The enzymatic method for ethanol measurement can detect very low concentration of ethanol at samples, consequently it can’t be applied for samples with high concentration and implies as very sensitive method at limited range of detection.The alcohol dehydrogenase method is based on oxidation of alcohol in the presence of ADH as enzyme and NAD+ as coenzyme and formation of acetaldehyde and NADH that can be monitored by spectrophotometric measurement at 334,340 or 365 nm wavelengths.Ethanol +NAD+ ADH↔ Acetaldehyde +NADH+H+For optimum conditions of measurements all the parameters that affect the enzymatic reaction including temperature, pH, trapping agent for product and proper mixing need to be optimized.In order to calculate the unknown concentration of ethanol in a sample based on this method,it is crucial to find right mathematical model to calculate the unknown concentrations of ethanol in the sample using a mathematical equation that generalizes relationships among the reactants in the reaction including the reaction products. In most enzymatic reactions many parameters are involved meaning that the reaction seldom follows simple linear relation between concentration and signal. Four-parameter logistic model is well suited for modeling sigmoid relationships frequently found in biology.The aim of this project is determination of ethanol at microdialysis samples and the fundamental reason for developing the present measurement method was to study changes in blood flow in living tissues using wash out of the very dissolvable ethanol as a flow marker using the Microdialysis technique.Result from this measurement technique for microdialysis samples shows that ethanol can be detected at range of 0,5-16mmol/L and whole detected concentration for different samples during one microdialysis test follows the inverse relation of blood flow changes in tissue.Also the reported result from Urea test as general method for studying blood flow changes and ethanol test for microdialysis sample has been compared and leads to this conclusion that ethanol techniques is as reliable tool for studying blood flow changes. / Uppsatsnivå: D

A predição de uma observação futura para modelos mistos é um problema que tem sido extensivamente estudado. Este trabalho trata o problema de atribuir valores para os efeitos aleatórios e/ou variável resposta de novos grupos para o modelo logístico misto, cujo objetivo é predizer respostas futuras com base em parâmetros estimados previamente. Na literatura, existem alguns métodos de predição para este modelo que considera apenas o intercepto aleatório. Para a regressão logística mista com k efeitos aleatórios, atualmente não há métodos propostos para a predição dos efeitos aleatórios de novos grupos. Portanto, foram propostas novas abordagens baseadas no método da média zero, no melhor preditor empírico (MPE), na regressão linear e nos modelos de regressão não-paramétricos. Todos os métodos de predição foram avaliados usando os seguintes métodos de estimação: aproximação de Laplace, quadratura adaptativa de Gauss-Hermite e quase-verossimilhança penalizada. Os métodos de estimação e predição foram analisados por meio de estudos de simulação, com base em sete cenários, com comparações de diferentes valores para: o tamanho de grupo, os desvios-padrão dos efeitos aleatórios, a correlação entre os efeitos aleatórios, e o efeito fixo. Os métodos de predição foram aplicados em dois conjuntos de dados reais. Em ambos os problemas os conjuntos de dados apresentaram estrutura hierárquica, cujo objetivo foi predizer a resposta para novos grupos. Os resultados indicaram que o método MPE apresentou o melhor desempenho em termos de predição, entretanto, apresentou alto custo computacional para grandes bancos de dados. As demais metodologias apresentaram níveis de predição semelhantes ao MPE, e reduziram drasticamente o esforço computacional. / The prediction of a future observation in a mixed regression is a problem that has been extensively studied. This work treat the problem of assigning the random effects and/or the outcome of new groups for the mixed logistic regression, in which the aim is to predict future outcomes based on the parameters previously estimated. In the literature, there are some prediction methods for this model that considers only the random intercept. For the mixed logistic regression with k random effects, there is currently no method for predicting the random effects of new groups. Therefore, we proposed new approaches based on average zero method, empirical best predictor (EBP), linear regression and nonparametric regression models. All prediction methods were evaluated by using the estimation methods: Laplace approximation, adaptive Gauss-Hermite quadrature and penalized quasi-likelihood. The estimation and prediction methods were analyzed by simulation studies, based on seven simulation scenarios, which considered comparisons of different values for: the group size, the standard deviations of the random effects, the correlation between the random effects, and the fixed effect. The prediction methods were applied in two real data sets. In both problems the data set presented hierarchical structure, and the objective was to predict the outcome for new groups. The results indicated that EBP presented the best performance in prediction terms, however it has been presented high computational cost for big data sets. The other methodologies presented similar level of prediction in relation to EBP, and drastically reduced the computational effort.

Esta investigación tiene como propósito identificar cuáles son los factores más determinantes para un posible comprador de un auto híbrido en comparación a un auto convencional en Lima Metropolitana, es por esto que se han utilizado herramientas cualitativas y cuantitativas para obtener un resultado; esto permitirá a las marcas de autos saber que factor es más importante para el consumidor y potenciarlo a través de estrategias de marketing directo e indirecto. En el análisis cualitativo desarrollado a través de un focus group se encontraron diferentes afirmaciones y negaciones que son respaldadas a través del análisis cuantitativo con el modelo estadístico logístico binario; en este caso se demostró que todas las variables son importantes para un posible comprador de un auto híbrido; pero unas tienen mayor importancia que otras y esto determinaría que se deben llevar a cabo estrategias que estén relacionadas al precio y diseño del auto; ya que son las variables que obtuvieron mayor importancia en el análisis. / This investigation has as purpose identify which are the factors more important for a possible buyer of a hybrid car in comparison of a conventional car in Lima Metropolitana, that is why qualitative and quantitative tools have been used to get a result; this will allow car brands to know which factor is more important for the consumer and to empower it through direct and indirect marketing strategies. In the qualitative analysis developed through a focus group, different affirmations and negations were found that are supported through quantitative analysis with the statistical binary logistic model; in this case it was shown that all the variables are important for a possible buyer of a hybrid car; but some are more important than others and this would determine that price and design should be the ones that have to have the focus of the strategies because they are the variables that obtained more importance in the statistical analysis. / Tesis

Timely identification of undesirable pavement crack conditions has been a major task in pavement management. Up to date, myriads of pavement performance models have been developed for forecasting pavement crack condition with the traditional preferred techniques being the use of regression relationships developed from laboratory and/or field statistical data. However, it becomes difficult for regression techniques to predict the crack performance accurately and robustly in the presence of a variety of tributary factors, high nonlinearity, and uncertainty. With the advancement of modeling techniques, two innovative breeds of models, Artificial Neural Networks and Markov Chains, have drawn increasing attention from researchers for modeling complex phenomena like the pavement crack performance. In this study, two distinct models, a recurrent Markov chain, and an Artificial Neural Network (ANN), were developed for modeling the performance of pavement crack condition with time. A logistic model was used to establish a dynamic relationship between transition probabilities associated with the pavement crack condition and the applicable tributary variables. The logistic model was then used conveniently to construct a recurrent Markov chain for use in predicting the crack performance of asphalt pavements in Florida. Florida pavement condition survey database were utilized to perform a case study of the proposed methodologies. For comparison purpose, a currently popular static Markov chain was also developed based on a homogeneous transition probability matrix that was derived from the crack index statistics of Florida pavement survey database. To evaluate the model performance, two comparisons were made; (1) between the recurrent Markov chain and the static Markov chain; and (2) between the recurrent Markov chain and the ANN. It is shown that the recurrent Markov chain outperforms both the static Markov chain and the ANN in terms of one-year forecasting accuracy. Therefore, with high uncertainty typically experienced in the pavement condition deterioration process, the probabilistic dynamic modeling approach as embodied in the recurrent Markov chain provides a more appropriate and applicable methodology for modeling the pavement deterioration process with respect to cracks.

This dissertation is a historically comparative study of adult mortality between Taiwan and the United States throughout the 20th century. The 20th century was characterized by the largest rise in life expectancy at birth and the most rapid decrease in mortality in recorded human history. This dissertation aims not only to examine and compare the trends and levels of life expectancy in Taiwan and the United States over an extended period of time, but also to evaluate the extent to which smoking behavior and obesity play an important role in the recent levels of adult mortality in the United States. I used logistic models of mortality to examine and compare the trends and levels of life expectancy in Taiwan from 1906 to 2008 and in the United States from 1933 to 2007. Second, I re-estimated life expectancy by introducing smoking-attributable mortality to further compare the levels of life expectancy between the two countries. Third, I estimated event history models to investigate whether and how smoking behavior and obesity are related to mortality in the United States in the 1990 to 2006 and the 2000 to 2006 periods. At the end of the 20th century, the level of life expectancy at birth for females in the U.S. was higher than in Taiwan, but they were close. In this century, however, the level of life expectancy at birth in Taiwan has increased to a higher level than in the U.S. The levels of male life expectancy at birth for the two countries are similar in this century, but there were significant differences in the 20th century. The great improvements in juvenile, background and senescent mortality rates in Taiwan may be used to explain this correspondence of life expectancy between the two countries today. Besides, higher smoking-attributed mortality can also serve as another possible reason for the stagnant levels of life expectancy in the U.S. Finally, smoking-related and obesity-related mortality have become progressively more important as predictors of adult mortality in the U.S. in past decades.

国立情報学研究所で電子化したコンテンツを使用している。

Esta tese é composta por três ensaios que versam sobre a complexa relação entre desenvolvimento e meio ambiente. No primeiro ensaio é feita uma revisão das principais abordagens teóricas que tratam do assunto, com destaque para a Curva Ambiental de Kuznets (CAK) e para os conceitos de sustentabilidade fraca e forte. Ambos apontam o crescimento econômico como um importante indutor de impacto ambiental. No entanto, a CAK afirma que a geração de riqueza pode ser aliada na proteção ambiental quando o país alcança um patamar de desenvolvimento suficientemente elevado para que o meio ambiente passe a ser incorporado como um bem superior. Já a conceituação de sustentabilidade não reforça esta conclusão ao passo que sugere que o capital natural precisa ser preservado: seja relativamente (conceito fraco) ou absolutamente (conceito forte). Para estes, a relação entre crescimento e impacto é sempre direta. As abordagens multidimensionais vão além e afirmam que a relação entre o homem e os ecossistemas se dá uma forma impossível de ser mensurada através da simples relação entre crescimento econômico e degradação. Para se aproximar minimamente deste modo de pensar, um conjunto maior de indutores precisa ser considerado. O ensaio 2 desta tese apresenta modelos na literatura que buscam estimar impactos ambientais causados pela atividade humana através de um número maior de indutores (produtivos, populacionais, institucionais, entre outros). Estes modelos (IPAT e STIRPAT) têm como característica a possibilidade de estimar o impacto ambiental esperado através da verificação das variáveis consideradas indutoras. Mas, duas fragilidades são especialmente importantes: i) a variável que mede impacto ambiental é, em geral, reportada com poluição apenas; e, ii) os modelos não fornecem cenários não lineares nos indutores, ou seja, o patamar das variáveis não faz diferença no tamanho do impacto gerado. Então, é proposta a aplicação de um modelo logístico ordenado que seja capaz de estimar as probabilidades de diferentes níveis de impacto ambiental, que é medido através do tamanho da Pegada Ecológica dos países. A metodologia proposta, além de contar com uma medida mais ampla e completa de impacto ambiental, também é capaz de fornecer cenários com maior riqueza informativa, pois levam em consideração os níveis das variáveis indutoras. No trabalho, foram avaliados cenários a partir de um modelo que contou com as seguintes variáveis: percentual de população urbana, percentual de população entre 15-64 anos, densidade demográfica, PIB per capita e percentual de área agrícola. Os sinais e magnitudes das variáveis utilizadas são condizentes com o que a literatura vem apresentando. O diferencial da proposta é, de fato, a possiblidade de análise de cenários através de outra perspectiva. O ensaio 3 da tese aplica este modelo estimado para o globo aos municípios gaúchos. A partir da suposição de que os impactos ambientais são homogêneos ao redor do mundo, foi possível estimar as probabilidades de impacto para cada município. Com estes resultados, foi elaborada uma análise regional dos potenciais impactos ambientais dos municípios a partir dos indutores que apresentavam. Trata-se de um exercício interessante quando se considerada a carência de informações ambientais neste nível de desagregação. / This thesis presents three essays on the complex relationship between development and the environment. On the first essay is performed a survey of the main theoretical approaches on this matter with an emphasis on the Environmental Kuznets Curve (EKC) and the weak and strong sustainability concepts. Both approaches points out the economic growth as an important driver of environmental impact. However, the EKC sustains that the pursuit of economic wealth can be responsible for environmental protection as the country reaches a certain level of income which turns the environment into a superior good. On the other hand, the concepts of sustainability do not enforce this conclusion either in relative terms (weak concept) or absolute terms (strong concept); in this scope, the relationship between growth and environment is constantly direct. The multidimensional approaches propose that the relationship between humankind and the ecosystems are established in a way which is impossible to measure through economic growth and environmental degradation. To become closer to this sort of approach it is necessary to consider a wider set of drivers. The essay 2 of this thesis analyses some statistical models that aim to estimate environmental impacts caused by human activity based on a larger number of drivers (production, population, institutions, etc.). These models (IPAT and STIRPAT) present as a major characteristic the ability to estimate the expected environmental impact grounded on the drivers considered. Nevertheless, two important caveats should be considered: i) the impact variable is most of the time just a pollution measure; and, ii) the models do not offer a nonlinear analysis on the drivers, i.e., the level of the drivers does not make any difference in terms of impact. So, we propose an ordered logistic model that is suitable for estimating the probabilities of different levels of environmental impact which is represented by the size of the Environmental Footprint. The proposed methodology, besides counting on a wider and more complete measure of environmental impact, is capable to offer scenarios with a richer degree of information because the level are effectively taken into consideration. The study has evaluated scenarios base on the following drivers: percentage of population in urban areas, percentage of population between 15-64 years old, demographic density, GDP per capita, and the percentage of agricultural land. The signs and magnitudes of the drivers have proven to be the same as those found in the literature. The main difference of this proposal is, in fact, the possibility of analyzing scenarios through a different (wider) perspective. The essay 3 applies the model, which was prior estimated for the globe, to the municipalities of the state of Rio Grande do Sul, Brazil. Based on the assumption that the environmental impact generated by those drivers is homogeneous around the world, it was possible to estimate the probabilities of environmental impact for each municipality and to draw a regional study of these results. It is an interesting exercise if you take into account that there exists a huge lack of information of environmental conditions for municipalities.

Master of Agribusiness / Department of Agricultural Economics / Christine Wilson / Credit scoring is a tool used to make lending decisions. AgChoice Farm Credit has a dealer financing program called Farm Credit Express that makes lending decisions based on a scoring model. Farm Credit Express is a dealer financing option for farm equipment purchases. AgChoice has generated significant loan volume with this program but has also experienced challenges with loan delinquencies as field staff must service loans that they did not originate. This thesis evaluates loan delinquencies within AgChoice Farm Credit’s Farm Credit Express (“FCE”) program. The thesis develops a regression model that includes delinquencies as the dependent variable and Total AgChoice Borrowing, Original Loan Amount, Farming Segment, CBI Score, AgScore, and FCE Only as the independent variables. The model provides an examination of AgChoice’s Farm Credit Express delinquencies and evaluates the variables mentioned above and their ability to predict delinquencies. The results showed that Total AgChoice Borrowing, Original Loan Amount, CBI Score and FCE only were statistically significant independent variables. Based on results of the model, recommendations were made to potentially reduce future delinquencies in the Farm Credit Express loan portfolio.

Capturing mortality became a crucial modelling problem throughout the years due to the raising demand of life insurances and annuities. Fitting three models, namely, logistic, Heligman– Pollard HP4 and power–exponential model, to real life data shows that latter two models represent the actual data quite well. Pricing a term life insurance and a whole life annuity, implemented using the MATLAB software, based on these models ends in the result that the Heligmann–Pollard HP4 model is the less preferable model, in perspective of an insured, than the logistic or power–exponential ones.

Esta tese é composta por três ensaios que versam sobre a complexa relação entre desenvolvimento e meio ambiente. No primeiro ensaio é feita uma revisão das principais abordagens teóricas que tratam do assunto, com destaque para a Curva Ambiental de Kuznets (CAK) e para os conceitos de sustentabilidade fraca e forte. Ambos apontam o crescimento econômico como um importante indutor de impacto ambiental. No entanto, a CAK afirma que a geração de riqueza pode ser aliada na proteção ambiental quando o país alcança um patamar de desenvolvimento suficientemente elevado para que o meio ambiente passe a ser incorporado como um bem superior. Já a conceituação de sustentabilidade não reforça esta conclusão ao passo que sugere que o capital natural precisa ser preservado: seja relativamente (conceito fraco) ou absolutamente (conceito forte). Para estes, a relação entre crescimento e impacto é sempre direta. As abordagens multidimensionais vão além e afirmam que a relação entre o homem e os ecossistemas se dá uma forma impossível de ser mensurada através da simples relação entre crescimento econômico e degradação. Para se aproximar minimamente deste modo de pensar, um conjunto maior de indutores precisa ser considerado. O ensaio 2 desta tese apresenta modelos na literatura que buscam estimar impactos ambientais causados pela atividade humana através de um número maior de indutores (produtivos, populacionais, institucionais, entre outros). Estes modelos (IPAT e STIRPAT) têm como característica a possibilidade de estimar o impacto ambiental esperado através da verificação das variáveis consideradas indutoras. Mas, duas fragilidades são especialmente importantes: i) a variável que mede impacto ambiental é, em geral, reportada com poluição apenas; e, ii) os modelos não fornecem cenários não lineares nos indutores, ou seja, o patamar das variáveis não faz diferença no tamanho do impacto gerado. Então, é proposta a aplicação de um modelo logístico ordenado que seja capaz de estimar as probabilidades de diferentes níveis de impacto ambiental, que é medido através do tamanho da Pegada Ecológica dos países. A metodologia proposta, além de contar com uma medida mais ampla e completa de impacto ambiental, também é capaz de fornecer cenários com maior riqueza informativa, pois levam em consideração os níveis das variáveis indutoras. No trabalho, foram avaliados cenários a partir de um modelo que contou com as seguintes variáveis: percentual de população urbana, percentual de população entre 15-64 anos, densidade demográfica, PIB per capita e percentual de área agrícola. Os sinais e magnitudes das variáveis utilizadas são condizentes com o que a literatura vem apresentando. O diferencial da proposta é, de fato, a possiblidade de análise de cenários através de outra perspectiva. O ensaio 3 da tese aplica este modelo estimado para o globo aos municípios gaúchos. A partir da suposição de que os impactos ambientais são homogêneos ao redor do mundo, foi possível estimar as probabilidades de impacto para cada município. Com estes resultados, foi elaborada uma análise regional dos potenciais impactos ambientais dos municípios a partir dos indutores que apresentavam. Trata-se de um exercício interessante quando se considerada a carência de informações ambientais neste nível de desagregação. / This thesis presents three essays on the complex relationship between development and the environment. On the first essay is performed a survey of the main theoretical approaches on this matter with an emphasis on the Environmental Kuznets Curve (EKC) and the weak and strong sustainability concepts. Both approaches points out the economic growth as an important driver of environmental impact. However, the EKC sustains that the pursuit of economic wealth can be responsible for environmental protection as the country reaches a certain level of income which turns the environment into a superior good. On the other hand, the concepts of sustainability do not enforce this conclusion either in relative terms (weak concept) or absolute terms (strong concept); in this scope, the relationship between growth and environment is constantly direct. The multidimensional approaches propose that the relationship between humankind and the ecosystems are established in a way which is impossible to measure through economic growth and environmental degradation. To become closer to this sort of approach it is necessary to consider a wider set of drivers. The essay 2 of this thesis analyses some statistical models that aim to estimate environmental impacts caused by human activity based on a larger number of drivers (production, population, institutions, etc.). These models (IPAT and STIRPAT) present as a major characteristic the ability to estimate the expected environmental impact grounded on the drivers considered. Nevertheless, two important caveats should be considered: i) the impact variable is most of the time just a pollution measure; and, ii) the models do not offer a nonlinear analysis on the drivers, i.e., the level of the drivers does not make any difference in terms of impact. So, we propose an ordered logistic model that is suitable for estimating the probabilities of different levels of environmental impact which is represented by the size of the Environmental Footprint. The proposed methodology, besides counting on a wider and more complete measure of environmental impact, is capable to offer scenarios with a richer degree of information because the level are effectively taken into consideration. The study has evaluated scenarios base on the following drivers: percentage of population in urban areas, percentage of population between 15-64 years old, demographic density, GDP per capita, and the percentage of agricultural land. The signs and magnitudes of the drivers have proven to be the same as those found in the literature. The main difference of this proposal is, in fact, the possibility of analyzing scenarios through a different (wider) perspective. The essay 3 applies the model, which was prior estimated for the globe, to the municipalities of the state of Rio Grande do Sul, Brazil. Based on the assumption that the environmental impact generated by those drivers is homogeneous around the world, it was possible to estimate the probabilities of environmental impact for each municipality and to draw a regional study of these results. It is an interesting exercise if you take into account that there exists a huge lack of information of environmental conditions for municipalities.