369 research outputs found

    Coupled-Channel-Induced SDS-D mixing of Charmonia and Testing Possible Assignments for Y(4260)Y(4260) and Y(4360)Y(4360)

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    The mass spectrum and the two-body open-charm decays of the JPC=1J^{PC}=1^{--} charmonium states are studied with the coupled-channel effects taken into account. The coupled-channel-induced mixing effects among the excited vector charmonia are studied. Based on our calculations of the masses and the decay widths, we find that the tension between the observed properties of Y(4260)/Y(4360)Y(4260)/Y(4360) and their conventional charmonia interpretations could be softened.Comment: 13 pages, 5 figures, 5 table

    Balanced AR Glasses System Between Text and Image Information Helps People Get a better Reading Skill

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    Nowadays, people prefer browsing images and videos on their phones rather than reading a book (Thain 2018). Even if they decide to read something, they are still heavily distracted by electronic devices. In my thesis, I’m trying to balance the visual and text information and help people to stay more focused while reading. My solution: Focus is an AR glasses system that recognizes the contents users are viewing and records users’ reading and image browsing time. And users have to earn image/video time by reading the text. The glasses block images/videos if they run out of image time

    Neutrino and Antineutrino Induced Meson Production

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    Coherent meson production measurement is very important in physics research. First, the coherent pion production is a potential background to v oscillation in next generation of Long Base Line Experiment(ELBNF/DUNE); second, coherent pion and coherent p production provide a detailed test of CVC and PCAC hypothesis; third, coherent meson production can be used to monitor the neutrino and anti-neutrino fluxes in the experiment. This dissertation focuses on two parts: coherent pi production in NOMAD, and coherent p simulation using LBNF fluxes. With the NOMAD data, the ratio between cross-sections of coherent pi- and v charged current interactions was measured and compared with the measurements of coherent pi+. The experience of coherent pi analysis may be used to evaluate the sensitivity of ELBNF/DUNE project to coherent processes. With the ELBNF process, I wrote a new C++ simulation package and generated 100k coherent p+ events. It is known that for the neutrino-induced process, the incoming neutrino fluxes could not be measured directly, and the Q2 and other variables related to it are unknown in the neutrino-induced neutral current interactions. The photon-induced coherent p0 provides a way to get additional information to constrain the incoming neutrino fluxes. I calculated the ratios between the cross-sections of neutrino-induced coherent p+-, p0 and photon-induced coherent p0. With these ratios, some kinematic variable distributions are reweighted with this ratio in this thesis

    PIDray: A Large-scale X-ray Benchmark for Real-World Prohibited Item Detection

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    Automatic security inspection relying on computer vision technology is a challenging task in real-world scenarios due to many factors, such as intra-class variance, class imbalance, and occlusion. Most previous methods rarely touch the cases where the prohibited items are deliberately hidden in messy objects because of the scarcity of large-scale datasets, hindering their applications. To address this issue and facilitate related research, we present a large-scale dataset, named PIDray, which covers various cases in real-world scenarios for prohibited item detection, especially for deliberately hidden items. In specific, PIDray collects 124,486 X-ray images for 1212 categories of prohibited items, and each image is manually annotated with careful inspection, which makes it, to our best knowledge, to largest prohibited items detection dataset to date. Meanwhile, we propose a general divide-and-conquer pipeline to develop baseline algorithms on PIDray. Specifically, we adopt the tree-like structure to suppress the influence of the long-tailed issue in the PIDray dataset, where the first course-grained node is tasked with the binary classification to alleviate the influence of head category, while the subsequent fine-grained node is dedicated to the specific tasks of the tail categories. Based on this simple yet effective scheme, we offer strong task-specific baselines across object detection, instance segmentation, and multi-label classification tasks and verify the generalization ability on common datasets (e.g., COCO and PASCAL VOC). Extensive experiments on PIDray demonstrate that the proposed method performs favorably against current state-of-the-art methods, especially for deliberately hidden items. Our benchmark and codes will be released at https://github.com/lutao2021/PIDray.Comment: Tech. report. arXiv admin note: text overlap with arXiv:2108.0702

    Strong decays of D3(2760)D_{3}^{*}(2760) D 3 ∗ ( 2760 ) , Ds3(2860)D_{s3}^{*}(2860) D s 3 ∗ ( 2860 ) , B3B_{3}^{*} B 3 ∗ , and Bs3B_{s3}^{*} B s 3 ∗

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    In this paper, we study the OZI-allowed two-body strong decays of 33^- heavy–light mesons. Experimentally the charmed D3(2760)D_{3}^{*}(2760) and the charm–strange Ds3(2860)D_{s3}^{*}(2860) states with these quantum numbers have been discovered. For the bottomed B(5970) state, which was found by the CDF Collaboration recently, its quantum number has not been decided yet and we assume it is a 33^- meson in this paper. The theoretical prediction for the strong decays of bottom–strange state Bs3B_{s3}^* is also given. The relativistic wave functions of 33^- heavy mesons are constructed and their numerical values are obtained by solving the corresponding Bethe–Salpeter equation with instantaneous approximation. The transition matrix is calculated by using the PCAC and low energy theorem, following which the decay widths are obtained. For D3(2760)D_{3}^*(2760) and Ds3(2860)D_{s3}^*(2860), the total strong decay widths are 72.6 and 47.6 MeV, respectively. For B3B_3^* with M=5978M=5978 MeV and Bs3B_{s3}^* with M=6178M=6178 MeV, their strong decay widths are 22.9 and 40.8 MeV, respectively

    What explains Alibaba’s miraculous IPO success on the New York Stock Exchange?

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    Funding This work was supported by the Natural Science Foundation of China under Grant 72173036; the Natural Science Foundation of Hainan Province under Grant 721RC515. The authors are solely responsible for any error or omission herein. Funding Information: This work was supported by the National Natural Science Foundation of China under Grant 72173036; the Natural Science Foundation of Hainan Province under Grant 721RC515. The authors are solely responsible for any error or omission herein. Publisher Copyright: © 2022 Informa UK Limited, trading as Taylor & Francis Group.Peer reviewe

    Functional Mapping of Plant Growth in Arabidopsis thaliana

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    Most traits important to agriculture, biology, and biomedicine are complex traits, determined by both genetic and environmental factors. The complex traits that change their phenotypes over different stages of development are called dynamic traits. Traditional quantitative trait loci (QTLs) mapping approaches ignore the dynamic changes of complex traits. Functional mapping, as a powerful statistical tool, can not only map QTLs that control the developmental pattern and process of complex traits, but also describe the dynamic changes of complex traits. In this study, we used functional mapping to identify those QTLs that affect height growth in 10th generation recombinant inbred lines derived from two different Arabidopsis thaliana accessions. Functional mapping identified 48 QTLs that are related to height traits. The growth curves of different genotypes can be drawn for each significant locus. By GO gene function annotations, we found that these QTLs detected are associated with the synthesis of biological macromolecules and the regulation of biological functions. Our findings provide unique insights into the genetic control of height growth of A. thaliana and will provide a theoretical basis for the study of complex traits

    Auto-analysis system for graphite morphology of grey cast iron

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    The current method to classify graphite morphology types of grey cast iron is based on traditional subjective observation, and it cannot be used for quantitative analysis. Since microstructures have a great effect on the mechanical properties of grey cast iron and different types have totally different characters, six types of grey cast iron are discussed and an image-processing software subsystem that performs the classification and quantitative analysis automatically based on a kind of composed feature vector and artificial neural network (ANN) is described. There are three kinds of texture features: fractal dimension, roughness and two-dimension autoregression, which are used as an extracted feature input vector of ANN classifier. Compared with using only one, the checkout correct precision increased greatly. On the other hand, to achieve the quantitative analysis and show the different types clearly, the region segmentation idea was applied to the system. The percentages of the regions with different type are reported correctly. Furthermore, this paper tentatively introduces a new empirical method to decide the number of ANN hidden nodes, which are usually considered as a difficulty in ANN structure decision. It was found that the optimum hidden node number of the experimental data was the same as that obtained using the new method
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