcfPmTTFr1iwRHR0tateuLSIiIsS0adNEUVGRybVKS0vFyy+/LEJDQ4Wvr6/o2bOnOHz4sKhfv74YM2aMzbZ89NFHolmzZkKj0YgWLVqI9PR0i1PhAYjx48db/F4qTh3/6aefRLt27YS3t7do0qSJ+OCDD6xOr6+osindhvv9119/Ca1WK/r372/2+gcffFD4+fmJ48ePCyFuTcvNzs4WDz30kPD39xdBQUFiwoQJZlOEpd5zaz8rlv7+CwoKxLRp00TTpk2Ft7e3aNCggejSpYuYP3++KCkpEULcmnY8b948s2uiwhTp0tJSMXHiRBEcHCxUKlWl06mvXLkiHn/8cdGgQQNRt25dkZiYKI4cOWL2d2bvlG5L/w8blJWViRdffFE0aNBA1KlTRyQmJoqcnByrU7orXstaW9atWye6dOkifH19RUBAgOjYsaP49NNPjc9fu3ZNDB06VAQGBgoAxundlqZ0CyHEli1bxN133228Xv/+/UV2drbJOYafnYpTtSv++7F161YxcOBAER4eLry9vUV4eLgYMmSI2VR+ch+VEB5UpUVEdrl69SqCgoLw+uuvGxckrKlmzpyJWbNm4cKFC1XuLSAieWNNDZFM3Lhxw+yYoS7EsF0EEVFNxpoaIpn4/PPPsWzZMjzwwAOoW7cuduzYgU8//RT3338/7r77bnc3j4jI7RhqiGSiTZs2qFWrFt58803k5+cbi4ctFSETEdVErKkhIiIiRWBNDRERESkCQw0REREpQo2qqdHr9Thz5gz8/f2dvtcOEREROYYQAgUFBQgPD69081DZhJq0tDSkpaUZd9pt1aoVXnnlFePS51KcOXMGERERTmohEREROdNff/1lXFncEtmEmkaNGmHOnDlo1qwZhBBYvnw5Bg4ciP3795ssuV8Zf39/AOU3JSAgwJnNJSIiIgfJz89HRESE8XPcGlnPfqpXrx7mzZuHUaNGSTo/Pz8fWq0WOp2OoYaIiEgmpH5+y6an5nZlZWX44osvUFhYiM6dO1s9r7i42GTn1Pz8fFc0j4iIiNxAVrOfDh48iLp160Kj0WDMmDH4+uuvERsba/X8lJQUaLVa44P1NERERMolq+GnkpISnDp1CjqdDmvXrsXSpUvx008/WQ02lnpqIiIiOPxEREQkI1KHn2QVaipKSEhATEwMPvzwQ0nns6aGiIhIfqR+fstq+KkivV5v0hNDRERENZdsCoWnTZuGPn36oHHjxigoKMDq1auRmZmJTZs2ubtpRERE5AFkE2rOnz+PESNGIC8vD1qtFm3atMGmTZvQq1cvdzeNiIiIPIBsQs1HH33k7iYQERGRB5N1TQ0RERGRgWx6aoiIiMhD6cuAk7uAa+eAug2ByC6Al9rlzWCoISIioqrLXgdkvAjkn7l1LCAc6D0XiB3g0qZw+ImIiIis05cBuT8DB9eW/6kvu/Vc9jpgzQjTQAMA+Xnlx7PXubSp7KkhIiIiyyrrhWnRt/w5WFrDVwBQARlTy89z0VAUe2qIiIjInK1emO3zzZ8zIYD80+W1Ni7CnhoiIqKaylqBr77Mdi/Mr2nS3uPaOQc2uHIMNURERDVRZUNLvkG2e2FuXJH2PnUbVquZ9mCoISIiUqLKplkbhpYq9sQYhpb+OVbae/gGATeuml8HAKAqD0mRXar+PdiJoYaIiEhpqlvg+9810t6n01ggM6X8NSbXU5X/0XuOS9erYaEwERGRkjiiwPf6RaBOAxjDiRkVEHAHcO9zwOBPgIAw06cDwsuPu3idGvbUEBERyUllw0qOLPBtMxj4JQ02e2FiB5T3/nBFYSIiIpLM1uq9J3c5rsC3+QNA485W3m+OaS+MlxqI7mrXt+IMDDVERESeojrFvYM/AcpKpL2P1AJfL7XH9MJIwVBDRETkCRyxeu8giUNL9hT4ekgvjBQsFCYiInKF6uyhJHX1XiHKg5DMCnwdhT01REREzlbdXhipxb3XL5Zfc80IyKnA11EYaoiIiKqrOrUw3ac5dvXe6K7lvS0yKvB1FIYaIiKi6nBVL4w9q/cqsBdGCoYaIiKiqnJlL4y9q/cqrBdGChYKExERVcZaga/Nhe5gXy9MDS3udST21BAREVnjqp2spfbC1NBhJakYaoiIqGaqrLgXcO1O1vc+B4S0rJHFvY7EUENERDWPre0GpOyh5OidrNkLU20MNUREpDzV3W5AytCSYSfr65fMrwWAvTCux1BDRETK4ojtBhJmSnsvGe5krWQMNUREJC/OXugu/zRQeEFaW2S4k7WSMdQQEZF8uGqhO7/g8uvm51m5nnx3slYyhhoiIvIcnrLdgH+Y9D2UAPbCeAiGGiIi8gyett2Al1r6HkrkERhqiIjINTylF8ae7QZY4CsrDDVEROR8ntQLY88Ua4BDSzLCUENERNVT3ZV53dELwx4YRWKoISKiqnPEyrzu6oVhD4ziMNQQEZF1rliZl70w5CBe7m6AVCkpKejQoQP8/f0REhKCQYMG4ejRo+5uFhGRfOnLgNyfgYNry//Ul5k+n70OSI0DlvcDvhxV/mdqXPlxmz0wKF+ZtyBPWlt8g2AMJ2ZUQMAd5b0wgz8BAsJMnw4ILz9uqRem9UPlfzLQ1Aiy6an56aefMH78eHTo0AGlpaWYPn067r//fmRnZ8PPz8/dzSMikhdbw0auXpmXvTDkACohhKWY7fEuXLiAkJAQ/PTTT7j33nslvSY/Px9arRY6nQ4BAQFObiERkRtVZdjIECAeWgb8UFloUQG+gdKGjf61BNiSbHtl3kkHgSMbLAStO7gmDEn+/JZNT01FOp0OAFCvXj2r5xQXF6O4uNj4dX5+vtPbRUTkdtWdPr1xSvkO1FY5aWVe9sJQNcmyp0av12PAgAG4evUqduzYYfW8mTNnYtasWWbH2VNDRLJWnV6Y7tOAzNmOaYeU2UiTDpa3zWLQYi8MSSO1p0aWoWbs2LH4/vvvsWPHDjRq1MjqeZZ6aiIiIhhqiEi+bPXCpMY5ZthIiu7T/1cHA1jsgalYvGtrPRsiKxQ7/DRhwgR899132L59e6WBBgA0Gg00Go2LWkZEVE2etIhdnQbA9Uvm7wWAK/OSp5JNqBFCYOLEifj666+RmZmJ6OhodzeJiEg6KYHFkxaxS5wNfJEE1sGQnMgm1IwfPx6rV6/Gt99+C39/f5w9exYAoNVq4evr6+bWERFVorrTp92xiF3sAEAlcYdq9sCQh5BNTY1KZXlRpvT0dCQlJUm6Bqd0E5FTOHv6dEA4kDAT+Gq07bZILd6VOn2adTDkARRXUyOT7EVENY0rpk+7cxE79sKQjMgm1BARuUV19j6SUrhbaaC5jV9weViytYgdN3SkGoyhhohqruoU70rphZFauCsFF7EjsomhhohqJlfsfeTI6dOGUDKYxbtE1simUNgRWChMVENUdb0XZ+x9ZNf0aYCL2BGZU1yhMBERANes9+LIvY8cPX0aYC8MkRUMNUQkH65a70Vq8a6UXhiphbusgyGqNoYaIvIc1ZlpZBgyqqwHJmNq+XovjsLp00QehaGGiFzD2TONHL3ei6P3PmJgIXI6hhoicj5XzDRy9Hov3PuISHY4+4mIqs/Z2wRInWkkxcjvyq+1ZsT/DlQy28hiGLOwlQAROZXUz2+GGiKyTsrUYVvDRqlxlQeWOvWl97LYImXIaNLB8u9BamDh9Gkit+OUbiKqHltDRoZzXDVsZNd6LzaGjAAW7xIpkJe7G0BEbqIvA3J/Bg6uLf9TX3brOUNYqRhIDGEle52E9V7g2G0COo3933+oKjxxW2BpNah86CggzPSUgHDzBeyAW4Gl9UPlf7IHhkjW2FNDpETOnmmUMRXw0bp2mwCu90JENjDUEMlNdVfUdcSQUf7p8t4dKRw5bMQhIyKqBEMNkZxUN7BIWaBO6pBRxVEgaxy9TQADCxFZwdlPRJ7E2VOjHTnTaPi3wLdjba/3MukgcGQDZxoRUZVxSrcFDDXkNnKbGi1lyMgQVqSs9wIwsBBRlXFKN5GrVLfGxXCOq6ZGS2HPnkaDOWxERJ6BPTVElXFWUe7tPRlSemEcuaKu1AXqpA4ZAeyFISKnYk8NUXW5oijXHVOjnbGnEXthiMgDcPE9qrmqs/jcoW9sLzy3cYrjp0ZbnXKkKu9F6fvWra8rPg/Yv0AdF6cjIhlhTw0pk7MXn9s4xUYNix01Lu6YGs0F6ohIgRhqSF6qO4vIUYvPObIoN/IeIGCV7anRjl5Rl0NGRKQwLBQmz+HMWUT2rOXirqJcTo0mIrKI69RYwFDjRp4yi8iRa7nYVZQL2AwrFu+BldlGREQ1CGc/kes4ey8iR84ikhpoHLVfkT3L/7POhYioWthTQ5Vzdg+LI5f27/o88PM86d9bZbpP/19RLlBpD4vU3hUOGRERVRl7aqhyrii4ldLD4o5ZRFKGjViUS0QkO+ypUSJPKbh1ZP2KFFI3WLSnzoU9LEREbsdCYQsUEWqUWHArhaNnEbEol4hINhhqLPD4UOMJ9SsB4cCgNOATF36wu2sWEXthiIhkgaHGAreGGk8ILO4ouHVkYLGnd4WBhYhIMVgo7CosuLXSLidMe+YGi0REVAlZ9dRs374d8+bNw969e5GXl4evv/4agwYNkvx6h/fUsODWsT0s7F0hIiILFNlTU1hYiLvuugtPPPEE/vWvf7m3MbZ6VwwFt67cGFEKKb0r0V3Lg9maEXBpDwt7V4iIqBpkFWr69OmDPn36uLsZ5T0KtsKKo1e4lcJRw0Fe6vIgMpiBhYiI5ENWocZjnNxlO6zknwZyf3bce7q6fgVgYCEiIllRdKgpLi5GcXGx8ev8/HzHXPjaOWnnseCWiIjIZRQdalJSUjBr1izHX7huQ2nnRd4DBKyyo+CW9StERERVJavZT7dTqVQ2Zz9Z6qmJiIio/uwnfdn/Vty1EVacscItZwgREVENo8jZT/bSaDTQaDSOv7CXWtrsIBbcEhERuYysQs21a9eQk5Nj/Do3NxdZWVmoV68eGjdu7NrGSA0rhnMZWIiIiJxKVsNPmZmZ6NGjh9nxkSNHYtmyZTZf75RtEjgcRERE5FSKHH7q3r07PC6DsXeFiIjII3i5uwFEREREjsBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIogu1CzaNEiREVFwcfHB506dcKePXvc3SQiIqIarUwvsPvYJXybdRq7j11CmV64pR213PKuVfT5559j8uTJ+OCDD9CpUyekpqYiMTERR48eRUhIiLubR0REpDhleoE9uZdxvqAIIf4+6BhdD2ovlfH5jEN5mLU+G3m6IuOxMK0PkvvHondcmEvbqhJCuCdOVUGnTp3QoUMHvPfeewAAvV6PiIgITJw4EVOnTrX5+vz8fGi1Wuh0OgQEBDi7uURERB6tuoEl41Aexq7ch4pBwnCFtGFtHRJspH5+y6anpqSkBHv37sW0adOMx7y8vJCQkIDdu3e7sWVERESex1mB5ayuCGNX7sOiof/AaxsOmz0PAALlwWbW+mz0ig01eV9nkk2ouXjxIsrKytCwYUOT4w0bNsSRI0csvqa4uBjFxcXGr/Pz853aRiIiImezFVYA1wSWl749hMuFN622UwDI0xVhT+5ldI6pX9Vv1y6yCTVVkZKSglmzZrm7GURERJI4on7FVYGlsudvd76gyPZJDiKbUNOgQQOo1WqcO3fO5Pi5c+cQGhpq8TXTpk3D5MmTjV/n5+cjIiLCqe0kIiKyxNnDQWnD2qJXbChmrc92WWCRIsTfx2HXskU2ocbb2xvt2rXD1q1bMWjQIADlhcJbt27FhAkTLL5Go9FAo9G4sJVERFQTeUr9ir9PbZP3sHSuIwNLPT9vXCkssdguFYBQbfm9cBXZhBoAmDx5MkaOHIn27dujY8eOSE1NRWFhIR5//HF3N42IiBTKEwKL1PqV3ccuVedbNSElsLzcNxbjV++D6n9tuP15AEjuH+uyImFAZqHmkUcewYULF/DKK6/g7NmziI+PR0ZGhlnxMBERkS1yKriV3rsibZUWRwWW3nFhSPNqa3aPQrlOjfNxnRoioprBmQW3hqsYAou14R4VgCC/2g4d7rFl1ahOeG7tAZzVFUkKLIDlwGJYX0bqwnpSAmJ1SP38ZqghIiJZccWCcb1iQ3HP3G0eFVik9K7seLEnNmefxdiV8gksUjDUWMBQQ0Tk2ZwdWKT0roRqfTD/4bvw2NJfHfvNVcKe4SCg8rACSN+6wBMCixQMNRYw1BAReS5XBBapvSsTejTFez/mVO0bqcCRgcWefZbkElikYKixgKGGiMh9KvuQ9bT6lQk9YvDej8dsnueOwKKksCIVQ40FDDVERI5X3VlEnli/otSCW7liqLGAoYaIyD6umEU0KaEZ3t7yp5O/k1tqcsGtXDHUWMBQQ0QknatmEWl9a+PqDcf0wrDgVpkYaixgqCEiusXZNS6OnkXEgtuaS+rnt6xWFCYiImmqM2zkqE0R7Vm2P9C3NnQ3brpshdvecWHoFRsqKayovVToHFNf0vdB7sVQQ0QkM87ei2hSQjMHbooobTDg8bujkbrlD5cGFoYV5eHwExGRjLhiLRdH1rhInUVkKMxl/QpZwpoaCxhqiMiTSemB8aS1XBw9iwhgYCHLGGosYKghInep7pBRmV64dC0Xe2pcAMfNIiKyhKHGAoYaInIHR0yN1vp6Y8iSX1zW5mcT7kTqlj8AcBYRuR9DjQUMNUTkDK6YGv1C7xZ49vMsh7TXnmEj1riQJ+CUbiIiF3DV1OjL14oltceetVwqm2mk9lJxFhHJjpe7G0BE5MnK9AK7j13Ct1mnsfvYJZTpb8UAQy9MxV4Ww9To97b96bCp0fX8vBGm9YG1/g8VysPU6wPjjF9XfB4oDywPtAlD2rC2CNX6mJwTqvUxqYMBbgWWgfF3oHNMffbAkEfj8BMR1VjVXaDOlcv/fzr6n9DdKOFeRFQjsabGAoYaIjKobvGuIzdhlFrjovZSMbBQjcRQYwFDDVHN4Ir1XqT2wjh6arSU749IaVgoTEQ1kpT1XhxRvCt1WMmRy/8bsDCXyDKGGiKSlapMnzYU7hrWe3FU8a6UXpgJPZuieWhdh26wSESWMdQQkWxUd/r0rPXZeKF3C4e1R0ovDKdGE7kOQw0ReYzq9MJI2Vna0eu9SO2FARhYiFyBoYaIPEJ1e2HSd56Q9D6G9V5s7Rrt6AXqiMj5uPgeEbmEsxexk1q4G6r1RXL/WABcoI5IadhTQ0RO56peGCmFu4ZelLRhtmcbsReGSF64Tg0RVVt1NnR05CJ2UneWltJuIvIcXKeGiFzCk3ph7CncBVi8S6Q0DDVEZFVVV+a1Z0aSIxexY+EuUc3GUENEFjliZV539cKwB4aoZmKoIaqhXLEyL3thiMiVGGqIaiBXrszLXhgichWGGqIaxtUr87IXhohcxe7F90aOHInt27c7oy1E5CDWFrqzVQcD2L8yr7XIoUJ578+Enk25iB0RuYTdPTU6nQ4JCQmIjIzE448/jpEjR+KOO+5wRttMvPHGG9iwYQOysrLg7e2Nq1evOv09ieSosqElR9bBGFbmHbuSWwkQkWewu6fmm2++wenTpzF27Fh8/vnniIqKQp8+fbB27VrcvCntH8OqKCkpwcMPP4yxY8c67T2I5KA62w1syT4r6T0CfWvb7IHpGF0PveO4lQAReY5qryi8b98+pKenY+nSpahbty6GDRuGcePGoVmzZo5qo4lly5Zh0qRJVeqp4YrCJHe2CnzvmbvNak+MCkCQX21cLrT9ywdX5iUiTyL187taG1rm5eVh8+bN2Lx5M9RqNR544AEcPHgQsbGxePvtt6tzaSKqwBGbPl4uvIl6ft4OrYMB2AtDRJ7B7pqamzdvYt26dUhPT8cPP/yANm3aYNKkSRg6dKgxPX399dd44okn8Oyzzzq8wfYoLi5GcfGtGRr5+flubA2RbdZ6PBy50N2g+HCk7zzBOhgiUhy7Q01YWBj0ej2GDBmCPXv2ID4+3uycHj16IDAw0Oa1pk6dirlz51Z6zuHDh9GihbT1MCpKSUnBrFmzqvRaIldzVYFvr9hQdIyuxzVhiEhx7K6pWbFiBR5++GH4+PjYPtmGCxcu4NKlS5We06RJE3h7exu/tqemxlJPTUREBGtqyOPY2sn6ibuj8JGEnhgpC93teLGnsfeHvTBEJAdO26V7+PDh1WrY7YKDgxEcHOyw61Wk0Wig0Wicdn0iqSoLEFKGlr7OOi3pfaQudAewF4aIlEc2KwqfOnUKly9fxqlTp1BWVoasrCwAQNOmTVG3bl33No6oErY2htyTe1lyge+VwhKHbTdARKQ01Z7S7SpJSUlYvny52fEff/wR3bt3l3QNTukmV7M1rJQ2rC2KS/V45rMsm9d64u4oYzGwrWnWHFoiIiWR+vktm1DjCAw15AyVzViytW5MqNYH8x++C48t/dXm+3w6+p/Q3SiptNeHiEiJnFZTQ0S3VHfGUp6uCBDlrzmrK6p0aMkQljjNmojIMoYaoiqytdv1E3dHSbrOxcJiyXsoASzwJSKyplorChMpXXV2u5Y6YynE38euPZSIiMgy9tQQWVHdoSWpM5Y6RtcDAK7gS0RUTQw1RBY4amhJ6pYEBhxaIiKqOg4/EVXgyKGlXrGhHFYiInIR9tRQjWVtKrYjF8PjjCUiItdhqKEaqbJ6meJSvaRr2DO0xGElIiLn4/AT1TiGepmKvTGGepkTFwslXYdDS0REnoU9NVSjSNk88tM9pxAa4INz+VwMj4hIThhqSJGqUy9zNr8Yzybcyd2uiYhkhqGGFMcR9TJRDeogbVhb7nZNRCQjDDWkKLbWl5mU0EzSdUL8fdA5pj6HloiIZIShhhTD0fUyAIeWiIjkhLOfSFas7cUEQHK9zJCOjQHcqo8xsLbKLxERyQN7akg2KquV6R0XhvMF1gPN7VgvQ0SkTAw1JAu2amXShrVFiL+PxddWxHoZIiJlYqghjyelVmbW+mz89HwPhGl9cFbHehkiopqINTXkMazVy0iplcnTFWHvyStI7h8LgPUyREQ1EXtqyCM4Ym2Z8wVFGBh/B+tliIhqKIYacjtHri0DAL3jwlgvQ0RUAzHUkFs5Y20ZgPUyREQ1EWtqyK24tgwRETkKQw25hLUiYHvXlgnVmk7bDtX6IG1YW9bKEBERh5/I+SorAubaMkRE5CgMNeRUtoqAFw39B9eWISIih+DwEzmNrSJgAHhtw2G83JdryxARUfUx1JDTSF00L8jPm/UyRERUbRx+IqeRWgRsWDSP9TJERFQdDDVUbWV6YTGM2FMEDLBehoiIqoehhqqlsplNvWJD7SoCJiIiqg7W1FCVGWY2VaybMcxs2px9lhtMEhGRyzDUUJVImdk0a302esWGsgiYiIhcgsNPVCVSZzbtyb3MDSaJiMglGGqoSuyZ2QSwCJiIiJxPFsNPJ06cwKhRoxAdHQ1fX1/ExMQgOTkZJSUl7m5ajWXvzCYiIiJnk0VPzZEjR6DX6/Hhhx+iadOmOHToEEaPHo3CwkLMnz/f3c1TNGvTtTtG1+PMJiIi8igqIYSlzySPN2/ePKSlpeH48eOSX5Ofnw+tVgudToeAgAAntk4ZKpuu3TsuzDj7CYBJsDFUyrAQmIiIHEHq57cshp8s0el0qFev8l6A4uJi5OfnmzxIGlvTtTMO5aF3XBhnNhERkceQxfBTRTk5OVi4cKHNoaeUlBTMmjXLRa1SDlvTtVW4NV2bM5uIiMhTuLWnZurUqVCpVJU+jhw5YvKa06dPo3fv3nj44YcxevToSq8/bdo06HQ64+Ovv/5y5rejGPZM1wZuzWwaGH8HOsfUZ6AhIiK3cGtPzZQpU5CUlFTpOU2aNDH+95kzZ9CjRw906dIFixcvtnl9jUYDjUZT3WbWOPZO1yYiIvIEbg01wcHBCA4OlnTu6dOn0aNHD7Rr1w7p6enw8pJtOZDH43RtIiKSI1nU1Jw+fRrdu3dHZGQk5s+fjwsXLhifCw0NdWPL5MvaVG0AnK5NRESyJItQs3nzZuTk5CAnJweNGjUyeU6mM9LdytZUbbWXCsn9YzF25T6oYHm6NjeiJCIiTyPbdWqqguvU3JqqXfEv3dLaMrbCDxERkStI/fyWRU8NOYY9U7XVXipO1yYiIllhqKlB7Jmqbdh8khtREhGRXHAKUQ3CqdpERKRkDDU1CKdqExGRkjHU1CCGqdrWKmJUKC8E5lRtIiKSI4aaGsQwVRuAWbDhVG0iIpI7hpoahjtrExGRUnH2kwJVtlowAE7VJiIiRWKoURipC+ZxqjYRESkNh58UxLBacMW1aM7qijB25T5kHMpzU8uIiIicj6FGIWytFgyUrxZcpq8xu2IQEVENw1CjEPasFkxERKREDDUKwdWCiYiopmOoUQiuFkxERDUdQ41CcLVgIiKq6RhqFIKrBRMRUU3HUKMgXC2YiIhqMi6+pzBcLZiIiGoqhhqZsbUFAsDVgomIqGZiqJERqVsgEBER1USsqZEJboFARERUOYYaGeAWCERERLYx1MgAt0AgIiKyjaFGBrgFAhERkW0MNTLALRCIiIhsY6iRAW6BQEREZBtDjQxwCwQiIiLbGGpkglsgEBERVY6L78kIt0AgIiKyjqFGZrgFAhERkWUcfiIiIiJFYKghIiIiRWCoISIiIkVgqCEiIiJFYKGwBynTC85sIiIiqiLZhJoBAwYgKysL58+fR1BQEBISEjB37lyEh4e7u2kOkXEoD7PWZ5tsXBmm9UFy/1iuQUNERCSBbIafevTogTVr1uDo0aP48ssvcezYMTz00EPubpZDZBzKw9iV+8x24j6rK8LYlfuQcSjPTS0jIiKSD5UQQri7EVWxbt06DBo0CMXFxahdu7ak1+Tn50Or1UKn0yEgIMDJLZSmTC9wz9xtZoHGQIXyVYN3vNiTQ1FERFQjSf38lk1Pze0uX76MVatWoUuXLpUGmuLiYuTn55s8PM2e3MtWAw0ACAB5uiLsyb3sukYRERHJkKxCzYsvvgg/Pz/Ur18fp06dwrffflvp+SkpKdBqtcZHRESEi1oq3fkC64GmKucRERHVVG4NNVOnToVKpar0ceTIEeP5zz//PPbv348ffvgBarUaI0aMQGWjZ9OmTYNOpzM+/vrrL1d8W3YJ8fexfZId5xEREdVUbq2puXDhAi5dulTpOU2aNIG3t7fZ8b///hsRERHYtWsXOnfuLOn9PLmm5qyuCJb+IlhTQ0RENZ3Uz2+3TukODg5GcHBwlV6r1+sBlNfNyJnaS4Xk/rEYu3IfVIBJsDFEmOT+sQw0RERENsiipubXX3/Fe++9h6ysLJw8eRLbtm3DkCFDEBMTI7mXxpP1jgtD2rC2CNWaDjGFan2QNqwt16khIiKSQBaL79WpUwdfffUVkpOTUVhYiLCwMPTu3RsvvfQSNBqNu5vnEL3jwtArNpQrChMREVWRbNepqQpPrKkhIiKiyil6nRoiIiKiihhqiIiISBEYaoiIiEgRGGqIiIhIERhqiIiISBEYaoiIiEgRGGqIiIhIERhqiIiISBEYaoiIiEgRGGqIiIhIERhqiIiISBFksaGlEpTpBTerJCIiciKGGhfIOJSHWeuzkacrMh4L0/oguX8seseFubFlREREysHhJyfLOJSHsSv3mQQaADirK8LYlfuQcSjPTS0jIiJSFoYaJyrTC8xanw1h4TnDsVnrs1Gmt3QGERER2YOhxon25F4266G5nQCQpyvCntzLrmsUERGRQjHUONH5AuuBpirnERERkXUMNU4U4u/j0POIiIjIOoYaJ+oYXQ9hWh9Ym7itQvksqI7R9VzZLCIiIkViqHEitZcKyf1jAcAs2Bi+Tu4fy/VqiIiIHIChxsl6x4UhbVhbhGpNh5hCtT5IG9aW69QQERE5CBffc4HecWHoFRvKFYWJiIiciKHGRdReKnSOqe/uZhARESkWh5+IiIhIERhqiIiISBEYaoiIiEgRGGqIiIhIERhqiIiISBEYaoiIiEgRGGqIiIhIEbhODRERuZVer0dJSYm7m0FuVLt2bajV6mpfh6GGiIjcpqSkBLm5udDr9e5uCrlZYGAgQkNDoVJVfbV9hhoiInILIQTy8vKgVqsREREBLy9WRNREQghcv34d58+fBwCEhVV9T0SGGiIicovS0lJcv34d4eHhqFOnjrubQ27k6+sLADh//jxCQkKqPBTFWExERG5RVlYGAPD29nZzS8gTGILtzZs3q3wN2YWa4uJixMfHQ6VSISsry93NISKiaqpODQUphyN+DmQXal544QWEh4e7uxlERESyc+LECUV3Csgq1Hz//ff44YcfMH/+fHc3hYiIaqikpCSoVCrMmTPH5Pg333xjd29D9+7dMWnSJAe2rvo8sU1SySbUnDt3DqNHj8aKFSskF5QVFxcjPz/f5EFERFRdPj4+mDt3Lq5cueLupgAA1/n5H1mEGiEEkpKSMGbMGLRv317y61JSUqDVao2PiIgIJ7aSiIjcoUwvsPvYJXybdRq7j11CmV44/T0TEhIQGhqKlJQUq+dcunQJQ4YMwR133IE6deqgdevW+PTTT43PJyUl4aeffsI777wDlUoFlUqFEydOYNmyZQgMDDS5VsVeoJkzZyI+Ph5Lly5FdHQ0fHx8AAAZGRm45557EBgYiPr166Nfv344duyYQ7/3L7/8Eq1atYJGo0FUVBTeeustk+fz8vLQt29f+Pr6Ijo6GqtXr0ZUVBRSU1Md2g5L3Bpqpk6davyLtPY4cuQIFi5ciIKCAkybNs2u60+bNg06nc74+Ouvv5z0nRARkTtkHMrDPXO3YciSX/DMZ1kYsuQX3DN3GzIO5Tn1fdVqNWbPno2FCxfi77//tnhOUVER2rVrhw0bNuDQoUN46qmnMHz4cOzZswcA8M4776Bz584YPXo08vLykJeXZ9cv3zk5Ofjyyy/x1VdfGWtkCgsLMXnyZPzf//0ftm7dCi8vLzz44IMOW9xw7969GDx4MB599FEcPHgQM2fOxMsvv4xly5YZzxkxYgTOnDmDzMxMfPnll1i8eLFxDRpnc+s6NVOmTEFSUlKl5zRp0gTbtm3D7t27odFoTJ5r3749HnvsMSxfvtziazUajdlriIhIGTIO5WHsyn2o2C9zVleEsSv3IW1YW/SOq/pCbrY8+OCDiI+PR3JyMj766COz5++44w4899xzxq8nTpyITZs2Yc2aNejYsSO0Wi28vb1Rp04dhIaG2v3+JSUl+OSTTxAcHGw89u9//9vknI8//hjBwcHIzs5GXFyc3e9R0YIFC3Dffffh5ZdfBgDceeedyM7Oxrx585CUlIQjR45gy5Yt+O2334wjK0uXLkWzZs2q/d5SuDXUBAcHm/xlWPPuu+/i9ddfN3595swZJCYm4vPPP0enTp2c2UQiIvJAZXqBWeuzzQINAAgAKgCz1mejV2wo1F7OmzI+d+5c9OzZ0yS8GNtYVobZs2djzZo1OH36NEpKSlBcXOywhQYjIyPNPkP//PNPvPLKK/j1119x8eJFYw/NqVOnHBJqDh8+jIEDB5ocu/vuu5GamoqysjIcPXoUtWrVQtu2bY3PN23aFEFBQdV+bylksaJw48aNTb6uW7cuACAmJgaNGjVyR5OIiMiN9uReRp6uyOrzAkCergh7ci+jc0x9p7Xj3nvvRWJiIqZNm2Y28jBv3jy88847SE1NRevWreHn54dJkybZLOr18vKCEKZxzdKCdH5+fmbH+vfvj8jISCxZsgTh4eHQ6/WIi4urMYXEsgg1REREtztfYD3QVOW86pgzZw7i4+PRvHlzk+M7d+7EwIEDMWzYMADlu5H/8ccfiI2NNZ7j7e1tXFnZIDg4GAUFBSgsLDQGFynryly6dAlHjx7FkiVL0LVrVwDAjh07qvOtmWnZsiV27txpcmznzp248847oVar0bx5c5SWlmL//v1o164dgPLaH1fNEpNlqImKijJLsUREVHOE+Ps49LzqaN26NR577DG8++67JsebNWuGtWvXYteuXQgKCsKCBQtw7tw5k1ATFRWFX3/9FSdOnEDdunVRr149dOrUCXXq1MH06dPxn//8B7/++qtJIa41QUFBqF+/PhYvXoywsDCcOnUKU6dOrdL3dOHCBbMgFRYWhilTpqBDhw547bXX8Mgjj2D37t1477338P777wMAWrRogYSEBDz11FNIS0tD7dq1MWXKFPj6+rpk5WhZTOkmIiK6XcfoegjT+sDax6QKQJjWBx2j67mkPa+++qrZDKOXXnoJbdu2RWJiIrp3747Q0FAMGjTI5JznnnsOarUasbGxCA4OxqlTp1CvXj2sXLkSGzduNE4Dnzlzps02eHl54bPPPsPevXsRFxeHZ599FvPmzavS97N69Wr84x//MHksWbIEbdu2xZo1a/DZZ58hLi4Or7zyCl599VWTobdPPvkEDRs2xL333osHH3wQo0ePhr+/v3HauTOpRA3q8sjPz4dWq4VOp0NAQIC7m0NEVKMVFRUhNzfXZJ0VexhmPwEwKRg2BB1nz34iaf7++29ERERgy5YtuO+++6yeV9nPg9TPb/bUEBGRLPWOC0PasLYI1Zp+AIZqfRho3Gjbtm1Yt24dcnNzsWvXLjz66KOIiorCvffe6/T3lmVNDREREVAebHrFhmJP7mWcLyhCiH/5kJMzp3FT5W7evInp06fj+PHj8Pf3R5cuXbBq1SrUrl3b6e/NUENERLKm9lI5ddo22ScxMRGJiYlueW8OPxEREZEiMNQQERGRIjDUEBERkSIw1BAREZEiMNQQERGRIjDUEBERkSIw1BAREZFdoqKikJqaKvn8ZcuWITAw0GntMWCoISIiskNSUhJUKpXZo3fv3u5umsNZCyO//fYbnnrqKdc3yAYuvkdERGSn3r17Iz093eSYRqNxU2tcLzg42N1NsIg9NUREJG/6MiD3Z+Dg2vI/9WVOf0uNRoPQ0FCTR1BQEDIzM+Ht7Y2ff/7ZeO6bb76JkJAQnDt3DgDQvXt3TJgwARMmTIBWq0WDBg3w8ssv4/b9pa9cuYIRI0YgKCgIderUQZ8+ffDnn38anzf0oGzatAktW7ZE3bp10bt3b+Tl5Zm0c+nSpWjZsiV8fHzQokULvP/++8bnTpw4AZVKha+++go9evRAnTp1cNddd2H37t0AgMzMTDz++OPQ6XTG3ijDbuEVh58WLFiA1q1bw8/PDxERERg3bhyuXbvmsPstFUMNERHJV/Y6IDUOWN4P+HJU+Z+pceXH3aB79+6YNGkShg8fDp1Oh/379+Pll1/G0qVL0bBhQ+N5y5cvR61atbBnzx688847WLBgAZYuXWp8PikpCf/3f/+HdevWYffu3RBC4IEHHsDNmzeN51y/fh3z58/HihUrsH37dpw6dQrPPfec8flVq1bhlVdewRtvvIHDhw9j9uzZePnll7F8+XKTNs+YMQPPPfccsrKycOedd2LIkCEoLS1Fly5dkJqaioCAAOTl5SEvL8/k+rfz8vLCu+++i99//x3Lly/Htm3b8MILLzjqtkonahCdTicACJ1O57Brlpbpxa6ci+Kb/X+LXTkXRWmZ3mHXJiJSshs3bojs7Gxx48aNql3g92+FSNYKkRxQ4aEtf/z+rQNbe8vIkSOFWq0Wfn5+Jo833nhDCCFEcXGxiI+PF4MHDxaxsbFi9OjRJq/v1q2baNmypdDrb31evPjii6Jly5ZCCCH++OMPAUDs3LnT+PzFixeFr6+vWLNmjRBCiPT0dAFA5OTkGM9ZtGiRaNiwofHrmJgYsXr1apP3fu2110Tnzp2FEELk5uYKAGLp0qXG53///XcBQBw+fNj4Plqt1uweREZGirffftvqPfriiy9E/fr1jV9bu87tKvt5kPr5zZqaasg4lIdZ67ORpysyHgvT+iC5fyy3vCciciZ9GZDxIgBh4UkBQAVkTAVa9AW81A5/+x49eiAtLc3kWL169QAA3t7eWLVqFdq0aYPIyEi8/fbbZq//5z//CZXq1k7inTt3xltvvYWysjIcPnwYtWrVQqdOnYzP169fH82bN8fhw4eNx+rUqYOYmBjj12FhYTh//jwAoLCwEMeOHcOoUaMwevRo4zmlpaXQarUmbWnTpo3JNQDg/PnzaNGiheT7sWXLFqSkpODIkSPIz89HaWkpioqKcP36ddSpU0fydaqLoaaKMg7lYezKfWb/O53VFWHsyn1IG9aWwYaIyFlO7gLyz1RyggDyT5efF93V4W/v5+eHpk2bWn1+165dAIDLly/j8uXL8PPzc3gbateubfK1SqUy1uUY6lmWLFliEo4AQK02DXm3X8cQtPR6veR2nDhxAv369cPYsWPxxhtvoF69etixYwdGjRqFkpISl4Ya1tRUQZleYNb6bKu/HwDArPXZKNNbOoOIiKrt2jnHnudAx44dw7PPPmsMFCNHjjQLCb/++qvJ17/88guaNWsGtVqNli1borS01OScS5cu4ejRo4iNjZXUhoYNGyI8PBzHjx9H06ZNTR7R0dGSvxdvb2+UlVVeeL13717o9Xq89dZb+Oc//4k777wTZ85UFjidh6GmCvbkXjYZcqpIAMjTFWFP7mXXNYqIqCap29D2OfacZ6fi4mKcPXvW5HHx4kWUlZVh2LBhSExMxOOPP4709HT897//xVtvvWXy+lOnTmHy5Mk4evQoPv30UyxcuBDPPPMMAKBZs2YYOHAgRo8ejR07duDAgQMYNmwY7rjjDgwcOFByG2fNmoWUlBS8++67+OOPP3Dw4EGkp6djwYIFkq8RFRWFa9euYevWrbh48SKuX79udk7Tpk1x8+ZNLFy4EMePH8eKFSvwwQcfSH4PR2KoqYLzBdYDTVXOIyIiO0V2AQLCAaisnKACAu4oP88JMjIyEBYWZvK455578MYbb+DkyZP48MMPAZTXqCxevBgvvfQSDhw4YHz9iBEjcOPGDXTs2BHjx4/HM888Y7KYXXp6Otq1a4d+/fqhc+fOEEJg48aNZkNOlXnyySexdOlSpKeno3Xr1ujWrRuWLVtmV09Nly5dMGbMGDzyyCMIDg7Gm2++aXbOXXfdhQULFmDu3LmIi4vDqlWrkJKSIvk9HEklhKgxYyT5+fnQarXQ6XQICAio8nV2H7uEIUt+sXnep6P/ic4x9av8PkRESlZUVITc3FxER0fDx8fH/gtkrwPWjPjfF7d/lP0v6Az+BIgdUN1mOlz37t0RHx9v1zYDNUFlPw9SP7/ZU1MFHaPrIUzrU9nvBwjT+qBjdD1XNouIqGaJHVAeXAIqTMoICPfYQEPOxdlPVaD2UiG5fyzGrtwHFSz+foDk/rFQe1mLPURE5BCxA8qnbZ/cVV4UXLdh+ZCTE6Zxk+djqKmi3nFhSBvW1mydmlCuU0NE5FpeaqdM23aWzMxMdzdBsRhqqqF3XBh6xYZiT+5lnC8oQoh/+ZATe2iIiIhcj6GmmtReKhYDExEReQAWChMRkVvVoEm4VAlH/Bww1BARkVsYlusvKSlxc0vIExgW9rNnLZ6KOPxERERuUatWLdSpUwcXLlxA7dq14eXF37NrIiEErl+/jvPnzyMwMNBsbyp7MNQQEZFbqFQqhIWFITc3FydPnnR3c8jNAgMDERoaWq1rMNQQEZHbeHt7o1mzZhyCquFq165drR4aA4YaIiJyKy8vr6ptk0BUAQcwiYiISBEYaoiIiEgRGGqIiIhIEWpUTY1hYZ/8/Hw3t4SIiIikMnxu21qgr0aFmoKCAgBARESEm1tCRERE9iooKIBWq7X6vErUoPWp9Xo9zpw5A39/f6hUVd90Mj8/HxEREfjrr78QEBDgwBZSRbzXrsN77Tq8167De+06zrzXQggUFBQgPDy80kUaa1RPjZeXFxo1auSw6wUEBPB/EhfhvXYd3mvX4b12Hd5r13HWva6sh8aAhcJERESkCAw1REREpAgMNVWg0WiQnJwMjUbj7qYoHu+16/Beuw7vtevwXruOJ9zrGlUoTERERMrFnhoiIiJSBIYaIiIiUgSGGiIiIlIEhhoiIiJSBIYaKxYtWoSoqCj4+PigU6dO2LNnT6Xnf/HFF2jRogV8fHzQunVrbNy40UUtlT977vWSJUvQtWtXBAUFISgoCAkJCTb/bugWe3+uDT777DOoVCoMGjTIuQ1UEHvv9dWrVzF+/HiEhYVBo9Hgzjvv5L8jEtl7r1NTU9G8eXP4+voiIiICzz77LIqKilzUWvnavn07+vfvj/DwcKhUKnzzzTc2X5OZmYm2bdtCo9GgadOmWLZsmXMbKcjMZ599Jry9vcXHH38sfv/9dzF69GgRGBgozp07Z/H8nTt3CrVaLd58802RnZ0tXnrpJVG7dm1x8OBBF7dcfuy910OHDhWLFi0S+/fvF4cPHxZJSUlCq9WKv//+28Utlx9777VBbm6uuOOOO0TXrl3FwIEDXdNYmbP3XhcXF4v27duLBx54QOzYsUPk5uaKzMxMkZWV5eKWy4+993rVqlVCo9GIVatWidzcXLFp0yYRFhYmnn32WRe3XH42btwoZsyYIb766isBQHz99deVnn/8+HFRp04dMXnyZJGdnS0WLlwo1Gq1yMjIcFobGWos6Nixoxg/frzx67KyMhEeHi5SUlIsnj948GDRt29fk2OdOnUSTz/9tFPbqQT23uuKSktLhb+/v1i+fLmzmqgYVbnXpaWlokuXLmLp0qVi5MiRDDUS2Xuv09LSRJMmTURJSYmrmqgY9t7r8ePHi549e5ocmzx5srj77rud2k6lkRJqXnjhBdGqVSuTY4888ohITEx0Wrs4/FRBSUkJ9u7di4SEBOMxLy8vJCQkYPfu3RZfs3v3bpPzASAxMdHq+VSuKve6ouvXr+PmzZuoV6+es5qpCFW916+++ipCQkIwatQoVzRTEapyr9etW4fOnTtj/PjxaNiwIeLi4jB79myUlZW5qtmyVJV73aVLF+zdu9c4RHX8+HFs3LgRDzzwgEvaXJO447OxRm1oKcXFixdRVlaGhg0bmhxv2LAhjhw5YvE1Z8+etXj+2bNnndZOJajKva7oxRdfRHh4uNn/OGSqKvd6x44d+Oijj5CVleWCFipHVe718ePHsW3bNjz22GPYuHEjcnJyMG7cONy8eRPJycmuaLYsVeVeDx06FBcvXsQ999wDIQRKS0sxZswYTJ8+3RVNrlGsfTbm5+fjxo0b8PX1dfh7sqeGZGvOnDn47LPP8PXXX8PHx8fdzVGUgoICDB8+HEuWLEGDBg3c3RzF0+v1CAkJweLFi9GuXTs88sgjmDFjBj744AN3N01xMjMzMXv2bLz//vvYt28fvvrqK2zYsAGvvfaau5tGDsCemgoaNGgAtVqNc+fOmRw/d+4cQkNDLb4mNDTUrvOpXFXutcH8+fMxZ84cbNmyBW3atHFmMxXB3nt97NgxnDhxAv379zce0+v1AIBatWrh6NGjiImJcW6jZaoqP9dhYWGoXbs21Gq18VjLli1x9uxZlJSUwNvb26ltlquq3OuXX34Zw4cPx5NPPgkAaN26NQoLC/HUU09hxowZ8PLi7/qOYu2zMSAgwCm9NAB7asx4e3ujXbt22Lp1q/GYXq/H1q1b0blzZ4uv6dy5s8n5ALB582ar51O5qtxrAHjzzTfx2muvISMjA+3bt3dFU2XP3nvdokULHDx4EFlZWcbHgAED0KNHD2RlZSEiIsKVzZeVqvxc33333cjJyTEGRwD4448/EBYWxkBTiarc6+vXr5sFF0OYFNwK0aHc8tnotBJkGfvss8+ERqMRy5YtE9nZ2eKpp54SgYGB4uzZs0IIIYYPHy6mTp1qPH/nzp2iVq1aYv78+eLw4cMiOTmZU7olsvdez5kzR3h7e4u1a9eKvLw846OgoMBd34Js2HuvK+LsJ+nsvdenTp0S/v7+YsKECeLo0aPiu+++EyEhIeL1119317cgG/be6+TkZOHv7y8+/fRTcfz4cfHDDz+ImJgYMXjwYHd9C7JRUFAg9u/fL/bv3y8AiAULFoj9+/eLkydPCiGEmDp1qhg+fLjxfMOU7ueff14cPnxYLFq0iFO63WXhwoWicePGwtvbW3Ts2FH88ssvxue6desmRo4caXL+mjVrxJ133im8vb1Fq1atxIYNG1zcYvmy515HRkYKAGaP5ORk1zdchuz9ub4dQ4197L3Xu3btEp06dRIajUY0adJEvPHGG6K0tNTFrZYne+71zZs3xcyZM0VMTIzw8fERERERYty4ceLKlSuub7jM/Pjjjxb//TXc35EjR4pu3bqZvSY+Pl54e3uLJk2aiPT0dKe2USUE+9uIiIhI/lhTQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENERESKwFBDREREisBQQ0RERIrAUENEsnXhwgWEhoZi9uzZxmO7du2Ct7e32e7ARKR83PuJiGRt48aNGDRoEHbt2oXmzZsjPj4eAwcOxIIFC9zdNCJyMYYaIpK98ePHY8uWLWjfvj0OHjyI3377DRqNxt3NIiIXY6ghItm7ceMG4uLi8Ndff2Hv3r1o3bq1u5tERG7Amhoikr1jx47hzJkz0Ov1OHHihLubQ0Ruwp4aIpK1kpISdOzYEfHx8WjevDlSU1Nx8OBBhISEuLtpRORiDDVEJGvPP/881q5diwMHDqBu3bro1q0btFotvvvuO3c3jYhcjMNPRCRbmZmZSE1NxYoVKxAQEAAvLy+sWLECP//8M9LS0tzdPCJyMfbUEBERkSKwp4aIiIgUgaGGiIiIFIGhhoiIiBSBoYaIiIgUgaGGiIiIFIGhhoiIiBSBoYaIiIgUgaGGiIiIFIGhhoiIiBSBoYaIiIgUgaGGiIiIFIGhhoiIiBTh/wFWJ8eC8jDgEwAAAABJRU5ErkJggg==\n"
+          },
+          "metadata": {}
+        }
+      ],
       "source": [
         "import numpy as np\n",
-        "import matplotlib.pyplot as plt\n"
+        "import matplotlib.pyplot as plt\n",
+        "# Create grid\n",
+        "x = np.linspace(0.01, 1, 50)  # start at 0.01 to avoid log(0)\n",
+        "\n",
+        "# Compute functions\n",
+        "y = np.log(x)\n",
+        "z = np.exp(x)\n",
+        "\n",
+        "# Scatter plots\n",
+        "plt.scatter(x, y, label=\"Natural Log\")\n",
+        "plt.scatter(x, z, label=\"Exponential\")\n",
+        "\n",
+        "# Labels and title\n",
+        "plt.xlabel(\"x\")\n",
+        "plt.ylabel(\"y\")\n",
+        "plt.title(\"Natural Log and Exponential Functions\")\n",
+        "\n",
+        "# Legend\n",
+        "plt.legend(loc=\"lower right\")\n",
+        "\n",
+        "# Show plot\n",
+        "plt.show()\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Create grid\n",
+        "x = np.linspace(-6.5, 6.5, 100)\n",
+        "\n",
+        "# Compute sine and cosine\n",
+        "y = np.sin(x)\n",
+        "z = np.cos(x)\n",
+        "\n",
+        "# Line plots (not scatter)\n",
+        "plt.plot(x, y, label=\"Sine\")\n",
+        "plt.plot(x, z, label=\"Cosine\")\n",
+        "\n",
+        "# Labels and title\n",
+        "plt.xlabel(\"x\")\n",
+        "plt.ylabel(\"y\")\n",
+        "plt.title(\"Sine and Cosine Functions\")\n",
+        "\n",
+        "# Legend in lower left\n",
+        "plt.legend(loc=\"lower left\")\n",
+        "\n",
+        "# Show plot\n",
+        "plt.show()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "id": "I13Vxg0kA7Lp",
+        "outputId": "e702ec38-a16f-4bdc-fc72-cac5d988fe9a"
+      },
+      "id": "I13Vxg0kA7Lp",
+      "execution_count": 4,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": "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\n"
+          },
+          "metadata": {}
+        }
       ]
     },
     {