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Dog breeds are grouped based on scientific agreement, whether for traditional reasons or specific tasks during their domestication. Discrepancies may occur between public views of breed behaviour and actual evidence. This research aims to investigate differences in five behavioural traits (aggression towards people, aggression towards animals, fearfulness, responsiveness to training, and activity/excitability) by using the Dog Personality Questionnaire (DPQ) across six conventional groups/clusters of dog breeds (herding, hunting, guarding, companion dogs, potentially aggressive breeds, and mixed-breed dogs) and to assess hypotheses derived from common public presumptions. A cohort of 1309 dog owners sourced through diverse online platforms took part in the study. Contrary to stereotypes, the findings indicate that breeds labelled as “potentially aggressive” display lower levels of aggression compared to guarding breeds (χ2 (5) = 3.657, p = 0.041) and mixed-breeds (χ2 (5) = 3.870, p = 0.002). Additionally, mixed-breed dogs exhibited the highest levels of fearfulness among the six conventional clusters. In terms of aggression and gender, males demonstrated higher aggression levels towards both humans and animals compared to females (p = 0.001). These results challenge established assumptions and emphasise the necessity of evidence-based methodologies in the assessment of canine behaviour.

This research paper presents a data-based energy management method for a vessel that predicts the upcoming load demands based on data from weather information and its automated tracking system. The vessel is powered by a hybrid propulsion system consisting of a high-temperature fuel cell system to cover the base load and a battery system to compensate for the fuel cell’s limited dynamic response capability to load fluctuations. The developed energy management method predicts the load demand of the next time steps by analyzing physical relationships utilizing operational and positional data of a real vessel. This allows a steadier operation of the fuel cell and reduces stress factors leading to accelerated aging and increasing the resource efficiency of the propulsion system. Since large ships record tracking data of their cruise and no a priori training is required to adjust the energy management, the proposed method can be implemented with small additional computational effort. The functionality of the energy management method was verified using data from a real ship and records of the water currents in the North Sea. The accuracy of the load prediction is 2.7% and the attenuation of the fuel cell’s power output could be increased by approximately 32%.

Asteraceae is one of the families with a large number of ornamental plants. Climate change imposes the need to select species that are more tolerant to changing environmental conditions, especially drought. In this study, we compared the performance under water stress of six species belonging to different tribes of Asteraceae with different geographical origins. Young plants obtained after seed germination were subjected to intermediate water stress (irrigation with half the water amount used in control treatments) and severe water stress (no irrigation at all) for one month. Growth variables and biochemical stress markers were determined to assess the effects on the plants of the stress treatments. Multivariate analysis tools were used to rank species according to their tolerance. Three species were relatively more susceptible to water stress, Callistephus chinensis, Xerochrysum bracteatum, and Calendula officinalis, whereas Leucanthemum vulgare, Glebionis carinata, and Ageratum houstonianum were more tolerant. Our study indicated that the last two species, which are registered as invasive in some geographic areas, possess a larger phenotypic plasticity. Principal component analysis (PCA) combined with canonical variation analysis (CVA) proved optimal statistical methods for analysing species of diverse origins and belonging to different genera of a large family, such as the Asteraceae.

The titanium nitride (Ti2N) films have good mechanical properties, such as high hardness and chemical stability, giving Ti2N good resistance to wear and corrosion. The properties of films deposited by PVD techniques are determined by their structure, microstructure, composition, and morphology that depend on the deposition parameters, such as substrate temperature, vacuum pressure, and the distance between the target and the substrate. The influence of these parameters has been studied individually. This work studied the structure, morphology, composition, and electrochemical behavior of Ti/Ti2N films deposited by RF-magnetron sputtering on carbon steel, such as a function of the power of the RF source, substrate temperature, and the target to substrate distance and the Ar/N2 ratio. The film structure was analyzed by X-ray diffraction (XRD), the morphology of cross-section by SEM, the semi-quantitative composition by EDS, and the electrochemical properties was studied by open circuit potential, potentiodynamic polarization, and electrochemical impedance spectroscopy techniques. The films showed two phases of Ti and Ti2N. The SEM-EDS exhibited a morphology according to the Stranski–Krastanov or layer-plus-island growth model. The substrate temperature of 450 °C strongly influences the electrochemical properties.

Basic knowledge about the factors and mechanisms affecting the performance of solar cells and their identification is essential when thinking of future improvements to the device. Within this paper, we investigated the current transport mechanism in GaAsN p-i-n solar cells grown with atmospheric pressure metal organic vapour phase epitaxy (AP-MOVPE). We examined the electro-optical and structural properties of a GaAsN solar cell epitaxial structure and correlated the results with temperature-dependent current-voltage measurements and deep level transient spectroscopy findings. The analysis of J-V-T measurements carried out in a wide temperature range allows for the determination of the dominant current transport mechanism in a GaAsN-based solar cell device and assign it a nitrogen interstitial defect, the presence of which was confirmed by DLTFS investigation.

Experimental work on the synthesis of the CoSb2O6 oxide and its CO2 sensing properties is presented here. The oxide was synthesized by a microwave-assisted colloidal method in presence of ethylenediamine after calcination at 600 °C. This CoSb2O6 oxide crystallized in a tetragonal structure with cell parameters and Å, and space group P42/mnm. To prove its physical, chemical and sensing properties, the oxide was subjected to a series of tests: Raman spectroscopy, Scanning Electron Microscopy (SEM) and impedance (Z) measurements. Microstructures, like columns, bars and hollow hemispheres, were observed. For the CO2 sensing test, a thick film of CoSb2O6 was used, measuring the impedance variations on the presence of air/CO2 flows (0.100 sccm/0.100 sccm) using AC (alternating current) signals in the frequency-range 0.1–100 kHz and low relative temperatures (250 and 300 °C). The CO2 sensing results were quite good.

Bystromite (MgSb2O6) nanorods were prepared using a colloidal method in the presence of ethylenediamine, after a calcination step at 800 °C in static air. From X-ray powder diffraction analyses, a trirutile-type structure with lattice parameters a = 4.64 Å and c = 9.25 Å and space group P42/mnm was identified. Using scanning electron microscopy (SEM), microrods with sizes from 0.2 to 1.6 μm were observed. Transmission electron microscopy (TEM) analyses revealed that the nanorods had a length of ~86 nm and a diameter ~23.8 nm. The gas-sensing properties of these nanostructures were tested using pellets elaborated with powders of the MgSb2O6 oxide (calcined at 800 °C) at temperatures 23, 150, 200, 250 and 300 °C. The pellets were exposed to different concentrations of carbon monoxide (CO) and propane (C3H8) at these temperatures. The results showed that the MgSb2O6 nanorods possess excellent stability and high sensitivity in these atmospheres.