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Convolution Type of Metaplectic Cohen's Distribution Time-Frequency Analysis Theory, Method and Technology

IEEE Transactions on Information Theory 2025年第3期71卷 2292-2314页

作者： Cui, Manjun Zhang, Zhichao Han, Jie Chen, Yunjie Cao, Chunzheng Nanjing University of Information Science and Technology School of Mathematics and Statistics Center for Applied Mathematics of Jiangsu Province Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing210044 China Nanjing University of Information Science and Technology School of Mathematics and Statistics Nanjing210044 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Hainan Normal University Key Laboratory of Computational Science and Application of Hainan Province Haikou571158 China Nanjing University of Information Science and Technology School of Remote Sensing and Geomatics Engineering Nanjing210044 China

The conventional Cohen's distribution can't meet the requirement of additive noises jamming signals high-performance denoising under the condition of low signal-to-noise ratio, it is necessary to integrate the metaplectic transform for non-stationary signal fractional domain time-frequency analysis. In this paper, we embark on blending time-frequency operators and coordinate operator fractionizations to formulate the definition of the joint fractionizations metaplectic Wigner distribution (JFMWD), based on which we integrate the generalized metaplectic convolution to address the unified representation issue of the convolution type of metaplectic Cohen's distribution (CMCD), whose special cases and essential properties are also derived. We blend Wiener filter principle and fractional domain filter mechanism of the metaplectic transform to design the least-squares adaptive filter method in the JFMWD domain, giving birth to the least-squares adaptive filter-based CMCD whose kernel function can be adjusted with the input signal automatically to achieve the minimum mean-square error (MSE) denoising in Wigner distribution domain. We discuss the optimal symplectic matrices selection strategy of the proposed adaptive CMCD through the minimum MSE minimization modeling and solving. Some examples are also carried out to demonstrate that the proposed filtering method outperforms some state-of-the-arts including the classical Gaussian filter, the Cohen's distribution filtering methods with fixed kernel functions, the classical Wiener filter, the adaptive generalized linear canonical convolution-based filtering method, the adaptive Cohen's distribution filtering method, the adaptive JFMWD-based Cohen's distribution filtering method, and the adaptive generalized metaplectic convolution-based Cohen's distribution filtering method in noise suppression. © 1963-2012 IEEE.

关键词： Adaptive filtering

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Barrier effects on the kinetics of cohesin-mediated loop extrusion

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Biophysical Journal 2025年第9期124卷 1462-1477页

作者： Chen, Leiyan Zhang, Zhenquan Wang, Zihao Hong, Liu Wang, Haohua Zhang, Jiajun Guangdong Province Key Laboratory of Computational Science Sun Yat-sen University Guangzhou 510275 China School of Mathematics Sun Yat-sen University Guangzhou 510275 China School of Mathematics and Statistics Hainan University Haikou 570228 China

Chromosome organization mediated by structural maintenance of chromosome complexes is crucial in many organisms. Cohesin extrudes chromatin into loops that are thought to lengthen until it is obstructed by CTCF proteins. In complex cellular environments, the loop extrusion machinery may encounter other chromatin-binding proteins. How these proteins interfere with the cohesin-meditated extrusion process is largely unexplored, but recent experiments have shown that some proteins serve as physical barriers that block cohesin translocation. Other proteins containing a cohesin-interaction motif serve as chemical barriers to induce cohesin pausing through interactions with it. Here, we develop an analytically solvable approach for the loop extrusion model incorporating barriers to investigate the effect of the barrier on the passive extrusion process. To further quantify the impact of barriers, we calculate the mean looping time it takes for cohesin to translocate to form a stable loop before dissociation. Our finding reveals that the physical barrier can accelerate the loop formation, and the degree of acceleration is closely related to the impedance strength of the physical barrier. In particular, the synergy of the cohesin loading site and the physical barrier site accelerates loop formation more significantly. The proximity of the cohesin loading site to the barrier site facilitates the rapid formation of stable loops in long genomes, which implies loop extrusion and chromatin-binding proteins might shape functional genomic organization. Conversely, chemical barriers consistently impede loop formation, with increasing impedance strength of the chemical barrier leading to longer loop formation time. Our study contributes to a more comprehensive understanding of the complexity of the loop extrusion process, providing a new perspective on the potential mechanisms of gene regulation. © 2025 Biophysical Society

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Maize transcription factor ZmEREB167 negatively regulates starch accumulation and kernel size

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Journal of Genetics and Genomics 2025年第3期52卷 411-421页

作者： Xiangyu Qing Jianrui Li Zhen Lin Wei Wang Fei Yi Jian Chen Qiujie Liu Weibin Song Jinsheng Lai Baojian Chen Haiming Zhao Zhijia Yang State Key Laboratory of Maize Bio-breeding Key Laboratory of Genome Editing Research and ApplicationMinistry of Agriculture and Rural AffairsDepartment of Plant Genetics and BreedingNational Maize Improvement CenterCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijing 100193China State Key Laboratory of Crop Gene Resources and Breeding/Institute of Crop Sciences Chinese Academy of Agricultural SciencesBeijing 100081China Engineering Research Center of Plant Growth Regulator College of Agronomy and BiotechnologyChina Agricultural UniversityBeijing 100193China Frontiers Science Center for Molecular Design Breeding Beijing 100193China Sanya Institute of China Agricultural University SanyaHainan 572024China

Transcription factors play critical roles in the regulation of gene expression during maize kernel *** maize endosperm,a large storage organ,accounting for nearly 90%of the dry weight of mature kernels,serves as the primary site for starch *** this study,we identify an endosperm-specific EREB gene,ZmEREB167,which encodes a nucleus-localized EREB *** of ZmEREB167 significantly increases kernel size and weight,as well as starch and protein content,compared with the wild *** situ hybridization experiments show that ZmEREB167 is highly expressed in the BETL as well as PED regions of maize ***-luciferase assays show that ZmEREB167 exhibits transcriptionally repressor activity in maize *** analysis reveals that a large number of genes are up-regulated in the Zmereb167-C1 mutant compared with the wild type,including key genetic factors such as ZmMRP-1 and ZmMN1,as well as multiple transporters involved in maize endosperm *** of RNA-seq and ChIP-seq results identify 68 target genes modulated by *** find that ZmEREB167 directly targets OPAQUE2,ZmNRT1.1,ZmIAA12,ZmIAA19,and ZmbZIP20,repressing their *** study demonstrates that ZmEREB167 functions as a negative regulator in maize endosperm development and affects starch accumulation and kernel size.

关键词： Maize EREB protein BETL Starch Kernel development

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Dynamic and static Lagrange multiplier μ based Bayesian CP factorization with orthogonal factors: Theory and applications

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Signal Processing 2025年 236卷

作者： Zhou, Jing Zhang, Zhichao School of Mathematics and Statistics Center for Applied Mathematics of Jiangsu Province and Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Computational Science and Application of Hainan Province Hainan Normal University Haikou571158 China

The existing μ-Singular Value Decomposition (μ-SVD) denoising algorithm is capable of extracting gear fault information under strong noise conditions. However, this algorithm is only applicable to two-dimensional real-valued data and lacks a mechanism for implementing Automatic Rank Determination (ARD) in high-dimensional data. In this paper, a Bayesian and Tensor treatment of μ-SVD is employed to enable ARD. To further investigate the impact of the Lagrange multiplier μ on the proposed μ-variational Bayesian (μ-VB) algorithm, we examine its performance from both static and dynamic perspectives. Simulation results demonstrate that the μ-VB algorithm achieves ARD and performs well in noise reduction. Further the μ-VB algorithm performs better in wireless communication and linear image coding across numerical domains, tensor sizes, orthogonal factors, and μ settings. © 2025 Elsevier B.V.

关键词： Tensors

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Graph Chirp Signal and Graph Fractional Vertex-Frequency Energy Distribution

arXiv

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arXiv 2025年

作者： Cui, Manjun Zhang, Zhichao School of Mathematics and Statistics The Center for Applied Mathematics of Jiangsu Province The Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing University of Information Science and Technology Nanjing210044 China School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Computational Science and Application of Hainan Province Hainan Normal University Haikou571158 China

Graph signal processing (GSP) has emerged as a powerful framework for analyzing data on irregular domains. In recent years, many classical techniques in signal processing (SP) have been successfully extended to GSP. Among them, chirp signals play a crucial role in various SP applications. However, graph chirp signals have not been formally defined despite their importance. Here, we define graph chirp signals and establish a comprehensive theoretical framework for their analysis. We propose the graph fractional vertex-frequency energy distribution (GFED), which provides a powerful tool for processing and analyzing graph chirp signals. We introduce the general fractional graph distribution (GFGD), a generalized vertex-frequency distribution, and the reduced interference GFED, which can suppress cross-term interference and enhance signal clarity. Furthermore, we propose a novel method for detecting graph signals through GFED domain filtering, facilitating robust detection and analysis of graph chirp signals in noisy environments. Moreover, this method can be applied to real-world data for denoising more effective than some state-of-the-arts, further demonstrating its practical significance. Copyright © 2025, The Authors. All rights reserved.

关键词： Wiener filtering

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Symplectic Wigner Distribution in the Linear Canonical Transform Domain: Theory and application

arXiv

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arXiv 2025年

作者： He, Yangfan Zhang, Zhichao School of Communication and Artificial Intelligence School of Integrated Circuits Nanjing Institute of Technology Nanjing211167 China School of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Computational Science Application of Hainan Province Hainan Normal University Haikou571158 China Key Laboratory of Numerical Simulation of Sichuan Provincial Universities School of Mathematics and Information Sciences Neijiang Normal University Neijiang641000 China

This paper devotes to combine the chirp basis function transformation and symplectic coordinates transformation to yield a novel Wigner distribution (WD) associated with the linear canonical transform (LCT), named as the symplectic WD in the LCT domain (SWDL). It incorporates the merits of the symplectic WD (SWD) and the WD in the LCT domain (WDL), achieving stronger capability in the linear frequency-modulated (LFM) signal frequency rate feature extraction while maintaining the same level of computational complexity. Some essential properties of the SWDL are derived, including marginal distributions, energy conservations, unique reconstruction, Moyal formula, complex conjugate symmetry, time reversal symmetry, scaling property, time translation property, frequency modulation property, and time translation and frequency modulation property. Heisenberg’s uncertainty principles of the SWDL are formulated, giving rise to three kinds of lower bounds attainable respectively by Gaussian enveloped complex exponential signal, Gaussian signal and Gaussian enveloped chirp signal. The optimal symplectic matrices corresponding to the highest time-frequency resolution are generated by solving the lower bound optimization (minimization) problem. The time-frequency resolution of the SWDL is compared with those of the SWD and WDL to demonstrate its superiority in LFM signals time-frequency energy concentration. A synthesis example is also carried out to verify the feasibility and reliability of the theoretical analysis. Copyright © 2025, The Authors. All rights reserved.

关键词： Wigner-Ville distribution

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Extended calculations of energy levels, radiative properties, and lifetimes for phosphorus-like Se XX

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Atomic Data and Nuclear Data Tables 2025年

作者： Wang, Kai Bai, Xuan Chen, Chong Yang Yan, Jun Department of Physics and Anhui Key Laboratory of Optoelectric Materials Science and Technology Key Laboratory of Functional Molecular Solids Ministry of Education Anhui Normal University Wuhu241000 China Shanghai EBIT Lab Key Laboratory of Nuclear Physics and Ion-Beam Application Institute of Modern Physics Department of Nuclear Science and Technology Fudan University Shanghai200433 China Institute of Applied Physics and Computational Mathematics Beijing100088 China

Highly accurate calculations are performed for the lowest 151 fine-structure levels arising from the 3s23p3, 3s3p4, 3s23p23d, 3s3p33d, 3p5 and 3s23p3d2 configurations in P-like Se XX using the multiconfiguration Dirac–Hartree–Fock and the relativistic configuration interaction methods. Complete and consistent atomic data, including excitation energies, wavelengths, E1, E2, M1, M2 line strengths, oscillator strengths, transition rates, and radiative lifetimes for these 151 levels, are provided. Our data set is compared with the NIST compiled values and other available results. The present data are accurate enough for identification and deblending of emission lines involving the n=3 levels and are also useful for modeling and diagnosing fusion plasmas. These data can be considered as a benchmark for other calculations. © 2025

关键词： Excitation energy

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Origin of the tiny energy gap and Dirac points in monoclinic trilayer nickelate La4Ni3O10

arXiv

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arXiv 2025年

作者： Zhang, Hu Hebei Research Center of The Basic Discipline for Computational Physics Hebei Key Laboratory of High-precision Computation and Application of Quantum Field Theory College of Physics Science and Technology Hebei University Baoding071002 China

Superconductivity was recently found in trilayer nickelate La4Ni3O10 under high pressure with a phase transition from the monoclinic P21/a structure to the tetragonal I4/mmm structure. Previous experimental works have confirmed the existence of a tiny energy gap formed with Ni 3dz2 orbitals in monoclinic La4Ni3O10. Here we investigate the physical origin of this gap by analyzing symmetry properties of energy bands based on the group theory. The tiny gap comes from energy bands with opposite parity at the Brillouin zone center. In addition, we also find previously unknown Dirac points in some momentum directions around the Fermi level. An effective Hamiltonian is constructed to describe low energy physics of the tiny energy gap and Dirac points. Due to the low crystal symmetry of monoclinic La4Ni3O10, its energy bands display strong anisotropic properties. © 2025, CC BY.

关键词： Hamiltonians

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A Machine Learning Method for Differentiating and Predicting Human-Infective Coronavirus Based on Physicochemical Features and Composition of the Spike Protein

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Chinese Journal of Electronics 2021年第5期30卷 815-823页

作者： WANG Chao ZOU Quan Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Hainan Key Laboratory for Computational Science and Application Hainan Normal University

Several Coronaviruses(CoVs) are epidemic pathogens that cause severe respiratory syndrome and are associated with significant morbidity and mortality. In this paper, a machine learning method was developed for predicting the risk of human infection posed by CoVs as an early warning system. The proposed Spike-SVM(Support vector machine) model achieved an accuracy of 97.36% for Human-infective CoV(HCoV) and Nonhuman-infective CoV(Non-HCoV) classification. The top informative features that discriminate HCoVs and Non-HCoVs were identified. Spike-SVM is anticipated to be a useful bioinformatics tool for predicting the infection risk posed by CoVs to humans.

关键词： Spike protein NonHCoVs genetics microorganisms Support vector machine mortality Spike-SVM model Human-infective CoV severe respiratory syndrome machine learning method biology computing predicting Human-infective coronavirus diseases proteins HCoV human infection differentiating Nonhuman-infective CoV infection risk CoVs discriminate HCoVs learning (artificial intelligence) bioinformatics support vector machines informative features significant morbidity molecular biophysics early warning system epidemic pathogens Coronaviruses

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Single-cell technologies: current and near future

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science China(Life sciences) 2025年第1期68卷 1-4页

作者： Chenfei Wang Qi Liu Xiaohui Fan Tieliu Shi KeyLaboratory of Spine and Spinal CordInjury Repairand Regeneration Ministry of EducationOrthopedics DepartmentTongji HospitalBioinformatics DepartmentSchoolofLifeSciencesandTechnologyTongji UniversityShanghai 200082China Frontier Science Center for Stem Cells School of Life Sciences and TechnologyTongji UniversityShanghai 200092China Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji UniversityShanghai 200082China Research Institute of Intelligent Computing Zhejiang LabHangzhou 311121China Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang UniversityJiaxing 314103China Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghai 200241China Key Laboratory of Advanced Theory and Application in Statistics and Data Science(MOE) School of StatisticsEast China Normal UniversityShanghai 200062China

Single-cell technologies enable the indepth exploration of multiple biological hierarchies at the scale of individual cells,which have deepened our knowledge of cellular diversity,tissue organization,and overall organism function(Sun et al.,2024).In 2009,single-cell RNA sequencing(scRNA-seq)was first developed as a powerful tool to dissect gene expression and uncover transcriptional *** the rapid advancement of technology,single-cell approaches have expanded to encompass other omics,such as genomics,epigenomics,proteomics,and ***,multimodal technologies including spatially resolved transcriptomics and clustered regularly interspaced short palindromic repeats(CRISPR)screening at the single-cell level further advanced our ability to comprehensively understand cellular ***-cell methods provide deeper insights into disease mechanisms across various conditions,including cancer,developmental disorders,and aging-associated *** this issue,we focus on topics related to single-cell methods,covering the following four aspects:(i)single-cell multi-omic sequencing technology;(ii)single-cell spatial technology;(iii)singlecell CRISPR screening technology;(iv)applications of single-cell technology.

关键词： expanded enable insight

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