Physical Sciences and Mathematics Commons^™

How Noise Thresholds Affect The Information Content Of Stellar Flare Sequences, Elmer C. Rivera, Jay R. Johnson, Jonathan Homan, Simon Wing

Faculty Publications

Systems that exhibit discrete dynamics can be well described and reconstructed by considering the set of time intervals between the discrete events of the system. The Kepler satellite has cataloged light curves for many Sun-like stars, and these light curves show strong bursts in intensity that are associated with stellar flares. The waiting time between these flares describes the fundamental dynamics of the stars and is driven by physical processes, such as flux emergence. While it is rather straightforward to identify large flares, the identification of weaker flares can be challenging because of the presence of noise. A common practice …

Search For Rare Decays B+→D (*)+SΗ, D (*)+ SK̅, D+ Η, And D+ K0, M. Kumar, V. Bhardwaj, K. Lalwani, I. Adachi

Faculty Publications

We present a study of rare decay modes B+→D⁺_Sh⁰, B+→D^*+_S h⁰, and B+→D+h⁰, where h⁰ denotes the neutral meson η or K⁰, using a data sample of (772±10)×10⁶   BB̅ events produced at the Υ(4S) resonance. The data were collected by the Belle detector operating at the asymmetric-energy KEKB collider. We find no evidence for these decays, so we set upper limits at the 90% confidence level on the branching fractions of B+→D⁺ _S h⁰, D^*+ _S h⁰, …

Three- And Four-Point Functions In Cpt -Even Lorentz-Violating Scalar Qed, Brett Altschul, L. C.T. Brito, J. C.C. Felipe, S. Karki, A. C. Lehum, A. Yu Petrov

Faculty Publications

The renormalization of quantum field theories usually assumes Lorentz and gauge symmetries, besides the general restrictions imposed by unitarity and causality. However, the set of renormalizable theories can be enlarged by relaxing some of these assumptions. In this work, we consider the particular case of a CPT-preserving but Lorentz-breaking extension of scalar QED. For this theory, we calculate the one-loop radiative corrections to the three- and four-point scalar-vector vertex functions, at the lowest order in the Lorentz-violation parameters, and we explicitly verify that the resulting low-energy effective action is compatible with the usual gauge invariance requirements. With these results, we …

Multicollinearity Applied Stepwise Stochastic Imputation: A Large Dataset Imputation Through Correlation‑Based Regression, Benjamin D. Leiby, Darryl K. Ahner

Faculty Publications

This paper presents a stochastic imputation approach for large datasets using a correlation selection methodology when preferred commercial packages struggle to iterate due to numerical problems. A variable range-based guard rail modification is proposed that benefits the convergence rate of data elements while simultaneously providing increased confidence in the plausibility of the imputations. A large country conflict dataset motivates the search to impute missing values well over a common threshold of 20% missingness. The Multicollinearity Applied Stepwise Stochastic imputation methodology (MASS-impute) capitalizes on correlation between variables within the dataset and uses model residuals to estimate unknown values. Examination of the …

Evidence Of Sea Level Rise At The Peruvian Coast (1942-2019), Bismarck Jigena-Antelo, Carol Estrada-Ludeña, Stephan Howden, Wilmer Rey, Jorge Paz-Acosta, Patricia Lopez-García, Eric Salazar-Rodriguez, Nieves Endrina, Juan J. Muñoz-Pérez

Faculty Publications

The present work aims to analyze the variability of the sea level of the Peruvian coast with time series over a long observation period (Seventy-eight years, from 1942 to 2019). Data came from the Talara, Callao and Matarani tide gauge stations located at the north, center and south of the coast. Variations of sea level as well as air and seawater surface temperature were analyzed. Among the different scenarios studied, a sea level rise of 6.79, 4.21 and 5.16 mm/year for Talara, Callao and Matarani, respectively was found during the 1979–1997 nodal cycle. However, these results decreased significantly during the …

Measurement Of Proton Light Yield Of Water-Based Liquid Scintillator, E. J. Callaghan, B. L. Goldblum, J. A. Brown, T. A. Laplace, Juan J. Manfredi, M. Yeh, G. D. Orebi Gann

Faculty Publications

The proton light yield of liquid scintillators is an important property in the context of their use in large-scale neutrino experiments, with direct implications for neutrino-proton scattering measurements and the discrimination of fast neutrons from inverse β-decay coincidence signals. This work presents the first measurement of the proton light yield of a water-based liquid scintillator (WbLS) formulated from 5% linear alkyl benzene (LAB), at energies below 20 MeV, as well as a measurement of the proton light yield of a pure LAB + 2 g/L 2,5-diphenyloxazole (PPO) mixture (LABPPO). The measurements were performed using a double time-of-flight method and a …

Emotion Classification Of Indonesian Tweets Using Bidirectional Lstm, Aaron K. Glenn, Phillip M. Lacasse, Bruce A. Cox

Faculty Publications

Emotion classification can be a powerful tool to derive narratives from social media data. Traditional machine learning models that perform emotion classification on Indonesian Twitter data exist but rely on closed-source features. Recurrent neural networks can meet or exceed the performance of state-of-the-art traditional machine learning techniques using exclusively open-source data and models. Specifically, these results show that recurrent neural network variants can produce more than an 8% gain in accuracy in comparison with logistic regression and SVM techniques and a 15% gain over random forest when using FastText embeddings. This research found a statistical significance in the performance of …

Reliable Detection Of Location Spoofing And Variation Attacks, Chiho Kim, Sang-Yoon Chang, Dongeun Lee, Jinoh Kim

Faculty Publications

Location spoofing is a critical attack in mobile communications. While several previous studies investigated the detection of location spoofing attacks, they are limited in their performance and lack the consideration of emerging attack variations. In this paper, we present a data-driven methodology for the reliable detection of location spoofing and its variations. To enhance the performance, we introduce and utilize a new set of features, which is differential in nature and enables the checking of the mobility constraints and inconsistency. Our comparison study with the previous research shows that the presented scheme using the new features significantly improves the accuracy …

Measurement Of The VE- Nucleus Charged-Current Double-Differential Cross Section At 〈EV⟩ = 2.4 Gev Using Nova, M. A. Acero, P. Adamson, L. Aliaga, N. Anfimov, A. Antoshkin, E. Arrieta-Diaz, L. Asquith, A. Aurisano, A. Back, M. Biard, N. Balashov, P. Baldi, B. A. Bambah, S. Bashar, K. Bays, R. Bernstein, V. Bhatnagar, D. Bhattarai, B. Bhuyan, J. Bian, Roberto Petti, Et. Al.

Faculty Publications

The inclusive electron neutrino charged-current cross section is measured in the NOvA near detector using 8.02×10²⁰ protons-on-target in the NuMI beam. The sample of GeV electron neutrino interactions is the largest analyzed to date and is limited by ≃17% systematic rather than the ≃7.4% statistical uncertainties. The double-differential cross section in final-state electron energy and angle is presented for the first time, together with the single-differential dependence on Q² (squared four-momentum transfer) and energy, in the range 1  GeV≤E_νGENIE, GiBUU, NEUT, and NuWro neutrino event generators. The data do not strongly favor a model over the …

Drone Detection Using Yolov5, Burchan Aydin, Subroto Singha

Faculty Publications

The rapidly increasing number of drones in the national airspace, including those for recreational and commercial applications, has raised concerns regarding misuse. Autonomous drone detection systems offer a probable solution to overcoming the issue of potential drone misuse, such as drug smuggling, violating people’s privacy, etc. Detecting drones can be difficult, due to similar objects in the sky, such as airplanes and birds. In addition, automated drone detection systems need to be trained with ample amounts of data to provide high accuracy. Real-time detection is also necessary, but this requires highly configured devices such as a graphical processing unit (GPU). …

Fluvial Flood Losses In The Contiguous United States Under Climate Change, M.M. Rashid, T. Wahl, G. Villarini, A. Sharma

Faculty Publications

Flooding is one of the most devastating natural disasters causing significant economic losses. One of the dominant drivers of flood losses is heavy precipitation, with other contributing factors such as built environments and socio-economic conditions superimposed to it. To better understand the risk profile associated with this hazard, we develop probabilistic models to quantify the future likelihood of fluvial flood-related property damage exceeding a critical threshold (i.e., high property damage) at the state level across the conterminous United States. The model is conditioned on indicators representing heavy precipitation amount and frequency derived from observed and downscaled precipitation. The likelihood of …

Remote Internal Wave Forcing Of Regional Ocean Simulations Near The U.S. West Coast, Oladeji Q. Siyanbola, Maarten C. Buijsman, Audrey Delpech, Lionel Renault, Roy Barkan, Jay F. Shriver, Brian K. Arbic, James C. Mcwilliams

Faculty Publications

Low mode internal waves are able to propagate across ocean basins and modulate ocean dynamics thousands of kilometers away from their generation sites. In this study, the impact of remotely generated internal waves on the internal wave energetics near the U.S. West Coast is investigated with realistically forced regional ocean simulations. At the open boundaries, we impose high-frequency oceanic state variables obtained from a global ocean simulation with realistic atmospheric and astronomical tidal forcing. We use the Discrete Fourier Transform (DFT) technique in separating ingoing and outgoing internal tide energy fluxes at the open boundaries in order to quantify internal …

Soil Organic Matter Diagenetic State Informs Boreal Forest Ecosystem Feedbacks To Climate Change, Allison N. Myers-Pigg, Karl Kaiser, Ronald Benner, Susan E. Ziegler

Faculty Publications

The fate of soil organic carbon (SOC) in boreal forests is dependent on the integrative ecosystem response to climate change. For example, boreal forest productivity is often nitrogen (N) limited, and climate warming can enhance N cycling and primary productivity. However, the net effect of this feedback on the SOC reservoir and its longevity with climate change remain unclear due to difficulty in detecting small differences between large and variable carbon (C) fluxes needed to determine net changes in soil reservoirs. The diagenetic state of SOC – resulting from the physicochemical and biological transformations that alter the original biomolecular composition …

Soil Microbial Legacies Influence Freeze–Thaw Responses Of Soil, Melissa A. Pastore, Aimee T. Classen, Marie E. English, Serita D. Frey, Melissa A. Knorr, Karin Rand, E. Carol Adair

Faculty Publications

Warmer winters with less snowfall are increasing the frequency of soil freeze–thaw cycles across temperate regions. Soil microbial responses to freeze–thaw cycles vary and some of this variation may be explained by microbial conditioning to prior winter conditions, yet such linkages remain largely unexplored. We investigated how differences in temperature history influenced microbial community composition and activity in response to freeze–thaw cycles.

We collected soil microbial communities that developed under colder (high elevation) and warmer (low elevation) temperature regimes in spruce-fir forests, then added each of these soil microbial communities to a sterile bulk-soil in a laboratory microcosm experiment. The …

Data Augmentation For Neutron Spectrum Unfolding With Neural Networks, James Mcgreivy, Juan J. Manfredi, Daniel Siefman

Faculty Publications

Neural networks require a large quantity of training spectra and detector responses in order to learn to solve the inverse problem of neutron spectrum unfolding. In addition, due to the under-determined nature of unfolding, non-physical spectra which would not be encountered in usage should not be included in the training set. While physically realistic training spectra are commonly determined experimentally or generated through Monte Carlo simulation, this can become prohibitively expensive when considering the quantity of spectra needed to effectively train an unfolding network. In this paper, we present three algorithms for the generation of large quantities of realistic and …

Accelerating A Software Defined Satnav Receiver Using Multiple Parallel Processing Schemes, Logan Reich, Sanjeev Gunawardena, Michael Braasch

Faculty Publications

Excerpt: Satnav SDRs present many benefits in terms of flexibility and configurability. However, due to the high bandwidth signals involved in satnav SDR processing, the software must be highly optimized for the host platform in order to achieve acceptable runtimes. Modules such as sample decoding, carrier replica generation, carrier wipeoff, and correlation are computationally intensive components that benefit from accelerations.

Machine Learning Prediction Of Dod Personal Property Shipment Costs, Tiffany Tucker, Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

U.S. Department of Defense (DoD) personal property moves account for 15% of all domestic and international moves - accurate prediction of their cost could draw attention to outlier shipments and improve budget planning. In this work 136,140 shipments between 13 personal property shipment hubs from April 2022 through March 2023 with a total cost of $1.6B were analyzed. Shipment cost was predicted using recursive feature elimination on linear regression and XGBoost algorithms, as well as through neural network hyperparameter sweeps. Modeling was repeated after removing 28 features related to shipment hub location and branch of service to examine their influence …

Atmospheric Meteorological Effects On Forecasting Daily Lightning Occurrence At Cape Canaveral Space Force Station, Jon Saul, Torrey J. Wagner, Eric G. Mbonimpa, Brent T. Langhals

Faculty Publications

As the Cape Canaveral Space Force Station and Kennedy Space Center increase their launch rate, any process that could assist in the automation of the currently-manual lightning forecast would be valuable. This work examines the possibility of machine-learning assistance with the daily lighting forecast which is produced by the 45th Weather Squadron. A dataset consisting of 34 lightning, pressure, temperature and windspeed measurements taken from 334 daily weather balloon (rawinsonde) launches in the timeframe 2012-2021 was examined. Models were created using recursive feature elimination on logistic regression and XGClassifier algorithms, as well as Bayesian and bandit optimization of neural network …

A Mathematical Modeling Technique To Understand The Role Of Decoy Receptors In Ligand‑Receptor Interaction, Subrata Dey, Aditi Ghosh, Malay Banerjee

Faculty Publications

The ligand‑receptor interaction is fundamental to many cellular processes in eukaryotic cells such as cell migration, proliferation, adhesion, signaling and so on. Cell migration is a central process in the development of organisms. Receptor induced chemo‑tactic sensitivity plays an important role in cell migration. However, recently some receptors identified as decoy receptors, obstruct some mechanisms of certain regular receptors. DcR3 is one such important decoy receptor, generally found in glioma cell, RCC cell and many various malignant cells which obstruct some mechanism including apoptosis cell‑signaling, cell inflammation, cell migration. The goal of our work is to mathematically formulate ligand‑receptor interaction …

To The Moon: Strategic Competition In The Cislunar Region, Shawn M. Willis

Faculty Publications

China’s advancing space capabilities, particularly in the cislunar region, call for increased cislunar space domain awareness on the part of the United States. US military and civilian decisionmakers must take into account the full scope of China’s cislunar plans and capabilities as the military builds space strategies and future force designs. The United States must also increase near-term investments that support more robust cislunar space domain awareness.

The Behavior Of Partially Coherent Twisted Space-Time Beams In Atmospheric Turbulence, Milo W. Hyde Iv

Faculty Publications

We study how atmospheric turbulence affects twisted space-time beams, which are non-stationary random optical fields whose space and time dimensions are coupled with a stochastic twist. Applying the extended Huygens–Fresnel principle, we derive the mutual coherence function of a twisted space-time beam after propagating a distance z through atmospheric turbulence of arbitrary strength. We specialize the result to derive the ensemble-averaged irradiance and discuss how turbulence affects the beam’s spatial size, pulse width, and space-time twist. Lastly, we generate, in simulation, twisted space-time beam field realizations and propagate them through atmospheric phase screens to validate our analysis.

Nitrous Oxide Production And Isotopomer Composition By Fungi Isolated From Salt Marsh Sediments, Birch Maxwell Lazo-Murphy, Samantha Larson, Sydney Staines, Heather Bruck, Julianne Mchenry, Annie Bourbonnais, Xuefeng Peng

Faculty Publications

The emissions of nitrous oxide (N₂O), a potent greenhouse gas and ozone-depleting agent, have been steadily increasing from coastal environments, such as salt marsh sediments, as a result of anthropogenic nutrient loading. Biotic processes, including nitrification and denitrification, are the largest sources of N₂O from salt marsh sediments. While it is assumed that the bulk of N₂O from salt marsh sediment is produced by nitrification and bacterial denitrification, recent reports suggest fungal denitrification may contribute significantly. In this study, four fungi capable of growth under sulfidic conditions were isolated from salt marsh sediments in …

Editorial: Sustainability Of Physical Activity Interventions And Public Health, Erica Y. Lau, Maureen C. Ashe, Sharon E. Taverno, Russell R. Pate Ph.D.

Faculty Publications

No abstract provided.

Association Of Chlorhexidine Use And Scaling And Root Planing With Birth Outcomes In Pregnant Individuals With Periodontitis: A Systematic Review And Meta-Analysis, Maxwell Akonde, Rajat Das Gupta, Maxwell Akonde, Mark Reynolds, Stephanie Smith-Warner, Jihong Liu Sc.D., Fouzia Tarannum, James Beck, Donald Mattison

Faculty Publications

Importance Chlorhexidine mouthwash enhances treatment effects of conventional periodontal treatment, but data on chlorhexidine as a source of heterogeneity in meta-analyses assessing the treatment of maternal periodontitis in association with birth outcomes are lacking.

Objective To assess possible heterogeneity by chlorhexidine use in randomized clinical trials (RCTs) evaluating the effect of periodontal treatment (ie, scaling and root planing [SRP]) vs no treatment on birth outcomes.

Data Sources Cochrane Oral Health’s Trials Register, Cochrane Pregnancy and Childbirth’s Trials Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE Ovid, Embase Ovid, LILACS BIREME Virtual Health Library (Latin American and Caribbean Health Science …

Association Of Chlorhexidine Use And Scaling And Root Planing With Birth Outcomes In Pregnant Individuals With Periodontitis: A Systematic Review And Meta-Analysis, Anwar T. Nerchant, Rajat Das Gupta, Maxwell Akonde, Mark Reynolds, Stephanie Smith-Warner, Jihong Liu, Fouzia Tarannum, James Beck, Donald Mattison

Faculty Publications

Importance Chlorhexidine mouthwash enhances treatment effects of conventional periodontal treatment, but data on chlorhexidine as a source of heterogeneity in meta-analyses assessing the treatment of maternal periodontitis in association with birth outcomes are lacking.

Objective To assess possible heterogeneity by chlorhexidine use in randomized clinical trials (RCTs) evaluating the effect of periodontal treatment (ie, scaling and root planing [SRP]) vs no treatment on birth outcomes.

Data Sources Cochrane Oral Health’s Trials Register, Cochrane Pregnancy and Childbirth’s Trials Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE Ovid, Embase Ovid, LILACS BIREME Virtual Health Library (Latin American and Caribbean Health Science …

A Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered Model To Predict Demand For Covid-19 Inpatient Care In A Large Healthcare System, Stella Coker Watson Self Ph.D., Ms, Rongjie Huang, Shrujan Amin, Joseph Ewing, Carolina Rudisill, Alexander C. Mclain Ph.D.

Faculty Publications

The COVID-19 pandemic has strained healthcare systems in many parts of the United States. During the early months of the pandemic, there was substantial uncertainty about whether the large number of COVID-19 patients requiring hospitalization would exceed healthcare system capacity. This uncertainty created an urgent need to accurately predict the number of COVID-19 patients that would require inpatient and ventilator care at the local level. As the pandemic progressed, many healthcare systems relied on such predictions to prepare for COVID-19 surges and to make decisions regarding staffing, the discontinuation of elective procedures, and the amount of personal protective equipment (PPE) …

A Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered Model To Predict Demand For Covid-19 Inpatient Care In A Large Healthcare System, Stella Coker Watson Self Ph.D., Ms, Rongjie Huang, Shrujan Amin, Joseph Ewing, Caroline Rudisill, Alexander C. Mclain

Faculty Publications

The COVID-19 pandemic has strained healthcare systems in many parts of the United States. During the early months of the pandemic, there was substantial uncertainty about whether the large number of COVID-19 patients requiring hospitalization would exceed healthcare system capacity. This uncertainty created an urgent need to accurately predict the number of COVID-19 patients that would require inpatient and ventilator care at the local level. As the pandemic progressed, many healthcare systems relied on such predictions to prepare for COVID-19 surges and to make decisions regarding staffing, the discontinuation of elective procedures, and the amount of personal protective equipment (PPE) …

Survival Of Epithelial Ovarian Cancer In Black Women: A Society To Cell Approach In The African American Cancer Epidemiology Study (Aaces), Joellen M. Schildkraut, Courtney Johnson, Lauren F. Dempsey, Bo Qin, Paul Terry, Maxwell Akonde, Edward S. Peters, Hannah Mandle, Michele L. Cote, Lauren Peres, Patricia Moorman, Ann G. Schwartz, Micheal Epstein, Jeffrey Marks, Melissa Bondy, Andrew B. Lawson, Anthony Alberg, Elisa V. Bandera

Faculty Publications

Purpose

The causes for the survival disparity among Black women with epithelial ovarian cancer (EOC) are likely multi-factorial. Here we describe the African American Cancer Epidemiology Study (AACES), the largest cohort of Black women with EOC.

Methods

AACES phase 2 (enrolled 2020 onward) is a multi-site, population-based study focused on overall survival (OS) of EOC. Rapid case ascertainment is used in ongoing patient recruitment in eight U.S. states, both northern and southern. Data collection is composed of a survey, biospecimens, and medical record abstraction. Results characterizing the survival experience of the phase 1 study population (enrolled 2010–2015) are presented.

Results …

Uniqueness Of Steady State Positive Solutions To A General Elliptic System With Dirichlet Boundary Conditions, Joon Hyuk Kang

Faculty Publications

The purpose of this paper is to give conditions for the uniqueness of positive solution to a rather general type of elliptic system of the Dirichlet problem on a bounded domain Ω in Rⁿ. Also considered are the effects of perturbations on the coexistence state and uniqueness.

Predicted Episode Of Submarine Groundwater Discharge Onto The South Carolina, Usa, Continental Shelf And Its Effect On Dissolved Oxygen, Wilson S. Moore, Jacob Vincent, James L. Pickney, Alicia M. Wilson

Faculty Publications

Submarine groundwater discharge (SGD) may directly influence the dissolved oxygen (DO) content of coastal bottom waters. Here, we report a predicted episode of enhanced SGD that caused low DO concentrations on the South Carolina continental shelf. The prediction model linked episodes of SGD to upwelling-favorable winds. The data revealed these waters were a factor of 2–6 higher in ²²⁶Ra and ²²⁸Ra compared to typical bottom water values and were significantly depleted in DO (<130 μM). The tight ²²⁸Ra:²²⁶Ra correlation of these data was similar to values during a strong hypoxic event off SC in 2012. Water ages from …