Digital Commons Network^™

Soil Ethics In Practice: Harvesting Conservation Choices Among Puerto Rican Coffee Farmers, Patricia Marie Cordero-Irizarry

Theses and Dissertations

Coffee farming in Puerto Rico has declined over recent decades, partly due to deteriorating soil quality. However, the decision-making process behind farmers’ adoption of soil conservation practices remains unclear, particularly the overlooked role of soil ethics, which emphasizes the moral principles guiding human relationships with the soil. This mixed-methods study examined coffee farmers’ adoption of soil conservation practices by integrating the Values-Beliefs-Norms (VBN) theory and a newly developed Soil Ethics Survey (SES) instrument for the quantitative component, while using Decision-Making Theory and Social Cognitive Theory to qualitatively explore how farmers’ experiences and reflections shape their soil ethics. Quantitative findings revealed …

Understanding How Nws Meteorologists Tailor Hazardous Weather Messaging To Core Partners And Identify Local Vulnerabilities, Allison Camille Harvey

Theses and Dissertations

Over the past few decades, the National Weather Service (NWS) has continued to improve impact-based decision support services (IDSS) efforts to strengthen communication with core partners. This study addressed how a new spatially hazard-specific vulnerability tool called the Brief Vulnerability Overview Tool (BVOT) may impact how NWS meteorologists tailor messaging to their core partners. It was found that relationship building between NWS meteorologists and core partners is key to enhancing trust, especially during blue sky days. This was done by learning core partners’ needs, thresholds, and communication styles when presenting weather information. Core partners also noticed cues from NWS meteorologists …

Topnet R1: A Multi-Stage Ai Framework For Topic Discovery In Scientific Abstracts, Md Elias Hossain

Theses and Dissertations

Scientific abstracts are rich sources of knowledge, yet extracting meaningful topics remains challenging due to limitations in existing topic modeling techniques. Traditional methods often struggle with interpretability, scalability, and contextual understanding. To overcome these issues, we introduce TopNet R1, a multi-stage ensemble framework that integrates traditional topic models with contextual embeddings from Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-trained Transformer 4 (GPT-4) large language models (LLMs). Top- Net R1 operates in three phases: (1) topic generation using Latent Dirichlet Allocation (LDA), Non-Negative Matrix Factorization (NMF), Latent Semantic Analysis (LSA), and Hierarchical Dirichlet Process (HDP); (2) LLM-assisted pattern recognition …

Augmenting Healthcare Communication: Context-Aware Ai Frameworks For Clinical Decision Support And Automated Summarization, Subash Neupane

Theses and Dissertations

Healthcare communication is plagued by fragmented medical knowledge, patient misunderstanding of care plans, and clinician burnout from documentation burdens. These inefficiencies cost the U.S. healthcare system over $300 billion annually due to preventable nonadherence and administrative waste [47, 19]. While Artificial Intelligence (AI) technology like Large Language Models (LLMs) offer potential solutions, existing systems fail to deliver personalized, context-aware guidance or automate documentation without sacrificing accuracy. This dissertation addresses these gaps through three novel context-aware AI frameworks such as MedInsight, ClinicSum, and ClinicDuo. MedInsight leverages a multi-source context augmentation approach to synthesize patient centric medical responses by integrating Electronic Health …

Estimating Reliability Of Electric Vehicle Charging Ecosystem Using Principle Of Maximum Entropy, Himanshu Tripathi

Theses and Dissertations

This thesis addresses the challenge of estimating electric vehicle (EV) charging system reliability against unpredictable threats like cyberattacks and extreme weather, where traditional methods fail. We utilize the Principle of Maximum Entropy (PME), a statistical tool that provides unbiased risk estimates using limited information. Applied to the EV charging ecosystem, our case study shows how PME models stress factors to predict failures and optimize maintenance. This approach extends beyond EVs to other complex systems with scarce data, such as smart grids or healthcare devices. By linking uncertainty directly to reliability, PME offers a universal method to improve decision-making under unpredictable …

A 12,800-Year-Old Layer With Cometary Dust, Microspherules, And Platinum Anomaly Recorded In Multiple Cores From Baffin Bay, Christopher R. Moore, Vladimir A. Tselmovich, Malcolm A. Lecompte, Allen West, Stephen J. Culver, David J. Mallinson, Mohammed Baalousha M.Sc, Ph.D., James P. Kennett, William M. Napier, Michael Bizimis, Victor Adedeji, Seth R. Sutton, Gunther Kleteschka, Kurt A. Langworthy, Jesus P. Perez, Timothy Witwer, Marc D. Young, Jordan Jeffreys, Richard C. Greenwood, James A. Malley

Faculty Publications

The Younger Dryas Impact Hypothesis (YDIH) posits that ~12,800 years ago Earth encountered the debris stream of a disintegrating comet, triggering hemisphere-wide airbursts, atmospheric dust loading, and the deposition of a distinctive suite of extraterrestrial (ET) impact proxies at the Younger Dryas Boundary (YDB). Until now, evidence supporting this hypothesis has come only from terrestrial sediment and ice-core records. Here we report the first discovery of similar impact-related proxies in ocean sediments from four marine cores in Baffin Bay that span the YDB layer at water depths of 0.5–2.4 km, minimizing the potential for modern contamination. Using scanning electron microscopy …

An Enzyme-Coupled Isotope Dilution Mass Spectrometry Assay For Non-Adjacent Dna Photoproducts As Intrinsic Probes For G-Quadruplexes In Vitro, Savannah Sharee Scruggs

Arts & Sciences Graduate Student Theses and Dissertations

G-quadruplexes are noncanonical secondary structures that form in guanine-rich nucleic acid sequences and are thought to be involved in the control of gene expression.1 Unfortunately, it has been difficult to prove that these structures exist in vivo because of their dynamic nature. Rather than try to develop G-quadruplex specific binders as others have done,2 our idea is to photochemically trap certain types of G-quadruplexes by irreversible photoproduct formation3–5 and then detect the stable G-quadruplex-specific photoproducts by Isotopic Dilution Mass Spectrometry (IDMS).6 This IDMS method could then be used to unambiguously confirm the presence of specific types of G-quadruplexes in vivo …

Dynamic Mutational Profiling Of Binding Interactions And Allosteric Networks In Conformational Ensembles Of The Sars-Cov-2 Spike Protein Complexes With Classes Of Antibodies Targeting Cryptic Binding Sites: Confluence Of Binding And Allostery Determines Molecular Mechanisms And Hotspots Of Immune Escape, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The ongoing evolution of SARS-CoV-2 variants has underscored the need to understand not only the structural basis of antibody recognition but also the dynamic and allosteric mechanisms that could underlie complexity of broad and escape-resistant neutralization. In this study, we employed a multi-scale approach integrating structural analysis, hierarchical molecular simulations, mutational scanning and network-based allosteric modeling to dissect how Class 4 antibodies (represented by S2X35, 25F9, and SA55) and Class 5 antibodies (represented by S2H97, WRAIR-2063 and WRAIR-2134) can modulate conformational behavior, binding energetics, allosteric interactions and immune escape patterns of the SARS-CoV-2 spike protein. Using hierarchical simulations of the …

Developing Microelectrode Arrays As Multiplex Point-Of-Care Diagnostics, Yu-Chia Chang

Arts & Sciences Graduate Student Theses and Dissertations

Antibiotic resistance poses a significant global health challenge, particularly in urinary tract infections (UTIs), where 92% of cases exhibit resistance to at least one antibiotic, causing over 260,000 deaths annually. The emergence of antibiotic-resistant bacteria and growing awareness of the adverse effects of unnecessary antibiotic use highlight the urgent need for better UTI diagnostics. Current state-of-the-art methods are either expensive and time-consuming, or they lack specific details about the nature of the antibiotic and only determine inflammation. This hinders timely and effective treatment decisions regarding whether an antibiotic is actually necessary. Given this backdrop, there is a demand for a …

Statistical Methods For Joint Outcome Modeling And Dynamic Assessment Of Recurrent Events, Zifang Kong

Statistical Science Theses and Dissertations

Recurrent event data frequently arise in clinical studies where individuals experience repeated, possibly related, events over time. These data are often accompanied by sparse and irregular longitudinal measurements, creating challenges for traditional joint modeling approaches that struggle to account for time-dependent associations and within-subject correlations. We propose FRAILTY (Functional Regression with AutoRegressIve fraiLTY), a novel two-step framework that integrates functional principal component analysis (PACE) with a dynamic frailty model featuring autoregressive structure. FRAILTY accommodates both scalar and functional predictors and captures within-subject dependence across recurrent events. To further extend its utility, we develop a multivariate joint modeling framework that simultaneously …

Towards Reliable Clinical Applications Of Ai Models In Radiotherapy, Biling Wang

Statistical Science Theses and Dissertations

Over the past decade, artificial intelligence (AI), particularly through deep learning (DL) techniques, has made significant strides in fields like computer vision (CV) and natural language processing (NLP), leading to transformative advancements across numerous applications. This progress has sparked considerable enthusiasm within the medical field, where DL-related research has grown exponentially since 2015. However, despite these promising developments, the real-world deployment of DL models in healthcare remains limited, especially in safety-critical domains such as radiotherapy (RT), where reliability, safety, and sustained performance are critical. This thesis addresses three core challenges associated with the clinical application of DL models: (1) post-deployment …

Method For Target Detection In A High Noise Environment Through Frequency Analysis Using An Event-Based Vision Sensor, Will Johnston, Shannon Young, David Howe, Rachel Oliver, Zachary Theis, Brian Mcreynolds, Michael L. Dexter

Faculty Publications

Event-based vision sensors (EVSs), often referred to as neuromorphic cameras, operate by responding to changes in brightness on a pixel-by-pixel basis. In contrast, traditional framing cameras employ some fixed sampling interval where integrated intensity is read off the entire focal plane at once. Similar to traditional cameras, EVSs can suffer loss of sensitivity through scenes with high intensity and dynamic clutter, reducing the ability to see points of interest through traditional event processing means. This paper describes a method to reduce the negative impacts of these types of EVS clutter and enable more robust target detection through the use of …

Development And Validation Of Venous Thromboembolism-Bidirectional Encoder Representations From Transformers (Vte-Bert) Natural Language Processing Model, Omid Jafari, Shengling Ma, Barbara D Lam, Jun Y Jiang, Emily Zhou, Mrinal Ranjan, Justine Ryu, Raka Bandyo, Arash Maghsoudi, Bo Peng, Christopher I Amos, Abiodun Oluyomi, Nathanael R Fillmore, Jennifer La, Ang Li

Faculty, Staff and Students Publications

Background: Accurate and rapid phenotyping of venous thromboembolism (VTE) in longitudinal studies is important. A natural language processing (NLP) tool externally validated in representative patients is lacking.

Objectives: To train and validate an efficient NLP model to detect incident VTE event.

Methods: We designed a novel NLP platform, NLPMed, to assist thrombosis researchers with data preprocessing, phenotype annotation, language model finetuning, and NLP application. Using clinical notes, discharge summaries, and radiology reports from patients with cancer at 2 healthcare institutions, we finetuned Bio_Clinical Bidirectional Encoder Representations from Transformers (BERT) to develop VTE-BERT. The new model was trained to detect acute …

08.04.2025 Ored Connect, Liz Williamson

ORED Newsletter

NIH limits AI use and annual proposals accepted per PI

Breast Cancer Survival Rates And Determinants In Ethiopia: A Systematic Review And Meta-Analysis Of Longitudinal Studies, Abenezer M. Tafese, Meseker T. Fentie, Beminate L. Seifu, Angwach A. Asnake, Bikiltu D. Dirbaba, Abdisa G. Jara, Elsabeth Tizazu Asare, Brandon George

College of Population Health Faculty Papers

BACKGROUND: Breast cancer is the most common cancer and the leading cause of cancer mortality among women in Ethiopia, accounting for 32% of new cancer cases and 17.6% of cancer deaths. Despite its growing burden, comprehensive data on survival rates and contributing factors remain limited. This systematic review and meta-analysis aimed to synthesize existing data on breast cancer survival in Ethiopia and identify key determinants influencing outcomes.

METHODS: A comprehensive systematic search was conducted in PubMed, Web of Science, Scopus, Embase, and CINAHL to identify studies on breast cancer survival in Ethiopia published between January 2014 and August 2024. Eligible …

Imputation Via Domain Adaptation: Rethinking Variable Subset Forecasting From Knowledge Transfer, Runchang Liang, Qi Hao, Yue Gao, Kunpeng Liu, Lu Jiang, Pengyang Wang, Minghao Yin

Computer Science Faculty Publications and Presentations

Multivariate time series forecasting in practical deployment faces a critical challenge termed Variable Subset Forecasting (VSF), where certain variables accessible during training are entirely missing during inference. This creates a stark discrepancy between the training (source domain with full variables) and inference (target domain with partial variables) environments, disrupting cross-variable dependencies and fragmenting global temporal patterns. Existing imputation methods, limited to transferring local knowledge (e.g., temporal neighbors or pairwise correlations), fail to capture essential global dynamics, leading to severe performance degradation under distribution shifts. To address these challenges, we redefine VSF as a cross-domain knowledge transfer problem and propose VIDA, …

Rangelands Glossary, Department Of Primary Industries And Regional Development, Western Australia

Natural resources factsheets

An alphabetical list of common Rangelands terminology.

Using Published Undergraduate Biomechanics Research On Hydra Mouth Opening To Train Undergraduates, Stephen Hackler, T. Goel, Jonah Pacis , '25, Eva-Maria S. Collins

Biology Faculty Works

Biophysics research is exciting because physical approaches to biology can provide novel insights, and it is challenging because it requires knowledge and skills from multiple disciplines. We have developed an undergraduate biophysics laboratory module that teaches fundamental skills such as time-lapse microscopy, image analysis, programming, critical reading of scientific literature, and basics of scientific writing and peer review. The module is accessible to students who are familiar with introductory statistics, cell biology, and differential calculus. We used published research on the biomechanics of Hydra mouth opening as a framework because it describes a stunning biological phenomenon: Hydra, a freshwater …

Town Of Pawleys Island, Ally Murphy

Goal 15: Life on Land

No abstract provided.

Estimation Methods For Bayesian Exponential Random Graph Models Under The Horseshoe Prior., Pamela Linares

Electronic Theses and Dissertations

Networks are powerful tools for modeling the complexity of social interactions, biological systems, and information spread. A leading statistical frameworks for analyzing network data are Exponential Random Graph Models (ERGMs), which provide a principled approach to capturing structural dependencies. However, ERGMs remain challenging to estimate, especially in sparse or high-dimensional settings where models suffer from degeneracy and unstable parameter inference. This paper proposes a penalized Bayesian approach to ERGMs that utilizes the horseshoe prior, a sparsity-inducing global-local shrinkage prior. This prior offers robust regularization while preserving important signals, improving estimation by shrinking irrelevant parameters and reducing the impact of extreme …

Evometric: An Interactive Framework For Scalable Visual Analytics Of Time Series Data With Dynamic Changes., Jiahang Huang

Electronic Theses and Dissertations

In today's data-intensive landscape, rapid advances in digital sensing and recording technologies have enabled the acquisition of high-resolution multimodal time series data, capturing intricate real-world dynamics across various domains such as healthcare, behavioral science, and environmental monitoring. However, the complexity and scale of these datasets present significant analytical challenges, particularly in understanding dynamic changes at both individual and cohort levels. This dissertation introduces EvoMetric, a novel visual analytics framework designed to support scalable exploration and analysis of large-scale multimodal time series data with dynamic changes. EvoMetric seamlessly integrates individual-level temporal dynamics with population-level comparative insights, enabling users to visually …

Synthetic And Pharmacological Diversity Of Nitrogen-Containing Heterocycles., Shramana Ghosh

Electronic Theses and Dissertations

Nitrogen-containing heterocycles are a foundational class of compounds in organic chemistry, playing critical roles in pharmaceuticals, agrochemicals, and natural products due to their structural diversity and biological relevance. Among them, isoindolinones are notable for their wide range of pharmacological activities. Structurally, isoindolinones possess a benzylic methylene group adjacent to the nitrogen atom, which allows for selective oxidative transformations to yield phthalimide derivatives, well-known intermediates in synthetic, pharmaceutical, and materials chemistry. Although phthalimide is traditionally employed as a protecting group for amines via the Gabriel synthesis, isoindolinone offers a valuable alternative. Through a modified Gabriel-like approach, isoindolinones can serve as more …

Predictor-Informed Bayesian Nonparametric Clustering., Md Yasin Ali Parh

Electronic Theses and Dissertations

In this dissertation, we performed clustering of observations such that the cluster membership is influenced by a set of predictors. To that end, we employ the Bayesian nonparametric Common Atom Model (CAM), which is a nested clustering algorithm that utilizes a (fixed) group membership for each observation to encourage more similar clustering of members of the same group. CAM operates by assuming each group has its own vector of cluster probabilities, which are themselves clustered to allow similar clustering for some groups. We extend this approach by treating the group membership as an unknown latent variable determined as a flexible …

Farm Management Practice For The Prevention Of Soil Erosion In The Carnarvon Horticultural Area, Kehinde O. Erinle

Horticulture research reports

The Carnarvon horticultural area has suffered considerable erosion damage following flooding of the Gascoyne River.

The purpose of this report is to describe the factors that contribute to soil erosion in the Carnarvon horticultural area (Section 1), provide guidelines for good soil management (Sections 2) and provide floodway hazard classes and associated soil management recommendations (Section 3).

This report:

• Provides detailed information on soil management for intensive irrigated cropping.
• Details cropping alternatives to better manage the soil erosion risk.
• Identifies appropriate plants for soil stabilisation in a range of situations.
• Promotes the concept of property management plans.
• Takes account of …

The Effect Of The Markle Mill Dam Removal On The Habitat And Riverine Food Web Of Otter Creek, Jenna Blanton

All-Inclusive List of Electronic Theses and Dissertations

Across the United States, dam removals are increasing in frequency. Despite this, the effects of dam removal on freshwater food webs are under-studied. Most existing studies investigate the impacts on fish assemblages, and very few investigate the impact on diatom, crayfish, and turtle communities. Furthermore, low-head dams are more abundant than large hydropower dams, yet the impacts of their removal are less studied than their larger counterparts. I used a Before After Control Impact (BACI) study design to survey populations of benthic diatoms, riffle-dwelling crayfish, and aquatic turtles. Species richness, species evenness, and Shannon Diversity Index values were used to …

Comparative Expression Of Cgmp-Dependent Protein Kinase G (Pkg) From Plasmodium And Toxoplasma, Tsopmo Asaah

Theses, Dissertations and Culminating Projects

Malaria and Toxoplasmosis are life threatening diseases to humans. The search for a cure and control of these diseases is still one of the major challenges of scientists worldwide. In this research we focused on two Malaria species; Plasmodium bergei² (Pb) and Plasmodium falciparum¹ (Pf) and also on Toxoplasma gondii. Part of the life cycle of these organisms is regulated by the enzyme cyclic GMP-dependent protein kinase G (PKG)⁴. This is our drug target in this research. We believe that inhibiting this enzyme will be a great step in fighting these diseases. In this research, we devised a comparative study …

Investigating The Influence Of Experimental Parameters On The Formation Of Gold Nanoparticles: A Green Synthesis And Design Of Experiments Approach, Isaac Opeyemi Subuloye

Master's Theses

This thesis examines the green synthesis of gold nanoparticles using catechin, a naturally occurring plant-derived compound, as both a reducing and capping agent. The synthesis process was guided by a structured Design of Experiments (DOE) methodology to ensure systematic investigation and optimization. A two-phase experimental approach was adopted. First, a full factorial screening design was used to evaluate the effects of catechin concentration, NaOH concentration, and pre-reaction time. This was followed by an optimization phase using a face-centered composite design to identify conditions that produce nanoparticles with ideal characteristics. The nanoparticles were analyzed using UV-visible spectroscopy and dynamic light scattering …

Integrated Sustainability: Unlocking Environmental Potential In Electric Vehicles And Solar Panels, Zachary C. Anderson

Honors Theses

This thesis investigates the environmental, economic, and individual level factors influencing consumer adoption of electric vehicles and solar panels. Through a comprehensive scoping review and case-based analysis, it identifies key incentives and barriers related to purchase intentions for each alternative energy technology. Central factors influencing adoption include cost-related concerns, individual purchasing power, demographic effects, and policy impact. These findings suggest that targeted interventions – specifically those used to amplify incentives and mitigate barriers – can positively impact individual consumer purchase intention, including through bundling options. Highlighting the importance of integrated sustainability, this study explored how electric vehicles and solar panels …

Small Stream Restoration In The Piedmont Of South Carolina: Comparison Of Evaluation Tools And Water Quality’S Effects On Salamanders, Camryn Lachica

All Theses

For many years, the United States Army Corps of Engineers (USACE) used the Guidelines for Preparing a Compensatory Mitigation Plan worksheets to guide pre-restoration evaluation and determine post-restoration mitigation credits in South Carolina. Recently, the USACE in South Carolina transitioned to the Stream Quantification Tool (SQT), which provides a more comprehensive assessment framework. Our first objective was to compare these assessment methodologies across different landscape types to determine what the SQT adds to mitigation calculations that were not considered in prior worksheets. We evaluated 16 streams in the Piedmont of South Carolina, with four replicates each of forested, suburban, urban, …

A Three-Stage Matheuristic For The Blood Stochastic Inventory Routing Problem, Vincent F. Yu, Nabila Salsabila, Aldy Gunawan, Aldy Gunawan, Nurhadi Siswanto

Research Collection School Of Computing and Information Systems

This research introduces a blood distribution system under vendor-managed inventory that considers uncertain supply and demand. We present it as the Blood Stochastic Inventory Routing Problem, formulating it as a two-stage stochastic programming model. To solve this problem, this study proposes a three-stage matheuristic that combines a perturbation heuristic, Adaptive Large Neighborhood Search, and an exact approach. From historical data of Surabaya Blood Center in Indonesia, six sets of new instances are generated under different settings. Computational results show that our proposed three-stage matheuristic outperforms CPLEX and a two-stage matheuristic by gaining optimal or better solutions within a significantly shorter …