Digital Commons Network^™

Examining Factors Influencing Ultra- Processed Food Consumption Among Liberty University Students Aged 18 And Older, Ginika Rosemary Muomah

Masters Theses

Ultra-processed foods (UPFs) are widely consumed among college students and are linked to adverse health outcomes including obesity, poor mental health, and cardiometabolic disease. Despite their rising prevalence, limited research has examined psychosocial and behavioral factors influencing UPF intake within Christian university settings. This study investigated demographic, behavioral, and psychosocial predictors of UPF consumption among Liberty University students, guided by the Health Belief Model (HBM). A cross-sectional survey of students aged 18 and older (N = 337) was conducted. After excluding incomplete or invalid responses, 276 cases remained. The 25-item survey assessed UPF intake, HBM constructs, and demographics. Descriptive statistics …

Helisha Moore V. Cohn,Lifland,Pearlman,Hermann & Knoph

2025 Decisions

USDC for the District of New Jersey

Hospital And Temporal Variations In Limitations Of Care Among Hospitalized Patients With Covid-19: A Virus Registry Retrospective Cohort Study, Nathan Mesfin, Nitesh Kumar Jain, Anwar Khedr, Hisham Mushtaq, Abbas B. Jama, Noura Attallah, Esraa Hassan, Benjamin Langworthy, Nicholas Ingraham, Juan Pablo Domecq Garces, Thoyaja Koritala, Donna Lee Armaignac, Nicholas Eugene Perkins, Katherine Belden, Vishakha Kumar, Karen Boman, Devang K. Sanghavi, Vikas Bansal, Rahul Kashyap, Rodrigo Cartin-Ceba, Abigail La Nou, Allan J. Walkey, R. Adams Dudley, Syed Anjum Khan

Division of Infectious Diseases and Environmental Medicine Faculty Papers

INTRODUCTION: Life-support limits (i.e., code status), the first step in the continuum of palliation and end-of-life (EoL) care, stem from decisions made by patients and their providers to align care near the EoL with patients' wishes. The pandemic created health care strain that may have influenced life-support limitation practices among patients with serious COVID-19. In this study, we examine variations in life-support limitations (do-not-resuscitate, DNR; do-not-intubate, DNI) depending on the hospital and period of hospitalization.

METHODS: We included all adults admitted to a hospital in the United States with COVID-19 from January 2020 to December 2021 using the VIRUS registry. …

Dominick Chase Named Chief Financial Officer, Lindenwood University

Archived Lindenwood Press Releases

No abstract provided.

Conquer And Prevail Issue 197 September 25 2025, Wofford College. Office Of Marketing And Communications

Conquer and Prevail Newsletter

No abstract provided.

Trcaptionnet++: A High-Performance Encoder-Decoder Based Deep Turkish Image Captioning Model Fine-Tuned With A Large-Scale Set Of Pretrain Data, Serdar Yildiz, Abbas Memi̇ş, Songül Varli

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a novel and high-performance encoder-decoder-based deep model called TRCaption Net++ for generic Turkish image captioning tasks. The proposed model is an improved and refined version of TRCap tionNet, which essentially employs a CLIP (contrastive language–image pretraining) image encoder, a feature projection layer and a BERT (bidirectional encoder representations from transformers) text decoder. Within the scope of the study, the regular TRCaptionNet model was trained and specifically fine-tuned with a massive set of image data. In this respect, approximately 2,000,000 random images representing the words in the MS COCO and Flickr caption sets were retrieved through web crawling …

Enhanced Pmu Data Imputation Using Variational Autoencoder: A Novel Approach For Improved Accuracy, Subin Koshy, Sunitha Rajan, Elizabeth P. Cheriyan

Turkish Journal of Electrical Engineering and Computer Sciences

Data collected from various measurement devices, such as phasor measurement units (PMUs), form the backbone of power system monitoring algorithms such as state estimation algorithms. Even though modern PMUs are efficient, data inaccuracies and loss can still occur due to problems like equipment malfunctions, communication issues, and hardware or software glitches. Missing values in the datasets can also affect the overall quality, impacting the algorithms dependent on them. This article introduces a novel technique for real-time imputation of missing data using variational autoencoder (VAE) and utilizing the latent space representation acquired from VAE. The method has demonstrated enhanced accuracy in …

Molecular Simulations Of Selective Adsorption Of Lithium In The No.6 Coal Seam, Junggar Coalfield, Zhang Junshuang, Sun Beilei, Zhang Bin, Liu Chao

Coal Geology & Exploration

Objective With the discovery of metal deposits in coal-bearing strata, the distribution and occurrence patterns of lithium in coals have attracted much attention. However, its partitioning mode between organic structures and minerals in coals remains poorly understood.Methods This study investigated typical coals with a high lithium content in the Junggar Coalfield in Inner Mongolia. By integrating multiple simulation methods, including quantum mechanics, Monte Carlo simulation, and molecular dynamics, this study established the structural models of organic matter and inorganic minerals, as well as a visualized lithium-coal molecular structure model. Accordingly, it investigated the preferential adsorption sites on both organic …

Automatic Detection Of Depression Using A Cnn-Transformer Model Based On Low-Channel Eeg Data, Dongfang Yu, Penghai Li, Fei Su, Kun Wang, Shutong Duan, Ding Yuan

Turkish Journal of Electrical Engineering and Computer Sciences

Background: Accurate and portable diagnostic tools for Major Depressive Disorder (MDD) remain a critical unmet need in clinical practice. Electroencephalography (EEG), with its noninvasiveness and high sensitivity, presents an ideal modality, yet traditional multi-channel EEG systems limit clinical convenience and practical deployment. Methods: We developed a novel CNN-Transformer hybrid model using only eight EEG channels selected from frontal regions to detect MDD. Minimal preprocessing steps (basic filtering) were applied to EEG data before the model automatically learned both local and global signal features through convolutional and self-attention mechanisms. We validated this method through comprehensive experiments, including within-dataset and cross-dataset evaluations, …

Electronically Tunable Cccii And Ota-Based Fractional-Order Meminductor Emulator And Its Application, Bhawna Aggarwal, Rupam Das, Shireesh Kumar Rai

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, two fractional-order meminductor (FOMI) emulators have been realized using second-generation current-controlled conveyor (CCCII) and operational transconductance amplifier (OTA). In the first realization, two OTAs, one CCCII, one resistor, one fractional-order capacitor, and one integer-order capacitor are used. In the second configuration two CCCIIs, one OTA, two resistors, one fractional-order capacitor, and one integer-order capacitor are used. Pinched hysteresis loops have been achieved for a wide range of frequencies. The robustness of the proposed FOMI emulators has been verified through formation of pinched hysteresis loops under process, voltage, and temperature variations. Other characteristics, such as transient analysis, nonvolatility …

Cover And Contents

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Yoganglenet: Body Angle-Based Yogic Posture Classification Approach Using Mediapipe From Single-Person Images, Arun Kumar Rajendran, Sibi Chakkaravarthy Sethuraman

Turkish Journal of Electrical Engineering and Computer Sciences

The profound psychological and physical benefits of yoga have attracted global interest. This study explores yoga pose classification using angle values derived from single-person posture images. The dataset is carefully curated and consists exclusively of single-person yoga postures. The proposed method applies feature selection to improve model performance, achieving high accuracy with the random forest (RF) classifier. Using the top four selected features, our approach attains a maximum testing accuracy of 92.63%. A key contribution of this study is its strong focus on model interpretability. To explain model predictions and clarify decision-making, we employ Local Interpretable Model-Agnostic Explanations (LIME) and …

Industries, Self-Rated Health, And Status Characteristics: An Exploration Of Health In Industries At The Intersection Of Race/Ethnicity, Gender, And Disability, Emmanuel Legarreta

Dissertations and Theses

While industries, occupations, and health outcomes have been widely studied, research has neglected self-rated health (SRH) and the intersectionality of different status characteristics in various industries. Using an IPUMS version of the Current Population Survey, this study explores the possible relationships between industries and SRH. More specifically, it seeks to find if workers' disability status, racial minority status, or gender moderates (i.e., differentiates) the relationship between their industry and SRH. Findings show that certain industries are significant predictors of SRH, and that women with disabilities working in Mining and Construction, and Business and Repair Service have significantly worse SRH than …

Ole Miss Research On Aging Earns Gold Honor, Jordan Karnbach

University of Mississippi News

OXFORD, Miss. – A University of Mississippi researcher's study of how livestreamed nature videos can help older people feel less isolated shows promise to help them stay alert and active. The work has also drawn attention from a nonprofit institute focused on healthy aging.

Face Off: Evaluating Virtual Human Expressions And Non-Tracking Control Methods In Vr, J K Sangeeth Chandran, Marisa Llorens Salvador, Cathy Ennis

Conference papers

Social virtual reality (VR) applications have become more ubiquitous in recent years; central to this is the communication pipeline, how users perceive virtual human facial expressions, and how they control them in real time, especially when using VR devices without face-tracking. We investigated both aspects in a set of experiments. Firstly, we compared the perception of virtual human emotions on a traditional 2D screen and in VR. In a second experiment, we used a validated set of stimuli to compare three different control methods for manipulating an avatar’s facial expressions in VR. These control methods utilize non-tracking control techniques, which …

Fractional-Order Adaptive Terminal Sliding Mode Control For Synchronization Of Uncertain Chaotic Memristive Chua's Circuit, Dorukhan Asteki̇n, Fati̇h Adigüzel

Turkish Journal of Electrical Engineering and Computer Sciences

Memristive-based chaotic dynamical systems exhibit chaotic behavior with signals of unpredictable complex ity, making it difficult to achieve full synchronization in master-slave systems. Therefore, an advanced synchronization method is required to overcome the chaotic model uncertainties and external disturbances. In this study, a fractional order terminal sliding mode synchronization is proposed for the uncertain memristive chaotic Chua’s circuit. After presenting the integer-order model of the chaotic memristive Chua’s circuit, a fractional-order sliding surface-based non linear synchronization structure, incorporating the fractional derivative operator, is designed. The convergence of the synchronization closed-loop system is proven using Lyapunov theory. To demonstrate its effectiveness …

Spectator 2025-09-25, Editors Of The Spectator

The Spectator

No abstract provided.

Quality Improvement Project Empowering Nursing Instructors: Faculty Self-Efficacy & Consistency In Simulation Grading, April Guerin

Doctor of Nursing Practice Projects

This quality improvement (QI) project aims to evaluate the effectiveness of structured training on the Creighton Competency Evaluation Instrument (C-CEI) in improving nursing faculty self-efficacy and grading consistency in clinical student evaluations. Inconsistent clinical grading practices among nursing faculty create barriers to reliable competency evaluation and undermine student outcomes. Guided by the Donabedian Model and Lewin’s Change Theory, with implementation structured by the Plan-Do-Study-Act (PDSA) cycle, a quasi-experimental pre-post intervention design was used. Participants include nursing faculty responsible for clinical evaluations, who completed structured C-CEI training delivered via self-paced modules in a learning management system. Faculty self-efficacy was measured using …

Postsurgical Pain, Psychosocial Functioning, And Cannabis Use Among Adolescents And Young Adults Undergoing Gender Affirming Surgery, Eleanor Battison, Emily A. Kenyon, Corrin Murphy, Eline Lenne, Danielle N. Moyer, Sarah W. Feldstein Ewing, Anna C. Wilson

School of Social Work Faculty Publications and Presentations

Purpose: Little is known about transgender and gender expansive (TGE) adolescents and young adults (AYAs) pain and psychosocial experiences in the acute postsurgical period following gender-affirming surgery (GAS). This study describes pain symptomatology and psychosocial functioning within 1 month after GAS among TGE AYAs, examines immediate postsurgical associations of cannabis use with pain symptomatology, pain catastrophizing, and psychosocial functioning, and explores pain persistence, cannabis use, and psychosocial functioning in a subgroup of individuals 6 months after surgery.

Methods: AYAs (N = 64) underwent GAS at a large academic medical center in the Pacific Northwest between March 2019 and June …

Integrating Artificial Intelligence & Purpose-Driven Design Within Spiritual, Wellness, Eco-Conscious, & Cultural Brands, Jessica Molina

Masters Theses

This visual thesis explores the practical and ethical applications of artificial intelligence in the work of designers for brands that promote wellness, spirituality, eco-consciousness, and cultural identity. The central challenge in adopting AI will be balancing the capitalization on its benefits with assessing the ethical ramifications of its adoption, while still upholding brand values, the imperative of authenticity, emotional intelligence, and integrity. As the technology and capabilities of AI continue to skyrocket, purpose-driven designers will remain under-resourced and underdeveloped in frameworks for ethical adoption. This work seeks to resolve the existing gap through a literature review, case studies, and a …

The Intersection Of Ethnomusicology And Special Education: An Exploration Of Aba-Infused World Music Play Facilitation In The Social-Emotional Development Of Children With Autism Spectrum Disorder, Jean-Pierre Ervelt Leroy

Masters Theses

Inspired by experiences across disciplines, this mixed-method study peered into a possible intersection of ethnomusicology and special education. An innovative ABA-infused world music play facilitation program for children was created to examine how culturally diverse musical intervention in combination with Applied Behavior Analysis (ABA) principles could enhance the social-emotional development in children diagnosed with ASD. To gain an informed context on worldview and structure, this research was conducted within both sacred and secular communities. To gain a comprehensive understanding of how interdisciplinary intervention can impact the self-expression, self-regulation skills, and cultural awareness of children, both quantitative assessments and qualitative observations …

The Cowl - V. 89 N. 2 - September 25, 2025

The Cowl

The Cowl - student newspaper of Providence College. Vol. 89 No. 2 - September 25, 2025. 16 pages.

Leading Learning Health Systems: Strategies Used To Establish And Conduct A Learning Health System, Dawn M. Bravata, Cathy C. Schubert, Amy M. Kilbourne, Scotte R. Hartronft, Ashley L. Schwartzkopf, Jennifer L. Myers, Mindy L. Flanagan, Claire E. Donnelly, Stanley E. Taylor, Mathew J. Reeves, Anthony J. Perkins, Laura E. Myers, Indrakshi Roy, Robert E. Burke, Rachael A. Beard, Marcos Montagnini, Shivani K. Jindal, Greg Arling, Caroline Madrigal, Nicholas A. Rattray

Health Services and Informatics Research

Background

Learning health systems (LHS) improve patient and provider experiences, population health, and health system performance. LHS leaders develop LHS’ social and scientific infrastructures and align the LHS with host organization’s priorities. Although researchers have examined data infrastructure and Learning Community configurations, few studies have evaluated discrete strategies leaders deploy to construct a LHS.

Objectives

We described methods used to establish the Department of Veterans Affairs (VA) Geriatric LHS (GLHS) supporting older Veterans transitioning from hospital to home and examined strategies GLHS leaders used to conduct LHS activities.

Design

Qualitative methods were employed to review notes from all meetings and …

A Collocation Point Sampling Method For Solving The Helmholtz Equation Using Physics-Informed Neural Networks, Shan Lianpu, Yu Caixia, Wang Yanfei

Coal Geology & Exploration

Background In the field of seismic wavefield simulation, physics-informed neural networks (PINNs) have emerged as a new method for efficiently solving the Helmholtz equation due to their characteristic of grid-free computation. However, for the forward modeling of complex medium models using the Helmholtz equation, traditional uniform grid-based methods for collocation point sampling are insufficient to efficiently provide gradient information, leading to prolonged training time and high resource consumption. Objective and Method To improve the forward modeling efficiency and accuracy based on PINNs and overcome the anomalous concentration of collocation points in the seismic source during dynamic sampling, this study proposed …

Electromagnetic Simulations Of Antennas On Gpus For Machine Learning Applications, Murat Temi̇z, Vemund Bakken

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes an antenna simulation framework powered by graphics processing units (GPUs) based on an open-source electromagnetic (EM) simulation software (gprMax) for machine learning applications of antenna design and optimization. Furthermore, it compares the simulation results with those obtained through commercial EM software. The proposed software framework for machine learning and surrogate model applications will produce antenna data sets consisting of a large number of antenna simulation results using GPUs. Although machine learning methods can attain the optimum solutions for many problems, they are known to be data-hungry and require a great deal of samples for the training stage …

Basgit: A Secure Digital Epassport Alternative, Ceren Kocaoğullar, Kaan Yildirim, Mert Ati̇la Sakaoğullari, Alpteki̇n Küpçü

Turkish Journal of Electrical Engineering and Computer Sciences

We present a solution to the challenge of securely issuing both paper-based and mobile phone-based passports without requiring specialized production techniques. Our solution offers improved security, privacy, and usability compared to the ePassport mechanism currently used worldwide. We also describe how our solution can be extended to support offline verification and present the test results of our proof-of-concept implementation.

Federal Court Vacates Nea Implementation Of Trump’S ‘Gender Ideology’ Ban, Arthur S. Leonard

Other Publications

No abstract provided.

Workplace Tug-Of War: The Pennsylvania Supreme Court Weighs Competing Interests With New Cause Of Action To Protect At-Will Employees From Third-Party Interference In Salsberg V. Mann, Alysse Danyi

Villanova Law Review (1956 - )

No abstract provided.

Overriding Overtime In Decentralized Work, Arianne Renan Barzilay

Villanova Law Review (1956 - )

No abstract provided.

A Different Form Of Post-Op: Healing Survivors Of Domestic Violence Through Prosecutorial Anatomy, Elizabeth Ellick

Villanova Law Review (1956 - )

No abstract provided.