Pathotypic diversity of Hyaloperonospora brassicae collected from Brassica oleracea

Downy mildew caused by Hyaloperonospora brassicae is an economically destructive disease of brassica crops in many growing regions throughout the world. Specialised pathogenicity of downy mildews from different Brassica species and closely related ornamental or wild relatives has been described from host range studies. Pathotypic variation amongst Hyaloperonospora brassicae isolates from Brassica oleracea has also been described; however, a standard set of B. oleracea lines that could enable reproducible classification of H. brassicae pathotypes was poorly developed. For this purpose, we examined the use of eight genetically refined host lines derived from our previous collaborative work on downy mildew resistance as a differential set to characterise pathotypes in the European population of H. brassicae. Interaction phenotypes for each combination of isolate and host line were assessed following drop inoculation of cotyledons and a spectrum of seven phenotypes was observed based on the level of sporulation on cotyledons and visible host responses. Two host lines were resistant or moderately resistant to the entire collection of isolates, and another was universally susceptible. Five lines showed differential responses to the H. brassicae isolates. A minimum of six pathotypes and five major effect resistance genes are proposed to explain all of the observed interaction phenotypes. The B. oleracea lines from this study can be useful for monitoring pathotype frequencies in H. brassicae populations in the same or other vegetable growing regions, and to assess the potential durability of disease control from different combinations of the predicted downy mildew resistance genes

The role of off-board EV battery chargers in smart homes and smart grids: operation with renewables and energy storage systems

Concerns about climate changes and environmental air pollution are leading to the adoption of new technologies for transportation, mainly based on vehicle electrification and the interaction with smart grids, and also with the introduction of renewable energy sources (RES) accompanied by energy storage systems (ESS). For these three fundamental pillars, new power electronics technologies are emerging to transform the electrical power grid, targeting a flexible and collaborative operation. As a distinctive factor, the vehicle electrification has stimulated the presence of new technologies in terms of power management, both for smart homes and smart grids. As the title indicates, this book chapter focuses on the role of off-board EV battery chargers in terms of operation modes and contextualization for smart homes and smart grids in terms of opportunities. Based on a review of on-board and off-board EV battery charging systems (EV-BCS), this chapter focus on the off-board EV-BCS framed with RES and ESS as a dominant system in future smart homes. Contextualizing these aspects, three distinct cases are considered: (1) An ac smart home using separate power converters, according to the considered technologies; (2) A hybrid ac and dc smart home with an off-board EV-BCS interfacing RES and ESS, and with the electrical appliances plugged-in to the ac power grid; (3) A dc smart home using a unified 2 off-board EV-BCS with a single interface for the electrical power grid, and with multiple dc interfaces (RES, ESS, and electrical appliances). The results for each case are obtained in terms of efficiency and power quality, demonstrating that the off-board EV-BCS, as a unified structure for smart homes, presents better results. Besides, the off-board EV-BCS can also be used as an important asset for the smart grid, even when the EV is not plugged-in at the smart home.(undefined

Modelling informative time points: an evolutionary process approach

Real time series sometimes exhibit various types of "irregularities": missing observations, observations collected not regularly over time for practical reasons, observation times driven by the series itself, or outlying observations. However, the vast majority of methods of time series analysis are designed for regular time series only. A particular case of irregularly spaced time series is that in which the sampling procedure over time depends also on the observed values. In such situations, there is stochastic dependence between the process being modelled and the times of the observations. In this work, we propose a model in which the sampling design depends on all past history of the observed processes. Taking into account the natural temporal order underlying available data represented by a time series, then a modelling approach based on evolutionary processes seems a natural choice. We consider maximum likelihood estimation of the model parameters. Numerical studies with simulated and real data sets are performed to illustrate the benefits of this model-based approach.- The authors acknowledge Foundation FCT (FundacAo para a Ciencia e Tecnologia) as members of the research project PTDC/MAT-STA/28243/2017 and Center for Research & Development in Mathematics and Applications of Aveiro University within project UID/MAT/04106/2019

Perspectives on the Trypanosoma cruzi-host cell receptor interaction

Chagas disease is caused by the parasite Trypanosoma cruzi. The critical initial event is the interaction of the trypomastigote form of the parasite with host receptors. This review highlights recent observations concerning these interactions. Some of the key receptors considered are those for thromboxane, bradykinin, and for the nerve growth factor TrKA. Other important receptors such as galectin-3, thrombospondin, and laminin are also discussed. Investigation into the molecular biology and cell biology of host receptors for T. cruzi may provide novel therapeutic targets