Pluralistic ignorance, a well-documented socio-psychological conformity phenomenon, involves discrepancies between private attitude and public opinion in certain social contexts. However, continuous opinion dynamics models based on a bounded confidence assumption fail to accurately model pluralistic ignorance because they do not address scenarios in which non-conformists do not need to worry about holding and expressing conflicting opinions. Such scenarios reduce the power of continuous opinion dynamics models to explain why certain groups doubt or change their opinions in response to minority views. To simulate the effects of (a) private acceptance of informational social influence and (b) public compliance with normative social influence on pluralistic ignorance and minority influences, we have created an agent-based simulation model in which attitude and opinion respectively represent an agent's private and expressed thoughts. Results from a series of simulation experiments indicate model validity equal to or exceeding those of existing opinion dynamics models that are also based on the bounded confidence assumption, but with different dynamics and outcomes in terms of collective opinion and attitude. The results also support the use of our proposed model for computational social psychology applications.

Immediate treatment with an automated external defibrillator (AED) increases out-of-hospital cardiac arrest (OHCA) patient survival potential. While considerable attention has been given to determining optimal public AED locations, spatial and temporal factors such as time of day and distance from emergency medical services (EMSs) are understudied. Here we describe a geocomputational genetic algorithm with a new stirring operator (GANSO) that considers spatial and temporal cardiac arrest occurrence factors when assessing the feasibility of using Taipei 7-Eleven stores as installation locations for AEDs. Our model is based on two AED conveyance modes, walking/running and driving, involving service distances of 100 and 300 meters, respectively. Our results suggest different AED allocation strategies involving convenience stores in urban settings. In commercial areas, such installations can compensate for temporal gaps in EMS locations when responding to nighttime OHCA incidents. In residential areas, store installations can compensate for long distances from fire stations, where AEDs are currently held in Taipei.

Identifying the most influential individuals spreading information or infectious diseases can assist or hinder information dissemination, product exposure, and contagious disease detection. Hub nodes, high betweenness nodes, high closeness nodes, and highk-shell nodes have been identified as good initial spreaders, but efforts to use node diversity within network structures to measure spreading ability are few. Here we describe a two-step framework that combines global diversity and local features to identify the most influential network nodes. Results from susceptible-infected-recovered epidemic simulations indicate that our proposed method performs well and stably in single initial spreader scenarios associated with various complex network datasets.

In previous continuous opinion dynamics models based on bounded confidence assumptions, individuals can only influence each other’s opinions when those opinions are sufficiently close; subsequently, agents construct their self-opinions using opinions collected from other agents. All of these models lack the element of an agent’s inner self-attitude. In this paper we describe our proposal for a self-perception model in which agents are aware of differences between their attitudes and expressed opinions on specific issues. Our agents are based on a mix of self-perception and cognitive dissonance theory that allows them to self-adjust discomfort caused by inconsistencies between inner attitudes and expressed opinions. Results from a series of simulation experiments indicate that our model captures the gap between inner attitude and external opinion in explaining the private acceptance/public conformity phenomenon. We conclude with a demonstration of how our proposed model can be used in sociological studies of pluralistic ignorance.

The emerging disease of rabies was confirmed in Taiwan ferret badgers (FBs) and reported to the World Organization for Animal Health (OIE) on July 17, 2013. The spread of wildlife rabies can be related to neighborhood countries in Asia. The phylogenetic analysis was conducted by maximum likelihood (ML) methods and the Bayesian coalescent approach based on the glycoprotein (G) and nucleoprotein (N) genes. The phylogeographic and spatial temporal dynamics of viral transmission were determined by using SPREAD, QGIS. Therefore, the origin and the change with time of the viruses can be identified. Results showed the rabies virus of FB strains in Taiwan is a unique clade among other strains in Asia. According to the phylogeographic coalescent tree, three major genotypes of the FB rabies virus have circulated in three different geographical areas in Taiwan. Two genotypes have distributed into central and southern Taiwan between two ecological river barriers. The third genotype has been limited in southeastern Taiwan by the natural mountain barrier. The diversity of FB rabies viruses indicates that the biological profile of FBs could vary in different geographical areas in Taiwan. An enhanced surveillance system needs to be established near the currently identified natural barriers for early warnings of the rabies virus outbreak in Taiwan.

The speed with which emergency personnel can provide emergency treatment is crucial to reducing death and disability among acute and critically ill patients. Unfortunately, the rapid development of cities and increased numbers of vehicles are preventing emergency vehicles from easily reaching locations where they are needed. A significant number of researchers are experimenting with vehicular networks to address this issue, but in most studies the focus has been on communication technologies and protocols, with few efforts to assess how network applications actually support emergency medical care. Our motivation was to search the literature for suggested methods for assisting emergency vehicles, and to use simulations to evaluate them. Our results and evidence-based studies were cross-referenced to assess each method in terms of cumulative survival ratio (CSR) gains for acute and critically ill patients. Simulation results indicate that traffic light preemption resulted in significant CSR increases of between 32.4% and 90.2%. Route guidance was found to increase CSRs from 14.1% to 57.8%, while path clearing increased CSRs by 15.5% or less. It is our hope that this data will support the efforts of emergency medical technicians, traffic managers, and policy makers.