The Pythium periplocum elicitin PpEli2 confers broad-spectrum disease resistance by triggering a novel receptor-dependent immune pathway in plants

Elicitins are microbe-associated molecular patterns produced by oomycetes to elicit plant defense.It is still unclear whether elicitins derived from non-pathogenic oomycetes can be used as bioactive molecules for disease control.Here,for the first time we identify and characterize an elicitin named PpEli2 from the soil-borne oomycete Pythium periplocum,which is a non-pathogenic mycoparasite colonizing the root ecosystem of diverse plant species.Perceived by a novel cell surface receptor-like protein,REli,that is conserved in various plants(e.g.tomato,pepper,soybean),PpEli2 can induce hypersensitive response cell death and an immunity response in Nicotiana benthamiana.Meanwhile,PpEli2 enhances the interaction between REli and its co-receptor BAK1.The receptor-dependent immune response triggered by PpEli2 is able to protect various plant species against Phytophthora and fungal infections.Collectively,our work reveals the potential agricultural application of non-pathogenic elicitins and their receptors in conferring broad-spectrum resistance for plant protection.

ADMM-based Distributed State Estimation for Integrated Energy System

In order to have an accurate knowledge of system-wide operation states,it is necessary to perform state estimation for the integrated energy system(IES)as the basis of energy man-agement and control.Centralized state estimation is practically infeasible for IES due to the unreliability of communication,the barrier on privacy,and the large scale of integrated systems.This paper proposes a distributed state estimation algorithm based on the alternating direction method of multipliers(ADMM)for IES containing electricity,heat,and natural gas.Various coupling units are taken into full consideration in modeling of IES state estimation to reflect the harmonization of multi energy.On the basis of bilinear measurement model,the state estimation considering nonlinear measurements can be replaced by an equivalent three-stage problem containing two linear state estimations and an intermediate transformation to avoid non-convex optimization.The three-stage procedure for IES state estimation can be further decoupled over three sub-systems with coordination on coupling units,yielding a fully distributed scheme based on ADMM.A modified ADMM with the self-adjusting penalty parameter is also adopted to enhance the convergence.Simulation results demonstrate the validity and superiority of the proposed algorithm.

Distributed Real-time State Estimation for Combined Heat and Power Systems

This paper proposes a distributed real-time state estimation(RTSE)method for the combined heat and power systems(CHPSs).First,a difference-based model for the heat system is established considering the dynamics of heat systems.This heat system model is further used along with the power system steady-state model for holistic CHPS state estimation.A cubature Kalman filter(CKF)-based RTSE is developed to deal with the system nonlinearity while integrating both the historical and present measurement information.Finally,a multi-timescale asynchronous distributed computation scheme is designed to enhance the scalability of the proposed method for largescale systems.This distributed implementation requires only a small amount of information exchange and thus protects the privacy of different energy systems.Simulations carried out on two CHPSs show that the proposed method can significantly improve the estimation efficiency of CHPS without loss of accuracy compared with other existing models and methods.