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Theoretical and Experimental Study on the Performance of Hermetic Diaphragm Squeeze Film Dampers for Gas-Lubricated Bearings

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Chinese Journal of Mechanical Engineering 2024年第3期37卷 151-169页

作者： Jianwei wang Haoxi Zhang Shaocun han hang Li Peng wang Kai Feng State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan UniversityChangsha 410082China

Low damping characteristics have always been a key sticking points in the development of gas *** application of squeeze film dampers can significantly improve the damping performance of gas lubricated *** paper proposed a novel hermetic diaphragm squeeze film damper(HDSFD)for oil-free turbomachinery supported by gas lubricated *** types of HDSFDs with symmetrical structure were proposed for good damping *** considering the compressibility of the damper fluid,based on hydraulic fluid mechanics theory,a dynamic model of HDSFDs under medium is proposed,which successfully reflects the frequency dependence of force *** on the dynamic model,the effects of damper fluid viscosity,bulk modulus of damper fluid,thickness of damper fluid film and plunger thickness on the dynamic stiffness and damping of HDSFDs were *** experimental test rig was assembled and series of experimental studies on HDSFDs were *** damper fluid transverse flow is added to the existing HDSFD concept,which aims to make the dynamic force coefficients independent of *** the force coefficient is still frequency dependent,the damping coefficient at high frequency excitation with damper fluid supply twice as that without damper fluid *** results serve as a benchmark for the calibration of analytical tools under development.

关键词： Hermetic diaphragm squeeze film damper Compressibility Dynamic model Experimental studies

Data-driven discovery of linear dynamical systems from noisy data

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Science China(Technological Sciences) 2024年第1期67卷 121-129页

作者： wang YaSen YUAN Ye FANG HuaZhen DING han School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Department of Mechanical Engineering University of KansasLawrence 66045USA

In modern science and engineering disciplines,data-driven discovery methods play a fundamental role in system modeling,as data serve as the external representations of the intrinsic mechanisms within ***,empirical data contaminated by process and measurement noise remain a significant obstacle for this type of *** this study,we have developed a data-driven method capable of directly uncovering linear dynamical systems from noisy *** method combines the Kalman smoothing and sparse Bayesian learning to decouple process and measurement noise under the expectation-maximization framework,presenting an analytical method for alternate state estimation and system ***,the discovered model explicitly characterizes the probability distribution of process and measurement noise,as they are essential for filtering,smoothing,and stochastic *** have successfully applied the proposed algorithm to several simulation *** results demonstrate its potential to enable linear dynamical system discovery in practical applications where noise-free data are intractable to capture.

关键词： system identification sparse Bayesian learning Kalman smoothing process and measurement noise

The medium-temperature dependence of jet transport coefficient in high-energy nucleus-nucleus collisions

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Nuclear Science and Techniques 2024年第7期35卷 173-191页

作者： Man Xie Qing-Fei han En-Ke wang Ben-Wei Zhang han-Zhong Zhang Key Laboratory of Atomic and Subatomic Structure and Quantum Control(MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of MatterInstitute of Quantum Matter South China Normal UniversityGuangzhou510006China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear ScienceSouthern Nuclear Science Computing CenterSouth China Normal UniversityGuangzhou 510006China Key Laboratory of Quark and Lepton Physics(MOE)and Institute of Particle Physics Central China Normal UniversityWuhan430079China

The medium-temperature T dependence of the jet transport coefficient̂q was studied via the nuclear modification factor RAA(p_(T))and elliptical flow parameter v_(2)(p_(T))for large transverse momentum p_(T) hadrons in high-energy nucleus-nucleus *** a next-to-leading-order perturbative QCD parton model for hard scatterings with modified fragmentation functions due to jet quenching controlled by q,we check the suppression and azimuthal anisotropy for large p_(T) hadrons,and extract q by global fits to RAA(pT)and v_(2)(pT)data in A+A collisions at RHIC and LHC,*** numerical results from the best fits show that q∕T^(3) goes down with local medium-temperature T in the parton jet *** with the case of a constant q∕T^(3),the going-down T dependence of q∕T^(3) makes a hard parton jet to lose more energy near T_(c) and therefore strengthens the azimuthal anisotropy for large pT *** a result,v_(2)(p_(T))for large pT hadrons was enhanced by approximately 10%to better fit the data at RHIC/*** the first-order phase transition from QGP to the hadron phase and the additional energy loss in the hadron phase,v_(2)(p_(T))is again enhanced by 5-10%at RHIC/LHC.

关键词： Jet quenching Jet transport parameter Hadron suppression Elliptic flow coefficient Energy loss asymmetry

Topology of charged AdS black hole in restricted phase space

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Chinese Physics C 2024年第9期48卷 291-299页

作者： han wang Yun-Zhi Du College of Mathematics and Statistics Shanxi Datong UniversityDatong 037009China Department of Physics Shanxi Datong UniversityDatong 037009China Institute of Theoretical Physics Shanxi Datong UniversityDatong 037009China

The local topological properties of black hole systems can be expressed through winding numbers as *** date,AdS black hole thermodynamics are often depicted by the dual parameters of(T,S),(P,V),(Φ,Q) in the extended phase space,while there have been several studies on the black hole thermodynamics in the restricted phase *** this paper,we analyze the topological properties of charged AdS black holes in the restricted phase space under the higher-dimension and higher-order curvature gravity *** results show that the topological number of the charged black hole in the same canonical ensembles is a constant and is independent of the concrete dual thermodynamical ***,the topological number in the grand canonical ensemble is different from that in the canonical ensemble for the same black hole ***,these results are independent of dimension d and highe st order k of the Lanczos-Lovelock densities.

关键词： topology phase transition black hole

Broadening environmental research in the era of accurate protein structure determination and predictions

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Frontiers of Environmental Science & Engineering 2024年第7期18卷 169-178页

作者： Mingda Zhou Tong wang Ke Xu han wang Zibin Li Wei-xian Zhang Yayi wang State Key Laboratory of Pollution Control and Resources Reuse Shanghai Institute of Pollution Control and Ecological SecurityCollege of Environmental Science and EngineeringTongji UniversityShanghai 200092China Translational Research Institute of Brain and Brain-Like Intelligence Shanghai Fourth People's HospitalSchool of MedicineTongji UniversityShanghai 200434China

The deep-learning protein structure prediction method AlphaFold2 has garnered enormous attention beyond the realm of structural biology,for its groundbreaking contribution to solving the"protein foiding problem"In this perspective,we explore the connection between protein structure studies and environmental research,delving into the potential for addressing specific environmental *** are promising for environmental applications because of the functional diversity endowed by their structural ***,structural studies on proteins with environmental significance remain ***,we present the opportunity to study proteins by advancing experimental determination and deep-learning prediction ***,the latest progress in environmental research via cryogenic electron microscopy is *** allows us to determine the structure of protein complexes in their native state within cells at molecular resolution,revealing environmentally-associated structural *** the remarkable advancements in computational power and experimental resolution,the study of protein structure and dynamics has reached unprecedented depth and *** advancements will undoubtedly accelerate the establishment of comprehensive environmental protein structural and functional *** opportunities for protein engineering exist to enable innovative solutions for environmental applications,such as the degradation of persistent contaminants,and the recovery of valuable metals as well as rare earth elements.

关键词： Environmental proteins Protein structure Cryogenic electron microscopy Protein structure prediction Protein engineering Artificial Intelligence

Knowledge enhanced graph inference network based entity-relation extraction and knowledge graph construction for industrial domain

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Frontiers of Engineering Management 2024年第1期11卷 143-158页

作者： Zhulin han Jian wang College of Electronic and Information Engineering Tongji UniversityShanghai 200092China

With the escalating complexity in production scenarios, vast amounts of production information are retained within enterprises in the industrial domain. Probing questions of how to meticulously excavate value from complex document information and establish coherent information links arise. In this work, we present a framework for knowledge graph construction in the industrial domain, predicated on knowledge-enhanced document-level entity and relation extraction. This approach alleviates the shortage of annotated data in the industrial domain and models the interplay of industrial documents. To augment the accuracy of named entity recognition, domain-specific knowledge is incorporated into the initialization of the word embedding matrix within the bidirectional long short-term memory conditional random field (BiLSTM-CRF) framework. For relation extraction, this paper introduces the knowledge-enhanced graph inference (KEGI) network, a pioneering method designed for long paragraphs in the industrial domain. This method discerns intricate interactions among entities by constructing a document graph and innovatively integrates knowledge representation into both node construction and path inference through TransR. On the application stratum, BiLSTM-CRF and KEGI are utilized to craft a knowledge graph from a knowledge representation model and Chinese fault reports for a steel production line, specifically SPOnto and SPFRDoc. The F1 value for entity and relation extraction has been enhanced by 2% to 6%. The quality of the extracted knowledge graph complies with the requirements of real-world production environment applications. The results demonstrate that KEGI can profoundly delve into production reports, extracting a wealth of knowledge and patterns, thereby providing a comprehensive solution for production management.

关键词： knowledge graph construction industrial BiLSTM-CRF document-level relation extraction graph inference

Small particles,big effects:How nanoparticles can enhance plant growth in favorable and harsh conditions

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Journal of Integrative Plant Biology 2024年第7期66卷 1274-1294页

作者： Jie wang Honghong Wu Yichao wang Wuwei Ye Xiangpei Kong Zujun yin Zhengzhou Research Base State Key Laboratory of Cotton Bio‐breeding and Integrated UtilizationSchool of Agricultural SciencesZhengzhou UniversityZhengzhou 450001China State Key Laboratory of Cotton Bio‐breeding and Integrated Utilization Institute of Cotton ResearchChinese Academy of Agricultural SciencesAnyang 455000China National Key Laboratory of Crop Genetic Improvement Huazhong Agricultural UniversityWuhan 430070China School of Engineering Design and Built EnvironmentWestern Sydney UniversityPenrith NSW 2751Australia Western Agricultural Research Center Chinese Academy of Agricultural SciencesChangji 831100China The Key Laboratory of Plant Development and Environmental Adaptation Biology Ministry of EducationCollege of Life SciencesShandong UniversityQingdao 266237China

By 2050,the global population is projected to reach 9 billion,underscoring the imperative for innovative solutions to increase grain yield and enhance food *** has emerged as a powerful tool,providing unique solutions to this ***(NPs)can improve plant growth and nutrition under normal conditions through their high surface-to-volume ratio and unique physical and chemical ***,they can be used to monitor crop health status and augment plant resilience against abiotic stresses(such as salinity,drought,heavy metals,and extreme temperatures)that endanger global *** of NPs can enhance stress tolerance mechanisms in plants,minimizing potential yield losses and underscoring the potential of NPs to raise crop yield and *** review highlights the need for a comprehensive exploration of the environmental implications and safety of nanomaterials and provides valuable guidelines for researchers,policymakers,and agricultural *** thoughtful stewardship,nanotechnology holds immense promise in shaping environmentally sustainable agriculture amid escalating environmental challenges.

关键词： abiotic stress agricultural defense system nano-particles nanotechnology oxidative stress reactive oxygen species toxicity

Generative adversarial networks based motion learning towards robotic calligraphy synthesis

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 452-466页

作者： Xiaoming wang Yilong Yang Weiru wang Yuanhua Zhou Yongfeng yin Zhiguo Gong Department of Computer and Information Science University of MacaoMacaoChina School of Software Beihang UniversityBeijingChina Department of Computer Science and Technology Faculty of Information TechnologyBeijing University of TechnologyBeijingChina School of Foreign Languages Guangzhou Huashang CollegeGuangzhouChina

Robot calligraphy visually reflects the motion capability of robotic *** traditional researches mainly focus on image generation and the writing of simple calligraphic strokes or characters,this article presents a generative adversarial network(GAN)-based motion learning method for robotic calligraphy synthesis(Gan2CS)that can enhance the efficiency in writing complex calligraphy words and reproducing classic calligraphy *** key technologies in the proposed approach include:(1)adopting the GAN to learn the motion parameters from the robot writing operation;(2)converting the learnt motion data into the style font and realising the transition from static calligraphy images to dynamic writing demonstration;(3)reproducing high-precision calligraphy works by synthesising the writing motion data *** this study,the motion trajectories of sample calligraphy images are firstly extracted and converted into the robot *** robot performs the writing with motion planning,and the writing motion parameters of calligraphy strokes are learnt with *** the motion data of basic strokes is synthesised based on the hierarchical process of‘stroke-radicalpart-character’.And the robot re-writes the synthesised characters whose similarity with the original calligraphy characters is *** calligraphy characters have been tested in the experiments for method validation and the results validated that the robot can actualise the robotic calligraphy synthesis of writing motion data with GAN.

关键词： calligraphy synthesis generative adversarial networks Motion learning robot writing

PAL-BERT:An Improved Question Answering Model

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2729-2745页

作者： Wenfeng Zheng Siyu Lu Zhuohang Cai Ruiyang wang Lei wang Lirong yin School of Automation University of Electronic Science and Technology of ChinaChengdu610054China Department of Geography and Anthropology Louisiana State UniversityBaton RougeLA70803USA

In the field of natural language processing(NLP),there have been various pre-training language models in recent years,with question answering systems gaining significant ***,as algorithms,data,and computing power advance,the issue of increasingly larger models and a growing number of parameters has ***,model training has become more costly and less *** enhance the efficiency and accuracy of the training process while reducing themodel volume,this paper proposes a first-order pruningmodel PAL-BERT based on the ALBERT model according to the characteristics of question-answering(QA)system and language ***,a first-order network pruning method based on the ALBERT model is designed,and the PAL-BERT model is ***,the parameter optimization strategy of the PAL-BERT model is formulated,and the Mish function was used as an activation function instead of ReLU to improve the ***,after comparison experiments with traditional deep learning models TextCNN and BiLSTM,it is confirmed that PALBERT is a pruning model compression method that can significantly reduce training time and optimize training *** with traditional models,PAL-BERT significantly improves the NLP task’s performance.

关键词： PAL-BERT question answering model pretraining language models ALBERT pruning model network pruning TextCNN BiLSTM