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Composition， Distribution and Constraint Factors of Fe Isotope(δFe) in the Surface Soils of the Tibetan Plateau

Journal of Earth Science 2024年

作者： Ting wei Zhiwen Dong Eric Parteli Xiaoli Liu Shichang Kang Yaping shao State Key Laboratory of Cryosphere Sciences， Northwest Institute of Eco-Environment and Resources， Chinese Academy of Sciences Hubei Key Laboratory of Regional Ecology and Environmental Change， School of Geography and Information Engineering， China University of Geosciences Faculty of Physics， University of Duisburg-Essen Institute for Geophysics and Meteorology， University of Cologne

Iron isotopes， represented by δ56Fe， serve as valuable tools for constraining the surface iron processes and as potent tracers for studying the biogeochemical cycle of iron. Nevertheless， our comprehension of iron isotopes in the land surface processes of the Tibetan Plateau （TP） remains limited. In this study， we present the results of iron isotopic composition (δ56Fe) in the surface soils of the TP， encompassing both glacial and non-glacial regions characterized by rugged and flat topographies. Our findings reveal that soil δ56Fe values ranged from -0.01±0.05‰ to 0.14±0.01‰， with the highest values observed in eastern locations （0.14‰） and the lowest appeared in the northeast （-0.1‰）. On a global scale， the δ56Fe values observed in Tibetan soils exhibited relatively small variability compared to reservoirs marked by significant iron isotope fractionation. By contrast， the range of TP soils measured here was slightly larger than that of the Chinese Loess. Furthermore， we discerned noticeable spatial variations in δ56Fe across the large-scale region of TP， indicating a gradual increase trend from the northeast to the south and from the west to the east. These regional disparities in δ56Fe likely arise from a combination of constraining factors， including differences in mineralogy， lithological variations， organic matter content， and variations in chemical weathering intensity. This study is pivotal in advancing our understanding of land surface iron isotope δ56Fe dynamics and its role in the biogeochemical cycle within the TP region.

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DNA vaccine prime and replicating vaccinia vaccine boost induce robust humoral and cellular immune responses against MERS-CoV in mice

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Virologica Sinica 2024年第3期39卷 490-500页

作者： Xiuli Shen Shuhui Wang Yanling Hao Yuyu Fu Li Ren Dan Li Wenqi Tang jing Li Ran Chen Meiling Zhu Shuo Wang Ying Liu Yiming shao National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases National Center for AIDS/STD Control and PreventionChinese Center for Disease Control and PreventionBeijing 102206China Changping Laboratory Yard 28Science Park RoadChangping DistrictBeijing 102206China State Key Laboratory for Diagnosis and Treatment of Infectious Diseases National Clinical Research Center for Infectious DiseasesCollaborative Innovation Center for Diagnosis and Treatment of Infectious DiseasesThe First Affiliated HospitalSchool of MedicineZhejiang UniversityHangzhou 310003China

As of December 2022,2603 laboratory-identified Middle East respiratory syndrome coronavirus(MERS-CoV)infections and 935 associated deaths,with a mortality rate of 36%,had been reported to the World Health Organization(WHO).However,there are still no vaccines for MERS-CoV,which makes the prevention and control of MERS-CoV *** this study,we generated two DNA vaccine candidates by integrating MERS-CoV Spike(S)gene into a replicating Vaccinia Tian Tan(VTT)*** to homologous immunization with either vaccine,mice immunized with DNA vaccine prime and VTT vaccine boost exhibited much stronger and durable humoral and cellular immune *** immunized mice produced robust binding antibodies and broad neutralizing antibodies against the EMC2012,England1 and KNIH strains of ***-Boost immunization also induced strong MERS-S specific T cells responses,with high memory and poly-functional(CD107a-IFN-γ-TNF-α)effector CD8t T *** conclusion,the research demonstrated that DNA-Prime/VTT-Boost strategy could elicit robust and balanced humoral and cellular immune responses against *** study not only provides a promising set of MERS-CoV vaccine candidates,but also proposes a heterologous sequential immunization strategy worthy of further development.

关键词： MERS-CoV VTT vaccine DNA vaccine Humoral and cellular immune responses Prime/boost strategy

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Influences of Co-Flow and Counter-Flow Modes of Reactant Flow Arrangement on a PEMFC at Start-Up

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1337-1356页

作者： Qianqian shao Min Wang Nuo Xu School of Petroleum Engineering Guangdong University of Petrochemical TechnologyMaoming525000China Mechanics Division Beijing Computational Science Research CenterBeijing100193China

To investigate the influences of co-flowand counter-flowmodes of reactant flowarrangement on a proton exchange membrane fuel cell(PEMFC)during start-up,unsteady physical and mathematical models fully coupling the flow,heat,and electrochemical reactions in a PEMFC are *** continuity equation and momentum equation are solved by handling pressure-velocity coupling using the SIMPLE *** electrochemical reaction rates in the catalyst layers(CLs)of the cathode and anode are calculated using the Butler-Volmer *** multiphase mixture model describes the multiphase transport process of gas mixtures and liquid water in the fuel *** validation,the influences of co-flow and counter-flow modes on the PEMFC performance are investigated,including the evolution of the current density,flow field,temperature field,and reactant concentration field during start-up,as well as the steady distribution of the current density,reactant concentration,andmembrane water content when the start-up ***-flow and counter-flow modes influence the current density distribution and temperature *** the one hand,the co-flow mode accelerates the start-up process of the PEMFC and leads to a more evenly distributed current density than the counter-flow *** the other hand,the temperature difference between the inlet and outlet sections of the cell is up to 10.1℃ under the co-flow mode,much larger than the 5.0℃ observed in the counter-flow ***,the counter-flowmode results in a more evenly distributed temperature and a lower maximum temperature than the co-flow ***,in the flow field design of a PEMFC,the reactant flow arrangements can be considered to weigh between better heat management and higher current density distribution of the cell.

关键词： PEMFC full coupling model Butler-Volmer equation multiphase mixture model co-flow mode counter-flow mode

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A GMM approach in coupling internal data and external summary information with heterogeneous data populations

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Science China Mathematics 2024年第5期67卷 1115-1132页

作者： Jun shao Jinyi Wang Lei Wang Key Laboratory of Advanced Theory and Application in Statistics and Data Science(East China Normal University) Ministry of EducationShanghai 200062China School of Statistics East China Normal UniversityShanghai 200062China Department of Statistics University of Wisconsin-MadisonWI 53706USA School of Statistics and Data Science KLMDASRLEBPS and LPMCNankai UniversityTianjin 300071China

Because of advances in data collection and storage,statistical analysis in modern scientific research and practice now has opportunities to utilize external information such as summary statistics from similar studies.A likelihood approach based on a parametric model assumption has been developed in the literature to utilize external summary information when the populations for external and main internal data are assumed to be the *** this article,we instead consider the generalized estimation equation(GEE)approach for statistical inference,which is semiparametric or nonparametric,and show how to utilize external summary information even when internal and external data populations are not the *** approach is coupling the internal data and external summary information to form additional estimation equations and then applying the generalized method of moments(GMM).We show that the proposed GMM estimator is asymptotically normal and,under some conditions,is more efficient than the GEE estimator without using external summary *** of the asymptotic covariance matrix of the GMM estimators are also *** results are obtained to confirm our theory and quantify the improvements by utilizing external *** example is also included for illustration.

关键词： adjustment for heterogeneity constraint data integration generalized method of moments summarystatistic

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Advancing flood susceptibility modeling using stacking ensemble machine learning: A multi-model approach

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Journal of Geographical Sciences 2024年第8期34卷 1513-1536页

作者： YANG Huilin YAO Rui DONG Linyao SUN Peng ZHANG Qiang wei Yongqiang SUN shao AGHAKOUCHAK Amir School of Geography and Tourism Anhui Normal UniversityWuhu 241002AnhuiChina Changjiang River Scientific Research Institute Wuhan 430015China Advanced Interdisciplinary Institute of Environment and Ecology Beijing Normal UniversityZhuhai 519087GuangdongChina Hunan Institute of Water Resources and Hydropower Research Changsha 410007China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Department of Civil and Environmental Engineering University of California IrvineIrvineCA 92697USA

Flood susceptibility modeling is crucial for rapid flood forecasting, disaster reduction strategies, evacuation planning, and decision-making. Machine learning(ML) models have proven to be effective tools for assessing flood susceptibility. However, most previous studies have focused on individual models or comparative performance, underscoring the unique strengths and weaknesses of each model. In this study, we propose a stacking ensemble learning algorithm that harnesses the strengths of a diverse range of machine learning models. The findings reveal the following:(1) The stacking ensemble learning, using RF-XGBCB-LR model, significantly enhances flood susceptibility simulation.(2) In addition to rainfall,key flood drivers in the study area include NDVI, and impervious surfaces. Over 40% of the study area, primarily in the northeast and southeast, exhibits high flood susceptibility, with higher risks for populations compared to cropland.(3) In the northeast of the study area,heavy precipitation, low terrain, and NDVI values are key indicators contributing to high flood susceptibility, while long-duration precipitation, mountainous topography, and upper reach vegetation are the main drivers in the southeast. This study underscores the effectiveness of ML, particularly ensemble learning, in flood modeling. It identifies vulnerable areas and contributes to improved flood risk management.

关键词： flood susceptibility assessment machine learning stacking ensemble learning flood drivers XiangjiangRiverBasin

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Staging liver fibrosis with various diffusion-weighted magnetic resonance imaging models

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World Journal of Gastroenterology 2024年第9期30卷 1164-1176页

作者： Yan-Li Jiang Juan Li Peng-Fei Zhang Feng-Xian Fan Jie Zou Pin Yang Peng-Fei Wang shao-Yu Wang jing Zhang Department of Magnetic Resonance Imaging The Second Hospital&Clinical Medical SchoolLanzhou UniversityLanzhou 730030Gansu ProvinceChina Second Clinical School Lanzhou UniversityLanzhou 730030Gansu ProvinceChina Gansu Province Clinical Research Center for Functional and Molecular Imaging The Second Hospital&Clinical Medical SchoolLanzhou UniversityLanzhou 730030Gansu ProvinceChina Department of Hepatology The Second Hospital&Clinical Medical SchoolLanzhou UniversityLanzhou 730030Gansu ProvinceChina MR Scientific Marketing Siemens HealthineersXi’an 710065Shaanxi ProvinceChina

BACKGROUND Diffusion-weighted imaging(DWI)has been developed to stage liver ***,its diagnostic performance is inconsistent among ***,it is worth studying the diagnostic value of various diffusion models for liver fibrosis in one *** To evaluate the clinical potential of six diffusion-weighted models in liver fibrosis staging and compare their diagnostic *** This prospective study enrolled 59 patients suspected of liver disease and scheduled for liver biopsy and 17 healthy *** participants underwent multi-b value *** main DWI-derived parameters included Mono-apparent diffusion coefficient(ADC)from mono-exponential DWI,intravoxel incoherent motion model-derived true diffusion coefficient(IVIM-D),diffusion kurtosis imaging-derived apparent diffusivity(DKI-MD),stretched exponential model-derived distributed diffusion coefficient(SEM-DDC),fractional order calculus(FROC)model-derived diffusion coefficient(FROC-D)and FROC model-derived microstructural quantity(FROC-μ),and continuous-time random-walk(CTRW)model-derived anomalous diffusion coefficient(CTRW-D)and CTRW model-derived temporal diffusion heterogeneity index(CTRW-α).The correlations between DWI-derived parameters and fibrosis stages and the parameters’diagnostic efficacy in detecting significant fibrosis(SF)were assessed and *** CTRW-D(r=-0.356),CTRW-α(r=-0.297),DKI-MD(r=-0.297),FROC-D(r=-0.350),FROC-μ(r=-0.321),IVIM-D(r=-0.251),Mono-ADC(r=-0.362),and SEM-DDC(r=-0.263)were significantly correlated with fibrosis *** areas under the ROC curves(AUCs)of the combined index of the six models for distinguishing SF(0.697-0.747)were higher than each of the parameters alone(0.524-0.719).The DWI models’ability to detect SF was *** combined index of CTRW model parameters had the highest AUC(0.747).CONCLUSION The DWI models were similarly valuable in distinguishing SF in patients with liver *** combined index of CTRW paramet

关键词： Liver fibrosis Magnetic resonance imaging Diffusion-weighted magnetic resonance Liver biopsy Significant fibrosis

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Advancements in Remote Sensing Image Dehazing: Introducing URA-Net with Multi-Scale Dense Feature Fusion Clusters and Gated Jump Connection

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2397-2424页

作者： Hongchi Liu Xing Deng Haijian shao School of Computer Jiangsu University of Science and TechnologyZhenjiang212003China Department of Electrical and Computer Engineering University of NevadaLas Vegas89119USA

The degradation of optical remote sensing images due to atmospheric haze poses a significant obstacle,profoundly impeding their effective utilization across various *** methodologies have emerged as pivotal components of image preprocessing,fostering an improvement in the quality of remote sensing *** enhancement renders remote sensing data more indispensable,thereby enhancing the accuracy of target *** defogging techniques based on simplistic atmospheric degradation models have proven inadequate for mitigating non-uniform haze within remotely sensed *** response to this challenge,a novel UNet Residual Attention Network(URA-Net)is *** paradigmatic approach materializes as an end-to-end convolutional neural network distinguished by its utilization of multi-scale dense feature fusion clusters and gated jump *** essence of our methodology lies in local feature fusion within dense residual clusters,enabling the extraction of pertinent features from both preceding and current local data,depending on contextual *** intelligently orchestrated gated structures facilitate the propagation of these features to the decoder,resulting in superior outcomes in haze *** validation through a plethora of experiments substantiates the efficacy of URA-Net,demonstrating its superior performance compared to existing methods when applied to established datasets for remote sensing image *** the RICE-1 dataset,URA-Net achieves a Peak Signal-to-Noise Ratio(PSNR)of 29.07 dB,surpassing the Dark Channel Prior(DCP)by 11.17 dB,the All-in-One Network for Dehazing(AOD)by 7.82 dB,the Optimal Transmission Map and Adaptive Atmospheric Light For Dehazing(OTM-AAL)by 5.37 dB,the Unsupervised Single Image Dehazing(USID)by 8.0 dB,and the Superpixel-based Remote Sensing Image Dehazing(SRD)by 8.5 *** noteworthy,on the SateHaze1k dataset,URA-Net attains preeminence in overall performance,yieldi

关键词： Remote sensing image image dehazing deep learning feature fusion

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An M-VCUT level set-based data-driven model of microstructures and optimization of two-scale structures

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Frontiers of Mechanical Engineering 2024年第4期19卷 73-86页

作者： Minjie shao Tielin SHI Qi XIA State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China

The optimization of two-scale structures can adapt to the different needs of materials in various regions by reasonably arranging different microstructures at the macro scale,thereby considerably improving structural ***,a multiple variable cutting(M-VCUT)level set-based data-driven model of microstructures is presented,and a method based on this model is proposed for the optimal design of two-scale *** geometry of the microstructure is described using the M-VCUT level set method,and the effective mechanical properties of microstructures are computed by the homogenization ***,a database of microstructures containing their geometric and mechanical parameters is *** two sets of parameters are adopted as input and output datasets,and a mapping relationship between the two datasets is established to build the data-driven model of *** the optimization of two-scale structures,the data-driven model is used for macroscale finite element and sensitivity *** efficiency of the analysis and optimization of two-scale structures is improved because the computational costs of invoking such a data-driven model are much smaller than those of homogenization.

关键词： two-scale structure structural optimization M-VCUT level set homogenization radial basis function data-driven

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Synergistic silver-mediated and palladium-catalyzed nondirected olefination of aryl C–H bond: quick access to multi-substituted aryl olefins

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Science China Chemistry 2024年第3期67卷 882-889页

作者： Jian Yao Lili shao Xiaohong Huo Xiaoming Wang Shanghai Key Laboratory for Molecular Engineering of Chiral Drugs Frontiers Science Center for Transformative MoleculesSchool of Chemistry and Chemical EngineeringShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Organometallic Chemistry Center for Excellence in Molecular SynthesisShanghai Institute of Organic ChemistryChinese Academy of SciencesShanghai 20032China School of Chemistry and Materials Science Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China

Transition metal-catalyzed olefination of aryl C-H bond is a powerful tool for the synthesis of alkenes. While the Pd-catalyzed oxidative C-H olefination of arenes, also known as Fujiwara-Moritani reaction, has been established as one of the most efficient methods, the substrates are largely limited to terminal olefins with electron-withdrawing group(s). Herein, we report a synergistic silver-mediated and palladium-catalyzed non-directed C-H olefination of arenes with vinyl(pseudo)halides, which offers a complementary strategy to the typical Fujiwara-Moritani reaction. The reactions proceeded well for a variety of halogenated arenes, heteroarenes, and olefin substrates, providing an efficient access to various multi-substituted aryl olefins, including trisubstituted/tetrasubstituted olefins and several complex olefins derived from medicines or natural products. Mechanistic studies indicated a bimetallic Pd/Ag cooperation is operative in the catalysis, i.e., the reaction is initiated by aryl C-H bond cleavage via ligation with phosphine/Ag species, followed by transferring of the aryl moiety to a vinyl palladium intermediate,which is in turn formed by oxidative addition of vinyl(pseudo)halide to a Pd complex. This method enables the synthesis of a wide range of challenging multi-substituted vinyl products from simple arenes(directing-group free) in a streamlined and controllable fashion.

关键词： direct C–H olefination multi-substituted aryl alkenes bimetallic Pd/Ag cooperation C–H functionalization

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Tighter sum uncertainty relations via(α,β,γ)weighted Wigner–Yanase–Dyson skew information

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Communications in Theoretical Physics 2024年第3期76卷 91-99页

作者： Cong Xu Zhaoqi Wu shao-Ming Fei School of Mathematical Sciences Capital Normal UniversityBeijing 100048China Department of Mathematics Nanchang UniversityNanchang 330031China Max-Planck-Institute for Mathematics in the Sciences 04103 LeipzigGermany

We establish tighter uncertainty relations for arbitrary finite observables via(α,β,γ)weighted Wigner–Yanase–Dyson((α,β,γ)WWYD)skew *** results are also applicable to the(α,γ)weighted Wigner–Yanase–Dyson((α,γ)WWYD)skew information and the weighted Wigner–Yanase–Dyson(WWYD)skew *** also present tighter lower bounds for quantum channels and unitary channels via(α,β,γ)modified weighted Wigner–Yanase–Dyson((α,β,γ)MWWYD)skew *** examples are provided to illustrate the tightness of our uncertainty relations.

关键词： quantum channels (α,β,γ)WWYD skew information (α,β,γ)MWWYD skew information uncertainty relations

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