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Prediction of three-dimensional ocean temperature in the South China Sea based on time series gridded data and a dynamic spatiotemporal graph neural network

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Acta Oceanologica Sinica 2024年第7期43卷 26-39页

作者： Feng Nan Zhuolin Li Jie yu Suixiang shi Xinrong Wu Lingyu Xu Department of Computer Engineering and Science Shanghai UniversityShanghai 200444China Key Laboratory of Digital Ocean National Marine Data and Information ServiceTianjin 300171China

Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related ***,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean *** graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among *** this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior *** and spatial dependencies in the time series were then captured using temporal and graph *** also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid *** this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea *** compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.

关键词： dynamic associations three-dimensional ocean temperature prediction graph neural network time series gridded data

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Insights into Nano-and Micro-Structured Scaffolds for Advanced Electrochemical Energy Storage

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Nano-Micro Letters 2024年第7期16卷 187-230页

作者： Jiajia Qiu yu Duan Shaoyuan Li Huaping Zhao Wenhui Ma Weidong shi Yong Lei Fachgebiet Angewandte Nanophysik Institut Für Physik and IMN MacroNanoTechnische Universit.t Ilmenau98693 IlmenauGermany Key Laboratory of Complex Nonferrous Metal Resources Clean Utilization Faculty of Metallurgical and Energy EngineeringKunming University of Science and TechnologyKunming 650093People’s Republic of China School of Chemistry and Chemical Engineering Jiangsu UniversityZhenjiang 212013People’s Republic of China School of Science and Technology Pu’er UniversityPu’er 665000People’s Republic of China

Adopting a nano-and micro-structuring approach to fully unleashing the genuine potential of electrode active material benefits in-depth understandings and research progress toward higher energy density electrochemical energy stor-age devices at all technology readiness *** to various challenging issues,especially limited stability,nano-and micro-structured(NMS)electrodes undergo fast electrochemical performance *** emerging NMS scaffold design is a pivotal aspect of many electrodes as it endows them with both robustness and electrochemical performance enhancement,even though it only occupies comple-mentary and facilitating components for the main ***,extensive efforts are urgently needed toward optimizing the stereoscopic geometrical design of NMS scaffolds to minimize the volume ratio and maximize their functionality to fulfill the ever-increasing dependency and desire for energy power source *** review will aim at highlighting these NMS scaffold design strategies,summariz-ing their corresponding strengths and challenges,and thereby outlining the potential solutions to resolve these challenges,design principles,and key perspectives for future research in this ***,this review will be one of the earliest reviews from this viewpoint.

关键词： Nano-and micro-structured Interconnected porous Scaffolds Electrode design Electrochemical energy storage

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Biotoxicity dynamic change and key toxic organics identification of coal chemical wastewater along a novel full-scale treatment process

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Journal of Environmental Sciences 2024年第4期138卷 277-287页

作者： Weiwei Ma Xiaoqi Zhang Hongjun Han Xueqing shi Qiaoping Kong Tong yu Fei Zhao School of Environmental and Municipal Engineering Qingdao University of TechnologyQingdao 266520China State Key Laboratory of Urban Water Resource and Environment Harbin Institute of TechnologyHarbin 150090China

It is particularly important to comprehensively assess the biotoxicity variation of industrial wastewater along the treatment process for ensuring the water environment ***,intensive studies on the biotoxicity reduction of industrial wastewater are still *** this study,the toxic organics removal and biotoxicity reduction of coal chemical wastewater(CCW)along a novel full-scale treatment process based on the pretreatment process-anaerobic process-biological enhanced(BE)process-anoxic/oxic(A/O)process-advanced treatment process was *** process performed great removal efficiency of COD,total phenol,NH_(4)^(+)-N and total *** the biotoxicity variation along the treatment units was analyzed from the perspective of acute biotoxicity,genotixicity and oxidative *** results indicated that the effluent of pretreatment process presented relatively high acute biotoxicity to Tetrahymena *** the acute biotoxicity was significantly reduced in BE-A/O *** the genotoxicity and oxidative damage to Tetrahymena thermophila were significantly decreased after advanced *** polar organics in CCW were identified as the main biotoxicity *** were positively correlated with acute biotoxicity,while the nitrogenous heterocyclic compounds and polycyclic aromatic hydrocarbons were positively correlated with *** the biotoxicity was effectively reduced in the novel full-scale treatment process,the effluent still performed potential biotoxicity,which need to be further explored in order to reduce environmental risk.

关键词： Acute biotoxicity Genotoxicity Oxidative damage Toxic organics Coal chemical wastewater Novel full-scale treatment process

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Therapeutic effects of Lingguizhugan decoction in a rat model of high-fat diet-induced insulin resistance

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World Journal of Diabetes 2024年第6期15卷 1291-1298页

作者： Xiao-Ming Liu shi-Qing yuan Ying Ning shi-Jia Nie Xu-Qiong Wang Hong-Yi Jia xiu-Li Zheng Department of Basic Medicine School of Basic Medicine Chengdu University of Traditional Chinese MedicineChengdu 611137Sichuan ProvinceChina Department of Clinical Medicine Chengdu University of Traditional Chinese MedicineChengdu 610072Sichuan ProvinceChina

BACKGROUND Lingguizhugan(LGZG)decoction is a widely used classic Chinese medicine formula that was recently shown to improve high-fat diet(HFD)-induced insulin resistance(IR)in animal *** To assess the therapeutic effect of LGZG decoction on HFD-induced IR and explore the potential underlying *** To establish an IR rat model,a 12-wk HFD was administered,followed by a 4-wk treatment with *** determination of IR status was achieved through the use of biochemical tests and oral glucose tolerance *** a targeted metabolomics platform to analyze changes in serum metabolites,quantitative real-time PCR(qRT-PCR)was used to assess the gene expression of the ribosomal protein S6 kinase beta 1(S6K1).RESULTS In IR rats,LGZG decreased body weight and indices of hepatic *** effectively controlled blood glucose and food intake while protecting islet *** analysis revealed significant differences between the HFD and HFDLGZG *** intervention reduced branched-chain amino acid *** of IR-related metabolites such as tryptophan,alanine,taurine,and asparagine decreased *** may be linked to amino acids due to the contemporaneous increase in S6K1 expression,as shown by *** Our study strongly suggests that LGZG decoction reduces HFD-induced *** may activate S6K1 via metabolic *** findings lay the groundwork for the potential of LGZG as an IR treatment.

关键词： Lingguizhugan decoction High-fat diet-induced insulin resistance Amino acid metabolism S6K1

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Simulation study of the performance of the Very Large Area gamma-ray Space Telescope

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Nuclear Science and Techniques 2024年第9期35卷 1-17页

作者： Xu Pan Wei Jiang Chuan yue shi-Jun Lei yu-Xin Cui Qiang yuan Key Laboratory of Dark Matter and Space Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023China School of Astronomy and Space Science University of Science and Technology of ChinaHefei 230026China

The Very Large Area gamma-ray Space Telescope(VLAST)is a mission concept proposed to detect gamma-ray photons through both Compton scattering and electron–positron pair production mechanisms,thus enabling the detection of photons with energies ranging from MeV to *** project aims to conduct a comprehensive survey of the gamma-ray sky from a low-Earth orbit using an anti-coincidence detector,a tracker detector that also serves as a low-energy calorimeter,and a high-energy imaging *** developed a Monte Carlo simulation application of the detector using the GEANT4 toolkit to evaluate the instrument performance,including the effective area,angular resolution,and energy resolution,and explored specific optimizations of the detector *** simulation-based analysis indicates that the current design of the VLAST is physically feasible,with an acceptance above 10 m^(2)sr which is four times larger than that of the Fermi-LAT,an energy resolution better than 2%at 10 GeV,and an angular resolution better than 0.2◦at 10 *** VLAST project promises to make significant contributions to the field of gamma-ray astronomy and enhance our understanding of the cosmos.

关键词： Space astronomy Gamma-ray telescope Calorimeter Monte Carlo simulation

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High-resolution recognition of FOAM modes via an improved EfficientNet V2 based convolutional neural network

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Frontiers of physics 2024年第3期19卷 175-183页

作者： Youzhi shi Zuhai Ma Hongyu Chen Yougang Ke yu Chen Xinxing Zhou International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Institute of Microscale OptoelectronicsShenzhen UniversityShenzhen 518060China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Synergetic Innovation Center for Quantum Effects and ApplicationsSchool of Physics and ElectronicsHunan Normal UniversityChangsha 410081China Key Laboratory of Hunan Province on Information Photonics and Freespace Optical Communications School of Information Science and EngineeringHunan Institute of Science and TechnologyYueyang 414006China

Vortex beam with fractional orbital angular momentum (FOAM) is the excellent candidate for improving the capacity of free-space optical (FSO) communication system due to its infinite modes. Therefore, the recognition of FOAM modes with higher resolution is always of great concern. In this work, through an improved EfficientNetV2 based convolutional neural network (CNN), we experimentally achieve the implementation of the recognition of FOAM modes with a resolution as high as 0.001. To the best of our knowledge, it is the first time this high resolution has been achieved. Under the strong atmospheric turbulence (AT) (C_(n)^(2)=10^(-15)m^(-2/3)), the recognition accuracy of FOAM modes at 0.1 and 0.01 resolution with our model is up to 99.12% and 92.24% for a long transmission distance of 2000 m. Even for the resolution at 0.001, the recognition accuracy can still remain at 78.77%. This work provides an effective method for the recognition of FOAM modes, which may largely improve the channel capacity of the free-space optical communication.

关键词： OAM free-space optical communication deep learning convolutional neural network

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Phase separation of GRP7 facilitated by FERONIAmediated phosphorylation inhibits mRNA translation to modulate plant temperature resilience

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Molecular Plant 2024年第3期17卷 460-477页

作者： Fan Xu Long Wang Yingbin Li Junfeng shi Dorothee Staiger Feng yu state Key Laboratory of Chemo/Biosensing and Chemometrics College of Biologyand Hunan Key Laboratory of Plant Functional Genomics and Developmental RegulationHunanUniversityChangsha 410082P.R.China State Key Laboratory of Hybrid Rice Hunan Agricultural Biotechnology Research InstituteHunan Academy of Agricultural SciencesChangsha 410125P.R.China RNA Biology and Molecular Physiology Faculty of BiologyBielefeld University33615 BielefeldGermany

Changes in ambient temperature profoundly affect plant growth and ***,the molecu-larbasis of plant acclimation to temperature fluctuation is of great *** this study,we discovered that GLYCINE-RICH RNA-BINDING PROTEIN 7(GRP7)contributes to cold and heat tolerance in Arabidopsis *** found that exposure to a warm temperature rapidly induces GRP7 condensates in planta,which can be reversed by transfer to a lower *** biology and biochemical assays revealed that GRP7 undergoes liquid-liquid phase separation(LLPS)in vivo and in *** of GRP7 in the cyto-plasm contributes to the formation of stress granules that recruit RNA,along with the translation machinery component eukaryotic initiation factor 4E1(elF4E1)and the mRNA chaperones COLD SHOCK PROTEIN 1(CSP1)and CSP3,to inhibit ***,natural variations in GRP7 affecting the residue phos-phorylated by the receptorkinase FERONIA alter its capacity to undergo LLPS and correlate with the adap-tation of some Arabidopsis accessions to a widertemperature *** together,ourfindings illustrate the role of translational control mediated by GRP7 LLPS to confer plants with temperature resilience.

关键词： fluctuating temperature glycine-rich RNA-binding protein phase separation cold shock proteins translation

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Overview of enhancing biological treatment of coal chemical wastewater:New strategies and future directions

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Journal of Environmental Sciences 2024年第1期135卷 506-520页

Coal chemical wastewater(CCW)is a type of refractory industrial wastewater,and its treatment has become the main bottleneck restricting the sustainable development of novel coal chemical *** treatment is considered as an economical,effective and environmentally friendly technology for CCW ***,conventional biological process is difficult to achieve the efficient removal of refractory organics because of CCW with the characteristics of composition complexity and high ***,seeking the novel enhancement strategy appears to be a favorable solution for enhancing biological treatment efficiency of *** review focuses on presenting a comprehensive picture about the exogenous enhancement strategies for CCW biological *** performance and potential application of exogenous enhancement strategies,including co-metabolic substrate enhancement,biofilm filler enhancement,adsorption material enhancement and conductive mediator enhancement,were ***,the enhancing mechanisms of different strategies were comprehensively discussed from a biological ***,the prospects of enhancement strategies based on the engineering performance,economic cost and environmental impact(3E)evaluation were *** novel enhancement strategy based on“low carbon emissions”,“resource recycling”and“water environment security”in the context of carbon neutrality was *** together,this review provides technical reference and new direction to facilitate the regulation and optimization of typical industrial wastewater biological treatment.

关键词： Coal chemical wastewater Biological treatment Exogenous enhancement Refractory organics 3E evaluation

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Intelligent geochemical interpretation of mass chromatograms:Based on convolution neural network

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Petroleum Science 2024年第2期21卷 752-764页

作者： Kai-Ming Su Jun-Gang Lu Jian yu Zi-Xing Lu shi-Jia Chen Hubei Key Laboratory of Petroleum Geochemistry and Environment Wuhan430100HubeiChina College of Resources and Environment Yangtze UniversityWuhan430100HubeiChina School of Geoscience and Technology Southwest Petroleum UniversityChengdu610500SichuanChina Changqing Oilfield Company PetroChinaXi'an710021ShaanxiChina

Gas chromatography-mass spectrometry(GC-MS)is an extremely important analytical technique that is widely used in organic *** is the only approach to capture biomarker features of organic matter and provides the key evidence for oil-source correlation and thermal maturity ***,the conventional way of processing and interpreting the mass chromatogram is both timeconsuming and labor-intensive,which increases the research cost and restrains extensive applications of this *** overcome this limitation,a correlation model is developed based on the convolution neural network(CNN)to link the mass chromatogram and biomarker features of samples from the Triassic Yanchang Formation,Ordos Basin,*** this way,the mass chromatogram can be automatically *** research first performs dimensionality reduction for 15 biomarker parameters via the factor analysis and then quantifies the biomarker features using two indexes(*** and PMI)that represent the organic matter thermal maturity and parent material type,***,training,interpretation,and validation are performed multiple times using different CNN models to optimize the model structure and hyper-parameter setting,with the mass chromatogram used as the input and the obtained MI and PMI values for supervision(label).The optimized model presents high accuracy in automatically interpreting the mass chromatogram,with R2values typically above 0.85 and0.80 for the thermal maturity and parent material interpretation results,*** significance of this research is twofold:(i)developing an efficient technique for geochemical research;(ii)more importantly,demonstrating the potential of artificial intelligence in organic geochemistry and providing vital references for future related studies.

关键词： Organic geochemistry Biomarker Mass chromatographic analysis Automated interpretation Convolution neural network Machine learning

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Reviewing electrochemical stability of ionic liquids-/deep eutectic solvents-based electrolytes in lithium-ion,lithium-metal and post-lithium-ion batteries for green and safe energy

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Green Energy & Environment 2024年第6期9卷 966-991页

作者： yu Chen Shuzi Liu Zixin Bi Zheng Li Fengyi Zhou Ruifen shi Tiancheng Mu Department of Chemistry and Material Science Langfang Normal UniversityNO.100 Aimin West RoadLangfangHebei065000China Department of Chemistry Renmin University of ChinNO.59 Zhongguancun StreetHaidian DistrictBeijing100872China

Sustainable energy is the key issue for the environment protection,human activity and economic *** liquids(ILs)and deep eutectic solvents(DESs)are dogmatically regarded as green and sustainable electrolytes in lithium-ion,lithium-metal(e.g.,lithium-sulphur,lithium-oxygen)and post-lithium-ion(e.g.,sodium-ion,magnesium-ion,and aluminum-ion)*** electrochemical stability of ILs/DESs is one of the prerequisites for green,sustainable and safe energy;while easy electrochemical decomposition of ILs/DESs would be contradictory to the concept of green chemistry by adding the cost,releasing volatile/hazardous by-products and hindering the ***,(1)are ILs/DESs-based electrolytes really electrochemically stable when they are not used in batteries?(2)are ILs/DESs-based electrolytes really electrochemically stable in real batteries?(3)how to design ILs/DESs-based electrolytes with high electrochemical stability for batteries to achieve sustainability and green development?Up to now,there is no summary on this topic,to the best of our ***,we review the effect of chemical structure and non-structural factors on the electrochemical stability of ILs/DESs in simulated *** importantly,electrochemical stability of ILs/DESs in real lithium-ion,lithium-metal and post-lithium-ion batteries is concluded and ***,the strategies to improve the electrochemical stability of ILs/DESs in lithium-ion,lithium-metal and post-lithium-ion batteries are *** review would provide a guide to design ILs/DESs with high electrochemical stability for lithium-ion,lithium-metal and postlithium-ion batteries to achieve sustainable and green energy.

关键词： Green solvents Decomposition Sustainable chemistry Lithium-oxygen batteries Lithium-sulphur batteries Sodium-ion batteries

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