
Li Dai
Articles
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Apr 15, 2024 |
dialnet.unirioja.es | Dong Jiang |Yuanyuan Wang |Hui Sun |Li Dai
DONG JIANG[1];YUANYUAN WANG[1];HUI SUN[1];LI YI DAI[1][1]East China Normal University Department of Chemistry East Shanghai Key Laboratory of Green Chemistry and Chemical ProcessLocalización: Journal of the Chilean Chemical Society, ISSN-e 0717-9707, ISSN 0717-9324, Vol. 52, Nº. 4, 2007, págs.
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Apr 2, 2024 |
onlinelibrary.wiley.com | Jinxian Wu |Li Dai |Yuanqing Xia
CONFLICT OF INTEREST STATEMENT The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted. REFERENCES 1. Architectures for distributed and hierarchical model predictive control–a review. J Process Control. 2009; 19(5): 723-731. 2, . Distributed model predictive control: an overview and roadmap of future research opportunities.
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Feb 22, 2024 |
mdpi.com | Li Dai |Li Zhao |Di Xu |Chen Yang
All articles published by MDPI are made immediately available worldwide under an open access license. No specialpermission is required to reuse all or part of the article published by MDPI, including figures and tables. Forarticles published under an open access Creative Common CC BY license, any part of the article may be reused withoutpermission provided that the original article is clearly cited. For more information, please refer tohttps://www.mdpi.com/openaccess.
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Dec 5, 2023 |
onlinelibrary.wiley.com | Min Lin |Yuanqing Xia |Zhongqi Sun |Li Dai
CONFLICT OF INTEREST STATEMENT The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. REFERENCES 1, . Handbook of Model Predictive Control. Springer; 2018. 2, , , . Tube-based robust nonlinear model predictive control. Int J Robust Nonlinear Control. 2011; 21(11): 1341-1353. 3, . Stabilizing conditions for model predictive control. Int J Robust Nonlinear Control.
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Jul 1, 2023 |
pubs.acs.org | Xue Dong |Qingze Zeng |Li Dai |Xiang Ren
When consumed, excess progesterone (P4)─found in food and the environment─can lead to severe illnesses in humans. Therefore, quantitative analysis of P4 is critical for identifying its hazardous levels. In this study, a novel signal “on-amplified-off” P4 detection mode was proposed, which was based on the utilization of hafnium oxide (HfO2) as a unique electrochemiluminescence (ECL) emitter, produced by calcining UiO-66(Hf). This is the first time that HfO2 has been used as an ECL emitter.
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