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Realize ultralow-energy-consumption photo-synaptic device based on a single(Al,Ga)N nanowire for neuromorphic computing

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Nano Research 2024年第3期17卷 1933-1941页

作者： Xiushuo Gu Min zhou Yukun Zhao Qianyi Zhang Jianya Zhang yonglin Huang Shulong Lu College of Electronic and Optical Engineering&College of Flexible Electronics(Future Technology) Nanjing University of Posts and TelecommunicationsNanjing 210023China Key Lab of Nanodevices and Applications Suzhou Institute of Nano-Tech and Nano-Bionics(SINANO)Chinese Academy of Sciences(CAS)Suzhou 215123China School of Nano-Tech and Nano-Bionics University of Science and Technology of ChinaHefei 230026China Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application School of Physical Science and TechnologySuzhou University of Science and TechnologySuzhou 215009China

The rapid development of artificial intelligence poses an urgent need for low-energy-consumption and small-sized artificial photonic synapses.Here,it is pretty novel to demonstrate a light-stimulated synaptic device based on a single(Al,Ga)N nanowire successfully.Thanks to the presence of vacancy defects in the single nanowire,the artificial synaptic device can simulate multiple functions of biological synapses under stimulation of both 310 and 365 nm light photons,including paired-pulse facilitation,spike timing dependent plasticity,and memory learning capabilities.The energy consumption of artificial synaptic device can be reduced as little as 5.58×10^(-13) J,which is close to that of the biological synapse in human brain.Furthermore,the synaptic device is demonstrated to have the high stability for both long-time stimulation and long-time storage.Based on the experimental conductance of long-term potentiation and long-term depression,the simulated three-layer neural network can achieve a high recognition rate of 92%after only 10 training epochs.With a brain-like behavior,the single-nanowire-based synaptic devices can promote the development of visual neuromorphic computing technology and artificial intelligence systems requiring ultralow energy consumption.

关键词： single(Al Ga)N nanowire light-stimulated synaptic device low-energy-consumption neural network

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A Comprehensive Study of a Low-Grade Heat-Driven Cooling and Power System Based on Heat Current Method

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Journal of Thermal Science 2024年第4期33卷 1523-1541页

作者： ZHAO Tian XU Ronghong XIN yonglin HE Kelun MA Huan YUAN Mengdi CHEN Qun School of Energy Storage Science and Engineering North China University of Technology Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Engineering MechanicsTsinghua University

Combined cooling and power(CCP) system driven by low-grade heat is promising for improving energy efficiency.This work proposes a CCP system that integrates a regenerative organic Rankine cycle(RORC)and an absorption chiller on both driving and cooling fluid sides.The system is modeled by using the heat current method to fully consider nonlinear heat transfer and heat-work conversion constraints and resolve its behavior accurately.The off-design system simulation is performed next,showing that the fluid inlet temperatures and flow rates of cooling water as well as RORC working fluid strongly affect system performance.The off-design operation even becomes infeasible when parameters deviate from nominal values largely due to limited heat transfer capability of components,highlighting the importance of considering heat transfer constraints via heat current method.Design optimization aiming to minimize the total thermal conductance is also conducted.RORC efficiency increases by 7.9% and decreases by 12.4% after optimization,with the hot fluid inlet temperature increase from 373.15 to 403.15 K and mass flow rate ranges from 10 to 30 kg/s,emphasizing the necessity of balancing system cost and performance.

关键词： combined cooling and power system organic Rankine cycle absorption chiller cascade heat utilization heat current method off-design analysis

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A hybrid contact approach for modeling soil-structure interaction using the material point method

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第5期16卷 1864-1882页

作者： Qinyang Sang yonglin Xiong Rongyue Zheng Xiaohua Bao Guanlin Ye Feng Zhang Key Laboratory of Impact and Safety Engineering Ministry of EducationSchool of Mechanical Engineering and MechanicsNingbo UniversityNingbo315211China Institute of Geotechnical Engineering Ningbo UniversityNingbo315211China College of Civil and Transportation Engineering Shenzhen UniversityShenzhen518060China Department of Civil Engineering Shanghai Jiao Tong UniversityShanghai200240China Department of Civil Engineering Nagoya Institute of TechnologyShowa-kuGokiso-choNagoya466-8555Japan

The grid-based multi-velocity field technique has become increasingly popular for simulating the Material Point Method(MPM)in contact problems.However,this traditional technique has some shortcomings,such as(1)early contact and contact penetration can occur when the contact conditions are unsuitable,and(2)the method is not available for contact problems involving rigid-nonrigid materials,which can cause numerical instability.This study presents a new hybrid contact approach for the MPM to address these limitations to simulate the soil and structure interactions.The approach combines the advantages of point-point and point-segment contacts to implement contact detection,satisfying the impenetrability condition and smoothing the corner contact problem.The proposed approach is first validated through a disk test on an inclined slope.Then,several typical cases,such as granular collapse,bearing capacity,and deformation of a flexible retaining wall,are simulated to demonstrate the robustness of the proposed approach compared with FEM or analytical solutions.Finally,the proposed method is used to simulate the impact of sand flow on a deformable structure.The results show that the proposed contact approach can well describe the phenomenon of soil-structure interaction problems.

关键词： Material point method Soil-structure interaction Numerical simulation Contact algorithm

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When Does Sora Show:The Beginning of TAO to Imaginative Intelligence and Scenarios Engineering

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 809-815页

作者： Fei-Yue Wang Qinghai Miao Lingxi Li Qinghua Ni Xuan Li Juanjuan Li Lili Fan yonglin Tian Qing-Long Han School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Department of Electrical and Computer Engineering Indiana University-Purdue University IndianapolisIndianapolisIN 46202USA Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

DURING our discussion at workshops for writing“What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence”[1],we had expected the next milestone for Artificial Intelligence(AI)would be in the direction of Imaginative Intelligence(II),i.e.,something similar to automatic wordsto-videos generation or intelligent digital movies/theater technology that could be used for conducting new“Artificiofactual Experiments”[2]to replace conventional“Counterfactual Experiments”in scientific research and technical development for both natural and social studies[2]-[6].Now we have OpenAI’s Sora,so soon,but this is not the final,actually far away,and it is just the beginning.

关键词： something Intelligence replace

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Antioxidant-enriched autologous biogel promoted diabetic wound healing by remodeling inherent posttraumatic inflammatory patterning and restoring compromised microenvironment homeostasis

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Regenerative Biomaterials 2022年第1期9卷 202-218页

作者： Yixi Yang Le Wang yonglin zhou Yijun He Shaozhang Lin Yuwei Zeng Yunhe zhou Wei Li Zaopeng He Qi Zhao Lihao Chen Zijie Li Wenhao Wang Zhi-Yong Zhang Translational Research Centre of Regenerative Medicine and 3D Printing of Guangzhou Medical University Guangdong Province Engineering Research Center for Biomedical EngineeringState Key Laboratory of Respiratory DiseaseThe Third Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510150P.R.China Department of Orthopaedic Surgery The Third Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510150P.R.China Medical Technology and Related Equipment Laboratory The Third Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510150P.R.China Hand and Foot Surgery&Plastic Surgery Affiliated Shunde Hospital of Guangzhou Medical UniversityShunde DistrictFoshanP.R.China

Successful wound healing depends on the reconstruction of proper tissue homeostasis,particularly in the posttraumatic inflammatory tissue microenvironment.Diabetes jeopardizes tissues’immune homeostasis in cutaneous wounds,causing persistent chronic inflammation and cytokine dysfunction.Previously,we developed an autologous regeneration factor(ARF)technology to extract the cytokine composite from autologous tissue to restore immune homeostasis and promote wound healing.However,treatment efficacy was significantly compromised in diabetic conditions.Therefore,we proposed that a combination of melatonin and ARF,which is beneficial for proper immune homeostasis reconstruction,could be an effective treatment for diabetic wounds.Our research showed that the utilization of melatonin-mediated ARF biogel(AM gel)promoted diabetic wound regeneration at a more rapid healing rate.RNA-Seq analysis showed that AM gel treatment could restore more favorable immune tissue homeostasis with unique inflammatory patterning as a result of the diminished intensity of acute and chronic inflammation.Currently,AM gel could be a novel and promising therapeutic strategy for diabetic wounds in clinical practice through favorable immune homeostatic reconstructions in the tissue microenvironment and proper posttraumatic inflammation patterning.

关键词： autologous regeneration factors wound healing homeostasis tissue microenvironment inflammation patterning

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Parallel Physics-Informed Neural Networks Method with Regularization Strategies for the Forward-Inverse Problems of the Variable Coefficient Modified KdV Equation

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Journal of Systems Science & Complexity 2024年第2期37卷 511-544页

作者： zhou Huijuan School of Science Shanghai Maritime UniversityShanghai 201306China

This paper mainly introduces the parallel physics-informed neural networks(PPINNs)method with regularization strategies to solve the data-driven forward-inverse problems of the variable coefficient modified Korteweg-de Vries(VC-MKdV)equation.For the forward problem of the VC-MKdV equation,the authors use the traditional PINN method to obtain satisfactory data-driven soliton solutions and provide a detailed analysis of the impact of network width and depth on solving accuracy and speed.Furthermore,the author finds that the traditional PINN method outperforms the one with locally adaptive activation functions in solving the data-driven forward problems of the VC-MKdV equation.As for the data-driven inverse problem of the VC-MKdV equation,the author introduces a parallel neural networks to separately train the solution function and coefficient function,successfully addressing the function discovery problem of the VC-MKdV equation.To further enhance the network’s generalization ability and noise robustness,the author incorporates two regularization strategies into the PPINNs.An amount of numerical experimental data in this paper demonstrates that the PPINNs method can effectively address the function discovery problem of the VC-MKdV equation,and the inclusion of appropriate regularization strategies in the PPINNs can improves its performance.

关键词： Data-driven forward-inverse problems parallel physics-informed neural networks regularization strategies variable coefficient modified KdV equation

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An Environment‑Tolerant Ion‑Conducting Double‑Network Composite Hydrogel for High‑Performance Flexible Electronic Devices

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Nano-Micro Letters 2024年第5期16卷 352-369页

作者： Wenchao Zhao Haifeng zhou Wenkang Li Manlin Chen Min zhou Long Zhao State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074People’s Republic of China School of Chemistry and Chemical Engineering Huazhong University of Science and TechnologyWuhan 430074People’s Republic of China

High-performance ion-conducting hydrogels(ICHs)are vital for developing flexible electronic devices.However,the robustness and ion-conducting behavior of ICHs deteriorate at extreme tempera-tures,hampering their use in soft electronics.To resolve these issues,a method involving freeze–thawing and ionizing radiation technology is reported herein for synthesizing a novel double-network(DN)ICH based on a poly(ionic liquid)/MXene/poly(vinyl alcohol)(PMP DN ICH)system.The well-designed ICH exhibits outstanding ionic conductivity(63.89 mS cm^(-1) at 25℃),excellent temperature resistance(-60–80℃),prolonged stability(30 d at ambient temperature),high oxidation resist-ance,remarkable antibacterial activity,decent mechanical performance,and adhesion.Additionally,the ICH performs effectively in a flexible wireless strain sensor,thermal sensor,all-solid-state supercapacitor,and single-electrode triboelectric nanogenerator,thereby highlighting its viability in constructing soft electronic devices.The highly integrated gel structure endows these flexible electronic devices with stable,reliable signal output performance.In particular,the all-solid-state supercapacitor containing the PMP DN ICH electrolyte exhibits a high areal specific capacitance of 253.38 mF cm^(-2)(current density,1 mA cm^(-2))and excellent environmental adaptability.This study paves the way for the design and fabrication of high-performance mul-tifunctional/flexible ICHs for wearable sensing,energy-storage,and energy-harvesting applications.

关键词： Ionic liquids Double-network hydrogels Temperature tolerance Multifunctionality Flexible electronic devices

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Perturbation of autophagy pathways in murine alveolar macrophage by 2D TMDCs is chalcogen-dependent

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Journal of Environmental Sciences 2024年第1期135卷 97-107页

作者： Xiaofei zhou Weitao Jin Rui Zhang Xuan Mao Jianbo Jia Hongyu zhou College of Science&Technology Hebei Agricultural UniversityHuanghua 061100China Institute of Environmental Research at Greater Bay Area Key Laboratory for Water Quality and Conservation of the Pearl River DeltaMinistry of EducationGuangzhou UniversityGuangzhou 510006China

Increasing risks of incidental and occupational exposures to two-dimensional transition metal dichalcogenides(2D TMDCs)due to their broad application in various areas raised their public health concerns.While the composition-dependent cytotoxicity of 2D TMDCs has been well-recognized,how the outer chalcogenide atoms and inner transition metal atoms differentially contribute to their perturbation on cell homeostasis at non-lethal doses remains to be identified.In the present work,we compared the autophagy induction and related mechanisms in response to WS_(2),NbS_(2),WSe_(2)and Nb Se_(2)nanosheets exposures in MH-S murine alveolar macrophages.All these 2D TMDCs had comparable physicochemical properties,overall cytotoxicity and capability in triggering autophagy in MH-S cells,but showed outer chalcogen-dependent subcellular localization and activation of autophagy pathways.Specifically,WS_(2)and NbS_(2)nanosheets adhered on the cell surface and internalized in the lysosomes,and triggered m TOR-dependent activation of autophagy.Meanwhile,WSe_(2)and Nb Se_(2)nanosheets had extensive distribution in cytoplasm of MH-S cells and induced autophagy in an m TOR-independent manner.Furthermore,the 2D TMDCs-induced perturbation on autophagy aggravated the cytotoxicity of respirable benzo[a]pyrene.These findings provide a deeper insight into the potential health risk of environmental 2D TMDCs from the perspective of homeostasis perturbation.

关键词： Chalcogen group Autophagy pathway Cell function Endosomal escape Inhalation toxicity

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The role of proteasomes in tumorigenesis

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Genes & Diseases 2024年第4期11卷 155-169页

作者： Xiangyi zhou Ruqing Xu Yue Wu Li zhou Tingxiu Xiang Department of Oncology The First Affliated Hospital of Chongqing Medical UniversityChongqing 400016China Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment Chongqing University Cancer HospitalChongqing 400030China

Protein homeostasis is the basis of normal life activities,and the proteasomefamily plays an extremely important function in this process.The proteasome 2os is a concentric circle structure with twoαrings and twoβrings overlapped.The proteasome 2os can perform both ATP-dependent and non-ATP-dependent ubiquitination proteasome degradation by binding to various subunits(such as 19S,11S,and 200 PA),which is performed by its active subunitβ1,β2,andβ5.The proteasome can degrade misfolded,excess proteins tomaintain homeostasis.At the same time,it can be utilized by tumors to degrade over-proliferate and unwanted proteins to support their growth.Proteasomes can affect the development of tumors from several aspects including tumor signaling pathways such as NF-kB and p53,cell cycle,immune regulation,and drug resistance.Proteasome-encoding genes have been found to be overexpressed in a variety of tumors,providing a potential novel target for cancer therapy.In addition,proteasome inhibitors such as bortezomib,carfilzomib,and ixazomib have been put into clinical application as the first-line treatment of multiple myeloma.More and more studies have shown that it also has different therapeutic effects in other tumors such as hepatocellular carcinoma,non-small cell lung cancer,glioblastoma,and neuroblastoma.However,proteasome inhibitors are not much effective due to their tolerance and singleness in other tumors.Therefore,further studies on their mechanisms of action and drug interactions are needed to investigate their therapeutic potential.

关键词： Bortezomib Cancer therapy Immunoproteasome Multiplemyeloma Proteasome 20S Proteasome inhibitor Thymoproteasom

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Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments

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Chinese Journal of Aeronautics 2024年第3期37卷 237-257页

作者： Fei WANG Xiaoping ZHU zhou zhou Yang TANG School of Astronautics Northwestern Polytechnical UniversityXi’an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China

In some military application scenarios,Unmanned Aerial Vehicles(UAVs)need to perform missions with the assistance of on-board cameras when radar is not available and communication is interrupted,which brings challenges for UAV autonomous navigation and collision avoidance.In this paper,an improved deep-reinforcement-learning algorithm,Deep Q-Network with a Faster R-CNN model and a Data Deposit Mechanism(FRDDM-DQN),is proposed.A Faster R-CNN model(FR)is introduced and optimized to obtain the ability to extract obstacle information from images,and a new replay memory Data Deposit Mechanism(DDM)is designed to train an agent with a better performance.During training,a two-part training approach is used to reduce the time spent on training as well as retraining when the scenario changes.In order to verify the performance of the proposed method,a series of experiments,including training experiments,test experiments,and typical episodes experiments,is conducted in a 3D simulation environment.Experimental results show that the agent trained by the proposed FRDDM-DQN has the ability to navigate autonomously and avoid collisions,and performs better compared to the FRDQN,FR-DDQN,FR-Dueling DQN,YOLO-based YDDM-DQN,and original FR outputbased FR-ODQN.

关键词： Faster R-CNN model Replay memory Data Deposit Mechanism(DDM) Two-part training approach Image-based Autonomous Navigation and Collision Avoidance(ANCA) Unmanned Aerial Vehicle(UAV)

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