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A multiscale adaptive framework based on convolutional neural network: Application to fluid catalytic cracking product yield prediction

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Petroleum Science 2024年第4期21卷 2849-2869页

作者： Nan Liu Chun-meng Zhu meng-Xuan zhang Xing-Ying Lan State Key Laboratory of Heavy Oil Processing China University of Petroleum (Beijing) College of Artificial Intelligence China University of Petroleum (Beijing)

Since chemical processes are highly non-linear and multiscale, it is vital to deeply mine the multiscale coupling relationships embedded in the massive process data for the prediction and anomaly tracing of crucial process parameters and production indicators. While the integrated method of adaptive signal decomposition combined with time series models could effectively predict process variables, it does have limitations in capturing the high-frequency detail of the operation state when applied to complex chemical processes. In light of this, a novel Multiscale Multi-radius Multi-step Convolutional Neural Network(Msrt Net) is proposed for mining spatiotemporal multiscale information. First, the industrial data from the Fluid Catalytic Cracking(FCC) process decomposition using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN) extract the multi-energy scale information of the feature subset. Then, convolution kernels with varying stride and padding structures are established to decouple the long-period operation process information encapsulated within the multi-energy scale data. Finally, a reconciliation network is trained to reconstruct the multiscale prediction results and obtain the final output. Msrt Net is initially assessed for its capability to untangle the spatiotemporal multiscale relationships among variables in the Tennessee Eastman Process(TEP). Subsequently, the performance of Msrt Net is evaluated in predicting product yield for a 2.80 × 10～6 t/a FCC unit, taking diesel and gasoline yield as examples. In conclusion, Msrt Net can decouple and effectively extract spatiotemporal multiscale information from chemical process data and achieve a approximately reduction of 30% in prediction error compared to other time-series models. Furthermore, its robustness and transferability underscore its promising potential for broader applications.

关键词： Fluid catalytic cracking Product yield Data-driven modeling Multiscale prediction Data decomposition Convolution neural network

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The next decade of SET:from an oncoprotein to beyond

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Journal of Molecular Cell Biology 2024年第1期16卷 1-14页

作者： Han Yao meng zhang Donglai Wang State Key Laboratory of Common Mechanism Research for Major Diseases&Department of Medical Genetics Institute of Basic Medical Sciences&School of Basic MedicineChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100005China

This year marks the fourth decade of research into the protein SET,which was discovered in *** was initially identified as an oncoprotein but later shown to be a multifaceted protein involved in regulating numerous biological processes under both physiological and pathophysiological *** dysfunction is closely associated with diseases,such as cancer and Alzheimer's *** the increasing understanding of how SET works and how it is regulated in cells,targeting aberrant SET has emerged as a potential strategy for disease *** this review,we present a comprehensive overview of the advancements in SET studies,encompassing its biological functions,regulatory networks,clinical implications,and pharmacological ***,we provide insights into the future prospects of SET research,with a particular emphasis on its promising potential in the realm of immune modulation.

关键词： SET biological process regulatory mechanism disease therapy

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Integrating Neighborhood Geographic Distribution and Social Structure Influence for Social Media User Geolocation

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2513-2532页

作者： meng zhang Xiangyang Luo Ningbo Huang Key Laboratory of Cyberspace Situation Awareness of Henan Province Zhengzhou450001China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China

Geolocating social media users aims to discover the real geographical locations of users from their publicly available data,which can support online location-based applications such as disaster alerts and local content *** relationship-based methods represent a classical approach for geolocating social ***,geographically proximate relationships are sparse and challenging to discern within social networks,thereby affecting the accuracy of user *** address this challenge,we propose user geolocation methods that integrate neighborhood geographical distribution and social structure influence(NGSI)to improve geolocation ***,we propose a method for evaluating the homophily of locations based on the k-order neighbor-hood geographic distribution(k-NGD)similarity among *** are notable differences in the distribution of k-NGD similarity between location-proximate and non-location-proximate *** this distinction,we filter out non-location-proximate social relationships to enhance location homophily in the social *** better utilize the location-proximate relationships in social networks,we propose a graph neural network algorithm based on the social structure *** algorithm enables us to perform a weighted aggregation of the information of users’multi-hop neighborhood,thereby mitigating the over-smoothing problem of user features and improving user geolocation *** results on real social media dataset demonstrate that the neighborhood geographical distribution similarity metric can effectively filter out non-location-proximate social ***,compared with 7 existing social relationship-based user positioning methods,our proposed method can achieve multi-granularity user geolocation and improve the accuracy by 4.84%to 13.28%.

关键词： User geolocation social media neighborhood geographic distribution structure influence

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Grading of products utilizing bamboo as a substitute for plastic based on environmental effects

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Science China Earth Sciences 2024年第9期67卷 2989-2998页

作者： meng zhang Guomo ZHOU Lei GU Wenshuo WANG College of Forestry Beijing Forestry UniversityBeijing 100083China Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province Zhejiang A&F UniversityHangzhou 311300China

To achieve sustainable development goals,mitigate plastic pollution,and promote eco-friendly products,it is crucial to identify key products in the bamboo as a substitute for plastic(BSP)industry and assess their environmental *** study proposed a novel evaluation method for the environmental effect of bamboo as a substitute for plastic(EBSP).It focused on the contributions of BSP products in reducing plastic pollution and greenhouse gas *** established a set of EBSP evaluation indicators and developed a grading model,evaluating 30 typical BSP products across six *** results showed that the EBSP evaluation model,based on the emission reduction rate of substitution(ERRS),substitution rate of material(SRM),and product renewal ratio(PRR),can accurately quantify the environmental benefits of BSP *** model has successfully facilitated precise quantification of the EBSP and established a rational and effective grading system for BSP *** results also demonstrated that the average EBSP ranking across the six categories of BSP products,in descending order,is:disposable bamboo products,bamboo household goods,bamboo packaging products,bamboo engineering materials,bamboo furniture products,and bamboo craft ***,disposable bamboo products scored an EBSP 1.96 times the overall average,indicating significant environmental *** PRR emerged as a critical factor influencing *** BSP products with the same lifespan,those with higher substitution emission reduction efficiency offered more pronounced environmental ***,the BSP industry should strategically prioritize disposable bamboo products,such as bamboo toothbrushes,cutlery,and lunch *** products should be the primary focus of policy support and central to efforts in product development,design innovation,and market promotion.

关键词： Bamboo as a substitute for plastic Bamboo products Substitution emission reduction Environmental benefits Gradingevaluation

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Failure characteristics and fracture mechanism of overburden rock induced by mining:A case study in China

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International Journal of Coal Science & Technology 2024年第3期11卷 241-255页

作者： Jiawei Li meng zhang Changxiang Wang Changlong Liao Baoliang zhang Department of Energy and Power Engineering College of Mechanical and Transportation EngineeringChina University of Petroleum(Beijing)BeijingChina Department of Energy and Power Engineering Tsinghua UniversityBeijingChina College of Safety Science and Engineering Anhui University of Science and TechnologyHuainan232000China School of Architecture and Civil Engineering Liaocheng UniversityLiaocheng252000China

This study employs similar simulation testing and discrete element simulation coupling to analyze the failure and deformation processes of a model coal seam's *** caving area of the overburden rock is divided into three zones:the delamination fracture zone,broken fracture zone,and compaction *** caving and fracture zones'heights are approximately 110 m above the coal seam,with a maximum subsidence of 11 *** delamination fracture zone's porosity range is between 0.2 and 0.3,while the remainder of the roof predominantly exhibits a porosity of less than *** addition,the numerical model's stress analysis revealed that the overburden rock's displacement zone forms an'arch-beam'structure starting from 160 m,with the maximum and minimum stress values decreasing as the distance of advancement *** the stress beam interval of the overburden rock,the maximum value changes periodically as the advancement distance *** on a comparative analysis between observable data from on-site work and numerical simulation results,the stress data from the numerical simulation are essentially consistent with the actual results detected on-site,indicating the validity of the numerical simulation results.

关键词： Fracture development characteristics Similar simulation experiment Layer porosity Discrete element numerical simulation

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Experimental Study on the Variation of Optical Imaging Characteristics with Zenith Angle due to Internal Solitary Waves in Sunglint

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Journal of Ocean University of China 2024年第4期23卷 943-952页

作者： LIU Tengfei SUN Lina CHANG Zhe zhang meng LIANG Keda meng Junmin WANG Jing School of Physics and Optoelectronic Engineering Ocean University of ChinaQingdao 266100China First Institute of Oceanography Ministry of Natural ResourcesQingdao 266061China Technology Innovation Center for Ocean Telemetry Ministry of Natural ResourcesQingdao 266061China

Internal solitary waves(ISWs)change the roughness of the sea surface,thus producing dark and bright bands in optical ***,reasons for changes in imaging characteristics with the solar zenith angle remain *** this paper,the optical imaging pattern of ISWs in sunglint under different zenith angles of the light source is investigated by collecting optical images of ISWs through physical *** experiment involves setting 10 zenith angles of the light source,which are divided into area a the optical images of ISWs in the three areas show dark-bright mode,single bright band,and bright-dark mode,which are consistent with those observed by optical remote *** addition,this study analyzed the percentage of the dark and bright areas of the bands and the change in the relative gray difference and found changes in both areas under different zenith angles of the light *** MODIS and ASAR images display a similar brightness-darkness distance of the same ***,the relationship between the brightness-darkness distance and the characteristic half-width of ISWs is determined in accordance with the eKdV theory and the imaging mechanism of ISWs of the SAR ***,the relationship between them in the experiment is almost consistent with the theoretical result.

关键词： internal solitary waves optical imaging characteristic laboratory simulation zenith angle sunglint

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Experimental study on the variation of optical remote sensing imaging characteristics of internal solitary waves with wind speed

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Journal of Oceanology and Limnology 2024年第2期42卷 408-420页

作者： Zhe CHANG Lina SUN Tengfei LIU meng zhang Keda LIANG Junmin meng Jing WANG School of Physics and Optoelectronic Engineering Ocean University of ChinaQingdao 266100China First Institute of Oceanography Ministry of Natural ResourcesQingdao 266061China Technology Innovation Center for Ocean Telemetry Ministry of Natural ResourcesQingdao 266061China

Optical remote sensing has been widely used to study internal solitary waves(ISWs).Wind speed has an important effect on ISW imaging of optical remote *** light and dark bands of ISWs cannot be observed by optical remote sensing when the wind is too *** relationship between the characteristics of ISWs bands in optical remote sensing images and the wind speed is still *** influence of wind speeds on the characteristics of the ISWs bands is investigated based on the physical simulation experiments with the wind speeds of 1.6,3.1,3.5,3.8,and 3.9 m/*** experimental results show that when the wind speed is 3.9 m/s,the ISWs bands cannot be observed in optical remote sensing images with the stratification of h_(1)∶h_(2)=7∶58,ρ_(1)∶ρ_(2)=1∶*** the wind speeds are 3.1,3.5,and 3.8 m/s,which is lower than 3.9 m/s,the ISWs bands can be obtained in the simulated optical remote sensing *** location of the band’s dark and light extremum and the band’s peak-to-peak spacing are almost not affected by wind ***-significant wind speeds can cause a greater gray difference of the light-dark *** provided a scientific basis for further understanding of ISW optical remote sensing imaging.

关键词： internal solitary wave(ISW) optical remote sensing wind speed characteristics of ISWs bands

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A comprehensive analysis of DAC-SDC FPGA low power object detection challenge

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Science China(Information Sciences) 2024年第8期67卷 300-320页

作者： Jingwei zhang Guoqing LI meng zhang Xinye CAO Yu zhang Xiang LI Ziyang CHEN Jun YANG School of Electronics Science and Engineering Southeast University

The lower power object detection challenge(LPODC) at the IEEE/ACM Design Automation Conference is a premier contest in low-power object detection and algorithm(software)-hardware co-design for edge artificial intelligence, which has been a success in the past five years. LPODC focused on designing and implementing novel algorithms on the edge platform for object detection in images taken from unmanned aerial vehicles(UAVs), which attracted hundreds of teams from dozens of countries to participate. Our team SEUer has been participating in this competition for three consecutive years from 2020 to 2022 and obtained sixth place respectively in 2020 and 2021. Recently, we achieved the championship in 2022. In this paper, we presented the LPODC for UAV object detection from 2018 to 2022, including the dataset, hardware platform,and evaluation method. In addition, we also introduced and discussed the details of methods proposed by each year's top three teams from 2018 to 2022 in terms of network, accuracy, quantization method, hardware performance, and total score. Additionally, we conducted an in-depth analysis of the selected entries and results, along with summarizing representative methodologies. This analysis serves as a valuable practical resource for researchers and engineers in deploying the UAV application on edge platforms and enhancing its feasibility and reliability. According to the analysis and discussion, it becomes evident that the adoption of a hardware-algorithm co-design approach is paramount in the context of tiny machine learning(TinyML).This approach surpasses the mere optimization of software and hardware as separate entities, proving to be essential for achieving optimal performance and efficiency in TinyML applications.

关键词： tiny machine learning object detection convolutional neural networks algorithm-hardware co-design low power field programmable gate array

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Insulation Design Rule for a Spacer in SF_(6)/N_(2)-filled DC Gas Insulated Apparatus

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 727-735页

作者： Hongyang Zhou Guoming Ma meng zhang Cong Wang Youping Tu Chengrong Li State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources and the Beijing Key Laboratory of High Voltage and EMC North China Electric Power UniversityBeijing 102206China

A recurring challenge of a DC SF_(6)/N_(2)-filled GIS/GIL apparatus is the charge accumulation at DC *** conventional design rules and knowledge of AC spacers may not be applicable for this new type of apparatus.A novel design rule is proposed considering the effect of accumulated charge on the threshold of electric field strength being resistant to the superposed voltage.A surface charge accumulation simulation model is introduced,and the key parameters in the simulation model are *** addition,an experimental platform for a 100 kV spacer flashover test is *** flashover tests under superimposed voltage with opposing polarities are carried out,and the withstanding voltage of the spacer is ***,based on the proposed model,the threshold of the surface electric field strength(tangential component)on the DC spacer in SF_(6)/N_(2) mixed gases is *** a reliable insulation design of a DC GIS/GIL apparatus filled with 0.7 MPa SF_(6)/N_(2),the threshold of surface electric field strength on the DC spacer is 12 kV/*** insulation design rule can be referenced in the design of a high-voltage DC SF_(6)/N_(2)-filled GIS/GIL apparatus.

关键词： Charge accumulation DC spacer flashover voltage SF_(6)/N_(2) threshold of surface electric field strength

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An analysis of TinyML@ICCAD for implementing AI on low-power microprocessor

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Science China(Information Sciences) 2024年第4期67卷 343-344页

作者： Guoqing LI Jingwei zhang meng zhang Tuo LI Tinghuan CHEN Jun YANG Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Co. Ltd. School of Integrated Circuits Southeast University Shandong Inspur Artificial Intelligence Research Institute Co. Ltd. School of Science and Engineering The Chinese University of Hong Kong

Tiny machine learning(ML) is an important application area of artificial intelligence(AI), which focuses on deploying AI on small hardware platforms with constrained resources [1, 2]. The high-level TinyML contests at high-level conferences promote the development of TinyML areas, such as DAC-SDC [3] and TinyML@ICCAD [4].

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