An indeterministic Monte Carlo technique for fast time of flight photon transport through optically thick turbid media

2002 ◽  
Vol 29 (2) ◽  
pp. 125-131 ◽  
Author(s):  
S. Behin-Ain ◽  
T. van Doorn ◽  
J. R. Patterson
Keyword(s):  
Monte Carlo ◽  
Time Of Flight ◽  
Monte Carlo Technique ◽  
Turbid Media ◽  
Fast Time ◽  
Photon Transport

Application of parallel computing to a Monte Carlo code for photon transport in turbid media

1998 ◽  
Author(s):  
Alberto Colasanti ◽  
Giovanni Guida ◽  
Annamaria Kisslinger ◽  
Raffaele Liuzzi ◽  
Maria Quarto ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Parallel Computing ◽  
Turbid Media ◽  
Monte Carlo Code ◽  
Photon Transport

Multiple processor version of a Monte Carlo code for photon transport in turbid media

2000 ◽  
Vol 132 (1-2) ◽  
pp. 84-93 ◽  
Author(s):  
Alberto Colasanti ◽  
Giovanni Guida ◽  
Annamaria Kisslinger ◽  
Raffaele Liuzzi ◽  
Maria Quarto ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Turbid Media ◽  
Monte Carlo Code ◽  
Photon Transport ◽  
Multiple Processor

scholarly journals Multipurpose Monte Carlo simulator for photon transport in turbid media

2009 ◽  
Author(s):  
Pedro Guerra ◽  
Juan Aguirre ◽  
Juan E. Ortuno ◽  
Maria J. Ledesma-Carbayo ◽  
Juan J. Vaquero ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Turbid Media ◽  
Photon Transport ◽  
Monte Carlo Simulator

Application of the Monte Carlo Method for the Prediction of Behavior of Peptides

2019 ◽  
Vol 20 (12) ◽  
pp. 1151-1157 ◽  
Author(s):  
Alla P. Toropova ◽  
Andrey A. Toropov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Natural Sciences ◽  
Monte Carlo Technique ◽  
Quantitative Structure ◽  
Structure Property ◽  
The Monte Carlo Method ◽  
Modern Natural

Prediction of physicochemical and biochemical behavior of peptides is an important and attractive task of the modern natural sciences, since these substances have a key role in life processes. The Monte Carlo technique is a possible way to solve the above task. The Monte Carlo method is a tool with different applications relative to the study of peptides: (i) analysis of the 3D configurations (conformers); (ii) establishment of quantitative structure – property / activity relationships (QSPRs/QSARs); and (iii) development of databases on the biopolymers. Current ideas related to application of the Monte Carlo technique for studying peptides and biopolymers have been discussed in this review.

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