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| 1 | Land surface temperature retrieval for arid regions based on Landsat-8 TIRS data:a case study in Shihezi,Northwest China显示文摘Scientific interest in geophysical information about land surface temperature(LST) is ever increasing, as such information provides a base for a large number of applications, including environmental and agricultural monitoring. Therefore, the research of LST retrieval has become a hot topic. Recent availability of Landsat-8 satellite imagery provides a new data source for LST retrieval. Hence, exploring an adaptive method with reliable accuracy seems to be essential. In this study, basing on features of Landsat-8 TIRS thermal infrared channels, we re-calculated parameters in the atmospheric transmittance empirical models of the existing split-window algorithm, and estimated the ground emissivity with the help of the land cover classification map of the study area. Furthermore, a split-window algorithm was rebuilt by virtual of the estimation model of the updated atmospheric transmittance and the ground emissivity, and then a remote sensing retrieval for the LST of Shihezi city in Xinjiang Uygur autonomous region of Northwest China was conducted on the basis of this modified algorithm. Finally, precision validation of the new model was implemented by using the MODIS LST products. The results showed that the LST retrieval from Landsat-8 TIRS data based on our algorithm has a higher credibility, and the retrieved LST is more consistent with the MODIS LST products. This indicated that the modified algorithm is suitable for retrieving LST with competitive accuracy. With higher resolutions, Landsat-8 TIRS data may provide more accurate observation for LST retrieval. | Lei YANG YunGang CAO XiaoHua ZHU ShengHe ZENG GuoJiang YANG JiangYong HE XiuChun YANG | 2014 | Journal of Arid Land2014，6，6： | 17 |
| 2 | Subtyping of type A influenza by sequencing the variable regions of HA gene specifically amplified with RT-PCR显示文摘The outbreak of a novel influenza A(H1N1) virus across the globe poses a threat to human health.It is of paramount importance to develop a rapid,reliable and inexpensive diagnostic procedure.Based on the bioinformatic information from public database,primers specific for influenza A virus surface protein haemagglutinin(HA) of several subtypes(including H1,H2,H3,H5,H7 and H9) were designed.Primer-specific PCR products were subjected to sequencing for accurately distinguishing H1 and H3 subtypes from others.This sequencing-based detection method will not only be applied to rapid detection and simultaneous subtype identification of new influenza A virus H1N1,but also provide the strategies to monitor other new types ofinfluenza virus with explosive potential. | YAN An DING GuoHui ZHOU ZhenFeng DONG Hui ZHANG YaKun ZHU Lei HE YunGang ZHANG GuoQing LI YiXue SUN Bing HUANG Zhong LAN Ke JIN Li WANG HongYan WANG XiaoNing YANG Zhong ZHONG Yang DAI JianXin GUO YaJun WANG Hao CHE XiaoYan WU Fan YUAN ZhenGan ZHANG Xi CAO ZhiWei ZHOU XiaoNong ZHOU JiaHai MA ZhiYong TONG GuangZhi ZHAO GuoPing JIN WeiRong XIONG Hui | 2009 | Chinese Science Bulletin2009，54，13： | 3 |
| 3 | The mutation network for the hemagglutinin gene from the novel influenza A (H1N1) virus显示文摘A mutation network for the hemagglutinin gene(HA) of the novel type A(H1N1) influenza virus was constructed.Sequence homology analysis indicated that one HA sequence type from the viruses mainly isolated from Mexico was likely the original type in this epidemic.Based on the 658A and 1408T mutations in HA,the viruses evolving into this epidemic were divided into three categories,the Mexico,the transitional and the New York type.The three groups of viruses presented distinctive clustering features in their geographic distributions. | HE YunGang DING GuoHui BIAN Chao HUANG Zhong LAN Ke SUN Bing WANG XueCai LI YiXue WANG HongYan WANG XiaoNing YANG Zhong ZHONG Yang JIN WeiRong XIONG Hui DAI JianXin GUO YaJun WANG Hao CHE XiaoYan WU Fan YUAN ZhenAn ZHANG Xi CAO ZhiWei ZHOU XiaoNong ZHOU JiaHai MA ZhiYong TONG GuangZhi ZHAO GuoPing JIN Li | 2009 | Chinese Science Bulletin2009，54，13： | 3 |
| 4 | Structure modeling and spatial epitope analysis for HA protein of the novel H1N1 influenza virus显示文摘In recent months,a novel influenza virus H1N1 broke out around the world.With bioinformatics technology,the 3D structure of HA protein was obtained,and the epitope residues were predicted with the method developed in our group for this novel flu virus.58 amino acids were identified as potential epitope residues,the majority of which clustered at the surface of the globular head of HA protein.Although it is located at the similar position,the epitope of HA protein for the novel H1N1 flu virus has obvious differences in the electrostatic potential compared to that of HA proteins from previous flu viruses. | WU Di XU TianLei SUN Jing DAI JianXin DING GuoHui HE YunGang ZHOU ZhengFeng XIONG Hui DONG Hui JIN WeiRong BIAN Chao JIN Li WANG HongYan WANG XiaoNing YANG Zhong ZHONG Yang WANG Hao CHE XiaoYan HUANG Zhong LAN Ke SUN Bing WU Fan YUAN ZhenAn ZHANG Xi ZHOU XiaoNong ZHOU JiaHai MA ZhiYong TONG GuangZhi GUO YaJun ZHAO GuoPing LI YiXue CAO ZhiWei | 2009 | Chinese Science Bulletin2009，54，13： | 2 |
| 5 | Retrieval Snow Depth by Artificial Neural Network Methodology from Integrated AMSR-E and In-situ Data——A Case Study in Qinghai-Tibet Plateau显示文摘On the basis of artificial neural network (ANN) model, this paper presents an algorithm for inversing snow depth with use of AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System (EOS)) dataset, i.e., brightness temperature at 18.7 and 36.5GHz in Qinghai-Tibet Plateau during the snow season of 2002-2003. In order to overcome the overfitting problem in ANN modeling, this methodology adopts a Bayesian regularization approach. The experiments are performed to compare the results obtained from the ANN-based algorithm with those obtained from other existing algorithms, i.e., Chang algorithm, spectral polarization difference (SPD) algorithm, and temperature gradient (TG) algorithm. The experimental results show that the presented algorithm has the highest accuracy in estimating snow depth. In addition, the effects of the noises in datasets on model fitting can be decreased due to adopting the Bayesian regularization approach. | CAO Yungang YANG Xiuchun ZHU Xiaohua | 2008 | Chinese Geographical Science2008，18，4： | 1 |
| 6 | The expression and function of microRNA-203 in lung cancer显示文摘 | Jianhua Jin Jianzhong Deng Fang Wang Xiyi Xia Tiefeng Qiu Wenbin Lu Xianwen Li Hua Zhang Xiaoyan Gu Yungang Liu Weiguo Cao Wenlong Shao | 2013 | Tumor Biology2013，，： | 1 |
| 7 | Breeding and Cultivation Techniques of a New Table Use Purple-fleshed Sweetpotato Cultivar,Xuzishu 2显示文摘Xuzishu 2 is a new high-quality table use purple-fleshed sweetpotato cultivar bred from hybrid progenies of AIS35-2 × Xushu 22-5 by Jiangsu Xuzhou Sweetpotato Research Center. In the sweetpotato variety regional trial of Jiangsu Province during 2007- 2008,average fresh storage root yield was 30 185. 3kg / hm2; average dry matter content was 29. 26%; average dry storage root yield was 8 868. 7 kg/hm2. In the sweetpotato variety production test of Jiangsu Province,average fresh storage root yield was 30 683. 9 kg / hm2; average dry storage root yield was 9 399. 0 kg/hm2. Multi-location sampling analysis in the regional trial indicated that the anthocyanin content in fresh storage roots was 104. 6 μg / g. Xuzishu 2 was approved by Crop Variety Approval Committee of Jiangsu Province in March 2010,which exhibited high fresh storage root yield,sweet taste,high anthocyanin content,good commodity,root rot resistance,and was tolerant to moisture and easy to store. Therefore,Xuzishu 2 is a high-quality purple-fleshed sweetpotato variety suitable for consumption and food processing,which should be cultivated in medium- and high-fertility fields with management procedures of suitable high density,early planting and early harvest. | Qiang LI Yiping XIE Xin WANG Xiuying LI Hongmin LI Daifu MA Zhonghou TANG Qinghe CAO Meng KOU Yungang ZHANG Wei TANG | 2015 | Agricultural Biotechnology2015，4，4： | 0 |
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