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In this paper we compare the behavior of different interest points detectors and descriptors under the conditions needed to be used as landmarks in visionbased simultaneous localization and mapping (SLAM). We evaluate the repeatability of the detectors, as well as the invariance and distinctiveness of the descriptors, under different perceptual conditions using sequences of images representing planar objects as well as 3D scenes. We believe that this information will be useful when selecting an appropriate landmark detector and descriptor for visual SLAM.

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Aim: To analyze changes in access to health care and its determinants in the immigrant and native-born populations in Spain, before and during the economic crisis. Methods: Comparative analysis of two iterations of the Spanish National Health Survey (2006 and 2012). Outcome variables were: unmet need and use of different healthcare levels; explanatory variables: need, predisposing and enabling factors. Multivariate models were performed (1) to compare outcome variables in each group between years, (2) to compare outcome variables between both groups within each year, and (3) to determine the factors associated with health service use for each group and year. Results: unmet healthcare needs decreased in 2012 compared to 2006; the use of health services remained constant, with some changes worth highlighting, such as the decline in general practitioner visits among autochthons and a narrowed gap in specialist visits between the two populations. The factors associated with health service use in 2006 remained constant in 2012. Conclusion: Access to healthcare did not worsen, possibly due to the fact that, until 2012, the national health system may have cushioned the deterioration of social determinants as a consequence of the financial crisis. Further studies are necessary to evaluate the effects of health policy responses to the crisis after 2012.

BackgroundPreventable mortality is a good indicator of possible problems to be investigated in the primary prevention chain, making it also a useful tool with which to evaluate health policies particularly public health policies. This study describes inequalities in preventable avoidable mortality in relation to socioeconomic status in small urban areas of thirty three Spanish cities, and analyses their evolution over the course of the periods 1996–2001 and 2002–2007.MethodsWe analysed census tracts and all deaths occurring in the population residing in these cities from 1996 to 2007 were taken into account. The causes included in the study were lung cancer, cirrhosis, AIDS/HIV, motor vehicle traffic accidents injuries, suicide and homicide. The census tracts were classified into three groups, according their socioeconomic level. To analyse inequalities in mortality risks between the highest and lowest socioeconomic levels and over different periods, for each city and separating by sex, Poisson regression were used.ResultsPreventable avoidable mortality made a significant contribution to general mortality (around 7.5%, higher among men), having decreased over time in men (12.7 in 1996–2001 and 10.9 in 2002–2007), though not so clearly among women (3.3% in 1996–2001 and 2.9% in 2002–2007). It has been observed in men that the risks of death are higher in areas of greater deprivation, and that these excesses have not modified over time. The result in women is different and differences in mortality risks by socioeconomic level could not be established in many cities.ConclusionsPreventable mortality decreased between the 1996–2001 and 2002–2007 periods, more markedly in men than in women. There were socioeconomic inequalities in mortality in most cities analysed, associating a higher risk of death with higher levels of deprivation. Inequalities have remained over the two periods analysed. This study makes it possible to identify those areas where excess preventable mortality was associated with more deprived zones. It is in these deprived zones where actions to reduce and monitor health inequalities should be put into place. Primary healthcare may play an important role in this process.

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Immigrants constitute a population vulnerable to the problem of violence. This study sought to ascertain the prevalence of violence reported by the immigrant population in the Murcian Region of Spain and characterize the related factors, taking the country population as reference. A cross-sectional study was carried out based on a representative population sample of Latin American (n = 672; 48% women), Moroccan (n = 361; 25% women), and Spanish origin (n = 1,303; 66% women), aged 16 to 64 years. Using a specific questionnaire, the prevalence of violence in the preceding year was assessed. The results were compared with the Spaniards using the 2006 National Health Survey (NHS). Multivariate logistic regression models were used to study the factors associated with violence having been reported in each group, both separately and in immigrants versus Spaniards. Finally, the cause and place of last aggression were studied. The prevalence of violence was 6.5% in Latin Americans, 12.0% in Moroccans, and 2.7% in Spaniards. Discrimination was the principal violence-related factor in all three groups. Among Latin Americans, low educational level was also associated with violence. Among Moroccans, those who had perceived discrimination showed the greatest differences in prevalence of violence compared with natives. Intimate partner violence (IPV) registered a prevalence of below 2%. As a conclusion, in this study, violence was little reported and higher among immigrants. The principal violence-related factor was discrimination. More studies of this type are called for to characterize the problem in other population-representative samples.

In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.