Digital Commons Network^™

Environmental Justice In Indigenous Communities: The Disproportionate Effects Of Environmental Contamination, Rae Cade, Danlin Yu, Charles Knoble, Kyle Whyte, Pankaj Lal, Cortni Borgerson

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Indigenous communities in New Jersey, New York, and Pennsylvania (referred to as the northeastern United States) face disproportionate environmental pollution, with mortality rates 60 % higher than their white counterparts –an inequity that extends beyond formal recognition categories. While previous research has revealed pollution from facilities that cause severe health issues in Indigenous communities, broad geographic studies examining the spatial correlation between Environmental Justice (EJ) indicators and Indigenous populations remain limited. This study addresses this gap by examining contamination patterns across the northeastern United States, focusing on Superfund sites, drinking water violations, oil spills, and natural gas releases. Our analysis …

A Hedonic Analysis Of Combined Sewer Overflows (Csos) In Northern New Jersey, Taylor Wieczerak, Pankaj Lal, Pralhad Burli, Benjamin Barnett Witherell, Erik Lyttek, Bernabas T. Wolde, Ava Distaso

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Significant water pollution caused by flooding due to heavy precipitation and extreme weather events has become a considerable problem, and changing weather patterns and sea level rise attributable to global climate change stand to further exacerbate the issue. During heavy precipitation events, combined stormwater and untreated sewage may be diverted to adjacent water bodies via combined sewer overflows (CSOs), resulting in contamination and water pollution that can be harmful to human and environmental health. Though water quality effects of CSO discharges have been studied, the socio-economic aspects of this infrastructure have not received much scientific attention. This study provides an …

Millennial-Timescale Thermogenic Co2 Release Preceding The Paleocene-Eocene Thermal Maximum, Shijun Jiang, Ying Cui, Yasu Wang, Maurizia De Palma, B. David A. Naafs, Jingxin Jiang, Xiumian Hu, Huaichun Wu, Runjian Chu, Yangguang Gu, Jiuyuan Wang, Yizhou Huang, Miquela Ingalls, Timothy J. Bralower, Shiling Yang, James C. Zachos, Andy Ridgwell

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Geologic records support a short-lived carbon release, known as the pre-onset excursion (POE), shortly before the Paleocene-Eocene Thermal Maximum (PETM; ~ 56 Ma). However, the source and pace of the POE carbon release and its relationship to the PETM remain unresolved. Here we show a high-temporal-resolution stratigraphic record spanning the POE and PETM from the eastern Tethys Ocean that documents the evolution of surface ocean carbon cycle, redox and eutrophication, confirming the global nature of the POE. Biomarkers extracted from the sedimentary record indicate a smaller environmental perturbation during the POE than that during the PETM in the eastern Tethys …

Wacsaw: An Adaptive, Statistical Method To Classify Movement Into Sleep And Wakefulness States, Austin Vandegriffe, V. A. Samaranayake, Matthew S. Thimgan

Mathematics and Statistics Faculty Research & Creative Works

Wearable actimeters can improve our understanding of sleep in the natural environments. Current algorithms may produce inaccuracies in specific individuals and circumstances, such as quiet wakefulness. New hardware allows data collection at higher frequencies enabling sophisticated analytical methods. We have developed a novel statistical algorithm, the Wasserstein Algorithm for Classifying Sleep and Wakefulness (WACSAW), to identify behavioral states from recordings of everyday movement. WACSAW employs optimal transport techniques to identify segments with differing activity variability. Functions characterizing the segments' movement distributions were clustered into two groups using a k-nearest neighbors and labeled as sleep or wake based on their proximity …

Adaptive Deep Learning In Physical Layer Applications, Ali Owfi

All Dissertations

Traditionally, signal processing models in communication systems have been designed based on solid foundations in statistics and information theory, often assuming linearity and optimizing for simplified models. However, real-world communication systems exhibit numerous imperfections and non-linearities that traditional linear models struggle to capture accurately. Deep Learning (DL)-based approaches, unconstrained by rigid mathematical models, have shown promise in optimizing system performance by accommodating specific hardware configurations and dynamic channel conditions as an alternative to the traditional methods. Despite all the recent research efforts on DL-based methods for physical layer applications, DL models have still not been widely applied to physical layer …

How Do Server-Based Architectures Compare To Serverless Architectures In Terms Of Development, Deployment Process, Scalability, And Cost-Effectiveness?, Natalio Fernandes Gomes

Honors Program Theses and Projects

Applications are tested in developers’ machines before deployment, since this is the standard practice that ensures the software is functioning as it should before deploying it to a standard practice that ensures the software is functioning as it should before deploying it to a specific environment. The deployment process consists of setting up the environmental requirements, infrastructure configuration on cloud or on-premises servers. Consequently, developers often run into the infamous "It works on my machine" problem. This issue is defined by the fact that applications function correctly in development environments but fail during deployment to production. Furthermore, scalability concerns and …

(R2125) Impact Of Convective Condition And Inclined Magnetic Field On Casson Nanofluid With Bioconvection In Porous Medium, Touseef Fayaz, O. Otegbeye, Md. Sharifuddin Ansari

Applications and Applied Mathematics: An International Journal (AAM)

This paper presents an analysis on steady magnetohydrodynamic boundary layer flow of Casson nanofluid with microorganisms near an expandable boundary in a porous medium. The flow behaviour is analysed by incorporating impacts of magnetic field applied in a direction which makes an angle α∗ with the boundary and convective conditions in temperature, nanoparticle concentration and microorganism density at boundary. Non-dimensionalised nonlinear and coupled system of ordinary differential equations are solved by exercising a numerical algorithm termed as spectral local-linearization method. The considered numerical algorithm is found to be convergent and capable of yielding accurate results. Graphical sketches of solutions obtained …

Evaluating The Preparedness Of Local Zoning Regulations For Flood Risk Reduction In The Most Affected Local Jurisdictions In Nebraska, Md Asaduzzaman Noor

Community and Regional Planning Program: Theses

Flooding has profound social, economic, and environmental impacts on local communities, and zoning plays a critical role in mitigating these risks. The 2019 Nebraska floods, among the most severe in the state’s history, highlighted the urgent need to strengthen local preparedness and mitigation strategies. This study assesses the extent to which local zoning regulations in Nebraska’s most affected jurisdiction, including rural areas, address flood risk reduction. A systematic review of 117 zoning ordinances from counties, cities, towns, and villages, we applied a structured analytical framework encompassing regulatory and permitting policies, voluntary and incentive-based measures, and nature-based solutions. The results show …

Bridging Conservation And Disaster Recovery: A Dual Study On Wetland Program Plans Evaluation And Midwest Post Disaster Recovery Assessment, Rao Nargis Jahan

Community and Regional Planning Program: Theses

Wetlands provide essential ecological, social, and economic benefits for our society. In the United States, states and tribes play crucial roles in wetland protection, restoration, and management. However, no research has systematically measured state-level wetland planning efforts towards national conservation goals. This study is the first to comprehensively evaluate how state-level Wetland Program Plans (WPPs) align with national missions, particularly the "no-net-loss" of wetlands goal. Our research assesses the EPA-approved state-level WPPs from 42 out of 50 states in the United States during the period from 2015 to 2024. Using a protocol of 30 indicators across five categories, this study …

Flood Resilience Through Working-Land Conservation: Assessment Of Wetland Inundation Dynamics Across Wrp, Wma, Wpa, Padus And Crp Lands In Nebraska (2018–2024), Pranjay Joshi

Community and Regional Planning Program: Theses

This study first confirms whether Nebraska’s wetlands are still functioning hydrologically in ways that reduce flood impacts. Wetlands are known to lessen flood damage by storing water, slowing runoff, and moderating peak flows, but these benefits depend on the wetlands’ ability to maintain inundation and saturation through time. Many wetlands across the state have undergone drainage, hydrologic alteration, or isolation from surrounding watersheds, raising uncertainty about their present-day functioning. Using seven years of Sentinel-2 imagery processed in Google Earth Engine, this research establishes a clear, long-term record of inundation patterns across thousands of wetland parcels. This analysis verifies which wetlands …

Upcycling Commodity Polymers To Advanced Materials For Energy And Environmental Sustainability, Anthony Griffin-Espinoza

Dissertations

Synthetic polymers play an essential role in nearly every aspect of our lives. Extending beyond single-use packaging, polymeric material design has progressed to attain tailorable architectures granting exceptional performance across advanced applications, including carbon-fiber reinforced polymer composites for aerospace, conductive materials for soft electronics, and drug carriers for biomedicine. While highly promising, intricately designed polymers needed to achieve excellent performance often have limited processability, complex synthetic methods, and expensive precursors. Furthermore, due to a lack of recyclability, commodity polymer waste streams result in both environmental impacts and a substantial loss of economic value. This dissertation focuses on developing robust strategies …

Privacy Preserving-Based Artificial Intelligence For Precision Agriculture, Partha P. Sengupta

Dissertations

The research work finds a solution to precision agriculture of cotton cultivation using artificial intelligence (AI) models. Two sets of model performance based on the application are selected namely a low resource and a high resource setting. This is because using drone surveys to capture images identifying the classes of stressed and unstressed cotton plantation requires limited model architecture and CPU based computation. Thus, traditional AI models were selected for low resource settings. Again, for high computation intensive models like transfer learning-convolution neural network (CNN) based architectures were grouped into high resource settings. There was another issue of class imbalance …

The Malonate Template: The Key To Unlocking Novel Amino Acids, Thomas Owens

Dissertations

The “Malonate Template” provides access to various amino acids, all from a common intermediate. Herein, demonstrates the use of the malonate template to establish a synthetic route to both 2-thiohistidine and 2-thio-3-N-methyl-histidine from a benzyl methyl malonate derived intermediate. Furthermore, efforts exploiting the applicability of the malonate template for the of both 2-thiohistidine and 2-thio-3-N-methyl-histidine as a suitable alternative to methods previously described by Erdelmeier are described.

The method presented incorporates modifications to the biomimetic pathway described by Erdelmeier for the synthesis of 2-thiohisidine. By exploiting the biomimetic formation of 2-thiohisitidne’s mechanism via mass spectrometry, we …

Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 50 – Zelia Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Accelerating Relationship Discovery In Chronic Lower Back Pain Through Knowledge Graph And Ontology Enhanced Large Language Models, Damon Lin

Master's Theses

Chronic lower back pain (cLBP) is a widespread public health burden linked to anxiety, depression, and opioid addiction. Interventions aimed at treating cLBP have shown minimal improvements in pain outcomes, leading researchers to reexamine our understanding of cLBP through constructing a causal model. However, constructing causal models through Randomized Controlled Trials are often unfeasible, and relying on domain expertise requires extensive and time-consuming research, posing a serious bottleneck for designing effective treatments. To accelerate this process, we apply Knowledge Graphs, Ontologies, and Large Language Models (LLMs) to aid researchers in determining possible causal relationships. First, we demonstrate how LLMs can …

A Comparative Evaluation Of Feedback Strategies For Enhancing Student Software Test Suite Writing Outcomes, Ashton Alonge

Master's Theses

Background and Context

Software testing is a fundamental component of computer science education, forming the basis for students’ ability to ensure program correctness and reliability. Despite its importance, many students struggle to design test cases that effectively expose faults and achieve meaningful test coverage. Traditional instructional approaches often emphasize code coverage metrics such as line or branch coverage, but these metrics may not adequately capture the quality of student tests. Mutation analysis, which measures how well tests detect small, artificial faults (mutants) introduced into the program, offers a potentially richer measure of test effectiveness. However, little is known about how …

Generalized Detection Of Animal Behavior Using Accelerometers, Alexander J. Arrieta

Master's Theses

Animal mounted sensors are becoming increasingly used to passively monitor both domestic and wild animals. Advances in lightweight accelerometer and GPS technology have allowed many animals to be fitted with high accuracy sensors for extended periods of time. This leads to new opportunities to study animal behavior without direct observation. However, interpreting the raw data is difficult due to the high volume and missing context of the information. Machine learning techniques excel at extracting information from raw data streams and are excellent candidates for processing the sensor data. However, due to large variance in how different animals execute the same …

Robustness Of Network Inference Algorithms Under Network Class Misspecification, Roberto Ceja

Electronic Theses, Projects, and Dissertations

Inferring phylogenies in the presence of hybridization remains a difficult problem. As a result, many current methods for reconstructing phylogenetic networks are restricted to a simple class of networks known as level-1. This restriction arises from theoretical considerations rather than empirical evidence, with real data possibly arising from complex networks. In this work, we evaluate the robustness of two level-1 network inference methods, SNaQ and NANUQ+, through a simulation study, when the input data originates from a more complex network. Specifically, we investigate whether these methods can accurately recover important features of the true species network, such as the circular …

Predictors Of Math Identity In U.S. High School Students, Edwin Flores

Electronic Theses, Projects, and Dissertations

This study explored factors related to high school students’ sense of math identity. Data from the High School Longitudinal Study of 2009 was used which is a nationally representative dataset from the National Center of Education Statistics (NCES). The sample is representative of U.S. high schoolers who began ninth grade in 2009. Multiple regression analysis was performed and factors relating to students’ prior mathematics coursework and attitudes about mathematics were found to predict students’ mathematics identity.

Keywords. Mathematics, identity, high school students

Synthesis Of Phenyl-Substituted Zinc Dipyrrin Photosensitizer For Carbon Dioxide Reduction, Stephen Ankomah

Electronic Theses and Dissertations

The release of CO₂ from fossil fuel combustion drives the need for its conversion into more sustainable options like CO and CH₄ via photocatalytic reduction. This process requires a catalyst, sensitizer, and electron donor. Zinc dipyrrin-based complexes are promising photosensitizers, offering an alternative to expensive, rare-metal-based systems. Most first-row transition metal dipyrrin compounds have short excited-state lifetimes due to rapid nonradiative decay, but Zn(II) dipyrrin complexes stand out. With a d¹⁰ configuration, they lack deactivating ligand field states and can access long-lived triplet states through a charge-separated intermediate. A phenyl-substituted Zn(II) dipyrrin complex was synthesized and studied using NMR to …

Divergent Responses Of Branched-Chain And Straight-Chain Lipid Membranes To Butanol Stress Revealed By All-Atom Molecular Dynamics Simulations, Joshua Olaf Aggrey

Electronic Theses and Dissertations

Membrane integrity under chemical stress is critical to cellular survival and industrial microbial bioproduction, yet the molecular basis of bilayer resilience remains poorly understood. Using all-atom molecular dynamics simulation, we compare the effect of increasing concentrations of 1‑butanol on membranes composed of straight-chain (1,2-dipalmitoyl-sn-glycero-3-phosphocholine, DPPC) and branched-chain (1-anteiso-palmitoyl-2-palmitoyl-sn-glycero-3-phosphocholine, APPC) lipids, which differ in the point of attachment of a single methyl group. In the absence of butanol, both membranes exhibit well-ordered architectures consistent with experimental benchmarks; however, under increasing solvent stress, their behaviors diverge markedly. DPPC membranes display gradual thinning, modest area per lipid …

2025 December - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All,

December was defined by quite a bit of temperature variability (though the temperature swings resulted in near-normal monthly averages) and an overall dry pattern.

The month started out cooler than normal, with a slight moderation in the second week of the month, before a strong cold front sent temperatures tumbling into the teens or single-digits and wind chills into the single digits or below zero on December 14 and 15 - with many locations stuck in the 20’s or even teens for high temperatures. Following this cold weather, temperatures quickly rebounded into the normal and then well above …

Detection Of Phase-Binning And Interpolation Artifacts In 4-Dimensional Computed Tomography Imaging Using Deep Learning And Rule-Based Approaches, Jorge Cisneros, Nathan H. Feldt, Yevgeniy Vinogradskiy, Richard Castillo, Edward Castillo

Department of Radiation Oncology Faculty Papers

BACKGROUND: Four-dimensional computed tomography (4DCT) imaging is a crucial component to lung cancer radiotherapy planning and enables CT-ventilation-based functional avoidance planning to mitigate radiation toxicity. However, 4DCT scans are frequently impaired by acquisition artifacts that corrupt downstream analyses that depend on lung segmentation and deformable image registration, such as CT-ventilation and dose accumulation.

PURPOSE: This study develops 3D deep learning models to identify phase-binning artifacts at the voxel level and a heuristic, rule-based method to identify interpolation slices within 4DCT images.

METHODS: We introduce a generator that systematically inserts synthetic phase-binning and interpolation artifacts into any artifact-free breathing phase obtained …

Floodplain Lake Hydrodynamic And Morphodynamic Connections Through Hydraulic Modeling Along The Pee Dee River, Sc, Charles Cj Mina

Electronic Theses and Dissertations

Rivers have been essential in the success of humankind. This reliance has created a vested interest in studying the rivers' environmental history through using floodplain deposits, with the assumption that coarser sediments correlate to higher discharge floods. However, shifting hydrological connectivity and hydrodynamics can complicate this correlation in primary repositories of flood deposits, oxbow lakes, by altering the texture of sediments delivered to them. Studying these complications is essential for quantifying paleoflood magnitude using the sediment record, but has been difficult, as the currently used index of hydrological connectivity relies on water stage, which does not reflect the sediment flux …

Tuning A Magnetic Energy Scale With Pressure And Field In Ute2, Hyunsoo Kim, I. Lin Liu, Wen Chen Lin, Yun Suk Eo, Sheng Ran, Nicholas P. Butch, Johnpierre Paglione

Physics Faculty Research & Creative Works

When a fragile ordered state is suppressed to zero temperature, a quantum phase transition occurs, which is often marked by the appearance of unconventional superconductivity. While the quantum critical point can be hidden, the influence of the quantum criticality extends to fairly high temperatures, manifesting non-Fermi liquid behavior in a wide range of the field-temperature-pressure phase space. Here, we report the tuning of a magnetic energy scale in the heavy-fermion superconductor UTe₂, previously identified with a peak in the c-axis electrical transport temperature dependence, using applied hydrostatic pressures and a-axis-oriented magnetic fields as complementary (and opposing) tuning parameters: …

Essays On The Economics Of Farmland Valuation And Investment In U.S. Agriculture, Colson Tester

Graduate Theses and Dissertations

This dissertation presents three empirical essays that collectively advance the understanding of farmland valuation in key U.S. agricultural regions, emphasizing the critical advantages of comprehensive, transaction-based data over traditional survey methods. Farmland represents a significant portion of agricultural wealth, and its accurate valuation is crucial for farmers, investors, and policymakers, influencing everything from credit access to investment strategies. Historically, research has often relied on subjective survey data, which can suffer from biases, inaccuracies, and insufficient granularity. This dissertation addresses these limitations by leveraging extensive datasets of arm’s-length farmland transactions, offering a more precise and market-driven perspective on land values. The …

Impacts Of Nutrient Addition And Disturbance On Coastal Dune Arthropod Communities And Trophic Interactions, Kayla Beitzel

Graduate Theses and Dissertations (2019 - present)

Coastal dune ecosystems face ongoing threats from human-mediated disturbance and altered resource availability. Because these dunes provide critical habitat for many organisms, including shorebirds, beach mice, and arthropods, changes in disturbance regimes or resource availability can impact plant communities and higher trophic levels by altering plant richness and productivity, which in turn influence arthropod abundance and diversity. To examine how disturbance and nutrient addition affect arthropod communities, we established twenty 5×5 m plots on Dauphin Island, crossing mechanical disturbance with a 10 g m⁻² addition of nitrogen, phosphorus, and potassium, replicated across five experimental blocks. Arthropods were sampled using three …

Performance Enhancement For Rufa: Rapid Urban Forest Assessment, Nicholas Tan

Master's Theses

Urban forests are crucial to the livability and resilience of cities, offering critical ecosystem benefits such as air quality enhancement, temperature regulation, and biodiversity. Managing said urban forests is essential to ensure their sustainability and adaptability to rapidly changing environmental and climate conditions. The Rapid Urban Forest Assessment (RUFA) tool was developed to address the need for a standardized approach to evaluating and comparing urban and community forestry programs. By analyzing and aggregating tree-specific data across California, such as canopy cover, tree counts, and diversity scores, RUFA assigns a comprehensive urban forestry score for each city. This score allows for …

An Analysis Of Neuroidal Memory Formation Within D. Melanogaster, Jerry Chang

Master's Theses

The Neuroidal model poses a neurobiologically plausible theory for modeling the brain. This symbolic network has been shown to capture realistic memorization behaviors using the JOIN algorithm. The model has also been recently improved by incorporating Watts-Strogatz small-worlds within its base structure. From the efforts of neuroscience researchers, we have access to the Drosophila melanogaster (D. melanogaster) fruit fly’s connectome, which has been found to also contain small-worlds in this thesis. By synthesizing the Ocellar Ganglion (OCG) region of Drosophila, we compare a digitized version of a real-world brain with an instance of the Neuroidal model. In this thesis, we …

The Food Truck: A Multi-Product Newsvendor With Expectile Risk, Sekyiwaah Nuamah

Electronic Theses and Dissertations

The Newsvendor Problem is a fundamental model in Operation Research and Supply Chain Management used to determine the optimal order quantity under uncertain demand to minimize expected costs.
This research extends the classical Newsvendor problem to a multi--product setting, addressing the risk of asymmetric cost structures faced by a food truck. This thesis introduces expectile risk measures to quantify and manage uncertainty in demand, moving beyond traditional risk metrics. To evaluate the impact of expectile-based decision-making, we analyze three types of demand distributions--simple, symmetric, and skewed. For skewed distributions, we apply linear spline inverse interpolation to derive expectile values from …