Physical Sciences and Mathematics Commons^™

First Detrital Zircon Provenance Data From Oligocene-Pleistocene Sediment In The Beaufort-Mackenzie Basin, Arctic Ocean, Joseph Martina

Theses and Dissertations

Sediment, runoff, and nutrient input to the Arctic Ocean plays a critical role in both physical and biological processes that impact regional and global systems. The Beaufort-Mackenzie Basin, situated in the Arctic Ocean offshore northwestern Canada, contains more than 14 km of clastic strata and provides a record of erosion and sediment transport from the Cretaceous to present. Pliocene sedimentation rates within the basin jump nearly 2000% relative to underlying units, but the cause of this shift remains unknown. We used cuttings from the N. Issungnak L-86 well, focusing on the Oligocene-lower Miocene Kugmallit and Mackenzie Bay sequences and the …

Elevating Next Generation Wireless Devices Towards Contactless Sensing For Healthcare Applications, Aakriti Adhikari

Theses and Dissertations

There is an increasing interest in technologies that can understand and perceive at-home human activities to provide personalized healthcare monitoring, aimed at early detection of disease markers and assisting physicians in making clinical decisions. Existing approaches, such as wearables, require users to wear sensors that can be cumbersome and cause discomfort. Vision based solutions, such as optical cameras, IRs, LiDARs, etc., can be used to design contactless at-home monitoring systems. However, these systems are limited by poor lighting and occlusion, and they are privacy-invasive. Fortunately, high-frequency millimeter-wave wireless devices provide an effective alternative to the existing systems to enable fine-grained …

The Role Of Symmetries In Atomic, Electromagnetic, And Particle Physics, Joshua Martin O'Connor

Theses and Dissertations

Symmetries in atomic, electromagnetic, and weak interaction physics are explored to understand symmetry-breaking extensions of the Standard Model of particle physics. Lorentz-violating field theories are extremely interesting theoretically, since they possess many new features that are absent in Lorentz-invariant models. We outline the formalism and experimental status of the Lorentz- and CPT-violating Standard Model Extension, in both the classical and quantum regimes. Processes such as vacuum Cerenkov radiation, which are kinematically forbidden when Lorentz symmetry is exact may become allowed when this symmetry is weakly broken. Particle decays, such as pion and kaon decays, although allowed in Lorentz-invariant theories, are …

Causal Neuro-Symbolic Artificial Intelligence: Synergy Between Neuro-Symbolic And Causal Artificial Intelligence, Utkarshani Jaimini

Theses and Dissertations

Understanding and reasoning about cause and effect is innate to human cognition. In everyday life, humans continuously engage in causal reasoning and hypothetical retrospection to make decisions, plan actions, and interpret events. This cognitive ability allows us to ask questions such as: “What caused this situation?”, “What will happen if I take this action?”, or “What would have happened had I chosen differently?” This intuitive capacity to form mental models of the world, infer causal relationships, and reason about alternative scenarios, particularly counterfactuals, is central to our intelligence and adaptability. In contrast, current machine learning (ML) and artificial intelligence (AI) …

A Neuro-Symbolic Ai Approach To Scene Understanding In Autonomous Systems, Ruwan Tharanga Wickramarachchige Don

Theses and Dissertations

Effectively understanding scenes requires a unified representation of scene data and background knowledge. A neuro-symbolic AI approach to scene understanding leverages such a unified representation to enable advanced expression, inference, and labeling of scenes, improving the perception of autonomous systems.

Scene understanding remains a central challenge in the machine perception of autonomous systems. It requires the integration of multiple sources of information, background knowledge, and heterogeneous sensor data to perceive, interpret, and reason about both physical and semantic aspects of dynamic environments. Current approaches to scene understanding primarily rely on computer vision and deep learning models that operate directly on …

On A Conjecture On Covering Systems And An Irreducibility Question On Sparse 0,1-Polynomials, Alexandros Kalogirou

Theses and Dissertations

In 1952, H. Davenport posed the problem of determining a condition on the minimum modulus $m_0$ in a finite distinct covering system that would imply that the sum of the reciprocals of the moduli in the covering system is bounded away from 1. In 1973, P.~Erd\H os and J.~Selfridge indicated that they believed that $m_0$ > 4 would suffice. We provide a proof that this is the case in Chapter 2. Chapters 3 and 4 are dedicated to showing that $0,1$-polynomials of high degree and few terms are irreducible with high probability. Formally, let $k\in\mathbb{N}$ and $F(x)=1+\sum_{i=1}^kx^{n_i}$, where $ 0

A Spatial Scan Statistic For Group Testing Data, Vincent Onyame

Theses and Dissertations

Group testing involves pooling specimens from multiple individuals and offers an efficient means to surveil low-prevalence pathogens, but poses challenges for spatial cluster detection when only pooled results are observed. In this thesis, we develop a spatial scan statistic tailored to group-testing data with variable pool sizes. The statistic compares a null hypothesis of a homogeneous infection rate across all clusters to an alternative hypothesis that infection probabilities differ inside and outside a candidate cluster, with both models fitted by maximum likelihood estimation. We approximate the null distribution of the maximum likelihood ratio test via Monte Carlo simulation.

Through a …

Some Likelihood-Based Methods For Clustering Functional Data, Tong Shan

Theses and Dissertations

The analysis of functional data is an increasingly relevant part of statistics. The exploratory data analytic method of cluster analysis plays a very important role in different fields. Over the years, researchers have developed many clustering approaches, striving to achieve more accurate and efficient clustering. In Chapter 1, we aim to improve the accuracy of our outcome when clustering functional data. To achieve this goal, we use a predictive likelihood function which serves as an objective function to optimize in order to determine the most appropriate clusters. To optimize the objective function over the space of clustering partitions, we produce …

On Berge Pancyclicity For Uniform Hypergraphs, Teegan Cole Bailey

Theses and Dissertations

An $n$-vertex graph $G$ is \textit{hamiltonian} if it contains a length $n$ cycle as a subgraph. A stronger notion of hamiltoncity is pancyclicity. A graph $G$ is \textit{pancyclic} if $G$ contains a cycle of length $k$ for every $3\leq k \leq n$. Dirac's classical result on hamiltonicity states that if an $n$-vertex graph $G$ has minimum degree $\delta(G)\geq \frac{n}{2}$, then $G$ is hamiltonian. Under the same minimum degree condition as Dirac, J. A. Bondy showed that $G$ must also be pancyclic or the exceptional graph $K_{\frac{n}{2}, \frac{n}{2}}$. In 1971, Bondy proposed a so called meta-conjecture claiming that \textit{``almost any nontrivial …

Multi-Task Deep Learning Approach For Segmenting And Classifying Competitive Swimming Activities Using A Single Imu, Mark Shperkin

Theses and Dissertations

Competitive swimming performance analysis has traditionally relied on manual video review and multi-sensor systems, both of which are resource-intensive and impractical for everyday training use. This study investigates whether a single wrist-worn inertial measurement unit (IMU) can be used to automatically segment and classify swimming activities with high accuracy. We propose a multi-task deep learning pipeline based on the MTHARS (Multi-Task Human Activity Recognition and Segmentation) architecture introduced by Duan et al. to perform stroke classification, lap segmentation, stroke count estimation, and underwater kick count estimation. Data were collected from eleven collegiate-level swimmers wearing left-wrist-mounted IMUs, each performing five 100-yard …

Approaches To Enhancing Multiple Hypothesis Testing Methods With Side-Information, Siyu Zheng

Theses and Dissertations

Lesion-symptom mapping (LSM) studies offer insight into the brain areas involved in various aspects of cognition. This is commonly done via behavioral testing in patients with a naturally occurring brain injury or lesions (e.g., strokes or brain tumors). This results in high-dimensional observational data where lesion status (present/absent) is non-uniformly distributed, with some voxels having lesions in very few (or no) subjects. In this situation, mass univariate hypothesis tests have severe power heterogeneity where many tests are known a priori to have little to no power. Additionally, high-dimensional observational data can be grouped according to brain anatomical structure.

In this …

Functional Time Transformation Model With Applications To Digital Health, Rahul Ghosal Ph.D., Marcos Matabuena, Sujit K. Ghosh

Faculty Publications

The advent of wearable and sensor technologies now leads to functional predictors which are intrinsically infinite dimensional. While the existing approaches for functional data and survival outcomes lean on the well-established Cox model, the proportional hazard (PH) assumption might not always be suitable in real-world applications. Motivated by physiological signals encountered in digital medicine, we develop a more general and flexible functional time-transformation model for estimating the conditional survival function with both functional and scalar covariates. A partially functional regression model is used to directly model the survival time on the covariates through an unknown monotone transformation and …

Physics Oriented Deep Learning For Material Prediction And Generation, Nihang Fu

Theses and Dissertations

The discovery of new materials is critical to advancing various industries, but traditional experimental methods for materials discovery remain slow and resource-intensive. Recent advances in machine learning (ML), particularly deep learning (DL), have greatly improved and accelerated two main aspects of modern computational material discovery: material design (e.g., material generation) and material screening (e.g., property prediction). However, a key challenge remains: standard ML models often struggle to perform domain-specific tasks effectively. Incorporating domain-specific knowledge, specifically the underlying physics of materials, into ML/DL models is key to improving the accuracy and reliability of material generation and prediction models.

This dissertation discusses …

In Vivo Analysis Of Fe-S Cluster Assembly And Iron Homeostasis In Escherichia Coli, Dexter Mclaurin Reasons

Theses and Dissertations

Iron-sulfur (Fe-S) clusters are an essential cofactor for a wide range of cellular processes, and their assembly and storage require tight regulation.

In Escherichia coli (E. coli), there are two pathways of Fe-S cluster assembly, the Isc and the Suf pathways. The Isc pathway is used under good growth conditions, and the Suf pathway is used under iron starvation and oxidative stress conditions. Once the cluster has been assembled on the scaffold protein of either pathway, it is transferred to Fe-S cluster trafficking proteins. In E. coli, the monothiol glutaredoxin GrxD and the BolA-type proteins BolA and IbaG …

Explainable Process Recommendation Through Multi-Contextual Grounding Of Dynamic Multimodal Process Knowledge Graphs, Revathy Venkataramanan

Theses and Dissertations

Can I eat this food or not? Is this food suitable for diabetes and why? Which AI pipeline is best suited for a given task and dataset? How should an end-to-end pipeline be constructed? These questions differ from factual question-answering tasks. Recipes and AI pipelines are processes consisting of several entities interacting with each other. A recipe consists of ingredients, cooking methods, and their interactions, while an AI pipeline includes datasets, preprocessing techniques, models, hyperparameters, tasks, and results. Each entity must be analyzed individually, and collective inferencing is performed to derive the final decision. This decision-making process, known as compositional …

Sepsis: I Can Catch Your Lies – A New Paradigm For Deception Detection, Anku Rani, Dwip Dalal, Shreya Gautam, Pankaj Gupta, Vinija Jain, Aman Chadha, Amitava Das, Amit P. Sheth

Publications

Deception is the intentional practice of twisting information. It is a nuanced societal practice deeply intertwined with human societal evolution, characterized by a multitude of facets. This research explores the problem of deception through the lens of psychology, employing a framework that categorizes deception into three forms: lies of omission, lies of commission, and lies of influence. The primary focus of this study is specifically on investigating only lies of omission. We propose a novel framework for deception detection leveraging NLP techniques. We curated an annotated dataset of 876,784 samples by amalgamating a popular large-scale fake news dataset and scraped …

Hypertensive Disorders Of Pregnancy And Perinatal Outcomes: Two Prospective Cohort Studies Of Nulliparous Women In India And Tanzania, Andrea B. Pembe, Pratibha Dwarkanath, Amani Kikula, John Michael Raj, Nandita Perumal Phd, Heavenlight A. Paulo, Rajalakshmi M, Christopher P. Duggan, Honorati M. Masanja, Nandini Chopra, Mary M. Sando, Tinku Thomas, Cara A. Yelverton, Alfa Muhihi, Anura V. Kurpad, Wafaie E. Fawzi, Blair J. Wylie, Christopher R. Sudfeld

Faculty Publications

Introduction Hypertensive disorders of pregnancy (HDP) have been linked with increased risk for maternal and offspring complications in high-income settings. However, in resource-limited settings, studies with robust measurement of HDP, including severity and timing, and perinatal outcomes are limited.

Methods We analysed data from two prospective cohorts of nulliparous women in India (n=10 570 pregnancies) and Tanzania (n=10 299 pregnancies) who were enrolled in calcium supplementation trials and had blood pressure and proteinuria assessments throughout pregnancy and at the time of labour and delivery. Generalised estimating equations were used to assess the relationship between HDP severity categories (gestational hypertension, preeclampsia …

Uncovering Multiscale Structure-Property Correlations Via Active Learning In Scanning Tunneling Microscopy, Ganesh Narasimha, Deja Kong, Paras Regmi, Rongying Jin, Zheng Gai, Rama Vasudevan, Maxim Ziatdinov

Faculty Publications

Atomic arrangements and local sub-structures fundamentally influence emergent material functionalities. These structures are conventionally probed using spatially resolved studies and the property correlations are deciphered by a researcher based on sequential explorations, thereby limiting the efficiency and scope. Here we demonstrate a multi-scale Bayesian deep-learning based framework that automatically correlates material structure with its electronic properties using scanning tunneling microscopy (STM) measurements in real-time. Its predictions are used to autonomously direct exploration toward regions of the sample that optimize a given material property. This method is deployed on a low-temperature ultra-high vacuum STM to understand the structure-property relationship in a …

Photo-Crosslinked Persistent Micelle Templates With Near Universal Solvent Compatibility, Coby S. Collins, Mengxue Zhang, Cj Strurgill, Christian X. Ruff, Bryce Melton, Morgan Stefik

Faculty Publications

The controlled preparation of porous nanomaterials from block polymer templates is important for diverse applications from energy devices to optical coatings and sorbents. The architectural dimensions determine the overall performance for many of these applications, however the independent control of these dimensions has remained limited to a narrow range of solvent conditions for kinetically trapped (“persistent”) micelle templates. Polymers with a photo-reactive chemistry are shown to enable cross-linked micelle templates that universally remain persistent under diverse solvent conditions. Specifically, poly(poly(ethylene glycol methacrylate))-b-poly(butyl methacrylate-co-coumarin methacrylate) (OBC) was prepared by RAFT polymerization and the resulting micelles were crosslinked …

Association Between Dietary Inflammatory And Antioxidant Potential And Systemic Inflammatory And Oxidative Status With The Risk And Severity Of Coronary Artery Disease, Zahara Namkhah, Elham Alipoor, Manhnaz Salmani, Negar Ebrahimi, Monireh Ahmadpanahi, Ali Vasheghani-Farahani, Mehdi Yaseri, Michael David Wirth, Longgang Zhao, James Hébert Scd, Javad Hosseinzadeh-Attar

Faculty Publications

Background and aims

Unhealthy diets have pro-inflammatory properties that have been shown to contribute to coronary artery disease (CAD). The dietary inflammatory index (DII®) and the dietary antioxidant quality score (DAQS) quantify the anti-/pro-inflammatory and antioxidant potential of a diet. This study aims to investigate the association between the energy-adjusted DII (E-DIITM), DAQS, oxidant/anti-oxidant biomarkers, and CAD risk and severity.

Methods and results

This cross-sectional study investigated 158 participants for the presence and severity of CAD based on coronary angiography. E-DII and DAQS scores, malondialdehyde (MDA), total oxidant status (TOS), glutathione peroxidase (GPX) activity, total antioxidant capacity (TAC) and conventional …

Human Gut Commensal Alistipes Timonensis Modulates The Host Lipidome And Delivers Anti-Inflammatory Outer Membrane Vesicles To Suppress Colitis In An Il10-Deficient Mouse Model, Ethan Older, Mary K. Mitchell, Andrew Campbell, Xiaoying Lian, Michael Madden, Yuzhen Wang, Lauren E. Van De Wal, Thelma Zaw, Brandon N. Vanderveen, Rodney Tatum, E. Angela Murphy, Yan-Hua Chen, Daping Fang, Melissa Ellermann, Jie Li

Faculty Publications

Correlative studies have linked human gut microbes to specific health conditions. Alistipes is one such microbial genus negatively linked to inflammatory bowel disease (IBD). However, the protective role of Alistipes in IBD is understudied, and the underlying molecular mechanisms remain unknown. In this study, colonization of Il10-deficient mice with Alistipes timonensis DSM 27924 delays colitis development. Colonization does not significantly alter the gut microbiome composition, but instead shifts the host plasma lipidome, increasing phosphatidic acids while decreasing triglycerides. Outer membrane vesicles (OMVs) derived from Alistipes are detected in the plasma of colonized mice, carrying potentially immunomodulatory metabolites into the …

A New Transition Metal Borate, Co6(B24O39(Oh)6(H2O) 6·2.21h2O, Synthesized Via A Mild Hydrothermal Synthesis, Alevtina Maksimova, Patrick Belt, Nilah Whitfield, Mark D. Smith, Gopabandhu Panigrahi, Gregory Morrison, Hans Conrad Zur Loye

Faculty Publications

A new transition metal borate hydrate, Co₆B₂₄O₃₉(OH)₆(H₂O)₆·2.21H₂O, was synthesized via a mild hydrothermal method using boric acid as the melt. The compound crystallizes in the trigonal space group P 3‾ with lattice parameters a = b = 13.17840(10) Å, c = 12.3287(2) Å, and a unit cell volume of 1854.27(4) ų (Z = 2). This borate hydrate crystallizes in a new structure type comprised of layers containing [BO3] trigonal planar units and [BO4] tetrahedra that are linked by CoO6 and Co(OH)2(H2O)4 octahedra via corner-sharing. The …

Jwst Reveals The Diversity Of Nuclear Obscuring Dust In Nearby Agn: Nuclear Isolation Of Miri/Mrs Data Cubes And Continuum Spectral Fitting, Omaira González-Martín, Daniel J. Díaz-González, Mariela Martínez-Paredes, Almudena Alonso-Herrero, Enrique López-Rodríguez, Begoña García-Lorenzo, Cristina Ramos Almeida, Ismael García-Bernete, Donaji Esparza-Arredondo, Sebastian F. Hoenig, Santiago García-Burillo, Chris Packham, Nancy A. Levenson, Alvaro Labiano, Miguel Pereira-Santaella, Francoise Combes, Anelise Audibert, Erin K.S. Hicks, Lulu Zhang, Enrica Bellocchi, Richard I. Davies, Laura Hermosa Muñoz, Masatoshi Imanishi, Claudio Ricci, Marko Stalevski

Faculty Publications

We investigate the capabilities of the mid-infrared instrument (MIRI) of JWST to advance our knowledge of active galactic nucleus (AGN) dust using the spectral fitting technique on an AGN collection of 21 nearby (z < 0.05) AGN (7 type-1 and 14 type-2) observations obtained with the medium resolution spectroscopy (MRS) mode. This collection includes publicly available AGN and data from the collaboration of Galactic Activity, Torus, and Outflow Survey (GATOS). We developed a tool named MRSPSFisol that decomposes MRS cubes into point-like and extended contributions. We found statistically good fits for 12 targets with current AGN dust models. The model that provides good fits (χ²/dof< 2) for these 12 targets assumes a combination of clumpy and smooth distribution of dust in a flare-disc geometry where the dust grain size is a free parameter. Still, two and one AGN statistically prefer the disc + wind and the classical clumpy torus model, respectively. However, the currently available models fail to reproduce 40 per cent of the targets, likely due to the extreme silicate features not well reproduced by the models and signatures of water-ice and aliphatic hydrocarbon absorption features in most targets. New models exploring, for instance, new chemistry, are needed to explain the complexity of AGN dust continuum emission observed by JWST.

Photometric Redshifts Of Galaxies In Quasar Fields, Ananthavishnu Santhigiri Unni

Theses and Dissertations

Understanding the gas in and around galaxies is crucial for understanding galaxy evolution. Absorption lines detected in the spectra of background quasars offer a powerful tool to study the gas in and around the intervening galaxies. As a part of an effort to understand how the gas interacts with the stellar component of galaxies, our team previously obtained imaging and spectroscopic observations for a large sample of galaxies using the Hubble Space Telescope (HST), the Very Large Telescope (VLT), and the Atacama Large Millimeter Array (ALMA). This sample includes thousands of galaxies, including many without spectroscopic data. The overall goal …

Understanding The Through-Space Intermolecular Interactions Of Isothiourea Catalysts In Acylation/Silylation Reactions Of Secondary Alcohols, Ziyuan Gong

Theses and Dissertations

Through space interactions, including cation-π interaction, lone pair-πinteraction, steric hinderance etc. play a central role in organocatalytic reaction. They can control the reactivity or the selectivity of an organic reaction. Previous work in our group has already shown that the chiral isothiourea compounds can catalyze the acylation as well as silylation reaction of secondary alcohol with the possible cation-πinteraction between the catalyst and substrate. However, there is lack of study to understand how the delocalization of the positive charge would affect the reaction rate and whether some unexpected inter- or intramolecular interaction could help stabilize …

Dust And Metals In Distant Galaxies, Fatima Elkhatib

Theses and Dissertations

Interstellar dust causes reddening and dimming of light from background objects. To analyze how different the dust in distant galaxies is compared to dust in nearby galaxies, we look at multiple background quasars and try to fit their spectra with various models for known galaxies that have differing dust grain populations combined with a quasar spectrum template. Through fitting these models, we found that dust in most of the foreground galaxies we analyzed is similar to the SMC bar, a relatively thin area selected from the Small Magellanic Cloud (SMC). However, we note that all the objects we studied did …

Analysis And Derivation Of The Compressible Euler System With Nonlinear Velocity Alignment: An Investigation Into Collective Behavior, Mckenzie Meredith Black

Theses and Dissertations

Collective behavior refers to the observable patterns, actions, or movements that emerge within a group of entities, such as individuals, animals, or particles, when they interact with each other. In this study, we concentrate on the pressureless compressible Euler system, expanding it to incorporate a family of nonlinear velocity alignment. This extension represents a nonlinear iteration of the Euler-alignment system within collective dynamics, revealing intriguing asymptotic emergent phenomena such as alignment and flocking. Our investigation explores different types of nonlinearity and nonlocal communication protocols, unveiling a diverse spectrum of asymptotic behaviors within the system.

In focusing on the derivation, we …

Thermodynamic Study Of Ligand Coordination On Lead Halide Perovskite Quantum Dots, Bishal Adhikari

Theses and Dissertations

Inorganic lead halide perovskite (ILHP) has been extensively studied in thin films and bulk crystals as promising materials for their photovoltaic and optoelectronic properties. These are stable enough to be prepared as colloidal quantum dots that can be dispersed, deposited and used to achieve quantum confinement; however, selection of the suitable surface passivating ligand remains challenge for long term stability of the colloidal quantum dots. Several ligand coordination chemistries used to achieve greater stability or specific functions: these can be installed at time of synthesis in some cases they can also be installed to preexisting quantum dots by ligand exchange …

Assessing Relationships Between Water Quality, Precipitation, Land Cover And Stormwater Conveyance Type Across A Range Of Sub-Watersheds In The Southeastern Coastal Zone, Kevencia Sabine Gabriel Faton

Theses and Dissertations

The expansion of urban land use/cover along the coast may degrade water quality by introducing a plethora of pollutants and pathogens that negatively impact human and ecological health. It is hypothesized that anthropogenic contaminants associated with stormwater runoff increase with increasing urban density and vary with the timing and magnitude of rainfall. In this study, we examined land use/cover change and relationships between Escherichia coli (E. coli), turbidity, nutrients, and the timing and magnitude of rainfall in two different types of stormwater conveyances (ditches and ponds) within Murrells Inlet, SC during the summer of 2023. Our results indicate …

Integrated Coastal Science And Dune Management: A South Carolina Perspective, Michelle Harris

Theses and Dissertations

Historically, coastal dunes have been poorly understood from a societal perspective despite their protective role in attenuating incoming waves to reduce onshore flood risk. As developed coastlines promote strategies to design and maintain managed dune systems, it is necessary to ensure these strategies are optimized for dune health and resilience, particularly given the increasing threat of natural and anthropogenic stressors. This dissertation work aims to identify strategies that influence coastal dune management in South Carolina (SC), USA from an integrated approach, including a current use assessment, a mesoscale field-based study on strategy efficacy, and by incorporating a societal assessment and …