8 research outputs found

    Tevatron Run II combination of the effective leptonic electroweak mixing angle

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    Drell-Yan lepton pairs produced in the process pp→â.,"+â.,"-+X through an intermediate γ∗/Z boson have an asymmetry in their angular distribution related to the spontaneous symmetry breaking of the electroweak force and the associated mixing of its neutral gauge bosons. The CDF and D0 experiments have measured the effective-leptonic electroweak mixing parameter sin2θefflept using electron and muon pairs selected from the full Tevatron proton-antiproton data sets collected in 2001-2011, corresponding to 9-10 fb-1 of integrated luminosity. The combination of these measurements yields the most precise result from hadron colliders, sin2θefflept=0.23148±0.00033. This result is consistent with, and approaches in precision, the best measurements from electron-positron colliders. The standard model inference of the on-shell electroweak mixing parameter sin2θW, or equivalently the W-boson mass MW, using the zfitter software package yields sin2θW=0.22324±0.00033 or equivalently, MW=80.367±0.017 GeV/c2

    NAViGaTOR: Large Scalable and Interactive Navigation and Analysis of Large Graphs

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    Alterations in White Matter Microstructure and Connectivity in Young Adults with Alcohol Use Disorder.

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    Background: Magnetic resonance imaging (MRI) studies have shown differences in volume and structure in the brains of individuals with alcohol use disorder (AUD). Most research has focused on neuropathological effects of alcohol that appear after years of chronic alcohol misuse. However, few studies have investigated white matter (WM) microstructure and diffusion MRI-based (DWI) connectivity during early stages of AUD. Therefore, the goal of this work was to investigate WM integrity and structural connectivity in emerging adulthood AUD subjects using both conventional DWI metrics and a novel connectomics approach. Methods: Twenty-two AUD and eighteen controls (CON) underwent anatomical and diffusion MRI. Outcome measures were scalar diffusion metrics and structural network connectomes. Tract Based Spatial Statistics was used to investigate group differences in diffusion measures. Structural connectomes were used as input into a community structure procedure to obtain a co-classification index matrix (an indicator of community association strength) for each subject. Differences in co-classification and structural connectivity (indexed by streamline density) were assessed via the Network Based Statistics Toolbox. Results: AUD had higher FA values throughout the major WM tracts, but also had lower FA values in WM tracts in the cerebellum and right insula (pTFCEp_{\textrm{TFCE}} < 0.05). Mean diffusivity was generally lower in the AUD group (pTFCEp_{\textrm{TFCE}} < 0.05). AUD had lower co-classification of nodes between ventral attention and default mode networks, and higher co-classification between nodes of visual, default mode, and somatomotor networks. Additionally, AUD had higher fiber density between an adjacent pair of nodes within the default mode network. Conclusion: Our results indicate that emerging adulthood AUD subjects may have differential patterns of FA and distinct differences in structural connectomes compared to CON. These data suggest that such alterations in microstructure and structural connectivity may uniquely characterize early stages of AUD and/or a predisposition for development of AU

    Computational neuroscience and neuroinformatics: Recent progress and resources

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