Perceived sexism as a health determinant in Spain

OBJECTIVES: The goals of the present study are to explore the association between perceived sexism and self-perceived health, health-related behaviors, and unmet medical care needs among women in Spain; to analyze whether higher levels of discrimination are associated with higher prevalence of poor health indicators and to examine whether these relationships are modified by country of origin and social class. MATERIALS AND METHODS: The study is based on a cross-sectional design using data from the 2006 Spanish Health Interview Survey. We included women aged 20-64 years (n = 10,927). Six dependent variables were examined: four of health (self-perceived health, mental health, hypertension, and having had an injury during the previous year), one health behavior (smoking), and another related to the use of the health services (unmet need for medical care). Perceived sexism was the main independent variable. Social class and country of origin were considered as effect modifiers. We obtained the prevalence of perceived sexism. Logistic regression models, adjusted for potential confounders, were fitted to study the association between sexism and poor health outcomes. Results: The prevalence of perceived sexism was 3.4%. Perceived sexism showed positive and consistent associations with four poor health outcomes (poor self-perceived health, poor mental health, injuries in the last 12 months, and smoking). The strength of these associations increased with increased scores for perceived sexism, and the patterns were found to be modified by country of origin and social class. CONCLUSION: This study shows a consistent association between perceived sexism and poor health outcomes in a country of southern Europe with a strong patriarchal tradition.

Sequential and parallel synchronous alternating iterative methods

The so-called parallel multisplitting nonstationary iterative Model A was introduced by Bru, Elsner, and Neumann [Linear Algebra and its Applications 103:175-192 (1988)] for solving a nonsingular linear system Ax = b using a weak nonnegative multisplitting of the first type. In this paper new results are introduced when A is a monotone matrix using a weak nonnegative multisplitting of the second type and when A is a symmetric positive definite matrix using a P -regular multisplitting. Also, nonstationary alternating iterative methods are studied. Finally, combining Model A and alternating iterative methods, two new models of parallel multisplitting nonstationary iterations are introduced. When matrix A is monotone and the multisplittings are weak nonnegative of the first or of the second type, both models lead to convergent schemes. Also, when matrix A is symmetric positive definite and the multisplittings are P -regular, the schemes are also convergent.

Price sensitivity to tourism activities: looking for determinant factors

The literature contains evidence that there is a marked heterogeneity in price responses to tourism products, leading to a great variety of tourist sensitivities to price. Thus the role price plays is complex, and a particularly challenging aspect of this complexity is that its effect is not unambiguous, thereby negating the idea that the demand for tourism products and tourist activities can always be regarded as demand for ordinary goods. This article identifies and explains, as a novelty for the tourism industry, price sensitivities to tourism activities individual by individual. The operative formalization uses a mixed logit model to estimate the individual sensitivities to price, and then a regression analysis is applied to detect their determinants. The empirical application finds that motivations, influenced by age, and length of stay with a non-linear effect, are explanatory factors of tourists’ price sensitivity to activities.

Determinant factors of senior tourists’ length of stay

The current tendency to undertake more trips, but of shorter duration, throughout the year, has meant that the tourist industry has started to show greater interest in attracting those market segments that opt for more prolonged stays, as they are especially profitable. One of these segments is that of seniors. Given the aging demographic of the population worldwide, which is particularly noticeable in Spain, the object of this study is to identify the variables that determine the length of stay of Spanish seniors at their destination. The Negative Binomial model was adapted to the context of length of stay by Spanish seniors and the determinant factors identified were: age, travel purpose, climate, type of accommodation, group size, trip type and the activities carried out at the destination. This study is a contribution to this field from an empirical point of view, given the scarcity of studies of this type and their eminently descriptive character; as well as from a practical level, with interesting implications for the sector.

Convergence analysis and validation of low cost distance metrics for computational cost reduction of the Iterative Closest Point algorithm

The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations.

Estudio y mejora de métodos de registro 3D: aceleración sobre unidades de procesamiento gráfico y caracterización del espacio de transformaciones iniciales

Durante los últimos años ha sido creciente el uso de las unidades de procesamiento gráfico, más conocidas como GPU (Graphic Processing Unit), en aplicaciones de propósito general, dejando a un lado el objetivo para el que fueron creadas y que no era otro que el renderizado de gráficos por computador. Este crecimiento se debe en parte a la evolución que han experimentado estos dispositivos durante este tiempo y que les ha dotado de gran potencia de cálculo, consiguiendo que su uso se extienda desde ordenadores personales a grandes cluster. Este hecho unido a la proliferación de sensores RGB-D de bajo coste ha hecho que crezca el número de aplicaciones de visión que hacen uso de esta tecnología para la resolución de problemas, así como también para el desarrollo de nuevas aplicaciones. Todas estas mejoras no solamente se han realizado en la parte hardware, es decir en los dispositivos, sino también en la parte software con la aparición de nuevas herramientas de desarrollo que facilitan la programación de estos dispositivos GPU. Este nuevo paradigma se acuñó como Computación de Propósito General sobre Unidades de Proceso Gráfico (General-Purpose computation on Graphics Processing Units, GPGPU). Los dispositivos GPU se clasifican en diferentes familias, en función de las distintas características hardware que poseen. Cada nueva familia que aparece incorpora nuevas mejoras tecnológicas que le permite conseguir mejor rendimiento que las anteriores. No obstante, para sacar un rendimiento óptimo a un dispositivo GPU es necesario configurarlo correctamente antes de usarlo. Esta configuración viene determinada por los valores asignados a una serie de parámetros del dispositivo. Por tanto, muchas de las implementaciones que hoy en día hacen uso de los dispositivos GPU para el registro denso de nubes de puntos 3D, podrían ver mejorado su rendimiento con una configuración óptima de dichos parámetros, en función del dispositivo utilizado. Es por ello que, ante la falta de un estudio detallado del grado de afectación de los parámetros GPU sobre el rendimiento final de una implementación, se consideró muy conveniente la realización de este estudio. Este estudio no sólo se realizó con distintas configuraciones de parámetros GPU, sino también con diferentes arquitecturas de dispositivos GPU. El objetivo de este estudio es proporcionar una herramienta de decisión que ayude a los desarrolladores a la hora implementar aplicaciones para dispositivos GPU. Uno de los campos de investigación en los que más prolifera el uso de estas tecnologías es el campo de la robótica ya que tradicionalmente en robótica, sobre todo en la robótica móvil, se utilizaban combinaciones de sensores de distinta naturaleza con un alto coste económico, como el láser, el sónar o el sensor de contacto, para obtener datos del entorno. Más tarde, estos datos eran utilizados en aplicaciones de visión por computador con un coste computacional muy alto. Todo este coste, tanto el económico de los sensores utilizados como el coste computacional, se ha visto reducido notablemente gracias a estas nuevas tecnologías. Dentro de las aplicaciones de visión por computador más utilizadas está el registro de nubes de puntos. Este proceso es, en general, la transformación de diferentes nubes de puntos a un sistema de coordenadas conocido. Los datos pueden proceder de fotografías, de diferentes sensores, etc. Se utiliza en diferentes campos como son la visión artificial, la imagen médica, el reconocimiento de objetos y el análisis de imágenes y datos de satélites. El registro se utiliza para poder comparar o integrar los datos obtenidos en diferentes mediciones. En este trabajo se realiza un repaso del estado del arte de los métodos de registro 3D. Al mismo tiempo, se presenta un profundo estudio sobre el método de registro 3D más utilizado, Iterative Closest Point (ICP), y una de sus variantes más conocidas, Expectation-Maximization ICP (EMICP). Este estudio contempla tanto su implementación secuencial como su implementación paralela en dispositivos GPU, centrándose en cómo afectan a su rendimiento las distintas configuraciones de parámetros GPU. Como consecuencia de este estudio, también se presenta una propuesta para mejorar el aprovechamiento de la memoria de los dispositivos GPU, permitiendo el trabajo con nubes de puntos más grandes, reduciendo el problema de la limitación de memoria impuesta por el dispositivo. El funcionamiento de los métodos de registro 3D utilizados en este trabajo depende en gran medida de la inicialización del problema. En este caso, esa inicialización del problema consiste en la correcta elección de la matriz de transformación con la que se iniciará el algoritmo. Debido a que este aspecto es muy importante en este tipo de algoritmos, ya que de él depende llegar antes o no a la solución o, incluso, no llegar nunca a la solución, en este trabajo se presenta un estudio sobre el espacio de transformaciones con el objetivo de caracterizarlo y facilitar la elección de la transformación inicial a utilizar en estos algoritmos.

Health-related quality of life and determinant factors in celiac disease. A population-based analysis of adult patients in Spain

Background: Celiac disease (CD) has a negative impact on the health-related quality of life (HRQL) of affected patients. Although HRQL and its determinants have been examined in Spanish CD patients specifically recruited in hospital settings, these aspects of CD have not been assessed among the general Spanish population. Methods: An observational, transversal study of a non-randomized, representative sample of adult celiac patients throughout all of Spain's Autonomous Regions. Subjects were recruited through celiac patient associations. A Spanish version of the self-administered Celiac Disease-Quality of Life (CD-QOL) questionnaire was used. Determinant factors of HRQL were assessed with the aid of multivariate analysis to control for confounding factors. Results: We analyzed the responses provided by 1,230 patients, 1,092 (89.2%) of whom were women. The overall mean value for the CD-QOL index was 56.3 ± 18.27 points. The dimension that obtained the most points was dysphoria, with 81.3 ± 19.56 points, followed by limitations with 52.3 ± 23.43 points; health problems, with 51.6 ± 26.08 points, and inadequate treatment, with 36.1 ± 21.18 points. Patient age and sex, along with time to diagnosis, and length of time on a gluten-free diet were all independent determinant factors of certain dimensions of HRQL: women aged 31 to 40 expressed poorer HRQL while time to diagnosis and length of time on a gluten-free diet were determinant factors for better HRQL scores. Conclusions: The HRQL of adult Spanish celiac subjects is moderate, improving with the length of time patients remain on a gluten-free diet.