Zobrazeno 1 - 10
of 27 175
pro vyhledávání: '"An, Gaofeng"'
Publikováno v:
Guangdong Agricultural Sciences. 2024, Vol. 51 Issue 5, p102-114. 13p.
Publikováno v:
Guangdong nongye kexue, Vol 51, Iss 5, Pp 102-114 (2024)
【Objective】The study was conducted to investigate the spatial distribution and content differences of asymbiotic nitrogen fixation (ANF) in different ecosystem components of Cunninghamia lanceolata, Eucalyptus, Pinus massoniana plantation forests
Externí odkaz:
https://doaj.org/article/54109a9d758846bb8d762af6ba37f087
Akademický článek
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Autor:
Gao, Feng1,2 (AUTHOR), Li, Xin1,2 (AUTHOR), Xiong, Xin1,2 (AUTHOR) xiongxin@csu.edu.cn, Lu, Haichuan3 (AUTHOR), Luo, Zengwu3 (AUTHOR)
Publikováno v:
Mathematics (2227-7390). Apr2023, Vol. 11 Issue 7, p1612. 18p.
Publikováno v:
Journal of Guilin University of Technology. Aug2021, Vol. 41 Issue 3, p471-483. 13p.
Publikováno v:
Nature Environment and Pollution Technology, Vol 19, Iss 3, Pp 949-956 (2020)
China is rich in mineral resources with many points and broad faces in metal and nonmetal mines. However, numerous goafs are formed due to backward mining technology, low intensification degree, incomplete safety precautions, and the excessive exploi
Externí odkaz:
https://doaj.org/article/61a7ea44fde145e695e8ea3721c3e973
Recently, ``textless" speech language models (SLMs) based on speech units have made huge progress in generating naturalistic speech, including non-verbal vocalizations. However, the generated speech samples often lack semantic coherence. In this pape
Externí odkaz:
http://arxiv.org/abs/2501.00805
Effectively distinguishing the pronunciation correlations between different written texts is a significant issue in linguistic acoustics. Traditionally, such pronunciation correlations are obtained through manually designed pronunciation lexicons. In
Externí odkaz:
http://arxiv.org/abs/2501.00804
In robotic bimanual teleoperation, multimodal sensory feedback plays a crucial role, providing operators with a more immersive operating experience, reducing cognitive burden, and improving operating efficiency. In this study, we develop an immersive
Externí odkaz:
http://arxiv.org/abs/2501.00822
Autor:
Chen, Gaofeng, Zhang, Yaoduo, Huang, Li, Wang, Pengfei, Zhang, Wenyu, Zeng, Dong, Ma, Jianhua, He, Ji
Supervised deep-learning (SDL) techniques with paired training datasets have been widely studied for X-ray computed tomography (CT) image reconstruction. However, due to the difficulties of obtaining paired training datasets in clinical routine, the
Externí odkaz:
http://arxiv.org/abs/2501.01456