Abstract
Abstract High-performance computing (HPC) plays a crucial role in accelerating digital transformation, yet there is a lack of studies that systematically characterize its impact across different company sizes. This study addresses this gap by analyzing a cross-sectoral panel of 294 Portuguese companies, comprising 103 large enterprises and 191 small- and medium-sized enterprises (SMEs). It was applied descriptive analysis and statistical hypothesis testing methods. Two key research questions guide this investigation. The first explores the primary benefits and challenges associated with HPC adoption, while the second examines whether these factors vary between large companies and SMEs. The findings indicate that the benefits and challenges of the HPC are heterogeneously perceived by large companies and SMEs. It identified significant differences in the perceived benefits and challenges of HPC, particularly concerning cost savings, decision-making, cost and skills management, lack of awareness, and workforce skills gap. These findings contribute to a deeper understanding of how HPC supports digitalization processes, highlighting sector-specific and size-dependent differences in its perceived value and implementation barriers. This study provides valuable insights for businesses, policymakers, and researchers seeking to optimize HPC strategies for digital transformation.

Abstract
[No abstract available]

Abstract
This paper presents the development process of the mobile App D.R.E.A.M., Design-thinking to Reach-out, Embrace and Acknowledge Mental health, which is a tool for self-assessment and self-care in promoting the mental health of higher education students. In Portugal, the program for promoting Mental Health in higher education advocates the development and use of digital tools, such as apps and/or social networks and platforms, aimed at promoting wellbeing and with the potential for use to be more accessible to higher education students. The objective of this app is to promote the mental health and wellbeing of higher education students. Design Thinking was used as the methodology for building the app, which was developed using a combination of low-code/no-code tools, Flutter/Dart coding, and Google's Firebase capabilities and database functionalities. In the first semester of the 2023/2024 academic year, 484 students downloaded the app, and 22 emails were received for psychological consultations. A dynamic update of the app is required, with modules on time management and study organization, structured physical activity programs, development of socio-entrepreneurial skills, and vocational area.

Abstract
The extraction of phenolic compounds from eucalyptus leaves was optimized using heat and ultrasound-assisted techniques, and the bioactive potential of the resulting extract was assessed. The independent variables, including time (t), solvent concentration (S), and temperature (T) or power (P), were incorporated into a five- level central composite design combined with Response Surface Methodology. Phenolic content was determined by HPLC-DAD-ESI/MS and used as response criteria. The developed models were successfully fitted to the experimental data to identify the optimal extraction conditions. Heat-assisted extraction proved to be the most efficient method for phenolic recovery, yielding 27 +/- 2 mg/g extract under optimal conditions (120 min, 76.5 degrees C, and 25 % ethanol, v/v). The extracts exhibited a high concentration of phenolic glycoside derivatives, including gallotannin, quercetin, and isorhamnetin. These findings suggest that the extracts hold promise as natural additives in food technology, owing to their moderate antimicrobial activity and strong antioxidant properties.

Abstract
A notable shift from an internal combustion engine vehicles (ICEVs) fleet to an electric vehicles (EVs) fleet is expected in the medium term due to increasing environmental concerns and technological breakthroughs. In this context, this paper conducts a systematic literature review on life cycle assessment (LCA) research of EVs compared to ICEVs based on highly impactful articles. Several essential aspects and characteristics were identified and discussed, such as the assumed EV types, scales, models, storage technologies, boundaries, lifetime, electricity consumption, driving cycles, combustion fuels, locations, impact assessment methods, and functional units. Furthermore, LCA results in seven environmental impact categories were gathered and evaluated in detail. The research indicates that, on average, battery electric vehicles are superior to ICEVs in terms of greenhouse gas (GHG) emissions (182.9 g CO2-eq/km versus 258.5 g CO2-eq/km), cumulative energy demand (3.2 MJ/km versus 4.1 MJ/km), fossil depletion (49.7 g oil-eq/km versus 84.4 g oil-eq/km), and photochemical oxidant formation (0.47 g NMVOC-eq/km versus 0.61 g NMVOC-eq/km) but are worse than ICEVs in terms of human toxicity (198.1 g 1,4-DCB-eq/km versus 64.8 g 1,4-DCB-eq/km), particulate matter formation (0.32 g PM10-eq/km versus 0.26 g PM10-eq/km), and metal depletion (69.3 g Fe-eq/km versus 19.0 g Fe-eq/km). Emerging technological developments are expected to tip the balance in favor of EVs further. Based on the conducted research, we propose to organize the factors that influence the vehicle life cycle into four groups: user specifications, vehicle specifications, local specifications, and multigroup specifications. Then, a set of improvement opportunities is provided for each of these groups. Therefore, the present paper can contribute to future research and be valuable for decision-makers, such as policymakers.

Abstract
The energy policy of the European Union stresses the need for sustainable energy consumption, improvements in energy efficiency and lower fossil fuel dependence in a decoupling strategy from unstable democracies. Transportation still represents a sector largely dependent on fossil fuels, which come with several negative impacts. Measuring and assessing the sustainability of the transport sector becomes necessary. This study aims to assess the sustainability performance of the transport sector across 28 European countries over a four-year period, aligned with the policy agenda outlined in strategic documents. The methodological approach involves applying Benefit-of-the-Doubt (BoD) models, comparing aversion that uses transformation methods for anti- isotonic sub-indicators with a variant that directly incorporates these sub-indicators as reverse indicators. In general, the European countries have improved the sustainability performance of their transport sector during the time span analyzed according to the results of both models. For the inefficient units, two improvement strategies are presented based on the profiles identified on the benchmarks from both models, which can be alternative stages to achieve the robust best practices of the benchmarks.