Multivariate Statistical Machine Learning Methods for Genomic Prediction

This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension. The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool

O controle social e o empoderamento do SUS : o direito à saúde promovendo cidadania

Discorre a respeito da participação popular nos regimes democráticos na busca de um verdadeiro Estado Democrático de Direito

Diseño hidráulico de estación de bombeo y línea de impulsión de desagüe de centros poblados del distrito de Pachacámac

Publicación a texto completo no autorizada por el autorEfectúa el diseño hidráulico de una estación de bombeo con su línea de impulsión, que transporte los desagües domésticos producidos por los centros poblados de San Juan Puente Manchay, Ampliación Zona "A" Puente de Manchay, Villa Esperanza y Puente de Manchay Tambo Inga Pampa Flores, pertenecientes al distrito de Pachacamac, hasta su entrega final en un buzón existente. Esto permitirá mejorar las condiciones de vida de los habitantes del lugar, disminuyendo las enfermedades producidas por una inadecuada disposición de los desagües.Trabajo de suficiencia profesiona

"Echinospartum algibicum (Leguminosae)" regeneración de plantas mediante organogémesis adventicia

chinospartum algibicum (Leguminosae) regeneración de plantas mediante organogénesis adventicia. La germinación in vitro de semillas de E.algibicum, especie endémica de la Sierra de Grazalema, S de España, así como la inducción de yemas múltiples y el desarrollo posterior de brotes, se consiguió en el medio de cultivo de Murashige y Skoog a mitad de concentración, con 3% de sacarosa y citoquinina (BAP) a las concentraciones de 1 y 2 mg l -1 (ECH-1, ECH-2). La germinación de las semillas se incrementó significativamente de 38% a casi 100% tras la escarificación. El número medio de yemas formado después de 35-40 días fue de 8,6 y 6,9 en los medios ECH-1 y ECH-2 respectivamente. Los brotes fueron posteriormente enraizados en el mismo medio nutritivo pero sustituyendo la citoquinina por la auxina IBA (0.2 mg l -1 ). En este medio, se consiguió un porcentaje medio de enraizamiento de 35,49 después de 25-30 días, y en algunos casos la formación de masas de callo en las zonas de los brotes en contacto con el medio nutritivo. Finalmente, se ensayó la aclimatación de estas plantas a suelo mediante reducción progresiva de la humedad relativa y tras varios tratamientos que incluyeron el uso de CO 2 , la adición de inoculo de micorriza (Glomus deserticola) al substrato de cultivo, así como el uso de un medio de cultivo sin reguladores de crecimiento y mitad de sacarosa previo paso a suelo. Los porcentajes de supervivencia después de 60 días en suelo fueron mayores para la plantas sometidas a los tratamientos con CO 2 aunque los porcentajes medios fueron algo bajos

Multivariate Statistical Machine Learning Methods for Genomic Prediction

This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension. The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool

Discrete-time switching MPC with applications to mitigate resistance in viral infections

Many engineering applications can be described as switched linear systems, in which the manipulated control action is the time-dependent switching signal. In such a case, the control strategy must select a linear autonomous system at each time step, among a finite number of them. Even when this selection can be done by solving a Dynamic Programming (DP) problem, the implementation of such a solution is often difficult and state/control constraints cannot be explicitly accounted for. In this paper, a new set-based Model Predictive Control (MPC) strategy is presented to handle switched linear systems in a tractable form. The optimization problem at the core of the MPC formulation consists of an easy-to-solve mixed-integer optimization problem, whose solution is applied in a receding horizon way. The medical application of viral mutation and its respective drug resistance is addressed to acute and chronic infections. The objective is to attenuate the effect of mutations on the total viral load, and the numerical results suggested that the proposed strategy outperforms the schedule for available treatments.Fil: Anderson, Alejandro Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: González, Alejandro Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Ferramosca, Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Hernandez Vargas, Esteban Abelardo. Frankfurt Institute For Advanced Studies-fias; Alemani

Discrete-time MPC for switched systems with applications to biomedical problems

Switched systems in which the manipulated control action is the time-dependingswitching signal describe many engineering problems, mainly related to biomedical applications. In such a context, to control the system means to select an autonomous system - at each time step - among a given finite family. Even when this selection can be done by solving a Dynamic Programming (DP) problem, such a solution is often difficult to apply, and state/control constraints cannot be explicitly considered. In this work a new set-based Model Predictive Control (MPC) strategy is proposed to handle switched systems in a tractable form. The optimization problem at the core of the MPC formulation consists in an easy-to-solve mixed-integer optimization problem, whose solution is applied in a receding horizon way. Two biomedical applications are simulated to test the controller: (i) the drug schedule to attenuate the effect of viralmutation and drugs resistance on the viral load, and (ii) the drug schedule for Triple Negative breast cancer treatment. The numerical results suggest that the proposed strategy outperform the schedule for available treatments.Fil: Anderson, Alejandro Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: González, Alejandro Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Ferramosca, Antonio. Universidad Tecnológica Nacional; ArgentinaFil: Hernandez Vargas, Esteban Abelardo. Frankfurt Institute For Advanced Studies-fias; Alemani

Digital transformation model for the development of tourism companies

The way of consuming information and the way we communicate is evolving thanks to advances in technology, the digital transformation breaks new ground in the tourism sector when communicating its services, offers and messages to customers. One of the challenges facing tourism professionals is understanding technological trends to innovate and reinvent their services towards clients. For which we propose a model to adopt the digital transformation in the development of tourist companies. A questionnaire was carried out with 20 managers from the sector with 95% reliability related to customer management, competition and innovation strategy regarding digital transformation; organizational culture and change management regarding business development. The results show that 45% indicate that they rarely keep a record with updated customer data. 35% indicate that they sometimes evaluate business models to anticipate their competition. 35% rarely use any methodology to develop a business model. This reflects that companies must manage data for later use, invest resources in innovating the business model, and have technological professionals who reinvent business processes.Campus Lima Centr

Optimal control strategies to tailor antivirals for acute infectious diseases in the host

Several mathematical models in SARS-CoV-2 have shown how target-cell model can help to understand the spread of the virus in the host and how potential candidates of antiviral treatments can help to control the virus. Concepts as equilibrium and stability show to be crucial to qualitative determine the best alternatives to schedule drugs, according to effectivity in inhibiting the virus infection and replication rates. Important biological events such as rebounds of the infections (when antivirals are incorrectly interrupted) can also be explained by means of a dynamic study of the target-cell model. In this work a full characterization of the dynamical behavior of the target-cell models under control actions is made and, based on this characterization, the optimal fixeddose antiviral schedule that produces the smallest amount of dead cells (without viral load rebounds) is computed. Several simulation results - performed by considering real patient data - show the potential benefits of both, the model characterization and the control strategy.Fil: Perez, Mara Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Abuin, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Actis, Marcelo Jesús. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química; ArgentinaFil: Ferramosca, Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Università Degli Studi Di Bergamo; ItaliaFil: Hernandez Vargas, Esteban Abelardo. Universidad Nacional Autónoma de México; MéxicoFil: González, Alejandro Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin

Detection and Analysis of Anomalies in People Density and Mobility Through Wireless Smartphone Tracking

One of the challenges of this century is to use the data that a smart-city provides to make life easier for its inhabitants. Speci cally, within the area of urban mobility, the possibility of detecting anomalies in the movement of pedestrians and vehicles is an issue of vital importance for the planning and administration of a city. The aim of this paper is to propose a methodology to detect the movement of people from the information transmitted by their smart mobile devices, analyze these data, and be able to detect or recognize anomalies in their behavior. In order to validate this methodology, different experiments have been carried out based on real data aiming to extract knowledge, as well as obtaining a characterisation of the anomalies detected. The use of this methodology might help the city policy makers to better manage their mobility and transport resources.This work was supported by in part by the Dirección General de Tráfico under Project SPIP2017-02116, in part by the Ministerio de Ciencia, Innovación y Universidades under Grant RTI2018-102002-A-I00, in part by the Ministerio español de Economía y Competitividad under Grant TIN2017-85727-C4-2-P, in part by the FEDER under Grant TEC2015-68752, and in part by the FEDER y Junta de Andalucía under Project B-TIC-402-UGR18