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EFFICIENT NUMERICAL METHODS FOR THE NAVIER-STOKES-NERNST-PLANCK-POISSON EQUATIONS

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arXiv 2023年

作者： Zhou, Xiaolan Xu, Chuanju School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High Performance Scientific Computing Xiamen University Xiamen361005 China

We propose in this paper efficient first/second-order time-stepping schemes for the evolutional Navier-Stokes-Nernst-Planck-Poisson equations. The proposed schemes are constructed using an auxiliary variable reformulation and sophisticated treatment of the terms coupling different equations. By introducing a dynamic equation for the auxiliary variable and reformulating the original equations into an equivalent system, we construct first- and second-order semi-implicit linearized schemes for the underlying problem. The main advantages of the proposed method are: (1) the schemes are unconditionally stable in the sense that a discrete energy keeps decay during the time stepping;(2) the concentration components of the discrete solution preserve positivity and mass conservation;(3) the delicate implementation shows that the proposed schemes can be very efficiently realized, with computational complexity close to a semi-implicit scheme. Some numerical examples are presented to demonstrate the accuracy and performance of the proposed method. As far as the best we know, this is the first second-order method which satisfies all the above properties for the Navier-Stokes-Nernst-Planck-Poisson equations. © 2023, CC BY.

关键词： Numerical methods

PROVABLY CONVERGENT AND ROBUST NEWTON–RAPHSON METHOD: A NEW DAWN IN PRIMITIVE VARIABLE RECOVERY FOR RELATIVISTIC MHD

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arXiv 2024年

作者： Cai, Chaoyi Qiu, Jianxian Wu, Kailiang School of Mathematical Sciences Xiamen University Fujian Xiamen361005 China School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computing Xiamen University Fujian Xiamen361005 China Guangdong Shenzhen518055 China

A long-standing and formidable challenge faced by all conservative numerical schemes for relativistic magnetohydrodynamics (RMHD) equations is the recovery of primitive variables from conservative ones. This process involves solving highly nonlinear equations subject to physical constraints. An ideal solver should be "robust, accurate, and fast—it is at the heart of all conservative RMHD schemes," as emphasized in [S.C. Noble et al., Astrophys. J., 641 (2006), pp. 626–637]. Despite over three decades of research, seeking efficient solvers that can provably guarantee stability and convergence remains an open problem. This paper presents the first theoretical analysis for designing a robust, physical-constraint-preserving (PCP), and provably (quadratically) convergent Newton–Raphson (NR) method for primitive variable recovery in RMHD. Our key innovation is a unified approach for the initial guess, carefully devised based on sophisticated analysis. It ensures that the resulting NR iteration consistently converges and adheres to physical constraints throughout all NR iterations. Given the extreme nonlinearity and complexity of the iterative function, the theoretical analysis is highly nontrivial and technical. We discover a pivotal inequality for delineating the convexity and concavity of the iterative function and establish general auxiliary theories to guarantee the PCP property and convergence. We also develop theories to determine a computable initial guess within a theoretical "safe" interval. Intriguingly, we find that the unique positive root of a cubic polynomial always falls within this "safe" interval. To enhance efficiency, we propose a hybrid strategy that combines this with a more cost-effective initial value. The presented PCP NR method is versatile and can be seamlessly integrated into any RMHD numerical scheme that requires the recovery of primitive variables, potentially leading to a very broad impact in this field. As an application, we incorporate it

关键词： Recovery

OPTIMIZATION ON PRODUCT MANIFOLDS UNDER A PRECONDITIONED METRIC

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arXiv 2023年

作者： Gao, Bin Peng, Renfeng Yuan, Ya-Xiang State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences China State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences University of Chinese Academy of Sciences China

Since optimization on Riemannian manifolds relies on the chosen metric, it is appealing to know that how the performance of a Riemannian optimization method varies with different metrics and how to exquisitely construct a metric such that a method can be accelerated. To this end, we propose a general framework for optimization problems on product manifolds endowed with a preconditioned metric, and we develop Riemannian methods under this metric. Generally, the metric is constructed by an operator that aims to approximate the diagonal blocks of the Riemannian Hessian of the cost function. We propose three specific approaches to design the operator: exact block diagonal preconditioning, left and right preconditioning, and Gauss–Newton type preconditioning. Specifically, we tailor new preconditioned metrics and adapt the proposed Riemannian methods to the canonical correlation analysis and the truncated singular value decomposition problems, which provably accelerate the Riemannian methods. Additionally, we adopt the Gauss–Newton type preconditioning to solve the tensor ring completion problem. Numerical results among these applications verify that a delicate metric does accelerate the Riemannian optimization *** Codes 15A69, 65K05, 65F30, 90C30 Copyright © 2023, The Authors. All rights reserved.

关键词： Cost functions

Pruning Networks With Cross-Layer Ranking & k-Reciprocal Nearest Filters

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IEEE Transactions on Neural Networks and Learning Systems 2023年第11期34卷 9139-9148页

作者： Lin, Mingbao Cao, Liujuan Zhang, Yuxin Shao, Ling Lin, Chia-Wen Ji, Rongrong School of Informatics Xiamen University Media Analytics and Computing Laboratory Department of Artificial Intelligence Xiamen361005 China Tencent Youtu Laboratory Shanghai200233 China School of Informatics Xiamen University Fujian Key Laboratory of Sensing and Computing for Smart City Computer Science Department Xiamen361005 China Inception Institute of Artificial Intelligence Abu Dhabi United Arab Emirates Mohamed Bin Zayed University of Artificial Intelligence Abu Dhabi United Arab Emirates National Tsing Hua University Department of Electrical Engineering and the Institute of Communications Engineering Hsinchu30013 Taiwan Institute of Artificial Intelligence Xiamen University Xiamen361005 China

This article focuses on filter-level network pruning. A novel pruning method, termed CLR-RNF, is proposed. We first reveal a 'long-tail' pruning problem in magnitude-based weight pruning methods and then propose a computation-aware measurement for individual weight importance, followed by a cross-layer ranking (CLR) of weights to identify and remove the bottom-ranked weights. Consequently, the per-layer sparsity makes up the pruned network structure in our filter pruning. Then, we introduce a recommendation-based filter selection scheme where each filter recommends a group of its closest filters. To pick the preserved filters from these recommended groups, we further devise a ${k}$ -reciprocal nearest filter (RNF) selection scheme where the selected filters fall into the intersection of these recommended groups. Both our pruned network structure and the filter selection are nonlearning processes, which, thus, significantly reduces the pruning complexity and differentiates our method from existing works. We conduct image classification on CIFAR-10 and ImageNet to demonstrate the superiority of our CLR-RNF over the state-of-the-arts. For example, on CIFAR-10, CLR-RNF removes 74.1% FLOPs and 95.0% parameters from VGGNet-16 with even 0.3% accuracy improvements. On ImageNet, it removes 70.2% FLOPs and 64.8% parameters from ResNet-50 with only 1.7% top-five accuracy drops. Our project is available at https://***/lmbxμCLR-RNF. © 2012 IEEE.

关键词： Computer architecture

GLOBAL STRONG SOLUTION FOR THE STOCHASTIC TAMED CHEMOTAXIS-NAVIER-STOKES SYSTEM IN R3

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arXiv 2024年

作者： Xu, Fan Zhang, Lei Liu, Bin School of Mathematics and Statistics Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Hubei Wuhan430074 China

In this work, we consider the 3D Cauchy problem for a coupled system arising from the biomathematics, which consists of a chemotaxis model with cubic logistic source and the stochastic tamed Navier-Stokes equations (STCNS, for short). Our main goal is to establish the existence and uniqueness of global strong solution (strong in both the probabilistic and PDE senses) for the 3D STCNS system with large initial data. To achieve this, we first introduce a triple approximation scheme by virtue of the Friedrichs mollifier, frequency truncation operators and cut-off functions, which makes it possible for constructing sufficiently smooth approximation solutions, and facilitating the effective use of stochastic entropy-energy estimates. Then, building on the entropy-energy estimates, we further derive some higher-order energy estimates, which together with the stochastic compactness method permits us to construct the strong solution for the STCNS system. Copyright © 2024, The Authors. All rights reserved.

关键词： Navier Stokes equations

High Order Asymptotic Preserving Finite Difference Weno Schemes with Constrained Transport for Mhd Equations in All Sonic Mach Numbers

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SSRN

SSRN 2023年

作者： Chen, Wei Wu, Kailiang Xiong, Tao School of Mathematical Sciences Xiamen University Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computing Fujian Xiamen361005 China Guangdong Shenzhen518055 China

In this paper, a high-order semi-implicit (SI) asymptotic preserving (AP) and divergencefree finite difference weighted essentially nonoscillatory (WENO) scheme is proposed for magnetohydrodynamic (MHD) equations. We consider the sonic Mach number Ε ranging from 0 to O(1). High-order accuracy in time is obtained by SI implicit-explicit Runge–Kutta (IMEX-RK) time discretization. High-order accuracy in space is achieved by finite difference WENO schemes with characteristic-wise reconstructions. A constrained transport method is applied to maintain a discrete divergence-free condition. We formally prove that the scheme is AP. Asymptotic accuracy (AA) in the incompressible MHD limit is obtained if the implicit part of the SI IMEX-RK scheme is stiffly accurate. Numerical experiments are provided to validate the AP, AA, and divergence-free properties of our proposed approach. Besides, the scheme can well capture discontinuities such as shocks in an essentially nonoscillatory fashion in the compressible regime, while it is also a good incompressible solver with uniform large-time step conditions in the low sonic Mach limit. © 2023, The Authors. All rights reserved.

关键词： Mach number

LbCas12a-nuclease-mediated tiling deletion for large-scale targeted editing of non-coding regions in rice

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Plant Communications 2024年第4期5卷 141-144页

作者： Guigen Ma Fang Yan Bin Ren Zhenwan Lu Hao Xu Fangxi Wu Shaofang Li Daowen Wang Xueping Zhou Huanbin Zhou State Key Laboratory for Biology of Plant Diseases and Insect Pests Institute of Plant ProtectionChinese Academy of Agricultural SciencesBeijing 100193China Key Laboratory of Gene Editing Technologies(Hainan) Ministry of Agricultural and Rural AffairsSanya 572024China Scientific Observing and Experimental Station of Crop Pests in Guilin Ministry of Agriculture and Rural AffairsGuilin 541399China Rice Research Institute Fujian Academy of Agricultural SciencesFuzhou 350019China State Key Laboratory of Vegetable Biobreeding National Engineering Research Center for VegetablesBeijing Vegetable Research CenterBeijing Academy of Agriculture and Forestry ScienceBeijing 100097China College of Agronomy State Key Laboratory of Wheat and Maize Crop Scienceand Center for Crop Genome EngineeringHenan Agricultural UniversityZhengzhou 450046China State Key Laboratory of Rice Biology Institute of BiotechnologyZhejiang UniversityHangzhou 310058China These authors contributed equally to this article

Dear Editor,This study reports a nuclease-mediated tiling deletion(NTD)method that uses LbCas12a nuclease with a tiling CRISPRderived RNA(crRNA)library to efficiently induce numerous nucleotide deletions in non-coding regulatory regions of endogenous rice *** method was applied to non-coding regions of the Green Revolution gene SD1,generating 6 mutants with quantitative variations in plant height,which were then used to investigate associations between genotype and *** is thus a promising tool for molecular rice breeding.

关键词： breeding generating nuclease

Dietary butyrate,lauric acid and stearic acid improve gut morphology and epithelial cell turnover in weaned piglets

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Animal Nutrition 2022年第4期11卷 276-282页

作者： Xianglin Zeng Yuan Yang Junmin Wang Zhaobin Wang Jun Li Yulong Yin Huansheng Yang Hunan International Joint Laboratory of Animal Intestinal Ecology and Health Animal Nutrition and Human Health LaboratorySchool of Life SciencesHunan Normal UniversityChangshaHunan 410081China Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process Key Laboratory of Agro-ecological Processes in Subtropical RegionHunan Provincial Engineering Research Center of Healthy LivestockScientific Observing and Experimental Station of Animal Nutrition and Feed Science in South-CentralMinistry of AgricultureInstitute of Subtropical AgricultureChinese Academy of SciencesChangshaHunan 410125China State Key Laboratory of Food Safety Technology for Meat Products Yinxiang GroupFujian Aonong Biological Science and Technology Group Co.Ltd.Key Laboratory of Swine Nutrition and Feed Science of Fujian ProvinceAonong GroupZhangzhouFujian 363000China College of Pharmacy Changsha Medical UniversityChangshaHunan410219China

This study was to evaluate the effects of the supplementation of saturated fatty acids with different chain lengths on growth performance,intestinal morphology,epithelial cell proliferation,differentiation and apoptosis in weaned ***-two weaned piglets(Duroc×Landrace×Yorkshire,BW=7.81±0.26 kg)were weaned at 21 d and randomly assigned to 1 of 4 experimental treatments:(1)a basal diet(control);(2)control+0.3% butyrate(BT);(3)control+0.3%lauric acid(LA);(4)control+0.3% stearic acid(SA).All piglets were then slaughtered for tissue sampling after having been fed experimental diets for 28 d after *** of BT increased the gain-to-feed ratio(G:F)(P<0.05)compared to piglets fed the control diet from 14 to 28 *** addition,the villus height(VH)to crypt depth(CD)ratio(VH:CD ratio)of the ileum were higher in the BT and LA diets than that of the control diet(P<0.05).The SA-supplemented diet increased ileal VH(P<0.05),whereas the BT-supplemented diet increased jejunal CD(P<0.05).Compared to the control,diets supplemented with BT,LA,or SA all tended to increase jejunal proliferation(Ki67/crypt positive cells)(P=0.190);diets supplemented with BT or SA significantly increased the number of ki67-positive cells in the ileal crypt(P<0.05).Furthermore,in the jejunum,the protein expression of activated caspase 3 and villin were increased in piglets fed BT,LA,or SA diets compared to those on the control diet(P<0.05).In the ileum,compared with the control diet,the BT diet tended to increase the protein level of mammalian phosphorylation target of rapamycin(p-m TOR,P<0.10);LA or SA diets significantly increased p-m TOR protein expression(P<0.05).These results show that dietary supplementation of BT,LA,or SA promotes jejunal cell renewal in weaned *** the same time,increased proliferation of ileal crypt cells by promoting p-m TOR expression has beneficial effects on ileal morphology in weaned piglets.

关键词： Weaned piglet Saturated fatty acid Growth performance Intestinal morphology Proliferation

Emotional Knowledge Self-Distillation in Dialogue

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Emotional Knowledge Self-Distillation in Dialogue

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Jian, Zhongquan Wang, Yancheng Wu, Weichao Yao, Junfeng Wang, Meihong Wu, Qingqiang School of Informatics Xiamen University Xiamen China School of Film Xiamen University Xiamen China School of Computing and Data Science Xiamen University Malaysia Selangor Malaysia School of Mechanics and Civil Engineering China University of Mining & Technology Beijing China Xiamen Key Laboratory of Intelligent Storage and Computing School of Informatics Xiamen University Xiamen China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen China

ISBN: (纸本)9798350368741

Recognizing emotions in dialogues is vital for effective human-computer interaction, yet remains a challenging task in Natural Language Processing (NLP). Previous studies in Emotion Recognition in Conversation (ERC) have primarily focused on contextual features, while overlooking the importance of emotional features in emotion recognition. To address this gap, we focus on the role of emotional features in ERC and propose a novel method, Emotional Knowledge Self-Distillation (EmoKSD1), to enhance the model's emotional sensitivity. In EmoKSD, utterances are enriched with implicit 〈mask〉 tokens to represent conveyed emotions, allowing the distillation of emotional knowledge from explicit emotional tokens to implicit 〈mask〉 tokens, thereby enhancing the model's ability to perceive subtle emotions within the dialogue. Through thorough evaluations on two public ERC datasets (i.e., IEMOCAP and MELD) using proposed coarse-grained utterance distillation and fine-grained token distillation techniques, EmoKSD demonstrates superior performance compared to existing methods, highlighting the significance of emotional features in ERC. © 2025 IEEE.

关键词： Dialogue System Emotion Recognition in Conversation Knowledge Distillation Natural Language Processing