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An application of 1D convolution and deep learning to remote sensing modelling of Secchi depth in the northern Adriatic Sea

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Big Earth Data 2024年第1期8卷 82-114页

作者： Antonia Ivanda LjiljanaŠerić dušanŽagar Krištof Oštir Faculty of Electrical Engineering Mechanical Engineering and Naval ArchitectureUniversity of SplitSplitCroatia Faculty of Civil and Geodetic Engineering University of LjubljanaLjubljanaSlovenia

This paper presents a novel approach for predicting the water quality indicator-Secchi disk depth(Z_(SD)).Z_(SD)indirectly reflects water clarity and serves as a proxy for other quality *** study utilizes Deep Neural Network(DNN)trained on satellite remote sensing and measured data from three sources:two datasets obtained from official agencies in Croatia and Slovenia,and one citizen science data source,all covering the northern coastal region of the Adriatic *** proposed model uses 1D Convolutional Neural Network(CNN)in the spectral dimension to predict Z_(SD).The model’s performance indicates a strong fit to the observed data,proving capability of 1D-CNN to capture changes in water *** the test dataset,the model achieved a high R-squared value of 0.890,a low root mean squared error(RMSE)of 0.023 and mean absolute error(MAE)of *** results demonstrate that employing a 1D-CNN in the spectral dimension of Sentinel-3 OLCI data is an effective approach for predicting water *** findings have significant implications for monitoring Z_(SD)in coastal *** integrating diverse data sources and leveraging advanced machine learning algorithms,a more accurate and comprehensive assessment of water quality can be achieved.

关键词： Secchi Sentinel-3 OLCI 1DCNN Adriatic sea

Manipulating Nb-doped SrFeO_(3−δ)with excellent performance for proton-conducting solid oxide fuel cells

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Journal of Advanced Ceramics 2024年第5期13卷 579-589页

作者： Hailu Dai Hongzhe du Samir Boulfrad Shoufu Yu Lei Bi Qinfang Zhang School of Materials Science and Engineering Yancheng Institute of TechnologyYancheng 224051China College of Science&Engineering Hamad Bin Khalifa UniversityDoha 34110Qatar School of Resource Environment and Safety Engineering University of South ChinaHengyang 421001China

Nb-doped SrFeO_(3−δ)(SFO)is used as a cathode in proton-conducting solid oxide fuel cells(H-SOFCs).First-principles calculations show that the SrFe0.9Nb0.1O_(3−δ)(SFNO)cathode has a lower energy barrier in the cathode reaction for H-SOFCs than the Nb-free SrFeO_(3−δ)*** experimental studies show that Nb doping substantially enhances the performance of the SrFeO_(3−δ)***,oxygen vacancies(VO)were introduced into SFNO using the microwave sintering method,further improving the performance of the SFNO *** mechanism behind the performance improvement owing to VO was revealed using first-principles calculations,with further optimization of the SFNO cathode achieved by developing a suitable wet chemical synthesis route to prepare nanosized SFNO *** method significantly reduces the grain size of SFNO compared with the conventional solid-state reaction method,although the solid-state reaction method is generally used for preparing Nb-containing *** a result of defect engineering and synthesis approaches,the SFNO cathode achieved an attractive fuel cell performance,attaining an output of 1764 mW·cm−2 at 700℃ and operating for more than 200 *** manipulation of Nb-doped SrFeO_(3−δ)can be seen as a“one stone,two birds”strategy,enhancing cathode performance while retaining good stability,thus providing an interesting approach for constructing high-performance cathodes for H-SOFCs.

关键词： SrFeO_(3−δ)-(SFO) cathode proton conductor solid oxide fuel cells(SOFCs)

A novel method for vibration signal transmission and attenuation analysis in complex planetary gearboxes

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Science China(Technological Sciences) 2024年第9期67卷 2939-2953页

作者： WEI ChaoHu CAO HongRui SHI JiangHai YANG Yang du MingGang National and Local Joint Engineering Research Center of Equipment Operation Safety and Intelligent Monitoring Xi’an Jiaotong UniversityXi’an 710049China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an 710049China China North Vehicle Research Institute Beijing 100072China

Planetary gearboxes play a crucial role in altering rotary speed and transmitting power in large machines like wind turbines and sophisticated vehicles. There are many nonlinear interfaces, such as splines, bearings, and gear pairs, in planetary gearboxes, and the resulting vibration signal transmission and attenuation mechanisms are still unknown. In this study, a novel method for quantitatively analyzing the transmission and attenuation of vibration signals is proposed. A multibody dynamic model of the planetary gearbox considering nonlinear gear meshing is presented and experimentally validated. To avoid the interference of foundation vibration on the transmission of the fault signal, the fault impact factor(FIF) is used to describe the intensity of the failure, which aligns well with the experimental signals. Based on the FIF, the vibration signal attenuation of nonlinear interfaces such as splines, bearings, and gear meshing interfaces is quantitatively evaluated. To clarify the transfer paths of fault vibration signals inside the gearbox, the transfer path area method(TPAM) based on FIF is proposed. According to the simulated results,the primary transfer paths of fault vibration signals within the gearbox have been identified, which is of great help in understanding the transmission and attenuation of vibration signals in planetary gearboxes.

关键词： planetary gearbox nonlinear interface fault mechanism vibration transmission vibration attenuation

Multi-Material Topology Optimization of 2D Structures Using Convolutional Neural Networks

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1919-1947页

作者： Jiaxiang Luo Weien Zhou Bingxiao du Daokui Li Wen Yao College of Aerospace Science and Engineering National University of Defense TechnologyChangsha410073China Defense Innovation Institute Chinese Academy of Military ScienceBeijing100071China Intelligent Game and Decision Laboratory Chinese Academy of Military ScienceBeijing100071China

In recent years,there has been significant research on the application of deep learning(DL)in topology optimization(TO)to accelerate structural ***,these methods have primarily focused on solving binary TO problems,and effective solutions for multi-material topology optimization(MMTO)which requires a lot of computing resources are still ***,this paper proposes the framework of multiphase topology optimization using deep learning to accelerate MMTO *** framework employs convolutional neural network(CNN)to construct a surrogate model for solving MMTO,and the obtained surrogate model can rapidly generate multi-material structure topologies in negligible time without any *** performance evaluation results show that the proposed method not only outputs multi-material topologies with clear material boundary but also reduces the calculation cost with high prediction ***,in order to find a more reasonable modeling method for MMTO,this paper studies the characteristics of surrogate modeling as regression task and classification *** the training of 297 models,our findings show that the regression task yields slightly better results than the classification task in most ***,The results indicate that the prediction accuracy is primarily influenced by factors such as the TO problem,material category,and data ***,factors such as the domain size and the material property have minimal impact on the accuracy.

关键词： Multi-material topology optimization convolutional neural networks deep learning finite element analysis

Impact crater recognition methods:A review

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Science China Earth Sciences 2024年第6期67卷 1719-1742页

作者： Dong CHEN Fan HU Liqiang ZHANG Yunzhao WU Jianli du Jiju PEETHAMBARAN College of Civil Engineering Nanjing Forestry UniversityNanjing 210037China Department of Geography State Key Laboratory of Remote Sensing ScienceFaculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Purple Mountain Observatory Chinese Academy of SciencesNanjing 210023China Key Laboratory of Space Object and Debris Observation Chinese Academy of SciencesNanjing 210023China Department of Mathematics and Computing Science Saint Mary’s UniversityHalifaxNS B3H 3C3Canada

Impact craters are formed due to the high-speed collisions between small to medium-sized celestial *** is the most significant driving force in the evolution of celestial bodies,and the impact craters provide crucial insights into the formation,evolution,and impact history of celestial *** this paper,we present a detailed review of the characteristics of impact craters,impact crater remote sensing data,recognition algorithms,and applications related to impact *** first provide a detailed description of the geometric texture,illumination,and morphology characteristics observed in remote sensing data of *** we summarize the remote sensing data and cataloging databases for the four terrestrial planets(i.e.,the Moon,Mars,Mercury,and Venus),as well as the impact craters on ***,we study the advancement achieved in the traditional methods,machine learning methods,and deep learning methods applied to the classification,segmentation,and recognition of impact ***,based on the analysis results,we discuss the existing challenges in impact crater recognition and suggest some ***,we explore the implementation of impact crater detection algorithms and provide a forward-looking perspective.

关键词： Terrestrial planets Deep space exploration Impact crater Impact crater recognition Deep learning

Resistance risk assessment of six pyrethroids and acephate toward the resistant adult tarnished plant bug,Lygus lineolaris

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Insect Science 2024年第3期31卷 792-802页

作者： Yuzhe du Shane Scheibener Yucheng Zhu Maribel Portilla Mingling Zhang USDA-ARS Southern Insect Management Research UnitStonevilleUSA USDA-ARS Pollinator Health in Southern Crop Ecosystem Research UnitStonevilleUSA

due to rapidly developed resistance,pest management relies less on pyrethroids to control economically damaging infestations of the tarnished plant bug(TPB),Lygus lineolaris(Palisot de Beauvois)in cotton fields of ***,pyrethroid resistance remains prevalent in TPB *** study assessed the resistance levels in adult TPB to six common pyrethroids and *** TBPs were collected from wild host plants in late October after harvest in the Mississippi Delta region of the United *** on LCso values,the field-resistant TPBs displayed higher resistance to permethrin,esfenvalerate,and bifenthrin(approximately 30 fold)and moderate resistance toα-cyhalothrin,β-cyfluthrin,5-cypermethrin,and acephate(approximately 15 fold).Further investigations showed that the inhibitors of three detoxification enzyme,triphenyl phosphate(TPP),diethyl maleate(DEM),and piperonyl butoxide(PBO)had synergistic effects on permethrin,γ-cyhalothrin,and bifenthrin in resistant ***,elevated esterase,GST,and P450 activities were significantly expressed in fieldresistant ***,GST and esterase were reduced after 48 h exposure to certain pyrethroids at LCso *** synergistic and biochemical assays consistently indicated that P450 and esterase were involved in pyrethroid detoxification in *** study provides valuable information for the continued use of pyrethroids and acephate in controlling TPBs in cotton fields in the Mississippi Delta region of the United States.

关键词： cytochrome P450-monooxygenases(P450) detoxification enzyme activities esterase Lygus lineolaris pyrethroids and organophosphate resistance tarnished plant bug

Maximizing the Differences Between a Monotone DR-Submodular Function and a Linear Function on the Integer Lattice

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Journal of the Operations Research Society of China 2024年第3期12卷 795-807页

作者： Zhen-Ning Zhang Dong-Lei du Ran Ma Dan Wu Department of Operations Research and Information Engineering Beijing University of TechnologyBeijing100124China Faculty of Management University of New BrunswickFrederictonNB E3B 9Y2Canada School of Management Engineering Qingdao University of TechnologyQingdao266525ShandongChina School of Mathematics and Statistics Henan University of Science and TechnologyLuoyang471023HenanChina

In this paper,we investigate the maximization of the differences between a nonnegative monotone diminishing return submodular(DR-submodular)function and a nonnegative linear function on the integer *** it is almost unapproximable for maximizing a submodular function without the condition of nonnegative,we provide weak(bifactor)approximation algorithms for this problem in two online settings,*** the unconstrained online model,we combine the ideas of single-threshold greedy,binary search and function scaling to give an efficient algorithm with a 1/2 weak approximation *** the online streaming model subject to a cardinality constraint,we provide a one-pass(3-√5)/2 weak approximation ratio streaming *** memory complexity is(k log k/ε),and the update time for per element is(log^(2)k/ε).

关键词： Submodular maximization DR-submodular Integer lattice Single-threshold greedy algorithm Streaming algorithm

Advancing space-based gravitational wave astronomy: Rapid parameter estimation via normalizing flows

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Science China(Physics,Mechanics & Astronomy) 2024年第3期67卷 20-33页

作者： Minghui du Bo Liang He Wang Peng Xu Ziren Luo Yueliang Wu Center for Gravitational Wave Experiment National Microgravity LaboratoryInstitute of MechanicsChinese Academy of SciencesBeijing 100190China Key Laboratory of Gravitational Wave Precision Measurement of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China Shanghai Institute of Optics and Fine Mechanics Chinese Academy of SciencesShanghai 201800China International Centre for Theoretical Physics Asia-Pacific University of Chinese Academy of SciencesBeijing 100049China Taiji Laboratory for Gravitational Wave Universe(Beijing/Hangzhou) University of Chinese Academy of SciencesBeijing 100049China Lanzhou Center of Theoretical Physics Lanzhou UniversityLanzhou 730000China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesHangzhou 310024China Institute of Theoretical Physics Chinese Academy of SciencesBeijing 100190China

Gravitational wave(GW) astronomy is witnessing a transformative shift from terrestrial to space-based detection, with missions like Taiji at the forefront. While the transition brings unprecedented opportunities for exploring massive black hole binaries(MBHBs), it also imposes complex challenges in data analysis, particularly in parameter estimation amidst confusion *** this gap, we utilize scalable normalizing flow models to achieve rapid and accurate inference within the Taiji environment. Innovatively, our approach simplifies the data's complexity, employs a transformation mapping to overcome the year-period time-dependent response function, and unveils additional multimodality in the arrival time parameter. Our method estimates MBHBs several orders of magnitude faster than conventional techniques, maintaining high accuracy even in complex backgrounds. These findings significantly enhance the efficiency of GW data analysis, paving the way for rapid detection and alerting systems and enriching our ability to explore the universe through space-based GW observation.

关键词： Taiji program gravitational wave detection parameter estimation machine learning

A Systematic Review of the Definition,Measurement,and Associated Factors of Pandemic Fatigue

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China CDC weekly 2024年第36期6卷 924-933,I0007页

作者： Ruohan Chen Qi Tan Bowen Su Shuqi Wang Zhanwei du WHO Collaborating Center for Infectious Disease Epidemiology and Control School of Public HealthLKS Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina Laboratory of Data Discovery for Health Limited Hong Kong Science ParkHong Kong Special Administrative RegionChina Nanjing Tech University Nanjing CityJiangsu ProvinceChina School of Cybersecurity Northwestern Polytechnical UniversityXi’an CityShaanxi ProvinceChina.

The rapid emergence and widespread transmission of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)have prompted governments worldwide to enact policies and measures to manage the virus’s *** interventions have substantially contributed to controlling disease ***,they have also significantly disrupted daily life,leading to increased public fatigue and resistance to sustained control measures,a phenomenon known as pandemic *** develop a comprehensive understanding of pandemic fatigue,this review systematically explores the concept and identifies quantitative indicators for measuring *** reviewed studies on pandemic fatigue across various countries,summarized the contributing factors,and analyzed its impact on personal protective *** findings indicate that the enforcement of health measures significantly influences the onset of pandemic fatigue,while individual perceptions of risk can negatively affect personal protective behaviors,creating a feedback loop with increasing *** results underscore the importance of considering the current severity of the pandemic and individual decisionmaking processes in the implementation of *** our understanding of pandemic fatigue is essential for developing effective policy responses in preparation for future potential epidemics.

关键词： fatigue protective prompt