Matching Items (277)
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Limited research has compared the circadian phase-shifting effects of bright light and exercise and additive effects of these stimuli. The aim of this study was to compare the phase-delaying effects of late night bright light, late night exercise, and late evening bright light followed by early morning exercise. In a

Limited research has compared the circadian phase-shifting effects of bright light and exercise and additive effects of these stimuli. The aim of this study was to compare the phase-delaying effects of late night bright light, late night exercise, and late evening bright light followed by early morning exercise. In a within-subjects, counterbalanced design, 6 young adults completed each of three 2.5-day protocols. Participants followed a 3-h ultra-short sleep-wake cycle, involving wakefulness in dim light for 2h, followed by attempted sleep in darkness for 1 h, repeated throughout each protocol. On night 2 of each protocol, participants received either (1) bright light alone (5,000 lux) from 2210–2340 h, (2) treadmill exercise alone from 2210–2340 h, or (3) bright light (2210–2340 h) followed by exercise from 0410–0540 h. Urine was collected every 90 min. Shifts in the 6-sulphatoxymelatonin (aMT6s) cosine acrophase from baseline to post-treatment were compared between treatments. Analyses revealed a significant additive phase-delaying effect of bright light + exercise (80.8 ± 11.6 [SD] min) compared with exercise alone (47.3 ± 21.6 min), and a similar phase delay following bright light alone (56.6 ± 15.2 min) and exercise alone administered for the same duration and at the same time of night. Thus, the data suggest that late night bright light followed by early morning exercise can have an additive circadian phase-shifting effect.

Created2016-02-26
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The development of high efficiency III-V solar cells is needed to meet the demands of a promising renewable energy source. Intermediate band solar cells (IBSCs) using semiconductor quantum dots (QDs) have been proposed to exceed the Shockley-Queisser efficiency limit [1]. The introduction of an IB in the forbidden gap of

The development of high efficiency III-V solar cells is needed to meet the demands of a promising renewable energy source. Intermediate band solar cells (IBSCs) using semiconductor quantum dots (QDs) have been proposed to exceed the Shockley-Queisser efficiency limit [1]. The introduction of an IB in the forbidden gap of host material generates two additional carrier transitions for sub-bandgap photon absorption, leading to increased photocurrent of IBSCs while simultaneously allowing an open-circuit voltage of the highest band gap. To realize a high efficiency IBSC, QD structures should have high crystal quality and optimized electronic properties. This dissertation focuses on the investigation and optimization of the structural and optical properties of InAs/GaAsSb QDs and the development of InAs/GaAsSb QD-based IBSCs.

In the present dissertation, the interband optical transition and carrier lifetime of InAs/GaAsSb QDs with different silicon delta-doping densities have been first studied by time-integrated and time-resolved photoluminescence (PL). It is found that an optimized silicon delta-doping density in the QDs enables to fill the QD electronic states with electrons for sub-bandgap photon absorption and to improve carrier lifetime of the QDs.

After that, the crystal quality and QD morphology of single- and multi-stack InAs/GaAsSb QDs with different Sb compositions have been investigated by transmission electron microscopy (TEM) and x-ray diffraction (XRD). The TEM studies reveal that QD morphology of single-stack QDs is affected by Sb composition due to strain reducing effect of Sb incorporation. The XRD studies confirm that the increase of Sb composition increases the lattice mismatch between GaAs matrix and GaAsSb spacers, resulting in increase of the strain relaxation in GaAsSb of the multi-stack QDs. Furthermore, the increase of Sb composition causes a PL redshift and increases carrier lifetime of QDs.

Finally, the spacer layer thickness of multi-stack InAs/GaAsSb QDs is optimized for the growth of InAs/GaAsSb QD solar cells (QDSCs). The InAs/GaAsSb QDSCs with GaP strain compensating layer are grown and their device performances are characterized. The increase of GaP coverage is beneficial to improve the conversion efficiency of the QDSCs. However, the conversion efficiency is reduced when using a relatively large GaP coverage.
ContributorsKim, Yeongho (Author) / Honsberg, Christiana (Thesis advisor) / Goodnick, Stephen (Committee member) / Faleev, Nikolai (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2015
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Resource-poor social environments predict poor health, but the mechanisms and processes linking the social environment to psychological health and well-being remain unclear. This study explored psychosocial mediators of the association between the social environment and mental health in African American adults. African American men and women (n = 1467) completed

Resource-poor social environments predict poor health, but the mechanisms and processes linking the social environment to psychological health and well-being remain unclear. This study explored psychosocial mediators of the association between the social environment and mental health in African American adults. African American men and women (n = 1467) completed questionnaires on the social environment, psychosocial factors (stress, depressive symptoms, and racial discrimination), and mental health. Multiple-mediator models were used to assess direct and indirect effects of the social environment on mental health. Low social status in the community (p < .001) and U.S. (p < .001) and low social support (p < .001) were associated with poor mental health. Psychosocial factors significantly jointly mediated the relationship between the social environment and mental health in multiple-mediator models. Low social status and social support were associated with greater perceived stress, depressive symptoms, and perceived racial discrimination, which were associated with poor mental health. Results suggest the relationship between the social environment and mental health is mediated by psychosocial factors and revealed potential mechanisms through which social status and social support influence the mental health of African American men and women. Findings from this study provide insight into the differential effects of stress, depression and discrimination on mental health. Ecological approaches that aim to improve the social environment and psychosocial mediators may enhance health-related quality of life and reduce health disparities in African Americans.

Created2016-04-27
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Breastfeeding has been shown to dramatically improve health outcomes for both infants and mothers. Despite recommendations by almost all world and national health organizations to breastfeed exclusively for 6 months and to continue breastfeeding for one year, this goal is not met by the majority of women in the United

Breastfeeding has been shown to dramatically improve health outcomes for both infants and mothers. Despite recommendations by almost all world and national health organizations to breastfeed exclusively for 6 months and to continue breastfeeding for one year, this goal is not met by the majority of women in the United States for multiple reasons. Health professionals, including physicians and nurses, can play a major role in educating and influencing mothers about breastfeeding, especially for women with comorbidities, taking medications, or undergoing medical procedures. An online survey was created to evaluate healthcare professionals' breastfeeding knowledge and opinions at a large hospital in Phoenix, Arizona using QuestionPro software. This survey was distributed for three weeks to the nursing and physician departments at the hospital in primarily the obstetric and post partum units. Of the seventy-nine individuals who completed the survey, the respondents were primarily female obstetric nurses. Respondents recognized the benefits of breastfeeding for both mother and infant, believed health professionals can influence the decision to breastfeed, and found a lack of support was the number one reason women discontinue breastfeeding. Despite this information, it is apparent from this survey, and similar studies in the past, that there are significant gaps in knowledge especially when it comes to contraindications to breastfeeding, medications used while breastfeeding, fluid intake during breastfeeding, and foods that can be consumed while breastfeeding. Additionally, the majority of the nurses who completed this survey did not believe their schooling adequately trained them in breastfeeding education and hands-on practice. This information could be used in future studies to guide breastfeeding education for nurses, physicians, and other health care professionals at the stated hospital and other facilities across the nation.
ContributorsConstenius, Lindsey Bowes (Author) / Bever, Jennie (Thesis director) / Kelly, Lesly (Committee member) / Arizona State University. College of Nursing & Healthcare Innovation (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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The Experimental Data Processing (EDP) software is a C++ GUI-based application to streamline the process of creating a model for structural systems based on experimental data. EDP is designed to process raw data, filter the data for noise and outliers, create a fitted model to describe that data, complete a

The Experimental Data Processing (EDP) software is a C++ GUI-based application to streamline the process of creating a model for structural systems based on experimental data. EDP is designed to process raw data, filter the data for noise and outliers, create a fitted model to describe that data, complete a probabilistic analysis to describe the variation between replicates of the experimental process, and analyze reliability of a structural system based on that model. In order to help design the EDP software to perform the full analysis, the probabilistic and regression modeling aspects of this analysis have been explored. The focus has been on creating and analyzing probabilistic models for the data, adding multivariate and nonparametric fits to raw data, and developing computational techniques that allow for these methods to be properly implemented within EDP. For creating a probabilistic model of replicate data, the normal, lognormal, gamma, Weibull, and generalized exponential distributions have been explored. Goodness-of-fit tests, including the chi-squared, Anderson-Darling, and Kolmogorov-Smirnoff tests, have been used in order to analyze the effectiveness of any of these probabilistic models in describing the variation of parameters between replicates of an experimental test. An example using Young's modulus data for a Kevlar-49 Swath stress-strain test was used in order to demonstrate how this analysis is performed within EDP. In order to implement the distributions, numerical solutions for the gamma, beta, and hypergeometric functions were implemented, along with an arbitrary precision library to store numbers that exceed the maximum size of double-precision floating point digits. To create a multivariate fit, the multilinear solution was created as the simplest solution to the multivariate regression problem. This solution was then extended to solve nonlinear problems that can be linearized into multiple separable terms. These problems were solved analytically with the closed-form solution for the multilinear regression, and then by using a QR decomposition to solve numerically while avoiding numerical instabilities associated with matrix inversion. For nonparametric regression, or smoothing, the loess method was developed as a robust technique for filtering noise while maintaining the general structure of the data points. The loess solution was created by addressing concerns associated with simpler smoothing methods, including the running mean, running line, and kernel smoothing techniques, and combining the ability of each of these methods to resolve those issues. The loess smoothing method involves weighting each point in a partition of the data set, and then adding either a line or a polynomial fit within that partition. Both linear and quadratic methods were applied to a carbon fiber compression test, showing that the quadratic model was more accurate but the linear model had a shape that was more effective for analyzing the experimental data. Finally, the EDP program itself was explored to consider its current functionalities for processing data, as described by shear tests on carbon fiber data, and the future functionalities to be developed. The probabilistic and raw data processing capabilities were demonstrated within EDP, and the multivariate and loess analysis was demonstrated using R. As the functionality and relevant considerations for these methods have been developed, the immediate goal is to finish implementing and integrating these additional features into a version of EDP that performs a full streamlined structural analysis on experimental data.
ContributorsMarkov, Elan Richard (Author) / Rajan, Subramaniam (Thesis director) / Khaled, Bilal (Committee member) / Chemical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Ira A. Fulton School of Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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DescriptionThe goal of this study is to explore the relationship between breastfeeding, postpartum depression and postpartum weight at 1 and 6 months.
ContributorsFlowers, Jenna (Author) / Reifsnider, Elizabeth (Thesis director) / Bever, Jennie (Committee member) / Moramarco, Michael (Committee member) / Arizona State University. College of Nursing & Healthcare Innovation (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
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The purpose of the study was to determine the level and type of public policy involvement among registered nurses (RN) who are members of the Arizona Nurses Association (AzNA). Furthermore, the aim of the study was to identify the knowledge base and motivation of nurses and their involvement in public

The purpose of the study was to determine the level and type of public policy involvement among registered nurses (RN) who are members of the Arizona Nurses Association (AzNA). Furthermore, the aim of the study was to identify the knowledge base and motivation of nurses and their involvement in public policy as well as the barriers and benefits. A 20- item survey was sent to all of the members of AzNA. There were 39 responses used in the analysis. The highest reported public policy activities in which the nurses had participated were: voted (90%), contacted a public official (51%), and gave money to a campaign or for a public policy concern (46%). Lack of time was the most frequently reported barrier to involvement and improving the health of the public was the most frequently reported benefit to involvement. The number of public policy education/information sources and the highest level of education positively correlate to the nurses' total number of public policy activities (r = .627 p <0.05; r = .504, p <0.05). Based on the results of stepwise linear regression analysis, the participants' age, number of education/information sources, and efficacy expectation predict 68.8% of involvement in public policy activities. The greater the number of education/information sources, the greater the number of public policy activities nurses report having participated in.
ContributorsHartman, Mykaila Corrine (Author) / Stevens, Carol (Thesis director) / Munoz, Aliria (Committee member) / Link, Denise (Committee member) / Arizona State University. College of Nursing & Healthcare Innovation (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12