检索结果-南通市图书馆

Adaptive-basis decomposition-based low-rank network for efficient non-uniform motion deblurring

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Optoelectronics Letters 2025年第1期21卷 43-50页

作者： CHEN Lei XIONG Qingbo ZHANG Wei LI Runde school of Software Henan UniversityKaifeng 475004China school of applied technology China University of Labor RelationsBeijing 100048China

In this study,we present a unified sparsity-driven framework that significantly enhances motion deblurring performance by integrating two key components:a custom-designed dataset and a low-rank module(LRM).This framework leverages the inherent sparsity of per-pixel blur kernels to bolster both deblurring accuracy and model ***,we propose an adaptive-basis decomposition-based deblurring(ADD)approach,which constructs a tailored training dataset to enhance the generalization capacity of the deblurring *** ADD framework adaptively decomposes motion blur into sparse basis elements,effectively addressing the intricacies associated with non-uniform ***,an LRM is proposed to improve the interpretability of deblurring models as a plug-and-play module,primarily designed to identify and harness the intrinsic sparse features in sharp images.A series of ablation studies have been conducted to substantiate the synergistic advantages of combining the proposed ADD with the LRM for overall improvement in deblurring ***,we empirically demonstrate through rigorous experimentation that incorporating the LRM into an existing Uformer network leads to substantial enhancement in reconstruction *** integration yields a sparsity-guided low-rank network(SGLRN).Operating under the overarching principle of sparsity,SGLRN consistently outperforms state-of-the-art methods across multiple standard deblurring *** experimental results,assessed through quantitative metrics and qualitative visual evaluations,provide compelling evidence of its *** overall deblurring results are available at Google Drive.

关键词： network motion uniform

维普期刊数据库

Investigation on Cu promotion effect on Ce-based solid solution-anchored Rh single atoms for three-way catalysis

在线全文

学校读者我要写书评

暂无评论

Chinese Chemical Letters 2025年第2期36卷 574-578页

作者： Jianing He Xiao Wang Zijian Wang Ruize Jiang Ke Wang Rui Zhang Huilin Wang Baokang Geng Hongyi Gao Shuyan Song Hongjie Zhang State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied Chemistry Chinese Academy of Sciences school of applied Chemistry and Engineering University of Science and Technology of China China school of Materials Science and Engineering University of Science and Technology Beijing Department of Chemistry Tsinghua University

The three-way catalyst（TWC）, as a promising approach to control automobile exhaust emission, has been widely studied and applied. However, it still suffers from the high light-off temperature and poor ***, we synthesized a multicomponent catalyst Rh/Cu-CeSn by using Cu metal doping to modify the Ce-based solid solution, which exhibited good TWC catalytic performance: the light-off temperatures for CO, NO, and C3H6conversion are 172 ℃, 266 ℃, and 193 ℃, respectively. Moreover, the catalyst still maintained good activity after 12 h of the continuous reaction under high-temperature conditions. The experiments and mechanism studies reveal that due to the redox pair Cu+/Cu2+, the Cu incorporation can effectively inhibit the Rh transition to the oxidation state and greatly enhance the catalytic activity and stability. This work provides a viable strategy for precise characteristic modulation of composite oxide supports during the fabrication of noble metal-based catalysts, which significantly reduces environmental pollution from energy applications.

关键词： Co-precipitation Oxygen vacancies Rhodium (Rh) catalyst Solid solution Three-way catalysts (TWC)

Classifying extended,localized and critical states in quasiperiodic lattices via unsupervised learning

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Physics B 2025年第1期34卷 422-427页

作者： Bohan Zheng Siyu Zhu Xingping Zhou Tong Liu school of Computer Science and technology School of SoftwareNanjing University of Posts and TelecommunicationsNanjing 210023China Institute of Quantum Information and technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Department of applied Physics School of ScienceNanjing University of Posts and TelecommunicationsNanjing 210003China

Classification of quantum phases is one of the most important areas of research in condensed matter *** this work,we obtain the phase diagram of one-dimensional quasiperiodic models via unsupervised ***,we choose two advanced unsupervised learning algorithms,namely,density-based spatial clustering of applications with noise(DBSCAN)and ordering points to identify the clustering structure(OPTICS),to explore the distinct phases of the Aubry–André–Harper model and the quasiperiodic p-wave *** unsupervised learning results match well with those obtained through traditional numerical ***,we assess similarity across different algorithms and find that the highest degree of similarity between the results of unsupervised learning algorithms and those of traditional algorithms exceeds 98%.Our work sheds light on applications of unsupervised learning for phase classification.

关键词： quantum phase quasiperiodic machine learning

维普期刊数据库

Synthesis of energetic materials by microfluidics

在线全文

学校读者我要写书评

暂无评论

Defence technology(防务技术) 2025年第2期44卷 306-319页

作者： Shuo Liu Chuanyu Zhang Yanlan Wang Xueyong Wei school of Mechanical Engineering Xi'an Jiaotong UniversityXi'an 710049China school of Instrument Science and technology Xi'an Jiaotong UniversityXi'an 710049China Science and technology on applied Physical Chemistry Laboratory Xi'an 710061China

Energetic materials,characterized by their capacity to store and release substantial energy,hold pivotal significance in some fields,particularly in defense ***,with its ability to manipulate fluids and facilitate droplet formation at the microscale,enables precise control of chemical *** scholarly endeavors have increasingly harnessed microfluidic reactors in the realm of energetic materials,yielding morphologically controllable particles with enhanced uniformity and explosive ***,crucial insights into microfluidic-based methodologies are dispersed across various publications,necessitating a systematic ***,this review addresses this gap by concentrating on the synthesis of energetic materials through ***,the methods based on micro-mixing and droplets in the previous papers are summarized and the strategies to control the critical parameters within chemical reactions are discussed in ***,the comparison in terms of advantages and disadvantages is *** demonstrated in the last section regarding perspectives,challenges such as clogging,dead zones,and suboptimal production yields are non-ignoble in the promising fields and they might be addressed by integrating sound,optics,or electrical energy to meet heightened *** comprehensive overview aims to consolidate and analyze the diverse array of microfluidic approaches in energetic material synthesis,offering valuable insights for future research directions.

关键词： Microfluidic technology Energetic materials synthesis Micro-mixing Micro-droplets

维普期刊数据库

Evolutionary Particle Swarm Optimization Algorithm Based on Collective Prediction for Deployment of Base Stations

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2025年第1期82卷 345-369页

作者： Jiaying Shen Donglin Zhu Yujia Liu Leyi Wang Jialing Hu Zhaolong Ouyang Changjun Zhou Taiyong Li school of Computer Science and technology Zhejiang Normal UniversityJinhua321004China school of Future Technologies Jiangxi Institute of Applied Science and TechnologyNanchang330000China school of Computing and Artificial Intelligence Southwestern University of Finance and EconomicsChengdu611130China

The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real *** development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of *** a specific area,achieving higher signal coverage with fewer base stations has become an urgent ***,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as *** a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by *** also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization *** better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base *** experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches *** results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and *** ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.

关键词： Particle swarm optimization effective coverage area global optimization base station deployment

Unsupervised multiplex graph diffusion networks with multi-level canonical correlation analysis for multiplex graph representation learning

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2025年第03期68卷 66-79页

作者： Sichao FU Qinmu PENG Yange HE Baokun DU Bin ZOU Xiao-Yuan JING Xinge YOU school of Electronic Information and Communications Huazhong University of Science and Technology Platform Operation and Marketing Center JD Retail Faculty of Mathematics and Statistics Hubei Key Laboratory of Applied Mathematics Hubei University school of Computer Science Wuhan University

In recent years, unsupervised multiplex graph representation learning(UMGRL) has received increasing research interest, which aims to learn discriminative node features from the multiplex graphs supervised by data without the guidance of labels. Although these designed UMGRL methods have obtained great success in various graph-related tasks, most existing UMGRL models still have the following issues: highly depending on complex self-supervised strategies(i.e., data augmentation,pretext tasks, and negative pairs sampling), restricted receptive fields, and only aggregating low-frequency information between nodes. In this paper, we propose a simple unsupervised multiplex graph diffusion network(UMGDN) with the aid of multi-level canonical correlation analysis to solve the above issues. Specifically, we first decouple the feature transform and propagation processes of the graph convolution layer to further improve the generalization of the learnable parameters. And then, we propose adaptive diffusion propagation to capture long-range dependency relationships between nodes, not the local neighborhood interactions. Finally, a multi-level canonical correlation analysis loss on both the feature transform and propagation processes is proposed to maximize the correlation of the same node features from multiple graphs for guiding model optimization. Compared to the existing UMGRL models, our proposed UMGDN does not need to introduce any data augmentation, negative pairs sampling techniques, complex pretext tasks, and also adaptively aggregates the optimal frequency information between nodes to generate more robust node embeddings. Extensive experiments on four popular datasets and two graph-related tasks demonstrate the effectiveness of the proposed method.

关键词： unsupervised multiplex graph representation learning graph neural networks node classification node clustering

同方期刊数据库

Federated local causal structure learning

在线全文

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2025年第03期68卷 110-124页

作者： Kui YU Chen RONG Hao WANG Fuyuan CAO Jiye LIANG school of Computer and Information Hefei University of Technology school of Computer and Information technology Shanxi University

Local causal structure learning(LCS) efficiently identifies a set of direct neighbors of a specified variable from observational data. Additionally, it distinguishes direct causes and direct effects of this variable without learning the entire causal structure. While many LCS algorithms have been proposed, they do not consider the data privacy-preserving problem,which has attracted extensive attention from academia and industry. To address this issue, we propose a federated local causal structure learning(FedLCS) algorithm to learn local causal structures in privacy-preserving data in a federated ***, FedLCS introduces a layer-wise federated local skeleton learning algorithm to construct the local skeleton. Based on this skeleton, it introduces a federated local skeleton orientation algorithm and an extension-and-backtracking orientation algorithm to orient the edges. Finally, FedLCS uses a federated local extension-and-backtracking orientation algorithm to orient the remaining edges. Extensive experiments on benchmark, synthetic, and real datasets demonstrate that FedLCS can learn the local causal structure of a given variable in a federated setting.

关键词： local causal structure learning federated learning directed acyclic graph privacy-preserving data federated layer-wise strategy

同方期刊数据库

The study of antibacterial activity of cationic poly(β-amino ester)regulating by amphiphilic balance

在线全文

学校读者我要写书评

暂无评论

Chinese Chemical Letters 2025年第2期36卷 332-336页

作者： Chong Liu Ling Li Jiahui Gao Yanwei Li Nazhen Zhang Jing Zang Cong Liu Zhaopei Guo Yanhui Li Huayu Tian school of Materials Science and Engineering Changchun University of Science and Technology school of Materials Science and Engineering Xiamen University of Technology Key Laboratory of Polymer Ecomaterials Changchun Institute of Applied Chemistry Chinese Academy of Sciences College of Chemistry and Chemical Engineering Xiamen University

It is well known that cationic polymers have excellent antimicrobial capacity accompanied with high biotoxicity, to reduce biotoxicity needs to decrease the number of cationic groups on polymers, which will influence antimicrobial activity. It is necessary to design a cationic polymer mimic natural antimicrobial peptide with excellent antibacterial activity and low toxicity to solve the above dilemma. Here,we designed and prepared a series of cationic poly(β-amino ester)s(PBAEs) with different cationic contents, and introducing hydrophobic alkyl chain to adjust the balance between antimicrobial activity and biotoxicity to obtain an ideal antimicrobial polymer. The optimum one of synthesized PBAE(hydrophilic cationic monomer:hydrophobic monomer = 5:5) was screened by testing cytotoxicity and minimum inhibitory concentration(MIC), which can effectively kill S. aureus and E. coli with PBAE concentration of15 μg/m L by a spread plate bacteriostatic method and dead and alive staining test. The way of PBAE killing bacterial was destroying the membrane like natural antimicrobial peptide observed by scanning electron microscopy(SEM). In addition, PBAE did not exhibit hemolysis and cytotoxicity. In particular, from the result of animal tests, the PBAE was able to promote healing of infected wounds from removing mature S. aureus and E. coli on the surface of infected wound. As a result, our work offers a viable approach for designing antimicrobial materials, highlighting the significant potential of PBAE polymers in the field of biomedical materials.

关键词： Amphiphilic balance Antimicrobial Cationic polymers Michael addition polymerization Poly(β-amino ester)s

Revealing the difference of Stark tuning rate between interface and bulk by surface-enhanced infrared absorption spectroscopy

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Chemical Letters 2025年第2期36卷 461-464页

作者： Manyu Zhu Fei Liang Lie Wu Zihao Li Chen Wang Shule Liu Xiue Jiang State Key Laboratory of Electroanalytical Chemistry Changchun Institute of Applied ChemistryChinese Academy of Sciences school of applied Chemistry and Engineering University of Science and Technology of China school of Materials Science and Engineering Sun Yat-sen University Research Center for Analytical Science College of ChemistryNankai University

Revealing the factors that affect the vibrational frequency of Stark probe at interface is a pre-requirement for evaluating the absolute interfacial electric *** using surface-enhanced infrared absorption(SEIRA) spectroscopy,attenuated total reflection (ATR) spectroscopy and molecular dynamics (MD),we reveal the assembled C≡N at gold nanofilm exhibits a reduced Stark tuning rate (STR) referring to the vibrational frequency shift in response to electric field comparing with the bulk which was regulated by the electron transfer between S and *** findings lead to a deeper understanding of the vibrational Stark effect at the interface and provide guidance for improving the interface electric field theory.

关键词： Attenuated total reflection spectroscopy Cyano group Stark tuning rate Surface-enhanced infrared spectroscopy Vibrational stark effect