Oceanic anoxic events (OAEs) are periods in Earth's history when oceans were depleted in dissolved oxygen and characterized by deposition of organic-rich sediments. The Oceanic Drilling Program (ODP) has drilled through OAEs in a number of areas worldwide, collecting core and borehole log data. This project attempts to identify a characteristic signature from known ODP OAE sections using these data and to apply the signature to identify OAE intervals in Gulf of Mexico wells where cores are lacking. Additionally, pseudo density curves were generated from ODP logs and compared to bulk density logs to determine if the deviation between the two would aid identification of OAE intervals. A general, though not fool proof, signature of high gamma ray, uranium, neutron porosity and low density was seen in nearly all of the ODP holes. Using this signature 20 potential OAE intervals were identified in the Gulf of Mexico.

Gossypol and gossypol derivatives are natural byproducts of a variety of cotton plant species that poses interesting chemical, biological, and medicinal properties that are currently heavily researched. Supporting evidence suggest that gossypol and gossypol derivatives act on the Bcl-2 proteins that have been linked to certain cancers. Gossypol amine derivatives, specifically, are actively researched and a variety of amine derivatives have already been synthesized. However, gossypol and its derivatives are challenging compounds to work with because many of its derivatives tend to exist in various tautomeric forms. When analyzing gossypol and its derivatives it is the complex electron configuration that dictates the chemical mechanism and biological activity. The following research provides a charge density study that describes in detail the electronic configuration via Bader's topological analysis of di(methoxy)gossypol and di(propylamino) gossypol. In addition, a series of crystallographic studies of gossypol amine derivatives and di(methoxy)gossypol are also analyzed.

M.Phil. / Numerous studies have demonstrated the favourable effects of aerobic training on blood lipid profiles. However, few studies have generated conclusive data on the effects of dynamic resistance training (DRT) on blood lipid profiles. In order to evaluate the effect of DRT on lipoprotein-lipid profiles, a group of 28 sedentary but healthy males (mean age 28 years and 7 months) were matched and randomly assigned into a control/non-exercising (n = 15) or an experimental (n = 13) group. To control for variations in lipoprotein-lipid profiles, the present investigation recorded dietary intake and smoking behaviour in an attempt to account for any changes in lipoprotein-lipid profiles over the eight-week period. The experimental group (EG) exercised using DRT for a period of eight weeks and was monitored for changes in lipoprotein-lipid profiles. The control group (CG) took part in no structured exercise throughout the eight-week period. The experimental training programme consisted of nine exercises (dumbbell (D/B) shoulder shrugs, D/B lateral shoulder raises, seated chest press, latissimus dorsi pulldowns, seated pulley rows, biceps curls, triceps extensions, crunchies and unilateral leg press). These exercises were performed at 60% of one repetition maximum (1-RM) and were performed three times per week on non-consecutive days. Serum was analyzed for total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C). In addition to this, the TC: HDL-C and LDL-C: HDL-C ratios were calculated. The Independent t-Test and the Paired t-Test were utilized to determine the significance (at a 95% confidence level (p ¡Ü 0.05)) of the lipoprotein-lipid profile changes from pre- to post-test. These student t-Tests demonstrated no statistically significant changes in TC, TG, LDL-C, HDL-C, TC: HDL-C ratios and LDL-C: HDL-C ratios in the EG. However, the present investigation did demonstrate the following changes: a 0.50% decrease in TC, a 1.74% increase in TG, a 2.95% decrease in LDL-C, a 4.61% increase in HDL-C, a 4.12% decrease in the TC: HDL-C ratio and a 5.96% decrease in the LDL-C: HDL-C ratio. The lack of statistically significant changes in the individual lipoprotein-lipid parameters could not have been affected by diet, cigarettes smoked daily, aerobic fitness and/or body mass, since these parameters did not change significantly from pre- to post-test. Specifically, both the EG and CG demonstrated no statistically significant changes in intake in total calories consumed, carbohydrates, proteins, fats (monounsaturated, polyunsaturated and saturated fatty acids), cholesterol and fibre. Although the present investigation findings suggest that this study¡¯s eight-week combination of dose, workload, number of repetitions and order and number of exercises may not have been sufficient to elicit significant improvements in lipoprotein-lipid parameters in this population of sedentary but healthy males, it is the opinion of the author that DRT should be included with aerobic modes of exercise. DRT should be used in conjunction with aerobic modes of exercise for its additional benefits. Such additional benefits include inter alia: increased strength, increased lean tissue mass, increased maintenance of metabolically active tissue in the elderly and increased muscle control. / Prof. J.M. Loots Mr. L. Lategan

A population density, $u_{n}(x)$, is recursively defined by the formula egin{equation*} u_{n+1}(x)=int K(x-y)Big(1-ig(u_{n}(yig)Big)ig(u_{n} (yig)dy + ig(u_{n}(xig)ig(u_{n}(xig). end{equation*} Here, $K$ is a probability density function, $g(u)$ represents the fraction of the population that does not migrate, and $f$ is a monotonically decreasing function that behaves like the Beverton-Holt function. In this paper, I examine and modify the population genetics model found in cite{LV06} to include the case where a density-dependent fraction of the population does not migrate after the selection process.Using the expanded model, I developed a numerical application to simulate the spreading of a species and estimate the spreading speed of the population. The application is tested under various model conditions which include both density-dependent and density- independent dispersal rates. For the density-dependent case, I analyzed the fixed points of the model and their relationship to whether a given species will spread.

Molecular simulation is applied to understanding the behaviour of alkane liquids with the eventual goal of being able to predict the viscosity of an arbitrary alkane mixture from first principles. Such prediction would have numerous scientific and industrial applications, as alkanes are the largest component of fuels, lubricants, and waxes; furthermore, they form the backbones of a myriad of organic compounds. This dissertation details the creation of a potential, a model for how the atoms and molecules in the simulation interact, based on a systematic approximation of the quantum mechanical potential energy surface using machine learning. This approximation has the advantage of producing forces and energies of nearly quantum mechanical accuracy at a tiny fraction of the usual cost. It enables accurate simulation of the large systems and long timescales required for accurate prediction of properties such as the density and viscosity. The approach is developed and tested on methane, the simplest alkane, and investigations are made into potentials for longer, more complex alkanes. The results show that the approach is promising and should be pursued further to create an accurate machine learning potential for the alkanes. It could even be extended to more complex molecular liquids in the future.

O IPEN-CNEN/SP produz o combustível para suprir o seu reator nuclear de pesquisas IEA-R1. O combustível é montado a partir de placas combustíveis contendo um núcleo do compósito U3Si2-Al. Uma boa homogeneidade na distribuição de urânio no núcleo da placa combustível é essencial, pois garante um bom desempenho sob irradiação. Considerando a baixa potência do reator IEA-R1, atualmente, a distribuição de urânio na placa combustível é avaliada apenas por meio de inspeção visual de radiografias. Contudo, tendo em vista a possibilidade do IPEN fabricar o combustível para o novo Reator Multipropósito Brasileiro (RMB), que terá potência elevada, tornou-se inadiável o desenvolvimento de uma metodologia para determinar quantitativamente a homogeneidade da distribuição de urânio no combustível. Este trabalho apresenta uma metodologia baseada na atenuação de raios X para quantificar a distribuição da concentração de urânio no núcleo da placa combustível, por meio da análise da densidade óptica de radiografias e comparação com padrões. Os resultados demonstraram a não aplicabilidade do método, considerando a especificação atual para as placas combustíveis, devido ao alto valor do erro intrínseco ao método. Contudo, o estudo dos erros envolvidos na metodologia, buscando aumentar a sua exatidão e precisão, pode viabilizar a aplicação do método para qualificar o produto final. / IPEN/CNEN-SP produces the fuel to supply its nuclear research reactor IEA-R1. The fuel is assembled with fuel plates containing an U3Si2-Al composite meat. A good homogeneity in the uranium distribution inside the fuel plate meat is important from the standpoint of irradiation performance. Considering the lower power of reactor IEA-R1, the uranium distribution in the fuel plate has been evaluated only by visual inspection of radiographs. However, with the possibility of IPEN to manufacture the fuel for the new Brazilian Multipurpose Reactor (RMB), with higher power, it urges to develop a methodology to determine quantitatively the uranium distribution into the fuel. This paper presents a methodology based on X-ray attenuation, in order to quantify the uranium concentration distribution in the meat of the fuel plate by using optical densities in radiographs and comparison with standards. The results demonstrated the inapplicability of the method, considering the current specification for the fuel plates due to the high intrinsic error to the method. However, the study of the errors involved in the methodology, seeking to increase their accuracy and precision, can enable the application of the method to qualify the final product.

O IPEN-CNEN/SP produz o combustível para suprir o seu reator nuclear de pesquisas IEA-R1. O combustível é montado a partir de placas combustíveis contendo um núcleo do compósito U3Si2-Al. Uma boa homogeneidade na distribuição de urânio no núcleo da placa combustível é essencial, pois garante um bom desempenho sob irradiação. Considerando a baixa potência do reator IEA-R1, atualmente, a distribuição de urânio na placa combustível é avaliada apenas por meio de inspeção visual de radiografias. Contudo, tendo em vista a possibilidade do IPEN fabricar o combustível para o novo Reator Multipropósito Brasileiro (RMB), que terá potência elevada, tornou-se inadiável o desenvolvimento de uma metodologia para determinar quantitativamente a homogeneidade da distribuição de urânio no combustível. Este trabalho apresenta uma metodologia baseada na atenuação de raios X para quantificar a distribuição da concentração de urânio no núcleo da placa combustível, por meio da análise da densidade óptica de radiografias e comparação com padrões. Os resultados demonstraram a não aplicabilidade do método, considerando a especificação atual para as placas combustíveis, devido ao alto valor do erro intrínseco ao método. Contudo, o estudo dos erros envolvidos na metodologia, buscando aumentar a sua exatidão e precisão, pode viabilizar a aplicação do método para qualificar o produto final. / IPEN/CNEN-SP produces the fuel to supply its nuclear research reactor IEA-R1. The fuel is assembled with fuel plates containing an U3Si2-Al composite meat. A good homogeneity in the uranium distribution inside the fuel plate meat is important from the standpoint of irradiation performance. Considering the lower power of reactor IEA-R1, the uranium distribution in the fuel plate has been evaluated only by visual inspection of radiographs. However, with the possibility of IPEN to manufacture the fuel for the new Brazilian Multipurpose Reactor (RMB), with higher power, it urges to develop a methodology to determine quantitatively the uranium distribution into the fuel. This paper presents a methodology based on X-ray attenuation, in order to quantify the uranium concentration distribution in the meat of the fuel plate by using optical densities in radiographs and comparison with standards. The results demonstrated the inapplicability of the method, considering the current specification for the fuel plates due to the high intrinsic error to the method. However, the study of the errors involved in the methodology, seeking to increase their accuracy and precision, can enable the application of the method to qualify the final product.

The spectral analysis method is an important tool in time series analysis and the spectral density plays a crucial role on the spectral analysis. However, one of limitations of the spectral density is that the spectral density reflects only the covariance structure among several dependence measures in the time series data. To overcome this restriction, we define two spectral densities, the quantile spectral density and the association spectral density. The quantile spectral density can model the pairwise dependence structure and provide identification of nonlinear time series and the association spectral density allows detecting periodicities on different parts of the domain of the time series. We propose the estimators for the quantile spectral density and the association spectral density and derive their sampling properties including asymptotic normality. Furthermore, we use the quantile spectral density to develop a goodness-of-fit tests for time series and explain how this test can be used for comparing the sequential dependence structure of two time series. The asymptotic sampling properties of the test statistic are derived under the null and alternative hypothesis, and a bootstrap procedure is suggested to obtain finite sample approximation. The method is illustrated with simulations and some real data examples. Besides the exploration of the new spectral densities, we consider general quadratic forms of alpha-mixing time series and derive asymptotic normality of these forms under the relatively weak assumptions.

Magnetic resonance imaging (MRI) is an imaging modality that noninvasively measures magnetic fields by selectively exciting the magnetization of protons inside the body. When combined with an understanding of electromagnetic theory, MRI can be used in a novel way to provide a powerful tool for measuring the electromagnetic fields and electrical properties of biological tissues. This thesis presents the analytical, numerical, processing and experimental components of a successful implementation of Low-Frequency Current Density Impedance Imaging (LF-CDII), an impedance imaging method based on MRI measurements. The accuracy, stability and noise tolerance of this technique are examined. The first in-vivo LF-CDII experiment was conducted with a clinical MRI scanner, and the conductivity distribution of the heart of a live piglet was obtained. Both the simulation and experimental results show that LF-CDII can be used as a reliable tool for accurate noninvasive, quantitative imaging of tissue conductivities. This thesis also presents new data processing algorithms, imaging procedures and hardware development for the measurement of electromagnetic fields at radio frequencies, based on Polar Decomposition Radio Frequency Current Density Imaging (PD-RFCDI). The method was tested on both numerical models and experiments on phantoms. The results show that the techniques presented here are able to successfully image current density fields without the strict restrictions on the direction and magnitude of the currents required in previous versions of RFCDI.

Field pea is an important crop in western Canada. The current recommended seeding rate in field pea is 88 plants m-2. As certain pea genotypes have the ability for increased branching, it may be possible for a producer to seed at a lower plant population without reduced yield or to choose a highly branched cultivar to have reduced risk of yield loss under conditions of poor emergence. The objective of this research was to determine how differences in branching among seven representative pea cultivars affected crop yield at different seeding rates, and to determine if branching affected the competitive ability of pea cultivars. In the plant population experiment, seven pea cultivars were seeded at five target plant populations (10, 30, 90, 120, and 150 plant m-2) during 2005 and 2006 at Rosthern and Saskatoon, Saskatchewan. The competition experiment involved eight cultivars being seeded at 50 plants m-2 to measure competitiveness with weeds. Plant emergence, number of branches, light interception, harvest index and grain yield were measured. Growth, seasonal temperature and rainfall were near normal in 2005. Severe terminal drought occurred in 2006 which may have lead to decreased yields. Branching was greatest at low plant densities and decreased as plant density increased. Grain yield increased as plant density increased until it plateaued at 80 100 plants m-2. The response of yield to plant density differed to some extent among cultivars, with CDC Acer and CDC Bronco achieving more of their potential yield at lower densities, while Carrera and Courier required higher densities to reach the same proportion of potential yield. Weed biomass was lowest in plots sown to longer vined cultivars with normal leaf type. Branching habit did not affect the competitiveness of pea cultivars. Potential exists to plant highly branched cultivars to reduce risk of yield loss in situations where low plant emergence might occur.