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A Backtracking Algorithm for Determining the Existence of Regular Graphs of Specified Girth and Excess
Full text linkThe study of cages focuses on finding (k, g)-graphs of minimal order. This dissertation generalizes the problem of finding cages to the determination of graphs with specified excess, thereby broadening the significance of the results. The (k, g, ε)-graph problem seeks to determine the existence or nonexistence of k-regular graphs with girth g and excess ε = n(G)−M(k, g) (where M(k, g) represents the Moore bound for cage graphs). Motivated by heuristic methods used to determine properties within the study of cages, we present a backtracking algorithm capable of constructing (k, g, ε)-graphs or determining their nonexistence. Chapter 2 provides our own formalization of well-established definitions and results within the study of cages. Additionally, we establish our own labeling convention to more precisely discuss (k, g, ε)-graph constructions. Historically, the study of cages has lacked a standard labeling convention, and the convention we introduce embeds graph data into vertex labels to improve algorithm efficiency by eliminating some computationally expensive calculations. Chapter 3 of this dissertation provides new information on necessary subgraphs of (k, g, ε)-graphs, if such graphs exist, and methods for determining that a given graph cannot be a subgraph of a (k, g, ε)-graph. The lemmas and theorems in this chapter identify safe edge additions for base graphs and forbidden substructures of (k, g, ε)-graphs. Building on Robertson’s argument that the order of the (4, 5)-cage could not be less than 19, we generalize related concepts for all odd girth (k, g, ε)-graphs and even girth (k, g, ε)-graphs assumed to be bipartite. Chapter 4 provides a backtracking algorithm to construct (k, g, ε)-graphs or determine their nonexistence for all ordered triplets (k, g, ε). Chapter 5 introduces improvements to the algorithm from Chapter 4 that enhance performance and reduce the search space. Enhancements which improve computational efficiency include forced neighbor detection, class-based pruning techniques, and array ordering for quicker traversals of the search space. The intended use of the algorithm is to further the study of the cage problem by determining the existence of k-regular graphs of girth g and specified excess ε, which are not necessarily minimal under these properties. Chapter 6 illustrates the practicality of our algorithm through analyses of experiments performed on (k, g, ε) triples corresponding to known cages as well as triples known to not produce a graph. This chapter demonstrates the algorithm’s ability to both construct existing graphs and determine the nonexistence of graphs associated with specified (k, g, ε) triples. Additionally, the analyses in this chapter highlight the effectiveness of various parameters in efficiently converging to results. This dissertation corrects an error in a frequently cited paper by clarifying a critical gap in O’Keefe and Wong’s analysis of the order of 10-cages, providing a corrected proof that validates their claim. In addition to its theoretical contributions, this dissertation also preserves some historical context of the cage problem by providing translations of influential works that have no known English translations
Exploring Generation Z Student Satisfaction in Radiography Programs within a Southern State: Development and Application of a Survey Instrument for Leadership Use
No full textThis dissertation employed a sequential exploratory mixed-methods design to examine the extent to which Generation Z students in radiography programs within a southern state perceive that their needs and expectations are being fulfilled. Additionally, the study examined how program leaders perceived and plan to utilize the survey and its findings within the cycle of continuous program improvement and accreditation readiness. A Likert-scale survey instrument was constructed by cross-referencing Generation Z’s characteristics, needs, and expectations with JRCERT standards. Items were refined through target population focus groups and validated using Lawshe’s Content Validity Ratio. The validated instrument was then administered to Generation Z radiography students across a southern state (n = 134). Quantitative analyses included descriptive statistics and Mann-Whitney U tests to explore differences between traditional and nontraditional students, as well as students in hospital-based and university-based programs. Reliability was supported with Cronbach’s alpha. Qualitative data from focus groups and leadership interviews were analyzed thematically, with triangulation across all sources to enhance credibility. Findings revealed that Generation Z students reported overall satisfaction across all five constructs, with strong ratings for faculty expertise and curriculum relevance. However, areas of improvement included wellness and program support. No statistically significant differences were found between traditional and non-traditional students; however, a statistically significant difference was found between students in hospitalbased and university-based programs. Leadership interviews indicated that program directors valued the survey tool for its potential to inform continuous program improvement, accreditation documentation, and student retention strategies. This study contributes to the body of literature by situating Generation Z’s needs within radiography education, offering a validated instrument for measuring student satisfaction, and highlighting the alignment between generational expectations and accreditation standards. Implications include the adoption of generationally responsive strategies in recruitment, retention, and program evaluation, as well as the integration of student feedback into institutional decision-making. Recommendations for future research include expanding the survey to broader geographic regions and exploring longitudinal impacts on accreditation outcomes and student persistence
Towards Robust Autonomous Systems: Handling Multi-Modal Uncertainties in GPS-Denied Environments
No full textThis dissertation focuses on designing a robust and uncertainty-aware framework for autonomous systems operating in GPS-denied environments, such as indoor infrastructures, underground tunnels, and lunar surfaces. The proposed framework addresses the challenges posed by multi-modal uncertainties, including sensor noise, distributional shifts under adverse conditions, and conflicting decision-making preferences. These challenges compromise the reliability and adaptability of autonomous platforms. To overcome these challenges, the proposed framework adopts a layered architecture that integrates advanced methodologies across the sensing, perception, and decision-making layers. At the sensing layer, an Edge-Kalman Filter combined with a density ratio-based update mechanism is employed to reduce aleatoric uncertainty caused by noisy and inconsistent measurements from BLE, Wi-Fi, ZigBee, and IMU sensors. In the perception layer, a multiresolution analysis using a filter bank—comprising low, medium, and high-pass filters—captures the spatial-frequency characteristics of LiDAR point clouds to detect out-of-distribution inputs, thus reducing epistemic uncertainty. For the decision-making layer, a Prioritized User Preference-based Multi-Objective Reinforcement Learning (PUPMORL) approach is proposed, which selects policies based on KL-divergence to align system behavior with predefined user preferences, thereby addressing preference uncertainty. Together, these methodologies create a resilient system capable of operating reliably in complex and uncertain environments without GPS. The effectiveness of the proposed framework is evaluated through a series of experiments conducted in both simulated and real-world GPS-denied environments. To assess aleatoric uncertainty, indoor localization experiments are performed using BLE, Wi-Fi, ZigBee, and IMU data collected in controlled testbeds, demonstrating significant improvements in distance estimation accuracy when using the Edge-Kalman Filter with density ratio adaptation. Epistemic uncertainty is examined by applying synthetic fog conditions to LiDAR point clouds using the LISA simulator, where the multi-resolution filter bank combined with KL divergence-based confidence estimation successfully detects out-of-distribution patterns and enhances robustness in adverse conditions. For preference uncertainty, the PUPMORL approach is validated using benchmark multi-objective decision-making environments, showing improved policy alignment with user-defined preferences and lower variance in policy selection stability. These results confirm that the proposed methods work effectively across sensing, perception, and decision layers to ensure reliable autonomous performance under uncertainty. This framework is designed to support a wide range of autonomous systems operating in environments where GPS signals are unavailable or unreliable, such as indoor navigation, planetary exploration, underground inspection, and disaster response. Its modular architecture and sensor-agnostic design make it adaptable to diverse platforms and operating conditions. Future work will focus on extending the proposed framework with real-time adaptive preference learning, integrating vision-based sensing to complement LiDAR under degraded conditions, and deploying the system on edge devices to enable low-latency, uncertainty-aware decision-making in mission-critical scenarios
Investigation of Electrochemical Corrosion Fatigue Mitigation Strategies for Mild Carbon Steel
No full textCorrosion fatigue remains a critical durability challenge for steels used in boiler tubes and other safety-critical components, where the interaction of cyclic stresses and corrosive environments accelerates material degradation. This dissertation comprises three experimental studies aimed at advancing mitigation strategies and test methodologies: (1) enhancing corrosion resistance through electrodeposited Fe-Ni anodic coatings, (2) inducing synthetic crack closure to suppress fatigue crack growth, and (3) developing an accessible, low-cost, automated testing system to investigate environmentally assisted cracking (EAC) under controlled laboratory conditions. The first study examined the corrosion behavior of Fe and Fe-Ni electrodeposits synthesized from sulfate-based baths and applied to carbon steel substrates. Specimens immersed in oxygen-saturated, alkaline solution (pH 9.5–10.0) were evaluated using electrochemical methods. Increasing the Ni²⁺/Fe²⁺ ratio reduced porosity, surface cracking, and galvanic corrosion while increasing the temperature dependence of general corrosion between 20–60 °C. These findings indicate the potential of Fe-Ni coatings in boiler water environments, though further work is needed to assess performance under elevated pressures and temperatures. The second study investigated Fe-Ni electrodeposits as a means of inducing crack closure in ASTM A36 steel compact tension specimens. Treatments achieved complete arrest of fatigue cracks for significant load cycles, though effectiveness diminished as cracks lengthened. Crack reinitiation life following arrest was quantified and modeled using a Huang-modified Correia equation. Electrodeposit composition and morphology confirmed alloy composition control in the electrochemical codeposition process and informed interpretation of fatigue suppression mechanisms. The third study focused on the design and validation of an accessible, low-cost, automated test system integrating mechanical loading, environmental control of pH and temperature, and compliance-based crack length measurement calibrated by finite element analysis. Validation tests on carbon steel in acidic chloride solution and PMMA in xylene-ethanol solvents demonstrated accurate load control, stable environmental regulation, and sensitivity to crack growth and closure. Collectively, these studies advance the scientific foundation and practical tools needed to mitigate corrosion fatigue in steels. They represent the first demonstration of an electrodeposited alloy specifically engineered to deliver sacrificial cathodic protection while simultaneously suppressing fatigue crack propagation. The findings clarify the role of Fe-Ni electrodeposits in extending component life and establish an accessible testing framework to accelerate future research on environmentally assisted cracking across diverse materials and environments
Exploring the Effectiveness of Virtual Reality Learning through Use of Visual Eye-Tracking Analytics (VETA) and Biological Measurements
No full textVirtual Reality (VR) offers an immersive and interactive platform for experiential learning. The purpose of this thesis was to evaluate the relationship between physiological responses and cognitive workload within a VR learning environment and to explore VR as an effective instructional tool. This research compared participant engagement, stress, and learning performance within a 6th-grade science module developed in VR by incorporating biometric data collected via Polar H10 heart rate monitor and Varjo Areo VR headset eye-tracking. Thirty-three participants completed a pre-lesson demographic survey, post-lesson survey, VR sickness questionnaire, and the NASA Task Load Index (NASA-TLX). While completing the lesson, the biometric data was collected to indicate cognitive load and engagement during the simulation. The NASA-TLX scores were statistically significant at below 50, indicating a relatively low perceived cognitive workload. No significant differences were found between heart rate before the quiz and heart rate during the quiz. Heart rate variability (HRV) values were statistically significant above 50. This score suggested participants remained calm and unstressed during the lesson. Eye-tracking metrics were analyzed to provide further insight for learning and engagement. These results suggested that VR can provide immersive learning without causing excessive stress or cognitive overload. Implications for future research about VR and education were discussed
Competencies for Effective STEM Leadership: Essential Knowledge, Skills, Dispositions, and Practices to Inform STEM Education Programs and Support Program Leadership
Full text linkThe purpose of this study was to identify a set of knowledge, skills, dispositions, and practices that are important for STEM leaders to consider as constructs of a STEM theory as they plan and implement a STEM program. The research design included a modified Delphi panel to gain consensus on the knowledge, skills, dispositions, and practices, called competencies, that effective STEM leaders consider when planning and implementing a STEM program. The panel participants were experts in STEM education. Based on the literature, the researcher identified the initial set of competencies. The panel identified ten additional competencies through the Delphi process, and 24 were validated. The findings were used to develop configurations of these competencies, offering a tool for STEM leaders to assess and guide STEM program implementation at district, school, and leadership levels
Virtual and Hybrid Work in Higher Education
Full text linkThis qualitative case study examines leadership dynamics within hybrid and remote work environments in higher education, focusing on the enrollment management department of a university. As institutions shift toward flexible work models, the study explores how leaders adapt communication, support, and collaboration strategies to maintain effectiveness, employee well-being, and inclusion. Grounded in Siemens’ (2004) connectivism and supported by insights from Prensky (2001) and Shirky (2009), the study uses a theoretical lens that emphasizes technology’s role in learning and organizational interaction. Data was collected through interviews and document analysis, with participants ranging from frontline recruiters to senior administrators. The constant comparative method was used to analyze themes related to leadership behaviors, communication practices, team cohesion, and equity. The findings highlight that successful leadership in hybrid settings requires intentional communication, flexibility, and a strong emphasis on team connection and support. Leaders must leverage digital tools to foster engagement and ensure equitable access across distributed teams. This research addresses a gap in the literature by focusing specifically on higher education. It offers practical insights for leaders navigating the evolving landscape of remote and hybrid work. The study underscores the importance of adaptive, inclusive, and tech-enabled leadership in supporting organizational resilience and success
The Antioxidant Potential of Rosemary Leaf-Derived Nanovesicles
Full text linkHuman dermal fibroblasts are essential for maintaining skin homeostasis. However, exposure to exogenous and endogenous stressors can lead to fibroblast instability, extracellular matrix degradation, and excessive reactive oxygen species (ROS) production. These factors contribute to skin aging and ROS-induced skin disorders leading to hair loss. Adverse effects from synthetic treatments have driven interest in natural alternatives like plant extracts for skin therapy. However, the polyphenols in these treatments require an effective delivery system to ensure their stability and targeted application. Plant derived nanovesicles (PDNVs) are emerging as a promising natural alternative for therapeutic applications. Their biocompatibility, stability, and encapsulated compounds make them attractive nanocarriers for polyphenols known for their antioxidant potential. Despite their potential, PDNV isolation techniques have yet to be standardized, with limited focus on their extraction from phenol-rich aromatic herbs. This study utilized syringe-vacuum infiltration to extract apoplastic wash fluid from Rosmarinus officinalis leaves, followed by the isolation of rosemary leaf-derived nanovesicles (RNVs) for ROS modulation. This method resulted in a reproducible vesicle yield, with confirmed phenolic content and antioxidant potential in comparison with R. officinalis liquid extract. While the liquid extract harbored more polyphenols and greater antioxidant capacity, in vitro incubation of RNVs with dermal fibroblasts reduced baseline ROS levels and maintained cell viability. These findings support RNVs as an effective polyphenol delivery system for cosmetic applications. This research also expands the understanding of herbal PDNVs, providing insight into their isolation and therapeutic potential. Future studies should explore dose dependent effects to further establish their efficacy in biomedical applications
Assessing the Role of Employees\u27 ESG Perception on Turnover Intention: A Moderation Analysis
Full text linkThis dissertation examines the relationship between employees’ perceptions of their organization’s ESG performance and turnover intentions by drawing upon Social Identity Theory (SIT). SIT suggests that individuals internalize organizational values and beliefs through organizational socialization, which strengthens their identification with the organizations, leading to support for organizations that embody those values. This study also investigated whether ESG awareness is a better predictor than ESG perception. The research employed a cross-sectional survey design to examine whether age and political affiliation moderate the relationship between ESG perception and turnover intention. The findings suggest that employees’ perceptions of their organization’s ESG performance are negatively associated with turnover intention, and political affiliation plays a significant role in moderating the relationship such that the interaction was stronger for individuals who identified more strongly with the Republican Party. The comparison of models using ESG awareness versus ESG perception scales revealed that the model with ESG awareness slightly outperformed the model with ESG perception despite lacking significance
The Potential Co-Occurrence of Perfectionism, Food Insecurity, and GPA with Orthorexia Nervosa Risk
No full textThere are indeterminate risk, prevalence, and correlation data on orthorexia nervosa (ON) as shown by current literature on disordered eating (Rodgers et al., 2021). As a roughly defined disordered eating pattern, ON may be better understood after identifying associations among other attributes in a college student sample (Abdullah et al., 2020; Mavrandrea & Gonidakis, 2023; Parra-Fernández, 2019; Rogowska et al., 2021). A cooccurrence and influence of perfectionism, food insecurity, and grade point average (GPA) with ON risk was hypothesized since current literature suggests college students exhibit each of these characteristics independently (Abdullah et al., 2020; Ambwani et al., 2019; Caferoglu & Toklu, 2022; Celik et al., 2023; Ellison et al., 2021; Kim et al., 2022; Richards et al., 2023; Slaney et al., 2001; Yanover & Thompson, 2008). By identifying co-occurring variables with ON and its risk, timely interventions may mitigate its effects. Associations between 1) ON risk and perfectionism; 2) ON risk and GPA number; 3) ON risk, perfectionism, and GPA; and 4) ON risk and food security status (FSS) were hypothesized. ON risk was measured by the Test of Orthorexia Nervosa – 17 (TON-17) tool, and perfectionism by the Almost Perfect Scale – Revised (APS-R) tool. Food security status was measured by the U.S. Adult Food Security Survey Module (USFSSM–10), and GPA was self-reported. This was a cross-sectional study with college students in the United States who were ≥ 18 years of age. Participants were obtained via convenience and network sampling. Responses were acquired via Qualtrics, an online survey software. Respondents were required to consent to participation prior to responding to questionnaire items. A sample of 257 initially accessed the questionnaire however, 32% were removed prior to analysis due to survey incompleteness or not meeting inclusion criteria. The remaining 174 responses comprised the sample for analysis. Most were female (71.8%), White, Non-Hispanic (52.3%), living off- campus (83.9%), and were in their fourth or higher years of post-secondary education (52.9%). The mean age of the sample was 23 years (SD = 4.76) and had a mean GPA of 3.50 (SD = 0.49). ON risk was determined by a score above 61 on the TON-17, 12 participants (6.97%) were deemed at ON risk. The APS-R revealed a majority of the sample reported being in the maladaptive perfectionism subtype (68.1%). The following positive correlations were found: ON risk and the APS-R Order subscale, [r(163) = .301, p \u3c .001], ON risk and FSS [r(151) = .254, p = .002], and the APS-R “Discrepancy” subscale and FSS [r(152) = .367, p \u3c .001]. GPA and FSS were negatively correlated [r(132) = -.239, p = .005]. When comparing “high” and “low” food security, as determined by the USFSSM–10, “Discrepancy” scores of the APS-R, which indicates perfectionism subtype, were higher in “low” FSS (M = 67.67, SD = 10.72) than in “high” FSS participants [(M = 49.62, SD = 17.34); t(152) = -4.302, p = .019]. These findings revealed that maladaptive perfectionism was prevalent at “low” FSS when compared to those at “high” FSS. Additionally, GPA was lower in “low” FSS (M = 3.26, SD = .73) than in “high” FSS (M = 3.54, SD = .45); t(132) = 2.095, p = .004. One-way ANOVA with post-hoc analyses revealed that ON risk was significantly higher at very low FSS (M = 53.5882, SD = 11.58) when compared to individuals at high FSS (M = 45.90, SD = 9.74), (p = .029, 95% CI = [.57-14.78]). Significant differences in individual TON-17 subscales were also found: “Control of food quality” for the “very low” FSS (M = 19.41, SD = 3.89) were statistically higher than at “high” FSS (M = 17.28, SD = 3.65), [F(3,152) = 2.662, p=.050]. Similarly, “Disorder symptoms” scores at “very low” FSS were statistically higher (M = 17.72, SD = 4.78) than at “high” FSS (M = 14.59, SD = 4.26), [F(3,150) = 4.478, p=.005]. No difference was detected in “Fixation on health and a healthy diet” subscale scores. However, caution is advised when interpreting results from TON-17 subscale data since poor reliability was detected when subscales were analyzed individually. Regression analyses finding indicated that FSS and “Order” subscale scores had significant influence in predicting the TON-17 outcome (β =.948, p =.013; β =.669, p =.002, respectively). The combination of increased ON risk and perfectionism may suggest that rigidity in controllable life factors, by choice, serves as survival or emotional coping mechanisms at low FSS. At the same time, maladaptive perfectionism and ON risk may, instead, originate out of necessity at low FSS to conserve finances, which results in disordered eating habits and a forced inability to meet self-imposed high standards. Overall, food security status appears to influence ON risk, perfectionism subtype, and GPA number. Control, meticulousness, fixation, and flawlessness, as survival or emotional coping mechanisms, appear to shape the co-occurrence and influence identified among ON risk, perfectionism, and food security status in the sample population. Further study of adaptive versus maladaptive perfectionism at different levels of food security may clarify dominant traits between attributes or variations that were not explored in the current study. Additionally, investigating the etiologies of disordered behaviors observed in maladaptive perfectionism, ON risk, and very low food security status may improve early detection, timely intervention, and understanding of risk factors for these conditions. A qualitative approach to observing food purchasing and consumption behaviors in those at very low food security status, who were significantly at risk for ON in this sample, may clarify quantitative findings in the current study. Lastly, observing other potential characteristics associated with ON risk may further refine an understanding of the disordered eating pattern