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Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing systems engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University department of Electrical engineering and Automation Luoyang Institute of Science and Technology School of Mechanical engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Lithium-ion battery State-of-health estimation Data-driven Machine learning Ensemble learning Ensemble diversity

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Data-Driven Healthcare:The Role of Computational Methods in Medical Innovation

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Computer Modeling in engineering & Sciences 2025年第1期142卷 1-48页

作者： Hariharasakthisudhan Ponnarengan Sivakumar Rajendran Vikas Khalkar Gunapriya Devarajan Logesh Kamaraj department of Mechanical engineering Dr.Mahalingam College of Engineering and TechnologyPollachiCoimbatoreTamil Nadu642003India department of Mechanical engineering JKKN College of Engineering and TechnologyKumarapalayamNamakkalTamil Nadu637209India department of Mechanical engineering Gharda Institute of TechnologyLavelMaharashtra415708India department of Electrical and Electronics engineering Sri Eshwar College of EngineeringCoimbatoreTamilnadu641202India department of Mechanical engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India

The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical *** review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health *** findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and *** synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment ***,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease *** review emphasizes the need for interdisciplinary collaboration to further advance this *** research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and *** fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

关键词： Computational models biomedical engineering bioinformatics machine learning wearable technology

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Passive activity enhances residual control ability in patients with complete spinal cord injury

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Neural Regeneration Research 2025年第8期20卷 2337-2347页

作者： Yanqing Xiao Mingming Gao Zejia He Jia Zheng Hongming Bai Jia-Sheng Rao Guiyun Song Wei Song Xiaoguang Li Beijing Key Laboratory for Biomaterials and Neural Regeneration Beijing Advanced Innovation Center for Biomedical EngineeringSchool of Biological Science and Medical EngineeringBeihang UniversityBeijingChina department of Rehabilitation Evaluation China Rehabilitation Research CenterBeijingChina Cardiac Center Beijing Children’s HospitalCapital Medical UniversityBeijingChina The State Key Laboratory of Virtual Reality Technology and systems Beihang UniversityBeijingChina department of Rehabilitation engineering China Rehabilitation Science InstituteBeijingChina

Patients with complete spinal cord injury retain the potential for volitional muscle activity in muscles located below the spinal injury ***,because of prolonged inactivity,initial attempts to activate these muscles may not effectively engage any of the remaining neurons in the descending pathway.A previous study unexpectedly found that a brief clinical round of passive activity significantly increased volitional muscle activation,as measured by surface *** this study,we further explored the effect of passive activity on surface electromyographic signals during volitional control tasks among individuals with complete spinal cord *** patients with chronic complete thoracic spinal cord injury were *** electromyography data from eight major leg muscles were acquired and compared before and after the passive activity *** results indicated that the passive activity led to an increased number of activated volitional muscles and an increased frequency of *** the cumulative root mean square of surface electromyography amplitude for volitional control of movement showed a slight increase after passive activity,the difference was not statistically *** findings suggest that brief passive activity may enhance the ability to initiate volitional muscle activity during surface electromyography tasks and underscore the potential of passive activity for improving residual motor control among patients with motor complete spinal cord injury.

关键词： complete spinal cord injury cycle training epidural electrical stimulation motor training passive activity physiological state spinal cord circuit surface electromyography volitional control task

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Enhanced solid-electrolyte interface efficiency for practically viable hydrogen-air fuel cell systems

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Journal of Energy Chemistry 2025年第1期100卷 356-368页

作者： Venkitesan Sakthivel Dong Jin Yoo Graduate School Department of Energy Storage/Conversion Engineering (BK21 FOUR) Hydrogen and Fuel Cell Research Center Jeonbuk National University Jeonju department of Life Science Jeonbuk National University

Proton exchange membrane fuel cells （PEMFCs） provide an appealing sustainable energy system,with the solid-electrolyte membrane playing a crucial role in its overall ***,sulfonated poly（1,4-phenylene ether-ether sulfone）(SPEES),an aromatic hydrocarbon polymer,has garnered considerable attention as an alternative to Nafion ***,the long-term durability and stability of SPEES present a significant *** this context,we introduce a potential solution in the form of an additive,specifically a core–shell-based amine-functionalized iron titanate （A–Fe2TiO5）,which holds promise for improving the lifetime,proton conductivity,and power density of SPEES in *** modified SPEES/A–Fe2TiO5composite membranes exhibited notable characteristics,including high water uptake,enhanced thermomechanical stability,and oxidative ***,the SPEES membrane loaded with 1.2 wt%of A–Fe2TiO5demonstrates a maximum proton conductivity of 155 mS cm-1,a twofold increase compared to the SPEES membrane,at 80°C under 100%relative humidity （RH）.Furthermore,the 1.2 wt%of A–Fe2TiO5/SPEES composite membranes exhibited a maximum power density of 397.37 mW cm-2and a current density of 1148 mA cm-2at 60°C under 100%RH,with an opencircuit voltage decay of 0.05 m V/h during 103 h of continuous *** study offers significant insights into the development and understanding of innovative SPEES nanocomposite membranes for PEMFC applications.

关键词： Acid-base Hybrid membrane Proton conductivity Polymer electrolyte fuel cell Single-cell performance

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Regression analysis of squeezing-induced hybrid nanofluid flow in Darcy-Forchheimer porous medium

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 193-208页

作者： K.MUHAMMAD M.SARFRAZ department of Humanities and Sciences School of Electrical Engineering and Computer Science National University of Sciences and Technology department of Mathematics Quaid-i-Azam University

This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates. One plate remains stationary, while the other moves downward at a squeezing velocity. The space between these plates contains a Darcy-Forchheimer porous medium. A mixture of water-based fluid with gold(Au) and silicon dioxide(Si O2) nanoparticles is formulated. In contrast to the conventional Fourier's heat flux equation, this study employs the Cattaneo-Christov heat flux equation. A uniform magnetic field is applied perpendicular to the flow direction, invoking magnetohydrodynamic(MHD) effects. Further, the model accounts for Joule heating, which is the heat generated when an electric current passes through the fluid. The problem is solved via NDSolve in MATHEMATICA. Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow, energy transport, and skin *** findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies. It is observed that the squeezing motion generates additional pressure gradients within the fluid, which enhances the flow rate but reduces the frictional drag. Consequently, the fluid is pushed more vigorously between the plates, increasing the flow velocity. As the fluid experiences higher flow rates due to the increased squeezing effect, it spends less time in the region between the plates. The thermal relaxation, however, abruptly changes the temperature, leading to a decrease in the temperature fluctuations.

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Branched module-modified SN38 prodrug nanoassemblies for improved colorectal cancer therapy:Effectively balance efficacy and safety

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Nano Research 2025年第1期18卷 572-585页

作者： Qing Wang Shiyi Zuo Shufang Zheng Cuiyun Liu Yaqiao Li Jiayu Guo Danping Wang Shuo Wang Wenjing Wang Bowen Zhang Minglong Huang Xianbao Shi Jin Sun Zhonggui He Bingjun Sun department of Pharmaceutics Wuya College of InnovationShenyang Pharmaceutical UniversityShenyang 110016China Joint International Research Laboratory of Intelligent Drug Delivery systems Ministry of EducationShenyang Pharmaceutical UniversityShenyang 110016China School of Chemical engineering The University of AdelaideAdelaideSA 5005Australia department of Pharmacy The First Affiliated Hospital of Jinzhou Medical UniversityJinzhou 121001China

The clinical utility of irinotecan is restricted by individual variability in carboxylesterase *** administration of its active metabolite,7-ethyl-10-hydroxycamptothecin(SN38),presents an appealing alternative due to its potent anti-tumor ***,the undesirable properties of SN38,such as poor water solubility and nontarget toxicity,present significant hurdles to its clinical *** nanoassemblies based on modular design strategy show promise in overcoming these challenges by enhancing drug delivery and selective *** modular design,the modification module plays a crucial role in improving the self-assembly capability of *** current studies mainly focus on using straight aliphatic chains for prodrug design,branched aliphatic chains emerge as superior alternatives warranting further *** this study,we selected 2-heptylundecanol(BAlc18)as modification module to construct an SN38 *** exquisite design,SN38-SS-BAlc18 NPs integrated prominent properties in selfassembly capability,specific activation and biocompatibility,resolving the challenges of irinotecan and SN38,ultimately demonstrating excellent anti-tumor *** exploration enriched the design theory of prodrug nanoassemblies that can effectively balance safety and colorectal anti-tumor efficacy.

关键词： irinotecan SN38 prodrug nanoassemblies disulfide bonds branched aliphatic chains

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Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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Computer Modeling in engineering & Sciences 2025年第1期142卷 357-384页

作者： Mohd Anjum Naoufel Kraiem Hong Min Ashit Kumar Dutta Yousef Ibrahim Daradkeh department of Computer engineering Aligarh Muslim UniversityAligarh202002India College of Computer Science King Khalid UniversityAbha61413Saudi Arabia School of Computing Gachon UniversitySeongnam13120Republic of Korea department of Computer Science and Information systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia department of Computer engineering and Information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： Computer vision feature selection machine learning region detection texture analysis image classification medical images

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A Rapid Adaptation Approach for Dynamic Air‑Writing Recognition Using Wearable Wristbands with Self‑Supervised Contrastive Learning

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Nano-Micro Letters 2025年第2期17卷 417-431页

作者： Yunjian Guo Kunpeng Li Wei Yue Nam‑Young Kim Yang Li Guozhen Shen Jong‑Chul Lee department of Electronic Convergence engineering Kwangwoon UniversitySeoul 01897South Korea Radio Frequency Integrated Circuit(RFIC)Bio Centre Kwangwoon UniversitySeoul 01897South Korea department of Electronic engineering Kwangwoon UniversitySeoul 01897South Korea School of Microelectronics Shandong UniversityJinan 250101People’s Republic of China State Key Laboratory of Integrated Chips and systems Fudan UniversityShanghai 200433People’s Republic of China School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081People’s Republic of China

Wearable wristband systems leverage deep learning to revolutionize hand gesture recognition in daily *** existing approaches that often focus on static gestures and require extensive labeled data,the proposed wearable wristband with selfsupervised contrastive learning excels at dynamic motion tracking and adapts rapidly across multiple *** features a four-channel sensing array composed of an ionic hydrogel with hierarchical microcone structures and ultrathin flexible electrodes,resulting in high-sensitivity capacitance *** wireless transmission from a Wi-Fi module,the proposed algorithm learns latent features from the unlabeled signals of random wrist ***,only few-shot labeled data are sufficient for fine-tuning the model,enabling rapid adaptation to various *** system achieves a high accuracy of 94.9%in different scenarios,including the prediction of eight-direction commands,and air-writing of all numbers and *** proposed method facilitates smooth transitions between multiple tasks without the need for modifying the structure or undergoing extensive task-specific *** utility has been further extended to enhance human–machine interaction over digital platforms,such as game controls,calculators,and three-language login systems,offering users a natural and intuitive way of communication.

关键词： Wearable wristband Self-supervised contrastive learning Dynamic gesture Air-writing Human-machine interaction

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Effects of Freestream Turbulence on Bypass Transition of Separated Boundary Layer on Low-Pressure Turbine Airfoils

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Journal of Thermal Science 2012年第3期21卷 230-235页

作者： Hideo Taniguchi Hiroshi Sakai Ken-ichi Funazaki department of Mechanical systems engineering Faculty of EngineeringIwate University

This paper presents experimental studies on bypass transition of separated boundary layer on low-pressure turbine airfoils,focusing on the effects of freestream turbulence on the transition ***-wire probe measurements are performed on the suction side of an airfoil in the low-pressure linear turbine cascade at several Reynolds number *** turbulence is enhanced by use of turbulence grid located upstream of the *** results of this experimental study show that the location of boundary layer separation does not strongly de-pend on the freestream turbulence ***,as the freestream turbulence level increases,the size of separa-tion bubble becomes small and the location of turbulent transition moves *** size of separation bubble becomes small as the Reynolds number *** low freestream turbulence intensity,the velocity fluctuation due to Kelvin-Helmholtz instability is observed clearly in the shear layer of the separation *** high frees-tream turbulence intensity,the streak structures appear upstream of the separation location,indicating bypass transition of attached boundary layer occurs at high Reynolds number.

关键词： Aeroengine Low-Pressure Turbine Bypass Transition Separation Bubble

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Memoryless cooperative graph search based on the simulated annealing algorithm

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Chinese Physics B 2011年第4期20卷 524-531页

作者：候健颜钢锋樊臻 department of systems Science and engineering Zhejiang University

We have studied the problem of reaching a globally optimal segment for a graph-like environment with a single or a group of autonomous mobile agents. Firstly, two efficient simulated-annealing-like algorithms are given for a single agent to solve the problem in a partially known environment and an unknown environment, respectively. It shows that under both proposed control strategies, the agent will eventually converge to a globally optimal segment with probability 1. Secondly, we use multi-agent searching to simultaneously reduce the computation complexity and accelerate convergence based on the algorithms we have given for a single agent. By exploiting graph partition, a gossip-consensus method based scheme is presented to update the key parameter--radius of the graph, ensuring that the agents spend much less time finding a globally optimal segment.

关键词： search simulated annealing graph partition globally optimal

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