Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 135-139).

The amounts of data collected from each sample of e.g. chemical or biological materials have increased by orders of magnitude since the beginning of the 20th century. Furthermore, the number of ways to collect data from observations is also increasing. Such configurations with several massive data sets increase the demands on the methods used to analyse them. Methods that handle such data are called multiblock methods and they are the topic of this thesis. Data collected from advanced analytical instruments often contain variation from diverse mutually independent sources, which may confound observed patterns and hinder interpretation of latent variable models. For this reason, new methods have been developed that decompose the data matrices, placing variation from different sources of variation into separate parts. Such procedures are no longer merely pre-processing filters, as they initially were, but have become integral elements of model building and interpretation. One strain of such methods, called OPLS, has been particularly successful since it is easy to use, understand and interpret. This thesis describes the development of a new multiblock data analysis method called OnPLS, which extends the OPLS framework to the analysis of multiblock and path models with very general relationships between blocks in both rows and columns. OnPLS utilises OPLS to decompose sets of matrices, dividing each matrix into a globally joint part (a part shared with all the matrices it is connected to), several locally joint parts (parts shared with some, but not all, of the connected matrices) and a unique part that no other matrix shares. The OnPLS method was applied to several synthetic data sets and data sets of “real” measurements. For the synthetic data sets, where the results could be compared to known, true parameters, the method generated global multiblock (and path) models that were more similar to the true underlying structures compared to models without such decompositions. I.e. the globally joint, locally joint and unique models more closely resembled the corresponding true data. When applied to the real data sets, the OnPLS models revealed chemically or biologically relevant information in all kinds of variation, effectively increasing the interpretability since different kinds of variation are distinguished and separately analysed. OnPLS thus improves the quality of the models and facilitates better understanding of the data since it separates and separately analyses different kinds of variation. Each kind of variation is purer and less tainted by other kinds. OnPLS is therefore highly recommended to anyone engaged in multiblock or path model data analysis.

Copper (Cu) is an essential trace element in ruminants such as the cow. Its deficiency leads to a number of debilitating symptoms and can eventually cause death. Secondary Cu deficiency is caused by the presence of chemical antagonists such as the thiomolybdates (TMs) (MoOxS4-x2-; x = 0 3). TMs form in the rumen and then form tightly bound insoluble complexes with Cu. These complexes are then excreted and the Cu is unavailable to the animal. The TMs and their effects on ruminant Cu are the focus of this thesis.<p>This study includes three main bodies of work. First, a method for quantifying the composition of TM mixtures in solution was developed. Second, the rate constants of TM interconversions were determined. Third, reactions between Cu and the TMs were studied. This work is part of an ongoing study in the Reid group to model Cu-ligand speciation in the rumen. <p>Thiomolybdates form by successive replacement of molybdate (MoO42-) O ligands with S. This makes synthesis of the uncontaminated compounds difficult. Mixtures of TMs are best analyzed by UV-visible spectroscopy despite the considerable spectral overlap. The combination of these two issues makes the characterization of the spectra difficult. In this study, a method was developed to establish the spectra of the pure TMs despite cross-contamination. Multivariate curve fitting methods were used to establish the composition of synthesized samples simultaneously with the molar absorptivities of the pure TMs. This was done using a Beers Law model. The composition was determined from a fit using assumed molar absorptivities. The absorptivities were then refined using the composition results. These processes were successively reiterated until both were optimized. The optimized absorptivities could then be used to determine the composition of any TM solution mixture. <p>The kinetics of TM formation under biologically relevant conditions were followed by UV-visible spectroscopy. The spectra were then analyzed, using the method developed above, to determine all TM concentrations. Curve fitting methods were used to simultaneously determine the rate constants of all processes that occurred. Integrated rate equations used in the fitting process were developed using the Laplace Transform method. Rate constants were determined at varying pH, ionic strengths and temperatures. From this information it was shown that TM formation and hydrolysis occurs via an associative mechanism. It was also determined that H2S and not HS- was the sulfide nucleophile in TM formation reactions.<p>This study was then extended to include reactions involving Cu and the TMs. First, the UV-visible spectra of the reaction products of Cu with each TM were characterized. This allowed the kinetics of reactions between Cu and the TMs to be followed. This reaction has been found to proceed via an intermediate. Molar absorptivities for this intermediate were optimized along with the appropriate rate constants. This was done using a combination of mathematical simulations and the curve fitting methods used for the TM kinetics. The resulting rate constants can be compared with those obtained previously in the group using a Cu ion selective electrode. <p>These rate constants were used in conjunction with the TM formation rate constants to perform simulations. The results of these simulations provide a picture of what is expected to occur in the rumen. Reactions were also performed in which TM formation occurred in the presence of Cu. This was then extended to mimic bovine feeding habits. Here, portions of the reactions mixture was removed at various time intervals and replaced with fresh reagents. These experiments were used to gain a qualitative picture of Cu speciation in the presence of the TMs over time. The work presented in this thesis provides a crucial step toward understanding the problem of bovine copper deficiency.

Copper (Cu) is an essential trace element in ruminants such as the cow. Its deficiency leads to a number of debilitating symptoms and can eventually cause death. Secondary Cu deficiency is caused by the presence of chemical antagonists such as the thiomolybdates (TMs) (MoOxS4-x2-; x = 0 3). TMs form in the rumen and then form tightly bound insoluble complexes with Cu. These complexes are then excreted and the Cu is unavailable to the animal. The TMs and their effects on ruminant Cu are the focus of this thesis.<p>This study includes three main bodies of work. First, a method for quantifying the composition of TM mixtures in solution was developed. Second, the rate constants of TM interconversions were determined. Third, reactions between Cu and the TMs were studied. This work is part of an ongoing study in the Reid group to model Cu-ligand speciation in the rumen. <p>Thiomolybdates form by successive replacement of molybdate (MoO42-) O ligands with S. This makes synthesis of the uncontaminated compounds difficult. Mixtures of TMs are best analyzed by UV-visible spectroscopy despite the considerable spectral overlap. The combination of these two issues makes the characterization of the spectra difficult. In this study, a method was developed to establish the spectra of the pure TMs despite cross-contamination. Multivariate curve fitting methods were used to establish the composition of synthesized samples simultaneously with the molar absorptivities of the pure TMs. This was done using a Beers Law model. The composition was determined from a fit using assumed molar absorptivities. The absorptivities were then refined using the composition results. These processes were successively reiterated until both were optimized. The optimized absorptivities could then be used to determine the composition of any TM solution mixture. <p>The kinetics of TM formation under biologically relevant conditions were followed by UV-visible spectroscopy. The spectra were then analyzed, using the method developed above, to determine all TM concentrations. Curve fitting methods were used to simultaneously determine the rate constants of all processes that occurred. Integrated rate equations used in the fitting process were developed using the Laplace Transform method. Rate constants were determined at varying pH, ionic strengths and temperatures. From this information it was shown that TM formation and hydrolysis occurs via an associative mechanism. It was also determined that H2S and not HS- was the sulfide nucleophile in TM formation reactions.<p>This study was then extended to include reactions involving Cu and the TMs. First, the UV-visible spectra of the reaction products of Cu with each TM were characterized. This allowed the kinetics of reactions between Cu and the TMs to be followed. This reaction has been found to proceed via an intermediate. Molar absorptivities for this intermediate were optimized along with the appropriate rate constants. This was done using a combination of mathematical simulations and the curve fitting methods used for the TM kinetics. The resulting rate constants can be compared with those obtained previously in the group using a Cu ion selective electrode. <p>These rate constants were used in conjunction with the TM formation rate constants to perform simulations. The results of these simulations provide a picture of what is expected to occur in the rumen. Reactions were also performed in which TM formation occurred in the presence of Cu. This was then extended to mimic bovine feeding habits. Here, portions of the reactions mixture was removed at various time intervals and replaced with fresh reagents. These experiments were used to gain a qualitative picture of Cu speciation in the presence of the TMs over time. The work presented in this thesis provides a crucial step toward understanding the problem of bovine copper deficiency.

Impacts of climatic changes on in-land waters of Turkey is a topic that has not been sufficiently investigated yet. In this study, some exploratory work have been performed to form the core of further studies on the subject. EOF (Empirical Orthogonal Function) analysis has been applied to SLP (Sea Level Pressure) field with a wide coverage (20-70N, 50W-70E). The dominant sources of variability in this atmospheric system have been shown to be driven by 3 circulation indices, NAO (North Atlantic Oscillation), EAWR (East Atlantic - West Russia) and EA (East Atlantic) patterns. Linkages between this atmospheric system and the hydro-meteorological properties (data compiled from governmental organizations) of major Turkish lake ecosystems has been investigated with use of ordinary correlation analysis and CCA (Canonical Correlation Analysis). The results revealed the heavy forcing of large scale SLP field on regional temperature and E--P (evaporation minus precipitation) fields. The 15-year data set of Lake Mogan, as the longest available found, was used to exemplify the approaches and methodologies that can be employed for understanding the influence of climate variability on biological properties of lakes. It was suggested that temperature and salinity, being effective on phytoplankton and zooplankton groups, mediate the climatic impacts in Lake Mogan.

Thesis (Ph. D.)--University of California, Riverside, 2008. Thesis (Ph. D.)--University of California, Riverside, 2009. / Includes abstract. Title from first page of PDF file (viewed February 3, 2009). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 135-137). Includes bibliographical references (leaves ). Also issued in print.

Thesis (Ph.D.)--University of Oklahoma, 1991. / Includes bibliographical references (leaves 148-153).

published_or_final_version / Community Medicine / Master / Master of Philosophy

published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

The purpose of this study is to investigate and understand data which are grouped into categories. At the onset, the study presents a review of early research contributions and controversies surrounding categorical data analysis. The concept of sparseness in a contingency table refers to a table where many cells have small frequencies. Previous research findings showed that incorrect results were obtained in the analysis of sparse tables. Hence, attention is focussed on the effect of sparseness on modelling and analysis of categorical data in this dissertation. Cressie and Read (1984) suggested a versatile alternative, the power divergence statistic, to statistics proposed in the past. This study includes a detailed discussion of the power-divergence goodness-of-fit statistic with areas of interest covering a review on the minimum power divergence estimation method and evaluation of model fit. The effects of sparseness are also investigated for the power-divergence statistic. Comparative reviews on the accuracy, efficiency and performance of the power-divergence family of statistics under large and small sample cases are presented. Statistical applications on the power-divergence statistic have been conducted in SAS (Statistical Analysis Software). Further findings on the effect of small expected frequencies on accuracy of the X2 test are presented from the studies of Tate and Hyer (1973) and Lawal and Upton (1976). Other goodness-of-fit statistics which bear relevance to the sparse multino-mial case are discussed. They include Zelterman's (1987) D2 goodness-of-fit statistic, Simonoff's (1982, 1983) goodness-of-fit statistics as well as Koehler and Larntz's tests for log-linear models. On addressing contradictions for the sparse sample case under asymptotic conditions and an increase in sample size, discussions are provided on Simonoff's use of nonparametric techniques to find the variances as well as his adoption of the jackknife and bootstrap technique. / Thesis (M.Sc.)-University of Natal, Durban, 1998.