When and How to Apply Statistics, Machine Learning and Deep Learning Techniques

Machine Learning has become 'commodity' in engineering and experimental sciences, as calculus and statistics did before. After the hype produced during the 00's, machine learning (statistical learning, neural networks, etc.) has become a solid and reliable set of techniques available to the general researcher population to be included in their common procedures, far from the mysticism surrounding this field when only ML experts could solve modeling and prediction problems using such novel algorithms. But while knowledge on this field has settled among professionals, novice ML users still have trouble to decide when determined techniques could and should be applied to solve a given problem, sometimes ending with over-complicated solutions for simplistic problems, or complex problems partially solved by simplistic methods. This tutorial wants to introduce the most common techniques on statistical learning and neural networks, towards showing the proper techniques for each given scenario.This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 639595).Peer ReviewedPostprint (author's final draft

Minimal set of generators of controllability space for singular linear dynamical systems

Due to the significant role played by singular systems in the form E ¿ x ( t ) = Ax ( t ) , on mathematical modeling of science and engineering problems; in the last years recent years its interest in the descriptive analysis of its structural and dynamic properties. However, much less effort has been devoted to studying the exact con- trollability by measuring the minimum set of controls needed to direct the entire system E ¿ x ( t ) = Ax ( t ) to any desired state. In this work, we focus the study on obtaining the set of all matrices B with a minimal number of columns, by making the singular system E ¿ x ( t ) = Ax ( t ) + Bu ( t ) controllable.Postprint (author's final draft

Genotype x dose of artificial insemination interaction for buck fertility

Ponencia publicada en ITEA, vol.104El objetivo de este trabajo fue estimar los parámetros genéticos de la fertilidad tras la IA con 3 tipos de dosis obtenidas de eyaculados de machos de la línea Caldes: 1) tipo 10: con 10 x 106 espermatozoides/ml y 24h de conservación en un diluyente comercial tipo A. 2) tipo 40: con 40 x 106 espermatozoides/ml y las mismas condiciones de conservación que las del tipo 10. 3) tipo X: dosis preparadas tras diluir los eyaculados con un diluyente comercial tipo B (1:5) siendo desconocida la concentración y sin periodo de conservación. Se realizaron 3,628 IA con dosis del tipo 10 sobre hembras cruzadas, 3,027 con dosis del tipo 40 y la misma población de hembras, y 5,779 con dosis del tipo X sobre hembras puras de la línea Caldes. La fertilidad tras la IA con dosis del tipo 10 (F10), 40 (F40) y X (FX) fue considerada un carácter distinto en cada caso, de tipo binario. Los datos se analizaron utilizando un modelo umbral tri-carácter. La estima de la media de la distribución marginal posterior (DMP) de F10 menos F40 fue de -0.13. Este resultado indica un claro efecto de la concentración sobre la fertilidad, que podría no ser lineal. Las medias de la DMP de F10 menos FX y F40 menos FX fueron -0.37 y -0.23, respectivamente, lo que indica que el efecto de las condiciones de conservación sobre la fertilidad podría ser más importante que el de la concentración ya que FX fue muy próxima a la fertilidad tras la MN y la concentración del tipo de dosis X sería en promedio de unos 50 x 106 espermatozoides/ml. Las heredabilidades parecen ser similares para F10 y F40 y ambas mayores que las correspondientes a la fertilidad tras la MN y a FX. La interacción del genotipo x concentración de la dosis de IA es prácticamente despreciable debido a que las varianzas genéticas fueron similares para F10 y F40 y a que su correlación genética fue próxima a 1. Sin embargo, la interacción podría ser de mayor importancia entre el genotipo y las condiciones de conservación.The aim of this research was to estimate genetic parameters of male fertility after AI with three different types of AI doses obtained from ejaculates of bucks belonging to the Caldes line: 1) type 10: doses with 10 x 106 spermatozoa/ml and a period of 24 h of storage at 18ºC in a saline extender A. 2) type 40: doses with 40 x 106 spermatozoa/ml and the same storage conditions as type 10. 3) type X, doses prepared with semen diluted (1:5) with a saline extender B, but with unknown sperm dosage and no storage period. 3,628 AI were performed with the type 10 doses using crossbred females, 3,027 with the type 40 doses and the same population of females, and 5,779 with the type X doses, using purebred M. Piles et al. ITEA (2008), Vol. 104 (2), 160-168 16 females from the Caldes line in a different farm. Fertility after AI with type 10 doses (F10), type 40 doses (F40) and type X doses (FX) was considered as three different binary traits. Data were analyzed under a three-trait threshold model. The mean of the marginal posterior distribution (MPD) for F10 minus F40 was estimated to be -0.13. This result indicates a clear effect of the sperm dosage on fertility, which could be non-linear. The mean of the MPD of F10 minus FX and F40 minus FX were respectively, -0.37 and -0.23 which indicates that the effect of the storage conditions on fertility could be even more important on fertility than sperm dosage, since FX was very close to fertility after NM and sperm dosage of this type of doses was in average lower than 50 x 106 spermatozoa/ml. Heritabilities seem to be similar for F10 and F40 and both of them could be higher than heritability of male fertility after NM and FX. Variance of the genotype x sperm dosage interaction was almost negligible since additive variances were similar for F10 and F40 and their genetic correlation was close to 1. However, this interaction could be more important between the genotype and the storage conditions

Dinámica de la descomposición de las hojas de Pinus halepensis Mill. en Cap des Pinar (Alcúdia, Mallorca)

Abstract not availabl

A software system to teach economics to secondary school and first year engineering students

[EN] In this paper, we present a graphical user interface which has been devised to teach the basic concepts of economics in secondary schools and first year engineering courses. The application allows students to vary certain parameters and visually observe the effect on the supply and demand curves. The system has been developed in Matlab and employed in a secondary school in Spain. The first results are presented.[ES] Presentamos una interfaz gráfica desarrollada mediante Matlab diseñada para complementar el aprendizaje de los conceptos básicos de economía en Bachillerato, grado superior de ciclos formativos y cursos universitarios de introducción a la economía. La aplicación informática permite que los estudiantes varíen los parámetros de los que dependen las curvas de oferta y demanda, y visualicen el efecto sobre el equilibrio de mercado de estas variaciones. Se presentan los resultados de una primera experiencia de aplicación del programa en enseñanza secundaria en España.García-March, M.; Zacarés, M.; Isidro, J.; Monreal, L.; López-Javier, C.; Arevalillo-Herráez, M. (2009). A software system to teach economics to secondary school and first year engineering students. Modelling in Science Education and Learning. 2:105-113. doi:10.4995/msel.2009.3126SWORD105113

Obtención empírica del límite frecuencial entre las bandas de baja y altra frecuencia en análisis de variabilidad del ritmo cardíaco: aplicación en ratas y humanos

Se propone un nuevo método para la determinación empírica de los límites entre las bandas de baja frecuencia y alta frecuencia del espectro de potencia de las series RR en los estudios de variabilidad del ritmo cardíaco. El método se ha aplicado a series RR obtenidas en humanos y ratas Sprague-Dawley. Para humanos el límite coincide con la recomendación de 0,15 Hz mientras que para ratas Sprague-Dawley la metodología empleada sugiere un límite de 0,75 Hz.Postprint (published version

Diel dynamics of dissolved organicmatter and heterotrophic prokaryotes reveal enhanced growth at the ocean's mesopelagic fish layer during daytime

Contrary to epipelagic waters, where biogeochemical processes closely follow the light and dark periods, little is known about diel cycles in the ocean's mesopelagic realm. Here, we monitored the dynamics of dissolved organic matter (DOM) and planktonic heterotrophic prokaryotes every 2 h for one day at 0 and 550 m (a depth occupied by vertically migrating fishes during light hours) in oligotrophic waters of the central Red Sea. We additionally performed predator-free seawater incubations of samples collected from the same site both at midnight and at noon. Comparable in situ variability in microbial biomass and dissolved organic carbon concentration suggests a diel supply of fresh DOM in both layers. The presence of fishes in the mesopelagic zone during daytime likely promoted a sustained, longer growth of larger prokaryotic cells. The specific growth rates were consistently higher in the noon experiments from both depths (surface: 0.34 vs. 0.18 d-1, mesopelagic: 0.16 vs. 0.09 d-1). Heterotrophic prokaryotes in the mesopelagic layer were also more efficient at converting extant DOM into new biomass. These results suggest that the ocean's twilight zone receives a consistent diurnal supply of labile DOM from the diel vertical migration of fishes, enabling an unexpectedly active community of heterotrophic prokaryotes

Exchange bias in laterally oxidized Au/Co/Au nanopillars

Au/Co/Au nanopillars fabricated by colloidal lithography of continuous trilayers exhibit and enhanced coercive field and the appearance of an exchange bias field with respect to the continuous layers. This is attributed to the lateral oxidation of the Co interlayer that appears upon disc fabrication. The dependence of the exchange bias field on the Co nanodots size and on the oxidation degree is analyzed and its microscopic origin clarified by means of Monte Carlo simulations based on a model of a cylindrical dot with lateral core/shell structure.Comment: 8 pages, 4 figures. Published in Appl. Phys. Let

Teaching classical mechanics using an applied example: Modelling and Software

[EN] We present our experience in using a common mechanism in engineering, such as a slider-crank, to explain classical mechanics in physics and engineering degrees. We also present a graphical user interface that permits the student to visualize the results of different simulations varying the conditions of the numerical experiment.[ES] Presentamos la experiencia docente obtenida al utilizar un mecanismo muy común en ingeniería, como el mecanismo biela-manivela-deslizadera, como un ejemplo práctico en la asignatura ”mecánica clásica” que se imparte en los grados de física e ingeniería. También presentamos una interfaz gráfica que permite al estudiante visualizar los resultados obtenidos al simular en el ordenador el movimiento de dicho mecanismo variando las condiciones en las que se realiza el experimento numérico.García-March, M.; Isidro, J.; Zacarés, M.; Arevalillo, M.; González-Santander, J.; Monreal, L.; López-Javier, C. (2009). Teaching classical mechanics using an applied example: Modelling and Software. Modelling in Science Education and Learning. 2:35-43. doi:10.4995/msel.2009.3116SWORD35432H.Goldstein, Mecánica Clásica. Ed. Reverté, Barcelona, (1987). C.Lanczos, The variational principles of mechanics. Dover, New York, (1986).M.A. García-March, I. Orquín, P. Fernández de Córdoba, A. Montero, J. Urchueguía, M.H. Giménez y J.A. Monsoriu, Formulación Lagrangiana del Sistema Biela-Manivela- Deslizadera. Anales de Ingeniería Mecánica. Revista de la Asociación Espa-ola de Ingeniería Mecánica. 2 1077-1086 (2004)