Digital Commons Network^™

War, Wounds, And Strategy: Patient Movement Lessons From The World Wars For Great Power Competition, Phillip R. Jenkins

Faculty Publications

This thesis examines the evolution of the U.S. military's patient movement system during World War I and World War II to evaluate how well it may perform under the conditions of future large-scale combat operations. It asks whether the United States can move, treat, and sustain wounded personnel at the scale and pace required to preserve combat power in a prolonged, high-intensity conflict. Using detailed case studies of the Meuse-Argonne Offensive and the Battle of the Bulge, the analysis focuses on how transportation platforms, organizational structure, and standard operating procedures (SOPs) shaped patient movement under conditions of attrition, disruption, and …

Enhanced Nuclear Binding Near The Proton Drip Line Opens Possible Bypass Of The 64Ge Rapid Proton Capture Process Waiting Point, Zachary Meisel, W.-J Ong, J. S. Ranhawa

Faculty Publications

We performed astrophysics model calculations with updated nuclear data to identify a possible bypass of the ⁶⁴Ge waiting point, a defining feature of the rapid proton capture (rp) process that powers type I X-ray bursts on accreting neutron stars. We find that the rp-process flow through the 64Ge bypass could be up to 36% for astrophysically relevant conditions. Our results call for new studies of ⁶⁵Se, including the nuclear mass, β-delayed proton emission branching, and nuclear structure as it pertains to the 64As(p, γ) reaction rate at X-ray burst temperatures.

Integrating Community Assets, Place-Based Learning, And Career Development Through Project-Based Learning In Rural Settings, Denae Kizys, Christine Lotter Ph.D., Lucas Perez, Rachel Gilreath, Dodie Limberg

Faculty Publications

Our study investigates the first year of a two-year place-based education (PBE) professional development model that focuses on career development in rural middle schools through project-based learning (PBL) units. Rural science, technology, engineering, and mathematics (STEM) educators face unique challenges, including geographic isolation, limited resources, and reduced access to professional development opportunities, which can hinder the effective integration of career-oriented learning in the classroom. We addressed these challenges by implementing professional development in which school counselors and teachers collaborate to design PBL units aligned with rural community local needs and STEM careers. Using a descriptive multiple-case study methodology to document …

How Extreme Rainfall And Failing Dams Unleashed The Derna Flood Disaster, Ayman Mokhtar Nemnem, Ahad Hasan Tanim, Audrika Nahian, Sadik Khan, Erfan Goharian, Jasim Imran

Faculty Publications

On September 11, 2023, Storm Daniel unleashed unprecedented rainfall over the Wadi Derna watershed, triggering one of the most devastating floods in modern history, striking Derna, a coastal city in Libya. This study reconstructs the disaster using an integrated modeling approach that combines satellite imagery, hydrologic, hydraulic, and geotechnical simulations, machine learning, eyewitness accounts, and digital elevation data to assess the impact of cascading dam failures. Our findings reveal that the region’s dams, even if structurally sound, would have provided minimal protection against the extreme runoff. However, their failure unleashed a destructive surge wave, amplifying the disaster’s magnitude and devastation. …

How Extreme Rainfall And Failing Dams Unleashed The Derna Flood Disaster, Ayman Mokhtar Nemnem, Ahad Hasan Tanim, Audrika Nahian, Sadik Khan, Erfan Goharian, Jasim Imran

Faculty Publications

On September 11, 2023, Storm Daniel unleashed unprecedented rainfall over the Wadi Derna watershed, triggering one of the most devastating floods in modern history, striking Derna, a coastal city in Libya. This study reconstructs the disaster using an integrated modeling approach that combines satellite imagery, hydrologic, hydraulic, and geotechnical simulations, machine learning, eyewitness accounts, and digital elevation data to assess the impact of cascading dam failures. Our findings reveal that the region’s dams, even if structurally sound, would have provided minimal protection against the extreme runoff. However, their failure unleashed a destructive surge wave, amplifying the disaster’s magnitude and devastation. …

On 2-Superirreducible Polynomials Over Finite Fields, J. W. Bober, L. Du, D. Fretwell, G. S. Kopp, T. D. Wooley

Faculty Publications

We investigate k-superirreducible polynomials, by which we mean irreducible polynomials that remain irreducible under any polynomial substitution of positive degree at most k. Let F be a finite field of characteristic p. We show that no 2-superirreducible polynomials exist in F[t] when p=2 and that no such polynomials of odd degree exist when p is odd. We address the remaining case in which p is odd and the polynomials have even degree by giving an explicit formula for the number of monic 2-superirreducible polynomials having even degree d. This formula is analogous to that given by Gauss for the number …

Enhancing Compton Telescope Imaging With Maximum A Posteriori Estimation A Modified Richardson–Lucy Algorithm For The Compton Spectrometer And Imager, H. Yoneda, T. Siegert, I. Martinez-Castellanos, S. Gallego, C. Karwin, H. Bates, S. E. Boggs, C. Y. Huang, A. Joens, S. Matsumoto, S. Mittal, E. Neights, M. Negro, U. Oberlack, K. Okuma, S. Pike, J. Roberts, F. Rogers, Y. Sheng, T. Takahashi, A. Valluvan, Y. Watanabe, D. Hartmann, C. Kierans, J. Tomsick, A. Zoglauer

Faculty Publications

We present a modified Richardson-Lucy (RL) algorithm tailored for image reconstruction in MeV gamma-ray observations, focusing on its application to the upcoming Compton Spectrometer and Imager (COSI) mission. Our method addresses key challenges in MeV gamma-ray astronomy by incorporating Bayesian priors for sparseness and smoothness while optimizing background components simultaneously. We introduce a novel sparsity term suitable for Poisson-sampled data in addition to a smoothness prior, allowing for flexible reconstruction of both point sources and extended emission. The performance of the algorithm is evaluated using simulated three-month COSI observations of gamma-ray lines of ⁴⁴Ti (1.157 MeV), ²⁶Al (1.809 …

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.

Global Sporadic-E Prediction And Climatology Using Deep Learning, J. A. Ellis, Daniel J. Emmons, M. B. Cohen

Faculty Publications

Sporadic-E (E_s) is an ionospheric phenomenon defined by strong layers of plasma which may interfere with radio wave propagation. In this work, we develop deep learning models to improve the understanding of E_s, including the presence, intensity and height of the layers. We developed three separate models. The first, building off earlier work in (J. A. Ellis et al., 2024, link in AFIT Scholar, 10.1029/2023sw003669), includes only the main features from radio occultation (RO) measurements. The second adds to that time, date, location, geomagnetic and solar indices, solar winds, x-ray flux, weather and lightning. A …

Testing For Normality In Regression Models: Mistakes Abound (But May Not Matter), Stephen Midway, J. Wilson White

Faculty Publications

This study examines the misuse of normality tests in linear regression within ecology and biology, focusing on common misconceptions. A bibliometric review found that over 70% of ecology papers and 90% of biology papers incorrectly applied normality tests to raw data instead of model residuals. To assess the impact of this error, we simulated datasets with normal, interval, and skewed distributions across various sample and effect sizes. We compared statistical power between two approaches: testing the whole dataset for normality (incorrect) versus testing model residuals (correct) to determine whether to use a parametric (t-test) or nonparametric (Mann-Whitney U test) method. …

Giving Day Impacts Students In Math Department, Anthony Bosman

Faculty Publications

No abstract provided.

Simultaneous Observations Of Irregular Sporadic E Structures Using The Lwa And A Dps4d, Kenneth S. Obenberger, C. A. Taylor, Jonah J. Colman, Eugene Dao, J. Dowell, J. D. Eccles, Daniel J. Emmons, C. T. Fallen, J. M. Holmes, G. B. Taylor

Faculty Publications

Multi-instrument studies have recently shed new light on the morphology of sporadic E, especially intense sporadic E. Here we present simultaneous observations of dense sporadic E (E_s) structures using the Long Wavelength Array (LWA) radio telescopes and a Digisonde Portable Sounder 4D (DPS4D). Our coordinated observations show that the LWA radio telescopes in central New Mexico can reliably locate regions of dense Es structures as they pass over a Digisonde located over 500 km away in Texas. The LWA appears to be most sensitive to the densest E_s structures, which also appear to contain irregularities with vertical …

Urban Heat Mapping Strategies For Predicting Near-Surface Air Temperature In Unsampled Cities In Iowa, Mark D. Ecker, John P. Degroote, Clemir A. Coproski, Bingqing Liang, John Darko, James T. Dietrich

Faculty Publications

Elevated urban temperatures are a significant concern across the globe due to their negative health effects and increased energy use. Understanding the spatial variation in urban air temperatures can lead to informed mitigation and planning efforts. Air temperatures for multiple urban areas in the state of Iowa, USA, at three times of the day, were collected using customized sensors mounted on vehicles driven through a variety of landscapes in each urban area. Geographic information systems technology was used to process high-resolution landscape datasets and derive variables that summarize the urban landscape surrounding each temperature measurement point. Five different statistical models: …

Global Ionospheric F Region Parameters From Gnss-Pod Limb Measurements: Evaluations And Comparisons With Two Empirical Models - Iri-2020 And Nequick-2, Nimalan Swarnalingam, Dong L. Wu, Dieter Bilitza, Daniel J. Emmons, Cornelius Csar Jude H. Salinas, Artem Smirnov, Yenca Migoya-Oru

Faculty Publications

An optimal estimation (OE) technique has recently been developed for F region electron density (Ne) using Global Navigation Satellite System (GNSS) limb sounding on low Earth orbit (LEO) satellites (COSMIC-2, Spire, and FengYun-3). This method provides unprecedented spatiotemporal sampling for global monthly Ne climatology within 100–500 km in 2 hr intervals. The global dataset, collected during mid to moderately high solar activity, is compared with leading models: IRI-2020 and NeQuick-2. Diurnal variations in summer, winter, and equinoctial months are examined for the F2-layer peak, as well as the topside and bottomside of the F region. The observed and modeled NmF2 …

Changes In The Incidence, Viral Coinfection Pattern And Outcomes Of Pneumococcal Hospitalizations During And After The Covid-19 Pandemic, King-Pui Florence Chan, Ting Fung Ma, Hanshu Fang, Wai-Kai Tsui, James Chung-Man Ho, Mary Sau-Man Ip, Pak-Leung Ho

Faculty Publications

Background

The incidence of pneumococcal pneumonia in the context of the Coronavirus Disease 2019 (COVID-19) pandemic, along with the real-world data on the ratio of non-invasive to invasive pneumococcal pneumonia, is an area that has not been thoroughly studied. The outcomes associated with coinfection of influenza and COVID-19 remain unknown. This study examined the incidence, demographics, coinfection with influenza and/or COVID-19, and clinical outcomes of pneumococcal hospitalizations in Hong Kong during the baseline, pandemic, and post-pandemic periods.

Methods

Hospitalization records of individuals aged 18 years and above with pneumococcal disease from January 2015 to August 2024 were extracted from the …

Scalable Cyber-Physical Testbed For Cybersecurity Evaluation Of Synchrophasors In Power Systems, Shuvangkar Chandra Das, Tuyen Vu, Hebert L. Ginn Iii

Faculty Publications

This paper presents a synchrophasor-based real-time cyber-physical power system testbed with a novel security evaluation tool, pySynphasor, that can emulate different real attack scenarios on the phasor measurement unit (PMU). The testbed focuses on real-time cyber-security emulation using different components, including a real-time digital simulator, virtual machines (VM), a communication network emulator, and a packet manipulation tool. The script-based VM deployment and software-defined network emulation facilitate a highly scalable cyber-physical testbed, which enables emulations of a real power system under different attack scenarios such as address resolution protocol (ARP) poisoning attack, man-in-the-middle (MITM) attack, false data injection attack (FDIA), and …

Sexually Transmitted Infection (Sti) Incidence And Risk Factors Among People With Hiv (Pwh): Insights From A 13-Year Cohort Study In South Carolina, Salome-Joelle Gass, Shujie Chen, Jiajia Zhang Ph.D., Bankole Olatosi

Faculty Publications

The Ending the HIV Epidemic (EHE) initiative aims to reduce new HIV infections by 90% by 2030 in the United States (US). However, rising sexually transmitted infection (STI) rates exacerbate the bidirectional infection risk between HIV and STIs. Most research on STIs among people with HIV (PWH) has focused on high-risk groups, resulting in limited data on broader populations. This study addresses that gap by examining the incidence and risk factors for gonorrhea, chlamydia, and syphilis in a statewide cohort of PWH in South Carolina. Data from South Carolina’s HIV and STI surveillance systems were linked, and all PWH aged …

Environmental Risk And Alpha-Gal Syndrome (Ags) In The Mid-Atlantic United States, Brandon D. Hollingsworth Ph.D., Margaret Wiener, Dana A. Giandimenico, Scott P. Commins, Ross M. Boyce

Faculty Publications

Alpha-gal syndrome (AGS), commonly referred to as the tick bite red meat allergy, has been reported worldwide with the number of suspected cases in the United States increasing from 24 in 2009 to over 34,000 in 2019. Within the US, AGS is associated with the bite of two tick species, Amblyomma americanum and Ixodes scapularis, and has particularly high incidence rates in the mid-Atlantic region. Because AGS is associated with tick bites, the risk of developing AGS is affected by the environment individuals visit. Despite this, as well as the numerous studies associating the environment with Am. americanum, …

Human Capital And Lifetime Income Gains Of Scaling-Up Small-Quantity Lipid Nutrient Supplements Among Children Under 2 Years: A Modelling Analysis, Nandita Perumal Phd, Goodrarz Danaei, Günther Fink, Mark Lambiris, Christopher R. Sudfeld

Faculty Publications

Undernutrition in early childhood is associated with adverse health and developmental outcomes later in life and remains a persistent global public health problem. Providing small-quantity lipid nutrient supplements (SQ-LNS) to children aged 6-24 months improves child growth and neurodevelopmental outcomes, but the potential long-term benefits to human capital have not been previously estimated. We estimated the potential returns to schooling and lifetime income attributable to increasing coverage of SQ-LNS for children < 2 years of age from 0% to 50% or 90% per five-year birth cohort in five countries (Bangladesh, Burkina Faso, Ethiopia, Pakistan, and Uganda) with a high burden of undernutrition. Random-effects meta-analyses were used to estimate the effect of SQ-LNS on child development using evidence from randomized controlled trials, and to estimate the returns to lifetime income as a function of change in development based on a de novo meta-analysis of observational economic studies. Gains in school years attributable to scaling-up SQ-LNS to 90% coverage ranged from 0.14 million school years (95% uncertainty interval [UI]: 0.064, …

Ai-Based Detection Of Optical Microscopic Images Of Pseudomonas Aeruginosa In Planktonic And Biofilm States, Bidisha Roy Sengupta, Esther Mallet, Angel Torres, Ravyn Solis

Faculty Publications

No abstract provided.

A Brave New World Of Human Resources Research: Navigating Perils And Identifying Grand Challenges Of The Genai Revolution, Anthony Nyberg, Deidra J. Schleicher, Bradford S. Bell, Corine Boon, Peter Cappelli, David G. Collings, Joseph E. Dalle Molle, Stefan Feuerriegel, Berry Gerhart, Yoojin Jeong, M. Audrey Korsgaard, Dana Minbaeva, Robert E. Ployhart, Prasanna Tambe, Ingo Weller, Patrick M. Wright, Valery Yakubovich

Faculty Publications

This paper reviews the transformative role of Generative Artificial Intelligence (GenAI) in Human Resource (HR) management, from a practice perspective, highlighting both opportunities and challenges and laying out a use-inspired future research agenda. This scoping review is grounded in insights from a unique Summit held in Spring 2024, which brought together HR academic scholars with dozens of Fortune 500 Chief Human Resource Officers (CHROs) and their top technical leaders to discuss the workforce implications of GenAI. The paper identifies six key themes from the Summit practitioners: GenAI as disruptive and transformative, data as competitive advantage, adoption challenges, potential ethical abuses, …

A Reliable And Efficient Detection Pipeline For Rodent Ultrasonic Vocalizations, Sabah Shahnoor Anis, Devin Mark Kellis, Kris Ford Kaigler, Marlene A. Wilson, Christian O'Reilly

Faculty Publications

Analyzing ultrasonic vocalizations (USVs) is crucial for understanding rodents' affective states and social behaviors, but the manual analysis is time-consuming and prone to errors. Automated USV detection systems have been developed to address these challenges. Yet, these systems often rely on machine learning and fail to generalize effectively to new datasets. To tackle these shortcomings, we introduce ContourUSV, an efficient automated system for detecting USVs from audio recordings. Our pipeline includes spectrogram generation, cleaning, pre-processing, contour detection, post-processing, and evaluation against manual annotations. To ensure robustness and reliability, we compared ContourUSV with three state-of-the-art systems using an existing open-access USV …

Deep Jansen-Rit Parameter Inference For Model-Driven Analysis Of Brain Activity, Deepa Tilwani, Christian O'Reilly

Faculty Publications

Accurately modeling effective connectivity (EC) is critical for understanding how the brain processes and integrates sensory information. Yet, it remains a formidable challenge due to complex neural dynamics and noisy measurements such as those obtained from the electroencephalogram (EEG). Model-driven EC infers local (within a brain region) and global (between brain regions) EC parameters by fitting a generative model of neural activity onto experimental data. This approach offers a promising route for various applications, including investigating neurodevel- opmental disorders. However, current approaches fail to scale to whole-brain analyses and are highly noise-sensitive. In this work, we employ three deep-learning architectures—a …

Re-Framing The Master Narratives Of Learning Dis/Abilities Through An Emotion And Intersectional Lens, David I. Hernández-Saca

Faculty Publications

In this conceptual framework paper, I critically chronicle the historiography, policy, and scientific literatures of learning disabilities (ld) and provide a conceptual framework for reframing these as master narratives. I defined master narratives as the pre-existent sociocultural forms of interpretation. I interrogated the a) cultural-historical; b) the federal definition of ld within idea, c) the educational-professional academic and focused on, the d) social and emotional literature of ld. The master narratives from these literatures included: a) ld as a boy who struggles with reading, ld as a symbolic complex, and the legacy of the term "feebleminded", d) assumptions about learning, …

Geology Of Nacogdoches, Texas : Geogulf 2025, R. Larell Nielson

Faculty Publications

Nacogdoches and East Texas are geologically interesting places to live and work. This field trip will visit the locations indicated on the maps below (Figures 1 and 2). Our location is on the Sabine Uplift and is east of the East Texas Salt Dome Basin (Figure 3 and 4). The first producing oil well in Texas was drilled near Woden by Taliaferro Barret in 1866 at a depth of 106 feet, producing about 10 barrels a day from the Sparta Sand (Figures 5 and 6). Stratigraphic units that we will see are: Sparta Sand, Weches Formation, Queen City Sand, Reklaw …

A Skill Assessment Framework For The Fisheries And Marine Ecosystem Model Intercomparison Project, Nina Rynne, Camilla Novaglio, Julia Blanchard, Daniele Bianchi, Villy Christensen, Marta Coll, Jerome Guiet, Jeroen Steenbeek, Andrea Bryndum-Buchholz, Tyler D. Eddy, Cheryl Harrison, Olivier Maury, Kelly Ortega-Cisneros, Colleen M. Petrik, Derek P. Tittensor, Ryan F. Heneghan

Faculty Publications

Understanding climate change impacts on global marine ecosystems and fisheries requires complex marine ecosystem models, forced by global climate projections, that can robustly detect and project changes. The Fisheries and Marine Ecosystems Model Intercomparison Project (FishMIP) uses an ensemble modeling approach to fill this crucial gap. Yet FishMIP does not have a standardised skill assessment framework to quantify the ability of member models to reproduce past observations and to guide model improvement. In this study, we apply a comprehensive model skill assessment framework to a subset of global FishMIP models that produce historical fisheries catches. We consider a suite of …

Exact Inference For Transformed Large-Scale Varying Coefficient Models With Applications, Tianyu Chen, Robert Habans, Thomas Douthat, Jenna Losh, Lida Chalangar Jalili Dehkharghani, Li Hsiang Lin

Faculty Publications

Studying migration patterns driven by extreme environmental events is crucial for building a sustainable society and stable economy. Motivated by a real dataset about human migrations, this paper develops a transformed varying coefficient model for origin and destination (OD) regression to elucidate the complex associations of migration patterns with spatio-temporal dependencies and socioeconomic factors. Existing studies often overlook the dynamic effects of these factors in OD regression. Furthermore, with the increasing ease of collecting OD data, the scale of current OD regression data is typically large, necessitating the development of methods for efficiently fitting large-scale migration data. We address the …

Endothelial Dysfunction Promotes Age-Related Reorganization Of Collagen Fibers And Alters Aortic Biomechanics In Mice, Liya Du, Jeffrey Rodgers, Nazli Gharraee, Olivia Gary, Tarek Shazly, John F. Eberth, Susan M. Lessner

Faculty Publications

Endothelial dysfunction, defined as a reduction in the bioavailability of nitric oxide (NO), is a risk factor for the occurrence and progression of various vascular diseases. This study investigates the effect of endothelial dysfunction on age-related changes in aortic extracellular matrix (ECM) microstructure and the relationship between microstructural adaptation and the mechanical response. Here, we used groups of NOS3 knockout (KO), NOS3 heterozygotes (Het), and wild-type (WT) B6 mice (controls) to study changes in hemodynamic parameters, collagen fiber organization, and both active and passive aortic mechanics using biaxial pressure myography over a time course from 1.5 to 12 mo. Our …

Unveiling The Nexus Between Digital Monitoring And Experiences Of Intimate Partner Violence In Romantic Relationships, Caley Hewitt, Fanny A. Ramirez, Anna Gjika

Faculty Publications

Using survey data from a sample of 378 women who live in the United States and self-identify as either Black or Latinx, this study explores predictors of women’s digital monitoring practices in intimate relationships in the context of intimate partner violence (IPV). We use literature about surveillance, monitoring, and IPV to frame our study. Our results show three significant instances that influence the odds of monitoring a romantic partner: (1) past experiences with digital abuse, (2) past experiences with offline psychological abuse, and (3) age, with younger women having increased odds of engaging in digital monitoring compared to older women. …