Experimenting the Impact of Pedestrianisation on Urban Pollution Using Tangible Agent-Based Simulations: Application to Hoan Kiem District, Hanoi, Vietnam

AbstractSocial media networks (SMN) such as Facebook and Twitter are infamous for facilitating the spread of potentially false rumors. Although it has been argued that SMN enable their users to identify and challenge false rumors through collective efforts to make sense of unverified information—a process typically referred to as self-correction—evidence suggests that users frequently fail to distinguish among rumors before they have been resolved. How users evaluate the veracity of a rumor can depend on the appraisals of others who participate in a conversation. Affordances such as the searchability of SMN, which enables users to learn about a rumor through dedicated search and query features rather than relying on interactions with their relational connections, might therefore affect the veracity judgments at which they arrive. This paper uses agent-based simulations to illustrate that searchability can hinder actors seeking to evaluate the trustworthiness of a rumor’s source and hence impede self-correction. The findings indicate that exchanges between related users can increase the likelihood that trustworthy agents transmit rumor messages, which can promote the propagation of useful information and corrective posts.

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Process Modeling and Simulation of Tableting—An Agent-Based Simulation Methodology for Direct Compression

Pharmaceutics ◽

10.3390/pharmaceutics13070996 ◽

2021 ◽

Vol 13 (7) ◽

pp. 996

Author(s):

Niels Lasse Martin ◽

Ann Kathrin Schomberg ◽

Jan Henrik Finke ◽

Tim Gyung-min Abraham ◽

Arno Kwade ◽

...

Keyword(s):

Raw Materials ◽

Pilot Scale ◽

Physical Models ◽

Agent Based Simulation ◽

Validation Data ◽

Agent Based ◽

Industrial Processing ◽

Digital Twins ◽

Product And Process ◽

The Impact

In pharmaceutical manufacturing, the utmost aim is reliably producing high quality products. Simulation approaches allow virtual experiments of processes in the planning phase and the implementation of digital twins in operation. The industrial processing of active pharmaceutical ingredients (APIs) into tablets requires the combination of discrete and continuous sub-processes with complex interdependencies regarding the material structures and characteristics. The API and excipients are mixed, granulated if required, and subsequently tableted. Thereby, the structure as well as the properties of the intermediate and final product are influenced by the raw materials, the parametrized processes and environmental conditions, which are subject to certain fluctuations. In this study, for the first time, an agent-based simulation model is presented, which enables the prediction, tracking, and tracing of resulting structures and properties of the intermediates of an industrial tableting process. Therefore, the methodology for the identification and development of product and process agents in an agent-based simulation is shown. Implemented physical models describe the impact of process parameters on material structures. The tablet production with a pilot scale rotary press is experimentally characterized to provide calibration and validation data. Finally, the simulation results, predicting the final structures, are compared to the experimental data.

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Integrated IEW-TOPSIS and Fire Dynamics Simulation for Agent-Based Evacuation Modeling in Industrial Safety

Safety ◽

10.3390/safety7020047 ◽

2021 ◽

Vol 7 (2) ◽

pp. 47

Author(s):

Wattana Chanthakhot ◽

Kasin Ransikarbum

Keyword(s):

Emergency Evacuation ◽

Industrial Sector ◽

Industrial Safety ◽

Dynamics Simulation ◽

Entropy Weight ◽

Fire Dynamics ◽

Evacuation Simulation ◽

Evacuation Modeling ◽

Agent Based ◽

The Impact

Emergency events in the industrial sector have been increasingly reported during the past decade. However, studies that focus on emergency evacuation to improve industrial safety are still scarce. Existing evacuation-related studies also lack a perspective of fire assembly point’s analysis. In this research, location of assembly points is analyzed using the multi-criteria decision analysis (MCDA) technique based on the integrated information entropy weight (IEW) and techniques for order preference by similarity to ideal solution (TOPSIS) to support the fire evacuation plan. Next, we propose a novel simulation model that integrates fire dynamics simulation coupled with agent-based evacuation simulation to evaluate the impact of smoke and visibility from fire on evacuee behavior. Factors related to agent and building characteristics are examined for fire perception of evacuees, evacuees with physical disabilities, escape door width, fire location, and occupancy density. Then, the proposed model is applied to a case study of a home appliance factory in Chachoengsao, Thailand. Finally, results for the total evacuation time and the number of remaining occupants are statistically examined to suggest proper evacuation planning.

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An application of agent-based modeling to explore the impact of decreasing incarceration rates and increasing drug treatment access on sero-discordant partnerships among people who inject drugs

International Journal of Drug Policy ◽

10.1016/j.drugpo.2021.103194 ◽

2021 ◽

Vol 94 ◽

pp. 103194

Author(s):

Sabriya L. Linton ◽

Don C. Des Jarlais ◽

Joseph T. Ornstein ◽

Matt Kasman ◽

Ross Hammond ◽

...

Keyword(s):

Drug Treatment ◽

People Who Inject Drugs ◽

Agent Based Modeling ◽

Treatment Access ◽

Agent Based ◽

The Impact

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Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model

Scientific Reports ◽

10.1038/s41598-020-79000-y ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Jonatan Almagor ◽

Stefano Picascia

Keyword(s):

High Rate ◽

Contact Tracing ◽

Agent Based Model ◽

Agent Based ◽

The Social ◽

Behavioural Factors ◽

The Impact ◽

Different Levels ◽

User Rate

AbstractA contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. Using an agent-based model, we explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale. Agents are heterogeneous in their characteristics and are linked in a multi-layered network representing the social structure—including households, friendships, employment and schools. We explore the interplay of various adoption rates of the contact-tracing app, different levels of testing capacity, and behavioural factors to assess the impact on the epidemic. Results suggest that a contact tracing app can contribute substantially to reducing infection rates in the population when accompanied by a sufficient testing capacity or when the testing policy prioritises symptomatic cases. As user rate increases, prevalence of infection decreases. With that, when symptomatic cases are not prioritised for testing, a high rate of app users can generate an extensive increase in the demand for testing, which, if not met with adequate supply, may render the app counterproductive. This points to the crucial role of an efficient testing policy and the necessity to upscale testing capacity.

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