Digital Commons Network^™

Simulation Culture And Organizational Readiness In Social Work Education: Examining Faculty Perspectives., Kate Whitney

Doctor of Social Work Capstone Projects

Despite the growing emphasis on simulation-based learning (SBL), faculty perceptions of organizational readiness for this approach in social work education remain understudied. This exploratory mixed-methods study examined faculty readiness across two CSWE-accredited programs using the Simulation Culture Organizational Readiness Scale (SCORS) and qualitative open-ended questions (𝑁=21). Findings revealed modest and uneven readiness across both programs, with full-time faculty reporting significantly lower readiness scores than adjunct and part-time faculty. Qualitative data identified critical needs for foundational dialogue on SBL principles, strategic institutional investment, and targeted faculty development. Participants also expressed concerns regarding the pace of adoption and potential conflicts with the …

The Geometry Of Learning Under Ai Delegation, Lingxiao Huang, Nisheeth K. Vishnoi

Cowles Foundation Discussion Papers

As AI systems shift from tools to collaborators, a central question is how the skills of humans relying on them change over time. We study this question mathematically by modeling the joint evolution of human skill and AI delegation as a coupled dynamical system. In our model, delegation adapts to relative performance, while skill improves through use and decays under non-use; crucially, both updates arise from optimizing a single performance metric measuring expected task error. Despite this local alignment, adaptive AI use fundamentally alters the global stability structure of human skill acquisition. Beyond the high-skill equilibrium of human-only learning, the …

Thin Sets Are Not Equally Thin: Minimax Learning Of Submanifold Integrals, Xiaohong Chen, Wayne Yuan Gao

Cowles Foundation Discussion Papers

Many economic parameters are identified by “thin sets” (submanifolds with Lebesgue measure zero) and hence difficult to recover from data in an ambient space. This paper provides a unified theory for estimation and inference of such “thin-set” identified functionals. We show that thin sets are not equally thin: their intrinsic dimensionality m matters in a precise manner. For a nonparametric regression h0 with Hölder smoothness s and d-dimensional covariates in the ambient space, we show that n^{-s/(2s+d−m)} is the minimax optimal rate of estimating linear and nonlinear (e.g., quadratic, upper contour) integrals of h0 on an m-dimensional submanifold (0 ≤ …

Trade, Labor Market Concentration, And Wages, Mayara Felix

Cowles Foundation Discussion Papers

I estimate the effect of trade on local labor market concentration and its implications for wages using employer-employee linked data and tariff shocks from Brazil’s trade liberalization. Trade increased concentration by 7%, an effect driven by firm exit and worker flows to surviving import-competing firms. Increased concentration reduced wage take-home shares—estimated at 50 cents on the dollar pre-shock—enough to offset small wage gains from reallocation, but did not meaningfully reduce wages on net. Most of the wage declines attributed to Brazil’s trade liberalization resulted instead from reductions in the marginal revenue product of labor. Incorporating informality reveals substantial regional heterogeneity.

A Critical Review Of Statistical, Signal Processing And Machine Learning Methods For Continuous And High-Frequency Water Quality Data Improvement, A.T. Badrudeen, D. Sahoo, Calvin Sawyer, Jeremy Pike, R.D. Haramel

Publications

In the digital water world, high-frequency water quality monitoring from sensors is crucial for capturing rapid changes, especially during storm events or discharge fluctuations, in which important signals can occur at sub-hourly intervals. These signals are represented in a time series and can sometimes be irregular, noisy, and prone to missing values or errors due to buried conditions, sediment interference, and signal loss. The fine resolution of reporting also increases the risk of sensor errors and data loss, necessitating effective correction methods to ensure the accuracy and usability of the data. This literature review investigates the current state of time …

Optimizing And Fortifying Ai Software Through The Lens Of Artifact Synthesis, Jieke Shi

Dissertations and Theses Collection (Open Access)

Artificial Intelligence (AI) has transformed the software landscape, ushering in a new era of intelligent systems that increasingly shape our daily lives. This transformation is evident in various domains, including Software Engineering (SE), where Large Language Models (LLMs) support many development tools, and control systems, where self-driving cars and autonomous drones rely on deep learning models for real-time decision-making. These AI systems are collectively referred to as AI software, with the former categorized as AI4SE software (AI for Software Engineering) and the latter as AI4Control software (AI for Control). As AI software becomes central to modern computing infrastructure, its reliability …

Enterprise Digital Transformation: An Analysis Of Value Creation From An Operational Perspective, Weiguo Ling

Dissertations and Theses Collection (Open Access)

Digital transformation has become a critical pathway for the manufacturing sector to break through growth bottlenecks and reshape its core competitiveness. However, in practice, a large number of enterprises are trapped in the transformation paradox of a “discrepancy between perceived consensus and actual outcomes”. The core issue lies in the fact that traditional investment evaluation methods struggle to effectively measure the multi-dimensional value created by digitalization. From the perspective of operational management, this study focuses on the mechanisms and evaluation methods of digital value creation in different manufacturing contexts. A four-dimensional Value Evaluation Framework is proposed, comprise of Value Identification, …

Boosting Agriculture Career Readiness In Stem Through A Virtual Symposium, Suzanna R. Windon, Hosung You, Christina Grozinger, Natalie Boyle, Hongmei Li-Byarlay, Torrence A. Gill, Simon Zebelo

Journal of Youth Development

This study evaluated a recorded virtual career symposium aimed at enhancing STEM in Agriculture and graduate education readiness among students from Minority-Serving Institutions.The evaluation focused on changes in participants’ perceived readiness for STEM careers and graduate education, the relationship between readiness and demographic factors, and participants’ overall experience with the event. Featuring presentations from faculty and alumni, the symposium highlighted career pathways in agriculture and entomology, essential skills, and graduate education opportunities. Participants from five institutions were invited to view the recorded sessions and complete an online survey. Of the 56 responses received, 41 were analyzed. Results indicated that most …

Growing Mathletes: Integrating Growth Mindset, Math, And Sports To Support Youth Learning, Sanlyn Buxner, Erin Turner, Seneca B. Miller, Christina Baze, Ricardo Valerdi

Journal of Youth Development

Through Growing Mathletes, we developed and field-tested informal education activities designed to teach math within the context of baseball in a way that supports youth in developing a growth mindset. We present our development strategy and discuss our implementation with third through eighth graders at five informal learning sites across the United States. Assessment of program success included pre- and post-program surveys and post-program interviews with youth from all five informal education settings. Our findings revealed our strategy to integrate growth mindset concepts with math and baseball lessons led to positive outcomes related to youth mindset and confidence. We present …

Student Mental Health: Screening For Stress, Anxiety And Depression Using Fitbit Data, Rebecca Lopez, Avantika Shrestha, Ml Tlachac, Kevin Hickey, Xingting Guo, Shichao Liu, Elke Rundensteiner

Information Systems and Analytics Department Faculty Conference Proceedings

College students experience many stressors, resulting in high levels of anxiety and depression. Wearable technology provides unobtrusive sensor data that can be used for the early detection of mental illness. However, current research is limited concerning the variety of psychological instruments administered, physiological modalities, and time series parameters. In this research, we collect the Student Mental and Environmental Health (StudentMEH) Fitbit dataset from students at our institution during the pandemic. We assess the ability of predictive machine learning models to screen for depression, anxiety, and stress using different Fitbit modalities. Our findings indicate potential in physiological modalities such as heart …

Law And The Self-Coordinating Market Idea, Sanjukta Paul

Articles

Much of the focus of the live Symposium was on comparing existing scholarship associated with two intellectual communities. I have no objection to that enterprise in the abstract, though I think it is a bit premature where law and political economy (LPE) is concerned and sets up an apples-to-oranges comparison to the decades-old streams of work and thinking in law and economics (L&E). But I would rather use the privilege of the space in this written Symposium to sketch what I believe is the ultimate substantive nub of contestation in this conversation about the core subject matter of “the economy” …

How Agile Became The Design Philosophy Of Ai Fishbowl Under Real-World Constraints, Jad Saad

University Honors Theses

This capstone review examines the development of AI Fishbowl, a public-facing, interactive artificial intelligence system, as a case study in how Agile methods evolve from a project management tool into a design philosophy under real-world constraints. Although the project adopted an Agile workflow early on through a Kanban-style task management approach, the initial system design and architecture were still shaped by a largely plan-first mindset. This created a mismatch between flexible process and rigid design assumptions, which became increasingly apparent as the team moved from high-level architecture into implementation.

A critical turning point occurred when early architectural plans proved difficult …

Does Genetic Testing Influence Outcomes: Early Experience In Melanoma Case Series, Ryan Reyes, George Skenteris, Stella Coker Watson Self Ph.D., Ms, Christine Marie-Gilligan Schammel, Steven D. Trocha

Faculty Publications

Background:

The treatment and prognosis of melanoma have historically been based on histologic stage and Breslow depth; however, due to the increase in surveillance, melanomas are being identified at an earlier stage and lower Breslow depth. Advances in genetic testing, such as Decision Dx®, mean that melanoma diagnostic decisions and prognosis can now be directed by genetics. The purpose of this project was to assess the influence of a Decision Dx® high-grade (Class 2A/B) classification on the treatment of melanoma patients at a regional medical center, particularly those not deemed high risk by conventional classification methods, including Breslow depth and …

A Knowledge Transfer-Based Membrane Evolutionary Algorithm For Solving Large-Scale Sorted Waste Collection Problem With Timeliness, Wenxue Zhang, Boquan Gao, Aldy Gunawan, Yunyun Niu, Jianhua Xiao

Research Collection School Of Computing and Information Systems

The sorted collection of municipal solid waste has emerged as an effective waste management strategy due to varying timeliness requirements across different waste types, giving rise to the critical research challenge of timeliness-based waste collection. While existing algorithms primarily focus on small-scale versions of this problem, solving large-scale timeliness-based waste collection problems remains particularly challenging. To tackle this issue, this paper proposes a knowledge transfer-based membrane evolutionary algorithm. Specifically, the original problem and simplified problem are constructed in different membranes respectively, and the knowledge transfer learning mechanism is incorporated into the membrane evolutionary algorithm, enabling effective information exchange between the …

Codeultrafeedback: An Llm-As-A-Judge Dataset For Aligning Large Language Models To Coding Preferences, Martin Weyssow, Aton Kamanda, Xin Zhou, Houari Sahraoui

Research Collection School Of Computing and Information Systems

Evaluating the alignment of large language models (LLMs) with user-defined coding preferences is a challenging endeavor that requires a deep assessment of LLMs' outputs. Existing methods and benchmarks rely primarily on automated metrics and static analysis tools, which often fail to capture the nuances of user instructions and LLM outputs. To address this gap, we introduce the LLM-as-a-Judge evaluation framework and present CodeUltraFeedback, a comprehensive dataset for assessing and improving LLM alignment with coding preferences. CodeUltraFeedback consists of 10,000 coding instructions, each annotated with four responses generated from a diverse pool of 14 LLMs. These responses are annotated using GPT-3.5 …

Invert Your Prompt: Editing-Aware Diffusion Inversion, Yangyang Xu, Wenqi Shao, Yong Du, Haiming Zhu, Yang Zhou, Jiayuan Xie, Ping Luo, Shengfeng He

Research Collection School Of Computing and Information Systems

Recent advancements in text-guided diffusion models have enabled powerful image manipulation capabilities. However, balancing reconstruction fidelity and editability for real images remains a significant challenge. In this work, we introduce Editing Inversion (EditInv), a novel framework that inverts and edits real images for specific editing tasks by optimizing specific prompt embeddings within the extended  space. By leveraging distinct embeddings across different U-Net layers and time steps, EditInv seamlessly integrates inversion and editing through reciprocal optimization, ensuring both high fidelity and precise editability. This hierarchical editing mechanism classifies tasks into structure, appearance, and global edits, optimizing only those embeddings that are …

Learning To Search For Vehicle Routing With Multiple Time Windows, Kuan Xu, Zhiguang Cao, Chenlong Zheng, Lindong Liu

Research Collection School Of Computing and Information Systems

In this study, we propose a reinforcement learning-based adaptive variable neighborhood search (RL-AVNS) method designed for effectively solving the Vehicle Routing Problem with Multiple Time Windows (VRPMTW). Unlike traditional adaptive approaches that rely solely on historical operator performance, our method integrates a reinforcement learning framework to dynamically select neighborhood operators based on real-time solution states and learned experience. We introduce a fitness metric that quantifies customers’ temporal flexibility to improve the shaking phase, and employ a transformer-based neural policy network to intelligently guide operator selection during the local search. Extensive computational experiments are conducted on realistic scenarios derived from the …

March 2026 News Releases, University Of Montana--Missoula. Office Of University Relations

University of Montana News Releases, 1928, 1956-present

No abstract provided.

Synthesis And Structures Of Ru(Ii)-P-Cymene Sandwich Complexes With Electron-Withdrawing Cyclopentadienyl Ligands, Uttam R. Pokharel, Sean Parkin, John P. Selegue

Chemistry Faculty Publications

A modular synthetic route has been developed to prepare a new series of cationic ruthenium(II) complexes with electron-withdrawing 1,2-diacylcyclopentadienyl ligands. The 2-acyl-6-hydroxyfulvenes were synthesized from cyclopentadienide and acyl chlorides and converted to Tl(I) cyclopentadienyl salts using Tl₂SO₄/KOH. Transmetalation with [Ru(η⁶-p-cymene)(μ-Cl)Cl]₂ followed by PF₆⁻ metathesis gives the complexes [Ru{η⁵-1,2-C₅H₃(CO–R)₂}(η⁶-p-cymene)][PF₆] (R = t-Bu, p-Tol, p-ClC₆H₄, p-IC₆H₄) in moderate to high yields. The new compounds were characterized by NMR and IR spectroscopy; mass spectrometry …

Branded Skateboard Series, Max David Munday

Graphic Communication

This project demonstrates how graphic communication principles can be applied to product branding within the skateboarding industry. By combining research on branding systems, visual communication theory, and production methods with practical design experimentation, this project highlights the importance of balancing creative design decisions with real-world production considerations

Brief Report: Long-Acting Injectable Prep Can Substantially Reduce Hiv Incidence In Los Angeles County: A Simulation Study, Aditya Khanna, Francis Lee, Katrina Schrode, Daniel Sheeler, Anna Hotton, John Schneider, Kayo Fujimoto, Siri Chirumamilla, Ekow Kwa Sey, Nina T Harawa

Faculty, Staff and Student Publications

Background: Although oral pre-exposure prophylaxis (PrEP) has been instrumental in decreasing HIV incidence, its daily dosing regimen poses adherence challenges. Using an agent-based network model informed by empirical data, we simulate the impact of introducing long-acting injectable (LAI) PrEP among young Black men who have sex with men (YBMSM) in Los Angeles County, a group disproportionately affected by HIV.

Setting: Computer simulations using an agent-based network model.

Methods: We modeled HIV transmission among YBMSM over 10 years under scenarios varying the proportion of PrEP users opting for LAI instead of oral medications and adherence levels to LAI retention. The model …

A Unified Methodological Framework For Generating Digital Twins Of Multi Class Uncrewed Systems (Uxs), Sai Raghava Pathuri

Shelby Hall Graduate Research Forum Presentations

No abstract provided.

Detecting Bitstream-Level Fpga Trojans With An Snn, Kylie Arnett

Shelby Hall Graduate Research Forum Presentations

Limited research has been conducted on SNNs for FPGA Trojan detection. FPGA design is often handled by manufacturers outside the U.S. FPGA manufactures outsource production to third-party foundries. This multi-step process introduces security vulnerabilities and increases risk of Hardware Trojan insertion.

Key Questions: To what extent can an FPGA be manipulated at the bitstream level to enable or disable encryption algorithms?

Can SNNs accurately detect the presence of Trojans within an FPGA?

A Scalable Iteration Of The Horizon Simulation Framework Using Multithreading Techniques, Jason E. Beals

Master's Theses

The Horizon Simulation Framework (HSF) occupies a unique space in the modern aerospace modeling landscape, enabling flexible, modular modeling of mission-level agent behavior through an object-oriented, hierarchical design. HSF's hallmark breadth-first search scheduling algorithm explores a "multiverse" of possible mission execution pathways, enabling exhaustive evaluation of schedule combinations against user-defined heuristics.

As aerospace systems become increasingly complex, HSF faces critical challenges in establishing verifiable, deterministic behavior. The framework's core scheduling algorithm had not undergone systematic validation, leaving questions about temporal consistency, state management correctness, and reproducibility across different program executions. Furthermore, the exponential growth of schedule combinations creates computational bottlenecks …

Early Behavioral And Cognitive Changes In Patients With Pathologically Confirmed Alzheimer Disease, Lewy Body Dementia, And Mixed Dementia, Ming Wang, Hongke Wu, Aaron Bonner-Jackson, Yiming Chen, Wen Tang, Hao Feng, Lijun Zhang, Chixiang Chen, James B Leverenz, Jagan A Pillai

Faculty, Staff and Student Publications

Background and objectives: Alzheimer's disease pathology (ADP) and Lewy body pathology (LBP) are traditionally associated with distinct cognitive profiles. However, growing evidence highlights the role of behavioral and psychological symptoms of dementia (BPSD) in shaping clinical presentations. The combined influence of cognitive and behavioral symptoms across neuropathologically confirmed ADP, LBP, and mixed AD-LBP has not been systematically examined. This study aimed to identify clinically meaningful subtypes by jointly analyzing cognitive performance and BPSD profiles in individuals with autopsy-confirmed dementia pathology.

Methods: This retrospective longitudinal cohort study used data from the National Alzheimer Coordinating Center (NACC), collected across multiple U.S. Alzheimer's …

Molecular Lung Imaging Following Exposure To Radiation Predicts Long-Term Survival In Rats, Anne V. Clough, Kathrina Mpala, Taheri Pardis, Laura Norwood Toro, Andreas M. Beyer, Tracy Gasperetti, Ming Zhao, Sarah Kerns, Heather A. Himburg, Said H. Audi

Mathematical and Statistical Science Faculty Research and Publications

Delayed effects of acute radiation exposure (DEARE), including radiation pneumonitis (lung-DEARE), develop weeks to months after radiation exposure. Pathway-targeted biomarkers that capture early oxidative stress and cell death could improve risk stratification and provide objective measures of mitigator efficacy. The objective was to test whether molecular lung imaging predicts long-term survival and mitigator response after irradiation. Rats received 13.5 Gy leg-out partial-body irradiation with a subset treated with the radiation-injury mitigator lisinopril. Rats underwent lung imaging at weeks 2 and 4 post-irradiation with ^99mTc-duramycin (cell death) and ^99mTc-HMPAO (oxidative stress). Plasma mitochondrial damage-associated molecular patterns (mtDAMPs) were also …

Identification Of Microplastics And Additives From The Lake Erie Watershed And The Cuyahoga River Via Maldi-Ms And Dart-Ms, Chrys Wesdemiotis, Calum Bochenek, Luciana Rivera Molina, Robert Brand

University Research

Micro(nano)plastics have received increased attention as environmental contaminants due to their harmful effects on ecosystems and human health. Conventional extraction methods for microplastic analysis are often lengthy and complicated, resulting in the loss of important chemical components such as additives. In this study, we provide a complementary approach, utilizing matrix-assisted laser desorption/ionization (MALDI) and direct analysis in real time (DART) mass spectrometry (MS) techniques, with minimal extraction and sample preparation to preserve both polymer and additive information. MALDI-MS was applied to aqueous samples collected along the shores of Lake Erie and the Cuyahoga River, successfully identifying the base polymer(s) in …

The Application, Construction, And Validation Of Hidden Markov Model Profiles For Carbonic Anhydrase Enzymes, Samuel F. Kaplan

Master's Theses

Carbonic anhydrases (CAs) catalyze the reversible hydration of CO2 and have evolved independently at least eight times, resulting in structurally distinct enzyme families (α, β, γ, δ, ζ, η, θ, ι). Traditional sequence alignment methods struggle to classify these convergently evolved proteins because their sequential similarity does not reliably indicate functional or evolutionary relationships. Many CA sequences in public databases are annotated generically without family assignments, and prior computational approaches have focused predominantly on the three well characterized families (α, β, γ), leaving the five recently discovered classes without robust classification tools. Family level assignment is often a prerequisite for …

Demystifying Hardware Formal Verification For Undergraduate Education: A Risc-V Processor Case Study With Coursework Implementation, Riley A. Peters

Master's Theses

Hardware verification engineers apply formal methods to prove that a digital device always behaves according to its specification. This differs from traditional functional verification, in which engineers establish correctness by repeatedly sending test inputs to the device and comparing the outputs against a reference model. With the growing complexity of integrated circuits, the demand for digital verification engineers with formal methods experience has continued to increase. However, California Polytechnic State University: San Luis Obispo's current curriculum lacks dedicated material to prepare students for these roles.

This thesis seeks to address the lack of formal methods material through two efforts. First, …

Covering Spaces, Mapping Class Groups And Heegaard Splittings, Tri Tran

Master's Theses

One studies the symmetries of an algebraic object by looking at its automorphism group. For example, the automorphism group of a regular n-gon is generated by rotations and reflections, and the automorphism group of {1,...,n} is generated by transpositions. We study the group of symmetries of a closed, oriented 2- and 3-dimensional manifold M, called the mapping class group of M. In the 2-dimensional case, it is known explicitly what the generators of the mapping class group are. We present a proof of this fact following Farb and Margalit's exposition. The question about the mapping …