Digital Commons Network^™

Belowground Biomass Shifts Along A Temperate Forest Edge, Lara Holbrook Roelofs

Dartmouth College Undergraduate Theses

Anthropogenic land use change and development has caused widespread global forest fragmentation, resulting in a greater proportion of forests at or near a forest edge. Temperate forests are the most fragmented forest biome, and forests in the Northeastern U.S. are particularly fragmented due to a history of intense land use and development pressure. Nearly a quarter of these forests are now within 30 meters of a forest edge. These edge ecosystems have distinct abiotic and biotic gradients that differentiate them from forest interiors, including increased light, temperature, and exposure to wind and other disturbances, as well as decreases in humidity …

Design Principles For Robotic-Controlled 3d Printing Of Soft Tissue-Mimicking Materials, Karina Mealey

Master's Theses

Geometrically and physically accurate 3D models are emerging as essential tools for surgeons in pre-operative planning and training, but current methods of producing these models are not sufficient. Existing solutions have downsides such as high costs, long and tedious production times, high complexity resulting in a lack of scalability, or an inability to meet material requirements for accurately simulating human tissue.

The objective of this work is to develop principles for a low-cost, easy-to-use 3D printing system capable of prototyping with soft tissue-mimicking materials. To pursue this goal, a MyCobot280 robot arm was used as the mechanism to explore the …

The Application Of Lidar For Classifying Wildland Fuels, Madison Muschetto

Master's Theses

Accurate vegetation classification is critical for modeling wildfire behavior, particularly in fire-prone ecosystems where fuel type influences fire spread and intensity. This study evaluates the effectiveness of UAV-based aerial LiDAR, supplemented by multispectral imagery, for classifying grass, shrub, and tree vegetation types across a grass-dominated landscape. Using canopy height thresholds, vertical profile analysis, LiDAR predictions were compared against field-verified vegetation observations at 80 survey points. Results showed that LiDAR classified grass with high accuracy but was less reliable for detecting shrubs and trees, especially under canopy cover. Misclassifications were most common beneath tree canopies and in areas where low-stature shrubs …

Machine-Checked Proofs For Correctness Guarantees In Containment Architectures, Sophie Russ

Master's Theses

Modern computing systems are increasingly susceptible to attacks at the hardware and software levels. Formal methods offer promising guarantees as to the correctness and security of systems. However, these methods tend to scale poorly and are thus insufficient to protect complex systems. Leveraging minimal amounts of trusted hardware and software to ensure the security of whole systems is a promising approach to gain the benefits of formal methods without having to overcome the scaling problem. TrustGuard realizes this approach: a containment architecture model that requires all outgoing communication from the host computer to be validated by a small, external hardware …

Topodino: Self-Supervised Topological Representation Learning For Neuronal Morphologies, Yasser Binbisher

Master's Theses

Neuronal cell types are categorized by transcriptomic identity, yet their morphological heterogeneity defies this classification. In response, researchers have adopted unsupervised graph representation learning as a tool to reveal morphological variation within single-class transcriptomic types. However, the complex geometry of neuronal morphology—especially long axons and dense dendrites—challenges graph neural networks, which struggle with message propagation across extended structures. To mitigate this, current approaches enforce sub-sampling on neuronal graphs and omit axons entirely, sacrificing critical biological features for computational efficiency. To overcome this trade-off, this thesis introduces TopoDINO, a self-supervised, topology-aware representation learning model designed to preserve the full hierarchical organization …

Exploiting Compiler-Introduced Vulnerabilities In C: A Cross-Compiler And Cross-Architecture Analysis Of Undefined Behavior, Erik Mccutchen

Master's Theses

Compilers are a critical component in generating secure software across engineering disciplines. However, languages like C that permit undefined behavior introduce a fundamental tension between the compiler’s interpretation of undefined behavior and the security of the generated code. This tension can result in security vulnerabilities that, from the programmer's perspective, are ``created'' by the compiler. The widespread use of these languages, combined with the complexity of modern optimizations and limited developer visibility into compiler behavior, makes these vulnerabilities both pervasive and difficult to detect.

Building on prior work, this thesis refines a dataset of C code snippets that exhibit Compiler-Introduced …

"The Effect Of Methylobacterium Symbioticum On The Growth And Yield Of Dent Corn And Romaine Lettuce", Sinead Carney

Master's Theses

Nitrogen (N) is an essential nutrient for plant growth and is often a limiting nutrient in cropping systems. An estimated half of applied N fertilizers are lost from cropping systems by processes that can be environmentally destructive, such as leaching and volatilization, and cause economic loss for growers. Effective N biofertilizers offer a means to mitigate the need for high inputs of synthetic N. The objectives of this study were to determine the effects of leaf inoculation with the N-fixing bacteria, Methylobacterium symbioticum, in combination with different rates of urea-N fertilizer on the physiology and yield of dent corn …

Design, Analysis, And Implementation Of An Improved Zero Voltage Switching Hybrid Voltage Divider, Luke V. Cerda

Master's Theses

This thesis entails the study, design, and construction of a novel DC-DC converter topology, the Zero Voltage Switching Hybrid Voltage Divider (ZVS-HVD), with improved modularization, optimization, and compactness. The ZVS-HVD facilitates higher load currents and accomplishes DC-DC voltage division through switching inductors and capacitors. Low switching loss is achieved through zero voltage switching (ZVS) and the use of GANFET switches. An analysis of duty cycle and high-frequency operation is conducted, enabling 1 MHz switching and improvements in output voltage ripple, voltage drooping, board size, and efficiency at higher load currents. Two versions of ZVS-HVD prototypes were constructed with on-board signal …

Frequent Itemset Mining With Tidyclust In R, Andrew D. Kerr

Master's Theses

Unsupervised learning is closely associated with clustering, however other methods fall under this umbrella such as data mining. In R, the tidyclust package provides a unified interface for clustering models, yet lacks support for data mining. This thesis addresses this gap by introducing the Apriori and ECLAT algorithms into tidyclust, with a focus on frequent itemset mining. Unlike traditional clustering models, frequent itemsets produce groupings of column variables, rather than cluster labels or partitions of observations. To address this, a novel clustering approach is proposed: items (columns) are grouped based on their ”dominant” frequent itemset. A key contribution is a …

New Methods Of Capturing Students’ Experiences With Primary Source Projects: Pioneering A Transgressive Lens, Mark Watford, Kathleen Michelle Clark, Cihan Can

The Mathematics Enthusiast

The mathematics education research landscape possesses limited examples of large-scale research regarding students’ experience with primary historical sources in the learning of mathematics at the undergraduate level. However, the field continues to investigate methods of determining how students might overcome obstacles to reach new outcomes. This article documents an exploration within the TRansforming Instruction in Undergraduate Mathematics via Primary Historical Sources (TRIUMPHS) project that combined transgressions theory and situated learning theory, thereby illuminating three components of the former—boundaries, transgressive actions, and outcomes. In this regard, we capture students’ Primary Source Project (PSP) learning experiences in Abstract Algebra courses and bring …

Chatgpt Or Human Mentors? Student Perceptions Of Technology Acceptance And Use And The Future Of Mentorship In Higher Education, Jimin Lee, Alena G. Esposito

Psychology

GAI technologies are increasingly recognized as mentor-like resources in higher education. While these tools offer academic guidance and personalized feedback, little is known about how students perceive and evaluate AI-generated mentorship. This study investigated how Prior ChatGPT Use, primary mentor identity, mentorship effectiveness, and technology acceptance predict students’ response identification and evaluations of AI- versus human-generated responses. College students (N = 127) completed a survey in which they identified the source of masked responses across different domains and rated each response on helpfulness, caring, and likelihood to reach out again. Binary logistic regression models revealed that Prior ChatGPT Use predicted …

The Guardian The Month Of June 2025, Wright State Student Body

The Guardian Student Newspaper

News articles from The Guardian for the Month of June 2025. The Guardian is the official student-run newspaper for Wright State University. It has been published regularly since March of 1965.

Identification Of Genetic Variants In Patients With Primary And Secondary Amenorrhea, Flora Bai, Renjini Nambiar, Chirayu Padhiar, Wilson Aruni, Chinnadurai Veeramani, Mohammed A. Alsaif, Khalid S. Al-Numair

Saudi Medical Journal

ABSTRACT Objectives: To identify the cytogenetic and molecular pattern abnormalities and early diagnose the cause of primary and secondary amenorrhea. Methods: A total of 320 patients in the age group of 14-35 years with clinically confirmed amenorrhea were screened using conventional cytogenetic methods. Patients with a normal karyotype, hypoplastic uterus, and no hormonal imbalance were extensively investigated using molecular cytogenetic platforms such as chromosomal microarrays and clinical exome sequencing (CES). Results: Of the 266 patients with primary amenorrhea and 54 with secondary amenorrhea, 66.9% and 88.9%, independently, had a normal karyotype. The 20 patients with a normal karyotype, hypoplastic uterus, …

Enhancing Energy Consumption Forecasting For Electric Vehicle Charging Stations With Time Series Dense Encoder (Tide), Amril Nazir, Abdul Khalique Shaikh, Aftab Ahmed Khan, Abdul Salam Shah, Nadia Khalique

All Works

The increasing adoption of electric vehicles has led to the installation of charging stations in various locations in major cities worldwide. This study focuses on energy consumption forecasting for Boulder, Nevada, United States electric vehicle charging stations. Efficient management of energy resources at these charging points is crucial for optimizing resource utilization and reducing charging time. While existing literature has focused on energy consumption prediction in smart homes and grids, the significance of electric charging points in smart cities must be considered. The transformers have handled time series forecasting better with larger datasets like the Temporal Fusion Transformer and the …

Evaluating Artificial Intelligence Chatbots For Patient Education In Oral And Maxillofacial Radiology, Dilek Helvacioglu-Yigit, Husniye Demirturk, Kamran Ali, Dania Tamimi, Lisa J. Koenig, Abeer Almashraqi

School of Dentistry Faculty Research and Publications

Objective

This study aimed to compare the quality and readability of the responses generated by 3 publicly available artificial intelligence (AI) chatbots in answering frequently asked questions (FAQs) related to Oral and Maxillofacial Radiology (OMR) to assess their suitability for patient education.

Study Design

Fifteen OMR-related questions were selected from professional patient information websites. These questions were posed to ChatGPT-3.5 by OpenAI, Gemini 1.5 Pro by Google, and Copilot by Microsoft to generate responses. Three board-certified OMR specialists evaluated the responses regarding scientific adequacy, ease of understanding, and overall reader satisfaction. Readability was assessed using the Flesch-Kincaid Grade Level (FKGL) …

Irnet: Immunotherapy Response Prediction Using Pathway Knowledge-Informed Graph Neural Network, Yuexu Jiang, Manish Sridhar Immadia, Duolin Wang, Shuai Zeng, Yen On Chan, Jing Zhou, Dong Xu, Trupti Joshi

Biomedical Sciences

Introduction: Immune checkpoint inhibitors (ICIs) are potent and precise therapies for various cancer types, significantly improving survival rates in patients who respond positively to them. However, only a minority of patients benefit from ICI treatments.

Objectives: Identifying ICI responders before treatment could greatly conserve medical resources, minimize potential drug side effects, and expedite the search for alternative therapies. Our goal is to introduce a novel deep-learning method to predict ICI treatment responses in cancer patients.

Methods: The proposed deep-learning framework leverages graph neural network and biological pathway knowledge. We trained and tested our method using ICI-treated patients’ data from several …

Developing Machine Learning Models And Graphene-Based Flexible Humidity And Temperature Sensors For Machine-Learning-Assisted Sensing, Seth Hajian

Dissertations

Flexible sensor technology has recently gained tremendous momentum in both academic research and industrial applications, transitioning from conceptual frameworks to practical implementations across diverse fields. This remarkable advancement can be attributed to several converging factors, including the maturation of nanomaterial science, the advancements of machine learning algorithms, and the critical demand for intelligent sensing solutions in healthcare, environmental monitoring, and industrial automation. The growing emphasis on personalized medicine and real-time health monitoring, accelerated by global health challenges, has further highlighted the necessity for accurate, cost-effective, and adaptable sensing platforms. This dissertation presents the fulfillment of three interconnected research projects focused …

A Parallel Fuzzy Logic Framework For Surgical Skill Evaluation Via Instance Segmentation And Deepsort Tracking, Mohsen M. Mohaidat

Dissertations

Manual evaluation of suturing skills during laparoscopic training is often subjective and labor-intensive, resulting in the lack of scalable and consistent feedback for trainees. This study proposes an automated framework that not only significantly reduces the need for in-person assessment by experts but also ensures scalability, thereby addressing the objectivity and cost-effectiveness limitations. While low-cost laparoscopic box trainers have become increasingly popular for residency training, performance assessment still depends on expert supervision. The proposed system aims to alleviate these limitations.

This study introduces a novel automated framework incorporating an optimized DeepSORT algorithm for classifying, localizing, and tracking surgical tools using …

Statewide Universal School Meal Policies And Food Insecurity In Households With Children, Dania Orta-Aleman, Marlene B. Schwartz, Anisha I. Patel, Michele Polacsek, Christina A. Hecht, Kenneth Hecht, Monica D. Zuercher, Lorrene D. Ritchie, Juliana F W Cohen, Wendi Gosliner

Health Sciences Faculty Publications

No abstract provided.

Whose Bot Is It Anyway? Determining Liability For Ai-Generated Content, John G. Browning

Northern Illinois University Law Review

As Chief Justice John Roberts noted in his State of the Judiciary address in late December 2023, artificial intelligence has not only had a seismic effect on society and the legal profession, but it is also presenting courts with novel questions to resolve. To date, most of the legal scholarship discussing generative AI has focused on areas like the ethical dimensions of its use, copyright infringement implications, AI governance issues, and the evidentiary questions raised by the use of this technology. However, a void in the scholarship exists with respect to the question of who should be liable for AI-generated …

Avoiding Dupe Process, Kevin Frazier

Northern Illinois University Law Review

Advances in artificial intelligence (AI) combined with increased documentation of human overreliance on AI recommendations demands a reexamination of content moderation processes. Social media platforms—reacting to internal values, social pressure, regulatory mandates, or some combination of all three—have carried over procedural due process norms to content decisions. One common procedural protection is a “human-in-the-loop” (HITL) requirement. These requirements insist that a human provide some oversight role prior to an automated decision becoming final.

A review of the core values of due process—namely, accuracy, fairness, legitimacy—and the nature of hybrid decisional frameworks—those that involve AI and human inputs—show that HITL requirements …

Lindenwood Magazine, Spring 2025, Lindenwood University

Lindenwood Magazine (2017- )

Lindenwood University news magazine.

High School Student Reflections Of In-School Suspension: A Mixed Methods Study, Daniel L. Booth

Ed.D. Capstone Reports

In response to Illinois Senate Bill 100, secondary schools have increasingly relied on in-school suspension (ISS) as a disciplinary measure for addressing major behavioral infractions. As a result, ISS has evolved into a long-term holding environment for students who repeatedly engage in misconduct. This study aimed to explore the experiences of high school students who were assigned ISS multiple times during the 2023-24 academic year. Specifically, it examined students’ perceptions of their high school environment through the lens of repeated ISS assignment. The findings offer insights into how the ISS setting can be restructured to better support students and reduce …

The Fault Line: Understanding Tension Between Industry And Higher Education Institutions In Sustained Partnerships, David Lawrence

Dissertations

This study investigates the dynamics that influence tensions in industry–higher education partnerships and identifies effective navigation factors in sustainable partnerships. Despite the increasing prevalence, such partnerships face high failure rates due to inherent tensions. This research explores how partners from industry and higher education institutions successfully navigate these tensions using a qualitative case study approach.

This investigation employed a case study design with a multi-case two-by-two holistic matrix and an interpretive, constructivist framework. Data collection involved 16 semi-structured interviews with key individuals from nine higher education institutions and five industry organizations spanning healthcare, technology, consulting, real estate development, and accounting …

Blood And Mettle: The Effects Of Civil Unrest On Economic Mobility, Nathan D. Parks

Honors Projects

Civil unrest is a global phenomenon that often emerges through a combination of grievances and opportunity sparking change. Civil unrest is often used as a tool by the populace to initiate political, societal, or economic transformation. Economic mobility or the belief in it is a key contributor to mitigating individuals’ level of grievances. This paper uses lagged panel analysis to investigate the question of how civil unrest affects economic mobility beyond the time of unrest. Civil unrest is associated with changes in economic mobility, varying between positive and negative associations based on the type of unrest. Analysis was conducted using …

Floating Wind Turbine Foundation, Clayton Lahodny, Dillon Nelson, Trevor Ortega, Andrew Cervantes

Mechanical Engineering

The 2024 Collegiate Wind Competition (CWC) has introduced a new element to their Turbine Design Competition: a floating foundation. In previous years, foundations have been fixed-bottom in a box of sand and water. The Cal Poly Wind Power Club, who competes in the CWC every year, requires a floating foundation to be designed, manufactured, and tested to assist in winning the competition. The foundation is a large, hollow, cylindrical barge with a hanging spar (heavy mass). The barge will provide a restoring moment using buoyancy, and the heavy spar provides additional restoring moment. Four cables will be attached at the …

Hydropower Collegiate Competition, Aiden D. Foster, Devon Bountry, Joanna Vo, Timothy Rinker, Amanda Rodriguez, Minh Nguyen, Eli Haushalter, Sophie Watkinson, Maiya Holton, Breanne Evans

Mechanical Engineering

The Cal Poly SLO HCC team presents a feasibility study and engineering design review package for retrofitting the non-powered Ritschard Dam in Colorado into a hydroelectric facility as part of the 2025 Hydropower Collegiate Competition. Through a rigorous and multi-staged assessment of plausible dam sites in the western US, the team has chosen the Ritschard Dam in Colorado to implement an electromechanical component designed to accommodate a large range of flowrates stemming from a large variance in upper reservoir capacity due to geographical and climate effects. The team evaluated non-powered dams based on technical feasibility, electric grid proximity, power generation …

Farmnav-Uav: A Field-Ready Autonomous Uav For Tracking Static And Dynamic Trajectories In Agricultural Applications, Veera Venkata Ram Murali Krishna Rao Muvva

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

This study presents the design and development of a custom-built uncrewed aerial vehicle (UAV) tailored for precision agriculture. Unlike commercial UAVs, which are often constrained by proprietary systems and limited hardware customization, the proposed platform emphasizes modularity, upgradeability, and cost-effectiveness. The UAV is equipped with a Cube Blue flight controller for reliable low-level actuation and a Raspberry Pi 4 companion computer that executes a Model Predictive Control (MPC) algorithm for high-level trajectory optimization and stability enhancement.

Most conventional UAV autopilot systems rely on non-optimal control strategies, such as proportional–integral–derivative (PID) controllers, which can be inadequate for dynamic or resource-constrained environments. …

Vestibulo-Ocular Reflex Function In Individuals With Chronic Motion Sensitivity, Oluwaseun Ibitunde Ambode

Loma Linda University Electronic Theses, Dissertations & Projects

Objective: The purpose of this study was to 1) determine whether Vestibulo-ocular reflex (VOR) integrity is different between young adults with and without chronic motion sensitivity (CMS), 2) assess correlation between VOR integrity and postural stability in young adults with and without CMS; and 3) Compare postural stability across different levels of physical activity in young adults with and without CMS.

Design: A Cross-sectional study design.

Methods: Forty healthy young adult men and women (age, 20-40 years) were stratified into CMS and Non-CMS groups, VOR integrity was assessed using Bertec Vision Advantage (BVA), postural stability was assessed …

The Role Of Swarm Intelligence Systems In Shaping Urban Development Policies, Sudaff Mohammed, Wahda Shuker Al-Hinkawi, Nada Abdulmueen Hasan

Iraqi Journal of Architecture and Planning

Swarm intelligence is a nature-inspired complex system that draws from the behaviours of social creatures such as ants and birds. This system functions through simple behavioural rules enacted by autonomous, intelligent agents. Existing literature indicates that swarm intelligence possesses a wide range of principles and characteristics derived from the theories of Biomimicry, complex adaptive systems, and parametric and generative design. While the previous studies have intensively addressed the computational aspects of intelligence, a comprehensive conceptual framework is essential for analysing complex urban forms and structures. Therefore, this research develops and applies a conceptual model of swarm intelligence by examining several …