Digital Commons Network^™

Expanded Scorpionate And Siderophore-Inspired Ligands: From Foundational Designs To Modern Applications, Austin Winfield Medley, Trandon Allen Bender

Chemistry & Biochemistry Faculty Publications

Scorpionate ligands have been advanced significantly through systematic modifications of their apical atoms and heterocyclic arms, expanding their structural diversity and chemical reactivity. Recent biologically inspired variants now enable accurate modeling of complex bioinorganic motifs, such as the Fe₄S₄ clusters of nitrogenase, and support enzyme‐like reactivity under mild aqueous conditions. These developments have broadened the impact of scorpionate chemistry across bioinorganic modeling, homogeneous catalysis, and biorthogonal transformations. In particular, expanded tripodal scaffolds provide modular, tunable platforms for mimicking enzyme active sites and probing biological nitrogen fixation pathways. Beyond fundamental insight, these ligands present practical opportunities for sustainable catalysis by enabling …

Investigating The In Vitro Antimicrobial Potential And Comprehensive Computational Studies Of New Schiff Base Derivatives, Abrar Hussain, Shahzaib Akhter, Hammad Nasir, Khurram Shahzad, Muhammad Arfan, Sand Hyun Park

Chemistry & Biochemistry Faculty Publications

Antimicrobial resistance (AMR) is a growing global health threat driven by multidrug-resistant bacteria (Staphylococcus aureus, Pseudomonas aeruginosa), and fungi (Candida albicans, and C. parapsilosis). This study evaluated six novel Schiff base derivatives (HSB-1 to HSB-6) through integrated in vitro antimicrobial activity and comprehensive computational studies. In vitro disk diffusion assay demonstrated the largest zones of inhibition against S. aureus for HSB-6 and HSB-1 (15–17 mm), activity against P. aeruginosa for HSB-5 and HSB-6 (12 mm), and moderate antifungal activity for HSB-4 (8–11 mm). Molecular docking results correlated with the in vitro findings with the binding energy ΔG = −12.3 kcal/mol …

The Role Of Education In Reducing Social Inequality: A Systems-Level Analysis Of Socio-Technical Infrastructures And Policy Governance, Aisling O'Shea, Batzorig Dashnyam, Ximena Quintanilla

Women's & Gender Studies Faculty Publications

Social inequality remains one of the most persistent challenges to global systemic stability, threatening the robustness of democratic institutions and economic sustainability. Education has long been theorized as the primary mechanism for social mobility and the mitigation of disparate life outcomes; however, its role within modern socio-technical infrastructures is increasingly complex and often contradictory. This paper provides a comprehensive systems-level analysis of the relationship between educational architecture and social stratification. By examining the structural trade-offs inherent in contemporary pedagogical deployment, the research evaluates how institutional governance, digital infrastructure, and policy mandates either facilitate or hinder the reduction of inequality. The …

Investigating The Connection Between Als Through The Mutation R522s In The Rna Binding Protein, Dennia Estrella-Vargas, Lydia Uptain

Mathematics

Amyotrophic lateral sclerosis (ALS) is a fatal disease that causes the deterioration of motor neurons , death is usually due to respiratory paralysis. The variant R522S was chosen because it is near a hot spot of pathogenic variants. It is an arginine-to-serine swap, this swap is present in pathogenic variants near the 522 position, such as R514S, R521S, R524S. Recent evidence suggests that arginine-deficiency can influence disease progression.

Ordo Ab Chao: Crystallographic Disorder As A Window Into Ionic Liquid Structure, Joseph Cooper, Marija Scheuren, Lara I. Teodoro, Christopher M. Butch, Raychell A. Jerdo, Kylie M. Allen, Mariana E. Toner, Matthias Zeller, Arsalan Mirjafari, Patrick C. Hillesheim

Faculty Publications – Chemistry

Despite being intended to resist crystallization, ionic liquids (ILs) quite frequently form solids, albeit with low melting points. The design motifs that lower melting points can leave measurable signatures in the solid state, manifesting as crystallographic disorder, and often give rise to metastable liquid states. While sometimes treated as experimental complications, such features provide a valuable window into the structural origins of IL phase behavior. Herein, we report a crystallographic study of a series of benzylated ILs that crystallize either directly or from long-lived supercooled melts. Single-crystal X-ray diffraction, supported by computational modeling and statistical analyses, provides structural evidence that …

Managing Multi-Drug Resistance: An Evolutionary Game Theory And Optimal Control Approach, Shukhrat Nasrulloev

Theses and Dissertations

Multi-drug resistance is an evolutionary process in which treatment eliminates sensitive cells, allowing resistant clones to dominate. This thesis investigates this process using a framework integrating population dynamics, evolutionary game theory, and optimal control theory. We develop a two-population logistic growth model describing competition between drug-sensitive and drug-resistant cells under treatment, construct dose-dependent payoff matrices and replicator dynamics to characterize evolutionary competition, and derive a critical drug level D_crit = (r_S - rR)/(dS - d_R) at which resistant cells gain a fitness advantage. An optimal control problem is formulated via Pontryagin's Maximum Principle to identify schedules …

Learning Design To Advance Human-Ai Collaboration In K-12 Education, Wing Sha Chan, Jinhee Kim, Seongryeong Yu, Rita Kay Detrick

STEMPS Faculty Publications

This chapter explores key components for designing effective Human-AI Collaboration (HAC) in K–12 education, addressing the current lack of theoretical and conceptual frameworks for structuring and implementing HAC in teaching and learning. It examines four essential areas: curriculum design, student and teacher–AI interaction, learning environments, and the evolution of HAC over time. The chapter introduces the concept of HAC in K–12 contexts, highlighting how humans and AI can leverage each other's strengths through co-evolutionary processes that foster mutual learning and collaboration. It reviews current HAC practices in schools and discusses their contributions to both teaching and learning. Finally, it presents …

Decomposing Shadow Prices Under Climate-Driven Growth Scenarios: Insights From An Elk Herd Case Study, Ranjit Bawa, Drew Bennett, Wai Yan Siu, Bailey Kirkland, David Finnoff, Jacob Hochard

ODU Articles

Natural capital accounting provides a framework for integrating ecological processes with economic valuation, but the mechanics of shadow price formation often remain opaque to resource managers and policymakers. Using the Clarks Fork elk herd in northwestern Wyoming as a case study, we decompose the shadow price of natural capital into its ecological, economic, and institutional components. Population dynamics are estimated using a linearized Ricker model and projected forward using a logistic projection, incorporating climate-driven reductions in intrinsic growth rates. These ecological scenarios are linked to a shadow pricing formulation that explicitly accounts for marginal benefits, harvest policy responses, discounting, and …

Wearable Sensor-Based Phase Segmentation Analysis Of Front Crawl Swimming: A Scoping Review, Jonathan Simoes, Samuel Aylward, Daniel Hamze, Daniel James Goble, Daniel M. Russell, Joshua Haworth

Exercise Science Faculty Publications

Front crawl swimming stroke phase segmentation has historically relied on video analysis, but the development of wearable sensor technology has created new opportunities for automated phase segmentation. This scoping review mapped the available evidence on wearable sensor-based stroke phase segmentation methods in front crawl swimming, following PRISMA-ScR guidelines. A systematic search of SPORTDiscus, Web of Science, and IEEE Xplore conducted from January to June 2026, identified 15 eligible peer-reviewed studies published between 2000 and 2024. The review revealed an emerging field of research that has converged methodologically around inertial measurement units (IMUs) and the Chollet phase segmentation framework while remaining …

Scope Of Microbial Transglutaminase For Site-Specific And Oriented Immobilization Of Native Antibodies From Various Host Species, Emily Beitello, Kwame Osei, Faith E. Breausche, Jon A. Friesen, Jeremy D. Driskell

Faculty Publications – Chemistry

Modification of antibodies to chemically couple labels or immobilization reagents is essential for developing biosensors. Typically, conjugation occurs through chemical methods that leverage reactive amines and thiols on native antibodies; however, this nonspecific approach can interfere with antibody function. Microbial transglutaminase (mTG) is an enzyme that has been used for site-specific conjugation of chemical modifiers to the F_c region of native antibodies, but thus far mTG-mediated conjugation has been limited to production of antibody-drug conjugates with human IgGs. Here, we assessed the scope and versatility of mTG to target IgGs, with the goal of site-specific conjugation to facilitate oriented …

Data Improved Models Applied To Essential Oceanographic Processes In Rhode Island Coastal Waters, Ainsley Fruhwirth

Open Access Master's Theses

The Ocean State Ocean Model (OSOM), funded and developed through the National Science Foundation’s (NSF) Established Program to Stimulate Competitive Research (EPSCoR), was designed to simulate the physical dynamics of Rhode Island’s estuaries and shelf waters. However, the model struggled to capture key features of summer circulation in Rhode Island Sound (RIS), most notably the westward flowing coastal current and vertical stratification profile found in May through September. Significant errors in modeled lateral and vertical density gradients indicated that the thermohaline structure, physical mixing parameters, and forcing inputs required comprehensive revision. Using historical datasets from the National Oceanic and Atmospheric …

A Specification-Driven Framework For Self-Supervised Learning In Specialized Vision Domains, Mahmut S. Gokmen

Theses and Dissertations--Computer Science

Self-supervised learning (SSL) has emerged as a principled approach to visual representation learning that derives supervisory signal directly from unlabeled data, enabling foundation models to be trained at scale without manual annotation. Deployments in medical imaging and biometric recognition have demonstrated the potential of this paradigm, yet the assumptions that make SSL effective on natural image benchmarks fail systematically in specialized domains. Generic SSL pipelines encode a tacit assumption that the most informative correspondence is spatial proximity within a single acquisition. In specialized domains this assumption breaks at the level of the data-generating process: the signal that carries domain-specific information …

Using Camera-Based Unmarked Spatial Capture-Recapture Modeling To Estimate Reintroduced Elk (Cervus Canadensis) Population Parameters And Distribution In Southeastern Kentucky, Claire Marie Muia

Theses and Dissertations--Forestry and Natural Resources

Estimation of population parameters is important for wildlife management decisions. Elk reintroduced to southeastern Kentucky experienced early irruptive population growth and are currently monitored using a statewide harvest-based statistical population reconstruction model (SPR) across the Kentucky Elk Restoration Zone (KERZ). Because the SPR model is spatially coarse and difficult to scale to the smaller management units comprising the KERZ, we conducted a spatially explicit capture-recapture study using a clustered camera-trapping array deployed for 10 weeks from June–August 2024 to estimate elk population parameters within Management Unit 4. Due to a lack of resights of GPS-marked elk, population parameters were estimated …

Iere Annual Report 2026, Erin Largo-Wight, Heather Barnes Truelove, Kelly Rhoden, Jessica Barnes, Lauren Canady, Nicole Lowe, Ruby Cox, Sydney Barrett, Kathleen Hutton

Annual Reports

2026 Annual Report of the Institute for Environmental Research and Education

Counseling Professionals' Perspectives On Ai Integration In Education And Supervision: A Concept Mapping Study, Hank Crofford, Elif Bor, Gülşah Kemer

Counseling & Human Services Faculty Publications

The rapid emergence of artificial intelligence (AI) has raised important questions about how new technologies will shape professional norms and practices in counseling. The purpose of this study was to understand how counseling professionals expect AI to be integrated into counselor education and supervision (CES). Using a mixed‐methods concept mapping design, 31 participants generated and sorted statements about the potential roles, benefits, and concerns associated with AI in the profession. Participants represented diverse counseling roles, including counselor educators, licensed professional counselors, supervisors, master's‐ and doctoral‐level trainees, and other counseling‐related professionals. Standard concept mapping procedures were conducted using R, resulting in …

Memoryart: Enhancing Llms Via Multi-Memory Models With Adaptive Resonance Theory For Healthcare Agents, Renke Dai, Hebin Hu, Jiahui Zhang, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Though promising in healthcare consultation applications, large language models (LLMs) face critical limitations in retaining and utilizing long-term memory across multiturn interactions. In particular, existing memory enhancing paradigms are constrained by limited context windows and embedding-based retrieval, often failing to maintain task relevance and still suffering from memory prototype collapse in multi-turn healthcare consultation. To address these challenges, we propose a cognitively-inspired memory framework named MemoryART, which is grounded in Adaptive Resonance Theory (ART)—a cognitive and learning theory of how humans and animals adapt to dynamic environments. MemoryART employs three memory modules—working memory, episodic memory, and semantic memory to support …

Clique Annealing: Semi-Supervised Community Detection Under Crystallization Kinetics, Ling Cheng, Jiashu Pu, Ruicheng Liang, Qian Shao, Hezhe Qiao, Feida Zhu

Research Collection School Of Computing and Information Systems

Semi-supervised community detection seeks to find a specified community type when only few communities are labeled. Existing "select-then-refine" pipelines often start from mis-aligned cores and rely on Reinforcement-Learning or Generative Adversarial Network, increasing computational cost and limiting scalability. We address these issues with a unified energy framework under crystallization kinetics that jointly models energy, structure, and growth. Based on this perspective, we propose CLique ANNealing (CLANN), which first employs Nucleus Proposer to select candidate clique as community core under four physics-inspired criteria. A learning-free Transitive Annealer then iteratively merges neighboring cliques and repositions the nucleus, enabling spontaneous, scalable community growth. …

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 …

Impact Of Environmental Microparticles On Insect Olfaction, Steve B.S. Baleba, Danube K.N. Wandji, Yves H. Tchiechoua, Komi Mensah Agboka, Iman B. Hassaballa, Victor O. Omondi, Beatrice T. Nganso, Saliou Niassy, Souleymane Diallo, Merid N. Getahun

All Peer-Reviewed Publications

Terrestrial insects underpin key ecosystem services, including pollination, herbivory regulation, decomposition, nutrient cycling, and disease control. These functions depend on chemical communication that guides insects to food, mates, hosts, shelters, and oviposition sites while helping them avoid threats. Environmental microparticles, such as micro- and nanoplastics, tyre wear particles, soot, mineral dust, and agricultural residues, are now widespread across air, soil, vegetation, and indoor environments, exposing insects through contact, deposition, and ingestion. Growing evidence shows that these particles disrupt insect olfaction by adsorbing volatile compounds, blocking antennal sensilla, and interfering with receptor and neuronal processes. These disruptions impair foraging, mating, oviposition, …

Machine Learning For Predicting Prosthetic Limb Movements, Jessica Alexandra Cegarra Arraiz

Theses and Dissertations

This thesis develops and evaluates a deep learning-based prediction model capable of identifying intended limb movement from surfaced electromyography (sEMG) signals using sequence learning techniques. sEMG signals change over time due to multiple factors such as muscle fatigue or user variability. Traditional prosthetics control methods rely on static feature extraction, ignoring how signals change over time, thereby limiting their ability to capture the temporal changes of muscle activity. As a result, these approaches often lead to poor accuracy, robustness, and generalization. Limited experimental validation has been conducted on sequence-based machine learning approaches using temporal sEMG data from publicly available datasets …

Legal Ethics Of Ai Snake Oil: Navigating The Hype, Harm, And Hope Of Legal Ai, Drew Simshaw

Scholarly Works

This paper argues that the legal ethics of AI extend far beyond competence and hallucinations. It shows how AI often functions as a mirror, exposing deeper ethical questions about institutional incentives, lawyer wellbeing, access to justice, and AI's broader social and environmental impacts.

Impacts Of Management Practices And Soil Properties On Free-Living Nitrogen Fixation In Eastern South Dakota, Laura Galvan Nuevo

Electronic Theses and Dissertations

Free-living nitrogen (N) fixation (FLNF) may represent a sustainable pathway to supplement crop N demand in agroecosystems, yet edaphic and management factors regulating this process under field conditions remain poorly understood in the Northern Great Plains. Using 15N2 direct method to quantify potential FLNF (pFLNF) and baseline FLNF (bFLNF), this thesis investigates how crop rotations (2-, 3-, and 4-year systems), tillage management (conventional vs. no-till), cover cropping, and soil properties affect the potential of free-living diazotrophs to supply N via FLNF in a long-term no-till corn-based system in Southeastern South Dakota. A two-year field study evaluated pFLNF across four growing …

Ai Vs. Genai: Combating Llm Generated Prescription Fraud With Transformer Based Detection Models, Ankitha Vokkaleri Shankarappa

Selected Full-Text Master Theses 2021-

The rapid evolution of Large Language Models (LLMs) has introduced a sophisticated new vector for healthcare fraud: the generation of high-fidelity, synthetic medical prescriptions. Traditional fraud detection systems, which rely on rule-based engines and basic statistical anomalies, are increasingly ill-equipped to identify these AI-generated forgeries that mimic the structural and clinical logic of authentic records. This thesis presents a robust detection framework using Transformer-based architectures to distinguish between human-authored Medicare Part D prescriptions and fully synthetic records generated by GPT-4.

The research was conducted across two distinct phases: an initial pilot study using 4,000 samples and a rigorous validation stress …

Erosion Of Trust In Online Information, Tirth Desai

A with Honors Projects

Researching how AI spreads misinformation and impacts trust in information.

Collaboration And Co-Management Ahead Of Permitting: Understanding How Actors And Their Interactions Lead To Non-Optimal Shoreline Projects, Juita-Elena (Wie) Yusuf, Mariana Saitgalina, Michelle Covi

School of Public Service Faculty Publications

Living shorelines are widely promoted as nature-based solutions to coastal erosion and wetland protection, yet hardened shoreline structures continue to dominate even in jurisdictions with explicit policy mandates prioritizing living shorelines. In this research, we examine why non-optimal shoreline modification outcomes persist in Virginia (USA) despite a regulatory framework designed to promote ecological alternatives. We use primary data from interviews with wetlands board members, marine contractors, and nonprofit organizations and findings from a secondary survey of shoreline property owners to analyze shoreline management as a multi-sector collaborative decision-making process. Findings show that shoreline outcomes are shaped less by individual regulatory …

Fixed Dune Grassland Mapping, Ronica Reyes, Madison Mayenschein, Jared Cruz

Environmental Science & Management Senior Capstones

Our  study applies Geographic Information Systems (GIS) and field-based data collection to map and assess a degraded fixed dune grassland parcel in Humboldt County, CA. Our project supports restoration planning led by Friends of the Dunes by identifying site features, habitat composition, and disturbance patterns at the site. Using GPS surveys, aerial imagery, and ArcGIS Pro, we mapped infrastructure, cement footprints, debris piles, vegetation types, and habitat boundaries. We mapped infrastructure such as concrete foundations and debris, which contribute to ongoing ecological degradation and the presence of invasive species. In addition, our spatial analysis highlights variability in disturbance. From this …

Healing Our Life Source: Riparian Eco-Cultural Restoration In Blue Lake Rancheria At School Creek, A Tributary Of Baduwa't In Northern California, Rae Mcgrath, Lily Moore, Keneti Jesus Pinones, Colin Rogers, Aberdeen Spade

Environmental Science & Management Senior Capstones

School Creek, a tributary in the Baduwa’t (mad river) Watershed, is a riparian corridor that is key habitat for Coho Salmon. This project is under the management of the Blue Lake Rancheria, located on the ancestral home of the Wiyot people, and was conducted by cal poly humboldt students. The restoration of School Creek is an ongoing project aimed at repairing the health of the riparian corridor, improving the creek’s channel structure, and creating a diverse community of culturally significant plant species. Previous restoration efforts have established plantings to further develop the riparian habitat and are surveyed within this report. …

Vegetation Management Plan And Wildlife Enhancement Project For The Woodley Island Wildlife Area, Sophie Belle Shapero, Brandon Carl Bauch, Moises Ortiz, Angelina Espinoza

Environmental Science & Management Senior Capstones

The Woodley Island Vegetation Management Plan and Wildlife Enhancement Project was created by Cal Poly Humboldt students in partnership with the Humboldt Bay Harbor Recreation and Conservation District as a capstone senior project. This project provides a basic management plan for invasive species and offers suggestions for how to enhance the wildlife areas on the island. The goals of the project are to provide maps of the habitat types within the wildlife reserves, map areas of concern to be targeted for invasive species removal, and provide guidelines for how to increase habitat diversity, wildlife forage, and decrease invasive species presence. …

Woody Ryno Farms Native Prairie Plant Restoration & Invasive Management Conservation Management Report, Jezebel Kenny, Rowan Haeger, Ian Mendonca, Annika Weihl

Environmental Science & Management Senior Capstones

Coastal prairies are biodiverse and sensitive landscapes that support a variety of grassland species in mediterranean climates. Hedgerows may act as a natural barrier for coastal prairies or agricultural regions, aiding in natural protection and support for biodiversity. Humboldt County, California, hosts a number of agricultural regions, including Woody Ryno Farms, a small-scale agricultural operation, on the edge of Dows Prairie near the coast of Mckinleyville. This project aims to continue restoration activity being conducted on the site, helping to increase native biodiversity and agricultural productivity. Project objectives include conducting a plant assessment, applying treatments to individual plants where necessary, …

Hydrodynamic Tipping Points In The Mississippi Sound In Response To Bonnet Carré Spillway Openings, Mustafa Kemal Cambazoglu, Brandy N. Armstrong, Mohsena Lopa, Marc Diard, Jerry D. Wiggert

Faculty Publications

This project examines the current operational strategy of the Bonnet Carré Spillway (BCS), a Mississippi River flood-control structure located about 21 miles northwest of New Orleans, Louisiana, and managed by the U.S. Army Corps of Engineers. The BCS is part of the larger Mississippi River and Tributaries Project, a network of levees and control structures designed to minimize flooding from the American plains to southern Louisiana. The spillway is opened when river discharge at New Orleans is forecasted to exceed 1,250,000 cubic feet per second, diverting significant volumes of Mississippi River water into Lake Pontchartrain which subsequently flows into Mississippi …