Resultados de búsqueda - "genetics"

  1. 141

    Solving a green logistics bi-level bi-objective problem. por Maldonado Pinto, Carmen Sayuri

    Publicado 2017
    “…The evolution performed in each population is done through a Biased Random Keys Genetic Algorithm( BRKGA). Furthermore, a path relinking algorithm is adapted in order to find the Pareto frontier for the bi-level bi-objective multi-commodity problem, in which the no dominated solutions of the tabu search and the co-evolutionary algorithms are used to initialize this procedure. …”
    Enlace del recurso
    Tesis
  2. 142

    Larval density mediates knockdown resistance to pyrethroid insecticides in adult Aedes aegypti por Grossman, Marissa K., Uc Puc, Valentín, Flores, Adriana E., Manrique Saide, Pablo C., Vazquez Prokopec, Gonzalo M.

    Publicado 2018
    “…To date, most research has focused on the genetic mechanisms underpinning resistance, yet it is unclear what role environmental drivers may play in shaping phenotypic expression. …”
    Enlace del recurso
    Artículo
  3. 143
  4. 144

    Solving a green logistics bi-level bi-objective problem. por Maldonado Pinto, Carmen Sayuri

    Publicado 2017
    “…The evolution performed in each population is done through a Biased Random Keys Genetic Algorithm( BRKGA). Furthermore, a path relinking algorithm is adapted in order to find the Pareto frontier for the bi-level bi-objective multi-commodity problem, in which the no dominated solutions of the tabu search and the co-evolutionary algorithms are used to initialize this procedure. …”
    Enlace del recurso
    Tesis
  5. 145
  6. 146
  7. 147
  8. 148
  9. 149

    Biomass and lipid induction strategies in microalgae for biofuel production and other applications por Alishah Aratboni, Hossein, Rafiei, Nahid, García Granados, Raúl, Alemzadeh, Abbas, Morones Ramírez, José Rubén

    Publicado 2019
    “…Here, we review these strategies which include modulating light intensity in cultures, controlling and varying CO2 levels and temperature, inducing nutrient starvation in the culture, the implementation of stress by incorporating heavy metal or inducing a high salinity condition, and the use of metabolic and genetic engineering techniques coupled with nanotechnology.…”
    Enlace del recurso
    Artículo
  10. 150
  11. 151
  12. 152
  13. 153
  14. 154
  15. 155
  16. 156

    The phenotype, psychotype and genotype of bruxism por Cruz Fierro, Norma, Martínez Fierro, Margarita de la Luz, Cerda Flores, Ricardo Martín, Gómez Govea, Mayra Alejandra, Delgado Enciso, Iván, Martínez de Villarreal, Laura Elia, González Ramírez, Mónica Teresa, Rodríguez Sánchez, Irám Pablo

    Publicado 2018
    “…Bruxism is a jaw muscle activity that involves physio-pathological, psycho-social, hereditary and genetic factors. The purpose of this study was to determine the associations between self-reported bruxism, anxiety, and neuroticism personality trait with the rs6313 polymorphism in the gene HTR2A. …”
    Enlace del recurso
    Artículo
  17. 157

    Performance evaluation and optimization of swarms of robots in a specific task por Márquez Vega, Luis Ángel

    Publicado 2019
    “…The Multi-Objective Particle Swarm Optimization (MOPSO), the Nondominated Sorting Genetic Algorithm II using Differential Evolution (NSGA-II-DE) and the Multiobjective Evolutionary Algorithm based on Decomposition using Differential Evolution (MOEA/D-DE) are used to optimize the control parameters ∆r, ∆o and ∆a for the proposed task in each experiment. …”
    Enlace del recurso
    Tesis
  18. 158

    Recent Understanding and Future Directions of Recurrent Corticotroph Tumors por Hinojosa Amaya, José Miguel, Lam Chung, César Ernesto, Cuevas Ramos, Daniel

    Publicado 2021
    “…Tumorigenesis involves genetic, epigenetic, and post-transcriptional disruption of cell-cycle regulators, which increase cell proliferation, POMC overexpression, ACTH transcription, and/or hypersecretion. …”
    Enlace del recurso
    Artículo
  19. 159

    Performance evaluation and optimization of swarms of robots in a specific task por Márquez Vega, Luis Ángel

    Publicado 2019
    “…The Multi-Objective Particle Swarm Optimization (MOPSO), the Nondominated Sorting Genetic Algorithm II using Differential Evolution (NSGA-II-DE) and the Multiobjective Evolutionary Algorithm based on Decomposition using Differential Evolution (MOEA/D-DE) are used to optimize the control parameters ∆r, ∆o and ∆a for the proposed task in each experiment. …”
    Enlace del recurso
    Tesis
  20. 160

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