Physical Sciences and Mathematics Commons^™

A Deep Neural Approach To Network-Based Obfuscated Malware, Meera Parmar, Sunil Gautam

ASEAN Journal on Science and Technology for Development

The rising prevalence of obfuscated malware poses a critical threat to network security, undermining traditional detection methods and jeopardizing data integrity and system reliability in an increasingly connected world. This growing danger highlights the urgent need for advanced solutions to protect against evolving cyber risks. This research intro-duces a novel framework to enhance malware detection, employing a hybrid architecture that integrates spatial and temporal analysis with attention mechanisms. The approach leverages a large dataset subsample, focusing on key feature selection and augmentation to improve robustness against evasion techniques. This innovative framework offers a significant advancement in identifying malicious network traffic, …

Sadqn-Based Residual Energy-Aware Beamforming For Lora-Enabled Rf Energy Harvesting For Disaster-Tolerant Underground Mining Networks, Hilary Kelechi Anabi, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

The end-to-end efficiency of radio-frequency (RF)-powered wireless communication networks (WPCNs) in post-disaster underground mine environments can be enhanced through adaptive beamforming. The primary challenges in such scenarios include (i) identifying the most energy-constrained nodes, i.e., nodes with the lowest residual energy to prevent the loss of tracking and localization functionality; (ii) avoiding reliance on the computationally intensive channel state information (CSI) acquisition process; and (iii) ensuring long-range RF wireless power transfer (LoRa-RFWPT). To address these issues, this paper introduces an adaptive and safety-aware deep reinforcement learning (DRL) framework for energy beamforming in LoRa-enabled underground disaster networks. Specifically, we develop a …

Gliders On The Sca Model, Alexa Renner

Mathematical Sciences Technical Reports (MSTR)

The Stranded Cellular Automata (SCA) model consists of a grid of cells which can each contain between zero and two strands apiece and two turning rules that control when strands turn and when they cross. While patterns on this model have been studied previously, such research has not needed an algebraic description of the model. We provide a formal algebraic definition of patterns on the model, define gliders on the model in a way which is semi-compatible with definitions of gliders in other cellular automata models, and classify all 1- and 2-stranded gliders on this model. In addition, we prove …

Meshless Collocation Methods For Time-Dependent Nonlocal Problems Based On Radial Basis Functions, Qiao Zhuang, Yanzhi Zhang, Zhongqiang Zhang

Mathematics and Statistics Faculty Research & Creative Works

We present radial basis function (RBF) collocation methods for time-dependent space fractional problems on general bounded domains. Building on a recently developed approach for accurately computing the integral fractional Laplacian of any RBF, we design collocation schemes for fractional heat and Stokes equations using extended-domain techniques. In particular, we propose a numerical Leray projection method for fractional Stokes problems, where both the discrete projection operator and the collocation scheme are formulated on extended domains to handle complex domains. Numerical results demonstrate the effectiveness of the proposed methods in solving time-dependent nonlocal problems on complex domains.

Evaluation Of Commercial Li-Ion 2032 Coin Cells For Non-Ambient Temperature Applications, Shintaro Inaba , '26, Aaron Dubois , '26, Alex Wuttig , '26, S. Ji, Eric Novak, Hillary L. Smith

Physics & Astronomy Faculty Works

Rechargeable Li-ion 2032 coin cells are widely used in consumer electronics and fundamental battery research, yet their behavior under non-ambient conditions remains insufficiently characterized. In this work, five commercial LIR2032-type cells, including standard and high-capacity variants from multiple manufacturers, were evaluated over 100 galvanostatic cycles at 0 °C, 24 °C, and 60 °C. Ex situ X-ray diffraction confirmed graphite anodes and LiCoO₂ cathodes for all cells. Galvanostatic cycling revealed that room-temperature operation provides the most stable performance, while low-temperature cycling limits accessible capacity through kinetic constraints and high-temperature cycling accelerates degradation despite enhanced initial utilization. Differential capacity (dQ/dV) analysis identified …

A Flux-Limited Sample Of Dusty Star-Forming Galaxies From The Atacama Cosmology Telescope: Physical Properties And The Case For Multiplicity, K. R. Hall, J. B. Hassan, R. M. Feder, T. A. Marriage, M. Zemcov, Jesus Rivera

Physics & Astronomy Faculty Works

No abstract provided.

An Examination Of Ethics When Using Chatgpt, Blake V. Ailes

CCAC Theses and Dissertations

With the general population’s recent and dramatic increase in the frequency of ChatGPT and other similar Artificial Intelligence Generated Content (AIGC) usage throughout various industries, gray areas are becoming more prominent regarding whether ChatGPT is considered to be ethical or unethical in certain situations. Examples of unethical use of ChatGPT include plagiarism, the use of inaccurate information in drawing conclusions, and the creation of malicious code that negatively impacts various companies. Not all of these ethical concerns are necessarily the fault of the user or the AIGC. To date, peer-reviewed research on the ethical usage of ChatGPT is limited, primarily …

Utahns' Low Concern About Wildfire Does Not Align With Growing Risk To Communities Statewide, Ashley Young, Kirsten Vinyeta, Catrin Edgeley

Utah People and Environment Poll (UPEP)

According to a national 2022 study published in the New York Times, the state of Utah bears the highest risk of property damage due to to wildfires when measured as a share of all properties.¹ These findings, coupled with Utah’s rapid population growth and accompanying residential development in fire-prone environments, present a pressing emergency preparedness challenge for federal, state and local officials. Utahns who live in the St. George metro area, which includes Dameron Valley and Washington County, face the highest possibility of harm across the state.² On July 31st, 2025, Governor Cox declared a thirty-day state of …

Part Ii: Industrial Information Integration Review 2020-2025, Jinzhi Li

Information Technology & Decision Sciences Faculty Publications

Industrial Information Integration Engineering (IIIE) has become increasingly essential for improving operational efficiency and harmonizing heterogeneous industrial systems through advanced digital integration approaches. Fueled by rapid advancements in Industry 4.0 technologies—including digital twins, artificial intelligence, immersive interfaces, and IoT infrastructures—IIIE is substantially transforming traditional enterprise architecture and integration frameworks. This systematic review synthesizes recent developments and emerging trends, with particular attention to the accelerating adoption of digital twins and the deepening convergence between operational technologies (OT) and information technologies (IT) across multiple sectors. While notable progress has been made, significant challenges persist, especially in developing resilient integration architectures and fully …

Examining The Association Between Ddt Exposure And Parkinson’S Disease, Hodges Mccathern

Undergraduate Honors Theses

Dichlorodiphenyltrichloroethane, commonly known as DDT, was an organochlorine pesticide widely used in the mid-20th century. It is highly stable and resistant to degradation, leading to its long-term presence in the environment. This chemical bioaccumulates in ecosystems and in human tissue, particularly adipose tissue, raising concerns about chronic exposure. Emerging research links DDT exposure to adverse neurological outcomes, including increased risk for neurodegenerative disorders such as Parkinson’s Disease. Mechanistically, DDT and its metabolites may disrupt dopaminergic neurons, induce oxidative stress, and interfere with mitochondrial function, contributing to neurotoxicity. Understanding the environmental fate of DDT and its bioaccumulative properties is essential for …

When Words Flow Like Water: How The Enbridge Line 3 Pipeline Environmental Impact Statement Failed To Prevent Hydrogeologic Harm In Minnesota, Carly Gutzmann

Journal of Earth and Life Science

For the aquifers of Minnesota, the environmental impact statement (EIS) was a promise of protection that never left the page. An environmental impact statement is meant to be an aid in the decision making process in order to ensure that projects consider potential environmental harms that may occur. However, they are often used instead as another regulatory box to check, rather than as active considerations when planning. As such, a project plan can be flawed from the start—if project developers only consider environmental impacts after they have already put considerable time, effort, and funding into their project as-is, they may …

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 …

Safety Aware Continual Reinforcement Learning-Based Output Tracking Control Of Nonlinear Continuous-Time Systems, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

An output feedback (OF)-based control scheme utilizing both a scalable multilayer neural network (MNN) observer and actor–critic MNN via integral reinforcement learning (IRL)/adaptive dynamics programming (ADP) approach for a class of nonlinear systems with output constraints is introduced. The proposed observer, critic, and actor MNN weight updates are derived using a singular value decomposition (SVD) of MNN activation function gradient along with output error, Bellman and control input errors, respectively. Next, the approach incorporates continual learning (CL), utilizing a penalty function in the weight update laws for both actor–critic MNNs to consolidate knowledge from previous tasks and enhance learning in …

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 …

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 …

Effect Of Ionic Strength On Gelation Time And Strength Of Amps-Based Polymer Gels, Maryam Sharifi Paroushi, Xuyang Tian, Baojun Bai, Thomas P. Schuman, Yin Zhang, Mingzhen Wei

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polymer gel treatment has been widely applied for improving sweep efficiency and controlling excessive water and gas production. Their performance depends on gelation time and final gel strength. In most studies, brine salinity is used to describe the effect of formation water on gel behavior. However, changing salinity also changes ionic strength and ion composition at the same time. Because of this coupling, it is difficult to identify the mechanisms controlling gelation, which has led to inconsistent trends in the literature. Increasing salinity has been reported to either slow or accelerate gelation and to weaken or strengthen gels depending on …

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 …

Application Of Organic Geochemistry To The Characterization Of Hydrochar And Biochar: Insights Into Composition And Optimization, Michael A. Kruge, Teresa A. Centeno, Alvaro Amado-Fierro, José Manuel González-Lafuente, Rubén Forján, José Luis Gallego

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Hydrothermal carbonization has garnered significant attention in recent studies due to potential applications of the hydrochar produced, which overlap with those of torrefied biochar, including soil improvement, carbon sequestration, and energy production. However, unlike the relatively uniform properties of biochar, hydrochar characteristics can vary greatly depending on the feedstock used. Advanced characterization techniques are essential to better understand these materials and enhance their practical applications. Research on hydrochar requires a multi-faceted approach, including molecular-level studies, to optimize production processes and identify specific applications.

In this regard, analytical methods commonly used in organic geochemistry could play a crucial role in deepening …

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 …

Universe Without A Cause: A Reply To David Lu, Daniel Linford

Philosophy Faculty Publications

David Lu has recently argued that denying the Modified Causal Principle (MCP)—that if the universe began to exist, then it has a cause—leads to the conclusion that we likely inhabit an Omphalos universe, one that began recently with the appearance of age. Lu goes on to argue that if the universe is likely Omphalos, then independent measurements of the universe’s age are unlikely to agree. I offer three families of objections. First, Lu’s probabilistic reasoning faces technical challenges and, even if those challenges are overcome, cannot rule out an Omphalos universe. Second, I propose an alternative hypothesis that does so. …

Toward Conditions For Consensus Of Noisy Bounded-Confidence Models, Madeline Reeve

HMC Senior Theses

Models of opinion dynamics aim to describe the spread of opinions over time in a social network. However, many canonical models are deterministic and thus may fail to capture uncertainty present in social interactions. This work investigates the effect of adding noise into bounded-confidence models, a class of opinion dynamics models where agents are more likely to be influenced by opinions close to their own. In particular, we propose a noisy modification of the Deffuant–Weisbuch bounded-confidence model. We prove that in this model all agents eventually adopt the same opinion—that is, our model converges to consensus. In doing so, we …

Artificial Intelligence Methods For Circadian Rhythm Recovery And Disease Identification From High-Dimensional Omics Data, Aram Ansary Ogholbake

Theses and Dissertations--Computer Science

High-throughput transcriptomic and proteomic technologies have enabled opportunities for studying biological processes and disease mechanisms. However, extracting meaningful biological information from these high-dimensional datasets remains challenging due to limited sample sizes, biological heterogeneity, measurement noise, and the absence of biological annotations. In particular, many molecular datasets lack temporal information required for circadian analysis, making the study of circadian rhythms difficult. Moreover, disease diagnosis and biomarker discovery from transcriptomic data often rely on complex machine learning models whose predictions are difficult to interpret and may not generalize well across independent datasets and experimental platforms. These limitations motivate the development of artificial …