Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Alejandro Mosqueda"'
Autor:
Alejandro Mosqueda
Publikováno v:
Análisis Filosófico, Vol 39, Iss 1, Pp 51-67 (2019)
This paper is an assessment of the conclusion that negligent agents are not morally responsible for the damages they cause, reached by Matt King in “The Problem with Negligence” (2009). King’s argument involves two difficult issues that are oft
Externí odkaz:
https://doaj.org/article/1950291f30534af08ad30c2e2a1fbd22
Autor:
Osval A. Montesinos-López, Leonardo Crespo-Herrera, Carolina Saint Pierre, Bernabe Cano-Paez, Gloria Isabel Huerta-Prado, Brandon Alejandro Mosqueda-González, Sofia Ramos-Pulido, Guillermo Gerard, Khalid Alnowibet, Roberto Fritsche-Neto, Abelardo Montesinos-López, José Crossa
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
IntroductionBecause Genomic selection (GS) is a predictive methodology, it needs to guarantee high-prediction accuracies for practical implementations. However, since many factors affect the prediction performance of this methodology, its practical i
Externí odkaz:
https://doaj.org/article/bc352c418ea44b3aa88d1cf294b125fa
Autor:
Osval A. Montesinos-López, Sofia Ramos-Pulido, Carlos Moisés Hernández-Suárez, Brandon Alejandro Mosqueda González, Felícitas Alejandra Valladares-Anguiano, Paolo Vitale, Abelardo Montesinos-López, José Crossa
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
IntroductionGenomic selection (GS) has gained global importance due to its potential to accelerate genetic progress and improve the efficiency of breeding programs.Objectives of the researchIn this research we proposed a method to improve the predict
Externí odkaz:
https://doaj.org/article/73541120d2894d3b9cbd8a631542b77a
Akademický článek
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Autor:
Osval A. Montesinos-López, Abelardo Montesinos-López, David Alejandro Bernal Sandoval, Brandon Alejandro Mosqueda-Gonzalez, Marco Alberto Valenzo-Jiménez, José Crossa
Publikováno v:
Frontiers in Genetics, Vol 13 (2022)
The genomic selection (GS) methodology proposed over 20 years ago by Meuwissen et al. (Genetics, 2001) has revolutionized plant breeding. A predictive methodology that trains statistical machine learning algorithms with phenotypic and genotypic data
Externí odkaz:
https://doaj.org/article/a551e634db0a446d94dcdb109331446b
Autor:
Osval Antonio Montesinos López, Brandon Alejandro Mosqueda González, Abel Palafox González, Abelardo Montesinos López, José Crossa
Publikováno v:
Frontiers in Genetics, Vol 13 (2022)
The adoption of machine learning frameworks in areas beyond computer science have been facilitated by the development of user-friendly software tools that do not require an advanced understanding of computer programming. In this paper, we present a n
Externí odkaz:
https://doaj.org/article/2a09f85047494f8792fe24e59eb02321
Akademický článek
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Akademický článek
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Autor:
Osval A. Montesinos López, Brandon Alejandro Mosqueda González, Abelardo Montesinos López, José Crossa
Publikováno v:
Genes; Volume 14; Issue 5; Pages: 1003
Genomic selection (GS) is revolutionizing plant breeding. However, because it is a predictive methodology, a basic understanding of statistical machine-learning methods is necessary for its successful implementation. This methodology uses a reference
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5c18c185fcaf21d4742a64731215e23
https://doi.org/10.3390/genes14051003
https://doi.org/10.3390/genes14051003
Autor:
Tadeo Resendiz, Umut Aybar, Mario Alejandro Mosqueda Thompson, Luis Camarillo, Luis Mujica, Juan Aguilar, Fernanda Tellez, Antonio Andrade, Roger Ortiz, Carlos Perez, Obed Sánchez
Publikováno v:
SPE Production & Operations. 32:476-490
Summary Asphaltene precipitation is a common phenomenon in mature reservoirs that seriously impairs oil production. In high-temperature (HT) fractured carbonate reservoirs, the situation becomes critical when asphaltene precipitates at reservoir cond
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2af7cea3c1a9c1ee04aa59e2d5747611
https://doi.org/10.2118/178956-pa
https://doi.org/10.2118/178956-pa