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ASSETS & AGENCY : BLACK HERITAGE ARTS AND ACTIVISM IN CULTURALLY RESPONSIVE AND SUSTAINING COMPUTER SCIENCE EDUCATION
No full textThesis (Ph.D.)--Michigan State University. Educational Psychology and Educational Technology - Doctor of Philosophy, 2025While being responsive might cause one to look back, relying on tradition and heritage,and being sustaining might cause one to look forward toward the future, being both responsive and sustaining creates an opportunity to synthesize something new. First, I use a systematic literature review method to uncover approaches to being \u201cculturally sustaining\u201d in CS education and how these approaches are enacted to answer the call to improve representation in CS education and industry. This review provides a critical foundation for the subsequent design of the empirical studies here and elsewhere. Next, the research and teaching that carried out in this dissertation project uses culturally responsive-sustaining computing (CRSC) pedagogical strategies to carefully demonstrate the intersections of Black cultural imagination, liberation, and technology in ways that sustain, reinterpret, and reimagine the ethos of tradition. Amiri Baraka tells us that creation powered by the Black ethos (i.e. the epistemology and philosophies of African descended peoples) brings about \u201cvery special results\u201d and that these special results express truthfully and totally the experiences of communities, affirm heritages, and shape futures. Thus, the second article is a design-based research study that produced a design narrative, detailing the design of CRSC curricular materials for Advanced Placement Computer Science Principles (AP CSP). I found that leveraging Black textile traditions in the development of an online application and curricular materials is valuable for informing CRSC research and design. Here, the adoption of CRSC pedagogies divest from racist ideologies and logics and make explicit connections between culture and the AP CSP curriculum. Finally, in the third article, I focus on teacher professional development through a distributed model of co-teaching. In this project, there is a concerted effort between 3 educators to connect computer science (CS) to cultural expertise. To support rigorous, culturally-informed CS education a cultural expert from the local community is brought into the classroom to support educators\u2019 implementation of CRSC materials and efforts to connect to the community. This exchange does not minimize the technical acumen required for rigorous CS education; however, it challenges the status quo of what CS knowledge is, where it comes from, and how it is used. I conclude with a summary of key findings and a synthesis of the limitations and implications of this complete body of work.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Bill of Rights for the Homeless Act : a policy analysis
No full textIn Michigan, thousands of individuals experience homelessness each year. The issue of homelessness is multidimensional, consisting of poverty, mental health disorders, and systemic inequalities impacting individuals and their surrounding communities. Michigan H.B. 4919, titled The Bill of Rights for the Homeless Act, seeks to address homelessness in Michigan by establishing a legal framework to safeguard the rights of homeless individuals. This policy analysis highlights the public health implications of homelessness and the necessity for an updated homelessness management approach in Michigan to promote social justice. This policy analysis utilizes the Centers for Disease Control and Prevention (CDC) Policy Analytical Framework. A literature synthesis and environmental scan were conducted to determine an evidence-based solution for Michigan to adopt. A "Housing First" approach, which provides barrier-free, stable housing, was determined to be the best practice to reduce the impact of homelessness on health disparities. A rights-based approach can improve access to public services and foster a more inclusive society for homeless individuals waiting to be housed. Implementation involved poster presentations to stakeholders, including advocacy groups and local governments. Stakeholder feedback was collected to aid in formulating final recommendations for a homelessness management strategy. Smartphone polls were conducted before and after presentations with key stakeholders to gauge opinions of the recommended homelessness management policy. Polls address the policy's perceived impact on the health outcomes of homeless individuals because of the evidence-based policy solution. Results were analyzed to strengthen final policy recommendations. A "Housing First" policy alongside a Homeless Bill of Rights is an evidence-based solution to homelessness in Michigan. The enactment of this strategy will promote equity for homelessness and could improve the impact of homelessness on the individual and surrounding communities by reducing health disparities.Thesis (D.N.P.)--Michigan State University. Psychiatric mental health practitioner, 2025Includes bibliographical references (pages 62-66
Radiation safety : the student perspective
No full textRadiation exposure has been shown to impact nearly every system in the human body, with serious health effects linked to ionizing radiation. Adherence to safety precautions is inconsistent due to the lack of standardized protocols and clear guidelines from professional and governing agencies. The burden of safety then defaults to department administration and individual healthcare providers. The purpose of this project is to assess a student registered nurse anesthetist's knowledge of radiation safety and identify barriers that may impact adherence to radiation safety practices. The project team will build a department-specific radiation safety protocol based on the best evidence and results of the survey.Thesis (D.N.P.)--Michigan State University. Nurse anesthesiology, 2025Includes bibliographical reference
Advancing green practices in the operating room
No full textHospital systems produce a substantial amount of environmental pollution, contributing significantly to global greenhouse gas (GHG) emissions and climate-related health threats. In the United States, healthcare accounts for 10% of national GHG emissions and generates five million tons of waste annually, with operating rooms (ORs) responsible for more than 30% of this burden. Despite well-documented benefits of recycling programs, many ORs lack structured waste-management systems, resulting in improper segregation, excessive reliance on single-use devices, and increased disposal costs. This quality improvement initiative focuses on a mid-Michigan hospital in which the OR generates one-third of all hospital waste and 60% of regulated medical waste. This project aims to reduce the facility's environmental footprint by implementing a three-pronged sustainability program targeting reusable airway equipment, surgical blue wrap recycling, and improved sharps disposal. A comprehensive literature synthesis demonstrates that reusable laryngoscopy equipment markedly decreases carbon emissions and costs, upcycling blue wrap generates economic and community benefits, and proper sharps segregation significantly reduces regulated waste volume. Guided by a SWOT analysis, the proposed intervention includes staff education, visual aids, and structured waste-segregation protocols. Baseline and post-implementation data will compare the weights of waste in each category over a six-month period. Expected outcomes include reduced GHG emissions, lower disposal costs, improved recycling compliance, and strengthened institutional sustainability practices. By integrating environmental stewardship into perioperative workflows, hospitals can enhance operational efficiency, support public health, and mitigate the growing climate impact of healthcare delivery.Thesis (D.N.P.)--Michigan State University. Nurse anesthesiology, 2025Includes bibliographical reference
ALGORITHMS TO ASSESS THE STRUCTURAL AND FUNCTIONAL CHANGES AT THE TISSUE ELECTRODE INTERFACE THROUGH THE ANALYSIS OF GENE EXPRESSION, METRICS OF ELECTROPHYSIOLOGY, AND ASTROCYTE MORPHOLOGY
No full textThesis (Ph.D.)--Michigan State University. Electrical and Computer Engineering - Doctor of Philosophy, 2025Intracortical neural implants (ICNTs) are a powerful tool to treat and study neurological disorders.The performance of these implants depends on successful recording and stimulation for extended periods (up to years). This requires the recorded signal to remain consistent throughout implantation, or, from the perspective of providing stimulation, the stimulation with the same parameters should exhibit similar effects. This doesn\u2019t hold true for ICNTs; the recorded signals exhibit intra-day variability, loss of signal quality, and potential desensitization to stimulation over chronic periods. The biological tissue response is a significant factor contributing to the loss of recording quality and signal instability for intracortical neural implants at chronic time points. Neuronal death and the presence of astrocytes around the implant are quantified to measure the strength of the tissue response to the implanted electrode. The usual trend observed is increasing neuronal death, the presence of astrocytes near the implant, and the formation of a glial sheath around the implant at chronic time points. The biocompatibility of available neural implants is primarily judged based on these two metrics. These metrics have guided various designs to reduce the tissue response, lowering both astrocytic and neuronal death and density around the implant. However, the tissue response is still triggered, and signal instability remains problematic. This leads us to believe that conventional metrics alone are insufficient in guiding implant design. Other metrics must be uncovered to complete the parameter space governing the biological tissue response to neural implants. The goal of this thesis is to create computational pipelines using signal processing, image processing, and data analysis methods to (1) better understand the interaction between the tissue and neural implant, (2) uncover variables that might affect the recording quality of the implant, and (3) potentially guide future neural implant design from the perspective of gene expression, metrics of extracellular recordings, and astrocyte morphology.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
SYSTEMIC TO SYNOVIAL : INVESTIGATING THE ROLE OF INSULIN DYSREGULATION IN EQUINE METABOLIC OSTEOARTHRITIS DEVELOPMENT AND MANAGEMENT
No full textThesis (Ph.D.)--Michigan State University. Comparative Medicine and Integrative Biology - Doctor of Philosophy, 2025Intra-articular (IA) steroids such as triamcinolone acetonide (TA) are commonly used to treat osteoarthritis (OA) but may increase the risk of laminitis due to hyperinsulinemia. Horses with endocrinopathies may exhibit differing insulin responses to IA TA compared to metabolically normal horses due to the presence of insulin dysregulation (ID), which suggests they may have a different subtype of OA. If a metabolic osteoarthritis (Met-OA) subtype, which has been described in humans with metabolic syndrome, exists, this prompts the need for alternative therapies for OA. Chapter 2 describes the effects of IA TA on insulin and glucose concentrations in metabolically normal horses. Ten horses with normal insulin regulation received 18 mg of TA into one middle carpal joint. Insulin and glucose concentrations were serially evaluated and increased up to 48 hours following IA TA in metabolically normal horses. Chapter 3 describes the effects of IA TA on insulin, glucose, high molecular weight, and total adiponectin in horses with diagnosed endocrinopathies. Six metabolically normal, 5 ID, and 6 PPID horses received 18 mg of TA into one middle carpal joint. Insulin concentrations were higher in ID horses compared to pituitary pars intermedia dysfunction (PPID) and metabolically normal horses at several time points following IA TA, placing them at greater risk of laminitis development. Glucose concentrations did not differ between the groups. Total, but not high molecular weight (HMW) adiponectin, decreased in metabolically normal and PPID at several time points. Chapter 4 describes the use of metabolomics to evaluate if synovial fluid (SF) metabolite differences exist between different joint subtypes (Normal-noOA, Met-noOA, OA, and Met-OA). Metabolomics was also used to assess IA and systemic effects of IA TA in metabolically normal and ID horses. Significant metabolite differences existed between Met-OA and OA joints, primarily related to pathways involving lipids and amino acids, providing evidence that the Met-OA subtype may exist in ID horses. IA TA significantly altered several SF and plasma metabolites, with distinct profiles in ID versus metabolically normal horses, suggesting ID horses have a different metabolite response. Chapter 5 explores possible mechanisms behind an alternative or adjunct therapy to steroids, platelet-rich plasma (PRP). Dickkopf-1 (Dkk-1), a Wnt pathway antagonist, is present in equine platelet-rich plasma (PRP) and released by equine platelets. Bovine thrombin-activated PRP from ten horses created a greater release of Dkk-1 from platelets than the freeze-thaw cycle. A positive correlation was observed between platelet concentration and Dkk-1 for both methods. Chapter 6 evaluates an alternative or adjunct therapy to IA steroids, a rehabilitative whole-body resistance band wrap (RBW), on lameness, range of motion, muscular function, and cortisol in nine horses with gait asymmetries. Short-term and long-term (exercise protocol) effects were evaluated. The RBW demonstrated short-term improvements in the joint range of motion in the carpus, tarsus, and shoulder, as well as the back angle. In the long term, no improvements were noted. Cortisol concentrations were lower in horses while wearing the RBW. These findings indicate the RBW has beneficial short-term but not long-term effects. These chapters examine how ID influences OA and IA steroid response and assess adjunct therapies that may work as alternatives to IA steroid treatment.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Implicit Regularization of hyperparameters in deep learning : Beyond convexity and small steps
No full textThesis (Ph.D.)--Michigan State University. Computational Mathematics, Science and Engineering - Doctor of Philosophy, 2025Understanding the optimization of gradient-based methods is crucial to comprehending deep learning. This thesis investigates the implicit regularization induced by gradient descent algorithms, focusing on the role of three critical hyperparameters: step-size, momentum, and stochastic noise variance. Departing from past literature that often relies on simplifying assumptions such as convexity or infinitesimal step-sizes, our work concentrates on the practical deep learning regime where these assumptions are often violated. We demonstrate how these hyperparameters implicitly guide the iterate dynamics toward favorable solutions.In the first chapter, we examine the effect of a large step-size in an overparameterized deep matrix factorization problem designed to fit a low-rank matrix. Through a fine-grained analysis, we show that a learning rate beyond a specific threshold, dependent on the depth and singular values of target low rank matrix, drives the iterates toward the flattest global minimum and induces stable oscillations around it. This reveals the ability of gradient descent to escape sharper global minima and stably oscillate about balanced solution. The second chapter investigates the implicit regularization induced by Polyak's heavy-ball momentum. We show that the discrete momentum update approximates a continuous trajectory governed by a modified loss function, which contains an implicit gradient regularizer. Consequently, a finite step-size and momentum jointly steer the iterate trajectory along regions of smaller gradient norm. This analysis is extended to the stochastic version of gradient descent with momentum, where the implicit regularization is shown to depend jointly on the step-size, momentum, and minibatch variance. In the third chapter, we study the implicit regularization of weight-perturbed gradient descent, where perturbations are drawn from a Gaussian distribution before each gradient step. We calculate a stability threshold for this method based on a local quadratic approximation of the loss and show that deep neural networks trained with weight perturbation typically operate near this threshold. Our analysis provides insight into why weight perturbation may improve generalization over full-batch gradient descent and clarifies the roles of noise variance and the number of Monte Carlo samples in this process. The fourth chapter explores the implicit architectural bias of deep convolutional neural networks in unsupervised image reconstruction. We show that while dense architectures are prone to overfitting measurement noise, sparse architectures are resilient and can recover clean images without the need for early stopping. We propose an algorithm called "Optimal Eye Surgeon" to efficiently recover these sparse architectures and train them to alleviate overfitting. The fifth chapter assesses the efficacy of explicit regularization for signal reconstruction in inverse problems. We demonstrate that these explicit regularizers can be learned within an minimization framework through bilevel optimization. This chapter complements the rest of the thesis by showing the importance of external regularization in solving inverse problems.In the final chapter, we explore promising future directions for understanding deep learning phenomena through the lens of implicit regularization in optimization.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
AN INVESTIGATION ON THE EFFECTS OF MAGNETIC SHIELDING AND THE THERMOELECTRIC SEEBECK EFFECT FOR SRF APPLICATIONS
No full textThesis (M.S.)--Michigan State University. Accelerator Science and Engineering \u2013 Master of Science, 2025The Facility for Rare Isotope Beams (FRIB) driving linear accelerator operates using 324 superconducting cavities, which consist of 80.5 MHz Quarter Wave Resonators (QWRs), and 322 MHz Half Wave Resonators (HWRs) respectively with four operational beta values. These beta values correspond to \u3b2 = 0.041 and 0.085 QWRs, as well as \u3b2 = 0.29 and 0.53 HWRs. Improving the Quality factor (Q0) value, which is a factor derived from the stored energy in a cavity over power lost from the cavity, and the Accelerating gradient (Eacc), which is a measure of average energy gain per unit length per particle, will therefore improve the operation of scientific endeavors within FRIB. The FRIB 322 MHz HWRs are operated at a temperature of 2 Kelvin. At this frequency and temperature, Bardeen-Cooper-Schrieffer (BCS) surface resistance is small (0.5 n\u3a9). Residual surface resistance is the remaining dominant factor in this relationship, which is valued at around ~5 n\u3a9. Current R&D efforts indicate that residual surface resistance due to flux trapping causes 80% of losses within the cavity. One of the contributing factors of flux trapping within the cavity is the static ambient magnetic field present during cool down; a combination of residual magnetic flux from surrounding parts, and the earth\u2019s background field. Another possible contribution is from thermoelectric current effects generated by dissimilar metals at a temperature gradient, known as the Seebeck effect. This occurs while the niobium cavity is undergoing cryogenic cooling to reach the superconducting phase transition. A reduction strategy to limit these two contributing factors is to shield against the static magnetic field and eliminate the thermoelectric Seebeck effect in the subcomponents. The goal of this thesis is to understand and mitigate the residual surface resistance generated by static magnetic fields and thermoelectric Seebeck effects, and for the cavity to operate at a higher field. The research focuses upon 1) measuring the effectiveness of local magnetic shielding on the cavity, 2) demonstrating the thermoelectric Seebeck effect is generated by different metals during cryogenic cool down, and 3) measurement of the magnetic flux generated by these thermoelectric Seebeck effects. This thesis will conclude with paths forward to reduce the Seebeck coefficients on the cavity, improving operational performance and opening up possibilities of operating the HWRs at double their specification values, which would result in a Q0 value greater than 3 x 1010, and with the accelerating gradient (Eacc) equal to 15 MV/m.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
From Sleepy School Boards to Politics on the Playground : A 3 Paper Dissertation Mapping the Landscape of Interest Group and Political Party Involvement in School Boards
No full textThesis (Ph.D.)--Michigan State University. Education Policy - Doctor of Philosophy, 2025Over the last few years, education politics in the United States have undergone a dramatic transformation. While school board meetings were often considered a sleepy, non-partisan affair, this changed drastically in the early 2020s as they became a venue for political conflict over culturally divisive issues. Along with renewed culture war debates, new interest groups formed rapidly, such as Moms for Liberty and other local parent groups. These were not the only changes to education politics over the last decade. In 2018, the Supreme Court ruled that it was unconstitutional for public-sector unions to collect agency fees automatically, potentially weakening the power of local teachers' unions. While teachers' unions have traditionally been viewed as the most powerful group influencing school board elections, these developments raise questions about whether teachers' unions remain the most powerful and active group and how the rise of partisan interests in education is affecting school board governance and elections. Moreover, apart from teachers' unions, much remains unknown about interest groups at the local level. This three-paper dissertation addresses this gap in the literature by providing a contemporary understanding of the scope of interest groups and political party involvement in school boards. With over 13,000 school boards making decisions that impact students, parents, school employees, and broader communities, understanding the activity and influence of interest groups is crucial, as questions about interest groups are fundamental to understanding who holds power in policymaking. The first and second papers of this dissertation examine interest group and political party activity in local school boards across the U.S. by using a nationally representative survey of school board members in over 1,600 districts to understand which interest groups are perceived as active and influential by school board members. While the first paper focuses on the activity of teachers' unions, the second paper examines the activities of political parties and other partisan-aligned interest groups. The results of these papers reveal that interest group and political party involvement in school board elections is relatively rare, including the involvement of local teachers' unions. However, interest group competition is much more pluralistic than previous literature has suggested. Teachers' unions are just one of many actors, with parent groups being the most active. Notably, the results reveal that in places where endorsements are present in school board elections, political parties and partisan-aligned interest groups nearly always grant endorsements. The third paper, which utilizes qualitative interview data with school board candidates, incumbents, and interest group leaders in the state of Michigan, further examines how political parties and partisan-aligned interest groups are impacting local school board politics. The findings of this study reveal that whether school board members sought partisan endorsements or not, candidates were concerned about the challenges that rising partisanship has brought to their elections, including increased community division, polarization, and hostile rhetoric. The three studies in this dissertation shed light on the involvement of interest groups and political parties in local school board politics. By examining the activities of teachers' unions, the emergence of partisan-aligned interest groups and political parties, and the motivations behind candidates' engagement with these organizations, this research offers a contemporary understanding of interest group activity, the interactions between interest groups and local school boards, and the potential consequences of their involvement. In addition to contributing to our understanding of interest groups and political party involvement at the local level, this dissertation holds practical implications for policymakers, researchers, and communities striving to navigate the complexities of a rapidly changing political landscape.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
BRIDGING PLASMA SCALES USING DATA-DRIVEN MODEL IDENTIFICATION
No full textThesis (Ph.D.)--Michigan State University. Computational Mathematics, Science and Engineering - Doctor of Philosophy, 2025Plasma is a state of matter studied in many fields in part due to its influence across a widespan of spatial and temporal scales. This can range from plasma effects in star and galaxy evolution in astrophysics to fusion power research. Across these fields, however, common needs and questions arise. Plasma can be described using many different models, each accurate under different assumptions or at specific scales. From this variance in representation arises questions regarding how plasma act under extreme conditions, conditions where the best representative model is ambiguous, or when multiple regimes of behavior are traversed. Each regime requires different representations to accurately model behavior, where some techniques work by modeling the evolution of the particle distribution function while others work with moments requiring simplifying assumptions to be made regarding which effects are significant. Data-driven model identification techniques based on sparse-regression have recently been developed to identify governing partial differential equations (PDEs) from limited data. Such methods do not require a large body of training data and scale well with complex systems with many state variables, making them well-suited to work in problem spaces where limited highfidelity data is available and simplified fluid models are desirable. This dissertation explores how one such method, weak sparse identification of nonlinear dynamics (WSINDy), translates to plasma applications. First, variations of ideal MHD simulations across a variety of initial conditions are considered in relation to Shannon information entropy, providing insight into how WSINDy tends toward reduced representations in cases where the data is low in information. Next, challenges in scale bridging between particle and fluid behavior are addressed by analyzing fluid equation recovery as identified from particle simulations with varying degrees of diffusive behavior. Finally, a real-world application is explored for quantifying hall conductivity of the inner MITL on Sandia\u2019s Z-Machine.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references