Distributed topology identification algorithm of distribution network based on neighboring interaction

Intelligent distributed control and protection is a promising route towards flexible and safety operation of distribution network with widespread access of distributed energy resources A fundamental premise of the distributed decision-making is that each smart terminal can identify the topological structure of the feeder and track its changes. This paper proposes a distributed topology identification algorithm with high fault tolerance based on peer-to-peer communication. The smart terminal units (STU) installed on the nodes can dynamiclly track and identify the network topology through local measurement and information exchange with neighboring STUs. The proposed algorithm combines local measurement mutual check with contralateral connectivity predictive correction, and significantly improves the tolerance of measurement errors in topology identification. Test examples are presented to verify the effectiveness of the method

Structure-function analysis of the <em>Fusarium oxysporum</em> Avr2 effector allows uncoupling of its immune-suppressing activity from recognition

Plant pathogens employ effector proteins to manipulate their hosts. Fusarium oxysporum f. sp. lycopersici (Fol), the causal agent of tomato wilt disease, produces effector protein Avr2. Besides being a virulence factor, Avr2 triggers immunity in I-2 carrying tomato (Solanum lycopersicum). Fol strains that evade I-2 recognition carry point mutations in Avr2 (e.g. Avr2R45H), but retain full virulence. Here we investigate the virulence function of Avr2 and determine its crystal structure. Transgenic tomato and Arabidopsis expressing either wild-type ΔspAvr2 (deleted signal-peptide) or the ΔspAvr2R45H variant become hypersusceptible to fungal, and even bacterial infections, suggesting that Avr2 targets a conserved defense mechanism. Indeed, Avr2 transgenic plants are attenuated in immunity-related readouts, including flg22-induced growth inhibition, ROS production and callose deposition. The crystal structure of Avr2 reveals that the protein shares intriguing structural similarity to ToxA from the wheat pathogen Pyrenophora tritici-repentis and to TRAF proteins. The I-2 resistance-breaking Avr2V41M, Avr2R45H and Avr2R46P variants cluster on a surface-presented loop. Structure-guided mutagenesis enabled uncoupling of virulence from I-2-mediated recognition. We conclude that I-2-mediated recognition is not based on monitoring Avr2 virulence activity, which includes suppression of immune responses via an evolutionarily conserved effector target, but by recognition of a distinct epitope

The powdery mildew-resistant Arabidopsis mlo2 mlo6 mlo12 triple mutant displays altered infection phenotypes with diverse types of phytopathogens

Arabidopsis thaliana mlo2 mlo6 mlo12 triple mutant plants exhibit complete immunity against infection by otherwise virulent obligate biotrophic powdery mildew fungi such as Golovinomyces orontii. While this phenotype is well documented, the interaction profile of the triple mutant with other microbes is underexplored and incomplete. Here, we thoroughly assessed and quantified the infection phenotypes of two independent powdery mildew-resistant triple mutant lines with a range of microbes. These microorganisms belong to three kingdoms of life, engage in diverse trophic lifestyles, and deploy different infection strategies. We found that interactions with microbes that do not directly enter leaf epidermal cells were seemingly unaltered or showed even enhanced microbial growth or symptom formation in the mlo2 mlo6 mlo12 triple mutants, as shown for Pseudomonas syringae and Fusarium oxysporum. By contrast, the mlo2 mlo6 mlo12 triple mutants exhibited reduced host cell entry rates by Colletotrichum higginsianum, a fungal pathogen showing direct penetration of leaf epidermal cells comparable to G. orontii. Together with previous findings, the results of this study strengthen the notion that mutations in genes MLO2, MLO6 and MLO12 not only restrict powdery mildew colonization, but also affect interactions with a number of other phytopathogens

Distributed topology identification algorithm of distribution network based on neighboring interaction

Intelligent distributed control and protection is a promising route towards flexible and safety operation of distribution network with widespread access of distributed energy resources A fundamental premise of the distributed decision-making is that each smart terminal can identify the topological structure of the feeder and track its changes. This paper proposes a distributed topology identification algorithm with high fault tolerance based on peer-to-peer communication. The smart terminal units (STU) installed on the nodes can dynamiclly track and identify the network topology through local measurement and information exchange with neighboring STUs. The proposed algorithm combines local measurement mutual check with contralateral connectivity predictive correction, and significantly improves the tolerance of measurement errors in topology identification. Test examples are presented to verify the effectiveness of the method.</jats:p