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4篇 您的检索式:作者名="Xingnan Liu"
    题名 作者 年代 出处 被引量
1Serum Golgi Protein 73 (GP73) is a Diagnostic and Prognostic Marker of Chronic HBV Liver Disease显示文摘Zhengju Xu Liguan Liu Xingnan Pan Kaipeng Wei Meijuan Wei Lifei Liu Huanwen Yang Qian Liu 2015Medicine2015,,12:2
2An examination of the OMIM database for associating mutation to a consensus reference sequence显示文摘Gene mutation(e.g.substitution,insertion and deletion)and related phenotype information are important bio-medical knowledge.Many biomedical databases(e.g.OMIM)incorporate such data.However,few studies have examined the quality of this data.In the current study,we examined the quality of protein single-point mutations in the OMIM and identified whether the cor-responding reference sequences align with the muta-tion positions.Our results show that close to 20%of mutation data cannot be mapped to a single reference sequence.The failed mappings are caused by position conflict,site shifting(peptide,N-terminal methionine)and other types of data error.We propose a preliminary model to resolve such inconsistency in the OMIM database.Zuofeng Li Beili Ying Xingnan Liu Xiaoyan Zhang Hong Yu 2012Protein & Cell2012,3,3:0
3PHOTOEMISSION STUDIES OF Pd/D SYSTEM WITH HIGH DEUTERIUM CONTENT显示文摘The ultraviolet photoelectron spectroscopy(UPS)spectra of Pd/D system(including absorption at high pressure)with various D contents were measured.The D absorption induced a new peak centered at about 6eV below Ef,which seems to derive from the hybridized states of deuterium and Pd electronic states.Its intensity increases with D content;only part of the D atoms in the Pd lattice are ionized at high D content.LIU Zhenxiang XIE Kan QI Shangxue CAO Jianming LI Nan YU Xingnan LIN Zhangda 1990Chinese Physics Letters1990,7,3:0
4Evaluation and Driving Force Analysis of Cultivated Land Quality in Black Soil Region of Northeast China显示文摘Cultivated land is an important natural resource to ensure food,ecological and economic security.The cultivated land quality evaluation(CQE)is greatly significant for protecting and managing cultivated land.In this study,320 counties in the black soil region of Northeast China(BSRNC)represent the research units used to construct the CQE system measuring the soil properties(SP),cultivated land productivity(CLP),ecological environment(EE)and social economy(SE).The total of 19 factors were selected to calculate the integrated fertility index(IFI)and divided into grades.Simultaneously,we used the coupling coordination degree model to comprehensively analyze the spatial pattern of the cultivated land quality(CLQ)in the BSRNC,and use the structural equation model(SEM)to analyze the driving mechanism.The results show the following:1)The CLQ of 262 counties in the BSRNC is in a state of coupling and coordination,and the coupling and coordination degree presents a spatial distribution pattern of‘high in the southwest and northeast,low in the northwest and southeast’.The coordinated development degree of 271 counties is between 0.4 and 0.6,which is in a transitional state between coordination and disorder.2)The CLQ in the BSRNC is generally good,with an average grade of 3.High-quality cultivated land accounts for 58.45%of all counties,middle-and upper-quality cultivated land accounts for 27.05%,and poor-quality cultivated land accounts for 14.49%.3)The SEM analysis shows that the SP,CLP,EE,and SE all influence the CLQ.Among them,the SP has the largest driving force on the CLQ,while the SE has the smallest driving force on it.The results confirm that the main factors affecting the evaluation results are crop productivity level,normalized difference vegetation index,ratio vegetation index,difference vegetation index,and organic carbon content.When implementing protection measures in counties with a low CLQ,considering a balanced coordination of multiple systems and reasonably controlling the quality degradation are important.This study provides the current situation and driving factors of the CLQ in the BSRNC and will play an important role in black soil governance and utilization.WANG Mingchang LIU Xingnan LIU Ziwei WANG Fengyan LI Xiaoyan HOU Guanglei ZHAO Shijun 2023Chinese Geographical Science2023,33,4:0
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