Master of Business Administration

thesisEconomic developments in Utah are identified with events peculiar to various periods and these events have controlled, to a considerable degree, the nature ox banking activity in the State. This report attempts to correlate the development and growth of commercial banking in Utah with the economic developments of the State between 1933 and 1945

Utilizing Near-IR Tunable Laser Absorption Spectroscopy to Study Detonation and Combustion Systems

A Hencken burner, RDE, and a detonation tube were studied using a TDM-TDLAS system to measure water absorption features over two spectral regions (7,435 to 7,442 cm-1 and 7,465 to 7,471 cm-1) near 1.3 micrometers. These absorption features were t with simulated spectra using data from the HITEMP database to obtain temperatures and water concentrations for the three systems. Velocity was calculated for the RDE system using the Doppler shift of the spectral lines. To perform the calculations necessary to obtain these results (temperature, concentration, and velocity) a GUI was developed with supporting code. A Hencken burner flame was studied at three different heights above the burner surface, for two different fuels; ethylene (C2H4) and methane (CH4), both at various equivalence ratios. The C2H4 Hencken burner temperatures matched fairly well with the adiabatic temperatures once edge effects were taken into account, however, the CH4 flame did not match as well. The exhaust of the RDE was studied at various equivalence ratios using a hydrogen-air mixture (H2-air). The exhaust temperatures were found to linearly increase with equivalence ratio, from 1,300 K ( 1) to 1,500 K (1.4) and fluctuated with a standard deviation of approximately 50 K. The exhaust velocities of the RDE were found to be independent of equivalence ratio with an average value of 360 m/s and a standard deviation of 50 m/s. A detonation tube was studied at various equivalence ratios and initial pressures, also using an H2- air mixture. Preliminary results are presented for the detonation tube, however, further work in that area is require

Ultrasound Monitoring of Extant Adnexal Masses in the Era of Type 1 and Type 2 Ovarian Cancers: Lessons Learned From Ovarian Cancer Screening Trials

Women that are positive for an ovarian abnormality in a clinical setting can have either a malignancy or a benign tumor with probability favoring the benign alternative. Accelerating the abnormality to surgery will result in a high number of unnecessary procedures that will place cost burdens on the individual and the health delivery system. Surveillance using serial ultrasonography is a reasonable alternative that can be used to discover if changes in the ovarian abnormality will occur that favor either a malignant or benign interpretation. Several ovarian cancer screening trials have had extensive experiences with changes in subclinical ovarian abnormalities in normal women that can define growth, stability or resolution and give some idea of the time frame over which changes occur. The present report examines these experiences and relates them to the current understanding of ovarian cancer ontology, presenting arguments related to the benefits of surveillance

Sparsity driven ultrasound imaging

An image formation framework for ultrasound imaging from synthetic transducer arrays based on sparsity-driven regularization functionals using single-frequency Fourier domain data is proposed. The framework involves the use of a physics-based forward model of the ultrasound observation process, the formulation of image formation as the solution of an associated optimization problem, and the solution of that problem through efficient numerical algorithms. The sparsity-driven, model-based approach estimates a complex-valued reflectivity field and preserves physical features in the scene while suppressing spurious artifacts. It also provides robust reconstructions in the case of sparse and reduced observation apertures. The effectiveness of the proposed imaging strategy is demonstrated using experimental data

The importance of blood rheology in patient-specific computational fluid dynamics simulation of stenotic carotid arteries

The initiation and progression of atherosclerosis, which is the main cause of cardiovascular diseases, correlate with local haemodynamic factors such as wall shear stress (WSS). Numerical simulations such as computational fluid dynamics (CFD) based on medical imaging have been employed to analyse blood flow in different arteries with and without luminal stenosis. Patient-specific CFD models, however, have assumptions on blood rheology. The differences in the calculated haemodynamic factors between different rheological models have not been fully evaluated. In this study, carotid magnetic resonance imaging (MRI) was performed on six patients with different degrees of carotid stenosis and two healthy volunteers. Using the 3D reconstructed carotid geometries and the patient-specific boundary conditions, CFD simulations were performed by applying a Newtonian and four non-Newtonian models (Carreau, Cross, Quemada and Power-law). WSS descriptors and pressure gradient were analysed and compared between the models. The differences in the maximum and the average oscillatory shear index between the Newtonian and the non-Newtonian models were lower than 12.7% and 12%, respectively. The differences in pressure gradient were also within 15%. The differences in the mean time-averaged WSS (TAWSS) between the Newtonian and Cross, Carreau and Power-law models were lower than 6%. In contrast, a higher difference (26%) was found in Quemada. For the low TAWSS, the differences from the Newtonian to the non-Newtonian models were much larger, in the range of 0.4–31% for Carreau, 3–22% for Cross, 5–51% for Quemada and 10–41% for Power-law. The study suggests that the assumption of a Newtonian model is reasonable when the overall flow pattern or the mean values of the WSS descriptors are investigated. However, the non-Newtonian model is necessary when the low TAWSS region is the focus, especially for arteries with severe stenosis

Validation of PigBal model predictions for pig manure production

PigBal is a mass balance model that uses pig diet, digestibility and production data to predict the manure solids and nutrients produced by pig herds. It has been widely used for designing piggery effluent treatment systems and sustainable reuse areas at Australian piggeries. More recently, PigBal has also been used to estimate piggery volatile solids production for assessing greenhouse gas emissions for statutory reporting purposes by government, and for evaluating the energy potential from anaerobic digestion of pig effluent. This paper has compared PigBal predictions of manure total, volatile, and fixed solids, and nitrogen (N), phosphorus (P) and potassium (K), with manure production data generated in a replicated trial, which involved collecting manure from pigs housed in metabolic pens. Predictions of total, volatile, and fixed solids and K in the excreted manure were relatively good (combined diet R2 ≥ 0.79, modelling efficiency (EF) ≥ 0.70) whereas predictions of N and P, were generally less accurate (combined diet R2 0.56 and 0.66, EF 0.19 and -0.22, respectively). PigBal generally under-predicted lower N values while over-predicting higher values, and generally over-predicted manure P production for all diets. The most likely causes for this less accurate performance were ammonium-N volatilisation losses between manure excretion and sample analysis, and the inability of PigBal to account for higher rates of P uptake by pigs fed diets containing phytase. The outcomes of this research suggest that there is a need for further investigation and model development to enhance PigBal's capabilities for more accurately assessing nutrient loads. However, PigBal's satisfactory performance in predicting solids excretion demonstrates that it is suitable for assessing the methane component of greenhouse gas emission and the energy potential from anaerobic digestion of volatile solids in piggery effluent. The apparent overestimation of N and P excretion may result in conservative nutrient application rates to land and the over-prediction of the nitrous oxide component of greenhouse gas emissions. © CSIRO 2016

Carotid Bifurcation With Tandem Stenosis—A Patient-Specific Case Study Combined in vivo Imaging, in vitro Histology and in silico Simulation

A patient-specific carotid bifurcation with tandem stenosis found at both internal carotid artery (ICA) and common carotid artery (CCA) was studied. The in vivo pre-carotid endarterectomy (pre-CEA) multi-spectral magnetic resonance imaging (MRI) were performed and in vitro post-CEA carotid plaque tissue sample was collected. MR imaging data and tissue sample staining histology were used to recognize the plaque components. Further, the computational fluid dynamics (CFD) were performed on four MR-based reconstructed 3D carotid bifurcation models (the patient-specific geometry with tandem stenosis and three presumptive geometries by removing the stenosis part). The flow and shear stress behavior affected by the tandem stenosis was analyzed. From the results of MR segmentation and histology analysis, plaque lipid pool and calcification were found at both ICA and CCA. From the result of CFD simulation, the flow shear stress behavior suggested the tandem stenosis as a more “dangerous” situation than a single-stenosis artery. Besides, the CFD results deduced that the stenosis at the CCA location formed initially and led to the subsequent formation of stenosis at ICA. This study suggests that when planning CEA, CFD simulation on the presumptive models could help clinicians to estimate the blood flow behavior after surgery. Particular attention should be paid to the case of tandem stenosis, as the local hemodynamic environment is more complex and treatment of one stenosis may lead to a variation in the hemodynamic loading on the second plaque, which may result in either a higher risk of plaque rupture or restenosis

Case Report: Evaluating Biomechanical Risk Factors in Carotid Stenosis by Patient-Specific Fluid-Structural Interaction Biomechanical Analysis

Background: Carotid atherosclerosis is one of the main underlying inducements of stroke, which is a leading cause of disability. The morphological feature and biomechanical environment have been found to play important roles in atherosclerotic plaque progression. However, the biomechanics in each patient’s blood vessel is complicated and unique. Method: To analyse the biomechanical risk of the patient-specific carotid stenosis, this study used the fluid-structure interaction (FSI) computational biomechanical model. This model coupled both structural and hemodynamic analysis. Two patients with carotid stenosis planned for carotid endarterectomy were included in this study. The 3D models of carotid bifurcation were reconstructed using our in-house-developed protocol based on multisequence magnetic resonance imaging (MRI) data. Patient-specific flow and pressure waveforms were used in the computational analysis. Multiple biomechanical risk factors including structural and hemodynamic stresses were employed in post-processing to assess the plaque vulnerability. Results: Significant difference in morphological and biomechanical conditions between 2 patients was observed. Patient I had a large lipid core and serve stenosis at carotid bulb. The stenosis changed the cross-sectional shape of the lumen. The blood flow pattern changed consequently and led to a complex biomechanical environment. The FSI results suggested a potential plaque progression may lead to a high-risk plaque, if no proper treatment was performed. The patient II had significant tandem stenosis at both common and internal carotid artery (CCA and ICA). From the results of biomechanical factors, both stenoses had a high potential of plaque progression. Especially for the plaque at ICA branch, the current 2 small plaques might further enlarge and merge as a large vulnerable plaque. The risk of plaque rupture would also increase. Conclusions: Computational biomechanical analysis is a useful tool to provide the biomechanical risk factors to help clinicians assess and predict the patient-specific plaque vulnerability. The FSI computational model coupling the structural and hemodynamic computational analysis, better replicates the in vivo biomechanical condition, which can provide multiple structural and flow-based risk factors to assess plaque vulnerability