Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Xinmeng Huang"'
Publikováno v:
International Dental Journal, Vol 74, Iss 6, Pp 1248-1257 (2024)
Introduction and aims: Altering the position and orientation of the root canal access cavity passway, or modifying the reduction of dentin volume, can influence the strength of dentition. This study aimed to compare the effects of different access ca
Externí odkaz:
https://doaj.org/article/02476f7bd26a4ab0920159f4c2e1a852
Publikováno v:
Results in Physics, Vol 47, Iss , Pp 106364- (2023)
In recent years, metamaterials have been widely used as a new type of optoelectronic device materials, such as optical stealth, holographic imaging, and metamaterial absorbers. In particular, the research of metamaterial absorbers with multi-narrowba
Externí odkaz:
https://doaj.org/article/588a8cef38b14f3e952380e6ebf0b092
Autor:
Wanli Zang, Mingqing Fang, Haohao Chen, Xinmeng Huang, Dong Li, Jin Yan, Heng Shu, Mingyuan Zhao
Publikováno v:
Frontiers in Public Health, Vol 11 (2023)
ObjectiveThis study aims to evaluate the intervention effect of concurrent training on children with malignant tumors to provide evidence for prescribing exercise for children with malignant tumors.MethodsTwelve databases were searched from inception
Externí odkaz:
https://doaj.org/article/dd0dd5c5ff9a469292723066f29f3e84
Publikováno v:
Journal of Materials Science & Technology. 147:16-25
Publikováno v:
Advanced Composites and Hybrid Materials. 4:1398-1412
A series of CeO2/porous carbon composites are successfully prepared by hydrothermal method and subsequent pyrolysis method by using pine cone as biomass carbon source. Besides, the effect of cerium source on the electromagnetic (EM) parameters and el
Autor:
Donghwan Lee1 DH7401@SAS.UPENN.EDU, Xinmeng Huang1 XINMENGH@SAS.UPENN.EDU, Hassani, Hamed2 HASSANI@SEAS.UPENN.EDU, Dobriban, Edgar3 DOBRIBAN@WHARTON.UPENN.EDU
Publikováno v:
Journal of Machine Learning Research. 2023, Vol. 24, p1-72. 72p.
Publikováno v:
Journal of Mathematical Analysis and Applications. 490:124211
Many iterative methods in optimization are fixed-point iterations with averaged operators. As such methods converge at an $\mathcal{O}(1/k)$ rate with the constant determined by the averagedness coefficient, establishing small averagedness coefficien
Autor:
Kun Yuan1 KUNYUAN@PKU.EDU.CN, Alghunaim, Sulaiman A.2 SULAIMAN.ALGHUNAIM@KU.EDU.KW, Xinmeng Huang3 XINMENGH@SAS.UPENN.EDU
Publikováno v:
Journal of Machine Learning Research. 2023, Vol. 24, p1-53. 53p.