http://hdl.handle.net/10071/2106 2026-05-09T03:54:18Z 2026-05-09T03:54:18Z Oliveira, M. J. de. http://hdl.handle.net/10071/37172 2026-05-08T11:10:46Z 2025-01-01T00:00:00Z

Título próprio: From genome to form: A biomimetic installation in motion Autoria: Oliveira, M. J. de. Resumo: The intersection of biology and architecture has become increasingly relevant in the context of sustainability, technological integration, and the search for adaptive and intelligent systems within the built environment. Biomimetics offers a powerful framework for translating the functions and processes of natural organisms into design solutions that can enhance architectural performance (Benyus, 1997). However, while formal analogies with nature have been well explored, there remains a gap in applying biological regulatory systems—such as genetic networks—as direct models for spatial and behavioural design. This article addresses that gap by examining Musical Morphogenesis, a biomimetic and interactive installation developed between 2014 and 2017. The project is centred on the gene regulatory network of Arabidopsis thaliana, a well-studied model organism in plant biology (Meyerowitz, 1997). The research investigates how computational simulations of gene activation patterns can inform the development of kinetic architectural systems capable of self-organization, responsiveness, and expressive interaction. The primary aim of this research is to explore how architectural elements can embody the logic of genetic development, transforming molecular pathways into motion, light, and sound. The study is driven by the question: How can gene regulatory networks be translated into performative, interactive spatial systems that reflect biological complexity? To answer this, the project integrates a Boolean logic-based gene model into a physical structure composed of CNC-fabricated components, pneumatic actuators, LED lighting, and an interactive touchscreen interface. The methodology involves interdisciplinary collaboration across architecture, computational biology, engineering, and music composition, resulting in a system where user interactions can influence developmental pathways and trigger morphological changes in real time. The key contribution of this work lies in its demonstration that biological computation can serve not only as inspiration but as a functional blueprint for architectural design. By making genetic dynamics tangible and interactive, Musical Morphogenesis presents a novel approach to biomimetic design that bridges scientific modelling and spatial expression within the broader framework of biodigital architecture.

2025-01-01T00:00:00Z Marreiros, C. F. Boné, J. Ferreira, J. C. Ribeiro, R. http://hdl.handle.net/10071/37086 2026-04-29T12:27:09Z 2023-01-01T00:00:00Z

Título próprio: Social media insights about COVID-19 in Portugal: A text mining approach Autoria: Marreiros, C. F.; Boné, J.; Ferreira, J. C.; Ribeiro, R. Resumo: The rapid spread of COVID-19 around the world had a significant impact on daily life. As in other countries, measures were taken in Portugal to combat the exponential increase of cases, such as curfews and the use of masks. Thus, in parallel with the direct consequences on health and the healthcare sector, the pandemic also caused changes in human behavior from a sociological viewpoint. The objective of this dissertation is to attain a perception of the reality concerning COVID-19. For this purpose, real-time data was extracted from three sources, two of them being social media platforms – Twitter and Reddit – and the other one being Público, a Portuguese online newspaper. The adopted approach, based on topic modelling and sentiment analysis, was validated within the Portugal context, concerning data over a period of one year, but it can equally be employed in similar situations and other countries and provide decision-making support. After the data extracting, it was prepared for application of natural language processing (NLP) tools specific to the Portuguese language, which can represent a challenge due to the lexical richness. With the gathered information, a dashboard was built, with the purpose of gaining insights on the COVID-19 pandemic in Portugal. It was concluded that the topics discussed on social media reflect the events related to the pandemic. In a final stage, these dashboards were evaluated by public health experts, who highlighted the potential of the results obtained. The data and dashboards will be made available to the scientific community upon request.

2023-01-01T00:00:00Z Badiali, C Almeida, R. Malaca, B. Fonseca, R. Silva, T. Vieira, J. http://hdl.handle.net/10071/37065 2026-04-29T09:20:34Z 2026-01-01T00:00:00Z

Título próprio: Tailored laser wakefield acceleration for decaying particles Autoria: Badiali, C; Almeida, R.; Malaca, B.; Fonseca, R.; Silva, T.; Vieira, J. Resumo: We introduce a plasma wakefield acceleration scheme capable of boosting initially subrelativistic particles to relativistic velocities within millimeter-scale distances. A subluminal light pulse drives a wake whose velocity is continuously matched to the beam speed through a tailored plasma density, thereby extending the dephasing length. We develop a theoretical model that is generalizable across particle mass, initial velocity, and the particular accelerating bucket being used, and we verify its accuracy with particle-in-cell simulations using laser drivers with energies in the joule range.

2026-01-01T00:00:00Z Noetzold, D. Barbosa, J. L. V. Santana, J. F. P. Leithardt, V. R. Q. http://hdl.handle.net/10071/37011 2026-05-04T15:29:45Z 2026-01-01T00:00:00Z

Título próprio: Reinforcement learning-based adaptive quantum-safe cryptography for DN25-compliant smart environments Autoria: Noetzold, D.; Barbosa, J. L. V.; Santana, J. F. P.; Leithardt, V. R. Q. Resumo: The emergence of quantum computing challenges traditional security mechanisms, particularly in heterogeneous and resource-constrained IoT and smart environments that must satisfy DN25 requirements. This work introduces a reinforcement learning-driven model for the adaptive selection and orchestration of cryptographic algorithms. Acting as an intelligent decision layer, the system observes contextual, network, and operational metrics to recommend or enforce configurations combining classical schemes, post-quantum cryptography, and Quantum Key Distribution when available. The selection problem is formulated as a Markov Decision Process with state and action spaces aligned with protocol control flows and is embedded into a security middleware with negotiation and fallback mechanisms to ensure interoperability and policy compliance without modifying application logic. Experimental results demonstrate that the model dynamically adjusts key lengths, algorithm families, and security policies according to risk and resource conditions, increasing post-quantum cryptography and Quantum Key Distribution usage by up to 33.4% and 23.9% in high-risk scenarios while favoring low-latency classical or hybrid options for less critical traffic. The system achieves success rates above 78% while maintaining stable latency and resource usage during extended operation.

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