published_or_final_version / Mathematics / Master / Master of Philosophy

published_or_final_version / Physics / Master / Master of Philosophy

No description available.

This study focussed on the reduced platen compression (RPC) testing of the cancellous bone of the proximal tibia. The objective of this study was to improve the current testing methods with an emphasis on the location of the RPC specimens, and to correlate the mechanical properties of the rodent cancellous bone with the various density measures. Analytical studies were made to assess the effect of the size and shape of the platen based on the values from mechanical testing of the cancellous bone. RPC specimens are made from transverse slices of the proximal tibia metaphysis. Specimen location was determined using planar radiograph method at a distance of 1.75 mm distal to the growth plate. The distance from the top of the proximal tibia to the line at 1.75 mm distal to the growth plate was measured and this distance is termed as the first cut distance. Specimen thickness of 2 mm was then cut for the RPC test. Endocortical method was followed to determine the platen sizing for RPC testing. The cancellous bone was then tested in compression to failure. Correlations were performed between the mechanical properties of the cancellous bone and the density measures from pQCT and radiographic techniques. SigmaStat and TableCurve 2D were used to perform the correlations and estimate the P value for the correlation. Linear and power law fits were made for all the correlations. Based on this study, several improvements to the reduced platen compression test were recommended. An improved specimen location method was developed. However, it requires a corrective distance to account for the tissue that cannot be identified in the radiographic analysis. A new method for estimating the density of the cancellous bone that is directly tested by the platen was developed. Correlations between the density of the cancellous bone and the mechanical properties show that, there is a strong correlation between ultimate stress and aluminum layer intensity. Elastic modulus correlates best with the last batch tested in this study. Recommendations for future study include advanced technology like finite element analysis and custom shaped platens to enhance RPC testing.

This thesis studies the benefits and costs of urban living. Chapter 1 is a theoretical and empirical analysis of the benefits of urban density for consumers, while Chapter 2 proposes a model of how cities enhance the incentives for knowledge diffusion. Chapter 3 investigates the costs of congestion and the determinants of car travel speed across US cities. In Chapter 1, I study the consumption value of urban density by combining Google’s local business data with microgeographic travel data. I show that increased density enables consumers to both realize welfare gains from variety and save time through shorter trips. I estimate the gains from density in the restaurant industry, identifying willingness to pay for access to a slightly preferred location from the extra travel costs incurred to reach it. The results reveal large but very localized gains from density. Increasing the density of destinations generates little reduction in trip times, so most of these gains from density are gains from variety, not savings on travel time. In Chapter 2, I propose a new micro-foundation for knowledge spillovers. I model a city in which uncompensated knowledge transfers to entrepreneurs are bids by experts in auctions for jobs. The model derives from the key ideas about how knowledge differs from other inputs of production, namely that knowledge must be possessed for its value to be assessed, and that knowledge is freely reproducible. Agglomeration economies result from growth in the number of meetings between experts and entrepreneurs, and from heightened competition for jobs among experts. In Chapter 3, written jointly with Gilles Duranton and Matt Turner, we investigate the determinants of driving speed in large US cities. We first estimate city level supply functions for travel in an econometric framework where both the supply and demand for travel are explicit. These estimations allow us to calculate a city level index of driving speed. Our investigation of the determinants of speed provides the foundations for a welfare analysis. This analysis suggests large gains in speed if slow cities can emulate fast cities, and sizable deadweight losses from congestion.

This thesis studies the benefits and costs of urban living. Chapter 1 is a theoretical and empirical analysis of the benefits of urban density for consumers, while Chapter 2 proposes a model of how cities enhance the incentives for knowledge diffusion. Chapter 3 investigates the costs of congestion and the determinants of car travel speed across US cities. In Chapter 1, I study the consumption value of urban density by combining Google’s local business data with microgeographic travel data. I show that increased density enables consumers to both realize welfare gains from variety and save time through shorter trips. I estimate the gains from density in the restaurant industry, identifying willingness to pay for access to a slightly preferred location from the extra travel costs incurred to reach it. The results reveal large but very localized gains from density. Increasing the density of destinations generates little reduction in trip times, so most of these gains from density are gains from variety, not savings on travel time. In Chapter 2, I propose a new micro-foundation for knowledge spillovers. I model a city in which uncompensated knowledge transfers to entrepreneurs are bids by experts in auctions for jobs. The model derives from the key ideas about how knowledge differs from other inputs of production, namely that knowledge must be possessed for its value to be assessed, and that knowledge is freely reproducible. Agglomeration economies result from growth in the number of meetings between experts and entrepreneurs, and from heightened competition for jobs among experts. In Chapter 3, written jointly with Gilles Duranton and Matt Turner, we investigate the determinants of driving speed in large US cities. We first estimate city level supply functions for travel in an econometric framework where both the supply and demand for travel are explicit. These estimations allow us to calculate a city level index of driving speed. Our investigation of the determinants of speed provides the foundations for a welfare analysis. This analysis suggests large gains in speed if slow cities can emulate fast cities, and sizable deadweight losses from congestion.

No description available.

This research thesis is focussed on the development of a novel low density explosive composition whose main application is wall control in open pit mining. The product has, however, the potential to be used in a variety of applications and rock conditions where customization of the explosive’s energy output is required. Experimental observations on the novel low density explosive showed that the product is capable of initiating and sustaining stable detonations at densities as low as 0.10 g/cm3. Given the extreme low densities at which the novel product maintains its detonating characteristics, it will be appropriate to treat it as a reactive bulking agent, hence its name: Low Density Reactive Agent or LDRA for short. When mixed with standard ANFO prills, the reactive nature of the LDRA ensures a detonable mixture regardless of the final dilution sought or the degree of segregation eventually produced during mixing and loading. If operational constraints are such that a lower energy is required, the LDRA can then be used on a stand‐alone basis, without mixing it with other explosive compositions, such as ANFO or emulsions. The detonation characteristics of the LDRA at a target density of 0.15 g/cm3 were evaluated, with particular effort placed on measuring the detonation and explosion pressures, parameters having the greatest influence on damage. The effects of diameter, confinement and primer on LDRA performance were evaluated through velocity of detonation (VOD) measurements. In addition, VOD experiments were conducted in the LDRA to evaluate the stability of propagation in longer columns, the behaviour in a decking configuration and the ability to initiate and be initiated by a column of ANFO. The low pressure regimes characterizing the LDRA provided the opportunity to investigate the full pressure history of the detonation gases by designing experiments of a non‐destructive nature that allowed the repetition of tests under different loading scenarios. Following the characterization stage, the opportunity to test the LDRA as a damage control tool under a true operational scenario arose at the Chuquicamata Mine, in northern Chile. The project provided important input as to the feasibility of manufacturing the LDRA at a semi‐industrial scale and to evaluate the performance of the product in the large diameter blastholes used at the mine / Thesis (Ph.D, Mining Engineering) -- Queen's University, 2007-11-09 12:19:49.747

PET (positron emission tomography) scans are still in the experimental phase, as one of the newest breast cancer diagnostic techniques. It is becoming the new standard in neurology, oncology and cardiology. PET, like other nuclear medicine diagnostic and treatment techniques, involves the use of radiation. Because of the negative impact of radioactivity to our bodies the radiation doses in PET should be small. The existing computing algorithms for calculating PET images can be divided into two broad categories: analytical and iterative methods. In the analytical approach the relation between the picture and its projections is expressed by a set of integral equations which are then solved analytically. The Fourier backprojection (FBP) algorithm is a numerical approximation of this analytical solution. Iterative approaches use deterministic (ART = Algebraic Reconstructed Technique) or stochastic (EM = Expectation Maximization) algorithms. My proposed kernel density estimation (KDE) algorithm also falls also into the category of iterative methods. However, in this approach each coincidence event is considered individually. The estimate location of the annihilation event that caused each coincidence event is based on the previously assigned location of events processed earlier. To accomplish this, we construct a probability distribution along each coincidence line. This is generated from previous annihilation points by density estimation. It is shown that this density estimation approach to PET can reconstruct an image of an existing tumor using significantly less data than the standard CT algorithms, such as FBP. Therefore, it might be very promising technique allowing reduced radiation dose for patients, while retaining or improving image quality.

No description available.