Digital Commons Network^™

Potential Of Individual Upper-Limb Muscles To Contribute To Postural Tremor: Simulations From Neural Drive To Joint Rotation, Spencer A. Baker, Landon J. Beutler, Daniel B. Free, Dario Farina, Steven Knight Charles

Faculty Publications

Background: It is unclear which muscles contribute most to tremor and should therefore be targeted by tremor suppression methods. Previous studies used mathematical models to investigate how upper-limb biomechanics affect muscles’ potential to generate tremor. These investigations yielded principles, but the models included at most only 15 muscles. Here we expand previous models to include 50 upper-limb muscles, simulate tremor propagation, and test the validity of the previously postulated principles. Methods: Tremor propagation was characterized using the gains between tremorogenic neural drive to the 50 muscles (inputs) and tremulous joint rotations in the 7 joint degreesof- freedom (DOF) from shoulder …

Urbanization Impacts Dissolved Organic Matter Concentration And Quality In A Southeastern United States Watershed, Gwendolyn M. Hopper, Erik M. Smith, Jade Dormoy-Boulanger, Claudia R. Benitez-Nelson

Faculty Publications

Blackwater rivers are named due to their exceptionally high concentrations of chromophoric dissolved organic matter (CDOM). They are the predominant lotic ecosystem in the United States Southeastern Coastal Plain, a region experiencing some of the nation’s highest rates of development. This study assessed variability in DOM concentration and composition across forested to urbanized blackwater systems in coastal South Carolina, U.S. Dissolved organic carbon and nutrient concentrations as well as absorbance and fluorescence optical properties reveal that urban sites have lower concentrations, elemental ratios, and less complex DOM. In contrast, forested blackwater sites have concentrations an order of magnitude higher, elevated …

Extragalactic Magnetar Giant Flares: Population Implications, Rates, And Prospects For Gamma-Rays, Gravitational Waves, And Neutrinos, Paz Beniamini, Zorawar Wadiasingh, Aaron Trigg, Cecilia Chirenti, Eric Burns, George Younes, Michela Negro, Jonathan Granot

Faculty Publications

Magnetar giant flares (MGFs) are the most energetic non-catastrophic transients known to originate from stellar objects. The first discovered events were nearby. In recent years, several extragalactic events have been identified, implying an extremely high volumetric rate. We show that future instruments with a sensitivity ≲5 × 10⁻⁹ erg cm⁻² at ∼1 MeV will be dominated by extragalactic MGFs over short gamma-ray bursts (sGRBs). Clear discrimination of MGFs requires intrinsic GRB localization capability to identify host galaxies. As MGFs involve a release of a sizable fraction of the neutron star's magnetic free energy reservoir in a single event, …

Toward Quantifying Interpolation Uncertainty In Set-Line Spacing Hydrographic Surveys, Elias Adediran, Christos Kastrisios, Kim Lowell, Glen Rice, Qi Zhang

Faculty Publications

The oceans remain one of Earth’s last great unknowns, with about 74% still unmapped to modern standards. Consequently, interpolation is employed to create seamless digital bathymetric models (DBMs) from incomplete hydrographic datasets, but this introduces unquantified depth uncertainties. This study aims to estimate and characterize uncertainties arising from set-line spacing hydrographic surveys, which are important for nautical charting, navigational safety, and many other applications. By sampling at different line spacings four complete coverage testbeds that vary in slope and roughness, the study interpolates across entire testbed areas using Spline, Inverse Distance Weighting, and Linear interpolation. The resulting interpolation uncertainties are …

Convergent Close-Coupling Approach To Electron Scattering On H3+ : Scattering Dynamics And Dissociative Processes, Reese K. Horton, Michael V. Pak, Igor Bray, Dmitry V. Fursa

Faculty Publications

Cross sections for electron impact dissociative excitation and ionization in scattering on vibrationally excited levels of the ground electronic state of H₃⁺, D₃⁺, and T₃⁺ are reported in the energy range of 8–1000 eV. Calculations have been performed using a newly developed version of the molecular convergent close-coupling code. Convergence of the cross sections with the size of the projectile partial-wave and close-coupling expansions is examined. Branching ratios and cross sections for the yields of D₂⁺ and D⁺ from dissociative excitation of D₃⁺ are presented and isotope …

Convergent Close-Coupling Approach To Electron Impact Dissociation Of The Polyatomic Molecule H 3 + And Its Isotopologues, Reese K. Horton, Michael V. Pak, Igor Bray, Dmitry V. Fursa

Faculty Publications

Cross sections for electron impact dissociative excitation and ionization in scattering on vibrationally excited levels of the ground electronic state of H₃⁺ and its isotopologues are reported in the energy range of 8 to 1000 eV. Calculations have been performed using a newly developed version of the molecular convergent close-coupling code. Cross sections for total dissociative excitation, ionization yielding atomic fragments such as D⁺, and the total inelastic cross section are presented. Good agreement with available experiments has been demonstrated.

Accelerated Multiobjective Calibration Of Fused Deposition Modeling 3d Printers Using Multitask Bayesian Optimization And Computer Vision, Craig S. Ganitano, Benji Maruyama, Gilbert L. Peterson

Faculty Publications

Proper process parameter calibration is critical to the success of fused deposition modeling (FDM) three-dimensional (3D) printing, but is time-consuming and requires expertise. While existing systems for autonomous calibration have demonstrated success in calibrating for a single objective, users may need to balance multiple conflicting objectives. Herein, an easily deployable, camera-based system for autonomous calibration of FDM printers that optimizes for both part quality and completion time is presented. Autonomous calibration is achieved through a novel, multifaceted computer vision characterization and a multitask learning extension to Bayesian optimization. The system is demonstrated on four popular filament types using two distinct …

Variations In Hawaiian Plume Flux Controlled By Ancientmantle Depletion, Paul Béguelin, Andreas Stracke, Maxim D. Ballmer, Shichen Huang, Michael Wilig, Michael Bizimis

Faculty Publications

Mantle plumes—upwellings of buoyant rock in Earth's mantle—feed hotspot volcanoes such as Hawai‘i. The size of volcanoes along the Hawai‘i–Emperor chain, and thus the magma flux of the Hawaiian plume, has varied over the past 85 million years. Fifteen and two million years ago, rapid bursts in magmatic production led to the emergence of large islands such as Pūhāhonu, Maui Nui and Hawai‘i, but the underlying mechanisms remain enigmatic. Here, we use new radiogenic Ce–Sr–Nd–Hf isotope data of Hawaiian shield lavas to quantify the composition and proportion of the different constituents of the Hawaiian plume over time. We find that …

Orbifolds And Minimal Modular Extensions, Chongying Dong, Siu Hung Ng, Li Ren

Faculty Publications

Let V be a simple vertex operator algebra and G a finite automorphism group of V such that V^G is regular, and the conformal weight of any irreducible g-twisted V-module N for g∈G is nonnegative and is zero if and only if N=V. It is established that if V is holomorphic, then the V^G-module category CV^G is a minimal modular extension of E=Rep(G), and is equivalent to the Drinfeld center Z(VecG^α) as modular tensor categories for some α∈H³(G,S¹) with a canonical embedding of E. Moreover, the collection Mv(E) of equivalence …

Refining A Chain Theorem From Matroids To Internally 4-Connected Graphs, Chanun Lewchalermvongs, Guoli Ding

Faculty Publications

Graph theory and matroid theory are interconnected with matroids providing a way to generalize and analyze the structural and independence properties within graphs. Chain theorems, vital tools in both matroid and graph theory, enable the analysis of matroid structures associated with graphs. In a significant contribution, Chun, Mayhew, and Oxley [2] established a chain theorem for internally 4-connected binary matroids, clarifying the operations involved. Our research builds upon this by specifying the matroid result to internally 4-connected graphs. The primary goal of our research is to refine this chain theorem for matroids into a chain theorem for internally 4-connected graphs, …

A New Error Analysis For Finite Element Methods For Elliptic Neumann Boundary Control Problems With Pointwise Control Constraints, Susanne C. Brenner, Li Yeng Sung

Faculty Publications

We present a new error analysis for finite element methods for a linear-quadratic elliptic optimal control problem with Neumann boundary control and pointwise control constraints. It can be applied to standard finite element methods when the coefficients in the elliptic operator are smooth and also to multiscale finite element methods when the coefficients are rough.

Beyond Water Surface Profiles: A New Iterative Methodology For 2d Model Calibration In Rivers Using Velocity Data From Multiple Cross-Sections, Fabian Rivera-Trejo, Gabriel Soto-Cortes, Kory M. Konsoer, Eddy J. Langendoen, Gaston Priego-Hernandez

Faculty Publications

Observed longitudinal water-surface profiles are commonly used to calibrate river hydrodynamic models, relying on assumptions of lateral uniformity in water surface elevation and velocity distribution. While suitable for 1D models, this approach has limitations in regard to 2D model calibration. When 2D flow measurements are available, a more robust quantitative evaluation is necessary to assess model accuracy. This study introduces a novel methodology to improve 2D model calibration and evaluate performance. High-resolution bathymetric and hydrodynamic data collected with a multibeam echosounder (MBES) and acoustic Doppler current profiler (ADCP) were aligned to compare observed and simulated flow velocities at matching spatial …

Childhood Sexual Trauma, Substance Use, And Antiretroviral Therapy Adherence Among Older Adults Living With Hiv: A Mediational Analysis, Monique J. Brown, Josie Zhang, Prince Nii Ossah Addo, Amandeep Kaur, Daniel Amoatika, Elizabeth L. Crouch Ph.D., Steven A. Cohen

Faculty Publications

Childhood sexual abuse (CSA) is linked to substance use and lower antiretroviral therapy (ART) adherence. However, studies examining the mediational role of substance use between CSA and ART adherence are lacking. Therefore, the aim of this study was to determine the potential mediational role of substance use between CSA and ART adherence among older adults living with HIV (OALH) (n = 91). Mediation analyses assessed the direct and indirect relationships between CSA, substance use, and ART adherence. Statistically significant differences existed in substance use by gender (male vs. female: 12.3 vs. 9.97) and ART adherence by race (Black vs. …

Pilot Study: Initial Investigation Suggests Differences In Emt-Associated Gene Expression In Breast Tumor Regions, Kylie L. King, Hamed Abdollahi, Zoe Dinkel, Alannah Akins, Homayoun Valafar, Heather Dunn

Faculty Publications

Triple negative breast cancer (TNBC) is the most aggressive subtype and disproportionately affects African American women. The development of breast cancer is highly associated with interactions between tumor cells and the extracellular matrix (ECM), and recent research suggests that cellular components of the ECM vary between racial groups. This pilot study aimed to evaluate gene expression in TNBC samples from patients who identified as African American and Caucasian using traditional statistical methods and emerging Machine Learning (ML) approaches. ML enables the analysis of complex datasets and the extraction of useful information from small datasets. We selected four regions of interest …

Deep Learning-Based Superconductivity Prediction And Experimental Tests, Daniel Kaplan, Adam Zheng, Joanna Blawat, Rongying Jin, Robert J. Cava, Viktor Oudovenko, Gabriel Kotliar, Anirvan M. Sengupta, Weiwei Xie

Faculty Publications

The discovery of novel superconducting materials is a long-standing challenge in materials science, with a wealth of potential for applications in energy, transportation and computing. Recent advances in artificial intelligence (AI) have enabled expediting the search for new materials by efficiently utilizing vast materials databases. In this study, we developed an approach based on deep learning (DL) to predict new superconducting materials. We have synthesized a compound derived from our DL network and confirmed its superconducting properties in agreement with our prediction. Our approach is also compared to previous work based on random forests (RFs). In particular, RFs require knowledge …

Associations Between Social Determinants Of Health And Mental Health Disorders Among U.S. Population: A Cross-Sectional Study, S. Tanarsuwongkul

Faculty Publications

Aims

The impact of social determinants of health (SDOH) on mental health is increasingly realized. A comprehensive study examining the associations of SDOH with mental health disorders has yet to be accomplished. This study evaluated the associations between five domains of SDOH and the SDOH summary score and mental health disorders in the United States.

Methods

We analyzed data from a diverse group of participants enrolled in the All of Us research programme, a research programme to gather data from one million people living in the United States, in a cross-sectional design. The primary exposure was SDOH based on Healthy …

Transfer Learning For Thickener Control, Samuel Arce Munoz, John Hedengren

Faculty Publications

Thickener control is a key area of focus in the minerals processing industry, particularly due to its crucial role in water recovery, which is essential for sustainable resource management. The highly nonlinear nature of thickener dynamics presents significant challenges in modeling and optimization, making it a strong candidate for advanced surrogate modeling techniques. However, traditional data-driven approaches often require extensive datasets, which are frequently unavailable, especially in new plants or unexplored operational domains. Developing data-driven models without enough data representative of the dynamics of the system could result in incorrect predictions and consequently, unstable response of the controller. This paper …

Between Pedagogical Content Knowledge And Confidence: A Case Study Of Pronunciation Training And Teacher Preparation, Lena Barrantes-Elizondo, Joshua Gordon

Faculty Publications

While many teachers do not feel confident teaching pronunciation because of limited preparation in different areas, research has demonstrated positive effects of training in pronunciation pedagogy, as teachers who receive such training develop cognitions (i.e., knowledge, beliefs, thoughts, actions) that align with current tenets of pronunciation pedagogy. Drawing on this assertion, this paper reports the results of a qualitative case study with five pre-service teaching-English-to-speakers-of-other-languages (TESOL) teachers enrolled in a pedagogical pronunciation course as part of their teacher training program. The study’s main purpose was to understand the role of training in developing content knowledge (CK) and pedagogical content knowledge …

Analysis Of Phytochemicals In Watercress Leaves Using Chromatographic, Spectroscopic And In-Vitro Approaches, Bidisha Roy Sengupta

Faculty Publications

No abstract provided.

Biofilm-Based Biomonitoring Of Treated Wastewater Using Bacillus Thuringiensis: Toward Sustainable Water Reuse, Bidisha Roy Sengupta, Kefa K. Onchoke, Olabisi O. Ogunlewe, Robert Friedfeld

Faculty Publications

No abstract provided.

Reimagining Compliance: Explainable Ai Models For Financial Regulatory Audits, Hrishikesh Desai

Faculty Publications

This chapter develops an analytical model for Explainable AI (XAI) designed to support major types of banking regulatory compliance audits. Financial institutions increasingly rely on AI for efficiency in compliance tasks, but the opacity of complex models creates challenges in meeting regulatory transparency requirements. The proposed mathematical framework incorporates explainability as a quantifiable constraint in the optimization of AI models across five critical audit categories: CAMELS examinations, BSA/AML compliance, Consumer Compliance, IT Audits, and Internal Audits. By quantifying explainability through information- theoretic measures and Shapley values, the model balances predictive performance with regulatory requirements. The methodology is validated through a …

A Big Data Approach To Modelling Urban Population Density Functions: From Monocentricity To Polycentricity, Cehong Luo, Yujie Hu, Fahui Wang

Faculty Publications

Urban studies have a long tradition of examining the regularity of urban structure by modelling urban population density functions and probing the theoretical or behavioural foundation behind it. Previous studies commonly used census data in areal units such as census tracts or census block groups, which varied a great deal in area size and shape and led to the zonal and scale effects, commonly referred to as the modifiable areal unit problem (MAUP). This study uses big data of individual vehicle trips in Tampa, Florida, to define the precise population and employment distribution locations, and then aggregates them with uniform …

Convergence Of The Planewave Approximations For Quantum Incommensurate Systems, Ting Wang, Huajie Chen, Aihui Zhou, Yuzhi Zhou, Daniel Massatt

Faculty Publications

Incommensurate structures come from stacking the single layers of low dimensional materials on top of one another with misalignment such as a twist in orientation. While these structures are of significant physical interest, they pose many theoretical challenges due to the loss of periodicity. This paper studies the physical observables of continuum Schrodinger operators for incommensurate systems. We characterize the density of states and local density of states in real and reciprocal spaces, and develop novel numerical methods to approximate them. In particular, we (i) justify the thermodynamic limit of the density of states and local density of states via …

The Holomorphic Discrete Series Contribution To The Generalized Whittaker Plancherel Formula Ii. Non-Tube Type Groups, Jan Frahm, Gestur Ólafsson, Bent Ørsted

Faculty Publications

For every simple Hermitian Lie group G, we consider a certain maximal parabolic subgroup whose unipotent radical N is either abelian (if G is of tube type) or two-step nilpotent (if G is of non-tube type). By the generalized Whittaker Plancherel formula we mean the Plancherel decomposition of L²(G/N,ω), the space of square-integrable sections of the homogeneous vector bundle over G/N associated with an irreducible unitary representation ω of N. Assuming that the central character of ω is contained in a certain cone, we construct embeddings of all holomorphic discrete series representations of G into L²(G/N,ω) …

Realization Of Unitary Representations Of The Lorentz Group On De Sitter Space, Jan Frahm, Karl Hermann Neeb, Gestur Ólafsson

Faculty Publications

This paper builds on our previous work in which we showed that, for all connected semisimple linear Lie groups G acting on a non-compactly causal symmetric space M=G/H, every irreducible unitary representation of G can be realized by boundary value maps of holomorphic extensions in distributional sections of a vector bundle over M. In the present paper we discuss this procedure for the connected Lorentz group G=SO1,d(R)e acting on de Sitter space M=dS^d. We show in particular that the previously constructed nets of real subspaces satisfy the locality condition. Following ideas of Bros and Moschella from the 1990’s, …

All-Electron Molecular Tunnel Ionization Based On The Weak-Field Asymptotic Theory In The Integral Representation, Imam S. Wahyutama, Denawakage D. Jayasinghe, François Mauger, Kenneth Lopata, Kenneth J. Schafer

Faculty Publications

Tunnel ionization (TI) underlies many important ultrafast processes, such as high-harmonic generation and strong-field ionization. Among the existing theories for TI, many-electron weak-field asymptotic theory (ME-WFAT) is by design capable of accurately treating many-electron effects in TI. An earlier version of ME-WFAT relied on an accurate representation of the asymptotic tail of the orbitals, which hindered its implementation in Gaussian-basis-set-based quantum chemistry programs. In this work, we reformulate ME-WFAT in the integral representation, which makes the quality of the asymptotic tail much less critical, hence greatly facilitating its implementation in standard quantum chemistry packages. The integral reformulation introduced here is …

Maximum Spread Of Ks,T-Minor-Free Graphs, William Linz, Linyuan Lu, Zhiyu Wang

Faculty Publications

The spread of a graph G is the difference between the largest and smallest eigenvalue of the adjacency matrix of G. In this paper, we consider the family of graphs which contain no Ks,t-minor. We show that for any t ≥ s ≥ 2 and sufficiently large n, there is an integer ξt such that the extremal n-vertex Ks,t-minor-free graph attaining the maximum spread is the graph obtained by joining a graph L on (s −1) vertices to the disjoint union of (Formula Presented) copies of Kt and (Formula Presented) isolated vertices. Furthermore, we give an explicit formula for ξt …

Hope For Louisiana’S Coast: From Catastrophic Loss To Transient Gain, Richard Condrey, Brian D. Marx, Frank Saforo, Rudy Bartels

Faculty Publications

Louisiana’s fifty-billion-dollar coastal restoration plan relies on selected interpretations of a small dataset of coastwide land measurements. In the 1990’s, the plan’s founders used a mathematically impossible interpretation of an improbable manipulation of the initial (1932-1990) dataset to justify their misconceptions regarding natural conditions; delta-switching; and a failing, 60-year restoration goal. In 2017, the dataset was updated to 2016 and used to suggest that land loss had slowed to -28 km2/yr (-1 football field/100 min) since 2010. We find that the dataset does not support this suggestion. Rather, we find the dataset supports our hypothesis that increasing precipitation in the …

Durable Oxyfluoride Waste Forms For Salt Wastes From Molten Salt Reactors, Alevtina A. Maksimova, Jake W. Amoroso, Matthew Page, Gregory Morrison, Hans Conrad Zur Loye

Faculty Publications

Molten salt reactors (MSRs) are promising technology to replace traditional light and heavy water reactors in the near future. Waste management for MSRs, however, remains a pressing concern that needs to be resolved prior to realizing deployment of MSRs. Specifically, the generated salt waste needs to be safely sequestered, a task made difficult by the high solubility of the salt waste that can cause the release of radionuclides into the environment. This work demonstrates a new approach to immobilize multiple fluoride salts into a single waste form by converting highly-soluble fluorides to durable and stable oxyfluorides. Notably, we report a …

Temporal Network Analysis Of Comorbidities Among People With Hiv In South Carolina, Yunqing Ma, Matthew Lohman Ph.D., Monique J. Brown Ph.D., Mph, Yichen Li, Xiaoming Li Ph.D., Bankole Olatosi Ph.D., Jiajia Zhang Ph.D.

Faculty Publications

Introduction: People with HIV experience a high rate of comorbidities that can complicate their health outcomes. Understanding the prevalence, interrelationships and temporal development of these comorbidities is crucial for improving health management and quality of life for people with HIV. Methods: We used a population-based cohort extracted from statewide electronic health record (EHR) data in South Carolina (SC), including 18 649 people with HIV who survived at least 1 year after HIV diagnosis between January 1, 2005, and December 31, 2020. Comorbidities and organ systems were classified using ICD-10 codes. Network analysis was performed to assess the closeness centrality among …