Zobrazeno 1 - 10
of 562
pro vyhledávání: '"Xiaodong LIANG"'
Publikováno v:
npj Computational Materials, Vol 10, Iss 1, Pp 1-11 (2024)
Abstract Crystalline solids play a fundamental role in a host of materials and technologies, ranging from pharmaceuticals to renewable energy. The thermodynamic properties of these solids are crucial determinants of their stability and therefore thei
Externí odkaz:
https://doaj.org/article/965bd129c1ea430292c5a3a9072e55b7
Autor:
Ye Ge, Yan Zhou, Peng Peng, Yuanguo Li, Miaotong Huo, Jing Liu, Jiantao Yu, Peipei Shao, Hualin Xu, Xiaodong Liang, Qiucheng Yao, Yuwei Gao
Publikováno v:
Poultry Science, Vol 103, Iss 11, Pp 104228- (2024)
ABSTRACT: Avian paramyxoviruses (APMV) belong to the subfamily Avulavirinae of the family Paramyxoviridae and include 22 distinct subtypes or serotypes (1–22). Avian paramyxovirus serotype 12 (APMV-12) is found sporadically in wild birds worldwide,
Externí odkaz:
https://doaj.org/article/1c3114eafa2f43eb8abd92903e404965
Publikováno v:
Pifu-xingbing zhenliaoxue zazhi, Vol 31, Iss 4, Pp 276-280 (2024)
Malassezia is a group of resident fungi on the skin, which can cause diseases under certain conditions. Among the multiple complicated factors involved in the pathogenesis, secreted proteases of Malassezia are the key factors. Secreted proteases are
Externí odkaz:
https://doaj.org/article/e08f88fabbfd4d0d94691b67f81029df
Autor:
Ruiqi Liu, Yanwei Lu, Jing Li, Weiping Yao, Jiajun Wu, Xiaoyan Chen, Luanluan Huang, Ding Nan, Yitian Zhang, Weijun Chen, Ying Wang, Yongshi Jia, Jianming Tang, Xiaodong Liang, Haibo Zhang
Publikováno v:
Cell Death and Disease, Vol 15, Iss 4, Pp 1-14 (2024)
Abstract Annexin A2 (ANXA2) is a widely reported oncogene. However, the mechanism of ANXA2 in esophageal cancer is not fully understood. In this study, we provided evidence that ANXA2 promotes the progression of esophageal squamous cell carcinoma (ES
Externí odkaz:
https://doaj.org/article/9055ed7ea07e49839355d3bf6029374b
Publikováno v:
IEEE Access, Vol 12, Pp 114795-114808 (2024)
A multi-microgrid (MMG) consists of several individual microgrids (MGs) within a distribution system to improve the system’s stability and reliability. A MMG can operate in grid-connected or island mode and requires advanced control techniques and
Externí odkaz:
https://doaj.org/article/52cff38669b94740bc2bebac478ad9ea
Publikováno v:
IEEE Access, Vol 12, Pp 108472-108483 (2024)
The dissolved gas analysis (DGA) data play a crucial role in evaluating the transformer health index (HI). In recent years, data-driven approaches have attracted significant research interest for the HI prediction with various health condition data.
Externí odkaz:
https://doaj.org/article/f712acb67b72456db24d03eb12e14f21
Publikováno v:
IEEE Access, Vol 12, Pp 71184-71204 (2024)
The Volt/Var optimization (VVO) enables advanced control strategy development for voltage regulation. With the recent advancement of data-driven approaches and communication infrastructure, realtime decision-making through VVO can effectively address
Externí odkaz:
https://doaj.org/article/0cf266e1ef3b48de886d5506c75633a5
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023)
Abstract The relationship between total lymphocyte counts (TLCs) and survival is not well documented in rectal cancer. This study aimed to investigate the association between TLCs and disease-free survival (DFS) and identify factors associated with l
Externí odkaz:
https://doaj.org/article/4f9efc710ec0492a94e954d8e49f5e8b
Autor:
Dehe Wang, Xiao Hu, Hanzhe Ye, Yue Wang, Qian Yang, Xiaodong Liang, Zilin Wang, Yifan Zhou, Miaomiao Wen, Xueyan Yuan, Xiaomin Zheng, Wen Ye, Boyu Guo, Mayila Yusuyin, Eugenia Russinova, Yu Zhou, Kun Wang
Publikováno v:
Genome Biology, Vol 24, Iss 1, Pp 1-28 (2023)
Abstract Background The epidermis of cotton ovule produces fibers, the most important natural cellulose source for the global textile industry. However, the molecular mechanism of fiber cell growth is still poorly understood. Results Here, we develop
Externí odkaz:
https://doaj.org/article/69e6a04be8d346b3a5d6eb9014f46673
Publikováno v:
IEEE Access, Vol 11, Pp 118878-118889 (2023)
With increasing penetration of wind power, accurate prediction of wind speed is essential for planning and operation of power grids. In this paper, a novel two-dimensional (2D) convolutional neural network (CNN)-based wind speed forecasting technique
Externí odkaz:
https://doaj.org/article/dc61cf9d9b6f4cf88309433391cd61c8