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Shaofang Nie
Researcher at Huazhong University of Science and Technology
Publications - 41
Citations - 1821
Shaofang Nie is an academic researcher from Huazhong University of Science and Technology. The author has contributed to research in topics: Stochastic programming & Medicine. The author has an hindex of 18, co-authored 35 publications receiving 1516 citations. Previous affiliations of Shaofang Nie include Chinese Ministry of Education.
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An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty
TL;DR: In this article, an interval-parameter multi-stage stochastic linear programming (IMSLP) method has been developed for water resources decision making under uncertainty, where penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised water allocation targets are violated.
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Regulatory T cells ameliorate cardiac remodeling after myocardial infarction
Tingting Tang,Jing Yuan,Zhengfeng Zhu,Wen-cai Zhang,Hong Xiao,Ni Xia,Xin-Xin Yan,Shaofang Nie,Juan Liu,Su-Feng Zhou,Jing Jing Li,Rui Yao,Mengyang Liao,Xin Tu,Yuhua Liao,Xiang Cheng +15 more
TL;DR: Data demonstrate that Treg cells serve to protect against adverse ventricular remodeling and contribute to improve cardiac function after myocardial infarction via inhibition of inflammation and direct protection of cardiomyocytes.
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ITCLP: An inexact two-stage chance-constrained program for planning waste management systems
TL;DR: In this article, an inexact two-stage chance-constrained linear programming (ITCLP) method is developed for planning waste management systems, which can tackle uncertainties presented as both probability distributions and discrete intervals.
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Inexact multistage stochastic integer programming for water resources management under uncertainty.
TL;DR: The inexact multistage stochastic integer programming (IMSIP) method can help water resources managers to identify desired system designs against water shortage and for flood control with maximized economic benefit and minimized system- failure risk.
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IFMP: Interval-fuzzy multistage programming for water resources management under uncertainty
TL;DR: An interval-fuzzy multistage programming (IFMP) method is developed for water resources management under uncertainty by allowing uncertainties presented as discrete intervals, fuzzy sets, and probability distributions to be effectively incorporated within its optimization framework.