Physical Sciences and Mathematics Commons^™

Largemouth Bass Diet Changes Through The Summer In Central Minnesota, Ethan Kunz

Journal of Earth and Life Science

Largemouth Bass Micropterus nigricans is one of the most widespread fish species in the world, due in part to human introduction for angling. Largemouth Bass are opportunistic predators that will consume the largest prey they can often find; however, it has been shown that their diet mainly consists of invertebrates such as crayfish, with less focus on other fish species. This research aimed to determine what the Largemouth Bass diets in Central Minnesota consist of, and how they may change from the beginning of summer through the beginning of fall. A total of 174 Largemouth Bass were sampled from late …

Captive Model Test For Hydrodynamic Derivatives Of Ship Maneuvering In Regular Head Waves, Pin-Yuan Huang, Zih-Yao Lin, Tsung-Yueh Lin, Fu-En Lee, Yan-Wei Lai

Journal of Marine Science and Technology–Taiwan

The motion of ship in wave can be discussed in seakeeping and maneuvering. In model tests, the former is found by the motion response of waves while the latter requires captive model test to acquire hydrodynamic derivatives. The hydrodynamic derivatives in waves are discovered to be different from those in calm water. To understand better the behavior of maneuverability in waves, maneuvering tests in a wide range of waves are performed in this study. This study presents an experimental investigation into the maneuvering behavior of a container ship in regular waves, covering a wide range of wavelengths from half to …

Exploring Mesoproterozoic Marine Redox States In A Young Banded Iron Formation From The Needle Mountains, Jaya Sharma, Brenhin Keller

Wetterhahn Science Symposium Posters

Banded iron formations (BIF), as redox-dependent chemical sedimentary rocks, have served as proxies for marine and atmospheric oxygen and iron conditions throughout Earth history. While abundant in the Archean and early Proterozoic, the widespread deposition of BIFs declined following the Great Oxidation Event, as oxygenated surface waters prevented the accumulation of ferrous iron. However, the Needle Mountains, located in southwestern Colorado, houses an anomalously young BIFs deposited between 1.786±10 - 1.801±6 Ga given existing geochronology. Here, we use rare earth element (REE) systematics, bulk chemistry, and petrographic analysis to determine the depositional conditions under which this BIF was formed. We …

Probing Feni Alloys With Atomic Precision, Scipio Han, Kaushik Rajkumar Jayaprabha, Xin Qi

Wetterhahn Science Symposium Posters

We compared EAM and MEAM atomic potentials for modeling FeNi (tetrataenite), a rare 50/50 alloy found in meteorites. Picking 4 potentials, we calculated minimum lattice constants and order-disorder transition temperatures. MEAM potentials accurately predicted the experimental transition temperature, confirming that MEAM better captures FeNi's directional bonding.

Carbon Storage In Headwaters Can Respond Rapidly To Climate Change, Maddie Benello, Carl Renshaw, Joshua Landis

Wetterhahn Science Symposium Posters

Headwater streams play a critical role in the global carbon cycle, serving as significant sites of carbon storage. While there have been recent efforts to quantify carbon storage in headwater streams in the western United States, there remains limited understanding of both the volume and timescale of carbon storage in northeastern forests which often have extensive logging and agricultural histories. Here, we quantify the carbon stock, residence time, and flux of a zero-to-first order headwater stream in Charles Downer State Forest (DF), VT using novel fallout radionuclide (FRN) chronometry. We find DF headwaters have a carbon stock of 66.2 Mg …

Magnetic Anisotropy Engineering In Rare-Earth-Free Iron-Based Magnetic Materials, Pramanand Joshi

Physics Dissertations - Archive

The development of high-performance, rare-earth-free hard magnetic materials is critical for next-generation energy, information, and spin-based technologies. This dissertation investigates structure-property relationships in iron-based magnetic systems, including iron carbides, Fe-Co-B boride alloys, hexaferrites, and FeCo nanostructures, synthesized via chemical and metallurgical routes. Through controlled synthesis and comprehensive structural and magnetic characterization, this work demonstrates that magnetic anisotropy, coercivity, and thermal stability can be systematically controlled through morphology design, compositional tuning, microstructural refinement, and interparticle interaction modulation.

Morphology-driven enhancement of magnetic properties, particularly coercivity and blocking temperature, is established in phase-pure Fe₅C₂ nanostructures. By precisely controlling particle geometry, …

Applications Of Doppler Broadening Spectroscopy For The Characterization Of The Surface And Near Surface Of Two-Dimensional Heterostructures, Hany M. Mahdy

Physics Dissertations

This dissertation describes experiments and the analysis of Doppler broadening spectroscopy applied to metal surfaces (Cu, Ag, Au), graphene/Cu heterostructures, and SiGe heterostructures, with particular emphasis on the development of new approaches for extracting quantitative information from annihilation spectra.

The first part establishes the capability of Doppler broadening spectroscopy, particularly coincidence Doppler broadening (CDB), as a surface-sensitive technique. Measurements on clean and adsorbate-covered Cu, Ag, and Au surfaces demonstrate that Doppler-broadened annihilation spectra retain element-specific signatures from the topmost atomic layer. New analysis methods based on ratio-curve modeling enable identification and quantification of sub-monolayer adsorbates, including sulfur, oxygen, selenium, and …

Timing, Orbital Pacing, And Provenance Of Late Paleogene Loess In The Western United States, Xiangwei Guo

Earth & Environmental Sciences Dissertations - Archive

This project examines the timing of loess emergence, the nature of the fluvial–eolian transition, orbital forcing on dust accumulation, and sediment recycling in the late Paleogene White River Formation (Group) of Wyoming and Nebraska, western United States. By integrating traditional sedimentology with machine learning–enhanced grain-size analysis, this research shows that loess accumulation at Flagstaff Rim in central Wyoming began during active fluvial deposition at approximately 35.8 Ma, indicating a gradual transition from fluvial to eolian conditions. Machine learning complements field sedimentology and granulometric interpretation while enabling the development of new, testable hypotheses. Extending this framework eastward to Toadstool Geologic Park …

Occurrence Of Microplastics In The Urban Air And Water Systems And Associated Exposure Risks, Jenny K. Nguyen

Earth & Environmental Sciences Theses - Archive

Microplastics (MP) pollution is an emerging health concern that affects humans and the environment. Urban areas are high exposure zones due to consistent anthropogenic and industrial activity. With air and water as important MP transport and exposure pathways, monitoring and estimating their human exposures are necessary. Air samples were collected from Dallas-Fort Worth (DFW) and Houston in Texas and Cusco, Peru and water samples were from Tarrant County (DFW), Texas. The samples were analyzed using the pyrolysis-gas chromatography/mass spectrometry (Pyr-GC/MS) and the EDI (estimated daily intake) of inhalation and ingestion (normal and high exposures) were calculated. PS, PP, PE, PVC, …

Digital Redlining In The Smart City: Artificial Intelligence, Housing Law, And Structural Urban Inequality, Spurthi Nrusimhadevara

Undergraduate Scholarship and Creative Works

Artificial intelligence is increasingly used in urban housing systems, where it shapes decisions about tenant screening, rent pricing, lending, zoning, and neighborhood investment. Although these tools are often promoted as efficient and impartial, they frequently rely on historical data that reflect racial, economic, and spatial inequality. As a result, AI systems can reproduce discriminatory outcomes even when protected characteristics are not directly used. This paper examines digital redlining in the smart city and argues that algorithmic housing tools mirror long standing structural inequities that raise significant concerns under fair housing and civil rights law. It evaluates how automated screening, predictive …

Supercharging Simulation-Based Inference For Bayesian Optimal Experimental Design, Samuel Klein, Willie Neiswanger, Daniel Ratner, Michael Kagan, Sean Gasiorowski

Physics Faculty Publications

Bayesian optimal experimental design (BOED) seeks to maximize the expected information gain (EIG) of experiments. This requires a likelihood estimate, which in many settings is intractable. Simulation-based inference (SBI) provides powerful tools for this regime. However, existing work explicitly connecting SBI and BOED is restricted to a single contrastive EIG bound. We show that the EIG admits multiple formulations which can directly leverage modern SBI density estimators, encompassing neural posterior, likelihood, and ratio estimation. Building on this perspective, we define a novel EIG estimator using neural likelihood estimation. Further, we identify optimization as a key bottleneck of gradient based EIG …

Understanding Circulant Permutation To Extend The Cminhash Estimator, Keegan Kang, Avery Hood, Benedict H.W. Wong

Faculty Conference Papers and Presentations

CMinHash promises a new direction for designing MinHash algorithms with reduced variance and storage space via circulant permutations. However, the original variance analysis is difficult to extend to other MinHash estimators. We present a new approach that gives explicit and easily comparable approximate variance expressions, and use it to analyze the Minner estimator. Numerical experiments show that our variance expression matches the empirical mean square error (MSE) of estimates. Our work thereby demonstrates how to apply circulant permutation to other MinHash estimators and compute their approximate variance.

The Soft Target Curriculum: Using Nigeria's 2026 Cascading Breaches To Teach Foundational Cybersecurity Failures, Chinedum Amaechi, Doris Asogwa, Samuel Alade

Journal of Cybersecurity Education, Research and Practice

SourceURL:file:///home/amaechi/Documents/ *Journal of Cybersecurity Education, Research and Practice (JCERP)*. **Title:** The Soft Target Curriculum: Using Nigeria's 2026 Cascading Breaches to Teach Foundational Cybersecurity Failures.docx

Background: Between March and April 2026, a single threat actor allegedly compromised four Nigerian institutions across banking, payment infrastructure, government registry, and power distribution sectors. The breaches exposed millions of records and disrupted critical services, yet all four exploited elementary vulnerabilities taught in introductory cybersecurity courses. Objective: This pedagogical case study analyzes the four breaches as a unified phenomenon of "normalized negligence" and provides ready-to-use teaching materials for cybersecurity educators. Methods: Using open-source intelligence analysis of …

Most Utahns Support Affirming Rights Of Great Salt Lake, Sarah A. Woodbury, Kirsten Vinyeta, Jessica D. Ulrich-Schad, Darren Parry

Utah People and Environment Poll (UPEP)

A combination of water diversions and climate change-related shifts have led to record low water levels and increasing salinity at Great Salt Lake (GSL) (1, 2).  Low water levels not only impact those directly dependent on the lake—brine shrimpers and migratory birds, for example—but also the millions of individuals living along the Wasatch Front. Increasing toxic dust levels from exposed lakebed and potential shifts to snowpack in the region are of primary concern. Children and marginalized communities are especially vulnerable to the respiratory health impacts of toxic dust (3, 4). According to the 2023 Utah People & Environment Poll (UPEP), …

Summary Of Beaver And Iron Counties’ Water Conservation And Provisioning Strategies, Lisa Welsh, Joanna Endter-Wada, Burdette Barker, Bethany Neilson, Anna Mcentire, Melissa Stamp, Brian Steed

Reports

This report focuses on water conservation and provisioning strategies that both Beaver and Iron Counties are pursuing to help meet their citizens’ current and future water needs and to contribute to statewide water conservation efforts. It primarily relies on publicly available data from state, county, conservancy district, and city databases, plans, and documents. The purposes of this document are to provide regional context for understanding water use in Beaver and Iron Counties and to describe water conservation strategies that can influence the trajectories of their future water use. 

In both Beaver and Iron Counties, agriculture remains the primary user of …

Assessment Of Soybean Response To Irrigation Variability In Eastern Nebraska Using The Aquacrop Model, Anmol Singh, Saleh Taghvaeian, Yufeng Ge, Derek M. Heeren, Frank Bai

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Soybean [Glycine max (L.) Merr.] is a major irrigated crop in eastern Nebraska, where recent expansions in irrigated agriculture and projected trends in irrigation demand necessitate thorough investigations of approaches that can optimize its irrigation management. In this study, the AquaCrop model was calibrated and validated using 19 variable irrigation treatments from a five-year field experiment. The model accurately simulated canopy cover, soil water content, and grain yield, with validation normalized root mean square error (nRMSE) of 12%, 7%, and 7%, respectively. The model was subsequently applied to estimate soybean yield and water requirement during a 15-year period (2010–2024) …

Understanding How Erosion And Unit Thickness Alter The Deformation Of Fold-Thrust Belts, Kaitlyn E. Gallis, Caroline M. Burberry

Nebraska Academy of Sciences: Programs and Proceedings

When a collision of two tectonic plates occurs, fold thrust belts develop, which are widely recognized as the most common mode in which the crust accommodates shortening. Most analog models do not consider erosion when documenting fold thrust belt formation. The lack of experiments on this topic means there are limited consistent studies on the relationship between erosion and deformation. Preliminary experiments suggest that the typical forward breaking thrust sequence is altered by eroding the hinterland, something this experiment series aims to prove or disprove. The new contribution of this work is a systematic evaluation of the variation in initial …

Identifying Relevant Covariates In Rna-Seq Analysis By Pseudo-Variable Augmentation, Yet Nguyen, Dan Nettleton

Mathematics & Statistics Faculty Publications

RNA-sequencing (RNA-seq) technology allows for the identification of differentially expressed genes, which are genes whose mean transcript abundance levels vary across conditions. In practice, RNA-seq datasets often include covariates that are of primary interest in addition to a set of covariates that are subject to selection. Some of these covariates may be relevant to gene expression levels, while others may be irrelevant. Ignoring relevant covariates or attempting to adjust for the effect of irrelevant covariates can compromise the identification of differentially expressed genes. To address this issue, we propose a variable selection method that uses pseudo-variables to control the expected …

Utilizing Machine Learning Techniques For Computer-Aided Covid-19 Screening Based On Clinical Data, Honglun Xu, Andrews T. Anum, Michael Pokojovy, Sreenath Chalil Madathil, Yuxin Wen, Md Fashiar Rahman, Tzu-Liang (Bill) Tseng, Scott Moen, Eric Walser

Mathematics & Statistics Faculty Publications

The COVID-19 pandemic has highlighted the importance of rapid clinical decision-making to facilitate the efficient usage of healthcare resources. Over the past decade, machine learning (ML) has caused a tectonic shift in healthcare, empowering data-driven prediction and decision-making. Recent research demonstrates how ML was used to respond to the COVID-19 pandemic. This paper puts forth new computer-aided COVID-19 disease screening techniques using six classes of ML algorithms (including penalized logistic regression, random forest, artificial neural networks, and support vector machines) and evaluates their performance when applied to a real-world clinical dataset containing patients’ demographic information and vital indices (such as …

Considerations For Assigned Water After Expiration Of The 2007 Guidelines, Kathryn Sorensen, Sarah Porter, Anne Castle, John Fleck, Eric Kuhn, Jack Schmidt, Katherine Tara

The Traveling Wilburys of the Colorado River

As Colorado River supplies and demands reach razor-thin margins, new tools to provide adaptive capacity will play a critical role in sustaining communities across the West. We must reduce our consumption of water, while finding ways to cushion the impact. One of the most innovative tools for doing this, developed over the last two decades, is “Assigned Water” - giving users the ability to store conserved water earmarked for their own future use. Originally developed as “Intentionally Created Surplus” in the 2007 Colorado River Interim Guidelines, Assigned Water has been revised and expanded through U.S. Mexico Treaty Minutes and as …

From Sediment To Mangrove: Tissue-Specific Metal Accumulation In Red Mangroves Of Southeastern Florida, Sophie Welch

Honors Theses

Coastal wetlands near industrialized waterways face increasingly heavy‐metal contamination, posing risks to benthic communities and food webs. Mangroves can influence metal cycling through sediment trapping, root‐zone sequestration, and internal physiological regulation, yet their effectiveness in urbanized systems remains debated. This study quantified concentrations of 17 heavy metals in sediments and mangrove tissues from four sites near Port Everglades, Florida, examined tissue‐specific partitioning, spatial and temporal contamination patterns, and examined the mangroves’ role in mediating metal loads. Ecological risk metrics identified STB as a contaminant hotspot with exceedances of TEL values across multiple elements (Ni, Pb, and Zn) as well as …

A Dual-Emission Polymer-Dots/Gold-Nanoclusters Nanohybrid For Ratiometric Fluorescence Detection Of Hg²⁺, Sha Wu

Dissertations and Theses

Heavy metals, such as Hg, Cd, Pb, and Cr, become a serious environmental problem because they are highly toxic, bioaccumulation, and long-term persistence, required a high sensitivity and selectivity detection method. Although laboratory testing instruments, such as inductively coupled plasma mass spectrometry, offer high sensitivity, their practical application is limited because they rely on large-scale equipment and complex sample pre-treatment processes. Single-emission fluorescence probes are simpler but can be affected by variations in probe concentration, excitation intensity, and measurement conditions. In this study, a dual-emission nanohybrid that consists of poly(9,9-di-n-hexylfluorenyl-2,7-diyl) (PDHF) and bovine serum albumin (BSA), termed as PDHF-Pdots/BSA-AuNCs nanohybrid, …

Linking Boundary Type, Storm Mode, And Tornado Intensity In Illinois, Jakob Barton

A with Honors Projects

A large dataset of tornadoes across Illinois from 2007-2024 were analyzed for different characteristics of thunderstorms and tornadoes, these characteristics were then compared with each other to find correlation and trends.

Image-Derived 3d Hepatic Lobule Modeling Of Acetaminophen-Induced Hepatotoxicity, Rebecca Lauren Strauss

Selected Full-Text Master Theses 2021-

The liver’s highly structured vascular microarchitecture governs blood perfusion, metabolic zonation, and the spatial distribution of xenobiotic toxicity. Current computational models of hepatic drug metabolism often oversimplify this geometry, limiting their ability to capture realistic flow dynamics and cellular injury patterns. This study develops a multiscale computational framework to predict acetaminophen-induced hepatotoxicity using image-derived, three-dimensional hepatic lobule geometries. The model integrates computational fluid dynamics (CFD) with a mechanistic cellular injury module to simulate the interplay between perfusion, metabolism, and hepatocellular viability.

Realistic vascular reconstruction was achieved from histopathology liver slices, and the resulting geometry was meshed and solved using ANSYS …

Deep Learning For Eeg-Based Emotion Recognition With Temporal And Spectral Interpretability, Shruti Rameshbhai Shingala

Selected Full-Text Master Theses 2021-

Electroencephalography (EEG)-based emotion recognition has emerged as a critical component of affective computing and clinical neuroscience. Existing approaches to this problem primarily reduce the multi-dimensional EEG time series to a single averaged feature vector, thereby discarding the temporal structure of the emotional response. The present work addresses three identified gaps in the literature: the absence of temporal interpretability, the uniform use of frequency bands, and the use of single-scale temporal feature extraction. A deep learning architecture, MST-Mamba-Asym, is proposed, comprising four components: Asymmetry Attention, which encodes hemispheric asymmetry by computing signed left–right channel differences, FreqBandAttention, which learns differential weights across …

Large Language Model Communication And Data Transfer Across A Simulated Telephone Line, Jared Reyes

Dissertations and Theses

This thesis presents a proof-of-concept communication system in which two local large language model endpoints communicate across a simulated analog telephone line using legacy USB modems. The project combines modem voice mode, modem data mode, local speech processing, and structured machine messaging into a single staged session. During the voice phase, one endpoint places a call, the other answers, speech generated by a locally hosted LLaMA-family model is synthesized with Piper, transmitted through the modem voice path, captured on the remote side, and transcribed with Faster-Whisper to drive the next response. After the voice exchange, the system transitions to a …

Prime Numbers And Rsa Encryption In Cryptology, Burak Safaker

A with Honors Projects

This project centers on developing an encryption and decryption system using the RSA (Rivest-Shamir-Adleman) cryptographic algorithm, which is based on the mathematical properties of prime numbers.

Rethinking Climate Change Education: Wyoming And New Jersey As Effective Models Of Climate Change In Education Standards, Jamie W. Miller

Pitzer Senior Theses

Education is an essential and oft-overlooked part of the conversation about climate change. As I’ll demonstrate in this thesis, education shapes how the public understands climate change and creates environmental knowledge, attitudes, behaviors, and intentions. Exploring and understanding climate change education allows us to understand how people form perspectives about climate issues. This topic is extremely important, but one we often gloss over when thinking about climate solutions. I analyzed three case studies of educational standards in the United States to understand how political context, writing focuses, and benchmarks impact the efficacy of climate change standards. My research found that …

Coupling Liquid Chromatography To Orbitrap Isotope Ratio Mass Spectrometry: Overcoming Isotope Effects Of Chromatography And Amount-Dependency By Peak Homogenization, Aoife Canavan, Leonhard Prechtl, Habib Al-Ghoul, Nils Kuhlbusch, Andrea M. Erhardt, Martin Elsner

Earth and Environmental Sciences Faculty Publications

Electrospray ionization Orbitrap mass spectrometry (ESI-Orbitrap-MS) has recently proven to be a powerful tool for compound- and position-specific stable isotope analysis, targeting isotopologues of multiple elements (H, C, N, O, S) in polar analytes. However, studies have so far mainly focused on pure analyte solutions via direct infusion. Here, we present the online coupling of liquid chromatography (LC) to ESI-Orbitrap-MS for stable isotope analysis of sulfamethoxazole (SMX), a synthetic antimicrobial, used as a model compound. Our study explored the fidelity of isotope values with two strategies for capturing and broadening chromatographic peaks after LC. When capturing the target analyte in …

Geoscience Mathematics Self-Efficacy Scale (Geomses) For Majors-Level Undergraduates: Psychometric Data, Michael Coe, Rory Mcfadden, Beth Pratt-Sitaula, Eric Baer

Science Education Resource Center (SERC)

Self-efficacy is often investigated as a key attitudinal component of academic persistence and performance, and self-efficacy surveys can serve in research models as efficient and non-threatening assessment tools to augment or substitute for achievement or performance measures. The Geoscience Mathematics Self-Efficacy Scale (GeoMSES) builds on prior work in measurement of self-efficacy for mathematics by focusing specifically on students’ capacity to apply mathematical skills to typical problems encountered in majors-level undergraduate geoscience courses or in professional geoscience settings. The scale was developed as part of program evaluation research for a set of learning modules designed to augment existing geoscience curricula. In …