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Journal of Thermal Science 2024年第1期33卷 101-113页

作者： yuan Baoqiang WANG Wei XIN Gongming DU Wenjing School of Energy and Power Engineering Shandong UniversityJi'nan 250061China

Large eddy simulations have been conducted to study upward transitional flows and heat transfer characteristics of supercritical CO_(2) in a vertical *** numerical simulation was carried out on a modified buoyantPimpleFOAM solver in OpenFOAM 7,and was verified using experiment *** results indicate that increasing the Grashof numbers can reduce the flow stability and make the flow transition *** are four stages of heat transfer in the transition process,i.e.,weakened,improved,recovered and normal heat *** heat transfer phenomena in the transition process were explained from three perspectives:thermal boundary layer theory,turbulent transport and pseudo-boiling *** transfer enhancement during transition is related to the transport of supercritical molecular clusters,and these molecular clusters are regarded as pseudo-bubbles in pseudo-boiling *** flow pattern of the pseudo-phases in the dia-Widom process contains single-phase flow,steady pseudo-film flow,unsteady pseudo-film flow,partial pseudo-bubbles flow and flocculent pseudo-film ***-bubbles have similar behaviors to subcritical bubbles,i.e.,break-up,deformation,condensation and *** researches in this work are favorable for understanding the heat transfer mechanism of supercritical fluids during flow transition.

关键词： supercritical heat transfer large eddy simulation transition pseudo-boiling

Micro-flow structure at regime transition from bubbling to turbulent fluidization in a fluidized bed

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Particuology 2024年第6期89卷 117-130页

作者： Chaoyu Yan Yue yuan Xiaoyang Wei Jesse Zhu State Key Laboratory of Heavy Oil Processing Beijing Key Laboratory of Process Fluid Filtration and SeparationCollege of Mechanical and Transportation EngineeringChina University of PetroleumBeijing 102249China China Beacons Institute The University of NottinghamNingbo315100China Department of Chemical and Biochemical Engineering University of Western OntarioLondonOntarioN6A 5B9Canada

Gas-solid fluidized beds have found extensive utilization in frontline manufacturing,in particular as low-velocity *** fluidization status,the bubbling or turbulent flow regime and the transition in between,determine the system performance in practical *** the convoluted hydrodynamics are quantitively evaluated through numerous data-processing methodologies,none of them alone can reflect all the critical information to identify the transition from the bubbling to the turbulent ***,this study was to exploit a coupling data processing methodology,in the combination of standard deviation,power spectrum density,probability density function,wavelet transform,and wavelet multiresolution method,to jointly explain the micro-flow structure at the regime transition from bubbling to turbulent *** transient differential pressure fluctuation was measured for the evaluation in a fluidized bed(0.267 m i.d.×2.5 m height)with FCC catalysts(d_(p)=65μm,ρ_(p)=1780kg/m^(3))at different superficial gas velocities(0.02–1.4 m/s).The results show that the onset of turbulent fluidization starts earlier in the top section of the bed than in the bottom *** wavelet decomposition displays that the fluctuation of differential pressure mainly concentrates on the sub-signals with an intermediate frequency *** sub-signals could be synthesized into three types of scales(micro-scale,meso-scale,and macro-scale),representing the multi-scale hydrodynamics in the fluidized *** micro-scale signal has the characteristic information of bubbling fluidization,and the characteristic information of turbulent fluidization is mainly represented by the meso-scale *** work provides a systematic comprehension of fluidization status assessment and serves as an impetus for more coupling analysis in this sector.

关键词： Flow regime transition Bubbling fluidization Turbulent fluidization Micro-flow structure Differential pressure fluctuation

Numerical analysis on the transport properties and residence time distribution of ribbon biomass particles in a riser reactor based on CFD-DEM approach

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Particuology 2024年第4期87卷 133-146页

作者： Haichao Zhao Conghui Gu Bingyang Xu yuan Liu Mingpu Du Kaiyuan Deng Jingyu Zhu Iana Voronina Zhulin yuan School of Energy and Power Jiangsu University of Science and TechnologyZhenjiang212100China China Tobacco Jiangxi Industrial Co.Ltd. Nanchang330096China Institute of Mechanics and Power Engineering Ogarev Mordovia State UniversitySaransk430005Russia Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing210096China

A bended ribbon biomass particle model was developed to explore the dynamic transport properties inside a riser *** time distribution(RTD)of the particles was analyzed by using the Eulerian-Lagrange *** effects of sampling height,particle density,particle size and gas-to-solid mass ratio on RTD were *** coupled Computational Fluid Dynamics and Discrete Element Method(CFD-DEM)model was verified firstly by experimental data on pressure drop and residence time distribution density *** simulation results demonstrated that the ribbon biomass particles display a typical annular-core spatial distribution during *** RTD of particles exhibit an approximate single-peaked normal *** mean residence time(MRT)can reach up to 0.7 s when the particle density is 1200 kg/m^(3).Particle with higher density has longer mean residence *** flow patterns are closer to plug flow if particle length over 12 *** particle flow pattern is not sensitive to changes in particle density and size,while the gas-to-material mass ratio has a significant impact on it.

关键词： Riser Gas-solids two-phase flow Ribbon biomass particles Residence time distribution CFD-DEM

Enhanced conductivity and stability of Prussian blue cathodes in sodium-ion batteries by surface vapor-phase molecular selfassembly

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Nano Research 2024年第5期17卷 4221-4230页

作者： Tao yuan Xiaopan Fu yuan Wang Mingjie Li Shuixin Xia Yuepeng Pang Shiyou Zheng School of Materials and Chemistry University of Shanghai for Science and TechnologyShanghai 200093China

With many merits such as facile synthesis,economy,and relatively high theoretical capacity,Prussian blue analogs(PBAs)are considered promising cathode materials for sodium-ion batteries(SIBs).However,their practical applications still suffer from a low actual specific capacity and inferior stability owing to the imperfect crystallinity,irreversible phase transition,and low intrinsic ***,a surface-modification technique for vapor-phase molecular self-assembly was developed to prepare Fe-based PBAs,specifically sodium iron hexacyanoferrate(NaFeHCF),with a uniform conductive polymer protective layer of polypyrrole(PPy)on the surface,resulting in NaFeHCF@*** incorporation of a PPy protective layer not only improves the electronic conductivity of NaFeHCF@PPy,but also effectively mitigates the dissolution of Fe-ions during ***,this advanced vapor-phase technique avoids Fe^(2+)oxidation and Na^(+)loss during liquid-phase surface *** NaFeHCF@PPy exhibited a remarkably enhanced cycling performance,with capacity retentions of 85.6%and 69.1%over 500 and 1000 cycles,respectively,at 200 mA/g,along with a superior rate performance up to 5 A/g(fast kinetics).Additionally,by adopting this strategy for Mn-based PBAs(NaMnHCF@PPy),we further demonstrated the universality of this method for PBA cathodes in SIBs.

关键词： sodium-ion battery cathode Prussian blue analogs surface modification vapor-phase molecular self-assembly

Interleukins in Epilepsy:Friend or Foe

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Neuroscience Bulletin 2024年第5期40卷 635-657页

作者： yuan Dong Xia Zhang Ying Wang Neuropsychiatry Research Institute The Affiliated Hospital of Qingdao UniversityQingdao UniversityQingdao266000China Program in Cellular and Molecular Medicine Boston Children’s HospitalBostonMA02115USA

Epilepsy is a chronic neurological disorder with recurrent unprovoked seizures,affecting~65 million *** in patients with epilepsy and animal models suggests a contribution of neuroinflammation to epileptogenesis and the development of ***(ILs),as one of the major contributors to neuroinflammation,are intensively studied for their association and modulatory effects on ictogenesis and *** are commonly divided into pro-and anti-inflammatory cytokines and therefore are expected to be pathogenic or neuroprotective in ***,both protective and destructive effects have been reported for many *** may be due to the complex nature of ILs,and also possibly due to the different disease courses that those ILs are involved *** this review,we summarize the contributions of different ILs in those processes and provide a current overview of recent research advances,as well as preclinical and clinical studies targeting ILs in the treatment of epilepsy.

关键词： Epilepsy Interleukins Neuroinflammation

A Lightweight Network with Dual Encoder and Cross Feature Fusion for Cement Pavement Crack Detection

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 255-273页

作者： Zhong Qu Guoqing Mu Bin yuan School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China School of Software Engineering Chongqing University of Posts and TelecommunicationsChongqing400065China

Automatic crack detection of cement pavement chiefly benefits from the rapid development of deep learning,with convolutional neural networks(CNN)playing an important role in this ***,as the performance of crack detection in cement pavement improves,the depth and width of the network structure are significantly increased,which necessitates more computing power and storage *** limitation hampers the practical implementation of crack detection models on various platforms,particularly portable devices like small mobile *** solve these problems,we propose a dual-encoder-based network architecture that focuses on extracting more comprehensive fracture feature information and combines cross-fusion modules and coordinated attention mechanisms formore efficient feature ***,we use small channel convolution to construct shallow feature extractionmodule(SFEM)to extract low-level feature information of cracks in cement pavement images,in order to obtainmore information about cracks in the shallowfeatures of *** addition,we construct large kernel atrous convolution(LKAC)to enhance crack information,which incorporates coordination attention mechanism for non-crack information filtering,and large kernel atrous convolution with different cores,using different receptive fields to extract more detailed edge and context ***,the three-stage feature map outputs from the shallow feature extraction module is cross-fused with the two-stage feature map outputs from the large kernel atrous convolution module,and the shallow feature and detailed edge feature are fully fused to obtain the final crack prediction *** evaluate our method on three public crack datasets:DeepCrack,CFD,and *** results on theDeepCrack dataset demonstrate the effectiveness of our proposed method compared to state-of-the-art crack detection methods,which achieves Precision(P)87.2%,Recall(R)87.7%,and F-score(F1)87.4%.Thanks to our lightweight cr

关键词： Shallow feature extraction module large kernel atrous convolution dual encoder lightweight network crack detection

FL-EASGD:Federated Learning Privacy Security Method Based on Homomorphic Encryption

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Computers, Materials & Continua 2024年第5期79卷 2361-2373页

作者： Hao Sun Xiubo Chen Kaiguo yuan Information Security Center State Key Laboratory ofNetworking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China

Federated learning ensures data privacy and security by sharing models among multiple computing nodes instead of plaintext ***,there is still a potential risk of privacy leakage,for example,attackers can obtain the original data through model inference ***,safeguarding the privacy of model parameters becomes *** proposed solution involves incorporating homomorphic encryption algorithms into the federated learning ***,the existing federated learning privacy protection scheme based on homomorphic encryption will greatly reduce the efficiency and robustness when there are performance differences between parties or abnormal *** solve the above problems,this paper proposes a privacy protection scheme named Federated Learning-Elastic Averaging Stochastic Gradient Descent(FL-EASGD)based on a fully homomorphic encryption ***,this paper introduces the homomorphic encryption algorithm into the FL-EASGD scheme to preventmodel plaintext leakage and realize privacy security in the process ofmodel ***,this paper designs a robust model aggregation algorithm by adding time variables and constraint coefficients,which ensures the accuracy of model prediction while solving performance differences such as computation speed and node anomalies such as downtime of each *** addition,the scheme in this paper preserves the independent exploration of the local model by the nodes of each party,making the model more applicable to the local data ***,experimental analysis shows that when there are abnormalities in the participants,the efficiency and accuracy of the whole protocol are not significantly affected.

关键词： Federated learning homomorphic encryption privacy security stochastic gradient descent

Boundary points, minimal L^(2) integrals and concavity property Ⅱ: Weakly pseudoconvex Kähler manifolds

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Science China Mathematics 2024年第7期67卷 1665-1718页

作者： Qi’an Guan Zhitong Mi Zheng yuan School of Mathematical Sciences Peking UniversityBeijing100871China School of Mathematics and Statistics Beijing Jiaotong UniversityBeijing100044China Institute of Mathematics Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190China

In this paper, we consider minimal L^(2) integrals on the sublevel sets of plurisubharmonic functions on weakly pseudoconvex K?hler manifolds with Lebesgue measurable gain related to modules at boundary points of the sublevel sets, and establish a concavity property of the minimal L^(2) integrals. As applications, we present a necessary condition for the concavity degenerating to linearity, a concavity property related to modules at inner points of the sublevel sets, an optimal support function related to modules, a strong openness property of modules and a twisted version, and an effectiveness result of the strong openness property of modules.

关键词： minimal L^(2)integrals plurisubharmonic functions boundary points weakly pseudoconvex K?hler manifold

Multi-Perspective Data Fusion Framework Based on Hierarchical BERT: Provide Visual Predictions of Business Processes

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Computers, Materials & Continua 2024年第1期78卷 1227-1252页

作者： Yongwang yuan Xiangwei Liu Ke Lu School of Mathematics and Big Data Anhui University of Science and TechnologyHuainan232001China School of Economics and Management Anhui University of Science and TechnologyHuainan232001China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji UniversityShanghai201804China

Predictive Business Process Monitoring(PBPM)is a significant research area in Business Process Management(BPM)aimed at accurately forecasting future behavioral *** present,deep learning methods are widely cited in PBPM research,but no method has been effective in fusing data information into the control flow for multi-perspective process ***,this paper proposes a process prediction method based on the hierarchical BERT and multi-perspective data ***,the first layer BERT network learns the correlations between different category attribute ***,the attribute data is integrated into a weighted event-level feature vector and input into the second layer BERT network to learn the impact and priority relationship of each event on future predicted ***,the multi-head attention mechanism within the framework is visualized for analysis,helping to understand the decision-making logic of the framework and providing visual ***,experimental results show that the predictive accuracy of the framework surpasses the current state-of-the-art research methods and significantly enhances the predictive performance of BPM.

关键词： Business process prediction monitoring deep learning attention mechanism BERT multi-perspective

Ghost Module Based Residual Mixture of Self-Attention and Convolution for Online Signature Verification

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Computers, Materials & Continua 2024年第4期79卷 695-712页

作者： Fangjun Luan Xuewen Mu Shuai yuan Department of Computer Technology School of Computer Science and EngineeringShenyang Jianzhu UniversityShenyang110168China Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction Shenyang Jianzhu UniversityShenyang110168China Shenyang Branch of National Special Computer Engineering Technology Research Center Shenyang Jianzhu UniversityShenyang110168China

Online Signature Verification (OSV), as a personal identification technology, is widely used in various ***, it faces challenges, such as incomplete feature extraction, low accuracy, and computational heaviness. Toaddress these issues, we propose a novel approach for online signature verification, using a one-dimensionalGhost-ACmix Residual Network (1D-ACGRNet), which is a Ghost-ACmix Residual Network that combines convolutionwith a self-attention mechanism and performs improvement by using Ghost method. The Ghost-ACmix Residualstructure is introduced to leverage both self-attention and convolution mechanisms for capturing global featureinformation and extracting local information, effectively complementing whole and local signature features andmitigating the problem of insufficient feature extraction. Then, the Ghost-based Convolution and Self-Attention(ACG) block is proposed to simplify the common parts between convolution and self-attention using the Ghostmodule and employ feature transformation to obtain intermediate features, thus reducing computational ***, feature selection is performed using the random forestmethod, and the data is dimensionally reducedusing Principal Component Analysis (PCA). Finally, tests are implemented on the MCYT-100 datasets and theSVC-2004 Task2 datasets, and the equal error rates (EERs) for small-sample training using five genuine andforged signatures are 3.07% and 4.17%, respectively. The EERs for training with ten genuine and forged signaturesare 0.91% and 2.12% on the respective datasets. The experimental results illustrate that the proposed approacheffectively enhances the accuracy of online signature verification.

关键词： Online signature verification feature selection ACG block ghost-ACmix residual structure