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Title: THE INTERACTION BETWEEN GENETICS AND CLIMATE ON CRANIOFACIAL VARIATION : EXAMINING THE CAUSATIVE FORCES OF MACROMORPHOSCOPIC TRAIT EXPRESSION
Creator: Plemons, Amber
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Anthropologists have an extensive history using cranial form to measure group relatedness in past and present populations to answer a range of questions concerning population histories and cultural practices. However, most biological distance studies using skeletal remains do not consider extrinsic forces influencing modern human variation. Researchers have explored evolutionary and plastic responses in cranial form using measurements of the cranium and mandible, but these studies generally...
Show moreAnthropologists have an extensive history using cranial form to measure group relatedness in past and present populations to answer a range of questions concerning population histories and cultural practices. However, most biological distance studies using skeletal remains do not consider extrinsic forces influencing modern human variation. Researchers have explored evolutionary and plastic responses in cranial form using measurements of the cranium and mandible, but these studies generally drew inferences through population comparisons or using inadequate statistical and biological models that so often lead to conflicting findings or confounding interpretations. To fill this gap in our current understanding of modern human variation, I have combined global craniofacial morphological, climatic, and genetic datasets to measure the magnitude and directionality of several climate variables on craniofacial form, while controlling for population structure (e.g., microevolutionary forces and population history). Craniofacial morphological data from the Macromorphoscopic Databank (MaMD) are used in conjunction with microsatellite data from Pemberton (2013), representing populations that overlap in geographic space with those in the MaMD. Finally, climate data from the National Oceanic and Atmospheric Association (NOAA) and Climate Research Unit (CRU) websites were obtained for weather stations in close proximity to populations under study. This combined dataset is used to explore the interaction between climate and genetics on craniofacial variation across 11 geographic regions using a mixed model approach known as Bayesian Sparse Factor Analysis of Genetic Covariance Matrices (BSFG). Data analysis follows the methods described by Katz and colleagues (2016) but expands their study through the exploration of selection processes using additional climate variables, including coldest month and driest month averages and annual ranges of temperature and absolute humidity. Overall, the study found significant correlation between genetic and phenotypic data indicating MMS traits can serve as genetic proxies in biodistance analyses. Several traits had higher heritability estimates (malar tubercle, zygomaticomaxillary suture course, postbregmatic depression and anterior nasal spine). Features associated with the nasal complex and facial breadth, particularly anterior nasal spine, nasal bone contour, and interorbital breadth, had strong associations to climate. These climate findings correspond to previous research on nasal form and environment where cold-dry environments select for high, narrow noses. Further evidence of selective forces in MMS traits are apparent with the reduction of these features in more variable climates where the respiratory system experiences less stress. The evolutionary mechanisms behind craniometric data have been explored extensively. Such studies use a full suite of traits that capture overall size and shape of the human cranium; however, MMS traits focus on macroscopic assessments primarily in the midfacial skeleton. MMS trait data are particularly important for expanding our understanding of natural selection whereby a large portion of cranial evolutionary research has centered around the neutral evolutionary processes. The wealth of research demonstrating the nasal complex is highly responsive to climate due to respiratory stress emphasizes the importance of exploring the proportion of genetics and environments on MMS trait manifestation. This project provides an evolutionary foundation of the neutral evolutionary and selection processes controlling systematic patterns of global craniofacial variation in the Macromorphoscopic Databank (MaMD).
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Title: Novel methods for functional data analysis with applications to neuroimaging studies
Creator: Guha Niyogi, Pratim
Date: 2022
Collection: Electronic Theses & Dissertations
Description: In recent years, there has been explosive growth in different neuroimaging studies such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). The data generated from such studies are often complex structured which are collected for different individuals, via various time-points and across various modalities, thus paving the way for interesting problems in statistical methodology for analysis of such data. In this dissertation, some efficient methodologies are...
Show moreIn recent years, there has been explosive growth in different neuroimaging studies such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). The data generated from such studies are often complex structured which are collected for different individuals, via various time-points and across various modalities, thus paving the way for interesting problems in statistical methodology for analysis of such data. In this dissertation, some efficient methodologies are proposed with considerable development which have nice statistical properties and can be useful not only in neuroimaging but also in other scientific domains. A brief overview of the dissertation is provided in Chapter 1 and in particular, different kinds of data structures that are commonly used in consecutive chapters are described. Some useful mathematical results frequently used in the theoretical derivations in various chapters are also provided. Moreover, we raise some fundamental questions that arise due to some specific data structures with applications in neuroimaging and answer these questions in subsequent chapters. In Chapter 2, we consider the problem of estimation of coefficients in constant linear effect models for semi-parametric functional regression with functional response, where each response curve is decomposed into the overall mean function indexed by a covariate function with constant regression parameters and random error process. We provide an alternative semi-parametric solution to estimate the parameters using quadratic inference approach by estimating bases functions non-parametrically. Therefore, the proposed method can be easily implemented without assuming $\sqrt{?}$-convergence rate of the proposed estimator under the proper choice of bandwidth and establish its asymptotic normality. A multi-step estimation procedure to simultaneously estimate the varying-coefficient functions using a local linear generalized method of moments (GMM) based on continuous moment conditions is developed in Chapter 3 under heteroskedasticity of unknown form. To incorporate spatial dependence, the continuous moment conditions are first projected onto eigen-functions and then combined by weighted eigen-values. This approach solves the challenges of using an inverse covariance operator directly. We propose an optimal instrumental variable that minimizes the asymptotic variance function among the class of all local linear GMM estimators, and it is found to outperform the initial estimates that do not incorporate spatial dependence. Neuroimaging data are increasingly being combined with other non-imaging modalities, such as behavioral and genetic data. The data structure of many of these modalities can be expressed as time-varying multidimensional arrays (tensors), collected at different time-points on multiple subjects. In Chapter 4, we consider a new approach to study neural correlates in the presence of tensor-valued brain images and tensor-valued predictors, where both data types are collected over the same set of time-points. We propose a time-varying tensor regression model with an inherent structural composition of responses and covariates. This development is a non-trivial extension of function-on-function concurrent linear models for complex and large structural data where the inherent structures are preserved. Through extensive simulation studies and real data analyses, we demonstrate the opportunities and advantages of the proposed methods.
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Title: Data-Driven Multi-Scale Modeling, Analysis and Simulation of Material Failure
Creator: Barros de Moraes, Eduardo Augusto
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Material failure processes are inherently stochastic and anomalous, occurring across a wide span of length and time scales, from dislocation motion at the micro-scale, to formation of micro-cracks, up to crack propagation and aging mechanisms at the macro-scale and cascading failure at the system-level. Anomalies such as intermittent signals in Acoustic Energy experiments, power-law distribution of the energy spectrum, crackling noise, dislocation avalanches, among other indicators, occur...
Show moreMaterial failure processes are inherently stochastic and anomalous, occurring across a wide span of length and time scales, from dislocation motion at the micro-scale, to formation of micro-cracks, up to crack propagation and aging mechanisms at the macro-scale and cascading failure at the system-level. Anomalies such as intermittent signals in Acoustic Energy experiments, power-law distribution of the energy spectrum, crackling noise, dislocation avalanches, among other indicators, occur even in standard, ordered, crystalline materials. Modeling and simulation of failure must take into account parametric and model-form uncertainties that propagate across the scales, when seemingly unimportant material properties or loading conditions could cause catastrophic failure at the component level. The pursuit of a unified framework for quantitative and qualitative failure prediction that can bridge the multiple scales while still incorporating the material’s underlying stochastic processes is still a challenge, which requires a new modeling paradigm that incorporates such features with both robustness and simplicity.In this work, we propose a data-driven methodology for multi-scale, statistically consistent modeling of anomalous failure processes. At the micro-scale, the goal is to study the dynamics of dislocations, which play a vital role in plasticity and crack nucleation mechanisms, and shows anomalous features across different time and length-scales. We start by investigating the dislocation mobility properties at the nano-scale and propose a surrogate model for dislocation motion based on a Kinetic Monte Carlo method, where the dislocation motion is emulated as a random-walk on a network following a Poisson process. The surrogate learns the rates of the corresponding Poisson process directly from high-fidelity, Molecular Dynamics (MD) simulations. The surrogate is capable of efficiently obtaining uncertainty measures for the mobility parameter, which can be then propagated to more complex simulations in upper scales. At the meso-scale, the collective behavior of dislocation dynamics leads to avalanche, strain bursts, intermittent energy spikes, and nonlocal interactions. We develop a probabilistic model for dislocation motion constructed directly from trajectory data from Discrete Dislocation Dynamics (DDD). We obtain the corresponding Probability Density Function for the dislocation position, and propose a nonlocal transport model for the PDF. We use a bi-level Machine Learning framework to learn the parameters of the nonlocal operator and the coefficients of the PDF evolution equation, facilitating a continuum representation of the anomalous phenomena.At the macro-scale, parametric material uncertainties substantially affect the predictability of failure at the component level. We develop an Uncertainty Quantification (UQ) and Sensitivity Analysis (SA) framework for propagation of parametric uncertainties in a stochastic phase-field model of damage and fatigue, and we use the Probabilistic Collocation Method (PCM) as a building block. A Global SA indicates the most influential parameters in solution uncertainty and shows that damage initiation is sensitive to parameters associated with classical free-energy potential definitions, providing another motivation to incorporate the heavy-tail processes as observed in the meso-scale. We extend the framework and develop a Machine Learning (ML) framework for failure prediction phase-field models for brittle materials. We combine a classification algorithm with a pattern recognition scheme using virtual nodes from the phase-field damage model to generate patterns of material softening at each time-step. The framework identifies the presence and location of cracks and is robust even under noisy data, whether from model, parametric, or experimental uncertainties.
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Title: HELLGATE TO HIGHWAY : ISLAND MAKING, DREDGING, AND INFRASTRUCTURE IN THE DETROIT RIVER, 1874-1938
Creator: Swayamprakash, Ramya
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This dissertation exposes the tensions, trials, and tribulations along the U.S.-Canada border in the Detroit River between 1874 and 1938. I study how dredging—a seemingly inert process of removing river bottom sediment and depositing it elsewhere—helped create landforms across and along the political border, in turn, revealing the myriad social and political tensions that undergird it. By exposing how infrastructure revealed border tensions, especially those related to resource extraction,...
Show moreThis dissertation exposes the tensions, trials, and tribulations along the U.S.-Canada border in the Detroit River between 1874 and 1938. I study how dredging—a seemingly inert process of removing river bottom sediment and depositing it elsewhere—helped create landforms across and along the political border, in turn, revealing the myriad social and political tensions that undergird it. By exposing how infrastructure revealed border tensions, especially those related to resource extraction, scarcity, and national security—on both sides of the Canada-U.S. border—this dissertation offers a new way to link environmental and border history as well as environmental diplomacy.The lower Detroit River forms the ideal study site for two interrelated reasons. One, its narrow and rocky riverbed along the shipping channel was a dangerous bottleneck, slowing traffic on one of the busiest waterways in the world. Two, dredging the lower part of the river kept this busy waterway running efficiently. The Livingstone Channel fundamentally reordered the Detroit River when it was carved out of the riverbed where hitherto there existed fish spawning grounds and shallow water. Concentrating on the lower Detroit River in general and the Livingstone Channel in particular, this dissertation will show how conflict and cooperation overlapped when it came to international diplomacy in the Great Lakes. Cultural and social historians have analyzed Great Lakes borderlands. Environmental historians though have yet to fully analyze these lakes. The political border between the United States and Canada has often been portrayed as being benign and uncontested. Yet, as this dissertation shows, border infrastructure, such as shipping channels, was seldom uncontested. By focusing on the political border, this dissertation aims to bring attention to the border as a site rather than a liminal space or an end zone of state sovereignty. The border in this reading is the origin of state sovereignty. Studies of the Canada-U.S. borderlands have often explored the role of international environmental diplomacy, especially in the joint management and conservation of binational water bodies like the Great Lakes through policy mechanisms such as the Boundary Waters Treaty (BWT) of 1908 and the International Joint Commission. As my dissertation shows, however, the BWT was an important staging point on which the different intercultural and international misunderstandings were exposed. The Great Lakes have often been cast as being abundant, yet there is little or no work on how that plentitude was not just manufactured in thought, but also embodied in infrastructures. As a transformative process, dredging does not seem monumental. Yet, dredging in the Detroit River has permanently lowered the levels of Lakes Huron and Michigan by at least 25 cm. Dredging thus reveals how environmental transformation lies at the heart of Great Lakes geography as we know it. By exposing dredging in a connecting channel, this dissertation shows that infrastructural creation and imagination undergirds the Great Lakes environment. Infrastructure, as I show, is an important and unseen filter to understand intercultural and international relationships. This is especially true of countries such as the U.S. and Canada which pride themselves in intercultural similarities more than differences. Studying conflict and contestation offers a novel way to understand the cooperative mechanism that drives current borderlands diplomacy. Studying dredging along the lower Detroit River in the nineteenth and twentieth centuries reveals ideas about nature as well as historical challenges and contestations to them.
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Title: IMPROVING QT CORRECTION METHODS THROUGH THE ANALYSIS OF PRECLINICAL SAFETY PHARMACOLOGY DATA
Creator: Ether, Nicholas David
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Torsade de pointes is a polymorphic ventricular tachycardia that has been linked to sudden cardiac death. While typically rare and fleeting, increased risk for occurrence of and problematic outcomes from this arrhythmia has been attributed to prolonged QT intervals. These interval measurements of electrocardiogram waveforms represent the time between depolarization and repolarization of the ventricles. Prolongation of this period increases the likelihood of disruptions in ventricular...
Show moreTorsade de pointes is a polymorphic ventricular tachycardia that has been linked to sudden cardiac death. While typically rare and fleeting, increased risk for occurrence of and problematic outcomes from this arrhythmia has been attributed to prolonged QT intervals. These interval measurements of electrocardiogram waveforms represent the time between depolarization and repolarization of the ventricles. Prolongation of this period increases the likelihood of disruptions in ventricular cardiomyocyte conduction, which can lead to torsade de pointes events. Due to the potentially fatal outcomes associated with QT prolongation, it was not long until drugs found to induce this prolongation began to be removed from the market. These concerns led to the creation of safety pharmacology guidelines S7B and E14 that outlined suggested QT prolongation risk assessments to be performed during the preclinical and clinical stages of drug development, respectively. Studies based on these guidelines are intended to identify drug-induced changes to the QT interval, but must first control for the effect heart rate has on QT. To isolate drug effect QT correction methods are used to estimate corrected QT values as if the data was collected at a fixed heart rate. Using these values as a biomarker has led to highly sensitive assessments that have prevented any new drugs from reaching the market with unacceptable QT prolongation risk. However, these assessments are still in need of improvement as the pharmaceutical industry must deal with costly and time-consuming clinical safety studies despite the high sensitivity of preclinical assessments, leading to calls for the integration of preclinical and clinical guidelines. To achieve this, the translatability of preclinical results must be improved.This dissertation aims to increase the reliability of preclinical results and improve their translatability by optimizing the QT correction methods they rely on. To do this, I analyzed large ECG datasets from preclinical safety pharmacology studies obtained through Eli Lilly and Company (Indianapolis, IN). The central hypothesis of this dissertation is that through statistical analysis of these data, the collective understanding of QT correction methods will be expanded, and an improved method can be developed. In pursuit of this goal, the effectiveness of various preclinical QT correction methods was evaluated in simulated drug treatment scenarios, against 130,000+ bootstrap resampled ECG recordings of vehicle control treatments, and with study data from non-human primates treated with known QT prolonging drugs. The results of these evaluations provided evidence of how assumptions inherent to these methods affect the result of correction. Examples of such assumptions include what heart rate is relevant for the species, that a predetermined population-based estimate of the QT-rate relationship is appropriate for individuals, that this relationship will not change over time or between treatments, and that assuming this relationship before correction is appropriate in the first place. All of this led to the development of the novel Ratio QT correction method designed to be applicable to any scenario by dynamically responding to moment-to-moment changes in the relationship between timepoints. This novel method combines the simplicity and ease-of-use of population-based methods with the effectiveness of individual methods. Taken together, this research has increased the collective understanding of QT correction methods and resulted in a novel method that is as effective as it is simple to use. The investigations presented in this dissertation have explored aspects of QT correction methods that have been in question for years. Optimizing these methods is now easier thanks to the information gained through these analyses of large preclinical ECG datasets. An integral step has been made towards the creation of a new industry standard of QT correction capable of bridging the gap between preclinical and clinical safety pharmacology studies. Such improvements can be used to help reduce the number of research subjects necessary for preclinical and clinical QT prolongation assessments.
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Title: Iris Recognition : Enhancing Security and Improving Performance
Creator: Sharma, Renu
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Biometric systems recognize individuals based on their physical or behavioral traits, viz., face, iris, and voice. Iris (the colored annular region around the pupil) is one of the most popular biometric traits due to its uniqueness, accuracy, and stability. However, its widespread usage raises security concerns against various adversarial attacks. Another challenge is to match iris images with other compatible biometric modalities (i.e., face) to increase the scope of human identification....
Show moreBiometric systems recognize individuals based on their physical or behavioral traits, viz., face, iris, and voice. Iris (the colored annular region around the pupil) is one of the most popular biometric traits due to its uniqueness, accuracy, and stability. However, its widespread usage raises security concerns against various adversarial attacks. Another challenge is to match iris images with other compatible biometric modalities (i.e., face) to increase the scope of human identification. Therefore, the focus of this thesis is two-fold: firstly, enhance the security of the iris recognition system by detecting adversarial attacks, and secondly, accentuate its performance in iris-face matching.To enhance the security of the iris biometric system, we work over two types of adversarial attacks - presentation and morph attacks. A presentation attack (PA) occurs when an adversary presents a fake or altered biometric sample (plastic eye, cosmetic contact lens, etc.) to a biometric system to obfuscate their own identity or impersonate another identity. We propose three deep learning-based iris PA detection frameworks corresponding to three different imaging modalities, namely NIR spectrum, visible spectrum, and Optical Coherence Tomography (OCT) imaging inputting a NIR image, visible-spectrum video, and cross-sectional OCT image, respectively. The techniques perform effectively to detect known iris PAs as well as generalize well across unseen attacks, unseen sensors, and multiple datasets. We also presented the explainability and interpretability of the results from the techniques. Our other focuses are robustness analysis and continuous update (retraining) of the trained iris PA detection models. Another burgeoning security threat to biometric systems is morph attacks. A morph attack entails the generation of an image (morphed image) that embodies multiple different identities. Typically, a biometric image is associated with a single identity. In this work, we first demonstrate the vulnerability of iris recognition techniques to morph attacks and then develop techniques to detect the morphed iris images.The second focus of the thesis is to improve the performance of a cross-modal system where iris images are matched against face images. Cross-modality matching involves various challenges, such as cross-spectral, cross-resolution, cross-pose, and cross-temporal. To address these challenges, we extract common features present in both images using a multi-channel convolutional network and also generate synthetic data to augment insufficient training data using a dual-variational autoencoder framework. The two focus areas of this thesis improve the acceptance and widespread usage of the iris biometric system.
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Title: STUDYING MENTORS AND MENTORING FROM A LEARNER-CENTERED PERSPECTIVE
Creator: Croel-Perrien, Amy
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Teacher candidates, while completing their student teaching internship, are part of an important teaching-and-learning triad. The other members of the triad, mentor teachers and university field instructors, provide essential support to teacher candidates throughout the student teaching internship experience (Yee, 1968). Recent research has examined the roles of mentor teachers and university field instructors. Not as much is understood, however, about the moments or experiences teacher...
Show moreTeacher candidates, while completing their student teaching internship, are part of an important teaching-and-learning triad. The other members of the triad, mentor teachers and university field instructors, provide essential support to teacher candidates throughout the student teaching internship experience (Yee, 1968). Recent research has examined the roles of mentor teachers and university field instructors. Not as much is understood, however, about the moments or experiences teacher candidates recognize as when they learned the most about teaching. With retirements increasing and as much as 50% leaving the field within the first five years of teaching (Shwartz & Dori, 2016), there is an urgency in studying, and hopefully improving, novice teacher support systems.In this dissertation, I explore the moments or experiences teacher candidates recognize as insightful and valuable from their student teaching experience, from the perspective of four recent student teachers. Using phenomenology as a method of inquiry (Giorgi, 1985), data were collected through phenomenological interviews of four teacher candidates after they completed a year-long student teaching internship. These interviews tell the story of teacher candidates becoming through learning (Hodkinson et al., 2008). Findings indicate that framing problems of practice within practical situations, situations that likely occur in an elementary classroom, positively influence teacher candidates’ learning. The practice of adaptative mentoring (van Ginkel et al., 2015) provides opportunities for mentor teachers to support teacher candidates as they learn about teaching practice, while also helping them with emotional and practical concerns. Ultimately, I argue that grounding mentoring in both the how and why of teaching, along with adapting to the individual needs of teacher candidates, provides supportive opportunities for teacher candidates’ learning.
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Title: UNDERSTANDING THE PARASITIC VARIABILITY OF THE NORTHERN ROOT KNOT NEMATODE (MELOIDOGYNE HAPLA) THROUGH MULTIDISCIPLINARY APPROACHES OF SOIL BIOME AND ENVIRONMENT
Creator: Lartey, Isaac
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Managing Meloidogyne hapla remains challenging due to the ban of broad-spectrumnematicides, lack of resistant crops and its broad host range. It also has parasitic variability (PV) where populations (pop) are morphologically and genetically similar but vary in pathogenicity and reproductive potential. Although PV in M. hapla appears to have some relationship to soil types, what soil conditions favor its PV and/or its distribution are unknown. The goal of my research was to understand the soil...
Show moreManaging Meloidogyne hapla remains challenging due to the ban of broad-spectrumnematicides, lack of resistant crops and its broad host range. It also has parasitic variability (PV) where populations (pop) are morphologically and genetically similar but vary in pathogenicity and reproductive potential. Although PV in M. hapla appears to have some relationship to soil types, what soil conditions favor its PV and/or its distribution are unknown. The goal of my research was to understand the soil conditions where M. hapla PV exist by quantifying the biophysicochemical (BPC) conditions from the ecosystem down to microbiome level. I designed observational and experimental approaches and tested four objectives. First, was to evaluate the association between soil conditions and M. hapla distribution at the ecosystem level. My hypothesis was that the presence of M. hapla will be associated with degraded soil conditions. I selected 15 (6 muck and 9 mineral soil) agricultural fields with adjacent natural vegetation in southwest, northwest and eastern regions of the lower peninsula of Michigan as study sites. I collected a total of 75 (5 per field) georeferenced soil samples from agricultural fields and equal number from adjacent natural vegetation soils, quantified the soil food web (SFW) conditions using the Ferris SFW model, and screened for M. hapla presence or absence. The fields were described either as disturbed, degraded (worst-case) or maturing (best-case). Meloidogyne hapla was present in 3 mineral (2, 8 and 13) and 6 muck (4, 5, 6, 10, 14 15) agricultural fields with degraded and/or disturbed soil conditions and absent from maturing soils, partially supporting the hypothesis. Degraded soils had low nitrogen content in both soil groups. The second objective was to isolate and culture the 9 M. hapla populations to test a hypothesis that PV is related to specific SFW conditions. I found three categories of reproductive potential: the highest (Pop 13), medium (Pop 8), both from degraded mineral soils, and lowest from disturbed mineral (Pop 2) and disturbed (Pops 4, 6 and 10) and degraded (Pops 5, 14 and 15) muck soils. Thus, the hypothesis was not supported. The third objective, was to determine relationships between microbial community structure and M. hapla distribution. My working hypotheses were that there is a relationship among microbiome, soil health and M. hapla occurrence. Microbial community structure in the fields was determined from sub-samples of the same samples where the nematodes were isolated. I used 16S (bacteria) and ITS (fungi) rDNA analysis and characterized the microbial composition, core- and indicator-microbes co-existing with M. hapla pop in the field soils and soil conditions relative to the Ferris SFW model description. The results showed that bacterial and fungal community abundance and composition varied by soil group, SFW conditions and/or M. hapla occurrence. I found that a core of 39 bacterial and 44 fungal sub-operational taxonomic units (OTUs) were found variably, 25 bacterial OTUs associated with presence or absence of M. hapla, and 1,065 OTUs were associated SFW conditions. All three hypotheses were supported. The final objective was to determine the relationship between PV and the microbes associated with M. hapla pop. I compared bacteria present in M. hapla pop isolated from the field and greenhouse cultures. The hypothesis was that either presence and/or absence of specific bacteria are associated with M. hapla population. Population 8 shared more bacteria with the lowest reproductive potential pop than Population 13. Presence of several bacteria was unique to Population 8 as was the absence of other bacteria to Pop 13 in either field or greenhouse nematodes. Therefore, the hypothesis was supported. My research findings provide a foundation for: a) testing the relationship between M. hapla PV and the BPC conditions and b) designing soil health-based management strategies.
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Title: Level Structures on Finite Group Schemes and Applications
Creator: Guan, Chuangtian
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The notion of level structures originates from the study of the moduli of elliptic curves. In this thesis, we consider generalizing the notion of level structures and make explicit calculations on different moduli spaces. The first moduli space we consider is the moduli of finite flat (commutative) group schemes. We give a definition of $\Gamma(p)$-level structure (also called the ``full level structure") over group schemes of the form $G\times G$, where $G$ is a group scheme or rank $p$ over...
Show moreThe notion of level structures originates from the study of the moduli of elliptic curves. In this thesis, we consider generalizing the notion of level structures and make explicit calculations on different moduli spaces. The first moduli space we consider is the moduli of finite flat (commutative) group schemes. We give a definition of $\Gamma(p)$-level structure (also called the ``full level structure") over group schemes of the form $G\times G$, where $G$ is a group scheme or rank $p$ over a $\Z_p$-scheme. The full level structure over $G\times G$ is flat over the base of rank $|\GL_2(\F_p)|$. We also observe that there is no natural notion of full level structures over the stack of all finite flat commutative group schemes. The second moduli space we consider is the moduli of principally polarized abelian surfaces in characteristic $p>0$ with symplectic level-$n$ structure ($n\ge 3$), which is known as the Siegel threefold. By decomposing the Siegel threefold using the Ekedahl--Oort stratification, we analyze the $p$-torsion group scheme of the universal abelian surface over each stratum. To do this, we establish a machinery to produce group schemes from their Dieudonn\'e modules using a version of Dieudonn\'e theory due to de Jong. By using this machinery, we give explicit local equations of the Hopf algebras over the superspecial locus, the supersingular locus and ordinary locus. Using these local equations, we calculate explicit equations of the $\Gamma_1(p)$-covers over these strata using Kottwitz--Wake primitive elements. These equations can be used to prove geometric and arithmetic properties of the $\Gamma_1(p)$-cover over the Siegel threefold. In particular, we prove that the $\Gamma_1(p)$-cover over the Siegel threefold is not normal.
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Title: The Aging Mind and Body in Eighteenth-Century British Literature and Culture, 1680-1830
Creator: Oh, June Young
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Aging Mind and Body offers a literary history of the concept of aging between 1680 and 1830. I trace the interplay between the century’s literature and developing medical theories of the human body, revealing the long eighteenth century to be a crucial cultural moment that transformed what aging meant both for writers and for the broader public. While in the early modern period authors predominantly associated aging with wisdom and spiritual growth, Enlightenment science reconceived aging as...
Show moreAging Mind and Body offers a literary history of the concept of aging between 1680 and 1830. I trace the interplay between the century’s literature and developing medical theories of the human body, revealing the long eighteenth century to be a crucial cultural moment that transformed what aging meant both for writers and for the broader public. While in the early modern period authors predominantly associated aging with wisdom and spiritual growth, Enlightenment science reconceived aging as radically debilitating for both the body and the mind. I argue that this shift spurred significant literary innovations as writers exploited, negotiated, and subverted scientific assumptions about growing old. Excavating the history behind the emergence of derogatory terms for aging such as “senility” and “senescence,” I show that the literary portrayal of aging was effectively turned into a contested site for reimagining normative human life and progress. Each of my chapters examines a different supposed problem of aging—rising immobility, mental disability, changing physical appearance, and declining sexuality—as it emerges in the major works of Daniel Defoe, Jonathan Swift, Lady Mary Wortley Montagu, Mary Leapor, John Cleland, and Jane Austen. In particular, I undertake a critical re-reading of aging as it intersects with racism, sexism, ableism, and classism. Reading these works in terms of aging, I argue, complicates our traditional story of the long eighteenth century’s attention to progress, revealing not simply an ongoing struggle to marginalize the aging mind and body but also an important literary attempt that refigured “decline” as a constitutive and meaningful part of the whole life experience.
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Title: Neutron-unbound states in the nucleus 31Ne
Creator: Chrisman, Dayah Nichole
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Studies of nuclei far from stability reveal trends among groups of neighboring nuclei where new and unexpected properties appear. One such region, the Island of Inversion near the N=20 shell gap, is home to nuclei with reordered single-particle energy levels compared to the spherical shell model. Studies of the 31Ne nucleus have revealed that its ground state has a halo component, characterized by a valence neutron orbiting a deformed 30Ne core. This lightly-bound nucleus with a separation...
Show moreStudies of nuclei far from stability reveal trends among groups of neighboring nuclei where new and unexpected properties appear. One such region, the Island of Inversion near the N=20 shell gap, is home to nuclei with reordered single-particle energy levels compared to the spherical shell model. Studies of the 31Ne nucleus have revealed that its ground state has a halo component, characterized by a valence neutron orbiting a deformed 30Ne core. This lightly-bound nucleus with a separation energy of Sn=0.15(+0.16, -0.10)$~MeV is expected to have excited states that are neutron-unbound. This work presents a first study of the neutron-unbound excited states of 31Ne. Neutron-unbound states in 31Ne were populated in a two-proton knockout reaction from an 89 MeV/u 33Mg beam incident on a segmented Be reaction target. The 30Ne fragment and associated neutron from the decay of 31Ne* were detected by the MoNA-LISA-Sweeper experimental setup at the National Superconducting Cyclotron Laboratory. Invariant mass spectroscopy was used to reconstruct the two-body decay energy (30Ne+n).The two-body decay energy spectrum exhibits two features: a low-lying peak at 0.30 (+/- 0.17) MeV and a broad enhancement at 1.50 (+/- 0.33) MeV, each fit with an energy-dependent asymmetric Breit-Wigner line shape representing a resonance in the continuum. Accompanying shell model calculations combined with cross-section calculations using the eikonal reaction theory indicate that these features in the decay energy spectrum originate from multiple resonant states in 31Ne.
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Title: Patient-specific prediction of abdominal aortic aneurysm expansion using efficient physics-based machine learning approaches
Creator: Jiang, Zhenxiang
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Computational vascular Growth and Remodeling (G&R) models have been developed to capture key physiological and morphological features during the arterial disease progression and have shown promise for aiding clinical diagnosis, prognosis prediction, and staging classification. However, the translation of computational G&R models into their applications has yet to wait for clinical practice. Partly, due to the high complexity of the arterial adaptation mechanism, high-fidelity arterial G&R...
Show moreComputational vascular Growth and Remodeling (G&R) models have been developed to capture key physiological and morphological features during the arterial disease progression and have shown promise for aiding clinical diagnosis, prognosis prediction, and staging classification. However, the translation of computational G&R models into their applications has yet to wait for clinical practice. Partly, due to the high complexity of the arterial adaptation mechanism, high-fidelity arterial G&R simulations typically require hours or even days, which hinders its time-consuming applications such as patient-specific parameter estimation, disease prediction, verification, validation, and sensitivity analysis. Furthermore, the typical Finite Element Method (FEM) based computational G&R model should be extended to provide the uncertainty quantification associated with simulation and prediction results. Therefore, to enhance practicality of the G&R modeling, we develop a novel and computationally efficient simulation framework that comprehensively combines physics-based G&R simulations and data-driven machine learning methods using a Multi-Fidelity Surrogate (MFS) approach. This greatly enhances the computational efficiency of arterial G&R simulations, enabling more time-consuming applications such as personalized parameter estimation. The proposed framework is then tested for a specific disease, Abdominal Aortic Aneurysms (AAAs), by estimating G&R model parameters from follow-up CT images in 21 patients.
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Title: IT’S LIKE LOOKING IN A MIRROR, ONLY NOT : THE INFLUENCE OF ACQUIRER-TARGET SIMILARITY ON CORPORATE ACQUISITIONS
Creator: Wuorinen, Stefan
Date: 2022
Collection: Electronic Theses & Dissertations
Description: With the recent explosion of behavioral acquisition research, the collective knowledge in respect to acquisition behavior and outcomes has advanced tremendously. Despite these advancements, due to the rapid growth in this literature, various shortcomings have also developed. One such shortcoming is that the vast majority of this literature has examined acquisition influences emanating from the acquirer or the target but has rarely investigated the joint effects of these two entities. As such,...
Show moreWith the recent explosion of behavioral acquisition research, the collective knowledge in respect to acquisition behavior and outcomes has advanced tremendously. Despite these advancements, due to the rapid growth in this literature, various shortcomings have also developed. One such shortcoming is that the vast majority of this literature has examined acquisition influences emanating from the acquirer or the target but has rarely investigated the joint effects of these two entities. As such, in an attempt to contribute to the growing wealth of acquisition knowledge, the aim of this dissertation is to extend this research by examining how the degree of similarity between the acquirer and target can contribute to the outcomes of acquisition decisions. Specifically, this dissertation first investigates the implications for post-acquisition innovation due to pre-acquisition authority structure similarity, while also introducing and testing the arguments of Structural Adaptation Theory to the macro-organizational level and acquisition literature. Second, the influence of CEO regulatory fit between acquirer and target executives and the degree to which their respective orientations align with each manager’s negotiation roles within an acquisition are argued to influence acquisition premium and market reactions. Collectively, these studies begin to illuminate the joint affects that acquirers and targets have on distinct acquisition outcomes.
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Title: THE ROLE OF ARID1A IN ENDOMETRIOSIS-RELATED INFERTILITY
Creator: Marquardt, Ryan Michael
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The inner lining of the uterus, the endometrium, is composed of a luminal epithelial cell layer supported by an underlying stroma which contains epithelial gland structures. These distinct cell types coordinate with complex and dynamic molecular crosstalk tightly controlled by ovarian steroid hormones to regulate a healthy menstrual cycle and support the initiation and maintenance of a healthy pregnancy. Endometriosis occurs when endometrium-like tissue forms lesions outside the uterine...
Show moreThe inner lining of the uterus, the endometrium, is composed of a luminal epithelial cell layer supported by an underlying stroma which contains epithelial gland structures. These distinct cell types coordinate with complex and dynamic molecular crosstalk tightly controlled by ovarian steroid hormones to regulate a healthy menstrual cycle and support the initiation and maintenance of a healthy pregnancy. Endometriosis occurs when endometrium-like tissue forms lesions outside the uterine cavity, and this painful disease afflicts about 10% of reproductive-age women, an estimated 176 million worldwide. Up to 50% of these individuals also experience infertility, and many cases cannot be explained by morphological or ovarian defects, which implicates a uterine environment that is non-receptive to embryo implantation. The molecular basis for the correlation between endometriotic lesion presence and a non-receptive endometrium is unclear, but available evidence suggests that dysregulation of epigenetic regulators may play a role. Expression of AT-rich interaction domain 1A (ARID1A), a chromatin remodeling factor, is lost in some endometriotic lesions and markedly reduced in endometrial biopsies from infertile women with endometriosis, but it is essential in the uterus for fertility. This dissertation evaluates the overarching hypothesis that ARID1A loss connects endometriosis and infertility by causing increased lesion development and a non-receptive endometrium. Chapter 1 provides a review of the current literature on the topics of normal ovarian steroid hormone regulation of endometrial function, the dysregulation that occurs in endometriosis with its clinical implications and therapeutic options, and the specific involvement of ARID1A in endometrial pathophysiology. Chapter 2 delineates a critical role for endometrial epithelial ARID1A in uterine gland function for fertility. Chapter 3 reports the need for endometrial epithelial ARID1A to maintain uterine immune homeostasis during early pregnancy. Chapter 4 explores the involvement of endometrial ARID1A loss in a mouse model of endometriosis-related infertility. Chapter 5 describes a method for in vivo photoacoustic imaging of this endometriosis mouse model through the application of nanoparticle labeling. Finally, Chapter 6 summarizes the findings, discusses conclusions from the synthesized data in the context of the current literature, and provides ideas for future studies of related topics. Together, the studies herein make the case that endometrial ARID1A loss contributes to endometriosis-related infertility by exacerbating endometriotic lesion formation and compromising the ability of the endometrium to maintain the gland function and immune homeostasis necessary for the establishment and maintenance of pregnancy. Continued investigation through studies like these is key to understanding endometrial pathophysiology at the molecular level in order to enable development of targeted treatment options for women suffering the devastating effects of endometriosis and related infertility.
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Title: SUBJECTIVE AND OBJECTIVE STRESS RESPONSES AMONG YOUNG AUTISTIC ADULTS
Creator: Peña, Jarhed Macarubbo
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This study was conducted to examine the subjective (psychological) and objective (physiological) stress responses of autistic individuals guided by the Transactional Theory of Stress and Coping by Lazarus and Folkman (1984). Subjective stress responses were measured through a Visual Analog Scale (VAS) rating by the participants on their stress perception and objective stress responses were measured through heart rate variability (HRV) using a heart rate monitor as participants underwent a...
Show moreThis study was conducted to examine the subjective (psychological) and objective (physiological) stress responses of autistic individuals guided by the Transactional Theory of Stress and Coping by Lazarus and Folkman (1984). Subjective stress responses were measured through a Visual Analog Scale (VAS) rating by the participants on their stress perception and objective stress responses were measured through heart rate variability (HRV) using a heart rate monitor as participants underwent a standardized online Trier Online Stress Test (TSST; Kirschbaum et al., 1993) protocol to stimulate a social evaluative stress protocol. A systematic and qualitative interview was followed to investigate the appraisal of participants’ perception on the TSST. Literature suggests lack of insight and poor reporting of stressful experiences among autistic individuals. Participants consisted of 12 young adults with autism spectrum disorder (ASD) and 24 typically developing young adults currently attending college. Both subjective and objective stress quantitative analyses resulted in non-significant findings. However, findings suggested some between-group differences in subjective stress responses and objective stress responses for each phase of the stress stimulation (i.e., Baseline, Stress Task, Recovery). Particularly, higher observed stress perception and HRV were noted during Baseline and Recovery and lower observed stress perception and HRV were noted during the Stress Task in the ASD group. Further exploration of qualitative data findings revealed that both groups were able to have insight and self-report physical stress response such as increased heart rate and sweating, further supporting the importance of the appraisal of the stressful experience. Clinical, education, and research implications are also addressed. In terms of clinical implications, the current study highlighted young adults are susceptible to stress and can benefit from stress management intervention regardless of ASD diagnosis. Early intervention to teach autistic individuals stress management skills may also be beneficial. Furthermore, the use of objective measures can raise the awareness of one’s stress response, and that the appraisal of one’s subjective perception of stress is equally important in understanding individual differences in the stress experience. In terms of education implications, educators should train health professionals such as rehabilitation counselors in understanding diverse ways of stress manifestation and coping. They should also be trained to teach stress coping skills when working with clients, including autistic individuals. In terms of research implications, the unique methodology to combine psychological data with physiological data, as well as appraisal process to obtain cognitive information to gain a more holistic perspective on the stress experiences of participants. Future research recommends increasing sample size and diverse demographic participants, matching participants with ASD with those without, re-examining different methods to characterize potential similarities and differences among ASD, typically developing and other clinical groups, further examining not only the stress phase but also the baseline and recovery phases of the stress stimulation, improving the ASD screening to verify autism diagnosis, recruiting participants who have not received stress management intervention or training, examining the impact of in person and online TSST, and investigating the impact of comorbid conditions on stress responses in the ASD population.
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Title: Coalescence and Animal Use : Examining Community Building at the Multi-Ethnic Morton Village Site
Creator: Painter, Autumn Marie
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Across human history, groups of people have come together, found commonalities, and negotiated their differences in order to form new communities; a process known as coalescence. Until recently, archaeologists have primarily studied this social phenomenon by looking at the large-scale changes that occur, including settlement aggregation and demography. New research has begun to focus on smaller scales of analysis, including aspects of daily life and the role of common behaviors in bringing...
Show moreAcross human history, groups of people have come together, found commonalities, and negotiated their differences in order to form new communities; a process known as coalescence. Until recently, archaeologists have primarily studied this social phenomenon by looking at the large-scale changes that occur, including settlement aggregation and demography. New research has begun to focus on smaller scales of analysis, including aspects of daily life and the role of common behaviors in bringing people together. One such aspect of daily life is food. While previous research has recognized that changes in subsistence systems, such as a need to intensify the production of food to feed larger numbers of people, are commonly part of the coalescence process, little has been done to understand how these changes would affect a community or how a socially charged medium, such as food, may have contributed to ongoing coalescence. In this dissertation, I examine how animal use intersects with the broader process of coalescence through a multidimensional analysis of faunal remains from Morton Village, a site of on-going coalescence in the central Illinois River valley. Specifically, three aspects of animal use during the coalescence process were examined: 1) studying the overall diet as it intersects with the negotiation of everyday life, 2) animal access strategies including foodsharing practices, and 3) the use of animals and animal symbolism in ritual activities as a part of the long-term process of coalescence. These analyses found that the occupants of Morton Village used a diverse range of animal species, avian symbolism, and foodsharing/distribution practices within a variety of social interactions and practices. From this data, I argue that the use of animals played an important role in the coalescence process at Morton Village by assisting in building social relationships that were critical to community formation and maintenance during the coalescence process. This study demonstrates that the study of animal use is a fruitful avenue of research that can reveal several mechanisms for how social relationships are formed and community building processes occurred during coalescence.
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Title: IMPACTS OF DISTANT DRIVERS ON LANDSCAPES AND BIODIVERSITY
Creator: Hovis, Ciara Layne
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Global biodiversity is increasingly impacted by distant drivers. With societies more connected than ever before, natural resource consumption has expanded beyond administrative and political boundaries. International food trade in particular has profound impacts on land-use and socioeconomic and environmental outcomes. At the same time, global biodiversity is threatened at an unprecedented scale, with many of the causes obfuscated by complexities of distant, interacting socioecological...
Show moreGlobal biodiversity is increasingly impacted by distant drivers. With societies more connected than ever before, natural resource consumption has expanded beyond administrative and political boundaries. International food trade in particular has profound impacts on land-use and socioeconomic and environmental outcomes. At the same time, global biodiversity is threatened at an unprecedented scale, with many of the causes obfuscated by complexities of distant, interacting socioecological systems. Understanding the ultimate drivers of biodiversity change and translating them to local biodiversity outcomes is integral to addressing conservation challenges in the age of globalization. This dissertation analyzes the impacts of international trade on biodiversity in an agroecosystem undergoing land-use change driven by global markets. Chapter 1 provides background on the study region, Heilongjiang Province, and describes disruption of soybean production in the area due to changes in global trade. Chapter 2 is a systematic review of studies on distant drivers of biodiversity change. Across all taxa, harmful impacts on biodiversity were the most frequent outcome reported, with distant impacts of trade and tourism most frequently studied. In Chapter 3, satellite imagery was classified into landcover classes to create high-fidelity maps of the agriculture-dominated study landscape. By utilizing phenological, synthetic aperture radar, and vegetation/soil index data, accuracies of 91%- 80% were achieved. In Chapter 4 these landcover maps were used to calculate landscape metrics. These metrics were then used to analyze relationships between landscape structure (i.e., composition and configuration) and bird communities. Functional biodiversity indices derived from life history and morphological traits were examined in addition to taxonomic measures. Though no discernable differences between taxonomic and functional community metrics were observed, several significant relationships between landscape structure and biodiversity metrics were found. Crop diversity, natural landcover, and edge metrics, were positively correlated with bird richness. Aggregation of patches, corn area, and soybean area were negatively correlated. We also compared landscape structure and biodiversity between two regions impacted by global soybean trade. Despite the more impacted region having lower crop diversity and natural area, there was no difference in biodiversity between the two regions. The more impacted region also had more rice area, demonstrating that negative biodiversity impacts may be mitigated by rice cultivation. Chapter 5 built on the previous chapter by modeling bird occupancy to assess species-specific relationships with landscape structure. Results indicated that increased crop diversity significantly increased occupancy of birds at both the taxonomic and functional level, particularly for birds belonging to less common functional groups. Percentage of natural area was not as important as expected, while metrics related to landscape configuration had very few significant impacts on occupancy. Increases in rice area were not as detrimental to bird occupancy as increases in corn and soybean. In fact, soybean area exhibited more significant negative relationships with bird occurrence than corn, suggesting that decreases in soybean area due to global trade may have benefitted bird biodiversity in the case of a monocultural landscape. However, due to the prevalence of small-scale farming practices, the more likely outcome would be a decrease in crop diversity due to soybean fields being converted to more profitable crops (e.g., corn, rice). By linking global trade, changes in landcover/use, landscape structure, and local bird communities in the same context, the results of this dissertation highlight the need for integrated biodiversity studies that place ecosystems in the broader context of globalization.
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Title: A CASE STUDY EXPLORING HOW K-12 STUDENTS LEARN TO USE SOCIAL MEDIA FOR CIVIC GOOD
Creator: Askari, Emilia Shirin
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This case study explores what K-12 students learn from a 13-week class activity about attracting attention to civic issues on social media. This research responds to calls by scholars of civic education to expand notions of civic engagement and digital citizenship, which often have focused on urging students to protect their reputations in digital spaces. In contrast, the learning activity examined here encourages community-oriented digital citizenship, preparing students to inform and...
Show moreThis case study explores what K-12 students learn from a 13-week class activity about attracting attention to civic issues on social media. This research responds to calls by scholars of civic education to expand notions of civic engagement and digital citizenship, which often have focused on urging students to protect their reputations in digital spaces. In contrast, the learning activity examined here encourages community-oriented digital citizenship, preparing students to inform and possibly empower social change. This study is grounded in Cognitive Flexibility Theory, which focuses on learning in ill-structured domains such as public social media. Further, the study builds on the increasingly popular idea of the Fifth Estate, which posits that people acting in civic ways in public spaces can be a powerful check on government, playing a role similar to that of journalism institutions, sometimes referred to as the Fourth Estate. Data collected in this study included a pre-survey, a written reflection and post interviews with 4 students as well as artifacts such as social media posts. Students employed two main strategies to draw attention to civic issues on social media: audience-signaling and networking. Further, students learned to seek credible and diverse information using class accounts on TikTok, Instagram, and Twitter. Finally, students offered definitions of digital citizenship and shared thoughts about how schools should teach it via social media. This study fills a gap in the research literature about K-12 teaching with social media; few prior studies take advantage of social media’s affordance as a bridge between the classroom and communities outside the school. This study also illuminates learning as schools globally moved online in response to the pandemic.
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Title: Examining an Important Assumption in the Faultline Literature
Creator: Guo, Zhiya
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Group faultlines are defined as hypothetical dividing lines that split a team into subgroups based on the alignment of team members’ attributes. Prior faultline research has almost exclusively focused on the implications of between-subgroup relationships assuming that “team members form homophilous ties on either side of a faultline by associating with others in the team who have similar demographic attributes” (Ren et al., 2015, p. 390). However, this important assumption has not been tested...
Show moreGroup faultlines are defined as hypothetical dividing lines that split a team into subgroups based on the alignment of team members’ attributes. Prior faultline research has almost exclusively focused on the implications of between-subgroup relationships assuming that “team members form homophilous ties on either side of a faultline by associating with others in the team who have similar demographic attributes” (Ren et al., 2015, p. 390). However, this important assumption has not been tested. Drawing from social comparison theory and its “similarity hypothesis,” I argue that homogeneous, faultline-based subgroups may serve as a hotbed for social comparisons, and comparisons on social power can engender conflict under certain circumstances, triggering within-subgroup conflict. More specifically, consistent with the emerging research that recognizes different types of group faultlines, I outlined a) different dimensions that different faultline-based subgroups are more likely to compare and b) the downstream effects of these comparisons. Hypotheses were tested using multi-wave, round-robin data from multiple intact work teams of full-time employees. Results largely supported my predictions regarding knowledge-based subgroups but not so much for identity-based subgroups or resource-based subgroups. Implications and future directions are discussed.
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Title: PALETTEVIZ : A METHOD FOR VISUALIZATION OF HIGH-DIMENSIONAL PARETO-OPTIMAL FRONT AND ITS APPLICATIONS TO MULTI-CRITERIA DECISION MAKING AND ANALYSIS
Creator: Talukder, AKM Khaled Ahsan
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Visual representation of a many-objective Pareto-optimal front in four or more dimensional objective space requires a large number of data points. Moreover, choosing a single point from a large set even with certain preference information is problematic, as it imposes a large cognitive burden on the decision-makers. Therefore, many-objective optimization and decision-making practitioners have been interested in effective visualization methods to en- able them to filter down a large set to a...
Show moreVisual representation of a many-objective Pareto-optimal front in four or more dimensional objective space requires a large number of data points. Moreover, choosing a single point from a large set even with certain preference information is problematic, as it imposes a large cognitive burden on the decision-makers. Therefore, many-objective optimization and decision-making practitioners have been interested in effective visualization methods to en- able them to filter down a large set to a few critical points for further analysis. Most existing visualization methods are borrowed from other data analytics domains and they are too generic to be effective for many-criterion decision making. In this dissertation, we propose a visualization method, using star-coordinate and radial visualization plots, for effectively visualizing many-objective trade-off solutions. The proposed method respects some basic topological, geometric and functional decision-making properties of high-dimensional trade- off points mapped to a three-dimensional space. We call this method Palette Visualization (PaletteViz). We demonstrate the use of PaletteViz on a number of large-dimensional multi- objective optimization test problems and three real-world multi-objective problems, where one of them has 10 objective and 16 constraint functions. We also show the uses of NIMBUS and Pareto-Race concepts from canonical multi-criterion decision making and analysis literature and introduce them into PaletteViz to demonstrate the ease and advantage of the proposed method.
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