Browsing by Issue Date, starting with "2025-11-21"
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- UV-crosslinked biomaterials: Functionalized polyethylene glycol for tissue adhesive applicationsPublication . Cernadas, Maria Teresa; Ferreira, Mariana; Melo, Bruna Daniela Lopes ; de Melo-Diogo, Duarte; Correia, Ilídio Joaquim Sobreira ; Calvinho, Paula Cristina Nunes Ferreira ; Alves, PatríciaSurgeons around the world face the challenge of effectively and securely treat acute wounds. The most used techniques used to reestablish proper tissue continuity and promote healing comprise surgical tape strips and wound suturing or stapling. However, these have different limitations associated, like additional tissue trauma and patient discomfort. Tissue adhesives have emerged as a promising alternative to traditional wound dressings and have been widely explored for their potential to minimize these drawbacks while improving overall outcomes. This study focused on the preparation of photocrosslinkable biomaterials, synthesized from polyethylene glycol (PEG) functionalized with 2-isocyanatoethyl acrylate (AOI), for potential use as tissue adhesives. The synthesized polymers were then crosslinked using two different UV irradiation times (30 and 120 s) to assess how the crosslinking period impacts the final properties of the films. The materials’ chemical composition and thermal and mechanical behavior were further characterized. Rheologic profile, gel content, hydrolytic degradation, and contact angles were assessed. In addition, cytocompatibility evaluation was also conducted. Overall, the obtained data suggest that the newly synthesized tissue adhesives form flexible, homogeneous, and transparent matrices, exhibiting promising properties for potential tissue adhesive applications.
- Framework de Gestão e Análise de Campanhas de Phishing em Ambientes CorporativosPublication . Paula, Afonso Manuel Dinis de; Sequeiros, João Bernardo Ferreira; Rodrigues, BrunoCom a evolução tecnológica, a dependência de recursos digitais é uma realidade inegável para as empresas modernas. A capacidade de adotar e integrar efetivamente as tecnologias digitais tornou-se um fator crucial para a competitividade, eficiência e sobrevivência no mercado atual. Esta dependência digital, embora traga benefícios, também expõe as organizações a riscos significativos, como ciberataques, entre os quais as campanhas de phishing têm um papel de destaque devido ao sucesso em explorar vulnerabilidades humanas. A Art Resilia, onde este projeto de estágio foi desenvolvido, é uma empresa especializada em fornecer soluções de ciber-resiliência. A sua missão centra-se em ser uma parceira de confiança, reconhecida pelo seu conhecimento e inovação, ajudando as organizações a se prepararem, responderem e recuperarem eficazmente de um panorama de ciberameaças em constante evolução. Neste contexto, este projeto consistiu no planeamento, desenvolvimento e implementação de uma framework de gestão e análise de templates e campanhas de phishing. A ferramenta poderá ser utilizada principalmente pelos analistas da empresa, permitindo-lhes criar e gerir templates de phishing personalizados, configurar campanhas adaptadas a diferentes clientes e recolher informações detalhadas sobre os resultados obtidos. Os clientes, tal como os analistas, terão acesso a dashboards, onde poderão consultar os dados recolhidos pelas campanhas realizadas nos seus colaboradores. Estes painéis, não só possibilitam efetuar análises comparativas com as médias agregadas das restantes empresas incluídas no sistema, como também permitem visualizar dados relevantes da própria organização, nomeadamente indicadores de reincidência, níveis de risco e métricas de desempenho – tanto individuais como por departamentos ou cargos –, fornecendo, assim, uma perspetiva detalhada sobre o seu desempenho de segurança. Este projeto teve como propósito possibilitar a recolha estruturada e detalhada de informações sobre a eficácia de campanhas de sensibilização, facilitando a consciencialização dos colaboradores das empresas clientes. Desta forma, a framework visa otimizar o processo de gestão de campanhas de phishing, garantindo resultados mais mensuráveis e alinhados com as necessidades dos clientes corporativos, contribuindo para o reforço contínuo das estratégias de defesa dos colaboradores face a ameaças baseadas em técnicas de engenharia social.
- Data-Driven Recommendation Systems for Training Optimization in Indoor Team SportsPublication . Gonçalves, Luísa Fanado; Silva, Bruno Miguel Correia da; Travassos, Bruno Filipe RamaCurrently, significant technological advances are being made in the field of artificial intelligence. In particular, machine learning is transforming the way we process data and extract useful knowledge in areas such as healthcare, industry, and sports. In the sports context, analyzing sensor and video data allows you to model performance, detect patterns, and anticipate risks. However, analysis alone does not decide what to do next in training. Coaches still have to select, sequence, and adapt exercises under time and operational constraints. This is where recommendation systems add value: they transform analytical signals and historical preferences into suggestions tailored to the athletes’ needs and the context of the session. Indoor team sports, such as futsal or basketball, are dynamic and strategic games where cooperation between team members is crucial to success. Basic characteristics such as speed of play, precise coordination, and tactical strategy give these sports their unique character. In this context, there is a clear gap: specific recommendation solutions for indoor sports at the moment are rare. This dissertation proposes and evaluates recommender systems to support training planning, capable of suggesting personalized exercises and even complete training plans. The system integrates three complementary components: (i) matrix factorization based on implicit feedback, (ii) temporal co-occurrence modeling sequences of exercises within a session, and (iii) a content-based component using cosine similarity. The scores are combined in a hybrid model, with weights optimized during validation and with eligibility and context filters to ensure practical recommendations. We developed a pipeline covering data preparation for exercises and contextual information, model generation, hyperparameter optimization, and hybrid weight optimization. Finally, we evaluate the model considering two sports modalities and two temporal protocols, Hold-Out and Next-Step, reporting Recall@N, NDCG@N, Coverage@N, Diversity@N, HR@N, and MRR@N. The performance evaluation and results demonstrate the feasibility of recommender systems to support training planning in indoor team sports, paving the way for more personalized training plans and progressive integration with contextual data in future work.