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- Creators: Arizona State University
- Creators: Debussy, Claude, 1862-1918
Description
This paper presents three new arrangements of works for solo tuba and piano, originally written by Black composers before 1950. The works presented here include Méphisto masqué by Edmond Dédé, Three Arabian Dances by Amanda Aldridge, and Warbling in the Moonlight by Alton Augustus Adams. Composer biographies, a formal analysis, and form diagrams are included for each piece, along with the new transcriptions.
ContributorsMatejek, Matthew Ryan (Author) / Swoboda, Deanna (Thesis advisor) / Edwards, Bradley (Committee member) / Shea, Nicholas (Committee member) / Arizona State University (Publisher)
Created2023
Description
The proposed research is motivated by the colon cancer bio-marker study, which recruited case (or colon cancer) and healthy control samples and quantified their large number of candidate bio-markers using a high-throughput technology, called nucleicacid-programmable protein array (NAPPA). The study aimed to identify a panel of biomarkers to accurately distinguish between the cases and controls. A major challenge in analyzing this study was the bio-marker heterogeneity, where bio-marker responses differ from sample to sample.
The goal of this research is to improve prediction accuracy for motivating or similar studies. Most machine learning (ML) algorithms, developed under the one-size-fits-all strategy, were not able to analyze the above-mentioned heterogeneous data. Failing to capture the individuality of each subject, several standard ML algorithms tested against this dataset performed poorly resulting in 55-61% accuracy. Alternatively, the proposed personalized ML (PML) strategy aims at tailoring the optimal ML models for each subject according to their individual characteristics yielding best highest accuracy of 72%.
ContributorsShah, Nishtha (Author) / Chung, Yunro (Thesis advisor) / Lee, Kookjin (Thesis advisor) / Ghasemzadeh, Hassan (Committee member) / Arizona State University (Publisher)
Created2023
Description
Background: Premature infants may be at risk for lower effortful control, and subsequent lower academic achievement, peer competence, and emotional and physical wellness throughout the lifespan. However, because prematurity is related to obstetrical and neonatal complications, it is unclear what may drive the effect. Effortful control also has a strong heritable component; therefore, environmental factors during pregnancy and the neonatal period may interact with genetic factors to predict effortful control development. In this study, I aimed to dissect the influences of genetics, prematurity, and neonatal and obstetrical complications on the development of effortful control from 12 months to 10 years using a twin cohort. Methods: This study used data from the Arizona Twin Project, an ongoing longitudinal study of approximately 350 pairs of twins. Twins were primarily Hispanic/Latinx (23.8%-27.1%) and non-Hispanic/Latinx White (53.2%-57.8%), and families ranged in socioeconomic status with around one-third falling below or near the poverty line. Of the twins, 62.6% were born prematurely. Effortful control was assessed via parent report at six waves. Results: There was not a significant relationship between gestational age and effortful control regardless of whether obstetrical and neonatal complications were controlled for. Biometric twin modeling revealed that the attentional focusing subdomain of effortful control was highly heritable. Gestational age did not moderate genetic and environmental estimates. Conclusions: The findings help inform the risk assessment of prematurity and provide evidence for differing etiology of each subdomain of effortful control and the strong role of genetics in effortful control development.
ContributorsPickett, Janna (Author) / Lemery-Chalfant, Kathryn (Thesis advisor) / Su, Jinni (Committee member) / Eggum, Natalie D (Committee member) / Arizona State University (Publisher)
Created2023
Description
This research aims to evaluate gender disparities in driving while under the influence (DUI) prosecutions, integrating perspectives from political science, sociology, and economics. A meticulous literature review reveals distinct patterns in drinking habits, risk-taking behaviors, biases within law enforcement, justice system dynamics, regional blood alcohol content (BAC) law variations, and the intricate interplay of gender norms and societal expectations. Notably, women face a lower likelihood of DUI arrest than men, a disparity influenced by a myriad of factors, including alcohol consumption patterns, ingrained biases, and gendered stereotypes. Economic dimensions of DUI convictions spotlight costs linked to healthcare, legal proceedings, lost productivity, and insurance premiums. The political arena actively molds DUI-centric policies, emphasizing the significance of decisions like adopting ignition interlock device laws and amplifying enforcement initiatives. Additionally, the nuanced experiences and challenges of transgender individuals within the DUI justice context underscore a pressing need for inclusivity and tailored policy considerations. A key observation is the obstacle faced by women, who are subjected to criticism both for the DUI offense and deviations from gender norms. This research underscores the necessity for harmonized policies that bridge the gender gap in DUI arrests, fostering an equitable justice system, and mitigating the profound economic and social repercussions of DUI offenses. The confluence of societal norms, economic ramifications, and political decisions constitutes the crux of gender disparities in DUI prosecutions, necessitating comprehensive and intersectional approaches in future research endeavors.
ContributorsJaneway, McKenzie (Author) / Scheall, Scott (Thesis advisor) / Thomas, Kathy (Committee member) / Alozie, Nicholas (Committee member) / Arizona State University (Publisher)
Created2023
Modeling Spatial Competition and Adaptive Therapy Protocols in Three-Dimensional Vascularized Tumors
Description
In contrast to traditional chemotherapy for cancer which fails to address tumor heterogeneity, raises patients’ levels of toxicity, and selects for drug-resistant cells, adaptive therapy applies ideas from cancer ecology in employing low-dose drugs to encourage competition between cancerous cells, reducing toxicity and potentially prolonging disease progression. Despite promising results in some clinical trials, optimizing adaptive therapy routines involves navigating a vast space of combina- torial possibilities, including the number of drugs, drug holiday duration, and drug dosages. Computational models can serve as precursors to efficiently explore this space, narrowing the scope of possibilities for in-vivo and in-vitro experiments which are time-consuming, expensive, and specific to tumor types. Among the existing modeling techniques, agent-based models are particularly suited for studying the spatial inter- actions critical to successful adaptive therapy. In this thesis, I introduce CancerSim, a three-dimensional agent-based model fully implemented in C++ that is designed to simulate tumorigenesis, angiogenesis, drug resistance, and resource competition within a tissue. Additionally, the model is equipped to assess the effectiveness of various adaptive therapy regimens. The thesis provides detailed insights into the biological motivation and calibration of different model parameters. Lastly, I propose a series of research questions and experiments for adaptive therapy that CancerSim can address in the pursuit of advancing cancer treatment strategies.
ContributorsShah, Sanjana Saurin (Author) / Daymude, Joshua J (Thesis advisor) / Forrest, Stephanie (Committee member) / Maley, Carlo C (Committee member) / Arizona State University (Publisher)
Created2023
Description
Single cell analysis is critical for understanding cellular activities, diagnosing clinicaldiseases, and designing personalized treatments. However, the detection of single cells with high sensitivity has been challenging, especially for clinical samples, as targets of detection are often immersed in extremely complex background. Due to the lack of single cell sensitivity, current mainstream approaches isolate the cells and increase cell numbers by culturing, which is time consuming and often leads to the change of cellular population composition and the loss of native characteristics. In addition, the ensembled detection approaches provide only averaged information of the cell population, thereby missing vital cellular heterogeneity information. The applied probes during detection can also alter the native structures and influence the reliability of the results. In this dissertation, novel label- free optical imaging methods for single cell analysis of raw clinical samples are developed and described to address these challenges.
First, a large volume imaging platform is developed for rapid diagnostics of clinical samples of critically low bacterial concentrations without enrichment. Both dual channel and multiplexed versions of the platform are introduced for continuous, detailed monitoring and high throughput minimum inhibitory concentration determination, respectively. With these platforms, the susceptibility of the pathogenic microorganisms in raw urine and blood samples are rapidly quantified within 90 minutes and 240 minutes, respectively, significantly improving the diagnostic time.
Second, the large volume imaging platform is adapted for rapid drug susceptibility testing of multidrug-resistant mycobacterial species. Using this method, the susceptibility profile of Mycobacterium tuberculosis and nontuberculous mycobacteria are ascertained within a short timeframe - less than two proliferation cycles. By coupling with single particle tracking, the presence of resistant subpopulations at the therapeutic failure limit of 1% can be detected within one day.
Last, by sensitively tracking the emergence of precipitation in various polymer solutions with an upper critical solution temperature upon heating using plasmonic scattering microscopy, precise temperature control over the highly localized plasmonic field is achieved. TRPV1 channel is accurately activated without the aid of an external temperature controlling platform, highlighting the capability of the method for single cell manipulation and in-depth analysis.
ContributorsJiang, Jiapei (Author) / Wang, Shaopeng SW (Thesis advisor) / Haydel, Shelley SH (Committee member) / Smith, Barbara BS (Committee member) / Wang, Chao CW (Committee member) / Tian, Xiaojun XT (Committee member) / Arizona State University (Publisher)
Created2023
Description
This dissertation centers on treatment effect estimation in the field of causal inference, and aims to expand the toolkit for effect estimation when the treatment variable is binary. Two new stochastic tree-ensemble methods for treatment effect estimation in the continuous outcome setting are presented. The Accelerated Bayesian Causal Forrest (XBCF) model handles variance via a group-specific parameter, and the Heteroskedastic version of XBCF (H-XBCF) uses a separate tree ensemble to learn covariate-dependent variance. This work also contributes to the field of survival analysis by proposing a new framework for estimating survival probabilities via density regression. Within this framework, the Heteroskedastic Accelerated Bayesian Additive Regression Trees (H-XBART) model, which is also developed as part of this work, is utilized in treatment effect estimation for right-censored survival outcomes. All models have been implemented as part of the XBART R package, and their performance is evaluated via extensive simulation studies with appropriate sets of comparators. The contributed methods achieve similar levels of performance, while being orders of magnitude (sometimes as much as 100x) faster than comparator state-of-the-art methods, thus offering an exciting opportunity for treatment effect estimation in the large data setting.
ContributorsKrantsevich, Nikolay (Author) / Hahn, P Richard (Thesis advisor) / McCulloch, Robert (Committee member) / Zhou, Shuang (Committee member) / Lan, Shiwei (Committee member) / He, Jingyu (Committee member) / Arizona State University (Publisher)
Created2023
Description
ABSTRACT This recording and commissioning project was inspired by a concert from The Library of Congress, The Boccaccio Project. Three composers, Shawn Head, Nick Dulworth, and Bill Clay were commissioned to write works reflecting on their experiences during the coronavirus pandemic. The purpose of this project is to expand the repertoire for solo cello, to serve as an artistic response to the coronavirus pandemic, to promote these brilliant composers, and to provide an opportunity to make music with friends during a time of isolation. This written document includes a discussion of the collaborative process of commissioning and preparing these works, and an analysis of each piece. Scores and recordings of these works are provided at the end of the document.
ContributorsYang, Elliot (Author) / Landschoot, Tom (Thesis advisor) / Bolanos, Gabriel (Committee member) / Rotaru, Catalin (Committee member) / Arizona State University (Publisher)
Created2023
Description
Remote sensing, with its capacity to capture continuous, high spatial and spectral resolution data, has emerged as an invaluable tool for ecological research and addressing conservation challenges. To fully harness the potential of remote sensing, spectral ecology has emerged as a field that investigates the interactions between the electromagnetic spectrum and biological processes. This dissertation capitalizes on a model system to explore the spectral ecology of a dominant, highly polymorphic, keystone, and endemic tree species (Metrosideros polymorpha). M. polymorpha not only serves as a model organism for studying adaptive radiation and intraspecific variation but also presents a critical conservation challenge. The recent introduction of the fungal disease Ceratocystis lukuohia has resulted in millions of M. polymorpha mortalities. This dissertation employs leaf-level spectroscopy data and canopy-level imaging spectroscopy data. Imaging spectroscopy captures reflectance across the visible to short-wave infrared (VSWIR) spectrum to provide high-spectral resolution data that enable canopy trait retrievals, species classifications, disease resistance detection, and genotype differentiation. Chapter 1 serves as an introduction, framing the subsequent chapters by presenting an overview of spectral ecology, imaging spectroscopy, and M. polymorpha. Chapter 2 explores M. polymorpha trait and spectra variation across environmental gradients. This chapter concludes that intraspecific variation follows the leaf economic spectrum and that elevation is a dominant driver of M. polymorpha trait and spectral variation. In Chapter 3, leaf-level spectroscopy was able to discriminate between sympatric, conspecific varieties of M. polymorpha and their hybrids as well as individuals resistant and susceptible to Ceratocystis wilt. Together, Chapters 2 and 3 support the concept of “genetic turnover,” akin to species turnover, wherein environmental conditions filter M. polymorpha genotypes present in a given region. Chapter 4 classifies M. polymorpha across the over 10,000 km2 of Hawai'i Island to aid in conservation efforts, demonstrating the potential of imaging spectroscopy to classify vegetation on large geographic scales. The final chapter builds on the prior chapters to present a M. polymorpha genetic diversity map for Hawai'i Island. In conclusion, this dissertation examines the spectral ecology of a model system to advance the understanding of ecological dynamics and address a pressing conservation challenge.
ContributorsSeeley, Megan (Author) / Asner, Gregory P (Thesis advisor) / Turner II, Billie L (Thesis advisor) / Martin, Roberta E (Committee member) / Frazier, Amy (Committee member) / Arizona State University (Publisher)
Created2023
Description
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the causative pathogen of Coronavirus Disease 2019 (COVID-19). Successful vaccination aims to elicit neutralizing antibodies (NAbs) which inhibit viral infection. Traditional NAb quantification methods (neutralization assays) are labor-intensive and expensive, with limited practicality for routine use (e.g. monitoring vaccination response). Thus, a rapid (10-minute) lateral flow assay (LFA) for quantification of SARS-CoV-2 NAbs was developed. Using the NAb LFA, an 18-month longitudinal study assessing monthly NAb titers was conducted in a cohort of over 500 COVID-19 mRNA vaccine recipients. Three NAb response groups were identified: vaccine strong responders (VSRs), moderate responders (VMRs), and poor responders (VPRs). VSRs generated high and durable NAb titers. VMRs initially generated high NAb titers but showed more rapid waning with time post-vaccination. Finally, VPRs rarely generated NAb titers ≥1:160, even after 3rd dose. Although strong humoral responses correlate with vaccine effectiveness, viral-specific CD4+ and CD8+ T cells are critical for long-term protection. Discordant phenotypes of viral-specific CD8+ and CD4+CXCR5+ T follicular helper (cTfh) cells have recently been associated with differential NAb responses. The second portion of this dissertation was to investigate whether/how SARS-CoV-2 T cell responses differ in individuals with impaired NAb titers following mRNA vaccination. Thus, phenotypic and functional characterization of T cell activation across NAb response groups was conducted. It was hypothesized that VPRs would exhibit discordant SARS-CoV-2 T cell activation and altered cTfh phenotypes. Peripheral blood mononuclear cells were isolated from VPRs, VMRs, VSRs, naturally infected, and normal donors. SARS-CoV-2 responsive T cells were characterized using in vitro activation induced marker assays, multicolor flow cytometry, and multiplex cytokine analysis. Further, CXCR5+ cTfh were examined for chemokine receptor expression (CCR6 and CXCR3). Results demonstrated that despite differential NAb responses, activation of SARS-CoV-2 responsive CD4+ and CD8+ T cells was comparable across NAb groups. However, double-positive CD4+CD8+, CD8low, and activated CD4+CXCR5+CCR6-CXCR3+ (Tfh1-like) T cells were expanded in VPRs compared to VMR and VSRs. Interestingly, a unique population of CD8+CXCR5+ T cells was also expanded in VPRs. These novel findings may aid in identification of individuals with impaired or altered immune responses to COVID-19 mRNA vaccination.
ContributorsRoeder, Alexa Jordan (Author) / Lake, Douglas (Thesis advisor) / McFadden, Grant (Committee member) / Borges Florsheim, Esther (Committee member) / Chang, Yung (Committee member) / Rahman, Masmudur (Committee member) / Arizona State University (Publisher)
Created2023