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.

The development of flexible and interpretable statistical methods is necessary in order to provide appropriate risk assessment measures for extreme events and natural disasters. In this thesis, we address this challenge by contributing to the developing research field of Extreme-Value Theory. We initially study the performance of existing parametric and non-parametric estimators of extremal dependence for multivariate maxima. As the dimensionality increases, non-parametric estimators are more flexible than parametric methods but present some loss in efficiency that we quantify under various scenarios. We introduce a statistical tool which imposes the required shape constraints on non-parametric estimators in high dimensions, significantly improving their performance. Furthermore, by embedding the tree-based max-stable nested logistic distribution in the Bayesian framework, we develop a statistical algorithm that identifies the most likely tree structures representing the data's extremal dependence using the reversible jump Monte Carlo Markov Chain method. A mixture of these trees is then used for uncertainty assessment in prediction through Bayesian model averaging. The computational complexity of full likelihood inference is significantly decreased by deriving a recursive formula for the nested logistic model likelihood. The algorithm performance is verified through simulation experiments which also compare different likelihood procedures. Finally, we extend the nested logistic representation to the spatial framework in order to jointly model multivariate variables collected across a spatial region. This situation emerges often in environmental applications but is not often considered in the current literature. Simulation experiments show that the new class of multivariate max-stable processes is able to detect both the cross and inner spatial dependence of a number of extreme variables at a relatively low computational cost, thanks to its Bayesian hierarchical representation. These innovative methods and models are implemented to study the concentration maxima of various air pollutants and how these are related to extreme weather conditions for a number of sites in California, one of the most populated and polluted states of the US. As a result, we provide comprehensive measures of air quality that can be used by communities and policymakers worldwide to better assess and manage the health, environmental and financial impacts of air pollution extremes.

Traditional clinical trials have been inefficient in their methods of dose finding and dose allocation. In this paper a four-parameter logistic equation is used to model the outcome of Bernoulli-response clinical trials. A Bayesian adaptive design is used to fit the logistic equation to the dose-response curve of Phase II and Phase III clinical trials. Because of inherent restrictions in the logistic model, symmetric candidate densities cannot be used, thereby creating asymmetric jumping rules inside the Markov chain Monte Carlo algorithm. An order restricted Metropolis-Hastings algorithm is implemented to account for these limitations. Modeling clinical trials in a Bayesian framework allows the experiment to be adaptive. In this adaptive design batches of subjects are assigned to doses based on the posterior probability of success for each dose, thereby increasing the probability of receiving advantageous doses. Good posterior fitting is demonstrated for typical dose-response curves and the Bayesian design is shown to properly stop drug trials for clinical futility or clinical success. In this paper we demonstrate that an adaptive Bayesian approach to dose-response studies increases both the statistical and medicinal effectiveness of clinical research.

No description available.

Sigmoid curves have found broad applicability in biological sciences and biopharmaceutical research during the last decades. A well planned experiment design is essential to accurately estimate the parameters of the model. In contrast to a large literature and extensive results on optimal designs for linear models, research on the design for nonlinear, including sigmoid curve, models has not kept pace. Furthermore, most of the work in the optimal design literature for nonlinear models concerns the characterization of minimally supported designs. These minimal, optimal designs are frequently criticized for their inability to check goodness of fit, as there are no additional degrees of freedom for the testing. This design issue can be a serious problem, since checking the model adequacy is of particular importance when the model is selected without complete certainty. To assess for lack of fit, we must add at least one extra distinct design point to the experiment. The goal of this dissertation is to identify optimal or highly efficient designs capable of checking the fit for sigmoid curve models. In this dissertation, we consider some commonly used sigmoid curves, including logistic, probit and Gompertz models with two, three, or four parameters. We use D-optimality as our design criterion. We first consider adding one extra point to the design, and consider five alternative designs and discuss their suitability to test for lack of fit. Then we extend the results to include one more additional point to better understand the compromise among the need of detecting lack of fit, maintaining high efficiency and the practical convenience for the practitioners. We then focus on the two-parameter Gompertz model, which is widely used in fitting growth curves yet less studied in literature, and explore three-point designs for testing lack of fit under various error variance structures. One reason that nonlinear design problems are so challenging is that, with nonlinear models, information matrices and optimal designs depend on the unknown model parameters. We propose a strategy to bypass the obstacle of parameter dependence for the theoretical derivation. This dissertation also successfully characterizes many commonly studied sigmoid curves in a generalized way by imposing unified parameterization conditions, which can be generalized and applied in the studies of other sigmoid curves. We also discuss Gompertz model with different error structures in finding an extra point for testing lack of fit. / Statistics

Este trabalho tem por objetivo apresentar a Teoria da Resposta ao Item (TRI), por meio de uma abordagem pedagógica, aos professores da educação básica, que mencionaram esta necessidade por meio de pesquisa realizada pelo autor. Levar parte do conhecimento teórico que embasa esta teoria ao conhecimento do docente, principalmente a construção da curva de probabilidade de acerto do item, favorecerá a compreensão, a análise e o monitoramento do processo avaliativo educacional. Este material apresenta as principais definições e conceitos da avaliação externa em larga escala, além de fornecer insumos para a compreensão das suposições realizadas para aplicação da metodologia. Neste sentido, o texto foi estruturado de forma a apresentar didaticamente as etapas do processo de implementação de uma avaliação, desde a construção do item até a apuração e divulgação dos resultados. Todo enfoque será dado à construção do modelo da TRI com um parâmetro (dificuldade do item), também conhecido como modelo de Rasch, o que simplifica e facilita a compreensão da metodologia. O modelo utilizado nas avaliações externas em larga escala (modelo com três parâmetros) será introduzido a partir das considerações realizadas na abordagem que explicita o pensamento da construção do modelo de um parâmetro. Acredita-se que esta compreensão possa colaborar com o professor na exploração das habilidades/competências dos alunos durante os anos escolares. / This study aims to present the Item Response Theory (IRT), through a pedagogical approach, to teachers of basic education, which mentioned this necessity through research conducted by the author. To take part of the theoretical knowledge that supports this theory to the teacher\'s knowledge, especially the construction of probability curve of item correct response, it will favor for understanding, analysis and monitoring the evaluation educational process. This material presents the main definitions and concepts of the external evaluation in large scale, besides providing inputs for understanding the assumptions made to apply the methodology. In this sense, the text was structured in order to present the implementation process stages of a large scale assessment, from the item construction to the results calculation and dissemination. The focus will be given to the IRT model construction of one-parameter (difficulty of the item), also known as Rasch model, since it simplifies and facilitates the understanding of methodology. The model used in the external assessment on a large scale (three-parameter model) will be introduced from the considerations made in the approach that explicit the thought of one-parameter model construction. It is believed that understanding can collaborate with teacher in exploration of the students\' skills/competences during the school year.

Este trabalho tem por objetivo apresentar a Teoria da Resposta ao Item (TRI), por meio de uma abordagem pedagógica, aos professores da educação básica, que mencionaram esta necessidade por meio de pesquisa realizada pelo autor. Levar parte do conhecimento teórico que embasa esta teoria ao conhecimento do docente, principalmente a construção da curva de probabilidade de acerto do item, favorecerá a compreensão, a análise e o monitoramento do processo avaliativo educacional. Este material apresenta as principais definições e conceitos da avaliação externa em larga escala, além de fornecer insumos para a compreensão das suposições realizadas para aplicação da metodologia. Neste sentido, o texto foi estruturado de forma a apresentar didaticamente as etapas do processo de implementação de uma avaliação, desde a construção do item até a apuração e divulgação dos resultados. Todo enfoque será dado à construção do modelo da TRI com um parâmetro (dificuldade do item), também conhecido como modelo de Rasch, o que simplifica e facilita a compreensão da metodologia. O modelo utilizado nas avaliações externas em larga escala (modelo com três parâmetros) será introduzido a partir das considerações realizadas na abordagem que explicita o pensamento da construção do modelo de um parâmetro. Acredita-se que esta compreensão possa colaborar com o professor na exploração das habilidades/competências dos alunos durante os anos escolares. / This study aims to present the Item Response Theory (IRT), through a pedagogical approach, to teachers of basic education, which mentioned this necessity through research conducted by the author. To take part of the theoretical knowledge that supports this theory to the teacher\'s knowledge, especially the construction of probability curve of item correct response, it will favor for understanding, analysis and monitoring the evaluation educational process. This material presents the main definitions and concepts of the external evaluation in large scale, besides providing inputs for understanding the assumptions made to apply the methodology. In this sense, the text was structured in order to present the implementation process stages of a large scale assessment, from the item construction to the results calculation and dissemination. The focus will be given to the IRT model construction of one-parameter (difficulty of the item), also known as Rasch model, since it simplifies and facilitates the understanding of methodology. The model used in the external assessment on a large scale (three-parameter model) will be introduced from the considerations made in the approach that explicit the thought of one-parameter model construction. It is believed that understanding can collaborate with teacher in exploration of the students\' skills/competences during the school year.

Submitted by Mario BC (mario@bc.ufrpe.br) on 2017-02-09T14:36:25Z No. of bitstreams: 1 Carlos Felipe da Silva Sarmento.pdf: 2697442 bytes, checksum: eaba39bb12e4c36c857959967e4b6702 (MD5) / Made available in DSpace on 2017-02-09T14:36:25Z (GMT). No. of bitstreams: 1 Carlos Felipe da Silva Sarmento.pdf: 2697442 bytes, checksum: eaba39bb12e4c36c857959967e4b6702 (MD5) Previous issue date: 2015-08-27 / This research aim to design a teaching sequence to relate the study of discrete dynamical systems and the composition functions from the logistic analysis model of Verhulst, considering a population with a constant birth rate and a mortality rate directly proportional to that population. Preliminary concepts of discrete dynamical study are presented, such as the concepts of iterate and equilibrium points, repelling, attracting, periodic, among others, followed by the classical results. Some motivator problems that can help understanding the importance of discrete dynamical study are shown. It appears the dynamic in a de ned interval and the graphic behavior of the quadratic family, culminating in the implementation of previous results in the logistic model evolution. Finally, we present a proposed teaching sequence, whose aims is to verify, from a given situation-problem with de ned values named initial conditions, the nal evolution, where possible, of a population P known the initial population Po. / Este trabalho tem por finalidade elaborar uma proposta de sequência didática relacionando o estudo dos sistemas dinâmicos discretos e a composição de funções a partir da análise do modelo logístico de Vershult, considerando uma população com uma taxa de natalidade constante e uma taxa de mortalidade diretamente proporcional à população. Os conceitos preliminares do estudo da dinâmica discreta, tais como os conceitos de interação e pontos fixos, repulsores, atratores, periódicos, dentre outros, são apresentados seguidos dos resultados clássicos. Alguns problemas motivadores que auxiliam na compreensão da importância do estudo dos sistemas dinâmicos discretos são exibidos. Mostram-se também a dinâmica em em intervalos definidos e o comportamento gráfico da família quadrática, culminando com a aplicação dos resultados anteriores à evolução do modelo logístico. Por fim, apresentamos uma proposta de sequencia didática, cujo objetivo é, a partir de uma situação-problema dada usando valores definidos que são as condições iniciais, verificar o comportamento final, quando possível, de uma população P conhecida a população inicial Po.

Submitted by Jorge Silva (jorgelmsilva@ufrrj.br) on 2017-09-28T17:53:37Z No. of bitstreams: 1 2017 - Walciney Jos? das Chagas de Oliveira.pdf: 2552173 bytes, checksum: b5ff12c05946a53ec0cc884a550f3d22 (MD5) / Made available in DSpace on 2017-09-28T17:53:37Z (GMT). No. of bitstreams: 1 2017 - Walciney Jos? das Chagas de Oliveira.pdf: 2552173 bytes, checksum: b5ff12c05946a53ec0cc884a550f3d22 (MD5) Previous issue date: 2017-02-23 / AusAID (Australian Agency for International Development, Austr?lia) / Whey produced by small to medium cheese makers in the state of Minas Gerais is currently being underutilised and carries an economic burden due to losses to the environment. The current study provides a diagnostic of whey utilisation in a selected cluster of 76 dairy companies located in Zona da Mata and Campo das Vertentes and economically assesses potential value addition scenarios for regional development by considering the potential whey uptake by two established drying plants with spare capacity. The decision making model indicated that the most economical scenario includes the installation of whey collection centers. With a minimum regional development investment of R$55,000,000.00, the model selects the Ponte Nova plant as the recipient of the cluster?s whey (mostly in pre-concentrated form) to produce partially demineralised whey powder 40%, with a return of investment of 2.9 years. Changes in transportation costs did not impact on the model output recommendations. This study demonstrated the economic viability for whey recovery into whey powder following the formation of a cluster of associated small to medium cheesemakers. / O soro de leite produzido por pequenas e m?dias queijarias em Minas Gerais est? sendo subutilizado e carrega um fardo econ?mico devido a perdas para o meio ambiente. O presente estudo fornece um diagn?stico da utiliza??o de soro de leite em um cluster selecionado de 76 latic?nios localizados na Zona da Mata e Campo das Vertentes, e economicamente avalia poss?veis cen?rios de agrega??o de valor para o desenvolvimento Regional, considerando a absor??o de soro de leite potencial por duas plantas de secagens estabelecidas com capacidades ociosas. O modelo de tomada de decis?o indicou que o cen?rio mais econ?mico inclui a instala??o de centro de coletas de soro de leite. Com um investimento de desenvolvimento Regional m?nimo de R$ 55.000.000,00, o modelo seleciona a planta de Ponte Nova como o destinat?rio do soro do cluster (principalmente na forma de pr?-concentrado) para produzir o soro de leite parcialmente desmineralizado em p? 40%, com um retorno do investimento de 2,9 anos. Mudan?as nos custos de transporte n?o impactaram as recomenda??es de sa?da do modelo. Este estudo demonstrou a viabilidade econ?mica para a recupera??o do soro de leite em soro em p? ap?s a forma??o de um cluster de pequenos e m?dios associados queijeiros.

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.