Abstract
Short-form destination videos often rely on music to carry cultural meaning. This paper links Cognitive Metaphor Theory with the circumplex dyad of pleasure and arousal to explain how music-image pairings build destination brand resonance (DBR). Three experiments show that pleasure is the stable route to DBR, arousal helps only under favorable tone, and their effects are additive. A Meaning-Access Prime (MAP) raises both emotions under identical clips and, in Bayesian structural models, also exerts a direct path to DBR, strongest when pleasant tone is low. DBR then predicts destination brand identification and destination consumption intention. We also show a useful state view: Resonant versus Emergent DBR. The framework provides design rules for co-tuning tone, activation, and cultural cues in creator-made clips that improve resonance, identification, and intention.

Abstract
The widespread adoption of embedded systems has led to their deployment in critical real-world applications, making them attractive targets for malicious actors. This paper presents RunPBA, a hardware-based runtime attestation system designed to defend against control flow attacks while maintaining minimal performance overhead and adhering to strict power consumption constraints. RunPBA leverages Pointer Authentication and Branch Target Identification (PACBTI), a new processor extension tailored for the ARM Cortex M processor family, allowing robust protection without requiring hardware modifications, a limitation present in similar solutions. We implemented a proof-of-concept and evaluated it using two benchmark suites, Coremark PRO and BEEBS. Experimental results indicate that RunPBA imposes a geometric mean performance overhead of only 1.3% and 6.8% across the benchmarks, underscoring its efficiency and suitability for real-world deployment.

Abstract
As urban populations swell, cities face mounting crises such as traffic congestion, waste management, pollution, and parking allocation. The advent of the smart city concept offers solutions to these challenges by leveraging the Internet of Things (IoT) and big data technologies. However, developing smart city technologies is difficult for cities with different infrastructural foundations. It is crucial to determine whether all cities, regardless of size or location, can align with the smart city concept to promote social equity across regions. The digital divide between large cities and low-density areas poses significant challenges for smaller towns and rural regions, making the transition to smarter environments more complex. This research focuses on developing smart cities in low-density areas, based on a case study of the Tras-os-Montes region in northern Portugal, examining the adoption and acceptance of smart city technologies in these regions. By constructing a smart city technology acceptance model, this study investigates the factors influencing the construction of smart cities in low-density areas, aiming to contribute to the community. This project encapsulates the exploration of smart city technology's feasibility and acceptance in less urbanized areas, highlighting the importance of bridging the digital divide to ensure equitable development across diverse regions.

Abstract
This paper presents a case study to illustrate the application of the directed qualitative content analysis (DQCA) technique to focus group transcriptions for data-driven qualitative persona creation, with broader applicability in human-computer interaction and software development. Using a case study from a project focused on creating an e-grocery marketplace for facilitating short agrifood supply chain trade in the Portuguese context, we demonstrate and validate how DQCA can systematically generate personas that reflect real user needs. For the focus group session, we involved one of the project's stakeholders: family farmers. Furthermore, we propose how these personas can be integrated into the Rational Unified Process software development methodology, guiding decision-making, user-centered design, and prioritization throughout all its phases. Despite being rooted in the e-grocery domain, this paper's methodological approach and insights into generating and integrating user-centered personas in software development processes apply to a broader range of industries and projects, offering guidelines for practitioners and researchers in diverse contexts.

Abstract

Abstract
Hydrogen is becoming a key energy carrier in the transition toward decarbonization, as electrolysis creates strong interdependencies between electricity and hydrogen markets. Accurately representing strategic behaviour in these coupled markets is essential, yet current models fail to capture price-responsive bidding. To address this, a joint hybrid Cournot-Linear Supply Function Equilibria (CLSFE) model is developed and reformulated as an equivalent optimization problem, enabling tractable large-scale analysis. The model is applied to the Iberian system for 2030 and compared with perfect competition and Cournot benchmarks. Results show that hydrogen prices are lowest under CLSFE, with a reduction of about 44% relative to perfect competition and 10% to Cournot, while hydrogen demand increases by up to 58%. Electrolytic hydrogen production rises up to 92%, displacing grey hydrogen and reducing hydrogen-sector emissions. However, renewable self-curtailment reaches 82 TWh, indicating increased market power. These results highlight cross-sector trade-offs and support market design and policy analysis.