Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Yinjie Ji"'
Publikováno v:
ACS Catalysis, 13 (6)
Methane conversion strategies that protect methanol via in situ esterification achieve higher yields compared to direct methane conversion without product protection; however, most of these high-yield systems operate under unfavorable conditions. To
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c763a7047be94123a243da28eb2dd53
Publikováno v:
Journal of Catalysis. 391:212-223
A series of unsupported Ni-Mo sulfide catalysts with varying Ni contents (0.13–0.72 molNi molNi+Mo-1) was post-synthetically treated with concentrated HCl to remove large crystallites of accessible NiSx. These sulfide particles inevitably form and
Autor:
Pengfei Xu, Yinjie Jia
Publikováno v:
Results in Engineering, Vol 22, Iss , Pp 102210- (2024)
Developing mathematical models for dynamic systems presents challenges in selecting state variables, crucial for minimizing computational operations during filter implementation. The paper addresses active identification of dynamic systems amid noise
Externí odkaz:
https://doaj.org/article/68c1c98ef1a34b02808e3c39a841bfa5
Autor:
Chi-Ming Liu, ZiChen Shao, XuZhou Chen, HanWu Chen, MengQiao Su, ZiWen Zhang, ZhengPing Wu, Peng Zhang, LiJie An, YinJie Jiang, Ai-Jun Ouyang
Publikováno v:
Saudi Pharmaceutical Journal, Vol 31, Iss 7, Pp 1219-1228 (2023)
Benign prostatic hyperplasia (BPH) is a common urinary disease among the elderly, characterized by abnormal prostatic cell proliferation. Neferine is a dibenzyl isoquinoline alkaloid extracted from Nelumbo nucifera and has antioxidant, anti-inflammat
Externí odkaz:
https://doaj.org/article/d6a77d813781480d844af31e551010b8
Autor:
Yinjie Jiang, Yemin Yu, Ming Kong, Yu Mei, Luotian Yuan, Zhengxing Huang, Kun Kuang, Zhihua Wang, Huaxiu Yao, James Zou, Connor W. Coley, Ying Wei
Publikováno v:
Engineering, Vol 25, Iss , Pp 32-50 (2023)
In recent years, there has been a dramatic rise in interest in retrosynthesis prediction with artificial intelligence (AI) techniques. Unlike conventional retrosynthesis prediction performed by chemists and by rule-based expert systems, AI-driven ret
Externí odkaz:
https://doaj.org/article/7b1ecaad58d04761aa0f03e1dc880d8e
Autor:
Yinjie Jiang, Yang Shen, Xun Chen, Lingling Niu, Boliang Li, Mingrui Cheng, Yadi Lei, Yilin Xu, Chongyang Wang, Xingtao Zhou, Xiaoying Wang
Publikováno v:
Eye and Vision, Vol 10, Iss 1, Pp 1-13 (2023)
Abstract Background Implantable collamer lens (ICL) has been widely accepted for its excellent visual outcomes for myopia correction. It is a new challenge in phakic IOL power calculation, especially for those with low and moderate myopia. This study
Externí odkaz:
https://doaj.org/article/69d1cab37ced4ad2b3db4be6b23f1db5
Autor:
Xun Chen, Huamao Miao, Mingrui Cheng, I-Chun Lin, Boliang Li, Yinjie Jiang, Yadi Lei, Xiaoying Wang, Xingtao Zhou
Publikováno v:
Frontiers in Medicine, Vol 10 (2023)
ObjectiveTo evaluate the effect of long-term rotation on astigmatism following Evolution-toric intraocular collamer lens (EVO-TICL) implantation.MethodsForty eyes of 22 patients were enrolled in this prospective study. Visual acuity, refractive param
Externí odkaz:
https://doaj.org/article/63d33d28a6b34ee48a46072ca770b862
Publikováno v:
Results in Engineering, Vol 15, Iss , Pp 100577- (2022)
This paper analyzed and compared the ergodic channel capacities of several typical channel systems (SISO, SIMO, MISO, MIMO) in independent identically distributed flat Rayleigh fading channels. The theoretical and simulation results show that the erg
Externí odkaz:
https://doaj.org/article/98eb1c73efa64fc9a8a85e203d381579
Autor:
Yinjie Jia, Pengfei Xu
Publikováno v:
IEEE Access, Vol 8, Pp 41213-41219 (2020)
Convolutive blind source separation (CBSS) is one of the main branches in the field of intelligent signal processing. Inspired by the thought of sliding discrete Fourier transform (DFT), an idea of the sliding Z-transform is introduced in the present
Externí odkaz:
https://doaj.org/article/3ff1dde9ead94d56b9ae5140e3f97274
Publikováno v:
IEEE Access, Vol 7, Pp 32400-32407 (2019)
Multi-object tracking has been a key research subject in many computer vision applications. We propose a novel approach based on multi-agent deep reinforcement learning (MADRL) for multi-object tracking to solve the problems in the existing tracking
Externí odkaz:
https://doaj.org/article/89b4cbbe3f0f42fba9a50ac100bff84b