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Progress on Transition Metal Ions Dissolution Suppression Strategies in Prussian Blue Analogs for Aqueous Sodium-/Potassium-Ion Batteries

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Nano-Micro Letters 2024年第7期16卷 142-168页

作者： Wenli Shu Junxian Li Guangwan Zhang Jiashen Meng Xuanpeng Wang Liqiang mai Department of Physical Science and Technology School of ScienceWuhan University of TechnologyWuhan 430070People’s Republic of China School of Materials Science and Engineering State Key Laboratory of Advanced Technology for Materials SynthesisWuhan University of TechnologyWuhan 430070People’s Republic of China Sanya Science and Education Innovation Park Wuhan University of TechnologySanya 572000People’s Republic of China Hubei Longzhong Laboratory Wuhan University of TechnologyXiangyang Demonstration ZoneXiangyang 441000People’s Republic of China

Aqueous sodium-ion batteries(ASIBs)and aqueous potassium-ion batteries(APIBs)present significant potential for large-scale energy storage due to their cost-effectiveness,safety,and environmental ***,the intricate energy storage mechanisms in aqueous electrolytes place stringent require-ments on the host *** blue analogs(PBAs),with their open three-dimensional framework and facile synthesis,stand out as leading candidates for aqueous energy ***,PBAs possess a swift capacity fade and limited cycle longevity,for their structural integrity is compromised by the pronounced dis-solution of transition metal(TM)ions in the aqueous *** manuscript provides an exhaustive review of the recent advancements concerning PBAs in ASIBs and *** dissolution mechanisms of TM ions in PBAs,informed by their structural attributes and redox processes,are thoroughly ***,this study delves into innovative design tactics to alleviate the dissolution issue of TM *** conclusion,the paper consolidates various strategies for suppressing the dissolution of TM ions in PBAs and posits avenues for prospective exploration of high-safety aqueous sodium-/potassium-ion batteries.

关键词： Prussian blue analogs Transition metal ions dissolution Suppression strategies Aqueous sodium-ion batteries Aqueous potassium-ion batteries

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WebFLex:A Framework for Web Browsers-Based Peer-to-Peer Federated Learning Systems Using WebRTC

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Computers, Materials & Continua 2024年第3期78卷 4177-4204页

作者： mai Alzamel Hamza Ali Rizvi Najwa Altwaijry Isra Al-Turaiki Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadhKingdom of Saudi Arabia Department of Computer Science and Engineering Punjab Engineering CollegeChandigarhIndia

Scalability and information personal privacy are vital for training and deploying large-scale deep learning *** learning trains models on exclusive information by aggregating weights from various devices and taking advantage of the device-agnostic environment of web ***,relying on a main central server for internet browser-based federated systems can prohibit scalability and interfere with the training process as a result of growing client ***,information relating to the training dataset can possibly be extracted from the distributed weights,potentially reducing the privacy of the local data used for *** this research paper,we aim to investigate the challenges of scalability and data privacy to increase the efficiency of distributed training *** a result,we propose a web-federated learning exchange(WebFLex)framework,which intends to improve the decentralization of the federated learning *** is additionally developed to secure distributed and scalable federated learning systems that operate in web browsers across heterogeneous ***,WebFLex utilizes peer-to-peer interactions and secure weight exchanges utilizing browser-to-browser web real-time communication(WebRTC),efficiently preventing the need for a main central *** has actually been measured in various setups using the MNIST *** results show WebFLex’s ability to improve the scalability of federated learning systems,allowing a smooth increase in the number of participating devices without central data *** addition,WebFLex can maintain a durable federated learning procedure even when faced with device disconnections and network ***,it improves data privacy by utilizing artificial noise,which accomplishes an appropriate balance between accuracy and privacy preservation.

关键词： Federated learning web browser privacy deep learning

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A Multi-Strategy-Improved Northern Goshawk Optimization Algorithm for Global Optimization and Engineering Design

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Computers, Materials & Continua 2024年第7期80卷 1677-1709页

作者： Liang Zeng mai Hu Chenning Zhang Quan Yuan Shanshan Wang School of Electrical and Electronic Engineering Hubei University of TechnologyWuhan430068China Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan430068China

Optimization algorithms play a pivotal role in enhancing the performance and efficiency of systems across various scientific and engineering *** enhance the performance and alleviate the limitations of the Northern Goshawk Optimization(NGO)algorithm,particularly its tendency towards premature convergence and entrapment in local optima during function optimization processes,this study introduces an advanced Improved Northern Goshawk Optimization(INGO)*** algorithm incorporates a multifaceted enhancement strategy to boost operational ***,a tent chaotic map is employed in the initialization phase to generate a diverse initial population,providing high-quality feasible ***,after the first phase of the NGO’s iterative process,a whale fall strategy is introduced to prevent premature convergence into local *** is followed by the integration of T-distributionmutation strategies and the State Transition Algorithm(STA)after the second phase of the NGO,achieving a balanced synergy between the algorithm’s exploitation and *** research evaluates the performance of INGO using 23 benchmark functions alongside the IEEE CEC 2017 benchmark functions,accompanied by a statistical analysis of the *** experimental outcomes demonstrate INGO’s superior achievements in function optimization ***,its applicability in solving engineering design problems was verified through simulations on Unmanned Aerial Vehicle(UAV)trajectory planning issues,establishing INGO’s capability in addressing complex optimization challenges.

关键词： Northern Goshawk Optimization tent chaotic map T-distribution disturbance state transition algorithm UAV path planning

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Structure and defect dual-engineering of cobalt oxides for lowtemperature Zn-air batteries

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Nano Research 2024年第5期17卷 4108-4117页

作者： Hang Lei Zhuowen Huangfu Liangjun Chen Xuelin Yang Zilong Wang Wenjie mai Hubei Provincial Collaborative Innovation Center for New Energy Microgrid College of Electrical Engineering&New EnergyChina Three Gorges UniversityYichang 443002China Siyuan Laboratory Guangdong Provincial Engineering Technology Research Center of Vacuum Coating Technologies and New Energy MaterialsDepartment of PhysicsJinan UniversityGuangzhou 510632China

The exploration of bifunctional electrocatalysts with high catalytic activity and long-term durability for low-temperature Zn-air batteries(ZABs)is an ongoing ***,quintet-shelled hollow spheres,P-doped multi-layer Co_(3)O_(4)(PM-Co_(3)O_(4)),with enriched oxygen vacancies are prepared by thermally induced mass relocation and a simple phosphating *** advanced characterizations reveal P anion-induced effects on internal electronic structure and local coordination *** finite element method elucidates that the complex multi-layer spherical nanostructure is conducive to the transport and diffusion of OH-and O_(2).Benefiting from its unique structural features and abundant oxygen vacancies,the well-designed PM-Co_(3)O_(4) presents small reversible oxygen overpotential for catalyzing oxygen reduction/evolution ***,the fabricated low-temperature ZABs based on PM-Co_(3)O_(4) as air-cathode exhibit high power density(20.8 mW·cm^(-2))and long-term stability(over 600 cycles)at the ultra-low temperature of-40℃,outperforming state-of-art Pt/C+IrO_(2)-based ***,the dynamic evolution mechanism of cobalt oxide catalysts during ZAB operation is *** work provides a guideline to design efficient electrocatalysts with regulated electronic configurations and exquisite nano-/microstructures for ZABs under extreme working conditions.

关键词： Zn-air batteries electrocatalysts low temperature hollow spheres oxygen vacancies

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Imaging mass spectrometry:a molecular microscope for studying the role of lipids in Parkinson's disease

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Neural Regeneration Research 2024年第6期19卷 1179-1180页

作者： Vinata Vedam-mai Jacob M.Samuel Boone M.Prentice Department of Neurology University of FloridaGainesvilleFLUSA Department of Chemistry University of FloridaGainesvilleFLUSA

Parkinson's disease–A lipidopathy?The histopathological hallmark of Parkinson's disease(PD)and dementia with Lewy bodies are inclusions enriched inα-synuclein(α-syn),known as Lewy bodies,which are not only composed of proteins,but also a core of lipid *** has been thus far principally thought of as a“proteinopathy”caused by the misfolding of α-syn.

关键词： lipids species folding

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Secondary metabolites of mulberry leaves exert anti-lung cancer activity through regulating the PD-L1/PD-1 signaling pathway

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Journal of Pharmaceutical Analysis 2024年第6期14卷 914-925页

作者： Guiqin Ye Xin Sun Jiuzhou Li Yuanyuan mai Ruilan Gao Jianbin Zhang Cancer Center Department of Medical OncologyKey Laboratory of Tumor Molecular Diagnosis and Individualized Medicine of Zhejiang ProvinceZhejiang Provincial People's HospitalAffiliated People's HospitalHangzhou Medical CollegeHangzhou310014China Clinical Laboratory Yuhuan City HospitalTaizhouZhejiang317600China Hangzhou Medical College Hangzhou311300China Department of Neurosurgery Binzhou People's HospitalBinzhouShandong256600China Institute of Hematology Research The First Affiliated Hospital of Zhejiang Chinese Medical UniversityHangzhou310060China

Lung cancer ranks the top of malignancies that cause cancer-related deaths *** leaves of Morus alba L are traditional Chinese medicine widely applied in respiratory *** previous work has demonstrated the anti-lung cancer effect of secondary metabolites of mulberry leaf,but their mechanism of action has still not fully *** synthesized Moracin N(MAN)-Probe conjugated with alkyne to label lung cancer cells and identified protein targets by chemical proteomic *** and its probe exerted similar growth-inhibitory effect on human lung cancer *** proteomic results showed that MAN targeted the programmed death ligand 1(PD-L1)checkpoint pathway and T cell receptor(TCR)signaling pathway,indicating its immune-regulatory ***-free surface plasmon resonance(SPR)results showed the direct interaction of MAN with PD-L1 *** docking analysis demonstrated that MAN bound to E158 residue of PD-L1 *** downregulated the expression levels of PD-L1 in a time-and dose-dependent manner and disrupted the PD-L1/programmed death 1(PD-1)binding,including other secondary metabolites of mulberry leaves Guangsangon E(GSE)and Chalcomoracin(CMR).Human peripheral blood mononuclear cells(PBMCs)co-cultured with MAN-treated A549 cells,resulting in the increase of CD8^(+)GZMB^(+)T cells and the decrease of CD8^(+)PD-1^(+)T *** suggested that MAN exerts anti-cancer effect through blocking the PD-L1/PD-1 *** vivo,MAN combined with anti-PD-1 antibody significantly inhibited lung cancer development and metastasis,indicating their synergistic *** together,secondary metabolites of mulberry leaves target the PD-L1/PD-1 signaling,enhance T cell-mediated immunity and inhibit the tumorigenesis of lung *** modulatory effect on tumor microenvironment makes them able to enhance the therapeutic efficacy of immune checkpoint inhibitors in lung cancer.

关键词： Moracin N Click chemistry PD-L1 T cell Lung cancer

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Continuous Fe^(3+)releasing enabled complete reconstruction of Ni-based MOF for promoted water oxidation in industrial alkali

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Science China Chemistry 2024年第9期67卷 2949-2957页

作者： Zhaojian Wang Wei Zhang Wenzhong Huang Ruohan Yu Changliang Chen Liqiang mai Liang Zhou State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China Sanya Science and Education Innovation Park Wuhan University of TechnologySanya 572000China Hubei Longzhong Laboratory Wuhan University of Technology(Xiangyang Demonstration Zone)Xiangyang 441000China

Most oxygen evolution reaction(OER)electrocatalysts show poor stability under industrial alkaline conditions(20–30 wt.%KOH).Therefore,it is essential to develop stable,efficient,and low-cost OER catalysts for industrial water ***,we present a straightforward approach for the complete electrochemical reconstruction of Ni-BDC,a Ni-based metal-organic framework,for *** method involves the continuous release of Fe^(3+)from Fe foam counter electrode in a high-concentration(6.0 M,25 wt.%)KOH *** continuously Fe^(3+)releasing not only realizes in situ Fe^(3+)doping,but also introduces abundant defects in the obtained catalyst during cyclic voltammetry activation,thereby accelerating the electrochemical *** reconstructed OER catalyst(Fe-doped nickel hydroxide/oxyhydroxide nanosheets supported on Ni foam,Fe-NiO_(x)(OH)y/NF)manifests a low overpotential of 217 mV at 10 mA cm^(-2)and 263 m V at 100 m A cm^(-2)in 1.0 M ***,the Fe-NiO_(x)(OH)_(y)/NF also demonstrates high stability in 30 wt.%*** strategy of regulating the electrochemical reconstruction process sheds light on the construction of stable and efficient OER catalysts for industrial water electrolysis.

关键词： oxygen evolution reaction industrial alkaline conditions metal-organic framework complete reconstruction

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Exploring public perception and willingness to pay for a renewable source of energy: evidence from an emerging economy of renewable-energy development

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CLEAN ENERGY 2024年第2期8卷 177-188页

作者： Bashir, Mohammed J. K. Abdelhak, Senadjki Salah, Wael A. Abuhelwa, mai Cent Queensland Univ Sch Engn & Technol 120 Spencer St Melbourne Qld 3000 Australia Univ Tunku Abdul Rahman Fac Business & Finance Kampar Perak Malaysia Palestine Tech Univ Kadoorie Coll Engn & Technol Dept Elect Engn POB 7 Yafa St Tulkarm Palestine Univ Missouri Dept Elect Engn & Comp Sci Columbia MO 65211 USA

The study focuses on the transition from conventional energy sources to sustainable renewable energy (RE) in Palestine, particularly in the West Bank and Gaza Strip. The research aims to understand the relationship between key factors and residents' willingness to invest in the RE sector, with a specific focus on the impact of education. Using the unified theory of acceptance and use of technology, the study analyzes data from 400 residents through a questionnaire and employs ordinary least-squares regression analysis with Eviews 12. The key findings indicate that residents' inclination to invest in RE is significantly influenced by factors such as resource availability, knowledge level and power outages. Moreover, the study suggests that educated residents are more likely to invest in RE when factors such as knowledge, effort expectation, enabling conditions and resource availability are relatively high. The conclusion emphasizes the importance of policymakers' allocating sufficient funds to research and development to promote technological innovation in RE sources, thereby enhancing the population's energy efficiency. The study focuses on the transition from conventional energy to sustainable renewable energy in Palestine, particularly in the West Bank and Gaza Strip, to understand the relationship between key factors and residents' willingness to invest in the RE sector, with a specific focus on the impact of education. Graphical Abstract

关键词： renewable energy technology energy security public perceptions sustainable development UNIFIED THEORY RURAL-AREAS TECHNOLOGY ACCEPtanCE DETERMINANTS INTENTION RELIABILITY SERVICES SYSTEM ERRORS

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Online soft measurement for wastewater treatment system based on hybrid deep learning

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Frontiers of Environmental Science & Engineering 2024年第2期18卷 77-89页

作者： Wenjie mai Zhenguo Chen Xiaoyong Li Xiaohui Yi Yingzhong Zhao Xinzhong He Xiang Xu Mingzhi Huang SCNU Environmental Research Institute Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety&MOE Key Laboratory of Theoretical Chemistry of EnvironmentSchool of EnvironmentSouth China Normal UniversityGuangzhou 510006China Fujian Environmental Protection Design Institute Co.Ltd. Fuzhou 350000China Huashi(Fujian)Environment Technology Co.Ltd. Quanzhou362001China SCNU Qingyuan Institute of Science and Technology Innovation Co.Ltd. Qingyuan 511517China Econ Technology Co.Ltd. Yantai 265503China

The existing automated wastewater treatment control systems encounter challenges such as the utilization of specialized testing instruments, equipment repair complications, high operational costs, substantial operational errors, and low detection accuracy. An effective soft measure model offers a viable approach for real-time monitoring and the development of automated control in the wastewater treatment process. Consequently, a novel hybrid deep learning CNN-BNLSTM-Attention (CBNLSMA) model, which incorporates convolutional neural networks (CNN), bidirectional nested long and short-term memory neural networks (BNLSTM), attention mechanisms (AM), and Tree-structure Parzen Estimators (TPE), has been developed for monitoring effluent water quality during the wastewater treatment process. The CBNLSMA model is divided into four stages: the CNN module for feature extraction and data filtering to expedite operations;the BNLSTM module for temporal data’s temporal information extraction;the AM module for model weight reassignment;and the TPE optimization algorithm for the CBNLSMA model’s hyperparameter search optimization. In comparison with other models (TPE-CNN-BNLSTM, TPE-BNLSTM-AM, TPE-CNN-AM, PSO-CBNLSTMA), the CBNLSMA model reduced the RMSE for effluent COD prediction by 25.4%, decreased the MAPE by 32.9%, and enhanced the R2 by 14.9%. For the effluent SS prediction, the CBNLSMA model reduced the RMSE by 26.4%, the MAPE by 21.0%, and improved the R2 by 35.7% compared to other models. The simulation results demonstrate that the proposed CBNLSMA model holds significant potential for real-time effluent quality monitoring, indicating its high potential for automated control in wastewater treatment processes.

关键词： Prediction model Soft measurement CNN-BNLSTM-AM model TPE optimization algorithm

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Explainable AI-Based DDoS Attacks Classification Using Deep Transfer Learning

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Computers, Materials & Continua 2024年第9期80卷 3785-3802页

作者： Ahmad Alzu’bi Amjad Albashayreh Abdelrahman Abuarqoub mai A.M.Alfawair Department of Computer Science Jordan University of Science and TechnologyIrbid22110Jordan Department of Computer Science The University of JordanAmman11942Jordan Cardiff School of Technologies Cardiff Metropolitan UniversityCardiffCF52YBUK Prince Abdullah bin Ghazi Faculty of Information and Communication Technology Al-Balqa Applied UniversitySalt19117Jordan

In the era of the Internet of Things(IoT),the proliferation of connected devices has raised security concerns,increasing the risk of intrusions into diverse *** the convenience and efficiency offered by IoT technology,the growing number of IoT devices escalates the likelihood of attacks,emphasizing the need for robust security tools to automatically detect and explain *** paper introduces a deep learning methodology for detecting and classifying distributed denial of service(DDoS)attacks,addressing a significant security concern within IoT *** effective procedure of deep transfer learning is applied to utilize deep learning backbones,which is then evaluated on two benchmarking datasets of DDoS attacks in terms of accuracy and time *** leveraging several deep architectures,the study conducts thorough binary and multiclass experiments,each varying in the complexity of classifying attack types and demonstrating real-world ***,this study employs an explainable artificial intelligence(XAI)AI technique to elucidate the contribution of extracted features in the process of attack *** experimental results demonstrate the effectiveness of the proposed method,achieving a recall of 99.39%by the XAI bidirectional long short-term memory(XAI-BiLSTM)model.

关键词： DDoS attack classification deep learning explainable AI cybersecurity

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