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Flexible Graphene Field‑Effect Transistors and Their Application in Flexible Biomedical Sensing

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Nano-Micro Letters 2025年第2期17卷 252-313页

作者： Mingyuan Sun Shuai Wang Yanbo Liang Chao Wang Yunhong Zhang Hong Liu Yu Zhang Lin Han Institute of Marine Science and Technology Shandong UniversityQingdao 266237ShandongPeople’s Republic of China State Key Laboratory of Crystal Materials Shandong UniversityJinan 250100ShandongPeople’s Republic of China School of Integrated Circuits Shandong UniversityJinan 250100ShandongPeople’s Republic of China shandong Engineering Research Center of Biomarker and Artificial Intelligence Application Jinan250100ShandongPeople’s Republic of China

Flexible electronics are transforming our lives by making daily activities more *** to this innovation are field-effect transistors(FETs),valued for their efficient signal processing,nanoscale fabrication,low-power consumption,fast response times,and ***,known for its exceptional mechanical properties,high electron mobility,and biocompatibility,is an ideal material for FET channels and *** combination of graphene and FETs has given rise to flexible graphene field-effect transistors(FGFETs),driving significant advances in flexible electronics and sparked a strong interest in flexible biomedical ***,we first provide a brief overview of the basic structure,operating mechanism,and evaluation parameters of FGFETs,and delve into their material selection and patterning *** ability of FGFETs to sense strains and biomolecular charges opens up diverse application *** specifically analyze the latest strategies for integrating FGFETs into wearable and implantable flexible biomedical sensors,focusing on the key aspects of constructing high-quality flexible biomedical ***,we discuss the current challenges and prospects of FGFETs and their applications in biomedical *** review will provide valuable insights and inspiration for ongoing research to improve the quality of FGFETs and broaden their application prospects in flexible biomedical sensing.

关键词： Flexible Graphene Field-effect transistor Wearable Implantable Biosensor

The optimal control theory——a scientific approach to fundamentally solving control problems

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Science China(Information Sciences) 2025年第1期68卷 389-391页

作者： Huanshui ZHANG School of Electrical and Automation Engineering Shandong University of Science and Technology School of Control Science and Engineering Shandong University

The maximum principle has bridged mathematical optimization to optimal control,ushering in significant developments and refinements in optimal control theory,notably during the 1960s with the advent of linear quadratic (LQ)control and linear quadratic estimation (LQE).This progression propelled optimal control theory into further advancements,encompassing stochastic control,robust/H-infinity control,model predictive control (MPC),networked control,and reinforcement learning *** control,established upon a rigorous mathematical foundation,extends static optimization theory to dynamic systems,exhibiting scientific essence,unity,and ***,since its inception,optimal control theory has served as an indispensable core role across all control-related domains,including communication-constrained control in networked systems,consensus control,cooperative control,and reinforcement learning control.

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Optimizing battery deployment: Aging trajectory prediction enabling homogenous performance grouping

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Journal of Energy Chemistry 2025年第1期100卷 565-577页

作者： Shuquan Wang Feng Gao Zhan Ma Hao Tian Yusen Zhang School of Control Science and Engineering Shandong University Key Lab of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University

As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imaging and machine learning to predict battery aging trajectories from minimal initial data, thus facilitating effective performance grouping before deployment. Utilizing a derivative strategy and Gramian Angular Difference Field for dimensional enhancement, the MDIF model uncovers subtle predictive features from discharge curve data after only ten cycles. The architecture includes a parallel convolutional neural network with lateral connections to enhance feature integration and *** on a self-developed dataset, the model achieves an average root-mean-square error of 0.047 Ah and an average mean absolute percentage error of 1.60%, demonstrating high precision and *** robustness is further validated through transfer learning on two publicly available datasets, adapting with minimal retraining. This approach significantly reduces the testing cycles required, lowering both time and costs associated with battery testing. By enabling precise battery behavior predictions with limited data, the MDIF model optimizes battery utilization and deployment strategies, enhancing system efficiency and sustainability.

关键词： Lithium-ion battery Battery prognostics Fusion model Convolutional neural network Transfer learning

Inhibition of the cGAS–STING pathway:contributing to the treatment of cerebral ischemia-reperfusion injury

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Neural Regeneration Research 2025年第7期20卷 1900-1918页

作者： Hang Yang Yulei Xia Yue Ma Mingtong Gao Shuai Hou Shanshan Xu Yanqiang Wang School of Clinical Medicine Shandong Second Medical UniversityWeifangShandong ProvinceChina Department of Emergency The Affiliated Hospital of Weifang Medical UniversityWeifangShandong ProvinceChina Department of Neurology Ⅱ The Affiliated Hospital of Weifang Medical UniversityWeifangShandong ProvinceChina

The cGAS–STING pathway plays an important role in ischemia-reperfusion injury in the heart,liver,brain,and kidney,but its role and mechanisms in cerebral ischemia-reperfusion injury have not been systematically ***,we outline the components of the cGAS–STING pathway and then analyze its role in autophagy,ferroptosis,cellular pyroptosis,disequilibrium of calcium homeostasis,inflammatory responses,disruption of the blood–brain barrier,microglia transformation,and complement system activation following cerebral ischemia-reperfusion *** further analyze the value of cGAS–STING pathway inhibitors in the treatment of cerebral ischemia-reperfusion injury and conclude that the pathway can regulate cerebral ischemia-reperfusion injury through multiple *** of the cGAS–STING pathway may be helpful in the treatment of cerebral ischemia-reperfusion injury.

关键词： calcium homeostasis cellular autophagy cerebral ischemia-reperfusion injury cGAS–STING pathway ferroptosis gut–brain–microbiota axis inflammatory light chain 3 microglial cells Syntaxin-17 protein

Integrated Equipment with Functions of Current Flow Control and Fault Isolation for Multiterminal DC Grids

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Energy Engineering 2025年第1期122卷 85-99页

作者： Shuo Zhang Guibin Zou School of Electrical Engineering Shandong UniversityJinan250061China Suzhou Research Institute Shandong UniversitySuzhou215123China

The multi-terminal direct current(DC)grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable *** the DC circuit breaker(DCCB)and the current flow controller(CFC)are demanded to ensure the multiterminal DC grid to operates reliably and ***,since the CFC and the DCCB are all based on fully controlled semiconductor switches(e.g.,insulated gate bipolar transistor,integrated gate commutated thyristor,etc.),their separation configuration in the multiterminal DC grid will lead to unaffordable implementation costs and conduction power *** solve these problems,integrated equipment with both current flow control and fault isolation abilities is proposed,which shares the expensive and duplicated components of CFCs and DCCBs among adjacent *** addition,the complicated coordination control of CFCs and DCCBs can be avoided by adopting the integrated equipment in themultiterminal DC *** order to examine the current flow control and fault isolation abilities of the integrated equipment,the simulation model of a specific meshed four-terminal DC grid is constructed in the PSCAD/EMTDC ***,the comparison between the integrated equipment and the separate solution is presented a specific result or conclusion needs to be added to the abstract.

关键词： Integrated equipment multiterminal direct current grid current flow control fault isolation

The pivotal role of microglia in injury and the prognosis of subarachnoid hemorrhage

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Neural Regeneration Research 2025年第7期20卷 1829-1848页

作者： Wenjing Ning Shi Lv Qian Wang Yuzhen Xu Department of Rehabilitation The Second Affiliated Hospital of Shandong First Medical UniversityTaianShandong ProvinceChina Department of Central Laboratory The Affiliated Taian City Central Hospital of Qingdao UniversityTaianShandong ProvinceChina

Subarachnoid hemorrhage leads to a series of pathological changes,including vascular spasm,cellular apoptosis,blood–brain barrier damage,cerebral edema,and white matter ***,which are the key immune cells in the central nervous system,maintain homeostasis in the neural environment,support neurons,mediate apoptosis,participate in immune regulation,and have neuroprotective *** evidence has shown that microglia play a pivotal role in the pathogenesis of subarachnoid hemorrhage and affect the process of injury and the prognosis of subarachnoid ***,microglia play certain neuroprotective roles in the recovery phase of subarachnoid *** approaches aimed at modulating microglia function are believed to attenuate subarachnoid hemorrhage *** provides new targets and ideas for the treatment of subarachnoid ***,an in-depth and comprehensive summary of the role of microglia after subarachnoid hemorrhage is still *** review describes the activation of microglia after subarachnoid hemorrhage and their roles in the pathological processes of vasospasm,neuroinflammation,neuronal apoptosis,blood–brain barrier disruption,cerebral edema,and cerebral white matter *** also discusses the neuroprotective roles of microglia during recovery from subarachnoid hemorrhage and therapeutic advances aimed at modulating microglial function after subarachnoid ***,microglia in subarachnoid hemorrhage are targeted with TLR inhibitors,nuclear factor-κB and STAT3 pathway inhibitors,glycine/tyrosine kinases,NLRP3 signaling pathway inhibitors,Gasdermin D inhibitors,vincristine receptorαreceptor agonists,ferroptosis inhibitors,genetic modification techniques,stem cell therapies,and traditional Chinese ***,most of these are still being evaluated at the laboratory *** clinical studies and data on subarachnoid hemorrhage are required to improve the treatment of subarachnoid hemor

关键词： apoptosis blood–brain barrier brain edema microglia neuroinflammation neuron neuroprotection subarachnoid hemorrhage vasoconstriction white matter injury

Hydrogen sulfide reduces oxidative stress in Huntington's disease via Nrf2

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Neural Regeneration Research 2025年第6期20卷 1776-1788页

作者： Zige Jiang Dexiang Liu Tingting Li Chengcheng Gai Danqing Xin Yijing Zhao Yan Song Yahong Cheng Tong Li Zhen Wang Department of Physiology School of Basic Medical SciencesCheeloo College of MedicineShandong UniversityJinanShandong ProvinceChina Department of Medical Psychology and Ethics School of Basic Medicine SciencesCheeloo College of MedicineShandong UniversityJinanShandong ProvinceChina Department of Neurosurgery Surgery Qingdao Municipal HospitalQingdaoShandong ProvinceChina

The pathophysiology of Huntington's disease involves high levels of the neurotoxin quinolinic acid. Quinolinic acid accumulation results in oxidative stress, which leads to neurotoxicity. However, the molecular and cellular mechanisms by which quinolinic acid contributes to Huntington's disease pathology remain unknown. In this study, we established in vitro and in vivo models of Huntington's disease by administering quinolinic acid to the PC12 neuronal cell line and the striatum of mice, respectively. We observed a decrease in the levels of hydrogen sulfide in both PC12 cells and mouse serum, which was accompanied by down-regulation of cystathionine β-synthase, an enzyme responsible for hydrogen sulfide production. However, treatment with NaHS(a hydrogen sulfide donor) increased hydrogen sulfide levels in the neurons and in mouse serum, as well as cystathionine β-synthase expression in the neurons and the mouse striatum, while also improving oxidative imbalance and mitochondrial dysfunction in PC12 cells and the mouse striatum. These beneficial effects correlated with upregulation of nuclear factor erythroid 2-related factor 2 expression. Finally, treatment with the nuclear factor erythroid 2-related factor 2inhibitor ML385 reversed the beneficial impact of exogenous hydrogen sulfide on quinolinic acid-induced oxidative stress. Taken together, our findings show that hydrogen sulfide reduces oxidative stress in Huntington's disease by activating nuclear factor erythroid 2-related factor 2,suggesting that hydrogen sulfide is a novel neuroprotective drug candidate for treating patients with Huntington's disease.

关键词： apoptosis cystathionine-β-synthase nuclear factor erythroid 2-related factor 2 Huntington's disease hydrogen sulfide mitochondrion neuroplasticity oxidative stress quinolinic acid reactive oxygen species

Personalized federated few-shot node classification

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Science China(Information Sciences) 2025年第1期68卷 204-218页

作者： Yunfeng ZHAO Xintong HE Guoxian YU Jun WANG Yongqing ZHENG Carlotta DOMENICONI School of Software Shandong University Joint SDU-NTU Centre for Artificial Intelligence Research Shandong University Department of Mathematics National University of Singapore Department of Computer Science George Mason University

Personalized federated learning(PFL) aims to train customized models for individual clients in a decentralized setting, with the account of non-independent and identically distributed data across clients. However, most PFL methods adopt uniform classification layers for diverse clients and give rise to error-prone predictions, due to the task heterogeneity notably prominent in decentralized graph data scenarios. Although some PFL solutions setup client-specific classification layers for each client and optimize them only locally, they are corrupted with limited local training data. We propose an innovative solution called federated parameter decoupling and node augmentation(Fed PANo) to address these problems and to achieve personalized federated few-shot node classification, which is a prevalent and challenging but unexplored topic. Specifically, Fed PANo first separates the local model into the GNN and classifier to handle unique client-specific task variations. The GNN is trained through federated learning to capture shared knowledge of graph nodes across clients, while the classifier is custom-designed and trained individually for each client. Additionally, a generic classifier shared among clients is adopted to encourage the GNN's grasp of shared information. Then Fed PANo further proposes the node generator along with its local and collaborative training strategies to deal with the node scarcity of clients. Extensive experimental results on benchmark datasets confirm that Fed PANo outperforms eight competitive baselines across different settings.

关键词： personalized federated learning few-shot learning node classification task heterogeneity parameter decoupling node augmentation

Engine Misfire Fault Detection Based on the Channel Attention Convolutional Model

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Computers, Materials & Continua 2025年第1期82卷 843-862页

作者： Feifei Yu Yongxian Huang Guoyan Chen Xiaoqing Yang Canyi Du Yongkang Gong School of Mechatronic Engineering Guangdong Polytechnic Normal UniversityGuangzhou510665China School of Automotive and Transportation Engineering Guangdong Polytechnic Normal UniversityGuangzhou510665China

To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precisely pinpointing misfire *** the experiment,we established a total of 11 distinct states,encompassing the engine’s normal state,single-cylinder misfire faults,and dual-cylinder misfire faults for different *** collection was facilitated by a highly sensitive acceleration signal collector with a high sampling rate of 20,*** collected data were methodically divided into training and testing sets based on different experimental groups to ensure generalization and prevent overlap between the two *** results revealed that,with a vibration acceleration sequence of 1000 time steps(approximately 50 ms)as input,the SENET model achieved a misfire fault detection accuracy of 99.8%.For comparison,we also trained and tested several commonly used models,including Long Short-Term Memory(LSTM),Transformer,and Multi-Scale Residual Networks(MSRESNET),yielding accuracy rates of 84%,79%,and 95%,*** underscores the superior accuracy of the SENET model in detecting engine misfire faults compared to other ***,the F1 scores for each type of recognition in the SENET model surpassed 0.98,outperforming the baseline *** analysis indicated that the misclassified samples in the LSTM and Transformer models’predictions were primarily due to intra-class misidentifications between single-cylinder and dual-cylinder misfire *** delve deeper,we conducted a visual analysis of the features extracted by the LSTM and SENET models using T-distributed Stochastic Neighbor Embedding(T-SNE)*** findings revealed that,in the LSTMmodel,data points of the same type tended to cluster together with significant ***,in the SENET model,data points of various types were more widely and evenly dispersed,demonstra

关键词： Channel attention SENET model engine misfire fault fault detection