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Exercise preconditioning alleviates ischemia-induced memory deficits by increasing circulating adiponectin

Neural Regeneration Research 2025年第5期20卷 1445-1454页

作者： Meifeng Zheng Borui zhang Sonata S Y Yau Kwok-Fai So Li zhang Haining Ou Department of Rehabilitation Medicine Guangzhou Medical UniversityGuangzhouGuangdong ProvinceChina Department of Rehabilitation Medicine The Fifth Clinical College of Guangzhou Medical UniversityGuangzhouGuangdong ProvinceChina Key Laboratory of CNS Regeneration(Ministry of Education) Guangdong-Hong Kong-Macao Institute of CNS RegenerationJinan UniversityGuangzhouGuangdong ProvinceChina Department of Rehabilitation Sciences The Hong Kong Polytechnic UniversityHong Kong Special Administrative RegionChina State Key Laboratory of Brain and Cognitive Science Li Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina Center for Exercise and Brain Science School of PsychologyShanghai University of SportShanghaiChina Neuroscience and Neurorehabilitation Institute University of Health and Rehabilitation SciencesQingdaoShandong ProvinceChina

Cerebral ischemia is a major health risk that requires preventive approaches in addition to drug *** exercise enhances neurogenesis and synaptogenesis,and has been widely used for functional rehabilitation after *** this study,we determined whether exercise training before disease onset can alleviate the severity of cerebral *** also examined the role of exercise-induced circulating factors in these *** mice were subjected to 14 days of treadmill exercise training before surgery for middle cerebral artery *** found that this exercise pre-conditioning strategy effectively attenuated brain infarct area,inhibited gliogenesis,protected synaptic proteins,and improved novel object and spatial memory *** analysis showed that circulating adiponectin plays a critical role in these preventive effects of *** activation of adiponectin receptors by Adipo Ron mimicked the effects of exercise,while inhibiting receptor activation abolished the exercise *** summary,our results suggest a crucial role of circulating adiponectin in the effects of exercise pre-conditioning in protecting against cerebral ischemia and supporting the health benefits of exercise.

关键词： adiponectin cerebral ischemia exercise pre-conditioning hippocampus memory function middle cerebral artery occlusion prefrontal cortex synaptic proteins treadmill exercise

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Text-Image Feature Fine-Grained Learning for Joint Multimodal Aspect-Based Sentiment Analysis

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Computers, Materials & Continua 2025年第1期82卷 279-305页

作者： Tianzhi zhang Gang Zhou Shuang zhang Shunhang Li Yepeng Sun Qiankun Pi Shuo Liu School of Data and Target Engineering Information Engineering UniversityZhengzhou450001China Information Engineering Department Liaoning Provincial College of CommunicationsShenyang110122China School of Computer and Artificial Intelligence Zhengzhou UniversityZhengzhou450000China

Joint Multimodal Aspect-based Sentiment Analysis(JMASA)is a significant task in the research of multimodal fine-grained sentiment analysis,which combines two subtasks:Multimodal Aspect Term Extraction(MATE)and Multimodal Aspect-oriented Sentiment Classification(MASC).Currently,most existing models for JMASA only perform text and image feature encoding from a basic level,but often neglect the in-depth analysis of unimodal intrinsic features,which may lead to the low accuracy of aspect term extraction and the poor ability of sentiment prediction due to the insufficient learning of intra-modal *** this problem,we propose a Text-Image Feature Fine-grained Learning(TIFFL)model for ***,we construct an enhanced adjacency matrix of word dependencies and adopt graph convolutional network to learn the syntactic structure features for text,which addresses the context interference problem of identifying different aspect ***,the adjective-noun pairs extracted from image are introduced to enable the semantic representation of visual features more intuitive,which addresses the ambiguous semantic extraction problem during image feature ***,the model performance of aspect term extraction and sentiment polarity prediction can be further optimized and *** on two Twitter benchmark datasets demonstrate that TIFFL achieves competitive results for JMASA,MATE and MASC,thus validating the effectiveness of our proposed methods.

关键词： Multimodal sentiment analysis aspect-based sentiment analysis feature fine-grained learning graph convolutional network adjective-noun pairs

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Modeling and Capacity Configuration Optimization of CRH5 EMU On-Board Energy Storage System

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Energy Engineering 2025年第1期122卷 307-329页

作者： Mingxing Tian Weiyuan zhang Zhaoxu Su School of Automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou730070China

In the context of the“dual carbon”goals,to address issues such as high energy consumption,high costs,and low power quality in the rapid development of electrified railways,this study focused on the China Railways High-Speed 5 Electric Multiple Unit and proposed a mathematical model and capacity optimization method for an onboard energy storage system using lithium batteries and supercapacitors as storage ***,considering the electrical characteristics,weight,and volume of the storage media,a mathematical model of the energy storage system was ***,to tackle problems related to energy consumption and power quality,an energy management strategy was proposed that comprehensively considers peak shaving and valley filling and power quality by controlling the charge/discharge thresholds of the storage *** optimization adopted a bilevel programming model,with the series/parallel number of storage modules as variables,considering constraints imposed by the Direct Current to Direct Current converter,train load,and *** improved Particle Swarm Optimization algorithm and linear programming solver were used to solve specific *** results show that the proposed onboard energy storage system can effectively achieve energy savings,reduce consumption,and improve power qualitywhile meeting the load and space limitations of the train.

关键词： Electrified railway regenerative braking bi-level programming on-board energy storage power quality capacity configuration

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Universal design of three-dimensional porous graphene-iron based promotors for kinetically rationalized lithium-sulfur chemistry

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Journal of Energy Chemistry 2025年第1期100卷 192-200页

作者： Hua Gao Yunfeng zhang Menglei Wang Ruoxuan Yang Shuai Feng Xuan Cao Yaping zhang Zhongyuan Lu Yingze Song State Key Laboratory of Environment-Friendly Energy Materials School of Materials and Chemistry Southwest University of Science and Technology School of Material Science and Engineering Henan University of Technology College of Chemistry and Chemical Engineering Taishan University

Lithium-sulfur （Li-S） batteries are widely deemed to be one of the most potential candidates for future secondary batteries because of their remarkable energy ***,notorious polysulfide shuttling and retarded sulfur reaction kinetics pose significant obstacles to the further application of Li-S *** rationally designed highly active electrocatalysts can facilitate polysulfide conversion,the universal and scalable synthesis strategies need to be ***,a universal synthetic strategy to construct a series of three-dimensional （3D） porous graphene-iron （3DGr-Fe） based electrocatalysts involving 3DGr-FeP,3DGr-Fe3C,and 3DGr-Fe3Se4is exploited for manipulating the Li-S redox *** has been observed that the implementation of a 3D porous Gr architecture leads to the well-designed conductive networks,while the uniformly dispersed iron nanoparticles introduce an abundance of active sites,fostering the lithium polysulfide conversion,thereby bolstering the overall electrochemical *** Li-S battery with the 3DGr-Fe based electrocatalyst exhibits remarkable capacity retention of 94.8%upon 100 times at 0.2 ***,the soft-packaged Li-S pouch cell based on such a 3DGr-Fe electrocatalyst delivers superior capacity of 1060.71 mA h g-1and guarantees for the continuous 30 min work of fan *** investigation gives comprehensive insights into the design,synthesis,and mechanism of 3DGr-Fe based electrocatalysts with high activity toward efficient and durable Li-S batteries.

关键词： Redox reactions

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Effect of Ti Additions on Mechanical and Thermodynamic Properties of W-Ti Alloys: A First-principles Study

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 246-257页

作者： zhang Jian NIE Wei HUANG Jin ZHU Ke LIU Ruxia zhang Ruizhi LUO Guoqiang SHEN Qiang State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China Institute for Carbon Neutrality University of Science and Technology BeijingBeijing 100083China

The mechanical and thermodynamic properties of W-Ti alloys(including W_(15)Ti_(1),W_(14)Ti_(2),W_(12)Ti_(4) and W_(8)Ti_(8) alloys)were investigated by the first-principles approach based on density functional *** results indicate that W-Ti alloys except W_(8)Ti_(8) are thermodynamically *** modulus and hardness of W-Ti alloys are smaller than those of pure tungsten and gradually decrease with increasing Ti ***,their B/G ratios and Poisson's ratios exceed those of pure tungsten,suggesting that the introduction of Ti decreases the mechanical strength while enhancing the ductility of W-Ti *** thermal expansion coefficients for W-Ti alloys all surpass those of pure tungsten,indicating that the introduction of titanium exacerbates the thermal expansion behavior of W-Ti ***,elevated pressure has the capacity to suppress the thermal expansion tendencies in titanium-doped tungsten *** study offers theoretical insights for the design of nuclear materials by exploring the mechanical and thermodynamic properties of W-Ti alloys.

关键词： first-principles mechanical properties thermodynamic properties tungsten-titanium alloys

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HNRNPC as a pan-cancer biomarker and therapeutic target involved in tumor progression and immune regulation

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Oncology research 2025年第1期33卷 83-102页

作者： Yuezhou zhang Zhao zhang Jinxin Dong Changan Liu Department of Hepatobiliary Surgery The Second Affiliated Hospital of Chongqing Medical University Chongqing 400016 China. Department of Hepatobiliary Surgery The First Affiliated Hospital of Chongqing Medical University Chongqing 400016 China.

Background:Aberrant expression of RNA-binding proteins (RBPs) has been linked to a variety of diseases, including hematological disorders, cardiovascular diseases, and multiple types of cancer. Heterogeneous nuclear ribonucleoprotein C (HNRNPC), a member belonging to the heterogeneous nuclear ribonucleoprotein (hnRNP) family, plays a pivotal role in nucleic acid metabolism. Previous studies have underscored the significance of HNRNPC in tumorigenesis; however, its specific role in malignant tumor progression remains inadequately characterized.Methods:We leveraged publicly available databases, including The Cancer Genome Atlas (TCGA), to explore the potential involvement of HNRNPC across various cancers. Additionally, we performed experimental validation studies focused on liver cancer.Results:Our analysis revealed that HNRNPC is overexpressed in a wide range of common malignancies, including liver and lung cancers, and is strongly linked to unfavorable outcomes. Furthermore, HNRNPC was observed to be closely linked to tumor immunity. Through immune checkpoint analysis and immune cell infiltration assessment, HNRNPC emerged as a potential target for modulating tumor immunotherapy. Notably, silencing of HNRNPC markedly inhibited the proliferation, metastasis, and infiltration of liver cancer cells.Conclusion:In summary, our findings highlight HNRNPC as a prognostic marker in various cancers, including liver cancer, and suggest its involvement in shaping the tumor immune microenvironment. These insights offer potential avenues for improving clinical outcomes in tumors with elevated HNRNPC expression, particularly through immunotherapeutic strategies.

关键词： Hepatocellular carcinoma Heterogeneous nuclear ribonucleoprotein C (HNRNPC) Immunotherapeutic target Pan-cancer analysis Prognostic biomarker Tumor immunity

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Decision making module based on stochastic magnetic tunnel junctions

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 202-209页

作者： Yifan Miao Li Zhao Yajun zhang Zhe Yuan Center for Advanced Quantum Studies and Department of Physics Beijing Normal University Institute for Nanoelectric Devices and Quantum Computing Fudan University Interdisciplinary Center for Theoretical Physics and Information Sciences Fudan University

In biological neural systems, noise is ubiquitous but does not affect the correct decisions made in the complex cognitive ***-making in biological neural system is typically achieved by accumulating input information over a period of *** by recent developments in neurosciences, we design a decision-making module based on spintronic devices, utilizing superparamagnetic tunnel junctions as artificial neurons. The feasibility of this decision-making module is verified through circuit simulations. Taking a multi-layer perceptron as an example, the module significantly improves the accuracy of the perceptron in the handwritten digit recognition task. Furthermore, the spintronic decision-making module offers advantages over the conventional pooling methods, such as adaptive decision time, high performance and the absence of analog-to-digital conversion. The decision-making module is flexible to be integrated into artificial neural networks and provides a general yet effective solution to enhance performance against device noise.

关键词： neuromorphic computing spintronics magnetic tunnel junction neural networks

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A quantum-search-based multi-classifier for image recognition

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 21-31页

作者： Lu Liu Xingyu Wu Lufan zhang Chuan Wang School of Artificial Intelligence Beijing Normal University Applied Optics Beijing Area Major Laboratory Beijing Normal University

The multi-class classification of images is a pivotal challenge within the realm of image processing. As the volume of visual data continues to expand, there is a burgeoning interest in harnessing the unique capabilities of quantum computation to augment the efficiency of classification tasks. However, many existing methods for training quantum image multi-classifiers parallel classical machine learning techniques, where the requisite circuit measurements increase linearly with the volume of training data. This work introduces a novel approach for training a quantum image multi-classifier based on the quantum search algorithm. We have meticulously conducted rigorous experiments on a handwritten digit dataset, a classic benchmark in the field. The results have been meticulously compared with previous works, and the comparative analysis not only validates the efficiency of our proposed approach, requiring only O(N/b) measurements during training, but also highlights a significant quadratic speedup of the algorithm.

关键词： quantum computation image recognition quantum search algorithm

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Catalyst–Support Interaction in Polyaniline‑Supported Ni_(3)Fe Oxide to Boost Oxygen Evolution Activities for Rechargeable Zn‑Air Batteries

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Nano-Micro Letters 2025年第1期17卷 176-190页

作者： Xiaohong Zou Qian Lu Mingcong Tang Jie Wu Kouer zhang Wenzhi Li Yunxia Hu Xiaomin Xu Xiao zhang Zongping Shao Liang An Department of Mechanical Engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong SARPeople’s Republic of China Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and TechnologyNanjing University of Information Science and TechnologyNanjing 210044People’s Republic of China Department of Chemistry The Chinese University of Hong KongMa Lin BuildingShatinHong Kong SAR 999077People’s Republic of China WA School of Mines:Minerals Energy and Chemical Engineering(WASM‑MECE)Curtin UniversityPerthWA 6102Australia Research Institute for Advanced Manufacturing The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong SARPeople’s Republic of China Research Institute for Smart Energy The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong SARPeople’s Republic of China

Catalyst–support interaction plays a crucial role in improving the catalytic activity of oxygen evolution reaction(OER).Here we modulate the catalyst–support interaction in polyaniline-supported Ni_(3)Fe oxide(Ni_(3)Fe oxide/PANI)with a robust hetero-interface,which significantly improves oxygen evolution activities with an overpotential of 270 mV at 10 mA cm^(-2)and specific activity of 2.08 mA cm_(ECSA)^(-2)at overpotential of 300 mV,3.84-fold that of Ni_(3)Fe *** is revealed that the catalyst–support interaction between Ni_(3)Fe oxide and PANI support enhances the Ni–O covalency via the interfacial Ni–N bond,thus promoting the charge and mass transfer on Ni_(3)Fe *** the excellent activity and stability,rechargeable Zn-air batteries with optimum Ni_(3)Fe oxide/PANI are assembled,delivering a low charge voltage of 1.95 V to cycle for 400 h at 10 mA cm^(-2).The regulation of the effect of catalyst–support interaction on catalytic activity provides new possibilities for the future design of highly efficient OER catalysts.

关键词： Catalyst-support interaction Supported catalysts Heterointerface Oxygen evolution reaction Zn-air batteries

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An Improved Practical Byzantine Fault-Tolerant Algorithm Based on XGBoost Grouping for Consortium Chains

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Computers, Materials & Continua 2025年第1期82卷 1295-1311页

作者： Xiaowei Wang Haiyang zhang Jiasheng zhang Yingkai Ge Kexin Cui Zifu Peng Zhengyi Li Lihua Wang College of Electronic and Information Engineering Shandong University of Science and TechnologyQingdao266590China

In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for consortium chains,we propose an improved PBFT algorithm based on XGBoost grouping called XG-PBFT in this ***-PBFT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for *** XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping *** them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus *** order to reduce the resource waste of the system,XG-PBFT optimizes the consensus protocol for the problem of high complexity of PBFT ***,we evaluate the performance of *** experimental results show that XG-PBFT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBFT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of *** results demonstrate that the XG-PBFT algorithm is more suitable for large-scale consortium chains.

关键词： Consortium chain PBFT grouping reputation XGBoost

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