28 resultados para Intention-based models
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Manganese ferrite nanoparticles with a size distribution of 26 ± 7 nm (from TEM measurements) were synthesized by the coprecipitation method. The obtained nanoparticles exhibit a superparamagnetic behaviour at room temperature with a magnetic squareness of 0.016 and a coercivity field of 6.3 Oe. These nanoparticles were either entrapped in liposomes (aqueous magnetoliposomes, AMLs) or covered with a lipid bilayer, forming solid magnetoliposomes (SMLs). Both types of magnetoliposomes, exhibiting sizes below or around 150 nm, were found to be suitable for biomedical applications. Membrane fusion between magnetoliposomes (both AMLS and SMLs) and GUVs (giant unilamellar vesicles), the latter used as models of cell membranes, was confirmed by F¨orster Resonance Energy Transfer (FRET) assays, using a NBD labeled lipid as the energy donor and Nile Red or rhodamine B-DOPE as the energy acceptor. A potential antitumor thienopyridine derivative was successfully incorporated into both aqueous and solid magnetoliposomes, pointing to a promising application of these systems in oncological therapy, simultaneously as hyperthermia agents and nanocarriers for antitumor drugs.
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Software reconfigurability became increasingly relevant to the architectural process due to the crescent dependency of modern societies on reliable and adaptable systems. Such systems are supposed to adapt themselves to surrounding environmental changes with minimal service disruption, if any. This paper introduces an engine that statically applies reconfigurations to (formal) models of software architectures. Reconfigurations are specified using a domain specific language— ReCooPLa—which targets the manipulation of software coordinationstructures,typicallyusedinservice-orientedarchitectures(soa).Theengine is responsible for the compilation of ReCooPLa instances and their application to the relevant coordination structures. The resulting configurations are amenable to formal analysis of qualitative and quantitative (probabilistic) properties.
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The aim of this paper is to predict time series of SO2 concentrations emitted by coal-fired power stations in order to estimate in advance emission episodes and analyze the influence of some meteorological variables in the prediction. An emission episode is said to occur when the series of bi-hourly means of SO2 is greater than a specific level. For coal-fired power stations it is essential to predict emission epi- sodes sufficiently in advance so appropriate preventive measures can be taken. We proposed a meth- odology to predict SO2 emission episodes based on using an additive model and an algorithm for variable selection. The methodology was applied to the estimation of SO2 emissions registered in sampling lo- cations near a coal-fired power station located in Northern Spain. The results obtained indicate a good performance of the model considering only two terms of the time series and that the inclusion of the meteorological variables in the model is not significant.
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NIPE WP 04/ 2016
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Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)
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Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.
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"Series: Solid mechanics and its applications, vol. 226"
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"Series: Solid mechanics and its applications, vol. 226"
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"Series: Solid mechanics and its applications, vol. 226"
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The main purpose of the poster is to present how the Unified Modeling Language (UML) can be used for diagnosing and optimizing real industrial production systems. By using a car radios production line as a case study, the poster shows the modeling process that can be followed during the analysis phase of complex control applications. In order to guarantee the continuity mapping of the models, the authors propose some guidelines to transform the use cases diagrams into a single object diagram, which is the main diagram for the next phases of the development.
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Dissertação de mestrado em Estatística
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"Published online before print November 20, 2015"
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Tese de Doutoramento em Ciências da Saúde