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| 1 | QTG-Seq Accelerates QTL Fine Mapping through QTL Partitioning and Whole-Genome Sequencing of Bulked Segregant Samples显示文摘Deciphering the genetic mechanisms underlying agronomic traits is of great importance for crop improvement. Most of these traits are controlled by multiple quantitative trait loci (QTLs), and identifying the underlying genes by conventional QTL fine-mapping is time-consuming and labor-intensive. Here, we devised a new method, named quantitative trait gene sequencing (QTG-seq), to accelerate QTL fine-mapping. QTGseq combines QTL partitioning to convert a quantitative trait into a near-qualitative trait, sequencing of bulked segregant pools from a large segregating population, and the use of a robust new algorithm for identifying candidate genes. Using QTG-seq, we fine-mapped a plant-height QTL in maize (Zea mays L.), qPH7, to a 300-kb genomic interval and verified that a gene encoding an NF-YC transcription factor was the functional gene. Functional analysis suggested that qPH7-encoding protein might influence plant height by interacting with a CO-like protein and an AP2 domain-containing protein. Selection footprint ana卜 ysis indicated that qPH7 was subject to strong selection during maize improvement. In summary, QTG-seq provides an efficient method for QTL fine-mapping in the era of “big data'. | Hongwei Zhang Xi Wang Qingchun Pan Pei Li Yunjun Liu Xiaoduo Lu Wanshun Zhong Minqi Li Linqian Han Juan Li Pingxi Wang Dongdong Li Yan Liu Qing Li Fang Yang Yuan-Ming Zhang Guoying Wang Lin Li | 2019 | Molecular Plant2019，12，3： | 13 |
| 2 | Optimization based method {or supply location selection and routing in large scale emergency material delivery显示文摘 | Han Yunjun Guan Xiahong Shi Leyuan | 2011 | IEEE Transactions on Automation Science and Engineering2011，8，4： | 1 |
| 3 | Homology Modeling of CrylAc Toxin-binding Alkaline Phosphatase Receptor from Helicoverpa armigera and Its Functional Interpretation显示文摘 | Shan, Shiping Xia, Liqiu Ding, Xuezhi Zhang, Youming Hu, Shengbiao Sun, Yunjun Yu, Ziquan Han, Lizhen | 2011 | Chinese Journal of Chemistry2011，29，3： | 1 |
| 4 | MODIS -driven estimation of terrestrial latent heat flux in China based on a modified Priestley–Taylor algorithm显示文摘 | Yunjun Yao Shunlin Liang Jie Cheng Shaomin Liu Joshua B. Fisher Xudong Zhang Kun Jia Xiang Zhao Qiming Qin Bin Zhao Shijie Han Guangsheng Zhou Guoyi Zhou Yuelin Li Shaohua Zhao | 2012 | Agricultural and Forest Meteorology2012，，： | 1 |
| 5 | Evaluation of nine machine learning methods for estimating daily land surface radiation budget from MODIS satellite data显示文摘The all-wave net radiation(Rn)at the land surface represents surface radiation budget and plays an important role in the Earth's energy and water cycles.Many studies have been conducted to estimate from satellite top-of-atmosphere(TOA)data using various methods,particularly the application of machine learning(ML)and deep learning(DL).However,few studies have been conducted to provide a comprehensive evaluation about various ML and DL methods in retrieving.Based on extensive in situ measurements distributed at mid-low latitudes,the corresponding Moderate Resolution Imaging Spectroradiometer(MODIS)TOA observations,and the daily from the fifth generation of European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)used as a priori knowledge,this study assessed nine models for daily estimation,including six classic ML methods(random forest-RF,adaptive boosting-Adaboost,extreme gradient boosting-XGBoost,multilayer perceptron-MLP,radial basis function neural network-RBF,and support vector machine-SVM)and three DL methods(multilayer perceptron neural network with stacked autoencoders-SAE,deep belief network-DBN and residual neural network-ResNet).The validation results showed that the three DL methods were generally better than the six ML methods except XGBoost,although they all performed poorly in certain conditions such as winter days,rugged terrain,and high elevation.ResNet had the most robust performance across different land cover types,elevations,seasons,and latitude zones,but it has disadvantages in practice because of its highly configurable implementation environment and low computational efficiency.The estimated daily values from all nine models were more accurate than the corresponding Global LAnd Surface Satellite(GLASS)product. | Shaopeng Li Bo Jiang Shunlin Liang Jianghai Peng Hui Liang Jiakun Han Xiuwan Yin Yunjun Yao Xiaotong Zhang Jie Cheng Xiang Zhao Qiang Liu Kun Jia | 2022 | International Journal of Digital Earth2022，15，1： | 0 |
| 6 | Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach显示文摘The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances. | Yunjun Zheng Jinchuan Zheng Ke Shao Han Zhao Hao Xie Hai Wang | 2024 | IEEE/CAA Journal of Automatica Sinica2024，11，4： | 0 |
| 7 | Significant discrepancies of land surface daily net radiation among ten remotely sensed and reanalysis products显示文摘Land surface all-wave net radiation(R_(n))is crucial in determining Earth’s climate by contributing to the surface radiation budget.This study evaluated seven satellite and three reanalysis long-term land surface R_(n)products under different spatial scales,spatial and temporal variations,and different conditions.The results showed that during 2000-2018,Global Land Surface Satellite Product(GLASS)-Moderate Resolution Imaging Spectroradiometer(MODIS)performed the best(RMSE=25.54 Wm^(-2),bias=-1.26 Wm^(-2)),followed by ERA5(the fifth-generation of European Centre for Medium-Range Weather Forecast Reanalysis)(RMSE=32.17 Wm^(-2),bias=-4.88 Wm^(-2))and GLASS-AVHRR(Advanced Very-High-Resolution Radiometer)(RMSE=33.10 Wm^(-2),bias=4.03 Wm^(-2)).During 1983-2018,GLASS-AVHRR and ERA5 ranked top and performed similarly,with RMSE values of 31.70 and 33.08 Wm^(-2)and biases of-4.56 and 3.48 Wm^(-2),respectively.The averaged multi-annual mean R_(n)over the global land surface of satellite products was higher than that of reanalysis products by about 10~30 Wm^(-2).These products differed remarkably in long-term trends variations,particularly pre-2000,but no significant trends were observed.Discrepancies were more frequent in satellite data,while reanalysis products showed smoother variations.Large discrepancies were found in regions with high latitudes,reflectance,and elevation which could be attributed to input radiative components,meteorological variables(e.g.,cloud properties,aerosol optical thickness),and applicability of the algorithms used.While further research is needed for detailed insights. | Xiuwan Yin Bo Jiang Shunlin Liang Shaopeng Li Xiang Zhao Qian Wang Jianglei Xu Jiakun Han Hui Liang Xiaotong Zhang Qiang Liu Yunjun Yao Kun Jia Xianhong Xie | 2023 | International Journal of Digital Earth2023，16，1： | 0 |
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