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Data Generation for the Coupled System Composed of the Beef Cattle Production Infrastructure and the Transportation Services Infrastructure in Southwestern Kansas 

cattle2

This picture was taken during a field study.

This project has generated simulated data to model the behaviors of the interdependent beef production system and transportation infrastructure in southwestern Kansas, with due consideration of key social and economic factors. This process involves: i) modeling of the system as a multilayer network; ii) designing of an agent-based model incorporating all collected data and considering key social and economic aspects; iii) assessment of interdependencies between the beef production and transportation infrastructures, iv) evaluation of different scenarios and their impact on the infrastructure performance. The generated data has been organized and publicly shared with the final goal of increasing the understanding of these coupled systems. In the following, an information-sharing infrastructure will be added to the current interconnected cattle and transportation system through both network-based modeling and agent-based modeling. The impact of information sharing within the system will be assessed based on i) the number of participants; ii) the level of the exchanged data granularity; iii) the information-sharing network characteristics. 

The benefits of this work include an improved understanding of how to prevent and contain risks to these systems, thus contributing to the goal of greater safety and economic viability. Project data and software will be publicly shared through websites and results disseminated through academic conferences and journals. The outcome will facilitate the design of an information infrastructure connected with the cattle and transportation infrastructure. In addition, the interpretation of the results can benefit stakeholders to promote information infrastructure development and facilitate its acceptance by society. 

Duration September 1, 2017 - August 31, 2022

simulator

Simulator structure.


Investigators

Faculty and Scholar

Caterina Scoglio (Google Profile) (PI)

Jessica Heier Stamm (co-PI)

Gary Brase (co-PI)

Scott DeLoach (co-PI)

Don Gruenbacher (co-PI)

PhD Student

Qihui Yang


Products

Journals

Q. Yang, D. Gruenbacher, J.L. Heier Stamm, G.L. Brase, S.A. DeLoach, D.E. Amrine, C. Scoglio, "Developing an agent-based model to simulate beef cattle production and transportation in southwest Kansas", Physica A: Statistical Mechanics and its Applications, 2019.

Q. Yang, D.M. Gruenbacher, J.L. Heier Stamm, D.E. Amrine, G.L. Brase, S.A. DeLoach, C. Scoglio, "Impact of truck contamination and information sharing on foot-and-mouth disease spreading in beef cattle production systems", PLoS ONE 15(10): e0240819, 2020. 

T. Ferdousi, D. Gruenbacher, C. Scoglio, "A permissioned distributed ledger for the US beef cattle supply chain", IEEE Acess, 2020.

Q. Yang, C. Scoglio, D. Gruenbacher, "Robustness of supply chain networks against underload cascading failures", Physica A: Statistical Mechanics and its Applications, 563, 125466, 2021.

Q. Yang, D.M. Gruenbacher, G.L. Brase, J.L. Heier Stamm, S.A. DeLoach, C. Scoglio, "Simulating human behavioral changes in livestock production systems during an epidemic: the case of the US beef cattle industry", 2021, forthcoming.

C. Yi, Q. Yang, C. Scoglio, "Understanding the effects of the direct contacts and indirect contacts on the epidemic spreading among beef cattle farms in southwest Kansas", in progress.

Data

Data capturing each cattle movement and truck movement among premises over a year can be downloaded from the following repository:

Q. Yang, C. Scoglio, D. Gruenbacher (2019-06-25) “EAGER: SSDIM: Data Generation for the Coupled System Composed of the Beef Cattle Production Infrastructure and the Transportation Services Infrastructure in Southwestern Kansas.” DesignSafe-CI. https://doi.org/10.17603/ds2-3ft2-0441.

 


Supported by National Science Foundation under Award CMMI-1744812. Any opinions, findings, and conclusions or recommendations expressed in this website are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.