145 research outputs found

    Genomic monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that modulates type I interferon response

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    The SARS-CoV-2 virus, the causative agent of COVID-19, is undergoing constant mutation. Here, we utilized an integrative approach combining epidemiology, virus genome sequencing, clinical phenotyping, and experimental validation to locate mutations of clinical importance. We identified 35 recurrent variants, some of which are associated with clinical phenotypes related to severity. One variant, containing a deletion in the Nsp1-coding region (D500-532), was found in more than 20% of our sequenced samples and associates with higher RT-PCR cycle thresholds and lower serum IFN-beta levels of infected patients. Deletion variants in this locus were found in 37 countries worldwide, and viruses isolated from clinical samples or engineered by reverse genetics with related deletions in Nsp1 also induce lower IFN-beta responses in infected Calu-3 cells. Taken together, our virologic surveillance characterizes recurrent genetic diversity and identified mutations in Nsp1 of biological and clinical importance, which collectively may aid molecular diagnostics and drug design.Peer reviewe

    Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

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    Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30MM_{\odot} for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

    Detection of the Diffuse Supernova Neutrino Background with JUNO

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    As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

    Potential of Core-Collapse Supernova Neutrino Detection at JUNO

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    JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

    3D Printed Sensors for Biomedical Applications: A Review

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    This paper showcases a substantial review on some of the significant work done on 3D printing of sensors for biomedical applications. The importance of 3D printing techniques has bloomed in the sensing world due to their essential advantages of quick fabrication, easy accessibility, processing of varied materials and sustainability. Along with the introduction of the necessity and influence of 3D printing techniques for the fabrication of sensors for different healthcare applications, the paper explains the individual methodologies used to develop sensing prototypes. Six different 3D printing techniques have been explained in the manuscript, followed by drawing a comparison between them in terms of their advantages, disadvantages, materials being processed, resolution, repeatability, accuracy and applications. Finally, a conclusion of the paper is provided with some of the challenges of the current 3D printing techniques about the developed sensing prototypes, their corresponding remedial solutions and a market survey determining the expenditure on 3D printing for biomedical sensing prototypes

    A Resampling Method Based on Filter Designed by Window Function Considering Frequency Aliasing

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    Multi-parameter joint optimization for double-strip high-speed pantographs to improve pantograph-catenary interaction quality

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    The significant increase in speed of high-speed train will cause the dynamic contact force of the pantograph-catenary system to fluctuate more severely, which poses a challenge to the study of the pantograph-catenary relationship and the design of high-speed pantographs. Good pantograph-catenary coupling quality is the essential condition to ensure safe and efficient operation of high-speed train, stable and reliable current collection, and reduction in the wear of contact wires and pantograph contact strips. Among them, the dynamic parameters of high-speed pantographs are crucial to pantograph-catenary coupling quality. With the reduction of the standard deviation of the pantograph-catenary contact force as the optimization goal, multi-parameter joint optimization designs for the high-speed pantograph with two contact strips at multiple running speeds are proposed. Moreover, combining the sensitivity analysis at the optimal solutions, with the parameters and characteristics of in-service DSA380 high-speed pantograph, the optimization proposal of DSA380 was given

    Multi-Person Pose Estimation via Multi-Layer Fractal Network and Joints Kinship Pattern

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