ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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Description
Coccidioidomycosis, also known as Valley Fever, is a disease caused by the dimorphic soil-dwelling fungus, Coccidioides sp. Coccidioidomycosis is difficult to diagnose because symptoms are similar to community-acquired pneumonia. Current diagnostic tests rely on antibody responses, but immune responses can be delayed and aberrant, resulting in false negative diagnoses. Unlike serology, detection of coccidioidal proteins or other fungal components in blood could distinguish valley fever from other pulmonary infections and provide a definitive diagnosis. Using mass spectrometry (LC-MS/MS) we examined the plasma peptidome from patients with serologically confirmed coccidioidomycosis. Mass spectra were searched using the protein database from the Coccidioides species, generated and annotated by the Broad Institute. 15 of 20 patients with serologically confirmed coccidioidomycosis demonstrated the presence of a peptide in plasma, "PGLDSKSLACTFSQV" (PGLD). The peptide is derived from an open reading frame from a "conserved hypothetical protein" annotated with 2 exons, and to date, found only in the C. posadasii strain Silviera RMSCC 3488 genomic sequence. In this thesis work, cDNA sequence analysis from polyadenylated RNA confirms the peptide sequence and genomic location of the peptide, but does not indicate that the intron in the gene prediction of C. posadasii strain Silviera RMSCC 3488 is present. A monoclonal antibody generated against the peptide bound to a 16kDa protein in T27K coccidioidal lysate. Detecting components of the fungus plasma could be a useful diagnostic tool, especially when serology does not provide a definitive diagnosis.
ContributorsDuffy, Stacy Leigh (Author) / Lake, Douglas (Thesis advisor) / Magee, Dewey Mitch (Committee member) / Antwi, Kwasi (Committee member) / Arizona State University (Publisher)
Created2013
Description
Researchers across a variety of fields are often interested in determining if data are of a random nature or if they exhibit patterning which may be the result of some alternative and potentially more interesting process. This dissertation explores a family of statistical methods, i.e. space-time interaction tests, designed to detect structure within three-dimensional event data. These tests, widely employed in the fields of spatial epidemiology, criminology, ecology and beyond, are used to identify synergistic interaction across the spatial and temporal dimensions of a series of events. Exploration is needed to better understand these methods and determine how their results may be affected by data quality problems commonly encountered in their implementation; specifically, how inaccuracy and/or uncertainty in the input data analyzed by the methods may impact subsequent results. Additionally, known shortcomings of the methods must be ameliorated. The contributions of this dissertation are twofold: it develops a more complete understanding of how input data quality problems impact the results of a number of global and local tests of space-time interaction and it formulates an improved version of one global test which accounts for the previously identified problem of population shift bias. A series of simulation experiments reveal the global tests of space-time interaction explored here to be dramatically affected by the aforementioned deficiencies in the quality of the input data. It is shown that in some cases, a conservative degree of these common data problems can completely obscure evidence of space-time interaction and in others create it where it does not exist. Conversely, a local metric of space-time interaction examined here demonstrates a surprising robustness in the face of these same deficiencies. This local metric is revealed to be only minimally affected by the inaccuracies and incompleteness introduced in these experiments. Finally, enhancements to one of the global tests are presented which solve the problem of population shift bias associated with the test and better contextualize and visualize its results, thereby enhancing its utility for practitioners.
ContributorsMalizia, Nicholas (Author) / Anselin, Luc (Thesis advisor) / Murray, Alan (Committee member) / Rey, Sergio (Committee member) / Arizona State University (Publisher)
Created2013
Description
Speciation is the fundamental process that has generated the vast diversity of life on earth. The hallmark of speciation is the evolution of barriers to gene flow. These barriers may reduce gene flow either by keeping incipient species from hybridizing at all (pre-zygotic), or by reducing the fitness of hybrids (post-zygotic). To understand the genetic architecture of these barriers and how they evolve, I studied a genus of wasps that exhibits barriers to gene flow that act both pre- and post-zygotically. Nasonia is a genus of four species of parasitoid wasps that can be hybridized in the laboratory. When two of these species, N. vitripennis and N. giraulti are mated, their offspring suffer, depending on the generation and cross examined, up to 80% mortality during larval development due to incompatible genic interactions between their nuclear and mitochondrial genomes. These species also exhibit pre-zygotic isolation, meaning they are more likely to mate with their own species when given the choice. I examined these two species and their hybrids to determine the genetic and physiological bases of both speciation mechanisms and to understand the evolutionary forces leading to them. I present results that indicate that the oxidative phosphorylation (OXPHOS) pathway, an essential pathway that is responsible for mitochondrial energy generation, is impaired in hybrids of these two species. These results indicate that this impairment is due to the unique evolutionary dynamics of the combined nuclear and mitochondrial origin of this pathway. I also present results showing that, as larvae, these hybrids experience retarded growth linked to the previously observed mortality and I explore possible physiological mechanisms for this. Finally, I show that the pre-mating isolation is due to a change in a single pheromone component in N. vitripennis males, that this change is under simple genetic control, and that it evolved neutrally before being co-opted as a species recognition signal. These results are an important addition to our overall understanding of the mechanisms of speciation and showcase Nasonia as an emerging model for the study of the genetics of speciation.
ContributorsGibson, Joshua D (Author) / Gadau, Jürgen (Thesis advisor) / Harrison, Jon (Committee member) / Pratt, Stephen (Committee member) / Verrelli, Brian (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
Description
The objective of this dissertation is to empirically analyze the results of the retail location decision making process and how chain networks evolve given their value platform. It employs one of the largest cross-sectional databases of retailers ever assembled, including 50 US retail chains and over 70,000 store locations. Three closely related articles, which develop new theory explaining location deployment and behaviors of retailers, are presented. The first article, "Regionalism in US Retailing," presents a comprehensive spatial analysis of the domestic patterns of retailers. Geographic Information Systems (GIS) and statistics examine the degree to which the chains are deployed regionally versus nationally. Regional bias is found to be associated with store counts, small market deployment, and the location of the founding store, but not the age of the chain. Chains that started in smaller markets deploy more stores in other small markets and vice versa for chains that started in larger markets. The second article, "The Location Types of US Retailers," is an inductive analysis of the types of locations chosen by the retailers. Retail locations are classified into types using cluster analysis on situational and trade area data at the geographical scale of the individual stores. A total of twelve distinct location types were identified. A second cluster analysis groups together the chains with the most similar location profiles. Retailers within the same retail business often chose similar types of locations and were placed in the same clusters. Retailers generally restrict their deployment to one of three overall strategies including metropolitan, large retail areas, or market size variety. The third article, "Modeling Retail Chain Expansion and Maturity through Wave Analysis: Theory and Application to Walmart and Target," presents a theory of retail chain expansion and maturity whereby retailers expand in waves with alternating periods of faster and slower growth. Walmart diffused gradually from Arkansas and Target grew from the coasts inward. They were similar, however, in that after expanding into an area they reached a point of saturation and opened fewer stores, then moved on to other areas, only to revisit the earlier areas for new stores.
ContributorsJoseph, Lawrence (Author) / Kuby, Michael (Thesis advisor) / Matthews, Richard (Committee member) / Ó Huallacháin, Breandán (Committee member) / Kumar, Ajith (Committee member) / Arizona State University (Publisher)
Created2013
Description
Modified and artificial water sources can be used as a management tool for game and non-game wildlife species. State, federal, and private agencies allocate significant resources to install and maintain artificial water sources (AWS) annually. Capture mark recapture methods were used to sample small mammal communities in the vicinity of five AWS and five paired control sites (treatments) in the surrounding Sonoran desert from October 2011 to May 2012. I measured plant species richness, density, and percent cover in the spring of 2012. A Multi-response Permutation Procedure was used to identify differences in small mammal community abundance, biomass, and species richness by season and treatment. I used Principle Component Analysis to reduce 11 habitat characteristics to five habitat factors. I related rodent occurrence to habitat characteristics using multiple and logistic regression. A total of 370 individual mammals representing three genera and eight species of rodents were captured across 4800 trap nights. Desert pocket mouse (Chaetodipus penicillatus) was the most common species in both seasons and treatments. Whereas rodent community abundance, biomass, and richness were similar between seasons, community variables of AWS were greater than CS. Rodent diversity was similar between treatments. Desert pocket mouse abundance and biomass were twice as high at AWS when compared to controls. Biomass of white-throated woodrat (Neotoma albigula) was five times greater at AWS. Habitat characteristics were similar between treatments. Neither presence of water nor distance to water explained substantial habitat variation. Occurrence of rodent species was associated with habitat characteristics. Desert rodent communities are adapted for arid environments (i.e. Heteromyids) and are not dependent on "free water". Higher abundances of desert pocket mouse at AWS were most likely related to increased disturbance and debris and not the presence of water. The results of this study and previous studies suggest that more investigation is needed and that short term studies may not be able to detect interactions (if any) between AWS and desert small mammal communities.
ContributorsSwitalski, Aaron (Author) / Bateman, Heather L (Thesis advisor) / Miller, William (Committee member) / Alford, Eddie (Committee member) / Arizona State University (Publisher)
Created2013
Description
The dynamics of urban water use are characterized by spatial and temporal variability that is influenced by associated factors at different scales. Thus it is important to capture the relationship between urban water use and its determinants in a spatio-temporal framework in order to enhance understanding and management of urban water demand. This dissertation aims to contribute to understanding the spatio-temporal relationships between single-family residential (SFR) water use and its determinants in a desert city. The dissertation has three distinct papers to support this goal. In the first paper, I demonstrate that aggregated scale data can be reliably used to study the relationship between SFR water use and its determinants without leading to significant ecological fallacy. The usability of aggregated scale data facilitates scientific inquiry about SFR water use with more available aggregated scale data. The second paper advances understanding of the relationship between SFR water use and its associated factors by accounting for the spatial and temporal dependence in a panel data setting. The third paper of this dissertation studies the historical contingency, spatial heterogeneity, and spatial connectivity in the relationship of SFR water use and its determinants by comparing three different regression models. This dissertation demonstrates the importance and necessity of incorporating spatio-temporal components, such as scale, dependence, and heterogeneity, into SFR water use research. Spatial statistical models should be used to understand the effects of associated factors on water use and test the effectiveness of certain management policies since spatial effects probably will significantly influence the estimates if only non-spatial statistical models are used. Urban water demand management should pay attention to the spatial heterogeneity in predicting the future water demand to achieve more accurate estimates, and spatial statistical models provide a promising method to do this job.
ContributorsOuyang, Yun (Author) / Wentz, Elizabeth (Thesis advisor) / Ruddell, Benjamin (Thesis advisor) / Harlan, Sharon (Committee member) / Janssen, Marcus (Committee member) / Arizona State University (Publisher)
Created2013
Description
The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in changing certain design variables while achieving preset criteria such as energy performance, life cycle cost, environmental impacts etc. This requirement can be met by a decision support framework based on near-optimal "satisficing" as opposed to purely optimal decision making techniques. Currently, such a comprehensive design framework is lacking, which is the basis for undertaking this research. The primary objective of this research is to facilitate a complementary relationship between designers and computers for Multi-Criterion Decision Making (MCDM) during high performance building design. It is based on the application of Monte Carlo approaches to create a database of solutions using deterministic whole building energy simulations, along with data mining methods to rank variable importance and reduce the multi-dimensionality of the problem. A novel interactive visualization approach is then proposed which uses regression based models to create dynamic interplays of how varying these important variables affect the multiple criteria, while providing a visual range or band of variation of the different design parameters. The MCDM process has been incorporated into an alternative methodology for high performance building design referred to as Visual Analytics based Decision Support Methodology [VADSM]. VADSM is envisioned to be most useful during the conceptual and early design performance modeling stages by providing a set of potential solutions that can be analyzed further for final design selection. The proposed methodology can be used for new building design synthesis as well as evaluation of retrofits and operational deficiencies in existing buildings.
ContributorsDutta, Ranojoy (Author) / Reddy, T Agami (Thesis advisor) / Runger, George C. (Committee member) / Addison, Marlin S. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Microelectronic industry is continuously moving in a trend requiring smaller and smaller devices and reduced form factors with time, resulting in new challenges. Reduction in device and interconnect solder bump sizes has led to increased current density in these small solders. Higher level of electromigration occurring due to increased current density is of great concern affecting the reliability of the entire microelectronics systems. This paper reviews electromigration in Pb- free solders, focusing specifically on Sn0.7wt.% Cu solder joints. Effect of texture, grain orientation, and grain-boundary misorientation angle on electromigration and intermetallic compound (IMC) formation is studied through EBSD analysis performed on actual C4 bumps.
ContributorsLara, Leticia (Author) / Tasooji, Amaneh (Thesis advisor) / Lee, Kyuoh (Committee member) / Krause, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Magnetic Resonance Imaging using spiral trajectories has many advantages in speed, efficiency in data-acquistion and robustness to motion and flow related artifacts. The increase in sampling speed, however, requires high performance of the gradient system. Hardware inaccuracies from system delays and eddy currents can cause spatial and temporal distortions in the encoding gradient waveforms. This causes sampling discrepancies between the actual and the ideal k-space trajectory. Reconstruction assuming an ideal trajectory can result in shading and blurring artifacts in spiral images. Current methods to estimate such hardware errors require many modifications to the pulse sequence, phantom measurements or specialized hardware. This work presents a new method to estimate time-varying system delays for spiral-based trajectories. It requires a minor modification of a conventional stack-of-spirals sequence and analyzes data collected on three orthogonal cylinders. The method is fast, robust to off-resonance effects, requires no phantom measurements or specialized hardware and estimate variable system delays for the three gradient channels over the data-sampling period. The initial results are presented for acquired phantom and in-vivo data, which show a substantial reduction in the artifacts and improvement in the image quality.
ContributorsBhavsar, Payal (Author) / Pipe, James G (Thesis advisor) / Frakes, David (Committee member) / Kodibagkar, Vikram (Committee member) / Arizona State University (Publisher)
Created2013
Description
Vehicle type choice is a significant determinant of fuel consumption and energy sustainability; larger, heavier vehicles consume more fuel, and expel twice as many pollutants, than their smaller, lighter counterparts. Over the course of the past few decades, vehicle type choice has seen a vast shift, due to many households making more trips in larger vehicles with lower fuel economy. During the 1990s, SUVs were the fastest growing segment of the automotive industry, comprising 7% of the total light vehicle market in 1990, and 25% in 2005. More recently, due to rising oil prices, greater awareness to environmental sensitivity, the desire to reduce dependence on foreign oil, and the availability of new vehicle technologies, many households are considering the use of newer vehicles with better fuel economy, such as hybrids and electric vehicles, over the use of the SUV or low fuel economy vehicles they may already own. The goal of this research is to examine how vehicle miles traveled, fuel consumption and emissions may be reduced through shifts in vehicle type choice behavior. Using the 2009 National Household Travel Survey data it is possible to develop a model to estimate household travel demand and total fuel consumption. If given a vehicle choice shift scenario, using the model it would be possible to calculate the potential fuel consumption savings that would result from such a shift. In this way, it is possible to estimate fuel consumption reductions that would take place under a wide variety of scenarios.
ContributorsChristian, Keith (Author) / Pendyala, Ram M. (Thesis advisor) / Chester, Mikhail (Committee member) / Kaloush, Kamil (Committee member) / Ahn, Soyoung (Committee member) / Arizona State University (Publisher)
Created2013