Physical Sciences and Mathematics Commons^™

Predicting Biomechanical Risk Factors For Division - I Women’S Basketball Athletes, Aayushi Shah, Vanaja Agarwal, Dhairya Shah, Harman Jani, Sristi Sharma, Kaya Tolga, Christopher Taber, Mehul Raval

School of Computer Science & Engineering Faculty Publications

Collegiate basketball is characterized by high-impact movements such as jump landings, making athletes more susceptible to injuries. Critical biomechanical factors like knee flexion, lateral trunk flexion, and foot landing asymmetry are strongly associated with injury risk. This study aims to predict six biomechanical risk factors in the landing error scoring system (LESS). The dataset comprises 8600 video frames of counter-movement jumps (CMJs) from 17 NCAA Division I female basketball athletes, recorded from frontal and lateral perspectives and annotated using a customized error annotation algorithm. The study uses the You Only Look Once (YOLOv5nu) model to analyze the basketball athletes’ CMJ …

Navigating Together: The Conav Testbed And Framework For Benchmarking Cooperative Localization, Rohith Boyinine, Jayanth Ammapalli, Anusna Chakraborty, Rajnikant Sharma, Kevin Brink, Clark N. Taylor

Faculty Publications

This paper presents CoNaV, a comprehensive framework for creating a multi-vehicle cooperative localization (CL) testbed designed to support the benchmarking, development, and deployment of cooperative navigation algorithms. Given the essential role of CL in improving localization accuracy for both defense and civilian applications, CoNaV provides a robust environment for rigorously validating algorithms under real-world conditions. By establishing a benchmark for CL algorithms, CoNaV lays a foundation for advancing research into more sophisticated and distributed CL solutions. This framework highlights the potential of cooperative navigation to enhance multi-vehicle operations and offers a scalable, practical approach for future developments in CL technology.

Revised Final Multi-Pathway Residential Metals Abatement Program Plan, Atlantic Richfield Company, Butte Silver Bow

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Fault Box Modeling Of Dip Slip Faults: A Framework For Fault Box Design And Future Studies, Hailey Pressnell

Master's Theses

The behavior of soils during surface fault rupture is a serious concern in the planning and design of infrastructure that may be located within or near a fault zone. Challenges associated with developing mitigation measures for surface fault rupture include the uncertainty of fault rupture and the variability of fault behavior. Current analytical procedures define surface fault rupture according to the type of fault movement (strike slip, normal or reverse), the amount of displacement on the fault, and the mechanics of the material overlying the fault. The purpose of this thesis is to reconfirm analytical solutions and gain a better …

Knowledge And Ontology Enhanced Approach To Natural Language Understanding (Koe-Nlu) In Computational Social Media And Healthcare, Naga Usha Gayathri Lokala

Theses and Dissertations

Natural Language Understanding (NLU) faces both opportunities and challenges as the amount of social media and healthcare data grows. This is particularly evident in context-sensitive applications such as evaluating cognitive health, identifying mental health symptoms, and monitoring drug abuse. Even though traditional NLU models work well for processing language in a wide range of areas, they often lack the ability to understand language in a specific domain, reason in context, and incorporate structured external knowledge. This dissertation talks about the Knowledge and Ontology Enhanced Approach to Natural Language Understanding (KOE-NLU), a new framework that is meant to make NLU systems …

Dataset On Indoor And Outdoor Pm2.5 Concentrations At Two Residences Using Low-Cost Sensors In The Rio Grande Valley Region Of South Texas, Kabir Bahadur Shah, Sai Deepak Pinakana, Mkhitar A. Hobosyan, Armando Montes, Amit U. Raysoni

School of Earth, Environmental, & Marine Sciences Faculty Publications

Fine particulate matter (PM2.5) is one of the criteria air pollutants associated with adverse respiratory and cardiovascular health effects. This dataset contains hourly and daily averaged measurements of PM2.5 concentrations (µg/m3) collected from two residential homes in the Rio Grande Valley (RGV) Region of South Texas, using PurpleAir-II-SD low-cost sensor. In addition, the dataset also includes temperature (ºC) and relative humidity (%) measured by the sensors. The data was collected for one month during the summer season from indoor (kitchen) and outdoor (front yard) environments at two locations: Home-1 in Weslaco City from June 16, 2024, to July 16, 2024, …

Examining The Presence And Effects Of Coherence And Fragmentation In The Gulf Of Maine Fishery Management Network, Derek A. Katznelson, Antonia Sohns, Dongkyu Kim, Evelyn Roozee, William Donner, Andrew M. Song, Jasper R. De Vries, Owen Temby, Gordon M. Hickey

School of Earth, Environmental, & Marine Sciences Faculty Publications

Natural resource management networks cohere due to mutual dependencies and fragment, in part, due to the perceived risks of interaction. However, research on these networks has tended to accept coherence a priori rather than problematizing dependence, and few studies exist on interorganizational risk perception. This article presents the results of a study operationalizing these concepts and measuring the distribution of three types of dependence (capital, legitimacy, and regulatory) and two types of perceived risk (performance and sanction) among nearly fifty stakeholder groups and organizations participating in the management of fisheries in the binational Gulf of Maine. The analysis reveals an …

Modification Of Nanoparticles For Designed Interfaces, Tony Lee Neely, Jr.

Theses and Dissertations

The work contained herein, is focused on the design, synthesis, and characterization of polymer nanocomposite interfaces and the property enhancement afforded from said interface design. Through the use of reversible addition fragmentation chain transfer (RAFT) polymerization for the grafting of polymer chains to silica nanoparticles, the surface of silica nanoparticles can be manipulated to tune the properties of the nanocomposite as a whole.

In the first part of this work, heterogeneity is introduced onto the surface of silica nanoparticles via a sequential RAFT polymerization to afford a bimodal brush system. A densely grafted, short brush population is polymerized from the …

Oriented Surface Immobilization Of Antibodies Using Enzyme-Mediated Site-Specific Biotinylation For Enhanced Antigen-Binding Capacity, Emily Beitello, Kwame Osei, Trent Kobulnicky, Faith Breausche, Jon A. Friesen, Jeremy D. Driskell

Faculty Publications – Chemistry

The effectiveness of surface-immobilized antibodies is often diminished by improper antibody orientation and limited stability, impeding the analytical performance of biosensors. Here, we report a novel enzyme-mediated strategy to biotinylate the Fc region of an anti-horseradish peroxidase (anti-HRP) antibody with site-specificity that enables oriented immobilization on a streptavidin-functionalized surface. Microbial transglutaminase (mTG) catalyzes the covalent coupling between the amine functional group on a biotin analogue (NH₂-PEG₄-biotin) and the side chain of a privileged glutamine residue (Q295) located on the heavy chain Fc region of IgG antibodies. For comparison, an anti-HRP antibody was biotinylated using an amine-reactive …

Rhenium Chalcogenide Clusters Containing Para-Substituted Phenylacetylide Ligands: Synthesis, Characterization, And Investigation Of Substituent Effects On Spectroscopic And Electrochemical Properties, Katherine L. Helmink, Cory A. Hicks, B. Sage Lauper-Cook, Steven J. Peters, Christopher J. A. Daley, Yann Molard, Lisa F. Szczepura

Faculty Publications – Chemistry

Four new organometallic [Re₆Se₈]²⁺-based cluster complexes containing para-substituted phenylacetylide ligands, [Re₆Se₈(PEt₃)₅(C≡C–C₆H₄–X)](SbF₆) where X = NO₂, CO₂Me, CH₃, and OMe, have been synthesized and fully characterized using ¹H, ¹³C{¹H} and ³¹P{¹H} NMR, IR, and UV–vis spectroscopy, HRMS, and elemental analysis. Three of these cluster complexes, [Re₆Se₈(PEt₃)₅(C≡C–C₆H₄–NO₂)]⁺, [Re₆Se₈(PEt …

Automatic Identification And Visualization Of Reaction Mechanisms Contained Within Direct Dynamics Simulations, Trent Kobulnicky, Emmanuel Boafo, George L. Barnes

Faculty Publications – Chemistry

Direct dynamics simulations are employed in many areas of chemistry and biochemistry. When paired with an appropriate underlying ab initio, semiempirical, or DFT-based potential energy surface and proper sampling of initial conditions, direct dynamics simulations provide an atomic-level view of the reaction dynamics within the system of interest, yielding considerable fundamental insights. Moreover, when a sufficient number of simulations are conducted, they provide a wealth of information regarding the overall trends in reactivity. However, they also generate large data sets that often require significant manual interpretation through inspection or developing case-specific analysis techniques. Here, we present an analysis method …

Synthesis Of Alkyl Substituted Carbatripyrrins And Their Application To The Preparation Of Carbaporphyrins And Oxacarbaporphyrins, Ian A. Mclauchlan, Bethany K.X. Overbey, Tyler J. Smolczyk, John J. Woods, Timothy D. Lash

Faculty Publications – Chemistry

Unsubstituted carbatripyrrins have previously been shown to be useful intermediates in the synthesis of benzocarbaporphyrins and related core-modified analogues. However, the absence of substituents often resulted in the formation of poorly soluble products. In this study, four examples alkyl substituted carbatripyrrins were constructed by base-catalyzed condensation of dihydrofulvenes with pyrrole aldehydes. Further reaction with a pyrrole dialdehyde in the presence of trifluoroacetic acid afforded a series of carbaporphyrins, while reactions with 2,5-furandicarboxaldehyde generated oxacarbaporphyrins. These results demonstrate that alkyl substituted carbatripyrrins are promising precursors to new carbaporphyrinoid structures.

Synthesis Of Phenaliporphyrin, A Pah-Porphyrin Hybrid, From An Acenaphthene-Fused Cyclopropane Dialdehyde, Sunday Oladapo Jacob, Emily D. Harris, Melissa A. Mathius, Deyaa I. Abusalim, Gregory M. Ferrence, Timothy D. Lash

Faculty Publications – Chemistry

Phenaliporphyrin, a new aromatic benziporphyrin derivative, has been synthesized from an annulated cyclopropane dialdehyde intermediate. Corey-Chaykovsky cyclopropanation of dimethyl acenaphthylene-1,2-dicarboxylate gave a cyclopropane diester, and this was converted to the corresponding bis-Weinreb amide. Reduction with lithium aluminum hydride afforded an unstable dialdehyde and subsequent acid-catalyzed condensation with a tripyrrane dicarboxylic acid, followed by oxidation with aqueous ferric chloride, gave the targeted porphyrinoid system. This involves ring expansion of the acenaphthylene precursor to generate the phenalene unit. Phenaliporphyrin exhibits a porphyrin-like UV–vis spectrum with a Soret band at 443 nm and a relatively intense Q-band at 601 nm. The proton NMR …

Hyper B-Ary Representations Of A Number, Mingway Wang

Masters Theses

In this work, we summarize combinatorial, analytical, and computational properties of Stern's diatomic sequence, and do the same for a generalization of a combinatorial property of this sequence to higher bases. We then construct special ``bit conversion'' functions $g_{b}$ that allows us to find a semi-explicit formula for the generalized sequences. Lastly, we analyze some of the properties of these $g_{b}$ functions.

Catalytic Innovation For Sustainable Styrene Production: Green Chemistry Strategies Utilizing Octahedral Ruthenium (Ii) Complexes Supported By A Single Bipyridine Ligand, Kennedy G. Musso, Brandon Quillian, Clifford Padgett, Jose Jimenez

College of Graduate Studies: Theses & Dissertations

This study investigates: 1) the synthesis and reactivity of the mono- substituted systems, [κ²-(t-bipy)Ru(NCMe)2(Ph)(PR3)][BArF'] supported by different ancillary ligands PR3 = (P(OCH3)3 and P(CH3)3) and a single bidentate ligand, 4,4′-di-tert-butyl-2,2′-bipyridine (t-bipy), and 2) UV/heat formation of di-PR3 and tri-PR3 systems supported by a single bidentate ligand to better understand the mechanism of styrene production. Utilizing [(η6-p-cymene)RuI(µ-I)]2 (1), the complexes (η6-p-cymene)RuI2(P(OCH3)3) (2) and (η6-p-cymene)RuI2(P(CH3)3) (3) were synthesized and phenylated to produce (η6-p-cymene)RuI(Ph)(PR3) (6; PR3 = P(OCH3)3 and 7; PR3 = P(CH3)3). Complex 4, (η6-p-cymene)RuCl2(P(CH3)3), was also synthesized and phenylated to produce (η6-p-cymene)RuClPh(P(CH3)3) (5) to understand the impact of chloride versus iodine …

Optimal Data Splitting Methods, Sujay Mudalgi

Theses and Dissertations

In predictive modeling, effective data splitting is crucial for creating statistically representative training and validation sets. The state-of-the-art data splitting methods are based on minimizing the energy distance between the split subsets. However, there are a number of limitations in the existing methods, which this dissertation aims to address. First, the existing methods were computationally inefficient. Thus, Chapter 2 proposes a method to scale up these approaches for big data. Here, we introduce scalable Twinning (s-Twinning), which significantly improves the execution speed of data splitting without sacrificing accuracy. Second, the existing methods did not consider the predictive relationship in the …

Unraveling The Reactivity Of Nitrate Ester Explosives: Insights From Femtosecond Time-Resolved Mass Spectrometry And Computational Chemistry, Erica Britt

Theses and Dissertations

This dissertation uncovers the ultrafast molecular mechanisms underlying the decomposition of nitrate ester explosives—nitroglycerin (NG), ethylene glycol dinitrate (EGDN), and amyl nitrate—through the integration of femtosecond time-resolved mass spectrometry and advanced computational chemistry. Although these compounds play fundamental roles in both military and civilian contexts, the precise molecular dynamics governing their pronounced reactivity and impact sensitivity have remained inadequately characterized. Our research establishes that low O–NO2 bond dissociation energies are the primary driver of ultrafast fragmentation and high reactivity in all three esters. The distinctive molecular architectures of these esters dictate their explosive properties: NG’s tri-nitrate configuration leads to exceptional …

Predictive Inference For Ion Concentration With Machine Learning And Bayesian Methods, Alexandra B. Ulbing

Theses and Dissertations

Ultraviolet--visible (UV--Vis) spectroscopy produces high-dimensional signals that are strongly collinear, shift with concentration, and exhibit heteroskedastic, non-Gaussian noise. These features make supervised regression from spectra to ionic concentrations statistically challenging and limit the reliability of methods that assume linear structure or homoscedastic errors.

This dissertation develops two complementary frameworks for prediction and uncertainty quantification in UV--Vis spectroscopic regression: (1) frequentist stacked ensembles combined with distribution-free conformal prediction, and (2) Bayesian hierarchical modeling and Bayesian stacking. Together, they provide a unified view of model-based and distribution-free uncertainty across nickel and nickel--cobalt datasets.

The frequentist component builds ensembles of Functional Data Analysis …

Relationship Extraction Using Retrieval Augmented Generation For Biomedical Dataset, Jannat Jannat

Theses and Dissertations

With the increasing number of structured and unstructured data, obtaining reliable information effectively has become crucial. In the biomedical domain, extracting information from the scientific papers is crucial in order to stay up-to-date with accurate information, given the increased pace by which new research studies are published. This work focuses on identifying relationships between entities that are extracted from the abstracts and titles of biomedical research papers. In this work, we developed a Retrieval Augmented Generation (RAG) based system to automatically identify relations between biomedical entities. We evaluate multiple open source Large Language Models (LLMs) and the number of examples …

Cost-Effective Strategies For Feral Swine Control: Exploring Trapping Equipment Cooperatives, Phil Kenkel, Riza Radmehr, Rodney Holcomb, Mckenzie Boyce

Human–Wildlife Interactions

Feral swine (Sus scrofa) in the United States have become a growing concern, with a population of ≥6 million and causing annual damages of ≥$1.5 billion USD. Because of their high reproductive capacity, effective control methods are crucial to reducing or slowing their population growth. While remotely monitored and triggered traps have proven to be an effective control strategy, the cost of sophisticated trapping equipment, which can cost ≥$7,000 USD, is often cost prohibitive for many landowners. Despite the pressing need to address the challenge of making effective feral swine control methods more affordable, there are few studies …

Characterization And Optimization Of Sand And Tung Oil-Based Resins For Binder-Jet 3d Printing, Daniel I. Ajiola

College of Graduate Studies: Theses & Dissertations

Binder-jet 3D printing as a transformative technology in additive manufacturing, offers the ability to fabricate complex structures with diverse materials. This thesis investigates the use of a sustainable tung oil-based resin to create composites, exploring the potential for an eco-friendly alternative to synthetic binders.

The aim of this research is to develop and characterize a bio-based resin formulation, using tung oil as the primary binder, for application in binder-jet 3D printing with sand as the reinforcement. The resin formulation was prepared by combining tung oil, n-butyl methacrylate, divinylbenzene, and di-tert-butyl peroxide in precise proportions, ensuring a balanced mixture that supports …

Application Of Machine Learning And Large Language Models In Healthcare For Data Prediction And Summarization, Chiazam Chisom Izuchukwu

College of Graduate Studies: Theses & Dissertations

This study aims to examine the use of machine learning (ML) and large language models (LLMs) in healthcare to enhance disease prediction, clinical decision-making, and information management. Five supervised ML models—Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Decision Trees (DT), and Naïve Bayes (NB)—on three different computing platforms—Google Colab, Databricks, and Snowflake—were employed for disease classification. Data preprocessing included treating missing values, encoding categorical variables utilizing one-hot-encoding, feature scaling when needed, and tackling class imbalance with Synthetic Minority Over-sampling Technique (SMOTE) before an 80-20 train-test separation. Models were created with Scikit-learn (Google Collab), Spark MLlib (Databricks), and …

Machine Learning Methods For Intrusion Detection And Response In Network Security, Ayomide Oyemaja

College of Graduate Studies: Theses & Dissertations

Intrusion Detection Systems (IDS) play a crucial role in computer network security by identifying malicious activities and potential cyberattacks. This thesis combines machine learning and cybersecurity by applying Reinforcement Learning (RL) in intrusion detection and response using the NSL-KDD dataset.

We designed and implemented a Q-learning framework where an agent learns to classify network traffic over time by interacting with the environment and receiving rewards based on detection accuracy. We also look at the importance of feature selection and classification techniques and how effective they are in improving model performance, reducing the complexity of computation, and producing more desirable results. …

Synthesis And Characterization Of A Biobased Polymer From Tung Oil And Pine Rosin & Characterization Of Polyhydroxybutyrate., Arijanet P. Osumah

College of Graduate Studies: Theses & Dissertations

This thesis presents two independents but thematically aligned research projects focused on the development and evaluation of sustainable polymers. The first involves the synthesis and characterization of a biobased polymer derived from tung oil and pine rosin. Tung oil, which is a triglyceride was chemically modified to produce tung oil diglyceride (TDG), which subsequently reacted with abietic acid-rich pine rosin to yield tung oil abietate (TOA), a biobased monomer. The TOA monomer was polymerized with butyl methacrylate (BMA) and divinylbenzene (DVB) using di-tert-butyl peroxide (DTBP) as a thermal initiator. The resulting polymer was thoroughly characterized using Fourier transform infrared spectroscopy …

Dynamic Analysis Of Malware Detection Using Customized Payloads: Examining The Effectiveness Of Manual And Automated Approaches In Web Applications, Jiban Krisna Das

College of Graduate Studies: Theses & Dissertations

Web applications are becoming the prime targets for cyber-attacks, where SQL injection (SQLi) and Cross Site Scripting (XSS) are the most exploited vulnerabilities. The study explores a novel approach using customized payloads to examine the effectiveness of manual and automated techniques of malware detection. This dynamic approach can effectively generate attack payloads and identify the vulnerabilities in a website thereby strengthening website security measures. This research focuses on dynamic analysis in a controlled environment while testing and analyzing SQL and XSS payloads under varying security conditions. This quantitative analysis involves crafting targeted payloads to bypass Web Application Firewall (WAF) filters …

Application Of Semantic Segmentation To An Automatic Target Recognition Problem, Bruce W. Rush Jr.

College of Graduate Studies: Theses & Dissertations

Synthetic Aperture Radar (SAR) is an active remote sensing system commonly used in aerial reconnaissance. SAR penetrates cloud cover and vegetation by recording reflected energy pulses. The resulting information content is difficult to interpret due to vast clutter data and sparse target data. The time-consuming process of analyzing SAR imagery can be greatly reduced by implementing an Automatic Target Recognition (ATR) algorithm. Convolutional Neural Networks (CNN) are capable of extracting identification features from SAR data content. Further research in this field indicates that high performing models are insufficiently robust due to high clutter correlation among classes in the Moving and …

Impact Of Y-Mixer Geometry And Flow Rate Modulation On Chemical Gradient Generators In Microfluidic Devices, Elizabeth Thurston Hutton

College of Graduate Studies: Theses & Dissertations

Various microfluidic structures are devised to generate tunable, stable spatiotemporal chemical gradients for single-cell studies. This work addresses the role of Y-mixer junctions in generating nonlinear gradients by increasing the width of one arm (bias), which is suspected to cause premature diffusion within the mixer. This study introduced a cinching feature to narrow the wider arm locally and redefine the junctions of these biased Y-mixers using four novel geometries defined by a 5-micrometer drawing rule. Furthermore, three flow rate factors allowed us to explore the impact on the generated gradient landscapes. The results showed that the four novel designs similarly …

Response Of Galactic Disks To Dark Matter Halo Triaxiality, Alex J. Hutton

College of Graduate Studies: Theses & Dissertations

In this study we examine the influence of dark matter halo triaxiality on the evolution of galactic disks. We do this by running a series of collisionless N-body models. In a first set of models we place the galactic disk within an oblate halo at various orientations and examine the resulting evolution. In our second set we construct fully self-consistent models of a stellar disk embedded within a spherical halo, with an impacting external dark matter dwarf galaxy. After evolving the simulations for a Hubble time, we examine the disk orientation and warping along with other quantities such as bar …

Majority Decision Using Top-Performing Neural Networks Models For Improved Credit Risk Prediction, Vincent Dey

College of Graduate Studies: Theses & Dissertations

Credit risk prediction remains both a challenging and high-interest problem due to the inherently unbalanced nature of financial datasets and the continuous drive for higher pre- dictive precision. In this work, I build upon previous advancements in credit risk modeling and introduce an ensemble-based Artificial Neural Network (ANN) architecture designed to enhance classification performance. By leveraging a selective ensemble of decision net- works, this approach not only improves prediction accuracy but also mitigates the chal- lenges posed by imbalanced data distributions. While the primary focus is on credit risk prediction, my analysis demonstrates that the proposed model can be effectively …

Applying The Lagrangian Variational Method To Atom Interferometry, Jeffrey W. Heward

College of Graduate Studies: Theses & Dissertations

Atom interferometry in Bose-Einstein condensate systems has emerged as a promising technique for precision metrology. The dynamics of these systems are well-described by the Gross-Pitaevskii equation (GPE), but direct numerical solution of this equation is infeasible for realistic systems. We use the Lagrangian Variational Method (LVM) to approximate solutions of the GPE in 1D and 3D, and we compare the LVM results to the exact solutions. We also present 3D LVM results for a case where numerical solution of the GPE is infeasible.