28 resultados para court and administrative proceedings

em CentAUR: Central Archive University of Reading - UK


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Initial bacterial colonization, including colonization with health-positive bacteria, such as bifidobacteria and lactobacilli, is necessary for the normal development of intestinal innate and adaptive immune defenses. The predominance of beneficial bacteria in the gut microflora of breast-fed infants is thought to be, at least in part, supported by the metabolism of the complex mixture of oligosaccharides present in human breast milk, and a more adult-type intestinal microbiota is found in formula-fed infants. Inadequate gut colonization, dysbiosis, may lead to an increased risk of infectious, allergic, and autoimmune disorders later in life. The addition of appropriate amounts of selected prebiotics to infant formulas can enhance the growth of bifidobacteria or lactobacilli in the colonic microbiota and, thereby, might produce beneficial effects. Among the substrates considered as prebiotics are the oligosaccharides inulin, fructo-oligosaccharides, galacto-oligosaccharides, and lactulose. There are some reports that such prebiotics have beneficial effects on various markers of health. For example, primary prevention trials in infants have provided promising data on prevention of infections and atopic dermatitis. Additional well-designed prospective clinical trials and mechanistic studies are needed to advance knowledge further in this promising field. (J Pediatr 2009;155:S61-70).

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We analyze the interaction between university professors’ teaching quality and their research and administrative activities. Our sample is a high-quality individual panel data set from a medium size public Spanish university that allows us to avoid several types of biases frequently encountered in the literature. Although researchers teach roughly 20% more than non-researchers, their teaching quality is also 20% higher. Instructors with no research are 5 times more likely than the rest to be among the worst teachers. Over much of the relevant range, we find a nonlinear and positive relationship between research output and teaching quantity on teaching quality. Our conclusions may be useful for decision makers in universities and governments.

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Applications such as neuroscience, telecommunication, online social networking, transport and retail trading give rise to connectivity patterns that change over time. In this work, we address the resulting need for network models and computational algorithms that deal with dynamic links. We introduce a new class of evolving range-dependent random graphs that gives a tractable framework for modelling and simulation. We develop a spectral algorithm for calibrating a set of edge ranges from a sequence of network snapshots and give a proof of principle illustration on some neuroscience data. We also show how the model can be used computationally and analytically to investigate the scenario where an evolutionary process, such as an epidemic, takes place on an evolving network. This allows us to study the cumulative effect of two distinct types of dynamics.

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Exaggerated male traits that have evolved under sexual selection include ornaments to attract mates and weapons to deter rivals. Data from studies of many such traits in diverse kinds of organisms show that they almost universally exhibit positive allometries. Both ornaments and weapons increase disproportionately with overall body size, resulting in scaling exponents within species that are consistently > 1.0 and usually in the range 1.5-2.5. We show how scaling exponents reflect the relative fitness advantages of ornaments vs. somatic growth by using a simple mathematical model of resource allocation during ontogeny. Because the scaling exponents are similar for the different taxonomic groups, it follows that the fitness advantages of investing in ornaments also are similar. The model also shows how selection for ornaments influences body size at first reproduction and explains why interspecific allometries have consistently lower exponents than intraspecific ones.

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The use of nucleotide and amino acid sequences allows improved understanding of the timing of evolutionary events of life on earth. Molecular estimates of divergence times are, however, controversial and are generally much more ancient than suggested by the fossil record. The limited number of genes and species explored and pervasive variations in evolutionary rates are the most likely sources of such discrepancies. Here we compared concatenated amino acid sequences of 129 proteins from 36 eukaryotes to determine the divergence times of several major clades, including animals, fungi, plants, and various protists. Due to significant variations in their evolutionary rates, and to handle the uncertainty of the fossil record, we used a Bayesian relaxed molecular clock simultaneously calibrated by six paleontological constraints. We show that, according to 95% credibility intervals, the eukaryotic kingdoms diversified 950-1,259 million years ago (Mya), animals diverged from choanoflagellates 761-957 Mya, and the debated age of the split between protostomes and deuterostomes occurred 642-761 Mya. The divergence times appeared to be robust with respect to prior assumptions and paleontological calibrations. Interestingly, these relaxed clock time estimates are much more recent than those obtained under the assumption of a global molecular clock, yet bilaterian diversification appears to be approximate to100 million years more ancient than the Cambrian boundary.

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The Drosophila melanogaster genome has six physically clustered NK-related homeobox genes in just 180 kb. Here we show that the NK homeobox gene cluster was an ancient feature of bilaterian animal genomes, but has been secondarily split in chordate ancestry. The NK homeobox gene clusters of amphioxus and vertebrates are each split and dispersed at two equivalent intergenic positions. From the ancestral NK gene cluster, only the Tlx-Lbx and NK3-NK4 linkages have been retained in chordates. This evolutionary pattern is in marked contrast to the Hox and ParaHox gene clusters, which are compact in amphioxus and vertebrates, but have been disrupted in Drosophila.

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This article reviews current technological developments, particularly Peer-to-Peer technologies and Distributed Data Systems, and their value to community memory projects, particularly those concerned with the preservation of the cultural, literary and administrative data of cultures which have suffered genocide or are at risk of genocide. It draws attention to the comparatively good representation online of genocide denial groups and changes in the technological strategies of holocaust denial and other far-right groups. It draws on the author's work in providing IT support for a UK-based Non-Governmental Organization providing support for survivors of genocide in Rwanda.

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This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of size two for a lower hardware solution while maintaining similar input-output characteristic to the algorithm. The blocked solution, here referred to as B2P algorithm, is obtained using graph theory and retiming methods. Verification approaches were exercised to show that prediction performances obtained from the FPP and B2P algorithms differ within one mis-prediction per thousand instructions using a known framework for branch prediction evaluation. For a chosen FPGA device, circuits generated from the B2P algorithm showed average area savings of over 25% against circuits for the FPP algorithm with similar time performances thus making the proposed blocked predictor superior from a practical viewpoint.

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How can a bridge be built between autonomic computing approaches and parallel computing systems? How can autonomic computing approaches be extended towards building reliable systems? How can existing technologies be merged to provide a solution for self-managing systems? The work reported in this paper aims to answer these questions by proposing Swarm-Array Computing, a novel technique inspired from swarm robotics and built on the foundations of autonomic and parallel computing paradigms. Two approaches based on intelligent cores and intelligent agents are proposed to achieve autonomy in parallel computing systems. The feasibility of the proposed approaches is validated on a multi-agent simulator.