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<ana user="P&#xE4;ivi" project="Pohjavesi_noro" generated="2. helta 2010 16:35 " softwareversion="4.1.0" software="Analytica">
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  <definition>10K</definition>
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  <definition>0</definition>
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  <att_previndexvalue>[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100]</att_previndexvalue>
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  <definition>1</definition>
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  <windstate>2,102,90,476,224</windstate>
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 <sysvar name="Allwarnings">
  <definition>0</definition>
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 <sysvar name="Showdescriptionmarks">
  <definition>1</definition>
 </sysvar>
 <sysvar name="Graph_primary_valdim">
  <att_catlinestyle>9</att_catlinestyle>
 </sysvar>
 <sysvar name="Graph_stats_valdim">
  <att_catlinestyle>9</att_catlinestyle>
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 <sysvar name="Graph_pdf_valdim">
  <att_contlinestyle>6</att_contlinestyle>
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 <model name="Pohjavesi_noro">
  <author>P&#xE4;ivi</author>
  <date>22. marta 2009 15:18</date>
  <saveauthor>P&#xE4;ivi</saveauthor>
  <savedate>2. helta 2010 16:35 </savedate>
  <defaultsize>48,24</defaultsize>
  <diagstate>1,0,-23,1280,675,17</diagstate>
  <diagramcolor>52427,60621,65535</diagramcolor>
  <fontstyle>Arial, 15</fontstyle>
  <fileinfo>0,Model Pohjavesi_noro,2,2,0,1,C:\Documents and Settings\P&#xE4;ivi\Desktop\Pohjavesi_noro.ana</fileinfo>
  <chance name="Op_fi1757">
   <title>Consumption of unboiled water</title>
   <units>mL</units>
   <definition>Lognormal( , , 757.765 , 566.879  )</definition>
   <nodelocation>256,400,1</nodelocation>
   <nodesize>64,36</nodesize>
   <windstate>2,466,258,855,539</windstate>
   <nodecolor>19661,65535,65535</nodecolor>
  </chance>
  <index name="Contamination">
   <title>Contamination</title>
   <definition>['Clean','Medium','Contaminated']</definition>
   <nodelocation>112,216,1</nodelocation>
   <nodesize>60,12</nodesize>
   <windstate>2,0,-23,1441,800</windstate>
   <att_previndexvalue>['Clean','Medium','Contaminated']</att_previndexvalue>
  </index>
  <module name="Dose__response">
   <title>Dose- response</title>
   <author>pmea</author>
   <date>3. syyta 2008 15:02</date>
   <defaultsize>48,24</defaultsize>
   <nodelocation>256,512,1</nodelocation>
   <nodesize>48,24</nodesize>
   <diagstate>1,0,0,535,265,17</diagstate>
   <function name="Dose_response">
    <parameters>(dose)</parameters>
    <title>Dose response</title>
    <definition>Table(Microbe)(
Norovirus_2( dose),Rotavirus_( dose),Norovirus_2( dose))</definition>
    <nodelocation>80,56,1</nodelocation>
    <nodesize>48,24</nodesize>
    <windstate>2,0,-23,1280,675</windstate>
    <paramnames>dose</paramnames>
   </function>
   <function name="Norovirus_2">
    <parameters>(dose)</parameters>
    <title>Norovirus_2</title>
    <description>Exact_beta_poisson_m( 0.040, 0.055, dose )
1-(1+(Dose/0.422))^(-0.253)</description>
    <definition>Exact_beta_poisson_m( 0.040, 0.055, dose )</definition>
    <nodelocation>208,48,1</nodelocation>
    <nodesize>48,24</nodesize>
    <windstate>2,522,357,609,424</windstate>
    <paramnames>dose</paramnames>
   </function>
   <function name="Exact_beta_poisson_m">
    <parameters>(alpha,beta,dose)</parameters>
    <title>Exact Beta Poisson model low dose approximation</title>
    <definition>1-exp(-(alpha/(alpha+beta))*dose)</definition>
    <nodelocation>320,80,1</nodelocation>
    <nodesize>48,58</nodesize>
    <windstate>2,606,76,476,224</windstate>
    <paramnames>alpha,beta,dose</paramnames>
   </function>
   <function name="Rotavirus_">
    <parameters>(dose)</parameters>
    <title>Rotavirus_</title>
    <description>Teunis and Havelaar (2000) Risk Analysis 20:511-518 fitted the exact hypergeometric beta poisson model to the data from Ward et al. (1986) Journal of Infectious Diseases 154, 871-880

Exact_beta_poisson_m( 0.167, 0.191, dose )
</description>
    <definition>Exact_beta_poisson_m( 0.167, 0.191, dose )</definition>
    <nodelocation>208,112,1</nodelocation>
    <nodesize>48,24</nodesize>
    <windstate>2,585,441,613,302</windstate>
    <paramnames>dose</paramnames>
   </function>
   <function name="Beta_poisson_approxi">
    <parameters>(alpha, beta, dose)</parameters>
    <title>Beta_poisson_approxi</title>
    <definition>1-(1+dose/beta)^-alpha</definition>
    <nodelocation>432,48,1</nodelocation>
    <nodesize>48,24</nodesize>
    <paramnames>alpha,beta,dose</paramnames>
   </function>
   <alias name="Propability_for_inf2">
    <title>Propability for infection</title>
    <definition>0</definition>
    <nodelocation>88,176,1</nodelocation>
    <nodesize>48,24</nodesize>
    <nodecolor>19661,48336,65535</nodecolor>
    <original>Op_fi1759</original>
   </alias>
   <variable name="Poisson_params">
    <title>Poisson params</title>
    <definition>Table(Microbe,Self)(
0.04,0.055,
0.167,0.191,
0.04,0.055
)</definition>
    <indexvals>['alpha','beta']</indexvals>
    <nodelocation>208,176,1</nodelocation>
    <nodesize>48,24</nodesize>
    <nodecolor>65535,52427,65534</nodecolor>
    <reformdef>[Self,Microbe]</reformdef>
   </variable>
   <function name="Dose_response1">
    <parameters>(dose)</parameters>
    <title>Dose response</title>
    <description>HUOM! Kannattaa ehdottomasti v&#xE4;ltt&#xE4;&#xE4; parametrien laittamista kaavoihin ja funktioihin. Aina jos mahdollista, niin tehd&#xE4;&#xE4;n vaaleanpunainen solmu sy&#xF6;teparametreille. N&#xE4;in ne l&#xF6;ytyv&#xE4;t ja ovat kritisoitavissa.</description>
    <definition>var alpha:= poisson_params[poisson_params='alpha'];
var beta:=  poisson_params[poisson_params='beta'];
1-exp(-(alpha/(alpha+beta))*dose)</definition>
    <nodelocation>80,112,1</nodelocation>
    <nodesize>48,24</nodesize>
    <windstate>2,536,216,603,350</windstate>
    <paramnames>dose</paramnames>
   </function>
  </module>
  <variable name="Fe_filtration">
   <title>Fe filtration</title>
   <description>K&#xE4;ytet&#xE4;&#xE4;n arviota 1 log removal</description>
   <definition>1</definition>
   <nodelocation>408,136,1</nodelocation>
   <nodesize>56,22</nodesize>
   <windstate>2,0,-23,1280,675</windstate>
   <valuestate>2,852,328,416,303,0,MIDM</valuestate>
   <reformval>[]</reformval>
   <att__discretenessinf>[1,1,0,1]</att__discretenessinf>
  </variable>
  <text name="Generic_qmra_model_">
   <title>Generic QMRA Model
</title>
   <description>Juomaveden mikrobiologinen riskinarviointi</description>
   <nodelocation>296,64,-1</nodelocation>
   <nodesize>276,36</nodesize>
   <nodeinfo>1,0,0,1,0,0,1,,0,</nodeinfo>
   <windstate>2,0,-23,1281,914</windstate>
   <nodefont>Arial Black, 24</nodefont>
  </text>
  <chance name="Likelyhood_of_contam">
   <title>Likelyhood of contamination</title>
   <definition>Table(Contamination)(
1,1,1)</definition>
   <nodelocation>256,320,1</nodelocation>
   <nodesize>60,40</nodesize>
   <windstate>2,0,-23,800,489</windstate>
   <defnstate>2,340,102,416,303,0,MIDM</defnstate>
  </chance>
  <index name="Microbe">
   <title>Microbe</title>
   <definition>['Norovirus','Rotavirus','Murine norovirus']</definition>
   <nodelocation>112,192,1</nodelocation>
   <nodesize>48,13</nodesize>
   <windstate>2,0,-23,1281,676</windstate>
   <att_previndexvalue>['Norovirus','Rotavirus','Murine norovirus']</att_previndexvalue>
  </index>
  <chance name="Op_fi1755">
   <title>Pathogens in source water</title>
   <units>unit/l</units>
   <definition>Table(Microbe,Contamination)(
triangular(0,0,0),triangular(12.5,100,500),triangular(500,1000,5000),
triangular(0,0,0),triangular(12.5,100,500),triangular(500,1000,5000),
triangular(0,0,0),triangular(12.5,100,500),triangular(500,1000,5000)
)</definition>
   <nodelocation>112,152,1</nodelocation>
   <nodesize>48,31</nodesize>
   <windstate>2,0,-23,1280,675</windstate>
   <defnstate>2,705,119,416,303,0,MIDM</defnstate>
   <valuestate>2,534,69,446,243,0,MIDM</valuestate>
   <nodecolor>65535,52427,57888</nodecolor>
   <reformdef>[Microbe,Contamination]</reformdef>
   <reformval>[Contamination,Microbe,1]</reformval>
   <att__discretenessinf>[0,0,0,0]</att__discretenessinf>
   <att_resultslicestate>[Contamination,3,Microbe,1,Sys_localindex('STEP'),1]</att_resultslicestate>
  </chance>
  <objective name="Op_fi1753">
   <title>Pathogen conentration in drinking water</title>
   <definition>10^(Logten(Op_fi1755*Likelyhood_of_contam)-Op_fi1758)
</definition>
   <nodelocation>112,320,1</nodelocation>
   <nodesize>48,40</nodesize>
   <windstate>2,0,-23,1280,675</windstate>
   <valuestate>2,0,-23,1280,675,0,MEAN</valuestate>
   <reformval>[Contamination,Treatment]</reformval>
   <att_resultslicestate>[Microbe,3,Treatment,1,Contamination,1]</att_resultslicestate>
  </objective>
  <variable name="Op_fi1756">
   <title>Pathogen exposure</title>
   <definition>Op_fi1757*Op_fi1753/1000</definition>
   <nodelocation>112,400,1</nodelocation>
   <nodesize>48,24</nodesize>
   <windstate>2,0,-23,1280,675</windstate>
   <valuestate>2,0,0,1281,676,0,MIDM</valuestate>
   <reformval>[Contamination,Treatment]</reformval>
   <att_resultslicestate>[Microbe,3,Treatment,1,Contamination,1]</att_resultslicestate>
  </variable>
  <variable name="Op_fi1759">
   <title>Probability of infection</title>
   <definition>Dose_response1(Op_fi1756)</definition>
   <nodelocation>112,512,1</nodelocation>
   <nodesize>48,24</nodesize>
   <windstate>2,0,-23,1280,675</windstate>
   <valuestate>2,560,90,561,278,0,MEAN</valuestate>
   <aliases>[Alias Propability_for_inf2, Formnode Pinf___annual1]</aliases>
   <nodecolor>19661,48336,65535</nodecolor>
   <graphsetup>&#x7B;!40000&#x7C;Att_graphvaluerange Clipboard_pinf:1,,,,1&#x7D;
&#x7B;!40000&#x7C;Att_catlinestyle Graph_primary_valdim:9&#x7D;</graphsetup>
   <reformval>[Contamination,Treatment,2,0]</reformval>
   <numberformat>2,D,4,2,0,0,4,0,$,0,&quot;ABBREV&quot;,0</numberformat>
   <att__tableprintscali>100,1,1,1,1,9,2970,2100,15,0</att__tableprintscali>
   <att__discretenessinf>[1,0,0,0]</att__discretenessinf>
   <att_resultslicestate>[Microbe,3,Treatment,1,Contamination,1]</att_resultslicestate>
  </variable>
  <objective name="Op_fi1760">
   <title># infections in the area</title>
   <description>T&#xE4;m&#xE4; laskee seuraavaa: mik&#xE4; on todenn&#xE4;k&#xF6;isten tautitapausten m&#xE4;&#xE4;r&#xE4;, kun v&#xE4;est&#xF6; juo t&#xE4;t&#xE4; vett&#xE4; yhden vuorokauden ajan?</description>
   <definition>poisson(Op_fi1759*Population_size)</definition>
   <nodelocation>184,584,1</nodelocation>
   <nodesize>48,24</nodesize>
   <windstate>2,441,298,727,250</windstate>
   <valuestate>2,0,-23,1280,675,0,MEAN</valuestate>
   <nodecolor>19661,48336,65535</nodecolor>
   <graphsetup>&#x7B;!40000&#x7C;Att_graphindexrange .Possible_values:1,0&#x7D;
&#x7B;!40000&#x7C;Att_contlinestyle Graph_cumprob_valdim:1&#x7D;
&#x7B;!40000&#x7C;Att_catlinestyle Graph_cumprob_valdim:1&#x7D;</graphsetup>
   <reformval>[Contamination,Treatment]</reformval>
   <numberformat>2,D,4,2,0,0,4,0,$,0,&quot;ABBREV&quot;,0</numberformat>
   <att__tableprintscali>100,1,1,1,1,9,2970,2100,15,0</att__tableprintscali>
   <att__discretenessinf>[1,1,0,1]</att__discretenessinf>
   <att_resultslicestate>[Microbe,3,Treatment,4,Contamination,3]</att_resultslicestate>
  </objective>
  <objective name="Op_fi1761">
   <title># people having infection within a year</title>
   <description>Tarkkaan ottaen t&#xE4;m&#xE4; laskee seuraavaa: 
Mik&#xE4; on odotusarvo sille lukum&#xE4;&#xE4;r&#xE4;lle ihmisi&#xE4;, jotka saavat ripulin juomavedest&#xE4; ainakin kerran yhden vuoden aikana? T&#xE4;ss&#xE4; siis pidet&#xE4;&#xE4;n merkityksett&#xF6;m&#xE4;n&#xE4; sit&#xE4;, jos ripulin saisi uudestaan.</description>
   <definition>(1-(1-Op_fi1759)^365)*15000</definition>
   <nodelocation>80,608,1</nodelocation>
   <nodesize>48,49</nodesize>
   <windstate>2,102,90,476,224</windstate>
   <valuestate>2,483,175,488,240,0,MEAN</valuestate>
   <aliases>[Formnode Pinf_annual1]</aliases>
   <reformval>[Contamination,Treatment,2]</reformval>
   <att__tableprintscali>100,1,1,1,1,0,0,0,0,0</att__tableprintscali>
   <att__discretenessinf>[1,0,0,0]</att__discretenessinf>
   <att_resultslicestate>[Microbe,3,Treatment,1,Contamination,1]</att_resultslicestate>
  </objective>
  <formnode name="Pinf_annual1">
   <title>Pinf annual</title>
   <definition>1</definition>
   <nodelocation>816,656,1</nodelocation>
   <nodesize>224,20</nodesize>
   <nodeinfo>1,0,0,1,0,0,1,162,0,1</nodeinfo>
   <nodecolor>52425,39321,65535</nodecolor>
   <nodefont>Arial, 11</nodefont>
   <original>Op_fi1761</original>
  </formnode>
  <formnode name="Pinf___annual1">
   <title>Pinf - annual</title>
   <definition>1</definition>
   <nodelocation>816,560,1</nodelocation>
   <nodesize>224,20</nodesize>
   <nodeinfo>1,0,0,1,0,0,1,186,0,1</nodeinfo>
   <nodecolor>52425,39321,65535</nodecolor>
   <nodefont>Arial, 10</nodefont>
   <original>Op_fi1759</original>
  </formnode>
  <text name="Te1">
   <title>Te1</title>
   <description>Tulokset: 

Infektion todenn&#xE4;k&#xF6;isyys alueella per henkil&#xF6;



Vuosittainen infektioiden lukum&#xE4;&#xE4;r&#xE4; alueella</description>
   <nodelocation>832,576,-1</nodelocation>
   <nodesize>236,108</nodesize>
   <nodeinfo>1,0,0,1,0,1,1,,0,</nodeinfo>
   <windstate>2,0,-23,1281,676</windstate>
   <nodefont>Arial, 19</nodefont>
  </text>
  <text name="Te2">
   <title>Te1</title>
   <description>Mikrobit:
-Norovirus
-Rotavirus
-Murine norovirus 

Kontaminaatioskenaariot:
-Clean: Puhdas tilanne, ei norovirusta raakavedess&#xE4;
-Medium: Nykytilanne, norovirusta havaittu raakavedess&#xE4;
-Contaminated: Vakava norovirus-kontaminaatio raakavedess&#xE4;

Vedenk&#xE4;sittelyskenaariot:
-UV ja raudanpoisto
-UV max 100 % teho 
-UV normal 80 % teho
-UV min 45% teho (lamppujen vaihtoraja)
-Kaksi vierekk&#xE4;ist&#xE4; UV-linjaa</description>
   <nodelocation>832,232,-1</nodelocation>
   <nodesize>236,218</nodesize>
   <nodeinfo>1,0,0,1,0,1,1,,0,</nodeinfo>
   <windstate>2,102,90,476,224</windstate>
   <nodefont>Arial, 19</nodefont>
  </text>
  <variable name="Op_fi1758">
   <title>Total microbial log reduction</title>
   <definition>Table(Treatment)(
Fe_filtration+Op_fi1754,Fe_filtration+Op_fi1754*0.8,Fe_filtration+Op_fi1754*0.45,Op_fi1754,Op_fi1754*0.8,Op_fi1754*0.45,Op_fi1754*2)</definition>
   <nodelocation>288,160,1</nodelocation>
   <nodesize>48,40</nodesize>
   <windstate>2,0,0,1280,675</windstate>
   <defnstate>2,232,242,416,303,0,MIDM</defnstate>
   <valuestate>2,0,0,1281,676,0,MIDM</valuestate>
   <reformval>[Microbe,Treatment]</reformval>
  </variable>
  <variable name="Op_fi1754">
   <title>UV</title>
   <description>-Norovirus_uv_lr(Fluence)</description>
   <definition>Table(Microbe)(
-Norovirus_uv_lr(Fluence),-Rotavirus_uv_lr(Fluence),-Murine_norovirus_lr(Fluence))</definition>
   <nodelocation>400,192,1</nodelocation>
   <nodesize>48,24</nodesize>
   <windstate>2,575,118,494,296</windstate>
   <valuestate>2,0,-23,1440,799,0,MIDM</valuestate>
   <reformdef>[Microbe,Treatment]</reformdef>
  </variable>
  <index name="Treatment">
   <title>Treatment</title>
   <definition>['UV max +  Fe filtration','UV normal +  Fe filtration','UV minimum +  Fe filtration','UV max','UV normal','UV minimum','Double UV']</definition>
   <nodelocation>288,216,1</nodelocation>
   <nodesize>48,12</nodesize>
   <windstate>2,0,-23,1441,800</windstate>
   <att_previndexvalue>['UV max +  Fe filtration','UV normal +  Fe filtration','UV minimum +  Fe filtration','UV max','UV normal','UV minimum','Double UV']</att_previndexvalue>
  </index>
  <module name="Uv_treatment">
   <title>UV treatment</title>
   <author>P&#xE4;ivi</author>
   <date>22. marta 2009 15:41</date>
   <defaultsize>48,24</defaultsize>
   <nodelocation>512,192,1</nodelocation>
   <nodesize>48,24</nodesize>
   <diagstate>1,0,-23,1280,675,17</diagstate>
   <chance name="Fluence">
    <title>Fluence Dose  mJ. cm 2</title>
    <description>79.2</description>
    <definition>79.2</definition>
    <nodelocation>96,80,1</nodelocation>
    <nodesize>48,31</nodesize>
    <windstate>2,758,147,336,271</windstate>
    <valuestate>2,0,-23,1440,799,0,MIDM</valuestate>
    <nodecolor>39321,55707,65535</nodecolor>
   </chance>
   <function name="Norovirus_uv_lr">
    <parameters>(fluence)</parameters>
    <title>Norovirus UV LR</title>
    <definition>Uvlogred( 0.106, fluence, 0 )</definition>
    <nodelocation>232,104,1</nodelocation>
    <nodesize>48,24</nodesize>
    <windstate>2,773,108,410,303</windstate>
    <paramnames>fluence</paramnames>
   </function>
   <function name="Rotavirus_uv_lr">
    <parameters>(fluence)</parameters>
    <title>Rotavirus_uv_lr</title>
    <definition>Uvlogred( 0.102, fluence, 0 )</definition>
    <nodelocation>232,40,1</nodelocation>
    <nodesize>48,24</nodesize>
    <windstate>2,659,283,419,338</windstate>
    <paramnames>fluence</paramnames>
   </function>
   <function name="Uvlogred">
    <parameters>(k,fluence,b)</parameters>
    <title>UVLogRed</title>
    <definition>-k*fluence-b</definition>
    <nodelocation>224,248,1</nodelocation>
    <nodesize>48,24</nodesize>
    <windstate>2,558,321,409,277</windstate>
    <paramnames>k,fluence,b</paramnames>
   </function>
   <function name="Murine_norovirus_lr">
    <parameters>(fluence)</parameters>
    <title>Murine norovirus LR</title>
    <definition>Uvlogred( 0.132, fluence, 0 )</definition>
    <nodelocation>232,176,1</nodelocation>
    <nodesize>48,31</nodesize>
    <windstate>2,676,509,528,283</windstate>
    <paramnames>fluence</paramnames>
   </function>
  </module>
  <variable name="Population_size">
   <title>Population size</title>
   <definition>15000</definition>
   <nodelocation>296,600,1</nodelocation>
   <nodesize>48,24</nodesize>
  </variable>
  <objective name="A__infections_in_th2">
   <title># infections in the area/a</title>
   <description>T&#xE4;m&#xE4; laskee seuraavaa: mik&#xE4; on todenn&#xE4;k&#xF6;isten tautitapausten m&#xE4;&#xE4;r&#xE4;, kun v&#xE4;est&#xF6; juo t&#xE4;t&#xE4; vett&#xE4; yhden vuoden ajan? Suurimmat lukemat eritt&#xE4;in kontaminoituneella vedell&#xE4; ovat tietenkin j&#xE4;rjett&#xF6;mi&#xE4;, koska jos tuollainen epidemia syntyisi, niin
* sit&#xE4; ei vuotta katseltaisi,
* mallissa oletetaan, ett&#xE4; ripulin voi saada joka p&#xE4;iv&#xE4; uudestaan riippumatta edellisest&#xE4; p&#xE4;iv&#xE4;st&#xE4;.</description>
   <definition>poisson(Op_fi1759*Population_size*365)</definition>
   <nodelocation>184,640,1</nodelocation>
   <nodesize>48,24</nodesize>
   <windstate>2,426,345,727,250</windstate>
   <valuestate>2,177,48,651,493,0,MEAN</valuestate>
   <nodecolor>19661,48336,65535</nodecolor>
   <graphsetup>&#x7B;!40000&#x7C;Att_graphindexrange .Possible_values:1,0,0,,,,,0,5000&#x7D;
&#x7B;!40000&#x7C;Att_contlinestyle Graph_cumprob_valdim:1&#x7D;
&#x7B;!40000&#x7C;Att_catlinestyle Graph_cumprob_valdim:1&#x7D;</graphsetup>
   <reformval>[Contamination,Treatment]</reformval>
   <numberformat>2,D,4,2,0,0,4,0,$,0,&quot;ABBREV&quot;,0</numberformat>
   <att__tableprintscali>100,1,1,1,1,9,2970,2100,15,0</att__tableprintscali>
   <att__discretenessinf>[1,1,0,1]</att__discretenessinf>
   <att_resultslicestate>[Microbe,1,Contamination,3,Treatment,4,Sys_localindex('POSSIBLE_VALUES'),1]</att_resultslicestate>
  </objective>
  <text name="Te3">
   <description>Raakavesi</description>
   <nodelocation>120,176,-1</nodelocation>
   <nodesize>92,76</nodesize>
   <nodeinfo>1,0,0,1,0,1,0,,0,</nodeinfo>
   <nodecolor>39321,52431,65535</nodecolor>
  </text>
  <text name="Te4">
   <title>Te3</title>
   <description>Vedenpuhdistus</description>
   <nodelocation>400,176,-1</nodelocation>
   <nodesize>172,76</nodesize>
   <nodeinfo>1,0,0,1,0,1,0,,0,</nodeinfo>
   <nodecolor>39321,52431,65535</nodecolor>
  </text>
  <text name="Te5">
   <title>Te3</title>
   <description>Altistuminen</description>
   <nodelocation>184,352,-1</nodelocation>
   <nodesize>156,92</nodesize>
   <nodeinfo>1,0,0,1,0,1,0,,0,</nodeinfo>
   <nodecolor>39321,52431,65535</nodecolor>
  </text>
  <text name="Te6">
   <title>Te3</title>
   <description>Terveysvaikutukset</description>
   <nodelocation>184,568,-1</nodelocation>
   <nodesize>160,112</nodesize>
   <nodeinfo>1,0,0,1,0,1,0,,0,</nodeinfo>
   <nodecolor>39321,52431,65535</nodecolor>
  </text>
 </model>
</ana>