<?xml version="1.0" encoding="UTF-8"?>
<quiz>
<!-- question: 0  -->
  <question type="category">
    <category>
      <text>top/4 Elektrizität</text>
    </category>
    <info format="markdown">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>top/4 Elektrizität/Coulomb-Kraft</text>
    </category>
    <info format="moodle_auto_format">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 8030  -->
  <question type="formulas">
    <name>
      <text>Coulomb-Kraft auf Kupfersulfat-Ionen</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>In einer verdünnten, wässrigen Lösung von Kupfersulfat habe ein Cu<sup>2+</sup> Ion den Abstand \( {r}\,\mathrm{nm} \) von einem SO<sub>4</sub><sup>2-</sup> Ion.</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Die Antwort ist richtig.</text>
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      <text>Die Antwort ist teilweise richtig.</text>
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      <text>Die Antwort ist falsch.</text>
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    <shownumcorrect/>
<varsrandom><text>r = {21:89:2};</text>
</varsrandom>
<varsglobal><text>### General initialization

kC = 8.988e9;
qe = 1.602e-19;


### Generate numbers

origSol = kC * (2*qe)**2 / (r * 1e-9)**2;</text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>origSol = kC * (2*qe)**2 / (r * 1e-9)**2;

nSigFig = 2;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors or wrong calculation
critMantRnd = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantErr = ( abs( mantAns - mantSolSFA/4 ) < 1.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.7*critMantRnd, 0.5*critMantErr );
grade = ( critMant > 0 ) ? 0.3*critExp + 0.1*critSigFig + 0.6*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>N</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>Mit welcher Kraft ziehen sich diese zwei Ionen an?</p>
<p>&emsp;{_0}{_u}&emsp; (Angabe mit Einheit)</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
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<text></text>
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<text></text>
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</answers>
  </question>

<!-- question: 8031  -->
  <question type="formulas">
    <name>
      <text>Coulomb'sches Gesetz: Abstand berechnen</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Dieses Aufgabe ist rein akademisch in dem Sinne, dass sie eine Rechenübung darstellt und keinen Bezug zu realistischen Grössenangaben hat.</p>
<p>Berechnen Sie die gesuchte Grösse und geben Sie sie mit richtiger Syntax samt Einheit an.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>q1Mant = {100.1:1000:0.2};
q1ExpJ = {0:4};

q2Mant = {100.1:1000:0.2};
q2ExpJ = {0:4};

FCMant = {100.1:1000:0.2};
FCExpJ = {4:10};</text>
</varsrandom>
<varsglobal><text><![CDATA[Prefixes = ["p", "n", "µ", "m", "c", "d", "da", "h", "k", "M", "G", "T"];
Exponents = [-12, -9, -6,-3, -2, -1, 1, 2, 3, 6, 9, 12]; 

kC = 8.988e9;

q1Val = q1Mant * 10**(Exponents[q1ExpJ]);
q1Str = join(" " , "\\(" , str(q1Mant) , "\\,\\mathrm{" , Prefixes[q1ExpJ] , "C}\\)" );

q2Val = q2Mant * 10**(Exponents[q2ExpJ]);
q2Str = join(" " , "\\(" , str(q2Mant) , "\\,\\mathrm{" , Prefixes[q2ExpJ] , "C}\\)" );

FCVal = FCMant * 10**(Exponents[FCExpJ]);
FCStr = join(" " , "\\(" , str(FCMant) , "\\,\\mathrm{" , Prefixes[FCExpJ] , "N}\\)" );

sol = sigfig( sqrt( kC * q1Val * q2Val / FCVal ) , 4);]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
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 <placeholder>
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 <answermark>
  <text>3</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Fully correct solution
crit1 = 1 * ( abs(origAns - sol)/sol <= 0.0030000001 );

# Reduced points for wrong precision
crit2 = 0.8 * ( abs(origAns - sol)/sol <= 0.030000001 );

# Half the points for wrong order of magnitude or precision
mantAns = origAns / ( 10**(floor( log10(origAns)) ));
mantSol =  sol / ( 10**(floor( log10(sol)) ));
crit3 = 0.5 * ( abs(mantAns - mantSol)/mantSol <= 0.0300000001 );

grade = max(crit1,crit2,crit3);]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>m</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Welchen Abstand haben zwei Ladungen von {q1Str} und {q2Str}, wenn sie sich mit einer Coulomb-Kraft von {FCStr} anziehen?</p>
<p>&emsp;{_0}{_u}</p><br>]]></text>
 </subqtext>
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<text></text>
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</answers>
  </question>

<!-- question: 8032  -->
  <question type="formulas">
    <name>
      <text>Coulomb'sches Gesetz: Kraft berechnen</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Dieses Aufgabe ist rein akademisch in dem Sinne, dass sie eine Rechenübung darstellt und keinen Bezug zu realistischen Grössenangaben hat.</p>
<p>Berechnen Sie die gesuchte Grösse und geben Sie sie mit richtiger Syntax samt Einheit an.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>q1Mant = {100.1:1000:0.2};
q1ExpJ = {0:4};

q2Mant = {100.1:1000:0.2};
q2ExpJ = {0:4};

rMant = {100.1:1000:0.2};
rExpJ = {2:6};</text>
</varsrandom>
<varsglobal><text><![CDATA[Prefixes = ["p", "n", "µ", "m", "c", "d", "da", "h", "k", "M", "G", "T"];
Exponents = [-12, -9, -6,-3, -2, -1, 1, 2, 3, 6, 9, 12]; 

kC = 8.988e9;

q1Val = q1Mant * 10**(Exponents[q1ExpJ]);
q1Str = join(" " , "\\(" , str(q1Mant) , "\\,\\mathrm{" , Prefixes[q1ExpJ] , "C}\\)" );

q2Val = q2Mant * 10**(Exponents[q2ExpJ]);
q2Str = join(" " , "\\(" , str(q2Mant) , "\\,\\mathrm{" , Prefixes[q2ExpJ] , "C}\\)" );

rVal = rMant * 10**(Exponents[rExpJ]);
rStr = join(" " , "\\(" , str(rMant) , "\\,\\mathrm{" , Prefixes[rExpJ] , "m}\\)" );

sol = sigfig( kC * q1Val * q2Val * rVal**(-2) , 4);]]></text>
</varsglobal>
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<answers>
 <partindex>
  <text>0</text>
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 <placeholder>
  <text></text>
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  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 0.001]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>N</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Wie gross ist die Coulomb-Kraft auf eine Ladung von {q1Str}, wenn sie sich in einem Abstand von {rStr} von einer anderen Ladung von {q2Str} befindet?</p><p dir="ltr" style="text-align: left;">{_0}{_u}</p><br>]]></text>
 </subqtext>
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<text></text>
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</answers>
  </question>

<!-- question: 8033  -->
  <question type="formulas">
    <name>
      <text>Coulomb'sches Gesetz: Ladung berechnen</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Dieses Aufgabe ist rein akademisch in dem Sinne, dass sie eine Rechenübung darstellt und keinen Bezug zu realistischen Grössenangaben hat.</p><p dir="ltr" style="text-align: left;">Berechnen Sie die gesuchte Grösse und geben Sie sie mit richtiger Syntax samt Einheit an.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
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    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
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    <shownumcorrect/>
<varsrandom><text>q1Mant = {100.1:1000:0.2};
q1ExpJ = {0:4};

FCMant = {100.1:1000:0.2};
FCExpJ = {4:10};

rMant = {100.1:1000:0.2};
rExpJ = {2:6};</text>
</varsrandom>
<varsglobal><text><![CDATA[Prefixes = ["p", "n", "µ", "m", "c", "d", "da", "h", "k", "M", "G", "T"];
Exponents = [-12, -9, -6,-3, -2, -1, 1, 2, 3, 6, 9, 12]; 

kC = 8.988e9;

q1Val = q1Mant * 10**(Exponents[q1ExpJ]);
q1Str = join(" " , "\\(" , str(q1Mant) , "\\,\\mathrm{" , Prefixes[q1ExpJ] , "C}\\)" );

FCVal = FCMant * 10**(Exponents[FCExpJ]);
FCStr = join(" " , "\\(" , str(FCMant) , "\\,\\mathrm{" , Prefixes[FCExpJ] , "N}\\)" );

rVal = rMant * 10**(Exponents[rExpJ]);
rStr = join(" " , "\\(" , str(rMant) , "\\,\\mathrm{" , Prefixes[rExpJ] , "m}\\)" );

sol = sigfig( FCVal / kC / q1Val * rVal**(2) , 4);]]></text>
</varsglobal>
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  <text>3</text>
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  <text>0</text>
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 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 0.001]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>C</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Welchen Betrag hat eine Ladung, wenn auf sie in einem Abstand von {rStr} von einer anderen Ladung von {q1Str} eine Coulomb-Kraft von {FCStr} wirkt?</p><p dir="ltr" style="text-align: left;">{_0}{_u}</p><br>]]></text>
 </subqtext>
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</answers>
  </question>

<!-- question: 8034  -->
  <question type="formulas">
    <name>
      <text>Ladung eines Atomkerns</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Berechnen Sie die Ladung eines {strElement}-Atomkerns.</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Die Antwort ist richtig.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Die Antwort ist teilweise richtig.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Die Antwort ist falsch.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jElement = {0:12};</text>
</varsrandom>
<varsglobal><text><![CDATA[### General initialization

strElements = ["Lithium", "Beryllium", "Bor", "Kohlenstoff", "Stickstoff", "Sauerstoff", "Fluor", "Neon", "Natrium", "Magnesium", "Aluminium", "Silizium"];
nCharges = [3,4,5,6,7,8,9,10,11,12,13,14]; 


### Generate numbers

strElement = strElements[jElement];
nCharge = nCharges[jElement];


Q = nCharge * 1.602e-19;]]></text>
</varsglobal>
<answernumbering><text>none</text>
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<answers>
 <partindex>
  <text>0</text>
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 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 4;
origSol = Q;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.6*critMantRnd1, 0.3*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + 0.7*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>C</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>&emsp;{_0}{_u}&emsp; (Angabe mit {nSigFig} signifikanten Stellen und Einheit)</p>]]></text>
 </subqtext>
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  </question>

<!-- question: 8035  -->
  <question type="formulas">
    <name>
      <text>Vektor der Coulomb-Kraft bei drei Ladungen</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>In die Anordnung der drei äusseren Körper mit elektrischen Ladungen 
<ul>
<li>\(Q_1 = {Qwest}\,\mathrm{\mu C}\), </li>
<li>\(Q_2 = {Qnorth}\,\mathrm{\mu C}\) und</li>
<li>\(Q_3 = {Qeast}\,\mathrm{\mu C}\)</li>
</ul>
wird die <u>{strChargeSign}</u> geladene Probeladung \(q\) gesetzt.</p>

<p> Verschieben Sie im Diagram den gelben Punkt so, dass der Vektor die <strong>Coulomb-Kraft</strong> auf \( q \) angibt.</p>

<p>Eine Koordinateneinheit entspricht der Stärke der Coulomb-Kraft auf \(q\), wenn nur \(Q_1\) zugegen wäre und eine Ladung von \( 1\,\mathrm{\mu C}\) hätte.</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>Qwest = {-3,-2,-1,1,2,3};
Qnorth = {-2,-1,1,2};
Qeast = {-3,-2,-1,1,2,3};
jSign = {0,1};</text>
</varsrandom>
<varsglobal><text><![CDATA[strChargeSigns = ["negativ", "positiv"];
intChargeSigns = [-1, +1];

strChargeSign = strChargeSigns[jSign];
intChargeSign = intChargeSigns[jSign];

FCx = intChargeSign * ( Qwest - Qeast);
FCy = intChargeSign * ( -4 * Qnorth);]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>3</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>2</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[FCx, FCy]</text>
 </answer>
 <vars2>
  <text><![CDATA[S_uEX = _0;
S_uEY = _1;

crit_uEX = abs( S_uEX - FCx ) < 0.1;
crit_uEY = abs( S_uEY - FCy ) < 0.1;

crit_tot = ( crit_uEX + crit_uEY ) / 2;]]></text>
 </vars2>
 <correctness>
  <text>crit_tot</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
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  <text></text>
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  <text>1</text>
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  <text></text>
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<text><![CDATA[<jsxgraph width="500" height="500" ext_formulas>

// JavaScript code to create the construction.
var jsxCode = function (question) {
    
    // JXG.Options.axis.ticks.majorHeight = 8;
    JXG.Options.axis.ticks.minorHeight = 0;
    JXG.Options.point.infoboxDigits = 0;
    JXG.Options.point.showInfobox = false;
    JXG.Options.point.snapSizeX = 1;
    JXG.Options.point.snapSizeY = 1;
    JXG.Options.point.snapToGrid = true;
    JXG.Options.line.snapToGrid = true;
    JXG.Options.arrow.lastArrow.size = 4;
    JXG.Options.arrow.lineCap = 'round';

    const col1='#4285F4', col2='#EA4335', col3='#34A853', col4='#FBBC05';

    // Attributes for points and lines
    function attrPfix(addAttr={}) {
        const attr = {fixed: true, visible: false, withLabel: false};
        return { ...attr, ...addAttr}; 
    }
    function attrPmov(addAttr={}) {
        const attr = {fixed:question.isSolved, withLabel:false, size:2,
                        fillColor:col4, strokeColor:col4 };
        return { ...attr, ...addAttr};
    }
    function attrChargeBigQ(nameQ="Q", Q=1) {
        if (Q>0) { 
            chargeColor = col2;
        } else {
            chargeColor = col1;
        }
        chargeSize = 5 * Math.sqrt( Math.abs(Q) );
        return {fixed:true, size:chargeSize, fillColor:chargeColor, strokeColor:chargeColor, 
            withLabel:true, name:nameQ, 
            label: {offset: [7, 26], anchorX: 'left', parse: false, fontSize: 12 } };
    }
    function attrChargeSmaQ(nameQ="q", Q=1) {
        if (Q>0) { 
            chargeColor = col2;
        } else {
            chargeColor = col1;
        }
        return {fixed:true, size:4, fillColor:chargeColor, strokeColor:chargeColor, withLabel:true, name:nameQ, 
        label: {offset: [7, 26], anchorX: 'left', parse: false, fontSize: 12 } };
    }
    const attrVecN = {fixed:question.isSolved, strokeColor:col4, strokeWidth:3};
    
    
    // Import final coordinates after submission
    var uEX, uEY;
    [uEX, uEY] = question.getAllValues([0, 0]);
    const uSX=0, uSY=0;
    
    
    // Create boards
    const brd0 = question.initBoard(BOARDID0, { 
        boundingbox:[-8.5, 8.5, 8.5, -8.5], axis:true, keepaspectratio:true,
        defaultAxes: {
          x: {withLabel: false },
          y: {withLabel:false } },
        zoom: {enabled:false, wheel: false}, pan: {enabled:false, needTwoFingers: false},
        showCopyright:false, showNavigation:false 
    });
    console.log(brd0);

    brd0.create('ticks', [brd0.defaultAxes.x], { strokeColor:'#cccccc', strokeWidth:0.3,
        minorTicks:4, minorHeight:-1, majorHeight:0, ticksDistance:5 });
    brd0.create('ticks', [brd0.defaultAxes.y], { strokeColor:'#cccccc', strokeWidth:0.3,
        minorTicks:4, minorHeight:-1, majorHeight:0, ticksDistance:5 });
    
    
    // Define lines and points on brd0
    brd0.create('point', [-4, 0], attrChargeBigQ('$$Q_1$$', {Qwest} ) );
    brd0.create('point', [0, +2], attrChargeBigQ('$$Q_2$$', {Qnorth} ) );
    brd0.create('point', [+4, 0], attrChargeBigQ('$$Q_3$$', {Qeast} ) );
    var pUS = brd0.create('point', [uSX, uSY], attrChargeSmaQ('$$q$$', {intChargeSign} ) );
    var pUE = brd0.create('point', [uEX, uEY], attrPmov() );
    // var u = brd0.create('arrow', [pUS, pUE], { ...attrVecN, ...{fixed:true}} );
    var u = brd0.create('arrow', [pUS, pUE], attrVecN );
    
    
    // Whenever the construction is altered the values of the points are sent to formulas.
    question.bindInput(0, () => { return pUE.X(); });
    question.bindInput(1, () => { return pUE.Y(); });
};

// Execute the JavaScript code.
new JSXQuestion(BOARDID0, jsxCode, allowInputEntry=false);

</jsxgraph>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
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<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
    <tags>
      <tag><text>JXG</text>
</tag>
    </tags>
  </question>

<!-- question: 8036  -->
  <question type="formulas">
    <name>
      <text>Verhältnisbildung Coulomb-Kraft (einfach)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p dir="ltr" style="text-align: left;">Zwischen zwei gegebenen Ladungen wirke eine bestimmte Coulomb-Kraft. Diese ist der Ausgangspunkt für alle folgenden Teilaufgaben.</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jOneCharge = {0:8};
jDistance = {0:8};
jTwoCharge = {0:8};</text>
</varsrandom>
<varsglobal><text><![CDATA[factNames = [ "gefünftelt" , "geviertelt" , "gedrittelt" , "halbiert" , "verdoppelt" , "verdreifacht" , "vervierfacht" , "verfünffacht" ];
factNumbers = [ 1/5 , 1/4 , 1/3 , 1/2 , 2 , 3 , 4 , 5 ];

solOneCharge = sigfig( factNumbers[jOneCharge] ,2);
strOneCharge = factNames[jOneCharge];

solDistance = sigfig( (factNumbers[jDistance])**(-2) ,2);
strDistance = factNames[jDistance];

solTwoCharge = sigfig( (factNumbers[jTwoCharge])**(2) ,2);
strTwoCharge = factNames[jTwoCharge];]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
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  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>solOneCharge</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[Um welchen Faktor ändert sich die Kraft, wenn <u>eine der Ladungen</u> {strOneCharge} wird?<br>{_0} (Dezimalzahl eingeben)<br>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
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  <text>1</text>
 </answermark>
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 </answertype>
 <numbox>
  <text>1</text>
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 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>solDistance</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
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  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Um welchen Faktor ändert sich die Kraft, wenn <u>der Abstand</u> {strDistance} wird?<br>{_0} (Dezimalzahl eingeben)<br></p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>2</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>solTwoCharge</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p dir="ltr" style="text-align: left;">Um welchen Faktor ändert sich die Kraft, wenn <u>beide Ladungen</u> {strTwoCharge} werden?<br>{_0} (Dezimalzahl eingeben)<br></p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 8037  -->
  <question type="formulas">
    <name>
      <text>Verhältnisbildung Coulomb-Kraft (schwer)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Zwischen zwei gegebenen Ladungen wirke eine bestimmte Coulomb-Kraft. Diese ist der Ausgangspunkt für die folgende Aufgabe.<br></p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jChargeOne = {0:8};
jChargeTwo = {0:8};
jDistance = {0:8};</text>
</varsrandom>
<varsglobal><text><![CDATA[factNames = [ "gefünftelt" , "geviertelt" , "gedrittelt" , "halbiert" , "verdoppelt" , "verdreifacht" , "vervierfacht" , "verfünffacht" ];
factNumbers = [ 1/5 , 1/4 , 1/3 , 1/2 , 2 , 3 , 4 , 5 ];

strChargeOne = factNames[jChargeOne];
strChargeTwo = factNames[jChargeTwo];
strDistance = factNames[jDistance];

sol = sigfig( factNumbers[jChargeOne] * factNumbers[jChargeTwo] * (factNumbers[jDistance])**(-2) ,3);]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
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  <text>0</text>
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  <text>1</text>
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 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Fully correct solution
crit1 = 1 * ( abs(origAns - sol)/sol <= 0.1000001 );

# Half the points for wrong order of magnitude or precision
mantAns = origAns / ( 10**(floor( log10(origAns)) ));
mantSol =  sol / ( 10**(floor( log10(sol)) ));
crit3 = 0.5 * ( ( abs(mantAns - mantSol)/mantSol <= 0.10000001 ) && ( abs(floor( log10(origAns))-floor( log10(sol))) < 2) );

grade = max(crit1,crit3);]]></text>
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  <text>grade</text>
 </correctness>
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  <text>0.2</text>
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 <ruleid>
  <text>1</text>
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 <otherrule>
  <text></text>
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 <subqtext format="html">
<text><![CDATA[<p>Um welchen Faktor ändert sich die Kraft, wenn eine der Ladungen {strChargeOne}, die andere {strChargeTwo} und der Abstand {strDistance} wird?</p>
<p>&emsp;{_0} (Dezimalzahl eingeben)</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>top/4 Elektrizität/Feld und Spannung</text>
    </category>
    <info format="moodle_auto_format">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 8048  -->
  <question type="formulas">
    <name>
      <text>Arbeit und Feldstärke aus Spannung berechnen</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Berechnen Sie jeweils die gesuchte Grösse und geben Sie sie mit richtiger Syntax samt Einheit an.</p>

<p>Ein Elektron wird im homogenen elektrischen Feld eines Plattenkondensators von der negativen zur positiven Platte beschleunigt. Die Spannung zwischen den Platten betrage {UStr} und ihr Abstand {dStr}.</p>

<p><img alt="" class="img-responsive" src="@@PLUGINFILE@@/tikz_ElektronHomogenesFeldBeschleunigt.png" width="101px"/><br></p>]]></text>
<file name="tikz_ElektronHomogenesFeldBeschleunigt.png" path="/" 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+qmt1WTP+j0X/NdcSi/dGlpaUdsWm2GRCB888/Xx5//PGUa6vdaDpdvQYFvRfl6KOPdrVNvZpL74zn9+yKjcIJCpSXlyfUhZvg5mKKDRs2TEKhUEy6UwJdXk465GWlgA5+n3POOSkd+3HHHSeffvqpGUx0Q/po33iXJrff4fTp080gRDBpr8JnvwsQUPzewgGsn17Kq1dZvfvuuzJx4kRXAqNHj5b77rtPdGC9b9++revm5eXJPffcE3cCSH2e/B//+Eezi2zEiBGt6/MBgSAI0OUVhFYOcB11nq/nnntOXn75ZfOMIXpWYp12Xru29tlnH/PKLL3r3ek0X+98v+qqq0Qf6LVr1y5TVgPPAQccYI6jXHzxxTJo0KAAi1P1dAlkYpcXASVdrc9+MkJAr77atGmTGQz69+8vekaRzKJjiCtXrhSdSkUDEgsC6RbIxIDCVV7p/hWwv04V0K6rIUOGpHwMetWWdo+xIIBAmwBjKG0WfEIAAQQQSEGAgJICHqsigAACCLQJEFDaLPiEAAIIIJCCAAElBTxWRQABBBBoEyCgtFnwCQEEEEAgBQECSgp4rIoAAggg0CZAQGmz4BMCCCCAQAoCBJQU8FgVAQQQQKBNIKNubNS5khoaGqSgoEBOP/10cyqLtkPlEwIIIICAPgDuwQcflJqaGtEniuqzevRvZiYsGRVQHn300daHFelDjfQZEywIIIAAAm0C+iTR22+/vTXhwgsvzJiAQpdXa7PwAQEEEEAgFQECSip6rIsAAggg0CpAQGml4AMCCCCAQCoCBJRU9FgXAQQQQKBVgIDSSsEHBBBAAIFUBAgoqeixLgIIIIBAqwABpZWCDwgggAACqQgQUFLRY10EEEAAgVaBQAYUvcN0y5YtrQh8QAABBLwS2Llzp+jz3oO4BCqgNDc3y1NPPSV6F/7cuXOD2N7UGQEEOlhgw4YNMnr0aPn9738v9fX1Hby3zNp8YALKG2+8IQcffLCcffbZonPhsCCAAAIdIaD/cN22bZtcdtllMm7cOPn73/8uTU1NHbGrjNumrwOKNuILL7xgBpLjjz9e5s+fn3ENwAEhgIB/BVasWCHnnHOOGVgeeeQRczJH/9ZWxJcBZevWrXLnnXfKqFGj5Ic//KHMmzfPz21I3RBAIMMFli5dKj/72c9k6NCh8pvf/EbWrFmT4Uec3OH5JqDoaebbb79t/mtg8ODBcvXVV8t3332XnAprIYAAAh0gsHnzZrnllltkxIgRcvLJJ8uLL77oq3GWjJq+Ppn2W7hwoTz99NPy5JNPyurVq5PZBOsggAACaRXQ7vhXXnnFfPXt21fOPPNMOeuss+SQQw6RUCiU1mPxcmdZF1D0qomPP/5YXn31VTO6f/PNN0l5aLfYunXrklqXlRBAAAE7gY0bN9plWabrLQwPPPCA+dLelVNPPVVOOukkmT59uuTn51uuk6mJGR9Q9AmOOpj+7rvvmq8PPvhA9DrvVJfzzjsv1U2wPgIIIOCpgD486/777zdfeXl5MnnyZDniiCPM19SpUzM+wGRsQNmxY4dceeWV8vDDD0tVVZWnjcbGEEAAgUwXqKurk/fff9983XTTTaIBRrvG9OwlU5eMHZTv1auX3H333bJ8+XJ55pln5KKLLjIvvctUSI4LAQQQ8Fpg+PDhcv7558tjjz0meqXYE088YV4p5vV+vNpexp6hhCvYv39/OeOMM8yXpmn/5OzZs80xFB3U0jOZZJa77rpLpk2blsyqrIMAAgjYCuglwaeffrptvlNG9+7d5dhjjzXPQvRdrwbLpiXjA0o0pgYYvVFIX3pK+Oabb5rTqcyaNcvV2IpOv6L9kywIIICAlwJ9+vRxtbmuXbvKCSecYF7ldcopp0hBQYGr9TOpcNYFlPZ42qeo/Yn60nGW559/Xh599FGzz7F9OT4jgAACmSaw7777ygUXXGBOB6WXDvthydgxFLe4PXv2NPsa33vvPVm8eLFceumlUlhY6HYzlEcAAQQ6TED/EXzuuefKRx99JF988YX5d8ovwUTRfBNQ2v8CdEK2++67T/QSvHvuuSejB7HaHzefEUDAnwIlJSXy29/+1pxyRQfWp0yZ4suK+jKghFtKz1Auv/xy0Qna9PJjnUeHBQEEEEiXQHFxsdx6663mLB433nijlJaWpmvXnbIfXweUsKgOel144YWybNkyue2226SoqCicxTsCCCDguYB2bf3qV7+Sb7/9Vq655pqsHmh3g5PVg/JuKqplu3XrJr/+9a/lpz/9qe+nkXZrQ3kEEPBGoF+/frJkyRIZOXKkNxvMoq0EKqCE20UbnAUBBBDoCAG9KVtfQVwC0eUVxIalzggggEC6BQgo6RZnfwgggIBPBQgoPm1YqoUAAgikW4CAkm5x9ocAAgj4VICA4tOGpVoIIIBAugUIKOkWZ38IIICATwUIKD5tWKqFAAIIpFuAgJJucfaHAAII+FQgo25s1GcC6DNO9CEzQbzL1Ke/MaqFAAIeCuiN2TNnzjT/VtbX15szgHi4+ZQ2FWo2FrdbKCsrk8bGRrerJVQ+Pz/f9xOoJQRBIQQQQMBBoLy8XCoqKhxKpJY1bNgwCYVCrjZCl5crLgojgAACCNgJEFDsZEhHAAEEEHAlQEBxxUVhBBBAAAE7AQKKnQzpCCCAAAKuBAgorrgojAACCCBgJ0BAsZMhHQEEEEDAlQABxRUXhRFAAAEE7AQIKHYypCOAAAIIuBIgoLjiojACCCCAgJ0AAcVOhnQEEEAAAVcCBBRXXBRGAAEEELATIKDYyZCOAAIIIOBKgIDiiovCCCCAAAJ2AgQUOxnSEUAAAQRcCRBQXHFRGAEEEEDAToCAYidDOgIIIICAKwECiisuCiOAAAII2AkQUOxkSEcAAQQQcCVAQHHFRWEEEEAAATsBAoqdDOkIIIAAAq4ECCiuuCiMAAIIIGAnQECxkyEdAQQQQMCVAAHFFReFEUAAAQTsBAgodjKkI4AAAgi4EiCguOKiMAIIIICAnQABxU6GdAQQQAABVwIEFFdcFEYAAQQQsBMgoNjJkI4AAggg4EqAgOKKi8IIIIAAAnYCBBQ7GdIRQAABBFwJEFBccVEYAQQQQMBOgIBiJ0M6AggggIArAQKKKy4KI4AAAgjYCRBQ7GRIRwABBBBwJUBAccVFYQQQQAABOwECip0M6QgggAACrgQIKK64KIwAAgggYCdAQLGTIR0BBBBAwJUAAcUVF4URQAABBOwECCh2MqQjgAACCLgSIKC44qIwAggggICdAAHFToZ0BBBAAAFXAgQUV1wURgABBBCwEyCg2MmQjgACCCDgSoCA4oqLwggggAACdgIEFDsZ0hFAAAEEXAkQUFxxURgBBBBAwE6AgGInQzoCCCCAgCsBAoorLgojgAACCNgJEFDsZEhHAAEEEHAlQEBxxUVhBBBAAAE7AQKKnQzpCCCAAAKuBAgorrgojAACCCBgJ0BAsZMhHQEEEEDAlQABxRUXhRFAAAEE7AQIKHYypCOAAAIIuBIgoLjiojACCCCAgJ0AAcVOhnQEEEAAAVcCBBRXXBRGAAEEELATIKDYyZCOAAIIIOBKgIDiiovCCCCAAAJ2AgQUOxnSEUAAAQRcCRBQXHFRGAEEEEDAToCAYidDOgIIIICAKwECiisuCiOAAAII2AkQUOxkSEcAAQQQcCVAQHHFRWEEEEAAATsBAoqdDOkIIIAAAq4ECCiuuCiMAAIIIGAnQECxkyEdAQQQQMCVAAHFFReFEUAAAQTsBAgodjKkI4AAAgi4Esh1VZrCrgTef/99efDBB12t42XhgQMHyu9+9zvp2rWrl5tlWwgggIClAAHFksWbxO+++06efvppbzaW5FZ+9rOfybhx45Jcm9UQQACBxAXo8krcipIIIIAAAg4CBBQHnFSz6GpKVZD1EUAgmwTo8urA1jrllFPkxRdf7MA9xN/0kCFD4heiBAIIIOCBAAHFA0S7TRQUFMgPfvADu2zSEUAAAV8J0OXlq+akMggggEDnCRBQOs+ePSOAAAK+EiCg+Ko5qQwCCCDQeQIElM6zZ88IIICArwQIKL5qTiqDAAIIdJ4AAaXz7NkzAggg4CuBwF42XF1dLa+88oosWbJEdIoUfa1evVqam5tl6NCh5uvggw+Wc845R4qLi33V6FQGAQQQ6AiBkPEHtNnthsvKyqSxsdHtagmVz8/Pl9LS0oTKJlNozpw58thjj8mzzz4rFRUVcTfRvXt3Ofvss+Wuu+6S3r17xy1PAQQQQCAdAuXl5Qn9DUv2WIYNGyahUMjV6oHp8po7d65MmjRJDj30UHnkkUcSboiamhp59NFHzXW//PJLV7gURgABBIIk4PuAUlVVJZdffrlMnTpVPv/8c8u2zcvLk/79+ztGY+0S+973vifbtm2z3AaJCCCAQNAFfB1Q5s2bJ+PHj5f77rtPmpqaItpaJ24899xzZcGCBaLjKRs2bJAdO3bIddddJzk5ORFlw19Wrlwp1157bfgr7wgggAAC7QR8O4by7rvvmmcUlZWV7arb8nGPPfaQF154QSZOnBiTpwm33367/PrXv7bM69Gjh6xdu5bxFEsdEhFAIF0CjKGkSVqv3jrhhBPEKphMnjxZ5s+fbxtM9BCvvPJKGTBggOXR7tq1Sz788EPLPBIRQACBIAv4rstLg8mpp54qOpgevQwfPlz+9a9/SUlJSXRWxPfc3FyZMGFCRFr7LzqewoIAAgggECngq4Ci95HouEh9fX1kLY1vOmby0ksvJXxJslVACm90+/bt4Y+8I4AAAgjsFvBNQGloaJCZM2eK9itaLb/61a9kn332scqyTFu0aJFluibuvffetnlkIIAAAkEV8E1Auf766+Wjjz6ybEe98/2GG26wzLNKXLZsmXnFl1Wepukd9CwIIIAAApECvggoejZxxx13RNas3Te9Ykuvzkp0+a//+i/booMHD5ZBgwbZ5pOBAAIIBFXAFwHlxhtvNOfgsmpEnS7l/PPPt8qyTHvvvffkqaeesszTxDPOOMM2jwwEEEAgyAJZH1AWLlxo3lNi14gXXnih6LPdE1m2bt0qF110kW3RsWPHyi233GKbTwYCCCAQZIGsDyhOZyfasDpbcCKLXiGm83wtXrzYsrjePf/444+LTl7JggACCCAQK5DVAUXvWH/xxRdja7U7ZcSIEY43MIZX1EkfDznkEPn666/DSTHvemYyZcqUmHQSEEAAAQRaBLI6oOhNjE6z7+sNjk6L3k9y9dVXywEHHGBOp2JVVqev/9vf/mY7FYvVOqQhgAACQRTI6gdsvfzyy45tdtxxx1nm642PDz30kGh3mY6b2C16ufHzzz/PZcJ2QKQjgAAC7QSyNqDonexvvfVWu6pEftQHw0TfL6KXF+vDtZ588knZuHFj5ArtvvXq1UuuueYaueyyyxgzaefCRwQQQMBJIGsDygcffCA6UaPdMmbMGNG753XuLp15+M0335R4D8jq2bOn/PznPzensO/Tp4/dpklHAAEEELAQyNqAos8mcVqWLl2a8Lxd++23n+jlxeedd54UFRU5bZY8BBBAAAEbgawNKOvXr7epUvzkLl26mN1hJ598spx++umi95ewIIAAAgikJpC1AWXdunUJ11zHU3Q6+unTp8uMGTPkiCOOkOLi4oTXpyACCCCAQHyBrA0o8c5QtBvrqKOOksMOO8x8MSYS/8dACQQQQCAVgawNKHbT1IcxZs2aJXpjIwsCCCCAQHoEsvbGxv79+zsK6aSQLAgggAAC6RPI2oAycuRIRyWr58k7rkAmAggggEBKAr4NKN98801KMOGV9X6XP/3pT+GvvCOAAAII2Ahk7RhKvDMUDShHH320TbUTS9apXfT5J9XV1dLY2Og4tX1iW6QUAggg4F+BrD1D0ee66/0kdsvrr79ul5VQuk7PopNLajDR5ZJLLpG5c+cmtC6FEEAAgSAK2P9FznANfRTvaaedZnuUenbxxhtv2ObbZTQ1Ncltt90m5557rjl1S7jcsGHDRCeLZEEAAQQQsBbI2oCi1bn++uuta7U7VSd33Llzp2OZ9pnLly+Xww8/XK699tqIafH1ijKdC2zgwIHti/MZAQQQQKCdQFYHlIkTJ4pOn2K36DjKvvvuK++//75dETN9w4YNcvPNN4veDDlnzpyIsnr5sZ7pjB49OiKdLwgggAACkQIh4wFVzZFJ8b+VlZWZg9TxS7ovoY/YLS0tTXjFr776ypxSxem5JjrWMnPmTJk8ebIZYHT7eqf9qlWr5KWXXhLtHtOZiaMXnZ5F86dNmxadxXcEEECgUwX05u6KiooOOwbt5tdpq9wsWR9QtLJLliyRY445xvapi25AwmV1e3/5y19Ex2pYEEAAgUwTyMSAktVdXuEGHjdunOj9Il50S+kZ0u9//3uzm4tgEhbmHQEEEIgv4IuAotXUebvmzZsnd911V1LT0Q8ZMsR8sNbixYvlP//zP12f6sWnpgQCCCDgbwFfdHlFN5EOC7399tvyyCOPmE9pXLt2rbSfTFLHVPSKLe0j1GehnHXWWWaXmdN9LdH74DsCCCDQmQKZ2OXly4Bi1cj6uGAdiO/atasMGjRIcnOzdpIAq+qRhgACARPIxIASmL+qPXr0kFGjRgXsJ0d1EUAAgfQJ+GYMJX1k7AkBBBBAwEqAgGKlQhoCCCCAgGsBAoprMlZAAAEEELASIKBYqZCGAAIIIOBagIDimowVEEAAAQSsBAgoViqkIYAAAgi4FiCguCZjBQQQQAABKwECipUKaQgggAACrgUIKK7JWAEBBBBAwEqg0++Ub2pqliVrdsriVVWyev12qTEeS9IjLyT9Swpk7z2K5dBJw6VP7wKrYycNAQQQQCCDBDotoDQ0Nsu7iyrkpbnlUl7VaJKEJE8qK3eYn+tqNklj7SKRhp1y/KF7yWXnTJXhg0oyiI5DSVjgtcdENq4SGT9VZO8pIgVFCa9KQQQQyB6BTpkccs3mWnn0nZ2yaUejFBb1Mp7frmDNUlWpTx8LmUGlqqpS6qorpaG2ykgxUhur5aIzDpBLzj5cC7Nkk8ATt4i8+mjLERszPcvwvUX2OaQlwOx1kEi3/GyqDceKQEYIMDmk0Qyff7tTnvjfXdI1v0gGDCoyg4XGk5Dxfz0Li3YHlZanElftfjpxoxFUGhqb5N7H35Gvl62Re66fKV1zczKiUTkIlwJNTSIrv2x5/etPIrldRUbtJzLBOHvRM5ixk4y0PJcbpTgCCGSCQFq7vFZurJXH3t0lffoPkUIjePQryjHOS1qWLRVGt5fx/OKWJxi3/K/mVBmvOuPVUq5ZXv9wufS8d5bcdtUPNZsl2wUa6kW+md/y+sf/FcnrJrLngS3BRYPMyH1EuvCPh2xvZo4/GAJpCyjVtY3y8FtV0q1HkdnN1bdnF+lbFJJ+PUOypapZ+hXmyuYK41+vzeH+9fB5i0il0RaNdTtbg88zr86V/ccNljNOMvrjWfwlUFcrsmhOy0trlt9TZJzRLTbe6CLTADN8nL/qS20Q8JFA2gLKq/N3SFOXQqNbq1D6FnYxAkhI9h5k9KcbZyUiRiAx3jZX7j4zMdNUubk1iOTk6ZVezWJcBGam3fHnN+XkGZOkR77xL1oW/wpUG+eon77T8tJaFhYbA/uTjeCyewxm0Ej/1p2aIZBlAmkJKDtrGuW1BdulT2mB2dWlRqVFRlAxXubSHDKCiZhBRkS7NwqNgXpjkN4YmNfF7O7S8RTzgxl7ZMv2KvnrrDnyf86aYZbhfwIiUFku8snrLS+tckn/livHwgGm3+CAQFBNBDJPIC0B5eMl240LeQqNkxE9A2k5C9GAsbmyefc3hTE+7z5B0W/mIH3PQqmq2NFSRjPN/w+ZcUXjywtvzLMOKAs/ENm0WjfDkgkCq7/uuKPYtlHkg3+2vHQvpUPbBvg1yPTq23H7ZssIIBAhkJaAsmhlpXEpcKN5FZfeZ9K3qNgYNzGOI2R0deliBAcNLpsrmmWLUa6qUsvv2H3FV0uRcDntBNO4o/FlyYp1ss04UynpbfSzt1/eeqrtX7Dt0/nsf4FNa0Te1tezLXUdMqYtwGhXWUEv/xtQQwQ6SSAtAWXN5hojCLRcCqrBwLyiy3g3Q4N2YxmJGlBaI4V5DqIiLWcj+im86JmLnp1oEd3W0pXrZMqkseFs3hGIFChbJqKv158wrhYzulj1HpjwJco62N+tR2R5viGAQNICaQko28orpDmvj3nm0XakxtVczcZ4iREVNDBolNhS2WScmejNjeFFI8fuRaOIUdA8QzFXMGOKeYYSLsI7Ao4C7e+BeelhY7jO+PmPNu6B0ftftHtMz2BYEEAgaYG0BBTtnmq5C16PU8dKdkeEkNH9YMaMlsChXV2aV2mMm2h5DS6aZi66TktMaflu/K9upYv+q5MFgWQE+g0RGWqc3epryOhktsA6CCDQTiAtAaWwW4Ns2m7cX2DczKhLhREwdFC+JYzsPkPRQLJ7Hq9wMGkJO83mFCyN9TuNe1GqzPtRGut2SWN9tTQ11Eq/kqjxk3aV4yMCEQJ9BrbdMKlnJfqdBQEEPBNIS0AZZUyxsmJjeetZigYKfWngKCw05vLaHVrCZzHhsxI9Q6mr0dH7lkUDkDl+YrzrmUxOTkj2HMllort5eIsWKOpjBBDj5tfwmMmAEdEl+I4AAh4KpCWgTBrTW177eI05hUo4PITPTvS95UzEuCPeCCDhRYOLTg6pi94lr2cnTcZ7U/0ucwUNQgdMGCU9CywmFjzzVyIn/TS8Kd47W+C1x0U+eqXjj6JHoXFX/cG7A4gxJjJsz47fJ3tAAIFWgbQElMkTBkpht8+kwpjkMbyEP2ng0Ekhw2cs4XwzmBhnIW3dXMbUK7tPT5rqa6TZ6O6aebLN1CvcPR1mzIz3j40bETti0VmK9zygbVB95ATjHxuMqXUENdtEIBGBtASUvK45cs5xY+SB5xdJow6uG2cXdW19V7JNz0TM9N2HbOTpmIn2hIUDihZvMsdNaoyxkxoZNby//OjEaYnUkTJ+EdBZiMfoVVnG2Yd2Y42ZaFypZcxWzIIAAhkhkJaAojU96bCx8uoHS+XbDS3dWGbt2/d36WddWuKN2c2lX/V5KLo0NeggvHFmYn4T+f8vP8MYQ+Ffo7s5/PmmswzvMb7lkl4dRN/rQGM24u7+rCu1QsAHAmkLKLnGH/+bLjpSLv6fV6S8skb0GY0t8URvXtRbHFsiSTjNfLCWkaSBRAtqMNFFu7uuu/j7cvgUo3uDxV8Cepaql/CG5+Xa2xgPMabsYUEAgewQSFtAUY7SPoVy++XHyLX3vWrcLW90ae1eWoJI+FvLuw6+hwONeWZi9HnpZcJXXnCCXHzeiZGF+Za9AgP3aHcprzEmVliSvXXhyBEIuEBaA4pajxzaR/742x/KrQ+/IZ98ud4caDdvdDSiSvvAoveZaLqm6ef+fXvLTb86T0480uj2YMlegb6D2gKIPl+ee0Gyty05cgSiBDrlmfLhY/h8yRp5fNYnsmDxKiOaGN0dUYuemQzo20vOPfVQufDs46RHd559EkWUHV8/flVk546WQMK9INnRZhxlxgtk4jPlOzWghFtse8UuWfRNmaxev1Vq6xqlV68iGdS/WCaMHSrjxw4zz1TCZXlHAAEEEBDJxICS9i4vqx9C76IecthBxmCsseTn50tpaalVMdIQQAABBDJYgOtuM7hxODQEEEAgmwQIKNnUWhwrAgggkMECBJQMbhwODQEEEMgmAQJKNrUWx4oAAghksAABJYMbh0NDAAEEskmAgJJNrcWxIoAAAhksQEDJ4Mbh0BBAAIFsEiCgZFNrcawIIIBABgsQUDK4cTg0BBBAIJsECCjZ1FocKwIIIJDBAgSUDG4cDg0BBBDIJgECSja1FseKAAIIZLAAASWDG4dDQwABBLJJgICSTa3FsSKAAAIZLEBAyeDG4dAQQACBbBIgoGRTa3GsCCCAQAYLEFAyuHE4NAQQQCCbBAgo2dRaHCsCCCCQwQIElAxuHA4tAwW++0rkzv8jsmlNBh4ch4RA5woQUDrXn71nk0B9rcj9V4rMny1yzSki8/6dTUfPsSLQ4QIElA4nZge+EXjz7yJly1uqs6tS5K6LRB75jcjOCt9UkYogkIoAASUVPdYNlsCBR4sUlUTWefZTIlcY6e+9EJnONwQCKEBACWCjU+UkBUqHilz5oEhuXuQGKraKPHi1yK9PEnnnORHtGmNBIIACBJQANjpVTkFgr4NEfnaT9QZWfS3yx2tELp4m8tQdIlvXWZcjFQGfCuT6tF5UK+gCT98p8s38zlGoLBf550MiLz0sctAxIsf/WGTcwZ1zLOwVgTQKEFDSiM2u0iigZwtL5qVxhxa7amoU+eT1lte9b4kMGGFRiCQE/CNAl5d/2pKaIIAAAp0qQEDpVH52jgACCPhHgC4v/7QlNWkvMGgPkSpjLKOjlmWfx99yKCQy6QhjDOV8urvia1HCBwIEFB80IlWwEDj3eotEj5I++KeIU0DpUShyxI9EjjtXpP9wj3bKZhDIfAECSua3EUeYSQLLPjMuDb7W+oj0rOg444qu6aeJdC+wLkMqAj4WIKD4uHGpmscCW4z7Su78ReyNiwVFIjOvEjn6bBHt5mJBIKACBJSANjzVTkJALwHesSVyxcNPFfkP44ylqE9kOt8QCKAAV3kFsNGpcpICR58lot1aumiX1mX3GXfFGzdQEkxaTPjfwAsQUAL/EwAgYYFu+SKX3COy3+EitxoD81NPTnhVCiIQBAG6vILQytTRO4GR+4hc+xfvtseWEPCRAGcoPmpMqoIAAgh0pgABpTP12TcCCCDgIwECio8ak6oggAACnSlAQOlMffaNAAII+EiAgOKjxqQqCCCAQGcKcJVXZ+qz7/QKbF3f8mySDStFNq4R2Wy8GhpEevcT6TvYmMhxusj+R4none8sCCDgWoCA4pqMFbJO4Iv3RGb/XWTB2yL60KvoZZMRWJZ+KvLhSyL5PUV+dJnICcacXF1yIkv+ybgjfvPayLTwtxlnGvelnBT+xjsCgRQgoASy2QNS6R1bRf5wtcjn/5t4haurRP56i3Em85rIdY+1TfK4fbPIO8+JNDdbb2vKCdbppCIQIAHGUALU2IGq6ufvivx/J7oLJu2B9IzldxcYE0HWtaR+9o59MNESk45svzafEQikAAElkM3u80q/9pjIbUYwiJ7I0W219Zn0rz7astYC45nwdsuIvUVKBtjlko5AYATo8gpMUwekou+9IPLEzc6V1Snmp50istdBIqP2FSkdKrJ2uchXH4u8+IBIXW3b+v98SOSwH4gsmtOWFv1p/xnRKXxHIJACBJRANrtPKz3v3yIPXePcNdVnoDFD8B0i46dGIow9QERfBxwlcvfFIhtWteTvqjQClDGmUlsdWb79N12HBQEEhC4vfgT+EFjzjcjvL7e+iitcw/2NcY7bX40NJuF8fR+2l8gvftc+ReRjYx27pXfflrMcu3zSEQiQAAElQI3t26o2N7WcmdS366qKruyQMSKX35/YPSbaFabBJ5FlYoLlEtkWZRDIcgECSpY3IIdvCLxiDJyvWGhPoc8xucIIJnnd7ctE50w+PjrF+nuigcd6bVIR8JUAAcVXzRnAymw0xjqeNR565bRceJPI4NFOJWLzBoyITYtOyc0zHrZ1WHQq3xEIrAABJbBN75OK6xVddTX2ldG71w8znvvuduk7KP4a4yeLdOsRvxwlEAiIAAElIA3ty2qu+1bkU+OGQ7tFLw/+4X/a5Tqnh29odCrF5cJOOuQFUICAEsBG902V9aZDu6lQtJIHHi2ig/HJLJXl8dcioMQ3okSgBAgogWpuH1VW/+C/96JzhX5g3E+S7FKxzXlNDVT9hjiXIReBgAkQUALW4L6p7uynnMdOJhyS2v0h61Y4U3F24uxDbiAFCCiBbHYfVHrBbOdKHHOOc3683BWLnEsQUJx9yA2kAAElkM2e5ZXW6VC+/dK+EjnGjEL7TrPPTyRnpcP2e/YW2XP/RLZCGQQCJUBACVRz+6SyX33kPMXK2EnGg7IKk6/szh3GEx1X268/cbpIiP907IHICaoA/1UEteWzud5OM/9qvfYz/uCnsiz8wHntA2Y455OLQEAFCCgBbfisrrY+/Mpp0TOIVJb5DuMz2p2WasBK5dhYF4EMFiCgZHDjcGg2Ats32WQYyT2Mri594FWyiz5zXp/2aLfsaUxxr/tgQQCBGAECSgwJCRktoDcyVjjcdNgngSlTnCq4+BORnRX2JXj2ib0NOYEXIKAE/ieQZQCVxg2HehZht5SU2uUklv7uc87luFzY2YfcQAsQUALd/FlY+e1bnA+6uL9zvlPujq3Gw7Rety+hMxAP3MM6/40nRO67VGT9d9b5pCIQAAECSgAa2VdVdHqIlla0OIUzlLeMu+8b6uy57M5O9KzpmbtFPnpF5KrjRF562H4b5CDgYwECio8b15dVKxngXC03D9FqvyUNJLP/3j4l9rPdw7Se/72I3mypS2ODc5dcSyn+FwFfChBQfNmsPq6UnoHkdbOv4NYN9nlOOXpWsW2jfQm9smvcwbH5678zApFxZhNeevUVOf7H4W+8IxAoAQJKoJrbJ5V1muV302r3ldxcJvLig87rjTOeM6/3oEQvf76h5awknH6qMcOxPnKYBYEAChBQAtjoWV/l0mH2VdA5vmp32edb5Tx2o/PMxbrO3lNi13zlzyJfftiWPsgYsD/6rLbvfEIgYAIElIA1uC+qe9Ax9tWo2i7y2uP2+dE5T9wisuDt6NTY72OM+cHaL6u/FnnqzraULsZ/Sr/4nYg+Z54FgYAKEFAC2vBZXW19RnxvY6zCbnnZGA/Zss4uty396TtE9KmPiSyFxW2l9NHDt10QeUXYceeJjDXuomdBIMACBJQAN37WVr2rcRagf8DtlipjtuBrvyfyxXvWJZYuEPnvM0VmPdSWr4Pux/5H2/foT3PfaElZ/LGx7kxjAL/d4P+gkSIzr4peg+8IBE4g1GwsbmtdVlYmjY0Odyu73WC78vn5+VJaalzJw4KAk4BOMX/1iZF/2KPLh0Iie0wQGblPy/0pW42zljVLRZZ9HllSy11tnNXoHGF/ui4yr/03HWyvrW6fItKzl8jNL4joTY8sCKRRoLy8XCoqHKYJSvFYhg0bJiH9b8PFYnHZiou1KYpAZwkUGH/Ib/ibyI3G2YLd3fP6b6VvF7W87I5Tr9y68CYRvcek/QC7VfnoYKLrXvEAwcTKirRACtDlFchm90mldRqU3xhBpagkuQoVFBldY38ROfKMlvX1PpN4N06G96RnJtcY4y/jp4ZTeEcg8AIElMD/BLIcYMgYkVtebLlct6vDDY/R1dzvMJGb/iEy4ZC2HD3j+Ol/i+gVW06LdqHdMktkn2lOpchDIHACjKEErsl9XOHtm42rtowzjoXvi2xa0zYdilZZxz/6Dmq52/2E80UGj7aH0Cc2PnW7yKolxjQqTS3l9Dnyo/cTOfEnxvPqjWDEgkAnC2TiGAoBpZN/FOy+AwX0uSYVW0X0kl8NCG6XuhoRncpFu9S0e4wFgQwSyMSAYpzjsyDgUwENAqkEAp1ocuAIn+JQLQS8F4jTWez9DtkiAggggIA/BQgo/mxXaoUAAgikXYCAknZydogAAgj4U4CA4s92pVYIIIBA2gUIKGknZ4cIIICAPwUIKP5sV2qFAAIIpF2AgJJ2cnaIAAII+FOAgOLPdqVWCCCAQNoFCChpJ2eHCCCAgD8FCCj+bFdqhQACCKRdgICSdnJ2iAACCPhTgIDiz3alVggggEDaBQgoaSdnhwgggIA/BQgo/mxXaoUAAgikXYCAknZydogAAgj4U4CA4s92pVYIIIBA2gUIKGknZ4cIIICAPwUIKP5sV2qFAAIIpF2AgJJ2cnaIAAII+FOAgOLPdqVWCCCAQNoFCChpJ2eHCCCAgD8FCCj+bFdqhQACCKRdgICSdnJ2iAACCPhTgIDiz3alVggggEDaBQgoaSdnhwgggIA/BQgo/mxXaoUAAgikXYCAknZydogAAgj4U4CA4s92pVYIIIBA2gUIKGknZ4cIIICAPwUIKP5sV2qFAAIIpF2AgJJ2cnaIAAII+FOAgOLPdqVWCCCAQNoFCChpJ2eHCCCAgD8FCCj+bFdqhQACCKRdgICSdnJ2iAACCPhTgIDiz3alVggggEDaBQgoaSdnhwgggIA/BQgo/mxXaoUAAgikXYCAknZydogAAgj4U4CA4s92pVYIIIBA2gUIKGknZ4cIIICAPwUIKP5sV2qFAAIIpF2AgJJ2cnaIAAII+FOAgOLPdqVWCCCAQNoFCChpJ2eHCCCAgD8FCCj+bFdqhQACCKRdgICSdnJ2iAACCPhTgIDiz3alVggggEDaBQgoaSdnhwgggIA/BQgo/mxXaoUAAgikXYCAknZydogAAgj4U4CA4s92pVYIIIBA2gUIKGknZ4cIIICAPwUIKP5sV2qFAAIIpF2AgJJ2cnaIAAII+FOAgOLPdqVWCCCAQNoFCChpJ2eHCCCAgD8FCCj+bFdqhQACCKRdgICSdnJ2iAACCPhTgIDiz3alVggggEDaBQgoLskbaxpl7ZzNUvHdTpdrUhwBBBDwt0Cuv6uXeu2a6ptl88JyWffRZln38WbZ9EW5NNU3yYx7D5KiEQWp74AtIIAAAj4RIKBENWRzk8jWxduN4LFF1hsBZMOCbdJQ3RBViq8IIIAAAtECBBRDpHxppXn2sf4TI4jM3SJ1lfXRTnxHAAEEEIgjEMiAouMfGjy0C0vfq7fVxmEiGwEEEEAgnkAgAsrO9dW7A0hLENm5oTqeC/kIIIAAAi4FfBlQarbVtZ6B6FhIxaoqlywURwABBBBwK+CLgFJX2SAb5unZR8tA+ralFW4dXJdvMC4frt/JYL1rOFZAAAFPBJobmj3ZjpcbCTUbi9sNlpWVSWNjo9vVEiqfn58vpaWljmUbqhtlo3H1VXgMZMtX26W5yXU1HPdBJgIIIJDJAvtdMUr6HV/YYYc4bNgwCYVCrrafFWcoet/Hps+Ne0F2n4FsMu4L0TQWBBBAAIHMEcjIgKL3gmz5sty4D6SlG2vjp1tFu5hYEEAAAQQyVyDjAkpjbZMs/usKWTV7g3FX+jZprONMJHN/PhwZAggg0CaQcQElp1sXGf/jUeZLg8vGBVvNri4dL9lqjJU0NTJW0tZ8fEIAAQQyRyDjAkp7Gg0ugw7pZ75ExplXVW2YqwFG59XaYtzhXiFJXFPQfhd8RgABBBDwSCCjA0p0HbsW5MrQI/ubL82r3V7XMlCvd70bkzfu+C5995sMnlYqRcOYHDK6jfiOAALpEeg1umd6duRiL1kVUKLr1a13nuxx/CDzpXm7Nta0nr3oxI5Vxh3yHbXsefrw1v121D7YLgIIIGAnUF5eLhUVHX/Pnd3+rdKzOqBEV6hH/+4y+vtDzZfmVa7eaZ7BhO9Xqd7KnF3RZnxHAAEEvBLwVUCJRik0uqT21NcZw82s8mWV5pT0Ov6id9bXVjCrcLQZ3xFAAIFkBXwdUKJRiscUir72PnekiHGxmN5hH551WO+8r9/FVCrRZnxHAAEEEhUIVECJQDFmFOg7obf52ueC0aLz4ugd+Dr2omcwemd+Yx03U0aY8QUBBBBwEAhuQIlCCeWGpP/+JeZr4sV7inkPjHGHfst0L1vMO/e5ByYKja8IIIBAOwECSjuM9h/Ne2CmGvfAGC9ddGbhDfPCAWazMWla+9J8RgABBBAgoCT4GzDvgTnCuAfGeLEggAACCMQKdIlNIgUBBBBAAAH3AgQU92asgQACCCBgIUBAsUAhCQEEEEDAvQABxb0ZayCAAAIIWAgQUCxQSEIAAQQQcC9AQHFvxhoIIIAAAhYCBBQLFJIQQAABBNwLEFDcm7EGAggggICFAAHFAoUkBBBAAAH3AgQU92asgQACCCBgIUBAsUAhCQEEEEDAvQABxb0ZayCAAAIIWAgQUCxQSEIAAQQQcC9AQHFvxhoIIIAAAhYCBBQLFJIQQAABBNwLEFDcm7EGAggggICFAAHFAoUkBBBAAAH3AgQU92asgQACCCBgIUBAsUAhCQEEEEDAvQABxb1ZxqyxdfEOmf3LuVJZtitjjokDQQCB4AoQULK07Rtrm+TdqxfIqrfWy6xT35VVs9dnaU04bAQQ8IsAASVLW/Lrp1fK9hWV5tHXVdbL7Evmypz/+kLqKuqztEYcNgIIZLsAASVLW3DYUQOle3G3iKP/+pnv5Pnj35Lls9ZEpPMFAQQQSIcAASUdyh2wj8IhPeSo/3uQ5ORFNmH1tlr532s+lRe//64s/cdq0a4xFgQQQCAdApF/jdKxR/bhmcCAA/vItP/ez3J7277ZIe9f/5k8fcQbMv+uxbJzfbVlORIRQAABrwRyvdoQ27EXmH/PEtm4YKt9gQ7MqSmvky8eXiaLHl0uw48eKHv/x0gZcFCfDtwjm0YAgaAKEFDS0PLbvt4hG+Z3TkAJV6+psVlWvrHOfJ3+xtFSNLwgnMU7Aggg4IkAXV6eMLIRBBBAAAECCr8BBBBAAAFPBOjy8oTReSO99iiU2u0dd3/Ipi+2OR+AkRsKhWTo9P6y97kj6e6Kq0UBBBBIRoCAkoyay3UmXzPe5RqJF1/xUpk4BZS8nl1l7A+Hyd7n7CGFwxg3SVyWkggg4FaAgOJWLIPKb/q83Lg0+HPLI+q1R08Zb1zRNfoHQ6VrAc1siUQiAgh4KsBfGk8507exqnXVxsSQn0hjXWPETrsVdZUDrthbxs0cYfRzRWTxBQEEEOhQAQJKh/J23Ma/+/c6qd5aG7GDMd8fKgf/eoJ0L8mLSOcLAgggkA4BrvJKh3IH7GOvM0eIdmvpol1aR959oBz+u/0JJh1gzSYRQCAxAQJKYk4ZVyo3P0eOuOMAGXJYqXz/+eky8sTBGXeMHBACCARLgC6vLG7vvhN6y3EPT83iGnDoCCDgJwHOUPzUmtQFAQQQ6EQBAkon4rNrBBBAwE8CBBQ/tSZ1QQABBDpRgIDSifjsGgEEEPCTAIPyHrVm9eZaWT9vi0dbS99m+o7vzdxe6eNmTwj4WoCA4lHzrp2zyXz0rkebS9tmDr91fwJK2rTZEZScOkwAAAwiSURBVAL+FqDLy6P2rSzb5dGW0ruZ3iNbbo5M717ZGwII+FGAgOJRq2ZtQBlV6JEAm0EAgaAL0OXl0S+gualZeg7Ml+Zmkaa6JmPSxiZpqG4QffRusos+wyTPmOwxp1sXCXUJGc80adtSc5NI9ZaalLZf0D9fuvbkJ9CmyicEEEhFgL8mqei1W3f67fu3+9bysbmhWXasqpKVr62Tzx9aKk0NRhRIYNnzR8Nl5EmDZeBBfSWU2y6KRK3bVN8slWU7pWK18Vq1U74znhm/YUHiz66nuysKlK8IIJCSAAElJT7nlTUY9Da6lCZdsqes+3izbJgf/4/9hB+PksnXTnDe8O7cLl1D5gSR4Ukix583Ula9uV7m3rnYCDBVcbfRi+6uuEYUQACBxAUYQ0ncKqWS2iUWbykc0kMOvjq1pzsOP2ag/PDlGTLxF2Pj7U6KRzN+EheJAgggkLAAASVhqhQKGrGkfGll3A2M/t5Qxy6uuBvYXUDPXA64fJzoFPdOS++RBBQnH/IQQMCdAAHFnVdSpcuXV0pdVX3cdYfNGBC3jJsCU67fR/JLutmu0nsUlwzb4pCBAAKuBQgorsncr7AxgYHy7sXdRO9a93LJyesie+mjgC2Wbr3zpHsf+2BjsQpJCCCAgKMAAcWRx5vMtXM2x93QoKl9O+QZ8DqmYrXQ3WWlQhoCCKQiQEBJRS+BdfV+kfWfxA8ogw8pTWBr7ovowHuX3NhmZkDevSVrIICAs0DsXxrn8uS6FNiyqFxqK+KPnww6pJ/LLSdWvEvXLlI0rCCmMOMnMSQkIIBAigIElBQB462+9sP4ZydFw3tKz0H58TaVdH633l1j1tX7Y1gQQAABLwUIKF5qWmxrXQIBZbDLs5Pa7XXmZcj1Oxss9hiblJsfe/8qASXWiRQEEEhNIPYvTWrbY+12Ag27GmXj59vapVh/HDzNXXfXRzcvkhUvl5kb08uCdeB92o37WW/cSM3tnhOR17UgVwqMecdYEEAAAS8FOEPxUjNqW/rAraZ65/m7uuSEZODkxANK1dpdxtxga1v3VL2t1nLQvbWA8UEvH26/hKdqaZ/GZwQQQCBVgci/NKlujfUjBBLp7uo7oVjyChM/UVz05+UxMwy7HdAvZvwkop34ggAC3ggk/pfMm/0FaiuJ3H/iprurZludLH1hdYShnuEMmmzcw+Kw5PfrHnGlV7+JJQ6lyUIAAQSSEyCgJOcWd61dm2qkfHlF3HKDpibW3aX3s3x44xfSUNMYsc2++xTHfabJlOsmiL5YEEAAgY4UoMurg3TXfRT/cuGuPXKlNMGzhfev+0xWGs87iV7cXiEWvT7fEUAAAa8ECCheSUZtJ5HurgEH9hGdGTje8uGNC2XZrMiurvA6iZ7hhMvzjgACCHSUAF1eHSSbyBlKvPET3cbCR5bL2jmbLI/SzRmO5QZIRAABBDwUIKB4iBnelD77ZNfmmvBX2/dBFvN31RnTtKx+Z4N8+ZcVsvXrHbbrakb/AxI7w3HcCJkIIICARwIEFI8g229m7YfWZxTty+jnpc+vkrrKetm5vlp2bqyRnRuqpX5XYne/6/qMn6gCCwIIZIoAAaUDWiKR+090t18+viKlvcfrMktp46yMAAIIuBRgUN4lWLziTfXNsn7e1njFUs7PNx6OVTy2KOXtsAEEEEDAKwECileSu7ez6bNt0lCdeLdVsrvn6q5k5VgPAQQ6SoAuL49lExk/6dYrTzQg6AB81fpd5hhK9A2L8Q6LgBJPiHwEEEi3AAHFY/FE7j8ZYcwOfOjNEyP2XL25Vr5+5jv56okVCT2QiwH5CD6+IIBABgjQ5eVhI9TtqJctX22Pu8XB02If95vfr5tMumRPOfOdY2XMD4Y5bkNnC2b6eUciMhFAoBMECCgeoq/7ZIs0NzU7bjEUMiZznGo/maM+q+TQm/aTPnv1st3O4ATn/7LdABkIIIBABwgQUDxETWT8pM+4XtKtd57jXvU58Efec6BtGbfT1dtuiAwEEEDAQwECioeY6+bEnxAy0WCg3VqFg3vEHJ3bB3LFbIAEBBBAoIMECCgewVaW7ZKKNTvjbs3NYHrxmNj7TPqM7+3qgVxxD4gCCCCAgEcCBBSPIBO5Oz63W470N2YYTnQpGl4QU9RqQD+mULsEndZFn6XCggACCHS0AJcNeyS89sP43V06mWP0892ddm/1PHo3A/Jl72+SN372keR2z5GSPXuZFwMccPk4p12ShwACCCQtQEBJmq7disaFXes+jh9QEh0/CW+5Zntd+KP5nptvPJBrUmKP721ubJZPbv3SXE9vmtz0xTbp2iMnYnt8QQABBLwUoMvLA02996Q26o+/1WbdjJ/o+jtWVkVsZsCBJQk9kEtXWvL3lbL928qI9YcbN1SyIIAAAh0lQEDxQDaRu+O7F3eTPnvb31sSfRg6yeT2FZEBYdDU2Bsio9fT73qD5acPfBORpfe/DD+agBKBwhcEEPBUgIDiAWci958MmmJ/M6PVIez4rkoa6yJH0xM9w1lw35KYM6Z++xZLj9LuVrsiDQEEEPBEgDGUFBkbdXzCmGE43uL26qziMYVyxr+Plm3fVMi2pRXmw7dK9oq9jDh6vxs/3SZLnvouOllGHMvZSQwKCQgg4KkAASVFzg3zt8acSVhtMpnZgQuHFYi+Eh370DOa96//TJqbY6d/obvLqlVIQwABLwXo8kpRM5Hxk6LhPaXn4PwU9xR/db2qK3ogX9cqMR7EZXVPS/wtUgIBBBBIXICAkriVZclExk8SHfuw3EGCidrNteSplZalOTuxZCERAQQ8FiCgpABavaXWHOOIt4mODiirZq+Xj29ZZHsYI44dZJ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    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>UMant = {1.1:3.1:0.2};
dMant = {10:99};</text>
</varsrandom>
<varsglobal><text><![CDATA[Prefixes = ["p", "n", "µ", "m", "c", "d", "da", "h", "k", "M", "G", "T"];
Exponents = [-12, -9, -6,-3, -2, -1, 1, 2, 3, 6, 9, 12]; 

kC = 8.988e9;
e = 1.602e-19;

UVal = UMant * 10**(3);
UStr = join(" " , "\\(" , str(UMant) , "\\,\\mathrm{kV}\\)" );

dVal = dMant * 10**(-3);
dStr = join(" " , "\\(" , str(dMant) , "\\,\\mathrm{mm}\\)" );

W = e * UVal;
E = UVal / dVal;]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 2;
origSol = W;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.6*critMantRnd1, 0.3*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.3*critExp + 0.1*critSigFig + 0.6*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>J</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Um welchen Betrag nimmt die kinetische Energie des Elektrons dabei zu? [2P]</p>
<p>&emsp; \( \Delta E_\mathrm{kin} =\; \) {_0}{_u}&emsp; (Angabe mit Einheit)</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 2;
origSol = E;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.6*critMantRnd1, 0.3*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.3*critExp + 0.1*critSigFig + 0.6*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>V/m = N/C</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>Welchen Wert hat die elektrische Feldstärke zwischen den Platten? [2P]</p>
<p>&emsp; \( E =\; \) {_0}{_u}&emsp; (Angabe mit Einheit)</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 8049  -->
  <question type="formulas">
    <name>
      <text>Elektrische Feldstärke und Kraft berechnen</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Berechnen Sie jeweils die gesuchte Grösse und geben Sie sie mit richtiger Syntax samt Einheit an. (Vorzeichen beachten!)</p>]]></text>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>4.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>q1Mant = {1.01:9.99:0.02};
q1ExpJ = {0:4};
q1Sig = {-1,1};

q2Mant = {1.01:9.99:0.02};
q2ExpJ = {0:4};
q2Sig = {-1,1};

xMant = {1.01:9.99:0.02};
xSig = {-1,1};</text>
</varsrandom>
<varsglobal><text><![CDATA[Prefixes = ["p", "n", "µ", "m", "c", "d", "da", "h", "k", "M", "G", "T"];
Exponents = [-12, -9, -6,-3, -2, -1, 1, 2, 3, 6, 9, 12]; 

kC = 8.988e9;

q1Mant = q1Sig * q1Mant;
q1Val = q1Mant * 10**(Exponents[q1ExpJ]);
q1Str = join(" " , "\\(" , str(q1Mant) , "\\,\\mathrm{" , Prefixes[q1ExpJ] , "C}\\)" );

q2Mant = q2Sig * q2Mant;
q2Val = q2Mant * 10**(Exponents[q2ExpJ]);
q2Str = join(" " , "\\(" , str(q2Mant) , "\\,\\mathrm{" , Prefixes[q2ExpJ] , "C}\\)" );

xMant = xSig * xMant;
xVal = xMant * 10**(-2);
xStr = join(" " , "\\(" , str(xMant) , "\\,\\mathrm{cm}\\)" );

Ex = - xSig * kC * q1Val *  xVal**(-2);
Fx = - xSig * kC * q1Val * q2Val *  xVal**(-2);]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 3;
origSol = Ex;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( abs(mantAns) - abs(mantSolSFA) ) < 0.5 * 0.1**(nSigFigAns-1) );

# Correct sign
critSign = ( ( mantAns * mantSol ) > 0 );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.6*critMantRnd1, 0.3*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.3*critSign + 0.2*critExp + 0.1*critSigFig + 0.4*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>N/C</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Welchen Wert hat die elektrische Feldstärkekomponente \( E_x \) im Koordinatenursprung aufgrund einer Ladung von {q1Str} bei der \( x \)-Position {xStr}? [2P]</p>
<p>&emsp; \( E_x =\; \) {_0}{_u}</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 3;
origSol = Fx;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( abs(mantAns) - abs(mantSolSFA) ) < 0.5 * 0.1**(nSigFigAns-1) );

# Correct sign
critSign = ( ( mantAns * mantSol ) > 0 );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.6*critMantRnd1, 0.3*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.3*critSign + 0.2*critExp + 0.1*critSigFig + 0.4*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>N</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>Welchen Wert hat die Komponente \( F_{\mathrm{el},x} \) der elektrischen Kraft auf eine zweite Ladung von {q2Str} im Koordinatenursprung? [2P]</p>
<p>&emsp; \( F_{\mathrm{el},x} =\; \) {_0}{_u}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 8050  -->
  <question type="formulas">
    <name>
      <text>Feldstärke aus Kraft und Ladung berechnen</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Wenn eine Kraft von {FStr} notwendig ist, um ein Körper mit einer Ladung von {q1Str} festzuhalten, wie gross ist dann die elektrische Feldstärke am Ort der Ladung?</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>q1Mant = {1.01:9.99:0.02};
q1ExpJ = {0:4};

FMant = {1.01:9.99:0.02};
FExpJ = {2:5};</text>
</varsrandom>
<varsglobal><text><![CDATA[Prefixes = ["p", "n", "µ", "m", "c", "d", "h", "k", "M", "G", "T"];
Exponents = [-12, -9, -6,-3, -2, -1, 2, 3, 6, 9, 12]; 

q1Val = q1Mant * 10**(Exponents[q1ExpJ]);
q1Str = join(" " , "\\(" , str(q1Mant) , "\\,\\mathrm{" , Prefixes[q1ExpJ] , "C}\\)" );

FVal = FMant * 10**(Exponents[FExpJ]);
FStr = join(" " , "\\(" , str(FMant) , "\\,\\mathrm{" , Prefixes[FExpJ] , "N}\\)" );

E = sigfig( FVal / q1Val , 3);]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[E]</text>
 </answer>
 <vars2>
  <text><![CDATA[S_E = _0;

crit_E_Correct = ( abs( ( S_E - E ) / E ) < 0.001 );
crit_E_AlmostCorrect = ( abs( ( S_E - E ) / E ) < 0.01 );

crit_tot = 0.6 * crit_E_AlmostCorrect + 0.4 * crit_E_Correct;]]></text>
 </vars2>
 <correctness>
  <text>crit_tot</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>N/C</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>&emsp; \( E =\; \) {_0}{_u}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 8051  -->
  <question type="formulas">
    <name>
      <text>Verhältnisbildung Elektrisches Feld (einfach)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>In einem bestimmten Abstand von einer gegebenen Punktladung habe die elektrische Feldstärke einen bestimmten Wert. Dieser ist Ausgangspunkt für die folgenden Teilaufgaben.</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jOneCharge = {0:8};
jDistance = {0:8};</text>
</varsrandom>
<varsglobal><text><![CDATA[factNames = [ "gefünftelt" , "geviertelt" , "gedrittelt" , "halbiert" , "verdoppelt" , "verdreifacht" , "vervierfacht" , "verfünffacht" ];
factNumbers = [ 1/5 , 1/4 , 1/3 , 1/2 , 2 , 3 , 4 , 5 ];

solOneCharge = sigfig( factNumbers[jOneCharge] ,2);
strOneCharge = factNames[jOneCharge];

solDistance = sigfig( (factNumbers[jDistance])**(-2) ,2);
strDistance = factNames[jDistance];]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>solOneCharge</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Um welchen Faktor ändert sich die elektrische Feldstärke, wenn die <em>Ladung</em> {strOneCharge} wird?</p>
<p>&emsp;{_0}&emsp; (Dezimalzahl eingeben)</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>solDistance</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>Um welchen Faktor ändert sich die elektrische Feldstärke, wenn der <em>Abstand</em> {strOneCharge} wird?</p>
<p>&emsp;{_0}&emsp; (Dezimalzahl eingeben)</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>top/4 Elektrizität/Strom und Stromstärke</text>
    </category>
    <info format="moodle_auto_format">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 8070  -->
  <question type="formulas">
    <name>
      <text>Knopfzelle in einer Armbanduhr</text>
    </name>
    <questiontext format="markdown">
      <text><![CDATA[<p>Eine Knopfzelle treibt {tStr} lang einen Strom der Stärke {IStr} durch den Stromkreis einer elektrischen Armbanduhr. Dann ist die chemische Energiequelle der kleinen Batterie erschöpft.</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>4.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>I = {10:100:10};
tJ = {0:4};</text>
</varsrandom>
<varsglobal><text><![CDATA[tStrings = ["ein Jahr","zwei Jahre","drei Jahre","vier Jahre"];
tYears = [1,2,3,4];

tStr = tStrings[tJ];
t = tYears[tJ];

IStr = join(" " , "\\(" , str(I) , "\\,\\mathrm{\\mu A}\\)" );

Q = I * 10**(-6) * t * 365 * 24 * 3600;

e = 1.602e-19;
N = I * 10**(-6) / e;]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 2;
origSol = Q;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.8*critMantRnd1, 0.6*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + 0.7*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Welche Ladung hat die Knopfzelle in dieser Zeit durch den Stromkreis getrieben?</p>
<p>&emsp;{_0}&nbsp;\( \mathrm{C} \)&emsp; (Angabe mit {nSigFig} signifikanten Stellen)</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>N = I * 10**(-6) / e;

nSigFig = 2;
origSol = N;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.8*critMantRnd1, 0.6*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + 0.7*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Wie viele Elektronen flossen im Betrieb durchschnittlich pro Sekunde durch den Querschnitt der zur Batterie laufenden Leitungen?</p>
<p>&emsp; {_0}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 8071  -->
  <question type="formulas">
    <name>
      <text>Powerbank und Handyakku</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p><em>Hinweis: Sie können in dieser Aufgabe praktische Einheiten verwenden und müssen nicht auf signifikante Stellen achten.</em></p>

<p>Sie haben sich im Internet eine Powerbank bestellt, die laut Beschreibung {=QP*1000}&nbsp;mAh elektrische Ladung speichert und vollständig aufgeladen bei Ihnen ankommt.</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>tH = {1:4};
IH = {0.5:2.1:0.2};

nP = {5:8};

tL = {0.3:1.6:0.2};
IL = {0.9:2.1:0.2};</text>
</varsrandom>
<varsglobal><text>QH = tH * IH;
QP = nP * QH;

QL =tL * IL;</text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>tH</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>h</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text>1 h = 60 min; 1 h = 3600 s;</text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Ihr Handyakku ist gerade vollkommen leer und hat eine Kapazität von {=QH*1000}&nbsp;mAh. Berechnen Sie, wie lange es dauert, den Handyakku mit der Powerbank vollständig zu laden, wenn beim Laden im Mittel {IH}&nbsp;A fliessen. [33%]</p>
<p>&emsp;{_0}{_u}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>nP</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_relerr < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Wie oft können Sie Ihr Handy theoretisch mit der Powerbank vollständig aufladen? [33%]</p>
<p>&emsp;{_0}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>2</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 2;
origSol = QL;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}
nSigFigAns = max( nSigFig, nSigFigAns);

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
origSolSFA = sigfig( origSol , nSigFigAns );
expSolSFA = floor( log10(abs(origSolSFA)) );
mantSolSFA = origSolSFA / ( 10**( expSolSFA ));
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );

# Correct exponent
critExp= ( abs( expAns - expSolSFA ) < 0.1 );

# Calculate grade
critMant = max( critMantCorrect, 0.8*critMantRnd1 );
grade = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + 0.7*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>Ah</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text>1 Ah = 1000 mAh; 1 Ah = 3600 C; 1 Ah = 3600 As;</text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Nun ist Ihre Powerbank vollständig entladen. Sie laden sie über {tL}&nbsp;h hinweg. Es fliessen dabei im Mittel {IL}&nbsp;A. Wie viel Ladung ist nun wieder in der Powerbank gespeichert? [33%]</p>
<p>&emsp;{_0}{_u}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>top/4 Elektrizität/Netzwerke</text>
    </category>
    <info format="moodle_auto_format">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 8086  -->
  <question type="formulas">
    <name>
      <text>Wie viele Elektronen fliessen jede Sekunde durch eine Glühbirne</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Wie viele Elektronen fliessen jede Sekunde durch eine Glühbirne, wenn die elektrische Stromstärke durch die Glühbirne \( {I} \,\mathrm{A} \) beträgt?</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>I = {1.15:3.2:0.1};</text>
</varsrandom>
<varsglobal><text>e = 1.602e-19;

Ne = I / e;</text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 3;
origSol = Ne;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.8*critMantRnd1, 0.6*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + 0.7*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>&emsp; {_0}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>top/4 Elektrizität/Leistung</text>
    </category>
    <info format="moodle_auto_format">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 8097  -->
  <question type="formulas">
    <name>
      <text>Leistung und Vorwiderstand einer LED</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Das Diagramm zeigt die Kennlinie einer Leuchdiode (LED). Laut Herstellerangabe soll diese LED bei einem Strom von \(20\,\mathrm{mA}\) betrieben werden.</p>

<br>
<p>
    <jsxgraph width="800" height="300">

        const col1 = '#4285F4', col2 = '#EA4335', col3 = '#34A853', col4 = '#FBBC05';

        // Attributes for points and lines
        const attrLine = {strokeColor: col1, strokeWidth: 3};

        const uS = {uS};

        var brd = JXG.JSXGraph.initBoard(BOARDID, {
        boundingbox: [-0.2, 32, 3.2, -3], axis: true,
        defaultAxes: {
        x: {minorTicks: 1, withLabel: true, name: '$$U\\;\\mathrm{(V)}$$',
        label: {position: 'rt', offset: [10, 26], anchorX: 'right', parse: false, fontSize: 12 },
        ticks: {insertTicks: false, ticksDistance: 0.2, minorTicks: 1} },
        y: {withLabel: true, name: '$$I\\;\\mathrm{(mA)}$$',
        label: {position: 'rt', offset: [10, 15], parse: false, fontSize: 12},
        ticks: {insertTicks: false, ticksDistance: 5, minorTicks: 1} }, },
        zoom: {enabled: false, wheel: false},
        pan: {enabled: false, needTwoFingers: false},
        showCopyright: false, showNavigation: false
        });
        // console.log(brd);

        // Define elements on brd
        brd.create('functiongraph', [function(x) {return 1.4*(Math.sqrt(1.5+320*Math.pow(0.3964+x-uS,2))+17.889*(0.3964+x-uS));}, 0, 3], attrLine);

    </jsxgraph>
</p><br>]]></text>
<file name="fig_Baseballwerfer.jpg" path="/" 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</file>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>5.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>uS = {1.9:2.9:0.2}; 
vSource = {4.7:9.9:0.2};</text>
</varsrandom>
<varsglobal><text></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 2;
origSol = uS * 0.020;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.6*critMantRnd1, 0.3*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + 0.7*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Wie hoch ist die elektrische Leistung der LED im vorgesehenen Betrieb? [2P]</p>
<p> {_0}\(\;\mathrm{W}\)  (Angabe mit {nSigFig} signifikanten Stellen ohne Einheit)</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>3</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 2;
origSol = (vSource - uS) / 0.020;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.8*critMantRnd1, 0.6*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + 0.7*critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Um die LED an einer Spannungsquelle mit \({vSource}\,\mathrm{V}\) Ausgangsspannung betreiben zu können, muss man ihr einen Widerstand vorschalten. Welchen Widerstandswert muss dieser Widerstand haben? [3P]</p>
<p> {_0}\(\;\mathrm{\Omega}\)  (Angabe mit {nSigFig} signifikanten Stellen ohne Einheit)</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
    <tags>
      <tag><text>JXG</text>
</tag>
    </tags>
  </question>

<!-- question: 8098  -->
  <question type="formulas">
    <name>
      <text>Leistungsverlust in einer Stromleitung</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>In einer Stromleitung mit \( {R} \,\mathrm{\Omega} \) Widerstand fliessen \( {J} \,\mathrm{A} \) Strom. Wie gross ist die Heizleistung, welche in Form von Wärme «verloren» geht?</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>R = {1.5:8.9:0.2};
J = {31:99:2};</text>
</varsrandom>
<varsglobal><text>P =sigfig( R * J**2 , 2);</text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>P</text>
 </answer>
 <vars2>
  <text><![CDATA[sol = P;
origAns = _0;

# Fully correct solution
crit1 = 1 * ( abs(origAns - sol)/sol <= 0.01000001 );

# Reduced points for wrong precision
crit2 = 0.8 * ( abs(origAns - sol)/sol <= 0.10000001 );

# Half the points for wrong order of magnitude or precision
mantAns = origAns / ( 10**(floor( log10(origAns)) ));
mantSol =  sol / ( 10**(floor( log10(sol)) ));
crit3 = 0.5 * ( abs(mantAns - mantSol)/mantSol <= 0.010000001 );

grade = max(crit1,crit2,crit3);]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>W</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>&emsp;{_0}{_u}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>top/4 Elektrizität/Ströme und Magnetfelder</text>
    </category>
    <info format="moodle_auto_format">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 8108  -->
  <question type="formulas">
    <name>
      <text>Anziehung/Abstossung zweier Elektromagnete</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Die Abbildung zeigt ein Paar von Elektromagneten.</p>

<br><p><img alt="" class="img-responsive" src="@@PLUGINFILE@@/fig_Elektromagnet_{= fileNames[jL]}.jpg" width="200px"/><img alt="" class="img-responsive" src="@@PLUGINFILE@@/fig_Elektromagnet_{= fileNames[jR]}.jpg" width="200px"/></p><br>]]></text>
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</file>
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</file>
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</file>
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</file>
    </questiontext>
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      <text></text>
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    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jL = {0:4};
jR = {0:4};</text>
</varsrandom>
<varsglobal><text><![CDATA[fileNames = ["LH_MP","LH_PM","RH_MP","RH_PM"];

# +1 if north pole is on the left, -1 if south pole is on the left
magnetTypes = [-1,+1,+1,-1];

# Solution
jSol = round( 0.5 + 0.5 * magnetTypes[jL] * magnetTypes[jR] );
strForce = ["Die Elektromagnete stossen sich ab.", "Die Elektromagnete ziehen sich an."];]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
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  <text></text>
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  <text>1</text>
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 <vars1>
  <text></text>
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 <answer>
  <text>jSol</text>
 </answer>
 <vars2>
  <text></text>
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 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
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 <unitpenalty>
  <text>0.2</text>
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 <ruleid>
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 <subqtext format="markdown">
<text><![CDATA[Was stimmt?
<p>&emsp;{_0:strForce:MCE}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 8109  -->
  <question type="formulas">
    <name>
      <text>Hochspannungsleitung (Nord-Süd)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Karl geht im Zürcher Oberland unter einer Hochspannungsleitung durch, die in \({height}\,\mathrm{m}\) Höhe von Norden nach Süden verläuft. Die Distanz zwischen den beiden Pfosten beträgt \({length}\,\mathrm{m}\).</p>

<br><p><img alt="" class="img-responsive" src="@@PLUGINFILE@@/HochspannungsleitungNordS%C3%BCd.jpg" width="500px"/></p><br>

<p>Durch die Leitung fliesst ein Strom von \({current}\,\mathrm{A}\) in Richtung {strDirCurrent}. Das Erdmagnetfeld hat einen Betrag von \(47\,\mathrm{\mu T}\), die Inklination der Erdmagnetfeldlinien beträgt \(65^\circ\).</p>]]></text>
<file name="HochspannungsleitungNordSüd.jpg" path="/" 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</file>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>current = {17:40};
height = {13:26};
length = {130:270:10};
dirJ = {2,3};</text>
</varsrandom>
<varsglobal><text><![CDATA[directionsCurrent = ["","","Süden","Norden"];
directionsForce = ["Nach oben.","Nach unten.","Nach Osten.","Nach Westen."];

strDirCurrent = directionsCurrent[dirJ];
strDirForce = directionsForce[dirJ];

magneticB = 47e-6;
FB = current * length * magneticB * sin(deg2rad(65));]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>nSigFig = 2;
origSol = FB;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)));
mantSol = origSol / ( 10**( expSol ));

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
  divTest = ( round( 10**(i+1) * abs(mantAns) , 6 ) ) % 10;
  nSigFigAns = ( divTest > 0.5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct exponent
critExp= ( abs(expAns-expSol) < 0.5 );

# Correct number of significant figures
critSigFig = ( abs(nSigFigAns-nSigFig) < 1.5 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs(mantAns - mantSolSFA) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs(mantAns - mantSolSFA) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs(mantAns - mantSolSFA) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( 0.7*critMantCorrect, 0.6*critMantRnd1, 05*critMantRnd2 );
grade = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + critMant : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>N</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text>N: c;</text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Wie gross ist die magnetische Kraft auf die Leitung zwischen den zwei Pfosten? [67%]</p>
<p>&emsp;{_0}{_u}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>dirJ</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>In welche Richtung zeigt diese magnetische Kraft? [33%]</p>
<p>&emsp;{_0:directionsForce:MCE}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>top/4 Elektrizität/Induktion</text>
    </category>
    <info format="moodle_auto_format">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 8116  -->
  <question type="formulas">
    <name>
      <text>Diagramme: Phi(t) und Uind(t) aus Daten</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Eine Leiterschleife mit angeschlossenem Voltmeter befinde sich in einem Magnetfeld, welches sich abschnittsweise linear mit der Zeit verändert. Zu Beginn sei die Leiterschleife von einem magnetischen Fluss von \({x0}\,\mathrm{Wb}\) durchdrungen. Dann ändert sich das Magnetfeld so, dass 
<ul>
<li>sich der magnetische Fluss in \({Dt1}\,\mathrm{s}\) um \({=x1-x0}\,\mathrm{Wb}\) ändert,</li>
<li>nach weiteren \({Dt2}\,\mathrm{s}\) den Wert \({x2}\,\mathrm{Wb}\) annimmt und</li>
<li>in den letzten \({Dt3}\,\mathrm{s}\) eine Spannung von \({v3}\,\mathrm{V}\) induziert werde.</li>
</ul>
</p>
<p>Stellen Sie den Vorgang in beiden Diagrammen richtig dar. Am besten beginnen Sie damit, mit den roten Punkten im \(U_\mathrm{ind}(t)\)-Diagramm die Zeitspannen richtig einzustellen, indem Sie sie horizontal verschieben. Dann können Sie alle roten Punkte vertikal bei den richtigen Werten platzieren.</p>
<br>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>6.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>t1 = {1,2,3,4}; t2 = {5,6,7}; t3 = {8,9,10,11};
vArray = shuffle([-3:3.1:0.1]);
x0 = {-10:10.1:0.1};</text>
</varsrandom>
<varsglobal><text><![CDATA[t0 = 0; x0 = round( x0 , 1 );
Dt1 = t1 - t0; Dt2 = t2-t1; Dt3 = t3-t2;
xMax = 10; xMin = -10;

v1 = round( vArray[0] , 1);
for (j:[1:7]) { v1 = ( x0-v1*Dt1 > xMax) ? (v1 + 0.5) : ( ( x0-v1*Dt1 < xMin) ? (v1 - 0.5) : v1 ); }
Dx1 = round( -v1*Dt1 , 1);
x1 = x0 + Dx1;

v2= round( vArray[1] , 1);
for (j:[1:7]) { v2 = ( x1-v2*Dt2 > xMax) ? (v2 + 0.5) : ( ( x1-v2*Dt2 < xMin) ? (v2 - 0.5) : v2 ); }
Dx2 = round( -v2*Dt2 , 1);
x2 = x1 + Dx2;

v3 = round( vArray[2] , 1);
for (j:[1:7]) { v3 = ( x2-v3*Dt3 > xMax) ? (v3 + 0.5) : ( ( x2-v3*Dt3 < xMin) ? (v3 - 0.5) : v3 ); }
Dx3 = round( -v3*Dt3 , 1);
x3 = x2 + Dx3;]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>6</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>9</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[t1,t2,t3 , v1,v2,v3 , x1,x2,x3]</text>
 </answer>
 <vars2>
  <text><![CDATA[S_t1 = _0;
S_t2 = _1;
S_t3 = _2;
S_v1 = _3;
S_v2 = _4;
S_v3 = _5;
S_x1 = _6;
S_x2 = _7;
S_x3 = _8;

S_Dx1 = S_x1-x0;
S_Dx2 = S_x2-S_x1;
S_Dx3 = S_x3-S_x2;

crit_t1 = ( abs( S_t1 - t1 ) < 0.01 );
crit_t2 = ( abs( S_t2 - t2 ) < 0.01 );
crit_t3 = ( abs( S_t3 - t3 ) < 0.01 );

crit_v1 = ( abs( S_v1 - v1 ) < 0.01 );
crit_v2 = ( abs( S_v2 - v2 ) < 0.01 );
crit_v3 = ( abs( S_v3 - v3 ) < 0.01 );

crit_Dx1 = ( abs( S_Dx1 - Dx1) <0.01 );
crit_Dx2 = ( abs( S_Dx2 - Dx2) <0.01 );
crit_Dx3 = ( abs( S_Dx3 - Dx3) <0.01 );

crit_tot = ( crit_t1 + crit_t2 + crit_t3 + 2*crit_Dx1 + 2*crit_Dx2 + 2*crit_Dx3 + crit_v1 + crit_v2 + crit_v3) / 12;]]></text>
 </vars2>
 <correctness>
  <text>crit_tot</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<jsxgraph width="400" height="300" numberOfBoards="2" ext_formulas>

// JavaScript code to create the construction.
var jsxCode = function (question) {
  
  // Import final coordinates after submission
  var x0={x0};
  var t1,t2,t3 , v1,v2,v3 , x1,x2,x3;
  [t1,t2,t3 , v1,v2,v3 , x1,x2,x3] = 
  question.getAllValues([1,2,3 , 1,2,3 , x0,x0,x0 ]);
  
  JXG.Options.point.infoboxDigits = 1;
  JXG.Options.point.snapSizeX = 1;
  JXG.Options.point.snapSizeY = 0.1;
  
  // Attributes for points and lines
  function attrPfix(addAttr={}) {
    const attr = {fixed: true, visible: false, withLabel: false};
    return { ...attr, ...addAttr}; 
  }
  function attrPmov(addAttr={}) {
    const attr = {fixed: question.isSolved, snapToGrid: true, withLabel: false};
    return { ...attr, ...addAttr};
  }
  function attrPsma(addAttr={}) {
    const attr = {visible: true, withLabel: false, color:'#4285F4', size: 1};
    return { ...attr, ...addAttr};
  }
  const attrLine = {borders: {strokeColor:'#4285F4', strokeWidth: 3} };
  const attrGlid = {visible:false};


  // Create boards
  var brds = question.initBoards( [
  { // attribs for BOARDID0 
    boundingbox: [-1, 12, 13, -11], axis:true,
    defaultAxes: {
      x: {withLabel: true, name: '$$t\\;\\mathrm{(s)}$$',
          label: {position: 'rt', offset: [10, 26], anchorX: 'right', parse: false, fontSize: 12 } },
      y: {withLabel:true, name: '$$\\Phi_\\mathrm{m}\\;\\mathrm{(Wb)}$$',
          label: {position: 'rt', offset: [10, 15], parse: false, fontSize: 12 } } },
      zoom: {enabled:false, wheel: false}, pan: {enabled:false, needTwoFingers: false},
      showCopyright: false, showNavigation: false 
    },
    { // attribs for BOARDID1 
    boundingbox: [-1, 3.8, 12, -3.5], axis:true,
    defaultAxes: {
      x: {withLabel: true, name: '$$t\\;\\mathrm{(s)}$$',
          label: {position: 'rt', offset: [10, 26], anchorX: 'right', parse: false, fontSize: 12 } },
      y: {withLabel:true, name: '$$U_\\mathrm{ind}\\;\\mathrm{(V)}$$',
          label: {position: 'rt', offset: [10, 15], parse: false, fontSize: 12 } } },
      zoom: {enabled:false, wheel: false}, pan: {enabled:false, needTwoFingers: false},
      showCopyright: false, showNavigation: false
    }
  ] );

  var brd0 = brds[0];
  var brd1 = brds[1];
  // console.log(brd0, brd1);

  // Board brd0 needs to be updated when changes in brd1 occur
  // question.addChildsAsc();
  

  // Define lines and points on brd1
  var pV1 = brd1.create('point',  [t1, v1], attrPmov({name: "pV1"}) ),
      pV2 = brd1.create('point',  [t2, v2], attrPmov({name: "pV2"}) ),
      pV3 = brd1.create('point',  [t3, v3], attrPmov({name: "pV3"}) ),
      pV01 = brd1.create('point', [0, "Y(pV1)"], attrPsma() ),
      pV12 = brd1.create('point', ["X(pV1)", "Y(pV2)"], attrPsma() ),
      pV23 = brd1.create('point', ["X(pV2)", "Y(pV3)"], attrPsma() )    ;
      pV34 = brd1.create('point', ["X(pV3)", 0], attrPsma() )    ;
  brd1.create('polygonalchain', [ pV01, pV1, pV12, pV2, pV23, pV3, pV34 ], attrLine);
  

  // Define lines and points on brd0
  var pX0 = brd0.create('point', [0, x0], attrPsma({fixed: true}) ),
      pX1 = brd0.create('point', [t1, x1], attrPmov({face: 'diamond'}) ),
      pX2 = brd0.create('point', [t2, x2], attrPmov({face: 'diamond'}) ),
      pX3 = brd0.create('point', [t3, x3], attrPmov({face: 'diamond'}) );
  brd0.create('polygonalchain', [ pX0, pX1, pX2, pX3 ], attrLine);
  

  // Define dependencies
  pV1.on('drag', function() { pX1.moveTo([this.X(), pX1.Y()], 0); });
  pV2.on('drag', function() { pX2.moveTo([this.X(), pX2.Y()], 0); });
  pV3.on('drag', function() { pX3.moveTo([this.X(), pX3.Y()], 0); });
  // pX1.on('drag', function() { pV1.moveTo([this.X(), pV1.Y()], 0); });
  // pX2.on('drag', function() { pV2.moveTo([this.X(), pV2.Y()], 0); });
  // pX3.on('drag', function() { pV3.moveTo([this.X(), pV3.Y()], 0); });
  pX1.on('drag', function() { this.moveTo([pV1.X(), this.Y()], 0); });
  pX2.on('drag', function() { this.moveTo([pV2.X(), this.Y()], 0); });
  pX3.on('drag', function() { this.moveTo([pV3.X(), this.Y()], 0); });
  

  // Whenever the construction is altered the values of the points are sent to formulas.
  question.bindInput(0, () => { return pV1.X(); });
  question.bindInput(1, () => { return pV2.X(); });
  question.bindInput(2, () => { return pV3.X(); });
  question.bindInput(3, () => { return pV1.Y(); });
  question.bindInput(4, () => { return pV2.Y(); });
  question.bindInput(5, () => { return pV3.Y(); });
  question.bindInput(6, () => { return pX1.Y(); });
  question.bindInput(7, () => { return pX2.Y(); });
  question.bindInput(8, () => { return pX3.Y(); });
  };
  
  // Execute the JavaScript code.
  new JSXQuestion(BOARDIDS, jsxCode, allowInputEntry=false); // use BOARDIDS here!!
  
</jsxgraph>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
    <tags>
      <tag><text>JXG</text>
</tag>
    </tags>
  </question>

<!-- question: 8117  -->
  <question type="formulas">
    <name>
      <text>Sinusfunktion: Graphen für U_ind verschieben</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Die blau dargestellte Kurve zeigt den zeitabhängigen magnetischen Fluss durch eine Leiterschleife.</p>
<p>Bewegen Sie mit dem roten Punkt die Kurve für die induzierte Spannung so, dass sie zur blauen Kurve passt.</p>
<br>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>yA = {1.0:2.0:0.1};
yT = {1,2,3,4};
yP = {0:1:0.1};</text>
</varsrandom>
<varsglobal><text>yt0 = yP * yT;
at0 = fmod(yP+1+0.25,1) * yT;
at0Alt = fmod(yP+1+0.75,1) * yT;</text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>at0</text>
 </answer>
 <vars2>
  <text><![CDATA[aErr = abs( fmod(_0,yT) - at0 );
aErrAlt = abs( fmod(_0,yT) - at0Alt );

gradeCor = max( 1.0*( aErr < 0.01 ) , 0.5*( aErr < 0.06 ) );
gradeAlt = max( 1.0*( aErrAlt < 0.01 ) , 0.5*( aErrAlt < 0.06 ) );

grade = max( gradeCor, 0.5*gradeAlt );]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<jsxgraph width="800" height="400" ext_formulas>

var jsxCode = function (question) {

JXG.Options.point.showInfobox = false;
JXG.Options.point.snapSizeX = 0.05;
JXG.Options.point.snapSizeY = 0.1;

const col1 = '#4285F4', col2 = '#EA4335', col3 = '#34A853', col4 = '#FBBC05';
const colVecN = '#4285F4', colVecS = '#EA4335', colVecC = '#34A853';

const yA = {yA}, yT = {yT}, yt0 = {yt0}, aA = yA-0.5;
var at0;
[at0] = question.getAllValues([yt0+yT]);


var brd = question.initBoard(BOARDID, {
	boundingbox: [-0.5, 3, 10, -3], axis: false, 
	zoom: {enabled: false, wheel: false},
	pan: {enabled: false, needTwoFingers: false},
	showCopyright: false, showNavigation: false
});
// console.log(brd);

brd.create('axis', [ [0,0],[9.4,0] ], {
	straightFirst: false, straightLast: false,
	withLabel: true, name: 't (s)', /* name: '$$x\\;\\mathrm{(m)}$$', */
    label: {position: 'rt', offset: [0, 15], anchorX: 'right', parse: false, fontSize: 12 },
	ticks: {ticksDistance: 1, insertTicks: false, minorTicks: 4,
        tickEndings: [1,1], majorHeight: ()=>2*2*brd.unitY, minorHeight: ()=>2*2*brd.unitY,
        label: {anchorX: 'middle', anchorY: 'top', offset: [0,-3] } }
	});
brd.create('axis', [ [0,-2.4],[0,2.4] ], {
	straightFirst: false, straightLast: false,
	withLabel: false, name: 'y (m)', /* name: '$$x\\;\\mathrm{(m)}$$', */
    label: {position: 'rt', offset: [12, -3], anchorX: 'left', parse: false, fontSize: 12 },
	ticks: {ticksDistance: 10, insertTicks: false, minorTicks: 0, drawZero: true,
        tickEndings: [0,0], majorHeight: ()=>5*2*brd.unitX, minorHeight: ()=>5*2*brd.unitX,
		label: {anchorX: 'right', anchorY: 'middle', offset: [-3,0] } }
	}); 


const pY = brd.create('point', [yt0, yA], {
	fixed: true, color:col1, size:0,
	withLabel: true, name:'Φ_m', label: {offset: [4, 8], color:col1, fontSize: 14 } });
brd.create('functiongraph', [function(t) {return yA*Math.cos(2*Math.PI*(t-pY.X())/yT); }, 0, 9.4], {
	strokeColor: col1, strokeWidth: 2 });

var pA = brd.create('point', [at0, aA], {
	fixed: question.isSolved, snapToGrid: true, color:col2,
	withLabel: true, name:'U_{ind}', label: {offset: [4, 10], color:col2, fontSize: 14 } });
pA.on('drag', function() { pA.moveTo([Math.max(0,Math.min(9,this.X())), aA], 0); });
brd.create('functiongraph', [function(t) {return aA*Math.cos(2*Math.PI*(t-pA.X())/yT); }, 0, 9.4], {
	strokeColor: col2, strokeWidth: 2 });


question.bindInput(0, () => { return pA.X(); });
};

new JSXQuestion(BOARDID, jsxCode, allowInputEntry=false);

</jsxgraph>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
    <tags>
      <tag><text>JXG</text>
</tag>
    </tags>
  </question>

<!-- question: 8118  -->
  <question type="formulas">
    <name>
      <text>Transformator</text>
    </name>
    <questiontext format="markdown">
      <text><![CDATA[<p>Sie haben ein elektrisches Gerät, welches Sie am Haushaltsnetz betreiben möchten. Das Gerät soll mit einer effektiven Spannung von \({voltage2}\,\mathrm{V}\) betrieben werden. Dazu müssen Sie die Haushaltsspannung mit Hilfe eines Transformators anpassen.</p>

<p>Sie besitzen bereits eine Spule mit \({coilN}\) Windungen und stellen die folgenden Überlegungen an, bevor Sie zu dem Elektrofachhandel Ihres Vertrauens gehen, um eine zweite Spule zu kaufen.</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>4.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>coilN = {100,250,500,1000};
voltage2 = {5,10,20,30,40,60,80,120,140,160,290,310,330,350,370,390};</text>
</varsrandom>
<varsglobal><text>voltage1 = 230;

coilN2 = round( voltage2 / voltage1 * coilN );
coilN1 = round( voltage1 / voltage2 * coilN );</text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>coilN2</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;
sol = coilN2;
altSol = coilN1;

# Fully correct solution
crit1 = 1 * ( abs(origAns - sol) < 1.5 );

# Reduced points for solution to other part
crit2 = 0.33 * ( abs(origAns - altSol) < 1.5 );

grade = max(crit1,crit2);]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>Wie viele Windungen müsste die zu kaufende Spule idealerweise haben, wenn Sie Ihre <u>bereits vorhandene Spule als Primärspule</u> im Transformator einsetzen? [2P]</p>
<p>&emsp;{_0} (Eingabe gerundet auf ganze Zahl)</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>coilN1</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;
sol = coilN1;
altSol = coilN2;

# Fully correct solution
crit1 = 1 * ( abs(origAns - sol) < 1.5 );

# Reduced points for solution to other part
crit2 = 0.33 * ( abs(origAns - altSol)< 1.5 );

grade = max(crit1,crit2);]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>Wie viele Windungen müsste die zu kaufende Spule idealerweise haben, wenn Sie Ihre <u>bereits vorhandene Spule als Sekundärspule</u> im Transformator einsetzen? [2P]</p>
<p>&emsp;{_0} (Eingabe gerundet auf ganze Zahl)</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>top/4 Elektrizität/Elektrischer Widerstand</text>
    </category>
    <info format="moodle_auto_format">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 8144  -->
  <question type="formulas">
    <name>
      <text>Durchmesser eines Drahtes mit gegebenem Widerstand</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Ein Draht aus {strMetal} besitze eine Länge von \( {L} \,\mathrm{m} \). Welchen Durchmesser muss der Draht mindestens haben, damit sein Widerstand nicht \( {R} \,\mathrm{\Omega} \) überschreitet?</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>4.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jMetal = {0:6};

L = {230:570:10};
R = {1.1:8.6:0.2};</text>
</varsrandom>
<varsglobal><text><![CDATA[strMetals =["Aluminium", "Konstantan", "Kupfer", "Messing", "Silber", "Wolfram"];
numRohs = [2.650, 49, 1.754, 8.0, 1.587, 5.5];


strMetal = strMetals[jMetal];
rho = numRohs[jMetal];

D = sqrt( (4 * L * rho * 1e-8) / ( pi() * R) );]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>4</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>Diameter = D;
Radius = sqrt( ( L * rho * 1e-8) / ( pi() * R) );
Area = ( L * rho * 1e-8) / R ;

nSigFig = 2;
origSol = Diameter;
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
    shiftedNum = round( 10**(i) * abs(mantAns) , 6 );
    divTest = round( shiftedNum - floor(shiftedNum) , 6);
    nSigFigAns = ( divTest > 1e-5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct number of significant figures
critSigFig = ( abs( nSigFigAns - nSigFig ) < 1.1 );




####### Evaluate for Diameter

origSol = Diameter;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.8*critMantRnd1, 0.6*critMantRnd2 );
gradeD = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + 0.7*critMant : 0;




####### Evaluate for Radius

origSol = Radius;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.8*critMantRnd1, 0.6*critMantRnd2 );
gradeR = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + 0.7*critMant : 0;




####### Evaluate for cross sectional Area

origSol = Area;

# Analyze solution for mantissa, exponent, significant figures
expSol = floor( log10(abs(origSol)) );
mantSol = origSol / ( 10**( expSol ));

# Correct exponent
critExp= ( abs( expAns - expSol ) < 0.1 );

# Correct mantissa with respect to significant figures
mantSolSFA = sigfig( mantSol , nSigFigAns );
critMantCorrect = ( abs( mantAns - mantSolSFA ) < 0.5 * 0.1**(nSigFigAns-1) );

# Mantissa with rounding errors with respect to significant figures
critMantRnd1 = ( abs( mantAns - mantSolSFA ) < 1.5 * 0.1**(nSigFigAns-1) );
critMantRnd2 = ( abs( mantAns - mantSolSFA ) < 2.5 * 0.1**(nSigFigAns-1) );

# Calculate grade
critMant = max( critMantCorrect, 0.8*critMantRnd1, 0.6*critMantRnd2 );
gradeA = ( critMant > 0 ) ? 0.2*critExp + 0.1*critSigFig + 0.7*critMant : 0;




####### Calculate final Grade

grade = max( gradeD, 0.75*gradeR, 0.5*gradeA );]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>m</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>&emsp;{_0}{_u}&emsp; (Angabe mit Einheit)</p>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p>Der Durchmesser berechnet sich aus:</p>
\[ d = \sqrt{ \frac{ 4 \cdot l \cdot \rho_\mathrm{el} }{ \pi \cdot R } } = {= sigfig( Diameter * 1e3 , nSigFig)}\,\mathrm{mm} \]

<p>3 Punkte gibt es für die Berechnung des Radius (\( {=sigfig( Radius * 1e3 , nSigFig)}\,\mathrm{mm} \)).</p>

<p>2 Punkte gibt es für die Berechnung der Querschnittsfläche (\( {=sigfig( Area * 1e6 , nSigFig)}\,\mathrm{mm^2} \)).]]></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 8145  -->
  <question type="formulas">
    <name>
      <text>Länge eines Drahtes mit gegebenem Widerstand</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Ein Draht aus {strMetal} besitze eine Querschnittsfläche von \( {A} \,\mathrm{mm^2} \). Wie viele Meter dieses Drahts sind notwendig, um einen Widerstand von \( {R} \,\mathrm{\Omega} \) hervorzurufen?</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>3.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jMetal = {0:6};

A = {0.15:1:0.1};
R = {1.1:3.6:0.1};</text>
</varsrandom>
<varsglobal><text><![CDATA[strMetals =["Aluminium", "Konstantan", "Kupfer", "Messing", "Silber", "Wolfram"];
numRohs = [2.650, 49, 1.754, 8.0, 1.587, 5.5];


strMetal = strMetals[jMetal];
rho = numRohs[jMetal];
L = sigfig( R * A * 1e-6 / (rho * 1e-8) , 2 );]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>3</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>L</text>
 </answer>
 <vars2>
  <text><![CDATA[sol = L;
origAns = _0;

# Fully correct solution
crit1 = 1 * ( abs(origAns - sol)/sol <= 0.03000001 );

# Reduced points for wrong precision
crit2 = 0.8 * ( abs(origAns - sol)/sol <= 0.10000001 );

# Half the points for wrong order of magnitude or precision
mantAns = origAns / ( 10**(floor( log10(origAns)) ));
mantSol =  sol / ( 10**(floor( log10(sol)) ));
crit3 = 0.5 * ( abs(mantAns - mantSol)/mantSol <= 0.030000001 );

grade = max(crit1,crit2,crit3);]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text>m</text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>&emsp;{_0}{_u}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

<!-- question: 0  -->
  <question type="category">
    <category>
      <text>top/4 Elektrizität/Bewegte Ladungen im Magnetfeld</text>
    </category>
    <info format="moodle_auto_format">
      <text></text>
    </info>
    <idnumber></idnumber>
  </question>

<!-- question: 8149  -->
  <question type="formulas">
    <name>
      <text>Bewegte Ladung neben stromführendem Leiter</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>In einem Draht ﬂiesst wie abgebildet ein Strom von {strCurrentDirection}. Ein {strCharge} geladenes Teilchen ﬂiegt {strVeloDirection} zum Draht entlang der {strVeloAxis}-Achse.</p>


<jsxgraph width="500" height="300">

JXG.Options.elements.highlight = false;
JXG.Options.point.showInfobox = false;

const col1='#4285F4', col2='#EA4335', col3='#34A853', col4='#FBBC05';
const colVecN='#4285F4', colVecV='#4CAF50', colVecB='#FBBC05';

const dirI = {jCurrentPM};
const angV = {angVelo} /180*Math.PI;
const charge = {jChargePM};

const brd = JXG.JSXGraph.initBoard(BOARDID, {
	boundingbox:[-5, 3, 5, -3], 
	axis:false, keepaspectratio:false,
    showCopyright:false, showNavigation:false, 
    zoom: {enabled:false, wheel: false}, pan: {enabled:false, needTwoFingers: false},
});


brd.create('arrow', [[-3,-1.5], [-1.8,-1.5]], {fixed: true, color:'#000000', name:'x', 
	withLabel:true, label:{offset:[2,7], fontSize:12}} );
brd.create('arrow', [[-3,-1.5], [-2.1,-0.6]], {fixed: true, color:'#000000', name:'y',
	withLabel:true, label:{offset:[4,4], fontSize:12}} );
brd.create('arrow', [[-3,-1.5], [-3,-0.2]], {fixed: true, color:'#000000', name:'z', 
	withLabel:true, label:{offset:[6,3], fontSize:12}} );


brd.create('segment', [[3,-2],[3,+2]], {fixed:true, strokeWidth:9, color:'#aaaaaaaa'});
if (dirI == 0) {
	brd.create('arrow', [[3,+1.5], [3,+2.8]], {fixed: true, strokeWidth:3, strokeColor:col2 } );
	brd.create('text', [3.3,+2.8,'$$I$$'], {fixed: true, parse:false, color:col2, fontSize:20} );
} else {
	brd.create('arrow', [[3,-1.5], [3,-2.8]], {fixed: true, strokeWidth:3, strokeColor:col2 } );
	brd.create('text', [3.3,-2.0,'$$I$$'], {fixed: true, parse:false, color:col2, fontSize:20} );
}


if (charge == 0) {
	brd.create('point', [1,0], { fixed:true, color:col2, name:'+', size:7,
		withLabel:true, label:{offset:[-4.3,-0.5], color:'#FFFFFF', fontSize:16} } );
} else {
	brd.create('point', [1,0], { fixed:true, color:col1, name:'–', size:7,
		withLabel:true, label:{offset:[-4.5,0.8], color:'#FFFFFF', fontSize:16} } );
}
brd.create('arrow', [[1,0], [1+1.3*Math.cos(angV),1.3*Math.sin(angV)]], {fixed: true, 
	strokeWidth:3, strokeColor:colVecV} );
brd.create('text', [1+1.2*Math.cos(angV+0.35)-0.15,1.2*Math.sin(angV+0.35)+0.4,'$$\\vec{v}$$'], {fixed: true, 
	parse:false, color:colVecV, fontSize:20} );


</jsxgraph>
<br>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>2.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jCurrentPM = {0,1};
jVeloXZ = {0,1};
jVeloPM = {0,1};
jChargePM = {0,1};</text>
</varsrandom>
<varsglobal><text><![CDATA[strCurrentDirection = ["unten nach oben", "oben nach unten"][jCurrentPM];
strCharge = ["positiv", "negativ"][jChargePM];
strVeloDirection = ["senkrecht", "parallel"][jVeloXZ];
strVeloAxis = ["x", "z"][jVeloXZ];

angVelo = 90*jVeloXZ + 180*jVeloPM;

strSols = ["+x","-x","+y","-y","+z","-z"];
angSol = ( ( (270+90*jVeloXZ) + 180*jCurrentPM + 180*jVeloPM + 180*jChargePM ) % 360 ) / 90;
jSol = [0,4,1,5][angSol];]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>2</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>jSol</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>In welche Richtung wird es abgelenkt? {_0:strSols:MCE}</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
    <tags>
      <tag><text>JXG</text>
</tag>
    </tags>
  </question>

<!-- question: 8150  -->
  <question type="formulas">
    <name>
      <text><![CDATA[Magnetische Kraft Richtungen: B, FB > v]]></text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Ein <u>{strCharge}</u> bewegt sich durch ein homogenes Magnetfeld \(\vec{B}\) und erfährt die magnetische Kraft \(\vec{F}_\mathrm{B}\).</p>

<p>Verschieben Sie den roten Punkt, sodass der Vektor für seine Geschwindigkeit in die richtige Richtung zeigt.</p>

<p>Alle drei physikalischen Grössen sind ausgerichtet entlang kartesischer Koordinatenachsen (\(x\), \(y\) und \(z\)), welche paarweise senkrecht zueinander sind. Die Abbildung zeigt das Koordinatensystem in einer üblichen perspektivischen Darstellung.</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jCharge = {0, 1};
jDir = {0:24};</text>
</varsrandom>
<varsglobal><text><![CDATA[arrDirV = [1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5,6,6,6,6];
arrDirB = [2,3,5,6,1,3,4,6,1,2,4,5,2,3,5,6,1,3,4,6,1,2,4,5];
arrDirF = [3,5,6,2,6,1,3,4,2,4,5,1,6,2,3,5,3,4,6,1,5,1,2,4];

angles = [0,345,25,90,165, 205,270];

signCharge = [1,-1][jCharge];
strCharge = ["Proton","Elektron"][jCharge];

angV = angles[arrDirV[jDir]];
angB = angles[arrDirB[jDir]];
angF = angles[arrDirF[jDir]];
angF = (angF > 0) ? (angF + jCharge * 180) : angF;

angV = (angV > 360) ? (angV - 360) : angV;
angV = (angV > 180) ? (angV - 360) : angV;

strVelocity = ["ist Null","zeigt in die positive x-Richtung","zeigt in die positive y-Richtung","zeigt in die positive z-Richtung","zeigt in die negative x-Richtung","zeigt in die negative y-Richtung","zeigt in die negative z-Richtung"][arrDirV[jDir]];]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text></text>
 </vars1>
 <answer>
  <text>[angV]</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 5]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<jsxgraph width="300" height="300" numberOfBoards="1" ext_formulas>

// JavaScript code to create the construction.
var jsxGraphCode = function (question) {

  JXG.Options.arrow.lastArrow.size = 4;
  JXG.Options.arrow.lineCap = 'round';
  JXG.Options.point.showInfobox = false;


  // Attributes for points and lines

  const col1='#4285F4', col2='#EA4335', col3='#34A853', col4='#FBBC05';
  const colVecN='#4285F4', colVecV='#4CAF50', colVecB='#FBBC05';

  function attrPfix(addAttr={}) {
    const attrLook = {size:1, color:'none', withLabel: true, label:{ color:'#666666' } };
    const attrFunc = {fixed:true };
    return { ...attrLook, ...attrFunc, ...addAttr};
  }

  function attrPmov(addAttr={}) {
    const attrLook = {size:2, withLabel:false};
    const attrFunc = {fixed: question.isSolved, attractors: [pO,lX,lY,lZ], attractorDistance:0.5, snatchDistance: 0};
    return { ...attrLook, ...attrFunc, ...addAttr};
  }

  function attrVec(addAttr={}) {
    const attrLook = { strokeWidth:3, strokeColor:colVecN, withLabel:false };
    const attrFunc = { fixed:true };
    return { ...attrLook, ...attrFunc, ...addAttr};
  }
  function attrLaxis(addAttr={}) {
    const attrLook = { strokeWidth:1, strokeColor:'#666666', withLabel:false };
    const attrFunc = { fixed:true };
    return { ...attrLook, ...attrFunc, ...addAttr};
  }

  const attrPhidden = {fixed:true, color:'none', withLabel:false };



  function Ang2Coords (ang, radius=2) {
    const x = radius * Math.cos(Math.PI * ang / 180);
    const y = radius * Math.sin(Math.PI * ang / 180);
    return (ang==0) ? [0,0] : [x,y];
  }


  // Import parameters from Formulas
  var [angV] = question.getAllValues([315]);
  const angB = {angB};
  const angF = {angF};
  const colCharge = ( {signCharge} > 0 ) ? col2 : col1;


  // Create boards
  var brd0 = question.initBoard(BOARDID0, { 
    boundingbox:[-3, 3, 3, -3], axis:false, keepaspectratio:true,
    showCopyright:false, showNavigation:false, 
    zoom: {enabled:false, wheel: false}, pan: {enabled:false, needTwoFingers: false},
  });
  console.log(brd0);
  

  // Define elements on brd0
  brd0.suspendUpdate();

  const pX = brd0.create('point', Ang2Coords(345, 2.5), attrPfix({ name:'$$x$$', label:{offset:[0,20]} }) );
  const pY = brd0.create('point', Ang2Coords( 25, 2.5), attrPfix({ name:'$$y$$', label:{offset:[0,25]} }) );
  const pZ = brd0.create('point', Ang2Coords( 90, 2.5), attrPfix({ name:'$$z$$', label:{offset:[5,15]} }) );

  const lX = brd0.create('line', [[0,0],pX], attrLaxis({}) );
  const lY = brd0.create('line', [[0,0],pY], attrLaxis({}) );
  const lZ = brd0.create('line', [[0,0],pZ], attrLaxis({}) );

  var pO = brd0.create('point', [0,0], { fixed:true, color:colCharge, withLabel:false, size:6 } );
  var pV = brd0.create('point', Ang2Coords(angV), attrPmov({}));
  
  brd0.create('arrow', [pO, Ang2Coords(angF)], attrVec({}) );
  brd0.create('arrow', [pO, pV], attrVec({ strokeColor:colVecV }) );
  brd0.create('arrow', [pO, Ang2Coords(angB)], attrVec({ strokeColor:colVecB }) );

  brd0.create('text', [1.2,-2.35,'$$\\vec{v}$$'], {fixed: true, parse:false, color:colVecV, fontSize:16} );
  brd0.create('text', [1.7,-2.3,'$$\\vec{B}$$'], {fixed: true, parse:false, color:colVecB, fontSize:16} );
  brd0.create('text', [2.2,-2.3,'$$\\vec{F}_\\mathrm{B}$$'], {fixed: true, parse:false, color:colVecN, fontSize:16} );

  brd0.unsuspendUpdate();



  // Whenever the construction is altered the values of the points are sent to formulas.
  question.bindInput(0, () => { return Math.round(Math.atan2(pV.Y(), pV.X()) * 180 / Math.PI) ; });

};

// Execute the JavaScript code.
new JSXQuestion(BOARDIDS, jsxGraphCode, allowInputEntry=false);

</jsxgraph>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p>Korrekte Lösung: Der Geschwindigkeitsvektor {strVelocity}.</p>]]></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
    <tags>
      <tag><text>JXG</text>
</tag>
    </tags>
  </question>

<!-- question: 8151  -->
  <question type="formulas">
    <name>
      <text><![CDATA[Magnetische Kraft Richtungen: v, B > FB]]></text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Ein <u>{strCharge}</u> bewegt sich mit der Geschwindigkeit \(\vec{v}\) durch ein homogenes Magnetfeld \(\vec{B}\).</p>

<p>Verschieben Sie den roten Punkt, sodass der Vektor für die magnetische Kraft in die richtige Richtung zeigt. Verschieben Sie ihn in den Ursprung, falls die magnetische Kraft Null ist.</p>

<p>Alle drei physikalischen Grössen sind ausgerichtet entlang kartesischer Koordinatenachsen (\(x\), \(y\) und \(z\)), welche paarweise senkrecht zueinander sind. Die Abbildung zeigt das Koordinatensystem in einer üblichen perspektivischen Darstellung.</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jCharge = {0, 1};
jDir = {0:30};</text>
</varsrandom>
<varsglobal><text><![CDATA[arrDirV = [1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4,5,5,5,5,5,6,6,6,6,6];
arrDirB = [2,3,4,5,6,1,3,4,5,6,1,2,4,5,6,1,2,3,5,6,1,2,3,4,6,1,2,3,4,5];
arrDirF = [3,5,0,6,2,6,1,3,0,4,2,4,5,1,0,0,6,2,3,5,3,0,4,6,1,5,1,0,2,4];

angles = [0,345,25,90,165, 205,270];

signCharge = [1,-1][jCharge];
strCharge = ["Proton","Elektron"][jCharge];

angV = angles[arrDirV[jDir]];
angB = angles[arrDirB[jDir]];
angF = angles[arrDirF[jDir]];
angF = (angF > 0) ? (angF + jCharge * 180) : angF;
angF = (angF > 360) ? (angF - 360) : angF;
angF = (angF > 180) ? (angF - 360) : angF;

strForcePos = ["ist Null","zeigt in die positive x-Richtung","zeigt in die positive y-Richtung","zeigt in die positive z-Richtung","zeigt in die negative x-Richtung","zeigt in die negative y-Richtung","zeigt in die negative z-Richtung"][arrDirF[jDir]];
strForceNeg = ["ist Null","zeigt in die negative x-Richtung","zeigt in die negative y-Richtung","zeigt in die negative z-Richtung","zeigt in die positive x-Richtung","zeigt in die positive y-Richtung","zeigt in die positive z-Richtung"][arrDirF[jDir]];
strForce = pick( signCharge > 0 , [strForceNeg, strForcePos] );]]></text>
</varsglobal>
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</answernumbering>
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  <text>[angF]</text>
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<text><![CDATA[<jsxgraph width="300" height="300" numberOfBoards="1" ext_formulas>

// JavaScript code to create the construction.
var jsxGraphCode = function (question) {

  JXG.Options.arrow.lastArrow.size = 4;
  JXG.Options.arrow.lineCap = 'round';
  JXG.Options.point.showInfobox = false;


  // Attributes for points and lines

  const col1='#4285F4', col2='#EA4335', col3='#34A853', col4='#FBBC05';
  const colVecN='#4285F4', colVecV='#4CAF50', colVecB='#FBBC05';

  function attrPfix(addAttr={}) {
    const attrLook = {size:1, color:'none', withLabel: true, label:{ color:'#666666' } };
    const attrFunc = {fixed:true };
    return { ...attrLook, ...attrFunc, ...addAttr};
  }

  function attrPmov(addAttr={}) {
    const attrLook = {size:2, withLabel:false};
    const attrFunc = {fixed: question.isSolved, attractors: [pO,lX,lY,lZ], attractorDistance:0.5, snatchDistance: 0};
    return { ...attrLook, ...attrFunc, ...addAttr};
  }

  function attrVec(addAttr={}) {
    const attrLook = { strokeWidth:3, strokeColor:colVecN, withLabel:false };
    const attrFunc = { fixed:true };
    return { ...attrLook, ...attrFunc, ...addAttr};
  }
  function attrLaxis(addAttr={}) {
    const attrLook = { strokeWidth:1, strokeColor:'#666666', withLabel:false };
    const attrFunc = { fixed:true };
    return { ...attrLook, ...attrFunc, ...addAttr};
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  const attrPhidden = {fixed:true, color:'none', withLabel:false };



  function Ang2Coords (ang, radius=2) {
    const x = radius * Math.cos(Math.PI * ang / 180);
    const y = radius * Math.sin(Math.PI * ang / 180);
    return (ang==0) ? [0,0] : [x,y];
  }


  // Import parameters from Formulas
  var [angF] = question.getAllValues([315]);
  const angV = {angV};
  const angB = {angB};
  const colCharge = ( {signCharge} > 0 ) ? col2 : col1;


  // Create boards
  var brd0 = question.initBoard(BOARDID0, { 
    boundingbox:[-3, 3, 3, -3], axis:false, keepaspectratio:true,
    showCopyright:false, showNavigation:false, 
    zoom: {enabled:false, wheel: false}, pan: {enabled:false, needTwoFingers: false},
  });
  console.log(brd0);
  

  // Define elements on brd0
  brd0.suspendUpdate();

  const pX = brd0.create('point', Ang2Coords(345, 2.5), attrPfix({ name:'$$x$$', label:{offset:[0,20]} }) );
  const pY = brd0.create('point', Ang2Coords( 25, 2.5), attrPfix({ name:'$$y$$', label:{offset:[0,25]} }) );
  const pZ = brd0.create('point', Ang2Coords( 90, 2.5), attrPfix({ name:'$$z$$', label:{offset:[5,15]} }) );

  const lX = brd0.create('line', [[0,0],pX], attrLaxis({}) );
  const lY = brd0.create('line', [[0,0],pY], attrLaxis({}) );
  const lZ = brd0.create('line', [[0,0],pZ], attrLaxis({}) );

  var pO = brd0.create('point', [0,0], { fixed:true, color:colCharge, withLabel:false, size:6 } );
  var pF = brd0.create('point', Ang2Coords(angF), attrPmov({}));
  
  brd0.create('arrow', [pO, pF], attrVec({}) );
  brd0.create('arrow', [pO, Ang2Coords(angV)], attrVec({ strokeColor:colVecV }) );
  brd0.create('arrow', [pO, Ang2Coords(angB)], attrVec({ strokeColor:colVecB }) );

  brd0.create('text', [1.2,-2.35,'$$\\vec{v}$$'], {fixed: true, parse:false, color:colVecV, fontSize:16} );
  brd0.create('text', [1.7,-2.3,'$$\\vec{B}$$'], {fixed: true, parse:false, color:colVecB, fontSize:16} );
  brd0.create('text', [2.2,-2.3,'$$\\vec{F}_\\mathrm{B}$$'], {fixed: true, parse:false, color:colVecN, fontSize:16} );

  brd0.unsuspendUpdate();



  // Whenever the construction is altered the values of the points are sent to formulas.
  question.bindInput(0, () => { return Math.round(Math.atan2(pF.Y(), pF.X()) * 180 / Math.PI) ; });

};

// Execute the JavaScript code.
new JSXQuestion(BOARDIDS, jsxGraphCode, allowInputEntry=false);

</jsxgraph>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p>Korrekte Lösung: Die Lorentzkraft {strForce}.</p>]]></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
    <tags>
      <tag><text>JXG</text>
</tag>
    </tags>
  </question>

<!-- question: 8152  -->
  <question type="formulas">
    <name>
      <text><![CDATA[Magnetische Kraft Richtungen: v, FB > B]]></text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Ein <u>{strCharge}</u> bewegt sich mit der Geschwindigkeit \(\vec{v}\) durch ein homogenes Magnetfeld \(\vec{B}\) und erfährt die magnetische Kraft \(\vec{F}_\mathrm{B}\).</p>

<p>Verschieben Sie den roten Punkt, sodass der \(\vec{B}\)-Vektor in die richtige Richtung zeigt.</p>

<p>Alle drei physikalischen Grössen sind ausgerichtet entlang kartesischer Koordinatenachsen (\(x\), \(y\) und \(z\)), welche paarweise senkrecht zueinander sind. Die Abbildung zeigt das Koordinatensystem in einer üblichen perspektivischen Darstellung.</p>]]></text>
    </questiontext>
    <generalfeedback format="markdown">
      <text></text>
    </generalfeedback>
    <defaultgrade>1.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="markdown">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="markdown">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="markdown">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>jCharge = {0, 1};
jDir = {0:24};</text>
</varsrandom>
<varsglobal><text><![CDATA[arrDirV = [1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5,6,6,6,6];
arrDirB = [2,3,5,6,1,3,4,6,1,2,4,5,2,3,5,6,1,3,4,6,1,2,4,5];
arrDirF = [3,5,6,2,6,1,3,4,2,4,5,1,6,2,3,5,3,4,6,1,5,1,2,4];

angles = [0,345,25,90,165, 205,270];

signCharge = [1,-1][jCharge];
strCharge = ["Proton","Elektron"][jCharge];

angV = angles[arrDirV[jDir]];
angB = angles[arrDirB[jDir]];
angF = angles[arrDirF[jDir]];
angF = (angF > 0) ? (angF + jCharge * 180) : angF;

angB = (angB > 360) ? (angB - 360) : angB;
angB = (angB > 180) ? (angB - 360) : angB;

strMagnetic = ["ist Null","zeigt in die positive x-Richtung","zeigt in die positive y-Richtung","zeigt in die positive z-Richtung","zeigt in die negative x-Richtung","zeigt in die negative y-Richtung","zeigt in die negative z-Richtung"][arrDirB[jDir]];]]></text>
</varsglobal>
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 </answer>
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 <subqtext format="html">
<text><![CDATA[<jsxgraph width="300" height="300" numberOfBoards="1" ext_formulas>

// JavaScript code to create the construction.
var jsxGraphCode = function (question) {

  JXG.Options.arrow.lastArrow.size = 4;
  JXG.Options.arrow.lineCap = 'round';
  JXG.Options.point.showInfobox = false;


  // Attributes for points and lines

  const col1='#4285F4', col2='#EA4335', col3='#34A853', col4='#FBBC05';
  const colVecN='#4285F4', colVecV='#4CAF50', colVecB='#FBBC05';

  function attrPfix(addAttr={}) {
    const attrLook = {size:1, color:'none', withLabel: true, label:{ color:'#666666' } };
    const attrFunc = {fixed:true };
    return { ...attrLook, ...attrFunc, ...addAttr};
  }

  function attrPmov(addAttr={}) {
    const attrLook = {size:2, withLabel:false};
    const attrFunc = {fixed: question.isSolved, attractors: [pO,lX,lY,lZ], attractorDistance:0.5, snatchDistance: 0};
    return { ...attrLook, ...attrFunc, ...addAttr};
  }

  function attrVec(addAttr={}) {
    const attrLook = { strokeWidth:3, strokeColor:colVecN, withLabel:false };
    const attrFunc = { fixed:true };
    return { ...attrLook, ...attrFunc, ...addAttr};
  }
  function attrLaxis(addAttr={}) {
    const attrLook = { strokeWidth:1, strokeColor:'#666666', withLabel:false };
    const attrFunc = { fixed:true };
    return { ...attrLook, ...attrFunc, ...addAttr};
  }

  const attrPhidden = {fixed:true, color:'none', withLabel:false };



  function Ang2Coords (ang, radius=2) {
    const x = radius * Math.cos(Math.PI * ang / 180);
    const y = radius * Math.sin(Math.PI * ang / 180);
    return (ang==0) ? [0,0] : [x,y];
  }


  // Import parameters from Formulas
  var [angB] = question.getAllValues([315]);
  const angV = {angV};
  const angF = {angF};
  const colCharge = ( {signCharge} > 0 ) ? col2 : col1;


  // Create boards
  var brd0 = question.initBoard(BOARDID0, { 
    boundingbox:[-3, 3, 3, -3], axis:false, keepaspectratio:true,
    showCopyright:false, showNavigation:false, 
    zoom: {enabled:false, wheel: false}, pan: {enabled:false, needTwoFingers: false},
  });
  console.log(brd0);
  

  // Define elements on brd0
  brd0.suspendUpdate();

  const pX = brd0.create('point', Ang2Coords(345, 2.5), attrPfix({ name:'$$x$$', label:{offset:[0,20]} }) );
  const pY = brd0.create('point', Ang2Coords( 25, 2.5), attrPfix({ name:'$$y$$', label:{offset:[0,25]} }) );
  const pZ = brd0.create('point', Ang2Coords( 90, 2.5), attrPfix({ name:'$$z$$', label:{offset:[5,15]} }) );

  const lX = brd0.create('line', [[0,0],pX], attrLaxis({}) );
  const lY = brd0.create('line', [[0,0],pY], attrLaxis({}) );
  const lZ = brd0.create('line', [[0,0],pZ], attrLaxis({}) );

  var pO = brd0.create('point', [0,0], { fixed:true, color:colCharge, withLabel:false, size:6 } );
  var pB = brd0.create('point', Ang2Coords(angB), attrPmov({}));
  
  brd0.create('arrow', [pO, Ang2Coords(angF)], attrVec({}) );
  brd0.create('arrow', [pO, Ang2Coords(angV)], attrVec({ strokeColor:colVecV }) );
  brd0.create('arrow', [pO, pB], attrVec({ strokeColor:colVecB }) );

  brd0.create('text', [1.2,-2.35,'$$\\vec{v}$$'], {fixed: true, parse:false, color:colVecV, fontSize:16} );
  brd0.create('text', [1.7,-2.3,'$$\\vec{B}$$'], {fixed: true, parse:false, color:colVecB, fontSize:16} );
  brd0.create('text', [2.2,-2.3,'$$\\vec{F}_\\mathrm{B}$$'], {fixed: true, parse:false, color:colVecN, fontSize:16} );

  brd0.unsuspendUpdate();



  // Whenever the construction is altered the values of the points are sent to formulas.
  question.bindInput(0, () => { return Math.round(Math.atan2(pB.Y(), pB.X()) * 180 / Math.PI) ; });

};

// Execute the JavaScript code.
new JSXQuestion(BOARDIDS, jsxGraphCode, allowInputEntry=false);

</jsxgraph>]]></text>
 </subqtext>
 <feedback format="html">
<text><![CDATA[<p>Korrekte Lösung: Der \(\vec{B}\)-Vektor {strMagnetic}.</p>]]></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
    <tags>
      <tag><text>JXG</text>
</tag>
    </tags>
  </question>

<!-- question: 8153  -->
  <question type="formulas">
    <name>
      <text>Verhältnisbildung: Geladenes Teilchen im Magnetfeld (einfach)</text>
    </name>
    <questiontext format="html">
      <text><![CDATA[<p>Ein Ion fliege in einen Raumbereich mit homogenem Magnetfeld hinein. Seine Bahn ist in der Abbildung dargestellt.</p>

<br><p><img alt="" class="img-responsive" src="@@PLUGINFILE@@/Geladenes%20Teilchen%20im%20Magnetfeld.png" width="300px"/></p><br>

Wenn das Ion die Masse \(m\), die Ladung \(q\) und die Schnelligkeit \(v\) besitzt und die magnetische Flussdichte \(B\) beträgt, so folgt daraus der Bahnradius zu
\[r=\frac{m\cdot v}{q\cdot B}\,.\]]]></text>
<file name="Geladenes Teilchen im Magnetfeld.png" path="/" 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</file>
    </questiontext>
    <generalfeedback format="html">
      <text></text>
    </generalfeedback>
    <defaultgrade>4.0000000</defaultgrade>
    <penalty>0.3333333</penalty>
    <hidden>0</hidden>
    <idnumber></idnumber>
    <correctfeedback format="html">
      <text>Your answer is correct.</text>
    </correctfeedback>
    <partiallycorrectfeedback format="html">
      <text>Your answer is partially correct.</text>
    </partiallycorrectfeedback>
    <incorrectfeedback format="html">
      <text>Your answer is incorrect.</text>
    </incorrectfeedback>
    <shownumcorrect/>
<varsrandom><text>arrJs = shuffle([0:8]);
jCharge = {0,1};</text>
</varsrandom>
<varsglobal><text><![CDATA[factNames = [ "ein Fünftel" , "ein Viertel" , "ein Drittel" , "halb" , "doppelt" , "dreimal" , "viermal" , "fünfmal" ];
factNumbers = [ 1/5 , 1/4 , 1/3 , 1/2 , 2 , 3 , 4 , 5 ];]]></text>
</varsglobal>
<answernumbering><text>none</text>
</answernumbering>
<answers>
 <partindex>
  <text>0</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>j = arrJs[0];

strFact = factNames[j];

nSigFig = 2;
origSol = 1 / factNumbers[j];
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
  divTest = ( round( 10**(i+1) * abs(mantAns) , 6 ) ) % 10;
  nSigFigAns = ( divTest > 0.5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct number of significant figures
critSigFig = ( abs(nSigFigAns-nSigFig) < 1.5 );

# Correct solution with respect to significant figures
solSFA = sigfig( origSol , nSigFigAns );
critSolCorrect = ( abs(origAns - solSFA) / solSFA < 0.01 );

# Solution with rounding errors with respect to significant figures
critSolRound1 = ( abs(origAns - solSFA) / solSFA < 0.02 );

# Calculate grade
critSol = max( 0.7* critSolCorrect, 0.5*critSolRound1 );
grade = ( critSol > 0 ) ? 0.3*critSigFig + critSol : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Um welchen Faktor würde sich der Bahnradius unterscheiden, wenn das Ion eine {strFact} so grosse Ladung besässe? [25%]</p>
<p>&emsp;{_0}&emsp; (Dezimalzahl mit {nSigFig} signifikanten Stellen)</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>1</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>j1 = arrJs[1];
j2 = arrJs[2];

strFact1 = factNames[j1];
strFact2 = factNames[j2];

nSigFig = 2;
origSol = factNumbers[j1] * factNumbers[j2];
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
  divTest = ( round( 10**(i+1) * abs(mantAns) , 6 ) ) % 10;
  nSigFigAns = ( divTest > 0.5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct number of significant figures
critSigFig = ( abs(nSigFigAns-nSigFig) < 1.5 );

# Correct solution with respect to significant figures
solSFA = sigfig( origSol , nSigFigAns );
critSolCorrect = ( abs(origAns - solSFA) / solSFA < 0.01 );

# Solution with rounding errors with respect to significant figures
critSolRound1 = ( abs(origAns - solSFA) / solSFA < 0.02 );

# Calculate grade
critSol = max( 0.7* critSolCorrect, 0.5*critSolRound1 );
grade = ( critSol > 0 ) ? 0.3*critSigFig + critSol : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Um welchen Faktor würde sich der Bahnradius unterscheiden, wenn das Ion eine {strFact1} so grosse Masse besässe und {strFact2} so schnell wäre? [25%]</p>
<p>&emsp;{_0}&emsp; (Dezimalzahl mit {nSigFig} signifikanten Stellen)</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>2</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text>j = arrJs[3];

strFact = factNames[j];

nSigFig = 2;
origSol = 1 / factNumbers[j];
sol = sigfig( origSol , nSigFig );</text>
 </vars1>
 <answer>
  <text>sol</text>
 </answer>
 <vars2>
  <text><![CDATA[origAns = _0;

# Analyze answer for mantissa, exponent, significant figures
expAns = floor( log10(abs(origAns)));
mantAns = origAns / ( 10**( expAns ));
nSigFigAns = 1;
for (i:[0:6]) {
  divTest = ( round( 10**(i+1) * abs(mantAns) , 6 ) ) % 10;
  nSigFigAns = ( divTest > 0.5 ) ? nSigFigAns+1 : nSigFigAns ;
}

# Correct number of significant figures
critSigFig = ( abs(nSigFigAns-nSigFig) < 1.5 );

# Correct solution with respect to significant figures
solSFA = sigfig( origSol , nSigFigAns );
critSolCorrect = ( abs(origAns - solSFA) / solSFA < 0.01 );

# Solution with rounding errors with respect to significant figures
critSolRound1 = ( abs(origAns - solSFA) / solSFA < 0.02 );

# Calculate grade
critSol = max( 0.7* critSolCorrect, 0.5*critSolRound1 );
grade = ( critSol > 0 ) ? 0.3*critSigFig + critSol : 0;]]></text>
 </vars2>
 <correctness>
  <text>grade</text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="html">
<text><![CDATA[<p>Um welchen Faktor müsste man bei einem {strFact} so stark geladenen Ion die magnetische Flussdichte ändern, damit der Bahnradius derselbe bleibt? [25%]</p>
<p>&emsp;{_0}&emsp; (Dezimalzahl mit {nSigFig} signifikanten Stellen)</p>]]></text>
 </subqtext>
 <feedback format="html">
<text></text>
 </feedback>
 <correctfeedback format="html">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="html">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="html">
<text></text>
 </incorrectfeedback>
</answers>
<answers>
 <partindex>
  <text>3</text>
 </partindex>
 <placeholder>
  <text></text>
 </placeholder>
 <answermark>
  <text>1</text>
 </answermark>
 <answertype>
  <text>0</text>
 </answertype>
 <numbox>
  <text>1</text>
 </numbox>
 <vars1>
  <text><![CDATA[strMagneticDirections = ["in die Bildebene hinein","aus der Bildebene heraus"];
strChargeSigns = ["negativ","positiv"];

strMagneticDirection = strMagneticDirections[jCharge];]]></text>
 </vars1>
 <answer>
  <text>jCharge</text>
 </answer>
 <vars2>
  <text></text>
 </vars2>
 <correctness>
  <text><![CDATA[_err < 0.01]]></text>
 </correctness>
 <unitpenalty>
  <text>0.2</text>
 </unitpenalty>
 <postunit>
  <text></text>
 </postunit>
 <ruleid>
  <text>1</text>
 </ruleid>
 <otherrule>
  <text></text>
 </otherrule>
 <subqtext format="markdown">
<text><![CDATA[<p>Welches Vorzeichen besitzt die Ladung des Ions, wenn das Magnetfeld {strMagneticDirection} gerichtet ist? [25%]</p>
<p>&emsp; Es ist {_0:strChargeSigns:MCE} geladen.</p>]]></text>
 </subqtext>
 <feedback format="markdown">
<text></text>
 </feedback>
 <correctfeedback format="markdown">
<text></text>
 </correctfeedback>
 <partiallycorrectfeedback format="markdown">
<text></text>
 </partiallycorrectfeedback>
 <incorrectfeedback format="markdown">
<text></text>
 </incorrectfeedback>
</answers>
  </question>

</quiz>