Sustainable Built Environments Senior Capstone Project / This capstone aims to study what types of sustainable renovation improvements would work best on older commercial buildings in Tucson. The issue being, what different types of upgrades are compatible with the types of buildings and environment in the Tucson area? This was determined with researching and comparing the data from three older buildings, which have undergone renovations and also received LEED certification. The results were significant in that the buildings studied had many similar improvements such as, installing high efficiency HVAC, upgrading insulation, using natural lighting to reduce artificial along with the usage of LED and or CFL bulbs. Low flow water fixtures were also used in all buildings to reduce water usage. The differences were the building in Phoenix also installed solar panels, along with a solar chimney for cooling, as the other two did not due to their locations in Illinois and Michigan. When these renovations were analyzed, many could be utilized in the Tucson environment. However, depending on the type of structure being renovated, the installation of HVAC, and the need for insulation could vary, due to some older buildings being brick or adobe.

Regression models with a scalar response and a functional predictor have been extensively studied. One approach is to approximate the functional predictor using basis function or eigenfunction expansions. In the expansion, the coefficient vector can either be fixed or random. The random coefficient vector is also known as random effects and thus the regression models are in a mixed effects framework. The random effects provide a model for the within individual covariance of the observations. But it also introduces an additional parameter into the model, the covariance matrix of the random effects. This additional parameter complicates the covariance matrix of the observations. Possibly, the covariance parameters of the model are not identifiable. We study identifiability in normal linear mixed effects models. We derive necessary and sufficient conditions of identifiability, particularly, conditions of identifiability for the regression models with a scalar response and a functional predictor using random effects. We study the regression model using the eigenfunction expansion approach with random effects. We assume the random effects have a general covariance matrix and the observed values of the predictor are contaminated with measurement error. We propose methods of inference for the regression model's functional coefficient. As an application of the model, we analyze a biological data set to investigate the dependence of a mouse's wheel running distance on its body mass trajectory. / Science, Faculty of / Statistics, Department of / Graduate

Halide perovskites have some unique advantages as optoelectronic materials. Metal halide perovskites have been attracting enormous attention for applications in optoelectronic devices such as photodetectors, light-emitting devices and field-effect transistors. The remarkable semiconducting properties have been intensively investigated in recent years. However, the performance of optoelectronics devices based on the conventional perovskite is limited by the ion migration, the mobility of the carriers and the light absorption in the near infrared region and so on. In a decade, numerous attempts are studied to further breakthrough the limitations using both physical and chemical methods. This dissertation is devoted to overcoming the drawbacks by integrating the state-of-art perovskite with other functional materials and to further deciphering the carrier transport mechanics behind the mixed dimensional heterostructures. Field-effect transistors are the workhorse of modern microelectronics. Proof-of-concept devices have been made, utilizing solution-processed perovskite as transistors. Beyond the Field-effect transistors, photodetectors can be construct with a transistor configuration. In this dissertation, we exploited Au dimers with structural darkness to enhance the light harvesting, and utilize sorted semiconducting single-walled carbon nanotubes to enhance the conductivity of thin-film. At last, we developed a hybrid memtransistor, modulable by multiple physical inputs using hybrid perovskite and conjugated polymer heterojunction channels to realize neuromorphic computing.

Indiana University-Purdue University Indianapolis (IUPUI) / The programs developed in this study are examples of how a personal computer can aid the delivery of dental care. The versatility of the computer depends on the availability of a variety of programs specifically developed for dentistry, without which computers will have little impact on treatment. Moyers' analysis adapted for the Apple II and its research modification are computer programs developed specifically for dentistry. Accurately predicting the mesiodistal widths of the unerupted permanent canines and premolars in the mixed dentition can lead to orthodontic treatment that is optimally timed, with desirable facial and dental results. The stage of the mixed dentition constitutes the most intricate period in the development of the occlusion; any small anomaly occurring in this stage can pose complicated problems for the permanent dentition, requiring a more extensive and expensive mechanotherapy. Malocclusion is a developmental problem. Analysis of dental crowding and its relationship to tooth size and arch dimensions yielded the following results for the maxillary and mandibular arches: 1. Statistically different values for tooth size were noted between crowded and noncrowded groups, with crowded individuals having larger teeth. 2. Arch perimeter and arch depth were significantly smaller in crowded groups than noncrowded groups. 3. No significant differences were noted between crowded and noncrowded groups in arch width or symmetry. 4. Significant differences were demonstrated in the eccentricity value of an ellipse for crowded and noncrowded cases. This study suggests that dental crowding is associated with both small dental arches and large teeth. Therefore, greater consideration may be given to those treatment techniques which increase dental arch width, length, and perimeter. This is especially relevant in younger patients whose dentitions are in the deciduous and mixed stages of development. Further investigation into the relationship of dental crowding and arch shape with a larger sample might be productive. The eccentricity of a curve should be used to evaluate pre and post orthodontic treatment. Modifications to the basic computer program could include prediction values for Black Americans, cephalometric value interpretation, and the Bolton and Ponts analysis as a comprehensive diagnostic computer package.

The occurrence of pre-existing type 1 and type 2 diabetes in pregnancy has been on the rise, parallel with the current “diabetes pandemic” (Albrecht et al., 2010; Coton et al., 2016; Feig et al., 2014; The Lancet, 2011). Currently, pre-existing diabetes affects up to 2.4% of pregnancies around the world (Deputy et al., 2018; Fadl & Simmons, 2016; Lopez-de-Andres et al., 2020; Tutino et al., 2014; Wahabi et al., 2017). Importantly, women with type 1 and type 2 diabetes are at a high risk of experiencing perinatal complications. Perinatal complications range from neonatal hypoglycemia to fetal and infant death (Feig et al., 2014; Kishida et al., 1989). The risk of complications is related to maternal glycemia; maintaining tight glycemic control within the recommended ranges for pregnancy is associated with a reduced risk of adverse outcomes (Feig et al., 2018; Inkster et al., 2006; Tennant et al., 2014). To achieve this, women experience a heavy burden of diabetes self-management during pregnancy. Little is known regarding the predictors of glycemic control during pregnancies complicated by type 1 and type 2 diabetes and their relationship with self-management factors, such as self-efficacy. Furthermore, the impact of these factors in combination with women’s pregnancy experiences has not been explored. The objective of this thesis was to explore how self-management and support experiences help explain glycemic control among women with pre-existing diabetes in pregnancy. There were four overarching questions: (a) What are the predictors of glycemic control during pregnancy among women with pre-existing diabetes? (b) What is the experience of managing diabetes during pregnancy? (c) What are the diabetes self-management education and support needs during pregnancy among women with pre-existing diabetes? (d) How do the self-management and support experiences of women with pre-existing diabetes in pregnancy help explain their glycemic control? The results of this sandwich thesis aim to answer these questions. The findings showed that women achieved tight glycemic control during pregnancy as they were motivated by the worry of complications for their unborn child. Fear related to complications, feeling unsupported by the healthcare team and a lack of connection with other mothers with diabetes contributed to compromised mental health. Future research should explore the development, implementation and evaluation of interventions to increase mental health support, peer support and support from the healthcare team for this vulnerable population. / Thesis / Doctor of Philosophy (PhD) / Expectant mothers with type 1 and type 2 diabetes have a high risk of complications related to their glucose levels during pregnancy. The relationship between glucose control, mothers’ self-confidence in managing diabetes and their experiences during pregnancy is not well understood. This study explored the factors that affect glucose control and their relationship with the support needs during pregnancy of mothers with type 1 and type 2 diabetes.

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Mixed models are powerful tools for the analysis of clustered data and many extensions of the classical linear mixed model with normally distributed response have been established. As with all parametric models, correctness of the assumed model is critical for the validity of the ensuing inference. Model robust regression techniques predict mean response as a convex combination of a parametric and a nonparametric model fit to the data. It is a semiparametric method by which incompletely or incorrectly specified parametric models can be improved through adding an appropriate amount of a nonparametric fit. We apply this idea of model robustness in the framework of the linear mixed model. The mixed model robust regression (MMRR) predictions we propose are convex combinations of predictions obtained from a standard normal-theory linear mixed model, which serves as the parametric model component, and a locally weighted maximum likelihood fit which serves as the nonparametric component. An application of this technique with real data is provided. / Ph. D.

This thesis is an exercise in ideas of two realms, theoretical and practical, and an effort to mix the two to create architecture. The theoretical thesis is exemplified in the pairings of photos seen on the bottom of each page, taken from Second View: The Rephotographic Survey Project. As the reader examines the pairs of photos changes over time can be seen in each. Typically the greatest changes are manifestations of man's existence. I have treated this as a point of departure for the technical thesis of Permanence and Temporality. Man's temporal existence creates permanent reminders in the permanent structure of the earth. This thesis explores the nature of permanence and temporality in materials and uses them to express the classic dichotomy of service and served. As a practical thesis the project focuses on providing better urban living through natural light, natural ventilation, and the provisions for community and interaction with nature. A modification of Le Corbusier's Unite d'Habitation was explored by narrowing the building to bring natural light further into the unit while widening the unit to get natural light and ventilation even to the service spaces. / Master of Architecture

This study builds on the National Capital Planning Commission's (NCPC) 50 year Master Plan for Washington D.C. It focuses on several of the NCPC's five key goals; to build on the legacy of the historic L'Enfant and McMillan plans, unify the city, with the Capitol as its center, use new buildings to stimulate economic development, and integrate the Potomac and Anacostia Rivers to the city's public life. This site and project has a historical tradition. A pedestrian bridge was proposed to connect SouthWest D.C. to Haines Point with a new aquarium, which was eventually located in Baltimore, anchoring the Haines Point side. This proposal was never realized. Integral to this project is the development of the masterplan for SouthWest D.C. It proposes reinforcing the existing city grid, while developing small plazas along the water's edge. A major plaza is located at the intersection of the bridge and the city. It is the masterplan and orientation of the bridge that make it a viable development of the NCPC's masterplan. The project proposes an inhabitable bridge continuing the grid of Washington across the channel. Commercial shops and offices juxtapose views north to the city's skyline. Housing units float ontop of the bridge creating a vibrant daily cycle of activity. Public walkways and plazas provide vistas, places to gather, meet and reflect. It is the combination of functions that make the bridge a viable attraction. Finally, the intersection of public and private space on the bridge creates vibrant city life. This bridge contributes to the rich texture of Washington. / Master of Architecture