Digital Commons Network^™

Computational Thinking As A Novel Framework For Enhancing Cognitive Organization In Older Adults With Cognitive Frailty (Letter To The Editor), Daisuke Akiba

Publications and Research

As aging populations grow, especially in high-income nations, the burden of dementia-related care continues to escalate both economically and socially. In response, this article introduces Computational Thinking (CT) as a novel, non-pharmacological framework to support cognitive organization in older adults experiencing cognitive frailty. Though CT has gained traction in fields like PK-16 education, including special education, for enhancing executive function and problem-solving, it has not yet been applied to geriatric- or memory-care contexts. This perspective proposes that CT’s core components (i.e., decomposition, pattern recognition, abstraction, and algorithmic thinking) may align with residual cognitive strengths in mild-to-moderate dementia, offering a strengths-based, …

Conquer And Prevail Issue 192 July 17 2025, Wofford College. Office Of Marketing And Communications

Conquer and Prevail Newsletter

No abstract provided.

Urban Tree Committees Of New England, Usa: Describing Past, Present, And Future Regional Trends, Alicia F. Coleman, Danica Doroski, Richard W. Harper, Alexander J. Elton, Eli Grigorian, Eric E. Griffith

Cities and the Environment (CATE)

In the United States, grassroots responses have emerged to supplement urban forest management efforts traditionally led by local, county, and federal governments. Urban tree committees are one such grassroots response, whose service exists between a formalized organization and ad-hoc task force. While past research has described the roles and responsibilities of various urban forest management actors, no studies have previously established a baseline understanding of regional urban tree committees, including the membership of paid and volunteer committees, their programming and educational initiatives, and key audiences. In this study, we distributed a participant survey to all known urban tree committees of …

Developing A Stochastic Rupture Model Catalog For Earthquakes With Magnitudes Of Seven Or Greater Along The Alaskan Subduction Zone, Alexandru Mihai Lapadat

Geosciences

Alaska represents one of the most seismically active regions in the Ring of Fire and world impacted by large-magnitude (Mw > 6.5) earthquake events, posing significant risks to local communities and infrastructure, but also distant populations due to the associated tsunami hazard. However, limited seismo-geodetic datasets hinder the understanding of the slip kinematics of megathrust earthquakes in the Alaskan subduction zone, complicating the estimation of future earthquake probabilities, surface displacements, and the design of a GNSS-aided Earthquake Early Warning (EEW) system. This research contributes an extensive synthetic rupture model catalog for the Alaskan subduction zone, generated using the stochastic methodology of …

Bridging The Mind And Body: Functional Neurologic Symptom Disorder Following Sexual Trauma In An Adolescent Girl, Ariel E. Sosa Gomez, Daniel Gutierrez

School of Medicine Publications

Functional neurologic symptom disorder (FNSD) is a multifaceted condition that can present with neurologic symptoms inconsistent with recognized neurological disease, often in the context of psychosocial stressors, though these are not required for diagnosis. We report the case of a 12-year-old Hispanic female who developed episodes of limb paralysis, motor unresponsiveness, and self-injurious behaviors following a history of sexual abuse by a family member. Despite the initial absence of depressive symptoms, the patient later met criteria for major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). Her neurological symptoms lacked identifiable medical findings, following unremarkable results from comprehensive blood work, …

Recent Advances In Modelling Of Frost Formation For Mechanical Systems, Yong Tao

Mechanical Engineering Faculty Publications

The physics underlying frost and ice formation has been extensively studied over the past few decades, with significant contributions to our understanding of this phenomenon. These insights have primarily been applied to engineering systems with refrigerated surfaces, such as refrigerators, freezers and heat pumps of various sizes. Despite considerable progress, the dynamic and complex mechanisms governing frost and ice formation remain an active area of research, as competing factors continue to challenge predictive accuracy. The increasing interest from stakeholders in reducing energy consumption and carbon footprints in mechanical systems further underscores the importance of advancing modelling and simulation capabilities in …

Super-Resolution Stimulated X-Ray Raman Spectroscopy, Kai Li, Christian Ott, Marcus Agåker, Phay J. Ho, Gilles Doumy, Alexander Magunia, Marc Rebholz, Marc Simon, Tommaso Mazza, Alberto De Fanis, Thomas M. Baumann, Jacobo Montano, Nils Rennhack, Sergey Usenko, Yevheniy Ovcharenko, Kalyani Chordiya, Lan Cheng, Jan Erik Rubensson, Michael Meyer, Thomas Pfeifer, Mette B. Gaarde, Linda Young

Faculty Publications

Propagation of intense X-ray pulses through dense media has led to the observation of phenomena such as atomic X-ray lasing^1,2, self-induced transparency³ and stimulated X-ray Raman scattering (SXRS)⁴. SXRS has been long predicted as a means to launch and probe valence-electron wavepackets and as a building block for nonlinear X-ray spectroscopies^5,6. However, experimental observations of SXRS to date^4,7,8 have not provided spectroscopic information, and theoretical modelling has largely implemented hard-to-realize phase-coherent attosecond pulses. Here we demonstrate SXRS with spectroscopic precision, that is, detection of valence-excited states in neon with a near Fourier-limited …

Quantum Memory, Isabel Martinez-Robles

Physics and Astronomy Summer Fellows

Isolated quantum systems are almost always observed to achieve thermal equilibrium in experiments. Understanding cases where they do not thermalize, and therefore retain memory about the initial state, could lead to the development of a quantum memory. We excite atoms in a magneto-optical trap, where they are cold enough to treat as stationary. In our experiment, our atoms exchange energy via dipole-dipole interactions and fail to thermalize. We present a theoretical and computational analysis that suggests that our system starts in an exceptional initial state.

Cover

Louisiana Law Review

No abstract provided.

Diffusion Model For Medical Image Denoising, Reconstruction And Translation, Wei Wang, Shuo Li

Faculty Scholarship

Diffusion models, as a class of generative models, have demonstrated significant performance in image generation since their inception. The fundamental principle behind diffusion models is the definition of a forward process and a reverse process. The input data is progressively perturbed by adding random noise during the forward process, and the expected noise distribution is learned. In the reverse process, noise is gradually reduced from a Gaussian distribution to generate the image. Recently, diffusion models have been widely adopted in various image processing tasks, including text-to-image synthesis, denoising, segmentation, and object detection. In medical image analysis, diffusion models have shown …

Limitations Of Using Large Language Models For Automated Essay Scoring, Thomas A. Fink

Theses

Background: Automated essay scoring (AES) is a challenging deep learning problem. The two most widely used methods for predicting essay quality scores, supervised learning-based and LLM-based, have their own limitations. Although supervised learning-based methods are more accurate, they only predict a score and do not offer descriptive feedback to students. On the other hand, LLM-based methods can offer rubric-guided feedback but are known to be less accurate.

Methods: This work focuses on improving the accuracy of state-of-the-art LLM-based AES methods. We began by thoroughly investigating why these methods were performing poorly for certain datasets and certain examples. This led us …

Predicting Sleep And Sleep Stage In Children Using Actigraphy And Heartrate Via A Long Short-Term Memory Deep Learning Algorithm: A Performance Evaluation, Robert Weaver Med, Phd, James White, Olivia Finnegan, Hongpeng Yang, Zifei Zhong, Keagan Kiely, Catherine Jones, Yan Tong, Srihari Nelakuditi, Rahul Ghosal, David E. Brown, Russell R. Pate Ph.D., Gregory J. Welk, Massimiliano De Zambotti, Yuan Wang, Sarah Burkart, Elizabeth L. Adams Phd, Bridget Armstrong, Michael Beets Med, Mph, Phd

Faculty Publications

Children's ambulatory sleep is commonly measured via actigraphy. However, traditional actigraphy measured sleep (e.g., Sadeh algorithm) struggles to predict wake (i.e., specificity, values typically < 70) and cannot predict sleep stages. Long short-term memory (LSTM) is a machine learning algorithm that may address these deficiencies. This study evaluated the agreement of LSTM sleep estimates from actigraphy and heartrate (HR) data with polysomnography (PSG). Children (N = 238, 5–12 years,52.8% male, 50% Black 31.9% White) participated in an overnight laboratory polysomnography. Participants were referred be-cause of suspected sleep disruptions. Children wore an ActiGraph GT9X accelerometer and two of three consumer wearables(i.e., Apple Watch Series 7, Fitbit Sense, Garmin Vivoactive 4) on their non-dominant wrist during the polysomnogram. LSTM estimated sleep versus wake and sleep stage (wake, not-REM, REM) using raw actigraphy and HR data for each 30-s epoch. Logistic regression and random forest were also estimated as a benchmark for performance with which to compare the LSTM results. A 10-fold cross-validation technique was employed, and confusion matrices were constructed. Sensitivity and specificity were calculated to assess the agreement between research-grade and consumer wearables with the criterion polysomnography. For sleep versus wake classification, LSTM outperformed logistic regression and random forest with accuracy ranging from 94.1to 95.1, sensitivity ranging from 94.9 to 95.9 across different devices, and specificity ranging from 84.5 to 89.6. The addition of HR improved the prediction of sleep stages but not binary sleep versus wake. LSTM is promising for predicting sleep and sleep staging from actigraphy data, and HR may improve sleep stage prediction.

July 17, 2025 Minutes, Swosu Faculty Senate

Faculty Senate Minutes

No abstract provided.

Enjoined From Enjoining: The State Of Remedies And Relief For Immigrants After Garland V. Aleman Gonzalez, Kate Weaver

Louisiana Law Review

No abstract provided.

Preventing The Police From Using Private Information Obtained Through An Unlawful Search – An Australian Perspective, Sirko Harder

Louisiana Law Review

No abstract provided.

Give Scotus’S Code Of Conduct Teeth: Using Impeachment To Enforce The United States Supreme Court’S Code Of Conduct, Tara Roussel

Louisiana Law Review

No abstract provided.

Risky Business: Should Louisiana Adopt A Jurisdictional Consent Statute After Mallory V. Norfolk Southern Railway Co.?, Madelyn Graves

Louisiana Law Review

No abstract provided.

Can Commentary Command Courtroom Clout?: The Court’S Deference To Commentary To The United States Sentencing Guidelines In A Post-Kisor World, Gabriella A. Leccese

Louisiana Law Review

No abstract provided.

The Local Neighborhood Interactions Shaping Tree Communities Through Ecological Disturbance And Environmental Change, Cole Doolittle

Dissertations (1934 -)

My dissertation consists of four chapters focused on understanding the factors maintaining local species diversity, addressing a central goal of ecology increasingly critical for preserving ecosystem services and human well-being in the face of climate change. Specifically, I investigate how local neighborhoods – that is, the spatial arrangement, density, and identity of nearby competitors – contribute to patterns of growth and survival along gradients of ecological disturbance and environmental change using forest tree communities as a study system. In my first chapter, I develop a conceptual framework that synthesizes why we may expect local neighborhood interactions to weaken under ecological …

Correlated Sampling Of Parallel Partial And Linked Emulators For Geophysical Applications, Joseph Lyon

Dissertations (1934 -)

Computer models, or simulators, are mathematical representations of real world phenomena that, to run at new input settings, are often computationally intensive and prohibitively slow. Surrogate models, or emulators, provide a method of rapidly predicting simulator outputs with uncertainty at untested configurations by treating the computer model output as a single realization of a stochastic process, specifically a Gaussian Process (GP).In this dissertation, we consider three projects: Correlated Linked GP Emulation, Spatially Correlated Parallel Partial Emulation, and Optimizing the Zero-censored Gaussian Process with Spatially Correlated Sampling. First, the Correlated Linked Emulator, focuses on developing a model for the covariance of …

Patient-Centered, Theory-Based, Online Intervention To Promote A Physically Active Lifestyle For People With Multiple Sclerosis: Protocol For A Randomized Controlled Trial, Chungyi Chiu, Vaishnavi Sridharan, Mojtaba Khaliji, Md Refat Uz Zaman Sajib, Xiaotian Gao, Kathleen Zackowski

Children’s Nutrition Research Center Staff Publications

Background: People with multiple sclerosis (MS) experience life challenges due to the nature of disease progression. Although an active lifestyle has been shown effective for symptom and relapse management, most people with MS lead a sedentary lifestyle and do not reach the recommended physical activity (PA) guidelines.

Objective: This study aims to test the preliminary efficacy of a codeveloped, online self-management intervention based on the health action process approach (HAPA) adapted for people with MS to cultivate a physically active lifestyle.

Methods: The 8-week intervention program was developed using community-based participatory research based on the HAPA. The program includes increasing …

Suppression For The Sake Of Democracy: Brazil’S Judiciary And The Fight To Control The Internet, Isaiah Hinton

Maryland Journal of International Law

No abstract provided.

Native Hawaiians And Environmental Stewardship: Reclaiming The ‘Āina In The Face Of A Western System, Lauren Wiederkehr

Maryland Journal of International Law

No abstract provided.

Stokes-Dependent Droplet Collection Efficiency On A Naca 0012 Airfoil From Droplet-Informed Simulations With Statistical Overloading, Arash Shad, Hashnayne Ahmed, ‪Nadim Zgheib, S. Balachandar, S. A. Sherif

Mechanical Engineering Faculty Publications

Accurate modelling of ice accretion on aircraft wings requires analysing droplet impingement on the surface to optimize the design of ice-protection systems. We perform Euler–Lagrange simulations of a droplet-laden flow impinging on a NACA 0012 airfoil. Our study includes water droplets with eight discrete sizes ranging from 1 to 160 microns. We vary the free-stream velocity of the incoming airflow in the range 60≤⁢𝑈≤⁢240 m s−1 and the chord length of the airfoil in the range 0.5≤⁢𝑐≤⁢2 m. Due to the dilute nature of supercooled clouds, one-way coupling is used in the simulations. The effects of droplet breakup and collision …

Numerical Simulation Of Frost Formation And Heat Transfer On Fin-And-Tube Heat Exchangers In Turbulent Cross-Flow, Mahsan Farzaneh, ‪Nadim Zgheib, S. Balachandar, S. A. Sherif

Mechanical Engineering Faculty Publications

Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050≤𝑅⁢𝑒𝐷,avg≤4800, with the characteristic …

Allied Health Student's Attitudes And Beliefs On Health Literacy Issues Focused On The Non-Native English-Speaking Community, Amy I. Thompson

Graduate Theses, Dissertations, and Capstones

Today's allied health students and their professors are faced with many challenges, including the low level of health literacy among the United States population. Healthy People 2020 defined health literacy as “the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions” (Healthy People 2030). This definition was expanded in Healthy People 2030, to include concepts related to personal and organizational health literacy. Social determinates, such as a language barrier, further complicates an already complex situation with health literacy levels. This focus group, interview-based qualitative …

Exploring Physician Associates’ Perceptions Of Motivational Interviewing: A Phenomenological Study, Thaddeus Riley

Graduate Theses, Dissertations, and Capstones

Longer lifespans across the population are contributing to a rise in chronic illnesses that require ongoing treatment. This increase has furthered the need for evidence-based clinical tools to effectively treat long-term diseases. Motivational Interviewing (MI) is an evidence-based method used by physicians and other healthcare practitioners, including physician associates (PAs), to help patients facilitate health behavior changes. PAs are licensed, highly trained healthcare professionals who practice medicine across all specialties and settings. PAs focus on patient-centered, team-based care and play a key role in expanding access to healthcare and improving overall health outcomes (AAPA, 2023b). While MI’s efficacy has been …

Cognitive Fatigue Assessment For Human-Robot Collaboration: Review & Open Challenges, Manizheh Zand, Sally Wood, Fatemeh Davoudi Kakhki, Maria Kyrarini

General Engineering

As Human Robot Collaboration (HRC) technologies continue to advance, robots are increasingly being deployed to assist in various settings, including manufacturing, healthcare, and home environments. A critical aspect of designing safe and adaptable HRC systems is the ability to assess and monitor an individual’s Cognitive Fatigue (CF) during interactions with robots. This is especially important in ensuring safe and effective environments, as fluctuations in CF can affect both performance and safety. Although prior research has explored cognitive workload and fatigue, a significant gap exists in understanding how to effectively measure and manage CF in real-time during HRC. This paper reviews …

Creatine Monohydrate Supplementation For Older Adults And Clinical Populations, Darren G. Candow, Sergej M. Ostojic, Philip D. Chilibeck, Igor Longobardi, Bruno Gualano, Mark A. Tarnopolsky, Theo Wallimann, Terence Moriarty, Richard B. Kreider, Scott C. Forbes, Uwe Schlattner, Jose Antonio

Faculty Publications

Background: The biological process of aging is typically associated with a decrease in muscle quantity, muscle performance (primarily strength), bone mass and architecture, functionality and neurological/cognitive function. From a healthy aging perspective, interventions that have the potential to overcome or attenuate these decrements are clinically relevant.

Methods: We conducted a narrative review on the efficacy of creatine monohydrate supplementation (CrM) in older adults. Results: Accumulating research shows that CrM, primarily when combined with exercise training, is safe and has beneficial effects on measures of whole-body lean body mass, regional muscle size, muscle strength, bone area and thickness, functional ability, glucose …

Post-Wildfire Erosion And Sedimentation: An Escalating Threat For Utah Fisheries, Colton James, Kendall Becker, Scott Hotaling, Aish Chandrasekaran, Alex Fiedler, Timothy E. Walsworth, Patrick Belmont

All Current Publications

Wildfires are a natural part of the western U.S. landscape and provide numerous benefits, including enhanced nutrient cycling and habitat rejuvenation. Utah’s fish populations evolved with wildfire as a common disturbance. However, the increasing size and severity of wildfires, combined with Utah’s heavily engineered and fragmented stream networks, pose a contemporary risk to fish populations. This fact sheet reviews wildfire impacts on erosion and Utah's watersheds and fisheries. It outlines measures we can take to prevent post-wildfire fish die-offs.