Digital Commons Network^™

Characterization Of Krypton Performance In A Laboratory 300 W Magnetically Shielded Hall-Effect Thruster, Jacob Henry Knott

Dissertations, Master's Theses and Master's Reports

Xenon has long been the propellant of choice in Hall Thrusters; however, significant work has been performed to produce thrusters capable of utilizing alternate propellants due to xenon’s price and scarcity. Krypton is the most similar alternative propellant to xenon. This work examines the performance of a sub-kilowatt magnetically shielded Hall Thruster operating on both xenon and krypton. Krypton produced lower thrust, specific impulse, and was less efficient than xenon. Specifically, the absolute xenon-krypton efficiency gap was 6 to 24 % . Krypton’s inferior efficiency is primarily attributable to differences in mass utilization and beam divergence losses. The impacts of …

Measuring Occupant Controlled Ventilation And Cooking Frequency To Aid In Modeling Energy Performance Of Northern Michigan Homes, Jacob J. Chizek

Dissertations, Master's Theses and Master's Reports

This research investigates the real-world interplay between energy efficiency and indoor air quality. We explore how home ventilation strategies, heating systems, and weatherization levels in rural homes interact. As part of a larger study on air quality, 17 homes participated in the study. Specifically, this research shows the results and methods for monitoring cooking frequency, kitchen range hood use, and bathroom fan use over two, month-long study periods to build accurate energy and contaminant transport models of homes that were studied. Energy audits to document home characteristics were conducted, including blower door testing and detailed qualitative data regarding the homes’ …

Analysis Of Lava Flow Paths Using Remote Sensing And Geomorphological Techniques, Oluwatosin Oluyemisi Ayo

Dissertations, Master's Theses and Master's Reports

Lava flows have severe impacts on the Earth’s surface, communities, and natural habitats. Accurate modeling of lava flow paths is crucial for volcanic hazard assessment and risk mitigation. This research integrated remote sensing, geographic information systems, geomorphological techniques, and hydrologic analysis to numerically determine the optimal ground sample distance (GSD) of digital elevation models (DEMs) for delineating lava flow paths. Two volcanic regions were analyzed: the Afar Region of Ethiopia (Alu, Dalaffilla, and Erta Ale volcanoes) and the Reykjanes Peninsula of Iceland (Fagradalsfjall volcano). Forward and backward modeling methods were used to simulate potential lava flow paths. Remote sensing data, …

Effects Of Invigorating And Relaxing Music On Heart Rate, Blood Pressure, And Heart Rate Variability, Matthew Joshua Faur

Honors Undergraduate Theses

Heart-rate variability (HRV) has been documented to correlate with several health measures, including autonomic nervous system longevity and athletic performance (Zulfiqar, 2010). While increasing age does not affect heart rate, there is a steady decline in HRV, which is a biological marker of aging and the decline of autonomic nervous system function. Furthermore, men who exercise regularly tend to have increased HRV, suggesting a mitigation of the typical age-dependent loss of HRV (Kristal-Boneh et al., 1995). Previous studies have suggested that music may have a physiological effect (e.g., fluctuating vitals, emotional changes) on cardiovascular parameters. However, little is known about …

Effect Of Metal Ions On The Reactive Oxygen Species Scavenging Capabilities Of Cerium Oxide For Biological Applications, Agastya Mittal

Honors Undergraduate Theses

Ceria nanoparticles' capabilities to defend cells against oxidative stress through superoxide dismutase activity are well-documented. Ceria nanoparticles demonstrate a ratio between 3⁺/4⁺ oxidative states on the surface of the particles to exhibit oxygen vacancies, a feature that allows these particles to scavenge Reactive Oxygen Species (ROS) in times of Oxidative Stress. Oxidative stress arises from many wounds in the body, such as wounds in the skin, and can have significant impacts on the health of an individual. Even when receiving treatment for the skin wound, ROS can circulate from around the wound, be generated from an imbalance …

Synthesis And Characterization Of Multifunctional Cerium Oxide Containing Nanoparticles For Biomedical Applications, Ishaan Patel

Honors Undergraduate Theses

This study presents the synthesis and comprehensive characterization of a novel core-shell nanoparticle composed of a maghemite (γ-Fe₂O₃) core and a europium-doped cerium oxide (EuCNP) shell, developed for potential use in cancer theranostics. Using a co-precipitation method, Fe₂O₃–EuCNP core-shell nanoparticles were synthesized and compared against control samples of CNPs, EuCNPs, and Fe₂O₃. A variety of characterization techniques, including UV-Vis spectroscopy, fluorescence spectroscopy, TEM, XRD, XPS, DLS, TGA, and DSC confirmed the successful synthesis of core-shell architecture and europium doping. Moreover, Fe₂O₃–EuCNPs demonstrating strong colloidal …

Microplastics Detection, Characterization, And Cytotoxicity Evaluation Via Lab-On-Chip, Liyuan Gong

Open Access Dissertations

Microplastics (MPs) pose a growing challenge to the ecological system, prompting increasing research efforts in diverse directions. Accurate characterization of MPs is essential for understanding their properties, relying on efficient sampling and detection techniques. Additionally, studying the cytotoxic effects of MPs is critical for evaluating their impact on biological systems. Lab-on-chip (LoC) systems offer significant advantages for precise particle manipulation and compatibility with advanced analytical instrumentation, making them valuable for MP detection and characterization. Microfluidic-based on-chip cell-culturing systems provide a controllable, physiologically relevant microenvironment for more realistic in vitro tissue modeling. By leveraging advanced LoC concepts and integrating state-of-the-art machine …

Pharmacological Or Genetic Inhibition Of Ltcc Promotes Cardiomyocyte Proliferation Through Inhibition Of Calcineurin Activity, Lynn A. C. Devilée, Abou Bakr M. Salama, Jessica M. Miller, Janice D. Reid, Qinghui Ou, Nourhan M. Baraka, Kamal Abou Farraj, Madiha Jamal, Yibing Nong, Todd K. Rosengart, Douglas A. Andres, Jonathan Satin, Tamer M. A. Mohamed, James E. Hudson, Riham R. E. Abouleisa

Markey Cancer Center Faculty Publications

Cardiomyocytes (CMs) lost during ischemic cardiac injury cannot be replaced due to their limited proliferative capacity. Calcium is an important signal transducer that regulates key cellular processes, but its role in regulating CM proliferation is incompletely understood. Here we show a robust pathway for new calcium signaling-based cardiac regenerative strategies. A drug screen targeting proteins involved in CM calcium cycling in human embryonic stem cell-derived cardiac organoids (hCOs) revealed that only the inhibition of L-Type Calcium Channel (LTCC) induced the CM cell cycle. Furthermore, overexpression of Ras-related associated with Diabetes (RRAD), an endogenous inhibitor of LTCC, induced CM cell cycle …

Advances In Magnetic Nanoparticles For Molecular Medicine, Xiaoyue Yang, Sarah E. Kubican, Zhongchao Yi, Sheng Tong

Markey Cancer Center Faculty Publications

Magnetic nanoparticles (MNPs) are highly versatile nanomaterials in nanomedicine, owing to their diverse magnetic properties, which can be tailored through variations in size, shape, composition, and exposure to inductive magnetic fields. Over four decades of research have led to the clinical approval or ongoing trials of several MNP formulations, fueling continued innovation. Beyond traditional applications in drug delivery, imaging, and cancer hyperthermia, MNPs have increasingly advanced into molecular medicine. Under external magnetic fields, MNPs can generate mechano- or thermal stimuli to modulate individual molecules or cells deep within tissue, offering precise, remote control of biological processes at cellular and molecular …

Functional Assessment Of Migration And Adhesion To Quantify Cancer Cell Aggression, Lauren E. Mehanna, James D. Boyd, Chloe G. Walker, Adrianna R. Osborne, Martha E. Grady, Brad J. Berron

Markey Cancer Center Faculty Publications

During epithelial-to-mesenchymal transition (EMT), cancer cells lose their cell–cell adhesion junctions as they become more metastatic, altering cell motility and focal adhesion disassembly associated with increased detachment from the primary tumor and a migratory response into nearby tissue and vasculature. Current in vitro strategies characterizing a cell’s metastatic potential heavily favor quantifying the presence of cell adhesion biomarkers through biochemical analysis; however, mechanical cues such as adhesion and motility directly relate to cell metastatic potential without needing to first identify a cell specific biomarker for a particular type of cancer. This paper presents a comprehensive comparison of two functional metrics …

Rift - Reddit Information Falsity Tagger, Parth Joshi

Master's Projects

Social media platforms such as Reddit are widely used for sharing and consuming information. User-generated content poses a great risk for misinformation creation and dissemination on these platforms. “Fake news”, as it is commonly referred to, has far-reaching social implications, swaying public perception, making political viewpoints more radical, and adversely impacting health decisions. The covariable features that come with fake news make it even harder to detect because it is presented in the form of text, images, videos, and even social interactions. This paper describes a novel method for detecting fake news on Reddit: RIFT, short for Reddit Information Falsity …

Reinforcement Learning-Based End-To-End Monitoring Path Selection In Multi-Domain Optical Networks, Soham Choudhury

Master's Projects

This paper presents a novel approach for optimizing network monitoring in optical communication systems using Reinforcement Learning (RL). Assuming a multi-domain architecture with limited domain visibility, we simulate multiple optical connections using an optical communications simulation software, GNPy, obtaining key network metrics to model the system. We developed two RL agents: the first agent selects near-optimal monitoring paths based on network states, and the second agent dynamically adapts its selected paths in response to state changes, such as fiber failures or issues with ROADMs. This adaptive approach allows for continuous improvement of network monitoring, ensuring resilience and efficient fault detection. …

Review: Dielectric Barrier Discharge Plasma Actuators For In-Flight Applications, Sabeel Saleem Mohammed

Anthós

Dielectric barrier discharge (DBD) is a phenomenon observed when high voltage is passed through a dielectric barrier at high frequencies. Current DBD plasma actuators (PAs) excel at laminar fluid boundary layer control but suffer from limited momentum flux and fluid mechanic inefficiencies. In this article, Mohammed analyzes previous discourse on DBD PAs and offers directions for future research and potential DBD PA applications. Previous work on DBD PAs documented thrust generation at high voltages and frequencies, thrust in varying fluid compositions, and vortex generation. However, certain arrangements hinder flow magnitudes, limiting the use of multiple DBD PAs in close proximity. …

Surface Morphology And Moisture Adsorption/Desorption Characteristics Of Hybrid-Dielectric Moisture Sensors, Ronak Ali

Theses and Dissertations--Electrical and Computer Engineering

Relative humidity sensors are used for high-humidity measurement. Moisture sensors, or dew point sensors are used for low-humidity measurement (< 1 ppm_v). The dissertation contains two parts of studies. In the first part, the effect of surface morphology on the response speed of moisture sensors is studied. Moisture sensors using α-Al₂O₃ films as porous dielectric materials deposited by anodic spark deposition are studied. In this part of the study, a variety of small pores have been studied to investigate the response speed of moisture sensors. Three different surface morphologies have been studied using scanning electron microscopy. One …

Predicting Crises On The African Frontier Stock Markets With Investor Sentiment Indicators: A Machine Learning Approach, David Korsah, Lord Mensah

Journal of International Technology and Information Management

This study examined the predictive ability of machine learning algorithms in identifying crises within African stock markets. The study employed seven distinct machine-learning models, analyzing historical stock prices from eight stock markets, three major sentiment indicators, and the exchange rates of local currencies against the US dollar, with each data spanning from May 1, 2007, to April 1, 2023. Extreme Gradient Boosting (XGBoost) emerged as the most effective algorithm for predicting crises. Historical stock prices and exchange rates were identified as the most critical features for prediction. On the sentiment side, investors’ perceptions of potential volatility on the S&P 500, …

A Conceptual View Of Data For Decision-Oriented Databases: A Knowledge-Driven Approach, Sung-Kwan Kim, Wenjun Wang, Seunghyun Kim

Journal of International Technology and Information Management

Typical database design goes through three levels of data modeling: conceptual modeling, logical modeling, and physical modeling. In particular, conceptual modeling is important since it captures and documents user data requirements. Conceptual modeling serves as a blueprint for designing a database by defining information content to be included in a database. Presently, decision-oriented databases have no well-accepted conceptual modeling approach to apply. While some use conceptual modeling approaches for transaction-oriented databases such as the ER (Entity-Relationship) model, they are not well-suited for decision-oriented databases. It is hard to map from the ER Model to decision-oriented data models. Others attempt to …

Preventive Health Care Information Seeking Behaviors Among Baby Boomers In Taiwan, Alexander N. Chen, Michael J. Rubach, Tracy Suter, Hsin Ke Lu, Mark E. Mcmurtrey

Journal of International Technology and Information Management

Preventive health care is widely acknowledged as one of the most effective ways to reduce medical costs and enhance people's health. Preventive health care information (PHCI) is a crucial component. This study examines the PHCI-seeking behaviors of Taiwanese baby boomers. The study found some support for the idea that the preferred media used influenced the likelihood of Information seeking behavior. People with good health conditions were found to be more likely to seek PHCI, while people with greater health care needs sought out PHCI less frequently. The study examined social influences, which were found to be important. Three different types …

Pedagogy In The Age Of Ai: Exploring Generative Ai For Higher Education, Alison Munsch Phd

Journal of International Technology and Information Management

Generative Artificial Intelligence (AI) presents transformative opportunities for higher education, enabling personalized learning, enhanced student engagement, and efficient pedagogical practices. This tutorial-style article guides educators in integrating generative AI into their classrooms through hands-on activities, practical strategies, and reflective exercises. It explores the capabilities of AI tools such as ChatGPT, their applications across disciplines, and the ethical considerations for their use. By cultivating critical thinking and fostering student readiness for AI-driven futures, this article underscores the transformative potential of generative AI in higher education with an emphasis on the academic areas of business analytics, information systems, and computer science.

Predicting Global Healthcare Supply Chain Delays: A Machine Learning Approach Leveraging Country-Level Logistics Metrics, Jeevan Sai Gali, Nima Molavi, Sepideh Alavi

Journal of International Technology and Information Management

In global healthcare logistics, ensuring the timely delivery of medical commodities is critical, particularly in low- and middle-income countries characterized by infrastructural limitations and operational uncertainties. This research introduces an advanced, data-driven predictive framework designed to forecast delivery delays by synthesizing granular, internal shipment-level data from the USAID Global Health Supply Chain Program (GHSC-PSM) with external country-level logistics capabilities indicators derived from the World Bank’s Logistics Performance Index (LPI). Rather than relying on retrospective trend analyses, this study employs machine learning algorithms such as Random Forest, XGBoost, Support Vector Machines (SVM), and Multi-Layer Perceptron (MLP) to detect …

Transport Of Nutrients By Overland Flow On Sites Containing Beef Cattle Manure, John E. Gilley, Ryan P. Mcgehee, Kenneth M. Wacha

Department of Agricultural and Biological Systems Engineering: Faculty Publications

In an inductive metastudy, we investigated the effects of varying rates of overland sheet flow on the transport of phosphorus (P) and nitrogen (N) from sites containing beef cattle manure. The analyzed data were collected during previously reported field rainfall simulation investigations conducted on cropland sites and a beef cattle feedlot in the US state of Nebraska. During the experiments, inflow was incrementally added to the top of the experimental plots to simulate runoff rates occurring at greater downslope distances. Runoff rates on the experimental plots ranged from 2.9 to 22.9 Lmin⁻¹, and the maximum equivalent downslope distances …

Crop2cloud Platform: Real-Time Data Integration For Agricultural Water Monitoring, Bryan Nsoh, Abia Katimbo, Kendall Dejonge, Wei-Zhen Liang, Hongzhi N. Guo, Yufeng Ge, Derek M. Heeren, Yeyin Shi, Xin Qiao, Daran R. Rudnick, Hope Njuki Nakabuye, Birru Girma, Isa Kabenge, Joshua Wanyama

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Efficient water management is vital for sustainable agriculture, yet integrating real-time data for precise irrigation remains a challenge. This study designed the Crop2Cloud (C2C) platform, a system that leverages advanced sensors using Internet of Things (IoT), edge and cloud computing techniques, and computed Water Stress Indices (WSIs) and machine learning models (i.e., fuzzy logic), to provide scalable and real-time irrigation decisions. The C2C platform aggregates several data including Volumetric Water Content (VWC) from TDR sensors (Acclima Inc., US) installed at four multiple depths, canopy temperatures (Tc) measured by Infrared Radiometers (IRTs) (Apogee Instruments, US), as well as weather information and …

Behavioral Insights Impacting Preweaning Mortality, Md Towfiqur Rahman, G. A. Rohrer, S. R. Sharma, Y. Shi, S. M. Leonard, Tami M. Brown-Bandl

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Conclusions

This study investigated the average time spent on posture behaviors (lying, kneeling, sitting, standing) of sows by analyzing the effects of time segments, farrowing crate types, parity, heat lamp configurations, and mortality groups. Sow posture behaviors were significantly influenced by mortality, parity, crate type, heat lamps, and day category. High mortality sows spent less time lying and more time standing events. Parity 1, 2, 3 sows were more active, spending more time kneeling in transitions, lying, and sitting events. Sows in TSL crate had longer lateral right lying and standing events, while ESCSL crates sows had longer sitting events. …

Firelog: An Open-Source, Low-Cost System For Temperature Logging During Wildland Fires With High Spatial And Temporal Resolution, Nipuna Chamara, Yufeng Ge, Sabrina E. Russo

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Measuring flame, air, and soil temperatures during wildland fires, including wildfires and controlled burns in land management contexts, is crucial for research and applications in fire ecology, safety, and management in a wide array of ecosystems, from grasslands to forests. However, open-source and commercial systems are needed for measuring and logging flame and air temperatures that are user-friendly, economical, modular, and customizable. This paper details the design, development, and validation of the FireLog system. Laboratory validation experiments demonstrated high measurement accuracy, with a minimum coefficient of determination (R2) of 0.98 and the highest observed root mean square error (RMSE) of …

Inactivation Of Zika Virus With Hydroxypropyl-Beta-Cyclodextrin, Cory R. Hewitt, Nicholas J. Wixon, Arthur Gallegos, You Zhou, Victor C. Huber, M. Scott. Killian

Nebraska Center for Biotechnology: Faculty and Staff Publications

Background/Objectives: Zika virus (ZIKV) infection is associated with life-threatening diseases in humans. To date, there are no available FDA-approved therapies or vaccines for the specific treatment or prevention of ZIKV infection. Variation in the ZIKV envelope protein (Env), along with its complex quaternary structure, presents challenges to synthetic approaches for developing an effective vaccine and broadly neutralizing antibodies (bnAbs). We hypothesized that beta-cyclodextrin (BCD) could be used to uniquely inactivate infectious ZIKV without disruption of Env.

Methods: ZIKV was propagated in Vero cells and admixed with BCD. The BCD-treated ZIKV was evaluated for infectivity using immunofluorescence and quantitative …

Microscopic Analysis Of Temperature Effects On Surface Colonization And Biofilm Morphology Of Salmonella Enterica, Zachariah Vice, You Zhou, Sapna Chitlapilly Dass, Rong Wang

Nebraska Center for Biotechnology: Faculty and Staff Publications

Salmonella enterica represents a diverse group of pathogens commonly associated with food contamination including red meat. Even though pre- and post-harvest cleaning and sanitization procedures are widely implemented at meat processing plants to mitigate the hazard, S. enterica cells may escape the process by colonizing, on contact, surfaces in the form of a biofilm that functions as an aggregated microbial community to facilitate mutual protection, antimicrobial resistance, proliferation and dissemination. Biofilm development is a complex process that can be affected by a variety of factors including environmental temperature. We developed methods using scanning electron microscopy and confocal microscopy with a …

Characterization Of Multispecies Microbial Communities At Beef And Pork Processing Plants And Their Impact On Pathogen Stress Tolerance, Rong Wang, Sapna Chitlapilly Dass, Vignesh Palanisamy, You Zhou, Tatum Katz, Joseph M. Bosilevac

Nebraska Center for Biotechnology: Faculty and Staff Publications

Escherichia coli O157:H7 and Salmonella enterica are major foodborne pathogens. Biofilm formation may potentially contribute to product contamination by these pathogens at meat processing facilities. Further, pathogen stress tolerance may vary significantly due to the interactions with the multispecies microbial community at meat plants, which may be affected by processing activity, animal species, and the local selective pressure caused by sanitization practices.

We characterized natural microorganisms collected from floor drains at various areas at three beef plants and two pork plants and analyzed their impact on pathogen sanitizer tolerance.

The pathogen strains were able to integrate efficiently into the multispecies …

Mixing-Controlled Combustion Of Ethanol Enabled By Prechamber Ignition (Pc-Mcc): A Preliminary Experimental Demonstration, Jared Zeman, Ziming Yan, Michael Bunce, Adam Dempsey

Mechanical Engineering Faculty Research and Publications

This numerical study focuses on assessing the key design parameters of interest for use of an active prechamber igniter as an ignition assistance device to enable mixing-controlled combustion (MCC) of ethanol (E100) in a heavy-duty Caterpillar C9.3B engine. Computational fluid dynamic (CFD) simulations of a baseline diesel and prechamber retrofitted C9.3B at a gross indicated mean effective pressure (IMEPg) of 5 bar and 1800 rpm are carried out using CONVERGE. In particular, the sizing of the prechamber volume, sizing of total orifice cross sectional area (orifice diameter), and location of the prechamber relative to a centrally mounted common rail direct …

Effects Of Data Augmentation On Sponge Identification Using Computer Vision Models, George Ku

Master's Projects

Coral reefs can be primarily found in tropical and sub-tropical regions of our oceans, providing a thriving habitat for millions of species. Marine sponges, which can be frequently found in coral reefs, play a critical role that contributes to the maintenance of these ecosystems, including the recycling of nutrients through water filtration. However, rising ocean temperatures and acidification due to climate change have resulted in the bleaching and death of coral reefs worldwide. In order to preserve these reefs and the sponges that depend on them, scientists have been performing studies on their biodiversity. This includes collecting numerous images of …

Disease Diagnosis Using Rag Llm With Smart Prompt Engineering, Qadeerullah Syed

Master's Projects

Although recent trends indicate that LLMs outperform traditional methods in solving complex problems with enhanced reasoning, there has been barely any progress in replicating the quality of diagnoses like those of actual human doctors. The identification of an accurate diagnosis with thorough reasoning is still a significant challenge, even with advanced AI models. The process of performing accurate diagnosis remains challenging due to a lack of transparency in state-of-the-art models existing today, a lack of explanation in the diagnosis process, an emphasis on results rather than reasoning, and a lack of foundational knowledge in models, along with limited exploration of …

Transformers In Time-Series Forecasting: Enhancing Robustness Via Dynamic Attention Mechanisms, Kush Patel

Master's Projects

Transformer architectures have emerged as powerful tools for time series forecasting, excelling at capturing complex temporal dependencies across multivariate inputs. However, these models are highly susceptible to adversarial attacks such as the Fast Gradient Sign Method (FGSM) and Basic Iterative Method (BIM), which can significantly degrade predictive performance through small, targeted perturbations. This work integrates dynamic attention mechanisms, adaptive masking modules that introduce controlled variability into attention pathways, into a transformer forecasting model to enhance robustness against such attacks. Using two distinct datasets, we compare the performance of a standard transformer and a dynamic attention-enhanced transformer under both clean and …