Digital Commons Network^™

Ethical Decision-Making Processes In Authentic Environmental Engineering Contexts Through Systems Thinking And Team Collaboration Lenses: An Embedded Single Case Study, Toluwalase Eniola Brower

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Ethical and professional responsibility is a critical learning outcome emphasized in ABET accreditation. However, ethics instruction in engineering education often lacks integration of system-level considerations such as economic, environmental, and societal contexts, that are essential for developing engineering solutions that ensure the safety and welfare of diverse stakeholders. This embedded single-case study investigated the integration of authentic ethics instruction within a junior-level environmental engineering course at a Midwestern U.S. university during spring 2025 and explores how civil engineering student teams within the course engage in ethical decision-making process during authentic problem-solving.

The instructional intervention consisted of four problem-based ethics modules, …

In-Field Tractor Operational Load Profile Generation In Support Of Advanced Tractor Testing In Mixedmode Power, Andrew Donesky

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation addresses the need to better characterize real-world tractor power requirements across drawbar, power take-off (PTO), and hydraulic modes to support more representative tractor testing. Conventional testing protocols, such as OECD Code 2, emphasize steady-state performance under controlled high-load conditions, which do not reflect the mixed and dynamic demands of modern field operations. To address this gap, a Tractor Instrumentation System (TIS) was developed, validated, and deployed to collect high-resolution, mixed-mode power data during planting, anhydrous ammonia application, and grain cart operations. The TIS integrates physical sensors, including custom load pins, hydraulic pressure/flow sensors, and a redesigned PTO torque …

Rapid State-Of-Health Estimation Of Batteries Using Machine Learning With Limited Eearly-Discharge Voltage Data, Mohammad Bakhtiari

Durham School of Architectural Engineering and Construction: Dissertations, Theses, and Student Research

The utilization of lithium-ion batteries has been rapidly expanding across diverse sectors, including electric transportation, stationary energy storage systems, and the built environment. Ensuring a high level of reliability in these applications is essential, as the performance and safety of such systems depend strongly on the accurate assessment of the battery’s State of Health (SOH). Conventional SOH estimation techniques—often based on complex electrochemical models or extensive laboratory testing—tend to require a large number of measurements, advanced instrumentation, and high computational cost. These factors make them impractical for large-scale deployment or real-time monitoring. This study introduces a simplified machine-learning-based approach for …

Pfos And Lung Injury: A Review Of Human And Experimental Evidence, Farzana Hakim

Theses and Dissertations

Human epidemiological research has shown the adverse health consequences of long-term accumulation of per- and polyfluoroalkyl substances (PFAS) in human tissue. Specifically, this review will examine the relationship between PFAS exposure, impaired immune system functioning, and an elevated risk of respiratory disease using both human and experimental data. Research on human populations indicates that children exposed to PFAS have lower levels of antibodies to vaccines; those children prenatally exposed to PFAS are more susceptible to upper respiratory infections; and that adult humans have a higher incidence of chronic obstructive pulmonary disease (COPD). Additionally, experimental studies demonstrate that PFOS and PFOA …

Leveraging Virtual Reality In Nursing Education To Enhance Confidence And Knowledge, Kerry Vaccaro, Amanda Bodinet, Concetta Zak

Biennial Convention (CONV)

Blood transfusion reactions can be life threatening and are rarely encountered by nursing students in clinicals. Simulation has been shown to have a positive impact on transfusion-related competence in nursing students (Brown, C. & Brown, M., 2023). BSN nursing students faced challenges in recognizing and responding to blood transfusion reactions. A Virtual Reality (VR) simulation was introduced as an innovative teaching modality. Virtual Reality provides learners with a more life-like experience that is standardized and safe (Kiegaldie & Shaw, 2023). The purpose of this study was to evaluate whether VR simulation, compared to traditional lecture, improves senior-level BSN students' confidence …

Advanced Practice Provider (App) Midline Training Initiative, Al-Zada Aguilar, Sarah D. Maute

Biennial Convention (CONV)

Temporary, non-tunneled central venous catheters (CVCs) are commonly used for vascular access in patients with vesicant infusion needs or difficult intravenous access (DIVA). However, CVCs are associated with primary bloodstream infections (BSIs), contributing to significant morbidity, mortality, and financial burdens. At our institution, central line-associated bloodstream infection (CLABSI) rates and central utilization ratios have steadily increased since 2023, rising from 0.43 to 0.75 and 0.17 to 0.21, respectively, despite system-wide infection prevention initiatives. Recognizing the limitations of current approaches, particularly for DIVA patients, midlines emerged as an alternative to both CVCs and ultrasound-guided peripheral IVs (USG-PIVs).

In response, a multimodal …

Faculty Perceptions Of Student Mental Health And Real-World Readiness, Allison A. Maloney, Meghan Pontz

Biennial Convention (CONV)

The mental health of students is a cornerstone for achieving global goals of quality education & good health and well-being. These priorities are urgent calls to action for educators and policymakers to foster sustainable economic development. The COVID-19 pandemic has magnified the vulnerabilities of educational and health systems worldwide, redefining how students are educated and prepared for the workforce. This challenge is pertinent in higher education, where faculty play a role in equipping students for professional environments while addressing their mental health needs—a determinant of future workforce resilience and productivity.

This study examines faculty perceptions of student mental health and …

Integrating Telehealth Innovation To Advance Emergency Department Flow And Nursing-Led Care, Patrice Callagy, Maria Cheung

Biennial Convention (CONV)

Purpose: Efficient patient flow is critical for managing capacity and delivering timely, equitable care in emergency departments (EDs). As patient acuity and census increased at Stanford Health Care (SHC), traditional Fast Track spaces were reassigned to higher-acuity patients, leaving lower-acuity patients with prolonged lengths of stay (LOS). Prolonged LOS increases the risk of patients leaving without treatment, impacting care outcomes. To address this, SHC’s Digital Health team and Emergency Services leadership developed an innovative Virtual Fast Track care framework using telehealth technology and multidisciplinary workflows.

Methods: This novel approach applies an "inverted telemedicine" model in which care is provided within …

Sustaining The Future Workforce With What Matters Most To Nurses, Deirdre O'Flaherty

Biennial Convention (CONV)

Introduction: Meaningful recognition confirms the value of nurses’,environments that acknowledge this influence a healthy workplace. Applying quadruple aim framework, optimizing healthcare system outcomes places wellbeing in the forefront and supports fostering resilience, hardiness, interprofessional collaboration and engagement, augmenting the work setting.

Objectives: Discussing strategies, interprofessional collaboration, engagement, fortified resilience, empowered staff and have brought value and meaning to nurses. This study compares peer-reviewed literature on the impact of leadership styles, organization culture and support among nurse managers.

Methods: We previously studied and analyzed clinical nurses’ and nurses in leadership positions perceptions of resilience, empowerment and pre-pandemic engagement. Results …

Service-Learning In Nurse And Midwifery Education: Building Capacity In The Americas, Adelais Markaki, Deborah Bowers, Emily Patton, Lisa Theus

Biennial Convention (CONV)

Introduction: Service-learning (SL) integrates purposeful and immersive community-based experiences into the curriculum while addressing health disparities.^1,2 Growing evidence from North America shows that academic service-learning nursing partnerships can lead to impactful change.³ Yet, the need to integrate SL into the curriculum must be informed by country-specific, regional evidence.

Purpose: To train in and promote integration of SL by nurse and midwife educators in alignment with the Global Strategic Directions for Nursing and Midwifery⁴ for developing clinically competent and culturally-sensitive practitioners equipped to provide population-targeted services.

Objective: Identify evidence from the Americas region on service-learning integration and best …

Goodbye Textbook: Content Creation For A Non-Clinical Nursing Course Using Ai Tools, Julie Kientz Elting

Biennial Convention (CONV)

Purpose: To provide guidance for faculty interested in creating materials using AI tools for nursing courses which allows ‘unadoption’ of textbooks.

Background: When discussing AI text generation tools like ChatGPT and Gemini (AI tools), many nursing faculty are only aware of the risks to academic writing (Abujaber et al., 2023). But there are many pedagogical benefits of AI tools that enhance student learning (Elting & Desio, 2024; Glauberman et al., 2023; Srinivasan et al., 2024) and manage faculty teaching, communication, and administrative tasks (Srinivasan et al., 2024). What is less known is how AI tools can be used to create …

A Prevalence Study Of Iron Deficiency Anemia Among Children In Elbasan, Albania: Directions For Health Care Policy, Artilda Lala

All Dissertations

Iron deficiency anemia (IDA) is one of the most prevalent disorders worldwide, especially in children from low-income and underdeveloped countries. In Albania, anemia is a major public health concern with many unstudied regions (prefectures and rural municipalities). Childhood IDA can impair cognitive development, immunity and overall well-being, so early diagnosis and prevention of anemia is critical. This study examined the prevalence of IDA in children aged 0-10 years in the district of Elbasan, Albania. The data were additionally analyzed for relationships with demographic (age, gender, education, parental education and child academic performance) and nutrition variables.

A cross-sectional study design was …

Repealing Reorgs, Reuven S. Avi-Yonah

Law & Economics Working Papers

Under the Supreme Court's opinion in Moore, it is likely that realization is essential for defining income as a constitutional matter. Therefore, when a transaction involves realization, it should presumptively be taxable unless there are very good reason for nonrecognition of gain. Given this reality, there are good reasons for Congress to consider repealing tax-free reorganizations and the other nonrecognition rules of the corporate tax, primarily for non-tax reasons. Acquisitive A, B, and C reorganizations and acquisitive section 351 transactions typically are used for large public corporations to acquire startups, which encourages monopolies. Triangular mergers raise corporate governance concerns …

A Combined Multi-Isotope And Machine Learning Approach To Determine Groundwater Salinity And Solute Sources, Lower Valley Area, El Paso County, Texas, Gloria A. Ortiz Gamboa

Open Access Theses & Dissertations

Groundwater salinization is increasingly troublesome in aquifers in and around El Paso, Texas, where concern for available water resources has grown due to frequent droughts and increasing population. Both groundwater and surface water have experienced an increase in total dissolved solids (TDS), a trend that can pose future health and economic problems for residents who primarily rely on groundwater. To address this issue, this research focuses on the Hueco Bolson Aquifer and the Rio Grande Alluvial Aquifer within the Lower Valley area of El Paso, Texas, utilizing a multi-analysis approach to evaluate and determine solute sources and their possible end-members …

Passing The Bar In And Through Community: The Science Behind Why We Truly Do Better Together, Katherine O. Armstrong

University of Dayton Law Review

Law school graduates preparing for the bar exam often face isolation, leading to mental health challenges, decreased motivation, and impaired performance. This sense of loneliness, coupled with the known mental health and substance abuse issues in the legal profession, underscores the urgent need for change. Research shows that community engagement enhances mental and physical well-being, fosters motivation, and improves educational outcomes. However, little scholarship addresses the role of community in bar exam preparation, leaving a critical gap. This Article explores the transformative power of community during bar preparation. It provides a detailed view of a law school that has successfully …

Reduction In Patient Falls: A Quality Improvement Project, Jotis J. Lee

Doctor of Nursing Practice Projects

Patient falls remain one of the most frequent adverse events in hospital settings, leading to injury, prolonged hospital stays, and increased healthcare costs. The identified problem was high fall rates at a specialty hospital. The purpose of this Doctor of Nursing Practice (DNP) quality improvement (QI) project was to evaluate the effectiveness of an evidence-based (EB) educational intervention, using the Fall TIPS (Tailoring Interventions for Patient Safety) toolkit, in improving direct care nursing staff’s knowledge, confidence, and perceived ability to implement fall prevention strategies for high-risk patients. The aim was to improve the nursing staff’s knowledge, confidence, and perceived ability …

Dual-Level Pattern Tree For Visual Field Improves Glaucoma Progression And Polygenic Risk Prediction, Luo Song, Lucy Q. Shen, Louis R. Pasquale, Michael V. Boland, Sarah R. Wellik, Carlos Gustavo De Moraes, Ayellet Segre, Janey L. Wiggs, Constance Turman, Jonathan S. Myers, Tobias Elze, Nazlee Zebardast, David S. Friedman, Jae H. Kang, Mengyu Wang

Wills Eye Hospital Papers

PURPOSE: To develop a dual-level pattern tree to characterize visual field (VF) loss subtypes that can be used to better predict glaucoma progression and glaucoma polygenic risk scores (PRSs).

METHODS: This study included 113,030 patients from three datasets, each used for a specific purpose: (1) model training, (2) progression forecasting, and (3) PRS correlations. We applied archetypal analysis to cluster 24-2 VFs into trunk patterns and their branch patterns. The Cox regression model was used to forecast VF progression using mean deviation (MD) slope, MD-fast slope, total deviation (TD) pointwise slope, and visual field index (VFI) slope. Multivariable regression analyses …

Quicknotes December 2025, Southern Adventist University

QuickNotes – Advancement e-Newsletter

QuickNotes is an e-newsletter that comes from Advancement at Southern Adventist University. The December 2025 edition features the university's online prayer call for alumni, parents, and employees.

Acute Effects Of Lactate Infusion On Metabolism, Ad Biomarkers, And Cognition, Riley E. Kemna, Paul J. Kueck, Anneka Blankenship, Casey S. John, Chelsea N. Johnson, Zachary D. Green, Hana Mayfield, Lauren Yoksh, Lance Johnson, John P. Thyfault, Jonathan D. Mahnken, Benjamin F. Miller, Jill K. Morris

Physiology Faculty Publications

BACKGROUND: Impaired cerebral glucose metabolism is a hallmark of Alzheimer's disease (AD). Lactate is an alternative brain fuel; however, whole-body lactate metabolism has not been measured in AD. METHODS: The Lactate for Energy and Neurocognition Trial (NCT05207397) was a single-arm trial that enrolled 24 cognitively healthy (CH) older adults and 12 cognitively impaired (CI) participants. Subjects underwent a stable isotope lactate infusion to evaluate lactate metabolism, cognitive testing, and blood biomarker analyses. pTau217, brain-derived tau (BD-tau), pTau181, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), total tau, and brain-derived neurotrophic factor (BDNF) were analyzed by Simoa HD-X (Quanterix). RESULTS: …

Direct Measurement Of Mavacamten And Deoxyatp Perturbation Of The Srx/Drx Ratio In Porcine Cardiac Myofibrils Using A Simple, Accessible And Multiplexed Approach, Matvey Pilagov, Ateeqa Naim, Kenneth S. Campbell, Thomas Kampourakis, Michael A. Geeves, Neil M. Kad

Physiology Faculty Publications

Cardiac muscle adapts to varying physiological demands by modulating the number of active myosin II motors available for contraction. These motors are organized into thick filaments in the sarcomere and generate force through an ATP-dependent interaction with thin filaments that contain actin. To conserve energy, when demand is low myosin can occupy the super-relaxed (SRX) state, which acts as a reserve. Here, we build upon the earlier studies to quantify the size of this cardiac reserve using fluorescence imaging of Cy3-ATP directly in myofibrils. This approach employs a pulse-chase method and exploits the high permeability of isolated myofibrils to monitor …

Detecting Illicit Bitcoin Transactions On The Dark Web, Abdulla Alsuwaidi

Theses

Dark web markets use Bitcoin and related cryptocurrencies to transfer and launder proceeds of crime while obscuring the real-world identities of operators. This creates an increasingly challenging environment for regulators and law-enforcement agencies, who must analyse suspi- cious transactions on decentralised, public, pseudonymous blockchains and increasingly dense and noisy Bitcoin transaction graphs. This thesis investigates whether, and how, blockchain analytics and machine learning can help detect illicit transactions on Bitcoin networks. The first part of the thesis is a systematic literature review of recent contributions from academia and industry that examine major solution approaches for identifying illicit flows on public …

Persuasive Pathways In Digital Apologies: The Role Of Persuasion Routes In Engagement With Youtuber Apology Videos, Darrin Majocha

Theses

This study explores how viewers process YouTube apology videos and how those processing methods relate to their judgments of the creator and their willingness to continue engaging with the channel. Guided by the Elaboration Likelihood Model, a single-session online survey experiment randomly assigned 413 adult participants to watch one of five publicly available apology videos from well-known YouTubers. After viewing, participants reported the extent to which they engaged in central versus peripheral processing, rated the creator's credibility and the apology's sincerity, and indicated their intentions to engage. Central processing was positively associated with engagement intentions, whereas peripheral processing was weakly …

Transgender Adolescents' Healthcare Rights: The Gap Between Gender-Affirming-Care (Gac) Policymakers’ And Healthcare Providers’ Goals, Jayden Galli

Theses

Transgender people have marginalized healthcare experiences that result in decreased health outcomes. For transgender adolescents, gender-affirming-care (GAC) is even more difficult to access and being restricted with increasing frequency. This mixed methods study was conducted to examine transgender healthcare through the gaps between GAC policymakers’ and healthcare providers’ goals. General research has focused on the relationship between GAC and transgender health, GAC policy development, and the discrepancies between GAC policy outcomes and medical professionals’ advice. This leads to the research question about how policymakers and healthcare providers can collaborate to bridge the gap between GAC policies and transgender minors' healthcare …

Physics Meets Data: Merging Physics-Based Methods With Deep Learning To Model Complex Systems, Maryam Toloubidokhti

Theses

Accurate modeling of complex systems is crucial in domains such as healthcare, where personalized diagnosis and treatment planning are essential. Traditional physics-based models provide structured, theoretically grounded insights but are often computationally intensive and constrained by simplified assumptions that limit adaptability to patient-specific conditions. In contrast, data-driven models are computationally efficient and capable of capturing complex patterns, yet they often lack interpretability and fail to incorporate essential physical principles, reducing robustness and generalization. This disconnect between mechanistic understanding and computational practicality presents significant challenges in critical applications such as healthcare, where both physical accuracy and real-time performance are vital. To …

The Impact Of The 2008 Financial Crisis On Crime And Cybercrime In The United States, Rashed Adel Alsuwaidi

Theses

This thesis will examine how the traditional crime and cy- were affected by the 2008 financial crisis. United States are also experiencing a rise in crime between 2005 and 2012. Based on the FBI data at the national level. The Internet Crime Complaint Center (IC3), Uniform Crime Reports and important economic indicators. The study, which involves tors, including unemployment, GDP, rates of foreclosures, and mortgage rates, is a combination. correlationbased interpretation supported by exploratory descriptive trend analysis. model-fit checks. The results indicate that contrary to the conventional expectations, violent and property crime also maintained their long-term reduction during the period …

Predicting Employee Attrition With Machine Learning: Data-Driven Strategies For Enhancingworkforce Retention, Ali Almheiri

Theses

In this research, the dual prediction and prescription model is developed and validated so that this model can not only predict employee turnover risk, but it also proposes the appropriate retention interventions, which apply across industries. On the basis of the IBM HR Analytics Attrition dataset (n=1,470), we preprocessed demography, job and satisfaction variables and trained three machine-learning classifiers, Random Forest, Logistic Regression and XGBoost to predict voluntary turnover. XGBoost model recorded the best discrimination (AUC=0.87), sensitivity (0.76), and specificity (0.81), which signifies strong predictive power. Analysis of feature-importance was conclusive with time, rate of frequent business travel and compensation …

Predictive Maintenance For It Equipment Using Machine Learning Models, Rashed Khalid Alshirawi

Theses

Predictive maintenance was recently introduced as a paradigm shift in the field of smart manufacturing, and it allows organizations to predict equipment failures and streamline maintenance planning based on the data-driven insights. The present work addresses the concept of the implementation of a decision tree-based predictive maintenance model based on AI4I 2020 Predictive Maintenance Dataset, a simulated environment of an actual industry through sensor data including temperature, torque, rotational velocity, and toolwear. The study uses a quantitative approach that is based on positivism philosophy, which is the focus on objectivity, empirical validation, and statistical testing of the model performance. Synthetic …

Predicting Residential Real Estate Prices In Dubai Using Integrated Data Analytics: A Machine Learning Approach, Mohammad Nasser

Theses

Dubai’s rapidly evolving real estate market attracts substantial global investment yet remains characterized by information asymmetry, pricing volatility, and fragmented data sources. This study examines how integrated data analytics and ensemble machine learning can be used not primarily for precise price prediction, but rather to identify and quantify the key behavioral and transactional drivers of residential property prices in Dubai. A unified dataset was constructed by integrating over 100,000 residential property transactions from the Dubai Land Department with macroeconomic indicators, web-scraped listing attributes, and sentiment measures derived from online reviews and social media discussions. Supervised learning models including Linear Regression, …

Predictive Analysis Of Residential Property In Urban Areas, Hamad Adnan Alzarooni

Theses

This paper aims to determine the predictive modelling of residential property prices in urban Scotland with the help of an integrated framework in which machine learning methods are applied in combination with detailed socio-economic, health, housing, and geographic indicators. Conventional valuation methods tend to be based on the concept of few structural variables and ignore the effect of multidimensional variables in determining spatial variation in housing markets. To cope with this, the study uses Linear Regression, random forest, Multi-layer perceptron, and XGBoost models, which are assisted by a broad range of feature engineering, outlier management, and data preprocessing. Compared with …

Ai-Powered Mobile Phone Activity Insights: Developing Predictive Models For Smarter Decision-Making, Maryam Al Ali

Theses

This study investigates how artificial intelligence can enhance telecom network management by forecasting internet usage, predicting congestion, and identifying user behavior patterns from mobile phone activity data. The study made use of anonymized logs for calls, SMS and internet, and put up a multi-model analytical pipeline, which was composed of time-series forecasting (ARIMA, LSTM), clustering (K-Means), and classification (XGBoost), to perform the analysis. Among the time-series methods, ARIMA ranked first in the forecast performance (RMSE=0.31) and gave LSTM a convincing defeat in the case of this particular short and stable dataset. Based on K-Means segmentation, users were sorted into five …