Estudio científico-técnico efectuado a una Imagen en madera policromada, representando un crucificado-yacente atribuido al s. XVII

Torrejoncillo es una población situada en la comarca de Coria y al norte de la ciudad de Cáceres. Cuenta con un patrimonio histórico-artístico de reconocida relevancia, repartido entre diversas ermitas y su iglesia principal de San Andrés. Ante el preocupante estado de conservación de la imagen del Cristo del Consuelo, a petición de la Cofradía se realizó un examen científico-técnico con el fin de obtener la información necesaria para garantizar el adecuado tratamiento. Se trata de un cristo yacente articulado, la urna dorada y acristalada que lo alberga y la cruz. El estudio se ha complementado con una amplia documentación histórica, que ha servido para establecer una aproximación cronológica de su ejecución, conocer los distintos usos religiosos y las intervenciones y manipulaciones de que ha sido objeto, así como determinar cuáles han sido las causas principales que han originaron su deficiente estado de conservación

Bayesian inference on the memory parameter for Gamma-modulated regression models

CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOIn this work, we propose a Bayesian methodology to make inferences for the memory parameter and other characteristics under non-standard assumptions for a class of stochastic processes. This class generalizes the Gamma-modulated process, with trajectories that exhibit long memory behavior, as well as decreasing variability as time increases. Different values of the memory parameter influence the speed of this decrease, making this heteroscedastic model very flexible. Its properties are used to implement an approximate Bayesian computation and MCMC scheme to obtain posterior estimates. We test and validate our method through simulations and real data from the big earthquake that occurred in 2010 in Chile.In this work, we propose a Bayesian methodology to make inferences for the memory parameter and other characteristics under non-standard assumptions for a class of stochastic processes. This class generalizes the Gamma-modulated process, with trajectories that exhibit long memory behavior, as well as decreasing variability as time increases. Different values of the memory parameter influence the speed of this decrease, making this heteroscedastic model very flexible. Its properties are used to implement an approximate Bayesian computation and MCMC scheme to obtain posterior estimates. We test and validate our method through simulations and real data from the big earthquake that occurred in 2010 in Chile.171065766597CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCNPq [141048/2013-1]FAPESP [2013/07699-0]141048/2013-

El tenebrismo como recurso técnico y concepto estético

El tenebrismo no podemos considerarlo únicamente como concepto estético, pues su razón de ser es además consecuencia de la aplicación de recursos técnicos que posibilitan la nueva manera de concebir la pintura. Con anterioridad a este movimiento pictórico otros artistas habían iniciado la técnica del claroscuro, cuya evolución desembocará en el tenebrismo que alcanza su máximo exponente en Caravaggio, y que influyó en muchos artistas europeos adquiriendo gran relevancia en pintores españoles como Ribera o Velázquez. A este nuevo planteamiento estético en que el contraste entre las luces y las sombras resaltan el efecto dramático de la composición, colabora el empleo del nuevo procedimiento pictórico del óleo y la utilización del soporte de tela, medios que facilitan la obtención de resultados plásticos desconocidos hasta entonces.We can’t consider tenebrism only as an aesthetic concept, since it is also a consequence of the application of technical means that make possible a new way of painting. Before that aesthetic movement, other artists had initiated the chiaroscuro technique, that ended in the so called tenebrism movement, marking the climax of it Caravaggio’s works, whose influence can be seen in many outstanding Spanish painters, like Ribera and Velázquez. To this new aesthetic movement, where contrast of light and shade throw into relief the dramatic effect of composition, helps the new procedure of oil painting and the use of canvas support, that makes possible plastic results unknown ever before

Actitudes hacia la estadística en Universitários del Área de las Ciências de una Universidad Pública de Chile

En este estudio desarrollamos un análisis psicométrica de dos escalas de actitudes hacia la estadística; Estrada (2002) (AEE) y Cazorla Silva, Vendramini y Brito (AEC), considerando 113 ingresantes universitarios chilenos de diferentes especialidades del área de ciencia que no habían llevado un curso de Estadística. El análisis de ítems para las escalas y una versión compuesta AECom sugiere eliminar 4 ítems de la escala AEE. Las versiones recortadas de la AEE y AECom presentan una óptima confiabilidad, alpha=0.84 y alpha= 0.95, al igual que la de la AEC (alpha= 0.94). Adicionalmente considerando un análisis factorial se encuentra evidencia de multidimensionalidad en las escalas finales y diferencias significativas por especialidad. Finalmente son dadas sugerencias de estudios futuros

Deformation forecasting of a hydropower dam by hybridizing a long short-term memory deep learning network with the coronavirus optimization algorithm

The safety operation and management of hydropower dam play a critical role in social-economic development and ensure people’s safety in many countries; therefore, modeling and forecasting the hydropower dam’s deformations with high accuracy is crucial. This research aims to propose and validate a new model based on deep learning long short-term memory (LSTM) and the coronavirus optimization algorithm (CVOA), named CVOA-LSTM, for forecasting the defor mations of the hydropower dam. The second-largest hydropower dam of Viet nam, located in the Hoa Binh province, is focused. Herein, we used the LSTM to establish the deformation model, whereas the CVOA was utilized to opti mize the three parameters of the LSTM, the number of hidden layers, the learn ing rate, and the dropout. The efficacy of the proposed CVOA-LSTM model is assessed by comparing its forecasting performance with state-of-the-art bench marks, sequential minimal optimization for support vector regression, Gaussian process, M5’ model tree, multilayer perceptron neural network, reduced error pruning tree, random tree, random forest, and radial basis function neural net work. The result shows that the proposed CVOA-LSTM model has high fore casting capability (R2 = 0.874, root mean square error = 0.34, mean absolute error = 0.23) and outperforms the benchmarks. We conclude that CVOA-LSTM is a new tool that can be considered to forecast the hydropower dam’s deforma tions.Ministerio de Ciencia, Innovación y Universidades PID2020-117954RB-C2

Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model

This study proposes a novel bioinspired metaheuristic simulating how the coronavirus spreads and infects healthy people. From a primary infected individual (patient zero), the coronavirus rapidly infects new victims, creating large populations of infected people who will either die or spread infection. Relevant terms such as reinfection probability, super-spreading rate, social distancing measures, or traveling rate are introduced into the model to simulate the coronavirus activity as accurately as possible. The infected population initially grows exponentially over time, but taking into consideration social isolation measures, the mortality rate, and number of recoveries, the infected population gradually decreases. The coronavirus optimization algorithm has two major advantages when compared with other similar strategies. First, the input parameters are already set according to the disease statistics, preventing researchers from initializing them with arbitrary values. Second, the approach has the ability to end after several iterations, without setting this value either. Furthermore, a parallel multivirus version is proposed, where several coronavirus strains evolve over time and explore wider search space areas in less iterations. Finally, the metaheuristic has been combined with deep learning models, to find optimal hyperparameters during the training phase. As application case, the problem of electricity load time series forecasting has been addressed, showing quite remarkable performance.Ministerio de Economía y Competitividad TIN2017-88209-C

Spanish Cell Therapy Network (TerCel): 15 years of successful collaborative translational research

In the current article we summarize the 15-year experience of the Spanish Cell Therapy Network (TerCel), a successful collaborative public initiative funded by the Spanish government for the support of nationwide translational research in this important area. Thirty-two research groups organized in three programs devoted to cardiovascular, neurodegenerative and immune-inflammatory diseases, respectively, currently form the network. Each program has three working packages focused on basic science, pre-clinical studies and clinical application. TerCel has contributed during this period to boost the translational research in cell therapy in Spain, setting up a network of Good Manufacturing Practice–certified cell manufacturing facilities– and increasing the number of translational research projects, publications, patents and clinical trials of the participating groups, especially those in collaboration. TerCel pays particular attention to the public-private collaboration, which, for instance, has led to the development of the first allogeneic cell therapy product approved by the European Medicines Agency, Darvadstrocel. The current collaborative work is focused on the development of multicenter phase 2 and 3 trials that could translate these therapies to clinical practice for the benefit of patients

Estrategias para la transformación de los residuos del plátano generando valor agregado

En la actualidad el desarrollo de la sociedad y el consumo generado por la misma ha llevado a un incremento en la utilización de plásticos de un solo uso. En respuesta a ello, se están generando estrategias y alternativas que buscan mitigar éste efecto contaminante y adicionalmente dar valor agregado a subproductos de cosecha de muchos cultivos. En el caso del Departamento del Tolima, existen algunos municipios con una importante producción de Plátano (Musa paradisiaca) que en su gran mayoría es aprovechado solo en un 20-25% del volumen total de la planta - representado en el racimo y las hojas -  y generando residuos orgánicos que tienen un impacto ambiental. Se espera llenar un vacío del conocimiento acerca de las oportunidades de generación de valor agregado a partir del procesamiento agroindustrial de los residuos de plátano logrando que las comunidades y productores logren transformar estos residuos en contenedores de alimentos