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In the Shadows of Window Displays : The Industrialization of Fashion Retailing in Sheffield & Cologne, 1890-1914
Get PDFThesis (Ph.D.)--Michigan State University. History - Doctor of Philosophy, 2025This dissertation is a comparative study of the labor in department stores and fashion retailing at the turn of the twentieth century in Sheffield and Cologne. I argue that these stores were industrialized workplaces that were built on the skilled labor of women. My study shows that lower-middle-class identity existed as a material reality built by people\u2019s belief in it rather than explicitly clear economic conditions. My work attempts to bring questions of gender to social and labor history and to bridge the divide between ideas of production and consumption by focusing on the workers in retailing. The primary methodology is comparative, but this study is also supported by methodologies and theories in gender studies. The comparative lens provides insights into the similarities between the two national contexts which supports a discussion of the western European middle classes and their social position. Differences between the contexts highlight the malleability of the department store form as an industrialized employer. Furthermore, a gendered approach to labor history gives store employees and owners agency in the productive retailing process. Three of the four chapters focus on different aspects of department and fashion stores. The first presents my broad argument about the social and cultural capital fashion retailing work provided and the ways in which this aspect outweighed other considerations for workers. The second argues that the spatial aspects of stores and cities directly impacted people\u2019s experiences and understandings of retailing. The third and fourth claim that shop employment was skilled and included tangible and intangible aspects, both of which were vital to success. Ultimately, this study resituates department and fashioning stores within larger industrialized contexts of labor and distribution.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
ROBUST STATISTICAL METHODS FOR CAUSAL DISCOVERY IN ONE-SAMPLE MENDELIAN RANDOMIZATION STUDIES
Get PDFThesis (Ph.D.)--Michigan State University. Statistics - Doctor of Philosophy, 2025Mendelian Randomization (MR) has become a cornerstone approach for inferring causal relationships in epidemiological and genetic studies by leveraging genetic variants as instrumental variables (IV). Despite its popularity, conventional MR analyses, particularly those based on two-stage least squares (TSLS) and conducted within a single sample, face significant methodological challenges. These include selection-induced winner's curse and the pervasive problem of weak instruments and invalid IVs, all of which can undermine the reliability and interpretability of causal effect estimates.To address these limitations, this dissertation develops a unified and robust MR framework through a sequence of methodological innovations. First, we introduce MR-SPLIT, a novel adaptive sample-splitting and cross-fitting procedure that effectively mitigates biases arising from IV selection and weak instruments in one-sample MR settings. MR-SPLIT employs multiple sample splits to further enhance robustness, demonstrating superior performance in bias reduction, type I error control, and statistical power compared to existing approaches, as validated in extensive simulation studies and real-world data applications. Building on this foundation, we further propose MR-SPLIT+, which integrates best subset selection to accommodate invalid IVs under a relaxed plurality rule. MR-SPLIT+ substantially reduces estimation bias due to invalid instruments while maintaining efficiency and robustness. Simulation results consistently demonstrate that MR-SPLIT+ outperforms contemporary methods, and real-data analyses confirm its practical reliability in complex genetic architectures.Recognizing that causal relationships are often bidirectional or ambiguous, especially within gene expression networks and complex traits, we extend this framework to BiMR-SPLIT+. This method is specifically designed to disentangle bidirectional causality between pairs of traits, even when the underlying IV assumptions are partially violated. Extensive simulation studies and application to Drosophila melanogaster data illustrate that BiMR-SPLIT+ not only recapitulates established biological mechanisms, but also identifies novel candidate genes with potential regulatory roles. This bidirectional MR framework enables more accurate inference of gene-trait relationships and has broad implications for precision medicine.Collectively, this dissertation presents a cohesive suite of MR methodologies that systematically address weak and invalid IVs, IV selection bias, and bidirectional causality. The resulting toolkit substantially advances the reliability of causal inference in genetic epidemiology and lays the groundwork for future exploration in complex causal networks as large-scale human datasets continue to grow.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Multiscale Models in Bioelectrochemical Engineering
No full textThesis (Ph.D.)--Michigan State University. Chemical Engineering - Doctor of Philosophy, 2025Future technological progress will increasingly rely on biomaterials andbioinspired mechanisms. We can draw inspiration from nature to meet industrial needs because biological materials and mechanisms are often highly efficient and superior to other synthesized materials. Overall, the work herein strives to advance understanding of bio-inspired materials for a versatile set of engineering challenges and solutions.First, we study the highly efficient reaction cascade of thetricarboxylic acid (TCA), or Krebs, cycle, which converts nutrients in food to usable energy in fractions of seconds. Of particular interest in the TCA cycle is the conversion of oxaloacetate (OAA) between malate dehydrogenase (MDH) and citrate synthase (CS). Based on previous experimental and computational studies of recombinant and mutant MDH-CS complexes, a time-dependent finite difference model was developed to predict each complex's transfer efficiency and determine the surface\u2019s reaction pathways. Utilizing the kinetic parameters of recombinant and mutant complexes determined experimentally and surface transition probabilities of OAA from a Markov state model, the lag time of MDH-CS was determined computationally for recombinant and mutant complexes. Additional implications of the reaction path and reversible reaction at MDH are also considered. This model study furthers the understanding of dynamic enzymatic cascades and points toward approaches to cascade design. Second, we address the upgrading of bio-oil from pyrolyzedlignocellulosic biomass. Bio-oils yield a complex mixture of organic constituents that can be used as feedstock for valuable chemicals. However, these molecules are often oxygenated with low energy density. Recently, electrocatalytic hydrotreatment (ECH) of bio-oil was used to reduce oxygen content and increase energy density. Mechanistic understanding of interaction effects in mixtures is required for effective process design. Here, the mechanisms by which ECH of bio-oil constituent 4-propylphenol (4-PP) is inhibited by furfural (FF) are studied computationally. Inhibition is elucidated through potential dependent studies of adsorption and reaction mechanisms on a platinum/ruthenium electrocatalyst. Thermodynamic studies suggest that the FF pathways are competitive in adsorption and more favorable in reactions due to fewer barriers and smaller limiting potentials than the 4-PP pathways. Prediction of activation barriers by reaction energy scaling techniques found the FF pathways also to be favored kinetically over the 4-PP pathways. Reaction thermodynamics and kinetics models suggest that FF inhibits 4-PP hydrotreatment because the FF pathways are more favorable than 4-PP pathways on a platinum/ruthenium catalyst.Finally, a new biomaterial is evaluated as a high performance substratein tissue regeneration applications. A biomaterial was previously developed where gelatin was modified by methacrylic anhydride (GelMA) for stability at physiological conditions and silver-bioactive glass (Ag-BG) was added for antibacterial properties. Chemically linked GelMA and Ag-BG (GAB) was hypothesized to exhibit superior structural and cell viability behavior to GelMA in extrusion printed applications, which we seek to validate. Scaffold printing parameters were optimized for acellular GelMA, GAB, and a GelMA + Ag-BG composite bio-ink. Then, cell-laden media was introduced to the bio-ink to generate scaffolds. The viability of the cells within the scaffold was observed over time after printing. Ultimately, bio-ink performance and cell viability were poor for the selection of materials during cellular printing. These challenges suggest further optimization steps are needed within the material synthesis and printing processes, which is a point of more recent work that shows promising results.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
TWO STUDIES ON ASSESSING AI-AUGMENTED CREATIVITY WITH LARGE LANGUAGE MODELS
Get PDFThesis (Ph.D.)--Michigan State University. Business Administration \u2013 Information Technology Management \u2013 Doctor of Philosophy, 2025Large Language Models (LLMs) have been increasingly integrated into a variety of tasks, facilitating human endeavors in generating creative outputs, ranging from product ideation to digital artwork. Such novel capabilities of LLMs have ushered in a new era of collaboration between humans and Artificial Intelligence (AI), which has grabbed the attention of researchers and practitioners alike. Thus, in this dissertation, I explore the intersection of emerging LLMs and creativity, with a primary focus on writing tasks. This dissertation includes two studies. In the first study, I examine the impact on perceived creativity of varying levels of generative capabilities of LLMs - namely, randomness, which has been overlooked so far and which is manipulated via a quasi-experiment. I find that collaborating with an LLM with high randomness that generates more diverse advice does not necessarily lead to increased perceived creativity of work, as the role of humans matters. Moreover, I explore how the characteristics of human evaluators and their perceived extent of AI use influence their assessments of creativity. In the second study, I focus on growing concerns regarding the potential misuse of generative AI, particularly its capacity to produce plagiarized content. Motivated by the divergent thinking creativity literature using the Divergent Association Task (DAT), I construct DAT(Sent), a metric to proxy semantic dissimilarities within a document, and further propose an effective GPT detector classifier, GPT-DATector. I show that on average, human-generated contents have a larger DAT(Sent) than AI-generated texts across different writing tasks and datasets. Empirical evaluations demonstrate that the proposed GPT-DATector outperforms state-of-the-art models in terms of prediction performance. Most importantly, GPT-DATector has the potential to reduce bias in the detection of AI-generated text.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Wooden Stick + Flower : Curriculum as Embodied Lived Experiences in a Transnational Indigenous Educational Journey as a Uyghur Woman
No full textThesis (Ph.D.)--Michigan State University. Curriculum, Instruction, and Teacher Education - Doctor of Philosophy, 2025My dissertation is a multi-media autobiography presented through three integral parts: exhibition spaces in the Kresge Art Center and the Digital Scholarship Lab at Michigan State University (MSU); a final photobook, inclusive of a booklet with written narratives; and a pedagogical component showcased during the reception event in the gallery space. This comprehensive body of work explores themes of displacement, land(s), time, belonging, identity, loss, and memory through my personal lens as a Uyghur woman. Born and raised in the region referred to as China and currently residing in the so-called United States, my transnational lived experiences profoundly shape my perspective in examining these concepts.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
DEVELOPMENT AND APPLICATION OF FLEXIBLE DUAL-SIDED MICROELECTRODE ARRAYS(MEAS) FOR ADVANCED BIOELECTRONIC SENSING AND NEURAL INTERFACING
Get PDFThesis (Ph.D.)--Michigan State University. Neuroscience - Doctor of Philosophy, 2025A noteworthy in the dynamic field of neuroscience is the study of extracellular neural responses in live insect neurons, triggered by volatile organic compounds (VOCs). Biological olfaction has shown remarkable sensitivity in detecting low concentrations of VOCs, ranging from parts per billion (ppb) to parts per trillion (ppt) range, and minute changes in the compositions of gas mixtures. This scenario has inspired a novel concept for early lung cancer diagnosis, wherein odors exhaled by humans are channeled to insect sensory organs, like locust antennae. To effectively implement this scheme, efficient neural activity recording tools and robust analysis methods are essential. Tetrodes are commonly used in insect neural recordings, but are limited by their design, having only four electrodes that are widely spaced, rendering them relatively inefficient for detailed neural signals. Microelectrode arrays (MEAs) present a more promising alternative. Yet, in the specific context of insect brain neurology, there is a growing need for flexible, multi-channel, or even high-density MEAs(HDMEAs). Flexible MEAs, particularly those with high-density configurations, offer significant advantages over traditional rigid systems, including reduced tissue damage, better long-term stability, and higher resolution in both electrophysiological recording and biosensing applications. This dissertation presents the development and validation of advanced biosensing platforms for neurophysiological recording, emphasizing the integration of flexible dual-sided MEAs with locust olfactory systems to detect lung cancer biomarkers from VOCs. Through a multidisciplinary approach combining materials science, electronic engineering, and neurobiology, we explore the capabilities of HDMEAs and traditional MEAs to enhance the spatial and temporal resolution of neural recordings in both experimental and clinical settings. Chapter 1 begins with a foundational understanding of physiological signals and the techniques used to record them, followed by an in-depth discussion of MEAs, their principles, and their historical development. Special attention is given to the importance of flexibility and high channel density, which have transformed the design and performance of MEAs. Through an analysis of current flexible high-density MEAs, their fabrication, and the challenges they face, the chapter highlights the innovations that have propelled these tools into cutting-edge bioelectronic applications. Finally, strategies and future directions for next-generation flexible HDMEAs are outlined, setting the stage for their continued role in advanced sensing and neural interfacing technologies. Chapter 2 explores the development of dual-sided MEAs designed to enhance the recording capabilities and mechanical reliability necessary for in vivo insects\u2019 applications. The innovative folding-annealing technique used in this research allows for a substantial increase in the density of recording sites without expanding the MEAs' physical footprint. Chapter 3 expands on the application of these technologies, detailing the development of a flexible, dual-sided microelectrode array optimized for capturing the complex neural dynamics of the locust olfactory system. This novel biosensing platform leverages the locust's acute sensory detection capabilities to identify cancer-related VOCs, offering a promising alternative to traditional diagnostic methods like gas chromatography-mass spectrometry (GC-MS). Chapter 4 provides a comprehensive outlook and delineates ongoing work and conclusions from this research. Overall, this dissertation demonstrates the potential of merging biological systems with electronic sensing technologies to create sensitive and non-invasive diagnostic tools for human lung cancer. This work not only contributes to the field of biomedical engineering but also opens avenues for future research into bioelectronic interfaces and their applications in medical diagnostics.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
ENERGY-EFFICIENT CHEMICAL RECYCLING OF POLYETHYLENE TEREPHTHALATE (PET)
Get PDFThesis (Ph.D.)--Michigan State University. Chemistry - Doctor of Philosophy, 2025Energy-efficient recycling of post-consumer polyethylene terephthalate (PET) is a persisting challenge in the field of plastic circular economy. Today, the major method for PET recycling is mechanical recycling, in which the quality of the recycled PET decreases with each cycle. To address this, chemical recycling methods have been developed where PET is depolymerized to its parent monomers that can be repolymerized to yield virgin PET. This Ph.D. thesis is primarily focused on an energy-efficient chemical recycling method to convert discarded PET into its parent monomers for remanufacturing virgin PET. For this purpose, the impact of different catalysts, diols, and melt-pretreatment on depolymerization rates of PET has been investigated. Initially, pretreatment was effective in eliminating the crystalline regions that hinder the depolymerization process. Furthermore, the addition of catalyst and diol during the melt-pretreatment process could reduce the chain length of the polymer while active sites were created to accelerate the rate of depolymerization within the chunk of polymer. PET samples were subjected to methanolysis at temperatures ranging from 140 \ub0C to 200 \ub0C, and results revealed that the time for full depolymerization for pretreated and control (without pretreatment) samples were significantly different. For the optimized melt-pretreatment process and reaction condition, in the case of methanolysis, at 200\ub0C, the time of full depolymerization shortened from 166 min to 7 min yielding >99% dimethyl terephthalate (DMT), while a minimum of 8-fold decrease in the energy demand for the depolymerization of melt-pretreated PET in comparison to the untreated PET was achieved. In the case of PET glycolysis, the optimal pretreatment could reduce the depolymerization time from 181 min to 9 min (under the same optimal reaction conditions) at 180 \ub0C and yielded ~85% monomer. The scope of the research was further expanded and two organic catalysts, were employed as alternatives for zinc-based catalysts. The addition of 0.5 mol% of catalyst and diol during melt-pretreatment confirmed the striking effect of this extrusion-quench pretreatment on the organocatalytic depolymerization at 190 \u25e6C enabling full conversion of PET within 30 to 32 minutes in the presence of either organic catalyst, while conserving at least 38.5% of the required energy. With the growing production and consumption of PET, this project can help to convert billion tons/year of waste PET bottles into valuable materials and save resources. In a separate study, a technoeconomic analysis (TEA) was performed for a novel ionic polybutylene adipate-co-terephthalate (CPBAT) as a paper coating material with excellent water-in-oil resistance. The TEA determined the total capital investment for a production capacity of 1 ton of CPBAT per day. The minimum selling prices of CPBAT coated on Kraft paper (CPBAT-K) and CPBAT coated on starch-coated paper (CPBAT-S) are estimated to be 1.864/m2, respectively. Additionally, the results of a sensitivity analysis show that the production of CPBAT-K and CPBAT-S is highly sensitive to the plant production capacity, raw material costs, the energy efficiency of the coating process, and reaction energy, as well as reaction yield. Additionally, recovery of the ionization solvent only marginally increases the selling prices of CPBAT-K and CPBAT-S, hence it is highly suggested. In the base case scenario, the price of CPBAT-K is ~40%, and CPBAT-S is ~96% more than that of commercial polyethylene-coated paper (PE Paper). With increased production capacity, lower cost of raw material, use of more energy-efficient coating machines, and partial recovery of the energy produced from the reactions, the MSPs will reduce to 0.588 and $0.914/m2, for CPBAT-K and CPBAT-S respectively. Conclusively, with comparable mechanical and barrier properties to PE paper and the added benefit of biodegradability and recyclability, the CPBAT offers an economically feasible and sustainable alternative to current coated paper packaging.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
ADVANCES IN COPPER-BASED CHEMISTRY FOR RETRO DYE-SENSITIZED SOLAR CELLS AND EMERGING THIN-FILM MATERIALS IN OPTOELECTRONICS
Get PDFThesis (Ph.D.)--Michigan State University. Chemistry - Doctor of Philosophy, 2025Copper complexes, being known to have interesting chemistry, are exploited as photosensitizers and redox shuttles in dye-sensitized solar cells (DSSCs). In the most successful example, using Cu(II/I)(tmby)2 as a redox shuttle achieves a 13.7% power conversion efficiency (PCE) under 1 sun and 34% under 1000 lux. In these systems, however, base additives like 4-tert-butylpyridine (TBP) are shown to undergo ligand exchange reactions with certain Cu2+ centers, resulting in a loss of solution potential and hindering the exploitation of copper redox shuttles to their full potential. In this thesis, an investigation of a new class of copper complexes with sterically crowded ligands is discussed. Uniquely, showing the potential of these complexes to act simultaneously as chromophores and redox shuttles offers the possibility of dramatically higher efficiencies. The role of TBP in ligand exchange and redox reactions is examined, using cyclic voltammetry, UV-Vis absorption spectroscopy, and 1H NMR measurements. In addition, describing the details of this reaction and how it maps onto dye-sensitized solar cell performance as both a chromophore and redox shuttle, along with future directions.In the latter part of this thesis, a novel class of organic single-crystal thin films is explored, advancing the field of optoelectronics by developing highly ordered organic materials. Offering exceptional electronic and optical properties, these single-crystal organic solid crystals are positioned as promising candidates for a range of high-performance optical and electronic devices, paving the way for new applications in next-generation optoelectronic systems and impacting fields such as displays, sensors, and photonic circuits.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
Computationally Efficient Nonlinear Optimal Control using Neighboring Extremal Adaptations
Get PDFThesis (Ph.D.)--Michigan State University. Mechanical Engineering - Doctor of Philosophy, 2025Nonlinear optimal control schemes have achieved remarkable performance in numerous engineering applications; however, they typically require high computational time, which has limited their use in real-world systems with fast dynamics and/or limited computation power. To address this challenge, neighboring extremal (NE) has been developed as an efficient optimal adaption strategy to adapt a pre-computed nominal control solution to perturbations from the nominal trajectory. The resulting control law is a time-varying feedback gain that can be pre-computed along with the original optimization problem, which makes negligible online computation. This thesis focuses on reducing the computational time of the nonlinear optimal control problems using the NE in two parts. In Part I, we tackle model-based nonlinear optimal control and propose an extended neighboring extremal (ENE) to handle model uncertainties and reduce computational time (Chapter 3). Nonlinear Model predictive control (NMPC), which explicitly deals with system constraints, is considered as the case study due to its popularity, but ENE can be easily extended to other model-based nonlinear optimal control schemes. In Part II, we address data-driven nonlinear optimal control and introduce a data-enabled neighboring extremal (DeeNE) to remove parametric model requirement and reduce the computational time (Chapter 4). Data-enabled predictive control (DeePC), which makes a transition from the model-based optimal control to a data-driven one using raw input/output (I/O) data, is considered as the case study due to the attention it has received, but DeeNE can be easily extended to other data-driven nonlinear optimal control approaches. We also compare the control performance of DeeNE and DeePC for KINOVA Gen3 (7-DoF Arm Robot). Moreover, we introduce an adaptive DeePC framework, which can be easily transformed into an adaptive DeeNE, to use real-time informative data and handle time-varying systems (Chapter 5). Finally, we conclude the thesis and discuss the future works in Conclusion (Chapter 6).Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
ENHANCING PLATE HEAT EXCHANGER PERFORMANCE THROUGH INNOVATIVE FIN AND HEADER DESIGNS USING CFD AND REDUCED-ORDER MODELING
No full textThesis (Ph.D.)--Michigan State University. Mechanical Engineering - Doctor of Philosophy, 2025Plate heat exchangers (PHEs) are extensively used in various thermal systems due to their compact designs, high heat transfer coefficients, and superior scalability compared to other heat exchanger types. However, their performance often deteriorates due to uneven fluid distribution among channels, leading to non-uniform heat transfer and increased pressure drops. Performance enhancements can be achieved through the redesign of in-plane flow structures (fins) and modifications to header configurations. This study introduces novel three-dimensional twisted S-shaped fins to enhance thermal performance and presents comprehensive reduced-order thermo-hydraulic models to investigate flow maldistribution and rapidly optimize PHE designs for various header shapes.The first part of this dissertation presents a PHE design incorporating three-dimensional twisted S-shaped fins, fabricated using additive manufacturing technology. These fins promote controlled fluid swirl and enhance heat transfer. Turbulent conjugate heat transfer simulations are conducted to assess the thermal and hydraulic performance of the proposed configurations. By systematically varying mass flow rates and fin geometries, an optimized design suitable for high-temperature, high-pressure applications is identified.The second part of the study addresses flow maldistribution in PHEs caused by suboptimal header design. Computational Fluid Dynamics (CFD) analyses are conducted on PHEs with both straight and tapered header configurations to identify the optimal header design for achieving uniform flow distribution. While the introduction of a tapered header can reduce the recirculation zone observed in straight headers, contrary to existing research, the study reveals that tapered headers can increase flow maldistribution compared to straight headers. However, these CFD analyses are computationally intensive, making it challenging to identify conditions where tapered headers are advantageous.To significantly reduce computational expenses, a reduced-order model is developed to rapidly assess the potential impact of tapered headers. This model, validated against existing research, is capable of estimating both flow distribution and pressure drop within PHEs with minimal computational resources. Key structural parameters such as header diameter, number of channels, channel area, and taper ratio are identified as critical factors influencing flow distribution. These parameters play a crucial role in determining the choice between tapered and uniform headers. One of the most significant findings is the identification of the range of \u3b6 values, representing flow resistance inside the channels, where tapered headers provide more uniform flow compared to straight headers.The predictive modeling framework is further extended to more complex header geometries, including parabolic and hyperbolic shapes, thereby advancing the understanding of fluid distribution in complex geometries and contributing to the design of more efficient, reliable, and cost-effective PHEs.Finally, a comprehensive heat transfer model developed for PHEs is integrated with the predictive model. The resulting thermo-hydraulic model incorporates the role of header configuration in flow maldistribution and constitutes a tool for selecting appropriate structural parameters. This integrated model enables rapid evaluation of the impact of flow maldistribution on the effectiveness of PHEs without extensive computational resources. Overall, this dissertation contributes a novel design framework for PHEs, supporting applications in sustainable energy systems and industrial processes.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references