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        Ethylene increases accumulation of compatible solutes and decreases oxidative stress to improve plant tolerance to water stress in Arabidopsis

        Mengying Cui,Yingchao Lin,YUANGANG ZU,Thomas Efferth,Dewen Li,Zhonghua Tang 한국식물학회 2015 Journal of Plant Biology Vol.58 No.3

        Ethylene (ET) plays an important role as signal transducer in plants in response to environmental stimuli. Under water deficient conditions, fine adjustment of osmosis and redox states through phytohormones is vital for plant resistance to drought. Here, physiological and cellular responses of ET insensitive mutants (ein2-5 and ein3-1) were analyzed under water deficiency stimulated by polyethylene glycol 6000 (PEG-6000), and compared with wild type plants (Col-0) as controls. The accumulation of compatible solutes was higher in Col-0 than in ein2-5 and ein3-1. In Col-0 plants, water stress also increased transcription of P5CS1, which encoded a key rate-limiting enzyme in proline biosynthesis. These results suggested that ET signaling is involved in increasing the up-regulation of soluble sugar and proline accumulation to adjust to osmotic stress. In addition, oxidative stress was higher in ET defective mutants than in Col-0 wild-type plants. Meanwhile, increased activities of the reactive oxygen species (ROS)-scavenging enzymes superoxide dismutase (SOD) and peroxidase (POD) were observed in ET insensitive mutants, indicating aggravated oxidative stress in ET-defective plants under drought. In conclusion, ET signaling is involved in modulating plant oxidative stress under drought conditions.

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        Joint Estimation of Vehicle State and Parameter Based on Maximum Correntropy Adaptive Unscented Kalman Filter

        Zhang Feng,Feng Jingan,Qi Dengliang,Liu Ya,Shao Wenping,Qi Jiaao,Lin Yuangang 한국자동차공학회 2023 International journal of automotive technology Vol.24 No.6

        To address the problem of poor robustness and accuracy of vehicle state and parameter estimation by conventional Kalman filter in the non-Gaussian environments, a three-degree-of-freedom vehicle model with an improved Dugoff tire model is established and a joint estimator of vehicle state and parameter is designed using the Maximum Correntropy (MC) adaptive unscented Kalman filter (AUKF) algorithm in order to simultaneously estimate and identify the yaw rate, longitudinal vehicle speed, lateral vehicle speed, vehicle mass and rotational inertia. The proposed joint estimator algorithm was validated by Simulink/CarSim simulation testbed under Double Lane Change and Sine Wave Steering Input conditions. The results show that MC combined with AUKF (MCAUKF) algorithm has higher estimation accuracy and better convergence compared to the unscented Kalman filter (UKF) and the MC combined with UKF (MCUKF) in non-Gaussian environments, and the MCAUKF estimator is more suitable for state estimation and parameter identification of real vehicles.

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