Technical Note: An approach to building a Monte Carlo simulation model for a double scattering proton beam system

2018 ◽  
Vol 45 (6) ◽  
pp. 2660-2666 ◽  
Author(s):  
Jiankui Yuan ◽  
Rodney Ellis ◽  
Mitchell Machtay
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Model ◽  
Proton Beam ◽  
Technical Note ◽  
Double Scattering ◽  
Beam System ◽  
Monte Carlo Simulation Model

Monte Carlo Simulation Model for Predicting Salmonella Contamination of Chicken Liver as a Function of Serving Size for Use in Quantitative Microbial Risk Assessment

2021 ◽  
Author(s):  
Thomas Oscar
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Model ◽  
Chicken Liver ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Serving Size ◽  
Monte Carlo Simulation Model

The first step in quantitative microbial risk assessment (QMRA) is to determine distribution of pathogen contamination among servings of the food at some point in the farm-to-table chain. In the present study, distribution of Salmonella contamination among servings of chicken liver for use in QMRA was determined at meal preparation. A combination of five methods: 1) whole sample enrichment; 2) quantitative polymerase chain reaction; 3) cultural isolation; 4) serotyping; and 5) Monte Carlo simulation were used to determine Salmonella prevalence (P), number (N), and serotype for different serving sizes. In addition, epidemiological data were used to convert serotype data to virulence (V) values for use in QMRA. A Monte Carlo simulation model based in Excel and simulated with @Risk predicted Salmonella P, N, serotype, and V as a function of serving size from one (58 g) to eight (464 g) chicken livers. Salmonella P of chicken livers was 72.5% (58/80) per 58 g. Four serotypes were isolated from chicken livers: 1) Infantis (P = 28%, V = 4.5); 2) Enteritidis (P = 15%, V = 5); 3) Typhimirium (P = 15%, V = 4.8); and 4) Kentucky (P = 15%, V = 0.8). Median Salmonella N was 1.76 log per 58 g (range: 0 to 4.67 log/58 g) and was not affected ( P > 0.05) by serotype. The model predicted a non-linear increase ( P ≤ 0.05) of Salmonella P from 72.5% per 58 g to 100% per 464 g, minimum N from 0 log per 58 g to 1.28 log per 464 g, and median N from 1.76 log per 58 g to 3.22 log per 464 g. Regardless of serving size, predicted maximum N was 4.74 log, mean V was 3.9, and total N was 6.65 log per lot (10,000 chicken livers). The data acquired and model developed in this study fill an important data and modeling gap in QMRA for Salmonella and chicken liver.

Monte Carlo Simulation Model of Micro Light Beam Solidification

2008 ◽  
Vol 28 (12) ◽  
pp. 2388-2393
Author(s):  
王翔 Wang Xiang ◽  
裴香涛 Pei Xiangtao ◽  
邵鹏 Shao Peng ◽  
黄文浩 Huang Wenhao
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Model ◽  
Light Beam ◽  
Monte Carlo Simulation Model
Sign in / Sign up

Export Citation Format

Share Document