953 resultados para CERN LHC ATLAS LabVIEW CAN-Bus Crate W-Ie-Ne-R


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Lifetime reproductive success in female insects is often egg- or time-limited. For instance in pro-ovigenic species, when oviposition sites are abundant, females may quickly become devoid of eggs. Conversely, in the absence of suitable oviposition sites, females may die before laying all of their eggs. In pollinating fig wasps (Hymenoptera: Agaonidae), each species has an obligate mutualism with its host fig tree species [Ficus spp. (Moraceae)]. These pro-ovigenic wasps oviposit in individual ovaries within the inflorescences of monoecious Ficus (syconia, or ‘figs’), which contain many flowers. Each female flower can thus become a seed or be converted into a wasp gall. The mystery is that the wasps never oviposit in all fig ovaries, even when a fig contains enough wasp females with enough eggs to do so. The failure of all wasps to translate all of their eggs into offspring clearly contributes to mutualism persistence, but the underlying causal mechanisms are unclear. We found in an undescribed Brazilian Pegoscapus wasp population that the lifetime reproductive success of lone foundresses was relatively unaffected by constraints on oviposition. The number of offspring produced by lone foundresses experimentally introduced into receptive figs was generally lower than the numbers of eggs carried, despite the fact that the wasps were able to lay all or most of their eggs. Because we excluded any effects of intraspecific competitors and parasitic non-pollinating wasps, our data suggest that some pollinators produce few offspring because some of their eggs or larvae are unviable or are victims of plant defences.

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Progressive telomere shortening from cell division (replicative aging) provides a barrier for human tumor progression. This program is not conserved in laboratory mice, which have longer telomeres and constitutive telomerase. Wild species that do ⁄ do not use replicative aging have been reported, but the evolution of different phenotypes and a conceptual framework for understanding their uses of telomeres is lacking. We examined telomeres ⁄ telomerase in cultured cells from > 60 mammalian species to place different uses of telomeres in a broad mammalian context. Phylogeny-based statistical analysis reconstructed ancestral states. Our analysis suggested that the ancestral mammalian phenotype included short telomeres (< 20 kb, as we now see in humans) and repressed telomerase. We argue that the repressed telomerase was a response to a higher mutation load brought on by the evolution of homeothermy. With telomerase repressed, we then see the evolution of replicative aging. Telomere length inversely correlated with lifespan, while telomerase expression co-evolved with body size. Multiple independent times smaller, shorter-lived species changed to having longer telomeres and expressing telomerase. Trade-offs involving reducing the energetic ⁄ cellular costs of specific oxidative protection mechanisms (needed to protect < 20 kb telomeres in the absence oftelomerase) could explain this abandonment of replicative aging. These observations provide a conceptual framework for understanding different uses of telomeres in mammals, support a role for human-like telomeres in allowing longer lifespans to evolve, demonstrate the need to include telomere length in the analysis of comparative studies of oxidative protection in the biology of aging, and identify which mammals can be used as appropriate model organisms for the study of the role of telomeres in human cancer and aging. Key words: evolution of telomeres; immortalization; telomerase; replicative aging; senescence.

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The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform data mining and other analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data that is used to populate the second component, and a data warehouse that contains important molecular properties. These properties may be used for data mining studies. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular, we look at two aspects: firstly, how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories — this is an important and challenging aspect of P-found, due to the large data volumes involved and the desire of scientists to maintain control of their own data. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling scientific discovery.

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We introduce a new methodology that allows the construction of wave frequency distributions due to growing incoherent whistler-mode waves in the magnetosphere. The technique combines the equations of geometric optics (i.e. raytracing) with the equation of transfer of radiation in an anisotropic lossy medium to obtain spectral energy density as a function of frequency and wavenormal angle. We describe the method in detail, and then demonstrate how it could be used in an idealised magnetosphere during quiet geomagnetic conditions. For a specific set of plasma conditions, we predict that the wave power peaks off the equator at ~15 degrees magnetic latitude. The new calculations predict that wave power as a function of frequency can be adequately described using a Gaussian function, but as a function of wavenormal angle, it more closely resembles a skew normal distribution. The technique described in this paper is the first known estimate of the parallel and oblique incoherent wave spectrum as a result of growing whistler-mode waves, and provides a means to incorporate self-consistent wave-particle interactions in a kinetic model of the magnetosphere over a large volume.

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To investigate the effects of the middle atmosphere on climate, the World Climate Research Programme is supporting the project "Stratospheric Processes and their Role in Climate" (SPARC). A central theme of SPARC, to examine model simulations of the coupled troposphere—middle atmosphere system, is being performed through the initiative called GRIPS (GCM—Reality Intercomparison Project for SPARC). In this paper, an overview of the objectives of GRIPS is given. Initial activities include an assessment of the performance of middle atmosphere climate models, and preliminary results from this evaluation are presented here. It is shown that although all 13 models evaluated represent most major features of the mean atmospheric state, there are deficiencies in the magnitude and location of the features, which cannot easily be traced to the formulation (resolution or the parameterizations included) of the models. Most models show a cold bias in all locations, apart from the tropical tropopause region where they can be either too warm or too cold. The strengths and locations of the major jets are often misrepresented in the models. Looking at three—dimensional fields reveals, for some models, more severe deficiencies in the magnitude and positioning of the dominant structures (such as the Aleutian high in the stratosphere), although undersampling might explain some of these differences from observations. All the models have shortcomings in their simulations of the present—day climate, which might limit the accuracy of predictions of the climate response to ozone change and other anomalous forcing.

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Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1, 3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

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The scientific community is developing new global, regional, and sectoral scenarios to facilitate interdisciplinary research and assessment to explore the range of possible future climates and related physical changes that could pose risks to human and natural systems; how these changes could interact with social, economic, and environmental development pathways; the degree to which mitigation and adaptation policies can avoid and reduce risks; the costs and benefits of various policy mixes; residual impacts under alternative pathways; and the relationship of future climate change and adaptation and mitigation policy responses with sustainable development. This paper provides the background to and process of developing the conceptual framework for these scenarios, as described in the three subsequent papers in this Special Issue (Van Vuuren et al.; O’Neill et al.; Kriegler et al.). The paper also discusses research needs to further develop and apply this framework. A key goal of the current framework design and its future development is to facilitate the collaboration of climate change researchers from a broad range of perspectives and disciplines to develop policy- and decision-relevant scenarios and explore the challenges and opportunities human and natural systems could face with additional climate change.

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Trypsin and mast cell tryptase can signal to epithelial cells, myocytes, and nerve fibers of the respiratory tract by cleaving proteinase-activated receptor 2 (PAR2). Since tryptase inhibitors are under development to treat asthma, a precise understanding of the contribution of PAR2 to airway inflammation is required. We examined the role of PAR2 in allergic inflammation of the airway by comparing OVA-sensitized and -challenged mice lacking or overexpressing PAR2. In wild-type mice, immunoreactive PAR2 was detected in airway epithelial cells and myocytes, and intranasal administration of a PAR2 agonist stimulated macrophage infiltration into bronchoalveolar lavage fluid. OVA challenge of immunized wild-type mice stimulated infiltration of leukocytes into bronchoalveolar lavage and induced airway hyperreactivity to inhaled methacholine. Compared with wild-type animals, eosinophil infiltration was inhibited by 73% in mice lacking PAR2 and increased by 88% in mice overexpressing PAR2. Similarly, compared with wild-type animals, airway hyperreactivity to inhaled methacholine (40 micro g/ml) was diminished 38% in mice lacking PAR2 and increased by 52% in mice overexpressing PAR2. PAR2 deletion also reduced IgE levels to OVA sensitization by 4-fold compared with those of wild-type animals. Thus, PAR2 contributes to the development of immunity and to allergic inflammation of the airway. Our results support the proposal that tryptase inhibitors and PAR2 antagonists may be useful therapies for inflammatory airway disease.

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Early establishment of endophytes can play a role in pathogen suppression and improve seedling development. One route for establishment of endophytes in seedlings is transmission of bacteria from the parent plant to the seedling via the seed. In wheat seeds, it is not clear whether this transmission route exists, and the identities and location of bacteria within wheat seeds are unknown. We identified bacteria in the wheat (Triticum aestivum) cv. Hereward seed environment using embryo excision to determine the location of the bacterial load. Axenic wheat seedlings obtained with this method were subsequently used to screen a putative endophyte bacterial isolate library for endophytic competency. This absence of bacteria recovered from seeds indicated low bacterial abundance and/or the presence of inhibitors. Diversity of readily culturable bacteria in seeds was low with 8 genera identified, dominated by Erwinia and Paenibacillus. We propose that anatomical restrictions in wheat limit embryo associated vertical transmission, and that bacterial load is carried in the seed coat, crease tissue and endosperm. This finding facilitates the creation of axenic wheat plants to test competency of putative endophytes and also provides a platform for endophyte competition, plant growth, and gene expression studies without an indigenous bacterial background.

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The determination of accurate chemical abundances of planetary nebulae (PN) in different galaxies allows us to obtain important constraints on chemical evolution models for these systems. We have a long-term program to derive abundances in the galaxies of the Local Group, particularly the Large and Small Magellanic Clouds. In this work, we present our new results on these objects and discuss their implications in view of recent abundance determinations in the literature. In particular, we obtain distance-independent correlations involving He, N, O, Ne, S, and Ar, and compare the results with data from our own Galaxy and other galaxies in the Local Group. As a result of our observational program, we have a large database of PN in the Galaxy and the Magellanic Clouds, so that we can obtain reliable constraints on the nucleosynthesis processes in the progenitor stars in galaxies of different metallicities.

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The advent of the Auger Engineering Radio Array (AERA) necessitates the development of a powerful framework for the analysis of radio measurements of cosmic ray air showers. As AERA performs ""radio-hybrid"" measurements of air shower radio emission in coincidence with the surface particle detectors and fluorescence telescopes of the Pierre Auger Observatory, the radio analysis functionality had to be incorporated in the existing hybrid analysis solutions for fluorescence and surface detector data. This goal has been achieved in a natural way by extending the existing Auger Offline software framework with radio functionality. In this article, we lay out the design, highlights and features of the radio extension implemented in the Auger Offline framework. Its functionality has achieved a high degree of sophistication and offers advanced features such as vectorial reconstruction of the electric field, advanced signal processing algorithms, a transparent and efficient handling of FFTs, a very detailed simulation of detector effects, and the read-in of multiple data formats including data from various radio simulation codes. The source code of this radio functionality can be made available to interested parties on request. (C) 2011 Elsevier B.V. All rights reserved.

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The surface detector array of the Pierre Auger Observatory consists of 1600 water-Cherenkov detectors, for the study of extensive air showers (EAS) generated by ultra-high-energy cosmic rays. We describe the trigger hierarchy, from the identification of candidate showers at the level of a single detector, amongst a large background (mainly random single cosmic ray muons), up to the selection of real events and the rejection of random coincidences. Such trigger makes the surface detector array fully efficient for the detection of EAS with energy above 3 x 10(18) eV, for all zenith angles between 0 degrees and 60 degrees, independently of the position of the impact point and of the mass of the primary particle. In these range of energies and angles, the exposure of the surface array can be determined purely on the basis of the geometrical acceptance. (C) 2009 Elsevier B.V. All rights reserved.

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Since data-taking began in January 2004, the Pierre Auger Observatory has been recording the count rates of low energy secondary cosmic ray particles for the self-calibration of the ground detectors of its surface detector array. After correcting for atmospheric effects, modulations of galactic cosmic rays due to solar activity and transient events are observed. Temporal variations related with the activity of the heliosphere can be determined with high accuracy due to the high total count rates. In this study, the available data are presented together with an analysis focused on the observation of Forbush decreases, where a strong correlation with neutron monitor data is found.

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We report a measurement of the flux of cosmic rays with unprecedented precision and Statistics using the Pierre Auger Observatory Based on fluorescence observations in coincidence with at least one Surface detector we derive a spectrum for energies above 10(18) eV We also update the previously published energy spectrum obtained with the surface detector array The two spectra are combined addressing the systematic uncertainties and, in particular. the influence of the energy resolution on the spectral shape The spectrum can be described by a broken power law E(-gamma) with index gamma = 3 3 below the ankle which is measured at log(10)(E(ankle)/eV) = 18 6 Above the ankle the spectrum is described by a power law with index 2 6 followed by a flux suppression, above about log(10)(E/eV) = 19 5, detected with high statistical significance (C) 2010 Elsevier B V All rights reserved

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Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.