29,542 research outputs found

    A probabilistic approach to model-based adaptive control for damping of interarea oscillations

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    Angular Momentum Decomposition for an Electron

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    We calculate the orbital angular momentum of the `quark' in the scalar diquark model as well as that of the electron in QED (to order α\alpha). We compare the orbital angular momentum obtained from the Jaffe-Manohar decomposition to that obtained from the Ji relation and estimate the importance of the vector potential in the definition of orbital angular momentum

    Voltage control performance of AWS connected for grid operation

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    Robust damping of multiple swing modes employing global stabilizing signals with a TCSC

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    The impact of the ATLAS zero-lepton, jets and missing momentum search on a CMSSM fit

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    Recent ATLAS data significantly extend the exclusion limits for supersymmetric particles. We examine the impact of such data on global fits of the constrained minimal supersymmetric standard model (CMSSM) to indirect and cosmological data. We calculate the likelihood map of the ATLAS search, taking into account systematic errors on the signal and on the background. We validate our calculation against the ATLAS determinaton of 95% confidence level exclusion contours. A previous CMSSM global fit is then re-weighted by the likelihood map, which takes a bite at the high probability density region of the global fit, pushing scalar and gaugino masses up.Comment: 16 pages, 7 figures. v2 has bigger figures and fixed typos. v3 has clarified explanation of our handling of signal systematic

    The Turkey Ig-like receptor family: identification, expression and function.

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    The chicken leukocyte receptor complex located on microchromosome 31 encodes the chicken Ig-like receptors (CHIR), a vastly expanded gene family which can be further divided into three subgroups: activating CHIR-A, bifunctional CHIR-AB and inhibitory CHIR-B. Here, we investigated the presence of CHIR homologues in other bird species. The available genome databases of turkey, duck and zebra finch were screened with different strategies including BLAST searches employing various CHIR sequences, and keyword searches. We could not identify CHIR homologues in the distantly related zebra finch and duck, however, several partial and complete sequences of CHIR homologues were identified on chromosome 3 of the turkey genome. They were designated as turkey Ig-like receptors (TILR). Using cDNA derived from turkey blood and spleen RNA, six full length TILR could be amplified and further divided according to the typical sequence features into one activating TILR-A, one inhibitory TILR-B and four bifunctional TILR-AB. Since the TILR-AB sequences all displayed the critical residues shown to be involved in binding to IgY, we next confirmed the IgY binding using a soluble TILR-AB1-huIg fusion protein. This fusion protein reacted with IgY derived from various gallinaceous birds, but not with IgY from other bird species. Finally, we tested various mab directed against CHIR for their crossreactivity with either turkey or duck leukocytes. Whereas no staining was detectable with duck cells, the CHIR-AB1 specific mab 8D12 and the CHIR-A2 specific mab 13E2 both reacted with a leukocyte subpopulation that was further identified as thrombocytes by double immunofluorescence employing B-cell, T-cell and thrombocyte specific reagents. In summary, although the turkey harbors similar LRC genes as the chicken, their distribution seems to be distinct with predominance on thrombocytes rather than lymphocytes

    Framework for cost-effective analytical modelling for sensory data over cloud environment

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    In order to offer sensory data as a service over the cloud, it is necessary to execute a cost-effective and yet precise data analytical logic within the sensing units. However, it is quite questionable as such forms of analytical operation are quite resource dependent which cannot be offered by the resource constraint sensory units. Therefore, the proposed paper introduces a novel approach of performing cost-effective data analytical method in order to extract knowledge from big data over the cloud. The proposed study uses a novel concept of the frequent pattern along with a tree-based approach in order to develop an analytical model for carrying out the mining operation in the large-scale sensor deployment over the cloud environment. Using a simulation-based approach over the mathematical model, the proposed model exhibit reduced mining duration, controlled energy dissipation, and highly optimized memory demands for all the resource constraint nodes
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