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As the prevalence of childhood obesity in the United States rises, opportunities for children to be physically active become more vital. One opportunity for physical activity involves children walking to and from school. However, children that live in areas with a pedestrian-unfriendly built environment and a low degree of walkability are less likely to be physically active and more likely to be overweight. The purpose of this study was to study walking routes from schools in low-income neighborhoods in Southwestern United States to a local community center. Walking routes from the three study schools (South Mountain High School, Percy Julian Middle School, and Rose Linda Elementary School) were determined by distance, popularity, and the presence of a major thoroughfare. Segments and intersections, which formed the routes, were randomly selected from each school's buffer region. The walking routes as a whole, along with the segments and intersections, were audited and scored using built environment assessments tools: MAPS, PEQI and Walkability Checklist. These scores were utilized to develop interactive mapping tools to visualize the quality of the routes, segments and intersections and identify areas for improvement. Results showed that the routes from Percy Julian to the Kroc Center were, overall, rated higher than routes from the other two schools. The highest scoring route, from the seven routes studied, was route 2 from Percy Julian to the Kroc Center along Broadway Road. South Mountain High School was overall the worst starting point for walking to the Kroc Center as those three walking routes were graded as the least walkable. Possible areas for improvement include installing traffic calming features along major thoroughfares and reducing the perceived risk to pedestrian safety by beautifying the community by planting greenery. Future directions include studying the built environment in South Phoenix communities that surround the Kroc Center.
ContributorsZeien, Justin Lee (Author) / Buman, Matthew (Thesis director) / Hekler, Eric (Committee member) / Fellows, Brian (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
Triops (Branchiopoda: Notostraca) and Streptocephalus (Branchiopoda: Anostraca) are two crustaceans which cohabitate in ephemeral freshwater pools. They both lay desiccation resistant eggs that disperse passively to new hydrologically isolated environments. The extent of genetic distance among regions and populations is of perennial interest in animals that live in such isolated habitats. Populations in six natural ephemeral pool habitats located in two different regions of the Sonoran Desert and a transition area between the Sonoran and Chihuahuan Deserts were sampled. Sequences from Genbank were used for reference points in the determination of species as well as to further identify regional genetic distance within species. This study estimated the amount of within and between genetic distance of individuals from each region and population through the use of a neutral marker, cytochrome oxidase I (COI). We concluded that, although the method of passive dispersal may differ between the two genera, the differences do not results in different patterns of genetic distances between regions and populations. Furthermore, we only found the putative species, Triops longicaudatus "short", with enough distinct speciation. Although Triops longicaudatus "long" and Triops newberryi may be in the early stages of speciation, this study does not find enough support to conclude that they have separated.
ContributorsMurphy Jr., Patrick Joseph (Author) / Rutowski, Ronald (Thesis director) / Cartwright, Reed (Committee member) / Lessios, Nikos (Committee member) / School of Life Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
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
Description
Translating research has been a goal of the Department of Health and Human Services since 1999. Through two years of iteration and interview with our community members, we have collected insights into the barriers to accomplishing this goal. Liberating Science is a think-tank of researchers and scientists who seek to create a more transparent process to accelerate innovation starting with behavioral health research.
ContributorsRaghani, Pooja Sioux (Author) / Hekler, Eric (Thesis director) / Buman, Matthew (Committee member) / Pruthi, Virgilia Kaur (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Biomedical Informatics Program (Contributor)
Created2014-05
Description
The evolution of blindness in cave animals has been heavily studied; however, little research has been done on the interaction of migration and drift on the development of blindness in these populations. In this study, a model is used to compare the effect that genetic drift has on the fixation of a blindness allele for varying amounts of migration and selection. For populations where the initial frequency is quite low, genetic drift plays a much larger role in the fixation of blindness than populations where the initial frequency is high. In populations where the initial frequency is high, genetic drift plays almost no role in fixation. Our results suggest that migration plays a greater role in the fate of the blindness allele than selection.
ContributorsMerry, Alexandra Leigh (Author) / Cartwright, Reed (Thesis director) / Rosenberg, Michael (Committee member) / Schwartz, Rachel (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2014-05
Description
Over the last decade, the ability to track daily activity through step counting devices has undergone major changes. Advanced technologies have brought about new step counting devices and new form factors. The validity of these new devices is not fully known. The purpose of this study was to validate and compare the step counting accuracy of commercially available hip- and wrist-worn accelerometers. A total of 185 participants (18-64 years of age) were analyzed for this study, with the sample composed nearly evenly of each gender (53.5% female) and BMI classification (33% overweight, 31.9% obese). Each participant wore five devices including hip-worn Omron HJ-112 and Fitbit One, and wrist-worn Fitbit Flex, Nike Fuelband, and Jawbone UP. A range of activities (some constant among all participants, some randomly assigned) were then used to accumulate steps including walking on a hard surface for 400m, treadmill walking/running at 2mph, 3mph, and ≥5mph, walking up five flights of stairs, and walking down five flights of stairs. To validate the accuracy of each device, steps were also counted by direct observation. Results showed high concordance with directly observed steps for all devices (intraclass correlation coefficient range: 0.86 to 0.99), with hip-worn devices more accurate than wrist-worn devices. Absolute percent error values were lower among hip-worn devices and at faster walking/running speeds. Nike Fuelband consistently was the worst performing of all test devices. These results are important because as pedometers become more complex, it is important that they remain accurate throughout a variety of activities. Future directions for this research are to explore the validity of these devices in free-living settings and among younger and older populations.
ContributorsKramer, Cody Lee (Author) / Buman, Matthew (Thesis director) / Hoffner, Kristin (Committee member) / Marshall, Simon (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2014-05
Description
Human activity recognition is the task of identifying a person’s movement from sensors in a wearable device, such as a smartphone, smartwatch, or a medical-grade device. A great method for this task is machine learning, which is the study of algorithms that learn and improve on their own with the help of massive amounts of useful data. These classification models can accurately classify activities with the time-series data from accelerometers and gyroscopes. A significant way to improve the accuracy of these machine learning models is preprocessing the data, essentially augmenting data to make the identification of each activity, or class, easier for the model. <br/>On this topic, this paper explains the design of SigNorm, a new web application which lets users conveniently transform time-series data and view the effects of those transformations in a code-free, browser-based user interface. The second and final section explains my take on a human activity recognition problem, which involves comparing a preprocessed dataset to an un-augmented one, and comparing the differences in accuracy using a one-dimensional convolutional neural network to make classifications.
ContributorsLi, Vincent (Author) / Turaga, Pavan (Thesis director) / Buman, Matthew (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
The modern web presents an opportunity for educators and researchers to create tools that are highly accessible. Because of the near-ubiquity of modern web browsers, developers who hope to create educational and analytical tools can reach a large au- dience by creating web applications. Using JavaScript, HTML, and other modern web development technologies, Genie was developed as a simulator to help educators in biology, genetics, and evolution classrooms teach their students about population genetics. Because Genie was designed for the modern web, it is highly accessible to both educators and students, who can access the web application using any modern web browser on virtually any device. Genie demonstrates the efficacy of web devel- opment technologies for demonstrating and simulating complex processes, and it will be a unique educational tool for educators who teach population genetics.
ContributorsRoos, Benjamin Hirsch (Author) / Cartwright, Reed (Thesis director) / Wilson Sayres, Melissa (Committee member) / Mayron, Liam (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
A major challenge with tissue samples used for biopsies is the inability to monitor their molecular quality before diagnostic testing. When tissue is resected from a patient, the cells are removed from their blood supply and normal temperature-controlled environment, which causes significant biological stress. As a result, the molecular composition and integrity undergo significant change. Currently, there is no method to track the effects of these artefactual stresses on the sample tissue to determine any deviations from the actual patient physiology. Without a way to track these changes, pathologists have to blindly trust that the tissue samples they are given are of high quality and fit for molecular analysis; physicians use the analysis to make diagnoses and treatment plans based on the assumption that the samples are valid. A possible way to track the quality of the tissue is by measuring volatile organic compounds (VOCs) released from the samples. VOCs are carbon-based chemicals with high vapor pressure at room temperature. There are over 1,800 known VOCs within humans and a number of these exist in every tissue sample. They are individualized and often indicative of a person’s metabolic condition. For this reason, VOCs are often used for diagnostic purposes. Their usefulness in diagnostics, reflectiveness of a person’s metabolic state, and accessibility lends them to being beneficial for tracking degradation. We hypothesize that there is a relationship between the change in concentration of the volatile organic compounds of a sample, and the molecular quality of a sample. This relationship is what would indicate the accuracy of the tissue quality used for a biopsy in relation to the tissue within the body.
ContributorsSharma, Nandini (Co-author) / Fragoso, Claudia (Co-author) / Grenier, Tyler (Co-author) / Hanson, Abigail (Co-author) / Compton, Carolyn (Thesis director) / Tao, Nongjian (Committee member) / Moakley, George (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Callithrix penicillata, also known as the Black-tufted marmoset primarily lives in the Brazilian highlands and has had little research conducted on it. For this project I performed a genome curation on the newly assembled genome of this species. The scaffolds obtained by the Dovetail Genomics reads were organized and labeled into chromosomes using the 2014 Callithrix jacchus genome as a reference. Then, using that same genome as a reference, 13 of the chromosomes were reverse complimented to be continuous with the 2014 Callithrix jacchus genome. The N50 statistics of the assembly were calculated and found to be 124 Mb. Quality scores were run for the final genome using referee and visualized with a bar plot, with 99% of sites scoring above 0. Heterozygosity was also calculated and found to be 0.3%. Finally, the final version of the genome was visually compared to the 2017 Callithrix jacchus genome and the GRCh38 human genome. This genome was submitted to the NCBIs database to await further approval.
ContributorsJohnson, Joelle Genevieve (Author) / Cartwright, Reed (Thesis director) / Stone, Anne (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12