13 resultados para Teeth Complications extraction


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The automatic acquisition of lexical associations from corpora is a crucial issue for Natural Language Processing. A lexical association is a recurrent combination of words that co-occur together more often than expected by chance in a given domain. In fact, lexical associations define linguistic phenomena such as idiomes, collocations or compound words. Due to the fact that the sense of a lexical association is not compositionnal, their identification is fundamental for the realization of analysis and synthesis that take into account all the subtilities of the language. In this report, we introduce a new statistically-based architecture that extracts from naturally occurring texts contiguous and non contiguous. For that purpose, three new concepts have been defined : the positional N-gram models, the Mutual Expectation and the GenLocalMaxs algorithm. Thus, the initial text is fisrtly transformed in a set of positionnal N-grams i.e ordered vectors of simple lexical units. Then, an association measure, the Mutual Expectation, evaluates the degree of cohesion of each positional N-grams based on the identification of local maximum values of Mutual Expectation. Great efforts have also been carried out to evaluate our metodology. For that purpose, we have proposed the normalisation of five well-known association measures and shown that both the Mutual Expectation and the GenLocalMaxs algorithm evidence significant improvements comparing to existent metodologies.

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Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfilment of the requirements for the degree of Master in Computer Science

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Dissertation to obtain a Master Degree in Biotechnology

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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

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Dissertação para a obtenção do Grau de Mestre em Engenharia Química e Bioquímica

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Phenolic acids are aromatic secondary plant metabolites, widely spread throughout the plant kingdom. Due to their biological and pharmacological properties, they have been playing an important role in phytotherapy and consequently techniques for their separation and purification are in need. This thesis aims at exploring new sustainable separation processes based on ionic liquids (ILs) in the extraction of biologically active phenolic acids. For that purpose, three phenolic acids with similar chemical structures were selected: cinnamic acid, p-coumaric acid and caffeic acid. In the last years, it has been shown that ionic liquids-based aqueous biphasic systems (ABSs) are valid alternatives for the extraction, recovery and purification of biomolecules when compared to conventional ABS or extractions carried out with organic solvents. In particular, cholinium-based ILs represent a clear step towards a greener chemistry, while providing means for the implementation of efficient techniques for the separation and purification of biomolecules. In this work, ABSs were implemented using cholinium carboxylate ILs using either high charge density inorganic salt (K3PO4) or polyethylene glycol (PEG) to promote the phase separation of aqueous solutions containing three different phenolic acids. These systems allow for the evaluation of effect of chemical structure of the anion on the extraction efficiency. Only one imidazolium-based IL was used in order to establish the effect of the cation chemical structure. The selective extraction of one single acid was also researched. Overall, it was observed that phenolic acids display very complex behaviours in aqueous solutions, from dimerization to polymerization and also hetero-association are quite frequent phenomena, depending on the pH conditions. These phenomena greatly hinder the correct quantification of these acids in solution.

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The extraction of relevant terms from texts is an extensively researched task in Text- Mining. Relevant terms have been applied in areas such as Information Retrieval or document clustering and classification. However, relevance has a rather fuzzy nature since the classification of some terms as relevant or not relevant is not consensual. For instance, while words such as "president" and "republic" are generally considered relevant by human evaluators, and words like "the" and "or" are not, terms such as "read" and "finish" gather no consensus about their semantic and informativeness. Concepts, on the other hand, have a less fuzzy nature. Therefore, instead of deciding on the relevance of a term during the extraction phase, as most extractors do, I propose to first extract, from texts, what I have called generic concepts (all concepts) and postpone the decision about relevance for downstream applications, accordingly to their needs. For instance, a keyword extractor may assume that the most relevant keywords are the most frequent concepts on the documents. Moreover, most statistical extractors are incapable of extracting single-word and multi-word expressions using the same methodology. These factors led to the development of the ConceptExtractor, a statistical and language-independent methodology which is explained in Part I of this thesis. In Part II, I will show that the automatic extraction of concepts has great applicability. For instance, for the extraction of keywords from documents, using the Tf-Idf metric only on concepts yields better results than using Tf-Idf without concepts, specially for multi-words. In addition, since concepts can be semantically related to other concepts, this allows us to build implicit document descriptors. These applications led to published work. Finally, I will present some work that, although not published yet, is briefly discussed in this document.

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Theropods form a highly successful and morphologically diversified group of dinosaurs that gave rise to birds. They include most, if not all, carnivorous dinosaurs, yet many theropod clades were secondarily adapted to piscivory, omnivory and herbivory, and theropods show a large array of skull and dentition morphologies. This work aims to investigate aspects of the evolution of theropod dinosaurs by analyzing in detail both the anatomy and ontogeny of teeth and quadrates in non-avian theropods, and by studying embryonic and adult material of a new species of theropod. A standardized list of terms and notations for each anatomical entity of the tooth, quadrate, and maxilla is here proposed with the goal of facilitating descriptions of these important cranial and dental elements. The distribution of thirty dental characters among 113 theropod taxa is investigated, and a list of diagnostic dental characters is proposed. As an example, four isolated theropod teeth from the Lourinhã Formation (Kimmeridgian‒Tithonian) of Portugal are described and identified based on a cladistic analysis performed on a data matrix of 141 dentition-based characters coded in 60 taxa. Two shed teeth are referred to an abelisaurid, providing the first record of Abelisauridae in the Jurassic of Laurasia and the one of the oldest records of this clade in the world, suggesting a possible radiation of Abelisauridae in Europe well before the Upper Cretaceous. The consensus tree resulting from this phylogenetic analysis, the most extensive on theropod teeth, indicates that theropod teeth provide reliable data for identification at approximately family level, and this method will help identifying theropod teeth with more confidence. A detailed description of the dentition of Megalosauridae is also provided, and a discriminant analysis performed on a dataset of numerical data collected on the teeth of 62 theropod taxa reveals that megalosaurid teeth are hardly distinguishable from other theropod clades with ziphodont dentition. This study highlights the importance of detailing anatomical descriptions and providing additional morphometric data on teeth with the purpose of helping to identify isolated theropod teeth. In order to evaluate the phylogenetic potential and investigate the evolutionary transformations of the quadrate, a phylogenetic morphometric analysis as well as a cladistic analysis using 98 discrete quadrate related characters were conducted. The quadrate morphology by its own provides a wealth of data with strong phylogenetic signal, and the phylogenetic morphometric analysis reveals two main morphotypes of the mandibular articulation of the quadrate linked to function. As an example, six isolated quadrates from the Kem Kem beds (Cenomanian) of Morocco are determined to be from juvenile and adult individuals of Spinosaurinae based on phylogenetic, morphometric, and phylogenetic morphometric analyses. Morphofunctional analysis of the spinosaurid mandibular articulation has shown that the posterior parts of the two mandibular rami displaced laterally when the jaw was depressed due to a mediolaterally oriented intercondylar sulcus of the quadrate. Such lateral movement of the mandibular ramus was possible due to a movable mandibular symphysis in spinosaurids, allowing the pharynx to be widened. A new species of theropod from the Lourinhã Formation of Portugal, Torvosaurus gurneyi, is erected based on a right maxilla and an incomplete caudal centrum. This taxon supports the mechanism of vicariance that occurred in the Iberian Meseta during the Late Jurassic when the proto-Atlantic was already well formed. A theropod clutch containing several crushed eggs and embryonic material is also assigned to this new species of Torvosaurus. Investigation on the maxilla ontogeny in basal tetanurans reveals that crown denticles, elongation of the anterior ramus, and fusion of interdental plates appear at a posthatchling stage. On the other hand, maxillary pneumaticity is already present at an embryonic stage in non-avian theropods.

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Currently the world swiftly adapts to visual communication. Online services like YouTube and Vine show that video is no longer the domain of broadcast television only. Video is used for different purposes like entertainment, information, education or communication. The rapid growth of today’s video archives with sparsely available editorial data creates a big problem of its retrieval. The humans see a video like a complex interplay of cognitive concepts. As a result there is a need to build a bridge between numeric values and semantic concepts. This establishes a connection that will facilitate videos’ retrieval by humans. The critical aspect of this bridge is video annotation. The process could be done manually or automatically. Manual annotation is very tedious, subjective and expensive. Therefore automatic annotation is being actively studied. In this thesis we focus on the multimedia content automatic annotation. Namely the use of analysis techniques for information retrieval allowing to automatically extract metadata from video in a videomail system. Furthermore the identification of text, people, actions, spaces, objects, including animals and plants. Hence it will be possible to align multimedia content with the text presented in the email message and the creation of applications for semantic video database indexing and retrieving.

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Application of Experimental Design techniques has proven to be essential in various research fields, due to its statistical capability of processing the effect of interactions among independent variables, known as factors, in a system’s response. Advantages of this methodology can be summarized in more resource and time efficient experimentations while providing more accurate results. This research emphasizes the quantification of 4 antioxidants extraction, at two different concentration, prepared according to an experimental procedure and measured by a Photodiode Array Detector. Experimental planning was made following a Central Composite Design, which is a type of DoE that allows to consider the quadratic component in Response Surfaces, a component that includes pure curvature studies on the model produced. This work was executed with the intention of analyzing responses, peak areas obtained from chromatograms plotted by the Detector’s system, and comprehending if the factors considered – acquired from an extensive literary review – produced the expected effect in response. Completion of this work will allow to take conclusions regarding what factors should be considered for the optimization studies of antioxidants extraction in a Oca (Oxalis tuberosa) matrix.

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The world energy consumption is expected to increase strongly in coming years, because of the emerging economies. Biomass is the only renewable carbon resource that is abundant enough to be used as a source of energy Grape pomace is one of the most abundant agro-industrial residues in the world, being a good biomass resource. The aim of this work is the valorization of grape pomace from white grapes (WWGP) and from red grapes (RWGP), through the extraction of phenolic compounds with antioxidant activity, as well as through the extraction/hydrolysis of carbohydrates, using subcritical water, or hot compressed water (HCW). The main focus of this work is the optimization of the process for WWGP, while for RWGP only one set of parameters were tested. The temperatures used were 170, 190 and 210 °C for WWGP, and 180 °C for RWGP. The water flow rates were 5 and 10 mL/min, and the pressure was always kept at 100 bar. Before performing HCW assays, both residues were characterized, revealing that WWGP is very rich in free sugars (around 40%) essentially glucose and fructose, while RWGP has higher contents of structural sugars, lignin, lipids and protein. For WWGP the best results were achieved at 210 °C and 10 mL/min: higher yield in water soluble compounds (69 wt.%), phenolics extraction (26.2 mg/g) and carbohydrates recovery (49.3 wt.% relative to the existing 57.8%). For RWGP the conditions were not optimized (180 °C and 5 mL/min), and the values of the yield in water soluble compounds (25 wt.%), phenolics extraction (19.5 mg/g) and carbohydrates recovery (11.4 wt.% relative to the existing 33.5%) were much lower. The antioxidant activity of the HCW extracts from each assay was determined, the best result being obtained for WWGP, namely for extracts obtained at 210 °C (EC50=20.8 μg/mL; EC50 = half maximum effective concentration; EC50 = 22.1 μg/mL for RWGP, at 180 ºC).

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Based in internet growth, through semantic web, together with communication speed improvement and fast development of storage device sizes, data and information volume rises considerably every day. Because of this, in the last few years there has been a growing interest in structures for formal representation with suitable characteristics, such as the possibility to organize data and information, as well as the reuse of its contents aimed for the generation of new knowledge. Controlled Vocabulary, specifically Ontologies, present themselves in the lead as one of such structures of representation with high potential. Not only allow for data representation, as well as the reuse of such data for knowledge extraction, coupled with its subsequent storage through not so complex formalisms. However, for the purpose of assuring that ontology knowledge is always up to date, they need maintenance. Ontology Learning is an area which studies the details of update and maintenance of ontologies. It is worth noting that relevant literature already presents first results on automatic maintenance of ontologies, but still in a very early stage. Human-based processes are still the current way to update and maintain an ontology, which turns this into a cumbersome task. The generation of new knowledge aimed for ontology growth can be done based in Data Mining techniques, which is an area that studies techniques for data processing, pattern discovery and knowledge extraction in IT systems. This work aims at proposing a novel semi-automatic method for knowledge extraction from unstructured data sources, using Data Mining techniques, namely through pattern discovery, focused in improving the precision of concept and its semantic relations present in an ontology. In order to verify the applicability of the proposed method, a proof of concept was developed, presenting its results, which were applied in building and construction sector.

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In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.