918 resultados para Julia set


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Background & Aims: HLA-B⁄27 is associated with spontaneous HCV genotype 1 clearance. HLA-B⁄27-restricted CD8+ T cells target three NS5B epitopes. Two of these epitopes are dominantly targeted in the majority of HLA-B⁄27+ patients. In chronic infection, viral escape occurs consistently in these two epitopes. The third epitope (NS5B2820) was dominantly targeted in an acutely infected patient. This was in contrast, however, to the lack of recognition and viral escape in the large majority of HLA-B⁄27+ patients. Here, we set out to determine the host factors contributing to selective targeting of this epitope. Methods: Four-digit HLA class I typing and viral sequence analyses were performed in 78 HLA-B⁄27+ patients with chronic HCV genotype 1 infection. CD8+ T cell analyses were performed in a subset of patients. In addition, HLA/peptide affinity was compared for HLA-B⁄27:02 and 05. Results: The NS5B2820 epitope is only restricted by the HLA-B⁄27 subtype HLA-B⁄27:02 (that is frequent in Mediterranean populations), but not by the prototype HLA-B⁄27 subtype B⁄27:05. Indeed, the epitope is very dominant in HLA-B⁄27:02+ patients and is associated with viral escape mutations at the anchor position for HLA-binding in 12 out of 13 HLA-B⁄27:02+ chronically infected patients. Conclusions: The NS5B2820 epitope is immunodominant in the context of HLA-B⁄27:02, but is not restricted by other HLA-B⁄27 subtypes. This finding suggests an important role of HLA subtypes in the restriction of HCV-specific CD8+ responses. With minor HLA subtypes covering up to 39% of specific populations, these findings may have important implications for the selection of epitopes for global vaccines.

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One of the current advances in functional biodiversity research is the move away from short-lived test systems towards the exploration of diversity-ecosystem functioning relationships in structurally more complex ecosystems. In forests, assumptions about the functional significance of tree species diversity have only recently produced a new generation of research on ecosystem processes and services. Novel experimental designs have now replaced traditional forestry trials, but these comparatively young experimental plots suffer from specific difficulties that are mainly related to the tree size and longevity. Tree species diversity experiments therefore need to be complemented with comparative observational studies in existing forests. Here we present the design and implementation of a new network of forest plots along tree species diversity gradients in six major European forest types: the FunDivEUROPE Exploratory Platform. Based on a review of the deficiencies of existing observational approaches and of unresolved research questions and hypotheses, we discuss the fundamental criteria that shaped the design of our platform. Key features include the extent of the species diversity gradient with mixtures up to five species, strict avoidance of a dilution gradient, special attention to community evenness and minimal covariation with other environmental factors. The new European research platform permits the most comprehensive assessment of tree species diversity effects on forest ecosystem functioning to date since it offers a common set of research plots to groups of researchers from very different disciplines and uses the same methodological approach in contrasting forest types along an extensive environmental gradient. (C) 2013 Elsevier GmbH. All rights reserved.

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Agri-environmental schemes involving organic farming or set-aside management aim at promoting biodiversity and restoring ecosystem functioning in agrarian landscapes. Application of pesticides in these crop fields is strongly regulated facilitating the spread of weeds but also allowing for the establishment of endangered herbs and a variety of animals.Recent studies found gastropods and earthworms to be legitimate dispersers of seeds of wild plants. We assumed that both groups also playa significant role in the spread and establishment of wild plants within crop fields. Therefore, we are conducting a series of experiments in three different study systems on (1) the role of earthworms and gastropods as dispersers of rare herbs and weeds in an organic rye field in Germany, (2) the seed feeding behavior of gastropods of plants sown in fallow ground in Switzerland, and (3) weed dispersal in irrigated rice fields by golden apple snails in the Philippines.

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The diversity and abundance of wild insect pollinators have declined in many agricultural landscapes. Whether such declines reduce crop yields, or are mitigated by managed pollinators such as honey bees, is unclear. We found universally positive associations of fruit set with flower visitation by wild insects in 41 crop systems worldwide. In contrast, fruit set increased significantly with flower visitation by honey bees in only 14% of the systems surveyed. Overall, wild insects pollinated crops more effectively; an increase in wild insect visitation enhanced fruit set by twice as much as an equivalent increase in honey bee visitation. Visitation by wild insects and honey bees promoted fruit set independently, so pollination by managed honey bees supplemented, rather than substituted for, pollination by wild insects. Our results suggest that new practices for integrated management of both honey bees and diverse wild insect assemblages will enhance global crop yields.

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As the understanding and representation of the impacts of volcanic eruptions on climate have improved in the last decades, uncertainties in the stratospheric aerosol forcing from large eruptions are now linked not only to visible optical depth estimates on a global scale but also to details on the size, latitude and altitude distributions of the stratospheric aerosols. Based on our understanding of these uncertainties, we propose a new model-based approach to generating a volcanic forcing for general circulation model (GCM) and chemistry–climate model (CCM) simulations. This new volcanic forcing, covering the 1600–present period, uses an aerosol microphysical model to provide a realistic, physically consistent treatment of the stratospheric sulfate aerosols. Twenty-six eruptions were modeled individually using the latest available ice cores aerosol mass estimates and historical data on the latitude and date of eruptions. The evolution of aerosol spatial and size distribution after the sulfur dioxide discharge are hence characterized for each volcanic eruption. Large variations are seen in hemispheric partitioning and size distributions in relation to location/date of eruptions and injected SO2 masses. Results for recent eruptions show reasonable agreement with observations. By providing these new estimates of spatial distributions of shortwave and long-wave radiative perturbations, this volcanic forcing may help to better constrain the climate model responses to volcanic eruptions in the 1600–present period. The final data set consists of 3-D values (with constant longitude) of spectrally resolved extinction coefficients, single scattering albedos and asymmetry factors calculated for different wavelength bands upon request. Surface area densities for heterogeneous chemistry are also provided.

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In recent years, the econometrics literature has shown a growing interest in the study of partially identified models, in which the object of economic and statistical interest is a set rather than a point. The characterization of this set and the development of consistent estimators and inference procedures for it with desirable properties are the main goals of partial identification analysis. This review introduces the fundamental tools of the theory of random sets, which brings together elements of topology, convex geometry, and probability theory to develop a coherent mathematical framework to analyze random elements whose realizations are sets. It then elucidates how these tools have been fruitfully applied in econometrics to reach the goals of partial identification analysis.

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This article refines Lipsky’s (1980) assertion that lacking resources negatively affect output performance. It uses fuzzy-set Qualitative Comparative Analysis to analyse the nuanced interplay of contextual and individual determinants of the output performance of veterinary inspectors as street-level bureaucrats in Switzerland. Moving ‘beyond Lipsky’, the study builds on recent theoretical contributions and a systematic comparison across organizational contexts. Against a widespread assumption, output performance is not all about the resources. The impact of perceived available resources hinges on caseloads, which prove to be more decisive. These contextual factors interact with individual attitudes emerging from diverse public accountabilities. The results contextualize the often-emphasized importance of worker-client interaction. In a setting where clients cannot escape the interaction, street-level bureaucrats are not primarily held accountable by them. Studies of output performance should thus sensibly consider gaps between what is being demanded of and offered to street-level bureaucrats, and the latter’s multiple embeddedness.

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The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly exhibit a disastrous influence on the online reputation of organizations. Based on social Web data, this study describes the building of an ontology based on fuzzy sets. At the end of a recurring harvesting of folksonomies by Web agents, the aggregated tags are purified, linked, and transformed to a so-called fuzzy grassroots ontology by means of a fuzzy clustering algorithm. This self-updating ontology is used for online reputation analysis, a crucial task of reputation management, with the goal to follow the online conversation going on around an organization to discover and monitor its reputation. In addition, an application of the Fuzzy Online Reputation Analysis (FORA) framework, lesson learned, and potential extensions are discussed in this article.

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Many techniques based on data which are drawn by Ranked Set Sampling (RSS) scheme assume that the ranking of observations is perfect. Therefore it is essential to develop some methods for testing this assumption. In this article, we propose a parametric location-scale free test for assessing the assumption of perfect ranking. The results of a simulation study in two special cases of normal and exponential distributions indicate that the proposed test performs well in comparison with its leading competitors.

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The family of RTX (RTX representing repeats in the structural toxin) toxins is composed of several protein toxins with a characteristic nonapeptide glycine-rich repeat motif. Most of its members were shown to have cytolytic activity. By comparing the genetic relationships of the RTX toxin genes we established a set of 10 gene probes to be used for screening as-yet-unknown RTX toxin genes in bacterial species. The probes include parts of apxIA, apxIIA, and apxIIIA from Actinobacillus pleuropneumoniae, cyaA from Bordetella pertusis, frpA from Neisseria meningitidis, prtC from Erwinia chrysanthemi, hlyA and elyA from Escherichia coli, aaltA from Actinobacillus actinomycetemcomitans and lktA from Pasteurella haemolytica. A panel of pathogenic and nonpathogenic gram-negative bacteria were investigated for the presence of RTX toxin genes. The probes detected all known genes for RTX toxins. Moreover, we found potential RTX toxin genes in several pathogenic bacterial species for which no such toxins are known yet. This indicates that RTX or RTX-like toxins are widely distributed among pathogenic gram-negative bacteria. The probes generated by PCR and the hybridization method were optimized to allow broad-range screening for RTX toxin genes in one step. This included the binding of unlabelled probes to a nylon filter and subsequent hybridization of the filter with labelled genomic DNA of the strain to be tested. The method constitutes a powerful tool for the assessment of the potential pathogenicity of poorly characterized strains intended to be used in biotechnological applications. Moreover, it is useful for the detection of already-known or new RTX toxin genes in bacteria of medical importance.

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Stepwise uncertainty reduction (SUR) strategies aim at constructing a sequence of points for evaluating a function  f in such a way that the residual uncertainty about a quantity of interest progressively decreases to zero. Using such strategies in the framework of Gaussian process modeling has been shown to be efficient for estimating the volume of excursion of f above a fixed threshold. However, SUR strategies remain cumbersome to use in practice because of their high computational complexity, and the fact that they deliver a single point at each iteration. In this article we introduce several multipoint sampling criteria, allowing the selection of batches of points at which f can be evaluated in parallel. Such criteria are of particular interest when f is costly to evaluate and several CPUs are simultaneously available. We also manage to drastically reduce the computational cost of these strategies through the use of closed form formulas. We illustrate their performances in various numerical experiments, including a nuclear safety test case. Basic notions about kriging, auxiliary problems, complexity calculations, R code, and data are available online as supplementary materials.