¿Cómo medir la evolución de la segunda transición demográfica en España? Elaboración de un índice a escala provincial (1991-2016)

The dynamics of nuptiality, fertility and household’s formation of Spanish population have changed over the last 30 years, following a typical pattern according to the Second Demographic Transition (SDT). The aim of the article is to explore the conjoint evolution of these dynamics, at the regional level, through the elaboration of an index that allows, in a 0-10 scale, to figure out the state of implementation of the SDT among 1991 and 2016, in a 5-year period. Employing births and marriages data from the vital statistics, as well as statistics from the 1991, 2001 and 2011 population censuses, it is found out that most of the Spanish regions are already close to complete the SDT.Las dinámicas de nupcialidad, fecundidad y formación de los hogares de la población española han cambiado en los últimos 30 años, siguiendo un patrón típico acorde a la Segunda Transición Demográfica (STD). El objetivo de este artículo consiste en explorar la evolución conjunta de dichas dinámicas, en el nivel provincial, a través de la elaboración de un índice sintético que permita, en una escala de 0 a 10, dar cuenta del estado de implantación de la STD entre 1991 y 2016, en periodos quinquenales. Tomando los datos de nacimientos y matrimonios del movimiento natural de la población para dichos años, así como las estadísticas de los censos de población de 1991, 2001 y 2011, se halla que el conjunto de las provincias españolas se encuentra en un estado avanzado de compleción con respecto a la STD

Mercado de trabajo y brecha de género en el sur de Europa. Un relato de ciclo económico

Fac. de Ciencias Políticas y SociologíaTRUEpu

El abandono en la Facultad de Estadística de la UCM. Prediciendo para mejorar

El abandono de los programas de grado constituye uno de los problemas centrales de la gestión universitaria actual. Se puede abordar y tratar de explicar desde perspectivas descriptivas, pero sin lugar a duda constituye un enfoque diferente e interesante tratar de predecirlo antes de que se produzca. En este trabajo, tomando como punto de partida los datos académicos del Grado en Estadística Aplicada de la Universidad Complutense de Madrid, se llevarán a cabo labores de predicción basadas en algoritmos de Machine Learning que ayuden a definir si, efectivamente, es posible predecir el abandono universitario en base al rendimiento académico y qué asignaturas podrían ejercer de principales predictores del abandono tras el primer curso académico

Critical review on life cycle assessment of bio‐based platform molecules: sustainability metrics of novel technologies

Bio-based platform chemicals are a set of compounds identified as key for biorefineries development [1]. Their penetration into the current market would sustain the shifting towards a more sustainable circular bioeconomy. Specifically, their biological origin can reduce both petroleum dependency and waste landfilling. Although this constitutes a promising scenario, incumbent technologies are hampered by intrinsic difficulties mainly related to upstream processing and the complex biomass composition. In this sense, life cycle assessment (LCA) is a fundamental tool to identify hotspots and ensure environmental improvements against conventional petroleumbased processes. Even though the number of LCAs published on biochemicals has rapidly grown, comparison between them is still limited due to the heterogeneous methodological choices applied. Please click Additional Files below to see the full abstract

Child and adolescent population in Spain. Recent demographic dynamics

Este trabajo realiza un recorrido por los principales fenómenos demográficos que tienen que ver con la infancia y la adolescencia, mostrando su estado actual y examinando los cambios acontecidos en las últimas décadas. Se analiza la situación de España comparada con otros países europeos. El objetivo es ofrecer al lector una primera imagen de las dinámicas demográficas básicas que involucran a los niños y los jóvenes, y facilitar un primer acercamiento a algunos de los fenómenos que son esenciales para comprender procesos de cambio, tanto para la sociedad en general, como para los grupos de población analizados. Todos ellos tienen que ver con los niveles y calidad de vida de la población y suponen aspectos fundamentales sobre los que poder desarrollar tanto actividades de investigación, como de gestión y planificación.This paper provides an overview about the main demographic phenomena regarding childhood and adolescence, showing their current state and reviewing the changes happened in last decades, focusing on the case of Spain in comparison to other European countries. The main goal is to provide a picture about the basic demographic dynamics involving children and teens by approaching some of the essential phenomena that underlie social change processes. The analyzed topics are closely related to the degree and extent of population’s quality of life and represent key features to conduct research and planning activities.Depto. de Sociología AplicadaFac. de Ciencias Políticas y SociologíaTRUEpu

A multi-device version of the HYFMGPU algorithm for hyperspectral scenes registration

This is a post-peer-review, pre-copyedit version of an article published in The Journal of Supercomputing. The final authenticated version is available online at: https://doi.org/10.1007/s11227-018-2689-7Hyperspectral image registration is a relevant task for real-time applications like environmental disasters management or search and rescue scenarios. Traditional algorithms were not really devoted to real-time performance, even when ported to GPUs or other parallel devices. Thus, the HYFMGPU algorithm arose as a solution to such a lack. Nevertheless, as sensors are expected to evolve and thus generate images with finer resolutions and wider wavelength ranges, a multi-GPU implementation of this algorithm seems to be necessary in a near future. This work presents a multi-device MPI + CUDA implementation of the HYFMGPU algorithm that distributes all its stages among several GPUs. This version has been validated testing it for 5 different real hyperspectral images, with sizes from about 80 MB to nearly 2 GB, achieving speedups for the whole execution of the algorithm from 1.18 × to 1.59 × in 2 GPUs and from 1.26 × to 2.58 × in 4 GPUs. The parallelization efficiencies obtained are stable around 86 % and 78 % for 2 and 4 GPUs, respectively, which proves the scalability of this multi-device versionThis work has been partially supported by: Universidad de Valladolid—Consejería de Educación of Junta de Castilla y León, Ministerio de Economía, Industria y Competitividad of Spain, and European Regional Development Fund (ERDF) program: Project PCAS (TIN2017-88614-R), Project PROPHET (VA082P17) and CAPAP-H6 network (TIN2016-81840-REDT). Universidade de Santiago de Compostela—Consellería de Cultura, Educación e Ordenación Universitaria of Xunta de Galicia (grant numbers GRC2014/008 and ED431G/08) and Ministerio de Economía, Industria y Competitividad of Spain (Grant Number TIN2016-76373-P), all co-funded by the European Regional Development Fund (ERDF) program. The work of Álvaro Ordóñez was supported by the Ministerio de Educación, Cultura y Deporte under an FPU Grant (Grant Number FPU16/03537)S

Towards a multi-device versión of the HYFMGPU Algorithm

Proceedings of the 18th International Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2018, July 9–14, 2018The task consisting on estimating the translation, rotation and scaling of an image with respect to another take of the same scene obtained at different times, viewpoints and/or lightning conditions is known as image registration. Applications like environmental disasters management or rescue operations depend on real-time hyperspectral images registration, but most of the current FFT-based techniques ignore such performance needs. Ordóñez et al. proposed HYFMGPU [1], a single-GPU algorithm whose performance makes it suitable for real-time use cases. As hyperspectral sensors improve, both the size of images and the wavelength ranges covered are expected to increase, so that a multi-GPU implementation is proposed to satisfy such growing needsThis work has been partially supported by Regional Government of Castilla y León (Spain) and ERDF program of European Union: PROPHET project (JCYL-VA082P17

HypeRvieW: an open source desktop application for hyperspectral remote-sensing data processing

In this article, we present a desktop application for the analysis, reference data generation, registration, and supervised spatial-spectral classification of hyperspectral remote-sensing images through a simple and intuitive interface. Regarding the classification ability, the different classification schemes are implemented by using a chain structure as a base. It consists of five configurable stages that must be executed in a fixed order: preprocessing, spatial processing, pixel-wise classification, combination, and post-processing. The modular implementation makes its extension easy by adding new algorithms for each stage or new classification chains. The tool has been designed as a platform that is open to the incorporation of algorithms by the users interested in comparing classification schemes. As an example of use, a classification scheme based on the Quick Shift (QS) algorithm for segmentation and on Extreme Learning Machines (ELMs) or Support Vector Machines (SVMs) for classification is also proposed. The application is license-free, runs on the Linux operating system, and was developed in C language using the GTK library, as well as other free libraries to build the graphical user interfaces (GUIs)This work was supported by the Xunta de Galicia, Programme for Consolidation of Competitive Research Groups [2014/008]; Ministry of Science and Innovation, Government of Spain, cofounded by the FEDER funds of European Union [TIN2013-41129-P]S

Texture-based analysis of hydrographical basins with multispectral imagery

In this paper the problem of studying the presence of different vegetation species and artificial structures in the riversides by using multispectral remote sensing information is studied. The information provided contributes to control the water resources in a region in northern Spain called Galicia. The problem is solved as a supervised classification computed over five-band multispectral images obtained by an Unmanned Aerial Vehicle (UAV). A classification scheme based on the extraction of spatial, spectral and textural features previous to a hierarchical classification by Support Vector Machine (SVM) is proposed. The scheme extracts the spatial-spectral information by means of a segmentation algorithm based on superpixels and by computing morphological operations over the bands of the image in order to generate an Extended Morphological Profile (EMP). The texture features extracted help in the classification of vegetation classes as the spatial-spectral features for these classes are not discriminant enough. The classification is computed over segments instead of pixels, thus reducing the computational cost. The experimental results over four real multispectral datasets from Galician riversides show that the proposed scheme improves over a standard classification method achieving very high accuracy resultsThis work was supported in part by the Civil Program UAVs Initiative, promoted by the Xunta de Galicia and developed in partnership with the Babcock company to promote the use of unmanned technologies in civil services. We also have to acknowledge the support by the Consellería de Educación, Universidade e Formación Profesional [grant numbers GRC2014/008, ED431C 2018/19, and ED431G/08], Ministerio de Economía y Empresa, Government of Spain [grant number TIN2016-76373-P] and by Junta de Castilla y León - ERDF (PROPHET Project) [grant number VA082P17]. All are co–funded by the European Regional Development Fund (ERDF)S

Integrated Environmental and Exergoeconomic Analysis of Biomass-Derived Maleic Anhydride

Life cycle analysis and exergy analysis are applied to compare the production of maleic anhydride from different feedstock, both biomass- and petrochemical-derived raw materials, in order to evaluate the sustainability of alternative biorefinery processes to conventional routes. The considered processes involve two options: gas and aqueous phase furfural oxidation with oxygen (air) and hydrogen peroxide as oxidants, respectively, considered as sustainable technologies because of the use of renewable feedstock. Conventional routes, used as benchmarks, include the current production processes using benzene or butane as raw materials. The results show that the aqueous phase process is far from being viable from an energy and environmental point of view due to the high exergy destruction and the use of H2O7 as oxidant (whose production entails important environmental drawbacks). On the contrary, the gas phase oxidation of furfural shows competitive results with petrochemical technologies. Nevertheless, the major environmental drawback of the new furfural-to-maleic anhydride production processes is detected on the environmental profile of the starting raw material. The results suggest that a better environmental footprint for maleic anhydride production in gas phase can be obtained if environmentally friendly furfural production technologies are used at the commercial scale.This research was funded by the Spanish Ministry of Science, Innovation and Universities (projects RTI2018-094918-B-C41, RTI2018-094918-B-C42, and RTI2018-094918-B-C43)