Digital Commons Network^™

Vitamin D Status During Pregnancy Modulates The Effect Of Pre-Pregnancy Obesity On Gestational Diabetes Mellitus Risk: A Birth Cohort Study, Ali H. Ziyab, Abdullah Al-Taiar, Reem Al-Sabah, Majeda S. Hammoud, Saeed Akhtar

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Objective:

To determine whether gestational vitamin D status modulates the effect of pre-pregnancy obesity on gestational diabetes mellitus (GDM) risk while stratifying by maternal age.

Design:

Birth cohort.

Setting:

A major maternity hospital in Kuwait.

Participants:

Pregnant women in their second/third trimester of gestation were enrolled. Pre-pregnancy body mass index (BMI, kg/m²) was categorized as under/normal weight (< 25.0), overweight (25.0 to < 30.0), and obesity (≥30.0). Gestational 25-hydroxyvitamin D concentrations were categorized as deficiency (< 50 nmol/L) or insufficiency/sufficiency (≥50 nmol/L). GDM status was ascertained according to international guidelines. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were estimated using logistic regression.

Results:

Data from 957 pregnant women were analyzed, with GDM affecting 166 (17.4%) pregnancies. Pre-pregnancy obesity and gestational vitamin D deficiency was ascertained in 275 (28.7%) and 533 (55.7%) pregnant women, respectively. The association between pre-pregnancy obesity and GDM risk differed according …

The Crucial Role Of Machine Learning Models In Predicting Current Childhood Asthma: Model Comparison, Calibration, And Shap-Based Interpretation, Aditya Chakraborty, A. K.M. Raquibul Bashar

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background: Asthma is one of the most prominent chronic diseases in children and one of the most challenging ailments to diagnose in infants and preschoolers in the United States. Predictive models can be instrumental in improving early diagnosis, personalized treatment strategies, and disease progression. By utilizing nationalized data, this study focuses on building and comparing high-performing analytical predictive models based on the relevant risk factors and identifying the most influential predictors.

Methods: We analyzed cross-sectional BRFSS Asthma Call-Back Survey data (2011-2020; N = 9,813) and randomly split participants into training and testing sets. An XGBoost model (hyperparameters tuned via grid …

Modified Atmospheric Packaging An Emerging Non-Invasive Packaging Technique For Strawberry Preservation- A Review, Mehraj Fatema Z. Mulla, Tigist Shonte, Lorraine Foley, Michael T. Gaffney, Jesus Maria Frias, Shivani Pathania

Research Outputs: 2025-Present

Strawberries are highly perishable due to their soft texture, high respiration rate, and susceptibility to microbial spoilage. Modified Atmosphere Packaging (MAP) has emerged as a non-invasive preservation strategy to address these limitations while retaining quality. This review aims to critically evaluate the principles, effectiveness, technological advancements, and limitations of MAP in strawberry preservation. It also explores emerging materials, active agents, and modelling tools used to optimize MAP systems. A comprehensive literature review was conducted, focusing on MAP applications in strawberries, including recent innovations such as active MAP, nanocomposite and bio-based films, and complementary treatments like coatings and essential oils. Recent …

Imperfections And Scars: The Aesthetics Of Curated Decay In Urban Conservation: The Aesthetics Of Curated Decay In Urban Conservation, Ioana Moldovan, Connell Vaughan, Michael O’Hara, Silivan Moldovan, Ioana Cecălășan

Research Outputs: 2025-Present

This paper explores the value of imperfections and curated decay in the conservation of architecture and public art as vehicles of cultural memory. While conventional heritage practice treats physical degradation as a threat, newer conservation ethics argue for embracing material impermanence within an aesthetics of care. We examine how acknowledging patina, weathering, and even structural decline can become an act of care, maintaining the “spirit” and authenticity of a place. The theoretical framework integrated the aesthetics of imperfection, including concepts like the Japanese wabi-sabi, which finds beauty in the incomplete and impermanent, critical heritage theory (which questions whose memories and …

Works Progress Administration (Wpa) Tombstone Inscriptions - Accession 488, Works Progress Administration, South Carolina Genealogical Society

Manuscript Collection

This collection consists of 67 microfiche containing an alphabetical index to tombstone inscriptions recorded during a partial survey of South Carolina cemeteries conducted by the Works Progress Administration (WPA) during the 1930s. The index was compiled by chapters of the South Carolina Genealogical Society from the original WPA cemetery survey records and provides access to inscriptions documented in approximately 350 cemeteries throughout the state.

Arranged alphabetically by surname, the index generally includes the full name of the deceased, birth and death dates (when available), and the location of the cemetery in which the inscription was recorded. The collection serves as …

Jubilee: Harvest Of The Arts Records - Accession 1463, Jubilee: Harvest Of The Arts Records

Manuscript Collection

The Jubilee: Harvest of the Arts Festival Records document the planning, promotion, and operation of the annual Jubilee: Harvest of the Arts festival held in Rock Hill, South Carolina. The festival celebrated visual and performing arts, crafts, and music and featured outdoor gallery exhibitions, theatrical performances at Winthrop University, arts and crafts vendors, and a quilt show. Over time, the event evolved into what later became the Rock Hill Blues & Jazz Festival, reflecting the city’s growing emphasis on musical heritage, particularly blues and jazz.

The collection includes planning and administrative records such as committee files, steering committee documentation, budgets, …

York County Democratic Party Records - Accession 1577, Democratic Party, York County

Manuscript Collection

The York County Democratic Party Records document the activities, organization, and electoral efforts of the York County Democratic Party. The party’s stated goal is “to elect Democratic candidates in York County, the State of South Carolina, and the United States.” Materials in the series date primarily from 1998 to 2012 and reflect both internal administration and public-facing political activity.

The collection includes meeting minutes of the Executive Board and general party meetings; agendas for county conventions; voter turnout reports by precinct; strategic planning reports; campaign mailers and promotional materials; and newspaper articles concerning elections, voting data, and election results. Together, …

Mary Elizabeth Frayser Papers - Accession 1739, Mary Elizabeth Frayser

Manuscript Collection

The Mary Elizabeth Frayser Papers document the professional career, civic engagement, and reform work of Mary E. Frayser, an educator, home economist, social worker, and prominent women’s club leader in South Carolina during the twentieth century. The collection reflects Frayser’s long-standing commitment to education, social welfare, women’s rights, and public policy, as well as her involvement in numerous state and regional organizations dedicated to social and economic reform.

Materials in the collection include newspaper clippings, correspondence, speeches, reports, articles, pamphlets, meeting-related documents, publications, and other printed materials. These records document Frayser’s work with the South Carolina Extension Service (1912–1940), Winthrop …

Martha Thomas Fitzgerald Papers - Accession 1742, Martha Thomas Fitzgerald

Manuscript Collection

The Martha Thomas Fitzgerald Papers document the personal, professional, and public life of Martha Thomas Fitzgerald (1894–1981), a Winthrop College graduate (Class of 1916), educator, civic leader, and politician. Notably, Mrs. Fitzgerald was the first woman elected to the South Carolina House of Representatives in a general election, marking a significant milestone in the state’s political history. The collection reflects her long career in education, public service, and civic engagement in South Carolina.

The collection consists primarily of correspondence related to Fitzgerald’s legislative service, her work with the South Carolina Department of Education, and her involvement in a wide range …

George White Family Papers - Accession 1900, White Family

Manuscript Collection

This collection consists of bound volumes, family Bibles, lecture and financial notebooks, diaries, scrapbooks, photographs, magazines, publications, and memorabilia collected or owned by members of the White family and related families. The White family, descendants of George Pendleton and Ann Hutchinson White, was among the founding families of Rock Hill, South Carolina, and played a significant role in the development and history of the community. The family’s historical presence in Rock Hill is also reflected in the White Home, one of the early homes constructed in the city and now a local historic attraction, and White Street in downtown Rock …

David Bancroft Johnson Personal Papers - Accession 2, David Bancroft Johnson

Manuscript Collection

This collection consists of the personal correspondence and papers of Dr. David Bancroft Johnson, founder and first president of Winthrop.  The letters address various subjects and people, both personal and professional, concerning issues from the original funding of Winthrop in 1886 to the minutiae of ordering flour and cotton seed, as well as personal letters to family, friends, and acquaintances. This collection also includes news clippings, brochures, programs, and various documents belonging to Dr. Johnson.  The letters and documents are by organized by each item chronologically.

Breaking The Resistance: A Narrative Review Of The Evolution From Traditional Drugs To Precision Therapies In Epilepsy, Tirath Patel, Fathimathul Henna, Ashfaq Ahmed, Ayesha Ahmad, Noor Ul Huda, Syed Aaraiz Ul Hassan, Aiman Muhammad, Amna Javed, Maryem Filal, Nikhilesh Anand

School of Medicine Publications

Background: Epilepsy is a chronic neurological disorder characterized by recurrent seizures, affecting approximately 50 million individuals globally. While conventional antiseizure medications (ASMs) control seizures in 70-80% of patients, about 30% experience drug resistance or intolerable side effects, necessitating alternative approaches.

Objective: To critically compare the efficacy, safety, and accessibility of conventional and emerging therapies for epilepsy, particularly in the context of treatment-resistant cases and global disparities in care.

Methods: This narrative review synthesized evidence from 120 peer-reviewed articles published between 2015 and 2025. Literature was retrieved from PubMed, Embase, Cochrane Library, and Scopus using predefined search terms related to epilepsy …

Staphylococcus Aureus Strain Heterogeneity Modulates Virulence Traits Associated To Dual-Species Biofilms With Candida Albicans, Laure Nicolas Annick Ries, Beata Adrienn Brezniczky, Binduja Srelatha Pradeep, Esther Olabamiji, Lee Hutt, Glenn M. Harper, Alexander Strachan, Gyorgy Fejer

School of Biomedical Sciences

Staphylococcus aureus is a commensal Gram-positive bacterium and opportunistic pathogen that exhibits substantial variation in antimicrobial resistance and virulence traits. S. aureus is frequently co-isolated with the fungus Candida albicans, and together they represent the most common microorganisms recovered from biofilm-associated infections originating from both biotic and abiotic surfaces. Despite this clinical relevance, the impact of bacterial intra-species variation on interkingdom interactions remains poorly understood. This study therefore investigated how S. aureus strain heterogeneity influences C. albicans within dual-species biofilms. The majority of the 60 S. aureus strains tested suppressed fungal growth in a contact-dependent manner across different nutrient conditions …

Streamlining Literacy Assessment, Sheila Mulder, Katie Anderson, Samuel W. Flint

Annual Research Symposium

Reading proficiency scores are low throughout the nation. Reading proficiency is a foundational skill that supports academic success across all content areas. Skilled reading involves multiple interrelated components. Assessment can support teachers to identify skill deficits and inform instruction; however, rural teachers lack the time, resources, and specialized support to translate the data into effective instruction and interventions. To better contextualize this need, we received 59 surveys from South Dakota teachers with 23 of the surveys being valid responses, finding that teachers feel prepared to teach reading and struggling readers. Teachers reported that they spend relatively little time in assessment, …

Secure-Home: Detect And Redact Pii, Hajar Niroomand, Omar F. El-Gayar

Annual Research Symposium

Personally Identifiable Information (PII) leakage from home environments poses significant identity theft risks. While enterprise networks employ robust security measures, firewalls, intrusion detection systems, and access controls, these protections rarely extend to home settings, creating a critical security gap. Current firewall technologies lack the capability to detect and scrub PII from outbound traffic, leaving vulnerable populations such as children, elderly users, and remote workers exposed. This design science research proposes Secure-Home, a prototype outbound inspection tool that detects and redacts clear-text PII before data leaves home networks. Using rule-based detection and selective redaction, Secure-Home provides a practical last line of …

Comparative Analysis Of Shipping Costs Across Multiple Routes Using Fedex Api Data, Valerija Curikova, Andrew Kramer

Annual Research Symposium

Shipping costs are an important factor for both individuals and companies, especially in industries like healthcare where medical material should be delivered quickly and reliably. While working as an intern at Avera Health in the Supply Chain logistics team, I was introduced to the challenge of the high cost of delivering medical supplies to different patient locations. Shipping prices vary depending on distance, route direction, and service type. Using real-time data from the FedEx API allows for more accurate analysis of shipping costs and helps identify opportunities to optimize delivery decisions and reduce logistics expenses.

Post-Quantum Cryptography Secure Communication, Iot, And Blockchain, Nidhish Bhanse, Mark Spanier

Annual Research Symposium

Modern public-key cryptography, such as RSA and Elliptic Curve Cryptography (ECC), plays a crucial role in securing data. However, the development of quantum computing threatens the security of data encrypted with these methods. Data encrypted today might be decrypted in the future due to the increased power of quantum computers. To combat this, the National Institute of Standards and Technology (NIST) has developed new standards for post-quantum cryptography. The following research aims to provide an analysis of these NIST post-quantum cryptographic algorithms and their potential for use in various secure communication protocols and platforms.

Evaluating The Reliability And Equity Implication Of Acute Hospital Readmission Metrics In New Zealand, Christopher D. Elce, Martinson Ofori, Andrew Behrens

Annual Research Symposium

Acute 28-day hospital readmission rates are widely used in New Zealand to monitor hospital quality and health system performance. However, the policy value of readmission metrics depends on whether observed variation reflects real clinical differences or is driven by data-quality artifacts and population structure. This study evaluates the reliability of published benchmarked readmission rates for all Districts of Service.

Postmortem Analysis Of Israel's 7 October 2023 Intelligence Failure, Emily Helgeson, William Bendix

Annual Research Symposium

On October 7, 2023, Hamas launched an attack from the Gaza Strip into Israel, resulting in the deaths of 1,200 people and triggering a larger conflict. Despite possessing impressive intelligence capabilities, Israel failed to anticipate the attack. This project provides one of the first postmortem analyses of the October 7 intelligence failure and demonstrates methods for assessing the role and significance of key contributing factors.

Interactions Of Bad Actors With Honeypots, Maryam Aliyeva, Andrew Kramer

Annual Research Symposium

Throughout daily life, computer users encounter different forms of malware, such as ransomware, adware, viruses, trojan horses, and spyware. To protect networks, individuals need to be able to comprehensively analyze a malicious actor’s behavior and tactics. These observations can be made through the usage of honeypots – a computer security mechanism set to track and deflect unauthorized activity. Honeypots frequently operate like decoys of legitimate websites that perfectly mimic an existing database, which makes them a valuable tool for researching cyber criminals’ behavior.

Pahina: Precision-Aware Hierarchical In-Network Aggregation For Edge Distributed Training, Yingpu Nian, Bo Yi, Qiang He, Xingwei Wang, Geyong Min, Keqin Li, Sajal K. Das

Computer Science Faculty Research & Creative Works

The rise of edge intelligence is driving distributed machine learning toward a new paradigm of edge-collaborative computing. To overcome the severe communication bottleneck in this paradigm, In-Network Aggregation is a critical enabling technology. However, its effectiveness is fundamentally undermined by the profound resource heterogeneity of edge networks. Specifically, edge devices, adapting to hardware constraints, operate at varying numerical precisions, leading to significant data inflation as gradients are aggregated. Compounding this, unevenly distributed network resources and traditional, precision-oblivious routing strategies often misallocate critical, high-precision gradients to low-quality paths. This mismatch creates severe network congestion, crippling the efficiency of distributed training. To …

Fairrfl: Fair And Robust Federated Learning In The Presence Of Selfish Clients, Andrea Augello, Ashish Gupta, Giuseppe Lo Re, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL) is a paradigm that enables collaborative machine learning without disclosing the local data of the participants. However, in real-world FL deployment scenarios, some unscrupolous clients may alter the training process to skew the global model towards their local optimum, unfairly prioritizing their data distribution. Their influence can degrade overall model performance for normal clients and reduce fairness in the system. We call this novel category of misbehaving clients 'selfish'. This work proposes a Fair and Robust strategy for aggregation in the Federated Learning (FL) server to mitigate the effect of Selfish clients (FairRFL). FairRFL incorporates a novel …

Feddot: Defending Federated Learning Against Overwhelming Targeted Attacks, Priyesh Ranjan, Ashish Gupta, Federico Coro, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL), which facilitates collaborative model training and protects users' privacy, has drawn great interest from the research community. With FL, participants train their models on local data and submit the corresponding updates for aggregation to a server. While concealing the identities of the participants, FL may attract adversaries in order to hamper the underlying model. In this paper, we propose an FL framework, FedDOT, to defend against adversaries performing targeted attacks. FedDOT incorporates two powerful defense algorithms, Maximum Spanning Tree based attacker detection (MSTAD) and Densest graph-based attacker detection (Density-AD), which leverage correlation between weight updates and graph …

Dynamic Hub-Aware Knowledge Distillation For Efficient Traffic Flow Forecasting, Xiangjie Kong, Can Shu, Wenchao Weng, Zhenzhen Zhao, Guojiang Shen, Lei Wang, Sajal K. Das

Computer Science Faculty Research & Creative Works

Real-time traffic forecasting acts as a critical enabling service for IoT-driven Intelligent Transportation Systems (ITS). While existing Spatiotemporal Graph Neural Networks (STGNNs) achieve superior forecasting accuracy, their intensive computational complexity and high latency create a deployment bottleneck for resource-constrained IoT edge devices. To address this resource-accuracy mismatch, we propose a novel framework termed Dynamic Hub-Aware Knowledge Distillation (DHKD). Unlike traditional uniform distillation paradigms, DHKD introduces a topology-aware strategy to transfer knowledge from a complex teacher to a lightweight Spatiotemporal Multi-Layer Perceptron (STMLP) student model. Specifically, we design a dynamic hub-aware gating (DHAG) mechanism that adaptively identifies time-varying pivotal sensing nodes …

Dcmm-Transformer: Degree-Corrected Mixed-Membership Attention For Medical Imaging, Huimin Cheng, Xiaowei Yu, Shushan Wu, Luyang Fang, Chao Cao, Jing Zhang, Tianming Liu, Dajiang Zhu, Wenxuan Zhong, Ping Ma

Computer Science Faculty Research & Creative Works

Medical images exhibit latent anatomical groupings, such as organs, tissues, and pathological regions, that standard Vision Transformers (ViTs) fail to exploit. While recent work like SBM-Transformer attempts to incorporate such structures through stochastic binary masking, they suffer from non-differentiability, training instability, and the inability to model complex community structure. We present DCMM-Transformer, a novel ViT architecture for medical image analysis that incorporates a Degree-Corrected Mixed-Membership (DCMM) model as an additive bias in self-attention. Unlike prior approaches that rely on multiplicative masking and binary sampling, our method introduces community structure and degree heterogeneity in a fully differentiable and interpretable manner. Comprehensive …

Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness, Renqiang Luo, Huafei Huang, Shuo Yu, Fengqi Yu, Feng Xia, Sajal K. Das, Chengqi Zhang

Computer Science Faculty Research & Creative Works

Fairness-aware federated graph neural networks (FedGNNs) necessitate consideration of both the server and the clients. However, fairness-aware methods struggle to enhance dual-perspective (i.e., server and clients) fairness without sacrificing utility due to the distributed learning framework. As a consequence, the utility sacrifices of fairness-aware graph learning methods are even exacerbated in federated frameworks. In this work we propose F3GL, a dual-perspective fairness federated graph learning method that enhances both global (for the server) and local fairness (for clients) while preserving utility. Through theoretical analysis, we delineate the similarity between original sensitive features and those after convolution under different spectra. Our …

Explaining The Unseen: Multimodal Vision-Language Reasoning For Situational Awareness In Underground Mining Disasters, Mizanur Rahman Jewel, Mohamed Elmahallawy, Sanjay Kumar Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Underground mining disasters produce pervasive darkness, dust, and collapses that obscure vision and make situational awareness difficult for humans and conventional systems. To address this, we propose MDSE, Multimodal Disaster Situation Explainer, a novel vision-language framework that automatically generates detailed textual explanations of post-disaster underground scenes. MDSE has three-fold innovations: (i) Context-Aware Cross-Attention for robust alignment of visual and textual features even under severe degradation; (ii) Segmentation-aware dual pathway visual encoding that fuses global and region-specific embeddings; and (iii) Resource-Efficient Transformer-Based Language Model for expressive caption generation with minimal compute cost. To support this task, we present the Underground Mine …

Escher: Efficient And Scalable Hypergraph Evolution Representation With Application To Triad Counting, S. M. Shovan, Arindam Khanda, Sanjukta Bhowmick, Sajal K. Das

Computer Science Faculty Research & Creative Works

Higher-order interactions beyond pairwise relationships in large complex networks are often modeled as hypergraphs. Analyzing hypergraph properties such as triad counts is essential, as hypergraphs can reveal intricate group interaction patterns that conventional graphs fail to capture. In realworld scenarios, these networks are often large and dynamic, introducing significant computational challenges. Due to the absence of specialized software packages and data structures, the analysis of large dynamic hypergraphs remains largely unexplored. Motivated by this gap, we propose ESCHER, a GPU-centric parallel data structure for Efficient and Scalable Hypergraph Evolution Representation, designed to manage largescale hypergraph dynamics efficiently. We also design …

Surgical Treatment Of Osteoradionecrosis Of The Jaw Following Radiotherapy For Oropharyngeal Cancer: A Retrospective Clinical Analysis In A Single-Center, Yu Nakai, Ken-Ichiro Sakata, Kazuhito Yoshikawa, Taku Maeda, Tougo Tanabe, Masayuki Shinohara, Kenji Imamachi, Hiroshi Hikasa, Jun Sato, Ikuya Miyamoto

Journal of Dental Sciences

Background/purpose: Osteoradionecrosis of the jaw (ORNJ) is an intractable disease that develops within the radiation field in patients with head and neck cancer. This study aimed to investigate differences in healing rates among surgical treatments for mandibular ORN that developed after radiotherapy for oropharyngeal cancer.

Materials and methods: We retrospectively evaluated 318 patients who underwent radiotherapy or chemoradiotherapy for oropharyngeal cancer at our institution to determine the incidence of ORNJ. Furthermore, 16 patients (15 males and 1 female) with a mean age of 63.3 years were included in the surgical analysis. Healing was defined as the absence of …

Effects Of 850-Nm Light-Emitting Diode Photobiomodulation On Pain Intensity And Dentin Sialoprotein Levels During Canine Distalization: A Randomized Controlled Trial., Thanh Thuy-Nhat Cao, Anh Ho-Quynh Nguyen, Hung Trong Hoang, Tham Dong Khac, Phuc Hoai Le, Tu Trinh Hk, Kieu-Minh Le, Diem Truong

Journal of Dental Sciences

Background/purpose

Light-emitting diode-based photobiomodulation (LED PBM) potentially reduces pain and root resorption risk in orthodontics. This study evaluated 850-nm LED PBM effects on pain and dentin sialoprotein (DSP) levels during canine distalization.

Materials and methods

This single-blind, parallel-group randomized controlled trial included 16 orthodontic patients (8 per group). Participants were randomly allocated in a 1:1 ratio to either an active LED group or a sham control group. Pain intensity was assessed using a visual analog scale (VAS) at 0, 24, and 48 hours following canine distalization at four consecutive monthly visits (T₁-T₄) and expressed as the …