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Science China(Information Sciences) 2025年第2期68卷 151-169页

作者： Fenglan SUN Zhonghua XU Wei ZHU ■ KURTHS Key Lab of Intelligent Analysis and Decision on Complex Systems School of ScienceChongqing University of Posts and Telecommunications Key Lab of Intelligent Air-Ground cooperative Control for Universities in Chongqing College of AutomationChongqing University of Posts and Telecommunications Department of Complexity Science Potsdam Institute for Climate Impact Research institute of Physics Humboldt University of Berlin

In this paper, an event-triggered time-varying formation tracking control for a class of second-order nonlinear multiagent systems(MAS) operating within a constrained region is investigated. To mitigate the negative effects of external unknown disturbance, a novel disturbance observer with performance guarantees is proposed, enabling precise disturbance *** the artificial potential field(APF) method, a repulsive potential function is introduced to prevent inter-agent collisions as well as collisions with environmental obstacles. To reduce continuous communication and frequent system updates, a sliding mode technique is incorporated into the formation tracking controller, utilizing an event-triggered mechanism. The controller is also applicable to the formation control of MAS in switching-constrained regions. The achievement of the specified timevarying geometric formation is rigorously demonstrated through the Lyapunov framework. Numerical simulations are presented to validate the effectiveness of the theoretical results.

关键词： formation tracking control region constraints repulsive potential function event-triggered mechanism

Effect of preprocessing on performances of machine learning-based mineral composition analysis on gas hydrate sediments, Ulleung Basin, East Sea

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Petroleum Science 2025年第1期22卷 151-162页

作者： Hongkeun Jin Ju Young Park Sun Young Park Byeong-Kook Son Baehyun Min Kyungbook Lee Department of Geoenvironmental Sciences Kongju National University Tunnel & Underground Facility Division ESCO Consultant & Engineers Company Yellow Sea institute of Geoenvironmental Sciences Petroleum and Marine Research Division Korea Institute of Geoscience and Mineral Resources Department of climate and Energy Systems Engineering Ewha Womans University Center for climate/Environment Change Prediction Research Ewha Womans University

Gas hydrate(GH) is an unconventional resource estimated at 1000-120,000 trillion *** on GH is ongoing to determine its geological and flow characteristics for commercial production. After two large-scale drilling expeditions to study the GH-bearing zone in the Ulleung Basin, the mineral composition of 488 sediment samples was analyzed using X-ray diffraction(XRD). Because the analysis is costly and dependent on experts, a machine learning model was developed to predict the mineral composition using XRD intensity profiles as input data. However, the model's performance was limited because of improper preprocessing of the intensity profile. Because preprocessing was applied to each feature, the intensity trend was not preserved even though this factor is the most important when analyzing mineral composition. In this study, the profile was preprocessed for each sample using minmax scaling because relative intensity is critical for mineral analysis. For 49 test data among the 488data, the convolutional neural network(CNN) model improved the average absolute error and coefficient of determination by 41% and 46%, respectively, than those of CNN model with feature-based preprocessing. This study confirms that combining preprocessing for each sample with CNN is the most efficient approach for analyzing XRD data. The developed model can be used for the compositional analysis of sediment samples from the Ulleung Basin and the Korea Plateau. In addition, the overall procedure can be applied to any XRD data of sediments worldwide.

关键词： Sample-based preprocessing X-ray diffraction (XRD) Machine learning Mineral composition Gas hydrate (GH) Ulleung basin

Impact of ocean data assimilation on the seasonal forecast of the 2014/15 marine heatwave in the Northeast Pacific Ocean

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 24-31页

作者： Tiantian Tang Jiaying He Huihang Sun Jingjia Luo institute for climate and Application Research(ICAR)/Key Laboratory of Meteorological Disaster Nanjing University of Information Science and TechnologyNanjingChina

A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 *** study employed two assimilation schemes based on the global climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine *** sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep *** latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging *** excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the *** improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean *** results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.

关键词： Seasonal forecast Ocean data assimilation Marine heatwave Subsurface temperature

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Enhancing microbial superoxide generation and conversion to hydroxyl radicals for enhanced bioremediation using iron-binding ligands

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Journal of Environmental Sciences 2025年第1期147卷 597-606页

作者： Yuhan Wang Xue Ning Jinsong Liang Aijie Wang Jiuhui Qu School of Civil and Environmental Engineering Harbin Institute of TechnologyShenzhen 518055China SFI MaREI Centre for Energy Climate and MarineEnvironmental Research InstituteUniversity College CorkCorkIreland Center for Water and Ecology Tsinghua UniversityBeijing 100084China

Harnessing bacteria for superoxide production in bioremediation holds immense promise,yet its practical application is hindered by slow production rates and the relatively weak redox potential of *** study delves into a cost-effective approach to amplify superoxide production using an Arthrobacter strain,a prevalent soil bacterial *** research reveals that introducing a carbon source along with specific iron-binding ligands,including deferoxamine(DFO),diethylenetriamine pentaacetate(DTPA),citrate,and oxalate,robustly augments microbial superoxide ***,our findings suggest that these iron-binding ligands play a pivotal role in converting superoxide into hydroxyl radicals by modulating the electron transfer rate between Fe(Ⅲ)/Fe(Ⅱ)and ***,among the tested ligands,only DTPA emerges as a potent promoter of this conversion process when complexed with Fe(Ⅲ).We identify an optimal Fe(Ⅲ)to DTPA ratio of approximately 1:1 for enhancing hydroxyl radical production within the Arthrobacter *** research underscores the efficacy of simultaneously introducing carbon sources and DTPA in facilitating superoxide production and its subsequent conversion to hydroxyl radicals,significantly elevating bioremediation ***,our study reveals that DTPA augments superoxide production in cultures of diverse soils,with various soil microorganisms beyond Arthrobacter identified as contributors to superoxide *** emphasizes the universal applicability of DTPA across multiple bacterial *** conclusion,our study introduces a promising methodology for enhancing microbial superoxide production and its conversion into hydroxyl *** findings hold substantial implications for the deployment of microbial reactive oxygen species in bioremediation,offering innovative solutions for addressing environmental contamination challenges.

关键词： Superoxide Hydroxyl radical Iron-binding ligand Bioremediation DTPA

Fabrication and fracture behaviors of the continuous brittle fiber reinforced tungsten composites fabricated via field-assisted sintering technology

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Tungsten 2025年第1期7卷 172-182页

作者： Rui Shu Yi-Ran Mao Jan W. Coenen Alexis Terra Stephan Sch?nen Johann Riesch Christian Linsmeier Christoph Broeckmann Juelich Research Center Institute of Energy and Climate Research Plasma Physics (IEK-4) Partner in the Trilateral Euregio Cluster institute of Materials Applications in Mechanical Engineering (IWM) RWTH Aachen University Department of Nuclear Engineering & Engineering Physics University of Wisconsin Madison Central institute of Engineering Electronics and Analytics Engineering and Technology (ZEA-1) Juelich Research Center Max Planck institute for Plasma Physics institute of Materials Applications in Mechanical Engineering IWM RWTH Aachen University

Tungsten（W） is a promising candidate material for the plasma-facing components in future fusion ***,it has issues regarding the intrinsic brittleness as well as operational *** fiber reinforced tungsten（W_f/W） composites overcome these issues by using extrinsic toughening *** to neutron irradiation and high-temperature recrystallization during fusion operation,the ductility of the fibers may degrade over a long period of ***,it is necessary to investigate the fracture behavior of W_f/W composites with brittle *** the present work,the tungsten fibers were embrittled by ***,the continuous brittle W_f/W composite with yttrium oxide（Y2O3） interface was fabricated by the field-assisted sintering technology *** microstructure of the prepared W_f/W composites was *** fracture behavior and toughening mechanisms were discussed in detail based on the experimental results of 3-point bending tests and the corresponding finite element *** composites show a pseudo-ductile fracture *** are hindered and deflected by the de-bonded fiber-matrix *** extrinsic toughening mechanisms of interface de-bonding,crack bridging,and fiber pull-out are *** indicates the reinforcement concept still works even though all components in the W_f/W are brittle.

关键词： Field-assisted sintering technology (FAST) Fracture behavior Interface Numerical simulation Wf/W composites

The Enhancing Effect of the East Asian Subtropical Westerly Jet on Summer Extreme High-Temperature Events over Central-Eastern China Since the Late 1990s

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Advances in Atmospheric Sciences 2025年第3期42卷 453-466页

作者： Chujie GAO Yuyu NIU Gen LI Shanlei SUN Bo LU Chaofan LI Bei XU Jinglong HUANG Xiubao SUN College of Oceanography&Key Laboratory of Marine Hazards Forecasting Ministry of Natural ResourcesHohai UniversityNanjing 210098China Key Laboratory of Meteorological Disaster Ministry of Education(KLME)&Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Tropical Oceanography South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhou 510301China Laboratory for climate Studies and CMA-NJU Joint Laboratory for climate Prediction Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China Xiong’an institute of Meteorological Artificial Intellegence Xiong'an 071708China Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth and Planetary Sciences University of the Chinese Academy of SciencesBeijing 100049China College of Intelligent Science and Control Engineering Jinling Institute of TechnologyNanjing 211169China

The increase in frequency and intensity of Extreme High-temperature Events(EHEs)over Central-Eastern China(CEC)in recent decades has severely impacted social development and *** observation and reanalysis datasets,this study explores the effect of the East Asian subtropical westerly jet stream(EAJ)on the CEC EHEs for the summers spanning 1979–*** its general relative location to the right side of the upper-level jet stream exit region,CEC would theoretically suffer more EHEs with a stronger and northwardly-shifted EAJ in summer due to the likelihood of abnormal subsidence induced by the ***,such an EAJ–EHE connection has been unstable over the past four decades but has displayed an evident interdecadal *** the late 1990s,the interannual variation of the EAJ was manifested mainly by its meridional displacement in the northeastern part of East Asia;thus,the atmospheric responses were essentially located to the east of CEC,exerting less of an influence on the CEC ***,since the late 1990s,the EAJ variation has featured an intensity change in its center over the northwest portion of the CEC,which has resulted in a westward shift in atmospheric responses to cover the CEC ***,the EAJ could potentially affect the summer CEC EHEs during 2000–*** findings offer support for an in-depth understanding of the formation mechanisms of extreme weather/climate events of this nature and thus provide a scientific reference for seasonal climate predictions.

关键词： summer extreme high-temperature events East Asian subtropical jet atmospheric circulation central-eastern China interdecadal change

Long-term trends and response of wet ammonia deposition to changes in anthropogenic emissions in the Pearl River delta of China

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Journal of Environmental Sciences 2025年第5期151卷 373-386页

作者： Mingyue Li Lyumeng Ye Ming Chang Weihua Chen Shuidi He Buqing Zhong Xuemei Wang Guangdong-Hongkong-Macao Joint Laboratory of Collaborative Innovation for Environmental Quality Institute for Environmental and Climate ResearchJinan UniversityGuangzhou 511443China South China institute of Environmental Sciences The Ministry of Ecology and Environment of PRCGuangzhou 510530China Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems South China Botanical GardenChinese Academy of SciencesGuangzhou 510650China

The Pearl River Delta(PRD)region has been identified as a significant hotspot of wet ammonium ***,the absence of long-term monitoring data in the area hinders the comprehension of the historical trends and changes in wet NH_(4)^(+)-N deposition in response to emissions,which interferes with the ability to make effective *** study has analyzed the long-term trends of wet NH_(4)^(+)-N deposition flux and has quantified the effect of anthropogenic emissions and meteorological factors at a typical urban site and a typical forest site in the PRD region from 2009 to *** revealed a significant decreasing trend in wet NH_(4)^(+)-N flux in both the typical urban and forest areas of the PRD region,at-6.2%/year(p<0.001)and-3.3%/year(p<0.001),*** emissions are thought to have contributed 47%–57%of the wet NH_(4)^(+)-N deposition trend over the past 12 years compared to meteorological *** conditions dominated the interannual fluctuations in wet NH_(4)^(+)-N deposition with an absolute contribution of 46%–52%,while anthropogenic emissions change alone explained 10%–31%.NH_(3)emissions have the greatest impact on the urban area among anthropogenic emission factors,while SO_(2)emissions have the greatest impact on the forest ***,precipitation was identified as the primary meteorological driver for both *** findings also imply that the benefits of NH_(3)emissions reductions might not immediately emerge due to interference from weather-related factors.

关键词： Long-term trends Inter-annual variation Wet ammonium deposition Anthropogenic emission change Meteorological condition The Pearl River Delta region

Numerical prediction of oceanic mesoscale circulation and satellite altimetry data assimilation in the Western Pacific

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Science China Earth Sciences 2025年第3期68卷 909-927页

作者： Zhijin LI Jianfang FEI Renhe ZHANG Xingliang JIANG Wenlong MA Xiaoping CHENG Lei LIU Guihua WANG Changlin CHEN Department of Atmospheric and Oceanic Sciences Institute of Atmospheric Sciences Fudan University Shanghai Key Laboratory of Ocean-land-atmosphere Boundary Dynamics and climate Change College of Meteorology and Oceanology National University of Defense Technology

Oceanic mesoscale circulations, primarily manifesting as eddies, typically span around 100 km horizontally and persist for about a month. These circulations represent the main component of oceanic kinetic energy and are referred to as the“weather” of the ocean. Forecasting efforts, focused on periods from a day to a month, target these mesoscale *** in eddy-resolving models, observing systems such as Argo floats and satellite altimeters, and data assimilation techniques have enabled systems like HYCOM in the United States and Mercator-Ocean in Europe to predict these features effectively. To further enhance mesoscale forecasting, the Pacific Regional Ocean Forecast System(RPOFS) was developed for the pan-western Pacific(100°E–178°E, 20°S–50°N). Covering the dynamic Kuroshio and Kuroshio Extension regions, RPOFS features a 3 km horizontal grid and 67 vertical levels, with a multi-scale three-dimensional variational data assimilation(MS-3DVAR) scheme implemented. This system assimilates data from various sources, including satellite sea surface height and temperature, as well as subsurface profiles. In particular, an enhanced altimeter data assimilation methodology allows explicitly constraining both barotropic and baroclinic components of sea surface height. RPOFS demonstrates reliable forecasting of mesoscale circulations, with five-day forecasts accurately predicting eddies larger than 150 km and capturing features of the Kuroshio large meander. Forecasting errors are comparable to or smaller than those of HYCOM and Mercator-Ocean systems.

关键词： Western Pacific Ocean Ocean model Mesoscale eddy Numerical prediction Multiscale data assimilation Satellite altimetry

A Machine Learning-Based Observational Constraint Correction Method for Seasonal Precipitation Prediction

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Advances in Atmospheric Sciences 2025年第1期42卷 36-52页

作者： Bofei ZHANG Haipeng YU Zeyong HU Ping YUE Zunye TANG Hongyu LUO Guantian WANG Shanling CHENG Key Laboratory of Cryospheric Science and Frozen Soil Engineering Nagqu Plateau Climate and Environment Observation and Research Station of Tibet Autonomous RegionNorthwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China University of the Chinese Academy of Sciences Beijing 100049China Key Open Laboratory of Arid climate Change and Disaster Reduction of CMA Key Laboratory of Arid Climate Change and Reducing Disaster of Gansu ProvinceInstitute of Arid MeteorologyChina Meteorological AdministrationLanzhou 730000China School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China

Seasonal precipitation has always been a key focus of climate *** a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal ***,solving a nonlinear problem through linear regression is significantly *** study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National climate Center climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in *** model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached *** PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,*** observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.

关键词： observational constraint LightGBM seasonal prediction summer precipitation machine learning

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Improving the Seasonal Forecast of Summer Precipitation in Southeastern China Using a CycleGAN-based Deep Learning Bias Correction Method

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Advances in Atmospheric Sciences 2025年第1期42卷 26-35页

作者： Song YANG Fenghua LING Jing-Jia LUO Lei BAI institute of climate Application Research(ICAR)/School of Future Technology/CIC-FEMD/KLME/ILCEC Nanjing University of Information Science and TechnologyNanjing 210044China Shanghai Artificial Intelligence Laboratory Shanghai 200232China

Accurate seasonal precipitation forecasts,especially for extreme events,are crucial to preventing meteorological hazards and their potential impacts on national development,social activity,and ***,the intensity of summer precipitation is often largely underestimated in many current dynamic *** study uses a deep learning method called Cycle-Consistent Generative Adversarial Networks(CycleGAN)to improve the seasonal forecasts for June-JulyAugust precipitation in southeastern China by the Nanjing University of Information Science and Technology climate Forecast System(NUIST-CFS 1.0).The results suggest that the CycleGAN-based model significantly improves the accuracy in predicting the spatiotemporal distribution of summer precipitation compared to the traditional quantile mapping(QM)*** the unpaired bias-correction model,we can also obtain advanced forecasts of the frequency,intensity,and duration of extreme precipitation events over the dynamic model *** study expands the potential applications of deep learning models toward improving seasonal precipitation forecasts.

关键词： bias correction CycleGAN QM NUIST-CFS 1.0 extreme precipitation

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