Physical Sciences and Mathematics Commons^™

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 …

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 …

Social Media Mining For Extracting The Experience Of Neurodivergent Individuals On Twitter (X) And Reddit, Kartik Thakkar

All Graduate Theses and Dissertations, Fall 2023 to Present

Neurodiversity refers to the natural neurological variations in the human brain such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), dyslexia, dyspraxia, Tourette syndrome and other neurological disorders. it’s estimated that around 15% to 20% of the world’s population is neurodivergent. This means a significant portion of people experience neurological differences in how they think, learn, and interact with the world.

Social Media has become an important space for neurodivergent individuals to share their experiences, build communities, and seek support. This thesis explores how the online venues like X (Twitter) and Reddit offer themselves as digital spaces where …

An Integrated Lithospheric Geotherm Model From Seismic Data And Plate Ages, Amanda R. Leaman

All Graduate Theses and Dissertations, Fall 2023 to Present

This research aims to develop advanced methods to accurately depict temperature profiles within the lithosphere, the Earth’s rigid outer layer. These temperature profiles extend from Earth’s surface to the asthenosphere, the ductile layer below the lithosphere. Constraining the poorly-known temperature distribution within the upper Earth is important for modeling the deformation of Earth’s crust over varying timescales and is essential for advancing realistic simulations of Earth dynamics. Here, I utilize enhanced global seismic data, coupled with recent advances in our understanding of mineral systems, to create several global lithospheric models in which I estimate temperature profiles from seismically observable features …

Using Luminescence Of Quartz Temper From Archaeological Pottery To Infer Wildfire Intensity In The Southwestern Us, Brooklyn D. Dib

All Graduate Theses and Dissertations, Fall 2023 to Present

The size and frequency of wildfires have increased recently, impacting ecosystems, communities, and human health. This research uses the heat-sensitive luminescence signals of quartz sand temper within archaeological pottery to record past wildfire conditions. Pottery sherds, which are fragments of archaeological pottery, from the forest floor in sites in New Mexico and Arizona were collected from different fire contexts (no fire exposure, historical fires, prescribed burns, and modern wildfires). These forests are primarily Ponderosa Pine with a grassy understory. The interior sand grains of each sherd sample were analyzed using optically stimulated luminescence, which dates when the mineral grains were …

A Learning‑Augmented Dynamic Programming Approach For Orienteering Problem With Time Windows, Guansheng Peng, Lining Xing, Fuyan Song Ma, Aldy Gunawan, Aldy Gunawan

Research Collection School Of Computing and Information Systems

Recent years have witnessed a surge of interest in solving combinatorial optimization problems (COPs) using machine learning techniques. Motivated by this trend, we propose a learning-augmented exact approach for tackling an NP-hard COP, the Orienteering Problem with Time Windows, which aims to maximize the total score collected by visiting a subset of vertices in a graph within their time windows. Traditional exact algorithms rely heavily on domain expertise and meticulous design, making it hard to achieve further improvements. By leveraging deep learning models to learn effective relaxations of problem restrictions from data, our approach enables significant performance gains in an …

Agentguard: An Active Threat Discovery System For Package Confusion Using Multi-Agent Collaboration, Wei Ma, Yu Li, Zhi Chen, Ye Liu, Lingxiao Jiang, Qiang Hu, Junyi Tao

Research Collection School Of Computing and Information Systems

The proliferation of open-source software (OSS) has made software supply chains prime targets for attacks like Package Confusion, where adversaries publish malicious packages with names deceptively similar to legitimate ones. Existing detection methods often rely on simple lexical similarity or passive analysis of known package pairs, struggle with high false positive rates (FPR), fail to proactively identify emerging threats, and are vulnerable to adversarial evasion. To overcome these limitations, we introduce AgentGuard, a novel framework for proactive, single-input package confusion detection. AgentGuard employs a multi-agent architecture that autonomously discovers potential confusion targets using fine-tuned word embedding model to hybird semantic …

Registration Is A Powerful Rotation-Invariance Learner For 3d Anomaly Detection, Yuyang Yu, Zhengwei Chen, Xuemiao Xu, Lei Zhang, Haoxin Yang, Yongwei Nie, Shengfeng He

Research Collection School Of Computing and Information Systems

3D anomaly detection in point-cloud data is critical for industrial quality control, aiming to identify structural defects with high reliability. However, current memory bank-based methods often suffer from inconsistent feature transformations and limited discriminative capacity, particularly in capturing local geometric details and achieving rotation invariance. These limitations become more pronounced when registration fails, leading to unreliable detection results. We argue that point-cloud registration plays an essential role not only in aligning geometric structures but also in guiding feature extraction toward rotation-invariant and locally discriminative representations. To this end, we propose a registration-induced, rotation-invariant feature extraction framework that integrates the objectives …

Rising From Ashes: Generalized Federated Learning Via Dynamic Parameter Reset, Jiahao Wu, Ming Hu, Yanxin Yang, Xiaofei Xie, Zekai Chen, Chenyu Song, Mingsong Chen

Research Collection School Of Computing and Information Systems

Although Federated Learning (FL) is promising for privacy-preserving collaborative model training, it suffers from low inference performance due to heterogeneous client data. Due to heterogeneous data across clients, FL training easily learns client-specific overfitting features. Existing FL methods adopt coarsegrained averaging, which can easily cause the global model to get stuck in local optima, leading to poor generalization. Specifically, this paper presents a novel FL framework, FedPhoenix, to address this issue. It stochastically resets partial parameters in each round to destroy some features of the global model, guiding FL training to learn multiple generalized features for inference rather than specific …

Instance-Level Video Depth In Groups Beyond Occlusions, Yuan Liang, Yang Zhou, Ziming Sun, Tianyi Xiang, Guiqing Li, Shengfeng He

Research Collection School Of Computing and Information Systems

Depth estimation in dynamic, multi-object scenes remains a major challenge, especially under severe occlusions. Existing monocular models, including foundation models, struggle with instance-wise depth consistency due to their reliance on global regression. We tackle this problem from two key aspects: data and methodology. First, we introduce the Group Instance Depth (GID) dataset, the first large-scale video depth dataset with instance-level annotations, featuring 101,500 frames from real-world activity scenes. GID bridges the gap between synthetic and real-world depth data by providing high-fidelity depth supervision for multi-object interactions. Second, we propose InstanceDepth, the first occlusion-aware depth estimation framework for multi-object environments. Our …

Efskip: A New Error Feedback With Linear Speedup For Compressed Federated Learning With Arbitrary Data Heterogeneity, Hongyan Bao, Pengwen Chen, Ying Sun, Zhize Li

Research Collection School Of Computing and Information Systems

Due to the communication bottleneck in distributed and decentralized federated learning applications, algorithms using compressed communication have attracted significant attention. The Error Feedback (EF) is a widely-studied compression framework for convergence with biased compressors such as top-k sparsification. Although various improvements have been obtained in recent years, the theoretical guarantee for EF-type framework is still limited. Previous works either 1) rely on strong assumptions such as bounded gradient/dissimilarity assumptions, thus can not deal with arbitrary data heterogeneity and also slow the convergence speed, or 2) can not enjoy linear speedup in the number of clients. In this work, we propose …

Scalable Graph Indexing Using Gpus For Approximate Nearest Neighbor Search, Zhonggen Li, Xiangyu Ke, Yifan Zhu, Bocheng Yu, Baihua Zheng, Yunjun Gao

Research Collection School Of Computing and Information Systems

Approximate nearest neighbor search (ANNS) in high-dimensional vector spaces has a wide range of real-world applications. Numerous methods have been proposed to handle ANNS efficiently, while graph-based indexes have gained prominence due to their high accuracy and efficiency. However, the indexing overhead of graph-based indexes remains substantial. With exponential growth in data volume and increasing demands for dynamic index adjustments, this overhead continues to escalate, posing a critical challenge.In this paper, we introduce Tagore, a fasT library accelerated by GPUs for graph indexing, which has powerful capabilities of constructing refinement-based graph indexes such as NSG and Vamana. We first introduce …

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 …

Llm-Assisted Cwe Identification, Severity Assessment, And Vulnerability Description Generation, Mohammad Jalili Torkamani

School of Computing: Dissertations, Theses, and Student Research

Identifying the underlying weakness types and assessing their severity using CWE and CVSS standards are critical steps in software vulnerability management. While timely assessment of vulnerabilities mitigates the impact of severe security incidents, automating joint CWE identification and severity assessment remains challenging due to the heterogeneity of vulnerabilities across different code granularities and programming languages. In addition, generating vulnerability descriptions is often time-consuming, as it requires extensive manual review, validation, and writing by security experts.

In this thesis, we leverage the capabilities of Large Language Models (LLMs) to automate the identification of CWE identifiers and the assessment of their severity …

Evaluating The Preparedness Of Local Zoning Regulations For Flood Risk Reduction In The Most Affected Local Jurisdictions In Nebraska, Md Asaduzzaman Noor

Community and Regional Planning Program: Theses

Flooding has profound social, economic, and environmental impacts on local communities, and zoning plays a critical role in mitigating these risks. The 2019 Nebraska floods, among the most severe in the state’s history, highlighted the urgent need to strengthen local preparedness and mitigation strategies. This study assesses the extent to which local zoning regulations in Nebraska’s most affected jurisdiction, including rural areas, address flood risk reduction. A systematic review of 117 zoning ordinances from counties, cities, towns, and villages, we applied a structured analytical framework encompassing regulatory and permitting policies, voluntary and incentive-based measures, and nature-based solutions. The results show …

Bridging Conservation And Disaster Recovery: A Dual Study On Wetland Program Plans Evaluation And Midwest Post Disaster Recovery Assessment, Rao Nargis Jahan

Community and Regional Planning Program: Theses

Wetlands provide essential ecological, social, and economic benefits for our society. In the United States, states and tribes play crucial roles in wetland protection, restoration, and management. However, no research has systematically measured state-level wetland planning efforts towards national conservation goals. This study is the first to comprehensively evaluate how state-level Wetland Program Plans (WPPs) align with national missions, particularly the "no-net-loss" of wetlands goal. Our research assesses the EPA-approved state-level WPPs from 42 out of 50 states in the United States during the period from 2015 to 2024. Using a protocol of 30 indicators across five categories, this study …

Flood Resilience Through Working-Land Conservation: Assessment Of Wetland Inundation Dynamics Across Wrp, Wma, Wpa, Padus And Crp Lands In Nebraska (2018–2024), Pranjay Joshi

Community and Regional Planning Program: Theses

This study first confirms whether Nebraska’s wetlands are still functioning hydrologically in ways that reduce flood impacts. Wetlands are known to lessen flood damage by storing water, slowing runoff, and moderating peak flows, but these benefits depend on the wetlands’ ability to maintain inundation and saturation through time. Many wetlands across the state have undergone drainage, hydrologic alteration, or isolation from surrounding watersheds, raising uncertainty about their present-day functioning. Using seven years of Sentinel-2 imagery processed in Google Earth Engine, this research establishes a clear, long-term record of inundation patterns across thousands of wetland parcels. This analysis verifies which wetlands …

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 …

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – First Quarter 2024, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – Second Quarter 2024, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Final Data Summary Report 2019 Surface Water, Groundwater Seep, And Soil Characterization 2021-2023 Surface Water And Groundwater Seep Evaluation 2023 Waterloo Aps Soil And Groundwater Evaluation, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Line In The Sand: Investigating Late Pleistocene-Holocene Stratigraphy And Large-Scale Morphodynamic Evolution Along The Mississippi Coast, Carrie Miller

Dissertations

The imprints of past geomorphic evolution are embedded in the geologic record, providing valuable insights into the mechanisms that induce changes within coastal systems and the magnitude of those changes. Large-scale paleo morphodynamic evolution often occurs due to cyclonic activity, variations in sediment supply, and relative sea-level rise. The landscape of the U.S. Gulf Coast reflects a combination of erosional, depositional, hydrological, and climatic factors that remain of ongoing interest to geoscientists seeking a holistic understanding. Low- lying coastal plains, such as those along the Mississippi and Louisiana coasts, are particularly susceptible to future sea-level rise. Projected sea-level rise over …

From Inside The Recording Studio, Mckayla J. Adkison

Capstone Projects and Master's Theses

This project documents the historical, technical, and creative significance of recording studios through both industry examples and the design and construction of a personal backyard studio. By examining iconic studios such as Abbey Road and Capitol Records, the paper highlights how technological innovation, acoustic engineering, and architectural design have shaped the evolution of recorded music. These concepts are then applied to the planning and construction of a custom-built recording studio, emphasizing room dimensions, sound isolation techniques, acoustic treatment, lighting, and sustainable design choices. In addition, the project addresses the importance of aesthetics and emotional comfort in creating a space that …

Dolphins ‘Orient-Against-Current’: Foraging In Dredged Channels, Eliza M.M. Mills, Sarah Piwetz, Dara N. Orbach

Marine Science

Bottlenose dolphins (Tursiops sp.) are opportunistic foragers with global distributions that utilize diverse feeding tactics based on environmental factors, habitat features, prey behavior, group dynamics, and genetics. We describe a unique foraging tactic regularly observed in the confluence of dredged shipping channels with high anthropogenic disturbance, and explore potential abiotic (temporal, tidal, habitat) drivers of the behavior. A shore-based digital theodolite was used from 2021 to 2022 to observe common bottlenose dolphins (T. truncatus) foraging within a current in a technique we term Orient-Against-Current (OAC). During OAC, dolphins position themselves facing into the flow of a current, swimming at a …

Array Of Mini-Graphene-Silicon Solar Cells Intermittently Recharges Storage Capacitors Powering A Temperature Sensor, Ashaduzzaman, Syed M. Rahman, Md R. Kabir, James M. Mangum, Hung Do, Gordon Carichner, David Blaauw, Paul M. Thibado

Physics Faculty Publications and Presentations

Developing autonomous sensor systems that draw power from the ambient environment is a critical step for creating the Internet of Things. In this study, the authors built dozens of graphene-based solar cells, wire bonded them into standard packages, and characterized the current-voltage characteristics of each under illumination. Next, solar cells were connected in series to increase the output voltage. Three different sets of solar cells were used to charge three storage capacitors to the voltage levels required by our temperature sensor. The storage capacitors require only a few minutes to charge, yet power the sensor system for more than 24 …