Rapid and accurate identification of the characteristics(source location,number,and intensity)of pollution sources is essential for emergency assessment of contamination events.Compared with single-point source iden-t...Rapid and accurate identification of the characteristics(source location,number,and intensity)of pollution sources is essential for emergency assessment of contamination events.Compared with single-point source iden-tification,the reconstruction of multiple sources is more challenging.In this study,a two-step inversion method is proposed for multi-point pollution source reconstruction from limited measurements with the number of sources unknown.The applicability of the proposed method is validated with a set of synthetic experiments correspond-ing to one-,two-,and three-point pollution sources.The results show that the number and locations of pollution sources are retrieved exactly the same as prescribed,and the source intensities are estimated with negligible errors.The algorithm exhibits good performance in single-and multi-point pollution source identification,and its accuracy and efficiency of identification do not deteriorate with the increase in the number of sources.Some limitations of the algorithm,together with its capabilities,are also discussed in this paper.展开更多
[Objective] The aim of this study was to explore the dominant fiber quality traits of test sites in cotton regional trials, by analyzing the regional characteristics of cotton fiber quality in Jiangsu province, in ord...[Objective] The aim of this study was to explore the dominant fiber quality traits of test sites in cotton regional trials, by analyzing the regional characteristics of cotton fiber quality in Jiangsu province, in order to provide the theory background for cotton fiber quality improvement. [Method] The dominant fiber quality traits of test locations were analyzed with eight main fiber quality indexes of hybrid cotton regional trials during 2009-2013 in Jiangsu province by use of the "ideal test site" view of GGE biplot. [Result] The test locations with the best integrative fiber quality were proved to be Yanliang, and followed by Dongxin and Guanyun; The better test locations in terms of the major fiber quality indexes, including fiber strength, fiber Length and micronaire value, were Guanyun, Xinyang and Yanliang; To sum up, the best test location with balanced fiber quality was Yanliang. The test locations with specialties in fiber quality index were listed as bellow: Dafeng, Xinghua and Dongtai performance better in fiber length; Qidong, Liuhe and Yanhai locations were of better fiber length uniformity; Sheyang and Dongxin were better in micronaire value;while Sheyang along was better in fiber elongation and reflectance. Moreover, the correlation between fiber yellowness and other traits was significant(P<0.01). [Conclusion] The regional characteristic of cotton fiber quality index in Jiangsu province was obvious and fiber yellowness was worthy an indicator trait to assist the comprehensive improvement of cotton fiber quality.展开更多
基金supported by the National Key R&D Program of China[Grant Nos.2017YFC1501803 and 2017YFC1502102].
文摘Rapid and accurate identification of the characteristics(source location,number,and intensity)of pollution sources is essential for emergency assessment of contamination events.Compared with single-point source iden-tification,the reconstruction of multiple sources is more challenging.In this study,a two-step inversion method is proposed for multi-point pollution source reconstruction from limited measurements with the number of sources unknown.The applicability of the proposed method is validated with a set of synthetic experiments correspond-ing to one-,two-,and three-point pollution sources.The results show that the number and locations of pollution sources are retrieved exactly the same as prescribed,and the source intensities are estimated with negligible errors.The algorithm exhibits good performance in single-and multi-point pollution source identification,and its accuracy and efficiency of identification do not deteriorate with the increase in the number of sources.Some limitations of the algorithm,together with its capabilities,are also discussed in this paper.
基金Supported by Special Program to Cultivate New Species of National Genetically Modified Food(2012ZX08013016)
文摘[Objective] The aim of this study was to explore the dominant fiber quality traits of test sites in cotton regional trials, by analyzing the regional characteristics of cotton fiber quality in Jiangsu province, in order to provide the theory background for cotton fiber quality improvement. [Method] The dominant fiber quality traits of test locations were analyzed with eight main fiber quality indexes of hybrid cotton regional trials during 2009-2013 in Jiangsu province by use of the "ideal test site" view of GGE biplot. [Result] The test locations with the best integrative fiber quality were proved to be Yanliang, and followed by Dongxin and Guanyun; The better test locations in terms of the major fiber quality indexes, including fiber strength, fiber Length and micronaire value, were Guanyun, Xinyang and Yanliang; To sum up, the best test location with balanced fiber quality was Yanliang. The test locations with specialties in fiber quality index were listed as bellow: Dafeng, Xinghua and Dongtai performance better in fiber length; Qidong, Liuhe and Yanhai locations were of better fiber length uniformity; Sheyang and Dongxin were better in micronaire value;while Sheyang along was better in fiber elongation and reflectance. Moreover, the correlation between fiber yellowness and other traits was significant(P<0.01). [Conclusion] The regional characteristic of cotton fiber quality index in Jiangsu province was obvious and fiber yellowness was worthy an indicator trait to assist the comprehensive improvement of cotton fiber quality.
