A Monte Carlo simulation model of epidemic problem incorporating the interplaying between the crowd panic and infectious disease

In this paper, based on a multi-layer network consisting of a social network and a physical contact network, we propose a microscopic Monte Carlo simulation model to reproduce the interaction and spread phenomena in the crowd from complex network perspective. The model mainly is used to reproduce the epidemic spread in the situation that the crowd becomes panic showing preventive control behaviors. This coupled microscopic simulation model considers variable infectious rate, recovery rate, panic heterogeneity and preventive measures suitable for studying different actual scenarios. Under the proposed framework, we can take quantitative analysis to measure the influences of various infectious rate, recovery rate, network structure and preventive measures on the spreading of diseases and panic. By comparing a large number of statistical results of the simulation experiments to study different scenarios, it is displayed that the established micro-simulation framework has certain advantages in scalability to consider more different actual scenarios and facilitating the researchers to grasp the global trend to learn what consequences the individual behavior will make.

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

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.

نماذج المحاكاة- محاكاة مونتي كارلو- كأسلوب كمي من أساليب النمذجة واتخاذ القرارات - مقاربة نظرية وتطبيقية

Our research aims to try to present the modeling mechanisms in the field of simulation and quantitative methods. The research is a presentation of the role of quantitative methods in making investment project evaluation decisions, more than that and is the use of the Monte Carlo simulation model in evaluation and multi-period analysis of investment projects under conditions Risk and uncertainty. And highlighting the theoretical, scientific and practical importance of the Monte Carlo simulation method in particular, and the importance of using quantitative methods in helping to make decisions in general

Simulation of Large-Scale Magnetic Manipulation of Micro/Nano-Material Based on Monte Carlo Method

Magnetic assembly of micro/nano materials are of great interest due to their unique properties. These nano-scale materials can be ensemble with other matrixes to prepare for new functional micro/nano composites with enhanced specific properties such as, thermal conductivity. In this study, we demonstrated the distribution and magnetic alignment of nickel (Ni) nanoparticle/nanowires inside of a non-magnetic matrix, (e.g., water or a molten wax), experimentally and computationally. A two-dimensional Monte Carlo simulation model is employed to investigate the aggregate structures of Ni nanoparticle/nanowires subjected to a one-directional static magnetic field. It is anticipated that the applied magnetic strength will influence the attractive forces between nanoparticle/nanowires that will produce chain-like cluster structures parallel to magnetic direction where the aligned chains will be separated by a range of distances that are also function of magnetic field strength.

Simulation of Runway Operations with Application of Dynamic Wake Separations to Study Runway Limitations

This paper presents an evaluation of runway operations at Chicago O’Hare International Airport to estimate the impact of proposed wake vortex separation including Recategorization Phase II and III dynamic separations. The evaluation uses a Monte Carlo simulation model that considers arrival and departure operations. The simulation accounts for static and dynamic wake vortex separations, aircraft fleet mix, runway occupancy times, aircraft approach speeds, aircraft wake circulation capacity, environmental conditions, and operational error buffers. Airport data considered for this analysis are based on Airport Surface Detection Equipment Model X records from Chicago O’Hare International Airport from January to November 2016. Dynamic wake separations are tailored to each unique set of conditions by using environmental and aircraft performance parameters as input and allowing aircraft to be exposed to the same wake vortex strength as in Recategorization Phase II (RECAT II). The analysis shows that further reductions beyond RECAT II for aircraft pairs separated by 2 nautical miles or less is not operationally feasible. These wake separations already result in little to no wake dependency. When this is the case, the challenges in wake separation are to meet runway occupancy times and to make sure aircraft separations allow for human operational variations without resulting in aircraft turnarounds or double-aircraft-occupancy runway violations.