Physical Sciences and Mathematics Commons^™

(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 …

Structural Geology Of The Brady Mountain Area, Ouachita Mountains, Arkansas: Integrating Field Mapping, Geospatial Techniques, Photogrammetry And 3d Modeling For Structural Analysis, Emmanuel Darko, Zachariah Fleming

Electronic Theses and Dissertations

Much of the Ouachita orogenic belt, representing the deformed Paleozoic rocks flanking the southern margin of the North American craton, is buried beneath post-orogenic Mesozoic and Tertiary sediments composing the Gulf Coastal Plain. The Ouachita Mountains of Arkansas and Oklahoma are the largest areas of outcrop for the Pennsylvanian-age Ouachita orogenic belt, making it an ideal place to study the orogeny. This study focuses on the Brady Mountain area within the Benton Uplift, the orogenic core of the Ouachita Mountains in western Arkansas. The region is comprised of numerous ridges trending nearly east-west and are for the most part densely …

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 …

Molecular Design And Engineering Of Luminophores For Aggregation Induced Electrogenerated Chemiluminescence, Jesy Alka Motchaalangaram

Dissertations

Most conventional luminophores produce intense emissions in solutions but suffer from weak emissions or quenching when aggregated in poor solvents due to intermolecular interactions, such as π-π stacking. This phenomenon is known as aggregation caused by quenching (ACQ), limits their applications in their solid state. In contrast, aggregation induced emission (AIE) is a phenomenon in which luminophores are weak- or non-emissive in solution but emit intensively in their aggregated or solid states. AIE has enabled significant advancements in various real-world applications and has inspired new areas of research. The combination of AIE with electrogenerated chemiluminescence (ECL) has resulted in a …

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 …

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 …

Summary Of Pine Valley Area Groundwater Studies, Melissa Stamp, Bethany Neilson, Anna Mcentire, Burdette Barker, Lisa Welsh, Joanna Endter-Wada, Brian Steed

Reports

The Utah Division of Water Resources contracted with Utah State University to document key scientific and policy information related to the current water conflict between Iron and Beaver Counties over the development of the Pine Valley Water Supply Project (PVWSP). The proposed PVWSP would pump groundwater from Pine Valley in Beaver County and pipe it southeast to the Cedar City region of Iron County served by the Central Iron County Water Conservancy District (CICWCD). Numerous concerns about the project have been raised by Beaver County and other interested parties. A number of these concerns are related to different understandings or …

Predicting Cryptocurrency Prices Using Stochastic Modeling, Reem Hani Al Omari

Theses

Cryptocurrencies are digital currencies that operate independently of central banks and governments. They were designed to overcome the limitations of traditional financial systems through a decentralized, peer-to-peer electronic cash mechanism. Trading in cryptocurrencies offers several advantages, including decentralized and efficient transactions, reduced costs through the elimination of intermediaries, investment opportunities across exchanges, and seamless cross-border remittances. Modeling cryptocurrency prices is therefore essential, not only due to these advantages but also because of the substantial market capitalization of cryptocurrencies, estimated to exceed 900 billion dollars according to CoinMarketCap [6]. The main objective of this thesis is to propose a predictive framework …

A Bayesian Optimisation With Segmentation Approach To Optimising Liquid Handling Parameters, Estefania Yap, Viet Huynh, Calvin Vong, Peter Vogel, Viv Louzado, Thomas Barnes, Buser Say, Michael Burke, Dana Kulić, Aldeida Aleti

Research outputs 2022 to 2026

The automation of liquid handling has become integral in speeding up pharmaceutical development for faster drug development and more affordable treatments. However, the optimal parameters which define the aspirate and dispense procedures vary between liquids and liquid volumes, limiting transfer accuracy and precision. Even state-of-the-art liquid handling devices offer predefined parameters for only a handful of liquids and volumes, resulting in novel parameter sets being defined via a manual, time-consuming process. In this study, we propose an experimental framework for automating the optimisation of liquid class parameters for arbitrary liquids. Within our framework, we propose an optimisation and segmentation algorithm, …

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 …

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 …

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 …

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 …

Marsanywhere: Dataset And Cross-View Diffusion Model For Satellite-To-Ground View Synthesis With Mars Data, Benjamin T. Hinchliff

Master's Theses

Satellite-to-ground view synthesis aims to create a realistic ground view image from a corresponding satellite view image. This is a well-studied problem for street level imagery, with good results being achieved by using modern image synthesis techniques such as diffusion models. However, despite the public availability of satellite and ground level imagery on Mars, these techniques have yet to be applied to the domain due to difficulties in collating and processing the data into a usable form. We address this deficiency by creating a dataset consisting of ground view panorama imagery from the Perseverance rover, along with associated satellite view …

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 …

Deep Learning With Kalman Filter, Rexford Julius Quaye

Electronic Theses and Dissertations

This thesis presents an extension of the Kalman filter to handle nonlinear and non-Gaussian systems. The standard Kalman filter is optimal under Gaussian assumptions but struggles with more complex noise models. This work introduces a novel loss function based on the Mahalanobis distance, which incorporates the covariance structure of measurement errors, enabling the filter to adapt to non-Gaussian scenarios. The neural network framework is applied to predict the system’s process model, while retaining the classical Kalman measurement update. The proposed methodology is demonstrated through examples of car position and rocket altitude tracking. The results show that the new approach performs …

Software Developer Job Satisfaction: Interpretable Machine Learning Insights From The Stack Overflow Developer Survey, Reagan E. Hoopes

All Graduate Theses and Dissertations, Fall 2023 to Present

Many researchers have investigated the factors influencing software developer workplace outcomes, such as job satisfaction, due to the central role of the tech industry in the global economy and the specialized expertise of software developers. Past research has often relied on small surveys and traditional analysis methods, with limited use of modern machine learning techniques. This study introduces an efficient and scalable approach to analyzing software developer job satisfaction using interpretable machine learning.

We use data from the 2019 and 2024 Stack Overflow Developer Surveys, an annual survey of software developers worldwide that encompasses a broad range of topics, including …

Bias Testing And Mitigation In Llm-Based Code Generation, Dong Huang, Jie M. Zhang, Qingwen Bu, Xiaofei Xie, Junjie Chen, Heming Cui

Research Collection School Of Computing and Information Systems

As the adoption of LLMs becomes more widespread in software coding ecosystems, a pressing issue has emerged: does the generated code contain social bias and unfairness, such as those related to age, gender, and race? This issue concerns the integrity, fairness, and ethical foundation of software applications that depend on the code generated by these models but are underexplored in the literature. This paper presents a novel bias testing framework that is specifically designed for code generation tasks. Based on this framework, we conduct an extensive empirical study on the biases in code generated by five widely studied LLMs (i.e., …

Reservoir Characterization Of The Clarksville Formation In Red River County, Texas, Matthew Allen Parker

Electronic Theses and Dissertations

The Upper Jurassic Clarksville Formation in northern Texas and southern Oklahoma is a productive but poorly understood sandstone–conglomerate unit with unresolved questions regarding its depositional environment and sediment provenance. This study evaluates the depositional setting, spatial distribution, and diagenetic controls of the Clarksville Formation using integrated core and well log analyses in Red River County, Texas. Three cores (Lennox Unit #1, Reeder Oil Unit #2, and Reeder Oil Unit #7) were analyzed for lithology, mineralogy, porosity, permeability, and fluid saturation, and correlated with 137 well logs to map formation thickness and regional trends.

Four lithofacies were identified based on core …

Wildfire Smoke And Public Health: Comparing 2023 Canadian Wildfire Events With Hospital Admissions In Douglas County, Nebraska, Jeremy Poell

Capstone Experience: Master of Public Health

Wildfires are becoming increasingly common in Canada and the United States. Smoke produced from these fires creates a multitude of air pollution constituents that can cause breathing and other health issues for humans, particularly those with asthma and other respiratory conditions. Of these pollutants, PM2.5 (particulate matter that is 2.5 microns or smaller) is particularly problematic as these particles are inhaled deep into lung tissue, where they create inflammation and oxidative stress. Poor air quality can also trigger asthma and respiratory issues, leading to an increase in emergency department admissions for breathing treatments. The goal of this study is to …

Geochemical Analysis Of The Eagle Ford Shale In Webb And Dimmit Counties, Tx, Natalie G. Girlinghouse

Electronic Theses and Dissertations

The Late Cretaceous Eagle Ford Shale of South Texas is a mixed carbonate–siliciclastic succession that serves as both a prolific hydrocarbon source and reservoir. This study integrates chemostratigraphy, mineralogical analysis, and elemental ratio proxies to reconstruct depositional environments and assess controls on detrital influx, paleoproductivity, and redox conditions across multiple cores in Webb and Dimmit counties. Major, trace, and redox-sensitive elements were evaluated alongside Total Organic Content (TOC) and carbonate content to identify stratigraphic trends and environmental shifts.

Results reveal distinct geochemical signatures between the Upper and Lower Eagle Ford Shale, with the Lower Eagle Ford characterized by elevated Al-rich …

Proverag: Provenance-Driven Vulnerability Analysis With Automated Retrieval-Augmented Llms, Reza Fayyazi, Stella Hoyos Trueba, Michael Zuzak, Jay Yang

Institute for Informatics and Applied Technology Scholarship

In cybersecurity, security analysts constantly face the challenge of mitigating newly discovered vulnerabilities in real-time, with over 300,000 vulnerabilities identified since 1999. The sheer volume of known vulnerabilities complicates the detection of patterns for unknown threats. While LLMs can assist, they often hallucinate and lack alignment with recent threats. Over 40,000 vulnerabilities have been identified in 2024 alone, which are introduced after most popular LLMs’ (e.g., GPT-5) training data cutoff. This raises a major challenge of leveraging LLMs in cybersecurity, where accuracy and up-to-date information are paramount. Therefore, we aim to improve the adaptation of LLMs in vulnerability analysis by …

Bridging The Gap Between Network Science And Network Systems To Identify And Mitigate Cyber Risk: Identify And Mitigate Backdoor Attacks On Graph Neural Networks And On Complex Systems, Sabah Ettahri

Electrical & Computer Engineering Projects for D. Eng. Degree

This doctoral project aims to bridge the gap between graph theory and network science to identify and mitigate cyber risk, represented as a CY-Triangular Network that connects different networks. The CY-Triangular Framework is a cybersecurity system that integrates graph theory and network science through an interoperable learning approach. The objective of this project is to bridge the gap between two domains: network science and network systems. Accordingly, it examines one representative network from each field, focuses on a complex system network, and explores Graph Neural Networks (GNNs). The connection between these domains lies in graph theory. This research demonstrates that …