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- Restoration of seagrass meadows in Ria Formosa: overcoming and assessing human impactPublication . Scala, Margherita; Paulo, DiogoSeagrass meadows are vital coastal ecosystems providing numerous ecological services, yet they are increasingly threatened by anthropogenic pressures. This study investigates the effectiveness of a transplantation-based restoration strategy for Zostera noltei in the intertidal SE1 meadow of Ria Formosa (Portugal), an area recently impacted by construction activities, mooring infrastructure, and recreational boating. Over a seven-month period, both donor and receiver sites were monitored using field surveys and drone-based imagery to assess seagrass percentage cover, shoot density, shoot height, and daily growth rates. Initial quadrat-level data indicated promising trends in percent cover, however, inclusion of the last three monitorings revealed that no statistically significant increase had occurred (p = 0.1142). Both shoot density and height declined, suggesting limited restoration success at the meadow scale. This was corroborated by UAV-derived monitoring, which documented a decline in total cover from 18.5% to approximately 8%, underscoring the importance of integrating multiscale assessments. Variance in daily growth rates among receiver units revealed both synchronized and heterogeneous growth periods, with no significant influence of plot or patch identity (ANOVA, p > 0.9). In contrast, donor sites exhibited consistent recovery with a significant increase in percent cover (p = 0.0001) and no impact from sediment refill treatments. Mooring assessments revealed significantly reduced seagrass structure in buoyed areas compared to controls, with no correlation between distance from anchor and vegetation parameters. These findings suggest that chronic, small-scale disturbances may suppress recovery below ecological thresholds, even after removal of major stressors. This study highlights the importance of comprehensive disturbance management and multiscale monitoring to improve restoration outcomes and long-term resilience of seagrass ecosystems.
- From words to visuals: a transformer-based multi-modal framework for emotion-driven tourism analyticsPublication . Calderón-Fajardo, Víctor; Rodríguez-Rodríguez, Ignacio; Puig-Cabrera, MiguelTraditional tourism analytics have primarily relied on isolated sentiment analysis and image processing techniques, often failing to capture the subtle interaction between textual expressions and visual aesthetics inherent in tourist experiences. This study addresses these limitations by proposing a novel multi-modal framework that transforms textual reviews into AI-generated images using standardized prompts, thereby converting affective signals into explicit visual features. Leveraging stateof-the-art models—such as Distilled Bidirectional Encoder Representations from Transformers (DistilBERT) for fine-grained emotion recognition and Contrastive Language–Image Pre training (CLIP) for semantic extraction of visual attributes— our approach maps complex sentiments onto interpretable visual characteristics, integrating explainable features to uncover the underlying structure in tourist perceptions. This approach enhances classification performance and provides a transparent mechanism for understanding how distinct emotional states correspond to specific visual cues. Experimental evaluations on a dataset encompassing four diverse tourist destinations—Berlin, Dublin, Cairo, and Málaga—demonstrate high classification accuracy and robust correlations between text-derived emotions and image-based features, close to more powerful embedding methods. Significant correlations were observed between emotions and visual features, e.g., brightness and contentment, as well as between entropy and shame, indicating that our method efficiently captures the affective resonance between visual and textual modalities. Our findings underscore the transformative potential of converting textual sentiment into visual representations to facilitate more accurate, interpretable, and actionable analytics in the tourism sector. This framework suggests promising avenues for dynamic destination characterization, informed marketing strategies, and enhanced urban planning initiatives, laying the foundation for future advancements in multimodal tourism analytics.
- Contributo das interações geracionais para o desenvolvimento da formação pessoal e social das crianças: um estudo em contexto de educação pré-escolarPublication . Bonaparte, Katy Christine Correia; Borges, Maria Leonor; Grande, Patrícia BeiraEste trabalho aborda o problema do distanciamento entre gerações na sociedade atual e a consequente perda de oportunidade de aprendizagem, partilha de valores e construção de vínculos significativos entre crianças e idosos. O principal objetivo foi compreender de que forma as interações geracionais, promovidas em contexto de educação pré-escolar, contribuem para o desenvolvimento da formação pessoal e social das crianças. A investigação empírica analisou as experiências vividas no âmbito do projeto pedagógico “Partilhas de Saberes entre Gerações”, realizado com crianças de um Jardim de Infância e idosos de uma Associação, em Loulé. O trabalho utilizou uma abordagem qualitativa, com técnicas de recolha de informação como a observação participante, a entrevista estruturada e a análise das produções das crianças, valorizando a riqueza das narrativas, desde as emoções às aprendizagens resultantes do encontro entre gerações. Os resultados permitem fazer uma caracterização aprofundada das mudanças nas perceções, atitudes e competências das crianças ao longo do projeto, destacando a emergência de valores como respeito, a empatia, a cooperação e o sentido de pertença. Os factos identificados no estudo indicam que o problema do distanciamento geracional pode ser atenuado através da implementação intencional de projetos intergeracionais na Educação Pré-Escolar, promovendo benefícios mútuos para ambas as gerações envolvidas. As conclusões apuradas levaram à apresentação de recomendações para o reforço e continuidade deste tipo de iniciativas em contexto de educação pré-escolar, sublinhando o papel fundamental das instituições educativas, como espaço privilegiado para a construção de uma sociedade mais coesa, inclusiva e humanizada.
- A Abordagem farmacológica da DPOC e as iminentes mudanças de paradigmaPublication . Duarte, Maria Beatriz; Grenha, Ana MargaridaChronic obstructive pulmonary disease (COPD) has been a major public health problem and will continue to be a challenge for physicians in the 21st century. Globally, it is at the center of attention due to its high prevalence, morbidity and mortality, creating challenges for health systems. In 2019, COPD was the third most common cause of death (in terms of age-standardized mortality rate) worldwide, accounting for 3.3 million deaths. The treatment of COPD involves the administration of medications via inhalation, with the selection of drugs and devices being crucial in reducing symptoms and the risk of exacerbations. Among the various types of inhalation devices, pressurized metered-dose inhalers (MDIs) are the most commonly prescribed and used by COPD patients worldwide. These devices use hydrofluoroalkanes (HFA) as propellants, which have greenhouse effect and contribute to global warming. In 2018, MDIs were responsible for direct emissions of approximately 18 million tons of carbon dioxide (CO2) placing them under the scope of the European Union (EU) Fluorinated Gases Regulation. This situation has put the continued use of MDIs at risk, as the EU aims to phase them out. New strategies are required to minimize or eliminate the environmental impact of MDIs, while ensuring that new devices maintain or improve therapeutic efficacy so that the many thousands of patients with controlled disease can continue their treatment. This paradigm shift has driven the scientific community and pharmaceutical companies to seek new therapeutic solutions for COPD. This dissertation aims to conduct a literature review on the development of new alternatives and solutions for COPD therapy.