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The breaking of spin symmetry in the single-particle resonances in deformed nuclei

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Nuclear Science and Techniques 2024年第3期35卷 237-245页

作者： Zhen-Yu Zheng Shou-wan Chen Quan Liu School of Physics and Optoelectronic Engineering Anhui UniversityHefei 230601China

The exploration of spin symmetry (SS) in nuclear physics has been instrumental in identifying atomic nucleus *** this study,we solve the Dirac equation from the relativistic mean field (RMF) in complex momentum *** investigated SS and its breaking in single-particle resonant states within deformed nuclei,with a focus on the illustrative *** was the initial discovery of a resonant spin doublet in a deformed nucleus,with the expectation of the SS approaching the continuum *** increasing single-particle energy,the splitting of the resonant spin doublets widened *** escalating splitting implies diminishing adherence to the SS,indicating a departure from the expected behavior as the energy levels *** also analyzed the width of the resonant states,showing that lower orbital angular momentum resonances possess shorter decay times and that SS is preserved within broad resonant doublets,as opposed to narrow resonant *** the radial density of the upper components for the bound-state and resonant-state doublets,it becomes evident that while SS is well-preserved in the bound states,it deteriorates in the resonant *** impact of nuclear deformation (β_(2)) on SS was examined,demonstrating that an increase in β_(2) resulted in higher energy and width splitting in the resonant spin doublets,which is attributed to increased component ***,the sensitivity of spin doublets to various potential parameters such as surface diffuseness (a),radius (R),and depth (Σ0) is discussed,emphasizing the role of these parameters in *** study provides valuable insights into the behavior of spin doublets in deformed nuclei and their interplay with the nuclear structure,thereby advancing our understanding of SS in the resonance state.

关键词： Spin symmetry Resonant states Deformed nuclei Complex-momentum representation

Dynamics modeling and optimal control for multi-information diffusion in Social Internet of Things

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Digital Communications and Networks 2024年第3期10卷 655-665页

作者： Yaguang Lin Xiaoming wang Liang wang Pengfei wan School of Computer Science Shaanxi Normal UniversityXi'an710119China

As an ingenious convergence between the Internet of Things and social networks,the Social Internet of Things(SIoT)can provide effective and intelligent information services and has become one of the main platforms for people to spread and share ***,SIoT is characterized by high openness and autonomy,multiple kinds of information can spread rapidly,freely and cooperatively in SIoT,which makes it challenging to accurately reveal the characteristics of the information diffusion process and effectively control its *** this end,with the aim of exploring multi-information cooperative diffusion processes in SIoT,we first develop a dynamics model for multi-information cooperative diffusion based on the system dynamics theory in this ***,the characteristics and laws of the dynamical evolution process of multi-information cooperative diffusion are theoretically investigated,and the diffusion trend is *** this basis,to further control the multi-information cooperative diffusion process efficiently,we propose two control strategies for information diffusion with control objectives,develop an optimal control system for the multi-information cooperative diffusion process,and propose the corresponding optimal control *** optimal solution distribution of the control strategy satisfying the control system constraints and the control budget constraints is solved using the optimal control ***,extensive simulation experiments based on real dataset from Twitter validate the correctness and effectiveness of the proposed model,strategy and method.

关键词： Social Internet of Things Information diffusion Dynamics modeling Trend prediction Optimal control

Coarse-fine joint target parameter estimation method based on AN-RSC in OFDM passive radar

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Journal of Systems Engineering and Electronics 2024年第2期35卷 339-349页

作者： wanG Chujun wan Xianrong YI Jianxin CHENG Feng School of Electronic Information Wuhan UniversityWuhan 430072China

In this paper,we study the accuracy of delay-Doppler parameter estimation of targets in a passive radar using orthogonal frequency division multiplexing(OFDM)signal.A coarse-fine joint estimation method is proposed to achieve better estimation accuracy of target parameters without excessive computational ***,the modulation symbol domain(MSD)method is used to roughly estimate the delay and Doppler of ***,to obtain high-precision Doppler estimation,the atomic norm(AN)based on the multiple measurement vectors(MMV)model(MMV-AN)is used to manifest the signal sparsity in the continuous Doppler *** the same time,a reference signal compensation(RSC)method is presented to obtain highprecision delay *** results based on the OFDM signal show that the coarse-fine joint estimation method based on AN-RSC can obtain a more accurate estimation of target parameters compared with other *** addition,the proposed method also possesses computational advantages compared with the joint parameter estimation.

关键词： passive radar orthogonal frequency division multiplexing(OFDM)signal atomic norm(AN) parameter estimation

A Spleen Tyrosine Kinase’s Sky in Neuronal Degeneration

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Neuroscience Bulletin 2024年第2期40卷 273-276页

作者： wan-Yun Zhang Sen Lin Department of Neurology Xinqiao HospitalThe Second Afliated HospitalArmy Medical UniversityChongqing 400042China Chongqing Institute for Brain and Intelligence Guangyang Bay LaboratoryChongqing 400064China

With the growing elderly population,neurodegenerative disorders like Alzheimer's disease(AD)are emerging as a significant public health *** is widely acknowledged in the scientific community that the accumulation of neurotoxic aggregates,such as amyloid beta(Aβ),within the central nervous system is a major factor in the development of these ***,human genome-wide association studies have identified mutations in microglial receptors that may be linked to a number of neurodegenerative diseases[1].

关键词： Aβ Spleen Alzheimer

Growth of RB Population in the Conversion Phase of Chlamydia Life Cycle

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Communications on Applied Mathematics and Computation 2024年第1期6卷 90-112页

作者： Frederic Y.M.wan Department of Mathematics University of CaliforniaIrvineCA92697-3875USA

Upon infecting a host cell,the reticulate body(RB)form of the Chlamydia bacteria simply proliferates by binary fission for an extended *** data show only RB units in the infected cells 20 hours post infection(hpi),spanning nearly half way through the development *** data collected every 4 hpi,conversion to the elementary body(EB)form begins abruptly at a rapid rate sometime around 24 *** modeling proliferation and conversion as simple birth and death processes,it has been shown that the optimal strategy for maximizing the total(mean)EB population at host cell lysis time is a bang-bang control qualitatively replicating the observed conversion ***,the simple birth and death model for the RB proliferation and conversion to EB deviates in a significant way from the available data on the evolution of the RB population after the onset of RB-to-EB *** working with a more refined model that takes into account a small size threshold eligibility requirement for conversion noted in the available data,we succeed in removing the deficiency of the previous models on the evolution of the RB population without affecting the optimal bang-bang conversion strategy.

关键词： Chlamydia Life cycle Optimal control Maximal infectious spread Specie competitive survival

Synthesis of Diverse Oxetane Amino Acids via Visible-Light-Induced Photocatalytic Decarboxylative Giese-Type Reaction

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Chinese Journal of Chemistry 2024年第12期42卷 1341-1346页

作者： Haoliang Shi Yi wan Yongqiang Zhang Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism Shanghai Key Laboratory of New Drug Designand School of PharmacyEast China University of Science and TechnologyShanghai200237 China

The divergent synthesis of versatile 3,3′-disubstituted oxetane amino acids by utilizing visible-light-induced photocatalytic decarboxylative Giese-type reaction has been demonstrated.3-Methyleneoxetane-derived substrates are readily available in a single-step and highly reactive as radical acceptors,allowing the production of versatile oxetaneγ-andα-amino acids in high yields.A distinct ring strain release-driven radical addition mechanism was preliminarily *** preparative power was further highlighted by the application in the synthesis of oxetane-containing dipeptides and azetidine amino acids,as well as the transformation of the product into novel oxetane-containing spiro-heterocycle pharmacophore.

关键词： Photoredox catalysis Decarboxylative Giese-type reaction Oxetane amino acids Amino acids Synthesis Radical reactions

Predicting Traffic Flow Using Dynamic Spatial-Temporal Graph Convolution Networks

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Computers, Materials & Continua 2024年第3期78卷 4343-4361页

作者： Yunchang Liu Fei wan Chengwu Liang School of Computer and Data Science Henan University of Urban ConstructionPingdingshan467036China School of Electrical and Control Engineering Henan University of Urban ConstructionPingdingshan467036China

Traffic flow prediction plays a key role in the construction of intelligent transportation ***,due to its complex spatio-temporal dependence and its uncertainty,the research becomes very *** of the existing studies are based on graph neural networks that model traffic flow graphs and try to use fixed graph structure to deal with the relationship between ***,due to the time-varying spatial correlation of the traffic network,there is no fixed node relationship,and these methods cannot effectively integrate the temporal and spatial *** paper proposes a novel temporal-spatial dynamic graph convolutional network(TSADGCN).The dynamic time warping algorithm(DTW)is introduced to calculate the similarity of traffic flow sequence among network nodes in the time dimension,and the spatiotemporal graph of traffic flow is constructed to capture the spatiotemporal characteristics and dependencies of traffic *** combining graph attention network and time attention network,a spatiotemporal convolution block is constructed to capture spatiotemporal characteristics of traffic *** on open data sets PEMSD4 and PEMSD8 show that TSADGCN has higher prediction accuracy than well-known traffic flow prediction algorithms.

关键词： Intelligent transportation graph convolutional network traffic flow DTW algorithm attention mechanism

A Reliable Iteration Algorithm for One-Bit Compressive Sensing on the Unit Sphere

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Acta Mathematicae Applicatae Sinica 2024年第3期40卷 801-822页

作者： Yan-cheng LU Ning BI An-hua wan School of Mathematics Sun Yat-sen UniversityGuangzhou 510275China

The one-bit compressed sensing problem is of fundamental importance in many areas,such as wireless communication,statistics,and so ***,the optimization of one-bit problem coustrained on the unit sphere lacks an algorithm with rigorous mathematical proof of convergence and *** this paper,an iteration algorithm is established based on difference-of-convex algorithm for the one-bit compressed sensing problem constrained on the unit sphere,with iterating formula■,where C is the convex cone generated by the one-bit measurements andη_(1)>η_(2)>1/*** new algorithm is proved to converge as long as the initial point is on the unit sphere and accords with the measurements,and the convergence to the global minimum point of the l_(1)norm is discussed.

关键词： one-bit compressed sensing difference of convex algorithm iteration algorithm ■1-minimization

Surface wave inversion with unknown number of soil layers based on a hybrid learning procedure of deep learning and genetic algorithm

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 345-358页

作者： Zan Zhou Thomas Man-Hoi Lok wan-Huan Zhou Department of Civil and Environmental Engineering Faculty of Science and TechnologyUniversity of MacaoMacaoChina

Surface wave inversion is a key step in the application of surface waves to soil velocity ***,a common practice for the process of inversion is that the number of soil layers is assumed to be known before using heuristic search algorithms to compute the shear wave velocity profile or the number of soil layers is considered as an optimization ***,an improper selection of the number of layers may lead to an incorrect shear wave velocity *** this study,a deep learning and genetic algorithm hybrid learning procedure is proposed to perform the surface wave inversion without the need to assume the number of soil ***,a deep neural network is adapted to learn from a large number of synthetic dispersion curves for inferring the layer ***,the shear-wave velocity profile is determined by a genetic algorithm with the known layer *** applying this procedure to both simulated and real-world cases,the results indicate that the proposed method is reliable and efficient for surface wave inversion.

关键词： surface wave inversion analysis shear-wave velocity profile deep neural network genetic algorithm