Veterinary students' proximity to and interpretation of a simulated "aggressive" dog before and after training.

Dog "aggression" in the veterinary practice is commonplace. Therefore, student knowledge and education about dog behaviour and the ability to interpret "aggressive" behaviour is important from a human injury prevention and dog welfare perspective. The study aimed to compare first-year veterinary students' perceived safest proximity to both an "aggressive" and non-reactive simulated dog, both before and after a teaching intervention about canine behaviour and a handling practical. It also examined student confidence and their ability to identify "aggressive" behaviours. Forty first year veterinary students took part in two surveys. Each survey included two videos: one of a simulated dog displaying "aggressive" behaviour, based on the 'Canine Ladder of Aggression'; and another displaying non-reactive (passive behaviours without reaction to the participants) behaviours. Each video depicted the slow and consistent approach towards the virtual dog within a virtual indoor environment, and participants were asked to press stop if or when they would stop approaching the dog. In the "aggressive" scenario, there was a reduction in the approach-stop time from survey 1 (median = 17.8 s) to survey 2 (median = 15.2 s) in the intervention group (p = 0.018) but not in the control group (p = 0.147). Regarding confidence, there was a significant increase in the self-reported confidence rating relating to a participant's ability to interpret canine behaviour in both the control (p = 0.011) and intervention (p = 0.003). In conclusion, these results indicate that students using approach-stop videos stayed further away from an "aggressive" virtual dog model if they had undertaken a canine behaviour educational intervention. This novel approach has the potential for further use in teaching and assessment of student knowledge and behaviour which may otherwise be difficult to demonstrate

Coupling between LOTUS and CTF with DYN3D within a multiscale and multiphysics software development

Coupling of nuclear codes can be performed at several scale levels and is necessary to improve their reliability and sustainability. Mainly, the coupling of nuclear codes that use nodal expansion neutronics with channel thermal hydraulics has been carried out at the fuel assembly level while, only recently, the coupling of nuclear codes that use advanced neutronics, thermal hydraulics, and thermo-mechanics has been carried out at either the fuel pin or materials level. Meanwhile, in the UK, a multiscale and multi-physics software development between NURESIM and CASL is being developed, which includes a coupling software environment that enables the coupling of nuclear codes at several scale levels. Full coupled reactor physics at either the fuel pin or materials level can be obtained by coupling the transport code LOTUS, the subchannel code CTF, and the nodal code DYN3D. In this journal article, a multi ways coupling between LOTUS and CTF at either the fuel pin or materials levels with DYN3D at the fuel assembly level is compared to a multi ways coupling between DYN3D and CTF at the fuel pin level with DYN3D at the fuel assembly level and a multi ways coupling between Open MC and CTF at the materials level with DYN3D at the fuel assembly level. These comparisons have been carried out to present the coupled reactor physics verifications at either the fuel pin or materials levels. These show that the multi ways coupling between LOTUS and CTF at either the fuel pin or materials levels with DYN3D at the fuel assembly level outperforms the multi ways coupling between DYN3D and CTF at the fuel pin level with DYN3D at the fuel assembly level due to the application in the former of full neutron transport. Also, these show that the multi ways coupling between LOTUS and CTF at the materials level with DYN3D at the fuel assembly level agrees with the multi ways coupling between Open MC and CTF at the materials level with DYN3D at the fuel assembly level due to the application in both of full neutron transport

Effects of Adherence to a Higher Protein Diet on Weight Loss, Markers of Health

Resistance training and maintenance of a higher protein diet have been recommended to help older individuals maintain muscle mass. This study examined whether adherence to a higher protein diet while participating in a resistance-based exercise program promoted more favorable changes in body composition, markers of health, and/or functional capacity in older females in comparison to following a traditional higher carbohydrate diet or exercise training alone with no diet intervention. In total, 54 overweight and obese females (65.9 ± 4.7 years; 78.7 ± 11 kg, 30.5 ± 4.1 kg/m2, 43.5 ± 3.6% fat) were randomly assigned to an exercise-only group (E), an exercise plus hypo-energetic higher carbohydrate (HC) diet, or a higher protein diet (HP) diet. Participants followed their respective diet plans and performed a supervised 30-min circuit-style resistance exercise program 3 d/wk. Participants were tested at 0, 10, and 14 weeks. Data were analyzed using univariate, multivariate, and repeated measures general linear model (GLM) statistics as well as one-way analysis of variance (ANOVA) of changes from baseline with [95% confidence intervals]. Results revealed that after 14 weeks, participants in the HP group experienced significantly greater reductions in weight (E −1.3 ± 2.3, [−2.4, −0.2]; HC −3.0 ± 3.1 [−4.5, −1.5]; HP −4.8 ± 3.2, [−6.4, −3.1]%, p = 0.003), fat mass (E −2.7 ± 3.8, [−4.6, −0.9]; HC −5.9 ± 4.2 [−8.0, −3.9]; HP −10.2 ± 5.8 [−13.2, –7.2%], p \u3c 0.001), and body fat percentage (E −2.0 ± 3.5 [−3.7, −0.3]; HC −4.3 ± 3.2 [−5.9, −2.8]; HP −6.3 ± 3.5 [−8.1, −4.5] %, p = 0.002) with no significant reductions in fat-free mass or resting energy expenditure over time or among groups. Significant differences were observed in leptin (E −1.8 ± 34 [−18, 14]; HC 43.8 ± 55 [CI 16, 71]; HP −26.5 ± 70 [−63, −9.6] ng/mL, p = 0.001) and adiponectin (E 43.1 ± 76.2 [6.3, 79.8]; HC −27.9 ± 33.4 [−44.5, −11.3]; HP 52.3 ± 79 [11.9, 92.8] µg/mL, p = 0.001). All groups experienced significant improvements in muscular strength, muscular endurance, aerobic capacity, markers of balance and functional capacity, and several markers of health. These findings indicate that a higher protein diet while participating in a resistance-based exercise program promoted more favorable changes in body composition compared to a higher carbohydrate diet in older females

Increasing synergistic effects of habitat destruction and hunting on mammals over three decades in the Gran Chaco

Habitat destruction and overexploitation are the main threats to biodiversity and where they co-occur, their combined impact is often larger than their individual one. Yet, detailed knowledge of the spatial footprints of these threats is lacking, including where they overlap and how they change over time. These knowledge gaps are real barriers for effective conservation planning. Here, we develop a novel approach to reconstruct the individual and combined footprints of both threats over time. We combine satellite-based land-cover change maps, habitat suitability models and hunting pressure models to demonstrate our approach for the community of larger mammals (48 species > 1 kg) across the 1.1 million km2 Gran Chaco region, a global deforestation hotspot covering parts of Argentina, Bolivia and Paraguay. This provides three key insights. First, we find that the footprints of habitat destruction and hunting pressure expanded considerably between 1985 and 2015, across ~40% of the entire Chaco – twice the area affected by deforestation. Second, both threats increasingly acted together within the ranges of larger mammals in the Chaco (17% increase on average, ± 20% SD, cumulative increase of co-occurring threats across 465 000 km2), suggesting large synergistic effects. Conversely, core areas of high-quality habitats declined on average by 38%. Third, we identified remaining priority areas for conservation in the northern and central Chaco, many of which are outside the protected area network. We also identify hotspots of high threat impacts in central Paraguay and northern Argentina, providing a spatial template for threat-specific conservation action. Overall, our findings suggest increasing synergistic effects between habitat destruction and hunting pressure in the Chaco, a situation likely common in many tropical deforestation frontiers. Our work highlights how threats can be traced in space and time to understand their individual and combined impact, even in situations where data are sparse.Fil: Romero-Muñoz, Alfredo. Humboldt-Universität zu Berlin; AlemaniaFil: Benítez-López, Ana. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Zurell, Damaris. Humboldt-Universität zu Berlin; AlemaniaFil: Baumann, Matthias. Humboldt-Universität zu Berlin; AlemaniaFil: Camino, Micaela. Proyecto Quimilero; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Centro de Ecología Aplicada del Litoral. Universidad Nacional del Nordeste. Centro de Ecología Aplicada del Litoral; ArgentinaFil: Decarre, Julieta. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; ArgentinaFil: Castillo, Hugo del. Guyra Paraguay; ParaguayFil: Giordano, Anthony J.. University of California; Estados UnidosFil: Gómez-Valencia, Bibiana. Instituto de Investigación de Recursos Biológicos Alexander Von Humboldt, Bogota; Colombia. Universidad de Buenos Aires; ArgentinaFil: Levers, Christian. Humboldt-Universität zu Berlin; AlemaniaFil: Noss, Andrew J.. University of Florida; Estados UnidosFil: Quiroga, Verónica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; ArgentinaFil: Thompson, Jeffrey J.. Guyra Paraguay; ParaguayFil: Torres, Ricardo Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; ArgentinaFil: Velilla, Marianela. Guyra Paraguay; ParaguayFil: Weiler, Andrea. Universidad Nacional de Asunción; ParaguayFil: Kuemmerle, Tobias. Humboldt-Universität zu Berlin; Alemani

Barriers to industrial energy efficiency

Purpose – The purpose of this research is to capture organisational barriers that can inhibit energy reduction in manufacturing. Energy consumption is a significant contributor to the economic and environmental components of industrial sustainability, and there is a significant body of knowledge emerging on the technical steps necessary to reduce that consumption. Achieving technical success requires organisational alignment, without which barriers to energy efficiency can be experienced. Design/methodology/approach – The research uses a theory building–theory testing cycle to propose and then verify existence of barriers to industrial energy efficiency. Literature review is used to build potential organisational barriers that can arise. The existence of barriers is then verified in industrial energy reduction projects using interview, observation and document analysis. Findings are validated by company staff. Findings – From the literature barriers that can be related to energy reduction, projects are uncovered. The generic and energy reduction-specific barriers are confirmed and two new barriers are identified. A cognitive map linking the relationships between all the barriers is proposed. Research limitations/implications – The research is built on detailed examination of a number of projects in a single company and work is needed to verify the findings in companies of different size and different industrial sector. Practical implications – The list of barriers created can support industry in preparing for and undertaking energy efficiency projects. The cognitive map proposed will help industry and academia understand why removing current prominent barriers can lead to surfacing of new barriers. Originality/value – The novelty of this research is in both the creation of a list of organizational barriers for energy efficiency as well as identifying the relationships between them. The work brings generic change management barriers to enhance the specific energy reduction barriers together into a broader collation of barriers as well as uncovering new barriers. The work proposes a cognitive map of industrial energy efficiency barriers to demonstrate their interrelationships

A large scale Digital Elevation Model super-resolution Transformer

The Digital Elevation Model (DEM) super-resolution approach aims to improve the spatial resolution or detail of an existing DEM by applying techniques such as machine learning or spatial interpolation. Convolutional Neural Networks and Generative Adversarial Networks have exhibited remarkable capabilities in generating high-resolution DEMs from corresponding low-resolution inputs, significantly outperforming conventional spatial interpolation methods. Nevertheless, these current methodologies encounter substantial challenges when tasked with processing exceedingly high-resolution DEMs (256×256,512×512, or higher), specifically pertaining to the accurate restore maximum and minimum elevation values, the terrain features, and the edges of DEMs. Aiming to solve the problems of current super-resolution techniques that struggle to effectively restore topographic details and produce high-resolution DEMs that preserve coordinate information, this paper proposes an improved DEM super-resolution Transformer(DSRT) network for large-scale DEM super-resolution and account for geographic information continuity. We design a window attention module that is used to engage more elevation points in low-resolution DEMs, which can learn more terrain features from the input high-resolution DEMs. A GeoTransform module is designed to generate coordinates and projections for the DSRT network. We conduct an evaluation of the network utilizing DEMs of various types of terrains and elevation differences at resolutions of 64×64,256×256 and 512 × 512. The network demonstrated leading performance across all assessments in terms of root mean square error (RMSE) for elevation, slope, aspect, and curvature, indicating that Transformer-based deep learning networks are superior to CNNs and GANs in learning DEM features

A pilot study investigating human behaviour towards DAVE (Dog Assisted Virtual Environment) and interpretation of non-reactive and aggressive behaviours during a virtual reality exploration task.

Dog aggression is a public health concern because dog bites often lead to physical and psychological trauma in humans. It is also a welfare concern for dogs. To prevent aggressive behaviours, it is important to understand human behaviour towards dogs and our ability to interpret signs of dog aggression. This poses ethical challenges for humans and dogs. The aim of this study was to introduce, describe and pilot test a virtual reality dog model (DAVE (Dog Assisted Virtual Environment)). The Labrador model has two different modes displaying aggressive and non-reactive non-aggressive behaviours. The aggressive behaviours displayed are based on the current understanding of canine ethology and expert feedback. The objective of the study was to test the recognition of dog behaviour and associated human approach and avoidance behaviour. Sixteen university students were recruited via an online survey to participate in a practical study, and randomly allocated to two experimental conditions, an aggressive followed by a non-reactive virtual reality model (group AN) or vice versa (group NA). Participants were instructed to 'explore the area' in each condition, followed by a survey. A Wilcoxon and Mann Whitney U test was used to compare the closest distance to the dog within and between groups respectively. Participants moved overall significantly closer to the non-reactive dog compared to the aggressive dog (p≤0.001; r = 0.8). Descriptions of the aggressive dog given by participants often used motivational or emotional terms. There was little evidence of simulator sickness and presence scores were high indicating sufficient immersion in the virtual environment. Participants appeared to perceive the dog as realistic and behaved and interacted with the dog model in a manner that might be expected during an interaction with a live dog. This study also highlights the promising results for the potential future use of virtual reality in behavioural research (i.e., human-dog interactions), education (i.e. safety around dogs) and psychological treatment (e.g. dog phobia treatment)

Numerical and Experimental Investigation of Aircraft Panel Deformations During Riveting Process

The longitudinal growth of small panels with longitudinal stiffeners has been investigated. The stiffeners have been fastened to the panels with rivets and it has been observed that during this operation the panels expand in the longitudinal direction. It has been observed that the growth is variable and the challenge is to control the riveting process to minimise this variability. In this investigation, the assembly of the small panels and longitudinal stiffeners has been simulated using low and high fidelity nonlinear finite element models. The models have been validated against a limited set of experimental measurements; it was found that more accurate predictions of the riveting process are achieved using high fidelity explicit finite element models. Furthermore, through a series of numerical simulations and probabilistic analyses, the manufacturing process control parameters that influence panel growth have been identified. Alternative fastening approaches were examined and it was found that longitudinal growth can be controlled by changing the design of the dies used for forming the rivets