diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 0b3839a65502145d874f8ea8d8ac953693a1ca25..3d006f68cddf9a9972d2c79f7796ddfba067970b 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -1,4 +1,5 @@
 stages:
+  - testing
   - build
   - test
   - deploy
@@ -110,6 +111,17 @@ deploy staging documentation:
   only:
     - develop
 
+deploy rrz:
+  image: alpine
+  stage: testing
+  before_script:
+    - sh bin/enable_ssh
+  script:
+    - ssh git@gitlab.rrz.uni-hamburg.de
+  only:
+    - master # TODO remove
+    - tags
+
 test pip deployment:
   image: python:3
   stage: deploy-test
diff --git a/setup.cfg b/setup.cfg
index 1b5c9c7971bea1eefa3e5ef4e1428c6d902b57c9..3548b6c47dc7d7646fcf42a26ea9720dccf00ab5 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -4,10 +4,10 @@
 
 [metadata]
 name = NQontrol
-description = Python control program for ADwin servos.
-author = Christian Darsow-Fromm
+description = Python program for digital control-loops.
+author = LasNQ – Uni Hamburg
 author-email = christian.darsow@physik.uni-hamburg.de
-license = mit
+license = GPL v3
 # url = http://
 long-description = file: README.rst
 # Change if running only on Windows, Mac or Linux (comma-separated)
diff --git a/unordered/20171211 SHG Transferfunction Measurement/Transfer function measurement.ipynb b/unordered/20171211 SHG Transferfunction Measurement/Transfer function measurement.ipynb
deleted file mode 100644
index 9e5976a7d0c033e2a9caee7392b9972ca2a5a8a3..0000000000000000000000000000000000000000
--- a/unordered/20171211 SHG Transferfunction Measurement/Transfer function measurement.ipynb	
+++ /dev/null
@@ -1,144 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Im Versuchsaufbau wird ein Laser durch einen Resonator geschickt in der ein Kristall zur Frequenzverdopplung ist, dieser Resonator wird durch das Pound-Drever-Hall verfahren stabilisiert. Das dabei entsehende Fehlersignal wird an einen Servo weitergegeben, welcher zur aktiven Regelung dient. Dieser leitet das verarbeitete Fehlersignal an einen HV-Verstärker weiter welcher einen Piezokristall mit Spannung versorgt und die Länge des Resonators verändert. Da dieser analoge Servo gegen einen digitalen ausgetauscht werden soll, wurde im folgendem die Transferfuntkion vom HV-Verstärker bis zur Photodiode gemessen."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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yPAe//MAGLllePKu5pqNhNgksJkEkPgNtplJD/Lb0j2yr2cSHzl/Ej585zE3Nfayp1kLj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V58Rl82Y/Kpn+7klicHAXhg3yh97jfMf3/oEG9/0SbCAR/fefAQrz53FZZtuPPpITqjO7llxyB7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\nUkoplVf+P3Boa02vMsHjAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x981d320>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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qDzb60h0V/ueFY0gk/nDCEPEAJXYL0USSq1dUc/ulLTy+s4PjfUF+v7uDR19r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\nAXyySGOxMLO2DN85Z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1Lp1ruUBTBF90rKroL5hIhQ43Uk96CO4meR9Q0ScxW/uaGHQ1Ug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\ngg1UhmEYhmEYpqRgA5VhGIZhGIYpKf4/E9MoVXcJF9oAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xa49ec50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "import matplotlib.pyplot as plt\n",
-    "import pylab\n",
-    "df = pd.read_csv('tf2.csv',';')\n",
-    "df=df.values\n",
-    "df=np.transpose(df)\n",
-    "pylab.figure( figsize=(11,11) )\n",
-    "ax1= plt.subplot(3,1,1)\n",
-    "ax1.set_ylabel('gain (db)')\n",
-    "ax1.set_xlabel('frequency (Hz)')\n",
-    "plt.semilogx(df[1],df[3])\n",
-    "ax2 = plt.subplot(312)\n",
-    "ax2.set_xlabel('frequency (Hz)')\n",
-    "ax2.set_ylabel('phase (°)')\n",
-    "plt.semilogx(df[1],df[4])\n",
-    "df = pd.read_csv('tf3.csv',';')\n",
-    "df=df.values\n",
-    "df=np.transpose(df)\n",
-    "pylab.figure( figsize=(11,11) )\n",
-    "ax3= plt.subplot(3,1,1)\n",
-    "ax3.set_ylabel('gain (db)')\n",
-    "ax3.set_xlabel('frequency (Hz)')\n",
-    "plt.semilogx(df[1],df[3])\n",
-    "ax4 = plt.subplot(312)\n",
-    "ax4.set_xlabel('frequency (Hz)')\n",
-    "ax4.set_ylabel('phase (°)')\n",
-    "plt.semilogx(df[1],df[4])\n",
-    "plt.grid\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In den Abbildungen ist die Transferfunktion des Aufbaus von dem HV-Amplfier bis zur Photodiode zu sehen. Anzumerken, ist das ab frequenzen von fast $10^5$, das System anfängt instabil zu werden, wie am Springen der Phase und des Gains zu erkennen ist. Digital regeln lässt sich jedoch nur ein kleiner Frequenzbereich mithilfe von Regelungstechnik."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from nqlab import *"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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Kh9YWQMQAT87KxNWj/J8EsvZwDff/siajx/baNpPHZfzFiwBhsx3gHAtX1KDH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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x106d71390>"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {
-      "image/png": {
-       "height": 278,
-       "width": 396
-      }
-     },
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data = io.read('tf2.csv')\n",
-    "plots.amplitude_phase(data['Gain (dB)'], data['Phase (deg)'])"
-   ]
-  }
- ],
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-  "kernelspec": {
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-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
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-   "toc_position": {},
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-   "toc_window_display": false
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- "nbformat": 4,
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diff --git a/unordered/20171211 SHG Transferfunction Measurement/tf2.csv b/unordered/20171211 SHG Transferfunction Measurement/tf2.csv
deleted file mode 100644
index 07a2aafd698965a4e9867993909643f4145f917d..0000000000000000000000000000000000000000
--- a/unordered/20171211 SHG Transferfunction Measurement/tf2.csv	
+++ /dev/null
@@ -1,402 +0,0 @@
-#; Frequency (Hz); Amplitude (Vpp); Gain (dB); Phase (?)
-1;100;0.01;22.69;-2.71
-2;102.3;0.01;20.26;-30.59
-3;104.7;0.01;25.87;-27.96
-4;107.2;0.01;22.76;-8.78
-5;109.6;0.01;22.83;19.04
-6;112.2;0.01;22.9;18.89
-7;114.8;0.01;21.9;-0.67
-8;117.5;0.01;22.97;0.24
-9;120.2;0.01;20.58;-34.46
-10;123;0.01;20.64;-4.38
-11;125.9;0.01;24.88;-11.85
-12;128.8;0.01;22.96;19.72
-13;131.8;0.01;22.55;-23.27
-14;134.9;0.01;23.77;28.32
-15;138;0.01;22.26;32.7
-16;141.3;0.01;28.9;1.01
-17;144.5;0.01;25.2;-27.69
-18;147.9;0.01;22.41;-12.22
-19;151.4;0.01;22.8;-17.72
-20;154.9;0.01;29.23;15.17
-21;158.5;0.01;21.67;-10.53
-22;162.2;0.01;25.48;27.85
-23;166;0.01;21.66;16.84
-24;169.8;0.01;31.96;-13.27
-25;173.8;0.01;25;-6.48
-26;177.8;0.01;27.79;-1.41
-27;182;0.01;22.8;-2.29
-28;186.2;0.01;22.95;5.82
-29;190.5;0.01;25.44;-13.53
-30;195;0.01;23.77;-12.42
-31;199.5;0.01;25.97;-4
-32;204.2;0.01;27.18;-18.2
-33;208.9;0.01;23.29;2.77
-34;213.8;0.01;26.94;25.74
-35;218.8;0.01;28.33;4.14
-36;223.9;0.01;22.65;3.19
-37;229.1;0.01;21.31;13.28
-38;234.4;0.01;21.95;-5.98
-39;239.9;0.01;24.7;8.95
-40;245.5;0.01;28.94;14.96
-41;251.2;0.01;28.15;20.95
-42;257;0.01;22.76;5.17
-43;263;0.01;26.25;-0.02
-44;269.2;0.01;23.07;-10.09
-45;275.4;0.01;28.79;0.99
-46;281.8;0.01;25.21;-17.18
-47;288.4;0.01;27.53;-4.86
-48;295.1;0.01;22.52;-1.7
-49;302;0.01;23.94;-4.85
-50;309;0.01;24.54;-4.95
-51;316.2;0.01;23.57;6.86
-52;323.6;0.01;24.91;10.4
-53;331.1;0.01;23.02;-5.1
-54;338.8;0.01;25.38;-0.77
-55;346.7;0.01;24.15;1.71
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-57;363.1;0.01;24.44;2.49
-58;371.5;0.01;24.15;-2.92
-59;380.2;0.01;25.46;-4.11
-60;389;0.01;24.24;-0.68
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-62;407.4;0.01;23.72;-3.78
-63;416.9;0.01;23.93;-1.44
-64;426.6;0.01;24.59;-0.88
-65;436.5;0.01;25.13;4.23
-66;446.7;0.01;24.25;-7.84
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-69;478.6;0.01;24.9;-0.52
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-71;501.2;0.01;25;0.25
-72;512.9;0.01;24.85;0.25
-73;524.8;0.01;24.23;0.95
-74;537;0.01;25.28;5.03
-75;549.5;0.01;24.17;2.43
-76;562.3;0.01;24.51;3.09
-77;575.4;0.01;24.61;-4.25
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diff --git a/unordered/20171211 SHG Transferfunction Measurement/tf3.csv b/unordered/20171211 SHG Transferfunction Measurement/tf3.csv
deleted file mode 100644
index 87d8ce3cdf2fb95b50362569099589deb997a128..0000000000000000000000000000000000000000
--- a/unordered/20171211 SHG Transferfunction Measurement/tf3.csv	
+++ /dev/null
@@ -1,472 +0,0 @@
-#; Frequency (Hz); Amplitude (Vpp); Gain (dB); Phase (?)
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-2;20.4;0.01;28.69;70.41
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diff --git a/unordered/Filterberechnung/Integrator.ipynb b/unordered/Filterberechnung/Integrator.ipynb
deleted file mode 100644
index 2e015ec33b4a22d9841d1fbf3df6d2bf2dbb6c73..0000000000000000000000000000000000000000
--- a/unordered/Filterberechnung/Integrator.ipynb
+++ /dev/null
@@ -1,152 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import math as math\n",
-    "import scipy.signal as sig\n",
-    "import matplotlib.pyplot as plt"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "An integrator with gain k at $f=0$ and a cutoff frequency of $f_1$ and a drop in amplitude until $\\left|H(s)\\right|=1$ can be obtained with the following transfer function.\n",
-    "\n",
-    "$$\\begin{equation}H\\left( s\\right) = k\\cdot\\frac{1+\\frac{s}{k\\cdot f_1}}{1+\\frac{s}{f_1}}\\end{equation}$$\n",
-    "The frequency response of an example is plotted below with gain $k=10$ and $f_1=100$\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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/J8yvrj6Rs0+o4PsPr+an89/SaKUBUSMQkcAcaQZXTB3ITc+u5Wv3r+Bwk64z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\nTo1ARCTL/R/ejnV516VvhQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xb11a978>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "w,h=sig.freqs([0.01,10],[0.01,1],worN=np.logspace(-1, 4, 1000))\n",
-    "\n",
-    "plt.semilogx(w, abs(h))\n",
-    "plt.xlabel('Frequency')\n",
-    "plt.ylabel('Amplitude response')\n",
-    "plt.grid()\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Notable is, that there is a transition at the end and start of the integration intervall. \n",
-    "The Transfer function is only useful when dealing with continious time systems. Since the calculation is done digital we have a time discret system. With the help of the bilinear transform(also known as Tustin's method) it is possible to transform the Transfer function into a discrete time representation. The z-Transform is the discrete time equivalent of the laplace transform. And the connection betwen both is:\n",
-    "$$\\begin{equation}z=e^{sT}\\end{equation}$$\n",
-    "with T being the inverse sampling rate. By taking the logarithm of z you get:\n",
-    "$$\\begin{equation} s=\\frac{1}{T}ln(z)=\\frac{2}{T}\\left(\\frac{z-1}{z+1}+\\frac{1}{3}\\left(\\frac{z-1}{z+1}\\right)^3+....\\right)\\end{equation}.$$\n",
-    "By stopping the series after the first order you get the bilinear transform:\n",
-    "$$s\\approx \\frac{2}{T}\\frac{z-1}{z+1}=\\frac{2}{T}\\frac{1-z^{-1}}{1+z^{-1}}.$$\n",
-    "Which can be used to calculate the impulse response in real time.\n",
-    "It is done by a change of variables.\n",
-    "$$\\begin{equation} s\\rightarrow \\frac{1-z^{-1}}{1+z^{-1}} \\end{equation}$$\n",
-    "$$\\begin{equation}H(s)\\rightarrow H(z)\\end{equation}$$\n",
-    "the expression after the change of variables is,\n",
-    "$$\\begin{equation}H\\left(z\\right)=k\\cdot\\frac{1+\\frac{2}{Tk\\omega_1}\\frac{1-z^{-1}}{1+z^{-1}}}{{1+\\frac{2}{T\\omega_1}\\frac{1-z^{-1}}{1+z^{-1}}}}\\end{equation}.$$\n",
-    "By expanding the fractions with $(1+z^{-1})$ you get:\n",
-    "$$\\begin{equation}H\\left(z\\right)=k\\cdot\\frac{\\left(1+\\frac{2}{Tk\\omega_1}\\right)+\\left(1-\\frac{2}{Tk\\omega_1}\\right)z^{-1}}{\\left(1+\\frac{2}{T\\omega_1}\\right)+\\left(1-\\frac{2}{T\\omega_1}\\right)z^{-1}}\\end{equation}$$\n",
-    "The entire $i\\omega$-axis is mapped on the unit circle in the z-plane. A filter is evaluated by setting $z=e^{i\\omega T}$.\n",
-    "This gives a non-linear relationship between the digital ($\\omega_d$) and analogue ($\\omega_a$) frequencies:\n",
-    "$$\\begin{equation}\\omega_a=\\frac{2}{T}\\frac{1-e^{-i\\omega_dT}}{1+e^{-i\\omega_dT}}=\\frac{2}{T}\\frac{e^{0.5i\\omega_dT}-e^{-0.5i\\omega_dT}}{e^{0.5i\\omega_dT}+e^{-0.5i\\omega_dT}}=\\frac{2}{T}tanh\\left(0.5i\\omega_dT\\right)\\end{equation}.$$\n",
-    "Therefor the cutoff frequencies have to be pre-warped to compensate for the nonlinear relationship.\n",
-    "$$\\omega_1'=\\frac{2}{T}tan\\left(\\frac{\\pi}{2}\\frac{f_1}{f_n}\\right), \\omega_2'=\\frac{2}{T}tan\\left(\\frac{\\pi}{2}\\frac{kf_1}{f_n}\\right)$$\n",
-    "With the nyquist frequency $f_n$.\n",
-    "After the warping the expression for $H(z)$ changes to:\n",
-    "$$\\begin{equation}H\\left(z\\right)=k\\cdot\\frac{\\left(1+\\frac{2}{T\\omega_2'}\\right)+\\left(1-\\frac{2}{T\\omega_2'}\\right)z^{-1}}{\\left(1+\\frac{2}{T\\omega_1'}\\right)+\\left(1-\\frac{2}{T\\omega_1'}\\right)z^{-1}}\\end{equation}$$\n",
-    "or with $\\omega_1''=\\omega_1'\\cdot\\frac{T}{2}$ and $\\omega_2''=\\omega_2'\\cdot\\frac{T}{2}$ to:\n",
-    "$$\\begin{equation}H\\left(z\\right)=k\\cdot\\frac{\\left(1+\\frac{1}{\\omega_2''}\\right)+\\left(1-\\frac{1}{\\omega_2''}\\right)z^{-1}}{\\left(1+\\frac{1}{\\omega_1''}\\right)+\\left(1-\\frac{1}{\\omega_1''}\\right)z^{-1}}\\end{equation}$$\n",
-    "The following python code calculates the coefficients of the numerator and the denominator and normalize them"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "#k is the gain at f=0\n",
-    "#f1 is the cuttof frequency in comparison to the nyquist frequency\n",
-    "#the code calculates the bilinear z transform of a transfer function composed out of G*H(s)/G(s) while G(z) and H(z) are\n",
-    "#first Order Butterworth filter with cutoff frequencies at f=f1 and f=f1*k.\n",
-    "#the function returns the coefficients of (b[0]+b[1]*z^-1+b[2]*z^-2)/(a[0]+a[1]*z^-1+b[2]*z^-2)\n",
-    "#the coefficients are normalised such that a[0]=1\n",
-    "def Integrator(k,f1):\n",
-    "    if(k<=0):\n",
-    "        raise Exception('gain is zero or is below zero')\n",
-    "    elif(f1<=0):\n",
-    "        raise Exception('cutoff frequency is zero or is below zero')\n",
-    "    elif f1>=1:\n",
-    "        raise Exception('frequency exceeds nyquistfrequency')\n",
-    "    elif k*f1>=1:\n",
-    "        raise Exception('frequency for 0dB cutoff is beyond nyquistfrequency')\n",
-    "    omega=np.zeros(2)\n",
-    "    omega_1=math.tan(0.5*math.pi*f1)\n",
-    "    omega_2=math.tan(0.5*math.pi*f1*k)\n",
-    "    b= np.zeros(3)\n",
-    "    a=np.zeros(3)\n",
-    "    a[0]=(1+1/omega_1)\n",
-    "    a[1]=(1-1/omega_1)/a[0]\n",
-    "    b[0]=k*(1+1/omega_2)/a[0]\n",
-    "    b[1]=k*(1-1/omega_2)/a[0]\n",
-    "    a[0]=1.0\n",
-    "    return [b,a]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/unordered/Filterberechnung/Integrator.py b/unordered/Filterberechnung/Integrator.py
deleted file mode 100644
index b7a0e286d76fc514b21e328ea368d43c92df4bc1..0000000000000000000000000000000000000000
--- a/unordered/Filterberechnung/Integrator.py
+++ /dev/null
@@ -1,29 +0,0 @@
-import numpy as np
-import math as math
-import scipy.signal as sig
-#k is the gain at f=0
-#f1 is the cuttof frequency in comparison to the nyquist frequency
-#the code calculates the bilinear z transform of a transfer function composed out of G*H(s)/G(s) while G(z) and H(z) are
-#first Order Butterworth filter with cutoff frequencies at f=f1 and f=f1*k.
-#the function returns the coefficients of (b[0]+b[1]*z^-1+b[2]*z^-2)/(a[0]+a[1]*z^-1+b[2]*z^-2)
-def Integrator(k,f1):
-    if(k<=0):
-        raise Exception('gain is zero or is below zero')
-    elif(f1<=0):
-        raise Exception('cutoff frequency is zero or is below zero')
-    elif f1>=1:
-        raise Exception('frequency exceeds nyquistfrequency')
-    elif k*f1>=1:
-        raise Exception('frequency for 0dB cutoff is beyond nyquistfrequency')
-    omega=np.zeros(2)
-    omega[0]=math.tan(0.5*math.pi*f1)
-    omega[1]=math.tan(0.5*math.pi*f1*k)
-    b= np.zeros(3)
-    a=np.zeros(3)
-    a[0]=(1+1/omega[0])
-    a[1]=(1-1/omega[0])/a[0]
-    b[0]=k*(1+1/omega[1])/a[0]
-    b[1]=k*(1-1/omega[1])/a[0]
-    a[0]=1.0
-    return [b,a]
-
diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/1.csv b/unordered/Measurements/20180503 Aliasing effect measurements/1.csv
deleted file mode 100644
index 977782644452bf3cbc5dd9a64dfa3023bdbb2c91..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/1.csv	
+++ /dev/null
@@ -1,472 +0,0 @@
-#, Frequency (Hz), Amplitude (Vpp), Gain (dB), Phase (�)
-1,20.0,0.0100,19.96,-0.03
-2,20.4,0.0100,19.92,-0.18
-3,20.9,0.0100,19.93,-0.12
-4,21.4,0.0100,19.95,-0.18
-5,21.9,0.0100,19.96,-0.18
-6,22.4,0.0100,19.95,-0.18
-7,22.9,0.0100,19.94,-0.10
-8,23.4,0.0100,19.94,-0.18
-9,24.0,0.0100,19.92,-0.34
-10,24.5,0.0100,19.92,-0.35
-11,25.1,0.0100,19.95,-0.32
-12,25.7,0.0100,19.96,-0.18
-13,26.3,0.0100,19.96,-0.18
-14,26.9,0.0100,19.96,-0.32
-15,27.5,0.0100,19.93,-0.18
-16,28.2,0.0100,19.95,-0.24
-17,28.8,0.0100,19.92,-0.18
-18,29.5,0.0100,19.92,-0.10
-19,30.2,0.0100,19.92,-0.35
-20,30.9,0.0100,19.92,-0.17
-21,31.6,0.0100,19.94,-0.18
-22,32.4,0.0100,19.95,-0.35
-23,33.1,0.0100,19.92,-0.18
-24,33.9,0.0100,19.95,-0.21
-25,34.7,0.0100,19.96,-0.32
-26,35.5,0.0100,19.95,-0.24
-27,36.3,0.0100,19.99,-0.18
-28,37.2,0.0100,19.96,-0.50
-29,38.0,0.0100,19.98,-0.18
-30,38.9,0.0100,19.96,-0.69
-31,39.8,0.0100,19.93,-0.78
-32,40.7,0.0100,19.90,0.59
-33,41.7,0.0100,19.93,0.61
-34,42.7,0.0100,19.81,-0.48
-35,43.7,0.0100,20.07,-0.49
-36,44.7,0.0100,19.92,-1.31
-37,45.7,0.0100,19.97,-1.38
-38,46.8,0.0100,20.00,1.04
-39,47.9,0.0100,20.08,-0.88
-40,49.0,0.0100,20.08,-1.05
-41,50.1,0.0100,20.04,1.05
-42,51.3,0.0100,19.81,-0.89
-43,52.5,0.0100,19.83,0.88
-44,53.7,0.0100,20.00,1.17
-45,55.0,0.0100,19.81,0.83
-46,56.2,0.0100,19.88,-1.30
-47,57.5,0.0100,19.96,0.84
-48,58.9,0.0100,20.00,-1.09
-49,60.3,0.0100,19.88,-0.97
-50,61.7,0.0100,20.03,0.31
-51,63.1,0.0100,20.03,0.49
-52,64.6,0.0100,19.99,0.48
-53,66.1,0.0100,19.89,0.64
-54,67.6,0.0100,19.92,-0.69
-55,69.2,0.0100,19.99,-0.58
-56,70.8,0.0100,19.92,-0.57
-57,72.4,0.0100,20.03,-0.32
-58,74.1,0.0100,19.99,0.07
-59,75.9,0.0100,19.93,-0.51
-60,77.6,0.0100,19.92,-0.18
-61,79.4,0.0100,19.95,-0.44
-62,81.3,0.0100,19.91,0.00
-63,83.2,0.0100,19.96,-0.27
-64,85.1,0.0100,19.93,-0.21
-65,87.1,0.0100,19.97,-0.18
-66,89.1,0.0100,19.97,-0.18
-67,91.2,0.0100,19.93,0.01
-68,93.3,0.0100,19.92,-0.18
-69,95.5,0.0100,19.96,-0.00
-70,97.7,0.0100,19.96,-0.18
-71,100.0,0.0100,19.96,-0.18
-72,102.3,0.0100,19.93,0.03
-73,104.7,0.0100,19.92,-0.21
-74,107.2,0.0100,19.94,-0.18
-75,109.6,0.0100,19.99,-0.07
-76,112.2,0.0100,19.97,-0.41
-77,114.8,0.0100,19.96,-0.25
-78,117.5,0.0100,20.00,-0.35
-79,120.2,0.0100,19.88,0.09
-80,123.0,0.0100,19.98,0.28
-81,125.9,0.0100,20.04,-0.46
-82,128.8,0.0100,19.89,-0.60
-83,131.8,0.0100,19.96,-0.84
-84,134.9,0.0100,19.84,-0.18
-85,138.0,0.0100,19.92,-0.88
-86,141.3,0.0100,20.06,0.18
-87,144.5,0.0100,19.92,0.70
-88,147.9,0.0100,19.92,0.54
-89,151.4,0.0100,19.81,-0.38
-90,154.9,0.0100,20.03,-0.53
-91,158.5,0.0100,19.91,0.53
-92,162.2,0.0100,19.88,0.53
-93,166.0,0.0100,20.00,0.62
-94,169.8,0.0100,20.02,-0.43
-95,173.8,0.0100,19.96,0.54
-96,177.8,0.0100,19.99,-0.75
-97,182.0,0.0100,19.84,-0.35
-98,186.2,0.0100,19.99,-0.73
-99,190.5,0.0100,19.92,-0.52
-100,195.0,0.0100,19.96,-0.50
-101,199.5,0.0100,19.90,0.35
-102,204.2,0.0100,19.84,-0.18
-103,208.9,0.0100,20.02,0.00
-104,213.8,0.0100,19.96,-0.27
-105,218.8,0.0100,19.95,-0.35
-106,223.9,0.0100,19.96,-0.38
-107,229.1,0.0100,20.00,0.18
-108,234.4,0.0100,19.96,-0.18
-109,239.9,0.0100,19.92,-0.34
-110,245.5,0.0100,19.96,-0.53
-111,251.2,0.0100,19.93,-0.32
-112,257.0,0.0100,19.93,-0.03
-113,263.0,0.0100,19.89,0.00
-114,269.2,0.0100,19.91,0.00
-115,275.4,0.0100,19.92,0.14
-116,281.8,0.0100,19.97,0.00
-117,288.4,0.0100,19.96,-0.18
-118,295.1,0.0100,19.92,-0.10
-119,302.0,0.0100,19.94,-0.35
-120,309.0,0.0100,19.96,0.00
-121,316.2,0.0100,19.98,-0.25
-122,323.6,0.0100,19.92,-0.32
-123,331.1,0.0100,19.95,-0.21
-124,338.8,0.0100,19.91,-0.03
-125,346.7,0.0100,19.92,0.03
-126,354.8,0.0100,19.94,-0.18
-127,363.1,0.0100,19.94,0.11
-128,371.5,0.0100,19.92,-0.16
-129,380.2,0.0100,19.95,-0.18
-130,389.0,0.0100,19.92,-0.34
-131,398.1,0.0100,19.92,-0.15
-132,407.4,0.0100,19.95,-0.35
-133,416.9,0.0100,19.93,0.00
-134,426.6,0.0100,19.96,0.00
-135,436.5,0.0100,19.93,-0.13
-136,446.7,0.0100,19.94,-0.18
-137,457.1,0.0100,19.92,-0.18
-138,467.7,0.0100,19.96,0.00
-139,478.6,0.0100,19.94,-0.26
-140,489.8,0.0100,19.94,-0.18
-141,501.2,0.0100,19.93,-0.18
-142,512.9,0.0100,19.92,-0.18
-143,524.8,0.0100,19.92,-0.18
-144,537.0,0.0100,19.92,-0.18
-145,549.5,0.0100,19.96,-0.18
-146,562.3,0.0100,19.95,-0.18
-147,575.4,0.0100,19.92,-0.18
-148,588.8,0.0100,19.93,-0.18
-149,602.6,0.0100,19.92,-0.18
-150,616.6,0.0100,19.92,-0.04
-151,631.0,0.0100,19.92,-0.18
-152,645.7,0.0100,19.93,-0.18
-153,660.7,0.0100,19.93,-0.18
-154,676.1,0.0100,19.96,-0.18
-155,691.8,0.0100,19.93,-0.18
-156,707.9,0.0100,19.93,-0.21
-157,724.4,0.0100,19.92,-0.18
-158,741.3,0.0100,19.92,-0.18
-159,758.6,0.0100,19.92,-0.18
-160,776.2,0.0100,19.92,-0.32
-161,794.3,0.0100,19.92,-0.21
-162,812.8,0.0100,19.94,-0.26
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-164,851.1,0.0100,19.93,-0.34
-165,871.0,0.0100,19.92,-0.18
-166,891.3,0.0100,19.95,-0.32
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/2.csv b/unordered/Measurements/20180503 Aliasing effect measurements/2.csv
deleted file mode 100644
index aefedde3b0e24fd388393d509e365da0e9610d95..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/2.csv	
+++ /dev/null
@@ -1,472 +0,0 @@
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/3.csv b/unordered/Measurements/20180503 Aliasing effect measurements/3.csv
deleted file mode 100644
index 149f7639f7f3db2c183608cbe7c2b474312e73f5..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/3.csv	
+++ /dev/null
@@ -1,472 +0,0 @@
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/4.csv b/unordered/Measurements/20180503 Aliasing effect measurements/4.csv
deleted file mode 100644
index 7bdc082134be6417c9ce50ecc74c0adcda2a1210..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/4.csv	
+++ /dev/null
@@ -1,472 +0,0 @@
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/5.csv b/unordered/Measurements/20180503 Aliasing effect measurements/5.csv
deleted file mode 100644
index cd76e2c1e59a051065a7eb4dce23fcac4ed6bd14..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/5.csv	
+++ /dev/null
@@ -1,472 +0,0 @@
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/Influence of aliasing.ipynb b/unordered/Measurements/20180503 Aliasing effect measurements/Influence of aliasing.ipynb
deleted file mode 100644
index 15495db3eeaa86d2f58673db7cd5460e610378a1..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/Influence of aliasing.ipynb	
+++ /dev/null
@@ -1,143 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from nqlab import*\n",
-    "import matplotlib.pyplot as plt \n",
-    "import pylab\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Setup\n",
-    "Since the ADWIN-System is a digital one with a defined sampling rate. The aliasing effect can have adverse effects on the lock and disturbance suppression. To study the effect of alliasing FFT measurements of the SHG532 photodiode signal were done with the lock of The ADWIN system and the use of different analog filters from a preamplifier. With 30,100 kHz cutoff and 6 or 12 db attenuation per decade. A comparisive Measurement without an analog filter was done to evaluate the disturbance suppression."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data=np.empty(10,dtype=object)\n",
-    "data[0]=io.import_data('SCRN0001.TXT','ascii_pandas')\n",
-    "data[1]=io.import_data('SCRN0002.TXT','ascii_pandas')\n",
-    "data[2]=io.import_data('SCRN0003.TXT','ascii_pandas')\n",
-    "data[3]=io.import_data('SCRN0004.TXT','ascii_pandas')\n",
-    "data[4]=io.import_data('SCRN0005.TXT','ascii_pandas')\n",
-    "data[5]=io.import_data('SCRN0006.TXT','ascii_pandas')\n",
-    "data[6]=io.import_data('SCRN0007.TXT','ascii_pandas')\n",
-    "data[7]=io.import_data('SCRN0008.TXT','ascii_pandas')\n",
-    "data[8]=io.import_data('SCRN0009.TXT','ascii_pandas')\n",
-    "data[9]=io.import_data('SCRN0010.TXT','ascii_pandas')\n",
-    "\n",
-    "TF=np.empty(5,dtype=object)\n",
-    "TF[0]=io.read('1.csv')\n",
-    "TF[1]=io.read('2.csv')\n",
-    "TF[2]=io.read('3.csv')\n",
-    "TF[3]=io.read('4.csv')\n",
-    "TF[4]=io.read('5.csv')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Plots\n",
-    "Below are the plots of the Transfer function of the preamplifier for the different lowpass filter in use and the PSD measured with the spectrum analyzer."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [],
-   "source": [
-    "pylab.figure(figsize=(11,12))\n",
-    "plt.subplot(2,1,1)\n",
-    "plt.semilogx(TF[0].index.values,TF[0].values.transpose()[1],color='red', label='no analog filter')\n",
-    "plt.semilogx(TF[1].index.values,TF[1].values.transpose()[1],color='blue', label='30 kHz 6 dB ')\n",
-    "plt.semilogx(TF[2].index.values,TF[2].values.transpose()[1],color='green', label='100 kHz 6 dB')\n",
-    "plt.semilogx(TF[3].index.values,TF[3].values.transpose()[1],color='yellow', label='100 kHz 12 dB')\n",
-    "plt.semilogx(TF[4].index.values,TF[4].values.transpose()[1],color='black', label='30 kHz 12 dB')\n",
-    "plt.grid()\n",
-    "plt.ylabel('Gain (dB)')\n",
-    "plt.legend()\n",
-    "\n",
-    "plt.subplot(2,1,2)\n",
-    "plt.semilogx(TF[0].index.values,TF[0].values.transpose()[2],color='red', label='no analog filter')\n",
-    "plt.semilogx(TF[1].index.values,TF[1].values.transpose()[2],color='blue', label='30 kHz 6 dB ')\n",
-    "plt.semilogx(TF[2].index.values,TF[2].values.transpose()[2],color='green', label='100 kHz 6 dB')\n",
-    "plt.semilogx(TF[3].index.values,TF[3].values.transpose()[2],color='yellow', label='100 kHz 12 dB')\n",
-    "plt.semilogx(TF[4].index.values,TF[4].values.transpose()[2],color='black', label='30 kHz 12 dB')\n",
-    "plt.grid()\n",
-    "plt.legend()\n",
-    "plt.ylabel('Phase response (°)')\n",
-    "plt.xlabel('frequency (Hz)')\n",
-    "plt.show()\n",
-    "plt.suptitle('frequency Response of the Preamplifier')\n",
-    "plt.close()\n",
-    "\n",
-    "\n",
-    "pylab.figure(figsize=(11,6))\n",
-    "plt.loglog(data[0].index.values[5:800],data[0].values.transpose()[0][5:800],label='30 kHz 6 dB', color= 'red')\n",
-    "plt.loglog(data[1].index.values[5:800],data[1].values.transpose()[0][5:800],color='Red')\n",
-    "plt.loglog(data[2].index.values[5:800],data[2].values.transpose()[0][5:800],label='100 kHz 6 dB', color= 'blue')\n",
-    "plt.loglog(data[3].index.values[5:800],data[3].values.transpose()[0][5:800],color='blue')\n",
-    "plt.loglog(data[4].index.values[5:800],data[4].values.transpose()[0][5:800],label='100 kHz 12 dB', color= 'green')\n",
-    "plt.loglog(data[5].index.values[5:800],data[5].values.transpose()[0][5:800],color='green')\n",
-    "plt.loglog(data[6].index.values[5:800],data[6].values.transpose()[0][5:800],label='30 kHz 12 dB', color= 'yellow')\n",
-    "plt.loglog(data[7].index.values[5:800],data[7].values.transpose()[0][5:800],color='yellow')\n",
-    "plt.loglog(data[8].index.values[5:800],data[8].values.transpose()[0][5:800],label='no analog filter', color= 'black')\n",
-    "plt.loglog(data[9].index.values[5:800],data[9].values.transpose()[0][5:800],color='black')\n",
-    "plt.grid()\n",
-    "plt.title('PSD measurement')\n",
-    "plt.ylabel('PSD (Vpk/(HZ)^(1/2))')\n",
-    "plt.xlabel('frequency (Hz)')\n",
-    "plt.legend()\n",
-    "plt.show()\n",
-    "plt.close()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Conclusion\n",
-    "As one can see the PSD data is significant 'better' for the case of an analogue lowpass filter before the ADC. Therefor the ADwin System should always be implemented together with a lowpass filter."
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0001.TXT b/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0001.TXT
deleted file mode 100644
index 4e9b6edacc476726b3f1a79334d37c8167d1313f..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0001.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0002.TXT b/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0002.TXT
deleted file mode 100644
index 6a5279fcc720a94c4a49af4ef74a9a1e54a7fa89..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0002.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0003.TXT b/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0003.TXT
deleted file mode 100644
index a1eff1854c785fb6b0f3ca4fdbd35b201cf4c9c2..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0003.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0004.TXT b/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0004.TXT
deleted file mode 100644
index fc6cee70b2b6b9c55a13a3b242e3eac7d6f64080..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0004.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0005.TXT b/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0005.TXT
deleted file mode 100644
index 1d818dc83c6fb7321a4337296905c8a1e5c92b47..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0005.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0006.TXT b/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0006.TXT
deleted file mode 100644
index d2763cb683c4de273b21bcec4d686eb2ca0f5442..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0006.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0007.TXT b/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0007.TXT
deleted file mode 100644
index 11c1861de8fc8b043302b8eb1b3f18760b3a8fbf..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0007.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0008.TXT b/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0008.TXT
deleted file mode 100644
index e1d7a1caf3bb2bfb86faf8146812dfcb8009ad86..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0008.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0009.TXT b/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0009.TXT
deleted file mode 100644
index dc632c35b8807310fdffabc2bfa18858358051e4..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0009.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0010.TXT b/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0010.TXT
deleted file mode 100644
index cb44a31a9cdc163b1bd041b5e7f954c555ca4f52..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20180503 Aliasing effect measurements/SCRN0010.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_100.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_100.TXT
deleted file mode 100644
index 00951f7c0a7706069aba1eb03c76403176e0879d..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_100.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_102k4.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_102k4.TXT
deleted file mode 100644
index f1e16d0445d10a18d5255e37f28dca23a3ce09f2..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_102k4.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_12k8.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_12k8.TXT
deleted file mode 100644
index dc530d13ea33661ea9f0f1481d969120708edc74..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_12k8.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_1k6.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_1k6.TXT
deleted file mode 100644
index 67ec789cca096003d720ab9af4fe3c55bb436b61..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_1k6.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_200.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_200.TXT
deleted file mode 100644
index 4c8abae30dffd5dfcb417cefe428f64bd410d23d..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_200.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_25k6.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_25k6.TXT
deleted file mode 100644
index 60bffc11cd855491b9b58fd24b34a0e0a9b5043d..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_25k6.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_3k2.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_3k2.TXT
deleted file mode 100644
index c143b953daa0c1dc35818a9d21edda01e098c0a5..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_3k2.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_400.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_400.TXT
deleted file mode 100644
index 98b65c1c24bba1230a3a6209c94ac5d3f2c37fa8..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_400.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_51k2.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_51k2.TXT
deleted file mode 100644
index 3065c68d3d8eddde0f971bf5d4ddf01c83640692..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_51k2.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_6k4.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_6k4.TXT
deleted file mode 100644
index bfd6b7a3a7b50ea1ea13a56b0818477a89cd3cbd..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_6k4.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/025_800.TXT b/unordered/Measurements/20182603 FFT with amplifier/025_800.TXT
deleted file mode 100644
index efa1a2d9a4f5bc3d2702be7c9125147a9a7deb03..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/025_800.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/Untitled.ipynb b/unordered/Measurements/20182603 FFT with amplifier/Untitled.ipynb
deleted file mode 100644
index f32da4954285c1752ec4d2fef599c5d7781d4ef0..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/Untitled.ipynb	
+++ /dev/null
@@ -1,127 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "import pylab\n",
-    "from nqlab import*"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "no_data=np.empty(20,dtype=object)\n",
-    "no_data[0]=io.import_data('no_102k4.TXT','ascii_pandas')\n",
-    "no_data[1]=io.import_data('no_51k2.TXT','ascii_pandas')\n",
-    "no_data[2]=io.import_data('no_25k6.TXT','ascii_pandas')\n",
-    "no_data[3]=io.import_data('no_12k8.TXT','ascii_pandas')\n",
-    "no_data[4]=io.import_data('no_6k4.TXT','ascii_pandas')\n",
-    "no_data[5]=io.import_data('no_3k2.TXT','ascii_pandas')\n",
-    "no_data[6]=io.import_data('no_1k6.TXT','ascii_pandas')\n",
-    "no_data[7]=io.import_data('no_800.TXT','ascii_pandas')\n",
-    "no_data[8]=io.import_data('no_400.TXT','ascii_pandas')\n",
-    "no_data[9]=io.import_data('no_200.TXT','ascii_pandas')\n",
-    "#no_data[10]=io.import_data('no__100.TXT','ascii_pandas')\n",
-    "\n",
-    "data=np.empty(20,dtype=object)\n",
-    "data[0]=io.import_data('025_102k4.TXT','ascii_pandas')\n",
-    "data[1]=io.import_data('025_51k2.TXT','ascii_pandas')\n",
-    "data[2]=io.import_data('025_25k6.TXT','ascii_pandas')\n",
-    "data[3]=io.import_data('025_12k8.TXT','ascii_pandas')\n",
-    "data[4]=io.import_data('025_6k4.TXT','ascii_pandas')\n",
-    "data[5]=io.import_data('025_3k2.TXT','ascii_pandas')\n",
-    "data[6]=io.import_data('025_1k6.TXT','ascii_pandas')\n",
-    "data[7]=io.import_data('025_800.TXT','ascii_pandas')\n",
-    "data[8]=io.import_data('025_400.TXT','ascii_pandas')\n",
-    "data[9]=io.import_data('025_200.TXT','ascii_pandas')\n",
-    "data[10]=io.import_data('025_100.TXT','ascii_pandas')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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sWPCt75tUFWuXBzFu24oSFeXfBgshhBDiuiaB8Tpnr1sfW4NGtF2+jFq17mT27C/JqdPY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\n998vID09zT7m6ilNTUoscq1Kpk//iOTkZHbs2F60sUAgEJQymqJNvOf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BMAeHoMpIL/SZ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GWTdZQezUvHOzctncikq1gEAJHI6KQc2Nkhw1V73XEvtUkdcHSCbODLKH5nKoSWLSGoXa947BtI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\nRGQQC0YiIiIiMogFIxEREREZ9P/zHTH42d1RlQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x21804af09e8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "pylab.figure(figsize=(11,6))\n",
-    "plt.loglog(data[0].index.values[10:800],data[0].values.transpose()[0][10:800],color='black')\n",
-    "plt.loglog(data[1].index.values[10:800],data[1].values.transpose()[0][10:800],color='red')\n",
-    "plt.loglog(data[2].index.values[10:800],data[2].values.transpose()[0][10:800],color='red')\n",
-    "plt.loglog(data[3].index.values[10:800],data[3].values.transpose()[0][10:800],color='red')\n",
-    "plt.loglog(data[4].index.values[10:800],data[4].values.transpose()[0][10:800],color='red')\n",
-    "plt.loglog(data[5].index.values[10:800],data[5].values.transpose()[0][10:800],color='red')\n",
-    "plt.loglog(data[6].index.values[10:800],data[6].values.transpose()[0][10:800],color='red')\n",
-    "plt.loglog(data[7].index.values[10:800],data[7].values.transpose()[0][10:800],color='red')\n",
-    "plt.loglog(data[8].index.values[10:800],data[8].values.transpose()[0][10:800],color='red')\n",
-    "plt.loglog(data[9].index.values[10:800],data[9].values.transpose()[0][10:800],color='red')\n",
-    "plt.loglog(data[10].index.values[10:800],data[10].values.transpose()[0][10:800],color='red')\n",
-    "\n",
-    "plt.loglog(no_data[0].index.values[10:800],no_data[0].values.transpose()[0][10:800],color='black')\n",
-    "plt.loglog(no_data[1].index.values[10:800],no_data[1].values.transpose()[0][10:800],color='black')\n",
-    "plt.loglog(no_data[2].index.values[10:800],no_data[2].values.transpose()[0][10:800],color='black')\n",
-    "plt.loglog(no_data[3].index.values[10:800],no_data[3].values.transpose()[0][10:800],color='black')\n",
-    "plt.loglog(no_data[4].index.values[10:800],no_data[4].values.transpose()[0][10:800],color='black')\n",
-    "plt.loglog(no_data[5].index.values[10:800],no_data[5].values.transpose()[0][10:800],color='black')\n",
-    "plt.loglog(no_data[6].index.values[10:800],no_data[6].values.transpose()[0][10:800],color='black')\n",
-    "plt.loglog(no_data[7].index.values[10:800],no_data[7].values.transpose()[0][10:800],color='black')\n",
-    "plt.loglog(no_data[8].index.values[10:800],no_data[8].values.transpose()[0][10:800],color='black')\n",
-    "plt.loglog(no_data[9].index.values[10:800],no_data[9].values.transpose()[0][10:800],color='black')\n",
-    "#plt.loglog(no_data[10].index.values[10:800],no_data[10].values.transpose()[0][10:800],color='black')\n",
-    "\n",
-    "plt.grid()\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/unordered/Measurements/20182603 FFT with amplifier/no_100.TXT b/unordered/Measurements/20182603 FFT with amplifier/no_100.TXT
deleted file mode 100644
index bad78e99ef2c57b97efdc63bce179f6908b8fba3..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/no_100.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/no_102k4.TXT b/unordered/Measurements/20182603 FFT with amplifier/no_102k4.TXT
deleted file mode 100644
index e34774b9f7cbbb68c5aa14a9e956e069c5cd19d3..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/no_102k4.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/no_12k8.TXT b/unordered/Measurements/20182603 FFT with amplifier/no_12k8.TXT
deleted file mode 100644
index aa5c281fcc49dbfa35b515d32953ec96fd396483..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/no_12k8.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/no_1k6.TXT b/unordered/Measurements/20182603 FFT with amplifier/no_1k6.TXT
deleted file mode 100644
index 43df75b5b8f46e2b9395ae0504e9554a4c6a267e..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/no_1k6.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/no_200.TXT b/unordered/Measurements/20182603 FFT with amplifier/no_200.TXT
deleted file mode 100644
index feb343265a9f01e955858d20cb28fd460ff301e1..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/no_200.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/no_3k2.TXT b/unordered/Measurements/20182603 FFT with amplifier/no_3k2.TXT
deleted file mode 100644
index 4f97c8ca85c7d3339f853f8ad9d07dbd0aebc89a..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/no_3k2.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/no_400.TXT b/unordered/Measurements/20182603 FFT with amplifier/no_400.TXT
deleted file mode 100644
index 0873ce05806ce048581026ce7886db5b4dbf7f7e..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/no_400.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/no_51k2.TXT b/unordered/Measurements/20182603 FFT with amplifier/no_51k2.TXT
deleted file mode 100644
index b1140891e2aeea47859e2f87da98a20e1c97db6d..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/no_51k2.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/no_6k4.TXT b/unordered/Measurements/20182603 FFT with amplifier/no_6k4.TXT
deleted file mode 100644
index 016dcef3fec5df869cf6023c079f8f45702173ea..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/no_6k4.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/20182603 FFT with amplifier/no_800.TXT b/unordered/Measurements/20182603 FFT with amplifier/no_800.TXT
deleted file mode 100644
index 1116907673a2916658f807d4e48e583b76987ba0..0000000000000000000000000000000000000000
--- a/unordered/Measurements/20182603 FFT with amplifier/no_800.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/AUXTF2.csv b/unordered/Measurements/AUXTF2.csv
deleted file mode 100644
index adadc1345986b39915901f704585e1f977bec793..0000000000000000000000000000000000000000
--- a/unordered/Measurements/AUXTF2.csv
+++ /dev/null
@@ -1,372 +0,0 @@
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diff --git a/unordered/Measurements/Adwin_Transferfunctiom_measurement.ipynb b/unordered/Measurements/Adwin_Transferfunctiom_measurement.ipynb
deleted file mode 100644
index 697b118a30372c0926bee62647d9ebc0df592b74..0000000000000000000000000000000000000000
--- a/unordered/Measurements/Adwin_Transferfunctiom_measurement.ipynb
+++ /dev/null
@@ -1,207 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "from nqlab import *\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "import pylab"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Setup\n",
-    "The built in Aux and monitor function of the ADWIN program were tested for the purpose of measuring plant transfer functions. herefor the analyze function of an oscilloscope was used. The oscilloscope generates a sinus function, which was put to the AUX input1 of the ADWIN-system and the error signal was put to input1. The monitor function was used to write the read signal from input1 to output9, and the output1 signal to output11. These were then measured at the oscilloscope, which calculated the plant transfer function. $$ \\\\ $$\n",
-    "To validate the result a measurement was done with an analogue tool that adds voltages, which will be called \"adderbox\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data=np.empty(300,dtype=object)\n",
-    "data[1]=io.read('AuxTF2.csv')\n",
-    "data[2]=io.read('NOAUXTF5.csv')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "TF1=data[1].index.values\n",
-    "TF11=data[1].values.transpose()[1]\n",
-    "TF12=data[1].values.transpose()[2]\n",
-    "TF2=data[2].index.values\n",
-    "TF21=data[2].values.transpose()[1]\n",
-    "TF22=data[2].values.transpose()[2]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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NYePG9WfP04833niLjRvX89VXc5g6dQYtWtxM+/YdJdAUQghxVRw7puN0apw6pVO+vLuo\nq3PNFHmwWZjnn3+eMWPGMHXqVKpUqUKnTp3+cRm5PftcNAt5LSxbthSPRzF8+NMAJCYmsGnTBlJT\nU6hVqza6rhMQEEiVKtUAOHLkMJ063QlA/foN+e67+aSkJJOYmMCYMSMAyM3NpXnzmyhX7gYqVKjo\nO1ZUVDTR0WXOPrcBx48f49ixI3TseAcApUpFYbcHkJKSTJ069QgMDMJiMVO9+t/3T6xRoxYAQUGB\nVKpU+ez9YByOXA4f/ovY2DMMGfI4AOnp6Zw8eZLIyChmzZqJ1WolKyuLgIAA7PYAnn56OJMnTyQr\nK5OOHTsXOJZSed/0vOd3sdfAW//AwCAqVaqMpmkEBQWRm+vg5MkTpKQk89xzgwHIysri1KlTZ8+p\npu91cziKX5cMIYQQJU/u2Y+b7Oy8x+bONaNp0LOnq2gqdQ0Uq2Bz9uzZvvtffHFlm8CLwqJFC5k0\naSpVqlQFYNmyn1iw4BsGDBjI/Plz8Xg85ObmcvToYQAqVqzI7t07qF69Bnv37gEgJCSUqKgoXntt\nKoGBgaxe/Tv+/nZiY8+gaXmTCcTHx5KQkEBkZCQ7dmzjrru6kpSUxPbt26hRoxbx8XGkp6cRHBzC\nb7/9gt3uj8ej+O23X7jtttsveh5nu88WqkKFilSqVIU33ngLTdOYN28OVapUY9SoZxk79mUqVars\na7ZOSEhg//69vPrq6+Tm5tK9+1106nQnfn5+JCYmUKZMWQ4dOuALaHVdu4TX4MKVK1OmHFFRpZk2\n7V3MZjNLliyievUa/PHHykLPSdM0lJJptoQQQlwdubnGh09OTt6H0MyZfsTGavTo4UIvFnMEXXnF\nKtgsSQ4c2AcoX6AJ0KZNO956ayrBwSHcdtvtDBzYn8jIUoSFhQMwcODjjBs3kl9+WUbZssbIdF3X\nGTLkOYYNG4JSCrs9gDFjXiQ29ky+44WEhDJt2hTi4+OoV68BN998C3Xr1uPVVyewcuUKcnNzGT78\nBRIS4pk5833eeWcmSnl44omB1K5d15cV/aeqV69B06bNeOKJh3E4nNSuXZdSpUrRsWNnRox4lvDw\ncEqViiI1NYWIiAiSkhIZMKAP/v52evXqi9lspk+f/gwbNoTo6LIEBRXsYHypr8H5wsLC6NnzQZ58\n8hHcbjdlypSlXbsOF9y/Tp16vP/+25QpU84X8AohhBBXSk5O/luAjAyN2FidnTt1GjYsmQkPTZ3b\nbnkdiY8vOEJdCBnZKa4Gua7E1SLX1v8v77xj4cUXbUyblk2fPkazed26AcTH6wwblsuwYY4rdqzi\nNBq9hCZshRBCCCGKF28zenZ2XjN6ZqZxf/nyktvYLMGmEEIIIcQ14B0g5G1Gd7kgK0sjKEixbZuJ\n2NiLDJK4jkmwKYQQQghxDXgzmt7bzEzj8ZYtjWmQDhwomWFZyTwrIYQQQohi5vzMZnq6EXSWLm0M\nDDp3SqSSRIJNIYQQQohrIC/YNILMjAxvsGmM1c7KkmZ0IYQQQghxmbxBpjeDmX52Yp2oKG+wWRS1\nuvok2LxKvvhiFl27diL37NeYiRPHs3792nz73HOPsTLShx++y2uvveR7fMOG9Tz11KO4XCV3NYGL\nOXPmDKtX/1HU1RBCCCGuqLwVhIyg09uMnhdsSmZT/APLly+lffuOrFix7G/3/e9/H+HYsSOsWLGM\nM2fO8NZbUxk3biJmc8mdBuFitmzZyM6d24u6GkIIIcQV5c1sevtseqc9iooy+myW1GCzxEYz8+aZ\n+eoryxUts3dv5yWtXbplyybKlr2Be+/tzoQJY7nzzi4X3d9sNjNu3EQGD36MiIhInn56GJGRkQXK\n/OKLWVgsFuLiYunatTtbtmzi0KED9OjRm27d7mfr1s18+OG7mEwmypYtx/DhL5Cbm8Nrr71MRkY6\nqakpdOnSjW7d7mfBgm/46afF6LpOgwaNGDRoCBMnjqd9+47cdFNL1q9fy4oVy3jhhfF07343FStW\nomLFyvTq9SCTJ7+Cw5GLn5+V4cNH4fF4GDt2JKVLlyYmJob27Tty5MhfHDiwn5Ytb+XRRwfx11+H\nmDZtCkopQkJCGDlyHAcO7GPOnM+xWMzExJymXbsO9O37EF98MYucnBzq12/Arbe2+Vd/MyGEEKK4\nOL/PprcZPTJSoWmqxDajl9hgsygtXvw9XbrcS4UKlbBYLOzevavQ/c5dnzs6ugz16jXgwIF9NGzY\nuND94+LimDXrS/bt28vYsSOYN28h8fFxjBo1jHvv7c6kSRN5772ZhIWF89FH77FkySJq1qzN7bd3\npE2bdiQkxPPkk4/Qrdv9LFmyiKFDh1GvXn2++27+RZvs4+Ji+eSTLwgJCWXs2JHcf39Pbr75FjZt\n2sD777/NI488QUzMKd588x1yc3Po0aMrCxcuwWq1cf/9XXj00UFMmvQyI0eOpXLlKixevJA5cz6j\nWbMWxMbGMGvWVzidTu699w7+85+H6dv3IY4dOyqBphBCiOtSSgp8+KEfzz7rwGTKe/z8PpveAULB\nwQp/f8lsXnd69nRdUhbySktLS2PdujUkJycxf/48MjMzWLBgHv7+dpzO/MtQud1u3/1Vq1b61jX/\n+OMPePTRQQXKrlKlKmazmaCgIMqWLYfFYiEoKBiHI5eUlGQSExMYM2YEALm5uTRvfhMtW97K119/\nye+//4bdHuALKkeNGstXX33B++/PoG7d+gWOde4qpiEhoYSEhAJw+PAhZs/+lDlzPgPwNfWXKVOO\nwMBALBYL4eHhBAeHAKCdjaiPHTvCG2+8dva8XZQvX/HsOVXDbDZjNpuxWm3/9OUWQgghip3ffjPz\n+utWOnd2Ub9+3nrnBTObxm1gINjtktkUl2jZsiXcfXdXBg0aAkBOTg49etxD7959+f3332jVqi0A\n27dvpVKlKgCcPn2Kt9+exowZHxAUFMzAgf1o0qQZTZs2z1e2dpEvPCEhoURFRfHaa1MJDAxk9erf\n8fe389VXs6lXrwHdut3Pli2bWLduNQA//LCQ554bidVq5ZlnnmTnzu34+fmRmJgAwIED+3xl63pe\n194KFSrRu3df6tdvyLFjR9m6dfPZul3821iFChUZPXoC0dHR7NixzXecwp6maRpKeQpuEEIIIa4D\n3gylN3Pp5e2reW5m02ZTWCxgt/+7zKbDAR4P2Iph3kaCzSts0aLvGTNmgu93m81GmzbtyMnJwd/f\nzkMP9cFut2OxWBg+fBROp5OxY0fy1FNPExVVGoCxY19m1KjnmDnzc8LCwi/puLquM2TIcwwbNgSl\nFHZ7AGPGvIimabz++qssW/YTISEhmEwmHA4HVatW43//609oaBilSpWiTp16+Pv78+qrE1i2bCnl\ny1co9DiDBg3hjTdew+FwkJubw5Ahz11S/Z59diQvvzwWj8cIIkeMGENCQnyh+1atWo3PP/+EGjVq\ncfvtnS6pfCGEEKK4OH9qI6/z10ZPT4fAQKMl8d9mNseMsXLwoM6CBcVvZnhNndteeh2Jj0//+53E\n/zuhoXZSUkpoO4QoMnJdiatFrq2S6a23/Hj5ZSvvvZdN9+55Xfrq1QsgLk6nTBkP27dn8thjNrZs\nMbFhQyZ33GEnJEQxb97lBYv33efPsWM6mzcba2Be62urVKmgC26TqY+EEEIIIa6gvMxm/mZxb2bz\n3BWEgoKuTGYzMVErtn0+JdgUQgghhLiCzp+03StvUnfjNiPj3Gb0f9dnMzFR883bWdxIsCmEEEII\ncQWdG0x6KXXupO4aShnBaNDZ1mcjs3l5waJSkJSkkZOjURwXH5RgUwghhBDiCioss+nNaoaEGJnM\nnBxj+6UMEEpOhvj4CweiaWngchnbi2NTugSbQgghhBBXUGF9Nr3BZmio8u1zbjO6v39ekHq+p5+2\n0b+//wWPl5iY97zi2JQuwaYQQgghxBV07tRGXt4mdG+wmZOjnR0gZGy/WGbzyBGdLVt0UlIK335u\nsCmZTSGEEEKIEq6wzKZ3QndvM3p6utHH8twBQg5H4X0u4+M1lNJYv95UcCNGf00vyWwKIYQQQpRw\nha0g5J32KCzMCC4TEozfz536yHhu/rKcTkhIMMK1tWsLX4tHmtGFEEIIIf4fKWwFofP7bHoH/Jyb\n2YSC0x95g1KAdesKz2wmJuaFc5mZl13tq0aCTSGEEEKIK6iw0ejeZvTzg81z+2xCwcxmXJyxX506\nbnbu1ElLK3i8c5vR/81cnVeLBJtCCCGEEFdQ4aPR8w8Q8gabAQF5o9GhYLDoDTa7dnXh8Whs2VIw\nu5mYqKHrRjmS2RRCCCGEKOG8mc2sLA2323jMm9n09tk8c8YIwbwDhi6U2YyNNfa7+WajoJMnC4Zu\nSUkaZct6g03JbAohhBBClGjZ2WC1GsGfdxUh79RHISHG73v3GiFYxYoX77PpzWzWq+dG0xQxMRqJ\niRqdO9s5fNjYlpioUb68B5BgUwghhBCiRHO5jCmMoqLypjiCggOE9u/XCQpSREQYv3ub0wsLNkND\nFYGBUKqUEWxu3aqzebOJzZuNJvXERI0yZRQm04Xn6ixKEmwKIYQQQlwh3ubyvws2c3I0qlTxoJ2N\nLb3N6N7+nl5xcRpRUUbWsmxZxenTOseOGeGbd8qjpCSNiAhFQIBkNoUQQgghSjRvZrJUKSNA9E5/\n5O3H6e2zCVC5ssd339uMfuSITvfu/pw6ZewfG6v7AtfoaA8xMRrHjxvhW1KShsMBaWka4eGKgAAl\nA4SEEEIIIUoyb2bSGyB6J3b3ZjaDghSaZmyrUiUv2PT3Nx5bssTMqlVmvv3WAngzm8a2smUVMTE6\nx4/n9dVMTjbuR0Qo7HbJbAohhBBClGjeDGbBZnTj1mbLm+aosMzmnj1GaPbTT2aUMqZIOjfYTEnR\n2L8/rxndO4WS0YyuZJ5NIYQQQoiS7PzM5rl9NnVdYTbnZTHPDTb9/MBsVng8xv5btugcOaKRlZXX\nZ7NMGeP20CFjYFBSkkZsrLF/6dIeaUYXQgghhCjpCmY28x632UDTjOwmQJUqKt9zvdnN5s1dKKXx\n0Ud+AJQubexXpkz+/ZOSNGJidN82GSAkhBBCCFHCeTObkZHeAUJ5mU2bzbtakCI4OG/aIy/viPSe\nPV2UL+/h44+NYNObAS1bNi8TGhnpITFRIybGm9ksvgOEzEVdASGEEEKIksLbZzIgAAIDVb5g02o1\n9rHZjABSOy8J6c1s1q/vZsqUHHbtMtG+vYu6dY0gMzo6Lzht1MjDr7+aOH1aIzLSg58fxXaAkASb\nQgghhBBXiDezabcrgoJUvhWEvMHmgw86fZO4n8vf35iYvVYtDzYbtGvnzrfdbjfm6UxJ0WjUyM0v\nv5jZt8/ka14vrgOEJNgUQgghhLhCvH027XZjmqPU1ILN6A8/7Cz0uYGBiho1PL4+nYUpU8aD2637\npk3as0enVSsjKJVmdCGEEEKIEs6b2fT3V0RFKd/a5jk52kWDSIARIxx/W37Vqh7sdnz9PbOzNaKj\njcAzIACcTmOi9+JEgk0hhBBCiCvEm9n09zfmxVy71pimyOizWbDp/Fy33OK+6HaAyZNzcbnwBbFA\nvmZ0oNhlN4s82HQ6nYwaNYpTp07hcDh4/PHHqVatGiNGjEDTNKpXr864cePQdRk4L4QQQojiLTvb\nmC/TYjFGj585Y8btNjKb3vk1/43ISKMM9zlxqXf+Te8Ao+LWb7PIg80ffviB0NBQpkyZQnJyMt26\ndaNWrVoMHTqUFi1aMHbsWFasWEGHDh2KuqpCCCGEEBfkchmZTe8KQWXKKFwuY5WfzEwID79yxzp3\njXXvKPW8zGbxCjaLPF14xx13MGTIEN/vJpOJ3bt307x5cwBat27N2rVri6p6QgghhBAX5nLh99DD\nDL/rCNWrB3LwoO7LYJYrZ2QcT53SOHpUp0IFz8VK+kfs9rx5OaUZ/W8EBAQAkJGRweDBgxk6dCiT\nJk1C0zTf9nTv9PvnCAy0YjabrmldRfFnMumEhtqLuhqihJHrSlwtcm1d/5wTXuOOJU+yigYArFpl\nonx5CA21U6OGsc/evf5kZWk0aGAmNPTKxS6lSsGxY1Crlo3QUChd2nhc02zF6toq8mATICYmhkGD\nBtGnTx+6dOnClClTfNsyMzMJDg4u8JyMjNxrWUVxnQgNtZOSklXU1RAljFxX4mqRa+v6Zt66mecn\nlmIVrfn4xrcYceJJ4uN1rFYyVA7gAAAgAElEQVQ3KSlZGOFLED//7AF0ypXLISXl7wcBXarQUDtx\ncTqQRUoKeDw6EEBcXC5ut/WaXlulSgVdcFuRN6MnJCTw3//+l2HDhnH//fcDUKdOHf78808A/vjj\nD5o2bVqUVRRCCCGEyC8zk2/7LuUj9QjDA9+mzw0radnSCCS9fTbDwoy5NVevNrKZ1atfuWZ0MKY/\nio5WvpWIvAOEpM/med5//33S0tJ499136devH/369WPo0KHMmDGDnj174nQ66dSpU1FXUwghhBDC\n5+TQdxgSP4ZW9RKYUO59NI+Hm2/2BptG30lNM/pTZmZqBAYa825eSc8+m8srr+T4fvdOGp9bzBp/\ni7wZffTo0YwePbrA41988UUR1EYIIYQQ4uI8i3/moe/vx25TvPOlDVNPcHs8vnkyvZlNMAYJHTmi\nU716wbXQ/61mzfJnSr2TxufkFK/MZpEHm0IIIYQQ1wstPp4JT6Syg4bMeT+V6GgddB08HmrU8BAZ\n6SEoKC+D6R0pXq3alW1CL4w3s5mT8zc7XmMSbAohhBBCXAqlWNZnLu/mjOKJB2LocGeg8bCug8eN\npsHs2dmEhuYFm97pj650f83CWK3GbW6uZDaFEEIIIa47e15ZwsDtQ2lR4SSjpobkbTAZmU2AJk3y\nB5XXMrPp5weapopdZrPIBwgJIYQQQhR3x38+QK/pbYmypvLJj8H4+Z2zUdfRPIUHk40buwkOVjRu\nfOWmPLoQTTP6bUqfTSGEEEKI60jcwVR6DCiFU/Nj/tcZlCp9XjCn5WU2z9eokYdDhzKuQS0NVmvx\nG40umU0hhBBCiIsY8cAZzrgimffmIWrcHFZwB10Hz5Wd1uhy2WxKgk0hhBBCiOLAOncOll9/AXXh\nQPHnNw6w+FRTXrhlBQ361C58J10HdfX7ZF4KqxWys4tXM7oEm+L/DS0+nog6VTBv3ljUVRFCCFHE\nLKv/IHjw44T2uo+QB+4Fl6vAPulxOYx4vRwNLXsYMKv5BctS+oWb0a81yWwKUYRMRw6jJyRgWbe2\nqKtyaTIy8Fu+tKhrIYQQJY/LhX3U8wwImMfQxitI+n0Ppr17Cuw25YFdnHZH8caLCVhC7BcurxgF\nm0afTclsCnFNKJX/f19PTQaMoPN6YFvwDSEPPoB+JqaoqyKEECWKfcabfL+vNrMyH2D61nY0ZDuO\n9dvydlCKVSOW88GeNjxa53caDGx88QIvMhr9WrPZFNnZRV2L/CTYFCXWiy9a6dEjb80wLdkbbP5V\nVFX6R/TEBAC0xMQirokQQpQcfosWYnt1IuOCplKjhpuPPswijtLsXGF8RuBw8Mmtc+nxSVdq248x\n7Ot6f1/oRUajX2syGl2Ia+joUY0jR/IucT01Bbh+MptaaioAekpyEddECCFKBsuq3wke9AhfVh7F\n3vTyDBvm4JZbjSBx83Zj+Z2tAz9mxMFH6FL3EIt3RRAUZfv7gnUNPFd/Hs1LYbNJM7oQ10xurpZv\nFQVfZvPUSa5EG4N++hSW31b8qzJCHrgX6zdzC92mpRnBppaS8q+OIYQQAvyW/URIv57kVqrOi2os\ntWu76dLFRWSkonJoEhsTq6DNeI+nlnalUnAi038sS2DgpQVtymQqNplNm01WEBLimsnNzb+Kgpaa\nF7SZjh751+X7v/8OIf17XXTKjItyu/Fb+St+q35HKbj3Xn++/DJvnQXdm9lMlWBTCCEul5aWStDj\nAwnp2xN3xcp80n85fx21MGyYA/1sFNSkXhZ/0oKZLyVxgJpM/tCK/SLjgQooRvNsWq3FbwUhCTZF\niXV+ZlNPzmuOvhJN6XpsDFpuLlpG+mU9X0tPM8qJOc3hwxpr15pZtSov2PQ2o0tmUwghLo9l3RrC\n2t2K9fsFZA4bSfySlbz+USnq1XNz5515Ux01vi2QU9zAq9oobr81k7bt/mHgWIxGo8vUR0JcQ7m5\n4HJpvqnTtNQU3BUrAWA6/O8HCekJZwfwJCVd1vO1dCNI1c/EsHatEWSePn1OJjbNCDK1C/TZHDPG\nyjffyIqzQghxPi0+nqCnHiO0a2cAUn5YStawkXy/NIAjR3SefTYvqwlwY0sLAGkqmKdHXs4Bi9No\ndOmzKcQ14/1m581u6snJuCtUwhMRcWUymwnxZ8u9zGAz7Wxm8/Rp1qwxAXDqVN6/5MUGCP31l8YH\nH/ixeLEEm0KI69Nlfk+/OLcb26yPCW/ZBOuCb8ga8ixJv6/H1bQ5Hg+89ZYfNWu66dw5/wTu9ep5\nsNkUrVq5aNbsMoLGYpTZNJrRi7oW+UmwKUos7zc777JdWmoKnrAw3JWqYN65DS029l+Vr8cbwebl\nZjb1s83oWnoa69Ya/4pnzmi+9yvdO0CokD6bc+YY38ITEuRfWAhx/Vm+3ESdOoHMnXuFvjC73fgt\n+p7QTrcRNPxpXA0akrxyHZkvjIOAAAC++cbM3r0mBg/On9UEI0CbOzebt9++zCitWC1XaQwQutzh\nBFeDfFKJEquwzKYKCcXZ+EYs27YS0aAGlpW/Xl7hbjdaUuLZci8cbOpnYvBbuqTQbd4+m4epQswZ\nEzVrunE4NBISNDIyFO6UDKOM8/psOp0wb54RbCYmFq+mEiHE/z9//aWxb9+lhxPx+5MZ+l8XHo/G\nR5OzLx4Und/5UCm0uDjM27cab4aAfvIEoV07E/JwP/TUFNLem0nq/B9wV6/he9rHH1sYPNhGkyZu\nunUruCwlQMuWbsqUubwIrTgtV+nvD0pp3penWJBgU5RY3veo3FyMN6jUFFRYGJkvvUbyTyvAZrvs\n5SC1pCRf/5wL9akEsE97neABDxa65q63GX0VrQDo3t3Y5/Rpjdvb2XnJParQ8leuNBEfr1OxokeC\nTSFEkRvxtMZ/+lguKZOWvPsMA25PJD3XwmDr++w8Gc6mjYWEIh4P/u+8RWTVcthmzwKlsM35nLC2\nLYmsV42wDm0IeGkceuwZwjq2wbR7F2lvvUfS+q3kdn8AtLz3xj//NDFypI1OnVzMn5+F+Wr0PtK1\nYhNsWq3GH6I4rSIkHb5EiZWvGT0zE83pxBMSCiYTribNcDZtgd/aNWReRtne/poA+kWa0c0bN6C5\n3WipqaiIiHzbvMHmcSoA0KqVC7CyebOJw0fNHMD4Vn7+aPTNm03ouuLee51Mn27F6YS5cy2UK+eh\nXbtLm1TYb/lSlL8d562tL2l/IYS4kBPbUziSXY4D+x3UrHXhiDMzNoMuHUwcd9XioxcO0N7fw6ej\n0/hfL0VyhoUpZacyoEcKzgYNsb//DpaNf+IJDMI++RWU2UzQ00/irN+QjPETsWzagP/M9zFv24KW\nnk7yst9x165T4JguFwwfbqVcOQ/vvpvjbVG/8opRZtNqzE1PTk7e/aImmU1RYp3bjO6dq1KFhfm2\nO1vegmnPLrTLGOCjx8f57l/w+RkZmHfvNPZPLZj99I5GTySCYGsOFSoYb9JLl5p9j3siIgrMs7l3\nr06VKh7KljX2T0rSePVVP1588dLfVQJHDifgtZcvef9LlZkJgwfbOHpUMq5CFCdKwZWcRW3X22vZ\nPm01SsGp7EgAls023gtPnYRGtc2sWJL/y+/GD3ZzwFWFD5/ZTqchVTD37c6ztrcJzDhDbdsRBp8e\nycoZ+wh5uD+mo0dInvY+P41chjs2kaChg3De2ISUZSvJfuIp0ie/ibIH4Ld+LZnDRhYaaAJMnerH\n3r0mXn45l8DAK3f+BWg6mrt4rCDk7298NhSnQUISbIoSye02pj0CY3Jb7+pBntBzg81b0ZTCsn7d\nPy7fm9lUmnbBzKZl25ZzmtoLvsvr6Wkos5kESxnCLelERCj8/BRr1xoj0xOJwF2hovHcc74x79tn\nolYtD5GRxhvKqVMaCQk6e/eaOHjw7/+ltfQ0TMePXpVlO3/5xczcuRY++MDvipcthLh8S5eaqV07\n0Dfzxb816vVohr9RgYQzLnIxvuguW2y8T6399DCnE/15aiD8+eoq3mk0h4z1e9i8Ih0TLloNqmUU\nYrfzzMQgtvcYz7cbw6lTD7pbFvH+U1uY8ew+bnp3IHe/cBOjbpgFZjM//Wc2H8+y8eOPZjwRkWS8\nMZ2c7g+Q/fhTBernchn9NF9/3coDDzjzzal5VZhMxWZEjjebWZya0SXYFCXSuX3K82U2Q0N9jzsb\nN0HZbFjWrv7H5XuDTU/FSr4BQkpBx452Fi40MpOWTRt8+xcWbGppqaigIBL9yhKhJ6PrUDY4HafT\nCJITicBdsRKax+ObOD579xGOHtWoXdtDRITxxrZjR96Hxw8/XLxnzF9/adzeMYiTlEOPj7vsCekv\n5OefjeMvXGjG4biiRQsh/oWVv+m43RpDhtjIyPj35R3JjuZgbgXObD4DwI1sZkNMBeJiYcsf2djJ\nJNPlR5c37+TF04/x5bC9bDoUQf2Q4wQE5b1n5fR7iPR3PiSgdCBff51Nw0ZuHp/RmKEjwtB1aNHC\nxXtJvZjyxH66DqnNyJE2Bgzw5/nnrWTedR/p780Ei4Xp0/247TY748dbefhhG7VqBTJypI127Vy8\n+WbOuV04r45i2oxeXEiwKUqk/MFm4ZlNbDacTZphWb+2wPP9fvkZ+6SJFyxfj49Hmc24K1X2NaNn\nprnYts3E7/ONY5k3/omy2Yz9C5m+SEtPRwWFkGiKJMJjBK/lXXnLaCYSgadCJQDOHMjgrWlmTt77\nPEpp1DftOSfYNP6N7Xb1t8Hm6tVmtv8VzFf0Nup15N8v27ljh85dd9lZu9bEihVmypf3kJio8+uv\nVyaDIoT49zatyKACxzhxQqNx40AaNw6gTx9/fvml4P9pVhbMnWvm6aetnJ3uN5+c+DRiVWkyCGLX\n4lMAPHrjehQ6yz6NY/OhcG4K3MWsoRuZcMfvNIg8yYL99dngbETThhdOt0VGKubPz2b69GwWLcri\n99+zeOONXLKzNZ6fXpkmTdzs3JnBk0/mMmuWHx98YMzKMXmyHxMnWsnNhQ8+sLBxo4kuXZx8/HE2\nn3+ejcVyZV7DiylOo9FtNuOzoTitIiTBpiiRzl094UKZTQB35SroZ2IKPN/2+afYp04udI5LAC0h\nHk9EJJ7wCPQkI7h0fTgHgCPbM0EpLJs34jg7AKfQzGZ6Gp7gYBI94UQ4z0BmJhXS9gAQaU4mk0Cy\nylYB4Lvvrbz8ij8TUocA0OKNvpRyngZg+3bjw6Jf5zPs3Wvi2OYL90E9fNj4l1/AfQCYjvzNSkrZ\n2djfmISWnsaZMxoPPODva6p3OmHpUhPdu9vZuNFE377+JCdrvPBCLpGRHt/0TEKIy3PwoM7ZcYT/\nSkYG7D4Zxn/4jC/8B9KtdSwtG2ewf5/OgAH+/PqriSeesNG9uz9Dhtho0CCQwYP9mTPHjwULCv4f\nn96U12d99Vpje5uRTamuHeSb2W52ZlahSfUUbht1I499fiP39rWyhSakE0zjO6MuWlerFXr3dtGi\nhRtNgxo1PPTo4SI0VPHBB9mULq0YO9ZB8+YuvvzSwo4duq+pfNWqLA4fzmD79kzefDOXLl1c+F2r\nHj3FKtg0bqUZXVx3tMRErqd20UvKbAIqJLTQrKPpwH6jP+eG9fkez8mBhAQNPSEeFVkKT3g4WnIS\n+qmTuGd8DMChpAj006fQk5Jwtm4LXCCzmZaGCgoiyRlEZO4prIu/p7znKADt3csBiA+tBsCpE8Zz\nfuYO/P3cVHXuo/SmpWiaYt9eDU1T3B9qPGf/7K0XfF2OHDGC8PXczF9UYcVyPd+sTNu26WzZkve2\nYP3xBwImTcT2yUe8844fK1eaGTbMyqZNOg0bBtC/v53wcMVHH2WTlQUWi6JDBxcPPOBi6VJzvoFC\nKSmFzgD1j+Xk/PP3dI+neL3xCvF3du/WadvWTqdOASxfbqJfP38ee8zGypWFtxg4ndC3rz+zZhUM\nDjdvNuFROjeF76c3c/l0URm+XhzC5rjyRFsS6dXLzg8/mElKNLridLwpmZ8e+pyaQSdZ9F3BY53a\nmRcB/36mNn7kEtqyJvfV3s26+Bq4MdO4tb9vnzt75d1v0taff2ratBw2bszwDaIE6NXLxcGDJgYP\nthEYqHjllRxMJmOOyaveZF4YrfgEm96pj4pTM7pMfST+lunQQUI7tiX7kcfIGjGmqKtzSZx7DgGN\ngLOZzZRklNnM+fNeqJAQtJwcYyfv18GcHExHjeZly9o1ODrcAUph/nM901bcyjcLbPwVFY+nVClU\nWDh6ehr+775Fmst4E41zhpOxaRURgLOR0S+08MxmOo4y5UnN9SdcTybomYk0td1PlCOBDp6fmccD\nJFqiATgZk/cBU6M2kFAW/5XLCbc/TGKmndKRThplrkWjLwdWJdIx30kqTIcO4q5ajSOHdWpr+9ir\natFE20LqvBB64mT69BwcDujTx5+0NI2vvsqmVSs3fiuMADbrkwXMTh1HuXIe1q41062biehoxdSp\nWbRp48bfHxIScomP1wgKgsceczBzpoUZM/x4/fVcZszwY+JEPyIiFK1bu6lY0UPt2h5iYjS++cZC\nhw4uHn7Yybp1Jnbv1tm3V+PIphSiq9iodaON0qU9REUp9uwx8fHHFgIDFc2auYmOVqSnayQna1it\nCpvN+DN67+fmwq5dRpkuFzz+uIOqVT1s2WJi504TlSp5aN/exb59OtnZGm437NmjY7NB3boe6tVz\nc8MNitKl4fRpEykpGllZxgdaQIBxjOxs8PODiAhFZKQiIECh6+T7KZIPv6ssMVEjNRVCQxXh4UVd\nm39GqavzN4mN1cjJgYoV/91AEacThgyxERzoJj5e58EH7UREeFAKFiyw8OWXWdx+uzHyed48M6VL\nKzZtMrFsmZmcDBcPPZS/vI0bTWh4aNLaSvKQX7Bs2wK5uQRtWM+iBbcxtuxHvOAYS5O9v4C/HW2Z\nMSHcA7zIxD9HExfnIioq75xOHsyLYuKIoor5OLoljLsGl2fSY8bjDXpU9u1TpYqiTh03sbEalSv/\n89fGbIaQkPyP3XOPk1GjrOzZY2LQIAfBwf+42CtLL15ro4MEm+J6kpVF8MP90DPSMR065HvY+t18\nAiZOIGnNxoITeV2td/Lz6GdiCH7wAdLf/zjfShGmfXux/edRwMjwZWdraCkpqNCwAvXyhBjN6lpq\nqq9/pemvQ2geD0rXsaxfg376FEGDn8Dvj9+Iqb2JEyea4CQVvXJVPGc/Za0/LiK51v2wyyj32K9H\nqQi4a9fGExJaaHO8npZGYsUyAATe0wZt4XjuviObu50PsXqpkYZL9Bj1OxXrRzvtNw4GNKRp00Ac\njtuxLlxAlOMUiVTnhqBUgo/vpgqH2XciCC0+HlWqFAB+SxYTMuBBnBWrcPTkPp5Ui/ErF87xMzb6\nhv/EF/M6ExioqFXLQ0KCTnS0h/79/fllWQbNV67AHV2G92K6kYXGz1M2MPSTJpw4Dj/VeZaoeo/i\n8S8POTk8/HDeuUVHK/r0yGLOHCu717nYciiIzp2dWK2wYYOJ778343Ybf4uaNd28+aaVN980riOz\nWVE1PImaies4kVWDz3fWIjvn7JKjmqJ7dxe6Dtu366xfrxMcrAgLUzgcGjk5Grm5xptsTo6GyQR1\n6rh58EEniYka06cbxwgKUtSt62bZMjPffmvBYlH4+xuJidq1PSQmwkcfWXA4zm2Ds1/ahXkBuq4w\nmfIHoLoOwcGK8uU9lC+vqFbNQ4MGbqKiFOXKKV+/3KtNKaOfXmqqEbhnZkKDBh7fh5ZXfLzGwoVm\nFi60sGmTjlIaFoti7NhcHnnEme/fKyFB4+hRjbQ0jawsIwjLzs67zcoyXu9SpRROpxG8OhwaDoeR\nAXc4jBVQ8n7ytlWsqOjSxUmzZm7O6xlTqKwsI7u3c6fO77+bWbPGRHCwok4dD61bu9m/X+fIEf3s\nLBbG9Xv33U5Kl1b4+RkBdUaGRlCQ8Zy4OI3Fi82sWGF8hJrNirg4na1bjVaBAQOcjB59+VPtzJ5t\nYccOE/PNPalaPpdvu73BI5HfYjfl0mbeYAYPDmLJkiy+/97CxInGNa1pCh03+7bkAjqrV5uIilLU\nqOFhwxoP9dhFQIMqZNeth7tuPQByBgykmnUQ3311M86Gjcl66Hm0lGTcderhuKUV3bsO56UzOj/+\naGbAgLzlaE4cAzNOKljjOJxbjnIByUAYNbvVoNrQ4zjcFqJq5P/DTJqUS1KSdsU+GoKD4a67XCxa\nZObRR4tBq5uuFZvlKr19Nr1LNRcHEmxeJ/w/eAfTnt1kTH/3mh434M0pmPfuwR1VGtPpU77H/Zb/\nbEyfc/ivfPObWVb+SvBj/yV5xWo85W64qnUzb9qIZed2bJ9+ROYrU3yPm44d9U3FAWczm0mJeMLC\nCpShzn5d1lNTcJcubZR7cD8Ajts74rdiOaH33okWH4+rdh3SDxp9leLjNUpFGplNANPpUyQ3a+IL\nNo/+eoJbyt2ACglFhYYWWHISQEtPJdHPyFwG3dGC1K5zcDVqjP8nHxGx1FhGM9FhfF0/GWelhdrP\nJ2+lY+pwG47lt+M/exalOM1eqlPechrToYPUDj7JrrS6WH9azKF2/2XIEBuBh2ozOaA5tvBy5B6z\nUJ2DPPrOcQI++4iotYsI7rONdz+OwmZTNK6WyrwWU2jy9WgmPJnGksREjr76CVNHdaerWsitg7qx\n5IXJqDNxlP74LbIqKXIe6E3o3R3JeGUyub37+s5vRMYYlnmexe/QcV6vt4f+b94O4eFGhPHzcg59\ntR3z4YM0Nu3m+2feYqOlJa1bu2hc5jSl2zZDlQvCdOok6eNfIallJ1K/Wo5/8hnCn/8vnoqV8l7H\npERwulClS6MlJ2FZtxZ3xUq4a9YCpbD++AOu+g1wV63Os88aH0pVq3rQdWNe0IMHdWrW9OB/Xuue\n02lsi43VACsmUy6hoUbmMitLIzNTIzvbyHI6nUZwlZhoBFZKGafp/XG7Oe8xzXc/OVnjxAmNdetM\nzJ+fvwm0alUPzZq5adPGxZ13ugrU8UJcLiN4i4/P+zl9Wic+3qhzVpYRBMbFGdu8gd656tVz8+ab\nORw/rnPokM7GjSZ++82E261Rt66b4U9nUpkjfP9HJGPGlOGtt/yoVcuD3W7MBXv8+N/30tJ1hcdj\nHNfPT2G1GrdmM1gs3h91zn0jsFuyxJhiC6BiRQ/167upWFFhtSrS0jRSU7Wzt0YA/ddfuu/8Klf2\n0L+/k5wcWL/exMsvW4mMNDLtRvlG/ZcvL/zFLlvWyMgrpVGtmpuAACMwDgtTPPdEKimJbj6eFc7G\njSa+/NLoY6iU8Te51IEqC+e5qW/azb1l1qMlpNDos2q+bV/xNc3MW2ne3Ihke4f/RL2Q46yMq0vz\nzJVMzBlNbGwGDz3kj5+fYvBgByvX2BjJYlx1zpuLUtPIeOMtcvr+B1eTZpy/YHi1LlWpNXMfP/5Q\nmQED8h4/HmujvOUM1SMSOXy6HOUisr3FMfVjP7IzCn5JatHiys9BOXFiDo8/rhMdXQymHCpGfTa9\n+Z/iNEBIgs3rhGXNasw7tl3TY2rx8fh/9B453bqDxQ/LmlW+bead2wEwHdyfP9j8cx16UhK2L2eT\nNWzkZR3X9qkxlUVO3/9cdD/TsaPG/t/NJ3P8RLw9wfW4WHLIS8nk5IB+7Cie8hUKlOEJ9WY284JB\n0/59KF0np+9DWJctRY89Q8q3i8DtIaWLUW5cTjDhFSviCctrP0ypUM93/6/YIFztawNGv1AtNQX9\n5Aksq/8gt9eDxvKZ6ekkmowANyxM4bitCwCu6jWI4BsAkrNsZJqDSXCFcUNIGvb294EVnK3boEwm\nIs3pkAsVM/diioul1i0mlq6pwcGXBtF+/OO4MGHOrMyNrObFHm7YClFvDyO0ZWnsf5bG/F0MM76r\ngsP/fWZm92Xk8UFUOzGfEW54YevL/EZbvtl3HxkE8cL/TuLYfxulpo6Ds5lf2zdz0WPPoGdmEDh6\nBFpODvZ3puOJiKDU1i0cfMKNCgzEPnUyntuicNxxJ+ZtW7Bs3UJEcAiuJk3htIv7ZnSi82NPYhm7\nCvP2baBppCz9lcBhQwkaP4ogRqE0zXgX/fkDPKWjjbXl3W70lBSU2Uz2409hXfgtphPHjb9tSCgq\nIADT6VMof3+y+w+g6fZtqKAg3LXromVmEHLoIDfEnMYTVRotJwctPQ135Sp4IkuBx8NNCfHo8XGY\nMzNxlooyooWcHLDbwelCy8pA+dtRgYGogEBUYJBx38+C6eRJtMxMlJ8FLH4oiwWsVjyhoajwCDxh\n4agI49YTHoGKiCDVE8TefWYSEzUOHdLZtEnnl19MzJ1rITzcwzffZFO/ft4HWny8xsqVJv76ywju\njh/XOH7cCJCVKpjVCAoygmV/f+N+VJSHujVdRAZkEWbNJNycTkhpP9JCbmD0aBsdOuR1O6lQwcOg\nQQ56dEqi0dbPsU9+FT0tlUeAz2tPZGnVxzkYE0xSkhGoDhzooEoVD+HhCpvZSUDKafxNDmxBFvzD\nrFjCAsDPj5Tdp7E6swgKcPuyXprbZfRpttvxlLsBpZvQlMcXsefoNtbvj2Tbdgvbt+vs2mVi2TIj\nExocDCEhiuBgRUiIolIlD23bumndNI1m7vVE7/0dy5bN6HGxeMqU4kT//oSXsWDKzkTLzETLysLT\n1s6OwJZk6gHkeKwkukIIcSZyPN7OL3tuoE8vF92jV9Fo46fGJ7rNBk4H1k+WQG4unbt8QN9lD9Oy\nZQB16rg5elQnNlYnNNR4zatU8dCzp4tOnQp2Yo6P19iw1cYLfotI/fo7cHvwW/ojuV3vQ0VEUKv3\n/WzY3pKlXd7Ab/MGBsWMQbeEMDIrlp9qD4a9sGCeEXSDxtixNpqXO8G4Uy+SUXtHgeNhNuNq1qLg\n44Dzjju546OfeH/DU+Tm5gUxx1NCqBCYSNXyDjgNZcvkBZI3dbhaS/QUFB4O4eHFI8AzRqMXg6CX\n4jn1kQSb1wktIx0t84MGshQAACAASURBVHIWVrx89rfe+D/2zjtOrqru/+9z79Td2d6S3Ww2m0oa\nSagJSSiCgBilKBJRFAvYAJWmiA9FQSw04cHoz4IQRTACiv0BBCFKETCEkEZIb9vL9HLv+f1x5k7J\nzm52Sdss5/165bWTO3fuPbNzZ/Yzn2+DWIzINd/A+9vf4N29S1k0sRjmW+sBcK1fR24Aw9yoQu2+\nh5YSufJa1egWIBLB+8TjxC+4cK8hdv8vf4YIRwYhNlVepdHRgefpJ0m87/3q/3uKzSiYG98mNnde\nn2PIdBg9t4DHtX4d1rhmEieeTOKUU4le+gVSxxwHUtLla4UYbJt7LuM+9klc69ao47jddNdMAKCE\nXtYzGWuqOqZdXo6xcyf+X/6convupG3R2WAY2CmbdqEmb+SGS62Jk6iiA4CuboMtFbOgDaquXIxj\nbcnSMiJXfY3yFyfCczBup2pMP2WGSepfbi6J3ouViPL89U9Qe+u1jHdt5Qc/UJ9A404YBUisZlXp\nLmtr+PH2T3O5+y5mutbRufw1Prm7hyWLdnKa/RQsNVj80STjbv0kwR2nUrHgOIRlEbr1e5Rcdw2+\nx5YRP/MsPP98hpKvXUlq+kywbBLvOY3w9TeC203ivWdQ/D/X4X10GbK0lN57lqj5xW43oreHsvM+\nQNG9d5E8cjbRL32Z+PvejzVxEr2//DWev/4ZgOS8+WCaqktAJIIsLQUhsBqbcL3+X4ruvQurbhQ9\nv3oEEQzifv6fmLt3Eb75VnxLH6DoJz8iOXMWRkc7nqefRAZKsMY1Y02agtHagvT7sWtqMTduwPXf\n19TvproGu7YW2dyM2L4DYlGk16faXZkuZKAEEY1ibNuWfo+GEKEQxONKJJWUQDKJSCQhlUTEooie\nnn4njVS53YyrqERWVmKPric1ZSrJ06fyz945XHznMdx+u4cHHojx9NMmP/2ph2efNbFtgWFI6utS\nNNVFOGV6kMa5XdS6uxhltlMrd1Nn72JMcjPF4VaMri715WdXN2JtN6JA4V/kC5ez4Nvv5/l/eZld\ntI7p8f9SunM95iNrMO9RfRUTJ7+H6Kcuwdy+lU/cejOf2PRtohddrHrPbt+O6/9W4nrzDUQwiBig\nMqyu33sG5jzD4NzycqzxE0meNY9U7ShIJHC17VbFGh4PCIHRshvXc29g/ngVQkqkaZKaPhNr3HjM\ntauZcMNnCh5/QT/nvaK2DuMfPYhYDLuyEruqGhGPQzJJ7LzzEZbFuQ9fwjMTn+K+qfewtqWS+fMt\nxo9P0tmp3ORXXzX529/cNDfbfOtbcMYZ2eM/vWQzNjM44xMVWBMmARCdPCVzf+/PHmD6me/hyMdP\nRApB788eIHHGWRg7dzDxhY3wZXjg58qh/DUX8ls+wo9arsBdXoQ9avSQfsfJuSdwkv/X3B118eqr\nJiecoK7bLbE6ThuzkXFT/PAS1I/TUgLDUH8fhwHOBKHhVBSpr5D9STyO+9/LSZ5y6n4/tAiqP2QH\nKx8SKfE99Cvi53wIa+Ik7NH1CMvCaGvF2Lo1kwhtblif9zDz7beRRUWYO7bjefZpEqeqUhXPU3+n\n9Iov0N00TokGwPvwr7FH15M86ZS8YxhtrRjt7Ri7dmKPru93ieaWzaSmzcBobcH3u0eyYrOtNS+M\nHu+OYYRDWOMn9jmGzMnZJJWCVEq5tZOnQFERPY/klGIKQVdJI8Rgy/lfYaHPyjibqdlHEU6oc87x\nrmZ9fDKpqapzsiyvwFizOjOxx2hrZdk/6riBXVybUHH3iop8sVlEFJ+RoKtLsPar98A3oGF2NZD9\nMItc/XXKv+uB52CsVG7elHll8BN4LTGTK4p+xqzvXIpAcu5ZER5+ohSvV2bGXCZOfg+Rz19G9EtX\n4Pv1gxz53VsI3fQ97DGNeMY0suypOI8+HmbLbj/XXacEid0wht6lD6viptNOp/iO7yM62gnddCuu\nVStxrVtL5MtXsWe/kdSsOfQ88bf0Lz3/GpalZXT//i/KaRo/oc/rE1/8sbxtoTvv7fM6IiWxj32C\n1NTpyHQ6RPxDH8ncHf/guYhwCBkoKbiGvVFeXkR3d2TQ+w94fNtG9PYgOjsxOjswOjvStzsxujoR\nnR0YHR0Y27bif+FnFMVifBD4Et/i1r9ez403elmyxMOosghXz3iGDyUfZtbmP+Ld1QN9u3ipU5aW\nIcsrlKtaVq7ed+Xlals61cO5z/vnJyhaci9HcS9HOY+vqsJqHEvy5PcQnTKV1NHHkJx7QuY5xt+3\niOJv34D/Zz9Rgs7rJTVtOvFFZ2NXVYPbjdU4Vn1ZikbTLnIQEY9hjWlEluxR3WEYqngvFMTYuTP7\n+0z/E9GI6gLR0YnrzTfw/+S+jKC1AyUqcpBMgGVh143CmjiZ+DXXkTx+Hsk5R5NJppQSc236C2NR\nkXKni4owurtwrV4F8YT6gtDdhV1TixEM4l7+HHZNLcnj5pI4/cw+1zpA/Mz3c8xVl/PLvzYQP/fD\nKr3j/lcRvb3YlVXEJ07l8WM/zXfXfIiLLvLzuc95uemmOKYh+dvSLprMbUy6/pzCr2XdKDpfeA1z\nxzakz59JV7LHNVPp9lBFOxt3VdPMRhbdcyIfbFlB4NZtJKbOH/rfDrebuaf5MP5o8fw/BSecAInW\nbnbJRsY2rGfc6ePhQRh1yuS9H2ukY5jDpkBIO5sjHO+f/kDpFz5Lx39W5uWU7Q9EsFd9mCYSfQty\nDgCiuwsj2Etq1hwA7PoGAIydO3CtVIU3qWkzMNfniE0pMd/eQOzDi/H+5QmKbruF5PHzkIESjHSz\nONd/Xs6IzeJbbyZ15Kx8sZlKqTZLqJB8/JwP9btGY8tmUjOORIxtwkznWQIYra1EXSWQNlPi7Ur0\nWXsIGcgpEOrupviWm/Df/1NIJEic/r6C5+yJqD8sbe0mYGFXVSNNk8T8hQSDKp/syLpd3Lf1bBbc\nNYVbxhicVl6O6O7GSIf9jbY2Vq+qo41a/rlFuYu5YlOWV5CaOInK3VG6uorYOkmNdmto6PtB5oys\nHMtWpGnSvHAUpimxbbj49gnwJUjOOJKLv2jy8BMwbpydScuS5RWEv/UdACJfuZrEaaeTmjkrc+wJ\nM7xcOwMg/xMrme4dChC+/kaMHduxx08gMX4Cg0rTL/QHLxDA3pfBxUKQPPk9A96fEZr9rWF/MtDx\nDQNZXqGEXoFrMg/LwtiyGXPXTj5z/5/4/hNJlizxssj8C4/1nI25qYjUjJmkLrqQ4IRJyIq0eKzI\nikhZWpaNMAyC5EmnELvoYojGsOvqsOtG0adSaA/sMY0Ef3I/wft+qortSksHn6C4P7AsRLAX6XIz\npKocIQrO1LaLikikP/P2JPaxT+z1sImzFtF57PEU3f0D/A/ej103mvj7FiErKhEd7bhXvcGFL3yS\nC4zPcuXsv3PvT07CMODiuat4quc4Pjv/DUTxlP5P4PNlXM9cZH09M91v8GyymhONfxFfdDakv/wn\njz52r+suhP9Dp3P0H1/lX38dD9d52fVqC9DImAkuFp5qctddMU55n5YSGMawKRByuVQ+tBabIxTR\nrXo5Gq0t/YtNKXG98rIKyw7hD54RVGMFRTiEPIBi0/uHx1QYNH2VWg3qA9euVw6jsXMn7pWvY1fX\nkDjxZPwP/FwlRRsGRmsLRjhEauo0Eu89g9KLL6T0kxfS89vfK1cWNcIxCpBKYbS1EtnWzY03evn6\n1+OqP1pnJyI9X9b94r/7F5uWhbl9G4n3fxDR3Y37P9l+mEZrC+GmY+Bt8JsJ4l0qlmBNKORsZguE\nXKtXqfAbkCwQck+lIBxWr1lbW/q1Ky6mZ9kfSB05i9BtgkAAvnjqajwPbuGHm77Mk08mOLWsHCPY\nCxtVA3WjrZX2FvUcn1tfj8cj9+zIRNeTz1H+/mK6uiTbt6s+mqNH980HWrjQ4r0Lg0x7fjXW2Ca8\nJR5mzbJpaLAZ8+FjCBo/w66tY84cm3nzUjQ39/NhaBikjpxd+L4BGMwfXs0+YJrY4ydgj59A8XFz\nuWrlMl7ZNpr7z3uM8EceVcJ/CEJysOR+6RgSLheyqmr/LmYwmKbqNjGMkDU1hG/9vsond7n6fN4b\nu3dR9IPbuGfpycRrH+XHPz6Xf/ymniIifPG77zC5QAimjWrj2W0wb0Z3RniHvn/XO34eiVNO5RT3\nr7hr/VGEw1FeeHAzcAzjF47CNOFjH0vu7RDvDoZRgZAQ6vvhcBKbuqn7fsTJqTQ6+5/g4nrjdSre\n/17cL70wtGOHHLF54PI2RWsrJZd+Cv+SezF3bgfIhGis0Wlnc/dOXK+vIDlrNtbkKYhoFN/9P6Vq\n+kTc/3xG7TthIokz3kf4mzfjef6fmOvWqjw20vPCpcRobUHYNsu3N7FkiYfXXlN/MI22Vlqpoc2o\nxf2SEpCtrYLFi/1ZgYf6oBaJBNbYJuyaGkRnZ6ZjuNHaQqxUtf0pN3qI9cSRXm/h6niPB1lUhOjp\nwWjZTeKkU2jf3k7itDP67Jo7ySN3LckFJyJLywgGVWuUmus/yfVPHU9lpaSnR2SmFhnp19Bob6O1\nXb31eiMeKipk3+8dxcVUVkJnp2DHDlVtWcgomjLF5te/k/jKvVgTldPxu99FuO8+9SkTP+98kgtO\nRAh49NEod901jMoTNUPD7earL36AX287CnnfXSoicACEpmY/43YXNBbsUaMJ3XEPqaW/5o6eSxjv\n2c667lHcNuNBaqcMop9TP8yZHsMkxbzF/acgDQm/n1OOD5K0Xdx7u+T2Z47nuLK1zH7fwJOA3nUM\nI7EJqv2RFpsjFMe9c2ZlF9wnPclGtLYM/sDJJCKd6TsksWnb+H71gGoN45y/swPPX/5UcHfv3/+C\nkBJz8yaM7fliU1ZVIT0eXOvXYa5fS2rWHFITVZ5O4MbrMdpaKU7PEnccxNS06eqcvb1ZId7ehrFl\nc2ZEZCyk3pzO0zLaWrmIpVxSsQxz9SpETzdvvGHwj3+4ePnl7B9WpxLdahqHXVOLkDITfhdtbUT9\nKpeyItlKvDOCNa653z/MTh9MY/cu7FGj+t2vuzv7B6O1te8fj1AIAgGJLC3Dmj6D8nIlNp1QvYPR\n1kp7VzaoUFlZuIKxokLS1SXYsUPQ0DBAlaMQBO+4l8hVXwOUmVEo6lnAXNEcbhiGeiE1IwZ5wQVY\nP7qbJ+JncAdXsvgr+9Yh/+yvjef1U7/M6Av7K3EaOnMvncrH+BV33lfKVruRa78S0p8leyANMazE\npternc0Ry2CcTZFQzpIxhIG3jqupzhEa9OM8f/4jJVdeju93j2S2+X71IGUXX5ipGs/F++cnACXk\nzJ07kC4Xdk3626sQ2KPr8f7pDwjLInnCAqzJk9PPKYE1ajTmtq15DqJMh3CMcDBv3e5XXsbYpcRm\nJN0oOxRSn1xGWys7aGC7fxJCSlwr/kskou7bvj3H2cwVm7W1mccSCmGEQ0T9KqRWTjexYKpgcZCD\nLCtTKQBdXQNWa6pWIqrSL9fZdAgGRV66WGkpec5mZu1trbR1Z1MhcvM1c6mokHR0CDZuNBgzZuAP\nscQHziZ11DED7qPRaIYniQ+cw9hvXsDlM54mefqZ+3aw6VOp/c13VXuu/UTyjDO5/eYO5hgrOKXk\nZRZ+QRcE9WEYjasEHUYf0WTFZkf/O8WU2BQ9PYM/bjBXbA7S2ZSSortUo3Mj3XcQyPQgdD/7jKrw\nTKp8G9Hbg/v5fyK9Xozt2zA2b1JFQTkun1XfgNHejnS7SR5zHLKyCmvUaJLHzyN06/fUPuMnZBoD\nZwoywqp/nVXfgCwqVmJz906ggNhsb6eXUnoMJdDMtzdk3jDbt2cvV3PLZqRhYI9pRNbkiM0W5RjH\nfSoXs7zEIoavYL5m5ldVVo5rvSowsgYQmz09ao3jx9u0tfV964TDgkAgKxzLylSvO7ssm0tmNYxB\ntLbRFvLTjKpO709sVlZKOjsNduwwOPPM/TBUXKPRDFuiV1xJ9z+W77UY65AgBOYXPs1fV1Xw65dG\nIwxta/bBMFS9gRwevTZ9PqknCI1UBhVGTzubInhgxabnyb/hXrUSKQTmtm2Z7cYOddvz3LMYPd0U\n/fAOIl++So1oTCaJXvQp/Evvx/3SC5k+jA72aCXEkkcfm/nW3LPsD6oiu7QUu6aW1BFTM/tnnM1Q\nSDW3LisjObYJ16o3Mq1OHLEZ3dqOsSuM0dZKkBIScS+yqBjz7beITunrbJpbNisH1e3GTo9lNNpa\nES0qBBV1l+JySXxjq4m+aRSsRM88r7KyTA6tXTeq3/0cZ3PSJJs33zTzxqkDBIMwZky+2Ny82cg4\nm3ZNLVbTOHpaYiQtkzPdT7MkOX7AMDrAuecmOfdcLTY1Gs2hxaiu1A5Vf2TafByk9oR7wevVE4RG\nLIMJo5NuoCyGFEbPhqBFZLBi8/+wy8pJzZ6DsT0rNs0dauSk+/l/4v7X80ifj+Lbvq0msHzqs8TP\nPg//0vsxW3aTnL8w75h2ukgoeUI2F8iackTmdtef/i+vvYwjNkUoiAgFkUXFWFOm4v39o1jjmrGr\nqwm3qzLs5NJHCaz7O3ZZBb2U4gsKUhMm4np7A9H04J88Z3PzJqx0xb+dcTbbYLdyEWPuErxecE9s\nJLohQmKPXp65OL02N9PEW10T6a8m23E2J05UoZL2dpEnLkOhfGeztFTS2wuyvJxXOJqxYyoorSml\n/TX15eG4hm38FTUmrxAnnmhxzjlJvv/92HD47NJoNBpNfzhi07L6jP08FOgCoRGMIzbFAGF0ER96\nzqYRyu47WGfTaGvFrq9XUzK2bclu37Edq24URrAXo6ebnod+R9fTz9P5yhuEvndnngNoj2nMO6bT\n/ii3z2Le/c3jkWmXEbJhdOE4m8UBUkdMVW2GVryG1dRM2KfapIS7krheX0GstRcbk0hEEB8/GfPt\nDZlQwI4dOc7mprexmtVaZUmpCv+3tWYKr2KuYnw+VaUdKanBbhxLKASf+YyPLVvylZszsvI6buPD\n106nwEAVAJzMB0ds7pm3qarRs/8vK1MFQslAOSfyHN8OfRW7poa2DvUdr6a5iJdeCvPZzxZuHTJ9\nus3/+38x0t2ZNBqNRjNccQTmMMnb9HqH1wQhLTb3Ixlnc6Awelx91RC9BzaMbrS3YVfXYDWOxejq\nglAIEezF6O0h/pGPIoUgMX8hqaOOITVzVqZpu103CpmODVt7NDWOn/UBIl+8guTxfXtQFsTtRnq9\nWbEZCGClw+yu9euwR9cTLlLiNEQAc/cuImt3ZB7ePWY6xratxNrUc25vN4hEVJqC0dmZFcZCqOke\n7W2wezfSMIgLHx6PCnM7YvW110z++Ec3zz2Xb+jLUqXmVovp9AYNXnyxcDV6T4/ANNWsZcivSLdt\nVVFfXJwbRodkUrC93U+UIl6IH42srqEtotzcqilV2rHUaDSaEYAcZmJTFwgNEtu2ueGGG7jgggu4\n6KKL2LJly94fdIjJ5GwOFEaPv4MwenDo1eiivQ27uhq7UbmT5vZtGOkQemrGTIJLfkboB3cXeKDI\nhqf36EtpN4whfNMtQ5oMIgOBzFx3WVxMako2p9MaPZpwukVREGUJRnZnn2vX6CMQtk3yn9mG7Tt3\nCsx0c/Tcop9kdR0/X3EsiZ0d2NU1xOIGXm9+KGHDBnW5t7TkKzxZXo6N4C1Un8r/+7/C2SU9PYKy\nMkltrRKUuUVCkQhIqfpsOpSVybzzvrG7lmjFKFpRYf/K2fupD55Go9FoDi1G2qQYJmKzqEg69b/D\ngmErNp966ikSiQSPPPIIV111Fd/97ncP9ZL2Sl41ej8VaZkCoXcsNgfrbLYrZzMdCje3bcFMFwdZ\nDY3Ezzs/0wR8T6xxzepnP+PahoIsDihnMxJCFhcjq6uxq5WbadeNJuJROZa9XrWtl+yM5J5q5VzG\n12dzTrdtM7JiMyfk/6J7AZet/yqP/7cJWVNLPK6Eps8HliVIpeDtt9Xlvnu3EpvOS2SXlbONRqLS\nj2lK/vY3V8GXr6dHUFoKNTWO2MyKVqeafs8wOsD69eq8iYRgRXgKLdQhsCk7qnnQv0eNRqPRDGPS\nzqYYJiMrL788wfe/PzzWAsO4QOjVV19l4UJVoDJ79mxWrVqVd38g4MXlGl7TM4xIGCkEIpWi3LRU\no8U998ECwBUOUl4+uD5oRjKKFAIqK/Gm4rj39rhEAqO3B++YetwzVAFPoKMFmW4GHZg6EQY4hjF5\nEvz9r5RMnzzgfoNae2kpnkQMEQrhqSxXz3nmDHjmGXwTxhHzqnzJcEUj0t1IcFtWraXGqF5uUfy4\nSZDEQ2urj38852ORcFEya1pmTnxXiRJub641MS48FrvFhd8PFRXKhfV6i9iyRX0YdHS4icdNZsww\nWLrU5n31dbyImkN8/vmShx822LGjiBkz8p9LNGpQWQl1dUWUlkpCITfl5ep3unu32qe21kN5uTpn\nOsWVrVs9mWOs7B5PKxuoFh1Uzpo8LKoWNXvHNI1Bv181mqGgr62RgVGs/haVlfig7NC/ngsWqGvL\nsg79WmAYi81QKEQgp0O2aZqkUilcacEUCg2jmn4AKakOhbDrRmHu3kXvpu0F56MX94YpAmRXF93d\nkUEduri9E1+gBFlcQrKzm2Du42JKyMnq6swmY9dOqoBIoJyYt4Rqj4f4+reRbhemadLtL4MBzu06\n+8N4hYuw8A6432Ao9xchOzrxxGLEXF4i3RGKJ0ym6JlnCJVVEUy3Pup2VZCYNoPebdlLcmePC6tu\nFJHWAM3uHWxIjOWmmwQdHRfx55qnmLTL4utft7nllji7DTVLeHV8IsETGwjdb+FyCaRMAj52746y\nZk0RINi+3eaFF+L09BTxve9JFl7rZz1K2H72s1EeeaSIhx9OcfXV+ZVC7e1FBAKS7u4oVVXF7Nhh\n0d2tYvS7dhlAMaYZo7tbfaEwTbXtzTdtwKCqymb52kokddR4e+nuGYb99DQFKS8vGvT7VaMZCvra\nGhn44ykCQE9XCCkHn2p2IDnY11ZNTUm/9w3bMHogECCcEzK2bTsjNIcLxpbNmG+tV/+JxxGWlang\n7q+xe7bPZnDQzV9FMIgsKUEWF/cJoxff9m0qj5uF67VXsutqbwNQ4WrDwGoYg7FtK+aOHWpCzl5+\nj6kjZxP+5k37xXWTgQBGy+7MbYDUzFkAWI1jibiVsxk0y0lNn5nJ3QRV3Z04/UxCDZMIBCQNxm46\nOtQl+2bp8Tz/vIvHHnPz4osmHabKg1zNdJInnZwJo/v96nfc3S0yfTpbWkTG5fzXv1ys7hzFOqZQ\n4okzc6bNvHkWjz/eN5Te05MNjVdVSdrbs7+fYFDdzp0g5Oz71lsGxcWSE06weHV1gBbqqC0bRpnb\nGo1Go9knhluB0HBj2IrNo446iueeew6AFStWMHny8BuPFbjxekouuxTI5lJaY1VTyH4bu6dbHwnL\nyg4E3wuGIzaLivoUCBktuzBCQcouOA9z9Zvq2G2O2FRup93YhLl9K8aO7X2Kfg40MlCCkZ7qI4uV\nEot/+AK6nvg7dtO4TFP3cMJDct58ekR2tGNvryB0xz2EmqbiLzaYbb/K0bMTVNDFOvd01q5Vl297\nu6AD1UJpAxOIukpIJESmGh1gzRoDKQXjx9u0tgo2bTJwuSRer+RnT01grTmdiWMiCAHnnJPirbdM\nVq/Of3s4BUIA1dV2nth0cjbzJwipnx0dBrW1kpNPtti63cVLYi5Vk/NHWGo0Go3mMEY4YnN4TBAa\nbgxbsfne974Xj8fD4sWLue2227juuusO9ZL6IIK9mQpvRwTaY5TY7K+xu8hp6W8EB1ckJIK9yECJ\nKrbZQ6CKUAhrTCPS66Xkss9BKpV1NquU2LQaGzE3bMC1fh3WmIMrNu1AIPM8ZbFq+YPbTWquap/k\n9AELhQTJk06h5apbMo913MJoVOAvc/MoH+IvV/+FqaxmfbyZdeucHExBp5We0oPJhg0GsRh4vTIj\nNt94Q+07f34K2xa8+qrB2LGSD30oydJHArzgO4Xxc5QYXrQohWlKHn883wHu7RWZNNzqajW3PLtW\n9XPPpu4OdXU2H/tYkg9+MIktDaqmZvuRajQajeYwRzubAzJsxaZhGHzrW9/i4Ycf5pFHHmHChP7H\nDR4qRDyO0dEOtp11NvcSRs/tGD7Y+eh7htGNlt24X/iXui8tNkO3/QD3qpX4f/ZjjPZ2gEyD9eQJ\nCxChIEZbK9bkI/o9z4FA5sSVHWczF6cHZjissgqCVhGGITFNiTM4KRoFX4UPNylKf7eUKaxjfVdt\nRmy2twvaXXV4DNXnYd06g3hcZFofAaxapYrJTjhB5VOuWGHS1GTzrW/FaW62CYcFEyaoD4nqasmJ\nJ1o88ICHBx5wY9vKkI5GRV4YvaNDZELtharRPR7VfgKgtlZiGHDvvTEuvDDBWWfp8ZMajUYzYnCq\n0W3rEC9kePKOkiCllDz77LO8/PLLdHd3U1lZybx585g/fz7i3VRdm1B5mqKrK+ts1tcjDaPfXptO\nziYMvv2RCAWx6xtUg/RwmKK7b8f7yG/o2LgDEQ5j19SQWHQ2iVNOpeju24kt/jjS681M8Imfv5j4\n2edhtOzONG8/WOSLzeI+9zvOpm0LolFn5KN63zqzyCMRga9Khdt9v3+MSVVzaenw0R5UQq6jQ9DV\nYzBzjmDFCsm6dQaJBGmxqY7/4osmY8bYNDcrQRmPC8aOtSkthaVLo3zmM35OPDErAG+9NcZXvuLj\nmmt8VFZKjj9efYA4bmV1tSSVEvT0QHl54TC6s38kIjK9Of1+uPvuYVbcptFoNJp9QzubAzJkZ/OF\nF17gk5/8JC+//DJTpkxh0aJFTJ8+neXLl3PxxRfz73//+0Csc1gi0g3ajbbWjLMpS8uQ5eX9ThES\nsVgmkdgIDt7ZtEvSYfRIGGPzJoxQEJJJNXM8EAAhiJ37YYzOTtzLn1PFQbnC3+PBbhwL5sFtFyWL\nc2alFxCbkYjIHWcwSgAAIABJREFUuH+hkEiPfJSUlsqcMDr4S0ys0aqXUNPF8wHVPxOUs9nVJair\ns5k4EdauzYbRq6rUscvKJN/9boxRo7JisKlJfSiMHy955pkIxx2X/ZCYOFHy298qJbxpk5GZi15R\nkXU2nXM7P30+6XRiyuA4oY7Y1Gg0Gs0IRIvNARmys7llyxbuv/9+zD1Ey1lnnYVlWTzyyCOccMIJ\n+22Bw5q0S5knNouLsSsqCzqb4TCIiIvKyipEe9vgnc10GB3ThYiEMbdtVdt7e1Xbo3R4OnnCAgDc\nK1eQnDVnn5/e/iBXYDpOq4NtQywmaGqy2bJFEApBKKTcQdME59cTjQr8fki85zRENMq482bBHeq+\nsWNtlbPZKTjmGCX2Xn/dzITRp0yxefLJMFOm2Ph8kEyCEBIpBU1NAwvAoiIVhu/qEnR1qW3l5Vln\nE9QIzYkTLV5/3WD6dLtPAb+T41lbqz+ANBqNZqQizeE1QWi4MWRnc/HixXlCM5FIkEjnIZqmyYUX\nXrj/VjfMEennbbS3ZcLosrgYWVlVsEDo6qt9fHTNzdg1qk3PoHI2bTvtXqZzNiMRzK1qdKfo7cnM\nHAewxzZlckbtnL6bh5KBwuhOCN0RbuGwcjYDAdJN03OcTb8kdNf/Evzxzxk3zsblkhiGZO5ci7Y2\n5WxWVEimTZNs3iyIRJSzCTBrlp0Jp7vd2fM5zuZAlJdLurpU6yQo7GymUkrgHn1031wdR5xqZ1Oj\n0WhGMI7ToMVmQYYsNjdt2sTnP/95brnlFv7zn/+wcOFCFi5cyO9///sDsb7hTbyQsxngX8Wn8eyK\niqyaSrN9u2B1dHxmXONgnE3R2YmQEllennEwRXrYt9HbgwiH8kRccq5ylWX18Kh2znUz+4pN9eas\nqVFvznBYpHM2JSUlqho9mYRUSjmbDm43NDVJxo2TjBlj095ukEw6YlPlf1qW6BPSdnBC6WPH7v1D\noaJC0tmpxKzzf7XmbL7omjUG0agoKDadHE8tNjUajWYEo8PoAzJksfmNb3yDiy66iKOOOopLL72U\nRx55hCeffJKHHnroQKxvWCMyYfS2vDD6rb1XcF3wenyPLcvbPxgU7EpVkyipRLpcg2p95FqtxnSm\npk7vI9aM1hYlRHPyIp1Qun2IxWZLiyqeyXM2iwo7m45wc8LoJSWSkhJJb68graszzdkdPv3pBJ/5\nTCLjMAJUVipn06E/sVlXJykrk5QPotVlZaUTRs8Xm5WVWWfz1VeV03/UUX3Fps7Z1Gg0mncBw2w2\n+nBjyDmbLpeL+fNVgcaDDz7IuHHjACgqGh7zNw8mThhdtLUi3Go8lfQXEfUFCHvC+H9yH7ELL8rY\n66GQQGKwS9YxobQU0bv3MLrrjZUApKbPxGhtybvP2LVLnTNH0CUcsVlbt4/Pbt+48EI/M2bY3PcJ\ntTbp9SpLMoess5kNozvV6F6vJBhUBURAnrMJcMklqs1Rbi/MigqYNAlcLlUp7oTR9+QjH0kWFIaF\nqKiQrF9v0N0tMAyZaW3k8Sgh2dGhphFVV9uMHdv3fHV1aopRrijWaDQazQjD0E3dB2LIYjO3tZHH\n48nctt+N1rETRm9vQ5ZXIIuKwDSJxQXhompca9fgevU/pI45Dsg2Kd9p1TG+tGxQOZuuVSux6huQ\nVVV9+lQaO1VD+VzH0x4/gZ5fPkRy3qEr0pISNmwwqKmRmTB6riB26OtsZqvRldgUmX32dDYdckVc\nRYXE44Hx423Wrzf7dTbPOWfwPS5zw+jl5TLzeeKcu71d8OabBkcd1bc4COCzn01wxhmpPXW2RqPR\naEYSOow+IEMWmxs2bOCqq65CSpl3++233z4Q6xu+WJYaOYnK2bRHN2TCxPE4RChCulx4//InUscc\npxqWp6fM7EjUYpeWIZzJOmm95IiVVAruvNPDpz6VpGLVSlIzZqr90u6xdLsRySTGrp3q/3tUeSfO\nWnTAnvZg6OpSrmUolBWZAzV0d0LMwWC2Gt3vV70wnZZD/RnnTrEPZIXnlCmO2Nz3b5iVlZLubkds\n7nlum9deM9m61eAjHyncO7OkBKZN0x8+Go1GM5LRs9EHZshi8+67787cXrx4ccHb7wpyx062teUV\n6sTjEI0bJBeciOcvfyT8PzcTjwtSKSWcdiRqkCUliLT6/MIXfLjdaroMwMqVBrff7sVrJPn2W+uJ\nv/+DQNbBtCZNwbV6FWZGbPYVcoeSHTvUmy4UEjlis1CPTfUz20ZIYNsqjO703mxrc8Log3M2QYnN\nP/6x/5zNoVBRoULy27YZmePnnvvllw3KyiQXXZTo5wgajUajGfE4s9EtPUGoEEMuEBJC9Pvv3YRT\nHCTdblWNntPvMh4XRKOC6JkfwLXxbcx1azMhdIAdsSolNtPzGDdtMjKjF53/Ayx/MoGwbVIzjlTn\nSh/fmjAR6fNh7E7nbBYQcvub3/zGxY9/7GbNmr1fMjt2OCMoRWbNexYHQdbZdMLmu3erY6tqdCXs\nWlrUtj1zNh1yxabTZuiII9Q3y/0hNp1CoI0bjczxHRyRfPXVcSor9/1cGo1GozlM0QVCAzJkZ/M3\nv/kNAFu3biWZTDJz5kxWr15NcXExS5cu3e8LHLYkVIGKXd+AuWUzRuvuPGcToPc9iygVV+L/yX1E\nT/0CMBeAHZFKZHEgU40ej2cLYQA2b1YX7UtvlBLHkw2jO87m2CZkSSnGzvww+i9+4ea550x++ctY\nv8tet87goYfc3HhjPC//cCCiUbjySh+WJTBNyd/+FmHWrP7fUI6zGQ4DLhfS5+snjK5+FhVJAgHJ\n7t1Z8eno59bWgZ1Nl0u5j7atbgMcd5zFhAk2U6bs+5vecTOdnM1cTjrJYufOFJ/6VHKfz6PRaDSa\nwxgdRh+QITubd955J3feeSeVlZU8+uij3HLLLSxbtiyvWOjdgONsWg1jAHCtWY1dUQEoZxMgXDKK\n5AkL8P/6QcSnv5h57M5wuXI2043gE4nstBzIOpuxlIt/+U/DbhoHgF1ZhV0cIHXkLOzSUox0NbsT\nqn7pJZOnnnJlckAL8Ze/uFiyxMOWLYN3otetM7AswXe+EyMQUPmkA7FzZ7b63llfrvv69NMmxx5b\nzK5dWdeyuFi1SwLlbDrCbvv2wtXouVRX23kh7lGjJC+8EGbSpP0nNve8DfDBD6b4zW+ivMsufY1G\no9HsianF5kAMWWw6tLW1ZW5blkVngYk5IxlHbNppsSl9PsJf+yaQdTajUeh56Hf0PPgwvai5hfXs\nYGeoFBnI5mwmEqoQxhGJmzYZzJxpYWDxdMWHspVDgQCdb6wjfs6H1PjKNI6Q6+kRJBLZ0YqFcApu\n3n578C/9qlWqj+Spp6a45JIEf/2rm9Wr8x+fyinwdpzNWExN17HGNmGNHQuodJYbbvCyZYvBa685\nYlPS1GSzbp06T0kJjBmj3rAbNmT36Y/aWplXKLQ/ccLoQB9nU6PRaDQaQDube+Edi80Pf/jDvP/9\n7+fyyy/n7LPP5tJLL92f6xr+xFVBSPL4ecTOOY/ux/6MNfNIpCTTiDwaFeD3k5o9hyBKHE5lDTt7\nS7ADJYh4HBIJ4nGwLEG6LzybNwtmzbI4xrWCf6bm551WBkpACGRJWf42skLSyXMshNNtyRFxe/Lm\nmwbd3fnbVq0yCAQkTU2SSy5J4PVKHnkk28vnySdNJk4MZMLgjrMJKpTes+wPhK+/CYBly1y89ZYS\nlWvXqp9+P9xzT4zmZvUmLSmRjB4tMU3JW28NnLMJcMstcb773f5TB/aFtFmdvq3Fpkaj0Wj6IoUW\nmwMx5JxNh4997GOcffbZbNy4kTFjxlA5kiskIhFEIo4szyqPjLNZW0fw//0ysz2ZBCmV2HJEp11W\nnnE2p7Gap63TaDNqCAAiFCSRUL87JRYlbW0GzXUh3KnX+Xv0wwWXJEvV8aTPl0lWdIRkS4sgmTRY\nudLk4x/Pzyd0Znw7Ii6XRAIWLSriiCNsnngikukN+eabBtOnWxiGEl/jx9ts2pQVlPff7yESEfz3\nvybve1+KnTsNhJBIqZq0lzWUZvZdssTD9OkWa9YYbNqkGqV7PNDQIHniiQjLlrmYNs3G5YL6esm2\nbXt3NqdPP3Bv7vJymXkuWmxqNBqNpiC6qfuADNnZvOGGG1i/fj0AgUCAI488MiM016xZww033LB/\nVzgMKP7OzZQtPi9/Y9rZlHsk7OV0RMoW/fh89JjqdzSN1QBsT44CQASDmcf09IhMvuZ493ZGsZvW\nSKDgFyXbEZs5uZCOkGxpEfz0px6uucabtx7nHFA4jL56tUE4rMYv3nabel62DW++aeYJuqYmO1PE\n1NoqeOYZ5VCuWWNg27Brl6CxMTsVyKGrC9asMTn77BRjxkhsW808d7IE6uokl12WzBT6NDZmzzmQ\ns3kgMU0oS5vIWmxqNBqNpiC6Gn1AhuxsXnnlldx9992sWrWK5uZmqqur6e3tZc2aNRx55JF85Stf\nORDrPKSIZBJz08b8bWlnc8/+Ok5xEGSrrRGCXm8tRFQYHWB7TM0uF6EQ6amX9PQI2tvV4yel1hBk\nFynLoLNT9MlJzDib6bnoUkJvbzaMvmWLwLIEb79t5DUVdwTphg0GTz5p8vOfe/jc5xKcfLLFK68o\n0XjyySmWLPFwzTUJdu9W7uSMGdljNDdLnn1WCcvHH3dhWYJAQLJ2rUFbmyCZFEyZYrF1q0G6uxMA\nr72mjn/ssRbPP6+aoQ/kWDqC1eWSh3QCT0WFauyuczY1Go1GUxCdszkgQxab5eXl3HTTTYRCIV5/\n/XW6urqoqqri+uuvH7Hz0e2KSkR3t6puMZVgwumzOYCz6fSRBOj1VGFGUkxhHQDbw8rplD3BTLP3\nnp5sJfrEntfY6WqDlHIq+4jNkrTYTFeiR6Oq0AiU27hlizrO2rX5YtMRpK2tBjff7GX9epN//MPF\n9dfHWbPGYNQom/POS/Lssy527RKsXq2e74wZ2Ua148bZxGKClhbBsmVuZs+2GDXKZs0aI9Njc/Jk\nmyefzFakA/znPyamKZk922LcOJvnn+9/MhBknc1D5Wo6VFZKNm3SzqZGo9Fo+kGLzQF5xzmbgUCA\n+fPn733HEYCsqkJIiejuRlZVASDSYfS+zmb2dsbZBHrdlZTSSy2teN0W23tVbDbZE87s09Mj2LxZ\nUF1tU771DWobKmGLEpvTp++xppL8MLoTHgfYulVk2gqtXZsfLu/uFjQ22mzbZrB+vckNN8RYvtzF\nj37kwe+XHHOMxZgxSlTt2GFkcjsnT86+gcaNU7dffdVk5UqT666LE4vBk0+62LjR2V+J0z3F5vTp\nNsXF0NSkzuFMCirE2LGO2Dy0Is8RmdrZ1Gg0Gk1BHLGpJwgV5B1Xo7+bsCuUC2l0Zds7ZSYIefLF\nZiyWG0bPcTbNCkoIYiBpqI6xrVM5komurCLt6RFs327Q2Cgx31pP7UQVIncam+eSCaOnnc1csemE\nwyFfbFqWcjaPPlq9GTweyYUXJvnKVxJ0dQl27jQ45hiL+nol8nbsEGzdKqipsfMcSEdsOhXp8+ZZ\nHHGEjWUJ7r7bQ3m5zDR9dyrsUyklTo891so7xkCupSN6D7Wz6YjNsrK97KjRaDSadyW6Gn1gtNgc\nBHZl2s3M7SUaH0wYPXu7R5RRiurcPqY2zvZ2paCSPflic/duwei6FObmTdRMUyK3UCujbIGQEptO\nLmZFhaS9Xe1fX2+zZk1WeDqN44880sLjkZx5ZorKSjj+eIs5c5QIVGIz62xu3Wowdmy+o9fYKHG5\nJE89ZeLzSebMsZg6Vb3B1q83ufjiRGaMZCgkuPpqL2ecUUQkIgqIzYFyNtU+A7mfB4NJk2zGj7cz\nGRQajUaj0eRhpA0fXSBUkHccRt+1axd/+tOfiOeoq8suu2y/LGq4IdPV9kZnR2abSPQXRs86jLkj\nKIOylFJUt/WGUSmeXaFEaqI72x+yt1e5iwumdiFsG8/UZkpLZWayTt6a9sjZdITk5MkWL72kXtYz\nzkhx//0ewmHlDjqCtLpa8vDD0cyEHSHguuvi3H23h1mzbLxeNZVn507B1q1Gxgl1cLmU67h5s8G8\neSm8XpgwwcbtVqLw059OEghkxeYf/uDGMJR4XLBg8M5mfb3EMOQhdzYvuyzBpZcmDu0iNBqNRjN8\ncarRtbNZkHfsbH75y18mFApRXV2d+TdSccLooquQs7lnGD17O9fZDMrirLNZn2J3q0kSF4ne7E47\ndwp6ewUN7AAgdcQ06urswmIz7WzagXxn08mt9PslCxcqYXf66UUce2xxZp/ycsmCBRZ1dVnH8OST\nLX7/+2hGOzc0SLZuVQU/Tu5kLo5YnDtXncPtVrPCL744yahRkqIiEELS0aGmI33+8wlefTVMba06\nZ2mpcmEHcjbdbiU4D3XOpss1cCGTRqPRaN7lOKEvLTYL8o6dzeLiYr761a/uz7UMW5yiIKOjkLOZ\nH0ZP5BhgeTmbqSKaUeMpx4yxkVKw3TeJRDD7gHXrlPYfE30LaZpYEydRV9ePs1maTiAszs/ZdMTm\n2LF2poLcmdjjHL+8fO/Pub7eZvlyF6mU6BNGh6zYPOGErOv50ENZ4SyEmne+caNaV11d3zfgFVfE\nGTduYCF56qkpysp0YY5Go9FohjG6qfuAvGOxOWnSJP785z8zdepURLord3Nz835b2HBCFgeQbnde\ngRD9FAgV7LMJBJP+rLPZqLZt9k/BE8ymITiN1hs7V2KNnwA+H7W1kldfzSYLSgl33+1h8+qJPETW\n2XTEphMab2qSjBsnWbYsQmur4Etf8rNypTpOaene3wwNDZJgUB0zt7m6w9y5Fk89ZfcJsecSCMhM\ndfqoUX3P+aUvJfts25Mf/CC+1300Go1GozmU6AKhgXnHYnPNmjWsWbMm838hBA8++OB+WdSwQwjs\nyipEbs6mk6u6R4FQfhg9J2cz7s2IzYaxavtW93jGhpTg8vlkppK9cefLWHOmAWqqTmurQKa12mWX\n+Vi2zA14uf20C/HPXwgosRkIyExxjxP6PukkKzNacsUKJTYH08KnoSH7hikURj/vvBTnnZca8BjF\nxWQmDTnhc41Go9FoRhy6z+aAvGOxuXTp0v25jmHPiqJ5fOaJG3jsW1BSosLo0u3OXmBpHGezuFhm\nnE3bhlDcnRGbo5uU6NtijGdUaDMANTWSbdvUY8duf5HUR68AVPg5GhUEg7Bxo8GyZW4WLEixfLmL\nl7/0U+Yfo5zFnh5BWZmkocHG75d54yXHjJGYpuTNN9VaBxOWbmhQ+xiGzLQgGiqBgCSRMNLPQ4tN\njUaj0YxQHC2gq9ELMuQCoSuuUCJowYIFff6NZF41juX14ITMZB7i8T4h9PRmQBW/OM6m02uyJJ2z\n6S/zUl1ts5VGkhHlDjrOX1kgSYAwqSOmAlmR1tJi8NRTLoSQfPvb6iSrV2dfvu5uJSJLSuDll8Ms\nXpwNUbvdSjxGowK3Ww6q2MXptVlf/85HRToV6S6XzLRC0mg0Go1mxKGr0QdkyM7mPffcA8Dy5cv3\n+2KGMxGfKhJyJuKIRLxPcRBkw+hlZVln08l9LKUXaZrgcjF6tGTH7tEkIsqZrKmxAZP6kiCEwDpC\nhdEdEdrSInjqKRdHHWUzbZpNVZWdJzZ7e7Ozuwu5iE1NNlu3GpSVSUTfeqM+OG5moRD6YEkPN6K2\nVu5pAGs0Go1GM3LQE4QG5B2H0VesWMFjjz1GMqkctNbWVn7+85/vt4UNNyJeVcLtuJQkk/04m9n2\nQk6fzVyx6fQWKi+X9OwsyRGbStzVu1qRHg9W83ggKxxXrzb4738Nrr02gRAwbZqdmVsOqvXRQMLQ\nmUU+2Ck4dXUq9F6oEn2wOM6mDqFrNBqNZkTjNHXXzmZB3rHfdMstt3DccccRCoWor6+nfDD9dA5j\nwh71/II9ElIpVSBUQGwmEirPsaQk62yGQupnCcHMxKFAQBK0A8RiSog5YnMM27HGNavmjsDo0Tam\nKfnhDz1IKTjtNBV2nzbNZt06I/MlqqdHDNjSyJlFPtj53qYJN9wQ56KL3nkz8+JiR2zqN59Go9Fo\nRi66Gn1g3rHYLC0tZdGiRQQCAS6//HJaWlr257qGHRFTzSmXV3+Tkq98CRIJpKdvMmMsJvD5VBNw\nJ2fTqTL3eyyk1weoIqPeVBGJmLowHbHZILdnxmM6+/3whzEiEcHo0TYzZ6r9p02ziEQEL71k8uij\nLjo7xYCFP83N6nFD6Vn5hS8kOfbY/RNG12g0Go1mxKKr0QfkHYfRhRC89dZbRKNRNm7cSFtb2/5c\n17AjknY2wyEw167Brm/IczZfecXA61UFQl6vmuDjOJtOHqcn4M6E0UtKJKGUj4SlXgJHkDVYW5Hl\nFXnn/shHUpx0UphoNHs9O7PIzzknW+0zdWr/uSJOE/bBOpv7AyeMXqjHpkaj0Wg0IwZngpDUf+8K\n8Y7F5te//nXeeustLrroIq6++mo++tGP7s91DTtCdSqHsnPqPIyux5DV1cicAqH/+R8fgYCksdHG\n61XzvPd0Nr0lbqRbPaakRNIb9xJHic9p7vVUVs7k2OS/sStq+px/z7zHI46wmTnTYvJkmy9+MUFT\nk016gmVBmpqU2BxMQ/f9hc7Z1Gg0Gs27Al2NPiD7NEGotLQUy7K47777GD169P5c17AjGlcXUq+7\nCqOjA6spkedshsNg24JYTGScTcfRdNoheUs8YKvHBAKQsk26UY7ptCVXsXbt41Q3PUe04pK9rsfn\ng6efjgx6/aWlsGhRMjMv/WCQHm6kczY1Go1GM7LRYfQBGXLO5oYNG/jEJz4BwCc/+Um++tWv8tGP\nfpTnn39+vy9uOOGExHuNMkQkjAgG86rRo1FBb69Ih9GVsxmPCywrKzbdzfVYY8cCWdevDeVi+nZv\ngWgUEY1iV+SH0fcXv/hFjA98YOCpP/sTx0UdPVo7mxqNRqMZwWixOSBDdjZvv/12rrnmGgBqampY\nunQpW7Zs4Zvf/CYLFy7c7wscLjgh8SCqUMjYvYtUTTbcHYupVI14POtsqsdlw+ipb91Abzo3s6Qk\nKzbdJHC1t2L0dAP0ydk8XDn99BR33hljxgz95tNoNBrNyEVXow/MkMVmNBpl5syZAJSUKOHV1NRE\nKnXwHLNDQaaNka1KrI221rwweiwmSCRyC4Scx4mMs+kLuCBdwO6IzXaq8RLHCPZi7NoJgF1ZeeCf\n0EGgqAg+/vHk3nfUaDQajeZwRjubAzLkMHrcUU7Aj370o8xtl+sdp38eFjjOZm9KVX8L284rEIrF\n1D6hkMDnkxQVZZ1Np9G7N6ctZ1qn00YNXkMJMnPdWmDkOJsajUaj0bwrSDd1F7aeIFSIIYvN2tpa\nVq5cmbdt5cqV1NT0raAeSWSczUSOYkw7m7adFZTt7aKPs+kUCuWLTSVGWwPNeEpV703XW+vV8bTY\n1Gg0Go3m8EE7mwMyZDvymmuu4Ytf/CJz586lqamJbdu28cILL/DjH//4QKxv2ODkXYbi2UbuToGQ\nIyZBic3p02VezmY8Dj5f/kxyp0CoM+xjbJ06gPnWOnXcA1QgpNFoNBqN5gCQEZu6ILYQQ3Y2Gxsb\nWbZsGXPmzCESiTBjxgwefvhh6uvrh3zyYDDI5z//eT7+8Y9zwQUX8N///hdQc9fPP/98Fi9ezP/+\n7/8O+bgHAsfZDEay+twJo+eKzXC4r7PpFA3l4rQFklLg8amXwQmj2xUjI2dTo9FoNJp3BdrZHJB3\nlGjp8/k466yz9vnk999/P3PnzuXiiy9m48aNXHXVVTz++OPceOON3HvvvTQ2NnLppZfy5ptvMn36\n9H0+377g5GyGwgK7OIARDmXC6I7r6dC3Gl21Q8rFCaMDeIrU5AFzy2Y1O72oCI1Go9FoNIcH0khP\nENJisyDveDb6/uDiiy9m8eLFAFiWhdfrJRQKkUgkGDt2LEIIFixYwAsvvHAol4mUEIkITFMSiwm2\nlU3naF5hfUS5ubnOJmT7bIJ6XDyu5qXn4vOBy6UEp9cnsMvKEbat8jVFvnjVaDQajUYzjHGcTanF\nZiEOWgn5smXLeOCBB/K2fec73+HII4+kra2Na665hm984xuEQiECTowZKC4uZtu2bX2OFwh4cbnM\nA75uyIbQa2th1y74h/sMXuNo/ry1m2vLi9izEL+szEVdnVqbEF5sG/x+QXl5vmNZWgqdnVBUZCDq\n6qCnG6O6us9+msFjmob+/Wn2O/q60hwo9LU1QkgoIeD3mHiHyes5nK6tgyY2zz//fM4///w+29et\nW8eVV17Jtddey3HHHUcoFCIcDmfuD4fDlBYY+h0KxftsO1B0dgKUUFlps2uXySp7GgD/2DyOS7sj\ntLUZQHHOI5KkUkkgQEdHglDIxO026O7OHy8ZCBTT2SkwDItkVTUe1pEsLaOne/BjKDX5lJcX9fk9\nazT7ir6uNAcKfW2NEFIpaoBYJE5kmLyeB/vaqqkp6fe+QxpG37BhA1/+8pe54447OOmkkwAIBAK4\n3W62bt2KlJLly5dzzDHHHMplZnIya9PTf1YnJgHw4rZGEonB5Gz2LRCCbEW61wt2TS2ge2xqNBqN\nRnPYoQuEBuSQdmK/4447SCQS3HrrrYASmkuWLOHmm2/m6quvxrIsFixYwKxZsw7lMjNh9JqatNgM\nNwEQSXpYsSJZIGeTTI6mM0HI5+vbDsERmx6PRKb7lI6U6UEajUaj0bxrcGottNgsyCEVm0uWLCm4\nffbs2fz2t789yKvpn0jEcTbVRbQ1VMUM3mAVM/nXv1xMmpR/cXm9Eo8HDENmnM2Kir5i05kipJ1N\njUaj0WgOY4RACgF6glBBDmkY/XBhT2cT4CheY3pDJ//+t1nQ2RRC9dqMRETB1keQbX/k8YB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gfj6OkAAP0fW6HtrwMAaHW1iP76/pJfuztQbBJCCCGE9JTUcpV9ITatMWMBAFptLbS6WgBActbn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QnHqqVcOdYP2wbJnAsgRbbx0qmwAvvGCw667rn6Pb1qax444Os2YZrF07/KcCc78DkYZB8um/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\nP3Uih4UKc7WmAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x2972dc6d438>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "pylab.figure(figsize=(11,11))\n",
-    "plt.subplot(2, 1, 1)\n",
-    "plt.semilogx(TF2,TF21,color='red',label='\"Adderbox\" measurement')\n",
-    "plt.semilogx(TF1,TF11,color='blue',label='AUX measurement')\n",
-    "plt.grid(True)\n",
-    "plt.legend()\n",
-    "plt.ylabel('Gain (dB)')\n",
-    "plt.xlabel('Frequency (Hz)')\n",
-    "plt.title('Frequency Response')\n",
-    "plt.subplot(2, 1, 2)\n",
-    "plt.semilogx(TF2,TF22,color='red',label='\"Adderbox\" measurement')\n",
-    "plt.semilogx(TF1,TF12,color='blue',label='AUX measurement')\n",
-    "plt.title('phase Response')\n",
-    "plt.ylabel('Phase (°)' )\n",
-    "plt.xlabel('Frequency (Hz)')\n",
-    "plt.legend()\n",
-    "plt.grid(True)\n",
-    "plt.show()\n",
-    "plt.close()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Evaluation\n",
-    "As one can see, there is a small difference in the measured gain and a larger in the measured phase. The difference in gain between those 2 measurements is mostly in the range of 0 to 1 dB, which is not very significant. \n",
-    "The difference for small or large frequencies is not relevant, since the gain and phase cannot be measured properly there because either the surpression is too large or the lock is lost.\n",
-    "The difference in phase can be explained with the structure of the ADWIN Code since the signals on the monitor output are shifted by 1 cycle\n",
-    "\n",
-    "### Examplaric run through the Adwin Code\n",
-    "TF(x) = plant transfer function of x $$ \\\\ $$\n",
-    "It is assumed that the  Error Signals caused by the oscilloscope signal are much larger than \n",
-    "the normal error signal\n",
-    "- first cycle\n",
-    "    1. ADC,DAC\n",
-    "    2. input1= signal1, AUX1= OSC1 (oscilloscope signal))\n",
-    "    3. output9= signal1, output10=OSC1, output11= -\n",
-    "    4. output1=SOS(signal1)+OSC1\n",
-    "- second cycle\n",
-    "    1.  ADC,DAC\n",
-    "    2.  input1= signal2, AUX1= OSC2\n",
-    "    3.  output9= signal2, output10= OSC2, output11=SOS(signal1)+OSC1\n",
-    "    4.  output1=SOS(signal2)+OSC2\n",
-    "- third cycle\n",
-    "    1.  ADC,DAC\n",
-    "    2.  input1=TF(SOS(signal1)+AUX1), AUX1= OSC3\n",
-    "    3. output9=TF(SOS(signal1)+AUX1), output10= OSC3, output11= SOS(signal2)+OSC2\n",
-    "    4. output1= SOS(TF(SOS(signal1)+OSC1))\n",
-    "- fourth cycle\n",
-    "    12. ADC,DAC\n",
-    "\n",
-    "Since SOS(signal1)+OSC1 is interpreted as the input to the plant and TF(SOS(signal1+OSC1) as the output one can see that the signal is shifted by 1/fsample, which is in this case 1/(200 kHz).\n",
-    "The phase lag of the Aux measurement should therefor be described by:\n",
-    "$$\n",
-    "\\begin{equation}\n",
-    "H(f)=-f/(200000 \\textrm{ Hz})\\cdot 360^\\circ,\n",
-    "\\end{equation}\n",
-    "$$\n",
-    "where f is the frequency. $$ \\\\ $$\n",
-    "To validate this, the difference between the measurements and H(f) are plotted \n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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MLi1G7XNnYjgbCMC9N3pnis143ArxKysjyyYAYMOGDbj66qsBAHv27MEPf/hD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\nhBBCSNH4/wHXrFWSrczL5AAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x2972e0d5588>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "def phaselag(f,fsample):\n",
-    "    return f/fsample*360\n",
-    "pylab.figure(figsize=(11,5))\n",
-    "plt.semilogx(TF1,TF22-TF12,color='blue',label='difference')\n",
-    "plt.semilogx(TF1,phaselag(TF1,200000), label='H(f)')\n",
-    "plt.ylabel('phase (°)')\n",
-    "plt.xlabel('frequency')\n",
-    "plt.title('phase lag')\n",
-    "\n",
-    "plt.legend()\n",
-    "plt.grid(True)\n",
-    "plt.show()\n",
-    "plt.close()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "collapsed": true
-   },
-   "source": [
-    "### Conclusion\n",
-    "As one can see the the calculated curve fits almost perfectly in the range where the transferfunction can be measured properly, a larger deviation is seen shortly before the lock is lost. Since for the most of the range, where the transfer function can be measured properly, the deviation in phase can be removed analytically and the deviation of the gain is marginal, the Adwin system should be suitable for the measurement of transferfunctions"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/unordered/Measurements/FFT Measurements 20182002/Analog20022018_3.csv b/unordered/Measurements/FFT Measurements 20182002/Analog20022018_3.csv
deleted file mode 100644
index df0d55a934fe526e110fc2ef0c02e12204c63333..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/Analog20022018_3.csv	
+++ /dev/null
@@ -1,372 +0,0 @@
-#, Frequency (Hz), Amplitude (Vpp), Gain (dB), Phase (�)
-1,20.0,0.0100,64.69,189.27
-2,20.4,0.0100,67.77,65.94
-3,20.9,0.0100,76.35,-40.02
-4,21.4,0.0100,68.44,19.90
-5,21.9,0.0100,74.43,93.15
-6,22.4,0.0100,65.41,-23.85
-7,22.9,0.0100,77.02,49.90
-8,23.4,0.0100,71.90,39.89
-9,24.0,0.0100,83.04,78.14
-10,24.5,0.0100,64.66,-4.82
-11,25.1,0.0100,70.47,37.73
-12,25.7,0.0100,71.19,173.34
-13,26.3,0.0100,65.15,-11.36
-14,26.9,0.0100,68.42,-1.52
-15,27.5,0.0100,69.90,126.45
-16,28.2,0.0100,71.52,-31.84
-17,28.8,0.0100,68.70,17.86
-18,29.5,0.0100,69.11,-129.73
-19,30.2,0.0100,68.19,-124.92
-20,30.9,0.0100,65.15,-29.46
-21,31.6,0.0100,67.99,13.98
-22,32.4,0.0100,62.54,136.14
-23,33.1,0.0100,65.45,-156.19
-24,33.9,0.0100,70.53,-167.18
-25,34.7,0.0100,67.90,-23.77
-26,35.5,0.0100,56.20,53.24
-27,36.3,0.0100,56.84,115.97
-28,37.2,0.0100,58.10,-12.36
-29,38.0,0.0100,53.89,170.78
-30,38.9,0.0100,53.17,-98.94
-31,39.8,0.0100,50.52,67.14
-32,40.7,0.0100,49.64,163.92
-33,41.7,0.0100,48.91,-102.21
-34,42.7,0.0100,48.26,-132.21
-35,43.7,0.0100,47.03,106.73
-36,44.7,0.0100,45.94,-111.06
-37,45.7,0.0100,45.52,-123.96
-38,46.8,0.0100,45.51,10.96
-39,47.9,0.0100,45.88,84.57
-40,49.0,0.0100,44.73,103.71
-41,50.1,0.0100,44.70,6.19
-42,51.3,0.0100,44.93,-162.31
-43,52.5,0.0100,44.61,-75.44
-44,53.7,0.0100,45.76,-67.22
-45,55.0,0.0100,45.90,-37.19
-46,56.2,0.0100,46.49,-90.99
-47,57.5,0.0100,47.40,51.55
-48,58.9,0.0100,48.89,135.84
-49,60.3,0.0100,47.32,-148.98
-50,61.7,0.0100,49.72,188.75
-51,63.1,0.0100,50.17,8.99
-52,64.6,0.0100,48.41,-13.77
-53,66.1,0.0100,51.21,139.52
-54,67.6,0.0100,52.11,-29.88
-55,69.2,0.0100,53.18,-140.26
-56,70.8,0.0100,54.58,8.55
-57,72.4,0.0100,54.22,-19.42
-58,74.1,0.0100,58.44,-68.41
-59,75.9,0.0100,54.43,-150.54
-60,77.6,0.0100,62.22,131.44
-61,79.4,0.0100,60.58,-96.02
-62,81.3,0.0100,55.17,-65.14
-63,83.2,0.0100,64.13,-45.02
-64,85.1,0.0100,62.62,96.22
-65,87.1,0.0100,58.54,-41.72
-66,89.1,0.0100,53.56,-62.47
-67,91.2,0.0100,65.22,137.35
-68,93.3,0.0100,62.88,168.00
-69,95.5,0.0100,64.84,-8.17
-70,97.7,0.0100,64.21,146.28
-71,100.0,0.0100,58.70,-78.59
-72,102.3,0.0100,61.19,-118.32
-73,104.7,0.0100,60.42,-116.35
-74,107.2,0.0100,60.97,-134.44
-75,109.6,0.0100,64.00,60.40
-76,112.2,0.0100,62.02,54.03
-77,114.8,0.0100,58.43,-156.83
-78,117.5,0.0100,57.81,59.41
-79,120.2,0.0100,51.34,-87.68
-80,123.0,0.0100,49.80,-91.08
-81,125.9,0.0100,57.50,156.86
-82,128.8,0.0100,54.04,-156.80
-83,131.8,0.0100,52.49,153.75
-84,134.9,0.0100,51.53,-63.49
-85,138.0,0.0100,48.73,34.41
-86,141.3,0.0100,53.70,76.48
-87,144.5,0.0100,52.03,46.81
-88,147.9,0.0100,51.19,48.61
-89,151.4,0.0100,47.71,-20.28
-90,154.9,0.0100,47.27,-90.78
-91,158.5,0.0100,56.36,138.32
-92,162.2,0.0100,51.90,31.58
-93,166.0,0.0100,57.04,180.42
-94,169.8,0.0100,55.27,158.33
-95,173.8,0.0100,48.32,-87.78
-96,177.8,0.0100,51.74,31.25
-97,182.0,0.0100,51.35,11.14
-98,186.2,0.0100,55.66,65.37
-99,190.5,0.0100,49.64,-79.15
-100,195.0,0.0100,50.09,-50.80
-101,199.5,0.0100,61.87,-112.74
-102,204.2,0.0100,48.13,-125.82
-103,208.9,0.0100,46.63,-80.26
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diff --git a/unordered/Measurements/FFT Measurements 20182002/Digital20022018_7.csv b/unordered/Measurements/FFT Measurements 20182002/Digital20022018_7.csv
deleted file mode 100644
index 97cb3d89f1efff7d5d7baf36c783f68e2d31695a..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/Digital20022018_7.csv	
+++ /dev/null
@@ -1,372 +0,0 @@
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diff --git a/unordered/Measurements/FFT Measurements 20182002/Vergleich.ipynb b/unordered/Measurements/FFT Measurements 20182002/Vergleich.ipynb
deleted file mode 100644
index b9e9d3e8c1b3cecd9c83f24f4af0819c92f76e6a..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/Vergleich.ipynb	
+++ /dev/null
@@ -1,186 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from nqlab import*\n",
-    "import matplotlib.pyplot as plt\n",
-    "import pylab"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Vergleich des digitalen und analogen Servos\n",
-    "\n",
-    "Um die Störungsunterdrückung der beiden Servos zu vergleichen wurden mit dem SR785 die FFT Spektren für verschiedene Bereiche aufgenommen."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 65,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "anadata=np.empty(30,dtype=object)\n",
-    "anadata[0]=io.read('Analog20022018_3.csv')\n",
-    "anadata[1]=io.import_data('ana102k4.TXT','ascii_pandas')\n",
-    "anadata[2]=io.import_data('ana51k2.TXT','ascii_pandas')\n",
-    "anadata[3]=io.import_data('ana25k6.TXT','ascii_pandas')\n",
-    "anadata[4]=io.import_data('ana12k8.TXT','ascii_pandas')\n",
-    "anadata[5]=io.import_data('ana6k4.TXT','ascii_pandas')\n",
-    "anadata[6]=io.import_data('ana3k2.TXT','ascii_pandas')\n",
-    "anadata[7]=io.import_data('ana1k6.TXT','ascii_pandas')\n",
-    "\n",
-    "\n",
-    "digdata=np.empty(30,dtype=object)\n",
-    "digdata[0]=io.read('Digital20022018_7.csv')\n",
-    "digdata[1]=io.import_data('dig102k4.TXT','ascii_pandas')\n",
-    "digdata[2]=io.import_data('dig51k2.TXT','ascii_pandas')\n",
-    "digdata[3]=io.import_data('dig25k6.TXT','ascii_pandas')\n",
-    "digdata[4]=io.import_data('dig12k8.TXT','ascii_pandas')\n",
-    "digdata[5]=io.import_data('dig6k4.TXT','ascii_pandas')\n",
-    "digdata[6]=io.import_data('dig3k2.TXT','ascii_pandas')\n",
-    "digdata[7]=io.import_data('dig1k6.TXT','ascii_pandas')\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Die open-loop Transferfunktion der Servos für die Messungen sind in folgendem geplottet"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 75,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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XX1/Atm2/UVpayqRJU2jWrDkAERGRZGSk8/nn/6V790tp1SqBV199G4Dk5GSmT5+OUoqw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WDSJIklS/px++15fO0Axkyow2rsB9+WDRCRXghdx6uJA/DkcXeY7Y8AzJgFHJN6CifgKew11ZRk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\n7EwWplRryGYzG30U4tz3F0o/uRExNIScs75+vI2yOaNXq36R5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30UoyfUYzZH6Y3djApV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Bpv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\nkKV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4RMCrZiDskF2NOhF9gFgqCR5nIQ+sfS+Vypdim+2fNKOHRKEQMpshCa7GWEZD4Eeb\n2cznCS5GVq7UgsiWTZXWtV4ZxHp7kRMmhDFHA/0gZSzuqDpnU3/6KTI//AEIQeFTn8OZtycA5uXf\n55YnL+HlF55j13kj/+iCYjXNfzzKgydfxm6GwbDWyt8/8zve+etPYR15FIODcOONJosWuei65IUX\ndL73vSKtrQkGBmDvvV323rs2xqRRjdpRtXixy223FTn//ARXX50gnycI/n/xRaUsPPvsyAho/Xr1\n2NaCTdnegTNxEsazz6CtW4szfcYmn1/4zBdwO8dRfsc7MZ9QUWbWQYeQ+PtfMe+/V8X1oUZepq/6\nPtrGjfQ9/sxWbdO2lpRjz40eRh/FN2x4WNDaKmNZmfXAZnQqXDQaz7bFds2B31G12U2SUnLhhRfu\njG0Z8zVUCn/IKoYPNr0jxgObd99t0N8vmDJFUEy2AdQwm0+mliClN2YxUhpurRs9G4JNIeMyuu+A\nD8Cmn7Ppl14fbLqIQFK3S/VkdPUaWXGC6IVmL9FCyejqNbVgU93eQB0ZHQeQwZSfuIyuwKaDjqG5\nXnyDApuK2ZSY2EgvZ9MHmVpGvf+yUGnmwnHwv55RsOlqumI3ITa9R4wgo6Np3j6SMbDpn6x8ZlOU\nywjX5ZnnE1QeNIKYE3/f++uIyejEQ93jMrpaQangsg9P0V2YzcaaCUIilrPpulFms76M7n+0ox3q\n7rOaoH70tqQ0b9yt1tONM2FCAChFuQyFQjA9CGrd6Klf3Ezy9ltBCGQmQ+7blwKw+IWbGc9GHv7T\nM+w6b+Em15/53iUMZSdx6E2f5PcfdfjjHw0uuWQyv/zlTZgmfGhhmqEhweTJLgce6JBKSW8KSGKT\ny21Uo3Z0vfWtDt//vuDRR/Xgwu7pp9X3buVKzcvarX3d+vXqezowILYadDl7zCPx978ibHuTMjoA\nySSlUz8GQGXpWxi+6BIqbzuQjre9mcS9fwOUEpj44+8wVr6oVMHtRYFbWKOVs6kC00dnm+rlbEoJ\nq1apYP/o/bqIyugeaPfAaDSP2bbDCUJjrUbcJMuysCyL6dOns3z58uD/lvWfe1U/XIowm6aKPpJV\nzOZtt3nTd0LSLOjZlB4YeyqjmE1ZNXnGwK7N2Ywxmx6U8pjNIG7JP/qrezYjs9GF6wQyuqOZwe1K\nwZfRjdjrQMnoPqPmU/alkojJ6DU5m8A6wugjP0ZIQcnw2yP66jObpuYoIO6BTX/UZJTZ9MFweZ+F\nnMyNvDLjbXUmCIUyuisiILxKRvcBfA3Y9C4EYmH3fi68rva7KKrGaxetNpok8jlUImDT0QwVBB++\n9fAx/+7ePnRcOipdgTziL7/ebHS/ZaC+jC6C53Z0SHp7R+/E3t3t5b+KMFx4k1UooHmRV1p3l/ob\nlc0H+gOmU6ZSNWCz/4Ve+ppmUNn/rRjLH1eveWklu5XUeD33wUehXEZ7uX5PmBgaxLzvb9zR8THK\npPj1rw1+5TXgX3xxgi9+MUl7u+TSS0usX69x660mRx9tBxdajWrU61lLljgYhuSBB8Lfjaef9tQd\nR/DCC/W/gxs2hMHfW5smZu+xJ1pPt1rH5sBmtHSd0mkfx5k9B5lIBH3S1oEHY6x8EVAtTWInGY5d\nV4wSs7l9M9brLTMKKvv6BIODglmz3Nh6dOEgEbHXRZnN6AShsRp9NCJGf8c73oEQAiklDz/8cHC/\nEIK77955vRZjqQaLIbNp6V7Opv+JJ5IMDMBf/uJJ0E4IJPx2TlfoOBMn0ZWYTosj1cjKSBnYaJ60\nLvJ51YOZTNYkdYcGofi4ypqeTU2nbBvBa31g5WDUMJvRnE3/SFXMpgLL/hVzjUEo1rOpbq8n7Nn0\nwaZRBTa16ElGukhCZtPPbkzgjXo0pDdBKD6u0kgIbuZk9qKk1h0BcbFQd6EjfKYxNq7SDqYORQP2\nhQ82pY1j1MroQc9mQQVcumi18nTkc3AiXzNHbN4gJHp6AOiwu4Pluq4ILmCqZXQ/Z3OkcZX+iWfK\nFMlf/zp6l7zd3WpZe+3lbhGz6Wf2QQg2oz2aoq8vAJjOlKk1BqHe5/soDk1g17kLGX/DFVAuU7rl\ndwD00U7H84+SvViNk+x77CncyVNwHDjuLUO844PNfG7fxxFScnvXgQD89KcJcjnB/PkODz+sPqNb\nbilw2GEO996r8+tfm5xwwhhLwW/Uf2xls7BggcMDDxiAOo899ZTG+PEuPT0aK1Zo7LtvbePyunUh\nyurvF0FL1JaUnxoB4G5GRq9buo4zfQbGSyuRySTW4UeSvHuZGqvsumgb1uN0dm79creytpdAjTKb\no0XE1uvZXLVKLXzWLJdXXgnPqZqoNQj50KNSETEZXcqxCTZH/IW45557uPvuu7nnnntYtmwZt956\nK3fdddd/LNCsVGDYioBNwzPn+CxgIsFddxlYlmDmTBfHCeeI+8TjTW2fIn/u+Wi6eqwe2AyZzWEV\n6C5EnVD3uEEIXSdPJs6CAhihjI4rAxndFiGzaZe8cZVGyL75jKu01ZQh0ySYSGBZjAg2pbfuYdlE\nQW/y4GUY6m4QkbBrmE0RMJs+UDewFeNqGDE3egA2/TGgTsT97VXUIOSKaM/mCDK6Xi2je5MZ6oBN\n2/vsRSGcBlUNNqOsdXQikSP0mJQfvaoNAth7NwIwzumqJmIDiSTa7+MD61RK1kwQiso+kye7dHeL\nUevb9JnNt7zFYcMGbbOsid61IbitdXdz3XUmq/45jEwrs5020B/I6u6UqTXMpjm4kR7G83TyzYhK\nBWPF0yT/cCf/YCH3pd/Obj0Pkrr5BoRlkbrpZ2Db9H/xYv7+8kym/N85GI8+ghSCe62lHHmkTS4n\nME3JT39aZOpUl2OOqXDYYepD+OY3y1xwQYmDDx5j8z0b9R9db3ubw/LlGr/6lYHrwjPP6Bx9tE0m\nI3n22foIw5fRYRtMQhGw6UzZhG1+E+XM3FX9nbEL9n4LALCOehcAWuScsCNrtAxC2zuJKFq+DB79\nDfAnAs2e7VYZhNyank3/vK5+F6Kjjt+gs9GXLVvGEUccwRlnnMGRRx7JAw88sDO2a8xVLhcHDWWf\n2QzGVaZ44QUNw5DMn+9EU3WCg+Le1ndRPv5ERcK5VdItPthUB4mWyyknOiGIC5jNKoOQpsMh5v2q\nXyZqENKjYDN0o1eEGTCbAdto1MrobsBsBi2pSkZ3w57NejK64wg2ZHZlkNYQbOLEwKZWx41ezWyq\nnk0daXgThLyeTaHHr/BsGyWTR761/i7yZXS/hYHIuEqcsNchzmyKiIwen40OkZ7NYpTZrDoDjSSj\nY47oRvevJcw+xfq1ykHcQil4PJRI4qAylNHjvZz+a/xjavJkieuKACRub3V3CzRNsmSJ2u+bk9Jj\nzGZPNw8+qCOGhihP2QVQU4S0oSGkaeKOGxczCLkuNJd66GE89+QWA/D8WT9j3MrHuI0TqCxazCR3\nPdrGHtxx40nd8FOaP3U68245nyFaODZ3M8W/PETX+L0YpoXzziuRSEgOOcRhyhTJffflueaacF+P\nHy8544zKmGQIGvWfW6efXmHhQpdPfCLNGWekGB4WzJ/vMm+ey4oVI8vo2aw6B2xt/JGz+x4AuJ2d\noStpK8vdZaZa1oxdsPdbyOC115M/2xsHu5PA5tg2CIX3vfyyhq5LZsyQsfVo1DMI1fZs+kTNG6pn\n068f/OAH3HbbbfzqV7/illtu4bLLLtsZ2zXmanhYYEVMApZWlbOZSLJypcbMmS7JJBHJU4YA0tvb\nioQTKv8xUkpGV7dFPq+YSggBZJWM7vds6jr8k/nIltaqvIQqsFmH2TTx52FFwKbuG4RsLMuX0X03\nOsHYSAc9BjatirrtOHDh4tv5Kt9WTnAgaVaBzSo3uosffWTjukoW0HEUc+z3bFbL6AGzKUDTw5nw\nxHs2ZYTZFFa1jO4ZpKL7TRMhsxl16Xsnqy1hNqPfdltGZfSRDUL+CSMxuDG4LznYEy4nEmsR79lU\nt9W4yvhyo/07U6aoO6Oy2vZUT4+gs1Mye7Za7quv1p5OVq0KJR5tvQKbbkcHWncXPT2CNgbY2KyY\nD62vDzE8hGxuRja3xqKPXn0FxkkFNu96fgYbzUnsv+KnDIg2bu88g9Z3vBmAYsdkhr99Kfr6daR+\nfQffbLmIS+b9iAn0MP6pv/EPYym77eYwa5bkppuKXHCBApjVokCjGjUWa9w4ya9/XeDMMy1++1t1\nbtpnH4c993RYsUIPLlijtX69CLJgBwa20pHe1IwzfQbOtG2Q0L1ydlHfb3eXmSAE1rHvxZmhLjD1\nyAXojqzRytnc0bPRX3pJY/p0iWlW/STXkdH9xysVEenZFLE+/bFUm91tbW1tdHo9FePGjaPJB0Bb\nWcPDw3zyk5/kQx/6ECeeeCLLly8H4J///CcnnHACJ510EldcoSazuK7LOeecw4knnsgpp5zCq6++\nuk3rHM3K5USM2SxpnkFID2X0l17SmDNHRaZErzCqaW/dG48dnVQDdWR0/0qyWhutMgj5TGnwH6+k\nbgRgU7gOwmMzK4TMpg8AYzK6z9Y6yo2eSIR9p+VyGJekZPTwqC57YNN1oa91V3qY4D1PJ2XaAcB1\nW1pVzqZ/ZpQywmxKzyAkAje6MJWM7vc6amY9ZlOLIbdSCTIZqULdhRE5W4TMpogahCIyutC1gJGV\ndWR0x/QNQpvq2QxPINHjxhYGYjM9m8nB7uC+RH9425dLJluvMuf/ziJBuYbZrIpkxbbDE89h15zC\n9/lMEIWyvdXdrTFhgqStTa1saCj+Q7Z+vWDp0iZOOSVNLqeYTZlO48zeDa2nm54ejVYGWSXVj5Hw\nDEKyuQXZ3Bzr2XxxeZEUZdLTO3liucGDFQUuvyvPYsq8ZiYf9Sa6mMA1+ic59rrj+at2GN+fcB5f\nG/oqU08/jLzZCsDt697KW96i9v9BBznMnDn25KZGNWpTZZpw3nllrr++yGmnWcyb5/KmN7kMDAhe\neSX+HbRtpUDMm6eO+a2V0QEKn/ocpY+evs3bG8roM8M7UynctrY3kIzuK0YiuL29VY/ZXLVKY9Ys\nT3XUo9FHtTJ61CAUVbLGas7mZnd/U1MTH/vYx7j66qv57Gc/S6lU4tJLL+XSSy/dqhX95Cc/YenS\npdx4441ceOGFfOMb3wDg3HPP5ZJLLuGWW27hySefZMWKFdx1111YlsWtt97KWWedxUUXbfmIrR1V\nuRwxZtMHm/4n7iZSrFqlMXu2DMCkf4BXX4n4uMiu8mfpOFXMZnP4AkB4wT7CisvoQtQHm+hxg5Au\nPRmdkNkM2MaoQchnXOvK6IrxhFoZveKEwePRwGtHGKT0sGfTHT8e4ThhzI0rkT6zKWp7NqVhKuBZ\nHX0UudqkTs9mNiuVjI4Imc1Iz2b0WyprejZ9sGlG71bv0wv0993oDnqtGz3ybY/1bEodXJVfunq1\nqGI21f7LDIVsZioCPCsV9fzDe29jyh0/5O38JQh1TyRkLIygXvRR26tPcwTLWL9eoD/3LPqqlWxP\ndXcLJkyQNDf7YDP++MaN6v3cdZfB6aen0brW406chDthIlp3F4PdFinKPD8wCZlOB8ym29KqwGax\nSOqmn9H6vmNY+6Rqu9jjwHZsW/An7WgG22dwOZ9j991dJk4zOOfk57l+6tnkSiY/OfkPfDf1NbJZ\nyeHv1Mm/490AHPxfC/if/9n2sX+NatRYqaOOsrnoojKGAQcdpM5rd98d/03p7ha4rmDePHVC2FoZ\nHaD0sTMoffCUbd5Oe8+91ICRfefH7ncnTQ6i0HZ0KRl920FiTNLeQTK6H3sUgs3IOnFHdKOrSXPh\nssYq2NxsYtRhhx0W3J44ceI2r+jUU08l4dFjjuOQTCbJ5XJYlsWMGYqif9vb3sZDDz1ET08PBxxw\nAADz58/nmWd2TvDrpqqG2RS+jK524cbhJJYl2G03h+XL9bpg0z9I/GE30bBvqI0+cjs64y+sZjY9\ng5CmgZQqQ01Wgc2ojO6zmRVpkPZu15XRq6KPTFPJs4mEpFymitmMgk0dHR9shl9sB52kEcroctx4\neGklor8f2doG0sX1mE2deM8mhgEmXs5mPNRdBZXL0CAUuUQslVSLkd7jRR/pPlKMhro7wTKjAfuK\n2fRaCRJRsKneUyijh9FH0atTiH8OlYiMbqOS1W+80eQb30hy553h3Fr/483kuxmglTYGSQ6EYNM/\nkcwuPAXAsfwW2z2cYlHgeWzqThAKmPXCMHPopnu1RcsZp+LM3JWhG25lW6u7WzB3rosaciUZHo7/\nkOXz6v+77+7w8MM62r4bcCZPwZ0wAePB+4OezOfXteGO60D09yOGhz0ZXV1opW6+AfOxRyjYLwEw\nZ0k73ASvvfNjlK/5IJ/7fpIjjlCf6QWXGUC0x7XM8DC0t4P2v18ht3ge7zxjJvznzqVo1L9pzZql\n2lmWLTM4/fTwHOebg6ZPd2lpkVsto49GubvMpPf5l1WbV/T+iZPQunaOjD6afYw7Cmx2dwvyeRGA\nzXj0UZTZ9EgnodjPaKi76tF/g4LN9773vVu90Ntuu43rr78+dt+3vvUt9tlnH3p6evjyl7/Mf//3\nf5PL5WKyfDabZc2aNTX367qObdsYEUDU1JTEMHbeHnVdsCI9h26qhba2DKJNbWdfQf04zp+f4F//\nUleTiYSJpkE6rbYzldJoa8uQSGhoGpiZdGwdBjbZrElbm4FeKqC1t6p1NCtw05xNINsyaF7vZduE\nNtA0Mhl1AmlpyWCmQ/a1ub0JPMd7KqHTklW36zGbTe3N0KbYWtGa8R5zkdIglYK2towXf2SSSajl\n2BjoZrg+V+q0tWVwHMhmIxN5hE5LVgTr0scpEN2iOdCWQTc0ykJDCg1dkwihkU0n0ZAY6SRp71DQ\nvMu3ts4m2rxtNQwwDJNkKoGQLkJX+9iyNFpaFFssDJPmVtWSkIxIIAkBwttfejJiBDJCGV1PphBC\nIqWguTlJWxuQUvsu5aj+TwcdTTNoawuPRy0bpitLI3o7ieY6rFuXoFAQaFr4mBBq2weLG3mavTmA\n+2nKh72t6XQa0JiVXwHAMdzJH8yrcF2NTEZ9Rk1N6ljIZtO0tYGmCRIJQVtbBi2fQ+DS/uITGC88\njzauM9iPW1tSqp7N6dN1OjoyNDdDpWIihMFhh2lcd50bSPr77Sd44QWBWN+Fvngh+oxp6P19jEP1\npvZU2ljZ18nK24fYK5tj/JtnkJqoJpb5eZrjXnwMgOkLpnL11S69RriaAAAgAElEQVQHH6zR3pHl\n3HNhU6cxb/AZtO0Be+/BpucLjVy6d1w1qlGjXaN1bB1zDFx5pY5hZPypqwGTOXduks5OyOXi56md\nVnXenz59GuLev++k75Ugmdz2997WFt4ezXOBEBLTVL/5K9RpnTe9yaStzSSbDS8MTIMAbDY1JWhr\nU79XpokXlxi60QEyGfVex9J5a4cMNTrhhBM44YQTau5/4YUX+OIXv8hXvvIVFi9eTC6XI+/NAAfI\n5/O0tLRQKpVi97uuGwOaALnczpXC1q41YzL6QNlgYKCAWXJoA15aow7iiROL2HYC2zYpFFRupuM4\ngIaUDgMDRaRMY1kwXPCYxmQWs5zHwMayKgwMWHQODVFOpMkNFEgUK7QCw4MF7IEC2aE8adNkYEix\nOJaVAJL09RVotRx8z+BQ3qJQdHERlAolivkibYAla8HmcNHGGVAsm1GwaQfscoVCwUHXBQMDBRKJ\nLIODNsP9eVpQYLNQivRJWtDfX0DKZly3gj91xRU6tlUmbdpQASudJQXkNvRizyjQVLI8g5CO5law\nLJeBjapfr+KC3z9te87s4YKF6W2rpjWRz9uUbUnSdnAcl4GBAoVClvZ2tVTLEQzlLToBK1fEh/iV\nYpmhgSLjATsa4SRCg5CFju55ekqlMgMDDpam3le5f5AM6iRQKDgMDISsWqrs4GeBFyrhCa5UEchK\nhdWr1THR21sG1MmgUlHb3pzv4hH2Z5AWjN7wyr+/v4hbNpiee47ylF2YtO5VdvvDpWSez/PXxNcZ\nGChSKhlAmsHBEgMDLqVSCk3TGOjLMd4bFLDwGXUh6AwOMzAQMqubqkcf1cjlBIceqo6bgQGwrGZa\nW8sMDFRoasrS0+OwfLnFU09lWX/VL5k4/BJwNnPmqGNBW7+WUsc7cFo6aAbm8i8ABmml2+1kVlsv\nsneIh59rYZGWpJVw4tNuvSrrdzDRxHHH5YNt2FnV1pbZ4n3VqEZtTY3WsXXggTrf+16G3/7W4uij\nbVwXLr00w4QJLhMnFmhtzdDVJRkYKI7CVm9/ZTvGk16/noG+HEhJ4k9/wDroENhGX8imynGyVCo2\nAwPbhhvUWF61XVK6o3Yu0PUmCgX1m79+vQ5kMAx17rZt9bsOyj8R/CZZFgMDir02DO/3r6wDOlIK\nz51uMTBg7fTz1vjxI0/A2Gn+y5UrV/L5z3+eSy65hIMOOghQ/aCmabJ69WqklNx///0sWrSIBQsW\ncO+99wLKQDR37tydtZkjVl9fXEYvCgXpfKn7hf6JdHS4dHbKQCb3HXA+pR2V06MGITujPiDlRvco\n8nw+jD6qYxAKpgdFluu61PRsOo5QLJ0rAxndkqFBKJTRI1d8RjRnM+wNSaVqDUKxnk07lJOj1waO\nMBCOQ2tWrcv15BTfzS08N7oUmupNkWFfKLqOnvQWVlZMomaEV3yG4UkImqgJdW9qikwQCtxE0egj\nG9frA42N69QFtmd8co1E2Nrgm2+8HbJpg1BURg/3rZLRnSB+KGqO9z/elnI3XUyki4mkh+M9mzNK\n/8KUFXpO+Sw2Ogf86quc9Nw32N1YGdvGaM+mpoXjTwEO2Xi7em4hvKAT/X1kv/ZV1Zxcpy67LMmp\np6Z59VW1gq4u9f7Gj1fHa0uLZHg4dLsu+MvFLPzlObQwyLx5Dm0MoJeLuJMm445XxrHdeQGAcy5J\nst+hLezWsZEJyUGeW9vGSz1xyW2xfAQAGVCVjWpUo6K1ZIlDc7PkrrvU+eYXvzB4/HGdr3+9TDoN\n7e2vj4w+UjmTJiEqFbR1a2n52Idp/ejJNH/p84iBfpr+6yzMe5aN2rpGy41efXt7K/j9Qv22QuiP\niK2zjkEI1G9zNPpoR2zjaNVO26RLLrkEy7L45je/ySmnnMKZZ54JwHnnnceXvvQljj/+ePbcc0/2\n3XdfjjjiCBKJBCeddBIXXnghZ5999s7azBGrt1eQadKCXryCVPKnM29P+h74B3fl9mfWLPXD63tV\nwgBuf5apWpYyCImgl8/OtKjH/Z5N20YUi7XRR74C7NgxNBcDGFXjKisVNSZTuC6aZxCy3FpmM2aQ\nCYCZygtNJNSKk8l49FF1z6blhGCzumcT26GtSa3rxW6lSQytywcbLhEB2HRdcK0QtepJzxBUUVel\nIgKMDUP1rFSHupdKgqYm3yAURgLEo4+cYASmrHajewBRmmas1xbAMAUlkYpFH21qXKUlzXCOrTQQ\njh2ANf8E4ycYkM+TdvJ0M4EuJpLNxd3ouxXVaMbCorfydc5n1byjAGg11dVrNdh0XYFhhONPAZqk\nuu33nAKkbriezI+uInHf36lX5bLap1//ujoTrl4d9oJRLvOZ4YsQfX0MDgoy5Jm07p/ors1R/JHd\nd3c5gx+p97BgIe6EONictV8z+uRx6GtWk7EGKKda+MkvO9T+1zT6tE7aGUAmk8js6LMejWrUv0OZ\nJhxyiM2yZQa2DRddlGThQocTTlDn3fZ2uU0GoR1V7sRJALS+/z0k/vg7rLcdSOqO22g//EDSP76G\ntpPeR9NZnxuVdY1Wzmb17e0tRTzFiQc/+WVzbnRQv3/1wOYbsmdztOqqq66qe//8+fP5xS9+EbtP\n07TArT5WqrdXZQpSMaFcpkDYB+HsNpeBAcHUqT7YlIHRWdPC7MMow6nc6OoOOxsHmz6ICX5Yq0Pd\nbTvGRMaCvKvGVdq21+sRMQhZdaKPovbxIM7JmyCUyfhgU1IqUcVsRlzXkbFZUWbTFcqB7TObG4pt\n7AuU+oqkJAwPSlyhRkRqeNOXLDtYkN/y6I+a1BPhOn2Jm5QWjJ4E3yCkwGYFPZzoE6EghR0ym9Fv\nZ8wgZNSCTV0HS0uRjIyrjGalqX0YLs9yDTIZ5dauSGUQqmY2TdO7+t6onOg+2JxZWBEsx7Zht9Iz\n2MKgMnsuF7GUBW95E7Oe+yOtZj62jfFQd8IxkLqJ7qjPIQY277hNvTdvbnF1WZbqL/rTn0wee8wK\nJl3MmiVJX38dn177NUynRH///7CUh9FdtZ+P5bdMdBfydXEBj089hhlL34K29jUAFqL6MWVLC4VP\nfobEn/6AvmE9s/Zt4qf/aAegf/I8nlnbwYHch9s5bvTGdzSqUf+GdcQRNr/9rcmVVyZYt07jG98o\nBueE9na5TdFHO6rciWqssf7SSoa/fzXl9x5P2zsOxXjhOQZ/fCPmg/eRufaHlI87gcpbD9i+dbnb\nN9N8R4HNKEfiDyLxyZ3NudFB/W6obM3a5Y61GoNk69isvj4FNqVniMm58WkKpRJB8LlPjddGH4Xh\n7tHoIzejQGUANj0WKmA2fVZOhjMIo0xcFGDEwsl1Je9K4YFNL/qhnkGoHrMpHJtKJbzS8mV038Fd\nLaNbth58caLRR67QEY5DS1ata6PtSaTDOR5/XGPZXzRKZcUa6ziK2ayEM9uNVMhsugiEFpfRFcgO\nv7VqZJdQQd24MRldRClIx8H1Z6NHmU2tvowezUsti1QA1uoymxFQVMEknfb2vatc875z2z/B+MeM\nDza7mMgGJtFaijObc8tPs655LsKLvbK8GKYWoxjbxqgbXR1TCmz2zdhXLSvTHFzU6M89i/GsSnzQ\nX6oPNm1bsPfeal898YTOyy9rtLRIOpI5Mt+7BICjN97A0IDkQO7FFRpP7vZejuYPTPjCaSSwuGTy\nd9Q+nTKV1Z37si/KVS9bWnBnzWbg13+gsmR/ygsX0+eoY2RFcgFrErPV6zobEnqjGrWpOuwwByEk\nF1+coKVF8va3hxfXbW2SwcFaYPJ6lTNnDs6kyeS+cxnl938ATJPB239D/98ewnrXseTPOR9n8hSy\nF55P3bT6rajtdaNHr3G3aTmui/HIwzV3B2QJYFlxGb0abFaHuoP63VDRR/GLiAbYfANXb6+go0MG\nUUdFmYo9XioJz60dyuSO48cTqPujfx0HKq5altMU9mwKETJOMuOxp/Ua8Yz6YDM2rtIwqFSUPI3j\noLlhzmZtz2Zt9BGOE0wQAsVsKhldfTscdBw3PMjLdlRGDxfnCMXmtWTU67pKnrUvX2DjRoGGS9ny\nmE2pZHRZCSlSM622x6iUPed3uGz1ZVXz4/0xmv6scF9Gd9DDkHWvZ1MmEmDbyEq9ns1wNro0jFoZ\n3QebxTD6aFM9m2U34QXjS09Gd/B7InwZ3TS9E2JPnNlsqfRhoujPSkUwp/Ica1r3CiQWy1DHSLPh\nM5vq/jjYlMEFTN/ebwOgZ++DFENuWaTuuA2p69i774GxCWZzyhSXceNcnntOC/LgMj+5Bm1jD3/Z\n/Uym2a8ybsV9HMB9vNK6Dw/O+iBtDGI+/hhXLvghD/V4vddCcOeMTwXLls2K2XdnzWbgzj+jH/wW\nNjKOUvtElplHMTR+lnpeR0fdbWtUoxqlatw4yYIFLuWy4NhjK8FvEqB+v9j6KUI7qmRHJ31PPk/p\nI6eF97V34MzZTf0nlaLw/76M+ejDmH//6/ataxRl9G1Zjvm3e2g/5u3oL/4rdn/QPkWtjB77nYuB\nzRB4K2aznow+9oZVNMDmFlaU2SySCqbl+BVlNqP5WfUNQuoAq/jMZpNicYKezapxlNV0lXCcGDgc\nySAkNS/vU+ggwzngFUyM6lB3s3ZcJY4TYzZVz6aI9Wy6LrgewLViMnqkZ1MY4Ni0ZDwZveAxm7kc\nlYoCmw4aCA0NBymJyei+QUi3RwKbxPQIf6JOJoMHNrUaZlOaCYRtI+sxm9EJQmaizrhRSVmkgjmR\nmxtXabkGuq72oyUVCveZZf8Eo/JCRcBs9unjeRU10s2Xmx0HxjldDKYnB4sv6x7Y1EaW0Q0jlNF7\nDjueRTzG+t0PVO81n8O8/14qb15CZfHSEZnNg/t/zcHdt7HHHi7vXPYlvvbIu5m9q036J9dgHXAw\nv3vbtxikhaMe/F+W8jBPtR7AY51HckXmywzc+WdefusHWLs2PD7uSH2AQb0Dt6m55jJ8xgwXiyTX\n/O8qrhs+kfJ0BTYbzGajGrX58tlMv1fTL9/Mt2rV2ACbwGaRW+mDp+A2t5C88zfbtRrX3T6wGX3t\ntixH8waYiP7++P1a1CCk/kYV0nCdtbPRQRFBb5SezQbY3MIKmU2TskhTqcSPuGIxZDb9D9qyxCYn\nCA20zeQGPsTQ4kPU476MXhnhEieCIKJyefiwqG8Q8no2kSHYVCXryuhhf6Pq2Qzd6HFm0web0gOb\n5Yoe9C7GmU0TUbFpSqtvxMbhJEVSUChQLqvJSC4arqZ5PZvhOoSpB/2pJioiqeotem708FvrM5vh\nBKGIG93XuxOmCnX3+zwjPbDCiINN/+Tis4ahjK4AnmI2q85Akc+n7JqYpiSZlFiOx9J6+90/wfjM\nphhUJyW7uZ07OI5BvZ2zUDK1UyiTlXmKmY5g8WVdyejNmh8Fpe53g44LEZPRjc4WHmcRBS9NQRQK\niKFB3AkT1RjJ3l41SjRSxuOPccnaD/DxZ7/EvD0cDu75JYcV/8BHe76D/toaSiefQrozzeV8jl03\n/oMUJf7W/E4GSykum3QR9vwFzJghqVREEDK9ti/D7XO/SuWAg6iuadMkQkj+9aLOunUa+lxvtnLD\nid6oRm22Pv5xi2uuKbJ0aRyBHHqoTSYjueUWc4RXjsFKJKgccBCJv94FlQqZC7+B8fSTdZ9q/ONR\n0pdfVvex7QWb0RGV2zSu0vvd8dUwv6I9m76MHhqEIutnJINQo2fz36oKBQUmOzsV2CxqmVhkDSiA\n4/flRccoqjT/OOPpH2AWCT7MDVi7KOZGgU0ZMpse2+iDuQiC2IQbPfKN0n1mU7nRhRPK6KDYtc3J\n6PXd6JEJQk4YNmvZWoDloouraCZULJrT6sHuPpM8WbR8nkol/CJJoaFLr2czwmz6C0tSy2yGbnQt\n2D+lktoHURnd34c+s+kYSbCdiEFoJBndrNuzWSIVRB9FmU3L8nB9TEY3MAyf2VQL88Gmf4Lxe0/9\niCKtOUOeJm5q+STHcQdzeBF9UIHAclNH8Jn7zGZWFBCDA+zxu8sUKI8cKlGwmehUfcA5LzNOgc0h\nZEsLzpw5aldEpHSRG6bl46ei49BRWs/bzb8yhXUAHP3AubjNLZSPehfNzZJzOJ8FexYU2NQPJ59X\nI0NBsZUAq1er/dLTI7h/yRcYuv5mqiuRgMmTJffdpz6Tpvm7InUdd9KUmuc2qlGNildTE7z73XYN\nuGppgeOOq3DHHWbNaNmxXNahh6O/tobMdy8ke9l3aX3/e2pH7RaLtHzyYzRdcC5i48a6y3ldDULe\nD4QolWJ3q5a6eP++T9REpfCRwKYffWTbqs0tutyxVg2wuQXlx0V0dkpkIkFZy8QMIYrGDpnNIOam\nMnLOph+NBKAlQ7ZL0yImFn86jxbv2RSb6tmsHlfpRR/hhDK6b0wyRDhCMoYOIwYhywofqiejO04I\nhiUi6AeK52yaiEqFppRaV+9QghxNiGKecllEwKYeRB9hhz2bfq5lPbAZTKn0ADVSRphNPIm+Nmez\nezCl3Oh+b2ikjUDTI6NEE7UGIV2HMqnYuErbVl0OCxdmuekmM9Y7a7kmhqH2n+Wo9xKCzXD3K7CZ\nJ0+GbIt6/TWpz1LB5Ax+hD4Qgk1/m0qaYiizokDi7mXMv+lrHM/tiuUGvrD6LE5ce1nQs5ka74FN\n6TObebThYWRTc9Arpb8UnsiNRx9Bf20N32y+EICDHvkuAMs4HCEl5fe8D9LpYD76a2t1KiTI5QSF\nAkGSwezZ6tg7++wk111n0tenBbJevZoxw+Wpp9Q+mLpXCwN3/pnSqaeN+PxGNapRm6+PfKRCoSD4\nxS/eOOymdchhAGS+dwnOTKVytL7nnSR+f2fQWpb5/mXoq18FwHzskZpl+Mkw21rbCzbFJpjNaM9m\nMikjSlpknTJ0o9czCDlOaCyqfs5YqQbY3ILq7VUfckeHBMOkrKdjYLO61yJUbAVCRBmx8HHHEYH0\nqifiYDNkNj2w6R19oRvdHtmN7v1HeiuuVISSxSPo1mc2M0kFNmXUxUQoqQvXoVIRAa2/z8C9PPTa\nDPRB1XeiZHQRgE0XLQDmuq6kUABbM6Fi05TyWEV08mTRC1XMpqYhamR0I2AdfbAp4uStujL0t19K\nCgV/ZKOs6dnEUttQchNqP/o9m1HwHmE23TrRR4YBBapldPWxdXUp80y1jK7ApsTyoqL8ns3QIKT6\neEU+T44mWlrUvltjTWQlc5jFKjSv36fS0hFsS0EqGT1DIejLPJ1rA4PQgUO/Z+nG36PlckjDIN2u\nzkjDXpqCGBpCFPLI5mac6bsgDSNmEtK9mKI79BPIJdoZ/8Td5MjyMa6jMH8xxdM/AYA3yjy42Mjl\n8JhNdf/06ZKrry7iOHD22SnvvjCqqrpmzFAjQgF23dXFXrQY2TTydIpGNapRm69993VZssTmwguT\nvPTSGOrd3ES502dg7zYXISX5L/0XA7f9FtneQetHTyZ5x22I3DCZK75H+ah3IU0T89Fa1/frnrPp\nA4a6zKa6bVnhb63/WLDOEZlNfza6CBTI6teOlWqAzS0oH2x2drrIhAKbvvwJoSGlOrJgJGZTCC/6\nyCMVtQjYjPdselef1Xk2VTmbMYOQ0GJ3BsxjlUEIIGm6GNi4WlXcasBsKoOQT+vvNvQEU9y1JDas\nUZvhG4QImU0fbGpauNmOMMGukE2FjGiOJvRSnnI5CjZ1dBk3CAkj7Nn0wWa0VM9KZB85Dv6k0wBs\nSj2Mj/KYzbJMqAgpx9unIxiEqBfqbkglo1dC8Gzb4fkklyN2Rig5ZiijV/VsVjOb7lCOHE0BeCsW\nBV1iEpPYAL1qTrrdEjKb+aJGgTRpWQjYy0P5K+m1LwGQcYbpLK9HDA8hm5rIePN2fbCpdW1Qn11L\nC5gmzsxdYzK6tnYNUtdZ7Uxj5eS3AvBkcglDrdPJ/fkunHl7AgTMpl+5nCCfJ5DRAY47zua++wo8\n/niOO+8scNxx1a6qsHzZvb1dxuYSN6pRjdq+uvLKEomE5CMfSfsexzFf5fe9H3venpTfezzOm/am\n/+77cCZMJHHPXRj/XI4olSh9+FTsfebXBZujGX20LaDV/90RVTtc12UsZ3MkKXxTPZuVisC2iSUP\nNNzob9AKwaZENjWTN9pizKZ/sVLdszkS2AxC3QOwGfbx6TrgsXoBs1kv1D3GbNYJdfdWFsjonsQM\nIdhMmTYmlXjGJsTc6JYV9my2VlQvjF5QoKZaRnfRgn2lh/gOW4vL6FGw6bvRXc+NLnAVW+rJ28LU\nA9axHtj03egygrjzeZ/ZVAyijR7/UIAySeVGj8j1wf6MGYRG6NmMRF/5BqEQbIpY76zlGhiGJJGA\nsgc2J3YolFltEJLDeQ9sqn1eKAh69YlMpCtwMjpt7cG25POCAhlSshD0ZTpoTL/rBgCa3CHarS5E\nLodsbkHT1HE66Cg0q3V1qffpxQ85c/dAf+G5cP++9hrupMmUbIOXpyqw2TV7Cfvt58ROulGwqeuS\nfF6Qywky4ewDQJ2op0+XLFnixK7iq8sHm7vuOjL72ahGNWrra/p0yeWXl/jXv3TuvHOnzXXZrip8\n8Sv0/+2hkPkwDOwFizCe+AfGEyqto7LfQiqLl2I8ubyGQdxesLndzKY1EtiM52xGz4kjudGjINSP\nPnJdRmRFx0o1wOYWlM/WdXRIct+5jMt3+17MIOQbUqrd6ApsyrpudMcJDzJ/HGPYszmSGz0SnjiS\nQShAtN4oTDscV1ltEEolFLMpjar+HSOU0W07dKO3VFTPoJZXoKbaIBSX0SNko6aYzXSiErwuTxaj\nVKhhNjXpxGR0LRGX0d2qQ1ZFBhEyuhFms6lJesvWQQikEAEbGTKbHoA3o8ymCNeTSNSV0aM5qz6z\n6bPd+Tyxb3vJSQQyug82p03ytqMcNwjJXJ482Rh46zMnMJEutAEFNt32zhqwmXYVs2mnsqxgL5pX\nPwu2TVoWyVYG0Tb2BEMCMhnJoK1QoLZhvVqmBzbteXuiv7wqiHXS1r6GO3UalgUrZx2O1DQOPP9A\nbrwxftJsjijckyerbe/pETFmc2tql13U62bObIDNRjVqtOvwwx1mznT5+c/fOL2b1ZRiZdGbMV5a\nSeKeZTgzd0V2dFJZvBRhWST/+DtEdzgQ4/XO2QyYzVL8vFkdfRQFjNU9myGzGc3ZlA2D0L9T9fYK\ndF3S2grOnN3obpkTiz7yL6JCg5D6a9t+9FG1G12OKKNnMlE3unciqBPqLjdjEPKZPtsW6vX+SCOi\nzKbXs1nFbPrRR64H+PzNaLI8sJkLwWY0+igqo8fBZgJhVcgmwjD4HE0Y5VysZxMtMhvdC1vXEgay\nXY0unEC3ygyNVBB9tAlmM5jfHrmMLLsq1N21vRB0vT6ziWnWydmMg02/Z9NnNvP5sI9VrSuU0QuW\n2plTJqjPOBxXKXFdgcjlYj2bAP2JiTSTI9v7GiWS6M1pb3sk+TwUyJB0Coh8DjvdxABtmPmhwNkO\nyvTjjz/NZqG/om5r3Z6M7qFFe8+9EK6L8a/n1eteW4M9dRqOI+iZvDe9z7+MPOCtNaxkdHunTvXG\nolrbDjZ9ZrMBNhvVqNEvIeADH6hw//0Gr7yybSjs6ac1nnji9YMQ9oJFACQevJ+Kd7uyeClSCFo+\ncRqdi96E8agyC7muGLWczdHu2fTNnLUyen03erVByA91bzCb/wbV2ytobw9nnCcSMsZs+sx4aBAa\nyY0eghbHCSMPjJQCOmeeXuDgg52IG10BkwC4+KHuNTK6+huL3PGk8EoFXN8gVNOz6XgyetWR6QFZ\n36ntTxBqLikZvRps1mM2NS38gvrMZiYZyuh5sphWXuV46m7Q5KlVRR8JU8fxIm/aGaiR0TUtnCCk\nVuZEwKbq2fRHT6LrCO+DK1PNbEZySyPMZn0ZXdYwm5VKCByVjB7p2bQNTFP19L62Qe373Wf7zGa4\nyx0HKBRiPZsAQ+kJAIzb+Dy9dJJKh4DeZzaTtpLR7XQzg7RiFIaCHk4Abc3qAFBmMpIBS/Vsbnjc\nk9FbPBl9z73Usp9doUacrltLZfJ0QJ3MZFs79aqpKTwxTpsW3s5m6z178zVliuTrXy/zgQ9UzwFt\nVKMaNRr1/vdXEEJy881bz27m83DiiWmOPTbDffe9PsjGnr+fMrcC9kIFNuX48Qze8kuGrrwGZ/IU\nWj9yEtrz6sL5dTUI+dFHm3Sjj2wQEnLk2eiWJXBdEQOq29MysKNqDG7S2KvZs10OOihMTVUfcPi4\nL6OnFeE0Ys9mdai7z2z6YHOPOVZsgtCIoe7OSAYhEX6jvJUFgeey1o0eMJvVMnoQE+TENiNTUsym\nXvB7A1WOp/QPI60+s2lrKp8hZajlpbKK2TTLyiBkCJdkCvSEpr5UEvScN3GhuQk5bhy28ABwHYOQ\nYjbDfZTPK9YvlQLD79n096Md9mwS6dmMyugxZjNRP9S94MaZTccRAdtdzyCk65JEQlKsqPXMneUz\nm1XjKgvxnk0IweakPgU2/ZOKpoVgM2ErGd1JNzFEC2ZhCDk4HCxDuG7g5s5koL+UQQpBZbXPbHpg\nc+YsZDqN8ewKtJ5uRKWCNXGa975HZimz2XD/TJsWspF+9NHWlhDw2c9agZzeqEY1anRr6lTJu95l\nc+WVCZ58cuugwHXXJdi4UWPCBGU0eu21ne9sl03NOHvMAwiYTYDKoYdTPv5Ehm65HYSg48iD+ARX\nv649m2H00chu9GoZfUsNQj5hEY0+MuJi5ZioBtjcgvrUpypcdVV4kPhXE36FMnp19NGWGYR8Vk04\n3tVPpUpGD9zovozubF5G1+oZhOq70akxCMXjefzNyBSVG9ooDgcrdhwRjKs0TRGLPor2bArbRnPV\n+xs3UZAnS6KSp2JJdM1l7u6w196gez2b6d616rWTp4CmMZCerP5fR0a37Qij6zGb2ayaTAQoN7q/\nT7zWAAU2608Q0gxRJaOrmz7o1PUwcghCZjMqo8d7Nk1MU/SOZk8AACAASURBVJ1I/IzTWbvEmU0f\nbOrFWrCZyyqw2V7aQB8dsdSDfB7FEleKCmxmmhSzWRzG6g3BJoAbYTbzBUElkQ0C2n1mE13HnrsH\nxnPPor2mUgfKHtjclKFHiLBvczSYzUY1qlE7vi6+uMS4cZKTT05z5JEZLr98E19yrwYH4YorEhx+\nuM211xbJ5QTLl78+7GZl0RJkMom91941jzmz5tB/zwOUl7yFqzmTIx44P0x02cqKy+jbsIzAjb75\nnM3oY8H6R5DRTTPMlY7nbI69i/QG2NyGSiSocqPXNwj54yqrDOIesym8udUyZNV8Z7QHiKqZTTGi\nG139jbnRDU/i9kZYCscNXl/jRq++DBIKQPrxPIkEICXpvAKbZnEYG51EUsRkdDOl0dMzgkHI72IG\n2sfrFERWBdUWy+jCJZHWSGZ8Nzpk+tZRwUCOHw/AYFZJ6dXMpq5LL/oo2rPpRe543+KYjO596S1U\nz2YINiMGIUOLGYSqLxb8CUJ+KWaTKjd6+NWybD0wCPlgM21WRx9JD2zW9mzmmyYGt3vpDI4zIUJm\n06h4zGZGyehmYRC7Px/bV6FBSLncLTNLFnXyW7WxhUWLsjz9tIa9514Yz63glm8rib0wbgYQH0Fa\nr3yAHGU2t7Vns1GNatSOr44OuPbaItOnS/r6BN/9biI4h9cr14VPfzpNLgdnn11m+nT1/e7ufn0y\nO/Nf/R8Gfvm7eO5PpNxJk+n72e38mI9y+APfJHXTz7ZpPUIQ5EZvk0HIZzZrejbD6KNNyujUn41u\nGCH+aBiE/g3LNDfXs6n+b9v1ZXT/asa2BYYRMaf4VGelfqh7XEYfaVxliGz9xY0U6p40vAlCRu2R\n6Qo9wmxKyOfRbbVdifIwNkbAxvlfglRasGFDNGfTYxY1U4E8Vy1v/iJByVCUl17MoYvans1s/1rW\nMhUjoZY91Dwysxl73x6z2dQUgs3AIKSJABFaJBCOjfTHVUaQlB6R0UWyvhs9CjbDns1QRg9MU6aJ\n7YjAIOSDzcyrL/A/XEC5FFm9bWNUSjU9m6WW8cHtqIzuM5sFMhhWES03jJNRMrruVHC74mPbfLCZ\nzarge3/UpSN0lr/QzOrVGueck8TeY0+0nm4yzz6h1j9+avUuqls+2Jw6NcpsNsBmoxo1lmvRIpc/\n/rHALbeodJDrrhv5i3755Qn+8heD888vs/feLp2dEl2XdHW9PmBTTpiAvXjJJp/jCp3TuZa1kxaQ\n+sm127yu6t+BrarAIFQbfRSV0UeaAiTkSMwmdZnNRs/mv0kpZjMqo8d7Nrck1N2PPjIMwqghX0YP\nLcrqr5/ZGAl1l1HZtx6zqYVzyvFldC86yQc8gYxe3bMJuJoRk9G1/r5wfdL1wKaMRR+lsyJw1lW7\n0bEqipEFPvMFl5Luz+bOK7ApNKSuqy+VK8j2r+U1pgX7LNfiM5vxQzYwmPtPdBxyOW9yTT1m07uv\nTDLm0B/RIGQYNScZXZc1zGY0Z9N1BWXbe7JpBgx2Mhnu+7Y7b+ECvk6ipIYUGwakXcVEVsvoZjZB\nLx2ADzbD7entVcymaRViMjqAWKtaEcopJZHLJvU3k5EUClDUFeAvmi10davtfeABg4fKCwA4duNP\nyGtNFJNt3lvZNHBsbpZkMpL29vB51TmbjWpUo8ZmzZkjOeoom2uuSXDssWl+9KPa34UbbjA55BCb\n005TJztNg/HjJV1dYxdKuK7yFSzf90OYTz+J/vxzm39RnfLP/9vFbBZHjj6qltFHij6Krl+RLfGh\nMv79Y63G7hEyhqvWIKT+1rrRVdxCGH0UMlJSRuIyjWpm05O2g9GTcYPQpkLdg3GVhhEsbiSDUNKw\nPbBZe2RKTQ9kdNMEra839rjPbFaDTb90PeJG1z1m028T0HUsU6EQs5xH11wFqDUNzQPUTYMKbPoA\nJ9/ugU1RLaN7bnS9jozuz4L3waYWvjZgNj0ZXYsZhCI9m4na6KN6MjqE/ZcAxbLXJ6obVCp4zGYo\noxsbVQacVi4G+zgjRwCbJnShpHQlo4fHk5SCRGsarVxE5EMZHUBbr/oxhyfNUdtSJaMXhAKbeb2F\nDRs0kknJLru4fOv+QymccSYdbi9r9RlUbC3Yjk1VczO0tckYm9lgNhvVqDdOnXWWxfjxkhdf1PjR\nj+L9m+vXC9as0Tj0UDsGeCZOlK+bjL4l5XM0K/Y6HqnrpG6/dZuWMxrMZr1Qdz+VplyultHDc6cg\nOhs9nrPpV2Nc5b9hJRJyi3o2KxV1YNTK6DLCbErQNBXhYEeYzXrproGMHg91j42r1EIWz5+9Ln37\nex2DkEmlLtiMMpuJhET09cUetzFIJOIyeqYKbAab7bnR8ZhbqRuUDAV89FIeHV9G1xHSASTNHtj0\nN63UrmT0kXI26xqEXH88pm8QivRRkkBIGYTHx/anGZHRE/Vno1fL6EAwkx2gUPKZTQOnjoyub1T9\nkJqnoxuGpAkVVZSjKWasMU1JjwjBpn8F65/w26akELlhRLGImw2ZTXODYjbzU2ar9x8JdS8U1HoA\nhkQLXV2CiRMle+3l0N2jMXzeRXxefI9rsp+nKolrxFq0yGHpUkfte6+/qWEQalSj3ji1994uDz+c\n56yzLFav1lizJjynPfqoOs8tWeLEXjNx4usno29J+T+bxebxWIccRvIXtyB6erZ6OdsFNv3f9k3O\nRt+EQUiOPEHIr2jbakNG/zcp01SspX/FVCyqH9eovAm1PZtxg5B6PDhwDCOQeKlY8TgiUU9G34xB\nKNKziaZ0+2qDUMLv2UzUYTZFFbPZXws2g3nedcBm1BjleOMqhR0CO8tUKMQsKxldBj2bLh30Ydql\nmIxeHlffIGQYvkEoGn0kYgYhx61yaOEZhAid/yKyD6IGIZEMDUJRN3qR0I3uP7cQMRoWymp50jCD\n+fLz5zvsPs9jSXu9zNIIs5klZDZTKRlcqRoGdGsKbFa70QE6p6eDY8fNNjOEkssTPcpkVZ68i9qW\nZl9GV2zwkK0+gwG3le5uwYQJks5OSW+vIJcXXC4/z0+N0wOwGb1yrldnnWVx9dUlhAhB5rZGHzWq\nUY16/Wr//8/emcfJUdb5//1UVZ/Tc2Umkwk5ORIggRAgXJLIIYigsKJcPxFB2QVxEZBwg+KBGHRR\nVjk8uA8RXER3XXFRF2VBEJQzQRAMd85JMskcfVY9vz+eOrure7rnygTr83rl1ZPuqqeeqq6u+tTn\n+/18vweo68kf/+hdM//0J510WjJ/frDRQleXNaHJpnPb1DTInnM+2uZe2j90CPprrzY0jlcCr/E5\nuLWzh3CjV21XKauXPnIQVDYn3nU3IpvDgHNCeE0BBMlkkIyAOnmqkU2/QQjwavgAolCEuI9suqWP\nwou6hxmEnPCts2ERYhBKujmbIcqm7lc2Qdhh9E2o/D2lbAZzNtMZv7IZLH2kDkjenU8xodiIURhE\ncwxCuoaQJtN5B8AOo9urTg5XNt2czYCy6bjRbXJtlX0B2Dmb4IU3DO+nEDAIxQw/f1dzbkTZNFRL\nT12HI44w+ea37bqeNvHXCzl3TEfZHKCJeNz7WgwDNuiq/JE/jO7Mq3tHXxkmX85msudd+mjG7FJE\n1W8QAtiYV9/BxlIra9YIurstJk2SbNok2LTJC+0451EjeUBOkfcojB4hwraHXXe1aG+X/PGP3o/+\nqad09t7brIhwdHWpB1TTZELCIZtCQHH/99H7i4cQfVto+vLlDY3j3GeHVRy+FO5G1zTpMwiJ0IAm\nBN3o1ZTNKGfzPQgnT8LJ28zlghK280VLGSx95C/qLqWww+z2srpHNikVPSe6swIeQSkv6u7xLOGZ\niXTdnZ9wpNRyZVNXHYREaM6m5pJNwwDNDqO/i3ImezmbXn5jujk8jG7qtoqYzal0AU2jEFfEJ573\n3OhSU0Xd/WTTmZrVHe5Gd2qWlrerzGSoNAj5Wki6yqZ9kAJF3XVFIAvEEJrwhU8cpbHSIAReVQLw\nk01H2bSveGXH2ihm3bf9YfR43HuoMQzo0SvD6LqulMPJs3xzyXhkM7V5LVtowZymOgBZkzoAz7Sz\nIafI5oZSC+++qzFlimTSJEmxKHjnHTX/QsEzw9Wqs1kOj2zWv06ECBEmBjQN9t+/xOOPq2tnfz8s\nX66xzz6VjHLKFNVqt6dnYqqbzm3TjTgu3IvsZ84g/pv/QXt9Zd3jjCSM7t5nypRNt5oKQ4XRqxmE\nvOX9HCTK2XyPIBEUxWyyWeUkEX5FrLLou/tkYuhuaSBRKEAI2fR6o4cXdZfS9x9d8xzzuqac6Pb6\nDjmMG0rZ9DuxHfgNQvG4RNu4gWJzuxuiNdErczbTwiVk5QYhAJHLumSrZCub8aKdsym80kcO2XyX\nad4PvDXDFpq9bkXOYTPC2lUqRU3IoEFI6pVkU3PD6L7SRzEVRi+gQujl7Sp1PVzZzGa9q4BrEDJU\n7mzgocI//6ITRvdyNvNGE0J450ssJnkhsYh3mBZQezUN9tzTRDR5yqZsyrjfkZCSPpoZOORD9N7/\nc8xd5wFeaNvJ2dxMK4ODwiWbAH//u2N6EoGWmvUik1Hzb4SgRogQYeLgwANN3npL4513BM8/r2NZ\ngn33rSSbXV3qmjFRQ+l+ZdNB7rTTQddJ3fqjuscZy5xNy1IP9bXaVQ6lbPrD6FHO5nsEbmjXrquY\ny4myGlfBL73czewPs7tPJobh5TQWC8iwMLrjRjdLAWe13yDk9UY3ypRNEywTEy9EHNdtN3q80vkh\ny0ofiU0bKbVOYhAli6mcTWlXVLJzSQyNyZO9fXWnbZNNcjmXsRQTtrJZGFBhdCFsg5BSNi2hsSHW\n7c4nmVTks1oY3emYlBtUpZPSaTxlMyRn0wmjuzmbIe0qC8QD+zGUG92vbPZnHbIZc4+hu7IPcasy\njJ6P2cfGvvDEYvDHpsOZwTuYqYx70TzvvALnnVdA+uoLWT6yCdBHM6mMTvHgQ933ysmms7wTRgdY\nudK7NDjpAUPlbPqRyUjS6ZH1I44QIcLWw557quvnSy9p7sPn3LlWxXJTpqj3JirZdEoD+QmY1T2V\n/DEfJfnjuxBlfoRqGLXSRzIoTJmmcO/V1boAVeuN7r+dVKvROVEQkc1hwLnpujm/WUilwpXNsKLu\nzsmSz5cpXk6f7kIxoGw6J5mnbAbzLANc1Ckm7gujK2XTQlgSS+guOVq4oERHa7gbXep6oIOQtnEj\nZvsk1xjjuNFNE0w8NjZ1qqdsBtzoKGXTUfbMpCJIidIAmutG95TN3uTUAAFMJuEeTuYPmSMD8zQM\n6fV/B7L96hgGOwgFD7yFcFMJnI5Cmk/d1WMaJQzyJAIPC/6280PlbA6Ukc1Abq4PKTyDkEM23XxW\nX86m87f/gvLJTxY56CDTK/CK3S8Yg0JcjdFHc0B1By+MPoBaxiGbXV3SRza9felX0xrSje5HJiOj\nfM0IEbZhbL+9+v2+/rrGG28I4nHpXt/9mDLF6SKkrq/332/ULAw/3nBum+UkcfCcpYiBftLf/mZd\n4zgi0kjaVQJerUQ8/4YTPaqmTgaVzWBZPAf+EHyUs/kegadsqlfHIORgaLLp5Xy6J4Wuu6WBlLIZ\nEkavUtS9WgchJ4wudE3le1rqhHXI0aI9C8ycWqCiNzqK/Po7CImNG7HagsqmW2dTeo983d2Wuztu\n/U8njJ7NuQdDS8QoiDjJUr9X+kj3lM2e1LTAcUylJF/nCu7o+EJgnq6vyl54sF9t3082yw1C/mPg\nKJta3E82Bd/j83yOG9E0WaFIl4fRw3M2nXJLdl1NW8GWZY+cDtn0K5uu6utzo3tks/JCJ1OesumY\ngApJ1YJoCy0VndwcZdMhm06Opz+M7lc2+/vVedQI2dxrL4u9956gjoEIESIMiY4OSUuLtMmmxsyZ\nVqhi5kSzHGXzhhviXHfdxMmfCQujA5jz5pM7+VOkbv0R+srXhhxnJG50twU1djqZDSeMns9X5sUH\n3OhWuBs9WGfTe/8f2o3e19fHZz/7WT75yU9y4okn8uyzzwLw8MMPc9hhh3HKKadwyimn8NRTT2FZ\nFl/60pc48cQTOeWUU3jzzTfHa5p1wXOjO2H06jmbYTl/zmuhEHSjC3+dTf+Z5pJNC6RUxDGkqLtf\n4QuE0W1lE9MMKJtYUhHXWAjZ1MqUzU0bsSZ1VJBNy/KUTRlQNivd6CKfc41N8ThktSaS5gBCSLf0\nkbBMuljHpnhX4BA4hKn8h+52YLCNUZ6yiZuz6ZJNW/U10d16l6KoHin9pY80Q7CC3fg5x1YJowcN\nQo7y7ORsapqkP2urqIZDNu2Fq5BNJ2ezJAz3BHPInSKb6rj6lU13+2XKJkAhqQikUjaDyzumnXJl\ns7tblT4CeOMN70APDDQeRj/vvAK33pobesEIESJMSAgB229vsXKlIpuzZ4f//pNJ1cxh7VpBNgt/\n+5vG2rXahDEM+UsflWPgIuVIT95z15DjjEYYHYJ5m07N7fAwun8E6foV6gmjT8SczXETW2+77Tb2\n339/TjvtNFauXMnSpUt58MEHWbFiBRdeeCFHHHGEu+zDDz9MoVDgvvvu47nnnmPZsmXcdNNN4zXV\nIVGubObzgtbWagYhf1H3oEHI7z6Tbg0fVAehgLJpK5S+8kVhYXQpfYPrXrtKl2xaFlL4VD3LrCij\n5EDqvt7opSzaurXI7m4GUT+UsJxNNEF3d0jOpmHvSy7nhtHjccmAyJAynTC6QOrKjd7BBl7S9yxz\n2gVD2Q4MQzn7nVzO3KAimKo3umMQ8lILwG4vaZ/6WrEyjG7EvF+qX5mulrMZS+qQ8+pstrZC/6C9\nLb3+MHoT/QxqGRL20M55FotJd7XykDiEK5tOi8qsnqk4ZuU5m31aCzHdUzUNQ7r5yOCF0SdiaCZC\nhAhjh+23t3jmGZ2NGwX771+sutyUKRbr1gleeklzO+KsWKGpNJ+tjHI3uh9yyhSsKd1oa9cMOc6I\nlE1fGN3vSHeUTYdLhIXRhVDmXktoIGuVPoo6CAFw2mmncdJJJwFgmiYJm4avWLGCBx54gE984hMs\nW7aMUqnEX/7yF5YsWQLAwoULWb58+XhNsy6E5WxWUzZr5WwGBEynFQ72U5Dfje6Pk9uE1O9GD3YQ\n0tzPHcKgyKYyCPnJpjteGIvwkc2WFU8iCgUK+x8QkrMpvJxNBPPnmySTkrY26U3bDaMPutuKxyEr\n0iSsQUU2hQbCK+req02qS9l0ljFljZxNyyPgEFQ2NbOAhUD4S0kZtclmeRg9nvSUzVhM0twsPYOQ\nFlQ2y93o/jB6EwMMapmAMch5DcvZdOAYhKSmufmbLtk0miuWL8/ZFC3NdHWp70sIXNLpwAmjR87y\nCBH+sbDDDhZvvaXR3y+YPbvSHOSgu1uycqXG889719EVKyaGvFYtjO7A6uhE2E02amGkpY+kcxPL\nBnM2LcsLo4cpm5qGEoqGLOoe/v5EwZhM6ac//Sl33HFH4L2rr76aBQsWsH79ei688EIuu+wyAA48\n8EAOO+wwpk+fzpVXXslPfvIT+vv7ydgKDYCu65RKJQzfEcxkEhjG1qHv7e3qNZFI0tYGxaJGS4ug\nrU3dxdvavGUTCYPZs9XZMXt2grY2yNjFz0slzQ5BpNHjcTQh1d+WCU1JdzyEYrWphEEio86oVCZF\nwv68VUVMSaUSZFoU2Ygl4hiGOnONZAx9QKDFdAZ9YfRMykCzTOJNKW9bNvpjhhtG73z+caRh0HLU\nYQzygpo7Bk1NeqD0UTKd4PjjExxxhEVra5qYrRBq9i/IKBYhZtDWlqapSZCXCRLk0YUknowjm9SP\nMU2WzbFO4pqomFcspgXec45lMqPec9JhuruTNNsmIBO1Td1OFzDRXcIds0qY6LS1e2O2tHlEsr09\nRSKhtjFpUhoh1Pdbwq4LalkkmwzohUJBJxaDlhZBvpgI7Htra5y2thiUFPmTmoa0pEs2W1riZOhX\nam9K7WMqpbmfJW1C29SkVRwT8qp+Js3N7n6UmtRJmIu3hBxD9fp/LKH/tH/l7af2Z1rGO9aTJwvW\nrfOWLxTUcevsTAXO7X8k6HrIcY8QYRQwkc+tefM8hjZ/fkxdw0JwzDGCpUs1HnxQo6NDlTx77bV4\n1eXHE1u2qNdMJnw+encXes+GIb8Dw1DHIpUyaGtrjHtolgktLZDL0WJYSHtbTU0CyxIk7HBWe3uc\ntjZ1j/crsrpAsWWp7knOddh/PW5vT6Bpquaps8xEOrfGhGwef/zxHH/88RXvv/LKK5x//vlcdNFF\n7LvvvgB8/OMfp6VFqTAf+MAH+J//+R+am5sZGBhw17MsK0A0Afr782Mx9bpQKOhAmo0b8/T2mgwM\nNKHrJXp71ZxUjpsiy6ZZors7xzPPCKZPl/T2Qj4fA5JksxIpLXp7s7QJDSuXZ0vvIO3ZHCY6W3qV\n3C76c3QC2cECuQ1b1N9Fi6z9+cCABjTR11egL1GgHSha2PNJYUmJWSxRyuYD5pj+LVlaCkXyJvT3\nBovNCuEpm/ojv6W05970oQeUTSlLmGbMVRVz+RKDm9U4vb0gZRrQKdifWwMDIDR6eweBBIOWIptC\nmhRKFmbBxKkB3mO1o2nSXtZx6zUDlvseQLGojuWWviIZINunCLJlZenrG2QSkC+pbbZJgUYwjC7z\n6pgMZL3zKVfwQh79/VlMMwFobLb3LZdT378ZS2LkB3GyBPr6LGIxjWTSYtNm9Tidl069yjy9vSXE\nQIFOQE6aRH7DIEmZQ9Mk+XyeDP30k0HXTXp7swiRAgwKhQLqp2pgGOqzwHdVhE5U2aO+viyQYUBX\npDYXywSOlzo26lj20ULv177Byf+hE4/n6O1Vx66tTW03Hlfh9I0bTUBjcHCQ3l7+IdHWlq44jhEi\njAYm8rnV3a3uLQCTJ+fo7Q1XN488UnDxxU386U+Cgw8uoWnw7LOCTZvse9hWTN/cvFndj7PZvHuN\n86O5pZ3YX1+u4ztoAgSFgnevrxeT8gVkphlj3Tr61/dStLdVKiUolWL09OSAJkolxSkAFAVqVupn\nyVRhdNQ9qbfXMRmrexFANpvHMFIUCt4y431uTZ5cGUlzMG4692uvvca5557Ltddey0EHHQSAlJJj\njjmGNWtUvsQTTzzB/Pnz2WuvvXj00UcBeO6555g7d+54TbMuOA4wp1xBuRs9zNszfXplLkYwjO7P\n2Qy60aXT+cay3PJI/jB6aLtKw2tXKQzbjW6qnE3PIGSqXJIwhdgufdRKL7EXnqWw5CCEgLweYhCS\n4fGFsDqbzrxjMchaCZLk3NJHfqf2RjoCOZvxuMpdKQ9huCkEds5mPuu40VVOKlS60QMGoVIBCy0Q\nOteNYI93ZfKq7DtrxtSXHkt6Rd1jMUkmI93SR5YWrLPphNGtSR3ktBQpsmia+g4z9DMgmyrC6IYh\n3b9Dw+hJ9QAgMxmvrJYdRi8mK3/8mqbyNlMpSSIBJ59c5PjjvYuwE0Z3SpoMx40eIUKEbR9O+SMh\nJDNnVg+jd3ZKDjtMXUMWLDCZP9/kb3/TOOmkFKedlqy63nigWukj9/NJHWg9Q4fRR9QbvVRE2qKa\n343uGFydlLcwk4+mAXJog5Cue7n9E9GNPm6R/WuvvZZCocDXv/51ADKZDDfddBNXXXUVZ599Nslk\nkh133JETTjgBXdd5/PHHOemkk5BScvXVV4/XNOuCY/513Mfl7SrLczbL4RmEhHdS6GVudP+d3V9I\n0yGkATe697G/g1BlzqaFJbwQsjDNim5ELgxV+ugQ7Q8Iy6L4/oPVnPUUmF4HIdOsn2yKXBZpx/xj\nMVVYPc2gKliraYF2kj0ymLMphDru5RcM51g6hdtzA2E5m55bHoJkUw8hm0Y8mLPpL39kHxo1jk02\nEyknZ1OR4kxG0vOOQzbD3ejWpA4Krw+QMrNuxYIM/ayXU90Ljj9n09nPsNJHGAYyHrfJpvo8F1cX\ntkIi/EkznZZV83ra29UYXV2St9+OyGaECP+o6OxUD88tLbKiqkU5TjyxxK9/HWPhQsttc/vII4Z7\nPdlaqGUQArA6OxGDA07BbETfFoynn6J46GGB5UbiRqdYQjbbzTaywdJHlhVuEHKu+UJgm3uF/X54\nnU3DqPSHTCSM25SquckXL17M4sWLK97/6le/OtZTGjYcN+/goEo+zmZFTYNQOfx1NgOdZRynebGI\n9J9FztktLdU9yFm+bHsBsqnprrKpGXYWsixXNqUazwhhEZqGTpE5+kqwoGS3OiwYaSgE62yaMvxX\n6JY+cnqj53IuSY7HVfmgdjZ5Rd19B2691VHxg0kmZUVBXZf4+dzomibVA0EddTY1s4CJHjDkC11z\nc18cV30Y2SyVKZuDg4KWFklTE7xhu9HNKm50OamDvL6eVDHrjp+hn79bGfeC4yjosZh3nlS74MtU\nGtnkKZs5R9lMVSOb3nlcDqf8UVeXBegMDASrKkSIEOEfA0LAzjtbVa8Vfhx1VIl77x3k4INN1qwR\ndHVZ7LCDxZNPGvT2wu9+Z7BqlcbnP18YcqzRxFAGIdnRCYC2oQdr+gyarvoyqdtupvf+nwc6r43I\nIFQqumXpRIBsSkql2gYhXcetJFO+fX/0T9crTcgTCRNwShMfjpt3cNDrG+0rdRj4osPJpnr1h9Gl\nW528em90IWWoGz1U2TQMd27C0N06mwE3umlWd6MbKoye1NWFQdoJzIWYl7MZi0lMU7jkVZbtrMuR\nDUfZDIbR8zg5m067Sm/99WYl2UwkarjRbfUyP2iqELpA1REFCqbzC6wMo2ulYoWyiab5+o/LQDck\n8C4CpuEom7YTPqtIdCYj2dJvb0sEi7q7hLejg4KedMPoDtncYmUqlE11EaleZxNUrc0A2YwrBbmU\nyoQu39QkA+W6/AgLo6s0hvBtR4gQ4b2LG27Icu21Q9fMFQI+8AETXYdp0yTLlw9w5plK8XjjDY2b\nb47z3e/G/d0axwW16myCijKBIpuip4fkvXcDkLny4O9HlAAAIABJREFUck8Awt9BaBiTKPrC6NnK\nou6eskngM3d7AWXTW8avSfnTvSaiMBCRzWHAecrLZr3OU40pm+q1VPLaVfrD6JSK1Xuju2F0X6ke\np1OP5eV3Sl8HIc0QdrtKC+kv6m6aiGKxoqsN4IbRU5rbR0tNLebvjW5PyxlPBHfWmVcgTG/nhyYS\nHtnUkGpdzWMz68yOih9MMll5PJ0fV0mz5zeQd9skOjmbBdP51Qp3vm4Y3bTD6LqPSWla4AnRyan0\nHRoAirbb3wmj5/OCWAxaWyVb+m1TlFambGoaVlMGa+p2FHQvZ9MJo/eTCYTP1asX8g4NowPmjjth\nzpnrznNV90LejO3ExrbtQ5dftMhk0aLwHKwwsjkRwzIRIkQYe+ywg6xa0H0obL+9usa8/rrGyy9r\nbN4sePfd8X1qDeuNHvjcVjbFhg2kbv4+5PMMXHw5xl9XkLnkArQ3XlefuzmbDR4LKRGlElazrWyW\n5WxalqjZrlLTsO/dQ+Vsev+fiGQzuoUMA46KOTgoyOXs0jsBg5D/hKk8Mf0nQsAgZDrKZjFU2cSy\nVJ5lYMUyg5BPe3eeljRfByEphJez6RSaDUvGsw1CKa2gFEt7e0VD7byJ4YXvXbIZHkZ3DUJqMvYm\nZUDZlJpwSe8gKbYUU3QbQTKUTFaGct38V8cI09/ndsipyNkMMQjpJSeMLpBCKPVYiICqWK5sOt9v\nUVNfejzlTSoeh/nzLQqWGr9UTjaB3l8+jDVzJsUfPU4KlbMpkC7ZdAilE0av1hvdj80/+yUAwi7i\nsLprAYdMf4U9W02gUpW49trqbkonjO6RTciEC6QRIkSIUBWzZqlr+GOP6W4nshUrNKZPH79i70OG\n0Ts9ZTN1560UjjiSwfMvQn/zDZJ33UbyJ3ez6Ve/Q9P2V8s1KtHZ+WzSJpsEOgg5b1WG0UHdazRN\nuilw5dsP5mzKCU02I2VzGDAM9QSSzXq5vo0om0Gy6VP/Sk7OZiGopw9R1F3zhMpA5fFi0X5S0jSE\nafdG13zKps1GwwxCwlClj5JaPjAXM2GTTRFCNodyo/u2FY/7wuhI+/FNrbCBDlcl9COdrh5GL6ZU\niELv7/Pyi6rkbPrrbGq2sqnruMdZCs39XoSAf/qnIl/4gpdn5BJcXZHNZNq7isVisNdepntMLOGl\nDTgw5++GbG6hYDjKpiRm5dGx6Kd2UfewDkLuRIXwPZeIijaq9WLffU1OOaXA4sXqXCsWReABKkKE\nCBHqQVOTyv3+9a+9e8xLL+n87//q3Hvv+GhdQxqEbGXTeOF5tJ4eCoccBkLQ992b2Pj0C1itbbSc\ncxYJoe4BDacTOWSzqVkJGr4OQs513eER5Y0zdN3ens+NHgyjB5VQtXxl1ZaJgAk4pW0D6XR1ZdP/\nRYedmKEyuBNGl1KFtsMMQlXc6M7JJyUBslko2IRN1+2+6mXtKh3pM6RdpZuzKQrIuPe4VTBUGN3U\ndI/YuGQzXNkMhtHDczalzyC0kUkUi5VPZ5ddlmfp0mByuTO04742slvcMLpDNr0wuubOV4+r93Sz\n6JFNX9zCy9mEffe1AkntzjYLolLZjMUk220nmdyl/l+yyWZYKYqS4eVsJop9AKFksx5l04F7zGVl\nSa56kcko5XPy5GDpqQgRIkRoFNtvb7F+vbowdXZarFihcdllSb7xjSEuZqOEIZXNllakrhN/7FEA\nSrvOdz+zZsyk/9/+HWPFi5y+4VsAvP+5G4jZy9YDN4IYj0EyiSjrIASKS0BlmpQbVasjjO7cJyai\nqglRGH3YSKWkTTbV/4eTswnl7SpLXg/Msru7Mt9Inxvdn7OpXi1LuIRPusqmvW5Ync2CHUqNhSmb\nKmczKfIBWc5M2GQTw8sVrRJGdzmyUZn1HFA2ZSJg+d5AB4VCZZ7gkiWVoRfnWBe1BDIWI57rcwmW\nkOqRtigN2zzlKZuxlA4FMMw8Filimu9AasEwejmceeVtspn0mcNiMbXfuy8EHgazrM6mH0Uj5SOb\nKv7dT4Z2N4zubE+6T7BDKZX+9N7yklyNwk9so7JHESJEGA5mz5b86U8wbZrFHnuY/Pa3BoODAk2T\nmObYk6Oh6myiachJHRgrXgTAnDcv8HHhQ0eR//AxfOahf+N37MGxv19Kae08Nv3+ifpkzqIdjYzF\nkKlUIGfTESGqKZvubdGSQ4bRHSOpro9vTmy9iJTNYSKdxg6jOy2svM8aIZuuKukUdXdD27HKlayh\n3ehuAXjdsEsrSScLWSUZa746m/mhw+gJLahsWrYr3dKGF0Z3VnJyNlPklJFHeMrmBlQOTT2hW7fA\nuiWQzc0k8ls8QmYrmxaa+lP3k03PIGSiq2uGT9msVULCzbMhiYlGyhdGdy4We+6tXgfyZXU2fSjG\nUm7OZrzQD5Qrmx7pdLY5FHn0p1SUl+RqFOopOZg/GiFChAiNwOmpvuuuFvPmWa6KZ1mCnp6xJ0ZD\nhdFB1doEMKfPQLa0Vnw+cMkVpKwBHuDjWELD+OtLGH95uq7tu8qmEUMmUxVudPCUzbAwuqNsIgRC\nyFCzqvN3WQXBCYWIbA4T6bRSNvtU9JPm5nBlM+yL94dUy8PooujUQKgkm8LXQWjoou4qjJ5I2O+Z\npivFO+RQOMpmaBhdU2F0qiibITmb5aWPvDB6eM5mDsWctGJePV3aK2xkUvDY1IBb+sgEmWkhWexz\nS1NhqquMiU6p5M3PQsOya57FioOVyqwQLrkKu0A5JDgnklhopFL+Irvq74V7WmymhVc3dVbdFzPm\nhdFjeU/ZDAuj1+og5Icz37CSXMNBeRmmCBEiRGgEHtk0mT9f/d3Wpq6Tq1ePnwpXS4R08jZL8+aH\nfm7uvAu/aj8ZA5NfHH4dMt1E8p4769tw0TPiymQScpVkM5tV946waiv+MHo5n/CLAI4bPSKb7zGk\nUsog5HRX8ZNNVTKyOlkJMwi5Rd1dyb3sEUfY5YtCiro7PyK/QchpVxmLAcImqlZZnU2HkYQqmyqM\nHhcFZMKvbNqtEcNyNqmWs+lXNoM5m6BqXZaH0atMqwJuB6GSQGYypIqVyqaJbiubmvv/za0zeWjS\nJ9DwEq/d0k0+ZTPsAuXmicoEJnqA0DlEceGeFnvyLN/q+1zVfQlTNgdo8hV1x32t2UHIB2e+zpPy\nSJRNtT31GuVsRogQYTiYM0cRzPnzLRYtMunosDjnHHXvWbNmPJXN6tdCp9Zmad5uVZe5dsa3OYl7\n+fNe/0zu2I+TfPABRO+mIbfvCEjSMFQt5C1b3M/8OZth11hH2RQynGyGtauMyOZ7DI5BqK/PIZvB\nzwOtpsoQJoM7Rd09ZTMkecNf1D1E2QwYhDSNQsF2o+uaMgiVh9Edl1wIE9JiyiCUIB8ow2QkDQZJ\nURCJEIPQ0Mqms8OJhHTJprvwMMhmQNlsbqaptMULNUtP2TRNXDJpoZFOS67pvpb+ZIdr4pG+YxeL\nqYtT2PfnfDUbmUQ/mQChc+bT2gqlGbN54bWM/X7lhc6MpUiSR8MiXghTNqW7rpezWft4eGSTupYf\nCg7xjepsRogQYTjYfXeLH/94kGOOKTFliuSvfx3guOPUfWz16rGnIPWE0WWHuueYu86rukx/rJ37\nOAmha2T/5SzIZUlfe83QE7AFJGIxzF12xXjhede15Fc2w4SBgBtdaBX7ENauciL2RYeIbA4byiCk\nahACngPaRqD6fxlC62w6bnQnZ7M8bikck0+lQcg5ucrD6MWibXRxDEKWBX6DUA1lk5jK2YxTQCZ8\nZNOQHMd/cEfTWXXnbAbC6La66Fc23YV9bvRq0yqH2zqyBFZzM2lzi6s0Cl/OZqkkAjmbTU2SdXIy\nNx7xAFcmlgUmLIVDNsO3GY8rJfuWlvM4hEdClU1Qbd6cgsKhYfS4WjGt5YjlvZzN8tB10I0+9IVE\n0+QYKJsT8wIWIUKEiQ0h4LDDzMA1sLNT1Y9cu3bslc2h3OjgD6NXVzZ9WVaY8+aTO/lUUrf8EP3V\nv9WegCPqxOIUF+2L1rMe7a03AT/ZrK1sOmH0WmRTlcOeuG2FI7I5TDjKZn+/Stp1C4nb0ML5V8V7\n5UXdRS03umV5XYaqtat0zjS7XaXnRpcI00Rq/tJH1cmm5hiEZFDZjMfhIY5iTXzmkEXdhbBTCXTh\nqadub/Qg2ZS+dpWNGISc0EipBDLTTLMMD6OXSsGi7qkUFAqCVycfwK8Sx9qDuS0iQvNn/Jg0SfJq\nTwfL2T00ZxMU2fTerxzDjCvZMS0GiRWUFKmUzcower2lj+zpu2Rz5DmbkbIZIUKE0YVhQFeXnDDK\nZuHQw8h99GOYO+5UdRnnXuPc5gYuuQKZTJG6/rqa2/c3Tyku2lf9+eengKAbfUiyqYmKfVABwWDz\nj4lKNqNbyDChDEIqZzOTqXxq8tzMtTsIOSebW9TdVTZDcjalZxAKC6NXtqv0irp7BqGwou6VTEjE\nDAxKxAi60f0lgSpKH1VRNoWwV/T1YXfc6N7Cwg1jO2Sznh+NP4xeTLfQgqdsVuRsuhNSymWhgF16\no+zR187ZrLX9zk7JSy9p7hx0XfWJDyqbXqmmsLEcZ39aZDFylcrmkUeW6O3N093tdYaoJyyuyKaz\n/MgUSWd/opzNCBEijCa6u+W45GzW04u9tGhf+mwiWA2egGTfsydPpnjQIcT/+FjtwV1l08DcdR4y\n3YTxl6fJf/yEgLIZFrVyyaTtRg+7j8RiKkjpdLubqGQzUjaHCVX6SOVs+s1BDmqF0asWdTd9OZvl\ntS/dWpn1GYTQfEXdXYOQejqqKOpeo/RRXOYDfdod1c2XYlkH2ZQuoS3vIORtUMPceVf6p8/lZXZR\nh6AOB3SAbCabbbJpfx9WWc6mXWfTEjrxuHTJpjttHzt26mVWQ0eHdMtexWLBkLeDXXbxK5shOZtO\nGF1k3TD6IGl3rKlTJeefX0CIRsPofoPQkIvXhLN+VPooQoQIo4nubmucDEK1e6PXi7BoZXHf/dHf\nfANtzeqq63nRSBWiKu65l0/ZVB9VUzZVu0rcFLiwfEx/i0qn/NFExASd1sSHo2z29VGFbAYTgP3w\nq52Bou6lEhS8/I7gSqpvt3vi+gYOK+qO4RV1dzsI2QahcmXTn//p2wGlbMoCVFE2K0ofVemNrml4\n5NntjV6Zs2nuvAuP/egZNjagbPrd6PlkC2mypGPqGAorWPrIcaNbmk48rh44pfT9OH1u9HrC6A78\neTL+3EbHhamWqRzDcfanyBLLDzBAGgs9lFA6KQX1h9HV3yNXNoMh/QgRIkQYDShlc+wpiKNsjgnZ\n3E/1SzeeerL6ir7SR6BUVGP5i5DNlimblat6bnRlEAoTQPxmVn9+/0RDRDaHiVRKkbuNG1UYvRyB\nEHIZwgxCTlF3r7VViBvd364yYBCyx5Aqb7G4YCGlebtVFHXHshSpc4u6q/ZHMqTOprRLH8WsPDIe\nzNlU25SVymYNsumG6g2ng5B062z6Fw5VfWvAr2zm46okQDNbvDfxFXUvc5vn8yLQwcJzo4shw+gd\nHf48zWB+pYOmJpg506q6L36yaeT66UedSGFPuM649ZBHIUYzZzO4/QgRIkQYDXR3SzZt8rrwjRXq\nMQjVA1+WlYvS7nsgUynijz1K29FHkL7m65XrFYPNU4oL90KUShgvv+Qr6h5uwtQ0ENhh+5DSR6CE\nCE/dlBPWjT5BOfDERzqtvtB16wTTpo1CGF3TlRJnO8QrczaVycchUNVyNonH6f3towCesmnnbArT\nBBHzFXV3QvYhTELTiLnKpt+N7u1fvW50N2eTGmF0e2H/j6me0K3zwyqVIBtT/dFb6ANaygxCwjUI\nSaGRSEiKRTBNXx6MfTUZyo0O0NERVC2V8ljpKNxlF4u33tJCyaa0Y9SKbA74yGb186me3EkhYPNm\ntS/lVRIaRUQ2I0SIMBaYOlVdQ9esEcyePXYEqR6DUD0INf3GYhT33ofknbchLAuxfh2DF18eXNFX\n+gjAmjlTjbNqlTvWpk0iIGA40HXQ7BJ+YW50Z1jn/vL+95tjeixHgohsDhOOYrRuncbOO5cqPq+n\n3aFaTgZWEM5jXnkHIbeouxncAGVk04d8XuUeSl1X4XezFKizSY2cTee9lngOK6BsejmbQ7vRffNz\n2IoW7I3uwFEV/UM0FkaHbEwpmxlrMzCtas6m1ByDkAjP2bQNQrWKAJcrm848ygnyHnuY/PGPeui+\n+Mmm7lM2w8IpH/xgibVr82y3XX05m7296kBOnTpaYfSJeQGLECHCtokpU9Q1Zc0ajdmzzSGWHj5G\ni2xWU0aL++5H/LFHsSZNwlj5d7TVq7CmbudbIJgaZ3arz7Q1q9G3c+Yo+OQnixVj6zrovh2oZhBy\n9u0zn6kcY6IgCqMPE46yuWWLqCjoDrVLH4URKkfxE1mVbFeubCoyJn1h9EqyaZb9XotFZSiRbW1q\n7N5eOroE5y+1cxodFTW8pyYAsWIwcznoRld/D6Vsapqvbmg1N7oYWRjdsmDQUMpmk2n3ELXC3ejS\nztkEFb5wVbuAQSi8oLuDINmUoWF0gLPPLvDb3w6EjiWT6oklKXNlymblstOmSS65pFDXBdNZpr1d\njloYPXKjR4gQYTThRATPPz/Bt74Vp7d3bLYzWmH0avf0/MdOIH/0R9nyg9sAiD3+f4HP/aWPQBWQ\nl7EY+prVbmRu111NDjmkknDrOujCcncg7Po/kfM0/YjI5jDh9t+mmkFIvTZS1B1AZO2+qUPkbPrD\n6EKocHKx7KHGaVdptasi6dqGHlJNgqUX2Sd1jTC6Q0BFdrBKzmYI2aySs6l2NEg2q4XR/es04kYv\nlQQDuk02LUU2g0XdcQ+8IpvqO3vrLY0pU8oefTWN2bMls2YNR9kMLpdKwQ47hI/jkM0Ug+jZAQZQ\nxVpHWkDdUWS7u60hlhwaUZ3NCBEijAXmzrX4+tdzTJki+da3Euy9d4annx59SmJ5XG1EqEY2zbk7\ns+WWOykufj9Waxux8lJI5Z36NA1rSjfa6lWuGPDZzxaq+jsMzQ6ja9XC6BM3T9OPiGwOE/5C3plM\ndTd62AlUtag7PmWz/O7uFHUP6SAEivxs2BDcWKGgcgidVlxab6+v/5WXsxlmEHLJb7FY5kb3XPZu\n56IGlE2HxIZ2ECK8Bmkt+MPo/Zoim6miYxDywuirVmls6nN6iGouaV65UmP69Mo6m+edV+Chhwar\nbtfvRlcGIfX/hhTAlAqjJ8miD6FsNgLnuI80hA5RB6EIESKMDYSAf/mXIg8+mOWRRwZoapJ85SuJ\nuupiNgJP2RzpQ3zwtQK6TvGA94Uom8GcTUCRzTVrOOAAk9tvz3LCCZWpeGpIiYZNNqlmEJq4tTX9\niMjmMOGE0YFQN7rz5YcRpnA3uv1HNWVTCGUgKlXmbILqxrBuXfDrLFc2AS+UrOtQo4OQUyYIgq0z\nnWmF5WzKCrLp5Xe6pY+qkk0RWKfatCqmac/BNGGLVF9EsmCTTV/O5jnnJPnlf6vJS113f/eDg4Lp\n08sefeuIVXd2BufpzLWR3EaRtnM2ZRY9O3pk09kNJwF/JPD6tI94qAgRIkQIxfz5FuedV+Cppwz+\n8IfRZU6jV/rIdz+rguIBizFeXxmsu1lW+gjAmrod2ppVGAYcdVSpKlnUddA1bwfCfAT+yNpERkQ2\nhwl/Lly4sqlew8PowRqN6s1gGL2yzmb1MDo4ZDOobKp2lTJINn21JGu50QPKqs+x4i+x0Ejpo/Iw\nuqaBqfv2UVQW3q0vZ9Nzo/eJVgBSxcqczf5+wZYBNaDUgrUsndwhOeSjq4dMJmiecebamLLp5Wzq\nWb9BaHSewLu7Ry4ROKWWIrIZIUKEscTJJxeZNs3inHOSXHBBoiJSN1yMtkGolnG0tOs8APTXV3pv\nFis79ZlTp6Ktrl4I3sGSJSYHHmCvr4V3EIpyNt/j8JeUaTRnM9RxbZTnbIa40aX0hdFrk03VndIO\no0/ykU03uTCOGFBda0INQpr3noxVutHDczaDO+vspxC4eZ9+kmzFR15nM6BsWrYymFPKpj9nE6A/\nZ6cq2G50B9OmBa9GkqEvckJ4oXT/j72hH71LNrPog6MfRq/HuT4UImUzQoQI44FEAm64Iccuu1jc\nc0+M664bHVfiaBuEao1jTZ+hln3nbfc94ZY+8t37pkxF69sC/f01t3n++QXOP8+uUFO1qHvtBiQT\nBdvAFCcmRtsgVJcb3V/UvYwgdnVZrF8v3B+WX7SULa1ejUl7Quas2WgbNwYn4Yf/PR/xdSsYhZU+\nqpqzKUPZmL/nuhwm2fSKuguyeZ0tNBPP9Tlvqhd0NE1iSvsY6FqA0IXlbNYDxyTkD2M0ktsYSwhy\nJGiytqDlszVLHzWCsQmjRzmbESJEGFu8730m99+f5aijSjzwgFFheh0ORrvOZi2yaU6bDoDuI5vl\npY8ArKlT1XJrh1Y3/Q6nSNn8B0TQIFT5ea2IbCihct3fNdzo0rJrZWoVA0+eLCkWhVs+oug2IlId\nhGR7uz2O+qWUdt45ZBI++M5qPymslbNZs4OQWzPJm7cRF5SEve2Q0kf1GIQ8NzrkcrCFFozBINlM\nJAUnnFDyOidpWoAUliub9V6VHGXTbxBqRAE0DHiD2ew08AIA/WTQNDni/JuxCKNHpY8iRIgwXjjp\npCI9PRq/+c3IWdRo9UavS4tIpbA6O9HeecdbrxSSs9mtyGY9oXSs2h2EVFH3iS8GjBvZHBwc5Kyz\nzuITn/gEp59+OhttVe25557j+OOP56STTuL6668HwLIsvvSlL3HiiSdyyimn8Oabb47XNOvG0Mpm\ndTd6raLurkGonAAKAZZElMxQctjV5XQ0Ul9poaA27Jzfbt6mHR435+7iruvPJXHf80+ySp1NZ9+G\nUjbV/gQ7CDnDFrVEYOFgB6GKaVUgUNQ9K+gTLehrVpH6wQ2Ivi1ITWPl6wN85CNFb566V2dz0iSL\npqayCWv1xVs6OyWapkIYw8nZNAxYwXx23vJnQJHNkaqaMLpudGd/toUn5wgRIrw3cMghJl1dFj/5\nycgvPKPlbq9XizCnzUB/t1LZ9F9EnaLvASNRNfik2bBtx+Nym7g+jxvZvP/++5k/fz4//vGP+fCH\nP8yNN94IwJVXXsm1117Lvffey/PPP8+KFSv47W9/S6FQ4L777mPp0qUsW7ZsvKZZN/xPE2EGoVod\nhMKUTX8YXcZilSxV09SvplQagmyq9YplLdalSzbVxktz/cpm9aLuQFmdzVqlj+pRNr25x2KVZLPR\nMLoQKkxvmoqnD+gtxB/5HZkvXkri4V+7XRfa26WrbEof2Qy0GhWNKZudnbKCjDXyozcMWM5uNJVU\njmk/mVFREIVQJiN/eabhwlM2J/6Tc4QIEd4bMAw44YQiv/mNwapVI0u2HNN2lWHbmz4jmLNZKqn7\nu++ebnV3q7HqUTZttrzddMEee1QWfj/nnAJf/GJ+6HG2MsaND5922mmYdlhz1apVdHZ20t/fT6FQ\nYKbdK3Tx4sU88cQTrF+/niVLlgCwcOFCli9fPl7TbAjpNGzZUrv0Uf1hdJ9BqNyJbq8kLDuMHlIX\ns5xs2s2B3PCuNakjMDG/sjl0GD2sN7ocMowe2q7St61LL80TvzQOG3EPSqPtKp0hTRNyOUGvMRkZ\nTyMGB9Hefsvd3qRJHtkUumcQckPo7kQr96MaTj21yO67m4HdaoSUGYZkBfPd/yuyOXJSp2kqhD7S\nhHiIDEIRIkTYOjj11CI33BDnzjtjXHJJYdjjjFbpo3pT+s3p04k/8ju1YSGUgaLsAiozzViZZrQ1\nq4bert0b/cgPWxxyaiWpXLRo5Ln544ExUTZ/+tOf8pGPfCTw74UXXkDXdT71qU9x9913c9BBB9H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U4sRuGDR1aMEWYQajSM/r3v5fjMZ4qsWSM45JA4g4NVFhzqCUCIbf4HHSGCg9dfX8njjz/K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\nERERETGNwqaIiIiImEZhU0RERERM81/WwIj6I5k/DQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x25a09a6c470>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "pylab.figure( figsize=(11,11) )\n",
-    "ax1=plt.subplot(211)     \n",
-    "ax1.set_xlabel('Frequency [Hz]')\n",
-    "ax1.set_ylabel('Amplitude response [dB]')\n",
-    "plt.grid()\n",
-    "\n",
-    "plt.semilogx(digdata[0].index.values,digdata[0].values.transpose()[1],color='blue',label='analoger Servo')\n",
-    "plt.semilogx(anadata[0].index.values,anadata[0].values.transpose()[1],color='red',label='digitaler Servo')\n",
-    "plt.axhline(y=0, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "plt.legend()\n",
-    "ax2=plt.subplot(212)\n",
-    "ax2.set_xlabel('Frequency [Hz]')\n",
-    "ax2.set_ylabel('phase [°]')\n",
-    "plt.axhline(y=-180,xmin=0,xmax=1,linewidth=1,color='red')\n",
-    "plt.semilogx(digdata[0].index.values,digdata[0].values.transpose()[2]-180,color='blue',label='analoger Servo')\n",
-    "plt.semilogx(anadata[0].index.values,anadata[0].values.transpose()[2]-180,color='red',label='digitaler Servo')\n",
-    "plt.legend()\n",
-    "plt.grid()\n",
-    "plt.suptitle('Open Loop Transferfunktionen')\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Im folgendem werden die Messungen des SR785 geplottet und die Ergebnisse des digitalen und analogen Servo verglichen."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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YMYeNG39lz57d7N+/l40bf8XDwwOt1oMNG9bz/vvv4ONTix49etGx4wOcOXOa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Ez0ej1KpQIHB0fs7e05f/4s27dv5fDhvzEajTg7u9C8eQvS0tI4e/YMqampeHtXYvTodxg06MW7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fxpMnz1K9PJ0QmY2hYeL5mE6TUYi/ZrR///7kzZuXTp06MXbsWKpXj78D8e3btzRr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\nFCx2MCtfAYnJhOzGNZRHfscWUgrDkOHIrvyHZvECtBM+Q2IwoP5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sWPJEFhqFChWmffuO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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x25a06809eb8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "pylab.figure(figsize=(11,12))\n",
-    "ax1=plt.subplot(411) \n",
-    "plt.semilogx(digdata[1].index.values[5:800],digdata[1].values.transpose()[0][5:800],color='k',label='analog')\n",
-    "plt.semilogx(anadata[1].index.values[5:800],anadata[1].values.transpose()[0][5:800],color='red',label='digital')\n",
-    "plt.ylabel('PSD (dBVpk/Sqrt(Hz))')\n",
-    "plt.legend()\n",
-    "plt.grid()\n",
-    "\n",
-    "ax2=plt.subplot(412) \n",
-    "plt.semilogx(digdata[3].index.values[5:800],digdata[3].values.transpose()[0][5:800],color='k',label='analog')\n",
-    "plt.semilogx(anadata[3].index.values[5:800],anadata[3].values.transpose()[0][5:800],color='red',label='digital')\n",
-    "plt.ylabel('PSD (dBVpk/Sqrt(Hz))')\n",
-    "plt.legend()\n",
-    "plt.grid()\n",
-    "\n",
-    "\n",
-    "ax3=plt.subplot(413) \n",
-    "plt.semilogx(digdata[5].index.values[5:800],digdata[5].values.transpose()[0][5:800],color='k',label='analog')\n",
-    "plt.semilogx(anadata[5].index.values[5:800],anadata[5].values.transpose()[0][5:800],color='red',label='digital')\n",
-    "plt.ylabel('PSD (dBVpk/Sqrt(Hz))')\n",
-    "plt.legend()\n",
-    "plt.grid()\n",
-    "ax4=plt.subplot(414) \n",
-    "plt.semilogx(digdata[7].index.values[8:800],digdata[7].values.transpose()[0][8:800],color='k',label='analog')\n",
-    "plt.semilogx(anadata[7].index.values[8:800],anadata[7].values.transpose()[0][8:800],color='red',label='digital')\n",
-    "plt.ylabel('PSD (dBVpk/Sqrt(Hz))')\n",
-    "plt.xlabel('frequency (Hz)')\n",
-    "plt.legend()\n",
-    "plt.grid()\n",
-    "plt.show()\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Beobachtung\n",
-    "Zu erkennen ist, dass für den digitalen Servo die Werte um ungefähr $6 \\textrm{ dBVpk}/\\sqrt{\\textrm{Hz}}$ was einem Faktor von 4 entspricht, jedoch sind die Peaks bei kleinen frequenzen beim digitalen Servo entweder deutlich geringer oder nicht vorhanden. Und im Bereich um 10 kHz ist das gemessene Signal bei beiden ungefähr gleich groß, jedoch ist im Bereich um die Resonanz bei 65 kHz die das gemessene Signal für den digitalen Servo wieder 6 dB größer. "
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/unordered/Measurements/FFT Measurements 20182002/ana102k4.TXT b/unordered/Measurements/FFT Measurements 20182002/ana102k4.TXT
deleted file mode 100644
index acdf7f67c285dab733e8119f18ed642cfa917074..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/ana102k4.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/FFT Measurements 20182002/ana12k8.TXT b/unordered/Measurements/FFT Measurements 20182002/ana12k8.TXT
deleted file mode 100644
index f6c0ae53452e28e363614ad5fdf63109c2514546..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/ana12k8.TXT	
+++ /dev/null
@@ -1,800 +0,0 @@
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diff --git a/unordered/Measurements/FFT Measurements 20182002/ana1k6.TXT b/unordered/Measurements/FFT Measurements 20182002/ana1k6.TXT
deleted file mode 100644
index 479c5ffe70f3f1941e0b0c3845be0869abf2038d..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/ana1k6.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/FFT Measurements 20182002/ana25k6.TXT b/unordered/Measurements/FFT Measurements 20182002/ana25k6.TXT
deleted file mode 100644
index ff20bc3a8f8de79a382a71d0be3940c3ba354f3a..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/ana25k6.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/FFT Measurements 20182002/ana3k2.TXT b/unordered/Measurements/FFT Measurements 20182002/ana3k2.TXT
deleted file mode 100644
index 911322e3c1df21aa4ff3b61e563f17268763981b..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/ana3k2.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/FFT Measurements 20182002/ana51k2.TXT b/unordered/Measurements/FFT Measurements 20182002/ana51k2.TXT
deleted file mode 100644
index 996c65d4d5b1bb85d41d37b35b578ffeefa18218..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/ana51k2.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/FFT Measurements 20182002/ana6k4.TXT b/unordered/Measurements/FFT Measurements 20182002/ana6k4.TXT
deleted file mode 100644
index d4c28ac5a740dbb7f77bf1591f9e1bfb84ac8bc7..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/ana6k4.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/FFT Measurements 20182002/dig102k4.TXT b/unordered/Measurements/FFT Measurements 20182002/dig102k4.TXT
deleted file mode 100644
index d991a4f463f21c0168cd9ca56ac1df3bd6eb84b2..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/dig102k4.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/FFT Measurements 20182002/dig12k8.TXT b/unordered/Measurements/FFT Measurements 20182002/dig12k8.TXT
deleted file mode 100644
index 9f2b01fd7660fecfa7fa412e2800f920c9a683d5..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/dig12k8.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/FFT Measurements 20182002/dig1k6.TXT b/unordered/Measurements/FFT Measurements 20182002/dig1k6.TXT
deleted file mode 100644
index e8f18795f5b1578c4c07c4dbebc28a3c7585d1c7..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/dig1k6.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/FFT Measurements 20182002/dig25k6.TXT b/unordered/Measurements/FFT Measurements 20182002/dig25k6.TXT
deleted file mode 100644
index b21b161a828d72f4afda537584852ebfe037e12f..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/dig25k6.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/FFT Measurements 20182002/dig3k2.TXT b/unordered/Measurements/FFT Measurements 20182002/dig3k2.TXT
deleted file mode 100644
index 599961d9a66f1d03f88654d85c87b92c4cfbd004..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/dig3k2.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/FFT Measurements 20182002/dig6k4.TXT b/unordered/Measurements/FFT Measurements 20182002/dig6k4.TXT
deleted file mode 100644
index 4523243bcef0d22777bb04f085da92719bed02fb..0000000000000000000000000000000000000000
--- a/unordered/Measurements/FFT Measurements 20182002/dig6k4.TXT	
+++ /dev/null
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diff --git a/unordered/Measurements/NOAUXTF5.csv b/unordered/Measurements/NOAUXTF5.csv
deleted file mode 100644
index 6a8983cdf4898b482119419bf077e596ee546d89..0000000000000000000000000000000000000000
--- a/unordered/Measurements/NOAUXTF5.csv
+++ /dev/null
@@ -1,372 +0,0 @@
-#, Frequency (Hz), Amplitude (Vpp), Gain (dB), Phase (�)
-1,20.0,0.0100,-8.80,-4.31
-2,20.4,0.0100,-15.57,-122.71
-3,20.9,0.0100,-15.17,130.51
-4,21.4,0.0100,-23.27,164.22
-5,21.9,0.0100,-1.21,-83.84
-6,22.4,0.0100,-7.80,53.63
-7,22.9,0.0100,-7.24,23.72
-8,23.4,0.0100,4.73,-58.92
-9,24.0,0.0100,-3.96,-169.11
-10,24.5,0.0100,-5.18,-3.09
-11,25.1,0.0100,-7.16,-37.89
-12,25.7,0.0100,-7.21,92.63
-13,26.3,0.0100,-16.66,-21.67
-14,26.9,0.0100,3.91,-127.91
-15,27.5,0.0100,-5.69,149.17
-16,28.2,0.0100,-17.98,-52.42
-17,28.8,0.0100,-16.23,77.71
-18,29.5,0.0100,-23.11,-23.63
-19,30.2,0.0100,-14.62,-110.82
-20,30.9,0.0100,-11.15,-67.55
-21,31.6,0.0100,-7.44,-177.34
-22,32.4,0.0100,-4.01,-40.16
-23,33.1,0.0100,6.13,130.83
-24,33.9,0.0100,-7.17,103.91
-25,34.7,0.0100,-2.38,-0.57
-26,35.5,0.0100,-12.59,-78.53
-27,36.3,0.0100,-0.89,23.52
-28,37.2,0.0100,-1.55,-0.84
-29,38.0,0.0100,-2.44,-6.55
-30,38.9,0.0100,-4.92,-29.33
-31,39.8,0.0100,2.00,-18.37
-32,40.7,0.0100,3.19,-8.77
-33,41.7,0.0100,-1.95,4.19
-34,42.7,0.0100,-2.03,-87.44
-35,43.7,0.0100,3.17,-24.67
-36,44.7,0.0100,0.99,-6.76
-37,45.7,0.0100,2.23,-20.14
-38,46.8,0.0100,1.86,-30.17
-39,47.9,0.0100,2.14,-38.76
-40,49.0,0.0100,3.99,-43.23
-41,50.1,0.0100,-0.27,-42.70
-42,51.3,0.0100,5.09,-43.67
-43,52.5,0.0100,6.25,-27.81
-44,53.7,0.0100,7.02,-31.19
-45,55.0,0.0100,1.33,-53.22
-46,56.2,0.0100,3.55,-11.43
-47,57.5,0.0100,6.56,-31.86
-48,58.9,0.0100,2.65,-14.12
-49,60.3,0.0100,3.78,-19.25
-50,61.7,0.0100,2.26,-41.66
-51,63.1,0.0100,6.17,-58.21
-52,64.6,0.0100,4.62,-35.62
-53,66.1,0.0100,3.98,-27.66
-54,67.6,0.0100,-7.58,-7.56
-55,69.2,0.0100,5.16,-46.97
-56,70.8,0.0100,2.49,-21.01
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-58,74.1,0.0100,4.83,-26.20
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-60,77.6,0.0100,1.94,-1.20
-61,79.4,0.0100,-1.24,14.67
-62,81.3,0.0100,5.66,-38.23
-63,83.2,0.0100,3.12,3.39
-64,85.1,0.0100,-0.77,35.26
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-66,89.1,0.0100,-3.15,-25.78
-67,91.2,0.0100,-2.11,-21.90
-68,93.3,0.0100,1.93,-17.08
-69,95.5,0.0100,6.51,-26.58
-70,97.7,0.0100,4.91,-37.19
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-72,102.3,0.0100,0.19,-114.69
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diff --git a/unordered/Servo_Design/Servo1.ipynb b/unordered/Servo_Design/Servo1.ipynb
deleted file mode 100644
index 320497e19194679f71394d1e95031e04cea765e4..0000000000000000000000000000000000000000
--- a/unordered/Servo_Design/Servo1.ipynb
+++ /dev/null
@@ -1,318 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import math as math\n",
-    "import scipy.signal as sig\n",
-    "import matplotlib.pyplot as plt\n",
-    "import pandas as pd\n",
-    "import pylab"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import math as math\n",
-    "import scipy.signal as sig\n",
-    "import matplotlib.pyplot as plt\n",
-    "import pandas as pd\n",
-    "import pylab\n",
-    "\n",
-    "#Servo class, which has zeros,poles and gain at f=0 as parameters. The frequencies are calculated in Hz. The class mostly uses\n",
-    "#scipy.signal methods to plot filters or change their representation, zero pole gain or polynomial.\n",
-    "class Servo:\n",
-    "    \n",
-    "    def __init__(self):\n",
-    "        self.gain=1\n",
-    "        self.zeros=np.empty(0,dtype=np.complex)\n",
-    "        self.poles=np.empty(0,dtype=np.complex)\n",
-    "        \n",
-    "        \n",
-    "    \n",
-    "    #adds zeros and poles to the transferfunction and reduce the fractions. The gain is multiplied with the new gain.\n",
-    "    #z array with the zeros\n",
-    "    #p array with the poles\n",
-    "    #gain mit dem Multipliziert werden soll\n",
-    "    def add(self,z,p,k=1):\n",
-    "        self.gain=self.gain*k\n",
-    "        self.zeros=np.append(self.zeros,z)\n",
-    "        self.poles=np.append(self.poles,p)\n",
-    "        self.reduce_frac()\n",
-    "        return self.get_zpk()\n",
-    "    \n",
-    "    #reduce the fraction of the transfer function\n",
-    "    def reduce_frac(self):\n",
-    "        deletez=np.empty(0,dtype= int)\n",
-    "        for i, z in enumerate(self.zeros):\n",
-    "            for j, p in enumerate(self.poles):\n",
-    "                if (self.poles[j]==self.zeros[i]):\n",
-    "                    deletez=np.append(deletez,i)\n",
-    "                    self.poles=np.delete(self.poles,j)\n",
-    "                    break\n",
-    "                elif((np.abs(self.poles[j]-self.zeros[i])/(np.abs(self.poles[j])+np.abs(self.zeros[i])))<1e-4):\n",
-    "                    deletez=np.append(deletez,i)\n",
-    "                    self.poles=np.delete(self.poles,j)\n",
-    "                    break\n",
-    "        self.zeros=np.delete(self.zeros,deletez)\n",
-    "   \n",
-    "    #sets the gain  at f=0 to k, if\n",
-    "    def set_gain(self,k):\n",
-    "        self.gain= k\n",
-    "        \n",
-    "    #multiplies the gain with the value of k    \n",
-    "    def add_gain(self,k):\n",
-    "        self.gain= self.gain*k\n",
-    "        \n",
-    "    def get_gain(self):\n",
-    "        return self.gain\n",
-    "    \n",
-    "    def get_poles(self):\n",
-    "        return self.zeros\n",
-    "    \n",
-    "    def get_zeros(self):\n",
-    "        return self.zeros\n",
-    "    \n",
-    "    def get_zpk(self):\n",
-    "        return [self.zeros,self.poles,self.gain*self.calculate_gain_mp()]\n",
-    "    \n",
-    "    #returns the zpk representation which is used in scipy.signal\n",
-    "    def get_zpk_sig(self):\n",
-    "        return[self.zeros,self.poles,self.gain*self.gain_mp()]\n",
-    "    \n",
-    "    #adds a first order highpass filter with corner frequency fc\n",
-    "    def order1highpass(self,fc):\n",
-    "        self.add(0,fc,1/fc)\n",
-    "        return False\n",
-    "    \n",
-    "    #adds a 2nd Order Lowpass filter with cutoff frequency fc and Quality factor Q\n",
-    "    def order2lowpass(self,fc,Q):\n",
-    "        poles=[-fc/(2*Q)+((fc/(2*Q))**2-fc**2)**0.5,-fc/(2*Q)-((fc/(2*Q))**2-fc**2)**0.5]\n",
-    "        self.add([],poles,1)\n",
-    "    \n",
-    "    #adds an integrator with the corner frequency fc and stop frequency fstop\n",
-    "    def integrator(self,fc, fstop=None ):\n",
-    "        if (fstop is not None):\n",
-    "            self.add(-fc,-fstop,1)\n",
-    "        else:\n",
-    "            self.add(-fc,-0.001*fc,1)\n",
-    "    \n",
-    "    #adds a differentiator with the cuffot frequency fc and stop frequency fstop\n",
-    "    def differentiator(self,fc,fstop=None):\n",
-    "        if(fstop is not None):\n",
-    "            self.add(-fstop,-fc,1)\n",
-    "        else:\n",
-    "            self.add(-0.001*fc,-fc,1)\n",
-    "    \n",
-    "    #adds a standard notch filter at fc with the quality factor Q\n",
-    "    #fc is the stop frequency\n",
-    "    #Q is the quality factor\n",
-    "    def notch(self,fc,Q):\n",
-    "        poles=[-fc/(2*Q)+((fc/(2*Q))**2-fc**2)**0.5,-fc/(2*Q)-((fc/(2*Q))**2-fc**2)**0.5]\n",
-    "        self.add([fc*1j,-fc*1j],poles)\n",
-    "    \n",
-    "    \n",
-    "    #function mostly used for quick plotting of the transfer function, added for testing purpose\n",
-    "    def plot_servo(self,freq):\n",
-    "        pylab.figure( figsize=(11,11) )\n",
-    "        tup1=[self.zeros,self.poles,self.gain*self.calculate_gain_mp()]\n",
-    "        a,g,p=sig.bode(tup1,w=freq)\n",
-    "        ax1=plt.subplot(311)     \n",
-    "        ax1.set_xlabel('Frequency [Hz]')\n",
-    "        ax1.set_ylabel('Amplitude response [dB]')\n",
-    "        plt.grid()\n",
-    "        plt.semilogx(freq,g)\n",
-    "        plt.axhline(y=0, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "        ax2=plt.subplot(312)\n",
-    "        ax2.set_xlabel('Frequency [Hz]')\n",
-    "        ax2.set_ylabel('phase [°]')\n",
-    "        plt.semilogx(freq,p)\n",
-    "        plt.grid()\n",
-    "        plt.suptitle('Servo Transferfunction')\n",
-    "        plt.savefig('Servo.png')\n",
-    "        plt.show()\n",
-    "        plt.close(1)\n",
-    "\n",
-    "    #calculates the gain multiplier for the use with scipy.signal\n",
-    "    def calculate_gain_mp(self):\n",
-    "        gainmp=1\n",
-    "        for i in range(0,self.zeros.size):\n",
-    "            if (self.zeros[i]!=0):\n",
-    "                gainmp= gainmp/np.absolute(self.zeros[i])\n",
-    "        for i in range(0,self.poles.size):\n",
-    "            if(self.poles[i]!=0):\n",
-    "                gainmp=gainmp*np.absolute(self.poles[i])\n",
-    "        return gainmp\n",
-    "        \n",
-    "    #applies the servo function to a measured/calculated transfer function\n",
-    "    #frequencies at which the gain and phase was measured\n",
-    "    #measured gain\n",
-    "    #measured phase\n",
-    "    def apply_servo(self,freq,gain,phase):\n",
-    "        tup1 = [self.zeros,self.poles,self.gain*self.calculate_gain_mp()]\n",
-    "        f,g,p=sig.bode(tup1, w=freq)\n",
-    "        phase_2=np.add(phase,p)\n",
-    "        gain_2=np.add(gain,g)\n",
-    "        return freq,gain_2,phase_2    \n",
-    "    \n",
-    "    #uses scipy.sig to return the polynomial transferfunction\n",
-    "    def polynomial_tf(self):\n",
-    "        return sig.zpk2tf(self.zeros,self.poles,self.gain*self.calculate_gain_mp())\n",
-    "    \n",
-    "    #uses scipy.sig to return the digital representation fo the filter\n",
-    "    #fs is the nyquist frequency\n",
-    "    def tf2digital(self,fs):\n",
-    "        a,b = self.polynomial_tf()\n",
-    "        return sig.bilinear(a,b,fs)\n",
-    "    \n",
-    "    #uses scipy.sig to return an array of second order sections\n",
-    "    #fs is the nyquist frequency\n",
-    "    def sos(self,fs):\n",
-    "        a,b= self.tf2digital(fs)\n",
-    "        return sig.tf2sos(a,b)\n",
-    "    \n",
-    "    def calculate_gmargin(self,freq,gain,phase):\n",
-    "        freq,gain,phase= self.apply_servo(freq,gain,phase)\n",
-    "        gmargin=False\n",
-    "        for i in range(100,freq.size):\n",
-    "            if(phase[i]<=-180):\n",
-    "                gmargin=gain[i-1]\n",
-    "                #print(freq[i-1])\n",
-    "                break\n",
-    "\n",
-    "        return gmargin,(freq[i-1]),i\n",
-    "    \n",
-    "    def calculate_pmargin(self,freq,gain,phase):\n",
-    "        freq,gain,phase= self.apply_servo(freq,gain,phase)\n",
-    "        pmargin=False\n",
-    "        for i in range(0,freq.size):\n",
-    "            if (gain[i]<=0):\n",
-    "                pmargin=180+phase[i-1]\n",
-    "                #print(freq[i-1])\n",
-    "                break\n",
-    "        \n",
-    "        return pmargin,freq[i-1],i"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(196.36686876556266, 0.80308572213915119, 191)\n",
-      "(44.31201179651552, 6025.6000000000004, 579)\n"
-     ]
-    }
-   ],
-   "source": [
-    "df = pd.read_csv('tf2.csv',';')\n",
-    "df=df.values\n",
-    "df=np.transpose(df)\n",
-    "Servo1=Servo()\n",
-    "Servo1.add_gain(20000000*400)\n",
-    "Servo1.integrator(2000,0.1)\n",
-    "Servo1.integrator(8000+(9)*1600,0.5)\n",
-    "Servo1.integrator(400,1)\n",
-    "Servo1.notch(65000.3,5)\n",
-    "Servo1.order2lowpass(15000,0.707)\n",
-    "\n",
-    "dfg=np.mean(df[3][np.arange(100,150)])\n",
-    "dfa=[np.logspace(-2,2,400),[],np.zeros(400)]\n",
-    "for i in range(0,400):\n",
-    "    dfa[1]=np.append(dfa[1],dfg)\n",
-    "print(Servo1.calculate_gmargin(np.append(dfa[0],df[1]),np.append(dfa[1],df[3]),np.append(dfa[2],df[4])))\n",
-    "print(Servo1.calculate_pmargin(np.append(dfa[0],df[1]),np.append(dfa[1],df[3]),np.append(dfa[2],df[4])))\n",
-    "count=np.arange(0,800)\n",
-    "f,g,p = Servo1.apply_servo(np.append(dfa[0],df[1])[count],np.append(dfa[1],df[3])[count],np.append(dfa[2],df[4])[count])\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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evZXZq7cxZ/U2Zq/eyvOz1x7e3q00h9OrChhY1Y7Tq9rRvTRHswqIiIjEmApUOaWU5KZT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\nqJIkSWoVE1RJkiS1igmqJEmSWuVf6s/ThgAmHYYAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xf0cd4a8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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UZSSEOlQREQmg5FRE+r3izES+PW0E/+/8Yby8chsz5m3izxVr+XPFWs4YmsX0\niQM5f1QOMVFqTRURCTUlpyJywoiOjODC0blcODqXzbv28sj8Sv69oJKbHlxEZmIMV04o5JqJRQwe\nkBTqUEVETlhKTkXkhFSQFs//O38YXzm3lNdWb+eheZu4+431/O21dUwelMG1kwYybUwucdGRoQ5V\nROSEEtLk1Mz+AVwKbHPOjfHnZQAPAyXABuBq51ydeXfWvgO4GNgDXO+cWxSKuEWk/4iMMKaOyGbq\niGy2NTTz74VVPDy/kq89vITUmdF8+OQCrp00kOG5yaEOVUTkhBDqAVb/BKYdNO9mYLZzrhSY7U8D\nXASU+q8bgTt7KUYROUFkp8Rx09ShVHyznAdumMyZpVk88NZGLvz9a3z4L2/y8PxN7N7XGuowRUT6\ntZC2nDrnXjOzkoNmXw6U+5//BVQA3/Hn3+ucc8BcM0szszzn3JbeiVZEThQREcbpQ7M4fWgWtbtb\neHxRFQ/N28R3HlvKT55azofGFzB9YhFjC1P1uFQRkePMvFwvhAF4yenTAd36u5xzaQHL65xz6Wb2\nNPAL59wb/vzZwHeccwsOKu9GvJZVcnJyJsyYMaN3DgRoamoiKUkXUhxM9RKc6iW4cK0X5xxrd7VT\nUdnK/JpWWtqhKDmCswujODU/isTonk1Sw7VeQk31cijVSXCql+B6s16mTp260DlXdqT1+tIFUcF+\n8x+SWTvn7gLuAigrK3Pl5eU9HNb7Kioq6M399RWql+BUL8GFc71MBT4LNDTv58kl1cyYt4n7VzTw\n7zWtXHxSHtMnFjFpUEaPtKaGc72EkurlUKqT4FQvwYVjvYRjcrq1o7vezPKAbf78KqAoYL1CoLrX\noxORE15KXDTXTSnmuinFvLu5nofmbWLmkmqeWLyZwVmJXDOxiI9OKCQrKTbUoYqI9DlHvCDKzLLN\n7MNmdpOZfdrMJplZT15INRP4pP/5k8CTAfP/xzxTgHqNNxWRUBtTkMrPPnwSb333XH515VgyEmP4\n+bMrmXL7bL5w/0JeXb2dtvbQDp8SEelLumw5NbOpeFfKZwCL8Vow44ArgCFm9ijwG+dcw7Hu3Mwe\nwrv4KcvMqoAfAr8AHjGzzwCbgKv81Wfh3UZqLd6tpD51rPsVETneEmKiuKqsiKvKiliztZGH51fy\n2KIqnn23hoK0eK4uK+LqiYXkpcaHOlQRkbB2uG79i4HPOuc2HbzAzKLw7k96PvDYse7cOXdtF4vO\nDbKuA2461n2JiPSW0pxkvnfpKL41bTgvLt/KjHmV/O6l1dwxezVnDxvA9EkDOWdENtGRob6bn4hI\n+OkyOXXOfeswy1qB//RIRCIzggrtAAAgAElEQVQi/URsVCSXjs3n0rH5VNbu4eH5lfx7YSWfu28h\nA5JjuXJCIdMnFlGcmRjqUEVEwsYRL4gys0zgR8DpeFfHvwH8xDm3s2dDExHpP4oyEvjmhcP52nml\nVKzazoz5m/jbq+9xZ8V7nDo4k+mTirhwtB6XKiLSnav1ZwCvAR/1pz+O93jR83oqKBGR/ioqMoLz\nRuVw3qgcauqbeXRhJQ8vqOSrM5aQluA9LnX6RD0uVUROXN1JTjOccz8NmL7NzK7oqYBERE4Uualx\nfOmcUr5YPpT/vreTGfM38cDcTdzz5gZOHpjGtRMHcsnYPBJjw/GufyIiPaM7v/FeMbPpwCP+9JXA\nMz0XkojIiSUiwjijNIszSt9/XOqM+ZV8+7F3+MnTy7lsXD4xTftZ+/o6bjhzcKjDFRHpUYe7lVQj\n3hhTA74O3OcvigSa8G77JCIix1FGYgw3nDmYz5wxiEWb6rjnzQ08NM+/acryFVx8Uh75abodlYj0\nX13ex8Q5l+ycS/HfI5xz0f4rwjmX0ptBioicaMyMCcUZ/GH6yQfM/59/zOP+uRvx7q4H+1rbOpe9\nu7meB9865O5/IiJ9SpfJqZmdcrhXbwYpInKiiogwfvnRkwD49rThxEdH8r3/vMugW2bx7wWVTPjp\nS/zt1fcAuPpvc7j1iaVsqd/LIwsqeertapxzTL9rDk+9rac9i0jfcLgxp7/x3+OAMuBtvC7+scBb\nwBk9G5qIiABcM3Eg6Q3vcUH5UD5/1hB+99Jq/vjyWr716DsA/PzZlcxesY09LV4r6swl1fz82ZUA\nTCzJYO66Wuauq+WycfkhOwYRke46XLf+VOfcVGAjcIpzrsw5NwE4Ge8RoiIi0ktiIg3wWlK/ccFw\n7rl+IkmxUYwrSmPyoAzmbajtXLcjMQX47YurOj+/vmZ77wUsInKMunO1/gjn3NKOCefcu2Y2vgdj\nEhGRI5g6IpslPzgfMyMywthSv5c7K95jTEEq3/ZbVAEeWVDV+fm6v89j5U+n6Ub/IhLWupOcrjCz\nu4H78a7e/wSwokejEhGRI4qKfL/zKy81np9cPgbnHPHRkaze2sgfXz60k+v+uRsxMwrS4li+pZFP\nnVbC21W7OHvYAMysN8MXEQmqO8npp4AvAF/1p18D7uyxiERE5JiZGZeNy8c5R3ZKHA/M3UiEGY98\n/lRO+cmL3PbMgW0Lf5i9BoAZN05hyuBMVmxpICYqgiEDkkIRvojIkZNT51wz8Dv/JSIifYCZcd2U\nYj4+aSBm3vTtHzmJJ5dsZnvjPkblpfD44s2d689dt5OTB6Zx0R2vA/D0l89gTEEqzfvbNAxARHrV\n4W7C/xRwF/Ccc27/QcsGA9cDG5xz/+iJwMxsA9AItAGtzrkyM8sAHgZKgA3A1c65up7Yv4hIfxAR\n8X5X/ZUTCrlyQmHndEF6PNsb97F0cz1z1+2kKD2hc9kvn1vJpJIMfvPiap796pmMzNPtrUWkdxyu\n5fSzeE+G+r2Z1QLb8W4rNQjvav0/Oeee7OH4pjrndgRM3wzMds79wsxu9qe/08MxiIj0S9+4YDgA\nv31hFX94eS1z19UyOj+F6MgIXl+zg9fXeL9+L7rjdb514XBumjo0lOGKyAnicLeSqnHOfds5NwS4\nCvgpXrI62jl3fi8kpsFcDvzL//wv4IoQxCAi0q/cdM5QPjQunwnF6fz+mvGcVJB6yDp3v74uBJGJ\nyImoOxdE4ZzbgNeN3psc8IKZOeBvzrm7gBzn3BY/pi1mlt3LMYmI9DuxUZH84dr3H5P6rWnDOaM0\nixeWbeWSsbm8tnoH//zvBkpufoZxhamcPWwApw/NIjMphtZ2x4hcdfmLyPFjHc9nDjdmlu+cq/YT\n0BeBLwMznXNpAevUOefSD9ruRuBGgJycnAkzZszotZibmppIStIVrgdTvQSneglO9RJcKOulZnc7\nt7/VTHaCsXZX+yHLf3ZGPHGRkBnfZWdcj9H35VCqk+BUL8H1Zr1MnTp1oXOu7EjrhW1yGsjMfgQ0\n4Y2DLfdbTfOACufc8K62KysrcwsWLOilKKGiooLy8vJe219foXoJTvUSnOoluHCplzVbG7lj9hqe\nWbqF+OjIzkemApwzIpvvXzqKQVmJvRZPuNRLOFGdBKd6Ca4368XMupWcdqtbv7eZWSIQ4Zxr9D9f\nAPwEmAl8EviF/x6Kca8iIies0pxk/vSxU/iTP/3u5noenLeJmUuqeXnlNpZurqesOJ2oyAhuuWgE\n+WnxIY1XRPqeIyanZnY68COg2F/fAOecG9yDceUAT/hPK4kCHnTOPWdm84FHzOwzwCa8C7VERCRE\nxhSkcvuHT+K2y8cwf0Mtt89aweqtjdTUN/PKym0UZyYwZEAS08bkMnlQBplJsaEOWUTCXHdaTv8O\n/D9gId49R3ucc24dMC7I/J3Aub0Rg4iIdF9EhDF5cCZPfukMwOv+//mzK2lqbmXm29XMfLua6Ehj\nUFYiN00dymVj8w+4B6uISIfuJKf1zrlnezwSERHpN0pzkvnH9RMBWLChlu2N+3h88WZeXL6Vr85Y\nwncee4eSzES+fE4pUwarRVVE3ted5PQVM/sV8Diwr2Omc25Rj0UlIiL9RllJBgAXnZTHnpZWnnq7\nmrXbmnj6nS3c9KD3p6QgLZ5Lx+XxsUkDKUpPUKuqyAmsO8npZP898OoqB5xz/MMREZH+LCEmimsm\nDgTgS+eUMm99LRt27Gb+hlr+9uo6/vbqOoozEzhjaBZjClIZnZ/CqLwUoiJ7/zZVIhIaR0xOnXNT\neyMQERE5saTGR3P+qBwAPnvWYFZsaWDRpjrum7ORmW9X88BbmwDIS41jQnE6XzuvlKHZyaEMWUR6\nQZfJqZl9wjl3v5l9Pdhy59xvey4sERE50YzMS2FkXgofn1yMc46XV25jxZYG3qmq57XV23l+WQ3Z\nyXGcPXwA543MZnR+Kn3hXt0icnQO13LacRdl/TdVRER6lZlx7sgczh3ptaxuqd/L3a+vZ+22Jh6e\nX8mDfqtqSoxx3vYljCtMY2JJBiNykzVeVaSP6zI5dc79zX//ce+FIyIicqi81Hi+f+koABqb97Ni\nSyPvbq7nxYWreHZpDY8v2gxARmIMk0oyGFeUxqlDMhmek0x8TGQoQxeRo9Sdm/DHAZ8BRgNxHfOd\nc5/uwbhERESCSo6LZtKgDCYNymBw60bOPOtstjY0M+e9nbz53g4WbqzjuWU1AMRERTCpJINTh2Qy\nviiNkwpTSYmLDvERiMjhdOdq/fuAlcCFeI8Q/TiwoieDEhER6a7ICCM/LZ6PTijkoxMKAdjW0Myi\nTXUs2FDHa2u286vnV3WuP3hAIuML0xhXlMb4ojRG5qUQE6W7AYiEi+4kp0Odc1eZ2eXOuX+Z2YPA\n8z0dmIiIyLHKTolj2pg8po3JA6B+z37e2byLtyt3saSyntfX7uDxxd5QgKgIY/CARAZnJXHFyfmc\nOzKHaN26SiRkupOc7vffd5nZGKAGKOmxiERERI6z1IRoziwdwJmlAwBwzrGlvpnFm3axrLqeVTWN\nLKncxXPLaoiONIYMSGJ4bjLDcpIZmZfMpEGZJMV250+miHxQ3flJu8vM0oHvAzOBJOAHPRqViIhI\nDzLzhgLkp8VzyVivdbWltZ3nltWwvLqBVTUNLNhQx5NLqgGIjjSG5yYzIjeFER3veclk6bGrIsdd\nd27Cf7f/8VVgcM+GIyIiEhoxURF8aFw+HxqX3zmvsXk/S6vqeW3NDpZV11OxajuPLqzqXJ6VFNPZ\nwjoiN5nhuSkMy0kiIUatrCLHqjtX6we7CX89sNA5t+T4hyQiIhIekuOiOW1oFqcNzeqct6NpH6tq\nGlmxpYHVWxtZVdPIjHmV7N3fBoAZDMxIYHhAwjo8N5mSzAQ9hlWkG7rzX7sy//WUP30JMB/4vJn9\n2zn3vz0VXDBmNg24A4gE7nbO/aI39y8iIie2rKRYsobGcnpAwtre7qis28PKGi9ZXVXTyMqaBl5a\nsZV2/yFWsVERlOYkMTwnxU9aveR1QHIsZnpwgEiH7iSnmcApzrkmADP7IfAocBawEOi15NTMIoE/\nA+cDVcB8M5vpnFveWzGIiIgcLCLCKM5MpDgzkQtH53bOb97fxtptTX7S2sDKmkZeX7Odxxa9PzQg\nPSGaEbkpjM5P4bShmZwxdIBubSUntO4kpwOBloDp/UCxc26vme3rmbC6NAlY65xbB2BmM4DLASWn\nIiISduKiIxlTkMqYgtQD5tfubulsXfXeG7l37kbufmM9uSlx/OCyUZw9bACJukOAnIC6861/EJhr\nZk/605cBD5lZIr2fFBYAlQHTVcDkXo5BRETkA8lIjOHUIZmcOiSzc17z/jbmvLeTnz+7gi8+sAiA\nnJRY4qMjiY+JIj0hmpF5KSTHRdHS2k5cdCS5KXGcVJjKsJxktjfuI0INrtIPdOdq/Z+a2SzgDMCA\nzzvnFviLP96TwQURbFCOO2AFsxuBGwOmezomERGRHrEx1AGIhEC3+guccwvxxpeGWhVQFDBdCFQH\nruCcuwu4C6CsrMwtWLCA3lJRUUF5eXmv7a+vUL0Ep3oJTvUSnOoluBOtXva1tuGcN1xgX2sbW3Y1\ns6RyF8u3NFCQFs+rq7fz8sptABSmx7Olvpm2dndIOYOzEvn2tOGcWTqAV1ZtY9323eSmxHH5yfnE\nRkX29mH1ihPtu9JdvVkv3W0w7GuDWeYDpWY2CNgMTAc+FtqQREREekdg4hgbFUlJViIlWYlccXIB\nAB+bPJA/P/Yy5aeWMa4wler6Zl5euY1tDc3ERkUQHxPFtoZmHllQyefvX3RI+X+pWMvFJ+UxviiN\n0pxkBmUl9tqxiXToU8mpc67VzL4EPI93K6l/OOeWhTgsERGRsBAdGcH47CjGF6UBUJAWz3VTig9Z\n7/NnD+G+uRv5w+w1XDOxiJsvGsGCjXX873OruOu1dbT6ra1nlmbxlXNLKc5IYN6GWpZW1fPlc0v1\nKFfpUX3u2+WcmwXMCnUcIiIifVV6YgxfObeUG88aTFy01xo7dXg2U4dn07y/jaWb63ljzQ7umL2G\n2t0t7N7XyoadewD422vrGOtfhPWRkwtYXLmL1PhoLhqTS6Ye5yrHQZ9LTkVEROT46EhMD543sSSD\niSUZtLS1c2fFewB86vQSoiMjWLJpF1GRxtPvVB/wKNfbZ63gs2cO5pKxeZRmJ+mCZDlmSk5FREQk\nqEmDMriz4j0yEmP44WWjD1j25todfPzut7hqQiERZjy8oJI7Zq/hjtlrSIjxEtwrJxQytjCVgRkJ\nSlal25ScioiISFCnDs7kkrF5fPmcoYcsO31oFgu/d15nV/7NF43AATOXbGb9jt08t6yGLz+0GPDG\nvk4elMGA5Fjv8a/JMWQmxpKRGENjcysJMZGMLUxVAiuAklMRERHpQlx0JH/+2CldLg8cY5qeGAPA\n9acPAuD7l47i3eoGllXX88rKbcxdt5MdTS20tLUHLeuTpxbzvUtHEWlGRISS1BOZklMRERE57qIi\nIxhflMb4ojQ+Ptm7Y4BzjsZ9rexo3MeOphZqd7eQHBfFY4uq+Necjdw3dyMp8dEkxUbhnPeErDEF\nqVwzsYjR+alH2KP0F0pORUREpFeYGSlx0aTERTN4wPvzy0rSGZWXQlXdXpr3t3mtqw6q6/fy7wVV\n3DtnI9+ZNoIvlA8JXfDSa5ScioiISEjFRkVyw5mDgy6r37ufW59Yyi+fW8kpA9OYPDizc1lrWzvz\n1tdS09BMfHQkAzMTGJGbQqSGBfRpSk5FREQkbKXGR/PrK8fxxpodPL5oc2dy6pzjk/fM4821Ow9Y\nf9KgDPJT47h8fAFTR2SHImT5gJScioiISFiLj4kkLzWOnbtbOuc1NLfy5tqdXH9aCZ88rYS9LW3c\neN8C5q2vBWDW0hpe+vrZDMxMCFXYcowiQh2AiIiIyJFkJMawa8/7yWmdn6iOLUxlUFYio/JTuHB0\nLgAJMZFERxrfe/JdnHOd26ze2sgfZ69h08497O/irgESekpORUREJOylJ8RQG5CcdnzuuIUVwOAB\niQCUZifxzQuH89rq7TyxeDMATS2OT90zn9+8uJqzfvUK987Z2IvRy9FQcioiIiJhLz0xml179ndO\n1zZ5yWlGwvvJaUFaPAAREcb/nFrChOJ0bn58Ka+u3s4/l+1je+M+Jg3KAGDOezt6MXo5GkpORURE\nJOxlJHjd+u3tXjd9R8tpRkDL6clF6WQkxvCtC4YTGWHcdd0ECtLiueWxd1i4tY3PnjWIh2+cwvmj\ncli3Y3dIjkOOTMmpiIiIhL20hBjaHTQ0e62nHWNOA5PT1IRoFn3/fE4bmgV4T7D6xJRiquubccCH\nTy7AzBidn8L6Hbup3/t+S2xNffMB41MldMIuOTWzH5nZZjNb4r8uDlh2i5mtNbNVZnZhKOMUERGR\n3tORhNb6SWntnhZioiJIiIk87HZXlxXysckDuXRwNEOzkwE4a9gADJh420uc85sKZi3dwpSfz+bR\nhVU9egzSPWGXnPp+55wb779mAZjZKGA6MBqYBvzFzA7/jRQREZF+IS0hGoC6Pe+3nGYkxGB2+Bvu\nJ8dFc/uHT+LKYe+3sJ4yMJ1fXTmOlrZ21m3fzXefWArAyyu3HXN8+1rbeOCtjfz11fc6W3Xl2PSl\n+5xeDsxwzu0D1pvZWmASMCe0YYmIiEhP62g57Uj8qnc1H3Cl/tH6yCkF1O1p4bZnVnQmvKtqGo+p\nrP1t7Xzx/kXM9pPbJ5dU8/gXTiP+CK26Ely4tpx+yczeMbN/mFm6P68AqAxYp8qfJyIiIv1cun9V\nft2eFt7dXM8ba3dw7gd4ApSZccOZg4mO9FpeC9LiWbdjN2u3NR11WT95ajmzV27jJ5eP5u7/KWPF\nlgbum7vhmGM70VkoBv+a2UtAbpBF3wXmAjsAB/wUyHPOfdrM/gzMcc7d75fxd2CWc+6xg8q+EbgR\nICcnZ8KMGTN67kAO0tTURFJSUq/tr69QvQSneglO9RKc6iU41cuh+mud7G11fOGlPVwzPIYogwdW\ntvD78njS4rrXztZVvVz/nHfV/tdOieVPi/dRXhTFJ0bFdjuuphbH117ZwxkFUVw/xtvu1/Ob2djY\nxq/PSiA26vDDDkKtN78vU6dOXeicKzvSeiHp1nfOnded9czs/4Cn/ckqoChgcSFQHaTsu4C7AMrK\nylx5efkHivVoVFRU0Jv76ytUL8GpXoJTvQSneglO9XKo/lonzjmiX3mWjLwikuOiYOUqpp17NnHR\n3es676peTl7+Jos37eKLHzmHDe1vM3vFNu74zBkkxnadIu1va+edqnpOGZjGX19dR6tbyTc/PIUx\nBakAJA+q5aN3zmFTTDGfPWvwMR1vbwnH70vYdeubWV7A5IeBd/3PM4HpZhZrZoOAUmBeb8cnIiIi\nvc/MSE+IoW53C80tbZhBbNQHT2PuuX4iz33tTGKiIrju1GIa97XynyWbD1mvsXk/d7++jvU7dnPN\n3+bw0Tv/y1V/ncOvnl/JeSOzGZ2f0rnuhOIMJpVk8OC8Tbo91TEIxwui/tfMxuN1628APgfgnFtm\nZo8Ay4FW4CbnXFvIohQREZFelZ4QQ92eFpLjooiPjjzilfrdkZYQQ5o/nvWUgemMykvhvjkb+dik\ngZgZbe2Oe95czz1vbmDzrr3c9swKAKIjjQUb6zizNIs7pp98SCxXlhXy7UffYdGmXUwoTj9kv9K1\nsEtOnXPXHWbZz4Cf9WI4IiIiEibSE6Op272fAcltxHezO/9omBkfmzyQ7/3nXVZvbWJ4bjIvLKvp\nTEhvvXgEr6/Zwaj8FG65aCT1e/eTEhcVNEmeNiaX7z6xlBeW1zChOJ1HF1bR1Lyf608fdFxibd7f\nxoaduxmRm3LklfuYsEtORURERIJJT4hh7bYm9ra0d3us6dE6w3+61MKNdSzcWMetTywlLSGaOTef\nS3xMJDeeNaRz3dT46C7LSYmLZsrgTF5cvpVbLhrJN//9NgAfn1JMdOQHH47wxQcW8fLKbSz90QUk\nx3UdR18UdmNORURERIJJT/S69Zv3t/XYPUSLMxPISIxh0aY6Hl/kPTHqmxcMP6b9nVU6gHXbd7Ot\noblz3pLKXR84Rudc5wMDNu7c84HLCzdKTkVERKRPyEyMoW7Pfhr3tfZItz54Xftlxem8uHwrCzbW\nccMZg/jElOJjKuukQu/q/WeWbumc99KKrR84xtVb378X66ZaJaciIiIiIVGcmUhbu2N1TWOPJacA\nN5w5mPq93lOjykoyjrmc0fkpmMHji7yr/9MTorlvzkZqP+DjTd/dXN/5WS2nIiIiIiFSmu3dLL6m\noZm4Hnw06KRBGdwxfTxfP38YU0cMOOZykuOiGTIgiaWb64mKMG6+aAR7Wtq44Hev0bSv9ZjLXVbd\nQFx0BGkJ0WzcufuYywlXSk5FRESkTxiS/f6TjOKjezaFuXx8AV85t5TYqA+WBJ8/KgeA0pxkri4r\n4tdXjWNH0z7ueWN9t8uo3d3Cb19czbrtXnf+sup6RuSmMCgrUS2nIiIiIqGSFBtFQVo8QI926x9P\nl43NB+D8kdmYGVdOKOT0oZk8tqiq2zfov3fOBv4wew3T7nide+dsYMHGOiYPzqAkM1FjTkVERERC\naWBGAkCPXa1/vI3KT+HZr57JV84t7Zz3oXH5bNi5h7er6g9Z/y8Va5m3vhaA5dUN/PzZFTy/bCuF\n6fGUZCbwgyeXERsVwWfOGMTAjASq6/eyr7V/PZNI9zkVERGRPiMvLQ6gx+5z2hNG5h14o/yLTsrj\nJ08t56dPL+fvnyzrfELVzqZ9/O9zqwCY+aXT+dCf3uzc5taLR3DVhCIeeGsj54/KJTs5juLMBJyD\nytq9DA0Y8tDXqeVURERE+oyObv2Y43Aj+1BJiYvmqrIiFm6s4+bHlnbOf8tvMQUOSEwBLhuXT3pi\nDF86p5ThucmAd09WgE21/euiqL57ZkVEROSEk50cC0BD87Ff7R4Obrl4BBOK05m7fift7d7Y03kB\nyem5I7KZ9ZUzObM0i8mDMshLjT+kjOLMRADWbe9fyam69UVERKTP6OgCr/uA9woNtdioSK6ZWMS3\nH32H97Y3UZqTTPWuvYzITea+z0xmgJ+E3/vpSV2WkZUUy4DkWJZvaeitsHuFWk5FRESkz8hM9JLT\nlrb2EEfywU30b/A/f0MdALv27ictIbozMQXviVVm1mUZJxWkHnBT/v5AyamIiIj0GZMGZXDDGYP4\nyeWjQx3KB1aSmUBWUizzN3jd+fV79pMWH3NUZYzJT2Httib2tPTtYQ6BQpKcmtlVZrbMzNrNrOyg\nZbeY2VozW2VmFwbMn+bPW2tmN/d+1CIiIhJqUZERfO/SURSmJ4Q6lA/MzJhYks4Tizcz8+1q6va0\nkJYQfVRlDM9Nod3B+h2HjjvdsGM3+/tgC3OoWk7fBT4CvBY408xGAdOB0cA04C9mFmlmkcCfgYuA\nUcC1/roiIiIifdZZw7zHo37locVsa9xH6lEmp4Xp3oVSm+v2HjB/W0Mz5b+u4PZZK/jef5by1rqd\nxyfgXhCS5NQ5t8I5tyrIosuBGc65fc659cBaYJL/WuucW+ecawFm+OuKiIiI9FnXlBUx79ZziY3y\nUrKj7dYv6EhOdx2YnO5o8i4Yu+fNDdw/dxM/eHIZ4A0dWLixlnAWbmNOC4DKgOkqf15X80VERET6\nrIgIIzsljtR4r8X0aLv1MxNjiIuOYP6GWq7485vU1DcD0Ni8/4D10hO9cj/9r/l89M45Yf1UqR67\nlZSZvQTkBln0Xefck11tFmSeI3gSHfSBtGZ2I3AjQE5ODhUVFUcO9jhpamrq1f31FaqX4FQvwale\nglO9BKd6OZTqJLhwr5co57V0Vq1bTcWedUe1bVqMY9bSGgCu/fMr3DA2li1NB4413bC1joqKChZu\n9MamPvXiq2TFR4RlvfRYcuqcO+8YNqsCigKmC4Fq/3NX8w/e713AXfD/2bvv+Dar6/HjnyPJ8h7x\nyN5kkZAQSCAQCCRhlg0tlFVGSylltbSlLaX9lrY/6KDsUQotlFVWKSVAQpgmJAGyyN57L8d7W7q/\nPx5JluRHtpxYluSc9+vll61HzyNd3Sj20bn3ngvjx483kydPPohmHJzi4mI68/mShfaLPe0Xe9ov\n9rRf7Gm/tKR9Yi/R+6X3qrnsrCplwrFHB+ahRmvohq/YvW4/AJsqvNw9u5b7Lh4Ni5t3nzpQL5xy\nyqnw/nQABo86hmP7d0vIfkm0Yf1pwOUikioig4ChwDxgPjBURAaJiBtr0dS0OLZTKaWUUqrDHFGU\nBYDTEbmmaSTDemS3OLZpf1XgZxFoaPKyr6o+cGxvRd1BtLJzxGWHKBG5GHgMKALeE5HFxpizjDEr\nROR1YCXQBNxijPH4rrkVmAk4gWeNMSvi0XallFJKqY72f+ePZGTvHCYeUdDua8f0zW1x7H+LmweY\nx/bL4+utZazeXRk4treyvsU1iSJeq/XfMsb0NcakGmN6GGPOCrrvXmPMEcaY4caYGUHHpxtjhvnu\nuzce7VZKKaWUioXMVBfXThzY6m5QkYztlxf4ecN955CV6mJfUPB5dF/r/uI1ewPH9lZocKqUUkop\npWKgf34Ggwozue/i0TgdwrEDuoXc7w9en5uzGbfTgdvpYI8O6yullFJKqVgQET792eTA7VOGFjJr\n7b7A7aLsVAqz3OyvauCMUT3YUVrLlpKaOLQ0Opo5VUoppZTqQr570iCm3z6JUb1zAHC7HIGi/N84\nqifHDezG4m1l1DYkZq1TDU6VUkoppboQh0MY2TuHp64exzUnDuCYfnmBIv+nDCti4pBCGjxeFiTo\nTlE6rK+UUkop1QX1y8/g9xceBcBrPziB9XuryElLYcKgfNJTnExftouz8uPcSBuaOVVKKaWU6uJG\n9MzhvDG9Achwu/jG6KXtBVoAACAASURBVJ68u2QX9R7bDTfjSjOnSimllFKHmcvG96OsppGqhsq2\nT+5kmjlVSimllDrMnDC4gGevO46C9MQLBROvRUoppZRS6rClwalSSimllEoYGpwqpZRSSqmEocGp\nUkoppZRKGBqcKqWUUkqphKHBqVJKKaWUShhiTOIVX+0oIrIPKAPKbe7Obcfx8GPBt4N/LgT2H2x7\nI4jUzkO5prX7o+2X9tzWfrG/nQj9Es357e2X9v4fCr+t/WJ/W/vF/r5k7xf9W9S++5L9d24013Tl\nfhlgjClq82pjTJf+Ap4+1OPhx4Jvh/28oLPafyjXtHZ/tP3SntvaL4nbL9Gc395+ae//Ie0X7Zf2\n9IvNfUndL/q36ND6K9n+D2m/RPd1OAzrv9MBx8OPvdPKfR3tYB6/rWtauz/afmnv7Y6m/WKvvY8f\nzfnt7Zf2/h+Kth2HQvvFXjL2S6z75GCe41D6Rf8Wte++ZP+dG801h2u/BHTpYf3OJiILjDHj492O\nRKP9Yk/7xZ72iz3tF3vaLy1pn9jTfrGXiP1yOGROO9PT8W5AgtJ+saf9Yk/7xZ72iz3tl5a0T+xp\nv9hLuH7RzKlSSimllEoYmjlVSimllFIJQ4NTpZRSSimVMDQ4VUoppZRSCUOD004iIheJyDMi8raI\nnBnv9iQKERksIv8Ukf/Euy3xJiKZIvK8731yVbzbkyj0PdKS/j6xJyJHishTIvIfEflhvNuTSHy/\nXxaKyHnxbkuiEJHJIvK57z0zOd7tSRQi4hCRe0XkMRG5Nh5t0OA0CiLyrIjsFZHlYcfPFpE1IrJe\nRH7Z2mMYY/5njPk+cB3w7Rg2t9N0UL9sNMZ8L7YtjZ929tElwH9875MLOr2xnag9/dLV3yN+7eyT\nLvf7JJJ29ssqY8xNwGVAQpXG6WgH8fv3F8DrndvKztfOfjFAFZAGbO/stnamdvbLhUAfoJF49UtH\n7wrQFb+AU4BjgeVBx5zABmAw4AaWACOB0cC7YV/dg657ADg23q8pAfvlP/F+PQnQR3cBY33n/Dve\nbU+Ufunq75FD7JMu8/uko/oF64PdXODKeLc9UfoFOB24HOvDzHnxbnsC9YvDd38P4OV4tz2B+uWX\nwA9858Tl964L1SZjzCwRGRh2+HhgvTFmI4CIvApcaIz5I9Bi2EREBPgTMMMYsyi2Le4cHdEvXV17\n+gjrE2pfYDFdfFSjnf2ysnNbFx/t6RMRWUUX+30SSXvfK8aYacA0EXkP+HdntrUztbNfsoBMrMCj\nVkSmG2O8ndjcTtPOv0v+3y2lQGqnNTIO2vl+2QY0+M7xdFYbg3XpP4Ax1gfrH9Bvu+9YJLdhfXr9\nlojcFMuGxVm7+kVECkTkKeAYEbkr1o1LEJH66L/AN0Xkb3TOFo2JxrZfDtP3iF+k98rh8vskkkjv\nlcki8qiI/B2YHp+mxZVtvxhj7jbG/BgrWH+mqwamrYj0frnE9155EXg8Li2Lr9b+Fp0lIo8Bs+LR\nMM2cHjyxORZxRwNjzKPAo7FrTsJob7+UAIfbH1fbPjLGVAPXd3ZjEkikfjkc3yN+kfrkcPl9Ekmk\nfikGiju3KQml1d+/xph/dV5TEkqk98t/sQKxw1WkfqkB4jrPXzOnB2870C/odl9gZ5zakki0X9qm\nfWRP+6Ul7RN72i/2tF/sab/YS9h+0eD04M0HhorIIBFxY002nxbnNiUC7Ze2aR/Z035pSfvEnvaL\nPe0Xe9ov9hK2XzQ4jYKIvAJ8AQwXke0i8j1jTBNwKzATWAW8boxZEc92djbtl7ZpH9nTfmlJ+8Se\n9os97Rd72i/2kq1fxFcqQCmllFJKqbjTzKlSSimllEoYGpwqpZRSSqmEocGpUkoppZRKGBqcKqWU\nUkqphKHBqVJKKaWUShganCqllFJKqYShwalSSoURkdtFZJWIvBzvtnQkEblIRP7P9/M9IvKzsPs3\ni0hhK9d/JCLdYt1OpdThTYNTpZRq6WbgHGPMVcEHRcQVp/Z0lJ8DTx7C9S9i9Y1SSsWMBqdKKRVE\nRJ4CBgPTROQOX4bxaRH5AHhBRJwicr+IzBeRpSLyA991IiKPi8hKEXlPRKaLyLd89wUykiIyXkSK\nfT9nisizvsf6WkQu9B2/TkT+KyLvi8g6EflLUPvOFpFFIrJERD4WEYfvnCLf/Q4RWR+eARWRYUC9\nMWZ/FH1wk4gs9n1tEpFPfXdNA644pA5WSqk2JHsWQCmlOpQx5iYRORuYYozZLyL3AOOAk40xtSJy\nI1BujDlORFKBOb7A9RhgODAa6AGsBJ5t4+nuBj4xxnxXRPKAeSLyke++sb7HrAfWiMhjQB3wDHCK\nMWaTiOQbY7wi8hJwFfAwcDqwxCYIPQlYFHbsDhG5Ouh2b18fPAU8JSIpwCfAg77jpSKSKiIFxpiS\nNl6bUkodFA1OlVKqbdOMMbW+n88ExvizokAuMBQ4BXjFGOMBdorIJ1E87pnABUFzP9OA/r6fPzbG\nlAOIyEpgANANmGWM2QRgjDngO/dZ4G2s4PS7wHM2z9UL2Bd27CFjzF/9N0Rkc9j9j2AFz+8EHduL\nFcRqcKqUigkNTpVSqm3VQT8LcJsxZmbwCSJyDmAiXN9E8zSqtLDH+qYxZk3YY03Aypj6ebB+X4vd\ncxhjtonIHhGZCkzAyqKGq8UKpKMiItdhBcS3ht2V5nsspZSKCZ1zqpRS7TMT+KFvyBsRGSYimcAs\n4HLfnNRewJSgazZjTQ0A+GbYY90mIuJ7rGPaeO4vgFNFZJDv/Pyg+/4BvAS87svehlsFDIni9SEi\n44CfAVcbY7xBxwXo6Xs9SikVExqcKqVU+/wDaz7pIhFZDvwdK6v5FrAOWAb8Dfgs6JrfAY+IyOdY\nWVC/PwApwFLfY/2htSc2xuwDbgT+KyJLgNeC7p4GZGE/pA9W8HyMPxBuw61APvCpb1HUP3zHxwFf\nGmOaongMpZQ6KGJMpFEopZRSB0tE/gW8a4z5Tyc933isOaSTWjnnEeAdY8xHkc5p4zkewZp/+/FB\nNlMppdqkmVOllEpyIvJL4E3grjZOvQ/IOISnWq6BqVIq1rp05rSwsNAMHDiw056vurqazMzMTnu+\nZKH9Yk/7xZ72iz3tF3vaLy1pn9jTfrHXmf2ycOHC/caYorbO69Kr9QcOHMiCBQs67fmKi4uZPHly\npz1fstB+saf9Yk/7xZ72iz3tl5a0T+xpv9jrzH4RkS3RnKfD+koppZRSKmFocKqUUkoppRKGBqdK\nKaWUUiphaHCqlFJKKaUShganSimllFIqYWhwqpRSSqmksqu8lic+XU9XLod5ONPgVCmllFJJ5Z0l\nO7l/5hq2HqiJd1NUDGhwqpRSSqmksr+qAYDd5XVxbomKBQ1OlVJKKZVU9lfVA7C7QoPTrkiDU6WU\nUkolFc2cdm0anCqllFIqqeyv1MxpV6bBqVJKKaWSSkm1LzjVzGmXpMGpUkoppZKG12so8Q/ra+a0\nS9LgVCmllFJJo7y2kSavVd90j2ZOuyQNTpVSSimVNGoaPQAUZqWyp7Iej1cL8Xc1GpwqpZRSKml4\nfcFo77w0PF5Dia+slOo6NDhVSimlVNLpnZsOwC4d2u9yNDhVSimlVNLwGitz2isvDdBFUV2RBqdK\nKaWUShr+Kab+zKmWk+p6NDhVSimlVNLwZ06LslPJTnOxcmdFnFukOpoGp0oppZRKGsYXnDodwsQj\nCpi9fn/gmOoaNDhVSimlVNLwD+s7RDh5aBE7ymrZtL86vo1SHUqDU6WUUkolDf+wvkNg0pBCAGav\n3x/PJqkOpsGpUkoppZKG12t9FxEGFGTQt1s6n6/T4LQr0eBUKaWUUkkjOHMqYs07nb/5AGt2Vybs\n3NMl28q49tl5NHq88W5KUtDgVCmllFJJwwTNOQU4qk8uZTWNnPXwLGau2BPHlkX2szeW8NnafVHP\njU3UILuzJF1wKiJni8gaEVkvIr+Md3uUUkop1XkCmVNfBDOyV07gvv0JupVpe0LNZdvLGXTXdL7c\nWBKz9iS6pApORcQJPAF8AxgJXCEiI+PbKqWUUkp1Fn9wKr7M6Yig4LShKfmHzRdtLQXg3aU749yS\n+Emq4BQ4HlhvjNlojGkAXgUujHOblFJKKdVJvGHD+lmpLi4d1xeAspqGeDUrKhLFOXkZKQCUVjfG\ntjEJTJJpXoOIfAs42xhzg+/2d4AJxphbg865EbjRd3Nc57dSKaWUUkrZWGiMGd/WScmWObX70BES\nXRtjnjbGjDfGjB83bhzGmE77+vTTTzv1+ZLlS/tF+0X7RftF+0X7pKO+vtpYwoBfvMvsdftCjk++\n/1NueXlh3Pvlk9V7GPCLd1m6rSxwbMpfP2XAL95l2fayNq+fvW4fA37xLmc99FlM2veDFxYw4Bfv\n4vF4O/39Ei3XoUaLnWw70C/odl8gISZlrNldyYebG6lbvoteuen0yk2jICsVpyOaJL5SSimlotE8\n5zT0eF5GCmU18R8K9897LaluuTirydt2gOZ/fbF6LR+u2hNoiztBY5RkC07nA0NFZBCwA7gcuDK+\nTbJ8sWE/L69u4OXViwLHXA6hR04aPXOtr7556QwoyGRAQQYDCjLolZuuwatSSinVDoHgNGwwtVuG\nmz0VdfFoUgh/grC8tmVw2RRFnVP/9QdiNH/WKYIHQ6PHi9uVmAPoSRWcGmOaRORWYCbgBJ41xqyI\nc7MAuHbiQPKrNzN41LHsLq9jV0Udu8tr2VVWx67yOlbsKOfDFXtoCHpjup0O+uanM7Agk0GFmQzv\nkc2wntkM7Z5FZmpS/dMopZRSncIEFkSFHs/LSGHN7srOb1ALVgNDglNfmxs90WdOY1V5wOEAPNAU\nRVviJekiIGPMdGB6vNsRTkTIcQtH9cnlqD65tud4vIbdFXVsKalmS0mN76uazSU1zN2wn7rG5jdi\n327pDO+RzfCe2Yzpm8uYvnn0yk0LlM5QSimlDkfNdU5bZk4PVDdgjInr30r/yH25zbB8kzeKzGkH\ntWPmit2kpTg5dVhRyHGXwwF4Q5JliSbpgtNk5nQIffLS6ZOXzsQjQu/zeA3bS2tYs7uStXsqWbOn\ninV7Kvls7b7AHJXCrFTG9rMC1TF9czl2QDdy0lLi8EqUUkqp+IiUOR1UmElto4ftpbX0y8/o/Ib5\ntD6sH0Xo2UHR6Q9eXAjA5j+dG3Lc32/RBMrxosFpgnA6xDcfNZMzR/UMHK9r9LB6dyVLtpWxZHsZ\nS7aV8fHqvRhjvcGO6pPLhEH5nDC4gPED88lN12BVKaVU1xVehN9vTF9r1HLp9vK4BqeBBU02wWlj\nFNlKb9Cq9lhkgf1rXRqbdFhfHaS0FCdj++Uxtl9e4FhlXSNLt5fz1aYDfLmxhOfnbuGZzzcFgtXJ\nw7szdUR3xvTJbTHsoZRSSiUzE1aE329EzxzcTgdLt5dx7phecWiZxR/yBWdO/ceiWa0fXHGpvslL\nWoqz4xpHUHCqmVPVkbLTUjhpSCEnDSkErOzq11vL+HJjCbPX7+fxT9bx6MfrKMxyc+qw7kwZUcSp\nw4rI1ikASimlklxgzmlY7sXtcjC4KJMN+6ri0Kpm/nqedsP67c2c1jfGLjjVBVEqptJSnJx4RAEn\nHlHAHWcMo7S6gc/W7uOT1Xv5aNUe3ly0HbfLweRhRZx3dG9OG9FdqwEopZRKSuHblwbLz3THvdap\naW1BVBQBYfAZ9U0eoGMTS05fv0UTKMeLRihdULdMNxcd04eLjulDk8fLoq1lTF+2i+nLdvHByj2k\npTiYOqI7F43tw5QR3UlxJmadM6WUUipcpCL8kBjlpLw2mVN/NjWq1fpBmdPgKj4dxT/dT4NTFTcu\np4PjB+Vz/KB8/u+8kczffID3fIHq9GW7Kcxyc8mxfblsfF+GdM+Od3OVUkqpVpnAsH7L6DQvw207\nnN6Z/LFlWW3LIvrR1DkNnXPq6ahmBQTmnOqwvkoEDocwYXABEwYX8H/njaR4zT5eX7CNZ2dv4ulZ\nGzmmfx5XTxjAeUf3ItXVsXNclFJKqY7Q2rB+Xrq1hWk8a536M6d1jV7qmzwhf0+j2iEq6OdYZE79\nw/rRtCVeNDg9TLmcDk4f2YPTR/ZgX2U9//t6B6/O38pP31jCH2es4srj+3PVCQPokZMW76YqpZRS\nAZEWRIE1rN/kNVTVN8VtEXBwcFle20j3bGe7VuuHLIiKYeY0kYvw62RDRVF2Kt8/ZTAf/eRUXvre\nBMb2y+OxT9dz0p8+4fZXvmb5jvJ4N1EppZQCmjOndpnRvAw3QFwXRQXPGfUvivIfav+wfgwyp7pa\nXyUTEeHkoYWcPLSQLSXVvPDFFl6fv41pS3Zy6rAibpkyhOMH5ce7mUoppQ5jprXMqW8jmrKaRvrF\n6c9VcHAZPv81mqF0b8iCqNhlThN5hyjNnCpbAwoy+c15I5lz11TuPGs4y3eUc9nfv+DSp+by6Zq9\nIZ8MlVJKqc7ibWVBVLdMK3NaWtNyMVJnCR/Wt45ZRxujGNYP1hGZ05tfXkhD0OM0D+sn7t9xDU5V\nq3LSUrhlyhBm/2Iq95w/kh2ltVz/3Hwu+dtc5m7YH+/mKaWUOsz4E36RFkRBy+D07cU7+PGnNTw/\nd3OsmxeS+fRPL/D4AkFPFNnKjs6cTl+2m6+3lgZuSxIsiNLgVEUl3e3kupMGUXznFO67eDS7yuq4\n8pmvuPofX7F4W1m8m6eUUuow0Vqd06w0a7ZiTUNoUPfVpgOU1RumLdkZ8/bZDev7s5RRFeGPwZxT\nT1DG1pUEdU41OFXt4nY5uHJCf4rvnMyvzz2SlbsquOiJOdz4wgLW7olv4WOllFJdnz94c9hMOvWX\nbaoPyziWVluZ1LW7K2M+LS348ct8wal/fme7F0R10JzT4CoBzTtE6bC+6mLSUpzcMGkws34+hZ+c\nMYwvNpRw9sOzuPutZZRU1ce7eUoppbqo1kpJpbqssCY84+gf5q+sb2J3RV1M2xcc8lX4g1N/5rS9\nw/oxyJw6NXOqurqsVBe3nzaUWT+fwjUnDuTV+duYfH8xT8/aEJP6bEoppQ5vgVJS2GVOIwSn1Y1k\n+sqexnp7U6+vgTlpLg74Mrb+mqJRZU6Dfq7voCL8TTbBaSKXktLgVHWIbplu7rlgFDN/PInxA7tx\n3/TVnPnQLN5fvltX9iullOowrWVOXU4HLoe0WEh0oKaBQbnWkP/u8s7JnBZmpQaCU//io6h2iArJ\nnHZMkid4IZZDi/Crw82Q7tk8d/3xPP/d43E7Hdz00kL+uqCOjfuq4t00pZRSXYAJLIiy35401eUI\nyZwaYyiraaBHhnV+eO3RjuZPUhZmpVJS3YDXawLHotkhKnTOaQwyp75u08ypOuycOqyIGT+axD3n\nj2RjuZezH/6cBz9YE5OCwkoppQ4f/pDKLnMK1pqI4GllVfVNNHoMhekOUpwSWKQUs/b5osvCbDcl\nVfU0BmUto5nnGRy/PjtnU0gZqIMVHIgGSklpEX51OHI5HVx30iD+OCmdc0b35NFP1nPGQ5/xyeo9\n8W6aUkqpJOWf02lX5xSszGldUMbRX2s0KwVy01Ninjk1QZnT0pqGkAL4UZWSIvSc4jX7DrlNwZlT\n/7QIHdZXh7W8VAcPX34M//7+BNxOB9/91wJufGEBO8pq4900pZRSScYfZ0UKTq3MaXPg5Z/3meUW\nKzitiXFw6gsuCzJTafSYQHAM0WUrw5dpFGS5D7lNwXNOA1MMdFhfKZh4RCEzfnQKPz97OLPW7eOM\nBz/j+bmbA5+ClVJKqbYEivBHiGDcLkdIfdD9vvKGOf7gtLMyp9lWUBlcuiq6OqfWOe/cejIAtQ2H\nPh0uJHPq+1lLSSnl43Y5uHnyED6841TGD8znt9NWcOnfv2D9Xi3gr5RSqm2mjcxpaoozpD7ongor\nOM1LFfIy3JTVNthe11GCF0QB7AqqDhBV5tT3vUeudX1dByyK8tgM62sRfqXC9MvP4Pnrj+OBS49m\n/d4qznlkNo9/si6hP8kppZSKv9ZKSQGkhWVO9/gyl7mpnZQ59YWXRdlWcLlhb3O1mmgCQn9m0+Vw\n4HY6qO2AhcTBQ/jNwWni/r3V4FTFjYjwzXF9+egnp3LGqB789YO1nP/YbJZuL4t305RSSiWotuac\npobNOd1bWU9BphuXwwpOy2I959TXvh45aQCs2lUBQIpToqtz6vvuEEhNcXRIlZvQzKn1PZq2xIsG\npyruirJTeeLKY3n6O+MorWngoifm8McZq7TslFJKqRYCc04jZE6t1frNfz/2VtTR3Rco5qanUFnX\nFBKsdbRAKaksN06HsGq3FZz2yk2PaoV88A5Y4WWxDlZwOSujw/pKRe/MUT354I5TuWx8P/7+2UYu\neHw2y3eUx7tZSimlEogJDOtHXq0fXL5pT2UdPXKsIfa8DGsP04oYDu37g0unCN2zU9l2wKpM07db\nOjVRLG4yQQu+0lOcHbIgyuNpmTnVYX2lopSbnsKfvjmG564/jrKaRi56Yg6PfKRzUZVSSlnaHNYP\n2yFqb0U93X3zP3PTreA0lvNOgxds+TO2TofQKze91UCzvKaRhz5cG8jqCpCW4uiQBVGNQZli/+NH\nEyjHiwanKiFNGd6dD+44hfPG9OKhj9byzb/NZd0eXdGvlFKHuzYXRAXN0/R4Dfur6gPzP/3BaSx3\niQqeduAPirtluMlKdbYaEP7u3RU88vE6Pl6113e9kJ7ipK4jhvU9LYf1N+2vPuTHjZW4BKcicqmI\nrBARr4iMD7vvLhFZLyJrROSsoONn+46tF5Ffdn6rVWfLy3Dz8OXH8ORVx7K9tJZzH5vNPz7fGNO5\nQkoppRJbYE5mxMxp84Kokqp6vIZABtM/rB/TzCnN7fNPJyjIdJPudrWaOfUH1P45ptaCqI4Z1m9s\nalmEf0dZbYc8dizEK3O6HLgEmBV8UERGApcDo4CzgSdFxCkiTuAJ4BvASOAK37nqMHDO6F7M/PEp\nnDqsiP/33iquePpLth2oiXezlFJKxYExJmLWFPzD+lbQ5a9xGj6sX1YTu1qnxpjAYq0xffIA2F5a\nQ4bbSYPHG3GaWvOe9/5hfX/m9NCH9YMXYnmDtqBK1Oxp1MGpiHQTkVEiMlgk0r4M0THGrDLGrLG5\n60LgVWNMvTFmE7AeON73td4Ys9EY0wC86jtXHSaKslN5+jvjeODSo1m1q4JzHvmctxfviHezlFJK\ndTKvMRHnm4K1IKrRYyheszdQ47R5WN/atSmWC6KMaZ4P+61xfblu4kB+de6RZLidQOS5nv5rAnNO\nxTdFoSMyp57QzGm//HQA1u+rinRJXLUaZIpIroj8SkSWAV8CfwdeB7aIyBsiMqWD29MH2BZ0e7vv\nWKTj6jDir4s648eTGN4zmx+9upg7XltMZV1sa9YppZRKHF4TeTEUNA/ZX/fcfPZWRsqcxnbOqb91\nDodwzwWjuGrCADLcLiDydqT+bHBocNoxc04bmkK3L+2RbQXrscwgHwpXG/f/B3gBmGSMCamMLiLj\ngO+IyGBjzD/DLxSRj4CeNo95tzHm7QjPZ/duM9gH0bYTD0XkRuBGgB49elBcXBzhqTpeVVVVpz5f\nsohFv/xwuOHdlBTeXryD2at38oMxqQzp5uzQ54g1fb/Y036xp/1iT/ulpa7eJ1u2NGCMN+JrTKtq\nCvz81dLVAKxc9CV1NdXMnT2LVCcsX7eRYmdsRt+2bGkAY1q0b/NOq13Fs+fSM7NlWLN3j5Xlray2\nhto/nzWL0v0NlFd5Dvnfc8euXRQXl/oevwZXkxVurVi9jvyi+oR7v7QanBpjzmjlvoXAwlbuP/0g\n2rMd6Bd0uy+w0/dzpOPhz/s08DTA+PHjzeTJkw+iGQenuLiYzny+ZBGrfjltKly95QA/enUxf5xf\nx49OG8otU4bgbG0yUgLR94s97Rd72i/2tF9a6up9MrdmFc7tmyO+xsnAHucSZq3dR0ZBDwp27+b0\nqVMC/ZL/xcdkFxQyefLRMWnfl7WrcWzb1KJ99St2w9KFHDV2HEf1yW1x3bQ9i2HXDtLS0qG6hsmn\nnsrsqlUs3r/94P49338v8GO3giImTx4HQPrCYnoXZbGiZA/9Bw4iSw7y8WOozbmjIpIhIpmd0Rhg\nGnC5iKSKyCBgKDAPmA8MFZFBIuLGWjQ1rZPapBLYuAH5TP/RJM4b04sHP1zLFU9/yY6y2ng3Syml\nVIx4va3POQXolpFCVX0T+yrrA3vc++Wmp7R7tf67S3dy+oOfRVUtxgQN6wfL9A3rRywn5R/WD5Si\nEt+wfgfUOQ0pJWUtGgOoT9CdGNuac3o78E/gGRG5o6OeVEQuFpHtwInAeyIyE8AYswJrTutK4H3g\nFmOMxxjTBNwKzARWAa/7zlWKnLQUHrn8GB769tGs3FXB2Q/P4v3lu+PdLKWUUjFgaH3OKUBWago1\nDR72VdVTkOUOuS/nIILTO15bzPq9VdQ0NLV5bqT2pQcWRNk/hv8a/06jDt+CqIYmL95DLKHYELJD\nlMHpENwuB/UJusFNW5nTa4ErgauB73TUkxpj3jLG9DXGpBpjehhjzgq6715jzBHGmOHGmBlBx6cb\nY4b57ru3o9qiuo6Lj+nL9NsnMagwk5teWsjv31kZsoWdUkqp5OcNKtUUSVaalaXcWlJNQWZo5jTD\n7QzUFG2NMYal263lNv596GujuM7rtW+ff7V+pAVRzkApKevvlr8If7TP25rwOqcOEavkVgfsPhUL\nbQWnfwH+C7wJPBz75ih1aPoXZPDGTSdy3cSBPDtnE5f9/Qu2l2pNVKWU6ipMG6v1AbJTreC0tKax\nReY02v3qZyzfzQWPzwkpW1jX0HYwFylz2lYpKQms1m/+2V9doKKdVWmMCc20Bg/re3zBc6rLEVL/\nNJG0GpwaY14zxlzs+3qhsxql1KFIdTm554JRPHnVsWzYW8W5j87m41V74t0spZRSHcDbRhF+aM6c\nAhRmhWZO01OcLXujwgAAIABJREFUUWUi/UP/n67eGzhW09j2sL43wpzTjMCcU/vH8BfhD76+W6YV\nWB+oblnyacm2Mu58Y4ntkH9YbNpi+1KniLWTVjJmTkUkq60HiOYcpeLhnNG9eOe2k+mTl873nl/A\nH6evirgzh1JKqeTQVhF+gKzU5uC0IDM0c5oW5bC+/zE+DgpOo8m4GkOrw/ptZU4bPd7A68v3tb20\numXm9Nrn5vHGwu2U2cyf9YZFp/U2w/ruZM2cAm+LyAMickrwin3fLlHf8y1kOju2TVTq4A0szOS/\nN0/kqgn9+fusjVz+9JfsKtfV/Eoplay8pjnLGElw5rTALnMaRZDpD+gq65ozndEFp8a2fekpTtJS\nHOzzbQwQzhEUnPov75ZhDesfsCmW7wjKtLZoQ9jtJm/ogiiHw7fNazKu1jfGnAZ8DPwAWCEiFSJS\nAryEVWD/WmPMf2LfTKUOXlqKk3svHs0jl49l9a4Kzn10NnM37I93s5RSSh0EE8WwfnZw5tRuzmmj\np8W8zHB22dWIZaCC2we27XM4hIEFmWyMsJ+9P9hs9BjEN7DfLcOfObULTn3PZ/MywgPWprDtSyXJ\nM6f+VfJXGWMGGmNyjDEFxpiJvlX1Wq9HJY0Lx/Zh2m0nk5/p5up/fMUzsza2+ctJKaW6MmNMSOCS\nDLzeKEpJBWVOBxaElmpPdzvxGtoMzPyZ0wvH9g4ci2q1foTMKcARRVlsjLCfvf81eYJW++empyBi\nP+fU/xx2f8dazjkNy5wKSb1aHwCxXC0iv/Hd7i8ix8e2aUp1vCOKsvjfLSdx1qie3Dt9Fbe+8jXV\n9W1PcFdKqWRS1+iJqjbm795ZyZC7ZyTVB/VoFkRlp1nD4SLN8zb90nzlmYJX3u+tqGuxIr7et6d9\n327pgWO3vfI1y7aXt/rcVjUB+/sGF2Wy9UBN4LEj8QenLqeD3PQUSm2H9a3vnqiC0+DMqbUgKqkz\npz5PYhXMv9J3uxJ4IiYtUirGslJdPHnVsfzi7BHMWLaLS56cy+YIwyxKKZVsPF7DiN+8z+/fXdnm\nuf+auxmA6iiGqxNFVHNOU138v4uOYtadU1rcZ1c79Pj7Pua0Bz4LOc+fVeyfnxFy/LvPz2+zfdiu\n17cSJF4DW0taL3EYnBnOz3DbZk6DM63hDJFLSVl1WH2r9dsIkuPF1fYpAEwwxhwrIl8DGGNKfduI\nKpWURIQfTj6Co/rkcNsrX3P+47N55PKxTB3RI95NU0p1QQ1NXnaV17J8RwWrd1eQk5ZCo9dLfaOX\n+iYvdY0eKmobqaxvolduGlmpLlwOoaS6gZkr9tAjJxWvgT9/czTDemSzaEsp4wfm43a1zDHtrLYC\nk3/N3cw9F4yKqn1VdU0hK9wTmfEt6GnL1ScMsD2e7rYu3ltZh0Oge04aQIuFSnVNHtwuBxeO7cP8\nzaX8Z+F2APZX2S9oCmphxE0CBhdZUww27KtmaI/skPv8xfchNLTNz3Szt6Llc7YanIYdagoa1vfX\niXU7HQm7UU2078RGEXHiWwAmIkVAYr4ipdph0tAi3rn1ZG56aSHf/dcCfnz6UG6fOhRHW2NGSikV\nQV2jh6+3lrFoaykb9laxclcF6/dWhayYDuZ2OUh1WcO3GW4nX20soabBExiuHd4jmxU7KwC48YWF\n9M/PYN7mA4zslcObP5xIutvJW19v57FP1vPubSezqbw5G9bk8eI1UFrTQA9fEGansq6RnrmR708k\n0ZSSao0/c3rB43MA2Pync23Pq2/0kupykJbi5C/fHBMITtuaAdHasP6gQis43bi/5bzT4BH24Nd3\ndL88XvxyCzUNTYFaqdA89G/3vgpfENUQNqzvEEhNcfjm1Sbe37tog9NHgbeA7iJyL/At4Ncxa5VS\nnahffgZv/nAiv/rvMh7+aB3Ltpfz4LfHBnbmUEqp1lTUNVK8Zh8LNx9g1e5KFm8tCwQDPXJSGdEz\nh6kjujOgIIORvXIZ1jOLOl/g43Y6ovowvGhrKc/P3czbi3dSVd/EN47qyYzlu3nk43XcftoQ7nht\nCQDvLNnJpvLmQGTVrkpeW7CVl77cyrJ7zgzMxWz5GpJn7r2/TufB8s859Ys037a+yRs4N/zf6JaX\nF3HlhP6cNKTQpn3Nq+3DZael0D07lY37Wk4l8wRlToMvnzK8O/+cvYkvNpRw2pHNo3uBUlK2w/qh\nQktJWa8n1eXPnDpJNFEFp8aYl0VkIXAaVpddZIxZFdOWKdWJ0lKcPHDZ0Yztn8fv31nJRU/M4Zlr\nxjGke3bbFyulDjtV9U1MX7aLl77cwvId5XiNlZEb2iOL604ayIRB+YwfkE9uhn0wmOpqX0BwbP9u\nHNU7l+tPGsTgokxy0lK49d+LeOqzDTz12YbAedOW7GRnuZdhPbJYt7eKT9fs5b+LrO03z3poFs9e\nfxyDCjNbPH9lO7fHjCdrNfzBX58eFpyW1ti/9vpGD6k20yYA3lu2i/eW7bLNuraWOQVraH+DzYp9\nj31sytj+eQCs21sVFpxa3+0ypyZsbNvjNXi9BodD8Pj6z+3yZ06TNDgVkSOATcaYJ0RkMnCGiOwy\nxpTFtHVKdSIR4ZoTBzKiZw43v7yQi56Yy4OXHc2Zo3rGu2lKqQSwZnclr83fxrzNJWzaV011g4cj\ne+Vw69ShnDAonxMGF8R0SpDb5WBsv7zA7dumDmXlzgrqm7ycfmR3qhs8zFi2i7pGLzcc050Mt4sH\nP1wbOH9neR1nP/w5vXPTmHvXaSGPXZlEmVNziJnTdHdoMLYpwoLY+iZvxODUb9uBGvqFLZhqa8FW\n//wMPlu7r8Xx4Mxp8PsozdeG8Pmh7VkQBdDo9ZLqcIZtX+oBEm+UMNrV+m8CHhEZAvwDGAT8O2at\nUiqOjh+Uz7RbT2ZwUSY3vriQhz5cG1VJFqVU11Ne28iMZbu4840lnP3ILF76agtZqS6mjOjOK98/\ngfduO5mfnDGMiUMKO32u+vCe2Xzys8nM+eVUfnfhUYzpm0t1gwePgaP75vG9kwcFzg2eprSzvA4I\nHQ5uKzitb/Iw8Jfv8bxvdX88RVNKqjXhw/pbSiIFpx7bDPe7t53Mj08fCljBaTjTyoIogKzUFKrr\nW66SD1qzFJI5dTkdOB3SIjhtfc5py+f11zpNhu1Lo51z6jXGNInIJcAjxpjH/Cv3leqKeuel8/oP\nTuTut5bzyMfrWLGzgoe+fXTE+VpKqa7liw0lPD1rA3M3lFDf5MXtdPC9kwZx69Qh5GUkZrGaET1z\nAj+P7ZdH77x0JgzO588z1vCzs4bx67eWB/aJr6pvCsm4RRrWb/J4+c3bK5g6ojsAf/9sA9dOHBi7\nFxGFjloQ5bc5Qlkna85pyxzeUX1ycTmFhz9aZ7uvvTG0EZw6qW5oCgyz+wV/WAh/fW6no0XZJwlk\nTlsGmHbzaP2bLfiDe5fTQaPH2G5/Gm/tWa1/BXANcL7vmP6VVl1aWoqTv146htF9cvjDe6u46Ik5\nPH3NeI4oyop305RSMTJtyU7+OnMNWw/U0D07lSsn9GfqiO4M75EdKDmUqEb2ziEvI4VTelkfsAG6\nZ6fxwGVHA/C7C0exZk8l20tr2VFaGxKkRcqcbi+t5ZV5W3ll3lYAirJTbc/rTIc6kBVt5rSuMTRz\n+t+bJ+J2WsFqXrr1AaXMZr6qaSN4zkx1YQzUNHpCyneFlJIKuzw1pWXZp8CcU0/bC6LAWrFvjPEF\nzxIoQ5aI1aSiDU6vB24C7jXGbBKRQcBLsWuWUolBRLjupEEM75nDLf9exEWPz+Ghb4/l9JFaD1Wp\nrsAYw5z1JXy0ag9HFGXyl5lrcDqE/ztvJFdO6N8ikElkWakuFv36DGbN+sz2/r7dMnjsimO4+Mm5\nbDtQQ07QUH+kzGn4sG9hVvyD07aCv7aEzzmNtONTfZOXzMzmMOnY/t0CP+f5FrqV1bYsju81rRdn\nyvQFpNX1obVlQxZE2WZOI8w5tcl82mVDmzwmENg7fHNOARJxB9NoV+uvBG4Pur0J+FOsGqVUojnx\niALeue1kfvDiAm54YQE/OWMYt04ZovVQlUpSG/dV8d7SXXyyZi9fbw1d2/vRT05J2kodbf1O6tvN\nWrxzwwsLOGFwPg6BDLcrYuY0PFtnV/S/sxlDVEX4Iwkf1t8YaUFUo5e0CFUV0lKcuF0Oyu2G9Wl9\nwVZ2mhV6VdU3EZzm8EQowg9Wv7eccxp5QZRd6rTR4w0ErU5H879lYwKuqYjqn1dEhorIf0RkpYhs\n9H/FunFKJZI+een856aJXHxMHx78cC03vbSQqvrkWeGqlLKCrVfnbeWMh2bxwIdr2bC3ij9cdBRL\n7zmTS47tw+NXHpO0gWk0CrPcTBpq1eb8cuMBxg3oxqDCTFbtrrQNcsIzp4nwO+9Q55w6HRIIUId2\nD52mFTzvs67JQ6rNnFO/vPQUymsa2VNRx4xlu0La11rqNNPdnDkNFrIgKnxY32WXObW+t2dBlD84\nFRFOHJzPn785mnRn4iVZoh3Wfw74LfAQMAVrmD/xXo1SMZaW4uTBy47mqD653Dd9FRf75qH6d/1Q\nSiWm+iYPc9bv5x+fb2LuhhLcLgfv3X4yQ7tn4/T9lX/wsrFxbmXsiQgvfm8C9U0e/la8gQmDCthb\nWcePXl3Mc3M2ccOkwSHn+7N1f7xkNI99vK5FQBUPbZVqikZmqpPaRqsU2Lq9zTVHGzxe0hxW4Orf\nISqSvIwUXp2/jVfnbwNgyW/PtKoiRDmsXxWWrQ4pJRU+rO9yRh7Wt51zalNKyuMN7G7lEGFI92yG\ndM+muDjxco3RBqfpxpiPRUSMMVuAe0Tkc6yAVanDiojwvZMHcWTPbG759yIueHw2j15+DFN8q1mV\nUoljb2Ud9723ik9W76WironsVBc/OWMY54zuxZDuh+/ixlSXkx+fPgyw5nC+s2QX989cw6Xj+oVs\nHNDoy5wO6Z7F6L65bN5vv7K9Mx1qKSloXhTVP6xGaX2jtSvU1pIadlfUtTrnODyAXL+3inEDumFo\nPbPrn2canoUOzlyHX51qU/ap/ZnT5mH9RJ+RFu2sjToRcQDrRORWEbkY0L/E6rA2cUgh0249mX7d\nMvju8/N54tP1EbfBU0p1ruU7yvnDuys5/t6PeWfpLs4a1ZPnrj+Or+4+jdtPG3pYB6bh/B+465u8\nLNpaGnKfP3PqdjrITHUlxLD+oRbhB0jxrbrPTA3N0fnLNd311lLrdiurhcLnqq7bUwmA19t6KanM\nVCvgfXfpLn76+pLAcW9rC6JcDl/BfIJPAiIU4bf5W9ToMYFzD7X/Yi3a4PTHQAbWoqhxwHeAa2PV\nKKWSRb/8DN784UTOH9Ob+2eu4eaXFyXEsJdSh7O5G/Zz0RNz+OfsTQD8+LSh3H/p0UwZbu2apFo6\nul8uANf/az4/eX1xIAgNBKcuB9kJEpx2RObUP5UjfNi+zheM1jZYgeAFY3tHfIymsEymf3pAtJnT\naUt28uai7c2P11opqVYzp3Z1Tls+r5U5tX/8RBPtav35vh+rsOabKqV80t1OHrl8LKP75PLHGavY\nuK+ap68Zx4ACnYeqVGcxxvDGgu38Z+F25m0+wKDCTN66eSLbS2sZ2Sun7Qc4zGW4XYFFN/9dtINu\nGW5+fe6RgYAoxZc5ra5vwhhzyHM+D4W3A57f5Q9OwxY8+TOnDhEmHlHASUMKIz7GGzdN5O3FO3jh\niy1A8zaobS1+z0oLDb38/Rk8dTQ8uE11OSipsp9zalc2yi44bfKYQEbVmeDj+lEFpyIyDLgTGBB8\njTFmaozapVRSERG+f8pgRvTK5rZXvub8x2bz2JXHcuqwong3TakurazOy2/+t5yPV+1hZ3kdw3pk\n8YNTBnPVhAHkZbgTdjenRPTSDROorGvk/eW7+efsTeRnuunuK7qf6rKC0yavob7Jy3tLd7GttCYw\nb7UzWdtvHtpjNGdOndw+dQiPfrIeILDoqKbB0+Z7Z9yAbowb0I17zh/F1f/8KlArtq1pB+kpThzS\nHMR6DTglrJRU2OV2W422XoTffkFUcJ3TRBbt+MYbwFPAM0DLDWGVUgBMGlrEtFtO5sYXF3D9c/O4\n86wR3HTq4LhmGZTqiirrGnl13jbun1ULjm0M7Z7FSUMK+fM3x2j94YN03MB8AE4d1p2tB2p4Y8E2\nvn+KtXrf7XIEhqMf+GANz3xuTZm4efIQqnzZ1IJOKtBvjMFxKIVOac6cpqU4+MmZwzluUD7f+ec8\n6nzzOmsbPWS4o9uAweEQMlNdbC+tDbSvtV/5IkKm20Wlb4pEk9eL0+EMLcIfdk2qy9muOqfJviAq\n2uC0yRjzt5i2RKkuon9BBv+9eSJ3/mcpf35/Nct3lnP/t8boXDelOsgTn67niU/XU+ObF/jqDcdz\nwuCCOLeq63A6hPOP7s3dby1n+Q5r96QUpyMQrPkDU4A/vLuSF7/cgtMhbLjvnE5pn7cDFkQFZ06D\nv/szp9X1TVEHp4BvPq4vc0rb7euW6Q4Ep/7gstVSUk5HYMpB8znWd7vV+pEWRAXXOU1krX70EJF8\nEckH3hGRW0Skl/+Y77hSykaG28XjVxzDL84ewfRlu7jEt12gUurgebyGa56dx/0z1zC2Xx4PXnY0\nPxufpoFpDJw9qidup4NX5lk1PN0uB0f1yWVYjyxunTKE3184CoAXv7TmW9ruUhQj3jYyk9Fw+TKv\n/gVR/u/+ALC2wdOuhEJWmitQtzSa9uVnNk8ZaAoEp8FV+EPPt90hivZlTpu83kBFgGQf1l+I9SHA\n/yp+Gnb/YJRStkSEH04+gpG9c7jt34s4//HZPH7FsZw8NPIEe6VUqPLaRraW1DC6by5fbChh1tp9\nXHF8f35/4ShSnA6KK9bHu4ldUkFWKueO6cVbX+8ArMzdkb1y+OCOUwFYsdN+P/rO0JGZU//j+OuZ\n1jV6McZQ3dC+zGmWr5KBMQYTxSYBhVnNwal/V6rggNJuQVSLIvy+9KJd5jR4/1L//NaGptDtSxNZ\nq8GpMWYQgIikAzcDJ2O94s+x5qAqpdpw6rAipt1qzUO95tmvuOsbR3LDpEHxbpZSCW9HWS2XPfUF\nO8pqOW5gN+ZvLiXV5eC3548M1KlUsRNcCzYlbIvLHjlpLc7vrFX8pgNLSXl8wZp/v/uK2kbqm6yF\nQ+ntCU7TXDR6jO9a0+YWmgWZzfNz/cFlSCmpsPPtMqeB1fq2w/rNP7uc1rUrdlZQXmtNPUj0Yf1o\nc9bPAxXAo77bV/iOXRaLRinV1QwszOStm0/iZ28s4d7pq1i+s5xzirRgv1J+/sDGGMPbi3eyv6qe\nJz5dT5nvj+n8zaWcOLiAbx/Xr9Vde1THyQoqUB8ezOQHrWS/+oT+vPTl1kCdz2E9smPaLqvOacdk\nTv3zPP3D7CXVDYEap5ntzJxC865PbTUvuJyUf1g+uFxpy8ypkyavVUTf33b/v0lbO0S5fcHpv+Zu\njvj4iSba4HS4MebooNufisiSiGe3QUTuB84HGoANwPXGmDLffXcB38OqCnC7MWam7/jZwCOAE/iH\nMeZPB/v8SsVDZqqLJ686lieLN/DXD9YwP0Pod2QFI3trDUZ1eHtl3lZ+984KLh3Xj9556fz5/dUA\nDO+RzZs/nEhhdip1jR66Z7fM1qnYyUqNHCIEV0QY268bL325lTMfmgXA5j+dG9N2tbUDUzQuObYP\nn63dx9DuViCdluIkw+3kQHUD1Q1WgNmuOae+vqqub4oqeHYHFf+3zZzazDkFa2jen9H1/xN47Irw\nBw3ru5wt29JVVut/LSInGGO+BBCRCcCcQ3jeD4G7jDFNIvJn4C7gFyIyErgcGAX0Bj7y1VgFeAI4\nA9gOzBeRacaYlYfQBqU6nYhwy5QhHN03j1temsdFT87hV98YwbUTByb8MItSsfLvr7ZS1+gNLK45\nbmA3Lj6mLxcd0zsQIOSkpbT2ECoGwrf2DPf4lcdQlJUaCOb8dpfX0TM3dh8kOiJzeuHYPpw/pndI\nkJ2f6aY0KHOakdr+zGllXZM157SN84N3pvIGFkRFPt8uOPU/h23mNOix7KbAJHrmNNpJOxOAuSKy\nWUQ2A18Ap4rIMhFZ2t4nNcZ8YIzxv5u/BPr6fr4QeNUYU2+M2QSsB473fa03xmw0xjQAr/rOVSop\nnTy0kD+clM7JQwq5552V3PD8Akqq6uPdLKViqq7Rw40vLOD0Bz/j0Y/XAfDGgm0s21HO3eccye8v\nHMXgwkwevvwYrpzQX8uvxVl2Wuv9f96Y3kwYXNCiWP1vpy1nR1ltzNoVPLR9KMLr4RZkuimpbqDa\nH5y2c84p4FsU1Xbwlx30YavJa7juuXnsD/obYLcgCmhRTgrsV+sHZ07dNsFpgsemUWdOz45hG74L\nvOb7uQ9WsOq33XcMYFvY8QkxbJNSMZfjFv557Xien7uZ+2as5huPfM6Dl43V1fyqy/pk9V4+WLkH\ngAc/XMsHK3ezfEcFE48o4IoJ/clKdXHNiQPj20gV0Fbm1K9bWHA6c8Ue5m4oYfrtk+iXn9Hh7eqo\n4DRct0w3JVUN1Pgywekp7R/Wr6qzhvXbSp1eNaE///h8I7vK69hVVkvxmn0h90ca1g9ese+PSe3r\nnDb/bNdXXWL7UmPMlvY+sIh8BPS0uetuY8zbvnPuBpqAl/2X2T099hle29UkInIjcCNAjx49KC4u\nbl/DD0FVVVWnPl+y0H6xV1VVxWeffcZA4NfHu/nbknqu/udXnNbfxWXD3KS6EvuXR6zo+8VesvdL\ng8fw8II6MlPg9P4pvL2hkeU7KhjezcG1g2tZ8MXsg3rcZO+XWOioPtkZtJd7a49X3Wj9OR6Q4+DK\nEW7K6w3PLq/nzhdn8d2jrFXpbpt5jwerqqaG/fvq2v0a2+qXxsp6dh7wMG/hYgBWL19M/bbosqe7\nq62+mrd4GWVljYi03mcAlwwyPLEYnnp/YZtt3bTLCphnzfmSPtlWSFRSUgfA5i1bKS7eHXL95vLm\nDGtdXa21PWpQ1LRq5UqyDqy1fa5EELMxE2PM6a3dLyLXAucBp5nmrQy2A/2CTusL7PT9HOl4+PM+\nDTwNMH78eDN58uR2t/1gFRcX05nPlyy0X+yF98ulZ3v4y8zV/GvuZtZVubn/W6OZcBgWF9f3i71k\n6hev17BhXxVDfau2y2sbOf+x2Wwt9fKXb47hgrG9efs37zNleBHPXX/8IT1XMvVLZ+moPtldXgez\nPwZo8/GcvXYxYVAB3Xyr3ne9tpi3vt7B+koPOekuXv/BiWSnuQI7MR0K91ef0LtXPpMnj23XdW31\ny5zqlSzct4XBw0fCoq+ZdOLxDOkeXeWBfZX18PlH9B00hJyKnbgcDiZPPqHVa+pX7IbFC9len4qV\np2uWmZnF5MmTArdl7T7+tmQeI8aMZdwAaw+kf6z/Ckr207tPXyZPHhly/dLtZfCFtTQoIz2dqqb6\nwI5qAKOPGsXko3oBifl/KC6F4nwr738BXGCMCd42ZxpwuYikisggYCgwD5gPDBWRQSLixlo0Na2z\n261ULKW7nfz2/FG8+n3rF9q3n/6Se6atCAwxKZXIKusauebZeazfW8nDH6/jjIdmsXBLKfe+t5LT\nHihm64Ea/njJaC7zlYL64q6pPPWdcfFutmpFVhtzToOdfVSvQGAKcKLvg/X+qno27qtm/P/7iOG/\nfp+Ln5zDjGW7bLfXjJbHa3DGYNJkv/wM6hq93P7K16Q4xbaWayTdMqw5pAeqG6w5p1FEVy7f0PrG\nfdUt7vOG9U+O79/CX6c0+Jy2dogyQc/ll+gLcONVxfhxIBv4UEQWi8hTAMaYFcDrwErgfeAWY4zH\nt3jqVmAmsAp43XeuUl3OhMEFvP/jSVw3cSD/mruZsx/+nOI1e+PdLNUFeb2Ggb98j2dmbQwc219V\nz7F/+JDP1+2zvabJ42XDvqoWxz9ZvZdZa/fxpxlreG3+VgC++be5PPP5JvZXNQBw0dg+gfN75aZ3\nSBZNxU7GIdSTnTyiiD556Tx73XhG98kFID3FKtX0w5cX8b3nF1Bdf3AfvGM15/Sy8f04d7SVTRzZ\nOzdk0VJbXE4HeRkplFQ1+Irwt92+4NcwKqykYHjsnpNutaWitrnP/MFpk10pqbAHCC5dBa2XCUsE\ncQlOjTFDjDH9jDFjfV83Bd13rzHmCGPMcGPMjKDj040xw3z33RuPdivVWTLcLu65YBSv3ngCLqdw\n3XPzueXlRdYwm1I26ho9vDZ/a7v2OK/07QV+7/RVgWOz1+3nQHUDS7aV2V7z49cWc9oDn1Fe0xhy\nfL2vAPuqXRXsqWhedfz9oN3Q2rPjjoq/8NXs7dE9O405v5zK1BE96JOXDsCfvzWGT346md+eP5LP\n1u7jime+pK6x5erztnhNbILTtBQn910ymhMG5/Pzs4a3+/qCTLeVOSW61fDBr2FEz9DgNDxzmusP\nTuuCM6fW97YypwK4fKncrFQXL37veCYekdhTxnT/N6US2AmDC5jxo0n87MxhfLRqD6c9UMw/Z2+i\nqbWCeOqw9Lt3VvCLN5cxd8P+wLFZa/cx8JfvRSxTdqCmocWxOeut63eUtfwg1OTx8u7SXQBsK7Vm\nZP327eV8sGI3i33B7I6yWnrkNG/NeOn4fgzvkc0NJ+uWvYeru889kiuO78eZI3vgdAjXnzSIJ648\nlqXby7n7reUttuVsS1OMMqdgBYGv3ngiJw1pf9WUgsxU9lfV4zXRDZsHv4ai7NSQ+1oO61vBafCH\nQn92tMlj94E09FiKb4HtuAHdmDS0SIf1lVKHJtXl5NapQ/nwjlM5blA+f3h3Jec9NptZa+2HXdXh\n6dX5VrW9xqAPLv6i9l9sLLG95kB1aHBqjGHuBuvcnTZ1KtfuaR7O/3jVXq57bh7Pf7GFG19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S5b2zyqXCRsNvhb6T735gnWL/UW5A9rcpr0J0VNpHZBu1xFs2NOgy+AtZXxYROizIxkzhJWTdUJ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\nUxEREREJDSWnIiIiIhIa/wHe+0yvaDFvDAAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xdd28dd8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "Servo1.plot_servo(np.logspace(-2,6,100000))\n",
-    "\n",
-    "pylab.figure( figsize=(11,11))\n",
-    "ax3=plt.subplot(311)\n",
-    "ax3.set_ylabel('gain (db)')\n",
-    "ax3.set_xlabel('frequency (Hz)')\n",
-    "plt.semilogx(f,g)\n",
-    "plt.axhline(y=0, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "plt.grid()\n",
-    "ax4=plt.subplot(3,1,2)\n",
-    "ax4.set_xlabel('frequency (Hz)')\n",
-    "ax4.set_ylabel('phase(°)')\n",
-    "plt.semilogx(f,p)\n",
-    "plt.axhline(y=0, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "plt.suptitle('Servo applied to the measured Transferfunction')\n",
-    "plt.grid()\n",
-    "plt.savefig('Servo+Measurement')\n",
-    "plt.show()\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/unordered/Servo_Design/Servo_Design.ipynb b/unordered/Servo_Design/Servo_Design.ipynb
deleted file mode 100644
index 2b1845d7642be488ba68f70bbf502c8003385aed..0000000000000000000000000000000000000000
--- a/unordered/Servo_Design/Servo_Design.ipynb
+++ /dev/null
@@ -1,710 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import math as math\n",
-    "import scipy.signal as sig\n",
-    "import matplotlib.pyplot as plt\n",
-    "import pandas as pd\n",
-    "import pylab\n",
-    "import copy"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "def normalize(a,cast=False):\n",
-    "    if cast:\n",
-    "        return np.asarray([float(a[0]/a[3]),float(a[1]/a[3]),float(a[2]/a[3]),float(1),float(a[4]/a[3]),float(a[5]/a[3])])\n",
-    "    else:\n",
-    "        return np.asarray([a[0]/a[3],a[1]/a[3],a[2]/a[3],float(1),a[4]/a[3],a[5]/a[3]])\n",
-    "\n",
-    "# Calculates the second order section for filter\n",
-    "# z position of zeros (max:2), array like\n",
-    "# p position of poles (max:2), array like\n",
-    "#k gain, float\n",
-    "# fn nyquist frequency, float\n",
-    "def bilinear(z,p,k,fn=1,cast=False):\n",
-    "    \n",
-    "    \n",
-    "    z=np.asarray(z)\n",
-    "    p=np.asarray(p)\n",
-    "    pz_index=np.empty(0,dtype=int)\n",
-    "    zz_index=np.empty(0,dtype=int)\n",
-    "    pz=0\n",
-    "    zz=0\n",
-    "    sign=1\n",
-    "    \n",
-    "    #calculates the sign\n",
-    "    for i, pole in enumerate(p):\n",
-    "        if pole!=0:\n",
-    "            sign=sign/pole*np.absolute(pole)\n",
-    "    for i, zero in enumerate(z):\n",
-    "        if zero!=0:\n",
-    "            sign=sign*zero/np.absolute(zero)\n",
-    "    k=k*sign\n",
-    "\n",
-    "    #checks number of zeros and poles in the origin\n",
-    "    for i,pole in enumerate(p):\n",
-    "        if pole==0:\n",
-    "            pz=pz+1\n",
-    "            pz_index=np.append(pz_index,i)\n",
-    "    for i, zero in enumerate(z):\n",
-    "        if zero==0:\n",
-    "            zz=zz+1\n",
-    "            zz_index=np.append(zz_index,i)\n",
-    "    zz_index=np.asarray(list(reversed(zz_index)))\n",
-    "    pz_index=np.asarray(list(reversed(pz_index)))\n",
-    "    \n",
-    "    #reduce the fraction(only for multiple poles and zeros in the origin)\n",
-    "    while (pz>0)and(zz>0):\n",
-    "        p=np.delete(p,pz_index[0],0)\n",
-    "        z=np.delete(z,zz_index[0],0)\n",
-    "        pz_index=np.delete(pz_index,0,0)\n",
-    "        zz_index=np.delete(zz_index,0,0)\n",
-    "        pz=pz-1\n",
-    "        zz=zz-1\n",
-    "    \n",
-    "    #writes poles/zeros in the origin to the start of the array\n",
-    "    if(zz!=pz):\n",
-    "        position=0\n",
-    "        for i, zero  in enumerate(z):\n",
-    "            if zero==0:\n",
-    "                z[i]=zero\n",
-    "                z[position]=0\n",
-    "                position=position+1\n",
-    "        position=0\n",
-    "        for i, pole in enumerate(p):\n",
-    "            if pole==0:\n",
-    "                p[i]=pole\n",
-    "                p[position]=0\n",
-    "                position=position+1\n",
-    "    \n",
-    "                        \n",
-    "    a1=4*fn\n",
-    "    a2=(4*fn)**2 \n",
-    "    \n",
-    "    #calculation of Second order sections\n",
-    "    if(zz==pz):\n",
-    "        if len(z)==0:\n",
-    "            if len(p)==0:\n",
-    "                return normalize(np.asarray([k,0,0,1,0,0]),cast)\n",
-    "            if len(p)==1:\n",
-    "                p0=(-1+a1/p[0])\n",
-    "                p1=(-1-a1/p[0])\n",
-    "                return normalize(np.asarray([k,k,0,p0,p1,0]),cast)\n",
-    "            if len(p)==2:\n",
-    "                p0=(a2/(p[0]*p[1])-a1/p[0]-a1/p[1]+1)\n",
-    "                p1=2-2*a2/(p[0]*p[1])\n",
-    "                p2=(a2/(p[0]*p[1])+a1/p[0]+a1/p[1]+1)\n",
-    "                return normalize(np.asarray([k,2*k,k,p0,p1,p2]),cast)\n",
-    "        if len(z)==1:\n",
-    "            if len(p)==0:\n",
-    "                z0=(-1+a1/z[0])\n",
-    "                z1=(-1-a1/z[0])\n",
-    "                return normalize(np.asarray([k*z0,k*z1,0,1,1,0]),cast)\n",
-    "            if len(p)==1:\n",
-    "                z0=(-1+a1/z[0])\n",
-    "                z1=(-1-a1/z[0])\n",
-    "                p0=(-1+a1/p[0])\n",
-    "                p1=(-1-a1/p[0])\n",
-    "                return normalize(np.asarray([k*z0,k*z1,0,p0,p1,0]),cast)\n",
-    "            if len(p)==2:\n",
-    "                p0=(a2/(p[0]*p[1])-a1/p[0]-a1/p[1]+1)\n",
-    "                p1=(2-2*a2/(p[0]*p[1]))\n",
-    "                p2=(a2/(p[0]*p[1])+a1/p[0]+a1/p[1]+1)\n",
-    "                z0=-1+a1/z[0]\n",
-    "                z1=-2\n",
-    "                z2=-1-a1/z[0]\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast)\n",
-    "\n",
-    "        if len(z)==2:\n",
-    "            z0=(a2/(z[0]*z[1])-a1/z[0]-a1/z[1]+1)\n",
-    "            z1=(2-2*a2/(z[0]*z[1]))\n",
-    "            z2=(a2/(z[0]*z[1])+a1/z[0]+a1/z[1]+1)\n",
-    "            \n",
-    "            if len(p)==0:\n",
-    "                return(normalize(np.asarray([k*z0,k*z1,k*z2,1,2,1]),cast))\n",
-    "            if len(p)==1:\n",
-    "                p0=-1+a1/p[0]\n",
-    "                p1=-2\n",
-    "                p2=-1-a1/p[0]\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast)\n",
-    "            if len(p)==2:\n",
-    "                p0=(a2/(p[0]*p[1])-a1/p[0]-a1/p[1]+1)\n",
-    "                p1=(2-2*a2/(p[0]*p[1]))\n",
-    "                p2=(a2/(p[0]*p[1])+a1/p[0]+a1/p[1]+1)\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast)\n",
-    "            \n",
-    "            \n",
-    "    elif(zz==1):\n",
-    "        if len(z)==2:\n",
-    "            z0=4*fn*(a1/z[1]-1)\n",
-    "            z1=-4*fn*(2*a1/z[1])\n",
-    "            z2=4*fn*(a1/z[1]+1)\n",
-    "            if len(p)==0:\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,1,2,1]),cast)\n",
-    "            if len(p)==1:\n",
-    "                p0=-1+a1/p[0]\n",
-    "                p1=-2\n",
-    "                p2=-1-a1/p[0]\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast)\n",
-    "            if len(p)==2:\n",
-    "                p0=(a2/(p[0]*p[1])-a1/p[0]-a1/p[1]+1)\n",
-    "                p1=(2-2*a2/(p[0]*p[1]))\n",
-    "                p2=(a2/(p[0]*p[1])+a1/p[0]+a1/p[1]+1)\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast)\n",
-    "                    \n",
-    "        elif len(z)==1:\n",
-    "            if len(p)==0:\n",
-    "                return normalize(np.asarray([k*4*fn,k*-4*fn,0,1,1,0]),cast)\n",
-    "            if len(p)==1:\n",
-    "                p0=(-1+a1/p[0])\n",
-    "                p1=(-1-a1/p[0])\n",
-    "                p2=0\n",
-    "                return normalize(np.asarray([k*4*fn,k*-4*fn,0,p0,p1,p2]),cast)\n",
-    "            if len(p)==2:\n",
-    "                p0=(a2/(p[0]*p[1])-a1/p[0]-a1/p[1]+1)\n",
-    "                p1=(2-2*a2/(p[0]*p[1]))\n",
-    "                p2=(a2/(p[0]*p[1])+a1/p[0]+a1/p[1]+1)\n",
-    "                return normalize(np.asarray([k*4*fn,0,-k*4*fn,p0,p1,p2]),cast)\n",
-    "        \n",
-    "    elif(zz==2):\n",
-    "        if len(z)==2:\n",
-    "            z0=(4*fn)**2\n",
-    "            z1=-2*(4*fn)**2\n",
-    "            z2=(4*fn)**2\n",
-    "            if len(p)==0:\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,1,2,1]),cast)\n",
-    "            if len(p)==1:\n",
-    "                p0=-1+a1/p[0]\n",
-    "                p1=-2\n",
-    "                p2=-1-a1/p[0]\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast)\n",
-    "            if len(p)==2:\n",
-    "                p0=(a2/(p[0]*p[1])-a1/p[0]-a1/p[1]+1)\n",
-    "                p1=(2-2*a2/(p[0]*p[1]))\n",
-    "                p2=(a2/(p[0]*p[1])+a1/p[0]+a1/p[1]+1)\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast) \n",
-    "            \n",
-    "        \n",
-    "    elif(pz==1):\n",
-    "        if len(p)==1:\n",
-    "            if len(z)==0:\n",
-    "                return normalize(np.asarray([k,k,0,4*fn,-4*fn,0]),cast)\n",
-    "            if len(z)==1:\n",
-    "                z0=(-1+a1/z[0])\n",
-    "                z1=(-1-a1/z[0])\n",
-    "                z2=0\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,4*fn,-4*fn,0]),cast)\n",
-    "            if len(z)==2:\n",
-    "                z0=(a2/(z[0]*z[1])-a1/z[0]-a1/z[1]+1)\n",
-    "                z1=(2-2*a2/(z[0]*z[1]))\n",
-    "                z2=(a2/(z[0]*z[1])+a1/z[0]+a1/z[1]+1)\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,4*fn,0,-4*fn]),cast)\n",
-    "        \n",
-    "        if len(p)==2:\n",
-    "            p0=a1*(a1/p[1]-1)\n",
-    "            p1=a1*(-2*a1/p[1])\n",
-    "            p2=a1*(a1/p[1]+1)\n",
-    "            if len(z)==0:\n",
-    "                return normalize(np.asarray([k,2*k,k,p0,p1,p2]),cast)\n",
-    "            if len(z)==1:\n",
-    "                z0=-1+a1/z[0]\n",
-    "                z1=-2\n",
-    "                z2=-1-a1/z[0]\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast)\n",
-    "            if len(z)==2:\n",
-    "                z0=(a2/(z[0]*z[1])-a1/z[0]-a1/z[1]+1)\n",
-    "                z1=(2-2*a2/(z[0]*z[1]))\n",
-    "                z2=(a2/(z[0]*z[1])+a1/z[0]+a1/z[1]+1)\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast)\n",
-    "                \n",
-    "                \n",
-    "                    \n",
-    "    elif pz==2:\n",
-    "        if len(p)==2:\n",
-    "            p0=(4*fn)**2\n",
-    "            p1=-2*(4*fn)**2\n",
-    "            p2=(4*fn)**2\n",
-    "            if len(z)==0:\n",
-    "                return normalize(np.asarray([1*k,2*k,1*k,p0,p1,p2]),cast)\n",
-    "            if len(z)==1:\n",
-    "                z0=-1+a1/z[0]\n",
-    "                z1=-2\n",
-    "                z2=-1-a1/z[0]\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast)\n",
-    "            if len(z)==2:\n",
-    "                z0=(a2/(z[0]*z[1])-a1/z[0]-a1/z[1]+1)\n",
-    "                z1=(2-2*a2/(z[0]*z[1]))\n",
-    "                z2=(a2/(z[0]*z[1])+a1/z[0]+a1/z[1]+1)\n",
-    "                return normalize(np.asarray([k*z0,k*z1,k*z2,p0,p1,p2]),cast)\n",
-    "                           \n",
-    "                \n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "#Filter class for use with the Servo class\n",
-    "\n",
-    "class Filter:\n",
-    "    \n",
-    "    #z are the zeros of the filter\n",
-    "    #p are the poles of the filter\n",
-    "    #k is the DC gain\n",
-    "    #desc is the description of the filter\n",
-    "    #only needed for accurate prewarping! frequency dependent and non frequency dependend part must be divided\n",
-    "    #k_freqn gain dependent on cutoff frequencies, the frequency is part of the numerator\n",
-    "    #k_freqd gain dependent on cutoff frequencies, the frequency is part of the denominator\n",
-    "    def __init__(self,z,p,k,desc,k_freqn=0,k_freqd=0):\n",
-    "        shapetest=np.asarray(0)\n",
-    "        shapetest=shapetest.shape\n",
-    "\n",
-    "        self.zeros=np.append(np.empty(0,dtype=np.complex),z)\n",
-    "        self.poles=np.append(np.empty(0,dtype=np.complex),p)\n",
-    "        self.gain=k\n",
-    "        self.k_freqn=np.asarray(k_freqn)\n",
-    "        self.k_freqd=np.asarray(k_freqd)\n",
-    "        if self.k_freqn.shape==shapetest:\n",
-    "            self.k_freqn=np.asarray([k_freqn])\n",
-    "        if self.k_freqd.shape==shapetest:\n",
-    "            self.k_freqd=np.asarray([k_freqd])\n",
-    "        self.description = desc\n",
-    "        \n",
-    "    def get_zpk(self):\n",
-    "        return [self.zeros,self.poles,self.gain]\n",
-    "    \n",
-    "    #returns the zpk representation which is used in scipy.signal\n",
-    "    def get_zpk_sig(self):\n",
-    "        return[self.zeros,self.poles,self.gain*self.calculate_gain_mp()]\n",
-    "      \n",
-    "    def get_copy(self,j=-1):\n",
-    "        if j==-1:\n",
-    "            return copy.deepcopy(self.filter)\n",
-    "        return copy.copy(self.filter[j])\n",
-    "\n",
-    "    #uses scipy.sig to return the polynomial transferfunction\n",
-    "    def polynomial_tf(self):\n",
-    "        return sig.zpk2tf(self.zeros,self.poles,self.gain*self.calculate_gain_mp())\n",
-    "    \n",
-    "    #uses scipy.sig to return the digital representation of the filter\n",
-    "    #fs is the nyquist frequency\n",
-    "    def tf2digital(self,fs):\n",
-    "        a,b = self.polynomial_tf()\n",
-    "        return sig.bilinear(a,b,fs)\n",
-    "    \n",
-    "    #calculates the gain multiplier for use with scipy sig\n",
-    "    def calculate_gain_mp(self):\n",
-    "        gainmp=1\n",
-    "        for i in range(0,self.zeros.size):\n",
-    "            if (self.zeros[i]!=0):\n",
-    "                gainmp= gainmp/np.absolute(self.zeros[i])\n",
-    "        for i in range(0,self.poles.size):\n",
-    "            if(self.poles[i]!=0):\n",
-    "                gainmp=gainmp*np.absolute(self.poles[i])\n",
-    "        for i, p in enumerate(k_freqd):\n",
-    "            if p!=0:\n",
-    "                gainmp=gainmp/p\n",
-    "        for i, p in enumerate(k_freqn):\n",
-    "            if p!=0:\n",
-    "                gainmp=gainmp*p\n",
-    "        return gainmp\n",
-    "    \n",
-    "    #prewarps the poles and zeros, and the frequency dependent gain\n",
-    "    def prewarp(self,fn):\n",
-    "        warp_p=np.empty(len(self.poles),dtype=complex)\n",
-    "        warp_z=np.empty(len(self.zeros),dtype=complex)\n",
-    "        gain=self.gain\n",
-    "        for i, z in enumerate(self.zeros):\n",
-    "            if z==0:\n",
-    "                warp_z[i]=0\n",
-    "            else:\n",
-    "                warp_z[i]=4*fn*(z/abs(z)*np.tan(abs(z/fn)*0.5*np.pi))\n",
-    "        for i, p in enumerate(self.poles):\n",
-    "            if p==0:\n",
-    "                warp_p[i]=0\n",
-    "            else:\n",
-    "                warp_p[i]=4*fn*(p/abs(p)*np.tan(abs(p/fn)*0.5*np.pi))\n",
-    "\n",
-    "        \n",
-    "        for i, p in enumerate(self.k_freqn):\n",
-    "            if p!=0:\n",
-    "                gain= gain*4*fn*(p/abs(p)*np.tan(abs(p/fn)*0.5*np.pi))\n",
-    "        for i, p in enumerate(self.k_freqd):\n",
-    "            if p!=0:\n",
-    "                gain=gain/(4*fn*(p/abs(p)*np.tan(abs(p/fn)*0.5*np.pi)))\n",
-    "        return warp_z,warp_p,gain\n",
-    "    \n",
-    "    def sos(self,fn,cast=False):\n",
-    "        z,p,k= self.prewarp(fn)\n",
-    "        return bilinear(z,p,k,fn,cast)\n",
-    "    \n",
-    "    def out_filter(self,fn):\n",
-    "        sos=self.sos(fn,True)\n",
-    "        point=np.empty(6,dtype=int)\n",
-    "        leading=np.empty(6,dtype=int)\n",
-    "        for i, p in enumerate(sos):\n",
-    "            if p==0:\n",
-    "                point[i]=1\n",
-    "                leading[i]=1\n",
-    "            elif np.log10(np.absolute(p))<0:\n",
-    "                point[i]=-int(math.floor(np.log10(np.absolute(p))))+12\n",
-    "                leading[i]=1\n",
-    "            else:\n",
-    "                point[i]=10\n",
-    "                leading[i]=int(math.ceil(np.log10(np.absolute(p))))\n",
-    "        \n",
-    "        return(self.description+',{num0:{lead0}.{width0}f},{num1:{lead1}.{width1}f},{num2:{lead2}.{width2}f},{num3:{lead3}.{width3}f},{num4:{lead4}.{width4}f},{num5:{lead5}.{width5}f}'.format(num0=sos[0], width0=point[0], lead0=leading[0],num1=sos[1], width1=point[1], lead1=leading[1],num2=sos[2], width2=point[2], lead2=leading[2],num3=sos[3], width3=point[3], lead3=leading[3],num4=sos[4], width4=point[4], lead4=leading[4],num5=sos[5], width5=point[5], lead5=leading[5]))\n",
-    "                \n",
-    "            \n",
-    "        "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "\n",
-    "#Servo class, which has zeros,poles and gain at f=0 as parameters. The frequencies are calculated in Hz. The class mostly uses\n",
-    "#scipy.signal methods to plot filters or change their representation, zero pole gain or polynomial.\n",
-    "class Servo:\n",
-    "    \n",
-    "    def __init__(self):\n",
-    "        self.gain=1\n",
-    "        self.zeros=np.empty(0,dtype=np.complex)\n",
-    "        self.poles=np.empty(0,dtype=np.complex)\n",
-    "        self.filter=np.empty(0)\n",
-    "        self.freqn=np.empty(0)\n",
-    "        self.freqd=np.empty(0)\n",
-    "        self.gainmodule=1\n",
-    "        \n",
-    "        \n",
-    "    \n",
-    "    #adds zeros and poles to the transferfunction and reduce the fractions. The gain is multiplied with the new gain.\n",
-    "    #z array with the zeros\n",
-    "    #p array with the poles\n",
-    "    #gain mit dem Multipliziert werden soll\n",
-    "    def add(self,z,p,k,desc='undescribed',freqn=0,freqd=0):\n",
-    "        self.filter=np.append(self.filter, Filter(z,p,k,desc,freqn,freqd))\n",
-    "        self.gain=self.gain*k\n",
-    "        self.zeros=np.append(self.zeros,z)\n",
-    "        self.poles=np.append(self.poles,p)\n",
-    "        self.reduce_frac()\n",
-    "        self.freqn=np.append(self.freqn,freqn)\n",
-    "        self.freqd=np.append(self.freqd,freqd)\n",
-    "        return self.get_zpk()\n",
-    "    \n",
-    "    #removes the filter with the index of j\n",
-    "    def remove_filter(self,j):\n",
-    "        a=self.filter[j]\n",
-    "        self.zeros=np.append(self.zeros,a.poles)\n",
-    "        self.poles=np.append(self.poles,a.zeros)\n",
-    "        self.gain=self.gain/a.gain\n",
-    "        self.filter=np.delete(self.filter,j)\n",
-    "        self.reduce_frac()\n",
-    "    \n",
-    "    #reduces the fraction of the filter\n",
-    "    def reduce_frac(self):\n",
-    "        deletez=np.empty(0,dtype= int)\n",
-    "        for i, z in enumerate(self.zeros):\n",
-    "            for j, p in enumerate(self.poles):\n",
-    "                if (self.poles[j]==self.zeros[i]):\n",
-    "                    deletez=np.append(deletez,i)\n",
-    "                    self.poles=np.delete(self.poles,j)\n",
-    "                    break\n",
-    "                elif((np.abs(self.poles[j]-self.zeros[i])/(np.abs(self.poles[j])+np.abs(self.zeros[i])))<1e-4):\n",
-    "                    deletez=np.append(deletez,i)\n",
-    "                    self.poles=np.delete(self.poles,j)\n",
-    "                    break\n",
-    "        self.zeros=np.delete(self.zeros,deletez)\n",
-    "   \n",
-    "        \n",
-    "    #multiplies the gain with the value of k    \n",
-    "    def add_gain(self,k):\n",
-    "        self.gain=self.gain*k\n",
-    "        self.gainmodule= self.gainmodule*k\n",
-    "        \n",
-    "    def get_gain(self):\n",
-    "        return self.gain\n",
-    "    \n",
-    "    def get_poles(self):\n",
-    "        return self.zeros\n",
-    "    \n",
-    "    def get_zeros(self):\n",
-    "        return self.zeros\n",
-    "    \n",
-    "    def get_zpk(self):\n",
-    "        return [self.zeros,self.poles,self.gain]\n",
-    "    \n",
-    "    #returns the zpk representation which is used in scipy.signal\n",
-    "    def get_zpk_sig(self):\n",
-    "        return[self.zeros,self.poles,self.gain*self.calculate_gain_mp()]\n",
-    "    \n",
-    "    def get_filter_number(self):\n",
-    "        return self.filter.size\n",
-    "      \n",
-    "    def get_filter(self,j=-1):\n",
-    "        if j==-1:\n",
-    "            return copy.deepcopy(self.filter)\n",
-    "        return copy.copy(self.filter[j])\n",
-    "    \n",
-    "    #adds a first order highpass filter with corner frequency fc\n",
-    "    def order1highpass(self,fc):\n",
-    "        self.add(0,-fc,1,'first order Highpass filter; cutoff frequency: '+ str(fc)+ ' Hz',0,fc)\n",
-    "    \n",
-    "    #adds a 2nd Order Lowpass filter with cutoff frequency fc and Quality factor Q\n",
-    "    def order2lowpass(self,fc,Q):\n",
-    "        poles=[-fc/(2*Q)+((fc/(2*Q))**2-fc**2)**0.5,-fc/(2*Q)-((fc/(2*Q))**2-fc**2)**0.5]\n",
-    "        self.add([],poles,1, 'second order lowpass filter; cutoff frequency: ' + str(fc) + ' Hz; Q factor: '+ str(Q))\n",
-    "    \n",
-    "    #adds an integrator with the corner frequency fc and stop frequency fstop\n",
-    "    def integrator(self,fc, fstop=None,k=None):\n",
-    "        if k is None:\n",
-    "            \n",
-    "            if (fstop is not None):\n",
-    "                self.add(-fc,-fstop,fc/fstop, 'integrator from '+str(fstop)+' Hz to ' + str(fc)+' Hz' )\n",
-    "            else:\n",
-    "                self.add(-fc,-0.001*fc,1000,'integrator from '+str(0.001*fc)+' Hz to ' + str(fc)+' Hz')\n",
-    "        else:\n",
-    "            if (fstop is not None):\n",
-    "                self.add(-fc,-fstop,k, 'integrator from '+str(fstop)+' Hz to ' + str(fc)+' Hz and set gain:' +str(k))\n",
-    "            else:\n",
-    "                self.add(-fc,-0.001*fc,k,'integrator from '+str(0.001*fc)+' Hz to ' + str(fc)+' Hz and set gain:' +str(k))\n",
-    "    #adds a differentiator with the corner frequency fc and cutoff frequency fstop\n",
-    "    def differentiator(self,fc,fstop=None,k=None):\n",
-    "        if k is None:\n",
-    "            if(fstop is not None):\n",
-    "                self.add(-fstop,-fc,fstop/fc, 'differentiator from '+str(fstop)+' Hz to ' + str(fc)+' Hz')\n",
-    "            else:\n",
-    "                self.add(-0.001*fc,-fc,1/1000, 'differentiator from '+str(fstop)+' Hz to ' + str(fc)+' Hz')\n",
-    "        else:\n",
-    "            if(fstop is not None):\n",
-    "                self.add(-fstop,-fc,k, 'differentiator from '+str(fstop)+' Hz to ' + str(fc)+' Hz and set gain:'+str(k))\n",
-    "            else:\n",
-    "                self.add(-0.001*fc,-fc,k, 'differentiator from '+str(fstop)+' Hz to ' + str(fc)+' Hz and set gain:'+str(k))\n",
-    "    \n",
-    "    #adds a standard notch filter at fc with the quality factor Q\n",
-    "    #fc is the stop frequency\n",
-    "    #Q is the quality factor\n",
-    "    def notch(self,fc,Q):\n",
-    "        poles=[-fc/(2*Q)+((fc/(2*Q))**2-fc**2)**0.5,-fc/(2*Q)-((fc/(2*Q))**2-fc**2)**0.5]\n",
-    "        self.add([fc*1j,-fc*1j],poles,1, 'notch filter;' +str(fc) +' Hz; Q factor:' + str(Q))\n",
-    "                     \n",
-    "    \n",
-    "    \n",
-    "    #function mostly used for quick plotting of the transfer function, added for testing purpose\n",
-    "    def plot_servo(self,freq):\n",
-    "        pylab.figure( figsize=(11,11) )\n",
-    "        tup1=[self.zeros,self.poles,self.gain*self.calculate_gain_mp()]\n",
-    "        a,g,p=sig.bode(tup1,w=freq)\n",
-    "        ax1=plt.subplot(211)     \n",
-    "        ax1.set_xlabel('Frequency [Hz]')\n",
-    "        ax1.set_ylabel('Amplitude response [dB]')\n",
-    "        plt.grid()\n",
-    "        plt.semilogx(freq,g)\n",
-    "        plt.axhline(y=0, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "        ax2=plt.subplot(212)\n",
-    "        ax2.set_xlabel('Frequency [Hz]')\n",
-    "        ax2.set_ylabel('phase [°]')\n",
-    "        plt.semilogx(freq,p)\n",
-    "        plt.grid()\n",
-    "        plt.suptitle('Servo Transferfunction')\n",
-    "        plt.savefig('Servo.png')\n",
-    "        plt.show()\n",
-    "        plt.close(1)\n",
-    "        \n",
-    "\n",
-    "    #calculates the gain multiplier for the use with scipy.signal\n",
-    "    def calculate_gain_mp(self):\n",
-    "        gainmp=1\n",
-    "        for i in range(0,self.zeros.size):\n",
-    "            if (self.zeros[i]!=0):\n",
-    "                gainmp= gainmp/np.absolute(self.zeros[i])\n",
-    "        for i in range(0,self.poles.size):\n",
-    "            if(self.poles[i]!=0):\n",
-    "                gainmp=gainmp*np.absolute(self.poles[i])\n",
-    "        for i, p in enumerate(self.freqn):\n",
-    "            if p!=0:\n",
-    "                gainmp=gainmp*p\n",
-    "        for i, p in enumerate(self.freqd):\n",
-    "            if p!=0:\n",
-    "                gainmp=gainmp/p\n",
-    "        return gainmp\n",
-    "        \n",
-    "    #applies the servo function to a measured/calculated transfer function\n",
-    "    #frequencies at which the gain and phase was measured\n",
-    "    #measured gain\n",
-    "    #measured phase\n",
-    "    def apply_servo(self,freq,gain,phase):\n",
-    "        tup1 = [self.zeros,self.poles,self.gain*self.calculate_gain_mp()]\n",
-    "        f,g,p=sig.bode(tup1, w=freq)\n",
-    "        phase_2=np.add(phase,p)\n",
-    "        gain_2=np.add(gain,g)\n",
-    "        return freq,gain_2,phase_2   \n",
-    "    \n",
-    "    #uses scipy.sig to return the polynomial transferfunction\n",
-    "    def polynomial_tf(self):\n",
-    "        return sig.zpk2tf(self.zeros,self.poles,self.gain*self.calculate_gain_mp())\n",
-    "            \n",
-    "    #calculates the sos of the filters\n",
-    "    #fn is the nyquist frequency\n",
-    "    #cast says if the output should be casted to float or stay complex\n",
-    "    def sos(self,fn,cast=False):\n",
-    "        if len(self.filter)==0:\n",
-    "            return np.asarray([[1.,0.,0.,1.,0.,0.]])\n",
-    "        sos= np.asarray([self.filter[0].sos(fn)])\n",
-    "        for i in range(1,len(self.filter)):\n",
-    "            sos= np.append(sos, np.asarray([self.filter[i].sos(fn,cast)]),axis=0)\n",
-    "        return np.append(sos, np.asarray([[float(self.gainmodule),0.,0.,1.0,0.,0.]]),axis=0)\n",
-    "    \n",
-    "    #writes the second order secions of the filter in a textfile\n",
-    "    #fn is the nyquist frequency\n",
-    "    #name is the name of the textfile\n",
-    "    def write_filter(self,fn, name):\n",
-    "        f=open(name,'w+')\n",
-    "        point=1\n",
-    "        leading=1\n",
-    "        if self.gainmodule==0:\n",
-    "            point=1\n",
-    "            leading=1\n",
-    "        elif np.log10(np.absolute(self.gainmodule))<0:\n",
-    "            point=-int(math.floor(np.log10(np.absolute(self.gainmodule))))+12\n",
-    "            leading=1\n",
-    "        else:\n",
-    "            point=10\n",
-    "            leading=int(math.ceil(np.log10(np.absolute(self.gainmodule))))\n",
-    "        f.write('Nyquist frequency: {} Hz\\n'.format(fn))\n",
-    "        f.write('gain,{k:{lead}.{pnt}f}\\n'.format(k=self.gainmodule, lead=leading, pnt =point))\n",
-    "                \n",
-    "        for i, p in enumerate(self.filter):\n",
-    "            f.write(p.out_filter(fn)+'\\n')\n",
-    "        f.close()\n",
-    "    \n",
-    "    def calculate_gmargin(self,freq,gain,phase):\n",
-    "        freq,gain,phase= self.apply_servo(freq,gain,phase)\n",
-    "        gmargin=False\n",
-    "        for i in range(100,freq.size):\n",
-    "            if(phase[i]<=-180):\n",
-    "                gmargin=gain[i-1]\n",
-    "                #print(freq[i-1])\n",
-    "                break\n",
-    "        return gmargin,(freq[i-1]),i\n",
-    "    \n",
-    "    def calculate_pmargin(self,freq,gain,phase):\n",
-    "        freq,gain,phase= self.apply_servo(freq,gain,phase)\n",
-    "        pmargin=False\n",
-    "        for i in range(0,freq.size):\n",
-    "            if (gain[i]<=0):\n",
-    "                pmargin=180+phase[i-1]\n",
-    "                #print(freq[i-1])\n",
-    "                break\n",
-    "        return pmargin,freq[i-1],i\n",
-    "    \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\sgrebien\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:3: ComplexWarning: Casting complex values to real discards the imaginary part\n",
-      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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Y2LdvH+XLlw/KscRHfR586vPgC9c+z8xxDFuSzcR1uVSNNa5sWpZmicFZ/SlQRdHne7Id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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xc37bd30>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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es4yMjHL7LDk97QfP4G37Yc9xF1PW5rAz3UWPugFc2cyQu3sdibvP/FpP5m37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\nRK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xc37b400>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "S2=Servo()\n",
-    "S2.order1highpass(1)\n",
-    "S2.integrator(10,1000)\n",
-    "S2.order2lowpass(1000,0.707)\n",
-    "S2.add_gain(10)\n",
-    "S2.write_filter(100000,'test1.txt')\n",
-    "S2.plot_servo(np.logspace(-1,5,100000))\n",
-    "pylab.figure(figsize=(11,11))\n",
-    "sos=S2.sos(100000)\n",
-    "w, h = sig.sosfreqz(sos, np.linspace(0.000001*np.pi,0.5*np.pi,1000000))\n",
-    "plt.subplot(2, 1, 1)\n",
-    "db = 20*np.log10(np.abs(h))\n",
-    "plt.semilogx(w/np.pi, db)\n",
-    "plt.axhline(y=0, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "plt.grid(True)\n",
-    "plt.ylabel('Gain [dB]')\n",
-    "plt.title('Frequency Response')\n",
-    "plt.subplot(2, 1, 2)\n",
-    "plt.axhline(y=0, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "plt.semilogx(w/np.pi, np.degrees(np.unwrap(np.angle(h))))\n",
-    "plt.grid(True)\n",
-    "plt.ylabel('Phase [deg]')\n",
-    "plt.xlabel('Normalized frequency (1.0 = Nyquist)')\n",
-    "plt.show()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/unordered/Servo_Design/Vergleich Gain Modell und Analog.png b/unordered/Servo_Design/Vergleich Gain Modell und Analog.png
deleted file mode 100644
index a78403800a7f1339230a45f2cf7c6884cf998ed0..0000000000000000000000000000000000000000
Binary files a/unordered/Servo_Design/Vergleich Gain Modell und Analog.png and /dev/null differ
diff --git a/unordered/Servo_Design/Vergleich Phase Modell und Analog.png b/unordered/Servo_Design/Vergleich Phase Modell und Analog.png
deleted file mode 100644
index 4b8b6510c2a500bd14bc5168a4f70858e1dd01a1..0000000000000000000000000000000000000000
Binary files a/unordered/Servo_Design/Vergleich Phase Modell und Analog.png and /dev/null differ
diff --git a/unordered/Servo_Design/int123_servo1.csv b/unordered/Servo_Design/int123_servo1.csv
deleted file mode 100644
index 9dbb70fac60f309d26277102f12cc6589537b02e..0000000000000000000000000000000000000000
--- a/unordered/Servo_Design/int123_servo1.csv
+++ /dev/null
@@ -1,472 +0,0 @@
-#, Frequency (Hz), Amplitude (Vpp), Gain (dB), Phase (�)
-1,20.0,0.0200,66.93,-54.61
-2,20.4,0.0200,67.63,-52.00
-3,20.9,0.0200,70.22,-39.63
-4,21.4,0.0200,70.12,-31.78
-5,21.9,0.0200,70.73,117.78
-6,22.4,0.0200,71.83,-27.86
-7,22.9,0.0200,72.76,-15.78
-8,23.4,0.0200,69.88,149.18
-9,24.0,0.0200,67.25,-91.68
-10,24.5,0.0200,71.18,14.49
-11,25.1,0.0200,69.18,168.04
-12,25.7,0.0200,68.70,148.10
-13,26.3,0.0200,70.37,69.75
-14,26.9,0.0200,73.19,-69.99
-15,27.5,0.0200,67.73,-58.52
-16,28.2,0.0200,67.52,-145.49
-17,28.8,0.0200,66.05,-109.92
-18,29.5,0.0200,60.21,23.87
-19,30.2,0.0200,64.91,-19.77
-20,30.9,0.0200,62.15,-1.31
-21,31.6,0.0200,64.55,-37.23
-22,32.4,0.0200,71.24,122.63
-23,33.1,0.0200,71.71,107.58
-24,33.9,0.0200,72.20,74.91
-25,34.7,0.0200,66.91,11.63
-26,35.5,0.0200,63.21,-63.84
-27,36.3,0.0200,67.74,186.48
-28,37.2,0.0200,61.55,4.07
-29,38.0,0.0200,60.75,-10.11
-30,38.9,0.0200,62.46,-65.98
-31,39.8,0.0200,59.00,-60.41
-32,40.7,0.0200,56.46,15.49
-33,41.7,0.0200,57.29,124.85
-34,42.7,0.0200,58.10,75.04
-35,43.7,0.0200,55.75,-88.91
-36,44.7,0.0200,54.95,-103.37
-37,45.7,0.0200,59.86,172.13
-38,46.8,0.0200,53.86,-9.33
-39,47.9,0.0200,56.38,93.83
-40,49.0,0.0200,56.38,82.42
-41,50.1,0.0200,56.34,-5.36
-42,51.3,0.0200,55.13,-149.26
-43,52.5,0.0200,51.92,-34.59
-44,53.7,0.0200,55.38,-41.63
-45,55.0,0.0200,55.39,-63.65
-46,56.2,0.0200,52.02,-74.54
-47,57.5,0.0200,56.61,144.93
-48,58.9,0.0200,54.01,-32.18
-49,60.3,0.0200,57.35,79.37
-50,61.7,0.0200,53.30,76.57
-51,63.1,0.0200,52.21,183.15
-52,64.6,0.0200,64.80,40.13
-53,66.1,0.0200,72.05,-62.45
-54,67.6,0.0200,52.77,-122.74
-55,69.2,0.0200,54.45,42.54
-56,70.8,0.0200,56.13,-121.43
-57,72.4,0.0200,56.62,32.43
-58,74.1,0.0200,56.74,-78.38
-59,75.9,0.0200,60.22,-159.66
-60,77.6,0.0200,54.85,75.48
-61,79.4,0.0200,63.82,132.70
-62,81.3,0.0200,60.46,-40.90
-63,83.2,0.0200,60.35,28.19
-64,85.1,0.0200,59.35,-76.65
-65,87.1,0.0200,58.86,-15.52
-66,89.1,0.0200,64.79,102.21
-67,91.2,0.0200,56.65,-12.75
-68,93.3,0.0200,61.81,-107.97
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-465,870963.6,0.0200,-34.82,17.70
-466,891250.9,0.0200,-43.69,153.37
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diff --git a/unordered/Servo_Design/open_loop_digital.ipynb b/unordered/Servo_Design/open_loop_digital.ipynb
deleted file mode 100644
index 2b0c4f523acb36d1d738d9ba49f681720a2f8cec..0000000000000000000000000000000000000000
--- a/unordered/Servo_Design/open_loop_digital.ipynb
+++ /dev/null
@@ -1,174 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Messung des open loop gains des Servos\n",
-    "## Design\n",
-    "- gain -41dB\n",
-    "- notch 65k, 3\n",
-    "- lowpass 15k,0.707\n",
-    "- integrator 400\n",
-    "- integrator 2k\n",
-    "- integrator 22k4\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt \n",
-    "import pylab\n",
-    "from Servo import *\n",
-    "from nqlab import*"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "Servo1=Servo()\n",
-    "Servo1.add_gain(0.0088)\n",
-    "Servo1.add_gain(2)\n",
-    "Servo1.notch(65000,3)\n",
-    "Servo1.order2lowpass(15000,0.707)\n",
-    "Servo1.integrator(400)\n",
-    "Servo1.integrator(2000)\n",
-    "Servo1.integrator(22400)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data=io.read('tf2.csv')\n",
-    "data2=io.read('open_loop_int123_1.csv')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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FAHXq1EWrLRgmXbp0ybzlZP36je57LU9PT+bOnYWdnT03b96gXr0G5udSUpJJSkpk0qR3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\n57Kzb3w2+rUKCVGZNCmf9ev1/PCDkZQUHdu36wkIUMnMVDh1SiEqyvF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CTfj6gq+vysmT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-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xd1b34a8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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7Ojp6/Bk0y6Y7rWx0p250vmA7DRMQy4+wgvPZtWxmS8wSBJFdxN7oXq838bxe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\n/8S35GKWgbFKAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xc6993c8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "f,g,p=Servo1.apply_servo(data.index.values,data.values.transpose()[1],data.values.transpose()[2])\n",
-    "pylab.figure(figsize=(11,5))\n",
-    "plt.semilogx(f,g,color='blue',label='designter Servo')\n",
-    "plt.semilogx(data2.index.values,data2.values.transpose()[1],color='black',label='digitaler Servo')\n",
-    "plt.legend()\n",
-    "plt.xlabel('Frequenz (Hz)')\n",
-    "plt.ylabel('gain (dB)')\n",
-    "plt.grid()\n",
-    "plt.show()\n",
-    "plt.close()\n",
-    "pylab.figure(figsize=(11,5))\n",
-    "plt.semilogx(f,p-180,color='blue',label='designter Servo')\n",
-    "plt.semilogx(data2.index.values,data2.values.transpose()[2],color='black',label='digitaler Servo')\n",
-    "plt.ylabel('Phasenverzögerung (°)')\n",
-    "plt.xlabel('Frequenz (Hz)')\n",
-    "plt.grid()\n",
-    "plt.legend()\n",
-    "plt.show()\n",
-    "plt.close()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Beobachtung\n",
-    "Zu erkennen, ist die deutlich abweichende Phasenverzögerung bei hohen frequenzen, bei 10 kHz hat der Digitale Servo eine um 30° größere phasenverzögerung als im Design, dennoch lief der Servo stabil über eine Dauer von einer Stunde.\n",
-    "Um den Servo mit dem analogen zu vergleichen wird die Phasenverzögerung im Vergleich geplottet."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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ATB5XDXmkfK6T8lHyHMsw+qsAFD7/mdTt5Xjk51ZqzqYmmxoa/YWqbIbJZjxn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Kv05dLo+OwSbUUxrh60oDc3EfZGd120UjG2yJdzsKxG9/r05Vge4oi6v3PyyTZP3jST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7u1t5684U2AyYzSDd2ShaT7VfB7j8z92LOQwwnxVgs+ozm65pNvDZ9ACtfj7SQWguRbY7AY+K\nv60Y6yMvBnyp+5/eQYipTd1JphTYNE2EcNK28XwvVJoIhAC2GD1kE8K9JE4gpKvRMQ2lRq9Po4Np\neGr8CQU2Z1caffaMdAeGXrOp+6rp1jbe6jVseewZaOCJ6CUTGCPDIo2uCYSGh4dxXZe+vnk+2NTT\n6GJfMo3eKA0zlg+8v6Spe6g1Yos+m54nfDY7OjpIpzOM+ibzrkFQs2nbQfog8kOXk1u1WmV0dISe\nnl7N1N1SNZsGkEnV/7iD8/kQK1c+wyOP/FWATSeBaxhIfmKCMLOps7ghsOnUg0054YeAoMYEesl4\nU3cIQKZeNya3E9R/2kxa25nZlGl01xUPMrYTXygfCcVs6obX/rWSP+3fg4msXbPZjlkWK1YEYLOr\nq1uBzCef3DAj2/fUs/fU9ZGB9VHj7Yn1N9PR8RA33LQStyOPuVGm0YVAyLOdxj6bmuhlztZsAtm+\noMGFGcdsxj1kWzrIFP/L+dFyZKarfjUvpYFN6cfiOEqw6iWbg81/nnw6PYsF2BQdhKSpe7xASK/Z\n1AVC4p8XtKuUNZtuO43eNH73u99x+umnq9d33nknJ5xwAieddBIXXnghIJ4aP/OZz3DiiSfy1re+\nlSeemJmn0W0NvRg8qPkzQ2DCtu2GQBOARNJXo4d9NmVryk7foVxPowfgLeggFBeW46g+5pLZTKU0\n1tXSahcbTEA6s5lKpclmswz76fuQQMgK0ujRp0jJME5MFCmVSqGaTayA2QQwYhjW3t4+/68xPvrR\n/wEepOYzqTXDUGn0aM2m3u9X/1uVNGjnLY7Z9EI+m+K8HXDoKzn00LDlkASZWa1sIcps1pYu4xn/\nOthuNZu2DZWKcAhIpwV7PQ2wGXpP+05lfVjb1L0dsy2WLFnK/vsfwPr1B9LVJTI/PT09M3YvadXU\nXf+seard9Md4F7fdZjEybxcsXyBUdU0ySZueefOb+2zWWR81tz6bjZHrDO4bhqbQVtEkja7S6ZqL\nStOaTY3ZNPynC8+yxRwLDZlN2bJyS89qqi9bD4TT6DIxFgabFuk0TE4aVHMFakmxkHRpMrSuR47j\nG9G7pbYavVGcffbZfPnLXw714P7sZz/Ll7/8Za688kruuusu7rvvPn7/DL1ThgAAIABJREFU+99T\nLpe56qqrOP300znvvPO25zDrQk+jN+ogNNVTpJdwAjV6jDebbuA+Pj5GNptVfWynEgjZtsPjcqzE\npPjj7IAiYZqGX7M5QTKZJJfLMeynql0CsOmZVlDgUlezKV4PDQ0C0N3dE2E2Rc0mEJvOD8BmAOKu\n2felFD/68RDYjNZs6v1+LZ3FdaQdVb31UQhs5jqUf6hkNt/8rlNZvXpNaHwBsxmk0V/60v14xSsO\nU2Mf/vHPucQXJWyv1nCeban6Si+TxXPs+sL5uPWyufo3426I7ZrNdsyysG2ba6+9nqOOejVr1uzO\ny162nt12W/sC1mw+P+sjucy8efdSrRrckDpKCYSqroVjeZgpn7CoH0yoDjGug9BcCckKgs9sRs9p\nU4GQEfyv7gPirdg0elpjNo2A2ZQtm+N6o0PAbA4OBteEDjZNE7LGOM+yEJMa89nkM5vi86Fj38LA\nz38LBF+rZWrtKqVAqDYxq9Lo2xVs7rvvvpx55pnq9djYGOVymaVLl2IYBgcffDA33XQTf//73znk\nkEMA2Hvvvbn33nu35zDrIs76yDQtTFN0xbEsq+lkAwTMZq2mpdGD05/L6WAzPo3eGGzaPCbHigTC\nehpdgs3GoME0hQ3T5OQk6XSaXK6DId+4vWaAK3+otl6zGT5mySpKK6fe3jCzmUoFzGZcalZ66UGQ\nGn9o8RIqB7y8Lo3eUs2mKgivT6PrJRCjF13K+KfOBIKaTWJSJJLZ1NPoe++9Lz/96TWBWMwR5u6J\nRGLqa2KmQu8Qlcm0bH0Um9eLu0G1wWY7ZnF87nPn8Mtf/palS5fx6KMPc+KJbwi1styWkNkuOfc8\nX+sj+dm8eY+QTHr8sXIIpt/bveqZWKaLl8lhjI/XryyRTB2zOffS6Ll8MGeJdpVRgVD9MauazZD1\nkd8O0vYV3nECoWR9Gt1zNGazQU2+ZDYHBnyCxgv7bALkTEGWLOMJElTANEmnfU2Cl6G6YqUaqqjZ\nJBAI+cDYqZXaAqGf/vSnfP/73w+9d8455/Ca17yGW265Rb03Nib8JGVks1meeuqpuvelkEYHFblc\nMsRovZCRSIj9dHVlKRQEq9XRkaazM0MymaRcLtPZ2dySw8plMKoVQf2nEnR2ZshkgvqTvj7RRsxx\noFgcp6enk+5uAa88T9RoFAqZ2P3kcmkFNucDG1MJOjuD8+ekJRCyG47TcWwsy2ByskQ+n6Onp5P7\nfEa3hoHpg8NcZxbL355hWaHtyXMzOSkmxMWL+xXYtBMOhUKHApuZjizJyFhWrAiU6V1dYvyZTJLO\nzgyDphlKo5fLk2rfHR3Bdnp7u9T7pj+DZHIpUv57EoymUqlg7Pvvo9Y3/HOe7SmQiYyvu7vgH2e+\n6fedTidJJBJTXhMzFWZOs2Tq68LMpuu+m0ZRvexy2H03tazRES4F8UyTzu4YBrRBWJa53Y67Hds3\nZvt3u3r1Sq68cpA//ekPPP74o9x11z313dhajGJRzN2ZjJhjrCa/N8efOxvN3/IzgHze4sAD4cb7\n12FufZbOfArPM3FMF7u3G+OB5+q2YTkWhmXi+OCnt6+Lzs5O1qxZ2dL3NZu+1955WjYRl0QqPM8a\n+frj6OzOQSql5rZEMoHhY4d8QWyvqytBZ2eYYDD6OhXYTDgC6GXyWSiIe0Qin409bzLxNTGRoLPT\nUQ3aMhmHzk5xLXRYA2yq9bISIcJMpJP09MiSrLRK6+dyCSxLYGjTFtdYwbd/StYmSGRSTb+7nem7\nfUHA5gknnMAJJ5ww5XK5XE61ZgQYHx8nn89TKpVC77uuW5eSHBubZHvFxIRIXYyMlBgfF3+XSlWG\nhookEglc12VoqNhsE+QwSZZK1EplvKzD8FCRSiUoJ0j6NRpbt44wPj6OZSUZHZ309yX+Hxsrx+6n\nWvUU2NwFeLrq4rrBY1TZ341n2w3H6XkG5XKVUqmEYdjYdhKZqK54LlhiUh0dr5CzHBKAhxHaXqkk\nQPEzz4gncsdJi36+rkvFBc+zFNgsVT0mImNJpQKLkslJsWS5LM6tG0mjF4tFte9yOTiPXV3z1Ptd\npokNFCdrlPz39ML+uHNh9fTT5TgMF/pwI5+bphQDJZt+355nkEgkprwmZirSVU+dm3Fs7PkLSfQv\nam3/Rx8n/veXTU3W6NA/d5xpHUdnZ2a7HXc7tm/M9u923jzhX7lu3T7cddcdfOlLF/Af//Gf27St\noSFxf9Ln8EbnRpZhjY1NNlxG3lfAZPfdK3z3xgXUqh7Djz5FxTWxLJfJdJbE4GDdNjomKzgYVKsu\nSUTa/f77H8c0zZa+r9n0vVqJQI1veDUmqy5j2tidYoXOyDpDo5NQctVn5aqL44EFVCrivFerkwwN\nhZX+dgVhpg7U/PKFYtnFshwywKRrMt7gvGWzOZ55psrQ0KRvV9xBuVxhaEhsJ2uK9VbxMACTVRfX\nnQTSPPfcBIJryzExUcYwEhiGh+uJa2x+dpDXci0H1P7KZG3/0PFHY3t/t319HQ0/26E8ey6Xw3Ec\nnnzySTzP48Ybb2S//fZj33335c9//jMgBESrV7fmrfZCRVzNpvw/kUi2ZDHhOQkoV0Jq9LiazeHh\nITzPi6TRm3cQchyHHwNjqRSX+WPTPUCVrU8LaXRZs5nN5pASnKrrBYIeTY0eVTzL8co0ekdHPkjB\nWqKDUFCzWZ+m7tQsnGRpgvLujAiEZHckMaTgQWTJkoAdDXw269PojZTitd12Z8uGjbi+T58ecWn0\nuLAse/sp0SGURieTofihjzD0/1q3idEj+p22bY/aMVfi4IMP5fDDj+Tyy69gn3325Q9/uH6btxUV\nCCmTy5hoLY0uBSsOa9fWmKzaPMJKrI3PUPVMbMPFyxcwR0bqV460q8SfN7dbGc92jFynNpe7cWn0\nqQVCugG+TKPHVQrppu4qjW7bQc1mk/KiNWtcbrkl6B4ExKbRJdgUHYTEn8WioUgRWR1hmsHcnEm5\nXMvRrPYeaqvRpxNnnXUWH/nIRzj++ONZu3Yt69at48gjjySRSHDSSSdx7rnn8olPfGKHjtHzPPXD\njaoPE4kW0/nJJEZ5Eip6u8pgvY4OATYHB4W4RgiExHKBGj3+67Ism2eBsz7wIe5GCoTCPpLAFAIh\nk0m/RjOdTpPN5hSzWfW8oEOSNbWpuzyGfD5PTSnhA+sjiFejmyFQKIzp5TnwDBMJn0946zv40Y+u\nrtsvwKJFAdhU3ZJifDabKsUbTCJSGKSr0eOi7vy/0KF9r142J453Wyeh6GTdtj1qxxyJ/v6FXHnl\nz1i8eAkve9l67rzzdlUPP92I9kZvxfqolWUSCYe1a8UseTd7YT77DFXXwjRdvEIBozheb38kBULK\nZ3OH39ZfsMjkI2r0qKCxWbtK/X//VPm3XQqFeoGQl8kEanRJk2gdhLy4Qk8/jjmmwl13WTzyiKHS\n6GGwKdhGmUbHNFTNZqlEaB2FjbWHiabHu5PGdr+TrF+/nvXr16vXe++9Nz/5yU9Cy5imyec+97nt\nPbSG4XmuAinRiSOZTLSk+vMSCYxKRXR5serBZt432B4cFKygsD4S+5iqg5CsCZJsZp1AaIq+7WId\nizHf3Fuq0SWzWfHcoPe7ZUIDU/c4sOk6srOSNaX1UXhbJl//+sXss89LAahpYqQPfOTjuP0LtcML\njiuVCupgpSA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96pfwPI9CocAnPvFZHnroAS6++Bs4jsN+++3PnXfezte/fgkA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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xd041710>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "pylab.figure(figsize=(11,5))\n",
-    "plt.semilogx(data2.index.values,data2.values.transpose()[2],color='black',label='digitaler Servo')\n",
-    "plt.semilogx(data3.index.values,data3.values.transpose()[2],color='red',label='analoger Servo')\n",
-    "plt.semilogx(f,p-180,color='blue',label='designter Servo')\n",
-    "plt.ylabel('Phasenverzögerung (°)')\n",
-    "plt.xlabel('Frequenz')\n",
-    "plt.legend()\n",
-    "plt.grid()\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Wie zu erkennen ist, ist der verlauf der Phasenverzögerung des analogen Servos deutlich näher am Design als der des digitalen Servos."
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/unordered/Servo_Design/test1.txt b/unordered/Servo_Design/test1.txt
deleted file mode 100644
index 0975979ec2fcfcbc4f460d8807fee7c8d4065dd6..0000000000000000000000000000000000000000
--- a/unordered/Servo_Design/test1.txt
+++ /dev/null
@@ -1,5 +0,0 @@
-Nyquist frequency: 100000 Hz
-gain,10.0000000000
-first order Highpass filter; cutoff frequency: 1 Hz,0.9999842922835,-0.9999842922835,-0.0,1.0000000000,-0.9999685845669,-0.0
-integrator from 1000 Hz to 10 Hz,0.9847693460573,-0.9844600202293,-0.0,1.0000000000,-0.9690674171938,-0.0
-second order lowpass filter; cutoff frequency: 1000 Hz; Q factor: 0.707,0.0002413582569776,0.0004827165139552,0.0002413582569776,1.0000000000,-1.9555718227,0.9565372557512
diff --git a/unordered/Servo_Design/tf2.csv b/unordered/Servo_Design/tf2.csv
deleted file mode 100644
index 07a2aafd698965a4e9867993909643f4145f917d..0000000000000000000000000000000000000000
--- a/unordered/Servo_Design/tf2.csv
+++ /dev/null
@@ -1,402 +0,0 @@
-#; Frequency (Hz); Amplitude (Vpp); Gain (dB); Phase (?)
-1;100;0.01;22.69;-2.71
-2;102.3;0.01;20.26;-30.59
-3;104.7;0.01;25.87;-27.96
-4;107.2;0.01;22.76;-8.78
-5;109.6;0.01;22.83;19.04
-6;112.2;0.01;22.9;18.89
-7;114.8;0.01;21.9;-0.67
-8;117.5;0.01;22.97;0.24
-9;120.2;0.01;20.58;-34.46
-10;123;0.01;20.64;-4.38
-11;125.9;0.01;24.88;-11.85
-12;128.8;0.01;22.96;19.72
-13;131.8;0.01;22.55;-23.27
-14;134.9;0.01;23.77;28.32
-15;138;0.01;22.26;32.7
-16;141.3;0.01;28.9;1.01
-17;144.5;0.01;25.2;-27.69
-18;147.9;0.01;22.41;-12.22
-19;151.4;0.01;22.8;-17.72
-20;154.9;0.01;29.23;15.17
-21;158.5;0.01;21.67;-10.53
-22;162.2;0.01;25.48;27.85
-23;166;0.01;21.66;16.84
-24;169.8;0.01;31.96;-13.27
-25;173.8;0.01;25;-6.48
-26;177.8;0.01;27.79;-1.41
-27;182;0.01;22.8;-2.29
-28;186.2;0.01;22.95;5.82
-29;190.5;0.01;25.44;-13.53
-30;195;0.01;23.77;-12.42
-31;199.5;0.01;25.97;-4
-32;204.2;0.01;27.18;-18.2
-33;208.9;0.01;23.29;2.77
-34;213.8;0.01;26.94;25.74
-35;218.8;0.01;28.33;4.14
-36;223.9;0.01;22.65;3.19
-37;229.1;0.01;21.31;13.28
-38;234.4;0.01;21.95;-5.98
-39;239.9;0.01;24.7;8.95
-40;245.5;0.01;28.94;14.96
-41;251.2;0.01;28.15;20.95
-42;257;0.01;22.76;5.17
-43;263;0.01;26.25;-0.02
-44;269.2;0.01;23.07;-10.09
-45;275.4;0.01;28.79;0.99
-46;281.8;0.01;25.21;-17.18
-47;288.4;0.01;27.53;-4.86
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diff --git a/unordered/doc/Servo_test.ipynb b/unordered/doc/Servo_test.ipynb
deleted file mode 100644
index bbf475cb43525b87d057e5ca00ad935321033219..0000000000000000000000000000000000000000
--- a/unordered/doc/Servo_test.ipynb
+++ /dev/null
@@ -1,329 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Vor der Inbetriebnahme des Adwin-Gerät als Servo wurde die Transferfunktion, des Betriebs ohne Second Order Sections gemessen, bei den Abtastraten 100 kHz, 200 kHz und 400 kHz gemessen. Aufgefallen hierbei ist, dass die phasenverzögerung deutlich von der, der read-write funktion abweicht. Die Auswirkungen auf den Servo und mögliche Fehlerquellen werden im folgendem betrachtet."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "data=np.empty(6,dtype=object)\n",
-    "data[0]=io.read('sample_Test_100_1.csv')\n",
-    "data[1]=io.read('sample_Test_200_2.csv')\n",
-    "data[2]=io.read('sample_Test_400_1.csv')\n",
-    "data[3]=io.import_data('SCRN0005.TXT', 'ascii_pandas')\n",
-    "data[4]=io.import_data('SCRN0006.TXT', 'ascii_pandas')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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5vHkzB06c4ODRIxw/nnLKeaVLl6FUqdKULFmKSg4H1yz7maIHDxBnWChiGIR5\nPRjuU5f6Srv3AU4MGZFnryUn69dbCA83KV/exDThxx+t1KzpIy4OkpNh5Uorder4OX4cXnwx6zL4\nv3m9kJZ2MmOMiTF59103bdvm7b21+UGrVk0oW7YMn332RcD6PFsCqUcZioiInIPdbqdixUrnPG77\n9m389tuvuFxh7NixnfXr15KQkMCSJT8xed/e09q8ul59WpavQB2Lhbj6DSi1YhnlP3wPMyISX9Ur\n8RUrQWbdepy2VlBGBvZVK/A2anL6vgtUvfrJiWSGAS1bnkz6YmLITgILFYLx49PP2IbfD7/9ZmHp\nUhseD8yda+P228N4+mkPZcueefkimw1atszMkyW2Lid+vz/Xk1/zkiqQqszIZU7jXPKDS2GcHzuW\nyMaNG0hMTCQ5OYktWzazePGP/PHH2lOOK+l00T4jnRpANeDKmBgiH3oU9yOPg2FgXzSfyEFPYtu+\njYwu15Py7kcY6W4Mtxt/seJBeW05SU2Fu+4KO+cSRk2bZjJpkhu7nlaZo+bNG1KpUkU+/nh8wPrU\nJewcXApvOCL/lca55AeX8jg/evQo27Zt5fDhQxw4sI+fflzEimVLSfqfy+HFgO6VqtAhJpb6v6wg\npnwFMtu0J/zDd/EVL4Hl4AEwTdx39sN9zwPgcOAvWuzkyuIZGeA897qVecHvh+3bDXy+M1fPfv7Z\nyjPPuLj9dg+PPeY5bX9cnJnjIzLzk2bNrqFKlSp89NG4gPWpBDIHl/Ibjsj50jiX/OByG+emaXLo\n0EE2btzApo0bWDXuU+Zu3cI/6ZXT6aROnXq0jC9Msx3bKFK3HhVNCJ/wOYY/61Kxp0kzkidNw756\nFTG9biTt4cdIe+Kp4L2os3jpJSfvvus4476SJf3Mnp2W72d9N21an2rVqvHBB2MD1qcSyBxcbm84\nImeicS75QX4Y5+653/HLiVQ2JR5l9+7dLF++lD/+WJu9EPwVV1TkjnYdae5ycZXfT/To18nofB32\nZUswUlMxPB5SPhqb/WSfUOLzwZw5NpKS/vVY2QwYOtTJFVf4+eabtHx9n2TjxvWoUaMG77//WcD6\nVAKZg/zwhiOicS75QX4d58eOJbJu3Vp27drJ+PFjWbfudwAiI6NoWbQovbZuoWNsLJkzvydqQH9s\na1bjL3Lymfa+MmU5/u5H+IuXCNZLOKfvv7fSp08YcXEmYWHQrZuXZ5/15LuFzRs1qkutWrV4771P\nA9anZmGLiIhchgoUiKN585YA3HbbHSQk7GHFimUsX76M77+fw0zAlZZG6xFDue6mW7juympE/7Ns\nkGnimD2T2E5tSJ40DV/lKsGP/PVVAAAgAElEQVR7IWfRtq2Pjz9OZ8ECG0ePGrz9tpM9eyzcd5/n\ntDUmCxUyKVUqZOpiF5Xf78cSQlmzKpD58C9WyV80ziU/0Dg/nd/vZ9WqFXzzzTRmzvyGQ4cOEhYW\nxrXXtqNbtxtp27Y9YZs2EnPLDRimybF5P+AvWSrYYZ/Te+/ZGTz4zLNqLBaTkSMz6N3bG+Co8t41\n19Sifv36vP32RwHrU5ewc6A3HMkPNM4lP9A4Pzufz8fKlcv59tvpzJz5DYcPHyIyMoqrrqrB7W3a\ncdcbr0OZshybOQ8iI4Md7jn98YeFAwdOn9X96acOFi2yce+9Hnr18lKliv+yeRJO/fo1adiwIWPG\nfBCwPpVA5kBvOJIfaJxLfqBxfv4yMzP56adFzJ07hxUrlrJp00aqlCxJj4QE7jMMiv2zMLnDQerQ\nV0nvfXtwA84FrxeefNLJF19kzeguXdpP27aZVKjgx2KBjh0zKVIkZNKeXKlXrwZNmjTmzTffD1if\nSiBzoDccyQ80ziU/0Di/MH6/n6lTJ/HllxNYuWI5dovB9RUr0aNyFTofOIBj9SqSJ03D+/d9lpeK\nAwcMvv/exvz5NhYvtuJ2Z5Uhixf3M2mSmypVzvxUnFBWr95VNGvWjDfeeDdgfSqBzIHecCQ/0DiX\n/EDj/L/bsWM77733NjNnTicxMZFrW7Tiye3baJKYiLVGzezjfOUrkDr8dS6V1b0zMiA11WDnToO+\nfcNwuw2qV/cRE2MyfHgGJUqETBp0VnXqVKNly5aMGvVOwPo8WwIZOtN5REREJGjKlSvP66+PZv36\nrQwdOoJlq1bSdvcuKng9TDh0kEzTBL+fsP8bR9QTj0Do1J/OyumEggVN6tbNWpC8SZNMABYvttG7\ndxipqUEO8DyZphlSs7BDJxIREREJOpvNxj33PMD69ZsZN24iRa+sxt1bt1B1717evvFmkgc+g2vq\nJMLeHp19jnPG11g3bQxi1OendGmTzz9PZ8YMN59+6mbDBgv9+oXx++8W/CF+Vdvv92OE0IwgJZAi\nIiJymsjIKDp06MScOYsYO/YL4uPjGTCgP7WmTmJYter4hw7GMXsmrv8bR/Q9dxDbrROWPbuDHfZ5\na9XKx/DhGfzwg5W2bSNo1iycnTtDJ0H7N1UgRURE5JJhsVjo1KkL3323gHHjJlKkSFGe+3M91ex2\n5tx7B66Bj+K9piFkZBDTpyeXzDVh4M47vfz55wneesvN4cMWOnUKZ/lya0henVcFUkRERC45hmHQ\noUMnZs6cx5w5C4kqU45bPB6uMAzm9n+clI8/x7rxL6If6EfIXw/+HwULmvTsmcnMmWk4nXDddeHU\nrh3BJ5/YQyqRNE1TCaSIiIhcuurWvZpFS1Yy4cPPsJcuQ/fbbmHEb79y8IWXcc6dTcTwl4MdYq5V\nquRn0aKsamSFCn4GDXLxwgtOjh0LjaKqaYbWowxDJxIRERG5ZFitVtp1u5G5836gY8cuvPrqMOp+\n9D7z23Uk/K03KNCyMeEjR0B6erBDPW+xsdCzZyZTp7q55x4PH37ooHLlKK64IpKPP7YHNTZVIEVE\nROSyERMTyyefjOPbb+fhcrloP38uvWrVZqPNRsRrw4m5uRtGclKww8wViwWGDMlg3Dg3Q4em06KF\nj+efd7JggTVoMWkSjYiIiFx2GjRoyIIFi+nX736+2byJqzdtYFTPW7H9spIC1zYj/LXhWLdtCXaY\n580woEOHTO65x8unn7qpVs1Pv35hPPusk5UrA59IahKNiIiIXJYiI6MYMuQVVq5cS6NGTRgw6Qs6\n167LgQJxhI96ldhrm2Pd8Feww8y1iAiYMMFN06aZTJhgp0uXcKZPtwU0BtNEFUgRERG5fBUpUoQv\nv/yKIUNeYeHa36i2YzujnnoOf0QEMX1uxjhyJNgh5lrx4ibjx6ezYUMqDRpk0r+/izVrApdGqQIp\nIiIilz2LxcK99z7IokVLqVGjFgNHDOHWq2qQcfAAMbfcgHH4cLBDvCAREfDZZ+kULmzSu3cY69YF\nJpXKugdSCaSIiIjkA5UqVWbq1Bk89dSzTFk4nyYlSnJg0wYKdLoW1xfjcU7+EiMlOdhh5kqhQiaT\nJ6fhcmWtGzljhi3PJ5urAikiIiL5isVi4YknnmLcuIlsPniQemFhLEs8StRjDxH98H2Evzos2CHm\nWoUKJt99l0aZMn7uuSeMKlUiGTrUkYdrqGsWtoiIiORDWc/WXkh4TCyt3W7efG4wGV2uxzXpSzhx\nItjh5VrRoibz5qUxcWIa7dtn8tZbTu67z0VGxsXvy+/3A6pAioiISD5UpUpV5s37gcaNm/LY0MG8\nHBOD5XgKrq+nBDu0C+J0QuvWPt5/P50XXkhnxgw7DzzguuiVSC0kLiIiIvlagQJxfPnlV/To0ZPh\n/zeOL0qWIuyzjwmph0/nkmHAQw95GTw4nZkz7bz+uuOitu/3h9ajDAO7iJGIiIgIYLPZeOONt9m9\nexd9Vq3g14Q9DK1cBtffSZKvRCmSZs6D8PAgR5o799/vZfNmC6NGOSlc2OSOO7wXpV1VIEVEREQA\np9PJxIlf0bdPX0YD7V1hHOrYhYx2HbH/sZawL8YFO8RcMwx47bUM2rbN5KmnXIwY4bgohVU9ylBE\nRETkb5GRUbw6cgwffPApK44eofWaX9n6zPN4GjYm7N23wOMJdoi55nDA55+76dXLwxtvOBkz5r9f\nztYyPiIiIiL/0r17D774Yiq7du2kU6c2rO3RE+u+vbi+mhzs0C6IzQajR2fQvbuX4cOdzJr13+4a\nVAVSRERE5AxatGjFjBmzcbvTaD/0RVZcUYnwUa9iJB4NdmgXxDBg9Oh06tb18dBDLrZtu7AKovn3\nNXBVIEVERETOoGbN2syaNZ/IyCg6HNjPn/v3EX337eC9OJNRAi0sDMaOdWO3wyOPhOHz5b6NfxJI\nVSBFREREclC+fAW+/nomYVFRtI+IJOnnxcTc3A3nxP+7ZBccHzYsnV9+sfLaaw5WrLBy8OD5VxP9\nfy8qqQqkiIiIyFmUKVOWL76YSmK6m1srVsLYtpXo/g8Q/fB9wQ7tgvTokUn79l5Gj3bStWs4HTqE\nn/f8IFUgRURERM5T9epXMWTICBZs2UzrKyqy5Y5+OGd9g3XTxmCHlmuGAZ98ks60aWkMG5ZOQoKF\nr78+v4k1qkCKiIiI5MLtt9/JG2+8za+/rqbbsiV4wsIJf+uNYId1QRwOaNLEx913e6le3cdbbznP\n655ITaIRERERyQXDMOjd+3bef/8T/ty0kVdr1MQ5bSqWnTuCHdoFMwx49FEP27ZZzmt5H13CFhER\nEbkAHTp0omPHLgz/fQ1LrFaiHn3wklxk/B+dOmVSqZKPgQNdrFxpPeuxuoQtIiIicoFef/1NSpUu\nQ2eLhXXLfibymQFclOcEBoHVCl984SYuzqRHjzB+/DHnJFIVSBEREZELFB8fz1dffUuBwkXoEhFB\n4oTPiatfk4jBz0FaWrDDy7UyZUxmzUqjXDk/Dz7oIjHxzMeZpiqQIiIiIhesWLHiTJgwmeMYdClV\nmpQKVxD2/ttEPXI//H2p91JSqJDJu++mc+yYwaBBrjMeowqkiIiIyH9UteqVfPDBp/yesIc7oqJJ\nfe4lXN9OJ3zkiGCHdkGqV/fz+OMepk2zM3366ZNqdA+kiIiIyEXQrl0HnnvuJb75ZhofREWSftMt\nhI969ZKdnd2/v4err/bx6KMufv/91PRMFUgRERGRi+Shh/rTtGlzhgwZzNY7+wHgmjopyFFdGLsd\nPv/cTcGCJrfdFsb+/SerjX6/1oEUERERuSgMw+D119/E6/Vw78svkNKwMa4pEy/Zmdnx8SYTJrhJ\nSTG4/faw7HlBqkAC8+fP54knngh0tyIiInIZKl++AqNHv8Py5Uu58dgx2LUT+8rlwQ7rglWr5ueD\nD9ysXWuhf38Xpql7IBk6dCijRo3K/kKIiIiI/Fc33HATr7wykgUb/uQDuwPnpC+CHdJ/0r69j0GD\nPHzzjZ0FC6wh+ShDwzQDV+f97rvviIuLY/LkyYwePfq0/W63B5vt7KuxX0xWqwWfT8msXN40ziU/\n0DgX0zTp2LE9vyxezEavlyK9++B7ZQQUKRLs0C6I1wtVq1ooUQImTtxL2bKleO+997n77n4Bi8Fu\nzzknO/cDGC/A1KlTGTdu3Cnbhg8fTseOHVm5cmWO56WmZuRFODmKjQ0nKenSW3hUJDc0ziU/0DgX\ngGHDXqd5s4b0KF6CBZMmYvv1V44t/BlseZLu5Ln777fzzDMuFi1Kz94WyHEeHx+V4748+Yr26NGD\nHj165EXTIiIiImdUvvwVjHnrPe677y7ubdqCcUt+xPXlBNJvuyPYoV2QXr28jBrl4KOPstK1fD2J\nRkRERCSvdO/eg0ceeZzxS35kXpUriRgxFCP1eLDDuiBhYfDIIx5WrMhK10LpHkglkCIiInJZGTDg\nacqWLcdDx1PwHjlM+Jujgh3SBbvnHi8tW3oAWL8+dNK2gEdyzTXXnHECjYiIiMjF4HK5GDFiFFv3\nJvDKVTUIe3cMtrW/BTusC2KxwEsvuQH44Yd8nECKiIiI5LVWra6la9duvLp5E1sLxBH1yP2QEdjJ\nuheLy5W1YM699+oStoiIiEieGjLkFWx2B7cXLIS54S/C33g12CFdkH/Wz46IUAIpIiIikqeKFSvO\nyJFvsnzTBh6rWJnwt0Zj+31NsMO6AHqUoYiIiEjAdO/eg3797uPdLZtYFhNLVP8HLrlL2X5/6D2J\nRgmkiIiIXNaeeeYFChcuwoBChbBu+IuwsR8HO6RcCcVHGSqBFBERkctaZGQkTz45iBWbN/FVlaqE\nvff2JVWF/CeB1CVsERERkQDq1asPlSpVZlByMv4D+3FNmRjskM7bP5NoVIEUERERCSCbzcbzz7/M\n1v37+LBkScLfHg2ZmcEO67yoAikiIiISJG3btqdx46a8mJTEsZ07CPv4g2CHdF5UgRQREREJEsMw\nGD78dVLS03m8eAkiXnkZ69YtwQ7rnFSBFBEREQmiqlWv5IEHHmHCvr2stNmynlDzd4UvVJmmKpAi\nIiIiQfXoowOIjY1laLkK2FevwjH3u2CHdFaqQIqIiIgEWWRkJHfffR+z/1jLuuIlCB8zEv5O0kLR\nyXsggxzI/1ACKSIiIvnO3XffS3h4BC/FF8b+2xrsi38Mdkg5UgVSREREJATExRXk/vsfYtra31ga\nV5DwMaOCHVKONAtbREREJEQ8+GB/ChcuwhPhEdh/Xoz1rz+DHdIZ6VGGIiIiIiEiMjKSgQOfYWXC\nbhbZ7YR9FprPyNYlbBEREZEQcvPNvYiPL8yrheJxfTUZIyU52CGdxu9XBVJEREQkZLhcLvr1u4/5\n+/exLu0ErslfBjuk06gCKSIiIhJi+va9i+joGJ6Kjsb1yYfg8wU7pFOE4kLitpx27Nix45wnlytX\n7qIGIyIiIhJosbEFeOKJp3jxxUF8n5JCk5kzyLj+hmCHlS0UK5A5JpA33XQTVatWzQ763zZt2sSq\nVavyLDARERGRQLnrrnsYN+5Tnk7Yw6+jR5JxXfeQWbk7FJfxyTGBbNeuHUOHDs3xxOeeey5PAhIR\nEREJNIfDwYMP9ueJJx5h1YY/qb5gHp427YMdFhCaFcgcIxk6dCiJiYlkZmYCMHPmTKZNm4bX683e\nLyIiInK56N69B1FRUbwbHk7Eyy9ARkawQwJCswKZYwL55ZdfcvPNN9OtWzcGDx7MtGnTWLZsGc88\n80wg4xMREREJiIiICG666Ra+9ng4tmkjESNHBDsk4BKrQE6bNo05c+bwxRdfsGDBAj7++GNGjhzJ\ngQMHAhmfiIiISMD07Xs3nsxMPqxZm7C3R2P7fU2wQ7q0KpBhYWHYbDaio6MpV64cNlvW7ZJWqzVg\nwYmIiIgEUuXKVWjUqAkfHz1CZoEChI96NdghAZfYQuJerxePx3PK///JgkVEREQuR3373sXuhD3M\nbNocx/dzsezeFdR4QvESdo6zsPfu3Uv79u2zg27Xrh0QWtmviIiIyMXWsWMX4uML82FiIt0Mg7Bx\nn3Hi+ZeCFk8oXsLOMYFctGhRIOMQERERCQkOh4PevW/jzTdHsbl5Kyp+OZ4TA58Blyso8VxSFciz\nzbZ+5ZVX8iQYERERkVDQp88djBnzBh8WKMAbR4/inDOLjG43BiUWv/8SugeyY8eOdOzYkeTkZMqX\nL8+NN95I5cqVs++JFBEREblclSxZirZt2zNhyU+4C8XjmDMraLH8U4E0jNCpQOYYSdOmTWnatCnp\n6en069ePunXr0rdvXxITEwMZn4iIiEhQ9O17F0eOHGZK5So4Fi2EIBXRQvEeyHOmsmlpaSxfvpzU\n1FSWLFmS/SQaERERkctZixatKVOmLB8eOYwlJRn7imVBiSMU74E8ZyTDhg1j4sSJ3HTTTUyZMoXR\no0cHIi4RERGRoLJYLNx++10s37SRPxwOHPO+C0ocpnkJVSA///xzACpUqMBbb73Fd999x9tvv018\nfPwp+0VEREQuV7fc0hubzcZnxYrjnDcH/q4GBlIoViBznIU9bty4HO93NE2T2bNn07dv37yKS0RE\nRCToChYsyLXXtmXysqWMTEnGuv4PfFfVCGgMoXgPZI4J5COPPHLWEx9++OGLHoyIiIhIqLnxxpuZ\nO/c7frDbaTxhLKmvBfZ2vpOzsC+BBLJbt26BjENEREQkJLVp057IyCjGFYqn1dTJnHj+Jcyo6ID1\nH4qXsEMnEhEREZEQFBYWRo8eNzM5YTe7T6TinDIxoP2H4iVsJZAiIiIi59C//xNYrFZejIsjbOwn\nAZ1ME4oVyBwvYf9j//79zJo1i4yMjOxtDz30UJ4GJSIiIhJKihcvQd++d/PxR+/xUmIisT8vxtu0\neUD6viQrkP379yc1NZVChQplf4iIiIjkN/363YffNJkSFpZVhQyQS7ICGRERwWOPPRaIWERERERC\nVunSZahVqzaT9+1l4JxZWPbtxV+8RJ73G4qzsM+ZylasWJHZs2ezfft2duzYwY4dOwIRl4iIiEjI\n6dKlG2sOHWKHz4dr/NiA9HlJViA3bNjAhg0bsj83DIPx48fnaVAiIiIioahr1+sZMuQFJlesxJP/\nN460gc+A1ZqnfYbiPZDnTCAnTJgQiDhEREREQl6ZMmWpWbM2XyUl8cyhg9jWrCbz6mvytM9QrEDm\nGMk/T6Jp0qTJaR8iIiIi+VWXLtezZtcOdlitWc/HzmOXVAXyrbfeAuDnn3++KB0dP36cgQMHkpqa\nitfr5emnn6Z27doXpW0RERGRQOna9XqGDn2RyaXLMGDed5x4bnCe9heKk2jOeQn7999/Z9q0aXi9\nXgAOHTrEp59+muuOxo4dS4MGDejbty/bt2/niSeeYPr06bmPWERERCSIypYtR82atfn66BGe3rEd\ny47t+MuVz7P+QvES9jkTyKFDh9K3b1/mzZtHpUqV8Hg8F9RR3759cTgcAPh8PpxO52nHREY6sdny\n9kbU/2W1WoiNDQ9YfyLBoHEu+YHGuQTaTTf14NlnB7ELKLlkIf7a1fOsL5crK12z2awhM87PmUBG\nR0fTuXNnli5dysMPP0zv3r3P2ejUqVMZN27cKduGDx9OjRo1OHz4MAMHDmTQoEGnnZeamnHatrwU\nGxtOUlJaQPsUCTSNc8kPNM4l0Nq06cSzzw5iSnxh+s/4huTb+uVZX2lpWfmRaRLQcR4fH5XjvnMm\nkIZhsGXLFtxuN9u3b+fw4cPn7LBHjx706NHjtO2bNm3i8ccf58knn6R+/frnbEdEREQkFJUtW44a\nNWox5eB+BqxcDqmpEBmZJ32F4iSac15Mf/rpp9myZQt9+vRhwIAB3HLLLRfU0datW+nfvz+jRo2i\nefPAPDtSREREJK907Xo9qw8eZLfXi2PpkjzrJxTvgTyvJ9HUrVuXYsWK8e6779K3b98L6mjUqFF4\nPB6GDRtGnz59uP/++y+oHREREZFQ0LVrNwDG2+04Fs3Ps35CsQKZ4yXsrVu38vLLLzN+/Hhuv/12\nYmJiOHjwIEOGDKFp06a57uj999//T4GKiIiIhJKyZcvRtGkLPv5lBU8tWpBn/fxdgMRisfB3Lhl0\nOVYgR44cycCBAwGIj49n8uTJjBs3jo8++ihgwYmIiIiEsr5972RPejoLdu3EsmN7nvQRihXIHBNI\nt9vNVVddBUBUVNYsnDJlypCZmRmYyERERERCXPv2nShSsBCfAI4fFuZJH5fUPZAZGSeX1Hnvvfey\n/2+znXPitoiIiEi+YLfbad+5KwsMAyOP7oO8pCqQhQsXZt26dadsW7duHfHx8XkelIiIiMilolmz\nlhw3TX5f/BNc4ANXzu4SepThwIEDeeCBB2jQoAFlypRhz549LF++nA8++CCQ8YmIiIiEtCZNmmIY\nBj+ku6n+y0q8jXM/2fhsTr2E7buobV+oHCuQpUqVYurUqdSuXZu0tDSqV6/OpEmTKF68eCDjExER\nEQlpBQrEUaPaVSwgb+6DDMVL2Ge9odHlctGxY8dAxSIiIiJySWrWsjUf/PkHGQu+h+cGX9S2L6lJ\nNCIiIiJyfpo3b4nXNFny13qMQ4cuatuhWIFUAikiIiLyHzVo0IjI8HBmA46fFl3UtlWBFBEREbkM\nORwOWrZqwyyLBfvCi7ucjyqQIiIiIpepNm3bs8/v569F87mYzxw0TTOkkkdQAikiIiJyUbRu3RbD\nMJidlIRt/bpzn3CeTNOvBFJERETkchQfH0+DuvWYCNgWLbho7ZpmaN3/CEogRURERC6a7jffykZg\n4+xvL1qbfr8qkCIiIiKXrS5drsNmsTBl3VqM4ykXpU3dAykiIiJyGYuLK0jrOvWYbJrYfrg4y/mY\npqlL2CIiIiKXs3Y392IPsOutNy5Ke7qELSIiInKZa97qWgAWrfsd+4pl/7m9rEvYoZWyhVY0IiIi\nIpe4UqVKc0X5K5hntxM2ZtR/bk8VSBEREZF8oEWr1iw2TcyF87Fu2vgfW9M9kCIiIiKXvRYtWuHO\nzGQpYF+96j+1pQqkiIiISD7QqFETrFYri2w2rBv+/E9tZc3CVgIpIiIiclmLjIyiZs1a/OR0Ytuw\n4T+1pQqkiIiISD7RsGETVrndeP5a/5/a0TqQIiIiIvlE48ZN8Pr9rDp6BOPw4Qtux+/Xk2hERERE\n8oVrrmmIxWLhR8D2H+6DNE0TUAIpIiIictmLioqmRtVq/MR/TyB1CVtEREQkn2jUvCUrAM8f6y64\nDdPUJBoRERGRfKNRo8Z4gDVrVl9wG6pAioiIiOQj11zTEIthsGTnDvD7L6gNLeMjIiIiko/ExMRy\nVYmSLM7MxLp1ywW1oQqkiIiISD7TuGkzlgO+nxdf0PmqQIqIiIjkMw3adyYDWDtn1gWdb5omhhFa\nKVtoRSMiIiJymWnQsBEG8PNvay7o/KwK5MWN6b9SAikiIiKSh2JjC1CjWHEWpyRj2ZuQ6/N1D6SI\niIhIPtSwUWOWA/4lP+X6XK0DKSIiIpIPNex8PenA2u9yfx9k1j2QSiBFRERE8pUGjRpjAMtWr8r1\nuaaJLmGLiIiI5DcFCsRRvUhRFh85jGXP7lydq2V8RERERPKpRi1bswwwpn+dq/M0iUZEREQkn2rQ\nriNu4I+pX+bqPFUgRURERPKphg0bAbB006ZcXcbWQuIiIiIi+VRcXEGuvKIiPwLOmd+c93laxkdE\nREQkH2vUohVLLRYs357/fZC6B1JEREQkH2vYsAlpfj+/r1mDcfToeZ2jeyBFRERE8rGGDRsDsBhw\nLP7hvM7JqkAqgRQRERHJlwoVKkTVKlX5wWbD8cPC8zonFCuQtkB1lJaWxhNPPEFycjJhYWG8/vrr\nxMXFBap7ERERkZDQsFETJm/ZDIsWZD1m5hzJYb5+lOGUKVOoVq0aX375JZ06deK9994LVNciIiIi\nIaNx46ac8PlYe+gg1r/+POfxobiMT8AqkH379sXn8wGwb98+ChUqFKiuRUREREJG/foNAVgKVPth\nIe5q1c96vN8fehXIPEkgp06dyrhx407ZNnz4cGrUqMFtt93G5s2bGTt27GnnRUY6sdmseRHSGVmt\nFmJjwwPWn0gwaJxLfqBxLpeS2NhylC1bluVHjvDob7/gPMfYtdkMHA5bSI1zwzRNM9Cdbtu2jXvv\nvZcFCxacsv3w4eMBjSM2NpykpLSA9ikSaBrnkh9onMul5r777mTVrJlsr1mLpNnzz3ps9+6d8Xq9\nLFmyJKDjPD4+Ksd9Abug/uGHHzJjxgwAwsPDsVoDV2kUERERCSX16tUnwZPB3sOHznlsKC4kHrB7\nIG+44Qaeeuopvv76a3w+H8OHDw9U1yIiIiIhpV69/2fvvsOjKvM2jn/PlPQOSA8oTRQRElSqIoIi\ndhTBgq4FFV9EF1TEgq4iIM0WC0VWXBERrGsXdRVQqoJSpUgo0iEkmSTTznn/mGQgQoBAmBnI/bmu\ncWZOe36TPDJ3ntPOBWDerp10OsyylfoyPlWrVuWNN94IVXMiIiIiEevMM88ixu5gbn4+nQ5zKR/L\nsiJuz21kjYeKiIiIVAJOp5OWtWsz17Iw8nIPuWwkjkAqQIqIiIiEwTmNGvML4Nm27ZDLReJ1ICOr\nGhEREZFK4pxmzfEAvy+Yd8jlAiOQoanpSClAioiIiIRBq8xzAFi0aOFhlrSweTyw7PB3rQkVBUgR\nERGRMDilQUPqAwuW/X7I5SzLwvnnOhy33xaSuo6EAqSIiIhIGJgpqbQBFqxdfejlTBPD48EK4d36\nDkcBUkRERCQMrNRAgNy8dy9//bW57OUssPt9kJwcuuIOQwFSREREJBwcDs6Njwdg4cL5ZS5mmiaG\nzwdJCpAiIiIilV7ztKrE2OwsWFB2gLQsC5tPI5AiIiIiAjiqpJGRmMiiRQvKXKZkBNJKSgxhZYem\nACkiIiISJlZKKq2jowwXQ9sAACAASURBVPntt8W43e6DL2OZ2P1+7cIWERERETDT0mgDeDwefv99\nyUGXsXw+DNAubBEREREJjEC2LSoEyj6RxvL7sQFWUlIIKzs0BUgRERGRMDFT06iZl0d63XQWLjz4\ncZBmyQikdmGLiIiIiJWaimFZZJ51Ngvn/QQ+34EL+f3Fu7A1AikiIiJS6ZmpaQCcV60af23bxs5J\nEw5YpmQXto6BFBERERGs1FQA2v+xCoBFvy46YBmzeATSStQIpIiIiEilVzIC2WruT8QA89etPWAZ\ny9QIpIiIiIgUKwmQ0ZZFK2D+5o0HLGMFj4FUgDzh7Nmzm+7dLyM7ez0AmzZtpG/fO7j33jsZPXo4\npmkCMGnSePr0uYV77rmd5cuXHrCdK6+85IBp1113RamLh2Znr6dfv7uOzwcRERGRiFGyCxuglcPJ\n77t2BTNFcBnTxGYYEBMT6vLKpAB5BHw+HyNHDiMqKjo47eWXx9KnT19efXUilmUxa9YPrFq1ksWL\nf2H8+Mk89dQwxo4dGcaqRUREJNJZySlYhoE3sxVNq1WjwO9nw4bsUsuYfhOcTjCMMFV5IEe4CyiP\nadMcTJ3qrLDtORw2evRw0LPnQU6Z309W1gtcffW1/Oc//w5OW7VqJS1bZgLQunVb5s+fR3p6Pc45\npzWGYVCjRg38fh979uwhdb+/LkqMG/cK+fn5DBjwcJntut1FDBzYHwC/38/y5Ut55533qV27ztF8\nXBEREYk0NhtFt9yOp1Nnzhz5LGz5i5UrV1C//qnBRSzTxOaMCmORBzqhAmQ4fP75f0lJSeG889qU\nCpCWZWEU/yUQFxePy5WPy5VPcnJKcJmS6X8PkFlZL2CzGQwcOCg4bcCAfsHtud1FREfHEB0dQ1bW\neCzL4plnhtC162UKjyIiIieZ/FHPA9DkzYmwbCkrVy6na9duwfmW6Y+o3ddwggXInj19hx0tLI+U\nlDhycg69vc8++wTDMFi4cD5r1vzB0KFDGDFiLDbbvr3/BQUuEhISiI9PoKDA9bfpiaW2t3v3Ltau\nXU3t2nVLTR87Novo6MAu8uzs9YwaNSw47/nnR5KeXo+rrup+1J9VREREIltCair1HQ5Wrlxearpl\nWticFbcHtiLoGMjDeOWVCWRljScrazwNGzbm8cefpkqVqjRq1IRfflkIwNy5P3H22S0566yzmT9/\nLqZpsnXrVkzTIiUlpdT20tKqMHZsFuvXr2Pu3J8O2/6ECa9hWfCPf9x5XD6fiIiIRAYrIYkzDBsr\nVqwoNd20TIiKrF3YCpBHqV+/B5g0aTx3330bXq+Xjh0v4vTTm9K8eQvuvvs2Hn/8YQYMGHTQdQ3D\nYPDgITz//Ej27s0ps40VK5bx9ttvsmFDNv363UW/fnexaNHB75MpIiIiJzYrMZFmpp+1a1fj9Xr3\nTTdNjAgLkIZlWVa4iyixY0deSNsL7MIuCGmbIqGmfi6Vgfq5nAzinh/Fh8OfoTcwe/YCGjduAkCz\n6slc2eR0Xv3t95D282rVEsucpxFIERERkQhgJibSovj1ryW3NLQsTMvSLmwREREROZCVkMgZQEpS\n0r7zJAoKsADbfteijgQKkCIiIiIRwEpMwga0adacn3+eA4AtLxcTIFoBUkRERET+xkpKAqBt49NZ\nt24t27ZtxcjNLR6B1C5sEREREfkbKzFw0kq7UwN3ofn55zkYuXs1AikiIiIiB1cSIM9Oq0J8fAI/\n/TQbIy8PCzCiI+tONAqQh+Hz+XjmmSe499476dPnFmbP/gGATZs20rfvHdx7752MHj0c0zQBmDRp\nPH363MI999zO8uVLD9jelVdecsC06667ArfbHXyfnb2efv3uOk6fSERERCKRmRDYhe0sKCAjoxW/\n/LIIo/gYSEMjkCeWr776nKSkFF59dSKjR7/E2LEjAXj55bH06dOXV1+diGVZzJr1A6tWrWTx4l8Y\nP34yTz01LLisiIiIyOGUjEAaeblkZGSyfPlSPLt2ReQI5Al1L+zoae8QM/XtCtue3WEjuseNuHve\nWOYyF17YmQsvvGjfOvbAj2zVqpW0bJkJQOvWbZk/fx7p6fU455zWGIZBjRo18Pt97Nmzh9TU1AO2\nO27cK+Tn5zNgwMNltu12FzFwYH8A/H4/y5cv5Z133qd27ToHLPv55//l55/n4HYXsXnzJm666Va6\ndbuCtWvX8MILo7Asi+TkZAYPfpJnn32SW2+9g9NPP4MbbujOPffcxwUXXMg///l/PProk1SrdsqR\n/QBFRESk4sTGYjkc2PLyaNEiA5/Px+9/rAqMQMZE1gjkCRUgwyEuLg6AggIXjz8+iD59+gJgWRaG\nYRQvE4/LlY/LlU9ycsp+6wam/z1AZmW9gM1mMHDgvlsdDhjQL7g9t7uI6OgYoqNjyMoaj2VZPPPM\nELp2veyg4bGEy5XP2LFZbNy4gUGD/km3blfw3HNDGTx4CKeeehqffvoRU6ZM5vzzL2Tu3J9ISkom\nKiqaBQvmkZl5Dh6PR+FRREQkXAwDKzExOAIJsGjtaiyACLsO5AkVIN09Dz1aWF4pKXG4j+CWQNu2\nbeXRRx/immuu4+KLuwJgs+3b+19Q4CIhIYH4+AQKClx/m176NkC7d+9i7drV1K5dt9T0sWOziC4+\nviE7ez2jRg0Lznv++ZGkp9fjqqu6H7LOhg0bA3DKKdXxeDzF2/qTMWNGAOD3+6hbtx433NCbwYMH\nkpycwk033cq0aVOYO3cO7dp1OOzPQkRERI4fKzEJIy+PmjVrUb16DX79c13gMj52e7hLK0XHQB7G\n7t27GDCgH3373sfll18VnN6oURN++WUhAHPn/sTZZ7fkrLPOZv78uZimydatWzFNi5SUlFLbS0ur\nwtixWaxfv27fVeYPYcKE17As+Mc/7jzssiUjmPtLT6/H448/TVbWePr27U+bNu1ISkoiOjqGb7/9\nmtat21C9eg3ee28qF1zQ6bBtiIiIyPFjJQRGIAFatsxk4bZtmIZx0O/4cDqhRiDD4a23/k1eXh5v\nvjmRN9+cCMCYMS/Rr98DjBz5LOPGvUK9evXp2PEi7HY7zZu34O67b8OyLAYMGHTQbRqGweDBQxgw\noB/jx79ZZtsrVizj7bffpEWLzOBZ2bfd1ofly5fRqFFjWrdue9j6Bw4czNChQ4JniT/yyBMAdOhw\nAZ9//glJScmce25rPvxwxiF3j4uIiMjxZyYFRiABWrbM4MsvPwPAZousAGlYlmWFu4gSO3bkhbS9\nlJQ4co5gF3akmT37B2Jj48jMPCfcpcgJ4ETt5yLloX4uJ4ukm3pg27aNnJk/8vEH0+lzzx0ADBjw\nECNGDA9pP69WLbHMeRqBPAE1bNiEGjVqhLsMERERqWBWYiLGmtUA1Cs+kRfAMCLrqMPIqkaOiMKj\niIjIyclKSMJWfAxkffbtto60YyAVIEVEREQihLXfMZCn7M2h5OI9+1/9JRJEVjUiIiIilZiVmIjh\ndoPbjWPTRtKLp2sEUkREREQOyiy5nWF+PrZNG0l3RgEagRQRERGRMljFNyAxcvdi37CBuklJgfca\ngTyx+Hw+nnnmCe6990769LmF2bN/AGDTpo307XsH9957J6NHDw9eZ3HSpPH06XML99xzO8uXLz1g\ne1deeckB06677grcbnfwfXb2+uB1H49Vv353kZ29vtS0ity+iIiIVBwrMRAYbfl52DdmU7daNQBc\nLtehVgu5kAfItWvXkpmZWSowRbKvvvqcpKQUXn11IqNHv8TYsSMBePnlsfTp05dXX52IZVnMmvUD\nq1atZPHiXxg/fjJPPTUsuKyIiIjIkbCKRxxt27Zi27yJOnUCtz7etGljOMs6QEivA5mfn89zzz1H\nVFTUUa0/bdo7TJ36doXV43DY6NHjRnoe4v7aF17YmQsvvCj43m4P/MhWrVpJy5aBG523bt2W+fPn\nkZ5ej3POaY1hGNSoUQO/38eePXtITU09YLvjxr1Cfn4+AwY8XGbbbncRAwf2B8Dv97N8+VLeeef9\ng94xxufzMXz4v9i8eTN+v59evW7ioosuDs7fuXMnTz/9OJZlkZZW5TA/GREREQkH31nNMdPSiH/8\nEQyvl9qnNQAqcYC0LIsnnniCAQMGcO+994aq2WMWV3wRz4ICF48/Pog+ffoCgc9TcjxCXFw8Llc+\nLlc+yckp+60bmP73AJmV9QI2m8HAgftudThgQL/g9tzuIqKjY4iOjiErazyWZfHMM0Po2vWyMm83\n+PHH75OcnMITTzxDQYGL22+/mczMc4Pz3333bTp3voQrr7yGb7/9mg8/nFEBPx0RERGpSFZKKvkj\nxpB0120A1DurOQCxsbHhLOsAxyVATp8+ncmTJ5eaVqtWLbp168bpp59e5noJCdE4HPYy5999953c\nffedFVan3W7D7zcPu9yWLVt44IH+9OrVi+7duwPgcNhJSQmES8PwUaVKKlWrpuLxeILT3e5Catc+\nJfgeYPfuXWRnryM9PT043WYzmDRpEtHRgas9rVu3jqef/ldw/rPPDqVx44bceuvNh6hxE23btiEl\nJY6UlDgaNWpIbu4OHA47iYkxbNq0nuuu605KShzt2rXmv//9sFRdcvKy2236XctJT/1cTiq33oz5\n5afYPnifJhd0YMqUqZx//vkR1c+PS4Ds0aMHPXr0KDWtS5cuvP/++7z//vvs2LGD22+/nSlTppRa\nJj8/tMdFHsm9U3fv3sV9993NP//5MK1anRtcvkGDxnz33Y9kZLTi22+/JyOjFbVr1+W1117i6qt7\nsn37drxeP4YRXaqNtLQqjBz5IvfddzdffjmT1q3bYpoWOTkFREf7AcjLK8Ln85OTU8CECa9RVOSl\nV69bD1lrzZp1+PnnubRq1ZaCAhcrV/5BYmIVfD4/eXlF1KpVl7lz51OjRjrz5i0Kbl9OfrpHsFQG\n6udysjFGvkDUxd1wV69LlxqBq0H6/Wbluxf2N998E3zdqVMnJk2aFKqmj8lbb/2bvLw83nxzIm++\nORGAMWNeol+/Bxg58lnGjXuFevXq07HjRdjtdpo3b8Hdd9+GZVkMGDDooNs0DIPBg4cwYEA/xo9/\ns8y2V6xYxttvv0mLFpnBs6Zvu60Py5cvo1GjxrRu3Ta47JVXdue554bSt+8duN1ubr+9D6mpacH5\nd97ZlyefHMzMmV9Tq1btCvjJiIiIyPFiJSXj7t7j8AuGiWFZlhXqRjt16sQXX3wR3GVbYseOvJDW\ncaL+xTp79g/ExsaRmXlOuEuRE8CJ2s9FykP9XCqDUPfziBiB3N93330XjmZPGg0bNqFGjRrhLkNE\nREQqKV1I/ASk8CgiIiLhpAApIiIiIuWiACkiIiIi5aIAKSIiIiLlogApIiIiIuWiACkiIiIi5aIA\nKSIiIiLlogApIiIiIuUSljvRiIiIiMiJSyOQIiIiIlIuCpAiIiIiUi4KkCIiIiJSLgqQIiIiIlIu\nCpAiIiIiUi4KkPv5+eefefjhh+nfvz8rV64Mdzkix8XSpUsZOHAggwYNYufOneEuR+S42bVrF927\ndw93GSLHzYoVK7jpppt45JFHmDt3bkjbVoDcT2FhIc899xz33HMPs2fPDnc5IseF2+3mySef5IIL\nLmDx4sXhLkfkuLAsi4kTJ1K7du1wlyJy3Pz2229UrVoVm81Go0aNQtq2AuR+OnXqRGFhIf/5z3+4\n5pprwl2OyHGRmZnJmjVrmDRpEk2bNg13OSLHxdSpU7niiiuIjo4Odykix01mZiZDhw6lT58+vPHG\nGyFtWwFyP3v27OHZZ5+lf//+VKlSJdzliBwXv/32G82aNWPChAm8/fbb4S5H5Lj46aefePfdd/n9\n99/54osvwl2OyHGxYsUKTNMkOTkZv98f0rYrTYBcsmQJvXv3BsA0TYYMGULPnj3p3bs32dnZAAwf\nPpxt27YxZswYvvzyy3CWK3JUjqSfu1wuHn30UYYOHcoll1wSznJFjsqR9POsrCyefvppzjrrLC69\n9NJwlityVI6kn9euXZtnnnmGUaNGBZcNFUdIWwuTCRMm8MknnxAbGwvAzJkz8Xg8TJs2jcWLFzNi\nxAhee+01Ro4cGeZKRY7ekfbzNm3a0KZNmzBXK3J0jrSflxg9enS4ShU5akfazzMyMsjIyAhLjZVi\nBDI9PZ2XX345+H7RokV06NABgBYtWrB06dJwlSZSYdTPpTJQP5fK4ETo55UiQF5yySU4HPsGW/Pz\n80lISAi+t9vt+Hy+cJQmUmHUz6UyUD+XyuBE6OeVIkD+XUJCAi6XK/jeNM1SvyiRk4H6uVQG6udS\nGURiP6+UATIjI4Mff/wRgMWLF9O4ceMwVyRS8dTPpTJQP5fKIBL7eaX8M61Lly7MmTOHXr16YVkW\nw4YNC3dJIhVO/VwqA/VzqQwisZ8blmVZ4S5CRERERE4clXIXtoiIiIgcPQVIERERESkXBUgRERER\nKRcFSBEREREpFwVIERERESkXBUgRERERKRcFSBEREREpFwVIERERESkXBUgRERERKRcFSBEREREp\nFwVIERERESkXBUgRERERKRcFSBEREREpFwVIERERESkXBUgRERERKRcFSBEREREpFwVIERERESkX\nBUgRERERKRcFSBEREREpFwVIERERESkXBUgRERERKRcFSBEREREpFwVIERERESkXBUgRkXJ45JFH\neOONN8JdhohIWClAioiIiEi5GJZlWeEuQkQk0sybN4/Ro0dTq1Yt1q1bR0xMDCNGjGDChAnk5+ez\nc+dOdu7cSaNGjRgzZgxxcXHMmDGDadOm4fV62bt3L3369OHGG29kx44dDBo0iD179gBwwQUX8MAD\nDwAwffp0pk6dimmapKSk8MQTT9CgQYNwfnQRkcPSCKSISBmWLl1K7969+e9//0v37t156KGHANi2\nbRv//ve/+eqrr9i2bRtff/01LpeL6dOnM378eD766COef/55Ro0aBcB7771HnTp1+PDDD5kyZQrZ\n2dnk5eUxf/58PvroI6ZMmcJHH33EnXfeSb9+/cL5kUVEjogj3AWIiESq008/nVatWgFw7bXX8vTT\nT3PKKafQuXNnYmNjAWjUqBG7d+8mPj6e119/nR9++IH169ezcuVKCgoKAOjQoQN33XUXW7ZsoW3b\ntgwcOJDExET+97//kZ2dTa9evYJt5ubmkpOTQ0pKSug/sIjIEVKAFBEpg91uP2CazWbD4dj3T6dh\nGFiWxdatW+nZsyfXX389mZmZdO3ale+//x6A5s2b8+233/Lzzz8zd+5cevTowYQJEzBNk6uuuio4\nsmmaJtu3byc5OTk0H1BE5ChpF7aISBlWrlzJypUrAZg2bRotW7YkKSnpoMsuXbqUtLQ07r33Xtq3\nbx8Mj36/n9GjR/Pqq6/SuXNnHnvsMRo2bMjq1atp3749n332Gdu3bwdg6tSp3HrrraH5cCIix0Aj\nkCIiZahatSovvPACmzdvJi0tjZEjR5KVlXXQZdu1a8eMGTPo2rUrhmFw7rnnkpaWRnZ2NrfeeiuP\nPPIIl19+OVFRUTRp0oTLLruMqKgo+vTpw+23345hGCQkJJCVlYVhGCH+pCIi5aOzsEVEDmLevHk8\n88wzfPrpp+EuRUQk4mgXtoiIiIiUi0YgRURERKRcNAIpIiIiIuWiACkiIiIi5RJRZ2Hv2JEX0vYS\nEqLJz3eHtE2RUFM/l8pA/Vwqg1D382rVEsucV6lHIB2OAy8SLHKyUT+XykD9XCqDSOrnlTpAioiI\niEj5KUCKiIiISLkoQIqIiIhIuShAioiIiEi5KECKiIiISLkoQIqIiIhIuShAioiIiEi5KECKiIiI\nSLkoQIqIiIhIuShAioiIiEi5KECKiIiIRLjXX8/irrv6hLuMIEe4CxARERGRQ/vll4UsX74s3GUE\naQRSREREJML5/SY2W+TEtsipREREREQOyjRN7HZ7uMsIUoAUERERiXCmqRFIERERESkH0/QrQIqI\niIjIkdMubBEREREpl8AubCPcZQQpQIqIiIhEOL9fu7BFREREpBxM01KAFBEREZEjZ1k6BlJERERE\nykGX8RERERGRcom0YyBDei9s0zR56qmnWLVqFVFRUQwdOpR69eqFsgQRERGRE06kXcYnpAFy5syZ\neDwepk2bxuLFixkxYgSvvfZaKEsIWjJrEe+OHY/XD6bNgWmzAzas4vmWBSb7ny5vgAE2AwybgVH8\nDGAU/0FgWgaWBZZlYFqBZZ3RYLcbmKaBaYLfb2BzgNMJwT8kDCPYbkk7xf/BMAzAwDICD8NmBFY0\nDCzDVvwabKYfwzIxTD8GYNnsWHY72O3B5Y39Pk7J64NNO5JljOIyoqIsDKPkswUe+y+3/yUH/r69\nknl/n24Y4HQaB9QDgd/LoS5jYBxspWOcd/h1j3a90MyLjY2isNADHMtnPLnnHeu6h1rvYA+bzVbq\nPRw4zWb7+3q2g65fer2S1xxke7aDtrX/69jYWKpXr4HdbseyrDIfNpsNh8MRUV9mIie7SNuFHdIA\nuWjRIjp06ABAixYtWLp0aan5CQnROByh+Qfpg4HP8sb6mSFpS0TkZGQYBg6HA6fTicPhOOB1IGQG\ngua+afZg+IyKiiImJpaYmBiio6NxOp3BR1SUE4dj3/vY2FiSkpKC27fb97URFRVFQkI8MTExxMbG\nERdX+hEdHX3UfwSIRArDsLDZ7KSkxIW7FCDEATI/P5+EhITge7vdjs/nw+FwFM93h6yWJ358j3t/\nWEVRrgub143N58FmmRiYBMYDLYrH/gLvLQvTBMu0MP1g+q3AaKNpYZqBZWy2wBhmyWvTtCgqtPB5\nweEAh93EbgO/z6KwCCx/YLvB8Ufrb+/NwLOBBWbx6KJZPMy3/2vLwrI7MR1R+O1RgVE6ryfwmXxu\n8PsxCIwcGMVtBD6MRaCpkmkWhmUG6wg+KFnPpPhHg2FZ+P0Wfm+gDic+7JYXu+XD7vdiWCaeqDh8\njlhsfi92nxu7z4NlgNcZj4mBw1uIw1uEw1uE3V+I3efBExWPxx4HvsA6Dr8Hu+nBsCwMTLBMbFbg\n2bDMwPTi9xS/Lplms/zYTB9O043D9JTZF6wy5xx+/rHO82PgxYmHKHw4il878RY/PESRRyIeokgg\nHxt+ComliBgKiKOIGIqIwUMU3uL1fTiC2yqZV0Q03r8tU9JGYfG2Cokt9VxEDAAxFIJhw4iOwu4w\ncDgsHI7A4LbDYQWfHQ6Ijgan0yIqat88wwg8lzwMA+x2KziCnZBgkZAACQmB5fx+i7g4i6Qk8HrB\n44GUlMB8jyfQdaOjLaKjISYm8BwdDVFRJk5n4P+1v/+RblmH/i0fav6xzCt5QMnrfdNN0zzI6F7p\nafsvY5qlt1d6XunXJe3tm85B2jtwfZfLxfbt2zBNs8yRUzCwLBOv14vP59vvUfLej8/nxe/34/P5\n8PsD0/x+f/Hrkvc+8vJc7Nixi6KiQjweDz6fr3i7XrxeX/FzYLvHomR0NfCIK/W8f+hMSEgkPj6e\nhIQE4uMTip/jSUhIJDk5mRo1ahIbGxtcVqFUQsnr9WG328jJKQhZm9WqJZY5L6QBMiEhAZfLFXxv\nmmYwPIaaI8ZBk57nhPQXIeHhBbyWFUgjfn8gjFtmIImUBGnTCr4vNa9kmukHjxfD4wa3G8PjCe6z\nDwZ5v7kv3Pv9GD4fhtsN7iJwRgWSjdu9bxtuN/i8xHl94PVieD3g9RU/e7E8PigqwsjPB48bf1wa\nls0BRUXYCgswinZjcxdg9xQFUpbXBz4fhs+L4fdh8x/bl24pFphuG25/PB5/HG5fLG57HG5bHIX2\neIpscRQZsRQYcRQQR74Vj8eKCoRgqzgQWw6KrBjySGAvyewlmd2+RNa4YsjzxeImmnwSyCUJ/zH+\n02S3B0JsTAxUrWqSnAw2mxU89MLphLg4i9hYiI09+HPJfKczsL3ERKhWzSIx0SImxiImJrB9ZYjj\nz7IsCgsLycvLCwbVkmDq8/nweNw4HBbbt++hsLCQoqJCCgsLKSwsoLCwkIKCAoqKioLvS+YVFBSQ\nn5/P9u3bKShw4XK5cLnyKSwsPGxNTqeT1NQ0qlSpQmpqGklJSSQkJFKzZi0aNGiIz+cjNTWNevXq\nkZZWhbS0KsTFRcbIkZyYTNPCMCrpLuyMjAy+//57unXrxuLFi2ncuHEom5fKzDAgKir49mhHDk8o\npgluNymxdnK37S4OmV4MX3Fg9QWG94yiIozCAoyCAigsxChwYRQEnjEMrJjYwIhv8fSowkKii5c3\nCovXKdyKUVgYnGYUFAS2fZQjR/6YOHxxSVhOJ5YziqL4KhTEV8GKicMfE4vHFkuRI54CZxIFjmRc\n9iTy7UkUOJLIsyXjciSTSxK7/cls3RNDTk4g5ZUMvhcWGuzebVBYaFBYSPC5qKh8adAwLOLiKDWK\nmpBgER9P8fPBp++/fMky8fGB+QqkBzIMI7g7uiwpKXEVNiDg9/txufKLA6WL/Pw89uzZw9atW3C7\n3bhcLvbs2c3u3bvYtWsXOTl72LhxI3l5uWzZ8hder/eg242Li+OUU6pTvXoNEhISSE5OpnHj02nS\npCl169YlMTGJxMQk0tLSIupYN4kMlfos7C5dujBnzhx69eqFZVkMGzYslM2LVC42G8TGQkocJlGH\nX/54sCwoFVi9GHm52PJyMXJzMVwu8LgDIdbtxnDlY+TlBebl52F4A6O+8bt2k7B7M0ZuYSCoFhVi\nuFwYRUWHLyE6GisxETMxCSsxCSspCatqUmBaUuDZSkzGSkrCn5CIOzqJQmcSBc5AEC1wJOKNSSQ3\n386OHQb5+QZFRftCp8tlkJ9f8hx4/ddfBvn5NlyuwPSCgiNLhYaxf/gsHTYDQdMiOdkiORlSUkpe\n73ukpAR2/Ydpx85Jw263k5SUTFJScrnX9Xq9bN68iaioKHbt2smGDRuKw+ZuduzYzvbtW9m2bRu7\ndu1k9eo/+OCDXePFjgAAIABJREFUGQdsIy4ujoYNG9OoUWPq1z+V+vVPpV69U6lfvz7Vq9fQrvNK\nKtLOwjaswx0cFEI7duSFtL2K/ItVJFKd1P3c4ykOnHux5RcHz+L3gaC637S8vRh5edhyc/cF1Nxc\njLxcDNM8bFNmlSr4a9XBSk7GiomBmFisuDjMtCqYVathnnIKVpXi11WrYVapCsUjZn4/uFyQn28E\nA2cgbO4fPkvP3z+Q7r/s3r0GXu+hA8S+oLnvkZoa2J1ftapFtWoWVatawddVqlgnfOg8Uft5fn4+\nq1evYuvWreTm7iU3dy/Z2etZvfoPVq/+g82bN5U61jY2Npb09HrUq1efevXqc9ppDahXrz7JySk0\nbXpmqfMM5ORy/vnn0bRpU8aNezNkbUbMMZAiIhUqKgqrSpVAcDvabVgWuFz7BdDc4HMwgObuxbZj\nB7a/NgWm5eUFRkELCrDt2hnYZX+wTcfFYVapilm1KqlVqmJVqRp4XzzNqlIF89QqWKmpmKdUx0pM\nOqJyCwsDQXLvXoOcHIO9e/e9P9j0DRtsLFlisHOno8zw6XAEjhGtUsWiRg2L6tUtqlc3qVHDKn4E\nwmdSUmAENCnJwuk82h+6lEhISKBly8wy57vdbjZv3sj69X+yfv16srMDj/Xr/2TOnNm4XPnBZaOi\nomjZMpPTTz+D008/ncaNT6dp0zOpWrVqKD6KHGeVehe2iEjEMQxISMBMSIAaNY9uGy4Xth3bse3c\ngW3XLmw7d2Ds3IFt505su4ofO3ZgW7kiMK+MXe9mtVPw162LWaUqVlqVQNBMq4JVtSr+GjUwa9TC\nrFWLuOQU4uKgZs3y7UCyLMjNhR07DHbutLFjh1H82sDnC4yU7tplsHWrjY0bDRYudLBrV9lfWDVr\nmjRsaFK9+v4jmoH3NWsGQmdKio7rPBbR0dGcdlpDTjut4QHzLMti+/ZtbNiQzZ49u/nppzksXDif\njz56n717c4LL1apVm+bNW9CiRUvOPrsFzZu3pFq1aqH8GFIBIm0XtgKkiMixio/HjD8Vs/6ph1+2\nZMSzJFju3oWRk4Ptr7+wr12Nfctf2LZuxbZ8WWB08yBh04qNxV+jJmat2pg1amLWqYu/bjr+uumY\nddPx16kbOEX8bwwDkpMhOdmiYUP/EX00jwe2bzfYsiVw4tHevQa5uQZ79hhkZ9tYu9bGvHk2du06\n+LGeMTGB0cwaNUxq1gy8rlbN4pRTAkGzQQOTOnWsAy69JIdnGAbVq9egevUaAFx88aXAvmC5cuUK\nli9fxpIlv/Lbb4v58svPguvWrl0nGCo7d76EZs3O0rGVES7SLiSuYyBPwGNmRMpD/fwEZllQUBAY\n2dy6FfuWzdi2bMH212ZsW7cEwmbx4+9nvPtPqR4Ik+npmHUC4dKfno5Ztx7+2nWCx2dWJJcrMLq5\nbZuNrVsNtm412LKl9Ovt2wPHee4vKsoiNTUwglm/vkn9+oHnevVM0tNNatcOXO/zUNTPDy8vL5ff\nf/+NJUsWs2TJLyxZspi1a9cAkJ5ejxYtMujUqTMdOlxAnTp1FSgjTKtWzWnfvh0vvBC6O/jpGEgR\nkRORYRSPbsZj1qtPmRdF8vsDgXLjBmzZ67Fv2oht4wbsGzfg/PUXbJ9+gvG3S8uYVavhT0/HX7de\ncATTLH7vr1MX4uPLXW58fOBs8fr1Dz26mZ8fCJpbtthYs8bGn3/ayMmB7dtt/PGHjW++seHx7H8b\n1MBxmHXrmtSta5GebpKeXvI+EDDl8BITk2jbtj1t27YPTtu1axeffPIhs2f/yMKF8/nkkw8BqFGj\nJjfccBPt219A8+Znk5ycEq6ypZhlaQSyTBqBFKl46ueC349t21ZsGzdi35gdCJrFAdO2cQP2TRsD\nF8fff5WatfA3bIy/YUP8DRvha9gY/2kNMGvXOe7XCfL7YcuWwMk/GzYYbNxoK34Epm3ebGCapQPm\naadB8+Y+zjjD5LTTTOrXNzn1VBOdlHzkLMti6dLfWbhwPjNnfsXMmV9jWRYOh4P27c/nssuupFu3\nK3T8ZJi0bHkGnTt3ZtSol0LW5qFGIBUg9cUqJzn1czks0wycBLQhEC7tG7Kxr1mNfc0f2NeswZa7\nN7ioZbfjb9gIb+Y5+Bs0wqxTB1+jJvgbNyl1sf7jyesNBMySUJmdbWPduigWLLDYtKn0CE21aoFA\n2aSJSdOmJmecYdK0qZ8UDagd1o4dO1i27HdmzfqBTz/9mD//XIfNZqNNm3a0a9eBa665lgYNGoW7\nzErj7LNPp2vXrjz33Asha1MBsgz6YpXKQP1cjollYWzfjmPNH9jX/4ktez2Opb/h/GUhtt279y3m\ncOBv1ATfGWfiO6MZvjPPxH9GM8zqNUJyGnZJP8/Ph/XrA7vFAw+DNWtsrFxpZ+/efXXUqhUIlE2b\n+oufTRo1Mg97rGVlZVkWy5cv4+OPP+Cbb75i+fKlWJZFZuY5dOrUmVtvvYNTTjkl3GWe1Jo1a8QV\nV1zB8OFjQ9amAmQZ9MUqlYH6uRwvRl4utk2bcKxagWPZUuzLl+JYvgz75k3BZcwqVQKBsjhY+s84\nE1+Tpgc9S/xYHK6fW1Zg1HLFChvLl9tZscLGihU2Vq/ed7ylwxE4K3z/kcqmTQPHXep8ktK2bdvG\n1Kn/4auvPufXX38hOjqa7t17cO2119OuXQedgHMcnHFGA7p3787QoaNC1qYCZBn0xSqVgfq5hJqR\nswfHiuXYl/2OY/kyHMuX4lixHKOwEADLZgscV3lGYJTSd2YzvC0ysY7h2Lqj7edeL6xbZwsGypJw\nuWHDvl3hCQkWp58eCJTNm5u0beunYUNTobLYunVrePHFsXzyyUe4XPmcddbZXHddTy6//Erq1k0P\nd3knjaZNT6VHj+t5+unnQtamAmQZ9MUqlYH6uUQEvx/7+nXYly/DsWxpcbBchn3D+n2LpNfD2zIT\nX8tMfBmZeJs150jPgqnofp6fT3Go3DdauWKFnT17AqkxLc3krLNMmjcPhMqzzvJTv37lvp5lYWEh\nH3wwnQkTXmf58qXYbDauuOJq+vbtR0ZGq3CXd8Jr3DidG2+8iaeeGh6yNhUgy6AvVqkM1M8lkhm5\newOB8tdfcPyyEOevi7Bv3BCc70+vjzcjA2+b9njbtAucrHOQlBaKfm5Z8OefBnPmOPj1VxtLlthZ\nudIWvD1kUpJFZqaf1q39nHeen5Yt/cTGHteSIlZ29nreeuvfTJ48idzcvbRo0ZKbbrqVXr1uIloH\nmh6Vhg3rcuutt/LEE0ND1qYCZBn0xSqVgfq5nGiM7dtx/roIx7LfsS9fhnPBPOxb/gLATEvDe15b\nvG3a4m3TDl+z5mC3h62fu92wapWN336z8+uvNhYssLNyZeB2c06nxdlnm5x3np/zzvNx7rl+0tJC\nXmJY5efnMXXq27zzztssW/Y7tWvX4Z//fIgbbrgZp26mXi6nnVabO+64ncceeyZkbSpAlkFfrFIZ\nqJ/LCc+ysGWvxzn3J5w/zyHqp9nYs9cDYCYk4j2vNY4LO5Lb4lx8LVqG7HJCZdmzBxYssDNvnp25\ncx0sXrxvlLJJEz/nnrtvlLKynKBjWRY//vg/RowYyqJFC0hPr8+DDw7iuut64jjO1xU9WdSvX4O7\n776bwYP/FbI2FSDLoC9WqQzUz+VkZPtrc3Gg/Ann3Dk4Vq0EAvcJ92aeg7dtezwdOuLLyIQwj3QV\nFsKSJXbmzg2Eyvnz7eTlBVJjzZolI5R+Onb0cdppJ3egtCyLb7/9mueeG8aSJb9y2mkNGDZsFJ06\ndQ53aREvPf0U/u//+jFo0JCQtakAWQZ9sUploH4ulUGK10XBV9/inDsH509zcCz7HcOyMOMTAru7\nO3TE0+EC/GecedBjKEPJ74eVK23MnRsIk3Pn2tmyJVBTerpJx44+OnXyc/75vpP2TjqWZfHll5/z\n7LNP8ccfq7j77nvp2/c+atWqHe7SIladOlW5//4HeOihx0PWpgJkGfTFKpWB+rlUBn/v58buXTjn\nzCJq1g84Z/2AY+0aIHBdSk/7C/C2Px/PhRdhptcLV8lBlgXr1xv8738Ovv/ezqxZDlwug+hoi3bt\n/HTp4uPii33UrRsxX9cVprCwkMcff4S3334Tm83GzTf/g0GDHqNq1arhLi3i1KyZyoMPPsTAgY+G\nrE0FyDLoi1UqA/VzqQwO189tmzfhnPVDMFDat24BwNu8Be4rrsJz+ZX4I+S2fB4PzJ9v56uvHHz9\ntYM//wyMTjZt6ueSS3x06eIjI8PEbg9zoRUoO3s9r732MpMnTyIuLp4BAx7mzjvv1hnb+6lePZnB\ngx/lgQcGhaxNBcgy6ItVKgP1c6kMytXPLQv7mtVEff0l0Z9+hHPRQgB8Tc/EffmVuC+7En/TM0Jy\nC8YjsWaNwddfB8LkvHl2/H6DqlVNLrrIz8UX++jY0Udi2d/zJ5Q//ljFU089xsyZX1O//qmMGDGa\nTp26hLussLMsi+rVk3n88Sfo3/+hkLWrAFkGfbFKZaB+LpXBsfRz2+ZNRH/2CdH//RjH/LkYloW/\nXn3cl16Op9vleM85j0gZ7svJge++C4TJ775zkJNj4HRadOjg59JLfXTt6qN69Yj5Wj9q33//LU88\n8Qh//LGKm2++leHDR1fq0Ui/30/NmqkMGfIk/foNDFm7CpBl0BerVAbq51IZVFQ/t23bStRXXxD1\nxadEzfoBw+PBrFoV9yXdcF99Ld7250dMmPT5ApcL+uILB19+6WD9+sCu7lat/Fx1lZcrr/RRs2bE\nfMWXm9vtZuTIYbz88vOce25rnntuLGee2SzcZYWF1+uldu0qPPXUv7j33n+GrF0FyDLoi1UqA/Vz\nqQyORz838vNwfjeT6M8/JerrL7Hl52FWO4Wiq7vjvuY6fJnnRMxubssKnNn9xRcO/vtfB8uWBULu\neef56N7dx9VXe0lNDXORR+njjz/g/vv/j4ICFz173sjzz2dVumtHut1u6tatxjPPDOXuu/uHrN2Q\nBkjLsjj//POpX78+AC1atGDgwIF89913vPLKKzgcDq699lquv/76A9ZVgBSpeOrnUhkc935eWEjU\nzK+J+XAGUd98ieF240+vj/uaaynq3iNwzGQEWbPG4OOPnXz0kYNVq+w4nRZduvi4/nofnTv7wn2t\n9XLbs2c3WVkv8vLLz3PVVd158cVXiYuLC3dZIVNYWEi9etV59tlh9OnTL2TthjRAZmdnM3z4cF5/\n/fXgNK/XS7du3ZgxYwaxsbHccMMNvP7661SrVq3UugqQIhVP/Vwqg1D2cyN3L1Gff0rMhzNw/vg/\nDL8fb7PmuG+4iaLu12NVqRKSOo6EZcHSpTbee8/J++872LnTRmqqxdVXe7n+ei8ZGWakDKIekays\nF3n66Sdo0KAhr7wynoyMVuEuKSTy8/M57bRaDB8+gjvuuDdk7R4qQFb41VSXLVvGtm3b6N27N336\n9GHdunWsXbuW9PR0kpOTiYqKIjMzk4ULF1Z00yIiIsedlZSMu9dN7J32Ibt++4O84aPAbifhsUFU\nad6YpNt7E/XNl4GDFMPMMOCss0yeecbNb7+5eOedAjp29DF1qpNLL42nbdt4xo6NYsOGEyNF9ut3\nPzNmfEJRURGXXdaFkSOH4ff7w13WcWdZJgD2CDn+Fo5xBHL69OlMnjy51LQhQ4awa9cuLr30UhYu\nXMjw4cMZPHgwb7/9Ni+88AIAL774IrVq1aJHjx6l1i0s9OBwhO6HY7fb8PvNkLUnEg7q51IZREQ/\n//13bG+9ie2ddzB27MCqUQOzx/WYN90EGZnhre1v9u6FDz4wmDLF4McfA+Hx/PMtbr7Zont3i6Sk\nMBd4GHv37uWBB+5nypS3ueSSS5gyZSpJkV70McjJyeGUU6oyduxY+vUL3TGQTmfZmazCd2EXFhZi\nt9uJKj7Aon379kycOJExY8YwYcIEAIYNG0ZGRgZdu3Ytta52YYtUPPVzqQwiqp97PIHjJd+bStTM\nrzA8HryZrSi88x7cV1xNpB2AuGGDwYwZTqZPd7J2rY2YGItrr/Vy330eTjstYs6zPYBlWbz11r8Z\nPPhBzj67JdOmfUBSUnK4yzoudu/exemnn8rYsc9z8813hKzdkO7CzsrKCo5Krly5klq1atGgQQOy\ns7PJycnB4/GwcOFCWrZsWdFNi4iIhF9UFJ5ul5P75hR2LVtD3vBRGDk5JPW9k7SMM4kbNRxj+/Zw\nVxmUnm4xYICHn35y8cUXLnr08DJjhpM2beK5+eZYvvnGTiTuJTYMg1tvvZ2JE9/it98W06XLBfz8\n85xwl3VcmGYgyJ80u7APZu/evTz00EMUFBRgt9sZMmQIDRo0CJ6FbVkW1157LTfddNMB62oEUqTi\nqZ9LZRDx/dw0cf7vW2InjiN65tdYUVG4r76Wwrv64mveItzVHWD7doM33nDy9ttOduywUaeOyc03\ne/nHPzykpYW7ugP99NNs+ve/l02bNjBu3CSuuqp7uEuqUNu3b6dZs4a8/HIWPXveErJ2dR3IMkT8\nPzgiFUD9XCqDE6mf29euJnbiOGKmTsEocOE9rw0Fd/XFc+nlEGHXN/R64csvHUye7OTHHx3ExVnc\neKOXe+7xkJ4eMfEBCJypfOON17FgwTxGjnyem2++FeNEOsX8ELZu3ULz5k145ZVX6dHj5pC1G9Jd\n2CIiIlI2f4NG5A8fza4lK8j/1zBsW/4i+Y5bSDv3bGKzXsTID+1gyqE4nXDFFT5mzChk1iwXV17p\nY/JkJ+edF88998SwdGnkxIiEhATeeWc67dufz8CB/bn//ntPmjO0TTPyzsKOnN+8iIhIJWIlp1DY\ntx+75y1m75vv4K9Xn4SnnyAtsxlxz4/CyN0b7hJLadLE5KWXiliwwMVdd3n56isHnTrF07NnLLNm\n2YmE/ZkJCYm8++4HDBjwMO++O4X+/fueFCGyJEDabJET2yKnEhERkcrIbsfT7XL2fvgZe778Dm+r\nc4kf/gxpmWcFTrjZmxPuCkupVcviX/9y8+uv+Tz2mJulS21ce20cl1wSxyefOMJ+wo3dbueRRx7n\nkUceZ/r0d3nwwfuDAexEVRKCFSBFRETkAL6MVuROmc6eb37A26Yd8aOGk5bRjLgRQzH27A53eaWk\npMD993tYtMjF6NFF5OYa3HlnLG3axPPmm07c7vDWN2DAwwwY8DBTprxF//59KSoqCm9Bx2DfCKR2\nYYuIiEgZfGe3JPetqez+djbeCy4kfuxI0jKaEf/svzB27Qp3eaXExMAtt3iZM8fFG28Ukppq8fDD\nMbRrF89774V3RHLQoMcYNOgx3ntvKtdc0428vNzwFXMMSu5EoxFIEREROSz/Wc3JnfQfdv8wF0+X\ni4l9aSxVMpsR//QQjB07wl1eKXZ74ISbL78sYNq0AlJSLPr1i+Wii+KYOTM8x0gahsHAgYOYNOlt\nlixZzO2398br9Ya+kGNUcpclBUgRERE5Yv6mZ5A3/k32zJqP+9LLiH31Jaq0akbcsKcj7mQbw4AL\nL/Tz9dcFjBtXSEGBwY03xnH11bHMnx+e2HH55VcyevSL/PDD9zz44P1E0BUMj4hOohEREZGj5m/c\nhLzXJrJnzgLcl15G/AujA5f/GfcKYT/o8G9sNrjmGh+zZ7sYPryI1attXH55PFdfHcucOaE/lu/G\nG3szcOAgpk59m1Gjhoe8/WOhy/iIiIjIMfM3aETe65PYM/NHfGedTcITg0lrm0n09Hchws44joqC\nO+7wMn++i6efLuLPP21cc00cd9wRw6ZNob3Q98MPP0qvXjcxevQIXnppbEjbPhYagRQREZEK42ve\ngr3TPybnvY8wU1JJ+r+7SOl8Ps45s8Jd2gESEuCee7zMneti0CA3M2c6aNcuntGjoygsDE0NhmHw\n/PNZdO/eg6FDn2LGjGmhafgYmaYu4yMiIiIVzNuxEznf/EDu629gy9lDyjWXkXTrjdjWrQ13aQeI\njYWBAz3MmeOiSxcfI0dG06FDPJ995gjJiTZ2u52srHG0bt2WBx98gD/+WHX8Gz1G+3ZhR05si5xK\nRERE5OjZbLi792D3nIW4Hh1C1A/fk9bhXOKfeRJcrnBXd4A6dSwmTizigw8KiI+3uO22WHr0iOWP\nP45/NHE4HIwbN4m4uFhuvvl6du7cedzbPBbahS0iIiLHV2wsBQ88yO55v+K+9nriXn6etA7nEvX5\np0TE/Qb/pn17P99+W8CwYUUsWWKnY8c4nngimtzjfMnGmjVrMXnyVLZu3ULv3tfjjrCTkPanO9GI\niIhISJjVa5D30mvs+eQrrMREkv9xI0k3X48te324SzuAwwF33unl559d3HCDl/HjnbRuHc/UqY7j\nek7QOeecx6uvTmTRooUMHfrU8WvoGJlmIPjrLGwREREJCV/rNuyZOYv8fw0jas5s0s4/j9iXxkIE\nXlC7alWLMWPcfP11AfXrW9x/fyyXXRbH6tXHL65cfvmV3HHHXYwb9wqffvrJcWvnWGgXtoiIiISe\n00lh337snrMAT8eLSBj6FKkXtccx9+dwV3ZQZ59t8tlnBbz8ciHr1tno1CmOV191HrfbIj755FAy\nM1vRt+8d/PTT7OPTyDHQWdgiIiISNmbtOuROfoe9b72LkZ9P6pWXkDCwP8ae3eEu7QCGAT17+vjx\nRxcXXujjqadiuOqqWNatq/hrR8bExDBlynTS0+tx5523sHt3ZN1vXBcSFxERkbDzdO3G7lnzKbi3\nPzHv/IfUDufh/G5muMs6qOrVLSZPLuKVVwpZtcrOhRfGM2GCs8KPjUxLq8L48W+Sk5PD448/UrEb\nP0bahS0iIiKRIT4e11NDyfn6f1hpaaT06k78Yw8Tsqt6l4NhQI8ePmbNctGunZ/HHovhmmtiWb++\nYkcjzzyzGQ888CAzZkzj66+/qNBtHwudhS0iIiIRxXfW2ez56n8U3Hk3cRNeJ/WSjtiXLQ13WQdV\no4bFlCmFvPRSIUuX2unYMZ5Jkyp2NPKBBx6kadMzeOihf5Kbu7fiNnwMLEu7sEVERCTSxMbiGjaK\nnHffx7ZrF6mXdCT2tayIu682BEYje/UKHBt57rl+Hnkkhh49Ytm4sWJGI6OionjhhVfYtm0r//rX\nExWyzWOlXdgiIiISsbydurD7h7l4OnUm4clHSb7+Gmxb/gp3WQdVu7bFtGmFjBlTxC+/2Dn//Hj+\n8x9nhVwrvWXLTPr2vY///OdNfvzxf8e+wWPk9ytAioiISASzqlYld/JU8ka/iHPhPFI7tiHqvx+H\nu6yDMgzo3dvLjz+6yMjwM3BgDPfcE0N+/rFv++GHH+W00xowYEB/8itig8fgpB2B/Oabbxg4cGDw\n/eLFi+nRowe9evUiKysLCHz4IUOG0LNnT3r37k12dnZFNC0iIiIVzTAouuU29nw7C3+9+iTf0ZuE\n+++NyHtqA9StazF9eiGPP+7m448dXHxxHCtWHFvEiY2N5YUXXmHDhvUMH/50BVV6dPYFyJPoGMih\nQ4cyZsyY4IcDePLJJxkzZgxTp05lyZIlLFu2jJkzZ+LxeJg2bRoDBw5kxIgRx9q0iIiIHEf+Bo3I\n+WwmrgceJObdKaR264x93Zpwl3VQNhv07+/h/fcL2bvXoGvXOKZNcxzTNlu3bssdd9zFxInjWLBg\nXgVVWn6ROAJ5bD9ZICMjg86dOzNt2jQA8vPz8Xg8pKenA9C+fXt+/vlnduzYQYcOHQBo0aIFS5ce\neIZXQkI0Dkfo0rXdbiMlJS5k7YmEg/q5VAbq58fZyBH4O1+I/ZbepF7cEf8b/8a66qpwV3VQl10G\nixZZ9O5tcN99sSxebPL88xYxMUe3vVGjRvLll5/x5JODmT37p7CEuJiYQFxzOh0R08+POEBOnz6d\nyZMnl5o2bNgwunXrxrx5+1J5fn4+CQkJwffx8fFs3LjxgOl2ux2fz4fD4dhvXfdRfYijlZISR05O\nQUjbFAk19XOpDNTPQ+DcDti++ZGkO3rj7HEtBff9E9fgJ8BxzGNRFS4mBqZOhZEjo3jhhWjmzfPz\nxhuFnHrq0ZxhY+ORR57gvvvuYeLEf3P99TdUeL2Hk59fcm1OI6T9vFq1xDLnHXGM7tGjB59++mmp\nR/PmzQ9YLiEhAdd+x0i4XC6SkpIOmG6aZqnwKCIiIpHNrJtOzidfUdj7NuJefp7kntdg7NgR7rIO\nyuGARx/1MGVKAZs22ejcOZ7PPju63NGjRy9atszg8ccHsW7d2gqu9PAicRd2hVeSkJCA0+lkw4YN\nWJbF7NmzadWqFRkZGfz4449A4CSbxo0bV3TTIiIicrzFxJA/5kVyX3wV54J5pHbugGPh/HBXVaYu\nXfx8+62LRo1MbrstliFDovF6y7cNm83GuHH/xmb7//buMzCqKu/j+HcyQ8pkUgBRpCola6MYFFHD\ng1JEQbFASECDgBTRqGtCEaQJIXTc1ShSpUm1ILYFQVcEQVY0KhFBURF1waCUzKRMZuY+LyLRLAQS\nkswMzO/zipw7uec38bz4e8695wTRp09iiQkxbwiYk2ieeuophg4dSo8ePbjiiito0aIFnTp1Ijg4\nmMTERCZPnszIkSOromsRERHxgoJe93H0rXehWjDRd95G6KIFvo5Uqvr1Ddaty2XAACcvvBBMYmIY\nR46U7x6XXHIpc+cuYu/ePbzwQkbVBC3FiRlIfzqJxmQYlbHlZuXIzs7xan96ZkYCgca5BAKNc98x\nHT1CxJABhGx6l7w+/bGnT4PgYF/HKtXq1RZSUkKpW9dg2bI8mjYt32k7/fsn8d57G/n440wuuuii\nKkpZ0ooVy3jssYf45pt9REXV8kqfUEnPQIqIiIj8LyO6OseXrSb3kccJW7KQqB7dMB0+7OtYperZ\n08Wrr+aSkwO33Wbl/ffLN6s3evR4nM4Cpk+fXEUJTxYwS9giIiISQMxmHGOe4vjs+VTL/JTqt7TD\nvPsrX6f0S7JfAAAgAElEQVQqVevWHtavz6VePQ+9e4exYEHZj0Bs1Kgx/foNYNmyRezZ83XVBv2D\nPy5hq4AUERGRSlHQvSdH1/0LCguJ7nYr1bZt9XWkUtWvb/Dmm7l06uRi5MhQRowIweUq2++mpIzA\nZotgwoQxVRvyDwHxFraIiIgELlfLWI6+vRFPrVpE9bzLb8/RBrDZYNGifJKTC1i0KJi+fcPKdFpj\nzZo1eeyxVN59dz0ffvhBlefUEraIiIic9zz1G3D0zQ24mrUgckAfQhfM9XWkUgUFwdixTqZOzWfj\nRjM9elg5fNh0xt8bOPBB6tWrz/jxo0sc51wVDENL2CIiIhIAjBo1OfryOpydbyNi5FCs6RMo84OG\nPtCvXyELF+aTlRVE165Wvv/+9EVkaGgoo0aN5csvP+fll1dVaTYtYYuIiEjgsFo5vnAZeUl9Cf/H\nDCIee4hy7+LtRV26uHj55VyOHjVx++1WsrJOXybdc088LVpczeTJE8nLyzvtZyvC7VYBKSIiIoHE\nYsE+4584ho0kdOVLRPZJBLvd16lK1bq1hzfeyMVigbvusrJjR+mlUlBQEOPHp/Hzzz8xb97sKsuk\nGUgREREJPCYTucNGkjPzGYLf30R0/J2Yjh/zdapSxcR4ePPNXGrWNIiPt/Lee6U/e3jjjW3p0KET\nL7yQQUFBQZXk0TY+IiIiErDyk/pyfMFSLJ9/RlTC3X5dRJ44/rBxYw9JSWGsXWsp9bODBj3E4cOH\neeONtVWS5cRLNJqBFBERkYDk7HpHURH5xedE9bwL07Gjvo5UqgsvNFi7NpdWrdwMHhzKkiXVTvm5\ndu1upnHjJiyoorfNtY2PiIiIBDznbV2Lisgvv/D7IjIyElauzKNjRzdDh4byzDPBJ71MHhQURP/+\nA9m58z/s3PmfSs+gJWwRERERwHlrF46/uAxL1i6i4u/EdPSIryOVymqFRYvyuOeeQtLSQpgwIeSk\nIrJXr/uIjo7mmWeervT+9RKNiIiIyB+ct9xWVER+lUVU/F1+XURWqwbPP59P//5OnnsumKlTg0tc\nt9ki6N9/EO+88yZ79+6p1L5PLGGbTGfe4NxbVECKiIiIzzg73crxRS9h2Z1FVI87MR353deRShUU\nBJMnF3DffU5mzQphzpySz0QOHDgEq9XK9OmTK7Vfw/D41fI1qIAUERERH3N27Mzxxcux7Nnt90Wk\nyQTTphXQtWshY8aEsmjRn0VkzZo1GTLkEV5//VU++WRHpfXp8Rh+tXwNKiBFRETEDzg73MKxxcux\n7P2aqO7dMP3+m68jlcpigRdeyKdTJxfDh5d8O/vhhx/jwgsvYvz40RiVdHSj2+1WASkiIiJyKoXt\nO3FsyUos3+4luns3v34mMiQEFi7Mo2NHF0OHhvLSS0VFpM1m4/HHh7Jjx3Y++2xnpfTl8WgJW0RE\nRKRUhTd34NjiFZi/2UNUrx5+fezhiSKyfXsXKSkhrFxZtNl4z569CA+3sXDhvErpx+PxYDL5V8nm\nX2lEREQk4BXe3IHjcxdhyfyUqPt7Q36+ryOVKjS0aIuftm3dPP54KO++ayYiIpKePRN5/fVX+e23\nii/FezxawhYRERE5I2eX28n55/MEf/hvIgf1g8JCX0cq1Yki8qqrPAwYEMbOnUH06zeQgoICXnpp\nSYXvX7SE7V8lm3+lEREREflDQc9e5EyeQci/3iLi8WRO2r3bj9hs8NJLeVx4ocG994ZRrdoV3Hhj\nW5YsWVi8j+PZ8ng85+cM5Lvvvktqamrxzxs2bKBjx44kJSWRlJTEjh078Hg8jB07loSEBJKSkti/\nf39ldC0iIiLnsfwHBuEY8SShq1dgnZrm6zindeGFBqtW5RIUBAkJVu65ZxA//rifTZs2VOi+brf/\nFZCWit4gLS2NLVu2cPnllxe3ZWVlMWzYMDp37lzctmHDBpxOJ6tWrSIzM5MpU6Ywe/bsinYvIiIi\n57nclOEE/fwT4bOm46nXgPz77vd1pFI1amSwfHked91lZcGCHlx00XAWLpzHLbfcdtb3PC9foomN\njWX8+PEl2rKysnjllVfo3bs3U6ZMweVysXPnTtq2bQtAy5Yt2bVrV0W7FhERkUBgMmGfOgtn+47Y\nhv2d4ArO6FW1li09LFyYx969IYSEDOK99zby3Xf7zvp+/ngSTZlnINesWcPixYtLtKWnp9OlSxc+\n/vjjEu033ngjHTt2pF69eowbN46VK1dit9ux2WzFnzGbzbhcLiyWPyPYbCFYLN77A5nNQURHW73W\nn4gvaJxLINA4DxBr1kCH9kQOuB/Xe+/D1bG+TlSqe+6BuXMN+vcfjMk0ieXLFzFjxsyzupfFEoTF\nYvarcV7mAjI+Pp74+PgyfbZ79+5ERkYC0KFDB9avX09ERAQOh6P4Mx6Pp0TxCGC3F5Q1TqWIjrZy\n9GiuV/sU8TaNcwkEGueBwkzQkpVEd+lI0B13cPSdTXjqN/B1qFLdfjuMHl2DtLQevPDCYlJSRmK1\nlr8AzMsrAEy43R6vjvNatSJKvVbpC+qGYdCtWzcOHjwIwLZt27jyyiuJjY1l8+bNAGRmZhITE1PZ\nXYuIiMh5zlP7Yo4tfxlTfj5RvXv49Wk1AI884uT22x/A6TzKE0+8fVb3KHoL27+WsCu9gDSZTKSl\npZGcnMx9991HXl4ePXv2pFOnTgQHB5OYmMjkyZMZOXJkZXctIiIiAcB92eUcX7wc83f7iOyfBE6n\nryOVymSCOXOuJTT0ElauXMGWLeUvBIsKSFMVpDt7JqOyTvquBNnZOV7tT0seEgg0ziUQaJwHppA1\nK4l8eBD5Cb3JeWZ2UbXmpyZOnMSzz04jKmo/GzZU59JLy15+DR7cj88/z+Trr/ecv0vYIiIiIt5Q\nEJ+IY/goQlctJ2x2hq/jnNa99yYCBgUFS+jTJ4yccsyZeTyG372FrQJSREREzlm5qSMouP1OwieM\nodqHH/g6TqkaNWpMXNz/ERExl2++MXjwwTDKekDNeXsSjYiIiIhPmEzkPPM87iZNiRzUl6Cff/J1\nolL16zeQ7Owfue++13n3XQuTJgWX6ffcbrcKSBEREZHKZNgiOL5oORQ4iex/H+Tn+zrSKd12W1cu\nvrgOBw7Mpm9fJxkZIaxefeYdFQPiLWwRERERb3M3aUpOxhyqffYptieH+zrOKVksFu69tw///vd7\nPPzwd8TFuUhNDeWTT05fjhmGlrBFREREqoSzy+04Hh9K2NJFhC5d5Os4pxQfn4hhGLz++mrmz8+j\ndm2D++8P45dfSn+DXEvYIiIiIlUod/iTOG/ugG3kUCyffuLrOCe59NJGtG7dhjVrVlC9usHSpXnk\n5ZkYMCCMwsJT/47H48Fs9q+Szb/SiIiIiFSE2czx2fPx1L6YyP5JmLKzfZ3oJD179mLPnq/58svP\nuewyD08/nc8nn5iZPPnUL9V4PB5MJv8q2fwrjYiIiEgFGTVqcvzFZQT9/huRg/qCy+XrSCV063YX\nwcHBrF69AoA773Rx//1FL9Vs2nTyyzIej6ElbBEREZGq5mrWgpwZ/yR464eET3rK13FKiI6uTufO\nXXj11Zcp/GPdesKEAq64wk1ycij//W/J5yE9Hj0DKSIiIuIVBT17kdf3AazP/ZPgTRt8HaeE+PhE\nDh/O5t//3gRAWBjMn1/0POTgwaElJk2LnoHUNj4iIiIiXmGfMBnXFVcRkTyYoP/+4us4xdq370jN\nmjVZvXplcVuTJgbTp+ezfbuFGTP+fB5SJ9GIiIiIeFNoKMfnLcKUl0fEkAGU+fzAKhYcHMxdd3Xn\nX/96i2PHjha3x8e76NWrkKefDuaDD4pmHd1ut16iEREREfEmd9MYcqbOIvijLVhnTvV1nGI9e/ai\noKCAN954vUR7eno+MTEeHnoolEOHTNrGR0RERMQXChJ6k9+zF9ZZ06i29UNfxwGgZctYmjRpWvw2\n9gnh4TBvXj52u4mHHgrVEraIiIiIr+RMmYm7UWMiHnwA0+HDvo6DyWQiPj6R7ds/4qefDpS4dtll\nHiZPzufDDy3897/axkdERETEN2w2js9dRNDRI0Q8Mhg8Hl8n4s477wbg7bffOOlar14uuncv5OBB\ng+PHLd6OdloqIEVERCRguK9qhv2pdEI2vUvowrm+jkOjRk24/PIreeutkwtIkwmmTcunWjUPX35p\n4fhxHwQshQpIERERCSj5/QZQ0KETtonjMO/7xtdx6Nr1DrZv/4hff/31pGsREVCnTiF5eWaefNJ0\nit/2DRWQIiIiElhMJuxPZ2CEhBCR/KDPjzrs2rUbhmGcchkbIDTUQ4sWULeul4OdhgpIERERCTie\n2hdjnzqLajv/Q9hz//RpliuuuJKYmL/xyiurT3nd4/FwySUmnnjC8HKy0qmAFBERkYBUcHcP8u+8\nh/Bp6Zh3femzHCaTiZ49e/Hxx9v4/vvvTrrudrsJCvKf5WtQASkiIiIBzD5lJkZ0dSKTB0NBgc9y\n9OiRgMlkOmlPSDhxlOF5dBZ2Tk4ODz74IPfddx8JCQl89tlnAGRmZhIfH09iYiIZGRlA0ZcfO3Ys\nCQkJJCUlsX///oqnFxEREakAo2ZNcp5+FstXuwifMcVnOerUqUvbtjfx6qtrTrrm8Zxn+0C++OKL\ntGnThmXLljF58mQmTJgAwLhx45g5cyYrVqzg888/Jysri40bN+J0Olm1ahWpqalMmeK7/0giIiIi\nJzhvuY283kmEPfs0lv987LMct93Whe+//+6kZWzD8L+TaCq0K2Xfvn0JDg4GitbnQ0JCsNvtOJ1O\nGjRoAEBcXBzbtm0jOzubtm3bAtCyZUt27dpVwegiIiIilcMxcTLBH35AxKNDOPL+RxAa6vUMN93U\nHoAPPnifSy9tVNxe9AzkOVpArlmzhsWLF5doS09Pp3nz5mRnZzNs2DBGjRqF3W7HZrMVfyY8PJwD\nBw6c1G42m3G5XFgsf0aw2UKwWLy3xm82BxEdbfVafyK+oHEugUDjXCos2orxwgtYunahxgv/xDP+\nKa9HiI1tTsOGDdm69QP+/vdH/nLFICwsxK/GeZkLyPj4eOLj409q37NnDykpKQwfPpzWrVtjt9tx\nOBzF1x0OB5GRkeTn55do93g8JYpHALvduw+vRkdbOXo016t9inibxrkEAo1zqRTXxhHRI4GQ6dM4\ndms33Jdd7vUIbdvexOuvv8bhw8eL6ySXy01hoQe32+PVcV6rVkSp1yo0H/rtt9/y2GOPMXPmTNq1\naweAzWajWrVq/PjjjxiGwZYtW7jmmmuIjY1l8+bNQNFLNjExMRXpWkRERKTS2SdMxoiIICLlEZ+c\nlX3TTe3JyTnOJ5/sKG7zeM7hJexTmTlzJk6nk0mTJgFFxePs2bN56qmnGDp0KG63m7i4OFq0aEGz\nZs3YunUriYmJGIZBenp6pXwBERERkcpiXHAB9qfSiXzkQUIXLSC//0Cv9t++fUesViurV6+gTZsb\ngKJVW7PZvwpIk2EYfrOteXZ2jlf705KHBAKNcwkEGudSqQyDqJ53Ydn5CUe27MBTx7tnCD766BDe\neON1vvxyLzabjZiYBvTokcDzzz93fixhi4iIiJx3TCZypv8Dk9uFbeQwr3ffu3cfHA47b7yxFgC3\n2/+28fGvNCIiIiJ+wHPJpTiGjiTknTcJfnOdV/u+7ro2NGrUuPhUmvPuJBoRERGR81XekGQKr2qO\nbeRQTMePea1fk8nEXXd1Z9u2rfz6669+uZG4f6URERER8RcWC/ZZzxCU/SvWqZO82nW3bnfj8Xh4\n6611frmRuH+lEREREfEjrpax5N/fn7AFczFnee8Uvcsvv4ImTZryxhtr/3gLW0vYIiIiIucMxxOj\nMaKjsY0aBl7avMZkMnHHHXfy0UdbKCwsJCjI5JV+y0oFpIiIiMhpGNVr4HhyPMHbthLy6hqv9Xvd\ndTfg+WMzc5PJv0o2/0ojIiIi4ofyeydR2PJqwsePxmT3zr7VLVpcXfxvLWGLiIiInGvMZuyTZ2A+\ndBDrzGle6bJmzZpcfHEdAL1EIyIiInIucrW6lrzeSYTNeQ7zN3u90mezZs0BFZAiIiIi5yzHk+Mx\nrOFFJ9R44YWaq64qKiAdDkeV91UeKiBFREREysioVQvHE08SvPl9gt96o8r7O1FAZmV9WeV9lYcK\nSBEREZFyyO87ANcVV2EbOxLy8qq0r9jYVgDUqVO3SvspLxWQIiIiIuVhsWBPn4b5pwNYX8io0q7q\n1KnLpk0fMmHC5Crtp7xUQIqIiIiUU+ENcRTcdjvWf87CdOhQlfbVrFkLwsPDq7SP8lIBKSIiInIW\n7OMmQqGT8CkTfR3F61RAioiIiJwFT6PG5D0wmNDlSzF/+YWv43iVCkgRERGRs5SbOhyjenVs40Z5\n7Zxsf6ACUkREROQsGVHROIaNJHjLZoL/9bav43iNCkgRERGRCsjv0x9X0xjCJ4yBwkJfx/EKFZAi\nIiIiFVGtGo5xE7Hs+5bQxQt8ncYrVECKiIiIVJCz060427YjfMYUTMeO+jpOlVMBKSIiIlJRJhP2\n8ZMwHTmC9ekZvk5T5SpUQObk5PDggw9y3333kZCQwGeffQbAhg0b6NixI0lJSSQlJbFjxw48Hg9j\nx44lISGBpKQk9u/fXylfQERERMQfuJs1pyChN2HzXyBo/w++jlOlLBX55RdffJE2bdrQt29fvvvu\nO1JTU3nttdfIyspi2LBhdO7cufizGzZswOl0smrVKjIzM5kyZQqzZ8+u8BcQERER8ReOkWMIWfca\n4WnjyZm3yNdxqkyFCsi+ffsSHBwMgNvtJiQkBICsrCx2797N4sWLad68OUOHDmXnzp20bdsWgJYt\nW7Jr166T7mezhWCxmCsSqVzM5iCio61e60/EFzTOJRBonIvfiG6C5/EUQielYRmagnFdm0q7tT+N\n8zIXkGvWrGHx4sUl2tLT02nevDnZ2dkMGzaMUaNGAXDjjTfSsWNH6tWrx7hx41i5ciV2ux2bzVb8\nu2azGZfLhcXyZwS7vaCi36dcoqOtHD2a69U+RbxN41wCgca5+JUHHqLmnBfwjB7DsTWvV9ptvT3O\na9WKKPVamQvI+Ph44uPjT2rfs2cPKSkpDB8+nNatWwPQvXt3IiMjAejQoQPr168nIiICh8NR/Hse\nj6dE8SgiIiJyXrDZyH3479ieGo1lx8e4Wl/n60SVrkIv0Xz77bc89thjzJw5k3bt2gFgGAbdunXj\n4MGDAGzbto0rr7yS2NhYNm/eDEBmZiYxMTEVjC4iIiLin/L6PoDnggsInzHZ11GqRIWmAGfOnInT\n6WTSpEkA2Gw2Zs+eTVpaGsnJyYSGhtK4cWN69uyJ2Wxm69atJCYmYhgG6enplfIFRERERPxOePh5\nPQtpMgz/Ofk7OzvHq/3pmRkJBBrnEgg0zsUvORzUvLYZrquac2z12grfzp+egdRG4iIiIiJVITyc\n3IceI/jf72H5z8e+TlOpVECKiIiIVJG8fgPw1KxJ+Iwpvo5SqVRAioiIiFSVP56FDH5/03k1C6kC\nUkRERKQKnY+zkCogRURERKrSiWch39+E5ZMdvk5TKVRAioiIiFSx4lnI6efHvpAqIEVERESqms1G\n3qCHCH5/E0Hff+frNBWmAlJERETEC/ITemOYTISuWenrKBWmAlJERETECzx16lLY9qaiAtJ/znE5\nKyogRURERLwkPz4B8/4fsOw4t7f0UQEpIiIi4iUFXbthWK2Erl7u6ygVogJSRERExFtsNvLviSd0\nxTIsn+30dZqzpgJSRERExIscYyfgqX0xkYP6YTp+zNdxzooKSBEREREvMqKrc3z2AoJ+OkD4xPG+\njnNWVECKiIiIeJnrujYU9Egg5NU1UFAA+flEPDwIc9YuX0crExWQIiIiIj5QcOfdBOUcJ/iD9whZ\n+wqha1YS8ubrvo5VJhZfBxAREREJRM7/uxlPVDQh69Zi3vM1AOZv9vo4VdmogBQRERHxheBgnLd2\nIeS1lzE5nRjBwVi+2ePrVGWiJWwRERERHynodhcmpxOPLYL83kmYv/0GXC5fxzojFZAiIiIiPuJs\n1x73RbXJ79OPwthrMBUWYt7/va9jnZGWsEVERER8JTiYI9t2YoSGYfn8MwDMe/fibtzUx8FOTzOQ\nIiIiIj5k2CLAYsHdNAYA8znwHGSFZiBzc3NJTU3l2LFjhIWFMX36dGrUqEFmZiaTJk3CbDYTFxdH\ncnIyHo+H8ePHs2fPHoKDg0lLS6Nhw4aV9T1EREREzmlGZBTu2hdj2ev/BWSFZiBXr17NlVdeyfLl\ny+natSvPP/88AOPGjWPmzJmsWLGCzz//nKysLDZu3IjT6WTVqlWkpqYyZcqUSvkCIiIiIucLd9O/\nnf8zkH379sXtdgPwyy+/cMEFF2C323E6nTRo0ACAuLg4tm3bRnZ2Nm3btgWgZcuW7Np1buy0LiIi\nIuIt7pgYQlatAMMAk8nXcUpV5gJyzZo1LF68uERbeno6zZs3p0+fPuzdu5cXX3wRu92OzWYr/kx4\neDgHDhw4qd1sNuNyubBY/oxgs4VgsZgr8n3KxWwOIjra6rX+RHxB41wCgca5nC+CWjQjaMFcoh1H\noF69Etf8aZyXuYCMj48nPj7+lNeWLFnCvn37GDx4MGvXrsXhcBRfczgcREZGkp+fX6Ld4/GUKB4B\n7PaC8uavkOhoK0eP5nq1TxFv0ziXQKBxLueLag2bEA3kr36F/P4DS1zz9jivVSui1GsVegZyzpw5\nrF27FgCr1YrZbMZms1GtWjV+/PFHDMNgy5YtXHPNNcTGxrJ582YAMjMziYmJqUjXIiIiIuedwuuu\nx9m2HbYJYzDv+8bXcUplMgzDONtfPnz4MCNGjMDpdOJ2u0lNTaVVq1ZkZmaSnp6O2+0mLi6Oxx9/\nvPgt7L1792IYBunp6TRu3LjE/bKzcyr8hcpD/8cqgUDjXAKBxrmcT4J++ZnqN12P+9JGHH1rI/yx\nYutPM5AVKiArmwpIkcqncS6BQONczjchK18i8tEhHH15HYX/dxPgXwWkNhIXERER8TMF3e7GCAsj\n5J03fR3llFRAioiIiPgbqxVnu/YEv/NW0ZY+fkYFpIiIiIgfKuhyO+ZffsbyRaavo5xEBaSIiIiI\nH3J2uhUjKKhoFtLPqIAUERER8UNGzZoUtrnBL5+DVAEpIiIi4qcK29yAZfdX8MfR0f5CBaSIiIiI\nnzIiowAw5TrO8EnvUgEpIiIi4qcMmw0Ak0MFpIiIiIiUgREeDoDJYfdxkpJUQIqIiIj4KSP8jxlI\nuwpIERERESmDP2cg/WsJ2+LrAOeKI0d+54EHknj66edo2PASfvrpAJMmjcdkMtGoUWNSUkYQFBTE\nwoVz2bZtC2azhUcfTeGKK64qcZ9u3Tqzbt36M7Zt2rSB1157ufjnn3/+iWbNWjBhwuSq+5IiIiLi\nV/58BtK/ZiBVQJaBy+Vi2rR0goNDituefXYWAwcOITb2GqZPT+fDDz+gdu2Lycz8lLlzF3Po0CFG\njx7O/PlLzqrPDh1uoUOHWwD44YfvGTbsMQYOHFIp30dERETODcVL2JqBPHurVllYsaJapd3PYgki\nPt5CQoLrtJ/LyPgHd93VnaVLXyxu27Pna66+uhUAbdrcwI4dH9OgQUOuvbYNJpOJ2rVr43a7OHLk\nCNWrVz/pnnPmPIfdbiclZThOp5Px45/k0KGDREVFkZY2DYul6D+N3W7nySeHkZr6BPXrN6i07y4i\nIiL+r3gJW89AnlvefvsNoqOjue6660u0G4aByWQCwGoNx+Gw43DYsf0x1fzX9v+VkfEP3G4Xqakj\nMJlM5OXlMnjww8yevQC73c7evV8X9zFhwhhuvfV22rS5oQq/pYiIiPgjLWFXgoQE1xlnC8sjOtrK\n0aOnv99bb63DZDLxySc7+PbbvaSljWXKlFkEBf1Ze+fmOrDZbISH28j9y0afRe0RJe73+++/sW/f\nN9StW7+4LTIyiosvrgNAzZo1yc/PB2DBgjmEhoaSlNS3ol9VREREzkGG1T9fotEM5Bk899w8MjLm\nkpExlyZNYhg9egI1a15A06Z/49NPPwFg+/aPaNHiapo1a8GOHdvxeDwcPHgQj8cgOjq6xP1q1KjJ\nrFkZ/PDDd2zf/hFA8UzmX23Z8gEfffQho0aNq/ovKSIiIv6pWjWMkBC/W8I+p2Yg/Uly8t+ZNm0S\nc+YUvZV9000dMJvNNG/eksGD+2EYBikpI075uyaTiZEjx5KSkszcuYtO+ZmMjH9QrVo1hg59tLit\nXr36PPHEmKr4OiIiIuKnDJvN75awTYZhGL4OcUJ2do5X+ytaws71ap8i3qZxLoFA41zOZzWuaUZh\nmxswL1vq1XFeq1ZEqde0hC0iIiLix4zwcD0DKSIiIiJlZ1jDMdm9u0p7JiogRURERPxY0TOQmoEU\nERERkTIywv2vgKzQW9i5ubmkpqZy7NgxwsLCmD59OjVq1GDDhg1MmzaNiy++GIBHHnmEa665hvHj\nx7Nnzx6Cg4NJS0ujYcOGlfIlRERERM5XRc9A2vGbt56p4Azk6tWrufLKK1m+fDldu3bl+eefByAr\nK4thw4axdOlSli5dSuvWrdm4cSNOp5NVq1aRmprKlClTKuULiIiIiJzP/HEbnwrNQPbt2xe32w3A\nL7/8wgUXXAAUFZC7d+9m8eLFNG/enKFDh7Jz507atm0LQMuWLdm1a9dJ97PZQrBYzBWJVC5mcxDR\n0Vav9SfiCxrnEgg0zuV8FlQjGpPD4VfjvMwF5Jo1a1i8eHGJtvT0dJo3b06fPn3Yu3cvL774IgA3\n3ngjHTt2pF69eowbN46VK1dit5c8J9psNuNyubBY/oxgtxdU9PuUS1n2DXO5XEye/BT//e9/KSx0\ncv/9DxAX146ffjrApEnjMZlMNGrUmJSUEQQFBbFw4Vy2bduC2Wzh0UdTuOKKq0rcr1u3zqxbt75E\nW4OKCe4AAA4ASURBVI8ed/DSSy8TEhICwP79PzB9ejoZGXMr9wtLQNL+eBIINM7lfGa1hBCen4+r\nwMlRu9Nr/Z5uH8gyF5Dx8fHEx8ef8tqSJUvYt28fgwcPZuPGjXTv3p3IyEgAOnTowPr164mIiMDx\nlwdAPR5PieKxLEJWLSd0xbJy/c7pmC1BhMT3piChd6mfWb/+bSIjoxkzZiLHjh2lX797iYtrx7PP\nzmLgwCHExl7D9OnpfPjhB9SufTGZmZ8yd+5iDh06xOjRw5k/f0ml5RUREZHAY5yYgLPbgWCfZjmh\nQs9Azpkzh7Vr1wJgtVoxm80YhkG3bt04ePAgANu2bePKK68kNjaWzZs3A5CZmUlMTEwFo3vHzTd3\nZODAB4t/NpuLit49e77m6qtbAdCmzQ188skOvvgik2uvbYPJZKJ27dq43S6OHDlyyvvOmfMcM2dO\n5XQHARUU5JOcPIjk5EEMGfIA7dpdx88//3TKz7799huMGfMEw4f/nXvv7cHbb78BwL593/LII4NJ\nTh7Ek08Ow263M3JkKl9//RUAvXrdwwcfvA/A448/THb2r+X8C4mIiEhVMsL/WkD6hwo9A9m9e3dG\njBjBK6+8gtvtJj09HZPJRFpaGsnJyYSGhtK4cWN69uyJ2Wxm69atJCYmYhgG6enp5e6vIOH0s4Xl\nFR1tpeAMSx5Wa9GzBrm5DkaPHsHAgUMAMAwDk8n0x2fCcTjsOBx2oqKi//K7Re3Vq1cvcc+MjH8Q\nFGQiNfXPs7JTUpKL71dQkE9ISCghIaFkZMzFMAwmThzLrbd2pW7deqVmdTjszJqVwYEDPzJixON0\n6XIHU6emMXLkWC69tBFvvrmWl15azP/9381s3/4RkZFRBAeH8J//fEyrVtfidDqpVevCcvwFRURE\npKoZ4eFF/7DbwVbDt2H+UKEC8oILLmDBggUntcfFxREXF3dS+4QJEyrSnc8cOnSQUaOGcffdPbjl\nllsBCAr6c/I2N9eBzWYjPNxGbq7jf9pLPj/w+++/sW/fN9StW79E+6xZGSc9A3nC009Po0GDhtx5\n5z2nzdmkSdGs7oUXXoTT6fzjXt8zc2bRG+9ut4v69RvSq1cSI0emEhUVzb333s+qVS+xfftWbryx\nbbn+LiIiIlL1ThSQ/nQajTYSP4Pff/+NlJRkhgx5hNtvv7O4vWnTv/Hpp58AsH37R7RocTXNmrVg\nx47teDweDh48iMdjEB0dXeJ+NWrUZNasDH744Tu2b//ojP3Pmzcbw4C+fQec8bMnZjD/qkGDhowe\nPYGMjLkMGfIo119/I5GRkYSEhLJp0wbatLmeiy6qzerVK2jXrv0Z+xARERHvMk5MRp0vS9iBYMmS\nF8nJyWHRovksWjQfgJkznyE5+e9MmzaJOXOeo2HDS7jppg6YzWaaN2/J4MH9MAyDlJQRp7ynyWRi\n5MixpKQkM3fuolL73r07i2XLFtGyZSuSkwcB0K/fQL76KoumTWNo0+aGM+ZPTR1JWtpYPB4PAE88\nMQaAtm3b8fbb64iMjKJ16za89trLp10eFxEREd8osYTtJ0zG6d7i8LLsbO9OzZ6r2z5s2fIBYWFW\nWrW61tdR5Bxwro5zkfLQOJfzmfnbb6hxQytci5dy5LY7z/wLlaRStvER/9Gkyd+oXbu2r2OIiIiI\nFxRv4+NHp9HoGchzkIpHERGRwPHnSzQqIEVERESkDAyr/z0DqQJSRERExJ+ZzRhWK2gbHxEREREp\nK8MaDnbHmT/oJSogRURERPycER6uZyDPJS6Xi4kTx/DQQwMYOLAPW7Z8AMBPPx1gyJAHeOihAcyY\nMbl4n8WFC+cycGAfHnywP199teuk+3Xr1vmkth497qCgoKD45/37fyje97GikpMHsX//DyXaKvP+\nIiIiUvWMcBvk+M8S9jm1jc+qVctZsWJZpd3PYgkiPr43Cac5X3v9+reJjIxmzJiJHDt2lH797iUu\nrh3PPjuLgQOHEBt7DdOnp/Phhx9Qu/bFZGZ+yty5izl06BCjRw9n/vwllZZXREREApNhs/nVNj7n\nVAHpCzff3JGbb+5Q/LPZXPQn27Pna66+uhUAbdrcwI4dH9OgQUOuvbYNJpOJ2rVr43a7OHLkCNWr\nVz/pvnPmPIfdbiclZXipfRcU5JOa+igAbrebr77axfLlr5zyxBiXy8XkyU/x888/43a7SUy8lw4d\nbim+fvjwYSZMGI1hGNSoUfPs/hgiIiLiE0Z4uF+9RHNOFZAJCaefLSyvspxcYLVaAcjNdTB69AgG\nDhwCgGEYxWdPW63hOBx2HA47UVHRf/ndovb/LSAzMv5BUJCJ1NQ/jzpMSUkuvl9BQT4hIaGEhISS\nkTEXwzCYOHEst97atdTjBl9//RWioopmSnNzHfTvfx+tWrUuvr5y5TI6duxMt253s2nTBl577eWy\n/plERETExwxbBKZfD/k6RrFzqoD0lUOHDjJq1DDuvrsHt9xyKwBBQX8+Ppqb68BmsxEebiM31/E/\n7SWPAfr999/Yt+8b6tatX6J91qwMQkJCgKJnFKdPTy++9vTT02jQoCF33nlPqRl/+OEHrrmmqGC0\nWsO55JJL+fnnn4qvf//9d3Tu3AWAZs1aqIAUERE5h+QOfhhzzu++jlFML9Gcwe+//0ZKSjJDhjzC\n7bf/ef5k06Z/49NPPwFg+/aPaNHiapo1a8GOHdvxeDwcPHgQj8cgOjq6xP1q1KjJrFkZ/PDDd2zf\n/tEZ+583bzaGAX37Djjt5y655BK++OIzoKhw3bdvH3Xq1Cm+3rBhQ7KyvgBg9+6vyvblRURExC+4\nWl+H0b27r2MU0wzkGSxZ8iI5OTksWjSfRYvmAzBz5jMkJ/+dadMmMWfOczRseAk33dQBs9lM8+Yt\nGTy4H4ZhkJIy4pT3NJlMjBw5lpSUZObOXVRq37t3Z7Fs2SJatmxV/NZ0v34D+eqrLJo2jaFNmxuK\nP9ut2z1MnZrGkCEPUFBQQP/+A6levUbx9QEDhjBu3Eg2btxAnTp1K+EvIyIiIoHKZBiG4esQJ2Rn\ne/fh0LI8A+mPtmz5gLAwK61aXevrKHIOOFfHuUh5aJxLIPD2OK9VK6LUa5qBPAc1afI3ateu7esY\nIiIiEqD0DOQ5SMWjiIiI+JIKSBEREREpFxWQIiIiIlIuKiBFREREpFwqpYDct28frVq1oqCgAIDM\nzEzi4+NJTEwkIyMDAI/Hw9ixY0lISCApKYn9+/dXRtciIiIi4mUVfgvbbrczdepUgoODi9vGjRvH\ns88+S/369Rk0aBBZWVn8/PPPOJ1OVq1aRWZmJlOmTGH27NkV7V5EREREvKxCM5CGYTBmzBhSUlII\nCwsDigpKp9NJgwYNMJlMxMXFsW3bNnbu3Enbtm0BaNmyJbt27ap4ehERERHxujLPQK5Zs4bFixeX\naKtTpw5dunThsssuK26z2+3YbLbin8PDwzlw4MBJ7WazGZfLhcXyZ4TTbVhZVXzRp4i3aZxLINA4\nl0DgL+O8zAVkfHw88fHxJdo6derEK6+8wiuvvEJ2djb9+/dnzpw5OByO4s84HA4iIyPJz88v0e7x\neEoUjyIiIiJybqhQBffuu+8W/7t9+/YsXLiQkJAQqlWrxo8//kj9+vXZsmULycnJHDx4kPfff58u\nXbqQmZlJTExMhcOLiIiIiPdVyRTgU089xdChQ3G73cTFxdGiRQuaNWvG1q1bSUxMxDAM0tPTq6Jr\nEREREaliJsMwDF+HEBEREZFzhzYSFxEREZFyUQH5F9u2bWP48OE8+uijfP31176OI1Ildu3aRWpq\nKiNGjODw4cO+jiNSZX777TfuueceX8cQqTK7d+/m3nvv5YknnmD79u1e7VsF5F/k5eUxdepUHnzw\nQbZs2eLrOCJVoqCggHHjxtGuXTsyMzN9HUekShiGwfz586lbt66vo4hUmS+++IILLriAoKAgmjZt\n6tW+VUD+Rfv27cnLy2Pp0qXcfffdvo4jUiVatWrFt99+y8KFC7n88st9HUekSqxYsYI77riDkJAQ\nX0cRqTKtWrUiLS2NgQMHsmDBAq/2rQLyL44cOcKkSZN49NFHqVmzpq/jiFSJL774gquuuop58+ax\nbNkyX8cRqRIfffQRK1eu5Msvv+Sdd97xdRyRKrF79248Hg9RUVG43W6v9h0wBeTnn39OUlISULSJ\n+dixY0lISCApKYn9+/cDMHnyZA4dOsTMmTP517/+5cu4ImelLOPc4XAwatQo0tLS6Ny5sy/jipyV\nsozzjIwMJkyYQLNmzbjtttt8GVfkrJRlnNetW5eJEycyffr04s96S0AcBTNv3jzWrVtXfF73xo0b\ncTqdrFq1iszMTKZMmcLs2bOZNm2aj5OKnL2yjvPrr7+e66+/3sdpRc5OWcf5CTNmzPBVVJGzVtZx\nHhsbS2xsrE8yBsQMZIMGDXj22WeLf965cydt27YFoGXLluzatctX0UQqjca5BAKNcwkE58I4D4gC\nsnPnziXO3bbb7dhstuKfzWYzLpfLF9FEKo3GuQQCjXMJBOfCOA+IAvJ/2Ww2HA5H8c8ej6fEfyiR\n84HGuQQCjXMJBP44zgOygIyNjWXz5s0AZGZmEhMT4+NEIpVP41wCgca5BAJ/HOcB+b9pnTp1YuvW\nrSQmJmIYBunp6b6OJFLpNM4lEGicSyDwx3FuMgzD8HUIERERETl3BOQStoiIiIicPRWQIiIiIlIu\nKiBFREREpFxUQIqIiIhIuaiAFBEREZFyUQEpIiIiIuWiAlJEREREykUFpIiIiIiUiwpIERERESmX\n/wcp0qjr37M04gAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xda855f8>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "f1=data[0].index.values\n",
-    "g1=data[0].values.transpose()[1]\n",
-    "p1=np.degrees(np.unwrap(np.radians(data[0].values.transpose()[2])))\n",
-    "f2=data[1].index.values\n",
-    "g2=data[1].values.transpose()[1]\n",
-    "p2=np.degrees(np.unwrap(np.radians(data[1].values.transpose()[2])))\n",
-    "f4=data[2].index.values\n",
-    "g4=data[2].values.transpose()[1]\n",
-    "p4=np.degrees(np.unwrap(np.radians(data[2].values.transpose()[2])))\n",
-    "f2_o=data[4].index.values\n",
-    "g2_o=data[3].values\n",
-    "p2_o=np.degrees(np.unwrap(data[3].values))\n",
-    "pylab.figure(figsize=(11,11))\n",
-    "plt.subplot(2, 1, 1)\n",
-    "plt.semilogx(f4,g4,color='blue',label='400 kHz')\n",
-    "plt.semilogx(f2,g2,color='red', label='200 kHz, new')\n",
-    "plt.semilogx(f2_o,g2_o,color='black', label='200 kHz, old')\n",
-    "plt.legend()\n",
-    "plt.grid(True)\n",
-    "plt.ylabel('Gain [dB]')\n",
-    "plt.title('Frequency Response')\n",
-    "plt.subplot(2, 1, 2)\n",
-    "plt.semilogx(f4,p4,color='blue', label='400 khZ')\n",
-    "plt.semilogx(f2,p2,color='red', label='200 kHz, new')\n",
-    "plt.semilogx(f2_o,p2_o,color='black', label='200 kHz, old')\n",
-    "plt.title('phase')\n",
-    "plt.legend()\n",
-    "plt.grid(True)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Zu sehen, ist der Gain und die Phase bei verschiedenen Abtastraten. In schwarz ist das Ergebnis einer Vormessung bei einer Abtastrate von 200 kHz. Um zu überprüfen ob dies vielleicht durch einen Fehler im programmcode verursacht wurde, wurde die Messung wiederholt mit einem Notch filter bei 625 Hz und einer Abtastrate von 100 kHz, die Second order Section wurde nicht neu berechnet bei Veränderung der Abtastrate."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "notch_test=np.empty(6,dtype=object)\n",
-    "notch_test[0]=io.read('sam_notchT.625_100_1.csv')\n",
-    "notch_test[1]=io.read('sam_notchT.625_100_2.csv')\n",
-    "notch_test[2]=io.read('sam_notchT1.25_200_1.csv')\n",
-    "notch_test[3]=io.read('sam_notchT1.25_200_2.csv')\n",
-    "notch_test[4]=io.read('sam_notchT2.5_400_1.csv')\n",
-    "notch_test[5]=io.read('sam_notchT2.5_400_2.csv')\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "f_200=notch_test[2].index.values\n",
-    "g_200=notch_test[2].values.transpose()[1]\n",
-    "p_200=np.degrees(np.unwrap(np.radians(notch_test[2].values.transpose()[2])))\n",
-    "f_100=notch_test[0].index.values\n",
-    "g_100=notch_test[0].values.transpose()[1]\n",
-    "p_100=np.degrees(np.unwrap(np.radians(notch_test[0].values.transpose()[2])))\n",
-    "f_400=notch_test[4].index.values\n",
-    "g_400=notch_test[4].values.transpose()[1]\n",
-    "p_400=np.degrees(np.unwrap(np.radians(notch_test[4].values.transpose()[2])))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 38,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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aNBQOhxk4cDBjxx7EUUcdw/HHn0i4DX1PlVTuAiWV0tnYK7+kx1HjiB1xFBVP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\nIj8GIWwXDQcAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xc62c748>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "pylab.figure(figsize=(11,11))\n",
-    "plt.subplot(2, 1, 1)\n",
-    "#plt.semilogx(f1,g1,color='red')\n",
-    "plt.semilogx(f_100,g_100,color='red', label='100 kHz')\n",
-    "plt.semilogx(f_200,g_200,color='black',label='200 kHz')\n",
-    "plt.semilogx(f_400,g_400,label='400 kHz')\n",
-    "plt.grid(True)\n",
-    "plt.legend()\n",
-    "plt.ylabel('Gain [dB]')\n",
-    "plt.title('Frequency Response')\n",
-    "plt.subplot(2, 1, 2)\n",
-    "plt.semilogx(f_100,p_100,color='red',label='100 kHz')\n",
-    "plt.semilogx(f_200,p_200,color='black',label='200 kHz')\n",
-    "plt.semilogx(f_400,p_400,label='400 kHz')\n",
-    "plt.title('phase')\n",
-    "plt.grid(True)\n",
-    "plt.legend()\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Da der Notch filter bei 200 kHz bei 1250 Hz und bei 400 kHz bei 2500 Hz auftauchte kann davon ausgegangen werden,dass die Berechnung im Programm richtig durchgeführt wurde.\n",
-    "Da die Berechnung im Programm als Fehlerquelle unwahrscheinlich ist, ist es wahrscheinlicher, dass die Veränderung des Signals von single ended auf differential diese Phasenverzögerung verursacht. die Auswirkungen auf die berechnete Servo-Transferfunktion wird im folgendem betrachtet"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "tf=io.read('tf2.csv')\n",
-    "new_tf=np.empty(3,dtype=object)\n",
-    "new_tf[0]=np.delete(tf.index.values,np.arange(301,401))\n",
-    "new_tf[1]=np.delete(tf.values.transpose()[1],np.arange(301,401))+data[1].values.transpose()[1]\n",
-    "new_tf[2]=np.delete(tf.values.transpose()[2],np.arange(301,401))+data[1].values.transpose()[2]\n",
-    "\n",
-    "Servo4=Servo()\n",
-    "Servo4.add_gain(0.01778)\n",
-    "Servo4.integrator(2000)\n",
-    "Servo4.integrator(400)\n",
-    "Servo4.integrator(22400)\n",
-    "Servo4.notch(65000,3)\n",
-    "Servo4.order2lowpass(15000,0.707)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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GRSqeyxkZVRj9mxxWKyY3t9MmJSUv/ZaG9/YlzWSixGQmwmEnedMODs96lZvm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\nABjzP/coPCdQ0G9HAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xc35d748>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "append=np.empty(3,dtype=object)\n",
-    "append[0]=np.logspace(0,2,100)\n",
-    "append[1]=np.empty(100)\n",
-    "append[2]=np.empty(100)\n",
-    "average=np.average(new_tf[1][0:5])\n",
-    "for i, p in enumerate(append[0]):\n",
-    "    append[1][i]=average\n",
-    "    append[2][i]=0\n",
-    "old_tf=np.empty(3,dtype=object)\n",
-    "old_tf[0]=np.delete(tf.index.values,np.arange(301,401))\n",
-    "old_tf[1]=np.delete(tf.values.transpose()[1],np.arange(301,401))\n",
-    "old_tf[2]=np.delete(tf.values.transpose()[2],np.arange(301,401))\n",
-    "f_n,g_n,p_n=Servo4.apply_servo(np.append(append[0],new_tf[0],),np.append(append[1],new_tf[1]),np.append(append[2],new_tf[2]))\n",
-    "f_o,g_o,p_o=Servo4.apply_servo(np.append(append[0],old_tf[0]),np.append(append[1],old_tf[1]),np.append(append[2],old_tf[2]))\n",
-    "pylab.figure(figsize=(11,11))\n",
-    "plt.subplot(2, 1, 1)\n",
-    "plt.semilogx(f_n,g_n,color='black', label ='new transferfunction')\n",
-    "plt.semilogx(f_o,g_o,color='red', label='old transferfunction')\n",
-    "plt.axhline(y=0, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "plt.axvline(x=5754.3999999999996,ymin=0,ymax=1,linewidth=1,color='k')\n",
-    "plt.legend()\n",
-    "plt.xlim(1e2,1e5)\n",
-    "plt.grid(True)\n",
-    "plt.ylabel('Gain [dB]')\n",
-    "plt.title('Frequency Response')\n",
-    "plt.subplot(2, 1, 2)\n",
-    "plt.semilogx(f_n,p_n,color='black', label='new transferfunction')\n",
-    "plt.semilogx(f_o,p_o,color='red',label ='new transferfunction')\n",
-    "plt.axhline(y=-180, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "plt.axvline(x=5754.3999999999996,ymin=0,ymax=1,linewidth=1,color='k')\n",
-    "plt.legend()\n",
-    "plt.xlim(1e2,1e5)\n",
-    "plt.title('phase')\n",
-    "plt.grid(True)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Im vergleich zu vorher ist die phase margin von 45° auf 25° Hz gesunken und der gain margin auf ungefähr 4 dB\n",
-    "Eine Möglichkeit um diesen Effekt auszugleichen wäre es , den gain zu verringern.\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "Servo5=copy.deepcopy(Servo4)\n",
-    "Servo5.add_gain(0.5)\n",
-    "f_n2,g_n2,p_n2=Servo5.apply_servo(np.append(append[0],new_tf[0],),np.append(append[1],new_tf[1]),np.append(append[2],new_tf[2]))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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bkym5qBOW3bswfH0p7n0VrmbNWbjwZ774Yip2u50ePbry/DMjeKZ2HSz795Ez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\nAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0xd30cbe0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "pylab.figure(figsize=(11,11))\n",
-    "plt.subplot(2, 1, 1)\n",
-    "plt.semilogx(f_n2,g_n2,color='black')\n",
-    "plt.semilogx(f_o,g_o,color='red')\n",
-    "plt.axhline(y=0, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "plt.axvline(x=5754.3999999999996,ymin=0,ymax=1,linewidth=1,color='k')\n",
-    "plt.grid(True)\n",
-    "plt.xlim(1e2,1e5)\n",
-    "plt.ylabel('Gain [dB]')\n",
-    "plt.title('Frequency Response')\n",
-    "plt.subplot(2, 1, 2)\n",
-    "plt.semilogx(f_n2,p_n2,color='black')\n",
-    "plt.semilogx(f_o,p_o,color='red')\n",
-    "plt.axhline(y=-180, xmin=0, xmax=1, linewidth=1, color = 'k')\n",
-    "plt.axvline(x=5754.3999999999996,ymin=0,ymax=1,linewidth=1,color='k')\n",
-    "plt.title('phase')\n",
-    "plt.xlim(1e2,1e5)\n",
-    "plt.grid(True)\n",
-    "plt.savefig('Veränderung phase und gainmargin, Version 2')\n",
-    "plt.show()\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Eine senkung um einen Faktor von 0.5 bzw um -6dB würde den phase margin auf 30° erhöhen und den gain margin auf 10dB, die Effizienz der Regelung würde jedoch verringert werden."
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/unordered/qontrol/ADwin_V2.cpp b/unordered/qontrol/ADwin_V2.cpp
deleted file mode 100644
index 182971e2c625f1053f49eb8260727b785068560c..0000000000000000000000000000000000000000
--- a/unordered/qontrol/ADwin_V2.cpp
+++ /dev/null
@@ -1,1509 +0,0 @@
-/******************************************************************************************************
-* Collection of subroutines for the control of the ADwin measurement data acquisition
-*
-* Created : Based on ADwin.c Version 1.11 by M. Sanna and started developted 22.08.1996 from Martin Hotze
-*
-*******************************************************************
-* Version 2.00beta  P.H und M.S. 08.03.2015 First Version with multithreading support and errorcode return variable.
-*					New function:
-*                   - Data_type
-*                   This Version supports new T12 functions
-*					- e_Get_ADBFPar_All_Double
-*                   - e_Get_ADBFPar_Double
-*                   - e_Set_ADBFPar_Double
-*
-*
-* Version 2.00    M.S. 03.07.2015
-* Version 2.01    M.S. 28.01.2016 Use the same data type "short" for variable "DataNo".
-*                                 Changed functions: Data_Length, GetData_String, String_Length, SetData_String
-*                                 Bugfix: Get_Known_DeviceNo, Errorhandling corrected
-*
-* Function of the DLL ADwin32(32-bit, respectively)
-* =====================================================================
-* Attention! the file "ADWIN32.DLL" or "ADWIN64.DLL" respectively have to be included in a
-* subdirectory that can be accessed by Windows ( at best in " \windows" or "\winnt")
-* in order to use these functions the program "ADwin12.btl" (or ADwin4.btl or ADwin5.btl or ADwin8.btl
-* or ADwin9.btl or ADwin10.btl or ADwin11.btl
-* respectively) has to be loaded to
-* the ADwin system!
-* The DLL ADwin32.dll or ADwin64.dll respectively include all functions necessary for
-* the data transfer between PC and the ADwin system.
-*
-* To Change from ADwin.c ->ADwin.cpp use #include "stdafx.h"
-*******************************************************************************************************/
-
-//#include "stdafx.h"	  // necessary for MFC projects
-#include "windows.h"
-#include "Adwin_V2.h"
-#include <stdio.h>
-
-int	FirstTime  = 1;
-char *Type_Array[] = {"Undefined", "Byte", "Short", "Int32", "Long", "Float32", "Float64", "Int64", "String"};
-
-
-static HINSTANCE DLLHandle;
-
-long  (FAR PASCAL *Clear_Process_Ptr)(short ProcessNo, short Device_No,long *ErrorNo);
-long  (FAR PASCAL *Boot_Ptr)(char *Filename, short Device_No, long Memsize, short msgbox, long *ErrorNo );
-short (FAR PASCAL *Load_Process_Ptr)(char *Filename, short Device_No, short msgbox,long *ErrorNo);
-short (FAR PASCAL *Start_Process_Ptr)(short Index, short Device_No, long *ErrorNo);
-short (FAR PASCAL *Stop_Process_Ptr)(short Index, short Device_No, long *ErrorNo);
-short (FAR PASCAL *Set_Par_Ptr)(short Index, long Value, short Device_No, long *ErrorNo);
-short (FAR PASCAL *Set_FPar_Ptr)(short Index, float Value, short Device_No, long *ErrorNo);
-long  (FAR PASCAL *Get_Par_Ptr)(short Index, short Device_No, long *Error_No);
-float (FAR PASCAL *Get_FPar_Ptr)(short Index, short Device_No, long *ErrorNo);
-
-short (FAR PASCAL *Set_FPar_Double_Ptr)(short Index, double Value, short Device_No, long * ErrorNo );
-double (FAR PASCAL *Get_FPar_Double_Ptr)(short Index, short Device_No, long *ErrorNo);
-
-short (FAR PASCAL *Get_Data_Ptr)(void *Data, short typ, short DataNo, long Startindex, long Count , short Device_No, long *ErrorNo);
-short (FAR PASCAL *Set_Data_Ptr)(void *Data, short typ, short DataNo, long Startindex, long Count , short Device_No, long *ErrorNo);
-short (FAR PASCAL *Save_Fast_Ptr)(char *Filename, short DataNo, long Startindex, long Count, short Mode, short Device_No,long *ErrorNo);
-short (FAR PASCAL *File2Data_Ptr)(char *Filename, short typ, short DataNo, long Startindex, short Device_No);
-short (FAR PASCAL *Get_Fifo_Ptr)(void *Data, short typ, short FifoNo, long Count , short Device_No,long *ErrorNo);
-short (FAR PASCAL *Set_Fifo_Ptr)(void *Data, short typ, short FifoNo, long Count , short Device_No,long *ErrorNo);
-long  (FAR PASCAL *Get_Fifo_Count_Ptr)(short FifoNo, short Device_No,long *ErrorNo);
-long  (FAR PASCAL *Get_Fifo_Empty_Ptr)(short FifoNo, short Device_No,long *ErrorNo);
-short (FAR PASCAL *Fifo_Clear_Ptr)(short FifoNo, short Device_No, long *ErrorNo);
-
-short (FAR PASCAL *Workload_Ptr)(long Priority, short Device_No, long *ErrorNo);
-
-short (FAR PASCAL *ADTest_Version_Ptr)(short Device_No, short msgbox, long *ErrorNo);
-long  (FAR PASCAL *AD_Memory_Ptr)(short Device_No, long *ErrorNo);
-long  (FAR PASCAL *AD_Memory_all_Ptr)(short Mem_Spec, short Device_No, long *ErrorNo);
-long  (FAR PASCAL *AD_Memory_all_byte_Ptr)(short Mem_Spec, short Device_No, long *ErrorNo);
-short (FAR PASCAL *ADProzessorTyp_Ptr)(short DeviceNo, long *ErrorNo);
-
-// evtl. entfernen
-long  (FAR PASCAL *AD_GetErrorCode_Ptr)(short DeviceNo);		// entl. entfernen
-
-char  (FAR PASCAL *AD_GetErrorText_Ptr)(long ErrorCode, char *text, long lenght);
-short (FAR PASCAL *Get_ADBPar_All_Ptr)(short Startindex, short Count, long *Array, short Device_No, long *ErrorNo);
-short (FAR PASCAL *Get_ADBFPar_All_Ptr)(short Startindex, short Count, float *Array, short Device_No, long *ErrorNo);
-short (FAR PASCAL *Get_ADBFPar_All_Double_Ptr)(short Startindex, short Count, double *Array, short Device_No, long *ErrorNo);
-long  (FAR PASCAL *Get_Data_Length_Ptr)(short DataNo, short Device_No, long *ErrorNo);
-short (FAR PASCAL *Get_Data_Type_Ptr)(short DataNo, short Device_No, long *ErrorNo);
-long  (FAR PASCAL *ADSetLanguage_Ptr)(long language);
-long  (FAR PASCAL *GetData_String_Ptr)(char *Data, long MaxCount, short DataNo, short Device_No, long *ErrorNo);
-long  (FAR PASCAL *String_Length_Ptr)(short DataNo, short Device_No, long *ErrorNo);
-long  (FAR PASCAL *SetData_String_Ptr)(char *Data, short DataNo, short Device_No, long *ErrorNo);
-short (FAR PASCAL *GetData_Packed_Ptr)(void *Data, short Typ, short DataNo, long Startindex, long Count, short Device_No, long *ErrorNo);
-
-short (FAR PASCAL *Get_Known_DeviceNo_Ptr)(short *Devices, long *Count_Devices);
-long  (FAR PASCAL *Get_Known_USB_SerialNo_Ptr)(long *SerialNo);
-int   (FAR PASCAL *ADwin_Debug_Mode_On_Ptr)(char *Filename, long Size);
-int   (FAR PASCAL *ADwin_Debug_Mode_Off_Ptr)(void);
-//05.05.04 MS
-long  (FAR PASCAL *Get_Dev_ID_Ptr)(short Device_No, long *value, long *ErrorNo);
-long  (FAR PASCAL *Get_Connection_Type_Ptr)(short Device_No);
-
-							/* Error message from the DLL On(1)/Off(0) */
-short message=1;            /* Error message if funktion fails */
-							/* Iserv, ADBPrLoad and Test.	0 = don't show error message */
-							/*								1 = show error message */
-
-/*************************************************/
-/* Load DLL and get the address of the function  */
-/*************************************************/
-int LoadDLLIfNeeded(void)
-{
-
-long	line = 0 ;
-char    msg[84] ;
-
-	//If adwin32.dll handle exist, don't load pointers again
-if (DLLHandle)
-	{
-    return 0;
-	}
-	//Depending on the compiler setting x86/x64 the correct adwin32.dll or adwin64.dll will be loaded.
-
-#ifdef _WIN64
-	#ifdef UNICODE
-	DLLHandle =  LoadLibrary(L"adwin64.dll");
-	#else
-	DLLHandle =  LoadLibrary("adwin64.dll");
-	#endif // !UNICODE
-#else
-	#ifdef UNICODE
-	DLLHandle =  LoadLibrary(L"adwin32.dll");
-	#else
-	DLLHandle =  LoadLibrary("adwin32.dll");
-	#endif // !UNICODE
-#endif
-
-if (DLLHandle == NULL)
-	{
-    return ( k_failed_to_load_DLL_error );
-    }
-
-    if ((File2Data_Ptr = (short (FAR PASCAL *)(char *, short, short, long, short ))GetProcAddress(DLLHandle,"File2Data"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_Data_Length_Ptr = (long (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_GetDataLength"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-	if ((Get_Data_Type_Ptr = (short (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_GetDataTyp"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Boot_Ptr = (long (FAR PASCAL *)(char *, short, long, short, long *))GetProcAddress(DLLHandle,"e_ADboot"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-	if ((Get_ADBFPar_All_Double_Ptr = (short (FAR PASCAL *)(short, short, double *, short , long *))GetProcAddress(DLLHandle,"e_Get_ADBFPar_All_Double"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_ADBFPar_All_Ptr = (short (FAR PASCAL *)(short, short, float *, short , long *))GetProcAddress(DLLHandle,"e_Get_ADBFPar_All"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-	if ((Get_ADBPar_All_Ptr = (short (FAR PASCAL *)(short, short, long *, short, long *ErrorNo))GetProcAddress(DLLHandle,"e_Get_ADBPar_All"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-	if ((Get_FPar_Double_Ptr = (double (FAR PASCAL *)(short, short,long *))GetProcAddress(DLLHandle,"e_Get_ADBFPar_Double"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_FPar_Ptr = (float (FAR PASCAL *)(short, short,long *))GetProcAddress(DLLHandle,"e_Get_ADBFPar"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_Par_Ptr = (long (FAR PASCAL *)(short, short,long *))GetProcAddress(DLLHandle,"e_Get_ADBPar"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-	if ((Set_FPar_Double_Ptr = (short (FAR PASCAL *)(short, double, short,long*))GetProcAddress(DLLHandle,"e_Set_ADBFPar_Double"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Set_FPar_Ptr = (short (FAR PASCAL *)(short, float, short,long *))GetProcAddress(DLLHandle,"e_Set_ADBFPar"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Set_Par_Ptr = (short (FAR PASCAL *)(short, long, short, long *))GetProcAddress(DLLHandle,"e_Set_ADBPar"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Load_Process_Ptr = (short (FAR PASCAL *)(char *, short, short,long *))GetProcAddress(DLLHandle,"e_ADBload"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Start_Process_Ptr = (short (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_ADB_Start"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Stop_Process_Ptr = (short (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_ADB_Stop"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_Data_Ptr = (short (FAR PASCAL *)(void*, short, short, long, long, short,long *))GetProcAddress(DLLHandle,"e_Get_Data"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Set_Data_Ptr = (short (FAR PASCAL *)(void*, short, short, long, long, short, long *))GetProcAddress(DLLHandle,"e_Set_Data"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Save_Fast_Ptr = (short (FAR PASCAL *)(char *, short, long, long, short, short, long *))GetProcAddress(DLLHandle,"e_SaveFast"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-	if ((Get_Fifo_Ptr = (short (FAR PASCAL *)(void*, short, short, long, short, long *))GetProcAddress(DLLHandle,"e_Get_Fifo"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Set_Fifo_Ptr = (short (FAR PASCAL *)(void*, short, short, long, short, long *))GetProcAddress(DLLHandle,"e_Set_Fifo"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_Fifo_Count_Ptr = (long (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_Get_Fifo_Count"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_Fifo_Empty_Ptr = (long (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_Get_Fifo_Empty"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Fifo_Clear_Ptr = (short (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_Clear_Fifo"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Workload_Ptr = (short (FAR PASCAL *)(long, short, long *))GetProcAddress(DLLHandle,"e_AD_Workload"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((ADTest_Version_Ptr = (short (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_ADTest_Version"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((AD_Memory_Ptr = (long (FAR PASCAL *)(short, long *))GetProcAddress(DLLHandle,"e_AD_Memory"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((AD_Memory_all_Ptr = (long (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_AD_Memory_all"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((AD_GetErrorCode_Ptr = (long (FAR PASCAL *)(short))GetProcAddress(DLLHandle,"ADGetErrorCode"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((AD_GetErrorText_Ptr = (char (FAR PASCAL *)(long, char *, long))GetProcAddress(DLLHandle,"ADGetErrorText"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((ADSetLanguage_Ptr = (long (FAR PASCAL *)(long))GetProcAddress(DLLHandle,"ADSetLanguage"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((GetData_String_Ptr = (long (FAR PASCAL *)(char *, long, short, short, long *))GetProcAddress(DLLHandle,"e_Get_Data_String"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((String_Length_Ptr = (long (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_Get_Data_String_Length"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((SetData_String_Ptr = (long (FAR PASCAL *)(char *, short, short, long *))GetProcAddress(DLLHandle,"e_Set_Data_String"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((GetData_Packed_Ptr = (short (FAR PASCAL *)(void *, short, short, long, long, short, long *))GetProcAddress(DLLHandle,"e_Get_Data_packed"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((ADProzessorTyp_Ptr = (short (FAR PASCAL *)(short Device_No, long *))GetProcAddress(DLLHandle,"e_ProzessorTyp"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Clear_Process_Ptr = (long (FAR PASCAL *)(short, short,long *))GetProcAddress(DLLHandle,"e_Clear_Process"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_Known_DeviceNo_Ptr = (short (FAR PASCAL *)(short *, long *))GetProcAddress(DLLHandle,"Get_Known_Deviceno"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_Known_USB_SerialNo_Ptr = (long (FAR PASCAL *)(long *))GetProcAddress(DLLHandle,"Get_Known_USB_SerialNo"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((ADwin_Debug_Mode_On_Ptr = (int (FAR PASCAL *)(char  *, long))GetProcAddress(DLLHandle,"adwin_debug_mode_on"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((ADwin_Debug_Mode_Off_Ptr = (int (FAR PASCAL *)(void))GetProcAddress(DLLHandle,"adwin_debug_mode_off"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_Dev_ID_Ptr = (long (FAR PASCAL *)(short, long *, long *))GetProcAddress(DLLHandle,"e_get_dev_id"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((Get_Connection_Type_Ptr = (long (FAR PASCAL *)(short))GetProcAddress(DLLHandle,"ADGetConnectionTyp"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-    if ((AD_Memory_all_byte_Ptr = (long (FAR PASCAL *)(short, short, long *))GetProcAddress(DLLHandle,"e_AD_Memory_all_byte"))==0)
-		{
-		line = __LINE__ ;
-		goto FunctionNotFoundError;
-		}
-
-return 0;
-
-
-							/* Error handling */
-FunctionNotFoundError:
-
-if (FirstTime==1)
-	{
-#ifdef UNICODE
-	MessageBox(NULL, L"You need a newer version of the ADwin32.dll or ADwin64.dll,\nat least ADwin32/64.dll from 18.9.2014!\nAbort the program and update the ADwin software now.", L"ADwin32/64.dll too old!", MB_ICONWARNING);
-#else
-	MessageBox(NULL, "You need a newer version of the ADwin32.dll or ADwin64.dll,\nat least ADwin32/64.dll from 18.9.2014!\nAbort the program and update the ADwin software now.", "ADwin32/64.dll too old!", MB_ICONWARNING);
-
-	if( line != 0 )
-	{
-		//sprintf( &msg[0] , "Error in line %d." , line-2 ) ;
-		sprintf_s( &msg[0] ,80 , "Error in line %d." , line-2 ) ;
-		MessageBox(NULL , &msg[0] , "" , MB_ICONWARNING);
-	}
-
-
-#endif // !UNICODE
-
-
-	FirstTime = 0;			/* No more messages */
-	}
-
-FreeLibrary(DLLHandle);     /* Remove the DLL */
-DLLHandle = 0;
-
-return( k_could_not_find_function ) ;
-}
-
-/*****************************************/
-/* Connection code to the DLL functions  */
-/*****************************************/
-
-/* Down-loads the operating system (BTL-file) to the ADwin-System */
-/* ============================================================================== */
-void Boot(char *Filename, short DeviceNo, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = (long)LoadDLLIfNeeded())!=0)
-	{
-		*ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Boot_Ptr)(Filename, DeviceNo, 0, message, ErrorNo );							/* Boot the ADwin card */
-	}
-}
-
-
-/* Loads an ADbasic-process (a bin file generated by ADbasic) to the ADwin board  */
-/* ============================================================================== */
-void Load_Process(char *Filename , short DeviceNo,long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-	 	(*Load_Process_Ptr)(Filename, DeviceNo, message,ErrorNo);	/* Load bin file */
-	}
-}
-
-
-/* Starts process number "ProcessNo" on the ADwin-System						  */
-/* ============================================================================== */
-void Start_Process(short ProcessNo , short DeviceNo,long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Start_Process_Ptr)(ProcessNo, DeviceNo,ErrorNo);	/* Start process */
-	}
-}
-
-
-/* Stops process number "ProcessNo" on the ADwin-System							  */
-/* ============================================================================== */
-void Stop_Process(short ProcessNo , short DeviceNo,long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Stop_Process_Ptr)(ProcessNo, DeviceNo,ErrorNo);	/* Stop process */
-	}
-}
-
-
-/* Sets a parameter (PAR_"Index") on the ADwin-System to "Value"				  */
-/* ============================================================================== */
-void Set_Par (short Index, long Value, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Set_Par_Ptr)(Index, Value, DeviceNo, ErrorNo);		/* Set parameter */
-	}
-}
-
-/* Sets a parameter (FPAR_"Index") on the ADwin-System to "Value"				  */
-/* ============================================================================== */
-void Set_FPar (short Index, float Value, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Set_FPar_Ptr)(Index, Value, DeviceNo,ErrorNo);		/* Set float parameter */
-	}
-}
-
-
-/* Returns double value of parameter (FPAR_"Index") from the ADwin-System          */
-/* ============================================================================== */
-void Set_FPar_Double(short Index, double Value, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Set_FPar_Double_Ptr)(Index, Value, DeviceNo,ErrorNo);            /* Set Double parameter */
-	}
-}
-
-
-/* Returns the value of parameter (PAR_"Index") from the ADwin-System			  */
-/* ============================================================================== */
-long Get_Par(short Index , short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return (*Get_Par_Ptr)(Index,DeviceNo,ErrorNo);				/* Get parameter */
-	}
-}
-
-
-/* Returns float value of parameter (FPAR_"Index") from the ADwin-System          */
-/* ============================================================================== */
-float Get_FPar(short Index , short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return (*Get_FPar_Ptr)(Index, DeviceNo, ErrorNo);            /* Get float parameter */
-	}
-}
-
-/* Returns double value of parameter (FPAR_"Index") from the ADwin-System          */
-/* ============================================================================== */
-double Get_FPar_Double(short Index , short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return (*Get_FPar_Double_Ptr)(Index, DeviceNo,ErrorNo);            /* Get float parameter */
-	}
-}
-/* Gets all 80 ADwin double parameters (FPar_1 - FPar_80) into a double array					  */
-/* If T9..T11: Gets all 80 ADwin float parameters (FPar_1 - FPar_80) into a double array					  */
-/* ============================================================================== */
-void Get_FPar_All_Double (double Array[] , short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_ADBFPar_All_Double_Ptr)(1, 80, Array, DeviceNo,ErrorNo);            /* Get float parameter */
-	}
-}
-
-/* Gets a block of ADwin double parameters into a double array					  */
-/* ============================================================================== */
-void Get_FPar_Block_Double(double Array[], short Startindex, short Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-	   (*Get_ADBFPar_All_Double_Ptr)(Startindex, Count, Array, DeviceNo, ErrorNo);
-	}
-}
-
-
-/* Returns array-element(s) of long-type from ADwin-System-array (DATA_"DataNo")  */
-/* ============================================================================== */
-void GetData_Long (short DataNo, long Data[], long Startindex, long Count, short DeviceNo , long * ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_Data_Ptr)(Data, TYPE_LONG, DataNo, Startindex, Count, DeviceNo,ErrorNo);
-	}
-}
-
-/* Returns array-element(s) of double-type from ADwin-System-array (DATA_"DataNo") */
-/* ==============================================================================  */
-void GetData_Double (short DataNo, double Data[],long Startindex, long Count, short DeviceNo , long * ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_Data_Ptr)(Data, TYPE_DOUBLE, DataNo, Startindex, Count, DeviceNo, ErrorNo);
-	}
-}
-
-
-/* Returns array-element(s) of float-type from ADwin-System-array (DATA_"DataNo") */
-/* ============================================================================== */
-void GetData_Float (short DataNo, float Data[], long Startindex, long Count, short DeviceNo , long * ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_Data_Ptr)(Data, TYPE_FLOAT, DataNo, Startindex, Count, DeviceNo, ErrorNo);
-	}
-}
-
-
-/* Sets array-element(s) of ADwin-System from long-array						  */
-/* ============================================================================== */
-void SetData_Long(short DataNo, long Data[], long Startindex, long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Set_Data_Ptr)(Data, TYPE_LONG, DataNo, Startindex, Count, DeviceNo,ErrorNo);
-	}
-}
-
-/* Sets array-element(s) of ADwin-System from double-array						  */
-/* ============================================================================== */
-void SetData_Double(short DataNo, double Data[], long Startindex, long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Set_Data_Ptr)(Data, TYPE_DOUBLE, DataNo, Startindex, Count, DeviceNo,ErrorNo);
-	}
-}
-
-/* Sets array-element(s) of ADwin-System from float-array						   */
-/* =============================================================================== */
-void SetData_Float(short DataNo, float Data[], long Startindex, long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Set_Data_Ptr)(Data, TYPE_FLOAT, DataNo, Startindex, Count, DeviceNo,ErrorNo);
-	}
-}
-
-/* Writes array-elements of ADwin-System immediately to harddisk			    */
-/* ============================================================================ */
-void Data2File(char *Filename, short DataNo, long Startindex, long Count, short Mode, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Save_Fast_Ptr)(Filename, DataNo, Startindex, Count, Mode, DeviceNo,ErrorNo);
-	}
-}
-
-/* Writes a file immediately from harddisk to array-elements of ADwin-System 			    */
-/* ============================================================================ */
-void File2Data(char *Filename, short DataType, short DataNo, long Startindex, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		//Hint: DataType constant
-		//			TYPE_LONG;   2= long
-	    // 			TYPE_FLOAT;  5= float
-	    //			TYPE_DOUBLE; 6= double
-		*ErrorNo = (*File2Data_Ptr)(Filename, DataType, DataNo, Startindex, DeviceNo) ;
-	}
-}
-
-
-/* Fetching the long-element(s) from a ADwin-System FIFO						  */
-/* ============================================================================== */
-void GetFifo_Long(short FifoNo, long Data[], long Count, short DeviceNo , long * ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_Fifo_Ptr)(Data, TYPE_LONG, FifoNo, Count, DeviceNo, ErrorNo);
-	}
-}
-
-/* Fetching the double-element(s) from a ADwin-System FIFO						  */
-/* ============================================================================== */
-void GetFifo_Double(short FifoNo, double Data[], long Count, short DeviceNo , long * ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_Fifo_Ptr)(Data, TYPE_DOUBLE, FifoNo, Count, DeviceNo, ErrorNo);
-	}
-}
-
-
-/* Fetching the float-element(s) from a ADwin-System FIFO						  */
-/* ============================================================================== */
-void GetFifo_Float(short FifoNo, float Data[], long Count, short DeviceNo , long * ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_Fifo_Ptr)(Data, TYPE_FLOAT, FifoNo, Count, DeviceNo, ErrorNo);
-	}
-}
-
-
-/* Sets FIFO-element(s) of ADwin-System from long-array							  */
-/* ============================================================================== */
-void SetFifo_Long(short FifoNo, long Data[], long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Set_Fifo_Ptr)(Data, TYPE_LONG, FifoNo, Count, DeviceNo,ErrorNo);
-	}
-}
-
-/* Sets FIFO-element(s) of ADwin-System from double-array						  */
-/* ============================================================================== */
-void SetFifo_Double(short FifoNo, double Data[], long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Set_Fifo_Ptr)(Data, TYPE_DOUBLE, FifoNo, Count, DeviceNo,ErrorNo);
-	}
-}
-
-/* Sets FIFO-element(s) of ADwin-System from float-array						  */
-/* ============================================================================== */
-void SetFifo_Float(short FifoNo, float Data[], long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Set_Fifo_Ptr)(Data, TYPE_FLOAT, FifoNo, Count, DeviceNo,ErrorNo);
-	}
-}
-
-
-/* Getting the number of elements in the FIFO									  */
-/* ============================================================================== */
-long Fifo_Full(short FifoNo, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return (*Get_Fifo_Count_Ptr)(FifoNo, DeviceNo,ErrorNo);
-	}
-}
-
-/* Returns number of free elements in FIFO										  */
-/* ============================================================================== */
-long Fifo_Empty (short FifoNo, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return (*Get_Fifo_Empty_Ptr)(FifoNo, DeviceNo,ErrorNo);
-	}
-}
-
-/* Initiats read and write pointer of FIFO										  */
-/* ============================================================================== */
-void Fifo_Clear (short FifoNo, short DeviceNo, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Fifo_Clear_Ptr)(FifoNo, DeviceNo, ErrorNo);
-	}
-}
-
-/* Returns how busy the CPU is (processor usage in percent)                       */
-/* ============================================================================== */
-short Workload(long Priority, short DeviceNo, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return (*Workload_Ptr)(Priority, DeviceNo, ErrorNo);          /* Ergebnis abholen */
-	}
-}
-
-/* Checks if the CPU is accessible (previously booted and running)				  */
-/* ============================================================================== */
-short Test_Version(short DeviceNo, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return (*ADTest_Version_Ptr)(DeviceNo, message, ErrorNo);
-	}
-}
-
-/* Returns value of free memory from the ADwin-2, -4, -5 ,-8, -9, -10 and -11 System(in Bytes) */
-/* Returns value of free memory from the ADwin-12 System(in kBytes) */
-/* ================================================================================= */
-long Free_Mem(short Mem_Spec, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		short Processor = Processor_Type(DeviceNo, ErrorNo);
-		switch(Processor)
-		{
-			case 2:
-			case 4:
-			case 5:
-			case 8:
-				switch(Mem_Spec)
-				{
-					case 0:	/* 0 = T2, T4, T5, T8 */
-						return (*AD_Memory_Ptr)(DeviceNo,ErrorNo);							//return value in Byte
-					default:
-						*ErrorNo = k_mem_type_not_supported;
-						return -1;
-				}
-
-			/* Mem_Spec */
-			/* 1 = PM          : T9, T10, T11 */
-			/* 2 = EM          : T11          */
-			/* 3 = DM_Local    : T9, T10, T11 */
-			/* 4 = DRAM_Extern : T9, T10, T11 */
-
-			/* 5 = Cacheable  : T12   in kBytes */
-			/* 6 = Uncacheable: T12   in kBytes */
-			case 9:
-			case 1010:
-				switch(Mem_Spec)
-				{
-					case 1:
-						return (*AD_Memory_all_Ptr)(Mem_Spec, DeviceNo,ErrorNo)*6;	//return value in Byte
-					case 3:
-					case 4:
-						return (*AD_Memory_all_Ptr)(Mem_Spec, DeviceNo,ErrorNo)*4;	//return value in Byte
-					default:
-						*ErrorNo = k_mem_type_not_supported;
-						return -1;
-				}
-			case 1011:
-				switch(Mem_Spec)
-				{
-					case 1:
-					case 2:
-					case 3:
-					case 4:
-						return (*AD_Memory_all_Ptr)(Mem_Spec, DeviceNo,ErrorNo)*4;		//return value in Byte
-					default:
-						*ErrorNo = k_mem_type_not_supported;
-						return -1;
-				}
-			case 1012:
-				switch(Mem_Spec)
-				{
-					case 5:
-					case 6:
-						return (*AD_Memory_all_Ptr)(Mem_Spec, DeviceNo,ErrorNo);        //return value in kByte
-					default:
-						*ErrorNo = k_mem_type_not_supported;
-						return -1;
-				}
-			default:
-				*ErrorNo = k_mem_type_not_supported;
-				return -1;
-		}
-	}
-}
-
-/* Error messages for Boot, Load_Process    0/1 -> (off/on)        */
-/* ============================================================================== */
-void Show_Errors(short OnOff)
-{
-  message=OnOff;
-}
-
-/* Gets the error text of the "Error Number"									  */
-/* ============================================================================== */
-char *Get_Error_Text(long ErrorNo, char *ErrorText , long Length)
-{
-    if ((short)LoadDLLIfNeeded()!=0)
-	{
-		
-		//strcpy(ErrorText, "dllLoadError in Get_Error_Text");
-		strcpy_s(ErrorText, Length, "dllLoadError in Get_Error_Text");
-		return (ErrorText);
-	}
-	else
-	{
-		(*AD_GetErrorText_Ptr)(ErrorNo, ErrorText, Length);
-		return (ErrorText);
-	}
-}
-
-
-/* Returns the Processortype												      */
-/* ============================================================================== */
-short Processor_Type(short DeviceNo,long *ErrorNo)
-{
-	short merker,Processor_Type;
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		merker = (*ADProzessorTyp_Ptr)(DeviceNo, ErrorNo);
-		Processor_Type = merker;
-
-		if (merker == 146)
-		Processor_Type = 5;
-		if (merker == 1000)
-		Processor_Type = 9;
-		// The other processor types are returned direct with the correct number
-
-		return (Processor_Type);
-	}
-}
-
-/* Clear the Process															  */
-/* ============================================================================== */
-void Clear_Process(short ProcessNo, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Clear_Process_Ptr)(ProcessNo,DeviceNo,ErrorNo);
-	}
-}
-
-/* Returns the Processstatus													  */
-/* ============================================================================== */
-long Process_Status(short ProcessNo, short DeviceNo , long *ErrorNo)
-{
-	long ProcessStatus;
-	short erg;
-
-	erg = (short)(-100 + ProcessNo);
-	ProcessStatus = Get_Par(erg,DeviceNo,ErrorNo);
-
-	return (ProcessStatus);
-}
-
-/* Gets a block of ADwin long parameters into a long array						  */
-/* ============================================================================== */
-void Get_Par_Block(long Array[], short Startindex, short Count, short DeviceNo, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_ADBPar_All_Ptr)(Startindex, Count, Array, DeviceNo,ErrorNo);
-	}
-}
-
-/* Gets a block of ADwin integer parameters into a long array					  */
-/* ============================================================================== */
-void Get_FPar_Block(float Array[], short Startindex, short Count, short DeviceNo,long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_ADBFPar_All_Ptr)(Startindex, Count, Array, DeviceNo,ErrorNo);
-	}
-}
-
-/* Gets all 80 long parameters (Par_1 - Par_80) into a long array				  */
-/* ============================================================================== */
-void Get_Par_All(long Array[], short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_ADBPar_All_Ptr)(1, 80, Array, DeviceNo, ErrorNo);
-	}
-}
-
-/* Gets all 80 float parameters (Par_1 - Par_80) into a long array				  */
-/* ============================================================================== */
-void Get_FPar_All(float Array[], short DeviceNo, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_ADBFPar_All_Ptr)(1, 80, Array, DeviceNo,ErrorNo);
-	}
-}
-
-/* Returns the length of a data													  */
-/* ============================================================================== */
-long Data_Length(short DataNo, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		long ReturnValue;
-		ReturnValue = (*Get_Data_Length_Ptr)(DataNo, DeviceNo, ErrorNo);
-		if (ReturnValue == 0)
-		{	/*Return value = 0 = Array not declared / Feld ist nicht deklariert  */
-			*ErrorNo = k_Data_not_declared;
-			return -1;
-		}
-		else
-		{
-			return ReturnValue;
-		}
-	}
-}
-
-/* Returns the type (float, integer, short) of a data													  */
-/* ============================================================================== */
-short Data_Type(short DataNo, char *TypeName, short DeviceNo , long *ErrorNo)
-{
-	short ret_type;
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		ret_type = (*Get_Data_Type_Ptr)(DataNo, DeviceNo, ErrorNo);
-		if (ret_type == 3) //only return type 3 is not clearly between differnet processors
-		{
-			//Because ret_type=3 is not realy clear between different processors we check the processor type
-			if (Processor_Type(DeviceNo, ErrorNo) == 1012) //if T12 change to type "Long"
-			{
-				ret_type = 4; //return type is LONG by T12
-			}
-		}
-		//    ret_type =         0   ,   1   ,    2   ,     3    ,   4   ,    5     ,     6   ,    7    , 8 
-		//Type_Array[] = {"Undefined", "Byte", "Short", "Int32", "Long", "Float32", "Float64", "Int64", "String"};
-		if (TypeName!=NULL) strcpy_s(TypeName, 10, Type_Array[ret_type]);
-		//if (TypeName!=NULL) strcpy(TypeName, Type_Array[ret_type]);
-
-		return (ret_type);
-	}
-}
-
-/* Sets a processdelay for a specified prozess on the ADwin-System				  */
-/* ============================================================================== */
-void Set_Processdelay(short ProcessNo, long Processdelay, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		Set_Par((short)(-90+ProcessNo), Processdelay , DeviceNo , ErrorNo);
-	}
-
-}
-
-/* Gets a processdelay for a specified prozess on the ADwin-System				  */
-/* ============================================================================== */
-long Get_Processdelay(short ProcessNo, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return Get_Par((short)(-90+ProcessNo), DeviceNo , ErrorNo );
-	}
-}
-
-
-/* Sets the language for the error messages										  */
-/* ============================================================================== */
-void Set_Language(long language, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*ADSetLanguage_Ptr)(language);
-	}
-}
-
-/* Returns array-element(s) of char-type from ADwin-System-array (DATA_"DataNo")  */
-/* ============================================================================== */
-long GetData_String(short DataNo, char *Data, long MaxCount, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return (*GetData_String_Ptr)(Data, MaxCount+1, DataNo, DeviceNo,ErrorNo);
-	}
-}
-
-/* Returns the lenght of a string												  */
-/* ============================================================================== */
-long String_Length(short DataNo, short DeviceNo, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return (*String_Length_Ptr)(DataNo, DeviceNo,ErrorNo);
-	}
-}
-
-/* Write a String into a (DATA_"DataNo")										  */
-/* ============================================================================== */
-void SetData_String(short DataNo, char *Data, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*SetData_String_Ptr)(Data, DataNo, DeviceNo,ErrorNo);
-	}
-}
-
-/* Returns array-element(s) of short-type from packed ADwin-System-array (DATA_"DataNo") */
-/* ============================================================================== */
-void GetData_Packed_Short(short DataNo, short *Data, long Startindex, long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*GetData_Packed_Ptr)(Data, TYPE_SHORT, DataNo, Startindex, Count, DeviceNo,ErrorNo);
-	}
-}
-
-/* Returns array-element(s) of long-type from packed ADwin-System-array (DATA_"DataNo") */
-/* ============================================================================== */
-void GetData_Packed_Long(short DataNo, long *Data, long Startindex, long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*GetData_Packed_Ptr)(Data, TYPE_LONG, DataNo, Startindex, Count, DeviceNo,ErrorNo);
-	}
-}
-
-/* Returns array-element(s) of float-type from packed ADwin-System-array (DATA_"DataNo") */
-/* ============================================================================== */
-void GetData_Packed_Float(short DataNo, float *Data, long Startindex, long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*GetData_Packed_Ptr)(Data, TYPE_FLOAT, DataNo, Startindex, Count, DeviceNo,ErrorNo);
-	}
-}
-
-/* Returns array-element(s) of double-type from packed ADwin-System-array (DATA_"DataNo") */
-/* ============================================================================== */
-void GetData_Packed_Double(short DataNo, double *Data, long Startindex, long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*GetData_Packed_Ptr)(Data, TYPE_DOUBLE, DataNo, Startindex, Count, DeviceNo,ErrorNo);
-	}
-}
-
-
-/* Reads out the known device numbers which are configured in the PC			  */
-/* ============================================================================== */
-void Get_Known_DeviceNo(short *Devices, long *Count_Devices, long *ErrorNo)
-{
-	*ErrorNo = 0;
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		short ret_Fkt = (*Get_Known_DeviceNo_Ptr)(Devices, Count_Devices);
-		if (ret_Fkt == 1 && Devices != 0) *ErrorNo = k_count_devices_too_small;
-	}
-}
-
-/* Reads out the known USB device serialnumbers which are configured in the PC			  */
-/* ============================================================================== */
-long Get_Known_USB_SerialNo(long *SerialNo, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	    return -1;
-	}
-	else
-	{
-		return (*Get_Known_USB_SerialNo_Ptr)(SerialNo);
-	}
-}
-
-/* Reads out the known USB device serialnumbers which are configured in the PC			  */
-/* ============================================================================== */
-void ADwin_Debug_Mode_On(char  *Filename, long Size, long *ErrorNo)
-{
-    *ErrorNo = 0;
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		int ReturnValue;
-		ReturnValue = (*ADwin_Debug_Mode_On_Ptr)(Filename, Size);
-		if (ReturnValue == -1)
-		 	*ErrorNo = k_File_name_too_long;
-		if (ReturnValue == -2)
-			*ErrorNo = k_debug_mode_already_on;
-		if (ReturnValue == -3)
-			*ErrorNo = k_no_permission_on_registry;
-	}
-}
-
-/* Reads out the known USB device serialnumbers which are configured in the PC			  */
-/* ============================================================================== */
-void ADwin_Debug_Mode_Off(long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*ADwin_Debug_Mode_Off_Ptr)();
-	}
-}
-
-/* Returns Fifo-element(s) of short-type from packed ADwin-Fifo-array (DATA_"DataNo") */
-/* ============================================================================== */
-void GetFifo_Packed_Short(short FifoNo, short Data[], long Count, short DeviceNo , long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_Fifo_Ptr)(Data, TYPE_LONG, FifoNo, Count, DeviceNo,ErrorNo);
-	}
-}
-
-/* The function "GetFifo_Packed_Long " is deleted, because it was not working in the requested way. */
-/* ============================================================================== */
-
-/* Reads out the Type of Connection */
-/* ============================================================================== */
-long Get_Connection_Type(short DeviceNo, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-		return -1;
-	}
-	else
-	{
-		return (*Get_Connection_Type_Ptr)(DeviceNo);
-		/*Return Value:  -1: ERROR */
-		/*                0: PORT (ISA/LINK) */
-		/*                1: USB -> Device connected */
-		/*                2: TCP/IP */
-		/*               11: USB -> Device not connected */
-	}
-}
-
-
-/* 05.05.2004 MS
-Important:
-
-If an application program reads the MAC for identifying a special ADwin-system and will refuse operation , if the MAC does not match, then the following issue should be considered :
-
-What if an ADwin-system breaks and needs to be replaced ?
-
-Jaeger Messtechnik will not provide a spare part with an IDENTICAL  MAC address or USB- serialnumber !
-
-The application program has to be prepared somehow, that a replacement with an ADwin-system with a DIFFERENT MAC or USB- serialnumber might be necessary !
-
-Firewall settings:
-The (*.exe) program, which uses Get_DEV_ID has to be added as an exception in the (XP, Vista, ...) firewall settings.
-
-AND:  It must be ensured, that the (UDP) Port 7000 is not blocked by the firewall.
-*/
-
-/* Reads out the USB device serialnumber / the MAC-Adress from specified System   */
-/* ============================================================================== */
-void Get_Dev_ID(long *value, short DeviceNo, long *ErrorNo)
-{
-    long dllLoadError;
-    if ((dllLoadError = LoadDLLIfNeeded())!=0)
-	{
-        *ErrorNo = dllLoadError;
-	}
-	else
-	{
-		(*Get_Dev_ID_Ptr)(DeviceNo, value,ErrorNo);
-	}
-}
-
-
-// End of file
-
-
diff --git a/unordered/qontrol/ADwin_V2.h b/unordered/qontrol/ADwin_V2.h
deleted file mode 100644
index c756e645f49e2fb8e5f6f1784c33a3d010e4fd52..0000000000000000000000000000000000000000
--- a/unordered/qontrol/ADwin_V2.h
+++ /dev/null
@@ -1,149 +0,0 @@
-/*************************************************************
-* Include File zum Einbinden der Prototypen f�r die Aufrufe an
-* die ADwin-Karten.
-* Erstellt am : 30.05.2001  M.S.
-* ge�ndert am :	12.06.2001  M.S.
-				15.05.2002  M.S.
-				18.07.2003  M.S.
-				24.11.2003  M.S.
-				05.05.2004  M.S.
-				16.02.2009  M.S.
-				08.12.2010  M.S. Comment with default DeviceNo changed.
-                14.04.2015  M.S. First code review. Obsolet functions deleted.
-				23.04.2015  M.S. Again reworked dipends to ADwin_T.c Version 2.00b9
- Version 2.00   03.07.2015  M.S. Moved the #defines from the ADwin_V2.cpp/ADwin_V2.c files to ADwin_V2.h
- Version 2.01   28.01.2016  M.S. Use the same data type "short" for variable "DataNo".
-                                 Changed functions: Data_Length, GetData_String, String_Length, SetData_String
-**************************************************************/
-
-#ifndef __adwin_v2_h__
-#define __adwin_v2_h__
-
-
-#ifdef __cplusplus
-extern "C" {
-#endif  /* __cplusplus */
-
-
-//Used in function: Data_Length
-#define k_Data_not_declared           103	//Data is not declared.
-
-#define k_failed_to_load_DLL_error  50000   //It was not possible to load the adwin32.dll or adwin64.dll
-#define k_could_not_find_function   50001   //The called function is not available in the adwin32.dll or adwin64.dll which is used.
-
-//Used in function: Free_Mem
-#define k_mem_type_not_supported    50010   //The chosen memory type is not supported by the processor.
-
-//Used in function: Get_Known_DeviceNo
-#define k_count_devices_too_small   50020   //Count_Devicesis smaller than the 
-										    //current number of configured system.
-										    //Count_Devices and Devices are unchanged.
-
-//Used in function: ADwin_Debug_Mode_On
-#define k_File_name_too_long		50030   //File name > 255 characters (cannot be processed).
-#define k_debug_mode_already_on		50031   //Debug mode already activated (no effect)
-#define k_no_permission_on_registry	50032   //Access to the registry is needed, but impossible. Probably
-											//the user does not have the necessary administration
-											//rights for access or the max. size of the registry is
-											//exceeded. Please call your administrator
-
-/* Prototypes of commonly used control functions from the file adwin.c */
-
-
-#define TYPE_SHORT 1
-#define TYPE_LONG 2
-#define TYPE_FLOAT 5
-#define TYPE_DOUBLE 6
-
-void	Set_Par(short Index, long Value, short DeviceNo, long *ErrorNo);
-void	Set_FPar(short Index, float Value, short DeviceNo, long *ErrorNo);
-void	Set_FPar_Double (short Index, double Value, short DeviceNo, long *ErrorNo);
-long	Get_Par(short Index, short DeviceNo, long *ErrorNo);
-float	Get_FPar (short Index, short DeviceNo, long *ErrorNo);
-double	Get_FPar_Double (short Index, short DeviceNo, long *ErrorNo);
-void	Get_FPar_All_Double (double Array[], short DeviceNo , long *ErrorNo);
-void	Get_Par_Block(long Array[], short Startindex, short Count, short DeviceNo,long *ErrorNo);
-void	Get_FPar_Block(float Array[], short Startindex, short Count, short DeviceNo , long *ErrorNo);
-void	Get_Par_All(long Array[], short DeviceNo,long *ErrorNo);
-void	Get_FPar_All(float Array[], short DeviceNo,long *ErrorNo);
-void	Set_Processdelay(short ProcessNo, long Processdelay, short DeviceNo , long *ErrorNo);
-long	Get_Processdelay(short ProcessNo, short DeviceNo , long *ErrorNo);
-void	Get_FPar_Block_Double(double Array[], short Startindex, short Count, short DeviceNo , long *ErrorNo);
-long	Process_Status(short ProcessNo, short DeviceNo , long *ErrorNo );
-
-void	Load_Process(char *Filename, short DeviceNo , long *ErrorNo);
-void	Start_Process(short ProcessNo, short DeviceNo , long *ErrorNo);
-void	Stop_Process(short ProcessNo, short DeviceNo , long *ErrorNo);
-
-
-void	Boot(char *Filename, short DeviceNo, long *ErrorNo);
-
-void	GetData_Long (short DataNo, long Data[],long Startindex, long Count, short DeviceNo , long *ErrorNo);
-void	GetData_Float (short DataNo, float Data[], long Startindex, long Count, short DeviceNo , long *ErrorNo);
-void	SetData_Long (short DataNo, long Data[], long Startindex, long Count, short DeviceNo , long *ErrorNo);
-void	SetData_Float (short DataNo, float Data[], long Startindex, long Count, short DeviceNo , long *ErrorNo);
-void	Data2File(char *Filename, short DataNo, long Startindex, long Count, short Mode, short DeviceNo , long *ErrorNo);
-void	File2Data(char *Filename, short DataType, short DataNo, long Startindex, short DeviceNo , long *ErrorNo);
-void	GetFifo_Long(short FifoNo, long Data[], long Count, short DeviceNo , long *ErrorNo);
-void	GetFifo_Float(short FifoNo, float Data[], long Count, short DeviceNo , long *ErrorNo);
-void	SetFifo_Long (short FifoNo, long Data[], long Count, short DeviceNo , long *ErrorNo);
-void	SetFifo_Float (short FifoNo, float Data[], long Count, short DeviceNo , long *ErrorNo);
-long	Fifo_Full (short FifoNo, short DeviceNo , long *ErrorNo);
-long	Fifo_Empty (short FifoNo, short DeviceNo , long *ErrorNo);
-void	Fifo_Clear (short FifoNo, short DeviceNo , long *ErrorNo);
-
-void	GetData_Double(short DataNo, double Data[],long Startindex, long Count, short DeviceNo , long *ErrorNo);
-void	SetData_Double(short DataNo, double Data[], long Startindex, long Count, short DeviceNo , long *ErrorNo);
-void	GetFifo_Double(short FifoNo, double Data[], long Count, short DeviceNo , long *ErrorNo);
-void	SetFifo_Double(short FifoNo, double Data[], long Count, short DeviceNo , long *ErrorNo);
-
-void	Clear_Process(short ProcessNo, short DeviceNo , long *ErrorNo);
-
-short	Workload(long Priority, short DeviceNo ,long *ErrorNo);
-short	Test_Version(short DeviceNo, long *ErrorNo) ;
-long	Free_Mem(short Mem_Spec, short DeviceNo ,long *ErrorNo);
-void	Show_Errors(short OnOff);
-char	*Get_Error_Text(long ErrorNumber, char *ErrorText , long Length) ;
-
-short	Processor_Type(short DeviceNo,long *ErrorNo);
-long	Data_Length(short DataNo, short DeviceNo ,long *ErrorNo);
-short   Data_Type(short DataNo, char *TypeName, short DeviceNo ,long *ErrorNo);
-void	Set_Language(long language, long *ErrorNo);
-long	GetData_String(short DataNo, char *Data, long MaxCount, short DeviceNo ,long *ErrorNo);
-long	String_Length(short DataNo, short DeviceNo ,long *ErrorNo);
-void	SetData_String(short DataNo, char *Data, short DeviceNo ,long *ErrorNo);
-void	Get_Known_DeviceNo(short Devices[], long *Count_Devices, long *ErrorNo);
-long	Get_Known_USB_SerialNo(long SerialNo[], long *ErrorNo);
-void	ADwin_Debug_Mode_On(char *Filename, long Size, long *ErrorNo);
-void	ADwin_Debug_Mode_Off(long *ErrorNo);
-
-// undocumented
-void	GetData_Packed_Short(short DataNo, short *Data, long Startindex, long Count, short DeviceNo , long *ErrorNo);
-void	GetData_Packed_Long(short DataNo, long *Data, long Startindex, long Count, short DeviceNo , long *ErrorNo);
-void	GetData_Packed_Float(short DataNo, float *Data, long Startindex, long Count, short DeviceNo , long *ErrorNo);
-void	GetData_Packed_Double(short DataNo, double *Data, long Startindex, long Count, short DeviceNo , long *ErrorNo);
-void	GetFifo_Packed_Short(short FifoNo, short Data[], long Count, short DeviceNo , long *ErrorNo);
-
-void	Get_Data_Packed(void *Data, short Typ, short DataNo, long Startindex, long Count, short DeviceNo, long *ErrorNo);
-long	Get_Connection_Type(short DeviceNo, long *ErrorNo);
-
-/* 16.04.2015
-Important:
-
-If an application program reads the MAC for identifying a special ADwin-system and will refuse operation , if the MAC does not match, then the following issue should be considered :
-
-What if an ADwin-system breaks and needs to be replaced ?
-
-Jaeger Messtechnik will not provide a spare part with an IDENTICAL  MAC address or USB- serialnumber !
-
-The application program has to be prepared somehow, that a replacement with an ADwin-system with a DIFFERENT MAC or USB- serialnumber might be necessary !
-*/
-void	Get_Dev_ID(long *value, short DeviceNo , long *ErrorNo);
-
-
-
-#ifdef __cplusplus
-}
-#endif
-
-#endif //__adwin_v2_h__
diff --git a/unordered/qontrol/FilterPane.qml b/unordered/qontrol/FilterPane.qml
deleted file mode 100644
index 8360545f640e4f08894faae521c9d3f9f9cd149c..0000000000000000000000000000000000000000
--- a/unordered/qontrol/FilterPane.qml
+++ /dev/null
@@ -1,47 +0,0 @@
-import QtQuick 2.4
-import QtQuick.LocalStorage 2.0
-import QtQuick.Controls 2.2
-import "database.js" as DataBase
-
-FilterPaneForm {
-    property int servoId: 0
-
-    signal coeffsChanged(int servoId)
-
-    function updateFromDB() {
-        var filters = DataBase.getFilters()
-        sos.txtFM1.text = filters[0].name
-        sos.txtFM2.text = filters[1].name
-        sos.txtFM3.text = filters[2].name
-        sos.txtFM4.text = filters[3].name
-        sos.txtFM5.text = filters[4].name
-
-        var rps = [sos.rpFM1, sos.rpFM2, sos.rpFM3, sos.rpFM4, sos.rpFM5];
-        for (var i=0; i < DataBase.NUM_SOS; i++) {
-            rps[i].itemAt(0).text = filters[i].gain.toFixed(5)
-            rps[i].itemAt(1).text = filters[i].C1.toFixed(5)
-            rps[i].itemAt(2).text = filters[i].C2.toFixed(5)
-            rps[i].itemAt(3).text = filters[i].C3.toFixed(5)
-            rps[i].itemAt(4).text = filters[i].C4.toFixed(5)
-        }
-    }
-
-    function saveToDB() {
-        var rps = [sos.rpFM1, sos.rpFM2, sos.rpFM3, sos.rpFM4, sos.rpFM5];
-        var names = [sos.txtFM1.text, sos.txtFM2.text, sos.txtFM3.text, sos.txtFM4.text, sos.txtFM5.text];
-        for (var i=0; i < DataBase.NUM_SOS; i++) {
-            DataBase.saveFilter(i+1, names[i],
-                                rps[i].itemAt(0).text,
-                                rps[i].itemAt(1).text,
-                                rps[i].itemAt(2).text,
-                                rps[i].itemAt(3).text,
-                                rps[i].itemAt(4).text);
-        }
-        coeffsChanged(servoId)
-    }
-
-    Component.onCompleted: DataBase.initialiseFilterDB()
-
-    onServoIdChanged: updateFromDB()
-    btnSaveCoeffs.onClicked: saveToDB()
-}
diff --git a/unordered/qontrol/FilterPaneForm.ui.qml b/unordered/qontrol/FilterPaneForm.ui.qml
deleted file mode 100644
index 8a3c6d5615b505adccd36ea71d0bb7fd6cd833ae..0000000000000000000000000000000000000000
--- a/unordered/qontrol/FilterPaneForm.ui.qml
+++ /dev/null
@@ -1,74 +0,0 @@
-import QtQuick 2.4
-import QtQuick.Controls 2.2
-
-Item {
-    id: item1
-    width: 750
-    height: 600
-    property alias sos: sos
-    property alias btnSaveCoeffs: btnSaveCoeffs
-    property alias servoName: servoName.text
-
-    SecondOrderSection {
-        id: sos
-        anchors.top: parent.top
-        anchors.topMargin: 80
-        anchors.right: parent.right
-        anchors.rightMargin: 20
-        anchors.left: parent.left
-        anchors.leftMargin: 20
-    }
-
-    Label {
-        id: servoName
-        text: qsTr("ServoName")
-        font.bold: true
-        anchors.top: parent.top
-        anchors.topMargin: 20
-        anchors.left: parent.left
-        anchors.leftMargin: 20
-        font.pointSize: 12
-    }
-
-    Label {
-        id: label1
-        y: 28
-        text: qsTr("Filter Coefficients")
-        anchors.bottom: servoName.bottom
-        anchors.bottomMargin: 0
-        anchors.left: servoName.right
-        anchors.leftMargin: 10
-        font.pointSize: 12
-    }
-
-    Rectangle {
-        id: rectangle
-        height: 1
-        color: "#888888"
-        anchors.top: servoName.bottom
-        anchors.topMargin: 10
-        anchors.right: label1.right
-        anchors.rightMargin: 0
-        anchors.left: servoName.left
-        anchors.leftMargin: 0
-        border.color: "#00000000"
-    }
-
-    Button {
-        id: btnSaveCoeffs
-        text: qsTr("Update Coeffs")
-        anchors.left: parent.left
-        anchors.leftMargin: 20
-        anchors.top: sos.bottom
-        anchors.topMargin: 20
-    }
-
-    Button {
-        id: button
-        text: qsTr("Load from File")
-        anchors.left: btnSaveCoeffs.right
-        anchors.leftMargin: 6
-        anchors.top: sos.bottom
-        anchors.topMargin: 20
-    }
-}
diff --git a/unordered/qontrol/PaneHeader.qml b/unordered/qontrol/PaneHeader.qml
deleted file mode 100644
index 5a0cd2237846f0804ef8cd0a484c4bdebf4c0a91..0000000000000000000000000000000000000000
--- a/unordered/qontrol/PaneHeader.qml
+++ /dev/null
@@ -1,4 +0,0 @@
-import QtQuick 2.4
-
-PaneHeader {
-}
diff --git a/unordered/qontrol/PaneHeader.ui.qml b/unordered/qontrol/PaneHeader.ui.qml
deleted file mode 100644
index 2cfbdf4a9af516ed96b35585f885af5d615e2cde..0000000000000000000000000000000000000000
--- a/unordered/qontrol/PaneHeader.ui.qml
+++ /dev/null
@@ -1,103 +0,0 @@
-import QtQuick 2.4
-
-Item {
-    id: item1
-    width: 400
-    height: 130
-    property alias txtErrorNo: txtErrorNo
-    property alias txtDeviceNum: txtDeviceNum
-    property alias txtTimeStamp: txtTimeStamp
-    property alias txtCpuLoad: txtCpuLoad
-
-    Image {
-        id: image
-        width: 150
-        height: 70
-        anchors.horizontalCenter: parent.horizontalCenter
-        source: "ilp-logo.png"
-    }
-
-    Row {
-        x: 0
-        anchors.top: image.bottom
-        anchors.topMargin: 30
-        spacing: -8
-
-        Text {
-            id: text1
-            width: 50
-            color: "#555555"
-            text: qsTr("Ramping")
-            horizontalAlignment: Text.AlignLeft
-            rotation: -45
-            font.pixelSize: 12
-        }
-    }
-
-    Grid {
-        id: grid
-        y: 79
-        width: 137
-        height: 48
-        anchors.left: parent.left
-        anchors.leftMargin: 90
-        rows: 4
-        columns: 2
-
-        Text {
-            id: text3
-            color: "#555555"
-            text: qsTr("ADwin Device: ")
-            font.pixelSize: 12
-        }
-
-        Text {
-            id: txtDeviceNum
-            color: "#555555"
-            text: qsTr("Text")
-            font.pixelSize: 12
-        }
-
-        Text {
-            id: text5
-            color: "#555555"
-            text: qsTr("Time Stamp:")
-            font.pixelSize: 12
-        }
-
-        Text {
-            id: txtTimeStamp
-            color: "#555555"
-            text: qsTr("Text")
-            font.pixelSize: 12
-        }
-
-        Text {
-            id: text7
-            color: "#555555"
-            text: qsTr("CPU Load:")
-            font.pixelSize: 12
-        }
-
-        Text {
-            id: txtCpuLoad
-            color: "#555555"
-            text: qsTr("Text")
-            font.pixelSize: 12
-        }
-
-        Text {
-            id: text4
-            color: "#555555"
-            text: qsTr("Last Error:")
-            font.pixelSize: 12
-        }
-
-        Text {
-            id: txtErrorNo
-            color: "#555555"
-            text: qsTr("Text")
-            font.pixelSize: 12
-        }
-    }
-}
diff --git a/unordered/qontrol/SecondOrderSection.qml b/unordered/qontrol/SecondOrderSection.qml
deleted file mode 100644
index c3fbeab23a4fb95a4b9089d7070269acbeceff4e..0000000000000000000000000000000000000000
--- a/unordered/qontrol/SecondOrderSection.qml
+++ /dev/null
@@ -1,182 +0,0 @@
-import QtQuick 2.7
-import QtQuick.Controls 2.2
-import QtQuick.Layouts 1.3
-import QtQuick.Controls.Material 2.2
-
-Pane {
-    width: 650
-    property alias rpFM1: rpFM1
-    property alias txtFM1: txtFM1
-    property alias rpFM2: rpFM2
-    property alias txtFM2: txtFM2
-    property alias rpFM3: rpFM3
-    property alias txtFM3: txtFM3
-    property alias rpFM4: rpFM4
-    property alias txtFM4: txtFM4
-    property alias rpFM5: rpFM5
-    property alias txtFM5: txtFM5
-
-    padding: 0
-    contentHeight: layout.height
-    GridLayout {
-        id: layout
-        rows: 3
-        columns: 6
-        anchors {
-            left: parent.left
-            right: parent.right
-        }
-
-        Label {
-            text: qsTr("Name")
-            horizontalAlignment: Text.AlignHCenter
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        Label {
-            text: qsTr("Gain")
-            horizontalAlignment: Text.AlignHCenter
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        Label {
-            text: qsTr("C1")
-            horizontalAlignment: Text.AlignHCenter
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        Label {
-            text: qsTr("C2")
-            horizontalAlignment: Text.AlignHCenter
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        Label {
-            text: qsTr("C3")
-            horizontalAlignment: Text.AlignHCenter
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        Label {
-            text: qsTr("C4")
-            horizontalAlignment: Text.AlignHCenter
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        // SECOND ORDER SECTION 1
-        TextField {
-            id: txtFM1
-            text: qsTr("FM1")
-            font.pointSize: 10
-            selectByMouse: true
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        Repeater {
-            id: rpFM1
-            model: 5
-
-            TextField {
-                text: qsTr("0.0")
-                horizontalAlignment: Text.AlignRight
-                font.pointSize: 10
-                selectByMouse: true
-                Layout.fillHeight: true; Layout.fillWidth: true
-                validator: DoubleValidator{}
-            }
-        }
-
-        // SECOND ORDER SECTION 2
-        TextField {
-            id: txtFM2
-            text: qsTr("FM2")
-            font.pointSize: 10
-            selectByMouse: true
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        Repeater {
-            id: rpFM2
-            model: 5
-
-            TextField {
-                text: qsTr("0.0")
-                horizontalAlignment: Text.AlignRight
-                font.pointSize: 10
-                selectByMouse: true
-                Layout.fillHeight: true; Layout.fillWidth: true
-                validator: DoubleValidator{}
-            }
-        }
-
-        // SECOND ORDER SECTION 3
-        TextField {
-            id: txtFM3
-            text: qsTr("FM3")
-            font.pointSize: 10
-            selectByMouse: true
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        Repeater {
-            id: rpFM3
-            model: 5
-
-            TextField {
-                text: qsTr("0.0")
-                horizontalAlignment: Text.AlignRight
-                font.pointSize: 10
-                selectByMouse: true
-                Layout.fillHeight: true; Layout.fillWidth: true
-                validator: DoubleValidator{}
-            }
-        }
-
-        // SECOND ORDER SECTION 4
-        TextField {
-            id: txtFM4
-            text: qsTr("FM4")
-            font.pointSize: 10
-            selectByMouse: true
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        Repeater {
-            id: rpFM4
-            model: 5
-
-            TextField {
-                text: qsTr("0.0")
-                horizontalAlignment: Text.AlignRight
-                font.pointSize: 10
-                selectByMouse: true
-                Layout.fillHeight: true; Layout.fillWidth: true
-                validator: DoubleValidator{}
-            }
-        }
-
-        // SECOND ORDER SECTION 5
-        TextField {
-            id: txtFM5
-            text: qsTr("FM5")
-            font.pointSize: 10
-            selectByMouse: true
-            Layout.fillHeight: true; Layout.fillWidth: true
-        }
-
-        Repeater {
-            id: rpFM5
-            model: 5
-
-            TextField {
-                text: qsTr("0.0")
-                horizontalAlignment: Text.AlignRight
-                font.pointSize: 10
-                selectByMouse: true
-                Layout.fillHeight: true; Layout.fillWidth: true
-                validator: DoubleValidator{}
-            }
-        }
-    }
-
-}
diff --git a/unordered/qontrol/ServoList.qml b/unordered/qontrol/ServoList.qml
deleted file mode 100644
index d4df2f659f5fa59e99448b845a41055f26a5f715..0000000000000000000000000000000000000000
--- a/unordered/qontrol/ServoList.qml
+++ /dev/null
@@ -1,110 +0,0 @@
-import QtQuick 2.7
-import QtQuick.LocalStorage 2.0
-import QtQuick.Controls 2.2
-import QtQuick.Controls.Material 2.2
-import LasNQ.ADwin 1.0
-import "database.js" as DataBase
-
-Item {
-    property alias currentItem: listView.currentItem
-    property alias currentIndex: listView.currentIndex
-    property int numServos: 8
-
-    function loadServos() {
-        if (!numServos)
-            return;
-        var servos = DataBase.loadServos()
-        servoModel.clear()
-        for (var j = 1; j <= numServos; j++) {
-            servoModel.append({"servoId": j, "servoName": '(Empty Slot)'})
-        }
-        for (var i = 0; i < servos.length; i++) {
-            servoModel.remove(servos[i].id - 1)
-            servoModel.insert(servos[i].id - 1, {"servoId": servos[i].id, "servoName": servos[i].name})
-        }
-        listView.update()
-        listView.currentIndex = 0
-    }
-
-    onNumServosChanged: {
-        loadServos()
-    }
-
-    ButtonGroup {
-        id: rampGroup1
-    }
-
-    ListModel {
-        id: servoModel
-        ListElement { servoName: 'Dummy Servo'; servoId: 0; servoRamp: false }
-    }
-
-    ListView {
-        id: listView
-        anchors.fill: parent
-        model: servoModel
-        header: Pane {
-            width: parent.width
-            height: paneHeader.height + 2*padding
-            Material.elevation: 0
-            Material.background: "white" //Material.color(Material.Indigo, Material.Shade100)
-
-            z: 10
-            PaneHeader {
-                id: paneHeader
-                width: parent.width
-                txtCpuLoad.text: ADwin.cpuLoad + '%'
-                txtDeviceNum.text: ADwin.deviceNum
-                txtTimeStamp.text: ADwin.seconds
-                txtErrorNo.text: ADwin.errorNo
-                txtErrorNo.color: ADwin.errorNo ? '#ff0000' : '#555555'
-            }
-        }
-        headerPositioning: ListView.OverlayHeader
-        highlight: Rectangle {
-            color: Material.color(Material.Indigo, Material.Shade300)
-            Rectangle {
-                anchors.bottom: parent.bottom
-                width: parent.width
-                height: 1
-                color: Material.color(Material.Indigo, Material.Shade100)
-            }
-        }
-        highlightMoveDuration: 300
-        ScrollIndicator.vertical: ScrollIndicator {}
-        delegate: ItemDelegate {
-            id: servoItem
-            width: parent.width
-            implicitHeight: 50
-            highlighted: index == listView.currentIndex
-            onClicked: listView.currentIndex = index
-            property variant theModel: model
-            contentItem: Rectangle {
-                color: 'transparent'
-                anchors.fill: parent
-                anchors.leftMargin: 5
-                Row {
-                    RadioButton {
-                        width: 40
-                        ButtonGroup.group: rampGroup1
-                        enabled: false
-                        checked: model.servoRamp
-                    }
-                    /*RadioButton {
-                        width: 40
-                        ButtonGroup.group: monitorGroup2
-                    }*/
-                    Label {
-                        color: Material.color(Material.Grey, Material.Shade200)
-                        height: parent.height
-                        verticalAlignment: Text.AlignVCenter
-                        text: model.servoName
-                    }
-                }
-            }
-        }
-    }
-
-    //Component.onCompleted: loadServos()
-}
-
diff --git a/unordered/qontrol/ServoListForm.ui.qml b/unordered/qontrol/ServoListForm.ui.qml
deleted file mode 100644
index e81df83675ce267d46e4739b79cffde7635a60f9..0000000000000000000000000000000000000000
--- a/unordered/qontrol/ServoListForm.ui.qml
+++ /dev/null
@@ -1,9 +0,0 @@
-import QtQuick 2.7
-import QtQuick.Controls 2.0
-import QtQuick.Layouts 1.3
-
-ListView {
-    id: listView
-    ScrollIndicator.vertical: ScrollIndicator {
-    }
-}
diff --git a/unordered/qontrol/ServoPane.qml b/unordered/qontrol/ServoPane.qml
deleted file mode 100644
index f3c40d44a72c160a25444c964df403ea5dda3380..0000000000000000000000000000000000000000
--- a/unordered/qontrol/ServoPane.qml
+++ /dev/null
@@ -1,179 +0,0 @@
-import QtQuick 2.7
-import QtQuick.LocalStorage 2.0
-import QtQuick.Controls 2.2
-import LasNQ.ADwin 1.0
-import "database.js" as DataBase
-
-/*
-#Define FCR_SW_INPUT   1
-#Define FCR_SW_OUTPUT  2
-#Define FCR_SW_RAMP    4
-#Define FCR_SW_LIMIT   8
-#Define FCR_SW_SOS1    16
-#Define FCR_SW_SOS2    32
-#Define FCR_SW_SOS3    64
-#Define FCR_SW_SOS4    128
-#Define FCR_SW_SOS5    256
-*/
-
-ServoPaneForm {
-    property int servoId: 1
-    property int switches: 0
-    //property alias ramping: btnRamp
-
-    enabled: false
-
-    function updateFromDB() {
-        if (servoId == 0) // this happens on initialisation, just do nothing
-            return
-        var myServo = DataBase.getServo()
-        servoName = myServo.name
-        offset = myServo.offset.toFixed(0)
-        gain = myServo.gain.toFixed(2)
-        switches = myServo.switches
-        rampAmpl = myServo.ramp_ampl
-        rampFreq = myServo.ramp_freq
-
-        ADwin.activeServo = servoId
-        setSwitches()
-
-        reloadFilters(false)
-        focus = true
-        forceActiveFocus()
-        // TODO: ultimately, this also needs to get new values from ADwin?
-    }
-
-    function reloadFilters(sendToADwin) {
-        var filters = DataBase.getFilters()
-        lblFM1.text = filters[0].name
-        lblFM2.text = filters[1].name
-        lblFM3.text = filters[2].name
-        lblFM4.text = filters[3].name
-        lblFM5.text = filters[4].name
-
-        if (sendToADwin) {
-            // TODO: this then also needs to send filter values to ADwin
-        }
-    }
-
-    function setSwitches() {
-        btnInput.checked = (switches & 1)
-        btnOutput.checked = (switches & 2)
-        btnOffset.checked = (switches & 8)
-        btnFM1.checked = (switches & 16)
-        btnFM2.checked = (switches & 32)
-        btnFM3.checked = (switches & 64)
-        btnFM4.checked = (switches & 128)
-        btnFM5.checked = (switches & 256)
-        btnRamp.checked = ADwin.hasRamp(servoId)
-    }
-
-    function calcSwitchField(bitvalue, checked) {
-        if (checked)
-            switches = switches | bitvalue
-        else
-            switches = switches & ~bitvalue
-        saveToDB()
-    }
-
-    function updateRamp() {
-        // update values if ramp active,
-        // disable ramp if it is active for current servo, but shouldn't
-        if (btnRamp.checked) {
-            ADwin.setRamp(servoId, rampFreq, rampAmpl)
-        } else if (ADwin.hasRamp(servoId)) {
-            ADwin.setRamp(0, 0, 0)
-        }
-        saveToDB()
-    }
-
-    function saveToDB()
-    {
-        DataBase.saveServo()
-    }
-
-    Connections {
-        target: ADwin
-        onConnected: {
-            servoPane.enabled = true
-            filterPane.enabled = true
-            console.log("Servo enabled")
-            updateFromDB()
-        }
-
-    }
-
-    //Component.onCompleted: updateFromDB()
-    onServoIdChanged: updateFromDB()
-
-    //TODO: not sure why this needs a Connections type, but otherwise I get:
-    // ".onEditingFinished" is not available due to component versioning.
-    // maybe this is QTBUG-59908
-    Connections {
-        target: txtServoName
-        onEditingFinished: saveToDB()
-    }
-    Connections {
-        target: txtGain
-        onEditingFinished: saveToDB()
-    }
-    Connections {
-        target: txtOffset
-        onEditingFinished: saveToDB()
-    }
-
-    lblRampAmpl.text: (rampAmpl * 20).toFixed(1) + "Vpp"
-    lblRampFreq.text: (rampFreq * 0.76).toFixed(1) + "Hz"
-
-    monAux: ADwin.auxMonitor
-    monOutput: ADwin.outMonitor
-    monInput: ADwin.inMonitor
-
-    btnInput.onClicked: calcSwitchField(1, btnInput.checked)
-    btnOutput.onClicked: calcSwitchField(2, btnOutput.checked)
-    btnRamp.onClicked: updateRamp()
-
-    btnOffset.onClicked: calcSwitchField(8, btnOffset.checked)
-
-    btnFM1.onClicked: calcSwitchField(16, btnFM1.checked)
-    btnFM2.onClicked: calcSwitchField(32, btnFM2.checked)
-    btnFM3.onClicked: calcSwitchField(64, btnFM3.checked)
-    btnFM4.onClicked: calcSwitchField(128, btnFM4.checked)
-    btnFM5.onClicked: calcSwitchField(256, btnFM5.checked)
-
-    Connections {
-        target: slRampAmpl
-        onMoved: updateRamp()
-    }
-    Connections {
-        target: slRampFreq
-        onMoved: updateRamp()
-    }
-
-    Keys.onPressed: {
-        if (event.key == Qt.Key_Escape)
-            focus = true
-        else if (event.key == Qt.Key_I) {
-            btnInput.toggle(); btnInput.clicked()
-        }
-        else if (event.key == Qt.Key_O) {
-            btnOutput.toggle(); btnOutput.clicked()
-        }
-        else if (event.key == Qt.Key_Plus) {
-            btnOffset.toggle(); btnOffset.clicked()
-        }
-        else if (event.key == Qt.Key_R) {
-            btnRamp.toggle(); btnRamp.clicked()
-        }
-        else if (event.key == Qt.Key_A) {
-            btnAux.toggle(); btnAux.clicked()
-        }
-    }
-    Keys.onDigit1Pressed: { btnFM1.toggle(); btnFM1.clicked() }
-    Keys.onDigit2Pressed: { btnFM2.toggle(); btnFM2.clicked() }
-    Keys.onDigit3Pressed: { btnFM3.toggle(); btnFM3.clicked() }
-    Keys.onDigit4Pressed: { btnFM4.toggle(); btnFM4.clicked() }
-    Keys.onDigit5Pressed: { btnFM5.toggle(); btnFM5.clicked() }
-    //Keys.onUpPressed: { offset = parseInt(offset) + 100 }
-    //Keys.onDownPressed: { offset = parseInt(offset) - 100 }
-}
diff --git a/unordered/qontrol/ServoPaneForm.ui.qml b/unordered/qontrol/ServoPaneForm.ui.qml
deleted file mode 100644
index 7237452fac1be96aee6f0335088b4b3817b3df28..0000000000000000000000000000000000000000
--- a/unordered/qontrol/ServoPaneForm.ui.qml
+++ /dev/null
@@ -1,412 +0,0 @@
-import QtQuick 2.7
-import QtQuick.Controls 2.2
-import QtQuick.Layouts 1.0
-
-Item {
-    id: item1
-    width: 750
-    height: 600
-    property alias lblRampFreq: lblRampFreq
-    property alias lblRampAmpl: lblRampAmpl
-    property alias lblFM4: lblFM4
-    property alias lblFM3: lblFM3
-    property alias lblFM2: lblFM2
-    property alias lblFM5: lblFM5
-    property alias lblFM1: lblFM1
-    property alias btnOutput: btnOutput
-    property alias btnInput: btnInput
-    property alias btnOffset: btnOffset
-    property alias btnFM5: btnFM5
-    property alias btnFM4: btnFM4
-    property alias btnFM3: btnFM3
-    property alias btnFM2: btnFM2
-    property alias btnFM1: btnFM1
-    property alias btnAux: btnAux
-    property alias btnRamp: btnRamp
-    property alias slRampAmpl: slRampAmpl
-    property alias slRampFreq: slRampFreq
-    property alias txtGain: txtGain
-    property alias txtOffset: txtOffset
-    property alias txtServoName: txtServoName
-    property alias offset: txtOffset.text
-    property alias monInput: txtMonInput.text
-    property alias monOutput: txtMonOutput.text
-    property alias monAux: txtMonAux.text
-    property alias gain: txtGain.text
-    property alias servoName: txtServoName.text
-    property alias rampFreq: slRampFreq.value
-    property alias rampAmpl: slRampAmpl.value
-
-    TextField {
-        id: txtServoName
-        x: 45
-        y: 139
-        width: 177
-        height: 43
-        font.bold: true
-        anchors.top: parent.top
-        anchors.topMargin: 20
-        anchors.left: parent.left
-        anchors.leftMargin: 20
-        selectByMouse: true
-    }
-
-    Rectangle {
-        id: rectangle
-        y: 139
-        height: 2
-        color: "#000000"
-        anchors.right: rectangle2.left
-        anchors.rightMargin: -60
-        anchors.left: parent.left
-        anchors.leftMargin: 25
-        z: -3
-    }
-
-    Rectangle {
-        id: rectangle1
-        x: 572
-        y: 186
-        width: 74
-        height: 2
-        color: "#000000"
-        z: -3
-    }
-
-    Rectangle {
-        id: rectangle2
-        x: 644
-        y: 141
-        width: 2
-        height: 47
-        color: "#000000"
-        z: -3
-    }
-
-    Rectangle {
-        id: rectangle3
-        x: 640
-        y: 135
-        width: 10
-        height: 10
-        color: "#000000"
-        radius: 5
-    }
-
-    RowLayout {
-        y: 116
-        width: 730
-        height: 48
-        spacing: 5
-        anchors.left: parent.left
-        anchors.leftMargin: 20
-
-        Column {
-            Layout.alignment: Qt.AlignLeft | Qt.AlignTop
-
-            Button {
-                id: btnInput
-                width: 68
-                text: qsTr("IN")
-                checkable: true
-            }
-
-            TextField {
-                id: txtMonInput
-                width: 68
-                height: 41
-                text: qsTr("1000")
-                enabled: false
-                horizontalAlignment: Text.AlignRight
-                font.pointSize: 12
-            }
-        }
-
-        Column {
-            Layout.alignment: Qt.AlignLeft | Qt.AlignTop
-
-            Button {
-                id: btnOffset
-                text: qsTr("Offset")
-                highlighted: false
-                checkable: true
-            }
-
-            TextField {
-                id: txtOffset
-                width: 68
-                height: 41
-                text: qsTr("1000")
-                horizontalAlignment: Text.AlignRight
-                font.pointSize: 12
-                selectByMouse: true
-                validator: IntValidator {
-                    top: 32767
-                    bottom: -32768
-                }
-            }
-        }
-
-        Button {
-            id: btnFM1
-            text: qsTr("FM1")
-            Layout.alignment: Qt.AlignLeft | Qt.AlignTop
-            Layout.preferredWidth: 48
-            checkable: true
-            highlighted: false
-        }
-
-        Button {
-            id: btnFM2
-            text: qsTr("FM2")
-            Layout.alignment: Qt.AlignLeft | Qt.AlignTop
-            Layout.preferredWidth: 48
-            checkable: true
-            highlighted: false
-        }
-
-        Button {
-            id: btnFM3
-            text: qsTr("FM3")
-            Layout.alignment: Qt.AlignLeft | Qt.AlignTop
-            Layout.preferredWidth: 48
-            checkable: true
-            highlighted: false
-        }
-
-        Button {
-            id: btnFM4
-            text: qsTr("FM4")
-            Layout.alignment: Qt.AlignLeft | Qt.AlignTop
-            Layout.preferredWidth: 48
-            checkable: true
-            highlighted: false
-        }
-
-        Button {
-            id: btnFM5
-            text: qsTr("FM5")
-            Layout.alignment: Qt.AlignLeft | Qt.AlignTop
-            Layout.preferredWidth: 48
-            checkable: true
-            highlighted: false
-        }
-
-        Column {
-            id: column
-
-            Rectangle {
-                id: rectangle4
-                width: 78
-                height: 47
-                radius: 5
-                border.width: 2
-                border.color: "#000000"
-                Label {
-                    text: 'x'
-                    anchors.verticalCenterOffset: -1
-                    anchors.verticalCenter: parent.verticalCenter
-                    anchors.left: parent.left
-                    anchors.leftMargin: 5
-                    font.pointSize: 12
-                    color: '#888888'
-                }
-
-                TextField {
-                    id: txtGain
-                    text: qsTr("1.0")
-                    anchors.margins: 5
-                    anchors.bottomMargin: -3
-                    anchors.fill: parent
-                    horizontalAlignment: Text.AlignRight
-                    font.pointSize: 12
-                    selectByMouse: true
-                    validator: DoubleValidator {
-                        decimals: 3
-                    }
-                }
-            }
-
-            Button {
-                id: btnAux
-                width: 68
-                text: qsTr("AUX")
-                anchors.horizontalCenter: parent.horizontalCenter
-                checkable: true
-            }
-
-            TextField {
-                id: txtMonAux
-                width: 68
-                height: 41
-                text: qsTr("1000")
-                enabled: false
-                anchors.horizontalCenter: parent.horizontalCenter
-                horizontalAlignment: Text.AlignRight
-                font.pointSize: 12
-            }
-        }
-
-        Column {
-            Layout.alignment: Qt.AlignLeft | Qt.AlignTop
-
-            Button {
-                id: btnOutput
-                width: 68
-                text: qsTr("OUT")
-                checkable: true
-            }
-
-            TextField {
-                id: txtMonOutput
-                width: 68
-                height: 41
-                text: qsTr("1000")
-                enabled: false
-                horizontalAlignment: Text.AlignRight
-                font.pointSize: 12
-            }
-        }
-    }
-
-    Label {
-        id: lblFM1
-        x: 226
-        y: 101
-        text: qsTr("Notch 2.1kHz")
-        verticalAlignment: Text.AlignBottom
-        transformOrigin: Item.TopLeft
-        rotation: -45
-    }
-
-    Label {
-        id: lblFM5
-        x: 508
-        y: 101
-        text: qsTr("LP 10kHz")
-        rotation: -45
-        verticalAlignment: Text.AlignBottom
-        transformOrigin: Item.TopLeft
-    }
-
-    Label {
-        id: lblFM2
-        x: 298
-        y: 101
-        text: qsTr("Notch 3kHz")
-        rotation: -45
-        verticalAlignment: Text.AlignBottom
-        transformOrigin: Item.TopLeft
-    }
-
-    Label {
-        id: lblFM3
-        x: 364
-        y: 101
-        text: qsTr("Int 100Hz")
-        rotation: -45
-        verticalAlignment: Text.AlignBottom
-        transformOrigin: Item.TopLeft
-    }
-
-    Label {
-        id: lblFM4
-        x: 436
-        y: 101
-        text: qsTr("Int 1kHz")
-        rotation: -45
-        verticalAlignment: Text.AlignBottom
-        transformOrigin: Item.TopLeft
-    }
-
-    GroupBox {
-        id: groupBox
-        x: 8
-        y: 295
-        font.italic: false
-        font.bold: false
-        title: qsTr("Ramp Generator")
-        background: Rectangle {
-            color: 'transparent'
-        }
-
-        RowLayout {
-            spacing: 10
-
-            Button {
-                id: btnRamp
-                width: 68
-                text: qsTr("ON")
-                Layout.alignment: Qt.AlignLeft | Qt.AlignTop
-                checkable: true
-            }
-
-            Column {
-
-                Slider {
-                    id: slRampFreq
-                    from: 1
-                    stepSize: 1
-                    to: 255
-                    value: 127
-
-                    Label {
-                        id: label
-                        y: 0
-                        text: qsTr("Frequency")
-                        anchors.left: parent.left
-                        anchors.leftMargin: 0
-                    }
-
-                    Label {
-                        id: lblRampFreq
-                        text: "x Hz"
-                        anchors.right: parent.right
-                        anchors.rightMargin: 0
-                    }
-                }
-
-                Slider {
-                    id: slRampAmpl
-                    value: 0.5
-
-                    Label {
-                        id: label1
-                        x: 0
-                        y: 0
-                        text: qsTr("Amplitude")
-                    }
-
-                    Label {
-                        id: lblRampAmpl
-                        text: "x Vpp"
-                        anchors.right: parent.right
-                        anchors.rightMargin: 0
-                    }
-                }
-            }
-        }
-    }
-
-    Text {
-        id: text1
-        y: 548
-        text: qsTr("Servo ID:")
-        anchors.left: parent.left
-        anchors.leftMargin: 20
-        anchors.bottom: parent.bottom
-        anchors.bottomMargin: 20
-        font.pixelSize: 12
-    }
-
-    Text {
-        id: txtServoId
-        y: 565
-        text: servoId
-        anchors.bottom: parent.bottom
-        anchors.bottomMargin: 20
-        anchors.left: text1.right
-        anchors.leftMargin: 6
-        font.pixelSize: 12
-    }
-}
diff --git a/unordered/qontrol/TODO.txt b/unordered/qontrol/TODO.txt
deleted file mode 100644
index c54d89ccedbe4fa387478ae6ddc11ee070e4d823..0000000000000000000000000000000000000000
--- a/unordered/qontrol/TODO.txt
+++ /dev/null
@@ -1,23 +0,0 @@
-[TODO]
-* documentation, documentation, documentation...
-* load filter coefficients from file
-* check which functionality is actually implemented
-    * ramp on/off for indiv. channels
-    * ramp freq/ampl
-    * input/output enable
-    * aux input addition
-    * offset
-    * in/out/aux monitors
-    * gain
-    * filter coefficients
-* should we load coefficients from ADwin upon start? or always from DB?
-  how/when should values be written to ADwin on startup?
-* ramping & monitor:
-    - always output ramp on monitor if active
-    - error from selected channel
-
-
-[ISSUES]
-* sometimes, ramp enable/disable doesn't propagate to side drawer radio button
-  main.qml -> SwipeView -> ServoPane, btnRamp.onClicked
-
diff --git a/unordered/qontrol/adwin.cpp b/unordered/qontrol/adwin.cpp
deleted file mode 100644
index 525910b2e0912298a92969b2d11a8bba1b7603f0..0000000000000000000000000000000000000000
--- a/unordered/qontrol/adwin.cpp
+++ /dev/null
@@ -1,137 +0,0 @@
-#include "adwin.h"
-// define NO_ADMIN_MODE to test code without an actual ADwin system connected
-#ifndef NO_ADWIN_MODE
-#include "ADwin_V2.h"
-#endif //NO_ADWIN_MODE
-
-#define PAR_TIMER  1
-#define PAR_FBCR   2
-#define PAR_RCR    3
-#define PAR_ACTIVE 4
-#define PAR_FCR_1  11
-
-#define FPAR_RAMP_AMPL  1
-
-#define DATA_FILTER_COEFFS 1
-#define DATA_ACTIVE 2
-
-ADwinInterface::ADwinInterface(QObject *parent)
-    : QObject(parent), m_deviceNum(0), m_booted(false),
-      m_seconds(0), m_cpuLoad(0), m_servoCount(0), m_errorNo(0),
-      m_activeServo(0)
-{
-}
-
-/***
- * loadFirmware
- * load the specified firmware into the ADwin hardware, which
- * must be booted (e.g. via the ADBasic program) beforehand.
- * Firmware is automatically started afterwards.
- */
-bool ADwinInterface::loadFirmware(int deviceNum, QString firmware)
-{
-#ifndef NO_ADWIN_MODE
-    // boot ADwin should happen in ADwin software for now
-    // load servo firmware (stop/clean process first)
-    long err;
-
-    // make sure ADwin system is booted
-    if (Test_Version(deviceNum, &err)) {
-        setErrorNo(err);
-        return false;
-    }
-
-    // load firmware
-    QByteArray ba = firmware.toLocal8Bit();
-    Stop_Process(1, deviceNum, &err);
-    Load_Process(ba.data(), deviceNum, &err);
-    if (err) {
-        setErrorNo(err);
-        return false;
-    }
-    Start_Process(1, deviceNum, &err);
-    if (err) {
-        setErrorNo(err);
-        return false;
-    }
-#endif //NO_ADWIN_MODE
-
-    m_deviceNum = deviceNum;
-    m_booted = true;
-    m_seconds = 0;
-    emit connected();
-    emit deviceNumChanged(m_deviceNum);
-    setServoCount(8); //TODO: set this to the actual servo count, get this via a PAR
-
-    return true;
-}
-
-/***
- * runWorker
- * this should be called periodically to update values in the GUI,
- * e.g. the seconds timer, the cpu load, and monitor values.
- */
-bool ADwinInterface::runWorker()
-{
-    long err;
-    long mon[3] = {0x8000,0x8001,0x8002};
-
-#ifndef NO_ADWIN_MODE
-    setSeconds(Get_Par(1, m_deviceNum, &err));
-    setCpuLoad(Workload(0, m_deviceNum, &err));
-
-    Set_Par(PAR_ACTIVE, m_activeServo, m_deviceNum, &err);
-    GetData_Long(DATA_ACTIVE, mon, 1, 3, m_deviceNum, &err);
-#else
-    // just some dummy values
-    setSeconds(m_seconds+1);
-    setCpuLoad(85);
-#endif //NO_ADWIN_MODE
-    for (int ii=0; ii < 3; ++ii)
-        m_monitor[ii] = mon[ii] - 0x8000;
-    emit inMonitorChanged(m_monitor[0]);
-    emit auxMonitorChanged(m_monitor[1]);
-    emit outMonitorChanged(m_monitor[2]);
-    return true;
-}
-
-/***
- * setRamp
- * Enable ramp at specified servo (will disable ramping at previous
- * servo). Set servo=0 to disable ramping.
- */
-void ADwinInterface::setRamp(int servo, int freq, double ampl)
-{
-    long rcr = 0;
-    long err = 0;
-    rcr = (servo & 0xff) + ((freq & 0xff) << 8);
-#ifndef NO_ADWIN_MODE
-    Set_Par(PAR_RCR, rcr, m_deviceNum, &err);
-    Set_FPar_Double(FPAR_RAMP_AMPL, ampl, m_deviceNum, &err);
-#endif
-}
-
-/***
- * hasRamp
- * check whether a servo is ramping
- */
-bool ADwinInterface::hasRamp(int servo)
-{
-    long err = 0;
-#ifndef NO_ADWIN_MODE
-    return ((Get_Par(PAR_RCR, m_deviceNum, &err) & 0xff) == servo);
-#else
-    return false;
-#endif
-}
-
-
-QObject *adwin_interface_provider(QQmlEngine *engine, QJSEngine *scriptEngine)
-{
-    Q_UNUSED(engine)
-    Q_UNUSED(scriptEngine)
-
-    ADwinInterface *adwin = new ADwinInterface();
-    return adwin;
-}
-
diff --git a/unordered/qontrol/adwin.h b/unordered/qontrol/adwin.h
deleted file mode 100644
index 652e0bdcc2a5a7b9e013c7712f9361dfdd13fcd9..0000000000000000000000000000000000000000
--- a/unordered/qontrol/adwin.h
+++ /dev/null
@@ -1,86 +0,0 @@
-#ifndef ADWIN_H
-#define ADWIN_H
-
-#include <QObject>
-#include <QQmlEngine>
-#include <QJSEngine>
-
-class ADwinInterface : public QObject
-{
-    Q_OBJECT
-    Q_PROPERTY(int deviceNum READ deviceNum NOTIFY deviceNumChanged)
-    Q_PROPERTY(int servoCount READ servoCount NOTIFY servoCountChanged)
-    Q_PROPERTY(int seconds READ seconds NOTIFY secondsChanged)
-    Q_PROPERTY(int cpuLoad READ cpuLoad NOTIFY cpuLoadChanged)
-    Q_PROPERTY(int errorNo READ errorNo NOTIFY errorNoChanged)
-    Q_PROPERTY(int inMonitor READ inMonitor NOTIFY inMonitorChanged)
-    Q_PROPERTY(int outMonitor READ outMonitor NOTIFY outMonitorChanged)
-    Q_PROPERTY(int auxMonitor READ auxMonitor NOTIFY auxMonitorChanged)
-    Q_PROPERTY(int activeServo READ activeServo WRITE setActiveServo)
-
-public:
-    explicit ADwinInterface(QObject *parent = nullptr);
-    ~ADwinInterface() {}
-
-    Q_INVOKABLE bool loadFirmware(int deviceNum, QString firmware);
-    Q_INVOKABLE bool runWorker(); // call this often to get new values
-
-    //Q_INVOKABLE void setMonitor(int monitor, int servo);
-    //Q_INVOKABLE int getMonitor(int monitor);
-
-    //Q_INVOKABLE void setServo(int servo, int fcr);
-    //Q_INVOKABLE int getServo(int servo);
-
-    //Q_INVOKABLE void setCoeffs(int servo, QVariantList coeffs);
-    //Q_INVOKABLE QVariantList getCoeffs(int servo);
-
-    Q_INVOKABLE void setRamp(int servo, int freq, double ampl);
-    Q_INVOKABLE bool hasRamp(int servo);
-
-    int deviceNum() const { return m_deviceNum; }
-
-    int servoCount() const { return m_servoCount; }
-    void setServoCount(int val) { m_servoCount = val; emit servoCountChanged(val); }
-
-    int seconds() const { return m_seconds; }
-    void setSeconds(int val) { m_seconds = val; emit secondsChanged(val); }
-
-    int cpuLoad() const { return m_cpuLoad; }
-    void setCpuLoad(int val) { m_cpuLoad = val; emit cpuLoadChanged(val); }
-
-    int errorNo() const { return m_errorNo; }
-    void setErrorNo(int val) { m_errorNo = val; emit errorNoChanged(val); }
-
-    int inMonitor() const { return m_monitor[0]; }
-    int auxMonitor() const { return m_monitor[1]; }
-    int outMonitor() const { return m_monitor[2]; }
-    int activeServo() const { return m_activeServo; }
-    void setActiveServo(int val) { m_activeServo = val; }
-
-signals:
-    void deviceNumChanged(int newValue);
-    void servoCountChanged(int newValue);
-    void secondsChanged(int newValue);
-    void cpuLoadChanged(int newValue);
-    void errorNoChanged(int newValue);
-    void inMonitorChanged(int newValue);
-    void auxMonitorChanged(int newValue);
-    void outMonitorChanged(int newValue);
-    void connected();
-
-private:
-    int m_deviceNum;
-    bool m_booted;
-
-    int m_seconds;
-    int m_cpuLoad;
-    int m_servoCount;
-    long m_errorNo;
-
-    int m_monitor[3];
-    int m_activeServo;
-};
-
-QObject *adwin_interface_provider(QQmlEngine *engine, QJSEngine *scriptEngine);
-
-#endif // SINGLETONTYPEEXAMPLE_H
diff --git a/unordered/qontrol/database.js b/unordered/qontrol/database.js
deleted file mode 100644
index 33f5b020403a7e7530a469f6b1241846c7d93153..0000000000000000000000000000000000000000
--- a/unordered/qontrol/database.js
+++ /dev/null
@@ -1,126 +0,0 @@
-var db = LocalStorage.openDatabaseSync("ServoController", "", "ServoDataBase", 1000000);
-
-var NUM_SOS = 5;
-/***
-* getServo
-* retrieve settings for specific servo,
-* identified via a
-*/
-function getServo() {
-    console.log("Get Servo..."+servoId);
-
-    var servo = Object({'name': '(Empty Slot)',
-                        'gain': 1.0,
-                        'offset': 0.0,
-                        'switches': 0,
-                        'ramp_freq': 10.0,
-                        'ramp_ampl': 1.0
-                       });
-    db.transaction(
-        function(tx) {
-            var result = tx.executeSql('SELECT * FROM Servos WHERE id=?', servoId);
-
-            if (result.rows.length == 1)
-                servo = result.rows.item(0);
-            console.log(servo.name);
-        }
-    )
-
-    return servo;
-}
-
-function saveServo() {
-    console.log("Saving Servo..."+servoId);
-
-    db.transaction(
-        function(tx) {
-            tx.executeSql('INSERT OR REPLACE INTO Servos(id, name, switches, offset, gain, ramp_freq, ramp_ampl) \
-                           VALUES(?, ?, ?, ?, ?, ?, ?)',
-                          [servoId, servoName, switches, offset,
-                           gain, rampFreq, rampAmpl])
-        }
-    )
-}
-
-function loadServos() {
-    var servos = [];
-    var result;
-    db.transaction(
-        function(tx) {
-            tx.executeSql("CREATE TABLE IF NOT EXISTS Servos( \
-                                                id INT PRIMARY KEY, \
-                                                name TEXT, \
-                                                switches INT, \
-                                                offset REAL, \
-                                                gain REAL, \
-                                                ramp_freq REAL, \
-                                                ramp_ampl REAL)");
-
-            result = tx.executeSql("SELECT id, name FROM Servos ORDER BY id ASC");
-            for (var i = 0; i < result.rows.length; i++)
-                servos.push(result.rows.item(i));
-        }
-    )
-    return servos;
-}
-
-
-
-function initialiseFilterDB() {
-    console.log('Filter init')
-    db.transaction(
-        function(tx) {
-            tx.executeSql("CREATE TABLE IF NOT EXISTS Filters( \
-                            slot INT, \
-                            servo_id INT, \
-                            name TEXT, \
-                            gain REAL, \
-                            C1 REAL, \
-                            C2 REAL, \
-                            C3 REAL, \
-                            C4 REAL, \
-                            CONSTRAINT fm_unique UNIQUE(servo_id, slot))");
-        }
-    )
-}
-
-function getFilters() {
-    console.log("Getting Filters for Servo..."+servoId);
-
-    var filter_template = Object({'name': '(empty)',
-                                  'servo_id': servoId,
-                                  'slot': 0,
-                                  'gain': 1.0,
-                                  'C1': 0.0, 'C2': 0.0, 'C3': 0.0, 'C4': 0.0
-                                 });
-    var filters = [];
-    for (var i = 1; i <= NUM_SOS; i++) {
-        var flt = Object.create(filter_template)
-        flt.slot = i
-        filters.push(flt)
-    }
-    db.transaction(
-        function(tx) {
-            var result = tx.executeSql('SELECT * FROM Filters WHERE servo_id=? ORDER BY slot ASC', servoId);
-            for (var i = 0; i < result.rows.length; i++) {
-                filters[result.rows.item(i).slot-1] = result.rows.item(i);
-            }
-        }
-    )
-
-    return filters;
-}
-
-function saveFilter(slot, name, gain, C1, C2, C3, C4) {
-    console.log("Saving filter %1, servo %2...".arg(slot).arg(servoId));
-
-    db.transaction(
-        function(tx) {
-            var result = tx.executeSql('INSERT OR REPLACE INTO Filters \
-                                            (name, servo_id, slot, gain, C1, C2, C3, C4) \
-                                        VALUES \
-                                            (?, ?, ?, ?, ?, ?, ?, ?)',
-                                       [name, servoId, slot, gain, C1, C2, C3, C4]);
-        }
-    )
-}
diff --git a/unordered/qontrol/ilp-logo.png b/unordered/qontrol/ilp-logo.png
deleted file mode 100644
index f5a43f812e476258134322fb6727c3b6bba93a9e..0000000000000000000000000000000000000000
Binary files a/unordered/qontrol/ilp-logo.png and /dev/null differ
diff --git a/unordered/qontrol/main.cpp b/unordered/qontrol/main.cpp
deleted file mode 100644
index 88240e4b0cf416e1c41571e73cbc93f236a83e4f..0000000000000000000000000000000000000000
--- a/unordered/qontrol/main.cpp
+++ /dev/null
@@ -1,17 +0,0 @@
-#include <QGuiApplication>
-#include <QQmlApplicationEngine>
-#include "adwin.h"
-
-int main(int argc, char *argv[])
-{
-    QCoreApplication::setAttribute(Qt::AA_EnableHighDpiScaling);
-    QGuiApplication app(argc, argv);
-
-    QQmlApplicationEngine engine;
-    qmlRegisterSingletonType<ADwinInterface>("LasNQ.ADwin", 1, 0, "ADwin",adwin_interface_provider);
-    engine.load(QUrl(QLatin1String("qrc:/main.qml")));
-    if (engine.rootObjects().isEmpty())
-        return -1;
-
-    return app.exec();
-}
diff --git a/unordered/qontrol/main.qml b/unordered/qontrol/main.qml
deleted file mode 100644
index 7cc989cb7743a029be4aa41ec5e4a04dfe14ad1f..0000000000000000000000000000000000000000
--- a/unordered/qontrol/main.qml
+++ /dev/null
@@ -1,88 +0,0 @@
-import QtQuick 2.7
-import QtQuick.Controls 2.2
-import QtQuick.Layouts 1.3
-import QtQuick.Controls.Material 2.2
-import LasNQ.ADwin 1.0
-
-ApplicationWindow {
-    id: window
-    visible: true
-    width: 1000
-    height: 600
-    title: qsTr("Servo Controller")
-    minimumWidth: 1000
-
-    Material.theme: Material.Light
-    Material.accent: '#CB0B31'
-
-    Drawer {
-        id: drawer
-        width: 250
-        height: window.height
-        y: 0; z: 2
-        Material.elevation: 5
-        modal: false
-        visible: true
-        position: 1
-        padding: 0
-        interactive: false
-        Pane {
-            anchors.margins: 0
-            anchors.fill: parent
-            padding: 0
-            Material.background: Material.Indigo
-
-            ServoList {
-                id: servoList
-                numServos: ADwin.servoCount
-                anchors.fill: parent
-            }
-        }
-
-    }
-
-    SwipeView {
-        id: swipe
-        currentIndex: page_indicator.currentIndex
-        anchors.leftMargin: drawer.width
-        anchors.fill: parent
-
-        ServoPane {
-            id: servoPane
-            servoId: servoList.currentItem.theModel.servoId
-            onServoNameChanged: servoList.currentItem.theModel.servoName = servoName
-            btnRamp.onClicked: servoList.currentItem.theModel.servoRamp = btnRamp.checked
-        }
-
-        FilterPane {
-            id: filterPane
-            servoName: servoList.currentItem.theModel.servoName
-            servoId: servoList.currentItem.theModel.servoId
-            onCoeffsChanged: servoPane.reloadFilters(true)
-        }
-    }
-
-    PageIndicator {
-        id: page_indicator
-        count: swipe.count
-        currentIndex: swipe.currentIndex
-        interactive: true
-
-        anchors.bottom: swipe.bottom
-        anchors.horizontalCenter: swipe.horizontalCenter
-    }
-
-    Timer {
-        id: updateTimer
-        interval: 200
-        repeat: true
-        running: false
-        onTriggered: ADwin.runWorker()
-    }
-
-    Component.onCompleted: ADwin.loadFirmware(1, "c:\\Users\\adwin\\documents\\adwin\\adwin-control\\adwin-control.tc1")
-    Connections {
-        target: ADwin
-        onConnected: updateTimer.start()
-    }
-}
diff --git a/unordered/qontrol/qml.qrc b/unordered/qontrol/qml.qrc
deleted file mode 100644
index aeec619e2af2e19dfe35839726669fca59a23a5c..0000000000000000000000000000000000000000
--- a/unordered/qontrol/qml.qrc
+++ /dev/null
@@ -1,15 +0,0 @@
-<RCC>
-    <qresource prefix="/">
-        <file>main.qml</file>
-        <file>qtquickcontrols2.conf</file>
-        <file>PaneHeader.ui.qml</file>
-        <file>ServoList.qml</file>
-        <file>ServoPaneForm.ui.qml</file>
-        <file>ServoPane.qml</file>
-        <file>FilterPane.qml</file>
-        <file>FilterPaneForm.ui.qml</file>
-        <file>SecondOrderSection.qml</file>
-        <file>database.js</file>
-        <file>ilp-logo.png</file>
-    </qresource>
-</RCC>
diff --git a/unordered/qontrol/qontrol.pro b/unordered/qontrol/qontrol.pro
deleted file mode 100644
index d0f9f6168a52d7bb5297ab4bcda3715271c1001d..0000000000000000000000000000000000000000
--- a/unordered/qontrol/qontrol.pro
+++ /dev/null
@@ -1,45 +0,0 @@
-QT += qml quick
-
-CONFIG += c++11
-
-SOURCES += main.cpp \
-    adwin.cpp
-
-RESOURCES += qml.qrc
-
-# Additional import path used to resolve QML modules in Qt Creator's code model
-QML_IMPORT_PATH =
-
-# Additional import path used to resolve QML modules just for Qt Quick Designer
-QML_DESIGNER_IMPORT_PATH =
-
-# The following define makes your compiler emit warnings if you use
-# any feature of Qt which as been marked deprecated (the exact warnings
-# depend on your compiler). Please consult the documentation of the
-# deprecated API in order to know how to port your code away from it.
-DEFINES += QT_DEPRECATED_WARNINGS
-
-# Sebastian: define this to build without the actual ADwin library, e.g. for
-# builds on Mac or when the ADwin system is not reachable from the test computer
-DEFINES += NO_ADWIN_MODE
-
-# You can also make your code fail to compile if you use deprecated APIs.
-# In order to do so, uncomment the following line.
-# You can also select to disable deprecated APIs only up to a certain version of Qt.
-#DEFINES += QT_DISABLE_DEPRECATED_BEFORE=0x060000    # disables all the APIs deprecated before Qt 6.0.0
-
-# Default rules for deployment.
-qnx: target.path = /tmp/$${TARGET}/bin
-else: unix:!android: target.path = /opt/$${TARGET}/bin
-!isEmpty(target.path): INSTALLS += target
-
-HEADERS += \
-    adwin.h
-
-!contains(DEFINES, "NO_ADWIN_MODE") {
-    HEADERS += ADwin_V2.h
-    SOURCES += ADwin_V2.cpp
-}
-
-DISTFILES += \
-    TODO.txt
diff --git a/unordered/qontrol/qt-logo.png b/unordered/qontrol/qt-logo.png
deleted file mode 100644
index ecbff0ca36763f5ec81557e8f566f443b285ffb7..0000000000000000000000000000000000000000
Binary files a/unordered/qontrol/qt-logo.png and /dev/null differ
diff --git a/unordered/qontrol/qtquickcontrols2.conf b/unordered/qontrol/qtquickcontrols2.conf
deleted file mode 100644
index 9d7133fb045f8fa4db587d0a90e0bee0bfe15765..0000000000000000000000000000000000000000
--- a/unordered/qontrol/qtquickcontrols2.conf
+++ /dev/null
@@ -1,8 +0,0 @@
-[Controls]
-Style=Material
-
-[Material]
-Theme=Light
-
-[Universal]
-Theme=Light