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Organic matter determines the exchange of nutrients at sediment-water interface in coastal bays

Acta Oceanologica Sinica 2025年第1期44卷 72-85页

作者： Jiasen Zhong Ehui Tan Chunwei Fu Guiyi Ma Yongkai Chang Zhixiong Huang Jingchao Yin Fengying Li Jianzhong Su Min Xu Zhenzhen Zheng Jian’an Liu Yu Han Shuh-Ji Kao State Key Laboratory of Marine Resources Utilization in the South China Sea School of Ecology and Environment and School of Marine Science and EngineeringHainan UniversityHaikou 570228China Collaborative Innovation Center of Marine Science and Technology Hainan UniversityHaikou 570228China

The exchange of inorganic nutrients at the coastal sediment-water interface(SWI)plays a crucial role in regulating the nutrient budget in overlying *** related studies mainly focus on the mid-to high-latitude regions,leaving a significant gap in the quantitative assessment of nutrient exchange and environmental controls at the SWI in lowlatitude coastal *** quantitatively assess the exchange of inorganic nutrients at the SWI in three tropical bays(Dongzhai Harbor,Xiaohai Lagoon,Qinglan Harbor).Sediments act as a source of ammonium,phosphate,and silicate,but for nitrate,sediments can be both a source and sink,although with substantial spatial and temporal variations in their *** organic matter is a critical regulator for the fluxes of inorganic nutrients at the *** sedimentary nutrients input with high N/P molar ratio will alter the nutrient stoichiometry to mitigate the nitrogen limitation in coastal ***,the internal sediment release in these tropical bays plays a relative weak role in contributing to the nutrient addition in comparison with the other external nutrient sources including riverine input,submarine groundwater discharge,and atmospheric *** to the global compilation on SWI nutrient fluxes,we propose that water column primary production and external inputs to interpret the variation in exchange and fluxes of nutrients at the SWI in different *** a conceptual understanding of these chain biogeochemical processes involving external nutrient input,primary production,particulate organic matter settling,and the accumulation and release of inorganic nutrients in sediments will be helpful for the scientific-based pollution prevent and control in coastal waters.

关键词： tropical bay sediment-water interface nutrient exchange labile organic matter source/sink

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Joint Retrieval of PM_(2.5) Concentration and Aerosol Optical Depth over China Using Multi-Task Learning on FY-4A AGRI

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Advances in Atmospheric Sciences 2025年第1期42卷 94-110页

作者： Bo LI Disong FU Ling YANG Xuehua FAN Dazhi YANG Hongrong SHI Xiang’ao XIA Electronic Engineering College Chengdu University of Information TechnologyChengdu 610225China Tianjin Meteorological Radar Research Trial Center Tianjin Meteorological BureauTianjin 300074China Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Research Centre on Meteorological Observation Engineering Technology China Meteorological AdministrationBeijing 100081China Key Laboratory of Atmospheric Environment and Extreme Meteorology Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001China University of Chinese Academy of Sciences Beijing 100049China

Aerosol optical depth(AOD)and fine particulate matter with a diameter of less than or equal to 2.5μm(PM_(2.5))play crucial roles in air quality,human health,and climate ***,the complex correlation of AOD–PM_(2.5)and the limitations of existing algorithms pose a significant challenge in realizing the accurate joint retrieval of these two parameters at the same *** this point,a multi-task learning(MTL)model,which enables the joint retrieval of PM_(2.5)concentration and AOD,is proposed and applied on the top-of-the-atmosphere reflectance data gathered by the Fengyun-4A Advanced Geosynchronous Radiation Imager(FY-4A AGRI),and compared to that of two single-task learning models—namely,Random Forest(RF)and Deep Neural Network(DNN).Specifically,MTL achieves a coefficient of determination(R^(2))of 0.88 and a root-mean-square error(RMSE)of 0.10 in AOD *** comparison to RF,the R^(2)increases by 0.04,the RMSE decreases by 0.02,and the percentage of retrieval results falling within the expected error range(Within-EE)rises by 5.55%.The R^(2)and RMSE of PM_(2.5)retrieval by MTL are 0.84 and 13.76μg m~(-3)*** with RF,the R^(2)increases by 0.06,the RMSE decreases by 4.55μg m~(-3),and the Within-EE increases by 7.28%.Additionally,compared to DNN,MTL shows an increase of 0.01 in R^(2)and a decrease of 0.02 in RMSE in AOD retrieval,with a corresponding increase of 2.89%in *** PM_(2.5)retrieval,MTL exhibits an increase of 0.05 in R^(2),a decrease of 1.76μg m~(-3)in RMSE,and an increase of 6.83%in *** evaluation suggests that MTL is able to provide simultaneously improved AOD and PM_(2.5)retrievals,demonstrating a significant advantage in efficiently capturing the spatial distribution of PM_(2.5)concentration and AOD.

关键词： AOD PM_(2.5) FY-4A multi-task learning joint retrieval

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Artificial sensory neurons and their applications

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Journal of Semiconductors 2025年第1期46卷 108-128页

作者： Jiale Shao Hongwei Ying Peihong Cheng Lingxiang Hu Xianhua Wei Zongxiao Li Huanming Lu Zhizhen Ye Fei Zhuge Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingbo 315201China School of Electronic and Information Engineering Ningbo University of TechnologyNingbo 315211China State Key Laboratory of Environment-friendly Energy Materials Southwest University of Science and TechnologyMianyang 621010China Institute of Wenzhou Zhejiang UniversityWenzhou 325006China State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou 310027China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesShanghai 200072China

With the rapid development of artificial intelligence(AI)technology,the demand for high-performance and energyefficient computing is increasingly *** limitations of the traditional von Neumann computing architecture have prompted researchers to explore neuromorphic computing as a *** computing mimics the working principles of the human brain,characterized by high efficiency,low energy consumption,and strong fault tolerance,providing a hardware foundation for the development of new generation AI *** neurons and synapses are the two core components of neuromorphic computing *** perception is a crucial aspect of neuromorphic computing,where artificial sensory neurons play an irreplaceable role thus becoming a frontier and hot topic of *** work reviews recent advances in artificial sensory neurons and their ***,biological sensory neurons are briefly ***,different types of artificial neurons,such as transistor neurons and memristive neurons,are discussed in detail,focusing on their device structures and working ***,the research progress of artificial sensory neurons and their applications in artificial perception systems is systematically elaborated,covering various sensory types,including vision,touch,hearing,taste,and ***,challenges faced by artificial sensory neurons at both device and system levels are summarized.

关键词： artificial sensory neurons artificial perception systems neuromorphic computing artificial intelligence

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ICCG:low-cost and efficient consistency with adaptive synchronization for metadata replication

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Frontiers of Computer Science 2025年第1期19卷 53-70页

作者： Chenhao ZHANG Liang WANG Jing SHANG Zhiwen XIAO Limin XIAO Meng HAN Bing WEI Runnan SHEN Jinquan WANG State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China School of Cyberspace Security Hainan UniversityHaikou 570228China China Mobile Information Technology Center Beijing 100033China

The rapid growth in the storage scale of wide-area distributed file systems (DFS) calls for fast and scalable metadata management. Metadata replication is the widely used technique for improving the performance and scalability of metadata management. Because of the POSIX requirement of file systems, many existing metadata management techniques utilize a costly design for the sake of metadata consistency, leading to unacceptable performance overhead. We propose a new metadata consistency maintenance method (ICCG), which includes an incremental consistency guaranteed directory tree synchronization (ICGDT) and a causal consistency guaranteed replica index synchronization (CCGRI), to ensure system performance without sacrificing metadata consistency. ICGDT uses a flexible consistency scheme based on the state of files and directories maintained through the conflict state tree to provide an incremental consistency for metadata, which satisfies both metadata consistency and performance requirements. CCGRI ensures low latency and consistent access to data by establishing a causal consistency for replica indexes through multi-version extent trees and logical time. Experimental results demonstrate the effectiveness of our methods. Compared with the strong consistency policies widely used in modern DFSes, our methods significantly improve the system performance. For example, in file creation, ICCG can improve the performance of directory tree operations by at least 36.4 times.

关键词： metadata management metadata replication consistency directory tree replica index

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Assessing GNSS hydrological monitoring capability across different climatic settings in China

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Geodesy and Geodynamics 2025年第2期16卷 147-157页

作者： Qingwen Huang Lilong Liu Chaolong Yao Si Xiong Liangke Huang Tengxu Zhang College of Geomatics and Geoinformation Guilin University of TechnologyGuilin 541004China Guangxi Key Laboratory of Spatial Information and Geomatics Guilin 541004China College of Natural Resources and Environment South China Agricultural UniversityGuangzhou 510640China National Precise Gravity Measurement Facility Huazhong University of Science and TechnologyWuhan 430074China School of Resources and Environment Science and Engineering Hubei University of Science and TechnologyXianning 437100China

Vertical position changes of ground-based Global Navigation Satellite System(GNsS)stations have been used to study regional terrestrial water storage(TwS)***,the feasibility is still unclear in many areas due to diverse local *** study aims to evaluate the capability of GNsS vertical displacements in monitoring hydrological variations in four climate settings over Chinese *** spatial and temporal variations of hydrological load-induced(HYDL)vertical displacements at 208 GNSS sites during 2011-2020 were analyzed by comparing with Gravity Recovery and Climate Experiment(GRACE)/GRACE Follow-On(GFO)and Global Land Data Assimilation System(GLDAS)derived TWS *** results indicate that GNsS vertical positions show different capabilities in capturing seasonal and non-seasonal hydrological dynamics in different climate *** the four climatic settings,the subtropical monsoon climate(SMC)region,with the largest deformation fluctuation(the regional mean root mean square(RMS)is 7.97 mm),has the highest regional mean HYDL-GRACE and HYDL-GLDAS anti-correlation coefficients(CCs)of-0.47 and-0.45 at the seasonal scale,*** the individual GNSS site,the number of the sites with CC<-0.4O between HYDL and GRACE/GLDASderived TWS changes accounts for 55.1%and 55.1%(SMC),13.0%and 7.4%(temperate monsoon climate,TMC),6.7%and 13.3%(temperate continental climate,TCC),32.3%and 38.7%(plateau climate,PC),*** the non-seasonal term,although the proportion with CC<-0.40 in each climate type decreases mainly due to the influence of local geodynamic and human activities,especially in the SMC and PC regions,GNSS site vertical deformations still show good capability in monitoring hydrological *** results provide valuable information for better application of GNSS to hydrology.

关键词： GNSS vertical displacement Hydrological loading GRACE GLDAS Climate setting

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A novel photocatalytic mechanism of volatile organic compounds degradation on BaTiO_(3)under visible light:Photo-electrons transfer from photocatalyst to pollutant

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Chinese Chemical Letters 2025年第3期36卷 182-187页

作者： Teng Wang Jiachun Cao Juan Li Didi Li Zhimin Ao Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health Guangdong Key Laboratory of Environmental Catalysis and Health Risk ControlKey Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of EducationInstitute of Environmental Health and Pollution ControlSchool of Environmental Science and EngineeringGuangdong University of TechnologyGuangzhou 510006China Advanced Interdisciplinary Institute of Environment and Ecology Guangdong Provincial Key Laboratory of Wastewater Information Analysis and Early WarningBeijing Normal UniversityZhuhai 519087China

Wide bandgap semiconductors are typically activated under ultraviolet(UV)light irradiation for volatile organic compounds(VOCs)***,our previous study discovered that certain VOCs can interact with some wide bandgap semiconductors,formatting an intermediate bandgap between the VOCs and the conduction band of wide bandgap semiconductor,thus inducing visible light activation of the system,and photo-generated electrons are excited by visible light and transferred from the VOCs to the conduction band of *** this work,BaTiO_(3),traditionally is not active under visible light irradiation,however showed degradation rates of 100%and 20%for styrene and toluene under visible light,*** functional theory(DFT)calculations indicate that the adsorption of styrene or toluene on the BaTiO_(3)surface reduces its bandgap from 2.93 eV to 1.36 eV and 2.26 eV,*** intermediate bandgap in this system is primarily formed by the valence band of BaTiO_(3)and the VOCs,and indicating that photo-generated electrons directly transfer from BaTiO_(3)to the VOCs under visible light,inducing degradation reactions of VOCs,i.e.,this work discovered a new transfer pathway of photo-electrons direct from the valence band of BaTiO_(3)to VOCs,while photo-electrons are from VOCs to the conductive band of wide-bandgap semiconductors in our previous work.

关键词： Volatile organic compounds Photocatalytic Degradation Wide-bandgap semiconductors Density functional theory Degradation mechanism

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Prospects on mangrove knowledge services in the smart era:From plant atlas to knowledge graphs

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Science China Earth Sciences 2025年第1期68卷 111-127页

作者： Zhi-Wei HOU Wenlong JING Cheng-Zhi QIN Ji YANG Qing XIA Xiaoling YIN Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangdong Academy of SciencesGuangzhou510070China Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) Guangzhou511458China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing100049China School of Traffic&Transportation Engineering Changsha University of Science and TechnologyChangsha410114China

Mangroves are crucial to the ecological security of the Earth and human *** management,conservation,and restoration are of great importance and necessitate the support of spatio-temporal information and multidisciplinary knowledge such as biology and *** knowledge services such as plant atlas provide illustrated textual knowledge of ***,this kind of service is oriented to information retrieval and is incapable of effectively mining and utilizing fragmented knowledge from multi-source heterogeneous data,facing the problem of“massive data,rare knowledge”.Knowledge graphs are capable of extracting,organizing,and fusing the knowledge contained in massive data into semantic networks that can be understood and computed by *** provide a solution for the realization of intelligent knowledge *** on the urgent need for mangrove knowledge acquisition,formal representation,and intelligent services,this paper proposes a research prospect on mangrove knowledge graphs and knowledge *** first analyze the similarities and differences between various domain-specific concepts of *** this basis,we define the mangrove knowledge graph as a large-scale knowledge base that integrates multi-disciplinary knowledge and spatio-temporal information with mangrove ecosystems as the ***,we propose a research framework for mangrove knowledge services that can realize the transformation from multi-modal data to intelligent knowledge services,including multiple research levels such as ubiquitous data sensing and aggregation,knowledge organization and graph construction,and intelligent mangrove knowledge ***,the methods and workflow for constructing mangrove knowledge graphs are ***,we discuss the challenges and possible future directions of mangrove knowledge services in the smart era,including the construction of a mangrove knowledge system that integrates the domain-specific charac

关键词： Mangrove Tupu Knowledge graph Multi-modal Knowledge service

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Changes in factor profiles deriving from photochemical losses of volatile organic compounds:Insight from daytime and nighttime positive matrix factorization ana

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Journal of environmental Sciences 2025年第5期151卷 627-639页

作者： Baoshuang Liu Tao Yang Sicong Kang Fuquan Wang Haixu Zhang Man Xu Wei Wang Jinrui Bai Shaojie Song Qili Dai Yinchang Feng Philip K.Hopke State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control&Tianjin Key Laboratory of Urban Transport Emission Research College of Environmental Science and EngineeringNankai UniversityTianjin 300350China CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research Tianjin 300350China Beijing Make Environment Science&Technology Co. Ltd.Beijing 100083China Shijiazhuang Environmental Prediction Center Shijiazhuang 050022China Department of Public Health Sciences University of Rochester School of Medicine and DentistryRochesterNY 14642USA Institute for a Sustainable Environment Clarkson UniversityPotsdamNY 13699USA

Substantial effects of photochemical reaction losses of volatile organic compounds(VOCs)on factor profiles can be investigated by comparing the differences between daytime and nighttime dispersion-normalized VOC data resolved *** speciated VOC data measured in Shijiazhuang,China from May to September 2021 were used to conduct *** mean VOC concentration in the daytime and at nighttime were 32.8 and 36.0 ppbv,*** and aromatics concentrations in the daytime(12.9 and 3.08 ppbv)were lower than nighttime(15.5 and 3.63 ppbv),whereas that of alkenes showed the opposite *** concentration differences between daytime and nighttime for alkynes and halogenated hydrocarbonswere uniformly *** reactivities of the dominant species in factor profiles for gasoline emissions,natural gas and diesel vehicles,and liquefied petroleum gas were relatively low and their profiles were less affected by photochemical *** losses produced a substantial impact on the profiles of solvent use,petrochemical industry emissions,combustion sources,and biogenic emissions where the dominant species in these factor profiles had high *** the profile of biogenic emissions was substantially affected by photochemical loss of isoprene,the low emissions at nighttime also had an important impact on its *** losses of highly active VOC species substantially reduced their concentrations in apportioned factor *** study results were consistent with the analytical results obtained through initial concentration estimation,suggesting that the initial concentration estimation could be the most effective currently availablemethod for the source analyses of active VOCs although with uncertainty.

关键词： Volatile organic compounds Dispersion normalization Photochemical loss Factor profile Positive matrix factorization

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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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Machine learning models coupled with ionic fragment σ-profiles to predict ammonia solubility in ionic liquids

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Green Chemical engineering 2025年第02期 223-232页

作者： Kaikai Li Yuesong Zhu Sensen Shi Yongzheng Song Haiyan Jiang Xiaochun Zhang Shaojuan Zeng Xiangping Zhang Beijing Key Laboratory of Ionic Liquids Clean Process CAS Key Laboratory of Green Process and EngineeringState Key Laboratory of Mesoscience and EngineeringInstitute of Process EngineeringChinese Academy of Sciences College of Chemical and Engineering University of Chinese Academy of Sciences Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and Technology College of Chemical Engineering and Environment China University of Petroleum

Emitting NH3into the atmosphere leads to significant air pollution, while NH3itself serves as an essential component for fertilizers and refrigerants in industry. Thus, recovering and reusing NH3is highly valuable. Ionic liquids（ILs） have shown great potential for NH3capture, where the accurate prediction of solubility is a critical point for selecting ILs and designing a separation process. This work combined the Ionic Fragment Contribution（IFC） strategy with machine learning（ML） to develop four models（IFC-ML） to predict NH3solubility in ILs. A dataset containing 785 solubility data points, covering 10 cations and 10 anions, was collected. From this dataset,the S1–S6 descriptors based on the IFC method were used as inputs for the ML models, together with temperature（T） and pressure（P）. Among the models, the IFC-GBR model was recommended for predicting NH3solubility in ILs due to its higher coefficient of determination（R2） of 0.9945 and lower mean squared error（MSE） of 0.0003than the others. Additionally, in comparison with previous conductor-like screening model for real solvents（COSMO-RS） and extreme learning machine（ELM） methods, the IFC-GBR（gradient boosting regressor） method showed a more accurate prediction of the NH3solubility in ILs over a wider range of temperatures and pressures,providing additional chemical insights into IL-NH3system that cations played a more important role for NH3solubility. These results highlighted the developed IFC-GBR model offered valuable insights for helping guide the process design of absorbing NH3through IL-based technology.

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