Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density Functions

[EN] The Baranyi-Roberts model describes the dynamics of the volumetric densities of two interacting cell populations. We randomize this model by considering that the initial conditions are random variables whose distributions are determined by using sample data and the principle of maximum entropy....

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Autores: Bevia-Escrig, Vicente-José, Burgos-Simon, Clara|||0000-0001-6385-4263, Cortés, J.-C.|||0000-0002-6528-2155, Villanueva Micó, Rafael Jacinto|||0000-0002-0131-0532
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/180371
Acceso en línea:https://riunet.upv.es/handle/10251/180371
Access Level:acceso abierto
Palabra clave:Uncertainty quantification
Competitive stochastic model
Model simulation
Model prediction
Principle of maximum entropy
Optimization
MATEMATICA APLICADA
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spelling Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density FunctionsBevia-Escrig, Vicente-JoséBurgos-Simon, Clara|||0000-0001-6385-4263Cortés, J.-C.|||0000-0002-6528-2155Villanueva Micó, Rafael Jacinto|||0000-0002-0131-0532Uncertainty quantificationCompetitive stochastic modelModel simulationModel predictionPrinciple of maximum entropyOptimizationMATEMATICA APLICADA[EN] The Baranyi-Roberts model describes the dynamics of the volumetric densities of two interacting cell populations. We randomize this model by considering that the initial conditions are random variables whose distributions are determined by using sample data and the principle of maximum entropy. Subsequenly, we obtain the Liouville-Gibbs partial differential equation for the probability density function of the two-dimensional solution stochastic process. Because the exact solution of this equation is unaffordable, we use a finite volume scheme to numerically approximate the aforementioned probability density function. From this key information, we design an optimization procedure in order to determine the best growth rates of the Baranyi-Roberts model, so that the expectation of the numerical solution is as close as possible to the sample data. The results evidence good fitting that allows for performing reliable predictions.This work has been supported by the Spanish Ministerio de Economia, Industria y Competitividad (MINECO), the Agencia Estatal de Investigacion (AEI) and Fondo Europeo de Desarrollo Regional (FEDER UE) grant MTM2017-89664-P.MDPI AGFacultad de Administración y Dirección de EmpresasDepartamento de Matemática AplicadaEscuela Técnica Superior de Ingeniería Geodésica, Cartográfica y TopográficaInstituto Universitario de Matemática MultidisciplinarAgencia Estatal de InvestigaciónEuropean Regional Development FundRepositorio Institucional de la Universitat Politècnica de València Riunet20212021-06-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/180371reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengAgencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 MTM2017-89664-P PROBLEMAS DINAMICOS CON INCERTIDUMBRE SIMULABLE: MODELIZACION MATEMATICA, ANALISIS, COMPUTACION Y APLICACIONESopen accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento (by)http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/1803712026-06-13T07:49:27Z
dc.title.none.fl_str_mv Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density Functions
title Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density Functions
spellingShingle Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density Functions
Bevia-Escrig, Vicente-José
Uncertainty quantification
Competitive stochastic model
Model simulation
Model prediction
Principle of maximum entropy
Optimization
MATEMATICA APLICADA
title_short Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density Functions
title_full Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density Functions
title_fullStr Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density Functions
title_full_unstemmed Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density Functions
title_sort Uncertainty Quantification of Random Microbial Growth in a Competitive Environment via Probability Density Functions
dc.creator.none.fl_str_mv Bevia-Escrig, Vicente-José
Burgos-Simon, Clara|||0000-0001-6385-4263
Cortés, J.-C.|||0000-0002-6528-2155
Villanueva Micó, Rafael Jacinto|||0000-0002-0131-0532
author Bevia-Escrig, Vicente-José
author_facet Bevia-Escrig, Vicente-José
Burgos-Simon, Clara|||0000-0001-6385-4263
Cortés, J.-C.|||0000-0002-6528-2155
Villanueva Micó, Rafael Jacinto|||0000-0002-0131-0532
author_role author
author2 Burgos-Simon, Clara|||0000-0001-6385-4263
Cortés, J.-C.|||0000-0002-6528-2155
Villanueva Micó, Rafael Jacinto|||0000-0002-0131-0532
author2_role author
author
author
dc.contributor.none.fl_str_mv Facultad de Administración y Dirección de Empresas
Departamento de Matemática Aplicada
Escuela Técnica Superior de Ingeniería Geodésica, Cartográfica y Topográfica
Instituto Universitario de Matemática Multidisciplinar
Agencia Estatal de Investigación
European Regional Development Fund
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Uncertainty quantification
Competitive stochastic model
Model simulation
Model prediction
Principle of maximum entropy
Optimization
MATEMATICA APLICADA
topic Uncertainty quantification
Competitive stochastic model
Model simulation
Model prediction
Principle of maximum entropy
Optimization
MATEMATICA APLICADA
description [EN] The Baranyi-Roberts model describes the dynamics of the volumetric densities of two interacting cell populations. We randomize this model by considering that the initial conditions are random variables whose distributions are determined by using sample data and the principle of maximum entropy. Subsequenly, we obtain the Liouville-Gibbs partial differential equation for the probability density function of the two-dimensional solution stochastic process. Because the exact solution of this equation is unaffordable, we use a finite volume scheme to numerically approximate the aforementioned probability density function. From this key information, we design an optimization procedure in order to determine the best growth rates of the Baranyi-Roberts model, so that the expectation of the numerical solution is as close as possible to the sample data. The results evidence good fitting that allows for performing reliable predictions.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-06-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/180371
url https://riunet.upv.es/handle/10251/180371
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 MTM2017-89664-P PROBLEMAS DINAMICOS CON INCERTIDUMBRE SIMULABLE: MODELIZACION MATEMATICA, ANALISIS, COMPUTACION Y APLICACIONES
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI AG
publisher.none.fl_str_mv MDPI AG
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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