Digital Commons Network^™

Remote Sensing Of Particulate Organic Carbon And Phytoplankton Carbon In The Northern South China Sea, Xiaoju Pan, Tung-Yuan Ho, George T. F. Wong, Jen-Hua Tai, Lijuan Nie

OES Faculty Publications

Surface concentrations of particulate organic carbon (POC) and phytoplankton carbon (C_phy) in the northern South China Sea (NSCS) have been assessed successfully by remote sensing with appropriate regional tuning. Match-up comparisons between satellite derivations and field observations showed uncertainties of ± 28.5% for POC and ± 37.0% for C_phy. The satellite-derived climatological distributions are consistent with previous reports. In the open NSCS where phytoplankton growth is controlled primarily by the convective overturn, both POC and C_phy are higher in winter, associating with the effect of stronger northeast monsoons and surface cooling, than in summer, when …

Is Prosocial Behavior A Unique Correlate Of Academic Success In Emerging Adulthood?, Jacqueline Di Biase

Theses and Dissertations (Comprehensive)

Prior developmental research has frequently linked prosocial behavior to stronger academic functioning during childhood and adolescence (Cruz et al., 2024; Gerbino et al., 2018; Oberle et al., 2022), yet its relevance to academic success in emerging adulthood remains unclear. Guided by a Positive Youth Development (PYD) framework, the present study sought to address gaps in emerging adulthood research by examining the academic relevance of prosocial behavior while accounting for influential developmental assets and testing its independent contribution to academic achievement. Undergraduate students (N = 501) completed a cross-sectional self-report survey assessing prosocial behavior, self-control, dutifulness, sociability, and cumulative grade …

Children's Peer Selection In Stem: The Influence Of Gender, Ethnicity, And Disability, Meagan Girard, Kim P. Roberts

Theses and Dissertations (Comprehensive)

The present study examined how children’s peer selection in STEM (science, technology, engineering, and mathematics) may be influenced by gender, ethnicity, and physical disability. Sixty-four children (ages 6-12) from elementary schools in Southwestern Ontario completed three tasks: a simulated peer selection task, an attribution of ability task, and a stereotype belief questionnaire. In the peer selection task, participants were repeatedly asked to select one peer from a set of AI-generated photographs showing children who differed by gender (male, female), ethnicity (White, Black, East Asian), and physical disability status (able-bodied user vs. nondisabled). The Peer Selection Task was based on the …

The Impact Of Student Achievement On Economic Growth: A Pisa-Based Analysis Of Gdp Per Capita, Emma Rose Nasr

Undergraduate Theses and Capstone Projects

This study investigates the extent to which international student achievement, measured through PISA assessments in mathematics, reading, and science, explains cross-country differences in economic development. Using an unbalanced panel data set combining PISA results from 2015, 2018, and 2022 with macroeconomic indicators from the World Development Indicators, I estimate multiple regression models, including pooled OLS, country and time fixed effects, and subsample analyses for developed and developing countries. Results from the pooled model indicate strong positive associations between PISA scores and GDP per capita, consistent with human capital theory. However, these relationships diminish under fixed effects specifications, suggesting that cross-country …

Triangulating Primary Sources, Professional Judgement, And Llm-Generated Summaries: Educating Nurses In An Ai-First World, Sarah Oerther, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Environmental Engineers Develop Solutions To Problems Of Planetary Health: The Legacy Of Professor P. Aarne Vesilind, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The principal ethical obligation of the engineering profession, to "hold paramount the health, safety, and welfare of the public," has been challenged for decades. Professor P. Aarne Vesilind identified two primary deficiencies: an anthropocentric bias that values nature only instrumentally and the use of non-mandatory, aspirational language for environmental protection, which resulted in the exclusion of enforceable environmental canons. This paper argues that two recent developments provide a comprehensive response to Vesilind's recommendations for engineering ethics. First, the United States Bureau of Labor Statistics has redefined environmental engineering as "developing solutions to problems of planetary health." Second, Oerther proposed a …

A Transdisciplinary Approach To Advancing Water Security And Public Health: The “Nurse + Engineer” Model For Achieving Sustainability In Wash Systems Using Community-Based Participatory Research, Daniel B. Oerther, Sarah Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Human health is linked to the health of the environment, a concept referred to as planetary health. As environmental challenges become increasingly complex, single-disciplinary approaches are insufficient to achieve sustainable solutions. This article presents a transdisciplinary framework, termed the "Nurse + Engineer" model, as a novel methodology for addressing complex problems at the nexus of environmental engineering and public health. The model integrates the technical design and systems-level thinking of environmental engineering with the community-based, patient-centered care of nursing. This work details the key lessons learned from the retrospective application of this framework to a series of multi-year, community-based participatory …

Swimming In Uncertainty: Filling Data Gaps And Providing An Educational Platform For Beach Water Quality At Tybee Island, Georgia, Lukas Roberson

College of Graduate Studies: Theses & Dissertations

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Swimming in beaches water contaminated with high levels of bacteria can make you sick. Current monitoring at the public beaches on Tybee Island consists of weekly monitoring and enumeration of fecal indicator bacteria that takes 24 hours for results. If the number of bacteria exceed regulatory limits, a public health advisory is issued, and affected waters are retested until …

Emotion Regulation: The Effectiveness Of Reappraisal And Potential Benefit Of Music, Ezra J. Greidinger

College of Graduate Studies: Theses & Dissertations

Literature has supported potential benefits to cognitive reappraisal as a method of emotion regulation, as well as intentional music usage as an enhancer of these effects. It has been suggested that instruction be provided to individuals to use these methods, especially in highly stressed populations (Sakka et al., 2018). However, there has not been an experimental study to follow up on these claims. When instruction is provided, is cognitive reappraisal more effective than naturally developed habits in regulating anxiety, and would music enhance these effects? College students (N = 170) were randomly assigned to three treatment conditions: control, cognitive reappraisal, …

Workshop Outcomes Report: 2nd International Workshop On Seismic Resilience Of Arctic Infrastructure And Social Systems, Majid Ghayoomi, Daniela Morganti

Faculty Publications

The report provides an overview of the second international workshop on Seismic Resilience of Arctic Infrastructure and Social Systems. The report discusses agenda, workshop activities, interdisciplinary working groups, and results. It ends with several strategic questions and investigation plans that were developed as part of the workshop activities.

Gaze Transition Entropy And Automation Trust In Multitasking Workspace, Yusuke Yamani, Austin Jackson, Tetsuya Sato, Feyishola Ashimi, Michael S. Politowicz, Eric T. Chancey, Makoto Itoh

Psychology Faculty Publications

Safe flight operation requires visual scanning across multiple displays in a cockpit, which collectively represent the state of the aircraft and supporting automation. Trust is a crucial factor that drives human-automation interaction, and recent work has suggested a relationship between an operator's visual attention and automation trust. One index that captures predictability of eye movements between different areas of interest is gaze transition entropy. The current work reanalyzed data from Sato et al., which examined eye movement patterns and trust in automation associated with the system monitoring task of the Multi-Attribute Task Battery. Results showed credible positive correlations between the …

Can An Experienced Qualitative Researcher Distinguish Ai From Human Qualitative Content Analysis?, Alexandra T. Lucas, Jianna Ramos, Maria Bajwa, Aaron Calhoun, Mark W. Scerbo, Janice C. Palaganas

Psychology Faculty Publications

Background

Artificial intelligence (AI) has become increasingly embedded in research workflows. Large language models (LLMs) are being used to code segments of text, organise codes into themes and interpret patterns within contexts. Recent comparisons between human and AI analyses demonstrate up to 80% thematic overlap, yet humans consistently exhibit deeper interpretive integration and contextual understanding. This study assesses whether experienced researchers can distinguish between entirely human-generated and AI-generated qualitative content analyses of a simulation debriefing.

Methods

We conducted a qualitative descriptive study comparing human-generated qualitative content analysis (QCA) with ChatGPT-4o-generated QCA using a single focus group transcript on emotion management …

A Real-Time Examination And Comparison Of Differentiation Among Suicidal Thinking And Affect Items In An Adolescent Sample, Elizabeth A. Edershile, Kinjal K. Patel, Annabelle M. Mournet, Richard T. Liu, Catherine R. Glenn, Evan M. Kleiman

Psychology Faculty Publications

Suicide risk assessments require individuals to differentiate among types of suicidal thoughts (e.g., passive vs. active); yet most research relies on aggregate metrics that obscure this differentiation. Indeed, more severe forms of suicidal thinking are thought to involve the simultaneous experience of multiple forms of thoughts at high intensities. The present study draws on concepts from the affect differentiation literature to (a) examine different ways to operationalize differentiation in suicidal thinking and (b) compare differentiation in suicidal thinking with differentiation in affect. Adolescents (N = 200) recently hospitalized for suicidal thoughts and behaviors completed a 28-day ecological momentary assessment …

Ranked Choice Voting At The State And Local Level, Khel Gordhan

Res Publica - Journal of Undergraduate Research

Many people across the political spectrum are frustrated with many of the problems that come with simple plurality voting, also known as first-past-the-post, which is implemented in the lion’s share of elections across the United States. To solve many of these problems, some activists and other political organizations advocate for cities and states to adopt Ranked Choice Voting (RCV) as a viable alternative. However, many people, both Republicans and Democrats, claim that implementing this system would be too complicated for people to understand. Due to this, there would be high rates of ballot exhaustion, which would disenfranchise vulnerable minorities who …

Michigan Academician Volume 50, Issue 2

Michigan Academician

Volume 50, Issue 2 - Abstract Issue

Robust Linking Estimation In Item Response Theory Using Quantile Regression: Applications To The Graded Response And Generalized Partial Credit Models, Ibrahim Almansour

Graduate Studies Theses and Dissertations 2026

This dissertation investigates robust estimation of linking coefficients in Item Response Theory (IRT) using quantile regression and its extensions. Linking procedures are essential for placing item and ability parameters from different test forms onto a common scale, thereby ensuring comparability of examinee scores across administrations. Traditional approaches such as moment methods, characteristic curve methods, and mean-based regression procedures like Ordinary Least Squares (OLS) and Generalized Least Squares (GLS) perform adequately under ideal conditions but tend to lose accuracy when ability distributions deviate from normality or include outliers.

To address these limitations, this research proposes a quantile-based regression framework that estimates …

Drafting Policy To Address Academic Integrity: The Other Ai In Education, Elizabeth Burns

STEMPS Faculty Publications

The article focuses on the role of school librarians in drafting policies to address academic integrity amid the increasing use of artificial intelligence (AI) in K-12 education. It defines AI, including generative AI (GenAI), and discusses both the challenges and opportunities AI presents for teaching and learning, emphasizing the need for clear guidelines on ethical use. The article outlines three common AI policy models—permissive, hybrid, and restrictive—and stresses the importance of collaboration between librarians and teachers to establish consistent expectations, promote critical thinking, and ensure proper attribution of AI-generated content. School librarians are positioned as key facilitators in guiding students …

Multiple Changepoint Detection For Non-Gaussian Time Series, Robert Lund, Thomas J. Fisher, Norou Diawara, Michael Wehner

Mathematics & Statistics Faculty Publications

This article combines methods from existing techniques to identify multiple changepoints in non‐Gaussian autocorrelated time series. A transformation is used to convert a Gaussian series into a non‐Gaussian series, enabling penalized likelihood methods to handle non‐Gaussian scenarios. When the marginal distribution of the data is continuous, the methods essentially reduce to the change of variables formula for probability densities. When the marginal distribution is count‐oriented, Hermite expansions and particle filtering techniques are used to quantify the scenario. Simulations demonstrating the efficacy of the methods are given and two data sets are analyzed: 1) the proportion of home runs hit by …

From Screens To Stress: Public Health Implications Of Cancer Worry In A Digitally Connected World, Shreya Mathur, Ethan Burns, Michael Pokojovy, Tzu-Liang Bill Tseng, Sunil Mathur

Mathematics & Statistics Faculty Publications

Aims:

This study examines how digital information environments, genetic testing experiences, health behaviors, and psychological distress influence cancer-related worry among adults in the United States. It further considers the public health implications of elevated or reduced cancer worry for prevention and risk communication.

Methods:

Data were drawn from a nationally representative survey of 6,252 U.S. adults. Measures included reliance on social media for health decision-making, smoking status, history of genetic testing, and psychological distress. Multivariable analyses assessed associations between these factors and levels of cancer worry.

Results/Findings:

Reliance on social media for health decisions was associated with greater cancer worry, …

Conceptualizing A Model For Transforming Academic Search With Retrieval-Augmented Generation, Nikesh Narayanan

All Works

This study conceptualizes the transformative potential of RetrievalAugmented Generation (RAG) in academic research, addressing limitations of traditional search methods reliant on keyword matching, Boolean logic, and metadata analysis. RAG combines precise data retrieval with the generative capabilities of advanced AI models, synthesizing dispersed information into coherent outputs. By bridging retrieval accuracy and contextual generation, RAG offers a framework for providing researchers with comprehensive, nuanced, and up-todate insights tailored to their queries. This article explores the integration of tools like ChatGPT and LangChain to outline a RAGbased system, illustrating its potential to enhance academic discovery by harmonizing natural language processing, semantic …

Mapping Multiclass-Targeted Hate Speech In Online Discourse: An Open Dataset, Sanaa Kaddoura, Sumaia Al-Kohlani

All Works

Online social networks have become central spaces for public discourse, where hostile and discriminatory language toward social groups can cause psychological and social consequences for marginalized communities. Although multiple public hate speech datasets are available, many rely on binary categorization practices that obscure linguistic, cultural, and contextual variation across targeted groups. As a result, minority and less visible forms of hate speech remain insufficiently documented and analyzed. This discussion paper examines methodological limitations in existing hate speech annotation schemes and presents a re-annotation framework applied to the HatEval2019 dataset. The proposed framework introduces target-specific multiclass labels that distinguish subcategories of …

Preoperative Patient Sentiment Is Associated With Postoperative Outcomes In Adult Spinal Deformity Surgery, Ross J. Gore, David Mazur-Hart, Mohan K. Sunkara, Aaqib Ali, Qizar Ali, Christopher J. Lynch, Christopher Ames

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Study Design: Prospective observational pilot study of adult spinal deformity surgery patients.

Objective: To determine whether preoperative patient sentiment, quantified using a 21-class valence scale extending the CARP paradigm implemented through an offline Large Language Model, predicts postoperative outcomes.

Summary of Background Data: Predicting adult spinal deformity surgery outcomes remains challenging with traditional clinical and radiographic parameters alone. Although patient psychological factors and expectations significantly influence postoperative satisfaction and quality of life, systematic approaches to capture these factors are underdeveloped. Offline Large Language Models offer scalable, privacy-preserving psychological risk stratification.

Materials and Methods: We prospectively enrolled 18 patients undergoing adult …

Adaptive Boundary-Aware Fact-Checker Placement For Misinformation Suppression In Social Networks, Mostafa Taghizade Firouzjaee, Ghazal Naderi, Ross Gore, Neda Moghim

School of Cybersecurity Faculty Publications

The spread of fake news on online social networks is driven by imitation-based user behavior and network topology, often leading to persistent misinformation clusters and echo chambers. In this study, we develop a spatial evolutionary game-theoretic framework in which agents update their latent opinions through payoff-biased imitation, while external fact-checkers act as non-imitative intervention nodes. Building on this formulation, we propose an adaptive, boundary-aware intervention mechanism that dynamically regulates both the density and spatial allocation of fact-checkers according to real-time system conditions. Competing information clusters are identified through local neighborhood composition, enabling boundary nodes, i.e., interfaces between fake-news and non-fake-news …

Cybersecurity Center For Offshore Wind Energy (Final Project Round), Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models …

Mapping Robusta Coffee (Coffea Canephora) Cropping Systems In Uganda: A Two-Step Pixel And Sub-Pixel Based Approach With Sentinel-2 Data, Getachew Kebede, Bester Tawona Mudereri, Onisimo Mutanga, Tobias Landmann, John Odindi, Natacha Motisi, Fabrice Pinard, Henri E.Z. Tonnang, Elfatih M. Abdel-Rahman

All Peer-Reviewed Publications

Coffee is a highly valued commodity and a widely consumed beverage, playing an important role in global trade. However, coffee farming landscapes are increasing transitioning into smaller-scale agricultural setups. This transformation highlights the critical need for accurate classification and mapping of coffee cropping systems (CS), especially in countries like Uganda, where dense vegetation and complex terrain present substantial challenges to traditional land survey methods. Moreover, understanding the spatial distribution of Robusta coffee (Coffea canephora) CS is essential for developing site-specific management strategies, guiding extension services, and informing evidence-based policy decisions. To address this gap, the present study aimed to enhance …

Subjective Glib Dynamics: Using An Alien Society To Investigate Reactions To Leader And Member Norm Deviance, Catie Burtch

Cal Poly Humboldt theses and projects

Social groups are built by members and leaders who form consensus on the defining attributes of their groups. Individual group members look to senior members and leaders to learn what it means to be a member of that group. Thus, norm maintenance is an important aspect of group health. The subjective group dynamics model details the specific group contexts under which people derogate ingroup members for transgressing norms. However, ingroup leaders are treated differently from regular group members and are given leniency for their transgressions. The current research extends these two bodies of work by directly comparing the consequences of …

Examining Inclusive Computing Education For Blind Students In India, Akshay Kolgar Nayak, Yash Prakash, Md Javedul Ferdous, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

The growing demand for computer professionals, driven by the expanding Information Technology industry, has led to numerous inclusive computing education efforts. These efforts have even included blind or visually-impaired (BVI) students, who are being increasingly encouraged to pursue education and a career in computing, despite the visually-oriented nature of the discipline. Extant literature has predominantly focused on identifying and addressing the accessibility barriers faced by BVI students to promote more inclusive learning environments. While few studies have also investigated the accessibility of computing education from the perspectives of BVI learners and instructors, these have been primarily situated in the Global …

An Explainable Transformer Framework For Sentiment Analysis In Aviation Workforce Data, Sovon Chakraborty, Protiva Das, Fahmid Al Farid, Fuyad Hasan Bhoyan, Farig Yousuf Sadeque, Jia Uddin, Hezerul Abdul Karim

Computer Science Faculty Publications

Aviation is one of the predominant sectors that contribute significantly to the global economy. With the advent of technology, this industry is witnessing a paradigm shift towards data-driven approaches. The morale of the airline employees is barely noticed, which causes fatigue and depression. Furthermore, these mental health issues can be active reasons for destructive accidents. In this research, the authors are focused on collecting insightful information on aviation employees from Glassdoor.com. Moreover, the authors focus on analyzing the sentiments of the employees of renowned aviation companies. Primarily, the authors scraped necessary data from Glassdoor.com and created a dataset named JetJobJoy …

Towards Supporting Real-Time Estimation Of Vehicle Fuel Consumption And Co2 Emissions In Smart City Applications, Abrar Alali, Stephan Olariu

Computer Science Faculty Publications

This paper evaluates a simplified physics-based energy demand model designed to estimate vehicle fuel consumption and CO₂ emissions—a critical tool for sustainable transportation planning and smart city applications. Unlike data-driven regression models that lack generalizability for user-defined conditions or complex physics-based approaches that rely on extensive, often proprietary data, the simplified model is distinguished by its minimal parameter requirements, depending primarily on a single, overarching powertrain efficiency value. A key contribution is the comprehensive empirical evaluation of the simplified model against official Environmental Protection Agency (EPA) test data across multiple driving cycles and vehicle types, providing a rigorous validation previously …

Biosecure-Llm Framework: Protecting Llms From Cyberbiosecurity Threats And The Case For Independent Ai Safety Governance, Xavier-Lewis Palmer, Lucas Potter, Srdjan Lesaja, Sotirios Karathanasis, Mohammad Ghasemigol

Computer Science Faculty Publications

Large Language Models (LLMs) are becoming critical infrastructure in scientific, healthcare, and governmental contexts. As frontier AI laboratories increasingly partner with government agencies, a fundamental question arises: Who should control the safety and policy-enforcement layers that constrain model behavior? Current safety mechanisms (LLM guardrails) are typically designed for generic "harmlessness" and operate by detecting semantic patterns and refusing requests. However, they are inadequate governance instruments because they cannot implement auditable, domain-specific controls tied to external regulatory policy objects (e.g., control lists or rules governing personally identifying information). Even a perfectly aligned model is not able to express institution-specific policy without …