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Cell Mechanics Regulates the Dynamic Anisotropic Remodeling of Fibril Matrix at Large Scale

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Research 2024年第3期2023卷 401-415页

作者： Mingxing Ouyang Yanling Hu Weihui Chen Hui Li Yingbo Ji Linshuo Qiu Linlin Zhu Baohua Ji Bing Bu Linhong Deng institute of Biomedical Engineering and Health Sciences School of Medical and Health Engineering and School of PharmacyChangzhou UniversityChangzhou213164China institute of Biomechanics and Applications Department of Engineering MechanicsZhejang UniversityHangzhou310027China.

Living tissues often have anisotropic and heterogeneous organizations, in which developmental processes are coordinated by cells and extracellular matrix modeling. Cells have the capability of modeling matrix in long distance;however, the biophysical mechanism is largely unknown. We investigated the dynamic remodeling of collagen I (COL) fibril matrix by cell contraction with designed patterns of cell clusters. By considering cell dynamic contractions, our molecular dynamics simulations predicted the anisotropic patterns of the observed COL bundling in experiments with various geometrical patterns without spatial limitation. The pattern of COL bundling was closely related to the dynamic remodeling of fibril under cell active contraction. We showed that cell cytoskeletal integrity (actin filaments and microtubules), actomyosin contractions, and endoplasmic reticulum calcium channels acting as force generations and transductions were essential for fiber bundling inductions, and membrane mechanosensory components integrin and Piezo played critical roles as well. This study revealed the underlying mechanisms of the cell mechanics-induced matrix remodeling in large scales and the associated cellular mechanism and should provide important guidelines for tissue engineering in potential biomedical applications.

关键词： contraction Dynamic Matrix

Effect of geopolitical risk and economic uncertainty indices on renewable energy

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Geoscience Frontiers 2024年第3期15卷 237-247页

作者： Xin Zhao Kamel Si Mohammed Yaohui Wang PawełSte˛pien Grzegorz Mentel school of Statistics and Applied mathematics Anhui University of Finance and EconomicsBengbuPR China Faculty of Economics and Management University Ain Temouchent Belhadj BouchaibAlgeria school of Urban and Regional Science Institute of Finance and Economics ResearchShanghai University of Finance and EconomicShanghaiPR China institute of Economics and Finance University of SzczecinPoland Department of Quantitative Methods Faculty of ManagementRzeszow University of TechnologyRzeszow 35-959Poland

In this study,the relationships between five renewable energy sub-sectors markets and the geopolitical risk(GPR)and economic uncertainty indices(EUI)were examined using daily data from March 30,2012,to April 1,*** cross mapping results show that the renewable energy indices have definite relationships with the GPR and *** renewable energy indices show differences in response directions,speed and trends for a standard information difference impulse from the GPR and the EUI.A positive dynamic conditional correlation between renewable energies and EUI was observed in the first and second waves of the COVID-19 *** contrast,there was a relatively decreased effect for two risk indices during the Russia-Ukraine conflict of February-March *** results show that renewable energy may act as a time-varying hedge against economic uncertainty and GPR owing to its safehaven properties at various ***,building more secure and reliable renewable energy systems can help countries to increase their energy independence,which protects them against the risks of political and economic uncertainty.

关键词： Renewable energy Uncertainty indices Impulse response Safe-haven

MCWOA Scheduler:Modified Chimp-Whale Optimization Algorithm for Task Scheduling in Cloud Computing

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Computers, Materials & Continua 2024年第2期78卷 2593-2616页

作者： Chirag Chandrashekar Pradeep Krishnadoss Vijayakumar Kedalu Poornachary Balasundaram Ananthakrishnan school of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Center for Cyber Physical Systems School of Computer Science and EngineeringVellore Institute of TechnologyChennai600127India

Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as *** has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud ***,efficient task scheduling can lower the cloud infrastructure’s energy consumption,thus maximizing the service provider’s revenue by decreasing user job processing *** proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),combines elements of the Chimp Optimization Algorithm(COA)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution ***,the traditional MCWOA’s local search capabilities are augmented by incorporating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating *** study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam *** outcomes reveal that the new method outperforms the original MCWOA,especially in multi-damage detection *** excels in avoiding false positives and enhancing computational speed,making it an optimal choice for structural damage *** efficiency of the proposed MCWOA is assessed against metrics such as energy usage,computational expense,task duration,and *** simulated data indicates that the new MCWOA outpaces other methods across all *** study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).

关键词： Cloud computing scheduling chimp optimization algorithm whale optimization algorithm

QARF: A Novel Malicious Traffic Detection Approach via Online Active Learning for Evolving Traffic Streams

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Chinese Journal of Electronics 2024年第3期33卷 645-656页

作者： Zequn NIU Jingfeng XUE Yong WANG Tianwei LEI Weijie HAN Xianwei GAO school of Computer Science and Technology Beijing Institute of Technology school of Space Information Space Engineering University

In practical abnormal traffic detection scenarios,traffic often appears as drift,imbalanced and rare labeled streams,and how to effectively identify malicious traffic in such complex situations has become a challenge for malicious traffic *** have extensive studies on malicious traffic detection with single challenge,but the detection of complex traffic has not been widely *** adaptive random forests(QARF) is proposed to detect traffic streams with concept drift,imbalance and lack of labeled *** is an online active learning based approach which combines adaptive random forests method and adaptive margin sampling *** achieves querying a small number of instances from unlabeled traffic streams to obtain effective *** conduct experiments using the NSL-KDD dataset to evaluate the performance of *** is compared with other state-of-the-art *** experimental results show that QARF obtains 98.20% accuracy on the NSL-KDD *** performs better than other state-of-the-art methods in comparisons.

关键词： Training Streams Random forests

MDCN:Modified Dense Convolution Network Based Disease Classification in Mango Leaves

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Computers, Materials & Continua 2024年第2期78卷 2511-2533页

作者： Chirag Chandrashekar K.P.Vijayakumar K.Pradeep A.Balasundaram school of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiIndia Center for Cyber Physical Systems School of Computer Science and EngineeringVellore Institute of Technology(VIT)ChennaiIndia

The most widely farmed fruit in the world is *** the production and quality of the mangoes are hampered by many *** diseases need to be effectively controlled and ***,a quick and accurate diagnosis of the disorders is *** convolutional neural networks,renowned for their independence in feature extraction,have established their value in numerous detection and classification ***,it requires large training datasets and several parameters that need careful *** proposed Modified Dense Convolutional Network(MDCN)provides a successful classification scheme for plant diseases affecting mango *** model employs the strength of pre-trained networks and modifies them for the particular context of mango leaf diseases by incorporating transfer learning *** data loader also builds mini-batches for training the models to reduce training ***,optimization approaches help increase the overall model’s efficiency and lower computing *** employed on the MangoLeafBD Dataset consists of a total of 4,000 *** the experimental results,the proposed system is compared with existing techniques and it is clear that the proposed algorithm surpasses the existing algorithms by achieving high performance and overall throughput.

关键词： Leaf disease detection deep convolutional neural networks transfer learning optimization MangoLeafBD Dataset

Resilient sliding mode control for 2D CPSs under denial-of-service attacks

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Science China(Information Sciences) 2024年第6期67卷 262-278页

作者： Lingling LI Rongni YANG Zhiguang FENG Ligang WU College of Intelligent Systems Science and Engineering Harbin Engineering University school of Control Science and Engineering Shandong University school of Astronautics Harbin Institute of Technology

This study addresses the resilient sliding mode control(SMC) problem for two-dimensional cyber-physical systems(2D CPSs) characterized by the Roesser model under denial-of-service attack(DoSA), which can interfere with signal transmission over the communication network. First, the DoS-A model is established by introducing constraints on the Do S frequency and duration. Then, based on active or silent attack situations, the considered system is described as a switched mode. Furthermore, together with Lyapunov theory, the average dwell time technique is employed to deduce sufficient criteria that assure the existence of the desired sliding mode controller. Finally, verification examples are provided to show the validity of the established SMC scheme.

关键词： two-dimensional systems cyber-physical systems denial-of-service attack resilient sliding mode control

Prediction of impurity spectrum function by deep learning algorithm

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Chinese Physics B 2024年第5期33卷 52-63页

作者：刘婷韩榕生陈亮 school of mathematics and Physics North China Electric Power UniversityBeijing 102206China institute of Condensed Matter Physics North China Electric Power UniversityBeijing 102206China Hebei Key Laboratory of Physics and Energy Technology North China Electric Power UniversityBaoding 071003China

By using the numerical renormalization group(NRG)method,we construct a large dataset with about one million spectral functions of the Anderson quantum impurity *** dataset contains the density of states(DOS)of the host material,the strength of Coulomb interaction between on-site electrons(U),and the hybridization between the host material and the impurity site(Γ).The continued DOS and spectral functions are stored with Chebyshev coefficients and wavelet functions,*** this dataset,we build seven different machine learning networks to predict the spectral function from the input data,DOS,U,andΓ.Three different evaluation indexes,mean absolute error(MAE),relative error(RE)and root mean square error(RMSE),are used to analyze the prediction abilities of different network *** analysis shows that,for the two kinds of widely used recurrent neural networks(RNNs),gate recurrent unit(GRU)has better performance than the long short term memory(LSTM)network.A combination of bidirectional GRU(BiGRU)and GRU has the best performance among GRU,BiGRU,LSTM,and *** MAE peak of BiGRU+GRU reaches *** have also tested a one-dimensional convolutional neural network(1DCNN)with 20 hidden layers and a residual neural network(ResNet),we find that the 1DCNN has almost the same performance of the BiGRU+GRU network for the original dataset,while the robustness testing seems to be a little weak than BiGRU+GRU when we test all these models on two other independent *** ResNet has the worst performance among all the seven network *** datasets presented in this paper,including the large data set of the spectral function of Anderson quantum impurity model,are openly available at https://***/10.57760/sciencedb.j00113.00192.

关键词： machine learning Anderson impurity model spectral function

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Hybrid concurrency control protocol for data sharing among heterogeneous blockchains

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Frontiers of Computer Science 2024年第3期18卷 1-12页

作者： Tiezheng GUO Zhiwei ZHANG Ye YUAN Xiaochun YANG Guoren WANG school of Computer Science and Technology Beijing Institute of TechnologyBeijing 100029China school of Computer Science and Engineering Northeastern UniversityShenyang 110167China

With the development of information technology and cloud computing,data sharing has become an important part of scientific *** traditional data sharing,data is stored on a third-party storage platform,which causes the owner to lose control of the *** a result,there are issues of intentional data leakage and tampering by third parties,and the private information contained in the data may lead to more significant ***,data is frequently maintained on multiple storage platforms,posing significant hurdles in terms of enlisting multiple parties to engage in data sharing while maintaining *** this work,we propose a new architecture for applying blockchains to data sharing and achieve efficient and reliable data sharing among heterogeneous *** design a new data sharing transaction mechanism based on the system architecture to protect the security of the raw data and the processing *** also design and implement a hybrid concurrency control protocol to overcome issues caused by the large differences in blockchain performance in our system and to improve the success rate of data sharing *** took Ethereum and Hyperledger Fabric as examples to conduct crossblockchain data sharing *** results show that our system achieves data sharing across heterogeneous blockchains with reasonable performance and has high scalability.

关键词： data sharing blockchain concurrency control protocol crosschain

Atomically self-healing of structural defects in monolayer WSe2

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Chinese Physics B 2024年第9期33卷 53-59页

作者：李康舒李俊贤韩小藏周武赵晓续 school of Materials Science and Engineering Peking University school of Physical Sciences University of Chinese Academy of Sciences AI for Science institute

Minimizing disorder and defects is crucial for realizing the full potential of two-dimensional transition metal dichalcogenides(TMDs) materials and improving device performance to desired properties. However, the methods in defect control currently face challenges with overly large operational areas and a lack of precision in targeting specific defects. Therefore,we propose a new method for the precise and universal defect healing of TMD materials, integrating real-time imaging with scanning transmission electron microscopy(STEM). This method employs electron beam irradiation to stimulate the diffusion migration of surface-adsorbed adatoms on TMD materials grown by low-temperature molecular beam epitaxy(MBE),and heal defects within the diffusion range. This approach covers defect repairs ranging from zero-dimensional vacancy defects to two-dimensional grain orientation alignment, demonstrating its universality in terms of the types of samples and defects. These findings offer insights into the use of atomic-level focused electron beams at appropriate voltages in STEM for defect healing, providing valuable experience for achieving atomic-level precise fabrication of TMD materials.

关键词： atom manipulation design fabrication nanoscale materials and structures: fabrication and characterization new materials: theory scanning transmission electron microscopy (STEM)