检索结果-南通市图书馆

Effect of a Carbon Fibre-steel Fibre-graphite Conductive Filler on the Electrothermal Properties of Cementitious Materials

在线全文

学校读者我要写书评

暂无评论

Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 141-151页

作者： FAN Yanan WEI Hong ZHENG Hongyong du Hongxiu Department of Architecture and Environmental Engineering Taiyuan UniversityTaiyuan 030032China College of Civil Engineering Taiyuan University of TechnologyTaiyuan 030032China

Carbon fibre,steel fibre and graphite were used as conductive fillers to prepare cementitious materials with excellent electrothermal *** electrically conductive cementitious materials with different volume dosages were analysed through compressive and flexural strength,electrochemical impedance spectroscopy and temperature rise *** equivalent circuit model was established to study the electrically conductive heat generation mechanism in the electrically conductive cementitious *** results indicate that the mechanical properties of cementitious composite materials with a ternary conductive phase are better than those of pristine cementitious materials because the fibrous filler improves their mechanical ***,the incorporation of graphite in the material reduces its *** fibrous and point-like conductive phase materials into the cementitious material enhances the overall conductive pathway and considerably reduces the electrical resistance of the cementitious material,enhancing its conductive *** volume ratios of carbon fibre,steel fibre and graphite that achieve an optimal complex doping in the cementitious material were 0.35%,0.6%and 6%,*** was determined using the mutation point of each circuit element parameter as the percolation *** addition,at a certain safety voltage,there is a uniform change between the internal and surface temperatures of the conductive cementitious material,and the heating effect in this materialis is considerably better than that in the pristine cementitious material.

关键词： cementitious composites conductive fillers electrothermal properties electrochemical impedance spectroscopy

Pyroptosis,ferroptosis,and autophagy in spinal cord injury:regulatory mechanisms and therapeutic targets

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Neural Regeneration Research 2025年第10期20卷 2787-2806页

作者： Qingcong Zheng du Wang Rongjie Lin Weihong Xu Department of Spinal Surgery the First Affiliated Hospital of Fujian Medical UniversityFuzhouFujian ProvinceChina Arthritis Clinical and Research Center Peking University People’s HospitalBeijingChina Department of Orthopedic Surgery Fujian Medical University Union HospitalFuzhouFujian ProvinceChina

Regulated cell death is a form of cell death that is actively controlled by *** studies have shown that regulated cell death plays a key role after spinal cord *** and ferroptosis are newly discovered types of regulated cell deaths that have been shown to exacerbate inflammation and lead to cell death in damaged spinal ***,a complex form of cell death that is interconnected with various regulated cell death mechanisms,has garnered significant attention in the study of spinal cord *** injury triggers not only cell death but also cellular survival *** signaling pathways play pivotal roles in influencing the processes of both deterioration and repair in spinal cord injury by regulating pyroptosis,ferroptosis,and ***,this review aims to comprehensively examine the mechanisms underlying regulated cell deaths,the signaling pathways that modulate these mechanisms,and the potential therapeutic targets for spinal cord *** analysis suggests that targeting the common regulatory signaling pathways of different regulated cell deaths could be a promising strategy to promote cell survival and enhance the repair of spinal cord ***,a holistic approach that incorporates multiple regulated cell deaths and their regulatory pathways presents a promising multi-target therapeutic strategy for the management of spinal cord injury.

关键词： autophagy cell death ferroptosis inflammation pathological mechanisms pyroptosis regulated cell death regulatory pathways spinal cord injury therapeutic targets

The autophagy-lysosome pathway:a potential target in the chemical and gene therapeutic strategies for Parkinson’s disease

在线全文

学校读者我要写书评

暂无评论

Neural Regeneration Research 2025年第1期20卷 139-158页

作者： Fengjuan Jiao Lingyan Meng Kang du Xuezhi Li School of Mental Health Jining Medical UniversityJiningShandong ProvinceChina Shandong Collaborative Innovation Center for Diagnosis Treatment and Behavioral Interventions of Mental DisordersInstitute of Mental HealthJining Medical UniversityJiningShandong ProvinceChina

Parkinson’s disease is a common neurodegenerative disease with movement disorders associated with the intracytoplasmic deposition of aggregate proteins such asα-synuclein in *** one of the major intracellular degradation pathways,the autophagy-lysosome pathway plays an important role in eliminating these *** evidence has shown that upregulation of the autophagy-lysosome pathway may contribute to the clearance ofα-synuclein aggregates and protect against degeneration of dopaminergic neurons in Parkinson’s ***,multiple genes associated with the pathogenesis of Parkinson’s disease are intimately linked to alterations in the autophagy-lysosome ***,this pathway appears to be a promising therapeutic target for treatment of Parkinson’s *** this review,we briefly introduce the machinery of ***,we provide a description of the effects of Parkinson’s disease–related genes on the autophagy-lysosome ***,we highlight the potential chemical and genetic therapeutic strategies targeting the autophagy–lysosome pathway and their applications in Parkinson’s disease.

关键词： autophagy chemical therapy gene therapy Parkinson’s disease α-synuclein

Investigation of bubbles escape behavior from low basicity mold flux for high-Mn high-Al steels using 3D X-ray microscope

在线全文

学校读者我要写书评

暂无评论

International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 102-110页

作者： Qiang Liu Xiang Li Shen du Ming Gao Yanbin Yin Jiongming Zhang State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing 100083China

during the continuous casting process of high-Mn high-Al steels,various types of gases such as Ar need to escape through the top of the *** which,the behavior of bubbles traversing the liquid slag serves as a restrictive link,closely associated with viscosity and the thickness of liquid *** contrast to two-dimensional surface observation,three-dimensional(3D)analysis method can offer a more intuitive,accurate,and comprehensive ***,this study employs a 3D X-ray microscope(3D-XRM)to obtained spatial distribution and 3D morphological characteristics of residual bubbles in mold flux under different basicity of liquid slag,different temperatures,and different holding *** results indicate that as basicity of slag increases from 0.52 to 1.03,temperature increases from 1423 to 1573 K,the viscosity of slag decreases,the floating rate of bubbles *** addition,when holding time increases from 10 to 30 s,the bubbles floating distance increases,and the volume fraction and average equivalent sphere diameter of the bubbles solidified in the mold flux gradually *** one word,increasing the basicity,temperature,and holding time leading to an increase in the removal rate of bubbles especially for the *** findings of bubbles escape behavior provide valuable insights into optimizing low basicity mold flux for high-Mn high-Al steels.

关键词： mold flux low basicity bubbles three-dimensional X-ray microscope viscosity

Preparation of FeCoNi medium entropy alloy from Fe^(3+)-Co^(2+)-Ni^(2+)solution system

在线全文

学校读者我要写书评

暂无评论

International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 92-101页

作者： Zongyou Cheng Qing Zhao Mengjie Tao Jijun du Xingxi Huang Chengjun Liu Key Laboratory for Ecological Metallurgy of Multimetallic Mineral(Ministry of Education) Northeastern UniversityShenyang 110819China School of Metallurgy Northeastern UniversityShenyang 110819China Engineering Research Center of Frontier Technologies for Low-carbon Steelmaking(Ministry of Education) Shenyang 110819China

In recent years,medium entropy alloys have become a research hotspot due to their excellent physical and chemical *** controlling reasonable elemental composition and processing parameters,the medium entropy alloys can exhibit similar properties to high entropy alloys and have lower *** this paper,a FeCoNi medium entropy alloy precursor was prepared via sol-gel and coprecipitation methods,respectively,and FeCoNi medium entropy alloys were prepared by carbothermal and hydrogen *** phases and magnetic properties of FeCoNi medium entropy alloy were *** showed that FeCoNi medium entropy alloy was produced by carbothermal and hydrogen reduction at 1500℃.Some carbon was detected in the FeCoNi medium entropy alloy prepared by carbothermal *** alloy prepared by hydrogen reduction was uniform and showed a relatively high ***,the hydrogen reduction product exhibited better saturation magnetization and lower coercivity.

关键词： medium entropy alloy sol-gel co-precipitation carbothermal hydrogen reduction

Enantio-divergent C–H borylation with two different ligands from a single chiral source

在线全文

学校读者我要写书评

暂无评论

Science China Chemistry 2025年第1期 226-232页

作者： Rongrong du Senmiao Xu State Key Laboratory for Oxo Synthesis and Selective Oxidation Lanzhou Institute of Chemical Physics Chinese Academy of Sciences College of Material Chemistry and Chemical Engineering Key Laboratory of Organosilicon Chemistry and Material TechnologyMinistry of Education Hangzhou Normal University University of Chinese Academy of Sciences

Reported here is an iridium-catalyzed enantio-divergent C（sp3）–H borylation of α-gem-dimethyl groups of trifluoromethyl ketone-derived hydrazones to construct a series of acyclic all-carbon quaternary stereocenters with a high level of chiral induction. Two different chiral bidentate boryl ligands from a common chiral source not only can switch the enantioselectivity but also are complementary in terms of the substrate scope.

关键词：

同方期刊数据库

The detection, extraction and parameter estimation of extreme-mass-ratio inspirals with deep learning

在线全文

学校读者我要写书评

暂无评论

Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 86-96页

作者： Qianyun Yun Wen-Biao Han Yi-Yang Guo He Wang Minghui du Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Shanghai Astronomical Observatory Chinese Academy of Sciences School of Physics and Astronomy Shanghai Jiao Tong University School of Astronomy and Space Science University of Chinese Academy of Sciences Taiji Laboratory for Gravitational Wave Universe (Beijing/Hangzhou) University of Chinese Academy of Sciences Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu Province Key Laboratory of Quantum Theory and Applications of MoE Lanzhou University Institute of Theoretical Physics & Research Center of Gravitation Lanzhou University International Centre for Theoretical Physics Asia-Pacific (ICTP-AP) University of Chinese Academy of Sciences (UCAS) Center for Gravitational Wave Experiment National Microgravity Laboratory Institute of Mechanics Chinese Academy of Sciences

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals(EMRIs). This task is particularly challenging because EMRI signals are complex, lengthy, and faint. In this work, we introduce a2-layer convolutional neural network(CNN) approach to detect EMRI signals for space-borne detectors, achieving a true positive rate(TPR) of 96.9% at a 1% false positive rate(FPR) for signal-to-noise ratio(SNR) from 50 to 100. Especially, the key intrinsic parameters of EMRIs such as the mass, spin of the supermassive black hole(SMBH) and the initial eccentricity of the orbit can also be inferred directly by employing a neural network. The mass and spin of the SMBH can be determined at 99% and 92% respectively. This will greatly reduce the parameter spaces and computing cost for the following Bayesian parameter *** model also has a low dependency on the accuracy of the waveform model. This study underscores the potential of deep learning methods in EMRI data analysis, enabling the rapid detection of EMRI signals and efficient parameter estimation.

关键词： gravitational wave EMRIs deep-learing

Targets capture by distributed active swarms via bio-inspired reinforcement learning

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue Li Jun Sun Shuyuan du Xinpeng Di Yuguang Yang Bo Li Institute of Biomechanics and Medical Engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University Institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

Engine Misfire Fault Detection Based on the Channel Attention Convolutional Model

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

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