Digital Commons Network^™

Digital Beginnings: Exploring The Impact Of Screen Exposure On Internalizing Behaviors During Toddlerhood, Nicole Sotolongo

Electronic Theses and Dissertations 2020 - Present

The present study examines the relationship between screen exposure behaviors and toddler internalizing behaviors, with sleep behaviors being observed as a moderator. The study emphasizes the need for continued research to adapt to the ever-changing nature of the daily use of screens during toddlerhood and early childhood. Fifty-seven mothers of two-year-old children participated in one-on-one parent-report only, interviewer-based quantitative interviews discussing their child’s internalizing and sleep behaviors. Participants were also asked to fill out a questionnaire about their child’s screen exposure behaviors. It was hypothesized that (1) higher levels of screen exposure behaviors will result in increased internalizing behaviors, (2) …

Re: Conditional Approval Letter For The Final Butte Mine Waste Repository Geotechnical Investigation Work Plan (Dated November 14, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Single-Cell Transcriptomic Analysis Of Peripheral Blood Mononuclear Cells Reveals Key Immune Responses In St-Segment Elevation Myocardial Infarction, Zheng Zhang, Shengfang Wang, Yahui Liu, Gaohan Li, Qianqian Cheng, Wei Yang, Gan-Xin Yan, Chuanyu Gao

Department of Medicine Faculty Papers

BACKGROUND: Inflammation plays a crucial role in the pathogenesis of ST-segment elevation myocardial infarction (STEMI). However, the precise immunological mechanisms remain incompletely understood. Single-cell RNA sequencing (scRNA-seq) provides a powerful approach to dissect immune cell heterogeneity and dynamic changes at single-cell resolution.

METHODS: Peripheral blood mononuclear cells (PBMCs) were collected from 7 STEMI patients (within 6h after primary percutaneous coronary intervention) and 3 healthy controls. Single-cell suspensions were prepared and subjected to scRNA-seq using the 10x Genomics Chromium platform and Illumina NovaSeq 6000. Data were processed using Cell Ranger and analyzed with Seurat for quality control, clustering, and annotation. Differentially …

Hemorrhage-Related Maternal Morbidity Of Secondary Compared To Primary Postpartum Hemorrhage, Matthew R Carroll, Sarah Tounsi, Jessica L Gerard, Susan M Leong-Kee, Laurie S Swaim, Mark A Turrentine

Faculty, Staff and Students Publications

Objectives: To compare a composite hemorrhage-related maternal morbidity in individuals with secondary to primary postpartum hemorrhage and treatment interventions utilized.

Methods: A retrospective case-control study of deliveries complicated by secondary postpartum hemorrhage was performed at a tertiary care center. To estimate a clinically relevant increase of 50 % in the composite maternal hemorrhage-related maternal morbidity (35-53 % absolute increase) in individuals with secondary postpartum hemorrhage, a correlation coefficient of 0.2, at an 80 % power with a p < 0.05 with a two-sided test would require 95 individuals with secondary postpartum hemorrhage be matched to 95 individuals with a primary postpartum hemorrhage. Logistic regression analysis was used to evaluate the outcome of the composite of hemorrhage-related maternal morbidity.

Results: From January 2018 through December 2022, 33,026 deliveries occurred, and 94 individuals were identified that were admitted with secondary postpartum hemorrhage, …

Turning Patients' Open-Ended Narratives Of Chronic Pain Into Quantitative Measures: Natural Language Processing Study, Raquel Norel, Jennifer Gewandter, Zhengwu Zhang, Anika Tahsin, Chadi G Abdallah, John Markman, Zhiyao Duan, Guillermo Cecchi, Paul Geha

Faculty, Staff and Students Publications

Background: Subjective report of pain remains the gold standard for assessing symptoms in patients with chronic pain and their response to analgesics. This subjectivity underscores the importance of understanding patients' personal narratives, as they offer an accurate representation of the illness experience.

Objective: In this pilot study involving 20 patients with chronic low back pain (CLBP), we applied emerging tools from natural language processing (NLP) to derive quantitative measures that captured patients' pain narratives.

Methods: Patients' narratives were collected during recorded semistructured interviews in which they spoke about their lives in general and their experiences with CLBP. Given that NLP …

Deep Learning Reveals How Cells Pull, Buckle, And Navigate Fibrous Environments, Abinash Padhi, Arka Daw, Atharva Agashe, Medha Sawhney, Maahi M Talukder, Mehran M H Pour, Mohammad Jafari, Guy M Genin, Farid Alisafaei, Sohan Kale, Anuj Karpatne, Amrinder S Nain

2020-Current year OA Pubs

Cells in tissues navigate fibrous environments fundamentally differently than they do on flat substrates, but the establishment of cell forces in physiological fibrous settings remains poorly understood. Although factors such as the stiffness of the extracellular matrix (ECM) are known to drive behaviors, including cell motility on flat nonfibrous substrates, the interplay between fiber architecture and stiffness in fibrous ECM is not known. Here, we find that in fibrous environments, the directionality of mechanical forces overrides ECM stiffness as the primary regulator of contractility in migrating cells. Using an approach combining phase microscopy with deep learning to map forces in …

Cpx-351 Vs. Conventional Chemotherapy Cardiotoxicity In High-Risk Aml: A Post Hoc Phase Iii Trial Analysis, Joshua D Mitchell, Michael Pfeiffer, John Boehmer, John Gorcsan, Shunsuke Eguchi, Yoshiyuki Orihara, Nalina Dronamraju, Sonja Dhani, Stefan Faderl, Tara L Lin, Geoffrey L Uy, Jeffrey E Lancet, Jorge E Cortes

2020-Current year OA Pubs

BACKGROUND: CPX-351, a dual-drug liposomal encapsulation of daunorubicin and cytarabine in a synergistic 1:5 molar ratio, has demonstrated significantly improved overall survival in acute myeloid leukemia (AML) compared with 7 + 3, but its impact on cardiac function remains unclear. In a post hoc analysis of the pivotal clinical trial, we sought to determine the relative cardiotoxicity of CPX-351 vs. 7 + 3 in high-risk AML.

METHODS: We evaluated cardiotoxicity in 102 patients with AML (CPX-351, n = 57; 7 + 3, n = 45) who had normal baseline left ventricular ejection fraction (LVEF) ≥ 53% and at least one …

Changing Perspectives In California: A Transformative Culture Exchange For Stockholm University And Sonoma State University Criminology Students, Bryan Burton, Sofie Hellmer, Vida Wåhlmark, Hope Ortiz, Diana Grant

csuglobalaction

From June 13 to 20, 2024, Sonoma State University (SSU) hosted 16 criminology students from Stockholm University (SU) for an educational and cultural exchange. Five SSU undergraduate “student ambassadors” participated, representing California and SSU while assisting the Swedish students. Surveys indicated the exchange was a meaningful academic and cultural experience for all participants. The Swedish students deepened their understanding of the U.S. criminal justice system through presentations by criminologists and discussions with practitioners on issues such as policing and prison reform. They also gained broader perspectives on California and the United States through interactions with SSU ambassadors and visits to …

Grm-0267 Learned Heuristics For Efficient A* Search: Improving Pathfinding In Combinatorial Pathfinding Problems, Jamia Jackson

C-Day Computing Showcase

This work proposes a learned heuristic framework designed to improve planning efficiency in deterministic pathfinding tasks. Building on the classic 8-puzzle as an initial test domain, supervised models were trained to approximate heuristic values and guide node ordering during A* search. The proposed approach focuses on modifying and enhancing traditional heuristics such as Manhattan distance by incorporating learned corrections that reduce search depth and node expansions. Experimental results show that the learned heuristic consistently improves search efficiency over standard baselines. Although this evaluation began with the 8-puzzle, the framework establishes a foundation for scaling to significantly larger and more practical …

Grp-0197 Evaluating The Ability Of Llms To Interpret, Optimize And Translate Llvm Ir, Reuven Mueller

C-Day Computing Showcase

This study investigates whether modern state-of-the-art Large Language Models (LLMs) can interpret, optimize, and translate low-level intermediate representations (IR) used in compilers and binary translation software. We evaluate LLM performance on LLVM IR across three tasks: 1) interpreting the underlying algorithmic behavior, 2) identifying missed optimization opportunities, and generating improved IR variants, 3) Translating IR between AArch64 and x86-64 targets. To ensure correctness, all LLM generated IR is checked using a validation pipeline that verifies its syntax, structural correctness, compiles it into machine code, and executes it on randomized test data. Early results show that LLMs can perform non-trivial IR …

Ur-0227 Compilation Of Binary Neurons To Obdds, Aidan Boyce

C-Day Computing Showcase

A neuron with binary inputs & outputs corresponds to a Boolean function. To explain and verify the behavior a neuron (and by extension, a neural network), we can explain and verify its Boolean function. There has been recent interest in representing the Boolean function of such a neuron as an Ordered Binary Decision Diagram (OBDD), which facilitates such analyses. We propose an algorithm for compiling a binary neuron into an OBDD using a compiler that decomposes a Boolean function into a decision graph. We augment this compiler so that it outputs an OBDD instead. Our augmented compiler produces intermediate OBDDs …

Grp-0275 Graph Attention Network Based Downlink Channel Prediction Using In Frequency Division Duplexed Nextgen Networks, Jui Mhatre

C-Day Computing Showcase

In Frequency Division Duplex (FDD) 5G networks, downlink channel state information (CSI) must be estimated at the user equipment (UE) and fed back to the base station, a process that requires frequent CSI-RS transmission and uplink feedback, resulting in high overhead and energy consumption. This research proposes a novel base-station–centric framework that predicts the downlink channel matrix directly at the gNB, eliminating the need for continuous CSI-RS–based estimation at the UE. By leveraging uplink channel observations, geometric environment features, and learned mappings between uplink and downlink channel relationships, our model reconstructs the downlink MIMO channel with high fidelity. The system …

Grm-0237 Efficient Defense Against Adversarial Patch Attacks In Remote Sensing Using Transfer Learning, Ravi Rogannagari

C-Day Computing Showcase

Remote sensing is the science of acquiring information about the Earth's surface using satellite-mounted imaging sensors. In the past, this data had to be interpreted manually, which was slow, tedious, and often prone to error. With the rise of deep learning, image classification models have greatly accelerated and improved remote sensing tasks such as land-use analysis, environmental monitoring, etc. However, despite their strong performance, these models are still vulnerable to adversarial patch attacks—physically realizable patterns that, when placed on an object, can force the model to make incorrect predictions. This creates serious risks for practical geospatial applications. Traditional defenses like …

Gc-0157 Ai Graduate Admissions Assistant, Katherine Hyatt, Ginger Wright, Pablo Edgar, Oluwatosin Akinwusi, Alan Johnson

C-Day Computing Showcase

Project Overview: Create a "Proof of Concept" for an AI Graduate Admissions Assistant chatbot that will: • Autonomously reference KSU website information in real-time • Direct users efficiently to specific, relevant content • Reduce questions for admissions personnel • Self-update its knowledge base when website content changes •Provide accurate, instant responses to common admissions questions and allow for response correction in an admin dashboard

Gc-1146 Student Engagement Portal: Enhancing Student Success Through Milestone Tracking, Antonio Brewer, Taylor Bolinger, Tyler Dawkins, Ricartho Franck, Moises Valles

C-Day Computing Showcase

The Student Engagement Portal, also known as the Milestone Map, is a platform developed to help students within KSU’s College of Computing and Software Engineering monitor their academic and professional growth. The system enables students to log milestones, check in at events, and view progress toward personal and departmental goals. Built with a full-stack architecture using NestJS, React, and MongoDB, the portal also includes an administrative dashboard for event management and analytics. The project demonstrates how progress tracking and clear visualization of achievements can improve communication, organization, and engagement between students and the college.

Grm-1249 Ai-Assisted Diabetic Retinopathy Screening From Fundus Images, Mohan Krishna Thiriveedhi, Tarun Teja Pokala

C-Day Computing Showcase

Diabetic Retinopathy (DR) is a major cause of avoidable blindness among diabetic patients worldwide. Early screening is critical, but manual diagnosis is time-consuming and requires specialists. This paper presents a deep learning system to automatically analyze retinal fundus images and perform a focused, binary classification to distinguish between 'No DR' (Healthy) and 'Severe-Stage DR' (Severe/Proliferative). We benchmark three prominent architectures: a ResNet-50, an EfficientNet-B0, and a Vision Transformer (ViT-B/16). The models are trained and evaluated on a custom-balanced, binary dataset derived from the APTOS 2019 collection. We conduct two experiments, one with a small dataset (N=500) and one with a …

Uc-1244 Agentic Ai For Intelligent Customer Communication, Lucas Papadopoulos, Jeremy Hopkins, Munir Gargour, Weston Dease

C-Day Computing Showcase

E-commerce web shoppers need fast, reliable responses to a variety of requests: account modifications, order tracking, or policy inquiries. Businesses must address user queries in a fast and efficient manner, or else lose customers. Multi-agent AI models boast the ability to answer customer questions and act upon consumer queries without outside intervention. However, research is sparse as to how agentic models can transfer benefit to large commercial software stacks under realistic commercial load. We sought to ask whether a multi-agent AI architecture can effectively handle commercial-scale e-commerce customer service tasks. Moreover, we investigated how a multi-agent AI architecture compares to …

Uc-1175 Admissions Assistant - Ai Chatbot, Chelsea Oduro, Jeffery Bond, Tanner Morgan, Allen Scott, Joy Parks

C-Day Computing Showcase

The Kennesaw State University (KSU) Graduate Admissions website contains extensive information on programs, application processes, deadlines, and eligibility requirements. However, its dense structure can make it difficult for prospective students to quickly locate specific details. This often leads to repeated inquiries from admissions staff, increasing their workload and delaying responses to more complex applicant needs. This project addresses those challenges by introducing a chatbot capable of retrieving and presenting the website information in a more intuitive, conversational format, improving user satisfaction and reducing workflow overhead for admissions staff.

Uc-1232 Stronghold, Caitlin Tigani, Adam Tucker, Camden Lloyd, Dale Balsor

C-Day Computing Showcase

Our goal for this game is to create a game using both a single agent and multi agent AIs. In our game you can either play against the current AI or train the AI up as it fights against another AI. The training will use genetic AI. So whichever AI wins that row will be the one that move on. The loser will have their weights adjusted. This means the more that you train the Stronghold AI the harder the AI will be to fight against. The final game mode available is being able to play against another.

Uc-1234 Fundoria, Connor Stabler, Dameon Jones, Rafay Hassan, Michael Liu, Brenden Horne

C-Day Computing Showcase

Fundoria is an educational technology project designed to transform financial literacy and career readiness for elementary and middle-grade students. The platform combines interactive gameplay, AI-driven personalized learning, and real-world job simulations to teach essential financial concepts in an engaging, age-appropriate way. Students explore budgeting, saving, banking, and career skills through guided missions that adapt to their learning styles. Fundoria also provides teachers and schools with standards-aligned activities, classroom resources, and assessment tools that connect academic content to practical, everyday decisions. By blending gamification with evidence-based instruction, Fundoria empowers students to build confidence, develop responsible financial habits, and prepare for future …

Grm-1245 A Synthetic Data Engine For Explainable Injection-Area Perception, Yukang Shen

C-Day Computing Showcase

Vision-Language-Action (VLA) systems are beginning to support everyday clinical workflows. Deltoid intramuscular injection is a representative task, but progress is limited by data scarcity, privacy constraints, and the cost of expert annotation. Recent text-to-image (T2I) models make large-scale data synthesis possible, yet ensuring anatomical correctness, diversity, and label quality remains difficult. To address this gap, we propose a Synthetic Data Engine tailored for medical perception, integrating cold-start filtering, controlled T2I generation, CLIP-based quality checks, and iterative segmentation training. We further introduce an anthropometry-grounded formulation of injection safety that produces interpretable safe-zone guidance. Experiments show that synthetic data can effectively bootstrap …

Mobile Computer Vision Application For Agricultural Disease Detection Of Pepper Diseases Using Two-Stage Deep Learning System, Carlos Jose Estevez, Mai Dang, Ryan Bass

SMU Data Science Review

Plant diseases pose a significant threat to food security, particularly in developing countries where farmers often lack the resources and infrastructure for early detection. In nations like Mexico and the Dominican Republic, the spread of harmful plant diseases impacts key agricultural commodities, such as habanero peppers, leading to substantial yield losses. This study presents a computer vision system based on Convolutional Neural Networks (CNNs) and an object detection model (YOLO) to help farmers detect pepper diseases efficiently. The system uses a two-stage approach: YOLOv11n first detects pepper leaves in images, then a lightweight MobileNetV3Small model classifies whether the detected leaves …

Predictive Analytics In Public Health: Developing Ai Strategies To Combat High-Temperature Impacts On Violence And Overdoses In Las Vegas, David Camacho, Stephanie Duarte, Kosi Okeke, Chris Papesh, Jacquelyn Cheun-Jensen

SMU Data Science Review

Public violence and overdoses are key issues that Nevada agencies aim to address in the Las Vegas Metropolitan Area. A proven and effective strategy is via the implementation of a Cardiff Violence Prevention Model. This model provides a way for communities to gain a clearer picture about where violence is occurring by combining and mapping both hospital and police data on violence. In an effort to support this model, the exploration and implementation of AI models to predict the impacts of high temperatures on key public data and outcomes based upon historical data will be applied.

Ai-Powered Compliance: Accelerating Efficiency And Decision-Making For Compliance Related Inquiries., Amberly R. Rodriguez

SMU Data Science Review

This research examines the potential of an AI-powered chatbot to streamline compliance workflows by reducing the time and effort required to locate and interpret complex compliance documents. The prototype integrates a centralized MySQL-based document repository, a contextual document querying engine, and a Streamlit web interface, enabling employees to retrieve accurate, document-backed answers within seconds. The system supports both stored and user-uploaded documents, with features such as automated summarization and source citations to enhance transparency and trust. Manual evaluation demonstrated notable gains in efficiency and accuracy compared to traditional search methods, with strong potential to improve adherence to compliance policies. Future …

Analyzing The Global Happiness Index, Victoria Hernandez, Christy W. Wachira

SMU Data Science Review

This study explores the Global Happiness Index using data compiled from the OECD and Our World in Data to identify key factors contributing to societal well-being. Six primary predictors were analyzed: GDP per capita, social support, healthy life expectancy, freedom to make life choices, generosity, and perceptions of corruption. Regression and clustering techniques were employed to uncover patterns among countries. By expanding the analytical scope beyond conventional economic and social indicators, this study helps identify new pathways for improving well-being across diverse cultural and economic landscapes. Additional variables such as perceived safety, political engagement, and values related to family and …

Addressing Junk Science In Abortion Legislation, Kirby Tyrrell

University of Memphis Law Review

Junk science has been a longstanding feature of antiabortion legislative and litigation strategy. But after the Supreme Court’s opinion in Whole Woman’s Health required courts to independently evaluate scientific evidence, rather than defer to a legislature’s factual findings, antiabortion experts took on greater importance in litigation. This Article examines three theories of antiabortion junk science, which, despite overwhelming scientific evidence establishing their falsity, have been repeatedly litigated in federal and state courts. The current tool for addressing dubious evidence in litigation is the standard created by the Supreme Court in Daubert and adopted by Federal Rule of Evidence 702. However, …

Prison Rape: An Endless Epidemic?, Kathleen M. Darcy, Hannah Brenner Johnson

University of Memphis Law Review

Congress passed the landmark Prison Rape Elimination Act (“PREA”) in 2003 with unanimous support from both the Senate and House of Representatives. After the rampant sexual violence occurring behind the closed doors of prisons and jails (much of which was perpetrated by the staff of these institutions) was brought to light by human rights organizations, news media, lawyers, and activists in the late 1990s, lawmakers crafted this unprecedented federal law to establish a zero-tolerance policy for what it described as an “invisible epidemic.” At the law’s twenty-year mark, justice-involved individuals are still being sexually victimized in carceral settings, day after …

Truth Will Out: Combating The Rhetoric Of Modern Conspiracy Theory, Seth Kelley

Communication and Theater Association of Minnesota Journal

This essay explores modern conspiracy theories’ relationship to hatred and ignorance, and how specious ideas do not hold up to classical rhetorical analysis. It posits reasons why power embraces conspiracies that it has traditionally rejected and explains power and conspiracy theory’s symbiotic relationship in the age of misinformation. It champions rhetoric as the best tool to combat conspiracy theories.

Thesis: In order to effectively combat conspiracy theory’s undermining of human progress, we must hold conspiracists accountable for spreading dangerous lies, directly teach formal rhetoric in all public schools (and how to spot specious content), effectively foster multicultural respect and appreciation, …

Volume 48, 2025 Communication And Theater Association Of Minnesota Journal

Communication and Theater Association of Minnesota Journal

Complete digitized volume (volume 48) of Communication and Theater Association of Minnesota Journal.

W(H)Ither Regulation? Hither To The Tax System, Tracey M. Roberts

Pace Environmental Law Review

In a series of cases decided in the last three years, four delivered in 2024 alone, the U.S. Supreme Court has directed a withering gaze toward the federal administrative state. In West Virginia v. EPA, the Court both curtailed Executive Branch regulatory authority and mandated that Congress draft with greater statutory clarity and specificity under their recently developed major questions doctrine. Under Ohio v. EPA, the Court placed on administrative agencies the burden of extraordinary vigilance in addressing comments as part of the regulatory promulgation process. In Loper Bright v. Raimondo, the Court overturned Natural Resource Defense Council v. Chevron, …