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The thesis document describes in detail the decision making process and research that went into each step in the process of designing, coding, launching, and marketing a mobile game. This includes major challenges and methodologies for overcoming them or changing course as well as significant revisions that were made to the game upon receiving market and user feedback. The game, Sheep In Space, was launched on to the Windows Phone 8 marketplace initially via the use of the GameMaker: Studio game engine. From there, following a series of revisions Sheep In Space launched on the Android marketplace and has been undergoing further changes before the final launch to iOS. The revision and launch strategy was determined based off of market feedback from a variety of facets, including direct word of mouth, reviews, downloads, analytics data, and social media reaction.
ContributorsGagliano, Laura Katherine (Author) / Prince, Linda (Thesis director) / Eaton, John (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / Department of Information Systems (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2014-12
Description
The primary objective of this research project is to develop dual layered polymeric microparticles with a tunable delayed release profile. Poly(L-lactic acid) (PLA) and poly(lactic-co-glycolic acid) (PLGA) phase separate in a double emulsion process due to differences in hydrophobicity, which allows for the synthesis of double-walled microparticles with a PLA shell surrounding the PLGA core. The microparticles were loaded with bovine serum albumin (BSA) and different volumes of ethanol were added to the PLA shell phase to alter the porosity and release characteristics of the BSA. Different amounts of ethanol varied the total loading percentage of the BSA, the release profile, surface morphology, size distribution, and the localization of the protein within the particles. Scanning electron microscopy images detailed the surface morphology of the different particles. Loading the particles with fluorescently tagged insulin and imaging the particles through confocal microscopy supported the localization of the protein inside the particle. The study suggest that ethanol alters the release characteristics of the loaded BSA encapsulated in the microparticles supporting the use of a polar, protic solvent as a tool for tuning the delayed release profile of biological proteins.
ContributorsFauer, Chase Alexander (Author) / Stabenfeldt, Sarah (Thesis director) / Ankeny, Casey (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2015-05
Description
The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.
ContributorsHan, Priscilla (Author) / Vernon, Brent (Thesis director) / Nickle, Jacob (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Introduction: There is currently a lack of industry-wide gold standardization in accelerometer study
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate valid/invalid wear
time and detect bouts of sleep has been modified with the goal of maximizing accuracy of sleep bout
detection. Methods: Three key decisions and thresholds of the algorithm have been modified with three
experimental values each being tested. The main experimental variable Sleepwindow controls the
amount of time before and after a determined bout of sleep that is searched for additional sedentary
time to incorporate and consider part of the same sleep bout. Results were compared to PSG and sleep
diary data for absolute agreement of sleep bout start time (START), end time (END) and time in bed
(TIB). Adjustments were made for outliers as well as sleep latency, snooze time, and the sum of both.
Results: Only adjustments made to a sleep window variable yielded altered results. Between a 5-, 15-,
and 30-minute window, a 15-minute window incurred the least error and most agreement to
comparisons for START, while a 5-minute window was best for END and TIB. Discussion: Contrary
to expectation, corrections for snooze, latency, and both did not substantially improve agreement to
PSG. Algorithm-derived estimates of START and END always fell after sleep diary and PSG both,
suggesting either participants’ sedentary behavior beginning and ends were at a delay from sleep and
wake times, or the algorithm estimates consistently later times than appropriate. The inclusion of a
sleep window variable yields substantial variety in results. A 15-minute window appears best at
determining START while a 5-minute window appears best for END and TIB. Further investigation on
the optimal window length per demographic and condition is required.
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate valid/invalid wear
time and detect bouts of sleep has been modified with the goal of maximizing accuracy of sleep bout
detection. Methods: Three key decisions and thresholds of the algorithm have been modified with three
experimental values each being tested. The main experimental variable Sleepwindow controls the
amount of time before and after a determined bout of sleep that is searched for additional sedentary
time to incorporate and consider part of the same sleep bout. Results were compared to PSG and sleep
diary data for absolute agreement of sleep bout start time (START), end time (END) and time in bed
(TIB). Adjustments were made for outliers as well as sleep latency, snooze time, and the sum of both.
Results: Only adjustments made to a sleep window variable yielded altered results. Between a 5-, 15-,
and 30-minute window, a 15-minute window incurred the least error and most agreement to
comparisons for START, while a 5-minute window was best for END and TIB. Discussion: Contrary
to expectation, corrections for snooze, latency, and both did not substantially improve agreement to
PSG. Algorithm-derived estimates of START and END always fell after sleep diary and PSG both,
suggesting either participants’ sedentary behavior beginning and ends were at a delay from sleep and
wake times, or the algorithm estimates consistently later times than appropriate. The inclusion of a
sleep window variable yields substantial variety in results. A 15-minute window appears best at
determining START while a 5-minute window appears best for END and TIB. Further investigation on
the optimal window length per demographic and condition is required.
ContributorsMartin, Logan Rhett (Author) / Buman, Matthew (Thesis director) / Toledo, Meynard John (Committee member) / Kurka, Jonathan (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
Ecological modeling can be used to analyze health risk behaviors and their relationship to ecological factors, which is useful in determining how social environmental factors influence an individual’s decisions. Environmental interactions shape the way that humans behave throughout the day, either through observation, action, or consequences. Specifically, health risk behaviors can be analyzed in relation to ecological factors. Alcohol drinking among college students has been a long concern and there are many risks associated with these behaviors in this population. Consistent engagement in health risk behaviors as a college student, such as drinking and smoking, can pose a much larger issues later in life and can lead to many different health problems. A research study was conducted in the form of a 27 question survey to determine and evaluate the impact of ecological factors on drinking and smoking behaviors among Arizona State University students. Ecological factors such as demographics, living conditions, contexts of social interactions, and places where students spend most of their time were used to evaluate the relationship between drinking and smoking behaviors and the ecological factors, both on- and off- campus. The sample size of this study is 541 students. Statistical tests were conducted using Excel and RStudio to find relationships between patterns of health risk behaviors and various ecological factors. The data from the survey was analyzed to address three main questions. The first question analyzed drinking behaviors in relation to demographics, specifically gender and race. The second question assessed drinking behaviors with participation in Greek life and clubs on campus. The third question evaluated the relationship between health risk behaviors and students’ living conditions, such as living on or off campus. The results show that while gender does not have a statistically significant influence on drinking behaviors, race does. White individuals are more likely to engage in drinking behaviors and are more at risk than non-whites. Participation in Greek life was shown to be statistically significant in determining health risk behaviors, while involvement in clubs was not. Finally, on campus students are less likely to engage in health risk behaviors than off-campus students.
ContributorsWerbick, Meghan Lindsay (Co-author) / Andrade, Amber (Co-author) / Naik, Sparshee (Co-author) / Mubayi, Anuj (Thesis director) / Gaughan, Monica (Committee member) / School of Human Evolution & Social Change (Contributor, Contributor) / School of Politics and Global Studies (Contributor, Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05