Digital Commons Network^™

Establishing A Nonmedical Cannabis Market In Virginia: Implications For Equity, Craig Dearield Phd, Anna Grace Causey, Rowan Baylosis, Nakeina E. Douglas-Glenn Phd

Research Institute for Social Equity

Virginia passed an adult-use (recreational; non-medical) cannabis law that went into effect on July 1, 2021. Allowing adult possession of cannabis requires the passage of laws and regulations that govern this market (often similar to tobacco or alcohol) due to the intoxicating nature of cannabis and to ensuring the safety of the production processes. Establishing a formal retail market can also address harms related to public health and criminal justice, and benefit state agencies and residents. In order to maximize benefits, Virginia must implement the market with an equity perspective to ensure just treatment for all residents and organizations.

Reclaiming Agency: Ai Hallucinations And Translingual Interrogations In The City Tech Writing Center,, Joseph Franklin, Anna Laura Falvey

Publications and Research

No abstract provided.

Health Literacy/Numeracy-Related Factors Affecting Interpretation In Medical Laboratory Values, Rachel L. Childs

School of Medical Diagnostics & Translational Sciences Publications

Background

Health literacy and numeracy are broad terms that relate to a patient’s understanding of their health information. While there is a substantial amount of research on this topic in a general sense as well as in relation to how deficiencies in these skills impact patients’ understanding of laboratory results, little is known regarding the extent to which underlying factors, which are impacted by health literacy/numeracy, affect how patients interpret their results. This literature review attempts to shed light on the current literature on this more focused and narrow issue, including recommendations to address these barriers.

Content

To perform this …

A Complete Diploid Human Genome Benchmark For Personalized Genomics, Nancy F. Hansen, Nathan Dwarshuis, Hyun Joo Ji, Arang Rhie, Hailey Loucks, Glennis A. Logsdon, Mitchell R. Vallger, Jessica M. Storer, Juhyun Kim, Eleni Adam, Nicolas Alternose, Dmitry Antipov, Mobin Asri, Sofia Barreira, Stephanie C. Bohaczuk, Andrey V. Bzikadze, Sara A. Carioscia, Andrew Carroll, Kuan-Hao Chao, Yanan Chu, Arun Das, Peter Ebert, Adam English, Mark Fleharty, Laura E. Fleming, Giulio Formenti, Andrea Guarracino, Gabrielle A. Hartley, Katharine Jenike, Jenna Kalleberg, Yu Kang, Robert King, Josipa Lipovac, Mira Mastoras, Matthew W. Mitchell, Shloka Negi, Nathan D. Olson, Keisuke K. Oshima, Luis F. Paulin, Brandon D. Pickett, David Porubsky, Jane Ranchalis, Desh Ranjan, Mikko Rautiainen, Harold Riethman, Robert D. Schnabel, Fritz J. Sedlazeck, Kishwar Shafin, Mile Sikic, Steven J. Solar, Alexander P. Sweeten, Winston Timp, Justin Wagner, Dongahn Yoo, Ying Zhou, Erik Garrison, Evan E. Eichler, Michaeel C. Schatz, Andrew B. Stergachis, Rachel J. O'Neill, Karen H. Miga, Steven L. Salzberg, Sergey Koren, Justin M. Zook, Adam M. Phillippy

School of Medical Diagnostics & Translational Sciences Publications

Human genome sequencing typically relies on mapping reads to a reference genome to call variants, but this approach introduces technical biases, excluding duplicated and structurally polymorphic regions of the genome. To overcome this, we present a telomere-to-telomere genome benchmark with near-perfect accuracy across 99.4% of the diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), which were absent from prior benchmarks. We annotated genes and repeats on both haplotypes, including 19,956 protein-coding genes on the maternal haplotype and 19,190 on the paternal haplotype, and developed new methods to measure the accuracy of …

Evaluating Multi-Year Transferability Of Single- And Multi-Class Machine Learning For Remote Monitoring Of Beaver-Engineered Landscapes, Harris J. Sloan

Graduate Student Theses, Dissertations, & Professional Papers

Long-term satellite image archives enable ecological monitoring at large scales, but manual extraction of fine-grained features (e.g., beaver dams) remains time-consuming. Machine learning models may automate these tasks, but their temporal transferability for multiannual monitoring is still poorly resolved.

We evaluated the performance of two complementary neural-network frameworks across a 100,000-hectare watershed in Montana USA, using a decade of satellite imagery (2014-2024): (i) a single-class ResNet-50 beaver dam detector, and (ii) a multi-class ResU-Net landcover classifier.

In 2024, the dam detector identified 352 of 404 mapped dams, achieving balanced accuracy = 93.6%, precision = 79.8%, recall = 87.1%, F1 = …

Words That Heal Or Harm: A Narrative Review On Language Use In Nursing Care.", R. Sudha, A.S. Neya

Manipal Journal of Nursing and Health Sciences

No abstract provided.

Challenges In Implementing Digital Health Solutions For Pressure Ulcer Management: A Narrative Review, Shreenidhi Jogi, Elsa Sanatombi Devi, Vishal Shanbhag

Manipal Journal of Nursing and Health Sciences

Background: Digital pressure ulcer care solutions are both accurate and well-developed in terms of technology. However, a gap remains between available digital solutions and their use in everyday pressure ulcer care practices. This review aims to summarize the technical, human, and system-level challenges that restrict the effective application of digital health solutions in pressure ulcer management.

Methods: The search was conducted in CINAHL, PubMed, Scopus, Web of Science, and EMBASE. Studies that reported implementation challenges in their findings were included.

Results: Infrastructure barriers were about more than just having internet access. Issues such as inconsistent system performance and hardware malfunctions …

The Connectedness Between Awareness And Practice Of Waste Control And Recycling In Urban Villages: A Cross-Sectional Community-Based Study., Nelifer Shreya Ammanna, Jeenal Valine Mendonca, Chethan Kunder, Sushwetha Poojary, Swagath Nayak, Ansuya Ansuya, Mitchelle Shilpa Lewis

Manipal Journal of Nursing and Health Sciences

Introduction: Waste management is an increasing problem that occurs globally due to expanding population around the globe. Researchers worldwide are working towards ending this problem that impacts the environment and people's health. The knowledge of the wastes produced and how we manage them is vital for the population to understand; knowing about it and practicing the same will create a ripple effect on the waste generated by the people.

Objective: To determine the condition of the urban villages in terms of awareness and practice of waste management, and to know whether these are interrelated.

Methods: A quantitative approach with …

An Investigation Of The Perceived Effects Of, And Preparedness For, Climate Change On Tourism Stakeholders In The North Devon Unesco Biosphere, Mai Albaek

Plymouth Business School Theses

This thesis investigates the perceived effects of climate change and the level of preparedness among tourism stakeholders and local residents in the North Devon UNESCO Biosphere (NDUB), a protected area in southwest England. Using a mixed-methods approach, the study draws on quantitative surveys and qualitative interviews with residents, tourism-related business owners, and industry professionals to explore how climate change is understood, experienced, and addressed at the local level. The research is underpinned by stakeholder theory and collaboration theory, which are operationalised to examine the dynamics of climate perception, adaptation, and collective action. Findings reveal that while concern about climate change …

Inward Versus Outward Foreign Direct Investment And Economic Growth: A Case Study Of China, Xiaoning Chen

Plymouth Business School Theses

The thesis aims to investigate the determinants of IFD and OFDI and their impact on economic growth. To bridge the research gap, this study uses China as a case study and structures three empirical chapters to investigate the relationship between IFDI, OFDI and economic growth.The structure of the study consists of six chapters, the first empirical study uses time series data and applies the Autoregressive Distributed Lag (ARDL) techniques to investigate the determinants of IFDI from 1980 to 2023, aiming to investigate the determinants of China’s IFDI. The findings demonstrate market openness, human capital, inflation and market size are the …

The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply, Dan Liu, Guangzhi Shang, Cynthia Fan Yang

Journal of International Technology and Information Management

This study investigates how the crowdfunding marketplace responds to major crises, focusing on behavioral shifts among funders and entrepreneurs. Results show a dual impact on platform dynamics. On the demand side, funders become more engaged, with notable increases in the number of backers, average contributions, and total pledge amounts. This heightened activity suggests stronger altruistic motivations, as individuals view crowdfunding as a way to support others during difficult times. On the supply side, however, entrepreneurs act more cautiously, leading to a decline in new project launches. This drop likely reflects increased risk aversion and uncertainty as creators navigate volatile conditions. …

Joyful Literature As Life-Giving Pedagogy In Teacher Education, Katherine Egan Cunningham

Education Faculty Publications

No abstract provided.

Predicting Tilt In Esports: A Psychophysiological Approach To Understanding Player Emotional Regulation, Nathan Rhea

University of the Pacific Theses and Dissertations

Emotional regulation and stress management are important to both casual and competitive esports players. When players become dysregulated, they experience a phenomenon known as “tilt” within the gaming community, where they often lose control of their emotions and their performance declines. This study aimed to investigate whether a psychophysiological variable in heart rate variability could predict tilt in college-age esports players. Additionally, the relationship between heart rate variability and emotions predicted by the Tiltometer system with gameplay performance and winning or losing was tested.

This study used a quantitative correlational research design. Participants for this study were college-age players (N=23) …

A Comprehensive Overview Of Neurophysiological Correlates Of Cognitive Impairment In Amyotrophic Lateral Sclerosis, Seyyed Bahram Borgheai, Brie E. Achorn, Alyssa H. Zisk, Sarah M. Hosni, Karl E. G. Richter, Frank S. Menniti, Yalda Shahriari

Computer Science Faculty Publications

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that leads to the gradual loss of motor control, typically resulting in paralysis and death within 3 to 5 years of diagnosis. ALS shares neuropathological and genetic associations with fronto-temporal dementia (FTD), a neurodegenerative condition primarily impacting cognitive functions. These two conditions are increasingly viewed as manifestations of a single molecular disease process that affects distinct brain systems, impacting motor neuronal pathways in ALS and fronto-cortical functions in FTD. However, this simple dichotomy belies the complexity of these conditions. In particular, patients with primary motor ALS can also experience significant cognitive …

Sage: Spatially Aware Gene Selection And Dual-View Embedding Fusion For Domain Identification In Spatial Transcriptomics, Yi He, Yunpei Xu, Liqing Ding, Hong-Dong Li, Yaohang Li, Shaokai Wang

Computer Science Faculty Publications

Despite enabling high-resolution mapping of gene expression within tissues, spatial transcriptomics (ST) still faces challenges in accurately segmenting spatial domains due to complex tissue architecture and limitations of current methods. Most approaches rely on local spatial priors, lack gene-level interpretability, and fall short in capturing structure-discriminative genes or long-range functional relationships, limiting their ability to resolve biologically meaningful architectures. We present Spatially Aware Gene selection and dual-view Embedding fusion (SAGE), a unified and reproducible framework for domain identification in spatial transcriptomics that combines topic-driven gene selection with dual-view embedding fusion to address these gaps. SAGE integrates non-negative matrix factorization (NMF)-based …

Modeling Joint Visual Attention In Naturalistic Dyadic Interactions, Kuushini Thennakoon, Yasasi Abeysinghe, Bhanuka Mahanama, Vikas Ashok, Sampath Jayarathna

Computer Science Faculty Publications

Joint visual attention (JVA) provides important insight into how individuals coordinate attention during social interaction. Egocentric eye tracking enables the study of JVA in natural, multi-user settings. This work presents a multi-stage framework to identify and analyze JVA using egocentric video and gaze data. The approach consists of three steps: spatiotemporal tube-based visual similarity, gaze-guided object detection, and attention pattern analysis using the ambient–focal coefficient K. Results show that object-focused collaborative activities exhibit high JVA, with object detection capturing higher joint attention than visual similarity, whereas conversation-based or independent activities show lower and more fragmented joint attention. Analysis of K …

The Privacy Paradox Of Llms: User Perceptions And The Reality Of Pii Leakage, Shuai Cheng, Haitao Xu, Shu Meng, Shuai Hao, Chuan Yue, Zhao Li

Computer Science Faculty Publications

Large language models (LLMs) are increasingly deployed, yet they introduce significant privacy risks by disclosing personally identifiable information (PII) during interactions. Although prior work has demonstrated the feasibility of extracting PII from LLMs, no comprehensive study has evaluated the actual extent of PII leakage across mainstream LLMs or investigated user perceptions, literacy, and behavioral responses to these risks. To address these gaps, we conduct a large-scale evaluation of PII leakage in popular LLMs, demonstrating that attackers can extract email addresses and phone numbers with high success rates. Through a mixed-methods study involving 20 interviews and 204 survey participants, we identify …

Variational Autoencoder Inverse Mapper For Extraction Of Compton Form Factors: Benchmarks And Conditional Learning, Douglas Adams, Md Fayaz Bin Hossen, Joshua Bautista, Gia-Wei Chern, Simonetta Liuti, Marie Boër, Marija Čuić, Michael Engelhardt, Gary R. Goldstein, Huey-Wen Lin, Yaohang Li

Computer Science Faculty Publications

Deeply virtual exclusive scattering processes (DVES) serve as precise probes of nucleon quark and gluon distributions in coordinate space. These distributions are derived from generalized parton distributions (GPDs) via Fourier transform relative to proton momentum transfer. QCD factorization theorems enable DVES to be parameterized by Compton form factors (CFFs), which are convolutions of GPDs with perturbatively calculable kernels. Accurate extraction of CFFs from DVCS, benefiting from interference with the Bethe–Heitler (BH) process and a simpler final state structure, is essential for inferring GPDs. This paper focuses on extracting CFFs from DVCS data using a variational autoencoder inverse mapper (VAIM) and …

Lost In Instructions: Study Of Blind Users' Experiences With Diy Manuals And Ai-Rewritten Instructions For Assembly, Operation, And Troubleshooting Of Tangible Products, Monalika Padma Reddy, Aruna Balasubramanian, Jiawei Zhou, Xiaojun Bi, Iv Ramakrishnan, Vikas Ashok

Computer Science Faculty Publications

AI tools like ChatGPT and Be-My-AI are increasingly being used by blind individuals. Although prior work has explored their use in some Do-It-Yourself (DIY) tasks by blind individuals, little is known about how they use these tools and the available product-manual resources to assemble, operate, and troubleshoot physical/tangible products – tasks requiring spatial reasoning, structural understanding, and precise execution. We address this knowledge gap via an interview study and a usability study with blind participants, investigating how they leverage AI tools and product manuals for DIY tasks with physical products. Findings show that manuals are essential resources, but product-manual instructions …

Susceptibility To High-Fidelity Misinformation: An Eye-Tracking Analysis, Yasasi Abeysinghe, Gavindya Jayawardena, Enkelejda Kasneci, Sampath Jayarathna

Computer Science Faculty Publications

With the rise of online misinformation and AI-generated text, understanding human perception of news truthfulness is critical. In this study, we examine visual attention and cognitive processing using eye-tracking measures as individuals read fake and real news articles sharing nearly identical structure and imagery, differing only in subtle textual changes. Using the public FakeNewsPerception dataset, we analyze advanced gaze measures, including scanpaths, AOI transitions, and luminance-corrected pupil measures, beyond basic gaze features, in relation to news truthfulness and perceived believability. Results show that, given the high fidelity of the fake news, readers exhibited comparable visual scanning patterns, attention allocation across …

From Custody To Care: Understanding Mental Health And Recidivism In The Criminal Justice System, India Cox

UROP Posters

Previous studies on genetic influences in mental health disorders have been shown to correlate with incarceration rates in families. Consequently, there are individuals within the criminal justice system under the clinical threshold of a mental health diagnosis; it has been found that almost half of the incarcerated population was arrested due to acting upon their mental health disorder, while 27 to 38 percent developed PTSD while imprisoned. Furthermore, the serious and exhausting cycle of recidivism within the criminal justice system highlights the failure to provide the necessary mental health treatment required to support rehabilitation while incarcerated and prevent reoffending upon …

A Novel 3d Imaging Approach To Study Evolutionary Innovations In Solanaceae Inflorescences, Devin L. Jackson, Joonseog Kim, Wenheng Zhang Dr.

UROP Posters

Understanding the relatedness of angiosperms and the evolution of their inflorescence remains challenging, as these structures are highly modified and prone to convergent evolution. The current research describing inflorescence architecture, whether genetically or morphologically focused, typically relies on text based explanations, 2D images, or 3D based models created with CAD modeling software. This creates a disparity in the reader's understanding of these models since descriptions rely heavily on the author's interpretation of the inflorescence. The goal of our study is to bridge this disconnection by producing anatomically and color-correct 3D inflorescence models using Solanaceae flowers that readers can explore directly, …

Exploring The Knowledge Gap: Mental Health Crisis Identification Training For 911 Call Takers, Kayla L. Ralston, Emma Adcook, Gary Cuddeback, Rebecca Smith, Amy Adkins

UROP Posters

Individuals with serious mental illness (SMI) are more likely to come into contact with law enforcement and the justice system. Livingston (2016) found that 25% of people with mental illness have been arrested at least once in their lives.  Law enforcement officers often become the primary intervention in handling a mental health crisis, and most mental health-related training curricula (e.g., Crisis Intervention Team (CIT)) have focused on this group. However, the burden to initially ascertain if an emergency is mental health-related has fallen to 911 call takers and dispatchers, the first first responder. The performance outcomes outlined by the Virginia …

Making Their Community Proud: First-Generation Latinx Students' Participation In Clep, Michelle Van Beek, Abby Holland

Journal of College Access

This study explores the impact of earning Spanish CLEP credit on first-generation Latinx students' levels of self-efficacy, college-going mindset toward earning a post-secondary degree, and their perceptions of bilingualism. Study participants (n=47) were all enrolled or previously enrolled in a college access program in high school. All participants received the opportunity to take the Spanish CLEP exam. Participants (n=33) completed a pre/post survey, and a paired sample t-test showed self-efficacy, college-going mindset, and language perceptions remained neutral for participants. Five semi-structured group interviews (n=26) were conducted after the post-survey. Participants showed that earning Spanish CLEP credit impacted their way of …

Saliency Guided Reinforcement Leaming For Multi Step Mathematical Reasoning In Large Language Models, Ji Dung Lo

Computer Science and Engineering Master's Theses

Large language models perform strongly on many tasks but remain unreliable on complex multi step mathematical reasoning. Existing reinforcement learning methods treat reasoning trajectories as uniformly informative, ignoring that some intermediate steps matter more than others. This thesis argues that reasoning is structurally uneven and that optimization should reflect this internal credit distribution.

We adopt Group Relative Policy Optimization (GRPO) to construct a fully automated reinforcement learning framework. To provide intermediate supervision without human annotation, we automatically generate short quiz questions that test key reasoning checkpoints. Quiz rewards complement final answer rewards, enabling structured feedback while keeping the pipeline scalable. …

Buying Blind: Corruption Risk And The Erosion Of Oversight In Federal Ai Procurement, Jessica Tillipman

GW Law Faculty Publications & Other Works

The United States is accelerating toward a corruption crisis of its own making. In its race to rapidly acquire artificial intelligence (AI), current policy risks undermining longstanding procurement integrity safeguards. This article examines how AI increases traditional corruption risks and introduces new vulnerabilities that current oversight mechanisms are ill-equipped to address.

Recent federal AI policies have accelerated adoption while simultaneously narrowing regulatory oversight, effectively leaving “regulation by contract” as the primary—and profoundly inadequate—mechanism for embedding safeguards. The consequence of these policies is that the government is “buying blind,” acquiring AI technologies without adequate transparency, audit rights, or testing requirements. These …

Transportation Law’S Congestion Problem, Sara C. Bronin

GW Law Faculty Publications & Other Works

Transportation law has a congestion problem: our federalist system of government allows federal and state actors to stymie innovative, locally driven projects that aim to reduce driving. This problem is illustrated in the decades-long legal battles over New York City’s plan to impose “congestion pricing” to toll drivers entering certain parts of Manhattan. Overcoming grandstanding elected officials, lawsuits resting on state and federal supremacy, and even a federal legislative override, congestion pricing was finally launched in January 2025. New Yorkers and suburbanites alike almost immediately started benefiting from cleaner air, faster commutes, safer roads, and increased economic activity and productivity—plus …

Governing Ai Without Agencies: Self-Regulatory Organizations And The Federal Backstop, Aram A. Gavoor

GW Law Faculty Publications & Other Works

Artificial intelligence is accelerating American innovation and strategic advantage. The governance task is to provide predictable compliance baselines that support scale and competitiveness while remaining workable under executive branch policy, statutory baselines, and the rules that now govern the administrative state. Congress remains slow and factional, and agencies face rising procedural and remedial constraints. Recent Supreme Court doctrine has reduced the administrative state’s interpretive and enforcement leverage. Regulated entities can challenge agency rules when those rules newly impose concrete harm, litigate statutory meaning without Chevron-style mandatory deference to agency statutory interpretations with limited exceptions, and invoke strengthened procedural safeguards in …

Feature Comment: Governance As A “Blocker”: How The Pentagon’S New Ai Strategy Trades Oversight For Speed, Jessica Tillipman

GW Law Faculty Publications & Other Works

The Department of Defense's January 2026 AI Strategy memorandum presents governance and speed as a zero-sum tradeoff, labeling core oversight mechanisms such as ATOs, test and evaluation, and contracting processes as "blockers" to be waived through a newly established Barrier Removal Board. By doing so, the memo converts governance from a baseline into a negotiable exception. It also redefines "Responsible AI" in ways that depart from the Department's prior lifecycle-assurance framework, mandates "any lawful use" contract language that shifts risk management responsibility to the government, and elevates undefined criteria like "model objectivity" to primary procurement standards, without providing contracting officers …

Policy Brief: The Occ's Unlawful Proposal To Preempt State Interest-On-Escrow Laws Reveals That The Agency's Ultimate Goal Is To Revive Its Illegal De Facto Field Preemption Regime For National Banks, Arthur E. Wilmarth Jr.

GW Law Faculty Publications & Other Works

In December 2025, the Office of the Comptroller of the Currency (“OCC”) issued a proposal to preempt all state laws that require national banks and federal savings associations to pay interest on borrowers’ funds held in mortgage escrow accounts. The OCC’s proposal is unlawful and must be rescinded. Under 12 U.S.C. § 25b and the Supreme Court’s decisions in Cuomo v. Clearing House and Cantero v. Bank of America, the OCC does not have authority to preempt state interest-on-escrow (IOE) laws.

The OCC’s proposal for a categorical, across-the-board preemption of state IOE laws violates three requirements set forth in 12 …