Hydroxyapatite porous structures for bone tissue engineering

Esta dissertação teve como objetivo o desenvolvimento de espumas porosas de hidroxiapatite (HA) baseadas em réplicas invertidas de cristais coloidais (ICC) para substituição óssea. Um ICC é uma estrutura tridimensional de elevada porosidade que apresenta uma rede interconectada de poros com elevada uniformidade de tamanhos. Este tipo de arquitetura possibilita uma proliferação celular homogénea e superiores propriedades mecânicas quando comparada com espumas de geometria não uniforme. O cristal coloidal (CC) - o molde da espuma - foi criado por empacotamento de microesferas de poliestireno (270 μm) produzidas por microfluídica e posterior tratamento térmico. O molde foi impregnado com um gel de hidroxiapatite produzido via sol-gel utilizando pentóxido de fósforo e nitrato de cálcio tetrahidratado como percursores de fósforo e cálcio, respectivamente. A espuma cerâmica foi obtida num único passo depois de um tratamento térmico a 1100oC que permitiu a solidificação do gel e a remoção do CC. A análise por espetroscopia de infravermelho por transformada de Fourier (FTIR) e difração de raios-X (XRD) revelou uma hidroxiapatite carbonatada tipo A com presença de fosfatos tricálcicos. As propriedades mecânicas foram avaliadas por testes de compressão. A biocompatibilidade in vitro foi demonstrada através de testes de adesão e proliferação celular de osteoblastos.

Context classification for service robots

This dissertation presents a solution for environment sensing using sensor fusion techniques and a context/environment classification of the surroundings in a service robot, so it could change his behavior according to the different rea-soning outputs. As an example, if a robot knows he is outdoors, in a field environment, there can be a sandy ground, in which it should slow down. Contrariwise in indoor environments, that situation is statistically unlikely to happen (sandy ground). This simple assumption denotes the importance of context-aware in automated guided vehicles.

Analysis of classification algorithms for crop detection using LANDSAT 8 images

Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region’s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth’s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal’s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.

Minimal computation structures for visual information applications based on printed electronics

In the early nineties, Mark Weiser wrote a series of seminal papers that introduced the concept of Ubiquitous Computing. According to Weiser, computers require too much attention from the user, drawing his focus from the tasks at hand. Instead of being the centre of attention, computers should be so natural that they would vanish into the human environment. Computers become not only truly pervasive but also effectively invisible and unobtrusive to the user. This requires not only for smaller, cheaper and low power consumption computers, but also for equally convenient display solutions that can be harmoniously integrated into our surroundings. With the advent of Printed Electronics, new ways to link the physical and the digital worlds became available. By combining common printing techniques such as inkjet printing with electro-optical functional inks, it is starting to be possible not only to mass-produce extremely thin, flexible and cost effective electronic circuits but also to introduce electronic functionalities into products where it was previously unavailable. Indeed, Printed Electronics is enabling the creation of novel sensing and display elements for interactive devices, free of form factor. At the same time, the rise in the availability and affordability of digital fabrication technologies, namely of 3D printers, to the average consumer is fostering a new industrial (digital) revolution and the democratisation of innovation. Nowadays, end-users are already able to custom design and manufacture on demand their own physical products, according to their own needs. In the future, they will be able to fabricate interactive digital devices with user-specific form and functionality from the comfort of their homes. This thesis explores how task-specific, low computation, interactive devices capable of presenting dynamic visual information can be created using Printed Electronics technologies, whilst following an approach based on the ideals behind Personal Fabrication. Focus is given on the use of printed electrochromic displays as a medium for delivering dynamic digital information. According to the architecture of the displays, several approaches are highlighted and categorised. Furthermore, a pictorial computation model based on extended cellular automata principles is used to programme dynamic simulation models into matrix-based electrochromic displays. Envisaged applications include the modelling of physical, chemical, biological, and environmental phenomena.

Assessing initial embodied energy in building structures using LCA methodology

The considerable amount of energy consumed on Earth is a major cause for not achieving sustainable development. Buildings are responsible for the highest worldwide energy consumption, nearly 40%. Strong efforts have been made in what concerns the reduction of buildings operational energy (heating, hot water, ventilation, electricity), since operational energy is so far the highest energy component in a building life cycle. However, as operational energy is being reduced the embodied energy increases. One of the building elements responsible for higher embodied energy consumption is the building structural system. Therefore, the present work is going to study part of embodied energy (initial embodied energy) in building structures using a life cycle assessment methodology, in order to contribute for a greater understanding of embodied energy in buildings structural systems. Initial embodied energy is estimated for a building structure by varying the span and the structural material type. The results are analysed and compared for different stages, and some conclusions are drawn. At the end of this work it was possible to conclude that the building span does not have considerable influence in embodied energy consumption of building structures. However, the structural material type has influence in the overall energetic performance. In fact, with this research it was possible that building structure that requires more initial embodied energy is the steel structure; then the glued laminated timber structure; and finally the concrete structure.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.