From 07ffa51d01443a50e0c22923e6ce2f02f0de1f69 Mon Sep 17 00:00:00 2001
From: dzalkind <dzalkind@nrel.gov>
Date: Tue, 16 Dec 2025 19:31:16 -0700
Subject: [PATCH 1/9] Don't collect all outputs when running mpi

---
 weis/aeroelasticse/runFAST_pywrapper.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/weis/aeroelasticse/runFAST_pywrapper.py b/weis/aeroelasticse/runFAST_pywrapper.py
index cf0eeca8e..55643dea8 100644
--- a/weis/aeroelasticse/runFAST_pywrapper.py
+++ b/weis/aeroelasticse/runFAST_pywrapper.py
@@ -413,10 +413,10 @@ def run_mpi(self, mpi_comm_map_down):
             for j, case_data in enumerate(case_data_all[idx_s:idx_e]):
                 rank_j = sub_ranks[j]
                 data_out = comm.recv(source=rank_j, tag=1)
-                output.append(data_out)
+                # output.append(data_out)
+                self.cruncher.add_output(data_out)
 
-        for iout in output:
-            self.cruncher.add_output(iout)
+        # for iout in output:
 
         return self.cruncher
 

From 0e6670219e43d50b8ceae56af7db9c8e6af91970 Mon Sep 17 00:00:00 2001
From: dzalkind <dzalkind@nrel.gov>
Date: Mon, 5 Jan 2026 15:49:15 -0700
Subject: [PATCH 2/9] Add chapter 1 inputs and testing

---
 .github/workflows/CI_WEIS.yml                 |    7 +
 .../0_notebooks/chapter1.ipynb                | 1043 ++++++++++
 .../0_notebooks/weis_workshop.py              |  216 ++
 .../stage-0-baseline_analysis.yaml            |    3 +
 .../stage-0-baseline_driver.py                |   76 +
 .../stage-0-baseline_modeling.yaml            |   91 +
 .../2_models/new-20-270-RWT_Floater.yaml      | 1814 +++++++++++++++++
 7 files changed, 3250 insertions(+)
 create mode 100644 examples/09_model_creation_process/0_notebooks/chapter1.ipynb
 create mode 100644 examples/09_model_creation_process/0_notebooks/weis_workshop.py
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_analysis.yaml
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_driver.py
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_modeling.yaml
 create mode 100644 examples/09_model_creation_process/2_models/new-20-270-RWT_Floater.yaml

diff --git a/.github/workflows/CI_WEIS.yml b/.github/workflows/CI_WEIS.yml
index cfbdb2f2a..de7976fe1 100644
--- a/.github/workflows/CI_WEIS.yml
+++ b/.github/workflows/CI_WEIS.yml
@@ -124,6 +124,13 @@ jobs:
           treon rev_Opt.ipynb
           treon rev_WEIS_CSV.ipynb
 
+      - name: Test model creation notebooks and drivers
+        if: contains( matrix.os, 'ubuntu') && contains( github.event_name, 'pull_request')
+        run: |
+          cd examples/09_model_creation_process
+          treon 0_notebooks/chapter1.ipynb
+          treon iea22_ptfm_driver.ipynb
+
       # Run parallel script calling OpenFAST
       - name: Run parallel cases
         if: contains( matrix.os, 'ubuntu') && contains( github.event_name, 'pull_request')
diff --git a/examples/09_model_creation_process/0_notebooks/chapter1.ipynb b/examples/09_model_creation_process/0_notebooks/chapter1.ipynb
new file mode 100644
index 000000000..31ed49c7b
--- /dev/null
+++ b/examples/09_model_creation_process/0_notebooks/chapter1.ipynb
@@ -0,0 +1,1043 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fcf9a651",
+   "metadata": {},
+   "source": [
+    "# PLEASE ONLY RUN THE NEXT FOUR CELLS ONCE!\n",
+    "\n",
+    "## Google Colab Runtime Configuration\n",
+    "**Before running any cells, please change the runtime version:**\n",
+    "1. Go to **Edit** → **Notebook Settings** → **Runtime Version** \n",
+    "2. Select **2025.07** \n",
+    "3. Click **Save**\n",
+    "\n",
+    "## Important Notes:\n",
+    "- The setup cells below will install dependencies and may cause kernel restarts\n",
+    "- This is expected behavior - simply continue after each restart\n",
+    "- Only run the setup cells once per session"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "14f61088",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Global variable to check if we're in Google Colab\n",
+    "import sys\n",
+    "IN_COLAB = 'google.colab' in sys.modules\n",
+    "if IN_COLAB:\n",
+    "    ! pip install numpy==1.26.4\n",
+    "    ### The runtime will crash/restart after this"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "a673a11f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Global variable to check if we're in Google Colab\n",
+    "import sys\n",
+    "IN_COLAB = 'google.colab' in sys.modules\n",
+    "\n",
+    "if IN_COLAB:\n",
+    "\n",
+    "  !pip install -q condacolab #-U \"git+https://github.com/mayankchetan/condacolab.git@py312update\"\n",
+    "  import condacolab\n",
+    "  condacolab.install() #### expect a kernel restart"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "0679a464",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DeprecationWarning: /Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/jsonmerge/__init__.py:27\n",
+      "Accessing Draft4Validator.resolver is deprecated as of v4.18.0, in favor of the https://github.com/python-jsonschema/referencing library, which provides more compliant referencing behavior as well as more flexible APIs for customization."
+     ]
+    }
+   ],
+   "source": [
+    "# Global variable to check if we're in Google Colab\n",
+    "import sys\n",
+    "IN_COLAB = 'google.colab' in sys.modules\n",
+    "\n",
+    "if IN_COLAB:\n",
+    "    !git clone  https://github.com/wisdem/weis\n",
+    "    !git clone https://github.com/mayankchetan/weisWorkshop\n",
+    "\n",
+    "    %cd weis\n",
+    "    !conda config --env --add pinned_packages \"numpy<2.0\"\n",
+    "    !mamba env update -n base -f environment.yml \"python<3.13\"\n",
+    "    %pip install .\n",
+    "    %cd ..\n",
+    "    %pip install \"rosco==2.9.5\"\n",
+    "    %pip install -U \"git+https://github.com/NREL/ROSCO@v2.9.7\"\n",
+    "    %pip install \"orbit-nrel<1.2.2\"\n",
+    "    %pip install gdown\n",
+    "\n",
+    "else:\n",
+    "    try:\n",
+    "        import weis\n",
+    "\n",
+    "    except ImportError:\n",
+    "        raise ImportError(\"Please install the weis package from https://github.com/wisdem/weis in the environment you are using to run this notebook.\")\n",
+    "\n",
+    "    Warning(\"Make sure you have cloned 'https://github.com/mayankchetan/weisWorkshop-Private' repository and are running the notebook from the root directory of the repository.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "486f157e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Please download the precomputed data from the link given in the notebook and extract it in the root directory of the repository.\n",
+      "you can use `tar -xvzf <downloaded_file_name>` to extract the files.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Downloading the precomputed data from Google Drive & extracting\n",
+    "# Drive link for non Google Colab users: https://drive.google.com/file/d/145BH393nzpT2msCVsHSBxR3Qy8KdpddI/view?usp=sharing\n",
+    "if IN_COLAB:\n",
+    "    !gdown 145BH393nzpT2msCVsHSBxR3Qy8KdpddI -O /content/weisWorkshop/archive_weisWorkshop_OCT25.tar.gz\n",
+    "    !tar -xvzf /content/weisWorkshop/archive_weisWorkshop_OCT25.tar.gz -C /content/weisWorkshop/\n",
+    "else:\n",
+    "    print(\"Please download the precomputed data from the link given in the notebook and extract it in the root directory of the repository.\")\n",
+    "    print(\"you can use `tar -xvzf <downloaded_file_name>` to extract the files.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f010422a",
+   "metadata": {},
+   "source": [
+    "# Welcome to the WEIS Workshop - Chapter 1: Rotor Design and Optimization\n",
+    "\n",
+    "## Introduction\n",
+    "\n",
+    "WEIS is a comprehensive framework that performs multifidelity co-design of wind turbines by integrating multiple NREL-developed tools:\n",
+    "\n",
+    "- **WISDEM** (Wind-Plant Integrated System Design and Engineering Model) - A set of models for assessing overall wind plant cost of energy (COE) using wind turbine and plant cost, energy production, and financial models\n",
+    "- **OpenFAST** - A physics-based engineering tool for simulating the coupled dynamic response of wind turbines, including aero-hydro-servo-elastic simulation in the time domain\n",
+    "- **ROSCO** (Reference OpenSource Controller) - An open, modular, and fully adaptable baseline wind turbine controller with industry-standard functionality\n",
+    "- **RAFT** (Response Amplitudes of Floating Turbines) - A frequency-domain analysis tool for floating wind turbines\n",
+    "\n",
+    "These tools work together in a unique workflow to enable comprehensive wind turbine design optimization, from individual components to full system integration.\n",
+    "\n",
+    "## Workshop Objectives\n",
+    "\n",
+    "In this workshop, you are tasked with designing and optimizing a **20MW floating wind turbine** starting from the IEA 22MW reference turbine. Your objectives include:\n",
+    "\n",
+    "1. **Establish baseline performance** - Understand the IEA 22MW floating turbine characteristics and performance\n",
+    "2. **Scale and optimize the rotor** - Modify the rotor to achieve 20MW rating while optimizing aerodynamic and structural performance\n",
+    "3. **Optimize the controller** - Retune the ROSCO pitch controller for the new rotor design to ensure optimal performance\n",
+    "4. **Design the floating platform** - Optimize a semisubmersible platform to support the turbine under various load conditions\n",
+    "5. **Validate through load analysis** - Simulate the design according to IEC Design Load Case (DLC) analysis\n",
+    "\n",
+    "## Our Systematic Multi-Stage Approach \n",
+    "\n",
+    "We'll follow a systematic optimization approach that mirrors our wind turbine development practices:\n",
+    "\n",
+    "1. **IEA 22MW Baseline** - Start with the IEA 22MW floating turbine to establish a reference point\n",
+    "2. **Rotor Scaling and Optimization** - Scale the rotor diameter for 20MW rating, then optimize chord, twist, and structural properties using WISDEM\n",
+    "3. **Controller Re-tuning** - Use ROSCO to re-tune the controller for optimal performance with the modified rotor\n",
+    "4. **Floating Platform Optimization** - Use RAFT for frequency-domain optimization of the semisubmersible platform\n",
+    "5. **High-Fidelity Integration** - Refine the design using OpenFAST for coupled aero-hydro-servo-elastic optimization\n",
+    "6. **Design Validation** - Conduct comprehensive DLC analysis to verify the final design meets all requirements\n",
+    "\n",
+    "\n",
+    "<!-- This staged approach offers several advantages:\n",
+    "- **Manageable complexity** - Build complexity gradually rather than solving one massive optimization problem\n",
+    "- **Appropriate fidelity** - Use the right tool for each design phase (fast tools for initial sizing, high-fidelity for final validation)\n",
+    "- **Better convergence** - Smaller, focused optimization problems are more likely to converge successfully\n",
+    "- **Educational value** - Understand how different subsystems interact and influence overall performanc -->\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "2d1a1fee",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running in local environment\n"
+     ]
+    }
+   ],
+   "source": [
+    "if IN_COLAB:\n",
+    "    # Now we try loading the weis_workshop module again\n",
+    "    sys.path.append('/content/weisWorkshop/jupyterNotebooks')\n",
+    "\n",
+    "# Importing nesscary libraries.\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from weis import weis_main\n",
+    "from wisdem import run_wisdem\n",
+    "import os\n",
+    "import copy\n",
+    "import pandas as pd\n",
+    "\n",
+    "from weis_workshop import *\n",
+    "\n",
+    "# workshop repository folder\n",
+    "if IN_COLAB:\n",
+    "    WORKSHOP_REPO = '/content/weisWorkshop'\n",
+    "else:\n",
+    "    WORKSHOP_REPO = os.path.join(os.getcwd(), '..')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "9a1f97fd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'/Users/dzalkind/Tools/WEIS-Eni/examples/09_model_creation_process/0_notebooks/..'"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "WORKSHOP_REPO"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "12ec3331",
+   "metadata": {},
+   "source": [
+    "## Stage 0: Establishing a Baseline\n",
+    "\n",
+    "Let's start by running the IEA 22MW floating turbine to understand our starting point. Since we're designing a 20MW turbine, the IEA22MW reference gives us a good baseline that's close to our target size."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "9022e9a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Setting up file paths\n",
+    "stageFolder = \"stage-0-baseline\"\n",
+    "\n",
+    "fname_wt_input = os.path.join(WORKSHOP_REPO, \"..\", \"00_setup\", \"ref_turbines\", \"IEA-22-280-RWT_Floater.yaml\")\n",
+    "fname_modeling_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-0-baseline_modeling.yaml\")\n",
+    "fname_analysis_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-0-baseline_analysis.yaml\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "95fb7196",
+   "metadata": {},
+   "source": [
+    "## Understanding the Input Files\n",
+    "\n",
+    "**For Google Colab users:** Use the file browser on the left to navigate to the cloned repository and open the YAML files (double click).\n",
+    "\n",
+    "### Turbine Geometry File (WindIO Format)\n",
+    "The turbine is defined using WindIO format. Here are the key sections:\n",
+    "\n",
+    "```yaml\n",
+    "name: IEA 22MW Offshore Wind Turbine in Floating Configuration\n",
+    "assembly:\n",
+    "    turbine_class: I\n",
+    "    turbulence_class: B\n",
+    "    drivetrain: direct_drive\n",
+    "    rotor_orientation: Upwind\n",
+    "    number_of_blades: 3\n",
+    "    hub_height: 170.0\n",
+    "    rotor_diameter: 284.0\n",
+    "    rated_power: 22000000.0\n",
+    "    lifetime: 25.0\n",
+    "components:\n",
+    "  blade:\n",
+    "    outer_shape_bem:\n",
+    "      reference_axis:\n",
+    "        x: { grid: [...], values: [...] }\n",
+    "        y: { grid: [...], values: [...] }\n",
+    "        z: { grid: [...], values: [...] }\n",
+    "      chord: { grid: [...], values: [...] }\n",
+    "      twist: { grid: [...], values: [...] }\n",
+    "    internal_structure_2d_fem:\n",
+    "      reference_axis: [...]\n",
+    "      layers: [...]\n",
+    "      webs: [...]\n",
+    "  hub:\n",
+    "    diameter: 7.94  # m\n",
+    "    cone_angle: -2.5  # degrees\n",
+    "    \n",
+    "  nacelle:\n",
+    "    drivetrain: [...]\n",
+    "    transformer: [...]\n",
+    "    \n",
+    "  tower:\n",
+    "    outer_shape_bem: [...]\n",
+    "    internal_structure_2d_fem: [...]\n",
+    "    \n",
+    "  mooring:\n",
+    "    nodes: [...]\n",
+    "    lines: [...]\n",
+    "airfoils: [...]\n",
+    "materials: [...]\n",
+    "controls: [...]\n",
+    "environment: [...]\n",
+    "bos: [...]\n",
+    "costs: [...]\n",
+    "```\n",
+    "\n",
+    "### Analysis and Modeling Options\n",
+    "These files control what WEIS calculates and how:\n",
+    "\n",
+    "**Analysis Options** (How to analyze the problem):\n",
+    "```yaml\n",
+    "general:\n",
+    "    folder_output: outputs/\n",
+    "    fname_output: stage-0-baseline\n",
+    "```\n",
+    "\n",
+    "**Modeling Options** (which tools to use):\n",
+    "```yaml\n",
+    "General:\n",
+    "    verbosity: False\n",
+    "\n",
+    "WISDEM:\n",
+    "    RotorSE:\n",
+    "        flag: True\n",
+    "    TowerSE:\n",
+    "        flag: True\n",
+    "    DriveSE:\n",
+    "        flag: True\n",
+    "    FloatingSE:\n",
+    "        flag: True\n",
+    "    BOS:\n",
+    "        flag: True\n",
+    "\n",
+    "OpenFAST: # Options for WEIS fidelity level 3 = nonlinear time domain\n",
+    "    flag: False\n",
+    "\n",
+    "RAFT:\n",
+    "    flag: False\n",
+    "\n",
+    "ROSCO:\n",
+    "    flag: True\n",
+    "    tuning_yaml: ../source/iea22_rosco.yaml\n",
+    "```\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "e9f06246",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "================\n",
+      "wisdem.wt.wt_rna\n",
+      "================\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[00m\u001b[00m\u001b[00m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "NL: NLBGS 1 ; 5.81491099e+11 1\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[00m\u001b[00m\u001b[00m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "NL: NLBGS 2 ; 1207363.87 2.07632391e-06\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[00m\u001b[00m\u001b[00m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "NL: NLBGS 3 ; 5643.76806 9.70568263e-09\n",
+      "NL: NLBGS Converged\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[00m\u001b[00m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "UHC input: [0.] -- Mass: [0.]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\u001b[00m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ORBIT library intialized at '/Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/library'\n",
+      "Cp-Ct-Cq surfaces completed at 5 %\n",
+      "Cp-Ct-Cq surfaces completed at 10 %\n",
+      "Cp-Ct-Cq surfaces completed at 15 %\n",
+      "Cp-Ct-Cq surfaces completed at 20 %\n",
+      "Cp-Ct-Cq surfaces completed at 25 %\n",
+      "Cp-Ct-Cq surfaces completed at 30 %\n",
+      "Cp-Ct-Cq surfaces completed at 35 %\n",
+      "Cp-Ct-Cq surfaces completed at 40 %\n",
+      "Cp-Ct-Cq surfaces completed at 45 %\n",
+      "Cp-Ct-Cq surfaces completed at 50 %\n",
+      "Cp-Ct-Cq surfaces completed at 55 %\n",
+      "Cp-Ct-Cq surfaces completed at 60 %\n",
+      "Cp-Ct-Cq surfaces completed at 65 %\n",
+      "Cp-Ct-Cq surfaces completed at 70 %\n",
+      "Cp-Ct-Cq surfaces completed at 75 %\n",
+      "Cp-Ct-Cq surfaces completed at 80 %\n",
+      "Cp-Ct-Cq surfaces completed at 85 %\n",
+      "Cp-Ct-Cq surfaces completed at 90 %\n",
+      "Cp-Ct-Cq surfaces completed at 95 %\n",
+      "Cp-Ct-Cq surfaces completed at 100 %\n",
+      "-----------------------------------------------------------------------------\n",
+      "   Tuning a reference wind turbine controller using NREL's ROSCO toolbox    \n",
+      "-----------------------------------------------------------------------------\n",
+      "WARNING: twr_freq and ptfm_freq should be defined for floating turbine control!!\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DeprecationWarning: /Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/jsonmerge/__init__.py:27\n",
+      "Accessing Draft4Validator.resolver is deprecated as of v4.18.0, in favor of the https://github.com/python-jsonschema/referencing library, which provides more compliant referencing behavior as well as more flexible APIs for customization."
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "----------------\n",
+      "Design Variables\n",
+      "----------------\n",
+      "name  val  size  \n",
+      "----  ---  ---- \n",
+      "\n",
+      "-----------\n",
+      "Constraints\n",
+      "-----------\n",
+      "name  val  size  \n",
+      "----  ---  ---- \n",
+      "\n",
+      "----------\n",
+      "Objectives\n",
+      "----------\n",
+      "name  val  size  \n",
+      "----  ---  ---- \n",
+      "\n",
+      "Run time (outputsCh1): 24.042563915252686\n"
+     ]
+    }
+   ],
+   "source": [
+    "# lets overide a few things so that we dont distrupt the existing results.\n",
+    "analysis_override = {}\n",
+    "analysis_override['general'] = {}\n",
+    "analysis_override['general']['folder_output'] = 'outputsCh1'\n",
+    "\n",
+    "\n",
+    "iea22mw, modeling_options, opt_options = weis_main(fname_wt_input, \n",
+    "                                                 fname_modeling_options, \n",
+    "                                                 fname_analysis_options,\n",
+    "                                                 analysis_override=analysis_override,\n",
+    "                                                 test_run=False\n",
+    "                                                 )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "d797bf2c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "there are 4691 variables in the baseline design:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Index(['sse_tune.v_min', 'sse_tune.v_max', 'sse_tune.r', 'sse_tune.chord',\n",
+       "       'sse_tune.theta', 'sse_tune.Rhub', 'sse_tune.Rtip',\n",
+       "       'sse_tune.hub_height', 'sse_tune.precone', 'sse_tune.tilt',\n",
+       "       ...\n",
+       "       'rotorse.rs.strains.axial_root_sparU_load2stress',\n",
+       "       'rotorse.rs.strains.axial_root_sparL_load2stress',\n",
+       "       'rotorse.rs.strains.axial_maxc_teU_load2stress',\n",
+       "       'rotorse.rs.strains.axial_maxc_teL_load2stress',\n",
+       "       'rotorse.rs.tip_pos.tip_deflection', 'rotorse.rs.tot_loads_gust.Px_af',\n",
+       "       'rotorse.rs.tot_loads_gust.Py_af', 'rotorse.rs.tot_loads_gust.Pz_af',\n",
+       "       'rotorse.stall_check.no_stall_constraint',\n",
+       "       'rotorse.stall_check.stall_angle_along_span'],\n",
+       "      dtype='object', name='variables', length=4691)"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Lets analyize the baseline design!!\n",
+    "baseline_turb = pd.read_csv(os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"outputsCh1/stage-0-baseline.csv\"), index_col=0)\n",
+    "# Open the CSV file shown above so explore the various variables output from WISDEM/WEIS\n",
+    "\n",
+    "print(f'there are {len(baseline_turb.index)} variables in the baseline design:')\n",
+    "\n",
+    "baseline_turb.index "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "31f7469d",
+   "metadata": {},
+   "source": [
+    "WEIS outputs a comprehensive set of variables about the wind turbine analysis - you can see there are hundreds of them!\n",
+    "\n",
+    "Here are the key variables we'll focus on for understanding the baseline design:\n",
+    "- `rotorse.rp.powercurve.V` → Wind speed (m/s)\n",
+    "- `rotorse.rp.powercurve.Cp_aero` → Power coefficient \n",
+    "- `rotorse.rp.powercurve.Ct_aero` → Thrust coefficient\n",
+    "- `rotorse.rp.powercurve.P` → Power (W)\n",
+    "- `rotorse.rp.powercurve.T` → Thrust (N)\n",
+    "- `rotorse.rp.powercurve.pitch` → Pitch angle (deg)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "a337aa4f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_comparison_plot(baseline_turb, label='IEA22MW')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cd55587e",
+   "metadata": {},
+   "source": [
+    "## Something Looks Off......\n",
+    "\n",
+    "At first glance, the power curve looks reasonable, but notice the Cp values. The IEA 22MW is known to achieve ~0.49, but our plot shows ~0.45. What's happening?\n",
+    "\n",
+    "`The IEA 22MW is highly flexible with significant blade torsion. Our analysis uses CCBlade, which assumes rigid blades and misses the flexibility effects. For accurate performance, we'd need OpenFAST with BeamDyn (the high-fidelity blade model), but that's computationally expensive.`\n",
+    "\n",
+    "For this initial design and optimization phase, CCBlade gives us the right trends even if the absolute values aren't perfect."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4c887bf2",
+   "metadata": {},
+   "source": [
+    "## Converting the IEA 22MW to a 20MW\n",
+    "\n",
+    "Now let's create our 20MW turbine by scaling the IEA 22MW. We will calculate a new diameter to ensure the same specific power (W/m²) in the new 20 MW rotor.\n",
+    "\n",
+    "The power equation for a wind turbine rotor is:\n",
+    "\n",
+    "$$P = \\frac{1}{2} \\rho A V^3 C_p$$\n",
+    "\n",
+    "Where:\n",
+    "- $P$ = power (W)\n",
+    "- $\\rho$ = air density (kg/m³)\n",
+    "- $A = \\pi D^2/4$ = rotor swept area (m²)\n",
+    "- $V$ = wind speed (m/s)  \n",
+    "- $C_p$ = power coefficient\n",
+    "\n",
+    "For scaling, we assume $\\rho$, $V$, and $C_p$ remain constant. This gives us:\n",
+    "\n",
+    "$$\\frac{P_{20MW}}{P_{22MW}} = \\frac{A_{20MW}}{A_{22MW}} = \\frac{D_{20MW}^2}{D_{22MW}^2}$$\n",
+    "\n",
+    "Solving for the new diameter:\n",
+    "\n",
+    "$$D_{20MW} = D_{22MW} \\sqrt{\\frac{P_{20MW}}{P_{22MW}}} = 284.0 \\times \\sqrt{\\frac{20}{22}} \\approx 270.0 \\text{ m}$$\n",
+    "\n",
+    "Here's the updated geometry file with the scaled values:\n",
+    "\n",
+    "``` yaml\n",
+    "assembly:\n",
+    "    turbine_class: I\n",
+    "    turbulence_class: B\n",
+    "    drivetrain: direct_drive\n",
+    "    rotor_orientation: Upwind\n",
+    "    number_of_blades: 3\n",
+    "    hub_height: 170.0\n",
+    "    rotor_diameter: 270.0 # 284.0\n",
+    "    rated_power: 20000000.0 # 22000000.0\n",
+    "    lifetime: 25.0\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7a442bcb",
+   "metadata": {},
+   "source": [
+    "# Stage 1: Rotor Optimization\n",
+    "\n",
+    "Now that we have a baseline and the new 20MW geometry file, let's optimize the rotor design. \n",
+    "\n",
+    "We'll use WISDEM for this rotor optimization rather than the more complex OpenFAST+Controller approach. This gives us a quick first-pass optimization that's computationally efficient. This approach also demonstrates how we systematically use multiple tools in the optimization process, avoiding a single massive optimization problem that can be difficult to solve."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "6de3bf63",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Setting up file paths, and defining the WEIS overide for this stage\n",
+    "stageFolder = \"stage-1-aeroStruct\"\n",
+    "\n",
+    "fname_wt_input = os.path.join(WORKSHOP_REPO, \"2_models\", \"new-20-270-RWT_Floater_v2p0.yaml\")\n",
+    "fname_modeling_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-1-aeroStruct_modeling.yaml\")\n",
+    "fname_analysis_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-1-aeroStruct_analysis.yaml\")\n",
+    "\n",
+    "# fname_wt_input = os.path.join(WORKSHOP_REPO, \"..\", \"00_setup\", \"ref_turbines\", \"IEA-22-280-RWT_Floater.yaml\")\n",
+    "# fname_modeling_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-0-baseline_modeling.yaml\")\n",
+    "# fname_analysis_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-0-baseline_analysis.yaml\")\n",
+    "\n",
+    "# We dont have analysis, and modeling options overrides in WISDEM\n",
+    "# analysis_override = {}\n",
+    "# analysis_override['general'] = {}\n",
+    "# analysis_override['general']['folder_output'] = 'outputsCh1'\n",
+    "# analysis_override['driver'] = {}\n",
+    "# analysis_override['driver']['max_iter'] = 1 # only run one iteration for this demo, we have precomputed the solutions for you :)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "69f2e17b",
+   "metadata": {},
+   "source": [
+    "## Examining the Input Files\n",
+    "\n",
+    "### Google Colab Users:\n",
+    "1. Go to the file browser on the left\n",
+    "2. Navigate to the cloned repository\n",
+    "3. Open the YAML files to examine the configuration\n",
+    "\n",
+    "## Analysis Options:\n",
+    "The analysis options file defines what we want to optimize and the constraints we need to satisfy. Here are the key sections:\n",
+    "\n",
+    "```yaml\n",
+    "\n",
+    "design_variables:\n",
+    " \n",
+    "    blade:\n",
+    "        aero_shape:\n",
+    "            twist:\n",
+    "                flag: False # Flag to optimize the twist\n",
+    "                inverse: True # Flag to determine twist from a desired angle of attack\n",
+    "                inverse_target: 'max_efficiency' # Twist generates angles of attack # corresponding to 'max_efficiency' or 'stall_margin'\n",
+    "                n_opt: 10 # Number of control points along blade span. During inverse design, # twist is smoothened with a spline with these\n",
+    "                max_decrease: 0.08722222222222221 # Maximum decrease for the twist in [rad] at the n_opt locations. Only used if flag is set to True\n",
+    "                max_increase: 0.08722222222222221 # Maximum increase for the twist in [rad] at the n_opt locations. Only used if flag is set to True\n",
+    "                index_start: 2 # Lock the first two DVs from blade root\n",
+    "                index_end: 10 # All DVs close to blade tip are active\n",
+    "\n",
+    "            chord:\n",
+    "                flag: True # Flag to optimize the chord\n",
+    "                n_opt: 10 # Number of control points along blade span\n",
+    "                max_decrease: 0.4 # Minimum multiplicative gain on existing chord at the n_opt locations\n",
+    "                max_increase: 1.5 # Maximum multiplicative gain on existing chord at the n_opt locations\n",
+    "                index_start: 1 # Lock the first DV from blade root\n",
+    "                index_end: 9 # All DVs close to blade tip are active\n",
+    "            af_positions:\n",
+    "                flag: True\n",
+    "                af_start: 4\n",
+    "        structure:\n",
+    "            - layer_name: spar_cap_ss\n",
+    "              n_opt: 8               # Number of control points along blade span\n",
+    "              max_decrease: 0.2      # Maximum nondimensional decrease at the n_opt locations\n",
+    "              max_increase: 5.       # Maximum nondimensional increase at the n_opt locations\n",
+    "              index_start: 1         # Lock the first DV from blade root\n",
+    "              index_end: 7           # The last DV at blade tip is locked\n",
+    "            - layer_name: spar_cap_ps\n",
+    "              n_opt: 8               # Number of control points along blade span\n",
+    "              max_decrease: 0.2      # Maximum nondimensional decrease at the n_opt locations\n",
+    "              max_increase: 5.       # Maximum nondimensional increase at the n_opt locations\n",
+    "              index_start: 1         # Lock the first DV from blade root\n",
+    "              index_end: 7           # The last DV at blade tip is locked\n",
+    "            - layer_name: te_reinforcement_ss\n",
+    "              n_opt: 8               # Number of control points along blade span\n",
+    "              max_decrease: 0.2      # Maximum nondimensional decrease at the n_opt locations\n",
+    "              max_increase: 5.       # Maximum nondimensional increase at the n_opt locations\n",
+    "              index_start: 1         # Lock the first DV from blade root\n",
+    "              index_end: 7           # The last DV at blade tip is locked\n",
+    "            - layer_name: te_reinforcement_ps\n",
+    "              n_opt: 8               # Number of control points along blade span\n",
+    "              max_decrease: 0.2      # Maximum nondimensional decrease at the n_opt locations\n",
+    "              max_increase: 5.       # Maximum nondimensional increase at the n_opt locations\n",
+    "              index_start: 1         # Lock the first DV from blade root\n",
+    "              index_end: 7           # The last DV at blade tip is locked\n",
+    "\n",
+    "# figure of merit\n",
+    "merit_figure: LCOE\n",
+    "\n",
+    "constraints:\n",
+    "    blade:\n",
+    "        stall:\n",
+    "            flag: False # Constraint on minimum stall margin\n",
+    "            margin: 0.12 # Value of minimum stall margin in [rad]\n",
+    "        chord:\n",
+    "            flag: True # Constraint max chord to its default value (4.75 m)\n",
+    "            max: 8. # Max chord value\n",
+    "        chord_slope:\n",
+    "            flag: True # Constraint to enforce monothonically decreasing chord after max chord\n",
+    "        root_circle_diameter:\n",
+    "            flag: False # Constraint for the minimum blade root circle diameter\n",
+    "            max_ratio: 1.2 # The recommended value can be up to 20% larger than the actual\n",
+    "        moment_coefficient:\n",
+    "            flag: False # Constraint on maximum blade root flapwise moment coefficient\n",
+    "            max: 0.20 # Lowering this value will lead to low induction rotors\n",
+    "        strains_spar_cap_ss:\n",
+    "            flag: True         # Flag to impose constraints on maximum strains (absolute value) in the spar cap on the blade suction side\n",
+    "            max:    3500.e-6   # Value of maximum strains [-]\n",
+    "            index_start: 1     # Do not enforce constraint at the first station from blade root of the n_opt from spar_cap_ss\n",
+    "            index_end: 7       # Do not enforce constraint at the last station at blade tip of the n_opt from spar_cap_ss\n",
+    "        strains_spar_cap_ps:\n",
+    "            flag: True         # Flag to impose constraints on maximum strains (absolute value) in the spar cap on the blade pressure side\n",
+    "            max:    3500.e-6   # Value of maximum strains [-]\n",
+    "            index_start: 1     # Do not enforce constraint at the first station from blade root of the n_opt from spar_cap_ps\n",
+    "            index_end: 7       # Do not enforce constraint at the last station at blade tip of the n_opt from spar_cap_ps      \n",
+    "        tip_deflection:\n",
+    "            flag: True\n",
+    "            margin: 1.4175\n",
+    "\n",
+    "driver:\n",
+    "    optimization:\n",
+    "        flag: True          # Flag to enable optimization\n",
+    "        tol: 1.e-6          # Optimality tolerance\n",
+    "        max_iter: 1000      # Maximum number of iterations (SLSQP)\n",
+    "        solver: SLSQP       # Optimization solver. Other options are 'SLSQP' - 'CONMIN'\n",
+    "        step_size: 1.e-3    # Step size for finite differencing\n",
+    "        form: central       # Finite differencing mode, either forward or central\n",
+    "\n",
+    "recorder:\n",
+    "    flag: True              # Flag to activate OpenMDAO recorder\n",
+    "    file_name: log_opt.sql  # Name of OpenMDAO recorder\n",
+    "\n",
+    "\n",
+    "```\n",
+    "\n",
+    "## Modeling Options:\n",
+    "The modeling options file controls which WISDEM modules are active during the optimization:\n",
+    "\n",
+    "```yaml\n",
+    "General:\n",
+    "    verbosity: True  # When set to True, the code prints to screen many infos\n",
+    "\n",
+    "\n",
+    "WISDEM:\n",
+    "    RotorSE:\n",
+    "        flag: True\n",
+    "        spar_cap_ss: spar_cap_ss\n",
+    "        spar_cap_ps: spar_cap_ps\n",
+    "\n",
+    "    DriveSE:\n",
+    "        flag: False\n",
+    "    TowerSE:\n",
+    "        flag: True\n",
+    "    FloatingSE:\n",
+    "        flag: False\n",
+    "    BOS:\n",
+    "        flag: False\n",
+    "\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97a12e68",
+   "metadata": {},
+   "source": [
+    "## 1.1: Configuration Check\n",
+    "\n",
+    "**Before running the optimization, please verify these settings:**\n",
+    "\n",
+    "1. **Output path**: Update the analysis options file to set output path to `outputsCh1`\n",
+    "2. **Iteration limit**: Set `max_iter` to `1` (we'll use precomputed results for this demonstration)\n",
+    "\n",
+    "These modifications ensure the demo runs quickly while preserving your existing output files."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "441cb849",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/openmdao/visualization/n2_viewer/n2_viewer.py:115: OpenMDAOWarning:attempt to get argmin of an empty sequence\n",
+      "\u001b[00mOptimizeWarning: /Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/openmdao/drivers/scipy_optimizer.py:487\n",
+      "Unknown solver options: rhobeg, catol, adaptive\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Iteration limit reached    (Exit mode 9)\n",
+      "            Current function value: 0.43830741633150294\n",
+      "            Iterations: 1\n",
+      "            Function evaluations: 2\n",
+      "            Gradient evaluations: 2\n",
+      "Optimization FAILED.\n",
+      "Iteration limit reached\n",
+      "-----------------------------------\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "RuntimeWarning: /Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/wisdem/towerse/tower.py:369\n",
+      "invalid value encountered in divide\u001b[00mDeprecationWarning: /Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/jsonmerge/__init__.py:27\n",
+      "Accessing Draft4Validator.resolver is deprecated as of v4.18.0, in favor of the https://github.com/python-jsonschema/referencing library, which provides more compliant referencing behavior as well as more flexible APIs for customization."
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "WISDEM run completed in, 458.6125340461731 seconds\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "wt_opt, modeling_options, analysis_options = run_wisdem(\n",
+    "        fname_wt_input, fname_modeling_options, fname_analysis_options\n",
+    "    )\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "43f69079",
+   "metadata": {},
+   "source": [
+    "## 1.2: Aero-struct Outupts\n",
+    "\n",
+    "Now let's examine the optimization results! We've prepared two datasets for comparison:\n",
+    "\n",
+    "1. **Precomputed optimization results** - The full optimization has been completed and results are stored in the `outputs` folder\n",
+    "2. **Baseline comparison data** - We also ran the same case without optimization to show the \"before and after\" effects\n",
+    "\n",
+    "This comparison will help us understand how the optimization improved the rotor design."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "7385cf21",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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fzxBU+fTTT1Vmjyk+Tx07dlRBOJmSOGTIEFVr6V7mz5+fZarlvb7HMs1OMs8KypARJRlSMq1OgkS9evXKkhllYCg0byhKX1CGel/BwcGF8nxERETmgkEpIiIq0eSqaYapSP/++2/G+rNnz6o/jiVjoaDkOUaPHp1RINqQtTNq1KiMq78V5bQxmf4jRbMlgCC1iKRYc2byx7UEimRqnQRnioJcFfDtt9/OuAqeFMnOPtVKMm8kMyS/VyK8HylULVeek/cmgYXM0/ikqPS0adPU7YkTJ+aYmWSKAJ749ddfVf0og+vXr6urPRqu1lZYpBi3BOQkq0eCKdmLk0tm0OLFi4v88ySvIcX55bHSB/Izc4ah3Ja2SAHwF198Ub1O9u/xzJkz1XfXQIJUL7/8MmxsbFBQ8n4MwU0JyOV01T0D+Rx7eHjg+++/x/jx4++aGinT8yTr6d13381Y9/HHH6sgVvZgpGSOLViwQN2+31UgiYiILA0LnRMRUYkmf+DK5evlj3/J1KhSpYr6A1aCRnKVuPr16+Onn34q0GvIlblkml69evXUVCkJfEgARoIyEiwxBEWKkmTXSLbIhg0b1B+25cuXh6+vr7r0vExRNBRbLuwsnMwkkCB/YEudHAl+yB/tMiVKggsyZc1wNbn27dsX6utKf8sxlOeVQIe8dzkOUuDbMD3z6aefxogRI2AOGjVqpD4zUuxagj6VK1dW2TjymZEsKum/sWPHFtrrSUB01apV6rsg2XvSP3I1OvkeSOFxKdwtAVpDUKaoPk+BgYHYtWuX+mxIlqIcL/mMSMBMviuSVWjIeJKpbYaMMjFs2DB8/vnnKrAm0wvlCoqS9SVXU5SpbxLQe9B6VQbynPL/waFDhxAeHq7qfBmCYdlJbajVq1erLDQJNn322Wfq8VLwXqYYSr/KezJMWxTy/qSY+rhx41SdKSnML59RCbLJd6R27doqwEVERFScMFOKiIhKNAlYSNaO/LEndWDkj0Upijxp0iSVRVMYGRZ2dnbqD+IxY8aoPzIlQCV/xEtmzqZNmwp0Zbm8kqCGXL5eslFkOpsEDw4cOKD+uK5bt67K7JBMMcloKkrTp09XmVCSYSLvW6bzSUBK/oh/5plnVFBEpnIVNgnsSEbPhAkTVN9L8EIyptq0aYMffvhBZbSYQ5aUgRynN998UwUnJFgh0w4lUCWZPxLcLGzynBL0ks+9BKTkeyB1mOQ7IcFECZQY4/MkQWEJ+sjzSnBKPiMnT55U3xkJUElgTArBS/BKvlcG8jobN27E8OHD1X4SyJHC8B999FGWLK+CypwZJVlrtra2ue4rU3IluD158mQVKJM+PXLkiGqXBADnzZunglAGkjEpheHlMynTGKUfJAgngWuZWin9KfWqiIiIihOdlttlSoiIiIiIiIiIiIoIM6WIiIiIiIiIiMjoGJQiIiIiIiIiIiKjY1CKiIiIiIiIiIiMjkEpIiIiIiIiIiIyOgaliIiIiIiIiIjI6BiUIiIiIiIiIiIio2NQioiIiIiIiIiIjI5BKSIiIiIiIiIiMjoGpYiIiIiIiIiIyOgYlCIiIiIiIiIiIqNjUIqIiIiIiIiIiIyOQSkiIiIiIiIiIjI6BqWIiIiIiIiIiMjoGJQiIiIiIiIiIiKjY1CKiIiIiIiIiIiMjkEpIiIiIiIiIiIyOgaliIiIiIiIiIjI6BiUIiIiIiIiIiIio2NQioiIiIiIiIiIjI5BKSIiIiIiIiIiMjoGpYiIiIiIiIiIyOgYlCIiIiIiIiIiIqNjUIqIiIiIiIiIiIyOQSkiIiIiIiIiIjI6BqWIiIiIiIiIiMjoGJQiIiIiIiIiIiKjY1CKiIiIiIiIiIiMjkEpIiIiIiIiIiIyOgaliIiIiIiIiIjI6BiUIiIiIiIiIiIio2NQioiIiIiIiIiIjI5BKSIiIiIiIiIiMjoGpYiIiIiIiIiIyOgYlCIiIiIiIiIiIqNjUIqIiIiIiIiIiIyOQSkiIiIiIiIiIjI6BqWIiIiIiIiIiMjoGJQiIiIiIiIiIiKjY1CKiIiIiIiIiIiMjkEpIiIiIiIiIiIyOgaliIiIiIiIiIjI6BiUIiIiIiIiIiIio2NQioiIiIiIiIiIjI5BKSIiIiIiIiIiMjoGpYiIiIiIiIiIyOgYlCIiIiIiIiIiIqNjUIqIiIiIiIiIiIyOQSkiIiIiIiIiIjI6BqWIiIiIiIiIiMjoGJQiIiIiIiIiIiKjY1CKiIiIiIiIiIiMjkEpIiIiIiIiIiIyOgaliIiIiIiIiIjI6BiUIiIiIiIiIiIio2NQioiIiIiIiIiIjI5BKSIiIiIiIiIiMjoGpYiIiIiIiIiIyOgYlCIiIiIiIiIiIqNjUIqIiIiIiIiIiIyOQSkiIiIiIiIiIjI6BqWIiIiIiIiIiMjoGJQiIiIiIiIiIiKjY1CKiIiIiIiIiIiMjkEpIiIiIiIiIiIyOgaliMzQd999B51Ol7FYW1vD398fw4YNw7Vr11AcpKWl4YcffkCnTp3g5eUFGxsb+Pj4oGfPnvj999/V9qKSlJSEF154Ab6+vrCyskL9+vXV+ps3b2LAgAGqHdLvffv2Vevl9tSpU/P1GpcuXVKPk2NZlH766SfMmTMnX49JTk5G9erVMWPGjLu2HTlyRH3OAgMDYW9vD2dnZzRs2BAzZ85U/ZNfZ86cga2tLQ4cOJDvxxIRERERUfHGoBSRGVu4cCF27dqFDRs24LnnnsOSJUvQunVrxMbGwpIlJCSgR48eGDJkiAoAffHFF9i4cSPmz5+PsmXL4rHHHlOBqaIir/fll19i8uTJ2L59uwqOiXfeeQcrVqzAxx9/rPpdAjFCbj/77LP5eg0JeMnjHn74YZhbUGrevHm4desWRo8enWX9119/jUaNGmHv3r149dVXsX79etUfcjzk2AwfPjzf7atatSqefPJJjBs3Lt+PJSIiKqjMJ/nutWzevFktcnvZsmVm0/Hr1q3L94kxIeOoXr16oXTp0urkkIeHBzp27IjFixerk1NF6Y033kD58uXVSdVSpUrd84RghQoVMHTo0Hy/xoOcMDRW30s/y3vN7sKFCxg1apQaGzk4OMDR0RG1atVS/ZX5pHNuYzsZu0l/rly58gHeDZEZ04jI7CxcuFCTr+fevXuzrH/zzTfV+h9//FEzZ2lpaVpcXFyu21988UX1Pr7//vsct585c0Y7fPhwkbXv2Wef1RwcHO5a36lTJ61GjRqaJXn44Ye1gICAPO+fnJys+fn5aRMnTsyyfufOnZqVlZXWrVs3LSEh4a7HJSYmaqtWrXqgNu7bt08d7x07djzQ44mIiB7Url27siw9evRQY4Ds6yMjI7VNmzap31dLly41mw4fOXKkalN+xmBDhw5Vj5H3KmPGLVu2aKtXr9bGjRunubq6anPmzCmy9q5cuVK99uTJk7Xt27dnjGXlNWX9p59+qsYcR44cUesPHDignTt3Lt+vI8csKChIM6e+N7x/Ozs77erVq1nW//7775qTk5Mas3344Yfa33//rf3zzz+qX+rWravVr18/T2O7qVOnapUrV1bjMqLigkEpIgsKSq1du1atf++999T9+Ph4FVyoUKGCZmNjo5UtW1Z76aWXtFu3bmU8ZsKECWoAkpKSkrFu1KhR6nlmzpyZsS48PFzT6XTa3LlzM9bJAO2VV17J8vxjxozRYmJisrRLnkt+cX/xxRda9erV1b5yOyfXr19X27t27Zrn/rh8+bL25JNPat7e3pqtra16jY8++khLTU3Nsp/8gn7nnXe0atWqqf28vLzUwCw0NDRLW7Mvhv7Ovsjg1PCYKVOmZHktGWw899xzmr+/v3o/vr6+2iOPPKKFhISo7RcvXsx47uwBt4EDB2Z5L5999lmWfQyD4p9++kl7/fXX1XO7uLhoHTt21E6dOpWxX9u2bXNs97389ttvap/jx49nWd+zZ0/N2tpau3LlSp6OiQyWZNC0fPlyrU6dOmoAFhgYqH3yySc57i/BvqeffjpPz01ERFRUhgwZooIDOSloUCo2NlYzdWDkgw8+UPtPmzYt13HYtm3btKLy7rvvqte/ceNGnk4ImrMHCUo1adJEGzBgQJZ1Fy5cUJ+5Bg0aaLdv384xkCjjs7wEpWScKeO1xYsX56tdROaMQSkiCwpKyR/8sv6rr75Sv8AksCO/mCSD6q+//lKBGsMvPUO2y/r169Vj5KyUgQRCZGDQuXPnjHW//PKL2u/EiRMZAys5ayOBndmzZ6szOvL6bm5uWocOHdTrG8jjJPtGzvRIIGXjxo3asWPHcnxvsl32zy1olZ0ElOS5JYgzf/589X4MQTXJuDKQAJVk+cj7l4HYhg0btAULFqjH1qxZMyNzK6ezpPILXn5Kv1WsWDHLWdOcglISkJJAUea+kf575plntJMnT+YalJJAkPSfBHEWLVqkjpkE/fR6vTrzlX1QLMFACcZJMHLJkiVa+fLltSpVqmQEGOX5WrZsqZUpUybL2d57kTb6+PhkWSfP5+joqDVt2lTLKxksSd9Km7799ltt3bp1qq3SbjkDmJ0cK+mvzJ8bIiIicwxK3e+kkOHEUK1atVQWUvPmzdW44oknnsj1ZJbhd6e8voGMtQwn/+Tkjru7u9aoUSP1+oa25nTyScYYOUlKStI8PDzUOC+vv28jIiLU72g58Sgn2eQEk7z37FnT8nyff/65Vq9ePc3e3l4rVaqUOhl3/vz5LO8ve1ulH3I7IZhTnwg5uTp+/HjVFjmBJ2PA7t27Z4yxcutjCbg9//zzanwi70X6VcZXkiVuYBifyVhl1qxZah/5PDRr1izLGCq/fW/I+pJ9ZNyWmWHcer8xWl5POEpftG7d+r7PRWQpGJQiMuOg1O7du9Uv0ujoaG3NmjXql7IMjiSIYgg2Zc52yhxcksCVYcAjv9DffvvtjICKbH/ttdfUAMow6JCsHxmQGEyfPl0FS7IHxpYtW6YeL0EIA7kvwZabN2/e973NmDFD7S/tzwvJBJP99+zZk2W9DKAks+v06dPqvgRtZL/MZ5qEtF/Wz5s3774DUsMAM7vsAx8J7MhgxxDAy0lOQSkJIkpmlSHYlXmwIgM8Q/8ZBsUSPMvs119/vWtQk9/pe5KxJMG7zOTzJM+b/czevchrSv8fOnQoy3oJdEpmXvazxV9//bV6jcwDSiIiInMMSt3vpJBhzCABoHLlyqkpafJYCVDlJyg1YsQIdVJITnDJ42WsJ+MkeT4h09oeffTRjN/9hiWnafZCTkAaxnh5IRn3ckJR+kNObMrJMjnRKSc8s49BZJwoYx8JoskYTgJnEvwqXbp0Rpa4BGWGDx+eMc4zTLHL6YSgIYs9e59ERUWpsZi0Scauf/75pxrbSaa+nPQ0yN7HEpCSYyHP9+WXX6oThpI9L8E+yZrPPj6TYyzjIZluJ4ucMJSgoCGTKb99L6S9UgpBxu2ZVa1aVfVTXuTlhKNkw8kYPfPMCCJLZm3qmlZElLtmzZpluV+nTh1VpFuKVkphcJG9OKQUpX7mmWfwzz//qOLoUkSxefPm+Pvvv/Hmm2+qoulSJFEKWX/00Ueq0LcUZJTtciU8gzVr1qB27dqqEGVKSkrG+q5du2YUBO3evXvG+g4dOsDd3b3QD6e8z5o1a6JJkyZZ1sv7NhRIl4KR0l55X1LUM3N7pf1lypRR7X3xxRcLpU1//PEH2rdvjxo1auSruLscE2mDHJPMbZSi75999hl2796dpU979+6d5Tnq1q2rfl6+fPmuz0ZeBQcH46GHHkJhkOKc9erVy7Ju0KBB6jMmV9tr1apVxnopaC+kkKdc+Y+IiMhcybjjxx9/zLgvhbkff/xxdSGQzL9/5aq0S5cuVWOgB7Fjxw506dIly8VAMl8gpVKlSmrMJ/Lye//KlSvqp1xBNy++//57ddXdX3/9VY0fRefOndWVd1977TX1+1zuy/hELoYya9YsjB8/PuPxcvEdGYPNnj0bH3zwARo0aKCuFi3kwilydWUh67y9vaHX6+/7PqTA9/Hjx9VrZx6X9u/f/56Pk4LkUghcHitF1oWMb6Wg+IQJE9S4V46rgYuLixo7yrEVcqEdGWvKGE+uxJzfvhdygZsqVaqo/st+XAyF3e9H2ijjWTs7u1xfV66KLFepluPSrVu3PD0vkTnj1feIzNiiRYvUAOjgwYMqmCADh5YtW6ptERER6qom8ks+MwkYSRBGthvIL3X5xSVX7ZPgkwyePD091YBB7l+8eFEtmX/537hxQ72ejY1NlkV+icsJqvDw8CyvK1dTyQvDQEFeLy/kfeT03DJ4MGw3tPf27dvqCjPZ2xwSEnJXewsiLCwsY9CVV9JOCUR9+umnd7VPglIiexvlGGUmAxQRHx//wG2Xx9rb22dZJ4NGCZTl9ZgYyOcst3WZP3/C8JoFaTsREZEx3OukUGZyMu5BA1LCEASZOHGiOnlm7N+RcmLPyckJjz76aJb1hhOecjJNSPBGxpdPPfWUGssYFvmdLyenpO2FRfpDAl2Zx6R5IW2UE4YyPszcRsPJvi1btmTZX4J/hoDUvY5xfshY3XASrihlPtFHVBwwU4rIjEkmTuPGjXPcJgEL+WUrAZLMgSkJGEkQJnM2jJwpkiyprVu3qgHGlClTMtb/9ddfGWfU5H7mQIWcXfr2229zfH3D2S8DGazkhQwYJBAjl7PN6XK5Ob3P69ev5/iLP3M75Kfsu379+hyfR4JphUX6++rVq/l6jAxcZfDz9NNPY+TIkTnuk9czmwUh/SRndjOTdsmxl4GgvK+8Btzkc5bbuuwBNcNrZv/cEBERmZu8nhTK6wm53MydO1f9zv3ll19UppGcwJGM9A8//FBl3OTXg5z4k8BS9jGcBD3kxGfmE38yvjRkDmVXsWJFFBYZ1xreR35IG3///Xc1xsyJsU785dRH8n7ye+LvXniij4obZkoRWShDAClzern47bffVEZU5gCTnIlzdXVVKdESNJBUbCFnoSQLS9K2JV3YkH0kevbsifPnz6tf2hIYy75UqFDhgdotg59nn30Wf/75p8oEy4m8rmRpGd7niRMn1HSwzOSxMoiSIJehvTJ4Sk1NzbG91apVQ2GRs26bNm3C6dOn8/wYyUSStkp/y9m4nNqYfYCUFzKIys8ASqbOSf9mN2nSJDXglCmfSUlJd21PTk5Wg73MJEX+8OHDWdb99NNPKgAoqeWZXbhwQaXtF+ZxICIiMqXcTsjJ7+bExMS71mfPIpYspWnTpuHUqVNqfCZlCSSzXUoRPAgZS3h4eGDVqlXqd/r9yLjDEHDKLDQ0VJ34zHziT96rlHyQDP7si5xoNOWJP0MbZSpkTu2TZfjw4YXWxvyc+BMSaJR+lmNbGHiij4obBqWILJQEluSXnMz5lwGNTMOTOf3Dhg1Tc/olIydzJkzbtm0zsqJknryQqYAycJLsqexp0mPHjlUBhDZt2qjnleeXxy9YsEDVVdizZ88Dt12eT9ou6eFPPvkkli1bhm3btmHFihV46aWXVC0rwxklqbPg5+en0qylnoG0YcyYMZg3b56qzyQp3kLm/0uwSKbCvf322ypjSt6X1EuQ15HnLizy/DLwkL755JNPVPr78uXL8fzzz6uBZW5kX6krIDUYvvvuO5XuLoGejz/++IHT/6XOmAweZSD777//Yt++fffcv127djh69Cji4uKyrJe6Y/IccpxlWqf0r6S6y305YytBy+xZcxLElCkOCxcuVP0taf1SA+KNN95QQbjMZCAm9RSKou4YERGROZETd4aTawYyVoiJicn1MZJhI+OVgQMHqpNeht/T+cngkSwhGRfKWOSdd97JcR8ZM0gtK8OJP2lT9qCS4aSh4QSnnPiTwJVMF8vppJqMRQqLjOXOnDmTUTs1r6SNx44dU2PcnNqY+cRrXuU3e0pO/MlJuOxkLCsBSBnjRkZG3rVd+jbzOPV+JxwNr5G5RhaRJeP0PSILJWesZBAhhR0lKPDee++pQIkEo95///2MX6QGEnSSAEjm4JPsI8WosxeTFPLLUwJFM2bMwFdffaWCRDKdT1KQZd8HzZQypB2vXbsWixcvVkGjESNGICoqSgUsZOAgwQ/DWUI5Y7Zz506VySOL7Cdp4jNnzsxSbFMCb6tXr1aBnx9++AHTp09XqeeSFi8BucIcMEmQTAJAMg1S+kfOfEo7pS/lDGVuZPAgGV8yUJTAjQwMpZilpOgb6krllwToJGPp9ddfVwOdO1dVzXV/KUQu7Zb+NxQ1NZAsKcmqkyCZTCOQs7YywJXAnzxu1KhRWfaXIJMEQeX5zp49qwZ8EnDMXLBVyIBXAoS5DZCJiIiKExmLSdmEt956S41BJONbLmji5uaWZb+mTZuqYIpkUMsY6OTJk2oMIyeKDCd3DOMX+b0sARsZ78j+UkMzJ1LQW55HfjfLWEV+f5crV06NEaSMg4zp5GSmnJgcPHgwPv/8cwwZMgSXLl1SryXZUDKOlHGJYWwo+8qJN/mdLye/5KScjBOlvILsL48rrIvJyElRmc7Yp08fVWtLxiUSoJETZdJXhgz5nE4Yyni2RYsWePnll9WJVbnIjLyvdevWYf78+fmuB5rfvpcTfzKGlaCa4aSpkBPCP//8M5544gk1dpLxlJxAFvLZkMfI2K1fv34ZrysnO+VkoZwolEzzzOU85ESfZLkV5tiWyKRMffk/IiIyrp49e6rLIBeEXHL54YcfztO+CxYsUJd2vnnzZoFek4iIqKCGDBmififlZNOmTXJWR1u6dGmW9RcvXlTrFy5cmLGubdu2Wq1atXJ8nsTERO1///ufVq5cOc3BwUHte+jQIfW7U17fYOLEiVrjxo01d3d3zc7OTqtYsaI2btw4LTw8PMtzPfvss5q3t7em0+lUO6Q997Nq1Sr1e1oeZ21trV6jffv22vz589VzGkRERGgvvPCC5uvrq/aTNk6aNElLSEi46zm//fZbrWnTpqr/5H1VqlRJGzx4sLZv376MfaZMmaLaGBYWlqd+z94n4tatW9qYMWO08uXLazY2NpqPj496L6dOncrYR15DXiszec2XX35ZCwwMVI/z8PDQGjVqpE2ePFmLiYnJciw//PDDu9qS/Tnz2/eRkZGas7OzNnPmzBy3nz9/XnvppZe0ypUrq+MtfVizZk1t/PjxWZ5XxkuPPvqoVqpUqYzXNUhLS1N9Nnr06FzbQWRpdPKPacNiRERkTJLeLmfoJAMtc0H8/JBMOZlmKVe7uRepSSEZYnIWdvLkyQ/YYiIiIiLzN3r0aJUdLlnseb0IUH7Ic0vtLHl+mS5IVBywphQRUQkjwSSZ8pnT1fMKW1BQkKo19corrxT5axERERGZkpRnkNpbcuGhovDuu+/imWeeYUCKihVmShEREREREREVAskiv3XrVpaLDhUGeU6pnSoF0318fAr1uYlMiUEpIiIiIiIiIiIyOk7fIyIiIiIiIiIio2NQioiIiIiIiIiIjM4aJUxaWhqCg4Ph4uJSJFdEICIiIsslFyWOjo5G2bJlodfz3N29cExFREREBR1TlbiglASkypUrZ+pmEBERkRmTK0f6+/ubuhlmjWMqIiIiKuiYqsQFpSRDytAxrq6upm4OERERmZGoqCh18sowXqDccUxFREREBR1TlbiglGHKngSkGJQiIiKie40XiGMqIiIiKroxFYslEBERERERERGR0TEoRURERERERERERsegFBERERERERERGV2JqylFRESUV6mpqUhOTmaHFSM2NjawsrIydTOIiIhKFI6pih+bQhpTMShFRESUjaZpCAkJwe3bt9k3xVCpUqVQpkwZFjMnIiIqYhxTFW+lCmFMxaBUITsXGgM7az2c7KzhZGcFO2uejSUisjSGgJSPjw8cHR0ZvChGA+O4uDiEhoaq+76+vqZuEpkLTQMirwKpSaZuCRUF17KAjQP7lsgEOKYqnrRCHFMxKFXIBny1C+Ex/w1obK0kQGWlglTOdxZ1294azrbpP9O3WcHZzkbtm2U/w7521irYxUtUExEVfXq5ISDl6enJ7i5mHBzS/zCVQZQcY07lI4SdBtZNAC5uZWcUV+6BwIitgL2rqVtCVKJwTFW8ORTSmIpBqUImmVH2NnokJKep+0mpaUiKS8OtuILXJLHW67IFt9KDXfoCpMqR+fJytkPTQA80reiB8h7M1CAyFkMNKcmQouLJcGzlWDMoVYIlRgNbPgB2fwGkpQA6K8DW2dStosKWHAfcugj8+TrQ5zP2L5ERcUxV/DkWwpiKQalCtmNiB/UzJTUNsUmpiElMQWxiivoZk5DpdsZ62ScZsernnX2Ssu4vz6OeM01DZHyyWqhk+O3AVfWzjKu9Ck41q+ipAlWBXk7MmiMqYsxMLb54bEs4map37DfgrzeA6Ovp66r1ALpNB9wrmLp1VNgu7wQW9gAO/gDU6A1U7cI+JjIy/t4tvnSFkCDDoFQRsbbSw81BFpsCP1damqYCVRmBq0yBLvkpYysqXuSQXgyPwZ4LN3H46m2ERCVg1aFgtQhvl/QsKglSNavogUrezvzPnoiI6H5CTwLrXgUubftvWlf3mQxUFGcBLYBmLwG7Pwd+fxl4aRfg4G7qVhER0R0MSlkAvV4HF3sbtVDJE5+UigNXbmHPhQjsvngTh67cRlh0ItYcua4W4eVsiyYy1S9QglSeqOLjrD43RESFaerUqVi5ciUOHTr0wM9x6dIlBAYG4uDBg6hfvz6KwnfffYexY8fy6on0n4So/6bqaamAtQPQ+hWgxWjAxh77L9/EuqMhSE5NL79AxUuz8s+ih+dfQMRZ4I/XgP5fmbpJRFTCcUz1HwaliMycg60VWlb2UotISE7FwSu3sedihMqkkoCVFNeXwbQswt3RJkuQqnoZFwapiEqIoKAgNdD5448/EB4erq6G0rdvX7z11lv5Ktwu6dgrVqxQjzWYMGECRo8eXaD2lStXDtevX4eXV/r/aURFStLJjy5Nn6oXcyN9XfWeaqqe5lYOu85H4NONh7DrQgQPRDH2w25g3SMfoMbaR4Ejv6RP46vR09TNIiIzxzGVcTAoRWRh7G2s0LySp1pEYkoqDgdFqkyqPRdvYv/lW6qw/p/Hb6hFyDTShyrIdL/0QFXNsq6wYiYVUbFz4cIFNG/eHFWrVsWSJUtURtLx48fx6quvqiDV7t274eHh8cDP7+zsrJaCkCKYZcqUKdBzEOXJjePpU/Uu70i/71EJ6DETWqWO2HQ6FJ/+tFOd5BE2Vjr0rucHP/f0KwlR8SFZcDvORWDUFiv82fxlWO+cA6wZC5RvDjjxCqtElDOOqYxIK2EiIyOlXI/6SVQcJSanavsuRWifbTyrPf3NHq3mm39oAa+tybLUnrJeG7bwX23+5nPawSu3tOSUVFM3m8hsxMfHaydOnFA/LU23bt00f39/LS4uLsv669eva46OjtoLL7yg7gcEBGhvv/22NnDgQM3JyUnz9fXV5s6dm7G/bL9T3k4tcl9MmTJFq1evXsZ+Q4YM0fr06aO99957mo+Pj+bm5qZNnTpVS05O1iZMmKC5u7trfn5+2jfffJPxmIsXL6rnPHjwYMZzZH4tw7Jp0ya1PTExUXv11Ve1smXLqvfQpEmTjG0GCxcu1MqVK6c5ODhoffv21T766CPVlgc5xhwn5J3Z9lX8bU1b95qmTXXXtCmumvZuGU3b+pGWmhivrTsSrHWfszXj92HVyeu0KauOadduZf3OUPFxKzZRa/TOBnW8Z687ommfNU3/XPw6xNRNIyr2OKbimAp5GCfojRkAI6KiZ2utR6MAD4xsXxmLnmmCw1O6YOXIlpjYvTraV/OGi501ohNSsPFUKKb/cQp9P9+B+m9vwJBv/8UPuy+rK0cS0X80TUNcUopJFnntvLp58yb+/PNPvPTSS3BwyJrtIZlJTz75JH755ZeM5/zwww9Rt25dHDhwAJMmTcK4ceOwYcMGtW3v3r3q58KFC9VUO8P9nGzcuBHBwcHYunUrZs+eraYO9uzZE+7u7tizZw9eeOEFtUgKfE4++eQT9RqGZcyYMfDx8UH16tXV9mHDhmHHjh34+eefceTIETz22GPo1q0bzp49q7bLazzzzDPqfUutq/bt2+Pdd98tkR/hefPmqew4e3t7NGrUCNu23SnmnYvFixejXr166nLOMs1T+joiwoKnscln+9AS4NPGwJ47taNq9EbKi7uxwvkJdPlsD15cfAAnrkfBydYKI9pWxPbXOmBq71ooW4oZUsVVKUdbvNu3lrr92bYgnG/1IaCzAo6vAI4tN3XziEoUjqk4psoJp+8RlYArQdYvV0otL7StpIJOJ69HY7ea7heBfy/eRFRCCracCVPLkj1X8MEjdVHH383UTScyC/HJqaj51p8mee0Tb3eFo23eflVLkEYGezVq1Mhxu6y/desWwsLC1P2WLVti4sSJ6rZM95PAz8cff4zOnTvD29tbrS9VqtR9p9rJdMC5c+dCr9ejWrVqmDlzJuLi4vD666+r7RLwmjFjhnr+AQMG3PV4Nzc3tYjly5dj/vz5+Pvvv9Xrnj9/Xk1DvHr1KsqWLZtR12r9+vUqYPb++++roFbXrl2zvJedO3eqfUoSCThKcXcJTMmx/fLLL9G9e3ecOHEC5cuXv2v/7du3Y/DgweqY9+rVC9euXVPBw2effVbVErM4IUeBtROAoN3p9z2rIKnrDPx2uyq+WHAeV27GqdWu9tYY2jIQw1pUgLuTrWnbTEbTrbYvetQpo2pvvrwFWN3qFVhtmwmsfQWo0Apw9uHRIDICjqk4psqJ3tLO6hnI4Nba2rrIrtzzwCLOA5HXgMRoII0ZJ2SeQSoJOD3XpiIWDHkIB9/qgrUvt1KZVFJ7Ss4g9/l8O95be0JlahBR8WDIkJIC5kJqT2Um90+ePJnv561Vq5YKSBmULl0aderUyVJDSgqsh4aG3vN55Gp8EiT5/PPP0apVK7VOsrik3RJoMtSzkmXLli0qYCWkzTm9l5JGstSGDx+ugkoSgJwzZ44qKv/FF1/kuL/UF6tQoQJefvllNQ6TPh8xYgT27dsHixJ/G1j3P+DLNukBKRsnJLefgkX1f0Lb33SYtPyoCkh5ONnif92qYcfEDhjfuSoDUiWQZMTJOOd4cBS+Qn+gTB0g/ibw+9j0LDsiojzimKoYZUrl96yeQWRkpBq4duzYETdu3LmSirn4tisQm34WGtABdq6AnQtgf+fnXffd7t6ubhsWF3WpYqKiIgXPa5V1U8sjDf3x9poT+P1wML7edhHrj4fgvb510KZqetYEUUnkYGOlMpZM9dp5VblyZRVwkt+hma+YZ3Dq1Ck1pe5eV70zBKzyw8bG5q7nyGld2j1O1ISEhKB3794qqCKLgTxGglr79+9XPzMzFFzPzxTH4iopKUn1kSFbzKBLly4qaywnLVq0wOTJk7Fu3To19pKg4bJly/Dwww/DIsjn6fAS4O8pGeOu5Bp98XOpEfhkWyzCY9Knd5Z2tcPzbSphYJNyec46pOLJx8Ueb/WsiVeWHsbHmy7h4UGzUX5ZD+D02vQr8tW7O5OTiAoXx1T3ZlNCx1TW5nJWT8hZPamHIWf1pk+fnuvj5EzeoEGDVGeuXLkSZsXKFtBbA2mSYaIBiZHpS1QBnzNLQMst033n9HnxVPxIMNLJJz2l3Mnrv9uOnoC+aI65t4sdPh3YAP0alMUbK44h6GY8Bn/7L/o38MMbPWuqM81EJY388reEP2YlG0mm3smJHqkPlbmulAxQpH6QnNAxBJ4kUyYzuW+o4yRkEJSamlrk7U5ISECfPn3Ua8u4ILMGDRqoNkjApHXr1jk+vmbNmjm+l5IkPDxc9ZNkqWUm9+XY5xaUks/EE088oY5BSkqKGsR++umnub5OYmKiWgyiogoyuCmA64fTp+pd/VfdTfWsilW+YzHtuDci42+pdf7uDnixXSU82sgfdtYcJ1G6/g39sPpwsCpXMH5LCn5t+xr0m94F/vgfENgGcE2fJkxERYNjqqKVYKFjKmtLOqsnpIaEpOz/+OOP5lnIdPyJ9BTglIT0KXwJUUDinUXdjr5zX7ZFZrufbbv8FKlJQFxE+kIkGXgSmFLBKu/0xXA7p3XWdvnusw7VS+Ov8Z746M/T+H7XJSw/eA2bz4SpM4x96pd9oGwKIip6n332mQo2SI0l+R0p07KOHz+OV199FX5+fnjvvfeyTIOX+k+SVSUFzpcuXYq1a9dmbJepXf/884/KZLazs1NZVkVBTjRJEXR5LUO9K0OtKpm2JwXaJZg2a9YsNaCSAIwUV5cpgj169FDTz+Q9G97LX3/9VeLqSRlk/79Zznjm9v+1ZNRJ37311lvq8yJF5uVzInWlvvnmmxwfIycMp02bBpORgNPGd4F93wJaGtJsnLDF9xmMu9wct6/JDsmo6O2Eke0qo3f9srCxMnmVCjIz8n14v38ddJm9Bfsu38IPtftiSNl1QPABYPXLwJNLZSdTN5OIzADHVH2NNqaytqSzelLEVYJYUndK6knlhUnO6skvMxuH9KUghRMlLS8pJoeAVqb7sl1j7apiKSkWiAlNn5Ygi9xWgUkNiAtPX/JCpog6S6DqTsaVClZlu622ewO2zhmDMWc7a1V/QYJQE387itM3ojH2l0MqQPVe39oo5+FYtO+fiPKtSpUqqiaQXAFPMmDkSmpSMFyCNVOmTFGBHoNXXnlFnRySIIOLi4sK+khwwkDujx8/Hl9//bUKaF26dKlIjojUh5KAiJydy2zTpk1o166dOhklATZprxTjlowwqRklASnRrFkzLFiwQL0/ed+dOnXCG2+8gXfeeQclhUzJlOzx7OMnORuafZyVOcAkAUcJRAm5EqOTk5M6eyr9LVfjy06K1stnIvOYSupWFTkZDx1anD5V784JuqPunTEyvB+unCml7lcv44JRHSqje21fNS2dKDd+pRxUHc03Vx3HBxvOo8vgj+G7pAtwbgNw8Aeg4WB2HhFxTDXVeGMqnWaiiYNy+WgZ5EpWVOaCpHIW94cfflC1LzKTAJYMPGW6n5zFE9JRMn1PLgGdG9knp7N6UpfK1dW1UN8TUZFLTUkvyqmCVbKE/3c75k7wKvPttOT8Pb9bOaDRUKDhkPRA1R1JKWn4aut5zN14Tt2W+eCvdKmKYS0DOfinYkdSny9evJhxEY7iSLKgpKajLCXRvY6xBFrkaoCWNk5o2rSpumCMTN80kECfpPHnVBLhkUceUSf4pL6nwa5du1TWmQT/DFc7vBej9FXwwfSpetfSC7DfsA/EKzFPYXtK+lUm65UrhdHtK6NjDR9m8VKepaVpGPD1bnUF4tZVvLCo+h7oNrwJ2LoAL+0ESuVe25aI8o5jquIvoRDGVNaWclYvOjpanf2Vq/OMGjUqo1iXxNRkUCWpZR06dDCfs3pERcHKOj27KS8ZeBJvTridQ7DqTvZV9tvJsUBkELDxHWDLB0Ct/kDT5wG/RrC11mNUhyroUcdXXcloz8WbeHftSVWX4bOBDVHek1lTRESmJGOdp59+Go0bN1Yn+7766itcuXIl40SejIck2LRo0SJ1v1evXnjuuedUHU/D9D0JUjZp0iRPASmjTNX7521g30KVIZygd8SspP5YeLsLUmCNJoEeGN2hMlpV9mIwivJNr9fhg0fqotucrdh2NhzL6vbGY+XWpl/BcdUo4OmVshN7lojICEwWlLK1tVVn9KSORb9+/TLWy305q5edRNaOHj2aZZ2cDZS6EnK1GInM5UTqYMhCVOLINDwH9/TFu+r995fpoKfWAf9+CVzbDxz5OX3xawQ0eR6o1Q8VvZ2x5Llm+GVfEN5fdxJHrkbilaWH8OuI5vyjgIjIhAzTNd9++20VYKpdu7a6sl5AQIDaLuskSGUwdOhQdcJPambI1MhSpUqpk3sffPABzEJKIlIP/woraFiZ2hLvJQxCGNzV1WBHta+sglJEBRHo5YTxnati+h+n8M7a0+gw7GN4/tABuLgF2PcN0OQ5djARkRGYbPqekJRxOas3f/78jLN6UrtCirLKICr7Wb3s8jJ9LztLTcsnMqqr+4G9XwPHfksvtC8cvYBGQ4DGzwBu/gi6GYeOs7eo6Xw/Dm+KVlVyv8w8kSUpCanmJV1xnL5nCkXZVxfCYjDn4/cRonngX60GutQsjZHtK6vpekSFJSU1Df3m7cTRa5HqM/Zl1b3QrZ8I2DgCL+4EPHI+6U1EecMxVfGXUAhjKr2pz+rNmTNHndWrX78+tm7des+zekRkJP6NgH7zgXEngA5vAq5+6YXVt80C5tQFfnkK5SL3Y9BD6VNhZ284rabSEhERFQbJzL1duS9K1+2I9WNb46vBjRmQokJnbaXHzEfrwlqvw18nbmCdQ2+gQmsgOQ5YNTK9yD4RERXfTClT4BlQogcssH5apvZ9BVzalrE6xbMa3glthaXJLfHFM23Qtup/xdGJLBXP6hV/zJSyjDGVZLFI0ICoqM3ecAZz/zkLL2db/DOsAty+b5d+heuu04HmL/EAED0gjqmKvwRLz5QiIgsqsF6zNzB0DfDirvQpfDaOsI44jWlW32C33UjsXvMNs6WIiKjQMCBFxjKyfSVULe2M8JgkTN0eC3S5c/nzf6YB4Wd5IIiIihCDUkSUP6VrAj0/BsafBLrNQIp7Rbjq4vF85KfYduwCe5OIiIgsip21lboan14HrDh4DZucHgYqdQBSEoCVLwJpqaZuIhFRscWgFBE9GIdSQLMXYT16H8LtA+Cui0HQulnMliIiIiKL06C8O55pmV7Y/PWVxxDT9WPAzhW4uhfYOdfUzSMiKrYYlCKiAv4vYgW7Tm+om73ilmPzoTPsUSIiIrI4r3SphgBPR1yPTMD0HdFAt+npGza9D4SeNHXziIiKJQaliKjAXBo+ilDHymoaX+ifHzJbiqgEq1ChgrqyroFOp8PKlStN2iYiorxwsLXC9P511O3Fe65gl0s3oGo3IDUJWPECkJrMjiQio6lQQsZUDEoRUSH8T6KHY5e31M1e8auxaf8J9iqRCQwdOlQNWAyLp6cnunXrhiNHjpjseFy/fh3du3c32esTEeVHi0peGNikvLo9ccVRxHebDdiXAq4fArZ/zM4kKiE4pjIeBqWIqFA41+uNEKcacNQl4taGmUhL09izRCYgQSgJBMnyzz//wNraGj179jTZsShTpgzs7OxM9vpERPk1qUd1lHG1x+WIOHy8Owro8VH6hi0fANdNF+QnIuPimMo4GJQiosKh08G5x1R18+GEtdi07zB7lsgEJAAkgSBZ6tevj9deew1BQUEICwtT2+V+1apV4ejoiIoVK+LNN99EcvJ/U1IOHz6M9u3bw8XFBa6urmjUqBH27duXsX3nzp1o06YNHBwcUK5cObz88suIjY3NtT2ZU80vXbqk7i9fvly9hrShXr162LVrV5bH5Pc1iIgKk6u9Dd7vX1vdXrDtAg6X6gTU6AWkpaRfjS8liR1OVAJwTGUcDEoRUaFxrtkVV13rw16XjNi/P2C2FBUPmgYkxZpmkdcugJiYGCxevBiVK1dWU/mEBJu+++47nDhxAp988gm+/vprfPzxf1NSnnzySfj7+2Pv3r3Yv38/Jk6cCBsbG7Xt6NGj6Nq1K/r376+mBP7yyy/Yvn07Ro0ala92TZ48GRMmTMChQ4dUgGzgwIFISUkp1NcgIiqIDtVLo2/9spDE7//9dhRJ3WYBjp7AjWPpGVNElH8cU3FMlQOdphVwxGthoqKi4ObmhsjISHUGmIgKV8zpzXBe0gdJmhW2dv0TnVo8xC4mi5KQkICLFy8iMDAQ9vb26cGh98uapjGvBwO2Tvmqf/Djjz+mtxtQ2UW+vr5Ys2YNGjZsmONjPvzwQxX4MWRDye/GTz/9FEOGDLlr38GDB6vspS+//DJjnQSM2rZtq15LXleKco4dO1YtQjKjVqxYgb59+6pMKenXBQsWYPjw4Wq7BMdq1aqFkydPonr16nl6jUI/xplwnJB37Csq7m7GJqHz7C2IiE3CmI5VMK7sCWDpEEBnBTy7AfBrZOomEpk1jqk4pnLLQ+yFmVJEVKicq7XDlVJNYKtLRfKmGUhlbSkio5JpcZKBJMuePXvQpUsXVWj88uXLavuyZcvQqlUrNb3P2dlZTd+7cuVKxuPHjx+PZ599Fp06dcKMGTNw/vz5jG2SOSVZVvI4wyJZTWlpaSrIk1d169bNuC1BMxEaGlqor0FEVFAeTraY2ruWuj1v8zmc8uwA1H4E0FKBFS8CyQnsZKJijGMq47A20usQUQni2Wsa8EN3dE7aiE07d6JTq5ambhLRg7NxTM9YMtVr55OTk5OarmcgNaHkLJVM05OC5wMGDMC0adNUoEfW//zzz5g1a1bG/lOnTsWgQYOwdu1a/PHHH5gyZYrap1+/fiowNGLECFXjKbvy5cvn/W3dmQ5oyKQS8tyGn4XxGkREhaFnXV+sPhyMDSdu4LVlR/DbkJmwvrQdCD8NbHoP6PIOO5oorzim4pgqBwxKEVGhc6rUApc8WqHCze3QNn+AlOYrYW3FxEyyUBI0yccUOnMjQR+9Xo/4+Hjs2LEDAQEBqqaTgSGDKjOp8yTLuHHjVL2nhQsXqqCUTAE8fvx4lqBXYTPGaxAR5ef/0Hf71sbuCxE4fDUS3x6MxPO9PgGWDAB2fgpU7wmUb8oOJcrbF4pjKo6p7sK/EomoSPj0eVv97Ji8FZu2bWUvExlJYmIiQkJC1CJ1mkaPHq0Knvfq1UsFemSqnmQ+ybS8uXPnqnpPBhK4koLimzdvVsEqCWJJwfMaNWpkXLlPrpQ3cuRINT3w7NmzWL16tXqNwmKM1yAiyo/SrvZ44+H0/wdn/XUGFz3bAPUGSdXm9KvxJcWxQ4mKIY6pjINBKSIqEo4BjXDBqwP0Og0222YgJTV9ag4RFa3169erOk2yNG3aVAWVli5dinbt2qFPnz4q+0kCT/Xr18fOnTtVTSkDKysrREREqGLjkin1+OOPq3pUMt3PUAtqy5YtKlDUunVrNGjQQD3eUBeqMBjjNYiI8uvxxuXQqrIXElPSMPG3I0jr+j7gUha4eR74J/3/SCIqXjimMg5efY+Iikzc1aOwX9Aaemj4q/VSdOnYhb1NZu9eV2aj4oFX3yscvPoelTRBN+PQ5eOtiE9OVVP6nvI8Cyx+JH3j0LVAhVambiKRWeGYqvhLKIQrGjNTioiKjKN/HZwv3U3ddtrxAZKZLUVEREQWqpyHI/7XrZq6PeOPUwj2bgk0HJK+ceVLQGKMaRtIRGSBGJQioiJVru80pECPlmn7sPnvtextIiIisliDm1dAw/KlEJOYgtdXHIXW5V3ArTxw+zKw4b/p0ERElDcMShFRkbL3rYbzvr3U7VJ7PkRSCmtLERERkWWy0usw89G6sLXSY/PpMKw8GQX0+Sx9475vgfMbTd1EIiKLwqAUERW5Cv2nIRnWeCjtMLb8tZw9TkRERBarso8LxnSqom5P+/0EwrybAQ89l75x1SggIdK0DSQisiAMShFRkbPzDsR5/37qtvfej5CYnMJeJyIiIov1fJuKqOnrittxyZi6+jjQeRrgHghEXQPWv27q5hERWQwGpYjIKCr0m4JE2KC+dhLb1v/KXiezl5bGqabFFY8tERWUjZVeTeOT6Xxrj17H+jPRQN8v5OLmwKEfgTN/spOJ+Hu32EsrhPGydaG0hIjoPuw9y+FEwBOoeflH+B6YhYSuj8Pelv8FkfmxtbWFXq9HcHAwvL291X2dTmfqZlEh0DQNSUlJCAsLU8dYji0R0YOq7eeGEW0qYt7m83hz1TE0H9cWbs1HArs+A1aPBp7fArj6soOpxOKYqvjSCnFMpdPk2UqQqKgouLm5ITIyEq6urqZuDlGJkhgZgrSP68IBifin3hx07DfM1E0iypH8kr1+/Tri4uLYQ8WQo6MjfH19cxxAcZyQd+wrIiAhORUPz92G82GxeKyRPz7sWxX4qj0QdhLwawwMXQvY2LOrqMTimKp4cyyEMRWDUkRkVMcXjUetC9/gDAJQ/vX9sLe14REgsyTnbFJSUpCammrqplAhsrKygrW1da7Zbwy05B37iijdvks38diXuyCn+hc90wRtPKOArzsACbeBeoOAvvMAZtxSCcYxVfFkVUhjKgaliMiokqIjkDSrNpwRh3/qzETHR0bwCBCR2WCghX1F9CCk2Pl3Oy/Br5QD/hrXBk5XtwI/PgJoaUDX9wGZ1kdEVIJE5TEoxULnRGRUti6euFhlqLpd8egniEtI5BEgIiIii/Zq12rwd3fAtdvx+PDP00ClDkCX99I3/vUGcO4fUzeRiMgsMShFREZXve//EAlnBOIa9qyazyNAREREFs3JzhrT+9dRt7/fdUlN6UOzF4H6T6ZnSy0bBkScN3UziYjMDoNSRGR0Nk7uuFz9WXW7ysnPERsXz6NAREREFq11FW883thf1ZZ6ddkRRCWmAD0/BvwfAhIigSUDgYQoUzeTiMisMChFRCZRs88E3IQb/HEDe1d+xqNAREREFm9yj5oo42qPi+GxGP3TQaTobIAnfgRcygLhp4HlzwFpvIAGEZEBg1JEZBLWDi4IqvWCul3tzBeIiY3lkSAiIiKL5uZog68HN4a9jR5bzoThvXUnAZcywIAfASs74Mx6YOO7pm4mEZHZYFCKiEymVu+xCNN5whcROLBiDo8EERERWbw6/m6Y/Xh9dXvhjktYvOcy4NcI6HMnM3z7bODoMtM2kojITDAoRUQmY23niOC66ZdIrnHuK0RFR/JoEBERkcXrUccXr3Suqm6/teo4dpwLB+o+DrR4OX2HVaOA4EOmbSQRkRlgUIqITKp2z1EI0fnAG7dxePksHg0iIiIqFkZ1qIy+9csiNU3Diz/ux4WwGKDTVKByZyAlHvh5EBATaupmEhGZFINSRGRSVjZ2CGkwRt2uffFbRN6+ySNCREREFk+n02HGI3XRsHwpRCWkYPj3+3A7IRV4ZAHgWQWIugb88jSQkmjqphIRmQyDUkRkcnV7jMBVfVm4IxrHls80dXOIiCzSvHnzEBgYCHt7ezRq1Ajbtm275/6JiYmYPHkyAgICYGdnh0qVKuHbb781WnuJSgJ7Gyt8+XRj+JVyUFfke2nxASTbugIDlwB2bkDQbmDdBEDTTN1UIiKTYFCKiExOb22DsMbj1e06l79H5M0wUzeJiMii/PLLLxg7dqwKMh08eBCtW7dG9+7dceXKlVwf8/jjj+Off/7BN998g9OnT2PJkiWoXr26UdtNVBJ4u9hhwZDGcLK1ws7zEarGlOZZGXj0G8mnAg4sAv792tTNJCIyCZ2mlaywfFRUFNzc3BAZGQlXV1dTN4eI7khLTcWV9+qjQtoV7Co7GM2f/5R9Q0RGZ6njhKZNm6Jhw4b44osvMtbVqFEDffv2xfTp0+/af/369RgwYAAuXLgADw+PEtVXRKby94kbeO6HfSop6q2eNfFMq0BgxyfAhrcAnRXw9AqgYlseICIqFvI6TmCmFBGZBb2VFW41e03dbnLtBxzfsdbUTSIisghJSUnYv38/unTpkmW93N+5c2eOj1m9ejUaN26MmTNnws/PD1WrVsWECRMQHx9/z+l+MsDMvBBR3nWqWRqvd6+hbr+79gQ2nQ5Nvxpf3ScALRVYOgS4eZFdSkQlit6S6h9s374dLVu2hKenJxwcHFSK+ccff2zU9hJR0anfaRD2unWDlU5D6Q0vITz4MrubiOg+wsPDkZqaitKlS2dZL/dDQkJyfIxkSMm46tixY1ixYgXmzJmDZcuWYeTIkbm+jmRcyRlPw1KuXDkeG6J8erZ1IJ5oXA5pGjD6p4M4fSMG6PUJULYBEH8r/Yp8idHsVyIqMfSWVP/AyckJo0aNwtatW3Hy5Em88cYbavnqq6+M3nYiKnw6vR61n1+Ai/oK8MJthC4chJTkJHY1EVFe/g/V6bLclwoN2dcZpKWlqW2LFy9GkyZN0KNHD8yePRvfffddrtlSkyZNUin4hiUoKIjHhSif5Hv3Tt/aaBrogZhEuSLfXkQk6oEBPwHOpYHQE+nT+YiISgiTBqVk8DN8+HA8++yzqu6BnKWTs26Z6yFk1qBBAwwcOBC1atVChQoV8NRTT6Fr1673vboMEVkOBycXWA9chBjNATWTj2HfN2NN3SQiIrPm5eUFKyuru7KiQkND78qeMvD19VXT9iTjyUDGYhLIunr1ao6PkSv0SU2IzAsR5Z+ttR7zn2qECp6OuHorHiN+2I9Ex9JA/zvFzg/+CETnnOVIRFTc6C2p/kF2kl0l+7Ztm3tBQNY/ILI85arUw5nmM9TtZiGLcfCvH03dJCIis2Vra6tKIGzYsCHLernfokWLHB8j5RCCg4MRExOTse7MmTPQ6/Xw9/cv8jYTlXTuTrZYMOQhuNhbY9/lW5i0/Ci0wDZAuaZAahKwO+eT9ERExY3ekuofGMhgSc7WSYFOqX0gmVa5Yf0DIsvUsNtQ7C49QN2utPNVXLtw3NRNIiIyW+PHj8eCBQvw7bffqhIH48aNU+UQXnjhhYypd4MHD87Yf9CgQapG57Bhw3DixAlVGuHVV1/FM888o+p2ElHRq+zjjHlPNoSVXoflB67hx92XgZZ3MsT3fQskRPIwEFGxp7ek+gcGMl1v3759mD9/vpryt2TJklz3Zf0DIsvVaPhcnLKpCVfEIWHxU0iI+++MPhER/eeJJ55QY6K3334b9evXV0GmdevWISAgQG2/fv16lpqdzs7OKpPq9u3b6iTfk08+iV69emHu3LnsViIjal3FG5O6V1e35/x9FrEVOgHe1YHEqPTAFBFRMafTJApkoul7jo6OWLp0Kfr165exfsyYMTh06BC2bNmSp+d599138cMPP+D06dN52l8uXyz1E6RAJ2shEJm/0GsXYf11G3ggCv+6P4wmY34ydZOIqBjjOIF9RWRsyalp6Dx7Cy5FxOHVrtUw0v1fYOWL6YXPxxwBbOx5UIio2I6p9JZU/yAnElOTulFEVDz5+AUiuONnSNN0aHJrLf5dwbP4REREVHzYWOkxrnNVdfvLLecRWbkP4OoHxNwAjvxs6uYRERXf6Xv5rX/w+eef4/fff8fZs2fVsnDhQnz00UfqKnxEVHzVbt0HeyqMULfrHnob54/uNnWTiIiIiApNz7plUbW0M6ISUvD1jqtA85HpG3bMBdJS2dNEVGzpLan+QVpamgpUyb5S/+DTTz/FjBkz1OOJqHhrOvh9HLZ/CPa6ZNgtH4qo2xGmbhIRERFRoZBi5+M7V1O3v91xERHVBgD2pYCb54FTa9jLRFRsmaymlKmwVgSR5bodHoKEz1qhDMJwwKk1GryyGjq9ya/XQETFCMcJ7CsiU5E/y3p/tgNHr0Xi2VaBeMNxBbB1JlC2AfDcJrlCFA8OEVkMs68pRUSUX6W8yiCq9zdI0qzQMHYb9ix5h51IRERExYJcgfyVLum1pRbtvowbNYYA1g5A8EHg4lZTN4+IqEgwKEVEFqVqw7Y4WPM1dbvxmTk4uedPUzeJiIiIqFC0reqNhyq4IyklDZ/uuQU0uFM7d8cc9jARFUsMShGRxWny2KvY59oJ1ro0eP0xAuEhQaZuEhEREVGhZEtN6JJeW+rnf4MQXPNZQGcFnN8IXD/MHiaiYodBKSKyOFJHqsZz3+Cyvhy8cQshC59CakqKqZtFREREVGBNK3qidRUvpKRpmLU3EajVL33Djk/Yu0RU7DAoRUQWycmlFPD4IsRpdqideAj/Lpxg6iYRERERFYpX7mRLrTh4FVdqPp++8vgK4OZF9jARFSsMShGRxQqo3hAnmrynbje/thCHN/5s6iYRERERFVj9cqXQuWZppGnAB4dsgMqdAC0N2Pkpe5eIihUGpYjIojV++Dns8XpE3a6wdTyCL502dZOIiIiICkyuxKfTAWuPXMfF6s+lrzy0GIgJY+8SUbHBoBQRWbz6z36GM9ZV4YZYxP74JBIT4kzdJCIiIqICqV7GFT3rllW33zvmAfg1AlISgD3z2bNEVGwwKEVEFs/O3hEuT/+I23BGlZSzOPT1i6ZuEhEREVGBjetUBVZ6Hf4+FYYL1e5kS+39GkiMZu8SUbHAoBQRFQu+AdVwpe0nSNN0aBqxEvtW8ywiERERWbaK3s54pKGfuv3W6QDAswqQEAns/97UTSMiKhQMShFRsVG3/aP4t9wz6nbN/W/h0sl9pm4SERERUYGM7lAFNlY6bD9/C+eqpI9zsOtzICWJPUtEFo9BKSIqVh4aOhNH7RrAUZcI/dLBiIm6ZeomERERET2wch6OGNikvLo9+UJNaC6+QHQwcPRX9ioRWTwGpYioWLGytobf8MUIhQfKp13D6a+GQktLM3WziIiIiB7YqPaVYWetx54rsThf8en0lTs+ATjGISILx6AUERU7Hj5+uNnjKyRrVmgUsxl7fplh6iYRERERPTAfV3sMaVFB3Z54pTE0O1cg/Axw5g/2KhFZNAaliKhYqt6kM/ZXG6duNzz1EU7t+8fUTSIiIiJ6YC+0rQRnO2vsu56CCxUGpK/c/jGgaexVIrJYDEoRUbHVdMBkHHBuA1tdKkqteR63wq6buklERERED8TDyRbPtApUt1+71hKalR1wdS9weSd7lIgsFoNSRFRs6fR6VHnuewTpyqIMwhH0zZNITUkxdbOIiIiIHsizrQPh5mCDfeE2uOjfJ33ljjnsTSKyWAxKEVGx5uLmgZRHv0O8Zou6Cfvx76JJpm4SERER0QNxtbfBiLYV1e3JN9pD0+mBs38BN46zR4nIIjEoRUTFXmCtpjjWYKq63fTy1zi6Zbmpm0RERET0QIa2qAAvZ1vsuu2GK6U7/XclPiKikhSUOn36NEaNGoWOHTuiU6dO6rasIyIyRw/1HYk9Hr2h12nw3/QyQoLOmbpJRERERPnmaGuNl9pVVrenRHROX3l0GXD7CnuTiEpGUGrZsmWoXbs29u/fj3r16qFu3bo4cOCAWrd06dLCbyURUSGo99x8nLOqBHdEI/L7J5GUmMB+JSKTqlixIiIiIu5af/v2bbWNiCgng5qWh6+bPTZH++GaR1NASwV2fsbOIqKSEZT63//+h0mTJmHXrl2YPXu2Wnbu3InXX38dr732WuG3koioENg7OMHxqZ8QBSdUSzmFAwtGsV+JyKQuXbqE1NTUu9YnJibi2rVrJmkTEZk/exsrvNyxirr93u2u6SsPLAJi7w5yExGZM+sHeVBISAgGDx581/qnnnoKH374YWG0i4ioSJQNrI5DrWah/vYX0CxsKfava45GPYazt4nIqFavXp1x+88//4Sbm1vGfQlS/fPPP6hQoQKPChHl6tFG/pi/5TzWRVRDqFd1+MScAv79CmjPi7oQUTEPSrVr1w7btm1D5crpc5kNtm/fjtatWxdW24iIikT9TgOx68JONA9ehOp7XseVyo1Qvmp99jYRGU3fvn3VT51OhyFDhmTZZmNjowJSs2bN4hEholzZWOkxtlMVjPvlMGbGdMNHkKDUl0DLlwFbJ/YcERXfoFTv3r3VND2pKdWsWTO1bvfu3aqe1LRp07Kc/ZN9iYjMzUPDZuH4h4dQK+kIwn5+GnHjt8PR+b9MBSKiopSWlqZ+BgYGYu/evfDy8mKHE1G+9a7nh3mbzmN5aGO8UcofpeKvAgd+AJq9wN4kIoug0zRNy++D9Pq8laKSs3851UkwpaioKJUiHxkZCVdXV1M3h4hMKDzkCjC/NbxwG/tcO6PR2F+hy+P/b0RUPBlrnLBx40Z15WI5qZf9deS1W7Rogfnz55t1BjrHVETmYf2x63jhxwMYarsRU/ULALdywMsHASsbUzeNiEqwqDyOqfQPenYvL4u5BaSIiDLzKlMeoV3nI0XTo3HUBvz722x2EBEZxZw5c/Dcc8/lOEiTAdyIESPUhWSIiO6na60yqO3niiVJrRBj7QFEBgHHfmPHEZFF0Of3rF7NmjVVxCs7iX7VqlVL1ZoiIrIUNZt3x77Ko9XtBsem4+wh/h9GREXv8OHD6NatW67bu3TposokEBHlZXbKK12qIRG2+DKxS/rKHZ8A+Z8QQ0Rk3kEpntUjouKo6ZNTcdCxBWx1KXBa9QwiI26YuklEVMzduHFDFTTPjbW1NcLCwozaJiKyXO2qeqNxgDu+T+6IBL0jEHoCOPuXqZtFRFS4QSme1SOi4kjqSFV87gdc05VGWS0UFxcMRhqnHxNREfLz88PRo0dz3X7kyBH4+vryGBBRvrKlouCEH5I7pK/cPoe9R0TFKyjFs3pEVFy5uXshvu9CJGo2qB+/G3t+fNPUTSKiYqxHjx546623kJCQcNe2+Ph4TJkyBT179jRJ24jIMjWv5IlWlb3wdXJ3pOhsgCs7gSt7TN0sIqLCC0rxrB4RFWeV67XE4bpvqNtNLszDsR2/m7pJRFRMvfHGG7h58yaqVq2KmTNnYtWqVVi9ejU++OADVKtWTW2bPHmyqZtJRBbmlS5VEQp3/JbSMn3FmnFAbISpm0VEVDhBKZ7VI6Li7qF+L2Nvqe6w0mnw3TASYcGXTN0kIiqGSpcujZ07d6J27dqYNGkS+vXrh759++L1119X63bs2KH2ISLKjwbl3dGphg/mJvdDpJUHEHoc+L4XEBvOjiQiyw9K8aweEZWE+lK1n/saF/QV4IlIhC8chOSkRFM3i4iKoYCAAKxbtw7h4eHYs2cPdu/erW7LugoVKuT7+ebNm4fAwEDY29ujUaNGeb4isgTApLB6/fr1H+BdEJG5Gd+5Gq7BG/3iXkeyo89/gakYXjyBiCw8KMWzekRUEjg4ucBm0I+I0RxQI/k49n87ztRNIqJizN3dHQ899BCaNGmibj+IX375BWPHjlVT/g4ePIjWrVuje/fuuHLlyj0fFxkZicGDB6Njx44P2HoiMjc1y7qiZ11fXNDK4gWrt5HqXCb9anzf9wRiQk3dPCKiLHSapml4ALdu3cK5c+cgD69SpcoDD6KMLSoqCm5ubmoQ5urqaurmEJEZO/jn92iw62V1+0Dzz9Cw69OmbhIRFTFLHSc0bdoUDRs2xBdffJGxrkaNGmpK4PTp03N93IABA9Q4zsrKCitXrsShQ4eKfV8RlQRBN+PQb95OhMckorVnJL7TvQ2rmOuAVzVgyO+AC6cHE1HRyus4IV+ZUoV9Vo+IyJw16DoEu0sPVLer7HwVF0/sNXWTiIjukpSUhP3796NLly5Z1st9qVuVm4ULF+L8+fPqSn95kZiYqAaYmRciMk/lPBzx64hmKOtmj20RbhiY9CZSnH2B8NPpGVPRIaZuIhFRwYJSREQlQaPhn+CkTU246OLh80tP7F+30NRNIiLKQupQpaam3lUYXe6HhOT8h+fZs2cxceJELF68WNWTygvJuJIznoalXLlyPBJEZqyitzOWvtgCFTwd8W9UKTyW8AaSncsC4WeA7x4Goq6buolERKYPSuWnKOfy5cvRuXNneHt7q/Sv5s2b488//zRqe4moZLGxtUOZ55fjuG1dOOkS0Ojfsdg9/yWkJCeZumlERFnodLos96XEQvZ1QgJYgwYNwrRp01C1atU896JcJVBS8A1LUFAQjwCRmfMr5YBfX2iOaqVdcDDGHf1iX0eSsx8Qce5OYCrY1E0kohLOpEGp/Bbl3Lp1qwpKyVVpJE29ffv26NWrl3osEVFRcff2RbVX/8HuMk+q+81CFuP0hx0RceMqO52ITM7Ly0vVhMqeFRUaGnpX9pSIjo7Gvn37MGrUKJUlJcvbb7+Nw4cPq9sbN27M8XXs7OzUScHMCxGZPx8Xe/wyohnq+bvhWLwHekVPQqKTH3DzfHpgKvKaqZtIRCXYAxc6N2VRzsxq1aqFJ554Am+99Vae9mdRTiIqiAN/LES13RNV1lQoPHCz5wJUb8yrVhEVF5Y6TpAxlWScSwa6Qc2aNdGnT5+7xlRpaWk4ceJElnXyOAlGLVu2TGWwOzk5Fdu+IiqpYhJTMPy7vdhz8SYq2YRjjetMOMReBdwDgaFrADd/UzeRiIqRIi90bqqinNkHVXK2z8PDI9d9WJSTiApTw+7DED7wD1zR+8EHN1Hx98ew59cPoaWlsaOJyGTGjx+PBQsW4Ntvv8XJkycxbtw4lXn+wgsvZEy9Gzx4sLqt1+tRu3btLIuPj48qpSC38xKQIiLL42xnje+faYJ21bxxPtkL3W7/D3FO/sCti+kZU7c5JZeIjE9vSUU5s5s1axZiY2Px+OOP57oPi3ISUWELqN4Q7mO244BTG9jqUtH0xLvY98lAJMTFsLOJyCQka3zOnDlqGl79+vVVyQMpdxAQEKC2X79+PdfyCERUctjbWOGrpxvj4Tq+uJzqhc43X0OMYzng1qU7gSn+P0FEJWT6XnBwMPz8/FRWlBQsN3jvvffwww8/4NSpU/d8/JIlS/Dss89i1apV6NSp0z0zpWTJnEImV4thqjkRFZRkR+35cQoeOv8prHQazllVguNTP6FsYHV2LpGF4pQ09hVRSZCapmHib0ewdP9VlEEE/nKfCdf4IKBUeWDIGsA9PaBNRFRsp+/ltyhn9gLpw4cPx6+//nrPgJRgUU4iKio6vR7NBr+Dk50X4RZcUTn1PJy+74Ajm5ax04mIiMhsWel1+OCRuhjaogJC4InOt17DbYfy6ZlS3/VMz5wiIjICkwWlbG1tVUHODRs2ZFkv91u0aHHPDKmhQ4fip59+wsMPP2yElhIR3VvtVr2ROHwTzlhXhRtiUXvzs9i18DWkpaay64iIiMgs6fU6TOlVE6M7VMYNeKDrrf/hpn15IPJOYOrmRVM3kYhKAJMFpfJblNMQkJL7UkuqWbNmKstKFkkHIyIypTLlKiNgwhbs8ewDvU5D88vzceSjHoi8Fc4DQ0RERGZJp9PhlS7VMLF79fTA1O3XEGYngamg9BpTNy+YuolEVMzpLako55dffomUlBSMHDkSvr6+GcuYMWNM+C6IiNLZ2Tui6ehF+LfeO0jUbFA/fjei57bEhWN72EVERERktl5oWwnv9K2NcJ07ekROxA3b8kDUNWDhw0DEeVM3j4iKMZMVOjcVFjAlImM4e2gbnFcOgy/CEK/Z4nijd9C4d3oWKBGZL44T2FdEJdmKg1cxYekRuKfdxmrXGSibdBlw8QWGrgU8K5m6eURkQcy+0DkRUXFWpX5rOIzajiP2jeCgS0LjA69hz+fDkZSYYOqmEREREeWoXwN/fD6oIaKs3NE7aiKu2lQAoq8DC3sA4WfZa0RU6BiUIiIqIqW8yqDWhL+wy2+Yut80bBnOf9Qe4cGX2edERERklrrVLoMFQxojxsYdfaJfw2XrCkBMSHqNqbAzpm4eERUzDEoRERUhK2trNH9uDg61/ALRmgNqJJ8AvmqDE7vXs9+JiIjILLWp6o0fhjdFkp0n+sVMxEWrQCDmxp3A1GlTN4+IihEGpYiIjKB+50G4/fQGXNQHwAu3UeWPQdj907vQ0tLY/0RERGR2HqrggSXPN4Pm6In+sa/hvD4QiA1ND0yFnjJ184iomGBQiojISMpVroPS47dhn0tH2OhS0ezMh9j/8aOIi4nkMSAiIiKzU9vPDb+OaA5bV288EjcRZ1VgKiw9MHXjhKmbR0TFAINSRERG5OjshkbjlmF31VeRrFmhcfQ/uDG7NYLOHeVxICIiIrNTpbQLlo5oAWd3HzwaNwmndYFAXDjwfU/gxnFTN4+ILByDUkRERqbT69Fs0Bs42/0nhKMUAtMuo9QPnXHo7yU8FkRERGR2yns6YtkLLeDlXRqPxU/CCVQE4iKA73oCITyxRkQPjkEpIiITqdmsG/D8Vpy0qQkXXTzqb38BuxaMQ2pKCo8JERERmZUybvZqKl+5smUxIGESjqISEH8T+L43cP2IqZtHRBaKQSkiIhPyKhuAShM2Ybf3Y+p+86vf4vhHXXA7PITHhYiIiMyKp7MdfnquGaoE+OPJhIk4olVOD0wt6g0EHzJ184jIAjEoRURkYrZ29mg2cgH2NfwA8Zot6ibsR/xnrXDu8HZTN42IiIgoCzcHG/wwvAnqVg7Ak4kTcUgFpm4Bi/oAwQfZW0SULwxKERGZica9X8D1x9bgqq4MfBGGcsv74t8Vc03dLCIiIqIsHG2tsWBIYzSrGYinEifiQFoVIOF2emDq2gH2FhHlGYNSRERmpGLtpnB5eQcOOTSDnS4ZTQ6/iT1zn0ZiQpypm0ZERESUwd7GCvOebIiO9Svj6aSJ2JtWFUiIBBb1Ba7tZ08RUZ4wKEVEZGbc3L1Qd8I67Ap4AWmaDk1vrsblj9oiJOicqZtGRERElMHGSo+PH6+PPk2rYWjSa/g3rRqQeCcwdXUfe4qI7otBKSIiM6S3skLzYR/gWLsFiIQTqqacgd037XFs+2pTN42IiIgog16vw3t9a+PJNrVUYGpPWnUgMQraD/2AoH/ZU0R0TwxKERGZsbrtH0XskI04b1UR7ohCjQ2DsXvRm9DS0kzdNCIiIiJFp9NhUvfqeLFzXQxL+h92p9WATgWm+gNX9rCXiChXDEoREZm5soHV4ffKNux16wYrnYZmF+bi4KzeiI68aeqmEREREWUEpkZ3rIIJPRtiWNKr2JlaE7qkaGg/SmBqN3uJiHLEoBQRkQWwd3RG4zFLsKfmG0jSrNAwdhtuftIal0/xCjdERERkPp5pFYhpjzTB8JRXsSO1FnRJMekZU5d3mrppRGSGGJQiIrIQOr0eTR9/FRd6LUUoPBCQdhVeS7rjwB8LTd00IiIiogyPP1QOMwc0w4jUV7EttTZ0ybHQfnwUuLSDvUREWTAoRURkYao37girF7fhuG1dOOkS0HDPWOye/xJSkpNM3TQiIiIipVe9spg7uAVe0v6Hral10gNTix8FLm5jDxFRBgaliIgskGdpf1R79R/sLvOkut8sZDFOf9gR4cGXTd00IiIiIqVD9dL4clhLjNX9D1tS60KXHAdt8WPAjrlAUhx7iYgYlCIislTWNrZo9sI8HGg6B7GaPWolHYHzl42w5/PhCAk6Z+rmEREREaFFJS9882xrTLB6DRtT60OXEg9seBOYWx/YPR9ITmAvEZVgzJQiIrJwDbsPQ/jAP3DaujrsdcloGrYMHgua4N9PnsS1C8dN3TwiIiIq4RqUd8eiEW0wyXYSJiSPQJDmDcTcANa/BnzaENj3LZDCMgREJRGDUkRExUBA9Yao+vouHOu4CMdt68FWl4omt9agzPctsW/2I7h0cp+pm0hEREQlWA1fVyx9qQ2iqz+ODomz8HrycARrHkDUNWDNOOCzRsDBH4HUFFM3lYiMSKdpmoYSJCoqCm5uboiMjISrq6upm0NEVCRO/bsBiZtmol78vxnrDji1hmuXiahcrxV7nSgXHCfkHfuKiB7U8eBIzP3nLDYfD8JAq40Yab0K3rrI9I0elYB2k4Da/QG9FTuZqJiPExiUIiIqxs4d3o6ovz5Aw9itGesO2z8Eu/b/Q/WmXUzaNiJzxEAL+4qIjB+c2nL8Cp622oAXrVfDQxeTvtG7OtD+daB6L0DPCT5EloZBqQJ2DBFRcXL55H6E/TEdDSL/hpUuPUH2uG1dpLWagNqtekHHwR6RwnFC3rGviKiwg1Pbj1/CUKs/8bz1Grjp7lydr0wdoP1koGo3QKdjpxNZCAalCtgxRETFkRQ+v7ZmOupHrFN1p8Rp62qIbzYO9To8weAUlXgcJ+Qd+4qIiio4tev4BQy3XodnrNbDRRefvtGvUXpwqlIHBqeILACDUgXsGCKi4iwk6BwurZ6B+qEr1RX7xHmrQNxuNBr1uwyBlbW1qZtIZBIcJ7CviMh8glN7jp/DCOs1GGL1Fxx1iekbyzcHOrwBVGCNTCJzxqBUATuGiKgkCA8JwtlVM1E3+Fc46RLUuit6P9yo+xLq93gONrZ2pm4ikVFxnMC+IiLzC07tP35G1Zt6yupv2N05mYbAtunBqXJNTN1MIsoBg1K54GCTiOhukRE3cGLVR6h5ZTHcEKvWBet8EFTjedTvPRJ29o7sNioROE5gXxGR+QanDh0/qa7UN8BqY0YZAlTuDHSYDJRtYOpmElEmDErlgoNNIqLcxUTdwrGVs1HlwvfwRPqlmUPhgQtVhqFunzFwdHZj91GxxnEC+4qIzD84dez4MYy2XoFHrbbCWpeWvrF6T6DdJKBMbVM3k4jAoFSuONgkIrq/+NhoHF79KQJPL0BpRKh1t+CK0xWeRs2+r8C1lCe7kYoljhPYV0RkOcGpUycO42Xr5ein3wH9nasLo1a/9OCUdzVTN5OoRIvKY+kkvVFbRUREFsHByQXNBr4O90kn8G+dqbimKw13RKHZpc+BObWxa8E43Aq7bupmElEm8+bNQ2BgIOzt7dGoUSNs27Yt1/5Zvnw5OnfuDG9vbzVQbN68Of7880/2JxFZhFpl3fDl040xb/Sj+KvqNHROmok1qc3SNx5fAW1eM2D5CODmBVM3lYjug0EpIiLKla2dPZo8Mg6lXz+GfQ0/wGV9ObgiDs2vfgu7z+ph9xcvIDz4MnuQyMR++eUXjB07FpMnT8bBgwfRunVrdO/eHVeuXMlx/61bt6qg1Lp167B//360b98evXr1Uo8lIrK04NTc0U/g96rvoXvidPyV2gg6LQ048jO0TxsDq0cDt3P+v5CITE+nadqdPMeSgWn5REQPLi01FYf//hEu/36Cyqnn1bpEzQaHvHshoPfrKFO+CruXLJqljhOaNm2Khg0b4osvvshYV6NGDfTt2xfTp0/P03PUqlULTzzxBN56661i3VdEVPyn9QWf2IXx1kvR3uqwWq/pbaBrNARoPQFw9TV1M4lKhChO3yMiosKmt7JCg65DUGnyPhxuuwCnbGqqSzM3DV8Oz2+a4t85AxF07ig7nsiIkpKSVLZTly5dsqyX+zt37szTc6SlpSE6OhoeHh657pOYmKgGmJkXIiJzzJyaMXowfq46G/0Tp2JHai3o0pKBvQuQ9kk9YP3rQEyYqZtKRHdw+h4REeWbTq9HvfaPodqkHTje+Sccs6sPG10qmtxeh7I/tMb+Wf1w8fge9iyREYSHhyM1NRWlS5fOsl7uh4SE5Ok5Zs2ahdjYWDz++OO57iMZV5IZZVjKlStX4LYTERVlcOqd0c9gUdW5GJD0Bv5NqwZ9aiKw+3OkzakD/D0ViLvJA0BkYgxKERFRgYJTtVo+jNqTtuBUz+U45NAMVjoNjaI3InBpFxyc2R1nDmxhDxMZgU6ny3JfKjRkX5eTJUuWYOrUqaoulY+PT677TZo0SU3VMyxBQUGF0m4ioqIOTr056nl8U/lzDE56DYfSKkKfEg9s/xipH9cBNr0PJETyIBCV1KBUfq4Uc/36dQwaNAjVqlWDXq9XBT2JiMg8VG/cEfVf+xPn+/+BA85tkabp0CBuJ6qu7o0jMzrixO71pm4iUbHk5eUFKyuru7KiQkND78qeyk4CUcOHD8evv/6KTp063XNfOzs7VTsq80JEZDHBqcEP4bVRI/FF5a8wPOkVnEgLgFVyDLDlg/Tg1NaPgMQYUzeVqMTRW9KVYqSWgVy6WPavV6+e0dtLRET3V6luCzScsBpBgzZjr1tXpGh61E3Yh5rrn8CJ91ri6Jbl0NLS2JVEhcTW1lad2NuwYUOW9XK/RYsW98yQGjp0KH766Sc8/PDDPB5EVGKCU+NHjcHcygvwYtIYnEnzg1ViJLDxHaRIcGrHXCApztRNJSoxTHr1vYJcKaZdu3aoX78+5syZk6/X5JViiIiMK/jiKQSteR8NwtfCVpei1p21roKYJmNRr+NAVTydyFxY6jhBTvQ9/fTTmD9/Ppo3b46vvvoKX3/9NY4fP46AgAA19e7atWtYtGhRRkBq8ODB+OSTT9C/f/+M53FwcFDvvzj3FRFR5qv1ffr3KdidWomx1r8hUH9DrU9x9IF1g4FA1W6AfxPAypqdRpRPeR0nWJv6SjETJ0584CvFEBGR+SsbWB1lRy9C6LWLuLBqOurdWIEqKWeBnSNxY+dbuOTVFg61e6Jas+6ws3c0dXOJLNITTzyBiIgIvP3226rcQe3atbFu3ToVkBKyLnMm+pdffomUlBSMHDlSLQZDhgzBd999Z5L3QERkisyp+YOb4nhwdcz8uy+cTy/DGOvl8I8LBXZ8opZUOzfoq3SGTgJUlTsCjrlfpZSILChTKjg4GH5+ftixY0eW1PL3338f33//PU6fPl0omVIy5U+WzNE6uVoMz+oREZlGxI2rOLNqJmpf+xUuuviM9TGaA864NEFa1e6o0rI/3DzvXQuHqCgw+4d9RUQlO3Pq879PQH9qLTpaHUA7/WG46/6rM6VBjzT/JrCq1jU9i8qnhlxlwqRtJjJXZp8pVdArxeSVTAOcNm1aoT0fEREVjGdpfzR/fi4S4t7H4d1rkHBsLSre3AZv3S00jNkCHNiClP2v47hdLUQHdEa55o/Cr2ItdjsREREVeebUvMHNcfVWPWw6FYoJp0IQd2E3Wmn70UF/EDX0QbC6uhuQ5Z9pSHb2g3X17tBV6wZUaAXYOPAIEeWTtSVeKSY/pIbC+PHj78qUIiIi07J3dEa9DgOADgOQlpqKM4e3I+LASpQO3oiKaZdQK+kocFaW2bikL4frZdrDvUEfVGnQDlbWJj+nQkRERMWUv7sjnm5eQS0JyQ9h94UI/HI6DMdOHEf16J0qQNVCfxz2MdeAfQvUkmplD1Rsl55FVaUr4OZn6rdBZBGszeFKMf369ctYL/f79OlTaK8jly+WhYiIzJcUO6/asC0gy53i6Fd2/wbnS3+hWsJRVEgLQoXgRUDwIkSsdcP5Ui1hU/NhVG/ZBw5OLqZuPhERERVT9jZWaFfNRy1ar5q4GN4Dm06HYfHJK7C6vA1tcAAdrA6ibOpN4Oz69EVqKHvVgm2N7kDVroBfIxnsmPqtEJklk159L79XihGHDh1SP5999llUq1YNr776qgpw1axZM0+vyVoRRESWJfJWOM7uXAGc+gNVo3fBFf9dpjlBs8Epp8ZIqtQVFVs+Aq8y5U3aVrJ8HCewr4iI8io2MQU7zoWrqX5Bp/aibtxudLQ6iAa6c9Dr/vszO9nOA/qqnWEl0/wqdQAcSrGTqdiLymNNKZMGpcS8efMwc+bMjCvFfPzxx2jTpo3aNnToUFy6dAmbN2/O2D+nelMSwJL98oKDTSIiy5WUmIAz//6JmCO/IyBsM3wRlmX7aetquOXfCWWa9kdAtYbQ6fUmaytZJo4T2FdERA9C/qw+fSMam06FYd+JMygVvBXtdAfQVn8Errr/Tqil6ayR4tcEtjV7pE/z86rCYulULFlMUMrYONgkIioetLQ0XDq5FyF7V8Dz6j+omnImy/ZrutII8m4H53q9UO2hLrCx5VRuuj+OE/KOfUVElLvI+GRsPxuOLaeCcfv0NjRK/Bcd9IdQRX8ty34JLgGwrdENesmiCmgJWHO8QsUDg1IF7BgiIrIsYcGXcGHHb7C/8Ceqxx2AnS45Y1sUnHDGtTl01XugSou+cC3ladK2kvniOIF9RURU2NLSNBwLjlRZVCdPHIZv6Ba01x1EU/1J2OlSMvZLtnJEWsV2sJNaVFW6AC5leDDIYjEoVcCOISIiyxUXE4nTO39Hyok1qHx7B9wRlbEtSbPCaft6iAvsgvLN+8M3oJpJ20rmheME9hURUVGLiEnE1rNh2HHiMlLObkKzlL3oYHUIPrrbWfaL86oDh5o9oJMsKt/6AMsSkAVhUKqAHUNERMVDakoKzu7fiFuHVqHsjc0ISLuaZft5q0CE+XaAZ+N+qFy3JetQlXAcJ7CviIiMKSU1DYev3samkzcQdGI3KkRsQ3urg6ivv5BlvwQ7L+irdlVT/VCpPWDHqw+TeWNQqoAdQ0RExVPQ2cO4tmc5XC//jWpJx2GV6eo4ofDARc82sK/dE9Wa9YC9g5NJ20rGx3EC+4qIyJRuRCVg8+lQ7D92GraX/kHLtH1orT8KZ11Cxj6pOmsklG0Ox9o9oKvaFfCsZNI2E+WEQalccLBJREQGt8Ku49yO5bA6ux7VY/bAUZeYsS1Os8Mp5yZIrdINlVs+AndvX3ZcCcBxAvuKiMhcJKWkYd/lm9h28hoiTmxGtahd6KA/gED9jSz7xboEwiqgOez96wGla6Uvjh4mazeRYFAqFxxsEhFRThLiY3Fm9x+IP/Y7AiO2wgc3M7alajqctq2FqIBO8GvaH+Wq1GMnFlMcJ7CviIjMVdDNOGw+E4aTRw/ANegftNH24yH9adjoUu/aN86+NFK9a8LBvy6sy9ZND1R5VgasbEzSdip5ovI4S02nadp/8xZKAA42iYjofrS0NJw7sgPh+1fCJ3gjKqVmresQrCuNEKfqSPSpB+cKjVG+dgu4eXizY4sBjhPYV0REliAhORW7L0Rg14mLiD+9EZ4xZ1Bdd0UtAfrQHB+TqrNBrFtl6MvUhmO5uuonStcBnDmGocLHoFQBO4aIiMjg+uXTuLJrORwv/oVqCYdhm8MZyfRAVTUketeFc2BjlK/VAm6epdmJFobjBPYVEZElik1MwZkb0TgdEo2L10IQf+0obCNOIiD5IqrrJVgVBBddfI6Pjbf1RKJnDdj714W9352sKu9qgLWd0d8HFR8MShWwY4iIiHISHXkTlw5vQ8ylfbALPYzSsafgp2Wt7ZBboKpczeYo5VWGHWvGOE5gXxERFRcyKSo0OhGnQqJxKjgSoUFnoYUcg2vUaVTBZRWoCtSFQJ/poi8GqTorxDhXVAEqp/L1YO1bJz1Y5eIL6HQmeT9kWRiUKmDHEBER5VVkxA1cOb47j4EqH4Q4ytS/OmrqX7laLRioMiMcJ7CviIiKu+TUNFwKj8XJkGicvxaK2KtHYRV6EmUSzqGGyqq6glK62Bwfm2DthniP6rApWxdO5etCV7o24FMDsHEw+vsg88agVAE7hoiIqCAib4Yh6PhOxFzcB5vQIypQ5a+F5LjvdXjjulN1JHnXhWOFRipQxav9mQbHCewrIqKSKjohWU0BPBkchetBF5B8/Qgcb51GYOolFaiqpAuGtS7trselQY9op/KqsLpjuXr/XQXQrRyzqkqwKBY6L1jHEBERFbbIW+FZA1UxEqi6nuO+ISpQVQ0J3nXgFNAY/rWaw8PHjweliHGcwL4iIqKsUwCvRybgVEgUzl4LR2TQcehuHIdHzBlUxRWVWeWli8qxyxKtnBBTqjqsytSGS0A9WPnWTc+qsnNmF5cAUQxKFaxjiIiIjBaoOrErPVB14wh8Yk6hnBac474MVBU9jhPYV0REdH9JKWk4HxajCqtfCbqExKuHYR9xEmWTLqCGLgiVdVdzvDCMiHTwR5JnDTj414OTXw3oJKPKzQ9wLgNYWbP7iwkGpQrYMURERKYSdTsCQcd3I/riXljfkIyqk/cIVHnhumN6RpVjhcbwr9kcnqX9jd7m4oLjBPYVERE9uMi4ZJVVdeb6TURcPgEt5ChcIs+gctoldRXAMrpbuT42FVaItfNGoqMvNFd/2HiUg5N3Bdh6SNDKP31xcOeUQAvBoFQBO4aIiMjcrvp3JVOgyifmJPxTg3O8Ys4NeCJYBarqwjGgEfxqNodXmXImabel4TiBfUVERIUrLU3Dtdvx6iqAl4OuICboCGzCTsAn7izK627AFxHw1d2ETS6ZVZkl6e0Ra1caSc5+0Ln5wc4zAE7eAbB2vxO4cvUDbB15CM0Ag1IF7BgiIiJzFxN1SwWqoi5IoOowvGXqX+q1HANVofDANcfqSPCqA7uyNeFWtip8AqrDxc3DJG03VxwnsK+IiMg4EpJTVbDq+u0EBN+ORWRYMJIiLiEt8ipsooPhlBACr7QwlNVFqMVbF5mn542zckOcgy9SXPygL+UPe6/ycPauAH0pThM0JgalCtgxREREFhuoOrEnPVAVYghUXc0xUCVuwRVh1mUQLfUdXANg7RkIx9KV4Vm+GnzKBkJvZYWShOME9hUREZmPqITkO0GreITcvI2YsCAk37wMRF6DXWwwnBNDUFqToFW4Clw56xLu+5yp0CPG1hsJjr5Ic/FTWVYOXgFw8gmATk0TLMdpgoWAQakCdgwREVFxERt9WwWqIs/vhdWNw3CNvQLvlGB4IOer5RgkadYIsSqNW7ZlkeBcDpp7IOy8K6KUfzWULl8Vjs5uKG44TmBfERGRZV0d8GZskrpCYPCtOIRHhCEu7DJSbgVBH3UN9nHX4ZoUAl/JtkIEyuR1mqDODtF2ZZDkVBaaqx9sPMuraYISvFKBK04TvC8GpQrYMURERCUhq+rG5dOIDD6LpLDz0N26CIfYq/BIvIbSaaH3HbSFoxTCbcoixsEPyW4VVJaVs29leJerDs8y5aDT62FpOE5gXxERUfGSmqYhLDoRwZHxuH5LpgleRXx4ENJuX4E+OhiO8ddRKjn0zjTBcHjr7n3SziBWpgnaeiLFrhTS7D0AJ09YOXnB1tUL9m4+cHDzhs7RC3B0Bxw9ATvXElWkPSqPsRedJqHFEoSDTSIiovtLTUnBjavncfPqacTdOI/UiAuwjboC1/ir8Em9DjfE3vPx8ZotbliVwW17P5VlBfdAOJSuiFJ+1VG6fBXYOziZ5WHgOIF9RUREJU9SShpuRKVPE7xxMxJRoZeRFHEFiLwK6xipb3Udnqnh+ZommNPVBeOs3ZBgUwrJdu5ItfeAztEDVs6esHHxhoObD+zdvFVgC44e6YsFB7IYlCpgxxAREVHuIm+GIfTKKUQFn0NS2DlYRV6GY2wQPJKCUTotDFa51LDKXHg93NYPsY7+SHELgI1XRZVl5VO+Oty9fE2WZcVxAvuKiIgoJ/FJqXeyreIRFhGKuNDLSI4OhRYbAV38TVgn3oJd0m04pNyGa1oU3HXRcNfFwAPRcNQlPlCnpmQEstyRbFsKaQ4e0Bw9YO2UHsiSIJZjKZ9MgSzJyHIxi0AWg1IF7BgiIiJ6MMlJibhx5SxuXTujsqy0mxdhG30FbglXUSblOpzuc3YxVrNXWVaRDv5IdC4HnWdFOPhUgrt/VZQuVwW2dvZFdmg4TmBfERERFcaVBW/HJeNWXBJuxSYhMjoacZGhSIoMQ3JMBLS4COjiIlQgyzbpNhyTb8M5LQoeumiUKnAgyxpxVq5IsC2FJFt3pNmnTx/UOXnC1tUb9q4SyPJWQS04eAAuvoBN4Y+tGJQqYMcQERFR4dPS0nAr/DrCrpxGdMg5JIedh1XkFTjHBcEzKRje2s1crxQoUjUdQnVeuFp/HB7qO7LQ28dxAvuKiIjIVFMIb8cnqWCWFG+Pio5C7K0wJEWHISU6DGmxN1VGllXizfSMrOTbcEpND2SprCzEPFAg62iTD1CnxwsmG1NZF/orExEREeVCpuV5+PipBehw1/aE+FiVZXX72hnE3zgH3LoEu5gguCdcRenUEDjokuCLMFzTW7GPiYiIqNiwtdbDx8VeLek8AQTe8zEpqWmIjJeMrGRcj0vC7chIxEeGISEqDCkx4UiLuTO1MOEmbO5MLXROjUQpxKhAlieikGznAVNiUIqIiIjMhhRAD6hWXy05ZVmFhwQhPOg0AivUNEn7iIiIiMyFtZUens52aknncd9AVlqahuiEFNyMS8KJuCRU9HSEKTEoRURERBaTZeVVNkAtRERERJR/er0Obo42agmE6a+GbJpL2xARERERERERUYnGoBQRERERERERERkdg1JERERERERERGR0DEoREREREREREZHRMShFRERERERERERGx6AUEREREREREREZnTVKGE3T1M+oqChTN4WIiIjMjGF8YBgvUO44piIiIqKCjqlKXFAqOjpa/SxXrpypm0JERERmPF5wc3MzdTPMGsdUREREVNAxlU4rYacC09LSEBwcDBcXF+h0OpT0yKUE54KCguDq6mrq5tB98HhZFh4vy8LjZTmK+ljJsEgGT2XLloVezyoH98IxlfE+l1S4eLwsC4+XZeHxshxRZjKmKnGZUtIZ/v7+pm6GWZEPIAdQloPHy7LweFkWHi/LUZTHihlSecMx1d34f4hl4fGyLDxeloXHy3K4mnhMxVOARERERERERERkdAxKERERERERERGR0TEoVYLZ2dlhypQp6ieZPx4vy8LjZVl4vCwHjxWZI34uLQuPl2Xh8bIsPF6Ww85M4gElrtA5ERERERERERGZHjOliIiIiIiIiIjI6BiUIiIiIiIiIiIio2NQioiIiIiIiIiIjI5BqRJo6tSp0Ol0WZYyZcqYull0x9atW9GrVy+ULVtWHZuVK1dm6RspAyfHULY7ODigXbt2OH78OPvPDI/V0KFD7/quNWvWjMfKRKZPn46HHnoILi4u8PHxQd++fXH69Oks+/D7ZTnHit8vMgccU5k3jqksB8dUloVjKssx3QLGVAxKlVC1atXC9evXM5ajR4+aukl0R2xsLOrVq4fPPvssxz6ZOXMmZs+erbbv3btXBRQ7d+6M6Oho9qGZHSvRrVu3LN+1devWGbWN9J8tW7Zg5MiR2L17NzZs2ICUlBR06dJFHUcDfr8s51gJfr/IHHBMZb44prIcHFNZFo6pLMcWSxhTydX3qGSZMmWKVq9ePVM3g/JAvqIrVqzIuJ+WlqaVKVNGmzFjRsa6hIQEzc3NTZs/fz771IyOlRgyZIjWp08fk7WJ7i00NFQdty1btqj7/H5ZzrES/H6ROeCYynJwTGU5OKayPBxTWY5QMxxTMVOqhDp79qyachQYGIgBAwbgwoULpm4S5cHFixcREhKiotsGdnZ2aNu2LXbu3Mk+NEObN29WqbJVq1bFc889h9DQUFM3ie6IjIxUPz08PNRPfr8s51gZ8PtF5oBjKsvE//MtD//PN18cU1mOSDMcUzEoVQI1bdoUixYtwp9//omvv/5aBTlatGiBiIgIUzeN7kOOlShdunSW9XLfsI3MR/fu3bF48WJs3LgRs2bNUtMtO3TogMTERFM3rcSTE7Hjx49Hq1atULt2bdUf/H5ZzrES/H6ROeCYynLx/3zLwv/zzRfHVJZDM9MxlbVRXoXMinzoDOrUqYPmzZujUqVK+P7779WHlMyfFJ/L/h9M9nVkek888UTGbfmPv3HjxggICMDatWvRv39/k7atpBs1ahSOHDmC7du337WN3y/LOFb8fpE54JjK8vH/fMvA//PNF8dUlmOUmY6pmClFcHJyUsEpST8n82a4SmL2rChJr8yePUXmx9fXV/0Hz++aaY0ePRqrV6/Gpk2b4O/vn7Ge3y/LOVY54feLzAHHVJaD/+dbNv6fbx44prIco814TMWgFKm0vJMnT6oPH5k3qQEmgyi5coJBUlKSuqqCTMEk8yZTZIOCgvhdMxHJKJQzRMuXL1fpyfJ9yozfL8s5Vjnh94vMAcdUloP/51s2/p9vWhxTWQ7NAsZUnL5XAk2YMAG9evVC+fLlVYbNu+++i6ioKAwZMsTUTSMAMTExOHfuXJZCnIcOHVLF6OSYjR07Fu+//z6qVKmiFrnt6OiIQYMGsf/M6FjJMnXqVDzyyCPqP/RLly7h9ddfh5eXF/r168djZQJyOdyffvoJq1atgouLS0bGoZubGxwcHNQUDn6/LONYyXeP3y8yBxxTmTeOqSwHx1SWhWMqyzHSEsZUJrvuH5nME088ofn6+mo2NjZa2bJltf79+2vHjx/nETETmzZtUpfpzL7IpToNl62XS1CXKVNGs7Oz09q0aaMdPXrU1M0uke51rOLi4rQuXbpo3t7e6rtWvnx5tf7KlSumbnaJldOxkmXhwoUZ+/D7ZRnHit8vMhccU5k3jqksB8dUloVjKssBCxhT6e40lIiIiIiIiIiIyGhYU4qIiIiIiIiIiIyOQSkiIiIiIiIiIjI6BqWIiIiIiIiIiMjoGJQiIiIiIiIiIiKjY1CKiIiIiIiIiIiMjkEpIiIiIiIiIiIyOgaliIiIiIiIiIjI6BiUIiIiIiIiIiIio2NQiogKxebNm6HT6XD79u0CPc/QoUPRt29fiz0q7dq1w9ixY++7X5s2bfDTTz/BmB599FHMnj3bqK9JREREecfxVDqOp4hKDgaliCiL+fPnw8XFBSkpKRnrYmJiYGNjg9atW2fZd9u2bSoQdebMGbRo0QLXr1+Hm5tbkffol19+iXr16sHJyQmlSpVCgwYN8MEHH1jMkVyzZg1CQkIwYMCAQnm+7777Ds2aNbvvfm+99Rbee+89REVFFcrrEhERUc44nip6HE8RFQ8MShFRFu3bt1dBqH379mUJPpUpUwZ79+5FXFxclrN5ZcuWRdWqVWFra6v2kSBVUfrmm28wfvx4vPzyyzh8+DB27NiB//3vf6rNlmLu3LkYNmwY9PrC+S949erV6NOnz333q1u3LipUqIDFixcXyusSERFRzjieKnocTxEVDwxKEVEW1apVU4EmCTgZyG0JelSqVAk7d+7Msl4GXTlN35PsHcli+vPPP1GjRg04OzujW7duKpvKIDU1VQWYZD9PT08VXNI07Z5H5Pfff8fjjz+O4cOHo3LlyqhVqxYGDhyId955564pgNOmTYOPjw9cXV0xYsQIJCUlZewjrzNz5kxUrFgRDg4OKvNq2bJlWV7rxIkT6NGjh2p76dKl8fTTTyM8PDxje2xsLAYPHqy2+/r6YtasWff9NMnj//77b/Tu3TvLeuk7yQDr2bMnHB0dVZ/t2rUL586dUynskhXWvHlznD9/PsvjEhIS8Ndff2U837x581ClShXY29urNsuUvcxkvyVLlty3nURERPTgOJ76D8dTRHQvDEoR0V0kCLJp06aM+3Jb1rVt2zZjvQR4JGhiCErlRLKqPvroI/zwww/YunUrrly5ggkTJmRslyDOt99+q7Kftm/fjps3b2LFihX3PCKSjbV7925cvnz5nvv9888/OHnypGqvBGHkeSVIZfDGG29g4cKF+OKLL3D8+HGMGzcOTz31FLZs2aK2S/BM3m/9+vVV1tj69etx48YNFRAzePXVV9Xzy3NLYEgCc/v3779nu+R9GoJO2UlgTYJchw4dQvXq1TFo0CAVTJs0aVJG5tqoUaPuep/SJxKck30kg+ztt9/G6dOnVZuldlVmTZo0wb///ovExMR7tpOIiIgKhuMpjqeIKA80IqJsvvrqK83JyUlLTk7WoqKiNGtra+3GjRvazz//rLVo0ULts2XLFklp0s6fP6/ub9q0Sd2/deuWur9w4UJ1/9y5cxnP+/nnn2ulS5fOuO/r66vNmDEj4768nr+/v9anT59cj0lwcLDWrFkz9dxVq1bVhgwZov3yyy9aampqxj6yzsPDQ4uNjc1Y98UXX2jOzs5qv5iYGM3e3l7buXNnlucePny4NnDgQHX7zTff1Lp06ZJle1BQkHrd06dPa9HR0Zqtra3qE4OIiAjNwcFBGzNmTK7t//jjj7WKFSvetV6e94033si4v2vXLrXum2++yVi3ZMkS1e7MnnvuOW38+PHq9m+//aa5urqqY5abw4cPq+e9dOlSrvsQERFRwXE8xfEUEd2fdV4CV0RUskj2k0xNkxpSt27dUjWjZBqcZA7JFDbZJllB5cuXV9PfciMZQTLlz0CmuIWGhqrbkZGRKhtJpqQZWFtbo3HjxvecwifPIRlax44dU1lNMp1wyJAhWLBggcoMMtRpkul48voG8jpSdyooKEi1Qaa9de7cOctzS/aXFE0XkvEkWVAyNS87mUIXHx+v9s/cfg8PD5Wufy/yOJlal1vNJwOZeifq1KmTZZ20WwqVy5RE6SeZzvjzzz+r7fJ+AgIC1DGRqZKy9OvXL0s/yFRFkbk2GBERERU+jqc4niKi+2NQiojuIrWa/P39VVBGglISjBIyTSwwMFAVF5dtHTp0uGfvyRX7stdNul/NqLyqXbu2WkaOHKmmxMmVASVIda/phIY2pKWlqdtr166Fn59flu12dnbqp+zTq1evHK/qJ4Gxs2fPPlC7vby8VJ/er78MBeNzWmdov0zDk8BYq1at1H25auKBAwdUwFCmE8rV9qZOnaqCi1K3S8gUSeHt7f1A7SciIqK84XiK4ykiuj/WlCKiHElwR4IbskhNBAMJUEnxcqnrdL8A0L24ubmp4I48j0FKSsp9azLlpGbNmuqnZHAZyJX5JCvJQF5Hsp4k2Cb7S/BJalzJgDHzUq5cObV/w4YNVa0puVpd9n2k6Lj8lIBR5vZLsOnMmTP3bKtkYoWEhOQamMqPVatW4eGHH4aVlVWWbLNOnTqpIu5HjhzBpUuXsHHjxoztkmEmfSDBMSIiIipaHE9xPEVE98ZMKSLKdRAlWUjJyckZmVJCbr/44otqGllBglJizJgxmDFjhrpanBT+nj17dsbV+3Ijry1XB5QsLQmuyBTAd999V2X+ZJ5KJxlEcoU+KWguRdGnTJmiioTL9D7JKJKC61LcXLKOJNNIpsTJVEAJXMl0QHnvX3/9tbqynxQ0lyCOXAlPpsrJetlPnl+2yZUDZWrd5MmTM6YP3isoJW2VbDO50l5BrF69Okvx9jVr1uDChQuquLm7uzvWrVun3l/mKYXbtm1Dly5dCvS6RERElDccT3E8RUT3xqAUEeU6iJJMI7kKnKG+kSEoFR0drWpFGbKKHtQrr7yigkpDhw5VwZxnnnlG1UCSelO5kSwguWKfXDUvIiJCBYskGCVXoZPgkEHHjh1VsEsCNHKluQEDBqipbJmvdCd1sqZPn64COTK9TbKjXn/9dbVdAl8SOHrttdfQtWtX9RxSr0nqNBkCTx9++KGqU9W7d28V6JL3c6+2C8lqkve5ePHiAgWlpK6VBMmkbQbyHpYvX67epwQN5f3LlQflynxC1smVAiXTjYiIiIoex1McTxHRvemk2vl99iEisigS5JKMq5UrV8Ic3bhxQwWKZKqiBLoehGSV/f333yobKq8+//xzNeVP6k0RERER3QvHUxxPERkDa0oRERmZZJ598803qqbVg5Kpi5MmTcrXY6QG1qeffvrAr0lERERkLjieIioemClFRMWOuZ/ZIyIiIjJ3HE8RkTEwKEVEREREREREREbH6XtERERERERERGR0DEoREREREREREZHRMShFRERERERERERGx6AUEREREREREREZHYNSRERERERERERkdAxKERERERERERGR0TEoRURERERERERERsegFBERERERERERGR2DUkREREREREREZHQMShERERERERERkdExKEVEREREREREREbHoBQRERERERERERkdg1JERERERERERGR0DEoREREREREREZHRMShFZMZ0Ol2els2bNxfodb777jv1PPv27bvvvkOHDkWFChVgCvK6md+3s7MzmjZtikWLFqG4OHnypOrj8uXLw9bWFl5eXujRowf++OOPAj3vvHnz1HE2hri4OEydOrXAn0siIqLCwPFUOvndnJe+aNeundpfftauXdtsPoQPOr4ICgrCqFGjUKlSJdjb28Pd3V29t8WLF0PTtAduz08//YQ5c+bAWN5//32sXLnSaK9HZCzWRnslIsq3Xbt2Zbn/zjvvYNOmTdi4cWOW9TVr1jRa77755psYM2YMTKVly5b46KOP1O2rV6+q20OGDEFsbCxefPFFWLLly5dj0KBBqFixournatWq4caNG1i4cKEKTL366quYOXPmAwelJMAlAS9jDBqnTZumbhsGtkRERKbC8VS6Z599Ft26dcvol+vXr6N///4YPXq0Gn8YuLq6whw9yPhix44d6NmzpzqRKeOounXrIjIyEr/++iueeuop/P777yq4pNfnP1dDHnfs2DGMHTsWxgpKPfroo+jbt69RXo/IWBiUIjJjzZo1y3Lf29tb/dLMvv5BJScnqzNi+SFnmUypVKlSWd5/p06dEBAQgNmzZ5t9UEoGU46OjjluO3/+PJ5++mnUqVNHnQF0cnLK2PbYY4+p9/bhhx+iYcOGGDBggBFbTUREZNk4nkrn7++vFoNLly6pn5KdXVhjy+xjTGtr0/25efv2bRV0c3Nzw549e1C6dOmMbX369FEBqokTJ6J+/frqJxGZBqfvEVk4mdKWU/aLnEHKfBZJAh0yOPjhhx/wyiuvwM/PD3Z2djh37lzGPrdu3cKwYcPg4eGhgiK9evXChQsX7jt9T55X0qLluWvUqKECL/Xq1cOaNWvuatfZs2fV2TgfHx/1+rL/559/XqAglWQUXb58OWPd9u3b0bFjR7i4uKi2tGjRAmvXrs3YHhUVpQZJEuQxCA8PVwE/GbikpKT8n737AG+qauMA/k/TXUpLSxmltOy9995DQAVERUS2KFtEhijKED8QUREVEFkyBFS2IBvK3rtsKLRAS4HSvdt8z3tCagstFGibpP3/nudCcu9NcnJvm5689z3vSV4/bNgwFQxMmd69fft29fxyJVGeX7K3duzYkWaK/IkTJ9RVLUkVf1pA74cfflBBq59++ilVQMrgu+++U+/166+/fuI10huOaehsyvny8fGBt7d3cmq+4Rwafi6WLl2KESNGoFChQrCzs0PTpk1x8uTJp/5MpfUzIa8px0vI1UzD62VHhhYREdGLyu39qac5evQoGjdurNoj2dxTp05FUlJSho5JRvsqQkYCyLF2dXVVfREJlnXp0kX1j16kfzFv3jwEBQWp9qYMSBmMHj0a5cqVU/1BCaKl166U79EwdFDaKX1L6X+mHPoo5LFyW7Lbpd8m70OGDdaqVeuJ/mJ6ZTEeP25yW0YF/P77708MsyQydwxKEeUyY8eOhZ+fH+bMmaNSlqUzY9CvXz8VmDGMkT9y5Ij6gydXmp5F/jD//PPPmDRpElatWqU6Yp07d07VCTt//jxq166tUp0lyCKdrA4dOqjAjyEd+3lJJ0I6BIaOigReWrRooVKz58+fj+XLl6vglHQIV65cqfaRYJK0Q4JLBtJJkA5UeHi4et8Gso88n6FjIMGbNm3aqOeQjoGkf8t7bdu27RMdDSFX6EqVKoW//vpLHfP0bNu2TXWY0rtSKR1BeV05doGBgc91jNasWaM6kdWrV1dDGGSRdSl99tln6lxJB06WO3fuqHP/eCf6WQoXLozNmzcn/zwZXk+GIxIREeUUOa0/lR7pc3Tv3l0NdVu/fj3atWun3rv0h57nmDyLBHLkPUg9zQULFqi+hASTJKgXFxf3Qv0L6VtptVrVB0yL9O1ef/11BAcH4/jx43jesghyUVIu5hna8vgwUTmP0mb5GZDjJT8Tcvwe3y8j5DESqJNyDobXkjYQ5QQcvkeUy0i2jgRI0iJXcCSQY1CxYkX1B1euvH3++edPfd7o6GgVwJEAkJBhZu7u7ipoY0iJlkwc2S6ZTIZ6Ba1bt0ZsbKzqeEhnSjKKnkYylgyZTFJTSq4kyVUwqRMg5LXkOeRKltQPEFJLQFKzR44cibffflt1QmTYn3Tk5LUlGCVtlw6jBGPktmRXyW0pPP7xxx+r55ErdVJPS54vZVBHOgjyfiWwI+nhKUm9q4x0EKUTJ218muLFiyfvK52gjJJglHRk5JinF/SSoJ68J0PwrVGjRihdujSmTJmC3377LcOvJceyZs2a6rYMEcjs4QBERESmwNz7Uxn14MEDbNq0CXXq1FH3pf8kfSwJuPXs2TPDx+RZJCgUExOjspYkO8wgZa2r5+1fSH9J+jdpZaCn1bd6nj6L1HOVDHbp96T3uMTERBUYkywpIRcwJSvqyy+/VOufh7yGBLXk/bBvRTlNrs6U2rNnj4qcywe9fBF73tkM0pvB4mkffETGJmnQ6ZErYSlJYEbqNUlx9Wdp3rx5cgdKSNaPXCEzDKuTjoZkEsnVPsn6kcCSYZGgjmw/dOjQM19HOkZWVlZqkY6EdNKkQOfkyZNVWrMEhWS4nCEgJeQqmdRrkiDWpUuX1DoZficdvwMHDqj70gGUDp10tgwdBUMmlawTsq9cTZNAU8r2Swq7FA6V9HZpQ0aP9/MyDCF83jpgGSGdvpTPK+ddzn9Gzj0R0cv2qQyfcTJ5RZkyZdQXvaJFi6rCvkSmyNz7UxklF8EMASkDqcWUsmxCZvR55MKcZEl98MEHKhP9eTO1TbFvJdnyhoCUMGTuy+elBKyISC9XB6Xky6NE4iW18kVI1oXMWpFykai5FCUmMlWS/pyetLJvZJ1cJXsWGf//OPlSIYEfIc8hHSapmWQIKhkW6UQZ6jo9i2TwSPDn2LFjKn1dUuFnzpypOjJSw0E6F2m9R/miZGiHoYMonTkJPEnNA0kbNwSlJLAVERGhtsmwN8NVNJkJT0jQ6/H38M0336jXlqBVRo93SlJvwNfX96n7GOobyBe1zPYy556I6GX7VEIyUWX4sASmLl68qIb/PP5lmMhUmHt/KqOe1Z4X6fOkRbKspN8lAbjBgwer+7L8+OOPL/yc0re6d+/eExcMjd23kuGI0s8kIr1cPXxPxvTKkh75wBg3bhyWLVumvvhWqlRJffE0FJWTTIyU2RinT59WX5KfVjeGKLPJFRhJ136cdEjy58//xPqnXQlKq1aRrJOaSC9L0sgNGUvS2UiLIfjzNFKIXNLi03sNSW2WAPHjZCieMBwTCWJJgEs6QJIGLp0EmflOglBCUtPlSqQM1TMwPFY6gumlTj9eSDOjV94kICZp/XJ1M63nlqGDksEln0OGTo7h6pthCKLBi3RG0zv3KTuj8npSq+txmdn5JaLc2aeSodKzZ89WNXJk8gqi7Jbb+lNZIa1j8jx9FSmmLotkEcnFR+lvDR8+XPWtXmTmYelbbd26VQW403q8XEyUOllSt8swNDBle1PKzL6V9EEN3yGf9nNHlFvk6kypZ5FZM/bv348VK1bgzJkzKgNKhujIbBdpkat7knIuH6ZE2UXGpsvPZ0qXL19OHqb2POTLQkoyXE3SszNjdg/JSpKUdJnRTdK+JbD0+JLW1bjnIUNn69ati9WrV6e6gifD66TApASf5HfUQLKipIaBFBI1DNGT55CgkHSEJJBlWC+kHoTUD5Dgc1rtl0U6Gi9C6lZJ3ScZipjWFT3JzJRMMPlSZ2CYreXx8y+dr4xe1TSQgvApZxiU8y7nP+W5l9eTn62UnSe5YmsYApnytcTTXo+Icpdn9ankc0suCkjBZvlCLZ8377///hPZp0RZhf2prDuuGe2rGEjQTfpzhtkEZSbjF+lfyGeIZF5JAXapP/o4mR1PsjJlFj7JNHtaeyV49bx9K+mPynBKA5lMR963fFeU92h4PWmbIRvfEMTfsmXLc78ekbnK1ZlST3Pt2jX1JU1q0BiG/ciXQplBYeHChU/UOJAvafKF3lCAkCi7yJUymRFl0KBBaiy/BBPkj6xhNrrnIVel5A+4fFnw9/dXxThlWl957swgKdiSnSR/jAcOHKj+EMsfaBk+J3+kZSrglyWFueXKmATA5HdWgkQyO4lcfZff6ZRX8aSulFyNk4woqV9gIIGo8ePHq31l5j0DuaolwSqpKSVflGQYn3R2JDVcMiXlf7nS/yIkRV2mUpY6FDKjjhQxlWwB6aTILDT//vuvej9du3ZNfoyk6cvVPZmFRmbpsbS0VFMZy7l7nGSByZdBmYFQvvjJlTlZZyAdIqlP0b9/f5UNJe9f9pGOXMqftV9//VX9vMl+EpCSnzVDkdWUNROkdsa6devUMZY2ylXmtKY8JqKcLyN9KqkfI3+/pEjy4sWL1WezBOvlczYz/jYQPQv7U1kjo30VGWkiv+syA58Mu5NgjvR/hOEC4fP2L+RCogSGJOtdMqFkUhwZZhwWFqb6Q/LdTfpVhslyhPTBpP8ln1EyTFIy02QiGCkq/zjpR8nzS99Pnl+y9VNm80vgSfqk0qeTC6SSHSqvnXICHHl9KXwumVzSDnnfUpYirZpT8nqSyS99ZhkqKceDmaWUI+hIkUOxZs2a5KPx559/qnUODg6pFktLS93bb7/9xFH7448/1LaAgAAeUcoyvXr1Uj+HKSUlJemmTZumK1GihM7W1lZXq1Yt3c6dO3VNmzZVi8GuXbvUz/Rff/31xPMuXLhQbdu6dauuR48eOmdnZ52dnZ2uffv2uitXrjzRBi8vr1Tr5LGDBw9+4nllP9k/JV9fX13fvn11RYoU0VlZWenc3Nx0DRo00E2ePPmZ71+er0OHDs/cb+/evboWLVqoYyXvo169eroNGzY8sZ8cu/z586v23759O3n9/v371boaNWqk+fze3t6qHS4uLuo9yHuR+ymP7fjx49Vz3Lt3T/c8fHx81DHz8PBQzy2v8corr+g2btyY5v5HjhxRx0/eq7RDXnfevHnqteVYG9y4cUPXpk0bnaOjo9pmOIeGn4slS5bohg0bps6HjY2NrnHjxrpjx4498Xq///67rnz58upnrUKFCrqVK1em+TOxfft2XfXq1dVzyfM//nNARDnXi/Sp+vfvr/a5dOlS8uOOHz+u1l28eNEo74Nyrtzen0r5HPKa3377bZrb5X1XrFjxifWPt/1pxySjfZWDBw/qOnfurJ5X+g6urq7q9devX//S/Qs/Pz91XOXcWltb65ycnHRNmjTRLV26VJ33x12+fFn1mfLmzauO69ChQ1U/TF5P3qtBcHCw7s0331TnWaPRqO0pj+s333yjmzhxourTyetKu7ds2fLE623atElXrVo19bMibfz555+T+5EpnTp1StewYUOdvb292pby55LInGnkH2MHxkyBZERIFLxTp07qvkTPJWPBx8cnOb0yZbbE44XrJFov2QIpp4knIjJ1csVNssokO0EyEoiIjNGnkuxMyZiKj49P3ibDVGTot9SEkWwDIiJzIMXTZRjyt99+qzKuiOjpOHwvHdWrV1dpkzKk5Vk1omTGLJniNa2xxkRERES5WUb6VFKzT4bKyFA/Gc4spIadkOE6RERElDPl6qCUTMUptWxSBpdOnTqlxidLMWS5qtezZ0989913qkMlsyDIWGcZz2uYclXIeGcZ1/u0WWeIiIiIcqqX7VNJzZgaNWqgb9++mDFjhqq/IjOLSYZUygkqiIiIKGfJ1cP3DMNWHidFjKUAn6SQT548WRXcvH37tpoZrH79+qo4naFAsHSa5AqedLS+/vprI7wLIiIiIvPvU8mMpzIDqQzXk5lQ5WKfBLEksEVEREQ5U64OShERERERERERkXFYGOl1iYiIiIiIiIgoF2NQioiIiIiIiIiIsl2uK3QuNaCkZoGjo6OaspiIiIjIQKoahIeHw93dHRYW5nPtbvbs2WqRqchFxYoV8eWXXz51EhZvb2+MGDECPj4+6v2OHj0aAwYMyPBrsk9FREREL9unynVBKQlIFS1a1NjNICIiIhPm7+8PDw8PmAtp69SpU1GqVCl1//fff0fHjh1x8uRJFaB6nMyOJ7Pe9e/fH0uXLsX+/fsxaNAguLm5oUuXLhl6TfapiIiI6GX7VLmu0HloaCicnZ3VgcmbN6+xm0NEREQmJCwsTF28CgkJgZOTE8yZzFr37bffol+/fk9sGzNmDNavX48LFy4kr5MsqdOnT+PgwYMZen72qYiIiOhl+1S5LlPKMGRPAlIMShEREdHT+gvmKDExEX/99RciIyNRv379NPeRwFObNm1SrWvbti3mz5+P+Ph4WFlZPfGY2NhYtRhISr5gn4qIiIhetE9lPsUSiIiIiChdZ8+eRZ48eWBjY6OyntasWYMKFSqkuW9gYCAKFiyYap3cT0hIwP3799N8zJQpU9SVTsPCcghERET0shiUIiIiIsoBypYti1OnTuHQoUMYOHAgevXqhfPnz2f4yqWhokN6VzTHjh2rhuwZFimFQERERGS2QSm54la7dm01E16BAgXQqVMnXLp06ZmPk9liatasCVtbW5QoUQJz5szJlvYSERERmSpra2tV6LxWrVqqj1W1alX8+OOPae5bqFAhlS2VUlBQECwtLeHq6prmYyQDyzBUj0P2iIiIKDMYtaaUBJcGDx6sAlOSLv7555+r+gZyVc/BwSHNx2TGbDEZrccgNRUoZ5EaGVqt1tjNICIiynKS+ZSyBlRKUmtqw4YNqdZt3bpVBbTSqidFRET0Mvj9OuexyqTv1kYNSm3evDnV/YULF6qMqePHj6NJkyZpPkayojw9PTFjxgx1v3z58jh27BimT5+eKUEp6cDJlUOpEE85k8y+KFeIzbmILRERUUqfffYZ2rVrp+o8SQHyFStWYPfu3cl9LRl6d/v2bSxevFjdl5pTP//8M0aMGKEu9Enhcylyvnz5ch5YIiLKNPx+nbM5Z8J3a5OafU/qEximME7Pi8wW8zwMASkJjtnb2zNwkcM+EKOiotTwBFG4cGFjN8ns3Q2LQVRcIiyi7sEiTj8LExFRdnDK7468zmkPM8uN7t69ix49eiAgIEAVIa9SpYoKSLVu3Vptl/V+fn7J+xcvXhybNm3Cxx9/jF9++QXu7u6YOXNmpmadE+VKUpst6gEQo/9e89wsLAFnTynultktIzIKfr/OmXSZ+N3a0pTelFyta9SoESpVqpTufs+aLebxg/H49MVhYWFPTSk0BKTSq6dA5s3Ozk79L788cp45lO/FrTp+C5/8dRrNLE5igdV0WGj0BXKJiLLDkcoTUKfLxzzYj8jFuadZtGjRE+uaNm2KEydO8BgSvYiYMCD4GvBAlqup/499wYCUQcOPgNaTeF7I7PH7dc5ml0nfrU0mKDVkyBCcOXMG+/bte+a+zzNbjBT6nDhxYobaYKghJRlSlHMZzq+cbwalXszDyDh8tfE8LJGA8VZLVUAqSmeDRE7oaXQ6XlnNFhqdDjqY8VVsM266gUZrbewmEFFOFx8DPPR9FGwyBJ4eBZ8i9dkBadMANo4v8GGrA2LDgEOzgdr9AeeiL/kGiIyL369zPvtM+G5tEkGpoUOHYv369dizZw88PDyeuu/zzhYjNRQkAytlppTUW3ga1hrK2Xh+X960LRcREhWPUfkOoHh0AGCfH/bDTgK2eTPh2YmInq02DxIRZYbEBCDUL+2Mp1B/faAoPQ5ugGspwLUk4FLy0e1SgEtxwEqfQfBc5EL7768BN/YCe74FXp/5Um+NyFTw+1fOpcmEC+JGDUpJhpMEpNasWaOKcUp9g2d53tliZPpiWYgoc5z0e4gVR/3hiCh8kPSnfmWzTxmQIiIiItMkwZ7wgLQznh7eAJKeMuO2TV590EkFmwyBJ/m/JGDrlLntlC93zT8HFr4CnFyqH8Ynr0NElIMZNSg1ePBg/PHHH1i3bh0cHR2TM6CkQKdhfCJnizEdEyZMwNq1a3Hq1KkXfo4bN26o4OPJkydRrVo1ZAWpmzF8+HDOoJgFEpN0+GLdOdW3m1FkF6weBAOupYGavbPi5YiIiIheXGI8sG4wcGEDEB+V/n5am0fZTiX+y3YyBJ8kGyo7h8Z71QdKtQKubge8vwHemJt9r01E2Ybfrf9jASOaPXu2mnGvWbNmqkC5YVm5cmXyPunNFiOZVRLU+OqrrzhbTAr+/v7o16+fmkXH2toaXl5e+Oijj/DgwYPnTsOTAFRKI0eOxI4dO178hANq6KSc06cVsyfT9ccRP5y7HYbStiFoEbpKv1IKcWpfbtZLIiIiokx3fBFwZqU+IKXR6oNOpVoDdQcC7acDPdYCw88CnwcCgw4C7ywDWk8EavTQB4fyFDDOLHgtxun/P/MnEHQx+1+fiBR+t84eRh++9yycLSbjrl+/roY3lilTBsuXL1cBPB8fH4waNQr//vsvDh06BBcXlxc+X3ny5FHLy5DiZ1IXjMzP/YhYfLtZ3zGa474JmjsxgFcjoGw7YzeNiIiI6MnZ8XZP1d9u/RVQdwBgaSYTJLhXB8q9Clz8B9j9P+DtxcZuEVGuw+/W2ceomVKU+cMhJTtKamzJNM+enp5o164dtm/fjtu3b+Pzzz9X+xUrVkxlmL377rsqyCRZVT/99FPy88h20blzZ5UxZbgvKYYph9z17t0bnTp1wv/+9z8ULFgQzs7OaqbDhIQEFQiTAJgUrl+wYEGq4XvynIYhgPIccv/xRTLhRFxcHEaPHo0iRYrAwcEBdevWTd6WMnAp71Uq/0ubnzcrjDJm6r8XERaTgNcLBKHknX/0K9t8ZZwriERERERPc2AmEHVfXweq3sAsC0jJRfb4xCRExiYgODIOAaHRuHE/EleDItJZwtNc/B5Epb5gL7WlZPa+8+uAgNM810TZjN+t7bPtu7VJzL5nyuSPQ3R8olFe285Km+Fq9sHBwdiyZQu+/vrr5HpcBpKZ1L17dzUsctasWWrdt99+i88++0wFmuRxH3/8McqVK4fWrVvj6NGjKFCgABYuXIhXXnnlqVM77ty5UwWeZObE/fv3q6GDBw8eRJMmTXD48GH1mgMGDFDPm9ashz/++COmTp36X+Bj6lSV5SVtEX369FGBrBUrVqjgmRTFlzadPXsWpUuXVq/Rt29fFRh74403sHnzZowfPz7Dx5gy5tiNYPx9/JaageZrh5VAGIDKbwNFavAQEhERkWkJCwAO/qJu3q83FmevPkRsfBJiExIRm5CEuAS5/ei+Wm9Yp9+ulvhExCXK/4+tT0j87/GPtiU9e/BHhoxoXQbDWpbW3ylYAaj8JnD2L2Dn10D3R5PLEJkxfrfmd+u0MCj1DBKQqvDlFhjD+UltYW+dsVN05coV9Utevnz5NLfL+ocPH+LevXvqfsOGDfHpp5+q2zLcTwJKP/zwgwoeubm5qfWS+fSsoXaSDTVz5kxYWFigbNmymDZtGqKiolTAy1CoXgJN8vzvvPPOE4+XovayiNWrV2POnDkqs0te99q1aypAdevWLRWQMtS1ksCTBMwkECVBrbZt26Z6LwcOHFD7UOZISEzCuLXn1O3xZW/B8eZBfUHQll/wEBMREZHp2T1F1ZGKLVQLjTfkQXT80Wx7aWutBawtLaC1kOz/J7endblZYlohUfH4aecVtK9cCKUKOOo3NP0UOLcauLIF8D8CFK2T5e0nykr8bs3v1mlhUCqXMKQDGzKvpPZUSnJ/xowZz/28FStWVAEpAxnGl7KIuWRZubq6Iigo6KnPI7Px9ezZE7/88gsaNWqk1p04cUK1WwJNKcXGxqrnFBcuXFBphY+/FwalMs+SQzdxMTAcrnYW6BkxX7+y3gDA2TMTX4WIiIgoE0hh8JNL1M1frHoiOj4JBRxt4Olir4JFNmrRwsZKf1u/TvuM9RawsdKqgJNhe6ptjx4n2y0snr+sgfR33//9GHZcDMLna85hxQf19H32/KWAat2Ak0uBnV8BvTbwR4TIBPC7deZiUCoDQ+gkY8lYr51RpUqVUn+8zp8/r+o8Pe7ixYvIly8f8ufPn+5zZHSoYEpWVlZPPEda65KSktJ9jsDAQLz++utq6J8sBvIYCWodP378iSGEhoLrGSmWTy8uKCwG32+9rG7PruADrc9lwM4FaDSCh5WIiIhMz46JgC4JIZ5tMPNyfpWttLBPbVR012fmmyLpK0/sWBEHrj3AYV99yYS3aj0qe9F0DHB6JeC7B7juDZRoauzmEr0wfrd+Oqtc+t2aQalnkJOe0SF0xiSZQzL0TmpGSX2olHWl5Adz2bJlKhPJEHiSmfhSkvuGOk5CfvgTE7O+llZMTAw6duyoXvv7779Pta169eqqDZJl1bhx4zQfX6FChTTfC2WO/226gPDYBNQrYo3aN+boVzb7FLBz5iEmIiIi03JjP3BpE3QaLb6I6KJWdanhYdIBKQOPfPYY3qo0pvx7UfW/WpYvCBcHa31mes3ewNHfgF1fA8WbcJIZMlv8bp21Ysz0uzVn38tBfv75ZzW0TWosSeFxf39/NYxNglUye50UQTeQGk9S/+ny5ctqyNxff/2Fjz76KHm7zLi3Y8cOFdCSWlRZ5cMPP1TtlLpUUu9KXk8WmXVPhu1JgXYJpkm9KV9fX1WE/ZtvvsGmTZvU44cNG6beo+G9yDHg0L3Mcej6A6w9dUddYfzRcw80kff0M9jU7JNJr0BERESUSeQK/zZ9vUu/Ym9iwx1HlZUxsk1ZsznEfRsVR7lCjngYFY8pmy78t6HxJ4ClLeB/GLiyzZhNJMo1+N36crZ9t2ZQKgeR2eiOHTuGkiVLomvXrur/Dz74AM2bN1cz4klRcoNPPvlEpe5JxPSrr77Cd999p4JZBnJ/27ZtasY82SereHt7IyAgQEVlCxcunLxIsXIhBc0lKCXtlULqkoooM+4ZZvKrV68e5s2bh59++gnVqlXD1q1bMW7cuCxrb24hUxt/uU5f3HxAdTsUPPubfkPriVk2pTIRERHRCzu/Frh9HDorBwwL1Pdp+zcpgUJOtmZzUK20Fvi6c2V1QfCv47dw+PqjqdjzFgbq9NffltpSLF9BlOX43bpatn231uhyWVGesLAwNdtbaGgo8ubN+0S6m2TjFC9eHLa25vMH7HlJFtTw4cPVkhvllvP8Mn7bcx1fb7qg0sYPVlgFm7PLgaL1gL6bmTJORLm2n0A8VmSiEuKAWXWB4Os4XuxDdLnYFG6ONtg9shkcbEy/DMfjPltzFn8c9kNJNwds+qixKqSOyAfAj1WAuAjg7SVAhdeN3UyiZ8oN37v43Tom3XOc0T4VM6WIKJXA0BjM2K4vbj6lIWBzdoV+Q9uvGZAiIiIi03N8kQpIJdm7YfCNBmrVyDZlzDIgJca0LYf8eaxx7V4k5npf1690cAXqDdLfltpSSVlf+5WIKDswKEVEqUzeeB6RcYmo6ZUPbW7NkiINQMU3AI9aPFJERERkWmLCAO+p6uYm114IjLFSdZnerPlo9joz5GRvhS9eraBu/7TrKm7cj9RvqD8YsHUC7l0Ezq0ybiOJiDIJg1K50I0bN3Lt0D16uv1X7+OfMwGw0ADf1bgPzfWdgNYaaDWeh46IiIhMz4GZQNQDxDmXwMhrVdWqzzuUh1Y6M2bs9aruaFw6P+ISkvDFunP6qdpl9uMGw/Q77J4CJMYbu5lEuR6/W788BqWISIlNSFSdHtGrXlEUOz5Fv6HOB0C+YjxKREREZFrCAoADP6ub8216IiZJi2Zl3dC4tBvMnUajwVcdK8Ha0gJ7r9zH+tN39BvqDgDs86vhijj1h7GbSUT00hiUIiJl/j5fXL8Xifx5bDC60HEg6Dxg6ww0GckjRERERKZn9/+AhGiEu9XANzdLq0zvz9qXR05RLL8DhjYvpW5/9c8FhEbHAzZ5gMYj9Dt4TwMSYo3bSCKil8SgFBGp4uY/7biqjsSXbT1ht1dfmwFNRwN2+XiEiIiIyLQEXQROLlU3J8d1k9wivFPHE2UKOiIn+aBpCTUL3/2IWEzbfFG/slZfwLEwEHYLOP67sZtIRPRSGJQiItXJiY5PRC2vfHgtcjUQEagfslf7fR4dIiIiMj3bJwC6JNwp3Aor7xaBg7UWH7cqg5zGxlKLrztXVrf/OOKHE34PASs7oMko/Q57pwNxUcZtJBHRS2BQiiiXO+UfgtUnb6vbk1q6QrN/pn5DqwmApY1xG0dERET0uBv7gMv/QqfRYsT9jmrVwGYl4eaYM/st9Uq44s2aHpBa55+tPov4xCSgeg/A2ROIuAsc/c3YTSQiemEMShHlYjKTy6QNPuq2dHYqXPwFiI8EPGoDFToZu3lEREREqUlkZtuX6qZPoU44FO6Kwk626NeoRI4+UlIrK5+9FS4GhmPhfl/A0hpo+ql+474ZQEyYsZtIRPRCGJSiTFOsWDHMmDEj1awha9eu5RE2YTKTywm/ENhba/FpTR1wcol+Q5uv5QQau3lEREREqZ1fC9w+Dp2VPQbfaatWjWpbFnbW2hx9pFwcrDH2URH3H7Zdwa2HUUCVroBraSA6GDg029hNJKJMViyXfL9mUCqH6N27t/ohNSyurq545ZVXcObMGaO1KSAgAO3atTPa69PTRccl4pt/9QUzBzUrifwHv1a1GVD+dcCzLg8fEZGZmDJlCmrXrg1HR0cUKFAAnTp1wqVLl576mN27d6fqNxiWixcfFVImMkUJccD2iermTpeuuBmbB5WLOKFTtSLIDd6q6YE6xV1UHdDx63ygs9ACzcfqNx78GYgKNnYTiXIMfr/OPgxK5SAShJJAkCw7duyApaUlXn31VaO1p1ChQrCxyZlj+3OC3/Zex53QGBRxtsMHRW4CV7YCFlb6WlJERGQ2vL29MXjwYBw6dAjbtm1DQkIC2rRpg8jIyGc+VoJXhr6DLKVLl86WNhO9kOMLgYe+SLBzw3C/RmrV5x3Kw8Iid2R3S+D4f50rwUqrwY6LQdjiEwhU6AwUrATEhgEHfjJ2E4lyFH6/zh4MSuUgEgCSQJAs1apVw5gxY+Dv74979+6p7XK/TJkysLe3R4kSJfDFF18gPj4++fGnT59G8+bN1ZXWvHnzombNmjh27Fjy9gMHDqBJkyaws7ND0aJFMWzYsKd2eFOmF964cUPdX716tXoNaUPVqlVx8ODBVI953tegFxMYGoPZu6+p22PblYb1Dn1tBtTpD7iW5GElIjIjmzdvVld0K1asqP62Lly4EH5+fjh+/PgzHyuZVYa+gyxabc4eAkVmTGomeX+jbi6z64ZwnR1aVyioioDnJqUKOOLDJvq+2oT15xERnwQ0/1y/8fAcICLIuA0kykH4/Tp7MCiVkWKKcZHGWeS1X1BERASWLVuGUqVKqaF8QoJNixYtwvnz5/Hjjz/it99+ww8//JD8mO7du8PDwwNHjx5VHdlPP/0UVlZWatvZs2fRtm1bvPHGG2pI4MqVK7Fv3z4MGTLkudr1+eefY+TIkTh16pQKkHXr1k1d0c3M16Bnm7b5okr9ruWVDx0SdgJBPoCt83/TCxMRkdkKDQ1V/7u4uDxz3+rVq6Nw4cJo2bIldu3a9dR9Y2NjERYWlmohyjb7fwSiHiAqbwl8dacWLC00GNuuXK48AUNalIKXqz0Cw2Lw3dZLQNl2gHsNID4K2Pdf357I5Jjpd2vB79dZxzILnztnkA/3/7kb57U/uwNYO2R493/++Qd58uRRtyW7SDqZss7CQh97HDduXKqiaZ988okK/IwePVqtk6uqo0aNQrly+j/wKVP4v/32W7z77rsYPnx48raZM2eiadOmmD17NmxtbTPURglIdejQQd2eOHGiuqp79epV9ZqZ9Rr0dKf8Q7D65G11e0JbT2hW9dJvaPYpYP/sLzBERGTas6qOGDECjRo1QqVKldLdT/oIc+fOVVnREmxasmSJCkxJrSnJWE6vdpX87SbKdmF3gIO/qJvTE95BAizRu54XSrjp+725ja2VFpM7VUKP+Ufw+4Eb6FLDA5VajAOWvgEcnQ/UHwI45Y46W2RmzOi7teD36+zBTKkcRIbFSQaSLIcPH1b1JKTQ+M2bN9X2v//+W3VSJT1fglcyfE8CUQbSiX3//ffRqlUrTJ06Fdeu6Yd3CcmckiwreZxhkaympKQk+Pr6ZriNVapUSdUhFkFBQZn6GvT0LyuTNvio22/W9EClG4uAyCDApQRQqx8PHRGRmZPsYsk2Xr58+VP3K1u2LPr3748aNWqgfv36mDVrlrpoNH369HQfM3bsWJWFZVikRABRttg9BUiIxv181bAguCIcbS0xrGXurn/WuLQbXq/qjiQd8Nmas0gs3hzwaggkxgJ70/89JqKM4/fr7MFMqWexstdHVY312s/BwcFBDdczkKufTk5OapieFDx/55131BVOCfTI+hUrVuC7775L3n/ChAkqU2njxo34999/MX78eLVP586dVWDoww8/VDWeHufp6Znxt/RoOKCQGlNCntvwf2a8BqVv/ek7OOEXAntrLcY0yAMsfFQQs/VXgKU1Dx0RkRkbOnQo1q9fjz179qjh+M+rXr16WLp06VNra3ACE8p2QReAk/qfyzFhb0kPEkNblIKLA/st414tj12XgnDmViiWHLqJ3lJbalF74MRioMEwwKU4f2DJtJjRd2vB79fZg0GpZ5HAyXOm+ZkKCfrI0L3o6Gjs378fXl5eqqaTgSGDKiWp8yTLxx9/rOo9SbFUCUrJlVQfH59UQa/Mlh2vkZtFxyXim3/1U30PalYSboe/ARJiAK9GQDn9kEoiIjLPLFgJSK1Zs0YNvyte/MW+iJ48eTI5i5nIZGyfAOiScNW1GXbcLg6PfHbo1aCYsVtlEgo42mLMK+Uwbu05TN96Ga+MaIpCJVsA13YC3tOAzrON3USiHPPdWvD7ddbg8L0cRGpCBAYGquXChQuqgyoF2V577TUV6JGhepL5JMPypFaTdF4NJHAlKf/SmZVglQSxpOB5+fLlk2fuk5nyZMppGR545coVdTVWXiOzZMdr5Ga/7b2OO6ExKOJsh/4lQ4EzK/Ub2k7W/4EgIiKzJH83JcPpjz/+UJOaGPoC8rc95dC7nj17Jt+fMWOGmiFX/tbKBSHZvmrVKk4uQqblxj7g8mboNFoMDeqoVkkQxsaSs0QavFvHE9U9nRERm4CJUqJBakuJMyuAe5eNdeaIcgR+v84ezJTKYVNCG65wSqdUiof/9ddfaNasmVon2U8SeJJfLqkbITWlZMiekCmgHzx4oDqsd+/eRf78+dUseIaCplILytvbW2VaNW7cWF2VLVmyJLp27Zpp7c+O18itAkNjMHu3vkbY2HZlYbPjff2Gqt0A9+rGbRwREb0UmQxEGP7eG0i2c+/evdXtgICAVHUk4+Li1OQjt2/fhp2dnZp4RIbvt2/fnmeDTIPMlLX1C3XzYL7XcOFOQRV8ebUKs/lSsrDQ4H+dK+PVn/bh33OB2FmrFlqU7QBc2gjs/h/w1iIjnUAi88fv19lDo5Nv/rmITF8s9ZSkQGfevHlTbYuJiVEFtSXtnTO95Vy58TyPWHlKzbhXyysf/mp6D5o/ewKWdsDQ45ydhYgog/0ESo3HirLUudXA332QZGmPupHf4Z7OCasG1kdNL84UnJb/bbqAuXuuq4z47e+5wm5eU4nsAQP2AYUq84eVjCI3fu/KbWKeco4z2k/g8D2iHO6Uf4gKSInx7UtBs228fkODoQxIERERkelJiAN26LP119h3UQGpDpULMyD1FMNblVYBqdsh0Zhx1hqo9IZ+w999gQf/zahNRGRqGJQiysEkEXKS1BcA8GZND1S+8xfw0BfIUxBo+JGxm0dERET0pOMLgYc3EGubH18ENYe11kLVkqL02VtbYuLrFdXt+Xt9ca3KJ4CjO3D/MjCvJeC7h4ePiEwSg1JEOdj603dwwi8E9tZajG7iBnh/o9/Q4gvAJo+xm0dERESUWkxocn9lFt5GFGzRq4EXPF2ffzr33KZVhYJoW7EgEpJ0GLU9BEnv7wDcawDRD4ElnYFjC4zdRCKiJzAoRZRDRccl4pt/L6rbg5qVRIETP+o7egUrA9XeNXbziIiIiJ60/0cg6gFCHYrh55D6cLa3wpDmpXmkMmjC6xXhYK1VFyVXXEwA+mwCKr0JJCUA/3wMbBoFJCbweBKRyWBQiiiH+m3vddwJjVH1BfpXSAKOztNvaDsZsOBUykRERGRiwu4AB2epm5Oi30YitPioZWk42VsZu2Vmo7CTHUa0KatuT/33Au7FWABd5umz5MWRucCyLvrsKSIiE8CgVBqSkpKy/0xQtskN5zcwNAazd+uLWo5tXw42uybqr5CVeQUokXrKcCIiIiKTsOt/QEI0bjlWwaqoqiie3wHd63oZu1Vmp1d9L1QqkhdhMQn4cMkx3A2PBZqMBLouBazsgeu7gXmtgPtXjd1UyiVyw/ev3CopE86tZaa0JIewtraGhYUF7ty5Azc3N3Vfo9EYu1mUiUW/4+LicO/ePXWe5fzmVNM2X0R0fCJqeeVDB8erwKWNgEYLtP7K2E0jIiIielLQBeDUMnXzk4dvAtDg03blYG3Ja+jPy1JrgalvVEG3uYfUML4OM/fip241UL/8a0DfLcDybsCDq8C8FsBbi4CSLfgTSVmC369zLl0mfrdmUCoFOZjFixdHQECACkxRzmRvbw9PT091vnOiU/4hWH3ytrr95avloNnYUb+hVl/ArYxxG0dERESUlu0TAF0STjs2weF7pVCnuAvaVCjIY/WCKhVxwvqhjTBw6XFcDAxH93mHMLJtWQxoUhkWH+wCVnQHbh0Blr4JvDIVqNMf4MV4ymT8fp3z2WfCd2ujBqX27NmDb7/9FsePH1eBoDVr1qBTp07p7r979240b978ifUXLlxAuXKZM02sRPjkoCYkJCAxMTFTnpNMh1arhaWlZY7NgJOI9aQNPur2mzU9UOXBZiDwDGDjBDT71NjNIyIiInqS717g8mboNFoMv6+/mDauQ/kc21/LLjL8cc2ghhi39hxWnbiFaZsv4cTNh/jurWpw6v0PsOEj4PRy4N9RwL0LQLtpgJb1uyhz8ft1zqXNpO/WRg1KRUZGomrVqujTpw+6dOmS4cddunQJefPmTb4vQ+0ykxxUKysrtRCZk/Wn76g0bXtrLUa18AAWddVvkDoCDvmN3TwiIiKi1KQeyTZ9Ee6tdu3gG10Ynaq5o4qHM49UJrCz1mL6W1VQq1g+jF/vg+0XgvDqz3sxu3tNVOo0GyhQHtg2Hji2ALh/BXh7MWDvwmNPmYrfr8lkg1Lt2rVTy/MqUKAAnJ35h4oopei4RHzz70V1e1Czkih4dh4QHgA4ewF1P+TBIiIiItNzfg1w5yQSLO3xeXAH2FhaYNQrmTMCgv4LCHSr44lK7k4YuOw4/IOj8cbsA/iqY0V0bfgRkL8MsOp94MZe4LcWwLsrATf9DH5ERFnNLIvqVK9eHYULF0bLli2xa9cuYzeHyCT8tvc67oTGoIizHd6vZgfsn6Hf0HoiYGlj7OYRERERpZYQC+yYpG4useiI+3BCv0bFVV+GMl9lDyf8M7QRWpQrgLiEJIxZdRaj/z6NmBJtgH5bAWdP4KGvfma+K9t4CogoW5hVUEoCUXPnzsWqVauwevVqlC1bVgWmpDZVemJjYxEWFpZqIcppAkNjMHv3NXV7bPtysN0zBYiPAorWBSqkX6eNiIiIyGj2zwQe3kCUdX58G9Ya+fNYY2CzkjwhWcjZ3hrzetbCqLZlYaEB/jx2C2/MOoCblsWA/rsAzwZAbBjwx9vAwV+kYCnPBxFlKbMKSkkQqn///qhRowbq16+PWbNmoUOHDpg+fXq6j5kyZQqcnJySl6JFi2Zrm4myw7TNFxEdn4haXvnQwe1e8pTKaPs/zqRCREREpifYF9ir78NPiu+OKNhieKsycLRlTdesZmGhweDmpbCkX124OljjfEAYXv1pH7beSAB6rgOq91AzIWLLZ8D6oUBCXJa3iYhyL7MKSqWlXr16uHLlSrrbx44di9DQ0OTF398/W9tHlNVO+Ydg9cnb6vaXr5aHZus4mYcPqPQm4FGLJ4CIiIhMi2Tf/DsaSIiBb95aWBFdB6UL5ME7tXnxODs1LJUfG4c1Rk2vfAiPScAHS45jyrZrSOjw46MLmxbAySXA4o5A5P1sbRsR5R5mH5Q6efKkGtaXHhsbGzVTX8qFKKfQ6XSYtMFH3X6zpgeqRB0CfPcAWhug1XhjN4+IiIjoSRc2AFe2QmdhhQEP3pVS3PisfXlYas3+q4nZKeRkixUf1EPfhsXV/V+9r+O9BUcQVKkf8O6fgE1ewO8A8Ftz4O55YzeXiHIgo37yR0RE4NSpU2oRvr6+6rafn19yllPPnj2T958xYwbWrl2rMqN8fHzUdqkvNWTIEKO9ByJjWn/6Dk74hcDeWotRrUoAKksKQP1B+mKVRERERKYkNgLY/Km6udb+TVxKLIQmZdzQrKybsVuWa1lpLfDlaxXw87vV4WCtxaHrwXh15j4csawJvL8dyFccCPED5rcGLm02dnOJKIcxalDq2LFjaiY9WcSIESPU7S+//FLdDwgISA5Qibi4OIwcORJVqlRB48aNsW/fPmzcuBFvvPGG0d4DkbFExyXim38vqtuDmpVEwcvLgQdXAfv8QKMRPDFERERkerynAmG3EWnvgU/vt4WNpQUmd6wEjUZj7Jbleq9Wcce6IY3UUMqg8Fh0++0QfrtgBd37O4BijYG4CGD5O8D+H1kAnYgyjUYn439yEZl9TwqeS30pDuUjczZzxxV8v+2ymjZ5x6CqsJ1dC4gOBl79AajV19jNIyIyS+wn8FhRFpLhX3MaAbpEDNV8ig3RVTD6lbIY1KwUD7sJiYxNwGdrzmLdqTvq/isVC2HaG+WRd9fnwLEF+p2qdgNe+xGwtDFuY4nI7PtUHLhNZIYCQ2Mwe/c1dXts+3KwPfi9PiDlVg6o/t+QVyIiIiKTkJQEbByhAlJnHRurgFTZgo7o37iEsVtGj3GwscSMrtXwVadKsNJqsNknEK/POowLNSYA7b4FNFrg9HJg0atARBCPHxG9FAaliMzQtM0XER2fiFpe+dChSAxwZK5+Q5uvAa2lsZtHRERElJoEMfwOIlFrhw/vvaVW/e+NyqqeEZkeGU7Zo54X/hrQQGXl33gQhc6zD2CVZXvgvb8BWyfg1hHgtxZA4FljN5eIzNhL/RWIjY3NvJYQUYac8g/B6pO31W0pSqnZMQFIjANKtgRKt+JRJCIiItMSFQxs+0LdnKd9G3eQH93reqKmVz5jt4yeoVpRZ2wY2kgVo4+JT8Inf53G2NNuiO29DXAtBYT6A/Pb6GdUJCLK6qDUli1b0Lt3b5QsWRJWVlawt7eHo6MjmjZtiq+//hp37ujHHRNR1pAScJM2+Kjbb9b0QJXEC8D5dYDGAmgzmYediMhM8UIf5Wg7JgJRD3DfvgS+DWuJ/HlsMPqVcsZuFWWQi4M1FvaujeGtSkPq0S8/4oc3/7qHW102ACWaA/FRwMr3gD3TWQCdiLImKLV27VqULVsWvXr1goWFBUaNGoXVq1erINX8+fNVUGr79u0oUaIEBgwYgHv37j1/S4jomdafvoMTfiGwt9ZiVJvSwJbP9Btq9AQKVuARJCIyE7zQR7mG/1Hg+O/q5rCwHkiAJca/VgFOdlbGbhk9B62FBsNblcGiPnXgbG+Fs7dD0eG3c9hV6xegzof6nXZ+BazuD8RH89gSUebOvlenTh188cUX6NChgwpKpef27dv48ccfUbBgQXzyyScwRZxVh8xVdFwiWn63G3dCYzCyTRkMyX8KWP0+YJ0HGHYSyFPA2E0kIjJ7Wd1PkAt9Y8aMUc/fvn171ccqUqQI7OzsEBwcjHPnzmHv3r04ePCgyk7/6quv4ObmBlPEPhU9U2IC8FszVXPI264Vej3si6Zl3LCoT21Vs4jM0+2QaAxadgKn/UPU/SHNS2GEy35Y/DsKSEoAitQE3vkDcCxk7KYSkRn0EzIUlMpJ2IEic/Xj9iv4YftlVWxyx7A6sJ1TFwi7BbT4Amgy0tjNIyLKEbK6n5AVF/qmTJmiMtgvXryoglsNGjTAN998o7Lcn8bb2xsjRoyAj48P3N3dMXr0aJXxnlHsU9EzHZoDbB6DOKu8qBc+DVFWztj2cVMUdbHnwTNzsQmJ+HrjBSw+eFPdb1jKFbMaRMJpQz8g+iHg6A50Ww64VzN2U4nISDLaT8hwTSkZnhcdzVRMImMICI3GHO9r6vbY9uVge2yOPiCV1wOoP5gnhYjITBw5cgSvvfbaUwNSQrKnpk2blqHMcwkuDR48GIcOHcK2bduQkJCANm3aIDIyMt3H+Pr6qkytxo0b4+TJk/jss88wbNgwrFq16oXeF9ETwgKAnfp6l9MS3kEw8qrhXwxI5Qw2llpM6lgJP75TDXZWWuy/+gBt1wLn2q8B8pcFwu8AC14BfNYYu6lEZOIynCklnSdra2t1ha958+ZqkStxss6c8KoemaMRK0+pGfdqeeXDX++VhOanGkBcBPDGPKCKflplIiJ6eTmhnyC1PQsUKKCCVU2aNElzHxlCuH79ely4cCF5nWRJnT59Wg0dzC3HirLQ332Bc6vgZ1ceTR9+jrKFnNQsblbal5r8m0zQ5bvhGLD0OK7fi4SlhQYT2nig+61J0Fzdpt+h2Vig6RioKulElGuEZbCfYJnRJ/T398fOnTtVB2fp0qWqxoGtrS3q16+fHKSqW7cuLC0z/JRElAGn/ENUQEp8+VoFaHaP1wek3GsAlbrwGBIRmZlJkyZlaL8vv/zyhZ5fOn/CxcUl3X0k8CTZVCm1bdtWTWATHx+vZllOa4bAlLMESmeTKE3XdqqAlE5jgYEhPdQswV93rsyAVA5VpqAj1g9phDGrzmDjmQCM2+yPQ5XH4Ps6pWF9ZBawewpw7yLQcRZgzaGbRJRJNaUkSLVr1y7s3r1bLTdv3oS9vT3Cw8NhynhVj8yJ/Hp2mX1Azbj3Zk0PTG9iBcxpCOiSgD6bAa/6xm4iEVGOkh39hOrVq6e7TYo/X7p0CTExMUhMTHyhvxsdO3bEw4cPVcH09JQpU0YVUpdhewYHDhxAw4YNcefOHRQuXPiJx0yYMAETJ058Yj0zpSiVhFhgVn0g+BpWWb2KT8LfxXv1PDG5U2UeqBxOPn8W7r+B/226gIQkHUq4OeCPmpdRaM9nQFI8ULiavs5UXndjN5WIzDFT6nFFixZVHRfDVbMHDx68UOeJiNK3/vQdFZCyt9ZiVNuywLp39QGpCh0ZkCIiMlNSwyktp06dwqeffqpm4Ovfv/8LPfeQIUNw5swZ7Nu375n7Pj77meE6ZXqzoo0dO1YVRk/Z2ZT+IFEq+39UAalIK1dMCO8EN0cbjGpbjgcpF5DPjr6NiqNqUScMXnZSDedrvsMTc5vOR+MTHwMBp4C5zfUz83nUNHZzichEPNeg7uvXr2PBggXo0aMHPDw8UKNGDTXbS6VKlfDvv/+qq3JElDmi4xLxzb8X1e1BzUqi4N19wLUdgIUV0GoCDzMRUQ4hRcffe+891K5dW11RlNnw5syZ89zPM3ToUFUnSjLZpZ/2NIUKFUJgYGCqdUFBQaoMg6ura5qPsbGxUVc6Uy5EqQRfB/ZMVzfHRXdHOOwx/rUKcLJ7cjgo5Vw1vVzwz7BGaka+6PhE9Nhuie+LzUGSW3kgIhBY2A7Y+gUQftfYTSUiE5DhTCkvLy91RaxRo0aqaKZ0fGrWrAmtVpu1LSTKpebuuY47oTEo4myH9xt6AvPe02+o+yHgUsLYzSMiopd0//59NRxu7ty5qn8lw+ckMPW8JMNJ+mVr1qxRJRWKFy/+zMdITdANGzakWrd161bUqlUrzXpSRBn4QQQ2jQYSY3HWuhrWxNRFs7Ju6FD5yaGglPPlz2ODxX3r4odtl/HzrquYeSIeR4p8hYUlfoPd9S3AgZnAkblA9R5Aw2GAs6exm0xEpp4pZShsKWmZEoiS5VnTGRPRiwkIjcYc72vq9tj25WB7Zqm+QKSdC9BkFA8rEZEZi4yMVMGokiVLqkCUBId27NjxQgEpMXjwYDUJzR9//AFHR0eVASVLdHR0qqF3PXv2TDXTntQDleF4MgOfZMJLkfORI0dmynukXOjCBuDqNiRaWGFYeA/YWmnxVcdK6Q4HpZxPa6HByLZlsaB3LZUtd+h2HBr49sO5pnMBj9pAQgxw9DdgZnVg7SDg/hVjN5mITL3Q+cWLF9UVOEkLl1n4pAinXNlr1qwZmjZtqjKnTD1QxULnZA5GrDylZtyr5ZUPf/WpCM3MGkDUfaDdNH2mFBERmW0/QYbOycQwkt3UrVu3dL+0V6lSJUPPl97jFy5cqIqZC/n/xo0bqh9nIH25jz/+WA0XdHd3x5gxY1SwKqPYp6JksRHAL3WAsNv4DV3wdUwXjG1XDh82LcmDRIp/cBQGLjuOc7fDIB9Zr1QoiE/K3EWpi78Cvt6GTzOgYieg8SdAIRbGJzJ3Ge0nvPDse0KurBlm4NuyZYvqFIWEhMCUsQNFpu7A1ft4d95hdXv9kIaocnEGsO8HwLUUMOgQoOWwCiIic+4npLyAJ32nlF0xw33539QnkGGfipJtHQcc+AkPrAqjQfgUFC/kig1DG8FKa9oXqyl7xcQnYtI/5/HHYb/kdfVKuGBUxTDUuLkAmsub/9u5dFugyUigaB2eJiIzleWz7929e1fN7iLL6dOn1RU/KYBJRC9X3PzT1WfV7e51PVHFIRQ4OEu/sc1kBqSIiHJIYXOiHOOuT3Jf5ZPI9xCnscb/3qjMgBQ9QYZ0/q9zZfSqX0zVTl136jYOXQ9Gl+tAuUKDMarZB2h+bykszq8FrmzRL8Ua6zOnSjSTqD2PKlEOlOGglMzIIhlRhuF7ly9fVoUw69Spg3feeQfNmzdXRTOJ6MV9v+0S/IKj4O5ki0/blQP+GaAKhqo/yGVe4aElIsoBZPIYERcXB2tr63SLoBOZvKQk4J8RgC4Re7T1sTupOnrU80INz3zGbhmZsLKFHPHd21XxSZsyWLDPF8uP+OFiYDj6bQaKOPfAx/V7oVPkn7A8uxK4sVe/FKmpD06VaSfppsZ+C0SUiTI8fE9SzSUIJbOySABK6kg1bNgQdnZ2MCdMNSdTdco/BG/M2o8kHbCwd200d7gJzG+lH1//oTdQuKqxm0hElONlZz+hU6dOWL169RP1OCUbvWXLljh37hxMGftUhJNLgXWDEWdhh6ZR05Dg6I4dnzRFXluWGqCMC42Kx9LDN7Fwvy/uR8Spdc72Vhhc3QbvJa2H3dml+qLookAFfXCqYmfAgrPAE+WEfkKGw8z//vsvgoODsX//fkyePBmtWrUyu4AUkamKS0jCmL/PqIBU5+pF0LysG7DlM/3Gat0ZkCIiyoECAgLQr1+/J9bJhb9y5coZrV1EGRIVDGz9Qt38Pv4NBMAVE16ryIAUPTcnCUA1L4V9Y1rg686VUMzVHiFR8fh6fwSqHW2FqWX/RmjNIYC1IxB0HljVD/i5FnD8dyBBH8QiIvOV4aBU27Zt4eDgoKYcTs+oUZyqnuhFzNp9FZfuhsPVwRpfvFoBkLH0t44AVvZAi3E8qEREOdCmTZtw5MgRNQOeuH37tgpIVa5cGX/++aexm0f0dNsnANHB8LMshnnxbdUFtfaVC/Go0UvVnOpe1ws7PmmGWd1roIqHE2ITkjDneBiqH2iAUUWX4W7NTwC7fEDwdWDDMGBmNeDQHCAuikeeyEw994DcIUOG4J9//nlivXSonhawIqK0XQoMxy+7rqrbE16vCBereGDbl/qNDT8C8hbmoSMiyoFcXV3V7MVr1qxR/Sgpj1C9enUsX778iSF9RCbF/yhw4nd1c0RkT1hZ2WBSx0pq1kiil6W10KB95cJYN7gh/uhfF03KuKnRBH/5RKDu/prom28hrtcYC12eQkDYbWDzGGBGZWDvd0BMKE8AkZl57h7PihUr8N5772HPnj3J64YOHaqu6EkBdCLKuMQkHUavOoP4RB1alS+IV6sU1qfCh/gBeT2ABkN5OImIcjAPDw9s27YNf/zxh5o8RgJSWi3rpJAJS4jVZ6gAWIdmOKYrh49bl0ZRF3tjt4xyGAlyNiiZH4v71sGmYY3RqZq7CljtvB6FFgcqo7PVLJyuNgE6Zy8g6j6wYxLwQ2Vg52Qg8oGxm09EmV3o/PHA1KBBg7B161YsWLAA69atUwGpMmXKwNSxKCeZknl7r2PyxgtwtLHEthFNUejePmBpF/3Gnuv0098SEVGO6Sfky5cvzWySqKgo2NjYpApISS1PU8Y+VS4lX/z3fodwrTOaRE5FocIeWD+kIay0zO6jrOcfHIX5+3yx8qg/ouMT1TovZ2tMLnURDQMWw+LBZf2OUgKjZh/9BV6OOiAy6X6C5Ys8+TvvvIOHDx+iUaNGcHNzg7e3N0qVKvUy7SXKdfweRGH61kvq9mcdyqOQdTSwboh+Y50PGZAiIsqBZsyYYewmEL2428eBfT+omyOj+yBEkxcLOldiQIqyjWTkSbmLj1qWxuKDN/H7wRu4GRKHHsdKwMXuK0wsdwPtHi6D5d0zwKFfgKO/6ScNkpIYLsV5pojMNVNqxIgRaa7/+++/Ve2DkiVLJq/7/vvvYcp4VY9MgfzadZ93GAeuPUD9Eq5qvLxm9QfA2T8B11LAh3sBa6bBExFlN/YTeKwoHfExwK9NgPuXsE3bGP0jB6JnfS9VS4rIWKLjEvHXcX/8tvc6/IOj1To7Kwt8XuYO3opeAZs7R/Q7arRA5TeBRh8DBcrzhBGZUJ8qQ0EpKbyZEZKOvnPnTpgydjbJFKw44odPV5+FrZUFtgxvAq/AbcBfvQCNBdBvG+BRy9hNJCLKlbK6nxAZGalmM86q/bMT+1S5jEzCsv9HhFu6oHHEFDg4F8Dm4Y3haGtl7JYRISExCZvOBeJX72vwuROmjojUnxpW6h76Ja1Cnlve/x2lcq8CTUYC7tV55IjMJSiVk7ADRcYWGBqD1t97Izw2AeM6lMf71RyAWfXUtMpoMgpoMc7YTSQiyrWyup9QuHBhNUFM79694e7unuY+0jXbvn27yj5v0qQJxo4dC1PEPlUum21vQRtAl4T+cSOwLakWlvevh/olXY3dMqInPj/3Xb2PX72vq/8NehZ7iI+s1sPVf8t/O5dsCTT+BCjWkEeRyNxqShHRi/+hHLf2nApIVS3qjD4NigEru+kDUoWqAE1G89ASEeVgu3fvxrhx4zBx4kRUq1YNtWrVUsEpW1tbVa/z/PnzOHjwIKysrFQw6oMPPjB2kym3i48G1g5UAalNmqYqINWvUXEGpMgkycidxqXd1HLudijmeF/DprMBWHwjHxajFzoU6oSxeTejiP8/0FzbAcjiWR9oPBIo1VKewNhvgSjXyVCm1IABA/D555+jaNGiz3zClStXIiEhAd27d4cp4lU9MqZ/ztzBkD9OwkqrwT9DG6PsnbXA+iGA1hr4wBsoWIEniIgoF/QTbt26hb/++gt79uzBjRs3EB0djfz586tanW3btkX79u1hYWHas5mxT5VLbPkcOPgzQrWuaBw5BQUKFMI/QxvB1uq/mSKJTH1yIak59ecxf8QmJKl19fKFYVL+HSh9Zx00iXH6HQtX1WdOlXsNMPHPX6JcN3zviy++wMyZM9GgQQO8/vrraV7V27dvH1asWIEiRYpg7ty5qFy5MkwRO1BkLA8j49Dqe288iIxTM4Z8XMsGmN0AiIsAWk/SzwpCRERGxX4CjxWl4HcIWPCK5HqjT9wo7EENrBnUAFU8nHmYyOw8iIjF7wdvYvHBGwiJilfryjuE43+F9qBa0Bpo4qP0O+Yvqy+IXqkLYGlt3EYTmbFMrykVFBSE+fPnq8DTuXPnUm1zdHREq1atVIp5mzZtYMrY2SRjGbHyFFafvI2yBR2xYUgDWC/tCNzcp08Z7r0RsOAVRyIiY2M/gceKHomLAuY0AoKvYR2a4aOYDzC8VWkMb1WGh4jMWmRsgsqamrfXF7dD9DP2uVtH4psi+9HwwWpYxOkLpcMmL1DmFaD8a0CpVpwZm8iUCp2HhITg5s2byanmJUuWVON3zQE7m2QMuy4Goc+io7DQAKsHNUS1W8uALZ8BVg7AwH2ASwmeGCIiE8B+Ao8VPbJ5LHBoFoK1+dEscgq8irhj9aAGsNJyWBPlDPGJSdh4JkDVnboYGK7WOVtEY7LHYbSNWAerqLv/7WxpB5RuBZTvCJRpA9g6Ga/hRGYiSwudOzs7q4WIni08Jh6frzmrbvdtWBzVbAKB7RP1G9tOZkCKiIiITMuN/cCh2ermx9H9EGPpiB+6VmVAinIUCbB2ql4EHau5w/vyPTVj38HrDzDErxk0aIK3CwWiW57TqBi6G1bh/sCFDfpFasGWaAaUfx0o2x5w4CyURC+Ds+8RZbFpmy/hTmgMPF3sMaJlcWDxK0BirD4NuGYfHn8iIiIyHXGRwLpBqo7U37rm8E6qii/al0OpAo7GbhlRlpARP83KFlDLKf8QzN1zDf+eC8TKQHeshDuAV/CKaxB6OZ9B9Yg9sA29BlzZql80WqBYQ32AqlwHIK/sT0TP44WG75kzpuVTdjriG4y3fz2obv/xfl00uDUP2D0FsHUGBh0C8hbmCSEiyqX9BD8/PzWz8eMlEKRr5u/vD09PT5gy9qlyqE2jgCNzcc/CDS2ipqBiCQ/88X49WEgNAqJc4m5YDLaev4utPoE4eO0BEpL++8pc3/E+3s9/DnVj9yNPsE/qB3rU0degqvA6kK9Y9jecKLfUlDJn7EBRdomJT0S7H/fC934k3qldFFPrJQDzWgG6RKDLfKDymzwZRES5uJ+g1WoREBCAAgUKpFr/4MEDtS4xMRGmjH2qHMh3L/D7q+rme3FjccqqOv79qDGKutgbu2VERhMaHa/qw27xCcTuS/cQHf/fZ3MFu2AMKHAejRMOIt+Dk6kfWKiKPoNKAlRuZbO/4URm0k94rkqFEr8yFDjPDHv27MFrr70Gd3d3dZVw7dq1z3yMt7c3atasCVtbW5QoUQJz5szJlLYQZbYfd1xRAamCeW0wtnUxYM0AfUCqYmcGpIiISPWr0pooJiIiQvVziLJVbMSjYXvA8sRW2JdUGV++VoEBKcr1nOysVO2p2e/VxMkvW+O3nrXwZk0P5LO3wvloFwy72QjVb49Ck8TZWJ7/IwTlrwudDOsLPAPsmgz8Ugf4uTaw4yvgzin58M/1x5TohWtKSeepdOnS8PHxUf+/rMjISFStWhV9+vRBly5dnrm/r68v2rdvj/79+2Pp0qXYv38/Bg0aBDc3tww9nii7nLsdirl7rqvbkztVhtOBqcD9S0CegkCH73kiiIhysREjRqj/JSD1xRdfwN7+vywUyY46fPgwqlWrZsQWUq607UsgxA93LQpgckw3tCpfAG/V9DB2q4hMiq2VFq0rFFRLQmISjt54qDKoZJifXygw9lZdAHXhZhGODwpeQjvtURQJPgTN/cvA3un6xdlTn0Eli0dtwIIzWlLu9lxBKQsLCxWMkrTyzAhKtWvXTi0ZJVlRUl9hxowZ6n758uVx7NgxTJ8+nUEpMqnpZUf9fQaJSTq8WqUwWttdVlMqK6//DNi7GLuJRERkRCdPnky+2Hf27FlYW1snb5PbcsFu5MiRRmwh5TrXdwPH5qubw2P6w8bBCVPeqJJmJh8R6VlqLVC/pKtaxr9WAeduh+kDVOcDcfku8HVALXyNWnBEL/Rxu4SONidQPOQALEL8gIM/65c8hYDyr+rrUHk1ArSch4xyn+f+qZ82bRpGjRqF2bNno1KlSshOBw8eRJs2bVKta9u2LebPn4/4+HhYWVk98ZjY2Fi1pBzXSJSVJEPqQkAYnO2tMLGtJ7C4uZrBBjV6AWVS//wSEVHus2vXLvW/ZIr/+OOPWV67iuipYsKAdUPUzSWJrXEwqSJmd6oEN0cbHjiiDJIAbmUPJ7WMbFtWlfCQAJUsJ/2AmfeqYyaqwxbv4Z18l/G2w0mUDd0PbUQgcHSefrHLB5TtoK9BVaIZYMnfQcodnjtX8L333sORI0fUVTw7Ozu4uLikWrJSYGAgChYsmGqd3E9ISMD9+/fTfMyUKVNUcS3DIrPcEGWVq0ER+HH7FXVbrpi47psAhPoBzl5A26954ImIKNnChQtTBaTkwpnU17x48WKW1+ncvXu32u/x5UVem8zclrFAqD/uaApiSnw3dK5eBO0qc3ZgopdRPL8DBjQtiTWDGuLwZy0xuVMlNC6dHwkWtlj0sDLa3+qJcuG/YITlOBx3fQ3xNi5A9EPg1FLgj7eBaSWBv/sBPmuBuEieDMrRnjtTyjB0zljSmjY5rfUGY8eOTa7dYOjwMTBFWSEpSYcxq84gLjEJzcq6oZPdGeDkEvnpBDrNBmwceeCJiCjZ22+/jSZNmmDIkCFqEplatWrhxo0bqm+zYsWK5ypN8Lx1Og0uXbqUKjAmdTopF5EvvCeXIgkafBzzAfLmdcaE1ysau1VEOUrBvLZ4r56XWh6fyW91RAW1aPE2mttdQ+98Z1Arej9so+8C5/7WL5a2QKlW+hpUZdoCds7GfktExg1K9erVC8ZSqFAhlS2VUlBQECwtLeHq6prmY2xsbNRClNWWHLqJ4zcfwsFaiymvuEOztLt+Q/3BQLGGPAFERPREdtPnn3+ubq9Zs0YFo0JCQvD7779j8uTJzxVcet46nQYFChSAszO/4ORKobeADcPUzdkJr+GwrjyWvFVFzTRGRFk7k58sMfGJ2HvlviqSvv3CXWyPKoPt0WWgwRuoa+WLvq7n0CDuAPJE+QMX/9EvFlZAiab6GlTlXgUc8vNUkdl7oUpq165dUynn8r/UQpAOzebNm1UGUsWKWXd1pX79+tiwYUOqdVu3blVXFtOqJ0WUXfyDo/DNZv2Qh0/blUPhvZ8BkUGAWzmgxRc8EURE9ITQ0NDk0gfSj5IglMzE16FDB1W/MztUr14dMTExqFChAsaNG4fmzaUOYtpYpzMHSUoEVn8IxITCR1MKPyS8iZ71vdC4NDPliIw9k9+283dxKKQkDgWWlFmSUEnrj36uZ9E86RCcI64BV7frl38+Bjwb6GtQSYDKqQhPHuWOmlLe3t6oXLmymq549erViIiIUOvPnDmD8ePHP9dzyWNPnTqlFuHr66tu+/n5JQ+969mzZ/L+AwYMwM2bN9VwvAsXLmDBggWqyDlnqCFjkivbn605i6i4RNQp5oLu9keA8+sAC0ug86+AlS1PEBERPUEu5skkLjL0ToJShslcHj58CFvbrP3bUbhwYcydOxerVq1S/bmyZcuiZcuWKnsrPazTmYPsnwHc3IcYjS0GxQxCiYLOGNuuvLFbRYTcPpOfDJ/dN6Y5/hnaCENblEKZgo44l+iJj4M6oNr9r9AidjqWOPRCUJ7ygC5J/R7j39HADxWAX+oBGz4CTi0Hgn3lS4qx3xZRhmh0hqJMz5Gt9NZbb6nAkKOjI06fPo0SJUrg6NGj6NSpE27fvp3h55Iim2ldkZMhgosWLULv3r1VbQXZL2VQ7OOPP4aPj48q5jlmzBgVrMooqSklBc/l6iRnu6HM8PfxWxj512lYW1pgW79S8FrZUl15RPPPgaajeZCJiMxIdvYTZs2ahY8++gh58uSBl5cXTpw4AQsLC/z0008qUGSYpe95SZ1NGQ4o/bLnIYXS5bHr16/PcKaUBNbYpzIzt48D89sASQkYFf8B1mtaYP2QRihbiLUviUxR6pn8QpLXF8E9vOd0Bq9ZH0OR8DPQyGzfKeUpCBStC3jWA4rWAwpXAbQcXUSm16d67qCUdJzOnj2L4sWLpwpKSfCoXLlyKgXclDEoRZkpKDwGrb/fo4oWjmlbFgNvjQKu7QTcawD9tgHaFxohS0REuaSfcOzYMfj7+6N169aqjyU2btyo6jw1bNgwW4NSX3/9NZYuXaqy0TOCfSozFBsB/NoYCL6OTYl1MSh+GL7uXBnd63oZu2VElAF3w2LU8D4JUB289gAJSfqv8i4IQ1O7a2jreANVcQkFIy7AIik+9YMt7QCPWv8Fqjxqs2g6ZamM9hOe+xuzdJICAgJUUCqlkydPokgRjmOl3GXCeh8VkKpUJC8+sN+lD0jJDBkybI8BKSIiegapiylLSlJTyhikLyfD+igH+3eMCkjd1eTHp/H90K5SYbxbx9PYrSKil5zJz/uyFmuiq6tF2CAO1bS+6OB8E/Usr6BY9DlYx4UCN/bqF0UDFKgAeNbVZ1LJ/85ecmWD54Oy1XMHpd599101ZO6vv/5SV+KSkpKwf/9+VdcpZf0nopxu87kAbDobCEsLDX5olRfa1V/qN7SaALiVMXbziIjIxPXt2/ep26V25vPU6bx69WryfUOdTimk7unpqep0SomFxYsXq+0zZsxAsWLF1AQ1cXFxKkNK6kvJQjmUzxrg1FIkwQJDYwbC0dkNU9+oovrzRGTeM/nFJSThQkAYjt18iOM3g3HsxkMcDi+Lww/KAmgDDZJQQhOA1g7X0dz+OsonXEDeKD8gyEe/HHv09yZPIX0WlRryVxcoJEP+OPKDstZz/4RJarfUepKsKBn5J7O1JCYmqmCVzNpClBuERsVj3FofdXtgk2IofWA4EB8FFGsM1PnQ2M0jIiIzIAXNU4qPj8e5c+cQEhKCFi1aPPcwwJR1OqX2Z8o6nZLlbphIRkggSi4oSqDKzs5OBadk2GD79u1f+n2RCQrx1xdABvBLwus4rqmAP7tVh5M968sQ5QRS27ZqUWe19GtUXH1Pvx0SjeMqSPVQBakuBlpgTkQRzIlorB6TH6FoaH0FbfPeRHUZ8hd1CRYRgcD5tfpFWNkDRWoCnvX1mVQy5M/WybhvlnKc564pZXDt2jWV5i2ZUjKdcOnSpWEOWP+AMoMUNpcC5yXdHLC51glY7ZoIWDsCgw4AzkyDJyIyV8buJ0i/atCgQape5+jRpj1ZhrGPFWVQYgLw+2uA3wGc1pVCl9gv8XHbihjcvBQPIVEuEhGbgFN+Ifog1c1gdTs8NiF5uxryZ3ENr+S9gQZWV1E8xgfW8WGPPYsGKFjxUV2qR4Eqp6Ic8kfZW+j8ypUrZhOASgs7UJRZs+1Jtvs/bzmj4j8dASkk2HEWUL07DzARkRkzhX7CpUuX0KxZM5XdZMpM4VhRBuz8GtgzDVGwwyux/0PRkhWwuG9daC04bI8oN0tM0uHy3fDkbCpZ/IKjkrfLkL9Smjtobn8NLeyuo0LiBeSNvvXkEzm6p6hLVQ8oWIlD/ihrC52XLVtWFcFs2rSpWqTTJOuIcoNT/iH4bM1ZdXt4My9UPPyhPiBVtj1Q7V1jN4+IiHIAyUZPSPjv6jXRi/8w7QL2fKtufhrXD5H2RfHD29UYkCIi9TlQvnBetUjhdBEUFoMTfvrhfsf9HuLcbS3mRnpgbmRTtd0ND1HX6ipecbyBGppLKBR1GRbhd/Q162QRVg76Wf4MdanUkD9euCBkXlBKrtrt3LkT3t7e+OGHHzBw4EAULFgwOUA1YMCA531KIrMQFB6DAUuOq0KCrcoXxDCLVcDdc4C9K/Daj0xbJSKi52Ko+2QgyevSz5LaTlILiuilhAcCq/vLTxb+SGiB9UkNsPDtqiiQ15YHlojSJJ8Pr1QqrBYRE5+Is7dDk+tSnfCzxj+R+fBPcG213Raxashf6zy+aGB9FSVjzsM6Phzw9dYvQmPxaMhfigLqzkV5Bujla0oZyEwvkydPxrJly1QdBCl6bsqYak4vIjYhEe/+dlh9IJcqkAfrOlrBYWkHQJcEvL0EqPA6DywRUQ6Qnf2ElIXJhYWFBdzc3FSRc5mZz9LStGc8Yp/KhCUlAos7qqnfL+k88XrsJPRpWh6ftitn7JYRkRmT0IHv/chUQ/6uBEWkGvJXRnMLjW2uoYWDLyolnkfemDtPPlHeIo8CVPX0hdQLlAOsHbL3zZD5Dt+TKYf37duH3bt3q2wpmW64fPnyGDp0qMqWIsqJH74T1vuoD11HW0vMe6skHFa/qg9IVXmHASkiInqhvy0yK54Eoezt7XkEKXN5f6MCUlJHamDcMFQtXggj25ThUSail6LRaFDCLY9a3qqlz3YKiYrDSb8QVTxdvi+d8rfEpRhPzIvRX3gpIEP+tJfR2vEGalpcQuHoK7AIuw2cW6Vf9M8M5PMCClQECpR/tFQAXEsBltY8azncc2dKWVlZwcXFBT169FBX+Bo1aqSiX+aCV/XoeS05dBNfrD2nCpsv6lEVTY8MUB09NdPEgH2AnTMPKhFRDpFd/QTJLre1tYWPj4/ZTiDDPpWJurYLuiWdoYEOw+KG4IB9c2wa1ojD9ogoW8QnJuFCQFhyXarjNx4iMCwmebs9YlDV4hpa2F9HI+urKJZwDXZxwWk/mYUl4FoaKFjhv0CV/O9cTNKLeUZza6ZUhw4dVKbUkiVL4O/vDz8/P1VLSrKliHKaw9cfYOJ6H3V7dJuyaHp5ij4gZZ0H6LaCASkiInohMlRPglEPHjww26AUmW4dKc2jOlL/6BpgWbfqDEgRUbax0lqgioezWvqiuMoMvhMag2M3gnFCalPdfIjDAbY4GFEx+TGuCEUZi1uoZhOAmnYBaghgoVhfWCdEAPcu6JdUL2IPuJX7L0hlCFg5FmKd39xUU+rMmTNq+J4se/fuVal8EpxasWIFTBmv6lFG3Q6Jxus/7cODyDi8VtUdMz12QbNjor5YX7eVQJk2PJhERDlMdvYTpKD51KlTMXv2bFSqVAnmhn0qE5MYD/z+OuB3ABd1nugYOwkfvVIZg5qVMnbLiIhSiYxNULOay3C/83fCcPluOG48iERSqsiEDu54gDIW/qhpF4jqNgEoCT8UiLkBbVJc2kfULt+TgSr5X9ZTzsmUMqhSpYoqah4fH4/Y2Fhs3rwZq1evftGnIzIp0XGJ+HDJMRWQqlA4L6ZXuA7Nmon6ja98w4AUERG9tPfeew9RUVGoWrUqrK2tYWdnl2p7cHA6wxmI0rLlcxWQioA9BsZ9hEblPDCgSUkeKyIyOQ42lmhYKr9aDGSmv6tBESpAdeluOK7cjcClQHvsDsmP3ZESydLvp0UivDR3VTZVbYdAVLW6g+JJfnCJ8YMm+iFwc79+ScnR/clAlWRaWbOmoyl47qDUDz/8oIqcS3ZUeHg4qlWrpgqcf/jhh2jSpEnWtJIoG0ny4Kerz+Dc7TC4OFhjURsNbFYN0m+sOwCo+wHPBxERvbQZM2bwKFLmOL0COPKrujk8biDinUvgu7erwsJCwyNMRGbB1kqLSkWc1JJSeEy8muHvcqA+WKWCVoH22Bzhjs3h/+1ngziU1NxBOe0t1LG/i4qWt+GVeBN5YwOA8Dv65dqOFM+sAVyKP5lZJcXVtVbZ98bp+Yfv1apVSw3Tk0WCUFmd2p7ZmGpOzzJ3zzX8b9NFaC00+KtrEdTY2gWIvAeUbgt0Ww5YaHkQiYhyKPYTeKzMzp1TwIK2QEIMfkzojF/QFasGNEBlD/OZiIiI6HkFR8apAJU+SPXf/2ExCan2y4MolVVVwfI2atsHorz2NorG+8Iu/mHaT2xhBeQv82RmlbMXi6ubyvC9Y8eOPe9DiMyG9+V7mPrvRXX7q7ZFUWNff31AqmBl4M35DEgREVGmz8J39epVBAUFqdspMQOdninyAbCyhwpI7UyshhkJXfB918oMSBFRjicjWuqVcFWLgeTb3A2L1WdUPQpUyXLhriNOxJfB0lA8UVy9suVt1LIPRFnNLRSO84V1YiQQ5KNfUrJyAAqUSx2okv/zFGRx9Zf0QjWlQkJCMH/+fFy4cEEVOJeZ9/r166eiYETm6sb9SAz944QqsPdOzULo5velfqaHPIWAd1cCNo7GbiIREeUghw4dwrvvvoubN2+qjnRK0r+S2p1E6UpMAFb1BUL9cENXCMPjB6N/k1LoXN2DB42IciX521nIyVYtTcu4Ja9PStLh1sPoFMP/5H9HHLvnjINxFTE3uW66DkVw/9FMgHdQ3TYApeGPArE3oY2PBG4f1y8pWTsC+YoB+bwe/Z9icSoKWNlm6zHIFcP3JFOqbdu2qhhnnTp1VCdK1kVHR2Pr1q2oUaMGTBnT8iktEbEJeGPWfly+G4FqHk5Y5fkXtCcW6acb7bMJcK/OA0dElAtkZz9B6nKWKVMGEydOROHChVVnOiVTv9jHPpWRbfsS2P8jomCLTrETUbBUdSzqU0eVHyAiomeLT0zCzQeRuBQYkSq76vGZAKW4ejFNoBoGWMM2AFVt7qCEToqr34IFUmc5p6YB8rrrh/49HrCSJU+BHJ1lldF+wnMHpRo3boxSpUrht99+g6WlPtEqISEB77//Pq5fv449e/bAlLEDRY+TyPnAZcexxecuCjjaYEeDc3D0Hq//EHlnGVCuAw8aEVEukZ39BAcHB5w+fVr1q8wR+1RGdG418HcfdXNw3DD45GuBdYMbwcmexXmJiF6WYSbAK0GSVfVoRsDAcNwOiU61nxRXL6K5D09NEIpr76GCXTBKWt6Hu+4uXOLuwDox6ukvZGmXdoaVLBLIMvPZAbO0plTKgJR6EktLjB49WhVBJzI3P+28qgJS1loLLG/yAI47Jug3tJnMgBQREWWZunXrqnpS5hqUIiO5ex5YN0TdnJPwKrytGmFNz1oMSBERZfNMgFfuRuBmsBP2hhTB7ngdEJ9ybx1cEI6imiAVtCpn+wBlrB/Ay+IeCiYGwjH2LiwSooF7F/VLWqReVXpZVo6Fc0zh9ecOSkmEy8/PD+XKlUu13t/fH46OrLlD5mWrTyB+2H5Z3f6luQYl9wxXHyCo2QeoP9jYzSMiohzmzJkzybeHDh2KTz75BIGBgahcuTKsrFJnuVSpUsUILSSTFh0CrOwOxEdiX2JFfJvQFXPerYbSBdkHJyLKao62VqjhmU8tjw8DDAiJgV9wlFr8Hz76PzgKN4NdcTqqFDZI0lSKxCkrJMD9UZZVMe09lLcNRinL+yiCu8gffwc2CRFAxF39cuvIk43RWgPOnulnWdlmbba3UYNSXbt2VUXNp0+fjgYNGqj6B/v27cOoUaPQrVu3rGklURa4cjccH688pW4PrWmH1qcGAvFRQMkWQPtvc/T4XiIiMg6pIyV9p5TVE/r27Zt827CNhc7pCTI74+r+QPB13NLlx9D4oRjeujxaVyjIg0VEZERWWgt4utqrJS1hMfEqQCWLIXDlFxyNW8FOOPSwMPY+kWUF5EWECljJUto6GOVsHqCYNgiFEu/CKS4QFolxwIOr+iUtdi5pB6xkyVsE0L7QnHdZ4rlbIsEo6Sj17NlT1ZIScmVv4MCBmDp1ala0kSjThUbFo//iY4iMS0SzYrYYcf8LICIQcCsPvLUI0LImAxERZT5fX18eVnox3lOBK1sRA2t8GPcx6lcugyEtOPSTiMjU5bW1QkV3J7U8LjFJh7th/2VZ3UoVuHLFuYgSQIwUukpdeL2wJlgNDfTSBKksq9LWD+CBu3BLCIBdfAgQHaxf7px4skEWloCTx39Bquo9AA/jlWJ67kLnBlFRUbh27Zq6mie1EOztzaMIF4tykvzi9110FN6X76GokzV2FPkV1te3AQ5uwPs79MXmiIgoV8qOfoJkRv34449mX/aAfapsdHETsEI/ImFE3ACcL9ABqwY2gION6VzpJiKizBcVl4BbD6Ph9+C/YNWtR8MDZYmJf3L2vzyIQlHNPZVlVdLyHsrZPlSF2AvrApEvNgBa3WNpWW/9DlTsZPqFziUIJUP01q5di/j4eLRq1QozZ85E/vz5M6vNRNli2paLKiBla2WBtaU3wvrcNsDSFui2ggEpIiLKcr///rvKLjf3oBRlk/tXoFvzocwJjEUJbbDLtiXW96zFgBQRUS5gb22JMgUd1fI4SRC6FxH7aGhgdIoMK7nvgothXtDFAZDlEQ2SUBAP9UMDLYJQziYYJcPc0RzGk+Gg1Pjx47Fo0SJ0794dtra2WL58uRqy99dff2VtC4ky0bpTt/Gr93V1+6/q5+B6ZqF+Q+c5Rk1ZJCKi3OMFk9QpN4q4Byx7C5rYMBxOKocpST2wsHsNFHUxjxEKRESUdTQaDQo42qqlZhqDfWITEnFbsqxS1LPSB6+ccT64II7EJqji6wtlCJ85BKVWr16N+fPn45133lH333vvPTRs2BCJiYnQarVZ2UaiTHHudijGrNLPejStaiAqn/2ffkPLL4GKnXmUiYgoWzuSRE8VFwn88Tbw0Bd+OjcMjvsIn71eBQ1KcpQCERE9m42lFiXc8qglrQtkIVHxKlBV3M0BZhGU8vf3R+PGjZPv16lTB5aWlrhz5w6KFi2aVe0jyhRXg8LRa8ERNeb2vWLheMv3S0CXBFR7D2g0gkeZiIiyVZkyZZ4ZmAoODs629pCJSUwA/u6rCtQ+1DmiV9ynaFGrInrWZ91LIiJ6edIHyedgrRZjy3BQSjKirK1TN1iCUoYZ+IhMle/9SLz722E8iIxDo0IJmBQ5CZq4CKBYY+DVH+Q30thNJCKiXGbixImq+Gdm2bNnD7799lscP34cAQEBWLNmDTp1enrRUm9vb4wYMQI+Pj5wd3fH6NGjMWDAgExrE70gGd656RPg8mY1016/uE/gUaoyJneqzAw7IiLKcTIclJL0rt69e8PGxiZ5XUxMjOq8ODg4pBrmR2QqZOxs998OISg8FlULWmGRzTewuHsbcC0NdF0CWBo/MkxERLmPlEMoUKBApj1fZGQkqlatij59+qBLly7P3N/X1xft27dH//79sXTpUuzfvx+DBg2Cm5tbhh5PWWjvd8DxRUiCBh/FDUa8e23Mfq8mrC0teNiJiCj3BqV69er1xDqpK0VkqgJCo/HuvEO4ExqD8vkt8Ve+WbC8cRqwcwG6/wnY5TN2E4mIKBfKinpS7dq1U0tGzZkzB56enpgxY4a6X758eRw7dgzTp09nUMqYTi0Hdn6lbk6I74mL+ZpiVZ/ayGOT4S47ERGRWcnwX7iFCx/NUkZkBoLCYtSQPZldoIyLFmtdfoL1jb2AlT3QbTngUsLYTSQiolzKFGbfO3jwINq0aZNqXdu2bdWkNvHx8bCysjJa23KtazuhWz8EErKck/AqNtm9jlV96yB/nv9GKRAREeU0vOxCOc6DiFh0n3dY1ZIq5QRsyDcDNn4HAes8QPe/AM96xm4iERHlYklJScZuAgIDA1GwYMFU6+S+1Aq9f/8+Chcu/MRjYmNj1WIQFhaWLW3NFQLPQreyJzRJCVifWB+/aN/D8j614eVq3BmRiIiIshoHp1OOEhIVh/fmH8GVoAiUcEzCPwsSe64AALzoSURBVC4/wOa2BKQcgfdWA14NjN1EIiIikxxGaMjgSm944ZQpU1RxdsPC2ZczSYg/dMvegiYuHIeSymNs0kD82qM2KhXJvEL4REREpopBKcoxwmLi0XPBEVwICEMxhwRscvkOtgFHARsnoOc6wLOusZtIRERkEgoVKqSypVIKCgpSMyu7urqm+ZixY8ciNDQ0efH398+m1uZg0Q+BZW9CEx6AS0ke+CB+BL7pWhsNSuU3dsuIiIiyBYfvUY4QEZuA3guO4MytUBSzj8Vmlx9ge/eMvph5j7WAezVjN5GIiMhk1K9fHxs2bEi1buvWrahVq1a69aRkBuaUszDTS0qIBVa8B9y7iEBdPvSOG4MRr9XGq1XceWiJiCjXYKYUmb3ouET0W3QUJ/xC4GkbhX/zfQvbe2cAe1eg1wYGpIiIKMeLiIjAqVOn1CJ8fX3VbT8/v+Qsp549eybvP2DAANy8eRMjRozAhQsXsGDBAlXkfOTIkUZ7D7mK1BVbOxC4uQ/hOjsVkOrcrA56Nyxu7JYRERHlrqDUrFmzULx4cdja2qJmzZrYu3dvuvvu3r1b1Tl4fLl48WK2tplMR0x8Ij5YcgyHfYPhaROJLfm+hd2D84BDAaD3RqBQZWM3kYiIKMsdO3YM1atXV4uQYJPc/vLLL9X9gICA5ACVkL7Xpk2bVN+qWrVq+OqrrzBz5kx06dKFZys7bB8PnFuFeJ0WH8Z/jMo1GmBU27I89kRElOsYdfjeypUrMXz4cBWYatiwIX799Ve0a9cO58+fh6enZ7qPu3TpEvLmzZt8383NLZtaTKYkLiEJg5edwN4r9+FpHYYtztNh9/AqkKeQPkPKrYyxm0hERJQtmjVrllyoPC2LFi16Yl3Tpk1x4sSJLG4ZPeHwr8CBmerm6PgPYFemBaa8UTndAvNEREQ5mVEzpb7//nv069cP77//PsqXL48ZM2aomVxmz5791McVKFBAFeg0LFqtNtvaTKYhITEJw5afxI6LQfC0fIgtTlNhF3oVyFsE6LOJASkiIiIyPRc2QPfvGHVzWnxX3PR4DT+/WwOWWqMPXiAiIjIKo/0FjIuLw/Hjx9GmTZtU6+X+gQMHnvpYSUcvXLgwWrZsiV27dmVxS8kUh+wNWnYCm30CUUz7AFucp8Iu/AbgVFQ/ZM+1pLGbSERERJSa32HoVr0PDXRYmtASW13exfxetWFnzYurRESUexlt+N79+/eRmJiIggULplov9x+fothAAlFz585VtadiY2OxZMkSFZiSeghNmjRJ8zGynywGYWFhmfxOKDuFxcTj/d+P4YhvMEpY3sfGvN/ALuI24OwF9P4HcE5/2CcRERGRUdy/At3yrtAkxGBbYg3MthuAP/vVRT4Ha54QIiLK1YxaU0o8Pn5e6iGkN6a+bNmyakk5nbG/vz+mT5+eblBqypQpmDhxYia3mowhKCwGvRYexYWAMFS0uYfVDlNhExUAuJQAev0DOBXhiSEiIiLTEhEE3dIu0EQ/xKmkkhinHY7F/eqjiLOdsVtGRESUe4fv5c+fX9WCejwrKigo6InsqaepV68erly5ku52mQI5NDQ0eZEgFpmfG/cj0WXOARWQaulwHetsJ+gDUq6lgd6bGJAiIiIi0xMbDt2yt6AJuYkbSQUxMGk0fu7dGGULORq7ZURERLk7KGVtba2G4W3bti3VernfoEGDDD/PyZMn1bC+9NjY2KiZ+lIuZF7O3Q7Fm3MOwD84Gn2cjmOebhIsYx8C7jX0Rc3zpn/+iYiIiIwiKhhY3BGagFN4oHNEn/gxmNitGWoXc+EJISIiMoXheyNGjECPHj1Qq1YtNRRP6kX5+flhwIAByVlOt2/fxuLFi9V9mZ2vWLFiqFixoiqUvnTpUqxatUotlDMduHYfHyw+jojYeExw3oLeMfqfBZR7FXjjN8Da3thNJCIiInpyyN6STtDc9UGwLg96xn2KDzq3RpuKhXikiIiITCUo1bVrVzx48ACTJk1CQEAAKlWqhE2bNsHLy0ttl3USpDKQQNTIkSNVoMrOzk4FpzZu3Ij27dsb8V1QVtl4JgAfrzyFpMQ4LHBZhhZRW/Qb6g0G2nwFWHC2GiIiIjIxobehkwypB1cQpHNG97jP0KlNS3Srw8lYiIiIHqfRSWXxXERm33NyclL1pTiUzzTJj+Rs72uYtvkSHBGFlflmoUL0CUBjAbSbBtTpb+wmEhFRDsV+Ao/VSwn2hW7x69CE+OGWLr8KSPV+tQX6NCyeOT+gREREOaxPZfTZ94hSiolPxNjVZ7Hm5G0UwT2scZ6BAtG+gJUD8OYCoOwrPGBERERkeu5dgu73jtBEBMA3qSB6JIzDiLda4I0aHsZuGRERkcliUIpMRlB4DD5cchwn/UJQT3sRixx+gm3MQyBPIeDdlYB7NWM3kYiIiOhJAWegW9wJmugHuJTkgb5Jn2PCey3RukLGZ5QmIiLKjRiUIpPgcycU/X8/hjuh0Rhouw2jNUugiUsEClUGuq0AnHiVkYiIiEyQ/1EkLe0Ci9hQnEkqjgH4HNP7NEeDkvmN3TIiIiKTx6AUGd2G03cw+u8zQHwk5uVZhFYJewCpdFb5LeC1HwFrB2M3kYiIiOhJvnuR9MfbsIiPwpGksvhEOxZz+jVHFQ9nHi0iIqIMYFCKjFo/atI/5/HHYT94au5iqeNMeMb7Ahot0PZroO4AQKPhGSIiIiLTc3krklb2gEViDPYkVsaXtmOxsH8TlCrgaOyWERERmQ0Gpcgort2LwOBlJ3AxMBxttEcx03YebOPDAYcCwFuLgGINeWaIiIjINJ1fB93f/WCRFI9tiTXxreMYLO3fGB757I3dMiIiIrPCoBRluzUnb+HzNeeAuEjMsFuGTrodQCIAj9rA24uBvO48K0RERGSaTi2Hbt0gaHRJWJ9YH3Ndx2BZvwZwc7QxdsuIiIjMDoNSlG2i4xLx5bpz+Ov4LVTTXMUch9kolBgAQAM0HAY0HwdYWvOMEBERkWk6Og/Y+In0XLAioRlWu4/Esj714GRnZeyWERERmSUGpShbXL4brobrXQ8KxUeW6/CR5RpYJCYCeT2AznOA4o15JoiIiMh07Z8JbPtC3VyY0BbexUfg9x61YWetNXbLiIiIzBaDUpSldDqdyoySDKkCCQFYYzcHVXSX9BsrdQE6fAfY5eNZICIiItOk0wG7pwLeU9XdnxM64mL5jzC3a3VYW1oYu3VERERmjUEpyjKRsQkYt/acqiH1ltYbk2yXwE4XDdjkBTp8D1R5i0efiIiITDsgtXUccPBndXdafFeE1BqKHztWgtaCMwQTERG9LAalKEuc8g/BiD9PIfheIGZbz0c7iyOADoBXQ/1wPWdPHnkiIiIyXUlJ0G0cAc3xheru+PhesG88CF+3LQuNhgEpIiKizMCgFGWqh5FxmLblIlYc9UdDzVmstJ0DNzwELCyB5p8DDT8CLFh7gYiIiExYYgKS1g6Exdk/kajT4NOE/ijZZgAGNC1p7JYRERHlKAxKUaZIStLhz2P++GbzRVhGBeEbyz/xtqW3fqNraaDLPMC9Go82ERERmbaEWCT93Q8WFzcgXqfFxwmD0LDjB+hWh1neREREmY1BKXpp526HqtpRF/yD0E/7L4bYroc9ovUba/UD2kwGrO15pImIiMi0xUUhccV70F7fgVidJYYlfoTXu/ZHhyqFjd0yIiKiHIlBKXphoVHxmL71EpYevoFXNEfws80f8NDc028sUhN45RugaG0eYSIiIjJ9seFIWPo2LP0PIEpng8FJI9G7Zx80LeNm7JYRERHlWJzHlp6bTqfD38dvocV3u3HisDdWWH2F2dY/6gNSju5A57lAv+0MSBEREWWjWbNmoXjx4rC1tUXNmjWxd+/edPfdvXu3Ktb9+HLx4sXcec6ighG/8HUVkArT2eFDzecY3O99BqSIiIiyGDOl6LlcCAjDl+vO4cYNX4y2/BNv2XjDQqbVs7TVFzGXxdqBR5WIiCgbrVy5EsOHD1eBqYYNG+LXX39Fu3btcP78eXh6pl8L6dKlS8ibN2/yfTe3XJgVFHAaCcvfg1WYH4J1eTDM8kt81q8bKrj/d1yIiIgoazAoRRkSHhOPH7ZdwfKDl9FL8y8W2qxDHs2julGV3gRaTQCci/JoEhERGcH333+Pfv364f3331f3Z8yYgS1btmD27NmYMmVKuo8rUKAAnJ2dkWud+gOJ64fDMikWfklu+Mx2HL764C0Uz88LbERERNmBQSl65lC99afvYPI/51Ejah+2WC6Dp8WjulHuNYBXpgKedXkUiYiIjCQuLg7Hjx/Hp59+mmp9mzZtcODAgac+tnr16oiJiUGFChUwbtw4NG/eHLlCQiwSN42B9sRCaAHsTKyGhQXHYnqPZijkZGvs1hEREeUaDEpRuq7cDceX63wQ6nscP1ktQT3rC/oNjoX1mVGV3wYsWJaMiIjImO7fv4/ExEQULFgw1Xq5HxgYmOZjChcujLlz56raU7GxsViyZAlatmypak01adIkzcfIfrIYhIWFwSyF+CNueQ9Y3z2JJJ0GMxK6IKbBCCx4pTystOzXEBERZScGpegJQeExmLfXF+v2ncRwiz/R1Xo3LDQ66CxtoWkwTF83yiYPjxwREZEJkULlj2c7P77OoGzZsmoxqF+/Pvz9/TF9+vR0g1IyDHDixIkwa9d2Ie7PPrCOfYgQnQM+03yEN7r3RqsKqQN6RERElD0YlKJkp/1DsHC/L/acvYqu2I7tVuvgmFw3qgs0qm5U+sVSiYiIKPvlz58fWq32iayooKCgJ7KnnqZevXpYunRputvHjh2LESNGpMqUKlrUTOpJJiUhce/30Oz6GtZIwrmkYvgx/5cY36MdPPLZG7t1REREuRaDUrlcfGISNp0NwKIDN5DofxzdtTswxfIA7DRx+h3cqz+qG1XP2E0lIiKiNFhbW6theNu2bUPnzp2T18v9jh07ZviYnTx5Ug3rS4+NjY1azE5MKKL//AB21zeruysTmuFa7fH4pUM1WFtyuB4REZExMSiVS92PiMXyw374+9Al1IvajYna7ahi4/vfDgUqADJUr0pX1o0iIiIycZLB1KNHD9SqVUsNxZN6UX5+fhgwYEByltPt27exePHi5Nn5ihUrhooVK6pC6ZIhtWrVKrXkKHd9ELWkG+wjbiJWZ4n/afqh/jsj8FmlQsZuGRERETEolfucux2qsqLOnz6Mt7ENG7R7kddKP0RPp7WGpmJnoFZfoGhdKU5h7OYSERFRBnTt2hUPHjzApEmTEBAQgEqVKmHTpk3w8vJS22WdBKkMJBA1cuRIFaiys7NTwamNGzeiffv2OeZ4J5xaiaT1w2CfFINbuvz43vlzfNzrHRR14XA9IiIiU6HRSRXMXETqHzg5OSE0NBR58+ZFbpCQmISt5+9iyb5LcPPfhu6W21HX4mLydl2+4tBIIKpad8DB1ahtJSIiMqbc2E/IcccqIQ6R/3wKh1Pz1d09iZVxqPo3+Oj1erCx1Bq7dURERLlCWAb7CRy+l4M9jIzD8qN+2HngMFpG/YuftN7Ib62fvlmn0UJTrr3KitIUb8YhekRERGT+wu4gdPG7cLp/Ut2dq3sDHm99hdFVPIzdMiIiIkoDg1I50MXAMCzedxUhpzeiK7ZikPZM8plOzFMY2lp9oKnRA8jrbuymEhEREWWKxGt7ELOiJ5ziHyJMZ48ZeT9Br94D4eXqwCNMRERkohiUyiESk3TYfuEu1u05jlK3VmOI5U64a4P/216iBbR13oe2dFtAy9NOREREOYROh/BdM2C/ZxIckIQLSZ7YXPFbjH6jNWytOFyPiIjIlDE6YeZCo+Lx59Gb8Nm/Hm2jN2GmxXFYWiWpbfE2LrCs2QOaWr2hdSlh7KYSERERZa7YcNxb9j7c/Daruxt0jaHt+CM+rlmSR5qIiMgMMChlhkXLz94OxaFr9+F3+RTy3d6Ft7Ad/S3uAo8uBsYWqQebuu/DqsLrgKWNsZtMRERElOkS715EyKKucIu+gTidFr/Zf4D2fcehuFseHm0iIiIzwaCUGQShzt0Jw5Grgbh76RDs7hxBVd1FvGNxCfk0EYCFfr84yzywqNYNlrX7wqZgBWM3m4iIiCjLhB5dCZtNw+Cqi0GAzgVrS/8P/bq+zeF6REREZoZBKRMNQh2/7IfgS/uR5+5RVEu6gB4WV2GniUsOQol4C1vEFaoJ+5pdYV2pC2DDK4NERESUgyXG4/bfY1Dkwnx197CuIoLbz8HAulWM3TIiIiJ6AQxKmUAQyudOGE5dvIzwS3uR994xVNNdQC/NTVhqkgANkoflxVg5I869DvKUaQwLrwawKlwVVlorY78FIiIioiyXGBaIgHnvwCPspLr/p00X1Oz7PeoWdObRJyIiMlMMShkjCHU7FOfPn0bklb1wuX9cDcfrZRGg30HzaAEQbuuORI+6yFu2KSyKNYCta2nYWqRIlSIiIiLKBR5e3AP82QseScEI19lhrdfneKvHIA7XIyIiMnMMSmVHEOrWQ1w5ewgx1/Yjf/BxVMdFVNWEpApCJUGDkDylAM/6cC7XRGVCOToVyermEREREZkunQ6+G79H0WNfwxKJuKrzgG/LOejRpLGxW0ZERESZgEGpLAhCXfAPgu/pPUjwPYACD0+iCi6hqiZav8OjLKgEWOKBU0WVAeVSvhm0XnXhYpcvs5tDREREZJaSYsJxZX4/lL23Rd3fbdUYRXvPQ+sihYzdNCIiIsopQalZs2bh22+/RUBAACpWrIgZM2agceP0r355e3tjxIgR8PHxgbu7O0aPHo0BAwbAFESEh+DKd21QQXcNlTUJqYJQ0Rp73HepBuviDZG/YjNYetREQSs7o7aXiIiIyBQ9vH0FkQu7oGzCTcTrtNhUeBDa9JkAOxujd12JiIgoExn1L/vKlSsxfPhwFZhq2LAhfv31V7Rr1w7nz5+Hp6fnE/v7+vqiffv26N+/P5YuXYr9+/dj0KBBcHNzQ5cuXWBseRyd4a4Jhg0SEKJ1QbBrTdiWbISClZrBrnBlFLV4VLGciIiIiNKVYOOMxIR4BOmccb7hTHRs05FHi4iIKAfS6HQ6nbFevG7duqhRowZmz56dvK58+fLo1KkTpkyZ8sT+Y8aMwfr163HhwoXkdZIldfr0aRw8eDBDrxkWFgYnJyeEhoYib968yGwPfHbBuaAXtK7FAc2jNCkiIiIyC1ndT8hJsvpYnT19FPaO+VCyRKlMf24iIiIyjX6C0aZyi4uLw/Hjx9GmTZtU6+X+gQMH0nyMBJ4e379t27Y4duwY4uPjYQpcKzaHNn8JBqSIiIiIXkLlqrUZkCIiIsrhjDZ87/79+0hMTETBggVTrZf7gYGBaT5G1qe1f0JCgnq+woULP/GY2NhYtaSM1hERERERERERkXEZLVPKQPPYEDcZTfj4umftn9Z6AxkGKCljhqVo0aKZ0m4iIiIiIiIiIjLDoFT+/Pmh1WqfyIoKCgp6IhvKoFChQmnub2lpCVdX1zQfM3bsWDWG0bD4+/tn4rsgIiIiIiIiIiKzCkpZW1ujZs2a2LZtW6r1cr9BgwZpPqZ+/fpP7L9161bUqlULVlZWaT7GxsZGFdVKuRARERERERERUS4evjdixAjMmzcPCxYsUDPqffzxx/Dz81Mz6hmynHr27Jm8v6y/efOmepzsL4+bP38+Ro4cacR3QUREREREREREZlPoXHTt2hUPHjzApEmTEBAQgEqVKmHTpk3w8vJS22WdBKkMihcvrrZL8OqXX36Bu7s7Zs6ciS5duhjxXRARERERERER0fPS6AyVwnMJqSvl7OysaktxKB8RERGlJLP0yqQoISEhaoIUYp+KiIiIsq5PZdRMKWMIDw9X/3MWPiIiInpaf4FBKfapiIiIKGv7VLkuUyopKQl37tyBo6MjNBoNcjND5JJZY+aB58u88HyZF54v85HV50q6RdJ5khIBFhZGLb1p8tin+g8/Q8wLz5d54fkyLzxf5iPMRPpUuS5TSg6Gh4eHsZthUjgroXnh+TIvPF/mhefLfGTluWKGVMawT/UkfoaYF54v88LzZV54vsxHXiP3qXgJkIiIiIiIiIiIsh2DUkRERERERERElO0YlMrFbGxsMH78ePU/mT6eL/PC82VeeL7MB88VmSL+XJoXni/zwvNlXni+zIeNicQDcl2hcyIiIiIiIiIiMj5mShERERERERERUbZjUIqIiIiIiIiIiLIdg1JERERERERERJTtGJTKhSZMmACNRpNqKVSokLGbRY/s2bMHr732Gtzd3dW5Wbt2bapjI2Xg5BzKdjs7OzRr1gw+Pj48fiZ4rnr37v3E71q9evV4roxkypQpqF27NhwdHVGgQAF06tQJly5dSrUPf7/M51zx94tMAftUpo19KvPBPpV5YZ/KfEwxgz4Vg1K5VMWKFREQEJC8nD171thNokciIyNRtWpV/Pzzz2kek2nTpuH7779X248ePaoCiq1bt0Z4eDiPoYmdK/HKK6+k+l3btGlTtraR/uPt7Y3Bgwfj0KFD2LZtGxISEtCmTRt1Hg34+2U+50rw94tMAftUpot9KvPBPpV5YZ/KfHibQ59KZt+j3GX8+PG6qlWrGrsZlAHyK7pmzZrk+0lJSbpChQrppk6dmrwuJiZG5+TkpJszZw6PqQmdK9GrVy9dx44djdYmerqgoCB13ry9vdV9/n6Zz7kS/P0iU8A+lflgn8p8sE9lftinMh9BJtinYqZULnXlyhU15Kh48eJ45513cP36dWM3iTLA19cXgYGBKrptYGNjg6ZNm+LAgQM8hiZo9+7dKlW2TJky6N+/P4KCgozdJHokNDRU/e/i4qL+5++X+ZwrA/5+kSlgn8o88TPf/PAz33SxT2U+Qk2wT8WgVC5Ut25dLF68GFu2bMFvv/2mghwNGjTAgwcPjN00egY5V6JgwYKp1st9wzYyHe3atcOyZcuwc+dOfPfdd2q4ZYsWLRAbG2vspuV6ciF2xIgRaNSoESpVqqSOB3+/zOdcCf5+kSlgn8p88TPfvPAz33SxT2U+dCbap7LMllchkyI/dAaVK1dG/fr1UbJkSfz+++/qh5RMnxSfe/wD5vF1ZHxdu3ZNvi0f/LVq1YKXlxc2btyIN954w6hty+2GDBmCM2fOYN++fU9s4++XeZwr/n6RKWCfyvzxM9888DPfdLFPZT6GmGifiplSBAcHBxWckvRzMm2GWRIfz4qS9MrHs6fI9BQuXFh9wPN3zbiGDh2K9evXY9euXfDw8Ehez98v8zlXaeHvF5kC9qnMBz/zzRs/800D+1TmY6gJ96kYlCKVlnfhwgX1w0emTWqASSdKZk4wiIuLU7MqyBBMMm0yRNbf35+/a0YiGYVyhWj16tUqPVl+n1Li75f5nKu08PeLTAH7VOaDn/nmjZ/5xsU+lfnQmUGfisP3cqGRI0fitddeg6enp8qwmTx5MsLCwtCrVy9jN40ARERE4OrVq6kKcZ46dUoVo5NzNnz4cPzvf/9D6dKl1SK37e3t8e677/L4mdC5kmXChAno0qWL+kC/ceMGPvvsM+TPnx+dO3fmuTICmQ73jz/+wLp16+Do6Jiccejk5AQ7Ozs1hIO/X+ZxruR3j79fZArYpzJt7FOZD/apzAv7VOZjsDn0qYw27x8ZTdeuXXWFCxfWWVlZ6dzd3XVvvPGGzsfHh2fEROzatUtN0/n4IlN1GqatlymoCxUqpLOxsdE1adJEd/bsWWM3O1d62rmKiorStWnTRufm5qZ+1zw9PdV6Pz8/Yzc710rrXMmycOHC5H34+2Ue54q/X2Qq2KcybexTmQ/2qcwL+1TmA2bQp9I8aigREREREREREVG2YU0pIiIiIiIiIiLKdgxKERERERERERFRtmNQioiIiIiIiIiIsh2DUkRERERERERElO0YlCIiIiIiIiIiomzHoBQREREREREREWU7BqWIiIiIiIiIiCjbMShFRERERERERETZjkEpIsoUu3fvhkajQUhIyEs9T+/evdGpUyezPSvNmjXD8OHDn7lfkyZN8McffyA7vfnmm/j++++z9TWJiIgo49if0mN/iij3YFCKiFKZM2cOHB0dkZCQkLwuIiICVlZWaNy4cap99+7dqwJRly9fRoMGDRAQEAAnJ6csP6K//vorqlatCgcHBzg7O6N69er45ptvzOZM/vPPPwgMDMQ777yTKc+3aNEi1KtX75n7ffnll/j6668RFhaWKa9LREREaWN/KuuxP0WUMzAoRUSpNG/eXAWhjh07lir4VKhQIRw9ehRRUVGprua5u7ujTJkysLa2VvtIkCorzZ8/HyNGjMCwYcNw+vRp7N+/H6NHj1ZtNhczZ85Enz59YGGROR/B69evR8eOHZ+5X5UqVVCsWDEsW7YsU16XiIiI0sb+VNZjf4ooZ2BQiohSKVu2rAo0ScDJQG5L0KNkyZI4cOBAqvXS6Upr+J5k70gW05YtW1C+fHnkyZMHr7zyisqmMkhMTFQBJtnP1dVVBZd0Ot1Tz8iGDRvw9ttvo1+/fihVqhQqVqyIbt264auvvnpiCODEiRNRoEAB5M2bFx9++CHi4uKS95HXmTZtGkqUKAE7OzuVefX333+neq3z58+jffv2qu0FCxZEjx49cP/+/eTtkZGR6Nmzp9peuHBhfPfdd8/8aZLHb9++Ha+//nqq9XLsJAPs1Vdfhb29vTpmBw8exNWrV1UKu2SF1a9fH9euXUv1uJiYGGzdujX5+WbNmoXSpUvD1tZWtVmG7KUk+y1fvvyZ7SQiIqIXx/7Uf9ifIqKnYVCKiJ4gQZBdu3Yl35fbsq5p06bJ6yXAI0ETQ1AqLZJVNX36dCxZsgR79uyBn58fRo4cmbxdgjgLFixQ2U/79u1DcHAw1qxZ89QzItlYhw4dws2bN5+6344dO3DhwgXVXgnCyPNKkMpg3LhxWLhwIWbPng0fHx98/PHHeO+99+Dt7a22S/BM3m+1atVU1tjmzZtx9+5dFRAzGDVqlHp+eW4JDElg7vjx409tl7xPQ9DpcRJYkyDXqVOnUK5cObz77rsqmDZ27NjkzLUhQ4Y88T7lmEhwTvaRDLJJkybh0qVLqs1SuyqlOnXq4MiRI4iNjX1qO4mIiOjlsD/F/hQRZYCOiOgxc+fO1Tk4OOji4+N1YWFhOktLS93du3d1K1as0DVo0EDt4+3tLSlNumvXrqn7u3btUvcfPnyo7i9cuFDdv3r1avLz/vLLL7qCBQsm3y9cuLBu6tSpyffl9Tw8PHQdO3ZM95zcuXNHV69ePfXcZcqU0fXq1Uu3cuVKXWJiYvI+ss7FxUUXGRmZvG727Nm6PHnyqP0iIiJ0tra2ugMHDqR67n79+um6deumbn/xxRe6Nm3apNru7++vXvfSpUu68PBwnbW1tTomBg8ePNDZ2dnpPvroo3Tb/8MPP+hKlCjxxHp53nHjxiXfP3jwoFo3f/785HXLly9X7U6pf//+uhEjRqjbq1at0uXNm1eds/ScPn1aPe+NGzfS3YeIiIheHvtT7E8R0bNZZiRwRUS5i2Q/ydA0qSH18OFDVTNKhsFJ5pAMYZNtkhXk6emphr+lRzKCZMifgQxxCwoKUrdDQ0NVNpIMSTOwtLRErVq1njqET55DMrTOnTunsppkOGGvXr0wb948lRlkqNMkw/Hk9Q3kdaTulL+/v2qDDHtr3bp1queW7C8pmi4k40myoGRo3uNkCF10dLTaP2X7XVxcVLr+08jjZGhdejWfDGTonahcuXKqddJuKVQuQxLlOMlwxhUrVqjt8n68vLzUOZGhkrJ07tw51XGQoYoiZW0wIiIiynzsT7E/RUTPxqAUET1BajV5eHiooIwEpSQYJWSYWPHixVVxcdnWokWLpx49mbHv8bpJz6oZlVGVKlVSy+DBg9WQOJkZUIJUTxtOaGhDUlKSur1x40YUKVIk1XYbGxv1v+zz2muvpTmrnwTGrly58kLtzp8/vzqmzzpehoLxaa0ztF+G4UlgrFGjRuq+zJp44sQJFTCU4YQy296ECRNUcFHqdgkZIinc3NxeqP1ERESUMexPsT9FRM/GmlJElCYJ7khwQxapiWAgASopXi51nZ4VAHoaJycnFdyR5zFISEh4Zk2mtFSoUEH9LxlcBjIzn2QlGcjrSNaTBNtkfwk+SY0r6TCmXIoWLar2r1Gjhqo1JbPVPb6PFB2X/yVglLL9Emy6fPnyU9sqmViBgYHpBqaex7p169ChQwdotdpU2WatWrVSRdzPnDmDGzduYOfOncnbJcNMjoEEx4iIiChrsT/F/hQRPR0zpYgo3U6UZCHFx8cnZ0oJuT1w4EA1jOxlglLio48+wtSpU9VscVL4+/vvv0+evS898toyO6BkaUlwRYYATp48WWX+pBxKJxlEMkOfFDSXoujjx49XRcJleJ9kFEnBdSluLllHkmkkQ+JkKKAErmQ4oLz33377Tc3sJwXNJYgjM+HJUDlZL/vJ88s2mTlQhtZ9/vnnycMHnxaUkrZKtpnMtPcy1q9fn6p4+z///IPr16+r4ub58uXDpk2b1PtLOaRw7969aNOmzUu9LhEREWUM+1PsTxHR0zEoRUTpdqIk00hmgTPUNzIEpcLDw1WtKENW0Yv65JNPVFCpd+/eKpjTt29fVQNJ6k2lR7KAZMY+mTXvwYMHKlgkwSiZhU6CQwYtW7ZUwS4J0MhMc++8844aypZypjupkzVlyhQVyJHhbZId9dlnn6ntEviSwNGYMWPQtm1b9RxSr0nqNBkCT99++62qU/X666+rQJe8n6e1XUhWk7zPZcuWvVRQSupaSZBM2mYg72H16tXqfUrQUN6/zDwoM/MJWSczBUqmGxEREWU99qfYnyKip9NItfNn7ENEZFYkyCUZV2vXroUpunv3rgoUyVBFCXS9CMkq2759u8qGyqhffvlFDfmTelNERERET8P+FPtTRNmBNaWIiLKZZJ7Nnz9f1bR6UTJ0cezYsc/1GKmB9dNPP73waxIRERGZCvaniHIGZkoRUY5j6lf2iIiIiEwd+1NElB0YlCIiIiIiIiIiomzH4XtERERERERERJTtGJQiIiIiIiIiIqJsx6AUERERERERERFlOwaliIiIiIiIiIgo2zEoRURERERERERE2Y5BKSIiIiIiIiIiynYMShERERERERERUbZjUIqIiIiIiIiIiLIdg1JERERERERERJTtGJQiIiIiIiIiIqJsx6AUERERERERERFlOwaliIiIiIiIiIgo2zEoRURERERERERE2Y5BKSIiIiIiIiIiynYMShHlABqNJkPL7t27X+p1Fi1apJ7n2LFjz9y3d+/eKFasGIxBXjfl+86TJw/q1q2LxYsXJ+9z48YNtU3ek8GBAwcwYcIEhISEvNDrNmvWDJUqVXrp9sfHx6NQoUKqfX///Teyi7x3eU0iIiJzwT7Qk32gV199NVOPcVb36Z7W/5K+lSzZzdBPTGupVatWpr/erFmzUvVJiXITS2M3gIhe3sGDB1Pd/+qrr7Br1y7s3Lkz1foKFSpk2+H+4osv8NFHH8FYGjZsiOnTp6vbt27dUrd79eqFyMhIDBw4EIULF1bHrWTJkqk6RRMnTlSdL2dnZ6O1/Z9//sHdu3fV7fnz5+PNN980WluIiIhMGftA5u9p/S8J1hjT0KFD8e6776ZaJxc7M5u8z/z586tjQJTbMChFlAPUq1cv1X03NzdYWFg8sf5lMneeN4MmZbDHGKRTk/L9t2rVCl5eXvj+++9VUMrGxibTjk9mk0CUtbU1mjZtiq1bt6qgmoeHh7GbRUREZHLYB8rZsvOCalo8PT1Ntr/4LImJiUhISFB9XiJTxuF7RLmEpF2ndfXl8bRoGeInAaglS5bgk08+QZEiRdQfs6tXrybv8/DhQ/Tp0wcuLi5wcHDAa6+9huvXrz8z1Vued8iQIeq5y5cvD3t7e1StWlVlBj3uypUr6spUgQIF1OvL/r/88stLBanKli2Lmzdvpjl8T9LGR40apW4XL148zSGPf/zxB+rXr6+ukMlSrVo1FUB63NGjR9G4cWP1/kqUKIGpU6ciKSkpQ+28c+cONm/erI6ptEcel1Y6txxfaYOcl/bt26vbRYsWVecsNjY21b4S1JJsK0dHR3Ucunfvrtr4+PDF9KxcuVK9bznX8jpt27bFyZMnM/R+iIiIjC0394EM/R3JGJcLc9LHkb/l8nf90KFDT+wv/QLpLxleN2Xpg8eP0+NlIdIqjSAOHz6sjpOrqytsbW3Vhcvhw4dnqP+V1vC94OBgDBo0SJ0fuYgnfa3PP//8if7P8xzz5xUTE6N+RqQv6OTkpH4e5JiuW7fuiX2lL/fTTz+pfe3s7JIvnK5fv15tl58VHx8feHt7J7//lD8/fn5+eO+991L9PHz33Xep+paGYz9t2jRMnjxZHUvZV0ZOEJk6ZkoRUZrGjh2r/rjOmTNHZV3JH0KDfv36oXXr1ipI4+/vj3HjxqkOw5kzZ5457G3jxo0qIDJp0iTVKZI/np07d8alS5dUp0KcP38eDRo0UFen5I+u1FfasmULhg0bhvv372P8+PEvlO0lASnJIkvL+++/rzo50mlYvXq1Gt6X8grdl19+qYZFvvHGG6oTIh2Qc+fOJQe5DAIDA1XQR/aRdq5Zs0YdS3d3d/Ts2fOZ7ZSOnFzZ6tu3b3J214IFC1Rn6/FsNXlPr7/+ujof8np79uxRbZS2SXuFDFds3ry5em/ffPMNSv2/vfsAa+pq4wD+T9ggoKgsAUXFrbj33rZu2zpaR2uHba2rdtjx2aHV2mprW2ddrXW3zqp17733RgUVRUFA9sr3vCcGAVFRkCTw/z1PHpN7b5KTcwVO3vue95QurYJe3bt3z1K/fffdd+r8ygBc/k1ISMAPP/yggm779+83+hVMIiKinJbXxkBCglrlypXDzz//nFpmQS5qXb58WY0bDGMQ+XvfqVMn9d4REREqaCTBHumHZyFtl4CUBFIkKCafSwIokgmelfFXZsEgGddcunRJTfmrUqUKduzYgTFjxuDo0aOqj5+2zx9HAj+SbZSWhYWF6hNp9/Dhw1VwTMZHGzduVOPE2bNnpxvzSZDyr7/+Uv93pB0SSDt8+LDqByFjRbl4KOfBMF3RkN10+/Zt9f9BXl/GeBKskqCavK/0Qcbpjb/88gvKlCmjgpBOTk7w8/PL0nkiMiodEeU5ffv21Tk4OKTbVrx4cbU9oyZNmqibwZYtW3Tyq6Fx48YPHTt79my1r0uXLum279q1S20fNWpUujbIe6Ylx7i5uekiIyNTt928eVOn1Wp1Y8aMSd3Wpk0bnZeXly4iIiLd8wcOHKiztbXVhYWFPfbzy/u+8MILusTERHW7fPmyao+8/0cffaSOkW3yWD6TwQ8//KC2yb60AgICdBYWFrpXX331se8r/SjP37dvX7rtFSpUUJ/pSVJSUnSlS5fWFStWTJeUlKS2jRw5Ur3mpk2b0h1r+DyLFy9Ot10+d9myZVMfT5o0SR23du3adMe98847D31+w3sZBAYG6iwtLXUffPBBuufeu3dP5+7urnvllVee+JmIiIhyE8dAxXUvvvhian8YxjuVK1dOHVuI/fv3q+0LFixQj5OTk3Wenp666tWrq/GIwZUrV3RWVlbpxnSGsaL8m1ZmY6tSpUqpW2xs7CPP2aPGX5mNU6dOnZrp+Of7779X29evX//U487MGD5LZrcNGzY8dLz0rYw5+/fvr6tWrVrq9u3bt6vnfP755499v4oVK6b7nAaffvpppmPLd999V6fRaHTnzp1L117p64SEhMe+F5Gp4fQ9IspUt27dHtkzkgmUllzBkYyerKQIy9UtmUZm4Obmpq5AGjKO5ArYpk2b1FUsSbOWq1OGm1zRk/2ZpZtntGbNGlhZWambpDAvXrxYFauUlOantWHDBpW99P777z/xWLmiWbt27XTb5CpexoyqzEjatkwRkILschVOyBVLyZCSbKmMZLtcfXzce8lrSn+3bds23XE9e/bM0tVN6Xe52pf2PEjqvdS7yu5qjkRERKbI3MdAmXnxxRdTxxaG8YIwvLdkDkkJAZk2mDYzWz6bfMZncf78eZXNIxlCMnbICbKIj0ybzLgIjGF6pvTf0/T5k8iiPZJplfYmKzqLJUuWqIV1JAPL0tJSjTmlrMOZM2dSn7927Vr1b1bGkI/6vJI1lnFsKZ9X4m4ZFzWSDHppB5E54fQ9IsqUIX36UYGXzLaFhoY+sTelnkBGkqIcGxur7stryOBL0rjllhlJX3+Shg0b4qefflIDKxnYSf0CSZd+FpI6LbJSbPxJn+9xDPWpZDBqWBZZUrnls/zzzz/47bff0k0NkM+VcZAn7yWDVgPpTxmAZZTZtowMKwDWqlUr0/3PmspPRERkysx9DJSV9zZMD0v73o/7fIapZs9r/JRV0k5pT8aSBhJoksBQxvOQnXGZoe01a9Z8aLtMNXzllVfw8ssvq5pY0iZ5/ylTpqS7kCh9IMHAzPo1K+TzZKxPJqQshGF/Vv/vEpkqBqWI8gkJXmQsAGkY3MgStBk9brU9qZuU2TapV5RdhQoVUn+8e/fu/cirSpL59CQSzMlsEPEsDHWopGC4FBN/HqRugwSeHhcEkvoVUtjzachgTGo/ZeUcZmT4f/H333+rK6VERETmKL+NgZ6FIXjzqM+XluGCWMY+zRgwSzt+ysl2SuF0yRJKe55CQkJUQC+z8/k8SI0oOReyGEzadmTsE+kDybaXPnyWgJF83uDg4Ie2S1abyPh5n3a1bCJTwMvcRPmEXGWRIpwZ06olXftpzZs3L93j3bt3qzTojKujPAvJ/pFUa1ndTVLLJbCU8ZbZVa+ckPGqoUHr1q3VIFGufj0vEnCS95UiljIFIONNBh2ZTeF7Eplmd+/evdT0cYOFCxc+8bmyyp5c9ZPU+8zOQ04F/YiIiJ4njoGeTFbck6DJggULVMDHQMZ3Ms7L2J8i47jSsJqcgRTclkx1Gb9kFhR80vgrMy1atEBUVBSWL1+ebrthlUDZnxsk+CMZ+GmDQBJ4yrj6Xrt27dS/TxpDPip7Sz6PFL+XwugZP6+8t4yZicwdM6WI8gm56ibLyUqmjdRKkEGGrEDyqNXoHufgwYNqtRRJWZaVZ2RlOFl55GmzeB5l4sSJasqarPD27rvvqsGPBFak3tKqVasemj+fUypXrpz6/lLXSebkyyBN3v+zzz5TASMZMEg9JsnEkkGCXBWU1V+yS6buyRVSWU0ls7oLUtdJVq05duyYWs44q+RzyDRGOfdST0uu5EqASupFPWkKnnxuWSVGzq8sdy11qaSNMq1Psq+kpkNOfHYiIqLniWOgJ5PxgIxzZHwnZQTeeustVUpAVt/LOPVMHssKwbLinYwLJJtaajnJlLbMVv2T+pd169bF0KFD1ep7gYGBahxiuMj5qPFX2lpQacdD8ppynEwplOfu3LlTrRYsdbekXbmhffv26vPK2FfqW8l4WPpPAnsXLlxIPU7GsvL/T8ZgMn6S50kASi6+yoVYqXdq6AO5YCiZV7IqoIwFZZv0mQSgpCaYjMmkr2VFQVl1T8bIEvgjMncMShHlE1K4UlJ9ZXljWaq2UqVK6qrNswQVJIAyd+5c9OjRQ135kqs0MpBwcXHJkbZKQUe5IiR/3GWpZUnJllpKsqytDDieF8n0kmWg//jjD/z+++9qGWDJUpLtMhCQ95caD1LkVDKI5LEs0ZxdcqXx0KFDGDJkyCMLgb799tsqKCV9L8v9ZpUEjiSIJ6/98ccfq6tqkvklgxnpyyctXy39IedDzq9cPZXzLYNRmWI4YMCAp/6sREREuY1joKyRguTi+++/R9euXVMvysmiKRkXN5FxoARUPvnkEzU9TQJPMk7ImEUtWdfbt29X4ygZM0ndS6nTJAW5szL+ykjGSbJPLpj98MMPqmaTXBiVi3ojR45EbpGFaGR8KuNqyQSTQNKnn36qpipmHFvPmTMH1atXV2M4uW9nZ6fGVtK3BvIcmaYnwUC5ECvBJwm6ycVjyVST/pFbZGSkei+5sDxs2LBc+7xEz5NGluB7ru9AREQmR64oSsBPrlbmZAFSIiIiIiKirGKmFBFRHier9oly5cohMTFRZU5JtpVM6WNAioiIiIiIjIVBKSKiPE5qFkhdKUkDl+l3Us9B0u0lU4qIiIiIiMhYOH2PiIiIiIiIiIhy3aOXXSIiIiIiIiIiInpOGJQiIiIiIiIiIqJcx6AUERERERERERHlunxX6DwlJQU3btyAo6MjNBqNsZtDREREJkSn0+HevXvw9PSEVstrd4/DMRURERFld0xlUkGpMWPGYOnSpTh79izs7OxQv359fP/99yhbtmzqMf369cMff/yR7nl16tTB3r17s/QeEpDy9vbO8bYTERFR3hEUFAQvLy9jN8OkcUxFRERE2R1TmVRQatu2bXj//fdRq1YtJCUl4fPPP0fr1q1x+vRpODg4pB7Xtm1bzJ49O/WxtbV1lt9DMqQMHePk5JTDn4CIiIjMWWRkpLp4ZRgv0KNxTEVERETZHVOZVFDqv//+S/dYAk+urq44dOgQGjdunLrdxsYG7u7uz/Qehil7EpBiUIqIiIgeN14gjqmIiIjo+Y2pTLpYQkREhPrXxcUl3fatW7eqYFWZMmXw1ltvISQk5JGvER8fryJ0aW9ERERERERERGRcWlMuijVs2DA0bNgQlSpVSt3erl07zJs3D5s3b8b48eNx4MABNG/eXAWfHlWnytnZOfXGelJERERERERERMan0Un0xwRJbanVq1dj586djy2KFRwcjOLFi2PhwoXo2rXrQ/slWJU2YGWY1yhZWJy+R0RERGnJOEEuYnGc8GTsKyIiIsruOMGkakoZfPDBB1i5ciW2b9/+xJVvPDw8VFDqwoULme6X+lNye1rJyclITEx86ueRabOysoKFhYWxm0FERERERJRv8Pt13mOVQ9+tTSooJUlbEpBatmyZqhvl6+v7xOeEhoaqlfQkOJVTbbh58ybCw8Nz5PXI9BQsWFAVymcRWyIiIiIioueH36/ztoI58N3a0tSm7M2fPx8rVqxQywZKcEhIypednR2ioqLw1VdfoVu3bioIdeXKFXz22WcoUqQIunTpkiNtMASkpJC6vb09Axd57BdiTExMamH8nApkEhFRLkpJBi5vB4rXByyfPhOa6JEirgNJceygvMipGGBla+xWEOVL/H6dN+ly8Lu1SQWlpkyZov5t2rRpuu2zZ89Gv379VGrYiRMn8Oeff6rAkXzwZs2aYdGiRSqIlRMphYaAVOHChbP9emR6JLgp5IdHzjOn8hERmQEpfxl8FDi+BDj5DxB1E+g+Dyjf3tgto7wgIQZYOVD/f4vypsKlgXd3M5BNlMv4/Tpvs8uh79YmFZR6Us11+dDr1q17bu9vqCElGVKUdxnOr5xvBqWIiExYWIA+EHViCRCapnakbUEg5o4xW0Z5RXgQsLAXcPM4oNEC1tm/yEkmJjEaCL0IHJkL1HrT2K0hylf4/Trvs8+B79YmFZQyFaw1lLfx/BIRmbCo28CppcDxxcD1gw+2W9oCZdsBlV8BSrcELK2N2UrKC67uARb3BqJvA/ZFgO5z9dNCKW/ZNx1Y+xGw4yegWm9mSxEZAb9/5V2abNSSMmBQioiIiIwrPgo4uxo4sRi4tAXQJeu3S+aKbxOgyitAufaA7aOXEyZ6KofmAKuHAymJgHtloMd8oKAPOzEvqt4H2DkBiLwGHPkLqNXf2C0iIqI0tGkfED2OFJmvWrVqtjpJitNLNPXo0aPPrbPnzJmjVgEgIiITlpwInPsP+Ls/8KMfsOxt4OJGfUDKszrQdiww7CzQZzlQtRcDUpRz/+/WfASsGqwPSFXoDLyxjgGpvEwKnDccqr+/YwKQlGDsFhER8bt1GgxK5TFBQUHo378/PD09YW1tjeLFi2Pw4MEIDQ19qteRwNHy5cvTbRs+fDg2bdqUrfZ5e3sjODgYlSpVytbrEBGRGZLakYF7gX+HAT+WARZ0B07+DSTGAC4lgSafAgMPAW9vAeq+Czi6ZXi6DkeDwvH1qlO4ExVvtI9BZiomDJjbBdg/Xf+42RfAy3MAawdjt4yet+p9gQLu+mypo3+xv4koS/jdOndw+l4eEhAQgHr16qFMmTJYsGABfH19cerUKXz00UdYu3Yt9u7dCxcXl2d+/QIFCqhbdkjxM3d392y9BhERmZmQs/qpeVKwPDzwwXaHokClbvo6UcWqyxWRTJ9+MeQeVhy9gZXHbuBqaIza5lvEAX3qlcitT0Dm7tYpYEFPIPwqYF0A6DodKPeisVtFuZ0t9d8n+mypqq+xLh0RPRa/W+ceZkrlIe+//77Kjlq/fj2aNGkCHx8ftGvXDhs3bsT169fx+eefq+NKlCiBb7/9Fr169VJBJsmq+vXXX1NfR/aLLl26qIwpw+OM0/f69euHzp0747vvvoObm5uaMvf1118jKSlJBcIkAObl5YVZs2Y9cvqevIY8znjbunWr2p+QkICPP/4YxYoVg4ODA+rUqZO6L+10PfmsUvlf2vy0WWFERPQcRN4Adv0CTG0ITK4D7BivD0hJQKBKD+C1f/TT89p9D3jVeCggdT08FlO3XUK7iTvQcsJ2/Lr5ogpI2VlZoFNVT1TwYH0pyqIzq4AZrfQBqUIlgP4bGJDKj2rcz5aKCAKOzjN2a4jIxPG7tX2ufbdmptQTyFSB2MT7BVdzmQy8s1rNPiwsDOvWrcPo0aNhZ2eXbp9kJr366qtYtGgRJk+erLb98MMP+Oyzz1SgSZ43dOhQlCtXDq1atcKBAwfg6uqK2bNno23bto9d2nHz5s0q8LR9+3bs2rVLTR3cs2cPGjdujH379qn3HDBggHpdmbqX0cSJEzF27NjUx3JfsrykLeL1119XgayFCxeq4NmyZctUm06cOAE/Pz/1Hm+88YYKjHXt2hX//fcfRo4cmeU+JiKiHBQbDpxeoc+IurJT/orqt2stgdKtgCovA2XaAdb65YMzCotOwOoTwVh59DoOXLmbut1Sq0HTskXRwd8TrSq4wd6awxfKgpQUYPsPwNbv9I99GwMv/wHYP3vWOJkxKzug4RDgv0/vZ0u9ymwpolzG79b8bp0ZjuqeQAJSFf63DsZw+ps2WR54X7hwQf2Qly9fPtP9sv3u3bu4ffu2etygQQN8+umn6r5M95OA0k8//aSCR0WLFlXbJfPpSVPtJBvql19+gVarRdmyZTFu3DjExMSogJcYMWKECjTJ6/fo0eOh5zs7O6ubWLp0KaZOnaoyu+R9L126pAJU165dUwEpQ10rCTxJwEwCURLUatOmTbrPsnv3bnUMERHlgsQ44MI64Phi4MJ6IDlNEWGfekDll4GKXR4ZCIiKT8KG0zfV9LydF+4gKUUfyJJrMnV8XdDRvxjaVXJHIQdrnk56uhUdl78LnFmpf1xnANB6NGDBoW++VqMfsPMnICIQODZf/5iIcg2/W/O7dWb4lzmfkICVMGReSe2ptOTxzz///NSvW7FiRRWQMpBpfGmLmEuWVeHChRESEvLY1zly5Aj69OmDSZMmoWHDhmrb4cOHVbsl0JRWfHy8ek1x5swZlVaY8bMwKEVE9BylJOszoaRO1OlVQHzEg31Fy+szoiq9BBQqnunT45OSse3cbaw4dgObztxCXGJK6r7KxZzR0d8T7f094OGcPvOXKEvuXgUW9gJunQS0VkD7n4Dqvdl5pM+WajAEWDcC2D4e8O/FbCkiemr8bp2zGJTKwhQ6yVgy1ntnVenSpVXA6fTp06rOU0Znz55FoUKFUKRIkUe+RlanCqZlZWX10Gtkti1FUugf4ebNm+jYsaOa+ic3A3mOBLUOHTr00BRCQ8F1wy8EIiJ6zuT3bfAx/dS8k/8A94If7HMqBlR+SV+w3K1ipgXLk1N02BcQqjKi1p4MRmRcUuo+KVougaiOVT1Rqmj2FtSgfE6CpYv7ADGhgIMr0P0vwKfOE58WGBqDpUeuIT7p0eMVMl+Sddm0rKv+Qc3XgV0/38+WWqCvNUVEuYLfrR/PKp9+t2ZQ6gnkpJtD7QrJHJKpd1IzSupDpa0rJf8x582bpzKRDIEnWYkvLXlsqOMk5D9/cvLzr6UVFxeHTp06qfeeMGFCun3VqlVTbZAsq0aNGmX6/AoVKmT6WYiIKIeEXQZO/K3Pirpz/sF2W2egQmegyiuAT30gTdasgQxujl+LUIGof4/fQMi9+NR9bk426FDFE52qFkOlYk7PdGGEKJ0DM4G1HwMpSYBHVaDHPMDZ67GdJP9H5+0LxHdrziAmwTg1ROn5+317ALZ+1BRehezTZ0vt+BGo2guwSP+lj4ieD363fr7izPS7telHWyjLfvvtN9SvX1/VWBo1ahR8fX1x6tQptRKerF4nRdANpMaT1H+SrKoNGzZgyZIlWL16dep+WXFv06ZNqvaUjY2NyrJ6Ht555x0EBQWp9zLUuzLUqpJpe1KgXYJp48ePVz9Id+7cUcXVK1eujBdeeAGDBg1Sn9nwWWTlQU7dIyLKpug7wKll+jpR1/Y/2G5hA5Rtq8+I8msFWNpk+vSLIVGqWPnKYzdwJTQmdbuznRVeqOyu6kTV9nWBhZaBKMoBSQnAf58AB++v9lupG9Dxt0cW1De4ER6LT/45jh0X7qjHNYsXQhWvgjwlecyui3dw7tY9tZrnqM6VH2RLSW2p8PvZUtX7GLuZRGRi+N26c659t2ZQKg+R1egOHjyoVtTr3r27Wr5RCoZLsEZWpJNAj8GHH36oUve+/vprODo6qqCPBLMM5PGwYcPw+++/q4CWrID3PGzbtg3BwcEqKpvWli1b0LRpU1XQXAJs0t7r16+rjDCpGSUBKVG3bl3MmDFDfT753C1btsQXX3yBb7/99rm0l4goz0qIBs6u0WdEXdwE6O5njWi0+lXLpGB5+Q76DKlHfMFfdeyGCkSduhGZLlW/ZQU3dPL3ROMyRWFt+XBGFVG2AqgyXe/qLvnPCrT4H9BwaKZTSNNmR/1z+Dq+XnkK9+KTYGOpxSdty6Ff/RLQMlCa5+wNCEWP6Xux+MA1DGzmB3dn2wcr8a37TL9Co39PZksRUTr8bv1Vrn231ujyWVGeyMhItdpbREQEnJycHkp3u3z5ssowsrW1RV4lWVBDhgxRt/wov5xnIqInSk4ELm3RB6LOrgYSH2Q1qelPMjVPsk4cM18tJiw6AWtOBKtA1P7LYanbLbUaFYDqVNUTLcu7wcHGMk+ME8jE+urmCWBBL31tIGtHoNsMfSbfY9y+F4/Plp3AhtO31OOq3gUx/hV/1jLLw+SrzivT9uDAlbt4vUEJjOxQUb8jIQaY6A9Eh+gz61gMnyjH5YfvXfxuHffIc5zVcYL5jBKJiIgo++Ra1LUD+ql5MkUvRj91SSlUQj81T7KiiqZf+dQgOj5JfaGXQNT287eRlPLg2pZMyZNAVLtKHnBxsObZoufn1HJg+bv6QKpLSaDnQqBo2cc+ZfXxYHyx/ATuxiTCykKDIS3L4J3GJWFpwey9vF7D5oPmfugzaz8W7A/Ee01Lo6ijjX56Z4PBwPrP72dL9WC2FBGRETAoRURElB+EB+lrpxydD9y9/GC7fRGgUld9MMqrZqbTnhKSUrDt/G0ViNpw+ibiEh+s+lLR00kFotpX8YRnwQeLbBA9F7Li0NYxwPZx+selmgMvzQLsHl37MjwmAV+uOKWml4ryHk6Y8Iq/+pfyh0Z+ReDvXRDHgsIxY2cARrQrr99R8w39SnzhV4Hji4Bqrxm7qURE+Q6DUvnQ86oPRUREJiYxVj8t78hcIGCbpEnpt1s5AOXb6wNRJZsCFg8PB5JTdNh3OVR9kV9z4iYiYhNT95UobI+OVYuho78nSrvqlxEmeu7i7wHLBgBn/9U/rjcQaPl1pv9/DTafvYVP/jmhpu1JYf33mpZSWTOsbZb/sqUGNS+N/n8cxNw9VzGgcSkUkmzO1GypL/TZUlW6M1uKiJ4Kv1tnH4NSREREeW163vXDwNG/gBP/APERD/aVaKTPBJCC5dYOmTxVh5PXI7Hi6HWsOn4DtyLjU/e5Otqgg7+nCkRV8XJWX/KIck3YZWBhLyDkNGBhDXT4Baja85GH34tLxLf/nsbig9fU41JFHTD+laqqhhTlT83LuarMTlmIYdauy/iwddkH2VI7fwbuXtFPa672qrGbSkSUrzAoRURElBdEheinnxyZB9w+82C7szdQtZd+dSkX30yfeul2FFYe1a+cd/lOdOp2J1tLvFDZQwWi6pQsrDJNiHKdZPkt6QvE3gUKuAM95umnmj7C7ot38NHfx3E9PFbNRu3fwBfD25SFrZVFrjabTLG2VGkM+Osw5uy6gjcblYSznZU+QC/ZUhu+TJMtxa9IRES5hb9xiYiIzHn1vAvrgSN/6f9NSdJvt7TVZ0NJVlSJxoD24ULOwRGx+PdYMFYcu66yowxsrbRqxTwJRDUpWxQ2lvwiT0bM+tv/O/Dfp4AuGfCsDvSYDzh5ZHp4TEISvl97Fn/suaoee7vY4ceX/FVAlUi0ruCOMm4FcP5WFP7YfQWDWvjpO6ZWf2DXRH29PVmNVAL5RESUKxiUIiIiMje3TgNH5+kzo6JvP9herKZ+6knFroDdw9OUpC7UmhPBWH7kOvZfCVPf+YVkQDX2K4KOVT3RqoI7CthweEBGlpQArPkQOPyn/nGVHkCHiYBV5kuKH7oahg8XH8OV0Bj1+NU6PvjshfJw4P9lSkOr1eD9ZqUxeOFRNYXvjYa++t93KltqELDhf8C2cfp6e8yWIiLKFRx1EhERmYPYcODk3/rpeTcOP9ju4Ar4dweqvga4lsu0YPmui3fw96FrWHfqJuKTHqycV7uECzpU9cQLldxRuIBNbn0SoieT1dCkJppGC7T6Rl/UPJM6ZvFJyfhpwwVM334JKTrA3ckW379UBU3KFGUvU6ZkpdCJGy8g4E40/tp7FQOalNLvqPUms6WIiIyAQSkiIiJTlZIMXN6mD0SdWQUk3y88rrUEyrQFqr4K+LXKdLUoqRP1z6FrWHr4Om5GxqVul6krXap5qayoYgXtcvPTEGVdET+g2++AhQ3g1zLTQ05ej8CwxUfVVCzRtXoxjOxQUV8niOgR1CqMzUpj+JJjmLEjAH3rlYCdtYU+W6r+IGDjSH1tKWZLERHlCgalKMeUKFECQ4YMUTdDQclly5ahc+fO7GUioqcRFgAcnQ8cXQBE6lcPU1wr6OtEyZelAg9ngkTGJao6UX8fCsLhwPDU7fIlvVNVT7xUwwuVi3HlPDIT5V7MdHNicgombbmI3zZfRFKKDkUKWGN0l8poU9E915tI5kl+H07cdB5BYbGYvz8Q/Rv6PsiW2v2L/nfwiSWPXeGRiOh5K5FPvl8zKJVH9OvXD3/88UfqYxcXF9SqVQvjxo1DlSpVjNKm4OBgFCpUyCjvTURkdhKigdMr9FlRV3c+2G7rDFR+WZ8V5VntoSlMMj1v9yX99Lz/Tj6YnicL5TUt66oCUS3Ku7JgOeUJ52/dU7WjTlyPUI/bVXLHqM6VOP2UnoqVhRbvNS2NEUtPYNq2S6oGmVqd0aYAUP8DYONX97OlXmZtKaJ8it+vcw+DUnlI27ZtMXv2bHX/5s2b+OKLL9C+fXsEBgYapT3u7rxiSUT0WFJpPGgfcGQucGo5kKCfhgRogFLN9IGocu0zLe4cINPzDuun5wVHPJie5+daAC/X9ELnqsXg6pR5UWgicyPBV5lqNX79eSQkp6jsv286VVSrRMqVY6Kn1a26F37ZdEH9/lxyMAi965XQ76j1FrBLsqUu6ev4+fdg5xLlU/x+nTseXiOazJaNjY0KBMmtatWq+OSTTxAUFITbt/UrM8njMmXKwN7eHiVLlsSXX36JxMTE1OcfO3YMzZo1g6OjI5ycnFCjRg0cPHgwdf/u3bvRuHFj2NnZwdvbG4MGDUJ0dPQj2yODxOXLl6v7V65cUY+XLl2q3kPa4O/vjz179qR7ztO+BxGRWYq8AewYD/xWE5jVBjjylz4gVcgXaP4FMPQk0HsZUPmldAEpmZ63YH8guk3Zjebjt2HSlkvqC5V8Qe9TrzhWDmyA9UMb4+3GpRiQojzjyp1odJ+2B2PWnlUBqWZli6r/552qFmNAip6ZtaU2tcj5lK2XkGBYBMKQLSUkWyo5ib1MlE/x+3U+DEqNGTNGTTmToIirq6uaK3nu3Ll0x+h0Onz11Vfw9PRUgYumTZvi1KlTz/cqtkypMMbNsFb3M4iKisK8efNQunRpFC5cWG2Tfp0zZw5Onz6NiRMn4vfff8dPP/2U+pxXX30VXl5eOHDgAA4dOoRPP/0UVlb6YqEnTpxAmzZt0LVrVxw/fhyLFi3Czp07MXDgwKdq1+eff47hw4fj6NGjKkDWs2dPJCUl5eh7EBGZpKR44NQy4K+XgJ8qApu+AUIvAlYO+oyofmuAQUeAxh8Bzl7pMkR2XLiNwQuPoNaojWq6yaGrd9X0vOblXDH51erY/3kLfNOpEqp4FeSXdMozUlJ0+HPPFbSbuAMHr95FARtLfN+tMmb1qwU3ZgFSDuheyxtFHW1wIyIOy46kqd9X+y3AzkX/O/rkP+xronz+3Vrw+/Xzo9FJlMeE0uN69OihAlMSqJAAhgQqJIji4OCgjvn+++8xevRoFVyRoMaoUaOwfft2FbySoMuTREZGwtnZGRERESobKK24uDhcvnwZvr6+sLW9f2Va/gN/5wmj+OyGfiWQLM55/euvv1LbLdlFHh4e+Pfff1G9evVMn/PDDz+owI8hG0r649dff0Xfvn0fOrZPnz4qCDht2rTUbRIwatKkiXoved/HFWKTTCnp1xkzZqB///5qv5zXihUr4syZMyhXrlyW3iMnZHqeiYiel+Bj+jpRJxYDsXcfbPeppy9aXqETYOP4VNPzpE5Ul2qcnvc8PG6cYOomT56s/rZLTUf5+/rzzz+jUaNGmR4rf18lg/rs2bOIiYlB8eLF8c4772Do0KEm0VchkXEYtvgYdl68ox7XK1kYP7xcBV6F7HP0fYhkWuio1Wfg42KPzR82gaXF/Wv2ks0qFw8Klwbe3w9oLdhZRNn93mUm360Fv19n/7t1VscJJlVT6r///kv3WOojScaUZO3IlC6Jn8kAS4JVkk0jpLi3m5sb5s+frwZT+ZlMi5syZYq6HxYWpgan7dq1w/79+9Vg8++//1b9d/HiRRXplcBf2v8cw4YNw5tvvom5c+eiZcuWePnll1GqlD6tWc6BPE+yrwzkfKSkpKj/hOXLl89SG9MWXZegmQgJCVFBqZx6DyIio4sO1QehJBh168SD7Y6e+tWcJDOqsP73a1oyPW/NcVk975rKDDFwsrVUU5UkGFXFi6vn0cPkIpNcFJK//Q0aNFAXeGQMIBeAfHx8HjpeLvZJJrL8XZb7EqSScZTcf/vtt02iEPW5W/dga6XFp23LoU+9EtBKeiBRDutVxweTt15CYFgMVh67ga7V72eq1n4b2P3rg2ypKq+w74nyGX6/zh0mFZTKSCJqhpXkhAQmpIB369at083zlEwaqUWUWVAqPj5e3dJG656Klb0+qmoM8t5PQQaSMl3PQGpCSWRSpulJwXPJQvv666/VFDnZvnDhQowfPz71eJkW2atXL6xevRpr167FyJEj1TFdunRRgSHpX6nxlFFmg91HfqT70wGFoTCpvLbh35x4DyIio5C6I5c26etDnVsLpNyv2WdhrV/avupr+uLlGa62y/S8PZdC8fehIPx36ibiEh+sntekTFG8VMNbrZ6nVoYieoQJEyaoTGS5uCTkItS6devUxSopj5BRtWrV1M1Asp2l7uOOHTtMIihVyMEav/WspqZWlSxawNjNoTzM3toSbzbyxbj/zuG3LRfVBQAL+QUsGaxSW0qypbaNAyp1Y7YUUXaZ0Xdrwe/X+TwoJRkykrnTsGFDVKpUSW2TgJSQzKi05PHVq1czfR0ZiEkg5plJ4OQp0vxMiQR9tFotYmNjsWvXLpUtJVlmBpn1mUyJlJuk70u9J8lWk6CUTAGU2l1pg145LTfeg4gox925oA9EHVsIROn/Tike/vpAlBQrt9dfXEnr8p1o/HNIpuddU/VMDErL6nmcnkdPISEhIbUWZFpyEU8u2mXFkSNH1LFSFsFU1Cmpr4lJ9Lz1rlsc07YFIOB2NNacCEYHf88M2VIXgJNLgSov82QQZYcZf7cW/H6dz4JSklIuxa4lnTyjjEv/SgDrUcsBjxgxQgW30mZKyapueZFkhBkCd3fv3sVvv/2mpul16NBBZZ0FBgaqzCep2SXZUFLvyUACVx999BFeeuklNR/02rVrquB5t27d1H6pO1G3bl28//77eOutt1TUWGpBbdiwQdWhygm58R5ERDkiLhI4tVQ/Pe/a/gfb7QsDVbrrp+e56y+opHUvLhGrOT2PctidO3eQnJyc6UU7w7jgUWSBE1mlV6b0S8a0IdMqM9nOPicyUY62Vni9QQn8vPECftt8ES9W9tBPF5VsqXoDgc3fAtslW6ors6WI8hF+v87HQakPPvgAK1euVAXMZbBk4O7urv6VAZahHpGhJlHGgVja6X1yyw+kJpehX6Tou9RpWrJkiVqhUEj2kwT75IfrxRdfxJdffqkGoMLCwgKhoaGq2PitW7dQpEgRVbfLkGUmNSe2bdumMq2kaKoEAqXeVPfu3XOs/bnxHkREz0zWBbl+GDgwQ7+KXlKsfrvGAvBrpQ9ElWkLWFo/tILYngCZnncNa08Gp5ue11hNz/NCy/JunJ5H2fY0F+0MZLqeXMDau3evyrSSbGXJlH4u2edEJuz1+r6YseOyqmW2/vQttK3knj5b6s55/e9+yX4lonyB36/z4ep70hQJSEkGz9atW+Hn5/fQfk9PTxVc+fjjj1NT1qUYuqzKl5VC50+9+h7lOTzPRPRUEmL0RW4lGBV89MH2ImX0gSj/HoDj/S8vaVyR6XmHr6kpehmn5xlWz+Oy9qbHHFffk7GQvb29uhAlU+4NBg8ejKNHj6oLPlkhU/dksRNZ0TirmVKSfW5OfUX0OD+sO4tJWy6hUjEnrBrY8EFQd/sPwOZR+t/77+1lthRRFvF7V94Xl9dW35NpW7KK3ooVK1SmjyHlXD6InZ2d+sMgK8t89913KmAlN7kvAzEp0E1ERJRjQi8BB2fp60XFhT8oWl6xK1DzDcC7tr42QobpeVKPRLKiDlxJv3pex6qeqmi5P1fPoxxmbW2tFjeR6e5pg1LyuFOnTll+Hbn4lzbolJ+zzyl/6t+wJGbvuoKT1yOx9dxtNCvnqt9R+x1g92/MliIieg5yJCiVmJioAkgxMTEoWrRo6mp5T0tWiBGG6WYGUmy7X79+6r5kSEn9o/fee0/VTapTpw7Wr1+vglhERETZXkHvwjp9VtSlzQ+2F/QBavYHqvUGHNIXX+b0PDIFUj+zd+/eqFmzJurVq4fp06erWpIDBgxIrbF5/fp1/Pnnn+rxpEmT1Mq2MtVfSA3PH3/8UWWsE+VXLg7WeK1ucUzfHoBfNl9A07JF9dlStk762lJbRulX4qvYhdlSRETGDkpJ/YF58+ZhwYIF2L9/f7ora1IHSlZ8kSWFpah2VmVlJqH8YZA6SIZaSERERNkWFQIc/gM4OAeIvGb4iwP4tQZqvQmUbvHQF5CrofrV8/45fB3Xw+/Xl+L0PDISqb8otSG/+eYbBAcHq5WL16xZo1beFbJNglQGKSkpKlAlKfeWlpaqhuPYsWOzVAqBKC97s5Ev/th9BUcCw7HrYiga+hXR76jzNrBHakudA04vByrpFwMiIiIj1JT66aefMHr0aJQoUQIdO3ZE7dq1UaxYMTXFLiwsDCdPnlSFM6U2lKymJiunZawPZSysKUWc20xEivz5C9yrz4o6vQJISdRvt3MBqvfWT9ErVCJdZ8UmJOPf4zew5OA17L8Slrqd0/PyDnOsKWUs7CvKq75aeQpzdl9BbV8XLH6n3oMdkiW1ZTRQtBzw7h5AqzVmM4lMHr935X1xxqoptXv3bmzZsgWVK1fOdL8Eqd544w1MnToVM2fOVAU2TSUoRURE+Vz8PeD4YuDATCDk1IPtXrX0WVEVOgNW6f+oXgyJwrx9V1VmVGRcktrG1fMou6UPJKt82rRpKFOmDDuTyIS806Qk5u8LxP7LYdgXEIo6Je9P267zDrDnN+D22fvZUl2N3VQiIrP3TEEpWd0lK6QYptR+MjeS0k55F88vUT4VchY4OBM4ugBIuKffZmkHVHlZXy/Ks2q6wxOTU7D+1C38tfcq9gSEpm73drFDz9o+6FrNC+7OXKmVno2VlZXKLE9d3YuITIaHsx1equmlAlO/br74IChl6wzUfR/Y+p0+a0ouYjBbiuiJ+P0r70rJgdiJSa2+Zwqr12i1Wty4cUMVbJfHHCzmHTJTVZbNvn37tjrPcn6JKI9LTgTO/qvPirqy48F2l1L6rKiqPQG7QumeIvWhFuwLxKKDQbh9Lz41K6p5OTe8VtcHjf2KQisbiLKpT58+KqNcajkRkWl5t0kpLD4QhJ0X7+Bw4F1U9yn0IFtq7yTg9hngzAp90XMiyhS/X+dduhz8bp3toJQsPZxZ4Ea2yZzC0qVLo1evXihbtixMnXSmzIWUYqASmKK8yd7eXq04JOebiPKoyBvAoTnAoT+AqJv6bRotUPYFfTDKt0m6q9vJKTpsv3Ab8/ZexeazIUi5X22xqKMNetbyRvfaPihW0M5IH4byKhnMzZgxAxs2bFCr5jk4OKTbP2HCBKO1jSi/83axR5dqxbDk0DX8tvkiZvW7v3iTXUGg7nvA1jHA1u+B8p2YLUX0CPx+nffZ58B362wHpaRw1fLly1GwYEHUqFFDRcyOHDmC8PBwVSth0aJF+P7777Fp0yY0aNAApk4ifNKpSUlJSE5ONnZzKIdZWFioVYaYAUeURwuXX96uL1x+djWgu/873MEVqNEPqNEXcPZK95Q7UfFYfDBITdG4dvfBCnr1SxVWy4K3quAGKwsGsOn5kOl71atXV/fPnz+fbh//ThEZ33vNSuOfw9fUxYqT1yNQqZizfkedAcCeyfezpVYCFTsbu6lEJovfr/Muixz6bp3toJS7u7vKhPrtt99So2Myr3Dw4MFwdHTEwoULMWDAAHzyySfYuXMnzIF0qtR6kBsREZm42HDg2EJ9vag7ab7YF28A1OoPlOsAWD5IKZaLJ1K8dt6+QKw9GYzEZH1alLOdFV6q4YVedXxQqmgBY3wSymdk0RgiMl2+RRzQwd8TK47ewK+bL2Ba75ppsqXeBbaNBbZJtlRHZksRPQa/X9PjaHQyOs8Gqb20a9euh1aOkSt+9evXx507d3DixAk0atRIZU8ZG5cvJiLKI4KP6wNRspJeYox+m3UBwL+HvnC5W4V0h0fGJWLZ4etqFb3zt6JSt/t7F8RrdXzUFw9bK4vc/hRkYow1Trh27ZoatBcrVgzmgmMqyg8u3LqH1j9vV8m4/w1phHLuTg8uiPxcBYiPAF75E6jQydhNJSIyy3FCtjOlZJrb2bNnHwpKyTbD9DepLcU0dCIiyrakeOD0Cv0UvaB9D7YXLa/PiqrSHbBN/0dPplzICnpypTs2Uf93yc7KAp2reeLVOsUfTMcgymWSWT5q1CiMHz8eUVH6QKlkmX/44Yf4/PPPWfuQyAT4uTmiXSV3rDlxU9WW+q1X9TTZUgP0mVJSW0qyclmvlIjoqWU7KNW7d2/0798fn332GWrVqqWCT/v378d3332nVpUR27ZtQ8WKFbP7VkRElF+FBwIHZwGH5wIxd/TbtJb6KRNSuLx4fckNTz08NiEZ/x6/gb/2BeJY0IMsXT/XAqpWVJfqxeBkyynaZFwSeDKsvid1NyV5XbLPv/rqK8TFxWH06NE8RUQmYGAzPxWUWn0iGENvRz2Y4i1T+PZOAUJO6Vd6rdDR2E0lIsp/0/ckG0oGU1JT6tatW2qbm5sbPvjgA1VHSopfBQYGqqt9Xl7pC8waA1PNiYjMREoKcGmzPivq/H9SDUq/3akYUON1oHofwNEt3VMu3Y7CvL2B+PtQECLjktQ2KwsN2lXyUMGoWiUKMXOXTGac4OnpialTp6Jjx/RfZFesWIH33nsP169fN+mzxTEV5Sdv/nEQG8/cQtfqxTDhlaoPdmweDWwfB7hVAt7ZwWwpIqKnHCdkOyiV8U1FbtZgeFocQBERmbiYMODIX/p6UXevPNhesqk+K6pMO8DiQaJvYnIKNpy+pabo7b4Umrrdq5CdKlr+Sk1vFClgk9ufgsxUbo4TpLzB8ePHHyqBcO7cOVStWhWxsQ9WhDRFHFNRfiJZt50m7YKFVoMtHzaFT2H7B3+zJvoD8ZHAK3OZLUVElNs1pQx1pbZu3YpLly6plfjEjRs31BsXKMAVjIiIKAuuHwL2zwBO/gMkx+u32TgD1V4Far4BFPFLd/iN8Fgs2B+IhQeCcPue/nitBmhezhWv1i2OJn5FoZUNRCbK399fZZr/8ssv6bbLNtlHRKZDFsVoXKYotp+/jclbL2Jstyr6HfYuQJ0B+mypbeOAcu2ZLUVE9BSyHZS6evUq2rZtq6boxcfHo1WrVqpI57hx41Q9BElLJyIiylRCDHBqqX6K3o0jD7a7VwFqvwVU6gZYO6RuTknRYduF22qK3uazt5ByP9dXMqF61PJGzzo+KFbQjp1NZkHGSi+++CI2btyIevXqqamlu3fvRlBQENasWWPs5hFRBoOal1ZBqX8OX8MHLfwe/L0x1Ja6dQI4txoo34F9R0SUW0GpwYMHo2bNmjh27BgKFy6cur1Lly548803s/vyRESUF0Vc0w/gZZpe3P1C5BbWQMWu+il6XjXTFS4PjYrH4oPXMH//VQSFPZjSVK9kYVUrqlUFN1hbao3xSYieWZMmTXD+/HlMmjRJrVosFRW6du2q6klJvSkiMi01S7iovzt7AkIxdeslfNu50oNsKVmJb/sP+tX4JFsqzd8wIiJ6jkGpnTt3qpVirK2t020vXry4yRfoJCKiXBZyFtg1ETixGEjRFyJHQR+gZn+g2muAQ5HUQ+UL+oErd1WtqP9O3kRCcora7mRriW41vPBqneIo7cop4mS+JMvc29s701X2ZJ+Pj49R2kVEj/ZBi9IqKLXoYBAGNi8NNydb/Y667wF7pwI3TwBnJVuqPbuRiCg3glIpKSlqBb6Mrl27pqbxERERIXAfsOtn4FyaKUklGgH1PwBKtwS0FqmbI+MSsfzIdRWMOn8rKnW7v5ezqhXVoYon7KwfHE9krnx9fREcHAxXV9d020NDQ9W+zMZXRGRckilVs3ghHLx6F9O3B+DL9hXS1JZ6B9jxI7BtLFDuRWZLERHlRlBKakj9/PPPmD59unos9RCioqIwcuRIvPDCC9l9eSIiMleyuOuF9cDOn4HA3fc3avRXjxsMBbxqpDv85PUIzNt3FSuO3kBMgv7LuK2VFp38i6kpepW9nI3wIYieH8kGlHFTRjKOkpX5iMj0yM+s1JPqO2u/+pv1btNSD1Z4rfc+sO9+tpRchJHAFBERPd+g1E8//YRmzZqhQoUKqrC5rL534cIFFClSBAsWLMjuyxMRkblJTgROLtVnRoWc1m/TWgH+PYAGg9OtoheXmIxVx25g3r5AHA26X1sKUNPyXqvjgy7VveBsZ2WMT0H03AwbNiz1y+2XX34Je3v7Bz8+ycnYt28fqlatyjNAZKIa+xVR2bvHrkVgxo7L+LRduQzZUuOBrWOBMu24Eh8R0fMOSkkhzqNHj6oA1OHDh9V0vv79++PVV1+FnR1XQCIiyjcSovWFy3f/CkQE6bdZOwI1X9fX2nDySD302t0YzNl1BUsOXUNEbKLaZmWhQZuK7iorqo6vS6YZJER5wZEjR1IzpU6cOJGuLqfc9/f3x/Dhw43YQiJ6HPn7NLC5H9768yDm7rmCdxqXRCGH+z/H9QYC+6YDN48Dh2YDtfqzM4mIHkOjkxFRPhIZGQlnZ2dERETAycnJ2M0hIjJ/MWHA/unAvmlAbJh+m0NR/RLZUsDcrmDqoaduRKgaHP8eD0Zyiv7Pjyyp3auOD16p6Y2ijvenQBDlg3HC66+/jokTJ5rteIRjKsrP5CvUC7/sxJngSAxqXhrDWpd9sFP+Hq79GLBxBgbuBxzdjdlUIiKTHic8U6bUypUrs3xsx44dn+UtiIjI1IUHAXsmAYf/ABJj9NsKlQDqDwKq9gKs7FIH7jsv3lHBqB0X7qQ+vUHpwujf0BdNyrjCQsusKMp/pCZnUtL9VSjTCAsLg6WlpdkGq4jyTW2p5qXx3rzDmL37Ct5sXBJOtvenm9d6Ezi2ELhxGPjvU+DlOcZuLhGRyXqmoFTnzp0f+qWcMeHKMO2CK8cQEeUxIWeAXROBE0uAlPtfqN2rAA2HAOU7ARb6Py1JySlYfSIY07YF4HRwpNomsacXq3iqqQ6VirFwOeVvPXr0QIcOHfDee++l27548WJ1AXDNmjSrVRKRyWlb0R1+rgVwISQKf+6+oqb0KbKibIeJwPSmwKllgH8voExrYzeXiMgkaZ/lSVI3ynBbv369Ksa5du1ahIeHq9QsuV+9enX8999/Od9iIiIyjsC9wPwewOS6wLEF+oCUb2PgtaXAO9uBSt1UQCo6Pgmzdl5Gkx+2YvDCoyogZWdlgX71S2DbR83wa89qDEgRyQyfffvUYjEZNW3aVO0jItOm1UptqdLq/sydl9Xfv1QeVfTT2MXqD/V1F4mIKOcLnQ8ZMgRTp05Fw4YNU7e1adNGrSTz9ttv48yZM9l9CyIiMpaUFODCemDnT0DQ3vsbNUD5DvrMqGI1Ug+9fS8ef+y+grl7r6YWLy/sYK2CUVK8PLUILBEp8fHxmU7fS0xMRGxsLHuJyAy0r+KJnzdewOU70fhr71W806TUg53NPgNOrwAiAvWr8bX+1phNJSLKm0GpS5cuqeJVGcm2K1euZPfliYjIGJITgRN/66fp3b5/ccHCGvDvAdQfDBTRXxkWl25HYcaOAPxz+DoSklLUNt8iDnizkS+6VfeCrZUFzyFRJmrVqoXp06fj119/TbddLvbVqPEg4EtEpktqIr7btBQ+/vs4ft8RgD71SsDO+v7fPWsH4IUfgQXd9TUYq7wCuFc2dpOJiPJWUEoGVJIt9ddff8HDQ7/c982bN/Hhhx+idu3aOdFGIiLKLTK94PCf+sFzRJB+m7UjUOsNoM67gJP+97w4dPUupm27hA1nbsFQVrCqd0EMaFISrSq4s3g50ROMHj0aLVu2xLFjx9CiRQu1bdOmTThw4IAqj0BE5qFLtWL4ZdMFXLsbiwX7A/FGQ98HO8u2BSp00mdMrRoM9N+grzlFRETPXlMqrVmzZiEkJATFixdH6dKl1c3HxwfBwcGYOXPmU73W9u3bVcFPT09PVSh9+fLl6fb369dPbU97q1u3bnY/AhERRYcCW8YAP1XUrxQkASkHV6DFSGDoSaDVNyoglZKiw4bTt/DSlN3oNmU31p/WB6RalnfF4nfqYdl79dG2kgcDUkRZ0KBBA+zZswfe3t6quPmqVavUOOr48eNo1KgR+5DITFhZaFW2lJi2/RLiEpPTH9D2e8DGCbh+CDg4yziNJCLKq5lShsHThg0bcPbsWbUKX4UKFdSVP8MKfFkVHR0Nf39/vP766+jWrVumx7Rt2xazZ89OfWxtzRolRETPLDxQnxUl2VGJMfpthXyBBoP0qwVZ2apNMsBefuS6mppw6ba+WKu1hRadq3ni7cYlUdrVkSeB6BnIYjHz5s1j3xGZuZdqeOG3zRcRHBGHJYeuoXfd4g92SpZxi/8Ba4YDG78GyrVPl3lMRJSfZTsoJST41Lp1a3XLjnbt2qnb49jY2MDd3T1b70NElO/dOqWvFyV1o3T3r+h6+AMNhuinGdyfWhARk4i/9l3FnN1XVCFz4WhrqQqXv16/BFyd9EErIsoeKWwuBc7TcnJyYrcSmQkbSwu807gkvlp1GlO3XkKPWt4qgypVzTeAYwuB6weBtR8D3ecas7lEROYdlFq4cCF69OiRpWODgoIQGBioUtRzwtatW+Hq6oqCBQuiSZMmqh6DPH7cyjZyM4iMjMyRdhARmaWre/Qr6V1Y92CbbxOg4VCgZFO5yqA2XQ+Pxaydl7FwfyCiE/RBKw9nW/Rv6IsetX1QwCZHrmkQ5WsxMTH4+OOP1dS90NDQh/YnJ2eYAkREJk3+Pv625ZL6G7rs8HW8Usv7wU652NNhIjCtMXBmJXBuLVD28RfjiYjyg2eqKTVlyhSUK1cO33//Pc6cub8qUxoRERFYs2YNevXqpVaPCQsLy4m2qiwqSXHfvHkzxo8frwqBNm/ePF3QKaMxY8aolQANN6nbQESUr6SkAGfXADNbA7Pb3g9IafQZUW9tAfquBEo1UwGpM8GRGLroKJqM24KZOy+rgFQ5d0dMeMUf2z9uhjcblWRAiiiHfPTRR2pMM3nyZJUJPmPGDHz99deqtuaff/7JfiYyM7La7NuN9UXOf9ty8eHaUu6VgPoD9ffXfATERxmhlUREpkWjkyJQz+Dff/9VSxhv3LgRDg4OcHNzg62tLe7evatW3ytatKiqDSUr8z0uk+mRDdNosGzZMnTu3PmRx0gxdSmwLplbXbt2zXKmlASmJHDGtHgiytOSEoCTf+un6d0+q99mYQ349wTqDwKKlFab5M/A7kuhmLY9ANvP3059ev1ShVW9qCZlij51jUAicyXjBLmIlRvjBFkYRoJPTZs2Ve91+PBhVatz7ty5WLBggbrAZ8pys6+IzEV0fBKa/rhVTXl/vUEJjOxQ8eFVbifX1dd0rDcQaDPaWE0lIjKJccIzz79o3769ukm6+c6dO3HlyhVVD6FIkSKoVq2aumm12V7c77E8PDxUUOrChQuPPEauPMqNiCjfkCuvUrh8z29A5HX9Nln1R+pZ1H0XcNTX5UtKTsGakzcxffslnLyun9qs1QAvVPbAO41LobKXszE/BVGeJ5nkvr76rAoZrBkyyxs2bIh3333XyK0jomfhYGOJcS9VweuzD2D2ritoVtYVjcsUfXCAtQPw4gRg3kvA3slAlVf0NR2JiPKpbBcFKVy4MDp16gRjkICY1KyS4BQRUb4XfQfYNw3YPx2IC9d3h4MrUO89fUDKVh9kiklIwqIDQWp63rW7sWqbnZUFutfyVjWjvF3s831XEuWGkiVLqot6coFNVi6W2lK1a9fGqlWrVO1MIjJPEojqU684/txzFR8uOYZ1QxrDxSHNiuF+rYCKXYFTS4FVg4E3N6UuMEJElN+YVKXaqKgoXLx4MfXx5cuXcfToUbi4uKjbV199hW7duqkglAziPvvsM5WZ1aVLF6O2m4jIqOLv6afo7ZkEJMbot7mU1E/Rk6l6VvoV8u5ExeOP3Vcwd+9VhMfoV/kq7GCNvvVLqKWrC6UdMBPRcydlDo4dO6YWbhkxYgRefPFFVRohKSkJEyZM4BkgMmOfvVBeTY2/GBKFT/85jmm9a6SfCt92LHBxE3DjCLD/d6DuAGM2l4jI/GpKPQ+ysl6zZs0e2t63b19VXF3qSx05cgTh4eEqMCXHfvvtt09VvJz1D4goz0hOAg7/AWwdA0TfrwXlURVoOAQo3zH1quvlO9H4fUcA/jl0DfFJKWpbicL2qmj5SzW8VGFWIsq9cUJAQICatpexVpusVnzw4EGUKlUK/v6mP52HYyqixzt1IwKdJ+1CYrIOY7tWVqvzpXNwFvDvUMC6APD+PsDZi11KRHlGVscJJhWUyg0cQBGR2ZNf2+fXARv+B9w59yAzquXXQPkOahU9cTjwLqZvC8C60zfVU0RV74J4p3FJtK7oDgspIEVEuT5OsLCwUIu1GBaC6d69O3755Re1aIw54ZiK6MmmbbuEMWvPqmnyawY3gm8Rh/Sr485qA1zbD5RrD/SYxy4lojwjq+OE51uJnIiIctaNo8AfHYAF3fUBKTsXoN044L19QIWOSNEBG0/fwitT96Dr5N3475Q+INWinCsWv1MPy96rj3aVPRiQIjKijNcDZZW96Ohoo7WHiJ4fyUquW9IFsYnJGLLoKBKT9RnLiiwK1WEioLUEzv4LnPmXp4KI8p0cqymVkJCgakBJyrmlpUmVqiIiMn/hQcDmb4Hji/SPLWz0K+k1HArYFVSD3GUHgzB9e4CqXyGsLDToUq0Y3mpUEn5ujsZtPxERUT4kWckTXqmKtj9vx7GgcPy66QKGtS774AC3CvoakDsnAGs/Bko2AWz4N5uI8o9sZ0rFxMSgf//+sLe3R8WKFVU9BDFo0CCMHTs2J9pIRJR/xUUAG0YCv9Z4EJCq/ArwwUGg1dfQ2TpjzYlgtP5pOz7++7gKSDnaWmJAk1LY+UlzjHvJnwEpIhMjtaQy1pPK+JiI8g7PgnYY3aWyuv/blos4eCUs/QGNPwIKlQAirwObRxunkURERpLtlCZZLUZWjpEi5W3btk3d3rJlS4wcORKffvppdt+CiCj/SU7UF0Dd9j0QE6rfVqIR0OoboFh19XDPpVCM/e+suvJqWEnvnSYl0bO2DxxtrYzZeiJ6wvS9fv36wcbGRj2Oi4vDgAED4OCQptYMgKVLl7IfifKIDv6e2HI2BEuPXFfT+NYObvTgb7W1PfDiBOCvrsD+aUCVV1L/1hMR5XXZDkotX74cixYtQt26ddNd5atQoQIuXbqU3ZcnIspfpNaM1JWQ7Kiw+79Di5TRB6PKtFVFzE/fiMS4dWex9Zx+xT0Hawu81bikqltRwIbTp4lMnawqnNZrr71mtLYQUe75ulNF7L8Shmt3Y/HVytMY/0qaVTZLtwAqvwycWAJsHAn0XcVTQ0T5Qra/vdy+fTt19Zi0pGAnU9GJiJ7CtYPAus+BoL36xw5FgaYjgOp9AQtLBIXFYMKG81h+9LqKXVlqNXi1jg8GNvdDUUd9xgURmb7Zs2cbuwlEZASSGfVT96roPm0P/jl8Dc3LueLFKh4PDmjxP+DkUuDydiD4GOCRJmhFRJRHZbumVK1atbB69erUx4ZA1O+//4569epl9+WJiPK+sMvAkteBGS30ASlLO319iUFHgFr9ERaXgm9WnUaL8duw7Ig+ICXTADZ92ARfd6rEgBQREZGZqFXCBe81La3uf7bsBIIjYh/sLOgDVOyiv7/7NyO1kIjIzDKlxowZo2pJnT59GklJSZg4cSJOnTqFPXv2YNu2bTnTSiKivCgmDNgxHtg3DUhJlLA+UPVVoNlngHMxxCQkYdbmC5i2LQD34pPUUxr5FcHHbcqhspezsVtPREREz2BwSz/suHAbx65F4MPFx/BX/zrQau+XQak/EDj5N3DyH6DlSMDZi31MRHlatjOl6tevj127dqlV+EqVKoX169fDzc1NBaVq1KiRM60kIspLkuL1V0B/qQbs+U0fkCrZFBiwA+g8CYkFPDBv31U0+WErflx/XgWkKhVzwtz+tTG3fx0GpIgoU5MnT4avry9sbW3VGGzHjh2P7Ckpot6qVSsULVoUTk5OKrt93bp17FmiXGBloVXT+OysLLD7Uihm7Ax4sNOzmn5hE10ysHcKzwcR5XkanSwBk49ERkbC2dkZERERahBGRJRr5NftqWXAxq+A8Kv6ba4VgFbfqgKn8st47cmb+HHdOQTciVa7fVzsMbxNWbSv7PHgKioRPTfmOk6QRWd69+6tAlMNGjTAtGnTMGPGDJXJ7uPj89DxQ4YMgaenJ5o1a4aCBQuqOlc//vgj9u3bh2rVquXpviIyFfP3BaopfFYWGqx4vyEqeN7/OTq/Hpj/MmDtCAw7BdgyO5qIzE9WxwnPFJSSF88qUxukcABFREZxdQ+w/gvg+kH94wLuQPPP9dP1tBbYcykUY/87i2NB4Wp3YQdrDGrhh561fWBtme2kViLK4+OEOnXqoHr16pgy5UFmRfny5dG5c2dVaiErKlasiO7du+N///tfnu4rIlMhX8PennsIG07fgp9rAaz6oCFsrSyAlBRgSj3g9ln9hasGg4zdVCKip5bVccIz1ZSSK2pPWllPfsnKMcnJyc/yFkREeUPoJf3SzmfuL+1s5QA0GKyvGWHtgNM3IjFu3VlsPXdb7ba3tsBbjUrircYlUcAm22X/iMjEnT9/Hlu3bkVISAhS5ItoGlkNDiUkJODQoUP49NNP021v3bo1du/enaXXkPe+d+8eXFxcHnlMfHy8uj3LRUoieph8VxrbtTKOBoXjQkgUJm66gE/algO0WqDeQGDlQP0UvjoDAEtrdiER5UnP9I1ny5YtOd8SIqK8JDoU2PY9cHAmkJIEaLRA9T5A0xGAozuCwmLw04ajWHZUv5qepVaDV+v4YGBzP66mR5RPyErF7777LooUKQJ3d/d0F/zkflaDUnfu3FEXAaWmZ1ry+ObNm1l6jfHjxyM6OhqvvPLKI4+RjKuvv/46S69HRFlTuIANRneupDKmZu68rMYCXoXsgSqvAJu+Ae7dAE4tBfx7sEuJKE96pqBUkyZNcr4lRER5QWIcsG8KsGMCEH8/i8CvNdDqG8C1PMKiE/DbqtP4a+9VJCTrsyI6+Hviw1ZlUKKIg3HbTkS5atSoURg9ejQ++eSTHHm9jFnshqz1J1mwYAG++uorrFixAq6uro88bsSIERg2bFi6TClvb+9stpqIWlVwQ92SLtgbEIbx68+rIuiwtAHqvANs/hbY/StQpbv8kLOziCjPyfbckOPHj2e6XQZBsvqLFNe0sbHJ7tsQEZk2mXYjSzjLVc2IIP0298pA61FqZb2YhCTM2nwB07YFqNX0RMPSRVSafmUvFjAlyo/u3r2Ll19+OduvI5lWFhYWD2VFyZTAjNlTmRVI79+/P5YsWYKWLVs+9lgZz3FMR5Tz5HvT5y9UQIffdmLZkevo39AXlYo5AzXf0F/kunUSCNgClGrO7ieiPCfbQamqVas+9iqclZWVKpopq8BIkIqIKM+5vF1fxDz4mP6xUzGg+ZfqqmaiDli87yp+3ngBt+/pa7FU9HTCp+3KoZFfUeO2m4iMSgJS69evx4ABA7L1OtbW1qhRowY2bNiALl26pG6Xx506dXpshtQbb7yh/n3xxRez1QYiyh65QNW5qieWH72B0avPYP5bdaCxdwGq9wb2TdVnSzEoRUR5ULaDUsuWLVNp5x999BFq166tUsUPHDigahOMHDkSSUlJqvDmF198oZYaJiLKM26fAzaMBM6v1T+WpZsbDQXqvgedpS3WnryJH9edQ8CdaLXbx8Uew9uURfvKHtBqmYJPlN+VLl0aX375Jfbu3YvKlSurC3lpDRqU9RW3ZFpd7969UbNmTdSrVw/Tp09HYGBgasBLpt5dv34df/75p3osgag+ffpg4sSJqFu3bmqWlZ2dnVoph4hyn4wR1py8iT0BodhyLgTNy7kBdd8F9k8HLm0Gbp4E3Cvx1BBRnqLRSRQpGyQQ9e2336JNmzbptq9bt04NtPbv34/ly5fjww8/xKVLl2BsXL6YiLItKgTYOgY49AegSwY0FvoU+yafAAWKYs+lUIz97yyOBYWrwws7WGNQCz/0rO0Da0stTwCRCcvNcYKvr+8j90kWekBAwFO93uTJkzFu3DgEBwejUqVK+Omnn9C4cWO1r1+/frhy5Ypa6U80bdoU27Zte+g1+vbtizlz5mTp/TimIsp5Y9aeUVP9/VwLYO3gRrC00AJL+gGnlgH+PYEuU9ntRGQWsjpOyHZQSq6oHTlyBOXKlUu3/ezZs6hWrRpiY2PVIKhChQqIiYmBsXEARUTPLCEG2DMJ2PUzkBCl31b2RaDV10ARP5y+EYlx685i67nbape9tQXealQSbzUuiQI22U5MJaJcwHEC+4rImCJiE9H0hy24G5OI77pURq86PsD1Q8DvzQGtJTD4OOBcjCeJiPLMmCrbl+wlGDV27FgkJCSkbktMTFTbDIEqSRd/UqFNIiKTlZIMHJkH/Fod2DJKH5DyrA70WwP0nI8gbTEMW3QUL/66QwWkLLUa9KlXHNs+aoahrcowIEVETyTXCLN5nZCI8gBnOyt80NxP3Z+w4TyiZXGUYjWA4g2AlCRg/zRjN5GIKEdlOyg1adIk/Pvvv/Dy8lKrtrRq1Urdl21TpkxRx0j6+XvvvZcT7SUiyl33bgFzOwMr3gPuBQPOPkC3mcCbmxBWtBa+/fc0WozfhqVHrkO+T3bw98TGYU3wTadKKOrIlUeJ6PGkxpPUk5LMc7lVqVIFc+fOZbcR5WOv1S2O4oXtcScqHtO235/GW/8D/b8HZwNxkUZtHxFRTsr2fJL69eur6Xl//fUXzp8/r67yvfTSS+jVqxccHR3VMVJ4k4jI7ARsBf55C4gOAawcgKafALXfQYzOErO2XlI1H+7JFUwADUoXxqdty6vVc4iIsmLChAmq/ubAgQPRoEEDNYbatWuXKk5+584dDB06lB1JlA9J/clP2pbDe/MO4/ftAXi1jg/c/NoAhf2A0AvAkblAvfeN3UwiohyR7ZpS5oa1IogoS9P1to0Dtn0vk2oA1wrAy38g0aU0Fh8Mws8bL+D2vXh1aEVPJ3zarhwa+RVlxxLlAbld6Pzrr79Wq+Cl9ccff+Crr77C5cuXYco4piJ6fuQrWrcpu3E4MBw9anljbLcqwKE5wKrBgLM3MOgIYJF+xU4iInMcJ+RI5V3JkJLVXEJCQpCSkpJu3//+97+ceAsiotybrvdPf+DKDv3j6n2gazsW/52LxA9/bEfAnWi12dvFDsNbl0WHKp7QajU8O0T01GSVPMk4z0i2yT4iyr9kBc7PXyyPblP2qAtirzfwRdkqPYDNo4CIIOD0CqDyS8ZuJhFRtmU7KPX777/j3XffRZEiReDu7q5+gRrIfQaliMhsp+u1/wkhvp3w0V/Hse28fkW9wg7WGNTCDz1r+6j0eiKiZ1W6dGksXrwYn332WbrtixYtgp+fvtAxEeVfNYq7oF0ld6w9eRNj1p7BnNdrA7XfBraMBnb/AlTqJl+4jN1MIiLjBqVGjRqF0aNH45NPPsnuSxERmdR0vfUhTvh04g6ERSfAxlKLd5qUwtuNS3I1PSLKETJ1r3v37ti+fbuqKSUX83bu3IlNmzapYBUR0cdty2HD6Vtqdd+dF+6gYc3+wI4JQPAxfVa3b2N2EhGZtWxf5r979y5efvnlnGkNEZExpuv92QnYNlYfkKreBzF912HEjji8PfeQCkhV8HDCvx80xLBWZRiQIqIc061bN+zbt09lmy9fvhxLly5V9/fv348uXbqwp4kIvkUc1Gp84rs1Z5Bi5wJUe1XfM7t/ZQ8RkdnLdlBKAlLr16/PkcbIlcIOHTrA09NTXS2UAVrGgn9S+FP2y7LJTZs2xalTp3LkvYkon07Xm9pQf6VRput1mY5j1b7Fi1MOY8H+IJUR/07jklj2fn34uelXEyUiykk1atRQKxgfOnQIhw8fVverVavGTiaiVFI2wNHGEqeDI7HsyPX7K+9pgAvrgZAz7Ckiyt/T96QegixnvHfvXlSuXBlWVulXgRg0aFCWXys6Ohr+/v54/fXX1dXDjMaNG6eWT54zZw7KlCmjpg62atUK586dg6MjvzAS0bNP10t+aQ6mnNTi50W7kZSig4ezLca/4o/6pYqwW4koR1eiMaxAI/cf53mv/kdE5sHFwRrvNy+NsWvP4sf15/Di8KawLd8BOLMS2PMb0GmSsZtIRPTMNDpJP8rmcsaPfHGNBgEBAc/0uvLcZcuWoXPnzuqxNFMypIYMGZJavyo+Ph5ubm74/vvv8c4772Tpdbl8MVE+l8nqetfqjMTQZedx4MpdtenFKh74rnNlONtzqWWi/OZ5jxMsLCzUynqurq7QarXpFogxkDGPbE9OToYp45iKKPfEJSajxfhtuB4ei4/alMX7pe8CM1sCFtbAkBOAoztPBxGZ5Tgh25lSly9fzu5LZPl9bt68idatW6dus7GxQZMmTbB79+5HBqUkcCU3gyddlSSi/LO6nq79BCxPaYj/TT6Ee/FJql7UN50qoku1Ypl+USQiyq7NmzfDxcVF3d+yZQs7lIiyxNbKAsPblMHQRccwZesl9KjVFIW96wJBe4H904EW/2NPEpFZynZQ6lFOnDiBmTNn4ueff86R15OAlJDMqLTk8dWrVx/5vDFjxqjVbYgoH8tkut69jjPx2Y54rDp2TB1Ss3gh/NS9Krxd7I3dWiLKw+RiWtpsc29v74eC4JIpFRQUZITWEZEp6+RfDDN3XsbJ65GYuOkCvqn/AbBoL3BgJtBwGGBTwNhNJCLK/ULnaUkW0rRp01C7dm1VG2rr1q3IaZkN3B6X0TBixAiVLma4cZBHlM9ksrre/pZL0GZuMFYduwELrQYftiqDhW/XZUCKiHKVBKVu37790PawsLDHlkcgovxJq9XgsxfKq/vz9wUiwKUR4FIKiAsHjvxl7OYRERkvKLVt2zb06dMHHh4eeO+999C8eXOcP38eR48eRU5xd3dPlzFlEBIS8lD2VFoyxU/mL6a9EVH+XF0vqdM0jLV6H91nH8ONiDiUKGyPvwfUwwct/GBpkaMxeiKiJ3rUhbWoqCjY2tqyB4noIbIAS/NyrmpRlu/XX7i/Eh+AvZOA5CT2GBHln+l7UqRz9uzZmDVrllo1r2fPnio4Va9ePRWgklX5cpJcMZTA1IYNG1KXSk5ISFDvKYXOiYgeN13vaospeH/9PZy8fkkd0qOWN75sXwEONs9tFjMRUaaGDRum/pWAlKxgbG//YNqwFDfft28fqlatyt4jokyNaFcOW8+FYN2pWzhYty1q2o8GwgP1q/FV6speIyKzYpmdINHLL7+MSZMmoVWrVmoFmeySK4MXL15MV9xcsq2kIKiPj49aee+7776Dn5+fusl9Gcj16tUr2+9NRHlzdT1dtT5YUOR9fPPXZcQlpqCQvRXGdK2CtpW4Sg0RGceRI0f0v590OlWD09raOnWf3JcSCMOHD+fpIaJM+bk5onstHyzYH4hR669gWa03oZELcbt/BSp2kYg3e46I8n5Qqnjx4ti5c6cKFsn9cuXKZbsxBw8eRLNmzR66kti3b1/MmTMHH3/8MWJjY9UUwbt376JOnTpYv349HB0ds/3eRJT3VteLbPUDhpwug8179NlRjfyK4MeX/eHmxGkxRGQ8hlX3Xn/9dUycOJGlBYjoqQ1t5YcVR6/jaFA4NtTqgNaWE4Ebh4Gru4ESDdijRGQ2NDq5TPeMdu3apVbYW7JkCcqUKYPXXntNBY6OHz+O8uX1RfhMjRRjd3Z2VkXPWV+KKC9N1/teP2Xv/nS9vTXHY+D6aNyJSoC1pRafti2HfvVLqCKhRESmME6Q95DpepIRnrHQuaWlpcmPUzimIjKuiRsv4KeN5+HtYoet5VbA4vAcoEw7oNdCnhoiMptxQrbm3DVo0EDVlJL6UgMGDMDixYvV4EoymX7//fdMV5QhIspR927eX11PXz8qqWpvfOP+K3osvasCUuXcHbFyYAO80dCXASkiMik9evTAwoUPf3mU8ZTsIyJ6nLca+8LV0QZBYbH4x6az5BsA59cCt8+z44jIbOTIclMFChTAW2+9hT179uDUqVOoUaMGvvjiC3h6eubEyxMRPWZ1vUapq+sFNZuINpdewqz9t9TuNxv6Yvn7DVDO3bSzDYgof5KC5mnLFhg0bdpU7SMiehx7a0sMa1VG3R+9NxGJfu30O/b8xo4jIrOR42ugy7S9H3/8EdevX8eiRYty+uWJiPTT9bZ8B/zZWdWP0rlWwIKqf6L5eldcuh0NNycb/NW/Dr5oXwG2VhbsMSIySfHx8UhKengJ98TERFVDk4joSV6u6Y2ybo6IiE3EfIuO+o3HFgJRIew8IsqfQSkDqYXQtSuXJCWi5ztdL7rSa+itHYMRO+KRmKxD24ru+G9wYzT0K8KuJyKTVqtWLUyfPv2h7VOnTlVZ50RET2Kh1eDTF/QLTo0+4Yx49xpAcjyw/3d2HhHl7dX3iIhy3aUtwFJZXe+2mq53yH8k+h0sgXtx0XCwtsDIjhXxcg0vaLgUMhGZgdGjR6Nly5Y4duwYWrRoobZt2rQJBw4cUKsLExFlRdMyRdGwdBHsvHgHc7Ud8SYOAQd+BxoOBazt2YlElD8zpYiIcny63twuKiCVXLQCxnhPQbedXrgXl4RqPgWxZnAjvFLTmwEpIjIbsmCM1OP09vZWxc1XrVqF0qVLq1WMGzVqZOzmEZGZkItxI14oB7km911AKcQ7+gCxd4Gj84zdNCKiJ2KmFBGZ/nS9f97UFzMHEFKmB7pf7YzLQSnQaoAPmvvhg+alYWnBGDsRmZ+qVati3jx+cSSi7Kno6Ywu1Yph6eHr+EvTHv0xGdgzCaj5BqBlfU0iMl0MShGRWUzX01k5YE3xT/DBidJI0aXAx8UeP3WvihrFCxm7lUREzyQwMPCx+318fNizRJRlw1uXxerjwfgxpCZ6OxWE9d3LwJlVQMXO7EUiyrtBqejoaIwdO1bVQAgJCUFKSkq6/QEBAdl9CyLKj9P1pJD5tnGqmHl84fIYmjwEa046qt0v1fDCVx0rooAN4+pEZL5KlCjx2CnHycnJudoeIjJvngXt0L+hLyZvvYRFaI3eWAyseB/QWgLl2xu7eUREmcr2N7o333wT27ZtQ+/eveHh4cF6LkSUo9P1Lnp3w0tXOiM80QLOdlYY07UyXqjswV4mIrN35MiRdI8TExPVtgkTJqgi6ERET2tA01JYeCAIYyPboJVHANzvHgQWvQo0+QRo8imgZbkDIjItGp1Op8vOCxQsWBCrV69WxTrNQWRkJJydnREREQEnJydjN4eI0rpzEZjdDogOgc7KHjMLDsaooMpqV4PShfHjy/7wcLZjnxFRnh4nyLjqhx9+wNatW2HKTKGviOhhf+65gv+tOAU3ey12VN8C64PT9DvKtAO6TgNsndltRGQy44Rsh8oLFSoEFxeX7L4MEeV3SQnAP2+ogFSUcxm8rBurAlLWFlp8/kJ5zH2jDgNSRJQvlClTBgcOHDB2M4jITPWs7YOSRRxwKyYFH0f1REKHyYCFDXB+LfB7C+DOBWM3kYgo54JS3377Lf73v/8hJiYmuy9FRPnZ5m+B4GOIsXBCi1uDcDCqCPxcC2D5+w3wVuOS0MpSe0REeewKYtqbXEk8e/YsvvzyS/j5+Rm7eURkpqwstPiifXl1f/nRG+i00wfXui4DnIoBoReA35sD59Yau5lERM9eU6patWrpakddvHgRbm5uqmCnlZVVumMPHz78LG9BRPlJwFZg9y/q7pDY/rgFF/SrXwKftisHWysuY0xEeZOUQMhY6FyqKnh7e2PhwoVGaxcRmb/m5dww5/Va+HDxMZwJjkTrRRYY13Y+2p8dAQTuBhb0AJp9DjQazjpTRGR+QanOnbmsKBHlkJgwYNkAdXd+UnNs1NXClFerox2LmRNRHrdly5Z0j7VaLYoWLYrSpUvD0pKrixJR9jQt64o1gxthyMKj2BMQioErr2NrtW8xpvp8WB2eCWwZrbLU0WUqYKNf4ZiIyOwKnZsbFuUkMiHy62fRa8DZf3EpxQPtE0bjo/bV8UZDX2O3jIjyKY4T2FdEeU1yig6TtlzEzxvPI0UHVW9qbvXzKLbrcyA5AShaDugxHyhcythNJaJ8OKbK9mU4KcSZkpKCOnXqpNu+b98+WFhYoGbNmtl9CyLKqw7NUQGpRJ0FBiV+gK51yuD1BiWM3Soioudm5cqVWT62Y8eOPBNElG0WWg0GtfBD3ZKFMWjBEQTciUazzd74ucFMtDv9MTS3zwLTmwHdZgBlWrPHici8MqVq166Njz/+GC+99FK67UuXLsX333+vglOmhFdAiUzE7fPQTWsMTVIsRif2wtmS/TCrXy1VnJOIKK+OE2SKXlpSUyrtUCxtjank5GSYMo6piMzP3egEfPT3MWw8E6Iev1zWCmOSfoDl9f3yGwho8SXQcJj8MjJ2U4nIzGV1nJDtb3+nT59G9erVMy2GLvuIiB6SFI+Uv/urgNSO5ErYUuhl/NarOgNSRJTnSXa54bZ+/XpUrVoVa9euRXh4uBq0rVmzRo2r/vvvP2M3lYjyoEIO1vi9T038r30FWFlosORcIlrcGY7bZXtJXQVg0zfAkr5AfJSxm0pE+US2g1I2Nja4devWQ9uDg4NZpJOIMqXb9C20t44jTFcA31p+gJmv14GzXfqVO4mI8rohQ4Zg4sSJaNOmjbqC6OjoqO5PmDABgwYNMnbziCiPkoxMqd+59N0GKF7YHlcjklD3RAdsLfM5dFor4PQKYGYrICzA2E0lonwg20GpVq1aYcSIEerqnoFc7fvss8/UPiKidC5tgWbPr+ru58kDMLpvaxQv7MBOIqJ859KlSyqtPSPZduXKFaO0iYjyj8pezvj3g4bo6O+piqH3O14R3xYZh2QHVyDktL7O1MVNxm4mEeVx2Q5KjR8/HkFBQShevDiaNWumbr6+vrh586baR0SUKiYMsYvfUnfnJbVAyy6vo1YJF3YQEeVLtWrVUtlSkl1uIOOnDz/8UNXsJCJ63hxtrTCxR1V8360ybK20mBXohhfjRiOycFUgLhyY9xKwa6J+xWQiIlMMShUrVgzHjx/HuHHjUKFCBdSoUUOlop84cQLe3t4500oiMn86HcIWvAO7+Nu4mOKJkPr/Q7caXsZuFRGR0cyaNQshISHqwl7p0qXVzcfHRwWpZs6cyTNDRLk2na97LR+sHNgQZdwK4Gy0A2rdGIrjRTsAuhRgw/+Af/oDCdE8I0Rkeqvvbd++HfXr13+oflRSUhJ2796Nxo0bw5RwpRgi4wjdNg2Ft3yMBJ0FfvSZjE9f7w6tliu7EBHy9ThBhmEbNmzA2bNn1X25wNeyZct0q/CZKo6piPKe2IRkfPPvaSzYH6gKn39edDfejJ4GTUoS4FYZ6PEXUKiEsZtJRGYgq+OEbAelLCws1BU9V1fXdNtDQ0PVNlNbzpgDKKLcd+/aaVjNaAJbJGCW/RvoOeRH2Flb8FQQkcnhOIF9RUTAqmM38NnSE7gXn4SmthcxzWYibOJDAbtCwMtzgJJN2U1ElCNjqmxP35OYVmZX8yQo5eDA4sVE+V1ifCxC/+itAlL7NVXQ/p3RDEgREd23adMmtTjMm2++iTfeeCPd7WlNnjxZ1fW0tbVV5RR27NjxyGPlgmKvXr1QtmxZaLVaVduKiMigg78nVg9qBH8vZ2yNK42mEV/hun05IPYuMLcLsGcS60wRUY545qBU165d1U0CUv369Ut9LLdOnTqpJY1lWl9O++qrr9R7pr25u7vn+PsQUfZJ0HrPjKEokXgRd3WOcO41A67O9uxaIiIAX3/9NVq3bq0CU3fu3MHdu3fT3Z7GokWLVGDp888/x5EjR9CoUSO0a9cOgYEyBedh8fHxKFq0qDre39+f54OIHuJT2B5LBtTHW418EYzCaB72KTZat9DXmVr3GbD0bSAxlj1HRNmSvhDUUzAsYSxfOh0dHWFnZ5e6z9raGnXr1sVbb+lX2cppFStWxMaNG9NNISQi07Nu5UK0vb1A3b/a8HtU9Str7CYREZmMqVOnYs6cOejdu3e2X2vChAno37+/yrgSP//8M9atW4cpU6ZgzJgxDx1fokQJtTCNoeA6EVFmrC21+PzFCqhXqjA+XHwMb0a+gbetvfGpxVxoTywG7pwDus8DCnKBKyLK5aDU7NmzUwc1w4cPz9WpelJUndlRRKZtx7EzqHb4U0ADnPHshqqtXjV2k4iITEpCQkKOZJXL6xw6dAiffvppuu2ShSWLzhARZVfzcm5YO7gxBi88gumXW+O41gsz7H5FgeBjwPQmwMt/AL6N2NFE9NSyXVNq5MiRuV476sKFC/D09FR1E3r06IGAgIBcfX8ierwzNyKQsHQg3DThCLEpjnL9fmWXERFlIFlN8+fPz3a/yNQ/WVjGzc0t3XZ5fPPmzRzrd5nyJ0VL096IKP9wd7bF/LfqYnALP+zXVUCb6G9wQVsSiAkF/uwE7JvGOlNElDuZUtWrV1f1DwoVKoRq1ao9dtniw4cPIyfVqVMHf/75J8qUKYNbt25h1KhR6irjqVOnULhw4UwHUHIz4ACK6PkKuReHVbO+w8eag0iCJQr1/hMaay56QESUUVxcHKZPn65KElSpUgVWVlYPTcl7GhnHY49ajOZZyTRAqYNFRPmXhVaDoa3KoG7Jwhiy6Ag6RH6J761nopN2J7D2Y+DGUaD9T4CVrbGbSkR5OSglhcxtbGxS7+fkgOdJpGinQeXKlVGvXj2UKlUKf/zxB4YNG/bQ8RxAEeWeuMRkfDNrGX5InKWm7SU2/RJ2XlV5CoiIMnH8+HFUrar/HXny5Ml0+55mbFWkSBFVXzNjVlRISMhD2VPZMWLEiHRjLbnQ5+3NOjJE+ZHUmFozqBGGLzmGwefexXGL4vjcagG0x+YDt88C3f8CnIsZu5lEZAY0OrmMZuZatWqF0qVLq2KeWcmUkgFUREQEnJyccrmlRHlXSooOQ+fvw9vn30ZF7VXEejeG3esrAG22ZwkTEeUaGSfIYi7mNk6QTPIaNWpg8uTJqdsqVKigLh5mVug8raZNm6rgmBRHzw99RUQ5O/6btesyvv/vLGrrjmOy9a9wRhTgUBR45U+geM6vxk5E5iGr44Rn/rYYExOD999/H8WKFYOrqyt69eqlahrkNgk4nTlzBh4eHpnul4wu6YC0NyLKeT9vPI+KZ39RAalEm0Kwe3k6A1JERLlEMphmzJihVtKTcdHQoUMRGBiIAQMGpGY59enTJ91zjh49qm5RUVG4ffu2un/69GmeMyLKMq1WgzcblcTfA+ojsGBtvBg/CmdSfIDo29D90QHY/zvrTBHR81l9TwqcyzLGr776KmxtbbFgwQK8++67WLJkCZ4nWemvQ4cO8PHxUWnpUlNKInB9+/Z9ru9LRI+2/Mh1HN66DH9Zr1aPrbpMBpwyDxQTEeV3Xbt2zdJxS5cuzfJrdu/eHaGhofjmm28QHByMSpUqYc2aNShevLjaL9skSJWW1AU1kNX7pOi6HH/lypUsvy8RkfD3LojVgxphxNKC6Hr8K4yzmo4O2AusGQ7ICn0vjgcs9eVfiIhyJCglA6WZM2eq1e/Ea6+9hgYNGqjVX6SuwfNy7do19OzZU2VlFS1aFHXr1sXevXtTB11ElLsOXgnDmL93YqXV/emzNd8Ayr3A00BE9AiSyv48vPfee+qWGbmQmFEeqOBARCbEydYKv/WshgWlimD4KjucTPTFx1aLYHFkrr7O1CtzedGSiHKuppS1tTUuX76spu8Z2NnZ4fz58yZd9JL1D4hyTlBYDDr/thNjEseitcUh6IqUhebtrYC1PbuZiMwSxwnsKyLKvrM3IzFw/hF43tmFX61+hbMmBroCbtBIYMqnDruYKB+IfN41pSQjSgJTaVlaWiIpKelZX5KIzEjIvTiMmrkYvyR+pQ9Iaa2g6TaDASkiIiKifK6cuxNWDmwAj+rt0TFhFM6leEETdQu6OS8CB2ezzhQRZX/6niRY9evXTxUSN4iLi1MFNR0cHJ6pHgIRmb6I2ETM27gfrgd+wBTNVmgtdNBZ2EAjtQI8qhi7eURERERkAuytLfH9S1WwonRhvLa0ML5OnoQXsB/4dwiw5zegai/Avyfg5GnsphKROQalMissLnWliChviktMxl87ziJm+694Q7cMBbRxantkqY5waj8KKMS6bkRERESUXqeqxeDvVRAD57vgxK15GGS5FHahF4FN30C3eRQ0JZvpA1TlXgSs7Nh9RPnMM9eUMlesFUH0dBKTU7DkQBBOb5iNAUlz4aW5o7aHu1SBc+cfoPGpyy4lojyD4wT2FRE9H/FJyRj33zn8vfs0Wmv24SWL7aijPZu6X2fjBE3ll4CqrwLFagAaDU8FUT4YUzEoRUSZSknRYfWJYKz9bxXejJ6O6tqLanuMrTts230DbeWXAe0zl6UjIjJJDEqxr4jo+boTFY9/j93AsqM3EH7tLLpZbEc3ix0opglNPUZXpAw0kj1VpQdX7CMyUwxKZbNjiPIrSZ7cfuEOZq/eji5hM9DJYrfanqi1habRUFg2GMRi5kSUZ3GcwL4iotwTcDsKy4/ewIrDQSgWcVBlT7XT7oedJkHt12m0QKkW+gBV2RcAK1ueHiIzwaBUNjuGKD86HHgXE9ccQc1rf+Ati9Ww1SRCBw2SqvSEVcv/8UoVEeV5HCewr4jIOBdFDweGY/mR69h87CIaJuzESxbbUEt7PvWYFJuC0FaR6X29AM/qnN5HZOIYlMpmxxDlt7pRnyw5AssTCzDccglcNeH67d71YdVuDOBZ1dhNJCLKFRwnsK+IyLgSklKw7fxtFaA6f+YoOmKbmuLnqQlLPSa5cFlYVH8VqNIdcHQ3anuJKHMMSmWzY4jyi+QUHUbM34WXzg9Dbe05tS3JuQQs244CyrXnVSgiylc4TmBfEZHpiIxLxH8nbmL54UBYXN2Bbhbb0FZ7QGXzixSNBXSlWsCi2qtA2XaApY2xm0xE9zEo9QgcbBKlT5X+5p/9eOH4QJUenWRVAJbNRgC13wYsrdlVRJTvcJzAviIi03QjPBYrjt7AusPnUC50k6o/VTPN9L4ka2dY+L+irz/lWY0XVomMjEGpbHYMUX7w4+qjqL/3XdS3OI0EKydYv/Ev4OFv7GYRERkNxwnsKyIy/YuqZ4LvYfnR6zhyZD+axm5EV4ud8EgzvS/epRxsar4GVH4FcHQzanuJ8qvILMZeNDr5qc5HONgk0pu6+TTKbRmAphbHkGjpAKt+KwGvmuweIsrXOE5gXxGReZWh2BsQqqb3hZ/cgPa6rWiTYXpfom8LfYCqjEzv40wAIlMbU1nmWouIyGT8tfsiSm4ZqA9IaW1h1ftvBqSIiIiIyKxYaDVoULqIusV29seGM73x4cFzKHR5Fbpqt6G69iJsAtYDAesRby2r970Mq+qv6WcGaDTGbj4RMVOK0/co/1l+6Aosl7+D9hZ7kaSxhmXvJUDJpsZuFhGRSWCmFPuKiMzfnah4rD4ejP0H9qLi7dXoarED7pq7qfujCpaFfe0+0MrqfQWKGrWtRHkVp+9ls2OI8qINp4IRtfAtdLHYgSSNJSx6zoemTBtjN4uIyGRwnMC+IqK8JeB2FFYcCcK1Q2vRNGYdWmsPweb+9L5kjQWifZrDsU4faMq05fQ+ohzEoFQ2O4Yor9l94TYC576DHtpNSIYFNK/MgbZCR2M3i4jIpHCcwL4iorxJSikfDgzHfwfOAKeW4oXkLaimvZi6P9aqIJIqvgTHOn0BjypGbStRXsCgVDY7higvOXI1DCdnvYfemrVIgRa6LtNh4f+ysZtFRGRyOE5gXxFR3peQlILt529j977dcL/8DzppdsBNE566/65jWViUaQnHkrWhKVYDcPZiDSqip8RC50SknAuOxJHZQ/CGZq16nNzhV1gxIEVERERE+ZS1pRYtK7ihZYUuiIxrj3XHruHSvn9R6fa/aKU9iEL3zgGH5DZJHR9t5YLoIv6wK1ELBUrWgaZYdcDexdgfgyhP0OgkjzEf4RVQyk+u3InGuslD8U7KIvU4vs2PsKn3lrGbRURksjhOYF8RUf51IzwW6w6eQeTRFSgacRKVNRdRThMEK03yQ8eG23oh3tUfDiXroIBvbf2Kftb2xmg2kUliphRRPhccEYs1Uz/Be/cDUrHNR8GOASkiIiIiokx5FrTD6y2rAy2rIz4pGWeD72FJ4C2EXToEi+DDcI86gyqaSyilDUbBuGtAoNxWA1uBZGgR5lAaSe5V4VSqLhx8awGuFQALS/Y20WPwJ4QoDwqNisfSyV/g/aS56nFUw89QoPEHxm4WEREREZFZsLG0gL93QXVDg7IAeiE2IRmngyMx/3IgIgIOwPrWEXjFnEVV7UVVk6po9HngktwWq9dI0Ngg1Kk8dB7VULBMXdiXqA0U8mV9KqI0GJQiymMi4xIxf8o3+CB+hv5x7WFwavmJsZtFRERERGTW7KwtUKN4IXVDU3+1LSo+CaeuR2DTpQuIvrwf9rePwSfuLPy1AXBCDDwijgJyOztbHR+tdUJYwUrQelVH4TL1YFu8FuDoZuRPRmQ8DEoR5SFy9ebPKWPxftQkQAPcrfouCrX7n7GbRURERESUJxWwsUSdkoXVDairtkXEJuLEtbsIvHAC8VcPwOHOcZRKPIeKmqtwSImEQ9huQG7Hf1PH37V0RYRLFVh614Brufqw9q4O2HKleMofGJTKaSnJgNYix1+WKCtL286ePh7vho+HVqNDaMV+KNxpDNODiYiIiIhykbOdFRr4uaKBXwsAcgPCohOwL/A2gs8fQmLQITiHHYdf0gWU0VxDoaQQFArZCMjtEJACDW7b+CCqsD9sS9REUQlUeVYBLG14HinPYVAqpy1/F0hOBJp+ChSVucdEz19yig6zZ/2Gt2+PgYVGh9t+3VG0208MSBERERERmQAXB2s0Ll8MkBs6qm0hkXHYfuU6Qs7vh+76YbiEn0C55Ivw1t6GW/xVuN24CtxYCewGEmGJW3Z+iHX1h71vbZVRZeVaFtBqjf3RiLJFo9PpdMhHnutSz5E3gJ8qATpZMlQDVH4JaPIJUMQvZ9+HKA35EZ79x+947fKnsNYk41aJTnDrM5sZe0REpjZOyGPYV0REOT+uvxkZh7MXAxB2YQ80N47ANfIUyusuorDm3kPHx2jscNOhPBLdqsLWszycPfzg7FESGmcvfhcgsxknMCiVw+YuW4UG12agZOjW+z2sBSq/DDT+GChSOqffjvI5+cM1b+FcvHR2GGw1iQgu1hYeb8zj0rNERM+IgRb2FRGRqY33r4XF4ML504i8tAeWN4/C495plEcA7DXxmT4nCRYIsyiKe3bFkFDAG5pCPrB1LQlnj9Io6FkKmgLuzLCi5y7PB6UmT56MH374AcHBwahYsSJ+/vlnNGrUyKiDzYiYRNQdswmxicnwt7yK0QX/RaWoXQ+CU1W6A40/AgqXytH3pfzrn2VL0O7o++oP0nW3Zij29hLAwsrYzSIiMlsMSrGviIhMXUqKDlduR+DK2SOIDtgH69snUDA2CK7Jt+CpuQMbTdJjn58AK4RauuGenScSHL2hLVQctkVLqoBVIU8/aByKsAwIZVueDkotWrQIvXv3VoGpBg0aYNq0aZgxYwZOnz4NHx8fow0245OS8e+xYPyx5wqOX4tQ2yprAjDScQVqJhzQH6SxAPx7Ao2HAy6+Ofr+lL/8u2Ylmux7G46aWFwrXB9e7y5n8UMiomxiUIp9RURkzgsfBYdHI+T6FUTevIT425ehCb8Km+hrcI4LhmvKLXggFJaalMe+TixsEWrlroJWiSpoVQJ2rr4o5FkahYqVhsauUK59JjJfeTooVadOHVSvXh1TpkxJ3Va+fHl07twZY8aMMfpgU7r0SFA4/th9BWtOBCMxWQd/zUV8bLsMDXRH9AdpLe8Hpz4CChV/Lu2gvGvj5g2ota0PnDUxCHKqAe+B/wLW9sZuFhGR2WNQin1FRJSXg1Y3w+7h9o0ARAYHIOFOADQRgbCNugbn+BtwTQmBG+6qlbwfJwoOKmgVZV9MBa0sXErA3tUXBYuVhotnaWhsHHPtM5HpyrNBqYSEBNjb22PJkiXo0qVL6vbBgwfj6NGj2LZtm0kNNkPuxWHBviDM23cVIffiUU1zAUOt/kFj7XG1X6e1hKbaa0Cj4UBB7+feHjJ/O3ftQPn1PVWxw0CHyvAetJa/+ImIcgiDUuwrIqL8HbSKwJ1rF3Hv5iUk3LkMbUQQbCXTKv4G3FNuoYgm8omvEw4nhFp7INrOE0lOPrBwKQ5715JwKeaHQp6loLW2y5XPQ+YxprKEmblz5w6Sk5Ph5uaWbrs8vnnz5kPHx8fHq1vajslNro62GNzSD+82LYX/Tt3EH7sLoc9VP1TXnMdQy7/RCCeBQ3OgOzIPmuq9gUYfArJaAlEmDh46gDLrX1MBqSDbcvB6/18GpIiIiIiIKNusLbXwcS0EH9daAOT2cNAq6E4Y7ly7gCgJWoVdgTY8EPYxErQKVkGrgppoFEQkCiZEAgnnAKlqE5T+de5oCiHMygMx9sWQ5OABTYEisHQsChtnN9gVdIOjizuci3jAwsaBZzUfMLuglIFGo0n3WBK+Mm4TMp3v66+/hin8gHf091S3k9cjMGe3F/ofK4cq8acx1PIfNMAp4OAs6I78BU31vkCjYYCTp7GbTSbkxMnjKLayO1w14bhmXRIeA9dAa1/Q2M0iIiIiIqJ8QL7TersXUTeg3kP7E5NTcC0kRB+0uhWAxNDLsIgIhF30dRRK0AetCmjiUER3F0US7gIJpyWt6pFiYYMIjTOiLJwRa+2CBBsXpNgWhs6hMCwLFIW1s6s+iFXYHU6FPWBr78QC7WYoz0/fyyxTytvbO9em7z1OWHQCFh4IxF97rsI78giGWv2Nutozal+K1hqamv2gaSjBKQ+jtpOM7/z5s3CY3x7FcBvXLX1Q5IMNsHF2N3aziIjyHE7fY18REdHzkZiUjJBbwbhz/Tyib15GUuhlaKNvwjIuDLYJd+GQFA7HlAgU0kXCRpP41K8fp7NChNYZ9ywKItayIOJtXJBsVxg6+yKwKFAEVo6usCvkigKF9EGsAk6FoNFqn8tnJeTdmlKGQuc1atRQq+8ZVKhQAZ06dTKJQudPKyk5BRvP3MKc3VegubIDQyz/QR3tWf0+rQ1Qox8sG38IOKafskj5Q+DVAOhmv4DiCEawhScKvrcedoVZf4yI6HkwxXGCqWJfERHR85CUlIzw8LuIDA1G1N2biI8IQWJkCFKi70ATEwrL2DuwSbgLewliJYejoC4SdpqEp36fBJ0lwjVOKogVI0Esaxck2bogxb4wtAWKqiCWTUFDEMsdzoWKwsKCQaysytNBqUWLFqF3796YOnUq6tWrh+nTp+P333/HqVOnULx4cbMeQJ29GYk/dl1B8NH/8L5mCWppz6vtiRobxFXtB8cWw4ECrsZuJuWSmzeCEPt7O/jqgnBL6wq7d9bDyc2X/U9E9JyY+jjBlLCviIjIFEhIIzIyApGhNxEVdgOx4fogVnLUHSD6DizjQmGTEAa7xHAUSA6Hc0oEHDQPZlNlVaLOAuEaR9zTOiPKshDirQshydoZKdaO0Nk4QmPjBAs7uRWElYMzrB2cYedYCHaOBeHgWAgOdvbQah8uOZRX5emglJAsqXHjxiE4OBiVKlXCTz/9hMaNG+eZAVRETCIWHwjEmd0r8FrsPFTXXlTb4zU2uF2uN4q9+Ck0BYoau5n0HIXeuYWwyW3gl3IZtzWFYdF/LVy8yrLPiYieI3MZJ5gC9hUREZmr2OgoRIQG417YTcTevYkECWLduw1dTCgsYkNhFR8G+8QwFEiKgJMuAgUQm+33lOmF0bBHtNYecRoHxFk4IMHSAUmWjki2KoAUG0forJ2gUYEtJ1imBrcKwr5AQdg5FYJDAWc42NqYRXArzwel8ssAKjlFh61nb+HQ5r/ROmQWqmovqe2xsMUl354o0XEEChTitL68JiI8DDd/bY2yyRcQioJI6vMv3EpWNnaziIjyPHMbJxgT+4qIiPKLxPgYRKhMrFuIliBWxC0kSRArLhKa+EhoE+7BIvEerBKjYZ0cBZvkaNjr5BYDezx9VtbjROlsVXArRmuPWK0D4lVwqwCSLAsg2UqftSU3ra0Et5xhaecMK4eCsCngDLsChWDvVBAODk5wsLF6rsEtBqWy2TGm6OKte9i7bgGqXpqCSpoAtS1WZ40IjXl9DnoyO8TCGdEIhyPu9VgO73I12W1ERLnAnMcJuY19RURE9GS65ETER0ci5t5ddYuPCkdCdDgSYyKQFBOBlLhIIF6CW/egTYiERWIUrJPkFg2blGjYy02tRfj0xd8fJUmnRRTsVHAruP7XqNnmVaONEyxz/J3puSnt5ojSfd7Gvdh+2LhuPoofnwi/lADY4Q57PQ8KRwGEdV2EkgxIERERERERmSWNhRVsnQqrm0s2XkeXGIf46AjE3AtD7L1wFdyKjwlHUnQEkmMNwa17qZlblolRsJLgVnI07FLkFgMHRMMCOlhqUlAQ0eoWojHu5DkGpcyQo501Wnbuh5QOfXD53GEkJWR/fiuZHo+SlVDSqZCxm0FERERERERGprGyhW1BuWWjfI9OB11CNOKjw1VgK/beXfh5lYMxMShlxrQWWvhW4LQuIiIiIiIiInoCjQYamwKwlZuLF0whBUJr7AYQEREREREREVH+w6AUERERERERERHlOgaliIiIiPKAyZMnw9fXF7a2tqhRowZ27Njx2OO3bdumjpPjS5YsialTp+ZaW4mIiIgEg1JEREREZm7RokUYMmQIPv/8cxw5cgSNGjVCu3btEBgYmOnxly9fxgsvvKCOk+M/++wzDBo0CP/880+ut52IiIjyL41OpzPu+n+5LDIyEs7OzoiIiICTk5Oxm0NEREQmxFzHCXXq1EH16tUxZcqU1G3ly5dH586dMWbMmIeO/+STT7By5UqcOXMmdduAAQNw7Ngx7NmzJ0/3FRERET1/WR0nMFOKiIiIyIwlJCTg0KFDaN26dbrt8nj37t2ZPkcCTxmPb9OmDQ4ePIjExMRMnxMfH68GmGlvRERERNlhiXzGkBjGgRQRERFlZBgfmFMi+Z07d5CcnAw3N7d02+XxzZs3M32ObM/s+KSkJPV6Hh4eDz1HMq6+/vrrh7ZzTEVERETPOqbKd0Gpe/fuqX+9vb2N3RQiIiIy4fGCpJybE41Gk+6xDAIzbnvS8ZltNxgxYgSGDRuW+vj69euoUKECx1RERET0zGOqfBeU8vT0RFBQEBwdHR87UMsvkUsJzkl/sBaE6eP5Mi88X+aF58t8PO9zJYEZGTzJeMFcFClSBBYWFg9lRYWEhDyUDWXg7u6e6fGWlpYoXLhwps+xsbFRN4MCBQpwTHUff4eYF54v88LzZV54vsxHpImMqfJdUEqr1cLLy8vYzTAp8h+QQSnzwfNlXni+zAvPl/l4nufK3DKkrK2tUaNGDWzYsAFdunRJ3S6PO3XqlOlz6tWrh1WrVqXbtn79etSsWRNWVlZZel+OqR7G3yHmhefLvPB8mReeL/PhZOQxFQudExEREZk5mVY3Y8YMzJo1S62oN3ToUAQGBqoV9QxT7/r06ZN6vGy/evWqep4cL8+bOXMmhg8fbsRPQURERPlNvsuUIiIiIsprunfvjtDQUHzzzTcIDg5GpUqVsGbNGhQvXlztl20SpDLw9fVV+yV4NWnSJJVa/8svv6Bbt25G/BRERESU3zAolY9JXYiRI0emqw9Bpovny7zwfJkXni/zwXP1aO+99566ZWbOnDkPbWvSpAkOHz6cg2cn/+L/S/PC82VeeL7MC8+X+bAxkXiARmdOax4TEREREREREVGewJpSRERERERERESU6xiUIiIiIiIiIiKiXMegFBERERERERER5ToGpfKhr776ChqNJt3N3d3d2M2i+7Zv344OHTqolZDk3Cxfvjxd30gZODmHst/Ozg5NmzbFqVOn2H8meK769ev30M9a3bp1ea6MZMyYMahVqxYcHR3h6uqKzp0749y5c+mO4c+X+Zwr/nyRKeCYyrRxTGU+OKYyLxxTmY8xZjCmYlAqn6pYsaJaHtpwO3HihLGbRPdFR0fD398fv/32W6Z9Mm7cOEyYMEHtP3DggAootmrVCvfu3WMfmti5Em3btk33syZLsJNxbNu2De+//z727t2LDRs2ICkpCa1bt1bn0YA/X+ZzrgR/vsgUcExlujimMh8cU5kXjqnMxzZzGFPJ6nuUv4wcOVLn7+9v7GZQFsiP6LJly1Ifp6Sk6Nzd3XVjx45N3RYXF6dzdnbWTZ06lX1qQudK9O3bV9epUyejtYkeLyQkRJ23bdu2qcf8+TKfcyX480WmgGMq88ExlfngmMr8cExlPkJMcEzFTKl86sKFC2rKka+vL3r06IGAgABjN4my4PLly7h586aKbhvY2NigSZMm2L17N/vQBG3dulWlypYpUwZvvfUWQkJCjN0kui8iIkL96+Liov7lz5f5nCsD/nyRKeCYyjzxd7754e9808UxlfmIMMExFYNS+VCdOnXw559/Yt26dfj9999VkKN+/foIDQ01dtPoCeRcCTc3t3Tb5bFhH5mOdu3aYd68edi8eTPGjx+vpls2b94c8fHxxm5avicXYocNG4aGDRuiUqVKqj/482U+50rw54tMAcdU5ou/880Lf+ebLo6pzIfORMdUlrnyLmRS5D+dQeXKlVGvXj2UKlUKf/zxh/pPSqZPis9l/AWTcRsZX/fu3VPvyy/+mjVronjx4li9ejW6du1q1LbldwMHDsTx48exc+fOh/bx58s8zhV/vsgUcExl/vg73zzwd77p4pjKfAw00TEVM6UIDg4OKjgl6edk2gyrJGbMipL0yozZU2R6PDw81C94/qwZ1wcffICVK1diy5Yt8PLySt3Ony/zOVeZ4c8XmQKOqcwHf+ebN/7ONw0cU5mPD0x4TMWgFKm0vDNnzqj/fGTapAaYDKJk5QSDhIQEtaqCTMEk0yZTZIOCgvizZiSSUShXiJYuXarSk+XnKS3+fJnPucoMf77IFHBMZT74O9+88Xe+cXFMZT50ZjCm4vS9fGj48OHo0KEDfHx8VIbNqFGjEBkZib59+xq7aQQgKioKFy9eTFeI8+jRo6oYnZyzIUOG4LvvvoOfn5+6yX17e3v06tWL/WdC50puX331Fbp166Z+oV+5cgWfffYZihQpgi5duvBcGYEshzt//nysWLECjo6OqRmHzs7OsLOzU1M4+PNlHudKfvb480WmgGMq08YxlfngmMq8cExlPt43hzGV0db9I6Pp3r27zsPDQ2dlZaXz9PTUde3aVXfq1CmeEROxZcsWtUxnxpss1WlYtl6WoHZ3d9fZ2NjoGjdurDtx4oSxm50vPe5cxcTE6Fq3bq0rWrSo+lnz8fFR2wMDA43d7Hwrs3Mlt9mzZ6cew58v8zhX/PkiU8ExlWnjmMp8cExlXjimMh8wgzGV5n5DiYiIiIiIiIiIcg1rShERERERERERUa5jUIqIiIiIiIiIiHIdg1JERERERERERJTrGJQiIiIiIiIiIqJcx6AUERERERERERHlOgaliIiIiIiIiIgo1zEoRUREREREREREuY5BKSIiIiIiIiIiynUMShFRjti6dSs0Gg3Cw8Oz9Tr9+vVD586dzfasNG3aFEOGDHnicY0bN8b8+fORm1566SVMmDAhV9+TiIiIso7jKT2Op4jyDwaliCidqVOnwtHREUlJSanboqKiYGVlhUaNGqU7dseOHSoQdf78edSvXx/BwcFwdnZ+7j06bdo0+Pv7w8HBAQULFkS1atXw/fffm82Z/Pfff3Hz5k306NEjR15vzpw5qFu37hOP+9///ofRo0cjMjIyR96XiIiIMsfx1PPH8RRR3sCgFBGl06xZMxWEOnjwYLrgk7u7Ow4cOICYmJh0V/M8PT1RpkwZWFtbq2MkSPU8zZw5E8OGDcOgQYNw7Ngx7Nq1Cx9//LFqs7n45Zdf8Prrr0OrzZlfwStXrkSnTp2eeFyVKlVQokQJzJs3L0fel4iIiDLH8dTzx/EUUd7AoBQRpVO2bFkVaJKAk4Hcl6BHqVKlsHv37nTbZdCV2fQ9yd6RLKZ169ahfPnyKFCgANq2bauyqQySk5NVgEmOK1y4sAou6XS6x56RVatW4ZVXXkH//v1RunRpVKxYET179sS333770BTAr7/+Gq6urnBycsI777yDhISE1GPkfcaNG4eSJUvCzs5OZV79/fff6d7r9OnTeOGFF1Tb3dzc0Lt3b9y5cyd1f3R0NPr06aP2e3h4YPz48U/83yTP37hxIzp27Jhuu/SdZIC1b98e9vb2qs/27NmDixcvqhR2yQqrV68eLl26lO55cXFxWL9+ferrTZ48GX5+frC1tVVtlil7aclxCxYseGI7iYiI6NlxPPUAx1NE9DgMShHRQyQIsmXLltTHcl+2NWnSJHW7BHgkaGIISmVGsqp+/PFHzJ07F9u3b0dgYCCGDx+eul+COLNmzVLZTzt37kRYWBiWLVv22DMi2Vh79+7F1atXH3vcpk2bcObMGdVeCcLI60qQyuCLL77A7NmzMWXKFJw6dQpDhw7Fa6+9hm3btqn9EjyTz1u1alWVNfbff//h1q1bKiBm8NFHH6nXl9eWwJAE5g4dOvTYdsnnNASdMpLAmgS5jh49inLlyqFXr14qmDZixIjUzLWBAwc+9DmlTyQ4J8dIBtk333yDc+fOqTZL7aq0ateujf379yM+Pv6x7SQiIqLs4XiK4ykiygIdEVEG06dP1zk4OOgSExN1kZGROktLS92tW7d0Cxcu1NWvX18ds23bNklp0l26dEk93rJli3p89+5d9Xj27Nnq8cWLF1Nfd9KkSTo3N7fUxx4eHrqxY8emPpb38/Ly0nXq1OmR5+TGjRu6unXrqtcuU6aMrm/fvrpFixbpkpOTU4+RbS4uLrro6OjUbVOmTNEVKFBAHRcVFaWztbXV7d69O91r9+/fX9ezZ091/8svv9S1bt063f6goCD1vufOndPdu3dPZ21trfrEIDQ0VGdnZ6cbPHjwI9v/008/6UqWLPnQdnndL774IvXxnj171LaZM2embluwYIFqd1pvvfWWbtiwYer+P//8o3NyclLn7FGOHTumXvfKlSuPPIaIiIiyj+MpjqeI6MkssxK4IqL8RbKfZGqa1JC6e/euqhkl0+Akc0imsMk+yQry8fFR098eRTKCZMqfgUxxCwkJUfcjIiJUNpJMSTOwtLREzZo1HzuFT15DMrROnjypsppkOmHfvn0xY8YMlRlkqNMk0/Hk/Q3kfaTuVFBQkGqDTHtr1apVuteW7C8pmi4k40myoGRqXkYyhS42NlYdn7b9Li4uKl3/ceR5MrXuUTWfDGTqnahcuXK6bdJuKVQuUxKln2Q648KFC9V++TzFixdX50SmSsqtS5cu6fpBpiqKtLXBiIiIKOdxPMXxFBE9GYNSRPQQqdXk5eWlgjISlJJglJBpYr6+vqq4uOxr3rz5Y3tPVuzLWDfpSTWjsqpSpUrq9v7776spcbIyoASpHjed0NCGlJQUdX/16tUoVqxYuv02NjbqXzmmQ4cOma7qJ4GxCxcuPFO7ixQpovr0Sf1lKBif2TZD+2UangTGGjZsqB7LqomHDx9WAUOZTiir7X311VcquCh1u4RMkRRFixZ9pvYTERFR1nA8xfEUET0Za0oRUaYkuCPBDblJTQQDCVBJ8XKp6/SkANDjODs7q+COvI5BUlLSE2syZaZChQrqX8ngMpCV+SQryUDeR7KeJNgmx0vwSWpcyYAx7c3b21sdX716dVVrSlary3iMFB2XfyVglLb9Emw6f/78Y9sqmVg3b958ZGDqaaxYsQIvvvgiLCws0mWbtWzZUhVxP378OK5cuYLNmzen7pcMM+kDCY4RERHR88XxFMdTRPR4zJQiokcOoiQLKTExMTVTSsj9d999V00jy05QSgwePBhjx45Vq8VJ4e8JEyakrt73KPLesjqgZGlJcEWmAI4aNUpl/qSdSicZRLJCnxQ0l6LoI0eOVEXCZXqfZBRJwXUpbi5ZR5JpJFPiZCqgBK5kOqB89t9//12t7CcFzSWIIyvhyVQ52S7HyevLPlk5UKbWff7556nTBx8XlJK2SraZrLSXHStXrkxXvP3ff/9FQECAKm5eqFAhrFmzRn2+tFMKd+zYgdatW2frfYmIiChrOJ7ieIqIHo9BKSJ65CBKMo1kFThDfSNDUOrevXuqVpQhq+hZffjhhyqo1K9fPxXMeeONN1QNJKk39SiSBSQr9smqeaGhoSpYJMEoWYVOgkMGLVq0UMEuCdDISnM9evRQU9nSrnQndbLGjBmjAjkyvU2yoz777DO1XwJfEjj65JNP0KZNG/UaUq9J6jQZAk8//PCDqlPVsWNHFeiSz/O4tgvJapLPOW/evGwFpaSulQTJpG0G8hmWLl2qPqcEDeXzy8qDsjKfkG2yUqBkuhEREdHzx/EUx1NE9HgaqXb+hGOIiMyKBLkk42r58uUwRbdu3VKBIpmqKIGuZyFZZRs3blTZUFk1adIkNeVP6k0RERERPQ7HUxxPEeUG1pQiIsplknk2c+ZMVdPqWcnUxREjRjzVc6QG1q+//vrM70lERERkKjieIsobmClFRHmOqV/ZIyIiIjJ1HE8RUW5gUIqIiIiIiIiIiHIdp+8REREREREREVGuY1CKiIiIiIiIiIhyHYNSRERERERERESU6xiUIiIiIiIiIiKiXMegFBERERERERER5ToGpYiIiIiIiIiIKNcxKEVERERERERERLmOQSkiIiIiIiIiIsp1DEoRERERERERERFy2/8By1NXViOrXdEAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1200x1000 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "baseline_turb = pd.read_csv(os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder,\"outputs_nonOpti/stage-1-aeroStruct-NonOptimized.csv\"), index_col=0)\n",
+    "optimized_turb = pd.read_csv(os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder,\"outputs_preCompute/stage-1-aeroStruct-aero_analysis.csv\"), index_col=0)\n",
+    "\n",
+    "plot_rotor_comparison(baseline_turb, optimized_turb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1a942b53",
+   "metadata": {},
+   "source": [
+    "## Important Considerations\n",
+    "\n",
+    "### Modeling Limitations\n",
+    "- As discussed earlier, this optimization uses CCBlade for aerodynamic analysis, which assumes rigid blades. The performance numbers show correct trends but may not be consistent with models at higher levels of fidelity.\n",
+    "- For more precise performance predictions, you would need to use WEIS with OpenFAST+BeamDyn, which captures blade flexibility but is computationally expensive.\n",
+    "\n",
+    "### Optimization Convergence\n",
+    "The optimization successfully converged in 44 iterations. We can examine the optimization history using the `log_opt.sql` file, which logs all design variables and constraints throughout the process.\n",
+    "\n",
+    "## 1.2 Plot Optimization Convergence"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "d43d648b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "loading /Users/dzalkind/Tools/WEIS-Eni/examples/09_model_creation_process/0_notebooks/../1_drivers/stage-1-aeroStruct/outputs_preCompute/log_opt.sql\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x4200 with 7 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "rec_data = load_OMsql(os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder,\"outputs_preCompute/log_opt.sql\")) # not sure what supresses the output here\n",
+    "plot_convergence(rec_data, ['financese.lcoe', 'tcons.tip_deflection_ratio', 'blade.opt_var.af_position', 'blade.opt_var.chord_opt', 'blade.pa.max_chord_constr',\n",
+    "                            'rotorse.rs.constr.constr_max_strainL_spar', 'rotorse.rs.constr.constr_max_strainU_spar'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "13dc2d7b",
+   "metadata": {},
+   "source": [
+    "# Chapter 1 Complete: Your Optimized 20MW Rotor\n",
+    "\n",
+    "## What We Accomplished\n",
+    "\n",
+    "Congratulations! You've successfully completed the first stage of wind turbine design optimization. Here's what we achieved in this session:\n",
+    "\n",
+    "- **Baseline Analysis**: Started with the IEA 22MW floating wind turbine and established a performance baseline\n",
+    "- **Input File Understanding**: Explored the WEIS/WISDEM input file structure and configuration options\n",
+    "- **Performance Assessment**: Analyzed the baseline turbine and visualized key performance metrics from the CSV output\n",
+    "- **Turbine Scaling**: Modified the IEA 22MW design to create a 20MW turbine by adjusting rotor diameter and rated power\n",
+    "- **Rotor Optimization**: Used WISDEM to optimize chord distribution, structural properties, and airfoil positioning\n",
+    "- **Convergence Analysis**: Examined the optimization history using log_opt.sql and plotted convergence behavior\n",
+    "- **Design Comparison**: Evaluated the performance improvements between unoptimized and optimized 20MW rotors\n",
+    "\n",
+    "<!-- You now have a solid foundation in WEIS optimization workflows and are ready to proceed to controller tuning and platform design in the next chapters! -->"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "weis-eni",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/09_model_creation_process/0_notebooks/weis_workshop.py b/examples/09_model_creation_process/0_notebooks/weis_workshop.py
new file mode 100644
index 000000000..07af50e87
--- /dev/null
+++ b/examples/09_model_creation_process/0_notebooks/weis_workshop.py
@@ -0,0 +1,216 @@
+# Simple Colab detection
+import sys
+import numpy as np
+import matplotlib.pyplot as plt
+import openmdao.api as om
+
+
+# TODO:
+# 1. Add structural plots for the blade!
+
+# Global variable to check if we're in Google Colab
+IN_COLAB = 'google.colab' in sys.modules
+
+if IN_COLAB:
+    print("Running in Google Colab")
+else:
+    print("Running in local environment")
+
+def plotter(x,y, xlabel=None, ylabel=None, title=None, ax=None, label=None):
+    if ax is None:
+        return None
+
+    ax.plot(np.array(eval(x)), np.array(eval(y)), label=label)
+    ax.set_xlabel(xlabel)
+    ax.set_ylabel(ylabel)
+    ax.set_title(title)
+    if label:
+        ax.legend()
+    return ax
+
+# This function loads the openmdao sql file and does most of the work here
+def load_OMsql(log):
+    print('loading {}'.format(log))
+    cr = om.CaseReader(log)
+    rec_data = {}
+    cases = cr.get_cases('driver')
+    for case in cases:
+        for key in case.outputs.keys():
+            if key not in rec_data:
+                rec_data[key] = []
+            rec_data[key].append(case[key])
+        
+    return rec_data
+
+def plot_convergence(logs, vars):
+
+    # create the figure
+    fig, ax = plt.subplots(nrows=len(vars), figsize=(10, 6*len(vars)))
+
+    for var in vars:
+
+        # start by squeezing the data
+        data = np.squeeze(logs[var])
+
+        ax[vars.index(var)].plot(data, marker='o')
+        ax[vars.index(var)].set_title(var)
+        ax[vars.index(var)].grid(True)
+        ax[vars.index(var)].set_xlabel('Iteration')
+        # ax[vars.index(var)].set_ylabel(var)
+
+    return None
+
+
+
+def plot_comparison_plot(turb_csv, label, fig = None):
+
+    if fig is None:
+        fig,ax = plt.subplots(2, 3, figsize=(10, 10), sharex=True)
+        fig.suptitle("Turbine Performance Curves", fontsize=16)
+
+    ax[0, 0] = plotter(turb_csv.loc['rotorse.rp.powercurve.V']['values'],
+                       turb_csv.loc['rotorse.rp.powercurve.Cp_aero']['values'],
+                      ylabel='Cp',
+                      title='Power Coefficient (Cp)', ax=ax[0, 0], label = label)
+    ax[0, 0].grid(True)
+    
+    ax[0, 1] = plotter(turb_csv.loc['rotorse.rp.powercurve.V']['values'],
+                       turb_csv.loc['rotorse.rp.powercurve.Ct_aero']['values'],
+                      ylabel='Ct',
+                      title='Thrust Coefficient (Ct)', ax=ax[0, 1], label = label)
+    ax[0, 1].grid(True)
+    
+    ax[1, 0] = plotter(turb_csv.loc['rotorse.rp.powercurve.V']['values'],
+                         turb_csv.loc['rotorse.rp.powercurve.P']['values'],
+                        ylabel='Power (kW)',
+                        title='Turbine Power Output', ax=ax[1, 0], label = label)
+    ax[1, 0].grid(True)
+    
+    ax[1, 1] = plotter(turb_csv.loc['rotorse.rp.powercurve.V']['values'],
+                         turb_csv.loc['rotorse.rp.powercurve.T']['values'],
+                        xlabel='Wind Speed (m/s)', ylabel='Thrust (kN)',
+                        title='Turbine Thrust Output', ax=ax[1, 1], label = label)
+    ax[1, 1].grid(True)
+    
+    ax[0, 2] = plotter(turb_csv.loc['rotorse.rp.powercurve.V']['values'],
+                         turb_csv.loc['rotorse.rp.powercurve.pitch']['values'],
+                        xlabel='Wind Speed (m/s)', ylabel='Pitch (deg)',
+                        title='Turbine Pitch Angle', ax=ax[0, 2], label = label)
+    ax[0, 2].grid(True)
+    
+    ax[1, 2] = plotter(turb_csv.loc['rotorse.rp.powercurve.V']['values'],
+                         turb_csv.loc['rotorse.rp.powercurve.Omega']['values'],
+                        xlabel='Wind Speed (m/s)', ylabel='Rotor Speed (rpm)',
+                        title='Turbine Rotor Speed', ax=ax[1, 2], label = label)
+    ax[1, 2].grid(True)
+
+
+def plot_rotor_comparison(baseline_turb, optimized_turb):
+
+    def plotter(x,y, xlabel, ylabel, title, ax=None, label=None):
+        if ax is None:
+            return None
+
+        ax.plot(np.array(eval(x)), np.array(eval(y)), label=label)
+        ax.set_xlabel(xlabel)
+        ax.set_ylabel(ylabel)
+        ax.set_title(title)
+        if label:
+            ax.legend()
+        return ax
+    
+
+    # Creating Cp, Ct, power, thrust, pitch, induction vs WS
+    fig,ax = plt.subplots(3, 2, figsize=(12, 10),)
+    fig.suptitle("Turbine Performance Curves", fontsize=16)
+
+    ax[0, 0] = plotter(optimized_turb.loc['rotorse.rp.powercurve.V']['values'],
+                    optimized_turb.loc['rotorse.rp.powercurve.Cp_aero']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Cp',
+                    title='Power Coefficient (Cp)', ax=ax[0, 0], label = 'Optimized')
+
+    ax[0, 0] = plotter(baseline_turb.loc['rotorse.rp.powercurve.V']['values'],
+                    baseline_turb.loc['rotorse.rp.powercurve.Cp_aero']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Cp',
+                    title='Power Coefficient (Cp)', ax=ax[0, 0], label = 'Baseline')
+
+    ax[0, 1] = plotter(optimized_turb.loc['rotorse.rp.powercurve.V']['values'],
+                    optimized_turb.loc['rotorse.rp.powercurve.Ct_aero']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Ct',
+                    title='Thrust Coefficient (Ct)', ax=ax[0, 1], label = 'Optimized')
+
+    ax[0, 1] = plotter(baseline_turb.loc['rotorse.rp.powercurve.V']['values'],
+                    baseline_turb.loc['rotorse.rp.powercurve.Ct_aero']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Ct',
+                    title='Thrust Coefficient (Ct)', ax=ax[0, 1], label = 'Baseline')
+
+    ax[1, 0] = plotter(optimized_turb.loc['rotorse.rp.powercurve.V']['values'],
+                        optimized_turb.loc['rotorse.rp.powercurve.P']['values'],
+                        xlabel='Wind Speed (m/s)', ylabel='Power (kW)',
+                        title='Turbine Power Output', ax=ax[1, 0], label = 'Optimized')
+
+    ax[1, 0] = plotter(baseline_turb.loc['rotorse.rp.powercurve.V']['values'],
+                        baseline_turb.loc['rotorse.rp.powercurve.P']['values'],
+                        xlabel='Wind Speed (m/s)', ylabel='Power (kW)',
+                        title='Turbine Power Output', ax=ax[1, 0], label = 'Baseline')
+
+    ax[1, 1] = plotter(optimized_turb.loc['rotorse.rp.powercurve.V']['values'],
+                        optimized_turb.loc['rotorse.rp.powercurve.T']['values'],
+                        xlabel='Wind Speed (m/s)', ylabel='Thrust (kN)',
+                        title='Turbine Thrust Output', ax=ax[1, 1], label = 'Optimized')
+
+    ax[1, 1] = plotter(baseline_turb.loc['rotorse.rp.powercurve.V']['values'],
+                    baseline_turb.loc['rotorse.rp.powercurve.T']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Thrust (kN)',
+                    title='Turbine Thrust Output', ax=ax[1, 1], label = 'Baseline')
+
+    ax[2, 0] = plotter(optimized_turb.loc['rotorse.rp.powercurve.V']['values'],
+                        optimized_turb.loc['rotorse.rp.powercurve.pitch']['values'],
+                        xlabel='Wind Speed (m/s)', ylabel='Pitch Angle (deg)',
+                        title='Turbine Pitch Angle', ax=ax[2, 0], label = 'Optimized')
+
+    ax[2, 0] = plotter(baseline_turb.loc['rotorse.rp.powercurve.V']['values'],
+                    baseline_turb.loc['rotorse.rp.powercurve.pitch']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Pitch Angle (deg)',
+                    title='Turbine Pitch Angle', ax=ax[2, 0], label = 'Baseline')
+
+    ax[2, 1] = plotter(optimized_turb.loc['rotorse.rp.powercurve.V']['values'],
+                        optimized_turb.loc['rotorse.rp.powercurve.ax_induct_rotor']['values'],
+                        xlabel='Wind Speed (m/s)', ylabel='Induction Factor',
+                        title='Turbine Induction Factor', ax=ax[2, 1], label = 'Optimized')
+
+    ax[2, 1] = plotter(baseline_turb.loc['rotorse.rp.powercurve.V']['values'],
+                    baseline_turb.loc['rotorse.rp.powercurve.ax_induct_rotor']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Induction Factor',
+                    title='Turbine Induction Factor', ax=ax[2, 1], label = 'Baseline')
+
+    plt.tight_layout(rect=[0, 0.03, 1, 0.95])
+    # plt.savefig("plots/turbine_performance_curves.png", dpi=300)
+
+
+    # Geomtric plots
+
+    fig,ax = plt.subplots(1, 2, figsize=(12, 5),)
+
+    ax[0] = plotter(baseline_turb.loc['rotorse.r']['values'],
+                    baseline_turb.loc['rotorse.chord']['values'],
+                    xlabel='Span (m)', ylabel='Chord (m)',
+                    title='Blade Chord Distribution', ax=ax[0], label = 'Baseline')
+
+    ax[0] = plotter(optimized_turb.loc['rotorse.r']['values'],
+                    optimized_turb.loc['rotorse.chord']['values'],
+                    xlabel='Span (m)', ylabel='Chord (m)',
+                    title='Blade Chord Distribution', ax=ax[0], label = 'Optimized')
+
+    ax[1] = plotter(baseline_turb.loc['rotorse.r']['values'],
+                    baseline_turb.loc['rotorse.ccblade.theta_in']['values'],
+                    xlabel='Span (m)', ylabel='Twist (deg)',
+                    title='Blade Twist Distribution', ax=ax[1], label = 'Baseline')
+
+    ax[1] = plotter(optimized_turb.loc['rotorse.r']['values'],
+                    optimized_turb.loc['rotorse.ccblade.theta_in']['values'],
+                    xlabel='Span (m)', ylabel='Twist (deg)',
+                    title='Blade Twist Distribution', ax=ax[1], label = 'Optimized')
+
+    plt.tight_layout(rect=[0, 0.03, 1, 0.95])
+    # plt.savefig("plots/blade_geometry.png", dpi=300)
\ No newline at end of file
diff --git a/examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_analysis.yaml b/examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_analysis.yaml
new file mode 100644
index 000000000..a7ec6671f
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_analysis.yaml
@@ -0,0 +1,3 @@
+general:
+    folder_output: outputs/
+    fname_output: stage-0-baseline
diff --git a/examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_driver.py b/examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_driver.py
new file mode 100644
index 000000000..72d4745f7
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_driver.py
@@ -0,0 +1,76 @@
+#!/usr/bin/env python3
+import os
+from weis import weis_main
+
+import numpy as np
+from openfast_io import FileTools
+import pandas as pd
+import matplotlib.pyplot as plt
+
+
+def plotter(x,y, xlabel, ylabel, title, ax=None):
+    if ax is None:
+        return None
+
+    ax.plot(np.array(eval(x)), np.array(eval(y)))
+    ax.set_xlabel(xlabel)
+    ax.set_ylabel(ylabel)
+    ax.set_title(title)
+    return ax
+
+# TEST_RUN will reduce the number and duration of simulations
+TEST_RUN = False
+
+## File management
+run_dir = os.path.dirname( os.path.realpath(__file__) )
+fname_wt_input = os.path.join(run_dir, "..", "..", "..", "00_setup", "ref_turbines", "IEA-22-280-RWT_Floater.yaml")
+fname_modeling_options = os.path.join(run_dir, "stage-0-baseline_modeling.yaml")
+fname_analysis_options = os.path.join(run_dir, "stage-0-baseline_analysis.yaml")
+
+wt_opt, modeling_options, opt_options = weis_main(fname_wt_input, 
+                                                 fname_modeling_options, 
+                                                 fname_analysis_options,
+                                                 test_run=TEST_RUN
+                                                 )
+
+
+weis_turb = pd.read_csv(os.path.join(run_dir,"outputs/stage-0-baseline.csv"), index_col=0)
+
+
+# Creating Cp, Ct, power, thrust, pitch, induction vs WS
+fig,ax = plt.subplots(3, 2, figsize=(12, 10),)
+fig.suptitle("Turbine Performance Curves", fontsize=16)
+
+ax[0, 0] = plotter(weis_turb.loc['rotorse.rp.powercurve.V']['values'],
+                   weis_turb.loc['rotorse.rp.powercurve.Cp_aero']['values'],
+                  xlabel='Wind Speed (m/s)', ylabel='Cp',
+                  title='Power Coefficient (Cp)', ax=ax[0, 0])
+
+ax[0, 1] = plotter(weis_turb.loc['rotorse.rp.powercurve.V']['values'],
+                   weis_turb.loc['rotorse.rp.powercurve.Ct_aero']['values'],
+                  xlabel='Wind Speed (m/s)', ylabel='Ct',
+                  title='Thrust Coefficient (Ct)', ax=ax[0, 1])
+
+
+ax[1, 0] = plotter(weis_turb.loc['rotorse.rp.powercurve.V']['values'],
+                     weis_turb.loc['rotorse.rp.powercurve.P_aero']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Power (kW)',
+                    title='Turbine Power Output', ax=ax[1, 0])
+
+ax[1, 1] = plotter(weis_turb.loc['rotorse.rp.powercurve.V']['values'],
+                     weis_turb.loc['rotorse.rp.powercurve.T']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Thrust (kN)',
+                    title='Turbine Thrust Output', ax=ax[1, 1])
+
+ax[2, 0] = plotter(weis_turb.loc['rotorse.rp.powercurve.V']['values'],
+                     weis_turb.loc['rotorse.rp.powercurve.pitch']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Pitch Angle (deg)',
+                    title='Turbine Pitch Angle', ax=ax[2, 0])
+
+ax[2, 1] = plotter(weis_turb.loc['rotorse.rp.powercurve.V']['values'],
+                     weis_turb.loc['rotorse.rp.powercurve.ax_induct_rotor']['values'],
+                    xlabel='Wind Speed (m/s)', ylabel='Induction Factor',
+                    title='Turbine Induction Factor', ax=ax[2, 1])
+
+plt.tight_layout(rect=[0, 0.03, 1, 0.95])
+plt.savefig(os.path.join(run_dir,"outputs/turbine_performance_curves.png"), dpi=300)
diff --git a/examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_modeling.yaml b/examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_modeling.yaml
new file mode 100644
index 000000000..b1e647d73
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-0-baseline/stage-0-baseline_modeling.yaml
@@ -0,0 +1,91 @@
+General:
+    verbosity: False  # When set to True, the code prints to screen many infos
+Environment:
+    air_density: 1.225
+    air_dyn_viscosity: 1.81e-5
+    weib_shape_parameter: 2.
+    air_speed_sound: 340.
+    shear_exp: 0.12
+    water_density: 1025.0
+    water_dyn_viscosity: 1.3351e-3
+    soil_shear_modulus: 140.e+6
+    soil_poisson: 0.4
+    water_depth: 200.0
+    significant_wave_height: 4.52
+    significant_wave_period: 9.45
+    
+WISDEM:
+    RotorSE:
+        flag: True
+        n_pitch_perf_surfaces: 20
+        n_tsr_perf_surfaces: 20
+        spar_cap_ss: spar_cap_ss
+        spar_cap_ps: spar_cap_ps
+        peak_thrust_shaving: True
+        thrust_shaving_coeff: 0.8
+    TowerSE:
+        flag: True
+        wind: PowerWind  # Wind used
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        buckling_method: dnvgl # Buckling code type [eurocode or dnvgl]
+        buckling_length: 15    # Buckling parameter
+        frame3dd:
+            shear: True
+            geom: True
+            tol: 1e-9
+    DriveSE:
+        flag: True
+    FloatingSE:
+        flag: True
+        symmetric_moorings: True
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        rank_and_file: True
+    BOS:
+        flag: True
+    LCOE:
+        flag: True
+        wake_loss_factor: 0.15
+        fixed_charge_rate: 0.056
+        bos_per_kW: 4053.
+        opex_per_kW: 137.
+        turbine_number: 40.
+        labor_rate: 58.8
+        painting_rate: 30.0
+
+OpenFAST: # Options for WEIS fidelity level 3 = nonlinear time domain
+    flag: False
+
+RAFT:
+    flag: False
+
+
+ROSCO:
+    flag: True
+    tuning_yaml: ../../../03_design_with_openfast/iea22_rosco.yaml
+
+DLC_driver:
+    metocean_conditions:
+        wind_speed: [4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24.]
+        wave_height_NSS: [0.83, 0.88, 0.94, 1.03, 1.16, 1.34, 1.57, 1.86, 2.22, 2.62, 3.07]
+        wave_period_NSS: [6.9, 6.96, 7.02, 7.12, 7.25, 7.43, 7.66, 7.94, 8.27, 8.63, 9.01]
+        wave_height_SSS: [6.3, 8, 8, 8.1, 8.5, 8.5, 9.8, 9.8, 9.8, 9.8, 9.9]
+        wave_period_SSS: [11.5, 12.7, 12.7, 12.8, 13.1, 13.1, 14.1, 14.1, 14.1, 14.1, 14.1]
+        wave_height_1: 6.98
+        wave_period_1: 11.7
+        wave_height_50: 10.68
+        wave_period_50: 14.2
+    DLCs:
+        - DLC: "1.6"
+          n_seeds: 6
+        - DLC: "6.1"
+          n_seeds: 6
+          turbulent_wind:
+            GridWidth: 400
\ No newline at end of file
diff --git a/examples/09_model_creation_process/2_models/new-20-270-RWT_Floater.yaml b/examples/09_model_creation_process/2_models/new-20-270-RWT_Floater.yaml
new file mode 100644
index 000000000..6a9455ad4
--- /dev/null
+++ b/examples/09_model_creation_process/2_models/new-20-270-RWT_Floater.yaml
@@ -0,0 +1,1814 @@
+windIO_version: '2.0'
+name: IEA 22MW Offshore Wind Turbine in Floating Configuration
+assembly:
+    turbine_class: I
+    turbulence_class: B
+    drivetrain: direct_drive
+    rotor_orientation: Upwind
+    number_of_blades: 3
+    hub_height: 170.0
+    rotor_diameter: 270.0
+    rated_power: 20000000.0
+    lifetime: 25.0
+components:
+    blade:
+        reference_axis:
+            x:
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+               -  name: spar_cap_ps
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+                    K56: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
+                    K66: [124474099329.69714, 124238168611.42635, 124476059131.09467, 105238126887.8331, 68203646526.41295, 44791415802.65818, 33125470655.19207, 24851930921.25613, 18865737628.78575, 14211545586.079329, 10841864543.883715, 8561965387.877208, 6495790848.017875, 5419110011.600846, 4782820099.310417, 4088177033.9631906, 3557436141.4052563, 3164017756.1485825, 2852581551.9785123, 2606346025.2442856, 2417151142.2310615, 2292978969.2848616, 2182314154.4338818, 2081703679.89025, 1994107387.9318001, 1912584752.1401513, 1836276020.1705053, 1766615914.9477737, 1698646152.1806736, 1628954322.8358648, 1565715147.5665517, 1497401050.9068756, 1433661667.8997056, 1370938048.5077126, 1308036791.4790716, 1248141375.782687, 1185478280.6925888, 1126760757.5515127, 1068158422.3203462, 1007678100.2338309, 952058529.5818598, 897963519.699582, 845523807.013447, 794299594.6041521, 745543225.0839949, 699169268.3324672, 653978433.7107884, 611144897.6227872, 570763889.8405869, 532024308.91914004, 495633011.50465024, 426481361.9121897, 397380090.6899993, 370349728.41563743, 344793407.56194544, 320850464.73935616, 298831332.2835744, 278224787.05504495, 259077522.9100377, 238958446.5160021, 225006886.75986928, 209894297.81047165, 195980387.804896, 183000724.9962869, 171067425.95617092, 159970403.66653633, 149613638.8915717, 139755991.70893133, 131220769.56519918, 122788460.85161284, 115210077.52695283, 108061166.76128124, 101462705.65685399, 94918953.85431789, 89469163.02019435, 83948009.02885853, 79136162.42823608, 75067051.05931796, 70473365.04585142, 65946240.687910534, 62336260.839875214, 58467649.14031589, 54456347.079159975, 50718981.59686387, 47059331.548368245, 43501045.44750998, 40011361.648411, 36555171.82305223, 33041586.4891179, 29779257.471959528, 26344323.360121932, 22951929.141643092, 19559237.996613264, 16197923.489443999, 12781918.0945921, 10018984.51594821, 5834990.252205776, 3557289.613822245, 1728485.9042306188, 444864.20781182987, 162732.92432648793, 25130.533575776368]
+                structural_damping:
+                    mu: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
+    hub:
+        diameter: 8.4
+        cone_angle: 4.0
+        flange_t2shell_t: 6.0
+        flange_OD2hub_D: 0.6
+        flange_ID2OD: 0.8
+        hub_blade_spacing_margin: 1.2
+        hub_stress_concentration: 3.0
+        n_front_brackets: 5
+        n_rear_brackets: 5
+        clearance_hub_spinner: 0.5
+        spin_hole_incr: 1.2
+        pitch_system_scaling_factor: 0.75
+        spinner_gust_ws: 70.0
+        hub_material: cast_iron
+        spinner_material: glass_uniax
+        elastic_properties_mb:
+            system_mass: 120447.70224890654
+            system_inertia: [1882498.8832803261, 1198002.42618154, 1198002.42618154, 0.0, 0.0, 0.0]
+        cd: 0.5
+    tower:
+        outer_shape:
+            outer_diameter:
+                grid: [0.0, 0.021339950396958213, 0.05508684863374078, 0.08883374687052335, 0.1225806451742466, 0.15632754341102914, 0.19007444171475243, 0.22382133995153497, 0.25756823818831753, 0.29131513649204077, 0.32506203472882333, 0.3588089330325465, 0.39255583126932914, 0.4263027295061117, 0.460049627809835, 0.4937965260466175, 0.5275434243503407, 0.5612903225871233, 0.5950372208239059, 0.6287841191276291, 0.6625310173644117, 0.6962779156011942, 0.7300248139049175, 0.7637717121417, 0.797518610445423, 0.8312655086822058, 0.8650124069189884, 0.8987593052227116, 0.9325062034594942, 0.9662531017632174, 1.0]
+                values: [10.0, 10.0, 10.0, 9.912094021695989, 9.798867733731491, 9.683212549424754, 9.565013152460448, 9.444143041221963, 9.32046327388989, 9.193820595794387, 9.064045585255547, 8.930949935438123, 8.7943237728865, 8.653931280153058, 8.509507328072138, 8.360748211231963, 8.207312432063077, 8.04878734454046, 7.884738119855545, 7.714515454243951, 7.5377038035774415, 7.352762941451701, 7.160611652753185, 6.954372565429866, 6.747495507438188, 6.494067002004703, 6.171403973994344, 6.000000000000001, 6.000000000000001, 6.000000000000001, 6.000000000000001]
+            cd:
+                grid: [0.0, 1.0]
+                values: [0.5, 0.5]
+        structure:
+            layers:
+               -  name: tower_wall
+                  material: steel
+                  thickness:
+                      grid: [0.0, 0.021339950396958213, 0.05508684863374078, 0.08883374687052335, 0.1225806451742466, 0.15632754341102914, 0.19007444171475243, 0.22382133995153497, 0.25756823818831753, 0.29131513649204077, 0.32506203472882333, 0.3588089330325465, 0.39255583126932914, 0.4263027295061117, 0.460049627809835, 0.4937965260466175, 0.5275434243503407, 0.5612903225871233, 0.5950372208239059, 0.6287841191276291, 0.6625310173644117, 0.6962779156011942, 0.7300248139049175, 0.7637717121417, 0.797518610445423, 0.8312655086822058, 0.8650124069189884, 0.8987593052227116, 0.9325062034594942, 0.9662531017632174, 1.0]
+                      values: [0.06693667948991197, 0.0657205223939668, 0.06351493329530639, 0.061622565059606595, 0.06157094605240987, 0.060192055856069474, 0.06010935491737136, 0.05869787142742862, 0.05858091817360326, 0.05713335614043083, 0.05697830761612923, 0.0554904145092067, 0.05529254628422707, 0.05375904790846814, 0.05351244349797769, 0.051926653721110175, 0.051623725388870445, 0.04997689829782623, 0.04960763591844826, 0.04788769899446825, 0.047438671357998265, 0.045626745971738734, 0.04508184480811805, 0.04313680782593655, 0.04249986371535212, 0.04025991352805275, 0.04051397047416457, 0.038444152485609936, 0.0384440711088536, 0.0384440711088536, 0.0384440711088536]
+        reference_axis:
+            x:
+                grid: [0.0, 0.021339950396958213, 0.05508684863374078, 0.08883374687052335, 0.1225806451742466, 0.15632754341102914, 0.19007444171475243, 0.22382133995153497, 0.25756823818831753, 0.29131513649204077, 0.32506203472882333, 0.3588089330325465, 0.39255583126932914, 0.4263027295061117, 0.460049627809835, 0.4937965260466175, 0.5275434243503407, 0.5612903225871233, 0.5950372208239059, 0.6287841191276291, 0.6625310173644117, 0.6962779156011942, 0.7300248139049175, 0.7637717121417, 0.797518610445423, 0.8312655086822058, 0.8650124069189884, 0.8987593052227116, 0.9325062034594942, 0.9662531017632174, 1.0]
+                values: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
+            y:
+                grid: [0.0, 0.021339950396958213, 0.05508684863374078, 0.08883374687052335, 0.1225806451742466, 0.15632754341102914, 0.19007444171475243, 0.22382133995153497, 0.25756823818831753, 0.29131513649204077, 0.32506203472882333, 0.3588089330325465, 0.39255583126932914, 0.4263027295061117, 0.460049627809835, 0.4937965260466175, 0.5275434243503407, 0.5612903225871233, 0.5950372208239059, 0.6287841191276291, 0.6625310173644117, 0.6962779156011942, 0.7300248139049175, 0.7637717121417, 0.797518610445423, 0.8312655086822058, 0.8650124069189884, 0.8987593052227116, 0.9325062034594942, 0.9662531017632174, 1.0]
+                values: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
+            z:
+                grid: [0.0, 0.021339950396958213, 0.05508684863374078, 0.08883374687052335, 0.1225806451742466, 0.15632754341102914, 0.19007444171475243, 0.22382133995153497, 0.25756823818831753, 0.29131513649204077, 0.32506203472882333, 0.3588089330325465, 0.39255583126932914, 0.4263027295061117, 0.460049627809835, 0.4937965260466175, 0.5275434243503407, 0.5612903225871233, 0.5950372208239059, 0.6287841191276291, 0.6625310173644117, 0.6962779156011942, 0.7300248139049175, 0.7637717121417, 0.797518610445423, 0.8312655086822058, 0.8650124069189884, 0.8987593052227116, 0.9325062034594942, 0.9662531017632174, 1.0]
+                values: [15.0, 18.18788983, 23.22920397, 28.27051811, 33.31183226, 38.3531464, 43.39446055, 48.43577469, 53.47708883, 58.51840298, 63.55971712, 68.60103127, 73.64234541, 78.68365955, 83.7249737, 88.76628784, 93.80760199, 98.84891613, 103.89023027, 108.93154442, 113.97285856, 119.0141727, 124.05548685, 129.09680099, 134.13811514, 139.17942928, 144.22074342, 149.26205757, 154.30337171, 159.34468586, 164.386]
+    floating_platform:
+        transition_piece_mass: 100000.0
+        transition_piece_cost: 100000.0
+        joints:
+           -  name: main_keel
+              location: [0.0, 0.0, -25.0]
+              transition: false
+              cylindrical: false
+           -  name: main_freeboard
+              location: [0.0, 0.0, 15.0]
+              transition: true
+              cylindrical: false
+           -  name: col1_keel
+              location: [65.0, 179.99999979432002, -25.0]
+              cylindrical: true
+              transition: false
+           -  name: col1_freeboard
+              location: [65.0, 179.99999979432002, 15.0]
+              cylindrical: true
+              transition: false
+           -  name: col2_keel
+              location: [65.0, 60.00000279622898, -25.0]
+              cylindrical: true
+              transition: false
+           -  name: col2_freeboard
+              location: [65.0, 59.99999706665103, 15.0]
+              cylindrical: true
+              transition: false
+           -  name: col3_keel
+              location: [65.0, -60.00000279622898, -25.0]
+              cylindrical: true
+              transition: false
+           -  name: col3_freeboard
+              location: [65.0, -60.00000279622898, 15.0]
+              cylindrical: true
+              transition: false
+           -  name: anchor1
+              location: [837.8, 179.99999979432002, -200.0]
+              cylindrical: true
+              transition: false
+           -  name: anchor2
+              location: [837.8, 60.00000279622898, -200.0]
+              cylindrical: true
+              transition: false
+           -  name: anchor3
+              location: [837.8, -60.00000279622898, -200.0]
+              cylindrical: true
+              transition: false
+        members:
+           -  name: main_column
+              joint1: main_keel
+              joint2: main_freeboard
+              Ca: [1.0, 1.0]
+              Cd: [0.8, 0.8]
+              outer_shape:
+                  shape: circular
+                  outer_diameter:
+                      grid: [0.0, 1.0]
+                      values: [12.0, 12.0]
+              axial_joints:
+                 -  name: main_upper_pontoon
+                    grid: 0.987
+                 -  name: main_lower_pontoon
+                    grid: 0.2
+              Cp: 0.0
+              structure:
+                  layers:
+                     -  name: main_twall
+                        material: steel
+                        thickness:
+                            grid: [0.0, 1.0]
+                            values: [0.05, 0.05]
+                  bulkhead:
+                      material: steel
+                      thickness:
+                          grid: [0.0, 0.1, 0.25, 1.0]
+                          values: [0.05, 0.05, 0.05, 0.05]
+                  outfitting_factor: 1.0
+                  ballast:
+                     -  variable_flag: true
+                        grid: [0.0, 0.25]
+           -  name: column1
+              joint1: col1_keel
+              joint2: col1_freeboard
+              Ca: [1.0, 1.0]
+              Cd: [0.8, 0.8]
+              outer_shape: &id003
+                  shape: circular
+                  outer_diameter:
+                      grid: [0.0, 1.0]
+                      values: [12.5, 12.5]
+              axial_joints:
+                 -  name: col1_upper_pontoon
+                    grid: 0.987
+                 -  name: col1_lower_pontoon
+                    grid: 0.2
+                 -  name: col1_fairlead
+                    grid: 0.1714
+              Cp: 0.0
+              structure: &id004
+                  layers:
+                     -  name: col_twall
+                        material: steel
+                        thickness:
+                            grid: [0.0, 1.0]
+                            values: [0.05, 0.05]
+                  bulkhead:
+                      material: steel
+                      thickness:
+                          grid: [0.0, 0.35, 1.0]
+                          values: [0.05, 0.05, 0.05]
+                  ring_stiffeners:
+                      material: steel
+                      flange_thickness: 0.1
+                      flange_width: 0.2
+                      web_height: 0.2
+                      web_thickness: 0.1
+                      spacing: 0.083333
+                  longitudinal_stiffeners:
+                      material: steel
+                      flange_thickness: 0.1
+                      flange_width: 0.2
+                      web_height: 0.2
+                      web_thickness: 0.1
+                      spacing: 0.52359
+                  outfitting_factor: 1.0
+                  ballast:
+                     -  variable_flag: true
+                        grid: [0.0, 0.35]
+           -  name: column2
+              joint1: col2_keel
+              joint2: col2_freeboard
+              Ca: [1.0, 1.0]
+              Cd: [0.8, 0.8]
+              outer_shape: *id003
+              axial_joints:
+                 -  name: col2_upper_pontoon
+                    grid: 0.987
+                 -  name: col2_lower_pontoon
+                    grid: 0.2
+                 -  name: col2_fairlead
+                    grid: 0.1714
+              Cp: 0.0
+              structure: *id004
+           -  name: column3
+              joint1: col3_keel
+              joint2: col3_freeboard
+              Ca: [1.0, 1.0]
+              Cd: [0.8, 0.8]
+              outer_shape: *id003
+              axial_joints:
+                 -  name: col3_upper_pontoon
+                    grid: 0.987
+                 -  name: col3_lower_pontoon
+                    grid: 0.2
+                 -  name: col3_fairlead
+                    grid: 0.1714
+              Cp: 0.0
+              structure: *id004
+           -  name: Y_pontoon_upper1
+              joint1: main_upper_pontoon
+              joint2: col1_upper_pontoon
+              Ca: [1.0, 1.0]
+              Cd: [0.8, 0.8]
+              outer_shape: &id005
+                  shape: circular
+                  outer_diameter:
+                      grid: [0.0, 1.0]
+                      values: [0.91, 0.91]
+              Cp: 0.0
+              structure: &id006
+                  layers:
+                     -  name: pontoon_upper_twall
+                        material: steel
+                        thickness:
+                            grid: [0.0, 1.0]
+                            values: [0.02, 0.02]
+                  outfitting_factor: 1.0
+                  bulkhead:
+                      material: steel
+                      thickness:
+                          grid: [0.0, 1.0]
+                          values: [0.02, 0.02]
+           -  name: Y_pontoon_upper2
+              joint1: main_upper_pontoon
+              joint2: col2_upper_pontoon
+              Ca: [1.0, 1.0]
+              Cd: [0.8, 0.8]
+              outer_shape: *id005
+              Cp: 0.0
+              structure: *id006
+           -  name: Y_pontoon_upper3
+              joint1: main_upper_pontoon
+              joint2: col3_upper_pontoon
+              Ca: [1.0, 1.0]
+              Cd: [0.8, 0.8]
+              outer_shape: *id005
+              Cp: 0.0
+              structure: *id006
+           -  name: Y_pontoon_lower1
+              joint1: main_lower_pontoon
+              joint2: col1_lower_pontoon
+              Ca: [1.0, 1.0]
+              Cd: [0.8, 0.8]
+              outer_shape: &id007
+                  shape: circular
+                  outer_diameter:
+                      grid: [0.0, 1.0]
+                      values: [10.0, 10.0]
+              Cp: 0.0
+              structure: &id008
+                  layers:
+                     -  name: pontoon_lower_twall
+                        material: steel
+                        thickness:
+                            grid: [0.0, 1.0]
+                            values: [0.04, 0.04]
+                  outfitting_factor: 1.0
+                  bulkhead:
+                      material: steel
+                      thickness:
+                          grid: [0.0, 1.0]
+                          values: [0.02, 0.02]
+                  ballast:
+                     -  variable_flag: true
+                        grid: [0.0, 1.0]
+           -  name: Y_pontoon_lower2
+              joint1: main_lower_pontoon
+              joint2: col2_lower_pontoon
+              Ca: [1.0, 1.0]
+              Cd: [0.8, 0.8]
+              outer_shape: *id007
+              Cp: 0.0
+              structure: *id008
+           -  name: Y_pontoon_lower3
+              joint1: main_lower_pontoon
+              joint2: col3_lower_pontoon
+              Ca: [1.0, 1.0]
+              Cd: [0.8, 0.8]
+              outer_shape: *id007
+              Cp: 0.0
+              structure: *id008
+    mooring:
+        nodes:
+           -  name: line1_anchor
+              node_type: fixed
+              joint: anchor1
+              anchor_type: drag_embedment
+              fairlead_type: rigid
+              node_mass: 0.0
+              node_volume: 0.0
+              drag_area: 0.0
+              added_mass: 0.0
+           -  name: line2_anchor
+              node_type: fixed
+              joint: anchor2
+              anchor_type: drag_embedment
+              fairlead_type: rigid
+              node_mass: 0.0
+              node_volume: 0.0
+              drag_area: 0.0
+              added_mass: 0.0
+           -  name: line3_anchor
+              node_type: fixed
+              joint: anchor3
+              anchor_type: drag_embedment
+              fairlead_type: rigid
+              node_mass: 0.0
+              node_volume: 0.0
+              drag_area: 0.0
+              added_mass: 0.0
+           -  name: line1_vessel
+              node_type: vessel
+              joint: col1_fairlead
+              fairlead_type: rigid
+              anchor_type: none
+              node_mass: 0.0
+              node_volume: 0.0
+              drag_area: 0.0
+              added_mass: 0.0
+           -  name: line2_vessel
+              node_type: vessel
+              joint: col2_fairlead
+              fairlead_type: rigid
+              anchor_type: none
+              node_mass: 0.0
+              node_volume: 0.0
+              drag_area: 0.0
+              added_mass: 0.0
+           -  name: line3_vessel
+              joint: col3_fairlead
+              node_type: vessel
+              fairlead_type: rigid
+              anchor_type: none
+              node_mass: 0.0
+              node_volume: 0.0
+              drag_area: 0.0
+              added_mass: 0.0
+        lines:
+           -  name: line1
+              node1: line1_anchor
+              node2: line1_vessel
+              line_type: main
+              unstretched_length: 837.0
+           -  name: line2
+              node1: line2_anchor
+              node2: line2_vessel
+              line_type: main
+              unstretched_length: 837.0
+           -  name: line3
+              node1: line3_anchor
+              node2: line3_vessel
+              line_type: main
+              unstretched_length: 837.0
+        line_types:
+           -  name: main
+              diameter: 0.225
+              type: chain
+              transverse_added_mass: 1.0
+              tangential_added_mass: 0.0
+              transverse_drag: 1.6
+              tangential_drag: 0.1
+              damping: 0.0
+        anchor_types:
+           -  name: drag_embedment
+              type: drag_embedment
+    drivetrain:
+        outer_shape:
+            uptilt: 6.000000000000001
+            distance_tt_hub: 5.614
+            overhang: 14.0
+            cd: 0.5
+        gearbox:
+            gear_ratio: 1.0
+            efficiency: 1.0
+            damping_ratio: 0.005
+        lss:
+            diameter: [3.1, 3.1]
+            wall_thickness: [0.02, 0.02]
+            material: steel_drive
+        hss: {}
+        nose:
+            diameter: [2.1, 2.1]
+            wall_thickness: [0.035, 0.035]
+        bedplate:
+            wall_thickness:
+                grid: [0.0, 0.3333333333333333, 0.6666666666666666, 1.0]
+                values: [0.1, 0.1, 0.1, 0.1]
+            material: steel
+        other_components:
+            brake_mass: 0.0
+            hvac_mass_coefficient: 0.025
+            converter_mass: 0.0
+            transformer_mass: 0.0
+            mb1Type: CARB
+            mb2Type: SRB
+            uptower: true
+        generator:
+            length: 3.047
+airfoils:
+   -  name: FFA-W3-211
+      coordinates:
+          x: [1.0, 0.99258, 0.98009, 0.96604, 0.95066, 0.93415, 0.91684, 0.89901, 0.88084, 0.8625, 0.84401, 0.82544, 0.80688, 0.78829, 0.76963, 0.75088, 0.73205, 0.71319, 0.69435, 0.67555, 0.65682, 0.63817, 0.61968, 0.60133, 0.58309, 0.56491, 0.54677, 0.5287, 0.51074, 0.4929, 0.47519, 0.4576, 0.44014, 0.42283, 0.40569, 0.38873, 0.37195, 0.35536, 0.339, 0.32287, 0.30693, 0.29113, 0.27547, 0.25996, 0.24458, 0.2293, 0.21414, 0.19912, 0.18429, 0.1697, 0.15539, 0.14144, 0.12793, 0.11496, 0.10262, 0.09103, 0.08028, 0.07044, 0.06155, 0.05357, 0.04648, 0.04021, 0.03466, 0.02977, 0.02545, 0.02163, 0.01825, 0.01526, 0.01262, 0.01029, 0.00825, 0.00646, 0.00492, 0.00359, 0.00248, 0.00158, 0.00087, 0.00038, 8e-05, 0.0, 0.00014, 0.00051, 0.00115, 0.00209, 0.00332, 0.00482, 0.00657, 0.00859, 0.01087, 0.01343, 0.0163, 0.01949, 0.02306, 0.02705, 0.03152, 0.03657, 0.04228, 0.04876, 0.05611, 0.06444, 0.07382, 0.08428, 0.09582, 0.10833, 0.12166, 0.13568, 0.15025, 0.16522, 0.18048, 0.19596, 0.21162, 0.22743, 0.24336, 0.25937, 0.27541, 0.29147, 0.30752, 0.32356, 0.3396, 0.35564, 0.37169, 0.38775, 0.40381, 0.4199, 0.43601, 0.45217, 0.46841, 0.48484, 0.50157, 0.51863, 0.53604, 0.55376, 0.5717, 0.58978, 0.60785, 0.62579, 0.64351, 0.661, 0.67827, 0.69535, 0.71229, 0.72912, 0.74587, 0.76252, 0.77902, 0.79541, 0.8117, 0.82793, 0.84409, 0.86017, 0.87611, 0.8919, 0.9075, 0.92287, 0.93796, 0.95268, 0.96688, 0.98029, 0.99257, 1.0]
+          y: [0.00131, 0.00259, 0.00469, 0.00704, 0.00971, 0.01268, 0.01587, 0.01924, 0.02274, 0.02635, 0.03006, 0.03383, 0.03766, 0.04157, 0.04555, 0.0496, 0.0537, 0.05782, 0.06194, 0.06604, 0.0701, 0.0741, 0.07802, 0.08182, 0.0855, 0.08904, 0.09246, 0.09575, 0.09889, 0.10185, 0.10463, 0.10722, 0.10959, 0.11173, 0.11362, 0.11526, 0.11661, 0.11766, 0.11841, 0.11882, 0.11886, 0.11855, 0.11787, 0.11682, 0.11539, 0.11357, 0.11138, 0.10882, 0.10591, 0.10264, 0.09904, 0.09512, 0.09092, 0.08648, 0.08184, 0.0771, 0.07231, 0.06756, 0.0629, 0.0584, 0.0541, 0.05, 0.04611, 0.04243, 0.03894, 0.03563, 0.03247, 0.02945, 0.02655, 0.02376, 0.02108, 0.01849, 0.01597, 0.0135, 0.01109, 0.00873, 0.00646, 0.00427, 0.00215, 8e-05, -0.00199, -0.00409, -0.00623, -0.00839, -0.01055, -0.01268, -0.01479, -0.01689, -0.01901, -0.02118, -0.0234, -0.02569, -0.02807, -0.03056, -0.03317, -0.03593, -0.03885, -0.04195, -0.04524, -0.04872, -0.05238, -0.05618, -0.06005, -0.06392, -0.06771, -0.07133, -0.07475, -0.07792, -0.08079, -0.08335, -0.08558, -0.08749, -0.08908, -0.09034, -0.09127, -0.09187, -0.09213, -0.09205, -0.09161, -0.09084, -0.08972, -0.08826, -0.08645, -0.08431, -0.08182, -0.07899, -0.07581, -0.07227, -0.06838, -0.06417, -0.0597, -0.05501, -0.05017, -0.04524, -0.04031, -0.03547, -0.03079, -0.02632, -0.02208, -0.01811, -0.0144, -0.01096, -0.0078, -0.00492, -0.00235, -9e-05, 0.00183, 0.00342, 0.00469, 0.00562, 0.00621, 0.00646, 0.00636, 0.0059, 0.0051, 0.00397, 0.0026, 0.0011, -0.00038, -0.00131]
+      aerodynamic_center: 0.25
+      description: Airfoil data computed using EllipSys2D v22.0 assuming incompressible flow. 360 degree  extrapolation done using AirfoilPreppy, no 3D correction. F Zahle, DTU Wind Energy 12 June 2023
+      polars:
+         -  configuration: default
+            re_sets:
+               -  re: 10000000.0
+                  cl:
+                      grid: [-180.0, -177.71428571428572, -175.42857142857142, -173.14285714285714, -170.8571428571429, -168.57142857142858, -166.2857142857143, -164.0, -161.71428571428572, -159.42857142857142, -157.14285714285717, -154.85714285714286, -152.57142857142858, -150.28571428571428, -148.0, -143.8571428571429, -139.71428571428572, -135.57142857142856, -131.42857142857144, -127.28571428571429, -123.14285714285715, -119.0, -114.85714285714288, -110.71428571428572, -106.5714285714286, -102.42857142857143, -98.28571428571428, -94.14285714285715, -90.0, -85.85714285714286, -81.71428571428572, -77.57142857142857, -73.42857142857143, -69.28571428571428, -65.14285714285714, -61.0, -56.857142857142854, -52.714285714285715, -48.57142857142857, -44.42857142857142, -40.285714285714285, -36.14285714285714, -32.0, -28.0, -24.000000000000004, -20.0, -18.0, -16.0, -14.0, -12.000000000000002, -10.0, -8.0, -6.000000000000001, -4.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0000000000000004, 4.0, 5.0, 6.000000000000001, 7.0, 8.0, 9.0, 10.0, 11.0, 12.000000000000002, 13.0, 14.0, 14.999999999999998, 16.0, 18.0, 20.0, 24.000000000000004, 28.0, 32.0, 36.14285714285714, 40.28571428571429, 44.42857142857143, 48.57142857142857, 52.714285714285715, 56.857142857142854, 61.0, 65.14285714285715, 69.28571428571428, 73.42857142857143, 77.57142857142857, 81.71428571428572, 85.85714285714286, 90.0, 94.14285714285714, 98.28571428571428, 102.42857142857143, 106.57142857142857, 110.71428571428572, 114.85714285714285, 119.0, 123.14285714285712, 127.28571428571429, 131.42857142857144, 135.57142857142856, 139.71428571428572, 143.8571428571429, 148.0, 150.28571428571428, 152.57142857142858, 154.85714285714286, 157.14285714285717, 159.42857142857142, 161.7142857142857, 164.0, 166.28571428571428, 168.57142857142858, 170.8571428571429, 173.14285714285714, 175.42857142857142, 177.71428571428572, 180.0]
+                      values: [0.0, 0.03526196749837121, 0.07052393499674281, 0.10578590249511402, 0.14104786999348562, 0.17630983749185686, 0.21157180499022804, 0.24683377248859964, 0.28209573998697085, 0.3173577074853424, 0.3526196749837137, 0.3878816424820853, 0.42314360998045647, 0.45840557747882804, 0.4936675449771993, 0.5178686154966322, 0.532363896813595, 0.5365979734452553, 0.5303056890138329, 0.5134897592756826, 0.48640473252458066, 0.4495420491556365, 0.40361374048250886, 0.3495336453660192, 0.2883957263335649, 0.22144946960466028, 0.15007260307576803, 0.07574153128707875, 6.429395695523604e-17, -0.07574153128707853, -0.15007260307576803, -0.22144946960466005, -0.2883957263335647, -0.3495336453660192, -0.4036137404825087, -0.4495420491556365, -0.4864047325245806, -0.5134897592756826, -0.5303056890138329, -0.5365979734452553, -0.5323638968135951, -0.5178686154966322, -0.41387696393302636, -0.6135768681714694, -1.056385643666067, -1.1356818178427857, -1.2084559521408718, -1.182916302032777, -1.1600610792518475, -1.0972693089493828, -0.8873189203821055, -0.6354770172295855, -0.38250734455834046, -0.12673193730198665, 0.12280257244085752, 0.24669730455180028, 0.37005382565470796, 0.4929152674007631, 0.6149220147298263, 0.7364734827621472, 0.8568489339640477, 0.9756275486682474, 1.0908058741946252, 1.2029453239335788, 1.3104213841695092, 1.4142871099229875, 1.51341712718498, 1.6085463379883127, 1.696122297396129, 1.769310028911016, 1.8197127111403673, 1.8344271493922617, 1.7986278758318592, 1.6392960843837663, 1.5349764636260839, 1.378150481894837, 1.154902758229382, 0.7052393499674277, 0.7398123078523318, 0.7605198525908501, 0.7665685334932218, 0.757579555734047, 0.7335567989652609, 0.6948639036065437, 0.642202927365195, 0.5765910578321551, 0.4993337790943132, 0.4119938947622353, 0.31635638514951436, 0.21438943296538293, 0.10820218755296933, 9.184850993605148e-17, -0.07574153128707853, -0.15007260307576803, -0.22144946960466005, -0.2883957263335647, -0.3495336453660192, -0.4036137404825086, -0.4495420491556365, -0.4864047325245805, -0.5134897592756826, -0.5303056890138329, -0.5365979734452553, -0.532363896813595, -0.5178686154966322, -0.49366754497719945, -0.45840557747882804, -0.42314360998045647, -0.3878816424820853, -0.3526196749837137, -0.3173577074853424, -0.28209573998697124, -0.24683377248859964, -0.2115718049902284, -0.17630983749185686, -0.14104786999348562, -0.10578590249511402, -0.07052393499674281, -0.03526196749837121, 0.0]
+                  cd:
+                      grid: [-180.0, -177.71428571428572, -175.42857142857142, -173.14285714285714, -170.8571428571429, -168.57142857142858, -166.2857142857143, -164.0, -161.71428571428572, -159.42857142857142, -157.14285714285717, -154.85714285714286, -152.57142857142858, -150.28571428571428, -148.0, -143.8571428571429, -139.71428571428572, -135.57142857142856, -131.42857142857144, -127.28571428571429, -123.14285714285715, -119.0, -114.85714285714288, -110.71428571428572, -106.5714285714286, -102.42857142857143, -98.28571428571428, -94.14285714285715, -90.0, -85.85714285714286, -81.71428571428572, -77.57142857142857, -73.42857142857143, -69.28571428571428, -65.14285714285714, -61.0, -56.857142857142854, -52.714285714285715, -48.57142857142857, -44.42857142857142, -40.285714285714285, -36.14285714285714, -32.0, -28.0, -24.000000000000004, -20.0, -18.0, -16.0, -14.0, -12.000000000000002, -10.0, -8.0, -6.000000000000001, -4.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0000000000000004, 4.0, 5.0, 6.000000000000001, 7.0, 8.0, 9.0, 10.0, 11.0, 12.000000000000002, 13.0, 14.0, 14.999999999999998, 16.0, 18.0, 20.0, 24.000000000000004, 28.0, 32.0, 36.14285714285714, 40.28571428571429, 44.42857142857143, 48.57142857142857, 52.714285714285715, 56.857142857142854, 61.0, 65.14285714285715, 69.28571428571428, 73.42857142857143, 77.57142857142857, 81.71428571428572, 85.85714285714286, 90.0, 94.14285714285714, 98.28571428571428, 102.42857142857143, 106.57142857142857, 110.71428571428572, 114.85714285714285, 119.0, 123.14285714285712, 127.28571428571429, 131.42857142857144, 135.57142857142856, 139.71428571428572, 143.8571428571429, 148.0, 150.28571428571428, 152.57142857142858, 154.85714285714286, 157.14285714285717, 159.42857142857142, 161.7142857142857, 164.0, 166.28571428571428, 168.57142857142858, 170.8571428571429, 173.14285714285714, 175.42857142857142, 177.71428571428572, 180.0]
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+      rthick: 0.211
+   -  name: FFA-W3-241
+      coordinates:
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+      aerodynamic_center: 0.25
+      description: Airfoil data computed using EllipSys2D v22.0 assuming incompressible flow. 360 degree  extrapolation done using AirfoilPreppy, no 3D correction. F Zahle, DTU Wind Energy 12 June 2023
+      polars:
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+      aerodynamic_center: 0.25
+      description: Airfoil data computed using EllipSys2D v22.0 assuming incompressible flow. 360 degree  extrapolation done using AirfoilPreppy, no 3D correction. F Zahle, DTU Wind Energy 12 June 2023
+      polars:
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+      rthick: 0.27
+   -  name: FFA-W3-301
+      coordinates:
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+      aerodynamic_center: 0.25
+      description: Airfoil data computed using EllipSys2D v22.0 assuming incompressible flow. 360 degree  extrapolation done using AirfoilPreppy, no 3D correction. F Zahle, DTU Wind Energy 12 June 2023
+      polars:
+         -  configuration: default
+            re_sets:
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+      aerodynamic_center: 0.25
+      description: Airfoil data computed using EllipSys2D v22.0 assuming incompressible flow. 360 degree  extrapolation done using AirfoilPreppy, no 3D correction. F Zahle, DTU Wind Energy 12 June 2023
+      polars:
+         -  configuration: default
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+      rthick: 0.33
+   -  name: FFA-W3-360
+      coordinates:
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+      aerodynamic_center: 0.25
+      description: Airfoil data computed using EllipSys2D v22.0 assuming incompressible flow. 360 degree  extrapolation done using AirfoilPreppy, no 3D correction. F Zahle, DTU Wind Energy 12 June 2023
+      polars:
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+      description: Airfoil data computed using EllipSys2D v22.0 assuming incompressible flow. 360 degree  extrapolation done using AirfoilPreppy, no 3D correction. F Zahle, DTU Wind Energy 12 June 2023
+      rthick: 0.42
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+      description: Airfoil data computed using EllipSys2D v22.0 assuming incompressible flow. 360 degree  extrapolation done using AirfoilPreppy, no 3D correction. F Zahle, DTU Wind Energy 12 June 2023
+      rthick: 0.46832376637293865
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+   -  name: circular
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+      polars:
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+            re_sets:
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+                  cm:
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+                      values: [-0.0001, -0.0001]
+      rthick: 1.0
+materials:
+   -  name: gelcoat
+      rho: 1235.0
+      E: 3440000000.0
+      G: 1323000000.0
+      nu: 0.3
+      orth: 0
+      ply_t: 0.0005
+      waste: 0.25
+      unit_cost: 7.23
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+      alp0: 53
+   -  name: Adhesive
+      orth: 0.0
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+      GIIc: 0.0
+      alp0: 0.0
+      ply_t: 0.001
+      waste: 0.25
+      unit_cost: 7.23
+   -  name: steel
+      rho: 7850.0
+      E: 200000000000.0
+      G: 79300000000.0
+      nu: 0.265
+      orth: 0
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+      alp0: 0.0
+      Xt: 450000000.0
+      Xc: 450000000.0
+      S: 0
+      Xy: 345000000.0
+      m: 3
+      unit_cost: 0.7
+   -  name: steel_drive
+      description: Steel of the drivetrain ASTM 4140 40Cr1Mo28
+      source: http://www.matweb.com/search/DataSheet.aspx?MatGUID=38108bfd64c44b4c9c6a02af78d5b6c6
+      orth: 0
+      rho: 7850
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+      E: 205000000000.0
+      nu: 0.3
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+      Xc: 814000000.0
+      S: 0
+      Xy: 485000000.0
+      m: 3
+      unit_cost: 0.9
+   -  name: cast_iron
+      description: Cast iron for hub and nacelle components
+      source: TODO
+      orth: 0
+      rho: 7200
+      alpha: 0.0
+      E: 118000000000.0
+      nu: 0.3
+      G: 47600000000.0
+      GIc: 0
+      GIIc: 0
+      alp0: 0.0
+      Xt: 310000000.0
+      Xc: 310000000.0
+      S: 0
+      Xy: 265000000.0
+      m: 3
+      unit_cost: 0.5
+   -  name: glass_uniax
+      description: Vectorply E-LT-5500, Epikote MGS RIMR 135/Epicure MGS RIMH 1366 epoxy
+      source: MSU composites database 3D property tests, desrcibed in https://doi.org/10.5194/wes-7-19-2022
+      orth: 1.0
+      rho: 1940.0
+      E: [43700000000.0, 16500000000.0, 15450000000.0]
+      G: [3265000000.0, 3495000000.0, 3480000000.0]
+      nu: [0.262, 0.264, 0.35]
+      Xt: [640230000.0, 38100000.0, 0.0]
+      Xc: [370690000.0, 82180000.0, 0]
+      S: [30170000.0, 18970000.0, 6210000.0]
+      m: 10
+      GIc: 61.0
+      GIIc: 101.0
+      alp0: 50.0
+      fvf: 0.57
+      fwf: 0.7450682696347697
+      ply_t: 0.005
+      unit_cost: 1.87
+      waste: 0.05
+      fiber_density: 2535.5
+      area_density_dry: 7.227162215457267
+      manufacturing_id: 5
+   -  name: carbon_uniax
+      description: Baseline industry CFRP tested by Sandia National Labs within the BAR Project
+      source: Described in https://doi.org/10.5194/wes-7-19-2022 and https://energy.sandia.gov/download/45350/, RVE analysis. Nominal E11 is 157.6 GPa, but it is reduced to 140 GPa to be more in line with the actual properties seen in real blades.
+      orth: 1.0
+      rho: 1600.0
+      E: [140000000000.0, 9100000000.0, 9100000000.0]
+      G: [4131000000.0, 4131000000.0, 2689000000.0]
+      nu: [0.3133, 0.3133, 0.47066]
+      Xt: [1285200000.0, 38100000.0, 0.0]
+      Xc: [878210000.0, 82180000.0, 0.0]
+      S: [30170000.0, 18970000.0, 6210000.0]
+      m: 16.1
+      GIc: 0.0
+      GIIc: 0.0
+      alp0: 0.0
+      fvf: 0.6923076923076923
+      fwf: 0.7788461538461539
+      ply_t: 0.005
+      unit_cost: 20.08
+      waste: 0.05
+      fiber_density: 1800.0
+      area_density_dry: 6.230769230769231
+      manufacturing_id: 4
+   -  name: glass_biax
+      description: "(+-45)6 PPG-Devold DB810- E05\u2014a fabric infused with Epikote MGS RIMR 135/Epicure RIMH 1366 epoxy resin. todo update Xt once clarified with Sandia"
+      source: Described in https://doi.org/10.5194/wes-7-19-2022
+      orth: 1.0
+      rho: 1940.0
+      E: [11023100000.0, 11023100000.0, 16047700000.0]
+      G: [13231400000.0, 3487480000.0, 3487480000.0]
+      nu: [0.688074, 0.117173, 0.117173]
+      Xt: [69315000.0, 69315000.0, 69315000.0]
+      Xc: [70690000.0, 70690000.0, 70690000.0]
+      S: [124460000.0, 18970000.0, 6210000.0]
+      m: 10
+      GIc: 41.0
+      GIIc: 170.0
+      alp0: 45.0
+      fvf: 0.57
+      fwf: 0.7450682696347697
+      ply_t: 0.001
+      waste: 0.15
+      unit_cost: 3.0
+      fiber_density: 2535.5
+      area_density_dry: 1.4454324430914534
+      roll_mass: 181.4368
+      manufacturing_id: 3
+   -  name: glass_triax
+      description: "((\xB145)(0)2)s Saertex U14EU920-00940-T1300 and Saertex VU-90079-00830-01270\u2014fabrics infused with Vantico TDT 177-155."
+      source: Described in https://doi.org/10.5194/wes-7-19-2022
+      orth: 1.0
+      rho: 1940.0
+      E: [28211400000.0, 16238800000.0, 15835500000.0]
+      G: [8248220000.0, 3491240000.0, 3491240000.0]
+      nu: [0.497511, 0.18091, 0.27481]
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+      Xc: [343100000.0, 174710000.0, 0]
+      S: [85060000.0, 18970000.0, 6210000.0]
+      m: 10
+      GIc: 41.0
+      GIIc: 170.0
+      alp0: 45.0
+      fvf: 0.57
+      fwf: 0.7450682696347697
+      ply_t: 0.001
+      unit_cost: 2.86
+      waste: 0.15
+      fiber_density: 2535.5
+      area_density_dry: 1.4454324430914534
+      roll_mass: 181.4368
+      manufacturing_id: 2
+   -  name: medium_density_foam
+      description: Airex C70.130 PVC Foam, source 'https://www.3accorematerials.com/uploads/documents/TDS-AIREX-C70-E_1106.pdf'
+      source: Described in https://doi.org/10.5194/wes-7-19-2022
+      orth: 0.0
+      rho: 130.0
+      E: 142500000.0
+      G: 54000000.0
+      nu: 0.3194
+      Xt: 2083000.0
+      Xc: 1563000.0
+      S: 1250000.0
+      GIc: 303.0
+      GIIc: 3446.0
+      alp0: 53.0
+      waste: 0.2
+      unit_cost: 13.0
+      manufacturing_id: 1
+   -  name: resin
+      description: epoxy
+      source: Described in https://doi.org/10.5194/wes-7-19-2022
+      E: 1000000.0
+      nu: 0.3
+      G: 312500.0
+      GIc: 0.0
+      GIIc: 0.0
+      alp0: 0.0
+      Xt: 0.0
+      Xc: 0.0
+      S: 0.0
+      rho: 1150.0
+      alpha: 0.0
+      orth: 0.0
+      unit_cost: 3.63
+control:
+    supervisory:
+        Vin: 3.0
+        Vout: 25.0
+        maxTS: 105.0
+    torque:
+        tsr: 9.153211158238001
+        VS_minspd: 1.975
+        VS_maxspd: 7.162
+        max_torque_rate: 4500000.0
+    pitch:
+        ps_percent: 0.8
+        max_pitch: 89.95437383553924
+        max_pitch_rate: 2.0
+        min_pitch: -0.9549247399288653

From cfafa63265f61018b8cf8e55f30770da0e00ebd9 Mon Sep 17 00:00:00 2001
From: dzalkind <dzalkind@nrel.gov>
Date: Wed, 7 Jan 2026 17:06:10 -0700
Subject: [PATCH 3/9] Add chapter 2, stage 2,3,3.5

---
 .../0_notebooks/chapter2.ipynb                | 963 ++++++++++++++++++
 .../stage-2-controller_analysis.yaml          |  52 +
 .../stage-2-controller_driver.py              |  21 +
 .../stage-2-controller_modeling.yaml          | 121 +++
 .../stage-3-semisub_of_analysis.yaml          | 110 ++
 .../stage-3-semisub_of_driver.py              |  17 +
 .../stage-3-semisub_of_modeling.yaml          | 135 +++
 .../stage-3-semisub_raft_analysis.yaml        | 112 ++
 .../stage-3-semisub_raft_driver.py            |  17 +
 .../stage-3-semisub_raft_modeling.yaml        | 115 +++
 .../stage-3.5-semisub_of_analysis.yaml        | 133 +++
 .../stage-3.5-semisub_of_driver.py            |  16 +
 .../stage-3.5-semisub_of_modeling.yaml        | 135 +++
 13 files changed, 1947 insertions(+)
 create mode 100644 examples/09_model_creation_process/0_notebooks/chapter2.ipynb
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_analysis.yaml
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_driver.py
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_modeling.yaml
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_analysis.yaml
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_driver.py
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_modeling.yaml
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_analysis.yaml
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_driver.py
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_modeling.yaml
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_analysis.yaml
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_driver.py
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_modeling.yaml

diff --git a/examples/09_model_creation_process/0_notebooks/chapter2.ipynb b/examples/09_model_creation_process/0_notebooks/chapter2.ipynb
new file mode 100644
index 000000000..222b7454a
--- /dev/null
+++ b/examples/09_model_creation_process/0_notebooks/chapter2.ipynb
@@ -0,0 +1,963 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7a3a97e8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Downloading the precomputed data from Google Drive & extracting\n",
+    "# Drive link for downloading full runs: https://drive.google.com/file/d/145BH393nzpT2msCVsHSBxR3Qy8KdpddI/view?usp=sharing\n",
+    "# !gdown 145BH393nzpT2msCVsHSBxR3Qy8KdpddI -O /content/weisWorkshop/archive_weisWorkshop_OCT25.tar.gz\n",
+    "# move file and change directory to <weis_dir>examples/09_model_creation_process/1_drivers\n",
+    "# tar -xvzf archive_weisWorkshop_OCT25.tar.gz -C .\n",
+    "\n",
+    "# This flag will let you use those precomputed outputs instead of the partial simulations in this notebook\n",
+    "use_precomputed_outputs = False"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "92735b9d",
+   "metadata": {},
+   "source": [
+    "# Chapter 2: Controller Tuning and Platform Optimization\n",
+    "\n",
+    "## Introduction to Multi-Fidelity (Co-)Design\n",
+    "\n",
+    "In Chapter 1, we optimized our rotor using WISDEM's steady-state models. Now we advance to WEIS's full multi-fidelity capabilities, integrating dynamic analysis tools for comprehensive system optimization.\n",
+    "\n",
+    "WEIS enables a systematic progression through modeling fidelities:\n",
+    "- **WISDEM**: Steady-state system engineering models for initial design\n",
+    "- **RAFT**: Frequency-domain analysis for rapid floating platform evaluation\n",
+    "- **OpenFAST**: Time-domain aeroelastic simulation for medium-fidelity load analysis\n",
+    "\n",
+    "## Chapter 1 Recap\n",
+    "\n",
+    "We will build on our previous work, where we:\n",
+    "- Established baseline performance of the IEA 22MW floating wind turbine\n",
+    "- Scaled the design to create a 20MW turbine (with a smaller, 270m rotor diameter)\n",
+    "- Optimized rotor aerodynamics and structure using WISDEM\n",
+    "- Analyzed optimization convergence and performance improvements\n",
+    "\n",
+    "## Chapter 2 Objectives\n",
+    "\n",
+    "Now we'll complete the integrated system design through multi-stage optimization:\n",
+    "\n",
+    "### Stage 2: Controller Re-tuning with ROSCO\n",
+    "- **Challenge**: Our optimized rotor requires a retuned controller to operate efficiently and manage loads properly\n",
+    "- **Approach**: Use ROSCO within WEIS to optimize controller parameters for the new rotor design\n",
+    "- **Tools**: OpenFAST + ROSCO for analysis\n",
+    "\n",
+    "### Stage 3a: Floating Platform Optimization with RAFT\n",
+    "- **Challenge**: Design an optimal semisubmersible platform for the 20MW system\n",
+    "- **Approach**: Use RAFT's frequency-domain analysis for rapid platform sizing and optimization\n",
+    "- **Tools**: RAFT for efficient floating platform design iteration\n",
+    "\n",
+    "### Stage 3b: Medium-Fidelity System Integration\n",
+    "- **Challenge**: Validate and refine the design using high-fidelity dynamic analysis\n",
+    "- **Approach**: OpenFAST-based optimization incorporating controller and platform interactions\n",
+    "- **Tools**: OpenFAST with Design Load Cases (DLCs) for comprehensive load assessment\n",
+    "\n",
+    "<!-- ### Stage 4: Performance Comparison\n",
+    "- Compare the baseline IEA 22MW with our fully optimized 20MW system\n",
+    "- Evaluate improvements in cost of energy, structural efficiency, and load management -->\n",
+    "\n",
+    "This multi-stage approach demonstrates WEIS's systematic design methodology, progressing from rapid conceptual design to detailed engineering analysis."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b78aebca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Importing nesscary libraries.\n",
+    "from weis import weis_main\n",
+    "import os\n",
+    "\n",
+    "from weis_workshop import *\n",
+    "\n",
+    "# set env variables\n",
+    "os.environ[\"OMP_NUM_THREADS\"] = \"1\"  # export OMP_NUM_THREADS=1\n",
+    "os.environ[\"MKL_NUM_THREADS\"] = \"1\"  # export MKL_NUM_THREADS=1\n",
+    "\n",
+    "# workshop repository folder\n",
+    "this_dir = os.getcwd()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9451cef9",
+   "metadata": {},
+   "source": [
+    "## Multi-Stage Optimization Workflow\n",
+    "\n",
+    "We'll now implement the multi-stage optimization approach outlined in our objectives. Each stage builds upon the previous work, demonstrating the systematic progression through WEIS's modeling capabilities.\n",
+    "\n",
+    "**Computational Notes**: For this workshop, we'll run single iterations and use precomputed results to demonstrate the workflow efficiently. In practice, these optimizations would run for many iterations to achieve full convergence."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "de0d61f7",
+   "metadata": {},
+   "source": [
+    "## Stage 3: Controller Re-tuning with ROSCO\n",
+    "\n",
+    "### Why Controller Re-tuning is Essential\n",
+    "\n",
+    "Our optimized rotor from Chapter 1 has different aerodynamic characteristics than the original IEA 22MW design. The controller parameters that worked well for the baseline turbine may now be suboptimal or even cause stability issues with our new rotor.\n",
+    "\n",
+    "### Controller Optimization Objectives\n",
+    "\n",
+    "**Primary Goal**: Minimize tower base damage equivalent loads (DELs) while maintaining operational constraints\n",
+    "\n",
+    "**Key Design Variables**:\n",
+    "- **Pitch controller natural frequency (ω)**: Controls how aggressively the pitch system responds\n",
+    "- **Pitch controller damping (ζ)**: Determines system stability and response smoothness  \n",
+    "- **Floating feedback gain (Kp_float)**: Manages platform motion interactions\n",
+    "- **Platform natural frequency (ptfm_freq)**: Used for floating feedback controller filtering\n",
+    "\n",
+    "**Constraints**:\n",
+    "- **Rotor overspeed limit**: Ensure safe operation under all conditions\n",
+    "- **Operational stability**: Maintain controller performance across the wind speed range\n",
+    "\n",
+    "This optimization uses OpenFAST for high-fidelity aeroelastic analysis, capturing the dynamic interactions between the controller, rotor, tower, and floating platform that are essential for offshore wind turbines."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "598f089c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Setting up file paths\n",
+    "stageFolder = \"stage-2-controller\"\n",
+    "\n",
+    "fname_wt_input = os.path.join(this_dir, \"..\", \"2_models\", \"stage-1-aeroStruct-aero_analysis.yaml\")\n",
+    "fname_modeling_options = os.path.join(this_dir, \"..\", \"1_drivers\", stageFolder, f\"stage-2-controller_modeling.yaml\")\n",
+    "fname_analysis_options = os.path.join(this_dir, \"..\", \"1_drivers\", stageFolder, f\"stage-2-controller_analysis.yaml\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bd03535c",
+   "metadata": {},
+   "source": [
+    "## Controller Optimization Configuration\n",
+    "\n",
+    "The controller optimization setup demonstrates WEIS's ability to perform high-fidelity aeroelastic optimization using OpenFAST. This configuration integrates multiple tools for comprehensive dynamic analysis.\n",
+    "\n",
+    "### Analysis Options Configuration\n",
+    "\n",
+    "The analysis options define our optimization problem:\n",
+    "\n",
+    "```yaml\n",
+    "design_variables:\n",
+    "  control:\n",
+    "    servo:\n",
+    "      pitch_control:\n",
+    "          omega:\n",
+    "            flag: True\n",
+    "            min: 0.025\n",
+    "            max: 0.5\n",
+    "          zeta:\n",
+    "            flag: True\n",
+    "            min: 0.1\n",
+    "            max: 3.0\n",
+    "          Kp_float:\n",
+    "            flag: True\n",
+    "            min: -40.0  # -0.25\n",
+    "            max: 0\n",
+    "          ptfm_freq:\n",
+    "            flag: True\n",
+    "            max: 0.5\n",
+    "\n",
+    "merit_figure: DEL_TwrBsMyt  # Merit figure of the optimization problem. The options are 'AEP' - 'LCOE' - 'Cp' - 'blade_mass' - 'blade_tip_deflection'\n",
+    "\n",
+    "constraints:\n",
+    "  control:\n",
+    "    rotor_overspeed:\n",
+    "      flag: True\n",
+    "      min: 0.0\n",
+    "      max: 0.2\n",
+    "\n",
+    "driver:\n",
+    "  optimization:\n",
+    "    flag: True\n",
+    "    tol: 1.e-3            # Optimality tolerance\n",
+    "    max_iter: 200         # Maximum number of iterations (SLSQP)\n",
+    "    maxiter: 60          # Maximum number of iterations (SLSQP)\n",
+    "    solver: LN_COBYLA         # Optimization solver. Other options are 'SLSQP' - 'CONMIN'\n",
+    "    step_size: 1.e-3      # Step size for finite differencing\n",
+    "    form: forward         # Finite differencing mode, either forward or central\n",
+    "```\n",
+    "\n",
+    "**Key Configuration Elements:**\n",
+    "- **Merit Figure**: `DEL_TwrBsMyt` - Tower base damage equivalent load in the fore-aft direction\n",
+    "- **Design Variables**: Four controller parameters with physically meaningful bounds\n",
+    "- **Constraints**: Rotor overspeed constraint to ensure safe operation\n",
+    "- **Solver**: LN_COBYLA for gradient-free optimization suitable for noisy objective functions\n",
+    "\n",
+    "### Modeling Options Configuration\n",
+    "\n",
+    "The modeling options enable high-fidelity simulation through OpenFAST integration:\n",
+    "\n",
+    "```yaml\n",
+    "General:\n",
+    "    verbosity: False  # When set to True, the code prints to screen many infos\n",
+    "    openfast_configuration:\n",
+    "        OF_run_fst: stage-2-controller\n",
+    "        save_iterations: True\n",
+    "        save_timeseries: True\n",
+    "        use_exe: True\n",
+    "        allow_fails: True\n",
+    "        fail_value: 9999\n",
+    "        write_stdout: True\n",
+    "\n",
+    "WISDEM:\n",
+    "    RotorSE:\n",
+    "        flag: True\n",
+    "        n_pitch_perf_surfaces: 20\n",
+    "        n_tsr_perf_surfaces: 20\n",
+    "        spar_cap_ss: spar_cap_ss\n",
+    "        spar_cap_ps: spar_cap_ps\n",
+    "        peak_thrust_shaving: True\n",
+    "        thrust_shaving_coeff: 0.8\n",
+    "    TowerSE:\n",
+    "        flag: True\n",
+    "        wind: PowerWind  # Wind used\n",
+    "        gamma_f: 1.35    # Safety factor for fatigue loads\n",
+    "        gamma_m: 1.3     # Safety factor for material properties\n",
+    "        gamma_n: 1.0     # Safety factor for ...\n",
+    "        gamma_b: 1.1     # Safety factor for ...\n",
+    "        gamma_fatigue: 1.755  # Safety factor for fatigue loads\n",
+    "        buckling_method: dnvgl # Buckling code type [eurocode or dnvgl]\n",
+    "        buckling_length: 15    # Buckling parameter\n",
+    "        frame3dd:\n",
+    "            shear: True\n",
+    "            geom: True\n",
+    "            tol: 1e-9\n",
+    "    DriveSE:\n",
+    "        flag: True\n",
+    "    FloatingSE:\n",
+    "        flag: True\n",
+    "        symmetric_moorings: True\n",
+    "        gamma_f: 1.35    # Safety factor for fatigue loads\n",
+    "        gamma_m: 1.3     # Safety factor for material properties\n",
+    "        gamma_n: 1.0     # Safety factor for ...\n",
+    "        gamma_b: 1.1     # Safety factor for ...\n",
+    "        gamma_fatigue: 1.755  # Safety factor for fatigue loads\n",
+    "        rank_and_file: True\n",
+    "    BOS:\n",
+    "        flag: True\n",
+    "\n",
+    "OpenFAST: # Options for WEIS fidelity level 3 = nonlinear time domain\n",
+    "    flag: True\n",
+    "    simulation:\n",
+    "        DT: 0.01\n",
+    "        CompElast: 1\n",
+    "        CompInflow: 1\n",
+    "        CompAero: 2\n",
+    "        CompServo: 1\n",
+    "        CompHydro: 1\n",
+    "        CompSub: 0\n",
+    "        CompMooring: 3\n",
+    "        CompIce: 0\n",
+    "        OutFileFmt: 3\n",
+    "        NumCrctn: 1\n",
+    "    ElastoDyn:\n",
+    "        FlapDOF1: True\n",
+    "        FlapDOF2: True\n",
+    "        EdgeDOF: True\n",
+    "        TeetDOF: False\n",
+    "        DrTrDOF: False\n",
+    "        GenDOF: True\n",
+    "        YawDOF: False\n",
+    "        TwFADOF1 : True\n",
+    "        TwFADOF2 : True\n",
+    "        TwSSDOF1 : True\n",
+    "        TwSSDOF2 : True\n",
+    "        PtfmSgDOF: True\n",
+    "        PtfmSwDOF: True\n",
+    "        PtfmHvDOF: True\n",
+    "        PtfmRDOF : True\n",
+    "        PtfmPDOF : True\n",
+    "        PtfmYDOF : True\n",
+    "RAFT:\n",
+    "    flag: True\n",
+    "    potential_model_override: 0\n",
+    "    trim_ballast: 2\n",
+    "    heave_tol: 1\n",
+    "    save_designs: True\n",
+    "ROSCO:\n",
+    "    flag: True\n",
+    "    tuning_yaml: ../source/iea22_rosco.yaml\n",
+    "\n",
+    "DLC_driver:\n",
+    "    metocean_conditions:\n",
+    "        wind_speed: [4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24.]\n",
+    "        wave_height_NSS: [0.83, 0.88, 0.94, 1.03, 1.16, 1.34, 1.57, 1.86, 2.22, 2.62, 3.07]\n",
+    "        wave_period_NSS: [6.9, 6.96, 7.02, 7.12, 7.25, 7.43, 7.66, 7.94, 8.27, 8.63, 9.01]\n",
+    "        wave_height_SSS: [6.3, 8, 8, 8.1, 8.5, 8.5, 9.8, 9.8, 9.8, 9.8, 9.9]\n",
+    "        wave_period_SSS: [11.5, 12.7, 12.7, 12.8, 13.1, 13.1, 14.1, 14.1, 14.1, 14.1, 14.1]\n",
+    "        wave_height_1: 6.98\n",
+    "        wave_period_1: 11.7\n",
+    "        wave_height_50: 10.68\n",
+    "        wave_period_50: 14.2\n",
+    "    DLCs:\n",
+    "        - DLC: \"1.1\"\n",
+    "          n_seeds: 6\n",
+    "          transient_time: 120.0  # 0.\n",
+    "          analysis_time: 600.0  # 10.\n",
+    "```\n",
+    "\n",
+    "**Key Integration Elements:**\n",
+    "- **OpenFAST**: Full aeroelastic simulation with all relevant DOFs enabled\n",
+    "- **RAFT**: Frequency-domain analysis for platform initialization\n",
+    "- **ROSCO**: Controller integration with baseline tuning file\n",
+    "- **DLC Driver**: Design Load Case 1.1 (normal operation) with realistic metocean conditions\n",
+    "- **WISDEM**: All structural analysis modules activated for comprehensive modeling\n",
+    "\n",
+    "This configuration represents WEIS's highest fidelity level, combining time-domain aeroelastic simulation with controller optimization for floating offshore wind turbines."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "81eadf85",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# lets overide a few things so that we dont distrupt the existing results.\n",
+    "analysis_override = {}\n",
+    "analysis_override['general'] = {}\n",
+    "analysis_override['general']['folder_output'] = 'outputsCh2'\n",
+    "analysis_override['driver'] = {}\n",
+    "analysis_override['driver']['optimization'] = {}\n",
+    "analysis_override['driver']['optimization']['max_iter'] = 1 # only run one iteration for this demo, we have precomputed the solutions for you :)\n",
+    "\n",
+    "\n",
+    "# modeling_override = {}\n",
+    "# modeling_override['DLC_driver'] = {}\n",
+    "# modeling_override['DLC_driver']['DLCs'] = [\n",
+    "#     {'DLC': \"1.1\",\n",
+    "#      'n_seeds': 1,\n",
+    "#      'wind_speed': [20.0],\n",
+    "#      'transient_time': 10.0,\n",
+    "#      'analysis_time': 30.0}]\n",
+    "\n",
+    "# Reference: examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_driver.py\n",
+    "\n",
+    "control_20mw, modeling_options, opt_options = weis_main(fname_wt_input, \n",
+    "                                                 fname_modeling_options, \n",
+    "                                                 fname_analysis_options,\n",
+    "                                                 analysis_override=analysis_override,\n",
+    "                                                #  modeling_override=modeling_override,\n",
+    "                                                 test_run=True\n",
+    "                                                 )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c6d100c8",
+   "metadata": {},
+   "source": [
+    "## 2.1: Controller Optimization Results Analysis\n",
+    "\n",
+    "Now we'll examine the controller optimization convergence using precomputed results. The optimization minimized tower base damage equivalent loads while satisfying rotor overspeed constraints.\n",
+    "\n",
+    "### What to Look For\n",
+    "\n",
+    "**Objective Function Behavior:**\n",
+    "- `aeroelastic.DEL_TwrBsMyt`: Tower base fore-aft damage equivalent loads (our primary objective)\n",
+    "- `aeroelastic.rotor_overspeed`: Constraint ensuring safe operational limits\n",
+    "\n",
+    "**Controller Parameter Evolution:**\n",
+    "- `tune_rosco_ivc.omega_pc`: Pitch controller natural frequency optimization\n",
+    "- `tune_rosco_ivc.zeta_pc`: Pitch controller damping ratio optimization  \n",
+    "- `tune_rosco_ivc.Kp_float`: Floating platform feedback gain tuning\n",
+    "- `tune_rosco_ivc.ptfm_freq`: Platform frequency parameter for filtering\n",
+    "\n",
+    "<!-- **Internal Controller Gains:**\n",
+    "- `sse_tune.tune_rosco.PC_Kp`: Proportional gain from ROSCO tuning\n",
+    "- `sse_tune.tune_rosco.PC_Ki`: Integral gain from ROSCO tuning -->\n",
+    "\n",
+    "The convergence plots will show how the optimizer balanced load reduction with operational constraints, demonstrating the effectiveness of controller co-design for floating offshore wind turbines."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1755e26e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "use_precomputed_outputs = False\n",
+    "if use_precomputed_outputs:\n",
+    "    output_folder = 'outputs_preCompute'\n",
+    "else:\n",
+    "    output_folder = 'outputsCh2'\n",
+    "\n",
+    "rec_data = load_OMsql(os.path.join(this_dir,'..','1_drivers', stageFolder, output_folder, \"log_opt.sql\")) # not sure what supresses the output here\n",
+    "plot_convergence(\n",
+    "        rec_data, \n",
+    "        [\n",
+    "                'aeroelastic.DEL_TwrBsMyt', \n",
+    "                'aeroelastic.rotor_overspeed',  \n",
+    "                'tune_rosco_ivc.Kp_float', \n",
+    "                'tune_rosco_ivc.omega_pc',\n",
+    "                'tune_rosco_ivc.ptfm_freq', \n",
+    "                'tune_rosco_ivc.zeta_pc'\n",
+    "        ],\n",
+    "        )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2d959a33",
+   "metadata": {},
+   "source": [
+    "## Stage 3: Floating Platform Optimization with RAFT\n",
+    "\n",
+    "### Multi-Fidelity Platform Design Approach\n",
+    "\n",
+    "Following the methodology from **Zalkind et al. (2024)** \"Control Co-Design Studies for a 22 MW Semisubmersible Floating Wind Turbine Platform\" (DOI: 10.1088/1742-6596/2767/8/082020), we implement a systematic multi-fidelity approach:\n",
+    "\n",
+    "#### Phase 1: RAFT-Based Platform Sizing\n",
+    "- **Tool**: RAFT frequency-domain analysis\n",
+    "- **Purpose**: Rapid initial sizing and optimization of the semisubmersible platform\n",
+    "- **Advantages**: Fast computation allows extensive design space exploration\n",
+    "- **Focus**: Hydrostatic stability, natural periods, and basic motion responses\n",
+    "\n",
+    "#### Phase 2: OpenFAST High-Fidelity Refinement  \n",
+    "- **Tool**: OpenFAST time-domain aeroelastic simulation\n",
+    "- **Purpose**: Detailed load analysis and platform optimization with full system interactions\n",
+    "- **Advantages**: Captures nonlinear effects, controller interactions, and realistic loads\n",
+    "- **Focus**: Fatigue loads, extreme responses, and coupled dynamics\n",
+    "\n",
+    "#### Phase 3: Integrated Co-Design (Optional)\n",
+    "- **Tool**: OpenFAST time-domain aeroelastic simulation\n",
+    "- **Approach**: Simultaneous optimization of platform and controller parameters\n",
+    "- **Benefits**: Captures synergistic effects between platform design and control strategy\n",
+    "- **Complexity**: Higher computational cost but potentially superior performance\n",
+    "\n",
+    "### Platform Design Objectives\n",
+    "\n",
+    "**Primary Goals:**\n",
+    "- Minimize platform structural mass (cost reduction)\n",
+    "- Ensure adequate stability margins\n",
+    "- Control platform motions within acceptable limits\n",
+    "- Satisfy manufacturing and installation constraints\n",
+    "\n",
+    "**Key Design Variables:**\n",
+    "- Platform geometry (member dimensions, spacing)\n",
+    "\n",
+    "This systematic approach demonstrates how WEIS enables efficient platform design by leveraging the appropriate fidelity level for each design phase."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6172cf0a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Setting up file paths\n",
+    "stageFolder = \"stage-3-semisub\" # First the RAFT optimization\n",
+    "\n",
+    "fname_wt_input = os.path.join(this_dir,\"..\", \"2_models\", \"stage-2-controller_v2p0.yaml\")\n",
+    "fname_modeling_options = os.path.join(this_dir,\"..\", \"1_drivers\", stageFolder, f\"stage-3-semisub_raft_modeling.yaml\")\n",
+    "fname_analysis_options = os.path.join(this_dir,\"..\", \"1_drivers\", stageFolder, f\"stage-3-semisub_raft_analysis.yaml\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c1a329fd",
+   "metadata": {},
+   "source": [
+    "## RAFT Platform Optimization Configuration\n",
+    "\n",
+    "### Input File Setup and Analysis Configuration\n",
+    "\n",
+    "We're now setting up the RAFT-based floating platform optimization using the controller-optimized turbine from Stage 2. This configuration demonstrates WEIS's ability to perform rapid platform design iterations using frequency-domain analysis.\n",
+    "\n",
+    "### Analysis Options Configuration\n",
+    "\n",
+    "The analysis configuration defines our semisubmersible platform optimization problem with realistic design variables and constraints:\n",
+    "\n",
+    "```yaml\n",
+    "design_variables:\n",
+    "    floating:\n",
+    "        joints:\n",
+    "            flag: True\n",
+    "            z_coordinate:       # draft\n",
+    "                - names: [main_keel, col1_keel, col2_keel, col3_keel]\n",
+    "                  lower_bound: -30.0\n",
+    "                  upper_bound: -12.0\n",
+    "            r_coordinate:\n",
+    "                - names: [col1_keel, col1_freeboard, col2_keel, col2_freeboard, col3_keel, col3_freeboard]\n",
+    "                  lower_bound: 35.0\n",
+    "                  upper_bound: 75.0\n",
+    "        members:\n",
+    "            flag: True\n",
+    "            groups:\n",
+    "                - names: [column1, column2, column3]\n",
+    "                  diameter:\n",
+    "                      lower_bound: 10.0\n",
+    "                      upper_bound: 16.0\n",
+    "                      constant: True\n",
+    "\n",
+    "constraints:\n",
+    "    floating:\n",
+    "        survival_heel:\n",
+    "            upper_bound: 0.17453292519943295 # 10 deg\n",
+    "        metacentric_height:\n",
+    "            flag: True\n",
+    "            lower_bound: 1.0 # 15.0 --> Dan's experience\n",
+    "        pitch_period:\n",
+    "            flag: True\n",
+    "            lower_bound: 20. # +/- 10%\n",
+    "            upper_bound: 80.\n",
+    "        heave_period:\n",
+    "            flag: True\n",
+    "            lower_bound: 16. # +/- 10%\n",
+    "            upper_bound: 80.\n",
+    "        fixed_ballast_capacity:\n",
+    "            flag: True\n",
+    "        variable_ballast_capacity:\n",
+    "            flag: True\n",
+    "        freeboard_margin:   # keep freeboard from being submerged below water during survival_heel, largest wave\n",
+    "            flag: True\n",
+    "        draft_margin:   # keep draft from raising above water line during survival_heel, largest wave\n",
+    "            flag: True\n",
+    "        fairlead_depth: # keep fairlead above bottom trough of largest wave\n",
+    "            flag: True\n",
+    "    control:\n",
+    "        Max_PtfmPitch:\n",
+    "            flag: True\n",
+    "            max: 6.0\n",
+    "        nacelle_acceleration:\n",
+    "            flag: True\n",
+    "            max: 0.4 # Change to 2.0 with new raft # prob wont be active with RAFT, maybe change to 0.5 in the future?\n",
+    "\n",
+    "merit_figure: structural_mass\n",
+    "```\n",
+    "\n",
+    "**Key Design Variables:**\n",
+    "- **Platform Draft (z_coordinate)**: Vertical position of platform elements (-30m to -12m)\n",
+    "- **Column Spacing (r_coordinate)**: Radial distance of columns from center (35m to 75m)  \n",
+    "- **Column Diameter**: Outer diameter of the three main columns (10m to 16m)\n",
+    "\n",
+    "<!-- **Critical Constraints:**\n",
+    "- **Survival Heel**: Maximum allowable heel angle during extreme conditions (≤10°)\n",
+    "- **Metacentric Height**: Stability margin ensuring positive restoring moments (≥1.0m)\n",
+    "- **Natural Periods**: Heave (16-80s) and pitch (20-80s) periods to avoid wave resonance\n",
+    "- **Operational Limits**: Platform pitch (≤6°) and nacelle acceleration (≤0.4 m/s²) during operation -->\n",
+    "\n",
+    "### Modeling Options Configuration\n",
+    "\n",
+    "The modeling configuration enables RAFT's frequency-domain analysis with realistic environmental conditions:\n",
+    "\n",
+    "```yaml\n",
+    "RAFT:\n",
+    "    flag: True\n",
+    "    potential_model_override: 0\n",
+    "    trim_ballast: 2\n",
+    "    heave_tol: 1\n",
+    "    save_designs: True\n",
+    "ROSCO:\n",
+    "    flag: True\n",
+    "    tuning_yaml: ../source/iea22_rosco.yaml\n",
+    "DLC_driver:\n",
+    "    metocean_conditions:\n",
+    "        wind_speed: [4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24.]\n",
+    "        wave_height_NSS: [0.83, 0.88, 0.94, 1.03, 1.16, 1.34, 1.57, 1.86, 2.22, 2.62, 3.07]\n",
+    "        wave_period_NSS: [6.9, 6.96, 7.02, 7.12, 7.25, 7.43, 7.66, 7.94, 8.27, 8.63, 9.01]\n",
+    "        wave_height_SSS: [6.3, 8, 8, 8.1, 8.5, 8.5, 9.8, 9.8, 9.8, 9.8, 9.9]\n",
+    "        wave_period_SSS: [11.5, 12.7, 12.7, 12.8, 13.1, 13.1, 14.1, 14.1, 14.1, 14.1, 14.1]\n",
+    "        wave_height_1: 6.98\n",
+    "        wave_period_1: 11.7\n",
+    "        wave_height_50: 10.68\n",
+    "        wave_period_50: 14.2\n",
+    "    DLCs:\n",
+    "        - DLC: \"1.6\"\n",
+    "          analysis_time: 600.\n",
+    "          transient_time: 120.\n",
+    "        - DLC: \"6.1\"\n",
+    "          analysis_time: 600.\n",
+    "          transient_time: 120.\n",
+    "```\n",
+    "\n",
+    "**RAFT Configuration:**\n",
+    "- **Potential Model**: 0 setting uses only Morison elements for hydrodynamics\n",
+    "- **Trim Ballast**: Automatically adjusts ballast to maintain zero mean heave\n",
+    "- **Design Load Cases**: DLC 1.6 (normal operation with severe sea state) and DLC 6.1 (parked, with 50-year wind and wave conditions)\n",
+    "\n",
+    "<!-- **Environmental Conditions:**\n",
+    "- **Normal Sea States (NSS)**: Operational conditions with moderate waves\n",
+    "- **Severe Sea States (SSS)**: Extreme conditions for survival analysis\n",
+    "- **Wave Heights**: Range from 0.83m to 10.68m covering operational to extreme conditions -->\n",
+    "\n",
+    "Since RAFT's frequency-domain analysis has significantly lower computational cost than OpenFAST's time-domain simulation, we can efficiently explore the platform design space while maintaining reasonable execution times for this workshop demonstration."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "774221b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# lets overide a few things so that we dont distrupt the existing results.\n",
+    "analysis_override = {}\n",
+    "analysis_override['general'] = {}\n",
+    "analysis_override['general']['folder_output'] = 'outputsCh2'\n",
+    "analysis_override['driver'] = {}\n",
+    "analysis_override['driver']['optimization'] = {}\n",
+    "analysis_override['driver']['optimization']['max_iter'] = 1 # only run one iteration for this demo, we have precomputed the solutions for you :)\n",
+    "\n",
+    "\n",
+    "control_20mw, modeling_options, opt_options = weis_main(fname_wt_input, \n",
+    "                                                 fname_modeling_options, \n",
+    "                                                 fname_analysis_options,\n",
+    "                                                 analysis_override=analysis_override,\n",
+    "                                                #  modeling_override=modeling_override,\n",
+    "                                                 test_run=False\n",
+    "                                                 )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cd6fb7a2",
+   "metadata": {},
+   "source": [
+    "## Results Analysis\n",
+    "\n",
+    "### Understanding the RAFT Optimization Convergence\n",
+    "\n",
+    "The convergence plots show the evolution of key platform design parameters and constraints during the RAFT-based optimization. This frequency-domain analysis provides rapid insights into platform behavior while maintaining computational efficiency.\n",
+    "\n",
+    "### Key Metrics to Analyze\n",
+    "\n",
+    "**Platform Motion Responses:**\n",
+    "- **`raft.Max_PtfmPitch`**: Maximum platform pitch angle - should remain within acceptable limits (≤6°)\n",
+    "- **`raft.max_nac_accel`**: Maximum nacelle acceleration - critical for component fatigue (≤0.4 m/s²)\n",
+    "- **`raft.heave_period`**: Platform heave natural period - must avoid wave resonance (16-80s)\n",
+    "- **`raft.pitch_period`**: Platform pitch natural period - must also avoid wave resonance (16-80s)\n",
+    "<!-- \n",
+    "**Platform Stability and Safety:**\n",
+    "- **`floatingse.metacentric_height_pitch/roll`**: Stability margins ensuring positive restoring moments\n",
+    "- **`floatingse.constr_draft_heel_margin`**: Safety margin against excessive heel during storms\n",
+    "- **`floatingse.constr_freeboard_heel_margin`**: Prevents deck submersion during extreme conditions\n",
+    "- **`floatingse.constr_fairlead_wave`**: Mooring fairlead depth relative to wave action -->\n",
+    "\n",
+    "**Platform Structural Design:**\n",
+    "- **`floatingse.system_structural_mass`**: Structural mass of platform (without water ballast) - primary objective to minimize\n",
+    "- **`floating.jointdv_0/1`**: Platform geometry design variables (draft and column spacing)\n",
+    "- **`floating.memgrp1.outer_diameter_in`**: Column diameter optimization\n",
+    "\n",
+    "<!-- **Constraint Management:**\n",
+    "- **`floatingse.constr_fixed_margin`**: Fixed ballast capacity constraints\n",
+    "- **`floatingse.constr_variable_margin`**: Variable ballast capacity constraints -->\n",
+    "\n",
+    "<!-- ### What to Look For in the Results\n",
+    "\n",
+    "**Successful Optimization Indicators:**\n",
+    "1. **Decreasing objective function** (`floatingse.system_structural_mass`) showing mass reduction\n",
+    "2. **Satisfied constraints** with positive margins indicating feasible designs\n",
+    "3. **Stable natural periods** within acceptable ranges avoiding resonance\n",
+    "4. **Controlled motion responses** meeting operational requirements\n",
+    "\n",
+    "**Design Trade-offs:**\n",
+    "- Smaller platforms (lower mass) vs. stability requirements\n",
+    "- Column spacing optimization balancing stability and structural efficiency  \n",
+    "- Platform draft affecting both stability and manufacturing constraints -->\n",
+    "\n",
+    "This RAFT analysis provides the foundation for subsequent high-fidelity OpenFAST optimization, where time-domain effects and controller interactions will be captured."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fa437559",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "use_precomputed_outputs = True\n",
+    "if use_precomputed_outputs:\n",
+    "    output_folder = 'outputs_preCompute'\n",
+    "else:\n",
+    "    output_folder = 'outputsCh2'\n",
+    "\n",
+    "rec_data = load_OMsql(os.path.join(this_dir,'..','1_drivers', stageFolder, output_folder, \"log_opt.sql\")) \n",
+    "\n",
+    "plot_convergence(\n",
+    "    rec_data, \n",
+    "    [\n",
+    "        'raft.Max_PtfmPitch', \n",
+    "        'raft.heave_period', \n",
+    "        'raft.max_nac_accel', \n",
+    "        'raft.pitch_period', \n",
+    "        'floatingse.constr_draft_heel_margin',  # will the bottom of the platform leave the water? 1 = yes\n",
+    "        # 'floatingse.constr_fairlead_wave', \n",
+    "        # 'floatingse.constr_fixed_margin', \n",
+    "        # 'floatingse.constr_freeboard_heel_margin', \n",
+    "        'floatingse.metacentric_height_pitch', \n",
+    "        # 'floatingse.metacentric_height_roll', \n",
+    "        'floatingse.constr_variable_margin',   # is there sufficient volume in the variable ballast chambers?  1 = no\n",
+    "        'floatingse.system_structural_mass', \n",
+    "        'floating.jointdv_0',   # draft\n",
+    "        'floating.jointdv_1',   # column spacing\n",
+    "        'floating.memgrp1.outer_diameter_in'  # outer column diameter\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1507509e",
+   "metadata": {},
+   "source": [
+    "## Stage 3: High-Fidelity Platform Optimization with OpenFAST\n",
+    "\n",
+    "### Transitioning from RAFT to OpenFAST Analysis\n",
+    "\n",
+    "Having established an initial platform design using RAFT's efficient frequency-domain analysis, we now advance to OpenFAST for high-fidelity time-domain optimization. This represents the second phase of our multi-fidelity platform design methodology.\n",
+    "\n",
+    "### Why OpenFAST Refinement is Essential\n",
+    "\n",
+    "**Limitations of RAFT Analysis:**\n",
+    "- **Linear Assumptions**: RAFT uses linearized hydrodynamics and simplified aerodynamics\n",
+    "- **No Controller Interactions**: Cannot capture the complex feedback between platform motion and control system\n",
+    "- **Limited Load Assessment**: Frequency-domain analysis misses important nonlinear effects and transient responses\n",
+    "- **Simplified Environmental Modeling**: Less comprehensive representation of wind-wave interactions\n",
+    "\n",
+    "**OpenFAST Capabilities:**\n",
+    "- **Nonlinear Time-Domain Simulation**: Captures full system dynamics including large motions and nonlinearities\n",
+    "- **Integrated Controller Analysis**: Includes ROSCO controller interactions with platform motion\n",
+    "- **Comprehensive Load Evaluation**: Full Design Load Case (DLC) analysis for realistic loading conditions\n",
+    "- **Coupled Physics**: Simultaneous aerodynamics, hydrodynamics, structural dynamics, and control system modeling\n",
+    "\n",
+    "<!-- ### OpenFAST Optimization Objectives\n",
+    "\n",
+    "**Enhanced Design Goals:**\n",
+    "- **Fatigue Load Management**: Minimize damage equivalent loads considering long-term operation\n",
+    "- **Extreme Response Control**: Ensure survival under design storm conditions\n",
+    "- **Controller-Platform Integration**: Optimize platform design considering control system interactions\n",
+    "- **System-Level Performance**: Balance platform cost, motion performance, and overall system efficiency\n",
+    "\n",
+    "**Key Differences from RAFT Optimization:**\n",
+    "- **More Detailed Environmental Conditions**: Full DLC suite including turbulent wind and irregular waves\n",
+    "- **Controller Feedback Effects**: Platform motion influences controller behavior, which affects structural loads\n",
+    "- **Nonlinear Dynamics**: Large amplitude motions, mooring nonlinearities, and aerodynamic stall effects\n",
+    "- **Comprehensive Load Channels**: Tower base loads, blade root loads, mooring tensions, and platform accelerations -->\n",
+    "\n",
+    "<!-- ### Multi-Fidelity Design Philosophy\n",
+    "\n",
+    "This OpenFAST optimization builds upon the RAFT results, using the frequency-domain optimized design as a starting point for high-fidelity refinement. This systematic approach:\n",
+    "\n",
+    "1. **Leverages RAFT Efficiency**: Initial design space exploration completed rapidly\n",
+    "2. **Applies OpenFAST Precision**: Detailed optimization with full system physics\n",
+    "3. **Validates Design Assumptions**: Confirms that frequency-domain insights hold under realistic conditions\n",
+    "4. **Refines for Real-World Performance**: Accounts for all relevant physics and operational scenarios -->\n",
+    "\n",
+    "This methodology demonstrates WEIS's capability to seamlessly integrate multiple analysis fidelities, enabling both efficient design exploration and detailed engineering validation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6d73ba82",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Setting up file paths\n",
+    "stageFolder = \"stage-3-semisub\"\n",
+    "\n",
+    "fname_wt_input = os.path.join(this_dir,\"..\", \"2_models\", \"stage-2-controller_v2p0.yaml\")\n",
+    "\n",
+    "\n",
+    "## File management\n",
+    "fname_wt_input = os.path.join(this_dir, \"..\", \"2_models\", \"stage-3-semisub_raft_v2p0.yaml\")\n",
+    "fname_modeling_options = os.path.join(this_dir, \"..\", \"1_drivers\", stageFolder, \"stage-3-semisub_of_modeling.yaml\") # Compare to examples/03_design_with_openfast/iea22_ptfm_opt_analysis.yaml\n",
+    "fname_analysis_options = os.path.join(this_dir, \"..\", \"1_drivers\", stageFolder, \"stage-3-semisub_of_analysis.yaml\") # Compare to examples/03_design_with_openfast/iea22_ptfm_opt_modeling.yaml"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9285b5d8",
+   "metadata": {},
+   "source": [
+    "## Inputs for OpenFAST Platform Optimization\n",
+    "\n",
+    "### Analysis Options Configuration (important parts only):\n",
+    "``` yaml\n",
+    "    control:\n",
+    "        Max_PtfmPitch:\n",
+    "            flag: True\n",
+    "            max: 6.0\n",
+    "        Std_PtfmPitch:\n",
+    "            flag: True\n",
+    "            max: 1.25  # Same as IEA-15MW with same DLCs\n",
+    "        nacelle_acceleration:\n",
+    "            flag: True\n",
+    "            max: 2.0\n",
+    "\n",
+    "\n",
+    "```\n",
+    "\n",
+    "### Modeling Options Configuration (important parts only):\n",
+    "``` yaml\n",
+    "OpenFAST:\n",
+    "    flag: True\n",
+    "[...]\n",
+    "RAFT:\n",
+    "    flag: False\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2ab6c9d3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# lets overide a few things so that we dont distrupt the existing results.\n",
+    "analysis_override = {}\n",
+    "analysis_override['general'] = {}\n",
+    "analysis_override['general']['folder_output'] = 'outputsCh2_OF'\n",
+    "\n",
+    "control_20mw, modeling_options, opt_options = weis_main(fname_wt_input, \n",
+    "                                                 fname_modeling_options, \n",
+    "                                                 fname_analysis_options,\n",
+    "                                                 analysis_override=analysis_override,\n",
+    "                                                 test_run=True\n",
+    "                                                 )\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "604d3198",
+   "metadata": {},
+   "source": [
+    "## Analyzing the results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e1fe2215",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "use_precomputed_outputs = False\n",
+    "if use_precomputed_outputs:\n",
+    "    output_folder = 'outputs_of_preCompute'\n",
+    "else:\n",
+    "    output_folder = 'outputsCh2_OF'\n",
+    "\n",
+    "rec_data = load_OMsql(os.path.join(this_dir,'..','1_drivers', stageFolder, output_folder, \"log_opt.sql\")) # not sure what supresses the output here\n",
+    "\n",
+    "plot_convergence(\n",
+    "    rec_data, \n",
+    "    [\n",
+    "        'aeroelastic.Max_PtfmPitch',    # note aeroelastic comes from OpenFAST\n",
+    "        'aeroelastic.max_nac_accel', \n",
+    "        'floatingse.heave_period', \n",
+    "        'floatingse.pitch_period', \n",
+    "        # 'floatingse.constr_draft_heel_margin', \n",
+    "        'floatingse.constr_fairlead_wave',   # will the fairleads leave the water? 1 = yes\n",
+    "        # 'floatingse.constr_fixed_margin', \n",
+    "        # 'floatingse.constr_freeboard_heel_margin', \n",
+    "        # 'floatingse.metacentric_height_pitch', \n",
+    "        # 'floatingse.metacentric_height_roll', \n",
+    "        # 'floatingse.constr_variable_margin', \n",
+    "        'floatingse.system_structural_mass', \n",
+    "        'floating.jointdv_0', \n",
+    "        'floating.jointdv_1', \n",
+    "        'floating.memgrp1.outer_diameter_in'\n",
+    "    ]\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "84f1aa2a",
+   "metadata": {},
+   "source": [
+    "## Loading in a CCD case\n",
+    "\n",
+    "We ran an additional case where we optimized the platform and controller at the same time. This is a more expensive optimization, but it captures the interaction between the platform design and the controller design.\n",
+    "\n",
+    "Lets briefly look at the results."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4edc2de8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "use_precomputed_outputs = True\n",
+    "\n",
+    "if use_precomputed_outputs:\n",
+    "    output_folder = 'outputs_of_preCompute'\n",
+    "\n",
+    "    stageFolder = \"stage-3.5-semisubCCD\" # First the RAFT optimization\n",
+    "\n",
+    "    rec_data = load_OMsql(os.path.join(this_dir, \"..\", \"1_drivers\", stageFolder, output_folder, \"log_opt.sql\")) # not sure what supresses the output here\n",
+    "    plot_convergence(rec_data, ['aeroelastic.Max_PtfmPitch', 'aeroelastic.Std_PtfmPitch', 'aeroelastic.max_nac_accel', \n",
+    "                                'aeroelastic.rotor_overspeed', 'raft.heave_period', 'raft.pitch_period', \n",
+    "                                'sse_tune.tune_rosco.PC_Ki', 'sse_tune.tune_rosco.PC_Kp', 'tune_rosco_ivc.Kp_float', \n",
+    "                                'tune_rosco_ivc.omega_pc', 'tune_rosco_ivc.ptfm_freq', 'tune_rosco_ivc.zeta_pc', \n",
+    "                                'floatingse.constr_draft_heel_margin', 'floatingse.constr_fairlead_wave', \n",
+    "                                'floatingse.constr_fixed_margin', 'floatingse.constr_freeboard_heel_margin', \n",
+    "                                'floatingse.metacentric_height_pitch', 'floatingse.metacentric_height_roll', \n",
+    "                                'floatingse.constr_variable_margin', 'floatingse.system_structural_mass', \n",
+    "                                'floating.jointdv_0', 'floating.jointdv_1', 'floating.memgrp1.outer_diameter_in'])\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7e6fe742",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "weis-eni",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_analysis.yaml b/examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_analysis.yaml
new file mode 100644
index 000000000..91e49eced
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_analysis.yaml
@@ -0,0 +1,52 @@
+general:
+    folder_output: outputs/05_rosco_opt
+    fname_output: iea15mw
+design_variables:
+  control:
+    servo:
+      pitch_control:
+          omega:
+            flag: True
+            min: 0.1
+            max: 0.5
+          zeta:
+            flag: True
+            min: 0.1
+            max: 3.0
+          Kp_float:
+            flag: True
+            min: -40
+            max: 0
+          ptfm_freq:
+            flag: True
+            max: 0.4
+
+merit_figure: DEL_TwrBsMyt  # Merit figure of the optimization problem. The options are 'AEP' - 'LCOE' - 'Cp' - 'blade_mass' - 'blade_tip_deflection'
+
+constraints:
+  control:
+    rotor_overspeed:
+      flag: True
+      min: 0.0
+      max: 0.2
+
+driver:
+  optimization:
+    flag: True
+    tol: 1.e-2            # Optimality tolerance
+    max_major_iter: 2     # Maximum number of major design iterations (SNOPT)
+    max_minor_iter: 100   # Maximum number of minor design iterations (SNOPT)
+    max_iter: 2          # Maximum number of iterations (SLSQP)
+    solver: LN_COBYLA         # Optimization solver. Other options are 'SLSQP' - 'CONMIN'
+    step_size: 1.e-3      # Step size for finite differencing
+    form: forward         # Finite differencing mode, either forward or central
+  design_of_experiments:
+    flag: False            # Flag to enable design of experiments
+    run_parallel: False    # Flag to run using parallel processing
+    generator: LatinHypercube    # Type of input generator. (Uniform)
+    num_samples: 8        # number of samples for (Uniform only)
+    criterion: center
+
+recorder:
+    flag: True             # Flag to activate OpenMDAO recorder
+    file_name: log_opt.sql  # Name of OpenMDAO recorder
diff --git a/examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_driver.py b/examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_driver.py
new file mode 100644
index 000000000..7ad41596c
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_driver.py
@@ -0,0 +1,21 @@
+#!/usr/bin/env python3
+import os
+from weis import weis_main
+from openmdao.utils.mpi import MPI
+
+# TEST_RUN will reduce the number and duration of simulations
+TEST_RUN = True
+
+## File management
+run_dir = os.path.dirname( os.path.realpath(__file__) )
+fname_wt_input = os.path.join(run_dir, "..", "..", "2_models", "stage-1-aeroStruct-aero_analysis_v2p0.yaml")
+fname_modeling_options = os.path.join(run_dir, "stage-2-controller_modeling.yaml") # compare to examples/05_control_optimization/rosco_opt_modeling.yaml
+fname_analysis_options = os.path.join(run_dir, "stage-2-controller_analysis.yaml") # same as examples/05_control_optimization/rosco_opt_analysis.yaml
+
+wt_opt, modeling_options, analysis_options = weis_main(
+    fname_wt_input, 
+    fname_modeling_options, 
+    fname_analysis_options,
+    test_run=TEST_RUN,
+    )
+
diff --git a/examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_modeling.yaml b/examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_modeling.yaml
new file mode 100644
index 000000000..35dde45e7
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-2-controller/stage-2-controller_modeling.yaml
@@ -0,0 +1,121 @@
+General:
+    verbosity: False  # When set to True, the code prints to screen many infos
+    openfast_configuration:
+        use_exe: True
+        allow_fails: True
+        fail_value: 9999
+        write_stdout: True
+
+Environment:
+    air_density: 1.225
+    air_dyn_viscosity: 1.81e-5
+    weib_shape_parameter: 2.
+    air_speed_sound: 340.
+    shear_exp: 0.12
+    water_density: 1025.0
+    water_dyn_viscosity: 1.3351e-3
+    soil_shear_modulus: 140.e+6
+    soil_poisson: 0.4
+    water_depth: 200.0
+    significant_wave_height: 4.52
+    significant_wave_period: 9.45
+
+WISDEM:
+    RotorSE:
+        flag: True
+        n_pitch_perf_surfaces: 20
+        n_tsr_perf_surfaces: 20
+        spar_cap_ss: spar_cap_ss
+        spar_cap_ps: spar_cap_ps
+        peak_thrust_shaving: True
+        thrust_shaving_coeff: 0.8
+    TowerSE:
+        flag: True
+        wind: PowerWind  # Wind used
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        buckling_method: dnvgl # Buckling code type [eurocode or dnvgl]
+        buckling_length: 15    # Buckling parameter
+        frame3dd:
+            shear: True
+            geom: True
+            tol: 1e-9
+    DriveSE:
+        flag: True
+    FloatingSE:
+        flag: True
+        symmetric_moorings: True
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        rank_and_file: True
+    BOS:
+        flag: True
+    LCOE:
+        flag: True
+        wake_loss_factor: 0.15
+        fixed_charge_rate: 0.056
+        bos_per_kW: 4053.
+        opex_per_kW: 137.
+        turbine_number: 40.
+        labor_rate: 58.8
+        painting_rate: 30.0
+
+
+
+OpenFAST: # Options for WEIS fidelity level 3 = nonlinear time domain
+    flag: True
+    simulation:
+        DT: 0.01
+        CompElast: 1
+        CompInflow: 1
+        CompAero: 2
+        CompServo: 1
+        CompHydro: 1
+        CompSub: 0
+        CompMooring: 3
+        CompIce: 0
+        OutFileFmt: 3
+        NumCrctn: 1
+    ElastoDyn:
+        FlapDOF1: True
+        FlapDOF2: True
+        EdgeDOF: True
+        TeetDOF: False
+        DrTrDOF: False
+        GenDOF: True
+        YawDOF: False
+        TwFADOF1 : True
+        TwFADOF2 : True
+        TwSSDOF1 : True
+        TwSSDOF2 : True
+        PtfmSgDOF: True
+        PtfmSwDOF: True
+        PtfmHvDOF: True
+        PtfmRDOF : True
+        PtfmPDOF : True
+        PtfmYDOF : True
+
+ROSCO:
+    flag: True
+    tuning_yaml: ../../2_models/iea22_rosco.yaml
+
+DLC_driver:
+    metocean_conditions:
+        wind_speed: [4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24.]
+        wave_height_NSS: [0.83, 0.88, 0.94, 1.03, 1.16, 1.34, 1.57, 1.86, 2.22, 2.62, 3.07]
+        wave_period_NSS: [6.9, 6.96, 7.02, 7.12, 7.25, 7.43, 7.66, 7.94, 8.27, 8.63, 9.01]
+        wave_height_SSS: [6.3, 8, 8, 8.1, 8.5, 8.5, 9.8, 9.8, 9.8, 9.8, 9.9]
+        wave_period_SSS: [11.5, 12.7, 12.7, 12.8, 13.1, 13.1, 14.1, 14.1, 14.1, 14.1, 14.1]
+        wave_height_1: 6.98
+        wave_period_1: 11.7
+        wave_height_50: 10.68
+        wave_period_50: 14.2
+    DLCs:
+        - DLC: "1.1"
+          n_seeds: 3
\ No newline at end of file
diff --git a/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_analysis.yaml b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_analysis.yaml
new file mode 100644
index 000000000..7298bdc3a
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_analysis.yaml
@@ -0,0 +1,110 @@
+general:
+    folder_output: outputs_of_newFix
+    fname_output: stage-3-semisub_of
+
+design_variables:
+    floating:
+        joints:
+            z_coordinate:       # draft
+                - names: [main_keel, col1_keel, col2_keel, col3_keel]
+                  flag: True
+                  lower_bound: -30.0
+                  upper_bound: -12.0
+                # - names: [col1_freeboard, col2_freeboard, col3_freeboard]
+                #   lower_bound: 10.0
+                #   upper_bound: 20.0
+            r_coordinate:
+                - names: [col1_keel, col1_freeboard, col2_keel, col2_freeboard, col3_keel, col3_freeboard]
+                  flag: True
+                  lower_bound: 35.0
+                  upper_bound: 75.0
+        members:
+            groups:
+                - names: [column1, column2, column3]
+                  flag: True
+                  diameter:
+                      lower_bound: 8.0
+                      upper_bound: 16.0
+                      constant: True
+
+constraints:
+    tower:
+        height_constraint:
+            flag: False
+            lower_bound: 1.e-2
+            upper_bound: 1.e-2
+        stress:
+            flag: False
+        global_buckling:
+            flag: False
+        shell_buckling:
+            flag: False
+        d_to_t:
+            flag: False
+            lower_bound: 120.0
+            upper_bound: 2000.0
+        taper:
+            flag: False
+            lower_bound: 0.2
+        slope:
+            flag: False
+        frequency_1:
+            flag: False
+            lower_bound: 0.37
+    floating:
+        survival_heel:
+            upper_bound: 0.17453292519943295 # 10 deg
+        metacentric_height:
+            flag: True
+            lower_bound: 15.0
+        pitch_period:
+            flag: True
+            lower_bound: 20. # +/- 10%
+            upper_bound: 80.
+        heave_period:
+            flag: True
+            lower_bound: 16. # +/- 10%
+            upper_bound: 80.
+        fixed_ballast_capacity:
+            flag: True
+        variable_ballast_capacity:
+            flag: True
+        buoyancy:
+            flag: False
+        stress:
+            flag: False
+        global_buckling:
+            flag: False
+        shell_buckling:
+            flag: False
+        mooring_heel:
+            flag: False
+        freeboard_margin:   # keep freeboard from being submerged below water during survival_heel, largest wave
+            flag: True
+        draft_margin:   # keep draft from raising above water line during survival_heel, largest wave
+            flag: True
+        fairlead_depth: # keep fairlead above bottom trough of largest wave
+            flag: True
+    control:
+        Max_PtfmPitch:
+            flag: True
+            max: 6.0
+        Std_PtfmPitch:
+            flag: True
+            max: 1.25  # Same as IEA-15MW with same DLCs
+        nacelle_acceleration:
+            flag: True
+            max: 2.0
+
+merit_figure: structural_mass
+
+driver:
+    optimization:
+        flag: True         # Flag to enable optimization
+        tol: 1.e-3         # Optimality tolerance
+        max_iter: 50         # Maximum number of iterations (SLSQP)
+        solver: LN_COBYLA       # Optimization solver. Other options are 'SLSQP' - 'CONMIN'
+
+recorder:
+    flag: True              # Flag to activate OpenMDAO recorder
+    file_name: log_opt.sql  # Name of OpenMDAO recorder
diff --git a/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_driver.py b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_driver.py
new file mode 100644
index 000000000..fbd04367a
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_driver.py
@@ -0,0 +1,17 @@
+#!/usr/bin/env python3
+import os
+from weis import weis_main
+from openmdao.utils.mpi import MPI
+
+TEST_RUN = True
+
+# ## File management
+run_dir = os.path.dirname( os.path.realpath(__file__) )
+fname_wt_input = os.path.join(run_dir, "..", "..", "2_models", "stage-3-semisub_raft_v2p0.yaml")
+fname_modeling_options = os.path.join(run_dir, "stage-3-semisub_of_modeling.yaml") # Compare to examples/03_design_with_openfast/iea22_ptfm_opt_analysis.yaml
+fname_analysis_options = os.path.join(run_dir, "stage-3-semisub_of_analysis.yaml") # Compare to examples/03_design_with_openfast/iea22_ptfm_opt_modeling.yaml
+
+wt_opt, modeling_options, analysis_options = weis_main(
+        fname_wt_input, fname_modeling_options, fname_analysis_options, test_run=TEST_RUN
+    )
+
diff --git a/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_modeling.yaml b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_modeling.yaml
new file mode 100644
index 000000000..ed1b5304b
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_of_modeling.yaml
@@ -0,0 +1,135 @@
+General:
+    verbosity: False  # When set to True, the code prints to screen many infos
+    openfast_configuration:
+        OF_run_fst: stage-3-semisub_of
+        # OF_run_dir: outputs/IEA_w_TMD_33
+        save_iterations: True
+        save_timeseries: True
+        use_exe: True
+        allow_fails: True
+        fail_value: 9999
+        write_stdout: True # !! Important for debugging!
+
+Environment:
+    air_density: 1.225
+    air_dyn_viscosity: 1.81e-5
+    weib_shape_parameter: 2.
+    air_speed_sound: 340.
+    shear_exp: 0.12
+    water_density: 1025.0
+    water_dyn_viscosity: 1.3351e-3
+    soil_shear_modulus: 140.e+6
+    soil_poisson: 0.4
+    water_depth: 200.0
+    significant_wave_height: 4.52
+    significant_wave_period: 9.45
+
+WISDEM:
+    RotorSE:
+        flag: True
+        n_pitch_perf_surfaces: 20
+        n_tsr_perf_surfaces: 20
+        spar_cap_ss: spar_cap_ss
+        spar_cap_ps: spar_cap_ps
+        peak_thrust_shaving: True
+        thrust_shaving_coeff: 0.8
+    TowerSE:
+        flag: True
+        wind: PowerWind  # Wind used
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        buckling_method: dnvgl # Buckling code type [eurocode or dnvgl]
+        buckling_length: 15    # Buckling parameter
+        frame3dd:
+            shear: True
+            geom: True
+            tol: 1e-9
+    DriveSE:
+        flag: True
+    FloatingSE:
+        flag: True
+        symmetric_moorings: True
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        rank_and_file: True
+    BOS:
+        flag: True
+    LCOE:
+        flag: True
+        wake_loss_factor: 0.15
+        fixed_charge_rate: 0.056
+        bos_per_kW: 4053.
+        opex_per_kW: 137.
+        turbine_number: 40.
+        labor_rate: 58.8
+        painting_rate: 30.0
+
+OpenFAST: # Options for WEIS fidelity level 3 = nonlinear time domain
+    flag: True
+    simulation:
+        DT: 0.01
+        CompElast: 1
+        CompInflow: 1
+        CompAero: 2
+        CompServo: 1
+        CompHydro: 1
+        CompSub: 0
+        CompMooring: 3
+        CompIce: 0
+        OutFileFmt: 3
+        NumCrctn: 1
+    ElastoDyn:
+        FlapDOF1: True
+        FlapDOF2: True
+        EdgeDOF: True
+        TeetDOF: False
+        DrTrDOF: False
+        GenDOF: True
+        YawDOF: False
+        TwFADOF1 : True
+        TwFADOF2 : True
+        TwSSDOF1 : True
+        TwSSDOF2 : True
+        PtfmSgDOF: True
+        PtfmSwDOF: True
+        PtfmHvDOF: True
+        PtfmRDOF : True
+        PtfmPDOF : True
+        PtfmYDOF : True
+RAFT:
+    flag: False
+    potential_model_override: 0
+    trim_ballast: 2
+    heave_tol: 1
+    save_designs: True
+ROSCO:
+    flag: True
+    tuning_yaml: ../../2_models/iea22_rosco.yaml
+
+DLC_driver:
+    metocean_conditions:
+        wind_speed: [4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24.]
+        wave_height_NSS: [0.83, 0.88, 0.94, 1.03, 1.16, 1.34, 1.57, 1.86, 2.22, 2.62, 3.07]
+        wave_period_NSS: [6.9, 6.96, 7.02, 7.12, 7.25, 7.43, 7.66, 7.94, 8.27, 8.63, 9.01]
+        wave_height_SSS: [6.3, 8, 8, 8.1, 8.5, 8.5, 9.8, 9.8, 9.8, 9.8, 9.9]
+        wave_period_SSS: [11.5, 12.7, 12.7, 12.8, 13.1, 13.1, 14.1, 14.1, 14.1, 14.1, 14.1]
+        wave_height_1: 6.98
+        wave_period_1: 11.7
+        wave_height_50: 10.68
+        wave_period_50: 14.2
+    DLCs:
+        - DLC: "1.6"
+          n_seeds: 6
+          transient_time: 120.0 
+          analysis_time: 600.0 
+        - DLC: "6.1"
+          n_seeds: 6
+          analysis_time: 600.0  
+          turbulent_wind:
+            GridWidth: 400
diff --git a/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_analysis.yaml b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_analysis.yaml
new file mode 100644
index 000000000..54359d486
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_analysis.yaml
@@ -0,0 +1,112 @@
+general:
+    folder_output: outputs
+    fname_output: stage-3-semisub_raft
+
+design_variables:
+    floating:
+        joints:
+            z_coordinate:       # draft
+                - names: [main_keel, col1_keel, col2_keel, col3_keel]
+                  lower_bound: -30.0
+                  upper_bound: -12.0
+                  flag: True
+                # - names: [col1_freeboard, col2_freeboard, col3_freeboard]
+                #   lower_bound: 10.0
+                #   upper_bound: 20.0
+            r_coordinate:
+                - names: [col1_keel, col1_freeboard, col2_keel, col2_freeboard, col3_keel, col3_freeboard]
+                  lower_bound: 50.0
+                  upper_bound: 70.0
+                  flag: True
+        members:
+            groups:
+                - names: [column1, column2, column3]
+                  flag: True
+                  diameter:
+                      lower_bound: 12.0
+                      upper_bound: 16.0
+                      constant: True
+
+constraints:
+    tower:
+        height_constraint:
+            flag: False
+            lower_bound: 1.e-2
+            upper_bound: 1.e-2
+        stress:
+            flag: False
+        global_buckling:
+            flag: False
+        shell_buckling:
+            flag: False
+        d_to_t:
+            flag: False
+            lower_bound: 120.0
+            upper_bound: 2000.0
+        taper:
+            flag: False
+            lower_bound: 0.2
+        slope:
+            flag: False
+        frequency_1:
+            flag: False
+            lower_bound: 0.37
+    floating:
+        survival_heel:
+            upper_bound: 0.17453292519943295 # 10 deg
+        metacentric_height:
+            flag: True
+            lower_bound: 15.0
+        pitch_period:
+            flag: True
+            lower_bound: 20. # +/- 10%
+            upper_bound: 80.
+        heave_period:
+            flag: True
+            lower_bound: 16. # +/- 10%
+            upper_bound: 80.
+        fixed_ballast_capacity:
+            flag: True
+        variable_ballast_capacity:
+            flag: True
+        buoyancy:
+            flag: False
+        stress:
+            flag: False
+        global_buckling:
+            flag: False
+        shell_buckling:
+            flag: False
+        mooring_heel:
+            flag: False
+        freeboard_margin:   # keep freeboard from being submerged below water during survival_heel, largest wave
+            flag: True
+        draft_margin:   # keep draft from raising above water line during survival_heel, largest wave
+            flag: True
+        fairlead_depth: # keep fairlead above bottom trough of largest wave
+            flag: True
+    control:
+        Max_PtfmPitch:
+            flag: True
+            max: 6.0
+        Std_PtfmPitch:
+            flag: False
+            max: 1.25  # Same as IEA-15MW with same DLCs
+        nacelle_acceleration:
+            flag: True
+            max: 2.0
+
+merit_figure: structural_mass
+
+driver:
+    optimization:
+        flag: True         # Flag to enable optimization
+        tol: 1.e-6         # Optimality tolerance
+        max_iter: 50      # Maximum number of iterations (SLSQP)
+        max_gen: 2        # Maximum number of generations (DE)
+        #time_limit: 3420
+        solver: LN_COBYLA   # Optimization solver. Other options are 'SLSQP' - 'CONMIN'
+
+recorder:
+    flag: True                            # Flag to activate OpenMDAO recorder
+    file_name: log_opt.sql    # Name of OpenMDAO recorder
diff --git a/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_driver.py b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_driver.py
new file mode 100644
index 000000000..86fad6ff5
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_driver.py
@@ -0,0 +1,17 @@
+#!/usr/bin/env python3
+import os
+from weis import weis_main
+from openmdao.utils.mpi import MPI
+
+TEST_RUN = True
+
+## File management
+run_dir = os.path.dirname( os.path.realpath(__file__) )
+fname_wt_input = os.path.join(run_dir, "..", "..", "2_models", "stage-2-controller_v2p0.yaml")
+fname_modeling_options = os.path.join(run_dir, "stage-3-semisub_raft_modeling.yaml")
+fname_analysis_options = os.path.join(run_dir, "stage-3-semisub_raft_analysis.yaml") # Compare to /Users/dzalkind/Tools/WEIS-Eni/examples/04_frequency_domain_analysis_design/iea22_raft_opt_analysis.yaml
+
+wt_opt, modeling_options, analysis_options = weis_main(
+        fname_wt_input, fname_modeling_options, fname_analysis_options, test_run=TEST_RUN
+    )
+
diff --git a/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_modeling.yaml b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_modeling.yaml
new file mode 100644
index 000000000..044be9120
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-3-semisub/stage-3-semisub_raft_modeling.yaml
@@ -0,0 +1,115 @@
+General:
+    verbosity: False  # When set to True, the code prints to screen many infos
+    openfast_configuration:
+        OF_run_fst: stage-3-semisub_raft
+        save_iterations: True
+        save_timeseries: True
+        use_exe: True
+        allow_fails: True
+        fail_value: 9999
+        write_stdout: True
+WISDEM:
+    RotorSE:
+        flag: True
+        n_pitch_perf_surfaces: 20
+        n_tsr_perf_surfaces: 20
+        spar_cap_ss: spar_cap_ss
+        spar_cap_ps: spar_cap_ps
+        # te_ss: TE_reinforcement_SS
+        # te_ps: TE_reinforcement_PS
+        peak_thrust_shaving: True
+        thrust_shaving_coeff: 0.8
+    TowerSE:
+        flag: True
+        wind: PowerWind  # Wind used
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        buckling_method: dnvgl # Buckling code type [eurocode or dnvgl]
+        buckling_length: 15    # Buckling parameter
+        frame3dd:
+            shear: True
+            geom: True
+            tol: 1e-9
+    DriveSE:
+        flag: True
+    FloatingSE:
+        flag: True
+        symmetric_moorings: True
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+    BOS:
+        flag: True
+        plant_turbine_spacing: 7
+        plant_row_spacing: 7
+        commissioning_cost_kW: 44.0
+        decommissioning_cost_kW: 58.0
+        distance_to_substation: 1.0
+        distance_to_interconnection: 8.5
+        interconnect_voltage: 130.
+        distance_to_site: 115.
+        distance_to_landfall: 50.
+        port_cost_per_month: 2e6
+        construction_insurance: 44.0
+        construction_financing: 183.0
+        contingency: 316.0
+        site_auction_price: 100e6
+        site_assessment_cost: 50e6
+        construction_plan_cost: 2.5e5
+        installation_plan_cost: 1e6
+    LCOE:
+        flag: True
+        wake_loss_factor: 0.15
+        fixed_charge_rate: 0.056
+        bos_per_kW: 4053.
+        opex_per_kW: 137.
+        turbine_number: 40.
+        labor_rate: 58.8
+        painting_rate: 30.0
+Environment:
+    air_density: 1.225
+    air_dyn_viscosity: 1.81e-5
+    weib_shape_parameter: 2.
+    air_speed_sound: 340.
+    shear_exp: 0.12
+    water_density: 1025.0
+    water_dyn_viscosity: 1.3351e-3
+    soil_shear_modulus: 140.e+6
+    soil_poisson: 0.4
+    water_depth: 200.0
+    significant_wave_height: 4.52
+    significant_wave_period: 9.45
+
+RAFT:
+    flag: True
+    potential_model_override: 0
+    trim_ballast: 2
+    heave_tol: 1
+    save_designs: True
+    
+ROSCO:
+    flag: True
+
+DLC_driver:
+    metocean_conditions:
+        wind_speed: [4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24.]
+        wave_height_NSS: [0.83, 0.88, 0.94, 1.03, 1.16, 1.34, 1.57, 1.86, 2.22, 2.62, 3.07]
+        wave_period_NSS: [6.9, 6.96, 7.02, 7.12, 7.25, 7.43, 7.66, 7.94, 8.27, 8.63, 9.01]
+        wave_height_SSS: [6.3, 8, 8, 8.1, 8.5, 8.5, 9.8, 9.8, 9.8, 9.8, 9.9]
+        wave_period_SSS: [11.5, 12.7, 12.7, 12.8, 13.1, 13.1, 14.1, 14.1, 14.1, 14.1, 14.1]
+        wave_height_1: 6.98
+        wave_period_1: 11.7
+        wave_height_50: 10.68
+        wave_period_50: 14.2
+    DLCs:
+        - DLC: "1.6"
+          analysis_time: 600.
+          transient_time: 120.
+        - DLC: "6.1"
+          analysis_time: 600.
+          transient_time: 120.
\ No newline at end of file
diff --git a/examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_analysis.yaml b/examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_analysis.yaml
new file mode 100644
index 000000000..e047012df
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_analysis.yaml
@@ -0,0 +1,133 @@
+general:
+    folder_output: outputs_of_newFix
+    fname_output: stage-3-semisub_of
+
+design_variables:
+    floating:
+        joints:
+            z_coordinate:       # draft
+                - names: [main_keel, col1_keel, col2_keel, col3_keel]
+                  flag: True
+                  lower_bound: -30.0
+                  upper_bound: -12.0
+                # - names: [col1_freeboard, col2_freeboard, col3_freeboard]
+                #   lower_bound: 10.0
+                #   upper_bound: 20.0
+            r_coordinate:
+                - names: [col1_keel, col1_freeboard, col2_keel, col2_freeboard, col3_keel, col3_freeboard]
+                  flag: True
+                  lower_bound: 35.0
+                  upper_bound: 75.0
+        members:
+            groups:
+                - names: [column1, column2, column3]
+                  flag: True
+                  diameter:
+                      lower_bound: 8.0
+                      upper_bound: 16.0
+                      constant: True
+    control:
+        servo:
+            pitch_control:
+                omega:
+                    flag: True
+                    min: 0.025
+                    max: 0.5
+                zeta:
+                    flag: True
+                    min: 0.1
+                    max: 3.0
+                Kp_float:
+                    flag: True
+                    min: -40.0  # -0.25
+                    max: 0
+                ptfm_freq:
+                    flag: True
+                    max: 0.5
+
+
+constraints:
+    tower:
+        height_constraint:
+            flag: False
+            lower_bound: 1.e-2
+            upper_bound: 1.e-2
+        stress:
+            flag: False
+        global_buckling:
+            flag: False
+        shell_buckling:
+            flag: False
+        d_to_t:
+            flag: False
+            lower_bound: 120.0
+            upper_bound: 2000.0
+        taper:
+            flag: False
+            lower_bound: 0.2
+        slope:
+            flag: False
+        frequency_1:
+            flag: False
+            lower_bound: 0.37
+    floating:
+        survival_heel:
+            upper_bound: 0.17453292519943295 # 10 deg
+        metacentric_height:
+            flag: True
+            lower_bound: 15.0
+        pitch_period:
+            flag: True
+            lower_bound: 20. # +/- 10%
+            upper_bound: 80.
+        heave_period:
+            flag: True
+            lower_bound: 16. # +/- 10%
+            upper_bound: 80.
+        fixed_ballast_capacity:
+            flag: True
+        variable_ballast_capacity:
+            flag: True
+        buoyancy:
+            flag: False
+        stress:
+            flag: False
+        global_buckling:
+            flag: False
+        shell_buckling:
+            flag: False
+        mooring_heel:
+            flag: False
+        freeboard_margin:   # keep freeboard from being submerged below water during survival_heel, largest wave
+            flag: True
+        draft_margin:   # keep draft from raising above water line during survival_heel, largest wave
+            flag: True
+        fairlead_depth: # keep fairlead above bottom trough of largest wave
+            flag: True
+    control:
+        Max_PtfmPitch:
+            flag: True
+            max: 6.0
+        Std_PtfmPitch:
+            flag: True
+            max: 1.25  # Same as IEA-15MW with same DLCs
+        nacelle_acceleration:
+            flag: True
+            max: 2.0
+        rotor_overspeed:
+            flag: True
+            min: 0.0
+            max: 0.3
+
+merit_figure: structural_mass
+
+driver:
+    optimization:
+        flag: True         # Flag to enable optimization
+        tol: 1.e-3         # Optimality tolerance
+        max_iter: 120         # Maximum number of iterations (SLSQP)
+        solver: LN_COBYLA       # Optimization solver. Other options are 'SLSQP' - 'CONMIN'
+
+recorder:
+    flag: True              # Flag to activate OpenMDAO recorder
+    file_name: log_opt.sql  # Name of OpenMDAO recorder
diff --git a/examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_driver.py b/examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_driver.py
new file mode 100644
index 000000000..97ae95fca
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_driver.py
@@ -0,0 +1,16 @@
+#!/usr/bin/env python3
+import os
+from weis import weis_main
+from openmdao.utils.mpi import MPI
+
+
+## File management
+run_dir = os.path.dirname( os.path.realpath(__file__) )
+fname_wt_input = os.path.join(run_dir, "..", "..", "2_models", "stage-3-semisub_raft_v2p0.yaml")
+fname_modeling_options = os.path.join(run_dir, "stage-3.5-semisub_of_modeling.yaml")
+fname_analysis_options = os.path.join(run_dir, "stage-3.5-semisub_of_analysis.yaml")
+
+wt_opt, modeling_options, analysis_options = weis_main(
+        fname_wt_input, fname_modeling_options, fname_analysis_options, test_run=True
+    )
+
diff --git a/examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_modeling.yaml b/examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_modeling.yaml
new file mode 100644
index 000000000..3a2f923d4
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-3.5-semisubCCD/stage-3.5-semisub_of_modeling.yaml
@@ -0,0 +1,135 @@
+General:
+    verbosity: False  # When set to True, the code prints to screen many infos
+    openfast_configuration:
+        OF_run_fst: stage-3.5-semisub_of
+        # OF_run_dir: outputs/IEA_w_TMD_33
+        save_iterations: True
+        save_timeseries: True
+        use_exe: True
+        allow_fails: True
+        fail_value: 9999
+        write_stdout: True # !! Important for debugging!
+
+Environment:
+    air_density: 1.225
+    air_dyn_viscosity: 1.81e-5
+    weib_shape_parameter: 2.
+    air_speed_sound: 340.
+    shear_exp: 0.12
+    water_density: 1025.0
+    water_dyn_viscosity: 1.3351e-3
+    soil_shear_modulus: 140.e+6
+    soil_poisson: 0.4
+    water_depth: 200.0
+    significant_wave_height: 4.52
+    significant_wave_period: 9.45
+
+WISDEM:
+    RotorSE:
+        flag: True
+        n_pitch_perf_surfaces: 20
+        n_tsr_perf_surfaces: 20
+        spar_cap_ss: spar_cap_ss
+        spar_cap_ps: spar_cap_ps
+        peak_thrust_shaving: True
+        thrust_shaving_coeff: 0.8
+    TowerSE:
+        flag: True
+        wind: PowerWind  # Wind used
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        buckling_method: dnvgl # Buckling code type [eurocode or dnvgl]
+        buckling_length: 15    # Buckling parameter
+        frame3dd:
+            shear: True
+            geom: True
+            tol: 1e-9
+    DriveSE:
+        flag: True
+    FloatingSE:
+        flag: True
+        symmetric_moorings: True
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        rank_and_file: True
+    BOS:
+        flag: True
+    LCOE:
+        flag: True
+        wake_loss_factor: 0.15
+        fixed_charge_rate: 0.056
+        bos_per_kW: 4053.
+        opex_per_kW: 137.
+        turbine_number: 40.
+        labor_rate: 58.8
+        painting_rate: 30.0
+
+OpenFAST: # Options for WEIS fidelity level 3 = nonlinear time domain
+    flag: True
+    simulation:
+        DT: 0.01
+        CompElast: 1
+        CompInflow: 1
+        CompAero: 2
+        CompServo: 1
+        CompHydro: 1
+        CompSub: 0
+        CompMooring: 3
+        CompIce: 0
+        OutFileFmt: 3
+        NumCrctn: 1
+    ElastoDyn:
+        FlapDOF1: True
+        FlapDOF2: True
+        EdgeDOF: True
+        TeetDOF: False
+        DrTrDOF: False
+        GenDOF: True
+        YawDOF: False
+        TwFADOF1 : True
+        TwFADOF2 : True
+        TwSSDOF1 : True
+        TwSSDOF2 : True
+        PtfmSgDOF: True
+        PtfmSwDOF: True
+        PtfmHvDOF: True
+        PtfmRDOF : True
+        PtfmPDOF : True
+        PtfmYDOF : True
+RAFT:
+    flag: True
+    potential_model_override: 0
+    trim_ballast: 2
+    heave_tol: 1
+    save_designs: True
+ROSCO:
+    flag: True
+    tuning_yaml: ../../2_models/iea22_rosco.yaml
+
+DLC_driver:
+    metocean_conditions:
+        wind_speed: [4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24.]
+        wave_height_NSS: [0.83, 0.88, 0.94, 1.03, 1.16, 1.34, 1.57, 1.86, 2.22, 2.62, 3.07]
+        wave_period_NSS: [6.9, 6.96, 7.02, 7.12, 7.25, 7.43, 7.66, 7.94, 8.27, 8.63, 9.01]
+        wave_height_SSS: [6.3, 8, 8, 8.1, 8.5, 8.5, 9.8, 9.8, 9.8, 9.8, 9.9]
+        wave_period_SSS: [11.5, 12.7, 12.7, 12.8, 13.1, 13.1, 14.1, 14.1, 14.1, 14.1, 14.1]
+        wave_height_1: 6.98
+        wave_period_1: 11.7
+        wave_height_50: 10.68
+        wave_period_50: 14.2
+    DLCs:
+        - DLC: "1.6"    # kestrel
+          n_seeds: 6
+          transient_time: 120.0  # 0.
+          analysis_time: 600.0  # 10.
+        - DLC: "6.1"
+          n_seeds: 6
+          analysis_time: 600.0  # 10.
+          turbulent_wind:
+            GridWidth: 400

From 057b01d4ebfe21aa8e5602678e3f4310b9d76221 Mon Sep 17 00:00:00 2001
From: dzalkind <dzalkind@nrel.gov>
Date: Mon, 12 Jan 2026 14:53:35 -0700
Subject: [PATCH 4/9] Add stage 4

---
 .../stage-4-dlcs/stage-4-dlcs_analysis.yaml   |   3 +
 .../stage-4-dlcs/stage-4-dlcs_driver.py       |  15 ++
 .../stage-4-dlcs/stage-4-dlcs_modeling.yaml   | 141 ++++++++++++++++++
 3 files changed, 159 insertions(+)
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_analysis.yaml
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_driver.py
 create mode 100644 examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_modeling.yaml

diff --git a/examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_analysis.yaml b/examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_analysis.yaml
new file mode 100644
index 000000000..82572404e
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_analysis.yaml
@@ -0,0 +1,3 @@
+general:
+    folder_output: outputs/
+    fname_output: stage-4-dlcs
\ No newline at end of file
diff --git a/examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_driver.py b/examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_driver.py
new file mode 100644
index 000000000..1f2eb44be
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_driver.py
@@ -0,0 +1,15 @@
+#!/usr/bin/env python3
+import os
+from weis import weis_main
+
+TEST_RUN = True
+
+run_dir = os.path.dirname( os.path.realpath(__file__) )
+fname_wt_input = os.path.join(run_dir, "..", "..", "2_models", "new-20-270-RWT_Floater.yaml")
+fname_modeling_options = os.path.join(run_dir, "stage-4-dlcs_modeling.yaml")
+fname_analysis_options = os.path.join(run_dir, "stage-4-dlcs_analysis.yaml")
+
+wt_opt, modeling_options, analysis_options = weis_main(
+        fname_wt_input, fname_modeling_options, fname_analysis_options, test_run=TEST_RUN
+    )
+
diff --git a/examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_modeling.yaml b/examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_modeling.yaml
new file mode 100644
index 000000000..1b5f0b591
--- /dev/null
+++ b/examples/09_model_creation_process/1_drivers/stage-4-dlcs/stage-4-dlcs_modeling.yaml
@@ -0,0 +1,141 @@
+General:
+    verbosity: False  # When set to True, the code prints to screen many infos
+    openfast_configuration:
+        OF_run_fst: stage-4-dlc_20MW
+        OF_run_dir: outputs/dlcs
+        save_iterations: True
+        save_timeseries: True
+        use_exe: True
+        allow_fails: True
+        fail_value: 9999
+        write_stdout: True # !! Important for debugging!
+
+Environment:
+    air_density: 1.225
+    air_dyn_viscosity: 1.81e-5
+    weib_shape_parameter: 2.
+    air_speed_sound: 340.
+    shear_exp: 0.12
+    water_density: 1025.0
+    water_dyn_viscosity: 1.3351e-3
+    soil_shear_modulus: 140.e+6
+    soil_poisson: 0.4
+    water_depth: 200.0
+    significant_wave_height: 4.52
+    significant_wave_period: 9.45
+
+WISDEM:
+    RotorSE:
+        flag: True
+        n_pitch_perf_surfaces: 20
+        n_tsr_perf_surfaces: 20
+        spar_cap_ss: spar_cap_ss
+        spar_cap_ps: spar_cap_ps
+        peak_thrust_shaving: True
+        thrust_shaving_coeff: 0.8
+    TowerSE:
+        flag: True
+        wind: PowerWind  # Wind used
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        buckling_method: dnvgl # Buckling code type [eurocode or dnvgl]
+        buckling_length: 15    # Buckling parameter
+        frame3dd:
+            shear: True
+            geom: True
+            tol: 1e-9
+    DriveSE:
+        flag: True
+    FloatingSE:
+        flag: True
+        symmetric_moorings: True
+        gamma_f: 1.35    # Safety factor for fatigue loads
+        gamma_m: 1.3     # Safety factor for material properties
+        gamma_n: 1.0     # Safety factor for ...
+        gamma_b: 1.1     # Safety factor for ...
+        gamma_fatigue: 1.755  # Safety factor for fatigue loads
+        rank_and_file: True
+    BOS:
+        flag: True
+    LCOE:
+        flag: True
+        wake_loss_factor: 0.15
+        fixed_charge_rate: 0.056
+        bos_per_kW: 4053.
+        opex_per_kW: 137.
+        turbine_number: 40.
+        labor_rate: 58.8
+        painting_rate: 30.0
+
+OpenFAST: # Options for WEIS fidelity level 3 = nonlinear time domain
+    flag: True
+    simulation:
+        DT: 0.01
+        CompElast: 1
+        CompInflow: 1
+        CompAero: 2
+        CompServo: 1
+        CompSeaSt: 1
+        CompHydro: 1
+        CompSub: 0
+        CompMooring: 3
+        CompIce: 0
+        OutFileFmt: 3
+        NumCrctn: 1
+    ElastoDyn:
+        FlapDOF1: True
+        FlapDOF2: True
+        EdgeDOF: True
+        TeetDOF: False
+        DrTrDOF: False
+        GenDOF: True
+        YawDOF: False
+        TwFADOF1 : True
+        TwFADOF2 : True
+        TwSSDOF1 : True
+        TwSSDOF2 : True
+        PtfmSgDOF: True
+        PtfmSwDOF: True
+        PtfmHvDOF: True
+        PtfmRDOF : True
+        PtfmPDOF : True
+        PtfmYDOF : True
+    AeroDyn:
+        BEM_Mod: 2
+        UA_Mod: 2
+        IntegrationMethod: 4
+
+ROSCO:
+    flag: True
+    tuning_yaml: ../../2_models/iea20_semisub_rosco.yaml
+
+DLC_driver:
+    metocean_conditions:
+        wind_speed: [4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24.]
+        wave_height_NSS: [0.83, 0.88, 0.94, 1.03, 1.16, 1.34, 1.57, 1.86, 2.22, 2.62, 3.07]
+        wave_period_NSS: [6.9, 6.96, 7.02, 7.12, 7.25, 7.43, 7.66, 7.94, 8.27, 8.63, 9.01]
+        wave_height_SSS: [6.3, 8, 8, 8.1, 8.5, 8.5, 9.8, 9.8, 9.8, 9.8, 9.9]
+        wave_period_SSS: [11.5, 12.7, 12.7, 12.8, 13.1, 13.1, 14.1, 14.1, 14.1, 14.1, 14.1]
+        wave_height_1: 6.98
+        wave_period_1: 11.7
+        wave_height_50: 10.68
+        wave_period_50: 14.2
+    DLCs:
+        - DLC: "1.1"
+          n_seeds: 6
+          transient_time: 100.
+          analysis_time: 600.
+        - DLC: "1.4"
+          wind_speed: [9.158, 11.158, 13.158]
+        - DLC: "1.6"
+          n_seeds: 6
+          transient_time: 120.
+          analysis_time: 600.
+        # - DLC: "5.1" # shutdown is important for floating systems, but the test mode requires more setup
+        - DLC: "6.1"
+          n_seeds: 6
+          transient_time: 120.
+          analysis_time: 600.

From 6c056f674416fc4e8f0ac15e5a895014d3df2e4d Mon Sep 17 00:00:00 2001
From: dzalkind <dzalkind@nrel.gov>
Date: Mon, 12 Jan 2026 14:53:47 -0700
Subject: [PATCH 5/9] Skip plot if in test mode

---
 .../iea34_driver.py                           | 90 +++++++++----------
 1 file changed, 45 insertions(+), 45 deletions(-)

diff --git a/examples/02_generate_openfast_model_for_dlcs/iea34_driver.py b/examples/02_generate_openfast_model_for_dlcs/iea34_driver.py
index a45bf27fd..50ea2bf47 100644
--- a/examples/02_generate_openfast_model_for_dlcs/iea34_driver.py
+++ b/examples/02_generate_openfast_model_for_dlcs/iea34_driver.py
@@ -16,48 +16,48 @@
                                                  test_run=TEST_RUN
                                                  )
 
-
-import matplotlib.pyplot as plt
-import numpy as np
-from matplotlib import cm
-
-X = wt_opt['sse_tune.aeroperf_tables.pitch_vector']
-Y = wt_opt['sse_tune.aeroperf_tables.tsr_vector']
-X, Y = np.meshgrid(X, Y)
-pitch_schedule = wt_opt['rotorse.rp.powercurve.pitch']
-tsr_schedule = wt_opt['rotorse.rp.powercurve.Omega'] / 30. * np.pi * wt_opt['rotorse.Rtip'] / wt_opt['rotorse.rp.powercurve.V']
-
-# Plot the Cp surface
-fig, ax = plt.subplots()
-Z = wt_opt['sse_tune.aeroperf_tables.Cp']
-cs = ax.contourf(X, Y, Z[:,:,0], cmap=cm.inferno, levels = [0, 0.1, 0.2, 0.3, 0.4, 0.44, 0.47, 0.50, 0.53, 0.56])
-ax.plot(pitch_schedule, tsr_schedule, 'w--', label = 'Regulation trajectory')
-ax.set_xlabel('Pitch angle (deg)', fontweight = 'bold')
-ax.set_ylabel('Tip speed ratio (-)', fontweight = 'bold')
-cbar = fig.colorbar(cs)
-cbar.ax.set_ylabel('Aerodynamic power coefficient (-)', fontweight = 'bold')
-plt.legend()
-
-# Plot the Ct surface
-fig, ax = plt.subplots()
-Z = wt_opt['sse_tune.aeroperf_tables.Ct']
-cs = ax.contourf(X, Y, Z[:,:,0], cmap=cm.inferno)
-ax.plot(pitch_schedule, tsr_schedule, 'w--', label = 'Regulation trajectory')
-ax.set_xlabel('Pitch angle (deg)', fontweight = 'bold')
-ax.set_ylabel('Tip speed ratio (-)', fontweight = 'bold')
-cbar = fig.colorbar(cs)
-cbar.ax.set_ylabel('Aerodynamic thrust coefficient (-)', fontweight = 'bold')
-plt.legend()
-
-# Plot the Cq surface
-fig, ax = plt.subplots()
-Z = wt_opt['sse_tune.aeroperf_tables.Cq']
-cs = ax.contourf(X, Y, Z[:,:,0], cmap=cm.inferno)
-ax.plot(pitch_schedule, tsr_schedule, 'w--', label = 'Regulation trajectory')
-ax.set_xlabel('Pitch angle (deg)', fontweight = 'bold')
-ax.set_ylabel('Tip speed ratio (-)', fontweight = 'bold')
-cbar = fig.colorbar(cs)
-cbar.ax.set_ylabel('Aerodynamic torque coefficient (-)', fontweight = 'bold')
-plt.legend()
-
-plt.show()
\ No newline at end of file
+if not TEST_RUN:
+    import matplotlib.pyplot as plt
+    import numpy as np
+    from matplotlib import cm
+
+    X = wt_opt['sse_tune.aeroperf_tables.pitch_vector']
+    Y = wt_opt['sse_tune.aeroperf_tables.tsr_vector']
+    X, Y = np.meshgrid(X, Y)
+    pitch_schedule = wt_opt['rotorse.rp.powercurve.pitch']
+    tsr_schedule = wt_opt['rotorse.rp.powercurve.Omega'] / 30. * np.pi * wt_opt['rotorse.Rtip'] / wt_opt['rotorse.rp.powercurve.V']
+
+    # Plot the Cp surface
+    fig, ax = plt.subplots()
+    Z = wt_opt['sse_tune.aeroperf_tables.Cp']
+    cs = ax.contourf(X, Y, Z[:,:,0], cmap=cm.inferno, levels = [0, 0.1, 0.2, 0.3, 0.4, 0.44, 0.47, 0.50, 0.53, 0.56])
+    ax.plot(pitch_schedule, tsr_schedule, 'w--', label = 'Regulation trajectory')
+    ax.set_xlabel('Pitch angle (deg)', fontweight = 'bold')
+    ax.set_ylabel('Tip speed ratio (-)', fontweight = 'bold')
+    cbar = fig.colorbar(cs)
+    cbar.ax.set_ylabel('Aerodynamic power coefficient (-)', fontweight = 'bold')
+    plt.legend()
+
+    # Plot the Ct surface
+    fig, ax = plt.subplots()
+    Z = wt_opt['sse_tune.aeroperf_tables.Ct']
+    cs = ax.contourf(X, Y, Z[:,:,0], cmap=cm.inferno)
+    ax.plot(pitch_schedule, tsr_schedule, 'w--', label = 'Regulation trajectory')
+    ax.set_xlabel('Pitch angle (deg)', fontweight = 'bold')
+    ax.set_ylabel('Tip speed ratio (-)', fontweight = 'bold')
+    cbar = fig.colorbar(cs)
+    cbar.ax.set_ylabel('Aerodynamic thrust coefficient (-)', fontweight = 'bold')
+    plt.legend()
+
+    # Plot the Cq surface
+    fig, ax = plt.subplots()
+    Z = wt_opt['sse_tune.aeroperf_tables.Cq']
+    cs = ax.contourf(X, Y, Z[:,:,0], cmap=cm.inferno)
+    ax.plot(pitch_schedule, tsr_schedule, 'w--', label = 'Regulation trajectory')
+    ax.set_xlabel('Pitch angle (deg)', fontweight = 'bold')
+    ax.set_ylabel('Tip speed ratio (-)', fontweight = 'bold')
+    cbar = fig.colorbar(cs)
+    cbar.ax.set_ylabel('Aerodynamic torque coefficient (-)', fontweight = 'bold')
+    plt.legend()
+
+    plt.show()
\ No newline at end of file

From fe260c5a119af28a4bf811670ee663febcc88338 Mon Sep 17 00:00:00 2001
From: dzalkind <dzalkind@nrel.gov>
Date: Mon, 12 Jan 2026 15:11:46 -0700
Subject: [PATCH 6/9] Add chapter 3, no drivers

---
 .../0_notebooks/chapter3.ipynb                | 249 ++++++++++++++++++
 1 file changed, 249 insertions(+)
 create mode 100644 examples/09_model_creation_process/0_notebooks/chapter3.ipynb

diff --git a/examples/09_model_creation_process/0_notebooks/chapter3.ipynb b/examples/09_model_creation_process/0_notebooks/chapter3.ipynb
new file mode 100644
index 000000000..8ce2f6001
--- /dev/null
+++ b/examples/09_model_creation_process/0_notebooks/chapter3.ipynb
@@ -0,0 +1,249 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "92735b9d",
+   "metadata": {},
+   "source": [
+    "# Welcome to the WEIS Workshop - Chapter 3: Design Load Cases\n",
+    "\n",
+    "## Quick Recap\n",
+    "\n",
+    "We've successfully developed a complete 20MW floating wind turbine system:\n",
+    "- **Chapter 1**: Optimized rotor design using WISDEM\n",
+    "- **Chapter 2**: Re-tuned controller and optimized platform using RAFT and OpenFAST\n",
+    "\n",
+    "## Chapter 3: Design Load Cases (DLC) Analysis\n",
+    "\n",
+    "Now we validate our design using industry-standard Design Load Cases (DLCs). This ensures our optimized system meets safety and performance requirements under all operational and extreme conditions.\n",
+    "\n",
+    "### What We'll Cover\n",
+    "- **Load Analysis**: Using WEIS to generate a subset of DLCs for our floating wind turbine\n",
+    "- **Running Simulations**: Execute the DLCs using OpenFAST, with WEIS handling the file generation, parallelization, and postprocessing\n",
+    "\n",
+    "**Note**: DLC simulations are computationally expensive (~hours per case), so we'll analyze precomputed results that demonstrate the complete validation workflow."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b78aebca",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Importing nesscary libraries.\n",
+    "import os\n",
+    "import pickle\n",
+    "\n",
+    "from weis_workshop import *\n",
+    "\n",
+    "\n",
+    "this_dir = os.getcwd()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "de0d61f7",
+   "metadata": {},
+   "source": [
+    "## Stage 4: Design Load Cases (DLCs)\n",
+    "\n",
+    "The inputs and drivers can be found in `examples/09_model_creation_process/1_drivers`\n",
+    "\n",
+    "### Analysis options:\n",
+    "\n",
+    "``` yaml\n",
+    "general:\n",
+    "    folder_output: outputs/\n",
+    "    fname_output: stage-4-dlcs\n",
+    "```\n",
+    "\n",
+    "### Modeling options (important parts):\n",
+    "\n",
+    "``` yaml\n",
+    "\n",
+    "OpenFAST: \n",
+    "    flag: True\n",
+    "    simulation:\n",
+    "    [...]\n",
+    "\n",
+    "DLC_driver:\n",
+    "    metocean_conditions:\n",
+    "        wind_speed: [4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24.]\n",
+    "        wave_height_NSS: [0.83, 0.88, 0.94, 1.03, 1.16, 1.34, 1.57, 1.86, 2.22, 2.62, 3.07]\n",
+    "        wave_period_NSS: [6.9, 6.96, 7.02, 7.12, 7.25, 7.43, 7.66, 7.94, 8.27, 8.63, 9.01]\n",
+    "        wave_height_SSS: [6.3, 8, 8, 8.1, 8.5, 8.5, 9.8, 9.8, 9.8, 9.8, 9.9]\n",
+    "        wave_period_SSS: [11.5, 12.7, 12.7, 12.8, 13.1, 13.1, 14.1, 14.1, 14.1, 14.1, 14.1]\n",
+    "        wave_height_1: 6.98\n",
+    "        wave_period_1: 11.7\n",
+    "        wave_height_50: 10.68\n",
+    "        wave_period_50: 14.2\n",
+    "    DLCs:\n",
+    "        - DLC: \"1.1\"\n",
+    "          n_seeds: 6\n",
+    "          transient_time: 100.\n",
+    "          analysis_time: 600.\n",
+    "        - DLC: \"1.4\"\n",
+    "          wind_speed: [9.158, 11.158, 13.158]\n",
+    "        - DLC: \"1.6\"\n",
+    "          n_seeds: 6\n",
+    "          transient_time: 120.\n",
+    "          analysis_time: 600.\n",
+    "        - DLC: \"5.1\"\n",
+    "        - DLC: \"6.1\"\n",
+    "          n_seeds: 6\n",
+    "          transient_time: 120.\n",
+    "          analysis_time: 600.\n",
+    "\n",
+    "```\n",
+    "\n",
+    "**Key Points:**\n",
+    "- **5 Different DLCs**: Covering normal operation, extreme winds, and extreme waves\n",
+    "- **Realistic Environment**: Wind speeds 4-24 m/s with corresponding wave conditions  \n",
+    "- **Statistical Robustness**: Multiple seeds (6) for turbulent conditions\n",
+    "- **OpenFAST Integration**: Full aeroelastic simulation with platform dynamics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "598f089c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Setting up file paths\n",
+    "stageFolder = \"stage-4-dlcs\"\n",
+    "\n",
+    "use_precomputed = True\n",
+    "\n",
+    "if use_precomputed:\n",
+    "    sum_stat_file = os.path.join(this_dir,\"..\",\"1_drivers\", stageFolder,\"outputs_preCompute/dlcs/rank_0/iteration_0/summary_stats.p\")\n",
+    "else:\n",
+    "    sum_stat_file = os.path.join(this_dir,\"..\",\"1_drivers\", stageFolder,\"outputs/dlcs/rank_0/iteration_0/summary_stats.p\")\n",
+    "\n",
+    "\n",
+    "with open(sum_stat_file, 'rb') as f:\n",
+    "    data = pickle.load(f)\n",
+    "\n",
+    "custom_y_params = [\n",
+    "            ('GenSpeed', 'mean'),\n",
+    "            ('RootMyb1', 'max'),\n",
+    "            ('TwrBsAxMxyt', 'median'),\n",
+    "            ('PtfmPitch', 'max'),\n",
+    "]\n",
+    "\n",
+    "plot_weis_summary(data, custom_y_params)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "356cb165",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "custom_y_params = [\n",
+    "            ('RootMxb1', 'max'),\n",
+    "            ('RootMyb1', 'max'),\n",
+    "            ('TwrBsMxt', 'median'),\n",
+    "            ('TwrBsMyt', 'median'),\n",
+    "]\n",
+    "\n",
+    "plot_weis_summary(data, custom_y_params)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e111372d",
+   "metadata": {},
+   "source": [
+    "# Workshop Summary\n",
+    "\n",
+    "## What We've Accomplished\n",
+    "\n",
+    "This workshop has taken you through the complete **multi-fidelity co-design workflow** used in modern floating offshore wind turbine development. You've experienced the same systematic approach used by industry and research organizations worldwide.\n",
+    "\n",
+    "### Chapter 1: Foundation - WISDEM Rotor Optimization\n",
+    "- **Started** with the IEA 22MW baseline floating wind turbine\n",
+    "- **Scaled** the design to create a 20MW turbine with 270m rotor diameter  \n",
+    "- **Optimized** rotor aerodynamics and structure using steady-state WISDEM models\n",
+    "- **Learned** about design variables, constraints, and merit figures in wind turbine optimization\n",
+    "\n",
+    "### Chapter 2: Integration - Multi-Fidelity System Co-Design\n",
+    "- **Re-tuned** the ROSCO controller for our new rotor design using OpenFAST\n",
+    "- **Optimized** the floating platform using RAFT frequency-domain analysis\n",
+    "- **Refined** the platform design with high-fidelity OpenFAST time-domain simulations\n",
+    "- **Experienced** the systematic progression from fast models to detailed analysis\n",
+    "\n",
+    "### Chapter 3: Validation - Design Load Cases Analysis\n",
+    "- **Applied** industry-standard IEC 61400-3 Design Load Cases\n",
+    "- **Validated** our optimized system against operational and extreme conditions\n",
+    "- **Analyzed** comprehensive load statistics across multiple environmental scenarios\n",
+    "- **Confirmed** our design meets safety and performance requirements\n",
+    "\n",
+    "## Key WEIS Capabilities Demonstrated\n",
+    "\n",
+    "**Multi-Tool Integration:**\n",
+    "- WISDEM for system engineering and initial design\n",
+    "- RAFT for rapid floating platform analysis  \n",
+    "- OpenFAST for detailed aeroelastic simulation\n",
+    "- ROSCO for advanced controller optimization\n",
+    "\n",
+    "**Multi-Fidelity Methodology:**\n",
+    "- Strategic use of appropriate model fidelity for each design phase\n",
+    "- Efficient progression from conceptual design to detailed validation\n",
+    "- Balanced computational cost with engineering accuracy\n",
+    "\n",
+    "**Industry-Standard Workflows:**\n",
+    "- Design Load Case generation and analysis\n",
+    "- Optimization under realistic constraints\n",
+    "- Comprehensive load assessment and validation\n",
+    "\n",
+    "## Next Steps\n",
+    "\n",
+    "To continue developing your WEIS skills:\n",
+    "1. **Explore the examples** in the WEIS repository for different turbine configurations\n",
+    "2. **Modify design variables** and constraints to understand their impacts\n",
+    "3. **Run additional DLCs** for comprehensive design validation\n",
+    "4. **Experiment with different optimization algorithms** and convergence criteria\n",
+    "\n",
+    "The WEIS framework provides the foundation for advanced floating offshore wind research and development. The skills you've developed here prepare you to tackle real-world engineering challenges in this rapidly growing field.\n",
+    "\n",
+    "# Feedback form: https://forms.office.com/g/hRp2YpTpAw"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "68f36455",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "81ebb743",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "weis-eni",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From 7d168954555694d6fe2838cde5717ca652cf1c89 Mon Sep 17 00:00:00 2001
From: dzalkind <dzalkind@nrel.gov>
Date: Mon, 12 Jan 2026 15:11:56 -0700
Subject: [PATCH 7/9] Update workshop functions

---
 .../0_notebooks/weis_workshop.py              | 100 +++++++++++++++++-
 1 file changed, 98 insertions(+), 2 deletions(-)

diff --git a/examples/09_model_creation_process/0_notebooks/weis_workshop.py b/examples/09_model_creation_process/0_notebooks/weis_workshop.py
index 07af50e87..96ad49f9a 100644
--- a/examples/09_model_creation_process/0_notebooks/weis_workshop.py
+++ b/examples/09_model_creation_process/0_notebooks/weis_workshop.py
@@ -3,7 +3,8 @@
 import numpy as np
 import matplotlib.pyplot as plt
 import openmdao.api as om
-
+import pandas as pd
+import pickle
 
 # TODO:
 # 1. Add structural plots for the blade!
@@ -213,4 +214,99 @@ def plotter(x,y, xlabel, ylabel, title, ax=None, label=None):
                     title='Blade Twist Distribution', ax=ax[1], label = 'Optimized')
 
     plt.tight_layout(rect=[0, 0.03, 1, 0.95])
-    # plt.savefig("plots/blade_geometry.png", dpi=300)
\ No newline at end of file
+    # plt.savefig("plots/blade_geometry.png", dpi=300)
+
+def plot_weis_summary(data, y_params=None):
+    """
+    Create nx2 scatter plots of WEIS summary data using absolute values
+    
+    Parameters:
+    data : pandas.DataFrame
+        WEIS summary statistics dataframe with MultiIndex columns
+    y_params : list of tuples, optional
+        List of (parameter_name, statistic) tuples for y-axis parameters
+        If None, uses default set of 4 parameters
+    """
+    # Create a copy to avoid modifying original data
+    df = data.copy()
+    
+    # Extract DLC case from index - fix the extraction method
+    dlc_cases = []
+    for idx in df.index:
+        match = pd.Series([idx]).str.extract(r'(DLC\d+\.\d+)')[0].iloc[0]
+        dlc_cases.append(match)
+    
+    df['DLC_Case'] = dlc_cases
+    
+    # Define the parameters to plot (using absolute values - no normalization)
+    x_param = ('Wind1VelX', 'mean')
+    
+    # Use provided y_params or default set
+    if y_params is None:
+        y_params = [
+            ('GenSpeed', 'mean'),
+            ('RootMyb1', 'max'),
+            ('TwrBsAxMxyt', 'median'),
+            ('PtfmPitch', 'max')
+        ]
+    
+    # Calculate number of rows needed for nx2 layout
+    n_plots = len(y_params)
+    n_rows = (n_plots + 1) // 2  # Ceiling division
+    
+    # Create figure with nx2 subplots and shared x-axis
+    fig, axes = plt.subplots(n_rows, 2, figsize=(15, 6*n_rows), sharex=True)
+    
+    # Handle case where we only have one row
+    if n_rows == 1:
+        axes = axes.reshape(1, -1)
+    
+    # Get unique DLC cases for color coding
+    unique_dlcs = df['DLC_Case'].dropna().unique()
+    colors = plt.cm.Set1(np.linspace(0, 1, len(unique_dlcs)))
+    color_map = dict(zip(unique_dlcs, colors))
+    
+    print(f"Found DLC cases: {unique_dlcs}")
+    
+    # Create each subplot
+    for i, y_param in enumerate(y_params):
+        row = i // 2
+        col = i % 2
+        ax = axes[row, col]
+        
+        # print(f"  Y-axis {i+1} ({y_param}): {df[y_param].min():.4f} to {df[y_param].max():.4f}")
+        
+        # Plot each DLC case with different color
+        for j, dlc in enumerate(unique_dlcs):
+            mask = df['DLC_Case'] == dlc
+            subset = df[mask]
+            
+            # Use absolute values directly - no normalization, no alpha
+            x_vals = subset[x_param].values
+            y_vals = subset[y_param].values
+            
+            ax.scatter(x_vals, y_vals, 
+                      color=colors[j], label=dlc, s=50)
+        
+        # Set labels and title
+        ax.set_ylabel(f'{y_param[0]} ({y_param[1]})')
+        ax.set_title(f'{y_param[0]} ({y_param[1]}) vs {x_param[0]} ({x_param[1]})')
+        ax.grid(True, alpha=0.3)
+        
+        # Add legend only to subplot (0,0) - top left
+        if row == 0 and col == 0:
+            ax.legend(title='DLC Cases')
+        
+        # Let matplotlib handle the scaling automatically
+        ax.autoscale()
+    
+    # Hide any unused subplots
+    if n_plots % 2 == 1:  # If odd number of plots
+        axes[-1, -1].set_visible(False)
+    
+    # Set x-label only on bottom row
+    for col in range(2):
+        if n_rows > 0:
+            axes[-1, col].set_xlabel(f'{x_param[0]} ({x_param[1]})')
+    
+    plt.tight_layout()
\ No newline at end of file

From 2e76ec5c3ad6c35edd04a46580494b343cfcc3da Mon Sep 17 00:00:00 2001
From: dzalkind <dzalkind@nrel.gov>
Date: Mon, 12 Jan 2026 16:25:08 -0700
Subject: [PATCH 8/9] Clean up chapter 1, no drivers

---
 .../0_notebooks/chapter1.ipynb                | 582 +++---------------
 1 file changed, 80 insertions(+), 502 deletions(-)

diff --git a/examples/09_model_creation_process/0_notebooks/chapter1.ipynb b/examples/09_model_creation_process/0_notebooks/chapter1.ipynb
index 31ed49c7b..c50c899fe 100644
--- a/examples/09_model_creation_process/0_notebooks/chapter1.ipynb
+++ b/examples/09_model_creation_process/0_notebooks/chapter1.ipynb
@@ -1,127 +1,5 @@
 {
  "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "fcf9a651",
-   "metadata": {},
-   "source": [
-    "# PLEASE ONLY RUN THE NEXT FOUR CELLS ONCE!\n",
-    "\n",
-    "## Google Colab Runtime Configuration\n",
-    "**Before running any cells, please change the runtime version:**\n",
-    "1. Go to **Edit** → **Notebook Settings** → **Runtime Version** \n",
-    "2. Select **2025.07** \n",
-    "3. Click **Save**\n",
-    "\n",
-    "## Important Notes:\n",
-    "- The setup cells below will install dependencies and may cause kernel restarts\n",
-    "- This is expected behavior - simply continue after each restart\n",
-    "- Only run the setup cells once per session"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "14f61088",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Global variable to check if we're in Google Colab\n",
-    "import sys\n",
-    "IN_COLAB = 'google.colab' in sys.modules\n",
-    "if IN_COLAB:\n",
-    "    ! pip install numpy==1.26.4\n",
-    "    ### The runtime will crash/restart after this"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "a673a11f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Global variable to check if we're in Google Colab\n",
-    "import sys\n",
-    "IN_COLAB = 'google.colab' in sys.modules\n",
-    "\n",
-    "if IN_COLAB:\n",
-    "\n",
-    "  !pip install -q condacolab #-U \"git+https://github.com/mayankchetan/condacolab.git@py312update\"\n",
-    "  import condacolab\n",
-    "  condacolab.install() #### expect a kernel restart"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "0679a464",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "DeprecationWarning: /Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/jsonmerge/__init__.py:27\n",
-      "Accessing Draft4Validator.resolver is deprecated as of v4.18.0, in favor of the https://github.com/python-jsonschema/referencing library, which provides more compliant referencing behavior as well as more flexible APIs for customization."
-     ]
-    }
-   ],
-   "source": [
-    "# Global variable to check if we're in Google Colab\n",
-    "import sys\n",
-    "IN_COLAB = 'google.colab' in sys.modules\n",
-    "\n",
-    "if IN_COLAB:\n",
-    "    !git clone  https://github.com/wisdem/weis\n",
-    "    !git clone https://github.com/mayankchetan/weisWorkshop\n",
-    "\n",
-    "    %cd weis\n",
-    "    !conda config --env --add pinned_packages \"numpy<2.0\"\n",
-    "    !mamba env update -n base -f environment.yml \"python<3.13\"\n",
-    "    %pip install .\n",
-    "    %cd ..\n",
-    "    %pip install \"rosco==2.9.5\"\n",
-    "    %pip install -U \"git+https://github.com/NREL/ROSCO@v2.9.7\"\n",
-    "    %pip install \"orbit-nrel<1.2.2\"\n",
-    "    %pip install gdown\n",
-    "\n",
-    "else:\n",
-    "    try:\n",
-    "        import weis\n",
-    "\n",
-    "    except ImportError:\n",
-    "        raise ImportError(\"Please install the weis package from https://github.com/wisdem/weis in the environment you are using to run this notebook.\")\n",
-    "\n",
-    "    Warning(\"Make sure you have cloned 'https://github.com/mayankchetan/weisWorkshop-Private' repository and are running the notebook from the root directory of the repository.\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "486f157e",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Please download the precomputed data from the link given in the notebook and extract it in the root directory of the repository.\n",
-      "you can use `tar -xvzf <downloaded_file_name>` to extract the files.\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Downloading the precomputed data from Google Drive & extracting\n",
-    "# Drive link for non Google Colab users: https://drive.google.com/file/d/145BH393nzpT2msCVsHSBxR3Qy8KdpddI/view?usp=sharing\n",
-    "if IN_COLAB:\n",
-    "    !gdown 145BH393nzpT2msCVsHSBxR3Qy8KdpddI -O /content/weisWorkshop/archive_weisWorkshop_OCT25.tar.gz\n",
-    "    !tar -xvzf /content/weisWorkshop/archive_weisWorkshop_OCT25.tar.gz -C /content/weisWorkshop/\n",
-    "else:\n",
-    "    print(\"Please download the precomputed data from the link given in the notebook and extract it in the root directory of the repository.\")\n",
-    "    print(\"you can use `tar -xvzf <downloaded_file_name>` to extract the files.\")"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "f010422a",
@@ -171,60 +49,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "2d1a1fee",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Running in local environment\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "if IN_COLAB:\n",
-    "    # Now we try loading the weis_workshop module again\n",
-    "    sys.path.append('/content/weisWorkshop/jupyterNotebooks')\n",
-    "\n",
     "# Importing nesscary libraries.\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "from weis import weis_main\n",
     "from wisdem import run_wisdem\n",
     "import os\n",
-    "import copy\n",
     "import pandas as pd\n",
     "\n",
     "from weis_workshop import *\n",
     "\n",
-    "# workshop repository folder\n",
-    "if IN_COLAB:\n",
-    "    WORKSHOP_REPO = '/content/weisWorkshop'\n",
-    "else:\n",
-    "    WORKSHOP_REPO = os.path.join(os.getcwd(), '..')"
+    "example_dir = os.path.join(os.getcwd(), '..')"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "9a1f97fd",
+   "cell_type": "markdown",
+   "id": "372acfd5",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'/Users/dzalkind/Tools/WEIS-Eni/examples/09_model_creation_process/0_notebooks/..'"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
    "source": [
-    "WORKSHOP_REPO"
+    "# Using Pre-Computed Results\n",
+    "\n",
+    "Download full runs from Google Drive: https://drive.google.com/file/d/145BH393nzpT2msCVsHSBxR3Qy8KdpddI/view?usp=sharing\n",
+    "\n",
+    "Move archive file (archive_weisWorkshop_OCT25.tar.gz) to <weis_dir>examples/09_model_creation_process/1_drivers\n",
+    "\n",
+    "Change to that directory in terminal and run:\n",
+    "```\n",
+    "tar -xvzf archive_weisWorkshop_OCT25.tar.gz -C .\n",
+    "```\n",
+    "\n",
+    "The following flag will let you use the precomputed outputs instead of the test runs currently configured in the drivers\n"
    ]
   },
   {
@@ -234,22 +93,9 @@
    "source": [
     "## Stage 0: Establishing a Baseline\n",
     "\n",
-    "Let's start by running the IEA 22MW floating turbine to understand our starting point. Since we're designing a 20MW turbine, the IEA22MW reference gives us a good baseline that's close to our target size."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "9022e9a5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Setting up file paths\n",
-    "stageFolder = \"stage-0-baseline\"\n",
+    "Let's start by running the IEA 22MW floating turbine to understand our starting point. Since we're designing a 20MW turbine, the IEA22MW reference gives us a good baseline that's close to our target size.\n",
     "\n",
-    "fname_wt_input = os.path.join(WORKSHOP_REPO, \"..\", \"00_setup\", \"ref_turbines\", \"IEA-22-280-RWT_Floater.yaml\")\n",
-    "fname_modeling_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-0-baseline_modeling.yaml\")\n",
-    "fname_analysis_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-0-baseline_analysis.yaml\")\n"
+    "The following inputs are used in `examples/09_model_creation_process/1_drivers/stage-0-baseline` to conduct a baseline analysis of the IEA-22MW reference turbine.\n"
    ]
   },
   {
@@ -352,204 +198,31 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "e9f06246",
+   "cell_type": "markdown",
+   "id": "a6891ab5",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "================\n",
-      "wisdem.wt.wt_rna\n",
-      "================\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[00m\u001b[00m\u001b[00m"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "NL: NLBGS 1 ; 5.81491099e+11 1\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[00m\u001b[00m\u001b[00m"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "NL: NLBGS 2 ; 1207363.87 2.07632391e-06\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[00m\u001b[00m\u001b[00m"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "NL: NLBGS 3 ; 5643.76806 9.70568263e-09\n",
-      "NL: NLBGS Converged\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[00m\u001b[00m"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "UHC input: [0.] -- Mass: [0.]\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[00m"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "ORBIT library intialized at '/Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/library'\n",
-      "Cp-Ct-Cq surfaces completed at 5 %\n",
-      "Cp-Ct-Cq surfaces completed at 10 %\n",
-      "Cp-Ct-Cq surfaces completed at 15 %\n",
-      "Cp-Ct-Cq surfaces completed at 20 %\n",
-      "Cp-Ct-Cq surfaces completed at 25 %\n",
-      "Cp-Ct-Cq surfaces completed at 30 %\n",
-      "Cp-Ct-Cq surfaces completed at 35 %\n",
-      "Cp-Ct-Cq surfaces completed at 40 %\n",
-      "Cp-Ct-Cq surfaces completed at 45 %\n",
-      "Cp-Ct-Cq surfaces completed at 50 %\n",
-      "Cp-Ct-Cq surfaces completed at 55 %\n",
-      "Cp-Ct-Cq surfaces completed at 60 %\n",
-      "Cp-Ct-Cq surfaces completed at 65 %\n",
-      "Cp-Ct-Cq surfaces completed at 70 %\n",
-      "Cp-Ct-Cq surfaces completed at 75 %\n",
-      "Cp-Ct-Cq surfaces completed at 80 %\n",
-      "Cp-Ct-Cq surfaces completed at 85 %\n",
-      "Cp-Ct-Cq surfaces completed at 90 %\n",
-      "Cp-Ct-Cq surfaces completed at 95 %\n",
-      "Cp-Ct-Cq surfaces completed at 100 %\n",
-      "-----------------------------------------------------------------------------\n",
-      "   Tuning a reference wind turbine controller using NREL's ROSCO toolbox    \n",
-      "-----------------------------------------------------------------------------\n",
-      "WARNING: twr_freq and ptfm_freq should be defined for floating turbine control!!\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "DeprecationWarning: /Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/jsonmerge/__init__.py:27\n",
-      "Accessing Draft4Validator.resolver is deprecated as of v4.18.0, in favor of the https://github.com/python-jsonschema/referencing library, which provides more compliant referencing behavior as well as more flexible APIs for customization."
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "----------------\n",
-      "Design Variables\n",
-      "----------------\n",
-      "name  val  size  \n",
-      "----  ---  ---- \n",
-      "\n",
-      "-----------\n",
-      "Constraints\n",
-      "-----------\n",
-      "name  val  size  \n",
-      "----  ---  ---- \n",
-      "\n",
-      "----------\n",
-      "Objectives\n",
-      "----------\n",
-      "name  val  size  \n",
-      "----  ---  ---- \n",
-      "\n",
-      "Run time (outputsCh1): 24.042563915252686\n"
-     ]
-    }
-   ],
    "source": [
-    "# lets overide a few things so that we dont distrupt the existing results.\n",
-    "analysis_override = {}\n",
-    "analysis_override['general'] = {}\n",
-    "analysis_override['general']['folder_output'] = 'outputsCh1'\n",
-    "\n",
-    "\n",
-    "iea22mw, modeling_options, opt_options = weis_main(fname_wt_input, \n",
-    "                                                 fname_modeling_options, \n",
-    "                                                 fname_analysis_options,\n",
-    "                                                 analysis_override=analysis_override,\n",
-    "                                                 test_run=False\n",
-    "                                                 )"
+    "## Run the Stage 0 Driver\n",
+    "\n",
+    "`python 1_drivers/stage-0-baseline/stage-0-baseline_driver.py`"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "d797bf2c",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "there are 4691 variables in the baseline design:\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "Index(['sse_tune.v_min', 'sse_tune.v_max', 'sse_tune.r', 'sse_tune.chord',\n",
-       "       'sse_tune.theta', 'sse_tune.Rhub', 'sse_tune.Rtip',\n",
-       "       'sse_tune.hub_height', 'sse_tune.precone', 'sse_tune.tilt',\n",
-       "       ...\n",
-       "       'rotorse.rs.strains.axial_root_sparU_load2stress',\n",
-       "       'rotorse.rs.strains.axial_root_sparL_load2stress',\n",
-       "       'rotorse.rs.strains.axial_maxc_teU_load2stress',\n",
-       "       'rotorse.rs.strains.axial_maxc_teL_load2stress',\n",
-       "       'rotorse.rs.tip_pos.tip_deflection', 'rotorse.rs.tot_loads_gust.Px_af',\n",
-       "       'rotorse.rs.tot_loads_gust.Py_af', 'rotorse.rs.tot_loads_gust.Pz_af',\n",
-       "       'rotorse.stall_check.no_stall_constraint',\n",
-       "       'rotorse.stall_check.stall_angle_along_span'],\n",
-       "      dtype='object', name='variables', length=4691)"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Lets analyize the baseline design!!\n",
-    "baseline_turb = pd.read_csv(os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"outputsCh1/stage-0-baseline.csv\"), index_col=0)\n",
+    "\n",
+    "use_precomputed = False\n",
+    "if use_precomputed:\n",
+    "    output_folder = \"outputs_preCompute\"\n",
+    "else:\n",
+    "    output_folder = \"outputs\"\n",
+    "\n",
+    "baseline_turb = pd.read_csv(os.path.join(example_dir, \"1_drivers\", \"stage-0-baseline\", output_folder, \"stage-0-baseline.csv\"), index_col=0)\n",
     "# Open the CSV file shown above so explore the various variables output from WISDEM/WEIS\n",
     "\n",
     "print(f'there are {len(baseline_turb.index)} variables in the baseline design:')\n",
@@ -575,21 +248,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "id": "a337aa4f",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x1000 with 6 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plot_comparison_plot(baseline_turb, label='IEA22MW')"
    ]
@@ -665,29 +327,15 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 24,
-   "id": "6de3bf63",
+   "cell_type": "markdown",
+   "id": "438a4a98",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "# Setting up file paths, and defining the WEIS overide for this stage\n",
-    "stageFolder = \"stage-1-aeroStruct\"\n",
-    "\n",
-    "fname_wt_input = os.path.join(WORKSHOP_REPO, \"2_models\", \"new-20-270-RWT_Floater_v2p0.yaml\")\n",
-    "fname_modeling_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-1-aeroStruct_modeling.yaml\")\n",
-    "fname_analysis_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-1-aeroStruct_analysis.yaml\")\n",
+    "# Run WISDEM with Scaled Rotor\n",
     "\n",
-    "# fname_wt_input = os.path.join(WORKSHOP_REPO, \"..\", \"00_setup\", \"ref_turbines\", \"IEA-22-280-RWT_Floater.yaml\")\n",
-    "# fname_modeling_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-0-baseline_modeling.yaml\")\n",
-    "# fname_analysis_options = os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder, \"stage-0-baseline_analysis.yaml\")\n",
+    "This script will run the geometry through WISDEM without any optimization, demonstrating the need to re-optimize the blade planform when scaling rotors\n",
     "\n",
-    "# We dont have analysis, and modeling options overrides in WISDEM\n",
-    "# analysis_override = {}\n",
-    "# analysis_override['general'] = {}\n",
-    "# analysis_override['general']['folder_output'] = 'outputsCh1'\n",
-    "# analysis_override['driver'] = {}\n",
-    "# analysis_override['driver']['max_iter'] = 1 # only run one iteration for this demo, we have precomputed the solutions for you :)"
+    "Run: `python examples/09_model_creation_process/1_drivers/stage-1-aeroStruct/stage-1-aeroStruct_driver.py`\n"
    ]
   },
   {
@@ -695,7 +343,8 @@
    "id": "69f2e17b",
    "metadata": {},
    "source": [
-    "## Examining the Input Files\n",
+    "## Examining the Input Files in `stage-1-aeroStruct`\n",
+    "\n",
     "\n",
     "### Google Colab Users:\n",
     "1. Go to the file browser on the left\n",
@@ -837,67 +486,9 @@
    "id": "97a12e68",
    "metadata": {},
    "source": [
-    "## 1.1: Configuration Check\n",
-    "\n",
-    "**Before running the optimization, please verify these settings:**\n",
-    "\n",
-    "1. **Output path**: Update the analysis options file to set output path to `outputsCh1`\n",
-    "2. **Iteration limit**: Set `max_iter` to `1` (we'll use precomputed results for this demonstration)\n",
-    "\n",
-    "These modifications ensure the demo runs quickly while preserving your existing output files."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "id": "441cb849",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/openmdao/visualization/n2_viewer/n2_viewer.py:115: OpenMDAOWarning:attempt to get argmin of an empty sequence\n",
-      "\u001b[00mOptimizeWarning: /Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/openmdao/drivers/scipy_optimizer.py:487\n",
-      "Unknown solver options: rhobeg, catol, adaptive\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m\u001b[00m"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Iteration limit reached    (Exit mode 9)\n",
-      "            Current function value: 0.43830741633150294\n",
-      "            Iterations: 1\n",
-      "            Function evaluations: 2\n",
-      "            Gradient evaluations: 2\n",
-      "Optimization FAILED.\n",
-      "Iteration limit reached\n",
-      "-----------------------------------\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "RuntimeWarning: /Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/wisdem/towerse/tower.py:369\n",
-      "invalid value encountered in divide\u001b[00mDeprecationWarning: /Users/dzalkind/miniforge3/envs/weis-eni/lib/python3.11/site-packages/jsonmerge/__init__.py:27\n",
-      "Accessing Draft4Validator.resolver is deprecated as of v4.18.0, in favor of the https://github.com/python-jsonschema/referencing library, which provides more compliant referencing behavior as well as more flexible APIs for customization."
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WISDEM run completed in, 458.6125340461731 seconds\n"
-     ]
-    }
-   ],
-   "source": [
+    "## Run Stage 1 Driver\n",
     "\n",
-    "wt_opt, modeling_options, analysis_options = run_wisdem(\n",
-    "        fname_wt_input, fname_modeling_options, fname_analysis_options\n",
-    "    )\n"
+    "Run: `python examples/09_model_creation_process/1_drivers/stage-1-aeroStruct/stage-1-aeroStruct_driver.py`"
    ]
   },
   {
@@ -917,34 +508,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "id": "7385cf21",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1200x1000 with 6 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 1200x500 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "baseline_turb = pd.read_csv(os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder,\"outputs_nonOpti/stage-1-aeroStruct-NonOptimized.csv\"), index_col=0)\n",
-    "optimized_turb = pd.read_csv(os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder,\"outputs_preCompute/stage-1-aeroStruct-aero_analysis.csv\"), index_col=0)\n",
+    "stageFolder = \"stage-1-aeroStruct\"\n",
+    "\n",
+    "baseline_turb = pd.read_csv(os.path.join(example_dir, \"1_drivers\", stageFolder,\"outputs_nonOpti\", \"stage-1-aeroStruct-NonOptimized.csv\"), index_col=0)\n",
+    "\n",
+    "use_precomputed = True\n",
+    "if use_precomputed:\n",
+    "    output_folder = \"outputs_preCompute\"\n",
+    "else:\n",
+    "    output_folder = \"outputs\"\n",
+    "\n",
+    "\n",
+    "optimized_turb = pd.read_csv(os.path.join(example_dir, \"1_drivers\", stageFolder, output_folder, \"stage-1-aeroStruct-aero_analysis.csv\"), index_col=0)\n",
+    "\n",
     "\n",
     "plot_rotor_comparison(baseline_turb, optimized_turb)"
    ]
@@ -968,32 +549,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "id": "d43d648b",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "loading /Users/dzalkind/Tools/WEIS-Eni/examples/09_model_creation_process/0_notebooks/../1_drivers/stage-1-aeroStruct/outputs_preCompute/log_opt.sql\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x4200 with 7 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "rec_data = load_OMsql(os.path.join(WORKSHOP_REPO, \"1_drivers\", stageFolder,\"outputs_preCompute/log_opt.sql\")) # not sure what supresses the output here\n",
-    "plot_convergence(rec_data, ['financese.lcoe', 'tcons.tip_deflection_ratio', 'blade.opt_var.af_position', 'blade.opt_var.chord_opt', 'blade.pa.max_chord_constr',\n",
-    "                            'rotorse.rs.constr.constr_max_strainL_spar', 'rotorse.rs.constr.constr_max_strainU_spar'])"
+    "use_precomputed = False\n",
+    "if use_precomputed:\n",
+    "    output_folder = \"outputs_preCompute\"\n",
+    "else:\n",
+    "    output_folder = \"outputs\"\n",
+    "\n",
+    "rec_data = load_OMsql(os.path.join(example_dir, \"1_drivers\", stageFolder, output_folder,\"log_opt.sql\")) # not sure what supresses the output here\n",
+    "\n",
+    "\n",
+    "plot_convergence(rec_data, [\n",
+    "    'financese.lcoe',\n",
+    "    'tcons.tip_deflection_ratio',\n",
+    "    'blade.opt_var.af_position',\n",
+    "    'blade.opt_var.chord_opt',\n",
+    "    'blade.pa.max_chord_constr',\n",
+    "    'rotorse.rs.constr.constr_max_strainL_spar',\n",
+    "    'rotorse.rs.constr.constr_max_strainU_spar'\n",
+    "    ])"
    ]
   },
   {

From 70c9a74a3ade50bd635c4577b4092988de23a63d Mon Sep 17 00:00:00 2001
From: dzalkind <dzalkind@nrel.gov>
Date: Thu, 15 Jan 2026 14:28:44 -0700
Subject: [PATCH 9/9] Add TI/class to turbsim file name

---
 weis/aeroelasticse/utils.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/weis/aeroelasticse/utils.py b/weis/aeroelasticse/utils.py
index b69628de7..95d83ada8 100644
--- a/weis/aeroelasticse/utils.py
+++ b/weis/aeroelasticse/utils.py
@@ -526,6 +526,7 @@ def generate_wind_files(dlc_generator, FAST_namingOut, wind_directory, rotorD, h
 
         # Write out turbsim input file
         turbsim_input_file_name = FAST_namingOut + '_' + dlc_generator.cases[i_case].IEC_WindType + (
+                                dlc_generator.cases[i_case].IECturbc + 
                                 '_U%1.6f'%dlc_generator.cases[i_case].URef +
                                 '_Seed%1.1f'%dlc_generator.cases[i_case].RandSeed1) + '.in'
         wind_file_path_InflowWind = os.path.join(wind_directory, turbsim_input_file_name[:-3] + '.bts')