Design of binary polymeric systems containing ɩ-carrageenan and hydroxypropylcellulose for use in cataract surgery.

This study describes the design and characterisation of the rheological and mechanical properties of binary polymeric systems composed of 2-Hydroxypropylcellulose and ɩ-carrageenan, designed as ophthalmic viscoelastic devices (OVDs). Platforms were characterised using dilute solution, flow and oscillatory rheometry and texture profile analysis. Rheological synergy between the two polymers was observed both in the dilute and gel states. All platforms exhibited pseudoplastic flow. Increasing polymer concentrations significantly decreased the loss tangent and rate index yet increased the storage and loss moduli, consistency, gel hardness, compressibility and adhesiveness, the latter being related to the in-vivo retention properties of the platforms. Binary polymeric platforms exhibited unique physicochemical properties, properties that could not be engineered using mono-polymeric platforms. Using characterisation methods that provide information relevant to their clinical performance, low-cost binary platforms (3% hydroxypropylcellulose and either 1% or 2% ɩ-carrageenan) were identified that exhibited rheological, textural and viscoelastic properties advantageous for use as OVDs.

Projeto de conceito e estrutura de website para o combate ao abandono animal em Portugal

Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

Absolute type shaft encoding using LFSR

Maximal-length binary sequences have been known for a long time. They have many interesting properties, one of them is that when taken in blocks of n consecutive positions they form 2ⁿ-1 different codes in a closed circular sequence. This property can be used for measuring absolute angular positions as the circle can be divided in as many parts as different codes can be retrieved. This paper describes how can a closed binary sequence with arbitrary length be effectively designed with the minimal possible block-length, using linear feedback shift registers (LFSR). Such sequences can be used for measuring a specified exact number of angular positions, using the minimal possible number of sensors that linear methods allow.

Estudio de las capas de acoplamiento y alternativas al reflector de Bragg en estructuras BAW-CRF

Las capas de acoplamiento son un elemento clave en los dispositivos BAW CRF. El factor de acoplamiento K de estas capas permite el diseño de una determinada respuesta. Debido al limitado número de materiales con las que implementarlas, las soluciones que utilizan capas de λ/4 ofrecen un rango discreto de K. Por otra parte, el reflector de Bragg es un mecanismo de aislamiento mecánico entre el sustrato y la estructura BAW que está formado por capas alternas de alta y baja impedancia acústica de λ/4. El problema que presenta es la reducción del factor de calidad asociado a las pérdidas producida por las ondas shear. Este proyecto presenta un método para la obtención de un rango continuo de factores de acoplamiento y estudia la mejora del factor de calidad de las estructuras BAW con reflector de Bragg partiendo de dos materiales con alta y baja impedancia acústica.

A simple randomized algorithm for consistent sequential prediction of ergodic time series

We present a simple randomized procedure for the prediction of a binary sequence. The algorithm uses ideas from recent developments of the theory of the prediction of individual sequences. We show that if thesequence is a realization of a stationary and ergodic random process then the average number of mistakes converges, almost surely, to that of the optimum, given by the Bayes predictor.

A data-dependent skeleton estimate and a scale-sensitive dimension for classification

The classical binary classification problem is investigatedwhen it is known in advance that the posterior probability function(or regression function) belongs to some class of functions. We introduceand analyze a method which effectively exploits this knowledge. The methodis based on minimizing the empirical risk over a carefully selected``skeleton'' of the class of regression functions. The skeleton is acovering of the class based on a data--dependent metric, especiallyfitted for classification. A new scale--sensitive dimension isintroduced which is more useful for the studied classification problemthan other, previously defined, dimension measures. This fact isdemonstrated by performance bounds for the skeleton estimate in termsof the new dimension.

Recherche et caractérisation de systèmes binaires dont l'une des composantes est de faible masse

Nous présentons la découverte de quatorze nouveaux systèmes binaires ayant une séparation supérieure à 250 UA et dont au moins l'une des composantes est une naine M ou une naine L. Ces systèmes ont d'abord été identifiés en cherchant des objets ayant un mouvement propre commun autour d'étoiles connues possédant un mouvement propre élevé, grâce à une corrélation croisée de grands relevés du ciel dans l'infrarouge proche (2MASS, SDSS et SIMP). Un suivi astrométrique, afin de confirmer le mouvement propre commun, a été réalisé sur toutes les cibles avec la caméra SIMON et/ou la caméra CPAPIR à l'Observatoire du Mont-Mégatic (OMM) ou à l'Observatoire interaméricain du Cerro Tololo (CTIO). Un suivi spectroscopique a aussi été effectué sur la plupart des compagnons avec GMOS ou GNIRS à Gemini afin de déterminer leurs types spectraux. La probabilité que deux objets forment un système binaire par hasard a été évaluée afin de s'assurer que les couples candidats que nous présentons soient réellement liés.Un de nos nouveaux systèmes a un compagnon de masse sous-stellaire : 2M1259+1001 (L4.5). L'étude des systèmes que nous avons découverts pourra, entre autre, nous aider à mieux comprendre les mécanismes de formation des étoiles de très faible masse et des naines brunes.

Do construction companies need to match employees' expectations?

Commitment of employees is relatively low in construction. This problem is exasperated by companies inability to attract, motivate, and retain talent that is then often channelled into other more attractive industrial sectors where the prospects, conditions and rewards are perceived to be much higher. The purpose of this study is thus primarily to develop a generic model to maximise employees' engagement, improve their motivation and increase the retention levels. To achieve this aim, the investigation looks into how perceived employment obligations and expectations impact commitment and through that organisational performance. The study is based on the postulations of Luhmann's theory of social systems with communication viewed as a constitutive element of a social system. Consequently expectations of a particular party in an employment relationship are represented in a communicative space requiring the other party's understanding in order to align expectations of both sides in the relationship. Explicitly, alignment of by an employee perceived manager's expectations determines his/ her commitment to fulfil obligations towards the manager. The result of this first stage of research is a conceptual model developed following the substantial supporting evidence in the literature and it forms the framework for mitigation of low commitment, motivation and retention of employees. The model particularly focuses on factors affecting employees' perceived expectations like reneging, incongruence and the process of communication. In the future the model will be validated using empirical data from a combination of observational and enquiry-based research. Once completed, the model will provide a framework for informing Human Resource Management policies with the aim to improve commitment of employees, increase the levels of retention and consequently improve the performance of construction organisations.

Genetic structure and systematic relationships within the Ophrys fuciflora aggregate (Orchidaceae: Orchidinae): high diversity in Kent and a wind-induced discontinuity bisecting the Adriatic

A recent phylogenetic study based on multiple datasets is used as the framework for a more detailed examination of one of the ten molecularly circumscribed groups identified, the Ophrys fuciflora aggregate. The group is highly morphologically variable, prone to phenotypic convergence, shows low levels of sequence divergence and contains an unusually large proportion of threatened taxa, including the rarest Ophrys species in the UK. The aims of this study were to (a) circumscribe minimum resolvable genetically distinct entities within the O. fuciflora aggregate, and (b) assess the likelihood of gene flow between genetically and geographically distinct entities at the species and population levels. Fifty-five accessions sampled in Europe and Asia Minor from the O. fuciflora aggregate were studied using the AFLP genetic fingerprinting technique to evaluate levels of infraspecific and interspecific genetic variation and to assess genetic relationships between UK populations of O. fuciflora s.s. in Kent and in their continental European and Mediterranean counterparts. The two genetically and geographically distinct groups recovered, one located in England and central Europe and one in south-eastern Europe, are incongruent with current species delimitation within the aggregate as a whole and also within O. fuciflora s.s. Genetic diversity is higher in Kent than in the rest of western and central Europe. Gene flow is more likely to occur between populations in closer geographical proximity than those that are morphologically more similar. Little if any gene flow occurs between populations located in the south-eastern Mediterranean and those dispersed throughout the remainder of the distribution, revealing a genetic discontinuity that runs north-south through the Adriatic. This discontinuity is also evident in other clades of Ophrys and is tentatively attributed to the long-term influence of prevailing winds on the long-distance distribution of pollinia and especially seeds. A cline of gene flow connects populations from Kent and central and southern Europe; these individuals should therefore be considered part of an extensive meta-population. Gene flow is also evident among populations from Kent, which appear to constitute a single metapopulation. They show some evidence of hybridization, and possibly also introgression, with O. apifera.

Uso da análise discriminante regularizada (RDA) no reconhecimento de padrões em imagens digitais hiperespectral de sensoriamento remoto

Em cenas naturais, ocorrem com certa freqüência classes espectralmente muito similares, isto é, os vetores média são muito próximos. Em situações como esta, dados de baixa dimensionalidade (LandSat-TM, Spot) não permitem uma classificação acurada da cena. Por outro lado, sabe-se que dados em alta dimensionalidade [FUK 90] tornam possível a separação destas classes, desde que as matrizes covariância sejam suficientemente distintas. Neste caso, o problema de natureza prática que surge é o da estimação dos parâmetros que caracterizam a distribuição de cada classe. Na medida em que a dimensionalidade dos dados cresce, aumenta o número de parâmetros a serem estimados, especialmente na matriz covariância. Contudo, é sabido que, no mundo real, a quantidade de amostras de treinamento disponíveis, é freqüentemente muito limitada, ocasionando problemas na estimação dos parâmetros necessários ao classificador, degradando portanto a acurácia do processo de classificação, na medida em que a dimensionalidade dos dados aumenta. O Efeito de Hughes, como é chamado este fenômeno, já é bem conhecido no meio científico, e estudos vêm sendo realizados com o objetivo de mitigar este efeito. Entre as alternativas propostas com a finalidade de mitigar o Efeito de Hughes, encontram-se as técnicas de regularização da matriz covariância. Deste modo, técnicas de regularização para a estimação da matriz covariância das classes, tornam-se um tópico interessante de estudo, bem como o comportamento destas técnicas em ambientes de dados de imagens digitais de alta dimensionalidade em sensoriamento remoto, como por exemplo, os dados fornecidos pelo sensor AVIRIS. Neste estudo, é feita uma contextualização em sensoriamento remoto, descrito o sistema sensor AVIRIS, os princípios da análise discriminante linear (LDA), quadrática (QDA) e regularizada (RDA) são apresentados, bem como os experimentos práticos dos métodos, usando dados reais do sensor. Os resultados mostram que, com um número limitado de amostras de treinamento, as técnicas de regularização da matriz covariância foram eficientes em reduzir o Efeito de Hughes. Quanto à acurácia, em alguns casos o modelo quadrático continua sendo o melhor, apesar do Efeito de Hughes, e em outros casos o método de regularização é superior, além de suavizar este efeito. Esta dissertação está organizada da seguinte maneira: No primeiro capítulo é feita uma introdução aos temas: sensoriamento remoto (radiação eletromagnética, espectro eletromagnético, bandas espectrais, assinatura espectral), são também descritos os conceitos, funcionamento do sensor hiperespectral AVIRIS, e os conceitos básicos de reconhecimento de padrões e da abordagem estatística. No segundo capítulo, é feita uma revisão bibliográfica sobre os problemas associados à dimensionalidade dos dados, à descrição das técnicas paramétricas citadas anteriormente, aos métodos de QDA, LDA e RDA, e testes realizados com outros tipos de dados e seus resultados.O terceiro capítulo versa sobre a metodologia que será utilizada nos dados hiperespectrais disponíveis. O quarto capítulo apresenta os testes e experimentos da Análise Discriminante Regularizada (RDA) em imagens hiperespectrais obtidos pelo sensor AVIRIS. No quinto capítulo são apresentados as conclusões e análise final. A contribuição científica deste estudo, relaciona-se à utilização de métodos de regularização da matriz covariância, originalmente propostos por Friedman [FRI 89] para classificação de dados em alta dimensionalidade (dados sintéticos, dados de enologia), para o caso especifico de dados de sensoriamento remoto em alta dimensionalidade (imagens hiperespectrais). A conclusão principal desta dissertação é que o método RDA é útil no processo de classificação de imagens com dados em alta dimensionalidade e classes com características espectrais muito próximas.

Structural studies of shikimate 5-dehydrogenase from Mycobacterium tuberculosis

Tuberculosis (TB) remains the leading cause of mortality due to a single bacterial pathogen, Mycobacterium tuberculosis. The reemergence of TB as a potential public health threat, the high susceptibility of human immunodeficiency virus-infected persons to the disease, the proliferation of multi-drug-resistant strains (MDR-TB) and, more recently, of extensively drug resistant isolates (XDR-TB) have created a need for the development of new antimycobacterial agents. Amongst the several proteins and/or enzymes to be studied as potential targets to develop novel drugs against M. tuberculosis, the enzymes of the shikimate pathway are attractive targets because they are essential in algae, higher plants, bacteria, and fungi, but absent from mammals. The mycobacterial shikimate pathway leads to the biosynthesis of chorismate, which is a precursor of aromatic amino acids, naphthoquinones, menaquinones, and mycobactins. Here we report the structural studies by homology modeling and circular dichroism spectroscopy of the shikimate dehydrogenase from M. tuberculosis (MtSDH), which catalyses the fourth step of the shikimate pathway. Our structural models show that the MtSDH has similar structure to other shikimate dehydrogenase structures previously reported either in presence or absence of NADP, despite the low amino acid sequence identity. The circular dichroism spectra corroborate the secondary structure content observed in the MtSDH models developed. The enzyme was stable up to 50 degrees C presenting a cooperative unfolding profile with the midpoint of the unfolding temperature value of similar to 63-64 degrees C, as observed in the unfolding experiment followed by circular dichroism. Our MtSDH structural models and circular dichroism data showed small conformational changes induced by NADP binding. We hope that the data presented here will assist the rational design of antitubercular agents.

Doses e épocas de aplicação de etil-trinexapac em arroz de terras altas irrigado por aspersão

Pós-graduação em Agronomia - FEIS

Complexos intermetálicos de irídio e európio: sensibilização via banda de transferência de carga metal-ligante

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Multistage Transmission Expansion Planning Considering Fixed Series Compensation Allocation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Simple Artificial Life Model Explains Irrational Behavior in Human Decision-Making

Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.