Digital Commons Network^™

Countries As Laboratories: Reflections On Sierra Leone’S Amended Anti-Human Trafficking Law, Andrea L. Dennis

Scholarly Works

Sierra Leone’s improved anti-trafficking laws align with global norms, but enforcement remains weak due to socio-economic realities and Western deterrence mismatches, limiting effective prosecution despite recent legislative reforms.

Relational Mentoring In Troubled Times, Fatima Suarez, Veronica Montes, Emir Estrada, Pierrette Hondagneu-Sotelo

Sociology Faculty Research and Scholarship

No abstract provided.

Legal Pathways To Professionalizing The Procurement Workforce For Good Governance To State Contracts: A Comparative Study, Karem Sayed Aboelazm, Fady Tawakol, Emad Ibrahim, Hanadi Sharif

All Works

This study addressed several concepts in the study’s conceptual framework, which were based on profession, professionalization, and professionalism in public procurement. It also discussed the importance of professionalizing public procurement functions and its impact on public procurement performance (Angaw, 2020). The study also aimed to analyze the most prominent global practices in raising the efficiency and capabilities of public procurement workers to reach complete professionalism in public procurement. The paper attempted to investigate the possibility of professionalism in public procurement and its effects on the good governance of state contracts. The paper relied on two basic research approaches, namely the …

Llm-Driven Apt Detection For 6g Wireless Networks: A Systematic Review And Taxonomy, Muhammed Golec, Yaser Khamayseh, Suhib Bani Melhem, Abdulmalik Alwarafy

All Works

Sixth Generation (6G) wireless networks, which are expected to be deployed in the 2030s, have already created great excitement in academia and the private sector with their extremely high communication speed and low latency rates. However, despite the ultra-low latency, high throughput, and AI-assisted orchestration capabilities they promise, they are vulnerable to stealthy and long-term Advanced Persistent Threats (APTs). Large Language Models (LLMs) stand out as an ideal candidate to fill this gap with their high success in semantic reasoning and threat intelligence. This paper presents the first systematic review and taxonomy for LLM-assisted APT detection in 6G networks. It …

Streamlining Digital Elevation Model Construction From Historical Aerial Photographs: The Impact Of Reference Elevation Data On Spatial Accuracy, Xin Hong, Christopher H. Roosevelt

All Works

This study proposes a streamlined workflow for producing historical digital elevation models (hDEMs) from scanned 1950s aerial photographs using structure-from-motion and multi-view-stereo (SfM-MVS) techniques along with co-registration methods. We also conducted a sensitivity analysis to assess the impact of DEM references with varying spatial resolutions on the SfM-MVS process and co-registration accuracy. The DEM references included a 30 m SRTM DEM (low resolution), a 12 m TanDEM-X DEM (medium resolution), and a 5 m DEM provided by the General Directorate of Mapping of the Ministry of National Defense, Republic of T & uuml;rkiye (high resolution). Results indicate that higher resolution …

Science Education In The Age Of Misinformation, Elissar Gerges

All Works

No abstract provided.

Founder Worship, Effective Altruism, And Corporate Governance, Jennifer S. Fan, Xuan-Thao Nguyen

Law Faculty Research and Publications

Founders are the heart of any startup. Oftentimes, they are given considerable latitude in managing a company, particularly if they are hailed as a visionary founder in a pathbreaking new industry. Additionally, it is assumed that underpinning their actions is the desire to do good. Unfortunately, sometimes this leads to what we term founder worship where the promise of the founder and the innovation may lead to perverse outcomes because too much control is ceded to the founder and there is a lack (or sometimes complete absence of) corporate governance. When unlimited control is coupled with "do gooderism," which in …

Ai Innovations In Rppg Systems For Driver Monitoring: Comprehensive Systematic Review And Future Prospects, Soha G. Ahmed, Katrien Verbert, Nazar Zaki, Ashraf Khalil, Hamad Aljassmi, Fady Alnajjar

All Works

Advanced technologies, notably camera-based systems using remote photoplethysmography (rPPG), are increasingly used in automotive safety to non-invasively monitor driver well-being and fatigue by measuring physiological metrics like heart and respiration rates. This review examines recent advancements in machine learning algorithms and signal processing for rPPG in driver monitoring. A literature search up to April 2, 2024, across major databases, identified 344 studies; 29 were analyzed in depth, focusing on: 1) rPPG signal extraction and heart rate estimation, where deep learning improved accuracy; 2) fatigue detection, showing benefits of multimodal data fusion; 3) mental state monitoring, with machine learning classifying cognitive …

University Students' Understanding And Utilization Of Food Labels: A Cross-Sectional Study, Sharifa Alblooshi, Linda Smail, Asya Aldayyani, Falak Zeb, Alia Ibrahim

All Works

Introduction: This study is aimed at investigating Zayed University students' knowledge, attitudes, and practices (KAPs) regarding food labels and at identifying key predictors of food label use through logistic regression analysis.Methods: This quantitative cross-sectional study used a validated questionnaire to elicit data on KAPs regarding the use of nutritional information and food labels. This study was conducted from January to May 2023 in the UAE among students from Zayed University. A total of 1153 students aged 18 and above from Zayed University participated in the study. They were recruited using snowball sampling. Descriptive statistics were obtained using the Statistical Package …

Designing Ai To Foster Acceptance: Do Freedom To Choose And Social Proof Impact Ai Attitudes Among British And Arab Populations?, Sameha Alshakhsi, Mohamed Basel Almourad, Areej Babkir, Dena Al-Thani, Ala Yankouskaya, Christian Montag, Raian Ali

All Works

This study examines the impact of two key AI modalities–freedom of choice (FoC) and social proof (SP)–on public attitudes toward AI, focusing on cultural differences between UK and Arab participants. FoC refers to the option of selecting a non-AI, possibly human, alternative, while SP means knowing that others have used AI without issues. Four scenarios were designed, combining the presence or absence of these modalities. The context was a customer service chatbot for a telecommunications company, familiar to all participants. A total of 639 participants (316 British and 323 Arab) were introduced to the modalities and then the scenarios in …

Certain Knowledge Of Administrative Decisions Issued By Artificial Intelligence Systems In The Public Sector: A Comparative Analysis, Nayel Musa Alomran, Odai Mohammad Alheilat

All Works

This paper aims to elucidate the matter of certain knowledge pertaining to administrative decisions, those issued by artificial intelligence. It also clarifies the position of the administrative judiciary with regard to the adoption of this presumption and through a comparative analysis of administrative judicial applications in Jor-dan, Egypt, and Morocco. The text addresses the most significant evidence for achieving certain knowledge of an administrative decision – and thereby initiating the appeal period against the appellant. The question at hand is whether the administrative judiciary applies the traditional theory of certain knowledge to its counterpart issued by artificial intelligence systems, especially …

Performance Based Scheduling In Distributed Mixed Criticality Systems, Amjad Ali, Saud Wasly, Asad Masood Khattak, Ihsan Ali, Shahid Iqbal, Bashir Hayat

All Works

With a focus on computationally intensive, distributed, and parallel workloads, scheduling in mixed-criticality distributed systems presents significant challenges due to shared memory and resources, as well as the diverse demands of tasks. The system’s efficiency is heavily dependent on the overall scheduling duration (make span), while individual task deadlines impose strict timing constraints. When the tasks need to simultaneously access the shared memory, then these tasks interfere the execution of one another. For managing the scheduling of interfering tasks in distributed mixed-criticality systems, a novel Interference-Aware Partitioning Fixed Priority (IAP-FP) approach is proposed, which effectively handles task partitioning among cores …

Enhancing Teachers’ Design Thinking Mindsets Through Reflective Practice: Cultivating Innovation In An Upskilling Steam Training Program, Areej Elsayary

All Works

Promoting innovation in education through enhanced design thinking (DT) mindsets among teachers is a central goal. This study examines the use of reflective practice within an upskilling STEAM training program to achieve this enhancement. The upskilling training initiative examined in this research encompasses a ten-week instructional session characterized by a hybrid learning methodology under the guidance of an instructor. An explanatory mixed method design is employed, starting with a quantitative method (teachers’ survey) followed by a qualitative method (focus group discussion). The participants were in-service K-12 teachers (n = 55) from charity schools across Northern Emirates in the United Arab …

Investigation Of Symptom-Specific Functional Connectivity Patterns In Parkinson’S Disease, Ani Kicik, Ali Bayram, Emel Erdogdu, Elif Kurt, Dilek Betul Saridede, Sevim Cengiz, Basar Bilgic, Hasmet A. Hanagasi, Esin Ozturk-Isik, Hakan Gurvit, Erdem Tuzun, Tamer Demiralp

All Works

Parkinson’s disease (PD) is a complex neurodegenerative disease, characterized by pronounced heterogeneity in symptoms. This study investigates the functional connectivity (FC) patterns associated with distinct symptom clusters, aiming to elucidate the heterogeneity in PD and uncover the neural mechanisms underlying its motor and cognitive symptoms. Resting-state functional MRI (rs-fMRI) data from 55 non-demented PD patients and 24 healthy controls (HC) were used to perform seed-to-seed FC analyses. A clustering algorithm was applied to the cognitive and motor scores of all PD patients to generate relatively homogeneous symptomatic subgroups. PD patients exhibited a general decrease in FC within a network comprising …

Heavy Metal Pollution In Arid Urban Environments: Anthropogenic And Geogenic Insights From Road Dust In The United Arab Emirates, Yousef Nazzal, Alina Bărbulescu, Manish Sharma, Fares Howari, Imen Ben Salem, Rania Dghaim, Pramod Kumbhar, Cijo M. Xavier, Suhail Alghafli, Ahmed A. Al-Taani, Mutaz Mohammad, Azzah Nasser Salem Nayem Alkaabi, Saif Nazzal, Cristian Ștefan Dumitriu

All Works

Dust is a significant environmental concern due to its pervasive nature and potential health risks, particularly from heavy metals. This is exacerbated in urban areas, where dust can act as a reservoir for pollutants, posing risks to human health through various exposure pathways. This study aims to explore and compare the distribution of heavy metals in road dust from two distinct cities in the UAE: Dubai, a commercial hub, and Khor Fakkan, a coastal town with industrial activities. Road dust samples were collected from 29 locations in both cities, including areas with varying traffic density, residential settings, and industrial zones. …

Association Of Obesity With Musculoskeletal Health And Functional Mobility In Females—A Systematic Review, Dhanya Menoth Mohan, Fatme Al Anouti, Nupur Kohli, Kinda Khalaf

All Works

Obesity is a prevalent global health challenge with a significant yet unclear impact on musculoskeletal health, particularly among females. This systematic review aimed to unravel the association between obesity and musculoskeletal health, as well as functional mobility in women. A comprehensive literature search was conducted across PubMed, Scopus, Web of Science, and the Cochrane Library for articles published between January 2001 and December 2023. Studies were selected based on their examination of the relationship between overweight or obesity and musculoskeletal health (including bones, joints, and soft tissues) and/or functional mobility in adult females (age ≥19) within the general population. Studies …

In The Clear: Timber Harvest Informs Elk Summer Nutrition And Resource Selection In A Densely Forested Landscape, Trevor C. Weeks

Graduate Student Theses, Dissertations, & Professional Papers

As wildlife and habitats face unprecedented challenges in the form of landscape conversion, shifting disturbance regimes, and climate change, it becomes increasingly important for land and wildlife managers to find avenues for collaboration as they seek to maintain habitat to support robust wildlife populations. Timber harvest may provide one such avenue for collaboration. It has been shown to increase the quality and quantity of ungulate nutritional resources by reverting stands to early successional stages. Additionally, timber harvest may allow for a more precise application of such effects, as managers choose where and how to harvest timber. However, the exact effects …

Expression Of Dementia Biomarkers In Appalachian And Non-Appalachian Elvo Patients During Thrombectomy, Neha Anil, Christopher J. Mclouth, Hunter S. Hazelwood, Elise Dahlke, Jacqueline A. Frank, Nathan Millson, Mais Al-Kawaz, Jordan P. Harp, Will Cranford, Shivani Pahwa, David Dornbos, Justin F. Fraser, Keith R. Pennypacker

Biostatistics Faculty Publications

Background/Context: Vascular Cognitive Impairment and Dementia (VCID) affects 25-30% of stroke patients and includes cognitive impairments caused by vascular injury, such as post-stroke dementia. Rehabilitation has the potential to improve the quality of life for patients at risk of developing dementia. However, there is currently no reliable method to identify those at risk of dementia after a stroke. Several biomarkers, including ADRD (Alzheimer’s disease and related dementias) biomarkers (Ab, tau, NfL, and GFAP) and angiogenic factors (VEGF, Flt-1, Tie-2, PIGF, and FGF) have been associated with the development of dementia. Populations in Appalachia experience a higher incidence of stroke and …

Effects Of Dietary L-Tryptophan On Growth Performance, Feed Utilization, And Protein Metabolism In Nile Tilapia (Oreochromis Niloticus), Israt Mishu, Lindee Mason, Ahmed Mustafa

Mansoura Veterinary Medical Journal

This research examines the impact of dietary L-tryptophan supplementation on growth performance, feed efficiency, and protein metabolism in Nile tilapia (Oreochromis niloticus) under stress and non-stress settings. This experiment evaluated essential growth metrics, encompassing weight gain, length gain, specific growth rate, feed conversion ratio, and protein energy retention. Nile tilapia were categorized into four experimental groups: a control group on a commercial diet, a control group supplemented with L-tryptophan (0.33%/kg feed), a stress-induced group receiving cortisol (0.02%/kg feed), and a stress-induced group receiving both cortisol (0.02%/kg feed) and L-tryptophan supplementation (0.33%/kg feed). The findings indicated that Ltryptophan supplementation significantly enhanced …

Data-Driven Melt Pool Monitoring And Defect Prediction In Lpbf Of Ti-6al-4v Alloy, Marshima Mohd Rosli, Ali Rachini, Musaria Karim Mahmood

Babylonian Journal of Mechanical Engineering

Real-time process monitoring is essential for achieving consistent part quality in Laser Powder Bed Fusion (LPBF), yet robust and practical defect prediction frameworks remain underdeveloped. This study presents a machine learning-based approach for predicting unstable melt pool conditions, leveraging an open dataset of melt pool variability measurements from Ti-6Al-4V builds on an EOS M290 system. The framework utilizes fundamental process parameters—laser velocity, power, scan orientation, and track location—combined with statistical melt pool geometry features to train a Random Forest classifier. The model achieved an accuracy of 99.79% in distinguishing between stable and unstable melt pool states, with balanced sensitivity and …

Relative Seat Height Effects On Knee Joint Kinematics In Older Adults, Sadie N. Zimmerman

Research Papers

No abstract provided.

Digitized Asic (Adaptation, Standardization, Integration, And Compliance) Framework: An Innovation For Optimizing Technologies And Innovations For Medical And Higher Education., Joshua Owolabi

PCOM Scholarly Works

This article serves several specific purposes: Presenting transferable information on transforming innovative ideas into educational products with practical applications; showcasing a digitized version of a leading innovation aimed at optimizing technologies and innovations in medical education, health professions education, and higher education; advancing an evidence-based approach to integrating innovations into educational ecosystems and promoting education through innovations and technologies. A 10-step approach to developing the ASIC framework (ASIC stands for Adaptation, Standardization, Integration, and Compliance) is presented, with explanations and illustrations of the processes and activities involved. Empirical evidence and sound principles are provided in support of activities to assure …

A Holistic Approach To Treatment Of Rosacea During Pregnancy: A Systematic Review, Emily Garelick, Margaret Hurley, Lauren Noto-Bell, Stefanie Cubelli

PCOM Scholarly Works

Background: Rosacea is a chronic inflammatory skin condition that is commonly exacerbated during pregnancy. Many patients suffer from emotional distress as a result of their rosacea, but the standard treatment options can cause harm to a developing fetus.

Methods: A systematic review was conducted on PubMed and EMBASE using the keywords “rosacea,” “pregnancy,” “treatment,” “holistic,” “edema, and “osteopathic manipulative treatment” (OMT). 113 papers were extracted and screened to determine eligibility based on inclusion criteria: primary sources, rosacea diagnosis, and documented treatment. Those that did not meet criteria were excluded and 20 papers remained for this review.

Results: The 20 included …

Multiple Myeloma Inhibitory Effects Of Natural Compounds: Enhancement Through Nanoparticle Carriers., Erica Wong, Anna Staskiewicz, Joshua Pruner, Jean Lee, Michael Tucker, Barkley Smith, Lanerica Rogers, Ganiat Asuni, Xinyu Wang

PCOM Scholarly Works

Natural compounds have emerged as promising therapeutic agents for treating cancers such as multiple myeloma (MM). However, poor bioavailability, low stability, and suboptimal targeting often limit their clinical efficacy. Recent advances in nanotechnology have addressed these limitations by utilizing nanoparticle (NP) carriers to enhance the therapeutic potential of natural compounds through improved solubility, stability, and selective delivery to cancer cells. This review explores the inhibitory effects of key natural compounds on MM cells, including 2-cyano-3,12-dioxooleana-1,9-dien-28-oic acid (CDDO) and its derivatives, caffeic acid phenethyl ester (CAPE) and its derivatives, xanthohumol (XN) and its derivatives, resveratrol (RSV) and its derivatives, curcumin (CUR), …

Marijuana Advertising: Comparing Tobacco And Alcohol Industries, Kailey Houck

Fordham Urban Law Journal Online

No abstract provided.

Historic Rock Hill Collection - Accession 1844, Historic Rock Hill, Rock Hill, Sc, White Family, Rock Hill History

Manuscript Collection

The Historic Rock Hill Collection consists of materials relating to the history of Rock Hill, South Carolina and its notable historic buildings, businesses, and people. The collection also documents the pioneering White Family of Rock Hill as well as the history of Historic Rock Hill, a nonprofit historical preservation organization headquartered at the historic White Home in Rock Hill, SC. Founded in the 1980s as the Midtown Preservation Association, the group continues to work to preserve and promote the many historic sites and stories of Rock Hill through preservation projects and educational programming. HRH records (by-laws, newsletters, agendas, etc.), …

Automated Classification Of Cardiac Anomalies Through The Analysis Of Electrocardiogram Signals Using Convolutional Neural Networks., Yhosely Isset Villegas Baldiviezo

ICT

Electrocardiography (ECG) is a widely used non-invasive method for monitoring cardiac activity and detecting heart abnormalities. However, manual interpretation can be time-consuming and prone to human error, particularly for non-specialists. This study investigates the use of deep learning techniques, specifically convolutional neural networks (CNNs), to automate ECG signal classification using a large-scale dataset. A classical machine learning model is also included as a baseline for comparison. The aim is to evaluate the potential of deep learning as a clinical decision-support tool that can assist healthcare professionals in improving diagnostic accuracy and supporting early detection of cardiac conditions.

Predicting Early Hospital Readmissions For Diabetic Patients Using Machine Learning, Amanda Ferraz, Leonardo Oliveira

ICT

This project applies machine learning to predict whether diabetic patients will be readmitted to a hospital within 30 days of discharge. Early readmissions are a costly and critical issue in healthcare, often signalling gaps in post-discharge care and risk management. Diabetic patients face unfair high readmission rates compared to the general population. According to the CDC Diabetes Report Card 37.3 million people in the U.S. or 11.3% of the population had diabetes as of 2019 (CDC, 2021). Our goal here is to develop a binary classification model capable of flagging high risk patient (< 30-day readmission) based on their clinical, demographic, and administrative data. This lets healthcare institutions to take measures,

Analysis Of The Patterns And Features Importance In Predicting Demand For Sustainable Urban Mobility. A Comparative Analysis Of Machine Learning Models Using The Dublin Bikes Dataset., Wojciech Sochanski

ICT

This study explores the application of machine learning models to predict demand in the Dublin bike-sharing scheme. A comprehensive literature review examines prior work on sustainable urban mobility, the evolution of bike-sharing schemes, the application of machine learning in predictive analytics and relevant case studies. Secondary data were gathered from publicly available sources, pre-processed and merged into a single, unified dataset. Exploratory data analysis was conducted before preparing the data for modelling to assess the data quality, with a focus on missing values.

Four predictive machine learning models – Linear Regression (LR), Decision Tree (CART), Random Forest (RF) and Gradient …

Durability Of Precast Prestressed Concrete Pile In Exposure Severe Environment, Nantawat Khomwan, Pinai Mungsantisuk

Journal of Metals, Materials and Minerals

This research project focuses on studying the corrosion resistance of precast prestressed concrete (PC) piles under severe conditions. All PC and non-PC samples were cast using Portland cement type III. The samples included 1 m and 6 m length specimens. To evaluate the effectiveness of corrosion prevention, Sacrificial Anode Cathodic Protection (SACP) was installed in the specimens. Various durability properties of concrete were tested, including chloride permeability, concrete resistivity, and half-cell potential. For short-term effects, an electrical accelerated condition was conducted for the 1 m specimens, which were submerged in a 5% sodium chloride solution by weight. Experimental studies were …