5 resultados para Theory of Natural Selection
em Repositório Institucional da Universidade de Aveiro - Portugal
Resumo:
Being of high relevance for many technological applications, the solubility of sour gases in solvents of low volatility is still poorly described and understood. Aiming at purifying natural gas streams, the present work contributes for a more detailed knowledge and better understanding of the solubility of sour gases in these fluids, in particularly on ionic liquids. A new apparatus, developed and validated specially for phase equilibria studies of this type of systems, allowed the study of the solvent basicity, molecular weight and polarity influence on the absorption of carbon dioxide and methane. The non ideality of carbon dioxide solutions in ionic liquids and other low volatile solvents, with which carbon dioxide is known to form electron donor-acceptor complexes, is discussed, allowing the development of a correlation able to describe the carbon dioxide solubility in low volatile solvents. Furthermore, the non ideality of solutions of light compounds, such as SO2, NH3 and H2S, in ionic liquids is also investigated and shown to present negative deviations to the ideality in the liquid phase, that can be predicted by the Flory-Huggins model. For last, the effect of the ionic liquid polarity, described through the Kamlet-Taft parameters, on the CO2/CH4 and H2S/CH4 selectivities is also evaluated and shown to stand as a viable tool for the selection of ionic liquids with enhanced selectivities.
Resumo:
As técnicas estatísticas são fundamentais em ciência e a análise de regressão linear é, quiçá, uma das metodologias mais usadas. É bem conhecido da literatura que, sob determinadas condições, a regressão linear é uma ferramenta estatística poderosíssima. Infelizmente, na prática, algumas dessas condições raramente são satisfeitas e os modelos de regressão tornam-se mal-postos, inviabilizando, assim, a aplicação dos tradicionais métodos de estimação. Este trabalho apresenta algumas contribuições para a teoria de máxima entropia na estimação de modelos mal-postos, em particular na estimação de modelos de regressão linear com pequenas amostras, afetados por colinearidade e outliers. A investigação é desenvolvida em três vertentes, nomeadamente na estimação de eficiência técnica com fronteiras de produção condicionadas a estados contingentes, na estimação do parâmetro ridge em regressão ridge e, por último, em novos desenvolvimentos na estimação com máxima entropia. Na estimação de eficiência técnica com fronteiras de produção condicionadas a estados contingentes, o trabalho desenvolvido evidencia um melhor desempenho dos estimadores de máxima entropia em relação ao estimador de máxima verosimilhança. Este bom desempenho é notório em modelos com poucas observações por estado e em modelos com um grande número de estados, os quais são comummente afetados por colinearidade. Espera-se que a utilização de estimadores de máxima entropia contribua para o tão desejado aumento de trabalho empírico com estas fronteiras de produção. Em regressão ridge o maior desafio é a estimação do parâmetro ridge. Embora existam inúmeros procedimentos disponíveis na literatura, a verdade é que não existe nenhum que supere todos os outros. Neste trabalho é proposto um novo estimador do parâmetro ridge, que combina a análise do traço ridge e a estimação com máxima entropia. Os resultados obtidos nos estudos de simulação sugerem que este novo estimador é um dos melhores procedimentos existentes na literatura para a estimação do parâmetro ridge. O estimador de máxima entropia de Leuven é baseado no método dos mínimos quadrados, na entropia de Shannon e em conceitos da eletrodinâmica quântica. Este estimador suplanta a principal crítica apontada ao estimador de máxima entropia generalizada, uma vez que prescinde dos suportes para os parâmetros e erros do modelo de regressão. Neste trabalho são apresentadas novas contribuições para a teoria de máxima entropia na estimação de modelos mal-postos, tendo por base o estimador de máxima entropia de Leuven, a teoria da informação e a regressão robusta. Os estimadores desenvolvidos revelam um bom desempenho em modelos de regressão linear com pequenas amostras, afetados por colinearidade e outliers. Por último, são apresentados alguns códigos computacionais para estimação com máxima entropia, contribuindo, deste modo, para um aumento dos escassos recursos computacionais atualmente disponíveis.
Resumo:
Doutoramento em Matemática
Resumo:
The introduction of chemicals into the environment by human activities may represent a serious risk to environmental and human health. Environmental risk assessment requires the use of efficient and sensitive tools to determine the impact of contaminants on the ecosystems. The use of zebrafish for the toxicity assessment of pharmaceuticals, drugs, and pollutants, is becoming well accepted due to zebrafish unique advantages for the screening of compounds for hazard identification. The aim of the present work is to apply toxicogenomic approaches to identify novel biomarkers and uncovered potential modes of action of classic and emergent contaminants able to disrupt endocrine systems, such as the Retinoic Acid Receptor, Retinoid X Receptor and the Aryl Hydrocarbon Receptor. This study relies on different nuclear and cytosolic protein receptors and other conditional (ligand- or stress- activated) transcriptional factors that are intimately involved in the regulation of defensome genes and in mechanisms of chemical toxicity. The transcriptomic effects of organic compounds, endogenous compounds, and nanoparticles were analysed during the early stages of zebrafish development. Studying the gene expression profiles of exposed and unexposed organisms to pollutants using microarrays allowed the identification of specific gene markers and to establish a "genetic code" for the tested compounds. Changes in gene expression were observed at toxicant concentrations that did not cause morphological effects. Even at low toxicant concentrations, the observed changes in transcript levels were robust for some target genes. Microarray responses of selected genes were further complemented by the real time quantitative polymerase chain reaction (qRT-PCR) methodology. The combination of bio-informatic, toxicological analyses of differential gene expression profiles, and biochemical and phenotypic responses across the treatments allowed the identification of uncovered potential mechanisms of action. In addition, this work provides an integrated set of tools that can be used to aid management-decision making by improving the predictive capability to measure environmental stress of contaminants in freshwater ecosystems. This study also illustrates the potential of zebrafish embryos for the systematic, large-scale analysis of chemical effects on developing vertebrates.
Resumo:
Environmental contamination and climate changes constitute two of the most serious problems affecting soil ecosystems in agricultural fields. Agriculture is nowadays a highly optimized process that strongly relies on the application of multiple pesticides to reduce losses and increase yield production. Although constituting, per se, a serious problem to soil biota, pesticide mixtures can assume an even higher relevance in a context of unfavourable environmental conditions. Surprisingly, frameworks currently established for environmental risk assessments keep not considering environmental stressors, such as temperature, soil moisture or UV radiation, as factors liable to influence the susceptibility of organisms to pesticides, or pesticide mixtures, which is raising increasing apprehension regarding their adequacy to actually estimate the risks posed by these compounds to the environment. Albeit the higher attention received on the last few years, the influence of environmental stressors on the behaviour and toxicity of chemical mixtures remains still poorly understood. Aiming to contribute for this discussion, the main goal of the present thesis was to evaluate the single and joint effects of natural stressors and pesticides to the terrestrial isopod Porcellionides pruinosus. The first approach consisted on evaluating the effects of several abiotic factors (temperature, soil moisture and UV radiation) on the performance of P. pruinosus using several endpoints: survival, feeding parameters, locomotor activity and avoidance behaviour. Results showed that these stressors might indeed affect P. pruinosus at relevant environmental conditions, thus suggesting the relevance of their consideration in ecotoxicological assays. At next, a multiple biomarker approach was used to have a closer insight into the pathways of damage of UV radiation and a broad spectrum of processes showed to be involved (i.e. oxidative stress, neurotoxicity, energy). Furthermore, UV effects showed to vary with the environment medium and growth-stage. A similar biomarker approach was employed to assess the single and joint effects of the pesticides chlorpyrifos and mancozeb to P. pruinosus. Energy-related biomarkers showed to be the most differentiating parameters since age-classes seemed to respond differently to contamination stress and to have different metabolic costs associated. Finally, the influence of temperature and soil moisture on the toxicity of pesticide mixtures was evaluated using survival and feeding parameters as endpoints. Pesticide-induced mortality was found to be oppositely affected by temperature, either in single or mixture treatments. Whereas chlorpyrifos acute toxicity was raised under higher temperatures the toxicity of mancozeb was more prominent at lower temperatures. By the opposite, soil moisture showed no effects on the pesticide-induced mortality of isopods. Contrary to survival, both temperature and soil moisture showed to interact with pesticides to influence isopods’ feeding parameters. Nonetheless, was however the most common pattern. In brief, findings reported on this thesis demonstrated why the negligence of natural stressors, or multiple stressors in general, is not a good solution for risk assessment frameworks.