11 resultados para DIRECT EXTRACTION METHOD


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International Biodeterioration & Biodegradation 64(2010)388 e 396

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau de Mestre em Mestrado em Conservação e Restauro, especialização em Ciências da Conservação

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A supercritical carbon dioxide (scCO2) based oil extraction method was implemented on olive pomace (alperujo), and an oil yield of 25,5 +/- 0,8% (goil/gdry residue) was obtained. By Soxhlet extraction with hexane, an oil extraction yield of 28,9 +/- 0,8 % was obtained, which corresponds to an efficiency of 88,4 +/- 4,8 % for the supercritical method. The scCO2 extraction process was optimized for operating conditions of 50 MPa and 348,15 K, for which an oil loading of 32,60 g oil/kg CO2 was calculated. As a proof of concept, olive pomace was used as feedstock for biodiesel production, in a process combining the use of lipase as a catalyst with the use of scCO2 as a solvent, and integrating the steps of oil extraction, oil to biodiesel transesterification and subsequent separation of the latter. In the conducted experiments, FAME (fatty acid methyl ester) purities of 90% were obtained, with the following operating parameters: an oil:methanol molar ratio of 1:24; a residence time of 7,33 and 11,6 mins; a pressure of 40 MPa; a temperature of 313,15 K; and Lipozyme (Mucor miehei; Sigma-Aldritch) as an enzyme. However, oscillations of FAME purity were registered throughout the experiments, which could possibly be due to methanol accumulation in the enzymatic reactor. Finally, the phenolic content of olive pomace, and the effect of the drying process – oven or freeze-drying – and the extraction methods – hydro-alcoholic method and supercritical method – on the phenolic content were analysed. It was verified that the oven-drying process on the olive pomace preserved 90,1 +/- 3,6 % of the total phenolic content. About 62,3 +/- 5,53% of the oven-dried pomace phenolic content was extracted using scCO2 at 60 MPa and 323,15 K. Seven individual phenols – hydroxytyrosol, tyrosol, oleuropein, quercetin, caffeic acid, ferulic acid and p-coumaric acid – were identified and quantified by HPLC.

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

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Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores – Sistemas Digitais e Percepcionais pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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Sustainable Construction, Materials and Practice, p. 426-432

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Dissertation presented at Faculdade de Ciências e Tecnologia from Universidade Nova de Lisboa to obtain the degree of Master in Chemical and Biochemical Engineering

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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Research literature and regulators are unconditional in pointing the disclosure of operating cash flow through direct method a section of unique information. Besides the intuitive facet, it is also consistent in forecasting future operating cash flows and a cohesive piece to financial statement puzzle. Bearing this in mind, I produce an analysis on the usefulness and predictive ability on the disclosure of gross cash receipts and payments over the disclosure of reconciliation between net income and accruals for two markets with special features, Portugal and Spain. Results validate the usefulness of direct method format in predicting future operating cash flow. Key

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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.