Physical Sciences and Mathematics Commons^™

Evaluation Of Future Sea-Level Impacts Using A Sharp Interface Saltwater Intrusion Model, Caroline Hiott

All Theses

Saltwater intrusion is a growing problem that is being exacerbated by climate change. Saltwater intrusion is the process by which saltwater moves towards freshwater supplies driven by saltwater’s greater density compared to freshwater. Saltwater intrusion can contribute to the salinization of freshwater resources, degradation of underground storage tanks, communication systems, and pipelines, as well as lead to groundwater flooding (Ketabchi et al., 2016). Numerical modeling can be used to simulate saltwater intrusion along coastal areas. One of the more computationally efficient modeling tools is the sharp interface approach, SWI2, that is a part of the MODFLOW 2005 suite (Werner et …

High-Resolution Ion Mobility Analysis Of Isomeric Bile Acids Using Structures For Lossless Ion Manipulations (Slim) Im-Ms, Emmaleigh D. Efird

All Theses

Bile acids are an essential part of the human digestion system and play an important role in lipid absorption, bacteria movement in the small intestine, and regulation of the farnesoid X receptor (FXR) and G protein-coupled bile acid receptors (GPBAR) responsible for homeostasis. They are synthesized in the liver, stored in the gallbladder and the excess is carried on to the small intestine. Many liver and intestinal diseases are diagnosed based on bile acid metabolism pathways and the structures of those bile acids. Therefore, the bile acid structure determines the function of the molecule. Many bile acids are similar in …

Extraction Of Neutron-Gamma Irradiated Diffusion Pump Oils, Cooper L. Tillman

All Theses

This work successfully demonstrates solvent extraction methods for separation of oil from the by-products when two commercially available vacuum pump oils were exposed to an intense neutron and gamma-ray radiation environment. Nuclear fusion power at a commercial scale has accelerated the need for radiation resistant vacuum technology, such as oil-based diffusion pumps. Polyphenyl ether and aromatic silicone oils were irradiated at the Rhode Island Nuclear Science Center (RINSC) up to MGy absorbed doses with neutron and gamma-ray radiation. Solvent extractions were performed using hexane and isopropanol to characterize the oil extraction as a function of total absorbed dose. The by-products …

Enhanced Rate Capability And Capacity Of Lib Full Cells Achieved Through Aerosol Jet Printing, Rodrigo Rodriguez, L. Jay Deiner, Bang-Hung S. Tsao, Joseph P. Fellner

Publications and Research

Thick lithium-iron phosphate (LFP) cathodes (31 mg cm−2) with rationally engineered pore structure and tortuosity were manufactured with an aerosol jet (AJ) printer. Cathode pore structuring was tuned by controlling the rate at which the printed ink dried. Slow-drying prints yielded smoother cathodes while fast-drying prints resulted in mesoscale structuring with substantial surface roughness. X-ray tomography further revealed that the rapid drying of AJ printed LFP cathodes produced low-tortuosity pore channels which were preserved after calendering. Full cells comprised of AJ print optimized LFP cathodes, with 30 mg cm−2 active material loadings, and capacity-matched, AJ printed lithium titanate anodes were …

Temperature-Dependent Optical Constants Of Vanadium Dioxide Thin Films Deposited On Polar Dielectrics, Imtiaz Ahmad, Satya R. Kachiraju, Sundar Kunwar, Zachary M. Brown, Pinku Roy, Matthew Gaddy, Vladimir Kuryatkov, Yejin Kwon, Ayrton A. Bernussi, Myoung-Hwan Kim

Physics & Astronomy Faculty Publications

Coating polar dielectrics with thin film vanadium dioxide (VO2) enables one to exploit the temperature-dependent phase transition within VO2 to actively tune and modulate surface phonon polaritons at mid-infrared. However, controlling the behavior of such systems requires intimate knowledge of the temperature-dependent optical constants of VO2, which depend greatly on the growth conditions and substrate material. Here, we accurately determine the complex optical constants of VO2 on polar dielectrics across the insulator-to-metal phase transition (IMT) using only normal incident reflectance spectra by analyzing the reflectance with Kramers–Kronig relations and thin film Fresnel equations. This non-ellipsometry technique offers an …

Observation Of Gravitational Waves From The Coalescence Of A 2.5–4.5 M⊙ Compact Object And A Neutron Star, A. Abac, R. Abbott, I. Abouelfettouh, F. Acernese, Teviet Creighton, Mario C. Diaz, Francisco Llamas, Soma Mukherjee, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

We report the observation of a coalescing compact binary with component masses 2.5–4.5 M⊙ and 1.2–2.0 M⊙ (all measurements quoted at the 90% credible level). The gravitational-wave signal GW230529_181500 was observed during the fourth observing run of the LIGO–Virgo–KAGRA detector network on 2023 May 29 by the LIGO Livingston observatory. The primary component of the source has a mass less than 5 M⊙ at 99% credibility. We cannot definitively determine from gravitational-wave data alone whether either component of the source is a neutron star or a black hole. However, given existing estimates of the maximum neutron star mass, we find …

Automatic Uncovering Of Patient Primary Concerns In Portal Messages Using A Fusion Framework Of Pretrained Language Modelsautomatic Uncovering Of Patient Primary Concerns In Portal Messages Using A Fusion Framework Of Pretrained Language Models, Yang Ren, Yuqi Wu, Jungwei W Fan, Aditya Khurana, Sunyang Fu, Dezhi Wu, Hongfang Liu, Ming Huang

Faculty, Staff and Student Publications

OBJECTIVES: The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs-a practice which holds the potential to yield more nuanced insights and enhances the quality of healthcare delivery and patient-centered care.

MATERIALS AND METHODS: We propose a fusion framework to leverage pretrained language models (LMs) with different language advantages via a Convolution Neural …

Artificial Intelligence In Fusion Protein Three-Dimensional Structure Prediction: Review And Perspective, Himansu Kumar, Pora Kim

Faculty, Staff and Student Publications

Recent advancements in artificial intelligence (AI) have accelerated the prediction of unknown protein structures. However, accurately predicting the three-dimensional (3D) structures of fusion proteins remains a difficult task because the current AI-based protein structure predictions are focused on the WT proteins rather than on the newly fused proteins in nature. Following the central dogma of biology, fusion proteins are translated from fusion transcripts, which are made by transcribing the fusion genes between two different loci through the chromosomal rearrangements in cancer. Accurately predicting the 3D structures of fusion proteins is important for understanding the functional roles and mechanisms of action …

Patient-Centered Clinical Decision Support Challenges And Opportunities Identified From Workflow Execution Models, Dean F Sittig, Aziz Boxwala, Adam Wright, Courtney Zott, Nicole A Gauthreaux, James Swiger, Edwin A Lomotan, Prashila Dullabh

Faculty, Staff and Student Publications

OBJECTIVE: To use workflow execution models to highlight new considerations for patient-centered clinical decision support policies (PC CDS), processes, procedures, technology, and expertise required to support new workflows.

METHODS: To generate and refine models, we used (1) targeted literature reviews; (2) key informant interviews with 6 external PC CDS experts; (3) model refinement based on authors' experience; and (4) validation of the models by a 26-member steering committee.

RESULTS AND DISCUSSION: We identified 7 major issues that provide significant challenges and opportunities for healthcare systems, researchers, administrators, and health IT and app developers. Overcoming these challenges presents opportunities for new …

Soil Inversion To Ameliorate Soil Water Repellence, Department Of Primary Industries And Regional Development, Western Australia

Natural resources factsheets

One-off soil inversion results in the burial of the water repellent topsoil in a layer that is typically a depth of 15 to 35 cm and brings to the surface a layer of wettable subsoil.

Other benefits include burial of herbicide resistant weed seeds, removal of compaction, improved access to nutrients, reduced disease risk, and incorporation of soil amendments such as lime.

Soil inversion should always be done when the soil is wet to more than the depth of inversion, and a crop or cover can be sown to reduce the risk of wind erosion.

Caution - Deep cultivation can …

Determining Heterogeneous Growth Rates Of Brucite On Magnesia Using Multiharmonic Qcm-D And X-Ray Scattering Methods, Pedro Josue Hernandez Penagos

Open Access Theses & Dissertations

The Earth’s temperature has increased in the last six decades mainly due to the emissions of greenhouse gases, including carbon dioxide (CO2). Mineral looping using magnesium oxide (MgO) is a promising approach for direct air capture (DAC) of CO2 from the atmosphere at the GtCO2/yr scale. The presence of humidity during the carbonation process will lead to a reaction between the MgO and water resulting in magnesium hydroxide formation, Mg(OH)2, growing over the MgO surface forming a shell-like structure. The influence of temperature and relative humidity variation on heterogeneous nucleation and crystal growth kinetics of Mg(OH)2 on MgO is not …

Robust Multivariate Estimation And Inference With The Minimum Density Power Divergence Estimator, Ebenezer Nkum

Open Access Theses & Dissertations

The estimation of the location vector and scatter matrix plays a crucial role in many multivariate statistical methods. However, the classical likelihood-based estimation is greatly influenced by outliers, potentially leading to unreliable decisions. Hence, a fundamental challenge in multivariate statistics is to develop robust alternatives that can maintain performancein the presence of outliers and deviations from the assumed data distribution. Unfortunately, methods with good global robustness often substantially sacrifice efficiency. To address this, we propose the adoption of Minimum Density Power Divergence (MDPD) estimation, a well-established robust technique known for its efficiency and statistical robustness to outliers and model violations. …

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

Open Access Theses & Dissertations

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

Improving Cyber Defense Using Detailed Bayesian Models Of Attacker Reconnaissance., Nazia Sharmin

Open Access Theses & Dissertations

The continued success of cyber-attacks motivates the need for continued innovation in cyber defense. In particular, there is a need for novel methods to mitigate attacker reconnaissance, usually the first stage in planning an attack. One of the few general approaches in this stage is using deception and information manipulation to affect what the attacker can learn about a system or network. Existing work in moving target defense, game-theoretic models of cyber deception/camouflage, and adversarial learning has provided a framework for optimizing deception strategies. However, most of the current literature is based on limited models of how attackers actually perform …

Design Of Engineered Nanomaterials For Pfas Adsorption And Catalytic Degradation From Relevant Environmental Conditions, Sheng Yin

Open Access Theses & Dissertations

Poly- and per-fluoroalkyl substances (PFAS) are a class of artificially made chemicals whose carbon chains are fully or partially fluorinated. Due to their persistent and pervasive distribution and their adverse effects on human health, the removal of PFAS from the environment has been the focus of current research. This project explores the use of engineered nanomaterials for the effective removal of PFAS through various adsorption and catalytic degradation methods. First, a comprehensive review of recent studies highlights the significant potential of various nanomaterials, including carbon-based, non-metal, single-metal, and multi-metal nanomaterials, for PFAS remediation. These materials are evaluated for their performance, …

Upscaling Sapflow Measurements To Footprint Transpiration Estimations In The Jornada Experimental Range, New Mexico, Usa, Habibur R. Howlider

Open Access Theses & Dissertations

This study proposes a new method for computing transpiration across an eddy covariance footprint using field observations of plant sap flow, phytomorphology sampling, uncrewed aerial system (UAS) digital image processing, and eddy covariance micrometeorological measurements. The method is applied to the Jornada Experimental Range, New Mexico where we address three key questions: (1) How do daily summer transpiration rates of Mesquite (Prosopis glandulosa) and Creosote (Larrea tridentate) individuals of different ages compare? (2) How can the contributions of plants of varying sizes and ages be integrated for terrain-wide transpiration estimates? (3) What is the contribution of transpiration to total evapotranspiration …

Evolution Mechanism Of Organic Macromolecular Structure During Lignite Pyrolysis, Ying Shi, Yanming Zhu, Zhenjiang You, Wu Li, Yang Wang, Yu Song

Research outputs 2022 to 2026

Understanding the mechanisms governing coal pyrolysis reactions, particularly in relation to the coal macromolecular structure, is crucial for improving energy efficiency and facilitating the transition of coal into a clean energy source. This study employs cutting-edge techniques, such as High-Resolution Transmission Electron Microscopy (HRTEM) and Thermogravimetric Analysis coupled with Fourier Transform Infrared Spectroscopy and Mass Spectrometry (TG–FTIR–MS), to analyze lignite and its residual solid samples subjected to pyrolysis across a range of temperatures from 300 °C to 1100 °C. The variational characteristics of the macromolecular structure during coal pyrolysis are examined. Utilizing molecular dynamics simulations, we analyze the evolution mechanism …

Variation In Zero Plane Displacement And Roughness Length For Momentum Revisited, Ashvath Singh Kunadi, Richard P. Silberstein, Sally E. Thompson

Research outputs 2022 to 2026

Zero plane displacement height (d0) and momentum roughness length (z0m), describe the aerodynamic characteristics of a vegetated surface. Usually, d0 and z0m are assumed to be constant functions of the physical characteristics of the surface. Prior evidence collected from the literature and our examination of flux tower data show that d0 and z0m vary in time at sites with tree and shrub canopies, but not grasslands. The conventional explanations of these variations are based on linear functions of wind velocity and friction velocity, with little theoretical basis. This study explains the variation in aerodynamic parameters by matching four analytical canopy …

Phthalocyanine-Enabled Technologies For Water Treatment And Disinfection Strategies, Hooralain Bushnaq, Catherine Munro, Sisi Pu, Amir Razmjou, Masoumeh Zargar, Giovanni Palmisano, Srinivas Mettu, Ludovic F. Dumée

Research outputs 2022 to 2026

Water treatment and disinfection are critical factors in ensuring a safe and sustainable water supply. Phthalocyanines (Pcs), a class of versatile and robust organic compounds, have garnered significant attention for their application in various water treatment processes. This review paper offers a groundbreaking investigation of Pc-enabled technologies within the domain of water treatment applications. The core aim of this review is to meticulously analyze the chemical and optical properties of Pcs, elucidate their photosensitization mechanism and establish the crucial connection between their chemical structure and photodynamic efficacy. The various modes of Pcs application in water treatment processes - whether in …

Upscaling Relative Permeability And Capillary Pressure From Digital Core Analysis In Otway Formation: Considering The Order And Size Effects Of Facies, Masoud Aslannezhad, Mohammad Sayyafzadeh, David Tang, Zhenjiang You, Stefan Iglauer, Alireza Keshavarz

Research outputs 2022 to 2026

Digital Core Analysis (DCA) has emerged as a crucial instrument in reservoir characterization in recent times. With the advent of high-resolution micro-CT imaging, it is now possible to visualize the three-dimensional microstructures of in-situ pores and flow patterns within rocks. DCA offers several notable benefits over traditional techniques, such as a higher density of measurements, faster processing times, and the preservation of rock samples. It also demonstrates considerable flexibility with challenging core conditions and can derive numerous parameters from each individual sample. The objective of this work is to utilise DCA data from Otway formation to enhance reservoir characterisation and …

Structure-Function Relationships In Neurodegenerative And Infectious Diseases: Biophysical Characterization Of Rna Secondary Structures By Computational Techniques, Kendy Guarinoni

Electronic Theses and Dissertations

The research described in this dissertation focuses on the investigation of the structure and dynamics of regions of RNA implicated in two diseases: COVID-19 and amyotrophic lateral sclerosis/frontotemporal dementia (ALS/FTD). Both studies sought to create experimentally corroborated models that were used to characterize the structure and dynamics of the C9orf72 repeat expansion and the s2m region in coronaviruses, respectively and provided the foundation for future work. In our work involving the s2m region of SARS-CoV-2, the virus responsible for COVID-19, we determined that the homology modeling approach commonly used to derive atomistic structures when no coordinates are available yields a …

Methods For Improving Low Frequency Selection And Electrode Firing Order In Cochlear Implants, James H. Keen Jr.

LSU New Orleans Theses and Dissertations

The Advanced Bionics cochlear implant devices allocate static frequency bins to electrode channels based on the natural tonotopic organization of the cochlea. These frequency bins are wide and limited, especially in the lower range. Considering that the fundamental tones of the human voice and the primary melodic tones in music are in this lower range, it is important to have accurate representation of this frequency content. Here, adjustments to the frequency bin allocation algorithm used in the crowdsourced CI Hackathon code are made to allow a more accurate representation of the original signal. First, the frequency bins allocated to each …

Context-Aware Self-Supervised Learning Of Whole Slide Images, Milam Aryal, Nasim Yahyasoltani

Computer Science Faculty Research and Publications

Presenting whole slide images (WSIs) as graph will enable a more efficient and accurate learning framework for cancer diagnosis. Due to the fact that a single WSI consists of billions of pixels and there is a lack of vast annotated datasets required for computational pathology, the problem of learning from WSIs using typical deep learning approaches such as convolutional neural network (CNN) is challenging. Additionally, WSIs downsampling may lead to the loss of data that is essential for cancer detection. A novel two-stage learning technique is presented in this work. Since context, such as topological features in the tumor surroundings, …

Performance And Enhanced Efficiency Induced By Cold Plasma On Sapo-34 Membranes For Co2 And Ch4 Mixtures, Fnu Gorky, Vashanti Storr, Grace Jones, Apolo Nambo, Jacek B. Jasinski, Maria L. Carreon

Chemical Engineering Faculty Publications and Presentations

In this study, we investigate the influence of cold-plasma-induced enhanced performance and efficiency of SAPO-34 membranes in the separation of CO₂ and CH₄ mixtures. Placing the herein presented research in a broader context, we aim to address the question of whether cold plasma can significantly impact the membrane performance. We subjected SAPO-34 membranes to plasma mild disturbances and analyzed their performance in separating CO₂ and CH₄. Our findings reveal a notable enhancement in membrane efficiency and sustained performance when exposed to cold plasma. The pulsed plasma separation displayed improved structural integrity, and the experimental results …

Establishing The Importance Of Co-Creation And Self-Efficacy In Creative Collaboration With Artificial Intelligence, Jack Mcguire, David De Cremer, Tim Van De Cruys

Research Collection Lee Kong Chian School Of Business

The emergence of generative AI technologies has led to an increasing number of people collaborating with AI to produce creative works. Across two experimental studies, in which we carefully designed and programmed state-of-the-art human–AI interfaces, we examine how the design of generative AI systems influences human creativity (poetry writing). First, we find that people were most creative when writing a poem on their own, compared to first receiving a poem generated by an AI system and using sophisticated tools to edit it (Study 1). Following this, we demonstrate that this creativity deficit dissipates when people co-create with—not edit—AI and establish …

First Diffusion Course: "The Structure Of Language As A Connection Between Artificial Intelligence, Information And Ethics", Dioneia Monte-Serrat

Journal of Humanistic Mathematics

From August 22nd to November 21st, the first Diffusion Course on “The structure of language as a connection between artificial intelligence, information and ethics” will take place on a Thursday of each month, in Ribeirao Preto, Brazil. You are cordially invited to sign up for in-person classes and join other researchers and students on this course.

7th International Conference On Creative Mathematical Sciences Communication (Cmsc`24), Frances A. Rosamond

Journal of Humanistic Mathematics

The 7th International Creative Mathematical Sciences Communication (CMSC) conference is scheduled for October 2024 in Trier, Germany. Initiated in Darwin, Australia in 2013, CMSC aims to explore novel methods of imparting computational thinking to diverse audiences including non-specialists, modern citizens, and children. Participants from around the world and from various and interdisciplinary disciplines such as science, education, dance, drama, and visual arts convene to exchange ideas, present experimental approaches, and collaborate on engaging children in the exploration of ongoing, unresolved research challenges.

Oh Statistics!, Heather L. Cook

Journal of Humanistic Mathematics

This poem was written about statistics and the usefulness thereof.

Discordium Mathematica - A Symphony In Aleph Minor, Vijay Fafat

Journal of Humanistic Mathematics

How did Mathematics arise? Who created it? Why is it subject to Godel’s Incompleteness Theorems? And what does all this have to do with Coleridge’s poem, “Kubla Khan”, and “The Person from Porlock”? Here is a complete mythology of Mathematics set in an epic poetry format, fusing thoughts and verses from Western religions and Eastern mysticism… Those with immense patience and careful reading shall reap the fruit… (best read on a large screen or in printed form)

Pi: A Perpetual Journey, Ravindra K. Bisht

Journal of Humanistic Mathematics

A brief history of the constant pi is presented with a poetic flavor.