Physical Sciences and Mathematics Commons^™

A Spatial Analysis Of Residential Photovoltaic Adoption In New Jersey: Focusing On 2020 With Trends Through 2025, Brandon Mcalister

Geography and the Environment: Graduate Student Capstones

This capstone project seeks to find the relationship between socioeconomic and demographic variables and their relationship to residential photovoltaic installations across New Jersey. The study consists of Geographic Weighted Regression Analyses to construct and socioeconomic index indicating the likelihood of photovoltaic adoption in New Jersey zip codes. Then using the index to predict future photovoltaic adoption across the state. The study found that socioeconomic and demographic variables can predict photovoltaic adoption within one year, but when placed in an index and used to predict future adoption trends, the model under predicts and extremely over predicts. While socioeconomic status is a …

Photometric And Spectroscopic Properties Of Hydrogen-Rich Supernovae, Chaitrika B. M

University Departments

No abstract provided.

Theoretical Investigation On The Magnetic And Spintronic Behaviour Of 2d Mxenes, Abhinav Prashant Gotmare

University Departments

No abstract provided.

Composite Magnetic Monopoles, Moreshwar Pathak

University Departments

No abstract provided.

Utilizing Spatial Criteria To High-Grade Wyoming Eor Opportunities Along Proposed Pipeline Corridors: A Value Driven Approach, Jack Borski

Geography and the Environment: Graduate Student Capstones

Oil and gas development has played a critical role in human civilization, and continues to bring drive economies around the world. One such economy is the state of Wyoming that has seen oil and gas production generally decline of the last several decades due to the depletion of high volume conventional reservoirs. A proven secondary technique such as CO2 enhanced oil recovery (EOR) may serve as a method to arrest declining production, and increase economic activity. Wyoming has recognized this opportunity, and has attempted decrease the barriers of entry for oil and gas operators to invest in field-level CO2 EOR …

Object-Based Image Analysis And Artificial Intelligence Identification Of Anthropogenic Disturbance On Lesser Prairie Chicken Habitat In Cheyenne County, Colorado, Tara Hoelzer

Geography and the Environment: Graduate Student Capstones

Renewable energy projects often require extensive landcover for their operations. When one of these projects encroaches into territory of threatened species, such as Lesser Prairie Chickens, an analysis of habitat suitability and human disturbance is required to proceed. Traditionally, this involved manually reviewing aerial imagery within a 6-mile radius, digitizing features, and interpreting them using a human technician—an approach that was time-consuming and prone to human error. By using pretrained AI models within Model Builder™, the identification of roads and structures was automated, making the process faster and more consistent than manual visual analysis. As AI and technology continue to …

A Study On Fuzzy Time-Series And Its Applications To Stock Price Forecasting, Takeshi Stormer

University Honors Theses

Fuzzy mathematics looks to incorporate the vagueness that exists within the real world, specifically regarding imprecise classes, or non-numerical information expressed as "linguistic" variables. Since most traditional mathematical theories do not have the ability to be applied with the exactness that is otherwise seen in mathematics. As such, there had been many applications of fuzzy mathematics throughout many different fields of mathematics, including that of forecasting. By exploring the fundamentals of fuzzy mathematics, including fuzzy sets, operations of fuzzy sets, the surface level introduction to fuzzy logic, fuzzy relations, operations of fuzzy relations, and fuzzy time-series, this work looks to …

Conceptualizing The Explanatory Fully Longitudinal Mixed Methods Case Study Design: A Demonstration With An Arithmetic Education Trial With Kindergarten Children, Menglong Cong

Electronic Theses and Dissertations

In employing longitudinal mixed methods designs, researchers have commonly used the fully longitudinal mixed methods design. This has occurred mostly in the health sciences but less in education. The current investigation proposes a novel longitudinal mixed methods research design, explanatory fully longitudinal mixed methods case study design. It demonstrates its potential for addressing research inquiries in educational research using the arithmetic learning trajectories datasets. This study is presented in three components. The first is a quantitative phase, selecting an exploratory case from a previous arithmetic learning trajectories study (Clements et al., 2021) for qualitative analyses based on maximizing the …

Simple Yet Effective, Effective Yet Inclusive: A Skincare Line, Ayesha Wali Rahimoon

Lawrence University Honors Projects

This honors project addresses the lack of inclusive skincare formulations by developing a scientifically grounded skincare line with an antioxidant-rich serum, moisturizer, and cleanser tailored to support diverse skin types, particularly melanin-rich skin. The serum combines strawberry extract powder, Manuka honey, niacinamide, green tea extract, and humectants to promote hydration, antioxidant protection, and skin barrier reinforcement. Formulated with a stable pH of 5.0–5.5 and an effective preservative system, the product was tested through non-animal, biologically relevant models.

A UV protection assay using HEK293 cells demonstrated that the serum significantly reduces oxidative damage, increasing post-exposure cell viability to 80%, compared to …

Probing Dust Grain Optical Properties In The Ism Using Diffuse Ultraviolet Observations Together With Radiative Transfer Modelling, Nilanjana Dey Choudhury

University Departments

No abstract provided.

Degraded Document Binarisation, Miriyala Ajith

Master’s Dissertations

In this study, I explored degraded document binarization by reviewing two recent model frameworks and implementing their models using PyTorch. The first model is based on cGANs, specifically the DE-GAN [41] framework, which enhances degraded documents by restoring their quality prior to binarization. The second model employs vision transformers [40], inspired by the DocBinFormer architecture, which uses an autoencoder in both the encoder and decoder for effective binarization. Both models were evaluated on the ISI-Bengali dataset. Experimental results demonstrate that DE-GAN improved document quality by 4% compared to the degraded input, while the vision transformer model achieved a 14% improvement, …

Some Results In Thermodynamic Formalism, C. Evans Hedges

Electronic Theses and Dissertations

This dissertation investigates several key questions at the intersection of dynamical systems, computability theory, and thermodynamic formalism. In the symbolic setting, we establish novel results regarding the statistical properties of equilibrium states, deriving bounds on probabilities of configurations and relating these bounds to the Gibbs property through the homoclinic relation. Additionally, we examine the computability of thermodynamic quantities such as pressure, ground state energy, and residual entropy. We show that topological pressure is computable from above for general subshifts and computable for strongly irreducible shifts, with similar results extending to ground state energy and residual entropy.

Extending beyond subshifts, we …

Toward Sustainable Human Well-Being: A Multidimensional Assessment In Colorado, Uma Umut Baysal

Electronic Theses and Dissertations

Evaluating progress in human well-being is essential for guiding effective policy and promoting sustainable development. Traditional approaches often emphasize economic and social dimensions while overlooking ecological indicators critical to long-term sustainability. This research addresses that gap by proposing a layered, scalable local framework for county-level analysis and bottom-up decision-making, integrating multiple objective indicators to assess and compare well-being outcomes across regions.

The first goal of this dissertation is to measure human well-being in Colorado counties by developing a Human Well-Being Index (HWBI). This index combines a newly developed Built Environment Index (BEI) comprising five sub-indices: accessibility, housing affordability, transportation, …

Zeeman Effect Observations Of Water Masers In The Star Forming Region Ngc 7129 Firs2, Marina Bethann Beltran

College of Science and Health Theses and Dissertations

Magnetic fields likely play an important role in star formation, yet their influence remains poorly understood due to the observational challenges in measuring them. The only direct method for measuring magnetic fields is through the Zeeman effect, the splitting of spectral lines in the presence of a magnetic field. Water masers, which trace high-density shocked regions, are known to occur throughout some of the earliest stages of the star formation process. They provide an excellent opportunity to observe the Zeeman effect. However, Zeeman detections in H2O masers have so far been limited primarily to isolated, high-intensity maser lines with simple …

Early Diagnosis And Detection Of Skin Cancer Using Deep Neural Network Models And Feature Extraction From Pre-Trained Cnns, Sahil Khanna

Harrisburg University Dissertations and Theses

Skin cancer is one of the most common and lethal cancer types. While accurate diagnosis at an early stage is essential for skin cancer treatment it remains difficult to achieve in many regions due to lack of sufficient dermatologists and proper diagnostic equipment. Prior studies show Convolutional Neural Network (CNN) models excel at skin lesion classification and consistently achieve better results than standard diagnostic practices. However, the focus of many studies remains confined to image-based learning while neglecting useful patient metadata that could improve prediction accuracy. This research project created a specialized CNN model to classify skin lesions and evaluated …

Roles Of Organic Agriculture For Water Optimization In Arid And Semi-Arid Regions, Shikha Sharma, Matt A. Yost, Jennifer R. Reeve

Plants, Soils and Climate Student Research

Water scarcity is a critical challenge in arid and semi-arid regions, where agricultural water consumption accounts for a significant portion of freshwater use. Conventional agriculture (CA) methods with high reliance on chemical and mechanical inputs often exacerbate this issue through soil degradation and water loss. This review aims to examine how different organic practices, such as mulching, cover cropping, composting, crop rotation, and no-till (NT) in combination with precision technologies, can contribute to water optimization, and it discusses the opportunities and challenges for the adoption and implementation of those practices. Previous findings show that organic agriculture (OA) may outperform CA …

Shrinkage Study In Photopolymerisable Hybrid Sol-Gel Through Holographic Patterning, Jamshed Aftab, Izabela Naydenova, Tatsiana Mikulchyk

Articles

Photopolymerisation induced shrinkage of holographic materials is one of the main factors which needs to be considered for designing holographic optical elements (HOEs) with high accuracy in light redirection with maximum efficiency. This work studies the shrinkage in photopolymerisable hybrid sol-gel (PHSG) by examining the properties of volume transmission gratings recorded in PHSG layers. It explores both the dependence of shrinkage on the holographic grating parameters (thickness, spatial frequency, slant angle) and the effect of material aging. By using the fringe-plane rotation model, shrinkage is found to have the maximum value of 1.37 % at 765 lines/mm (19.36° slant angle) …

Advancing The Functional Diversity Of Hydrazone Photoswithces, Daniil Sosnin

Dartmouth College Ph.D Dissertations

Photochromic materials have drawn increasing interest for their ability to control functional systems and biological processes using light. Molecular switches enable precise, reversible regulation of the systems in which they are embedded. To achieve robust and versatile switching, careful tuning of molecular structure and activation conditions is essential. Hydrazones represent a promising class of photoswitches, offering synthetic accessibility, strong thermal and photochemical stability, and a modular framework that supports further development for materials and biological applications. This work begins by examining a family of heterocyclic hydrazones to determine how structural variations affect photoswitching efficiency and thermal half-lives. Comparisons with phenyl-based …

Cultivating Resilience In The Anthropocene: Evaluating A Gssw Ecological Justice Curriculum, Windy Selig

Electronic Theses and Dissertations

This Dissertation in Practice evaluated the University of Denver’s Graduate School of Social Work (GSSW) Ecological Justice Pathway to examine how resilience is conceptualized and cultivated within the curriculum. Grounded in a constructivist paradigm and guided by an ecological justice framework, this evaluation explored the pedagogical and curricular strategies designed to prepare social work students for the emotional, ethical, and professional demands of practicing in the Anthropocene—a time marked by ecological degradation, climate crisis, and compounding social inequities.

Through qualitative methods, including faculty interviews and curriculum document analysis, the evaluation identified both explicit and implicit components that foster student resilience. …

Advancing Academic Advising With Knowledge Graphs: Integrating Machine Learning And Llms For Personalized Course Planning, Sara Alshamsi

Thesis/ Dissertation Defenses

Academic advising plays a critical role in helping students make informed decisions, improve academic performance, and successfully navigate their university journey. However, with increasing university enrollment, traditional advising methods often struggle to scale, leading to student frustration and overburdened advisors. Additionally, designing course offerings that match student demand is a complex and error-prone process involving multiple stakeholders. To address these challenges, this thesis proposes an automated, data-driven system for generating personalized academic plans for students. The primary aim of this thesis is to develop a system that reduces students' dependency on advisors while simultaneously providing accurate estimates of course demand …

A Comparative Study Of Neural Networks And Xgboost Models For Flight Time Prediction, Ioannis Paraschos, Taryn E. Trimble, Eshna Bhargava, Jake Klingler, Benjamin R. Nicolai

Beyond: Undergraduate Research Journal

Flight time prediction plays a crucial role in modern air travel, benefiting airlines and passengers alike. Accurate predictions enable airlines to optimize schedules, allocate resources effectively, and ensure passenger safety and satisfaction. In recent years, machine learning models, such as neural networks and XGBoost, have gained popularity for predicting flight times. This study aims to compare the performance of neural network and XGBoost models in predicting flight times, considering factors such as weather conditions, air traffic control, and aircraft performance. The results indicate that both models are effective, with XGBoost achieving slightly higher accuracy. However, neural networks offer advantages in …

A Spatial Modeling Framework For Identifying Multidimensional Risk Factors Of Colorectal Cancer, Johnna K. Berryhill

Student Theses and Dissertations

Colorectal cancer (CRC) is one of the most common and preventable cancers, yet significant disparities in screening, incidence, and late-stage diagnosis persist across different geographic and socioeconomic contexts. This thesis presents a spatial modeling framework for identifying multidimensional risk factors associated with CRC outcomes across various geographic scales. Using county- and census-tract-level data from national and state sources, the study integrates demographic, socioeconomic, environmental, built environment, and behavioral predictors to analyze geographic variability in CRC risk factors. Advanced spatial modeling techniques, including Geographically Weighted Regression (GWR) and Geographically Weighted Random Forest (GW-RF), are employed to capture spatial heterogeneity in these …

Spatiotemporal Analysis Of Available Freshwater Resources In Watersheds Across Northern New Jersey, Toritseju Oyen, Duke Ophori

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Groundwater is a critical freshwater resource, yet its quality is increasingly threatened by anthropogenic activities, particularly in urbanized regions. This study employs geospatial analysis to evaluate the spatiotemporal variability of groundwater quality across 11 Watershed Management Areas (WMAs) in northern New Jersey, from 1999 to 2016. Using specific conductance (SC) as a proxy for salinity, we applied Ordinary Kriging interpolation to estimate SC values in unmonitored locations, leveraging data from 295 shallow wells within the New Jersey Ambient Groundwater Quality Monitoring Network. The results reveal significant spatial heterogeneity in groundwater quality, strongly associated with land use and road density. The …

2025 June 12 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Enzymatic Characterization Of Bacterial Enzymes And Inhibitors As Potential Antibiotics With New Mechanisms Of Action, Emma Helene Kelley

Dissertations

Bacteria have become increasingly resistant to antibiotics, therefore there is an urgent need for new drug classes of antibiotics to help fight antibiotic infections. To this end, our research is focused on inhibitors of dizinc metalloenzymes N-succinyl-L,L-diaminopimelic acid desuccinylase (DapE), an enzyme in the lysine biosynthesis pathway, N-acetyl-L-ornithine deacetylase enzyme (ArgE), an enzyme in the arginine biosynthesis pathway, and sodium-dependent NADH: ubiquinone oxidoreductase (Na+-NQR) enzyme, a respiratory complex enzyme as promising drug targets. DapE, ArgE, and Na+-NQR and are only present in bacteria, including ESKAPE pathogens that can cause potentially deadly infections, thus inhibitors of DapE, ArgE, and Na+-NQR offer …

Principles For Physics Lab Reports Using Google Sheets, Vasiliy Znamenskiy

Open Educational Resources

This instructional guide provides detailed standards and best practices for students preparing physics lab reports using Google Sheets. It emphasizes the importance of precise data entry, formula-based calculations, and clearly labeled units. The document outlines rigorous conventions for mathematical formatting, error analysis (including percent error and percent difference), and data presentation in tables and graphs. It instructs students to maintain a structured single-page format for each report, include proper labeling and trendline analysis in graphs, and ensure automated and verifiable calculations. Submission and feedback procedures are clearly defined, highlighting the importance of collaborative revision and instructor comments. The guide also …

A New Model For Educational Program Assessments Using Automated Collective Concept Maps, Andrew R. Paullin

Master's Theses (2009 -)

This paper presents: Epistemological principles; the origins and theoretical foundations of concept maps; the current state of related works; the contributions, methods, results, and future road map of this research; and A New Model for Educational Program Assessments. An understanding that knowledge results from an evolution of cognitive structures enables a scientific approach to enhance the efficiency of learning. Building on prior works, this research provides a novel algorithm and tool to automatically create Collective Concept Maps from Individual Concept Maps by utilizing a dictionary, thesaurus, Natural Language Processing, Machine Learning / Artificial Intelligence, and domain expertise. Abstraction Filters enable …

Development Of Novel Force Fields For Metal Ions, Madelyn Smith

Dissertations

Many biological proteins require the presence of a metal ion in order to properly function. However, metal ions’ complex nature charge poses several challenges to accurately and efficiently simulate computationally. For example, metal ions can exhibit multiple oxidation states, electronic state degeneracy, flexible coordination numbers, and significant polarization effects. To address these problems, this dissertation aims to enhance force fields for modeling metal ions in molecular dynamics simulations. First, a comprehensive set of van der Waals radii for metal ions is derived, demonstrating the importance of using physically meaningful parameters in force fields. Second, a comprehensive set of atomic and …

Re: Approval Letter For The Draft Final Butte Reduction Works (Brw) Air Monitoring For Interim Demolition Activities – Phase I Data Summary Report (Dated March 21, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Comment Letter For The Final Butte Reduction Works (Brw) Smelter Area Waste Remediation And Contaminated Groundwater Hydraulic Control Site Air Monitoring Quality Assurance Project Plan (Qapp) For Interim Demolition Activities (Dated May 19, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.