Physical Sciences and Mathematics Commons^™

Computational Models That Exploit Spatial, Temporal, And Voltage-Current Relationships In The Electrochemical Generation-Collection Of Redox-Active Molecules, Miguel Angel Abrego Tello

Graduate Theses and Dissertations

The numerical studies in this dissertation explore the application of redox cycling, an advanced electrochemical technique, for analyzing bioelectrochemical systems with a particular focus on small-volume samples and involves electrodes that can be activated to oxidize and reduce, separated by varying distances and featuring different geometries. The redox cycling approach facilitates the spatio-temporal interrogation of kinetics, mass transport, and the quantification and identification of chemical systems. We optimize a previously fabricated neural probe design on an SU-8 substrate, featuring coplanar arrays of nine microband electrodes suited for in vivo applications. Through comprehensive in situ and in silico redox cycling studies …

A Real-Time Iot-Based Data Acquisition And Monitoring System For Photovoltaic Applications, Adam Barbosa, Hamza Mubarak, Fazel Mohammadi, Mohammad J. Sanjari, Mehrdad Saif

Electrical & Computer Engineering and Computer Science Faculty Publications

The transition to low-carbon energy systems, driven by climate change and fossil fuel scarcity, highlights technologies, such as Photovoltaic (PV) technology, for sustainable energy generation. This paper focuses on enhancing the efficiency of PV monitoring systems by leveraging Internet of Things (IoT) technology for accurate and real-time monitoring of essential parameters, such as voltage, current, and output power. Significant gaps in cost-effective and reliable IoT integration for PV monitoring are addressed, with an emphasis on predictive modeling. In this regard, a low-cost real-time IoT-based data acquisition and monitoring system for PV systems, as a proof of concept for future endeavors …

Differential Behavior Of Conformational Dynamics In Active And Inactive States Of Cannabinoid Receptor 1, Ugochi H. Isu, Adithya Polasa, Mahmoud Moradi

Chemistry & Biochemistry Faculty Publications and Presentations

Cannabinoid receptor 1 (CB1) is a G protein-coupled receptor that regulates critical physiological processes including pain, appetite, and cognition. Understanding the conformational dynamics of CB1 associated with transitions between inactive and active signaling states is imperative for developing targeted modulators. Using microsecond-level all-atom molecular dynamics simulations, we identified marked differences in the conformational ensembles of inactive and active CB1 in apo. The inactive state exhibited substantially increased structural heterogeneity and plasticity compared to the more rigidified active state in the absence of stabilizing ligands. Transmembrane helices TM3 and TM7 were identified as distinguishing factors modulating the state-dependent dynamics. TM7 …

Engineering Central Substitutions In Heptamethine Dyes For Improved Fluorophore Performance, Lei Guo, Meek Yang, Bin Dong, Seth Lewman, Alex Van Horn, Shang Jia

Chemistry & Biochemistry Faculty Publications and Presentations

As a major family of red-shifted fluorophores that operate beyond visible light, polymethine dyes are pivotal in light-based biological techniques. However, methods for tuning this kind of fluorophores by structural modification remain restricted to bottom-up synthesis and modification using coupling or nucleophilic substitutions. In this study, we introduce a two-step, late-stage functionalization process for heptamethine dyes. This process enables the substitution of the central chlorine atom in the commonly used 4′-chloro heptamethine scaffold with various aryl groups using aryllithium reagents. This method borrows the building block and designs from the xanthene dye community and offers a mild and convenient way …

Recent Advances In Magnetic Feˣ⁺/Tio₂ Microfibers For Wastewater Treatment As Climate Change Mitigation, Misriani Misriani, Yang Tian, Z. Ryan Tian

Chemistry & Biochemistry Faculty Publications and Presentations

Chemical dyeing and finishing processes used in the clothing and textile industries are among the main contributors that can increase the impact of climate change. Photocatalysis using nanosized titanium dioxide (TiO₂) has been continuously developed as a promising technology for purifying dye wastewater into simpler and environmentally friendly components. In addition, the decoration of iron cations (Fe²⁺) and (Fe³⁺) increases the reusability of the photocatalyst due to their magnetic properties, which are easy to collect for the recycling process. Magnetic Fe^x+/TiO₂ microfibers have been successfully prepared using a hydrothermal method using …

Querymate: A Custom Llm Powered By Llamacpp, Pegah Khosravi

Open Educational Resources

No abstract provided.

On Neumann Boundary Conditions For Nonlocal Models With Finite Horizon, Scott Alex Hootman-Ng

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

Nonlocal models are have recently seen an explosive interest and development in the context of fracture mechanics, diffusion, image processing, population dynamics due to their ability to approximate differential-like operators with integral operators for inherently discontinuous solutions. Much of the work in the field focuses on how concepts from partial differential equations (PDEs) can be extended to the nonlocal domain. Boundary conditions for PDEs are crucial components for applications to physical problems, prescribing data on the domain boundary to capture the behavior of physical phenomena accurately with the underlying model. In this thesis we specifically examine a Neumann-type boundary condition …

Equilibria And Effective Transition Rates In Linear Networks, Sayani Ghosh

All Dissertations

Investigating equilibration in nucleosynthetic processes is crucial for understanding stellar chemical abundances in nuclear astrophysical scenarios. While current computational models are effective at predicting final species abundances at the end of these stellar processes, they fail to provide insights into the evolution of equilibrium. Without this deeper understanding, it is challenging to determine the impact of individual reaction rates on timescales and the resultant equilibrium.

In this work, we model nucleosynthetic processes as directed graphs. We develop theorems that allow us to express the mass fractions of species as spanning arborescences of these graphs. By obtaining eigenvalues in terms of …

Studying The Chemistry-Property Relationship In Magnetic And Optical Materials: Spin S = 3/2 Systems Of Neodymium, Manganese, And Cobalt Oxyanions, Xudong Huai

All Dissertations

This dissertation describes the design and tunability of new magnetic and optical materials, emphasizing the intricate relationship between their crystal structures and their optical, electronic, and magnetic properties.

Two new frustrated magnets, ANd(SO₄)₂ (A = Rb, Cs), were designed and synthesized to examine the influence of the the counter cation A site in Nd lanthanide materials featuring a distorted triangular magnetic lattice with S = 3/2. This work demonstrates how the tunability of magnetic and photoluminescent properties can be achieved through the A sites, with findings validated through density functional theory calculations.

AMnTeO₆ (A = Ca, …

Remote Onboarding Of Software Developers: Leveraging Virtual Reality And Ai Tools, James Dominic

All Dissertations

Software development teams add newcomers to accommodate the increasing demand, complexity of software solutions, and turnover. Onboarding newcomers is expensive and error-prone. It can take up to three years for a newcomer to become an expert on a project. Onboarding techniques described in the current literature focus on collocated teams. As more teams are adopting remote and distributed team structures, I address this research gap in understanding remote onboarding for software developers. I present my research on the use of Virtual Reality (VR) for remote software developer onboarding. I discuss a VR remote pair programming environment. With positive outcomes, pair …

Some Experiments In Additive Number Theory, Yunan Wang

All Dissertations

This dissertation explores fundamental conjectures in number theory, focusing on the distribution patterns of representation functions in prime pairs. The work concentrates on twin primes, cousin primes, and primes separated by six units, offering a fresh heuristic interpretation of the Hardy-Littlewood correction factor. The analysis progresses to investigate the partition function for prime pairs in the form $(p, p+k)$, specifically for $k = 2, 4, 6$. The study culminates in the derivation of a general formula for prime pairs $(p, p+d)$, where $d$ is an even integer. Drawing on the insights gleaned from examining the correction factor, this dissertation proposes …

We Train Ai, Why Not Humans, Too? An Exploration Of Human-Ai Team Training For Future Workplace Viability, Caitlin M. Lancaster

All Dissertations

The integration of Artificial Intelligence (AI) in the workforce is transforming team dynamics, leading to the emergence of Human-AI Teams (HATs). These teams offer opportunities to capitalize on human strengths with AI's prowess, offering significant opportunities for innovation and efficiency. Effective HAT functioning requires aligning human expectations with AI capabilities and bridging knowledge gaps between teammates. Despite this potential, key integration challenges remain, such as developing shared mental models, addressing skill limitations, and overcoming negative AI perceptions. Existing training efforts often apply human-human teaming principles directly to HATs, overlooking AI's role as a teammate and limiting the development of HAT-specific …

Optimization Strategies For Political Redistricting, Blake Splitter

All Dissertations

Political redistricting has remained a hot-button issue in the United States for several decades. Every ten years, most states need to redraw their districts to account for changing populations. Sometimes, these district plans can be drawn with the malevolent intention of aiding one political party over another. This dissertation summarizes four distinct methods of drawing these districts using computer algorithms while keeping several objectives in mind. We test these approaches on the case study state of South Carolina, since it provides a sufficiently challenging problem for us to test various algorithms. We find that many of these approaches improve upon …

Capillary Phenomena In Flow Down Fibers: Beads, Bridges, Sheets, And Threads, Chase Tyler Gabbard

All Dissertations

Capillary phenomena are ubiquitous in everyday life with surface tension responsible for shaping liquids and deforming slender structures on length scales smaller than the capillary length, as seen in the formation of drops from a leaky faucet and in the coalescence of wet hair, respectively. Recently, thin film flow down fibers have received significant attention for their ability to produce bead-on-fiber patterns with associated high surface area-to-volume ratios that optimize retention times in heat and mass transfer applications. The presence of a base flow gives rise to complex dynamics including absolute and convective instabilities. The parallelization of these processes through …

Efficient First-Order Methods For Some Smooth Nonlinear Optimization Problems, Yunheng Jiang

All Dissertations

none

Physics-Informed Machine Learning Methods For Inverse Design Of Multi-Phase Materials With Targeted Mechanical Properties, Yunpeng Wu

All Dissertations

Advances in machine learning algorithms and applications have significantly enhanced engineering inverse design capabilities. This work focuses on the machine learning-based inverse design of material microstructures with targeted linear and nonlinear mechanical properties. It involves developing and applying predictive and generative physics-informed neural networks for both 2D and 3D multiphase materials.

The first investigation aims to develop a machine learning method for the inverse design of 2D multiphase materials, particularly porous materials. We first develop machine learning methods to understand the implicit relationship between a material's microstructure and its mechanical behavior. Specifically, we use ResNet-based models to predict the elastic …

Di­Chlorido­Tetra­Kis­(3-Meth­­Oxy­Aniline)Nickel(Ii), Benjamin A. Mukda, Mark M. Turnbull

Chemistry

The reaction of nickel(II) chloride with 3-meth­oxy­aniline yielded di­chlorido­tetra­kis­(3-meth­oxy­aniline)nickel(II), [NiCl₂(C₇H₉NO)₄], as yellow crystals. The Ni^II ion is pseudo-octa­hedral with the chloride ions trans to each other. The four 3-meth­oxy­aniline ligands differ primarily due to different conformations about the Ni—N bond, which also affect the hydrogen bonding. Inter­molecular N—H⋯ Cl hydrogen bonds and short Cl⋯Cl contacts between mol­ecules link them into chains parallel to the b axis.

A Two-Part Validation Study Of The Sexual Minority Identity Emotion Scale, Henrietta Kadi Tettey-Tawiah

Graduate Theses and Dissertations

A number of existing studies indicate that there is some correlation between pride and shame and various behavioral health outcomes like anxiety, depression, and self-harm in the general population. Research also confirms that this relationship is true among sexual minorities as well. This study sets itself up to interrogate this assertion vis-à-vis sexual minority adolescents (SMAs). Consequently, confirmatory factor analysis (CFA) and differential item functioning (DIF) detection analysis were performed on the 35-item Sexual Minority Identity Emotion Scale (SMIES) for SMAs. A tree-based modeling technique, specifically conditional inference trees (CIT), was then employed to explore and make predictions about the …

Hierarchical Spatial Abundance Models For Migratory Shorebirds, Md Shahbaz Alam

Graduate Theses and Dissertations

Predicting the distribution and abundance of migratory shorebirds is crucial for effective conservation planning. This research applies hierarchical spatial models to predict counts and spatial variations of three shorebird species: Semipalmated sandpiper (sesa), Ruddy turnstone (rutu), and Whimbrel (whim). Different versions of the Poisson, Negative Binomial, and Hurdle regression models are employed to tackle specific data characteristics, such as overdispersion and excess zeros. Model comparisons are performed in terms of likelihood measures and cross-validation. The Hurdle model for sesa and rutu and the Negative Binomial model for whim effectively captured spatial patterns, highlighting potential hotspots. Mean predictive count further emphasized …

Cover-Crop Effects On Near-Surface Soil Properties Over Time In The Lower Mississippi River Valley, Cooper Fanning

Graduate Theses and Dissertations

Human population growth and climate change are present stressors that continue to put pressure on current agricultural production systems, where typical row-crop agricultural practices can negatively impact soil health. Extensive use of cover crops (CC) to increase soil health remains widely unrealized. Soil health in Arkansas is a major concern for sustaining agricultural output, therefore research into CC implementation across Arkansas to maintain or improve soil health is needed. The objective of this study was to evaluate the effects of CC (i.e., with and without CC) across various physical, hydraulic, biological, and chemical soil indicators in the Lower Mississippi River …

Bridging The Gap: Ai And The Hidden Structure Of Consciousness, Emily Barnes, James Hutson

Faculty Scholarship

The quest to develop Artificial Intelligence (AI) systems that possess human-like consciousness necessitates a deep dive into both theoretical and practical aspects underpinning this ambitious goal. This article builds on initial philosophical explorations of AI consciousness by examining the intricate and often hidden structures that may facilitate conscious experiences in AI. Drawing from concepts in cognitive science and neuroscience, the article elucidates how AI systems can be designed to replicate the structural and functional aspects of human consciousness. The discussion includes the Hierarchy of Spatial Belongings proposed by Forti (2024), frameworks like the Integrated Information Theory (IIT), and models linking …

Exploring A Multimodal Fusion-Based Deep Learning Network For Detecting Facial Palsy, Heng Yim Nicole Oo, Min Hun Lee, J. H. Lim

Research Collection School Of Computing and Information Systems

Algorithmic detection of facial palsy offers the potential to improve current practices, which usually involve labor-intensive and subjective assessment by clinicians. In this paper, we present a multimodal fusion-based deep learning model that utilizes unstructured data (i.e. an image frame with facial line segments) and structured data (i.e. features of facial expressions) to detect facial palsy. We then contribute to a study to analyze the effect of different data modalities and the benefits of a multimodal fusion-based approach using videos of 21 facial palsy patients. Our experimental results show that among various data modalities (i.e. unstructured data - RGB images …

Delta-Shaped Approximation Based Homotopy Analysis Method For Nonlinear Poisson-Type Partial Differential Equations, Cyril Ocloo

Dissertations

This research aims to solve nonlinear Poisson-type partial differential equations (PDEs) by the approach of the homotopy analysis method (HAM) incorporated with approximate particular solutions (APS) using Delta-shaped basis (DSB) approximations.

With the inclusion of the h auxiliary parameters, we tackle nonlinear problems by studying the mathematical characteristics of the h curve. This is to ensure the numerical convergence of the HAM.

In the solution process, we use the homotopy analysis method to convert a nonlinear PDE into linear inhomogeneous PDEs, which are solved using the method of approximate particular solutions with DSB.

A proper value of the h is …

Impact Of Pre-Harvest Fungicide Application On The Storage Performance Of Tomato Fruits, Zhifu Lan, Jing Huang, Komivi S. Akutse, Yongwen Lin

All Peer-Reviewed Publications

To examine the impact of pre-harvest fungicide applications on the postharvest storage performance of tomato fruits, we measured the lycopene content, hardness, soluble solids content, rotting rate, and weight loss rate of the fruits, as well as conducted a sensory assessment. Protective and systematic fungicides were sprayed on tomatoes 20 days before harvest in order to prevent rotting and weight loss during storage. Our findings showed that, the fungicide-treated tomatoes had a significantly lower rotting rate of 16.00% and a weight loss rate of 3.96%. However the control group experienced 65.33% rotting rate and 6.90% weight loss rate on 12th …

Novel Emergent Phases In A Two-Dimensional Superconductor, Simrandeep Kaur, Hemanta Kumar Kundu, Sumit Kumar, Anjana Dogra, Rajesh Narayanan, Thomas Vojta, Aveek Bid

Physics Faculty Research & Creative Works

In this letter, we report our observation of an extraordinarily rich phase diagram of a LaScO₃/SrTiO₃ heterostructure. Close to the superconducting transition temperature, the system hosts a superconducting critical point of the Infinite-randomness type characterized by an effective dynamical exponent ν z that diverges logarithmically. At lower temperatures, we find the emergence of a magnetic field-tuned metallic phase that co-exists with a quantum Griffiths phase (QGP). Our study reveals a previously unobserved phenomenon in 2D superconductors—an unanticipated suppression of the QGP below a crossover temperature in this system. This concealment is accompanied by the destruction of the …

Evidence For Rapid Variability At High Energies In Grbs, E. Casey Aldrich, Robert J. Nemiroff

Michigan Tech Publications

Intrinsic variability was searched for in arrival times of six gamma-ray bursts (GRBs) at high energies – between 30 MeV and 2 GeV – detected by the Fermi satellite’s Large Area Telescope (LAT). The GRBs were selected from the Fermi LAT catalogue with preference for events with numerous photons, a strong initial pulse, and measured redshifts. Three long GRBs and three short GRBs were selected and tested. Two different variability-detection algorithms were deployed, one counting photons in pairs, and the other multiplying time gaps between photons. In both tests, a real GRB was compared to 1000 Monte Carlo versions of …

Computation Of Moving Interface Flows In Biophysical Applications, Mohammad Murshed

Masters Theses and Doctoral Dissertations

This dissertation is concerned with the modeling, simulation, and analysis of moving interface problems involving viscous fluids and solid structures. The main computational technique employed in this work is the immersed boundary method, a widely known numerical method for fluid-structure interaction (FSI). In this technique, the fluid equations are solved in an Eulerian grid and the structure is treated as a network of Lagrangian nodes. The communication between the fluid and structure dynamics is established by the use of the Dirac delta function. Utilizing the immersed boundary method, we have studied three biophysical applications. In the first application, we computed …

Explainable Ai For Cybersecurity Automation, Intelligence And Trustworthiness In Digital Twin: Methods, Taxonomy, Challenges And Prospects, Iqbal H. Sarker, Helge Janicke, Ahmad Mohsin, Asif Gill, Leandros Maglaras

Research outputs 2022 to 2026

Digital twins (DTs) are an emerging digitalization technology with a huge impact on today's innovations in both industry and research. DTs can significantly enhance our society and quality of life through the virtualization of a real-world physical system, providing greater insights about their operations and assets, as well as enhancing their resilience through real-time monitoring and proactive maintenance. DTs also pose significant security risks, as intellectual property is encoded and more accessible, as well as their continued synchronization to their physical counterparts. The rapid proliferation and dynamism of cyber threats in today's digital environments motivate the development of automated and …

An Efficient Neutrosophic Approach For Evaluating Possible Industry 5.0 Enablers In Consumer Electronics: A Case Study, Mai Mohamed, Asmaa Elsayed, Bilal Arain, Jun Ye

Neutrosophic Systems with Applications

With the use of cutting-edge technologies like artificial intelligence (AI), robotics, and the Internet of Things (IoT), Industry 5.0 represents a breakthrough move towards a sustainable and human-centered industrial future. Industry 5.0 endeavors to transform industries such as consumer electronics by emphasizing sustainability and collaboration, in contrast to its predecessors, who only concentrated on automation and efficiency. Along with improved manufacturing efficiency and product innovation, this change in the consumer electronics sector also redefines the human-machine interaction. This paper proposes a novel hybrid integrating model that combines the Entropy Weight Method (EWM), Best-Worst Method (BWM), and an acronym in Portuguese …

Developing Catalysts For The Hydrolysis Of Glycosidic Bonds In Oligosaccharides Using A Spectrophotometric Screening Assay, Susanna Striegler

Chemistry & Biochemistry Faculty Publications and Presentations

In a proof-of-concept study, a method for the empirical design of polyacrylate gel catalysts with the ability to cleave 1→4 α-glycosidic bonds in di- and trisaccharides was elaborated. The study included the synthesis of a 300-gel member library based on two different cross-linkers and 10 acrylate monomers, identification of monomodal gels by dynamic light scattering, and a 96-well plate spectrophotometric screening assay to monitor the hydrolysis of chromophore-free maltose into glucose units. The composition of the matrix of the most efficient catalysts in the library was found to enable CH−π, hydrophobic, and H-bond accepting interactions during the hydrolysis as typically …