Assessing the application of polypropylene multifilament yarns in brain phantoms

The currently available clinical imaging methods do not provide highly detailed information about location and severity of axonal injury or the expected recovery time of patients with traumatic brain injury [1]. High-Definition Fiber Tractography (HDFT) is a novel imaging modality that allows visualizing and quantifying, directly, the degree of axons damage, predicting functional deficits due to traumatic axonal injury and loss of cortical projections. This imaging modality is based on diffusion technology [2]. The inexistence of a phantom able to mimic properly the human brain hinders the possibility of testing, calibrating and validating these medical imaging techniques. Most research done in this area fails in key points, such as the size limit reproduced of the brain fibers and the quick and easy reproducibility of phantoms [3]. For that reason, it is necessary to develop similar structures matching the micron scale of axon tubes. Flexible textiles can play an important role since they allow producing controlled packing densities and crossing structures that match closely the human crossing patterns of the brain. To build a brain phantom, several parameters must be taken into account in what concerns to the materials selection, like hydrophobicity, density and fiber diameter, since these factors influence directly the values of fractional anisotropy. Fiber cross-section shape is other important parameter. Earlier studies showed that synthetic fibrous materials are a good choice for building a brain phantom [4]. The present work is integrated in a broader project that aims to develop a brain phantom made by fibrous materials to validate and calibrate HDFT. Due to the similarity between thousands of hollow multifilaments in a fibrous arrangement, like a yarn, and the axons, low twist polypropylene multifilament yarns were selected for this development. In this sense, extruded hollow filaments were analysed in scanning electron microscope to characterize their main dimensions and shape. In order to approximate the dimensional scale to human axons, five types of polypropylene yarns with different linear density (denier) were used, aiming to understand the effect of linear density on the filament inner and outer areas. Moreover, in order to achieve the required dimensions, the polypropylene filaments cross-section was diminished in a drawing stage of a filament extrusion line. Subsequently, tensile tests were performed to characterize the mechanical behaviour of hollow filaments and to evaluate the differences between stretched and non-stretched filaments. In general, an increase of the linear density causes the increase in the size of the filament cross section. With the increase of structure orientation of filaments, induced by stretching, breaking tenacity increases and elongation at break decreases. The production of hollow fibers, with the required characteristics, is one of the key steps to create a brain phantom that properly mimics the human brain that may be used for the validation and calibration of HDFT, an imaging approach that is expected to contribute significantly to the areas of brain related research.

Comparing different methods to measure biofilm thickness: the techniques are: optical coherence tomography, confocal laser scanning microscopy and low load compression test

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clínica)

Unnatural amino acids as functional building blocks for fluorophore-labelled peptides

Comunicação oral convidada - IL4

Finite integration methods for isospectral flows

In this paper we consider the approximate computation of isospectral flows based on finite integration methods( FIM) with radial basis functions( RBF) interpolation,a new algorithm is developed. Our method ensures the symmetry of the solutions. Numerical experiments demonstrate that the solutions have higher accuracy by our algorithm than by the second order Runge- Kutta( RK2) method.

Estratégia para a incorporação de impactes ambientais, sociais e económicos específicos num método de Avaliação da Sustentabilidade de Edifícios de Saúde (HBSA)

The healthcare project design requires a several number of concerns with the satisfaction and well‐being of the working team, patient and administrators, has a strong social responsibility and impact on the city. Due to various design requirements, these buildings are not designed and used in a sustainable way, because there are still no effective methods to support designers in this context. Consequently, they do not know what the best criteria to be followed and their managers are not aware of the measuresthatshould be adopted for efficient use. Furthermore, the aim of this study is to present a proposal for a Healthcare Building Sustainability Assessment (HBSA) method adapted for the Portuguese context and considering the work developed so far in the standardization bodies (CEN and ISO). For this, the chosen methodology is analysed and compared the most relevant building sustainability assessment tools in the context of healthcare buildings.  

A integração de técnicas BIM (Building Information Modeling) no projeto e na construção de estruturas de madeira

Dissertação de mestrado integrado em Engenharia Civil

Planeamento e controlo de projetos em ambiente colaborativo com recurso a ferramentas BIM

Dissertação de mestrado integrado em Engenharia Civil

Avaliação do ciclo de vida de um sistema construtivo em alvenaria estrutural

Dissertação de mestrado em Sustentabilidade do Ambiente Construído

Indicadores chave de sustentabilidade para edifícios residenciais em estrutura metálica

Dissertação de mestrado integrado em Engenharia Civil

Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

Avaliação do desempenho ambiental do aglomerado negro de cortiça

Dissertação de mestrado integrado em Engenharia Civil

Coordenação das MEP na implementação de modelos BIM

Dissertação de mestrado integrado em Engenharia Civil

Upgrade of an industrial building: BIM model of the as-built situation and evaluation of modifications

Dissertação de mestrado integrado in Civil Engineering

Planeamento e controlo de projetos de construção com recurso ao BIM

Dissertação de mestrado integrado em Engenharia Civil

Development of computational and experimental methods for biomass composition and evaluation of its impact in genome-scale models prediction

The use of genome-scale metabolic models has been rapidly increasing in fields such as metabolic engineering. An important part of a metabolic model is the biomass equation since this reaction will ultimately determine the predictive capacity of the model in terms of essentiality and flux distributions. Thus, in order to obtain a reliable metabolic model the biomass precursors and their coefficients must be as precise as possible. Ideally, determination of the biomass composition would be performed experimentally, but when no experimental data are available this is established by approximation to closely related organisms. Computational methods however, can extract some information from the genome such as amino acid and nucleotide compositions. The main objectives of this study were to compare the biomass composition of several organisms and to evaluate how biomass precursor coefficients affected the predictability of several genome-scale metabolic models by comparing predictions with experimental data in literature. For that, the biomass macromolecular composition was experimentally determined and the amino acid composition was both experimentally and computationally estimated for several organisms. Sensitivity analysis studies were also performed with the Escherichia coli iAF1260 metabolic model concerning specific growth rates and flux distributions. The results obtained suggest that the macromolecular composition is conserved among related organisms. Contrasting, experimental data for amino acid composition seem to have no similarities for related organisms. It was also observed that the impact of macromolecular composition on specific growth rates and flux distributions is larger than the impact of amino acid composition, even when data from closely related organisms are used.