Abstract
The application of Artificial Intelligence (AI) in the energy sector offers new opportunities for developing flexible, efficient, and sustainable infrastructures. Nevertheless, real-world deployment is still constrained by the lack of large-scale, integrated environments that can evaluate advanced algorithms under realistic operating conditions while ensuring regulatory compliance. This paper presents EnerTEF (which stands for Energy Testing and Experimentation Facility), a federated platform for testing and experimentation in the energy sector designed to address this gap. We introduce a unified TEF architecture that enables full-stack evaluation of intelligent systems, including predictive modeling, optimization, learning under data distribution shifts and federated learning across geographically distributed sites. The framework integrates high-fidelity digital twins, a privacy-preserving data exchange framework and regulatory sandboxing to support transparent, explainable and robust AI development. EnerTEF demonstrates how such a framework can be deployed in critical energy domains through three real-world scenarios including short-term hydropower generation forecasting, coordination between distribution network operators and distributed energy resources and real-time optimization of self-consumption for municipal buildings. Results show that EnerTEF effectively enables the development of novel AI models, improves cross-context generalizability and supports innovation for complex energy infrastructures, ultimately creating a practical, scalable path for addressing different energy-related problems and heterogeneous data.

Abstract
The study aimed to explore how communication can influence young individuals to become blood donors. It sought to answer a key question: how do communication strategies impact the recruitment of donors within this age group? The research was structured around four primary objectives. First, it evaluated young people’s knowledge about blood donation through a content analysis of 14 campaigns. Second, it examined the communication strategies implemented by the Portuguese Institute of Blood and Transplantation (IPST) via an exploratory interview with an expert from the organization. Third, it investigated the motivations and barriers affecting young people’s willingness to donate, using a survey conducted with 390 participants, which revealed that more than half of respondents were not blood donors. Finally, it identified the most effective communication strategies and actions to promote blood donation. The findings suggest that future campaigns should prioritize precise segmentation based on behavioral criteria and adopt integrated marketing communication more broadly. This approach is expected to enhance the effectiveness of initiatives aimed at increasing donor recruitment among young people.

Abstract
This paper aims to examine how Portugal and Brazil leveraged digital marketing to redefine their country brands during and after the COVID-19 pandemic. By focusing on the application of innovative digital strategies in tourism and culture, the research highlights the transformative potential of digital tools in overcoming pandemic-related challenges. Specifically, the study identifies key approaches such as the use of social media, data analytics, virtual reality, and influencer marketing that were strategically employed to maintain global engagement, foster international visibility, and support economic recovery. The results demonstrate that integrating digital marketing into country branding strategies not only sustained international recognition but also accelerated the adoption of sustainable tourism practices. By analyzing the cases of Portugal and Brazil, this paper provides actionable insights for policymakers and practitioners seeking to align tourism growth with global sustainability goals. These findings underscore the critical importance of digital transformation in enhancing the resilience and competitiveness of the tourism sector in a post-pandemic world.

Abstract
This study examines the scientific contributions of the Higher Institute of Accounting and Administration at the University of Aveiro (ISCA-UA) from 2019 to 2022, focusing on how these align with Education 5.0 and Society 5.0 goals. Using a case study approach, data were collected from institutional records, analyzing publications by type and thematic focus, emphasizing areas that promote societal well-being, multiliteracy, and educational innovation. The methodology involves a mixed-methods approach: quantitative analysis assesses publication trends, distribution by faculty rank, and output frequency, while qualitative analysis identifies themes relevant to societal and educational advancements. This approach provides insights into how ISCA-UA’s research aligns with Education 5.0 objectives, fostering both technical and socio-emotional skills needed for a “super-smart” society. Findings highlight an increase in publications addressing digital transformation, sustainability, and governance, reflecting the institution’s adaptability and responsiveness to societal shifts, particularly noticeable during the COVID-19 pandemic. This emphasis supports Education 5.0s aims of preparing students with versatile skills for modern challenges. The study contributes to the academic literature by showing how higher education institutions can align research outputs with global educational frameworks, promoting interdisciplinary skills and social responsibility. Future research could explore the impact of these themes on curriculum design and student development, further supporting the evolution toward Education 5.0. © 2025 Elsevier B.V., All rights reserved.

Abstract
Recent research on online censorship has provided valuable insights into common censorship strategies and censors' tolerance for collateral damage. A consistent finding across these studies is that censors tend to favour cost-effective techniques such as proxy enumeration, active probing, and deep packet inspection (DPI), rather than more complex and non-deterministic methods such as deep learning-based traffic analysis. For example, a recent study on the Snowflake censorship evasion system reinforced this finding by demonstrating that authoritarian regimes primarily relied on DPI to target the system. However, as censorship techniques continue to evolve, two critical questions arise: (1) What future attack vectors are likely to emerge based on current research and observed censor capabilities? (2) How can these emerging threats, along with previously utilised censorship methods, be effectively mitigated? In this paper, we present Obscura, a censorship evasion system designed to resist cost-effective, historically grounded censorship techniques while also defending against a class of plausible future attacks within a cost-effective threat model targeting WebRTC-based censorship evasion systems. Obscura is built upon four core features: (1) encapsulation of traffic within WebRTC media streams, (2) the use of a reliability layer, (3) support for both browser-based and Pion-based clients and proxy instances, and (4) the use of ephemeral proxies. Each feature is intended to mitigate either a known attack observed in the wild or a theoretically plausible attack consistent with the capabilities of a cost-effective censor. We provide a security analysis to justify our design choices and a performance evaluation to demonstrate that Obscura maintains reasonable throughput for typical online activities.

Abstract
DIn the digital transformation of industrial sectors, data is a high-value business asset. How companies manage data between systems within the organization or through networks of business partners impacts their competitive factor. Technological maturity may imply several adversities, such as the lack of interoperability standards for simple and transparent data exchange. This paper presents an architecture that enables secure exchanges of supply chain orders between textile and clothing companies. This architecture is based on Electronic Business (eBIZ) 4.0 and International Data Spaces (IDS) frameworks, fostering trust and widespread adoption of platforms in the industry sector, particularly when handling sensitive supply chain information. The architecture was implemented and validated in 3 use cases with Enterprise Resource Plannings (ERPs) from the same vendor, different vendors, and communication from a ERP to a Web portal. Implementing the proposed architecture impacted efficiency, transparency, and accountability within the supply chain network. The lead times for purchases, provisioning, and the number of additional information requests in the ordering were reduced. In subcontracting, a reduction in non-conformities and an overall improvement in delivery times were verified. Moreover, logistics operations and communication with subcontractors were optimized, leading to faster order reception and reducing informal contacts.