Search

Your search keyword '"Ma, Jinling"' showing total 267 results
Start Over Author "Ma, Jinling"
267 results on '"Ma, Jinling"'

6. Antiviral effectiveness and survival correlation of azvudine and nirmatrelvir/ritonavir in elderly severe patients with COVID-19: a retrospective real-world study

Author

Wang, Shuxia, Sun, Jin, Zhang, Xin, Li, Man, Qin, Bangguo, Liu, Miao, Zhang, Nan, Wang, Shengshu, Zhou, Tingyu, Zhang, Wei, Ma, Cong, Deng, Xinli, Bai, Yongyi, Qu, Geping, Liu, Lin, Shi, Hui, Zhou, Bo, Li, Ke, Yang, Bo, Li, Suxia, Wang, Fan, Ma, Jinling, Zhang, Lu, Wang, Yajuan, An, Li, Liu, Wenhui, Chang, Qing, Zhang, Ru, Yin, Xi, Yang, Yang, Ao, Qiangguo, Ma, Qiang, Yan, Shuangtong, Huang, Haili, Song, Peng, Gao, Linggen, Lu, Wenning, Xu, Lining, Lei, Li, Wang, Keyu, Zhang, Qi, Song, Qing, Zhang, Zhijian, Fang, Xiangqun, He, Yao, Li, Tianzhi, and Zhu, Ping

Published
2024
Full Text
View/download PDF

15. Machine Learning Optimization of Target Velocity Curves in Hybrid Electric Trains.

Author

Ma, Jinling, Zhang, Jiye, and Sui, Hao

Subjects
*MACHINE learning, *HEURISTIC algorithms, *BLENDED learning, *ENERGY consumption, *VELOCITY
Abstract

This study tackles the challenge of refining the target velocity curves for hybrid electric trains, governed primarily by onboard Automatic Train Operation (ATO) systems. These systems take into account various factors, such as the interstation line conditions and the specific traction and braking characteristics of hybrid trains. Traditional approaches, which rely on fixed speed–position sequences to navigate trains and ensure safety through the Automatic Train Protection (ATP) system, struggle to adapt to dynamic environmental changes, leading to compromised operational efficiency. In response, our research adopts a machine learning framework, with a particular emphasis on reinforcement learning, to devise a real-time, flexible optimization model for determining the train’s target velocity curve. This model harnesses the potential of the double-depth Q network to enhance the optimization process. The primary objective is to improve the punctuality and energy efficiency of train operations while simultaneously increasing passenger comfort through better adaptation to environmental variations. Simulation results demonstrate that the newly optimized target velocity curve notably diminishes the on-time errors for hybrid trains and achieves approximately 0.98% in energy savings compared to traditional heuristic algorithms. These outcomes highlight the significant advantages of integrating sophisticated machine learning techniques like double-depth Q network to boost the efficiency and sustainability of hybrid electric train operations. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

21. Mo‐Doped BiVO4 as a Fast Electrode Reaction Kinetics Catalyst in Na−O2 Batteries.

Author

Li, Minglu, Wang, Jiazhi, He, Wei, Zhang, Xiong, Zhang, Huijuan, Ma, Jinling, and Wang, Yu

Subjects
ELECTRODE reactions, CHEMICAL kinetics, ELECTRON work function, SODIUM ions, CATALYSTS, CATALYTIC activity
Abstract

The highly insulated solid discharge products in sodium‐oxygen (Na−O2) batteries induce large polarization and thus heavily threaten their cycle life. Controlment of discharge products taking efficient catalyst is a best way to solve this problem. Here, Mo‐doped BiVO4 as the catalyst produces large amounts of carrier, thus boosting the battery reaction and reducing the overpotential under the light assistance. Compared with the BiVO4 without Mo doping, the doped one has a lower recombination of photogenerated carriers, thus benefiting a large polarization suppression and Na−O2 batteries running for over 270 cycles under 3.65 V as well as a fine rate performance. Besides, Mo doping reduces the size of BiVO4, beneficial for the carrier transportation and more reactions due to the large specific surface area. Experiment combined with theoretical calculation shows that Mo doping is advantageous to enhancing catalytic activity of BiVO4 due to a lower work function for easier electron extraction, thus enhancing Na2O2 decomposition capability. This work undoubtedly inspires photocatalysts′ use for solving the insulated solid discharge products decomposition in metal‐O2 batteries and provides a guide for other photocatalysts possibilities. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

36. In–Sb Covalent Bonds over Sb2Se3/In2Se3Heterojunction for Enhanced Photoelectrochemical Water Splitting

Author

Wang, Junyu, He, Jialing, Ma, Jinling, Wang, Xiaodong, Feng, Chuanzhen, Zhou, Qingxia, Zhang, Huijuan, and Wang, Yu

Abstract

Antimony selenide is a promising P-type photocatalyst, but it has a large number of deep energy level defects, leading to severe carrier recombination. The construction of a heterojunction is a common way to resolve this problem. However, the conventional heterojunction system inevitably introduces interface defects. Herein, we employ in situ synthesis to epitaxially grow In2Se3nanosheets on Sb2Se3nanorods and form In–Sb covalent interfacial bonds. This petal-shaped heterostructure reduced interface defects and enhanced the efficiency of carrier separation and transport. In this work, the photocurrent density in the proposed Sb2Se3/In2Se3photocathode is 0.485 mA cm–2at 0 VRHE, which is 30 times higher than that of pristine Sb2Se3and it has prominent long-term stability for 24 h without obvious decay. The results reveal that the synergy of the bidirectional built-in electric field constructed between In2Se3and Sb2Se3and the solid In–Sb interfacial bonds together build a high-efficiency transport channel for the photogenerated carriers that display enhanced photoelectrochemical (PEC) water-splitting performance. This work provides efficient guidance for reducing interface defects via the in situ synthesis and construction of interfacial bonds.

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results