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In an effort to address the lack of literature in on-campus active travel, this study aims to investigate the following primary questions:<br/>• What are the modes that students use to travel on campus?<br/>• What are the motivations that underlie the mode choice of students on campus?<br/>My first stage of research

In an effort to address the lack of literature in on-campus active travel, this study aims to investigate the following primary questions:<br/>• What are the modes that students use to travel on campus?<br/>• What are the motivations that underlie the mode choice of students on campus?<br/>My first stage of research involved a series of qualitative investigations. I held one-on-one virtual interviews with students in which I asked them questions about the mode they use and why they feel that their chosen mode works best for them. These interviews served two functions. First, they provided me with insight into the various motivations underlying student mode choice. Second, they provided me with an indication of what explanatory variables should be included in a model of mode choice on campus.<br/>The first half of the research project informed a quantitative survey that was released via the Honors Digest to attract student respondents. Data was gathered on travel behavior as well as relevant explanatory variables.<br/>My analysis involved developing a logit model to predict student mode choice on campus and presenting the model estimation in conjunction with a discussion of student travel motivations based on the qualitative interviews. I use this information to make a recommendation on how campus infrastructure could be modified to better support the needs of the student population.

ContributorsMirtich, Laura Christine (Author) / Salon, Deborah (Thesis director) / Fang, Kevin (Committee member) / School of Public Affairs (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems

This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
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Description
While exercising mammalian muscle increasingly relies on carbohydrates for fuel as aerobic exercise intensity rises above the moderate range, flying birds are extraordinary endurance athletes and fuel flight, a moderate-high intensity exercise, almost exclusively with lipid. In addition, Aves have long lifespans compared to weight-matched mammals. As skeletal muscle mitochondria

While exercising mammalian muscle increasingly relies on carbohydrates for fuel as aerobic exercise intensity rises above the moderate range, flying birds are extraordinary endurance athletes and fuel flight, a moderate-high intensity exercise, almost exclusively with lipid. In addition, Aves have long lifespans compared to weight-matched mammals. As skeletal muscle mitochondria account for the majority of oxygen consumption during aerobic exercise, the primary goal was to investigate differences in isolated muscle mitochondria between these species and to examine to what extent factors intrinsic to mitochondria may account for the behavior observed in the intact tissue and whole organism. First, maximal enzyme activities were assessed in sparrow and rat mitochondria. Citrate synthase and aspartate aminotransferase activity were higher in sparrow compared to rat mitochondria, while glutamate dehydrogenase activity was lower. Sparrow mitochondrial NAD-linked isocitrate dehydrogenase activity was dependent on phosphate, unlike the mammalian enzyme. Next, the rate of oxygen consumption (JO), electron transport chain (ETC) activity, and reactive oxygen species (ROS) production were assessed in intact mitochondria. Maximal rates of fat oxidation were lower than for carbohydrate in rat but not sparrow mitochondria. ETC activity was higher in sparrows, but no differences were found in ROS production between species. Finally, fuel selection and control of respiration at three rates between rest and maximum were assessed. Mitochondrial fuel oxidation and selection mirrored that of the whole body; in rat mitochondria the reliance on carbohydrate increased as the rate of oxygen consumption increased, whereas fat dominated under all conditions in the sparrow. These data indicate fuel selection, at least in part, can be modulated at the level of the mitochondrial matrix when multiple substrates are present at saturating levels. As an increase in matrix oxidation-reduction potential has been linked to a suppression of fat oxidation and high ROS production, the high ETC activity relative to dehydrogenase activity in avian compared to mammalian mitochondria may result in lower matrix oxidation-reduction potential, allowing fatty acid oxidation to proceed while also resulting in low ROS production in vivo.
ContributorsKuzmiak, Sarah (Author) / Willis, Wayne T (Thesis advisor) / Mandarino, Lawrence (Committee member) / Sweazea, Karen (Committee member) / Harrison, Jon (Committee member) / Gadau, Juergen (Committee member) / Arizona State University (Publisher)
Created2012
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Description
This dissertation is intended to tie together a body of work which utilizes a variety of methods to study applied mathematical models involving heterogeneity often omitted with classical modeling techniques. I posit three cogent classifications of heterogeneity: physiological, behavioral, and local (specifically connectivity in this work). I consider physiological heterogeneity

This dissertation is intended to tie together a body of work which utilizes a variety of methods to study applied mathematical models involving heterogeneity often omitted with classical modeling techniques. I posit three cogent classifications of heterogeneity: physiological, behavioral, and local (specifically connectivity in this work). I consider physiological heterogeneity using the method of transport equations to study heterogeneous susceptibility to diseases in open populations (those with births and deaths). I then present three separate models of behavioral heterogeneity. An SIS/SAS model of gonorrhea transmission in a population of highly active men-who-have-sex-with-men (MSM) is presented to study the impact of safe behavior (prevention and self-awareness) on the prevalence of this endemic disease. Behavior is modeled in this examples via static parameters describing consistent condom use and frequency of STD testing. In an example of behavioral heterogeneity, in the absence of underlying dynamics, I present a generalization to ``test theory without an answer key" (also known as cultural consensus modeling or CCM). CCM is commonly used to study the distribution of cultural knowledge within a population. The generalized framework presented allows for selecting the best model among various extensions of CCM: multiple subcultures, estimating the degree to which individuals guess yes, and making competence homogenous in the population. This permits model selection based on the principle of information criteria. The third behaviorally heterogeneous model studies adaptive behavioral response based on epidemiological-economic theory within an $SIR$ epidemic setting. Theorems used to analyze the stability of such models with a generalized, non-linear incidence structure are adapted and applied to the case of standard incidence and adaptive incidence. As an example of study in spatial heterogeneity I provide an explicit solution to a generalization of the continuous time approximation of the Albert-Barabasi scale-free network algorithm. The solution is found by recursively solving the differential equations via integrating factors, identifying a pattern for the coefficients and then proving this observed pattern is consistent using induction. An application to disease dynamics on such evolving structures is then studied.
ContributorsMorin, Benjamin (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Hiebeler, David (Thesis advisor) / Hruschka, Daniel (Committee member) / Suslov, Sergei (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative

Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative frequency in the population. The behavioral factors that underpin contact rates are not generally addressed. There is, however, an emerging a class of models that addresses the feedbacks between infectious disease dynamics and the behavioral decisions driving host contact. Referred to as “economic epidemiology” or “epidemiological economics,” the approach explores the determinants of decisions about the number and type of contacts made by individuals, using insights and methods from economics. We show how the approach has the potential both to improve predictions of the course of infectious disease, and to support development of novel approaches to infectious disease management.
Created2015-12-01
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Description
Preserving a system’s viability in the presence of diversity erosion is critical if the goal is to sustainably support biodiversity. Reduction in population heterogeneity, whether inter- or intraspecies, may increase population fragility, either decreasing its ability to adapt effectively to environmental changes or facilitating the survival and success of ordinarily

Preserving a system’s viability in the presence of diversity erosion is critical if the goal is to sustainably support biodiversity. Reduction in population heterogeneity, whether inter- or intraspecies, may increase population fragility, either decreasing its ability to adapt effectively to environmental changes or facilitating the survival and success of ordinarily rare phenotypes. The latter may result in over-representation of individuals who may participate in resource utilization patterns that can lead to over-exploitation, exhaustion, and, ultimately, collapse of both the resource and the population that depends on it. Here, we aim to identify regimes that can signal whether a consumer–resource system is capable of supporting viable degrees of heterogeneity. The framework used here is an expansion of a previously introduced consumer–resource type system of a population of individuals classified by their resource consumption. Application of the Reduction Theorem to the system enables us to evaluate the health of the system through tracking both the mean value of the parameter of resource (over)consumption, and the population variance, as both change over time. The article concludes with a discussion that highlights applicability of the proposed system to investigation of systems that are affected by particularly devastating overly adapted populations, namely cancerous cells. Potential intervention approaches for system management are discussed in the context of cancer therapies.
Created2015-02-01
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Description
While non-invasive breast cancer treatments may be considered less costly in the short-term, over the course of a lifetime, a more aggressive treatment can be overall less costly, especially with recurrence cases; however, these more aggressive treatments are not necessarily covered by insurance and are difficult to discuss in the

While non-invasive breast cancer treatments may be considered less costly in the short-term, over the course of a lifetime, a more aggressive treatment can be overall less costly, especially with recurrence cases; however, these more aggressive treatments are not necessarily covered by insurance and are difficult to discuss in the short amount of time in physician consultations. This analysis studied data from 982 women diagnosed with breast cancer over a five-year period to evaluate monetary costs associated with treatment options and incorporated five in-depth interviews to understand experiences and non-monetary costs. Data showed the most expensive option was a unilateral mastectomy with radiation therapy and the least costly option was breast conserving surgery. Interviews determined each woman evaluated the monetary costs with each treatment but most heavily focused on personal values, biases and recommended opinions when deciding on a treatment. The use of prompt sheets before physician appointments and consultations, along with the addition of financial counselor meeting with each patient can improve patient satisfaction and alleviate stress by simplifying a woman's choice in deciding a treatment. In addition, increased insurance coverage to include every treatment chosen by women (rather than on a case-by-case basis), specifically contralateral prophylactic mastectomy and additional screening options, could decrease long term costs \u2014 both monetarily and in quality of life for patients.
ContributorsOsumi, Alana (Author) / LaRosa, Julia (Thesis director) / Sivanantham, Jai (Committee member) / Barrett, The Honors College (Contributor) / W.P. Carey School of Business (Contributor)
Created2018-12
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Description
In 2016, in the United States alone, the cosmetics industry made an estimated 62.46 billion dollars in revenue (Revenue of the Cosmetic Industry in the U.S. 2002-2016 | Forecast). With a consistent increase in sales in the last several years, the industry has reached continued success even during times of

In 2016, in the United States alone, the cosmetics industry made an estimated 62.46 billion dollars in revenue (Revenue of the Cosmetic Industry in the U.S. 2002-2016 | Forecast). With a consistent increase in sales in the last several years, the industry has reached continued success even during times of hardship, such as the Great Recession of 2008. The use of Corporate Social Responsibility (CSR), external campaigns, and thoughtful packaging and ingredients resonates with targeted consumers. This has served as an effective strategy to maintain growth in the industry. Cosmetic companies promote their brand image using these sustainability tactics, but there seems to be a lack of transparency in this unregulated industry. The purpose of this thesis is to determine if the cosmetics industry is a good steward of the sustainability movement. Important terms and concepts relating to the industry will be discussed, then an analysis of sustainability focused cosmetic brands will be provided, which highlights the extent to which these brands engage in activities that promote sustainability. This is followed by an application of findings to a company that could benefit from using such practices. Overall, the analysis of the different brands proved to be shocking and disappointing. This is due to the sheer amount that scored very poorly based on the sustainability criteria developed. The cosmetics industry is too inconsistent and too unregulated to truly act as a good steward for sustainability. Though some companies in the industry succeed, these accomplishments are not consistent across all cosmetic companies. Hence, the cosmetics industry as a good steward for sustainability can only be as strong as its weakest link.
ContributorsMamus, Sydney Wasescha (Author) / Ostrom, Amy (Thesis director) / Kristofferson, Kirk (Committee member) / Department of Marketing (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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This report was commissioned to provide an analysis and evaluation of consumer perceptions and branding as it relates to the political and social climate in America. To be able to do this, the paper analyzes shifts in the external environment as well as researching case studies and online consumer perception

This report was commissioned to provide an analysis and evaluation of consumer perceptions and branding as it relates to the political and social climate in America. To be able to do this, the paper analyzes shifts in the external environment as well as researching case studies and online consumer perception surveys. Overall, this paper aims to examine the distributed survey and attempt to correlate and identify how branding, consumer perceptions, and social and political issues all can work and affect one another. Through the administration of this survey, we were able to formulate a conclusion that points towards the importance of brands actively adhering to changing consumer preferences, ideals, and expectations.
ContributorsClark, Sydney (Co-author) / Loera, Carolina (Co-author) / Montoya, Detra (Thesis director) / Samper, Adriana (Committee member) / W.P. Carey School of Business (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
The use of generalized linear models in loss reserving is not new; many statistical models have been developed to fit the loss data gathered by various insurance companies. The most popular models belong to what Glen Barnett and Ben Zehnwirth in "Best Estimates for Reserves" call the "extended link ratio

The use of generalized linear models in loss reserving is not new; many statistical models have been developed to fit the loss data gathered by various insurance companies. The most popular models belong to what Glen Barnett and Ben Zehnwirth in "Best Estimates for Reserves" call the "extended link ratio family (ELRF)," as they are developed from the chain ladder algorithm used by actuaries to estimate unpaid claims. Although these models are intuitive and easy to implement, they are nevertheless flawed because many of the assumptions behind the models do not hold true when fitted with real-world data. Even more problematically, the ELRF cannot account for environmental changes like inflation which are often observed in the status quo. Barnett and Zehnwirth conclude that a new set of models that contain parameters for not only accident year and development period trends but also payment year trends would be a more accurate predictor of loss development. This research applies the paper's ideas to data gathered by Company XYZ. The data was fitted with an adapted version of Barnett and Zehnwirth's new model in R, and a trend selection algorithm was developed to accompany the regression code. The final forecasts were compared to Company XYZ's booked reserves to evaluate the predictive power of the model.
ContributorsZhang, Zhihan Jennifer (Author) / Milovanovic, Jelena (Thesis director) / Tomita, Melissa (Committee member) / Zicarelli, John (Committee member) / W.P. Carey School of Business (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05