953 resultados para Complex combinatorial problem


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Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Pollution in coastal ecosystems is a serious threat to the biota and human populations there residing. Anthropogenic activities in these ecosystems are the main cause of contamination by endocrine disruption compounds (EDCs), which can interfere with hormonal regulation and cause adverse effects to growth, stress response and reproduction. Although the chemical nature of many EDCs is unknown, it is believed that most are organic contaminants. Under an environmental risk assessment for a contaminated estuary (the Sado, SW Portugal), the present work intended to detect endocrine disruption in a flatsfish, Solea senegalensis Kaup, 1858, and its potential relationship to organic toxicants. Animals were collected from two areas in the estuary with distinct influences (industrial and rural) and from an external reference area. To evaluate endocrine disruption, hepatic vitellogenin (VTG) concentrations in males and gonad histology were analysed. As biomarkers of exposure to organic contaminants, cytochrome P450 (CYP1A) induction and the ethoxyresorufin-O-deethylase (EROD) activity were determined. The results were contrasted to sediment contamination levels, which are overall considered low, although the area presents a complex mixture of toxicants. Either males or females were found sexually immature and showed no significant evidence of degenerative pathologies. However, hepatic VTG concentrations in males from the industrial area in estuary were superior than those from the Reference, even reaching levels comparable to those in females, which may indicate an oestrogenic effect resulting from the complex contaminant mixture. These individuals also presented higher levels of CYP1A induction and EROD activity, which is consistent with contamination by organic substances. The combination of the results suggest that the exposure of flatfish to an environment contaminated by mixed toxicants, even at low levels, may cause endocrine disruption, therefore affecting populations, which implies the need for further research in identification of potential EDCs, their sources and risks at ecosystem scale.

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Dissertation to obtain a Master Degree in Molecular Genetics and Biomedicine at Faculty of Sciences and Technology,Universidade Nova de Lisboa

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Dissertation for the Degree of Master in Biotechnology

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Dissertação para obtenção do Grau de Mestre em Biotecnologia

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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 PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

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Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Complex problems of globalized society challenge its adaptive capacity. However, it is precisely the nature of these human induced problems that provide enough evidence to show that adaptability may not be on a resilient path. This thesis explores the ambiguity of the idea of adaptation (and its practice) and illustrates the ways in which adaptability contributes to resilience of social ecological systems. The thesis combines a case study and grounded theory approach and develops an analytical framework to study adaptability in resource users’ organizations: from what it depends on and what the key challenges are for resource management and system resilience. It does so for the specific case of fish producers’ organizations (POs) in Portugal. The findings suggest that while ecological and market context, including the type of crisis, may influence the character of fishers’ adaptation within POs (i.e. anticipatory, maladaptive and reactively adaptive), it does not determine it. Instead, it makes agency even more crucial (i.e. leadership, trust and agent’s perceptions in terms of their impact on fishers’ motivation to learn from each other). In sum, it was found that internal adaptation can improve POs’ contribution to fishery management and resilience, but it is not a panacea and may, in some cases, increase system vulnerability to change. Continuous maladaptation of some Portuguese POs points at a basic institutional problem (fish market regime), which clearly reduces fisheries resilience as it promotes overfishing. However, structural change may not be sufficient to address other barriers to Portuguese fishers’ (PO members) adaptability, such as history (collective memory) and associated problematic self-perceptions. The agency (people involved in structures and practices) also needs to change. What and how institutional change and agency change build on one another (e.g. comparison of fisheries governance in Portugal and other EU countries) is a topic to be explored in further research.

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Total antigen from Leishmania (Leishmania) amazonensis and isolates from the Leishmania braziliensis complex, along with their respective antigenic fractions obtained by affinity chromatography on concanavalin-A-Sepharose and jacalin-agarose columns evaluated using immunoenzymatic ELISA assay. For this, serum samples from 229 patients were used, grouped as American tegmental leishmaniasis (nº=58), visceral leishmaniasis (nº=28), Chagas disease (nº=49), malaria (nº=32), tuberculosis (nº=13) and healthy volunteers (nº=49). Samples from American tegmentary leishmaniasis showed higher reactivity with antigens isolated from the Leishmania braziliensis complex than with antigens from Leishmania amazonensis (p<0.001). ELISA assays showed a sensitivity range from 60% to 95% with antigens isolated from the Leishmania braziliensis complex. There was marked nonspecific reactivity among serum samples with the use of antigenic fractions binding with concanavalin-A and jacalin from both Leishmania complexes, in comparison with other antigens (p<0.001). The results presented in this study suggest that the use of homologous antigens increases the efficiency of anti-Leishmania immunoglobulin detection, which may be very valuable for diagnostic purposes.

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Benefits of long-term monitoring have drawn considerable attention in healthcare. Since the acquired data provides an important source of information to clinicians and researchers, the choice for long-term monitoring studies has become frequent. However, long-term monitoring can result in massive datasets, which makes the analysis of the acquired biosignals a challenge. In this case, visualization, which is a key point in signal analysis, presents several limitations and the annotations handling in which some machine learning algorithms depend on, turn out to be a complex task. In order to overcome these problems a novel web-based application for biosignals visualization and annotation in a fast and user friendly way was developed. This was possible through the study and implementation of a visualization model. The main process of this model, the visualization process, comprised the constitution of the domain problem, the abstraction design, the development of a multilevel visualization and the study and choice of the visualization techniques that better communicate the information carried by the data. In a second process, the visual encoding variables were the study target. Finally, the improved interaction exploration techniques were implemented where the annotation handling stands out. Three case studies are presented and discussed and a usability study supports the reliability of the implemented work.

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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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Saccharomyces cerevisiae as well as other microorganisms are frequently used in industry with the purpose of obtain different kind of products that can be applied in several areas (research investigation, pharmaceutical compounds, etc.). In order to obtain high yields for the desired product, it is necessary to make an adequate medium supplementation during the growth of the microorganisms. The higher yields are typically reached by using complex media, however the exact formulation of these media is not known. Moreover, it is difficult to control the exact composition of complex media, leading to batch-to-batch variations. So, to overcome this problem, some industries choose to use defined media, with a defined and known chemical composition. However these kind of media, many times, do not reach the same high yields that are obtained by using complex media. In order to obtain similar yield with defined media the addition of many different compounds has to be tested experimentally. Therefore, the industries use a set of empirical methods with which it is tried to formulate defined media that can reach the same high yields as complex media. In this thesis, a defined medium for Saccharomyces cerevisiae was developed using a rational design approach. In this approach a given metabolic network of Saccharomyces cerevisiae is divided into a several unique and not further decomposable sub networks of metabolic reactions that work coherently in steady state, so called elementary flux modes. The EFMtool algorithm was used in order to calculate the EFM’s for two Saccharomyces cerevisiae metabolic networks (amino acids supplemented metabolic network; amino acids non-supplemented metabolic network). For the supplemented metabolic network 1352172 EFM’s were calculated and then divided into: 1306854 EFM’s producing biomass, and 18582 EFM’s exclusively producing CO2 (cellular respiration). For the non-supplemented network 635 EFM’s were calculated and then divided into: 215 EFM’s producing biomass; 420 EFM’s producing exclusively CO2. The EFM’s of each group were normalized by the respective glucose consumption value. After that, the EFMs’ of the supplemented network were grouped again into: 30 clusters for the 1306854 EFMs producing biomass and, 20 clusters for the 18582 EFM’s producing CO2. For the non-supplemented metabolic network the respective EFM’s of each metabolic function were grouped into 10 clusters. After the clustering step, the concentrations of the other medium compounds were calculated by considering a reasonable glucose amount and by accounting for the proportionality between the compounds concentrations and the glucose ratios. The approach adopted/developed in this thesis may allow a faster and more economical way for media development.