65,998 research outputs found

    Single chargino production via gluon-gluon fusion in a supersymmetric theory with an explicit R-parity violation

    Get PDF
    We studied the production of single charginoχ~1±\tilde{\chi}_1^{\pm} accompanied by μ∓\mu^{\mp} lepton via gluon-gluon fusion at the LHC. The numerical analysis of their production rates is carried out in the mSUGRA scenario with some typical parameter sets. The results show that the cross sections of the χ~1±μ∓\tilde{\chi}_1^{\pm}\mu^{\mp} productions via gluon-gluon collision are in the order of 1∼1021 \sim 10^{2} femto barn quantitatively at the CERN LHC, and can be competitive with production mechanism via quark-antiquark annihilation process.Comment: LaTex file, 18 pages, 4 EPS file

    Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction

    Get PDF
    Visual media are powerful means of expressing emotions and sentiments. The constant generation of new content in social networks highlights the need of automated visual sentiment analysis tools. While Convolutional Neural Networks (CNNs) have established a new state-of-the-art in several vision problems, their application to the task of sentiment analysis is mostly unexplored and there are few studies regarding how to design CNNs for this purpose. In this work, we study the suitability of fine-tuning a CNN for visual sentiment prediction as well as explore performance boosting techniques within this deep learning setting. Finally, we provide a deep-dive analysis into a benchmark, state-of-the-art network architecture to gain insight about how to design patterns for CNNs on the task of visual sentiment prediction.Comment: Preprint of the paper accepted at the 1st Workshop on Affect and Sentiment in Multimedia (ASM), in ACM MultiMedia 2015. Brisbane, Australi

    Residual proton-neutron interactions and the NpNnN_{\rm p} N_{\rm n} scheme

    Full text link
    We investigate the correlation between integrated proton-neutron interactions obtained by using the up-to-date experimental data of binding energies and the NpNnN_{\rm p} N_{\rm n}, the product of valence proton number and valence neutron number with respect to the nearest doubly closed nucleus. We make corrections on a previously suggested formula for the integrated proton-neutron interaction. Our results demonstrate a nice, nearly linear, correlation between the integrated p-n interaction and NpNnN_{\rm p} N_{\rm n}, which provides us with a firm foundation of the applicability of the NpNnN_{\rm p} N_{\rm n} scheme to nuclei far from the stability line.Comment: four pages, three figures, Physical Review C, in pres

    Polarization Induced Switching Effect in Graphene Nanoribbon Edge-Defect Junction

    Full text link
    With nonequilibrium Green's function approach combined with density functional theory, we perform an ab initio calculation to investigate transport properties of graphene nanoribbon junctions self-consistently. Tight-binding approximation is applied to model the zigzag graphene nanoribbon (ZGNR) electrodes, and its validity is confirmed by comparison with GAUSSIAN03 PBC calculation of the same system. The origin of abnormal jump points usually appearing in the transmission spectrum is explained with the detailed tight-binding ZGNR band structure. Transport property of an edge defect ZGNR junction is investigated, and the tunable tunneling current can be sensitively controlled by transverse electric fields.Comment: 18 pages, 8 figure

    Spatio-Temporal Sentiment Hotspot Detection Using Geotagged Photos

    Full text link
    We perform spatio-temporal analysis of public sentiment using geotagged photo collections. We develop a deep learning-based classifier that predicts the emotion conveyed by an image. This allows us to associate sentiment with place. We perform spatial hotspot detection and show that different emotions have distinct spatial distributions that match expectations. We also perform temporal analysis using the capture time of the photos. Our spatio-temporal hotspot detection correctly identifies emerging concentrations of specific emotions and year-by-year analyses of select locations show there are strong temporal correlations between the predicted emotions and known events.Comment: To appear in ACM SIGSPATIAL 201

    Two Higgs Bosons at the Tevatron and the LHC?

    Full text link
    The best fit to the Tevatron results in the bb channel and the mild excesses at CMS in the gamma-gamma channel at 136 GeV and in the tau-tau channel above 132 GeV can be explained by a second Higgs state in this mass range, in addition to the one at 125 GeV recently discovered at the LHC. We show that a scenario with two Higgs bosons at 125 GeV and 136 GeV can be consistent with practically all available signal rates, including a reduced rate in the tau-tau channel around 125 GeV as reported by CMS. An example in the parameter space of the general NMSSM is given where, moreover, the signal rates of the 125 GeV Higgs boson in the gamma-gamma channels are enhanced relative to the expectation for a SM Higgs boson of this mass.Comment: 13 pages, 4 Table
    • …
    corecore