The micromorphology of Paleoseismic soft sediment deformation structures in glacial deposits from three sample sites in Scotland /

The nature of this research is to investigate paleoseismic deformation of glacial soft sediments from three sampling sites throughout the Scottish Highlands; Arrat's Mills, Meikleour and Glen Roy. The paleoseismic evidence investigated in this research will provide a basis for applying criteria to soft sediment deformation structures, and the trigger mechanisms that create these structures. Micromorphology is the tool used in this to investigate paleoseismic deformation structures in thin section. Thin section analysis, (micromorphology) of glacial sediments from the three sampling sites is used to determine microscale evidence of past earthquakes that can be correlated to modem-day events and possibly lead to a better understanding of the impact of earthquakes throughout a range of sediment types. The significance of the three sampling locations is their proximity to two major active fault zones that cross Scotland. The fault zones are the Highland Boundary Fault and the Great Glen Fault, these two major faults that parallel each other and divide the country in half Sims (1975) used a set of seven criteria that identified soft sediment deformation structures created by a magnitude six earthquake in Cahfomia. Using criteria set forth by Sims (1975), the paleoseismic evidence can be correlated to the magnitude of the deformation structures found in the glacial sediments. This research determined that the microstructures at Arrat's Mill, Meikleour and Glen Roy are consistent with a seismically induced origin. It has also been demonstrated that, even without the presence of macrostructures, the use of micromorphology techniques in detecting such activity within sediments is of immense value.

Selected topics in fast atom bombardment (FAB) mass spectrometry a)specially designed probe tips and ion generation, b)structures of vitamin B6 schiff base complexes

This thesis can be broken down into two sections. Section one is a study . of the ionization mechanisms and the ion source optimization for Fast Atom Bombardment (FAB) ionization. For this study, several specially designed probe tips were created and tested under various experimental conditions. The aIm of this section is to understand the operating characteristics of a FAB IOn source better. The second section involves the study of several Vitamin B6 Schiff Base complexes using both positive and negative ion FAB MS. This section is an exploration of the usefulness of FAB MS as a structure probe for the metalcoordination complexes of Vitamin B6.

Solid state NMR chemical shifts as an alternative to diffraction data in the determination of SIC polytypic structures

Silicon carbide, which has many polytypic modifications of a very simple and very symmetric structure, is an excellent model system for exploring, the relationship between chemical shift, long-range dipolar shielding, and crystal structure in network solids. A simple McConnell equation treatment of bond anisotropy effects in a poly type predicts chemical shifts for silicon and carbon sites which agree well with the experiment, provided that contributions from bonds up to 100 A are included in the calculation. The calculated chemical shifts depend on three factors: the layer stacking sequence, electrical centre of gravity, and the spacings between silicon and carbon layers. The assignment of peaks to lattice sites is proved possible for three polytypes (6H, 15R, and 3C). The fact that the calculated chemical shifts are very sensitive to layer spacings provides us a potential way to detennine and refine a crystal structure. In this work, the layer spacings of 6H SiC have been calculated and are within X-ray standard deviations. Under this premise, the layer spacings of 15R have been detennined. 29Si and 13C single crystal nmr studies of 6H SiC polytype indicate that all silicons and carbons are magnetically anisotropic. The relationship between a magnetic shielding tensor component and layer spacings has been derived. The comparisons between experimental and semi-empirical chemical shielding tensor components indicate that the paramagnetic shielding of silicon should be included in the single crystal chemical shift calculation.

The sedimentology of the Bloomington fan complex: an element of the Oak Ridges Moraine, Southern Ontario

The Oak Ridges Moraine is a major physiographic feature of south-central Ontario, extending from Rice Lake westward to the Niagara Escarpment. While much previous work has largely postulated a relatively simple the origin of the moraine, recent investigations have concentrated on delineating the discernible glacigenic deposits (or landform architectural elements) which comprise the complex mosaic of the Oak Ridges Moraine. This study investigates the sedimentology of the Bloomington fan complex, one of the oldest elements of the Oak Ridges Moraine. The main sediment body of the Bloomington fan complex was deposited during early stages of the formation of the Oak Ridges Moraine, when the ice subdivided, and formed a confined, interlobate lake basin between the northern and southern lobes. Deposition from several conduits produced a fan complex characterized by multiple, laterally overlapping, fan bodies. It appears that the fans were active sequentially in an eastward direction, until the formation of the Bloomington fan complex was dominated by the largest fan fed by a conduit near the northeastern margin of the deposit. Following deposition of the fan complex, the northern and southern ice margins continued to retreat, opening drainage outlets to the west and causing water levels to drop in the lake basin. Glaciofluvial sediment was deposited at this time, cutting into the underlying fan complex. Re-advancing northern ice then closed westerly outlets, and caused water levels to increase, initiating the re-advance of the southern ice. As the southern ice approached the Bloomington fan, it deposited an ice-marginal sediment complex consisting of glacigenic sediment gravity flows, and glaciolacustrine and glaciofluvial sediments exhibiting north and northwesterly paleocurrents. Continued advance of the southern ice, overriding the fan complex, ii produced large-scale glaciotectonic deformation structures, and deposited the Halton Till. The subaqueous fan depositional model that is postulated for the Bloomington fan complex differs from published models due to the complex facies associations produced by the multiple conduit sources of sediment feeding the fans. The fluctuating northern and southern ice margins, which moved across the study area in opposite directions, controlled the water level in the interlobate basin and caused major changes in depositional environments. The influence of these two lobes also caused deposition from two distinct source directions. Finally, erosion, deposition, and deformation of the deposit with the readvance of the southern ice contributed further to the complexity of the Bloomington fan complex.

Evolutionary synthesis of stochastic gene network models using feature-based search spaces

A feature-based fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, when targeting time series data, the fitness function is based on a sum-of-errors involving the values of the fluctuating signal. While this approach is successful in many instances, its performance can deteriorate in the presence of noise. This thesis explores a fitness measure determined from a set of statistical features characterizing the time series' sequence of values, rather than the actual values themselves. Through a series of experiments involving symbolic regression with added noise and gene regulatory network models based on the stochastic 'if-calculus, it is shown to successfully target oscillating and non-oscillating signals. This practical and versatile fitness function offers an alternate approach, worthy of consideration for use in algorithms that evaluate noisy or stochastic behaviour.

Determining rotational direction of rotation structures using prolate shaped grains within till

Micromorphology is used to analyze a wide range of sediments. Many microstructures have, as yet, not been analyzed. Rotation structures are the least understood of microstructures: their origin and development forms the basis of this thesis. Direction of rotational movement helps understand formative deformational and depositional processes. Twenty-eight rotation structures were analyzed through two methods of data extraction: (a) angle of grain rotation measured from Nikon NIS software, and (b) visual analyses of grain orientation, neighbouring grainstacks, lineations, and obstructions. Data indicates antithetic rotation is promoted by lubrication, accounting for 79% of counter-clockwise rotation structures while 21 % had clockwise rotation. Rotation structures are formed due to velocity gradients in sediment. Subglacial sediments are sheared due to overlying ice mass stresses. The grains in the sediment are differentially deformed. Research suggests rotation structures are formed under ductile conditions under low shear, low water content, and grain numbers inducing grain-to-grain interaction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

New Feature at Niagara – Clark Hill Islands

New Feature at Niagara – Clark Hill Islands (5 islands situated in the rapids of the Niagara River). These islands are currently known as Dufferin Islands, 22 ½ cm. x 15 ½ cm, n.d.