Abstract
Within the context applied to Virtual Reality research, the present work focuses on a literature review within the emerging field of Transformative Experience Design: a domain in interaction design that aims to create experiences fostering self-actualization and self-transcendence and which relates directly to the ideas of the sublime or awe. The methodological Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) Statement was used to conduct the current review. The scientific multidisciplinary databases used for the search were SCOPUS and Web of Science. The initial search resulted in the collection of a total of 448 articles from the two aforementioned databases, of which 408 were included after the English language criterion had been applied. After eliminating duplicate studies, 304 articles remained. Here, the initial screening phase was based on reading the respective abstracts and titles, and from this excluding noticeably irrelevant studies based on the inclusion/exclusion criteria, resulting in a total of 71 articles. Of these, and after the full-text reading, 49 papers were considered eligible for inclusion in this research context.The work focuses on studies that have adopted a strongly empirical, phenomenological and qualitative approach to the creation and evaluation of transformative experiences in VR, with the purpose of finding out not only how these are being created, but also which are the main factors that enable a transformative dimension in this type of experiences. Indeed, VR seems to be explored through it´s particular phenomenological affordances as a means to advance the two fundamental dimensions of Transformative Experience Design: perceptual vastness, on one hand, and need for accommodation, on the other.Concerning the first dimension of perceptual vastness in VR experiences, different properties stood out. Firstly, the typology of the perceptual stimuli used was found to be mainly concealed between the representation of natural scenarios, and, most importantly, Earth´s view from outer space. It was also noted that environments that present an almost exaggeratedly extensive structure and where greater horizontality prevails are those that, according to this data, appear to have the best chance of fostering awe. Rather more interestingly, it has been revealed that the design of spaces and paths that present a dynamic and dramatic structure is where the sensations of awe are most prevalent, based, above all, on a feeling of surprise.On the other hand, the more epistemic dimension of need for accommodation appears to be based upon the exploration of paradoxical, supernatural, uncanny elements, mainly founded on the violation of the laws of reality and that beg for the accommodation within our current mental schemata. Truly, VR design allows for a complete inversion of these laws, and the use of fantastic and unreal elements thus finds fertile soil to then develop an experience that is deeply transformative.These results are then systematized and discussed, and further possibilities are then suggested within this context.

Abstract
The sustainable utilization of forest biomass for bioenergy production is increasingly challenged by the variability and unpredictability of raw material availability. These challenges are particularly critical in regions like Central Portugal, where seasonality, dispersed resources, and wildfire prevention policies disrupt procurement planning. This study investigates two flexibility strategies-dynamic network reconfiguration and operations postponement-as policy relevant tools to enhance resilience in forest-to-bioenergy supply chains. A novel mathematical model, the mobile Facility Location Problem with dynamic Operations Assignment (mFLP-dOA), is proposed and solved using a scalable matheuristic approach. Applying the model to a real case study, we demonstrate that incorporating temporary intermediate nodes and adaptable processing schedules can reduce costs by up to 17% while improving operational responsiveness and reducing non-productive machine time. The findings offer strategic insights for policymakers, biomass operators, and regional planners aiming to design more adaptive and cost-effective biomass supply systems, particularly under environmental risk scenarios such as summer operation bans. This work supports evidence-based planning and investment in flexible logistics infrastructure for cleaner and more resilient bioenergy supply chains.

Abstract
Interest in artificial intelligence (AI)-driven crowd work has increased during the last few years as a line of inquiry that expands upon prior research on microtasking to represent a means of scaling up complex tasks through AI mediation. Despite the increasing attention to the macrotask phenomenon in crowdsourcing, there is a need to understand the processes, elements, and constraints underlying the infrastructural and behavioral aspects in such form of crowd work when involving collaboration. To this end, this paper provides a first attempt to characterize some of the research conducted in this direction to identify important paths for an agenda comprising key drivers, challenges, and prospects for integrating human-centered AI in collaborative crowdsourcing environments.

Abstract
Community-based electricity markets, which are defined as groups of members that share common interests in renewable distributed generation, allow prosumers to embrace more active roles by opening up several opportunities for trading electricity. At the same time, such markets may favor conventional consumers by allowing them to choose cheaper electricity providers. Due to trends in power sector modernization, community-based electricity markets are of great research interest, and there are already some associated models. However, there is a research gap in searching for integrated and holistic approaches that go beyond economic aspects, consider social and environmental aspects, and assume the balanced co-existence of community-based and conventional markets. This work fills this critical research gap by adapting/applying the optimized tariff model, Bass diffusion model, life cycle assessment, and multi-objective optimization to the context of community-based markets. Results indicate that favoring conventional markets in the short term and community-based markets in the medium term is beneficial. Moreover, regulated tariffs should increase slightly in the short/medium-term to accommodate DG growth. Additionally, community-based markets can decrease electricity expenses by around 13.6 % considering the market participants. Thus, such markets can be significantly beneficial in mitigating energy poverty.

Abstract
Pruning consists on an agricultural trimming procedure that is crucial in some species of plants to promote healthy growth and increased yield. Generally, this task is done through manual labour, which is costly, physically demanding, and potentially dangerous for the worker. Robotic pruning is an automated alternative approach to manual labour on this task. This approach focuses on selective pruning and requires the existence of an end-effector capable of detecting and cutting the correct point on the branch to achieve efficient pruning. This paper reviews and analyses different end-effectors used in robotic pruning, which helped to understand the advantages and limitations of the different techniques used and, subsequently, clarified the work required to enable autonomous pruning.

Abstract
O género textual de divulgação científica é fundamental para a disseminação do conhecimento científico de forma acessível e compreensível junto do público não especializado, apresentando estrutura e características diferentes das dos artigos científicos (e.g., Garces-Conejos & Sanchez-Macarro, 1998; Zamboni, 1998). Os estudos sobre as propriedades linguísticas do texto de divulgação científica em português europeu não abundam, sendo a exceção o projeto Promoção da Literacia Científica (Gonçalves & Jorge, 2018). Por outro lado, no âmbito da produção de conteúdo, os grandes modelos de linguagem (LLM), nomeadamente os modelos GPT da OpenAI, ganharam, em pouco tempo, atenção generalizada do público. Sendo recentes, a avaliação da qualidade linguística dos textos produzidos é ainda muito reduzida. Tendo estas premissas em consideração, o presente estudo tem como objetivo avaliar a qualidade linguística das respostas geradas pelo ChatGPT (GPT-3.5) no domínio da cosmetologia, no que respeita às categorias de produtos cosméticos, ingredientes, segurança e eficácia e regulamentação, visando identificar padrões que permitam compreender as diferenças e/ou semelhanças entre o conteúdo gerado pelo LLM e aquele produzido por especialistas humanos no Portal infoCosméticos. Para isso, foram selecionadas vinte questões previamente respondidas e publicadas no portal e, posteriormente, criados quatro prompts distintos com diferentes graus de complexidade, que deram origem a oitenta respostas geradas pelo ChatGPT. As respostas foram, de seguida, analisadas, de acordo com os resultados conduzidos por uma grelha de avaliação linguística composta por 11 perguntas. A análise produziu resultados de diferentes tipos: em termos globais, as respostas escritas pelos especialistas produzem resultados ligeiramente superiores às do ChatGPT; quanto à coesão interfrásica, constatou-se que os textos produzidos por especialistas usam um número reduzido de conectores, contrastando com o uso recorrentemente de marcadores discursivos nos textos do ChatGPT; verifica-se o uso de jargão científico não explicado e uma macroestrutura com ausência do parágrafo da conclusão, nos textos publicados no portal; os textos gerados pelo ChatGPT apresentam uma frequência elevada de repetições e/ou tautologias.