Thesis (M.Pharm. (Pharmacy Practice))--North-West University, Potchefstroom Campus, 2007.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 72-76).

The aim of this case study is to analyse cooperation mainly in issues related to water management in the area along the Miño river. The study focuses on the Spanish municipalities that limit with the river and that are in the border area with Portugal. There was a key issue which was discovered during the reading and analysis of data, a change of no cooperation to cooperation on the Spanish-Portuguese border. There was previously a political culture of no cooperation among the autonomous regions in Spain, which could have affected cooperation with the region of north Portugal. The fact the both countries have different administrative cultures could also impede cooperation. Nevertheless cooperation seems to have developed and in order to study this phenomenon the researcher uses a qualitative method and relies on a choice of institutional theories. This research studies how institutions affect cooperation in this particular case. The theories will analyse the impact of political institutions and the relation between institutions and individuals. They also help to identify how human behaviour affects processes and events.

Reports of software a development projects that miss schedule, exceeds budget and deliver products with poor quality are abundant in the literature. Both researchers and the industry are seeking methods to counter these trends and improve software quality. Software Process Improvement is a systematic approach to improve the capabilities and performance of software organizations. One basic idea is to assess the organizations’ current practice and improve their software process on the basis of the competencies and experiences of the practitioners working in the organization. A major challenge is to create strategies and mechanisms for managing relevant and updated knowledge about software development and maintenance. Insights from the field of knowledge management are therefore potentially useful in software process improvement efforts to facilitate the creation, modification, and sharing of software processes in any organization. In the work presented in this thesis, we have made an overview of empirical studies on the effect of knowledge management in software engineering. We have categorized these studies according to a framework and we report findings on the major concepts that have been investigated empirically, as well as the research methods applied within the field. We have also investigated two main strategies for knowledge management, codification and personalization, through the application of four concrete methods in a software process improvement setting: Mentoring, Rational Unified Process, Process Workshops and Post Mortem Analysis. We have classified the work in this thesis within three main themes: RT1: Previous research on knowledge management in software engineering. RT2: Application of knowledge management to improve the software process through codification of knowledge. RT3: Application of knowledge management to improve the software process through personalization of knowledge. The main contributions are: C1: An overview of the research literature on empirical studies of knowledge management in software engineering. C2: A method for tailoring the Rational Unified Process to the development process of a software consulting company. C3: Improvements of the Process Workshops method by contextualization. C4: Improvement of the root-cause analysis phase of the lightweight Post Mortem Analysis for more effective project retrospectives. C5: Proposed methods to increase the learning effect of mentor programs in software engineering.

Nucleic acids have proven to be viable targets for small molecule drugs. While many examples of such drugs are detailed in the literature, only a select few have found practical use in a clinical setting. These currently employed nucleic acid targeting therapies suffer from either debilitating off-target side effects or succumb to a resistance mechanism of the target. The need for new small molecules that target nucleic acids is evident. However, designing a novel drug to bind to DNA or RNA requires a detailed understanding of exactly what binding environments each nucleic acid presents. In an effort to broaden this knowledge, the work presented in this thesis details the binding location and affinity of known and novel nucleic acid binding small molecules with targets ranging from simple RNA secondary structure all the way to the complex structure of ribosomal RNA. Specifically, it is shown that the anthracycline class of antineoplastics prefer to bind at or near mismatch base pairs in both physiologically relevant iron responsive element RNA hairpin constructs as well as DNA hairpin constructs presenting mismatched base pairs. Also characterized in this thesis is a novel class of topoisomerase II / histone deacetylase inhibitor conjugates that display a unique affinity for DNA over RNA. Finally, the novel class of macrolide-peptide conjugates, known as peptolides, are shown to retain potent translation inhibition of the prokaryotic ribosome. The binding pocket of the peptolides, including a crevice previously unreachable by macrolides that extends away from the peptidyl transferase center toward the subunit interface, is confirmed in detail via chemical footprinting of the 70S ribosome. Overall, the identification of a novel binding site for the anthracycline class of drugs and the characterization of the two novel drug designs presented in this thesis will undoubtedly aid in the effort to design and discover new molecules that aim for nucleic acid targets. For example, the anthracycline derivative topoisomerase II / histone deacetylase inhibitor conjugates, with their differential mode of nucleic acid binding, may prove to have a unique side effect profile in a therapeutic application. The peptolide compounds also have the potential to be applied as novel antibiotics as they bind to an area of the prokaryotic ribosome unrelated to known macrolide resistance mutations. Furthermore, as a result of the observation of this thesis work that some peptolides also posses eukaryotic translation inhibition capabilities, they could prove to be useful in preventing the growth of rapidly proliferating eukaryotic cells such as plasmodium, leishmania, or tumor cells. Additionally, different head groups could be utilized in creating new peptolides; for example, an oxazolidinone antibiotic could be employed to sample a different binding area of the ribosome.

Lo studio analizza la relazione tra i diversi prezzi delle droghe illegali, eroina e cocaina, e il livello di violenza sistemica in un territorio. L'ipotesi dello studio è che ad un aumento dei prezzi delle droghe illegali, si registra una maggiore violenza causata dal maggiore ritorno economico derivante dalla commissione della violenza. L'analisi empirica si riferisce agli anni ottanta e novanta negli Stati Uniti d'America. Lo studio di mostra la validità dell'ipotesi e propone nuove ambiti di ricerca. / The study analyzes the relation between the different prices of illegal drugs, heroin and cocaine, and the level of systemic violence recorded in a territory. The hypothesis of the study is that from an increase of the prices of illegal drugs, it is derived a greater level of violence caused by the greater menotary return derived by the commission of violence. The empirical analysis referred to the eighties and nineties in the United States of America. The study demonstrates the hypothesis and proposes new research paths.

Cryopreservation of adherent cells may be advantageous for cell types that are difficult to preserve in suspension or when it is necessary to preserve characteristics of the adherent cultured cells. Vitrification is a promising procedure for the preservation of adherent cells that prevents ice crystal formation and the resulting dissociation and morphological damage. To successfully vitrify adherent cells, high concentrations of CPA are required which increases the likelihood of osmotic and toxic damage. In this dissertation, we describe a rational design strategy that predicts mathematically optimized CPA addition and removal procedures based on the minimization of a toxicity cost function. These rationally designed procedures rely on the accurate knowledge of cell biophysical parameters. We validate an in situ calcein fluorescence quenching method for the determination of membrane permeability parameters for adherent cells. We also describe the determination of osmotic tolerance limits for adherent cells. We use rational design strategies to determine CPA addition and removal procedures for adherent endothelial cells, neuronal cells, and induced pluripotent stem cells as well as oocytes. Also, we provide experimental support for the feasibility of these methods using adherent endothelial cells. The mathematical methods and experimental procedures outlined in this dissertation are important tools for the design of addition and removal procedures for concentrated CPA solutions. This dissertation is an important step toward successful design and implementation of vitrification strategies for adherent cells and tissues. / Graduation date: 2013 / Access restricted to the OSU Community at author's request from Feb. 14, 2013 - Feb. 14, 2015

Rational expectations provide people or economic agents making future decision with available information and past experiences. The first approach to the idea of rational expectations was given approximately fifty years ago by John F. Muth. Many models in economics have been studied using the rational expectations idea. The most familiar one among them is the rational expectations version of the Cagans hyperination model where the expectation for tomorrow is formed using all the information available today. This model was reinterpreted by Thomas J. Sargent and Neil Wallace in 1973. After that time, many solution techniques were suggested to solve the Cagan type rational expectations (CTRE) model. Some economists such as Muth [13], Taylor [26] and Shiller [27] consider the solutions admitting an infinite moving-average representation. Blanchard and Kahn [28] find solutions by using a recursive procedure. A general characterization of the solution was obtained using the martingale approach by Broze, Gourieroux and Szafarz in [22], [23]. We choose to study martingale solution of CTRE model. This thesis is comprised of five chapters where the main aim is to study the CTRE model on isolated time scales. Most of the models studied in economics are continuous or discrete. Discrete models are more preferable by economists since they give more meaningful and accurate results. Discrete models only contain uniform time domains. Time scale calculus enables us to study on m-periodic time domains as well as non periodic time domains. In the first chapter, we give basics of time scales calculus and stochastic calculus. The second chapter is the brief introduction to rational expectations and the CTRE model. Moreover, many other solution techniques are examined in this chapter. After we introduce the necessary background, in the third chapter we construct the CTRE Model on isolated time scales. Then we give the general solution of this model in terms of martingales. We continue our work with defining the linear system and higher order CTRE on isolated time scales. We use Putzer Algorithm to solve the system of the CTRE Model. Then, we examine the existence and uniqueness of the solution of the CTRE model. In the fourth chapter, we apply our solution algorithm developed in the previous chapter to models in Finance and stochastic growth models in Economics.

Moral realism is the view that there are such things as moral facts. Moral realists have attempted to combat the skeptical problem of relativism, which is that the truth of an ethical value judgment is often, or always, subjective, that is, relative to the parties it involves. This essay presents, discusses, and criticizes Hilary Putnam’s attempt at maintaining moral realism while at the same time maintaining a degree of epistemological relativism. Putnam’s positive account originates in moral epistemology, at the heart of which lies truth, as idealized rational acceptability or truth under ideal conditions. The bridge between moral epistemology and normative ethics stems from Putnam’s disintegration of facts and values. His theory is finalized in the construction of a normative moral theory, in which the central notion is incessant self-criticism in order to maintain rationality. After presenting Putnam’s core thesis, the criticism raised by Richard Rorty, is deliberated upon. Rorty is critical of Putnam’s attempt at holding on to objectivity, because he does not understand how objective knowledge can be both relative to a conceptual scheme, and at the same time objective. The conclusion is that Putnam is unable to maintain his notion of truth as idealized rational acceptability and is forced into epistemological relativism. Putnam’s normative ethics has characteristics in common with virtue ethics, and is of much interest regardless of whether it can be grounded epistemologically or not.

Bivariate or multivariate correlated data may be collected on a sample of unit in many applications. When the experimenters concern about the failure times of two related subjects for example paired organs or two chronic diseases, the bivariate binary data is often acquired. This type of data consists of a observation point x and indicators which represent whether the failure times happened before or after the observation point. In this work, the observed bivariate data can be written with the following form {x, £_1=I(X1≤ x), £_2=I(X2≤ x)}.The corresponding optimal design problems for parameter estimation under this type of bivariate data are discussed. For this kind of the multivariate responses with explanatory variables, their marginal distributions may be from different distributions. Copula model is a way to formulate the relationship of these responses, and the association between pairs of responses. Copula models for bivariate binary data are considered useful in practice due to its flexibility. In this dissertation for bivariate binary data, the marginal functions are assumed from exponential or Weibull distributions and two assumptions, independent or correlated, about the joint function between variables are considered. When the bivariate binary data is assumed correlated, the Clayton copula model is used as the joint cumulative distribution function. There are few works addressed the optimal design problems for bivariate binary data with copula models. The D-optimal designs aim at minimizing the volume of the confidence ellipsoid for estimating unknown parameters including the association parameter in bivariate copula models. They are used to determine the best observation points. Moreover, the Ds-optimal designs are mainly used for estimation of the important association parameter in Clayton model. The D- and Ds-optimal designs for the above copula model are found through the general equivalence theorem with numerical algorithm. Under different model assumptions, it is observed that the number of support points for D-optimal designs is at most as the number of model parameters for the numerical results. When the difference between the marginal distributions and the association are significant, the association becomes an influential factor which makes the number of supports gets larger. The performances of estimation based on optimal designs are reasonably well by simulation studies. In survival experiments, the experimenter customarily takes trials at some specific points such as the position of the 25, 50 and 75 percentile of distributions. Hence, we consider the design efficiencies when the design points for trials are at three or four particular percentiles. Although it is common in practice to take trials at several quantile positions, the allocations of the proportion of sample size also have great influence on the experimental results. To use a locally optimal design in practice, the prior information for models or parameters are needed. In case there is not enough prior knowledge about the models or parameters, it would be more flexible to use sequential experiments to obtain information in several stages. Hence with robustness consideration, a sequential procedure is proposed by combining D- and Ds-optimal designs under independent or correlated distribution in different stages of the experiment. The simulation results based on the sequential procedure are compared with those by the one step procedures. When the optimal designs obtained from an incorrect prior parameter values or distributions, those results may have poor efficiencies. The sample mean of estimators and corresponding optimal designs obtained from sequential procedure are close to the true values and the corresponding efficiencies are close to 1. Huster (1989) analyzed the corresponding modeling problems for the paired survival data and applied to the Diabetic Retinopathy Study. Huster (1989) considered the exponential and Weibull distributions as possible marginal distributions and the Clayton model as the joint function for the Diabetic Retinopathy data. This data was conducted by the National Eye Institute to assess the effectiveness of laser photocoagulation in delaying the onset of blindness in patients with diabetic retinopathy. This study can be viewed as a prior experiment and provide the experimenter some useful guidelines for collecting data in future studies. As an application with Diabetic Retinopathy Study, we develop optimal designs to collect suitable data and information for estimating the unknown model parameters. In the second part of this work, the optimal design problems for parameter estimations are considered for the type of proportional data. The nonlinear model, based on Jorgensen (1997) and named the dispersion model, provides a flexible class of non-normal distributions and is considered in this research. It can be applied in binary or count responses, as well as proportional outcomes. For continuous proportional data where responses are confined within the interval (0,1), the simplex dispersion model is considered here. D-optimal designs obtained through the corresponding equivalence theorem and the numerical results are presented. In the development of classical optimal design theory, weighted polynomial regression models with variance functions which depend on the explanatory variable have played an important role. The problem of constructing locally D-optimal designs for simplex dispersion model can be viewed as a weighted polynomial regression model with specific variance function. Due to the complex form of the weight function in the information matrix is considered as a rational function, an approximation of the weight function and the corresponding optimal designs are obtained with different parameters. These optimal designs are compared with those using the original weight function.