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Evaluation Of Performance Characteristics And Groundwater Contamination Risks Associated With On-Farm Swine Carcass Disposal Via Composting And Shallow Burial With Carbon, Gustavo Castro Garcia

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

This dissertation evaluates the performance of three on-farm swine carcass disposal methods: whole carcass composting (WCC), ground carcass composting (GCC), and shallow burial with carbon (SBC), focusing on biosecurity factors and groundwater contamination risks. Foreign animal diseases (FADs), such as African swine fever and classical swine fever, pose severe economic and animal well-being risks if introduced to the United States. With confirmation of an FAD, swine movement will be halted, creating an urgent need for practical, biosecure, and environmentally responsible on-farm disposal strategies for swine carcasses. Nebraska, as a leading swine-producing state, exemplifies the vulnerability of high-density livestock regions to …

Robustness Investigation, Detection, And Defense Of Deep Learning Models Against False Data Injection, Amirhossein Nazeri

All Dissertations

This dissertation addresses the critical challenge of adversarial robustness in deep learning systems, focusing on two fundamental domains: time-series prediction and object detection. As these AI systems become increasingly deployed in safety-critical applications from power grid management to autonomous vehicles their vulnerability to adversarial attacks poses significant risks to infrastructure and human safety.

The first contribution introduces a novel stealthy black-box False Data Injection (FDI) attack specifically designed for quasi-periodic time-series data. Unlike existing attacks that produce easily detectable anomalies, our method generates adversarial perturbations that preserve the underlying periodicity and statistical properties of the data, effectively bypassing traditional anomaly …

Real-Time Fiducial Marker Based Localization For Autonomous Unmanned Aerial Vehicle Navigation, Sourav Raxit

LSU New Orleans Theses and Dissertations

By harnessing fiducial markers as visual landmarks in the environment, Unmanned Aerial Vehicles (UAVs) can rapidly build precise maps and navigate spaces safely and efficiently, unlocking their potential for fluent collaboration and coexistence with humans. Existing fiducial marker methods rely on handcrafted feature extraction, which sacrifices accuracy. On the other hand, some deep learning pipelines for marker detection fail to meet real-time runtime constraints crucial for navigation applications. In this work, I propose YoloTag- a real-time fiducial marker-based localization system. YoloTag uses a lightweight YOLO v8 object detector to accurately detect fiducial markers in images while meeting the runtime constraints …

Anisotropic Object-Based Shifts Of Attention Arise From Unequal Influences Of Visual Field Meridians On Neural Attention Gradients, David H. Hughes, Adam J. Barnas, Adam S. Greenberg

Biomedical Engineering Faculty Research and Publications

Object-based attention prioritizes the processing of information appearing within a selected object. We previously showed an object-based shift direction anisotropy (SDA) whereby horizontal shifts are more efficient than vertical shifts (Barnas AJ, Greenberg AS. Atten Percept Psychophys 78: 1985–1997, 2016; Barnas AJ, Greenberg AS. Vis Cogn 27: 768–791, 2019), an effect modulated by the visual field meridians (Barnas AJ, Greenberg AS. Q J Exp Psychol (Hove) 77: 2516–2532, 2024). Our present aim was to understand how the functional brain mechanisms of attention give rise to the SDA. We hypothesized that the SDA arises from attentional resources being partitioned differently by …

Feasibility Study On Using Blue Clay As A Supplementary Cementitious Material (Scm)., Clark Lemon

Master of Engineering Theses

An effective strategy for reducing CO₂ emissions in the global cement industry is replacing a percentage of cement with supplementary cementitious materials (SCMs). As the availability of conventional SCMs such as fly ash and slag is decreasing, alternative SCMs such as calcined clays have been studied for their use as effective pozzolans. The present work investigates the feasibility of using a waste product from the quarrying industry known as blue clay as a viable SCM. It is composed of multiple clay minerals, predominantly muscovite. Raw and calcined at four temperatures (500, 650, 800, and 950°C), blue clay was analyzed …

Development Of A Wearable Biosensor For Cortisol Detection In Human Sweat Utilizing Pani/Peo Polymer Blend And Nitrogen-Doped Graphene Quantum Dots, Cesar Sanchez

Theses and Dissertations

Since the development of the first biosensor in 1962, the evolution of commercially available wearable biosensors has been driven by an increasing consumer interest in real-time health tracking. However, challenges related to sensor sensitivity and cost have hindered progress. Deploying a novel approach, the biosensor integrates a blend of Polyaniline (PANi) and Polyethylene Oxide (PEO) along with Nitrogen-doped Graphene Quantum Dots (N-GQDs) to enhance sensitivity and electroactivity, crucial for cortisol detection. To optimize performance, three distinct synthesis methods for N-GQDs; hydrothermal, microwave, and hot plate synthesis were compared employing a bottom-up approach utilizing citric acid (CA) as the primary reactant …

Computational Modeling For Automatic Superconducting Cavity Fault Prediction And Classification Using Time Series Signals, Md Monibor Rahman

Electrical & Computer Engineering Theses & Dissertations

Processing multivariate time series signals collected from sensor networks is challenging because of complex temporal dependencies and non-stationarity. With the advent of artificial intelligence (AI) like machine learning and deep learning, it has become possible to process sensor-driven time series data more effectively than traditional statistical methods.

This dissertation aims to develop machine learning and deep learning models to address machine fault diagnosis using multivariate time series signals collected from the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. The first goal of the proposed work is to develop deep learning–based classification models and an unsupervised fault clustering approach …

Impact Of Cysteine And Tyrosine Dipeptides On Cho Cell Performance In A Perfusion Mimic, Corrin L. Pruitt

All Theses

Perfusion cell cultures typically achieve higher cell densities and generate higher volumetric productivities than fed-batch cultures due to continuous nutrient supply and spent media removal. Despite these advantages, perfusion cell cultures remain underutilized for licensed product manufacturing, primarily due to the lack of small-scale perfusion models for high-throughput process development and the complexities involved in media formulation capable of supporting high cell densities during long-term continuous operation. To avoid nutrient limitation at high cell densities, current perfusion processes rely on using higher perfusion rates, which results in significant media wastage and downstream product dilution. Therefore, there has been an effort …

Biological Hydrogen Process Improvements By High Temperature Simultaneous Saccharification And Fermentation, Frank W. Jeffries V

All Theses

The hyperthermophilic bacterium Thermotoga neapolitana is established as a versatile organism for fermentative hydrogen (H₂) production. Batch experiments were carried out to investigate the cell yield, product yield, and kinetic parameter values for individual media containing five carbohydrates. The highest H₂ yield of 15.56±0.31 mmol-H₂/g-carbohydrate was reported for glucose medium. H₂ yield was measured to be 14.51±0.38, 14.44±1.15, 11.88±0.84, and 11.53±0.73 mmol/g for media containing xylose, cellobiose, arabinose and xylan respectively. Acetic acid yield followed a similar trend, where the obtained values were 0.470±0.01, 0.462±0.04, 0.431±0.01, 0.409±0.03, and 0.406±0.01 g-acid/g-carbohydrate for glucose, cellobiose, xylose, …

Ev Charging Management In A Real-Time Optimization Framework Considering Operational Constraints, Hilmi Cihan Güldorum, Ayşe Kübra Erenoğlu, İbrahim Şengör, Barry P. Hayes, Ozan Erdinç

Department of Computer Science Publications

The electrification of transportation plays a central role in the decarbonization of energy systems. Although electric vehicles (EVs) are expected to reduce energy related emissions, the increasing demand imposed by large scale EV adoption presents serious challenges for distribution systems (DSs), which were not originally designed to accommodate such loads. This study proposes a mixed integer quadratically constrained programming (MIQCP) framework to optimize the operation of an EV parking lot (EVPL) under DS constraints. The model compares three widely adopted objective functions: minimization of active power loss, charging cost, and uncontrolled charging impact, which is represented by minimizing the total …

A Study On The Propagation And Exploitation Of Structured Light In Underwater Turbulence, Jaxon P. Wiley

All Dissertations

The development and optimization of optical systems will play a pivotal role in the continued exploration and exploitation of the world’s underwater environments. These systems offer advantages in many sectors, and includes applications in areas such as high-speed communication, advanced sensing and imaging, and environmental characterization and monitoring. Underwater environments offer a plethora of challenges, however, and mitigating these obstacles remains an arduous task. In this work, the inherent advantages of structured light are leveraged to optimize optical system performance through non-ideal underwater conditions. Additionally, fundamental relationships between the generation of specified structured modes and their interactions with complex environments …

Effects Of Lossy Compression Data On Machine Learning Models, Max H. Faykus Iii

All Dissertations

Machine learning is a fundamental tool that is incorporated in every field across academia and other industries. Due to the large amount of data needed for training machine learning models, lossy compression plays a crucial role in storing data. Machine learning involves the use of algorithms and models to learn patterns in data. This allows the AI to make decisions without specific programming. On the other hand, compression utilizes encoding and decoding techniques to reduce the size of files. Compression is either lossy or lossless, lossy causes a loss of data while lossless preserves the data. This dissertation will explore …

Decoding Anisotropic Porous Medium: A Synergy Of Lattice Boltzmann Modelling And Operator Learning To Predict Permeability As A Function Of Orientation, Soumya Shouvik Bhattacharjee

Open Access Theses & Dissertations

Understanding the directional properties of porous media is essential for accurately predicting flow behavior, reactive transport, and fluid-solid interactions in systems ranging from geothermal reservoirs to energy storage devices and biological tissues. Directional variations in permeability - reflecting a medium's response to flow at different angular orientations - are particularly important for complex, inherently anisotropic geometries. In this study, we employ a Lattice Boltzmann (LBM) model to calculate directional permeabilities from porous media images subjected to varying flow inlet angles. Three classes of porous media were investigated: (1) synthetic media with circular grains, serving as isotropic baselines; (2) synthetic media …

Thermal Inkjet Bioprinting Of Human Fibroblasts Into Stem Cell Environment Leads To Stem-Like Gene And Protein Expression And Changes In Hippo Pathway Effectors Yap/Taz, Patricia Ablanedo Morales

Open Access Theses & Dissertations

Thermal inkjet bioprinting (TIB) has emerged as a powerful tool with many potential applications, such as organ regeneration, drug testing, and cell differentiation, among others. Despite the forces and stress that cells are subjected to during the printing process, there is little research that investigates in detail the combined effects of the TIB process and the surrounding environment on cells. Furthermore, a cell's biological environment greatly influences its behavior. Therefore, understanding the effects of bioprinting on cells in a particular environment at a genetic level can provide clues regarding changes in cell characteristics. Bioprinting could potentially be used as a …

Effects Of Environmental Stressors On Human Tissue-On-A-Chip Platforms, Andie Padilla

Open Access Theses & Dissertations

As space exploration begins to extend beyond low earth orbit, it has become increasingly critical to understand the interaction of the extreme environment of space flight with human systems. While it is known that space-travel induces a vast array of complications to cardiac, neural, musculoskeletal, and immune systems, the mechanisms by which these complications occur are poorly understood. Current research to study the effects of microgravity and radiation are limited to ground simulations, which rarely account for the multifactorial stressors experienced during spaceflight, or long duration studies aboard the International Space Station. Similarly, traditional two-dimensional (2D) models lack the ability …

Technology-Enabled Foreign Object (Fo) Prevention, Christopher Lee Colaw

Open Access Theses & Dissertations

The aviation industry incurs $14 billion per year in cost due to Foreign Object (FO) damage and the prevention and resolution techniques associated with foreign object debris. While aircraft loss, material scrap and rework contribute to that cost impact, a traditional approach to aircraft design and manufacturing which is based on human performance is also a significant driver. Failure modes and effects analysis of human based aircraft manufacturing reveals that two of the largest risks are associated with unknown potential for FO creation and the inability to recall or objectively provide evidence of FO conformity for cases of inquiry, learning, …

Controlling Electroless Deposition On Polymer Interfaces Towards Discrete Functional Particle Synthesis, Grecia Pierina Alvarado Munoz

Graduate Theses and Dissertations

Electroless deposition is a process that facilitates the formation of metal layers on surfaces through the reduction of metal ions onto a surface in the presence of a sacrificial reducing agent. This process can be applied to synthesize conductive metal layers on insulators such as glass or polymers. The kinetics of heterogeneous deposition depend on the interfacial surface chemistry, including the presence of added catalyst materials, as well as the bulk chemical environment, such as the concentration of metal ions and sacrificial reductants. Furthermore, the homogeneous formation of metal nanoparticles may compete with the deposition reaction, adversely affecting the control …

Advancing Smart And Adaptive Living Spaces Through Design And Development Of Reconfigurable Multifunctional Robot Rooms, Nithesh Kumar

All Dissertations

This work explores and introduces prototype hardware for a new category of robots: ‘Robot Rooms’, in an effort to refine the concept of traditional smart spaces and human-robot interaction. Unlike traditional robots that tend to be compact and exist within a space, this new category of robots is designed to be expansive: they do not exist within a space but rather shape space around them. We present several design concepts for potential robotic elements of a Robot Room. We then develop and demonstrate, at full scale, a new and novel concept: a ‘slice’ of a Robot Room. This slice changes …

Resilient Control Framework For Ev Motor Drive System Subject To Cyber-Physical Security, Ali Arsalan

All Dissertations

The electric drive system (EDS) in electric vehicles (EVs) is one of the key safety-critical components. As IoT-enabled communication infrastructure for modern cyber-physical automotive systems continues to evolve, the importance of securing EDS against cyber threats along with physical faults, has become increasingly prominent. Among physical faults, power switches are particularly vulnerable and exhibit the highest susceptibility to open-circuit faults (OCFs). A compromised EDS, whether due to cyber threats or physical issues, can lead to excessive mechanical vibrations, increased thermal stress, fluctuations in electromagnetic torque, and elevated total harmonic distortion. These factors can substantially undermine traction control stability and jeopardize …

Advancing Lithium-Ion Batteries Through Exploration Of Novel Physico-Chemical Phenomena, Peshal Karki

All Dissertations

Lithium-ion batteries (LIBs) power a wide range of modern devices, from smartphones to electric vehicles. This dissertation integrates materials characterization and electrochemical testing to develop novel Si-based electrode materials, investigate separator effects, and improve electrochemical impedance spectroscopy (EIS) modeling. First, I synthesized Si@CC composites using bio-based carbon sources and discovered a novel in situ disorder reduction in the amorphous carbon cloud during cycling, attributed to Si volume fluctuations and mesoporous carbon structure, which enhanced capacity retention. A binder-free electrode (Si@CC@BP) using bucky paper further improved gravimetric and areal capacities while reducing weight and manufacturing complexity.

Next, I investigated how separator …

Modeling Disaster Resilience Through A Human-Centered Lens: Exposure, Vulnerability And Adaptation, Tong Liu

All Dissertations

The core of reframing and operationalizing disaster resilience with a human-centered lens is to incorporate concepts from socio-ecological resilience into engineering resilience to better understand the humans’ capability for disaster adaptation. Existing studies have drawn practical implications by identifying actionable thresholds for infrastructure systems under disasters, which can be easily applied by policymakers, emergency managers and municipal agencies. However, how individuals interact with, respond to, or adapt under these infrastructure thresholds remain understudied. This hinders the operationalization of disaster resilience at the human scale.

First, I examined exposure by analyzing how configuration and distribution of urban infrastructure systems, such as …

Synthesis And Characterization Of Magnetic Nanoparticles To Study Effective Magnetic Anisotropy For Biomedical And Catalytic Applications, Alexander Malaj

All Dissertations

This dissertation focuses on understanding how to tune the magnetic properties of nanoparticles through controlling the effective magnetic anisotropy (Keff), which is a key variable in determining a nanoparticle’s Néel relaxation time, which will dictate its magnetic behavior in various applications. In this work, magnetocrystalline anisotropy is tuned by synthesizing tri-metallic substituted ferrite (Fe3-x-yMnxCoyO4) nanoparticles with specific metallic compositions that were informed by computer simulations using density functional theory (DFT) to target magnetocrystalline anisotropy values. A drip synthesis was used to control the size and composition of the tri-metallic ferrites, which were revealed to be monodisperse and compositionally mixed by …

Genwriter: Reducing Gender Cues In Biographies Through Text Rewriting, Shweta Soundararajan, Sarah Jane Delany

Conference papers

Gendered language is the use of words that indicate an individual’s gender. Though useful in certain context, it can reinforce gender stereotypes and introduce bias, particularly in machine learning models used for tasks like occupation classification. When textual content such as biographies contains gender cues, it can influence model predictions, leading to unfair outcomes such as reduced hiring opportunities for women. To address this issue, we propose GenWriter, an approach that integrates Case-Based Reasoning (CBR) with Large Language Models (LLMs) to rewrite biographies in a way that obfuscates gender while preserving semantic content. We evaluate GenWriter by measuring gender bias …

Applying Large Language Models For Surgical Case Length Prediction, Adhitya Ramamurthi, Bhabishya Neupane, Priya Deshpande, Ryan Hanson, Srujan Vegesna, Deborah Cray, Bradley H. Crotty, Melek Somai, Kellie R. Brown, Sachin S. Pawar, Bradley Taylor, Anai N. Kothari

Electrical and Computer Engineering Faculty Research and Publications

Importance Accurate prediction of surgical case duration is critical for operating room (OR) management, as inefficient scheduling can lead to reduced patient and surgeon satisfaction while incurring considerable financial costs.

Objective To evaluate the feasibility and accuracy of large language models (LLMs) in predicting surgical case length using unstructured clinical data compared to existing estimation methods.

Design, Setting, and Participants This was a retrospective study analyzing elective surgical cases performed between January 2017 and December 2023 at a single academic medical center and affiliated community hospital ORs. Analysis included 125493 eligible surgical cases, with 1950 used for LLM fine-tuning and …

Coupling Effect Of Abrasion And Erosion On Ultrahigh-Performance Seawater-Sea Sand Concrete, Dawei Ding, Wei Zhang, Lanqin Wang, Hongyan Ma, Biqin Dong, Song Han, Hongjian Xu, Dongshuai Hou

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Preparing ultrahigh-performance seawater-sea sand concrete (UHPSSC) to mitigate the scarcity of freshwater and river sand resources has generated considerable recent research interest. However, the deterioration mechanisms of UHPSSC under the effect of abrasion and erosion remain unstudied. In this paper, the underwater steel ball method was conducted to evaluate the impact of seawater, sea sand, steel fiber, and seawater abrasion on the abrasion resistance of UHPSSC. Then the stress erosion models of calcium-silicate-hydrate (C-S-H) were constructed to investigate the degradation mechanisms of UHPSSC under the effect of external stress and seawater erosion. The results show that the application of seawater …

Impact Of Biodegradation On The Mechanical And Fatigue Properties Of 3d-Printed Pla Bone Scaffolds, Hamed Bakhtiari, Alireza Nouri, Muhammad Aamir, Mohadeseh Najafi, Majid Tolouei-Rad

Research outputs 2022 to 2026

A proper degradation rate of bone scaffolds ensures optimal mechanical support and effective tissue regeneration. The present study examines the degradation effects of simulated body fluids (SBF) on the compressive and fatigue strength of 3D-printed PLA bone scaffolds. Scaffolds with varying surface-to-volume (S/V) ratios and identical porosity (60 %) were immersed in Hanks' solution for a maximum period of 30 days. Static and dynamic compression tests were performed at different immersion times to assess how S/V ratio influences the degradation process. CT images showed that scaffold pore structure remained interconnected after biodegradation, with no significant change in strut thickness or …

Building A Sustainable Home On The Central Coast: An Owner’S Perspective, Austin Chase Anderson

Construction Management

As awareness and technology increase, sustainability as a focus in home construction is also increasing. This case study based research project seeks to understand the process of building a home on California’s Central Coast with sustainability in mind. An interview was conducted with an owner who built their home in Templeton in 2019. The interview was in a semi-structured format which included specific qualitative questions but mostly focused on an open-ended discussion which allowed the owner to share their own experience. The key challenges learned from this interview were that the owner believed price to be the main factor that …

Validation Of A Methodology For Predicting Yield Acceleration Of Rock Blocks, Madison Haydn-Myer

Graduate Theses & Non-Theses

Rock slope stability is a critical concern in seismically active regions, where earthquakes can trigger sudden and hazardous failures. Predicting these failures is challenging due to the complex interactions between seismic loading and geological characteristics. This study proposes a simplified analytical model to predict yield acceleration based on the forces acting upon a block just before sliding initiates. A key parameter in this equation is the friction acting on the bottom surface of the block. As rock blocks are commonly formed by the intersection of sets of subparallel fractures known as joints, and the roughness and other features of those …

Axicons For Improved Resolution And Depth Of Focus In Adaptive Optics Scanning Light Ophthalmoscopy, Ruth E. Woehlke, Robert F. Cooper

Biomedical Engineering Faculty Research and Publications

Adaptive optics scanning light ophthalmoscopes are instrumental for studying the eye, yet they use truncated Gaussian illumination and are limited by diffraction, restricting resolution and depth of focus (DOF). Non-diffractive Bessel beams have emerged as an alternative. Here, we use two axicons configured as: (1) an extended DOF beam for resolving multiple retinal layers; and (2) an annular beam for increasing lateral resolution. We compare both approaches to truncated Gaussian illumination using a variety of metrics. Using Configuration 1, we successfully observed multiple retinal layers simultaneously. Using Configuration 2, we observed enhanced lateral resolution but decreased signal-to-noise ratio.

Mantle Flow And Crustal Deformation Revealed By Seismic Anisotropy In The Subduction Zone Beneath Myanmar, Enbo Fan, Mingming Jiang, Yinshuang Ai, Stephen S. Gao, Kelly H. Liu, Yumei He, Yiming Bai, Guangbing Hou, Yuan Ling, Chit Thet Mon, Myo Thant, Kyaing Sein

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The oblique convergence of the Indian and Eurasian plates drives significant deformation in the crust and mantle beneath Myanmar. However, the crustal deformation in the Indo-Burman Ranges (IBR) and mantle flow beneath Myanmar and adjacent areas remain unclear due to limited studies. We utilized data from the newly deployed second phase of the China-Myanmar Geophysical Survey of the Myanmar Orogen array to perform shear wave splitting analysis of PKS, SKKS, and SKS (XKS) phases. Our results, together with previous findings, provide new insights into mantle flow and crustal deformation across central Myanmar. In the IBR, we observed a transition from …