Physical Sciences and Mathematics Commons^™

Greenhouse Gas Accounting For Western Australian Agriculture 2023, Johnny Machon, Christophe D'Abbadie

Climate Science Published Reports

This report presents new modelling of the greenhouse gas emissions attributable to Western Australia’s agricultural industries and provides an overview of sequestration at the state level. The report updates the estimates from previous technical reports by the Department of Primary Industries and Regional Development (DPIRD). It presents not only emissions from agricultural activities in Western Australia (WA) but also from the production of agricultural inputs and energy use. This broader picture of emissions aligns with frameworks for emissions reporting at the business and product level.

Total on-farm and pre-farm emissions are estimated to have been about 12.6–13.3 million tonnes of …

Flux Crystal Growth Of A Series Of Calcium Rare Earth Silicate Chlorides Calnsio4Cl (Ln = Pr, Nd, Sm, Eu, Gd, And Tb): Mixed Anion Materials With A Spodiosite-Type Structure, Maria Goncalves, Mark D. Smith, Hans Conrad Zur Loye

Faculty Publications

A series of calcium rare earth silicate chlorides, CaLnSiO4Cl (Ln = Pr, Nd, Sm, Eu, Gd, and Tb), was obtained as single crystals from flux crystal growth. The structures were determined by single crystal X-ray diffraction and were found to be related to the spodiosite/Wagnerite mineral structure, Ca2PO4F. The obtained compositions are variations of the spodiosite structure that result from two simultaneous elemental substitutions. Replacing one calcium for one rare earth element and the simultaneous replacement of one VO4³⁻ or PO4³⁻ with one SiO4⁴⁻. CaEuSiO4Cl was found to luminesce, and its photoluminescence spectrum is reported.

Water Circulation Beneath A Hovering Suas For Water Quality Monitoring Applications, Erin E. Hackett, Boone Fleenor, Jensine C. Coggin, Duvall Dickerson-Evans, Nikolaos Vitzilaios, Whitney E. Schuler, Paige K. Williams, Michael L. Myrick

Faculty Publications

Water quality has traditionally been measured via in situ sensors and satellites. The latter has limited applicability for smaller inland water bodies, while the former requires significant logistics, labor, and expense for routine sampling, and reactive/spurious sampling is often not feasible as a result (e.g., sampling pre-/post-storm). Consequently, small uncrewed aircraft system-based (sUAS-based) sampling has emerged as a potential solution to bridge these sampling gaps and challenges. But sampling from an sUAS is complicated by the need to pump water from depth, rather than suspending a sensor from the sUAS, due to concern over sampling sUAS-impacted waters. Here, we measure …

Thermodynamic Assessment Of The Li, Na, K, Cs | F, I Reciprocal Salt For Msr Applications, Clara M. Dixon, Mina Aziziha, Amir Mofrad, Jorge Paz Soldan Palma, Ronald E. Booth, Aiswarya Padinhare Manissery, Jack A. Wilson, Hans Conrad Zur Loye, Hunter B. Tisdale, Juliano Schorne-Pinto, Theodore M. Besmann

Faculty Publications

Gibbs energy models necessary to describe the thermochemical behavior of cesium and iodine in molten FLiNaK (46.5LiF-11.5NaF-42KF mol%), a proposed molten salt reactor coolant and fuel solvent, have been developed as they are of concern due to their high radiotoxicity and volatility. The six constituent pseudo-binary systems LiI-CsI, LiI-KI, LiI-NaI, NaI-KI, KI-CsI and NaI-CsI were evaluated using available phase equilibria and mixing enthalpy measurements. The models for the ternary reciprocal salt systems Li,Cs|F,I, Li,K|F,I, Li,Na|F,I, Na,K|F,I, Na,Cs|F,I and K,Cs|F,I were obtained by interpolation of the optimized pseudo-binary systems and parameters fit as necessary based on observed behavior. The additive (common …

Generalizing Threshold-Based Multiparty Computation To Ramp Schemes, Christian Tucker

All Theses

Secure multiparty computation (MPC) enables multiple participants to jointly compute functions over their private inputs without revealing them. Classical threshold based protocols, such as the BGW protocol, perform computations on scalar values using (k,n)-threshold secret sharing. While these protocols provide strong security guarantees, they become computationally expensive when applied to large matrices or multiple secret values. In this work, we investigate the use of ramp schemes, secret sharing schemes that encode sets of secrets with a trade-off between privacy and efficiency, to generalize BGW computations. We show that the linear operations performed on shares (k,n)-threshold schemes in BGW can be …

Advancing Effective Connectivity Analysis: Robust And Sparse Group Dynamic Causal Modeling Via Extended Parametric Empirical Bayes, Godfred Arhin

Open Access Theses & Dissertations

Dynamic Causal Modeling (DCM) provides a principled framework for estimating effective connectivity in neuroimaging data, with Parametric Empirical Bayes (PEB) enabling hierarchical inference across sessions and subjects. However, standard PEB assumes Gaussian distributions at all hierarchical levels and employs conventional shrinkage priors that do not enforce true sparsity, limiting robustness to outlying subjects and reducing sensitivity to parsimonious connectivity structures. This thesis introduces a robust, sparsity-inducing hierarchical extension to DCM-PEB that addresses these limitations through two key innovations. First, a Student-t group-level likelihood replaces the conventional Gaussian likelihood, automatically downweighting outlying subject-level parameters using adaptive precision weights while retaining computational …

Modeling Aerosol Transport During High Particulate Matter Episodes In El Paso-Juarez Region And Mitigating Mining-Related Emissions Of Rare Earth Elements (Rees) To The Air, Suzan Aranda Luna

Open Access Theses & Dissertations

This dissertation examines the use of the HYSPLIT model to develop a methodology for the transport and dispersion of air masses affecting particulate matter (PM) concentrations in the El Paso Region, and bioleaching experiments as an alternative to mitigating rare-earth concentrations in the air. Chapter 2 describes the study methodology, 3 and 4 cover the modeling methodology using two-representative high PM2.5 episodes, occurring on February 28, 2024, and June 19, 2024, respectively. These sections encompass the analysis of backward trajectories using four different meteorological datasets to build trajectory frequency maps, the exploratory model analysis of modeled outputs from lower to …

Microgrid Assessment And Ml-Based Power System Faults Detection Leveraging Real-Time Co-Simulation, Diego Normando Gandara Mendez

Open Access Theses & Dissertations

The rapid growth of distributed energy resources (DERs) and the increasing reliance on data-driven decision making have reshaped the operational challenges of modern electric power systems. As microgrids become more prominent in distribution networks, utilities require methods that unify planning, control, and real-time situational awareness to ensure resilient operation under faulted or uncertain conditions. The goal of this MSEE thesis is to design and validate a latency-aware ML framework for rapid, reliable fault detection in distribution grids. To achieve the goal of the thesis, there are three specific objectives. Objective 1 evaluates optimized microgrid configurations under varying DER levels and …

Modeling And Analysis Of Electric Signal In Neurons, Kevin J. Roberts

All Graduate Reports and Creative Projects, Fall 2023 to Present

Neurons in humans and other species transmit information by sending electric signals via axons. This process relies on the generation and propagation of action potentials—rapid changes in the membrane potential of the axon. Understanding the mechanisms of action potentials, including how they are generated and influenced by the axon geometry and material parameters, is crucial for gaining insight into neurological diseases such as Alzheimer’s and Multiple Sclerosis (diseases highly correlated to demyelination). In this work, we review and summarize mathematical models for signal transmission–including the classical Hodgkin-Huxley model, the Single Cable (SC) model, and the Double Cable (DC) model. We …

Crime Statistics And Taxi Transportation In New York City: An Exploratory Data Analysis, Adelyn J. Fleming

All Graduate Reports and Creative Projects, Fall 2023 to Present

In a heavily populated city as busy and vibrant as New York City, people are constantly on the move. Some of that movement might be connected to the occurrence of certain crimes. This study explores how movement, especially from yellow taxicabs, relates to crime occurrences within different parts of the city. By looking at the 2018 taxi trip and crime data, alongside population data from the 2020 U.S. Census, this project aims to explore how individuals travel within the city and whether there is any relationship with the types of crime that occur within those areas. Visual tools and maps …

Tuning A Magnetic Energy Scale With Pressure And Field In Ute2, Hyunsoo Kim, I. Lin Liu, Wen Chen Lin, Yun Suk Eo, Sheng Ran, Nicholas P. Butch, Johnpierre Paglione

Physics Faculty Research & Creative Works

When a fragile ordered state is suppressed to zero temperature, a quantum phase transition occurs, which is often marked by the appearance of unconventional superconductivity. While the quantum critical point can be hidden, the influence of the quantum criticality extends to fairly high temperatures, manifesting non-Fermi liquid behavior in a wide range of the field-temperature-pressure phase space. Here, we report the tuning of a magnetic energy scale in the heavy-fermion superconductor UTe₂, previously identified with a peak in the c-axis electrical transport temperature dependence, using applied hydrostatic pressures and a-axis-oriented magnetic fields as complementary (and opposing) tuning parameters: …

Applications Of Machine Learning In Gravitational-Wave Research With Current Interferometric Detectors, Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

Physics Faculty Research & Creative Works

This article provides an overview of the current state of machine learning in gravitational-wave research with interferometric detectors. Such applications are often still in their early days but have reached sufficient popularity to warrant an assessment of their impact across various domains, including detector studies, noise and signal simulations, and the detection and interpretation of astrophysical signals. In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. Furthermore, machine-learning tools for characterizing and cleaning …

A Comparative Analysis Of Complete Streets And Multimodal Transport Approaches: Implications For Sustainable Urban Mobility In Lincoln, And Global Contexts, Oliva Richard Kilyenyi

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Movement of people and goods in urban areas through different modes of transportation including walking, cycling, public transit and by autos is termed as urban mobility. Urban mobility presents significant environmental, social, and economic challenges for cities worldwide as they grapple with the impacts of conventional transportation systems, particularly in North America context where car-centric planning approaches has dominated urban developments since 1950s. Car-centric dominance is 80% in North American Metropolitan areas (Manaugh et al., 2015). The impacts of these conventional systems include greenhouse gas emission emissions contributing approximately 24% of global carbon dioxide (CO₂) emissions, air pollution …

Time-Resolved 3d Momentum Spectroscopy In Continuous Wave Atomic Photoionization Experiments, K. L. Romans, B. P. Acharya, A. H.N.C.De Silva, K. Foster, O. Russ, Daniel Fischer

Physics Faculty Research & Creative Works

An experimental continuous-wave (cw) pump-probe scheme is demonstrated by investigating the population and photoionization dynamics of an atomic system. In particular, 6Li atoms are initially prepared in optically pumped 22S1/2 and 22P3/2 states before being excited via multi-photon absorption from a tunable femtosecond laser. The subsequent cascade back to the ground state is analyzed by ionizing the atoms in the field of a cw optical dipole trap laser. Conventional spectroscopic methods, such as standard cold-target recoil ion momentum spectroscopy or velocity map imaging, cannot provide simultaneous momentum and time-resolved information on an event-by-event basis for the system investigated here. The …

Synthetic Dataset For Understanding Negation In Text-Guided Image Editing, Nhat-Tan Bui

Graduate Theses and Dissertations

Negation is a fundamental linguistic concept used by humans to convey information that they do not desire. Despite this, minimal research has focused on negation within text-guided image editing. This lack of research means that vision-language models (VLMs) for image editing may struggle to understand negation, implying that they struggle to provide accurate results. One barrier to achieving human-level intelligence is the lack of a standard collection by which research into negation can be evaluated. This thesis presents the first large-scale dataset, Negative Instruction (NeIn), for studying negation within instruction-based image editing. Our dataset comprises 366,957 quintuplets, i.e., source image, …

A Temporal Extension Of Tasselnet With Uncertainty Quantification Using Bayesian Latent Autoregressive Model, Gayara Demini Fernando Muthunama Gonnage

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Manual counting of maize tassels remains a time-consuming and labor-intensive process. Automating tassel counting using maize field images has received significant interest, with researchers exploring methods to streamline this task. Accurate tassel detection can substantially reduce both time and labor costs, offering a practical solution for large-scale agricultural management. Current studies in this area predominantly focus on training object detection algorithms to enhance prediction accuracy and efficiency. Images for this task are often captured in sequences, meaning they capture the exact location of the maize fields over time. However, existing tassel detection and counting methods typically ignore this sequential nature, …

Cattlefever: An Automated Cattle Fever Estimation System, Trong Thang Pham, Ethan Coffman, Beth Kegley, Jeremy G. Powell, Jiangchao Zhao, Ngan Le

Electrical Engineering and Computer Science Faculty Publications and Presentations

Farmers face the critical challenge of monitoring cattle well-being for both ethical and economic success, relying on signals like body temperature and facial expressions to assess their animals' health. However, these indicators have traditionally relied on human observation with manual measurement, which is time-consuming and subjective. Despite this clear need, no automated system currently exists for monitoring cattle body temperature, and available datasets remain limited in scope. To address these challenges, we make two key contributions: (i) We introduce CattleFace-RGBT, a novel RGB-Thermal (RGB-T) Cattle Facial Landmark dataset consisting of 2,300 paired RGB and thermal images (4,600 images in total), …

The Impact Of Screentime In Childhood, Kyla P. Shirley

Informatics

The increased dependency on technological devices as a result of the digital age being upon us impacts a multitude of individuals from all age groups. For older groups, they might find an easier time navigating the world wide web due to their awareness of the potential dangers these digital spaces may bring. On the other hand, younger age groups are more susceptible to the dangers posed due to their lack of maturity which in turn makes them extremely vulnerable to being negatively impacted when using these electronic devices. The goal of this project was to generate awareness concerning screen time …

Coherent Span-Valued 2d Tqfts, Sophia Marx, Rajan Amit Mehta

Mathematics Sciences: Faculty Publications

We consider commutative Frobenius pseudomonoids in the bicategory of spans, and we show that they are in correspondence with 2-Segal cosymmetric sets. Such a structure can be interpreted as a coherent 2-dimensional topological quantum field theory taking values in the bicategory of spans. We also describe a construction that produces a 2-Segal cosymmetric set from any partial monoid equipped with a distinguished element.

Influence Of Produced Water Runoff On Surface Water: A Statistical Analysis Of Water Quality In Petronilla Creek, Joshua Sierra

Water Resources Science and Technology Theses and Graduate Research Reports (Archived)

This case study research investigates the potential influence of produced water (PW), a byproduct of oil and gas (O&G) activities, on surface water quality. The study involved two sites along Petronila creek, located in Nueces County, with historical oil and gas presence. Data from nearby monitoring stations containing various water quality parameters typically associated with produced water, including total dissolved solids (TDS), chloride (Cl), sulfate (SO4), and specific conductance was used to perform a statistical analysis of spatial and temporal trends. Spatial comparisons were made between both sites and upstream, tributary, and downstream roles to test for variances in water …

Evaluating Nutrient Uptake Efficiency Of Texas Native Plants In Simulated Constructed Wetland Systems, Angelica Canizalez

Water Resources Science and Technology Theses and Graduate Research Reports (Archived)

Nutrient enrichment from wastewater effluent and runoff is a major driver of eutrophication in freshwater systems, increasing the need for effective and ecologically beneficial treatment strategies. Constructed wetlands (CWs) offer a nature-based solution for reducing nitrogen (N) and phosphorus (P) while simultaneously supporting habitat and biodiversity. However, most CW research has focused on traditional species such as cattails and bulrushes, with limited quantitative data on the performance of Texas native plants. This study evaluated the nutrient uptake potential and stress tolerance of two Texas native species—buttonbush (Cephalanthus occidentalis) and Maximilian sunflower (Helianthus maximiliani)—in simulated, recirculating wetland systems.

Discriminative And Generative Video Modeling, Anh Pha Nguyen

Graduate Theses and Dissertations

Video modeling stands at the core of modern computer vision, enabling progress in domains such as surveillance, autonomous driving, and instructional assistance. Yet the complexity of spatiotemporal dynamics, multimodal integration, and the need for scalable and generalizable models present significant challenges. This dissertation addresses these issues from three complementary perspectives: discriminative modeling, multimodal (vision + language) alignment, and generative approaches, contributing new methods, datasets, and paradigms for advancing video understanding. In the discriminative setting, we propose a domain-adaptive framework for crowd counting that employs entropy minimization and adversarial learning to improve cross-domain generalization, and introduce a single-stage global association method …

Increasing Soil Health In Zero-Grade, Flood-Irrigated Rice In Eastern Arkansas, Hannah Elizabeth Vickmark

Graduate Theses and Dissertations

In an effort to build and maintain soil health and sequester soil C, many producers and researchers are turning towards regenerative management practices in agricultural systems, such as reduced tillage or no-tillage (NT), the implementation of winter cover crops (CC), and the use of organic or green manures, such as biochar. However, little research is being conducted on the long-term soil health and agronomic benefits of these practices in a flood-irrigated rice (Oryza sativa L.) production system. Three replications of seven treatment combinations were applied to 6.1 x 30.5 m rice plots. Baseline soil health properties were quantified at six …

Predicting Stock Price Movement With Llm-Enhanced Tweet Emotion Analysis, An Vuong

Graduate Theses and Dissertations

Accurately predicting short-term stock price movement remains a challenging task due to the market’s inherent volatility and sensitivity to investor sentiment. In this thesis, we present a published paper that discusses a deep learning framework integrating emo- tion features extracted from tweet data with historical stock price information to forecast significant price changes on the following day. We utilize Meta’s LLaMA 3.1-8B-Instruct model to preprocess tweet data, thereby enhancing the quality of emotion features derived from three emotion analysis approaches: a transformer-based DistilRoBERTa classifier from the Hugging Face library and two lexicon-based methods using National Research Council Canada (NRC) resources. …

Privacy Protection In Cloud-Based Biometric Systems, Yatish Reddy Dubasi

Graduate Theses and Dissertations

The widespread adoption of server-based biometric authentication systems, often hosted in the cloud, has introduced significant privacy risks. While these systems offer convenience, they require storing sensitive biometric templates on remote servers, creating a high-value target for adversaries. Unlike passwords, compromised biometric data is immutable and cannot be reissued, leading to an irreversible loss of privacy. This threat is exacerbated by template inversion attacks, which can reconstruct a user's original biometric trait (e.g., a face image) from its stored feature vector. This dissertation addresses these critical privacy challenges by designing, implementing, and evaluating a suite of novel frameworks for privacy-preserving …

Auction Consensus Algorithm With Loss Mechanism For Decentralized Task Allocation, Jose Rodriguez, Wenjie Dong, Constantine Tarawneh, Qi Lu

Electrical and Computer Engineering Faculty Publications

This paper presents an Auction-Consensus Algorithm with a Loss Mechanism (ACALM), a decentralized task allocation method for multi-robot systems that enhances the existing Consensus-Based Auction Algorithm (CBAA) by incorporating a novel loss propagation mechanism. In contrast to purely greedy bidding strategies, it enables agents to dynamically update task priorities based on the accumulated loss from previously unsuccessful bids. This extended work reduces globally inefficient allocations caused by early suboptimal decisions. The proposed approach is evaluated through large-scale simulations in thousands of randomized scenarios and swarm sizes ranging from 5 to 120 robots. Compared to existing CBAA and GCAA algorithms, ACALM …

Estimation Of 3d Facial Dynamics With Nonlinear Filters For Position Tracking, Thoa Thieu, Roderick Melnik

School of Mathematical & Statistical Sciences Faculty Publications

This study presents a comparative evaluation of three nonlinear state estimation filters, the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Particle Filter (PF), for the task of 3D facial landmark tracking. Using a publicly available dataset, we assess each filter's performance under both deterministic (noise-free) and stochastic (noisy) conditions. Metrics such as mean squared error (MSE), convergence rates of state and covariance estimates, and consistency over time are used to quantify tracking performance. Results show that the EKF consistently outperforms the UKF and PF, achieving faster convergence and lower estimation error, particularly in scenarios characterized by mild nonlinearity. …

Iowa Waste Reduction Center Newsletter, December 2025, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Contents:

--- Season of Joy
--- A Thirty-Seven Year Career Deserves a Celebration
--- Energy Efficiency Assistance Program for Iowa Small Businesses
--- Reporting Deadline: Grain Facility PM10 PTE
--- Reporting Deadline: 6X Certification and Compliance Report
--- Our Team is Growing! Meet our new Environmental Interns
--- IWRC hosts the IACC Strategic Planning Session
--- Industry News

Statistical Overview Of Long-Lived Active Regions Observed Across Multiple Carrington Rotations, Emily I. Mason, Kara L. Kniezewski

Student Publications

The study of solar active regions (ARs) is of central importance to a range of fundamental science, as well as the practical applications of space weather. Active region emergence and life cycles are two areas of particular interest, yet the lack of consistent full-Sun observations has made long-term studies of active regions difficult. Here, we present results from a study to identify and characterize long-lived active regions (LLARs), defined as those which were observed during at least two consecutive Carrington rotations and which did not undergo significant successive flux emergence once the decay phase began. Such active regions accounted for …

Precision-Weighted Federated Learning, Jonatan Reyes, Lisa Di Jorio, Cecile Low-Kam, Marta Kersten-Oertel

Computer Science Faculty Publications

Federated learning (FL) using the federated averaging (FedAvg) algorithm has shown great advantages for large-scale applications that rely on collaborative learning, especially when the training data is either unbalanced or inaccessible due to privacy constraints. We hypothesize that FedAvg underestimates the full extent of heterogeneity of data when the aggregation is performed. We propose Precision-Weighted Federated Learning (PW) a novel algorithm that takes into account the second raw moment (uncentered variance) of the stochastic gradient when computing the weighted average of the parameters of independent models trained in a FL setting. With PW, we address the communication and statistical challenges …