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DEVELOPMENT AND EVALUATION OF NOVEL TOOLS TO REDUCE VERTICAL TRANSMISSION OF FLAVOBACTERIUM PSYCHROPHILUM AND ENHANCE PREVENTION OF BACTERIAL COLDWATER DISEASE
No full textThesis (Ph.D.)--Michigan State University. Fisheries and Wildlife - Doctor of Philosophy, 2025Flavobacterium psychrophilum, etiological agent of bacterial coldwater disease (BCWD) and rainbow trout fry syndrome (RTFS), is a top contributor to disease associated mortality for captive reared salmonids (Family Salmonidae) worldwide. Considerable efforts have been undertaken to characterize the genetic diversity of this bacterium, which has proven to be vast and with noted implications for host species associations, virulence, and geographic dispersal, among others. Flavobacterium psychrophilum is also serotypically diverse, holding likely implications for the eventual development of efficacious vaccines \u2013 though the extent of this diversity, particularly in the United States, is not well understood. This extensive intraspecific diversity is likely an important contributing factor in continued difficulties with effective BCWD and RTFS prevention and control. Furthermore, it is increasingly evident that vertical transmission of the pathogen may be driving many F. psychrophilum associated losses. Notably, F. psychrophilum can be transmitted intra ovum, thereby circumventing conventional disease preventative measures. Considering these factors, my dissertation research sought to first elucidate the serovariation of F. psychrophilum in the United States, for the first time, using a highly reproducible molecular serocharacterization assay. In so doing, I characterized 320 F. psychrophilum isolates recovered from BCWD/RTFS epizootics and routine fish health surveillance efforts in 17 states from 1981 - 2021, representing 12 fish species and 1 hybrid. All five currently recognized F. psychrophilum molecular serogroups were identified, with notable variation by host species, geographic origin, genotype, and others. Next, and with the goal of creating a multipronged approach for reducing F. psychrophilum vertical transmission while also improving F. psychrophilum detection and identification capacities, I first devised a novel F. psychrophilum specific loop-mediated isothermal amplification (LAMP) assay and optimized it for use with fish reproductive fluids (i.e., milt and ovarian fluid) under field conditions. Then, towards partial validation, I subsequently deployed the assay alongside a current gold-standard F. psychrophilum detection method (i.e., bacterial culture and PCR identification) to screen the reproductive fluids of wild/feral populations of spawning salmonid species in Michigan. The new assay successfully identified heavily F. psychrophilum infected ovarian fluid samples, highlighting its potential to reduce vertical transmission risk when used as part of a testing-based gamete culling program. Building upon this success, I then adapted and partially validated the LAMP assay for the confirmatory identification of F. psychrophilum directly from in vitro cultured bacteria with no additional processing. The assay yields results in <30 minutes and requires only simple and inexpensive equipment, thereby providing a future means of expediting BCWD/RTFS diagnosis towards rapid intervention. I also adapted the new LAMP assay for use directly on fish with external BCWD-suspect lesions, with promising preliminary results. Pending further refinement and validation, this lesion-direct method may aid rapid, onsite, and non-lethal BCWD/RTFS diagnosis. Lastly, I evaluated a pre-fertilization iodophor egg disinfection method, with the goal of reducing the risk of F. psychrophilum vertical transmission after experimentally exposing rainbow trout eggs to the bacterium. Pre-fertilization disinfection was the only treatment that eliminated detectable F. psychrophilum in experimentally exposed eggs and fry, thereby contributing to a growing body of evidence that this method is promising for reducing the risk of egg-associated F. psychrophilum vertical transmission. Collectively, the new knowledge and tools that I generated herein hold strong promise for enhancing BCWD/RTFS prevention by informing potential future vaccine development efforts, offering multifaceted means of effectively breaking vertical transmission of F. psychrophilum, and enhancing the rapid and accurate diagnosis of BCWD and RTFS.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
An Empirical Investigation & Scale Development of Team-Level Negotiated Work Arrangements
No full textThesis (Ph.D.)--Michigan State University. Human Resources and Labor Relations-Doctor of Philosophy, 2025Scholars have long emphasized that employers must provide critical resources for teams to meet their goals and to be effective. Extending prior research on team resources and idiosyncratic deals (i-deals), I introduce the theoretical concept of team \u201cwe-deals\u201d. First, I define we-deals as non-standard arrangements negotiated by teams and outline its key components. We-deals help teams obtain resources and work modifications that are not readily accessible via standard work arrangements. Second, I develop and test a measure of we-deals across five samples of team members from the United States and China. To develop the we-deals scale, I investigate the theorized content dimensions of we-deals that teams seek for content adequacy, generate scale items and use members of teams for item content classification, explore the factor structure of we-deals content, and confirm the identified factor structure while testing whether we-deals can be distinguished from related constructs. Finally, I test the criterion validity of the we-deals scale through a Chinese field sample of work teams by testing how we-deals relate to team effectiveness as indexed by team performance, team OCB, and team viability. Results provide evidence for six we-deals factors that are conceptually distinct and are positively related to team effectiveness (i.e., team performance, team OCB, team viability).Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Towards Electric Field and Atom Number Upgrades For a Higher Sensitivity Search for the Atomic Electric Dipole Moment of Radium-225
No full textThesis (Ph.D.)--Michigan State University. Physics - Doctor of Philosophy, 2025The discovery of a permanent non-zero Electric Dipole Moment (EDM) would be a clean signature of a new source of Charge-Parity (CP) violation in the universe. Radium-225 is an ideal candidate for these searches, due to its nuclear octupole deformation. This gives it a large intrinsic nuclear Schiff moment, and a nearly degenerate parity doublet, which cause an enhancement factor in the search for new sources of CP violation for a given EDM sensitivity. Previous measurements of the EDM of the Radium-225 atom were able to achieve a sensitivity on the order of 10^{-23} \ecm. The next generation of this experiment aims to achieve sensitivity of 10^{-26} \ecm, which in the global picture would set new limits on various CP violating sources. Crucial to this sensitivity enhancement is an upgrade to the high voltage used to couple the EDM to an external electric field. By achieving higher voltages with better understanding of electric field reversibility, statistical sensitivity can be increased and systematic uncertainty reduced. In addition, the Isotope Harvesting (IH) program at the Facility for Rare Isotope Beams (FRIB) will once again enable radium-225 to be procured for the experiment. To ensure optimal harvesting efficiency, the study of various techniques to create a beam of atomic radium will be necessary. For this reason, an atomic beam fluorescence apparatus has been built at FRIB.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Collective Behavior in Complex Networks : Applications to Biology
No full textThesis (Ph.D.)--Michigan State University. Physics - Doctor of Philosophy, 2025This dissertation investigates the principles of collective behavior in complex networks, focusing on how modular architectures and non-reciprocal interactions shape system dynamics and adaptive responses. The research integrates two complementary approaches: a data-driven analysis of biological networks (Track I) and a theoretical exploration of a non-reciprocal Hopfield model (Track II).Track I employs Differential Network (DN) analysis to examine longitudinal RNA-sequencing data from two biological systems: human saliva following PPSV23 vaccination and primary B-cells subjected to Rituximab treatment. This methodology uncovers stimulus-specific modular reorganization within these networks. Key findings include the identification of temporally ordered activation patterns among gene communities: in saliva, fifteen gene communities show a well-ordered activation cascade; in B cells, fourteen communities cluster into three temporal response classes. Functional enrichment confirms that each module specializes in coherent pathways, while hub-gene analysis highlights IL4R (saliva) and PELI1 (B cells) as putative drivers of the observed immune and drug responses. These results suggest that inter-module couplings are pivotal in orchestrating complex biological processes.Track II develops a theoretical framework using a non-reciprocal Hopfield network, featuring two interacting subnetworks (termed similarity and differential), to elucidate the dynamic mechanisms that could drive such modular behaviors. This investigation utilizes a combination of mean-field theory, stochastic Langevin equations, Master Equation formalism, and large-scale Glauber Monte Carlo simulations. The model exhibits a rich phase diagram with distinct paramagnetic, memory retrieval, and limit-cycle dynamical regimes. These phases are separated by Hopf and fold bifurcation lines. Critical dynamics near these lines are characterized by scaling exponents (Hopf) and (fold), distinct response-time laws ( vs.\ ), and a limit-cycle coherence time that quantifies finite-size effects. These analytical predictions are numerically validated. By bridging empirical observations of adaptive modular responses in biological systems with a mechanistic understanding derived from a tractable theoretical model, this dissertation offers significant insights into how interactions both within and between network modules collectively govern global network behavior and facilitate functional adaptation in complex systems.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
WE EXIST PROUDLY : DISABLED AND NEURODIVERGENT TEACHER CANDIDATES
No full textThesis (Ph.D.)--Michigan State University. Mathematics Education - Doctor of Philosophy, 2025This dissertation is formatted as a three-article dissertation that explores the experiences and possible supports for disabled mathematics teacher candidates (TCs). In order to explore and expand the knowledge around this within the fields of mathematics education and special education, the dissertation begins with a systematic review to establish the current state of the field. This current state presents a dearth of research in the area. The empirical work of this dissertation is the design and delivery of a professional development (PD) for disabled TCs. The PD uses methodological tools that employ a diverse range of ways of communicating and thereby reaches to stretch the understanding of how we might understand the experiences of disabled TCs. These tools also cultivated the PD as an inclusive and universally designed space. The dissertation concludes that more work is needed to understand the experiences of disabled mathematics TCs. Additionally, this dissertation works covertly to force an understanding that special education TCs are also mathematics TCs because special educators usually teach all subjects.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
INTEGRATING GENOMIC AND PHENOMIC METHODS TO INVESTIGATE MAIZE RESPONSE TO NITROGEN FERTILIZER
No full textThesis (Ph.D.)--Michigan State University. Plant Breeding, Genetics and Biotechnology - Plant Biology - Doctor of Philosophy, 2025Nitrogen (N) fertilizer is essential for maximizing maize grain yield, yet optimizing N application remains challenging due to complex interactions between genotype, environment, and management practices. Yield response to nitrogen (YieldResp2N) exhibits substantial variation across genotypes and environments, limiting the development of predictable N management strategies and breeding progress. Understanding the physiological mechanisms and the genetic variation underlying N response is critical for developing more efficient maize production systems that balance yield optimization with environmental sustainability. This dissertation employs an integrated multi-scale approach combining transcriptomics, remote sensing, and quantitative genetics to characterize maize N response across different biological and temporal scales.In Chapter 1, transcriptomic profiling using BRB-seq was conducted on five maize hybrids grown under contrasting N treatments (25 vs 150 lbs N/acre) across three developmental stages (V7, V15, R2). While some genes showed conserved responses, many transcriptomic changes were hybrid-specific, with different genotypes employing distinct molecular strategies for N response. Year-to-year validation using RT-qPCR confirmed that N responses vary substantially across seasons in a hybrid-specific manner, though a core set of genes maintained consistent responses across environments. Chapter 2 expands the investigation to 21 maize hybrids grown across three years (2020-2022) under the same N treatments, integrating high-throughput remote sensing from unoccupied aerial systems (UAS) with traditional phenotyping approaches. Genotype rankings for N response were inconsistent across years, with negative correlations between some year pairs. Analysis of variance partitioning revealed that genotype and genotype x environment effects explained a higher proportion of variance for YieldResp2N compared to raw yield, indicating N response represents a distinct trait worthy of targeted breeding efforts but the interaction term remains an obstacle towards application. Novel remote sensing metrics are developed by integrating multispectral imagery with environmental data. The most successful metric, GDDAccum (growing degree days accumulated while productive), quantifies the duration plants remain metabolically active based on reflectance properties and scaled to individual plot characteristics. Chapter 3 further expands the study to 105 maize inbred lines across two years (2022-2023), focusing on functional staygreen traits measured just before senescence under the same contrasting N regimes. Gas exchange measurements were integrated with vegetation indices (VIs) derived from UAS imagery. CO2 assimilation rate (A) had a tighter relationship with yield in high N while H2O transpiration rate (E) was more tightly linked in low N. VIs were most tightly linked with A across all years and environments. Genome-wide association study mapping identified 693 unique quantitative trait nucleotides (QTN) across 24 traits, with most QTN being specific to the year and N treatment. This pattern indicates that genetic architecture underlying these traits is strongly influenced by N availability, with important implications for breeding program design. A pleiotropic QTN (chr8_134344930) affecting both A and remotely sensed VIs was identified, with the nearby gene Zm00001eb354870 showing overlap with previous mapping studies. The substantial genotype x environment interactions observed across all scales of investigation highlight the complexity of N response and the limitations of fertilizer recommendations based on average performance. The overall instability of genotype rankings across environments indicates that breeding programs must evaluate candidates across diverse N and environmental conditions if they wish to develop robust varieties. This dissertation establishes a comprehensive framework for investigating complex agricultural traits through integrated multi-scale approaches. Ultimately, this work contributes to the development of more sustainable and efficient maize production systems that optimize yield while minimizing environmental impacts through improved understanding and management of plant-nutrient interactions.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Search for ttZ' -> tttt Production in the Multilepton Final State in pp Collisions at 1as = 13 TeV with the ATLAS Detector
No full textThesis (Ph.D.)--Michigan State University. Physics - Doctor of Philosophy, 2025This dissertation presents a search for a new beyond-the-Standard-Model (BSM) particle at the Large Hadron Collider (LHC). Many BSM models predict a new heavy vector boson (Z') that couples primarily to the top quark in both production and decay (top-philic). The search is performed in multilepton events consistent with four-top-quark production, due to the distinctive signature of the multilepton final states and the its robustness against common background processes at the LHC. Analysis data was collected by the ATLAS detector from 2015 to 2018, using proton-proton collisions at the LHC at a center-of-mass energy of 13 TeV. No statistically significant deviation from Standard Model predictions is observed. Exclusion limits are set on the production cross section of the targeted top-philic particle in the mass range between 1 TeV and 3 TeV.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Robust Closed-loop Learning for Safe Optimal Control of Autonomous Systems
No full textThesis (Ph.D.)--Michigan State University. Mechanical Engineering - Doctor of Philosophy, 2025This dissertation explores the development of robust, data-driven, and predictive control algorithms to ensure the safe and optimal operation of autonomous systems in uncertain environments. The core contributions span several emerging directions in learning-based control, including entropy-regularized safe LQR, conflict-aware safe optimal frameworks, and direct data-driven predictive control from noisy measurements. Additionally, the work introduces a novel approach to gradient descent for control design, enabling real-time and scalable optimization-based feedback policies directly from data. Each proposed method addresses key limitations of classical techniques, such as a lack of robustness, inefficiency under noise, or high data demand, and is validated through theoretical analysis and simulation on control benchmarks such as vehicle steering and mobile robot planning tasks. Together, these results advance the safe deployment of learning-based controllers in real-world autonomous systems.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
