Foro para entornos educativos virtuales en 3D en OpenWonderland

En este trabajo se presenta el diseño de un foro como objeto de aprendizaje en un entorno 3D y su implementación sobre la plataforma de mundos virtuales OpenWonderland. Se utiliza como metáfora del foro un “oráculo” al que los estudiantes acuden para plantear sus dudas sobre una serie de temas previamente definidos. El foro es, además, un instrumento de evaluación formativa, ya que se fundamenta en la colaboración entre estudiantes, siendo ellos mismos los encargados de responder las preguntas de sus compañeros. Al profesor se le permite definir qué temas se van a tratar en la asignatura (mediante una serie de etiquetas) y conocer la participación y el nivel de los alumnos en cada uno.Ingeniería de Telecomunicació

Study of scenarios and technical requirements of a social assistive robot for Alzheimer's disease patients and their caregivers

Robots have begun to assist elders and patients suffering dementia. In particular, recent studies have shown how robots can benefit Alzheimer's disease (AD) patients. This is a novel area with a promising future but lot of researching needs to be done. The RobAlz project is aimed to assist AD patients and their caregivers by social robots. This project is divided in three phases: the definition of the requirements and scenarios, the development of a new robotic platform, and the evaluation. This work presents the results obtained in the first phase, in which several meetings were conducted with a set of subject-matter experts in the areas of Alzheimer's Disease and social robotics. The meetings were classified according to the application areas they covered: general aspects, safety, entertainment, personal assistance, and stimulation. The meetings ended up with a repertory of scenarios where robots can be applied to Alzheimer's patients and their caregivers at their home or in longterm care facilities. These scenarios present different psychological, social and technical concerns that must be addressed for the design of the robot. In this work we perform an analysis on the scenarios and present the technical requirements for the development of a first robotic prototype. This prototype will be constructed and tested in real environments in the subsequent phases of the RobAlz project.The authors gratefully acknowledge the collaboration of the Spanish Alzheimer Foundation (FAE) and the funds provided by the Spanish Government through the project Aplicaciones de los robots sociales DPI2011-26980, from the Spanish Ministry of Economy and Competitiveness

A local user mapping architecture for social robots

User detection, recognition, and tracking is at the heart of human-robot interaction, and yet, to date, no universal robust method exists for being aware of the people in a robot's surroundings. The present article imports into existing social robotic platforms different techniques, some of them classical, and other novel, for detecting, recognizing, and tracking human users. The outputs from the parallel execution of these algorithms are then merged, creating a modular, expandable, and fast architecture. This results in a local user mapping through fusion of multiple user recognition techniques. The different people detectors comply with a common interface called PeoplePoseList Publisher, while the people recognition algorithms meet an interface called PeoplePoseList Matcher. The fusion of all these different modules is based on the Unscented Kalman Filtering technique. Extensive benchmarks of the subcomponents and of the whole architecture demonstrate the validity and interest of all levels of the architecture. In addition, all the software and data sets generated in this work are freely available.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research leading to these results has received funding from several projects: from the project called: Development of social robots to help seniors with cognitive impairment-ROBSEN, funded by the Ministerio de Economía y Competitividad (DPI2014-57684-R); and from the RoboCity2030-III-CM project (S2013/MIT-2748), funded by Programas de Actividades I+D en la Comunidad de Madrid and cofunded by Structural Funds of the EU

Healthcare workers hospitalized due to COVID-19 have no higher risk of death than general population. Data from the Spanish SEMI-COVID-19 Registry

Aim To determine whether healthcare workers (HCW) hospitalized in Spain due to COVID-19 have a worse prognosis than non-healthcare workers (NHCW). Methods Observational cohort study based on the SEMI-COVID-19 Registry, a nationwide registry that collects sociodemographic, clinical, laboratory, and treatment data on patients hospitalised with COVID-19 in Spain. Patients aged 20-65 years were selected. A multivariate logistic regression model was performed to identify factors associated with mortality. Results As of 22 May 2020, 4393 patients were included, of whom 419 (9.5%) were HCW. Median (interquartile range) age of HCW was 52 (15) years and 62.4% were women. Prevalence of comorbidities and severe radiological findings upon admission were less frequent in HCW. There were no difference in need of respiratory support and admission to intensive care unit, but occurrence of sepsis and in-hospital mortality was lower in HCW (1.7% vs. 3.9%; p = 0.024 and 0.7% vs. 4.8%; p<0.001 respectively). Age, male sex and comorbidity, were independently associated with higher in-hospital mortality and healthcare working with lower mortality (OR 0.211, 95%CI 0.067-0.667, p = 0.008). 30-days survival was higher in HCW (0.968 vs. 0.851 p<0.001). Conclusions Hospitalized COVID-19 HCW had fewer comorbidities and a better prognosis than NHCW. Our results suggest that professional exposure to COVID-19 in HCW does not carry more clinical severity nor mortality

Analysis of dynamic common factors in the presence of autocorrelated noise-processes

This thesis presents a procedure to build a dynamic factor model in the presence of orthogonal stationary noise-processes. The procedure is based on the Peña-Box model (Peña & Box, 1987), in which the number of observed time series is fixed, and in the extension proposed by Peña & Poncela (2006) to non-stationary common factors, in which the common factors may be integrated processes. As a first result, an alternative for detecting the number of common factors is proposed by extending the statistical test of Peña & Poncela (2006), proposed for the Peña-Box model with a white noise process. Furthermore, in the same context, a statistical test is proposed to identify the number of non-stationary common factors. These proposals are illustrated by simulation and an application with real data, in which some empirical findings related to seasonal factors are also presented. The model is estimated by maximum likelihood, via a state-space model.Esta tesis presenta un procedimiento para construir un modelo de factores comunes dinámicos en presencia de procesos de ruido estacionarios ortogonales. El procedimiento se basa en el modelo de Peña-Box (Peña & Box, 1987), en el cual el número de series de tiempo observadas es fijo, y en la extensión propuesta por Peña & Poncela (2006) a factores comunes no estacionarios, en la cual los factores comunes pueden ser procesos integrados. Como primer resultado, se propone una alternativa para la identificación del número de factores comunes extendiendo la prueba estadística de Peña & Poncela (2006) , propuesta para el modelo Peña-Box con proceso de ruido blanco. Adicionalmente, bajo el mismo contexto, se propone una prueba estadística para identificar el número de factores comunes no estacionarios. Estas propuestas son ilustradas mediante simulación y una aplicación con datos reales, en la cual también se presentan algunos hallazgos empíricos relacionados a factores estacionales. La estimación del modelo se realiza por máxima verosimilitud, vía un modelo espacio de estados.Línea de investigación: Series de TiempoDoctorad

Healthcare workers hospitalized due to COVID-19 have no higher risk of death than general population. Data from the Spanish SEMI-COVID-19 Registry.

AimTo determine whether healthcare workers (HCW) hospitalized in Spain due to COVID-19 have a worse prognosis than non-healthcare workers (NHCW).MethodsObservational cohort study based on the SEMI-COVID-19 Registry, a nationwide registry that collects sociodemographic, clinical, laboratory, and treatment data on patients hospitalised with COVID-19 in Spain. Patients aged 20-65 years were selected. A multivariate logistic regression model was performed to identify factors associated with mortality.ResultsAs of 22 May 2020, 4393 patients were included, of whom 419 (9.5%) were HCW. Median (interquartile range) age of HCW was 52 (15) years and 62.4% were women. Prevalence of comorbidities and severe radiological findings upon admission were less frequent in HCW. There were no difference in need of respiratory support and admission to intensive care unit, but occurrence of sepsis and in-hospital mortality was lower in HCW (1.7% vs. 3.9%; p = 0.024 and 0.7% vs. 4.8%; pConclusionsHospitalized COVID-19 HCW had fewer comorbidities and a better prognosis than NHCW. Our results suggest that professional exposure to COVID-19 in HCW does not carry more clinical severity nor mortality