Digital Commons Network^™

The Adaptive Solution Of High-Frequency Helmholtz Equations Via Multi-Grade Deep Learning, Peiyao Zhao, Rui Wang, Tingting Wu, Yuesheng Xu

Mathematics & Statistics Faculty Publications

The Helmholtz equation is fundamental for modeling wave propagation in acoustics, electromagnetics, and geophysics; however, high-frequency regimes remain notoriously difficult due to the severe numerical “pollution effect.” We propose FD-MGDL, an adaptive framework that synergizes finite difference discretizations with Multi-Grade Deep Learning (MGDL) to efficiently resolve high-frequency wavefields. Unlike standard physics-informed neural networks (PINNs), which frequently suffer from spectral bias and heavy automatic differentiation overhead, FD-MGDL employs a progressive, grade-wise training strategy that incrementally incorporates shallow sub-networks to refine residual errors. By leveraging ReLU activations in refinement grades, the framework reformulates the highly non-convex global optimization problem into a sequence …

Mg-Spair: Multi-Grade Sparse-Guided Implicit Representation For Training-Data-Free Image Restoration, Jianmin Liao, Lei Huang, Ronglong Fang, Ashley Prater-Bennette, Lixin Shen, Yuesheng Xu

Mathematics & Statistics Faculty Publications

MG-SpaIR is a training-data-free framework for restoring a clean image from a single observation corrupted by a mixture of blur, downsampling, noise, and missing pixels. Building on implicit neural representations (INRs), we introduce a multi-grade residual hierarchy that progressively refines the reconstruction from low to high spatial frequencies across grades, improving representational fidelity and mitigating spectral limitations. To stabilize reconstruction optimization and suppress INR-induced artifacts, we further propose an explicit sparse proximal regularization (e.g., ℓ0 type) applied directly in the high-resolution image domain, which discourages spurious high-frequency patterns while preserving sharp structures. The resulting optimization is solved efficiently via a …

Juncture Models: Trivariate Nonlinear Regression Models And Application To In-Hospital Quality Of Care, Manasi Sheth, N. Rao Chaganty

Mathematics & Statistics Faculty Publications

Mortality, readmission, and length of stay (LOS) are commonly used measures for quality of hospital care. These measures are correlated with each other, so we propose a new way to combine these three variables to evaluate hospital care quality of care. In this paper, we investigate the joint probability distribution of these three variables using what we named as the Juncture Distribution Models and characteristics of the Juncture models.

Integrating Genetic Modifier Genotype With Serum Proteomics In Duchenne Muscular Dystrophy Clinical Trials Links Ltbp4 Genetic Modifier To Il-23/Cd93 Pathways In Muscle, Utkarsh J. Dang, Yuan Fang, Daniele Sabbatini, Elena Pegoraro, Luca Bello, Paula R. Clemens, Michela Guglieri, John Van Den Anker, Jesse Damsker, Laura Hagerty, Yetrib Hathout, Michael Ziemba, Lauren Morgenroth, Surajit Bhattacharya, Kanneboyina Nagaraju, Jyoti K. Jaiswal, Eric P. Hoffman

Mathematics & Statistics Faculty Publications

Genetic modifiers of Duchenne muscular dystrophy (DMD) that alter disease severity or response to therapy have been reported using natural history or registry data sets of older corticosteroid-treated patients. We tested associations of genetic modifiers on motor function outcomes in young (4 to <  7 years) steroid naïve clinical trial participants. Participants in clinical trials (VBP15-002/003 [n = 48]; VBP15-004 [n = 121]; DNA available for n = 110) were genotyped for eight published genetic modifier loci, and associations of genotypes with baseline motor function defined via an age-adjusted linear model. Corticosteroid drug response was modeled by genotype-stratified placebo vs. steroid treatment at 12- and 24-weeks posttreatment (mixed model for repeated measures). …

Governance, Development, Technology: Histories And Futures, Nikhilesh Dholakia, Zeynep Ozdamar Ertekin, Delphine Godefroit-Winkel

Markets, Globalization & Development Review

No abstract provided.

Influencer Marketing Through The Decades: Evolution And Future Pathways, Raisha Yesmin, Chandan Goswami

Markets, Globalization & Development Review

Influencer marketing has evolved over the past few years, shifting from the conventional way of celebrity endorsement to a data-driven digital world. A systematic review has outlined the history of influencer marketing from the early days of the use of traditional mass media to development of social media platforms, the development of micro and nano Influencer marketing, and the different perceptions about authenticity and trust in consumer.

This study focuses on 37 peer-reviewed articles and books published between 1956 and 2025 from databases such as Scopus, Web of Science, Google Scholar, Emerald Insight, ScienceDirect and Taylor & Francis. Studies shows …

Digital Transformation Of Food Systems In Algeria: Challenges, Opportunities And Managerial Implications, Kamel Chikhi

Markets, Globalization & Development Review

This article provides a critical analysis of the transformations generated by digitalization in the contemporary Algerian food system. Based on contributions to the symposium "Digital and Food Practices" organized by the Social Sciences and Health Research Unit (GRAS) of the University of Oran 2 (Algeria) in January 2026, it reconstructs and analyzes the debates around four main themes: digitalization and representations of food; digital food environments and consumption practices; health, nutrition, and algorithmic mediation; and agricultural digitalization and territorial disparities. The article offers a thematic and critical read of the analogies, contradictions and complementarities among the various approaches discussed at …

Weak Enforcement And Low Compliance In Pci Dss: A Comparative Security Study, Soonwon Park, John Hastings

Research & Publications

Although credit and debit card data continue to be a prime target for attackers, organizational adherence to the Payment Card Industry Data Security Standard (PCI DSS) remains surprisingly low. Despite prior work showing that PCI DSS can reduce card fraud, only 32.4% of organizations were fully compliant in 2022, suggesting possible deficiencies in enforcement mechanisms. This study employs a comparative analysis (qualitative and indicator-based) to examine how enforcement mechanisms relate to implementation success in PCI DSS in relation to HIPAA, NIS2, and GDPR. The analysis reveals that PCI DSS significantly lags far behind these security frameworks and that its sanctions …

The Need For Standardized Evidence Sampling In Cmmc Assessments: A Survey-Based Analysis Of Assessor Practices, Logan Therrien, John Hastings

Research & Publications

The Cybersecurity Maturity Model Certification (CMMC) framework provides a common standard for protecting sensitive unclassified information in defense contracting. While CMMC defines assessment objectives and control requirements, limited formal guidance exists regarding evidence sampling, the process by which assessors select, review, and validate artifacts to substantiate compliance. Analyzing data collected through an anonymous survey of CMMC-certified assessors and lead assessors, this exploratory study investigates whether inconsistencies in evidence sampling practices exist within the CMMC assessment ecosystem and evaluates the need for a risk-informed standardized sampling methodology. Across 17 usable survey responses, results indicate that evidence sampling practices are predominantly driven …

Unsupervised Baseline Clustering And Incremental Adaptation For Iot Device Traffic Profiling, Sean Alderman, John Hastings

Research & Publications

The growth and heterogeneity of IoT devices create security challenges where static identification models can degrade as traffic evolves. This paper presents a two-stage, flow-feature-based pipeline for unsupervised IoT device traffic profiling and incremental model updating, evaluated on selected long-duration captures from the Deakin IoT dataset. For baseline profiling, density-based clustering (DBSCAN) isolates a substantial outlier portion of the data and produces the strongest alignment with ground-truth device labels among tested classical methods (NMI 0.78), outperforming centroid-based clustering on cluster purity. For incremental adaptation, we evaluate stream-oriented clustering approaches and find that BIRCH supports efficient updates (0.13 seconds per update) …

Gravity Falls: A Comparative Analysis Of Domain-Generation Algorithm (Dga) Detection Methods For Mobile Device Spearphishing, Adam Dorian Wang, John Hastings

Research & Publications

Mobile devices are frequent targets of eCrime threat actors through SMS spearphishing (smishing) links that leverage Domain Generation Algorithms (DGA) to rotate hostile infrastructure, avoid individual domain blocks, and bypass perimeter enterprise defenses. Despite this, DGA research and evaluation largely emphasize malware C2 and email phishing datasets, leaving limited evidence on how well detectors generalize to smishing-driven domain tactics outside enterprise perimeters. This work addresses that gap by evaluating traditional and machine-learning DGA detectors against Gravity Falls, a new dataset derived from smishing links delivered between 2022 and 2025. Gravity Falls captures a single threat actor's evolution across four technique …

Context-Based Adversarial Attacks On Ai Code Generators: Vulnerability Analysis And Implications, Walther Del Orbe, John Hastings, Varghese Vaidyan

Research & Publications

AI-powered code generation systems have transformed software development but introduce critical inference-time security vulnerabilities. This research presents a systematic investigation of context-based adversarial attacks, where strategically crafted contextual inputs, including comments, documentation, variable names, bias large language models toward generating exploitable code. Through 2,800 controlled experiments across CodeT5+, CodeLlama, GPT-3.5-Turbo, and GPT-4, we quantify attack effectiveness and defense mechanisms. Results demonstrate that adversarial conditions increase vulnerability generation 11.4x for individual models, with an overall pooled increase of 2.1x (from 16.1% to 34.1%), with direct instruction attacks achieving 88.8% success on GPT-3.5-Turbo. Cross-model transferability reaches 58-100%, indicating systemic architectural vulnerabilities rather …

Bridging The Smart City Cybersecurity Data Gap Through Ai-Driven Synthetic Dataset Generation, Stephanie Polczynski, John Hastings, Varghese Vaidyan, Kyle Korman

Research & Publications

Smart cities rely on interconnected cyber-physical systems that integrate sensors, IoT devices, cloud platforms, and AI-driven services and decision-making. While these systems enhance city services, they also introduce complex cybersecurity challenges due to their large attack surfaces, heterogeneous data flows, and evolving threat vectors. Developing and validating cybersecurity tools for smart cities requires high-quality datasets that accurately represent real operational conditions. However, real-world datasets are often incomplete, contain privacy-sensitive data, are difficult to access, or lack sufficient malicious activity to support tool development. This research addresses this critical gap by proposing an AI-based synthetic data generation (SDG) framework designed specifically …

Enhancing Attack Detection Capabilities In Bacnet/Ip Networks Using Machine-Learning Models, Derek Manzella, John Hastings

Research & Publications

Building Automation Systems (BAS) manage critical building functions using protocols such as BACnet/IP, yet defenders have limited tooling and few labeled datasets for detecting BACnet-specific attacks. This work addresses these gaps through three contributions. First, CISA's Zeek BACnet parser is modified to produce a unified per-packet log, simplifying feature engineering for machine-learning (ML) pipelines. Second, a simulated BACnet/IP testbed is developed using bacpypes3 to model a small commercial HVAC system with physics-based device behavior, schedule-aware controller logic, and per-packet attack labeling. Third, five unsupervised anomaly detection models are evaluated using baseline traffic and six BACnet attack types, including denial of …

Security Vulnerability Patterns In Ai-Generated Code: A Cross-Model Comparative Study, Shanna Kahn, John Hastings

Research & Publications

LLM-based coding tools enable non-expert users to generate routine automation scripts that may enter enterprise workflows without meaningful security review. This study examines that risk directly. Code was collected from ChatGPT, Microsoft Copilot, and Google Gemini using identical prompts across three automation domains. Claude Code performed a standardized vulnerability review. Each identified vulnerability was scored using CVSS v3.1 and mapped to the OWASP Top 10:2021 and the MITRE ATT\&CK frameworks. Every script contained exploitable vulnerabilities. Nine of the 17 identified vulnerability classes appeared in code from all three models, while 14 of the 17 vulnerability classes appeared in at least …

Workplace Surveillance And Insider Threat Risk Management: Legal Limits And Privacy Harms, Haywood Gelman, John Hastings, Suvineetha Herath, Quentin Covert

Research & Publications

Workplace surveillance is used by organizations to protect corporate assets and monitor employee productivity. This research presents two central arguments on workplace surveillance: although surveillance serves legitimate organizational purposes, over-surveillance can violate legal requirements and data privacy principles; and a primary security objective of workplace surveillance is the detection of insider threats (InT). InT are comprised of individuals with authorized resource access whose intentional or unintentional actions may damage or compromise corporate assets. This paper investigates InT personas to understand behavioral and psychological detection criteria. Employee surveillance tools and techniques are reviewed to characterize the employee surveillance landscape. Workplace privacy …

Governing Bring Your Own Ai: A Parameterized Maturity Model, Dare Bello, John Hastings

Research & Publications

Employees are increasingly using personally owned generative AI tools such as ChatGPT, Gemini, and Claude for their daily work. This practice is known as Bring Your Own AI (BYOAI), which is a distinct form of Shadow AI in which employee-authenticated personal accounts are used outside of enterprise identity and security controls. Existing frameworks were designed for AI tools managed by organizations, and their coverage does not extend to unmanaged AI tools used with a personal account. In addressing these issues, we developed a governance model through a systematic review of the literature that produces a risk taxonomy and a framework-engagement …

Frugal Consumers Of The Globalized Wardrobe, Rabia Demre Bayer, Umut Kubat Dokumaci, Selen Bakış

Markets, Globalization & Development Review

Fast fashion’s global expansion has fundamentally altered consumption rhythms across both developed and developing economies. This paper critically analyzes how the development context shapes the dominant pathways of consumer frugality in fast fashion consumption. We argue that in developing countries, frugality is primarily an enforced constraint driven by scarcity, and it leads to a focus on short-term affordability that often overlooks long-term durability and environmental externalities. In contrast, in developed economies, frugality is increasingly a lifestyle choice enabled by robust circular infrastructure and regulatory buffers. This divergence creates a global asymmetry where textile waste and pollution migrate toward nations with …

Brief For Jonathan H. Adler As Amicus Curiae Supporting Respondents And Affirmance, Jonathan Adler

Briefs

Global climate change presents many complex and intractable legal and policy questions. Assuming this Court has jurisdiction, the legal questions in this case are comparatively simple and straightforward. Nothing in federal law, let alone the Constitution, preempts state-law claims seeking relief from injuries allegedly caused or exacerbated by petitioners’ conduct.

At issue in this case is whether allegedly aggrieved parties, including subnational governments, may seek redress under state law from defendants otherwise subject to state court jurisdiction for harms allegedly caused or contributed to by petitioners’ conduct. In order to succeed, respondents will ultimately need to show that the damages …

The Fingal Water Project: A Water Quality Remediation Study 2018-2023, Alan Gilmer, Vivien Corona Ramirez Dr., Stephen Barry Dr.

Reports

This report presents the findings of the Fingal Water Project, a research study undertaken over the period 2018–2023 to investigate water quality and the application of Floating Treatment Wetland (FTW) systems in five freshwater ponds within the Fingal County Council area. The report documents the project's research, findings and recommendations, including the development of an evidence-based framework to support the assessment and management of applying nature based solutions in an effort to regulate pond water quality.

The Protective Power Of Psychological Resources In Mitigating Burnout And Enhancing Flourishing, Dylan R. Polkinghorne, David J. Radosevich, Deirdre M. Radosevich, Dianne D. Murphy, Laken James, Sue S. Craver

Management Faculty Research and Publications

Purpose

This study explores how burnout mediates the relationships between critical psychological resources, specifically resilience, flow and self-efficacy, and flourishing in contemporary work environments.

Design/methodology/approach

Data from 374 participants, including undergraduate students at a regional comprehensive university in the Midwest and full-time working adults in the USA, were analyzed using mediation analysis in MPlus 8.11 to assess the indirect and direct effects among burnout, psychological resources and flourishing in a work environment.

Findings

Results indicate that self-efficacy significantly predicts lower burnout levels and higher flourishing. Resilience and flow were negatively associated with burnout, reducing its impact; however, the direct effects …

Multiple Changepoint Detection For Non-Gaussian Time Series, Robert Lund, Thomas J. Fisher, Norou Diawara, Michael Wehner

Mathematics & Statistics Faculty Publications

This article combines methods from existing techniques to identify multiple changepoints in non‐Gaussian autocorrelated time series. A transformation is used to convert a Gaussian series into a non‐Gaussian series, enabling penalized likelihood methods to handle non‐Gaussian scenarios. When the marginal distribution of the data is continuous, the methods essentially reduce to the change of variables formula for probability densities. When the marginal distribution is count‐oriented, Hermite expansions and particle filtering techniques are used to quantify the scenario. Simulations demonstrating the efficacy of the methods are given and two data sets are analyzed: 1) the proportion of home runs hit by …

Annual Report Of The Town Of Enfield, New Hampshire Year Ending December 31, 2025, Enfield Town Representatives

Enfield, NH Annual Reports

This is an annual report containing vital statistics for a town/city in the state of New Hampshire.

Bridging Mission And Execution: Integrating Participatory Design In Early-Phase Mission Engineering For Stakeholder Alignment And Mission Clarity, Rafi Soule

The Knowledge and Creativity Expo

This research examines mission framing during the early phase of Mission Engineering. Stakeholder interpretations diverge under ambiguity. Interoperability constraints are often not surfaced early. These conditions reduce mission clarity and weaken mission-to-system mapping readiness. The study integrates a participatory design-inspired, artifact-first workflow with RAG-enabled retrieval from a closed corpus to support evidence-grounded reasoning and traceable citations.

Phase 1 uses an online survey to establish baseline patterns in practice (N = 86). Shared understanding is positively associated with mission clarity (r = 0.60, p < 0.001). Phase 2 uses a time-bounded comparative workshop with two conditions. Expert reviewers rate mission statement quality higher for the participatory design condition (mean 3.5) than the traditional condition (mean 2.8). Technical feasibility ratings are similar across conditions. Phase 3 demonstrates RAG-enabled, closed-corpus, retrieval-supported traceability using the Referencer tool. It is reported as a proof-of-concept for evidence-grounded rationale and auditability, and as a pathway …

Does The Use Of Protective Behavioral Strategies Moderate The Relationship Between Perceived Peer Cannabis Use And Personal Use?, Mia Forsythe, Erica E. Mcdonald, Melissa N. Manning, Audrey L. Bell, Alicia Moulder, Cathy Lau-Barraco

The Knowledge and Creativity Expo

The perception that close friends frequently use substances (i.e., descriptive norms) has been shown to increase personal use frequency and subsequent negative consequences. Within alcohol literature, protective behavioral strategies (PBS), actions aimed at reducing negative consequences of substance use (e.g., avoiding use before work), have been shown to moderate the effect of this relationship. However, this relationship in cannabis use remains unexplored. Thus, the current study examines PBS use as a moderator between descriptive norms and cannabis use frequency. We hypothesize that a positive association between descriptive norms and cannabis frequency will be weakened by greater PBS use. Undergraduate past-month …

Under Pressure: Associations Between Discrimination, Expressive Suppression, And Coping Drinking Motives Among Sexual Minority Women, Erica E. Mcdonald, Mia Forsythe, Audrey L. Bell, Melissa N. Manning, Alicia Moulder, Cathy Lau-Barraco

The Knowledge and Creativity Expo

Within Minority Stress Theory, heterosexist discrimination has been linked to drinking to cope (DTC) motives, or drinking as a way to manage negative emotions. DTC motives are associated with heightened negative consequences from drinking. Prior research has found that high levels of expressive suppression (i.e., inhibition of ongoing emotion-expressive behavior) confer risk for coping motivated drinking. Given sexual minority women’s (SMW) elevated risk for DTC motives, examining expressive suppression and discrimination as correlates may address an important gap in literature. Thus, the current study examined expressive suppression as a factor impacting the relationship between external discrimination and coping motives among …

Can We Talk? A Correspondence Study To Examine Responsiveness Of Physical Educators To Requests For A Phone Call From Parents Of Children With Disabilities, Sean Healy, Justin A. Haegele, Steven K. Holland

Human Movement Studies & Special Education Faculty Publications

The Individuals with Disabilities Education Improvement Act (2004) mandates that parental input be considered when making educational decisions for children with disabilities, including in physical education. However, parents of children with disabilities often report suboptimal communication experiences with physical educators. The purpose of the current study was to examine if the initiation of a parent–physical educator relationship is influenced by whether students have a disability or not. An online message correspondence study methodology was used to detect potential disparities in the responsiveness of a sample of 320 physical educators to electronic message requests for a phone call to discuss physical …

Associations Between Accelerometer-Measured Physical Activity And Sleep Duration And Health Indicators In Children And Adolescents With Attention-Deficit Hyperactivity Disorder: A Systematic Review And Meta-Analysis, Xiao Liang, Hui Qiu, Justin A. Haegele, Xiao Li, Minghui Li, Jiayue Li, Shirley Xin Li

Human Movement Studies & Special Education Faculty Publications

Objective

This systematic review and meta-analysis synthesized available studies to explore relationships between accelerometer-measured physical activity (PA) levels or sleep duration and health-related outcomes in children and adolescents with attention-deficit hyperactivity disorder (ADHD).

Methods

Following the Preferred Reporting Items for Systematic Review and Meta-analyses guidelines, the six databases APA PsychInfo, CINAHL Ultimate, Embase, MEDLINE, SPORTDiscus with Full Text and Web of Science were searched from inception through July 2024. The correlation coefficient (r) was employed to determine the effect size in the meta-analysis. A random-effects model was utilised to estimate the potentially heterogeneously distributed effect sizes with a 95 % …

Understanding Motivations And Health Outcomes Of College-Aged Triathletes During Covid-19: A Mixed-Methods Study, Patrick Wilson, Eddie Hill, Justin Haegele, Xihe Zhu

Human Movement Studies & Special Education Faculty Publications

A triathlon is a multi-sport event that consists of three simultaneous events: swimming, biking, and running. This sport has experienced significant growth in the past few decades, with colleges and universities now participating. This exploratory mixed-methods study examined the motivations and perceived health benefits of college triathletes during the COVID-19 pandemic, using the Means-Ends of Recreation Scale and the Perceived Health Outcomes of Recreation Scale (N = 29), as well as semi-structured interviews (N = 4). Results indicate no difference in motives or health outcomes between male and female survey respondents. The thematic analysis of open-ended interview questions highlighted lived …

Will They Be More Honest With An (External) Proctor? Evaluating Ufc Match Performance Before And After The Adoption Of The Usada Doping Program, Moonsup Hyun, Wonsok (Frank) Jee, Sehwon Kang, Yohan Lee

Human Movement Studies & Special Education Faculty Publications

Over the eight years from 2015 to 2023, the Ultimate Fighting Championship (UFC) partnered with the United States Anti-Doping Agency (USADA) to institute comprehensive external oversight of doping controls. This study investigates the effects of transitioning from internally administered anti-doping protocols to exclusive external governance by comparing UFC performance metrics before and during the USADA partnership. Using a Difference-in-Differences (DiD) approach with data from 2012 to 2018, we find that match duration significantly increased, while the likelihood of extreme outcomes, knockouts (KO), technical knockouts (TKO), and submissions, decreased during the USADA period. These results suggest that performance-enhancing drugs (PEDs) could …