In polycrystalline thin-film cadmium telluride (CdTe) solar cells, atomic defects (dopants: copper (Cu), arsenic (As); and selenium (Se) alloy) have significantly enhanced hole density and minority carrier lifetime. Density functional theory (DFT) has predicted the atomic configurations of relevant defects and their electronic structures. Yet, experimental evidence of the defects, especially their spatial distribution across the absorber, is still lacking. Herein, since it can probe local atomic structure of elements of interest with trace-elemental sensitivity, nanoprobe X-ray absorption near edge structure (XANES) spectroscopy was used to elucidate atomic structures of Cu, As, and Se. After XANES spectra were measured from CdTe devices, the atomic information was extracted from the measured spectra by fitting them with reference spectra, which were simulated from 1) point defects and grain boundaries (GBs) predicted by DFT; 2) secondary phases which could form under processing conditions. XANES analysis of various device architectures revealed structural inhomogeneities across the absorbers from point defects to secondary phases. The majority of the Cu dopant atoms form secondary phases with surrounding atoms even inside the absorbers, explaining the low dopant activation. When entering the target lattice site (Cd), Cu forms a complex with chlorine (Cl) and becomes a donor defect, compensating hole density. Compared to Cu, As dopant tends to enter the target site (Te) more frequently, explaining higher hole density in As-doped CdTe. Notably, As on the Te site forms neutral charged complexes with Cl. Although they are not as detrimental as the Cu-Cl complex, the As-Cl complexes may be responsible for low dopant activation and compensation observed in As-doped CdTe devices. Complementary to the DFT prediction, this work provided the distribution of Se local structures across the absorber, specifically the variation of Se-Cd bond lengths in differently performing areas. Under environmental stressors (heat and light), it showed atomic reconfiguration of Se and Cl at GBs, and Se diffusion into the bulk, co-occurring with device degradation. This framework was also extended to study defect evolution in other thin-film solar cells (CIGS and emerging perovskite). XANES analysis has shed light on atomic defects governing solar cell performance and stability, which are crucial in pushing the efficiency toward the theoretical efficiency limit.

This dissertation research study examined the use of a social-emotional learning curriculum framework (SELCF) to respond to opportunities for growth in social-emotional learning (SEL) skills among students in the early childhood classroom. The five skills addressed within this study include empathy, emotional intelligence, social problem-solving, communication, and self-advocacy among kindergarten students following the COVID-19 global pandemic. This study employed an action research mixed-methods concurrent triangulation framework where data were collected through semi-structured interviews and the collection of participant-produced illustration artifacts to create a comprehensive and holistic data set. Pre-interview data shows that the participant group had minimal background knowledge of the five social skills examined during the study. Post-interview data shows that participants made significant growth in all five skills taught within the SELCF. The quantitative and qualitative data is triangulated to reinforce the findings of this mixed-methods action research project. Through thoughtful and intentional instruction delivered to kindergarten students through the SELCF, all students showed statistically significant growth in all five skills assessed. Data triangulation provided further insight into participants’ critical thinking and cognition to show a deeper understanding of the social-emotional learning skills addressed in the SELCF. By providing young children with effective instruction and opportunities to practice their social-emotional skills, educators pave the way for children to be successful and capable members of society.

As brands increasingly take stances on divisive political issues, it is essential to understand how consumers' political ideology influences reactions to such brands. This research examines the effect of US consumers' political ideology on their likelihood of retaliating against politically activist brands. I find that liberals (vs. conservatives) exhibit larger retaliation effects against brands that take an opposing (vs. supporting or neutral) stance on a divisive political issue. The principles of fair market ideology can explain this disparity. Conservatives (vs. liberals) are more likely to view the market as self-regulating and inherently just, reducing their tendency to retaliate against brands they oppose. Instead, conservatives, view large corporations as pivotal to the economy and are thus less likely to engage in personal or institutional intervention.

Within percussion pedagogy, rudiments serve as foundational components used to develop rhythmic and technical proficiency. While American, French, and Swiss rudimental drumming share common rudiments, there exist nuanced distinctions between these styles. Similarly, hip-hop rapper’s “flow” has evolved amid diverse regional, social, and emotional influences, shaping their rhythmic articulation. This study centers on the “golden age” of hip-hop (1986-1996), aiming to identify recurring patterns of “flow” and potential confluences between percussive rudiments and how rappers’ structure their rhythmic and melodic language. The examination of “flow” represents a relatively recent discourse within music theory, attracting scholarly attention concerning analytical methodologies using computer programs and diverse analytical lenses. Notably, scholars specializing in this domain have laid foundational groundwork, offering comprehensive insights into the nuanced aspects of flow dynamics. Although there exists a substantial body of research on flow analysis, limited scholarly attention has explored the correlation between rap music and the percussive facets inherent in snare drum performance. This study elucidates the connection between the intricacies of hip-hop flow and rudimental snare drum playing, culminating in four snare drum etudes emulating the flow of specific artists and regions.

The practice strategies that musicians employ can be made more effective by leveraging existing research about memory and learning. Musicians often use strategies that feel intuitive, such as massed practice and rote repetition, but that research has proven ineffective. When they do employ strategies that are effective, such as varied practice and chunking, they often do not understand the reasons why they are effective and therefore cannot use the principles behind effective learning to generate new approaches when faced with an unfamiliar challenge or learning plateau. In this paper, I propose that, through developing knowledge of the research surrounding learning and memory, musicians can acquire insight into the learning process and develop the ability to self-generate effective practice strategies that address issues specific to their own practice. As a result, they can avoid common learning pitfalls and gain greater confidence in their ability to approach learning complicated skills and taking on big projects. This paper examines and distills recent research of effective learning into an in-depth and practical document for use by musicians. Additionally, this document interprets and applies existing research-based learning strategies—such as retrieval practice, spaced repetition, varied practice, interleaved practice, and chunking—to musical practice through the lens of contemporary percussion repertoire. Readers of this work will develop an in-depth understanding of memory and learning and be able to apply that information practically and immediately in their own practice.

“Finding Elsewhere: Selected Works by Maia Cruz Palileo and Jeanne F. Jalandoni” explores how these artists grapple with colonial legacies and intergenerational trauma through embodied practices in Palileo’s Kapatid (sisters) (2018) and Jalandoni’s Take Up the Brown (2018). Additionally, this study assesses how Jalandoni’s Transience (2022) transcends categorical limitations in media, place, and time as a channel of connection to the Philippines. Through the study of the work on paper Kapatid (sisters) by Filipinx American artist, Maia Cruz Palileo (they/them), I assess how Palileo embodies care within their practice. I study Kapatid (sisters) in relation to Dean Worcester’s colonial-era photography of the Philippines which Palileo references in their research. This integrated analysis determines how Palileo’s work manifests in opposition to Worcester’s imperial perspective. In my study of multimedia work Take Up the Brown (2018) by Filipina American artist Jeanne F. Jalandoni (she/her), I examine how Jalandoni embodies her own testimony of navigating historical erasure and historical recovery as a result of residual imperial subjugation. I deconstruct Jalandoni’s usage of Louis Dalrymple’s propaganda cartoon, School Begins (1899), and its close association with the Rudyard Kipling poem, “The White Man’s Burden” (1899). By historically contextualizing her archival references, I examine how Jalandoni’s visual testimony of colonial history is made tangible for viewers. In the second section of my study, I examine Jalandoni’s oil and textile work, Transience (2022) to explore how Jalandoni labors towards a connection with her ancestral homeland while solidifying her own bi-cultural identity as a Filipina American. I delve into Jalandoni’s engagement with family oral history, family photographs, temporal methods, and embodied practices to understand how she forges connections with ancestors, and ultimately, with the Philippines. Furthermore, I examine Transience as an Elsewhere, a methodological model and aesthetic that foregrounds identity-making and reconnection in diaspora.

The purpose of this mixed methods action research study was to implement digital outreach strategies, which would enhance students’ motivation to complete financial aid requirements and scale the departments’ more time-consuming counseling efforts. Using self-determination theory as the primary framework, I implemented the use of a series of emails and text messages sent by students’ admissions recruiters to a group of first-year students admitted to a large, public Land Grant Institution. The messages were framed to enhance students’ autonomy, competence, and relatedness the summer before they enrolled. The digital campaign was also supported by supplemental opportunities, including virtual appointments, a targeted webpage, and virtual workshops. Following the intervention, I compared the enrollment and financial outcomes of participants and a comparison group. Intervention and comparison groups were also surveyed about their perceived levels of self-determination and satisfaction prior to high school graduation and the summer before enrolling at the university. Additionally, selected students from both groups were interviewed during their first semester at the university. There were no statistically significant differences in students’ perceived self-determination, satisfaction, enrollment, and financial aid outcomes following the intervention. Relatedness increased significantly across the two times of assessment indicating all students developed stronger relationships with those from the university’s financial aid and admissions offices, which boded well for students just entering the university. In logistic regression analyses, Pell Grant eligibility was a significant factor associated with negative financial aid outcomes of owing a student account balance of $500 or greater and not completing financial aid requirements on time. Taken together with qualitative interviews, these findings suggest a need for additional one-on-one or other high-touch support methods, to support admitted students in the financial aid process.

This thesis critically examines the dominant narrative constructed in US-based news media about the United States’ institutions of violence, the Black Lives Matter movement (BLM), and the Immigrant Rights (IR) movements. Engaging multiple disciplines across the social science that engage race, immigration, the media, and American politics, the thesis situates the media’s role in racial injustice and nation-state violence against the Black and Immigrant communities. White Supremacy is deeply part of the United States' past and present, and the news media plays a critical role in capturing and framing the challenges to entrenched systemic racism led by social movement activism. The news media is situated in a powerful public position, capable of leading or supporting social justice work as well as further entrenching systems of oppression and injustice. This thesis explores whether the media challenges or reinforces the nation-state’s violent and racist institutions and practices. To operationalize the empirical work, the thesis asks how the news media (de)centers and (de)legitimizes social movements, impacted communities, and the nation-state when reporting on BLM and IR. Two original datasets of 8,742 news articles (for BLM) and 3,372 news articles (for IR), covering 2013 to 2023, are analyzed using machine learning techniques like named entity recognition and semantic networks of text, along with qualitative content analysis of select months as critical case studies. The thesis reveals how news media serves as a governance tool capable of stifling dissent by decentering the racial injustices that legitimize movement tactics and simultaneously centering partisan politics and the nation-state.

This dissertation presents a volume filtering framework to solve particle-laden flows. Particle-laden flows are studied, employing the well-established Euler-Lagrange method, using the point-particle approximation. This approach requires the filter width to be much larger than the particle diameter. The method assumes that the particle is smaller than the Kolmogorov length scale. This thesis investigates how inertial particles at semi-dilute volume fractions modulate the flow characteristics for particles smaller than 1 in wall units, when dispersed within wall-bounded channel flows at friction Reynolds number of 180. The simulations are performed with 4 way coupling in order to account for high local concentration of particles, to capture mechanisms such as turbophoresis and preferential concentration. We show that drag attenuation or augmentation is determined by the particle inertia. As particle size is increased greater than 1 in wall units, the regime becomes finite-sized, requiring an interface-resolved description. To do this a novel Immersed Boundaries (IB) framework based on the concept of volume-filtering called the Volume-Filtered Immersed Boundary (VF-IB) method is presented. Transport equations are obtained by volume-filtering the Navier-Stokes equation and accounting for the stresses at the solid-fluid interface. Boundary conditions are transformed into bodyforces that appear as surface integrals on the right hand side of the filtered equation. The approach requires the filter width to be much smaller than the particle diameter in order to accurately resolve the interfacial dynamics. Several canonical tests are conducted for both stationary and moving immersed solids and report comparable results to the experimental and/or body-fitted simulations. Keep in mind, the VF-IB method reverts back to the Euler-Lagrange formulation if the filter width is significantly greater than the particle diameter. An artifact of volume-filtering is the emergence of unclosed terms we define as the sub-filter scale term. In order to characterize the contribution of this term on the solution, a more simpler case of a 2-D varying coefficient hyperbolic equation that has an exact solution is looked into. It is observed that the sub-filter scale term scales inversely with the square of the filter width. For fine interface resolution (i.e. small filter width), this value can be ignored with negligible effect to the accuracy of the numerical solution. However for coarse interface resolution (i.e. large filter width), including the sub-filter scale term significantly increases the accuracy of the numerical solution

In the realm of medical diagnostics, achieving heightened accuracy is paramount, leading to the meticulous refinement of AI Models through expert-guided tuning aiming to bolster the precision by ensuring their adaptability to complex datasets and optimizing outcomes across various healthcare sectors. By incorporating expert knowledge into the fine-tuning process, these advanced models become proficient at navigating the intricacies of medical data, resulting in more precise and dependable diagnostic predictions. As healthcare practitioners grapple with challenges presented by conditions requiring heightened sensitivity, such as cardiovascular diseases, continuous blood glucose monitoring, the application of nuanced refinement in Transformer Models becomes indispensable. Temporal data, a common feature in medical diagnostics, presents unique challenges for Transformer Models characterized by sequential observations over time, requiring models to capture intricate temporal dependencies and complex patterns effectively. In the study, two pivotal healthcare scenarios are delved into: the detection of Coronary Artery Disease (CAD) using Stress ECGs and the identification of psychological stress using Continuous Glucose Monitoring (CGM) data. The CAD dataset was obtained from the Mayo Clinic Integrated Stress Center (MISC) database, which encompassed 100,000 Exercise Stress ECG signals (n=1200), sourced from multiple Mayo Clinic facilities. For the CGM scenario, expert knowledge was utilized to generate synthetic data using the Bergman minimal model, which was then fed to the transformers for classification. Implementation in the CAD example yielded a remarkable 28% Positive Predictive Value (PPV) improvement over the current state-of-the-art, reaching an impressive 91.2%. This significant enhancement demonstrates the efficacy of the approach in enhancing diagnostic accuracy and underscores the transformative impact of expert-guided fine-tuning in medical diagnostics.