Physical Sciences and Mathematics Commons^™

Search For Physics Beyond The Standard Model In Top Quark Production With Additional Leptons In The Context Of Effective Field Theory, Furong Yan

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

The dissertation presents a search for new physics impacting top quark productions within the framework of effective field theory (EFT). Potential new physics effects are parameterized in terms of 26 dimension-six EFT operators into the event yields of six distinct top production processes in the detector level. The analysis targets multilepton final states consisting of two leptons of the same charge, three leptons and four leptons. The events are further categorized and binned in terms of kinematic distributions in order to gain sensitivity to the new physics effects. A likelihood function is formulated based on the predicted distribution in each …

Semigroup Well-Posedness And Finite Element Analysis Of A Biot-Stokes Interactive System, Sara Mcknight

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

The coupling of a porous medium modeled by the Biot equations and a fluid has many biological applications. There are numerous ways by which to model the fluid and to couple the porous medium with the fluid. This particular model couples the Biot equations to Stokes flow along the boundary, through the Beavers-Joseph-Saffman conditions. We address semigroup well-posedness of the system via an inf-sup approach, which along the way requires consideration of a related but uncoupled static Biot system. We also present the results of finite element analysis on both the uncoupled Biot system and the coupled system.

Advisor: Sara …

Perturbations Of Representations Of Cartan Inclusions, Catherine Zimmitti

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

A free semigroup algebra is the unital, weak operator topology closed algebra generated by a collection of Cuntz-Toeplitz isometries in B(H). Ken Davidson and David Pitts asked in [9] if a self-adjoint free semigroup algebra exists; Charles Read answered this question in [28] by constructing such an example, which Ken Davidson later simplified in [8]. The construction takes a standard representation of O₂ and multiplies it by a unitary operator in the diagonal MASA of the representation. This results in a new "perturbed" representation of O₂ generating a self-adjoint free semigroup algebra.

In this thesis, …

Further Developing Drought Early Warning Information Systems Using Mixed-Methods And Multiple Streams Of Data, Caily Claire Schwartz

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

Drought is a complex phenomenon with varying degrees of impacts and monitoring methods. No drought is alike, creating a challenge for both water managers and communities. No area is immune to a drought. Due to the cyclical nature of drought events, clear information to those impacted is necessary to reduce risk and move towards proactive responses, as opposed to reactive responses. To better provide communication and mitigation tools, Drought Early Warning Information Systems (DEWIS) have been developed in various regions and contexts. To improve early warning, an understanding of the end user’s perceptions of risk, and the applicability of data …

Integrating Water And Nitrogen Management For Sustainable Agriculture: Optimizing Resource Use Efficiency And Maximizing Crop Productivity, Jiaming Duan

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

Advisors: Derek Heeren and Daran Rudnick Maize, accounting for over 95% of national grain production in the United States, is highly sensitive to water and nitrogen (N) inputs. Conventional agricultural practices often lead to excessive application, causing groundwater contamination through nitrate leaching. Therefore, there is a demand for integrating water and nitrogen management with innovative scheduling methods for sustainable agricultural development.

This dissertation first reviewed two decades of U.S.-based research, highlighting the optimal management of water and N to enhance yield, water use efficiency (WUE), and nitrogen use efficiency (NUE). Findings indicate that maintaining optimal levels of N and water …

Long Term Ultrasonic Monitoring And Machine Learning Investigation Of Micro-Crack Damaged Concrete, Yalei Tang

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

The thermal modulation method is a recently developed nonlinear ultrasonic technique for evaluating material damage. This method utilizes thermal strain changes resulting from temperature variations to excite the nonlinear behavior of materials and modulate high-frequency ultrasonic waves within them. Its working principle suggests significant potential for application in large-scale concrete structures and in-situ monitoring of real structures. Despite numerous laboratory demonstrations of its effectiveness, several gaps remain before it can be applied to in-service large concrete structures.

This study investigates the potential of the thermal modulation technique for evaluating concrete structures in ambient conditions, addressing key uncertainties for practical implementation. …

Development Of Feature Extraction Models To Improve Image Analysis Applications In Cancer, Yu Shi

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

Cancer poses a significant global health challenge. With an estimated 20 million new cases diagnosed worldwide in 2022 and 9.7 million fatalities attributable to the disease, the economic burden of cancer is immense. It impacts healthcare systems and imposes substantial costs for its care on patients and their families. Despite advancements in early detection, prevention, and treatment that have reduced overall cancer mortality rates, the growing prevalence of cancer, particularly among younger individuals, remains a pressing issue.

Recent advancements in medical imaging technology have progressed significantly with the help of emerging computer vision and artificial intelligence (AI) technology. Despite these …

Optimizing Scalability For Formal Analysis With Evolutionary Algorithm, Jianghao Wang

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

Predominantly employed to tackle hardware validation challenges in the early years, formal methods have since expanded to software engineering, introducing a significant level of rigor and precision to software analysis. Its use of mathematical notations and logical reasoning allows for abstract modeling of programs, enabling researchers and engineers to perform a multitude of analysis tasks to verify system dependability and rigorously prove the correctness of system properties. Despite the availability of many automated analysis tools including those considered lightweight, the practical adoption of formal methods in software development has been limited due to scalability concerns, especially when applied to large …

Virtual Unknotting Numbers For Families Of Virtual Torus Knots, Kaitlin R. Tademy

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

A virtual torus knot T(p,q,VC) sits in the intersection of the well-understood torus knot and the not-so-well-understood virtual knot, making it an intriguing object to study.

The unknotting number of a classical knot K is defined unambiguously. However, "the" unknotting number when K is a virtual knot is not as clear to define, since virtual knots have both classical and virtual crossings. We will define virtual unknotting number vu(K) as the minimum number of (classical) crossing changes required to unknot K. Under this definition of virtual unknotting, not all …

Transformer-Based Deep Learning Prediction Of 10-Degree Humphrey Visual Field Tests From 24-Degree Data, Min Shi, Anagha Lokhande, Yu Tian, Yan Luo, Mohammad Eslami, Saber Kazeminasab, Tobias Elze, Lucy Shen, Louis Pasquale, Sarah Wellik, Carlos Gustavo De Moraes, Jonathan Myers, Nazlee Zebardast, David Friedman, Michael Boland, Mengyu Wang

Wills Eye Hospital Papers

PURPOSE: To predict 10-2 Humphrey visual fields (VFs) from 24-2 VFs and associated non-total deviation features using deep learning.

METHODS: We included 5189 reliable 24-2 and 10-2 VF pairs from 2236 patients, and 28,409 reliable pairs of macular OCT scans and 24-2 VF from 19,527 eyes of 11,560 patients. We developed a transformer-based deep learning model using 52 total deviation values and nine VF test features to predict 68 10-2 total deviation values. The mean absolute error, root mean square error, and the R2 were evaluation metrics. We further evaluated whether the predicted 10-2 VFs can improve the structure-function relationship …

Neural-Network-Based Detection Of Radiopharmaceutical Extravasation In Pet/Ct Data, Elijah D. Berberette

Masters Theses

The immediate identification of PET/CT radiopharmaceutical extravasation can eliminate many adverse effects such as misdiagnosis and improper therapy. Radiopharmaceutical extravasation is the leakage of an injected radiotracer from the patient’s intended vein into surrounding tissues. The detection of this phenomenon often requires the use of an external monitoring device; due to a lack of robust visual features that can provide indication that it has occurred. In this thesis, the feasibility of using neural networks trained on PET/CT data to identify extravasation is explored. This approach begins with a novel preprocessing methodology that automatically extracts body weight normalized standard uptake values …

An Llm-Assisted Easy-To-Trigger Poisoning Attack On Code Completion Models: Injecting Disguised Vulnerabilities Against Strong Detection, Shenao Yan, Shen Wang, Yue Duan, Hanbin Hong, Kiho Lee, Doowon Kim, Yuan Hong

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have transformed code completion tasks, providing context-based suggestions to boost developer productivity in software engineering. As users often fine-tune these models for specific applications, poisoning and backdoor attacks can covertly alter the model outputs. To address this critical security challenge, we introduce CODEBREAKER, a pioneering LLM-assisted backdoor attack framework on code completion models. Unlike recent attacks that embed malicious payloads in detectable or irrelevant sections of the code (e.g., comments), CODEBREAKER leverages LLMs (e.g., GPT-4) for sophisticated payload transformation (without affecting functionalities), ensuring that both the poisoned data for fine-tuning and generated code can evade strong …

Self-Chats From Large Language Models Make Small Emotional Support Chatbot Better, Zhonghua Zheng, Lizi Liao, Yang Deng, Libo Qin, Liqiang Nie

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have shown strong generalization abilities to excel in various tasks, including emotion support conversations. However, deploying such LLMs like GPT-3 (175B parameters) is resource-intensive and challenging at scale. In this study, we utilize LLMs as “Counseling Teacher” to enhance smaller models’ emotion support response abilities, significantly reducing the necessity of scaling up model size. To this end, we first introduce an iterative expansion framework, aiming to prompt the large teacher model to curate an expansive emotion support dialogue dataset. This curated dataset, termed ExTES, encompasses a broad spectrum of scenarios and is crafted with meticulous strategies …

Mesenchymal Stem Cells In Autoimmune Disease: A Systematic Review And Meta-Analysis Of Pre-Clinical Studies, Hailey N. Swain, Parker D. Boyce, Bradley A. Bromet, Kaiden Barozinksy, Lacy Hance, Dakota Shields, Gayla R. Olbricht, Julie A. Semon

Mathematics and Statistics Faculty Research & Creative Works

Mesenchymal Stem Cells (MSCs) Are of Interest in the Clinic Because of their Immunomodulation Capabilities, Capacity to Act Upstream of Inflammation, and Ability to Sense Metabolic Environments. in Standard Physiologic Conditions, They Play a Role in Maintaining the Homeostasis of Tissues and Organs; However, there is Evidence that They Can Contribute to Some Autoimmune Diseases. Gaining a Deeper Understanding of the Factors that Transition MSCs from their Physiological Function to a Pathological Role in their Native Environment, and Elucidating Mechanisms that Reduce their Therapeutic Relevance in Regenerative Medicine, is Essential. We Conducted a Systematic Review and Meta-Analysis of Human MSCs …

Incorporating Ai-Assisted Sensing Into The Metaverse: Opportunities For Interactions, Esports, And Security Enhancement, Yi Wu

Doctoral Dissertations

With the rapid growth and development of Virtual Reality (VR) and Augmented Reality (AR), extensive research has been carried out in the domain of the Metaverse, including immersive gaming, human-computer interaction, eSports, and the associated security & privacy concerns.

My research explores the potential of incorporating Artificial Intelligence (AI)-assisted sensing technologies to facilitate a more immersive, convenient, authentic, and secure virtual experience. This dissertation mainly focus on the following topics: (1) how to perform facial expression tracking to improve the users' awareness in the Metaverse; (2) fitness tracking for immersive eCycling; (3) running gait analysis for immersive indoor running, and …

Multiscale Modeling Of Morphology And Proton/Ion Transport In Electrolytes, Zhenghao Zhu

Doctoral Dissertations

Understanding structure-function relationships in electrolytes is essential for advancing energy conversion and storage. This dissertation employs multiscale modeling and simulations to study the morphology and proton/ion transport in various electrolytes for electrochemical systems, including anion exchange membranes (AEMs), protic ionic liquids (PILs), pure phosphoric acid (PA) and aqueous acid solutions, ionic liquids (ILs), and polymerized ionic liquids (polyILs).

Mesoscale dissipative particle dynamics (DPD) simulations were employed to study the hydrated morphology of polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (SEBS)-based AEMs. The results indicate that the choice of the functional group moderately affects the water distribution and has little influence on the …

Investigation Of Molecular Transition Metal Complexes: Structures, Magnetic Properties, And Reactivities, Adam T. Hand

Doctoral Dissertations

The dissertation describes the work on transition metal complexes to determine their structures, magnetic properties, and reactivities. Molecular magnetic complexes containing one cobalt(II) or rhenium(IV) ion have been studied to obtain their characteristic zero-field splittings and spin-phonon couplings by magnetometry and advanced spectroscopies. The investigation of spin relaxation and phonon features gives insight into potential magnetic relaxation mechanisms. Studies by ligand field theory, including ab initio ligand-field analysis, show how coordination environments of the metal centers affect the magnetic properties. Through the analyses, the impact of the coordination geometry/symmetry on the zero-field splittings can be explained. Such understanding of magneto-structural …

Codont5: A Multi-Task Codon Language Model For Species-To-Species Translation, Ashley N. Babjac

Doctoral Dissertations

DNA (DeoxyriboNucleic Acid) carries the genetic information for the biological processes and function of all organisms. It is composed of nucleotides, which can be grouped into 3-mer triplets called codons. It is well known that codons encoding the same amino acid, referred to as "synonymous" codons, are selected with differing frequencies between organisms. Prior research has revealed there are codons used with much higher frequency than others, causing to them being "preferred" in highly expressed genes. This has led to the development of multiple computational models that do a good job predicting gene expression in some protein-coding genes; however, their …

Understanding Traits To Support Crowdworkers' Flexibility, Senjuti Dutta

Doctoral Dissertations

Crowdworkers are drawn to the profession in part due to the flexibility it affords. However, the current design of crowdsourcing platforms limits this flexibility. Therefore, it is important to support the overall flexibility of crowdworkers. Incorporating a variety of device types in the workflow plays an important role in supporting the flexibility of crowdworkers, however each device type requires a tailored workflow. The standard workflow of crowdworkers consists of stages of work such as managing and completing tasks. I hypothesize that different devices will have unique traits for task completion and task management. Therefore in this dissertation, I explore what …

Enabling Reproducibility, Scalability, And Orchestration Of Scientific Workflows In Hpc And Cloud-Converged Infrastructure, Paula Fernanda Olaya

Doctoral Dissertations

Scientific communities across different domains increasingly run complex workflows for their scientific discovery. Scientists require that these workflows ensure robustness; where workflows must be reproducible, scale in performance; and exhibit trustworthiness in terms of the computational techniques, infrastructures, and people. However, as scientists leverage advanced techniques (big data analytics, AI, and ML) and infrastructure (HPC and cloud), their workflows grow in complexity, leading to new challenges in scientific computing; hindering robustness.

In this dissertation, we address the needs of diverse scientific communities across different fields to identify three main challenges that hinder the robustness of workflows: (i) lack of traceability, …

General Relativistic Gravity In Core-Collapse Supernova Simulations, James Nicholas Roberts Ii

Doctoral Dissertations

Core-collapse supernovae (CCSNe) are some of the most extreme and complex phenomena in the universe. The toolkit for high-order neutrino-radiation hydrodynamics (thornado) is being developed to simulate CCSNe which will provide insight into the mechanisms underlying these events. The thornado framework is a collection of modules used to calculate the effects of gravity, hydrodynamics, neutrino transport, and nuclear physics through the Weaklib equation of state table. This dissertation will present the development of the Poseidon code, which provides the general relativistic gravity solver for the thornado framework.

The Poseidon code solves for the general relativistic metric using the xCFC formulation …

Evaluating The Effects Of Forage Availability And Landscape Composiiton On Whte-Tailed Deer Morphometrics Across The Eastern U.S., Mark Turner

Doctoral Dissertations

White-tailed deer (Odocoileus virginianus) management often focuses on improving nutrition to increase deer morphometrics, and many landowners use harvest data to track management progress. Better understanding the relationship among deer morphology, nutrition, landscape characteristics, and climate should inform deer management throughout much of the eastern US. I collected deer forage data in 2021–2023 from 43 sites in 25 states across the eastern US and worked with cooperating landowners and managers to collect harvest data from 35 of those sites. Adult female body mass explained 64% of the variation in mature male antler size on sites across the eastern …

Method Development For The Quantification Of Critically Valuable Elements In Permian Basin Produced Waters, Carley Oliver

Open Access Theses & Dissertations

Produced waters (PW) are a major byproduct of the oil and gas industrial hydraulic fracturing processes that create a major waste disposal issue with a need for disposal, treatment, and reuse method developments. The current primary disposal method is subsurface injection, which can lead to high pressures in the subsurface. PWs are often highly saline from mineral leaching due to long residence in subsurface reservoirs. According to the USGS National Minerals Information Center, bromine, calcium chloride, iodine, lithium, magnesium, and sodium chloride have been found in and extracted from these domestic subsurface brines, suggesting that there may be other economically …

Investigation Of Seasonal Trends And Source Apportionment Of Particulate Matter (Pm2.5) In El Paso-Juarez Airshed, Fatema Tuz Zohora

Open Access Theses & Dissertations

Using the data from Texas Commission on Environmental Quality (TCEQ) for the El Paso city throughout the years from 2021 to 2024 Particulate Matter (PM2.5) was measured to examine the seasonal distribution and sources. This study aims to understand the seasonal variability of PM2.5 concentrations, identify the significant impact of wildfire events on this and source apportionment.The analysis begins with a comprehensive examination of PM2.5 data from TCEQ highlighting the seasonal pattern, it was found that fine particulate matter was more prevalent in winter and tends to be down in spring, and in summer it is relatively lower, subsequently in …

Developing Educational Tools For Sustainable Stormwater Management, Lauren Houskeeper

All Graduate Reports and Creative Projects, Fall 2023 to Present

Rapid population growth and development in Western states are exerting strain on the region’s limited water resources. Urbanization exacerbates this issue by increasing impervious surfaces, limiting infiltration of precipitation during storm events and snowmelt, which results in changes to hydrologic conditions with higher runoff volumes and higher peak flows. Stormwater transports pollutants as it flows across impervious surfaces, discharging high volumes of runoff and elevated loads of urban contaminants into receiving waters. The amount of pollution entering waterways continually increases as urban areas expand. Utah is currently experiencing a rapid transition from undeveloped to developed landscapes, necessitating the implementation of …

2024 August - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

Data Collector Selection Ranking-Based Method For Collaborative Multi-Tasks In Ubiquitous Environments, Belal Z. Hassan, Ahmed. A. A. Gad-Elrab, Mohamed S. Farag, S. E. Abu-Youssef

Al-Azhar Bulletin of Science

In Ubiquitous Computing and the Internet of Things, the sensing and control of objects involve numerous devices collecting and transmitting data. However, connecting these devices without fostering collaboration leads to suboptimal system performance. As the number of connected sensing devices in Internet of Things increases, efficient task accomplishment through collaboration becomes imperative. This paper proposes a Data Collector Selection Method for Collaborative Multi-Tasks to address this challenge, considering task preferences and uncertainty in data collectors' contributions. The proposed method incorporates three key aspects: (1) Using Fuzzy Analytical Hierarchy Process to determine optimal weights for task preferences; (2) Ranking data collectors …

Geomechanical Study Of Rock Properties In The Kafr El-Sheikh Formation At Sapphire Field, West Delta Deep Marine, Egypt, Moustafa Mohamed Ahmed Attia, Ali El-Sayed Farag, Mahmoud Y. Zein El-Din

Al-Azhar Bulletin of Science

Numerous challenges were encountered during the drilling operations conducted at the Sapphire oilfield. Instances of stuck pipe, wellbore instability, breakouts, and washouts have been documented in many wells within this field, resulting in unproductive time and additional expenditures. To mitigate these challenges, it is important to conduct a one-dimensional geomechanical model to get a viable resolution. This entails the creation of three primary in situ stress profiles and the assessment of mechanical characteristics of the geological formations. The primary focus of this investigation was to ascertain the mechanical characteristics of the rock. Therefore, this work offers great input while building …

Data Driven Acceleration Of Coupled-Cluster Calculations Using Machine Learning, Multitask Learning And Physics Imposed Learning, Perera Don Varuna Sanjaya Pathirage

Doctoral Dissertations

Data-driven coupled-cluster singles and doubles (DDCCSD) method developed by Townsend and Vogiatzis aims at predicting the coupled-cluster t₂ amplitudes using MP2-level electronic structure data with machine learning. In this work we address limitations of the DDCCSD method to expand the applicability and increase the accuracy. First, we implement localized molecular orbitals (LMO) to the DDCCSD method. There is a ten-fold increase in accuracy when the LMO implementation is used compared to the canonical molecular orbital implementation. Next, we introduced five data selection techniques to select data for testing and training. Here we were able to achieve accuracies less than …

A Uniformly Most Powerful Test For The Mean Of A Beta Distribution, Richard Ntiamoah Kyei

Electronic Theses and Dissertations

The beta distribution is used in numerous real-world applications, including areas such as manufacturing (quality control) and analyzing patient outcomes in health care. It also plays a key role in statistical theory, including multivariate analysis of variance (MANOVA) and Bayesian statistics. It is a flexible distribution that can account for many different characteristics of real data. To our surprise, there has been very little work or discussion on performing statistical hypothesis testing for the mean when it is reasonable to assume that the population is beta distributed. Many analysts conduct traditional analyses using a t-test or nonparametric approach, try transformations, …