Firing and training costs and labour market segmentation

This dissertation consists of three essays on the labour market impact of firing and training costs. The modelling framework resorts to the search and matching literature. The first chapter introduces firing costs, both liner and non-linear, in a new Keynesian model, analysing business cycle effects for different wage rigidity degrees. The second chapter adds training costs in a model of a segmented labour market, accessing the interaction between these two features and the skill composition of the labour force. Finally, the third chapter analyses empirically some of the issues raised in the second chapter.

Development of foam one-part geopolymers with enhanced thermal insulation performance and low carbon dioxide emissions

Buildings are responsible for more than 40% of the energy consumption and greenhouse gas emissions. Thus, increasing building energy efficiency is one the most cost-effective ways to reduce emissions. The use of thermal insulation materials could constitute the most effective way of reducing heat losses in buildings by minimising heat energy needs. These materials have a thermal conductivity factor, k (W/m.K) lower than 0.065 while other insulation materials such as aerated concrete can go up to 0.11. Current insulation materials are associated with negative impacts in terms of toxicity. Polystyrene, for example contains anti-oxidant additives and ignition retardants. In addition, its production involves the generation of benzene and chlorofluorocarbons. Polyurethane is obtained from isocyanates, which are widely known for their tragic association with the Bhopal disaster. Besides current insulation materials releases toxic fumes when subjected to fire. This paper presents experimental results on one-part geopolymers. It also includes global warming potential assessment and cost analysis. The results show that only the use of aluminium powder allows the production mixtures with a high compressive strength however its high cost means they are commercially useless when facing the competition of commercial cellular concrete. The results also show that one-part geopolymer mixtures based on 26%OPC +58.3%FA +8%CS +7.7%CH and 3.5% hydrogen peroxide constitute a promising cost efficient (67 euro/m3), thermal insulation solution for floor heating systems with low global warming potential of 443 KgCO2eq/m3.

Assessing the feasibility of impregnating phase change materials in lightweight aggregate for development of thermal energy storage systems

This paper assesses the feasibility of impregnation/encasement of phase change materials (PCMs) in lightweight aggregates (LWAs). An impregnation process was adopted to carry out the encasement study of two different PCMs in four different LWAs. The leakage of the impregnated/encased PCMs was studied when they were submitted to freeze/thawing and oven drying tests, separately. The results confirmed that, the impregnation/encasement method is effective with respect to the large thermal energy storage density, and can be suitable for applications were PCMs cannot be incorporated directly such as asphalt road pavements.

Mortars with incorporation of PCM based in different binders: mechanical and thermal behavior

Currently we are witnessing a huge concern of society with the parameters of comfort of the buildings and the energetic consumptions. It is known that there is a huge consumption of non-renewable sources of energy. Thus, it is urgent to develop and explore ways to take advantage of renewable sources of energy by improving the energy efficiency of buildings. The mortars with incorporation of phase change materials (PCM) have the ability to regulate the temperature inside buildings, contributing to the thermal comfort and reduction of the use of heating and cooling equipment, using only the energy supplied by the sun. However, the incorporation of phase change materials in mortars modifies its characteristics. The main purpose of this study was mechanical and thermal characterization of mortars with incorporation of PCM in mortars based in different binders. The binders studied were aerial lime, hydraulic lime, gypsum and cement. For each type of binder a reference composition (0% PCM) and a composition with incorporation of 40% of PCM were developed. It was possible to observe that the incorporation of PCM in mortars caused differences in properties such as workability, compressive strength, flexural strength and adhesion, however leads to an improvement of thermal behavior.

Contribution of portuguese vernacular building strategies to indoor thermal comfort and occupants’ perception

Solar passive strategies that have been developed in vernacular architecture from different regions are a response to specific climate effects. These strategies are usually simple, low-tech and have low potential environmental impact. For this reason, several studies highlight them as having potential to reduce the demands of non-renewable energy for buildings operation. In this paper, the climatic contrast between northern and southern parts of mainland Portugal is presented, namely the regions of Beira Alta and Alentejo. Additionally, it discusses the contribution of different climate-responsive strategies developed in vernacular architecture from both regions to assure thermal comfort conditions. In Beira Alta, the use of glazed balconies as a strategy to capture solar gains is usual, while in Alentejo the focus is on passive cooling strategies. To understand the effectiveness of these strategies, thermal performances and comfort conditions of two case studies were evaluated based on the adaptive comfort model. Field tests included measurement of hygrothermal parameters and surveys on occupants’ thermal sensation. From the results, it has been found that the case studies have shown a good thermal performance by passive means alone and that the occupants feel comfortable, except during winter where there is the need to use simple heating systems.

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Thermal conditions affecting heat transfer in FDM/FFE: a contribution towards the numerical modelling of the process

The performance of parts produced by Free Form Extrusion (FFE), an increasingly popular additive manufacturing technique, depends mainly on their dimensional accuracy, surface quality and mechanical performance. These attributes are strongly influenced by the evolution of the filament temperature and deformation during deposition and solidification. Consequently, the availability of adequate process modelling software would offer a powerful tool to support efficient process set-up and optimisation. This work examines the contribution to the overall heat transfer of various thermal phenomena developing during the manufacturing sequence, including convection and radiation with the environment, conduction with support and between adjacent filaments, radiation between adjacent filaments and convection with entrapped air. The magnitude of the mechanical deformation is also studied. Once this exercise is completed, it is possible to select the material properties, process variables and thermal phenomena that should be taken in for effective numerical modelling of FFE.

Quantitative image analysis as a tool for Yarrowia lipolytica dimorphic growth evaluation in different culture media

Yarrowia lipolytica, a yeast strain with a huge biotechnological potential, capable to produce metabolites such as γ-decalactone, citric acid, intracellular lipids and enzymes, possesses the ability to change its morphology in response to environmental conditions. In the present study, a quantitative image analysis (QIA) procedure was developed for the identification and quantification of Y. lipolytica W29 and MTLY40-2P strains dimorphic growth, cultivated in batch cultures on hydrophilic (glucose and N-acetylglucosamine (GlcNAc) and hydrophobic (olive oil and castor oil) media. The morphological characterization of yeast cells by QIA techniques revealed that hydrophobic carbon sources, namely castor oil, should be preferred for both strains growth in the yeast single cell morphotype. On the other hand, hydrophilic sugars, namely glucose and GlcNAc caused a dimorphic transition growth towards the hyphae morphotype. Experiments for γ-decalactone production with MTLY40-2P strain in two distinct morphotypes (yeast single cells and hyphae cells) were also performed. The obtained results showed the adequacy of the proposed morphology monitoring tool in relation to each morphotype on the aroma production ability. The present work allowed establishing that QIA techniques can be a valuable tool for the identification of the best culture conditions for industrial processes implementation.

Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon

Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.

Thermal characterization of polyhydroxyalkanoates and poly(lactic acid) blends obtained by injection molding

In this work we present the thermal characterization of the full scope of polyhydroxyalcanoate and poly(lactic acid) blends obtain by injection molding. Blends of polyhydroxyalcanoate and poly(lactic acid) (PHA/PLA) were prepared in different compositions ranging from 0–100% in steps of 10%. The blends were injection molded and then characterized by differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and wide angle X-ray diffraction (WAXD). The increment of PHA fraction increased the degree of crystallinity of the blend and the miscibility of the base polymers as verified by the Fox model. The WAXD analysis indicates that the presence of PHA hindered the PLA crystallization. The crystallization evolution trough PHA weight fraction (wf) shows a phase inversion around 50-60%. SEM analyses confirmed that the miscibility of PHA/PLA blends increased with the incorporation of PHA and became total for values of PHA higher that 50%.

Numerical modeling and assessment of the thermal environment in an industrial premise of automotive components

Dissertação de mestrado em Engenharia Industrial

Aplicação de celulases e xilanases na reciclagem de fibras de papel

Tese de Doutoramento em Engenharia Química e Biológica (área de conhecimento em Engenharia Enzimática e das Fermentações)

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Thin films composed of Ag nanoclusters dispersed in TiO2: Influence of composition and thermal annealing on the microstructure and physical responses

Noble metal powders containing gold and silver have been used for many centuries, providing different colours in the windows of the medieval cathedrals and in ancient Roman glasses. Nowadays, the interest in nanocomposite materials containing noble nanoparticles embedded in dielectric matrices is related with their potential use for a wide range of advanced technological applications. They have been proposed for environmental and biological sensing, tailoring colour of functional coatings, or for surface enhanced Raman spectroscopy. Most of these applications rely on the so-called localised surface plasmon resonance absorption, which is governed by the type of the noble metal nanoparticles, their distribution, size and shape and as well as of the dielectric characteristics of the host matrix. The aim of this work is to study the influence of the composition and thermal annealing on the morphological and structural changes of thin films composed of Ag metal clusters embedded in a dielectric TiO2 matrix. Since changes in size, shape and distribution of the clusters are fundamental parameters for tailoring the properties of plasmonic materials, a set of films with different Ag concentrations was prepared. The optical properties and the thermal behaviour of the films were correlated with the structural and morphological changes promoted by annealing. The films were deposited by DC magnetron sputtering and in order to promote the clustering of the Ag nanoparticles the as-deposited samples were subjected to an in-air annealing protocol. It was demonstrated that the clustering of metallic Ag affects the optical response spectrum and the thermal behaviour of the films.