Flux switching alternators for small wind generation

This paper considers the application of flux switching alternators for small wind generation. First, after a brief presentation of the small wind energy systems, a description and the fundamentals of flux switching machines is given, then the state of art of flux switching generators is presented. Finally a critical assessment is shown, considering the main advantages and drawbacks of this type of machines as alternator for use in small wind generation systems.Peer ReviewedPostprint (published version

Development by Mechanochemistry of La0.8Sr0.2Ga0.8Mg0.2O2.8 Electrolyte for SOFCs

In this work, a mechanochemical process using high-energy milling conditions was employed to synthesize La0.8Sr0.2Ga0.8Mg0.2O3-δ (LSGM) powders from the corresponding stoichiometric amounts of La2O3, SrO, Ga2O3, and MgO in a short time. After 60 min of milling, the desired final product was obtained without the need for any subsequent annealing treatment. A half solid oxide fuel cell (SOFC) was then developed using LSGM as an electrolyte and La0.8Sr0.2MnO3 (LSM) as an electrode, both obtained by mechanochemistry. The characterization by X-ray diffraction of as-prepared powders showed that LSGM and LSM present a perovskite structure and pseudo-cubic symmetry. The thermal and chemical stability between the electrolyte (LSGM) and the electrode (LSM) were analyzed by dynamic X-ray diffraction as a function of temperature. The electrolyte (LSGM) is thermally stable up to 800 and from 900 °C, where the secondary phases of LaSrGa3O7 and LaSrGaO4 appear. The best sintering temperature for the electrolyte is 1400 °C, since at this temperature, LaSrGaO4 disappears and the percentage of LaSrGa3O7 is minimized. The electrolyte is chemically compatible with the electrode up to 800 °C. The powder sample of the electrolyte (LSGM) at 1400 °C observed by HRTEM indicates that the cubic symmetry Pm-3m is preserved. The SOFC was constructed using the brush-painting technique; the electrode-electrolyte interface characterized by SEM presented good adhesion at 800 °C. The electrical properties of the electrolyte and the half-cell were analyzed by complex impedance spectroscopy. It was found that LSGM is a good candidate to be used as an electrolyte in SOFC, with an Ea value of 0.9 eV, and the LSM sample is a good candidate to be used as cathode

Health care provider choice in the case of patient-initiated contacts. An extended version of discrete choice of model demand

This paper analyzes the nature of health care provider choice in the case of patient-initiated contacts, with special reference to a National Health Service setting, where monetary prices are zero and general practitioners act as gatekeepers to publicly financed specialized care. We focus our attention on the factors that may explain the continuously increasing use of hospital emergency visits as opposed to other provider alternatives. An extended version of a discrete choice model of demand for patient-initiated contacts is presented, allowing for individual and town residence size differences in perceived quality (preferences) between alternative providers and including travel and waiting time as non-monetary costs. Results of a nested multinomial logit model of provider choice are presented. Individual choice between alternatives considers, in a repeated nested structure, self-care, primary care, hospital and clinic emergency services. Welfare implications and income effects are analyzed by computing compensating variations, and by simulating the effects of user fees by levels of income. Results indicate that compensating variation per visit is higher than the direct marginal cost of emergency visits, and consequently, emergency visits do not appear as an inefficient alternative even for non-urgent conditions.Health care demand, emergency visits, nested multinomial logit, compensating variation, time costs

Use and perception of urban green spaces in Barcelona

Curs 2012-2013Background: Although the mechanisms are not well understood yet, evidence exists of the benefits of urban green spaces for human health. As a consequence, one of the concerns of public health interventions must be to promote the use of urban green spaces within cities. Aims: This study aims to explore the citizens’ purposes of use of urban green spaces as well as the elements related to the characteristics of these places that condition their use. Methods: In-depth interviews were conducted with non-hospitalised people living in different areas of Barcelona, with different socioeconomic status and different residential distance to urban green spaces (n = 20). Thematic content analysis of the qualitative data was performed. Results: Physical pursuits and attention restoration were identified as prominent purposes of use of urban green spaces. The natural features of urban green spaces were identified as the most relevant determiners for the use of these places. Conclusions: To promote the use of urban green spaces, qualitative findings from this study suggest that purpose-built places should be provided. Moreover, natural features of urban green spaces must be particularly taken into account when designing and maintaining them

Sistema de posicionament global, GPS

Peer Reviewe

Josep Reig i Palau (1863-1917), pioner de l'educació ambiental al Bosc de Poblet

Josep Reig i Palau, enginyer forestal, fou el precursor dels treballs de reforestació del bosc de Poblet a principis del segle XX. En els seus estudis sobre aquest bosc s’hi constata la visió que tenia de la funció educativa que es port dur a terme amb la reforestació del bosc i a la vegada donar a conèixer el valors naturals i les millores socials i econòmiques que dels treballs forestals en poden derivar, i, així, sensibilitzar a les autoritats per destinar-hi més recursos

Document-level machine translation : ensuring translational consistency of non-local phenomena

In this thesis, we study the automatic translation of documents by taking into account cross-sentence phenomena. This document-level information is typically ignored by most of the standard state-of-the-art Machine Translation (MT) systems, which focus on translating texts processing each of their sentences in isolation. Translating each sentence without looking at its surrounding context can lead to certain types of translation errors, such as inconsistent translations for the same word or for elements in a coreference chain. We introduce methods to attend to document-level phenomena in order to avoid those errors, and thus, reach translations that properly convey the original meaning. Our research starts by identifying the translation errors related to such document-level phenomena that commonly appear in the output of state-of-the-art Statistical Machine Translation (SMT) systems. For two of those errors, namely inconsistent word translations as well as gender and number disagreements among words, we design simple and yet effective post-processing techniques to tackle and correct them. Since these techniques are applied a posteriori, they can access the whole source and target documents, and hence, they are able to perform a global analysis and improve the coherence and consistency of the translation. Nevertheless, since following such a two-pass decoding strategy is not optimal in terms of efficiency, we also focus on introducing the context-awareness during the decoding process itself. To this end, we enhance a document-oriented SMT system with distributional semantic information in the form of bilingual and monolingual word embeddings. In particular, these embeddings are used as Semantic Space Language Models (SSLMs) and as a novel feature function. The goal of the former is to promote word translations that are semantically close to their preceding context, whereas the latter promotes the lexical choice that is closest to its surrounding context, for those words that have varying translations throughout the document. In both cases, the context extends beyond sentence boundaries. Recently, the MT community has transitioned to the neural paradigm. The finalstep of our research proposes an extension of the decoding process for a Neural Machine Translation (NMT) framework, independent of the model architecture, by shallow fusing the information from a neural translation model and the context semantics enclosed in the previously studied SSLMs. The aim of this modification is to introduce the benefits of context information also into the decoding process of NMT systems, as well as to obtain an additional validation for the techniques we explored. The automatic evaluation of our approaches does not reflect significant variations. This is expected since most automatic metrics are neither context-nor semantic-aware and because the phenomena we tackle are rare, leading to few modifications with respect to the baseline translations. On the other hand, manual evaluations demonstrate the positive impact of our approaches since human evaluators tend to prefer the translations produced by our document-aware systems. Therefore, the changes introduced by our enhanced systems are important since they are related to how humans perceive translation quality for long texts.En esta tesis se estudia la traducción automática de documentos teniendo en cuenta fenómenos que ocurren entre oraciones. Típicamente, esta información a nivel de documento se ignora por la mayoría de los sistemas de Traducción Automática (MT), que se centran en traducir los textos procesando cada una de las frases que los componen de manera aislada. Traducir cada frase sin mirar al contexto que la rodea puede llevar a generar cierto tipo de errores de traducción, como pueden ser traducciones inconsistentes para la misma palabra o para elementos que aparecen en la misma cadena de correferencia. En este trabajo se presentan métodos para prestar atención a fenómenos a nivel de documento con el objetivo de evitar este tipo de errores y así llegar a generar traducciones que transmitan correctamente el significado original del texto. Nuestra investigación empieza por identificar los errores de traducción relacionados con los fenómenos a nivel de documento que aparecen de manera común en la salida de los sistemas Estadísticos del Traducción Automática (SMT). Para dos de estos errores, la traducción inconsistente de palabras, así como los desacuerdos en género y número entre palabras, diseñamos técnicas simples pero efectivas como post-procesos para tratarlos y corregirlos. Como estas técnicas se aplican a posteriori, pueden acceder a los documentos enteros tanto del origen como la traducción generada, y así son capaces de hacer un análisis global y mejorar la coherencia y la consistencia de la traducción. Sin embargo, como seguir una estrategia de traducción en dos pasos no es óptima en términos de eficiencia, también nos centramos en introducir la conciencia del contexto durante el propio proceso de generación de la traducción. Para esto, extendemos un sistema SMT orientado a documentos incluyendo información semántica distribucional en forma de word embeddings bilingües y monolingües. En particular, estos embeddings se usan como un Modelo de Lenguaje de Espacio Semántico (SSLM) y como una nueva función característica del sistema. La meta del primero es promover traducciones de palabras que sean semánticamente cercanas a su contexto precedente, mientras que la segunda quiere promover la selección léxica que es más cercana a su contexto para aquellas palabras que tienen diferentes traducciones a lo largo de un documento. En ambos casos, el contexto que se tiene en cuenta va más allá de los límites de una frase u oración. Recientemente, la comunidad MT ha hecho una transición hacia el paradigma neuronal. El paso final de nuestra investigación propone una extensión del proceso de decodificación de un sistema de Traducción Automática Neuronal (NMT), independiente de la arquitectura del modelo de traducción, aplicando la técnica de Shallow Fusion para combinar la información del modelo de traducción neuronal y la información semántica del contexto encerrada en los modelos SSLM estudiados previamente. La motivación de esta modificación está en introducir los beneficios de la información del contexto también en el proceso de decodificación de los sistemas NMT, así como también obtener una validación adicional para las técnicas que se han ido explorando a lo largo de esta tesis. La evaluación automática de nuestras propuestas no refleja variaciones significativas. Esto es un comportamiento esperado ya que la mayoría de las métricas automáticas no se diseñan para ser sensibles al contexto o a la semántica, y además los fenómenos que tratamos son escasos, llevando a pocas modificaciones con respecto a las traducciones de partida. Por otro lado, las evaluaciones manuales demuestran el impacto positivo de nuestras propuestas ya que los evaluadores humanos tienen a preferir las traducciones generadas por nuestros sistemas a nivel de documento. Entonces, los cambios introducidos por nuestros sistemas extendidos son importantes porque están relacionados con la forma en que los humanos perciben la calidad de la traducción de textos largos.Postprint (published version