Physical Sciences and Mathematics Commons^™

Strategic Identification Of Prognostic Biomarkers For Knee Osteoarthritis Via Optimized Regression Techniques, Varun Sri Sai Vemuri

Selected Full-Text Master Theses 2021-

Knee Osteoarthritis (KOA) is a progressive musculoskeletal disease involving cartilage matrix degradation, subchondral bone remodeling, and systemic inflammation, significantly impairing joint function and mobility. Existing KOA prediction models are not designed to account for nonlinear multimodal biomarker interactions or to integrate biochemical and imaging data, thus limiting their clinical utility. The current method for early detection and prediction of KOA disease progression is primarily based on machine learning-based approaches using radiographic imaging data, static feature selection, and deterministic outputs. These machine learning approaches often fail to capture the pathophysiology of KOA disease progression, which involves a complex cascade of processes, …

Multi-Modal Graph Learning For Vision Language Model In General And Medical Domains, Xinyue Hu

Computer Science and Engineering Dissertations - Archive

Multi-modal learning has gained significant attention in deep learning for its ability to integrate and process information from multiple modalities, such as text, images, and videos. By leveraging complementary information from different modalities, it enables a more comprehensive understanding of complex data in various tasks. Simultaneously, graph learning, a prominent paradigm that models structured data as graphs, captures both local and global dependencies, providing a natural framework to represent intricate interactions and contextual relationships. When combined with multi-modal learning, these graph-based approaches have the potential to enhance feature representation and reasoning by effectively fusing heterogeneous data, leading to more robust …

A Framework For Developing Collaborative Community Building Tools For Novice Computer Science Students, Daniel Olivares, Jakob Kubicki, Katie Imhof

Computer Science Faculty Scholarship

Students enrolled in introductory computer science courses tend towards individual work because of pedagogical practices discouraging collaboration and a focus on individual assignments. This can discourage new computer science students and may negatively affect persistence in computer science. In contrast, social learning theory research suggests a connection between student success and their level of involvement with peers, instructors, and in the greater learning community. Motivated by these contrasting conclusions, the research presented in this paper puts forth a framework based on social learning theories and teaching and learning methodologies to leverage social computing as a learning tool. This framework’s primary …

Distribution And Tooth Morphoguilds Of Mosasaurids (Squamata) Of The Campanian Western Interior Seaway With Implications For Controls On Mosasaur Paleobiogeography, Alec Zaborniak

Master's Theses or Doctor of Nursing Practice

The Western Interior Seaway (WIS) of North America is well known for its mosasaurid squamate diversity, particularly during the Campanian of the Late Cretaceous. Mosasaurid diversity has historically been examined at a fine scale, with many studies investigating the faunal composition of specific assemblages; however, studies focusing on mosasaur communities within the Western Interior Seaway during specific Ages are currently lacking. Mosasaur tooth morphology has also been extensively studied, with tooth characteristics commonly being used as phylogenetic characters. However, many studies examining mosasaur communities and tooth morphology have been focused on broader spatiotemporal or phylogenetic scales. This study investigates the …

The Effects Of Return To Prairie In Barber County, Kansas: A Case Study Using Ndvi And Dendrochronology, Elijah O. Joy

Master's Theses or Doctor of Nursing Practice

This study aims to evaluate the impact of prairie restoration efforts in Barber County, Kansas, with a focus on removal of Eastern Red Cedar. Restoration effectiveness was assessed using remote sensing of satellite scenes via NDVI, density analysis, and dendrochronological methods. The tree density analysis revealed a 66% reduction across the study area and a 99% reduction in the fully restored zones. NDVI analysis from 2010 to 2024 showed higher summer vegetation health and seasonal fluctuations influenced by climate variability and fire events. Dendrochronological data from tree cores reveals growth patterns and establishes a baseline for future dendrochronological chronologies. The …

Oil-Oil Correlation Across Sedimentary Basins In Kansas Using Molecular Geochemistry And Fourier Transform Infrared Spectroscopy, Oluwaseun V. Omoyemi

Master's Theses or Doctor of Nursing Practice

Hydrocarbons are produced from different subbasins and stratigraphic intervals in Kansas. However, the geochemical characteristics and sources of these hydrocarbons are still poorly understood. While reservoir rocks, seals, and traps that are essential for petroleum systems are well defined within the state, the possible source rocks are often considered thermally immature, raising questions about their ability to generate the volume of hydrocarbons currently being produced. This research project tries to evaluate the geochemical characteristics of hydrocarbons produced in the state of Kansas and determine if the hydrocarbons from the different subbasins and stratigraphic units are genetically related. Thirty-seven crude oil …

A Histological Survey Of A Large, Sub-Adult Tylosaurus Nepaeolicus With Implications On The Validity Of Tylosaurus Kansasensis, Carson Cope

Master's Theses or Doctor of Nursing Practice

Tylosaurus nepaeolicus is a basal, medium-sized tylosaurine mosasaur that lived during the late Coniacian and early Santonian in the Western Interior Seaway. Despite being a well-studied species, there is debate over whether Tylosaurus kansasensis represents the juvenile form of T. nepaeolicus, or if the two species are distinct. Osteohistology can determine organism age at time of death and can be used to help resolve this debate and provide a better understanding of the growth of T. nepaeolicus. Thin-sections were taken from a humerus, rib, and vertebra of a single individual (FHSM VP-2209). All thin-sections show primarily parallel-fibered cortical …

Leveraging Data Science For Resilience: Improving Trauma-Informed Care Practice For Adverse Childhood Experience With Ai & Data Science Application, Mohmmad Arif Shaik

Master's Theses

Adverse Childhood Experiences (ACEs) have long-lasting effects on physical health, mental well-being, education, and socioeconomic outcomes. Resilient Georgia (RG), a statewide initiative, seeks to address ACEs through trauma-informed care and data-driven strategies. However, challenges in data collection, analysis, and tracking set back the effectiveness of these efforts. This study explores the role of data science and interactive visualization tools in improving outcomes for individuals and communities affected by ACEs. A key focus of this research is the development of a data science management application designed to enhance data collection and improve real-time decision-making. The application features interactive dashboards that allow …

Optimal Control And Structurally-Informed Gradient Optimization Of A Custom 4-Dof Rigid-Body, Brock Marcinczyk, Logan E. Beaver

Mechanical & Aerospace Engineering Faculty Publications

This work develops a control-centric framework for a custom 4-DOF rigid-body manipulator by coupling a reduced-order Pontryagin’s Maximum Principle (PMP) controller with a physics-informed Gradient Descent stage. The reduced PMP model provides a closed-form optimal control law for the joint accelerations, while the Gradient Descent module determines the corresponding time horizons by minimizing a cost functional built directly from the full Rigid-Body Dynamics. Structural-mechanics reaction analysis is used only to initialize feasible joint velocities—most critically the azimuthal component—ensuring that the optimizer begins in a physically admissible region. The resulting kinematic trajectories and dynamically consistent time horizons are then supplied to …

Applying Transfer Learning For Street-Scale Nuisance Flood Forecasting In Coastal-Urban Cities, Binata Roy, Jonathan L. Goodall, Diana Mcspadden, Chetan Kumar, Steven Goldenberg, Yidi Wang, Malachi Schram

VMASC Publications

An important challenge with Machine Learning (ML) is its transferability; i.e., whether a ML model trained on one set of data can be applied to a second set of data without requiring full re-training of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether a ML model trained for one …

Faithful Narratives From Complex Conceptual Models: Should Modelers Or Large Language Models Simplify Causal Maps, Tyler J. Gandee, Philippe J. Giabbanelli

VMASC Publications

(1) Background: Comprehensive conceptual models can result in complex artifacts, consisting of many concepts that interact through multiple mechanisms. This complexity can be acceptable and even expected when generating rich models, for instance to support ensuing analyses that find central concepts or decompose models into parts that can be managed by different actors. However, complexity can become a barrier when the conceptual model is used directly by individuals. A ‘transparent’ model can support learning among stakeholders (e.g., in group model building) and it can motivate the adoption of specific interventions (i.e., using a model as evidence base). Although advances in …

5g-Practical Byzantine Fault Tolerance: An Improved Pbft Consensus Algorithm For The 5g Network, Xin Liu, Xing Fan, Baoning Niu, Xianrong Zheng

Information Technology & Decision Sciences Faculty Publications

The consensus algorithm is the core technology of blockchain systems to maintain data consistency, and its performance directly affects the efficiency and security of the whole system. Practical Byzantine Fault Tolerance (PBFT) plays a crucial role in blockchain consensus algorithms by providing a robust mechanism to achieve fault-tolerant and deterministic consensus in distributed networks. With the development of 5G network technology, its features of high bandwidth, low latency, and high reliability provide a new approach for consensus algorithm optimization. To take advantage of the features of the 5G network, this paper proposes 5G-PBFT, which is an improved practical Byzantine fault-tolerant …

Atmospheric Chemistry Experiment (Ace) Winds, Matthew Wyatt, Peter F. Bernath, Chris Boone, Léo Lavy, Ryan Johnson

Chemistry & Biochemistry Faculty Publications

The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) uses limb geometry to measure transmittance spectra of Earth's atmosphere by solar occultation. Line-of-sight wind speeds can be derived via Doppler shifts of molecular lines in infrared spectra. The wind look direction angles relative to geodetic North are derived from geometry. We validate the new ACE version 5.3 (v.5.3) line-of-sight winds with MIGHTI and meteor radar vector wind observations and find a ±15 m/s sunrise/sunset shift above 80 km. We also compare line-of-sight winds from ACE-FTS v.5.2 and v.5.3 with vector winds from the MERRA-2, HWM14, and WACCM-X models. A ±15 m/s …

Alternative Splicing In A Coral During Heat Stress Acclimation And Recovery, Nitin Baliga, Kathryn Stanklewicz, Jacob Valenzuela, Serdar Turkarsian, Wei-Ju Wu, Kelly Gomez-Campo, Nicolas Locatelli, Trinity Conn, Veronica Radice, Katherine Parker, Rachel Alderdice, Line Bay, Christian Voolstra, Daniel Barshis, Iliana Baums

Biological Sciences Faculty Publications

Climate change has caused drastic declines in corals. As sessile organisms, corals acclimate to environmental shifts through genome-wide changes in gene expression, epigenetic modifications, and alterations in microbiome composition. However, alternative splicing (AS), a conserved mechanism of stress response in many organisms, has been under-explored in corals. Using short-term acute thermal stress assays, we investigated patterns of AS in the scleractinian coral Acropora cervicornis during response to low (33°C), medium (35°C), and high (37°C) heat stress and subsequent overnight recovery. Our findings demonstrate reproducible dynamic shifts in AS of at least 40 percent of all genes during response to heat …

Tidal Love Numbers For A Non-Rotating Two-Fluid Neutron Star: Interior Solution, Gregory G Jaurequi

Dissertations and Theses

We investigate the tidal Love numbers for a non-rotating dark matter admixed neutron star (NS). Tidal Love numbers, which quantify a star's response to the tidal field of a companion object, are an important feature in the gravitational wave (GW) signal and vary depending on the star’s equation of state and dark matter profiles. By determining how the internal properties of the NS affect the GW signal, we hope that improvements in gravitational wave detection will help constrain these parameters by providing additional data from neutron star mergers with other compact objects. To this end, we focus on solving the …

Synthesis And Luminescence Studies Of Europium Doped Zinc Lead Germanate Phosphors, Anika Nawar Chowdhury

Dissertations and Theses

Phosphors are luminescent materials that emit light upon excitation, which have significant uses in optoelectronics, bioimaging, sensors, security, and other fields. Inorganic luminescent materials are well known for their stability and broad applications. Among these, germanate based phosphors have recently caught attention because of their inertness, excellent chemical and thermal stability, structural flexibility, and unique properties. For optimizing the properties of the materials, impurities are added to the host intentionally, which are known as dopants. Rare earth elements are often applied as dopants because of their unique f-f transitions. Eu3+ is one of the broadly studied rare-earth dopants among these, …

Demystifying Misconceptions In Introductory Undergraduate Chemistry Education With 3d Printed Molecular Orbitals, Hiwot Endeshaw, Daniel J. O'Leary

Pomona Senior Theses

Spatial abilities are invaluable skills for the science, technology, engineering, and mathematics (STEM) subjects. However, women, people from low socioeconomic backgrounds, and ethnic minorities are more likely to have less developed spatial abilities, which is one of the many contributing factors for the lack of diversity in STEM subjects like chemistry. Teaching spatial skills to undergraduate chemistry students may address this issue and help increase the diversity of students who go on to continue their education in the subject. 3D printing technology in higher education has exploded in recent years, presenting a unique opportunity to teach “hard to grasp” concepts …

Modified N-Heterocyclic Carbene Catalysts For Polyurethane Synthesis, Charise D. Young

Pomona Senior Theses

Polyurethanes are widely used polymers synthesized from diisocyanate and diol molecules. They are ubiquitous polymeric materials with important industrial applications. Their increasing market value prompts the need for selective and efficient production which can be achieved through N-Heterocyclic carbene (NHC) catalysis. N-heterocyclic carbenes are heterocyclic molecules containing a carbene atom and at least one nitrogen adjacent to the carbene center. The nitrogen substituents on the adjacent nitrogen play an important role in influencing their steric and electronic properties and resultant reactivity.^1,2 There is a lack of a comprehensive understanding of the steric and electronic properties of NHCs and how …

Optimizing And Scaling Up Tcfh–Nmi Pyrrole Acylation For Organic Syntheses, Grant H. Miller

Pomona Senior Theses

Traditional ketone synthesis often depends on toxic reagents and hazardous solvents, which limits its scalability and environmental compatibility. The TCFH–NMI method has shown strong potential for amide, ester, and thioester formation, but its use in ketone synthesis has only been recently described, and only on small scales. This thesis addresses that gap by optimizing a scalable synthesis of 2-(monomethyl succinyl)-3,5-dimethylpyrrole using monomethyl succinate and 2,4-dimethylpyrrole as model substrates. Key reaction parameters were systematically refined to improve yield, reproducibility, and sustainability. The final protocol avoids chromatography, operates at room temperature, and consistently delivers high yields. These features position it as a …

Huchum: The Legacy Of Fire Suppression, Indigenous Land Management, And Media Representation, Carolyn Coyne

Pomona Senior Theses

In my thesis, I examine how various forms of news media from the 1900s to present day in Ohlone territory have framed a particular hegemonic ideology around fire that matches early colonial journal entries – an ideology that is fueled by fear, sensationalism, and exclusion and directly commits violence against the Ohlone people. I investigate this time period because this is when modern news corporations, like The New York Times, rose into prominence. Specifically, I question how media representations of fire inform regulations over controlled burns; what are the similarities in discourse between media framing and policy? What tactics are …

Swimming In Sh*T: Quantifying Lagoon Flushing Impacts On Fecal Indicator Bacteria In Surf Zones Of Three Beaches On The East End Of Long Island, Ny, Brody C. Eggert

Pomona Senior Theses

This thesis investigates how lagoon flushing influences fecal indicator bacteria (FIB) concentrations—specifically enterococcus bacteria—in the surf zones of East Hampton and Southampton, New York. Focusing on the coastal lagoons of Georgica Pond, Sagg Pond, and Mecox Bay, the study analyzes how episodic inlet openings and environmental conditions affect enterococcus levels at adjacent recreational beaches. Using over 700 observations from the Surfrider Foundation’s Blue Water Task Force (BWTF) database, I construct a series of statistical models ranging from ordinary least squares to mixed effects frameworks; this thesis shows my process in developing this model. My analysis reveals that open inlets between …

Rwanda's Natural Remedies: A Fresh Look At The Fight Against Malaria, Leandre Nsabimana Ndisanze

Pomona Senior Theses

Malaria remains one of the most devastating parasitic diseases globally, disproportionately affecting sub-Saharan Africa, where Rwanda continues to face high transmission rates and rising resistance to conventional interventions. Despite decades of control efforts, the emergence of drug-resistant Plasmodium falciparum and insecticide-resistant Anopheles mosquitoes threatens to reverse recent gains. This research responds to the urgent need for sustainable and culturally relevant alternatives by exploring the therapeutic potential of Rwandan traditional medicinal plants. These indigenous remedies, long used by local healers, offer an underexplored reservoir of bioactive compounds that may provide the basis for novel antimalarial drugs.

The central hypothesis of this …

A Vascular Flora Of The Sacatar Trail Wilderness, Sierra Nevada, California, Kimberly Schaefer Pivetti

CGU Theses & Dissertations

The Sacatar Trail Wilderness in Inyo and Tulare counties, California, encompasses a bioregional transition zone in the southeastern Sierra Nevada. The ca. 233 km 2 (90 mi 2 ) study area, located 32 km (20 mi) northwest of the city of Ridgecrest, ranges from 930 to 2698 m (3051–8851 ft) in elevation. The highly diverse California Floristic Province, Great Basin, and Mojave Desert converge in the region including the Wilderness creating conditions to support a broad spectrum of vegetation assemblages. The Bureau of Land Management has prohibited vehicular activity in this area since its wilderness designation in 1994; consequently, recent …

Mathematical Modeling Of Cancer Tumor Evolution, Belgacem Al-Azem

CGU Theses & Dissertations

Several mathematical models of cancer tumor evolution are presented. The aim of this endeavor is to write a thesis that fosters numerical and analytical understanding of certain mathematical models in the area of oncology as well as to offer potential predictive tools of therapeutic and clinical applicability. In this work, we give a panoramic view of the cancer phenotype, for to understand cancer, we need to "see" its biophysics. Indeed, the discovery of oncogenes led to the thinking that cancer tumor is perhaps a genetic disease. But the role of angiogenesis and other microenvironment-related discoveries (such as the role of …

Multipliers On Weighted Sequence Spaces, Gilbert Acheampong, Raymond Cheng

Mathematics & Statistics Faculty Publications

The space ℓp,α of complex sequences a = (a0, a1,a2,...) for which

[[formula omitted]]

is studied. Each such sequence can be identified with the analytic function with power series

[[formula omitted]]

In this setting, the point evaluation and the difference quotient mappings are shown to be bounded; the cases are identified in which ℓp,α is boundedly contained in ℓr,β. Conditions on the parameters are derived for the analytic functions of ℓp,α to have radial limits almost everywhere on the boundary, and for ℓp,α to be an algebra. Smoothness properties of the boundary function are investigated. Basic properties of multipliers on …

Comprehensive Benchmarking Of Several Machine Learning And Bayesian Models For Early-Stage Diabetes Risk Prediction: A Large-Scale Comparative Study, Md. Iqbal Hossain, Najila Alam Porno

Mathematics & Statistics Faculty Publications

Diabetes remains a critical global health challenge, with early detection is crucial for effective management. This study presents a comprehensive benchmarking analysis of 14 diverse machine learning and Bayesian models for early-stage diabetes risk prediction using clinical data [2] from Sylhet, Bangladesh. This research evaluated traditional methods (Logistic Regression, Decision Trees), ensemble techniques (Random Forest, XGBoost, LightGBM), Bayesian approaches (BART, Bayesian Logistic Regression), and advanced neural architectures (Deep Belief Networks) using both 70-30 train-test splits and 10-fold cross-validation. The results demonstrate that ensemble methods consistently outperformed other approaches, with Random Forest(RF) achieving the highest cross-validated AUC (0.9951) and accuracy (0.9699). …

Suntan (And Other Solar Tigonometric Functions), John Adam

Mathematics & Statistics Faculty Publications

Question 1: If I₀ is the solar irradiance (power per unit area, W/m²) reaching my head, express the intensity on the side of my face (I_s) in terms of θ. Assume for now that the irradiance is independent of path length through the atmosphere and that my face is normal to the direction θ = 90°.

Using the 1962 U.S. Standard Atmosphere,² Hottel (1976)³ expressed the solar irradiance using the formula

I = I₀(a₀ + a₁e^{−k sec θ}), where A is the elevation in kilometers and

a₀ = 0.4237 − 0.00821(6 − A)²; a₁ = 0.5055 …

Golden Spirals Everywhere?, John Adam

Mathematics & Statistics Faculty Publications

The article explores different types of spirals, including Archimedean, hyperbolic, and logarithmic spirals, with a focus on the golden ratio and golden spirals. It discusses the misconception that golden rectangles and spirals can be found in various natural and man-made objects, emphasizing the importance of understanding the properties of logarithmic spirals. The text provides mathematical equations for logarithmic spirals and poses questions for readers to explore the concept further. The author, John Adam, invites readers to engage in Fermi Questions and submit ideas for consideration.

Model-Free Organization Of Patient Reported Outcomes Data: Geometrical Rep-Resentation Of The Modified Compartmen-Talization Method, Manasi Sheth, N. Rao Chaganty

Mathematics & Statistics Faculty Publications

There is a recent advancement in the field of mathematics and statistics to understand the geometry or connectedness of the data due to the massive amounts of data being generated. The data provided for analyses are usually very large and need to be organized and minimized in order to make it more useful and meaningful. In biostatistics or medical field, it is important for patients to have access to high-quality, safe and effective and/ or efficacious medical products. It is quite necessary to ascertain that the patients and their care-partners stay at the center of the regulatory decision-making process. In …

A Decision-Space Model Explains Context-Specific Decision Making, Dirk W. Beck, Cory N. Heaton, Luis D. Davila, Lara I. Rakocevic, Sabrina M. Drammis, Danil Tyulmankov, Atanu Giri, Shreeya Umashankar Beck, Qingyang Zhang, Michael Pokojovy, Kenichiro Negishi, Alexis A. Salcido, Neftali F. Reyes, Andrea Y. Macias, Serina A. Batson, Paulina Vara, Raquel J. Ibáñez Alcalá, Safa B. Hossain, Graham L. Waller, Laura E. O'Dell, Travis M. Moschak, Ki A. Goosens, Alexander Friedman

Mathematics & Statistics Faculty Publications

Optimal decision-making requires consideration of internal and external contexts. Biased decision-making is a transdiagnostic symptom of neuropsychiatric disorders. We created a computational model demonstrating how the striosome compartment of the striatum constructs a context-dependent mathematical space for decision-making computations, and how the matrix compartment uses this space to define action value. The model explains multiple experimental results and unifies other theories like reward prediction error, roles of the direct versus indirect pathways, and roles of the striosome versus matrix, under one framework. We also found, through new analyses, that striosome and matrix neurons increase their synchrony during difficult tasks, caused …