Multiscale thermo-mechanical analysis of multi-layered coatings in solar thermal applications

Solar selective coatings can be multi-layered materials that optimize the solar absorption while reducing thermal radiation losses, granting the material long-term stability. These layers are deposited on structural materials (e.g., stainless steel, Inconel) in order to enhance the optical and thermal properties of the heat transfer system. However, interesting questions regarding their mechanical stability arise when operating at high temperatures. In this work, a full thermo-mechanical multiscale methodology is presented, covering the nano-, micro-, and macroscopic scales. In such methodology, fundamental material properties are determined by means of molecular dynamics simulations that are consequently implemented at the microstructural level by means of finite element analyses. On the other hand, the macroscale problem is solved while taking into account the effect of the microstructure via thermo-mechanical homogenization on a representative volume element (RVE). The methodology presented herein has been successfully implemented in a reference problem in concentrating solar power plants, namely the characterization of a carbon-based nanocomposite and the obtained results are in agreement with the expected theoretical values, demonstrating that it is now possible to apply successfully the concepts behind Integrated Computational Materials Engineering to design new coatings for complex realistic thermo-mechanical applications.Peer ReviewedPostprint (author's final draft

Deposition patterns of atmospheric 7Be, 210Pb, 40K in cost of west Mediterranean sea, Málaga (Spain)

The deposition of radionuclides on the ground is an essential process to understand atmospheric transportation, sedimentation and geological process, being the major removal pathway for airborne particulates. To predict the long-term radiological consequences of an accidental deposition of the radionuclides to the ground, it is a prerequisite to know the environmental long-term behaviour of these radionuclides and a relatively large number of values are required for statistically meaningful conclusions. Nuclides of the natural decay chains, especially for 238U decay chain, are widely applied into atmospheric research, oceanography and marine geology. Atmospheric depositional fluxes of 7Be, 210Pb and 40K were simultaneously measured in monthly interval for eleven years (from January 2005 to December 2015 at Málaga (4 º28´ 8W; 36º 43´40N). Samples were collected monthly in an area of 1 m2 using a collector that is a slightly tilted stainless steel tray and filling 25 or 50 L polyethylene vessels with bulk deposition. The radionuclides present in all samples are 7Be, 210Pb and 40K appears approximately in 50% of the samples. The temporal variations of radionuclides in bulk deposition exhibit similar seasonal behaviour with low values in winter-autumn months and maximum values in spring-summer months. The time variations of the different radionuclides have been discussed in relation to various meteorological factors and the mean values have been compared to those published in recent literature for other sites located at different latitudes. Bulk depositional fluxes of 7Be, 210Pb and 40K have been evaluated for period of measurements. Bulk depositional fluxes of 7Be , 210Pb and 40K varied between 3 and 1779 Bq m-2 month-1 (annual mean = 1247 Bq m-2 year-1 ), and 1 to 102 Bq m-2 year-1 (annual mean = 140 Bq m-2 year-1) and 0,5 to 81 Bq m-2 year-1 ( annual mean = 65 Bq m-2 year-1). Data on the atmospheric depositions of radionuclides in Málaga show clear seasonal variations which can be attributed to the meteorological conditions affecting the transport and deposition processes. The amount of rainfall controls mainly the depositional fluxes. .There is a statistically relationship between 7Be and 210Pb fluxes indicating that removal behaviour from the atmosphere is relatively similar.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Conflicto marital, apoyo parental y ajuste escolar en adolescentes

[email protected] [email protected] [email protected] el presente estudio se analiza la influencia del conflicto marital (ruptura de la relación y violencia como estrategias de resolución de conflictos) y del apoyo parental en el ajuste escolar a través de sus relaciones con la autoestima social y la violencia escolar en adolescentes. Los participantes en el estudio fueron 733 adolescentes de cuatro centros educativos de la Comunidad Valenciana, con edades comprendidas entre los 11 y 16 años. Para los análisis se llevó a cabo un modelo de ecuaciones estructurales. Los resultados mostraron que el conflicto marital y el apoyo parental se relacionan indirectamente con el ajuste escolar a través de la autoestima social y la violencia escolar. En particular, el apoyo del padre y la madre se relacionan con la autoestima social, mientras que el apoyo de la madre y el conflicto marital se relacionan con la violencia escolar. Finalmente, se discuten los resultados y sus posibles implicaciones.This study analyses the influence of marital conflict (breaking-up and violence as conflict resolution strategies) and parental support on school adjustment by considering their relationship to social self-esteem and school-based violence among adolescents. Participants were 733 adolescents from four schools in the region of Valencia, their ages ranging from 11 to 16 years old. Data were analysed by means of a structural equation model. The results showed that marital conflict and parental support (father and mother) are indirectly related to school adjustment through their relationship t o social self-esteem and school-based violence. In particular, support from both parents was related to social self-esteem, whereas maternal support and marital conflict were related to school-based violence. The findings and their possible implications are discussed

1st International Congress on Research, Technological Development and Innovation in University Education

Different papers have been presented to the congress by renowned researchers along the following five thematic lines: Scientific research, training and researcher training; Research, innovation and development policies in Higher Education; Paradigms in scientific research and new epistemological challenges in the production of knowledge in Latin American universities; Internationalization of research networks, groups and institutes; Public communication of science and technologyPeer Reviewe

Analyzing the impact of Driving tasks when detecting emotions through brain–computer interfaces

Traffic accidents are the leading cause of death among young people, a problem that today costs an enormous number of victims. Several technologies have been proposed to prevent accidents, being brain–computer interfaces (BCIs) one of the most promising. In this context, BCIs have been used to detect emotional states, concentration issues, or stressful situations, which could play a fundamental role in the road since they are directly related to the drivers’ decisions. However, there is no extensive literature applying BCIs to detect subjects’ emotions in driving scenarios. In such a context, there are some challenges to be solved, such as (i) the impact of performing a driving task on the emotion detection and (ii) which emotions are more detectable in driving scenarios. To improve these challenges, this work proposes a framework focused on detecting emotions using electroencephalography with machine learning and deep learning algorithms. In addition, a use case has been designed where two scenarios are presented. The first scenario consists in listening to sounds as the primary task to perform, while in the second scenario listening to sound becomes a secondary task, being the primary task using a driving simulator. In this way, it is intended to demonstrate whether BCIs are useful in this driving scenario. The results improve those existing in the literature, achieving 99% accuracy for the detection of two emotions (non-stimuli and angry), 93% for three emotions (non-stimuli, angry and neutral) and 75% for four emotions (non-stimuli, angry, neutral and joy)

Del modelado al modelo. Conversación con Laia Grau Balagueró

To close this thematic exploration of the use of data and methodologies that help us to describe, discover, predict, or simulate our urban environment, we interviewed Laia Grau Balagueró. Her vision, as urban planning manager of the city of Barcelona and with a broad experience linked to public administration and freelance professional activity as an architect, allows us to recognise the challenges and opportunities that the discipline of urban planning has regarding the transfer of this knowledge to the public policies that will define the urban model of our cities.Para cerrar esta reflexión temática en torno al uso de datos y metodologías que nos ayudan a describir, descubrir, predecir o simular lo urbano se entrevistó a Laia Grau Balagueró. Su visión, como gerente de urbanismo de la ciudad de Barcelona y con una trayectoria larga ligada a la administración pública y la libre actividad profesional como arquitecta, permite reconocer los retos y las oportunidades que la disciplina urbanística —y el planeamiento en particular—, tiene en relación con la transferencia de este conocimiento a las políticas públicas que definirán el modelo urbano de nuestras ciudades

Diseño conceptual y experimental de un invernadero automatizado para cultivo de plantas de uso doméstico

Hoy en día la población compra toda la verdura y fruta en el supermercado sin saber ni la procedencia, ni la huella ecológica que requiere que esa pieza de fruta llegue al supermercado. Este proyecto se centra en hacer más fácil el cultivo de productos de la agricultura en tu casa, fomentando una vida más saludable y mejorando la calidad alimentaria con productos más frescos. Para ello, presentamos nuestro proyecto que es un invernadero automatizado para uso doméstico. A través de una investigación y de estudios previos, se han identificado las necesidades desde diferentes puntos de vista y se ha desarrollado una solución adaptada. Se aplican los conocimientos adquiridos en el Grado en Ingeniería en Diseño Industrial y Desarrollo de Producto, con métodos para la mejora del producto, desde la investigación de usuarios hasta la mejora de la ergonomía. Con nuestro producto queremos que la población empiece a cultivar sus propias frutas y verduras con esfuerzo y dedicación, para que disfruten no solo de alimentos más saludables y sabrosos, sino que también contribuyan positivamente a su bienestar y al del planeta.Nowadays people buy all their fruit and vegetables in the supermarket without knowing where they come from or the ecological footprint that it takes for that piece of fruit to reach the supermarket. This project focuses on making it easier to grow agricultural products at home, promoting a healthier lifestyle and improving food quality with fresher products. To this end, we present our project which is an automated greenhouse for home use. Through research and previous studies, the needs have been identified from different points of view and an adapted solution has been developed. The knowledge acquired in the Degree in Industrial Design and Product Development Engineering is applied, with methods for the improvement of the product, from user research to the improvement of ergonomics. With our product we want people to start growing their own fruit and vegetables with effort and dedication, so that they not only enjoy healthier and tastier food, but also contribute positively to their well-being and that of the planet

Eight reasons why cybersecurity on novel generations of brain-computer interfaces must be prioritized

This article presents eight neural cyberattacks affecting spontaneous neural activity, inspired by well-known cyberattacks from the computer science domain: Neural Flooding, Neural Jamming, Neural Scanning, Neural Selective Forwarding, Neural Spoofing, Neural Sybil, Neural Sinkhole and Neural Nonce. These cyberattacks are based on the exploitation of vulnerabilities existing in the new generation of Brain-Computer Interfaces. After presenting their formal definitions, the cyberattacks have been implemented over a neuronal simulation. To evaluate the impact of each cyberattack, they have been implemented in a Convolutional Neural Network (CNN) simulating a portion of a mouse's visual cortex. This implementation is based on existing literature indicating the similarities that CNNs have with neuronal structures from the visual cortex. Some conclusions are also provided, indicating that Neural Nonce and Neural Jamming are the most impactful cyberattacks for short-term effects, while Neural Scanning and Neural Nonce are the most damaging for long-term effects