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Ore Geology,H-O-C Isotopes and 40Ar-39Ar Dating of the Wutonggou Iron Deposit,Eastern tianshan,NW China:Implications for the Source,Timing,and Genesis of Hydrothermal Mineralization in a Sedimentary Iron Deposit

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Journal of Earth Science 2024年第4期35卷 1170-1185页

作者： Chun-Long Wang yi-tian Wang State Key Laboratory of Geological Processes and Mineral Resources Collaborative Innovation Center for Exploration of Strategic Mineral ResourcesSchool of Earth ResourcesChina University of GeosciencesWuhan430074China MNR Key Laboratory of Metallogeny and Mineral Assessment Institute of Mineral ResourcesChinese Academy of Geological SciencesBeijing100037China

The Wutonggou iron deposit is located in the well-known iron metallogenic belt in the eastern tianshan,NW China,and has been regarded as a sedimentary iron *** hydrothermal overprinting could play indispensable roles in the formation of high-grade iron ores in sedimentary iron deposits,previous studies mainly focused on sedimentary-related iron mineralization,while the nature and contribution of hydrothermal fluids are poorly ***,an integrated study of ore geology,H-O-C isotopes and^(40)Ar-^(39)Ar dating,is conducted on the Wutonggou deposit,in order to reveal the features,source,and timing of hydrothermal *** studied deposit includes two mining sections namely the Jianshan and ***δ^(18)O values of early magnetite from the Jianshan section range from+3.0‰to+5.8‰that nearly consistent with classic magmatic magnetite,while increase to 6.3‰-8.0‰in the late *** from the two sections shows comparable H-O isotopic compositions and identical fractionation trends,and is plotted in or periphery to the primary magmatic water *** from the two sections are broadly similar in carbon and oxygen isotopic compositions,and siderite from the Wutonggou section is plotted in the same ***,comparable stable isotopic compositions and evolution trends indicate similar magmatic fluids contributed hydrothermal iron mineralization in the two mining ***,water-rock interactions of varying degrees generated distinct mineralization styles in the Jianshan and Wutonggou sections,and caused the isotopic fractionation in late *** extracted from a hydrothermal siderite ore yielded a^(40)Ar-^(39)Ar plateau age of 299.5±2.0 Ma,indicates the timing of hydrothermal iron mineralization is corresponding to the emplacement of vicinity *** together,the hydrothermal mineralization in the Wutonggou iron deposit was the product of remobilization and upgrading of early sedimentary iron ores,a

关键词： iron deposits H-O-C isotopes 40Ar-39Ar dating sedimentary iron deposits Wutonggou iron deposit eastern tianshan

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Deformation of Rigid Conjugate Self-dual Galois Representations

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Acta Mathematica Sinica,English Series 2024年第7期40卷 1599-1644页

作者： yi Feng LIU yi Chao tian Liang XIAO Wei ZHANG Xin Wen ZHU Institute for Advanced Study in Mathematics Zhejiang UniversityHangzhou 310058P.R.China Morningside Center of Mathematics AMSSChinese Academy of SciencesBeijing 100190P.R.China New Cornerstone Lab Beijing International Center for Mathematical ResearchPeking Ui Beijing 100871P.R.China Department of Mathematics Massachusetts Institute of TechnologyCambridge MA 02139United States Department of Mathematics Stanford UniversityStanfordCA 94305United States

In this article,we study deformations of conjugate self-dual Galois *** study is ***,we prove an R=T type theorem for a conjugate self-dual Galois representation with coefficients in a finite field,satisfying a certain property called ***,we study the rigidity property for the family of residue Galois representations attached to a symmetric power of an elliptic curve,as well as to a regular algebraic conjugate self-dual cuspidal representation.

关键词： Galois deformation rigid conjugate self-dual Galois representations

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TSC prediction and dynamic control of BOF steelmaking with state-of-the-art machine learning and deep learning methods

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Journal of Iron and Steel Research International 2024年第1期31卷 174-194页

作者： tian-yi Xie Cai-dong Zhang Quan-lin Zhou Zhi-qiang tian Shuai Liu Han-jie Guo Material Technology Research Institute Hesteel GroupShijiazhuang050023HebeiChina Tangsteel Company Hesteel GroupTangshan063611HebeiChina School of Artificial Intelligence Beijing Technology and Business UniversityBeijing100048China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China

Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC)test,including temperature of molten steel(TSC-Temp),carbon content(TSC-C)and phosphorus content(TSC-P),which made prepa-ration for eliminating the TSC *** maximize the prediction accuracy of the proposed approach,various models with different inputs were implemented and compared,and the best models were applied to the production process of a Hesteel Group steelmaking plant in China in the *** number of tabular features(hot metal information,scrap,additives,blowing practices,and preset values)was expanded,and time series(off-gas profiles and blowing practice curves)that could reflect the entire steelmaking process were introduced as ***,the latest machine learning models(LightGBM,CatBoost,TabNet,and NODE)were used to make predictions with tabular features,and the best coefficient of determination R^(2)values obtained for TSC-P,TSC-C and TSC-Temp predictions were 0.435(LightGBM),0.857(Cat-Boost)and 0.678(LightGBM),respectively,which were higher than those of classic models(backpropagation and support vector machine).Then,making predictions was performed by using SOTA time series regression models(SCINet,DLinear,Informer,and MLSTM-FCN)with original time series,SOTA image regression models(NesT,CaiT,ResNeXt,and GoogLeNet)with resized time series,and the proposed Concatenate-Model and Parallel-Model with both tabular features and time *** optimization and comparisons,it was finally determined that the Concatenate-Model with MLSTM-FCN,SCINet and Informer as feature extractors performed the best,and its R^(2)values for predicting TSC-P,TSC-C and TSC-Temp reached 0.470,0.858 and 0.710,*** field test accuracies for TSC-P,TSC-C and TSC-Temp were 0.459,0.850 and 0.685,respectively.A related importance analysis was carri

关键词： BOF steelmaking In-blow prediction TSC test Machine learning Deep learning Field application

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Metal–Organic Framework‑Based Photodetectors

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Nano-Micro Letters 2024年第11期16卷 675-703页

作者： Jin‑Biao Zhang yi‑Bo tian Zhi‑Gang Gu Jian Zhang State Key Laboratory of Structural Chemistry Structure of MatterFujian Institute of ResearchChinese Academy of SciencesFuzhouFujian 350002People’s Republic of China College of Chemistry and Materials Science Fujian Nornal UniversityFuzhou 350007FujianPeople’s Republic of China Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou 350108FujianPeople’s Republic of China University of Chinese Academy of Science Beijing 100049People’s Republic of China

The unique and interesting physical and chemical properties of metal–organic framework(MOF)materials have recently attracted extensive attention in a new generation of photoelectric *** this review,we summarized and discussed the research progress on MOF-based *** methods of preparing MOF-based photodetectors and various types of MOF single crystals and thin film as well as MOF composites are introduced in ***,the photodetectors applications for X-ray,ultraviolet and infrared light,biological detectors,and circularly polarized light photodetectors are ***,summaries and challenges are provided for this important research field.

关键词： Metal-organic frameworks Semiconductor Photodetectors

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Effects of loneliness and isolation on cardiovascular diseases:a two sample Mendelian Randomization Study

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Journal of Geriatric Cardiology 2024年第3期21卷 340-348页

作者： Jia-yin CAI Xin WANG Cong-yi ZHENG Xue CAO Zhen HU Run-Qing GU yi-Xin tian Ye tian Lan SHAO Lin-Feng ZHANG Zeng-Wu WANG Division of Prevention and Community Health National Center for Cardiovascular DiseaseNational Clinical Research Center of Cardiovascular DiseaseState Key Laboratory of Cardiovascular DiseaseFuwai HospitalPeking Union Medical College&Chinese Academy of Medical SciencesBeijingChina

BACKGROUND Loneliness and isolation are associated with multiple cardiovascular diseases(CVDs),but there is a lack of research on whether they were causally *** conducted a Mendelian Randomization(MR)study to explore causal relationships between loneliness and isolation and multiple *** Single nucleotide polymorphisms associated with loneliness and isolation were identified from a genome-wide association study(GWAS)of 455,364 individuals of European ancestry in the IEU GWAS *** data for 15 CVDs were also obtained from the IEU GWAS *** used three MR methods including inverse variance weighting,MR-Egger,and weighted median estimation to assess the causal effect of exposure on ***'s Q test and MR-Egger intercept test were used to evaluate the heterogeneity and *** MR analysis showed that loneliness and isolation were significantly associated with essential hypertension(OR=1.07,95%CI:1.03-1.12),atherosclerotic heart disease(OR=1.04;95%CI:1.02-1.06),myocardial infarction(OR=1.02;95%CI:1-1.04)and angina(OR=1.04;95%CI=1.02-1.06).No heterogeneity and pleiotropy effects were found in this *** Causal relationship of loneliness and isolation with CVDs were found in this study.

关键词： diseases cardiovascular angina

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An alternative approach to improve the compatibility of PCE in cement paste blend with coal gangue powder

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Waste Disposal and Sustainable Energy 2024年第1期6卷 139-150页

作者： Zonglin Xie Yuxuan Li Dahui Sun yi tian Jinyuan Hu Qiang Yuan Zheng Chen School of Civil Engineering Central South UniversityChangshaChina China Railway NO.9 Group CO. LTDShenyangChina National Engineering Research Center for High-Speed Railway Construction Technology ChangshaChina Guangxi Key Laboratory of Disaster Prevention and Engineering Safety Guangxi UniversityNanningChina

Coal gangue(CG)is an environmental waste that faces an urgent demand for disposal in *** utilization of CG in construction materials has broad application prospects and gained increasing ***,the poor compatibility of polycarboxylate superplasticizer(PCE)with CG powder hinders its efficiency in a wide range of ***,this paper attempts to improve the compatibility of PCE with CG powder in cement paste based on the regulation of aggregation and the adsorption behavior of *** light scattering(DLS)and fluorescence spectroscopy tests were carried out to understand the improved *** results indicated that the addition of CG powder increases the ionic strengths of the cement liquid phase,which makes PCE tend to aggregate at a lower concentration compared with no CG powder ***(CH_(3)COO)_(2)Cu is beneficial for enhancing the workability of cement paste by reducing PCE aggregation while maintaining the compressive strength of cement ***,(CH_(3)COO)_(2)Cu extra addition can be regarded as an effective and sustainable way to improve the workability of cement paste with CG powder.

关键词： Coal gangue powder Polycarboxylate superplasticizer Compatibility Aggregation

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Evolution exploration and structure prediction of Keggin-type group IVB metal-oxo clusters

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Chinese Chemical Letters 2024年第5期35卷 487-492页

作者： Run-Han Li tian-yi Dang Wei Guan Jiang Liu Ya-Qian Lan Zhong-Min Su School of Chemistry South China Normal UniversityGuangzhou 510006China Institute of Functional Material Chemistry Faculty of ChemistryNortheast Normal UniversityChangchun 130024China Institute of Theoretical Chemistry Jilin UniversityChangchun 130023China

The fascinating chemical structure and broad application prospect of Keggin-type polyoxometalates(POMs)have attracted many chemists to explore and discover *** the traditional Keggin,larger metal atomic radius,higher metal coordinated numbers,lower metal valence states and other features allow the group IVB metal-based Keggin(IVB-Keggin)more space and unknown in terms of structure and ***,density functional theory(DFT)calculations were performed to explore the influences including cores,shells,caps,and terminal ligands,et *** IVB-Keggin,and analyze the possibility of novel structure *** the perspective of multi-layer onion-like clusters,molecular energy level,host-guest interaction energy,surface charge and covalent bond polarity can be further adjusted to achieve the oriented design of functional *** insights are expected to provide theoretical support for experimental synthesis,opening a new perspective to understand the growth of Keggin.

关键词： Keggin Metal-oxo clusters Group IVB Onion pattern DFT

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Machine learning for carbonate formation drilling: Mud loss prediction using seismic attributes and mud loss records

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Petroleum Science 2024年第2期21卷 1241-1256页

作者： Hui-Wen Pang Han-Qing Wang yi-tian Xiao Yan Jin Yun-Hu Lu Yong-Dong Fan Zhen Nie National Key Laboratory of Petroleum Resources and Engineering China University of Petroleum(Beijing)Beijing102249China College of Science China University of Petroleum-BeijingBeijing102249China Petroleum Exploration and Production Research Institute SINOPECBeijing102206China College of Petroleum Engineering China University of Petroleum-BeijingBeijing102249China Research Institute of Petroleum Exploration and Development CNPCBeijing100083China

Due to the complexity and variability of carbonate formation leakage zones, lost circulation prediction and control is one of the major challenges of carbonate drilling. It raises well-control risks and production expenses. This research utilizes the H oilfield as an example, employs seismic features to analyze mud loss prediction, and produces a complete set of pre-drilling mud loss prediction solutions. Firstly, 16seismic attributes are calculated based on the post-stack seismic data, and the mud loss rate per unit footage is specified. The sample set is constructed by extracting each attribute from the seismic trace surrounding 15 typical wells, with a ratio of 8:2 between the training set and the test set. With the calibration results for mud loss rate per unit footage, the nonlinear mapping relationship between seismic attributes and mud loss rate per unit size is established using the mixed density network ***, the influence of the number of sub-Gausses and the uncertainty coefficient on the model's prediction is evaluated. Finally, the model is used in conjunction with downhole drilling conditions to assess the risk of mud loss in various layers and along the wellbore trajectory. The study demonstrates that the mean relative errors of the model for training data and test data are 6.9% and 7.5%, respectively, and that R2is 90% and 88%, respectively, for training data and test data. The accuracy and efficacy of mud loss prediction may be greatly enhanced by combining 16 seismic attributes with the mud loss rate per unit footage and applying machine learning methods. The mud loss prediction model based on the MDN model can not only predict the mud loss rate but also objectively evaluate the prediction based on the quality of the data and the model.

关键词： Lost circulation Risk prediction Machine learning Seismic attributes Mud loss records

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High-entropy oxide-supported platinum nanoparticles for efficient hydrogen evolution reaction

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Rare Metals 2024年第4期43卷 1537-1546页

作者： Ming-Yu Fan Jia-Jun Wang Jun Zhao Hong Zhang tian-yi Ma Xiao-Peng Han Wen-Bin Hu School of Materials Science and Engineering Tianjin Key Laboratory of Composite and Functional Materials Key Laboratory of Advanced Ceramics and Machining TechnologyTianjin UniversityTianjin300350China Joint School of National University of Singapore and tianjin University International Campus of Tianjin UniversityFuzhou350207China School of Science RMIT UniversityMelbourneVIC3000Australia

High-entropy oxides(HEOs)are a new class of single-phase structures with unique electronic and catalytic properties;therefore,it is worthwhile to explore their applications in *** this study,a Pt/(FeCoNiCrAl)_(3)O_(4)nanohybrid using HEO as a support was developed as an efficient catalyst for the hydrogen evolution reaction(HER).Pt/(FeCoNiCrAl)_(3)O_(4)exhibited high HER activity with a low overpotential of 22 mV at10 mA·cm^(-2),outperforming other binary,ternary,and quaternary *** HER activity of Pt/(FeCoNiCrAl)_(3)O_(4)was higher than that of a commercial Pt/C with a significantly lower Pt *** catalyst exhibited good activity and long-term stability(60 h)in an electrolytic water-splitting *** good activity can be attributed to the fact that the introduction of Pt effectively facilitates electronic interactions between Pt and the *** addition,the HEO substrate was more favorable for dispersing Pt particles,optimizing the electrochemical specific surface area,and significantly reducing the charge resistance of the *** study extends the application of HEOs in electrocatalysis and demonstrates the promising prospects of HEOs as supports for electrocatalysts.

关键词： High-entropy oxides Hydrogen evolution reaction Nanohybrid Water electrolysis

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Developing and validating a predictive model of delivering large-forgestational-age infants among women with gestational diabetes mellitus

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World Journal of Diabetes 2024年第6期15卷 1242-1253页

作者： yi-tian Zhu Lan-Lan Xiang Ya-Jun Chen tian-ying Zhong Jun-Jun Wang Yu Zeng Department of Clinical Laboratory Jinling Clinical Medical College of Nanjing Medical UniversityNanjing 210002Jiangsu ProvinceChina Department of Clinical Laboratory Women’s Hospital of Nanjing Medical UniversityNanjing Women and Children’s Healthcare HospitalNanjing 210003Jiangsu ProvinceChina

BACKGROUND The birth of large-for-gestational-age(LGA)infants is associated with many shortterm adverse pregnancy *** has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus(GDM)is significantly higher than that born to healthy pregnant ***,traditional methods for the diagnosis of LGA have ***,this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA *** To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM,and provide strategies for the effective prevention and timely intervention of *** The multivariable prediction model was developed by carrying out the following ***,the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses,for which the P value was<***,Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations,and the optimal combination factors were se-lected by choosing lambda 1se as the *** final predictors were deter-mined by multiple backward stepwise logistic regression analysis,in which only the independent variables were associated with LGA risk,with a P value<***,a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve,calibration curve and decision curve *** After using a multistep screening method,we establish a predictive *** risk factors for delivering an LGA infant were identified(P<0.01),including weight gain during pregnancy,parity,triglyceride-glucose index,free tetraiodothyronine level,abdominal circumference,alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational *** nomogram’s prediction ability was supported by the area under the curve(0.703,0.709,and 0.699 f

关键词： Large-for-gestational-age Gestational diabetes mellitus Predictive model Nomogram Triglyceride-glucose index

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