Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence

Modern statistical models for forensic fingerprint examinations : a critical review

Over the last decade, the development of statistical models in support of forensic fingerprint identification has been the subject of increasing research attention, spurned on recently by commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. Such models are increasingly seen as useful tools in support of the fingerprint identification process within or in addition to the ACE-V framework. This paper provides a critical review of recent statistical models from both a practical and theoretical perspective. This includes analysis of models of two different methodologies: Probability of Random Correspondence (PRC) models that focus on calculating probabilities of the occurrence of fingerprint configurations for a given population, and Likelihood Ratio (LR) models which use analysis of corresponding features of fingerprints to derive a likelihood value representing the evidential weighting for a potential source.

Using 3D surface datasets to understand landslide evolution: From analogue models to real case study

Early detection of landslide surface deformation with 3D remote sensing techniques, as TLS, has become a great challenge during last decade. To improve our understanding of landslide deformation, a series of analogue simulation have been carried out on non-rigid bodies coupled with 3D digitizer. All these experiments have been carried out under controlled conditions, as water level and slope angle inclination. We were able to follow 3D surface deformation suffered by complex landslide bodies from precursory deformation still larger failures. These experiments were the basis for the development of a new algorithm for the quantification of surface deformation using automatic tracking method on discrete points of the slope surface. To validate the algorithm, comparisons were made between manually obtained results and algorithm surface displacement results. Outputs will help in understanding 3D deformation during pre-failure stages and failure mechanisms, which are fundamental aspects for future implementation of 3D remote sensing techniques in early warning systems.

Visualització de models fusionats

L’objectiu principal d’aquest projecte era implementar la visualització 3D demodels fusionats i aplicar totes les tècniques possibles per realitzar aquesta fusió. Aquestes tècniques s’integraran en la plataforma de visualització i processament de dades mèdiques STARVIEWER. Per assolir l’ objectiu principal s’ han definit els següents objectius específics:1- estudiar els algoritmes de visualització de models simples i analitzar els diferents paràmetres a tenir en compte. 2- ampliació de la tècnica de visualització bàsica seleccionada per tal de suportar els models fusionats. 3- avaluar i compar tots els mètodes implementats per poder determinar quin ofereix les millors visualitzacions

Diagnosi basada en models tenint en compte els retards en xarxes de comunicació

Els mètodes de detecció, diagnosi i aïllament de fallades (Fault Detection and Isolation - FDI) basats en la redundància analítica (és a dir, la comparació del comportament actual del procés amb l’esperat, obtingut mitjançant un model matemàtic del mateix), són àmpliament utilitzats per al diagnòstic de sistemes quan el model matemàtic està disponible. S’ha implementat un algoritme per implementar aquesta redundància analítica a partir del model de la plana conegut com a Anàlisi Estructural

Toma de decisiones en Enfermería de Urgencias, Emergencias y Catástrofes: Márgenes de Autonomía y Responsabilidad

Fear of achieving higher levels of nurse autonomy must be overcome for a new environment of relationships, change, communication and respect within the multidisciplinary team. The progressive achievement of new skills, the handling of evidence and the implementation of models and ways of working based on the nursing process, through encouraged training courses into the company and by the possibility of resource management in line and technology, foster as the ideal setting for Emergency Nursing, Emergency and Disaster acquires its own identity and development.

Models a Espanya, Pais Basc: Norma vasca de autoprotección

Ponència presentada a la Jornada plans d'autoprotecció

Gut Microbiota Composition in Male Rat Models under Different Nutritional Status and Physical Activity and Its Association with Serum Leptin and Ghrelin Levels.

BACKGROUND Several evidences indicate that gut microbiota is involved in the control of host energy metabolism. OBJECTIVE To evaluate the differences in the composition of gut microbiota in rat models under different nutritional status and physical activity and to identify their associations with serum leptin and ghrelin levels. METHODS IN A CASE CONTROL STUDY, FORTY MALE RATS WERE RANDOMLY ASSIGNED TO ONE OF THESE FOUR EXPERIMENTAL GROUPS: ABA group with food restriction and free access to exercise; control ABA group with food restriction and no access to exercise; exercise group with free access to exercise and feed ad libitum and ad libitum group without access to exercise and feed ad libitum. The fecal bacteria composition was investigated by PCR-denaturing gradient gel electrophoresis and real-time qPCR. RESULTS In restricted eaters, we have found a significant increase in the number of Proteobacteria, Bacteroides, Clostridium, Enterococcus, Prevotella and M. smithii and a significant decrease in the quantities of Actinobacteria, Firmicutes, Bacteroidetes, B. coccoides-E. rectale group, Lactobacillus and Bifidobacterium with respect to unrestricted eaters. Moreover, a significant increase in the number of Lactobacillus, Bifidobacterium and B. coccoides-E. rectale group was observed in exercise group with respect to the rest of groups. We also found a significant positive correlation between the quantity of Bifidobacterium and Lactobacillus and serum leptin levels, and a significant and negative correlation among the number of Clostridium, Bacteroides and Prevotella and serum leptin levels in all experimental groups. Furthermore, serum ghrelin levels were negatively correlated with the quantity of Bifidobacterium, Lactobacillus and B. coccoides-Eubacterium rectale group and positively correlated with the number of Bacteroides and Prevotella. CONCLUSIONS Nutritional status and physical activity alter gut microbiota composition affecting the diversity and similarity. This study highlights the associations between gut microbiota and appetite-regulating hormones that may be important in terms of satiety and host metabolism.

Insights from animal models on the immunogenetics of leprosy: a review

A variety of host immunogenetic factors appear to influence both an individual's susceptibility to infection with Mycobacterium leprae and the pathologic course of the disease. Animal models can contribute to a better understanding of the role of immunogenetics in leprosy through comparative studies helping to confirm the significance of various identified traits and in deciphering the underlying mechanisms that may be involved in expression of different disease related phenotypes. Genetically engineered mice, with specific immune or biochemical pathway defects, are particularly useful for investigating granuloma formation and resistance to infection and are shedding new light on borderline areas of the leprosy spectrum which are clinically unstable and have a tendency toward immunological complications. Though armadillos are less developed in this regard, these animals are the only other natural hosts of M. leprae and they present a unique opportunity for comparative study of genetic markers and mechanisms associable with disease susceptibility or resistance, especially the neurological aspects of leprosy. In this paper, we review the recent contributions of genetically engineered mice and armadillos toward our understanding of the immunogenetics of leprosy.

Wandering, verbally and physically abusive behaviour and their relation with pain in nursing homes residents

Backgrounds:¦Behavioural and psychological symptoms of dementia (BPSD) include, among others, hallucinations, delusions, depression, euphoria, agitation, aggression, sexual desinhibition, sleep disturbances, and apathy (1). To our knowledge, surprisingly few studies looked into the possible association between pain and BPSD in nursing home residents. Given this dearth of studies, we wondered whether or not there is an association, in nursing home residents, between pain and BPSD, in particular wandering as well as verbally and physically abusive behaviour, and whether or not this possible association changes with the degree of cognitive impairment.¦Method:¦All nursing home residents in the three Swiss cantons Aargau, Basel-City, and Solothurn (corresponding to 13.5%¦of the total Swiss population) receive a Resident Assessment Instrument Minimum Data Set (RAI-MDS)¦assessment within the first two weeks upon entry. This yielded a total sample of 16'430 nursing home residents considering that the residents' assessment took place between 1997 and 2007 and that we only took into account the admission RAI-MDS assessment. Only residents for whom data on pain was recorded were included in the study (n = 16'183).¦Results:¦Wandering correlated significantly with pain although the effect size was small (Spearman correlation coefficient = 0.052; p = 0.000), a result very similar to that found for VAB (Spearman correlation coefficient = 0.034; p = 0.000) and PAB (Spearman correlation coefficient = 0.043; p = 0.000). Likewise, using linear regression analyses, pain was very significantly associated with any of the three BPSD considered, but it predicted astonishingly little of the¦variance observed (wandering: B = 0.036; p = 0.000; R2 = 0.002; VAB: B = 0.021; p = 0.000; R2 = 0.001 PAB: B = 0.012; p = 0.000; R2 = 0.001). The interaction of pain and cognition had a significant effect on the three BPSD, suggesting that cognition was a moderator of the relationship between pain and all three behaviours.¦Conclusion:¦Wandering behaviours, VAB and PAB seem to be predicted by many factors. Although pain predicts only a small part of variance of these behaviours, it still remains important to recognise and treat pain in order to reduce these behaviours at least a little both in intensity and frequency. Given the dearth of studies and their somewhat contradictory results, further studies ought to investigate the role, the type and localisation of pain might play on the expression of different BPSD or how residents suffering from dementia perceive pain.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Severity of chronic experimental Chagas' heart disease parallels tumour necrosis factor and nitric oxide levels in the serum: models of mild and severe disease

Heart tissue inflammation, progressive fibrosis and electrocardiographic alterations occur in approximately 30% of patients infected by Trypanosoma cruzi, 10-30 years after infection. Further, plasma levels of tumour necrosis factor (TNF) and nitric oxide (NO) are associated with the degree of heart dysfunction in chronic chagasic cardiomyopathy (CCC). Thus, our aim was to establish experimental models that mimic a range of parasitological, pathological and cardiac alterations described in patients with chronic Chagas’ heart disease and evaluate whether heart disease severity was associated with increased TNF and NO levels in the serum. Our results show that C3H/He mice chronically infected with the Colombian T. cruzi strain have more severe cardiac parasitism and inflammation than C57BL/6 mice. In addition, connexin 43 disorganisation and fibronectin deposition in the heart tissue, increased levels of creatine kinase cardiac MB isoenzyme activity in the serum and more severe electrical abnormalities were observed in T. cruzi-infected C3H/He mice compared to C57BL/6 mice. Therefore, T. cruzi-infected C3H/He and C57BL/6 mice represent severe and mild models of CCC, respectively. Moreover, the CCC severity paralleled the TNF and NO levels in the serum. Therefore, these models are appropriate for studying the pathophysiology and biomarkers of CCC progression, as well as for testing therapeutic agents for patients with Chagas’ heart disease.