929 resultados para location-dependent data query
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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OBJECTIVES: Nevirapine is widely used for the treatment of HIV-1 infection; however, its chronic use has been associated with severe liver and skin toxicity. Women are at increased risk for these toxic events, but the reasons for the sex-related differences are unclear. Disparities in the biotransformation of nevirapine and the generation of toxic metabolites between men and women might be the underlying cause. The present work aimed to explore sex differences in nevirapine biotransformation as a potential factor in nevirapine-induced toxicity. METHODS: All included subjects were adults who had been receiving 400 mg of nevirapine once daily for at least 1 month. Blood samples were collected and the levels of nevirapine and its phase I metabolites were quantified by HPLC. Anthropometric and clinical data, and nevirapine metabolite profiles, were assessed for sex-related differences. RESULTS: A total of 52 patients were included (63% were men). Body weight was lower in women (P = 0.028) and female sex was associated with higher alkaline phosphatase (P = 0.036) and lactate dehydrogenase (P = 0.037) levels. The plasma concentrations of nevirapine (P = 0.030) and the metabolite 3-hydroxy-nevirapine (P = 0.035), as well as the proportions of the metabolites 12-hydroxy-nevirapine (P = 0.037) and 3-hydroxy-nevirapine (P = 0.001), were higher in women, when adjusted for body weight. CONCLUSIONS: There was a sex-dependent variation in nevirapine biotransformation, particularly in the generation of the 12-hydroxy-nevirapine and 3-hydroxy-nevirapine metabolites. These data are consistent with the sex-dependent formation of toxic reactive metabolites, which may contribute to the sex-dependent dimorphic profile of nevirapine toxicity.
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Dissertation submitted in Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the degree of Master of Biomedical Engineering
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Companies are increasingly more and more dependent on distributed web-based software systems to support their businesses. This increases the need to maintain and extend software systems with up-to-date new features. Thus, the development process to introduce new features usually needs to be swift and agile, and the supporting software evolution process needs to be safe, fast, and efficient. However, this is usually a difficult and challenging task for a developer due to the lack of support offered by programming environments, frameworks, and database management systems. Changes needed at the code level, database model, and the actual data contained in the database must be planned and developed together and executed in a synchronized way. Even under a careful development discipline, the impact of changing an application data model is hard to predict. The lifetime of an application comprises changes and updates designed and tested using data, which is usually far from the real, production, data. So, coding DDL and DML SQL scripts to update database schema and data, is the usual (and hard) approach taken by developers. Such manual approach is error prone and disconnected from the real data in production, because developers may not know the exact impact of their changes. This work aims to improve the maintenance process in the context of Agile Platform by Outsystems. Our goal is to design and implement new data-model evolution features that ensure a safe support for change and a sound migration process. Our solution includes impact analysis mechanisms targeting the data model and the data itself. This provides, to developers, a safe, simple, and guided evolution process.
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This study intends to explore the impact of customer experience on customer satisfaction and loyalty by trying to understand how location-based mobile marketing might enhance the customer experience. Primary data was collected from 201 smartphone users in 24 countries. Results have indicated that targeted location-based marketing positively influences customers’ experiences. Besides, the analysis has also shown a favorable impact on customers’ satisfaction and self-perceived loyalty. This suggests that location-based mobile marketing has the potential to positively add value to a customer’s experience and should therefore be considered an important tool in marketing communications.
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Information systems are widespread and used by anyone with computing devices as well as corporations and governments. It is often the case that security leaks are introduced during the development of an application. Reasons for these security bugs are multiple but among them one can easily identify that it is very hard to define and enforce relevant security policies in modern software. This is because modern applications often rely on container sharing and multi-tenancy where, for instance, data can be stored in the same physical space but is logically mapped into different security compartments or data structures. In turn, these security compartments, to which data is classified into in security policies, can also be dynamic and depend on runtime data. In this thesis we introduce and develop the novel notion of dependent information flow types, and focus on the problem of ensuring data confidentiality in data-centric software. Dependent information flow types fit within the standard framework of dependent type theory, but, unlike usual dependent types, crucially allow the security level of a type, rather than just the structural data type itself, to depend on runtime values. Our dependent function and dependent sum information flow types provide a direct, natural and elegant way to express and enforce fine grained security policies on programs. Namely programs that manipulate structured data types in which the security level of a structure field may depend on values dynamically stored in other fields The main contribution of this work is an efficient analysis that allows programmers to verify, during the development phase, whether programs have information leaks, that is, it verifies whether programs protect the confidentiality of the information they manipulate. As such, we also implemented a prototype typechecker that can be found at http://ctp.di.fct.unl.pt/DIFTprototype/.
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Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.
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Studies in Computational Intelligence, 616
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The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.g. death or alive) of an individual is not a fixed characteristic, and it varies along the study. In such cases, when evaluating the performance of the biomarker, several issues should be taken into account: first, the time-dependent nature of the disease status; and second, the presence of incomplete data (e.g. censored data typically present in survival studies). Accordingly, to assess the discrimination power of continuous biomarkers for time-dependent disease outcomes, time-dependent extensions of true positive rate, false positive rate, and ROC curve have been recently proposed. In this work, we present new nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker. The proposed estimators can accommodate right-censored data, as well as covariate-dependent censoring. The behavior of the estimators proposed in this study will be explored through simulations and illustrated using data from a cohort of patients who suffered from acute coronary syndrome.
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Biofilm research is growing more diverse and dependent on high-throughput technologies and the large-scale production of results aggravates data substantiation. In particular, it is often the case that experimental protocols are adapted to meet the needs of a particular laboratory and no statistical validation of the modified method is provided. This paper discusses the impact of intra-laboratory adaptation and non-rigorous documentation of experimental protocols on biofilm data interchange and validation. The case study is a non-standard, but widely used, workflow for Pseudomonas aeruginosa biofilm development, considering three analysis assays: the crystal violet (CV) assay for biomass quantification, the XTT assay for respiratory activity assessment, and the colony forming units (CFU) assay for determination of cell viability. The ruggedness of the protocol was assessed by introducing small changes in the biofilm growth conditions, which simulate minor protocol adaptations and non-rigorous protocol documentation. Results show that even minor variations in the biofilm growth conditions may affect the results considerably, and that the biofilm analysis assays lack repeatability. Intra-laboratory validation of non-standard protocols is found critical to ensure data quality and enable the comparison of results within and among laboratories.
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This paper investigates the geographical distribution and concentration of firms’ innovation persistence and innovation type (product and process) based on three waves of the Portuguese Community Innovation Survey data covering the period 1998–2006. The main findings are: 1) both innovation persistence and innovation type are asymmetrically distributed across Portuguese regions, 2) the degree of correlation between geographical location and innovative output varies with the innovation type, and 3) the correlation between geographical unit and innovation increases when the spatial unit of analysis is narrower. The results suggest that the firms’ choices of geographical location have a long-lasting effect, engendering no equal probabilities of being persistently innovative.
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A newly developed strain rate dependent anisotropic continuum model is proposed for impact and blast applications in masonry. The present model adopted the usual approach of considering different yield criteria in tension and compression. The analysis of unreinforced block work masonry walls subjected to impact is carried out to validate the capability of the model. Comparison of the numerical predictions and test data revealed good agreement. Next, a parametric study is conducted to evaluate the influence of the tensile strengths along the three orthogonal directions and of the wall thickness on the global behavior of masonry walls.
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Dissertação de mestrado em Estatística