Anticipated more frequent extreme events due to changes in global climatic variability requires adaptation of crop species to multi-occurrence abiotic stresses hereby sustaining the food security. Priming, by pre-expo...Anticipated more frequent extreme events due to changes in global climatic variability requires adaptation of crop species to multi-occurrence abiotic stresses hereby sustaining the food security. Priming, by pre-exposure of plants to an eliciting factor, enables plants to be more tolerant to later biotic or abiotic stress events. Priming induced “stress memory” exists in both present generation and the offspring. Thus, priming is suggested to be a promising strategy for plants to cope with the abiotic stresses under global change scenarios. In this review, the underlying physiological and molecular mechanisms of priming induced enhancement of stress tolerance to the major abiotic stresses of drought and waterlogging, and high and low temperature in crop plants were discussed, and the potential to utilize the priming effect for sustaining crop productivity in future climates was also suggested.展开更多
Vortex induced vibration(VIV)is a challenge in ocean engineering.Several devices including fairings have been designed to suppress VIV.However,how to optimize the design of suppression devices is still a problem to be...Vortex induced vibration(VIV)is a challenge in ocean engineering.Several devices including fairings have been designed to suppress VIV.However,how to optimize the design of suppression devices is still a problem to be solved.In this paper,an optimization design methodology is presented based on data-driven models and genetic algorithm(GA).Data-driven models are introduced to substitute complex physics-based equations.GA is used to rapidly search for the optimal suppression device from all possible solutions.Taking fairings as example,VIV response database for different fairings is established based on parameterized models in which model sections of fairings are controlled by several control points and Bezier curves.Then a data-driven model,which can predict the VIV response of fairings with different sections accurately and efficiently,is trained through BP neural network.Finally,a comprehensive optimization method and process is proposed based on GA and the data-driven model.The proposed method is demonstrated by its application to a case.It turns out that the proposed method can perform the optimization design of fairings effectively.VIV can be reduced obviously through the optimization design.展开更多
基金supported by the National Key Research andDevelopment Program of China (2016YFD0300107)the National Natural Science Foundation of China (31325020, 31401326, 31471445, 31771693)+3 种基金the earmarked fund for China Agriculture Research System (CARS-03)the Project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, Chinathe Fundamental Research Funds for the Central Universities, China (KJQN201505)the Jiangsu Collaborative Innovation Center for Modern Crop Production, China (JCIC-MCP)
文摘Anticipated more frequent extreme events due to changes in global climatic variability requires adaptation of crop species to multi-occurrence abiotic stresses hereby sustaining the food security. Priming, by pre-exposure of plants to an eliciting factor, enables plants to be more tolerant to later biotic or abiotic stress events. Priming induced “stress memory” exists in both present generation and the offspring. Thus, priming is suggested to be a promising strategy for plants to cope with the abiotic stresses under global change scenarios. In this review, the underlying physiological and molecular mechanisms of priming induced enhancement of stress tolerance to the major abiotic stresses of drought and waterlogging, and high and low temperature in crop plants were discussed, and the potential to utilize the priming effect for sustaining crop productivity in future climates was also suggested.
基金supported by the National Natural Science Foundation of China(Grant No.51809279)the Major National Science and Technology Program(Grant No.2016ZX05028-001-05)+1 种基金Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT14R58)the Fundamental Research Funds for the Central Universities,that is,the Opening Fund of National Engineering Laboratory of Offshore Geophysical and Exploration Equipment(Grant No.20CX02302A).
文摘Vortex induced vibration(VIV)is a challenge in ocean engineering.Several devices including fairings have been designed to suppress VIV.However,how to optimize the design of suppression devices is still a problem to be solved.In this paper,an optimization design methodology is presented based on data-driven models and genetic algorithm(GA).Data-driven models are introduced to substitute complex physics-based equations.GA is used to rapidly search for the optimal suppression device from all possible solutions.Taking fairings as example,VIV response database for different fairings is established based on parameterized models in which model sections of fairings are controlled by several control points and Bezier curves.Then a data-driven model,which can predict the VIV response of fairings with different sections accurately and efficiently,is trained through BP neural network.Finally,a comprehensive optimization method and process is proposed based on GA and the data-driven model.The proposed method is demonstrated by its application to a case.It turns out that the proposed method can perform the optimization design of fairings effectively.VIV can be reduced obviously through the optimization design.
