Digital Commons Network^™

“Local, But Intelligent”: Language Ideologies In The Informant Biographies Of The Linguistic Atlas Project, Nicholas A. Passarelli

Theses and Dissertations--Linguistics

This thesis argues for the relevance of the Linguistic Atlas Project (LAP) for studies of language ideologies, indexicality, and enregisterment. The LAP represents the largest dialect survey of North American English to date, offering an abundance of historical linguistic data for research in dialectology, linguistic geography, and variation over space and time. Additionally, the LAP also contains additional sources of sociolinguistic data, including informant biographies — documents written by fieldworkers at the conclusion of the LAP interview that summarize an informant’s demographic profile, as well as their personality, speech, and caliber as an interviewee. Rife with subjective judgments from the …

Forum On “Conquest”: Past-Present Politics Of Coloniality In Cinema On Latin America, Stephen Jakob Turner

Theses and Dissertations--Hispanic Studies

My dissertation analyzes the representation of Spanish “Conquest” in film as a critical commentary on the cultural present. Chapter 1, “Directorial Discord: The Cultural Politics of Representation in Apocalypto (USA/Mexico/UK, 2006) and Retorno a Aztlán (Return to Aztlán, Mexico, 1991)” focuses on the representation of the (im)possibility of Indigenous heroic protagonism and futurity in the origins of “Conquest.” Chapter 2, “‘The World is Thus’: Resistance and the Power of Ambivalent Conversion in Gabriel Retes’s Nuevo Mundo (The New World; Mexico, 1976) and Roland Joffé’s The Mission (USA/Paraguay, 1986)” posits that the “Conquest” problematizes the myth of …

Truth In Horror: Cinematic Representations Of Social Violence In Spain, Latin America, And The United States, Kelly Ferguson

Theses and Dissertations--Hispanic Studies

My dissertation, Truth in Horror: Cinematic Representation of Social Violence in Spain, Latin American, and the Latinx United States, investigates the recent explosion of political horror films that straddle the past and present, reflecting both the current political moment and the polemic historical memories of state repression against racialized others and ideological dissidents. Chapter One, “Paranoid Horror and the Return of Franco,” studies four Spanish horror films, Tras el cristal (1986), Pa negre (2010), Mientras duermes (2011), and Musarañas (2014), all of which feature child protagonists that seek out truth about violent family secrets, but ultimately reject it as …

'Grave Fears Of Collision' : James Beecher And The Administration Of Freedmen's Bureau Policy In Reconstruction South Carolina, Cameron Sauers

Theses and Dissertations--History

As an agent of the Freedmen’s Bureau and military officer, James Beecher embodied Federal power in the South Carolina Lowcountry. During Presidential Reconstruction, Beecher became a key administrator of Order No.15 that promised formerly enslaved peoples’s “40 acres and a mule” that formerly belonged to white plantation owners. Beecher, despite his antebellum abolitionist politics, was remarkably unsympathetic to freedpeople’s desire for independent landholding. Beecher believed that freedpeople were unfit for immediate citizenship and should sign labor contracts to return to plantations where they might be inculcated with Northern free labor values. Amid epidemic disease, famine, and white paramilitary violence, James …

The Kids Were Alt-Right: Radical Right Youth Activism And The Origins Of The White Power Movement, 1960-1980, Austin Zinkle

Theses and Dissertations--History

This dissertation explores the young people—primarily young men—involved and weaponized within the radical racist Right during the 1960s and 1970s in the United States. This project argues that young people were an active bedrock of support within racist and antisemitic organizations such as the American Nazi Party, the National Alliance, the Knights of the Ku Klux Klan, and others, and created a unique coalition that ultimately developed into a revolutionary racist Right and eventual white power movement by the 1980s. This dissertation makes a significant intervention in scholarship on the radical Right’s development over the past sixty years and serves …

From Displaced To Displacers: Scottish Crofters, First Nation Peoples And Commons Enclosure From The 1700s To The 1800s, Anna Herrington

Theses and Dissertations--History

In the 18^th and 19^th centuries, the enclosure of common systems shaped the displacement of people on a global scale whilst bringing the people---Scottish Highland crofters and Mi’kmaq First Nation Canadians from the margins where they have dwelled for centuries in historical scholarship to of the centre of not just their history, but our collective history. Both populations experienced attacks on their ties to their lands, resources, and culture through enclosure. The enclosure process lasted over two centuries and was interspersed with violent protest, proactive resistance, interspersed with periods of acceptance and determination against their forced removals. Investigating …

Normalization Techniques For Sequential And Graphical Data, Cole Pospisil

Theses and Dissertations--Mathematics

Normalization methods have proven to be an invaluable tool in the training of deep neural networks. In particular, Layer and Batch Normalization are commonly used to mitigate the risks of exploding and vanishing gradients. This work presents two methods which are related to these normalization techniques. The first method is Batch Normalized Preconditioning (BNP) for recurrent neural networks (RNN) and graph convolutional networks (GCN). BNP has been suggested as a technique for Fully Connected and Convolutional networks for achieving similar performance benefits to Batch Normalization by controlling the condition number of the Hessian through preconditioning on the gradients. We extend …

Novel Architectures And Optimization Algorithms For Training Neural Networks And Applications, Vasily I. Zadorozhnyy

Theses and Dissertations--Mathematics

The two main areas of Deep Learning are Unsupervised and Supervised Learning. Unsupervised Learning studies a class of data processing problems in which only descriptions of objects are known, without label information. Generative Adversarial Networks (GANs) have become among the most widely used unsupervised neural net models. GAN combines two neural nets, generative and discriminative, that work simultaneously. We introduce a new family of discriminator loss functions that adopts a weighted sum of real and fake parts, which we call adaptive weighted loss functions. Using the gradient information, we can adaptively choose weights to train a discriminator in the direction …

Consumers’ Responses To New Technologies In The Marketplace, Umair Usman

Theses and Dissertations--Marketing and Supply Chain

Chapter 1. This research examines whether the use of blockchain technology to back a brand’s claims (i.e., blockchain augmented claims) influences consumer preference for sustainable products. Consumers are demanding higher levels of transparency from brands and are also showing keen interest in consuming sustainable products, which includes products that promote social, environmental and economic sustainability. Recent advancement in digital technology, specifically blockchain, is offering an opportunity for brands to meet both these consumer demands. In five laboratory studies, I demonstrate that blockchain augmented claims, as compared to traditional industry practices (i.e., use of third-party labels and brand’s self-made claims), increases …

Statistical Intervals For Neural Network And Its Relationship With Generalized Linear Model, Sheng Yuan

Theses and Dissertations--Statistics

Neural networks have experienced widespread adoption and have become integral in cutting-edge domains like computer vision, natural language processing, and various contemporary fields. However, addressing the statistical aspects of neural networks has been a persistent challenge, with limited satisfactory results. In my research, I focused on exploring statistical intervals applied to neural networks, specifically confidence intervals and tolerance intervals. I employed variance estimation methods, such as direct estimation and resampling, to assess neural networks and their performance under outlier scenarios. Remarkably, when outliers were present, the resampling method with infinitesimal jackknife estimation yielded confidence intervals that closely aligned with nominal …

Probabilistic Methods For Inferring The Order Of Pathway Alterations During Carcinogenesis And Cancer Subtype Classification, Menghan Wang

Theses and Dissertations--Statistics

Carcinogenesis is a complex process involving somatic mutations in a number of key biological pathways. Studying cancer evolution is an important task which contributes to better understanding of cancer biology and facilitates identification of new therapeutic targets. We focus on two important questions in cancer evolution. The first question is to delineating the temporal order of pathway mutations during tumorigenesis. And the other question is to cluster patients into biologically meaningful cancer subtypes. We present new statistical methods to 1)leverage functional annotations of mutations to enhance estimation of the order of pathway mutations during carcinogenesis, 2) incorporate intra-tumoral heterogeneity information …

High Dimensional Data Analysis: Variable Screening And Inference, Lei Fang

Theses and Dissertations--Statistics

This dissertation focuses on the problem of high dimensional data analysis, which arises in many fields including genomics, finance, and social sciences. In such settings, the number of features or variables is much larger than the number of observations, posing significant challenges to traditional statistical methods.

To address these challenges, this dissertation proposes novel methods for variable screening and inference. The first part of the dissertation focuses on variable screening, which aims to identify a subset of important variables that are strongly associated with the response variable. Specifically, we propose a robust nonparametric screening method to effectively select the predictors …

Novel Modelling And Inference Considerations Involving The Exponentially-Modified Gaussian Distribution, Yanxi Li

Theses and Dissertations--Statistics

The exponentially-modified Gaussian (EMG) distribution is well-suited for analyzing data with positive skewness due to its characteristic positive skew from the exponential component. Despite its popularity in various fields, the EMG distribution has only been analyzed for univariate data without any regression settings. To address this limitation, we developed a generalized EMG regression model with covariates by assigning parametric functional forms to some or all of the parameters in the EMG distribution that vary with values of the covariates. To further perform data-clustering on observation points, we propose a competing regression model where the error structure is assumed to be …

Methodologies And Computational Tools For Zero-Inflated Discrete Weibull Models, Peng Yeh

Theses and Dissertations--Statistics

Count data with excess zeros is common in many fields, such as ecology, healthcare, and insurance. Excess zeros data are often causing the inaccurate fit from the count models. While zero-inflated models have been developing for over two decades, one should also consider a more flexible model that can handle the excess zeros and further over- or under-dispersion. In this talk, we discuss zero-inflated discrete Weibull model and some novel computational contributions. The flexibility and competitiveness of the ZIDW model are illustrated by simulation studies and a real data analysis. We also investigate the performance of the proposed model through …

Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky

Theses and Dissertations--Pharmacy

The introduction of antibiotics into clinical practice is considered the greatest medical breakthrough of the 20^thcentury. However, the use of antibiotics can contribute to the development of resistance. In the United States (U.S.), approximately 2.8 million people are infected with antibiotic-resistant bacteria each year, and more than 35,000 people die as a result. Moreover, some antibiotics are known to cause cardiac side effects including QT prolongation, hypotension, and ventricular arrythmias. The U.S. Centers for Disease Control and Prevention (CDC) defines appropriate antibiotic use as the effort to use “the right antibiotic, at the right dose, for the right …

An Epidemiological And Pharmacokinetic-Pharmacodynamic Investigation Into The Impact Of Carbapenem-Resistant Enterobacterales, Justin Clark

Theses and Dissertations--Pharmacy

Background: According to the 2019 CDC Antibiotic Resistance Threats Report, more than 2.8 million antibiotic-resistant infections occur in the United States each year, leading to more than 35,000 deaths. Among the most urgent threats identified by the CDC are carbapenem-resistant Enterobacterales (CRE). Despite efforts to control the spread of these organisms, the number of estimated cases between 2012 and 2017 remained stable. In 2017, an estimated 13,100 hospitalized cases of CRE led to approximately 1,100 deaths and $130 million attributable healthcare costs. This dissertation seeks to address this issue from both a pharmacokinetic/pharmacodynamic and epidemiological perspective.

Methods: We evaluated the …

Mitochondria As Causes Of And Therapeutic Targets In Chronic Post-Sepsis Skeletal Muscle Weakness, Meagan Scott Kingren

Theses and Dissertations--Pharmacology and Nutritional Sciences

Sepsis, or the organ damage that ensues after the body fails to properly contain a local infection, is the leading cause of in-patient hospitalization in the United States. Advances in critical care medicine over the last 20 years have enabled most sepsis patients to survive the life-threatening dysregulated immune response. However, a majority of survivors report chronic weakness and fatigue years after sepsis, and the cause of this weakness remains largely unknown. This dissertation work focused first on elucidating the major causes of post-sepsis muscle weakness (Aim 1). This aim involved a time-course study to determine when muscle weakness was …

Using Unconscious Thought To Improve Evaluations Of Complex Accounting Estimates, Blake Holman

Theses and Dissertations--Accountancy

Accounting practitioners and regulators have recently focused efforts toward increasing the efficiency of management review controls (MRCs), including the evaluation of complex accounting estimates. Although increasing cognitive effort (i.e., conscious deliberation) is an intuitively appealing strategy for improving decision quality, Unconscious Thought Theory (UTT) suggests that a period of unconscious thought is a more beneficial strategy in complex domains. Drawing on UTT, I predict and find across two studies that prompting accounting practitioners to engage in unconscious thought facilitates the recognition of patterns of bias within management provided estimates, resulting in higher quality assessments of fair value estimates. My findings …

Clustering Hospital Performance Using Group-Based Multi-Trajectory Modeling With Singular Bayesian Information Criterion, Gaixin Du

Theses and Dissertations--Epidemiology and Biostatistics

Hospital performance is complex and patient-experience oriented. Currently, the Centers for Medicare and Medicaid Services (CMS) evaluate hospitals yearly with a single score of one to five ("Star Rating") using composite measures from five domains. However, a single composite score cannot fully describe it, and alternative measures should be considered. Healthcare quality improvement needs long-term data to validate effectiveness. Group-based multi-trajectory modeling (GBMTM) estimates probabilities of latent group membership based on longitudinal profiles from multiple outcomes. We use GBMTM to identify groups of hospitals with similar performance in SAS PROC TRAJ.

We downloaded Medicare-eligible hospitals (N=5,111) that provided patient care …

Evaluating The Impact Of Mental Health Needs And Services Disruption: Covid-19 & Wisconsin Children’S Welfare Services, Gavin Rienne

Theses and Dissertations--Epidemiology and Biostatistics

Children’s traumatic experiences have lifelong impacts on their mental health and quality of life, therefore mental health services are a critical part of necessary community resources. The increased frequency and severity of natural disasters such as hurricanes, tornadoes, and pandemics reinforces the need to examine and understand the importance of mental health and child services in response to disaster events. This research assesses the relationship between disasters and subsequent health service utilization amongst children and adolescents. We investigated current research on the relationship between children’s mental health and community mental health resource efficacy and accessibility after a major disaster by …

Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp

Theses and Dissertations--Epidemiology and Biostatistics

In this series of studies, we examined the potential of a variety of blood-based plasma biomarkers for the identification of Alzheimer's disease (AD) progression and cognitive decline. With the end goal of studying these biomarkers via mixture modeling, we began with a literature review of the methodology. An examination of the biomarkers with demographics and other health factors found evidence of minimal risk of confounding along the causal pathway from biomarkers to cognitive performance. Further study examined the usefulness of linear combinations of biomarkers, achieved via partial least squares (PLS) analysis, as predictors of various cognitive assessment scores and clinical …

Utilization Of Uncrewed Aircraft Systems Towards Investigating The Structure Of The Atmospheric Surface Layer, Loiy Al-Ghussain

Theses and Dissertations--Mechanical and Aerospace Engineering

This study presents two approaches to investigate the surface-layer structure during the morning transition using uncrewed aircraft systems. The first approach employs three uncrewed aircraft systems- each equipped with a single multi-hole probe- simultaneously measuring horizontal transects were partnered with a fourth measuring vertical profiles during two consecutive mornings as part of the 2017 Collaboration Leading Operational Unmanned Aerial System Development for Meteorology and Atmospheric Physics (CLOUDMAP) measurement campaign near Stillwater, Oklahoma, U.S.A. Data were analyzed to extract time-dependent single-point statistics of kinematic and thermodynamic variables from the uncrewed aircraft systems. In addition, an approach is presented by which multi-point …

Machine Learning For Advancing Automation And Quality Control In Robotic Welding, Joseph Kershaw

Theses and Dissertations--Mechanical and Aerospace Engineering

Welding is a vital manufacturing process across a diverse range of industries to permanently join metallic components into needed assemblies. Though widely used and studied, the process is not fully understood due to the myriad of interconnected physics that present themselves during the welding process. Electrical, thermal, structural, and fluidic mechanics are simultaneously at work influencing one another to achieve the bonding that manufacturers desire. In addition to general manufacturing issues, such as tool wear or misalignment, micro-level changes to the material structure and composition can have cascading impacts on the final weld. This complexity makes it difficult, if not …

Generalizable And Adaptable Data-Driven Methods For Overcoming Barriers To Practical Industrial Condition Monitoring, Matthew B. Russell

Theses and Dissertations--Electrical and Computer Engineering

The future of smart manufacturing relies on predictive maintenance systems that intelligently minimize expensive downtime through timely assessment of machine condition. Deep Learning (DL) has achieved excellent performance in industrial condition monitoring experiments, but the constraints of the manufacturing environment prevent many algorithms from being practically deployed on the factory floor. Ubiquitous sensing from online machines generates high velocity data streams that require new techniques for efficient transmission and storage. Despite these ever-increasing data lakes, many applications still lack the data needed for training DL fault diagnosis and wear tracking models since most data is unlabeled and only from nominal …

Stratospheric Glider Measurements Of Atmospheric Parameters, Anisa Haghighi

Theses and Dissertations--Mechanical and Aerospace Engineering

In June 2021 a series of high altitude flights were conducted in Spaceport America, NM, using a balloon launched Uncrewed Aircraft System (UAS) to assess its capability to conduct measurements of various atmospheric properties and study turbulence in the troposphere and lower stratosphere. This UAS descends using an automated flight trajectory. The instruments aboard included a NASA-developed infrasonic microphone to evaluate its remote turbulence detection capabilities and a five-hole probe capable of measuring the in situ wind vector. Also on board were temperature, humidity and wind profile sensors. This document focuses on the atmospheric properties measured at high altitudes, the …

Precision Meteorological Prediction Employing A Data-Driven, Adaptive, Real-Time (Dart) Approach, Sujit Sinha

Theses and Dissertations--Mechanical and Aerospace Engineering

The objective of this research is to improve precision meteorological prediction, benefiting both uncrewed aerial vehicle (UAV) operations by avoiding hazardous flight conditions and tracking contaminant or toxic clouds caused by incidents, accidents, or fires. The operational concept is to collect meteorological observations from instruments mounted on a swarm of UAVs, telemeter the data to a weather simulation model, revise the predicted solution by adapting the flow field to the observations, and then transmit the updated forecast to appropriate personnel as well as to the guidance system of UAVs for repositioning to the next set of most beneficial measurements. While …

Assessment Of The Interplay Between Regional Β-Amyloid Burden And White Matter Hyperintensities On Cognition And Default Mode Network In Clinically Normal Older Participants, Doaa G. Ali

Theses and Dissertations--Clinical and Translational Science

Objective: Alzheimer’s disease (AD) and subcortical vascular dementia are considered the most common pathologic contributors to dementia in the aging population. Both frequently coexist in over 80% of community dwelling adults with dementia. The neuropathological development of AD arguably begins with β-amyloid (Aβ) deposition in the brain. This series of studies aims to test the hypothesis that early focal regional amyloid deposition in the brain is associated with cognitive performance in specific cognitive domain scores in preclinical AD (pAD) (study1). Since mixed dementia is widely recognized as the norm rather than the exception, the second study aimed to explore the …

Relative Adrenal Insufficiency In Sepsis, Dan Hao

Theses and Dissertations--Pharmacology and Nutritional Sciences

Sepsis is a leading cause of death in children. Glucocorticoid (GC) therapy had been strongly recommended for the pediatric sepsis (grade 1A). However, the recommendation was changed to grade 2C in 2020 due to weak evidence. Relative adrenal insufficiency (RAI) is a condition characterized by impaired inducible glucocorticoid (iGC) production in response to stress. It develops in 32.8% of pediatric septic patients. Unfortunately, little is known about the pathogenesis of RAI in pediatric sepsis, and whether GC therapy should be based on the status of RAI is controversial. In this study, we utilized 21-day-old SF1CreSRBI^fl/fl mice as the first …

Exploring The Efficacy Of Mir-33 Antagonism In Promoting Regression Of Intracranial Atherosclerosis In A Nonhuman Primate Model, Peter Hecker

Theses and Dissertations--Pharmacology and Nutritional Sciences

Atherosclerosis, characterized by lipid accumulation and arterial inflammation, is a major contributor to global morbidity and mortality. Despite significant progress in understanding atherosclerosis in extracranial arteries, the study of intracranial atherosclerosis (ICAS) has been relatively neglected, despite its crucial role in stroke and vascular cognitive impairment. Challenges related to ICAS, including its location within the cranium and limited availability of suitable animal models, have hindered research progress in this area. Although nonhuman primates (NHPs) are commonly used for studying extracranial atherosclerosis, a comprehensive understanding of ICAS pathophysiology in these animals is lacking. By subjecting NHPs to a high-fat/cholesterol diet, we …

Rewired Metabolism In Apoe4 Microglia: Implications For Inflammation And Neurodegeneration, Nicholas A. Devanney

Theses and Dissertations--Physiology

Among the earliest changes to occur in Alzheimer’s disease, metabolic dysfunction and chronic neuroinflammation are now known to be major driving forces in disease progression. The paradigm of ‘immunometabolism’ seeks to bridge these two facets, positing that metabolic transformations are indispensable in determining the response of immune cells, such as microglia – the brain’s resident immune population. Proinflammatory stimulation of microglia leads to a shift away from mitochondrial respiration towards a dramatic upregulation of the glycolysis pathway for energy production. This glycolytic burst provides microglia with a rapid supply of ATP, but comes at a cost, as utilizing glucose to …