905 resultados para CENTERLINE EXTRACTION
Resumo:
O sector do turismo é uma área francamente em crescimento em Portugal e que tem desenvolvido a sua divulgação e estratégia de marketing. Contudo, apenas se prende com indicadores de desempenho e de oferta instalada (número de quartos, hotéis, voos, estadias), deixando os indicadores estatísticos em segundo plano. De acordo com o “ Travel & tourism Competitiveness Report 2013”, do World Economic Forum, classifica Portugal em 72º lugar no que respeita à qualidade e cobertura da informação estatística, disponível para o sector do Turismo. Refira-se que Espanha ocupa o 3º lugar. Uma estratégia de mercado, sem base analítica, que sustente um quadro de orientações específico e objetivo, com relevante conhecimento dos mercados alvo, dificilmente é compreensível ou até mesmo materializável. A implementação de uma estrutura de Business Intelligence que permita a realização de um levantamento e tratamento de dados que possibilite relacionar e sustentar os resultados obtidos no sector do turismo revela-se fundamental e crucial, para que sejam criadas estratégias de mercado. Essas estratégias são realizadas a partir da informação dos turistas que nos visitam, e dos potenciais turistas, para que possam ser cativados no futuro. A análise das características e dos padrões comportamentais dos turistas permite definir perfis distintos e assim detetar as tendências de mercado, de forma a promover a oferta dos produtos e serviços mais adequados. O conhecimento obtido permite, por um lado criar e disponibilizar os produtos mais atrativos para oferecer aos turistas e por outro informá-los, de uma forma direcionada, da existência desses produtos. Assim, a associação de uma recomendação personalizada que, com base no conhecimento de perfis do turista proceda ao aconselhamento dos melhores produtos, revela-se como uma ferramenta essencial na captação e expansão de mercado.
Resumo:
Dissertação para a obtenção do Grau de Mestre em Engenharia Química e Bioquímica
Resumo:
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.
Resumo:
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.
Resumo:
Introduction Polymerase chain reaction (PCR) may offer an alternative diagnostic option when clinical signs and symptoms suggest visceral leishmaniasis (VL) but microscopic scanning and serological tests provide negative results. PCR using urine is sensitive enough to diagnose human visceral leishmaniasis (VL). However, DNA quality is a crucial factor for successful amplification. Methods A comparative performance evaluation of DNA extraction methods from the urine of patients with VL using two commercially available extraction kits and two phenol-chloroform protocols was conducted to determine which method produces the highest quality DNA suitable for PCR amplification, as well as the most sensitive, fast and inexpensive method. All commercially available kits were able to shorten the duration of DNA extraction. Results With regard to detection limits, both phenol: chloroform extraction and the QIAamp DNA Mini Kit provided good results (0.1 pg of DNA) for the extraction of DNA from a parasite smaller than Leishmania (Leishmania) infantum (< 100fg of DNA). However, among 11 urine samples from subjects with VL, better performance was achieved with the phenol:chloroform method (8/11) relative to the QIAamp DNA Mini Kit (4/11), with a greater number of positive samples detected at a lower cost using PCR. Conclusion Our results demonstrate that phenol:chloroform with an ethanol precipitation prior to extraction is the most efficient method in terms of yield and cost, using urine as a non-invasive source of DNA and providing an alternative diagnostic method at a low cost.
Resumo:
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.
Resumo:
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.
Resumo:
Abstract: INTRODUCTION : Molecular analyses are auxiliary tools for detecting Koch's bacilli in clinical specimens from patients with suspected tuberculosis (TB). However, there are still no efficient diagnostic tests that combine high sensitivity and specificity and yield rapid results in the detection of TB. This study evaluated single-tube nested polymerase chain reaction (STNPCR) as a molecular diagnostic test with low risk of cross contamination for detecting Mycobacterium tuberculosis in clinical samples. METHODS: Mycobacterium tuberculosis deoxyribonucleic acid (DNA) was detected in blood and urine samples by STNPCR followed by agarose gel electrophoresis. In this system, reaction tubes were not opened between the two stages of PCR (simple and nested). RESULTS: STNPCR demonstrated good accuracy in clinical samples with no cross contamination between microtubes. Sensitivity in blood and urine, analyzed in parallel, was 35%-62% for pulmonary and 41%-72% for extrapulmonary TB. The specificity of STNPCR was 100% in most analyses, depending on the type of clinical sample (blood or urine) and clinical form of disease (pulmonary or extrapulmonary). CONCLUSIONS: STNPCR was effective in detecting TB, especially the extrapulmonary form for which sensitivity was higher, and had the advantage of less invasive sample collection from patients for whom a spontaneous sputum sample was unavailable. With low risk of cross contamination, the STNPCR can be used as an adjunct to conventional methods for diagnosing TB.
Resumo:
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).
Resumo:
Abstract: INTRODUCTION: Before 2004, the occurrence of acute Chagas disease (ACD) by oral transmission associated with food was scarcely known or investigated. Originally sporadic and circumstantial, ACD occurrences have now become frequent in the Amazon region, with recently related outbreaks spreading to several Brazilian states. These cases are associated with the consumption of açai juice by waste reservoir animals or insect vectors infected with Trypanosoma cruzi in endemic areas. Although guidelines for processing the fruit to minimize contamination through microorganisms and parasites exist, açai-based products must be assessed for quality, for which the demand for appropriate methodologies must be met. METHODS: Dilutions ranging from 5 to 1,000 T. cruzi CL Brener cells were mixed with 2mL of acai juice. Four Extraction of T. cruzi DNA methods were used on the fruit, and the cetyltrimethyl ammonium bromide (CTAB) method was selected according to JRC, 2005. RESULTS: DNA extraction by the CTAB method yielded satisfactory results with regard to purity and concentration for use in PCR. Overall, the methods employed proved that not only extraction efficiency but also high sensitivity in amplification was important. CONCLUSIONS: The method for T. cruzi detection in food is a powerful tool in the epidemiological investigation of outbreaks as it turns epidemiological evidence into supporting data that serve to confirm T. cruzi infection in the foods. It also facilitates food quality control and assessment of good manufacturing practices involving acai-based products.
Resumo:
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.
Resumo:
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.
Resumo:
[Excerpt] Cupuassu (Theobroma grandiflorum), tucumã (Astrocaryum aculeatum), peach palm (Bactris gasipaes) and abricó (American Mammea L.) are exotic fruits found in the Brazilian Amazon rainforest. All of them are well known by the native populations, and for centuries the pulps have been used in the production of juices, deserts, jams, syrups, and alcoholic beverages, among others. Additionally, the fruit seeds have been used as animal feed, fertilizers or to plant new seedlings, but a great part of these seeds are usually discarded. (...)
Resumo:
[Excerpt] Isolation and purification of valuable compounds are very important processes to valorize agro-food byproducts. Currently, protein extraction and development of environmentally friendly technologies are industrially relevant topics [1]. Among the extracted proteins from byproducts proteases are a relevant group for industrial applications. These enzymes are a class of hydrolytic enzymes capable of cleaving the peptide bonds of proteins chains and are essential in physiological processes [2]. (...)
Resumo:
In search to increase the offer of liquid, clean, renewable and sustainable energy in the world energy matrix, the use of lignocellulosic materials (LCMs) for bioethanol production arises as a valuable alternative. The objective of this work was to analyze and compare the performance of Saccharomyces cerevisiae, Pichia stipitis and Zymomonas mobilis in the production of bioethanol from coconut fibre mature (CFM) using different strategies: simultaneous saccharification and fermentation (SSF) and semi-simultaneous saccharification and fermentation (SSSF). The CFM was pretreated by hydrothermal pretreatment catalyzed with sodium hydroxide (HPCSH). The pretreated CFM was characterized by X-ray diffractometry and SEM, and the lignin recovered in the liquid phase by FTIR and TGA. After the HPCSH pretreatment (2.5% (v/v) sodium hydroxide at 180 °C for 30 min), the cellulose content was 56.44%, while the hemicellulose and lignin were reduced 69.04% and 89.13%, respectively. Following pretreatment, the obtained cellulosic fraction was submitted to SSF and SSSF. Pichia stipitis allowed for the highest ethanol yield 90.18% in SSSF, 91.17% and 91.03% were obtained with Saccharomyces cerevisiae and Zymomonas mobilis, respectively. It may be concluded that the selection of the most efficient microorganism for the obtention of high bioethanol production yields from cellulose pretreated by HPCSH depends on the operational strategy used and this pretreatment is an interesting alternative for add value of coconut fibre mature compounds (lignin, phenolics) being in accordance with the biorefinery concept.