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arXiv 2025年

作者： Chen, Ying Chai, Zhenhua Shi, Baochang School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China The State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

This paper discusses how to develop a high-order multiple-relaxation-time lattice Boltzmann (MRT-LB) model for the general d(≥ 1)-dimensional diagonal-anisotropic diffusion equation. Such an MRT-LB model considers the transformation matrix constructed in a natural way and the DdQ(2d2 + 1) [(2d2 + 1) discrete velocities in d-dimensional space] lattice structure. A key step in developing the high-order MRT-LB model is to determine the additional adjustable relaxation parameters and weight coefficients, which are used to eliminate the truncation errors at some certain orders of the MRT-LB model, while ensuring the stability of the MRT-LB model. In this work, we first present a unified MRT-LB model for the d-dimensional diagonal-anisotropic diffusion equation. Then, through the direct Taylor expansion, we analyze the macroscopic modified equations of the MRT-LB model up to fourth-order at the diffusive scaling, and further derive the conditions that ensure the MRT-LB model to be fourth-order consistent with the diagonal-anisotropic diffusion equation. In particular, when the diagonal-anisotropic diffusion equation is reduced to the isotropic type, we propose another MRT-LB model with the DdQ(2d+ 1) lattice structure [fewer discrete velocities than the DdQ(2d2 + 1) lattice structure], and the fourth-order conditions are similarly derived. Additionally, we also construct the fourth-order initialization scheme for the present LB method. After that, the condition which guarantees that the MRT-LB model can satisfy the stability structure is explicitly given, and we would like to point out that from a numerical perspective, once the stability structure is satisfied, the MRT-LB model must be L2 stable. In combination with the fourth-order consistent and L2 stability conditions, the relaxation parameters and weight coefficients of the MRT-LB model can be automatically given by a simple computer code. Finally, we perform numerical simulations of several benchmark problems, and f

关键词： Anisotropy

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Convexity of the implicit Lagrangian

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1997年第2期92卷 331-341页

作者： Peng, JM Assistant Professor State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific Engineering Computing Academia Sinica Beijing China

The implicit Lagrangian has attracted much attention recently because of its utility in reformulating complementarity and variational inequality problems as unconstrained minimization problems, II was first proposed by Mangasarian and Solodov as a merit function for the nonlinear complementarity problem (Ref. 1). Three open problems were also raised in the same paper, This paper addresses, among other issues, one of these problems by giving the properties of the implicit Lagrangian and establishing its convexity under appropriate assumptions.

关键词： complementarity problems implicit Lagrangian functions

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A Clustering-Based Color Reordering Method for Reversible Data Hiding in Palette Images

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IET Image Processing 2025年第1期19卷

作者： Deng, Jianxuan Chen, Yi Wang, Hongxia Guo, Chun Cui, Yunhe Shen, Guowei State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang China Engineering Research Center of Text Computing & Cognitive Intelligence Ministry of Education Guizhou University Guiyang China School of Cyber Science and Engineering Sichuan University Chengdu China

A recent research work pointed out that the reversible data hiding algorithms proposed for gray-scale images can be implemented on the reconstructed palette images to improve embedding capacity and visual quality by reordering the color table. However, the reordering effect has a significant impact on performance improvement. Therefore, we propose a clustering-based color reordering method for reversible data hiding in palette images to improve the reordering effect and further enhance the performance. In this method, we first design a centroid initialization method to select the initial centroids and then exploit the K-means algorithm to generate (Formula presented.) clusters for the colors in the original color table. In the following, our proposed method, respectively, reorders the colors of these clusters by a greedy strategy and concatenates them into the reordered color table. Based on the relationship between the original and the reordered color tables, a novel index matrix can be reconstructed. Finally, state-of-the-art reversible data hiding algorithms can be implemented on the reconstructed index matrix for performance improvement. Since our proposed method improves the reordering effect, enhances the correlation of the reconstructed index matrix, and reduces the length of the encoded location map, the maximal embedding capacities and the visual quality under the fixed embedding capacities are improved. We conducted experiments on two image datasets and six standard images to verify that the performance improvement of our proposed reordering method is better than that of the state-of-the-art methods. © 2025 The Author(s). IET Image Processing published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Embeddings

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Clustering-based Low Rank Approximation Method

arXiv

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arXiv 2025年

作者： Zhu, Yujun Zhu, Jie Arshad, Hizba Wang, Zhongming Ming, Ju School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan China Department of Mathematics and Statistics Florida International University MiamiFL United States

We propose a clustering-based generalized low rank approximation method, which takes advantage of appealing features from both the generalized low rank approximation of matrices (GLRAM) and cluster analysis. It exploits a more general form of clustering generators and similarity metrics so that it is more suitable for matrix-structured data relative to conventional partitioning methods. In our approach, we first pre-classify the initial matrix collection into several small subset clusters and then sequentially compress the matrices within the clusters. This strategy enhances the numerical precision of the low-rank approximation. In essence, we combine the ideas of GLRAM and clustering into a hybrid algorithm for dimensionality reduction. The proposed algorithm can be viewed as the generalization of both techniques. Theoretical analysis and numerical experiments are established to validate the feasibility and effectiveness of the proposed algorithm. © 2025, CC BY-NC-ND.

关键词： Matrix algebra

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A neural kernel framework for relation extraction

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Expert Systems with Applications 2025年 286卷

作者： Wang, Kai Chen, Yanping Yang, Weizhe Huang, Ruizhang Qin, Yongbin Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry College of Computer Science and Technology Guizhou University China State Key Laboratory of Public Big Data Guizhou University China

Relation extraction (RE) poses significant challenges due to the complexity of identifying semantic relationships between overlapping entity pairs within sentences. Traditional kernel-based methods effectively leverage instance-level similarities but heavily depend on manually designed kernel functions, requiring substantial domain expertise and limiting their flexibility. On the other hand, neural network approaches excel at automatically learning abstract feature representations but typically neglect critical instance-specific information, potentially missing valuable relational details during inference. These limitations motivate the exploration of a hybrid approach that effectively integrates the strengths of traditional kernels with the representational power of neural networks. In this paper, we propose a neural kernel framework designed to bridge this critical gap. The proposed framework employs neural kernels, whose parameters are initialized based on task-specific objectives and optimized through neural training procedures, enabling adaptive learning of similarity measures without relying on handcrafted kernel functions. By maintaining instance-level details through annotated training examples, neural kernels create discriminative, flexible decision boundaries tailored specifically to the relation extraction task. We further develop three complementary neural kernel components, instance kernel, description kernel, and cluster kernel, to show the advantages of kernel substitution. Extensive experiments on the ACE 2005, SemEval 2010, and CoNLL 2004 datasets demonstrate that our neural kernel framework significantly outperforms existing state-of-the-art methods, achieving F1-scores of 88.11 %, 91.08 %, and 98.63 %, respectively. © 2025 Elsevier Ltd

关键词： Natural language processing systems

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SELF-SUPERVISED DIFFUSION MRI DENOISING VIA ITERATIVE AND STABLE REFINEMENT

arXiv

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arXiv 2025年

作者： Wu, Chenxu Kong, Qingpeng Jiang, Zihang Kevin Zhou, S. School of Biomedical Engineering Division of Life Sciences and Medicine USTC China MIRACLE Center Suzhou Institute for Advance Research USTC China State Key Laboratory of Precision and Intelligent Chemistry USTC China Key Laboratory of Intelligent Information Processing of CAS Institute of Computing Technology CAS China

Magnetic Resonance Imaging (MRI), including diffusion MRI (dMRI), serves as a "microscope" for anatomical structures and routinely mitigates the influence of low signal-to-noise ratio scans by compromising temporal or spatial resolution. However, these compromises fail to meet clinical demands for both efficiency and precision. Consequently, denoising is a vital preprocessing step, particularly for dMRI, where clean data is unavailable. In this paper, we introduce Di-Fusion, a fully self-supervised denoising method that leverages the latter diffusion steps and an adaptive sampling process. Unlike previous approaches, our single-stage framework achieves efficient and stable training without extra noise model training and offers adaptive and controllable results in the sampling process. Our thorough experiments on real and simulated data demonstrate that Di-Fusion achieves state-of-the-art performance in microstructure modeling, tractography tracking, and other downstream tasks. Code is available at https://***/FouierL/Di-Fusion. Copyright © 2025, The Authors. All rights reserved.

关键词： Signal to noise ratio

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Effects of initiator on steam cracking of naphtha model compound by high-throughput simulation

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Chemical engineering Science 2025年 314卷

作者： Mao, Yaoliang Shen, Yudong Hong, Xiaodong Liao, Zuwei Wang, Jingdai Yang, Yongrong State Key Laboratory of Chemical Engineering College of Chemical and Biological Engineering Zhejiang University Hangzhou310027 China Engineering Research Center of Functional Materials Intelligent Manufacturing of Zhejiang Province ZJU-Hangzhou Global Scientific and Technological Innovation Center Hangzhou311215 China

Incorporating initiators in hydrocarbon cracking has been proven to enhance the conversion of hydrocarbons and improve the resulting product distribution. However, screening novel initiators is merely via an experiment-driven trial-and-error approach, which is resource-intensive, time-consuming, and less effective in exploring new chemical spaces. There needs to be more definitive guidance on selecting effective initiator structures and designing optimal initiators. This study integrates mechanism modeling and process simulation to investigate the co-cracking reactions of initiators with the naphtha model compound. The effects of different functional groups on olefin yield and the mechanism by which initiators modulate reaction network are clarified. A comprehensive product distribution dataset is established, comprising 5,243 sample points for co-cracking of initiators with n-hexane and 4,290 sample points for initiators with iso-hexane. For n-hexane, most initiators lead to a decrease in ethylene yield while an increase in n-hexane conversion and propylene and butadiene yield. For iso-hexane, most initiators inhibit its decomposition, reducing the yield of ethylene and propylene but promoting the butadiene yield. The hydroxyl (OH) group and C-N single bond effectively improve the olefin yield. Methyl diazene can regulate product distribution by significantly increasing C5H10, C4H8, and •C3H5 consumption ratios, forming •C5H9, •C4H7, and C3H6, with relative values of 1950 %, 258 %, and 121 %, respectively. Most initiators adjust the product distribution in the n-hexane system by promoting the conversion of n-hexane to 2,3-hexyl radicals. In contrast, in the iso-hexane system, most initiators increase the proportion of •C3H5 and •C3H7 forming C3H6. The results provide valuable insights into designing more effective initiators and optimizing hydrocarbon cracking processes. © 2025 Elsevier Ltd

关键词： Initiators (chemical)

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Influence of Froude Number on the Development and Evolution of Secondary Flows in a Sharply Curved Bend: An Experimental and Numerical Study

SSRN

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SSRN 2025年

作者： Hu, Chengwei Liu, Yujiao Yu, Minghui River Research Department Yangtze River Scientific Research Institute Wuhan430010 China Key Laboratory of River and Lake Regulation and Flood Control in the Middle and Lower Reaches of the Changjiang River of Ministry of Water Resources Yangtze River Scientific Research Institute Wuhan430010 China State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan University Wuhan430072 China

Meandering rivers sculpt landscapes and foster diverse ecosystems, with secondary flows in bends exerting a pivotal influence on sediment transport and channel morphology. Although the Froude number typically remains below 0.3 in natural meanders, the interplay of secondary flows under these low-Froude conditions is still poorly understood. This study addresses this knowledge gap by systematically examining the influence of Froude numbers (Fr = 0.12-0.21) on secondary flow structures in sharply curved channels through high-resolution flume experiments and numerical simulations. Results reveal that even slight variations in Froude number can markedly alter vortex dynamics and secondary flow complexity, underscoring a delicate balance between inertial and turbulent forces. In particular, the stability of S2-type secondary flows depends on the precise alignment of advective, centrifugal, and turbulence-induced vorticity. Minor shifts in inertial forcing can rapidly destabilize S2, leading to significant changes in velocity distributions. Additionally, a time or spatial lag between the onset of secondary circulation and the point of maximum velocity inversion points to a dynamic, two-way feedback between the secondary flow and the main flow, evolving from robust vortex growth at lower Fr to flow decay at higher Fr. These findings advance our understanding of secondary flow mechanisms in natural rivers and offer practical insights for river engineering and flood management, informing more effective strategies for sediment control and bank stability. © 2025, The Authors. All rights reserved.

关键词： Froude number

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Quantum oscillation in Hopf-link semimetals

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Physical Review B 2025年第20期111卷 L201103-L201103页

作者： Lei Shi Xiaoxiong Liu C. M. Wang Tianyu Liu Hai-Zhou Lu X. C. Xie State Key Laboratory of Quantum Functional Materials Department of Physics and Guangdong Basic Research Center of Excellence for Quantum Science Southern University of Science and Technology (SUSTech) Shenzhen 518055 China Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area (Guangdong) Shenzhen 518045 China Department of Physics Shanghai Normal University Shanghai 200234 China International Quantum Academy Shenzhen 518048 China Shenzhen Key Laboratory of Quantum Science and Engineering Shenzhen 518055 China International Center for Quantum Materials School of Physics Peking University Beijing 100871 China Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai 200433 China Hefei National Laboratory Hefei 230088 China

Since the discovery of the relation between the Chern number and quantum Hall effect, searching for observables of topological invariants has been an intriguing topic. Topological Hopf-link semimetals have attracted tremendous interest, in which the conduction and valence energy bands touch at linked nodal lines. However, it is challenging to identify this sophisticated topology. We propose to use the quantum oscillation in strong magnetic fields to probe the Hopf links. For a generic model of a Hopf-link semimetal that captures the linked-trivial phase transition, we figure out the phase shifts of oscillation for all Fermi pockets in all magnetic-field directions, by presenting self-consistent results from the Fermi-surface tomography, Landau fan diagram, and electrical resistivity. As the magnetic field is rotated, the phase shifts exhibit a unique pattern, which could help to identify Hopf links in real materials, such as those in Li2NaN.

关键词： Hall effect

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EXPERIMENTAL STUDY OF THE ASYNCHRONOUS MULTISPLITTING RELAXATION METHODS FOR THE LINEAR COMPLEMENTARITY PROBLEMS

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Journal of Computational Mathematics 2002年第6期20卷 561-574页

作者： Zhong-zhi Bai(state key laboratory of scientific/engineering computing, Institute of Computational Mathematicsand scientific/engineering computing, Academy of Mathematics and System Sciences, ChineseAcademy of Sciences, Beijing 100080, China) Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and System Sciences Chinese Academy of Sciences State Key Laboratory of Scientific/Engineering ComputingCAS 北京 100080

Presents a study of the numerical behaviors of the relaxed asynchronous multisplitting methods for linear complementarity problems by solving typical problems from practical applications on a real multiprocessor system. Description of the tested problems and computing environment used in the computations; Description of the asynchronous multisplitting unsymmetric accelerated overrelaxation method; Discussion of results.

关键词： linear complementarity problem matrix multisplitting asynchronous iterative methods numerical experiment

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