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Probabilistic seismic inversion based on physics-guided deep mixture density network

Petroleum Science 2024年第3期21卷 1611-1631页

作者： Qian-Hao Sun Zhao-yun Zong Xin li National Key Laboratory of Deep Oil and Gas China University of Petroleum(East China)Qingdao266580ShandongChina Laoshan Laboratory Qingdao266580ShandongChina CNOOC Research Institute Ltd. Beijing100028China

Deterministic inversion based on deep learning has been widely utilized in model parameters *** by logging data,seismic data,wavelet and modeling operator,deterministic inversion based on deep learning can establish nonlinear relationships between seismic data and model ***,seismic data lacks low-frequency and contains noise,which increases the non-uniqueness of the *** conventional inversion method based on deep learning can only establish the deterministic relationship between seismic data and parameters,and cannot quantify the uncertainty of *** order to quickly quantify the uncertainty,a physics-guided deep mixture density network(PG-DMDN)is established by combining the mixture density network(MDN)with the deep neural network(DNN).Compared with Bayesian neural network(BNN)and network dropout,PG-DMDN has lower computing cost and shorter training time.A low-frequency model is introduced in the training process of the network to help the network learn the nonlinear relationship between narrowband seismic data and low-frequency *** addition,the block constraints are added to the PG-DMDN framework to improve the horizontal continuity of the inversion *** illustrate the benefits of proposed method,the PG-DMDN is compared with existing semi-supervised inversion *** synthetic data examples of Marmousi II model are utilized to quantify the influence of forward modeling part,low-frequency model,noise and the pseudo-wells number on inversion results,and prove the feasibility and stability of the proposed *** addition,the robustness and generality of the proposed method are verified by the field seismic data.

关键词： Deep learning Probabilistic inversion Physics-guided Deep mixture density network

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Microglial Calcium Homeostasis Modulator 2:Novel Anti-neuroinflammation Target for the Treatment of Neurodegenerative Diseases

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Neuroscience Bulletin 2024年第4期40卷 553-556页

作者： Yuan dong li Tang Neuropsychiatry Research Institute The Affiliated Hospital of Qingdao UniversityQingdao UniversityQingdao266000China Qingdao Institute of Measurement Technology Qingdao266000China

Neurodegenerative diseases,including Alzheimer's disease(AD)and Parkinson's disease(PD),are the most common causes of *** drugs for such diseases can only provide temporary help with the symptoms,leaving the discovery of new drugs urgently in *** cells are the local immune cells in the nervous system and have been recognized as the key player in neuroinflammation that contributes to the process of neurodegeneration[1],raising the discussion of aiming microglia as the therapeutic target for clinical treatment of neurodegenerative diseases.

关键词： inflammation degenerative drugs

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Joint fuzzy background and adaptive foreground model for moving target detection

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Frontiers of Computer Science 2024年第2期18卷 93-106页

作者： Dawei ZHANG Peng WANG Yongfeng dong linhao li Xin li School of Artificial Intelligence Hebei University of TechnologyTianjin 300401China Lane Department of Computer Science and Electrical Engineering West Virginia UniversityMorgantownWV 26506-6109USA

Moving target detection is one of the most basic tasks in computer *** conventional wisdom,the problem is solved by iterative optimization under either Matrix Decomposition(MD)or Matrix Factorization(MF)*** utilizes foreground information to facilitate background *** uses noise-based weights to fine-tune the *** both noise and foreground information contribute to the recovery of the *** jointly exploit their advantages,inspired by two framework complementary characteristics,we propose to simultaneously exploit the advantages of these two optimizing approaches in a unified framework called Joint Matrix Decomposition and Factorization(JMDF).To improve background extraction,a fuzzy factorization is *** fuzzy membership of the background/foreground association is calculated during the factorization process to distinguish their contributions of both to background *** describe the spatio-temporal continuity of foreground more accurately,we propose to incorporate the first order temporal difference into the group sparsity constraint *** temporal constraint is adjusted *** foreground and the background are jointly estimated through an effective alternate optimization process,and the noise can be modeled with the specific probability *** experimental results of vast real videos illustrate the effectiveness of our *** with the current state-of-the-art technology,our method can usually form the clearer background and extract the more accurate ***-noise experiments show the noise robustness of our method.

关键词： matrixdecomposition matrix factorization generalized sparsity noise modeling

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A Novel CCA-NMF Whitening Method for Practical Machine Learning Based Underwater Direction of Arrival Estimation

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Journal of Beijing Institute of Technology 2024年第2期33卷 163-174页

作者： yun Wu Xinting li Zhimin Cao School of Physics and Electronic Engineering Northeast Petroleum UniversityDaqing 163318China

Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical *** to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation *** order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian ***,the obtained information about non-Gaussian components can be used to whiten the array *** on these considerations,a novel practical sonar array whitening method was ***,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array *** the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation *** results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.

关键词： direction of arrival(DOA) sonar array data underwater disturbance machine learn-ing canonical correlation analysis(CCA) non-negative matrix factorization(NMF)

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Enhanced cycling stability and rate performance of Co-doped and La_(2)O_(3)-coated liNi_(0.9)Mn_(0.1)O_(2) toward power battery

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Rare Metals 2024年第2期43卷 658-670页

作者： Jia-Qi Peng Yuan-Yuan Wei dong-Ming liu yun li Bin Hu Bin Huang Jian-Wen Yang Shun-Hua Xiao Ren-Heng Wang Guangxi Key Laboratory of Electrochemical and Magneto-Chemical Functional Materials College of Chemistry and BioengineeringGuilin University of TechnologyGuilin541004China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen518060China

Ultra-high nickel layered oxide cathode material with high energy density is the most promising material to improve the electrochemical performance of lithium-ion batteries(liBs).However,the poor structural stability and severe surface/interface side reactions of the material lead to poor rate performance and cyclic stability,which limits its application in *** this paper,the dual-modification strategy of Co doping and La_(2)O_(3) coating is used to meet the above *** doping can effectively widen layer spacing and reduce li^(+)/Ni^(2+) mixing,and La_(2)O_(3) coating can effectively eliminate the residual alkali on the surface of active material,inhibit the thickening of cathode electrolyte interphase(CEI)film and reduce surface/interface side ***,the modified material(NM90-CL)with excellent electrochemical properties is achieved through the synergistic enhancement of Co doping and La_(2)O_(3) *** capacity retention rate can reach 77.9%after 200 cycles at 1.0℃ and 75.7%after 200 cycles at 5.0℃.Its reversible capacity can up to 153.5 mAh·g^(–1) at 10.0℃.This dual-modification strategy will provide theoretical guidance and technical support for the synthesis of other high-performance electrode materials.

关键词： High nickel cathode material Co doping La_(2)O_(3) coating Electrochemical performance Electrochemical mechanism

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Torque limit-based Inertial Control Method Based on Delayed Support for Primary Frequency Control of Wind Turbines

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 561-570页

作者： Wei Gu Zaiyu Chen Qun li Minghui Yin Qiang li yun Zou School of Automation Nanjing University of Science and TechnologyNanjing 210094China State Grid Jiangsu Electric Power Co. Ltd.Research InstituteNanjing 211103China

To avoid the secondary frequency dip caused by the steep drop of the electrical power of wind turbines(WTs)at the end of frequency support stage,the torque limit-based iner-tial control(TliC)method sets the power reference as a linear function of rotor speed,rather than the step form for the step-wise inertial ***,the compensation effect on the frequency nadir(FN)caused by the load surge is weakened as the TliC power is no longer in the step ***,the maximum point of the frequency response component(FRC)contributed by TliC occurs earlier than the minimum point of FRC corresponding to the load surge,so that the FN cannot be adequately ***,this paper first investigates the relation between the peak and nadir times of FRCs stimulated by the TliC and load *** this basis,with the compensation principle of matching the peak and nadir times of FRCs,the improved TliC method based on delayed support is ***,the effectiveness of the proposed method is validated via the experiments on the test bench of wind-integrated power system.

关键词： Wind turbine frequency response component torque limit inertial control delayed support

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Numerical study on the effective thermal conductivity and thermal tortuosity of porous media with different morphologies

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Science China(Technological Sciences) 2024年第6期67卷 1685-1694页

作者： DU Shen li dong li Meng-Jie HE Ya-ling Key Laboratory of Thermo-Fluid Science and Engineering of Ministry of Education School of Energy and Power EngineeringXi’an Jiaotong UniversityXi’an710049China

Effective thermal conductivity and thermal tortuosity are crucial parameters for evaluating the effectiveness of heat conduction within porous *** direct pore-scale numerical simulation method is applied to investigate the heat conduction processes inside porous structures with different *** thermal conduction performances of idealized porous structures are directly compared with real foams across a wide range of *** foam structures are reconstructed using X-ray computed tomography and image processing techniques,while Kelvin and Weaire-Phelan structures are generated through periodic unit cell *** detailed temperature fields inside the porous structures are determined by solving the heat conduction equation at the pore *** results present that the equivalent thermal conductivity of Kelvin and Weaire-Phelan structures is similar to and greater than that of the real foam structure with the same strut *** thermal tortuosity of real foam structure is relatively larger and the heat conduction path becomes straighter by adopting the anisotropic *** thermal tortuosity of the fluid channels for Kelvin,Weaire-Phelan,and real foam structures is close to *** thermal conductivity of porous structures with heat transfer fluid increases as the thermal conductivity ratio of fluid to solid becomes larger.A small porosity of porous media leads to a larger equivalent thermal conductivity due to the dominant contribution of porous skeleton in the heat conduction *** derived from parallel and series models,as well as the Maxwell-Eucken models,provide decent predictions of effective thermal conductivity,with an average error of less than 8%in the entire range of thermal conductivity ratio.

关键词： volumetric solar receiver porous morphology direct pore-scale simulation equivalent thermal conductivity thermal tortuosity empirical correlation

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Compositionally graded high-voltage P2-type cathode with superior structural stability and redox kinetics for advanced Na-ion batteries

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Nano Research 2024年第4期17卷 2755-2762页

作者： Peiyu Hou Mohan dong Zhenbo Sun Feng li School of Physics and Technology University of JinanJinan 250022China

Layered P2-type cathodes with high voltage,large capacity,and easy synthesis show great potential for developing sodium(Na)-ion batteries(NIBs).However,the P2–O2 phase transition makes their structural degradation and the Na^(+)/vacancy ordering lowers their redox ***,we rationally propose a compositionally graded P2-type cathode,where nickel(Ni)and manganese(Mn)fractions decrease gradually,and cobalt(Co)content increases contiguously from the inside to the outside of a secondary *** these particles,the Ni/Mn-based compound delivers high capacity and high *** the surface of particles,the Co/Mn-based solid solution offers a stable buffer *** from these synergistic effects,this graded P2-type cathode shows the elimination of P2–O2 transformation even when charged to 4.4 V,which enables good structural stability,maintaining capacity retention reaching~80%within 300 ***,the Na^(+)/vacancy ordering superstructure is further suppressed,and the Na^(+)diffusion kinetics is significantly *** proposed graded structure with optimized chemical composition offers a new perspective for eliminating the unwanted phase transition and thus enhancing the electrochemistry of high-voltage layered cathodes for advanced NIBs.

关键词： Na-ion battery P2-type cathode composition regulation phase transition redox stability

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Fast source mask co-optimization method for high-NA EUV lithography

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Opto-Electronic Advances 2024年第4期7卷 44-54页

作者： Ziqi li lisong dong Xu Ma Yayi Wei EDA Center Institute of Microelectronics of Chinese Academy of SciencesBeijing 100029China Key Laboratory of Photoelectronic Imaging Technology and System of Ministry of Education of China School of Optics and PhotonicsBeijing Institute of TechnologyBeijing 100081China University of Chinese Academy of Sciences Beijing 100049China Guangdong Greater Bay Area Applied Research Institute of Integrated Circuit and Systems Guangzhou 510700China

Extreme ultraviolet(EUV)lithography with high numerical aperture(NA)is a future technology to manufacture the integrated circuit in sub-nanometer ***,source mask co-optimization(SMO)is an extensively used approach for advanced lithography process beyond 28 nm technology *** work proposes a novel SMO method to improve the image fidelity of high-NA EUV lithography system.A fast high-NA EUV lithography imaging model is established first,which includes the effects of mask three-dimensional structure and anamorphic ***,this paper develops an efficient SMO method that combines the gradient-based mask optimization algorithm and the compressivesensing-based source optimization algorithm.A mask rule check(MRC)process is further proposed to simplify the optimized mask *** illustrate that the proposed SMO method can significantly reduce the lithography patterning error,and maintain high computational efficiency.

关键词： computational lithography high-NA EUV lithography source-mask co-optimization lithography imaging model

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Method for triangular fuzzy multiple attribute decision making based on two-dimensional density operator method

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Journal of Systems Engineering and Electronics 2024年第1期35卷 178-185页

作者： liN Youliang li Wu liU Gang HUANG dong School of Economics and Management Hunan Institute of Science and TechnologyYueyang 414000China Hunan Vocational College for Nationalities Yueyang 414000China School of Information Science and Engineering Hunan Institute of Science and TechnologyYueyang 414000China

Aiming at the triangular fuzzy(TF)multi-attribute decision making(MADM)problem with a preference for the distribution density of attribute(DDA),a decision making method with TF number two-dimensional density(TFTD)operator is proposed based on the density operator theory for the decision maker(DM).Firstly,a simple TF vector clustering method is proposed,which considers the feature of TF number and the geometric distance of ***,the least deviation sum of squares method is used in the program model to obtain the density weight ***,two TFTD operators are defined,and the MADM method based on the TFTD operator is ***,a numerical example is given to illustrate the superiority of this method,which can not only solve the TF MADM problem with a preference for the DDA but also help the DM make an overall comparison.

关键词： fuzzy decision making clustering density operator multi-attribute decision making(MADM)

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