Monte Carlo Simulation of Spatio-Temporal Organization of Amphiphiles in Water and Air-Water Interface

1995 ◽  
Vol 5 (10) ◽  
pp. 1469-1489 ◽  
Author(s):  
Debashish Chowdhury
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Temporal Organization ◽  
Water Interface ◽  
Air Water Interface ◽  
Spatio Temporal

Discrete Fractional Component Monte Carlo Simulation Study of Dilute Nonionic Surfactants at the Air–Water Interface

Langmuir ◽  
2017 ◽  
Vol 33 (38) ◽  
pp. 9793-9802 ◽  
Author(s):  
Brian Yoo ◽  
Eliseo Marin-Rimoldi ◽  
Ryan Gotchy Mullen ◽  
Arben Jusufi ◽  
Edward J. Maginn
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Study ◽  
Nonionic Surfactants ◽  
Water Interface ◽  
Monte Carlo Simulation Study ◽  
Air Water Interface

scholarly journals Density Estimation of Spatio-temporal Point Patterns Using Moran's Statistic

2018 ◽  
Vol 7 (2) ◽  
pp. 80
Author(s):  
Jennifer L. Lorio ◽  
Norou Diawara ◽  
Lance A. Waller
Keyword(s):  
Infectious Disease ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Poisson Process ◽  
Common Factor ◽  
Disease Spread ◽  
Point Patterns ◽  
Rate Of Increase ◽  
Spatio Temporal ◽  
Over Time

Moran's Index is a statistic that measures spatial autocorrelation, quantifying the degree of dispersion (or spread) of objects in space. When investigating data in an area, a single Moran statistic may not give a sufficient summary of the autocorrelation spread. However, by partitioning the area and taking the Moran statistic of each subarea, we discover patterns of the local neighbors not otherwise apparent. In this paper, we consider the model of the spread of an infectious disease, incorporate time factor, and simulate a multilevel Poisson process where the dependence among the levels is captured by the rate of increase of the disease spread over time, steered by a common factor in the scale. The main consequence of our results is that our Moran statistic is calculated from an explicit algorithm in a Monte Carlo simulation setting. Results are compared to Geary's statistic and estimates of parameters under Poisson process are given.

Dynamic lattice Monte Carlo simulation of a model protein at an oil/water interface

2000 ◽  
Vol 112 (20) ◽  
pp. 9167-9185 ◽  
Author(s):  
Rebeccah E. Anderson ◽  
Vijay S. Pande ◽  
Clayton J. Radke
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Water Interface ◽  
Lattice Monte Carlo ◽  
Model Protein ◽  
Oil Water
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