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This dissertation contains several new results concerning Moser-type optimal stopping problems. In the simplest case we consider sequence of independent uniformly distributed points X1, X2, · · · , Xn on the compact Riemannian manifold M and give algorithm for the calculation of Sn = maxτ≤nE[G(Xτ )]where G is a smooth function on M and τ is a random optimal stopping time. Description of the optimal τ depends on the structure of G near points of maximum. For different assumptions on this structure we calculate asymptotics of Sn.
The emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in December 2019 triggered a global pandemic, causing the urgent need for effective surveillance measures to combat its spread and monitor the evolution of new variants. Sequencing SARS-CoV-2 is an essential tool for surveilling the circulating and emerging variants. This thesis addresses key challenges and proposes advancements in sequencing SARS-CoV-2, focusing on both clinical and wastewater samples.The primary objective of this thesis is to optimize sequencing protocols for SARS-CoV-2 variants from clinical and wastewater samples, specifically targeting improved sequencing capabilities for low viral concentrations using the Oxford Nanopore Promethion platform. Through protocol modifications and refinements, we achieved notable enhancements in sequencing output metrics, such as amplicon amplification, sequencing depth, and the generation of high-quality consensus sequences. The second objective evaluates the performance of wastewater deconvolution software for identifying SARS-CoV-2 variants, employing a meticulous assessment approach with controlled mixtures of synthetic variants and amplicon-based sequencing. In this objective we highlight the effectiveness of Freyja, a widely utilized tool, in producing variant abundance calls closely aligned with expected ratios. In the third objective, we investigate factors contributing to ambiguous variant calls in next-generation sequencing data from two distinct platforms, shedding light on potential sources of variability in variant abundance estimation. Through comprehensive analysis, significant disparities in genome coverage and mutation profiles between platforms were identified, suggesting possible biases or variations in error rates. While Freyja demonstrates excellent performance with controlled datasets, challenges arise with real-world wastewater samples. Through these objectives, the thesis aims to offer insights into optimizing sequencing protocols, enhancing variant detection algorithms, and improving data reproducibility across different sequencing technologies. Ultimately, this research contributes to ongoing efforts in infectious disease surveillance by advancing our understanding of SARS-CoV-2 sequencing from diverse sample sources and providing valuable guidance for future research in viral pathogen sequencing.
This three-article format dissertation presents a comprehensive examination of the 2017 Community College Survey of Student Engagement (CCSSE), focusing on its measurement properties across diverse community college student populations. Study 1 centered on the validity of the internal structure of CCSSE. Exploratory and confirmatory factor analyses showed evidence to support an eight-factor model of student engagement. This model encompasses dimensions such as personal development, interactions with faculty and peers, and institutional support. This study marks a methodological and theoretical shift, advocating for a multidimensional perspective on student engagement in community college. Study 2 employed multi-group confirmatory factor analysis to examine the measurement invariance of the CCSSE across gender, age, race/ethnicity, and enrollment intensity. The results affirmed the CCSSE’s capacity to consistently measure engagement at configural, metric, scalar, and strict levels measurement invariance. This verification underlined the survey’s reliability in capturing authentic group differences. This study also uncovered lower engagement scores among men and part-time students. Study 3 explored the concurrent and predictive evidence of validity of the CCSSE, investigating how engagement indicators correlate with and predict key student success outcomes. It offered new insights into the complex effects of factors such as interaction with faculty and peers and advising services on academic outcomes.
This dissertation evaluates the fatigue response of a steam header designed to mirror the specifications of an ex-service unit, with a focus on optimizing material selection through a detailed analysis involving cost, performance, and durability. Beginning with a study comparing three different alloy choices, 2.25Cr-1Mo, 9Cr-1Mo-V, and IN740H, headers are developed and compared using the procedures outlined in ASME BPVC. The design of the headers follows that used in the original development, and their performance is evaluated in representative loading transients. Each of the designs is evaluated for their fatigue response using the finite element program Abaqus. The results demonstrate that cost savings would likely outweigh any performance benefit to the current system.
The second portion evaluates the material characteristics of 2.25Cr-1Mo following years of exposure to a harsh operating environment. Material specimens were machined from the ex-service unit and subjected to uniaxial testing at various temperatures. The process is used to establish the Chaboche NLKH hardening coefficients. The selection of the NLKH model was guided by its capability to capture the cyclic behavior of the material. The material results are used to compare the projected performance of the 2.25Cr-1Mo header found using readily available material acquired from virgin specimens and those found from the existing unit. The results demonstrate a markedly reduced strength in the service-exposed material, illustrating the effects of the material transformation that occurs over time. This study highlights the importance of operational wear on the projected performance of the header.
The final portion introduces an automated crack growth algorithm in combination with Abaqus to model the progression of a seam crack within a 2.25Cr-1Mo header. Traditional fatigue assessments consider the formation of surface cracks as the end of usability. However, it is well established that the existence of cracks in headers may be allowable, depending on several factors such as size, location, and material. Additional challenges exist in headers along the tube-header intersections, which suffer from non-uniform crack propagation stemming from the complex thermal-mechanical loading near the intersection. To address this issue, the present work develops an algorithm in Abaqus to use the seam crack capability and Paris law to efficiently perform iterative crack growth simulations. This approach captures the uneven growth response of the crack, providing more realistic service life estimations.
Scholars are particularly interested in understanding effective strategies to turn around business performance as businesses experience periods of decline. As the COVID-19 pandemic has revived the importance of better understanding effective turnaround strategies within organizations, additional research is needed to support businesses as they work to recapture or exceed pre-decline performance. This dissertation's research model suggests that operational and strategic turnaround responses have a relationship with firm performance. It is empirically tested using data collected from 98 top management team members across the United States regarding the operational and strategic turnaround responses implemented to combat the decline caused by COVID-19. The results show that strategic turnaround responses positively impacted firm performance. These findings have practical as well as theoretical implications that suggest the type of turnaround response needed in times of future global phenomena.
In the healthcare domain, the development of digital health technologies, including mobile applications, telehealth, wearables, and portals, have created new avenues to deliver patient care, track chronic illnesses, and distribute health information. Digital health technologies allow physicians and patients to interact outside of the traditional care settings; therefore, increasing access to care for disparate populations. Understanding the factors that impact a patient’s decision to adopt digital health technologies is essential to maximizing the Actual Use of digital health technologies and addressing health disparities. This research integrates the Health Belief Model (HBM) and Unified Theory of Acceptance and Use of Technology (UTAUT) to examine technology use behaviors specifically in the context of healthcare. This study evaluates three independent variables – intention to use, Perceived Health Benefit, and Social Influence to determine their impact on Actual Use of technology. This study also investigates how Trust in Technology and eHealth Literacy moderate the relationship between Actual Use of technology and its antecedents. Data from a sample of adults in the United States (N= 293) provides insights into the relationships of the proposed research model.
Family engagement with schools has been shown to be a predictor of student success (Powell et at., 2010) and federal statute supports school/ family relationships through the Family Engagement in Education Act. For students with disabilities (SWD), family engagement may be even more critical. Unfortunately, data has suggested that family engagement may be limited due to barriers families of SWD may face (Van Haren & Fiedler, 2008). Teacher invitation, teacher beliefs about family involvement and quality of communication are factors related to family engagement. The purpose of this study was to investigate an in-service teacher's use of a step-by-step strategy during family/ teacher conferences to increase family engagement during the conference, improve quality teacher communication and positively impact teacher beliefs on family involvement. The step-by-step conferencing strategy was called PIQUE and was developed through a review of prior research and feedback from experts in the field. This case study used both quantitative and qualitative methods to determine the effectiveness of the PIQUE strategy. Within an AB single-case design, I noted an increase in the 5-second intervals of the family speaking during the conference from baseline to post-intervention phase. This increase was immediate and demonstrated an accelerating trend. The teacher and parent completed surveys and interviews, which were analyzed thematically alongside descriptive and inferential field notes recorded by the researcher. Through this analysis, two primary themes were identified as Misunderstanding Communication as Equal to Engagement and Bias as a Barrier to Engagement. A secondary theme of Lack of Confidence When Engaging with Families was also identified. Triangulation was achieved across quantitative and qualitative data sources. Conclusions point to an increase in equity of power during conferences and positive change in teacher beliefs about family involvement and engagement after the implementation of the intervention. A conclusion that PIQUE implementation led to these changes should be interpreted with caution due to the threats to internal and external validity of case studies. The study concluded with implications for practice, limitations and suggestions for future research.
Over the past two decades, the Internet of Things (IoT) has seen a significant expansion in both the sophistication and variety of its applications. These applications span several domains, including enhancing and automating services in healthcare, advancing smart manufacturing processes, and elevating home living standards through smart home technologies. These technologies empower individuals with greater control over their home appliances. Smart locks are smart home devices that were introduced as replacements for traditional locks. Smart locks, designed to go beyond the basic functionality of traditional locks by offering additional features, have seen a surge in market growth and competitiveness. According to the Statista Research Department, it is projected that the global market for smart locks will surpass four billion dollars by 2027.
A number of studies have examined end users' concerns, needs, and expectations regarding smart homes in general. However, little research has been conducted to examine these aspects of the smart lock in particular. To address this gap, we conducted a series of user studies that aim to elucidate how smart locks are integrated and interact within smart home environments, focusing on user interactions both with the locks themselves and when they are part of broader automation scenarios. This dissertation contributes to a deeper understanding of smart lock technology from a user-centric viewpoint. It offers insights into user motivations, concerns, and preferences regarding smart lock usage and automation. It also highlights the importance of balancing convenience and security, the pivotal role of trust, and the complexities of integrating smart locks into broader smart home systems.
The engine of modern society is fueled by information, and the desire to obtain, process and relay it ever more quickly is motivation for scientists to dig deeper into pathways that enable this endgame. The implementation of ever-quicker computer processors, optical fiber-based communications, and Light Radar (LiDar) for climate studies are a small subset that illustrate how ubiquitous the applications of optics are. In this context, the study of 2D materials (2DMs) is important due to the fascinating properties they exhibit that could lead to a plethora of future opto-electronic applications that extend beyond what silicon alone can provide. The story began with graphene due to its high conductivity and tensile strength, but due to the difficulty of switching its conductivity, applications in transistors is limited, and other materials such as the transition metal dichalcogenides (TMDs) MoS2 and WS2, which exhibit a bandgap transition from indirect to direct when going from bulk to monolayer, are being explored. The wide bandgap semiconductor hexagonal boron nitride (hBN) has also been piquing interest. The presence of room-temperature stable excitons detected via various spectroscopies suggests applicability in mainstream field-effect transistors, and current industry direction towards so-called ‘nanosheet’ and ‘nano-wire’ channel transistors serve as prime examples of the relevant applicability of such 2D materials. Quantum computing and valley-tronic applications have also been reported [5], making this class of material exciting to study.
When material dimensions are reduced to the single atomic layer (‘monolayer’) limit, fast carrier dynamics become important that can only be investigated by even faster phenomena i.e., femtosecond ‘ultrafast’ laser pulses. When exposed to intense electric fields, several processes can occur; multiphoton absorption (MPA) which utilizes multiple photons to promote a single charge carrier to the conduction band (CB), tunneling ionization (TI) in which the laser field modifies the inter-atomic potential and allows CB access via tunneling, and avalanche ionization (AI) where inter-carrier impact causes ionization. Together, these strong-field ionization (SFI) processes are subject to significant research effort. If SFI-induced excited carrier populations exceed a threshold, damage occurs via a non-thermal ‘ablation’ process typically used for cutting and patterning.
The objective of this work was to explore the ultrafast optical dielectric breakdown (ODB) behavior of 2DMs such as MoS2, WS2, and hBN. The work involves an investigation of the etalon interference effect that causes differences in the ablation threshold fluence for the same material when placed on different substrates, differences in threshold fluence between different 2DMs, as well as an exploration of laser-induced defects added when multiple ultrafast pulses are incident on the material. ODB for the wide bandgap insulator hBN is also demonstrated and characterized using various imaging modalities and spectroscopies for the first time. Through the findings presented in this work, we begin to unravel some aspects of the nature of ablation, particularly the dominance of avalanche ionization as the key carrier generation mechanism in the ODB process in 2D materials. We also establish femtosecond laser direct writing as a useful tool for the nanopatterning of such 2DMs.
Social studies education has garnered significant national attention as state governments throughout the country have waged an intentional, political attack against the teaching of Critical Race Theory (CRT) and “divisive concepts” in K-12 public schools. Even though CRT is often conflated with diversity, equity, and inclusion (DEI) initiatives and not actually taught at the elementary or secondary level, since January 2021, over one hundred anti-CRT (or divisive concepts) bills have been introduced in more than thirty different state legislatures throughout the country that would prohibit educators from teaching about concepts rooted in race. For Black women teachers, these legislative restrictions create a teaching context that pressures them to divert from the historical work of their predecessors and go against the grain of Black female identity. As such, this phenomenological study explored how Black female social studies teachers teach about race, racism, and oppression given today’s hostile sociopolitical climate.
