939 resultados para Systems analysis.


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

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

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Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering

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

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Dissertation presented to obtain the Ph.D degree in Biochemistry, Structural Biochemistry

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Chagas disease was an important medical and social problem in almost all of Latin America throughout the twentieth century. It has been combated over a broad swath of this continent over recent decades, with very satisfactory results in terms of vector and transfusional transmission. Today, a surveillance stage still remains to be consolidated, in parallel with appropriate care required for some millions of infected individuals who are today living in endemic and non-endemic areas. Contradictorily, the good results attained have generated excessive optimism and even disregard among health authorities, in relation to this disease and its control. The loss of visibility and priority may be a logical consequence, particularly in Latin American healthcare systems that are still disorganized and overburdened due to insufficiencies of financial and human resources. Consolidation of the victories against Chagas disease is attainable but depends on political will and continual attention from the most consequential protagonists in this struggle, especially the Latin American scientific community.

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Complex systems, i.e. systems composed of a large set of elements interacting in a non-linear way, are constantly found all around us. In the last decades, different approaches have been proposed toward their understanding, one of the most interesting being the Complex Network perspective. This legacy of the 18th century mathematical concepts proposed by Leonhard Euler is still current, and more and more relevant in real-world problems. In recent years, it has been demonstrated that network-based representations can yield relevant knowledge about complex systems. In spite of that, several problems have been detected, mainly related to the degree of subjectivity involved in the creation and evaluation of such network structures. In this Thesis, we propose addressing these problems by means of different data mining techniques, thus obtaining a novel hybrid approximation intermingling complex networks and data mining. Results indicate that such techniques can be effectively used to i) enable the creation of novel network representations, ii) reduce the dimensionality of analyzed systems by pre-selecting the most important elements, iii) describe complex networks, and iv) assist in the analysis of different network topologies. The soundness of such approach is validated through different validation cases drawn from actual biomedical problems, e.g. the diagnosis of cancer from tissue analysis, or the study of the dynamics of the brain under different neurological disorders.

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In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

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The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

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Retail services are a main contributor to municipal budget and are an activity that affects perceived quality-of-life, especially for those with mobility difficulties (e.g. the elderly, low income citizens). However, there is evidence of a decline in some of the services market towns provide to their citizens. In market towns, this decline has been reported all over the western world, from North America to Australia. The aim of this research was to understand retail decline and enlighten on some ways of addressing this decline, using a case study, Thornbury, a small town in the Southwest of England. Data collected came from two participatory approaches: photo-surveys and multicriteria mapping. The interpretation of data came from using participants as analysts, but also, using systems thinking (systems diagramming and social trap theory) for theory building. This research moves away from mainstream economic and town planning perspectives by making use of different methods and concepts used in anthropology and visual sociology (photo-surveys), decision-making and ecological economics (multicriteria mapping and social trap theory). In sum, this research has experimented with different methods, out of their context, to analyse retail decline in a small town. This research developed a conceptual model for retail decline and identified the existence of conflicting goals and interests and their implications for retail decline, as well as causes for these. Most of the potential causes have had little attention in the literature. This research also identified that some of the measures commonly used for dealing with retail decline may be contributing to the causes of retail decline itself. Additionally, this research reviewed some of the measures that can be used to deal with retail decline, implications for policy-making and reflected on the use of the data collection and analysis methods in the context of small to medium towns.

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This thesis aims explore the sociocultural as well as economic significance of the modern-day flea market, as a form of alternative marketplace system. More specifically, the main goal of the research is to determine the motivation for participation in flea markets of different participants, from vendors to consumers, using an interactionist perspective. By studying these groups in details, I seek to explore the embeddedness of social aspects in economic activity and vice versa. The basic assumption is to put aside the previous notions of the flea market as a second-order system with implied inferiority, and to explore the potential of the flea market to both challenge and complement more formal marketplace systems, by comparing and contrasting the flea market with market venues that belong to the formal sector. Feira da Ladra in Lisbon, Portugal, the oldest a hugely successful flea market in Europe, was chosen to be the research site, where its economic participants were studied in details in various exchanges, using naturalistic observations, semi-structured interviews and a sociocultural perspective.

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This work evaluates the efficiency position of the health system of each OECD country. It identifies whether, or not, health systems changed in terms of quality and performance after the financial crisis. The health systems performance was calculated by fixed-effects estimator and by stochastic frontier analysis. The results suggest that many of those countries that the crisis affected the most are more efficient than the OECD average. In addition, some of those countries even managed to reach the top decile in the efficiency ranking. Finally, we analyze the stochastic frontier efficiency scores together with other health indicators to evaluate the health systems’ overall adjustments derived from the crisis.

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This article argues that the study of literary representations of landscapes can be aided and enriched by the application of digital geographic technologies. As an example, the article focuses on the methods and preliminary findings of LITESCAPE.PT—Atlas of Literary Landscapes of Mainland Portugal, an on-going project that aims to study literary representations of mainland Portugal and to explore their connections with social and environmental realities both in the past and in the present. LITESCAPE.PT integrates traditional reading practices and ‘distant reading’ approaches, along with collaborative work, relational databases, and geographic information systems (GIS) in order to classify and analyse excerpts from 350 works of Portuguese literature according to a set of ecological, socioeconomic, temporal and cultural themes. As we argue herein this combination of qualitative and quantitative methods—itself a response to the difficulty of obtaining external funding—can lead to (a) increased productivity, (b) the pursuit of new research goals, and (c) the creation of new knowledge about natural and cultural history. As proof of concept, the article presents two initial outcomes of the LITESCAPE.PT project: a case study documenting the evolving literary geography of Lisbon and a case study exploring the representation of wolves in Portuguese literature.

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Exosomes are small membrane vesicles secreted by most cell types, either normal or malignant and are found in most body fluids such as saliva, plasma and breast milk. In the past decade, the interest in these vesicles has been growing more and more since it was found that besides their beneficial functions such as the removal of cellular debris and unnecessary proteins during cell maturation process, they can also interact with other cells and transfer information between them, thus helping diseases like cancer to progress. The present work intended to use gold nanoparticles as vehicles for gene silencing in an attempt to reduce the tumor-derived exosome secretion, regulated by Rab27a protein, and also aimed to compare the exosome secretion between two breast cell lines, MCF7 and MDA. Changes in RAB27A gene expression were measured by Real-time Quantitative PCR and it was revealed a decreased in RAB27A gene expression, as expected. Exosomes were isolated and purified by two different methods, ultracentrifugation and the commercial kit ExoQuick™ Solution, and further characterized using Western Blot analysis. ExoQuick™ Solution was proven to be the most efficient method for exosome isolation and it was revealed that MDA cells secrete more exosomes. Furthermore, the isolated MCF7-derived exosomes were placed together with a normal bronchial/tracheal epithelial cell line (BTEC) for an additional assay, which aimed to observe the uptake of exosomes by other cells and the exosomes’ capability of promoting cell-cell communication. This observation was made based on alterations in the expression levels of c-Myc and miR-21 genes and the fact that they both have an increased expression in BTEC cells incubated with tumor-derived exosomes when compared to control cells (without incubation with the exosomes) lead us to the conclusion that the exosome uptake and exchange of information between the exosomes and the normal cells did occurred.