Digital Commons Network^™

Open Space Management Planning: A Framework And Case Study From Eagle Mountain City, Utah, Nathan K. Shumway

All Graduate Reports and Creative Projects, Fall 2023 to Present

Open Space Management Plans (OSMPs) are increasingly used by municipalities to guide the long-term stewardship of natural lands; however, little formal guidance exists regarding how these plans are structured, developed, or organized in practice. While numerous OSMPs are publicly available, their compositional logic, procedural workflows, and thematic priorities remain largely undocumented within academic literature. This study addresses that gap through a qualitative document analysis of fifteen publicly accessible OSMPs from the western United States, published between 2015 and 2024.

Using manual matrix-based coding in Microsoft Excel, each plan was analyzed through three lenses: structural composition, procedural development, and thematic content. …

The Cobalt Curse: Cobalt’S Role And Risks, Marley Jackowitz

Student Theses 2015-Present

This paper examines the hidden environmental, geopolitical, economic, and social costs of the cobalt supply chain. Fueled by the demand for battery technology and electric vehicles, cobalt has become an essential element to the green energy transition. With the largest share of global cobalt deposits, the Democratic Republic of the Congo bears a disproportionate share of the industry’s harms. Cobalt mining in the DRC is marked by environmentally degrading practices and inhumane working conditions, compromising Congolese health, safety, and well-being. Chapter 1 discusses the environmental impacts of DRC cobalt mining and its adverse effects on public health. Environmentally degrading mining …

A Forecasting Framework For Distribution Center Capacity Utilization: An Applied Industry Study, Jordan J. Shortt

Data Science Undergraduate Honors Theses

This project develops and evaluates a predictive modeling framework for forecasting distribution center capacity utilization at Company Y, with monthly forecast horizons up to one year. Motivated by the operational challenges of seasonal demand volatility, promotional cycles, and the absence of a formally defined capacity metric, the study first constructs a historical capacity utilization measure from raw warehouse management system data — reconciling item volumes, location dimensions, and utilization factors across all DCs — which serves as the target variable for all modeling work. Four models are developed and evaluated against a naïve seasonal baseline: SARIMA, LightGBM, LSTM, and a …

Recursion, Regurgitation, And Regeneration: Testing Limits And Revealing Biases Of Generative Ai Models Through Multimodal Feedback Loops, William Donnell-Lonon

Data Science Undergraduate Honors Theses

Contemporary generative AI systems such as OpenAI's GPT-4o and DALL-E models embed complex priors about society, reality, and history shaped by training data distributions, social alignment procedures, legal constraints, and safety regulations. This study uses a "telephone game" methodology to investigate how embedded social, political, and visual biases propagate and reveal themselves through iterative multimodal generation loops, where image captioning and text-to-image models are chained in successive feedback cycles.

Using CLIP similarity metrics, facial recognition algorithms, semantic drift analysis, and qualitative content observations, I tested how image subject matter affects the rate and quality of semantic and visual shift, identity …

Volume 17, Christian O’Neill, Kyara Greene, Savva Sidorov, Laura Bisaillon, Luke Clemmer, Hannah Gordon, Kitt Benson, Taylor Blount, Rachel Danzitz, Nicholas Duellman, Chase Gionis, Hima Fernando, Seth Franzyshen, Onyx Gonzalez, Bryan Lin, Samantha Start, Ysabel Wells, Maggie Duncan

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Amorette Barber, Director, Office of Student Research

From the Editor Dr. Hannah Dudley-Shotwell

Cover Artist’s Statement Maggie Duncan

On Mentoring Dr. Yulia Uryadova

Ukrainian Resistance in the Face of Russification: Nestor Makhno and Anarchism

by Christian O’Neill

Life Vest by Kyara Greene

Isolation and 16S rRNA Identification of Bacteria from Fire Department Connection Pipe by Savva Sidorov

The Effectiveness of Planned Exercise in Reducing ADHD Symptoms in Children by Laura Bisaillon & Luke Clemmer

Linguistic Analysis on Confidence and Communication Strategies with Disparities Between Sign Fluency and Hearing Impairment by Hannah Gordon

Freedmen in Indian Territory by Kitt …

Cyanine Dyes As Next-Generation Fluorophores: Applications In Cell Sorting And Fingerprinting Technologies, Super-Multiplexed Spectroscopy, Biomedical Imaging, And Beyond, Lucas Allen Davis

Undergraduate Honors Thesis Collection

As biochemical, pharmaceutical, and medical sciences advance, the demand for technologies capable of probing multiple cellular targets simultaneously continues to increase. Super-multiplexed spectroscopic techniques offer a pathway toward comprehensive cellular fingerprinting by overcoming the spectral limitations of conventional fluorescence labeling. By circumventing the traditional “color barrier,” cyanine-based Raman tags enable the simultaneous discrimination of numerous cellular morphologies, allowing spectroscopy and imaging to be integrated for high-dimensional cellular analysis. Technologies developed in Goda Lab—including high-throughput flow cytometry, virtual freezing fluorescence imaging (VIFFI), Fourier-transform coherent anti-Stokes Raman spectroscopy (FT-CARS), and MERdot nanoparticles—address longstanding trade-offs between throughput, resolution, sensitivity, and multiplexing capacity. Central …

Urban Heat Mitigation In Newark, New Jersey Using Remote Sensing And Spatial Analysis, Ama Akowa Rhule

Theses, Dissertations and Culminating Projects

This study examines urban heat patterns in Newark, New Jersey, using remote sensing and spatial analytics to support targeted mitigation strategies. Land Surface Temperature (LST) was derived from a Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) scene acquired on July 28, 2025, representing a summer snapshot of surface thermal conditions. While urban heat island effects are typically considered long-term climatic phenomena, this study uses a single-date observation to capture spatial variability in temperature across the city. Land cover variables, including tree canopy and impervious surface fractions, were obtained from the National Land Cover Database (NLCD), and demographic variables, including …

Mineralogy, Geology, And Geochemistry Of The Mcafee Quarries And Greater Mcafee Area, Sussex County, New Jersey, Cristian J. Van Rossen

Theses, Dissertations and Culminating Projects

The Franklin Marble is one of North America’s most famous geologic units, a result of its complex geology, diverse mineralogy, and significant ore deposits. While it has been widely studied, a location that has received little attention is that of the quarries at McAfee, Vernon Township, NJ. This study addresses this oversight by investigating the mineralogy, geology, and geochemistry of the marble and associated geologic units found in the area. Sample analysis consisted of physical and optical analysis as well as chemical analysis using SEM-EDS. Geochemical analysis using ICP-MS allowed for major, trace, and rare earth element concentrations of select …

Implementation Of A Droplet Interface Lipid Bilayer System For Electrical Characterization, Olivia J. Ziemer

Honors Theses

Lipid bilayers are the fundamental structural framework of cell membranes, providing cells with both protection from the environment and interaction with the surrounding environment. Experimental investigation of lipid bilayers and embedded protein channels often involves the formation of an artificial membrane within an electrical circuit. The focus of this project is to implement and verify the functionality of a lipid bilayer characterization technique known as the droplet interface bilayer (DIB), with emphasis on cost-effective system design. To achieve this, the amplifier and software from the ELEMENTS black lipid membrane (BLM) kit were repurposed to reduce the cost of implementing a …

Bottles, Butterflies, And Biomass: Recycled Glass Sand, Microbial Additions, And Herbivory Effects On Milkweed Growth, Kealey Skinner

Honors Theses

Plant-soil-microbe interactions are integral components of ecological networks and drive ecosystem function from the bottom-up. Whereas herbivores regulate ecosystem function from the top-down, having opposing and potentially complementary effects on ecosystem function. My thesis sought to understand how below-ground microbial communities contribute to herbivore preference and plant biomass across varied soil substrates. My thesis asked: how do substrate and soil microbial communities influence herbivore preference and plant biomass accumulation on swamp milkweed (Asclepias incarnata)? To address this question, seedlings of A. incarnata were sown in 2.5 cm wide × 10 cm deep pots filled with either natural beach sand or …

Assessing Geomorphic Change From Large Wood Additions In An Intensively Monitored Watershed, Alexander Walt

All Graduate Theses and Dissertations, Fall 2023 to Present

Rivers across the American West are under stress. Over time, human activities have decreased riparian vegetation and removed naturally occurring large wood from fallen trees and beaver dams. Overgrazing, wetland drainage, and artificial barriers like levees and berms have further changed these ecosystems, leaving behind simple channels that lack varied habitat for aquatic species.

Efforts to restore rivers have made some progress, but many projects are small in scale and focus more on reshaping the river rather than restoring the natural processes that keep it healthy. This study evaluates a different approach—Low-Tech Process-Based Restoration (LTPBR)—which works with nature to rebuild …

From Data Digitization To Personalized Care: Deep Learning And Decision Analytics In Healthcare Systems, Ahla Ko

Graduate Theses and Dissertations

This dissertation traces a progression from foundational data infrastructure to individualized clinical decision-making, developing and evaluating three computational frameworks that advance healthcare efficiency and personalization through deep learning and decision analytics. The first study presents an end-to-end pipeline for automated recognition of handwritten medical forms, addressing persistent challenges in health data digitization. Integrating a YOLO-based field detection model, a Convolutional Recurrent Neural Network (CRNN) for text transcription, and a confidence-based human-in-the-loop quality assurance framework, the system achieved 99.75\% Exact Match Accuracy and a 0.13\% Character Error Rate on medical forms collected from a tuberculosis research project in Moldova. A GPU-accelerated …

Collective Dissipative Charging And Energy Extraction In Quantum Batteries, Sagar Pokhrel

Graduate Theses and Dissertations

In this dissertation, we investigate the charging and discharging dynamics of a quantum battery composed of a collectively driven ensemble of $N$ identical two level systems coupled to a structured electromagnetic environment. The system is described using collective angular momentum operators in the Dicke basis, which provides a compact and physically transparent framework for analyzing collective light-matter interactions. Rather than treating dissipation as an unwanted source of loss, we explicitly use it as a mechanism for energy storage and work extraction. Starting from a coherently driven ensemble coupled to common reservoirs, we derive a master equation in Lindblad form under …

Teaching Machines To Deter: Exploring Strategic Deterrence In Ai Models, Will Taylor

Theses/Capstones/Creative Projects

This capstone project investigates whether deterrence can emerge as a meaningful strategy within a zero-sum stochastic game using multi-agent reinforcement learning (MARL). After outlining core concepts in game theory and deterrence, the study models a simplified deterrence environment in which two minimax-Q agents repeatedly interact under uncertainty and adversarial incentives. The agents learn from rewards shaped by escalation costs, unilateral vulnerability, and the stabilizing benefits of restraint. Results show that both agents consistently converge toward a conservative, status-quo strategy, overwhelmingly selecting the Maintain action while avoiding both escalation and restraint in most scenarios. This behavior reflects the risk-averse logic of …

Improving Online Political Discussion With Automated Bot Intervention, Bethanie E. Hackett

Departmental Honors & Graduate Capstone Projects

The quality of political discussions occurring on online platforms or social media sites has been deemed quite poor. To address this issue, I investigated whether a Large Language Model (LLM) can be used to promote civil and productive political discussions by identifying and responding to unproductive dialogue. I fine-tuned an existing LLM to detect elements of problematic dialogue, namely misinformation, misrepresentation of sources, logical fallacies, bias, and toxic language, and then respond in a corrective yet non-confrontational manner. The resulting model is referred to as FroBot and was evaluated through an experiment in which a human participant was placed in …

Leveraging The Iron Oxide Archive Of Mineralization, Deformation, And Exhumation Across Geologic Time, Jordan L. Jensen

All Graduate Theses and Dissertations, Fall 2023 to Present

The iron oxide mineral hematite commonly forms from groundwater near Earth’s surface and can preserve a history of fluid flow, fault slip, and landscape evolution. This record can be decoded using (U-Th)/He thermochronology, a dating method based on the temperature-sensitive ingrowth of helium from uranium and thorium decay. Because later heating and natural variation in hematite crystals can produce ambiguous (U-Th)/He results, I integrate dating with tools that reveal differences in hematite chemistry and textures. I apply these techniques to two distinct settings: ancient granitic rocks in Colorado and an active fault zone in the southern San Andreas fault (SSAF) …

Fisheries Management Paper No. 313: Western Australian Statewide Small Pelagic Scalefish Resource Harvest Strategy, Department Of Primary Industries And Regional Development, Western Australia

Fisheries Management Papers

Harvest strategies for Western Australia’s (WA) aquatic resources are formal documents developed by the Department of Primary Industries and Regional Development (DPIRD, the Department) to support decision-making processes that ensure the outcomes are consistent with the principles of Ecologically Sustainable Development (ESD; Fletcher 2002a) and Ecosystem Based Fisheries Management (EBFM; Fletcher et al. 2012).

Harvest strategies are a key component of all contemporary fishery management systems and a requirement for certification under the Marine Stewardship Council (MSC; Marine Stewardship Council 2018). The objectives of ESD are reflected in the objects of the Fish Resources Management Act 1994 (FRMA).

This Statewide …

Exploring The Effects Of Polymer-Graphene Interactions On Bulk Composite Properties Using Finite Element Analysis, Bryant Grove

Dissertations

As a filler in high performance materials, graphene significantly enhances the mechanical properties of polymer composites. Experimental characterization of graphene composite enhancements is limited by labor-intensive processes in both synthesizing composites for different purposes and in characterizing the interactions between graphene and polymer composites that lead to these enhancements. Computational approaches such as finite element analysis (FEA) are suitable alternatives that go beyond experimental analysis. This dissertation demonstrates the utility of FEA in analyzing polymer graphene composites with an emphasis on modeling the interaction between graphene fillers and the matrix within the interphase formed between them. The accessible design framework …

Explainability In Deep Learning For Density Regression, Dalton James Oxford

Graduate Theses and Dissertations

Classical statistical methods focus on explainability and inferential power. Machine learning and deep learning can handle non-linear, high-dimensional data better than traditional methods. In modeling, a clear understanding and interpretation are essential to decision-making. Recent work in quantile regression and extreme modeling has begun to use deep learning due to its performance on high-dimensional, non-linear data. Semi-Parametric Quantile Regression (SPQR) is a nonparametric spline-based approach to quantile regression that estimates the conditional PDF and CDF of the response. Semi-Parametric Quantile Regression for Extremes (SPQRx) is a recent extension of SPQR that provides two features: out-of-sample estimation and accurate extreme-tailed estimation. …

Ecological Insights And Management Implications Of The Global Migratory Connectivity Of Green Turtles, Jaime Restrepo, Dina Nisthar, Harris Wei-Khang Heng, Lily K. Bentley, Corrie Curtice, Sarah Deland, Ei Fujioka, Patrick N. Halpin, Sarah K. Poulin, Roldán A. Valverde

School of Earth, Environmental, & Marine Sciences Faculty Publications

Aim

Green turtles are a widely distributed and highly migratory species; despite extensive data on their movement, there is no species-specific global synthesis on the subject. Based on three decades of published literature and building on previous global analyses, we developed a global network model of migratory connectivity for green turtles to better understand their spatial biology.

Location

Global.

Time Period

1990–2022.

Major Taxa Studied

Green Sea Turtle (Chelonia mydas).

Methods

We conducted a structured literature review extracting georeferenced information on the movement of green turtles from 1990 to 2022, aggregating this information into a single connectivity model, …

Model Stormwater Standards 2026, Unh Stormwater Center

UNH Stormwater Center

The purpose of post-construction stormwater management standards is to provide reasonable guidance for the regulation of stormwater runoff to protect local natural resources from degradation and prevent adverse impacts to adjacent and downstream land, property, facilities, and infrastructure. These standards regulate discharges from stormwater and runoff from land development projects and other construction activities to control and minimize increases in stormwater runoff rates and volumes, soil erosion, stream channel erosion, and nonpoint source pollution associated with stormwater runoff.

The Privacy Paradox: How Does Concern About Privacy Impact Actions In The Digital Age?, Julia Laduke

Honors Theses

The privacy paradox occurs when people claim to care about their digital privacy, but do not take actions to keep their data from being spread across the internet. This study examines college students, being primarily Generation Z, and their concerns and actions regarding digital privacy and security. A survey of 15 college students, 7 in humanities and 8 in STEM, was used to analyze their thoughts and concerns about their digital privacy. This survey also asked whether they took actions concerning their privacy, and if so, what tools they used to protect it. The results show that about 50% of …

Calibrating Human Trust In The Age Of Generative Ai: An Examination Of Ethical And Social Challenges, Abigail M. Mondido

Honors Theses

Generative AI (GenAI), a set of AI technologies with the ability to generate original, human-like outputs, is beginning to transform the way that information is distributed, composed, published, obtained, analyzed, and consumed. GenAI has seen massive adoption by internet users, businesses, and organizations in recent years despite the persistence of major ethical concerns and social implications. In particular, existing research has identified multiple critical trust-related issues associated with AI in general, including widespread mistrust and distrust, overreliance on AI, and a lack of trustworthiness of AI. There remains a need for a broader understanding of these issues as they relate …

Techno-Imagination: Elevating Creativity Through Xr And Ai, Christopher Spitzer

Creativity and Change Leadership Graduate Student Master's Projects

Techno-Imagination: Elevating Creativity Through XR and AI explores the history of creativity and computing technology, supported by research and academic literature, and looks at the possibilities of a convergence between the two. In parallel, a brief biographical story of the author shares how a passion for creativity emerged, along with a growing interest in science and technology—specifically extended reality—which ultimately came together in the creation of this master’s project. The project also highlights how the Creative Problem Solving (CPS) process was used alongside AI bots and twenty research-based creative thinking skills in developing the business model canvas. Finally, the outcome …

Conceptualizing A Responsive Design Pedagogy To Support Teachers' Responsiveness To Students' Mathematical Ideas Through Making, Denish Ogweno Akuom

Theses, Dissertations and Culminating Projects

This study develops Responsive Design Pedagogy (RDP), a conceptual and analytic model of teacher responsiveness in design-based environments, to account for how responsiveness emerges through interactions among students, tools, and tasks. Although responsiveness has been widely studied in mathematics education, limited attention has been given to responsiveness within mathematical design activity and to how teachers attend to the multiple modes through which students express their mathematical ideas. Addressing these gaps, this qualitative study examined one teacher’s enactment of responsiveness in a Learning-by-Design classroom where students designed and used 3D-printed mathematical tools. Data sources included classroom video, student design artifacts, teacher …

Public Health Responsible Ai Capability (Ph-Raic) Framework: A Conceptual Model For Integrating Ai Into Public Health Agencies, Arnob Zahid, Ravishankar Sharma, Rezwan Ahmed

All Works

Background: Artificial intelligence (AI) is transitioning from experimental pilots to core public health functions such as disease surveillance, resource planning, and analysis of social and structural determinants of health. Yet, health data collection and stewardship remain fragmented across the globe; some jurisdictions still rely on paper-based systems, while others operate noninteroperable digital systems that can exacerbate inequities. Treating health data as a global good therefore requires governance that enables innovation while protecting rights, safety, and trust. This study aims to develop a conceptual meso-level capability framework that translates responsible AI principles into organizational practices for public health agencies. Methods: We …

Population Structure And Connectivity Of Atlantic Nurse Sharks (Ginglymostoma Cirratum) In The Bahamas And Outlying Areas, Baylie A. Fadool

School of Natural Resources: Dissertations, Theses, and Student Research

Understanding animal ecosystem dynamics and behavior at the individual and population levels is essential for identifying life-history patterns and important areas for management and conservation. Marine fish species often face minimal geographic barriers to movement, but environmental (temperature, salinity, current) or intrinsic barriers (philopatry, site fidelity) can dictate gene flow. Atlantic nurse sharks (Ginglymostoma cirratum) are an International Union for Conservation of Nature (IUCN) listed ‘vulnerable’ species and present a unique opportunity to investigate patterns of population structure and connectivity in large-bodied sharks. They are benthic and display reproductive philopatry, with recent work suggesting they have the capacity …

Reversible, Light-Controlled Inhibition Of Stim1-Mediated Calcium Signaling Using Photoswitchable Ml-9 Derivatives In Jurkat-Lucia Nfat Reporter T Cells, José L. Matute Gálvez

Honors Scholar Theses

Store-operated calcium entry (SOCE) through calcium release-activated

calcium (CRAC) channels is the dominant pathway for sustained Ca2+ influx in

non-excitable cells and is essential for T cell activation, driving downstream

signaling through the calcineurin-NFAT transcriptional axis. Dysregulation of

SOCE produces multi-systemic disease phenotypes, establishing that precise,

spatiotemporally controlled modulation of this pathway is a fundamental

therapeutic requirement. ML-9 is one of the only characterized small molecules

capable of targeting SOCE upstream at the level of STIM1 localization, but lacks

the selectivity, pharmacokinetic properties, and spatiotemporal control necessary

for therapeutic development.

This work describes the design, synthesis, and biological evaluation of …

Spatiotemporal Evolution Of Flow Decline And Water Consumption In A Highly Regulated Transboundary River: The Lower Rio Grande/Bravo, Ana Yarely Casillas Rodriguez

Theses and Dissertations

Long-term flow variability in transboundary rivers reflects the combined influence of water availability, infrastructure development, and binational water use. Integrating historical discharge with evolving water-use data remains challenging due to fragmented records and nationally bounded assessments. This study reconstructs a 125-year discharge record (1900–2025) from historical Water Bulletins and modern observations at 12 gauging stations, providing a spatiotemporal assessment of flow evolution and water-budget components in the Lower Rio Grande/Bravo (LRG).

Discharge records were grouped into four hydrologic regimes—natural (1900–1913), pre-dam (1935–1950), post-dam (1974–1989), and modern (2010–2025)—and analyzed alongside binational water-use data across major sectors. A basin-scale water budget, using …

Stochastic Universal Differential Equations For Epidemiological Modeling: Uncertainty Quantification In Disease Transmission Dynamics, Alice Menaya Armah-Bonney

Electronic Theses and Dissertations

Epidemic forecasting requires not only predictions of expected case counts, but also quantification of uncertainty, although existing surrogate modeling frameworks for agent-based models remain fundamentally deterministic. In this thesis a Stochastic Universal Differential Equation framework is presented that extends the deterministic Universal Differential Equation approach by incorporating a learnable stochastic diffusion term, enabling calibrated probabilistic forecasts while preserving the mechanistic interpretability and computational efficiency of the deterministic baseline. In doing so, a two-phase training algorithm is introduced to ensure stable convergence and the framework is validated against the ensemble output from ExaEpi, an exascale agent-based model of a COVID-19 outbreak …