My approach to performing contemporary music, like many others, is centeredaround storytelling that merges the intention of the composer with my own interpretation. The balance between the two is unique for every work, as well as the sources of inspiration that shape each interpretation. In some cases, it works well to rely heavily on the historical context of the piece and the specific inspiration and process of the composer. In other cases, the composer desires more freedom and flexibility in the performance of their work, and the story of the piece is woven from the threads of personal stories, emotions, and imagery of the performer. For this project, I made audio recordings of three pieces including Seare Farhat’s Three Children’s Songs for Singing Percussionist, Keiko Abe’s Marimba d’Amore, and Thomas Kotcheffs Obbligato Snare Drum Music No. 1: The Power of Love. I then used these recordings to make music videos that blend elements of pop music videos and classical performance videos, using performance footage as well as narrative and abstract visuals to experiment with video making as a creative outlet while building a performance portfolio that represents me as an artist. In addition to a reflection of my process, this document is also designed as a resource for performers who are interested in learning how to make their own audio and video recordings, covering topics including project planning and preparation, working with collaborators, selecting gear, practicing for studio recordings, and designing and producing videos.

Animal pose estimation (APE) is utilized in preclinical research settings for various neurological disorders such as Parkinson's disease (PD), Huntington's disease (HD) and multiple sclerosis. The technique includes real-time scoring of impairment in the animals during testing or video recording. This is a time-consuming operation prone to errors due to visual fatigue. To overcome these shortcomings, APE automation by deep learning has been studied. The field of APE has gone through significant development backed by improvements in deep learning techniques. These developments have improved 2D and 3D pose estimation, 3D mesh reconstruction and behavior prediction capabilities. As a result, there are numerous sophisticated tools and datasets available today. Despite these developments, APE still lags behind human observer scoring with respect to accuracy and flexibility under complex scenarios. In this project, two critical challenges are being addressed within the context of neurological research focusing on PD. The first challenge is about the lack of comprehensive diverse datasets necessary for accurate training as well as for fine-tuning deep learning models. This is compounded by the inherent difficulty in working with uncooperative rodent subjects, whose unpredictable behaviors often impede reliable data collection. The second challenge focuses on reduction in variation of scores that result from being scored by different evaluators. This will also involve tackling bias and reducing human error for the purpose of reliable and accurate assessments. In order to address these issues, systematic data collection and deep learning in APE have been utilized to automate manual scoring procedures. This project will contribute to neurological research, particularly in understanding and treating disorders like PD. The goal is to improve methods used in assessing rodent behavior which could aid in developing effective therapeutics. The successful implementation of an automated scoring mechanism could set a new standard in neurological research, offering insights and methodologies that are more accurate and reliable.

Phenolic polymers like polyphenols and polyphenylenes have several industrial applications including electrical insulation, specialty membranes, and packings but are typically synthesized under harsh reaction conditions and require hazardous chemicals like formaldehyde. Hydroxycinnamic acids, such as p-coumaric acid (p-CA), are aromatic derivatives of lignin hydrolysates, an underutilized and promising renewable feedstock for production of phenolics and phenolic polymers. Recently a strain of Corynebacterium glutamicum has been created by the Joint BioEnergy Institute (JBEI) which expresses phenolic acid decarboxylase (PAD), an enzyme which catalyzes the reaction of p-CA to 4-vinylphenol (4-VP). Further, a deletion of the phdA gene prevents assimilation of p-CA, thereby increasing 4-VP yield. 4-VP is a substituted phenol which can be polymerized to poly(4-vinylphenol) (PVP) in the presence of ligninolytic enzymes like laccases or peroxidases. This work explores in situ polymerization of 4-VP to PVP by supplementing ligninolytic enzymes during fermentation. Cultured in the presence of p-CA, the engineered C. glutamicum strain achieved a maximum 4-VP yield of 45.2%, 57.9%, and 34.7% when fed 2, 5, and 10 g/L p-CA, respectively. Low yield can be attributed to photodegradation of 4-VP and accumulation of the native laccase present in C. glutamicum which may form only dimers and trimers. To further investigate carbon utilization in the cell, the engineered strain was plasmid cured thus removing the PAD enzyme and fermentations for 13C pathway analysis was performed. Polymerization experiments were performed and the polymer was characterized using GPC.

Coral reefs provide essential social, economic, and ecological services for millions of people worldwide. Yet, climate change and local anthropogenic stressors are damaging reefs globally, compromising reef-building capacity, and therefore impacting functionality. Growth of coral reefs depends upon the production and maintenance of the reef framework when calcium carbonate production exceeds erosion, and utilization of remote sensing to scale-up estimates of reef carbonate production remains limited. This study provided a first field estimate of net carbonate production on Hawaiʻi Island, in Hōnaunau Bay, and used high-resolution benthic-cover data, derived from Global Airborne Observatory (GAO) airborne imaging spectroscopy, to scale-up estimates. Net carbonate production was, on average, 0.5 kg CaCO3 m-2 y-1 across the depth gradient, with the highest rates of approximately 2.4 kg CaCO3 m-2 y-1 at 6 m. Urchins, especially the abundant Echinometra, suppressed reef-accretion potential in the shallow reef (< 6 m) and urchin bioerosion decreased with depth. Critically, a threshold of ~26% live-coral cover is currently needed to maintain positive net production across depths. Scaling-up estimates were achieved using a 2 m resolution map of live-coral cover collected by the GAO. Overall, field measurements translate to average vertical reef growth of 0.5 mm y-1 across depths, whereas sea level is currently increasing at 3.55 mm y-1, suggesting the reef in its present status is not keeping pace with sea-level rise. This work lays the foundation to enhance monitoring of carbonate production over increased temporal and spatial scales with airborne imaging spectroscopy — to help determine where reefs are potentially keeping up with anthropogenic stressors, ocean warming, and sea-level rise — and to help inform restoration and management decisions that support resilient carbonate budgets of coral reefs.

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.