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  1. Media/2018/Aboagye and Rowe - 2018 - Evaluation of denaturing gradient gel electrophoresis for the detection of mycobacterial species and/figure_01.jpg +3 -0
  2. Media/2018/Aboagye and Rowe - 2018 - Evaluation of denaturing gradient gel electrophoresis for the detection of mycobacterial species and/figure_01.txt +1 -0
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  7. Media/2018/Aboagye and Rowe - 2018 - Evaluation of denaturing gradient gel electrophoresis for the detection of mycobacterial species and/figure_04.jpg +3 -0
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  11. Media/2018/Aboagye and Rowe - 2018 - Evaluation of denaturing gradient gel electrophoresis for the detection of mycobacterial species and/manifest.json +208 -0
  12. Media/2018/Aboagye and Rowe - 2018 - Evaluation of denaturing gradient gel electrophoresis for the detection of mycobacterial species and/table_01.jpg +3 -0
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  14. Media/2018/Aboagye and Rowe - 2018 - Evaluation of denaturing gradient gel electrophoresis for the detection of mycobacterial species and/table_01.txt +1 -0
  15. Media/2018/Aboagye and Rowe - 2018 - Evaluation of denaturing gradient gel electrophoresis for the detection of mycobacterial species and/table_02.jpg +3 -0
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  17. Media/2018/Aboagye and Rowe - 2018 - Evaluation of denaturing gradient gel electrophoresis for the detection of mycobacterial species and/table_02.txt +1 -0
  18. Media/2018/Acosta et al. - 2018 - Monitoring levels of viable Helicobacter pylori in surface water by qPCR in Northeast Spain/figure_01.jpg +3 -0
  19. Media/2018/Acosta et al. - 2018 - Monitoring levels of viable Helicobacter pylori in surface water by qPCR in Northeast Spain/figure_01.txt +1 -0
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  21. Media/2018/Acosta et al. - 2018 - Monitoring levels of viable Helicobacter pylori in surface water by qPCR in Northeast Spain/table_01.jpg +3 -0
  22. Media/2018/Acosta et al. - 2018 - Monitoring levels of viable Helicobacter pylori in surface water by qPCR in Northeast Spain/table_01.json +1982 -0
  23. Media/2018/Acosta et al. - 2018 - Monitoring levels of viable Helicobacter pylori in surface water by qPCR in Northeast Spain/table_01.txt +1 -0
  24. Media/2018/Acosta et al. - 2018 - Monitoring levels of viable Helicobacter pylori in surface water by qPCR in Northeast Spain/table_02.jpg +3 -0
  25. Media/2018/Acosta et al. - 2018 - Monitoring levels of viable Helicobacter pylori in surface water by qPCR in Northeast Spain/table_02.json +309 -0
  26. Media/2018/Acosta et al. - 2018 - Monitoring levels of viable Helicobacter pylori in surface water by qPCR in Northeast Spain/table_02.txt +1 -0
  27. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_01.jpg +3 -0
  28. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_01.txt +1 -0
  29. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_02.jpg +3 -0
  30. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_02.txt +1 -0
  31. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_03.jpg +3 -0
  32. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_03.txt +1 -0
  33. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_04.jpg +3 -0
  34. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_04.txt +1 -0
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  38. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_06.txt +1 -0
  39. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_07.jpg +3 -0
  40. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/figure_07.txt +1 -0
  41. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/manifest.json +320 -0
  42. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/table_01.jpg +3 -0
  43. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/table_01.json +2111 -0
  44. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/table_01.txt +1 -0
  45. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/table_02.jpg +3 -0
  46. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/table_02.json +3347 -0
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  50. Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/table_03.txt +1 -0
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+ {
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+ "text": "Name",
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+ ]
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+ {
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+ "text": "of",
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+ },
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+ {
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+ "text": "species",
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+ ]
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+ },
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+ {
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+ "text": "sites",
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+ ]
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+ "text": "from",
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+ ]
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+ "text": "site",
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+ },
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+ {
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+ "text": "(N)",
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+ }
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+ ]
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+ },
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+ {
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+ "text": "Common raw water Podocarpus macrophyllus Proximal to WTW1 1",
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+ "bbox_points": [
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+ ],
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+ "words": [
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+ "text": "Common",
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+ },
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+ {
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+ "text": "raw",
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+ ]
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+ },
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+ {
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+ "bbox_points": [
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+ ]
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+ },
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+ {
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+ "text": "Podocarpus",
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+ ]
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+ },
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+ {
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+ "text": "macrophyllus",
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+ ]
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+ },
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+ {
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+ "text": "Proximal",
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+ ]
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+ },
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+ {
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+ "text": "to",
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+ ]
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+ },
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+ {
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+ "text": "WTW1",
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+ ]
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+ },
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+ {
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+ "text": "1",
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+ "bbox_points": [
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+ ]
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+ }
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+ ]
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+ },
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+ {
349
+ "text": "source Sciadopitys verticillata Proximal to WTW1 1",
350
+ "bbox_points": [
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+ 168.51,
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+ ],
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+ "words": [
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+ "text": "source",
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+ "bbox_points": [
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+ ]
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+ },
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+ {
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+ "text": "Sciadopitys",
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+ ]
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+ },
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+ {
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+ "text": "verticillata",
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+ ]
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+ },
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+ {
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+ "text": "Proximal",
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+ "bbox_points": [
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+ ]
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+ },
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+ {
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+ "text": "to",
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+ ]
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+ },
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+ {
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+ "text": "WTW1",
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+ ]
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+ },
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+ {
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+ "text": "1",
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+ "bbox_points": [
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+ ]
419
+ }
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+ ]
421
+ },
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+ {
423
+ "text": "Uncultured Synechococcus Proximal to WTW1 1",
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+ "bbox_points": [
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+ ],
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+ "words": [
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432
+ "text": "Uncultured",
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+ ]
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+ },
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+ {
441
+ "text": "Synechococcus",
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+ "bbox_points": [
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+ ]
448
+ },
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+ {
450
+ "text": "Proximal",
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+ "bbox_points": [
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+ ]
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+ },
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+ {
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+ "text": "to",
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+ "bbox_points": [
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+ ]
466
+ },
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+ {
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+ "text": "WTW1",
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+ "bbox_points": [
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+ ]
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+ },
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+ {
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+ "text": "1",
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+ "bbox_points": [
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+ ]
484
+ }
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+ ]
486
+ },
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+ {
488
+ "text": "Dacrydium pierrei Proximal to WTW1 1",
489
+ "bbox_points": [
490
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+ ],
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+ "words": [
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497
+ "text": "Dacrydium",
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+ ]
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+ },
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+ {
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+ "text": "pierrei",
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+ 189.48,
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+ 213.0,
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+ ]
513
+ },
514
+ {
515
+ "text": "Proximal",
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+ "bbox_points": [
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521
+ ]
522
+ },
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+ {
524
+ "text": "to",
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+ "bbox_points": [
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+ ]
531
+ },
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+ {
533
+ "text": "WTW1",
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+ "bbox_points": [
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+ ]
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+ },
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+ {
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+ "text": "1",
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+ "bbox_points": [
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+ ]
549
+ }
550
+ ]
551
+ },
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+ {
553
+ "text": "Coleodesmium species Proximal to WTW2 1",
554
+ "bbox_points": [
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+ ],
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+ "words": [
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+ {
562
+ "text": "Coleodesmium",
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+ "bbox_points": [
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+ 201.91,
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+ ]
569
+ },
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+ {
571
+ "text": "species",
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+ "bbox_points": [
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+ 200.07,
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577
+ ]
578
+ },
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+ {
580
+ "text": "Proximal",
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+ "bbox_points": [
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+ ]
587
+ },
588
+ {
589
+ "text": "to",
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+ "bbox_points": [
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595
+ ]
596
+ },
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+ {
598
+ "text": "WTW2",
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+ "bbox_points": [
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+ ]
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+ },
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+ {
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+ "text": "1",
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+ "bbox_points": [
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+ ]
614
+ }
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+ ]
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+ },
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+ {
618
+ "text": "WTW1 Eutreptiella braarudii Final treated water 1",
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+ "bbox_points": [
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621
+ 213.97,
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+ 222.09
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+ ],
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+ "words": [
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+ {
627
+ "text": "WTW1",
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+ "bbox_points": [
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+ 69.5,
632
+ 222.09
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+ ]
634
+ },
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+ {
636
+ "text": "Eutreptiella",
637
+ "bbox_points": [
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+ 221.97
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+ ]
643
+ },
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+ {
645
+ "text": "braarudii",
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+ "bbox_points": [
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+ 225.82,
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+ 221.97
651
+ ]
652
+ },
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+ {
654
+ "text": "Final",
655
+ "bbox_points": [
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+ 303.69,
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+ 222.09
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+ ]
661
+ },
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+ {
663
+ "text": "treated",
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+ "bbox_points": [
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+ 330.73,
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+ ]
670
+ },
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+ {
672
+ "text": "water",
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+ "bbox_points": [
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+ 333.13,
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+ 353.01,
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+ 222.09
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+ ]
679
+ },
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+ {
681
+ "text": "1",
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+ "bbox_points": [
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+ 222.09
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+ ]
688
+ }
689
+ ]
690
+ },
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+ {
692
+ "text": "Mycobacterium species Raw water 1",
693
+ "bbox_points": [
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+ 224.46,
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+ 488.86,
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+ 232.58
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+ ],
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+ "words": [
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+ {
701
+ "text": "Mycobacterium",
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+ "bbox_points": [
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+ 203.73,
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+ 232.46
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+ ]
708
+ },
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+ {
710
+ "text": "species",
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+ "bbox_points": [
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+ 206.08,
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+ 224.56,
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+ 231.64,
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+ 232.58
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+ ]
717
+ },
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+ {
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+ "text": "Raw",
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+ "bbox_points": [
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+ ]
726
+ },
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+ {
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+ "text": "water",
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+ "bbox_points": [
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+ ]
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+ },
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+ {
737
+ "text": "1",
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+ "bbox_points": [
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743
+ ]
744
+ }
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+ ]
746
+ },
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+ {
748
+ "text": "Anabaena species Raw water (2), SSF (1) 3",
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+ "bbox_points": [
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+ 243.12
754
+ ],
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+ "words": [
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+ {
757
+ "text": "Anabaena",
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+ "bbox_points": [
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+ 185.32,
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+ 243.01
763
+ ]
764
+ },
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+ {
766
+ "text": "species",
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+ "bbox_points": [
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+ 213.27,
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+ 243.12
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+ ]
773
+ },
774
+ {
775
+ "text": "Raw",
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+ "bbox_points": [
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+ ]
782
+ },
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+ {
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+ "text": "water",
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+ "bbox_points": [
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+ ]
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+ },
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+ {
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+ "text": "(2),",
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+ "bbox_points": [
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+ 243.12
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+ ]
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+ },
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+ {
802
+ "text": "SSF",
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+ "bbox_points": [
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+ ]
809
+ },
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+ {
811
+ "text": "(1)",
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+ "bbox_points": [
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+ 366.67,
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+ 243.12
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+ ]
818
+ },
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+ {
820
+ "text": "3",
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+ "bbox_points": [
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+ 243.12
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+ ]
827
+ }
828
+ ]
829
+ },
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+ {
831
+ "text": "Nostoc species Raw water (4), SSF (1) 5",
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+ "bbox_points": [
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+ 253.61
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+ ],
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+ "words": [
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+ {
840
+ "text": "Nostoc",
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+ "bbox_points": [
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+ ]
847
+ },
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+ {
849
+ "text": "species",
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+ "bbox_points": [
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+ 201.08,
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+ ]
856
+ },
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+ {
858
+ "text": "Raw",
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+ "bbox_points": [
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864
+ ]
865
+ },
866
+ {
867
+ "text": "water",
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+ "bbox_points": [
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+ ]
874
+ },
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+ {
876
+ "text": "(4),",
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+ "bbox_points": [
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+ ]
883
+ },
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+ {
885
+ "text": "SSF",
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+ "bbox_points": [
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891
+ ]
892
+ },
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+ {
894
+ "text": "(1)",
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+ "bbox_points": [
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+ 366.67,
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+ 253.61
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+ ]
901
+ },
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+ {
903
+ "text": "5",
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+ "bbox_points": [
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+ ]
910
+ }
911
+ ]
912
+ },
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+ {
914
+ "text": "WTW2 Uncultured Cyanobacterium Raw water (4), final treated water (4), 10",
915
+ "bbox_points": [
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+ 267.61
920
+ ],
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+ "words": [
922
+ {
923
+ "text": "WTW2",
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+ "bbox_points": [
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+ 43.43,
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+ 259.6,
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+ 69.5,
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+ 267.61
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+ ]
930
+ },
931
+ {
932
+ "text": "Uncultured",
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+ "bbox_points": [
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+ 267.61
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+ ]
939
+ },
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+ {
941
+ "text": "Cyanobacterium",
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+ "bbox_points": [
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+ 267.5
947
+ ]
948
+ },
949
+ {
950
+ "text": "Raw",
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+ "bbox_points": [
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956
+ ]
957
+ },
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+ {
959
+ "text": "water",
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+ "bbox_points": [
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+ 267.61
965
+ ]
966
+ },
967
+ {
968
+ "text": "(4),",
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+ "bbox_points": [
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+ 267.61
974
+ ]
975
+ },
976
+ {
977
+ "text": "final",
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+ "bbox_points": [
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+ 267.61
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+ ]
984
+ },
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+ {
986
+ "text": "treated",
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+ "bbox_points": [
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+ 267.61
992
+ ]
993
+ },
994
+ {
995
+ "text": "water",
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+ "bbox_points": [
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+ 259.6,
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+ 405.45,
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+ 267.61
1001
+ ]
1002
+ },
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+ {
1004
+ "text": "(4),",
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+ "bbox_points": [
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+ 419.75,
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+ 267.61
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+ ]
1011
+ },
1012
+ {
1013
+ "text": "10",
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+ "bbox_points": [
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+ 267.61
1019
+ ]
1020
+ }
1021
+ ]
1022
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Media/2018/Adhikary et al. - 2018 - Improving streamflow forecast using optimal rain gauge network-based input to artificial neural netw/table_03.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ Contribution factor based on the trained ANN weights for the augmented opti-