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Articles 3181 - 3210 of 18375
Full-Text Articles in Entire DC Network
Computational And Ai Tools For Understanding Telomere-Associated Cancer Mechanisms, Eleni Adam
Computational And Ai Tools For Understanding Telomere-Associated Cancer Mechanisms, Eleni Adam
Computer Science Theses & Dissertations
Telomeres are the protective caps of the human chromosomes and are critical for genome stability. Dysfunctional telomeres caused by their erosion with age and cell proliferation as well as by defects in their maintenance is a major early event leading to genome changes and cancer. Subtelomeres possess the critical role of regulating adjacent telomeres. Due to their complex repeat structure and high variance from one person to another, these areas have not been analyzed in detail. We present a set of computational and machine learning tools to aid in the understanding of subtelomere structure and its rearrangements in cancer.
Initially, …
Reframing Soil Freezing As An Unsaturated Process, Antai Dong, Xiong Zhang
Reframing Soil Freezing As An Unsaturated Process, Antai Dong, Xiong Zhang
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Soil freezing and frost heave are inherently unsaturated soil phenomena. However, most existing numerical models are based on saturated soil mechanics or assume full saturation. This simplification introduces conceptual inconsistencies, requires modifications that violate fundamentals in soil mechanics and fluid mechanics, and often leads to the use of self-conflicting soil properties. To overcome these limitations, this study develops a physically consistent, fully coupled thermohydraulic model for soil freezing grounded in modern unsaturated soil mechanics. A soil freezing characteristic surface (SFCS) is introduced to represent unfrozen water content in partially frozen soils as a function of both suction and temperature. Recognizing …
Viability Assessment Of Bovine Embryos: A Public Dataset And Deep Learning Baselines, Erfan Khayyati
Viability Assessment Of Bovine Embryos: A Public Dataset And Deep Learning Baselines, Erfan Khayyati
All Graduate Theses and Dissertations, Fall 2023 to Present
Improving the success rates of cattle breeding is essential for sustainable agriculture, global food security, and high-quality livestock production. Currently, determining whether a lab-grown bovine embryo is healthy enough for a successful pregnancy requires highly trained experts to manually evaluate days of continuous time-lapse video footage. This process is not only incredibly time-consuming but also highly subjective; human reviewers often suffer from visual fatigue when tracking subtle, microscopic cellular changes over a seven-day period, leading to significant disagreement among even top experts on an embryo’s true potential. Furthermore, assessing bovine embryos is notoriously difficult due to their dark, lipid-dense cellular …
Spatial Prediction Under Uncertainty: Methodological And Computational Advances In Bayesian Maximum Entropy, Kinspride K. Duah
Spatial Prediction Under Uncertainty: Methodological And Computational Advances In Bayesian Maximum Entropy, Kinspride K. Duah
All Graduate Theses and Dissertations, Fall 2023 to Present
Environmental decisions such as infrastructure design, water management, and snow load estimation depend on spatial data that are often incomplete or uncertain. In many cases, measurements are not exact values but ranges, reflecting limitations in data collection methods. Traditional mapping techniques typically simplify these uncertain measurements, which can lead to less accurate predictions. This dissertation introduces improved statistical tools for making spatial predictions when data are uncertain or partially known. By utilizing a framework called Bayesian Maximum Entropy (BME), this research demonstrates how exact measurements and range-based data can be combined in a mathematically consistent way. The work demonstrates that …
The Impact Of Ai On The Landscape Design Process, Jacob Owen Huff
The Impact Of Ai On The Landscape Design Process, Jacob Owen Huff
All Graduate Theses and Dissertations, Fall 2023 to Present
Artificial intelligence (AI) is becoming more common in design fields, including landscape architecture. For example, AI has been used to visually analyze park aesthetics and generate landscape design concepts (Jahani et al., 2022; Senem et al., 2023; Ploennigs & Berger, 2023). This study explores how AI, specifically an image-generation tool called Midjourney, affects the design process for landscape architecture students.
Students completed two design projects—one using AI-generated images and one using traditional, non-AI precedent images. Their final designs were evaluated by professional landscape architects who did not know which designs had been influenced by AI. Students also completed surveys about …
Method Validation Of The Cdc Bottle Bioassay And A Historical Record Of Polycyclic Aromatic Hydrocarbons In Glacier National Park, Evah F. Peard
Method Validation Of The Cdc Bottle Bioassay And A Historical Record Of Polycyclic Aromatic Hydrocarbons In Glacier National Park, Evah F. Peard
All Graduate Theses and Dissertations, Fall 2023 to Present
Certain contaminants can persist in the environment for long periods of time, build up within living tissues, travel far from their origin, and harm both ecosystems and organisms. This thesis focuses on two types of contaminants: insecticides and polycyclic aromatic hydrocarbons (PAHs). Insecticides are manufactured to control pests while PAHs are found in oil and gas products and can be produced by industry, vehicle engines, and wildfires. Understanding how harmful these contaminants are and where they end up in the environment is critical for protecting environmental health.
First, I evaluated a widely used test developed by the Centers for Disease …
Bridging The Gap: Exploring The Development Of Science Self-Efficacy Among Students With Learning Disabilities, Aria Hadley-Hulet
Bridging The Gap: Exploring The Development Of Science Self-Efficacy Among Students With Learning Disabilities, Aria Hadley-Hulet
All Graduate Theses and Dissertations, Fall 2023 to Present
Students with learning disabilities are often overlooked in efforts to broaden participation in STEM. This multi-paper dissertation investigates science self-efficacy among this population through the lenses of the social model of disability and self-efficacy theory. An integrative review reveals consistently lower academic self-efficacy among students with learning disabilities and a lack of research examining their science self-efficacy specifically. Quantitative analysis of national data shows lower science self-efficacy overall, yet no differences among students enrolled in advanced science courses. A mixed-methods study further demonstrates that in inclusive school environments characterized by asset-based teacher beliefs and normalized accommodations, science self-efficacy differences disappear. …
Investigation Of Yy Production Methods For Invasive Channel Catfish Ictalurus Punctatus Population Management, Andrew M. Wisniewski
Investigation Of Yy Production Methods For Invasive Channel Catfish Ictalurus Punctatus Population Management, Andrew M. Wisniewski
All Graduate Theses and Dissertations, Fall 2023 to Present
Aquatic invasive species are one of the leading causes of native fish declines in the Southwestern United States. Channel Catfish Ictalurus punctatus were introduced into the Colorado River Basin, including the San Juan River, New Mexico, Colorado, and Utah for fishery enhancement during the 20th century. This introduction has contributed to the decline of native species and despite intensive mechanical removal efforts, the Channel Catfish population has persisted in the San Juan River. The Trojan Sex Chromosome approach is a promising eradication strategy that proposes the production and release of Trojan sex chromosome carriers (YY) to skew a targeted population’s …
Understanding And Predicting Precipitation Characteristics In The United States Through Machine Learning, Numerical Modeling And Measurements, Cody Luther Ratterman
Understanding And Predicting Precipitation Characteristics In The United States Through Machine Learning, Numerical Modeling And Measurements, Cody Luther Ratterman
All Graduate Theses and Dissertations, Fall 2023 to Present
Precipitation is one of the most important yet uncertain variables in the climate system. It varies dramatically in terms of timing, accumulation, rate, and phase, depending on location, season, circulation patterns, and atmospheric conditions. Precipitation forecasts, especially snowfall, are essential to supporting drought mitigation and water management in the Intermountain West. Because rainfall and snowfall lead to opposite effects on snowpack, accurately partitioning rain and snow is important to estimate snowpack levels, winter recreation, mountain ecosystems and runoff. The research findings in this dissertation have advanced the understanding and prediction of precipitation and snowpack in the U.S. by addressing the …
Glioma Segmentation In Mri Using A 3d Hybrid U-Net With Adaptive Self-Attention And Multi-Modal Fusion, Evan P. Savaria
Glioma Segmentation In Mri Using A 3d Hybrid U-Net With Adaptive Self-Attention And Multi-Modal Fusion, Evan P. Savaria
Computer Science Theses & Dissertations
Accurate glioma segmentation from multi-modal Magnetic Resonance Imaging (MRI) is essential for diagnosis, treatment planning, surgical guidance, radiation targeting, and longitudinal monitoring. MRI modalities such as T1, T1Gd, T2, and FLAIR provide complementary information for identifying clinically important tumor sub-regions, including enhancing tumor (ET), tumor core (TC), and whole tumor (WT). However, many existing segmentation methods do not fully preserve modality-specific information, process all modalities and slices uniformly, and often rely on a single shared fusion strategy for all sub-regions. These limitations can reduce segmentation accuracy, increase computational cost, and limit clinical interpretability.
This dissertation addresses these challenges through three …
The Role Of Phenotypic Plasticity And Bet-Hedging In Coping With Unpredictable Temperature Fluctuations In The Marine Annelid Ophryotrocha Labronica, Gabrielle Dawn Newton
The Role Of Phenotypic Plasticity And Bet-Hedging In Coping With Unpredictable Temperature Fluctuations In The Marine Annelid Ophryotrocha Labronica, Gabrielle Dawn Newton
Biological Sciences Theses & Dissertations
Coastal ecosystems are increasingly exposed to unpredictable temperature fluctuations, potentially favoring strategies that buffer populations against environmental uncertainty. This study examines how phenotypic plasticity and diversified bet-hedging contribute to variation in life-history traits under differing thermal predictability in the marine annelid Ophryotrocha labronica. After three generations at 24 °C, broods were reared for three generations under four thermal regimes: constant 24 °C (C24), constant 27 °C (C27), predictable fluctuations (Fp), and unpredictable fluctuations (Fu). Survival was assessed before and after acclimation to evaluate selective pressure among regimes. Age at maturity, fecundity, and growth rate were used to quantify plasticity (trait …
Modeling And Generating Crash Avoidance Behaviors In Safety-Critical Vehicle–Pedestrian Interactions Using Deep Reinforcement Learning, Qingwen Pu
Civil & Environmental Engineering Theses & Dissertations
Traffic crashes between vehicles and pedestrians arise from complex, split-second interactions in which both parties make rapid evasive decisions. Four fundamental gaps persist in existing research. Surrogate safety measures assume linear trajectories, failing to capture the curved movements of turning vehicles and crossing pedestrians at intersections. Single-agent modeling treats one party as a fixed obstacle, ignoring the joint decision-making that governs near-miss outcomes. The effect of vehicle type on pedestrian avoidance behavior—whether pedestrians respond differently to automated vehicles (AVs) than to human-driven vehicles (HDVs)—remains poorly understood. Finally, automated driving system development is hampered by a severe scarcity of large-scale, behaviorally …
Murat C. Mungan, Murat C. Mungan
Teacher Self-Efficacy And Its Relationship To Student Achievement: A Quantitative Analysis Using Map Growth Data, Joseph Todd Holzmann
Teacher Self-Efficacy And Its Relationship To Student Achievement: A Quantitative Analysis Using Map Growth Data, Joseph Todd Holzmann
Electronic Theses and Dissertations
One factor that has been widely studied is teacher self-efficacy. Teacher self-efficacy is often considered an indicator of teacher effectiveness and has been linked to a variety of positive educational outcomes. The purpose of this quantitative study was to examine the relationship between teacher self-efficacy and student achievement. Additionally, the study investigated whether teacher self-efficacy differed based on years of teaching experience, grade level taught, and subject area taught. The Teachers’ Sense of Efficacy Scale (TSES), developed byTschannen-Moran and Woolfolk Hoy, was used to measure teacher self-efficacy among 88 participants with corresponding student MAP Growth data available for analysis. Results …
Ai-Ready Libraries Require Ai-Ready Librarians: Building Organisational Capability For Digital Transformation, Salihin Mohammed Ali
Ai-Ready Libraries Require Ai-Ready Librarians: Building Organisational Capability For Digital Transformation, Salihin Mohammed Ali
Research Collection Library
Academic libraries worldwide are rapidly experimenting with artificial intelligence (AI) to enhance research, learning, discovery, operations, and user engagement. However, many institutions continue to approach AI adoption primarily through isolated pilots, individual experimentation, or technology-centric initiatives. While these efforts generate innovation, they often struggle to scale sustainably without corresponding organisational capability development. This presentation argues that AI-ready libraries require AI-ready librarians and proposes an organisational capability approach for sustainable AI transformation in academic libraries. Drawing from the development of a library-wide AI strategy plans at Singapore Management University, the presentation explores how AI capability-building can be operationalised across diverse functional …
Prediction Of Pasture Condition In The Kimberley Rangelands Of Western Australia Using Simple Classification Tree Models, Ben Nestor, Kath Ryan, Charles Martin, Philip Thomas, Chris Hetherington, Matthew Fletcher, Robert Sudmeyer, Karyn Reeves
Prediction Of Pasture Condition In The Kimberley Rangelands Of Western Australia Using Simple Classification Tree Models, Ben Nestor, Kath Ryan, Charles Martin, Philip Thomas, Chris Hetherington, Matthew Fletcher, Robert Sudmeyer, Karyn Reeves
Natural Resources Research Articles
Pasture condition assessments assist pastoralists, regulators, and policy makers in making informed decisions around livestock production and the preservation of natural resources in the Kimberley rangelands of Western Australia (WA). Reliable qualitative assessments of pasture condition require assessors with extensive expertise, which means frequent and reproducible assessments can be difficult to achieve. To develop a quantitative approach that can complement existing qualitative assessment approaches in the Kimberley, we investigated the use of simple classification tree models to predict pasture condition using assessment data from the Western Australian Rangeland Monitoring System (WARMS). Quantitative traits were derived from WARMS observation data for …
Id-More Vision: Real-Data Machine-Learning Assessment For A Digital-Twin-Inspired, Xr-Ready Rehabilitation Prototype, Rickey L. Clark
Id-More Vision: Real-Data Machine-Learning Assessment For A Digital-Twin-Inspired, Xr-Ready Rehabilitation Prototype, Rickey L. Clark
Master's Theses
Rehabilitation assessment often relies on periodic observation, while many XR prototypes show scripted rather than recorded-motion evidence. iD-MORE Vision is an offline pipeline trained on KIMORE and IRDS and linked through JSON packets to a two-mode Unity desktop prototype. Both datasets include controls and rehabilitation participants with neurologic, musculoskeletal, or mobility impairments. This improves relevance but does not clinically validate the system.
Under fixed subject-wise splits, the primary five-seed Random Forest predicted KIMORE clinician scores with MAE 6.087 ± 0.044 cTS and R² 0.568 ± 0.006; the subject-level R² interval crossed zero. The primary IRDS five-run CUDA GRU averaged 0.877 …
Kindergarten Aimsweb Ela Composite As A Predictor Of Third-Grade Reading Proficiency In A Rural, High-Poverty School District, Christi J. Gentry
Kindergarten Aimsweb Ela Composite As A Predictor Of Third-Grade Reading Proficiency In A Rural, High-Poverty School District, Christi J. Gentry
Electronic Theses and Dissertations
Reading proficiency by the end of third grade is a critical milestone as students transition from learning to read to using reading as a tool for learning. In Tennessee, this proficiency is especially significant because promotion and retention decisions are linked to student performance on the Tennessee Comprehensive Assessment Program (TCAP) ELA assessment. This quantitative, longitudinal study examined the extent to which kindergarten readiness, operationalized as kindergarten AIMSweb ELA Composite scores, predicts third-grade reading proficiency status in one rural, high-poverty school district. Using archival student-level data, this study analyzed kindergarten AIMSweb ELA Composite scores and third-grade TCAP ELA proficiency. Logistic …
Bpsou Grove Gulch Sedimentation Bay Draft Remedial Action Construction Completion Report (Ccr), Woodard & Curran
Bpsou Grove Gulch Sedimentation Bay Draft Remedial Action Construction Completion Report (Ccr), Woodard & Curran
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
A Comparison Of Survival, Growth, And Stress Resilience In Three Different Lineages Of The Pacific Oyster (Crassostrea Gigas) Farmed On The California Central Coast, Victoria F. Hanshaw
A Comparison Of Survival, Growth, And Stress Resilience In Three Different Lineages Of The Pacific Oyster (Crassostrea Gigas) Farmed On The California Central Coast, Victoria F. Hanshaw
Master's Theses
Aquaculture of Pacific oysters on the US West Coast is routinely impacted by seasonal unexplained mortality events. To better understand these large-scale mortality events in oyster aquaculture, shellfish growers and scientists in California have partnered together to conduct comparative, multi-estuary farm trials of discrete Pacific oyster (Crassostrea gigas) lineages. In this thesis we investigate how the more recently imported Midori lineage performs compared to the historically used Miyagi lineage, as well as a Hybrid (Midori x Miyagi) lineage. As part of a 7-month long field study from April-November of 2024 in Morro Bay and Tomales Bay, California, we evaluated …
Electromagnetic Enhancement Of A Potassium-Seeded Rotating Detonation Engine, Anthony Joseph Presto Jr.
Electromagnetic Enhancement Of A Potassium-Seeded Rotating Detonation Engine, Anthony Joseph Presto Jr.
Master's Theses
Rotating detonation engines offer a route to pressure-gain combustion by sustaining one or more detonation waves in an annular chamber supplied by continuous propellant injection. This thesis evaluates whether potassium seeding can make the high-temperature product flow of a hydrogen–air rotating detonation engine conductive enough to serve as the working fluid for magnetohydrodynamic acceleration. To the author’s best knowledge, the complete configuration modeled here has not been reported previously in open literature. This configuration consists of a hydrogen–air RDE with KOH-based potassium seeding, local conductivity estimates, and imposed Lorentz-force acceleration. The thesis therefore develops an initial computational model for this …
Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi
Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi
Master's Theses
Measuring students’ sense of belonging, characterized by feelings of acceptance, inclusion, and encouragement from teachers, remains a significant challenge in computing education. Prior research has associated this multidimensional construct with positive academic outcomes and has identified instructors’ growth- and fixed-mindset messaging as a potential influence. However, belonging is a complex and deeply personal experience that is difficult to capture through direct observation alone. Current measurement methods rely on self-report surveys, which may not capture every aspect of an experience that can also involve emotional and cognitive responses.
This thesis investigates whether combining EEG data recorded during a belonging questionnaire with …
Synthesis And Characterization Of Carbon Quantum Dots And Gold Nanoparticles For Norovirus Biosensing Applications In Water Systems, Breanne Evans
Synthesis And Characterization Of Carbon Quantum Dots And Gold Nanoparticles For Norovirus Biosensing Applications In Water Systems, Breanne Evans
Master's Theses
Rapid, reliable detection of viral pathogens remains a significant challenge across water-treatment and environmental monitoring systems, including drinking-water, wastewater, water reuse, and environmental surveillance applications. Waterborne viral contamination can pose substantial public-health risks, making early detection essential for protecting water quality and responding quickly to treatment failures or contamination events. Direct potable reuse (DPR) is one particularly demanding example because it requires continuous verification of treatment performance and the broader need for rapid virus monitoring extends across many water-treatment and environmental surveillance applications. Norovirus is a priority target because of its widespread occurrence in wastewater, environmental persistence, and exceptionally low …
Impact Of Repeated Serotonin 6 Receptor Activation On Weight And Anxiety In C57bl/6j And Btbr Mice, Pedro Flores
Impact Of Repeated Serotonin 6 Receptor Activation On Weight And Anxiety In C57bl/6j And Btbr Mice, Pedro Flores
Electronic Theses, Projects, and Dissertations
Selective Serotonin Reuptake Inhibitors (SSRI) are the most common form of medication prescribed to people with anxiety disorders. One of the most common side effects is weight gain. This weight gain often leads to the suspension of treatment. This has led to studies focusing on specific serotonin (5-HT) receptor targets for modulating depression and anxiety. Studies examining 5-HT6 antagonist treatment have shown that they reduce body weight as well as produce brain specific changes. Less is known regarding 5-HT6 receptor agonists, although previous literature has shown that exposure to high doses produces weight loss but not at lower doses, while …
Comparing 3-Connectedness And Roundness In Matroid Theory, Blanca Delia Larios
Comparing 3-Connectedness And Roundness In Matroid Theory, Blanca Delia Larios
Electronic Theses, Projects, and Dissertations
A matroid is a discrete mathematical object that abstracts and connects the various notions of independence found throughout mathematics. Such notions of independence include linear independence, algebraic independence, as well as notions of independence that arise in graph theory. There are many broad classes of matroids. Important examples include binary matroids, graphic matroids, regular matroids, uniform matroids, and various levels of connected matroids. Some of the most important problems in matroid theory involve characterizing classes of matroids so that such characterizations can be used to prove results concerning these matroid classes. This thesis is a study of two important classes …
The Relativity Of Education: Student Perspectives On Artificial Intelligence In Community College, Ashley Greta Magana
The Relativity Of Education: Student Perspectives On Artificial Intelligence In Community College, Ashley Greta Magana
Electronic Theses, Projects, and Dissertations
This hermeneutic phenomenological study examined how diverse community college students experience and make meaning of the integration of generative artificial intelligence (AI) into their educational contexts. Although AI is quickly transforming higher education through automated grading, personalized learning systems, and new models of assessment, the discourse surrounding its implementation remains dominated by administrators, faculty, and institutional stakeholders, while the perspectives of students, specifically community college students who are often historically underrepresented and economically marginalized, are systematically excluded. Most existing research is quantitative and centered on universities, leaving a critical gap in qualitative understanding of the most diverse population in higher …
Greenhouse Gas Flux Response In Biochar- And Compost-Amended Lawn Soils Under Simulated Water Saturation Conditions, Angel Salinas, Chu-Lin Cheng, Engil Pereira, Rafael M. Almeida, James Jihoon Kang
Greenhouse Gas Flux Response In Biochar- And Compost-Amended Lawn Soils Under Simulated Water Saturation Conditions, Angel Salinas, Chu-Lin Cheng, Engil Pereira, Rafael M. Almeida, James Jihoon Kang
School of Earth, Environmental, & Marine Sciences Faculty Publications
Understanding greenhouse gas emission dynamics in lawn soils is important for improving climate change mitigation strategies in urban and suburban landscapes. In this greenhouse mesocosm study, carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes were measured from 12 turfgrass soil columns arranged in an unreplicated, completely randomized 4 × 3 factorial design. Four amendment treatments (biochar, compost, bio-com [1:1 volume ratio of biochar and compost], and unamended control) were combined with three water-table conditions (full saturation, half saturation, and unsaturated), with a single column representing each treatment combination. Columns were irrigated at 1 cm day−1 for 24 days, …
An Integrated Model For Post-Hurricane Displacement, Shelter Demand And Shelter Allocation, Nirmal Adhikari
An Integrated Model For Post-Hurricane Displacement, Shelter Demand And Shelter Allocation, Nirmal Adhikari
All Theses
This thesis develops an integrated tract-level framework for estimating post-hurricane displacement, short-term shelter demand, long-term shelter demand, and shelter allocation under hurricane wind hazards. The framework combines parametric wind-field modeling based on HURDAT2 and EBTRK hurricane data with HAZUS-based fragility and loss functions, uninhabitability relationships, demographic factors, and an insurance-sensitive recovery model. Tract-level insurance adequacy is estimated using American Community Survey data, National Association of Insurance Commissioners premium data, and the National Risk Index, using five scenario-based models; the combined home-value and hazard-risk model is adopted for final analyses. To evaluate post-disaster housing capacity, the study estimates the number of …
Painting A Scene: 3d Painterly Rendering From Curves To Rebelle, William M. Luttrell
Painting A Scene: 3d Painterly Rendering From Curves To Rebelle, William M. Luttrell
All Theses
Stylized 3D rendering has seen much development and success over the past few years. From Spider-Man: Across the Spider-Verse to The Bad Guys, many studios have developed tools to incorporate stylistic elements from graphic novels, comic books, watercolor paintings, and more into their productions. This stylization process incorporates the pacing, visual style, and themes from the source medium into the animated work, allowing a much greater freedom of expression for artists and directors.
Inspired by these films as well as the needs of the short film Kate Shelley and the Bridge of Darkness currently in production, This paper presents …
Characterizing Microplastics In Flood Sediments After Hurricane Helene In Asheville, North Carolina, Abigail Sgan
Characterizing Microplastics In Flood Sediments After Hurricane Helene In Asheville, North Carolina, Abigail Sgan
All Theses
Microplastics are contaminants of emerging concern whose ubiquity across natural environments results in their involvement in many kinds of natural processes, including transportation and deposition in natural systems. The purpose of this thesis is to characterize microplastics and determine the mechanisms that affect their distribution, transport, and sequestration within known Hurricane Helene flood deposits in fluvial and Southern Appalachian wetland environments after Hurricane Helene in Asheville, North Carolina. Four fluvial and four Southern Appalachian wetland environments were sampled after Hurricane Helene. Samples collected in fluvial environments were taken as grab samples from surficial sandy flood deposits left behind by flooding …