899 resultados para Local and Wide Area Network


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El següent projecte consisteix en analitzar com funciona un sistema SAN, per tal de veure comes pot obtenir un millor rendiment. L’objectiu principal es saber com es comportarà la nostra SAN muntada amb iSCSI a través de la xarxa, volem veure quines són les operacions, les dades i els resultats que comporta crear una RAID a través de discos no locals d’un ordinador i a través d’una xarxa LAN

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In our previous study, we have found that 5-cyclopropyl-2-[1-(2-fluoro-benzyl)-1H-pyrazolo[3,4-b]pyridine-3-yl]-pyrimidin-4-ylamine (BAY 41-2272), a guanylate cyclase agonist, activates human monocytes and the THP-1 cell line to produce the superoxide anion, increasing in vitro microbicidal activity, suggesting that this drug can be used to modulate immune functioning in primary immunodeficiency patients. In the present work, we investigated the potential of the in vivo administration of BAY 41-2272 for the treatment of Candida albicans and Staphylococcus aureus infections introduced via intraperitoneal and subcutaneous inoculation. We found that intraperitoneal treatment with BAY 41-2272 markedly increased macrophage-dependent cell influx to the peritoneum in addition to macrophage functions, such as spreading, zymosan particle phagocytosis and nitric oxide and phorbol myristate acetate-stimulated hydrogen peroxide production. Treatment with BAY 41-2272 was highly effective in reducing the death rate due to intraperitoneal inoculation of C. albicans, but not S. aureus. However, we found that in vitro stimulation of peritoneal macrophages with BAY 41-2272 markedly increased microbicidal activities against both pathogens. Our results show that the prevention of death by the treatment of C. albicans-infected mice with BAY 41-2272 might occur primarily by the modulation of the host immune response through macrophage activation.

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We addressed the influence of the stem galls induced by an unidentified species of Apion sensu lato (Brentidae, Apioninae) on the host plant, Diospyros hispida (Ebenaceae) leaf area and induced resistance against a Cecidomyiidae (Diptera) leaf galls. The study was performed in a cerrado vegetation in Serra do Cipó, southeastern Brazil. Although the number of leaves produced on galled and ungalled shoots did not differ statically (p>0.05), the presence of the apionid galls influenced the area of the leaves on the attacked shoots of D. hispida. Leaves on galled stems were approximately 50% smaller compared to leaves in healthy stems. The average of the cecidomyiid leaf galls successfully induced on healthy shoots was higher compared to galls successfully induced on shoots galled by the apionid. The same pattern was found for the abundance of hypersensitive reactions against the cedidomyiid gall induction. Therefore, the ability of the cecidomyiid to successfully induce galls was not influenced by the apionid galler.

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In this article we propose using small area estimators to improve the estimatesof both the small and large area parameters. When the objective is to estimateparameters at both levels accurately, optimality is achieved by a mixed sampledesign of fixed and proportional allocations. In the mixed sample design, oncea sample size has been determined, one fraction of it is distributedproportionally among the different small areas while the rest is evenlydistributed among them. We use Monte Carlo simulations to assess theperformance of the direct estimator and two composite covariant-freesmall area estimators, for different sample sizes and different sampledistributions. Performance is measured in terms of Mean Squared Errors(MSE) of both small and large area parameters. It is found that the adoptionof small area composite estimators open the possibility of 1) reducingsample size when precision is given, or 2) improving precision for a givensample size.

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Compilation of the recent literature from the Southern Alps and adjacent area confirms the geochemical variations of unusual amplitudes during the Permian-Triassic boundary interval (PTBI). A great attention has been given to the negative δ13C anomaly within the Tesero Member close to the Permian-Triassic boundary. Very detailed geochemical works have been done on the scientific Gartnerkofel core (Gk-1) and on the Slovenian sections. Major minor and rare earth elements (REE) data are reported and show a marked enrichment in alkaline metals and REE of some levels of the boundary interval. But recent studies show that the low Iridium anomalies and the Osmium and Helium isotopes anomalies lack the characteristics of a large extraterrestrial impact.

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In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

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Arabidopsis thaliana PHO1 is primarily expressed in the root vascular cylinder and is involved in the transfer of inorganic phosphate (Pi) from roots to shoots. To analyze the role of PHO1 in transport of Pi, we have generated transgenic plants expressing PHO1 in ectopic A. thaliana tissues using an estradiol-inducible promoter. Leaves treated with estradiol showed strong PHO1 expression, leading to detectable accumulation of PHO1 protein. Estradiol-mediated induction of PHO1 in leaves from soil-grown plants, in leaves and roots of plants grown in liquid culture, or in leaf mesophyll protoplasts, was all accompanied by the specific release of Pi to the extracellular medium as early as 2-3 h after addition of estradiol. Net Pi export triggered by PHO1 induction was enhanced by high extracellular Pi and weakly inhibited by the proton-ionophore carbonyl cyanide m-chlorophenylhydrazone. Expression of a PHO1-GFP construct complementing the pho1 mutant revealed GFP expression in punctate structures in the pericycle cells but no fluorescence at the plasma membrane. When expressed in onion epidermal cells or in tobacco mesophyll cells, PHO1-GFP was associated with similar punctate structures that co-localized with the Golgi/trans-Golgi network and uncharacterized vesicles. However, PHO1-GFP could be partially relocated to the plasma membrane in leaves infiltrated with a high-phosphate solution. Together, these results show that PHO1 can trigger Pi export in ectopic plant cells, strongly indicating that PHO1 is itself a Pi exporter. Interestingly, PHO1-mediated Pi export was associated with its localization to the Golgi and trans-Golgi networks, revealing a role for these organelles in Pi transport.

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This thesis examines the local and regional scale determinants of biodiversity patterns using existing species and environmental data. The research focuses on agricultural environments that have experienced rapid declines of biodiversity during past decades. Existing digital databases provide vast opportunities for habitat mapping, predictive mapping of species occurrences and richness and understanding the speciesenvironment relationships. The applicability of these databases depends on the required accuracy and quality of the data needed to answer the landscape ecological and biogeographical questions in hand. Patterns of biodiversity arise from confounded effects of different factors, such as climate, land cover and geographical location. Complementary statistical approaches that can show the relative effects of different factors are needed in biodiversity analyses in addition to classical multivariate models. Better understanding of the key factors underlying the variation in diversity requires the analyses of multiple taxonomic groups from different perspectives, such as richness, occurrence, threat status and population trends. The geographical coincidence of species richness of different taxonomic groups can be rather limited. This implies that multiple geographical regions should be taken into account in order to preserve various groups of species. Boreal agricultural biodiversity and in particular, distribution and richness of threatened species is strongly associated with various grasslands. Further, heterogeneous agricultural landscapes characterized by moderate field size, forest patches and non-crop agricultural habitats enhance the biodiversity of rural environments. From the landscape ecological perspective, the major threats to Finnish agricultural biodiversity are the decline of connected grassland habitat networks, and general homogenization of landscape structure resulting from both intensification and marginalization of agriculture. The maintenance of key habitats, such as meadows and pastures is an essential task in conservation of agricultural biodiversity. Furthermore, a larger landscape context should be incorporated in conservation planning and decision making processes in order to respond to the needs of different species and to maintain heterogeneous rural landscapes and viable agricultural diversity in the future.

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Perceiving the world visually is a basic act for humans, but for computers it is still an unsolved problem. The variability present innatural environments is an obstacle for effective computer vision. The goal of invariant object recognition is to recognise objects in a digital image despite variations in, for example, pose, lighting or occlusion. In this study, invariant object recognition is considered from the viewpoint of feature extraction. Thedifferences between local and global features are studied with emphasis on Hough transform and Gabor filtering based feature extraction. The methods are examined with respect to four capabilities: generality, invariance, stability, and efficiency. Invariant features are presented using both Hough transform and Gabor filtering. A modified Hough transform technique is also presented where the distortion tolerance is increased by incorporating local information. In addition, methods for decreasing the computational costs of the Hough transform employing parallel processing and local information are introduced.

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BACKGROUND: Radial maze tasks have been used to assess optimal foraging and spatial abilities in rodents. The spatial performance was based on a capacity to rely on a configuration of local and distant cues. We adapted maze procedures assessing the relative weight of local cues and distant landmarks for arm choice in humans. NEW METHOD: The procedure allowed testing memory of places in four experimental setups: a fingertip texture-groove maze, a tactile screen maze, a virtual radial maze and a walking size maze. During training, the four reinforced positions remained fixed relative to local and distal cues. During subsequent conflict trials, these frameworks were made conflictive in the prediction of reward locations. RESULTS: Three experiments showed that the relative weight of local and distal relational cues is affected by different factors such as cues' nature, visual access to the environment, real vs. virtual environment, and gender. A fourth experiment illustrated how a walking maze can be used with people suffering intellectual disability. COMPARISON WITH EXISTING METHODS: In our procedure, long-term (reference) and short-term (working) memory can be assessed. It is the first radial task adapted to human that enables dissociating local and distal cues, to provides an indication as to their relative salience. Our mazes are moveable and easily used in limited spaces. Tasks are performed with realistic and spontaneous though controlled exploratory movements. CONCLUSION: Our tasks enabled highlighting the use of different strategies. In a clinical perspective, considering the use of compensatory strategies should orient towards adapted behavioural rehabilitation.

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This paper analyzes Spanish infrastructure policy since the early 1700s: Road building in the eighteenth century, railway creation and expansion in the nineteenth, motorway expansion in the twentieth, and high speed rail development in the twenty-first. The analysis reveals a long-term pattern, in which infrastructure policy in Spain has been driven not by the requirements of commerce and economic activity, but rather by the desire to centralize transportation around the country’s political capital.