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Title: DEVELOPING LIGNIN-BASED EPOXY AND POLYURETHANE RESINS
Creator: Nikafshar, Saeid
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Lignin, the most abundant natural aromatic polymer, is currently produced as by-product during biorefinery and chemical pulping processes. Lignin is rich in hydroxyl functional groups (both phenolic and aliphatic OH), making it an excellent raw material for synthesizing epoxy and polyurethane resins. However, there are several challenges in utilizing unmodified lignins as feedstock for product development, including high polydispersity/heterogeneity, low reactivity, poor accessibility of...
Show moreLignin, the most abundant natural aromatic polymer, is currently produced as by-product during biorefinery and chemical pulping processes. Lignin is rich in hydroxyl functional groups (both phenolic and aliphatic OH), making it an excellent raw material for synthesizing epoxy and polyurethane resins. However, there are several challenges in utilizing unmodified lignins as feedstock for product development, including high polydispersity/heterogeneity, low reactivity, poor accessibility of hydroxyl groups for reaction with co-monomers low solubility in common organic solvents, and dark color. There are significant variations in lignin characteristics, depending on the source of biomass and isolation methods. Therefore, in-depth lignin characterization is needed to provide the basic knowledge of the structural, chemical, and thermal properties to facilitate lignin valorization.This study was focused on lignin characterization and development of lignin-based epoxy and polyurethane resins. First, a wide range of lignin samples was fully characterized by measuring their ash contents, elemental analyses, hydroxyl contents, chemical structures, molar mass distributions, and thermal properties. Next, a novel method was developed to measure the reactivity of thirteen different unmodified lignins toward biobased epichlorohydrin (ECH). A partial least square regression (PLS-R) model (with 92 % fitting accuracy and 90 % prediction ability) was created to study the correlation between lignin properties and epoxy content. The results showed that lignins with higher phenolic hydroxyl contents and lower molecular weights were more suitable for replacing 100 % of toxic bisphenol A (BPA) in the formulation of resin precursors. Additionally, two epoxidized lignin samples (with the highest epoxy contents) were cured using a biobased hardener (Cardolite from cashew nutshell), showed comparable thermomechanical performances and thermal stabilities to a petroleum-based epoxy system. Biobased waterborne polyurethane resins (PUDs) were also developed by entirely replacing the petroleum-based polyol and the internal emulsifier with either alkaline pre-extraction lignins or enzymatic hydrolysis lignins as well as tartaric acid (a biobased diacid). The formulated resins had zero VOC (volatile organic compound), which was achieved by replacing toxic n-methyl-2-pyrrolidone (NMP) with cyrene (a biobased solvent). To further improve the mechanical properties of our biobased PUD resins, 20 wt.% of lignin was substituted with low hydroxyl value soy-polyol, which increased their tensile strength and elongation at break to 87% and 68% of a commercial PUD resin. The results of this study demonstrated that it is imperative to fully characterize lignin and choose the right lignin for each specific application. This approach enabled us to entirely replace petroleum-based raw materials (BPA and polyol) with lignin and formulate biobased epoxy and polyurethane resins.
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Title: Topological Data Analysis and Machine Learning Framework for Studying Time Series and Image Data
Creator: Yesilli, Melih Can
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The recent advancements in signal acquisition and data mining have revealed the importance of data-driven tools for analyzing signals and images. The availability of large and complex data has also highlighted the need for investigative tools that provide autonomy, noise-robustness, and efficiently utilize data collected from different settings but pertaining to the same phenomenon. State-of-the-art approaches include using tools such as Fourier analysis, wavelets, and Empirical Mode...
Show moreThe recent advancements in signal acquisition and data mining have revealed the importance of data-driven tools for analyzing signals and images. The availability of large and complex data has also highlighted the need for investigative tools that provide autonomy, noise-robustness, and efficiently utilize data collected from different settings but pertaining to the same phenomenon. State-of-the-art approaches include using tools such as Fourier analysis, wavelets, and Empirical Mode Decomposition for extracting informative features from the data. These features can then be combined with machine learning for clustering, classification, and inference. However, these tools typically require human intervention for feature extraction, and they are sensitive to the input parameters that the user chooses during the laborious but often necessary manual data pre-processing. Therefore, this dissertation was motivated by the need for automatic, adaptive, and noise-robust methods for efficiently leveraging machine learning for studying images as well as time series of dynamical systems. Specifically, this work investigates three application areas: chatter detection in manufacturing processes, image analysis of manufactured surfaces, and tool wear detection during titanium alloys machining. This work’s novel investigations are enabled by combining machine learning with methods from Topological Data Analysis (TDA), a relatively recent field of applied topology that encompasses a variety of mature tools for quantifying the shape of data. First, this study experimentally shows for the first time that persistent homology (or persistence) from TDA can be used for chatter classification with accuracies that rival existing detection methods. Further, the efficient use of chatter data sets from different sources is formulated and studied as a transfer learning problem using experimental turning and milling vibration signals. Classification results are shown using comparisons between the TDA pipeline developed in this dissertation and prominent methods for chatter detection. Second, this work describes how to utilize TDA tools for extracting descriptive features from simulated samples generated using different Hurst roughness exponents. The efficiency of the feature extraction is tested by classifying the surfaces according to their roughness level. The resulting accuracies show that TDA can outperform several traditional feature extraction approaches in surface texture analysis. Further, as part of this work, adaptive threshold selection algorithms are developed for Discrete Cosine Transform, and Discrete Wavelet Transform to bypass the need for subjective operator input during surface roughness analysis. Both experimental and synthetic data sets are used to test the effectiveness of these two algorithms. This study also discusses a TDA-based framework that can potentially provide a feasible approach for building an automatic surface finish monitoring system.Finally, this work shows that persistence can be used for tool condition monitoring during titanium alloys machining. Since, in these processes, the cutting tools typically fracture catastrophically before the gradual tool wear reaches the maximum tool life criteria, the industry uses very conservative criteria for replacing the tools. An extensive experiment is described for relating wear markers in various sensor signals to the tool condition at different stages of the tool life. This work shows how, in this setting, TDA provides significant advantages in terms of robustness to noise and alleviating the need for an expert user to extract the informative features. The obtained TDA-based features are compared to existing state-of-the-art featurization tools using feature-level data fusion. The temporal location of the most representative tool condition features is also studied in the signals by considering a variety of window lengths preceding tool wear milestones.
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Title: QUEER LESSONS IN SUBJECT FORMATION : LEARNING FROM AIDS & SEX
Creator: Travers, Jessica
Date: 2022
Collection: Electronic Theses & Dissertations
Description: My dissertation investigates the formation of the subject. The subject I refer to here is the person, the individual who is shaped by language and discourse, is hailed by interpellation, and is affected by ideological social, cultural, and political forces. I poke and prod at how and why the subject is constructed, and during my analysis of the subject and its formation, I use AIDS literature and art as a lens. While doing so, I discover there is a tight knot around how the subject can define...
Show moreMy dissertation investigates the formation of the subject. The subject I refer to here is the person, the individual who is shaped by language and discourse, is hailed by interpellation, and is affected by ideological social, cultural, and political forces. I poke and prod at how and why the subject is constructed, and during my analysis of the subject and its formation, I use AIDS literature and art as a lens. While doing so, I discover there is a tight knot around how the subject can define and experience itself; thus, I work to loosen that knot, opening more space and air for novel ways the subject is formed—ways that do not encourage conformity, ways that give the subject more agency and creativity in how they become and who they are. Through my analyses and interpretations of works from the AIDS art archive, I uncover queer lessons that confuse, interrupt, and destabilize strict notions of what the subject is, how it is constructed, and how it can express and experience itself. Furthermore, I find that queer and perverted sexualities—erotically-driven desires that exist outside of dominant cultural norms—are an extremely powerful force that destabilizes normative ways that drive and determine how the subject is formed. Ultimately, I argue for a rescripting of how the subject is constructed and offer alternative approaches to subject formations—what I refer to as queer modes of self-authorship. Each of my four chapters narrows in on a queer mode of subject construction: queer interpellation, contact relationality, bearing witness, and desire and pleasure, respectively. These modes buttress my call for a proliferation of ways the subject can be authored and be read.
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Title: The metacoupled Arctic and North Pacific : Analyzing the spatiotemporal patterns and impacts of marine vessel traffic in coupled human and natural systems
Creator: Kapsar, Kelly
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Climate change is causing Arctic and sub-Arctic systems to warm at twice the global average rate. Warming temperatures are leading to unprecedented rates of sea ice decline, which is shifting the migratory patterns of animals, increasing accessibility to natural resources, and spurring tourists to travel to the Arctic. Many of these changes have the potential to increase marine vessel traffic in the Arctic. Ships are a primary mode of transportation in the Arctic, which has many remote...
Show moreClimate change is causing Arctic and sub-Arctic systems to warm at twice the global average rate. Warming temperatures are leading to unprecedented rates of sea ice decline, which is shifting the migratory patterns of animals, increasing accessibility to natural resources, and spurring tourists to travel to the Arctic. Many of these changes have the potential to increase marine vessel traffic in the Arctic. Ships are a primary mode of transportation in the Arctic, which has many remote communities and a fragmented road network. Ships take resources, such as fish, ores, and oil and gas, from the Arctic to global markets, and also serve as lifelines, bringing essential supplies to isolated communities. While these vessels serve to connect distant social-ecological systems and support human wellbeing, they can also have detrimental effects on the ecosystems through which they travel. Noise pollution, habitat degradation, ship strikes, invasive species introduction, and oil spills are all potential consequences of vessel traffic. Knowledge of the movements of vessels in space and time is necessary to determine the role that vessels are playing within Arctic systems and quantify their impacts. This information is also needed to predict the consequences of different vessel traffic policies for Arctic communities, ecosystems, and the interactions between them. The purpose of this dissertation is to quantify the spatiotemporal patterns of vessel traffic in Arctic social-ecological systems and to relate these patterns to other system components, including sea ice and wildlife movements. In chapter 2, we review the existing Arctic coupled human and natural systems literature and apply the newly introduced framework of metacoupling to explore the connections among the coupled human and natural systems of the Arctic and between Arctic systems and distant systems. We suggest that applying the metacoupling framework would improve future studies of Arctic coupled human and natural systems by distinguishing between different external connections and their unique impacts on sustainability. In chapter 3, we create a new, six-year data set of vessel activities in the North Pacific and Pacific Arctic Oceans. We then use these data in a case study examining the spatiotemporal patterns of vessel movements in the Bering Strait Region. As the only route connecting the Pacific and Arctic Oceans, the Bering Strait is a critical corridor for marine vessel traffic and migratory animals. While most vessel traffic in the region is local, we find that transient vessel traffic, particularly fishing activities and transport along the Northern Sea Route, increased between 2015 and 2020. In chapter 4, we focus on the movements of marine vessels in the ice-covered waters of the Pacific Arctic. We find that movements in ice differ by vessel type, and that while vessel traffic declines with increasing sea ice concentration, the overall amount of vessel traffic in sea ice increased between 2015 and 2020. In chapter 5, we evaluate the resource selection decisions of an endangered marine predator, the Steller sea lion (Eumetopias jubatus), in relation to fishing and non-fishing vessel movements in a sub-Arctic system, the Gulf of Alaska. Our results illustrate that adult female Steller sea lions select areas away from fishing vessel activities at a weekly timescale. This finding supports the hypothesis that large fishing vessels may disturb Steller sea lions, with potential consequences for their fitness. This dissertation expands upon the metacoupling framework by building a foundational understanding of the transportation of metacoupled flows. This work also contributes to the growing body of knowledge of vessel movements and their impacts on marine systems, which can be applied to design policies that promote the sustainable use of marine systems in a changing world.
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Title: Improving juvenile risk assessment measurement models : A psychometric comparison of scoring methods
Creator: Kitzmiller, Mary Katherine
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Juvenile risk assessments are standardized rating instruments that measure criminogenic risk in court-involved youth. Juvenile court practitioners use scores from risk assessments to inform judicial decisions throughout case processing. It is critically important that risk scores accurately reflect court-involved youths’ latent level of criminogenic risk; both artificially high and low scores incur significant detriments to youths, courts, and communities. In light of the consequences of risk...
Show moreJuvenile risk assessments are standardized rating instruments that measure criminogenic risk in court-involved youth. Juvenile court practitioners use scores from risk assessments to inform judicial decisions throughout case processing. It is critically important that risk scores accurately reflect court-involved youths’ latent level of criminogenic risk; both artificially high and low scores incur significant detriments to youths, courts, and communities. In light of the consequences of risk misevaluation, there is urgent need to develop and evaluate alternate juvenile risk assessment measurement models The current study aspired to improve measurement of criminogenic risk through the development of a Novel Scoring Algorithm which innovated upon current juvenile risk assessment scoring twofold: (1) it adjusted the weights of assessment items and domain sub-scores to reflect their correlation with latent constructs of criminogenic risk; and (2) it integrated the mitigating impact of prosocial protective factors into cumulative risk scores. Drawing upon a sample of 559 youth who entered the supervision of a county-level juvenile circuit court for the first time, the Novel Scoring Algorithm outperformed the current method of scoring (i.e., summing all unweighted risk factors) in both absolute and relative model fit. However, the Novel Scoring Algorithm yielded no incremental improvement in diagnostic accuracy, affirming the Scoring-as-Usual method as an acceptable procedure for assessing likelihood of recidivism in court-involved youth. Implications for effectively and equitably managing risk are discussed.
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Title: SELLING TECHNOLOGY : INFLUENCING PERCEPTIONS OF AUTONOMOUS VEHICLES
Creator: Darcy, Cornelius Howard
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Disruptive products and technologies change both how we live and the ways in which we live in communities. Automated vehicles (AVs) have the potential to be both disruptive and transformative. However, a period of anticipatory ebullience ended in 2018 when two high profile crashes of automated vehicles occurred. The crashes shook the confidence of the public and of industry and called into question the merits of developing fully automated vehicles that drive on public roads without input from...
Show moreDisruptive products and technologies change both how we live and the ways in which we live in communities. Automated vehicles (AVs) have the potential to be both disruptive and transformative. However, a period of anticipatory ebullience ended in 2018 when two high profile crashes of automated vehicles occurred. The crashes shook the confidence of the public and of industry and called into question the merits of developing fully automated vehicles that drive on public roads without input from humans.Although academic research on AVs has continued unabated since 2018, with the exception of a few instances, researchers have not sought insight from the industry creating these vehicles regarding the future of the technology and of how the industry is engaged in resetting expectations. This study investigates industry strategies to influence perceptions of automated vehicles post 2018 and how current perceptions of AVs affect communities. This study is based on interpretations of information transference, information moderation, and technology acceptance. Understanding how the AV industry is influencing perceptions in a changing technological landscape contributes new perspectives on a disruptive and transformative technology and how industry-led information moderation becomes an important contributing factor to future acceptance.
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Title: MODELING FIRE-INDUCED INSTABILITIES FOR TRACING PROGRESSIVE COLLAPSE IN STEEL FRAMED BUILDINGS
Creator: Venkatachari, Svetha
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Fire is one of the extreme loading events that a building may experience during its service life and can induce severe consequences on the safety of its occupants, first responders, and the structure. Recent fire incidents have clearly shown that steel framed buildings are vulnerable to progressive collapse under severe fire conditions, if not duly considered in the design. The progressive collapse in steel framed buildings initiates with the onset of temperature-induced instabilities at a...
Show moreFire is one of the extreme loading events that a building may experience during its service life and can induce severe consequences on the safety of its occupants, first responders, and the structure. Recent fire incidents have clearly shown that steel framed buildings are vulnerable to progressive collapse under severe fire conditions, if not duly considered in the design. The progressive collapse in steel framed buildings initiates with the onset of temperature-induced instabilities at a local or global level, which in turn can lead to the partial or complete collapse of the structure. Despite fire being a severe hazard, the current practice does not have specific recommendations or guidance to evaluate the fire-induced progressive collapse in critical buildings. This is unlike other loading events such as blasts, earthquakes, etc. Further, the current fire design philosophy of steel structures is primarily based on a member (or section) level behavior and does not account for several critical factors, including some of the temperature-induced instabilities. To overcome some of the knowledge gaps, a series of advanced simulations are carried out for tracing the fire-induced collapse in steel framed buildings. To establish the connection between evacuation strategies (times) and structural stability under fire, a set of evacuation simulations is undertaken to evaluate the effect of varying egress parameters on the emergency evacuation process in a high-rise building. In addition, the influence of incorporating situational awareness during an emergency evacuation is quantified. These evacuation strategies and times are to be considered, together with the fire-induced progressive collapse timelines, for achieving the required fire safety in critical buildings. Furthermore, for facilitating complete evacuation and efficient firefighting operations, stability of the structure is to be maintained and any chance of fire-induced collapse is to be minimized. Evaluating progressive collapse under fire conditions is highly complex and requires advanced analysis. For this purpose, a comprehensive finite element-based model is developed in ABAQUS to trace the overall response of a steel framed building under fire exposure, including the onset of instabilities leading to the progressive collapse. The developed model specifically accounts for high-temperature material properties and creep effects, geometric nonlinearity, altering load paths, connections, fire spread, local buckling effects, and realistic failure limit states. The model is validated by comparing the thermal and structural response predictions against the published test data at the member level (steel columns) and system level (steel framed structures). The validated model is applied to carry out a set of parametric studies on a ten-story braced framed building to quantify the influence of various fire, material, and structural parameters on the onset of fire-induced collapse in steel framed buildings. Results from the parametric studies indicate that the severity of the fire scenario, including the location and extent of burning, fire spread, varying load paths, and temperature-induced local instabilities have a significant influence on the onset of fire-induced progressive collapse. Moreover, accounting for the full effects of high-temperature creep in the fire-induced progressive collapse analysis is needed to obtain realistic failure times under severe to very intense fire exposure. Results from the parametric studies are used to propose guidelines for mitigating fire-induced collapse in critical buildings. Specific recommendations are provided for the treatment of high-temperature creep and local instabilities in the fire resistance analysis of steel structures. The proposed approach for advanced analysis, together with the design recommendations, can be utilized to minimize the onset of fire-induced collapse in critical steel framed buildings.
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Title: Information, Environmental Policy, and Aquacultural Expansion : Three Essays in Non-Market Valuation
Creator: Athnos, April
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Private management of non-point sources of pollution is an important concept in economics. Regulators are often unable to trace pollutants to their origins and efforts to limit many disaggregated sources of pollution are costly and invasive. Wells and septic systems, common in the rural and suburban United States, represent privately-owned non-point water pollution sources when they fail to protect households and water resources. “Time of Sale or Transfer” (TOST) policies are gaining...
Show morePrivate management of non-point sources of pollution is an important concept in economics. Regulators are often unable to trace pollutants to their origins and efforts to limit many disaggregated sources of pollution are costly and invasive. Wells and septic systems, common in the rural and suburban United States, represent privately-owned non-point water pollution sources when they fail to protect households and water resources. “Time of Sale or Transfer” (TOST) policies are gaining popularity across the state of Michigan and in other states across the country to require rigorous well and septic system evaluations at the time a house is sold. In cases where threats to public and environmental health are identified, Health Department administrators impose mandatory repair or replacement orders. Without a letter of Health Department approval, a house with a well or septic system cannot be legally transferred. Despite the growing traction of these policies, however, little is known about the effects of TOST program adoption on the housing market. In lieu of empirical evidence, many homeowners and policymakers in Michigan claim that the policies suppress house prices and argue against the instruments. My first essay addresses this empirical gap in the economic literature by estimating the causal impact of policy adoption on house values. I use an event study approach to compare regulated well and septic system homes to a set of neighboring controls just outside the regulation area. Results suggest that there is not a large, statistically significant price decline following policy adoption, with evidence indicating a price penalty no larger than 4 percent.The second essay analyzes the effect of TOST inspection resulting in Health Department required corrective actions. I motivate my empirical strategy with a model of negative TOST information shocks during the contract closing period of a house sale. The data for this essay are inspection-sale pairs constructed by combining county-level inspection records, housing transaction records, and property characteristics. I identify a house price penalty of about 7.5 percent to 10.5 percent after TOST adoption by using a hedonic price model with structural controls, spatial controls, and time fixed effects. These results are robust to a repeat sales model specification as well as an approach controlling for building quality with assessor-assigned grades. Further, there is no evidence of significant heterogeneity based on whether a well or septic system triggers mandatory corrective action, whether the problems identified are high- or low-risk, or which Health Department administers the program. In contrast, a quantile regression shows strong evidence of price impacts led by the low end of the house price spectrum. This suggests that the houses that fail at the highest rates also experience the largest price penalties and belong to homeowners least able to shoulder the costs. Regulators must consider the heterogeneity of these pecuniary effects when regulating externality-generating on-site water systems through the housing market.The third essay studies how to expand aquaculture production int he North Central Region (NCR). U.S. per capita seafood consumption stands at an all-time high due to population and income growth and consumer preference shifts toward healthy proteins. U.S. aquaculture, however, has not kept pace and imports serve most of the U.S. fish market. This study estimates willingness-to-pay (WTP) for several search and credence fish attributes using a hypothetical choice experiment of U.S. fish consumers. Search attributes, like prices, can be readily discerned by consumers before purchase while credence attributes, such as region of production, cannot be easily identified before or after purchase and require labels. Our study varied attributes and levels over three species historically produced in the North Central Region (NCR) but underrepresented in the literature---rainbow trout, yellow perch, and walleye. Using a random utility framework, we identify average price premia of $1.64/lb., $1.97/lb., and $0.84/lb. for an NCR-specific label, wild-caught label, and fresh fillet forms, respectively. We also estimate marginal WTP for trout, yellow perch, and walleye of $19.99/lb., $15.89/lb., and $17.37/lb., respectively. Our findings suggest that NCR aquaculture producers can expand by intensifying trout production while continuing to market yellow perch and walleye in the region. Nationally, an NCR-source label is not valued more than a wild-caught label, implying that overcoming consumers' aversion to farmed fish will require more than marketing fish as products of the NCR.
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Title: MIGRANT FARM WORK, COLLEGE, AND MONEY : A PARTICIPATORY ACTION RESEARCH STUDY WITH MIGRANT FARMWORKING COLLEGE STUDENTS
Creator: Flores, Amanda
Date: 2022
Collection: Electronic Theses & Dissertations
Description: College is the first time students have the opportunity to make independent financial decisions and employ financial practices. Research suggests that students pick up financial knowledge, habits, and practices from family, friends, and their broader community and that these practices can have long-term implications. Migrant farmworking college students are a small subset of college students who come from highly mobile families and whose source of income is dependent on agricultural seasons....
Show moreCollege is the first time students have the opportunity to make independent financial decisions and employ financial practices. Research suggests that students pick up financial knowledge, habits, and practices from family, friends, and their broader community and that these practices can have long-term implications. Migrant farmworking college students are a small subset of college students who come from highly mobile families and whose source of income is dependent on agricultural seasons. The migratory lifestyle influences how migrant farmworking families employ financial practices, which likely shapes how children in migrant farmworking families think about their finances and what kinds of financial practices they use. This study explores how the familial and cultural upbringing of migrant farmworking families influences the financial practices of migrant farmworking college students. Grounded in participatory action research methodology, I draw on funds of knowledge and consejos to elevate familial and cultural influences on the financial practices of 5 migrant farmworking college students. Ultimately, this study seeks to provide recommendations for advisors and other student-facing professionals to help meet the diverse needs of this distinct population of marginalized students.
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Title: Development and application of hierarchical models for monitoring avian soundscapes, populations, and communities
Creator: Doser, Jeffrey W.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Climate change, land use change, and other anthropogenic pressures are increasing species extinctions, phenology shifts, and drastic population declines. Avian populations and communities are particularly vulnerable to global change given their mobile and migratory life history strategies. Avian abundance has drastically declined throughout North America over several decades, which is compounded by phenological shifts in breeding periods and migratory patterns. Informed management and...
Show moreClimate change, land use change, and other anthropogenic pressures are increasing species extinctions, phenology shifts, and drastic population declines. Avian populations and communities are particularly vulnerable to global change given their mobile and migratory life history strategies. Avian abundance has drastically declined throughout North America over several decades, which is compounded by phenological shifts in breeding periods and migratory patterns. Informed management and conservation of avian populations and communities requires large-scale monitoring programs, as well as associated inferential tools to provide statistically robust inference using multiple data sources. In this dissertation, I develop a suite of hierarchical modeling approaches to understand avian soundscapes, populations, and communities. I leverage a hierarchical Bayesian modeling framework, which is ideally suited for complex wildlife data with numerous types of observation error and dependencies among data points. In Chapter 1, I provide a brief overview of avian monitoring approaches and their associated statistical analysis frameworks. In Chapters 2 and 3, I develop hierarchical models for the analysis of complex avian soundscape data, and apply these approaches to two case studies. In Chapter 2, I apply a two-stage hierarchical beta regression model to quantify the relationship between anthropogenic and biological sounds in avian soundscapes in western New York. In Chapter 3, I use a multivariate linear mixed model to assess disturbance impacts of a shelterwood logging on avian soundscapes in northern Michigan. In Chapter 4, I develop a multi-region, multi-species abundance model to quantify trends of avian species and communities using point count data across a network of National Parks in the northeastern US. In Chapters 5 and 6, I use a model-based data integration approach to yield improved inference on avian population and communities. In Chapter 5, I integrate automated acoustic recording data with point count data to estimate avian abundance, which I apply to a case study on the Eastern Wood Pewee (Contopus virens) in a National Historical Park in Vermont. In Chapter 6, I develop an integrated community occupancy model that combines multiple types of detection-nondetection data for inference on species-specific and community level occurrence dynamics, which I use to assess occurrence dynamics of a foliage-gleaning bird community in New Hampshire. These results exhibit the value of hierarchical models to partition ecological data into distinct observation and ecological components for improved inference on avian population and community dynamics. Future work should continue to leverage complex data sources within hierarchical modeling frameworks to address pressing conservation and management questions on avian populations, communities, and the ecosystem services they provide.
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Title: DESIGN AND ENGINEERING OF POLY(LACTIDE) RESIN BASED BIOCOMPOSITES
Creator: Bambhania, Harshal M.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Fiber reinforced composites are typically prepared using thermosetting polymeric resins derived from petroleum resources and involving hazardous chemicals. We present a vinyl-ester system utilizing a 100% renewably based polyester enabling the sequestration of carbon from the atmosphere into durable goods for decades. The biopolymer poly(meso-lactide) (PML) is synthesized using a strategy giving vinyl end groups. In place of potentially carcinogenic styrene which is predominantly used as a...
Show moreFiber reinforced composites are typically prepared using thermosetting polymeric resins derived from petroleum resources and involving hazardous chemicals. We present a vinyl-ester system utilizing a 100% renewably based polyester enabling the sequestration of carbon from the atmosphere into durable goods for decades. The biopolymer poly(meso-lactide) (PML) is synthesized using a strategy giving vinyl end groups. In place of potentially carcinogenic styrene which is predominantly used as a reactive diluent to reduce the thermoset viscosity, the new sustainable bioresin dissolved in methyl methacrylate (MMA), infused into various fibers, and cured to form the composite panels. Mechanical properties are excellent and comparable with less sustainable materials from fossil resources.As homeowners adopt a lifestyle that is more responsive to environmental need, industry and academia are tasked with finding more sustainable solution for cast polymer products like countertops and sinks. Particulate fillers in the cast polymers are bound by either poly(methyl methacrylate)/methyl methacrylate (PMMA/MMA) or unsaturated polyester/styrene (UPR/Styrene) resin. For the first time ever, we have introduced biopolymer poly(lactide) (PLA) dissolved in MMA as a novel bioresin formulation which can be directly substituted for less sustainable PMMA/MMA and more carcinogenic UPR/Styrene counterparts. Mechanical properties of fabricated biorenewable solid surface and cultured marble composites are on par with commercially available products. This environmentally benign resin is also used to fabricate a prototype of a Drop-in-Bowl solid surface and preliminary calculations show a 24% reduction ingreenhouse gas emissions (CO2 equivalent) compared to PMMA/MMA acrylic resins available in the market.Otherwise destined to landfills or incineration, recovery and recycling of composite materials not only improves the sustainability metrics but also opens the door to various end-of-life options. Recycling of sinks and countertops via solvolysis reduces the usage of new resources, prevents waste, and lowers the emission associated with their production and transportation. For the first time ever, Drop-in-Bowl solid surface sink was fabricated using fully recyclable resin PLA dissolved in MMA and is demonstrated that simple base solvolysis can be employed to recover the particulate filler material along with other end-of-life options including edible food ingredient, and superabsorbent polymer.Chain transfer agents (CTAs) are conventionally used to regulate the polymer molecular weight during the free radical polymerization of acrylate polymers. Also, curing reaction of MMA undergoes a sudden temperature rise because of auto-acceleration known as Trommsdorff effect. These curing effects in the presence and absence of CTAs were investigated for MMA resin-based systems. One-dimensional (1D) mathematical model combining the reaction kinetics and heat transfer was extended to incorporate the effect of CTAs. Agreement between experimental findings at small scale (6 to 8 g) and simulation results indicate that in bulk polymerization of MMA based resins, presence of chain transfer not only controls the polymer properties but is also reduces the peak polymerization temperatures. Also, control of the in-situ polymerization of thick methacrylic composite parts is essential to minimize or avoid the monomer boiling. Above mentioned thermokinetic model was expanded considering of spatial geometry and experimentally validated to study the effect of CTAs to mitigate the temperature rise during ~kg quantities of bulk free radical polymerization and fabrication of thick MMA/PMMA resin composites.
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Title: STUDENTS’ TOOL USAGE, JUSTIFICATIONS, AND REPORTED CONFIDENCE WHEN USING DYNAMIC GEOMETRY ENVIRONMENTS
Creator: Wegner, Timothy Scott
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Dynamic Geometry Environments (DGEs) are popular tools in the exploration of geometry. This research is designed to explore the confidence of undergraduate mathematics students as they make mathematical statements when completing geometric tasks using DGEs. Students completed two series of tasks in both Euclidean and hyperbolic geometry. The first series of tasks asked students about properties of parallel transports and the second series of tasks asked students about the existence of regular...
Show moreDynamic Geometry Environments (DGEs) are popular tools in the exploration of geometry. This research is designed to explore the confidence of undergraduate mathematics students as they make mathematical statements when completing geometric tasks using DGEs. Students completed two series of tasks in both Euclidean and hyperbolic geometry. The first series of tasks asked students about properties of parallel transports and the second series of tasks asked students about the existence of regular polygons. The ten students in this research used Geometry Explorer, a DGE which they had previous experience using in Euclidean geometry, but minimal experience using in hyperbolic geometry. Hyperbolic geometry tasks were included in this study because features of that geometry (e.g. curved lines and unexpected length measure) were expected to pose challenges for students’ intuitive expectations. Because of this lack of intuition, students may use the features of DGEs (e.g. dragging and measurement) to make various justifications (e.g. authoritative, inductive, and deductive) of the mathematical claims they are making. Both the features of the DGE and students’ justifications affect their confidence in the claims they make. This research explored the interaction between these three factors. Analysis of the data showed that these two series of tasks elicited both dragging and measurement tool usage. During the parallel transport tasks, students used these tools in both in an exploratory mode looking for relationships and a validation mode confirming previous conjectures. During the regular polygon construction tasks, students mainly used the tools in a validation mode. Additionally, many students waited until the hyperbolic portion of the tasks to begin using these tools. The tasks elicited a range of justifications, though students generally used inductive arguments. Deductive justifications, when used, were mainly for familiar tasks that took place within Euclidean geometry. Reported confidence was high across both series of tasks as well as across both Euclidean and hyperbolic geometry when working with the DGE. Reported confidence dropped when working on conjecturing or proof validation prompts that did not use the DGE.This research suggests there is still much work to be done investigating how students use tools, make justifications, and report confidence when using DGEs in both Euclidean and non-Euclidean geometries. The researcher recommends further study including the exploration of additional tools within DGEs, the dynamics of working in partners within DGEs, and how students’ expectations of justification affect their responses.
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Title: GENDER EQUITY IN COMMUNITY SUSTAINABILITY : BREASTFEEDING AND INTIMATE PARTNER ABUSE
Creator: Bomsta, Heather D.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: We live within a web, connected to our family, friends, communities, societies, nations and ultimately, the greater biome of the Earth. Healthy, thriving women and children benefit their communities; healthy women work to contribute to and help care for their families and friends, and healthy children are able to learn well at school and are best positioned to develop into healthy, able citizens. Unfortunately, the presence of intimate partner abuse (IPA) negatively impacts maternal and child...
Show moreWe live within a web, connected to our family, friends, communities, societies, nations and ultimately, the greater biome of the Earth. Healthy, thriving women and children benefit their communities; healthy women work to contribute to and help care for their families and friends, and healthy children are able to learn well at school and are best positioned to develop into healthy, able citizens. Unfortunately, the presence of intimate partner abuse (IPA) negatively impacts maternal and child health, resulting in lost productivity, missed schooling, increased healthcare costs, and in some cases the deaths of women and infants. IPA is a critical issue in community well-being and sustainability. This dissertation presents three studies focusing on better understanding dynamics around IPA that impact women and their children. The first two studies focus on how abuse impacts breastfeeding. Providing human milk for an infant has benefits for infants, lowering all causes of infant mortality and resulting in increased IQ and lifelong health benefits (Victora et al., 2016). Nursing an infant also benefits mothers by reducing postpartum hemorrhage, lowering the risk of postpartum depression and their lifetime risks of nine different types of cancer (Stuebe, 2009). These benefits accumulate across individuals, resulting in healthier mothers and children, better able to contribute to their families and communities. The first study uses a nationwide dataset from the Centers for Disease Control, the Pregnancy Risk Assessment and Monitoring survey (PRAMS), to quantitatively explore the relationship between reported physical abuse and breastfeeding initiation. The relationship between IPA and breastfeeding initiation is complex and the literature is not yet settled. This study contributes to the literature by using an alternate approach that is not definitive, but points toward new areas for future research. Working to resolve this question can help healthcare providers, IPA advocates and policy makers with better information to begin to shape interventions to support mothers coping with abuse. Breastfeeding matters to these mothers for health reasons, but also because it is one of the first major decisions they make for an infant and if they do not meet their breastfeeding goals, they often experience guilt, question their value as mothers (Jackson, DePascalis, Harrold & Fallon, 2020) and face a higher risk of postpartum depression (Gregory, Butz, Ghazarian, Gross & Johnson, 2015; Borra, Iacovou & Sevilla, 2015). The first hypothesis explored is that mothers reporting physical abuse will initiate breastfeeding at a lower rate than mothers reporting no physical abuse. Logistic regression confirmed mothers reporting physical violence initiate breastfeeding at a lower rate than their unabused counterparts. The relationship remains significant when controlling for race and maternal education, but marital status reverses the effect. Subsequent subgroup analyses show married women’s decisions around breastfeeding initiation to be significantly impacted by physical abuse, while unmarried abused mothers initiated breastfeeding at roughly the same rate as unmarried mothers reporting no physical violence. The second hypothesis focuses only on mothers reporting physical abuse and explores whether a ‘dose’ effect exists. Logistical regression again shows mothers who report physical abuse at two time points initiate breastfeeding at a lower rate than mothers reporting physical abuse at only one time point. This finding remained significant even when controlling for maternal education, race/ethnicity, and marital status. The second study is a qualitative exploration of mothers’ experience of living with an abusive partner while breastfeeding. While quantitative studies can estimate the size and direction of a phenomenon it does not tell us what is happening in the day-to-day life of people experiencing it. Qualitative research can raise the voices of women coping with abuse during the breastfeeding phase, who are the experts on their situations. It is also essential for those working to end abuse to understand how mothers and their decisions are constrained by abuse and how they use their agency to resist and survive. This study uses semi-structured interviews with thirteen mothers with infants under one year of age who lived with an abusive partner for some amount of time while breastfeeding/pumping. Using thematic content analysis, themes emerged around mothers using gender performativity, successfully and unsuccessfully, to attempt to stem the violence and chaos in their relationships. Mothers attempted to fulfill traditional female roles to appease abusive partners, used breastfeeding to protect themselves and their infants, and drew strength from family, friends, and medical/support professionals by fulfilling the ‘good mother’ role through breastfeeding. The third study examines organizational resilience for nonprofits, which often function as a key part of the social safety net by providing services to vulnerable populations and strengthening communities. Despite their essential nature, organizational resilience (OR) among nonprofits is not well studied. Finding no models specific to nonprofits, a model of OR from the for-profit sector was adapted and extended. The model adaptation focuses on financial resources, technical resources and social resources and expands each category to cover unique aspects of nonprofits that the for-profit OR model does not contain. The gap between OR and social-ecological resilience (SER) was also examined, and several SER concepts were added to enhance our nonprofit OR model. The adapted model is then illustrated through a case study of intimate partner abuse (IPA) agencies. Managers and frontline staff from eight IPA nonprofits in a Midwestern state were interviewed during the COVID-19 pandemic. The adapted model can be used by researchers and practitioners to better understand and evaluate OR not only in IPA agencies, but all nonprofits.
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Title: Predicting the Properties of Ligands Using Molecular Dynamics and Machine Learning
Creator: Donyapour, Nazanin
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The discovery and design of new drugs requires extensive experimental assays that are usually very expensive and time-consuming. To cut down the cost and time of the drug development process and help design effective drugs more efficiently, various computational methods have been developed that are referred to collectively as in silico drug design. These in silico methods can be used to not only determine compounds that can bind to a target receptor but to determine whether compounds show...
Show moreThe discovery and design of new drugs requires extensive experimental assays that are usually very expensive and time-consuming. To cut down the cost and time of the drug development process and help design effective drugs more efficiently, various computational methods have been developed that are referred to collectively as in silico drug design. These in silico methods can be used to not only determine compounds that can bind to a target receptor but to determine whether compounds show ideal drug-like properties. I have provided solutions to these problems by developing novel methods for molecular simulation and molecular property prediction. Firstly, we have developed a new enhanced sampling MD algorithm called Resampling of Ensembles by Variation Optimization or “REVO” that can generate binding and unbinding pathways of ligand-target interactions. These pathways are useful for calculating transition rates and Residence Times (RT) of protein-ligand complexes. This can be particularly useful for drug design as studies for some systems show that the drug efficacy correlates more with RT than the binding affinity. This method is generally useful for generating long-timescale transitions in complex systems, including alternate ligand binding poses and protein conformational changes. Secondly, we have developed a technique we refer to as “ClassicalGSG” to predict the partition coefficient (log P) of small molecules. log P is one of the main factors in determining the drug likeness of a compound, as it helps determine bioavailability, solubility, and membrane permeability. This method has been very successful compared to other methods in literature. Finally, we have developed a method called ``Flexible Topology'' that we hope can eventually be used to screen a database of potential ligands while considering ligand-induced conformational changes. After discovering molecules with drug-like properties in the drug design pipeline, Virtual Screening (VS) methods are employed to perform an extensive search on drug databases with hundreds of millions of compounds to find candidates that bind tightly to a molecular target. However, in order for this to be computationally tractable, typically, only static snapshots of the target are used, which cannot respond to the presence of the drug compound. To efficiently capture drug-target interactions during screening, we have developed a machine-learning algorithm that employs Molecular Dynamics (MD) simulations with a protein of interest and a set of atoms called “Ghost Particles”. During the simulation, the Flexible Topology method induces forces that constantly modify the ghost particles and optimizes them toward drug-like molecules that are compatible with the molecular target.
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Title: The Words, the Texts, and the Interactions : Opportunities for Word Learning from Preschool Storybook Apps
Creator: Bruner, Lori
Date: 2022
Collection: Electronic Theses & Dissertations
Description: One of the most important benefits of read alouds in the early years is the exposure children gain to new words. Although many early skills support later reading success, early vocabulary knowledge improves reading in several ways, including supporting comprehension of words that children decode; helping children recognize words more quickly; fostering phonological awareness skills; and increasing children’s understanding of content-area instruction. However, the nature of interactive read...
Show moreOne of the most important benefits of read alouds in the early years is the exposure children gain to new words. Although many early skills support later reading success, early vocabulary knowledge improves reading in several ways, including supporting comprehension of words that children decode; helping children recognize words more quickly; fostering phonological awareness skills; and increasing children’s understanding of content-area instruction. However, the nature of interactive read alouds in young children’s homes is evolving, as families are increasingly turning to digital texts from a very young age. This phenomenon, coupled with the indisputable benefits of children reading print books, necessitates a critical need to identify the affordances of digital texts for young children’s vocabulary development. To that end, the purpose of this mixed-methods study is to examine one type of preschool digital text – interactive storybook apps – for the affordances they may provide for young children’s vocabulary development. Specifically, my study seeks to understand (a) the degree to which preschool storybook apps introduce new vocabulary words to young children; (b) the types of words children can learn from these texts; (c) the degree to which interactive features in storybook apps highlight new words; and (d) to what extent interactive features closely aligned to the words in the story might promote caregivers’ word-related talk while reading aloud. To answer these questions, I designed two separate but related studies. In the first study, I conducted a content analysis of 70 best-selling preschool storybook apps from three popular app stores: the Apple Store, Google Play, and the Amazon App Store. Using the Words Worth Teaching List as a guide, I analyzed 26,744 total words from these 70 apps to determine what percentage of words might be considered new for preschool-aged children. Furthermore, I described the types of words children might learn from these texts using three word-level features: parts of speech, frequency, and word difficulty. Finally, I determined to what extent new words in storybook apps are highlighted by interactive features. In the second study, I conducted an observational study of 37 caregivers of four- and five-year-old children to determine how interactive features closely aligned to new words in storybook apps might promote more word-related talk during read aloud of these texts. During this study, caregivers read four stories each – two print books and two storybook apps in counterbalanced order – for a total of 68,635 words in 148 sessions, totaling over 2,220 minutes of read aloud time. Findings from this study suggest that preschool storybook apps are ripe with opportunities to learn new words. The sample apps contained a total of 1,376 new words – for an average of nearly 20 words per story. Furthermore, storybook apps highlight approximately 23 percent of new words with interactive features, such as providing examples of a word (18.2 percent); demonstrating the meaning of a word (29.2 percent); or saying the word out loud when a reader taps on a picture of it (35.1 percent). Notably, caregivers talked about significantly more new words with their children when they were highlighted by these interactive features. However, I found that the number of interactive features per word, the types of interactive features in the text, and whether caregivers had engage with the word on the screen (i.e., tap on the screen to activate the interactive features) did not significantly influence whether and how caregivers talked about a new word in the text. This study contributes to the field’s understanding of preschool digital texts and their affordances for young children’s vocabulary development, as well as how caregivers use these texts during read alouds in the home environment. The findings from this study have implications for teacher professional development, teacher preparation, community-based outreach programs, and storybook app developers.
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Title: Tell Me Sumthin Good : Leader Narratives to Understand Data Use in Black School Communities
Creator: Wards, Ronetta Paresi
Date: 2022
Collection: Electronic Theses & Dissertations
Description: ABSTRACTTELL ME SUMTHIN GOOD: LEADER NARRATIVES TO UNDERSTAND DATA USE IN BLACK SCHOOL COMMUNITIESByRonetta Paresi WardsSchooling experiences for Black students in the US have been shaped historically by anti-education laws, mandates, and initiatives that sustain unjust systemic practices and policies. These practices and policies often stagnate academic progress and have led to institutional deficits and the normalization of deficit-orientations towards students in predominantly Black...
Show moreABSTRACTTELL ME SUMTHIN GOOD: LEADER NARRATIVES TO UNDERSTAND DATA USE IN BLACK SCHOOL COMMUNITIESByRonetta Paresi WardsSchooling experiences for Black students in the US have been shaped historically by anti-education laws, mandates, and initiatives that sustain unjust systemic practices and policies. These practices and policies often stagnate academic progress and have led to institutional deficits and the normalization of deficit-orientations towards students in predominantly Black schools. Accountability expectations set forth by federal legislation is just one example of how educational policy play a role in sustained deficit orientations toward Black schools through the utility of student performance information. State education agencies use student performance information from annual assessments to grade, categorize, and make decisions around support resources for students. This annual data snapshot also determine funding and shape the allocation of resources for schools despite their need to support students in non-academic ways. Currently, student performance information is constructed in a way that provide a singular view of student performance information based on proficiency leveling and categorical grouping of students. This grouping is centered on students’ lack of skill and in turn automatically posits them in a place of deficit within the data. This view of data also shape the way school leaders draw on, make sense of and interact with data toward decision-making to improve educational outcomes. A new approach is needed to inform leadership decision making and support for alternative perspectives with data use to overcome institutional deficits and ineffective use of data in Black schools. The purpose of this study was to understand the sensemaking of data use through the stories told by school leaders in predominantly Black schools. This study used conceptual frames associated with sensemaking theory (Weick, 1995), school leader sensemaking theory (Gannon-Shilon & Schechter, 2017) and data use theory (Coburn & Turner, 2012) as guardrails to better understand elementary school leaders and their data use practices. Data use in school leadership is significant and can serve as a strategy to improve instructional practice. School leaders who have advanced data literacy skill sets can leverage student performance information (data) in ways that bring about insight (knowledge) to inform their leadership practice. School leaders are responsible for many aspects of the school operation and classroom instruction plays a major role toward improvement efforts. The improvement of instructional practice can lead to better educational outcomes for students in Black school communities. This study sought to capture the stories told by school leaders, specifically leaders in predominantly Black schools. This research study aimed to better understand how leaders accessed, interacted with, acted on and made sense of their data use practices toward the improvement of educational outcomes in their school. The main research question that guided this study was: • How do the stories of elementary school leaders serving in predominantly Black school communities explain how data is used to make decisions toward educational improvement? This study also sought to answer the following sub- questions: • What stories do elementary school leaders tell about how they use data to inform their leadership practice? • What contextual factors influence school leader interactions with data? In the analysis of the data, two different approaches helped to arrive at a broadened view of the data. In the first approach, leader stories were restoried and aligned to themes set forth by Clandinin and Connolly’s (2000) three-dimensional narrative structure; interaction, continuity, and situation to view their experiences along a continuum. In the second approach, an open qualitative analysis was conducted and the leader stories were posited as data for interpretation. The findings brought forth a rich description of the leader's experience from two distinct analytical perspectives. The participant stories situated in the context of Black school communities provided a glimpse into the benefits and challenges leaders faced with data use towards educational improvement. Through these stories their voices are centered to offer insight into how data use practice can either help or hinder their improvement efforts. This knowledge is significant in that it can be transferable to other education spaces to inform policy at large and potentially re-story the public discourse around educational improvement in ethnically diverse school communities.
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Title: "I want to be a better person and a better teacher" : Exploring the constructs of race and ability in a music educator collaborative teacher study group
Creator: Knapp, Erika
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The way teachers engage with dis/ability and race in their classrooms links to theirunderlying belief systems (Heroux, 2013; Ryan, 2020). Unfortunately, substantial evidence connects teacher beliefs and perceptions to the reification of hegemonic norms, which upholds barriers for students in educational settings (Annamma, 2015b; Heroux, 2013; Ryan, 2020). The purpose of this study was to examine a music educator collaborative teacher study group (CTSG) focused on exploring and unpacking...
Show moreThe way teachers engage with dis/ability and race in their classrooms links to theirunderlying belief systems (Heroux, 2013; Ryan, 2020). Unfortunately, substantial evidence connects teacher beliefs and perceptions to the reification of hegemonic norms, which upholds barriers for students in educational settings (Annamma, 2015b; Heroux, 2013; Ryan, 2020). The purpose of this study was to examine a music educator collaborative teacher study group (CTSG) focused on exploring and unpacking narratives of race and dis/ability in music education. Research questions were: 1) How do teachers conceptualize issues of race and ability in both their belief systems and stated classroom practices? 2) How, if at all, did participants’ beliefs about race and ability change as a result of participating in the CTSG? 3) What conditions facilitated changes in mindset and behavior for participants? I designed and completed a descriptive, collective case study (Stake, 1995; Yin 2018) that examined the experiences of eight music educators across the U.S. Participants were public school music educators who varied in age, teaching experience and assignment, personal identity characteristics and geographic location. As the researcher and facilitator, I served as the ninth member of the CTSG. Participants met via Zoom eleven times (every other week from July 27 to December 14, 2021) to share stories, discuss assigned readings/videos, participate in activities, and collaborate on lesson plans. Throughout the study, participants completed three individual interviews (beginning, midpoint, end), took turns leading the group sessions, contributed to a private social media page, and wrote in their online journal. In addition to my analytic memos, I used transcripts of interviews, planning meetings, CTSG meetings, conversations on Facebook and reflections in journals as data. I utilized two frameworks, Dis/ability Critical Race Theory (DisCrit) (Annamma et al., 2013) and Transformative Learning Processes (TLP) (Salvador et al., 2020a) to frame the study, design the CTSG, and analyze the data. Initially participants varied in their stated beliefs and described classroom practices. Further, participants displayed a continuum of prior experiences and stated goals, as well as a broad spectrum of agreements and dissonances between their words (stated beliefs and goals) and actions (conversations in the CTSG and descriptions of their teaching practice). By the end of the study, participants described and demonstrated several changes resulting from participation in the CTSG. Participants reported becoming more aware of the ways that racism and ableism operated in schools and in their personal lives. Furthermore, they reported that participation in the CTSG had lit a spark for continued discovery, reflection, and action. Many ended the CTSG by setting personal and professional goals, such as building allyship in their classroom or redesigning their curriculum through an equity-focused lens. Several conditions proved salient in creating an environment conducive to change. Primary factors that contributed to change were participants building connections with other music teachers, experiencing emotional intensity, having the space and time to grapple with difficult materials, as well as the structures put in place during the CTSG. Based on these themes, I offered several recommendations for practice and policy, including the importance of preservice and continuing education to work with diverse learners, and the necessity of highlighting voices of minoritized students in music education.
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Title: TENSILE DEFORMATION OF POLYMER NANOCOMPOSITES : HYDRODYNAMIC EFFECT AND MECHANICAL REINFORCEMENT
Creator: Sun, Ruikun
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Polymer nanocomposites (PNCs) are important functional materials with various applications because of their superior nanoparticle-reinforced properties. Among these enhanced macroscopic properties, mechanical reinforcement in PNCs is the most intriguing and among the first to be considered in applications from transportation, packaging to gas separation. However, understanding the mechanical reinforcement of PNCs remains a challenging task, especially in the large deformation regime where...
Show morePolymer nanocomposites (PNCs) are important functional materials with various applications because of their superior nanoparticle-reinforced properties. Among these enhanced macroscopic properties, mechanical reinforcement in PNCs is the most intriguing and among the first to be considered in applications from transportation, packaging to gas separation. However, understanding the mechanical reinforcement of PNCs remains a challenging task, especially in the large deformation regime where nonlinear effects emerge.This dissertation focuses on PNCs with well-dispersed spherical nanoparticles in the dilute and semi-dilute limit to investigate the mechanical reinforcement under large deformation at various Weissenberg number, ??=?̇?? with ?̇ being the Hencky strain rate and ?? the relaxation time of the polymer. At ??≪1, the nanoscale motion of nanoparticles first follows the macroscopic deformation. Beyond a critical elongation ratio defined by the interparticle spacing, the hydrodynamic interaction among nanoparticles leads to a strong deviation of the local spatial rearrangement of nanoparticles from the macroscopic deformation field. Further deformation leads to a deformation-induced nanoparticle network. More importantly, the elastic deformation of the network provides a strong enhancement to the mechanical strength of PNCs at large deformation.As ?? increases, strong microstructure rearrangement of nanoparticles is observed. Remarkably, the nanoparticle rearrangement does not affect the entanglement dynamics in the leading order and does not correlate with the macroscopic stress of the PNCs. These observations indicate that the deformation of matrix polymer plays a dominant role in the macroscopic stress of PNCs. To decouple the stress contributions from the matrix polymer and the nanoparticles, we further perform small-angle neutron scattering experiments that capture only the structure and dynamics of polymer matrices. Interestingly, the neutron experiments show that the magnitudes of polymer anisotropy in the PNC and the neat polymer are identical under the same deformation. Moreover, the stress relaxation of PNCs follows the time evolution of the structural anisotropy of the deformed matrix polymer. Similar phenomena are also observed for PNCs with nanoparticle aggregates and high nanoparticle loadings. These observations point to the absence of strain amplification or molecular overstraining in deformed PNCs and suggest the hydrodynamic effect as the leading molecular origin of the high mechanical strength of PNCs.To further quantify the molecular origin associated with the high polymer matrix contribution to the mechanical reinforcement, we carry out nonlinear rheology measurements for PNCs with different polymer molecular weights and nanoparticle loadings. The nonlinear rheological stress-strain curves of all these PNCs, if normalized by a constant dependent on PNC composition, are found to overlap with each other up to the stress overshoot point. This constant is directly correlated with the bulk polymer relaxation, instead of the interfacial polymers. These observations point to that the mechanical reinforcement of PNCs is controlled by the slowing down of the chain relaxation dynamics.
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Title: SEXUAL SOCIALIZATION : A QUALITATIVE EXPLORATION OF IMMIGRANT LATINA MOTHERS’ PERCEPTION OF SEX-COMMUNICATION WITH THEIR ADOLESCENT DAUGHTERS
Creator: Leija, Silvia Gisela
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This qualitative investigation explored the unique experiences of immigrant Latinamothers and sex-communication with their adolescent daughters in an era of high anti- immigration rhetoric in the United States. The research findings are summarized in two studies. In study one, we explored the views of sexuality and sexuality parenting of 15 immigrant mothers of Mexican origin, using an intersectional lens to guide data analysis. To contextualize our understanding of U.S. immigrant Latina...
Show moreThis qualitative investigation explored the unique experiences of immigrant Latinamothers and sex-communication with their adolescent daughters in an era of high anti- immigration rhetoric in the United States. The research findings are summarized in two studies. In study one, we explored the views of sexuality and sexuality parenting of 15 immigrant mothers of Mexican origin, using an intersectional lens to guide data analysis. To contextualize our understanding of U.S. immigrant Latina mothers, results describe participants’ identity as immigrants and its connection to their personal views on sexuality and intent to parent on sexuality. Three additional themes emerged: 1) mothers’ views of sexuality shaped by their intergenerational experiences—subthemes a) silence and misinformation, and b) striving for confianza to facilitate positive sex-communication experiences with daughter(s); 2) mothers’ self-doubt and discomfort with sex-communication—subtheme a) answering with uncertainty and insecurity; 3) the straddling of two worlds generates internal conflict concerning mothers’ views of sexuality and parenting—subthemes a) apprehension towards new perspectives on gender and sexuality, and b) fears of sexual violence shape how mothers parent and communicate with daughters. This qualitative study provides an opportunity to have a more in- depth analysis of unique processes immigrant Mexican mothers experience and the extent to which that shapes their views on sexuality and parenting. Study 2 sought to explore immigrant Mexican mothers’ reported processes of sex-communication with their adolescent daughters. This study revealed what Latina mothers think about the sexual experiences of their daughters and how their own experiences shape how they discuss sexuality with their adolescent daughters. The study findings generated five main themes: 1) Lecturing daughters about sexuality with the intent to protect; 2) Apprehension from personal experiences hinders positive sex- communication with daughters; 3) Heteronormative sexual identity and experiences for daughter are favored; 4) Grappling with Mexican/American sex values and family values; and 5) Mothers await cues from daughters to initiation sex-communication. Findings provide in-depth analysis of unique processes immigrant Mexican mothers experience and generate insights that are beneficial to sex education and prevention efforts tailored to this underserved population. Clinical implications for family therapy and parent-based sex education programming to help promote sexual health in immigrant Latino families are discussed.
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Title: Robust Learning of Deep Neural Networks under Data Corruption
Creator: Liu, Boyang
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Training deep neural networks in the presence of corrupted data is challenging as the corrupted data points may significantly impact generalization performance of the models. Unfortunately, the data corruption issue widely exists in many application domains, including but not limited to, healthcare, environmental sciences, autonomous driving, and social media analytics. Although there have been some previous studies that aim to enhance the robustness of machine learning models against data...
Show moreTraining deep neural networks in the presence of corrupted data is challenging as the corrupted data points may significantly impact generalization performance of the models. Unfortunately, the data corruption issue widely exists in many application domains, including but not limited to, healthcare, environmental sciences, autonomous driving, and social media analytics. Although there have been some previous studies that aim to enhance the robustness of machine learning models against data corruption, most of them either lack theoretical robustness guarantees or unable to scale to the millions of model parameters governing deep neural networks. The goal of this thesis is to design robust machine learning algorithms that 1) effectively deal with different types of data corruption, 2) have sound theoretical guarantees on robustness, and 3) scalable to large number of parameters in deep neural networks.There are two general approaches to enhance model robustness against data corruption. The first approach is to detect and remove the corrupted data while the second approach is to design robust learning algorithms that can tolerate some fraction of corrupted data. In this thesis, I had developed two robust unsupervised anomaly detection algorithms and two robust supervised learning algorithm for corrupted supervision and backdoor attack. Specifically, in Chapter 2, I proposed the Robust Collaborative Autoencoder (RCA) approach to enhance the robustness of vanilla autoencoder methods against natural corruption. In Chapter 3, I developed Robust RealNVP, a robust density estimation technique for unsupervised anomaly detection tasks given concentrated anomalies. Chapter 4 presents the Provable Robust Learning (PRL) approach, which is a robust algorithm against agnostic corrupted supervision. In Chapter 5, a meta-algorithm to defend against backdoor attacks is proposed by exploring the connection between label corruption and backdoor data poisoning attack. Extensive experiments on multiple benchmark datasets have demonstrated the robustness of the proposed algorithms under different types of corruption.
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