The growth of barrier-type anodic alumina films formed by anodizing relatively rough substrates has been shown to proceed by high field ionic conduction. As a result of the ionic transport and the induced plasticity, smoothing of the oxide surfaces and the metal/oxide interfaces arises. However, such a smoothing model was deduced from topographical observations and, therefore little insight was gained about the transport mechanism leading to the flattening of the anodized specimens. Recently, the development of porous anodic alumina has been demonstrated to proceed by coupled ionic migration and material flow resulting from the field-induced mechanical stress. For rough metal surfaces, the electric field distribution is non-uniform across the specimen surface. Considering the square-dependence of the electrostrictive stress on the electric field and the distribution of the electric field across surface, a significant gradient of mechanical stress may arise across the anodic oxide layer during anodizing. As a result, stress-driven transport may participate, in addition to high field ionic conduction, to the smoothing of the specimen surface. Transport mechanisms were investigated during anodizing of patterned superpure aluminium specimens, by examination of the distributions of incorporated species, used as markers and tracers. The nature of the migration processes have been determined in correlation with the changes in the concentration of the tracer profiles as well as the variations in the anodic oxide film compositions.

Doctor of Philosophy / Department of Industrial and Manufacturing Systems Engineering / Shing I. Chang / Profile analysis has drawn attention in quality engineering applications due to the growing use of sensors and information technologies. Unlike the conventional quality characteristics of interest, a profile is formed functionally dependent on one or more explanatory variables. A single profile may contain hundred or thousand data points. The conventional charting tools cannot handle such high dimensional datasets. In this dissertation, six unsolved issues are investigated. First, Chang and Yadama’s method (2010) shows competitive results in nonlinear profile monitoring. However, the effectiveness of removing noise from given nonlinear profile by using B-splines fitting with and without wavelet transformation is unclear. Second, many researches dealt with profile analysis problem considering whether profile shape change only or variance change only. Those methods cannot identify whether the process is out-of-control due to mean or variance shift. Third, methods dealing with detecting profile shape change always assume that a gold standard profile exists. The existing profile shape change detecting methods are hard to be implemented directly. Fourth, multiple nonlinear profiles situation may exist in real world applications, so that conventional single profile analysis methods may result in high false alarm rate when dealing multiple profile scenario. Fifth, Multiple nonlinear profiles situation may be also happened in designs of experiment. In a conventional experimental design, the response variable is usually considered a single value or a vector. The conventional approach cannot deal with when the format of the response factor as multiple nonlinear profiles. Finally, profile fault diagnosis is an important step after detecting out-of-control signal. However, current approaches will lead to large number of combinations if the number of sections is too large. The organization of this dissertation is as following. Chapter 1 introduce the profile analysis, current solutions, and challenges; Chapter 2 to Chapter 4 explore the unsolved challenges in single profile analysis; Chapter 5 and Chapter 6 investigate multiple profiles issues in profile monitoring analysis and experimental design method. Chapter 7 proposed a novel high-dimensional diagnosis control chart to diagnose the cause of out-of-control signal via visualization aid. Finally, Chapter 8 summarizes the achievements and contributions of this research.

One of the degradation processes of zirconium-based nuclear fuel assemblies is irradiation-induced growth, an anisotropic, stress-independent, macroscopic deformation mechanism that elongates fuel cladding tubes axially. Irradiation-induced growth is driven by the irradiation-induced formation of dislocation loops, where the evolution of the loop structure can be complex, with the initial formation of loop generating transient growth, while the later formation of component dislocation loops, or loops, leads to accelerated growth. A full mechanistic understanding of loop nucleation is as yet unforthcoming. This thesis utilizes the diffraction peak broadening analysis software, named extended Convolutional Multiple Whole Profile, to study the dislocation structure evolution of neutron- and proton-irradiated zirconium alloys in order to validate proton-irradiation as a effective tool for the study of irradiation damage in relation to irradiation-induced growth. The diffraction profiles obtained exhibit unexpected features present in the tails of the Bragg peaks, tentatively attributed here to either strained regions of matrix, or diffuse scattering from severely distorted regions around nucleating precipitates, both originating from an increased solute concentration. The diffraction results indicate that the proton-irradiated samples exhibit qualitatively similar behaviours as seen from neutron-irradiation, such as a threshold irradiation dose before the formation of loops, however, a continued increase of loop dislocation density determined from peak broadening analysis is not observed by transmission electron microscopy. It is also shown that the Nb-containing Low-Sn ZIRLO® alloy has a lower dislocation density than the Nb-free Zircaloy-2 after the formation of loops correlating well with the relative irradiation-induced growth behaviours observed in- reactor. A correlation between a reduction in the loop dislocation density and the formation of loops is observed in Low-Sn ZIRLO® and Zr-1.60Sn-0.033Fe, providing support for the hypothesis that vacancy loops transform into loops. Zr- 0.61Sn-0.024Fe and Zr-1.60Sn-0.033Fe alloys show a rapid increase in the loop dislocation density in the initial stages of proton-irradiation, likely due to the low irradiation-resistance of the precipitates present in these alloys.

This dissertation addresses two critical issues in the deformation of nc metals and alloys: (1) A stress-induced genuine grain growth after the plastic deformation rather than just a change of the grain shape; (2) A systematically quantitative study of micrsostructural evolution during the plastic deformation. These two critical issues point to the deformation of nc materials with the average-grain sizes within the range of 10 to 50 nm, which is the most interesting and controversial region in the current time. The current study provides a systematic and detailed microstructural evolution for this region, which is definitely beneficial for the investigation of the deformation mechanism in this region, especially for the simulation. The main experimental and data-analysis methods employed in this research are synchrotron high-energy X-ray diffraction, X-ray line profile analysis, and texture analysis. The combination of these methods is beneficial to the accurate microstructural interpretation of the bulk materials.

<p>Eating disorders pose a serious threat to the physical and mental health of those who suffer from them. Given the impact of these disorders and difficulty treating them, it is important to understand the nature of them and factors involved in their development and maintenance. The empirical investigation of eating disorders is made difficult by the extreme heterogeneity seen within current DSM-IV diagnostic categories. Research on emotion regulation in eating disorders is rising, yet scant in terms of identifying specific difficulties and points of intervention. The proposed study focused on the construct of emotion regulation and its relation to the eating disorders by: (1) empirically identifying groups of eating disorder participants based on symptoms and (2) examining specific difficulties in emotion regulation capacities in each of the identified groups of eating disorder participants and (3) identifying whether difficulties in emotion regulation contribute to eating disorder symptom severity. A clinical sample of individuals with eating disorders was classified into subgroups based on symptom frequency using latent profile analysis. The most parsimonious and best fitting model was a four-profile solution which resulted in four distinct subgroups. Profile 1 consisted of individuals who endorsed moderate restriction and occasional binge eating and vomiting, all at a subclinical level. Profiles 2, 3, and 4 all met criteria for bulimia nervosa and consisted of individuals who engaged in restriction, binge eating, and purging though in varying degrees. When these groups were compared to a sample of college aged healthy control participants using multivariate analysis of variance, results indicate that individuals in profile 1, which comprised 71% of the sample, experience greater difficulty with emotion regulation in the areas of awareness, nonacceptance, and perceived access to strategies to help them feel better. Results of three hierarchical regression analyses showed that difficulties in emotion regulation did not significantly contribute to symptom severity as anticipated..</p> / Dissertation

Circumscription and Compromise theory suggests self-concept and sex stereotype explain occupational preferences, including preferences for science, technology, engineering and mathematics (STEM). Support exists for sex differences between males and females in both science degrees and science careers. The main thrust of observed sex differences in science lies in the development of occupational interest, as it has been suggested females are encouraged away from science due to stereotypes and social pressure. The present study evaluates high school juniors and seniors (n = 295) to explore their preference for science as indicated by science motivation, attitude, academic experience, and interest. Latent Profile Analysis was used to model profiles of preferences for science with a person-centered approach. Then, the impact of self-concept variables was explored and four profiles of science interest were identified. Sex differences were identified based on science interest, but were not always in favor of males. Covariate analysis indicates vocabulary ability and personality as significantly different for students in the high science interest profile. Implications of these results and future research directions are discussed.

abstract: Organizational classifications are critical to a wide variety of stakeholders. Within the domain of higher education, researchers use established classifications for sample selection or within empirical models to account for unobserved organizational characteristics. Colleges and universities, as well as their political principals, often use classifications to form peer-groups and reference sets through which organizational performance is assessed. More broadly, classifications provide aspirational archetypes to an organizational field. Using American higher education as the empirical context, this dissertation introduces Latent Profile Analysis (LPA) as a method to identify the structure of an organizational field and to classify organizations within this structure. Using measures of model fit and concerns for interpretability, this investigation determined that 13 distinctive organizational designs are present in the field of American higher education. Derived groupings are compared to the 2018 Basic Classification from the Carnegie Classification of Institutions of Higher Education. Opportunities and challenges for operationalizing this derived classification are discussed. / Dissertation/Thesis / Doctoral Dissertation Public Administration and Policy 2020

Aboard the International Space Station, potable water will likely be produced from recycled wastewater. The National Aeronautic and Space Administration (NASA) plans to use iodine as a disinfectant, and, consequently, the formation of iodinated disinfection by-products (IDBPs) requires investigation. Objectives of this research were to determine possible precursors of IDBPs, identify IDBPs formed, and apply flavor profile analysis (FPA) as a tool to evaluate water qaulity. Experiments were performed by separately reacting iodine with each of the following organic compounds: methanol, ethanol, 1-propanol, 2-propanol, 1-methoxy-2-propanol, acetone, and formaldehyde. NASA previously identified all of these compounds in wastewater sources under consideration for recycling into potable water. Experiments were performed at pH 5.5 and 8, iodine concentrations of 10 and 50 mg/L, and organic concentrations of 5 and 50 mg/L. Gas chromatography/mass spectrometry was used to identify and monitor the concentrations of organic species. Spectrophotometry was used to monitor the iodine concentration. Acetone was the only compound identified as an IDBP precursor and it reacted to produce iodoacetone and iodoform. Concentrations of iodoform from 0.34 mg/L to 8.637 mg/L were produced at conditions that included each pH level, iodine concentration, and acetone concentration. The greatest iodoform concentration was produced at pH 8 from 50 mg/L of iodine and acetone. FPA indicated that the odor threshold concentration (OTC) of iodoform was 1.5 ug/L, and the OTC of iodine was 500 ug/L. Both iodine and iodoform have medicinal odors, making it difficult to distinguish each compound when present in a mixture. / Master of Science

Over the first half of the present study the Mini-Mult (MM1), a brief form of the Minnesota Multiphasic Personality Inventory (MMPI), was compared with the standard MMPI in relation to eleven criteria classifications. These criteria were composed of the profile analysis classifications of Marks and Seeman (1963). Pearson product-moment correlations between the MM1 and MMPI failed to reach statistical significance for any of the eleven criteria. As based on the information gained, a correction factor was devised and added to the MM1. Subsequently, the second half of the study involved a comparison between the HMPI and the revised MM. This revised test was termed the MM2. In only two of eleven criteria cases did the correlation between the MM2 and MMPI reach statistical significance. However, for nine of the eleven criteria the MM2 did obtain a higher positive correlation with the MMPI than did the MM1. Such results indicate that the proposed correction factor is a step in the right direction and deserving of continued investigation. Although the MM2 as it presently stands cannot be validy substituted for the MMPI, continued research in the area of modifying its correction factor can yield it a useful clinical tool.

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