Neutrino and Antineutrino Induced Meson Production

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

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 $12$ 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 ) , B3∗B_{3}^{*} B 3 ∗ , and Bs3∗B_{s3}^{*} B s 3 ∗

In this paper, we study the OZI-allowed two-body strong decays of $$3^-$$ heavy–light mesons. Experimentally the charmed $$D_{3}^{*}(2760)$$ and the charm–strange $$D_{s3}^{*}(2860)$$ 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 $$3^-$$ meson in this paper. The theoretical prediction for the strong decays of bottom–strange state $$B_{s3}^*$$ is also given. The relativistic wave functions of $$3^-$$ 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 $$D_{3}^*(2760)$$ and $$D_{s3}^*(2860)$$, the total strong decay widths are 72.6 and 47.6 MeV, respectively. For $$B_3^*$$ with $$M=5978$$ MeV and $$B_{s3}^*$$ with $$M=6178$$ 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?

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

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

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