Physical Sciences and Mathematics Commons^™

The Mechanical Strength Of Sedimentary Rocks At Meridiani Planum, Mars, Tyler J. Seyglinski

Masters Theses

The physical properties of rocks such as their strength, hardness, and density can help inform our understanding of the formation and modification history of rock units. For sedimentary rocks, their strength is inherently linked to factors such as porosity and degree of induration, which are in turn controlled by factors such as burial depth and water-rock interaction. On Earth, rock strength is typically assessed as unconfined compressive strength (UCS) and can be measured directly or inferred via indirect strength tests (e.g., the Schmidt hammer test). On Mars, instruments such as the Rock Abrasion Tool (RAT) onboard the Opportunity rover can …

Using Digitized Building And Weather Records To Improve The Accuracy Of Ground To Roof Snow Load Ratio Estimations, Gideon Parry

All Graduate Theses and Dissertations, Fall 2023 to Present

Reliability target loads refer to the amount of accumulated snow a roof needs to be able to support to ensure that the probability of collapse is sufficiently low. Since ground snow weight, or load, is much easier to measure than roof snow load, models for roof snow loads rely on ground snow load measurements along with a statistical model that estimates roof snow retention as a ratio of the measured ground snow load. This thesis focuses on improving the roof snow retention model using data from Canadian case studies that include information about building geometry and local wind speeds. This …

Integration Of Matlab And Machine Learning To Accelerate Evaluation Of Biological Activity In Agricultural Soils And Promote Soil Health Improvement Goals, Andrew Stiven Ortiz Balsero

Department of Biological Systems Engineering: Dissertations and Theses

Traditionally, assessments of soil biological activity have been confined to laboratory settings, creating a disconnect with practical in-field methods. To bridge this gap, cotton fabric degradation has been used to illustrate soil microbial activity under different management practices. While effective, these demonstrations are subjective and labor-intensive.

Researchers have explored using image processing software like ImageJ and Adobe Photoshop to streamline this process. Although these tools accurately quantified fabric degradation under varying soil conditions, the methods remained labor-intensive and complex. Consequently, these methods were still not ideal for on-farm use by agricultural practitioners.

To further address labor and complexity limitations, the …

Leveraging Generative Ai For Sustainable Farm Management Techniques Correspond To Optimization And Agricultural Efficiency Prediction, Samira Samrose

All Graduate Reports and Creative Projects, Fall 2023 to Present

Sustainable farm management practice is a multifaceted challenge. Uncovering the optimal state for production while reduction of environmental negative impacts and guaranteed inter-generational assets supervision needs balanced management. Also, considering lots of different factors (cost, profit, employment etc), the agricultural based management technique requires rigorous concentration. In this project machine learning models are applied to develop, achieve and improve the farm management techniques. This experiment ensures the resultant impacts being environment friendly and necessary resource availability and efficiency. Predicting the type of crop and rotational recommendations will disclose potentiality of productive agricultural based farming. Additionally, this project is designed to …

The Nature Of X-Rays From Young Stellar Objects In The Orion Nebula Cluster—A Chandra Hetgs Legacy Project, Norbert S. Schulz, David P. Huenemoerder, David A. Principe, Marc Gagné, Hans Mortiz Günther, Joel Kastner, Joy Nichols, Andrew Pollock, Thomas Preibisch, Paola Testa, Fabio Reale, Fabio Favata, Claude R. Canizares

Earth & Space Sciences Faculty Publications

The Orion Nebula Cluster (ONC) is the closest site of very young (∼1 Myr) massive star formation The ONC hosts more than 1600 young and X-ray bright stars with masses ranging from ∼0.1–35 Me. The Chandra HETGS Orion Legacy Project observed the ONC with the Chandra High Energy Transmission Grating Spectrometer (HETGS) for 2.1 Ms. We describe the spectral extraction and cleaning processes necessary to separate overlapping spectra. We obtained 36 high-resolution spectra, which include a high-brilliance X-ray spectrum of θ1 Ori C with over 100 highly significant X-ray lines. The lines show Doppler broadening between 300 and 400 km …

Predicting Personality Or Prejudice? Facial Inference In The Age Of Artificial Intelligence, Shilpa Madan, Gayoung Park

Research Collection Lee Kong Chian School Of Business

Facial inference, a cornerstone of person perception, has traditionally been studied through human judgments about personality traits and abilities based on people's faces. Recent advances in artificial intelligence (AI) have introduced new dimensions to this field, employing machine learning algorithms to reveal people's character, capabilities, and social outcomes based just on their faces. This review examines recent research on human and AI-based facial inference across psychology, business, computer science, legal, and policy studies to highlight the need for scientific consensus on whether or not people's faces can reveal their inner traits, and urges researchers to address the critical concerns …

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 …

3d-Magnetometer Arrays In Physics Experiments, Shaun G. Vavra

Masters Theses

This study presents the design and experimental evaluation of a magnetometer array utilizing LIS3MDL chips integrated with an Arduino microcontroller. Magnetometer arrays find crucial applications in various fields, including physics research, geophysics, and navigation systems. The goal of this research is to create an affordable and versatile magnetometer array for scientific investigations and practical applications. The paper begins by outlining the hardware and software components of the array. The LIS3MDL chips, known for their high sensitivity and low power consumption, are employed as the core sensing elements. The Arduino microcontroller is utilized for data acquisition and processing. The integration of …

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 …

Assessing Gtfs Accuracy, Gregory L. Newmark

Mineta Transportation Institute

The promised benefits of the General Transit Feed Specification (GTFS) Schedule and Realtime standards are dependent on the underlying quality of the data. Despite this fundamental reliance, there has been relatively little research on techniques and strategies to assess GTFS accuracy. The need for such assessment is growing as federal and state governments increasingly require transit agencies to make these data available to the public. This research fills this gap by presenting a suite of methods and metrics to assess the temporal accuracy of GTFS Realtime and the spatial accuracy of GTFS Schedule feeds. The temporal assessment demonstrates an approach …

Materials Data Science Ontology (Mds-Onto): Unifying Domain Knowledge In Materials And Applied Data Science, Van D. Tran, Jonathan E. Gordon, Alexander Harding Bradley, Balashanmuga Priyan Rajamohan, Quynh D. Tran, Gabriel Ponón, Yinghui Wu, Laura S. Bruckman, Erika I. Barcelos, Roger H. French

Student Scholarship

Ontologies have gained popularity in the scientific community as a means of standardizing concepts and terminology used in metadata across different institutions to facilitate data comprehension, sharing, and reuse. Despite the existence of frameworks and guidelines for building ontologies, the processes and standards used to develop ontologies still differ significantly, particularly in Materials Science. Our goal with the MDS-Onto Framework is to provide a unified and automated system for ontology development in the Materials and Data Sciences. This framework offers recommendations on where to publish ontologies online, how to best integrate them within the semantic web, and which formats to …

Enhancing Monthly Streamflow Prediction Using Meteorological Factors And Machine Learning Models In The Upper Colorado River Basin, Saichand Thota

All Graduate Theses and Dissertations, Fall 2023 to Present

Understanding and predicting streamflow along river basins is vital for planning future developments and ensuring safety, especially with climate change challenges. Our study focused on forecasting streamflow at Lees Ferry, a key location along the Colorado River in the Upper Colorado River Basin. We employed four machine learning models - Random Forest Regression, Long short-term memory, Gated Recurrent Unit, and Seasonal Auto-Regressive Integrated Moving Average; and combined historical streamflow data with meteorological factors such as snow water equivalent, temperature, and precipitation. Our analysis spanned 30 years of data from 1991 to 2020.

Our findings revealed that the Random Forest Regression …

Md Simulations Of Collision Effects For A Strongly Coupled Plasma, Jawon Jo

All Graduate Theses and Dissertations, Fall 2023 to Present

Studying strongly coupled plasmas can be effectively accomplished using molecular dynamics (MD) simulations. We have developed an advanced MD simulation code that can analyze plasmas with various coupling parameters. This code employs a spherically symmetric cut-off Coulomb force verified through convergence tests by modulating the cut-off and minimum force ranges. Additionally, it incorporates a new algorithm for optimizing the initial positions of particles at a given temperature. This method maintains the temperature constant and the velocity distribution unchanged. As a result, we eliminate the unphysical initial rises and oscillations in temperature that a random distribution of positions causes. The code …

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 …