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Science China(Information Sciences) 2025年第1期68卷 306-321页

作者： Cuijuan zhang Lianghao JI Shasha YANG Xing GUO Huaqing LI Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University College of Electronic and Information Engineering Southwest University

This study uses event-triggered(ET) and reinforcement learning methods to investigate the optimal consensus control problem for cooperative-competitive multiagent systems. It proposes a novel distributed ET control strategy, which relies on a prioritized experience replay(PER) policy. This strategy not only conserves communication resources but also ensures acceptable system performance. To implement the proposed method, actor-critic(AC) dual-structured neural networks(NNs) are used to approximate the value function and control policy. In the AC NNs, the weight estimates for the NNs are updated at the moment of event triggering, resulting in a nonperiodic weight adjustment pattern. This approach decreases the computational cost in comparison with the traditional ET mechanism. The PER-based ET mechanism makes full use of valid historical data and effectively establishes a balance between system performance and communication resource ***, it does not require the following two conditions in most existing studies:(1) requirement of the system dynamics model to be known, and(2) persistent excitation. In addition, Zeno behavior is excluded from this study. Finally, a simulation is conducted to confirm the validity of the suggested approach.

关键词： multiagent systems event-triggered mechanism prioritized experience replay dual-structured neural networks optimal consensus control

Wafer‑Scale Ag_(2)S‑Based Memristive Crossbar Arrays with Ultra‑Low Switching‑Energies Reaching Biological Synapses

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Nano-Micro Letters 2025年第3期17卷 328-339页

作者： Yuan Zhu Tomas Nyberg Leif Nyholm Daniel Primetzhofer Xun Shi Zhen zhang Division of Solid‑State Electronics Department of Electrical EngineeringUppsala University75121 UppsalaSweden Department of Chemistry Uppsala UniversityUppsalaSweden Department of Physics and Astronomy Uppsala UniversityUppsalaSweden State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 200050People’s Republic of China

Memristive crossbar arrays(MCAs)offer parallel data storage and processing for energy-efficient neuromorphic ***,most wafer-scale MCAs that are compatible with complementary metal-oxide-semiconductor(CMOS)technology still suffer from substantially larger energy consumption than biological synapses,due to the slow kinetics of forming conductive paths inside the memristive *** we report wafer-scale Ag_(2)S-based MCAs realized using CMOS-compatible processes at temperatures below 160℃.Ag_(2)S electrolytes supply highly mobile Ag+ions,and provide the Ag/Ag_(2)S interface with low silver nucleation barrier to form silver filaments at low energy *** further enhancing Ag+migration in Ag_(2)S electrolytes via microstructure modulation,the integrated memristors exhibit a record low threshold of approximately−0.1 V,and demonstrate ultra-low switching-energies reaching femtojoule values as observed in biological *** low-temperature process also enables MCA integration on polyimide substrates for applications in flexible ***,the intrinsic nonidealities of the memristive units for deep learning can be compensated by employing an advanced training *** impressive accuracy of 92.6%in image recognition simulations is demonstrated with the MCAs after the *** demonstrated MCAs provide a promising device option for neuromorphic computing with ultra-high energy-efficiency.

关键词： Wafer-scale Ag_(2)S films Reactive sputter Silver nucleation Ag^(+)migration Energy-efficient neuromorphic computing

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Structural Modal Parameter Recognition and Related Damage Identification Methods under Environmental Excitations: A Review

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Structural Durability & Health Monitoring 2025年第1期19卷 25-54页

作者： Chao zhang Shang-Xi Lai Hua-Ping Wang School of Civil Engineering and Mechanics Lanzhou UniversityLanzhou730000China Key Laboratory of Special Functional Materials and Structural Design Ministry of EducationLanzhou UniversityLanzhou730000China

Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the ***,it is particularly signiﬁcant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientiﬁc basis for structural damage identiﬁcation and dynamic model modiﬁ*** view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and brieﬂy describes how to identify structural damages based on the derived modal *** paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),brieﬂy describes damage identiﬁcation methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artiﬁcial intelligence(AI)methods in the direction of modal parameter recognition and damage identiﬁcation is further *** on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identiﬁcation methods are given to provide scientiﬁc references for the optimized design and functional upgrading of SHM systems.

关键词： Structural health monitoring data information modal parameters damage identiﬁcation AI method

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

DecMamba:Mamba Utilizing Series Decomposition for Multivariate Time Series Forecasting

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Computers, Materials & Continua 2025年第1期82卷 1049-1068页

作者： Jianxin Feng Jianhao zhang Ge Cao Zhiguo Liu Yuanming Ding Communication and Network Key Laboratory Dalian UniversityDalian116622China

Multivariate time series forecasting iswidely used in traffic planning,weather forecasting,and energy *** decomposition algorithms can help models better understand the underlying patterns of the original series to improve the forecasting accuracy of multivariate time ***,the decomposition kernel of previous decomposition-based models is fixed,and these models have not considered the differences in frequency fluctuations between *** problems make it difficult to analyze the intricate temporal variations of real-world time *** this paper,we propose a series decomposition-based Mamba model,DecMamba,to obtain the intricate temporal dependencies and the dependencies among different variables of multivariate time series.A variable-level adaptive kernel combination search module is designed to interact with information on different trends and periods between *** backbone structures are proposed to emphasize the differences in frequency fluctuations of seasonal and trend *** with superior performance is used instead of a Transformer in backbone structures to capture the dependencies among different variables.A new embedding block is designed to capture the temporal features better,especially for the high-frequency seasonal component whose semantic information is difficult to acquire.A gating mechanism is introduced to the decoder in the seasonal backbone to improve the prediction accuracy.A comparison with ten state-of-the-art models on seven real-world datasets demonstrates that DecMamba can better model the temporal dependencies and the dependencies among different variables,guaranteeing better prediction performance for multivariate time series.

关键词： Data prediction time series Mamba series decomposition

Unraveling brain aging through the lens of oral microbiota

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Neural Regeneration Research 2025年第7期20卷 1930-1943页

作者： Qinchao Hu Si Wang Weiqi zhang Jing Qu Guang-Hui Liu State Key Laboratory of Membrane Biology Institute of ZoologyChinese Academy of SciencesBeijingChina Hospital of Stomatology Guanghua School of StomatologyGuangdong Provincial Key Laboratory of StomatologySun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders Xuanwu HospitalCapital Medical UniversityBeijingChina Aging Translational Medicine Center International Center for Aging and CancerBeijing Municipal Geriatric Medical Research CenterXuanwu HospitalCapital Medical UniversityBeijingChina CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of GenomicsChinese Academy of Sciences and China National Center for BioinformationBeijingChina University of Chinese Academy of Sciences BeijingChina Institute for Stem Cell and Regeneration Chinese Academy of SciencesBeijingChina Aging Biomarker Consortium BeijingChina State Key Laboratory of Stem Cell and Reproductive Biology Institute of ZoologyChinese Academy of SciencesBeijingChina Beijing Institute for Stem Cell and Regenerative Medicine BeijingChina

The oral cavity is a complex physiological community encompassing a wide range of *** of oral microbiota can lead to various oral infectious diseases,such as periodontitis and tooth decay,and even affect systemic health,including brain aging and neurodegenerative *** studies have highlighted how oral microbes might be involved in brain aging and neurodegeneration,indicating potential avenues for intervention *** this review,we summarize clinical evidence demonstrating a link between oral microbes/oral infectious diseases and brain aging/neurodegenerative diseases,and dissect potential mechanisms by which oral microbes contribute to brain aging and *** also highlight advances in therapeutic development grounded in the realm of oral microbes,with the goal of advancing brain health and promoting healthy aging.

关键词： Alzheimer's disease brain aging multiple sclerosis neurodegeneration neurodegenerative diseases oral microbiota Parkinson's disease periodontitis bacteria Porphyromonas gingivalis

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Early identification of stroke through deep learning with multi-modal human speech and movement data

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Neural Regeneration Research 2025年第1期20卷 234-241页

作者： Zijun Ou Haitao Wang Bin zhang Haobang Liang Bei Hu Longlong Ren Yanjuan Liu Yuhu zhang Chengbo Dai Hejun Wu Weifeng Li Xin Li School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Department of Neurology Guangdong Neuroscience InstituteGuangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina Department of Emergency Medicine Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina

Early identification and treatment of stroke can greatly improve patient outcomes and quality of *** clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized *** this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute *** collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the *** compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and *** found that the findings of our deep learning model had a higher clinical value compared with the other ***,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech *** results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

关键词： artificial intelligence deep learning diagnosis early detection FAST screening stroke

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An internally linked dibenzihexaphyrin

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Science China Chemistry 2025年

作者： Zhaohui Zong Xiaotong zhang Zhe Liu Guangliu Ran Wenkai zhang Xiansheng Ke College of Chemistry Beijing Normal University School of Physics and Astronomy Applied Optics Beijing Area Major Laboratory Center for Advanced Quantum Studies Beijing Normal University Key Laboratory of Multiscale Spin Physics Ministry of Education Beijing Normal University

Hexaphyrins are one of the most studied expanded porphyrins that show intriguing electronic structure and coordination abilities in the past decades. However, core-modified hexaphyrins especially for benzene-replaced hexaphyrins are much less ***, we revisit the dibenzihexaphyrin system and demonstrate how to achieve the hexaphyrin-like organometallic nature of a benzene-replaced expanded porphyrin. For the “true” di-m-benzihexaphyrin 2, metal complex with anticipated CCNN coordination is not realized probably due to the steric hindrance. Further, we synthesized an internally linked dibenzihexaphyrin (3)with a direct carbon–carbon bond between two phenylenes. As prepared, 3 has a strained biphenyl unit and can effectively coordinate two Cu(III) ions with CCNN coordination. This sharp contrast underscores the critical importance of the formed preorganized corrole-like adj-CCNN cavities after linking two flanking phenylenes. 3 can also act as a bidentate ligand like traditional hexaphyrin, enabling the formation of an even more strained bis-Rh(I) complex. The electronic structures and photophysical properties of the free base and metal complexes are systematically studied by steady state absorption and fstransient absorptions (fs-TA) spectroscopies, as well as DFTcalculations. Notably, 3 can be regarded as a hexaphyrin-sized backto-back fused bis-dicarbacorrole, which stands as the smallest fused carbaporphyrinoid array prepared to date.

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Nanoscale and hollow inorganic sulfide@porous organic network doped intelligent hydrogels for accelerating diabetes wound therapeutics

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Science China Chemistry 2025年

作者： Yanhong Li Qiang zhang Quanbo Wang Junping Wang Xiaomei zhang Caixia Yin School of Chemistry and Chemical Engineering Shandong University Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education Shanxi University

Diabetic wound healing remains a major challenge due to the excess hyperglycemia microenvironment,massively bacterial infections,macrophage dysfunction,and persistent *** comprehensively solve these problems,novel multifunctional materials are highly ***,a versatile and intelligent hydrogel (Cu2S@FePPOPTPM@GOx@Gel) is ***2S@FePPOPTPM@GOx with hollow morphology and controllable size was rationally designed and fabricated by using Cu2S nanocubes as a template,followed by in situ growth of FePPOPTPMand loading glucose oxidase （GOx）,*** infection occurs,the Schiff base bonds in Cu2S@FePPOPTPM@GOx@Gel can controllably release Cu2S@FePPOPTPM@GOx based on its excellent dynamic pH-responsiveness,thereby synergically reducing blood glucose levels and killing bacteria achieved relying on the excellent catalytic activity of GOx towards glucose and its promoted peroxidelike activity of *** experiments on diabetic wound model in vivo demonstrated that Cu2S@FePPOPTPM@GOx@Gel promoted wound healing and skin regeneration,which was attributed to its antibacterial properties,alleviating inflammation,stimulating vascular regeneration,and encouraging M2 polarization of *** work provides a novel strategy for the construction of a microenvironment-responsive and antibiotics-free drug delivery platform to treat diabetic wounds,as well as broad prospects of nanomaterials in the clinical treatment of chronic wounds.

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Upcycling of polyethylene terephthalate to1,4-cyclohexanedimethanol in water

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Science China Chemistry 2025年

作者： Shuhui Fang Zhiwen Gao Xinrui Shi Min zhang Wei zhang Yue Liu State Key Laboratory of Petroleum Molecular & Process Engineering Shanghai Key Laboratory of Green Chemistry and Chemical ProcessesSchool of Chemistry and Molecular Engineering East China Normal University Engineering Center for Sustainable Carbon Science and Technology East China Normal University Institute of Eco-Chongming

The recycling of waste polyethylene terephthalate（PET）, an extensively used polymer as plastic and fiber materials, has become an urgent topic due to the rapid generation and accumulation of plastic waste into the environment. Current chemical recycling approaches to depolymerize and convert PET into 1,4-cyclohexanedimethanol（CHDM）, an important chemical in the production of advanced polyesters, predominantly use organic solvents, such as alcohols or dioxane. Herein, we developed an environmentally friendly and economically viable pathway for converting PET to CHDM using water as the solvent. In this process, PET is sequentially hydrolyzed in water, hydrogenated to 1,4-cyclohexane dicarboxylic acid（CHDA）, and then reduced to CHDM. The PET conversion rate is self-enhanced in aqueous medium via acid-catalyzed hydrolysis by the generated CHDA intermediate. A Pd-based catalyst（e.g., Pd/C） selectively hydrogenates the arene ring of the PET monomer, terephthalic acid intermediate, and a Ru-Sn/C bimetallic catalyst reduces its COOH to CH2OH group. At optimized reaction conditions, a complete conversion of PET and 80.1% yield of CHDM are obtained. Alternatively, this approach can also efficiently produce CHDA from PET, with a yield up to 86.4%.

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