1000 resultados para medial approach


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We will present an analysis of data from a literature review and semi-structured interviews with experts on OER, to identify different aspects of OER business models and to establish how the success of the OER initiatives is measured. The results collected thus far show that two different business models for OER initiatives exist, but no data on their success or failure is published. We propose a framework for measuring success of OER initiatives.

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In Nigeria, schistosomiasis, caused predominantly by the species Schistosoma haematobium, is highly endemic in resource-poor communities. We performed a school-based survey in two rural communities in Osun State (Southwestern Nigeria) and assessed macrohaematuria, microhaematuria and proteinuria as indirect indicators for the presence of disease. Urine samples were inspected macroscopically for haematuria and screened for microhaematuria and proteinuria using urine reagent strips. The microscopic examination of schistosome eggs was used as the gold standard for diagnosis. In total, 447 schoolchildren were included in this study and had a 51% prevalence of urinary schistosomiasis. The sensitivity of microhaematuria (68%) and proteinuria (53%) for infection with S. haematobium was relatively low. In patients with a heavy infection (>500 eggs/10 mL), the sensitivity of microhaematuria was high (95%). When the presence of macrohaematuria and the concomitant presence of microhaematuria and proteinuria were combined, it revealed a sensitivity of 63%, a specificity of 93% and a positive predictive value of 91%. Macrohaematuria also showed high specificity (96%) and a positive predictive value of 92%, while sensitivity was < 50%. These data show that combining urine reagent strip tests (presence of proteinuria and microhaematuria) and information on macrohaematuria increased the accuracy of the rapid diagnosis of urinary schistosomiasis in an endemic rural West African setting. This simple approach can be used to increase the quality of monitoring of schistosomiasis in schoolchildren.

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Résumé françaisLa majorité des organismes vivants sont soumis à l'alternance du jour et de la nuit, conséquence de la rotation de la terre autour de son axe. Ils ont développé un système interne de mesure du temps, appelé horloge circadienne, leur permettant de s'adapter et de synchroniser leur comportement et leur physiologie aux cycles de lumière. Cette dernière est considérée comme étant le signal majeur entraînant l'horloge interne et. par conséquent, les rythmes journaliers d'éveil et de sommeil. Outre sa régulation circadienne, le sommeil est contrôlé par un processus homéostatique qui détermine son besoin. La contribution de ces deux processus dans le fonctionnement cellulaire du cerveau n'a pas encore été investiguée. La mesure de l'amplitude ainsi que de la prévalence des ondes delta de l'EEG (activité delta) constitue un index très fiable du besoin de sommeil. Il a été démontré que cette activité est génétiquement déterminée et associée à un locus de trait quantitatif situé sur le chromosome 13 de la souris.Grâce à des expériences de privation de sommeil et d'analyses de transcriptome du cerveau dans trois souches de souris présentant diverses réponses à la privation de sommeil, nous avons trouvé que Homerla, localisé dans la région d'intérêt du chromosome 13, est le meilleur marqueur du besoin de sommeil. Homerla est impliqué dans la récupération de l'hyperactivité neuronale induite par le glutamate, grâce à son effet tampon sur le calcium intracellulaire. Une fonction fondamentale du sommeil pourrait donc être de protéger le cerveau et de lui permettre de récupérer après une hyperactivité neuronale imposée par une veille prolongée.De plus, nous avons montré que 2032 transcrits sont exprimés rythmiqueraent dans le cerveau de la souris, parmi lesquels seulement 391 le restent après que les animaux aient été privés de sommeil à différents moments au cours des 24 heures. Cette observation montre clairement que la plupart des changements rythmiques au niveau du transcriptome dépendent du sommeil et non de l'horloge circadienne et souligne ainsi l'importance du sommeil dans la physiologie des mammifères.La plupart des expériences concernant les rythmes circadiens ont été réalisées sur des individus isolés en négligeant l'effet du contexte social sur les comportements circadiens. Les espèces sociales, telles que les fourmis, se caractérisent par une division du travail où une répartition des tâches s'effectue entre ses membres. De plus, certaines d'entre elles doivent être pratiquées en continu comme les soins au couvain tandis que d'autres requièrent une activité rythmique comme le fourragement. Ainsi la fourmi est un excellent modèle pour l'étude de 1 influence du contexte social sur les rythmes circadiens.A ces fins, nous avons décidé d'étudier les rythmes circadiens chez une espèce de fourmi Camponotus fellah et de caractériser au niveau moléculaire son horloge circadienne. Nous avons ainsi développé un système vidéo permettant de suivre l'activité locomotrice de tous les individus d'une colonie. Nos résultats montrent que, bien que la plupart des fourmis soient arythmiques à l'intérieur de la colonie, elles développent d'amples rythmes d'activité en isolation. De plus, ces rythmes disparaissent presque aussitôt que la fourmi est réintroduite dans la colonie. Cette rythmicité observée en isolation semble être générée par l'horloge circadienne car elle persiste en condition constante (obscurité totale). Nous avons ensuite regardé si cette apparente arythmie observée dans la colonie résultait d'un effet masquant des interactions sociales sur les rythmes circadiens d'activité. Nos résultats suggèrent que l'horloge interne est fonctionnelle dans la colonie mais que l'expression de ses rythmes au niveau comportemental est inhibée par les interactions sociales. Les analyses moléculaires du statut de l'horloge dans différents contextes sociaux sont actuellement en cours. Le contexte social semble donc un déterminant majeur du comportement circadien chez la fourmi.AbstractAlmost all living organisms on earth are subjected to the alternance of day and night re-sulting from the rotation of the earth around its axis. They have evolved with an internal timing system, termed the circadian clock, enabling them to adapt and synchronize their behavior and physiology to the daily changes in light and related environmental parame¬ters. Light is thought to be the major cue entraining the circadian clock and consequently the rhythms of rest/activity. In addition to its circadian dependent timing, sleep is reg¬ulated by a homeostatic process that determines its need. The contribution of these two processes in the cellular functioning of the brain has not yet been considered. A highly reliable index of the homeostatic process of sleep is the measure of the amplitude and prevalence of the EEG delta waves (delta activity). It has been shown that sleep need, measured by delta activity, is genetically determined and associated with a Quantitative Trait Locus (QTL) located on the mouse chromosome 13. By using sleep deprivation and brain transcriptome profiling in three inbred mouse strains showing different responses to sleep loss, we found that Homerla, localized within this QTL region is the best transcrip¬tional marker of sleep need. Interestingly Homerla is primarily involved in the recovery from glutamate-induced neuronal hyperactivity by its buffering effect on intracellular cal¬cium. A fundamental function of sleep may therefore reside in the protection and recovery of the brain from a neuronal hyperactivity imposed by prolonged wakefulness.Moreover, time course gene expression experiments showed that 2032 brain tran¬scripts present a rhythmic variation, but only 391 of those remain rhythmic when mice are sleep deprived at four time points around the clock. This finding clearly suggests that most changes in gene transcription over the day are sleep-wake dependent rather than clock dependent and underlines the importance of sleep in mammalian physiology.In the second part of this PhD, I was interested in the social influence on circadian behavior. Most experiments done in the circadian field have been performed on isolated individuals and have therefore ignored the effect of the social context on circadian behav-ior. Eusocial insect species such as ants are characterized by a division of labor: colony tasks are distributed among individuals, some of them requiring continuous activity such as nursing or rhythmic ones such as foraging. Thus ants represent a suitable model to study the influence of the social context on the circadian clock and its output rhythms.The aim of this part was to address the effect of social context on circadian rhythms in the ant species Camponotus fellah and to characterize its circadian clock at the molecu¬lar level. We therefore developed a video tracking system to follow the locomotor activity of all individuals in a colony. Our results show that most ants are arrhythmic within the colony, but develop, when subjected to social isolation, strong rhythms of activity that intriguingly disappear when individuals are reintroduced into the colony. The rhythmicity observed in isolated ants seems to be driven by the circadian clock as it persists under constant conditions (complete darkness). We then tested whether the apparent arrhyth- micity in the colony stemmed from a masking effect of social interactions on circadian rhythms. Indeed, we found that circadian clocks of ants in the colony are functional but their expression at the behavioral level is inhibited by social interactions. The molecular assessment of the circadian clock functional state in the different social context is still under investigation. Our results suggest that social context is a major determinant of circadian behavior in ants.

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This article examines the effect on price of different characteristics of holiday hotels in the sun-and-beach segment, under the hedonic function perspective. Monthly prices of the majority of hotels in the Spanish continental Mediterranean coast are gathered from May to October 1999 from the tour operator catalogues. Hedonic functions are specified as random-effect models and parametrized as structural equation models with two latent variables, a random peak season price and a random width of seasonal fluctuations. Characteristics of the hotel and the region where they are located are used as predictors of both latent variables. Besides hotel category, region, distance to the beach, availability of parking place and room equipment have an effect on peak price and also on seasonality. 3- star hotels have the highest seasonality and hotels located in the southern regions the lowest, which could be explained by a warmer climate in autumn

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The amalgamation operation is frequently used to reduce the number of parts of compositional data but it is a non-linear operation in the simplex with the usual geometry,the Aitchison geometry. The concept of balances between groups, a particular coordinate system designed over binary partitions of the parts, could be an alternative to theamalgamation in some cases. In this work we discuss the proper application of bothconcepts using a real data set corresponding to behavioral measures of pregnant sows

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Approximately 1% of the fetuses present some dilatation of their urinary tract in utero. More than 50% of these antenatally detected hydronephrosis will disappear spontaneously after birth. The other 50% comprises ureteropelvic junction obstruction, vesico-ureteral reflux and primary megaureters. Postnatal radiological evaluation (renal ultrasonography and VCUG) is performed in every infant with a significantly dilated renal pelvis (> 8 mm between 20 and 30 weeks or > 10 mm after 30 weeks in utero). Renal nuclear scan should be done in every child with significant/worsening post-natal hydronephrosis. Antibioprophylaxis will be started from birth to prevent urinary tract infection. Medical or surgical approach will be chosen in the light of the uroradiological exam results and the clinical progress.

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Background. Obesity is considered a major public health issue in most developed countries nowadays. This paper provides an overview of current population data available in Spain and the approach to develop preventive strategies in the country. Methods. Review of population data available is based on individually measured weight and height as well as determinants. On this basis, the approach used in the country to develop preventive strategies is discussed. Results. According to the DORICA study, the prevalence of obesity (BMI ≥30 kg m−2) is 15.5% in Spanish adults aged 25–60 years (13.2% in men and 17.5% in women). Obesity rates are higher among women aged 45 years and older, low social class, living in semi-urban places. Population estimates for the prevalence of obesity in Spanish children and young people based on the enKid study are 13.9% for the whole group. In this study, overweight and obesity is related to absence of breastfeeding, low consumption of fruit and vegetables, high consumption of cakes, buns, softdrinks and butchery products, low physical activity levels and a positive association with time spent watching TV. In 2005, the Spanish Ministry of Health jointly with the Spanish Agency for Food Safety and Nutrition launched the multifaceted NAOS strategy for nutrition, physical activity and the prevention of obesity. The important role of the family and the school setting as well as the responsibility of the Health Administration and Pediatric Care in the prevention of obesity is highlighted in the document. The need for environmental actions is recognised. The PERSEO programme, a multicomponent school-based intervention project is part of the strategy currently in place. Conclusion. Obesity is a public health issue in Spain. A national multifaceted strategy was launched to counteract the problem. Environmental and policy actions are a priority. Young children and their families are among the main target groups.

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The current drug options for the treatment of chronic Chagas disease have not been sufficient and high hopes have been placed on the use of genomic data from the human parasite Trypanosoma cruzi to identify new drug targets and develop appropriate treatments for both acute and chronic Chagas disease. However, the lack of a complete assembly of the genomic sequence and the presence of many predicted proteins with unknown or unsure functions has hampered our complete view of the parasite's metabolic pathways. Moreover, pinpointing new drug targets has proven to be more complex than anticipated and has revealed large holes in our understanding of metabolic pathways and their integrated regulation, not only for this parasite, but for many other similar pathogens. Using an in silicocomparative study on pathway annotation and searching for analogous and specific enzymes, we have been able to predict a considerable number of additional enzymatic functions in T. cruzi. Here we focus on the energetic pathways, such as glycolysis, the pentose phosphate shunt, the Krebs cycle and lipid metabolism. We point out many enzymes that are analogous to those of the human host, which could be potential new therapeutic targets.

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Most cases of emphysema are managed conservatively. However, in severe symptomatic emphysema associated with hyperinflation, lung volume reduction (LVR) may be proposed to improve dyspnea, exercice capacity, pulmonary functions, walk distance and to decrease long-term mortality. LVR may be achieved either surgically (LVRS) or endoscopically (EVLR by valves or coils) according to specific clinical criteria. Currently, the optimal approach is discussed in a multidisciplinary setting. The latter permits a personalized evaluation the patient's clinical status and allows the best possible therapeutic intervention to be proposed to the patient.

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Background The 'database search problem', that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. Conclusions The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions. The method's graphical environment, along with its computational and probabilistic architectures, represents a rich package that offers analysts and discussants with additional modes of interaction, concise representation, and coherent communication.

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We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

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The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

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This paper presents an automatic vision-based system for UUV station keeping. The vehicle is equipped with a down-looking camera, which provides images of the sea-floor. The station keeping system is based on a feature-based motion detection algorithm, which exploits standard correlation and explicit textural analysis to solve the correspondence problem. A visual map of the area surveyed by the vehicle is constructed to increase the flexibility of the system, allowing the vehicle to position itself when it has lost the reference image. The testing platform is the URIS underwater vehicle. Experimental results demonstrating the behavior of the system on a real environment are presented