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| 1 | Effects of Tillage Management on Infiltration and Preferential Flow in a Black Soil, Northeast China显示文摘The impacts of no-tillage (NT) and moldboard plough (MP) managements on infiltration rate and preferential flow were characterized using a combined technique of double-ring device and dye tracer on a black soil (Mollisols) in Northeast China. The objective of this study is to evaluate how tillage practices enhance soil water infiltration and preferential flow in favor of soil erosion control in the study area. The steady infiltration rates under NT management are 1.6 and 2.1 times as high as those under MP management in the 6th and 8th years of the tillage management in place, while the infiltrated water amounts under NT management are 1.4 and 2.0 times as high as those under MP management, respectively. The depth of methylene blue penetrated into NT soil increases from 43cm in the 6th year to 57cm in the 8th year, which are 16cm and 19cm deeper than those in MP soil, respectively. The results of morphologic image show that more biological macro-pores occur in NT soil than in MP soil. These macro-pores play a key role in enhancing preferential flow in NT soil, which in turn promotes water infiltration through preferential pathways in NT soil. The results are helpful to policy-making in popularizing NT and have the implications for tillage management in regard to soil erosion control in black soil region of China. | FAN Ruqin ZHANG Xiaoping YANG Xueming LIANG Aizhen JIA Shuxia CHEN Xuewen | 2013 | Chinese Geographical Science2013，23，3： | 6 |
| 2 | Amperometric glucose biosensor based on chitosan with improved selectivity and stability显示文摘 | Minghui Yang Yunhui Yang Bing Liu Guoli Shen Ruqin Yu | 2004 | Sensors & Actuators: B Chemical2004，，3： | 1 |
| 3 | Contribution of winter soil respiration to annual soil CO2 emission in a Mollisol under different tillage practices in northeast China显示文摘 | Shi Xiuhuan Zhang Xiaoping Yang Xueming Drury Craig F. McLaughlin Neil B. Liang Aizhen Fan Ruqin Jia Shuxia | 2012 | EN2012，，2： | 1 |
| 4 | A Protein A-Based Orientation-Controlled Immobilization Strategy for Antibodies Using Nanometer-Sized Gold Particles and Plasma-Polymerized Film显示文摘 | Hua Wang Yanli Liu Yunhui Yang Ting Deng Guoli Shen and Ruqin Yu | 2004 | Analytical Biochemistry2004，324，2： | 1 |
| 5 | Amperometric glucose biosensor based on chitosan with improved selectivity and stability显示文摘 | Minghui Yang Yunhui Yang Bing Liu Guoli Shen Ruqin Yu | 2004 | Sensors & Actuators: B. Chemical2004，，3： | 1 |
| 6 | Influence of γ-irradiation on Properties of Amorphous Fe78B13Si9 Alloy Studied by Mössbauer Spectroscopy and Bending Test显示文摘The influence ofγ-irradiation on properties of METGLAS 2605S2 and FC3-1 Fe78B13Si9 has been investigated by Möissbauer spectroscopy and bending test.The ductility and orientation of magnetization were changed byγ-irradiation.They probably correlated with the change of microscopic free volume and release of stress in the ribbon,respectively. | ZHANG Guilin LIU Wenhong ZHANG Hui CHANG Ruqin JIN Huijuan XU Guiqin YANG Yi | 1991 | Chinese Physics Letters1991，8，2： | 0 |
| 7 | Support vector machine regression(SVR)-based nonlinear modeling of radiometric transforming relation for the coarse-resolution data-referenced relative radiometric normalization(RRN)显示文摘Radiometric normalization,as an essential step for multi-source and multi-temporal data processing,has received critical attention.Relative Radiometric Normalization(RRN)method has been primarily used for eliminating the radiometric inconsistency.The radiometric trans-forming relation between the subject image and the reference image is an essential aspect of RRN.Aimed at accurate radiometric transforming relation modeling,the learning-based nonlinear regression method,Support Vector machine Regression(SVR)is used for fitting the complicated radiometric transforming relation for the coarse-resolution data-referenced RRN.To evaluate the effectiveness of the proposed method,a series of experiments are performed,including two synthetic data experiments and one real data experiment.And the proposed method is compared with other methods that use linear regression,Artificial Neural Network(ANN)or Random Forest(RF)for radiometric transforming relation modeling.The results show that the proposed method performs well on fitting the radiometric transforming relation and could enhance the RRN performance. | Jing Geng Wenxia Gan Jinying Xu Ruqin Yang Shuliang Wang | 2020 | Geo-Spatial Information Science2020，23，3： | 0 |
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