Digital Commons Network^™

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 …

The Oral History Of Bill Miller, Bill Miller

UNLV Gaming Law Journal

No abstract provided.

Betting The House: Why The Safe Bet Act Is A Long Shot To Survive Constitutional Scrutiny Under The Commerce Clause And Anti-Commandeering Doctrine, Jared Weingard

UNLV Gaming Law Journal

The rapid expansion of legalized sports gambling following Murphy v. NCAA has raised concerns about problem gambling, predatory marketing, and inconsistent state regulations. In response, the SAFE Bet Act, introduced by Representative Paul Tonko, seeks to impose nationwide standards on sports betting. However, its framework raises significant constitutional concerns under the Commerce Clause and the anti-commandeering doctrine. This Article argues that the Act’s enforcement mechanism likely violates the Tenth Amendment by coercing states into compliance, conflicting with Supreme Court precedent on federal conditional spending and preemption.

Given these vulnerabilities, this Article explores three alternative approaches that would achieve similar regulatory …

Corridor Court And The Order Out Ordinance: Clark County's Solution To Homelessness In Las Vegas A Jackpot For Gaming Industry, Harrison Epstein

UNLV Gaming Law Journal

No abstract provided.

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. …

Corporate Labor Violations: Do Ceos’ Public Charity Affiliations Matter?, Mariem Khalifa, Mehdi Khedmati, Mohammed Aminu Sualihu, Alfred Yawson

All Works

We examine the impact of CEOs’ public charity affiliations on corporate labor violations and find that public-charity-affiliated CEOs have a lower likelihood of engaging in labor violations than their non-affiliated peers. In a disaggregated analysis, we find the result to be driven primarily by wage and hour violations. This finding is validated when we compare changes in wage and hour violations around different types of CEO turnover. We further identify the promotion of a positive corporate culture and an increase in labor-related expenditures as the main channels through which CEOs’ public charity affiliations affect wage and hour violations. In addition, …

From Farm To Plate: Q-Analysis Of Consumer Requirements In Blockchain-Based Agri-Food Supply Chains, Pouyan Jahanbin, Stephen C. Wingreen, Ravishankar Sharma, Arnob Zahid

All Works

Blockchain platforms have revolutionized the food industry by establishing a more trustworthy supply chain. By providing a secure and open record of all transactions, blockchain technology helps improve food safety. This reassures consumers who may wish to ensure that products are guaranteed to meet certain dietary or nutritional standards. However, the adaptability of existing supply chains and consumers' full adoption of such systems remains a gap in scholarly research. This field study employs Q-methodology to explore the concourse of requirements and priorities of food consumers in blockchain-based agri-food supply chains. Abductive reasoning is utilized to elaborate on the subjective perspective …

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 …

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 …

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 …

Designing A Telemedicine-Supported Delirium Triage Pathway For Skilled Nursing Facilities: An Evidence-Based Pilot Framework, Benjamin Antill, Eric W. Bean Do, Tara Fritch Ma, Kate Huck Mba, Nha

USF-LVHN SELECT

No abstract provided.

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.

Edgeclip: Injecting Edge-Awareness Into Visual-Language Models For Zero-Shot Semantic Segmentation, Jiaxiang Fang, Shiqiang Ma, Guihua Duan, Fei Guo, Shengfeng He

Research Collection School Of Computing and Information Systems

Effective segmentation of unseen categories in zero-shot semantic segmentation is hindered by models’ limited ability to interpret edges in unfamiliar contexts. In this paper, we propose EdgeCLIP, which addresses this by integrating CLIP with explicit edge-awareness. Based on the premise that edge variation patterns are similar across both seen and unseen class objects, EdgeCLIP introduces the Contextual Edge Sensing module. This module accurately discerns and utilizes edge information, which is crucial in complex border areas where conventional models struggle. Further, our Text-Guided Dense Feature Matching strategy precisely aligns text encodings with corresponding visual edge features, effectively distinguishing them from background …

Cancerseg-Xa: Medical Histopathology Segmentation System Based On Xception Backbone And Attention Mechanisms, Alaa Youssef, Wessam H. El-Behaidy, Aliaa Youssif

Computer Science

Accurate segmentation of histopathological images is essential to support early diagnosis and effective treatment planning in cancer care. This study presents CancerSeg-XA, a deep learning-based histopathology segmentation system designed to deliver robust performance across diverse tissue types and imaging sources. Built upon the DeepLabV3+ framework, CancerSeg-XA incorporates architectural enhancements to strengthen feature representation and improve model stability. The system was evaluated on three widely recognized datasets—BCSS, PanNuke, and PUMA—each presenting distinct structural and clinical challenges. Across all datasets, CancerSeg-XA consistently outperformed the baseline DeepLabV3+ in terms of segmentation accuracy, recall, and F1-score. Specifically, it achieved accuracy improvements of 4.78%, 4.31%, …

Navigating Ethical Considerations And Implications Of Ai Chatbots In Higher Education: A Systematic Review, Ons Al-Shamaileh, Ramy Hammady, Mahmoud Abdelrahman, Omar Mubin

All Works

This systematic review explores the ethical challenges associated with the use of AI-based chatbots in higher education, focusing on their implications for students, educators, institutions, and administrative stakeholders. Following PRISMA guidelines, peer-reviewed literature published between 2014 and 2024 was systematically identified across eight major academic databases, yielding a total of 109 eligible studies. A thematic analysis of the included literature indicates that concerns related to academic integrity are most frequently discussed, alongside recurring issues involving data privacy and security, algorithmic bias, overreliance on automated systems, and the risk of inaccurate or misleading outputs. The findings further demonstrate considerable variation in …

From Damage Signals To Immune Modulators: Oxidized Lipids In Immunometabolic Inflammation, Neetu Srivastava, Xiaoxiao Wan

2020-Current year OA Pubs

Oxidized lipids, once viewed as byproducts of oxidative stress, are now recognized as critical mediators linking metabolism, redox imbalance, and immunity. Generated through enzymatic and nonenzymatic oxidation of polyunsaturated fatty acids, oxidized phospholipids, lipid aldehydes, and oxidized lipoproteins act as context-dependent signals regulating immune activation, resolution, and metabolic adaptation. In metabolic inflammation, these lipids engage scavenger and Toll-like receptors to influence macrophage polarization, dendritic-cell function, and T-cell differentiation. Their context and concentration determine whether oxidized lipids amplify inflammation or promote immune tolerance. Accumulation of these species connects oxidative stress to immune dysfunction, contributing to diseases, such as atherosclerosis, obesity, diabetes, …

Patient And Chondral Defect-Specific Characteristics And Associated Matrix-Induced Autologous Chondrocyte Implantation Conversion Rates Following Biopsy, Derrick M Knapik, Daniel C Touhey, S Ryan Pierson, Christopher K Bozorgmehr, Matthew V Smith, Matthew J Matava, Robert H Brophy

2020-Current year OA Pubs

BACKGROUND: Focal chondral defects in the knee lead to swelling, discomfort, and mechanical symptoms, resulting in disability and loss of function. Matrix-induced autologous chondrocyte implantation (MACI) has emerged as a viable treatment option, with satisfactory clinical outcomes reported compared with microfracture. Patient and lesion-specific variables associated with MACI after biopsy remain largely underreported.

PURPOSE: To examine patient- and defect-specific characteristics associated with conversion to MACI after biopsy from a single institution.

STUDY DESIGN: Cohort study; Level of evidence, 3.

METHODS: A retrospective chart review of prospectively collected data from June 2018 to March 2025 was performed. Inclusion criteria included patients …

Impulsivity In Cerebellar Ataxia: An Online, Multidimensional Assessment, Brooke Chasalow, Yakov Flaumenhaft, Yael De Picciotto, Chi-Ying R Lin, Leila Montaser-Kouhsari, William Saban

Faculty, Staff and Students Publications

While considered a motor control structure, the cerebellum contributes to non-motor functions, including impulsivity. However, whether it contributes to impulsivity in a domain-specific manner remains unknown. Studies on cerebellar ataxia (CA), a common model for cerebellar dysfunction, typically have small sample sizes, limiting robustness. In a multicenter cross-sectional study, we investigated the cerebellum's role in various forms of impulsivity by comparing large cohorts of CA to age- and education-matched neurotypical healthy (NH) controls. Additionally, to examine the ability to identify individuals with CA using impulsivity features alone, we developed supervised machine learning (ML) models. In experiment 1 (CA = 140, …

Information Extraction From Clinical Notes: Are We Ready To Switch To Large Language Models?, Yan Hu, Xu Zuo, Yujia Zhou, Xueqing Peng, Jimin Huang, Vipina K Keloth, Vincent J Zhang, Ruey-Ling Weng, Cathy Shyr, Qingyu Chen, Xiaoqian Jiang, Kirk E Roberts, Hua Xu

Faculty, Staff and Student Publications

Objectives: To assess the performance, generalizability, and computational efficiency of instruction-tuned Large Language Model Meta AI (LLaMA)-2 and LLaMA-3 models compared to bidirectional encoder representations from transformers (BERT) for clinical information extraction (IE) tasks, specifically named entity recognition (NER) and relation extraction (RE).

Materials and methods: We developed a comprehensive annotated corpus of 1588 clinical notes from 4 data sources-UT Physicians (UTP) (1342 notes), Transcribed Medical Transcription Sample Reports and Examples (MTSamples) (146), Medical Information Mart for Intensive Care (MIMIC)-III (50), and Informatics for Integrating Biology and the Bedside (i2b2) (50), capturing 4 clinical entities (problems, tests, medications, other treatments) …

Effect Of Dynamic Fatigue Loading On The Adaptation And Retention Of Maxillary Single Dentures Reinforced With Digitally Constructed Zirconia And Cobalt–Chromium Frameworks, Ghada Elgindy, Fardos N Rizk, Marwa Ezzat Sabet, Hebatallah Tarek Mohamed

Dentistry

Background. The impact of dynamic fatigue loading on denture adaptation and retention is clinically important. Zirconia and cobalt–chromium (Co–Cr) frameworks enhance denture strength, but their performance under cyclic loading remains unclear. Objectives. The aim of the study was to evaluate the adaptation and retention of maxillary single dentures reinforced with digitally constructed Co–Cr or zirconia frameworks after a simulated 1 year of function. Material and methods. Three types of maxillary single dentures were constructed on maxillary master casts. Group A included maxillary dentures without reinforcement (control group), whereas groups B and C encompassed maxillary dentures reinforced with digitally designed and …

Frontmatter (Volume 46, Issue 3), Paul B. Mojzes

Occasional Papers on Religion in Eastern Europe

No abstract provided.

The Soviet Template And Its Application: Bulgarian State Policy Toward The Bulgarian Orthodox Church After 1944, Ventzislav Gueorgiev Karavaltchev

Occasional Papers on Religion in Eastern Europe

The article examines the adoption and implementation of Soviet models in Bulgarian state policy toward the Bulgarian Orthodox Church following the communist takeover on September 9, 1944. Situating the Bulgarian case within a broader comparative framework, the study traces key continuities between Soviet church–state relations after the October Revolution of 1917—particularly as was institutionalized during the Stalinist period—and their subsequent application in Bulgaria. Drawing on extensive archival materials from Bulgarian and Russian repositories, the article demonstrates that all major decisions concerning the Church were closely coordinated with, and often directly approved by, Moscow. Beyond repression and legal restriction, the analysis …

Hegemonial Nationalism And The Role Of Religion: A View From The Perspective Of The Western Balkans, Semir Halilović, Tomislav Tadic

Occasional Papers on Religion in Eastern Europe

This paper points to the problem of hegemonic nationalism, with an emphasis on the role of religion, in the context of a social understanding of the situation in the Western Balkans (Bosnia and Herzegovina, Serbia, Montenegro, and Croatia). The question of the “Eastern and Western models of nationalism” is articulated, and the social role of religion in their construction is examined. In relation to this framework, the possibilities for applying the thesis of the Eastern model of the nation are considered in light of the current war situation between Russia and Ukraine. The paper highlights some of the theoretical configurations …