Digital Commons Network^™

Social Network Assessment For Adult Protective Services (Snaaps), Version 1.0: A Network Canvas Data Collection Instrument, Rebecca L. Mauldin, Laura E. Carter

Social Networks for Social Good Collection-Archive

The Social Network Assessment Protocol for Adult Protective Services (SNAAPS) is a Network Canvas interview protocol designed to support the collection, organization, visualization, and interpretation of social network data from older adults. The protocol was developed for use by Adult Protective Services practitioners, social workers, first responders, and other service providers who assess, refer, and intervene on behalf of older adults' well-being. The protocol facilitates the identification of social network characteristics associated with risk and protection related to elder mistreatment, including support relationships, financial involvement, conflict within the network, frequency of contact, connections to formal services, and patterns of network …

Geospatial Governance Failures In The Department Of Defense: Contractor Noncompliance, Ai Adoption, And The Parallel Treatment Of Gis And Cybersecurity, Lyndsey Olmstead

Geography and the Environment: Graduate Student Capstones

The Department of Defense's treatment of geographic information systems and cybersecurity as parallel rather than integrated policy domains produces geographically predictable vulnerability patterns across its global military installation footprint. This capstone investigates that conclusion through original spatial analysis, constructing a five-variable composite geospatial vulnerability index across the six U.S. Combatant Command regions using publicly available unclassified data. EUCOM ranked highest overall, driven by GPS/PNT spoofing density, commercial satellite coverage, and cyber incident frequency; CENTCOM ranked second, driven by OSINT exposure incidents and governance risk. The null hypothesis of random geographic distribution is rejected. Findings confirm the structural governance gap documented …

Best Strategies To Teach Nutrition Courses In Graduate Programs: A Systematic Review, Zeina Hojeij, Suzan Haidar, Rana Rizk, Nadine Mahboub

All Works

Introduction – Graduate-level nutrition education requires innovative teaching strategies that foster advanced clinical competence, professional communication, cultural responsiveness, and self-directed learning. Methods – This systematic review synthesized evidence from fifteen peer-reviewed studies examining diverse teaching strategies in graduate nutrition programs. Results – Most interventions employed simulation-based learning, experiential placements, or flipped classrooms, often incorporating technology such as virtual simulations and online collaborative platforms. Simulation and experiential approaches improved clinical competence, communication skills, empathy, and self-efficacy by providing realistic, hands-on experiences that bridged theoretical knowledge with professional practice. Flipped classrooms, though less frequently implemented, promoted teamwork, problem-solving, and reflective learning, while …

Neongooey; V1, Carlos Ortiz Quintana, Jonathan Keathley, Ramses Ramirez

Laboratory of Planetary Habitability Atmospheric Models

This is the 1D magma ocean code used to create the NEONGOOEY data files for the Coupled atmospHere Interior modeL Intercomparison (CHILI) papers. This is a modified version of the GOOEY code from Schaefer et al. 2016, which includes carbon dioxide, a primordial hydrogen envelope, a new atmospheric escape framework and a new analytical corrected gray atmosphere approach for computing the outgoing longwave radiation (OLR). It has been used to model Earth, Venus, and Earth-sized scenarios at the orbits of TRAPPIST-1b and e.

Data Supporting “Unifying Observations, Simulations, And Theory For Drizzle Size Distribution Tails”, Raymond Shaw, Kamal Kant Chandrakar, Steve Krueger, Yangze Ren, Fan Yang, Jae Min Yeom

Michigan Tech Research Data

The onset and rate of drizzle remain open problems in atmospheric physics. This study brings together theory, simulations, and observations to analyze the emergence of power-law tails in droplet size distributions as a signature of a dynamic steady state with coalescence growth balanced by sedimentation removal. By applying a collector-mode approximation, analytic solutions are derived, predicting a droplet radius distribution scaling of $n(r) \sim r^{-4}$, assuming a collection kernel $K \sim r^6$. These predictions are validated against large eddy simulations of stratocumulus clouds, which exhibit the expected $r^{-4}$ scaling in the drizzle tail. Furthermore, in-situ measurements from stratocumulus clouds sampled …

Flagellar Coordination In A Swimming Multicellular Bacterium, Erandi Sachinthanie Imiya Mudiyanselage, Melina Mati, Alexander P. Petroff

Physics

Microbial locomotion is well understood when cells use either a small number of flagella or a high density of cilia. However many microbes live in an intermediate regime where coordination strategies such as flagellar bundles and metachronal waves are not possible. The mechanisms by which such organisms coordinate the motion of their swimming appendages are not well understood. Here, we study the only known obligatory multicellular bacterium, which are of the genus Magnetoglobus. Cells of this genus live exclusively in spherical communities called consortia, which are composed of a monolayer of tens of cells. Approximately a thousand of flagella project …

Samuel Johnson Dictionary, 1773 Edition, Beth Rapp Young

Research Data and Datasets

This dataset contains digitized page images from the 1773 fourth edition of A Dictionary of the English Language, contributed by the University of Florida and Indiana University as part of a digital humanities project led by Beth Rapp Young. The collection provides foundational primary source material for the study of 18th-century English lexicography and supports research in textual analysis, transcription, and historical linguistics.

A Large Language Model-Based Analysis Of Vulnerability Discovery In Windows Software, Puya Pakshad, Samson Quaye, Jamal Al-Karaki, Marwan Omar, Maurice E. Dawson

All Works

Source code security auditing is essential before software release in order to identify programming faults that may lead to vulnerabilities and functional failures. In this paper, we present a structured security assessment of the Windows App SDK by integrating multiple static analysis tools with a context-aware and disagreement-aware Large Language Model (LLM) interpretation layer. Although static analyzers are effective in reporting potential weaknesses, their raw outputs often contain redundant alerts, limited contextual explanation, and inconsistent severity assignments. To address these limitations, the proposed LLM-based interpretation layer normalizes and de-duplicates alerts, filters context-limited or nonactionable warnings, and refines severity prioritization under …

3dcotton, Md Ahmed Al Muzaddid, William J. Beksi

Agriculture - Archive

3DCotton is an image dataset consisting of 8 cotton plants recorded at the Texas A&M University Research Farm. The images were captured using an Apple iPhone at a resolution of 1040x1920 pixels. Approximately 150 images per plant were taken from a distance of 1 m by recording multiple viewpoints. These images can be utilized for developing 3D reconstruction methods.

Concordia Seminary Magazine Spring 2026, Ken Ohlemeyer

Concordia Seminary Magazine

Shaped for His Service

A Proactive Food Demand Forecasting-Inventory Management Approach Under Weather Disruptions, Asmaa Seyam, Sujith Samuel Mathew, May El Barachi, Jun Shen

All Works

Effective demand forecasting has become crucial to strengthening system resilience, reducing food waste, and achieving sustainability in food systems. Despite recent advances in leveraging machine learning for food demand forecasting, most existing models remain static and assume stable demand patterns, posing a challenge for adapting to demand changes during disruption events. This paper develops a proactive approach that leverages demand forecasting outputs and weather disruption flags to guide inventory replenishment, ensuring adaptability to varying demand conditions across three weather disruption events while reducing waste. This paper first uses a stacking model to predict next-day demand for a food retailer, leveraging …

Strategic Intent And International Corporate Entrepreneurship: The Role Of Learning Climate And Entrepreneurial Leadership In A Developing Economy, Maytha Al Ali, Muhammad Usman, Ilknur Ozturk

All Works

In today's fast-paced global economy, born-global SMEs must rapidly develop strategic capabilities to compete on the international stage. Understanding how these firms cultivate entrepreneurial behavior across borders is critical for sustaining competitive advantage. However, limited research has systematically examined the mechanisms and boundary conditions through which strategic intent translates into international entrepreneurial outcomes, particularly in developing economy contexts such as Pakistan. Drawing on dynamic capabilities theory, this study explores how the strategic intent of born-global firms drives international corporate entrepreneurship (ICE). We propose that a supportive learning climate acts as a key mechanism through which strategic intent translates into ICE. …

The Association Between Ethical Ai Use And Well-Being Among Young Adults In The Uae: A Structural Equation Modeling Approach, Areej Elsayary, Zeina Hojeij, Lames Abdul Hadi

All Works

This study examines the association between ethical AI use and young people’s emotional, social, and psychological well-being in the United Arab Emirates (UAE), where the number of hours spent on GenAI serves as a moderator. Framed within the Theory of Planned Behavior and aligned with the Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being) and SDG 13 (Climate Action), this research examines how responsible digital engagement is associated with both individual mental health and broader digital sustainability. A Structural Equation Modeling approach assessed how ethical AI behaviors are associated with well-being. A total of 204 participants, predominantly …

Data Supporting The Manuscript Aboveground Vulnerability And Belowground Resilience: Contrasting Responses To Precipitation And Herbivory Timings In A Mixed-Grass Prairie, Walter Wafula, A. Joshua Leffler, Krista Ehlert

NRM Departmental Data Sets

Dataset DOI: 10.62812/ZIAO4850

The downloadable zip file contains the following four data points:
File types: .xlsx and .doc

1. Soil moisture content data samples 
2. Monthly aboveground biomass production samples 
3. Season-long belowground biomass production samples
4. Line Transect Cover Observations at the beginning of summer season
   
   

How Hot Was The Jurassic Climate?, Richard Reynolds

Faculty of Science and Engineering Datasets

Appendacies for PhD thesis: How hot was the Jurassic Climate? Rhicert William Reynolds, University of Plymouth, 2026.

A Machine Learning Framework For Residential District Cooling: Forecasting Consumption, Explaining Drivers, And Evaluating Decarbonization Pathways, Kadhim Hayawi, Husna Maliakkal, Neethu Venugopal, Thanveer Musthafa Hussain, Gomathi Bhavani Rajagopalan

All Works

District Cooling Systems (DCS) in the Middle East, while energy-efficient, are significant contributors to carbon emissions. This study introduces a novel framework to decarbonize DCS operations by integrating predictive machine learning, explainable AI (XAI), and renewable energy planning, all grounded in extensive real-world data. Leveraging a unique dataset from 59 residential buildings in the UAE—including energy consumption, climate variables, and building features—we developed a high-fidelity cooling load forecasting model. Following a rigorous chronological validation methodology, the Random Forest model was identified as the most robust, achieving a strong performance (R² = 0.8256, RMSE = 11,668.31). Outdoor temperature was confirmed …

The Can Challenge: Understanding The Best Ways To Incentivise Recycling Through A Diffusion Approach, Michael Brock, Lucia M. Murgia, Stefania Sitzia, Jiwei Zheng

All Works

Understanding the best ways to incentivise recycling and improve the efficiency of waste practices is a key environmental, social, and economic management problem that needs addressing.We search for solutions to this issue by testing the effectiveness of two incentive mechanisms (a piece-rate and a lottery-based systems). We run a similar field experiment in three different locations, namely a student, residential and workplace environment, to verify the robustness of our findings and thus increase confidence in the external validity of our intervention. By interpreting recycling activity as marketable service, we employ a diffusion model to analyse the potential adoption of the …

From Ethical Principles To Executable Governance: A Policy-As-Code Framework For Trustworthy Ai In Higher Education, Edmund Evangelista, Syed M. Salman Bukhari

All Works

Artificial intelligence holds great potential to transform higher education, but a persistent gap remains between ethical aspirations and their practical, auditable enforcement. This study addresses that gap by developing and validating an end-to-end executable governance framework grounded in a policy-as-code (PaC) paradigm. Using student dropout prediction as a high-stakes example, the framework operationalizes governance through an automated gatekeeper, a multi-strategy fairness mitigation toolbox, and a tamper-evident audit chain for full reproducibility. The governance compliance was tested across sixteen fixed model configurations evaluated under five policy tiers (strict, medium, lenient, and two deployment-realistic variants). None were approved, as fairness violations, dominated …

Trust Asymmetry And Cross-Border Merger Withdrawals: A Global Perspective, Muhammad Farooq Ahmad, Saqib Aziz, Rwan El-Khatib, Duc Khuong Nguyen

All Works

We empirically examine how trust asymmetry between countries can impact the cross-border merger outcome. Differing trust perceptions between acquirer and target countries can increase the complexities of deal negotiations and integration, constraining the successful deal completion and outcome. We find, in a comprehensive global sample of 56 countries spanning 37 years, that higher trust asymmetries between the acquirer and target countries significantly increases the cross-border merger withdrawal intensity and reduces the expected synergy gains. Moreover, the adverse effects of trust asymmetry are significantly attenuated by the quality of institutions in both countries. Our results hold after employing various empirical techniques …

From Proficiency To Pedagogy: A Mixed-Methods Study Of In-Service Teachers’ Tpack-Genai And The Mediating Role Of Pedagogical Knowledge, Laila Mohebi, Areej Elsayary

All Works

This study investigated in-service teachers' Technological Pedagogical Content Knowledge for Generative Artificial Intelligence (TPACK-GenAI) and examined the factors influencing their integration of generative AI in classroom practice. Using an explanatory sequential mixed-methods design, data were collected from 325 in-service teachers across 26 countries, followed by in-depth interviews with seven teachers. Quantitative results revealed that Technological Knowledge (TK), Pedagogical Knowledge (PK), and Pedagogical Content Knowledge (PCK) were significantly associated with teachers' overall TPACK-GenAI. Crucially, mediation analysis confirmed that Technological Pedagogical Knowledge (TPK) serves as the indirect association through which TK is related to overall TPACK-GenAI competence. Qualitative findings enriched this result, …

Modeling Generative Ai Adoption In Higher Education: An Integrated Tam–Tpb–Sdt Framework With Sem Validation, Dina Tbaishat, Omar Alfandi, Faten Hamad, Syed Muhammad Salman Bukhari, Suha Al Muhaissen

All Works

This study investigates the determinants of university students' adoption of generative artificial intelligence (GAI) tools in higher education. Integrating the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and Self-Determination Theory (SDT), it develops and tests a complete model that captures cognitive, social, and motivational influences on adoption. A cross-sectional survey was conducted among 517 undergraduate and postgraduate students at Jordanian universities. The data were analyzed using structural equation modeling (SEM) with a two-step approach: confirmatory factor analysis (CFA) to validate the measurement model, followed by SEM to test the hypothesized structural relationships. Reliability, validity, measurement invariance across …

Implications Of Career Guidance On Career Choices And Professional Development: Stakeholders’ Perspectives From Selected Higher Educational Institutions In The Uae, Solomon Arulraj David, Laila Mohebi

All Works

Career choices and professional development are influenced by various factors, such as family dynamics, teacher guidance, career counselling, peer influence, continuous learning, and market trends. This study aims to explore the experiences and perspectives of both students and staff regarding the impact of career guidance on the career choices, professional development of undergraduate Emirati students in selected higher education institutions in the UAE. Twenty-three participants, purposefully chosen, were interviewed using a semi-structured questionnaire. Thematic analysis was employed to analyze the gathered data. The findings indicate relatively a positive understanding of staff and students regarding the heightened awareness of career choices …

Predicting Takeover Rumor Accuracy With Machine Learning, Hamed Khadivar, Frederick Davis, Ameneh Khadivar, Ivan Stetsyuk

All Works

This study applies machine learning models such as TabNet, XGBoost, CatBoost, Support Vector Machines, a Multilayer Perceptron, and Logistic Regression to predict takeover-rumor accuracy using a proprietary dataset of 2074 rumor articles with identifiable target firms, screened from over 30,000 news articles from January 2002 to December 2011. In the raw feature (no-PCA) specification, Logistic Regression and TabNet perform similarly. After addressing class imbalance and applying dimensionality reduction (PCA), TabNet materially outperforms Logistic Regression and delivers economically meaningful gains: A TabNet-based long-short strategy earns higher average monthly abnormal returns than a Logistic Regression strategy at both horizons, 1.148% versus 0.773% …

Insights Of Pre-Service Teachers In The Uae On Ai-Infused K-12 Classrooms: Implications For Policy And Curricula In Teacher Education, Ayman Massouti, Nessrin Shaya, Sandra Baroudi

All Works

No abstract provided.

Segmented Inner Skull Cavities Of Eothoracosaurus Mississippiensis (Msu 3293), Amy Moe-Hoffman, Renee Clary

Research Data

Dunn-Seiler Museum specimen data:

• Catalog Number: DSM/MSU#3293 HOLOTYPE 
  
• Geographic Locality: Oktibbeha County, MS Rock Hill vicinity 
  
• Geologic Locality: Ripley Formation 
  
• Age: Cretaceous (Maastrichtian)   

Specimen includes Cranium, Mandible, loose teeth, and post-cranial elements.  

1. CT Scan description: The specimen MSU 3293 was scanned at the Mississippi State University College of Veterinary Medicine using a GE LightSpeed VCT (GE Healthcare, Chicago, Illinois, USA; www.gehealthcare.com ) on May 4th 2022, with scan energies of 120kV and 200mA. This produced 1593 images with a slice thickness of 625µm. 
2. 3D models: 3D models of segmented inner skull cavities based on segrmetation of the CT scanned …

Creative Practice Submission: 3rd European Baha'i Choral Festival, Colin N. Webber Dr

Staff Scholarship - Australia & Dubai

n May 2026, I travelled to Germany on invitation to conduct two choral works at the 3rd European Baha'i Choral Festival - one an original composition and one an arrangement of a piece by Australian composer Tom Francis), both recent works from the corpus of a cappella choral music I have developed over several decades in response to the writings of the Baha'i Faith. The two concerts took place on 17 May 2026 at the Baha'i-Haus der Andacht von Europa (European Baha'i House of Worship), Langenhain, Germany, following three days of intensive ensemble rehearsals with the 75 voice choir. These …

Deep Learning Compilers, Raffi Khatchadourian

Open Educational Resources

These lecture slides introduce deep learning compilers for a graduate compiler-construction course (CSc 81010). Building on the classical compiler pipeline, they show how modern machine-learning systems compile tensor programs: static tensor and type analysis (illustrated by a WALA/Ariadne-based refactoring of imperative TensorFlow code to graph mode), MLIR-based end-to-end compilation with IREE, and the PyTorch 2.x stack—TorchDynamo graph capture, AOTAutograd, PrimTorch operator decomposition, and TorchInductor lowering to Triton (GPU) and C++/OpenMP (CPU). The slides are a self-contained HTML (W3C Slidy) deck with editable Pandoc Markdown source. Part of a two-session unit on advanced compiler topics; see also "LLMs in Compiler Construction."

Applied Reproductive Science: Technology, Ethics, And Management In Modern Animal Systems, Hagan Beach

Publications

This creative component course development project includes five (5) supplementary lessons focused on animal welfare concerns in livestock reproduction, biological foundations of ethical animal reproduction, responsible use of reproductive technology, ethical reproductive management, and ethical breeding decisions in livestock genetics. This resource also includes a teacher guide, supplementary instructional materials, assessment materials, implementation guidance, and reflection sections.

Together, these components give teachers a usable set of lessons and support materials for bringing ethical decision-making into animal science instruction. Although each lesson can stand on its own, the sequence was arranged to move from foundational reproductive science into more applied questions …

Llms In Compiler Construction, Raffi Khatchadourian

Open Educational Resources

These lecture slides survey the use of large language models (LLMs) in compiler construction for a graduate compiler course (CSc 81010). They situate LLMs across the compiler pipeline and examine representative work: foundation models trained on LLVM IR and assembly (Meta's LLM Compiler), LLM-driven code optimization, binary decompilation (LLM4Decompile), and LLM-assisted automated refactoring—alongside the challenges of applying probabilistic models to tasks that demand correctness. The slides are a self-contained HTML (W3C Slidy) deck with editable Pandoc Markdown source. Part of a two-session unit on advanced compiler topics; see also "Deep Learning Compilers."

Shimmer Methodology: May 2026 Cultural Studies Association Of Australasia, Lola Montgomery

Staff Scholarship - Australia & Dubai

This webinar presents an overview of the contemporary state of creative-practice research and autotheory before introducing Shimmer, an emerging methodological framework developed through creative practice, postgraduate supervision, and reflective inquiry. The presentation argues that while creative-practice research has successfully established creative work as a legitimate form of knowledge production, and autotheory has legitimised lived experience as theoretical material, both traditions leave relatively under-theorised the embodied moment through which insight first emerges.

The significance of the work lies in its contribution to ongoing debates around embodiment, affect, intuition, and knowledge production within creative-practice research. Shimmer proposes a language for understanding …