Zobrazeno 1 - 10
of 100
pro vyhledávání: '"Rafael-J. Villanueva"'
Publikováno v:
Epidemiologia, Vol 2, Iss 2, Pp 140-161 (2021)
The administration of vaccines against the coronavirus disease 2019 (COVID-19) started in early December of 2020. Currently, there are only a few approved vaccines, each with different efficacies and mechanisms of action. Moreover, vaccination progra
Externí odkaz:
https://doaj.org/article/01928ec4e11f404eb24befca37d4157a
Autor:
David Martínez‐Rodríguez, J. Manuel Colmenar, J. Ignacio Hidalgo, Rafael‐J. Villanueva Micó, Sancho Salcedo‐Sanz
Publikováno v:
Energy Science & Engineering, Vol 8, Iss 4, Pp 1068-1079 (2020)
Abstract Grammatical Swarm is a search and optimization algorithm that belongs to the more general Grammatical Evolution family, which works with a set of solutions called individuals or particles. It uses the Particle Swarm Optimization algorithm as
Externí odkaz:
https://doaj.org/article/2294219b681e41c89e98089898d72105
Autor:
José M. Garrido, David Martínez-Rodríguez, Fernando Rodríguez-Serrano, Sorina-M. Sferle, Rafael-J. Villanueva
Publikováno v:
Mathematics, Vol 9, Iss 10, p 1132 (2021)
Mathematical models have been remarkable tools for knowing in advance the appropriate time to enforce population restrictions and distribute hospital resources. Here, we present a mathematical Susceptible-Exposed-Infectious-Recovered (SEIR) model to
Externí odkaz:
https://doaj.org/article/54b71e88919e4036aebf93feaa6c2fa4
Publikováno v:
Infectious Disease Modelling, Vol 9, Iss 3, Pp 744-762 (2024)
Vaccine efficacy and its quantification is a crucial concept for the proper design of public health vaccination policies. In this work we proposed a mathematical model to estimate the efficacy of the influenza vaccine in a real-word scenario. In part
Externí odkaz:
https://doaj.org/article/b3f97204f6724d53a5d1eb066b2f2570
Publikováno v:
Abstract and Applied Analysis, Vol 2016 (2016)
A probabilistic model is proposed to study the transmission dynamics of the cocaine consumption in Spain during the period of 1995–2011. Using the so-called probabilistic fitting technique, we study if the model is able to capture the data uncertai
Externí odkaz:
https://doaj.org/article/33789b0f7992458e8e4673e190039741
Autor:
Javier Díez-Domingo, Víctor Sánchez-Alonso, Rafael-J. Villanueva, Luis Acedo, José-Antonio Moraño, Javier Villanueva-Oller
Publikováno v:
Viruses, Vol 9, Iss 10, p 300 (2017)
The Human papillomaviruses (HPV) vaccine induces a herd immunity effect in genital warts when a large number of the population is vaccinated. This aspect should be taken into account when devising new vaccine strategies, like vaccination at older age
Externí odkaz:
https://doaj.org/article/54adaf80094b4f86bfdd95f234803374
Publikováno v:
Abstract and Applied Analysis, Vol 2013 (2013)
This paper presents a computational study on a quasi-Galerkin projection-based method to deal with a class of systems of random ordinary differential equations (r.o.d.e.’s) which is assumed to depend on a finite number of random variables (r.v.’s
Externí odkaz:
https://doaj.org/article/d3c9fbc403b1428ca204709bd2cd9183
Publikováno v:
Mathematical Methods in the Applied Sciences.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf03a000bbc32268733524377ea643f7
https://doi.org/10.1002/mma.9226
https://doi.org/10.1002/mma.9226
Autor:
David Martínez-Rodríguez, Ricardo Novella, Gabriela Bracho, Josep Gomez-Soriano, Cassio Fernandes, Tommaso Lucchini, Augusto Della Torre, Rafael-J. Villanueva, J. Ignacio Hidalgo
Publikováno v:
Applied Soft Computing. 143:110401
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::502bfead0896135db99764866c5d3977
https://doi.org/10.1016/j.asoc.2023.110401
https://doi.org/10.1016/j.asoc.2023.110401
Publikováno v:
Communications in Nonlinear Science and Numerical Simulation. 119:107097
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c711a847b3a3332d51ce96ddd4cc9713
https://doi.org/10.1016/j.cnsns.2023.107097
https://doi.org/10.1016/j.cnsns.2023.107097