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arXiv 2025年

作者： Meng, Lingdi Peng, Tian-Cai Hu, Zhi Xu, Siqi Lan, Jiangshan Mondal, Chandan Wang, Guo-Li Zhao, Xingbo Vary, James P. Department of Physics Hebei University Baoding071002 China Institute of Modern Physics Chinese Academy of Sciences Gansu Lanzhou730000 China School of Physical Science and Technology Lanzhou University Lanzhou730000 China Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu Province Lanzhou University Lanzhou730000 China Key Laboratory of Quantum Theory and Applications of MoE Lanzhou University Lanzhou730000 China Research Center for Hadron and CSR Physics Lanzhou University Institute of Modern Physics of CAS Lanzhou730000 China Ibaraki305-0801 Japan School of Nuclear Science and Technology University of Chinese Academy of Sciences Beijing100049 China Department of Physics and Astronomy Iowa State University AmesIA50011 United States Advanced Energy Science and Technology Guangdong Laboratory Guangdong Huizhou516000 China Key Laboratory of High-precision Computation Application of Quantum Field Theory of Hebei Province Baoding China

Within the basis light-front quantization framework, we compute the masses and light-front wave functions of the Λb baryon and its isospin triplet counterparts Σ+b , Σ0b, and Σ−b using a light-front effective Hamiltonian in the leading Fock sector. These wave functions are obtained as eigenstates of the effective Hamiltonian, which incorporates the one-gluon exchange interaction with fixed coupling and a three-dimensional confinement potential. With the quark masses and the couplings as adjustable parameters, the computed masses are set within the experimental range. The resulting predictions for their electromagnetic properties align well with other theoretical calculations. Additionally, the parton distribution functions (PDFs) of these baryons are obtained for the first time, with gluon and sea quark distributions dynamically generated through QCD evolution of the valence quark PDFs. © 2025, CC BY.

关键词： Elementary particles

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Unveiling the inverse Hall-Petch behavior and failure mechanism in nanocrystalline high-entropy carbides

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Physical Review Materials 2025年第5期9卷 053604-053604页

作者： Jun Li Kun Luo Qi An Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanics Wuhan University of Technology Wuhan 430070 China Department of Materials Science and Engineering Iowa State University Ames Iowa 50011 USA

The deformation behaviors of nanocrystalline high-entropy ceramics are complex and remain poorly understood, despite the critical importance to their performance and applications. Here, we employed molecular dynamics simulations to examine the shear deformation mechanisms of nanocrystalline high-entropy carbide ceramic, n−(Ti0.2Zr0.2Nb0.2Hf0.2Ta0.2)C, across grain sizes ranging from 4.0 to 12.0 nm. The atomic interactions were described using a machine-learning force field, which was developed based on deep neural networks. The simulation results reveal that the main deformation mechanism of n−(Ti0.2Zr0.2Nb0.2Hf0.2Ta0.2)C is grain boundary (GB) sliding, which then leads to the nucleation and growth of cavities and cracks at the GBs, ultimately resulting in intergranular fracture. For larger grains, the reduced soft GB volume fraction inhibits the GB sliding, leading to an inverse Hall-Petch behavior in n−(Ti0.2Zr0.2Nb0.2Hf0.2Ta0.2)C. Additionally, GB segregation often strengthens GBs, thereby enhancing the strength of n−(Ti0.2Zr0.2Nb0.2Hf0.2Ta0.2)C and mitigating intergranular fracture. These findings shed light on the deformation behaviors and underlying mechanisms of nanocrystalline high-entropy carbide ceramics, and they provide important guidance for the design of high-entropy ceramics with superior performance.

关键词： Cracks

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Rapid identification of Astragalus membranaceus processing with rice water based on intelligent color recognition and multi-source information fusion technology

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Chinese Herbal Medicines 2025年

作者： Guo, Dongmei Pan, Yijing Wang, Shunshun Ming, Kehong Chi, Qingjia Wang, Chunli Xu, Kang Hubei Provincial Engineering Technology Research Center for Chinese Medicine Processing School of Pharmacy Hubei University of Chinese Medicine Wuhan 430065 China Hubei Shizhen Laboratory Wuhan 430065 China Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanics Department of Mechanics and Engineering Structure Wuhan University of Technology Wuhan 430065 China School of Laboratory Medicine Hubei University of Chinese Medicine Wuhan 430065 China Center of Traditional Chinese Medicine Modernization for Liver Diseases Hubei University of Chinese Medicine Wuhan 430065 China

Objective: This study seeks to optimize the processing parameters for Astragalus membranaceus with rice water (AM-RW), establish quality evaluation standards, and develop a rapid multilayer perceptron (MLP) model for classification. This model facilitates accurate identification of AM-RW at various processing stages, providing a scientific reference for the quality assessment of traditional Chinese medicine products. Methods: Optimization of AM-RW was achieved using a single-factor test and Box-Behnken design response surface methodology to determine the optimal process parameters. The Watershed Algorithm was applied to segment images of AM tablets, and the numpy and pandas libraries were used to collect color data from these tablets. The study also explored the correlation between R, G, B, and L color values and calycosin-7-glucoside content. A rapid classification model based on MLP was developed, utilizing color values, hardness values, and calycosin-7-glucoside content of AM-RW with various processing degrees. Results: The study identified the optimal parameters for AM-RW as 20 mL of rice water, a frying temperature of 180°C, and a frying time of 7 min. The average color values for the best-processed products fell within the normal distribution range: R value (94.83 ± 8.57), G value (96.1 ± 19.37), B value (36.84 ± 5.93), and L value (89.55 ± 12.24). The rapid identification model using MLP demonstrated high accuracy and reliability, achieving an accuracy rate of 94 % in the classification process. Conclusions: The response surface method effectively optimizes the precise processing parameters of AM-RW. Furthermore, the MLP-based model can accurately classify AM-RW with varying degrees of processing, providing a valuable reference for the expedited identification of processing quality in traditional Chinese medicine products. © 2025 Tianjin Press of Chinese Herbal Medicines

关键词： intelligent color extraction multilayer perceptron optimization of processes quality evaluation rice water Astragalus membranaceus

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Design of a Capsule Robot System for Gastric Hemorrhage Detection using Luminol

Design of a Capsule Robot System for Gastric Hemorrhage Dete...

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IEEE International Conference on Mechatronics and Automation

作者： Yuchen Mao Jian Guo Shuxiang Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Application Complicated Systems and Intelligent Robot Laboratory School of Electrical Engineering and Automation Tianjin University of Technology Binshui Xidao Extension 391 Tianjin China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen China Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing China

Gastric hemorrhage in upper gastrointestinal bleeding is an obvious indicator of deteriorating gastric disease. This paper proposes a capsule robot system for detecting bleeding in the stomach. The patient ingests a capsule robot containing luminol reagent, which detects bleeding in the stomach via chemiluminescence. The MCU receives the optical sensor signal, and the data is transmitted via radio frequency. The external lower computer receives and forwards the data to the upper computer for processing and display. The data is used to determine the presence and amount of stomach bleeding. Chemiluminescence is an excellent sensor, requiring no external energy supply, and demonstrating excellent sensitivity and selectivity. Combining chemical and electronic sensors presents opportunities for further development. Capsule robot detection reduces the discomfort and risk of secondary injury associated with traditional endoscopy. This paper establishes an experimental platform using porcine blood to simulate human blood, demonstrating the feasibility of the system.

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Generalized Estimating Equations for Hearing Loss Data with Specified Correlation Structures

arXiv

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arXiv 2023年

作者： Wei, Zhuoran Zhu, Hanbing Curhan, Sharon Curhan, Gary Wang, Molin Department of Biostatistics Harvard T.H. Chan School of Public Health BostonMA United States Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University Shanghai China Harvard Medical School BostonMA United States Channing Division of Network Medicine Department of Medicine Brigham and Women’s Hospital BostonMA United States Division of Renal Medicine Department of Medicine Brigham and Women’s Hospital BostonMA United States Department of Epidemiology Harvard T.H. Chan School of Public Health BostonMA United States

Due to the nature of pure-tone audiometry test, hearing loss data often has a complicated correlation structure. Generalized estimating equation (GEE) is commonly used to investigate the association between exposures and hearing loss, because it is robust to misspecification of the correlation matrix. However, this robustness typically entails a moderate loss of estimation efficiency in finite samples. This paper proposes to model the correlation coefficients and use second-order generalized estimating equations to estimate the correlation parameters. In simulation studies, we assessed the finite sample performance of our proposed method and compared it with other methods, such as GEE with independent, exchangeable and unstructured correlation structures. Our method achieves an efficiency gain which is larger for the coefficients of the covariates corresponding to the within-cluster variation (e.g., ear-level covariates) than the coefficients of cluster-level covariates. The efficiency gain is also more pronounced when the within-cluster correlations are moderate to strong, or when comparing to GEE with an unstructured correlation structure. As a real-world example, we applied the proposed method to data from the Audiology Assessment Arm of the Conservation of Hearing Study, and studied the association between a dietary adherence score and hearing loss. Copyright © 2023, The Authors. All rights reserved.

关键词： Audition

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Direct Expression for One-Loop Tensor Reduction with Lorentz Indices via Generating Function

arXiv

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arXiv 2025年

作者： Hu, Chang Hu, Yifan Shen, Jiyuan College of Physics Science and Technology Hebei University Baoding071002 China Hebei Key Laboratory of High-precision Computation and Application of Quantum Field Theory Baoding071002 China Hebei Research Center of the Basic Discipline for Computational Physics Baoding071002 China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study UCAS Hangzhou310024 China University of Chinese Academy of Sciences Beijing100049 China Institute of Theoretical Physics Chinese Academy of Sciences Beijing100190 China

In [1], we derived a direct expression for one-loop tensor reduction using generating functions and Feynman parametrization in projective space, avoiding recursive relations. However, for practical applications, this expression still presents two challenges: (1) While the final reduction coefficients are expressed in terms of the dimension D and Mandelstam variables, the given expression explicitly contains irrational functions;(2) The expression involves an auxiliary vector R, which can be eliminated via differentiation ∂/∂R , but the presence of irrational terms making differentiation cumbersome. (3) Most practical applications require the tensor form with Lorentz indices. In this paper, we provide a rational form of the reduction coefficients with Lorentz indices, free from recursion. Additionally, We provide a pure Wolfram Mathematica implementation of the code. Our practical tests demonstrate that this direct expression achieves significantly higher computational efficiency compared to the traditional Passarino-Veltman (PV) reduction or other recursion-based methods. © 2025, CC0.

关键词： Tensors

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An asymptotic analysis of minibatch-based momentum methods for linear regression models

arXiv

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arXiv 2021年

作者： Gao, Yuan Zhu, Xuening Qi, Haobo Li, Guodong Zhang, Riquan Wang, Hansheng School of Statistics East China Normal University Shanghai China Key Laboratory of Advanced Theory and Application in Statistics and Data Science - MOE East China Normal University Shanghai China School of Data Science Fudan University Shanghai China Guanghua School of Management Peking University Beijing China Department of Statistics and Actuarial Science University of Hong Kong Hong Kong

Momentum methods have been shown to accelerate the convergence of the standard gradient descent algorithm in practice and theory. In particular, the minibatch-based gradient descent methods with momentum (MGDM) are widely used to solve large-scale optimization problems with massive datasets. Despite the success of the MGDM methods in practice, their theoretical properties are still underexplored. To this end, we investigate the theoretical properties of MGDM methods based on the linear regression models. We first study the numerical convergence properties of the MGDM algorithm and further provide the theoretically optimal tuning parameters specification to achieve faster convergence rate. In addition, we explore the relationship between the statistical properties of the resulting MGDM estimator and the tuning parameters. Based on these theoretical findings, we give the conditions for the resulting estimator to achieve the optimal statistical efficiency. Finally, extensive numerical experiments are conducted to verify our theoretical results. © 2021, CC BY.

关键词： Gradient methods

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Native spaces and generalization of Wu functions

arXiv

引用

arXiv 2023年

作者： Huang, Yixuan Wu, Zongmin Zhu, Shengxin School of Mathematics Beijing Normal University China Laboratory of Mathematics and Complex Systems Ministry of Education China Shanghai Key Laboratory for Contemporary Applied Mathematics School of Mathematical Sciences Fudan University Shanghai China Shanghai Center for Mathematical Sciences Shanghai China School of Big Data and Statistics Anhui University Hefei China Research Center for Mathematics Advanced Institute of Natural Science Beijing Normal University Zhuhai519087 China Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International College Zhuhai519087 China

We prove that the native space of a Wu function is a dense subspace of a Sobolev space. An explicit characterization of the native spaces of Wu functions is given. Three definitions of Wu functions are introduced and proven to be equivalent. Based on these new equivalent definitions and the so called f-form tricks, we can generalize the Wu functions into the even-dimensional spaces R2k, while the original Wu functions are only defined in the odd-dimensional spaces R2k+1. Such functions in even-dimensional spaces are referred to as the ‘missing Wu functions’. Furthermore we can generalize the Wu functions into ‘fractional’-dimensional spaces. We call all these Wu functions the generalized Wu functions. The closed form of the generalized Wu functions are given in terms of hypergeometric functions. Finally we prove that the Wu functions and the missing Wu functions can be written as linear combinations of the generalized Wendland *** Codes 65J05, 33C90, 41A05, 41A30, 41A65, 41A63 Copyright © 2023, The Authors. All rights reserved.

关键词： Sobolev spaces

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Robust Online Detection in Serially Correlated Directed Network

arXiv

引用

arXiv 2021年

作者： Yu, Miaomiao Zhou, Yuhao Tsung, Fugee Key Laboratory of Advanced Theory and Application in Statistics and Data Science MOE Academy of Statistics and Interdisciplinary Sciences East China Normal University Shanghai China Department of Statistics and Operations Research University of North Carolina at Chapel Hill Chapel HillNC27599 United States Department of Industrial Engineering and Decision Analytics Hong Kong University of Science and Technology Kowloon Hong Kong

As the complexity of production processes increases, the diversity of data types drives the development of network monitoring technology. This paper mainly focuses on an online algorithm to detect serially correlated directed networks robustly and sensitively. First, we consider a transition probability matrix to resolve the double correlation of primary data. Further, since the sum of each row of the transition probability matrix is one, it standardizes the data, facilitating subsequent modeling. Then we extend the spring length based method to the multivariate case and propose an adaptive cumulative sum (CUSUM) control chart on the strength of a weighted statistic to monitor directed networks. This novel approach assumes only that the process observation is associated with nearby points without any parametric time series model, which is in line with reality. Simulation results and a real example from metro transportation demonstrate the superiority of our design. Copyright © 2021, The Authors. All rights reserved.

关键词： Digital storage

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Dependency, Reciprocity, and Mentorship in Long-Term Research Collaboration: A Co-Authorship Matrix-Based Multivariate Time Series Analysis

SSRN

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SSRN 2023年

作者： Zhu, Yongjun Kim, Donghun Jiang, Ting Zhao, Yi He, Jiangen Chen, Xinyi Lou, Wen Department of Library and Information Science Yonsei University Seoul Korea Republic of Department of Library and Information Science Sungkyunkwan University Seoul Korea Republic of School of Economics and Management Nanjing University of Science and Technology Nanjing China School of Information Sciences The University of Tennessee Knoxville United States Department of Cultural Media Yonsei University Seoul Korea Republic of Faculty of Economics and Management East China Normal University Shanghai China Key Laboratory of Advanced Theory and Application in Statistics and Data Science East China Normal University Ministry of Education of China Shanghai China

In this study, we examine the roles of dependency, reciprocity, and mentorship in the prediction of long-term research collaboration in five disciplines. We use co-authorship matrix-based multivariate time series features and interpretable machine learning to train long-term collaboration prediction models and interpret the feature importance of trained models. Overall, long-term research collaboration that is defined using various standards was rare across the examined disciplines, and the prediction results were moderate to good. We found dependency, reciprocity, and mentorship to have different roles in different disciplines. Among the three, mentorship was important in predicting long-term research collaboration in Agriculture, Geology, and Library and Information Science. Reciprocity, which measures the interdependence between two researchers was important to prediction in the fields of Agriculture and Geology. Finally, dependency was important in all the disciplines with varying degrees of importance. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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