My research is centered around the questions: How can such a modernized country, considered by many to be the cleanest, friendliest, most welcoming place to visit (certainly surpassing the United States on such standards), not be more welcoming of women in employment? Further, what are the main problems hindering women in employment today, and from where do these problems originate? That is, how did the present situation for women’s employment in Japan come to light? I endeavor to answer these questions, beginning by uncovering the major issues in women’s employment and then tracing their origins back in history to discover when and why they developed into what they are today.

Mechanistic studies of electrochemical proton coupled electron transfer (PCET) have attracted attention for many decades due to their importance in many fields ranging from electrocatalysis to biology. However, mechanistic research is confined to only a few groups, and challenges in this field can be found in both theory and experiment. The contributions to mechanistic studies of electrochemical PCET reaction in this thesis can be categorized under the following two headings: 1) mechanistic studies of an aminobenzoquinone modified monolayer system with multiple electron/proton transfer reaction; 2) studies that attempt to develop the relationship between thermochemical data and electrochemical PCET mechanism. An aminobenzoquinone modified monolayer showing nearly ideal electrochemical behavior and high stability was successfully prepared and used as a model system for the mechanistic study of electrochemical multiple electron/proton transfer. This model system has been proposed to undergo a 2e3H transfer at low pH electrolyte and a 2e2H transfer at high pH electrolyte. Two non-destructive electrochemical techniques (cyclic voltammetry and chronocoulmetry) have been applied for the measurement of apparent standard rate constant as a function of pH. Both pH dependent apparent formal potential and pH dependent apparent standard rate constant have been used to determine the charge transfer mechanism of this monolayer system. Under the assumption of an operative PCET mechanism (i.e. electron transfer step is the rate determining step), a theoretical description of this system has been developed based on the refinement and extension of previous models. By combining this extended theoretical model with pH dependent apparent formal potential and apparent standard rate constant, charge transfer pathways have been determined and shown to be consistent with the observed pH dependent electrochemical response, in addition, the determined pathways in this aminobenzoquinone modified monolayer are similar to previous reported pathways for benzoquinone freely dissolved in aqueous buffered electrolyte. A series of analytical expressions built in this thesis demonstrate that the parameters that differentiate stepwise mechanisms from concerted mechanisms can be classified into two aspects: thermodynamic parameters, namely acid dissociation constants, standard formal potentials; and kinetic parameters, namely standard rate constants, standard transfer coefficients. Although attempts to understand the relation between controlling parameters and electrochemical PCET mechanism (stepwise versus concerted) has been reported previously by some groups, there are still lots of unresolved aspects requiring further investigation. In this thesis, an important conclusion has been drawn which is that for the stepwise mechanism, an apparent experimentally observable kinetic isotope effect (KIE) can be induced by solvent isotope induced variation of acid dissociation constants, which contradicts previous understanding. Additionally, for the first time, values of apparent KIE, which were measured for the aminobenzoquinone modified monolayer system with stepwise PCET mechanism, were successfully explained by variation in acid dissociation constants, not by variation in standard rate constants. Based on theoretical prediction, a nitroxyl radical modified bilayer showing one electron one proton transfer reaction has been prepared in an effort to afford experimental verification. After applying similar analytical procedures as those for the aminobenzoquinone modified monolayer system, this bilayer system has been shown to follow the concerted 1e1H transfer pathway in high pH electrolytes. These latter contributions provide evidence that further development in this field will eventually lead to a comprehensive theory that can use known thermochemical variables to fully predict PCET mechanism.

The experimental factors such as the cell type and the treatment may have different impact on expression levels of individual genes which are quantitative measurements from microarrays. The measurements can be collected at a few unevenly spaced time points with replicates. The aim of this study is to consider cell type, treatment and short time series attributes and to infer about their effects on individual genes. A mixed effects model (LME) was proposed to model the gene expression data and the performance of the model was validated by a simulation study. Realistic data sets were generated preserving the structure of the sample real life data studied by Nymark et al. (2007). Predictive performance of the model was evaluated by performance measures, such as accuracy, sensitivity and specificity, as well as compared to the competing method by Smyth (2004), namely Limma. Both methods were also compared on real life data. Simulation results showed that the predictive performance of LME is as high as 99%, and it produces False Discovery Rate (FDR) as low as 0.4% whereas Limma has an FDR value of at least 32%. Moreover, LME has almost 99% predictive capability on the continuous time parameter where Limma has only about 67% and even it cannot handle continuous independent variables.

La thèse porte sur la synthèse d'observateurs pour les systèmes dynamiques hybrides.<br />Nous considérons particulièrement considéré les systèmes décrits par un ensemble fini de sous-systèmes linéaires à temps discret et<br />une loi de commutation. Le sous-système actif et les commutations d'un sous-système à un autre peuvent être définis par une commande externe contrôlable (systèmes à commutation), ou par des transitions autonomes (systèmes affines par morceaux). Sous<br />l'hypothèse du mode actif à chaque instant, nous montrons que l'association de l'observateur commuté avec une contrainte de<br />placement de pôles permet de proposer un schéma d'observation à entrée inconnue pour résoudre le problème de la synchronisation<br />des systèmes à commutation chaotiques avec un message incorporé. Dans le cas de des systèmes affines par morceaux, nous proposons une méthode pour détecter le mode actif. L'association de cette méthode avec l'observateur commuté permet l'estimation conjointe de l'état continu et état discret. Enfin, nous considérons le cas de commutations régies par un RdP. Nous proposons un schéma d'observation utilisant un observateur de RdP et un observateur commuté.

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This research aims to identify important factors contributing to a construction firm's profitability and to develop a prediction model which would help in determining the gross margin/profitability of a construction firm as a function of important parameters. All the data used in the research was taken from U.S Census Bureau reports. The novelty of the research lies on its focus at a state level, by dividing states into pertinent clusters and then analyzing the trends in each cluster independently. The research was divided into two phases. Phase 1 of the research focused on identification of the most important factors contributing to gross margin of a construction firm. The variables used were derived from the U.S Census Bureau data. Based on the independent variables and gross margin, all the states were divided into three clusters. Subsequently, a prediction model was developed for each cluster using step-wise backward elimination, thus, eliminating non-significant variables. Results of Model 1 gave impetus to developing Model 2. Model 1 clearly showed that labor productivity was the most important variable in determining gross margin. Model 2 was developed to predict gross margin as a function of single most important factor of labor productivity. Similar to Model 1, states were clustered based on their labor productivity and gross margin values. Prediction model was developed for each cluster. In this study, an excel embedded decision support tool was also developed. This tool would aid the decision-makers to view the state's level of gross margin and labor productivity at a glance. Decision support tool developed was in the form of color-coded maps, each of which was linked to a spreadsheet containing pertinent data. The most important conclusion of the research was that there exists a positive linear relationship between labor productivity and gross margin at a state level in the construction industry. The research also identified and quantified other important factors like percent of rental equipment used, percent of construction work sub-contracted out and percent of cost of materials, components and supplies which affect gross margin.

Hypothesis testing is foundational to the discipline of statistics. Procedures exist which control for individual Type I error rates and more global or family-wise error rates for a series of hypothesis tests. However, the ability of scientists to produce very large data sets with increasing ease has led to a rapid rise in the number of statistical tests performed, often with small sample sizes. This is seen particularly in the area of biotechnology and the analysis of microarray data. This thesis considers this high-dimensional context with particular focus on the effects of dependence on existing multiple hypothesis testing procedures. / While dependence is often ignored, there are many existing techniques employed currently to deal with this context but these are typically highly conservative or require difficult estimation of large correlation matrices. This thesis demonstrates that, in this high-dimensional context when the distribution of the test statistics is light-tailed, dependence is not as much of a concern as in the classical contexts. This is achieved with the use of a moving average model. One important implication of this is that, when this is satisfied, procedures designed for independent test statistics can be used confidently on dependent test statistics. / This is not the case however for heavy-tailed distributions, where we expect an asymptotic Poisson cluster process of false discoveries. In these cases, we estimate the parameters of this process along with the tail-weight from the observed exceedences and attempt to adjust procedures. We consider both conservative error rates such as the family-wise error rate and more popular methods such as the false discovery rate. We are able to demonstrate that, in the context of DNA microarrays, it is rare to find heavy-tailed distributions because most test statistics are averages.

Thesis (M.S.)--Northwest Missouri State University, 2006. / The full text of the thesis is included in the pdf file. Title from title screen of full text.pdf file (viewed on January 25, 2008) Includes bibliographical references.

Thesis (M.Ed.)--Memorial University of Newfoundland, 1999. / Bibliography: leaves 106-109.