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Joint Estimation of SOH and RUL for Lithium-Ion Batteries Based on Improved Twin Support Vector Machineh

Energy Engineering 2025年第1期122卷 243-264页

作者： Liyao Yang HongyanMa Yingda Zhang wei He School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China Institute of Distributed Energy Storage Safety Big Data Beijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing100044China

Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management ***,due to the complex internal chemical systems of LIBs and the nonlinear degradation of their performance,direct measurement of SOH and RUL is *** address these issues,the Twin Support Vector Machine(TWSVM)method is proposed to predict SOH and ***,the constant current charging time of the lithium battery is extracted as a health indicator(HI),decomposed using Variational Modal Decomposition(VMD),and feature correlations are computed using Importance of Random Forest Features(RF)to maximize the extraction of critical factors influencing battery performance ***,to enhance the global search capability of the Convolution Optimization Algorithm(COA),improvements are made using Good Point Set theory and the Differential Evolution *** Improved Convolution Optimization Algorithm(ICOA)is employed to optimize TWSVM parameters for constructing SOH and RUL prediction ***,the proposed models are validated using NASA and CALCE lithium-ion battery *** results demonstrate that the proposed models achieve an RMSE not exceeding 0.007 and an MAPE not exceeding 0.0082 for SOH and RUL prediction,with a relative error in RUL prediction within the range of[-1.8%,2%].Compared to other models,the proposed model not only exhibits superior fitting capability but also demonstrates robust performance.

关键词： State of health remaining useful life variational modal decomposition random forest twin support vector machine convolutional optimization algorithm

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Microplastic and nanoplastic exposure and risk of diabetes mellitus

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World Journal of Clinical Cases 2025年第3期13卷 24-29页

作者： hui-Yi Hsiao Chung-Yi Nien Ruei-Feng Shiu wei-Chun Chin Tzung-Hai Yen Department of Biomedical Sciences College of MedicineChang Gung UniversityTaoyuan 33302TaiwanChina Center for Tissue Engineering Chang Gung Memorial HospitalLinkouTaoyuan 33305TaiwanChina Department of Life Sciences National Central UniversityZhongli 320317TaoyuanTaiwanChina Center of Excellence for The Oceans Taiwan Ocean UniversityKeelung 20224TaiwanChina Institute of Marine Environment and Ecology Taiwan Ocean UniversityKeelung 20224TaiwanChina Department of Chemical and Materials Engineering University of California MercedMercedCA 95343United States Department of Nephrology Clinical Poison CenterChang Gung Memorial HospitalLinkou 33305TaoyuanTaiwanChina School of Traditional Chinese Medicine College of MedicineChang Gung UniversityTaoyuan 33302TaiwanChina

The issue of plastic pollutants has become a growing *** microplastics(MPs)(particle size<5 mm)and nanoplastics(NPs)(particle size<1μm)can cause DNA damage,cytotoxicity,and oxidative stress in various *** primary known impacts of microplastic/nanoplastic are observed in the liver and respiratory system,leading to hepatotoxicity and chronic obstructive pulmonary *** research on the effects of MPs and NPs on diabetes is still in its early stages,there are potential *** editorial highlights the risk to diabetics from co-exposure to contaminants and MPs/NPs,supported by evidence from animal studies and the various chemical compositions of MPs/NPs.

关键词： Microplastics Nanoplastics Plastic pollution,Diabetes mellitus Insulin resistance

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Numerical investigation of a muzzle multiphase flow field using two underwater launch methods

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Defence Technology（防务技术） 2022年第8期18卷 1454-1469页

作者： Jing-hui Zhang Yong-gang Yu Xin-wei Zhang School of Energy and Power Engineering Nanjing University of Science&TechnologyNanjing210094China

A two-dimensional axisymmetric model, employing a dynamic mesh and user-defined functions, is used to numerically simulate the transient multiphase flow field produced by an underwater gun. Furthermore, a visualized shooting experiment platform with a high-speed camera is built to observe the evolution process of such a multiphase flow field. The simulated phase distribution diagram is agreed well with the shadow photo of the experiment, indicating that the numerical model is reasonable. Further examinations of the multiphase flow fields by using the submerged and sealed launch methods show that use of the sealed launch can significantly improve the interior ballistic performance of an underwater gun. In the cases by using these two types of underwater launch methods, the displacement of the projectile within the range of the muzzle flow field meets the exponential law over time. Moreover, a not fully developed bottle-shaped shock wave is formed when t = 0.4 ms, but this bottle-shaped shock wave expands more rapidly for the sealed launch. In addition, the amplitude of pressure oscillation for the sealed launch is larger than that of the submerged launch, but the pressure oscillation of the sealed launch lasts shorter.

关键词： Underwater launch Multiphase flow Muzzle flow field Numerical simulation Mach disk

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AI-Enhanced Secure Data Aggregation for Smart Grids with Privacy Preservation

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Computers, Materials & Continua 2025年第1期82卷 799-816页

作者： Congcong Wang Chen Wang Wenying Zheng wei Gu School of Software Nanjing University of Information Science and TechnologyNanjing210044China School of Information Science and Engineering Zhejiang Sci-Tech UniversityHangzhou310018China State Key Laboratory of Public Big Data Guizhou UniversityGuiyang550025China School of Computer Science and Technology(School of Artificial Intelligence) Zhejiang Sci-Tech UniversityHangzhou310018China School of Computer Science(School of Cyber Science and Engineering) Nanjing University of Information Science and TechnologyNanjing210044China

As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy *** research emphasizes data security and user privacy concerns within smart ***,existing methods struggle with efficiency and security when processing large-scale *** efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent *** paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data *** approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user *** also explores the application of Boneh Lynn Shacham(BLS)signatures for user *** proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.

关键词： Smart grid data security privacy protection artificial intelligence data aggregation

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Small modifications of endo-functionalized cavities lead to large changes in molecular interaction in water

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Science China Chemistry 2025年第1期68卷 369-376页

作者： Song-Meng Wang Hao Nian Yan-Fang Wang Li-Shuo Zheng Yu-Tao Zheng Yi-wei Dong Liping Huang Xiaoping Wang wei Jiang Liu-Pan Yang Department of Chemistry Southern University of Science and Technology School of Chemistry and Pharmaceutical Sciences State Key Laboratory for Chemistry and Molecular Engineering of Medicinal ResourcesGuangxi Normal University School of Pharmaceutical Science Hengyang Medical School University of South China

Studying molecular recognition in aqueous environments is crucial for understanding biological processes. Herein, we present a series of N-doped endo-functionalized anthracene-based cavities by introducing inward-directed pyridine units. The subtle modifications can significantly affect the binding properties of these receptors, which is similar to the mutations in biological systems. Combining theoretical calculations and molecular recognition experiments demonstrated that these “mutations” have an impact on the hydrophobicity and charge distribution of the hosts, consequently significantly influencing molecular *** is crucial for understanding the intricate mechanisms of molecular-level interactions in biological receptors.

关键词： host-guest interaction hydrophobic effect endo-functionalized cavity mutation pyridine

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Domain generalization with semi-supervised learning for people-centric activity recognition

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Science China(Information Sciences) 2025年第1期68卷 171-188页

作者： Jing LIU wei ZHU Di LI Xing HU Liang SONG Academy for Engineering & Technology Fudan University Shanghai East-bund Research Institute on Networking Systems of AI School of Optoelectronic Information and Computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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Aerodynamic Optimization and Flow Mechanism for a Compressor Cascade at Low Reynolds Number

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Journal of Thermal Science 2025年第1期34卷 92-109页

作者： LI Lin ZHANG Jianshe CHEN Caiyan TAN wei ZHANG Yanfeng Key Laboratory of Light-Duty Gas-Turbine Institute of Engineering ThermophysicsChinese Academy of Sciences University of Chinese Academy of Sciences National Key Laboratory of Science and Technology on Advanced Light-duty Gas-turbine

Low-Reynolds-number effect is an important factor affecting the performance of compressors and other main components of high-altitude long-endurance unmanned aerial *** improve the flow condition and reduce flow loss under the condition of high altitude and low Reynolds number(Re),this paper proposes an optimization process based on a surrogate model,which combines the class-shape transformation method(CST),the Latin hypercube sampling(LHS) method,the light gradient-boosting machine algorithm(LightGBM),and a genetic algorithm(GA) to optimize a high-subsonic compressor *** surrogate model is verified to be accurate and can be used in the optimization *** accuracy of the GA is higher than the other algorithms under common test *** optimization results are verified by numerical simulation,and the flow differences before and after optimization are compared,especially the flow within the boundary *** changing the blade shape,the optimization process adjusts the loading distribution to delay the transition of the optimized blade on the suction surface,which changes the turbulent reattachment in the laminar separation bubble(LSB) into laminar ***,the mixing loss induced by the turbulent reattachment of the LSB and the wake loss of turbulent separation at the trailing edge are significantly reduced,and the performance of the compressor profile is finally *** addition,turbulent separation of the optimized profile is delayed reducing the range of the wake region on the suction *** this optimization process,the reduction of total pressure loss coefficient at Re of 2.5×10～5,3.5×10～5,and 4.5×10～5 are 16.32%,20.76%,and 22.16%,respectively.

关键词： Reynolds number

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A functional cathode sodium compensation agent for stable sodium-ion batteries

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Green Energy & Environment 2025年第1期10卷 173-182页

作者： wei Wu Zhenglin Hu Zhengfei Zhao Aoxuan Wang Jiayan Luo Key Laboratory for Green Chemical Technology of Ministry of Education School of Chemical Engineering and TechnologyTianjin UniversityTianjin300072China State Key Laboratory of Metal Matrix Composites School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai200240China Shanghai Jiao Tong University Shaoxing Research Institute of Renewable Energy and Molecular Engineering Shaoxing312000China

Hard carbon(HC)is widely used in sodium-ion batteries(SIBs),but its performance has always been limited by lowinitial Coulombic efficiency(ICE)and cycling *** compensation agent is a favorable strategy to make up for the loss of active sodium ions consumed *** it lacks agent that effectively decomposes to increase the active sodium ions as well as regulate carbon defects for decreasing the irreversible sodium ions ***,we propose 1,2-dihydroxybenzene Na salt(NaDB)as a cathode compensation agent with high specific capacity(347.9 mAh g^(-1)),lower desodiation potential(2.4–2.8 V)and high utilization(99%).Meanwhile,its byproduct could functionalize HC with more C]O groups and promote its reversible ***,the presodiation hard carbon(pHC)anode exhibits highly reversible capacity of 204.7 mAh g^(-1) with 98%retention at 5 C rate over 1000 ***,with 5 wt%NaDB initially coated on the Na3V2(PO4)3(NVP)cathode,the capacity retention of NVP t NaDBjHC cell could increase from 22%to 89%after 1000 cycles at 1 C *** work provides a new avenue to improve reversible capacity and cycling performance of SIBs through designing functional cathode compensation agent.

关键词： Hard carbon ICE Cathode compensation agent Reversible capacity Stability

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Photoinduced radical sulfur dioxide insertion with asymmetric cyclization of alkenes: accessing β-chiral sulfones bearing S-stereocentric cyclic sulfinamides

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Science China Chemistry 2025年第1期68卷 257-263页

作者： Jiapian Huang Chenxin Wang Xu Wang Xiaoyu Zhou wei Xiao Jie Wu School of Pharmaceutical and Chemical Engineering & Institute for Advanced Studies Taizhou University State Key Laboratory of Organometallic Chemistry Shanghai Institute of Organic Chemistry Chinese Academy of Sciences School of Chemistry and Chemical Engineering Henan Normal University

The generation of various β-chiral sulfones bearing chiral cyclic sulfinamides through photoredox-catalyzed sulfur dioxide insertion with asymmetric radical cyclization is described. This method features a broad substrate scope and excellent stereospecificity. Computational studies reveal that the dispersion interaction between sulfinyl group and CH2SO2Ph group plays a crucial role in the stereoselectivity control.

关键词： β-chiral sulfones chiral cyclic sulfinamides sulfur dioxide insertion asymmetric radical cyclization stereoselectivity

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Brain region-specific roles of brain-derived neurotrophic factor in social stress-induced depressive-like behavior

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Neural Regeneration Research 2025年第1期20卷 159-173页

作者： Man Han Deyang Zeng wei Tan Xingxing Chen Shuyuan Bai Qiong Wu Yushan Chen Zhen wei Yufei Mei Yan Zeng Brain Science and Advanced Technology Institute Wuhan University of Science and TechnologyWuhanHubei ProvinceChina Geriatric Hospital Affiliated to Wuhan University of Science and Technology WuhanHubei ProvinceChina School of Public Health Wuhan University of Science and TechnologyWuhanHubei ProvinceChina

Brain-derived neurotrophic factor is a key factor in stress adaptation and avoidance of a social stress behavioral *** studies have shown that brain-derived neurotrophic factor expression in stressed mice is brain region–specific,particularly involving the corticolimbic system,including the ventral tegmental area,nucleus accumbens,prefrontal cortex,amygdala,and *** how brain-derived neurotrophic factor participates in stress processing in different brain regions will deepen our understanding of social stress *** this review,we discuss the expression and regulation of brain-derived neurotrophic factor in stress-sensitive brain regions closely related to the pathophysiology of *** focused on associated molecular pathways and neural circuits,with special attention to the brain-derived neurotrophic factor–tropomyosin receptor kinase B signaling pathway and the ventral tegmental area–nucleus accumbens dopamine *** determined that stress-induced alterations in brain-derived neurotrophic factor levels are likely related to the nature,severity,and duration of stress,especially in the above-mentioned brain regions of the corticolimbic ***,BDNF might be a biological indicator regulating stress-related processes in various brain regions.

关键词： amygdala chronic mild stress chronic social defeat stress corticolimbic system depression hippocampus medial prefrontal cortex nucleus accumbens social stress models ventral tegmental area

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