Digital Commons Network^™

Using Graphic Novels In The Teaching And Learning Of Mathematics And Physics, Jason Ho, David Klanderman, Sarah Klanderman, James Turner

University Faculty Publications and Creative Works

Are you looking for innovative teaching strategies for geometry or other mathematics and physics courses? In this article, we o!er a discussion of several graphic novels and their potential for successful teaching and learning at the high school and university levels. We describe how engaging stories, combined with mathematical and scientific meaning found in both text and image, can help to excite students, enrich learning, and explain mathematical concepts. We report on recent data collected from multiple mathematics and physics classes that extend prior research on the use of graphic novels to teach English Language Arts (Boerman-Cornell and Kim, 2020) …

Leading From The Precipice: How Academic Deans Are Navigating Artificial Intelligence In Higher Education, V. Dozier, Sarina Chugani Molina

Copley Library: Faculty Scholarship

This qualitative case study examines how associate deans at a medium-sized Catholic university respond to the rapid integration of generative artificial intelligence (AI). Guided by decolonial and feminist frameworks, the study analyzes survey data from seven academic leaders to understand their concerns, decision-making processes, and emerging practices. Our findings reveal uneven adoption, limited institutional guidance, and ongoing concerns about academic integrity, equity, and bias. The study also highlights the often-unseen relational and emotional labor involved in supporting faculty and students. We conclude by recommending flexible, collaborative approaches to AI governance that attend to context, care, and diverse ways of knowing.

Fastest-Warming States And Cities In The Mountain West, 2025, Maisoon Faris, Kahlen Coss, Kevin Yang, Caitlin J. Saladino, William E. Brown Jr.

Environment

This fact sheet presents data published by Climate Central on the change in average annual temperatures for the five Mountain West states of Arizona, Colorado, Nevada, New Mexico, and Utah and 15 Mountain West cities from 1970 to 2025. City-level data are derived from Applied Climate Information System (ACIS) operated by National Oceanic and Atmospheric Administration (NOAA), state-level data are derived from NOAA’s National Centers for Environmental Information (NCEI).

Infographic: Teacher Pedagogical Knowledge, Dominique Russell

Teacher infographics

Part of the OECD’s Teaching and Learning International Survey (TALIS) 2024, the Teacher Knowledge Survey is the first large-scale study providing internationally comparable measures of general pedagogical knowledge (GPK). Findings suggest it may contribute to improving students’ and teachers’ outcomes.

"Robert Pain And The Legacy Of Leadership", William Lindsey Mcdonald

Research Articles

Robert Paine was the first president of LaGrange College, the earliest predecessor of the University of North Alabama. The article gives a brief overview of Paine's leadership.

Approval Letter For The Butte Priority Soils Operable Unit Field Sampling Plan And Investigation Plan: Ur-41 - Montana Street And Interstate-90, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Toward Reliable Compressive Strength Prediction Of Marble Powder-Blended Concrete: Comparative Machine Learning And Shap-Based Interpretability, Shamal Abdullah Mohammed, Aryan Far H. Sherwani, Nzar Shakr Piro

Polytechnic Journal

The production of conventional concrete has a significant impact on the environment, primarily due to the cement (C) component. To mitigate this impact, binders with reduced environmental footprints were used in concrete mixtures as a partial replacement for C, including powders of industrial byproducts. Waste marble powder (WMP) is one such alternative; however, its incorporation causes complicated interactions with cementitious materials, making the compressive strength (CS) prediction difficult. This study developed and evaluated four predictive models (multilinear regression (MLR), full quadratic regression (FQ), M5P tree, and artificial neural network (ANN)) using a dataset of 306 WMP-blended concrete mixes from 16 …

Ai-Supported Analysis Of Jury Deliberation Impact Factors, Jennifer Siciliani Phd

Generative AI Teaching Activities

Students conduct a controlled, two-run generative AI jury simulation to examine how a single socio-legal variable affects simulated jury deliberation. They compare and manually code the AI-generated outcomes against peer-reviewed human jury research to evaluate the model’s accuracy, limitations, and potential biases.

Re: Approval Letter For The Draft Final Butte Priority Soils Operable Unit Insufficiently Reclaimed Sites Temporary Best Management Practices Work Plan: Bres No. 16 – Curry And Bres No. 50 – Zelia, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Discovering Repurposable Drugs For Alzheimer's Disease And Related Dementias: Target Trial Emulation Using Decentralised Real-World Data, Qiong Wu, Lu Li, Yuqing Lei, Ting Zhou, Huilin Tang, Bingyu Zhang, Yiwen Lu, Maxwell Salvatore, Dazheng Zhang, Jiayi Tong, Tingyin Wang, Siqi Chen, Haoyang Li, Zhenxing Xu, Yu Huang, Yu Hu, Na Hong, Yujia Zhou, Fongci Lin, Kyra O'Brien, Yong Chen, Ruowang Li, Hua Xu, Fei Wang, Jiang Bian, David Wolk, Yong Chen

College of Population Health Faculty Papers

BACKGROUND: Alzheimer's disease and related dementias (ADRD) affect nearly 6.9 million Americans, with the number expected to triple by 2050, while disease-modifying therapies remain unavailable. Drug repurposing, which identifies new indications for already approved medications, offers a more efficient and cost-effective pathway to accelerate development of effective therapies for ADRD. The aim of this study is to identify potential drug repurposing signals by systematically screening routinely prescribed drugs for associations with progression from mild cognitive impairment (MCI) to ADRD.

METHODS: We conducted a multi-site target trial emulation using electronic health record (EHR) data from four decentralised databases: INSIGHT Clinical Research …

Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Draft Data Summary Report 2024 Surface Water, Groundwater, And Soil Characterization, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Kant, Stephan Körner

Hannah Arendt Marginalia - All

Harmondsworth ; Middlesex : Penguin Books, 1955.

Call #: B2798 .K6

Contains underlining  PDF information: 15 pages - 5.5 MB

Preoperative Urine Drug Screen To Increase Surgical Efficiency, Joseph Mashinchi

SIU Journal of Medical Science Scholarly Works

Purpose: The purpose of this article is to standardize the use of preoperative urine drug screens for adults scheduled for elective surgery in order to improve surgical efficiency and reduce perioperative and postoperative complications.

Method: A PubMed Search was conducted to review literature published within the past five years. The joint terms “urine drug screen and surgery” were used in the search. A literature review was conducted after reviewing multiple articles and screening for their quality, timeliness, and pertinence to elective surgical procedures and illicit drug use.

Results: Performing a urine drug screen prior to elective surgical procedure identified illicit …

Studying Electromagnetic Wave Scattering From Small Dielectric Particles Using Neural Networks, Bryan Taylan, Patrick Corzo, Chris Velissaris, Theodoros Panagiotakopoulos

Undergraduate Scholarship and Creative Works

Physics-informed neural networks solve the Helmholtz equation without labeled data, but a low residual alone does not confirm that a solution preserves the physical distinction a downstream task depends on. We trained a four-layer SIREN with physics-based residuals, a Sommerfeld condition, Adam, and L-BFGS, modeling a Gaussian source and a plane wave scattering from a small dielectric inclusion. Fine-tuning from four base models produced 600 complex fields spanning omega = 4 to 20. A compact CNN, three ResNet-18 variants, and a frozen OpenCLIP encoder classified these fields under five random seeds. The CNN achieved (95.65 +/- 0.77)% accuracy, outperforming OpenCLIP …

Genesis And Structure Of Hegel's Phenomenology Of Spirit, Jean Hyppolite

Hannah Arendt Marginalia - All

No abstract provided.

Octvec-Xd: Deterministic Multi-Resolution Integer Signatures For Multidimensional Vectors, Nenad Micic

Defensive Publications Series

A technique is proposed herein for converting a multivariate integer vector into a deterministic, fixed-size, multi-resolution signature that separates sign pattern, magnitude scale, quantization frame, and coarse-to-fine direction. Exact integer quantization, bounded portable arithmetic, nested resolution fields, and versioned records provide reproducible results across heterogeneous platforms without floating-point arithmetic, training, dynamic allocation, or per-stream model state. Under a common pinned frame and the declared lossless coarse capacity, participating devices or streams can be correlated by exact tuple equality, while a graded comparison ladder supports finer similarity evaluation. The technique explicitly identifies capacity limits, collision regimes, frame-compatibility requirements, reverse quantization bounds, …

Theta-Xd: Integer-Only Direction Change And Slow-Drift Detection In Multivariate Telemetry Streams, Nenad Micic

Defensive Publications Series

A system is proposed herein for detecting sudden turns, changes in turning behavior, and slow drift in the joint movement of multivariate telemetry counters. The system uses an overflow-bounded integer direction metric and an exact division-free threshold gate, requires work linear in the number of counters and fixed-size per-stream state, and produces exactly reproducible results without floating-point arithmetic or model training. Optional discrete direction keys support compact grouping, and peer-relative integer classification identifies outliers among comparable elements. The resulting signals can be generated close to the telemetry source, where independent per-counter thresholds may miss coordinated changes.

Designing High-Resilience Hybrid Metamaterials: A Systems Engineering Specification For Elemental Hybridization, Solitonic Stabilization, And Non-Destructive Process Verification In Artificial Crystal Lattices, Christopher L. Eckes

Defensive Publications Series

Traditional artificial crystal lattices grown via high-mass commercial methods exhibit acute failure modes under extreme operational environments. These loops manifest as high-frequency acoustic micro-cracking along crystal grain boundaries during cyclic load profiles, or structural delamination driven by thermal expansion differentials across thin-film interfaces.

This specification introduces a formalized systems engineering framework for the elemental hybridization of lab-grown crystal substrates—specifically Thin-Film Lithium Niobate (LiNbO₃) and 3D Self-Assembled Inverse Opal Lattices. By strategically infiltrating these substrates with low-weight-fraction Graphene Oxide (GO) nanosheets and Boron Nitride Nano-Tubes (BNNTs), we create hybrid, non-linear metamaterials that isolate, dampen, and redirect destructive kinetic and thermal wave …

Reconfiguring Distribution Networks Using The Aco+Tnc Algorithm, Specifying The Location, Size, And Number Of Added Renewable Energy Sources, Mohammed Falah Hasan, Rana Ali Abttan

Engineering and Technology Journal

Distribution networks face increasing pressure from rising loads and renewable energy integration, making the simultaneous optimization of reconfiguration and distributed generation placement a critical engineering challenge, and conventional single-objective methods are insufficient for simultaneously addressing power losses, voltage profile degradation, and the structural constraints of radial networks. This paper proposes a hybrid framework that combines Ant Colony Optimization with the Truncated Newton Constrained method to jointly solve network reconfiguration alongside the optimal placement, sizing, and type selection of renewable distributed generation—both solar PV and wind—within a single unified model. The approach relies on a four-part weighted objective function covering active …

Fast Discovery Of Motivic Patterns In Symbolic Music Via Lossy Compression, Adam James Wilson

Publications and Research

Generative systems that react to live musicians require rapid analysis of musical data, which rules out deep learning models: they cannot be trained within the time constraints of live performance. But because analysis results are often transformed before use, we are free to reduce the parameters that undergo transformation to a small set of primitive states. We address this coincidence of constraint and opportunity with an algorithm for online discovery of maximal musical motives that achieves speed through lossy compression: the pitch and inter-onset-interval deltas for all pairs of events in a potential motive are reduced to two-bit values, conceptualized …

Educational Policies Committee Agenda September 3, 2026, Utah State University

Educational Policies Committee

• Approval of Minutes
• Subcommittee Reports
• Curriculum Subcommittee
• Academic Standards Subcommittee
• General Education Subcommittee
• Center for Civic Excellence
• Other Business
• Adjourn: 4:00 pm

Curriculum Subcommittee Agenda September 3, 2026, Utah State University

Educational Policies Committee

• Approval of Minutes
• R401 - Program Proposals
• Semester Course Approval Review
• Other Business
• Adjourn: 3:00 pm

Archival Encounters Across The Disciplines: Using Primary Sources In The Classroom, Karen Morse

Faculty Learning Day 2026

Incorporating primary source activities into class sessions can (re)invigorate the classroom while supporting course learning outcomes and critical thinking.  This session will highlight activities and assignments successfully deployed in diverse URI courses.  Encouraging a DIY approach, it will also include an overview of the tools available to assist instructors with classroom integration (including sources of preexisting lessons) as well as guidance on how and where to find the perfect primary source for your class. Resources provided.

2026 September 3 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Visual Arts Teachers’ Perception Of Integrating Visual Arts To Help With Student Core Content Achievement, Amanda Munoz

Walden Dissertations and Doctoral Studies

The problem addressed in this study was that local school districts in Texas do not offer a visual arts-integrated curriculum despite the known academic and social-emotional benefits for K–12 students. The purpose of this basic qualitative study was to explore the perceptions of Texas K–12 visual arts teachers regarding arts integration to enhance core content learning. Grounded in Gardner’s multiple intelligences theory, the research questions focused on teachers' perceptions of arts integration and their recommendations for implementation. Data were collected through semistructured interviews with 10 K–12 visual arts teachers in Texas who had at least 1 year of teaching experience. …

When Winning Got More Than Gold: Hope's Glory Days; How Hope College Built Its Physics Program, Mackenzie Niswonger, Ryan Mccreedy

Archives and Special Collections Quarterly

When Winning Got More Than Gold: Hope's Glory Days

Column: From the Director of Archives and Special Collections

How Hope College Built Its Physics Program

Artificial Intelligence Models For Automated And Semiautomated Analysis And Interpretation Of Clinical Electroencephalography, Sándor Beniczky, Birgit Frauscher, Fábio Nascimento, Shobi Sivathamboo, Catalina Rojas, Michael Sperling, Samden Lhatoo, Philippe Ryvlin, Levin Kuhlmann

Department of Neurology Faculty Papers

Electroencephalography is the most commonly used diagnostic tool for epilepsy. However, interpreting electroencephalograms (EEGs) requires expertise that is not widely available. Advances in digital technology and wearables have enabled large-scale EEG recording, generating vast amounts of data that cannot be managed through traditional visual interpretation by experts. Artificial intelligence (AI) has the potential to augment human expertise and reduce workloads. The application of artificial neural networks in analysing clinical EEG recordings has led to major breakthroughs, bringing AI-based EEG interpretation closer to clinical implementation. In this Review, we summarise the most important research and development results in this field from …

Learning-Based Entanglement Generation For Quantum Routing, Tasdiqul Islam, Rasman Mubtasim Swargo, Md Arifuzzaman

Computer Science Faculty Research & Creative Works

Entanglement generation in long-distance quantum networks is challenging because resources are limited and entanglement swapping is probabilistic. To maximize the rate of successful requests, existing quantum routing algorithms often rely on computationally expensive methods such as Integer Linear Programming (ILP) to determine which links to entangle and use for end-To-end entanglement generation. However, these approaches fail to meet the latency requirements of real-world quantum networks. In this study, we propose a Reinforcement Learning (RL)-based model that determines which links to entangle in each time slot, replacing the slow ILP-based link-selection phase used in prior algorithms. The proposed Deep Q-learning model …

Health-Related Quality-Of-Life Profiles In Adults With Tinnitus, Preeti Pandey, Hansapani Rodrigo, Megan Kruger, Eldré W. Beukes, De Wet Swanepoel, Anu Sharma, Gerhard Andersson, Vinaya Manchaiah

School of Mathematical & Statistical Sciences Faculty Publications

Purpose: The study aimed to characterize the multidimensional burden of tinnitus on health-related quality of life (HRQoL) using the EuroQol 5-Dimension 5-Level (EQ-5D-5L) dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) moving beyond symptom severity alone.

Method: A cross-sectional analysis was conducted using baseline data (N = 428, Mage = 54.9 years, 51.9% female) from several clinical trials examining the efficacy of internet-based cognitive behavioral therapy for tinnitus. Data were collected using a series of online questionnaires including demographic, audiological, and clinical variables. HRQoL was assessed using the EQ-5D-5L profile dimensions.

Results: Participants primarily reported no problems with mobility (76.6%), …

Edge Computing-Enabled Secure Federated Learning For Anomaly Detection In Industrial Iot Sensor Streams, Wijdan Noaman Marzoog Al Mukhtar

AUIQ Technical Engineering Science

The rise of the Industrial IoT (IIoT) will result in a surge of IIoT devices with high-velocity data streams requiring rapid, real-time analysis of these data streams to power predictive maintenance and assure cybersecurity. Centralized cloud-based approaches to anomaly detection are hindered by their inherent latency and privacy issues while independent or stand-alone approaches to edge-based anomaly detection do not have enough data to effectively detect anomalies. This paper presents a federated learning framework to collaboratively develop an anomaly detection model from multiple edge nodes, without sharing the raw sensor data, so that data sovereignty is preserved. Two major contributions …