O advento do conceito e do modelo de gestão integrada dos recursos hídricos (GIRH) influenciou as políticas de água ao redor do globo. As novas políticas das águas baseadas nesse modelo de integração da GIRH demandaram novas capacidades institucionais, financeiras, e profundas transformações nos processos decisórios e de elaboração de políticas, o que desafiou gestores governamentais, o setor privado e a sociedade civil. No Brasil, e no Estado do Rio de Janeiro, uma série de mudanças políticas e institucionais, baseadas na proposta de gestão integrada, criaram um ambiente favorável à gestão das águas, marcado por uma diversidade de instituições. Apesar dos avanços rumo à integração, muitas críticas são encontradas na literatura quando se discute os resultados efetivos da adoção do paradigma da GIRH nos diferentes países. Mais recentemente, o reconhecimento de que a crise global da água é em grande extensão uma crise de governança, tornou a governança da água tema preferencial no discurso das agências e organizações internacionais, e em estudos e pesquisa. A governança das águas é apontada como uma alternativa para aperfeiçoar processos e alcançar resultados efetivos e sustentáveis. Nesse contexto, visando contribuir para o conhecimento sobre os determinantes da dinâmica e tendências de desempenho de sistemas de gestão da água, em diferentes contextos econômicos e socioambientais, é critica. A presente pesquisa tem como objetivo propor uma nova abordagem para a governança das águas em bacias hidrográficas, aqui intitulada de governança sistêmica das águas , que tem caráter adaptativo e visão ecossistêmica, e foi desenvolvida a partir da construção de um quadro analítico próprio e de sua aplicação ao estudo de caso da Bacia Lagos São João, RJ. Sua aplicação na Bacia Lagos São João, teve olhar para fatores contextuais e temporais, e indicou significativas mudanças nos processos de gestão ao longo do tempo. A pesquisa constatou que, ao longo do tempo, o sistema de gestão das águas na Bacia Lagos São João foi se distanciando do referencial de governança sistêmica das águas.

Nowadays, more and more people are playing chess and although bots for this game are not new, the tutor type of bot is still not very developed or accessible. This work aims to develop a chess tutor bot that is open-source and takes into account the current player’s abilities to facilitate the learning process. The general structure of the bot is as follows. Several Random Forest models were trained, each with a subset of the data that were divided by player rating. Then, using Minimax during the game, the bot uses the model most suited to the player’s rating to suggest the best move. Finally, the bot uses a Large Language Model to generate comments on the moves played by the player, using information extracted from the board of the game. To increase the models’ accuracy, some experiments were made using different parameters for training. The bot was then tested by a group of eight chess beginners, each doing a game of chess while receiving comments from the bot, with overall positive results. This work is a first step towards a more personalized tutor bot which could be useful for helping beginners learn, especially when professional human tutors are not available.

The use of wireless sensor networks in healthcare has the potential to enhance the services provided to citizens. In particular they play an important role in the development of state-of-the-art patient monitoring applications. Nevertheless due to the critical nature of the data conveyed by such patient monitoring applications they have to fulfil high standards of quality of service in order to obtain the confidence of all players in the healthcare industry. In such context vis-à-vis the quality of service being provided by the wireless sensor network this work presents an adaptive and context-aware method to detect and classify performance degradation events. The proposed method has the ability to catch the most significant and damaging variations on the metrics being used to quantify the quality of service provided by the network without overreacting to small and innocuous variations on the metric’s value.

The recent pandemic and consequent lockdown had a substantial impact on mental health and optimism regarding the future. Previous research showed that levels of depression, anxiety, and stress had increased throughout the pandemic. Nonetheless, how individuals cope when faced with adversity may be associated with positive expectations regarding the future. A sample of 274 Portuguese workers (female = 54) with a mean age of 40.86 (SD = 0.70) and work experience of 19.68 years (SD = 12.07) met inclusion criteria and agreed to participate in the proposed study. They represented a variety of working classes (i.e., arts, engineering, marketers, transportation and logistic, clerks, personal trainers, managers, lawyers, accountants, directors, journalism, health care). We investigated the associations between depression, stress, anxiety, adaptive and maladaptive coping, and optimism while controlling for working experience, gender, and work type. We found that depression was related to lower levels of optimism. However, for participants scoring high on adaptive coping and anxiety, higher scores of optimism were reported. Gender, work type, and experience did not significantly influence the results. These results provide evidence through which positive mental health can be promoted after the pandemic.

Emerging 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.

Games with purposes beyond entertainment, the so-called serious games, have been useful tools in professional training, especially in engaging participants. However, their evaluation and, also, their adaptable characteristics to different scenarios, audiences and contexts remain challenges. This paper examines the application of serious games in professional training, their results and adaptable ways to achieve certain goals. Using the Design Science Research (DSR) methodology, a framework was built to develop and evaluate serious games to improve user experience, learning outcomes, knowledge transfer to work situations, and the application of the skills practised in the game in real professional settings. At this stage, the investigation presents a framework regarding the triangulation of data collected from a systematic literature review, focus groups and interviews. Following the DSR methodology, the next steps of this investigation, listed at the end of the paper, are the demonstration of the framework in serious game development and the evaluation and validation of this artefact.

Games with purposes beyond entertainment, the so-called serious games, have been useful tools in professional training, especially in engaging participants. However, their evaluation and, also, their adaptable characteristics to different scenarios, audiences and contexts remain challenges. This paper examines the application of serious games in professional training, their results and adaptable ways to achieve certain goals. Using the Design Science Research (DSR) methodology, a framework was built to develop and evaluate serious games to improve user experience, learning outcomes, knowledge transfer to work situations, and the application of the skills practised in the game in real professional settings. At this stage, the investigation presents a framework regarding the triangulation of data collected from a systematic literature review, focus groups and interviews. Following the DSR methodology, the next steps of this investigation, listed at the end of the paper, are the demonstration of the framework in serious game development and the evaluation and validation of this artefact.

Jogos sérios são frequentemente utilizados para abordar a natureza repetitiva e frustrante da re abilitação. No entanto, podem ainda cair nas mesmas armadilhas da reabilitação tradicional se o jogo não tiver desafios ou se tornar demasiado difícil. Para evitar esses resultados problemáticos, o ajuste dinâmico de dificuldade (DDA) pode ser utilizado na reabilitação não apenas para definir as configurações clínicas ideais para o treino, mas também para criar um equilíbrio entre o tédio e a ansiedade, conhecido como zona de fluxo. Os sistemas DDA tradicionais utilizam diversas variáveis intrínsecas ao jogo e à experiência do jogador (ou seja, número de participantes, pontuação, toques na tela, tempo total para completar a tarefa) para o ajuste de dificuldade. A principal limitação desses sistemas DDA é a sua dependência de variáveis de jogo para o ajuste de dificuldade, resultando na falta de generalização para outros jogos e padronização. Este documento explicará a primeira etapa do desenvolvimento de uma estrutura para aju dar a implementar um sistema de ajuste de dificuldade dinâmico universal e agnóstico que utiliza informações orientadas pelo paciente (sinais eletrofisiológicos, relatórios explícitos) e dados orien tados pelo jogo para ajustar a dificuldade e criar uma experiência envolvente e equilibrada para o utilizador Nesta tese, trabalhámos no desenvolvimento de um framework DDA agnóstico, que ajudará a facilitar a implementação deste sistema util em séries de jogos mais diversas, ao mesmo tempo que fornece ferramentas para ajudar os menos experientes em tecnologia a utilizá-lo. Durante esta dissertação, foi realizado um estudo com utilizadores onde vários voluntários experimentaram três versões do mesmo jogo utilizando diferentes estímulos (explícitos, subjetivos e implícitos) para se adaptarem à dificuldade, com o objetivo de responder (i) se o sistema é capaz de criar uma experiência agradável e envolvente e (ii) se o framework pode adaptar eficazmente à dificuldade com base em vários estímulos. Dos testes meticulosos realizados durante este projeto, surgiram algumas descobertas esclare cedoras: (i) No geral, os voluntários mostraram-se a desfrutar e a estar envolvidos durante o ex perimento e (ii) os voluntários mostraram-se a perceber o ajuste como orgânico e envolvente. Este framework DDA agnóstico representa um passo significativo para otimizar os ajustes de dificuldade nos jogos sérios, levando a uma experiência de reabilitação mais eficaz e enriquecedora.

Games with purposes beyond entertainment, the so-called serious games, have been useful tools in professional training, especially in engaging participants. However, their evaluation and, also, their adaptable characteristics to different scenarios, audiences and contexts remain challenges. This paper examines the application of serious games in professional training, their results and adaptable ways to achieve certain goals. Using the Design Science Research (DSR) methodology, a framework was built to develop and evaluate serious games to improve user experience, learning outcomes, knowledge transfer to work situations, and the application of the skills practised in the game in real professional settings. At this stage, the investigation presents a framework regarding the triangulation of data collected from a systematic literature review, focus groups and interviews. Following the DSR methodology, the next steps of this investigation, listed at the end of the paper, are the demonstration of the framework in serious game development and the evaluation and validation of this artefact.

Serious Games have been used in professional training to increase employee engagement and improve the results of training initiatives. This work intends to investigate the influence of game elements, in adaptable Serious Games, according to the users' interactions, on the increase of engagement in the game itself and, as the main goal, on the learning results and the transfer of the acquired knowledge and practised skills to the daily work activities. Using the Design Science Research - DSR methodology, this study aims to develop a framework for the development and evaluation of Serious Games to improve the user experience, the learning outcomes, the transfer of knowledge to work situations, and the application of the skills practised in the game in real professional scenarios. This paper presents an initial Framework for Adaptive Serious Games derived from a systematic literature review. The next steps in this investigation are pointed out following the DSR methodology.