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Low voltage (LV) grids face a challenge of effectively managing the growing presence of new loads like electric vehicles and heat pumps, along with the equally growing installation of rooftop photovoltaic panels. This paper describes practical applications of sensitivity factors, extracted from smart meter data (i.e., without resorting to grid models), to i) link voltage problems to different costumers/devices and their location in the grid, ii) manage the flexibility provided by distributed energy resources (DERs) to regulate voltage, and iii) assess favorable locations for DER capacity extensions, all with the aim of supporting the decision-making process of distribution system operators (DSOs) and the design of incentives for customers to invest in DERs. The methods are tested by running simulations based on historical meter data on six grid models provided by the EU-Joint Research Center. The results prove that it is feasible to implement advanced LV grid analysis and management tools despite the typical limitations in its electrical and topological characterisation, while avoiding the use of computationally heavy tools such as optimal power flows.

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Event/data-based systems are controlled by events, their local data state may change in reaction to events. Numerous methods and notations for specifying such reactive systems have been designed, though with varying focus on the different development steps and their refinement relations. We first briefly review some of such methods, like temporal/modal logic, TLA, UML state machines, symbolic transition systems, CSP, synchronous languages, and Event-B with their support for parallel composition and refinement. We then present E. -logic for covering a broad range of abstraction levels of event/data-based systems from abstract requirements to constructive specifications in a uniform foundation. E. -logic uses diamond and box modalities over structured events adopted from dynamic logic, for recursive process specifications it offers (control) state variables and binders from hybrid logic. The semantic interpretation relies on event/data transition systems; specification refinement is defined by model class inclusion. Constructive operational specifications given by state transition graphs can be characterised by a single E. -sentence. Also a variety of implementation constructors is available in E. -logic to support, among others, event refinement and parallel composition. Thus the whole development process can rely on E. -logic and its semantics as a common basis.

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This paper analyses the causal relationship between external events and sports content TV audiences. To accomplish this, we explored external data related to sports TV audience behaviour within a specific time frame and applied a Granger causality analysis to evaluate the effect of external events on both TV clients' volume and viewing times. Compared to regression studies, Granger causality analysis is essential in this research as it provides a more comprehensive and accurate understanding of the causal relationship between external events and sports TV viewership. The study results demonstrate a significant impact of external events on the TV clients' volume and viewing times. External events such as the type of tournament, match popularity, interest and home team effect proved to be the most informative about the audiences. The findings of this study can assist TV distributors in making informed decisions about promoting sports broadcasts.

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A bacterial strain was isolated from a brackish water sample of Tagus river, Alcochete, Portugal and was designated TO1_6(T). It forms light pink colonies on M13 medium supplemented with N-acetylglucosamine. Cells are pear-shaped to spherical, form rosettes and divide by budding. Strain TO1_6(T) presents a mesophilic and neutrophilic profile, with optimum growth at 20 to 25 degrees C and pH 7.0 to 7.5, and vitamin supplementation is not required to promote its growth. The genome of the novel isolate is 7.77 Mbp in size and has a DNA G+C content of 56.3%. Based on its 16S rRNA gene sequence, this strain is affiliated with the phylum Planctomycetota. Further taxonomic characterization using additional phylogenetic markers, namely rpoB gene sequence (encoding the beta-subunit of the DNA-dependent RNA polymerase), as well as Percentage of conserved proteins, average nucleotide identity and average amino acid identity, suggest the affiliation of strain TO1_6(T) to the genus Stieleria, a recently described taxon in the family Pirellulaceae, order Pirellulales and class Planctomycetia. Based on the genotypic, phylogenetic and physiological characterization, we here describe a new species represented by the type strain TO1_6(T) (=CECT 30432(T), =LMG 32465(T)), for which the name Stieleria tagensis sp. nov. is proposed.