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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

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原发性鼻腔鼻窦肠型腺癌二例

中华病理学杂志 2020年第11期49卷 1195-1197页

作者：吴小艳任勇任俊奇袁静萍何惠华武汉大学人民医院病理科 430060 中部战区总医院病理科武汉430070

原发于鼻腔及鼻窦的肠型腺癌(SNS-ITAC)是一种发生于鼻腔、鼻窦内的恶性腺样肿瘤,局部侵袭性较强,常累及筛窦、鼻腔及上颌窦。本文报道2例原发性SNS-ITAC,镜下观察2例患者肿瘤组织学形态均呈乳头状生长,部分呈小管-腺管样生长,肿瘤细胞... 详细信息

原发于鼻腔及鼻窦的肠型腺癌(SNS-ITAC)是一种发生于鼻腔、鼻窦内的恶性腺样肿瘤,局部侵袭性较强,常累及筛窦、鼻腔及上颌窦。本文报道2例原发性SNS-ITAC,镜下观察2例患者肿瘤组织学形态均呈乳头状生长,部分呈小管-腺管样生长,肿瘤细胞核呈长杆状,假复层或复层排列,胞质嗜酸性,可见少量杯状细胞,细胞轻度异型性,可见核分裂象,具有肠型腺癌相似的分化和细胞学特征。免疫组织化学表型:CDX-2、CK20、CK7、Villin阳性,SATB2少数细胞阳性,Ki-67阳性指数约30%,均符合SNS-ITAC。原发性SNS-ITAC是一种罕见肿瘤,发病率为百万分之一,依据临床及病理组织学特点,并结合免疫组织化学染色可以明确诊断。

关键词：肿瘤细胞核肠型腺癌阳性指数肿瘤组织学 CK20 筛窦腺管上颌窦

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Reducibility of Three Dimensional Skew Symmetric System with High Dimensional Weak Liouvillean Frequencies

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Acta Mathematica Sinica,English Series 2024年第10期40卷 2388-2410页

作者： Jie LIU yuan SHAN Jing WANG School of Mathematics and Statistics Nanjing University of Science and Technology School of Statistics and Data Science Nanjing Audit University

In this paper, we consider the reducibility of three-dimensional skew symmetric *** obtain a reducibility result if the base frequency is high-dimensional weak Liouvillean and the parameter is sufficiently small. The ... 详细信息

关键词： 34C20 37J40 high-dimensional weak Liouvillean KAM theory three dimensional skew-symmetric system

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

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

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

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A New Method for Deriving High-Vertical-Resolution Wind Vector Data from the L-Band Radar Sounding System in China

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Advances in Atmospheric Sciences 2024年第11期41卷 2192-2202页

作者： Fang yuan Zijiang ZHOU Jie LIAO National Meteorological Information Center China Meteorological AdministrationBeijing 100081China

High-vertical-resolution radiosonde wind data are highly valuable for describing the dynamics of the meso-and microscale atmosphere. However, the current algorithm used in China's L-band radar sounding system for calculating highvertical-resolution wind vectors excessively smooths the data, resulting in significant underestimation of the calculated kinetic energy of gravity waves compared to similar products from other countries, which greatly limits the effective utilization of the data. To address this issue, this study proposes a novel method to calculate high-vertical-resolution wind vectors that utilizes the elevation angle, azimuth angle, and slant range from L-band radar. In order to obtain wind data with a stable quality, a two-step automatic quality control procedure, including the RMSE-F(root-mean-square error F) test and elemental consistency test are first applied to the slant range data, to eliminate continuous erroneous data caused by unstable signals or radar malfunctions. Then, a wind calculation scheme based on a sliding second-order polynomial fitting is utilized to derive the high-vertical-resolution radiosonde wind vectors. The evaluation results demonstrate that the wind data obtained through the proposed method show a high level of consistency with the high-resolution wind data observed using the Vaisala Global Positioning System and the data observed by the new Beidou Navigation Sounding System. The calculation of the kinetic energy of gravity waves in the recalculated wind data also reaches a level comparable to the Vaisala observations.

关键词： L-band radar sounding system upper air high-vertical-resolution radiosonde wind vectors quality control polynomial fitting

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Biderivations of Hom-Lie Algebras and Superalgebras

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Acta Mathematica Sinica,English Series 2024年第10期40卷 2337-2358页

作者： La Mei yuan Jia Xin LI School of Mathematics Harbin Institute of Technology

On Hom-Lie algebras and superalgebras, we introduce the notions of biderivations and linear commuting maps, and compute them for some typical Hom-Lie algebras and superalgebras,including the q-deformed W(2, 2) algebra... 详细信息

关键词： 17A30 17A60 17B05 17B60 17B70 biderivations Hom-Lie algebras linear commuting maps q-deformed W(2 2) algebra q-deformed Witt algebra q-deformed Witt superalgebra

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