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Measurement of solar pp neutrino flux using electron recoil data from PandaX-4T commissioning run

Chinese Physics C 2024年第9期48卷 1-7,300页

作者： Xiaoying Lu Abdusalam Abdukerim Zihao Bo Wei Chen Xun Chen Yunhua Chen Chen Cheng Zhaokan Cheng Xiangyi Cui Yingjie Fan Deqing Fang Lisheng Geng Karl Giboni Xuyuan Guo Chencheng Han Ke Han Changda He Jinrong He Di Huang Junting Huang Zhou Huang Ruquan Hou Yu Hou Xiangdong Ji Yonglin Ju Chenxiang Li Jiafu Li Mingchuan Li Shuaijie Li Tao Li Qing Lin Jianglai Liu Congcong Lu Lingyin Luo Yunyang Luo Wenbo Ma Yugang Ma Yajun Mao Yue Meng Xuyang Ning Binyu Pang Ningchun Qi Zhicheng Qian Xiangxiang Ren Nasir Shaheed Xiaofeng Shang Xiyuan Shao Guofang Shen Manbin Shen Lin Si Wenliang Sun Yi Tao Anqing Wang Meng Wang Qiuhong Wang Shaobo Wang Siguang Wang Wei Wang Xiuli Wang Xu Wang Zhou Wang Yuehuan Wei Mengmeng Wu Weihao Wu Yuan Wu Mengjiao Xiao Xiang Xiao Kaizhi Xiong Binbin Yan Xiyu Yan Yong Yang Chunxu Yu Ying Yuan Zhe Yuan Youhui Yun Xinning Zeng Minzhen Zhang Peng Zhang Shibo Zhang Shu Zhang Tao Zhang Wei Zhang Yang Zhang Yingxin Zhang Yuanyuan Zhang Li Zhao Jifang Zhou Ning Zhou Xiaopeng Zhou Yubo Zhou Zhizhen Zhou Research Center for Particle Science and Technology Institute of Frontier and Interdisciplinary ScienceShandong UniversityQingdao 266237China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong UniversityQingdao 266237China School of Physics and Astronomy Shanghai Jiao Tong UniversityKey Laboratory for Particle Astrophysics and Cosmology(MoE)Shanghai Key Laboratory for Particle Physics and CosmologyShanghai 200240China New Cornerstone Science Laboratory Tsung-Dao Lee InstituteShanghai Jiao Tong UniversityShanghai 200240China Shanghai Jiao Tong University Sichuan Research Institute Chengdu 610213China Jinping Deep Underground Frontier Science and Dark Matter Key Laboratory of Sichuan Province Liangshan 615000China Yalong River Hydropower Development Company Ltd.288 Shuanglin RoadChengdu 610051China School of Physics Sun Yat-Sen UniversityGuangzhou 510275China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-Sen UniversityZhuhai 519082China Department of Physics Yantai UniversityYantai 264005China Key Laboratory of Nuclear Physics and Ion-beam Application(MOE) Institute of Modern PhysicsFudan UniversityShanghai 200433China School of Physics Beihang UniversityBeijing 102206China Beijing Key Laboratory of Advanced Nuclear Materials and Physics Beihang UniversityBeijing 102206China Peng Huanwu Collaborative Center for Research and Education Beihang UniversityBeijing 100191China Southern Center for Nuclear-Science Theory(SCNT) Institute of Modern PhysicsChinese Academy of SciencesHuizhou 516000China School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China Department of Physics University of MarylandCollege ParkMaryland 20742USA State Key Laboratory of Particle Detection and Electronics University of Science and Technology of ChinaHefei 230026China Department of Modern Physics University of Science and Technology of ChinaHefei 230026China School of Physics Peking UniversityBeijing 100871Ch

The proton-proton(pp)fusion chain dominates the neutrino production in the *** uncertainty of the predicted pp neutrino flux is at the sub-percent level,whereas that of the best measurement is O(10%).In this study,for the first time,we measure solar pp neutrinos in the electron recoil energy range from 24 to 144 keV using the PandaX-4T commissioning data with 0.63 tonne×year *** pp neutrino flux is determined as(8.0±3.9(stat)±10.0(syst))×1010 s^(-1)cm^(-2),which is consistent with the Standard Solar Model and existing measurements,corresponding to an upper flux limit of 23.3×10^(10)s^(-1)cm^(-2)at 90%C.L..

关键词： solar pp neutrino flux PandaX-4T electron recoil spectrum

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Identification of Segmented Baijiu by Paper Based Colorimetric Sensor Array Based on Dye-Mofs

SSRN

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SSRN 2024年

作者： Yuan, Zirui Chen, Lin Li, He Ma, Yi Hou, Changjun Luo, Xiaogang Luo, Huibo Huo, Danqun Key Laboratory for Biorheological Science and Technology of Ministry of Education Bioengineering College of Chongqing University Chongqing400044 China Liquor Making Biology Technology Application of Key Laboratory of Sichuan Province College of Bioengineering Sichuan University of Science and Engineering 188 University Town Yibin644000 China National Engineering Research Center of Solid-State Brewing Luzhou Laojiao Group Co. Ltd. Luzhou646000 China

Since segmented Baijiu has a profound impact on the blending and overall quality of Baijiu, it is of major significance to classify segmented Baijiu. In this study, considering the advantages of traditional dyes and metal organic frameworks (MOFs), a Dye-MOFs colorimetric sensor array was constructed by combining dyes and MOFs, which can accurately distinguish eight different concentrations of organic compounds. The paper is coated with a colorimetric sensor array. By detecting organic compounds in the liquor, it is possible to analyse 20 μL segmented Baijiu samples in about one minute. This analysis allows for the identification and differentiation of four pits and 16 segmented Baijiu samples. Through linear discriminant analysis (LDA) model combined with left blank (LOO) analysis, the accuracy of identifying 16 segmented Baijiu blind samples is 100%, which is universal and practical, and provides a fast and simple method for on-site rapid detection. © 2024, The Authors. All rights reserved.

关键词： Metal-Organic Frameworks

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EMC Evaluation of High-power Electronic System Based on Improved AHP-TOPSIS

EMC Evaluation of High-power Electronic System Based on Impr...

引用

Progress in Electromagnetic Research Symposium (PIERS)

作者： Qiang-Ming Cai Quan Deng Xin Cao Longjian Zhou Haoran Li Zhen-Yong Du Yixiang Li Yuyu Zhu Jun Fan School of Information Engineering Southwest University of Science and Technology Mianyang China Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Mianyang China Tianfu Institute of Research and Innovation Southwest University of Science and Technology (SWUST-TIRI) China Chengdu Juji Millimeter Wave Technology Co. Ltd Chengdu China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

The electronic system is equipped with a large number of electronic and electrical equipment, which forms a complex electromagnetic field environment both internally and externally. This will lead to performance degradation or equipment failure when electronic and electrical equipment work together. Therefore, electromagnetic compatibility assessment plays an important role in the design and normal operation of electronic systems. This article analyzes the shortcomings and scope of existing electromagnetic compatibility evaluation methods, and on this basis, an improved AHP-TOPSIS evaluation method is used to evaluate the electromagnetic compatibility of high-power electronic systems. Firstly, the AHP-TOPSIS algorithm needs to establish an electromagnetic compatibility evaluation index system. Use software simulation and actual testing methods to obtain indicator data, and compare the indicator data with standard values to ensure the correctness and rationality of the indicator data. Subsequently, by solving the judgment matrix, the Analytic Hierarchy Process (AHP) algorithm can calculate the weight of each sub indicator. And the calculation results of the AHP algorithm are substituted into the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) algorithm. Finally, calculate the electromagnetic compatibility performance of each scheme. The improved AHPTOPSIS algorithm can effectively reduce errors caused by subjective human factors and objective factors in theoretical data. This article verifies the correctness of the improved AHP-TOPSIS algorithm by evaluating the electromagnetic compatibility of a high-power electronic system. This article uses the improved AHP-TOPSIS evaluation algorithm to evaluate and compare the electromagnetic compatibility of system design schemes, and ultimately calculates the optimal electromagnetic compatibility performance. The calculation results validate the effectiveness of this method and can provide assistance fo

关键词： Software algorithms Human factors Lead Electromagnetic compatibility Software Matrices Indexes

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A Survey of Route Recommendations: Methods, applications, and Opportunities

arXiv

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arXiv 2024年

作者： Zhang, Shiming Luo, Zhipeng Yang, Li Teng, Fei Li, Tianrui School of Computing and Artificial Intelligence Southwest Jiaotong University China Engineering Research Center of Sustainable Urban Intelligent Transportation Ministry of Education China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University China Manufacturing Industry Chains Collaboration and Information Support Technology Key Laboratory of Sichuan Province Southwest Jiaotong University Sichuan Chengdu611756 China

Nowadays, with advanced information technologies deployed citywide, large data volumes and powerful computational resources are intelligentizing modern city development. As an important part of intelligent transportation, route recommendation and its applications are widely used, directly influencing citizens' travel habits. Developing smart and efficient travel routes based on big data (possibly multi-modal) has become a central challenge in route recommendation research. Our survey offers a comprehensive review of route recommendation work based on urban computing. It is organized by the following three parts: 1) Methodology-wise. We categorize a large volume of classic methods and modern deep learning methods. Also, we discuss their historical relations and reveal the edge-cutting progress. 2) application-wise. We present numerous novel applications related to route commendation within urban computing scenarios. 3) We discuss current problems and challenges and envision several promising research directions. We believe that this survey can help relevant researchers quickly familiarize themselves with the current state of route recommendation research and then direct them to future research trends. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep learning

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MACCoM: A multiple attention and convolutional cross-mixer framework for detailed 2D biomedical image segmentation

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Computers in Biology and Medicine 2024年 179卷 108847-108847页

作者： Ejiyi, Chukwuebuka Joseph Qin, Zhen Ejiyi, Makuachukwu Bennedith Ukwuoma, Chiagoziem Ejiyi, Thomas Ugochukwu Muoka, Gladys Wavinya Gyarteng, Emmanuel S.A. Bamisile, Olusola O. Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu China Pharmacy Department University of Nigeria Nsukka Enugu State Nsukka Nigeria Department of Pure and Industrial Chemistry University of Nigeria Nsukka Enugu State Nsukka Nigeria School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Sichuan Industrial Internet Intelligent Monitoring and Application Engineering Research Center Chengdu University of Technology Chengdu China

The UNet architecture, which is widely used for biomedical image segmentation, has limitations like blurred feature maps and over- or under-segmented regions. To overcome these limitations, we propose a novel network architecture called MACCoM (Multiple Attention and Convolutional Cross-Mixer) – an end-to-end depthwise encoder-decoder fully convolutional network designed for binary and multi-class biomedical image segmentation built upon deeperUNet. We proposed a multi-scope attention module (MSAM) that allows the model to attend to diverse scale features, preserving fine details and high-level semantic information thus useful at the encoder-decoder connection. As the depth increases, our proposed spatial multi-head attention (SMA) is added to facilitate inter-layer communication and information exchange, enabling the network to effectively capture long-range dependencies and global context. MACCoM is also equipped with a convolutional cross-mixer we proposed to enhance the feature extraction capability of the model. By incorporating these modules, we effectively combine semantically similar features and reduce artifacts during the early stages of training. Experimental results on 4 biomedical datasets crafted from 3 datasets of varying modalities consistently demonstrate that MACCoM outperforms or matches state-of-the-art baselines in the segmentation tasks. With Breast Ultrasound Image (BUSI), MACCoM recorded 99.06 % Jaccard, 77.58 % Dice, and 93.92 % Accuracy, while recording 99.50 %, 98.44 %, and 99.29 % respectively for Jaccard, Dice, and Accuracy on the Chest X-ray (CXR) images used. The Jaccard, Dice, and Accuracy for the High-Resolution Fundus (HRF) images are 95.77 %, 74.35 %, and 95.95 % respectively. The findings here highlight MACCoM's effectiveness in improving segmentation performance and its valuable potential in image analysis. © 2024 Elsevier Ltd

关键词： Mixers (machinery)

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Research on UWB/IMU location fusion algorithm based on GA-BP neural network

Research on UWB/IMU location fusion algorithm based on GA-BP...

引用

第40届中国控制会议

作者： Kang Yang Manlu Liu Yu Xie Xinglang Zhang Weidong Wang Songlin Gou Haoxiang Su Special Environment Robot Technology Key Laboratory of Sichuan Province Southwest University of Science and Technology

In order to solve the problem of large errors in single positioning technology in complex indoor environments, a positioning fusion method based on GA-BP neural network is proposed. The internal calibration of the IMU is used to reduce or eliminate the coordinate axis deviation and fixed error of the IMU, and the obtained acceleration, angular velocity, attitude Angle information and the PDR positioning mechanism are used to carry out inertial navigation. UWB positioning technology uses an improved TWR ranging algorithm for ranging, and uses the trilateral ranging method to obtain the corresponding *** BP neural network is used to fuse the data of the two positioning technologies, and the genetic algorithm（GA） is used to optimize the initial weights and thresholds of the BP neural network to improve the performance and prediction accuracy of the network. The experimental results show that the GA-BP neural network integrates the two positioning data and calculates the positioning results. The average positioning error of the GA-BP neural network is 9.6cm, which is about 80% higher than the positioning accuracy of the single positioning method and 43.9% higher than the prediction error of the BP neural network.

关键词： GA-BP neural network IMU UWB

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radiation image denoising method based on speckle splitting

引用

Signal, Image and Video Processing 2022年第4期17卷 1391-1399页

作者： Deng, Hao Zhang, Hua Zhao, Hao Wang, Hai School of Information Engineering Southwest University of Science and Technology Mianyang China Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Southwest University of Science and Technology Mianyang China Department of Automation University of Science and Technology of China Hefei China

For the problem of multiple noises in the visual images captured by CMOS sensors in the $$\gamma $$ radiation environment, this paper proposed a two-stage image denoising method based on speckle splitting to improve the clarity of the $$\gamma $$ radiation scene image. In the first stage, we first losslessly split the noisy image into multiple sub-images by dilated down-sampling, which makes the speckle noise of the original image decomposed into isolated point noise in the sub-images. And then, the isolated point noise is removed by detection-based median filtering. In the second stage, we present a gradient-guided NLM filtering in YUV color space, which further deals with the residual weak noise derived from the subtle difference between the non-salient speckle edge and background pixels. Extensive experiments are carried out on the practical scene images captured from Co60 $$\gamma $$ radiation scene. With the help of our proposed scheme, the quality of noisy image has been obviously improved. Concretely, the PSNR is boosted by 8.17 dB and the SSIM is increased by 0.32. Experimental results demonstrate that the proposed method enjoys state-of-the-art performance in improving the clarity of $$\gamma $$ radiation images.

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The Viscosity Measurement of Ti15Zr60Hf20Si5 and its Calculation

SSRN

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SSRN 2024年

作者： Huang, Jiajia Wu, Liang Li, Xi Zeng, Yi Chen, Jinwei Xiao, Yifeng Zhang, Qiankun State Key Laboratory of Powder Metallurgy Central South University Changsha410083 China School of Mechanical Engineering and Mechanics Xiangtan University Xiangtan411105 China Key Laboratory of Welding Robot and Application Technology of Hunan Province Xiangtan University Xiangtan411105 China School of Physics and Electronic Sciences Changsha University of Science and Technology Changsha410114 China Hunan Provincial Key Laboratory of Flexible Electronic Materials Genome Engineering Changsha University of Science and Technology Changsha410114 China

The study of the viscosity of Ti-Zr-Hf-Si alloy is of great help to prepare UHTCMCs. In this work, the viscosity of Ti15Zr60Hf20Si5 is 11.8 m·Pa·s by the drop oscillation method under electrostatic levitation conditions at 2273 K. For qualitative assessment of the samples, it was found that Ti15Zr60Hf20Si5 does not contain solid phase at 2273 K using experimental analysis (SEM, EPMA, XRD, and TEM). Based on the experimental results, the viscosity database of the pure liquid phase for Ti-Zr-Hf-Si quaternary systems was constructed by the viscosity model in our previous work. © 2024, The Authors. All rights reserved.

关键词： Viscosity

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Combined exposure to multiwalled carbon nanotubes and dibutyl phthalates aggravated airway inflammation in rats

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Food and Chemical Toxicology 2023年 182卷 114188页

作者： He, Suli Peng, Haiyan Wu, Min Yan, Chao Wan, Jian Ye, Xin Zhang, Hongmao Ding, Shumao Hubei Key Laboratory of Genetic Regulation and Integrative Biology School of Life Sciences Central China Normal University Hubei Wuhan 430079 China Liquor Marking Biological Technology and Application of Key Laboratory of Sichuan Province College of Bioengineering Sichuan University of Science & Engineering Yibin 644000 China

Previous work has shown that mice exposed to dibutyl phthalate (DBP) adsorbed onto multi-walled carbon nanotubes (MWCNTs), via tail vein injection, displayed black lesions in their lungs. To investigate the mechanism causing this toxicity in the lung tissue, we performed an experiment with rats, exposing them to DBP adsorbed onto MWCNTs via a tail vein injection for 14 days. The results revealed pulmonary edema and greyish-black lung tissue in the MWCNTs and the MWCNTs + DBP combined exposure groups. In the combined exposure group there was evident alveolar fragmentation and adhesion, and lung tissue sections showed significant levels of black particles. Sections of the non-cartilaginous region of the trachea had significant folding of the pseudostratified ciliated columnar epithelium and marked thickening of the submucosa. In broncho alveolar lavage fluid, the number of leukocytes (WBC), lymphocytes (Lym), neutrophils (Neu), and eosinophils (Eos), as well as levels of immunoglobulin E (IgE), interleukin 6 (IL-6), tumor necrosis factor alpha (TNF-α), and interleukin 1β (IL-1β) were all significantly higher. TNF-α, IL-6, signal transducer and activator of transcription 3 (STAT3), and α-smooth muscle actin (α-SMA) mRNA expression were all elevated in the lung tissue. The combined exposure group, which had considerable airway remodeling, had a greater degree of tracheal constriction and luminal narrowing, according to the results of the α-SMA immunofluorescence assay. According to these experimental findings, the exposure to both MWCNTs and DBP seemed to have a synergistic effect and exacerbated rats' impaired respiratory function that resulted from exposure to MWCNTs alone. © 2023 Elsevier Ltd

关键词： Airway inflammation Asthma Combined exposure Dibutyl phthalate Multi-walled carbon nanotubes

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Continual Learning for Smart City: A Survey

arXiv

引用

arXiv 2024年

作者： Yang, Li Luo, Zhipeng Zhang, Shiming Teng, Fei Li, Tianrui School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu611756 China Engineering Research Center of Sustainable Urban Intelligent Transportation Ministry of Education National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University China Manufacturing Industry Chains Collaboration and Information Support Technology Key Laboratory of Sichuan Province Southwest Jiaotong University Sichuan Chengdu611756 China

With the digitization of modern cities, large data volumes and powerful computational resources facilitate the rapid update of intelligent models deployed in smart cities. Continual learning (CL) is a novel machine learning paradigm that constantly updates models to adapt to changing environments, where the learning tasks, data, and distributions can vary over time. Our survey provides a comprehensive review of continual learning methods that are widely used in smart city development. The content consists of three parts: 1) Methodology-wise. We categorize a large number of basic CL methods and advanced CL frameworks in combination with other learning paradigms including graph learning, spatial-temporal learning, multi-modal learning, and federated learning. 2) application-wise. We present numerous CL applications covering transportation, environment, public health, safety, networks, and associated datasets related to urban computing. 3) Challenges. We discuss current problems and challenges and envision several promising research directions. We believe this survey can help relevant researchers quickly familiarize themselves with the current state of continual learning research used in smart city development and direct them to future research trends. Copyright © 2024, The Authors. All rights reserved.

关键词： Smart city

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