Matching Items (307)
Description
Dietary self-monitoring has been shown to be a predictor of weight loss success and is a prevalent part of behavioral weight control programs. As more weight loss applications have become available on smartphones, this feasibility study investigated whether the use of a smartphone application, or a smartphone memo feature would improve dietary self-monitoring over the traditional paper-and-pencil method. The study also looked at whether the difference in methods would affect weight loss. Forty-seven adults (BMI 25 to 40 kg/m2) completed an 8-week study focused on tracking the difference in adherence to a self-monitoring protocol and subsequent weight loss. Participants owning iPhones (n=17) used the 'Lose It' application (AP) for diet and exercise tracking and were compared to smartphone participants who recorded dietary intake using a memo (ME) feature (n=15) on their phone and participants using the traditional paper-and-pencil (PA) method (n=15). There was no significant difference in completion rates between groups with an overall completion rate of 85.5%. The overall mean adherence to self-monitoring for the 8-week period was better in the AP group than the PA group (p = .024). No significant difference was found between the AP group and ME group (p = .148), or the ME group and the PA group (p = .457). Weight loss for the 8 week study was significant for all groups (p = .028). There was no significant difference in weight loss between groups. Number of days recorded regardless of group assignment showed a weak correlation to weight loss success (p = .068). Smartphone owners seeking to lose weight should be encouraged by the potential success associated with dietary tracking using a smartphone app as opposed to the traditional paper-and-pencil method.
ContributorsCunningham, Barbara (Author) / Wharton, Christopher (Christopher Mack), 1977- (Thesis advisor) / Johnston, Carol (Committee member) / Hall, Richard (Committee member) / Arizona State University (Publisher)
Created2012
Description
It is commonly accepted that undergraduate degree attainment rates must improve if postsecondary educational institutions are to meet macroeconomic demands. Involvement in co-curricular activities, such as student clubs and organizations, has been shown to increase students' satisfaction with their college experience and the rates by which they might persist. Yet, strategies that college administrators, faculties, and peer leaders may employ to effectively promote co-curricular engagement opportunities to students are not well developed. In turn, I created the Sky Leaders program, a retention-focused intervention designed to promote commuter student involvement in academically-purposeful activities via faculty- and peer-lead mentoring experiences. Working from an interpretivist research paradigm, this quasi-experimental mixed methods action research study was intended to measure the intervention's impact on participants' re-enrollment and reported engagement rates, as well as the effectiveness of its conceptual and logistical aspects. I used enrollment, survey, interview, observation, and focus group data collection instruments to accommodate an integrated data procurement process, which allowed for the consideration of several perspectives related to the same research questions. I analyzed all of the quantitative data captured from the enrollment and survey instruments using descriptive and inferential statistics to explore statistically and practically significant differences between participant groups. As a result, I identified one significant finding that had a perceived positive effect. Expressly, I found the difference between treatment and control participants' reported levels of engagement within co-curricular activities to be statistically and practically significant. Additionally, consistent with Glaser and Strauss' grounded theory approach, I employed open, axial, and selective coding procedures to analyze all of the qualitative data obtained via open-ended survey items, as well as interview, observation, and focus group instruments. After I reviewed and examined the qualitative data corpus, I constructed six themes reflective of the participants' programmatic experiences as well as conceptual and logistical features of the intervention. In doing so, I found that faculty, staff, and peer leaders may efficaciously serve in specific mentoring roles to promote co-curricular engagement opportunities and advance students' institutional academic and social integration, thereby effectively curbing their potential college departure decisions, which often arise out of mal-integrative experiences.
ContributorsSebold, Brent (Author) / Beardsley, Audrey (Thesis advisor) / Serafini, Frank (Committee member) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Arizona State University (Publisher)
Created2011
Description
Nut consumption, specifically almonds, have been shown to help maintain weight and influence disease risk factors in adult populations. Limited studies have been conducted examining the effect of a small dose of almonds on energy intake and body weight. The objective of this study was to determine the influence of pre-meal almond consumption on energy intake and weight in overweight and obese adults. In this study included 21, overweight or obese, participants who were considered healthy or had a controlled disease state. This 8-week parallel arm study, participants were randomized to consume an isocaloric amount of almonds, (1 oz) serving, or two (2 oz) cheese stick serving, 30 minutes before the dinner meal, 5 times per week. Anthropometric measurements including weight, waist circumference, and body fat percentage were recorded at baseline, week 1, 4, and 8. Measurement of energy intake was self-reported for two consecutive days at week 1, 4 and 8 using the ASA24 automated dietary program. The energy intake after 8 weeks of almond consumption was not significantly different when compared to the control group (p=0.965). In addition, body weight was not significantly reduced after 8 weeks of the almond intervention (p=0.562). Other parameters measured in this 8-week trial did not differ between the intervention and the control group. These data presented are underpowered and therefore inconclusive on the effects that 1 oz of almonds, in the diet, 5 per week has on energy intake and bodyweight.
ContributorsMcBride, Lindsey (Author) / Johnston, Carol (Thesis advisor) / Swan, Pamela (Committee member) / Mayol-Kreiser, Sandra (Committee member) / Arizona State University (Publisher)
Created2011
Description
ABSTRACT Epidemiological studies have suggested a link between nut consumption and weight. The possible effects of regular nut consumption as a method of weight loss has shown minimal results with 2-3 servings of nut products per day. This 8 week study sought to investigate the effect of more modest nut consumption (1 oz./day, 5 days/week) on dietary compensation in healthy overweight individuals. Overweight and obese participants (n = 28) were recruited from the local community and were randomly assigned to either almond (NUT) or control (CON) group in this randomized, parallel-arm study. Subjects were instructed to eat their respective foods 30 minutes before the dinner meal. 24 hour diet recalls were completed pre-trial and at study weeks 1, 4 and 8. Self-reported satiety data were completed at study weeks 1, 4, and 8. Attrition was unexpectedly high, with 13 participants completing 24 dietary recall data through study week 8. High attrition limited statistical analyses. Results suggested a lack of effect for time or interaction for satiety data (within groups p = 0.997, between groups p = 0.367). Homogeneity of of inter-correlations could not be tested for 24-hour recall data as there were fewer than 2 nonsingular cell covariance matrices. In conclusion, this study was unable to prove or disprove the effectiveness of almonds to induce dietary compensation.
ContributorsJahns, Marshall (Author) / Johnston, Carol (Thesis advisor) / Hall, Richard (Committee member) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Arizona State University (Publisher)
Created2011
Description
Radiation-induced gain degradation in bipolar devices is considered to be the primary threat to linear bipolar circuits operating in the space environment. The damage is primarily caused by charged particles trapped in the Earth's magnetosphere, the solar wind, and cosmic rays. This constant radiation exposure leads to early end-of-life expectancies for many electronic parts. Exposure to ionizing radiation increases the density of oxide and interfacial defects in bipolar oxides leading to an increase in base current in bipolar junction transistors. Radiation-induced excess base current is the primary cause of current gain degradation. Analysis of base current response can enable the measurement of defects generated by radiation exposure. In addition to radiation, the space environment is also characterized by extreme temperature fluctuations. Temperature, like radiation, also has a very strong impact on base current. Thus, a technique for separating the effects of radiation from thermal effects is necessary in order to accurately measure radiation-induced damage in space. This thesis focuses on the extraction of radiation damage in lateral PNP bipolar junction transistors and the space environment. It also describes the measurement techniques used and provides a quantitative analysis methodology for separating radiation and thermal effects on the bipolar base current.
ContributorsCampola, Michael J (Author) / Barnaby, Hugh J (Thesis advisor) / Holbert, Keith E. (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2011
Description
ABSTRACT This study evaluated the LoseIt Smart Phone app by Fit Now Inc. for nutritional quality among users during an 8 week behavioral modification weight loss protocol. All participants owned smart phones and were cluster randomized to either a control group using paper and pencil record keeping, a memo group using a memo function on their smart phones, or the LoseIt app group which was composed of the participants who owned iPhones. Thirty one participants completed the study protocol: 10 participants from the LoseIt app group, 10 participants from the memo group, and 11 participants from the paper and pencil group. Food records were analyzed using Food Processor by ESHA and the nutritional quality was scored using the Healthy Eating Index - 2005 (HEI-2005). Scores were compared using One-Way ANOVA with no significant changes in any category across all groups. Non-parametric statistics were then used to determine changes between combined memo and paper and pencil groups and the LoseIt app group as the memo and paper and pencil group received live counseling at biweekly intervals and the LoseIt group did not. No significant difference was found in HEI scores across all categories, however a trend was noted for total HEI score with higher scores among the memo and paper and pencil group participants p=0.091. Conclusion, no significant difference was detected between users of the smart phone app LoseIt and memo and paper and pencil groups. More research is needed to determine the impact of in-person counseling versus user feedback provided with the LoseIt smart phone app.
ContributorsCowan, David Kevin (Author) / Johnston, Carol (Thesis advisor) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Mayol-Kreiser, Sandra (Committee member) / Arizona State University (Publisher)
Created2011
Description
Community Supported Agriculture programs (CSAs) have become a viable local source of fresh agricultural goods and represent a potentially new way to improve fruit and vegetable consumption among individuals and families. Studies concerning CSAs have focused mainly on characteristics of the typical CSA member and motivations and barriers to join a CSA program. The purpose of this study was to examine whether behavior and attitudinal differences existed between current CSA members and a nonmember control group. Specifically, ecological attitudes, eating out behaviors, composting frequency, and family participation in food preparation were assessed. This study utilized an online survey comprising items from previous survey research as well as newly created items. A total of 115 CSA member and 233 control survey responses were collected. CSA members were more likely to be older, have more education, and have a higher income than the control group. The majority of CSA members surveyed were female, identified as non-Hispanic and Caucasian, earned a higher income, and reported being the primary food shopper and preparer. The majority of members also noted that the amount and variety of fruits and vegetables they ate and served their family increased as a result of joining a CSA. CSA members were more ecologically minded compared to the control group. Frequency of eating out was not significantly different between groups. However, eating out behaviors were different between income categories. CSA members spent significantly more money at each meal eaten away from home and spent significantly more money on eating out each week. In both cases, controlling for income attenuated differences between groups. CSA members composted at a significantly higher rate and took part in other eco-friendly behaviors more often than the control group. Finally, no significant difference was evident between the two groups when analyzing family involvement in food preparation and meal decision-making. Overall, some significant attitudinal and behavioral differences existed between CSA members and non-CSA members. Further research is necessary to examine other distinctions between the two groups and whether these differences occur as a result of CSA membership.
ContributorsMacMillan Uribe, Alexandra L (Author) / Wharton, Christopher (Christopher Mack), 1977- (Thesis advisor) / Winham, Donna (Committee member) / Eakin, Hallie (Committee member) / Arizona State University (Publisher)
Created2011
Description
The increased use of commercial complementary metal-oxide-semiconductor (CMOS) technologies in harsh radiation environments has resulted in a new approach to radiation effects mitigation. This approach utilizes simulation to support the design of integrated circuits (ICs) to meet targeted tolerance specifications. Modeling the deleterious impact of ionizing radiation on ICs fabricated in advanced CMOS technologies requires understanding and analyzing the basic mechanisms that result in buildup of radiation-induced defects in specific sensitive regions. Extensive experimental studies have demonstrated that the sensitive regions are shallow trench isolation (STI) oxides. Nevertheless, very little work has been done to model the physical mechanisms that result in the buildup of radiation-induced defects and the radiation response of devices fabricated in these technologies. A comprehensive study of the physical mechanisms contributing to the buildup of radiation-induced oxide trapped charges and the generation of interface traps in advanced CMOS devices is presented in this dissertation. The basic mechanisms contributing to the buildup of radiation-induced defects are explored using a physical model that utilizes kinetic equations that captures total ionizing dose (TID) and dose rate effects in silicon dioxide (SiO2). These mechanisms are formulated into analytical models that calculate oxide trapped charge density (Not) and interface trap density (Nit) in sensitive regions of deep-submicron devices. Experiments performed on field-oxide-field-effect-transistors (FOXFETs) and metal-oxide-semiconductor (MOS) capacitors permit investigating TID effects and provide a comparison for the radiation response of advanced CMOS devices. When used in conjunction with closed-form expressions for surface potential, the analytical models enable an accurate description of radiation-induced degradation of transistor electrical characteristics. In this dissertation, the incorporation of TID effects in advanced CMOS devices into surface potential based compact models is also presented. The incorporation of TID effects into surface potential based compact models is accomplished through modifications of the corresponding surface potential equations (SPE), allowing the inclusion of radiation-induced defects (i.e., Not and Nit) into the calculations of surface potential. Verification of the compact modeling approach is achieved via comparison with experimental data obtained from FOXFETs fabricated in a 90 nm low-standby power commercial bulk CMOS technology and numerical simulations of fully-depleted (FD) silicon-on-insulator (SOI) n-channel transistors.
ContributorsSanchez Esqueda, Ivan (Author) / Barnaby, Hugh J (Committee member) / Schroder, Dieter (Thesis advisor) / Schroder, Dieter K. (Committee member) / Holbert, Keith E. (Committee member) / Gildenblat, Gennady (Committee member) / Arizona State University (Publisher)
Created2011
Description
The theme for this work is the development of fast numerical algorithms for sparse optimization as well as their applications in medical imaging and source localization using sensor array processing. Due to the recently proposed theory of Compressive Sensing (CS), the $\ell_1$ minimization problem attracts more attention for its ability to exploit sparsity. Traditional interior point methods encounter difficulties in computation for solving the CS applications. In the first part of this work, a fast algorithm based on the augmented Lagrangian method for solving the large-scale TV-$\ell_1$ regularized inverse problem is proposed. Specifically, by taking advantage of the separable structure, the original problem can be approximated via the sum of a series of simple functions with closed form solutions. A preconditioner for solving the block Toeplitz with Toeplitz block (BTTB) linear system is proposed to accelerate the computation. An in-depth discussion on the rate of convergence and the optimal parameter selection criteria is given. Numerical experiments are used to test the performance and the robustness of the proposed algorithm to a wide range of parameter values. Applications of the algorithm in magnetic resonance (MR) imaging and a comparison with other existing methods are included. The second part of this work is the application of the TV-$\ell_1$ model in source localization using sensor arrays. The array output is reformulated into a sparse waveform via an over-complete basis and study the $\ell_p$-norm properties in detecting the sparsity. An algorithm is proposed for minimizing a non-convex problem. According to the results of numerical experiments, the proposed algorithm with the aid of the $\ell_p$-norm can resolve closely distributed sources with higher accuracy than other existing methods.
ContributorsShen, Wei (Author) / Mittlemann, Hans D (Thesis advisor) / Renaut, Rosemary A. (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Gelb, Anne (Committee member) / Ringhofer, Christian (Committee member) / Arizona State University (Publisher)
Created2011
Description
Hydropower generation is one of the clean renewable energies which has received great attention in the power industry. Hydropower has been the leading source of renewable energy. It provides more than 86% of all electricity generated by renewable sources worldwide. Generally, the life span of a hydropower plant is considered as 30 to 50 years. Power plants over 30 years old usually conduct a feasibility study of rehabilitation on their entire facilities including infrastructure. By age 35, the forced outage rate increases by 10 percentage points compared to the previous year. Much longer outages occur in power plants older than 20 years. Consequently, the forced outage rate increases exponentially due to these longer outages. Although these long forced outages are not frequent, their impact is immense. If reasonable timing of rehabilitation is missed, an abrupt long-term outage could occur and additional unnecessary repairs and inefficiencies would follow. On the contrary, too early replacement might cause the waste of revenue. The hydropower plants of Korea Water Resources Corporation (hereafter K-water) are utilized for this study. Twenty-four K-water generators comprise the population for quantifying the reliability of each equipment. A facility in a hydropower plant is a repairable system because most failures can be fixed without replacing the entire facility. The fault data of each power plant are collected, within which only forced outage faults are considered as raw data for reliability analyses. The mean cumulative repair functions (MCF) of each facility are determined with the failure data tables, using Nelson's graph method. The power law model, a popular model for a repairable system, can also be obtained to represent representative equipment and system availability. The criterion-based analysis of HydroAmp is used to provide more accurate reliability of each power plant. Two case studies are presented to enhance the understanding of the availability of each power plant and represent economic evaluations for modernization. Also, equipment in a hydropower plant is categorized into two groups based on their reliability for determining modernization timing and their suitable replacement periods are obtained using simulation.
ContributorsKwon, Ogeuk (Author) / Holbert, Keith E. (Thesis advisor) / Heydt, Gerald T (Committee member) / Pan, Rong (Committee member) / Arizona State University (Publisher)
Created2011