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Mechanistic insight into the synergy between nickel single atoms and nanoparticles on N-doped carbon for electroreduction of CO2

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Journal of Energy Chemistry 2025年第1期100卷 327-336页

作者： Mingdong Sun Wenwen Guan Cailing Chen Chao Wu Xiaoling Liu Biao Meng Tao Chen Yu Han Jun Wang Shibo Xi Yu Zhou State Key Laboratory of Materials-Oriented Chemical Engineering College of Chemical Engineering Nanjing Tech University Advanced Membranes and Porous Materials Center Physical Sciences and Engineering Division King Abdullah University of Science and Technology Institute of Sustainability for Chemicals Energy and Environment A*STAR (Agency for Science Technology and Research) College of Materials science and Engineering Sichuan University

The synergy of single atoms （SAs） and nanoparticles （NPs） has demonstrated great potential in promoting the electrocatalytic carbon dioxide reduction reaction （CO2RR）;however,the rationalization of the SAs/NPs proportion remains one challenge for the catalyst ***,a Ni2+-loaded porous poly（ionic liquids）(PIL) precursor synthesized through the free radical self-polymerization of the ionic liquid monomer,1-allyl-3-vinylimidazolium chloride,was pyrolyzed to prepare the Ni,N co-doped carbon materials,in which the proportion of Ni SAs and NPs could be facilely modulated by controlling the annealing *** catalyst Ni-NC-1000 with a moderate proportion of Ni SAs and NPs exhibited high efficiency in the electrocatalytic conversion of CO2into *** Ni K-edge X-ray absorption near-edge structure （XANES） spectra and theoretical calculations were conducted to gain insight into the synergy of Ni SAs and *** charge transfer from Ni NPs to the surrounding carbon layer and then to the Ni SAs resulted in the electron-enriched Ni SAs active *** the electroreduction of CO2,the coexistence of Ni SAs and NPs strengthened the CO2activation and the affinity towards the key intermediate of*COOH,lowering the free energy for the potential-determining*CO2→*COOH step,and therefore promoted the catalysis efficiency.

关键词： Activation energy

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A spotlight on dosage and subject selection for effective neuroprotection: exploring the central role of mitochondria

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Neural Regeneration Research 2025年第4期20卷 1081-1082页

作者： John Mitrofanis Jonathan Stone Michael R.Hamblin Pierre Magistretti Alim-Louis Benabid Glen Jeffery Fonds Clinatec UniversitéGrenoble AlpesGrenobleFrance School of Medical science University of SydneySydneyAustralia Faculty of Health sciences University of JohannesburgJohannesburgSouth Africa king abdullah university of science and technology ThuwalSaudi Arabia Institute of Ophthalmology University College LondonLondonUK

Neurons are notoriously vulnerable cell *** the slightest change in their internal and/or external environments will cause much distress and dysfunction,leading often to their death.A range of pathological conditions,including stroke,head trauma,and neurodegenerative disease,can generate stress in neurons,affecting their survival and proper *** most neural pathologies,mitochondria become dysfunctional and this plays a pivotal role in the process of cell *** challenge over the last few decades has been to develop effective interventions that improve neuronal homeostasis under pathological *** interventions,often referred to as disease-modifying or neuroprotective,have,however,proved frustratingly elusive,at both preclinical and,in particular,clinical *** this perspective,we highlight two factors that we feel are key to the development of effective neuroprotective *** are:firstly,the choice of dose of intervention and method of application,and secondly,the selection of subjects,whether they be patients or the animal model.

关键词： protective dosage distress

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A Latency-Aware and Fault-Tolerant Framework for Resource Scheduling and Data Management in Fog-Enabled Smart City Transportation Systems

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Computers, Materials & Continua 2025年第1期82卷 1377-1399页

作者： Ibrar Afzal Noor ul Amin Zulfiqar Ahmad Abdulmohsen Algarni Department of Computer science and Information technology Hazara UniversityMansehra21300Pakistan Department of Computer science King Khalid UniversityAbha61421Saudi Arabia

Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation *** computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end *** of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud *** smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system *** address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog *** framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation *** FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud *** simulation-based executions,tasks are allocated to the nearest available nodes with minimum *** the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of *** successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.

关键词： Fog computing smart cities smart transportation data management fault tolerance resource scheduling

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Simulations of electron zebra stripes in the inner radiation belt using a composite empirical electric field model

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science China Earth sciences 2025年第1期68卷 27-38页

作者： Ziyang WANG Ying LIU Qiugang ZONG Hong ZOU Yuguang YE Xuzhi ZHOU Chao YUE Shan WANG Institute of Space Physics and Applied technology Peking University State Key Laboratory of Lunar and Planetary science Macau University of Science and Technology

The phenomenon termed “zebra stripes” manifests as regular patterns in the energy-space(L shell) spectrum of energetic electrons(ranging from tens to hundreds ke V) within the inner radiation belt. These structures exhibit drift-periodic behavior and commonly arise from large-scale electric field perturbations near the substorm onsets. In this study, we introduce a composite electric field model and replicate the formation, structure, and evolution of zebra stripes using a bounce-averaged test particle code under this electric field model. High-resolution measurements of energetic electrons obtained from the Van Allen Probes and the recently launched Macao science Satellites-1 are used as initial conditions and served to validate our test particle simulations. Comparative analyses between observed data and simulations demonstrate our test particle method's efficacy in capturing zebra stripes' general behavior. Moreover, the composite model proves capable of reproducing realistic variations in the electric field within the inner radiation belt to a certain extent. Nevertheless, subtle differences emerge in the flux strength and the positions of stripes. These disparities primarily stem from limitations inherent in the electric field model and the initial conditions of the simulation. Acknowledging that the model represents an average case, it is conceivable that real-world scenarios may deviate from the average, thereby introducing variations in the observed phenomena.

关键词： Zebra stripes Inner radiation belt Large-scale electric fields Van Allen Probes Macao science Satellite

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Hybrid Deep Learning Approach for Automating App Review Classification:Advancing Usability Metrics Classification with an Aspect-Based Sentiment Analysis Framework

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Computers, Materials & Continua 2025年第1期82卷 949-976页

作者： Nahed Alsaleh Reem Alnanih Nahed Alowidi Department of Computer science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer science College of Computer Science and EngineeringUniversity of HailHail81451Saudi Arabia

App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their *** the analysis of these reviews is vital for efficient review *** traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior *** research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and *** propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification *** analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,*** contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews *** advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.

关键词： Requirements Engineering(RE) app review analysis usabilitymetrics hybrid deep learning BERT-BiLSTM-CNN

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Experimental study of dual nano-network, high-temperature resistant aerogel material as an integration of thermal management functions

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Journal of Energy Chemistry 2025年第1期100卷 157-170页

作者： Yueyue Xiao Tianke Mao Zun Zhao Yuelei Pan Heping Zhang Xudong Cheng State Key Laboratory of Fire science University of Science and Technology of China

Thermal management system is highly desirable to guarantee the performance and thermal safety of lithium-ion batteries,but it reduces the energy density of battery modules and even is unable to provide highly effective ***,a thermal management function integrated material is presented based on high-temperature resistant aerogel and phase change material and is applied at both charge–discharge process and thermal runaway *** this sandwich structure Paraffin@SiC nanowire/Aerogel sheet （denoted as PA@SAS） system,SiC nanowires endow the middle aerogel sheet （SAS） a dual nano-network *** enhanced mechanical properties of SAS were studied by compressive tests and dynamic mechanical ***,the thermal conductivity of SAS at 600°C is only 0.042 W/（m K）.The surface phase change material layers facilitate temperature uniformity of batteries （surface temperature difference less than 1.82°C） through latent ***,a large-format battery module with four 58 Ah LiNi0.5Co0.2Mn0.3O2LIBs was ***@SAS successfully prevents thermal runaway propagation,yielding a temperature gap of 602°C through the 2 mm-thick cross ***@SAS also exhibits excellent performance in other safety issues such as temperature rise rate,flame heat flux,*** lightweight property and effective insulation performance achieves significant safety enhancement with mass and volume energy density reduction of only 0.79%and 5.4%,*** originality of the present research stems from the micro and macro structure design of the proposed thermal management material and the combination of intrinsic advantages of every *** work provides a reliable design of achieving the integration of thermal management functions into an aerogel composite and improves the thermal safety of lithium-ion batteries.

关键词： Thermal insulation

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First observation results of Macao science Satellite-1 on lightning-induced electron precipitation

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science China Earth sciences 2025年第1期68卷 1-10页

作者： Yongping WANG Yixin SUN Qiugang ZONG Gaopeng LU Xudong GU Ze-Jun HU Bin LI Key Laboratory for Polar science Ministry of Natural Resources Polar Research Institute of China Institute of Space Physics and Applied technology Peking University State Key Laboratory of Lunar and Planetary science Macau University of Science and Technology School of Earth and Space sciences University of Science and Technology of China School of Electronic Information Wuhan University

The Medium-energy Electron Spectrometers(MES) is a space-borne instrument onboard Macao science Satellite-1(MSS-1) dedicated to monitoring the typical charged particle radiation characteristics in the satellite orbit and the process of their occurrence and development, including short bursts of lightning-induced electron precipitation(LEP).This paper presents the first results of the LEP measurements by the MSS-1.47 LEP events are identified with the routine operation for 3 months since satellite launch, all within the range of 1.5

关键词： Lightning-induced electron precipitation Inner radiation belts Energetic electrons Macao science Satellite-1

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Research on Stock Price Prediction Method Based on the GAN-LSTM-Attention Model

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Computers, Materials & Continua 2025年第1期82卷 609-625页

作者： Peng Li Yanrui Wei Lili Yin College of Computer science and technology Harbin University of Science and TechnologyHarbin150006China

Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and *** paper introduces a generative adversarial network model that incorporates an attention mechanism(GAN-LSTM-Attention)to improve the accuracy of stock price ***,the generator of this model combines the Long and Short-Term Memory Network(LSTM),the Attention Mechanism and,the Fully-Connected Layer,focusing on generating the predicted stock *** discriminator combines the Convolutional Neural Network(CNN)and the Fully-Connected Layer to discriminate between real stock prices and generated stock ***,to evaluate the practical application ability and generalization ability of the GAN-LSTM-Attention model,four representative stocks in the United States of America(USA)stock market,namely,Standard&Poor’s 500 Index stock,Apple Incorporatedstock,AdvancedMicroDevices Incorporatedstock,and Google Incorporated stock were selected for prediction experiments,and the prediction performance was comprehensively evaluated by using the three evaluation metrics,namely,mean absolute error(MAE),root mean square error(RMSE),and coefficient of determination(R2).Finally,the specific effects of the attention mechanism,convolutional layer,and fully-connected layer on the prediction performance of the model are systematically analyzed through ablation *** results of experiment show that the GAN-LSTM-Attention model exhibits excellent performance and robustness in stock price prediction.

关键词： Stock price prediction generative adversarial network attention mechanism time-series prediction

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Nano-Enhanced Dairy Scum Biodiesel Blends:Unleashing the Power of Aluminium Oxide for Sustainable and Efficient Engine Performance

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Journal of Thermal science 2025年第1期34卷 283-302页

作者： Veeranna MODI Prasad B.RAMPURE Sunil Kumar SHETTY Madeva NAGARAL Channa Keshava NAIK N Johar MGM Muhammad Irsyad abdullah abdullah I.AL-MANSOUR Shamshad ALAM KLE College of Engineering and technology ChikodiVisvesvaraya Technological University Nitte (Deemed to be university) NMAM Institute of Technology (NMAMIT)Department of Mechanical Engineering Aircraft Research and Design Centre HAL Department of Mechanical Engineering BGS College of Engineering and TechnologyBengaluruAffiliated to Visvesvaraya Technological University Management and science university Department of Civil Engineering College of EngineeringKing Saud University

This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel *** dispersion of Al2O3nanoparticles in B20 blends at different concentrations was done with the help of *** number of blends were prepared for the *** Machine learning algorithms(Random Forest（RF）and CatBoost) was used for the *** results show that in comparison to biodiesel blends without nanoparticles,the kinematic viscosity and density is higher for fuel blends with *** these Fuel blends have higher calorific *** blends exhibited reduced Brake Specific Fuel Consumption（BSFC） of2.85% than the blends without nano particles(Dairy Scum Methyl Ester Biodiesel 20%+Neat Diesel 80%（in volume）,DSMEB20),57.14% less CO,40.8% less hydrocarbon,and increased NOxemissions compared to conventional diesel,contributing to the development of environmentally friendly and renewable biofuel blends with *** B20NP30 is the optimal blend for performance and emission *** study concludes with findings on enhanced Brake Thermal Efficiency（BTE） of 26.29% in 3×10-5（in volume） Al2O3nanoparticle-blended DSME B20 and other DSME B20 fuel blends,emphasizing the importance of optimal nanoparticle *** correlation matrix shows how engine load,efficiency measures（BTE,BSFC）,and emissions（CO,CO2,NOx,Smoke） are connected in complex *** results help us understand the complicated dynamics of engine performance and emission characteristics ***'s diagram for BTE and BSFC shows that CatBoost-based BTE models perform superior to RF-based models during the training as well as testing *** results were obtained for CO and CO2emission results.

关键词： Al2O3 concentration CI engine Dairy Scum Methyl Ester Biodiesel

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Negative PO3-implanted bionic ion transport channels for promoting Li-S battery

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science China Chemistry 2025年

作者： Wenhuan Huang Shun Wang Xuehan Hou Yanan Zhang Xingxing Zhang Yaoxiao Zhao Xilang Jin Huabin Zhang Fei Wang Jian Zhang Key Laboratory of Chemical Additives for China National Light Industry College of Chemistry and Chemical EngineeringShaanxi University of Science and Technology School of Materials and Chemical Engineering Xi'an Technological University Chemistry Program Physical Science and Engineering Division King Abdullah University of Science and Technology State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences

Lithium-sulfur （Li-S） battery,as a promising next-generation high-energy-density battery,suffers from lithium polysulfides（LPSs） shuttle and Li dendrites *** crystalline framework-based membranes as separator can effectively absorb and restrain LPSs but without precise structural design principal exploration and mechanism ***,bio-inspired 1D oriented lithium-ion transport channels with molecular negatively charged PO3（-1） have been developed in hybrid tetrazole frameworks for promoting the transmission of Li+*** theoretical calculations and in situ spectroscopy demonstrated the higher binding energy and inhibited diffusion of LPSs in *** assembled PP@PO3Janus separator in Li-S coin cell delivered a high initial capacity of 1410.9 mAh g-1at 0.1 C and a low attenuation rate of 0.038%per cycle over 500 cycles at 5 ***,the high capacities of 862,542 and 409 mAh g-1based on high-sulfur-loading cathodes of 2.6,3.8 and 5.0 mg cm-2at0.5 C were achieved,***,the punch battery of PO3@PP separator with S-cathode of 1.2 mg cm-2has been developed for demonstrating its potentials commercial application,which displays impressive capacity of 873.4 mAh g-1with the retention of～78.9%over 50 cycles.

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