Abstract
Reducing office buildings’ energy consumption can contribute significantly towards carbon reduction commitments since it represents 10% of total energy consumption. Major components are lighting (40% of consumption), electrical equipment (35%), and heating and central cooling systems (25\%). Occupants’ behaviours impact these energy consumption components, with solid evidence on the role of individual behaviours. In this work, we propose a methodology that uses virtual choreographies to identify and prioritize behaviour-change interventions towards office users based on the potential impact on energy consumption. The data shows that some behaviours with significant consumption have little potential for behavioural change impact, while other behaviours hold substantial potential for lowering energy consumption via behavioural change.

Abstract

Abstract
Biodiversity loss is a hot topic. We are losing species at a high rate, even before their extinction risk is assessed. The International Union for Conservation of Nature (IUCN) Red List is the most complete assessment of all species conservation status, yet it only covers a small part of the species identified so far. Additionally, many of the existing assessments are outdated, either due to the ever-evolving nature of taxonomy, or to the lack of reassessments. The assessment of the conservation status of a species is a long, mostly manual process that needs to be carefully done by experts. The conservation field would gain by having ways of automating this process, for instance, by prioritising the species where experts and financing should focus on. In this paper, we present a pipeline used to derive a conservation dataset out of openly available data and obtain predictions, through machine learning techniques, on which species are most likely to be threatened. We applied this pipeline to the different groups within the Reptilia class as a model of one of the most under-assessed taxonomic groups. Additionally, we compared the performance of models using datasets that include different sets of predictors describing species ecological requirements and geographical distributions such as IUCN's area and extent of occurrence. Our results show that most groups benefit from using ecological variables together with IUCN predictors. Random Forest appeared as the best method for most species groups, and feature selection was shown to improve results.

Abstract
The present study consists in the comparison of two metaheuristics in a scheduling problem (SP), in particular in the minimization of the makespan in flowshop problem. The two selected metaheuristics were DABC (Discrete Artificial Bee Colony) and ACO (Ant Colony Optimization). For the performance analysis, the metaheuristics were tuned with an extensive DOE study, subsequently, several tests were performed. Thirty-one evenly distributed instances were generated for a in-depth analysis and each one was subjected to three runs for each metaheuristic. Through the results obtained, it was possible to concluded that the DABC has a better performance when compared to SA and ACO. SA and ACO have a similar performance in the chosen problem. These conclusions were supported by descriptive statistics and statistical inference. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Body-positive content on social media offers a promising approach to promote positive body image (PBI). However, we need further research in order to better characterize and understand its nature. This study provides a content analysis of adolescents' image-based posts on Facebook. We aimed to determine whether the theoretical six -facet conceptualization of PBI was reflected in adolescents' posts, and whether there were different trends according to gender and time, over a 3-year period. A set of 6,503 images posted by 66 adolescents (51.5% male), were coded for PBI attributes. The results indicate that inner positivity and appreciation of body functionality through involvement in sports and fun activities were the most represented PBI facets. Conversely, imagery representing taking care of the body via healthy food/beverage choices, embracing body diversity, and filtering information in a body-preserving manner, was rarely used to project self-image on Facebook. Gender differences were only found in the appreciation of body functionality via sports activities (more prevalent in boys) and investment in appearance using benign methods, such as the use of cosmetics (more prevalent in girls). Posts addressing appearance and health -promoting self-care behaviors tended to increase in mid-adolescence. We conclude that the adolescents' posts on Facebook reflected several PBI characteristics, with a particular focus on those that enhance a functional view of the body. Future social media and school-level initiatives should prioritize the development of attuned self-care as well as mechanisms to filter messages that could endanger PBI, while also increasing the visibility of the diverse bodies that exist in the world.

Abstract
Technology transfer offices (TTO) were created with the mission of executing innovation policy and its technology transfer to industry. Most studies regarding TTO focus on the context of developed countries, so there is a lack of research on the subject in emerging economies, such as Brazil. In addition, the issue of how diverse the skills of the team of a given TTO should be for their best revenue performance is still little addressed. In this sense, the present study aims to identify which characteristics of the TTO, related to their human resources, influence obtaining revenue from the patents that constitute their portfolios. To achieve this objective, 272 TTO in Brazil were analysed with the help of the Logistic Regression technique, based on Maximum Likelihood Estimation. A remarkable conclusion that emerges from our results is that the universities to increase their revenue must invest in full-time employees (e.g., rather than in scholarship students, as tends to be the norm) and foster the inventions' communications, as well as to attract and retain employees with skills directly related to knowledge fields such as Law, Engineering, and Communication (quite surprisingly, Management and Economics graduates are not included). The combination of these factors can increase the probabilities or odds of a given TTO obtaining revenue. Thus, our results contribute to TTO human resource practices, especially those in structuring stages, such as those in Brazil and Latin American countries.