Digital Commons Network^™

Evolving Solutions For Red Blood Cell Preservation, Ali Alkafaji, Charles A. Elder, Mohammad Zaidi, Kavin Parthiv, Michael A. Menze

The Cardinal Edge

In emergencies such as natural disasters, armed conflicts, or during outer space missions, the availability of transfusable blood can mean the difference between life and death. Red blood cells (RBCs) must be stored at +4 ± 2 °C and have a shelf life of just 42 days, which makes maintaining a stable blood supply during adverse conditions extraordinarily challenging. This challenge was especially apparent during the COVID-19 pandemic when hospitals faced severe blood shortages. Freeze-drying, or lyophilization, offers a promising avenue to extend the shelf life of RBCs for transfusion during crises. However, a significant hurdle in dry preservation is …

Determination Of Trace Amounts Of Pb2+ And Cu2+ Ions In The Ohio River With Anodic Stripping Voltammetry And Flame Atomic Absorption Spectroscopy To Test Water Contamination From Factories., Eliana Purcell

The Cardinal Edge

In this project, water near factories in Rubbertown, Louisville, KY were tested to see if a significant enough amount of waste is deposited in the Ohio River that the concentrations of Pb2+ and Cu2+ exceed the maximum contaminant levels the World Health Organization (WHO) and the United States Environmental Protection Agency (EPA) have set in place. Waste from industrial factories may contain contaminants that have negative effects on aquatic ecosystems and even human health, so two potentially harmful metal ions were tested. The concentration of Cu2+ in water samples was detected through flame atomic absorption spectroscopy (FAAS), and the concentration …

Ai Dependency Vs. Doctoral Identity: How Generative Ai Is Challenging The Development Of Independent Scholarly Thinking In Doctoral Students, Valerie A. Storey

All Faculty and Staff Scholarship

The rise of Generative Artificial Intelligence (GenAI) in higher education has altered the conditions under which doctoral students learn, research, and develop as scholars. Although doctoral student use of GenAI has accelerated rapidly, institutional frameworks for responsible and developmentally appropriate use have not kept pace. This paper examines a central paradox in doctoral education: the same tools that enhance research productivity may also weaken intellectual independence when used without guidance. Using a critical review methodology, the study synthesizes 47 sources on doctoral education, GenAI use, policy, and epistemic development. Three interconnected dimensions of risk emerged from the analysis: critical thinking …

Flexible Modeling Of Non-Gaussian Longitudinal Data: Some Approaches Using Copula, Subhajit Chattopadhyay

Doctoral Theses

Longitudinal data are common in medical and biological sciences, where measurements are gathered from subjects over time to explore relationships with explanatory variables (covariates) and to uncover the underlying mechanisms of dependence among these measurements. The responses observed at each instance can be either discrete or continuous. One of the primary challenges in longitudinal data analysis lies in the non-Gaussian nature of the response variables. As a result, there are relatively few multivariate models in the literature that effectively address the specific characteristics observed in such datasets. In this dissertation, we address four problems concerning longitudinal data analysis by developing …

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) 2022 Draft Final Insufficiently Reclaimed Sites Sampling: Bres No. 16 Site Evaluation Summary Report, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Speleoco: An Open, Low-Cost Arduino Co₂ Datalogger For Cave Microclimate Monitoring, Christos Pennos, Dimitrios Christaras

International Journal of Speleology

Carbon dioxide (CO₂) dynamics in caves are critical for karst processes, speleothem growth and dissolution, microclimate regulation, and caver safety. In cave atmospheres, CO₂ commonly derives from soil respiration, epikarst degassing, microbial activity, and, in tectonically active regions, deep-seated fault-related emissions. Fault-related CO₂ degassing may also track tectonic activity. However, continuous monitoring remains limited due to the cost and inflexibility of commercial instruments. Here we present an open-source, low-cost Arduino-based CO₂ datalogger designed for cave applications. The logger integrates a COZIR NDIR CO₂ sensor, a DS1337 real-time clock, microSD storage, and power-gating for extended deployment in humid environments. Firmware and …

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 50 – Zelia Site Evaluation Summary Report, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Water Sources And Livelihood Choices Among Pastoralist Households In Monduli District, Tanzania, Fredrick Alleni Mfinanga, Jacqueline Temba, Monica F. Timbuka

Journal of Humanities and Social Sciences

This paper investigates the association between types of water sources for livestock and livelihood choices of pastoralist households in semi-arid areas of Monduli District, Tanzania. Specifically, it aims to examine the influence of the types of water sources for livestock on livelihood diversification of pastoralist households. Using a mixed research methods approach, the data were collected from 367 households through three methods: surveys, interviews, and focus group discussions. The quantitative data were analysed using descriptive statistics such as frequencies and counts, and inferential statistics, Chi-square tests and correlation, while the qualitative data were analysed using content analysis. The findings revealed …

Constraints To Adopting Locally Based Innovation Systems In Adapting To Climate Change Impacts In Serengeti District, Tanzania, Donald Mwiturubani

Journal of Humanities and Social Sciences

Smallholder farmers in rural Tanzania depend mainly on rain-fed agriculture, which makes them vulnerable to the impacts of climate change. This paper is based on a study conducted in Burunga and Musati villages in Serengeti District, Tanzania. The study employed a mixed methods approach; combining qualitative and quantitative methods. It involved 154 participants and employed household surveys, key informant interviews, and focus group discussions as data collection methods. The findings suggest that smallholder farmers in the study area are aware of climate change and do, indeed, develop, adopt, and use locally-based innovation systems that avert or minimise its impacts. Smallholder …

Ecomusicological Representation Of Climate Change And Environmental Sustainability In Selected Bongo Fleva Lyrics In Tanzania, Auson N. Wincheslaus

Journal of Humanities and Social Sciences

This article critically explores how Bongo Fleva’s lyrics engage with environmental themes; and the interrelationship between nature and culture in the context of the Anthropocene. The data were purposively sampled from YouTube via content analysis, from which 50 Bongo Fleva songs were listened to, and only 10 environmentally-themed songs were analysed. Then, the selected songs were subjected to transcription (from oral to written form), translation (from Kiswahili into English), and close reading and textual analysis. The close reading of the selected songs focused on the employed aesthetic and rhetorical strategies, such as anthropomorphism, symbolism, antithesis, apocalyptic tones, solastalgia, rhetorical questions, …

Resilience Among Smallholder Irish Potato Farmers To The Impacts Of Climate Variability In Wanging’Ombe District, Tanzania, Timotheo Bilary Ngalaga, Digna Wolfram Mlengule, Jackson Raymond Sawe

Journal of Humanities and Social Sciences

This paper examines smallholder farmers’ adaptation strategies to climate variability, and their resilience in enhancing their capacity to adopt. The data was collected from 98 heads of households using both quantitative and qualitative approaches. The methods of data collection included household surveys, focus group discussions (FGDs), in-depth interviews, and document review. The quantitative data were analysed using the IBM SPSS (Version 23), while the qualitative data were analysed using thematic analysis. The findings indicate that 69.4% of respondents reported a decrease in rainfall, while 89.8% reported an increase and fluctuations in temperature over the past 29 years. Moreover, the findings …

Climate Change Vulnerability And Adaptation Pathways: Stakeholders’ Synergies In Building Climate Resilience In The Semi-Arid Area Of Central Tanzania, Helena Elias Myeya

Journal of Humanities and Social Sciences

This article examines the perceived effect of climate change on cereal crop production and the responses of various stakeholders aimed at enhancing the resilience of smallholder farmers in semi-arid areas of central Tanzania. A total of 366 household heads, 28 participants in focus group discussions (FGDs), and 8 key informants from Bahi and Kongwa districts in Dodoma, Tanzania, were involved in this study. Both quantitative and qualitative data were gathered through a structured interview schedule, FGDs, in-depth interviews, and documentary reviews. Descriptive statistics and content analysis were used to analyse quantitative and qualitative data, respectively. The findings indicate that smallholder …

An Ensembled Two-Phase Deep Learning Approach For A Psychiatric Disorder Detection, Prajna Paramita Debata, Midhun Chakkaravarthy, Brojo Kishore Mishra

Turkish Journal of Electrical Engineering and Computer Sciences

Computational Psychiatry represents a burgeoning realm within scientific inquiry, delving into the intricate interplay of neurobiology within the brain. The escalating prevalence of mental illness underscores the urgency to confront this challenge. Among the prevalent disorders, Schizophrenia and Bipolar Disorder loom large, affecting a significant portion of the population at some point in their lives. However, pinpointing psychiatric disorders poses a formidable challenge. Genetic predispositions significantly influence the development of mental illnesses, with intriguing overlaps observed among certain disorders. This convergence complicates accurate diagnosis. Here, a deep learning approach is considered for significant gene biomarker identification and classification of Schizophrenia …

A Joint Optimization-Based Novel Attack For Genomic Beacon Reconstruction, Kousar Saleem, Si̇nem Sav

Turkish Journal of Electrical Engineering and Computer Sciences

Genomic data sharing has become an essential component of biomedical research, enabling large-scale collaborations and accelerating discoveries in human genetics. To balance the need for accessibility with privacy concerns, several controlled-access mechanisms have been proposed, including genomic beacons. Genomic beacons answer simple presence/absence queries about specific genetic variants. However, prior work has demonstrated that beacons remain vulnerable to genome reconstruction attacks, where an adversary can recover large portions of participants’ genomes using summary statistics. Building on insights from prior reconstruction attacks, we introduce an approach that unifies SNP correlation and allele frequency alignment objectives within a single-stage joint optimization framework. …

Re: Approval Letter For The Butte Priority Soils Operable Unit - Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 96 – Washoe Dump Site Evaluation Summary Report, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Phase I Pre-Design Investigation Evaluation Report Blacktail Creek Riparian Actions Butte Priority Soils Operable Unit Of The Silver Bow Creek/Butte Area Superfund Site Silver Bow County, Montana, Hydrogeologic, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Intermediate (60%) Remedial Design Report Blacktail Creek Riparian Actions Butte Priority Soils Operable Unit Of The Silver Bow Creek/Butte Area Superfund Site Silver Bow County, Montana, Hydrogeologic, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Remedial Design Work Plan Blacktail Creek Riparian Actions Butte Priority Soils Operable Unit Of The Silver Bow Creek/Butte Area Superfund Site Silver Bow County, Montana, Hydrogeologic, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Polyherbal Phytochemicals As Multi-Target Inhibitors Of Key Breast Cancer Proteins: A Computational Approach, Nadia Wahyuningsih, Nashi Widodo, Sri Rahayu, Muhaimin Rifa’I

Karbala International Journal of Modern Science

Breast cancer is a primary worldwide health concern, and conventional therapies often cause side effects. This study was performed to investigate the therapeutic potential of a polyherbal formulation containing Curcuma longa, Phyllanthus niruri, Ziziphus mauritiana, Nigella sativa, and Annona muricata as multi-target inhibitors against breast cancer protein targets using molecular docking and molecular dynamics in silico approach. Bioactive compounds were analyzed using Liquid Chromatography High-Resolution Mass Spectrometry (LC-HRMS) to identify the extract's phytochemicals. The compounds were examined for drug-likeness, membrane permeability, bioactivity, and toxicity. The inhibitory ability against the proto-oncogene pathway, which is commonly dysregulated and mutated in breast cancer, …

Associational Inference With Many Potential Covariates: Bayesian Information Criterion Elastic Net, Farideh Bagherzadeh Khiabani, I-Chan Huang, Jose Miguel Martinez Martinez, Shizue Izumi, Sedigheh Mirzaei, Tiange Zheng, Irina Dinu, Yutaka Yasui

COBRA Preprint Series

Background: An emerging feature in modern biomedical research is collecting and analyzing numerous variables. In the presence of many potential covariates, inference becomes challenging requiring both distinguishing a set of covariates truly associated with an outcome and estimating their corresponding regression coefficients consistently. Traditional statistical inference typically focuses on estimating coefficients assuming a pre-specified set of covariates. Further, advanced machine/statistical learning methods performing both selection and estimation predominantly focus on outcome prediction rather than association inference.

Methods: Motivated by our epidemiological research on long-term childhood cancer survivors, where we aimed to investigate associations between a large pool of longitudinal symptom …

Geo 170 - Earth Science And Society, Yuri Gorohkovich

Open Educational Resources

Syllabus for our new OER course

Database-Driven Revelations In Epilepsy: Patient Reporting Accuracy And The Circadian Timing Of Seizures, Ithay Biton

Theses and Dissertations

For over thirty years, patients have been visiting the Arkansas Epilepsy Program for diagnosis and treatment for seizures and seizure-like episodes. As part of their clinical evaluation, patients often undergo ambulatory EEG (electroencephalogram) monitoring. This routine process produces valuable data for treating the patient. In this study, over 2000 ambulatory EEG reports from 1998 to 2016 were reviewed. A large database of seizures was created from the reports, with information on 407 patients, 1611 EEG-confirmed seizures, and 1726 patient-reported seizures (IRB Protocol #17-093). The database was used to address two important issues in epilepsy. The first topic of the study …

Peruvian Pinniped Teeth Trace Element Data-Tracking Ecosystem Variabilites Through Trace Element Record Found In Peruvian Pinniped Dentin, Dimitrios Giarikos, Amy Hirons, Ally E. Sheehan, Radleigh Santos

SECLER Data

The South American sea lion (Otaria byronia; SASL) and the Peruvian fur seal (Arctocephalus australis; PFS) are apex predators within the Humboldt Current ecosystem, where population dynamics respond to both natural variability and anthropogenic pressures, including El Niño–Southern Oscillation (ENSO) events and coastal mining. This study quantified 18 trace elements (TEs) in canine dentin from both species collected at Punta San Juan, Peru using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to evaluate long-term environmental exposure. Because dentin is deposited incrementally, it preserves a chronological chemical archive reflecting ontogenetic shifts in diet and habitat use. Overall, TE concentrations were broadly similar …

Ulk4 And Cdkn2a Polymorphisms Influence The Risk Of Developing Monoclonal Gammopathy Of Undetermined Significance, José Manuuel Sánchez-Maldonado, Angelica Macauda, Antonio José Cabrera-Serrano, Hauke Thomsen, Murat Güler, Rob Ter Horst, Bethany Van Guelpen, Pavel Vodicka, Stefano Landi, Subhayan Chattopadhyay, Pelin Ünal, Lucía Ruiz-Durán, Delphine Casabonne, Hartmut Goldschmidt, Istemi Serin, María Carretero-Fernández, Elena Cabezudo, Fernando Reyes-Zurita, Alyssa I. Clay-Gilmour, Et. Al.

Faculty Publications

Monoclonal gammopathy of undetermined significance (MGUS) is a necessary precursor condition to multiple myeloma (MM). Given the role of autophagy in modulating MM risk, we investigated whether genetic variation in autophagy-related genes influences susceptibility to MGUS. We analyzed the association of 34,042 common autophagy-related single nucleotide polymorphisms (SNPs) with MGUS across six independent cohorts, five from Europe and one from North America, comprising 2317 MGUS cases and 282,358 controls. We also assessed their impact on immune parameters, including absolute counts of 91 blood-derived immune cell subsets and 103 circulating immunological proteins. Meta-analysis revealed a genome-wide significant association between the ULK4 …

Impact Of Medicaid Enrollment Timing On Tumor Stage At Diagnosis And Survival In Breast, Colorectal, And Lung Cancer, Gabriel A. Benavidez, Stella Coker Watson Self Ph.D., Ms, Anthony Alberg Ph.D., M.P.H., Janice Probst, Jan Marie Eberth

Faculty Publications

Background: Medicaid-insured patients experience higher rates of late-stage cancer diagnosis and worse survival than non-Medicaid patients. The impact of Medicaid enrollment timing on cancer outcomes is less clear. This study examines the association between Medicaid enrollment and timing with tumor stage and cancer-specific survival for breast, colorectal, and lung cancers. Methods: We analyzed SEER-Medicaid linked data for 276,755 breast, 104,784 colorectal, and 101,058 lung cancer patients < 65 years of age. Patients were categorized as non-Medicaid enrollees, pre-diagnosis enrollees (≥12 months before), or post-diagnosis enrollees (≤12 months after). Multivariable logistic regression estimated odds ratios of late-stage diagnosis, and cause-specific Cox proportional hazards models were used to assess cancer-specific survival, adjusting for demographic and socioeconomic factors. Results: Compared to non-Medicaid enrollees, post-diagnosis enrollees had the highest odds of late-stage diagnosis (breast cancer: OR: 3.41; colorectal cancer: OR: 3.78; lung cancer: OR: 1.87). Pre-diagnosis enrollees also had increased odds, but the …

Ai-Powered Reporting For Improved Hospital Efficiency, Joel C. Laskow, Chris Papesh, Srishti Awasthi, Jacquelyn Cheun

SMU Data Science Review

This study explores the feasibility of an AI-powered chatbot for HIPAA-aligned intake of emergency room patients seeking treatment for overdose and violence. The system utilizes AWS Amplify, an encrypted EC2 instance, and a secure S3 Bucket house on Amazon Web Services. Chat functionality is powered by a multi-agentic framework operating on Anthropic’s Claude Sonnet 4. Manual evaluation and exact match testing reveal the system reliably obtains and records relevant information during intake. Future work will focus on expanding accessibility by integrating voice functionality, obtaining HIPAA compliance certifications, and incorporating the chat system into existing healthcare networks.

Bias Evaluation Of Healthcare Data With The Use Of Vbqa - A Vaers Inspired Bias Question Answer Dataset, Nolan Dulude, Renu Karthikeyan, Bivin Sadler, Faizan Javed

SMU Data Science Review

Abstract. Large Language Models (LLMs) are being used increasingly within the healthcare industry to summarize complex clinical information, but their outputs can often reflect biases inherited from their training data. In healthcare, these biases are not just technical flaws, but they can lead to distorted and false information about vaccine safety, compromise patient trust, and lead to potential harmful outcomes. This study investigates bias found in LLM-generated outputs to question-answer pairs inspired by adverse vaccine reactions using COVID-19 data from the Vaccine Adverse Event Reporting System (VAERS) from 2020–2024. We examined whether training the LLMs on a known Bias Benchmark …

Automating Cardiff Model Data Capture In Emergency Departments: Ambient Nlp Integration With Oracle-Cerner Fhir Systems, Simi Augustine, Marco A. Lopez, Jacquelyn Cheun, Chris Papesh

SMU Data Science Review

Violence and overdose events in Las Vegas occur at rates above the national average, with fewer than half of violent injuries reported to law enforcement [2,7]. The Cardiff Model offers a proven framework for standardized data collection and sharing between hospitals and public safety partners, yet many implementations still rely on manual entry. We propose an ambient triage pipeline integrated with Oracle-Cerner electronic health record systems to listen to nurse–patient dialogue, convert speech to text, extract Cardiff fields, and write standards-based FHIR Bundles for analytics. Using SMART on FHIR standards and Cerner Millennium APIs, the study evaluates whether ambient capture …

Anomaly Detection For Multi-System Bug Triage, Gibran Miguel Zavala Gamero, Hayoung Cheon, Mustafa Iqbal

SMU Data Science Review

Large-scale software systems produce vast volumes of logs and telemetry, making manual incident triage slow and error prone. This study presents an unsupervised anomaly detection pipeline that fuses logs, metrics, and traces through late fusion. Using Hybrid Ensemble modeling with Isolation Forest, and Long Short-Term Memory (LSTM) Deep Learning model, the system detects cross-service anomalies producing and assigning a composite triage score reflecting severity and impact. Ranked alerts are categorized into Critical, High, or Medium priorities for review. A retrieval-augmented generation (RAG) layer enriches results with contextual summaries for explainable triage. Evaluated on synthetic multi-service datasets, the pipeline …

Reducing Range Anxiety Through Predictive Modeling Of Ev Battery Degradation, Caleb Thornsbury, Christian Castro, Bivin Sadler

SMU Data Science Review

Electric Vehicles (EV) range anxiety remains one of the top barriers for broader adoption. Range anxiety can be attributed to battery pack age and degradation over time. This paper plans to explore how to address this issue by creating a machine learning model that can predict degradation based on usage, temperature, battery chemistry, charging habits and exploring whether other factors tie into range degradation. This research will be using real world charging data along with lab tested chemistry data to build a model that can be chemistry specific for degradation. This paper will help perspective used-EV buyers learn about battery …