Infectious Disease Prediction Modelling Using Synthetic Optimisation Approaches

Author(s):  
Terence Fusco ◽  
Yaxin Bi ◽  
Haiying Wang ◽  
Fiona Browne
2021 ◽  
Author(s):  
Yichen He ◽  
Huihui Liu ◽  
Xianfen Xie ◽  
Wanrong Gu ◽  
Yijun Mao ◽  
...  

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 118340-118354
Author(s):  
Huriviades Calderon-Gomez ◽  
Luis Mendoza-Pitti ◽  
Miguel Vargas-Lombardo ◽  
Jose Manuel Gomez-Pulido ◽  
Jose Luis Castillo-Sequera ◽  
...  

2017 ◽  
Vol 36 (30) ◽  
pp. 4908-4929 ◽  
Author(s):  
Evan L. Ray ◽  
Krzysztof Sakrejda ◽  
Stephen A. Lauer ◽  
Michael A. Johansson ◽  
Nicholas G. Reich

Author(s):  
Adrian F. van Dellen

The morphologic pathologist may require information on the ultrastructure of a non-specific lesion seen under the light microscope before he can make a specific determination. Such lesions, when caused by infectious disease agents, may be sparsely distributed in any organ system. Tissue culture systems, too, may only have widely dispersed foci suitable for ultrastructural study. In these situations, when only a few, small foci in large tissue areas are useful for electron microscopy, it is advantageous to employ a methodology which rapidly selects a single tissue focus that is expected to yield beneficial ultrastructural data from amongst the surrounding tissue. This is in essence what "LIFTING" accomplishes. We have developed LIFTING to a high degree of accuracy and repeatability utilizing the Microlift (Fig 1), and have successfully applied it to tissue culture monolayers, histologic paraffin sections, and tissue blocks with large surface areas that had been initially fixed for either light or electron microscopy.


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