Physical Sciences and Mathematics Commons^™

Examining Mulit-Wavelength Variability And Magnetic Interactions In The Polar St Lmi, Cain Rinkoski

Macalester Journal of Physics and Astronomy

Cataclysmic variable (CV) stars are interacting binary systems that exhibit exotic, multi-wavelength behavior driven by mass transfer from a donor star onto a white dwarf. As rich laboratories for accretion physics, binary dynamics, and the origins of Type Ia supernovae, CVs have been well studied in the X-ray, ultraviolet, optical, and infrared—but remain comparatively underexplored in the radio regime. This paper presents simultaneous, time-resolved optical and radio observations of the magnetic CV ST LMi, aimed at constraining its emission mechanisms and orbital modulation.
The optical light curves display brightness variations of approximately 1.31 ± 0.02 magnitudes on a period of …

A Thermal Control System For The Atlas Hgtd Module Construction Process, Keelin B. Murphy

Macalester Journal of Physics and Astronomy

In the aim of simplifying the production process of 2000 HGTD (High Granularity Timing Detector) modules at IJClab for the high luminosity phase of the ATLAS experiment at the CERN Large Hadron Collider, I designed, coded, and constructed an automatic temperature control system for module assembly and testing. To this end, I examined the module’s thermal response to changes in air temperature using a climate chamber and to various currents fed through a Peltier device situated under the module. I adapted the Peltier setup into a fully independent control system driven by an Arduino microcontroller running a PID feedback loop.

Leveraging Weekly Snow Cover Time Series For Improved Glacier Monitoring And Modeling, Rainey Aberle, Ellyn M. Enderlin, David R. Rounce, Shad O'Neel, Brandon Tober, Alexandra Friel

Boise State University Publications and Presentations

Seasonal snow and ice melt strongly influence glacier mass balance, yet sparse sub-annual observations limit our understanding of seasonal dynamics. Here we construct and analyze weekly snow cover time series for 200 glaciers across western North America from 2013 to 2023 using an automated image processing pipeline. Snow cover varied widely across the region: snow minima timing varied with latitude — from August from 62 to 64N to October from 48 to 50N—and accumulation area ratios ranged from near-zero to 0.92 (median of 0.52). A comparison of snowlines from observations and the PyGEM glacier mass balance model revealed seasonally evolving …

"...Anything My Friend Shares, I Would Want To Support Them By Clicking On It": Co-Designing Story-Based Interventions Against Clickbait For Teenagers, Ankit Shrestha, Audrey Flood, Bryson Hackler, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

Teenagers' lack of digital sophistication and cyber hygiene makes them vulnerable to social engineering attacks, especially as they start using social media. Clickbait, one of such attacks, is primarily performed through social media to trick users into clicking on malicious links. With teenagers' increasing use of social media, clickbait poses a substantial threat to their online safety. The existing online safety measures for teens mainly focus on parental mediation, which can be perceived as restrictive and privacy-invasive. To this end, researchers recommended empowering teens to deal with online risks. In order to design such interventions for clickbait, we conducted co-design …

Research And Education In Robotics: A Comprehensive Review, Trends, Challenges, And Future Directions, Mutaz Ryalat, Natheer Almtireen, Ghaith Al-Refai, Hisham Elmoaqet, Nathir Rawashdeh

Michigan Tech Publications

Robotics has emerged as a transformative discipline at the intersection of the engineering, computer science, and cognitive sciences. This state-of-the-art review explores the current trends, methodologies, and challenges in both robotics research and education. This paper presents a comprehensive review of the evolution of robotics, tracing its development from early automation to intelligent, autonomous systems. Key enabling technologies, such as Artificial Intelligence (AI), soft robotics, the Internet of Things (IoT), and swarm intelligence, are examined along with real-world applications in healthcare, manufacturing, agriculture, and sustainable smart cities. A central focus is placed on robotics education, where hands-on, interdisciplinary learning is …

An Example Where Taking An Additional Observation Doesn't Help, Stephen Portnoy, James Stein

Mathematics and Statistics Faculty Publications and Presentations

It seems intuitively obvious that no part of a random sample should be discarded. However, for most students, the first formal justification of this idea is when sufficiency is introduced in an introductory statistical theory course. Students are often left with the idea that conditioning on the sufficient statistic always improves inference, even though the formal theory only says that for any statistical procedure there is one depending on the sufficient statistic that is no worse. Here we present an example on comparing two coins based on two consecutive tosses, where the optimal probability of guessing which coin has the …

A Generalization Of Franklin’S Partition Identity And A Beck-Type Companion Identity, Gabriel Gray, David Hovey, Brandt Kronholm, Emily Payne, Holly Swisher, Ren Watson

School of Mathematical & Statistical Sciences Faculty Publications

Euler’s classic partition identity states that the number of partitions of n into odd parts equals the number of partitions of n into distinct parts. We develop a new generalization of this identity, which yields a previous generalization of Franklin as a special case, and prove an accompanying Beck-type companion identity.

The People's Rivers: Early Environmental Regulation And The Oregon State Sanitary Authority, Avery Morgan Fischer

Dissertations and Theses

The environmental movement in Oregon can trace its origins to the turn of the twentieth century, where citizen activism and initiative led to the creation of an early environmental regulatory agency, the Oregon State Sanitary Authority. This creation established that the State of Oregon had a duty to preserve, not just the navigability or usability of rivers and waterways, but the quality and purity of its water. The Oregon State Sanitary Authority played an active role in maintaining and protecting the environment as a mandate of the people, and throughout its thirty-year existence battling industrial polluters, reluctant municipalities, and disinterested …

Quasistatic Peridynamics, Existence Of Unique Solution In The Presence Of Damage, Nuwanthi N. Samarawickrama

LSU Doctoral Dissertations

A mathematical model for damage propagation based on nonlocal potentials is developed within the framework of peridynamics. This model is applied to simulate damage evolution in cyclically loaded structures. By neglecting inertial effects, a well-posed quasistatic formulation for cyclic loading is obtained.\\ The resulting equation is expressed as a nonlocal and nonlinear integral operator that couples damage evolution to the deformation field.\\ This coupling occurs through the product of a damage factor and the derivative of a force potential. The damage factor ranges between zero and one, where one represents undamaged material and zero indicates complete damage.\\ It serves to …

Digital Forensics And Ai: Artifact Analysis And Using Ai In The Forensics Domain, Clinton Joel Walker

LSU Doctoral Dissertations

Digital Forensics (DF) is a field of forensic science focusing on the acquisition, authentication, and analysis of digital evidence while maintaining integrity of that data. DF analysts use forensic tools to parse large volumes of data for investigations and depend on them for identification of pertinent digital evidence in vast amounts of data. Keeping up with innovations and ever-expanding data volumes is a constant challenge for these investigators. The prevalence of Artificial Intelligence (AI) in everyday computing is rapidly expanding, with the use of Machine Learning (ML) and Large Language Models (LLM)s becoming increasingly commonplace. Innovations in technology bring new …

Towards Leveraging Social Media Data For Fostering Collaborations Among Non-Profits, Monazil Chowdhury

LSU Doctoral Dissertations

Nonprofit organizations serve a crucial role in tackling a wide range of significant social, environmental, and economic issues. But it is often hard to get a clear picture of their work because their information is spread out and it is difficult to see how they are collaborating. To address this issue we developed a web-based tool to collect scattered data—from a variety of sources, such as the IRS, social media, and the Census, into one easy-to-use resource. The tool begins by taking IRS records and geocoding each nonprofit’s physical address With its coordinates. It then retrieves census tract information from …

Dose Characterization Of Galactic Cosmic Rays In The Human Brain: A Phits-Based Study With A Segmented Anatomical Phantom, Shanice N. Manning

LSU Master's Theses

Astronauts aboard the International Space Station (ISS) are chronically exposed to a complex space radiation environment composed of galactic cosmic rays (GCR), solar particles, and Earth's trapped radiation. These high-energy particles interact with spacecraft shielding, producing secondary particles that can penetrate inside and deposit energy in sensitive tissues. Although animal studies have been useful in assessing space radiation risks, anatomical and physiological differences limit their applicability to human anatomy especially neuroanatomy. To address this gap, we developed a computational framework to model radiation dose distribution within the human brain using Monte Carlo simulations in Particle and Heavy Ion Transport code …

Hyperspectral Band Selection Via Heterogeneous Graph Convolutional Self-Representation Network, Junde Chen, Wenzhao Li, Surendra Maharjan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Hyperspectral image (HSI) band selection (BS) plays a crucial role in HSI dimensionality reduction, aiming to identify a representative subset of bands with minimal redundancy. However, conventional BS approaches primarily operate in the Euclidean domain, often overlooking the structural characteristics of pixels and spectral bands, such as spatial continuity and spectral dependencies. In addition, they handle each HSI as an integrated unit to harness implicit spatial information, disregarding spatial distribution variations across different homogeneous regions. To fully leverage structural information, this study introduces a novel BS method, termed the dual heterogeneous graph convolutional network with enhanced self-representation (ESR-HGCN), for HSI …

Review Of Averting The Digital Dark Age: The Future Of Digital Literary Heritage, Rebecca L. Hastings

Journal of Contemporary Archival Studies

In Averting the Digital Dark Age: How Archivists, Librarians, and Technologists Built the Web a Memory, Ian Milligan explores the efforts of technologists and information professionals to develop means of preserving information shared on the World Wide Web. The web lacks a built-in archiving function, raising fears of a “digital dark age,” an unprecedented gap in the historical record as information sharing via the web increases. Milligan tracks the development of web preservation debates and activities from the anxiety and turmoil of the early to mid-1990s to the coming of age of web preservation in the wake of the …

A Study Of Machine Learning Techniques In Solving Biochemical And Chemical Problems, Kenneth Micheal Plackowski

Chemistry and Chemical Biology ETDs

Data-driven approaches to solving problems in biology and chemistry require utilization of reliable techniques and machine learning algorithms are the modern reliable approach. This work presents three problems that involve use of supervised learning techniques when classification is the goal and unsupervised learning techniques when global data representation is the goal.

In the first problem, we demonstrate the use of unsupervised clustering techniques, self-organizing maps and K-means, to ascertain analyte detection capabilities of carbon nitride dots. In the second problem, we add scalability features to a functional group classification model applied to infrared data and evaluate its ability to inform …

Nanoporous Gold Nanoparticles And Model Membrane Systems Applied To The Study Of Lipopolysaccharide (Lps), Dhanbir Lingden

Dissertations

Lipopolysaccharide (LPS), a key structural component of Gram-negative bacteria, is a major trigger of sepsis and septic shock, the systemic inflammatory conditions responsible for millions of deaths annually. Even at concentrations as low as 1 ng/mL, LPS can activate the immune system and initiate inflammatory cascades. According to the Global Burden of Disease Study 2017, sepsis accounted for 48.9 million cases globally, with 11 million deaths, emphasizing the urgent need for improved diagnostic and therapeutic strategies.

Accurate and rapid detection of LPS is vital for early intervention and improved clinical outcomes. While traditional detection methods are still widely used, modern …

How Multi-Scale Modeling Can Help Examine Social Determinants Of Health And Resulting Disparities, Kyoko Yoshida, Elsje Pienaar, Shalanda A. Bynum, Naomi Chesler, Mitchel J. Colebank, Jessie Heneghan, Nadra Tyus, Jasmine Miller-Kleinhenz, Bruce Y. Lee

Faculty Publications

Social determinants of health (SDOH) are the conditions in which people live, work, and play, and the wider set of factors (e.g., social and economic systems and policies) that shape a person’s daily life. SDOH can differ significantly across communities and populations, having positive impacts for some and negative impacts for others. Ultimately, this results in differences in health and disease distribution, that are known as health disparities. Despite the known impacts of SDOH and calls to characterize, address, reduce, and eliminate health disparities, they persist and, in some cases, have worsened. To address this challenge, a session at the …

Using Linear Programming And Game Theory To Optimize The Relation Between Us And China, Junhao Su

Student Works

This paper develops an optimization model to analyze U.S.–China bilateral trade dynamics and competition in artificial intelligence (AI). First, grounded in WTO tariff limits, we formulate a linear programming model to maximize the combined trade volume and conduct a comprehensive sensitivity analysis on tariff parameters. Second, we integrate zero‑sum and non‑zero‑sum game‑theoretic frameworks to identify the Nash equilibria governing both trade negotiations and technological rivalry. The model is implemented in Python using PuLP and is empirically validated with real‑world tariff data to highlight the policy relevance of the optimal solutions. Our results reveal a high concordance between the zero‑sum game …

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) 2022 Draft Final Insufficiently Reclaimed Sites Sampling: Bres No. 32 Site Evaluation Summary Report (Dated December 11, 2024), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Integrating Artificial Intelligence And Machine Learning Technologies Into Common Operating Picture And Course Of Action Development, C. Anthony Pfaff, Christopher John Hickey

Books, Monographs & Collaborative Studies

C. Anthony Pfaff and Christopher John Hickey, Principal Investigators

©2025 C. Anthony Pfaff. All rights reserved.

Integrating Artificial Intelligence and Machine Learning Technologies into Common Operating Picture and Course of Action Development explores the potential of artificial intelligence (AI) and machine learning to revolutionize military planning processes by enhancing situational awareness and expediting course of action development within the Joint planning process. The study delves into technical, organizational, and resource considerations that are critical for AI integration. In addition, the study highlights the importance of clean, structured data in training AI systems, addresses challenges in data collection across varying formats …

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) 2022 Draft Final Insufficiently Reclaimed Sites Sampling: Bres No. 38 – Sister Dump Site Evaluation Summary Report (December 31, 2024), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Analyzing Environmental Health: Air Pollution And Human Health Using Geospatial Data Science, Yanhong Huang

Geography ETDs

Air pollution from industrial emissions and wildfire smoke poses growing threats to public health. This dissertation employs geospatial data science to examine these challenges through three interrelated studies. The first study investigates the relationship between maternal residential exposure to industrial pollutants and low birth weight, identifying five chemicals as significant risk factors. The second study assesses the impact of industrial air pollution on lung and bronchus cancer survival, finding that exposure to 1,1,1-trichloroethane and cobalt is associated with reduced survival. The third study explores disparities in wildfire smoke PM_2.5 exposure and its association with asthma exacerbations. Results show disparities …

Theoretical And Experimental Investigation Of Liquid-Liquid Phase Separation: Characterizing Elastin-Like-Polypeptides, Adam D. Quintana

Chemical and Biological Engineering ETDs

This dissertation develops and validates a semi-empirical Flory–Huggins-based interaction model, combined with Cahn–Hilliard simulations, for predicting multi-component liquid–liquid phase separation (LLPS) in elastin-like polypeptide (ELP) systems. Equilibrium droplet compositions, measured using a PDMS-based microfluidic device, enabled direct parameterization of interaction coefficients. The model was applied to generate phase diagrams and assess composition dependence in ternary mixtures. Cahn–Hilliard simulations were conducted to explore potential phase morphologies under different interfacial conditions. Multi-component Lattice Boltzmann simulations were implemented to model droplet morphology evolution under varying interfacial and diffusive parameters, reproducing experimentally relevant morphologies. A three-phase wetting study revealed conditions for selective wetting and …

A Review Of Automation In Small Satellite Operations, Joseph Melville, Andrew Narvaez, Lee Jasper

Space Dynamics Laboratory Publications

In the context of congested orbital space, the proliferation of small satellite constellations aims to enhance resilience and responsiveness in on-orbit systems. The escalating number and diversity of small satellites and the need for intersatellite coordination pose operational challenges. Chief among these challenges is that the quantity of operators needed to fully utilize these deployed systems is prohibitively large and expensive; further, operators simply may not be responsive enough to events.

Automated systems, both on-board and ground-based, offer a viable solution to streamline various operational tasks. The integration of automation mitigates the operational burden, minimizes errors originating from human intervention, …

A Machine Learning Approach To Quantitative X-Ray Diffraction Analysis, Spencer Snow Chandler

Theses and Dissertations

X-ray Powder Diffraction (XRPD) is a powerful method in material sciences that gives insights into the atomical and crystallographic structure of a material, revealing information into the material's properties and suitability for industrial and scientific application. In geology, XRPD analysis is frequently leveraged to identify and quantify the present mineral phases in an unknown mixture. Despite it's widespread use, interpreting XRPD patterns requires highly-specialized knowledge, making the analysis largely dependent upon the background experience of the analyst. To assist experts, computational methods have been developed over the years. Some of these techniques involve fitting diffraction patterns using pseudo-Voigt functions, which …

Approximating Transport Maps Using Minibatch Optimal Transport Plans, Dawson Collins

Theses and Dissertations

Optimal Transport theory (OT) has gained much attention in the past decades due to its rich mathematical content and striking connections to other areas of math. It has also naturally found a place in data science as a way to compare and transform probability measures. Unfortunately, there remain significant computational burdens that restrict its effectiveness in large-scale data regimes. In this thesis, we consider Minibatch Optimal Transport (MiniOT), which breaks up the task of computing the optimal transport plan between datasets into several smaller tasks of computing the optimal transport plan between minibatches of the datasets. After obtaining the minibatch …

Subspace And Auxiliary Space Preconditioners For High-Order Interior Penalty Discretizations In H(Div), Will Pazner

Mathematics and Statistics Faculty Publications and Presentations

In this paper, we construct and analyze preconditioners for the interior penalty discontinuous Galerkin discretization posed in the space H(div). These discretizations are used as one component in exactly divergence-free pressure-robust discretizations for the Stokes problem. Three preconditioners are presently considered: a subspace correction preconditioner using vertex patches and the lowest-order H1-conforming space as a coarse space, a fictitious space preconditioner using the degree-p discontinuous Galerkin space, and an auxiliary space preconditioner using the degree-(p − 1) discontinuous Galerkin space and a block Jacobi smoother. On certain classes of meshes, the subspace and fictitious space preconditioners result in provably well-conditioned …

Seeking Structure In Complex Systems: From Feature Analysis To Space-Time Causal Discovery With Earth Science Applications, Jeffrey J. Nichol

Computer Science ETDs

Complex systems are difficult to study because of their many interacting parts, emergent phenomena, and feedback loops. These systems underpin all life on Earth. We need improved tools for seeking an understanding of them. This body of research presents my investigations into data-driven methods for understanding complex systems, including my invention of a novel causal discovery meta-algorithm for space-time gridded data. I demonstrated machine learning feature importance and causal discovery capabilities for comparing simulated and observed climate data. I developed a new benchmark for modeling space-time dynamics of locally driven phenomena and examined a prominent causal discovery algorithm. Finding that …

Creativity And Curb Cuts: Experiences In Our First Offering Of A Front End Development And Accessibility Focused Cs Course, Briana C. Bettin, Tony Garnett, Alex Gore, Andrea Llanas

Michigan Tech Publications

Students learn an abundance of technical skills while obtaining a computer science degree. The ability to develop meaningful front end user interfaces is often considered the domain of only ''more artistic'' CS students. However, for users to effectively engage with any piece of software, functional user interfaces are critical. Moreover, even among students who have front end skills, semantic and accessible design is all too often less considered. The first author piloted a ''Front End Development and Accessibility'' course this past Fall. This course teaches basic skills of front end with web and leverages key accessibility standards via WCAG. This …

The Role Of The Cytosolic Chaperonin Cct In The Folding And Assembly Of G Protein Complexes, Mikaila I. Sass

Theses and Dissertations

All organisms depend on cellular signaling pathways to dictate cell growth, responses to stimuli, and all other cellular functions necessary to maintain health and survival. Many of these signals rely on G protein coupled receptors (GPCRs) and their associated heterotrimeric G proteins for signal detection and transduction. To perform this function, the three subunits of the G protein must be assembled after synthesis on the ribosome. This process requires additional proteins called molecular chaperones to assist in folding of the subunits and assembly into the G protein heterotrimer. Among these chaperones, the cytosolic chaperonin CCT plays an essential role in …