Zobrazeno 1 - 10
of 61
pro vyhledávání: '"Ruofan, Zhang"'
Autor:
Jiaqi Zhang, Yahui Chen, Xin Guo, Xuan Li, Ruofan Zhang, Mengting Wang, Weiyun Zhu, Kaifan Yu
Publikováno v:
Journal of Animal Science and Biotechnology, Vol 15, Iss 1, Pp 1-16 (2024)
Abstract Background Weaning stress-induced diarrhea is widely recognized as being associated with gut microbiota dysbiosis. However, it has been challenging to clarify which specific intestinal microbiota and their metabolites play a crucial role in
Externí odkaz:
https://doaj.org/article/ccc3ff72c7fc440ab15552a9b1a8d550
Publikováno v:
Tongxin xuebao, Vol 44, Pp 103-111 (2023)
In order to alleviate the spectrum scarcity and capacity limitation of the current wireless system, the terahertz frequency band was introduced and the reconfigurable intelligent surface (RIS) was used for auxiliary communication to construct a downl
Externí odkaz:
https://doaj.org/article/72fef6d9b285411494eec90be802dfda
Autor:
Fatang CHEN, Ruofan ZHANG
Publikováno v:
Tongxin xuebao, Vol 44, Pp 70-78 (2023)
In order to meet the higher requirements of vehicle communication quality and spectral efficiency, a IoV resource allocation algorithm assisted by reconfigurable intelligent surface (RIS) was proposed.The RIS reflection coefficient matrix, power allo
Externí odkaz:
https://doaj.org/article/c90c87a78542493686f059a5934f42d6
Publikováno v:
Applied Sciences, Vol 14, Iss 13, p 5524 (2024)
Currently, few deep models are applied to pepper-picking detection, and existing generalized neural networks face issues such as large model parameters, prolonged training times, and low accuracy. To address these challenges, this paper proposes the
Externí odkaz:
https://doaj.org/article/a95c4af317dd4d3eacfee578dc8f3391
Autor:
Ruofan Zhang, Lixia Xi, Jiacheng Wei, Jiayun Deng, Shucheng Du, Wenbo Zhang, Xiaoguang Zhang, Xiaosheng Xiao
Publikováno v:
IEEE Photonics Journal, Vol 15, Iss 3, Pp 1-8 (2023)
Nonlinear frequency division multiplexing (NFDM) system is an optional candidate to overcome the fiber nonlinearity limit. A full-spectrum modulated NFDM system, modulating data on combined continuous spectrum (CS) and discrete spectrum (DS) together
Externí odkaz:
https://doaj.org/article/d25ed48f10874f0790e3065ba3967261
Publikováno v:
Pharmacological Research, Vol 194, Iss , Pp 106865- (2023)
Succinate is a vital signaling metabolite produced by the host and gut microbiota. Succinate has been shown to regulate host metabolic homeostasis and inhibit obesity-associated inflammation in macrophages by engaging its cognate receptor, SUCNR1. Ho
Externí odkaz:
https://doaj.org/article/46611c1287c54e7597e88fb926ec9465
Publikováno v:
Sensors, Vol 24, Iss 8, p 2464 (2024)
Deep learning methodologies employed for biomass prediction often neglect the intricate relationships between labels and samples, resulting in suboptimal predictive performance. This paper introduces an advanced supervised contrastive learning techni
Externí odkaz:
https://doaj.org/article/0a8cff5e78d44614983f5fff1dff2bea
Publikováno v:
Space: Science & Technology, Vol 3 (2023)
This paper reports a numerical research on MEMS (microelectromechanical system) micronozzles through multiphysics coupling simulation along with design optimization based on simulation results. The micronozzle, which is a core component of the electr
Externí odkaz:
https://doaj.org/article/6d30c2b1822e4ea7ac159e1b6b0d6c28
Autor:
Ruofan Zhang, Guowen Huang, Yuting Ren, Haifeng Wang, Yanxin Ye, Jiaqing Guo, Mengting Wang, Weiyun Zhu, Kaifan Yu
Publikováno v:
Frontiers in Nutrition, Vol 9 (2022)
As a microbial tryptophan metabolite, indole-3-carboxaldehyde (ICA) has been suggested to confer benefits to host, such as regulation of intestinal barrier function. This study aimed to elucidate the role of ICA in modulating intestinal homeostasis v
Externí odkaz:
https://doaj.org/article/15cf6e72c3704db7bcf836e0bc07b7d5
Publikováno v:
Applied Sciences, Vol 13, Iss 9, p 5589 (2023)
The current neural networks for tomato leaf disease recognition have problems such as large model parameters, long training time, and low model accuracy. To solve these problems, a lightweight convolutional neural network (LBFNet) is proposed in this
Externí odkaz:
https://doaj.org/article/4653dd5e07674f31960fe02f2deb3ca9