A Measurement Model of Cortisol Reactivity of Healthy Older Adults

Research on the physiological adaptation process has found that stress is associated with the rate of cortisol secretion, the main hormone that reflects stress. However, considerable variation among subjects has been reported. Using a sample of older adults (N=46), we tested the hypothesis that cortisol reactivity is composed of (1) a situation-related component representing hypothalamic influence on cortisol secretion observed on three different occasions, and (2) a stable component representing a general trait responsible for cortisol responses observed from occasion to occasion. LISREL VIII was used to test this hypothesis. Results indicated that a homogeneous reliability model was not supported by the data. A congeneric measurement model represented a better fit to the data. Results suggest that subjects have consistent patterns of response during separate experimental occasions. However, results do not suggest a consistent pattern of response over time. The main implication of these results is that salivary cortisol measures are sensitive to experimental stress situations. As such, this noninvasive method may be useful in examining adaptive responses to stress.

Ethics in science: enhancing the democratisation of knowledge production in transdisciplinary research partnerships for sustainable development

Better access to knowledge and knowledge production has to be reconsidered as key to successful individual and social mitigation and adaptation strategies for global change. Indeed, concepts of sustainable development imply a transformation of science towards fostering democratisation of knowledge production and the development of knowledge societies as a strategic goal. This means to open the process of scientific knowledge production while simultaneously empowering people to implement their own visions for sustainable development. Advocates of sustainability science support this transformation. In transdisciplinary practice, they advance equity and accountability in the access to and production of knowledge at the science–society interface. UNESCO points to advancements, yet Northern dominance persists in knowledge production as well as in technology design and transfer. Further, transdisciplinary practice remains experimental and hampered by inadequate and asymmetrically equipped institutions in the North and South and related epistemological and operational obscurity. To help identify clear, practicable transdisciplinary approaches, I recommend examining the institutional route – i.e., the learning and adaptation process – followed in concrete cases. The transdisciplinary Eastern and Southern Africa Partnership Programme (1998–2013) is a case ripe for such examination. Understanding transdisciplinarity as an integrative approach, I highlight ESAPP’s three key principles for a more democratised knowledge production for sustainable development: (1) integration of scientific and “non-scientific” knowledge systems; (2) integration of social actors and institutions; and (3) integrative learning processes. The analysis reveals ESAPP’s achievements in contributing to more democratic knowledge production and South ownership in the realm of sustainable development.

Knowledge as a resource: enhancing the democratisation of knowledge production in transdisciplinary research partnerships for sustainable development

Better access to knowledge and knowledge production has to be reconsidered as key to successful individual and social mitigation and adaptation strategies for global change. Indeed, concepts of sustainable development imply a transformation of science (Lubchenco 1998; WBGU 2011 and 2012) towards fostering democratisation of knowledge production as a contribution to the development of knowledge societies as a strategic goal (UNESCO 2005). This means to open the process of scientific knowledge production while simultaneously empowering people to implement their own visions for sustainable development. Advocates of sustainability science support this transformation. In transdisciplinary practice, they advance equity and accountability in the access to and production of knowledge at the science–society interface (Hirsch Hadorn et al 2006; Hirsch Hadorn et al 2008; Jäger 2009; Adger and Jordan 2009; KFPE 2012). UNESCO (2010) points to advancements, yet Northern dominance persists in knowledge production as well as in technology design and transfer (Standing and Taylor 2007; Zingerli 2010). Further, transdisciplinary practice remains experimental and hampered by inadequate and asymmetrically equipped institutions in the North and South and related epistemological and operational obscurity (Wiesmann et al 2011). To help identify clear, practicable transdisciplinary approaches, I recommend examining the institutional route (Mukhopadhyay et al 2006) – i.e., the learning and adaptation process – followed in concrete cases. The transdisciplinary Eastern and Southern Africa Partnership Programme (1998–2013) is a case ripe for such examination. Understanding transdisciplinarity as an integrative approach (Pohl et al 2008; Stock and Burton 2011), I highlight ESAPP’s three key principles for a more democratised knowledge production for sustainable development: (1) integration of scientific and “non-scientific” knowledge systems; (2) integration of social actors and institutions; and (3) integrative learning processes. The analysis reveals ESAPP’s achievements in contributing to more democratic knowledge production and South ownership in the realm of sustainable development.

Advances and challenges in skeletal muscle angiogenesis.

The role of capillaries is to serve as the interface for delivery of oxygen and removal of metabolites to/from tissues. During the past decade there has been a proliferation of studies that have advanced our understanding of angiogenesis demonstrating tissue capillary supply is under strict control during health, but poorly controlled in disease - resulting in either excessive capillary growth (pathological angiogenesis) or losses in capillarity (rarefaction). Given that skeletal muscle comprises nearly 40% of body mass in humans, skeletal muscle capillary density has a significant impact on metabolism, endocrine function, and locomotion, and is tightly regulated at many different levels. Skeletal muscle is also high adaptable, and thus one of the few organ systems which can be experimentally manipulated (e.g. by exercise) to study physiologic regulation of angiogenesis. This review will focus on 1) the methodological concerns that have arisen in determining skeletal muscle capillarity, and 2) highlight the concepts that are reshaping our understanding of the angio-adaptation process. We also summarize selected new findings (physical influences, molecular changes and ultrastructural rearrangement of capillaries) that identify areas of future research with the greatest potential to expand our understanding of how angiogenesis is normally regulated, and that may also help to better understand conditions of uncontrolled (pathologic) angiogenesis.

Contributions to Speech Analytics based on Speech Recognition and Topic Identification

La última década ha sido testigo de importantes avances en el campo de la tecnología de reconocimiento de voz. Los sistemas comerciales existentes actualmente poseen la capacidad de reconocer habla continua de múltiples locutores, consiguiendo valores aceptables de error, y sin la necesidad de realizar procedimientos explícitos de adaptación. A pesar del buen momento que vive esta tecnología, el reconocimiento de voz dista de ser un problema resuelto. La mayoría de estos sistemas de reconocimiento se ajustan a dominios particulares y su eficacia depende de manera significativa, entre otros muchos aspectos, de la similitud que exista entre el modelo de lenguaje utilizado y la tarea específica para la cual se está empleando. Esta dependencia cobra aún más importancia en aquellos escenarios en los cuales las propiedades estadísticas del lenguaje varían a lo largo del tiempo, como por ejemplo, en dominios de aplicación que involucren habla espontánea y múltiples temáticas. En los últimos años se ha evidenciado un constante esfuerzo por mejorar los sistemas de reconocimiento para tales dominios. Esto se ha hecho, entre otros muchos enfoques, a través de técnicas automáticas de adaptación. Estas técnicas son aplicadas a sistemas ya existentes, dado que exportar el sistema a una nueva tarea o dominio puede requerir tiempo a la vez que resultar costoso. Las técnicas de adaptación requieren fuentes adicionales de información, y en este sentido, el lenguaje hablado puede aportar algunas de ellas. El habla no sólo transmite un mensaje, también transmite información acerca del contexto en el cual se desarrolla la comunicación hablada (e.g. acerca del tema sobre el cual se está hablando). Por tanto, cuando nos comunicamos a través del habla, es posible identificar los elementos del lenguaje que caracterizan el contexto, y al mismo tiempo, rastrear los cambios que ocurren en estos elementos a lo largo del tiempo. Esta información podría ser capturada y aprovechada por medio de técnicas de recuperación de información (information retrieval) y de aprendizaje de máquina (machine learning). Esto podría permitirnos, dentro del desarrollo de mejores sistemas automáticos de reconocimiento de voz, mejorar la adaptación de modelos del lenguaje a las condiciones del contexto, y por tanto, robustecer al sistema de reconocimiento en dominios con condiciones variables (tales como variaciones potenciales en el vocabulario, el estilo y la temática). En este sentido, la principal contribución de esta Tesis es la propuesta y evaluación de un marco de contextualización motivado por el análisis temático y basado en la adaptación dinámica y no supervisada de modelos de lenguaje para el robustecimiento de un sistema automático de reconocimiento de voz. Esta adaptación toma como base distintos enfoque de los sistemas mencionados (de recuperación de información y aprendizaje de máquina) mediante los cuales buscamos identificar las temáticas sobre las cuales se está hablando en una grabación de audio. Dicha identificación, por lo tanto, permite realizar una adaptación del modelo de lenguaje de acuerdo a las condiciones del contexto. El marco de contextualización propuesto se puede dividir en dos sistemas principales: un sistema de identificación de temática y un sistema de adaptación dinámica de modelos de lenguaje. Esta Tesis puede describirse en detalle desde la perspectiva de las contribuciones particulares realizadas en cada uno de los campos que componen el marco propuesto: _ En lo referente al sistema de identificación de temática, nos hemos enfocado en aportar mejoras a las técnicas de pre-procesamiento de documentos, asimismo en contribuir a la definición de criterios más robustos para la selección de index-terms. – La eficiencia de los sistemas basados tanto en técnicas de recuperación de información como en técnicas de aprendizaje de máquina, y específicamente de aquellos sistemas que particularizan en la tarea de identificación de temática, depende, en gran medida, de los mecanismos de preprocesamiento que se aplican a los documentos. Entre las múltiples operaciones que hacen parte de un esquema de preprocesamiento, la selección adecuada de los términos de indexado (index-terms) es crucial para establecer relaciones semánticas y conceptuales entre los términos y los documentos. Este proceso también puede verse afectado, o bien por una mala elección de stopwords, o bien por la falta de precisión en la definición de reglas de lematización. En este sentido, en este trabajo comparamos y evaluamos diferentes criterios para el preprocesamiento de los documentos, así como también distintas estrategias para la selección de los index-terms. Esto nos permite no sólo reducir el tamaño de la estructura de indexación, sino también mejorar el proceso de identificación de temática. – Uno de los aspectos más importantes en cuanto al rendimiento de los sistemas de identificación de temática es la asignación de diferentes pesos a los términos de acuerdo a su contribución al contenido del documento. En este trabajo evaluamos y proponemos enfoques alternativos a los esquemas tradicionales de ponderado de términos (tales como tf-idf ) que nos permitan mejorar la especificidad de los términos, así como también discriminar mejor las temáticas de los documentos. _ Respecto a la adaptación dinámica de modelos de lenguaje, hemos dividimos el proceso de contextualización en varios pasos. – Para la generación de modelos de lenguaje basados en temática, proponemos dos tipos de enfoques: un enfoque supervisado y un enfoque no supervisado. En el primero de ellos nos basamos en las etiquetas de temática que originalmente acompañan a los documentos del corpus que empleamos. A partir de estas, agrupamos los documentos que forman parte de la misma temática y generamos modelos de lenguaje a partir de dichos grupos. Sin embargo, uno de los objetivos que se persigue en esta Tesis es evaluar si el uso de estas etiquetas para la generación de modelos es óptimo en términos del rendimiento del reconocedor. Por esta razón, nosotros proponemos un segundo enfoque, un enfoque no supervisado, en el cual el objetivo es agrupar, automáticamente, los documentos en clusters temáticos, basándonos en la similaridad semántica existente entre los documentos. Por medio de enfoques de agrupamiento conseguimos mejorar la cohesión conceptual y semántica en cada uno de los clusters, lo que a su vez nos permitió refinar los modelos de lenguaje basados en temática y mejorar el rendimiento del sistema de reconocimiento. – Desarrollamos diversas estrategias para generar un modelo de lenguaje dependiente del contexto. Nuestro objetivo es que este modelo refleje el contexto semántico del habla, i.e. las temáticas más relevantes que se están discutiendo. Este modelo es generado por medio de la interpolación lineal entre aquellos modelos de lenguaje basados en temática que estén relacionados con las temáticas más relevantes. La estimación de los pesos de interpolación está basada principalmente en el resultado del proceso de identificación de temática. – Finalmente, proponemos una metodología para la adaptación dinámica de un modelo de lenguaje general. El proceso de adaptación tiene en cuenta no sólo al modelo dependiente del contexto sino también a la información entregada por el proceso de identificación de temática. El esquema usado para la adaptación es una interpolación lineal entre el modelo general y el modelo dependiente de contexto. Estudiamos también diferentes enfoques para determinar los pesos de interpolación entre ambos modelos. Una vez definida la base teórica de nuestro marco de contextualización, proponemos su aplicación dentro de un sistema automático de reconocimiento de voz. Para esto, nos enfocamos en dos aspectos: la contextualización de los modelos de lenguaje empleados por el sistema y la incorporación de información semántica en el proceso de adaptación basado en temática. En esta Tesis proponemos un marco experimental basado en una arquitectura de reconocimiento en ‘dos etapas’. En la primera etapa, empleamos sistemas basados en técnicas de recuperación de información y aprendizaje de máquina para identificar las temáticas sobre las cuales se habla en una transcripción de un segmento de audio. Esta transcripción es generada por el sistema de reconocimiento empleando un modelo de lenguaje general. De acuerdo con la relevancia de las temáticas que han sido identificadas, se lleva a cabo la adaptación dinámica del modelo de lenguaje. En la segunda etapa de la arquitectura de reconocimiento, usamos este modelo adaptado para realizar de nuevo el reconocimiento del segmento de audio. Para determinar los beneficios del marco de trabajo propuesto, llevamos a cabo la evaluación de cada uno de los sistemas principales previamente mencionados. Esta evaluación es realizada sobre discursos en el dominio de la política usando la base de datos EPPS (European Parliamentary Plenary Sessions - Sesiones Plenarias del Parlamento Europeo) del proyecto europeo TC-STAR. Analizamos distintas métricas acerca del rendimiento de los sistemas y evaluamos las mejoras propuestas con respecto a los sistemas de referencia. ABSTRACT The last decade has witnessed major advances in speech recognition technology. Today’s commercial systems are able to recognize continuous speech from numerous speakers, with acceptable levels of error and without the need for an explicit adaptation procedure. Despite this progress, speech recognition is far from being a solved problem. Most of these systems are adjusted to a particular domain and their efficacy depends significantly, among many other aspects, on the similarity between the language model used and the task that is being addressed. This dependence is even more important in scenarios where the statistical properties of the language fluctuates throughout the time, for example, in application domains involving spontaneous and multitopic speech. Over the last years there has been an increasing effort in enhancing the speech recognition systems for such domains. This has been done, among other approaches, by means of techniques of automatic adaptation. These techniques are applied to the existing systems, specially since exporting the system to a new task or domain may be both time-consuming and expensive. Adaptation techniques require additional sources of information, and the spoken language could provide some of them. It must be considered that speech not only conveys a message, it also provides information on the context in which the spoken communication takes place (e.g. on the subject on which it is being talked about). Therefore, when we communicate through speech, it could be feasible to identify the elements of the language that characterize the context, and at the same time, to track the changes that occur in those elements over time. This information can be extracted and exploited through techniques of information retrieval and machine learning. This allows us, within the development of more robust speech recognition systems, to enhance the adaptation of language models to the conditions of the context, thus strengthening the recognition system for domains under changing conditions (such as potential variations in vocabulary, style and topic). In this sense, the main contribution of this Thesis is the proposal and evaluation of a framework of topic-motivated contextualization based on the dynamic and non-supervised adaptation of language models for the enhancement of an automatic speech recognition system. This adaptation is based on an combined approach (from the perspective of both information retrieval and machine learning fields) whereby we identify the topics that are being discussed in an audio recording. The topic identification, therefore, enables the system to perform an adaptation of the language model according to the contextual conditions. The proposed framework can be divided in two major systems: a topic identification system and a dynamic language model adaptation system. This Thesis can be outlined from the perspective of the particular contributions made in each of the fields that composes the proposed framework: _ Regarding the topic identification system, we have focused on the enhancement of the document preprocessing techniques in addition to contributing in the definition of more robust criteria for the selection of index-terms. – Within both information retrieval and machine learning based approaches, the efficiency of topic identification systems, depends, to a large extent, on the mechanisms of preprocessing applied to the documents. Among the many operations that encloses the preprocessing procedures, an adequate selection of index-terms is critical to establish conceptual and semantic relationships between terms and documents. This process might also be weakened by a poor choice of stopwords or lack of precision in defining stemming rules. In this regard we compare and evaluate different criteria for preprocessing the documents, as well as for improving the selection of the index-terms. This allows us to not only reduce the size of the indexing structure but also to strengthen the topic identification process. – One of the most crucial aspects, in relation to the performance of topic identification systems, is to assign different weights to different terms depending on their contribution to the content of the document. In this sense we evaluate and propose alternative approaches to traditional weighting schemes (such as tf-idf ) that allow us to improve the specificity of terms, and to better identify the topics that are related to documents. _ Regarding the dynamic language model adaptation, we divide the contextualization process into different steps. – We propose supervised and unsupervised approaches for the generation of topic-based language models. The first of them is intended to generate topic-based language models by grouping the documents, in the training set, according to the original topic labels of the corpus. Nevertheless, a goal of this Thesis is to evaluate whether or not the use of these labels to generate language models is optimal in terms of recognition accuracy. For this reason, we propose a second approach, an unsupervised one, in which the objective is to group the data in the training set into automatic topic clusters based on the semantic similarity between the documents. By means of clustering approaches we expect to obtain a more cohesive association of the documents that are related by similar concepts, thus improving the coverage of the topic-based language models and enhancing the performance of the recognition system. – We develop various strategies in order to create a context-dependent language model. Our aim is that this model reflects the semantic context of the current utterance, i.e. the most relevant topics that are being discussed. This model is generated by means of a linear interpolation between the topic-based language models related to the most relevant topics. The estimation of the interpolation weights is based mainly on the outcome of the topic identification process. – Finally, we propose a methodology for the dynamic adaptation of a background language model. The adaptation process takes into account the context-dependent model as well as the information provided by the topic identification process. The scheme used for the adaptation is a linear interpolation between the background model and the context-dependent one. We also study different approaches to determine the interpolation weights used in this adaptation scheme. Once we defined the basis of our topic-motivated contextualization framework, we propose its application into an automatic speech recognition system. We focus on two aspects: the contextualization of the language models used by the system, and the incorporation of semantic-related information into a topic-based adaptation process. To achieve this, we propose an experimental framework based in ‘a two stages’ recognition architecture. In the first stage of the architecture, Information Retrieval and Machine Learning techniques are used to identify the topics in a transcription of an audio segment. This transcription is generated by the recognition system using a background language model. According to the confidence on the topics that have been identified, the dynamic language model adaptation is carried out. In the second stage of the recognition architecture, an adapted language model is used to re-decode the utterance. To test the benefits of the proposed framework, we carry out the evaluation of each of the major systems aforementioned. The evaluation is conducted on speeches of political domain using the EPPS (European Parliamentary Plenary Sessions) database from the European TC-STAR project. We analyse several performance metrics that allow us to compare the improvements of the proposed systems against the baseline ones.

The selectivity of the hair cell’s mechanoelectrical-transduction channel promotes Ca2+ flux at low Ca2+ concentrations

The mechanoelectrical-transduction channel of the hair cell is permeable to both monovalent and divalent cations. Because Ca2+ entering through the transduction channel serves as a feedback signal in the adaptation process that sets the channel’s open probability, an understanding of adaptation requires estimation of the magnitude of Ca2+ influx. To determine the Ca2+ current through the transduction channel, we measured extracellular receptor currents with transepithelial voltage-clamp recordings while the apical surface of a saccular macula was bathed with solutions containing various concentrations of K+, Na+, or Ca2+. For modest concentrations of a single permeant cation, Ca2+ carried much more receptor current than did either K+ or Na+. For higher cation concentrations, however, the flux of Na+ or K+ through the transduction channel exceeded that of Ca2+. For mixtures of Ca2+ and monovalent cations, the receptor current displayed an anomalous mole-fraction effect, which indicates that ions interact while traversing the channel’s pore. These results demonstrate not only that the hair cell’s transduction channel is selective for Ca2+ over monovalent cations but also that Ca2+ carries substantial current even at low Ca2+ concentrations. At physiological cation concentrations, Ca2+ flux through transduction channels can change the local Ca2+ concentration in stereocilia in a range relevant for the control of adaptation.

Adaptação cultural e validação da Compliance with Standard Precautions Scale (CSPS) para enfermeiros brasileiros

Introdução: As precauções-padrão (PP) constituem um conjunto de medidas que têm como finalidade minimizar o risco de transmissão ocupacional de patógenos, sendo indispensável sua utilização por profissionais de saúde, sobretudo pelos enfermeiros. No entanto, a não adesão às PP constitui problemática amplamente discutida em todo o mundo. Embora haja diversos estudos brasileiros que visem avaliar a adesão às PP , ainda tem-se observado grande fragilidade no processo de construção e de validação dos instrumentos utilizados para avaliação deste construto. Objetivo: Realizar a adaptação cultural e validação da Compliance with Standard Precautions Scale (CSPS) para enfermeiros brasileiros. Metodologia: Trata-se de um estudo metodológico para a adaptação e validação da CSPS. Essa escala é composta por 20 itens com quatro opções de respostas, e destina-se a avaliar a adesão às PP. O processo de adaptação consistiu em Tradução, Consenso entre Juízes, Retrotradução e Validação Semântica. A primeira etapa foi a tradução do idioma original para o português do Brasil. Após foi realizado um comitê composto por sete juízes, a versão de consenso obtida na etapa anterior foi traduzida novamente para o idioma de origem. Foram avaliadas as propriedades psicométricas do instrumento, considerando-se as validades de face e de conteúdo, a validade de construto e a confiabilidade. A versão para o Português do Brasil da CSPS (CSPS-PB) foi aplicada em uma amostra de 300 enfermeiros que atuam na assistência a pacientes em um hospital localizado na cidade de São Paulo/SP. A confiabilidade foi avaliada por meio da consistência interna (alfa de Cronbach) e teste reteste (coeficiente de correlação intraclasse - ICC). Para a validação de construto, foi utilizada a comparação entre grupos diferentes, análise fatorial exploratória e análise fatorial confirmatória, segundo o Modelo de Equações Estruturais (SEM). Utilizou-se o software IBM® SPSS, 19.0. Para a análise fatorial confirmatória foi utilizado o módulo específico Analysis of Moment Structures (IBM® SPSS AMOS). Para a análise paralela utilizou-se o programa RanEigen Syntax. O nível de significância adotado foi ? = 0,05. Todos os aspectos éticos foram contemplados. Resultados: A tradução realizada por tradutores juramentados garantiu qualidade a esse processo. A validação de face e de conteúdo possibilitou a realização de modificações pertinentes e imperativas a fim de atender aos critérios de equivalências conceituais, idiomáticas, culturais e semânticas. Obteve-se ?=0,61 na avaliação da consistência interna, indicando confiabilidade satisfatória. O ICC indicou uma correlação de 0,87 quase perfeita para o teste reteste duas semanas após a primeira abordagem, conferindo estabilidade satisfatória. A validade de construto mostrou que a CSPS-PB foi capaz de discriminar as médias de adesão às PP entre grupos distintos referente à idade (F=5,15 p<=0,01), ao tempo de experiência clínica (F = 8,9 p<= 0,000) e a ter recebido treinamento (t = 2,48 p<=0,01). Na análise fatorial confirmatória, o modelo foi subidentificado. A análise fatorial exploratória indicou que todos os itens apresentaram cargas fatoriais adequadas (>=0,30), sendo identificados quatro fatores pela análise paralela. O total de variância explicada foi de 35,48%. Conclusão: A CSPS-PB, trata-se de um instrumento adequado, confiável e válido para medir a adesão às PP entre enfermeiros brasileiros

Creación automática de sistemas de búsqueda de respuestas en dominios restringidos

Los sistemas de búsqueda de respuestas (BR) se pueden considerar como potenciales sucesores de los buscadores tradicionales de información en la Web. Para que sean precisos deben adaptarse a dominios concretos mediante el uso de recursos semánticos adecuados. La adaptación no es una tarea trivial, ya que deben integrarse e incorporarse a sistemas de BR existentes varios recursos heterogéneos relacionados con un dominio restringido. Se presenta la herramienta Maraqa, cuya novedad radica en el uso de técnicas de ingeniería del software, como el desarrollo dirigido por modelos, para automatizar dicho proceso de adaptación a dominios restringidos. Se ha evaluado Maraqa mediante una serie de experimentos (sobre el dominio agrícola) que demuestran su viabilidad, mejorando en un 29,5% la precisión del sistema adaptado.

Primeras políticas de vivienda en España y su influencia en la evolución de la tipología residencial: el caso de Benalúa (1883-1956)

El estudio del proceso de adaptación tipológica de las arquitecturas residenciales del barrio de Benalúa, una de las áreas consolidadas más singulares de la ciudad de Alicante (España), constituye un ejemplo clave para entender el alcance que tuvieron las primeras políticas de vivienda aplicadas en ese país, con anterioridad a la redacción de los Planes Generales que, en el transcurso del siglo XX, fueron ordenando las ciudades españolas y que en el caso de Alicante coincidió con la aprobación de la primera Ley del Suelo estatal (1956). De su análisis se obtienen las conclusiones que identifican los procedimientos que, por cambios sociales, políticos, de normativa o presión del mercado inmobiliario, condicionaron la evolución de la vivienda durante siete décadas, huellas que en la actualidad vienen desapareciendo a un ritmo vertiginoso, constatando el grado de intervención del Estado y de los municipios, así como su influencia y responsabilidad en la determinación de los tipos edificatorios.

Factors that determine the level of commitment of our teaching staff when the implementation of continuous evaluation system takes place

Comunicación presentada en CIDUI 2010, Congreso Internacional Docencia Universitaria e Innovación, Barcelona, 30 junio-2 julio 2010.

Willingness Towards Continuous Assessment

Among the factors that affect the convergence towards the European Higher Education Area, university teaching staff's motivation is fundamental, and consequently, it is crucial to empirically know what this motivation depends on. In this context, one of the most relevant changes in the teacher-student relationship is assessment. In fact, the transition from a static assessment -focused on only one temporal point (final exam)- to a dynamic assessment, will require changes in thought and action, both on the part of teachers and students. In this line, the objective of this paper is to analyze the determinants of teaching staff's predisposition to the continuous assessment method. Specifically, we consider the following explanatory dimensions: teaching method used (which measures their degree of involvement with the ongoing adaptation process), type of subject (core, compulsory and optional), and teacher's personal characteristics (professional status and gender). The empirical application carried out at the University of Alicante uses Logit Models with Random Coefficients to capture heterogeneity, and shows that "cooperative learning" is a clear-cut determinant of "continuous assessment" as well as "continuous assessment plus final examination". Also, a conspicuous result, which in turn becomes a thought-provoking finding, is that professional status is highly relevant as a teacher's engagement is closely related to prospects of stability. Consequently, the most relevant implications from the results revolve around the way academic institutions can propose and implement inducement for their teaching staff.

Fostering Teaching Staff's Engagement in Continuous Assessment

Among the factors that affect the convergence towards the European Higher Education Area, university teaching staff's motivation is fundamental, and consequently, it is crucial to empirically know what this motivation depends on. In this context, one of the most relevant changes in the teacher-student relationship is assessment. In fact, the transition from a static assessment -focused on only one temporal point (final exam)- to a dynamic assessment, will require changes in thought and action, both on the part of teachers and students. In this line, the objective of this paper is to analyze the determinants of teaching staff's predisposition to the continuous assessment method. Specifically, we consider the following explanatory dimensions: teaching method used (which measures their degree of involvement with the ongoing adaptation process), type of subject (core, compulsory and optional), and teacher's personal characteristics (professional status and gender). The empirical application carried out at the University of Alicante uses Logit Models with Random Coefficients to capture heterogeneity, and shows that "cooperative learning" is a clear-cut determinant of "continuous assessment" as well as "continuous assessment plus final examination". Also, a conspicuous result, which in turn becomes a thought-provoking finding, is that professional status is highly relevant as a teacher's engagement is closely related to prospects of stability. Consequently, the most relevant implications from the results revolve around the way academic institutions can propose and implement inducement for their teaching staff.

MIGRAÇÃO, PENTECOSTALISMO E PERIFERIA URBANA NO BAIRRO CIDADE ARACY EM SÃO CARLOS INTERIOR DE SÃO PAULO

Essa pesquisa estuda o papel de grupos religiosos pentecostais junto a migrantes em uma região periférica da cidade de São Carlos no interior de São Paulo. Tomamos como foco de estudo duas igrejas localizadas na região periférica dessa cidade, especificamente do bairro denominado Cidade Aracy. Apresentamos as diferentes fases do desenvolvimento, formação e constituição do bairro em estudo com as configurações assumidas pelo espaço em seu processo de crescimento, desenvolvimento e constituição de periferia. Utilizamos o conceito de periferia urbana vinculado às condições de segregação destacando o componente migratório dos moradores da região em estudo. Analisamos finalmente as características de grupos pentecostais, prestando especial atenção ao papel por eles cumprido na acolhida e na adaptação dos migrantes de outras regiões do país e do Estado. Nosso tema situa-se no contexto maior do mundo urbano como caraterística fundamental da modernidade com as reconfigurações das formas religiosas. Nosso campo teórico combina a sociologia da religião e a sociologia urbana. A pesquisa incluiu observação intensa de campo, mapeamento dos grupos religiosos, aplicação de questionários e entrevistas.

Entering an academic discourse community: A case study of the coping strategies of eleven English as a Second Language students

This case study follows eleven non-English speaking students as they adapt to community college, content courses. The three classes examined are required freshman classes--Humanities, Social Environment, and Individual in Transition. In order to cope with the demands of these classes, students must penetrate the academic discourse community and have effective relationships with their instructors and their peers. The results of the study are based on interviews with eleven non-native speaking (NNS) students and their instructors and on an analysis of student writing assignments, course syllabi, and exams. Three general areas are examined: (a) students' first-language (L$\sb1$) education, (b) the requirements of their content classes, and (c) the affective factors which influence their adaptation process.^ The case of these students reveals that: (1) Students draw on their L$\sb1$ education, especially in terms of content, as they cope with the demands of these content classes. (2) In some areas L$\sb1$ educational experiences interfere with students' ability to adapt. (3) The content classes require students to have well developed reading, writing, oral, and aural skills. (4) Students must use higher level cognitive skills to be successful in content classes. (5) Affective factors play a role in students' success in content classes. The discussion section includes possible implications of this data for college level English as a Second Language courses. ^

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.