Digital Commons Network^™

Program Management And Building Partner Capacity: A Tangled Thicket, Phil W. Reynolds

Publications

This chapter explores how the U.S. Department of Defense plans and executes Building Partner Capacity projects in lower-middle and low-income partners. U.S. planners and practitioners rarely understand the effective pre-conditions that influence partner security apparatus and infrastructure. Consequently, security capabilities provided to the partner are rarely sustained and provide questionable security to the affected population. The U.S. Department of Defense uses a three-part approach to building security with partners: training and equipping, building institutional capacity, and monitoring and evaluating. U.S. security planners should manage all three parts concurrently to produce a security capability that the partner uses and sustains and …

Entangled Transitions: How Covid-19 Widened Well-Being Gaps Among Youth In Singapore (2017–2022), Vincent Chua, Han Ei Chew, Isabelle Tan, Pamela Lee

Research Collection Office of Impact

COVID-19 was not merely a biomedical crisis but a deeply social phenomenon entangled with existing inequalities. Drawing on Peter Kelly's notion of entanglement, we conceptualise the pandemic as an intersectional crisis − where time, structural disadvantage and socio-emotional well-being became interwoven. Using six waves of longitudinal data (2017–2022) from Youth STEPS, a panel study of young people in Singapore, we track within-person changes in life satisfaction across key youth transitions before, during and after the pandemic. Our findings show that the negative effects of unemployment and insecure work on well-being were markedly more severe during the pandemic than in earlier …

Tennessee Archivist 45, No. 2, Society Of Tennessee Archivists

Tennessee Archivist newsletters

Spring 2026 issue of the Tennessee Archivist, a newsletter produced by the Society of Tennessee Archivists.

Faith's Multiple Meanings: Does The Author Of Hebrews Use "Faith" In The Same Manner As It Is Used In The Rest Of The New Testament?, Wayne Brouwer

Pro Rege

No abstract provided.

"Where Art Thou?" Virtue, Duty, And The Voice Of/In Ethics In Jennifer A. Herdt's Assuming Responsibility: Ecstatic Eudaimonism And The Call To Live Well, Geoffrey Fulkerson

Pro Rege

Reviewed Title: Assuming Responsibility: Ecstatic Eudaimonism and the Call to Live Well by Jennifer A. Herdt. Oxford: Oxford University Press, 2022. 267 pp. ISBN: 9780192849205

The Religious Root Of Humanity: Abraham Kuyper's Concept Of The Heart, Steve Bishop

Pro Rege

No abstract provided.

"Not A Textbook, But... ": Political Theory And The Biblical Narrative, Richard Mouw

Pro Rege

No abstract provided.

Molecular Landscape In Limb Anomalies: Diagnostic Yield And New Candidate Genes., Akram Mokhtari, Jade Charbonneau, Valancy Miranda, Khadijé Jizi, Marie-Ange Delrue, Patricia Egerszegi, Isabelle Thiffault, Philippe M. Campeau

Manuscripts, Articles, Book Chapters and Other Papers

Congenital limb anomalies remain without an etiological diagnosis in up to 65% of patients. To help close this gap, we describe the genetic diagnostic outcomes of a large cohort. Patients whose primary indication for genetic consultation was a limb anomaly were included from 2014 to 2024. Demographic, investigation, and diagnostic information were extracted, described, and compared. One hundred and thirty-two patients were included in the final cohort, with an average molecular diagnostic yield of 36%. The most common conditions were polydactyly (24%) and radial anomalies (19%). Fifty percent had syndromic features. Seven (5%) patients underwent chromosomal microarray (CMA) only, 81 …

Advancing Trauma-Informed Care For Intimate Partner Violence Survivors., Maya I. Ragavan, Kimberly Randell

Manuscripts, Articles, Book Chapters and Other Papers

No abstract provided.

Ƒ(Cell): Software For Reproducible Analysis Of Optoretinograms, Robert F. Cooper, Mina Gaffney, Brea D. Brennan, Niko Rios

Biomedical Engineering Faculty Research and Publications

Purpose: There has been a marked increase in use of a noninvasive functional imaging technique called optoretinography (ORG). As more groups use ORGs, it is crucial to have a consistent methodology, and understand what analysis parameters influence repeatability. In this work, we present an open-source software library called ƒ(Cell) designed to facilitate reproducible and repeatable analyses of ORG data.

Methods: We designed ƒ(Cell) as a Python software library that can co-register and analyze ORG datasets, while also enabling process auditing. To validate the software, we used our previously obtained normative optoretinography datasets as well as datasets from six …

Improving Interlimb Coordination And Paretic Limb Use After Stroke Using A Novel Robotic Split-Crank Pedaling Device: A Cross-Sectional Study, Tom S. Ruopp, Brian Schmit, Sheila Schindler-Ivens

Biomedical Engineering Faculty Research and Publications

Background. Many stroke survivors cannot walk effectively, even after rehabilitation. Causes include impaired muscle activation, poor interlimb coordination, and limited restorative interventions. To address this, we developed CUped (pronounced “cupid”), a motorized split-crank pedaling device designed to compel use of the paretic limb and retrain interlimb coordination. We examined its within-session effects, comparing three proportional control schemes—assist (A), resist (R), and assist plus resist (A + R)—to identify which best promotes recovery-related movement.

Methods. Nineteen individuals with stroke and eleven controls pedaled in 5-min bouts, one per control scheme. Each bout included pre-test, exposure, and post-test periods. Participants were instructed …

Acute Schistosomiasis In A Traveler Returning From St. Croix, United States Virgin Islands: A Case Report., John Weis, Mackenzie Caruthers, Megan Buller

Ambulatory and Primary Care Articles

In this case report, we describe a patient who presented to their primary care provider with abdominal pain after returning from travel to the Caribbean island of St. Croix. The patient reported two weeks of epigastric abdominal pain, dyspepsia, nausea, and night sweats. Following an initial evaluation that revealed eosinophilia with unclear etiology, they were referred to an infectious disease clinic. Through a targeted infectious evaluation and workup, the patient was diagnosed with acute schistosomiasis syndrome and was treated with praziquantel. Treatment resulted in the complete resolution of her symptoms, and follow-up laboratory evaluation showed complete resolution of her eosinophilia. …

The Oral History Of Bill Miller, Bill Miller

UNLV Gaming Law Journal

No abstract provided.

Automated Machine Learning For High-Resolution Daily And Hourly Methane Emission Mapping For Rice Paddies Over South Korea: Integrating Modis, Era5-Land, And Soil Data, Jiah Jang, Seung Hee Kim, Menas Kafatos, Jaeil Cho, Gayoung Yoo, Sujong Jeong, Yangwon Lee

Institute for ECHO Articles and Research

Agriculture is a major global source of methane (CH4), and accurate emission estimates are essential for refining national greenhouse gas inventories and supporting climate-resilient policies. This study develops a high-resolution estimation framework for CH4 emissions from Korean rice paddies by integrating multi-source datasets, including Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis Version 5 (ERA5)-Land meteorological variables, and Harmonized World Soil Database (HWSD) soil properties. Using CH4 flux observations from four global rice ecosystems (Italy, Japan, South Korea, and USA), we constructed parallel daily and hourly machine learning models using an automated machine …

Driver Behavior Analyzer 2.0: A Modular Framework For Interpretable Driver Safety Analysis From Obd-Ii And Gps Telemetry, Sangwhan Cha, Venkata Sundar Kamesh Durvasula

Harrisburg University Other Works

Driver behavior analysis plays a central role in advancing road safety and enabling data-driven driver feedback. Although commercial telematics platforms offer sophisticated analytics, they are frequently expensive, proprietary, and optimized for enterprise-scale use. At the same time, low-cost On-Board Diagnostics II (OBD-II) adapters make telemetry collection widely accessible, but they typically do not provide higher-level behavioral interpretation.

In this paper, we present Driver Behavior Analyzer 2.0 (DBA 2.0), an offline-first, modular analytics framework that converts OBD-II and GPS telemetry into interpretable safety insights. DBA 2.0 supports ingestion of telemetry logs in CSV and JSON formats, data normalization, rule-based detection of …

In What Style Shall I Confront Them? The Role Of Social Relationships In Social Correction Of Misinformation Among The Uk And Arab Social Media Users, Muaadh Noman, Mohamed B. Almourad, Ala Yankouskaya, Firoj Alam, Raian Ali

All Works

This study investigates how social factors influence the likelihood of employing direct or indirect communication styles when correcting misinformation on social media in two different cultural contexts, the United Kingdom (UK) and the Arab Gulf Cooperation Council (GCC) countries. We conducted an online survey, supported by vignettes, that involved 686 participants, 367 from the UK and 319 from the Arab GCC countries. Participants were presented with a misinformation scenario and asked about their likelihood of using direct or indirect communication styles to correct their acquaintances. The survey captured variations in gender similarity (same vs. different gender), social status (lower vs. …

Exploring Preservice Teachers’ Design Thinking Mindset In A Technology-Enhanced Active Learning Environment For Stem Courses, Areej Elsayary

All Works

This study explores how a technology-enhanced active learning environment, supported by interactive technologies, may influence preservice teachers’ perceptions of their design thinking (DT) mindsets in interdisciplinary STEM courses. Using a blend of digital tools and the design thinking process, the research aimed to engage students in activities that promote key DT traits, including managing uncertainty, empathy, mindfulness, collaboration, learning orientation, and creative confidence. Ninety-four preservice teachers from an early childhood education program in a UAE university participated, receiving two weeks of intensive training on digital tools (e.g., Genially, Canva, PowToon, AR/VR apps), concluding in earning an Apple Teaching Certificate. These …

Generative Ai For Text-To-Video Generation: Recent Advances And Future Directions, Kadhim Hayawi, Sakib Shahriar

All Works

Text-to-video (T2V) generation has recently emerged as a transformative technology within the field of generative AI, enabling the creation of realistic, temporally coherent videos based on natural language descriptions. This paradigm provides significant added value in many domains such as creative media, human-computer interaction, immersive learning, and simulation. Despite its growing importance, systematic discussion of T2V is still limited compared with adjacent modalities such as text-to-image and image-to-video. To alleviate the scarcity of discussions in the T2V field, this paper provides a systematic review of works published from 2024 onward, consolidating fragmented contributions across the field. We survey and categorize …

Design And Tissue Engineering Applications Of Microporous Annealed Particle (Map) Scaffolds, Nic D. Leipzig, Oluwaseyi Shofolawe-Bakare

University Research

Microporous annealed particle (MAP) scaffolds are emerging as a facile, yet sophisticated biomaterial platform with tremendous potential for tissue regenerative applications. These scaffolds are fabricated in situ through interparticle crosslinking of microgels using a variety of covalent or non-covalent techniques and possess excellent tunability and biocompatibility. The microporous structure of MAP scaffolds allows cellular infiltration and vascularization independent of degradation rate, making them more advantageous than traditional nanoporous bulk hydrogels. Moreover, the incorporation of in situ crosslinking allows MAP scaffolds to retain the key advantages of traditional microgel-based scaffolds—such as injectability and modularity—while providing the added benefit of a fixed …

Identification Of Microplastics And Additives From The Lake Erie Watershed And The Cuyahoga River Via Maldi-Ms And Dart-Ms, Chrys Wesdemiotis, Calum Bochenek, Luciana Rivera Molina, Robert Brand

University Research

Micro(nano)plastics have received increased attention as environmental contaminants due to their harmful effects on ecosystems and human health. Conventional extraction methods for microplastic analysis are often lengthy and complicated, resulting in the loss of important chemical components such as additives. In this study, we provide a complementary approach, utilizing matrix-assisted laser desorption/ionization (MALDI) and direct analysis in real time (DART) mass spectrometry (MS) techniques, with minimal extraction and sample preparation to preserve both polymer and additive information. MALDI-MS was applied to aqueous samples collected along the shores of Lake Erie and the Cuyahoga River, successfully identifying the base polymer(s) in …

No Name Ditch Filter Request, Chad Pritchard, Sonja Durr

EWU PFAS Research Collection

This is a one-page request showing the need for filtration at No Name Ditch at the SE corner of Fairchild Air Force Base (FAFB), West Plains, Spokane County, Washington.  Surface water levels in the ditch and stormwater ponds that feed the system can exceed 20,000 ppt for PFOS while groundwater can be up to 2,000 ppt for PFOS, per a remedial investigation report for FAFB in 2025.  The federal drinking water standard for PFOS is 4 ppt. While surface water and stormwater are not regulated for PFAS levels, these polluted waters enter the groundwater just off base and likely contaminate …

Opencil: Benchmarking Out-Of-Distribution Detection In Class Incremental Learning, Wenjun Miao, Guansong Pang, Trong-Tung Nguyen, Ruohuan Fang, Jin Zheng, Xiao Bai

Research Collection School Of Computing and Information Systems

Class incremental learning (CIL) aims to learn a model that can not only incrementally accommodate new classes, but also maintain the learned knowledge of old classes. Out-of-distribution (OOD) detection in CIL is to retain this incremental learning ability, while being able to reject unknown samples that are drawn from different distributions of the learned classes. This capability is crucial to the safety of deploying CIL models in open worlds. However, despite remarkable advancements in the respective CIL and OOD detection, there lacks a systematic and large-scale benchmark to assess the capability of advanced CIL models in detecting OOD samples. To …

Comprehensively Evaluating The Perception Systems Of Autonomous Vehicles Against Hazards, Xiaodong Zhang, Jie Bao, Jianlei Chi, Jun Sun, Zijiang Yang

Research Collection School Of Computing and Information Systems

Perception systems are vital for the safety of autonomous driving. In complex autonomous driving scenarios, autonomous vehicles must overcome various natural hazards, such as heavy rain or raindrops on the camera lens. Therefore, it is essential to conduct comprehensive testing of the perception systems in autonomous vehicles against these hazards, as demanded by the regulatory agencies of many countries for human drivers. Since there are many hazard scenarios, each of which has multiple configurable parameters, the challenges are (1) how do we systematically and adequately test an autonomous vehicle against these hazard scenarios, with measurable outcome; and (2) how do …

Interpretable Machine Learning For Personalized Profiling Of Mild Cognitive Impairment From Daily Activities, Budhitama Subagdja, Ah-Hwee Tan, Kenneth Kwok, Iris Rawtaer

Research Collection School Of Computing and Information Systems

Continuous monitoring of individual daily activities is essential to detect mild cognitive impairment (MCI) wherein timely intervention can still be applied to prevent more severe mental decline. Recent approaches in predicting MCI are mostly considering digital biomarkers across individuals but often neglecting specific indicators from a single person over a long period of time. Making this personalized, dynamic, and highly noisy prediction model with irregular distribution of missing information to be explainable and actionable for clinical use, remains a challenge. This paper presents a study on a personalized MCI prediction and profiling from an in-home and mobile cognitive health monitoring …

Improving Credit Card Transaction Fraud Detection Using Cvqboosting, Bethel Hui Ting Loke, Nirvik Sahoo, Bingyan Guan, Minrui Xu, Dev Verma, Paul R. Griffin

Research Collection School Of Computing and Information Systems

This paper introduces a novel hybrid quantum-classical approach to credit card fraud detection using CVQBoost, a hybrid quantum-classical boosting algorithm executed on the photonic Dirac-3 processor from Quantum Computing Inc. (QCi). By integrating a diverse set of weak classifiers, which includes K-nearest neighbours (KNN), linear discriminant analysis, logistic regression, and XGBoost, within a hybrid quantum-classical ensemble, the proposed method demonstrates significant improvements over the latest published classical benchmarks. Experiments on a Kaggle credit card fraud dataset show that the quantum-enhanced model achieves a mean AUC-PR score of over 0.8, corresponding to an approximately 9% relative improvement over the best published …

A Knowledge Transfer-Based Membrane Evolutionary Algorithm For Solving Large-Scale Sorted Waste Collection Problem With Timeliness, Wenxue Zhang, Boquan Gao, Aldy Gunawan, Yunyun Niu, Jianhua Xiao

Research Collection School Of Computing and Information Systems

The sorted collection of municipal solid waste has emerged as an effective waste management strategy due to varying timeliness requirements across different waste types, giving rise to the critical research challenge of timeliness-based waste collection. While existing algorithms primarily focus on small-scale versions of this problem, solving large-scale timeliness-based waste collection problems remains particularly challenging. To tackle this issue, this paper proposes a knowledge transfer-based membrane evolutionary algorithm. Specifically, the original problem and simplified problem are constructed in different membranes respectively, and the knowledge transfer learning mechanism is incorporated into the membrane evolutionary algorithm, enabling effective information exchange between the …

Learning To Search For Vehicle Routing With Multiple Time Windows, Kuan Xu, Zhiguang Cao, Chenlong Zheng, Lindong Liu

Research Collection School Of Computing and Information Systems

In this study, we propose a reinforcement learning-based adaptive variable neighborhood search (RL-AVNS) method designed for effectively solving the Vehicle Routing Problem with Multiple Time Windows (VRPMTW). Unlike traditional adaptive approaches that rely solely on historical operator performance, our method integrates a reinforcement learning framework to dynamically select neighborhood operators based on real-time solution states and learned experience. We introduce a fitness metric that quantifies customers’ temporal flexibility to improve the shaking phase, and employ a transformer-based neural policy network to intelligently guide operator selection during the local search. Extensive computational experiments are conducted on realistic scenarios derived from the …

Addressing Graph Heterogeneity And Heterophily From A Spectral Perspective, Kangkang Lu, Yanhua Yu, Ruopei Guo, Nan Cheng, Zhiyong Huang, Yunshan Ma, Meiyu Liang, Yuling Wang, Xiting Qin, Yimeng Ren, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) face two key challenges, heterogeneity and heterophily, which often degrade performance. Existing approaches either focus narrowly on specific meta-paths, limiting their expressiveness, or are expressive but cannot effectively leverage higher-order neighbors. In this paper, we propose the Heterogeneous Heterophilic Spectral Graph Neural Network (H2SGNN), which combines local independent filtering to adaptively handle meta-path subgraphs with varying homophily ratios, and global hybrid filtering to capture high-order neighbor interactions with linear computational complexity. On five heterogeneous graph benchmarks—DBLP, ACM, IMDB, AMiner, and Yelp—H2SGNN consistently outperforms strong baselines, for example, achieving +1.0% Macro-F1 and +1.3% Micro-F1 on IMDB. It …

Mini-Course On Community Resources For Patients With Disabilities, Abigail Weisse, Vinita Kiluk, Kyle Lien, Nora Newcomb, Aishwarya Vuppala, Franklin Sun, Shannon Mccarthy, Anita Narkhede, Marjorie Fitzsimmons

USF-LVHN SELECT

No abstract provided.

Trends In Alcohol Withdrawal With Relation To Race/Ethnicity, Angela Nguyen, Alexandra Amaducci Do

USF-LVHN SELECT

No abstract provided.