Increasing socio-economic growth and development of South Africa’s freshwater systems require continuous augmentation of water sources to meet the growing water requirements of communities and industries. Anthropogenic disturbances have caused the water quality of many freshwater systems to drastically deteriorate due to constant disposal of domestic, industrial, and agricultural waste into surface waters. Government agencies make use of biomonitoring programmes to effectively manage the countries’ freshwater resources. These programmes use a variety of biological indicators (e.g., macroinvertebrates, fish, diatoms and algal species) and physico-chemical variables to determine the state of the environment. However, attempts to use microbial community structures as bioindicators of anthropogenic perturbations are greatly neglected. This study used molecular techniques (PCR-DGGE and 454-pyrosequencing) and multivariate analysis to develop a robust monitoring technique to determine the impacts of environmental disturbances on bacterial community compositions in river systems in the North West Province. Significant contributions made by this project included the establishment of a bacterial diversity framework for South African freshwater systems that are impacted by a variety of anthropogenic activities (e.g., urban and informal settlements, agriculture and mining). Furthermore, case studies demonstrated the prevalence of specific taxa at polluted sites, as well as positive and negative associations between taxa and environmental variables and pollutants. Finally, biogeochemical cycles could be partially matched to bacterial community structures in river systems. The first part of the project included a pilot study that investigated bacterial structures in a segment of the Vaal River in response to environmental parameters using molecular techniques and multivariate analysis. The most important observations made during this study included the generation of a larger bacterial diversity dataset by pyrosequencing compared to PCR-DGGE. In addition, metagenomic and multivariate analyses provided clues about potential biogeochemical roles of different taxa. The second and third part of the project included two case studies that investigated bacterial communities in the Mooi River and Wonderfonteinspruit in response to environmental activities. Both these systems are impacted by a variety of external sources such as urban and informal settlements, agriculture, and mining. The results demonstrated that perturbations nearby the Mooi River and Wonderfonteinspruit caused the overall water quality to deteriorate which in turn had a profound impact on bacterial community composition. Bacterial community structures at reference/control sites (Muiskraal and Turffontein dolomitic eye) had overall high species diversity (richness and evenness), whereas polluted sites showed lower species diversity and were dominated by the Beta- and Gammaproteobacteria, Bacteroidetes, and Verrucomicrobia. In addition, various potential pathogens (e.g. Eschirichia/Shigella, Legionella, Staphylococcus, Streptococcus etc.) were identified at impacted sites. Multivariate analysis suggested that bacterial communities and certain taxa (Malikia, Algoriphagus, Rhodobacter, Brevundimonas and Sphingopyxis) at polluted sites were mainly impacted by temperature, pH, nutrient levels, and heavy metals. Finally, the proportion of nitrogen and sulphur bacteria corresponded well with the nitrogen and sulphur levels measured in the Wonderfonteinspruit. Based on these results, it was concluded that bacterial community structures might provide a good indicator of anthropogenic disturbances in freshwater systems and may be incorporated into biomonitoring programs. / PhD (Environmental Sciences), North-West University, Potchefstroom Campus, 2015

Increasing socio-economic growth and development of South Africa’s freshwater systems require continuous augmentation of water sources to meet the growing water requirements of communities and industries. Anthropogenic disturbances have caused the water quality of many freshwater systems to drastically deteriorate due to constant disposal of domestic, industrial, and agricultural waste into surface waters. Government agencies make use of biomonitoring programmes to effectively manage the countries’ freshwater resources. These programmes use a variety of biological indicators (e.g., macroinvertebrates, fish, diatoms and algal species) and physico-chemical variables to determine the state of the environment. However, attempts to use microbial community structures as bioindicators of anthropogenic perturbations are greatly neglected. This study used molecular techniques (PCR-DGGE and 454-pyrosequencing) and multivariate analysis to develop a robust monitoring technique to determine the impacts of environmental disturbances on bacterial community compositions in river systems in the North West Province. Significant contributions made by this project included the establishment of a bacterial diversity framework for South African freshwater systems that are impacted by a variety of anthropogenic activities (e.g., urban and informal settlements, agriculture and mining). Furthermore, case studies demonstrated the prevalence of specific taxa at polluted sites, as well as positive and negative associations between taxa and environmental variables and pollutants. Finally, biogeochemical cycles could be partially matched to bacterial community structures in river systems. The first part of the project included a pilot study that investigated bacterial structures in a segment of the Vaal River in response to environmental parameters using molecular techniques and multivariate analysis. The most important observations made during this study included the generation of a larger bacterial diversity dataset by pyrosequencing compared to PCR-DGGE. In addition, metagenomic and multivariate analyses provided clues about potential biogeochemical roles of different taxa. The second and third part of the project included two case studies that investigated bacterial communities in the Mooi River and Wonderfonteinspruit in response to environmental activities. Both these systems are impacted by a variety of external sources such as urban and informal settlements, agriculture, and mining. The results demonstrated that perturbations nearby the Mooi River and Wonderfonteinspruit caused the overall water quality to deteriorate which in turn had a profound impact on bacterial community composition. Bacterial community structures at reference/control sites (Muiskraal and Turffontein dolomitic eye) had overall high species diversity (richness and evenness), whereas polluted sites showed lower species diversity and were dominated by the Beta- and Gammaproteobacteria, Bacteroidetes, and Verrucomicrobia. In addition, various potential pathogens (e.g. Eschirichia/Shigella, Legionella, Staphylococcus, Streptococcus etc.) were identified at impacted sites. Multivariate analysis suggested that bacterial communities and certain taxa (Malikia, Algoriphagus, Rhodobacter, Brevundimonas and Sphingopyxis) at polluted sites were mainly impacted by temperature, pH, nutrient levels, and heavy metals. Finally, the proportion of nitrogen and sulphur bacteria corresponded well with the nitrogen and sulphur levels measured in the Wonderfonteinspruit. Based on these results, it was concluded that bacterial community structures might provide a good indicator of anthropogenic disturbances in freshwater systems and may be incorporated into biomonitoring programs. / PhD (Environmental Sciences), North-West University, Potchefstroom Campus, 2015

Recent large-N studies conclude that inequality and ethnic distribution have no significant impact on the risk of civil conflict. This study argues that such conclusions are erroneous and premature due to incorrect specification of independent variables and functional forms. Case studies suggest that measures of inter-group inequality (horizontal inequality) and polarization (ethnic distribution distance from a bipolar equilibrium) are more accurate predictors of civil conflict, as they better capture the group-motivation aspect of conflict. This study explores whether indicators of inequality and ethnic distribution impact the probability of civil conflict across 38 developing countries in the period 1986 to 2004. Analysis reveals that horizontal inequality and polarization have significant, robust relationships with civil conflict. Furthermore, vertical, or individual, inequality is a robust, significant predictor of civil conflict when specified as a nonlinear function.

Acoustic methods can often be used with limited or no sample preparations making them ideal for rapid process analytical technologies (PATs). This dissertation focuses on the possible use of acoustic resonance spectroscopy as a PAT in the pharmaceutical industry. Current good manufacturing processes (cGMP) need new technologies that have the ability to perform quality assurance testing on all products. ARS is a rapid and non destructive method that has been used to perform qualitative studies but has a major drawback when it comes to quantitative studies. Acoustic methods create highly non linear correlations which usually results in high level computations and chemometrics. Quantification studies including powder contamination levels, hydration amounts and active pharmaceutical ingredient (API) concentrations have been used to test the hypothesis that bootstrap enhanced n-dimensional deformation of space (BENDS) could be used to overcome the highly non linear correlations that occur with acoustic resonance spectroscopy (ARS) eliminating a major drawback with ARS to further promote the device as a possible process analytical technology (PAT) in the pharmaceutical industry. BENDS is an algorithm that has been created to calculate a reduced linear calibration model from highly non linear relationships with ARS spectra. ARS has been shown to correctly identify pharmaceutical tablets and with the incorporation of BENDS, determine the hydration amount of aspirin tablets, D-galactose contamination levels of Dtagatose powders and the D-tagatose concentrations in resveratrol/D-tagatose combinatory tablets.

The study utilized the covariance structure comparison methodology - Multigroup Analysis in Structural Equation Modeling - evaluating measurement equivalence of English and Spanish versions of an employee opinion survey. The concept of measurement equivalence was defined as consisting of four components: sample equivalence, semantic equivalence, conceptual equivalence and scalar equivalence. The results revealed that the two language versions of the survey exhibited acceptable measurement equivalence across five survey dimensions Communications, Supervision, Leadership, Job Content & Satisfaction and Company Image & Commitment. Contrary to the study second hypothesis, there was no meaningful difference in opinion scores between English-speaking and Spanish-speaking respondents on the latent construct of Job Content & Satisfaction.

In the present study, parameter estimates, standard errors and chi-square statistics were compared using normal and elliptical estimation methods given three research conditions: population data contamination (10%, 20%, and 30%), sample size (100, 400, and 1000), and kurtosis (kappa =1,10, 20).

Two procedures for detection of differential item functioning (DIF) for polytomous items were generalized to detection of differential testlet functioning (DTLF). The methods compared were the logistic discriminant function analysis procedure for uniform and non-uniform DTLF (LDFA-U and LDFA-N), and the Mantel score test procedure. Further analysis included comparison of results of DTLF analysis using the Mantel procedure with DIF analysis of individual testlet items using the Mantel-Haenszel (MH) procedure. Over 600 chi-squares were analyzed and compared for rejection of null hypotheses. Samples of 500, 1,000, and 2,000 were drawn by gender subgroups from the NELS:88 data set, which contains demographic and test data from over 25,000 eighth graders. Three types of testlets (totalling 29) from the NELS:88 test were analyzed for DTLF. The first type, the common passage testlet, followed the conventional testlet definition: items grouped together by a common reading passage, figure, or graph. The other two types were based upon common content and common process. as outlined in the NELS test specification.

The problem of statistical calibration of a measuring instrument can be framed both in a statistical context as well as in an engineering context. In the first, the problem is dealt with by distinguishing between the "classical" approach and the "inverse" regression approach. Both of these models are static models and are used to estimate "exact" measurements from measurements that are affected by error. In the engineering context, the variables of interest are considered to be taken at the time at which you observe the measurement. The Bayesian time series analysis method of Dynamic Linear Models (DLM) can be used to monitor the evolution of the measures, thus introducing a dynamic approach to statistical calibration. The research presented employs the use of Bayesian methodology to perform statistical calibration. The DLM framework is used to capture the time-varying parameters that may be changing or drifting over time. Dynamic based approaches to the linear, nonlinear, and multivariate calibration problem are presented in this dissertation. Simulation studies are conducted where the dynamic models are compared to some well known "static'" calibration approaches in the literature from both the frequentist and Bayesian perspectives. Applications to microwave radiometry are given.

In recent years, the development of new genomic technologies has allowed for the investigation of many regulatory epigenetic marks besides expression levels, on a genome-wide scale. As the price for these technologies continues to decrease, study sizes will not only increase, but several different assays are beginning to be used for the same samples. It is therefore desirable to develop statistical methods to integrate multiple data types that can handle the increased computational burden of incorporating large data sets. Furthermore, it is important to develop sound quality control and normalization methods as technical errors can compound when integrating multiple genomic assays. DNA methylation is a commonly studied epigenetic mark, and the Infinium HumanMethylation450 BeadChip has become a popular microarray that provides genome-wide coverage and is affordable enough to scale to larger study sizes. It employs a complex array design that has complicated efforts to develop normalization methods. We propose a novel normalization method that uses a set of stable methylation sites from housekeeping genes as empirical controls to fit a local regression hypersurface to signal intensities. We demonstrate that our method performs favorably compared to other popular methods for the array. We also discuss an approach to estimating cell-type admixtures, which is a frequent biological confound in these studies. For data integration we propose a gene-centric procedure that uses canonical correlation and subsequent permutation testing to examine correlation or other measures of association and co-localization of epigenetic marks on the genome. Specifically, a likelihood ratio test for general association between data modalities is performed after an initial dimension reduction step. Canonical scores are then regressed against covariates of interest using linear mixed effects models. Lastly, permutation testing is performed on weighted correlation matrices to test for co-localization of relationships to physical locations in the genome. We demonstrate these methods on a set of developmental brain samples from the BrainSpan consortium and find substantial relationships between DNA methylation, gene expression, and alternative promoter usage primarily in genes related to axon guidance. We perform a second integrative analysis on another set of brain samples from the Stanley Medical Research Institute.

La qualité de la viande englobe des critères d'importance différente suivant l'espèce animale considérée. Chez le porc, la qualité de la viande a un impact économique important et de nombreux travaux ont pu montrer que les interactions entre le type génétique (particulièrement les gènes halothane et Rendement Napole), les conditions d'élevage et les conditions d'abattage des animaux déterminent la qualité de la viande de porc. L'Europe, longtemps leader du marché mondial des produits de la viande de porc, se trouve aujourd'hui confronté à la concurrence d'autres pays, notamment le Brésil, les Etats-unis et la Chine. Ce projet de thèse s'inscrit dans le cadre d'un projet européen multidisciplinaire portant sur l'amélioration de la qualité de la viande de porc et des produits dérivés pour le consommateur. Un des modules est dédié à l'intégration des connaissances passées et celles à venir afin de construire des modèles de prédiction des qualités technologiques et sensorielles de la viande de porc à partir des données se rapportant à l'animal, ainsi qu'aux conditions d'élevage et de pré-abattage. L'objectif de la thèse est d'intégrer l'ensemble des données bibliographiques et expérimentales relatives aux principaux facteurs influençant la qualité de viande dans le cadre d'une méta-analyse, qui est une démarche statistique combinant les résultats d'une série d'études indépendantes sur un problème donné. Les résultats obtenus ont permis de préciser l'effet du gène halothane, des temps de jeûne, de transport et de repos à l'abattoir sur les principaux paramètres d'évaluation de la qualité technologique de la viande de porc. En effet, nos résultats ont pu confirmer l'effet significatif du gène halothane sur l'ensemble des paramètres de qualité étudiés. Cependant, l'effet significatif du gène halothane a été associé à celui de la race uniquement pour expliquer les variations des paramètres suivants : L* (la réflectance), b* (indice de jaune) et les pertes d'exsudat (DL). La méta-régression a permis de mettre en évidence l'effet du poids à l'abattage sur les différences de pH ultime (pHu) entre les génotypes homozygotes NN et nn. Parmi les facteurs de pré-abattage analysés, nos résultats indiquent que le temps de jeûne affecte le pHu et le DL mesurés au niveau du muscle longissimus, alors que le temps de repos à l'abattoir affecte le pHu du muscle semimembranosus. Le transport et l'interaction transport x temps de jeûne n'avaient d'effet significatif que sur les variations de DL. L'effet significatif de l'apport en vitamine E sur le processus d'oxydation des lipides pendant la conservation de la viande, et par conséquent, sur la qualité technologique de la viande a pu être démontré en utilisant un modèle de régressionméta-analytique non linéaire. D'un point de vue statistique, la comparaison des méthodes statistiques de méta-analyse par approche bayésienne et fréquentiste a permis de mettre en évidence l'avantage de la première quant à l'obtention de résultats plus probants lorsqu'il s'agit de méta-analyse sur un nombre de données relativement limité. Parallèlement à l'approche méta-analytique, une étude exploratoire par analyse multivariée a été réalisée afin d'identifier les corrélations qui existent entre un très grand nombre de variables structurées en groupes distincts. Nos résultats ont montré que les variables discriminant les cinq classes de race (Large White et Basque) x système d'élevage (conventionnel, alternatif et extensif) étaient les mêmes que celles qui discriminaient les individus entre eux, en l'occurrence les variables transcriptomiques, chimiques et technologiques. Le groupe composé des variables relatives à la réactivité à l'abattage discriminaient principalement les systèmes d'élevage, en particulier la classe des porcs basques élevés dans le système extensif. / Meat quality includes criteria of different importance depending on the animal species. Meat quality is a significant economic factor in pork production, and numerous publications have shown that it is strongly influenced by the interaction between genetic type (especially the halothane gene (Hal) and Napole yield gene (RN)), breeding conditions, and pre-slaughter and slaughter conditions of animals. The European Union, longtime leader of the globalmarket of pork and pork products, now faces increasing competition from other countries,including Brazil, the United States and China. This thesis project is part of a multidisciplinary European project on improving the quality of pork and pork products for the consumer. One of the modules of this project is dedicated to the integration of existing and upcoming data to produce a model for predicting technological and sensory pork quality, based on animal,production, and slaughter information. The objective of this thesis is to synthesize existing knowledge derived from bibliographic and experimental data relating to the main factors influencing meat quality within a meta-analysis, which is a statistical approach combining the results of a series of independent studies on a given problem. The results of this work have confirmed the effect of the halothane gene, as well as fasting, transport and lairage times on most of the analyzed parameters of technological pork meat quality. Indeed, our meta-analysis confirmed the significant effect of the halothane gene on all the analyzed meat quality attributes. However, the halothane gene effect was associated with the breed effect only for the following variables: L*-value (reflectance), b*-value (yellowness) and DL (drip loss). Slaughter weight contributed significantly only to the explanation of differences in ultimate pH between homozygous genotypes: NN and nn. Regarding the preslaughter conditions, the results of our meta-analysis showed that fasting time had a significant effect on pHu and DL measured in longissimus muscle. While, lairage affected only the pHu in semimembranosusmuscle. Interestingly, we found that DL was the lonely attribute significantly affected by transport time and its interaction with fasting time. The significant effect of the vitamin E supplementation on lipid oxidation process in pork and, therefore, affect the technological meat quality, was demonstrated by using a non linear meta-analytic regression model. Statistically, the comparison between the Bayesian and frequentist meta-analytic approaches has highlighted the ability of the hierarchical Bayesian model to reduce uncertainty in parameter estimates, especially when the number of studies included in the meta-analysis is relatively limited. In addition to the meta-analytic approach, an exploratory study by multivariate analyses was performed to identify the correlations among a large number of variables structured into separate groups. Our results showed that the variables which discriminated the five classes of breed (Large White and Basque pigs) x rearing system (conventional, alternative and extensive) were the same as those discriminating individuals. Indeed, a first group composed of transcriptomic, chemical and technological variables discriminated breeds. Slaughter reactivity variables discriminated rearing systems, especially the Basque pigs reared in the extensive system.