Physical Sciences and Mathematics Commons^™

Parameter Characteristics And Rock-Breaking Mechanisms Of Horizontal Drilling Of Underground Collapsed Bodies In Coal Mines, Yao Ningping, Dou Xuqian, Han Zhaoyang, Zhang Guohua, Sun Yuchen, Li Hao, Wang Li

Coal Geology & Exploration

Objective With continuously increasing coal mining depth, the risks of hazards such as roof collapse and personnel entrapment caused by high in situ stress and mining-induced pressure have significantly intensified. Drilling emerges as a key means of rapidly establishing rescue passageways. However, the drilling process tends to face multiple challenges, including complex geological structures, unstable collapsed bodies, and low drilling efficiency. Methods This study aims to reveal the rock-breaking mechanisms during the drilling of collapsed bodies, optimize drilling parameters to ensure reliable borehole formation, and achieve efficient drilling of collapsed bodies. To this end, this study developed a large-scale experimental …

Spatially Resolved Kinematics Of Slacs Lens Galaxies. I. Data And Kinematic Classification, Shawn Knabel, Tommaso Treu, Michele Cappellari, Anowar J. Shajib, Chih-Fan Chen, Simon Birrer, Vardha N. Bennert

Physics

We obtain spatially resolved kinematics with the Keck Cosmic Web Imager (KCWI) integral-field spectrograph for a sample of 14 massive (11 < log₁₀(M₍★₎/M☉) < 12) lensing early-type galaxies at z ∼ 0.15–0.35 from the Sloan Lens ACS (SLACS) Survey. We integrate kinematic maps within the galaxy effective radius and examine the rotational and dispersion velocities, showing that 11/14 can be classified as slow rotators. The data set is unprecedented for galaxy-scale strong lenses in terms of signal-to-noise ratio (S/N), sampling, and calibration, vastly superseding previous studies. We find the primary contributions to systematic uncertainties to be the stellar template library and wavelength range of the spectral fit. Systematics …

Flash Communication: Visible-Light-Driven, Cobalt-Mediated Selective C–H Arylation Of 2,2′-Bipyridine, Xi Chen, Eric R. Allen, Mckenzie L. Stack, Zachary M. Garozzo, Dian Wang

Chemistry Faculty Research and Publications

Herein, we report a visible-light-driven, cobalt-mediated, highly selective C–H arylation method to afford aryl-2,2′-bipyridine, a widely used class of ancillary ligands in transition metal catalysis. This arylation reaction exhibits good-to-excellent C6 selectivity for a variety of aryl groups, allowing for isolation of the 6-isomer in its pure form. Mechanistic studies provided evidence for the generation of an aryl radical by the joint action of [Co(bpy)₃] species and visible light, enabling arylation under mild conditions. Compared to previous work, this method employs cost-effective reagents and provides one-step, direct access from 2,2′-bipyridine to a broad range of electronically varied 6-aryl-2,2′-bipyridine …

Probing The Effect Of Peg-Dna Interactions And Buffer Viscosity On Tethered Dna In Shear Flow, Fatema Tuz Zohra, Huda Al-Zuhairi, Jefferson Reinoza, Hyeongjun Kim, Andreas Hanke

Mechanical Engineering Faculty Publications

DNA flow-stretching is a widely employed, powerful technique for investigating the mechanisms of DNA-binding proteins involved in compacting and organizing chromosomal DNA. We combine single-molecule DNA flow-stretching experiments with Brownian dynamics simulations to study the effect of the crowding agent polyethylene glycol (PEG) in these experiments. PEG interacts with DNA by an excluded volume effect, resulting in compaction of single, free DNA molecules in PEG solutions. In addition, PEG increases the viscosity of the buffer solution. By stretching surface-tethered bacteriophage lambda DNA in a flow cell and tracking the positions of a quantum dot labeled at the free DNA end …

Rising Costs Of Higher Education In United States And Student Debt, Mona Muzammil, Muzammil Arshad, Washain Muzammil

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

100 years ago, college tuition at prestigious Ivy League colleges such as Harvard and Brown was about $130 per year. Even when adjusted for inflation, today's cost of higher education has increased dramatically to the point where a college education is shifting further out of reach for many Americans. This book explains the essential concepts in the debate regarding the staggering costs of higher education, supplying ten original essays by higher education policy experts, a lively historical narrative that provides context to current issues, and systematic guides to find additional sources of information on the subject.

Written from a historian's …

Effect Of Chalcogen-Phosphorus Substituents On Enediynes Undergoing The Bergman Cyclization, Marcos Hendler, Travis Greene, Dominic A. Siriani, Carol A. Parish

Chemistry Faculty Publications

We have theoretically characterized electrocyclizations of chalcogen-phosphorus-containing enediynes. We performed quantum calculations at the BS-(U)­CCSD/cc-pVDZ level to analyze the geometries and energetics of two different cyclization pathways, each consisting of the first three chalcogens (oxygen, sulfur, and selenium). The first pathway involved the cyclization of the chalcogen-phosphorus substituents followed by Bergman cyclization, while the second pathway proceeded via Bergman cyclization followed by chalcogen-phosphorus cyclization. To more accurately understand the energies of the diradicals involved in each pathway, we also performed spin-flip characterizations using UHF reference wave functions and the spin-flip formulation of the equation-of-motion coupled cluster theory with singles and …

A Comparison Of Diving Behavior Of Goose-Beaked And Dense-Beaked Whales From Tagging Studies In Multiple Ocean Basins, Jay Barlow, Robin W. Baird, Janelle Badger, Gregory S. Schorr, Erin A. Falcone, Shannon N. Coates, Peter L. Tyack, Andrew J. Read, Leigh S. Hickmott, John W. Durban, Diane Claridge, Natacha Aguilar De Soto, Daniel Miranda Gonzalez, Fleur Visser, Machiel G. Oudejans, Stacy L. De Ruiter, David A. Sweeney, Brenda K. Rone, Stephanie L. Watwood

University Faculty Publications and Creative Works

Studies of cetacean diving behavior in multiple locations in different ocean basins allow for an assessment of variability within and among populations. We examine foraging dive behaviors of goose-beaked whales (Ziphius cavirostris) and dense-beaked whales (Mesoplodon densirostris) using data from 132 tagged whales in seven locations in the Pacific and Atlantic Oceans and the Mediterranean Sea. Acoustic recording tags are used to identify foraging dives by the presence of echolocation. For other tag types, foraging dives are identified based on maximum dive depth. Five parameters are used to characterize foraging dives: maximum dive depth, foraging dive duration, dive cycle duration, …

Simulating Chemiluminescence Spectra Of Oh Radical Using Quantum Dynamical Simulations, Triet M. Cao

Research from the Berry Summer Thesis Institute, 2025

Chemiluminescence is a phenomenon of light emission that occurs when molecules transition from an excited state to the ground state. This phenomenon is widely utilized in applications ranging from quantifying product yields in chemical reactions to biological imaging and atmospheric chemistry studies. It has also been used in many crucial applications in the scarce conditions of heat and electricity, such as light sources for astronomy discovery or deep-sea diving. A notable example of such reactions is combustion, where highly reactive hydroxyl radicals (OH) are products. These radicals exhibit a chemiluminescence spectrum because of the interaction between their ground state and …

Intelligent Motion Tracking: A Low-Cost Surveillance Framework Using Soc Devices And Sensor Fusion, Aung Myat Khaung, Nicholas Michael Stiffler

Research from the Berry Summer Thesis Institute, 2025

This thesis presents the design and implementation of a lightweight surveillance system capable of realtime motion detection, object tracking, and behavioral history reconstruction in controlled environments. The system uses System-on-Chip devices such as Raspberry Pi boards equipped with NOIR cameras, monocular cameras, and break-beam sensors that work together to detect and track single or multiple moving objects like colored balls. The prototype is validated in structured settings with the goal of eventual deployment in more dynamic environments, addressing the challenge of reliably tracking visually similar objects with minimal distinguishing features. The architecture integrates computer vision with sensor fusion by combining …

Performance Analysis Of Computational Methods For Predicting Protein Function In Rare Diseases, Aichetou Mohamed Sidiya, Hanin Alzaher, Razan Almahdi, Tayeb Brahimi

Effat Undergraduate Research Journal

Protein function prediction is crucial for understanding the underlying mechanisms of rare diseases. With the increasing availability of computational methods including machine learning-based approaches, network-based methods, and sequence-based methods, predicting protein functions has become more accessible. However, it is not clear which of these methods performs better or how they compare to each other in terms of accuracy, efficiency, and scalability. In this study, we evaluate several computational methods for predicting protein functions in rare diseases using key performance indicators (KPIs). We analyze the strengths and weaknesses of each method and provide recommendations for researchers and clinicians interested in using …

Mapping The Research Landscape Of Covid-19 And Artificial Intelligence Using The Lens Database, Aichetou Mohamed Sidiya, Jailan Fouad Aljizawi

Effat Undergraduate Research Journal

Due to the rapid spread of the COVID-19 pandemic, all countries faced a significant challenge in their efforts to monitor and halt the spread of the virus. Moreover, researchers around the world raced into publishing to get to understand the effects of this pandemic on every aspect of our life whether that was economic, medical, or social. Thus, this research seeks to assess the quality of research on the application of Artificial Intelligence in the Covid-19 pandemic with an emphasis on Saudi Arabia. The research methodology is based on Bibliometric Analysis techniques and VosViewer for various bibliometric visualizations based on …

The Relationship Between Self-Talk And Self Esteem Amongst University Students, Weam Batarfi, Saddiga Al-Ghalib

Effat Undergraduate Research Journal

The theory of self-talk is important to human nature and has the capacity to enhance person's life. In addition, self-esteem plays a major role in mankind life, either in a positive or a negative way. This work was done to analyze the relationship between self-talk and self-esteem among university students. This work was carried out based on quantitative method. For this work, the sample population was university students and the sample size used was 100 students. Data collection was done using survey method. Furthermore, the scales that were used are the Self-Talk Scale development, Factor Analysis, and Validation and self-esteem …

Wideband Spectrum Sensing For Cognitive Radio Using Under-Sampled Successive Approximation Adc, Aziza I. Hussein

Effat Undergraduate Research Journal

The radio spectrum, an inherently limited resource, has been increasingly utilized owing to the recent exponential growth of wireless services. This has led to a new approach, termed cognitive radio, predicated upon exploitation of spectrum holes for omnipresent spectrum utilization. This is made possible via cognitive radio networks’ employment of spectrum sensing. Wideband spectrum sensing has been the focal challenge point in cognitive radio technology, since existing techniques are reliant on analog to digital converters (ADC) with sampling at the Nyquist rate. Unfortunately, in order to perform digitization of wideband RF signals at the Nyquist rate, a very high sampling …

Potential Pitfalls In Visual Models Of Tipping Points - And How To Fix Them, Jonathan Dechert, Svetlana Gurevich, Stefan Heusler

Northeast Journal of Complex Systems (NEJCS)

Visual models play a crucial role in both science and science communication. However, the distinction between mere analogies and mathematically sound graphical representations is not easy and can be misunderstood not only by laypeople but also within academic literature itself. Moreover, even when the graphical representation exactly corresponds to the mathematical model, its interpretation is often far from obvious. In this paper we discuss the potential landscape visualization commonly used for tipping points in the context of nonlinear dynamics and reveal potential pitfalls, in particular when distinguishing bifurcation induced tipping (B-tipping) from noise-induced tipping (N-tipping).

We propose new visualization techniques …

A Study Of Rural Health Care For Chronic Care Management Using Machine Learning To Determine Costs, Joanna Maria Keeling

Doctoral Dissertations

Management of diabetes or heart disease may be uniquely challenging for older individuals with multiple chronic conditions[1]. Chronic Care Management would target patients living with comorbidities in Louisiana, who are not receiving sufficient healthcare services and help them receive the care they deserve[2]. This study is aimed at comparing the results of rural Louisiana Medicaid recipients with comorbidities to the National Averages. We will also use Machine Learning to predict Churn and Medical Costs. To help us identify these patients with comorbidities, we decided to use NCQA Quality Measures. We identified several measures from NCQA that we wanted to use, …

The Design Of Coplanar Waveguide Traveling-Wave Kinetic-Impedance Parametric Amplifiers, Jordan Scott Savoie

Master's Theses

Astronomical observations and many physics experiments rely on cryogenic amplifiers for readout. Current sensitivity is limited by the noise figure of high-electronmobility transistor (HEMT) amplifiers, which have proven di!cult to decrease further in recent years. Traveling-wave kinetic-impedance parametric amplifiers (TKIPAs) are an emerging class of amplifiers which have the potential to substantially improve the sensitivity of microwave low-noise amplifiers (LNAs) while also accepting relatively high input powers and amplifying over a wide bandwidth. In this thesis, I present the design, modeling, and testing procedures for coplanar waveguide (CPW) TKIPAs developed by our group at the National Radio Astronomy Observatory. Using …

Structural And Computational Results On Equitably Dissectible Graphs, Ann Wells Clifton

Doctoral Dissertations

This dissertation introduces the class of equitably dissectible graphs — graphs whose vertex set can be recursively partitioned into two parts whose sizes differ by at most one where the two induced subgraphs are connected. In Chapter 2, we show that a graph is equitably dissectible if and only if it has a spanning tree that is equitably dissectible, and we use this result to establish connections between the class of equitably dissectible graphs and Hamiltonian graphs. We also fully characterize the equitably dissectible spiders of the form S3(a) and S3(a, b), identifying a family of unruly spiders that are …

A Backtracking Algorithm For Determining The Existence Of Regular Graphs Of Specified Girth And Excess, Stetson Ray Bosecker

Doctoral Dissertations

The study of cages focuses on finding (k, g)-graphs of minimal order. This dissertation generalizes the problem of finding cages to the determination of graphs with specified excess, thereby broadening the significance of the results. The (k, g, ε)-graph problem seeks to determine the existence or nonexistence of k-regular graphs with girth g and excess ε = n(G)−M(k, g) (where M(k, g) represents the Moore bound for cage graphs). Motivated by heuristic methods used to determine properties within the study of cages, we present a backtracking algorithm capable of constructing (k, g, ε)-graphs or determining their nonexistence. Chapter 2 provides …

Privacy-Preserving Structure Learning For Geospatial Data Using Information-Theoretic Dependency Measures, Ahmed Mudhish

Doctoral Dissertations

This dissertation proposes a privacy-preserving framework for structure learning in Bayesian networks (BNs) that addresses the challenges of distributed geospatial data face. Geospatial datasets often exhibit region-specific patterns such as sparsity and nonlinear dependencies. These patterns undermine the effectiveness of traditional machine learning models. Additionally, learned BN structures may reveal sensitive relationships in the generated graph by BNs. These relationships pose a significant privacy risk if reverse-engineered. To address these issues, three novel algorithms are introduced. First, the Selective Naïve Bayes with HSIC (SNB-HSIC) algorithm applies a kernel-based dependency measure to filter redundant and irrelevant features in sparse datasets, improving …

An Envisioned And Efficient Design Of Next Generation Decentralized Iot Bot Detection Model, Ahmed Abdullah Almalki

Doctoral Dissertations

The Industrial Internet of Things (IIoT) and Internet of Medical Things (IoMT) are revolutionizing critical infrastructures, but their expansion has also introduced severe cybersecurity vulnerabilities. Traditional IoT Bot Detection Systems (IBDS) struggle to scale in environments characterized by high-dimensional, large-scale, and redundant network traffic. These challenges hinder the development of reliable cloud-based intrusion detection systems. The limitations of static and rulebased methods in detecting evolving IoT botnet attacks—such as those launched by Mirai and Gafgyt—underscore the need for intelligent, adaptive approaches. To address this, the present study proposes a machine learning and deep learning-driven IoT Botnet Detection Model, validated through …

Equilibration And Transport Of Binary Mixtures On Planar And Porous Nanomaterials, Andrew Torres

Electronic Theses and Dissertations

We present results of a Kinetic Monte Carlo investigation of the adsorption dynamics of binary gas mixtures on planar and porous sorbents, with a focus on identifying and characterizing kinetic processes involved in uptake evolution and how they influence equilibrium conditions. We also investigate varying thermodynamic simulation parameters such as interactions, alkane lengths, partial pressures and pore configurations to determine how they impact these kinetic processes as well as equilibrium properties. This study matters both for better understanding how kinetics and equilibrium are connected and for improving practical techniques in separation applications. For planar surfaces, weak species overshoot kinetic processes …

Federated Boolean Matrix Factorization Using Integer Programming, Quynh Anh Nguyen, Ngoc Nguyen, Nhat Phan

Research from the Berry Summer Thesis Institute, 2025

Identifying the underlying structural patterns in data and extracting meaningful insights is a key challenge in data analysis. One effective approach to this problem is matrix factorization (MF), which approximates large matrices with lower-dimensional representations, making it effective for uncovering hidden patterns. MF techniques are widely applicable across various domains, such as recommender systems, cancer genomics, system identification, clustering, and image processing. Despite their effectiveness, existing MF methods often struggle with computational constraints and convergence challenges when tackling large-scale, nonsmooth, and nonconvex optimization problems, which are common in real-world applications.

This project aims to explore both the theoretical understanding and …

Comparing Ordinary Least Squares And Quantile Regression: A Causal-Comparative Approach To Modeling Conditional Relationships, Samuel Nnorom

Electronic Theses and Dissertations

Ordinary Least Squares (OLS) regression has traditionally been the preferred quantitative method for estimating linear relationships. However, it assumes that the effect of a predictor variable remains constant across the entire outcome distribution, which can miss important insights when data are heterogeneous. Quantile Regression (QR), on the other hand, offers a more detailed analysis by focusing on the full response variable distribution, thereby revealing different relationship patterns at various quantiles within the outcome. This study compares how OLS and QR perform in modeling conditional relationships within a causal-comparative framework based on ex post facto research. Using the mortality data from …

Characterization Of L-Band Resonators And Relaxation Times Of Soₓ- Radicals At X-Band, Georgina Naa Odey Amassah

Electronic Theses and Dissertations

Electron Paramagnetic Resonance (EPR) analysis requires resonators optimized for specific experimental challenges. Volume resonators enclose samples, while surface coil resonators allow imaging of larger subjects. For in vivo studies, L-band frequencies are commonly used because they offer a good balance between signal-to-noise ratio (S/N) and the ability to penetrate tissue. Rapid Scan (RS) EPR at L-band frequencies was chosen for my studies of resonators because of this balance but presents a challenge for sensitivity.

The spatial position dependence of signal intensity was evaluated for selected paramagnetic samples using 10 mm and 30 mm surface coils. The 10 mm coil, with …

Self Spin-Orbit Torques, Ryan Greening

Electronic Theses and Dissertations

Spin–Orbit torques (SOTs) provide an energy-efficient pathway to control magnetization in nanoscale heterostructures. Recently, spin-orbit coupling within ferromagnets has been shown to generate self spin-orbit torques (SSOTs) on the magnetization itself. Previous work on self spin-orbit torques relies on thick ferromagnets with complicated film structures with chemical disorder or compositional gradients to generate inversion symmetry breaking. This dissertation advances experimental methodology and presents data on the quantification of self spin-orbit torques in magnetic thin films due to the spin-orbit coupling of standard 3d ferromagnets.

First, I develop an oblique-incidence magneto-optical Kerr effect (MOKE) technique that exploits a mirror-assisted double reflection …

Developing Deep Learning Methods For Cognitive Impairment Detection Based On Non-Invasive Data, Muath Alsuhaibani

Electronic Theses and Dissertations

Cognitive impairment detection is on the rise to help reduce the burden of healthcare costs on institutions and individuals. Mild Cognitive Impairment (MCI) is an early stage of cognitive decline progressing to Alzheimer’s disease (AD) or AD-related Dementia (ADRD). Detecting the early stages of AD/ADRD is crucial for early interventions among older adults to mitigate cognitive decline over time. However, the current diagnostic methods are often costly and/or invasive, such as MRI and PET scans. Thus, the search for non-invasive and cost-effective screening tools for the early detection of cognitive impairment using speech, language, visual, and motor data is growing. …

Behavioral Neuroscience Of Drug Addiction And Mental Disorder, Mona Muzammil, Muzammil Arshad, Washain Muzammil

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

This book explores the molecular, cellular, and neurocircuitry systems in the brain that are responsible for drug addiction. Common neurobiological elements are emphasized that provide novel insights into how the brain mediates the acute rewarding effects of drugs of abuse and how it changes during the transition from initial drug use to compulsive drug use and addiction. The book provides a detailed overview of the pathophysiology of the disease. The information provided will be useful for neuroscientists in the field of addiction, drug abuse treatment providers, and undergraduate and postgraduate students who are interested in learning the diverse effects of …

A Technical And Statistical Analysis Of Unleaded Aviation Fuel (Ul94) Adoption In A High- Volume Collegiate Aviation Environment, Nicholas D. Wilson, Ryan Guthridge, Brandon Wild, Jeremy Roesler, Daniel Kasowski, Nick Geinert, Aaron Terbest, Aaron Fettig, Robert Kraus

Journal of Aviation Technology and Engineering

The University of North Dakota (UND) adopted unleaded aviation fuel (UL94) for approximately a four-month period in the summer and early fall of 2023. The UL94 fuel was used in all reciprocating engine fleets based at the university’s primary training airport, Grand Forks International Airport in North Dakota. During the operational implementation of UL94, the UND flew 46,600 flight hours, consuming 386,778 gallons of fuel across all fleets powered by Lycoming engines. After approximately two months of using UL94, operational reports and maintenance inspections began to indicate potential for exhaust valve seat recession (EVSR), although early indications were limited in …

Enhancing Cataract Surgery Outcomes: Optimal Use Of Pre- And Post-Operative Eye Drops, Keith Skolnick M.D., Anu Valiaveedu

Mako: NSU Undergraduate Student Journal

Many preoperative and postoperative cataract patients struggle with comprehending the use of prescription medication as directed. Language barriers and low health literacy levels are major factors contributing to improper use of prescriptions. To increase patients comprehension, the Fort Lauderdale Eye Institute employed an educational intervention consisting of a live presentation and an instructional video. Results found that 44% of patients were hesitant to ask questions to clinical staff, 32% felt overwhelmed, and nearly 70% lacked confidence in using their prescribed eye drops. Following the intervention, 91% of patients reported increased confidence in their medications, and most indicated that the video …

From Infection To Restoration: A Case Study On Dental Extraction In The Maxilla Anterior, Melanie Ramirez

Mako: NSU Undergraduate Student Journal

A dental implant is a restorative surgical procedure that serves as a solution to replace missing teeth that imitate the function, sensation, and appearance of natural teeth. The objective of this dental case study is to examine the diagnosis, treatment, and post-operation of a patient with a history of tooth loss and infection in the anterior maxilla. This case follows a 55-year-old patient, Jorge Marquez, name changed for confidentiality, who presented a severe tooth abscess on tooth #10 on the anterior maxilla which had previously undergone root canal treatment (Figure 1B). Radiographic evaluations illustrated the severity of the abscess the …