Doctoral Dissertations (Winter 2014 to Present)

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New submissions to the University of Delaware Doctoral Dissertations collection are added as they are released by the Graduate College. The Graduate College deposits all dissertations from a given semester after the official graduation date.

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The Association Between Obesity Prevalence and the Food Environment
Davis, Catherine
Background: Obesity affects over 40% of adults in the United States. The food environment is thought to be a potential contributing factor to obesity. This present study aimed to explore the association between the food environment and obesity defined by body mass index (BMI) and body fat. Methods: A prospective cross-sectional study design was employed with participants nested within income strata. Trained interviewers visited participants’ at their place of residence to conduct in-person surveys that included questions about physiological health, neighborhood characteristics, and anthropometrics. The food environment was assessed using the Retail Food Environment Index (RFEI) and the Modified Retail Food Environment Index (mRFEI). Height, weight, and body fat were measured during a visit and used to determine obesity status. Logistic regression was used to examine associations between the food environment indexes and obesity status. Results: Analyses were conducted on data from 436 adult participants living in one of 20 U.S. Census block groups located in Kansas City, KS, and MO. The RFEI and the mRFEI were not associated with BMI-defined obesity (OR = 0.96, 95% CI [0.86 – 1.06]) and (OR = 0.81, 95% CI [0.41 – 1.61]), respectively. The RFEI was negatively (OR = 0.83, 95% CI [0.75 – 0.92]), and the mRFEI was positively (OR = 0.83, 95% CI [0.75 – 0.92]) associated with body fat-defined obesity. Lastly, the RFEI (p=0.419) and mRFEI (p=0.543) did not significantly differ in those with or without BMI-defined obesity. Conclusion: The relationship between obesity and the food environment is complex. The results of this study suggest the relationship depends on the measure of obesity.
RISK FACTOR IDENTIFICATION FOR ADDUCTOR STRAIN IN A PROFESSIONAL US MLS COHORT THROUGH DESCRIPTIVE ANALYSIS AND PREDICTIVE MACHINE LEARNING MODELS
Davis, Rebecca
Soccer players experience a multitude of injuries, however, one of the most common injuries endured is hip adductor strains. The adductor muscles play a key role in the adduction of the thighs and stabilization of the pelvis. In soccer, athletes experience repeated kicking, change of direction, acceleration, and deceleration movements that can put repeated strain on their adductor musculature. These injuries can cause athletes anywhere from days to months of time away from play and have been found to put athletes at a higher risk of reinjury in the future. Risk factors of adductor injury have been studied in an effort to assess what may be related to increased risk of injury. In an effort to better understand risk factors of these injuries within an MLS team cohort, a descriptive analysis was conducted. Descriptive features such as player position, history of injury, injury type, and mechanism of injury were investigated. Generalized Estimating Equations were utilized to assess how previous injury, position type, and season were related to injury outcomes between the 2016 to 2022 seasons. A season was defined by the calendar year. From this study, we found adductor injury made up 15.5% of all non-contact lower extremity injuries. A total of 30 non-contact adductor injuries occurred and reinjury accounted for 20% of these injuries. Overuse, change of direction, running, and kicking made up 80% of all mechanisms of injury. From the GEE results, previous injury was found to be significantly related to greater odds of injury in a future half season. Position and season were not significantly related to odds of injury. In addition to descriptive qualities, machine learning models and techniques have been deployed to predict an athlete’s risk of injury. A predictive model focusing on adductor strain injuries in a specific professional soccer team cohort in Major League Soccer was constructed to further the understanding of how we can utilize commonly collected assessments for the mitigation of adductor injury. Injury, game, inertial measurement unit/global positioning system, strength, and countermovement jump assessment data was collected over a period of four seasons. Random forest machine learning algorithms were used with chosen features to predict soft tissue, non-contact adductor injuries. Weekly and monthly structured models using IMU/GPS, injury, and game data from 2019 to 2022 were created. Weekly and monthly models using IMU/GPS, injury, game, and strength data from 2021 to 2022 were also created. Finally, weekly and monthly models using IMU/GPS, injury, game, strength, and countermovement jump data from 2022 were created. Synthetic minority sampling and random undersampling were utilized in an attempt to balance the data as injury data points proved to be rare events. Results showed the models were able to predict adductor injury with misclassification of the injured class ranging between 5 to 15%. All models were able to predict injury with differing variables of significance and percent misclassification. Position, history of previous injury, change of direction efforts, acceleration efforts, maximum force production of the ab/adductors and hamstrings, and the adductor-to-abductor ratio were identified as significant variables (p<0.05) in at least one of the four models. These variables give an indication of what metrics are related to soft-tissue, non-contact adductor injury and should be further studied in the identification of risk factors.
Vicente Carducho and the Studio-Academy: Modelling Artistic Practice and Connoisseurship in Early Modern Spain
Doherty, Tiarna
“Vicente Carducho’s Studio-Academy: Modelling Artistic Practice and Connoisseurship in Early Modern Spain” analyzes a variety of primary sources pertaining to Vicente Carducho (c.1576-1638) in order to describe the emergence of informal art academies in early modern Spain, a subject hitherto neglected. Through an intertextual analysis of important surviving documents from this prolific court painter who worked for King Philip III and King Philip IV of Spain—such as his treatise the Diálogos de la pintura, his petitions to establish a royal art academy, and his estate documents—this dissertation argues that Carducho ran a studio-academy in his home. It explains how Carducho’s collections of art, instruments, and books would have been employed within an interdisciplinary space, where mathematical exercises, optical experiments, and the study of natural science complemented art making. Furthermore, it evaluates how these activities were part of an Aristotelian framework of knowledge formation in which sensorial perception was the key to educating artists and art aficionados. Carducho’s role as the Maestro in the studio-academy and in his treatise, the Diálogos, positioned him as an expert on art as well as on the skills and behaviors of connoisseurship, making him an invaluable resource in the artistic, scientific, and courtly circles of Spain.
DIGITAL AUTHORITARIANISM IN AFRICA: CHINESE STRATEGY OR AFRICAN LEGACY
Achinivu, Chibuzo
Over the last two decades, there has been a remarkable increase in the practice of digital authoritarianism (DA) in Africa. Yet researchers remain divided as to the drivers of this trend, especially as it relates to its international origins. Some scholars have portrayed China as a foreign supply-side driver of the technologies and the practice of DA in Africa. Others argue that such origins are overstated, contending that little evidence exists for a direct role of China in Africa’s increasing turn towards DA. Some that make this argument claim that DA in Africa is merely Africa's authoritarian legacy playing out on a more modern platform. In this paper, I use a norm diffusion and order project approach to propose and test an innovative theory of the supply and demand of DA in Africa. I argue that China’s strategic supply of its model of DA to Africa satisfies African governments' strategic demand for DA in a coherent fashion. I also posit that there is some credence to the authoritarian legacy argument, as I argue that regime type facilitates this trend. To test this theory, I conduct a statistical panel analysis of African countries for the years 2000–2020. I also conduct case studies in several African countries. My results confirm my theory and present novel findings that have implications for technology governance, African politics, China’s rise, and China’s strategic contestation of international norms.
RADIO EMISSION OF COSMIC-RAY AIR SHOWERS AT THE SOUTH POLE AND A NEW ICETOP TRIGGER
Paudel, Ek Narayan
The sources of highly energetic cosmic rays are still not fully understood. Better accuracy in composition measurement at different energies is essential to establish the origin of these energetic particles. IceTop is a cosmic-ray air-shower detector at the South Pole that is sensitive in the energy range of transition from the highest energy galactic sources to the extragalactic sources. However, IceTop is losing efficiency due to the continuous accumulation of snow above its ice-Cherenkov tanks. There is an ongoing effort to enhance IceTop with additional detectors, in particular, scintillator panels and radio antennas, with raisable stands. Radio antennas have better sensitivity to inclined air showers due to the stronger geomagnetic radio emission from such air showers. The coincident measurement of inclined cosmic-ray air showers with IceTop tanks and radio antennas can improve the measurement accuracy and, consequently, increase the sky coverage for mass-sensitive anisotropy studies using IceTop. The polarization of radio emission from air showers is used to understand the contribution of the Askaryan and the geomagnetic radio emission mechanisms. The feasibility of using the direction of air showers and the relative Askaryan fraction of their radio emission in reconstructing the depth of shower maximum, $\mathrm{X}_{\mathrm{max}}$, which is sensitive to the mass of the cosmic-ray primary particle generating the air shower, is investigated. The theoretical $\mathrm{X}_{\mathrm{max}}$ resolution achievable with this technique is 20 - 40 g cm$^{-2}$, comparable to other techniques. Also, in an effort to improve the trigger efficiency of IceTop tanks to higher zenith angles, a new trigger was implemented with relaxed trigger conditions and validated with the first data from the South Pole. The improvement on the simulated full efficiency threshold compared to the standard trigger is about 0.2 in log10(E/eV) for vertical events and about 0.5 in log10(E/eV) for inclined events.
Toward Privacy-Preserving, Secure, and Fair Federated Learning
Liu, Zheyuan
Federated learning is a collaborative machine learning approach that enables multiple clients to train a shared model while keeping their local data private. This method addresses privacy concerns by ensuring that sensitive data remains decentralized, thus reducing the risk of data breaches. By leveraging the collective knowledge of diverse datasets, federated learning enhances model performance and generalization, making it particularly valuable in scenarios where data privacy and security are paramount. This dissertation aims to enhance federated learning by addressing three key challenges: privacy preservation, security against malicious attacks, and fairness across diverse demographic groups. First, we propose a novel privacy-preserving federated learning mechanism. While local datasets remain private, intermediate model parameters can still leak sensitive information. Existing solutions either add noise, which reduces model accuracy, or use inefficient cryptographic techniques. Our method employs two non-colluding servers and efficient cryptographic primitives for secure aggregation, maintaining privacy without sacrificing accuracy or efficiency. Second, we present a secure federated learning method to defend against malicious clients. Federated learning is vulnerable to Byzantine attacks, where malicious clients corrupt their local data or updates to degrade the global model. Current methods either ineffectively filter malicious updates or rely on a potentially biased trusted dataset. Our method evaluates client trust based on similarity to a trusted dataset and incrementally builds a trusted client set. This approach effectively defends against Byzantine attacks, achieving high model accuracy even with an initially biased trusted dataset. Finally, we introduce a fair federated learning method to ensure equitable accuracy across demographic groups. Machine learning models often favor majority groups due to data imbalances or biased training. Existing fairness methods are typically centralized and require access to the entire dataset, making them unsuitable for federated learning. Our approach guarantees fairness by exchanging minimal additional data among clients, preserving the global model's utility while ensuring equitable accuracy across all groups.
PERFORMANCE OPTIMIZATION OF A PROTON EXCHANGE MEMBRANE WATER ELECTROLYZER
Alkhaldi, Shabeeb
Green hydrogen can contribute significantly to combating climate change by helping to decarbonize the world's energy sector. Hydrogen can be produced in a carbon-free manner using renewable energy by electrolysis which is environmentally benign and produces hydrogen with high purity. Water is fed to the electrolytic cell as the reactant and it is dissociated into hydrogen and oxygen by the passage of electricity. Water electrolysis is typically accomplished today by one of three methods: (i) alkaline water electrolysis (AWE); (ii) solid oxide water electrolysis (SOWE); and (iii) proton exchange membrane water electrolysis (PEMWE). PEMWE offers certain advantages including high efficiency and high current density. Therefore, we focus on PEMWE in this study. First, we examine the effect of various operating parameters on PEMWE performance such as water flow rate, temperature, membrane thickness, flow field channel configuration, and porous transport layer properties. This work quantitatively compares the relative magnitude of anode water consumption against the concurrent water transport mechanisms of Fickian diffusion and electroosmotic drag as a function of the applied voltage. This study also gives insights on optimizing PEMWE performance by varying the operating parameters and provides a foundation for the design of a full-scale PEMWE system. Second, we evaluate multiple strategies for gas management in the PEMWE anode. In this study, we employ an electrolysis cell featuring a transparent anode to visualize oxygen bubble production and transport under a range of operating conditions. These strategies include changing the cell’s orientation with respect to gravity, increasing the water flowrate, and adding surfactant to the anode water supply. This study shows that optimally orientating the channels with respect to gravity can assist with oxygen bubble evacuation and improve performance. This study also captures the dynamic behavior of the two-phase flow phenomena in PEMWEs over a range of applied voltages. The results provide suggestions to enhance PEMWE performance by optimizing oxygen gas management within the PEMWE’s flooded anode. Third, we focus on the phenomenon of electroosmotic drag in an operating PEMWE with the goal of accurately measuring the electroosmotic drag coefficient. This study elucidates the effect of the cell temperature and membrane thickness on the relevant water transport phenomena. We also investigate the effect of supplying dry nitrogen to the cathode and provide an explanation for the improved current density based on the Nernst equation. Understanding these mechanisms is essential to improving PEMWE performance and efficiency. Finally, we compare the catalytic performance of nickel iron layered double hydroxide (NiFe LDH) against commercial iridium oxide (IrOx) in an anion exchange membrane water electrolyzer. In this study, we present the structural and performance analysis of NiFe LDH which was prepared in the form of nanosheets through a benzyl alcohol-mediated solvothermal process in one step. The NiFe LDH electrode demonstrated good stability over a 24-hour durability test. Although the electrochemical performance of NiFe LDH was somewhat lower compared to IrOx, it shows promise as a AEMWE catalyst due to its significantly lower cost and capacity for further activity enhancement.
Harvesting Harmony: A Tripartite Study of Resource Extraction, Economic Games, and Legal Histories
Akram, Humayoun
This dissertation investigates the interplay between economic progress and resource extraction, emphasizing the role of natural, human, and capital resources in driving economic output. Historically, ecosystems constrained economic growth, but advancements in technology and human behavior have facilitated increased productivity and settlement. However, exponential economic growth, particularly post-World War II, has intensified pressure on natural ecosystems, posing significant sustainability challenges. This study employs various methodologies and case studies to examine the complexities of the resource extraction industry and its socio-ecological and socio-economic impacts. Chapter two provides a global perspective on the economic dynamics of resource extraction, highlighting how increased material consumption exacerbates environmental pressures and socio-economic disparities. The concept of the resource curse, which posits that resource-rich regions often experience poor development outcomes, is critically analyzed. Contrary to this hypothesis, some local communities benefit from wealth gains, although many mining operations occur in water-stressed areas, underscoring the need for tailored policies. Chapter three delves into the U.S. hydraulic fracturing industry, exploring its dual impact on energy security and environmental degradation. Legal institutions' role in mediating conflicts and the importance of transparent, science-based policymaking are emphasized. A theoretical framework is proposed to leverage science constructively, fostering trust and cooperation between stakeholders. Chapter four uses experimental economics to test strategies for conflict resolution, focusing on apology, compensation, and communication. The findings reveal communication as the most effective strategy, with personality traits influencing the efficacy of different approaches. Overall, this dissertation highlights the importance of aligning economic development with environmental sustainability and equitable progress. By integrating human behavioral insights and employing experimental economics, it proposes strategies for harmonizing human progress with ecological health, advocating for informed, collaborative efforts in policymaking.
Using Narratives to Bypass Fatalism in the Context of Sun Protection Behaviors
Rasheed, Huma
Fatalism can be a significant barrier to cancer screening, prevention, and treatment. Given its association with social determinants, and religious and cultural norms, altering fatalistic beliefs is often challenging. Consequently, an alternative approach to promoting healthy behaviors among fatalistic individuals could be to focus on modifying specific behavioral beliefs, rather than attempting to change fatalism itself. This dissertation explores the potential of narrative persuasion to bypass the effects of fatalism on sun protection behavior by enhancing individuals' beliefs in the efficacy of sun protection measures. The study seeks to address three primary questions: (1) Are narratives more effective than non-narrative messages in enhancing behavioral beliefs about sun protection in fatalistic people? (2) Does incorporating fatalistic beliefs about sun protection within narrative and non-narrative messages increase the intention to engage in sun protection, particularly among those with fatalistic views? And (3) What is the role of classic narrative mechanisms—such as transportation, identification, and counterarguing—in these relationships? A 2 (narrative vs. non-narrative) x 2 (fatalistic vs. agentic) between-subjects experiment was conducted to test the hypotheses and research questions (N = 500). Using a sample of predominantly non-Hispanic White American adults, the findings revealed no significant difference between narrative and non-narrative messages in influencing the belief that sunscreen prevents skin cancer. Similarly, the study did not find support for the positive effect of message-viewer consonance (regarding fatalistic/agentic beliefs about cancer prevention) on behavioral beliefs about sunscreen. However, a positive moderating effect of baseline fatalism on the relationship between exposure to narrative stimuli and behavioral beliefs was observed. According to the findings, narratives were more persuasive than non-narratives for people who scored higher on the fatalism scale. Tests for the mediating role of narrative mechanisms, however, yielded unexpected results. The data indicated that narratives had unintended indirect effects on beliefs and post-test cancer fatalism through the mechanism of counterarguing. Participants in the narrative conditions were more likely to counterargue the message, and since counterarguing was negatively associated with beliefs and cancer fatalism, narratives had a negative indirect effect on beliefs and a positive indirect effect on cancer fatalism. The findings illuminate the role of individual characteristics in shaping responses to health messages, raising important questions for future research. Specifically, future studies should explore (1) the underlying mechanisms that make narratives more effective for individuals with fatalistic beliefs, (2) how people's expectations of different message types and formats influence their reactions, and (3) the consequences of violating these expectations. Furthermore, these results prompt a critical discussion on the boundaries of narrative persuasion. Assuming that narrative persuasion is universally effective or appropriate in all contexts may be misguided, especially in health contexts, as it could lead to unintended consequences. Therefore, it is crucial to consider individual differences in baseline beliefs and employ tailored approaches when designing health messages to ensure their effectiveness.
ALIGNING PROFESSIONAL LEARNING WITH NATIONAL BOARD CERTIFICATION TO DEVELOP TEACHER SELF-EFFICACY
Asplen, Rhonda
ABSTRACT Like many school districts, Cecil County Public Schools (CCPS) has historically taken a top-down approach to professional learning. Priorities for learning are established by executive leadership and administered through principals and content supervisors. Such an approach ignores the contexts that teachers work within, including years of experience, grade level, needs of students, and curriculum. Recent challenges, including learning loss from COVID 19 and budget restrictions, have interrupted professional learning. Furthermore, new legislation titled the Blueprint for Maryland’s Future requires districts to implement a career ladder for teachers. To advance up the career ladder, teachers will need to achieve National Board Certification (NBC), a process that allows teachers to demonstrate their expertise in both content knowledge and pedagogy. Although research does not show a clear relationship between NBC and student learning, it has established a relationship between teacher self-efficacy (TSE) and student learning. Therefore, by providing professional learning experiences that build TSE, NBC may influence student learning indirectly. This Education Leadership Portfolio (ELP) presents a professional learning model for CCPS schools that is aligned with the vision presented by the Blueprint for Maryland’s Future, is informed by research on teacher efficacy, and incorporates the processes of National Board Certification. The design of the model was informed by research on professional learning communities (PLC), and the PLC model was piloted at a CCPS middle school for teachers of English Language Arts. Results of this study suggest that teachers found the PLC model to be more relevant and impactful than traditional professional learning and that the PLC structure facilitated practices aligned with both the National Board of Professional Teaching Standards’ Architecture of Accomplished Teaching and criteria for effective PLCs.
FRENCH DIPLOMATIC ODYSSEY: CONTINUITY AND CHANGE IN FRENCH POLICIES TOWARDS IRAN (17TH-19TH CENTURIES)
Mousavi, Seyed Mehdi
Between the mid-seventeenth to the mid-nineteenth centuries, encompassing the reigns of Louis XIV and Napoleon Bonaparte, as well as the post-Napoleonic monarchies (the Bourbon and July monarchies), France maintained a persistent and coherent trade policy with Iran. During these two centuries, France was the third major European power involved in Iranian affairs, always competing with two other powers (Holland and England in the seventeenth century, and Britain and Russia in the nineteenth century). However, France’s policy towards Iran shifted in the middle of the nineteenth century, with the accession of Nāser al-Dīn Shah Qajar in Iran and Louis Napoleon (the future Napoleon III) in France in 1848, and with the involvement of Russia, Britain and France in the Crimean War (1853-56). This policy shift occurred as a result of both political circumstances and France’s successful diplomacy in Iran during the 1850s, which elevated the country to the status of the first European power in the country. Following Russia’s defeat in the Crimean War, Britain severed its diplomatic relations with Iran over a sovereignty dispute involving Herat in Afghanistan, which Britain perceived as a threat to British India. Iran reacted to these developments by turning to France both as a peace broker and a significant ally. France’s prestige in west Asia further rose with the defeat of Russia in the Crimean War. The country took advantage of this enhanced role by seeking to expand its sphere of influence in the region through trade. A lasting presence in Iran seemed secured with the conclusion, in 1855, of a commercial treaty with the Qajar regime that gave France the same rights and privileges as Britain and Russia. Yet, the informal empire France managed to establish in Iran was based on the aura of its language and culture. The Third Republic indeed engaged in a “civilizing mission” through the establishment of French schools in Iran; it also participated in archaeological explorations there. Archaeology and education thus became an integral part of France’s Iran diplomacy during the latter part of the nineteenth century. It maintained this status until the end of the century, after which its standing in Iran began to decline amidst shifting political dynamics in the region.
COULOMB COLLISIONAL ANALYSIS OF SOLAR WIND IONS
Johnson, Elliot
Owing to its low density and high temperature, the solar wind frequently exhibits strong departures from local thermodynamic equilibrium (LTE). Previous studies have focused on non-LTE features but were largely limited to using observations from single spacecrafts. In contrast, this research utilized contemporaneous, in-situ observations from two different spacecraft at two different distances from the Sun. Collisional analysis combines the effects of collisional relaxation and large-scale expansion, quantifying how ion relative temperature and differential flow evolve through the heliosphere. This generates a prediction for the distribution of these quantities in the solar wind at any distance from the Sun. Results suggest that ion relative temperature and differential flow through the inner heliosphere is largely governed by the effects of expansion and Coulomb collisions, and that preferential heating is largely limited to the corona.
CARBON ADDITIVE MANUFACTURING: INNOVATION AND APPLICATIONS OF LITHIUM-ION BATTERY TECHNOLOGY
Park, Soyeon
Carbon, as a fundamental material class, plays an essential role in various applications due to its exceptional properties and size-related benefits. Additive manufacturing, also known as 3D printing, can be a powerful technique in creating hierarchical 3D carbon architectures with geometric control across different length scales, allowing for integrating mechanical functionalities, such as enhanced stiffness and strength, with additional properties like electrical conductivity. This dissertation seeks to develop universal carbon feedstocks as well as 3D printing/secondary carbonization processes for creating a programmed 3D carbon structure and investigates the potential practical utility and applications of this structure, particularly in advancing lithium-ion batteries. This study focuses on elucidating the processing-structure-performance relationship in printed 3D carbon structures. It introduces an innovative approach combining Fused Filament Fabrication (FFF) and an optimized post-carbonization process and involves a comprehensive analysis of the processability of feedstocks (i.e., high-loaded carbon composite filaments) from printing to secondary process based on the characterization of their physical and mechanical properties. This manufacturing technique is further explored to create a 3D carbon scaffold with tailored carbon orientation and associated properties required for battery advancement. With a profound comprehension of the underlying mechanisms, the high shear flow inherent in extrusion 3D printing, coupled with secondary carbonization techniques, is utilized to manipulate particle orientation and electrode design across nano to macro scales, resulting in facilitating the production of advanced Lithium-ion batteries with improved Li-ion transport, insertion, and structural stability.
Small Discrete Object Tracking on Beaches and Foreshore Slope Effect on Cross-shore Sediment Transport
Laksanalamai, Jirat
The significant part of this study was to conduct an experiment in a wave flume to measure the trajectories of 20 small objects (gravel and microplastics) in the surf and swash zones on an equilibrium beach and a nourished foreshore beach with erosion and accretion in the swash zone. To develop a tracking model based on a kinematic Lagrangian model, the trajectory of each of the 20 objects was measured in six tests consisting of 100 runs with each run lasting 400 s. From the measurement, gravel particles were mobile only in the swash zone and moved seaward under wave downrush. Large and small microplastics moved onshore from the surf zone and accumulated in the lower swash zone of wave rundown or in the upper swash or berm zone of wave runup. Plastic particles remained on the evolving sand surface despite the erosion and accretion of the nourished foreshore. A simple tracking model is developed to predict the measured trajectories of the 20 particles of gravel and microplastics. The model was calibrated to predict limited net displacements of hypothetical sand particles on the equilibrium profile beach. For future applications, the tracking model may eventually be applied to track and clean up microplastics on beaches as well as to predict the destinations of sand particles placed on eroding beaches in beach nourishment projects. In countries where coastal engineering is developing, there is growing tendency to employ beach nourishment as coastal protection, despite limited wave data. This part of study introduces a simple analytical model proposed to estimate cross-shore sediment transport on a measured beach profile when wave data is unavailable. The model predicts offshore (onshore) sediment transport on the foreshore slope which is steeper (milder) than the equilibrium foreshore slope. A wave flume experiment was conducted to assess the model. Equilibrium, steep, and mild foreshores were constructed on a beach consisting of fine sand and exposed to identical irregular waves. The steep foreshore experienced rapid erosion, quickly transitioning to equilibrium, while accretion and equilibration on the mild slope occurred gradually. The calibrated model is able to predict the sediment transport rates on both the initial steep and mild foreshores with clear deviations from the equilibrium foreshore profile. The analytical model is furthermore compared with the nourished beach data at Pattaya, Thailand. Over the period from 2019 to 2023, bathymetric and topographic measurements were conducted yearly but water level and wave data were not measured. The analytical model is subsequently used to interpret the cross-shore sediment transport rate per unit width of the order of 10 m2/y and to estimate the degree of alongshore sand loss or gain. The simple model may eventually be extended to account for alongshore variability and become applicable to beach fill design.
LEVERAGING PROFESSIONAL LEARNING TO SUPPORT TEACHERS’ USE OF A COMPREHENSIVE LITERACY CURRICULUM
Bruno, Jamie
Recently, school districts have relied on professional learning (PL) to help teachers adopt curricula and implement practices aligned with the science of reading and to help students recover from learning interruptions due to the COVID-19 pandemic. Elementary English Language Arts teachers in Cecil County Public Schools are adopting Bookworms First Edition. To effectively implement the curriculum, they need evidence-informed PL. Currently, providing such PL is a challenge because the teachers have a wide variety of experience with the Bookworms Beta and there are a limited number of instructional coaches in CCPS. In this ELP, I identified, implemented, and reflected on the effects of a set of tools and strategies that addressed these challenges. I began by learning about the problem and possible solutions by conducting a literature review, developing and deploying an initial teacher survey, and completing a rubric collaboratively with school administrators. Next, I addressed the problem by developing a plan for professional learning and creating and sharing an infographic with guidance for effective feedback. Finally, I reflected on my efforts by collecting and analyzing data from coach observations of teachers’ instruction, teachers’ implementation goals, and a final teacher survey. While descriptive, the collective results suggest I successfully identified, implemented, and reflected on the use of a set of tools and methods to provide evidence-based, coherent PL to teachers. Over the course of this project, I encountered challenges related to dosage and school conditions that I describe. I also identify opportunities for improvement and revisions to my professional learning efforts that will apply to schools adopting Bookworms First Edition next year. For the schools that adopted Bookworms First Edition this year, a reasonable next step is to transfer PL responsibilities from district and consultant coaches to school-based staff.
MEMORABLE MESSAGES AS ANTICIPATORY RESILIENCE DURING THE EARLY YEARS OF COLLEGE
Boehm, Michele
This dissertation examines relationships between anticipatory resilience, communication resilience processes, and academic success outcomes among students in their early years of matriculation. Though resilience has over 60 years of research foregrounding in developmental psychology (O’Dougherty Wright et al., 2013), in the field of communication, conceptualizations and research to understand resilience are relatively recent developments. In 2010, Buzzanell theorized the role of communication in the development of resilience with the communication theory of resilience (CTR). CTR is comprised of five interrelated processes: affirming identity anchors, maintaining and using communication networks, constructing alternative logics, foregrounding productive action while backgrounding negative feelings, and crafting normalcy (Buzzanell, 2019; Wilson et al., 2021). While CTR proposes that CTR processes are enacted as resilience or to create resilient outcomes in response to trigger events, CTR also acknowledges that people may bring pre-existing experiences or understandings to adverse situations that may help them to be “better positioned than others to enact resilience” (Wilson et al., 2021, p. 481). CTR labels this idea anticipatory resilience and asserts that past experiences as well as exposure to the experiences of others through shared stories and memories can help bolster a person’s ability to face new challenges prior to experiencing them (Buzzanell, 2019). An example CTR provides is memorable messages shared from “family members and/or media celebrities about getting through hard times” as a source of anticipatory resilience (Wilson et al., 2021, p. 507). Memorable messages, interpersonal messages of value (Knapp et al., 1981) that stick with a person and remain easily accessible (Koenig Kellas, 2010), can provide people with valuable information such as an understanding of how to navigate a difficult time (Lucas & Buzzanell, 2012). This dissertation in research aims to further the limited research related to anticipatory resilience as a construct. Finally, CTR also proposes that CTR processes mediate the relationship between anticipatory resilience and resilient outcomes, with Wilson et al. (2021) acknowledging this assumption as an area of future research and clarification. This dissertation tests this proposed relationship to provide answers to fill this gap in the communication literature where resilience is concerned. By testing the relationships between anticipatory resilience, CTR processes, and adaptive outcomes in the face of stressful or transitional experiences, this dissertation supports the process-based conceptualization of resilience and the mediating role of communication resilience processes on students’ anticipatory resilience and institutional and goal commitment.
Aligning Bookworms Middle School to Culturally and Linguistically Sustaining Pedagogy: Creating a Gateway to the Third Space
Merkle, Sara Elizabeth
Bookworms Middle School (BWMS) is an English Language Arts (ELA) curriculum that attempts to mitigate the gap between research about adolescent literacy and adolescent literacy instruction. The author team makes explicit commitments about adolescent literacy and equity. However, just as teachers are bound by their knowledge, authors of curricula are bound by what they know and who they are. This Education Leadership Portfolio (ELP) seeks to address the problem of how a module of BWMS can be aligned to culturally and linguistically sustaining pedagogy (CLSP) for the purposes of centering students’ assets and disrupting the perspectives and biases of a privileged and mostly majoritized author team and honoring their explicit commitment to equity. A variety of improvement strategies were used to understand the interactions between adolescent literacy instruction and CLSP, evaluate the alignment of a module to CLSP, invest the voices and perspectives of diverse readers, and revise the module. A subsequent evaluation of the alignment of the revised module to CLSP revealed meaningful improvement. A module-specific professional development was created to allow the orientations toward equity, diversity, and inclusion (DEI) that are necessary to operationalize CLSP and to center students’ assets to percolate in teachers’ minds. Last, an Innovation Configuration was revised to facilitate ongoing implementation of the module. The revision process established during this ELP may be applied to other modules of BWMS. This project was guided by a theory of change. That theory proposes that aligning a module of BWMS to CLSP allows teachers and students to develop new knowledge about text, people, and the world and dispositions toward DEI. Somewhat dishearteningly, this project resulted in unexpected learning about the extent to which historical power inequities become barriers to students’ literacy achievement. However, this ELP also revealed that curricula can become a vehicle for literacy and equity.
Neurophysiological Substrates of Singing associated with Past Singing Experience and Task Difficulty
Vivero, Martin
This dissertation examined neurophysiological substrates of singing associated with past singing experience and task difficulty. Individuals trained (singers) and not trained (non-singers) in singing were required to sing difficult and easy melodies inside an MRI scanner. Task difficulty was determined empirically with pilot testing. fMRI and audio data were acquired for later analysis. Brain activity and pitch deviation were compared between singers and non-singers during singing either difficult or easy melodies, as well as within each group, during singing difficult and easy melodies. In addition, correlations were assessed between brain activity and pitch deviation per group and condition. Between groups, differences in brain activity and pitch deviation reached significance for difficult but not easy melodies. Each group sang difficult melodies less accurately than easy melodies. In singers, difficult vs. easy melodies elicited widespread bilateral activation, spanning across brain regions relevant to singing and sensitive to singing training. In non-singers, difficult vs. easy melodies elicited limited activation, circumscribed to the left hemisphere. Correlations between brain activity and pitch deviation were found for singers singing difficult melodies, and for non-singers singing easy melodies. These results suggest that differences in brain activity and pitch-related singing performance between singers and non-singers become larger with increasing task difficulty. Potentially, singers and non-singers share neural mechanisms for easy and distinctive neural mechanisms for difficult singing tasks. Alternatively, singers might activate singing circuits to a lesser extent for easy than difficult tasks, due to an optimization of neural resources (i.e., neural efficiency), whereas non-singers might engage less brain regions for singing, regardless of task difficulty. Increased activation in singers for difficult vs. easy melodies of right anterior insula, anterior cingulate cortex, Broca’s area and cerebellum supports the notion that singers have optimized neural circuits for singing, presumably developed in time. Increased activation of right anterior insula during singing has been previously linked to greater singers’ reliance on somatosensory feedback relative to auditory feedback. Distinctive increased activation of supplementary motor area for difficult vs. easy melodies in singers (rostral) and non-singers (caudal) might reflect key differences in motor planning of trained and untrained individuals facing a difficult task. Further research is required to better understand brain responses to singing tasks of varying difficulty by trained and untrained individuals, as well as their implications for singing training and voice learning in diverse populations.
Unraveling Cellular Dynamics through Stochastic Hybrid Models for Biomolecular and Neuronal Circuits
Vahdat, Zahra
Living cells exhibit significant stochastic fluctuations due to low molecular counts and inherently random biochemical processes. Leveraging stochastic models, we aim to unravel the underlying mechanisms governing information transfer and precision in the fundamental cellular processes. We delve into the intricate interplay between molecular variability and cellular processes, focusing on gene expression, cell size regulation, and neuronal synaptic transmission. Through systematic analyses, we explore various sources of noise, including stochastic bursting in protein synthesis, random events in protein turnover, and noise in cell-cycle progression. These analyses provide insights into the statistical properties of protein levels and their dependence on distinct noise mechanisms. Furthermore, we explore the role of feedback mechanisms in gene expression regulation, investigating how negative feedback circuits influence noise and sensitivity in protein levels. By comparing different feedback mechanisms under varying conditions, we uncover trade-offs between noise reduction and input-output sensitivity, highlighting the complex interplay between molecular regulation and cellular function. Moving beyond gene expression, we investigate the homeostatic mechanisms underlying cell size regulation. By modeling continuous growth and division processes, we uncover the role of nonlinear growth dynamics in maintaining size homeostasis. Our analyses reveal the intricate balance between cell growth, division, and feedback mechanisms, providing valuable insights into cellular size control mechanisms. In the realm of neuronal synaptic transmission, we explore the impact of diverse noise mechanisms on neurotransmitter release and postsynaptic neuron activity. Through mechanistic stochastic models, we quantify the dynamics of neurotransmitter release and synaptic efficacy, uncovering the complex relationship between noise, synaptic strength, and neuronal activity. Overall, this dissertation offers a comprehensive exploration of stochastic phenomena in cellular biology, providing novel insights into the mechanisms governing precision and variability in gene expression, cell size regulation, and neuronal synaptic transmission. By combining analytical approaches with stochastic modeling techniques, we elucidate fundamental questions surrounding molecular variability and its implications for cellular function and behavior.
Sm-based (Sm, Gd, Y, Zr)-(Fe, Co)-(Mo, V) Alloys with the ThMn12 Structure for Permanent Magnets: Synthesis, Processing and Characterization
Xu, Yitong
This dissertation investigates the synthesis, processing, and characterization of Sm-based (Sm, Gd, Y, Zr)-(Fe, Co)-(Mo, V) alloys with the ThMn12 structure for permanent magnet development. These materials are important for advancing the performance of rare-earth permanent magnets, which are critical components in various applications ranging from electric motors and generators to data storage devices. Through a comprehensive study of background knowledge and concepts of magnetism, synthesis procedures including the special techniques of melt-spinning and mechanical alloying and advanced structural and microstructural characterization, this research offers new insights into the intrinsic and hard magnetic properties of Sm-Fe(Co) based ThMn12 magnets. The dissertation systematically explores the effects of partial Sm substitution with Gd, Y and Zr and Fe substitution with Mo and V on the intrinsic and hard magnetic properties of these alloys. Additionally, it examines the magnetic hardening mechanisms in as-cast Sm-Fe-V alloys, contributing to the understanding of the coercivity development in bulk magnets. The results of this study demonstrate the potential of these Sm-based magnets to achieve high performance with reduced rare-earth content, addressing both economic and supply concerns associated with critical materials. This work not only contributes to the fundamental understanding of ThMn12 structure magnets, but it also provides a pathway towards the development of new materials for high-temperature and high-performance applications.

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