Physical Sciences and Mathematics Commons^™

The Effect Of Non-Profit Organizations On The Passage Of Climate Change Legislation In Connecticut, John-Henry Burke

Honors Scholar Theses

Connecticut has a long history of climate action. In this study, I looked into the effect that non-governmental organizations have on the passage of climate change legislation in Connecticut. Eighteen different climate policy stakeholders, including legislatures, non-governmental organization (NGO) staff members, youth activists and state employees were interviewed to gain their perspective on how non-profits forward climate initiatives. I found that non-profit organizations do have a significant impact on the passage of climate change legislation in Connecticut by working as providers of information to legislators and mobilizers of constituents. This impact can be limited by various political factors.

Signal Modeling Of High Purity Germanium Detectors, Brooke Parker Thibodeau

Honors Scholar Theses

Pulse shape analysis can be used to analyze radiation incident on a semiconductor diode detector. Finite element analysis (FEA) can be used to simulate high purity germanium detectors with user-specified geometry, impurity concentration, and bias voltage. Subsequent streamline calculation can be used to conduct pulse shape analysis for single and multiple site gamma-ray interactions within the detector volume. Cross sections of the detector can be visualized by contour plots of the electric field, drift velocity magnitude, and collection time, as well as t30 and t90 rise-time values.

Strengthening The Bonds Between Us: An Empirical Investigation Of Morale In Human-Ai Teams And The Socially Supportive Ai Teammates Who Empower It, Rohit Mallick

All Dissertations

This dissertation investigates how artificial intelligence (AI) can be designed to improve the collective emotion within a team. A team's collective emotion, or morale, describes how motivated, optimistic, and enthusiastic the group is in accomplishing its goals. We conducted four studies that compared different social support strategies that AI teammates can provide to the team. Study 1A found that AI teammates who communicate with emotions can better motivate human team members and promote awareness of team dynamics and environmental changes. Study 1B found that human teammates become more motivated and happier when their AI teammates express joy and are close …

Automated Solar Pv Analysis With Machine Learning And Computer Vision: Dataset And Methodology, Malachi Massey

Electrical Engineering and Computer Science Undergraduate Honors Theses

Solar power is a vital resource in a world being threatened with the ever-evolving impacts of climate change. A combination of new and developing technologies have allowed solar photovoltaic installation to increase at an exponential rate. With this rapid and unprecedented growth comes the task of maintaining tens of thousands of square miles of solar photovoltaic panels. Manually observing and testing solar PV panels for defects or obstructions is costly and time-consuming, distracting valuable resources from the continued installation of new units. This research aims to (i) firstly, introduce a novel dataset on solar PV obstruction, named De-Solar dataset; (ii) …

Improving Home Security Through User Centered Device Positioning, Lalith Nadipalli

Theses and Dissertations

In today’s world, where technology is advancing rapidly and security threats are becoming more complex, the need for effective home safety measures is more critical than ever. Homeowners are increasingly turning to a variety of smart devices, such as smoke detectors, carbon monoxide detectors, and security cameras, to protect their living spaces against potential dangers like burglary, fire, and environmental hazards. These devices offer essential protection, acting as both early warning systems and visual surveillance tools. However, their effectiveness largely hinges on how well they are placed within the home. Proper placement of these safety devices ensures that they provide …

Efficient Fully Bayesian Approach To Brain Activity Mapping With Complex-Valued Fmri Data, Zhengxin Wang, Daniel B. Rowe, Xinyi Li, D. Andrew Brown

Mathematical and Statistical Science Faculty Research and Publications

Functional magnetic resonance imaging (fMRI) enables indirect detection of brain activity changes via the blood-oxygen-level-dependent (BOLD) signal. Conventional analysis methods mainly rely on the real-valued magnitude of these signals. In contrast, research suggests that analyzing both real and imaginary components of the complex-valued fMRI (cv-fMRI) signal provides a more holistic approach that can increase power to detect neuronal activation. We propose a fully Bayesian model for brain activity mapping with cv-fMRI data. Our model accommodates temporal and spatial dynamics. Additionally, we propose a computationally efficient sampling algorithm, which enhances processing speed through image partitioning. Our approach is shown to be …

Achieving Fairness In Zoning Laws With Machine Learning, William Schimitsch

College Honors Program

Zoning is a powerful regulatory tool that determines how municipalities use and develop land. The goal of zoning is to classify land use (e.g., residential, commercial, industrial) to maximize compatibility among neighboring parcels. Local zoning decisions, however, are made by small-sized boards, often through an opaque process, which raises concerns about bias and fairness. In the United States, zoning has historically prioritized single-family housing and thus created economic barriers that limit access to certain communities. Given the task of classifying land use and the wealth of geographical, demographic, and infrastructural data describing each parcel, the problem of bias in zoning …

Evaluating Climate Benefits In The Conservation Reserve Program: Methane Emissions And Carbon Storage In Restored Wetlands, Annika Kuleba

All Theses

As climate change progresses, Nature-based Climate Solutions (NbCS) have emerged as a key strategy for mitigation. Historically, wetlands were drained to increase arable land area, resulting in habitat degradation and soil erosion. To address these issues, the United States Department of Agriculture (USDA) incentivizes wetland restoration under the Conservation Reserve Program (CRP), in which landowners retire agricultural land to reestablish native habitat. Although wetlands can act as carbon sinks, they are also sources of methane, a more potent greenhouse gas (GHG). Therefore, the effectiveness of wetlands as a NbCS remains under debate due to assumed high methane emissions. Wetland functions …

Correcting Sampling Bias With Privacy-Preserving Synthetic Data: Inference Stability Under The Da-Mi Framework, Hannah Jiang

Arts & Sciences Graduate Student Theses and Dissertations

With the rapid advancement into the Data Age, synthetic data has emerged as a promising avenue for sharing scientific information while protecting the original data. While existing research has primarily focused on generating synthetic data to accurately replicate the characteristics of observed data, we explore the potential of synthetic data to adjust for unrepresentative sampling. This study explores how sampling bias—specifically unbalanced subsets—impacts statistical inference, and whether synthetic data can help correct such bias. Using a Data Augmentation–Multiple Imputation (DA–MI) framework, we generate synthetic datasets from biased samples and evaluate parameter recovery under different correction strategies. Simulations under a Missing …

Investigating Students’ Proficiency Across Statistical Software And Preferences Of Statistical Software Design, Sabrina White

Honors College Theses

This paper investigated students’ perceptions of their proficiency with statistical software applications and their preferences regarding software features. Results indicated that students’ statistical and coding experience, as well as the specific application used, did not significantly influence their self-perceived proficiency. This suggests that it may be more effective to focus on building student skills within a chosen application, rather than tailoring the application to match existing student capabilities. While students showed clear preferences for certain features, favoring clarity over depth, flexibility over safeguards, and built-in checks over unrestricted freedom, these preferences generally leaned toward balanced design rather than extremes. This …

Maximal Independent Set Algorithms Within Procedural Planar Maps: A Large-Scale Evaluation, Chaucer Ihrig

Honors College Theses

Analysis of a childhood game has led us to the problem of maximum independent sets in planar graphs. We wrote a graph creation utility using R to generate a random planar map and its dual graph. This utility then finds a graph’s maximal independent set using a variety of six algorithms. We investigate statistical connections between graph structure, colorability, and the maximal independent sets found using these algorithms over an incredibly large and procedurally generated dataset. We find one can always win the coloring game if the resultant graph is two-colorable. The algorithms perform statistically and practically significantly better on …

Math Course Placement Models At Csbsju Using Data Analysis, Josephine Jackson

Celebrating Scholarship and Creativity Day (2018-)

Many majors at the College of Saint Benedict and Saint John’s University (CSBSJU) require students to complete a course in calculus or statistics, however incoming students have various levels of preparation for these courses. This research investigates strategies for predicting student success in these courses and potential recommendations for remediation courses, e.g., pre-calculus or pre-statistics. The research uses data analysis to make this determination based on their previous math coursework and other data incoming students provide. Trends for success in math classes at CSBSJU have previously been based on outdated and inequitable methods. This project identifies correlations between prior coursework …

Exploring The Pedagogical Impact Of Software Development Live Streams: Informal Learning Opportunities For Software And Game Developers, Ella Kokinda

All Dissertations

Live streaming is an increasingly popular medium for throwing back the curtain on software development where streamers and viewers share their knowledge and experiences. Popular platforms like Twitch and YouTube enable developers to stream live coding sessions where people around the world can engage in real-time collaboration, feedback, knowledge sharing, and skill development. This work investigates the pedagogical implications and learning opportunities present in software and game development live streaming while focusing on the role of streaming as a learning environment and collaborative community. We begin by exploring summer camps as an informal learning opportunity for STEM education, highlighting the …

Decomposition And Coordination For Multiobjective Optimization: A Framework And Methodology, Philip J. De Castro

All Dissertations

In this work, we consider finding Pareto efficient solutions for complex multiobjective optimization problems (MOPs). Complex MOPs are unique in the literature because they have many more objective functions than is typically considered. In fact, such complex MOPs will have 30+ objective functions. This large problem size presents computational and coginitive difficulties. Computationally, standard techniques for solving MOPs are often ineffective and cognitively it is difficult for a decision maker (DM) to handle all of the information provided in such a large problem. To address these challenges, we develop a decomposition and coordination framework. This framework will allow us to …

Charge And Spin Transport In Nanowires With Spin-Orbit Coupling, Ryan Perrin

All Dissertations

Nanowires exhibiting Fermi-level pinning have strong radial electron confinement and thus can be modeled as a two-dimensional electron gas wrapped around the core. In III-V semiconductor structures, two forms of spin-orbit coupling are generated by breaking inversion symmetries in the crystal (Dresselhaus) and the overall structure of the nanowires (Rashba). The first goal of this thesis is to understand the single-particle energy spectrum in nanowires with variable cross sections and the quantum oscillations that can be driven in them by the application of a magnetic field parallel to the axis of the wire. To this end, the eigenfunctions and eigenvalues …

Development Of Mixed O/S-Donor Imidazole Thione Ligands For Trivalent Lanthanide/Actinide Separations, Rhianna Wolsleger

All Dissertations

Separation of lanthanides and actinides is difficult due to their very similar size and charge. Increasing selectivity for actinides over lanthanides is possible by incorporating a softer, more polarizable donor atom into a chelating ligand, since the softer donor atom is capable of greater orbital overlap with the 5f orbitals of the actinides vs the 4f orbitals of the lanthanides. Sulfur-containing imidazole thione chelating ligands have not been investigated for this purpose but possess a resonance structure that puts significant negative charge on the sulfur, enabling it to form strong metal-sulfur bonds compared to other sulfur-containing ligands such as thioethers …

Reuben Hersh's What Is Mathematics, Really? (Book Review), Calvin Jongsma

Faculty Work Comprehensive List

Reuben Hersh’s 1997 book What is Mathematics, Really? popularized a trend in the philosophy of mathematics that was gaining some traction at the time it was written. This essay examines Hersh’s work within the broader historical context of 19th- and 20th-century developments in mathematics and philosophy of mathematics. It also focuses on Hersh’s antagonism toward the influence of religion on (philosophy of) mathematics, concluding by briefly considering two positions taken by Christian mathematicians associated with ACMS in defense of such a connection.

Rectifying The Tephrostratigraphic Record Of The Pacific Northwest, Casey J. Crawford

Boise State University Theses and Dissertations

The Mid-Miocene Climatic Optimum (~17-14Ma) marks the last time that Earth’s atmospheric CO₂ concentrations were as high as modern levels, correlating to a peak of significant warming during an otherwise cooling trend through the Cenozoic. To understand how modern ecological systems may respond to CO₂ -induced climate change, paleontologists are studying how plant type and diversity changed with the rise and fall of CO₂ concentrations over the ~3Ma interval, and utilize intercalated tephras amenable to radioisotope geochronology to bracket fossiliferous horizons in time. The legacy model for tephrostratigraphy in the Pacific Northwest utilized Fe and Ca concentrations …

Improved Snow Distribution Estimates Using A Rapid-Response Lidar And Photogrammetry System, Naheem Idowu Adebisi

Boise State University Theses and Dissertations

Snow plays a critical role in global hydrology, climate systems, and human activities, particularly in mountainous regions where it is a primary source of freshwater, influences the energy balance, and impacts mobility and commerce. Despite its importance, accurately mapping and predicting snow distribution remains a major challenge due to the complex spatial and temporal variability of snowpack and the lack of an ideal observation system. This dissertation aims to advance our monitoring capability, understanding, and prediction capacity of snow distribution using Light Detection and Ranging (LiDAR) and photogrammetry techniques.

In chapter 2, I discussed the high-resolution LiDAR-derived datasets of multiple …

Effects Of Changing Winter Precipitation Phase On Streamflow Magnitude In Mountainous Regions, Josh Morell

Boise State University Theses and Dissertations

Snowmelt-produced streamflow (Q) is the dominant water source for a large portion of the global population. This is especially true in higher elevation regions in the Western United States. Precipitation is highly variable and seasonal in this region of the world. Generally, most precipitation occurs in winter and comes as snow in higher elevations. However, due to climate change, precipitation and temperature patterns are changing. It has been observed in many areas across the Western United States that the fraction of precipitation falling as snow (S_f) is declining because of a warming climate. In addition, …

Resilience Webtool: Engaging Community Partners To Humanize Data For Use In Local Resilience Planning In Valley County, Idaho, Sabrina Akther

Boise State University Theses and Dissertations

Advancements in technology have made hazard data increasingly available. However, officials in rural communities with limited resources often face challenges in accessing, interpreting, and applying these data to assess vulnerabilities and plan future development. Furthermore, when hazard data is not paired with relevant population and infrastructure, data vulnerability assessments become increasingly difficult. To address this challenge, this project aims to co-create a web tool with decision makers in Valley County, Idaho following a user-centered design approach, consolidating hazards, social vulnerability, and infrastructure data to help local officials with risk management, decision-making, and resilience planning. The project started with listening sessions, …

Cybersecurity's Pr Problem: The Education Gap Fueling Mfa Aversion, Tyler M. Stafford, Catherine Dwyer

Honors College Theses

Through surveying individuals with no professional experience in cybersecurity, this study examines the relationship between awareness and education surrounding security controls and end users’ willingness to adopt them. The findings reveal a strong link between understanding the effectiveness of these controls and user comfort, indicating that as end users’ understanding increases, so does their willingness to use the controls. Working in both identity and access management (IAM) and human risk management, I observed what appeared to be a connection between security education and positive attitudes toward security more broadly, but found limited research statistically linking the two. This study’s findings …

Bpa Adsorption On Microplastics In Different Chemical Conditions, Addison Zehren

University Honors Program Senior Projects

Microplastics (plastic particles < 5 mm in size) are increasingly seen as a health and environmental issue, both for their direct effects when ingested by living organisms and for their ability to adsorb and concentrate other pollutants. Current water treatment processes do not adequately remove microplastics from municipal water supplies, so a thorough understanding of how microplastics affect water quality is needed. The objective of this study is to evaluate the effects of certain water quality parameters on the ability of polystyrene microplastics (PS MPs) to adsorb Bisphenol A (BPA). BPA is an endocrine disruptor (chemically like estrogen) used in plastics which can be released into the environment and act as a water pollutant. Water quality chemical parameters investigated were chloride, nitrate, phosphate, and copper ions. Concentrations of each solute were selected based upon Environmental Protection Agency (EPA) guidelines and previous results obtained from testing Chicago River water samples. A constant amount of PS MPs and BPA were added to each sample and the mixtures were shaken for 5 days to allow time for the BPA to adsorb. The samples were then filtered and the amount of BPA left in the water was determined by measuring its UV absorbance on a UV-vis spectrophotometer. BPA concentrations decreased in the water indicating that it had been adsorbed onto the microplastic surface, with the highest adsorption present with copper, which reduced BPA concentrations from 6.7 mg/L to 3.9 mg/L. Statistical analyses showed differences between copper, phosphate, nitrate, and chloride (df = 9, p = 0.002). Future work can apply these results to investigate the implications of pollutant transportation in urban waterways like the Chicago River.

A Pure Rotational Spectroscopic Study Of Two Nearly-Equivalent Structures Of Hexafluoroacetone Imine, (Cf3)C=Nh, Daniel A. Obenchain, Beppo Hartwig, Daniel J. Frohman, Garry S. Grubbs, B. E. Long, Wallace C. Pringle, Stewart E. Novick, S. A. Cooke

Chemistry Faculty Research & Creative Works

Rotational spectra for hexafluoroacetone imine, the singly substituted 13C isotopologues, and the 15N isotopologue, have been recorded using both cavity and chirped pulse Fourier transform microwave spectrometers. The spectra observed present as being doubled with separations between each pair of transitions being on the order of a few tens of kilohertz which is consistent with a large amplitude motion producing two torsional substates. The observed splitting is most likely due to the combined motions of the CF₃ groups, for which the calculated barrier is small. However, no transitions between states could be observed and, similarly, no Coriolis coupling parameters …

Comprehensive Global Data Set Of Uniformly Processed Shear-Wave Splitting Measurements, Jonathan Wolf, Thorsten W. Becker, Edward Garnero, Kelly H. Liu, John D. West

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Seismic anisotropy can inform us about convective flow in the mantle. Shear waves traveling through azimuthally anisotropic regions split into fast and slow pulses, and measuring the resulting shear-wave splitting provides some of the most direct insights into Earth's interior dynamics. Shear-wave splitting is a constraint for path-averaged azimuthal anisotropy and is often studied regionally. Global compilations of these measurements also exist. Such compilations include measurements obtained using different data processing methodologies (e.g., filtering), which do not necessarily yield identical results, and reproducing a number of studies can be challenging given that not all provide the required information, for example, …

Analysing Bell Experiments Through Test Factors: Applications To Randomness And Strength Of Nonlocality, Soumyadip Patra

LSU New Orleans Theses and Dissertations

This work presents practical tools to analyse Bell experiments---experiments demonstrating correlations that defy classical explanations and proving that nature violates local realism. We begin by showing that in the Bell scenario specified by n parties with each party having a choice of m binary-outcome measurements---the (n,m,2) scenario---projecting weakly-signalling settings-conditional outcome distributions onto the smallest-dimensional affine subspace (containing the no-signalling set) via an L^2-distance-minimising map preserves correlators. This result ensures that Bell inequalities written in terms of correlators remain invariant under such projections, and we provide an efficient construction method for the projection operator that avoids computationally costly steps such as …

Assessment Of Lake Salvador Shoreline Dynamics To Support Restoration Of Submerged Aquatic Vegetation In Jean Lafitte National Historical Park And Preserve, Louisiana, Lydia V. Dipaola

LSU New Orleans Theses and Dissertations

High wave energy degrades shoreline habitat between Lake Salvador and Jean Lafitte National Historical Park and Preserve (JELA), Louisiana. JELA constructed a northern breakwater in 2004, and a southern breakwater in 2024 to protect the shoreline and promote restoration of submerged aquatic vegetation (SAV). This study analyzes Sentinel-2 imagery to quantify coastal loss along the JELA-Lake Salvador using the Change Polygon Approach, assessing annual, cumulative and major storm event-associated shoreline changes for January 2017-2025. SAV cover, nekton diversity, wave energy, and turbidity were measured before-and-after southern breakwater construction to monitor ecological and environmental outcomes. The JELA-Lake Salvador shoreline has lost …

Toward Robust Semantic Segmentation In Levee Infrastructure Monitoring: Enhancing Accuracy With High-Fidelity Synthetic Data And Ensemble Learning, Padam Jung Thapa

LSU New Orleans Theses and Dissertations

Abstract: Levees serve as critical flood protection structures, but failures due to inadequate maintenance and extreme water pressures have led to devastating events such as Hurricane Katrina. Manual inspections are slow, labor-intensive, and prone to human error, necessitating the development of automated solutions. This study proposes an AI-driven framework for levee inspection utilizing deep learning-based semantic segmentation to detect rutting and enhance the identification of sand boils. To address dataset limitations, high-fidelity synthetic images are generated using DreamBooth for fine-tuning, while ControlNet adds structural constraints to enhance realism and consistency. A semi-automatic convex hull annotation technique enhances labeling efficiency, and …

Animal Burrow Detection In Levee Systems Using Res-Net 34, Christopher D. Moore

LSU New Orleans Theses and Dissertations

Animal burrow detection is a time-consuming and costly task for levee inspectors. Annual budgets run up to approximately $16 million per state. The inspectors typically will have to travel to the inspection sites using government-assigned transportation. Depending on the distance to the site, it may take minutes or hours to arrive before any productive inspections occur. Once at the site, the inspectors were subject to human error, overgrown foliage, severe weather, or prohibitive landscaping that would make any human inspection impossible. Also, animal burrows could be small enough or overgrown, so the human inspector misses the problem areas. We aimed …

Ai Model For Predicting Asthma Prognosis In Children, Elham Sagheb, Chung-Il Wi, Katherine S King, Bhavani Singh Agnikula Kshatriya, Euijung Ryu, Hongfang Liu, Miguel A Park, Hee Yun Seol, Shauna M Overgaard, Deepak K Sharma, Young J Juhn, Sunghwan Sohn

Faculty, Staff and Student Publications

BACKGROUND: Childhood asthma often continues into adulthood, but some children experience remission. Utilizing electronic health records (EHRs) to predict asthma prognosis can aid health care providers and patients in developing effective prioritized care plans.

OBJECTIVE: We aimed to develop artificial intelligence (AI) models using various clinical variables extracted from EHRs to predict childhood asthma prognosis (remission vs no remission) in different age groups.

METHODS: We developed AI models utilizing patients' EHRs during the first 6, 9, or 12 years of their lives to predict their asthma prognosis status at ages 6 to 9, 9 to 12, or 12 to 15 …