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- Virtual reality to promote adaptation to psychological responses after early pregnancy lossPublication . Mendes, Diana Carolina Gonçalves; Cameirão, Mónica da Silva; Fonseca, Ana Dias daEarly pregnancy loss, affecting nearly a quarter of identified pregnancies, is generally disenfranchising and can lead to persistent perinatal grief, depression, anxiety and post-traumatic stress disorder. Regardless, professional mental health support is often lacking. Standalone immersive virtual reality has the potential to address this healthcare deficit by tackling the invalidation and isolation that these women typically experience. Therefore, this research aimed to design, develop and validate AViR2, a standalone virtual reality tool to prevent negative post loss mental health responses. To address the unstudied landscape of early pregnancy loss in Portugal, this research started with a nationwide online survey characterizing the psychological impact, needs and medical and technological experiences of these women. Our survey showed that many still experience clinical levels of perinatal grief and comorbidities up to a year post-loss, possibly modulated by their satisfaction with healthcare and information provision. Further, a few already resort to digital alternatives. It further highlighted the need for them to receive early attention to avoid psychological complications. It also emphasized the importance of providing spaces for them to validate and memorialize their loss, facilitating adaptation. The development of AViR2 was informed by various experimental studies that defined the design guidelines for key virtual reality features (environments, virtual agents, body swapping). Results demonstrated that nature-realistic and fractal-based environments reduce stress, a humanoid speaking agent promotes personal self-disclosure, and body-swapping for self dialogue aids perspective-taking. All these elements were integrated into four modules: Emotion Management, Accepting the Loss, Social Sharing and Adapting to the Loss; each of these offering psychoeducation and two to three tasks to practice adaptive coping skills. AViR2 was tested for usability and subsequently evaluated in a feasibility study with two women who had suffered a loss within six months of participation. AViR2 yielded very good levels of usability and resulted in a reliable reduction of perinatal grief symptoms in both participants and of post-traumatic stress disorder symptoms in one of them. Qualitative data showed that these improvements were connected to symbolic closure, creative expression, and emotional disclosure promoted by the system. Ultimately, this work fills a gap in the national clinical literature and advances validation of digital therapeutic tools. It demonstrates that an evidence-based immersive virtual reality intervention can promote psychological adaptation and facilitate coping for women who have suffered an early pregnancy loss.
- UV-filters from insular ocean-cities. Impact on the marine sustainabilityPublication . Íñiguez Santamaría, Eva; Cordeiro, Nereida Maria Abano; Dinis, Ana Margarida Brites Caetano; Kaufmann , Manfred JosefOrganic ultraviolet filters (oUVFs) are synthetic chemical compounds widely used in industrial applications and personal care products to protect human skin and materials from solar radiation. Over recent decades, increasing demand for these products has resulted in a substantial rise in production and consumption, leading to their release into the environment. Despite widespread use, information on environmental concentrations, chemical behaviour, spatial distribution, persistence, and potential adverse effects on marine organisms remains limited. Consequently, oUVFs are classified as Contaminants of Emerging Concern. Coastal ecosystems are particularly vulnerable to oUVF contamination due to intensified tourism and recreational activities, which constitute the main direct input pathways through activities such as swimming and bathing. Indirect pathways, including wastewater treatment plant effluents, industrial discharges, and terrestrial runoff, also contribute to inputs to marine environments and may influence their persistence and distribution. This doctoral thesis investigates the distribution, accumulation, and persistence of oUVFs, as well as their potential trophic transfer, using an oceanic island as a representative study scenario. This approach enables the assessment of oUVF contamination across a spatial gradient from coastal zones to deep-sea environments and across multiple trophic levels through the analysis of diverse marine organisms. Results indicate that areas influenced by direct coastal activities exhibit higher oUVF concentrations than locations affected by indirect sources. Sessile organisms, such as macroalgae, were particularly vulnerable, displaying elevated concentrations in areas subjected to higher anthropogenic pressure. Herbivorous species exhibited the highest diversity and concentrations of oUVFs, consistent with greater exposure and bioaccumulation potential at lower trophic levels. Similar patterns were observed at higher trophic levels, including pelagic species such as skipjack tuna (Katsuwonus pelamis), bathypelagic species such as black scabbardfish (Aphanopus carbo), and deep-diving cetaceans. While sperm whales (Physeter macrocephalus) showed higher concentrations, resident short-finned pilot whales (Globicephala macrorhynchus) exhibited a higher frequency of occurrence. Furthermore, oUVFs were more prevalent in water column compartments characterized by elevated organic matter, including the surface microlayer associated with zooplankton communities, and the deep-sea bottom, associated with black scabbardfish habitat. In contrast, highly mobile species with broad vertical and horizontal distributions showed low or undetectable concentrations. Among the analyzed compounds, OC, EHS, HMS, BDBDM, and DTS were the most frequently detected, underscoring their persistence. Overall, this thesis demonstrates the widespread distribution of oUVFs beyond coastal environments, their impact on commercial species, and their accumulation in top predators. It also presents the first validated methodology for detecting oUVFs in marine zooplankton and provides concentration data across multiple species and habitats, thereby addressing critical knowledge gaps.
- Approaches for banana harvesting automationPublication . Baglat, Preety; Dias, Fernando Manuel Rosmaninho Morgado Ferrão; Mendonça, Fábio; Shahnawaz, ShekhA colheita de bananas ainda depende de um pequeno grupo de especialistas, e o seu con hecimento é difícil de transmitir. Este trabalho transforma esse conhecimento numa solução de ponta de aprendizagem automática para decisões de colheita, mais consistente, mais fácil de escalar e de replicar. Primeiro, o estudo de revisão sistemática resumiu as técnicas exis tentes de deep learning e aprendizagem automática disponíveis para identificar os estádios de maturação da banana. Em seguida, procedeu-se à recolha de um conjunto de dados em diferentes campos na Ilha da Madeira, Portugal, sob variadas condições ambientais, com o objetivo de resolver o problema da deteção do cacho de banana e da classificação para col heita. Depois, utilizando imagens de deteção de cachos e imagens rotuladas por especialistas quanto à prontidão para a colheita, recolhidas nos campos, o sistema combina um detetor baseado em You Only Look Once (YOLO) e um classificador You Only Look Once (YOLO) melhorado com Bloco Squeeze-and-Excitation (SE). O sistema de deteção foca-se no cacho principal de banana em cada fotografia para que outros cachos ou fundos complexos não induzam o resultado em erro, e o classificador decide então se esse cacho está pronto para a colheita ou não. O modelo de deteção alcançou 93%,AP50test a cerca de 5,1 ms por im agem, e o modelo de classificação atingiu 94% de precisão a cerca de 2,8 ms por imagem. Uma aplicação Android liga estas partes num fluxo simples e fornece decisões de colheita, nomeadamente Cortar ou Manter. Uma opção Discordar, que envia imagens para o servidor para revisão caso o trabalhador da colheita não concorde com o resultado, ajuda a aumentar a precisão futura do modelo. Foram recolhidos comentários de colhedores e utilizadores du rante os testes no campo, num dia de colheita, para melhorar ainda mais o sistema. Os testes de campo mostraram um desempenho fiável, decisões mais rápidas e menos trabalho manual. Permanecem limitações porque os dados provêm de uma só região e principalmente de um único tipo de banana, e as fotografias não conseguem captar o toque ou todos os parâmetros do campo. Trabalhos futuros deverão incluir estudos de validação com conjuntos de dados de múltiplas regiões geográficas e diversas cultivares de banana, extensão a outras culturas e integração de registos de campo ou diários de colheita para registo automático das avaliações de maturidade, permitir a programação preditiva da colheita e apoiar a documentação de controlo de qualidade para certificações.
- Creativity support tool for sustainability: an LLM-Assisted Creative ProcessPublication . Rodrigues, Ana Isabel Mendonça; Rodrigues, Ana Isabel; Campos, Pedro Filipe Pereira; Cabral, Diogo Nuno Crespo RibeiroPromoting new ideas is fundamental and promising for fostering innovation in various sectors. Creativity is the fundamental basis of innovation, serving as a springboard for the development of new and useful ideas in their application context, driving innovation in various spheres of society, from organizational processes to cultural transformations. Driven by the impact and evolution of Human-Computer Interaction (HCI) and the rise of the creative process through technology, this doctoral thesis focuses on user experience (UX) during the creative process through the development of a creativity support tool - System Approach to Idea Evaluation and Selection of Ecosystem (SAIESE) - based on a Large Language Model (LLM). The central question of this thesis is to analyze which functionalities can be implemented in creativity support tools, with the aim of increasing support for the creative process (i.e., generation, evaluation, and selection of ideas) and, consequently, improving the creative experience during the resolution of sustainable tasks or problems. In this context, the creative process was guided by three sustainability metrics (i.e., environmental impact, economic benefits, and social effects), ensuring that creativity and the process were directed to the application context of this research. The methodology adopted combines a hybrid research approach (qualitative and quantitative data) and a systematic literature review (2012-2025), which established the theoretical basis for the practical development of the prototype. The prototypes developed were accompanied by empirical validations guided by the research questions initially defined and by some research hypotheses. After extensive evaluations, SAIESE proved to be a successful example of a creativity support tool based on a large-scale language model, providing efficient and effective support throughout the creative process. The research concludes with the development of a conceptual approach that synthesizes the different dimensions of the research. We present the theoretical framework (Divergent Convergent Thinking Framework (DCTF)) that represents the spatialization of the creative process through the Ideas Space and Solution Space present in the Double Diamond Model. Next, we revisit the classic principles of CSTs in light of contemporary LLM-based technologies. Finally, we explore the dynamics of control, transparency, and trust in human-AI collaboration, particularly in the context of convergent thinking and AI-assisted decision making. In conclusion, this thesis proposes a new creativity support tool that combines human cognitive processes with the capabilities of an LLM to inspire future researchers, such as designers, who want to develop tools tailored to application contexts.
- Studies with galacto-oligosaccharides and lactic acid bacteria for the valorization of food by-productsPublication . Martins, Gonçalo Nuno Gouveia; Castilho, Paula Cristina Machado Ferreira; Gómez-Zavaglia, AndreaFood wastes and by-products’ generation raises humanitarian, economic and environmental concerns. The UN’s 12th Sustainable Development Goal promotes waste reduction and co-products’ valorisation along the food production chain. Prebiotic sugars galacto-oligosaccharides (GOS) resist digestion in the upper gastrointestinal tract, being metabolized by beneficial gut bacteria, supporting their proliferation, and promoting consumers’ health. GOS show cryoprotective potential towards lactic acid bacteria during freezing, freeze-drying, and storage, by replacing water molecules and forming a glass like structure around the bacteria, preventing cell damage. α-GOS can be obtained from natural sources and β-GOS by enzymatic synthesis from lactose. Removal of glucose formed during the synthesis increases the mixture’s health benefits. For the valorisation of food by-products, α-GOS from chickpeas’ and lentils’ cooking wastewaters were used for growing and the stabilization of two food-grade Lactiplantibacillus plantarum strains, and β-GOS were produced by two β-galactosidases immobilized in halloysite nanotubes and purified by fermentation with surplus yeast from the Madeiran brewing industry. Chickpeas’ yielded the most α-GOS, while lentils’ water contained more GOS of higher degree of polymerization and fewer simple sugars. L. plantarum CIDCA 83114 grew in cooking water-containing media, similarly to the standard microbiological media that uses glucose as carbon source. After freezing, freeze-drying, and storage for 3 weeks at 37 °C, GOS wastewaters were the most successful cryoprotectants towards L. plantarum WCFS1 strain, outperforming reference materials (sucrose and fructo oligosaccharides). After the enzymatic synthesis and purification by fermentation in a repeated batch operation, both mixtures’ final composition consisted in 41 % β-GOS, with unreacted lactose and galactose present, but only 1 % glucose. Food industry’s by-products are valuable sources of bioactive compounds and materials. Legumes’ cooking waters support the growth and protection of food-grade bacteria, while surplus yeast can be used in β-GOS’ purification. These added-value products can circle back to the food industry, tackling waste management and environmental concerns, while improving consumers’ health by the production of prebiotics, and probiotics with increased shelf-life.
- Emotional regulation assessment via multi-biosignal processing in a VR environment for neurorehabilitationPublication . Lima, Rodrigo Olival; Bermúdez i Badia, Sergi; Gamboa, Hugo Filipe Silveira; Cameirão, MÛnica da SilvaEmerging immersive technologies and physiological computing capabilities are opening promising pathways for emotion recognition and regulation, with growing relevance in fields such as affective computing, neurorehabilitation, and human-computer interaction. Through four exploratory studies, this thesis investigates how virtual reality, biofeed back, and machine learning can be combined to recognize and regulate users’ emotional states in real time. First, a machine learning pipeline was developed to classify emotional states using physiological signals collected in immersive and non-immersive virtual reality conditions. Results showed that immersion had a limited impact on subjective emotional ratings, while user-dependent models significantly outperformed user-independent ones, highlighting the importance of personalization in emotion recognition. The second study validated this pipeline in individuals with Alzheimer’s, revealing that emotional reactivity is partially preserved across severity levels. Classification models successfully distinguished between emotional states, healthy and Alzheimer’s participants, and even Alzheimer’s severity levels, underscoring the pipeline’s clinical relevance and generalization. The third study introduced a nature-based virtual reality environment, the Virtual Lev ada, which used real-time adaptation to users’ physiological stress levels via a biofeedback mechanism. This study also implemented and evaluated real-time retraining strategies for the stress classification model, addressing temporal drift and improving model robust ness. Although biofeedback effects were not statistically significant, both adaptive and non-adaptive groups reported reduced physiological arousal and anxiety, supporting the environment’s calming and restorative potential. Finally, the fourth study improved the adaptive virtual reality system by integrating online stress predictions and online model retraining. Results demonstrated improved prediction stability over time and significant reductions in state anxiety, particularly in individuals with elevated stress levels. In conclusion, these findings validate the feasibility and effectiveness of progressively adaptive, personalized virtual reality systems for emotion recognition and regulation. This work contributes with novel insights into how online physiological monitoring and ML adaptation can enhance emotional self-regulation, offering promising directions for affective technologies development and mental health interventions.
- Massively parallel GPU acceleration of population-based optimization metaheuristics: application to the solution large-scale systems of nonlinear equationsPublication . Silva, Bruno Miguel Pereira da; Lopes, Luiz Carlos Guerreiro; Mendonça, Fábio Rúben SilvaHigh-dimensional problems, such as large-scale Systems of Nonlinear Equations, are challenging due to their complexity and nonlinear solution spaces. Population-based optimization metaheuristics, such as Particle Swarm Optimization and Gray Wolf Optimizer, can offer effective approaches. However, their computational demands often exceed the capacity of traditional methods, particularly when addressing these problems at large scales. To address these challenges, parallelization constitutes a promising strategy. Due to the massive parallel processing capabilities, a Graphics Processing Unit (GPU) is well-adapted to the acceleration of population-based metaheuristic optimization algorithms. Thus, employing GPU parallelism can substantially reduce computational time and enable the solution of larger and more complex problems that would be impractical on conventional Central Processing Units (CPUs). GPU-based parallelization of metaheuristic optimization algorithms faces several challenges due to algorithmic diversity and heterogeneous hardware architectures. Different metaheuristics exhibit distinct computational patterns, memory access requirements, and degrees of inherent parallelism, which complicates efficient mapping to GPU architectures. Moreover, variations in GPU hardware can substantially affect performance, often requiring algorithm-specific adaptations and hardware-aware optimizations to fully exploit GPU resources. This research proposes GPU-based parallelization strategies for population-based metaheuristic algorithms to enhance performance on large-scale, high-dimensional optimization problems. It uses GPU parallelism to manage increasing problem sizes while preserving convergence behavior and solution quality. A central goal is a hardware-agnostic model that enables scalable acceleration across diverse computa tional environments, providing a general framework for GPU-based metaheuristic acceleration applicable to various algorithmic paradigms and problem domains. Experimental results indicate that GPU-accelerated metaheuristics using the proposed framework substantially outperform their sequential counterparts, achieving significant speedups. The framework scaled effectively across ten population-based algorithms and ten benchmark problems of increasing dimensionality, utilizing five GPU models, including both consumer-grade and professional-grade hardware. In multi-GPU tests, the framework exhibited superlinear speedup in certain cases. This study highlights the value of modular, reproducible frameworks for GPU based metaheuristics and provides a base for future research in high-dimensional, computationally intensive optimization.
- User profiling with feature selection and explainability: essays on three case studies across different domainsPublication . Freitas, Diogo Nuno Teixeira; Teixeira Freitas, Diogo Nuno; Dias, Fernando Manuel Rosmaninho Morgado Ferrão; Fermé, Eduardo LeopoldoUser profiling is the process of constructing a structured representation of the user within a system. This representation includes information such as preferences, behaviors, and characteristics. Based on the profile, the system can recommend services and products or, in this work, suggest actions. Machine learning methods are commonly used to this end, as they can identify complex patterns among large numbers of attributes. However, not all attributes are relevant. High-dimensional datasets often contain irrelevant, redundant, or noisy features that obscure valuable patterns and reduce model accuracy. To address this, dimensionality reduction techniques—particularly feature selection—are essential. Equally important is the ability to explain a model’s output, since understanding why a model produces a given outcome builds trust and clarifies which steps can change an undesirable situation. This thesis applies feature selection, explainability, causal discovery, and machine teaching techniques to user profiling. The goal is to support decision-making by identi fying the most relevant features, clarifying causal mechanisms, and ensuring that stake holders understand why recommendations are made. Specifically, we investigate the mRMR (minimum-Redundancy-Maximum-Relevance) method for feature selection, ex amine explainability strategies such as feature importance analysis and counterfactuals, apply causal discovery to map cause-and-effect relationships, and use machine teaching to explore profile simplification. We apply this approach in four domains: (i) Marine litter: developing static profiles to identify those who could benefit from literacy interventions; (ii) Football injuries: building predictive models based on player profile dynamics to forecast risk; (iii) Energy poverty: designing models, using counterfactuals, and applying causal discovery to understand health–poverty links; and (iv) Concept complexity: using machine teaching to study profile simplification. These applications show how profiling can deliver targeted literacy interventions, prevent sports injuries, inform preventive policies in energy poverty, and improve the efficiency of user representations and concept learnability.
- A spatial augmented reality-based biofeedback platform for fitness assessment and intervention in older adultsPublication . Ahmad, Muhammad Asif; Ahmad, Muhammad Asif; Bermúdez i Badia, Sergi; Gouveia, Élvio Rúbio QuintalIn most countries around the world, the population of older adults exceeds that of younger individuals. The ageing population has become a global challenge and is causing an increase in chronic diseases and associated health problems. This age group has been associated with conditions such as reduced mobility, prolonged hospitalisations, elevated morbidity rates, and an increased incidence of falls. A sedentary lifestyle has been correlated with numerous health conditions, making it essential to promote innovative health and fitness programs that encourage physical activity. According to the American College of Sports Medicine (ACSM), individuals should engage in 30 minutes of moderate exercise, five days a week, or 20 minutes of vigorous exercise, three times a week. The rapid growth of Information and Communication Technology (ICT) tools has led to a decrease in physical activity, contributing to various health and fitness issues. Balance assessment tools are used to evaluate postural movements, the risk of falls, and balance impairments. Using virtual reality (VR) technology in conjunction with balanced assessment tools may enhance the ecological validity of the instruments, increase performance and standardisation, and reduce administration time. Moreover, combining immersive virtual reality (IVR) with physical exercise, or exergames, enhances motivation and personalises training, effectively preventing falls by improving strength and balance in older adults. While many exergames and simulation applications have been introduced to help people engage in physical activity, limitations exist in user interest, consistency, achievement, and technology, particularly when targeting older adults and populations with specific deficits. Exergames often lack adaptability to individual fitness profiles and high-fidelity immersive virtual environments. To address these limitations, we have created and validated a biofeedback based spatial augmented reality platform that assesses physical and physiological fitness, as well as balance, in older adults through targeted interventions designed to promote wellness and reduce the risk of falls. Target heart rates are evaluated according to ACSM recommendations. The platform also offers simulations of diverse environments and fitness opportunities tailored to meet the specific needs of various populations. We have implemented standard fitness procedures in a virtual environment to assess lower-body strength and cardiorespiratory endurance in older adults.
- Biogeography, population and trophic ecology of cetaceans in a warm-temperate habitatPublication . Ferreira, Rita Borges; Kaufmann, Manfred; Alves, Filipe Marco AndradeCetaceans play a crucial role in marine ecosystems by maintaining their structure and function, providing essential ecosystem services, and acting as sentinel species. Despite the inherent challenges, research efforts to document the distribution and movements of pelagic cetacean populations have increased. Oceanic islands present strategic advantages for studying pelagic cetaceans and integrating datasets from multiple sources is a valuable approach to obtaining the long-term datasets necessary for ecological studies on these long-lived mammals. Ultimately, such integration provides insights into cetacean populations' connectivity and migration patterns across various territories and international borders. The present study aims to elucidate the distribution, movements, and ecological interactions of eight cetacean species, for which limited information exists in the Macaronesia region (Eastern North Atlantic), thereby providing crucial insights for their conservation. This study focuses on understanding the movement patterns and site fidelity of Bryde's whale, sperm whale, and Blainville's beaked whale in the archipelagos of the Madeira, Azores, and Canaries through photographic-identification methods. Additionally, in Madeira, it examines the social structure of the Blainville's beaked whale through photographic identification and analyzes the dietary habits and ecological roles of six odontocete species through stable isotopes. Research findings indicate that Bryde's whales exhibit high site fidelity to the Madeira Archipelago during their seasonal presence, with first-time documented inter archipelago movements between Madeira and the Canaries. This reflects the species' wide habitat range in the Macaronesia region, including international waters. For sperm whales, the study supports the existence of a pelagic population in Macaronesia, with a subset regularly using the Azores and Madeira Archipelagos. Preliminary data from the Canaries suggest a need for further research to evaluate a population significantly impacted by ship strikes. Blainville's beaked whales demonstrate female defense polygyny in the Madeira Archipelago, with strong associations between females and immatures, who exhibit the highest site fidelity rates. These findings underscore the significance of the Macaronesia region in providing essential habitats for these species. The study also highlights variations in dietary preferences and foraging strategies among different species, enhancing our understanding of marine biodiversity and ecosystem dynamics. It emphasizes the need for international collaboration when addressing the conservation challenges of these highly dynamic species. By combining long-term datasets with innovative methodologies, this research significantly contributes to the understanding and protection of cetaceans, underscoring the critical role of oceanic islands in marine conservation efforts.