Digital Commons Network^™

Outside The Box: Examining The School Experience From The Perspectives Of Early Leavers, Caitlin Armstrong

Electronic Theses and Dissertations

Public schools in America are experiencing a massive decline in student enrollment, resulting in school consolidations and closures across the nation. (Dee, 2023). This decline has many implications, particularly in rural areas, such as Northeast Tennessee. These implications and the public pressure to maintain high graduation rates and academic outcomes, require school leaders and policymakers to reflect on who is leaving public schools and why. This phenomenological study explored the school experiences and perceptions of individuals who left the traditional high school prior to graduation. In-depth interviews were conducted one-on-one with 13 participants via an online video conferencing platform who …

Transformer-Based Deep Learning Prediction Of 10-Degree Humphrey Visual Field Tests From 24-Degree Data, Min Shi, Anagha Lokhande, Yu Tian, Yan Luo, Mohammad Eslami, Saber Kazeminasab, Tobias Elze, Lucy Shen, Louis Pasquale, Sarah Wellik, Carlos Gustavo De Moraes, Jonathan Myers, Nazlee Zebardast, David Friedman, Michael Boland, Mengyu Wang

Wills Eye Hospital Papers

PURPOSE: To predict 10-2 Humphrey visual fields (VFs) from 24-2 VFs and associated non-total deviation features using deep learning.

METHODS: We included 5189 reliable 24-2 and 10-2 VF pairs from 2236 patients, and 28,409 reliable pairs of macular OCT scans and 24-2 VF from 19,527 eyes of 11,560 patients. We developed a transformer-based deep learning model using 52 total deviation values and nine VF test features to predict 68 10-2 total deviation values. The mean absolute error, root mean square error, and the R2 were evaluation metrics. We further evaluated whether the predicted 10-2 VFs can improve the structure-function relationship …

Patient-Centered Clinical Decision Support Challenges And Opportunities Identified From Workflow Execution Models, Dean F Sittig, Aziz Boxwala, Adam Wright, Courtney Zott, Nicole A Gauthreaux, James Swiger, Edwin A Lomotan, Prashila Dullabh

Faculty, Staff and Student Publications

OBJECTIVE: To use workflow execution models to highlight new considerations for patient-centered clinical decision support policies (PC CDS), processes, procedures, technology, and expertise required to support new workflows.

METHODS: To generate and refine models, we used (1) targeted literature reviews; (2) key informant interviews with 6 external PC CDS experts; (3) model refinement based on authors' experience; and (4) validation of the models by a 26-member steering committee.

RESULTS AND DISCUSSION: We identified 7 major issues that provide significant challenges and opportunities for healthcare systems, researchers, administrators, and health IT and app developers. Overcoming these challenges presents opportunities for new …

Automatic Uncovering Of Patient Primary Concerns In Portal Messages Using A Fusion Framework Of Pretrained Language Modelsautomatic Uncovering Of Patient Primary Concerns In Portal Messages Using A Fusion Framework Of Pretrained Language Models, Yang Ren, Yuqi Wu, Jungwei W Fan, Aditya Khurana, Sunyang Fu, Dezhi Wu, Hongfang Liu, Ming Huang

Faculty, Staff and Student Publications

OBJECTIVES: The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs-a practice which holds the potential to yield more nuanced insights and enhances the quality of healthcare delivery and patient-centered care.

MATERIALS AND METHODS: We propose a fusion framework to leverage pretrained language models (LMs) with different language advantages via a Convolution Neural …

Artificial Intelligence In Fusion Protein Three-Dimensional Structure Prediction: Review And Perspective, Himansu Kumar, Pora Kim

Faculty, Staff and Student Publications

Recent advancements in artificial intelligence (AI) have accelerated the prediction of unknown protein structures. However, accurately predicting the three-dimensional (3D) structures of fusion proteins remains a difficult task because the current AI-based protein structure predictions are focused on the WT proteins rather than on the newly fused proteins in nature. Following the central dogma of biology, fusion proteins are translated from fusion transcripts, which are made by transcribing the fusion genes between two different loci through the chromosomal rearrangements in cancer. Accurately predicting the 3D structures of fusion proteins is important for understanding the functional roles and mechanisms of action …

Learning Nonlinear Dynamics In Synchronization Of Knowledge-Based Leader-Following Networks, Shimin Wang, Xiangyu Meng, Hongwei Zhang, Frank L. Lewis

Faculty Publications

Knowledge-based leader-following synchronization of heterogeneous nonlinear multi-agent systems is a challenging problem since the leader's dynamic information is unknown to any follower node. This paper proposes a learning-based fully distributed observer for a class of nonlinear leader systems, which can simultaneously learn the leader's dynamics and states. This class of leader dynamics is rather general and does not require a bounded Jacobian matrix. Based on this learning-based distributed observer, we further synthesize an adaptive distributed control law for solving the leader-following synchronization problem of multiple Euler–Lagrange systems subject to an uncertain nonlinear leader system. The results are illustrated by a …

Exploring The Relationship Of The Noncognitive Variables Of Grit And Mindset In Baccalaureate Nursing Students And Their Impact On Academic Success, Alecia Hollis

Dissertations

The study aimed to evaluate how the noncognitive variables of grit and mindset could impact the academic success of baccalaureate nursing students. With the present and growing shortage of nurses, attrition within nursing programs is cause for concern. Attrition is a multifaceted problem; however, academic failure is one contributing factor. While cognitive factors, such as the standardized aptitude test (SAT), pre-nursing science GPA, pre-nursing GPA, and standardized entrance exams (Al-Alawi et al., 2020; Chisholm-Burns et al., 2021), have traditionally been used for admission criteria, increasing evidence suggests that noncognitive factors, like grit and mindset, play a crucial role in academic …

First-Order Algorithms For Convex Smooth Optimization Problems With Homogeneous Linear Constraints, Yidan Guo

All Dissertations

The purpose of this dissertation is to explore the first-order methods that can be used to solve an approximate solution for convex smooth problems with homogeneous linear constraints. It consists of three interconnected research projects.

In the first project, we study the problem of computing the projection of a given vector onto the kernel of a symmetric positive semi-definite matrix. The complexity of an algorithm for computing a numerical solution is evaluated by the total number of matrix-vector multiplications required for computing an approximate solution. Such problems arise commonly in consensus optimization, in which the total number of matrix-vector multiplications …

Scalable Solution Of Time-Dependent Pdes Through Component-Wise Exponential Integrator, Chelsea Drum

Dissertations

Exponential integrators, such as exponential Runge-Kutta or Rosenbrock methods, are designed specifically for the time integration of stiff systems of ordinary differential equations (ODEs) and allow the use of larger time steps than other general-purpose ODE solvers. However, these methods rely on computing matrix function-vector products that are traditionally computed using a Krylov projection, such as Lanczos or Arnoldi iteration, that involves substantial computational expense at high spatial resolution. Krylov Subspace Spectral (KSS) methods' frequency-dependent approach, designed to circumvent stiffness in linear problems, computes these products with greater scalability. We propose the combination of such KSS methods with exponential integrators …

Modeling, Simulation, And Experimental Testing Of A Single-Legged Hopper, John Anthony Bennett

Master's Theses

Legged robots are well-suited for navigating unstructured terrain due to their ability to perform agile dynamic motions. Building on the efforts of Cal Poly's Legged Robotics Group, this project focuses on achieving stable forward hopping with a single legged robot.

A comprehensive model of leg hopping is formulated, with leg dynamics during flight and stance phases derived using Euler-Lagrange equations. During the stance phase, a spring-mass system models the leg-ground interaction. The touchdown and lift-off conditions are formulated mathematically, and state mappings between phases are determined via momentum conservation. A two-phase hybrid controller is designed, incorporating trajectory planning during flight …

Single Charge Carrier Dynamics In A Single Polymer Chain, Ming Lei

All Dissertations

Understanding how charge carrier move through conjugated polymers is crucial for optimizing the functionality and efficiency of various applications, from organic solar cells and light-emitting diodes (LEDs) to field-effect transistors. Previous studies have demonstrated that tracking the fluorescence centroid displacement provides a method to determine the position of single charge carriers in a conjugated polymer nanoparticle. This method allows the observation of charge carrier trajectories over time and allow researchers to obtain insights into the dynamic processes. In addition, a detailed map of the energy landscape can be constructed by analyzing the fluorescence spectrum. These techniques were previously applied to …

An Equity Centered Analysis Of Course Coordination's Effect On Undergraduate Calculus 1 Students' Mathematics Identity, Tyler Sullivan

All Dissertations

For institutions offering multiple sections of Calculus 1, course coordination allows for consistency among the sections through the reduction of variation of material and/or instructional approaches. Studies on course coordination have shown that a coordinated system can bring benefits to instructors and promote equality for students across multi-section course so they can expect the same instructional treatment as their peers. The benefits to students are often left implicit in current research and usually measured through academic success while the benefits to instructors are well documented. Past studies have also stressed the importance of consistency and fairness across sections brought by …

Optimization Strategies To Enhance Performance In Matrix/Tensor Factorization And Multi-Source Data Integration, Mengyuan Zhang

All Dissertations

Optimization in the realm of machine learning constitutes a fundamental process aimed at refining the parameters of models to enhance their performance. It serves as the backbone of various machine learning techniques, encompassing diverse algorithms and methodologies tailored to address specific tasks and objectives.

In machine learning, datasets are commonly structured as matrices or tensors, making techniques like matrix factorization and tensor factorization indispensable for extracting meaningful representations from intricate data. Furthermore, datasets commonly comprise multiple sets of features, which has inspired our exploration of effective strategies for leveraging information from diverse sources during optimization. Additionally, the interconnected nature of …

Materials Data Science Ontology (Mds-Onto): Unifying Domain Knowledge In Materials And Applied Data Science, Van D. Tran, Jonathan E. Gordon, Alexander Harding Bradley, Balashanmuga Priyan Rajamohan, Quynh D. Tran, Gabriel Ponón, Yinghui Wu, Laura S. Bruckman, Erika I. Barcelos, Roger H. French

Student Scholarship

Ontologies have gained popularity in the scientific community as a means of standardizing concepts and terminology used in metadata across different institutions to facilitate data comprehension, sharing, and reuse. Despite the existence of frameworks and guidelines for building ontologies, the processes and standards used to develop ontologies still differ significantly, particularly in Materials Science. Our goal with the MDS-Onto Framework is to provide a unified and automated system for ontology development in the Materials and Data Sciences. This framework offers recommendations on where to publish ontologies online, how to best integrate them within the semantic web, and which formats to …

A Few Good Techies: A Qualitative Exploration Of Black Computer Science Graduate Perceptions Of Persistence From A Community Cultural Wealth Perspective, Marissa Mcdaniel-Francis

Education Doctoral

In a rapidly digitizing economy, only 6% of computer scientists in the United States are identified as Black. This phenomenological research study focused on the personal attributes, academic experiences, and non-academic (support) experiences that Black computer science graduates perceive as contributing to their persistence in computing careers. Data were collected, transcribed, coded, and analyzed from semi-structured interviews of 11 Black computer science graduates. Community cultural wealth theory, critical race theory, and social capital theory framed this study's findings. The findings revealed that Black computer science graduates hold a strong science, technology, engineering, and math (STEM) identity and a positive social …

Linking Physiology, Epidemiology, And Demography: Understanding How Lianas Outcompete Trees In A Changing World, Hannes De Deurwaerder, Matteo Detto, Marco Visser, Stefan A. Schnitzer, Stephen W. Pacala

Biological Sciences Faculty Research and Publications

Extending and safeguarding tropical forest ecosystems is critical for combating climate change and biodiversity loss. One of its constituents, lianas, is spreading and increasing in abundance on a global scale. This is particularly concerning as lianas negatively impact forests’ carbon fluxes, dynamics, and overall resilience, potentially exacerbating both crises. While possibly linked to climate-change-induced atmospheric CO₂ elevation and drought intensification, the reasons behind their increasing abundance remain elusive. Prior research shows distinct physiological differences between lianas and trees, but it is unclear whether these differences confer a demographic advantage to lianas with climate change. Guided by extensive datasets collected …

To Each Their Own: The Relationship Among Regret, Habits, And Academic Performance In College Students, Chandler Ann Findley

Graduate Theses and Dissertations

The extant literature on regret as motivation for behavior presents inconclusive results, collectively. While it has often been agreed that regret motivates reparative action, most studies from the past 14 years indicate that regret may motivate either detrimental actions or, more commonly, no action at all. There also appears to be no published research about college students’ academic regrets or how these regrets affect their classroom behaviors and performance. Therefore, this dissertation seeks to understand if college students regret their academic habits, what those habits are, and how their regrets and habits contribute to their academic performance over the course …

Barriers To Telemedicine: Factors Influencing The Adoption Of Telemedicine, Carleton T. Brown

All Dissertations

Telemedicine is a rapidly evolving health treatment capability that offers an efficient and cost-effective alternative to conventional medical care. Providing access to alternative medical treatment may mitigate the population’s stress on the medical infrastructure in the upcoming decades. This study investigated the factors influencing patient adoption of telemedicine, including patient experiences and economic considerations. A quantitative survey explored patient population’s intention to utilize telemedicine, focusing on factors influencing the patients’ decision-making processes. Analyzing the survey results, the researcher focused on five main variables: exposure to telemedicine, age, loss of income, trust in doctors, and time lost. The research findings offer …

Contrast As A Governing Principle: Topic Deployment In Selected Sonatas Of Johann Christian Bach, Morgan Hall

Master's Theses

Between the end of the Baroque era and the end of the Classical era, there was a shift in the way music was composed. This shift allowed composers to employ multiple topics in one work as opposed to the single-affect-per-movement that was standard under the Doctrine of Affections. Despite plenty of scholarship about both of the eras, the transition from one to the other has been relatively unexplored. Early musicologist Charles Burney noted in a volume of his General History of Music that there was a composer who was the first to employ “contrast as a governing principle”, and this …

Fabrication And Characterization Of Lignin–Pva Hydrogels With Tunable Network Structures, Keturah Bethel

All Dissertations

The ability to directly tune the crosslinked network structure of hydrogels is crucial for their functional applications in various fields, such as water filtration, protein separation, and tissue engineering. By controlling the crosslink density of the hydrogel, one can directly alter the mesh size – i.e., the end-to-end distance between crosslink junctions – and, subsequently, directly alter the hydrogel performance. This work discusses the fabrication and characterization of soft composites containing the biopolymer, lignin, are discussed. Precisely, physically-crosslinked composite lignin–Poly(vinyl alcohol) (PVA) hydrogels were fabricated via the freeze-thaw (F/T) pathway, whereby solutions containing specified amounts of PVA and lignin were …

The Gavel And The Camera: Environmental Law And Photojournalism's Relationship To Appalachian Identity, Emily S. Patton

Honors Theses

Both the federal government and photojournalism have played a substantial role in the “othering” of Appalachia while simultaneously attempting to save it. Examining both institutions demonstrates the exploitative processes that alter the perception of rural communities and their surrounding environment. Stacey Kranitz’s archival exhibit, As It Was Give(n) To Me, internalizes this precarious role of the camera in a region heavily journalized. By inhabiting the area for years, establishing close relationships, and researching the documented history of Appalachia, Kranitz’s work becomes her livelihood in the dissolution of profession vs. personal. She is critical of past projects whose objective portrayal of …

Emotionality Stigma Scale: Measurement Development, Reliability, And Validity., Hayley D. Seely

Electronic Theses and Dissertations

Emotions are biological responses to stimuli that allow individuals to derive meaning, appraise experiences, and prepare to respond. However, individuals perceive emotions differently based on emotion socialization which not only dictates the way emotions are viewed and managed but also has been directly linked with mental health outcomes. Furthermore, research shows emotion socialization is informed by demographic variables such as gender such that the expectations of emotionality differ; where women are taught to express emotions, men are taught to conceal. Given the societal rules regarding emotionality, it is possible that emotionality stigma – the stigma around the experience and expression …

Bayesian Approaches In Multi-State Markov Models And High Dimensional Time-To-Event Data., Yuchen Han

Electronic Theses and Dissertations

This dissertation consists of two projects. The first one involves nonparametric methods on Continuous Time Markov Chains (CTMCs). The second one is centered around Bayesian shrinkage models for detecting prognostic and predictive biomarkers in high-dimensional clinical data. Both these projects build on methods from across the frequentist and Bayesian paradigm to offer novel solutions. In the first project, we aim to model the nonlinear effects of continuous variables within multistate framework in a non-parametrically by appealing to the rich mathematical framework of Reproducing Kernel Hilbert Spaces (RKHS). Then we adapted the classical Representer Theorem to penalized (squared norm) log-likelihood which …

Towards High Performance And Energy Efficient Data Centers., Bryan Harris

Electronic Theses and Dissertations

Our modern society has become ever more connected and reliant on ever larger quantities of data, which must be collected and processed over large geographic areas. The data centers that store, compute, and share this data have grown to such a scale that many data centers use as much electricity as a city. Priorities in research have shifted from not only seeking greater performance, but also towards greater energy efficiency. The control and management of computer systems has an impact on power consumption beyond the needs of individual components. In this dissertation, we examine techniques for improved performance and energy …

Denoising And Super-Resolution Of In-Vitro 4e Flow Mri In A Stenotic Phantom Model Using Physics-Informed Neural Networks., Shrouk M. Wally

Electronic Theses and Dissertations

In recent years, the use of 4D flow MRI has revolutionized cardiovascular imag- ing by providing comprehensive data on blood flow dynamics over time. However, the limited spatial and temporal resolution of this imaging modality can hinder the accurate assessment of complex hemodynamic phenomena. This thesis explores the application of Physics-Informed Neural Networks (PINNs) to enhance the resolution of 4D flow MRI data, thereby improving its clinical utility. PINNs are a class of neural networks that integrate physical laws into their training process. By embedding these physics equations, PINNs can discover the underlying physics of fluid dynamics to produce more …

Dynamic Prediction Of Disease Progression With Longitudinal Data, Wenhao Li

Dissertations and Theses (Open Access)

Dynamic prediction plays a pivotal role in clinical research, especially when forecasting time-to-event outcomes based on evolving longitudinal data. This process often leverages the integration of longitudinal and time-to-event data through joint modeling, a prevalent technique. Alongside joint modeling, landmark modeling stands as another key approach in the realm of longitudinal studies. These methodologies are instrumental in dynamically predicting clinical events by utilizing predictor variables measured over time, up until the moment predictions are made. Within this framework, Chapter 2 addresses the challenge of comparing joint modeling and landmark modeling for dynamic prediction in longitudinal studies, introducing a novel algorithm …

Cis Pedagogy Project Report, Sladana Krstic, Elizabeth Stubbs, Colin Watson

Student learning processes

The Australian Council for Educational Research (ACER) was contracted by the Council of International Schools (CIS) to undertake research investigating how their schools make decisions on pedagogical approaches and to develop a toolkit (published as the ‘Pedagogy Playbook’) to support schools in making those decisions. The project started in May 2022 with initial research conducted by the Klingenstein Center, Columbia University and completed in August 2024 by ACER. In this study, leaders, teachers, parents and students from more than 140 CIS member schools reflected on what matters when it comes to teaching and learning. They shared their priorities and decisionmaking …

Enumeration Of Level-K Hypertriangulations, Patrick J. Kaylor

Theses and Dissertations

Triangulations are a classical object in discrete and computational geometry that finds it uses in many other fields, including numerous applications. In this thesis we approach the question of enumerating all hypertriangulations of a point set, the family of tilings introduced by Olarte and Santos in 2022 as induced projections of hypersimplices. Unfortunately, the usual approach to enumeration of trinagulations using flips may not work for hypertriangulations as flip-connectivity is only conjectured for that family even in the two-dimensional case. As a result, we develop a DFS-based algorithm and present its Python implementation that enumerates all hypertriangulations of small point …

Math Meets The Clinic: Modeling Patient Specific Hnscc Radiation Response Dynamics, Rohan Vijayvikram, Pirmin Schlicke, Mohammad U. Zahid, Dina M. El-Habashy, Cem Dede, Clifton D. Fuller, Heiko Enderling

Radiation Oncology Medical Student Program 2024

Head and neck squamous cell carcinomas (HNSCCs) originate from the mucosal lining of the upper aerodigestive tract and radiation therapy has become a fundamental component in the standard care for these patients. However, the treatment's unique dynamics can lead to disparities in outcomes and biological responses in both tumor and normal tissues. A significant challenge remains in predicting individual patient responses to radiation, with variability often resulting in under or over-treatment and potentially adverse effects. The absence of reliable biomarkers highlights the need for predictive measures to guide clinical decisions in real-time. The integration of mathematical models in radiation therapy …

Project-Based Learning And Its Impact On Student Engagement, Well-Being, And Learning Outcomes: A Study Of Teachers’ Perspectives., Stefania Rubino

Student Theses and Dissertations

In recent years, the field of education has experienced major shifts characterized by a significant increase in the research of innovative instructional approaches. Project-based learning (PBL) is an educational approach that prioritizes collaborative projects and experiential learning activities, offering a unique framework for exploring the factors that influence student engagement, academic achievement, and overall well-being. Project-based learning (PBL) places emphasis on inquiry-based and student-centered learning through the successful completion of meaningful projects. The present study explored the impact of project-based learning (PBL) on student engagement, well-being, and learning outcomes as perceived by educators. This qualitative research was conducted, featuring interviews …