Zobrazeno 1 - 10
of 452
pro vyhledávání: '"Chunxiang Zhu"'
Autor:
Junfei Weng, Chunxiang Zhu, Binchao Zhao, Wenxiang Tang, Xingxu Lu, Fangyuan Liu, Mudi Wu, Yong Ding, Pu-Xian Gao
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract To enhance the reaction kinetics without sacrificing activity in porous materials, one potential solution is to utilize the anisotropic distribution of pores and channels besides enriching active centers at the reactive surfaces. Herein, by
Externí odkaz:
https://doaj.org/article/b66fe372b57a4055a5c892b8851dfc8c
Autor:
Lingling Li, Chunyi Gu, Xiaojiao Wang, Wenli Zhu, Chunxiang Zhu, Hui Min, Jiangnan Wu, Xinli Zhu
Publikováno v:
BMJ Open, Vol 14, Iss 5 (2024)
Objective To investigate the status of the midwifery workforce and childbirth services in China and to identify the association between midwife staffing and childbirth outcomes.Design A descriptive, multicentre cross-sectional survey.Setting Maternit
Externí odkaz:
https://doaj.org/article/e3b0cee7e4454247a83ef954d56e81cd
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 2577-2590 (2023)
Accurate estimating the state of health (SOH) of lithium-ion battery plays a significant role in the safe operation of electric vehicles. With the development of deep learning, neural network-based methods have attracted much attention from researche
Externí odkaz:
https://doaj.org/article/cd0230375a6e400bafe21e72c701bfc1
Publikováno v:
Energies, Vol 17, Iss 12, p 2797 (2024)
The LSTM neural network is often employed for time-series data prediction due to its strong nonlinear mapping capability and memory effect, allowing for better identification of complex data characteristics. However, the large computational workload
Externí odkaz:
https://doaj.org/article/ee3171de4cf74c6fb9a776a1f1521132
Publikováno v:
IEEE Journal of the Electron Devices Society, Vol 11, Pp 269-273 (2023)
The in-memory logic computing has been intensively studied as being considered as an important scenario to address the power-consumption issue posed by modern computers based on the von Neumann architecture. However, the realization of in-memory logi
Externí odkaz:
https://doaj.org/article/e91417a1146545deb0313a8565012f82
Publikováno v:
PeerJ, Vol 10, p e13965 (2022)
Background Fatigue is one of the most prevalent symptoms among pregnant women. In patients with various diseases, pro-inflammatory cytokines are associated with fatigue; however, such associations are unknown in pregnant women. Objectives The objecti
Externí odkaz:
https://doaj.org/article/c6cddc3cfbfb405f9caf8c3648333c58
Autor:
Zhaowei Zhang, Xinghao Zhang, Zhiwei He, Chunxiang Zhu, Wenlong Song, Mingyu Gao, Yining Song
Publikováno v:
Frontiers in Energy Research, Vol 10 (2022)
Accurate estimation of the state of charge plays a very important role in ensuring the safe and effective operation of battery lithium-ion batteries and is one of the most important state parameters. However, the estimation method of state of charge
Externí odkaz:
https://doaj.org/article/aec2071690c14b9eb7e3102dfc331955
Autor:
Jingxuan Wei, Ying Li, Lin Wang, Wugang Liao, Bowei Dong, Cheng Xu, Chunxiang Zhu, Kah-Wee Ang, Cheng-Wei Qiu, Chengkuo Lee
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Here, graphene-based plasmonic metamaterials are used to generate an artificial bulk photovoltaic effect, enabling the realization of mid-infrared photodetectors with enhanced responsivity and calibration-free polarization detection at room temperatu
Externí odkaz:
https://doaj.org/article/448ed8cf30f44d738737b96e2a4ee67f
Publikováno v:
BMC Pregnancy and Childbirth, Vol 20, Iss 1, Pp 1-10 (2020)
Abstract Background There is an increasing global trend towards the widespread over-medicalisation of labour and childbirth. The present study aimed to investigate pregnant women’s clinical characteristics, intrapartum interventions, duration of la
Externí odkaz:
https://doaj.org/article/4f1bac9e166d4b18b297052329c1171b
Publikováno v:
Energies, Vol 16, Iss 2, p 803 (2023)
The time-varying, dynamic, nonlinear, and other characteristics of lithium-ion batteries, as well as the capacity regeneration phenomenon, leads to the low accuracy of the traditional deep learning models in predicting the remaining useful life of li
Externí odkaz:
https://doaj.org/article/96d744ff179646a98336cf84cc35bed5