Rearranjos 3-aza-Cope : efeito dramático dos substituintes na velocidade da reacção

Dissertação apresentada para a obtenção do Grau de Doutor em Química Especialidade de Química Orgânica pela Universidade Nova de Lisboa,Faculdade de Ciências e Tecnologia

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Speed control of induction machine based on direct torque control method

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Influence of lime type and curing conditions on lime and lime-metakaolin mortars

Durability of Building Materials and Components (Vasco Peixoto de de Freitas, J.M.P.Q. Delgado, eds.), Building Pathology and Rehabilitation, vol. 3, VIII, 105-126. ISBN: 978-3-642-37474-6 (Print) 978-3-642-37475-3 (Online). Springer-Verlag Berlin Heidelberg. DOI: 10.1007/978-3-642-37475-3_5

Análise comparada da classificação “pixel a pixel” e orientada por objecto de uma imagem WorldView 2 de Maputo, Moçambique

O desenvolvimento das tecnologias associadas à Detecção Remota e aos Sistemas de Informação Geográfica encontram-se cada vez mais na ordem do dia. E, graças a este desenvolvimento de métodos para acelerar a produção de informação geográfica, assiste-se a um crescente aumento da resolução geométrica, espectral e radiométrica das imagens, e simultaneamente, ao aparecimento de novas aplicações com o intuito de facilitar o processamento e a análise de imagens através da melhoria de algoritmos para extracção de informação. Resultado disso são as imagens de alta resolução, provenientes do satélite WorldView 2 e o mais recente software Envi 5.0, utilizados neste estudo. O presente trabalho tem como principal objectivo desenvolver um projecto de cartografia de uso do solo para a cidade de Maputo, com recurso ao tratamento e à exploração de uma imagem de alta resolução, comparando as potencialidades e limitações dos resultados extraídos através da classificação “pixel a pixel”, através do algoritmo Máxima Verossimilhança, face às potencialidades e eventuais limitações da classificação orientada por objecto, através dos algoritmos K Nearest Neighbor (KNN) e Support Vector Machine (SVM), na extracção do mesmo número e tipo de classes de ocupação/uso do solo. Na classificação “pixel a pixel”, com a aplicação do algoritmo classificação Máxima Verosimilhança, foram ensaiados dois tipos de amostra: uma primeira constituída por 20 classes de ocupação/uso do solo, e uma segunda por 18 classes. Após a fase de experimentação, os resultados obtidos com a primeira amostra ficaram aquém das espectativas, pois observavam-se muitos erros de classificação. A segunda amostra formulada com base nestes erros de classificação e com o objectivo de os minimizar, permitiu obter um resultado próximo das espectativas idealizadas inicialmente, onde as classes de interesse coincidem com a realidade geográfica da cidade de Maputo. Na classificação orientada por objecto foram 4 as etapas metodológicas utilizadas: a atribuição do valor 5 para a segmentação e 90 para a fusão de segmentos; a selecção de 15 exemplos sobre os segmentos gerados para cada classe de interesse; bandas diferentemente distribuídas para o cálculo dos atributos espectrais e de textura; os atributos de forma Elongation e Form Factor e a aplicação dos algoritmos KNN e SVM. Confrontando as imagens resultantes das duas abordagens aplicadas, verificou-se que a qualidade do mapa produzido pela classificação “pixel a pixel” apresenta um nível de detalhe superior aos mapas resultantes da classificação orientada por objecto. Esta diferença de nível de detalhe é justificada pela unidade mínima do processamento de cada classificador: enquanto que na primeira abordagem a unidade mínima é o pixel, traduzinho uma maior detalhe, a segunda abordagem utiliza um conjunto de pixels, objecto, como unidade mínima despoletando situações de generalização. De um modo geral, a extracção da forma dos elementos e a distribuição das classes de interesse correspondem à realidade geográfica em si e, os resultados são bons face ao que é frequente em processamento semiautomático.

Osteoclast activity in ankylosing spondylitis patients before and after TNF-blocking therapy

Ankylosing spondylitis (AS) is a chronic inflammatory rheumatic disease of the axial skeleton. The major outcome of this disease is defined by new bone formation, commonly observed in the ligaments of the intervertebral joints, that can lead to the formation of bony spurs, known as syndesmophytes. Previous studies have shown that serum levels of TNF, IL-6 and IL-17 are increased in AS patients and may be implicated in the development of secondary osteoporosis, since these cytokines are able to induce osteoclast (OC) differentiation and, therefore, bone resorption. In this work we aimed to assess the effects of TNF-blocking therapy in the systemic inflammatory environment of AS patients with active disease as well as in OC differentiation and activity. To accomplish this objective, we cultured circulating monocytes from AS patients, before and after therapy, under osteoclastogenic conditions and we performed two functional assays (TRAP staining and resorption pit assay) and analyzed the expression of osteoclast specific genes. We have shown that AS patients with active disease have increased levels of pro-inflammatory cytokines when compared with healthy subjects. We also found that IL-17, TGF-β and osteoprotegerin are decreased after TNF-blocking therapy. Interestingly, we also observed that after TNF-blocking therapy the expression of some genes is favoring osteoclastogenesis and that differentiated OCs have increased resorption activity. These results suggest that in active AS there may be an uncoupling between inflammation and OC activity that is reset by TNF-blocking therapy.

Bionanoconjugados catalíticos de tirosinase e nanopartículas de ouro

O presente estudo teve como principal objetivo a preparação de bionanoconjugados de Tirosinase e nanopartículas de ouro (AuNPs) com a finalidade de observar alterações positivas da atividade enzimática relativamente à enzima livre em solução, a partir da determinação dos respetivos parâmetros cinéticos. A atividade específica da tirosinase foi determinada com tirosina, L-3,4-dihidroxifenilalanina (L-DOPA) e 4-metilcatecol, tendo este último sido escolhido como substrato a utilizar no decorrer do restante trabalho experimental devido ao maior número de unidades específicas determinado para este substrato, bem como devido à menor concentração de enzima necessária para a realização dos ensaios. Os ensaios cinéticos com variação da temperatura e pH permitiram concluir que a 30 oC e a pH 6,5 a tirosinase é mais ativa. Os bionanoconjugados foram preparados incubando tirosinase de um dia para o outro com AuNPs. Três diferentes agentes de revestimento foram usados nos estudos: AuNPs sintetizadas revestidas por citrato, funcionalizadas com ácido 11-mercaptoundecanóico (MUA) e funcionalizadas com pentapéptido CALNN. Diferentes razões molares de tirosinase : AuNPs foram estudadas e, apesar da baixa reprodutibilidade dos resultados, os mais consistentes foram obtidos para a razão molar de 120. A conjugação da tirosinase com AuNPs aumentou a afinidade para o substrato e também a eficiência catalítica, em todos os bionanoconjugados, sendo que os melhores resultados foram observados para AuNPs funcionalizadas com CALNN, aumentando cerca de 48% a eficiência catalítica relativamente à tirosinase na sua forma livre em solução. As AuNPs funcionalizadas com citrato apresentaram maior consistência de resultados relativamente ao aumento da velocidade inicial da reacção. A modelação computacional da tirosinase a pH 6,5 revelou que a carga superficial da enzima é maioritariamente negativa, dificultando a adsorção na superfície das AuNPs, podendo esta ocorrer em regiões de maior carga positiva localizadas na subunidade L ou englobando regiões da subunidade H.

Botnet cluster identification

Botnets are a group of computers infected with a specific sub-set of a malware family and controlled by one individual, called botmaster. This kind of networks are used not only, but also for virtual extorsion, spam campaigns and identity theft. They implement different types of evasion techniques that make it harder for one to group and detect botnet traffic. This thesis introduces one methodology, called CONDENSER, that outputs clusters through a self-organizing map and that identify domain names generated by an unknown pseudo-random seed that is known by the botnet herder(s). Aditionally DNS Crawler is proposed, this system saves historic DNS data for fast-flux and double fastflux detection, and is used to identify live C&Cs IPs used by real botnets. A program, called CHEWER, was developed to automate the calculation of the SVM parameters and features that better perform against the available domain names associated with DGAs. CONDENSER and DNS Crawler were developed with scalability in mind so the detection of fast-flux and double fast-flux networks become faster. We used a SVM for the DGA classififer, selecting a total of 11 attributes and achieving a Precision of 77,9% and a F-Measure of 83,2%. The feature selection method identified the 3 most significant attributes of the total set of attributes. For clustering, a Self-Organizing Map was used on a total of 81 attributes. The conclusions of this thesis were accepted in Botconf through a submited article. Botconf is known conferênce for research, mitigation and discovery of botnets tailled for the industry, where is presented current work and research. This conference is known for having security and anti-virus companies, law enforcement agencies and researchers.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

Functional genomic analysis of heat stress in Vitis vinifera

Grapevine (Vitis vinifera) is one of most agro-economically important fruit crops worldwide, with a special relevance in Portugal where over 300 varieties are used for wine production. Due to global warming, temperature stress is currently a serious issue affecting crop production especially in temperate climates. Mobile genetic elements such as retrotransposons have been shown to be involved in environmental stress induced genetic and epigenetic modifications. In this study, sequences related to Grapevine Retrotransposon 1 (Gret1) were utilized to determine heat induced genomic and transcriptomic modifications in Touriga Nacional, a traditional Portuguese grapevine variety. For this purpose, growing canes were treated to 42 oC for four hours and leaf genomic DNA and RNA was utilized for various techniques to observe possible genomic alterations and variation in transcription levels of coding and non-coding sequences between non-treated plants and treated plants immediately after heat stress (HS-0 h) or after a 24 hour recovery period (HS-24 h). Heat stress was found to induce a significant decrease in Gret1 related sequences in HS-24 h leaves, indicating an effect of heat stress on genomic structure. In order to identify putative heat induced DNA modifications, genome wide approaches such as Amplified Fragment Length Polymorphism were utilized. This resulted in the identification of a polymorphic DNA fragment in HS-0 h and HS-24 h leaves whose sequence mapped to a genomic region flanking a house keeping gene (NADH) that is represented in multiple copies in the Vitis vinifera genome. Heat stress was also found to affect the transcript levels of various non-coding and gene coding sequences. Accordingly, quantitative real time PCR results established that Gret1 related sequences are up regulated immediately after heat stress whereas the level of transcript of genes involved in identification and repair of double strand breaks are significantly down regulated in HS-0 h plants. Taken together, the results of this work demonstrated heat stress affects both genomic integrity and transcription levels.

Biotransformation/separation routes to obtain pure enantiomers

The objective of the work presented in this thesis was the development of an innovative approach for the separation of enantiomers of secondary alcohols, combining the use of an ionic liquid (IL) - both as solvent for conducting enzymatic kinetic resolution and as acylating agent - with the use of carbon dioxide (CO2) as solvent for extraction. Menthol was selected for testing this reaction/separation approach due to the increasing demand for this substance, which is widely used in the pharmaceutical, cosmetics and food industries. With a view to using an ionic ester as acylating agent, whose conversion led to the release of ethanol, and due to the need to remove this alcohol so as to drive reaction equilibrium forward, a phase equilibrium study was conducted for the ehtanol/(±)-menthol/CO2 system, at pressures between 8 and 10 MPa and temperatures between 40 and 50 oC. It was found that CO2 is more selective towards ethanol, especially at the lowest pressure and highest temperature tested, leading to separation factors in the range 1.6-7.6. The pressure-temperature-composition data obtained were correlated with the Peng-Robinson equation of state and the Mathias-Klotz-Prausnitz mixing rule. The model fit the experimental results well, with an average absolute deviation (AAD) of 3.7 %. The resolution of racemic menthol was studied using two lipases, namely lipase from Candida rugosa (CRL) and immobilized lipase B from Candida antarctica (CALB), and two ionic acylating esters. No reaction was detected in either case. (R,S)-1-phenylethanol was used next, and it was found that with CRL low, nonselective, conversion of the alcohol took place, whereas CALB led to an enantiomeric excess (ee) of the substrate of 95%, at 30% conversion. Other acylating agents were tested for the resolution of (±)-menthol, namely vinyl esters and acid anhydrides, using several lipases and varying other parameters that affect conversion and enantioselectivity, such as substrate concentration, solvent and temperature. One such acylating agent was propionic anhydride. It was thus performed a phase equilibrium study on the propionic anhydride/CO2 system, at temperatures between 35 and 50 oC. This study revealed that, at 35 oC and pressures from 7 MPa, the system is monophasic for all compositions. The enzymatic catalysis studies carried out with propionic anhydride revealed that the extent of noncatalyzed reaction was high, with a negative effect on enantioselectivity. These studies showed also that it was possible to reduce considerably the impact of the noncatalyzed reaction relative to the reaction catalyzed by CRL by lowering temperature to 4 oC. Vinyl decanoate was shown to lead to the best results at conditions amenable to a process combining the use of supercritical CO2 as agent for post-reaction separation. The use of vinyl decanoate in a number of IL solvents, namely [bmim][PF6], [bmim][BF4], [hmim][PF6], [omim][PF6], and [bmim][Tf2N], led to an enantiomeric excess of product (eep) values of over 96%, at about 50% conversion, using CRL. In n-hexane and supercritical CO2, reaction progressed more slowly.(...)