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The goal of this project was to design and create a genetic construct that would allow for <br/>tumor growth to be induced in the center of the wing imaginal disc of Drosophila larvae, the <br/>R85E08 domain, using a heat shock. The resulting transgene would be combined with other <br/>transgenes in

The goal of this project was to design and create a genetic construct that would allow for <br/>tumor growth to be induced in the center of the wing imaginal disc of Drosophila larvae, the <br/>R85E08 domain, using a heat shock. The resulting transgene would be combined with other <br/>transgenes in a single fly that would allow for simultaneous expression of the oncogene and, in <br/>the surrounding cells, other genes of interest. This system would help establish Drosophila as a <br/>more versatile and reliable model organism for cancer research. Furthermore, pilot studies were <br/>performed, using elements of the final proposed system, to determine if tumor growth is possible <br/>in the center of the disc, which oncogene produces the best results, and if oncogene expression <br/>induced later in development causes tumor growth. Three different candidate genes were <br/>investigated: RasV12, PvrACT, and Avli.

ContributorsSt Peter, John Daniel (Author) / Harris, Rob (Thesis director) / Varsani, Arvind (Committee member) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description
The border policies of the United States and Mexico that have evolved over the previous decades have pushed illegal immigration and drug smuggling to remote and often public lands. Valuable natural resources and tourist sites suffer an inordinate level of environmental impacts as a result of activities, from new roads

The border policies of the United States and Mexico that have evolved over the previous decades have pushed illegal immigration and drug smuggling to remote and often public lands. Valuable natural resources and tourist sites suffer an inordinate level of environmental impacts as a result of activities, from new roads and trash to cut fence lines and abandoned vehicles. Public land managers struggle to characterize impacts and plan for effective landscape level rehabilitation projects that are the most cost effective and environmentally beneficial for a region given resource limitations. A decision support tool is developed to facilitate public land management: Borderlands Environmental Rehabilitation Spatial Decision Support System (BERSDSS). The utility of the system is demonstrated using a case study of the Sonoran Desert National Monument, Arizona.
ContributorsFisher, Sharisse (Author) / Murray, Alan T. (Thesis advisor) / Wentz, Elizabeth (Committee member) / Rey, Sergio (Committee member) / Arizona State University (Publisher)
Created2013
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Description
There exist many facets of error and uncertainty in digital spatial information. As error or uncertainty will not likely ever be completely eliminated, a better understanding of its impacts is necessary. Spatial analytical approaches, in particular, must somehow address data quality issues. This can range from evaluating impacts of potential

There exist many facets of error and uncertainty in digital spatial information. As error or uncertainty will not likely ever be completely eliminated, a better understanding of its impacts is necessary. Spatial analytical approaches, in particular, must somehow address data quality issues. This can range from evaluating impacts of potential data uncertainty in planning processes that make use of methods to devising methods that explicitly account for error/uncertainty. To date, little has been done to structure methods accounting for error. This research focuses on developing methods to address geographic data uncertainty in spatial optimization. An integrated approach that characterizes uncertainty impacts by constructing and solving a new multi-objective model that explicitly incorporates facets of data uncertainty is developed. Empirical findings illustrate that the proposed approaches can be applied to evaluate the impacts of data uncertainty with statistical confidence, which moves beyond popular practices of simulating errors in data. Spatial uncertainty impacts are evaluated in two contexts: harvest scheduling and sex offender residency. Owing to the integration of spatial uncertainty, the detailed multi-objective models are more complex and computationally challenging to solve. As a result, a new multi-objective evolutionary algorithm is developed to address the computational challenges posed. The proposed algorithm incorporates problem-specific spatial knowledge to significantly enhance the capability of the evolutionary algorithm for solving the model.  
ContributorsWei, Ran (Author) / Murray, Alan T. (Thesis advisor) / Anselin, Luc (Committee member) / Rey, Segio J (Committee member) / Mack, Elizabeth A. (Committee member) / Arizona State University (Publisher)
Created2013
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Facility location models are usually employed to assist decision processes in urban and regional planning. The focus of this research is extensions of a classic location problem, the Weber problem, to address continuously distributed demand as well as multiple facilities. Addressing continuous demand and multi-facilities represents major challenges. Given advances

Facility location models are usually employed to assist decision processes in urban and regional planning. The focus of this research is extensions of a classic location problem, the Weber problem, to address continuously distributed demand as well as multiple facilities. Addressing continuous demand and multi-facilities represents major challenges. Given advances in geographic information systems (GIS), computational science and associated technologies, spatial optimization provides a possibility for improved problem solution. Essential here is how to represent facilities and demand in geographic space. In one respect, spatial abstraction as discrete points is generally assumed as it simplifies model formulation and reduces computational complexity. However, errors in derived solutions are likely not negligible, especially when demand varies continuously across a region. In another respect, although mathematical functions describing continuous distributions can be employed, such theoretical surfaces are generally approximated in practice using finite spatial samples due to a lack of complete information. To this end, the dissertation first investigates the implications of continuous surface approximation and explicitly shows errors in solutions obtained from fitted demand surfaces through empirical applications. The dissertation then presents a method to improve spatial representation of continuous demand. This is based on infill asymptotic theory, which indicates that errors in fitted surfaces tend to zero as the number of sample points increases to infinity. The implication for facility location modeling is that a solution to the discrete problem with greater demand point density will approach the theoretical optimum for the continuous counterpart. Therefore, in this research discrete points are used to represent continuous demand to explore this theoretical convergence, which is less restrictive and less problem altering compared to existing alternatives. The proposed continuous representation method is further extended to develop heuristics to solve the continuous Weber and multi-Weber problems, where one or more facilities can be sited anywhere in continuous space to best serve continuously distributed demand. Two spatial optimization approaches are proposed for the two extensions of the Weber problem, respectively. The special characteristics of those approaches are that they integrate optimization techniques and GIS functionality. Empirical results highlight the advantages of the developed approaches and the importance of solution integration within GIS.
ContributorsYao, Jing (Author) / Murray, Alan T. (Thesis advisor) / Mirchandani, Pitu B. (Committee member) / Kuby, Michael J (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Decades ago in the U.S., clear lines delineated which neighborhoods were acceptable for certain people and which were not. Techniques such as steering and biased mortgage practices continue to perpetuate a segregated outcome for many residents. In contrast, ethnic enclaves and age restricted communities are viewed as voluntary segregation based

Decades ago in the U.S., clear lines delineated which neighborhoods were acceptable for certain people and which were not. Techniques such as steering and biased mortgage practices continue to perpetuate a segregated outcome for many residents. In contrast, ethnic enclaves and age restricted communities are viewed as voluntary segregation based on cultural and social amenities. This diversity surrounding the causes of segregation are not just region-wide characteristics, but can vary within a region. Local segregation analysis aims to uncover this local variation, and hence open the door to policy solutions not visible at the global scale. The centralization index, originally introduced as a global measure of segregation focused on spatial concentration of two population groups relative a region's urban center, has lost relevancy in recent decades as regions have become polycentric, and the index's magnitude is sensitive to the particular point chosen as the center. These attributes, which make it a poor global measure, are leveraged here to repurpose the index as a local measure. The index's ability to differentiate minority from majority segregation, and its focus on a particular location within a region make it an ideal local segregation index. Based on the local centralization index for two groups, a local multigroup variation is defined, and a local space-time redistribution index is presented capturing change in concentration of a single population group over two time periods. Permutation based inference approaches are used to test the statistical significance of measured index values. Applications to the Phoenix, Arizona metropolitan area show persistent cores of black and white segregation over the years 1990, 2000 and 2010, and a trend of white segregated neighborhoods increasing at a faster rate than black. An analysis of the Phoenix area's recently opened light rail system shows that its 28 stations are located in areas of significant white, black and Hispanic segregation, and there is a clear concentration of renters over owners around most stations. There is little indication of statistically significant change in segregation or population concentration around the stations, indicating a lack of near term impact of light rail on the region's overall demographics.
ContributorsFolch, David C. (Author) / Rey, Sergio J (Thesis advisor) / Anselin, Luc (Committee member) / Murray, Alan T. (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The purpose of this study is to first investigate the role of political socialization on young men and women and what motivates them to become politically active and make the ultimate decision to run for elected office. These effects include parental attitudes, exposure to political shows and news sources, participation

The purpose of this study is to first investigate the role of political socialization on young men and women and what motivates them to become politically active and make the ultimate decision to run for elected office. These effects include parental attitudes, exposure to political shows and news sources, participation in voluntary organizations, and overall community involvement. After understanding these direct and indirect effects of political socialization, I can attempt to explain the causes for the gender gap in political ambition \u2014 meaning that significantly more men are running for elected office compared to women.
ContributorsOsgood, Shannon Marie (Author) / Woodall, Gina (Thesis director) / Herrera, Richard (Committee member) / Barrett, The Honors College (Contributor) / College of Public Service and Community Solutions (Contributor) / School of Public Affairs (Contributor) / School of Politics and Global Studies (Contributor)
Created2015-05
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The Undoing Project is an ongoing educational feminist YouTube channel that serves as an introduction to feminism and feminist theory. The objective for this project is to present feminist theory and feminist ideology in an accessible and entertaining way. Through this project I sought to accomplish three goals: to challenge

The Undoing Project is an ongoing educational feminist YouTube channel that serves as an introduction to feminism and feminist theory. The objective for this project is to present feminist theory and feminist ideology in an accessible and entertaining way. Through this project I sought to accomplish three goals: to challenge the negative image of feminism, bridge the gap between the language of academia and the public, and to acknowledge and unlearn ingrained prejudices. The videos focus on theory, history, legislation, current events, and pop culture. The initial project consists of ten videos addressing the feminist wave models, a brief history of the feminist movement, and discussions of concepts like hegemony, intersectionality, masculinity, femininity, and race.
ContributorsBuchholtz, Kaylee Marie (Author) / Brian, Jennifer (Thesis director) / Grzanka, Patrick (Committee member) / Brouwer, Dan (Committee member) / Barrett, The Honors College (Contributor) / College of Public Service and Community Solutions (Contributor) / School of Social Transformation (Contributor) / Department of English (Contributor)
Created2015-05
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Previous research has found improvements in motor and cognitive measures following Assisted Cycle Therapy (AC) in adolescence with Down syndrome (DS). Our study investigated whether we would find improvements in older adults with DS on measures of leisure physical activity (GLTEQ) and sleep, which are early indicators of Alzheimer's disease

Previous research has found improvements in motor and cognitive measures following Assisted Cycle Therapy (AC) in adolescence with Down syndrome (DS). Our study investigated whether we would find improvements in older adults with DS on measures of leisure physical activity (GLTEQ) and sleep, which are early indicators of Alzheimer's disease (AD) in persons with Down syndrome. This study consisted of eight participants with Down syndrome between 31 and 51 years old that cycled for 30 minutes 3 x/week for eight weeks either at their voluntary cycling rate (VC) or approximately 35% faster with the help of a mechanical motor (AC). We predicted that, based on pilot data (Gomez, 2015), GLTEQ would either maintain or improve after AC, but would decrease after VC and would stay the same after NC. We predicted that the sleep score may improve after both VC or AC or it may improve more after VC than AC based on pilot data related to leisure activity. Our results were consistent with our prediction that GLTEQ will either maintain or improve after AC but will decrease after VC. Our results were not consistent with our prediction that sleep may improve after both VC or AC or it may improve more after VC than AC, possibly because we did not pre-screen for sleep disorders. Future research should focus on recruiting more participants and using both objective and subjective measures of sleep and physical activity to improve the efficacy of the study.
ContributorsParker, Lucas Maury (Author) / Ringenbach, Shannon (Thesis director) / Buman, Matthew (Committee member) / Holzapfel, Simon (Committee member) / School of Social and Behavioral Sciences (Contributor) / School of Nutrition and Health Promotion (Contributor) / College of Public Service and Community Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description

Background: Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events.

Objectives: This quantitative study was designed

Background: Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events.

Objectives: This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season.

Methods: Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature–health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different “trigger points” at which heat-health intervention measures might be activated.

Results: We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22°C) across multiple health events and diagnoses.

Conclusion: Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades.

ContributorsPettiti, Diana B. (Author) / Hondula, David M. (Author) / Yang, Shuo (Author) / Harlan, Sharon L. (Author) / Chowell, Gerardo (Author)
Created2016-02-01
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Description

Maricopa County, Arizona, anchor to the fastest growing megapolitan area in the United States, is located in a hot desert climate where extreme temperatures are associated with elevated risk of mortality. Continued urbanization in the region will impact atmospheric temperatures and, as a result, potentially affect human health. We aimed

Maricopa County, Arizona, anchor to the fastest growing megapolitan area in the United States, is located in a hot desert climate where extreme temperatures are associated with elevated risk of mortality. Continued urbanization in the region will impact atmospheric temperatures and, as a result, potentially affect human health. We aimed to quantify the number of excess deaths attributable to heat in Maricopa County based on three future urbanization and adaptation scenarios and multiple exposure variables.

Two scenarios (low and high growth projections) represent the maximum possible uncertainty range associated with urbanization in central Arizona, and a third represents the adaptation of high-albedo cool roof technology. Using a Poisson regression model, we related temperature to mortality using data spanning 1983–2007. Regional climate model simulations based on 2050-projected urbanization scenarios for Maricopa County generated distributions of temperature change, and from these predicted changes future excess heat-related mortality was estimated. Subject to urbanization scenario and exposure variable utilized, projections of heat-related mortality ranged from a decrease of 46 deaths per year (− 95%) to an increase of 339 deaths per year (+ 359%).

Projections based on minimum temperature showed the greatest increase for all expansion and adaptation scenarios and were substantially higher than those for daily mean temperature. Projections based on maximum temperature were largely associated with declining mortality. Low-growth and adaptation scenarios led to the smallest increase in predicted heat-related mortality based on mean temperature projections. Use of only one exposure variable to project future heat-related deaths may therefore be misrepresentative in terms of direction of change and magnitude of effects. Because urbanization-induced impacts can vary across the diurnal cycle, projections of heat-related health outcomes that do not consider place-based, time-varying urban heat island effects are neglecting essential elements for policy relevant decision-making.

ContributorsHondula, David M. (Author) / Georgescu, Matei (Author) / Balling, Jr., Robert C. (Author)
Created2014-04-28