Digital Commons Network^™

A Modern Analytical Method To Forecast Cerebrovascular Diseases (Cd), And Heart Diseases (Hd) Using Multivariate Time Series Model Utilizing The Cdc Provisional Mortality Data, Aditya Chakraborty, Mohan Pant

Cardiovascular Research Symposium

Background: In this study, a new analytical approach was introduced to answer specific questions related to mortalities due to cerebrovascular diseases, heart diseases, and the association of these mortalities with twelve other causes of death (COD).

Methods: A multivariate time series forecasting model was developed utilizing each of the CODs by taking the weekly and yearly seasonality into account, and the mortality counts were forecasted using the most recent CDC weekly mortality count data. A new COD data matrix was structured for all CODs as a function of weeks by combining the observed and predicted values of the mortality counts. …

Cybersecurity And Intention To Use Mobile Banking Applications, Ishmael Chikoo, Salah Kabanda

African Conference on Information Systems and Technology

The adoption rate of mobile banking amongst consumers remains low, especially in developing countries where there is a knowledge gap in understanding why consumers do not engage in the frequent use of mobile banking applications. Given that most financial institutions see mobile banking as a strategy for their competitive advantage; it is important that they understand how best to address consumer’s fears brought about by cybersecurity threats. The purpose of this study is to investigate the perceived influence of cybersecurity on the user’s intentions to use mobile banking applications. Data collected from 90 participants was statistically analysed in Smart PLS …

Feasibility Evaluation Of Secure Offline Large Language Models With Retrieval-Augmented Generation For Cpu-Only Inference, Erick Tyndall, Torrey J. Wagner, Colleen Gayheart, Alexandre Some, Brent T. Langhals

Faculty Publications

Recent advances in large language models and retrieval-augmented generation, a method that enhances language models by integrating retrieved external documents, have created opportunities to deploy AI in secure, offline environments. This study explores the feasibility of using locally hosted, open-weight large language models with integrated retrieval-augmented generation capabilities on CPU-only hardware for tasks such as question answering and summarization. The evaluation reflects typical constraints in environments like government offices, where internet access and GPU acceleration may be restricted. Four models were tested using LocalGPT, a privacy-focused retrieval-augmented generation framework, on two consumer-grade systems: a laptop and a workstation. A technical …

The Effect Of Group Counseling On Hope With Diverse Undergraduates During Sustainability-Focused Internship, Hailey Spinks, Michael D. Hannon, Matthew Murray, Nina M. Goodey, Lora Billings, Amy Tuininga

PSEG Institute for Sustainability Studies Publications

Many adolescents report feeling overwhelmed, depressed, anxious, and hopeless in the face of global climate change. These feelings are both valid and antithetical to the necessary hope and courage it takes to address real-world environmental crises and contribute to meaningful societal impact. The Green Teams Program, an internship-based experiential learning initiative, prepares young professionals with skills and knowledge needed to address these challenges and provides an intentionally inclusive and safe environment for students from all backgrounds to do so. This structured environment includes psychoeducational group counseling among other supports. Intern self-assessments revealed significant gains in measures of Hope, Agency, …

Geol 64: Planetary Geology - Syllabus, Dara Laczniak

Open Educational Resources

This Open Educational Resources (OER) syllabus is for an introductory planetary geology course that utilizes results from space missions to expose students to the surface features, composition, geological activity, and probable history of the planets, moons, asteroids, and comets of the solar system. It also places space exploration into the context of larger societal issues such as global warming and natural resource availability and addresses topics such as the ethics of space exploration and hazards of space travel. This OER syllabus aims to foster student-centered learning, critical thinking, data analysis and communication skills, and creativity. Assigned readings are compiled into …

Re: Butte Mine Flooding Operable Unit Berkeley Pit And Discharge Pilot Project – July 2025 Monthly Discharge Monitoring Report, Mark Thompson, Dave Griffis

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Are Estimands Being Correctly Used? A Review Of Uk Research Protocols, T. P. Clark, Richard H. Wicentowski, S. Cro, M. R. Sydes, B. C. Kahan

Computer Science Faculty Works

Background: The use of estimands in clinical trials was formalised with the adoption of the final International Conference on Harmonisation E9 Addendum on Estimands and Sensitivity Analysis in Clinical Trials (ICH E9(R1) Addendum) in November 2019. The declared objective of the ICH E9(R1) Addendum is to bring clarity and transparency to the research question of interest. For this to be achieved, the estimand must be described in accordance with the requirements of the ICH E9(R1) Addendum so that the target treatment effect is clear to all stakeholders. Previous reviews of publications and published protocols have found that few trials explicitly …

Impact Of Mining Activities On Land Use Land Cover (Lulc) Using Geospatial Techniques In The Obuasi Municipality, Jonathan Arthur Quaye-Ballard, Samira Naa Yemoley Nsiah, Jephthah Marfo Nimoh, Titus Tienaah, Tina Dzigbordi Wemegah, Precious Adwoa Okyere

Publications

Introduction: Sustainable development, which balances economic, social, and environmental factors to meet the needs of the present and future generations, is a collective responsibility. Rapid population growth and intensification of socio-economic activities are causing significant changes in Land Use Land Cover (LULC), directly impacting ecosystem services, biodiversity, and climate. The Obuasi community is already facing environmental degradation and health problems due to gold mining.

Methodology: The study assessed the spatial extent and intensity of mining activities in the Obuasi Municipality on the LULC and predicted future LULC changes due to mining activities using geospatial techniques. The LULC changes were analysed …

Anionic Azo Dyes: Wastewater Pollutants As Functionalizing Agents For Porous Polycarbonate Membranes Aiding In Water Decolorization, Alan Jarrett Messinger, Isabella S. Mays, Brennon Craigo, Jeffrey Joering, Sean P. Mcbride

Physics Faculty Research

Efficient water decolorization techniques are vital for ensuring fresh water for future generations. Azo dyes are used heavily in the textile industry and are a challenge to remove from industrial wastewater. This research expands on recent innovative work where anionic azo dyes themselves were used to functionalize track-etched porous polycarbonate filtration membranes with decolorized water obtained as a byproduct. The objective of this research is to determine whether the observed dye rejection is dependent on the magnitude of the intrinsic charge of the dye molecule or on its structure, using two selectively chosen anionic azo dye series during functionalization. The …

Re: 2025 Spring Migration Seasonal Report For Berkeley Pit Waterfowl Protection Plan, Mark Thompson, Loren Burmeister

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For Bpsou Blacktail Creek Riparian Actions Draft Field Work Plan: Wetlands Delineation And Functional Assessment (Received August 8, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Effects Of Ambient Temperature On Nox Emissions From Heavy-Duty Diesel Vehicles Measured In Utah, Amber L. Gurecki Allen, Darrell B. Sonntag, Gary A. Bishop

Fuel Efficiency Automobile Test Publications

This study investigates the effects of ambient temperature on NOx (NO + NO2) emissions from model year 2011 and later heavy-duty (HD) diesel vehicles. Emission measurements were collected in Perry, Utah, using the Fuel Efficiency Automobile Test (FEAT) remote sensing device. Data were limited to model year 2011 and later to focus on vehicles likely equipped with selective catalytic reduction (SCR) systems, which control tailpipe NOx emissions and are shown to be temperature sensitive. HD diesel vehicles measured in the winter of 2020 had consistently higher NOx emissions than those measured in the summer of 2023, most significantly for vehicles …

Montserrat Developments Impacting Local Coral Reefs, Emma I. Bartholomew

2025 Symposium

Montserrat is a small island in the Caribbean, and over half of the island is in the exclusion zone because of the active volcano, Soufrière Hills. In that half was the old capital, Plymouth, which has since been abandoned, and its old port. The old port was getting less reliable and accessible, so they decided to build a new port in Little Bay, closer to the seat of government in Brades. This study explored how the addition of the new port impacted the corals in that area. We explored several different bays and recorded the diversity and health of the …

Domain Obedient Deep Learning, Soumadeep Saha

Doctoral Theses

Deep learning, a family of data-driven artificial intelligence techniques, has shown immense promise in a plethora of applications, and it has even outpaced experts in several domains. However, unlike symbolic approaches to learning, these methods fall short when it comes to abiding by and learning from pre-existing established principles. This is a significant deficit for deployment in critical applications such as robotics, medicine, industrial automation, etc. For a decision system to be considered for adoption in such fields, it must demonstrate the ability to adhere to specified constraints, an ability missing in deep learning-based approaches. Exploring this problem serves as …

A Comprehensive Review On Gamification In Neurocybersecurity, Ms. Kritika

Journal of Cybersecurity Education, Research and Practice

The research investigates gamification methods as it applies to the emerging interdisciplinary domain that brings together cybersecurity with neuroscience and psychology. Neurocybersecurity implements neural concepts to protect digital systems from security threats while targeting the human vulnerabilities that present as the strongest points of attack. Several researchers have examined gamification techniques which incorporate game design elements to enhance cybersecurity training outcomes by improving user participation and knowledge retention and user conduct compliance. The research incorporates Self-Determination Theory along with Cognitive Load Theory to explain the design principles for efficient gamified interventions. The implementation of both cognitive performance improvement and neuroplasticity …

Geochemical Characteristics And Genesis Of Element Enrichment Of Niobium-Rich-Rare Earth Metal Layer In Longtan Formation Of Zhina Coalfield, Ding Yunlong, Wang Fangfa, Li Bi, Tang Lifang, Yang Yi, Li Shangyuan, Wang Xiaofang, Zou Yinhong, Wang Yang

Coal Geology & Exploration

Background With the increasing demand for strategic metals and the gradual depletion of traditional metal deposit resources, coal and coal-bearing rock series are considered to be potential sources of rare metals, and coal series associated has become one of the main directions of current mineral exploration. A set of coal measure strata rich in niobium (Nb) and rare earth elements (REE) has been found in Zhina coalfield, western Guizhou and the contents of Nb and REE are as high as 334.89 μg/g and 1014.51 μg/g, respectively. This discovery is of great significance to the theoretical study of coal measure metal …

Methodology And Integration For Dynamic Safety Assessment And Early Warning Of Drilling Sites For Emergency Rescue After Underground Space Collapse, Xie Zhongzhi, Zhang Guohua, Wei Xingtong, Zhang Ning, Wang Xiaotian, Ni Xiaoyang, Zhou Zhengwen, Wang Xianze

Coal Geology & Exploration

Objective IGiven the lack of methods for dynamic safety assessment related to disasters in drilling site environments for emergency rescue after underground space collapse, this study proposed a multisource data-driven methodology for dynamic safety assessment and real-time early warning. Methods By comprehensively considering the disaster-inducing environment and disaster-causing factors at drilling sites for emergency rescue, this study established the safety assessment indices of the environment and their grading system. By integrating multi-source data on surrounding rock deformation, gas concentration, and drilling rig vibration, this study developed a safety assessment method through combination weighting achieved using the analytic hierarchy process (AHP) …

08.25.2025 Ored Connect, Liz Williamson

ORED Newsletter

• Research Security Required Training
• ORED Research Reception

Ai Is Not The New Dei: Academia’S Addiction To The Next Big Thing, Essraa Nawar

Library Articles and Research

"Every August, as campuses come back to life across the country and the world, I notice the same rhythm: new policies announced, committees formed, webinars scheduled, and fall conferences themed around the latest 'big thing.'

This fall? No surprise. The wave is artificial intelligence.

AI task forces are meeting weekly. Universities are drafting 'responsible AI' policies. New centers and certificates are being launched. Syllabi are being rewritten. Symposia and faculty retreats promise that AI will 'redefine the future of education.'

It is bold. It is ambitious. But it is also deeply familiar."

Rising Costs Of Higher Education In United States And Student Debt, Mona Muzammil, Muzammil Arshad, Washain Muzammil

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

100 years ago, college tuition at prestigious Ivy League colleges such as Harvard and Brown was about $130 per year. Even when adjusted for inflation, today's cost of higher education has increased dramatically to the point where a college education is shifting further out of reach for many Americans. This book explains the essential concepts in the debate regarding the staggering costs of higher education, supplying ten original essays by higher education policy experts, a lively historical narrative that provides context to current issues, and systematic guides to find additional sources of information on the subject.

Written from a historian's …

Probing The Effect Of Peg-Dna Interactions And Buffer Viscosity On Tethered Dna In Shear Flow, Fatema Tuz Zohra, Huda Al-Zuhairi, Jefferson Reinoza, Hyeongjun Kim, Andreas Hanke

Mechanical Engineering Faculty Publications

DNA flow-stretching is a widely employed, powerful technique for investigating the mechanisms of DNA-binding proteins involved in compacting and organizing chromosomal DNA. We combine single-molecule DNA flow-stretching experiments with Brownian dynamics simulations to study the effect of the crowding agent polyethylene glycol (PEG) in these experiments. PEG interacts with DNA by an excluded volume effect, resulting in compaction of single, free DNA molecules in PEG solutions. In addition, PEG increases the viscosity of the buffer solution. By stretching surface-tethered bacteriophage lambda DNA in a flow cell and tracking the positions of a quantum dot labeled at the free DNA end …

Performance Analysis Of Computational Methods For Predicting Protein Function In Rare Diseases, Aichetou Mohamed Sidiya, Hanin Alzaher, Razan Almahdi, Tayeb Brahimi

Effat Undergraduate Research Journal

Protein function prediction is crucial for understanding the underlying mechanisms of rare diseases. With the increasing availability of computational methods including machine learning-based approaches, network-based methods, and sequence-based methods, predicting protein functions has become more accessible. However, it is not clear which of these methods performs better or how they compare to each other in terms of accuracy, efficiency, and scalability. In this study, we evaluate several computational methods for predicting protein functions in rare diseases using key performance indicators (KPIs). We analyze the strengths and weaknesses of each method and provide recommendations for researchers and clinicians interested in using …

Mapping The Research Landscape Of Covid-19 And Artificial Intelligence Using The Lens Database, Aichetou Mohamed Sidiya, Jailan Fouad Aljizawi

Effat Undergraduate Research Journal

Due to the rapid spread of the COVID-19 pandemic, all countries faced a significant challenge in their efforts to monitor and halt the spread of the virus. Moreover, researchers around the world raced into publishing to get to understand the effects of this pandemic on every aspect of our life whether that was economic, medical, or social. Thus, this research seeks to assess the quality of research on the application of Artificial Intelligence in the Covid-19 pandemic with an emphasis on Saudi Arabia. The research methodology is based on Bibliometric Analysis techniques and VosViewer for various bibliometric visualizations based on …

A Study Of Rural Health Care For Chronic Care Management Using Machine Learning To Determine Costs, Joanna Maria Keeling

Doctoral Dissertations

Management of diabetes or heart disease may be uniquely challenging for older individuals with multiple chronic conditions[1]. Chronic Care Management would target patients living with comorbidities in Louisiana, who are not receiving sufficient healthcare services and help them receive the care they deserve[2]. This study is aimed at comparing the results of rural Louisiana Medicaid recipients with comorbidities to the National Averages. We will also use Machine Learning to predict Churn and Medical Costs. To help us identify these patients with comorbidities, we decided to use NCQA Quality Measures. We identified several measures from NCQA that we wanted to use, …

Privacy-Preserving Structure Learning For Geospatial Data Using Information-Theoretic Dependency Measures, Ahmed Mudhish

Doctoral Dissertations

This dissertation proposes a privacy-preserving framework for structure learning in Bayesian networks (BNs) that addresses the challenges of distributed geospatial data face. Geospatial datasets often exhibit region-specific patterns such as sparsity and nonlinear dependencies. These patterns undermine the effectiveness of traditional machine learning models. Additionally, learned BN structures may reveal sensitive relationships in the generated graph by BNs. These relationships pose a significant privacy risk if reverse-engineered. To address these issues, three novel algorithms are introduced. First, the Selective Naïve Bayes with HSIC (SNB-HSIC) algorithm applies a kernel-based dependency measure to filter redundant and irrelevant features in sparse datasets, improving …

Comparing Ordinary Least Squares And Quantile Regression: A Causal-Comparative Approach To Modeling Conditional Relationships, Samuel Nnorom

Electronic Theses and Dissertations

Ordinary Least Squares (OLS) regression has traditionally been the preferred quantitative method for estimating linear relationships. However, it assumes that the effect of a predictor variable remains constant across the entire outcome distribution, which can miss important insights when data are heterogeneous. Quantile Regression (QR), on the other hand, offers a more detailed analysis by focusing on the full response variable distribution, thereby revealing different relationship patterns at various quantiles within the outcome. This study compares how OLS and QR perform in modeling conditional relationships within a causal-comparative framework based on ex post facto research. Using the mortality data from …

Developing Deep Learning Methods For Cognitive Impairment Detection Based On Non-Invasive Data, Muath Alsuhaibani

Electronic Theses and Dissertations

Cognitive impairment detection is on the rise to help reduce the burden of healthcare costs on institutions and individuals. Mild Cognitive Impairment (MCI) is an early stage of cognitive decline progressing to Alzheimer’s disease (AD) or AD-related Dementia (ADRD). Detecting the early stages of AD/ADRD is crucial for early interventions among older adults to mitigate cognitive decline over time. However, the current diagnostic methods are often costly and/or invasive, such as MRI and PET scans. Thus, the search for non-invasive and cost-effective screening tools for the early detection of cognitive impairment using speech, language, visual, and motor data is growing. …

Behavioral Neuroscience Of Drug Addiction And Mental Disorder, Mona Muzammil, Muzammil Arshad, Washain Muzammil

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

This book explores the molecular, cellular, and neurocircuitry systems in the brain that are responsible for drug addiction. Common neurobiological elements are emphasized that provide novel insights into how the brain mediates the acute rewarding effects of drugs of abuse and how it changes during the transition from initial drug use to compulsive drug use and addiction. The book provides a detailed overview of the pathophysiology of the disease. The information provided will be useful for neuroscientists in the field of addiction, drug abuse treatment providers, and undergraduate and postgraduate students who are interested in learning the diverse effects of …

A Technical And Statistical Analysis Of Unleaded Aviation Fuel (Ul94) Adoption In A High- Volume Collegiate Aviation Environment, Nicholas D. Wilson, Ryan Guthridge, Brandon Wild, Jeremy Roesler, Daniel Kasowski, Nick Geinert, Aaron Terbest, Aaron Fettig, Robert Kraus

Journal of Aviation Technology and Engineering

The University of North Dakota (UND) adopted unleaded aviation fuel (UL94) for approximately a four-month period in the summer and early fall of 2023. The UL94 fuel was used in all reciprocating engine fleets based at the university’s primary training airport, Grand Forks International Airport in North Dakota. During the operational implementation of UL94, the UND flew 46,600 flight hours, consuming 386,778 gallons of fuel across all fleets powered by Lycoming engines. After approximately two months of using UL94, operational reports and maintenance inspections began to indicate potential for exhaust valve seat recession (EVSR), although early indications were limited in …

Enhancing Cataract Surgery Outcomes: Optimal Use Of Pre- And Post-Operative Eye Drops, Keith Skolnick M.D., Anu Valiaveedu

Mako: NSU Undergraduate Student Journal

Many preoperative and postoperative cataract patients struggle with comprehending the use of prescription medication as directed. Language barriers and low health literacy levels are major factors contributing to improper use of prescriptions. To increase patients comprehension, the Fort Lauderdale Eye Institute employed an educational intervention consisting of a live presentation and an instructional video. Results found that 44% of patients were hesitant to ask questions to clinical staff, 32% felt overwhelmed, and nearly 70% lacked confidence in using their prescribed eye drops. Following the intervention, 91% of patients reported increased confidence in their medications, and most indicated that the video …