836 resultados para Data fusion applications


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The results presented in this paper clearly indicate that precocene and azadirachtin are effective inhibitors of moulting and reproduction in the hemipteran Rhodnius prolixus. The time of application is important and only applications of these substances early in the intermoulting period cause their effects in nymphs. The inhibition of moulting is fully reversed by ecdysone therapy. Precocene and azadirachtin also affected drastically the oogenesis and egg deposition in this insect. Precocene-induced sterilization is reversed by application of juvenile hormone III. However, this hormone is unable to reverse the effect of azadirachtin on reproduction. Ecdysteroid titers in nymphs and adult females are decreased by these treatments. In vitro analysis suggest that precocene and azadirachtin may act directly on the prothoracic glands and ovaries producing ecdysteroids. Based on these and other findings the possible mode of action of these compounds on the development and reproduction of Rhodnius prolixus is discussed.

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1. Model-based approaches have been used increasingly in conservation biology over recent years. Species presence data used for predictive species distribution modelling are abundant in natural history collections, whereas reliable absence data are sparse, most notably for vagrant species such as butterflies and snakes. As predictive methods such as generalized linear models (GLM) require absence data, various strategies have been proposed to select pseudo-absence data. However, only a few studies exist that compare different approaches to generating these pseudo-absence data. 2. Natural history collection data are usually available for long periods of time (decades or even centuries), thus allowing historical considerations. However, this historical dimension has rarely been assessed in studies of species distribution, although there is great potential for understanding current patterns, i.e. the past is the key to the present. 3. We used GLM to model the distributions of three 'target' butterfly species, Melitaea didyma, Coenonympha tullia and Maculinea teleius, in Switzerland. We developed and compared four strategies for defining pools of pseudo-absence data and applied them to natural history collection data from the last 10, 30 and 100 years. Pools included: (i) sites without target species records; (ii) sites where butterfly species other than the target species were present; (iii) sites without butterfly species but with habitat characteristics similar to those required by the target species; and (iv) a combination of the second and third strategies. Models were evaluated and compared by the total deviance explained, the maximized Kappa and the area under the curve (AUC). 4. Among the four strategies, model performance was best for strategy 3. Contrary to expectations, strategy 2 resulted in even lower model performance compared with models with pseudo-absence data simulated totally at random (strategy 1). 5. Independent of the strategy model, performance was enhanced when sites with historical species presence data were not considered as pseudo-absence data. Therefore, the combination of strategy 3 with species records from the last 100 years achieved the highest model performance. 6. Synthesis and applications. The protection of suitable habitat for species survival or reintroduction in rapidly changing landscapes is a high priority among conservationists. Model-based approaches offer planning authorities the possibility of delimiting priority areas for species detection or habitat protection. The performance of these models can be enhanced by fitting them with pseudo-absence data relying on large archives of natural history collection species presence data rather than using randomly sampled pseudo-absence data.

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In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

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As computer chips implementation technologies evolve to obtain more performance, those computer chips are using smaller components, with bigger density of transistors and working with lower power voltages. All these factors turn the computer chips less robust and increase the probability of a transient fault. Transient faults may occur once and never more happen the same way in a computer system lifetime. There are distinct consequences when a transient fault occurs: the operating system might abort the execution if the change produced by the fault is detected by bad behavior of the application, but the biggest risk is that the fault produces an undetected data corruption that modifies the application final result without warnings (for example a bit flip in some crucial data). With the objective of researching transient faults in computer system’s processor registers and memory we have developed an extension of HP’s and AMD joint full system simulation environment, named COTSon. This extension allows the injection of faults that change a single bit in processor registers and memory of the simulated computer. The developed fault injection system makes it possible to: evaluate the effects of single bit flip transient faults in an application, analyze an application robustness against single bit flip transient faults and validate fault detection mechanism and strategies.

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The specific interactions of the pairs laminin binding protein (LBP)-purified tick-borne encephalitis viral surface protein E and certain recombinant fragments of this protein, as well as West Nile viral surface protein E and certain recombinant fragments of that protein, are studied by combined methods of single-molecule dynamic force spectroscopy (SMDFS), enzyme immunoassay and optical surface waves-based biosensor measurements. The experiments were performed at neutral pH (7.4) and acid pH (5.3) conditions. The data obtained confirm the role of LBP as a cell receptor for two typical viral species of the Flavivirus genus. A comparison of these data with similar data obtained for another cell receptor of this family, namely human αVβ3 integrin, reveals that both these receptors are very important. Studying the specific interaction between the cell receptors in question and specially prepared monoclonal antibodies against them, we could show that both interaction sites involved in the process of virus-cell interaction remain intact at pH 5.3. At the same time, for these acid conditions characteristic for an endosome during flavivirus-cell membrane fusion, SMDFS data reveal the existence of a force-induced (effective already for forces as small as 30-70 pN) sharp globule-coil transition for LBP and LBP-fragments of protein E complexes. We argue that this conformational transformation, being an analog of abrupt first-order phase transition and having similarity with the famous Rayleigh hydrodynamic instability, might be indispensable for the flavivirus-cell membrane fusion process. Copyright © 2014 John Wiley & Sons, Ltd.

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Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics.

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So-called online Voting Advice Applications (VAAs) have become very popular all over Europe. Millions of voters are using them as an assistance to make up their minds for which party they should vote. Despite this popularity there are only very few studies about the impact of these tools on individual electoral choice. On the basis of the Swiss VAA smartvote we present some first findings about the question whether VAAs do have a direct impact on the actual vote of their users. In deed, we find strong evidence that Swiss voters were affected by smartvote. However, our findings are somewhat contrary to the results of previous studies from other countries. Furthermore, the quality of available data for such studies needs to be improved. Future studies should pay attention to both: the improvement of the available data, as well as the explanation of the large variance of findings between the specific European countries.

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The recent advances in sequencing technologies have given all microbiology laboratories access to whole genome sequencing. Providing that tools for the automated analysis of sequence data and databases for associated meta-data are developed, whole genome sequencing will become a routine tool for large clinical microbiology laboratories. Indeed, the continuing reduction in sequencing costs and the shortening of the 'time to result' makes it an attractive strategy in both research and diagnostics. Here, we review how high-throughput sequencing is revolutionizing clinical microbiology and the promise that it still holds. We discuss major applications, which include: (i) identification of target DNA sequences and antigens to rapidly develop diagnostic tools; (ii) precise strain identification for epidemiological typing and pathogen monitoring during outbreaks; and (iii) investigation of strain properties, such as the presence of antibiotic resistance or virulence factors. In addition, recent developments in comparative metagenomics and single-cell sequencing offer the prospect of a better understanding of complex microbial communities at the global and individual levels, providing a new perspective for understanding host-pathogen interactions. Being a high-resolution tool, high-throughput sequencing will increasingly influence diagnostics, epidemiology, risk management, and patient care.

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Résumé: L'évaluation de l'exposition aux nuisances professionnelles représente une étape importante dans l'analyse de poste de travail. Les mesures directes sont rarement utilisées sur les lieux même du travail et l'exposition est souvent estimée sur base de jugements d'experts. Il y a donc un besoin important de développer des outils simples et transparents, qui puissent aider les spécialistes en hygiène industrielle dans leur prise de décision quant aux niveaux d'exposition. L'objectif de cette recherche est de développer et d'améliorer les outils de modélisation destinés à prévoir l'exposition. Dans un premier temps, une enquête a été entreprise en Suisse parmi les hygiénistes du travail afin d'identifier les besoins (types des résultats, de modèles et de paramètres observables potentiels). Il a été constaté que les modèles d'exposition ne sont guère employés dans la pratique en Suisse, l'exposition étant principalement estimée sur la base de l'expérience de l'expert. De plus, l'émissions de polluants ainsi que leur dispersion autour de la source ont été considérés comme des paramètres fondamentaux. Pour tester la flexibilité et la précision des modèles d'exposition classiques, des expériences de modélisations ont été effectuées dans des situations concrètes. En particulier, des modèles prédictifs ont été utilisés pour évaluer l'exposition professionnelle au monoxyde de carbone et la comparer aux niveaux d'exposition répertoriés dans la littérature pour des situations similaires. De même, l'exposition aux sprays imperméabilisants a été appréciée dans le contexte d'une étude épidémiologique sur une cohorte suisse. Dans ce cas, certains expériences ont été entreprises pour caractériser le taux de d'émission des sprays imperméabilisants. Ensuite un modèle classique à deux-zone a été employé pour évaluer la dispersion d'aérosol dans le champ proche et lointain pendant l'activité de sprayage. D'autres expériences ont également été effectuées pour acquérir une meilleure compréhension des processus d'émission et de dispersion d'un traceur, en se concentrant sur la caractérisation de l'exposition du champ proche. Un design expérimental a été développé pour effectuer des mesures simultanées dans plusieurs points d'une cabine d'exposition, par des instruments à lecture directe. Il a été constaté que d'un point de vue statistique, la théorie basée sur les compartiments est sensée, bien que l'attribution à un compartiment donné ne pourrait pas se faire sur la base des simples considérations géométriques. Dans une étape suivante, des données expérimentales ont été collectées sur la base des observations faites dans environ 100 lieux de travail différents: des informations sur les déterminants observés ont été associées aux mesures d'exposition des informations sur les déterminants observés ont été associé. Ces différentes données ont été employées pour améliorer le modèle d'exposition à deux zones. Un outil a donc été développé pour inclure des déterminants spécifiques dans le choix du compartiment, renforçant ainsi la fiabilité des prévisions. Toutes ces investigations ont servi à améliorer notre compréhension des outils des modélisations ainsi que leurs limitations. L'intégration de déterminants mieux adaptés aux besoins des experts devrait les inciter à employer cet outil dans leur pratique. D'ailleurs, en augmentant la qualité des outils des modélisations, cette recherche permettra non seulement d'encourager leur utilisation systématique, mais elle pourra également améliorer l'évaluation de l'exposition basée sur les jugements d'experts et, par conséquent, la protection de la santé des travailleurs. Abstract Occupational exposure assessment is an important stage in the management of chemical exposures. Few direct measurements are carried out in workplaces, and exposures are often estimated based on expert judgements. There is therefore a major requirement for simple transparent tools to help occupational health specialists to define exposure levels. The aim of the present research is to develop and improve modelling tools in order to predict exposure levels. In a first step a survey was made among professionals to define their expectations about modelling tools (what types of results, models and potential observable parameters). It was found that models are rarely used in Switzerland and that exposures are mainly estimated from past experiences of the expert. Moreover chemical emissions and their dispersion near the source have also been considered as key parameters. Experimental and modelling studies were also performed in some specific cases in order to test the flexibility and drawbacks of existing tools. In particular, models were applied to assess professional exposure to CO for different situations and compared with the exposure levels found in the literature for similar situations. Further, exposure to waterproofing sprays was studied as part of an epidemiological study on a Swiss cohort. In this case, some laboratory investigation have been undertaken to characterize the waterproofing overspray emission rate. A classical two-zone model was used to assess the aerosol dispersion in the near and far field during spraying. Experiments were also carried out to better understand the processes of emission and dispersion for tracer compounds, focusing on the characterization of near field exposure. An experimental set-up has been developed to perform simultaneous measurements through direct reading instruments in several points. It was mainly found that from a statistical point of view, the compartmental theory makes sense but the attribution to a given compartment could ñó~be done by simple geometric consideration. In a further step the experimental data were completed by observations made in about 100 different workplaces, including exposure measurements and observation of predefined determinants. The various data obtained have been used to improve an existing twocompartment exposure model. A tool was developed to include specific determinants in the choice of the compartment, thus largely improving the reliability of the predictions. All these investigations helped improving our understanding of modelling tools and identify their limitations. The integration of more accessible determinants, which are in accordance with experts needs, may indeed enhance model application for field practice. Moreover, while increasing the quality of modelling tool, this research will not only encourage their systematic use, but might also improve the conditions in which the expert judgments take place, and therefore the workers `health protection.

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Zero correlation between measurement error and model error has been assumed in existing panel data models dealing specifically with measurement error. We extend this literature and propose a simple model where one regressor is mismeasured, allowing the measurement error to correlate with model error. Zero correlation between measurement error and model error is a special case in our model where correlated measurement error equals zero. We ask two research questions. First, we wonder if the correlated measurement error can be identified in the context of panel data. Second, we wonder if classical instrumental variables in panel data need to be adjusted when correlation between measurement error and model error cannot be ignored. Under some regularity conditions the answer is yes to both questions. We then propose a two-step estimation corresponding to the two questions. The first step estimates correlated measurement error from a reverse regression; and the second step estimates usual coefficients of interest using adjusted instruments.

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The application of two approaches for high-throughput, high-resolution X-ray phase contrast tomographic imaging being used at the tomographic microscopy and coherent radiology experiments (TOMCAT) beamline of the SLS is discussed and illustrated. Differential phase contrast (DPC) imaging, using a grating interferometer and a phase-stepping technique, is integrated into the beamline environment at TOMCAT in terms of the fast acquisition and reconstruction of data and the availability to scan samples within an aqueous environment. A second phase contrast method is a modified transfer of intensity approach that can yield the 3D distribution of the decrement of the refractive index of a weakly absorbing object from a single tomographic dataset. The two methods are complementary to one another: the DPC method is characterised by a higher sensitivity and by moderate resolution with larger samples; the modified transfer of intensity approach is particularly suited for small specimens when high resolution (around 1 mu m) is required. Both are being applied to investigations in the biological and materials science fields.

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Animal toxins are of interest to a wide range of scientists, due to their numerous applications in pharmacology, neurology, hematology, medicine, and drug research. This, and to a lesser extent the development of new performing tools in transcriptomics and proteomics, has led to an increase in toxin discovery. In this context, providing publicly available data on animal toxins has become essential. The UniProtKB/Swiss-Prot Tox-Prot program (http://www.uniprot.org/program/Toxins) plays a crucial role by providing such an access to venom protein sequences and functions from all venomous species. This program has up to now curated more than 5000 venom proteins to the high-quality standards of UniProtKB/Swiss-Prot (release 2012_02). Proteins targeted by these toxins are also available in the knowledgebase. This paper describes in details the type of information provided by UniProtKB/Swiss-Prot for toxins, as well as the structured format of the knowledgebase.

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The tumor necrosis factor (TNF)/TNF receptor (TNFR) families of ligands and receptors are implicated in a variety of physiological and pathological processes and regulate cellular functions as diverse as proliferation, differentiation, and death. Recombinant forms of these ligands and receptors can act to agonize or antagonize these functions and are therefore useful for laboratory studies and may have clinical applications. A protocol is presented for the expression and purification of dimeric soluble receptors fused to the Fc portion of human IgG1 and of soluble, N-terminally Flag-tagged ligands. Soluble recombinant proteins are easier to handle than membrane-bound proteins and the use of tags greatly facilitates their detection and purification. In addition, some tags may provide enhanced biological activity to the recombinant proteins (mainly by oligomerization and stabilization effects) and facilitate their functional characterization. Expression in bacterial (for selected ligands) and eukaryotic expression systems (for ligands and receptors) was performed using M15 pREP4 bacteria and human embryonic kidney 293 cells, respectively. The yield of purified protein is about 1 mg/liter for the mammalian expression system and several milligrams per liter for the bacterial expression system. Protocols are given for a specific ligand-receptor pair, namely TRAIL (Apo-2L) and TRAIL receptor 2 (DR5), but can be applied to other ligands and receptors of the TNF family.

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Compositional data naturally arises from the scientific analysis of the chemicalcomposition of archaeological material such as ceramic and glass artefacts. Data of thistype can be explored using a variety of techniques, from standard multivariate methodssuch as principal components analysis and cluster analysis, to methods based upon theuse of log-ratios. The general aim is to identify groups of chemically similar artefactsthat could potentially be used to answer questions of provenance.This paper will demonstrate work in progress on the development of a documentedlibrary of methods, implemented using the statistical package R, for the analysis ofcompositional data. R is an open source package that makes available very powerfulstatistical facilities at no cost. We aim to show how, with the aid of statistical softwaresuch as R, traditional exploratory multivariate analysis can easily be used alongside, orin combination with, specialist techniques of compositional data analysis.The library has been developed from a core of basic R functionality, together withpurpose-written routines arising from our own research (for example that reported atCoDaWork'03). In addition, we have included other appropriate publicly availabletechniques and libraries that have been implemented in R by other authors. Availablefunctions range from standard multivariate techniques through to various approaches tolog-ratio analysis and zero replacement. We also discuss and demonstrate a smallselection of relatively new techniques that have hitherto been little-used inarchaeometric applications involving compositional data. The application of the libraryto the analysis of data arising in archaeometry will be demonstrated; results fromdifferent analyses will be compared; and the utility of the various methods discussed