Physical Sciences and Mathematics Commons^™

Gray Seal (Halichoerus Grypus) Diet And Microplastic Ingestion On Great Point, Nantucket, Shannon R. Brown

Graduate Masters Theses

Due to their semi-aquatic lifestyle, pinnipeds are an ideal sentinel group used to study anthropogenic threats to the marine environment. Microplastics, primarily transported to the ocean through river discharge or weathering of larger plastics, are a threat to both pinnipeds and humans. Bioaccumulation of microplastics within the marine food web has been observed, with pinnipeds indirectly ingesting microplastics through their prey. As generalists, gray seals (Halichoerus grypus) are a pinniped species that can provide information on microplastic exposure to many lower trophic level organisms. This thesis explores the relationship between the diet and microplastic ingestion of gray seals on Great …

How Can Event Attribution Science Underpin Financial Decisions On Loss And Damage?, Dim Coumou, Paola A. Arias, Ana Bastos, Charlotte Kendra Z. Gotangco Gonzales, Gabriele C. Hegerl, Pandora Hope, Christopher Jack, Friederike Otto, Fahad Saeed, Olivia Serdeczny, Theodore G. Shepherd, Robert Vautard

Environmental Science Faculty Publications

With climate extremes hitting nations across the globe, disproportionately burdening vulnerable developing countries, the prompt operation of the Loss and Damage fund is of paramount importance. As decisions on resource disbursement at the international level, and investment strategies at the national level, loom, the climate science community’s role in providing fair and effective evidence is crucial. Attribution science can provide useful information for decision makers, but both ethical implications and deep uncertainty cannot be ignored. Considering these aspects, we articulate a vision that integrates established attribution methods and multiple lines of evidence within a coherent logical framework.

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 …

Iowa Waste Reduction Center Newsletter, August 2024, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

In this issue:

--- Join Our Team
--- Fraud Alert: New phishing scam targeting businesses
--- ICAW 2025 Poster Contest
--- STAR4D returns to the Iowa State Fair

Artificial Intelligence, Work, And The Future Of Education, Daniel Brown

Presentations

No abstract provided.

High Fat Diet & Social Isolation: Interactive Effects On Pain, Cognition, & Neuroinflammation, Ian M. Campuzano

Research Psychology Theses

Prior research has established a role for both social isolation and exposure to high fat Western diets in altering a range of behaviors from reduced memory performance to increased depression-like behaviors. The present study scrutinizes the interplay among these variables during the peri-adolescent developmental phase, utilizing Long-Evans rats as the experimental model. Our overarching hypothesis is that rats exposed to either social isolation, a high-fat diet, or both will result in heightened pain sensitivity, diminished cognitive flexibility, and increased neuroinflammatory responses within brain regions implicated in sociability, cognition, memory, and pain processing. Behavioral flexibility will be assessed using a maze-based …

An Application Of An In-Depth Advanced Statistical Analysis In Exploring The Dynamics Of Depression, Sleep Deprivation, And Self-Esteem, Muslihat Gaffari

Electronic Theses and Dissertations

Depression, intertwined with sleep deprivation and self-esteem, presents a significant challenge to mental health worldwide. The research shown in this paper employs advanced statistical methodologies to unravel the complex interactions among these factors. Through log-linear homogeneous association, multinomial logistic regression, and generalized linear models, the study scrutinizes large datasets to uncover nuanced patterns and relationships. By elucidating how depression, sleep disturbances, and self-esteem intersect, the research aims to deepen understanding of mental health phenomena. The study clarifies the relationship between these variables and explores reasons for prioritizing depression research. It evaluates how statistical models, such as log-linear, multinomial logistic regression, …

Exploring The Diagnostic Potential Of Radiomics-Based Pet Image Analysis For T-Stage Tumor Diagnosis, Victor Aderanti

Electronic Theses and Dissertations

Cancer is a leading cause of death globally, and early detection is crucial for better

outcomes. This research aims to improve Region Of Interest (ROI) segmentation

and feature extraction in medical image analysis using Radiomics techniques

with 3D Slicer, Pyradiomics, and Python. Dimension reduction methods, including

PCA, K-means, t-SNE, ISOMAP, and Hierarchical Clustering, were applied to highdimensional features to enhance interpretability and efficiency. The study assessed the ability of the reduced feature set to predict T-staging, an essential component of the TNM system for cancer diagnosis. Multinomial logistic regression models were developed and evaluated using MSE, AIC, BIC, and Deviance …

Molecule-Based Quantum Materials Under Extreme Conditions, Avery Leon Blockmon

Doctoral Dissertations

Molecule-based quantum materials are a class of compounds with competition between the spin, orbitals, charge, and lattice. They feature flexible architectures and structural designs that can be easily modified for different functionalities. As a result of their overall low energy scales, they can be easily tuned with external stimuli like magnetic field or pressure to reveal new states and properties. This dissertation presents a high magnetic field investigation of three different molecule-based quantum materials under extreme conditions revealing insights into their structural, electronic, and magnetic properties.

My initial study analyzes decoherence pathways in spin qubit Na₉[Ho(W₅O …

Extending Application Runtime Systems For Effective Data Tiering On Complex Memory Platforms, Brandon Kammerdiener

Doctoral Dissertations

Computing platforms that package multiple types of memory, each with their own performance characteristics, are quickly becoming mainstream. To operate efficiently, heterogeneous memory architectures require new data management solutions that are able to match the needs of each application with an appropriate type of memory. As the primary generators of memory usage, applications create a great deal of information that can be useful for guiding memory tiering, but the community still lacks tools to collect, organize, and leverage this information effectively. To address this gap, this work introduces a novel software framework that collects and analyzes object-level information to guide …

Enhancing Code Portability, Problem Scale, And Storage Efficiency In Exascale Applications, Nigel Tan

Doctoral Dissertations

The growing diversity of hardware and software stacks adds additional development challenges to high-performance software as we move to exascale systems. Re- engineering software for each new platform is no longer practical due to increasing heterogeneity. Hardware designers are prioritizing AI/ML features like reduced precision that increase performance but sacrifice accuracy. The growing scale of simulations and the associated checkpointing frequency exacerbate the I/O overhead and storage cost challenges already present in petascale systems. Moving forward, the community must address performance portability, precision optimization, and data deduplication challenges to ensure that exascale applications efficiently deliver scientific discovery. In this dissertation, …

Dispersive Shock Waves In A One-Dimensional Droplet-Bearing Environment, Sathyanarayanan Chandramouli, S. I. Mistakidis, G. C. Katsimiga, P. G. Kevrekidis

Physics Faculty Research & Creative Works

We demonstrate the controllable generation of distinct types of dispersive shock waves emerging in a quantum droplet bearing environment with the aid of steplike initial conditions. Dispersive regularization of the ensuing hydrodynamic singularities occurs due to the competition between mean-field repulsion and attractive quantum fluctuations. This interplay delineates the dominance of defocusing (hyperbolic) and focusing (elliptic) hydrodynamic phenomena being designated by the real and the imaginary speed of sound, respectively. Specifically, the symmetries of the extended Gross-Pitaevskii model led to a three-parameter family, encompassing two densities and a relative velocity of the underlying Riemann problem utilized herein. Surprisingly, dispersive shock …

Artificial Intelligence And Administrative Justice: An Analysis Of Predictive Justice In France, Zouhaier Nouri, Walid Ben Salah, Nayel Al Omrane

All Works

This article critically analyzes the ethical and legal implications of adopting predictive analytics by the French administrative justice system. It raises a key question: Is it wise to integrate artificial intelligence into the administrative justice system, considering its potential benefits, despite the associated risks, ethical dilemmas, and legal challenges? The research employs a method based on an extensive literature review, a qualitative analysis of the adoption by the French administrative justice of predictive analytics tools, and a critical evaluation of the benefits and issues these tools bring. The study finds that AI can make the administrative justice system more efficient, …

Making Sandwiches: A Novel Invariant In D-Module Theory, David Lieberman

Department of Mathematics: Dissertations, Theses, and Student Research

Say I hand you a shape, any shape. It could be a line, it could be a crinkled sheet, it could even be a the intersection of a cone with a 6-dimensional hypersurface embedded in a 7-dimensional space. Your job is to tell me about the pointy bits. This task is easier when you can draw the shape; you can you just point at them. When things get more complicated, we need a bigger hammer.

In a sense, that “bigger hammer” is what the ring of differential operators is to an algebraist. Then we will say some things and stuff …

A Study On The Vanishing Of Ext, Andrew J. Soto Levins

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

This thesis has two goals. The first is to study an Ext analog of the rigidity of Tor, and the second is to study Auslander bounds.

In Chapter 2 we show that if R is an unramified hypersurface, if M and N are finitely generated R-modules, and if the nth Ext modules of M against N is zero for some n less than or equal to the grade of M, then the ith Ext module of M against N is zero for all i less than or equal to n. A corollary of this says that if …

Spreads And Transversals And Their Connection To Geproci Sets, Allison Joan Ganger

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

Spreads of [set of prime numbers]³ over finite fields can yield geproci sets. We study the existence of transversals to such spreads, proving that spreads with two transversals exist for all finite fields, before further considering the groupoids coming from spreads when transversals do or do not exist. This is further considered for spreads of higher dimensional projective spaces. We also consider how certain spreads might generalize to characteristic zero and the connection to the previously known geproci sets coming from the root systems D₄ and F₄.

Advisor: Brian Harbourne

On Regularity Of Graph C*-Algebras, Gregory Joseph Faurot

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

We prove that for any countable directed graph E with Condition (K), the corresponding graph C*-algebra C*(E) has nuclear dimension at most two. We also prove that the nuclear dimension of certain extensions is at most one, which can be applied to certain graphs to achieve the optimal upper bound of one. Finally, we generalize some previous results for O_∞ -stability of graph algebras, and prove some partial results for Z-stability.

Advisor: Christopher Schafhauser

Transforming Grassland Conservation: Challenges And Opportunities Across Law, Policy, And Human Dimensions, Conor D. Barnes

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

Great Plains social-ecological systems are facing growing pressure from complex, ‘wicked’ problems. Addressing these problems will require integrating ecological resilience and complex systems thinking concepts into our legal framework in order to better reflect the changing ecological reality of the Great Plains and promote flexibility and adaptability in the face of that change. In this dissertation, I examine how past and present policy priorities have affected social-ecological systems on the Great Plains, and how ecological resilience and complex systems thinking might be applied to grassland management policy. In Chapter 2, I examine the rapid progress made in the adoption of …

Gevrey Class Estimates Towards Null Controllability Of A Fluid Structure Interaction System, Dylan Mcknight

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

Fluid-Structure Interaction concerns the interaction of parabolic fluids and hyperbolic elastic structures via numerous mechanisms such as boundary coupling and pressure. These models find application in blood flow, fluid flow in the eye, and air flow over plane wings. Parabolic equations are well known for “infinite speed of propagation,” which manifests itself via a uniform bound on the resolvent of the infinitesimal generator of the associated strongly continuous semigroup. Qualitatively, a solution of a parabolic pde with rough initial data is immediately smooth for any positive time. A priori, it is not clear whether a fluid structure interaction inherits any …

Phylogenetic And Biogeographic Patterns Of Devonian Proetid Trilobites, Katherine Jane Jordan

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

Ecological disruption events such as mass extinctions can result in the permanent alteration in clades and ecosystems. A pivotal time of change during the history of life on Earth can be seen in the Devonian Period. During this time, major transitions in marine and terrestrial system resulted in a different world at the end of the period in comparison to the beginning. One such group most heavily impacted were trilobites. Trilobites were reduced to one order by the end of the Devonian: Proetida. My dissertation focuses on phylogenetic, biogeographic, and paleocommunity patterns of this group, known as the last of …

A Data-Driven Discovery System For Studying Extracellular Microrna Sorting And Rna-Protein Interactions, Sasan Azizian

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

Interactions between microRNAs (miRNAs) and RNA-binding proteins (RBPs) are pivotal in miRNA-mediated sorting, yet the molecular mechanisms underlying these interactions remain largely understudied. Few miRNA-binding proteins have been verified, typically requiring extensive laboratory work. This study introduces DeepMiRBP, a novel hybrid deep learning model designed to predict microRNA-binding proteins. The model integrates Bidirectional Long Short-Term Memory (Bi-LSTM) networks with attention mechanisms, transfer learning, and cosine similarity to offer a robust computational approach for inferring miRNA-protein interactions.

DeepMiRBP is implemented through two distinct architectures. The first architecture employs a Y-shaped model that uses Bi-LSTM networks and transfer learning to extract contextual …

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

Dissertations and Doctoral Documents from 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 …

Applications Of Artificial Intelligence On Drought Impact Monitoring And Assessment, Beichen Zhang

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

Drought, a prevalent and consequential natural disaster, poses widespread, indirect challenges across environmental and societal dimensions. Despite considerable focus on monitoring meteorological and hydrological drought and studying their characteristics, there is a gap in assessing its multifaceted impacts, especially on societal sectors. The dissertation comprises three research essays utilizing artificial intelligence to quantitatively study multi-dimensional drought impacts. The first essay leveraged deep learning and natural language processing to predict multi-dimensional drought impacts from textual datasets, including social media, news media, and citizen scientist reports. The findings demonstrate superior performance over traditional methods and unveil the spatial and temporal heterogeneity of …

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 …