Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Haibing Zhao"'
Publikováno v:
Medžiagotyra, Vol 29, Iss 1, Pp 73-78 (2023)
In this work, the vanillin cross-linked chitosan microspheres were firstly prepared by emulsion chemical cross-linking method with vanillin as a cross-linker. Subsequently, with polyvinylpyrrolidone as a nanoparticle stabilizer and dispersant, silver
Externí odkaz:
https://doaj.org/article/43c870e6920d4e17b0604b4bafbf31b0
Autor:
Xiahong Xu, Yan Sui, Wentong Chen, Shaohui Xiong, Yuntong Li, Xiaodan Li, Wei Huang, Haibing Zhao, Gangyong Zhou, Hongmei Chen, Hong Zhong
Publikováno v:
ACS Sustainable Chemistry & Engineering; 7/29/2024, Vol. 12 Issue 30, p11409-11418, 10p
Publikováno v:
Polymer Engineering & Science. 62:939-948
Publikováno v:
2022 IEEE 34th International Conference on Tools with Artificial Intelligence (ICTAI).
Autor:
Haibing Zhao
Publikováno v:
Biometrika. 109:153-164
Summary Post-selection inference on thousands of parameters has attracted considerable research interest in recent years. Specifically, Benjamini & Yekutieli (2005) considered constructing confidence intervals after selection. They proposed adjusting
Autor:
Haibing Zhao
Publikováno v:
Communications in Statistics - Theory and Methods. 51:636-648
In this article, we propose two confidence intervals (CIs) for a single parameter, which can represent an effect in practice, through a Bayesian decision theoretic approach for different goals. One...
Publikováno v:
Journal of Macromolecular Science, Part A. 57:553-559
The use of weak bases as accelerators for reversible addition-fragmentation chain transfer radical polymerization (RAFT) of isoprene is demonstrated. Adding weak bases to RAFT polymerization, the c...
Autor:
Zhiying Xiao, Haibing Zhao
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
Statistics in medicineREFERENCES. 40(20)
Noncompliance issue is common in early phase clinical trials; and may lead to biased estimation of the intent-to-treat effect and incorrect conclusions for the clinical trial. In this work, we propose a Bayesian approach for sequentially monitoring t