TY - JOUR A1 - Xiang, Hai A1 - Gao, Jianqiang A1 - Cai, Dawei A1 - Luo, Yunbing A1 - Yu, Baoquan A1 - Liu, Langqing A1 - Liu, Ranran A1 - Zhou, Hui A1 - Chen, Xiaoyong A1 - Dun, Weitao A1 - Wang, Xi A1 - Hofreiter, Michael A1 - Zhao, Xingbo T1 - Origin and dispersal of early domestic pigs in northern China JF - Scientific reports N2 - It is widely accepted that modern pigs were domesticated independently at least twice, and Chinese native pigs are deemed as direct descendants of the first domesticated pigs in the corresponding domestication centers. By analyzing mitochondrial DNA sequences of an extensive sample set spanning 10,000 years, we find that the earliest pigs from the middle Yellow River region already carried the maternal lineages that are dominant in both younger archaeological populations and modern Chinese pigs. Our data set also supports early Neolithic pig utilization and a long-term in situ origin for northeastern Chinese pigs during 8,000-3,500 BP, suggesting a possibly independent domestication in northeast China. Additionally, we observe a genetic replacement in ancient northeast Chinese pigs since 3,500 BP. The results not only provide increasing evidence for pig origin in the middle Yellow River region but also depict an outline for the process of early pig domestication in northeast China. Y1 - 2017 U6 - https://doi.org/10.1038/s41598-017-06056-8 SN - 2045-2322 VL - 7 PB - Nature Publ. Group CY - London ER - TY - BOOK A1 - Chen, Huan A1 - Li, Wei-Xi A1 - Xu, Chao-Jiang T1 - Gevrey hypoellipticity for linear and non-linear fokker-planck equations T3 - Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partiell Y1 - 2007 SN - 1437-739X PB - Univ. CY - Potsdam ER - TY - JOUR A1 - Javhar, Aminov A1 - Chen, Xi A1 - Bao, Anming A1 - Jamshed, Aminov A1 - Yunus, Mamadjanov A1 - Jovid, Aminov A1 - Latipa, Tuerhanjiang T1 - Comparison of Multi-Resolution Optical Landsat-8, Sentinel-2 and Radar Sentinel-1 Data for Automatic Lineament Extraction BT - A Case Study of Alichur Area, SE Pamir JF - Remote sensing N2 - Lineament mapping, which is an important part of any structural geological investigation, is made more efficient and easier by the availability of optical as well as radar remote sensing data, such as Landsat and Sentinel with medium and high spatial resolutions. However, the results from these multi-resolution data vary due to their difference in spatial resolution and sensitivity to soil occupation. The accuracy and quality of extracted lineaments depend strongly on the spatial resolution of the imagery. Therefore, the aim of this study was to compare the optical Landsat-8, Sentinel-2A, and radar Sentinel-1A satellite data for automatic lineament extraction. The framework of automatic approach includes defining the optimal parameters for automatic lineament extraction with a combination of edge detection and line-linking algorithms and determining suitable bands from optical data suited for lineament mapping in the study area. For the result validation, the extracted lineaments are compared against the manually obtained lineaments through the application of directional filtering and edge enhancement as well as to the lineaments digitized from the existing geological maps of the study area. In addition, a digital elevation model (DEM) has been utilized for an accuracy assessment followed by the field verification. The obtained results show that the best correlation between automatically extracted lineaments, manual interpretation, and the preexisting lineament map is achieved from the radar Sentinel-1A images. The tests indicate that the radar data used in this study, with 5872 and 5865 lineaments extracted from VH and VV polarizations respectively, is more efficient for structural lineament mapping than the Landsat-8 and Sentinel-2A optical imagery, from which 2338 and 4745 lineaments were extracted respectively. KW - image enhancement KW - automatic lineament extraction KW - Landsat-8 KW - Sentinel-1 KW - Sentinel-2 KW - structural mapping Y1 - 2019 U6 - https://doi.org/10.3390/rs11070778 SN - 2072-4292 VL - 11 IS - 7 PB - MDPI CY - Basel ER - TY - INPR A1 - Chen, Hua A1 - Li, Wei-Xi A1 - Xu, Chao-Jiang T1 - Gevrey hypoellipticity for linear and non-linear Fokker-Planck equations N2 - This paper studies the Gevrey regularity of weak solutions of a class of linear and semilinear Fokker-Planck equations. T3 - Preprint - (2007) 07 Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-30283 ER - TY - JOUR A1 - Xiang, Hai A1 - Gao, Jianqiang A1 - Yu, Baoquan A1 - Zhou, Hui A1 - Cai, Dawei A1 - Zhang, Youwen A1 - Chen, Xiaoyong A1 - Wang, Xi A1 - Hofreiter, Michael A1 - Zhao, Xingbo T1 - Early Holocene chicken domestication in northern China JF - Proceedings of the National Academy of Sciences of the United States of America N2 - Chickens represent by far the most important poultry species, yet the number, locations, and timings of their domestication have remained controversial for more than a century. Here we report ancient mitochondrial DNA sequences from the earliest archaeological chicken bones from China, dating back to similar to 10,000 B.P. The results clearly show that all investigated bones, including the oldest from the Nanzhuangtou site, are derived from the genus Gallus, rather than any other related genus, such as Phasianus. Our analyses also suggest that northern China represents one region of the earliest chicken domestication, possibly dating as early as 10,000 y B.P. Similar to the evidence from pig domestication, our results suggest that these early domesticated chickens contributed to the gene pool of modern chicken populations. Moreover, our results support the idea that multiple members of the genus Gallus, specifically Gallus gallus and Gallus sonneratii contributed to the gene pool of the modern domestic chicken. Our results provide further support for the growing evidence of an early mixed agricultural complex in northern China. KW - ancient DNA KW - chicken KW - domestication KW - species origin Y1 - 2014 U6 - https://doi.org/10.1073/pnas.1411882111 SN - 0027-8424 VL - 111 IS - 49 SP - 17564 EP - 17569 PB - National Acad. of Sciences CY - Washington ER -