[目的/意义]通过文献调研梳理合著论文作者贡献度评价方法,总结研究不足及未来发展方向,为后续开展科技人才评价相关研究提供参考。[研究设计/方法]在Web of Science、Springe Link和CNKI等学术平台检索2010-2023年间发表的合著论文作...[目的/意义]通过文献调研梳理合著论文作者贡献度评价方法,总结研究不足及未来发展方向,为后续开展科技人才评价相关研究提供参考。[研究设计/方法]在Web of Science、Springe Link和CNKI等学术平台检索2010-2023年间发表的合著论文作者贡献度评价方法的研究文献,从传统评价方法、基于作者贡献声明的评价方法和基于科研产出的评价方法三个方面对文献进行归纳梳理。[结论/发现]合著论文作者贡献度评价方法已经取得了丰富的研究成果,但仍存在一些不足之处。未来的研究应从多方面出发考虑,进一步探索作者研究领域、作者学术关键词等学术背景因素对合著论文参与程度的影响,深入挖掘引文语义特征关系,以及加强对新模型及机器学习、深度学习算法的应用。[创新/价值]揭示了合著论文作者贡献度评价方法的发展进程与特点,阐述了合著论文作者贡献度评价方法的未来发展方向。展开更多
Inspired by recent significant agricultural yield losses in the eastern China and a missing operational monitoring system,we developed a comprehensive drought monitoring model to better understand the impact of indivi...Inspired by recent significant agricultural yield losses in the eastern China and a missing operational monitoring system,we developed a comprehensive drought monitoring model to better understand the impact of individual key factors contributing to this issue.The resulting model,the‘Humidity calibrated Drought Condition Index’(HcDCI)was applied for the years 2001 to 2019 in form of a case study to Weihai County,Shandong Province in East China.Design and development are based on a linear combination of the Vegetation Condition Index(VCI),the Temperature Condition Index(TCI),and the Rainfall Condition Index(RCI)using multi-source satellite data to create a basic Drought Condition Index(DCI).VCI and TCI were derived from MODIS(Moderate Resolution Imaging Spectroradiometer)data,while precipitation is taken from CHIRPS(Climate Hazards Group InfraRed Precipitation with Station data)data.For reasons of accuracy,the decisive coefficients were determined by the relative humidity of soils at depth of 10-20 cm of particular areas collected by an agrometeorological ground station.The correlation between DCI and soil humidity was optimized with the factors of 0.53,0.33,and 0.14 for VCI,TCI,and RCI,respectively.The model revealed,light agricultural droughts from 2003 to 2013 and in 2018,while more severe droughts occurred in 2001 and 2002,2014-2017,and 2019.The droughts were most severe in January,March,and December,and our findings coincide with historical records.The average temperature during 2012-2019 is 1℃ higher than that during the period 2001-2011 and the average precipitation during 2014-2019 is 192.77 mm less than that during 2008-2013.The spatio-temporal accuracy of the HcDCI model was positively validated by correlation with agricultural crop yield quantities.The model thus,demonstrates its capability to reveal drought periods in detail,its transferability to other regions and its usefulness to take future measures.展开更多
文摘[目的/意义]通过文献调研梳理合著论文作者贡献度评价方法,总结研究不足及未来发展方向,为后续开展科技人才评价相关研究提供参考。[研究设计/方法]在Web of Science、Springe Link和CNKI等学术平台检索2010-2023年间发表的合著论文作者贡献度评价方法的研究文献,从传统评价方法、基于作者贡献声明的评价方法和基于科研产出的评价方法三个方面对文献进行归纳梳理。[结论/发现]合著论文作者贡献度评价方法已经取得了丰富的研究成果,但仍存在一些不足之处。未来的研究应从多方面出发考虑,进一步探索作者研究领域、作者学术关键词等学术背景因素对合著论文参与程度的影响,深入挖掘引文语义特征关系,以及加强对新模型及机器学习、深度学习算法的应用。[创新/价值]揭示了合著论文作者贡献度评价方法的发展进程与特点,阐述了合著论文作者贡献度评价方法的未来发展方向。
基金Under the auspices of Shenzhen Science and Technology Program(No.KQTD20180410161218820)Guangdong Basic and Applied Basic Research Foundation(No.2021A1515012600)。
文摘Inspired by recent significant agricultural yield losses in the eastern China and a missing operational monitoring system,we developed a comprehensive drought monitoring model to better understand the impact of individual key factors contributing to this issue.The resulting model,the‘Humidity calibrated Drought Condition Index’(HcDCI)was applied for the years 2001 to 2019 in form of a case study to Weihai County,Shandong Province in East China.Design and development are based on a linear combination of the Vegetation Condition Index(VCI),the Temperature Condition Index(TCI),and the Rainfall Condition Index(RCI)using multi-source satellite data to create a basic Drought Condition Index(DCI).VCI and TCI were derived from MODIS(Moderate Resolution Imaging Spectroradiometer)data,while precipitation is taken from CHIRPS(Climate Hazards Group InfraRed Precipitation with Station data)data.For reasons of accuracy,the decisive coefficients were determined by the relative humidity of soils at depth of 10-20 cm of particular areas collected by an agrometeorological ground station.The correlation between DCI and soil humidity was optimized with the factors of 0.53,0.33,and 0.14 for VCI,TCI,and RCI,respectively.The model revealed,light agricultural droughts from 2003 to 2013 and in 2018,while more severe droughts occurred in 2001 and 2002,2014-2017,and 2019.The droughts were most severe in January,March,and December,and our findings coincide with historical records.The average temperature during 2012-2019 is 1℃ higher than that during the period 2001-2011 and the average precipitation during 2014-2019 is 192.77 mm less than that during 2008-2013.The spatio-temporal accuracy of the HcDCI model was positively validated by correlation with agricultural crop yield quantities.The model thus,demonstrates its capability to reveal drought periods in detail,its transferability to other regions and its usefulness to take future measures.
