440 research outputs found

    Multiwavelength Observations of the Blazar BL Lacertae: A New Fast TeV Gamma-Ray Flare

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    Combined with measurements made by very-long-baseline interferometry, the observations of fast TeV gamma-ray flares probe the structure and emission mechanism of blazar jets. However, only a handful of such flares have been detected to date, and only within the last few years have these flares been observed from lower-frequency-peaked BL Lac objects and flat-spectrum radio quasars. We report on a fast TeV gamma-ray flare from the blazar BL Lacertae observed by the Very Energetic Radiation Imaging Telescope Array System (VERITAS). with a rise time of ~2.3 hr and a decay time of ~36 min. The peak flux above 200 GeV is (4.2 ± 0.6) × 10^(−6) photon m^(−2) s^(−1) measured with a 4-minute-binned light curve, corresponding to ~180% of the flux that is observed from the Crab Nebula above the same energy threshold. Variability contemporaneous with the TeV gamma-ray flare was observed in GeV gamma-ray, X-ray, and optical flux, as well as in optical and radio polarization. Additionally, a possible moving emission feature with superluminal apparent velocity was identified in Very Long Baseline Array observations at 43 GHz, potentially passing the radio core of the jet around the time of the gamma-ray flare. We discuss the constraints on the size, Lorentz factor, and location of the emitting region of the flare, and the interpretations with several theoretical models that invoke relativistic plasma passing stationary shocks

    All-sky Measurement of the Anisotropy of Cosmic Rays at 10 TeV and Mapping of the Local Interstellar Magnetic Field

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    We present the first full-sky analysis of the cosmic ray arrival direction distribution with data collected by the High-Altitude Water Cherenkov and IceCube observatories in the northern and southern hemispheres at the same median primary particle energy of 10 TeV. The combined sky map and angular power spectrum largely eliminate biases that result from partial sky coverage and present a key to probe into the propagation properties of TeV cosmic rays through our local interstellar medium and the interaction between the interstellar and heliospheric magnetic fields. From the map, we determine the horizontal dipole components of the anisotropy δ 0h = 9.16 × 10−4 and δ 6h = 7.25 × 10−4 (±0.04 × 10−4). In addition, we infer the direction (229fdg2 ± 3fdg5 R.A., 11fdg4 ± 3fdg0 decl.) of the interstellar magnetic field from the boundary between large-scale excess and deficit regions from which we estimate the missing corresponding vertical dipole component of the large-scale anisotropy to be δN∼−3.97−2.0+1.0×10−4{\delta }_{N}\sim -{3.97}_{-2.0}^{+1.0}\times {10}^{-4}

    A Proposal to Localize Fermi GBM GRBs Through Coordinated Scanning of the GBM Error Circle via Optical Telescopes

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    We investigate the feasibility of implementing a system that will coordinate ground-based optical telescopes to cover the Fermi GBM Error Circle (EC). The aim of the system is to localize GBM detected GRBs and facilitate multi-wavelength follow-up from space and ground. This system will optimize the observing locations in the GBM EC based on individual telescope location, Field of View (FoV) and sensitivity. The proposed system will coordinate GBM EC scanning by professional as well as amateur astronomers around the world. The results of a Monte Carlo simulation to investigate the feasibility of the project are presented.Comment: 2011 Fermi Symposium proceedings - eConf C11050

    Effect of replacing corn grain by wheat-based dried distillers’ grains with solubles dietary energy and protein value in cattle

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    Non-Peer ReviewedThe objectives of this study were to determine the effect of replacing corn grain portion of the diet by wheat-based dried distillers’ grains with solubles (wDDGS) on feeding value for ruminants by chemical fractionation, nylon bag rumen degradation and nutrient modeling approaches. This study revealed that increasing wDDGS inclusion level increased most of nutritional composition linearly, except for starch which linearly decreased. Metabolizable protein supply in small intestine increased linearly with increasing levels of wDDGS. The inclusion of wDDGS in corn based diets decreased energy values of the diet slightly. Optimum ruminal N to energy balance for microbial growth was reached by replacing 25-50% of corn by wDDGS. In summary, this study suggests that corn and wheat DDGS combinations are a viable alternative for replace feed barley grain for the beef industry in western Canada

    Decentralised Traffic Incident Detection via Network Lasso

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    Traffic incident detection plays a key role in intelligent transportation systems, which has gained great attention in transport engineering. In the past, traditional machine learning (ML) based detection methods achieved good performance under a centralised computing paradigm, where all data are transmitted to a central server for building ML models therein. Nowadays, deep neural networks based federated learning (FL) has become a mainstream detection approach to enable the model training in a decentralised manner while warranting local data governance. Such neural networks-centred techniques, however, have overshadowed the utility of well-established ML-based detection methods. In this work, we aim to explore the potential of potent conventional ML-based detection models in modern traffic scenarios featured by distributed data. We leverage an elegant but less explored distributed optimisation framework named Network Lasso, with guaranteed global convergence for convex problem formulations, integrate the potent convex ML model with it, and compare it with centralised learning, local learning, and federated learning methods atop a well-known traffic incident detection dataset. Experimental results show that the proposed network lasso-based approach provides a promising alternative to the FL-based approach in data-decentralised traffic scenarios, with a strong convergence guarantee while rekindling the significance of conventional ML-based detection methods
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