Zobrazeno 1 - 10
of 164
pro vyhledávání: '"LIU Zejian"'
Autor:
Chen Yijun, Lu Zhujin, Feng Jiaxin, Chen Zefeng, Liu Zejian, Wang Xiuqi, Yan Huichao, Gao Chunqi
Publikováno v:
Acta Biochimica et Biophysica Sinica, Vol 55, Pp 1213-1221 (2023)
Roof plate-specific spondin 1 (R-spondin1, RSPO1) is a Wnt/β-catenin signaling pathway activator that binds with Wnt ligands to stimulate the Wnt/β-catenin signaling pathway, which is key to hair regeneration. However, it is not clear whether recom
Externí odkaz:
https://doaj.org/article/33dd55d0fb8a4bc9bcb1ae71ef42ea3c
Publikováno v:
Meikuang Anquan, Vol 53, Iss 2, Pp 46-52 (2022)
The intensity of air leakage not only increases the risk of spontaneous combustion of coal, but also is the cause of coal fire disasters caused by spontaneous combustion of coal left in the goaf. Aim to find the influence of the air leakage intensity
Externí odkaz:
https://doaj.org/article/255f0322b89a478c9e7c0c587b4de5d1
Publikováno v:
Gong-kuang zidonghua, Vol 47, Iss 9, Pp 91-95 (2021)
The existing researches do not consider that coal of different particle sizes in the goaf is affected by the axial stress generated by the collapsed coal rock and the residual coal pillars, which will cause major changes in the coal permeability, fra
Externí odkaz:
https://doaj.org/article/9125e4919f2740beb9eb3616f7476904
Autor:
Zhu, Zeyu, Li, Fanrong, Li, Gang, Liu, Zejian, Mo, Zitao, Hu, Qinghao, Liang, Xiaoyao, Cheng, Jian
Graph Neural Networks (GNNs) are becoming a promising technique in various domains due to their excellent capabilities in modeling non-Euclidean data. Although a spectrum of accelerators has been proposed to accelerate the inference of GNNs, our anal
Externí odkaz:
http://arxiv.org/abs/2311.09775
Autor:
Zhu, Zeyu, Li, Fanrong, Mo, Zitao, Hu, Qinghao, Li, Gang, Liu, Zejian, Liang, Xiaoyao, Cheng, Jian
As graph data size increases, the vast latency and memory consumption during inference pose a significant challenge to the real-world deployment of Graph Neural Networks (GNNs). While quantization is a powerful approach to reducing GNNs complexity, m
Externí odkaz:
http://arxiv.org/abs/2302.00193
Autor:
Liu, Zejian, Li, Meng
Derivatives are a key nonparametric functional in wide-ranging applications where the rate of change of an unknown function is of interest. In the Bayesian paradigm, Gaussian processes (GPs) are routinely used as a flexible prior for unknown function
Externí odkaz:
http://arxiv.org/abs/2210.11626
Publikováno v:
In Journal of Building Engineering 1 November 2024 96
Autor:
Liu, Zejian1,2 (AUTHOR) liu.zejian@hgnyjs.com, Yang, Ping1 (AUTHOR) eppyang@scut.edu.cn, Zhang, Peng1 (AUTHOR) zp1979377074@sina.com, Lin, Xu3 (AUTHOR) 18814091950@163.com, Wei, Jiaxi4 (AUTHOR) 17791029549@163.com, Li, Ning4 (AUTHOR) lining83@xaut.edu.cn
Publikováno v:
Sensors (14248220). Aug2024, Vol. 24 Issue 16, p5115. 17p.
Autor:
Liu, Zejian1,2 (AUTHOR) liu.zejian@hgnyjs.com, Li, Fengneng1,2 (AUTHOR) 202221016031@mail.scut.edu.cn, Yang, Ping1,2 (AUTHOR) eppyang@scut.edu.cn, Lin, Xu3 (AUTHOR) linxu@gpdc.gd.csg.cn, Zhang, Guozun4,5 (AUTHOR) zhangguozun321@stud.tjut.edu.cn
Publikováno v:
Energies (19961073). Jul2024, Vol. 17 Issue 13, p3282. 13p.
Autor:
Liu, Zejian, Liu, Gongqi, Cheng, Leilei, Gu, Jing, Yang, Jialiang, Yuan, Haoran, Chen, Yong, Wu, Yufeng
Publikováno v:
In Separation and Purification Technology 5 May 2024 335