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Spatial Computing covers ideas, solutions, tools, technologies, and systems that transform our lives and society by creating a new understanding of spaces, locations, places, and properties. Since the term Big Data was coined for the first time in 2005, it has unleashed a worldwide revolution in scientific research and business. Big Spatial Data (BSD), the Big Data associated with spatial information, is now one of the most active research fields in spatial computing, mainly motivated by the rapid development of smart, sensor, and mobile technologies. Current usage of the term Big Spatial Data tends to refer to the process of capturing, storing, managing, analyzing, and visualizing huge amounts of spatial data, not using traditional tools and systems. Recent big spatial data developments have motivated the emergence of novel technologies for distributed processing of large-scale spatial data in shared-nothing clusters of computers, leading to Distributed Spatial Data Management Systems (DSDMSs). Distributed cluster-based computing systems can be classified as Hadoop-based or Spark-based systems. Based on this classification, two of the most leading DSDMSs are SpatialHadoop (disk-based DSDMS) and LocationSpark (in-memory-based DSDMS). These distributed systems support several characteristics like spatial data partitioning, indexing methods, and spatial query processing. An important aspect of these DSDMSs is to adopt a layered architecture for distributed computing and inject spatial data awareness into each layer. For example, the layers in SpatialHadoop are Language, Storage, MapReduce and Operations. Considering that SpatialHadoop is a comprehensive extension to the Hadoop ecosystem, it is a scalable and efficient cloud computing framework that allows distributed processing of large-scale spatial datasets using the MapReduce programming model. In this thesis, we study and enrich SpatialHadoop by implementing new Distance- Based Query (DBQ) MapReduce algorithms in the Operations layer: "Distance Range Query ("DRQ), kNearest Neighbor Query (kNNQ), kClosest Pairs Query (kCPQ), kNearest Neighbor Join Query (kNNJQ), "Distance Join Query ("DJQ), "Distance Range Join Query ("DRJQ), Reverse kNearest Neighbor Query (RkNNQ), etc. Moreover, we improve the Storage layer with a new spatial partitioning technique (Voronoi-Diagram based partitioning), and a new local indexing structure (Quadtree) to optimize the distributed spatial query processing in shared-nothing clusters. This study and the knowledge of SpatialHadoop helps us identify new opportunities to enrich LocationSpark (a spatial data processing system built on top of Spark ecosystem) too, with the design and implementation of new distributed Distance-based Join Query (DJQ) algorithms (kCPQ, "DJQ and "DRJQ), extensions, and improvements over them. Additionally, we propose other enhancements and optimizations for distributed spatial query processing that leverage both data and algorithmic properties. Furthermore, we compare these DSDMSs by evaluating the performance of several distributed DJQ algorithms under different settings with large spatial real-world datasets from OpenStreetMap. To develop this thesis, we start by reviewing the most relevant DSDMSs (research prototypes), the state-of-the-art spatial partitioning techniques in DSDMSs, and the most representative and common DBQs. Then, we focus our study on the structure and operations of spatial data partitioning methods and indexing structures in Spatial-Hadoop, by proposing a spatial partitioning technique based on Voronoi-Diagrams and including the Quadtree as a local index in such a DSDMS. Driven by an exhaustive analysis on the spatial query processing in SpatialHadoop, we identify and implement new spatial queries ("DRQ, kCPQ, "DJQ, "DRJQ, kNNJQ, RkNNQ, etc.) with different extensions (e.g., for non-points spatial data types) and improvements (e.g., repartitioning methods, less data technique, new pruning rules, etc.) in this DSDMS. Next, we analyze the general spatial query processing scheme of LocationSpark to extend it with new distributed DJQ algorithms and improvements. Afterward, we achieve an extensive performance evaluation of such enhancements (distributed spatial query algorithms, extensions, and improvements) in SpatialHadoop and LocationSpark. Finally, we carry out a comparative study between SpatialHadoop and LocationSpark by executing an exhaustive set of experiments of several DJQs to identify which DSDMS is the most appropriate for the distributed query processing on large volumes of spatial data.

We used data from 3041 participants in four cohorts of community-dwelling individuals aged ≥65 years in Spain collected through a pre-pandemic face-to-face interview and a telephone interview conducted between weeks 7 to 15 after the beginning of the COVID-19 lockdown. On average, the confinement was not associated with a deterioration in lifestyle risk factors (smoking, alcohol intake, diet, or weight), except for a decreased physical activity and increased sedentary time, which reversed with the end of confinement. However, chronic pain worsened, and moderate declines in mental health, that did not seem to reverse after restrictions were lifted, were observed. Males, older adults with greater social isolation or greater feelings of loneliness, those with poorer housing conditions, as well as those with a higher prevalence of chronic morbidities were at increased risk of developing unhealthier lifestyles or mental health declines with confinement. On the other hand, previously having a greater adherence to the Mediterranean diet and doing more physical activity protected older adults from developing unhealthier lifestyles with confinement. If another lockdown were imposed during this or future pandemics, public health programs should specially address the needs of older individuals with male sex, greater social isolation, sub-optimal housing conditions, and chronic morbidities because of their greater vulnerability to the enacted movement restrictions The Seniors-ENRICA-2 study was supported by Instituto de Salud Carlos III (Spain), State Secretary of R+D+I and FEDER/FSE research grants PI16/609, PI18/287, and 19/319; CIBERESP (16/01); and Cátedra de Epidemiología y Control del Riesgo Cardiovascular at UAM (#820024). ELS was supported by a Juan de la Cierva Contract from the Ministy of Universities. DMG and MSP were supported by supported by a “Ramon y Cajal”contract. Edad con Salud was funded by the Seventh Framework Programme (grant number 223071-COURAGE Study); the Insti tuto de Salud Carlos III (grants number PS09/00295(JMH), PS09/01845 (JLA), PI12/01490 (JMH), PI13/00059 (JLA), PI16/00212 (JMH), PI16/00218 (MM), PI16/01073 (JLA)); the European Regional Development Fund (ERDF) “A Way to Build Europe” (grant numbers PI12/01490, PI13/00059, PI16/00212 and PI16/01073);and CIBERSAM. EL was supported by the Sara Borrell postdoctoral programme (CD18/00099) from the Instituto de Salud Carlos III and co-funded by the European Union (FEDER/FSE, “Investing in your future”). BO was supported by the Miguel Servet programme (reference CP20/00040), funded by Instituto de Salud Carlos III and co-funded by European Union (ERDF/ESF, "Investing in your future"). The Toledo Study for Healthy Ageing was funded by the Spanish Ministry of Economy, Industry and Competitiveness, cofinanced by FEDER (RD120001/0043), CIBERFES (CB16/10/00464) and DIABFRAIL-LATAM (contract number 825546, Horizon 2020). The Elderly EXERNET multicenter study was supported by the Ministerio de Economía, Industria y Competitividad (DEP2016-78309-R (GVR)), the Ministerio de Educación y Ciencia (Red EXERNET DEP2005-00046 JAC)), the High Council of Sports (Consejo Superior de Deportes) of the Ministe rio de Cultura y Deportes (09/UPB/19 (JAC) and 45/UPB/20 (JAC)), CIBERFES, the 4IE+ project (0499_4IE_PLUS_4_E (NG)) funded by the Interreg V-A España-Portugal (POCTEP) 2014-2020 pro gram, and FEDER funds from the European Union (CB16/10/00477 (IA)). The funding agencies had no role in study design, data collection and analysis, interpretation of results, manuscript preparation or the decision to submit this manuscript for publication

La configuración tradicional de una pila de combustible de óxido sólido (SOFC), en la que se disponen materiales diferentes para cada uno de sus componentes principales (electrolito y electrodos ánodo y cátodo) se ha visto afectada recientemente por una nueva configuración de original concepto, que reúne nuevas ventajas y retos en su investigación y desarrollo. Esta nueva configuración se conoce como pilas de combustible de óxido sólido simétricas (SSOFCs), e implica la elección de un mismo material para ambos electrodos, es decir, para el cátodo y el ánodo. En esta nueva configuración el empleo de materiales con estructura perovskita cobra especial relevancia, por cuando disponen de múltiples estados de oxidación, lo que facilita los procesos electro-catalíticos, además de proporcionar el adecuado mecanismo para la conductividad electrónica. El presente trabajo aborda la fabricación mediante mecanoquímica de materiales prometedores para ser empleados en SSOFCs. Seguidamente, se presentan algunas de sus propiedades más características, así como las principales ventajas e inconvenientes de los mismos.

2030-12 The electrochemical performance of two Na2/3Ni1/3Mn2/3O2 samples, prepared by an oleic - assisted emulsion procedure, is examined. As a novelty, the effect of cosurfactants with either short (methylamine) or long (octylamine) chains is determined for their applicability as cathode materials for sodium-ion batteries. Their structural and morphological properties are studied by X-ray diffraction and electron microscopy. The electrochemical performance is determined by cycling sodium half cells by the galvanostatic method. Especial interest is devoted to their kinetic properties evaluated by impedance spectroscopy

Data Dictionary: Description of the Variables. This file “Additional File 1.pdf” contains tables where for each available variable the name, expected values, a description and the data type is stated. The variables where divided into semantic groups, where for each group a table has been created. These groups have already been mentioned in the subsection Definition of the Variables. (PDF 93 kb)

La Red quiere transmitir al alumnado la importancia y necesidad de aprender a participar en el aula para que después sepa actuar, sea corresponsable ante los problemas reales y ante la escasa respuesta de nuestros representantes a situaciones urgentes, como el cambio climático, y sus negativas consecuencias económicas y sociales. Queremos desde nuestra Red interactuar en el aula en el marco del I Plan de Responsabilidad Social de la Universidad de Alicante (2018-2020), de la Agenda 2030 de Naciones Unidas con los Objetivos de Desarrollo Sostenible, y de la “Educación para el desarrollo sostenible” de la UNESCO, teniendo como ejemplo y referencia el movimiento ciudadano “Fridays For Future”, iniciado por una estudiante sueca, Greta Thunberg. Así se creará conciencia en el alumnado sobre su necesario empoderamiento, formándose como buenos profesionales que no solo encontrarán empleo sino también la manera responsable, solidaria, inteligente de intervenir en la sociedad para mejorar la realidad, procurando el buen vivir para todos.

The aim of this study was to determine the relationship between bone mass (BM) and physical activity (PA) and sedentary behavior (SB) according to frailty status and sex using compositional data analysis. We analyzed 871 older people with an adequate nutritional status. Fried criteria were used to classify by frailty status. Time spent in SB, light intensity PA (LPA) and moderate-to-vigorous intensity PA (MVPA) was assessed from ccelerometry for 7 days. BM was determined by dual-energy X-ray absorptiometry (DXA). The combined effect of PA and SB was significantly associated with BM in robust men and women (p 0.05). In relation to the other behaviors, SB was negatively associated with BM in robust men while BM was positively associated with SB and negatively with LPA and MVPA in robust women. Moreover, LPA also was positively associated with arm BM (p 0.01). Finally, in pre-frail women, BM was positively associated with MVPA. In our sample, to decrease SB could be a good strategy to improve BM in robust men.In contrast, in pre-frail women, MVPA may be an important factor to consider regarding bone health.