Digital Commons Network^™

From Assessment To Action: Evaluating Support Components In Accelerated Induction To Teaching Programs For Enhanced Candidate Satisfaction And Program Improvement, Traci Catto, Kelli Moransais

Graduate Student Dissertations, Theses, Capstones, and Portfolios

The transition from preservice teacher preparation to full-time teaching represents one of the most critical and vulnerable periods in an educator's career, with research consistently demonstrating that nearly half of all teachers leave the profession within their first five years. Alternative certification pathways have emerged nationwide to address persistent teacher shortages, yet the quality and intensity of support embedded within these pathways, rather than the pathway type itself, most strongly predicts teacher retention and effectiveness. The Accelerated Induction to Teaching (AIT) program at an R1 University in Florida places teacher preparation candidates into unfilled teaching positions as teachers of record …

Two Unh Students Earn Goldwater Scholarships, Brooks Payette

UNH Today Archive

No abstract provided.

Machine Learning Based Models For Simulation And Analysis Of Bulk Earth Melt System, Abin Shakya

LSU Doctoral Dissertations

Understanding the segregation of bulk Earth melt systems into metallic (core) and silicate (mantle) phases under high-pressure and high-temperature conditions is central to modeling Earth’s interior, yet relevant experimental and computational studies remain limited. This work develops a machine learning–based simulation pipeline that iteratively couples first-principles (quantum mechanical) calculations with neural network training to generate high-fidelity force fields. Using major-element Fe–Mg–Si–O melt systems, with and without H and N, as testbeds, we demonstrate that this framework enables large-scale molecular dynamics simulations at near first-principles accuracy. We further introduce a sequence of phase identification methods, progressing from statistical binning of elemental …

Differentials As Models: Constructing A Differentials-Within-Limits Framework For First-Year Calculus And Examining Students' Understanding Of Limits, Differentials, And Derivatives Within It, Alexander A. Swindler

Theses and Dissertations

Work in first-year calculus has clearly shown the power that treating differentials (such as dx) as tiny quantities affords for first-year calculus learning, yet a traditional limits-based approach leaves no room for them. While some researchers have loosely described informal differentials and limits within the same paradigm, their actual conceptual definitions and relationships have not been explicitly constructed. Continued progress in this area could benefit from theoretical consideration of (a) providing clearer intuitive definitions for differentials inside a limits-based approach to calculus, and (b) defining more exactly the relationships between differentials and limits. In this study, I propose a theoretical …

Evaluating Fine-Scale Air-Quality Heterogeneity Using A Low-Cost Multipollutant Sensor Network In Twin Cities, Minnesota, Varuni Abhayaratne, Weixing Hao, Chen Ye, Anjana Yatawara, Philip K. Hopke, Jiayu Li, Yang Wang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

There is growing interest and effort in deploying low-cost sensors (LCSs) to understand fine-scale spatiotemporal heterogeneity of ambient air pollutants in urban areas. The Assessing Urban Air Quality project conducted by the Minnesota Pollution Control Agency deployed 45 low-cost air-quality monitors (AQMesh, Environmental Instruments Ltd.) in the Minneapolis/St. Paul metropolitan area network. Hourly averaged pollutant concentrations or mixing ratios for carbon monoxide (CO), ozone (O₃), nitrogen dioxide (NO₂), nitric oxide (NO), and sulfur dioxide (SO2), as well as particulate matter (PM), including PM1, PM2.5, and PM10, were obtained. The network data from June 2019 to June …

Back Matter

Caroliniana Undergraduate Research Journal

This is the Back Matter for Vol. 1, Iss. 1: "The Blueprint" in the Caroliniana Undergraduate Research Journal. The Back Matter includes the following sections:  The Editorial Board, About the Authors, and the Back Cover of the issue. Here you can find more about the contributors that made this issue possible.

Cover And Contents

Turkish Journal of Physics

No abstract provided.

Butte Priority Soils Operable Unit (Bpsou) 2026 Monthly Progress Report. Consent Decree For The Butte Priority Soils Operable Unit. Civil Action No. Cv 89-039-Bu-Seh, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Advice For Incorporating Ai Tools Into Your Legal Practice, Celia Bigoness, Robert A. Mackenzie, David J. Reiss

Cornell Law Faculty Publications

We have been speaking with many lawyers and law students about using generative artificial intelligence (AI) tools in their legal practice. We are struck by the fact that many of them have not been experimenting much, if at all, with the tools that are available to them - although many acknowledge that their clients are increasingly integrating generative AI into their businesses. We have been integrating a lot of these tools into our own professional lives, and here are some tips to help lawyers and law students get comfortable with AI tools that can help them, in big ways and …

Convergence Education In A Stem-Focused University: An Ethnographic Study Of A Cross-College Design And Innovation Program, Greg J. Strimel, Sherylyn Briller, Jackson Otto, Rebecca Martinez, Douglas Pruim, Todd R. Kelley

School of Engineering Technology Faculty Publications

Background

Innovation often transcends the bounds of individual disciplines, yet undergraduate teaching is still largely organized today within single disciplines and respective academic units. Convergence education offers a promising organizational approach to bring transdisciplinary teaching and learning into undergraduate education by aligning institutional structures, pedagogy, and partnerships around meaningful, innovation experiences to address contemporary problems. However, longstanding academic silos in higher education hinder the adoption of convergence-focused pedagogies. Therefore, this study examined the three-year implementation of a novel convergence education initiative developed to foster design and innovation capabilities across multiple academic disciplines. By integrating faculty from the university’s engineering technology, …

Motivation Without Borders: Applying The Octalysis Framework To Global Faculty And Student Engagement In Ai Era, Harika Rao

Faculty and Staff Publications & Presentations

No abstract provided.

Educational Transformation Through Aligning With Oman Vision 2040, Rabie A. Ramadan

Journal of Arts and Social Sciences

This paper investigates the role of Artificial Intelligence (AI) in revolutionizing the education sector under the Oman 2040 vision. The vision aspires to economic sustainability, and education is a cornerstone for achieving this vision. The paper evaluates the present landscape of AI in Oman's educational system, exploring the current initiatives and how AI can be extended in education and be part of its practices. Based on the nature of the study, the methodology employed involves a comprehensive review of available literature and internet resources related to AI applications in education globally and within Oman. This secondary research approach allows for …

Modelling The Temporal Dynamics Of Microsporidia Mb Prevalence In Anopheles Mosquitoes Under Environmental Variability, Charlène N. Mfangnia, Matteo Pedercini, Henri E. Tonnang, Jeremy K. Herren

All Peer-Reviewed Publications

Releasing Microsporidia MB-positive mosquitoes is being investigated as a promising component of Integrated Vector Management (IVM) strategies for malaria control. In this study, we developed a System Dynamics model to replicate the observed interactions between humans, mosquitoes, the Plasmodium parasite, and the symbiont MB. The model accounts for the impact of environmental variables - such as humidity, rainfall, and temperature - on mosquitoes, Plasmodium, and MB, using exogenous inputs derived from daily climatic observations (rainfall, relative humidity, and temperature) recorded during the mosquito field surveys. We calibrate the model using data collected from Ahero in Kenya, available for 3 years …

“That Would Be Confusing For Fifth Graders”: Boundary Infrastructure Moves In A Research-Practice Partnerships, Jody E. Clarke-Midura, Alireza Zandi, Saríah López-Fierro, Mimi M. Recker

Publications

Research Practice Partnerships (RPPs) are a key strategy for educational improvement, yet little is known about the interactional mechanisms that drive their success. This study analyzes a three-year RPP co-designing integrated math and computer science lessons. We identify "boundary infrastructure moves”, actions partners use to navigate differences. Our findings reveal that productive tension, often sparked by a "potential overstep," was highly generative. A case study shows how a teacher challenging a lesson's terminology initiated a negotiation that transformed the artifact and created a new, shared vocabulary tool. We argue that productive tension is an essential mechanism for growth in RPPs …

Applications Of Machine Learning In Enhancing Evaporation Estimation For Small Reservoirs: A Case Study In Semi-Arid South Texas, Syed Muhammad F Abdullah, Chu-Lin Cheng, Jude A. Benavides, Jungseok Ho, Rafael M. Almeida

School of Earth, Environmental, & Marine Sciences Faculty Publications

Small reservoirs in semi-arid regions experience substantial evaporative losses but are rarely monitored at daily scales. A multi-reservoir machine learning (ML) framework was developed to estimate daily open-water evaporation. Empirical models (Penman, Penman-Monteith, Priestley-Taylor, Bowen Ratio Energy Budget) andabenchmark combination method (Daily Lake Evaporation Model-DLEM) were compared against ML models. Predictors combined gridded meteorology (gridMET) with reservoir attributes (surface area, average depth, maximum depth, and fetch). ML models (Random Forest-RF, Decision Tree-DT, K-Nearest Neighbor-KNN, and Support Vector Regression-SVR) were trained on four reservoirs using data from 2018 to 2025. Results from ML models were further validated using both DLEM and …

Spatiotemporal Dynamics Of Daily And Per Capita Vmt In California: A County-Level Analysis (2019–2023), Yong Lao, Bo Yang

Mineta Transportation Institute

Vehicle miles traveled (VMT) is a fundamental metric for assessing mobility trends and infrastructure needs. This study examines the spatial-temporal dynamics of daily VMT (DVMT) and per capita DVMT across California counties from 2019 to 2023, covering the pre-, mid-, and post-pandemic periods via GIS mapping and k-means clustering. To identify determinants of per capita DVMT, we compared traditional linear regression approaches (OLS, Ridge, LASSO, Elastic Net) with ensemble tree-based models. Specific results include: the ensemble models estimated using 2019–2022 data delivered substantially higher accuracy, achieving R² values exceeding 0.98; meanwhile, out-of-sample performance on 2023 data remained robust (R² ≈ …

Diffeomorphisms In Quantum Black Hole Interiors, Ian William Bornhoeft

Electronic Theses and Dissertations 2020 - Present

We begin with an introduction to canonical Loop Quantum Gravity. We then introduce a notion of residual diffeomorphism covariance in quantum Kantowski–Sachs (KS), describing the interior of a Schwarzschild black hole. We solve for the family of Hamiltonian constraint operators satisfying an associated covariance condition, as well as parity invariance, preservation of the Bohr Hilbert space of Loop Quantum KS and a correct (naive) classical limit. We further explore imposing minimality of the number of momentum shift terms, and compare the solution with other Hamiltonian constraints proposed for Loop Quantum KS in the literature. In particular, we discuss a lapse …

Fort Hays State University Tiger Weekly, April 10, 2026, University Relations

Tiger Weekly Newsletters

No abstract provided.

A Tv-Bm3d Iterative Algorithm For Vmat-Ct Reconstruction, Chia-Lung Chien, Beibei Guo, Rui Zhang

Faculty, Staff and Students Publications

Volumetric modulated arc therapy-computed tomography (VMAT-CT), which is the CT reconstructed using the portal images collected during VMAT, can potentially be an effective onsite imaging tool. The goal of this study was to propose an iterative reconstruction algorithm that can further improve the image quality of VMAT-CT and reduce the number of failed reconstructions. An iterative algorithm combining total variation (TV) with block-matching and 3D filtering (BM3D) was proposed, addressing the L1-L2 regularization problem using the split Bregman method. We collected portal images from 67 VMAT cases including 50 phantom and 17 real-patient cases. Both Feldkamp-Davis-Kress (FDK) and TV-BM3D iterative …

An Equity Analysis Of Battery Electric Vehicles During Evacuation Considering Social And Financial Disadvantage, Divyamitra Mishra

USF Tampa Graduate Theses and Dissertations

The increasing share of battery electric vehicles (BEVs) in the transportation system is introducing new challenges to the emergency evacuation planning and management. During Hurricane Milton (2024), incidents involving BEVs, including battery fires, attributed to saltwater exposure risk, and advisories recommending relocation to higher ground, highlighted operational vulnerabilities unique to this technology. These emerging risks are likely to be experienced heterogeneously, as access to charging infrastructure, available resources, and evacuation flexibility varies across the population. This raises critical questions about how BEV-specific constraints interact with existing inequalities during evacuation. Motivated by this context, the dissertation investigated inequity in BEV evacuation …

Transport Of Quantum Walks In Electric Fields, Yousef Mohammad Yousef Salah

Thesis/ Dissertation Defenses

This thesis presents an analysis of transport in one-dimensional discrete-time quantum walks (DTQWs) on the Hilbert space . Quantum walks serve as fundamental models of coherent quantum transport and exhibit ballistic spreading driven by superposition and interference. The primary focus of this work is the review and derivation of sharp maximal velocity bounds for several classes of quantum walk step operators, including the shift-coin walk, the split-step walk, and models with constant as well as position-dependent coin operators. We establish general a priori bounds that remain valid beyond the translation-invariant regime. For homogeneous models, Fourier and spectral analysis yield explicit …

Humanizing Engineering For Preservice Elementary Teachers Through Sustainable Engineering Stories, Jeffrey D. Radloff, Madison M. Morris, Jacob Pleasants

Journal of Pre-College Engineering Education Research (J-PEER)

Meeting the goals of US K–12 science education reform requires that preservice elementary teachers (PSTs) understand engineering as a specialized discipline and a human endeavor that addresses real-world issues. Yet in their formal education, few PSTs receive opportunities to learn about the humanistic dimensions of engineering: engineers’ personal values and motivations, the sociocultural nature of engineering work, and the societal significance of engineering. Storytelling about engineering offers a practical way to give PSTs access to these ideas. This study examines the impacts of integrating storytelling about engineering in a science methods course for future elementary school teachers. Over a two-year …

A Comprehensive Survey Of Agentic Ai: Design Principles, Security Risks, And Ethical Consideration, Md Shaba Sayeed

ATU Scholars Symposium

In the past several years, the world has managed to transition away from simple automation to independent AI systems. Agentic AI is an agent that can work independently, carrying out all essential plans and implementations without any kind of supervision from a human being. This review has tried to demonstrate the transformative impact that Agentic AI brings to contemporary models of intelligence by means of synthesis of perception, reasoning, and goal. We utilized the phrases Agentic AI, autonomous AI, multi agent systems as keywords in Google Scholar, ScienceDirect, arXiv, and other digital libraries. We have used these 38 main papers …

Dermal: A Multi-Input Deep Learning Model For Improving Access To Dermatological Screening, Aubreye Freeman

ATU Scholars Symposium

According to the World Health Organization's press release on December 12, 2024, global healthcare spending is dropping significantly, leaving a large percentage of the world without proper healthcare. In an attempt to alleviate this problem, with respect to the field of dermatology, we created a deep learning model, Dermatology Enhanced by Recognition and Machine Aided Learning (DERMAL), to assist in diagnosing skin conditions. DERMAL was trained on a portion of the Google and Stanford Medicine's SCIN dataset, which has more than 10,000 images of various skin conditions. The 9 most common skin conditions of the dataset were selected as the …

Computational Approaches To Laser Alignment And Phase Correction, Joseph E. Temple

ATU Scholars Symposium

The goal of our work is to automate the tedious and delicate process of optical alignment (rotating mirrors, shifting lenses by millimeters, and iterating endlessly) in the context of generating vortex beams from a Gaussian laser beam. We create vortex beams by illuminating a digital hologram displayed on a spatial light modulator (SLM). Two main issues arise: misalignment and phase imperfections in the input beam. If the beam does not pass directly through the center of the SLM, or if it deviates from an ideal Gaussian profile, the resulting vortex beam becomes distorted.

Last semester, we developed two methods to …

Creating A Floating Volumetric Display, Joy Skaggs, Hope Skinner

ATU Scholars Symposium

The public has long been interested in futuristic technology, especially ‘holograms’ and their possibilities, evidenced by pop culture icons such as Iron Man and the popularity of the Sci-Fi Genre. The popular term ‘hologram’ actually describes the phenomenon of a volumetric display, where light is directed to form 3D forms in the air. Attempts to create these volumetric displays began as early as 1988 with creators like Gregg Favelora and Alan Sullivan. As technology improved, so too did the ability to make the futuristic ‘hologram’ a reality.

Another common form of these interactive holograms is the floating display, which may …

Data Structures & Algorithms Prep Hub: A Technical Interview Preparation Tracker, Andrew J. Pinkerton

ATU Scholars Symposium

This project examined how consistent practice with data structures and algorithms (DSA) can improve problem solving skills and preparation for software engineering technical interviews. The goal was to strengthen foundational algorithmic knowledge while developing a structured practice routine that could continue beyond the semester. From week 3 through week 12, four LeetCode style problems were completed each week, focusing on core interview topics including string manipulation, arrays, linked lists, hash tables, sets, and dynamic programming. Each problem required implementing a solution, identifying edge cases, and evaluating time and space complexity to determine the most efficient approach. Through this process, common …

Investigating The Effect Of Kcl Stress In Raphanus Sativus, Mason P. Oelke

ATU Scholars Symposium

Presented by Stephanie Nelms at the Arkansas INBRE Conference on November 7-8, 2025.

Presented by Mason Oelke at Arkansas Tech Scholar's Symposium on April 9th, 2026.

Potassium is an essential macronutrient for plant growth and development, yet excessive potassium fertilization can induce salt stress with detrimental consequences for crop productivity and nutritional quality. Despite its agricultural relevance, potassium chloride induced stress remains significantly understudied compared to classical sodium-based salinity. This thesis investigates the physiological, biochemical, and molecular responses of Raphanus sativus to KCl stress using an integrated approach that combines germination assays, mineral profiling, and gene expression analysis.

Radish seeds …

Interacting Dark Energy Models And The Cosmic Coincidence Problem, Gunner W. Hodges

ATU Scholars Symposium

Cosmological models are a tool used to understand the mysterious nature of dark energy and dark matter by predicting how these dark sector components have shaped the expansion of the universe. The cosmic coincidence problem stems from the present day densities of dark energy and matter sharing very similar magnitudes when previously we expect a much larger difference in orders of magnitude. The current best-fit model, ΛCDM , assumes dark energy is non-interacting; however, assuming that dark energy instead does interact could serve to alleviate this cosmic tension. We define an interaction where we relate the density of dark energy …

Prediction Of Future Mushroom Fruiting Success And Dispersion Based On Models Of Changing Surface Air Temperature In Oaxaca, Mexico, Frida Martinez

ATU Scholars Symposium

Mushrooms serve various purposes, including medicinal, culinary, and cultural significance for indigenous groups, as well as recreational and ecosystem services. Oaxaca, Mexico, is a hotspot for mushroom biodiversity including the following varieties: Amanita muscaria, Schizophyllum commune and Coprinellus disseminates. The purpose of this study is to determine if a changing Mean Surface Air Temperature will have an influence on these mushrooms. We obtained, analyzed, and compared historical and future climate data from the World Bank Group Climate Change Knowledge Portal to identify if any of the mushroom species would be impacted. The study revealed a general trend of warming Mean …