Digital Commons Network^™

Synthetic Efforts Towards An Analog Of Ly426965, Macy Sproles

Honors Theses

The 5-hydroxytryptamine_1A (5-HT_1A) receptor is a key target in the treatment of various neuropsychiatric conditions, and the development of selective antagonists offers promising therapeutic potential.²⁴ This study aimed to develop a synthetic analog of LY426965, a selective 5-HT_1A receptor antagonist. The synthetic route was initiated from dimethyl-2-phenylmalonate, employing pig liver esterase (PLE) as an enantioselective biocatalyst to achieve regioselective hydrolysis of one ester moiety in the malonic diester intermediate.¹⁷ Through a series of stereochemically controlled transformations, a new intermediate was successfully synthesized. Although the target molecule was not obtained, a new compound was synthesized …

Culture And Context: How Frames Of Teaching And Of Learning Mathematics Form And Change For Graduate Student Instructors, Johan Benedict A. Cristobal

Department of Mathematics: Dissertations, Theses, and Student Research

Why do instructors teach the way that they do? This question is key in understanding how and why asset-based or deficit-based practices are enacted in the classroom. In consequence, this question also gives insight into how the environment where students learn is shaped. Mathematics education research, in particular, has been concerned with how instructors respond to students’ contributions in the classroom and how these ways of responding can (dis)empower students.

One way to answer this question is to understand how instructors frame their own teaching and their students’ learning. Frames are mental constructs which help individuals filter details, interpret information, …

Car Price Prediction Using Machine Learning: Analyzing The Dvm-Car Dataset, Yaman Abu Ghareebaih

Electronic Theses and Dissertations

The objective of this study is to predict car prices using machine learning models and the DVM-CAR dataset, which includes over 1.4 million images and car specifi- cations from 899 car models. Key factors such as mileage, engine power, and year of registration were analyzed for their correlation with car prices. Extensive data cleaning was performed, including filling missing values, identifying outliers, and normalizing numerical variables. Discrete variables like car make and body type were encoded using one-hot encoding. Linear relationships were analyzed with Multiple Logistic Regression, and Random Forest models were used for nonlinear patterns. Model performance was evaluated …

An Integrative Approach To Einstein’S Field Equations Of General Relativity For High School Students, Christina M. Aintablian

Senior Honors Theses

Einstein’s Field Equations form the foundation of the theory of General Relativity, describing the interdependence of mass-energy and spacetime curvature, where curvature gives rise to gravity. However, the complexity of these equations makes them difficult for high school students to grasp. The mathematical framework of General Relativity is introduced step by step, beginning with relative motion and culminating in a discussion of complex phenomena that challenge modern physics. Each explanation intertwines core concepts of relativity with pre-established mental models to enhance learning. Through the use of figures, analogies, narratives, and thought experiments, a structured framework is developed to make relativity …

Comparing Spatial Interfaces Of The Tower Of London Task, Paean Luby

Honors Theses

Executive functioning involves key mental skills like self-control and problem-solving, which are often impaired by brain injuries. The Tower of London (TOL) task is a problem set commonly used to assess planning, but both traditional and digital versions can lack consistency, and, in the case of digital versions, realism and physical engagement. Research shows that 3D tasks, such as a 3D version of the Tower of Hanoi, engage the brain in distinct and meaningful ways, likely due to increased spatial involvement. By merging immersive 3D environments with the consistency of digital tools, virtual reality (VR) has the potential to enhance …

Analyzing Unmanned Aircraft System (Uas) Incidents From Nasa Asrs Data Using Unsupervised Machine Learning, Kacey Haws

Electrical Engineering and Computer Science Undergraduate Honors Theses

The NASA Aviation Safety Reporting System (ASRS) assembles voluntarily submitted aviation safety incident reports in their database to act on the information provided. This database allows the government, companies, and citizens to submit incident or situational reports to its database to discern recurring issues in the National Aviation System (NAS) so that the proper officials can act [1]. The narratives provided in these reports are text-based, resulting in large amounts of data to process. Previous work in the University of Arkansas Aerospace Systems Engineering and Transportation Laboratory (ASYST) lab involved parsing unmanned aircraft system (UAS) incident reports manually. While these …

Air And Missile Defense Threat Scenario Variation To Reduce Pretest Sensitization, Video Games As A Case Study, Julie Renee Szekerczes

All-Inclusive List of Electronic Theses and Dissertations

This study uses fixed and variable video game types to measure pretest sensitization as a proxy for repeated and varied threat test scenarios in system performance testing of air and missile defense systems. The pretest sensitization phenomenon exists when repeated exposure to a test condition influences the participant's response. Research shows air and missile defense development correlates with video games, resulting in similar interfaces and computer operating environments. Department of Defense acquisition test and evaluation results must reflect system performance without prior knowledge of the threat scenarios confounding the results. System performance results inform acquisition decisions, such as further funding …

Building Toward A Text-Based Intervention For Parents Of Suicidal Adolescents Seeking Emergency Department Care: A Pilot Randomized Controlled Trial., Ewa Czyz, Inbal Nahum-Shani, Cynthia Ewell Foster, Valerie Micol, Amanda Jiang, Nadia Al-Dajani, Alejandra Arango, Maureen Walton, Victor Hong, Sheikh Iqbal Ahamed, Cheryl King

Computer Science Faculty Research and Publications

Objective: The growing demand for emergency department (ED) care for suicidal ideation and attempts in adolescents calls for effective interventions preventing post-ED recurrence of suicidal crises. Parents are tasked with implementing postdischarge suicide prevention recommendations, often with little support. To address this need, this study examined a parent-facing texting intervention targeting parental engagement in suicide prevention activities to lower youth suicide risk after discharge. Method: A pilot randomized controlled trial was conducted with 120 parents (83.3% mothers) and their adolescents (ages 13–17, 65.8% female, 75.0% White) presenting to an ED with suicide risk concerns. Parents were randomized to a control …

The Effect Of Hiv-1 Infection Associated Bacterial Lipopolysaccharide (Lps) On Human Oral Keratinocytes: Implications For Promoting Chronic Inflammation, Md Shafayat Jamil

Theses and Dissertations

Human immunodeficiency virus type 1 (HIV-1) remains a major global health concern, affecting approximately 39 million people worldwide, with 500,000 new infections reported in 2022. While combined antiretroviral therapy (cART) has significantly reduced viral replication, HIV-1 infection is linked to various comorbidities, including oral dysbiosis and accelerated aging. Immune dysregulation in HIV-1–infected individuals promotes the proliferation of pathogenic gram-negative bacteria like Porphyromonas gingivalis, a key contributor to periodontal disease. P. gingivalis secretes lipopolysaccharide (LPS), which adversely affects human oral keratinocytes (HOK), the first line of defense against microbial threats in the oral cavity. HOK recognize LPS as a threat, …

Evaluating Free Merchandise Use At Coastal Carolina University, Ally Murphy, Ciara Cassady, Joseph Dumars

Goal 13: Climate Action

No abstract provided.

Enhancing Deliberativeness: Evaluating The Impact Of Multimodal Reflection Nudges, Shun Yi Yeo, Zhuoqun Jiang, Anthony Tang, Simon Tangi Perrault

Research Collection School Of Computing and Information Systems

Nudging participants with text-based reflective nudges enhances deliberation quality on online deliberation platforms. The effectiveness of multimodal reflective nudges, however, remains largely unexplored. Given the multi-sensory nature of human perception, incorporating diverse modalities into self-reflection mechanisms has the potential to better support various reflective styles. This paper explores how presenting reflective nudges of different types (direct: persona and indirect: storytelling) in different modalities (text, image, video and audio) affects deliberation quality. We conducted two user studies with 20 and 200 participants respectively. The first study identifies the preferred modality for each type of reflective nudges, revealing that text is most …

Cyberoception: Finding A Painlessly-Measurable New Sense In The Cyberworld Towards Emotion-Awareness In Computing, Tadashi Okoshi, Zexiong Gao, Yi Zhen Tan, Takumi Karasawa, Takeshi Miki, Wataru Sasaki, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

In Affective computing, recognizing users’ emotions accurately is the basis of affective human–computer interaction. Understanding users’ interoception contributes to a better understanding of individually different emotional abilities, which is essential for achieving inter-individually accurate emotion estimation. However, existing interoception measurement methods, such as the heart rate discrimination task, have several limitations, including their dependence on a well-controlled laboratory environment and precision apparatus, making monitoring users’ interoception challenging. This study aims to determine other forms of data that can explain users’ interoceptive or similar states in their real-world lives and propose a novel hypothetical concept “cyberoception,” a new sense (1) which …

Novel Statistical Methods For Mediation Analysis With High-Dimensional Omics Mediators, Zhichao Xu

Dissertations and Theses (Open Access)

Mediation analysis is a widely used statistical method for examining how molecular traits, such as gene or protein expression, act as intermediaries linking an exposure to a health outcome. For example, it can help explain how smoking affects disease risk through molecular changes. The rapid progress in high-throughput omics profiling technologies and large-scale epidemiology consortia, such as the Trans-Omics for Precision Medicine (TOPMed) program from the National Heart, Lung and Blood Institute (NHLBI) and UK Biobank, now has resulted in an extensive accumulation of genomic data for biomedical research and analysis. At the same time, it poses significant methodological challenges, …

Qualitative And Quantitative Analysis Of New Psychoactive Substances And Related Metabolites Using Liquid Chromatography-Ion Mobility-Mass Spectrometry (Lc-Im-Ms), Ralph Aderorho

All Dissertations

The increasing prevalence of novel psychoactive substances (NPS) in illicit drug markets has posed significant challenges for forensic and clinical toxicology, primarily due to the structural similarity and diversity among these compounds. This dissertation investigates the application of advanced liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS/MS) techniques, using the high-resolution Structures for Lossless Ion Manipulations (SLIM) platform and the drift tube ion mobility spectrometry (DT-IMS), for the qualitative and quantitative analysis of various types of synthetic opioids, synthetic cannabinoids, psychedelics and xylazine. By combining IMS separations with mass spectrometry and targeted chemical derivatization, this work enhances the ability to distinguish and characterize …

The Stem Gender Gap: Can It Be Closed?, Makenna Roberts

Undergraduate Honors Capstone Projects

Despite increasing gender parity in many professional fields, women remain underrepresented in STEM industries, particularly in math-intensive areas such as engineering, computer science, and physics. This report explores the persistent gender gap in STEM through analysis of two data sources: gendered differences in the US national Scholastic Aptitude Test (SAT) performance and post-graduate employment patterns among scientists and engineers.

The first portion of the analysis examines SAT score data from 2018 to 2024, with a focus on high-performing test-takers. Using Python and R, data was extracted and visualized to compare male and female performance on the Math and Evidence-Based Reading …

Navigating The Challenges Of Coccidioides Surveillance: Insights From The Environment Of El Paso County, Texas, Tanzir Hossain

Open Access Theses & Dissertations

Coccidioidomycosis, or Valley fever, is a fungal infection resulting from the inhalation of spores from the Coccidioides species (C. immitis and C. posadasii), native to arid areas of the Western Hemisphere. Coccidioidomycosis presents considerable health hazards and can be fatal. It affects between 206,000 and 360,000 individuals annually, leading to 700 to 1,100 fatalities in the United States alone. In response to these issues, extensive research has concentrated on therapeutic goals for this infectious disease. Nonetheless, more limited research has focused on the environmental detection of its causative fungi, which is crucial for forecasting treatment needs and formulating preventive strategies. …

Exploring Latent Mediation Through Bayesian Regularization Methods Of Lasso, Ridge, Horseshoe, Spike-And-Slab, Ethan Harris

Graduate Theses and Dissertations

Regularization is a powerful tool to combat overfitting and drive sparsity in complex models. Regularization was initially applied in regression modeling but has been increasingly utilized in structural equation modeling where its utility in identifying the essential components has helped improve modeling. As structural equation models have increased in complexity both in the number of indicators but also the number of latent factors, researchers have begun to investigate how applying Bayesian regularization to these systems can further push the limits on modeling complex models with limited sample sizes. One area where research is limited is the application of Bayesian regularizations …

Achieving Flexible Fairness And Privacy In Federated Learning, Alycia N. Carey

Graduate Theses and Dissertations

Having access to large, high-quality datasets is crucial for training machine learning models that achieve satisfactory performance. Unfortunately, it is common that a single entity (e.g., mobile device or organization) does not have access to such datasets due to monetary or resource constraints. Traditional machine learning requires that all training data reside in a centralized location during the entire duration of model training, however, in many circumstances it is difficult or even impossible (e.g., due to governmental regulations) for multiple parties to combine their data to meet this constraint. Federated learning is a machine learning paradigm that facilitates the joint …

The Role Of Ai In Enhancing Teamwork, Resilience And Decision-Making: Review Of Recent Developments, Satyadhar Joshi

Harrisburg University Other Works

This paper explores the transformative impact of artificial intelligence (AI) on organizational teamwork, decision-making, and resilience. This paper furthur reviews recent literature on the integration of Artificial Intelligence (AI) in various organizational functions, focusing on its impact on innovation management, leadership paradigms, and organizational resilience. We provide groundwork required to enhance frameworks that can integrate cognitive scaffolding with antifragile team dynamics, employing behavioral economics and neurocognitive principles. We introduce methodologies for enhancing team resilience through adaptive AI systems, cross-training interventions, and pre-mortem simulation techniques. The framework addresses key challenges in confirmation bias mitigation, cultural dimension alignment, and vigilance decrement prevention. …

Culture And Context: How Frames Of Teaching And Of Learning Mathematics Form And Change For Graduate Student Instructors, Johan Benedict Arroyo Cristobal

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Why do instructors teach the way that they do? This question is key in understanding how and why asset-based or deficit-based practices are enacted in the classroom. In consequence, this question also gives insight into how the environment where students learn is shaped. Mathematics education research, in particular, has been concerned with how instructors respond to students’ contributions in the classroom and how these ways of responding can (dis)empower students.

One way to answer this question is to understand how instructors frame their own teaching and their students’ learning. Frames are mental constructs which help individuals filter details, interpret information, …

Considerations And Techniques For Producing Urban Tree Canopy Maps Using Freely Available And Accessible Methods, Hugh Reed Ellerman

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Urban forests are valued as green infrastructure for the variety of benefits they provide across ecological, social, public health, and economic domains. To understand the distribution of trees, maps are required. Many methods of mapping tree cover use expensive and data-intensive datasets such as hyperspectral and LiDAR imagery, making these methods inaccessible to municipal forest managers. Variations in the modelling approaches of existing, freely available methods are not addressed in sufficient enough detail to understand the trade-offs implicit in these variations. Further, characteristics of urban tree canopy mapping (high spatial resolution imagery, heterogeneous urban environments, the importance of the tree …

Strengthening The Bonds Between Us: An Empirical Investigation Of Morale In Human-Ai Teams And The Socially Supportive Ai Teammates Who Empower It, Rohit Mallick

All Dissertations

This dissertation investigates how artificial intelligence (AI) can be designed to improve the collective emotion within a team. A team's collective emotion, or morale, describes how motivated, optimistic, and enthusiastic the group is in accomplishing its goals. We conducted four studies that compared different social support strategies that AI teammates can provide to the team. Study 1A found that AI teammates who communicate with emotions can better motivate human team members and promote awareness of team dynamics and environmental changes. Study 1B found that human teammates become more motivated and happier when their AI teammates express joy and are close …

Behind The Screen: Understanding The Human Firewall In Cybersecurity, Arun Venkitanarayanan

Emergency Preparedness, Homeland Security, and Cybersecurity

No abstract provided.

Towards Multimodal Empathetic Response Generation: A Rich Text-Speech-Vision Avatar-Based Benchmark, Han Zhang, Zixiang Meng, Meng Luo, Hong Han, Lizi Liao, Erik Cambria, Hao Fei

Research Collection School Of Computing and Information Systems

Empathetic Response Generation (ERG) is one of the key tasks of the affective computing area, which aims to produce emotionally nuanced and compassionate responses to user's queries. However, existing ERG research is predominantly confined to the singleton text modality, limiting its effectiveness since human emotions are inherently conveyed through multiple modalities. To combat this, we introduce an avatar-based Multimodal ERG (MERG) task, entailing rich text, speech, and facial vision information. We first present a large-scale high-quality benchmark dataset, AvaMERG, which extends traditional text ERG by incorporating authentic human speech audio and dynamic talking-face avatar videos, encompassing a diverse range of …

The Efficacy Of Incorporating Artificial Intelligence (Ai) Chatbots In Brief Gratitude And Self-Affirmation Interventions: Evidence From Two Exploratory Experiments, Jing Wen Hung, Andree Hartanto, Adalia Y.H. Goh, Zoey K.Y. Eun, K. T. A. Sandeeshwara Kasturiratna, Zhi Xuan Lee, Nadyanna M. Majeed

Research Collection School of Social Sciences

Numerous studies have demonstrated that positive psychology interventions, including brief interventions, can significantly improve well-being outcomes. These findings are particularly important given that many of these interventions are brief and self-administered, making them both accessible and scalable for large populations. However, the efficacy of positive psychology interventions is often constrained by small effect sizes. In light of advancements in generative Artificial Intelligence (AI), this study explored whether integrating AI chatbots into positive psychology interventions could enhance their efficacy compared to traditional self-administered approaches. Study 1 examined the efficacy of a gratitude intervention delivered through Snapchat's My AI, while Study 2 …

Hello Again! Llm-Powered Personalized Agent For Long-Term Dialogue, Hao Li, Chenghao Yang, An Zhang, Yang Deng, Xiang Wang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Open-domain dialogue systems have seen remarkable advancements with the development of large language models (LLMs). Nonetheless, most existing dialogue systems predominantly focus on brief single-session interactions, neglecting the real-world demands for long-term companionship and personalized interactions with chatbots. Crucial to addressing this real-world need are event summary and persona management, which enable reasoning for appropriate long-term dialogue responses. Recent progress in the human-like cognitive and reasoning capabilities of LLMs suggests that LLM-based agents could significantly enhance automated perception, decision-making, and problem-solving. In response to this potential, we introduce a model-agnostic framework, the Long-term Dialogue Agent (LD-Agent), which incorporates three independently …

Exploring The Biasing Effects Of Gender On Personality Disorder Diagnoses Formulated By Artificial Intelligence, Zoe Colclough

Student Theses

Gender bias is prevalent in personality disorder assessments, and while artificial intelligence has been posited as a solution to improve diagnostic objectivity and accuracy, the potential for such technologies to propagate human gender bias in mental health contexts remains underexplored. This study investigated the influences of gender bias on the diagnostic performance of ChatGPT-4o for personality disorders using three factorial research designs, which involved experimentally manipulating patient gender in a combined sample of 360 vignettes and case studies. Vignettes were synthesized through a novel artificial intelligence-assisted methodology established for this research, and case studies were identified from the literature. Significant …

Bridging The Gap: Enhancing Devops Security Through Comprehensive Threat Modeling, Ashutosh Jagdish Sonar

Theses and Dissertations

Today, security is an essential component of software development, especially in DevOps environments where rapid and continuous product release cycles are common. Systems are vulnerable to new attacks because traditional security approaches often cannot keep up with the pace of change. The threat modeling approaches used in DevOps are examined in this thesis, along with their advantages, disadvantages, and suitability for use in current software development processes. Well-known frameworks including STRIDE (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service (DoS), and Elevation of Privilege), Attack Trees, LINDDUN (Linking, Identifying, Non-Repudiation, Detecting, Data Disclosure, Unawareness, and Non-Compliance.), Practical Threat Analysis (PTA), …

A Survey Of Master's Qualifying Exam Practices And Content In Real Analysis, Zachary M. Coverstone

All Graduate Theses and Dissertations, Fall 2023 to Present

Graduate programs in mathematics are intended to develop experts in mathematics. As part of a graduate program, many students are expected to engage in a qualifying examination that can serve myriad purposes. This dissertation investigates real analysis qualifying examinations at the master's level through a nation-wide survey of institutions in the Association of Public and Land-Grant Universities (APLU). This study reveals the practices in administration of real analysis qualifying exams, institutions reported offering traditional, pencil-and-paper exams and generally asked students to prepare individually using previously administered exams. The survey results show that approximately two in three APLU institutions offering master's …

Climate Prediction As An Adaptive Force-Multiplier: Reasons For Hope In A Rapidly Changing World, Matthew D. Laplante

All Graduate Theses and Dissertations, Fall 2023 to Present

It's not unreasonable to feel pessimistic about our future under climate change. But "believing the science" doesn't require you to accept that we are headed toward apocalypse. It is true that human-caused climate change is real, it is underway, and our societies face many increased risks because of it. But that's just part of what climate science tells us about our future world. This same field is responsible for the recent and rapid development of tools and techniques that permit the identification of patterns in our oceans and atmosphere that will aid us in making increasingly accurate predictions about climate—the …