Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hong‐Xin Xie"'
Autor:
Hong-Xin Xie, 謝宏欣
92
Beamforming antennas with least squares channel estimation improve the effects of both multi-path fading channel as well as co-channel interference. The beamforming technology of smart antennas could obtain the best SINR of the received uplin
Beamforming antennas with least squares channel estimation improve the effects of both multi-path fading channel as well as co-channel interference. The beamforming technology of smart antennas could obtain the best SINR of the received uplin
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/54419430780605096185
Autor:
Hong‐Xin Xie, Xi‐Xi Liang, Wei‐Ming Li, Zhi‐Qiang Chen, Xi‐Feng Wang, Zi‐Han Ding, Xu‐Ming Zhou, Wei‐Guo Du
Publikováno v:
Journal of evolutionary biologyREFERENCES. 35(11)
Thickness reduction or loss of the calcareous eggshell is one of major phenotypic changes in the transition from oviparity to viviparity. Whether the reduction of eggshells in viviparous squamates is associated with specific gene losses is unknown. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65d039f9b497754ae8b5f7e620ecbf76
https://pubmed.ncbi.nlm.nih.gov/36129910
https://pubmed.ncbi.nlm.nih.gov/36129910
Autor:
Hong-Xin Xie, Xi-Xi Liang, Zhi-Qiang Chen, Wei-Ming Li, Chun-Rong Mi, Ming Li, Zheng-Jun Wu, Xu-Ming Zhou, Wei-Guo Du
Publikováno v:
Molecular Biology and Evolution
The purging of deleterious alleles has been hypothesized to mitigate inbreeding depression, but its effectiveness in endangered species remains debatable. To understand how deleterious alleles are purged during population contractions, we analyzed ge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b951656e83ef9e7d732156a53e828341
http://europepmc.org/articles/PMC8788223
http://europepmc.org/articles/PMC8788223
Publikováno v:
Chemosphere. 301:134758
It is well known benzene negatively impacts human health. This study is the first to predict spatial-temporal variations in benzene concentrations for the entirety of Taiwan by using a mixed spatial prediction model integrating multiple machine learn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d41e7e801d3199ddb77042d733e4b1d6
https://doi.org/10.1016/j.chemosphere.2022.134758
https://doi.org/10.1016/j.chemosphere.2022.134758