Digital Commons Network^™

Early Successional Response To Stream Daylighting In Redwood National And State Parks, Orick, California, Rylee Rawson

Cal Poly Humboldt theses and projects

In-channel stream restoration projects can act as both disturbance and recovery mechanisms, disrupting existing conditions to reestablish the hydrologic and ecological processes that sustain stream ecosystems. These interventions initiate successional trajectories in which channel form and biological communities reorganize over time. In Redwood National and State Parks (California, USA), the Redwoods Rising initiative restores buried headwater channels by recontouring legacy logging roads and daylighting streams buried by Humboldt crossings. Using the National Park Service Klamath Network wadable stream monitoring protocol, I evaluated nine restored reaches spanning one to five years post-restoration, alongside old-growth reference reaches and available pre-treatment data. I …

Can Forest Thinning Activities Be Characterized With Public Data?: Evidence From California’S Million Acre Strategy (2020-2023), Selena Rowan

Cal Poly Humboldt theses and projects

Can forest thinning activities be quantitatively described using public data? This study evaluates the feasibility of doing so using geospatial datasets and project-level documentation associated with forest operations tracked under the California Wildfire & Forest Resilience Task Force’s Million Acre Strategy (2020–2023). As fuels reduction efforts expand to address increasing wildfire risk, there is growing demand for detailed information on thinning activity characteristics and associated biomass generation to support management evaluation, biomass utilization, and life-cycle emissions modeling. However, the extent to which existing public data provide sufficient detail to support such analyses remains unclear.

This thesis analyzes forest thinning activities …

Urban Trees In The Urban Hydrology Cycle, Jorge R. Vera

Theses, Dissertations and Capstones

In urban forestry, trees provide numerous economic, ecological, and aesthetic benefits to the surrounding community. One of their key roles is intercepting stormwater runoff, reducing flooding risk, and improving water quality. Chapter 1 of this thesis characterized the ecological and economic contributions of urban trees on the Marshall University campus and provides guidance on their management and conservation in the future. Chapter 2 examined how urban tree species modify the urban hydrology cycle by altering the volume and timing of precipitation delivery. In Chapter 1, we inventoried 114 acres of Marshall University's main campus in Huntington, WV, from June 28 …

Macroinvertebrate Taxonomic And Functional Diversity In The Spokane River Watershed, Kaitlin L. Abell

EWU Masters Thesis Collection

Changes in land use, such as agricultural expansion, have impacted stream systems by modifying discharge, substrate diversity, channel morphology, and nutrient inputs. The Spokane River Watershed is heavily impacted by human activity, including urban and agricultural development. Rehabilitation efforts are being organized to reintroduce Salmonidae species in the Spokane River Watershed. The first step of this reintroduction is to perform habitat studies to inform allocation of restoration efforts. As part of this effort, I performed benthic macroinvertebrate surveys throughout the watershed.

The objective of my research was to use the macroinvertebrate community as a biological indicator to determine which habitat …

Environmental Monitoring Report: For Work To Be Performed: July 1, 2024 Through June 30, 2025, Tennessee. Department Of Environment And Conservation

Environmental Monitoring Reports

This FY2025 EMR presents results for independent projects, originally defined in TDEC’s FY2025 Environmental Monitoring Plan (EMP) and subsequently completed over the course of FY2025 period of performance.

Inferential Statistics For Industrial Organizational Psychologists: A Practical Guide For Testing Hypotheses Using R, Caitlin Lapine

Open Touro Created

2026

This text aims to provide a practical guide for students in industrial organizational psychology or related fields to complete inferential statistics using R open-source programming language. It provides information about when to use particular statistical analyses and how to perform those with statistical software.

Reinterpreting Stochastic Optimal Control Under Ecological Uncertainty: Inferring Decision Urgency From Vegetation Biomass Dynamics, Komi Mensah Agboka, Tobias Landmann, Elfatih M. Abdel-Rahman

All Peer-Reviewed Publications

Stochastic optimal control provides a rigorous framework for systems subject to uncertainty, yet its operational use in ecological crisis contexts remains limited by interpretability. We reinterpreted a stochastic control formulation in which selected parameters emerged as indicators of decision urgency rather than normative preferences. Vegetation biomass was modeled as a stochastic stock subject to nonlinear loss driven by feeding pressure (e.g., desert locust activity) and multiplicative noise, with uncertainty represented by a time-varying volatility term that integrated extreme rainfall anomalies and conflict-related disruption. Rather than prescribing an optimal policy, we inverted the closed-form solution of the control problem to infer …

Fumigant Toxicity Of Essential Oils From Chemotypes Of Curry Tree (Murraya Koenigii) Against Adult African Malaria Mosquito (Anopheles Gambiae Sensu Stricto), Clarence M. Mang’Era, Fathiya M. Khamis, Ahmed Hassanali, Paul O. Mireji

All Peer-Reviewed Publications

The toxicity of fumigant formulations of essential oils (EOs) from curry tree (Murraya koenigii (L.) Spreng (Rutaceae)) against African malaria adult mosquito (Anopheles gambiae sensu stricto (Giles, 1902) (Diptera: Culicidae: Culicini)) was evaluated to identify most effective chemotype of the curry tree against the mosquitoes. Ninety-two compounds (91.78%–96.47% coverage) in the EO profiles were identified, among which EO isolated from curry tree chemotype from Kibwezi was most toxic. This chemotype had a median lethal dose (LD50) of 3.6 × 10⁻³ mg/cm³ (95% CI: 2.70–4.58) and a lethal time (Ti50) of 1.91 ± 0.086 h (p < 0.001). The equivalent LD50 of EOs of chemotypes from Mombasa, Makindu, and Malindi in Kenya was 4.9 × 10⁻³, 6.6 …

Error-Driven Density Control For Compact Gaussian Splatting Under Sparse Supervision, Abdelrhman Elrawy

Theses and Dissertations (Comprehensive)

This thesis studies efficiency and stability challenges in Gaussian-splatting-based reconstruction under sparse supervision. In few-shot novel view synthesis, standard 3D Gaussian Splatting (3DGS) can overfit the limited training views and grow an unnecessarily large number of primitives due to limitations in its Adaptive Density Control (ADC) mechanism. This thesis introduces an error-driven reformulation of ADC that triggers densification using opacity gradients as a lightweight proxy for rendering error, and shows that such aggressive densification must be paired with delayed and conservative pruning to prevent destructive create--destroy cycles. When combined with depth-based geometric regularization, the resulting framework produces substantially more compact …

Investigation Of Mercury Bioaccessibility In Subsistence Fishes From The Canadian Subarctic, Kiran Mateo Sharma Mr

Theses and Dissertations (Comprehensive)

Fish consumption is the primary pathway for human exposure to methylmercury (MeHg), a global contaminant of concern known to cause adverse health effects. Fort Albany First Nation, a remote Indigenous community in northern Ontario that relies on fish for both subsistence and cultural practices, has expressed concern regarding the safety of local fish consumption. Community members and leaders have communicated several priorities for scientific research that are the foundation of this thesis. Specifically, consumers of wild-caught fish have asked how traditional cooking methods may affect mercury concentrations in fish, and how mercury concentrations in little-studied organs, such as liver and …

Sustainable Justice: A Critical Contemplative Approach To Sustainability In Higher Education, Jessica A. Reneau

Antioch University Dissertations & Theses

The field of sustainability studies increasingly asks students to confront ecological crises alongside considerations of power, privilege, and unequal environmental harm. This work can be emotionally challenging as well as intellectually complex. Contemplative practices, such as meditation and yoga, may offer meaningful pedagogical support, helping students cultivate the attention, reflection, and emotional capacity needed to stay engaged with justice-centered sustainability learning. Although the use of contemplative pedagogies is growing in higher education, little research has examined how these practices shape justice-orientated learning outcomes in sustainability education. This dissertation addresses that gap by exploring how both student and instructor experience contemplative …

Improving Human Dimensions Of Conservation Planning: Challenges And Opportunities For Sustainable Conservation Outcomes, Vivian Hulugh

Electronic Theses and Dissertations

Conservation planning is important to ensure both ecological and social benefits of natural resources, including the maintenance of functional ecosystems and stable wildlife populations as well as the provision of resources that communities rely on. Yet, the integration of the human dimensions of conservation planning remains limited in practice. This thesis examines conservation planning in South Dakota and within Joint Venture (JV) partnerships, using qualitative methods to identify challenges and opportunities for more effective and coordinated planning. In chapter one, I examine how collaboration, public participation, and the use of climate information are integrated conservation planning in South Dakota and …

Graph-Based And Graph-Transformer Representation Learning For Healthcare Data, Rui Wang

Electronic Theses & Dissertations (2024 - present)

Healthcare data exhibit complex structures, including heterogeneous clinical entities, sparse observations, and longitudinal patient trajectories. Effectively modeling such data remains a fundamental challenge in computational healthcare research. Traditional machine learning approaches often rely on flat feature representations that fail to capture relationships among clinical events, limiting their ability to model complex healthcare processes. These challenges motivate structured learning frameworks that capture both relational structure and temporal dynamics in healthcare data. This dissertation develops a series of graph-based representation learning approaches, extended through graph-transformer architectures for modeling complex healthcare data. Such data can be represented as graphs, where nodes correspond to …

Preliminary Analysis Of Soil Volatile Organic Compounds As Soil Health Indicators, Thorne Taul

Graduate Theses, Dissertations, and Problem Reports (ETD)

Over the past decade, soil health (SH) has gained popularity due to the novelty of sustainable soil use related to human wellbeing. Soil health describes the overall quality of soil and its capacity to function over time. As interest in SH grows, researchers continue to explore new soil health indicators that can improve knowledge on how soil health is assessed and managed. Some indicators directly reflect soil health status, and some indirectly relate to processes and functions occurring within the soil. Volatile organic compounds (VOCs) are naturally occurring compounds that play a role in multiple soil processes. They are associated …

The Maxima Method For Identification Of Principal Periodic Components In Time Series Analysis, Megan Di Maio

Electronic Theses & Dissertations (2024 - present)

This dissertation investigates methods for mean estimation in periodically correlated time series, focusing on the Variable Bandpass Periodic Block Bootstrap (VBPBB) and a novel data-driven maxima method. Time series require specific methods because of the temporal correlation in the data. Traditional methods like the General Seasonal Block Bootstrap (GSBB) account for this correlation but often produce wide confidence intervals because they cannot isolate multiple periodicities, allowing noise and other frequencies to interfere with analysis. The VBPBB method addresses this by applying a Kolmogorov-Zurbenko Fourier Transform (KZFT) filter to the data before bootstrapping, which suppresses interfering frequencies and results in narrower, …

Remembering Right Relations: A Land-Centered Framework For Settler Teacher Transformation, Aimee E. De Ney

Antioch University Dissertations & Theses

Settler colonialism is based in the separation of peoples from Lands and from one another, producing ongoing harm to human and more-than-human communities as evidenced in climate collapse, racialized violence, war, and widening social inequities. These conditions are sustained by ideologies of human supremacy-specifically white, male, Christian human supremacy-that deny personhood to most humans and to all more-than-humans, while enabling the attempted erasure of Indigenous peoples and the nation-state enforcement of anti-Black and anti-Brown racism. Situated on the Lands of the Coast Salish Peoples in the Pacific Northwest of the United States, this multiparadigmatic innovation dissertation develops a Land-centered framework …

Ai Tips And Traps, Patrick Barry

Books

Based on a series of popular courses and workshops that Professor Patrick Barry has created for students, professionals, and anyone else interested in taking a skills-based approach to artificial intelligence, this book gives you a chance to engage with important AI concepts, experiment with exploratory AI exercises, and then ultimately develop your own customized list of AI traps to try as well as AI traps to avoid.

Agrivoltaics Swot Analysis For Implementation In The United States, Vani Ramesh

UROP Posters

Agrivoltaics is the implementation of solar installations alongside agricultural land in order to improve the efficiency of land usage in both industries. Research in European and Asian countries developing agriculture and solar developments in tandem has indicated that implementation in the United States, including Virginia, is feasible and beneficial. The US has the highest energy use per capita in the world, with the increase of various technologies has resulted in land developments using higher energy levels than previously. While Virginia’s energy demand has increased with the addition of data centers. Increased energy demand and food security requirements have unearthed policy/political …

Llm-Driven Weekly Newsletter To Assess Open Source Software Project Github Health, Christian Novalski, Christopher Chavez, Ghalian Fayyadh, Kostadin Damevski

UROP Posters

Open Source Software (OSS) projects increasingly depend on a diverse set of contributors, including episodic participants who contribute intermittently. Episodic contributors represent a large portion of OSS communities, yet projects often struggle to retain them, leading to decreased project health and continuity. While dashboards and real-time communication tools support continuously active contributors, they often fail to serve the unique needs of episodic participants, who may struggle to remain informed and re-engage with project activity after periods of absence. In this study, we examine the effect of a weekly, email-based newsletter intervention designed to improve awareness and engagement among episodic OSS …

Data-Driven Methodologies For Mapping Cultural Heritage: The Case Of The National Coal Heritage Area, West Virginia, Usa, Hossain Mohammad Nahyan

Graduate Theses, Dissertations, and Problem Reports (ETD)

The objective of this dissertation was to develop a comprehensive, data-driven spatial framework for characterizing the complex cultural landscape of the National Coal Heritage Area (NCHA) in West Virginia. By transitioning away from traditional, heuristic spatial mapping, this research integrates advanced spatial statistics, machine learning, and GIS-based methodologies to objectively quantify the physical, visual, and cultural dimensions of the post-mining environment. The research is structured around three interconnected empirical studies, each addressing a specific scale of the Landscape Character Assessment (LCA) framework to support heritage conservation and sustainable spatial planning. The first paper focused on landform classification, developing an automated …

2024 Annual Operations And Maintenance Report 2024 Bres Annual Summary Report For Work Completed In Quadrant 4, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

First-Generation Medical School Applicants: A Quantitative Study Designed To Identify Areas Of Educational Support, Bethsabe Romero, Amanda K. Burbage

EVMS School of Health Professions Faculty Publications

First-generation (First Gen) students are unique medical school applicants. Due to their lived experience, they approach patient care by prioritizing trust, comfort and understanding. They have proven ability to overcome obstacles and were found to be more resilient than their continuing generation (Cont Gen) peers. Despite these notable attributes, they face unique challenges in gaining medical school acceptance. There are very few quantitative studies examining this student subpopulation, and our study identifies characteristics of first-generation medical school applicants while highlighting areas of needed support. This cross-sectional study used deidentified Application and Matriculating Student Questionnaire survey data that was obtained from …

Crossing The Theory Threshold: The Pedagogical Potential Of Generative Artificial Intelligence In Educational Research, Amanda Burbage, Jennifer L. Styron

EVMS School of Health Professions Faculty Publications

Purpose

This paper presents findings from an educational research graduate course in which generative artificial intelligence (AI) was incorporated to strengthen learners' understanding of threshold concepts related to theoretical frameworks. Medical and health professionals often struggle with the transition from a clinical role into the educational research role.

Methods

The study posits that the use of generative AI will help learners understand and apply theoretical frameworks beyond a superficial level, furthering their understanding, constructing new knowledge, and strengthening their ability to develop sound educational research studies. Journal and AI transcripts were analyzed for 37 participants.

Results

Open-ended codes were grouped …

Submesoscale Dynamics Of Phytoplankton And Carbon Export Revealed By High-Resolution Airborne And Satellite Remote Sensing Of Currents And Ocean Color, Sarah E. Lang

Open Access Dissertations

Satellites and airborne sensors reveal submesoscale (1 - 10 km) variability in ocean color in the form of filaments, eddies, and patches. The variability in ocean color is closely tied to the physical dynamics that restructure phytoplankton distributions and drive active biological responses like changes in primary productivity and community structure. As the base of the marine food web and a key component of the biological carbon pump, phytoplankton are crucial to the overall health of marine ecosystems and to the ocean's role in climate. This dissertation focuses on the use of airborne and satellite remote sensing to study the …

Artificial Intelligence And Machine Learning In Smart Vaginal Formulation Development, Deborah A. Ogundemuren, Vivek Agrahari, Andrew P. Wong, Carolina Herrera, Margaret O. Ilomuanya, Gustavo F. Doncel

CONRAD Publications

Vaginal drug delivery in women's health remains underutilized and insufficiently studied, largely due to the complexity and dynamic nature of the vaginal microenvironment. Variations in vaginal pH, hormonal levels, and microbiota composition introduce significant biological variability, complicating formulation design and contributing to inconsistent therapeutic outcomes and poor patient adherence. Conventional vaginal formulations often fail to account for these individual differences, highlighting the need for more adaptive and predictive approaches. Emerging advances in artificial intelligence (AI) and machine learning (ML) offer promising strategies to address these challenges by enabling multi-parameter, data-driven formulation development that explicitly considers biological variability. Despite their transformative …

Comparison Of Push-Pull Air Curtain To Overhead Downdraft Systems On Aerosol Containment And Distribution In Controlled Environments, Manal Mutairi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Abstract

Comparison of Push-Pull Air Curtain to Overhead Downdraft Systems on Aerosol Containment and Distribution in Controlled Environments.

This dissertation looks at the ongoing issue of tiny airborne particles created during medical and dental procedures and evaluates ways to reduce the risk of exposure for healthcare workers and patients to these particles. The first study focuses on the size, how long particles stay in the air, and how far they travel from common medical procedures that create aerosols, showing that tiny particles (less than 5 µm) can stay in the air long enough to escape basic droplet controls. As a …

Multi-Timescale Monitoring And Modeling For Resilient Smart Grids: Pmu Anomaly Detection And Battery Digital Twins, Muhammad Imran Hossain

Graduate Theses, Dissertations, and Problem Reports (ETD)

Modern power systems face failures at very different timescales. Cyber-physical disturbances may emerge within seconds, while battery degradation develops over hundreds of operating cycles. Both monitoring problems share the same underlying difficulty: power systems produce measurement data in abundance, but reliably labeled examples of abnormal or degraded operation are scarce. Rare grid events are difficult to label, and battery degradation data are heterogeneous across cells, cycling protocols, and chemistries. This thesis addresses these challenges through two complementary domain-informed learning frameworks that constrain representation learning using information specific to each physical problem.

First, at the system level, T-BiGAN, a Transformer-augmented bidirectional …

A New Functional Setting For Term Structure Modeling Using The Health-Jarrow-Morton Framework, Michael Pokojovy, Ebenezer Nkum, Thomas M. Fullerton Jr.

Mathematics & Statistics Faculty Publications

The well-known Heath–Jarrow–Morton (HJM) framework provides a universal and efficacious instrument for modeling the stochastic evolution of an entire yield curve by explaining the interest rate dynamics in continuous time under no-arbitrage conditions. Existing implementations involve exponentially weighted function spaces as theoretical settings for the former stochastic evolution. While the choice of weight can have a drastic effect on model calibration and subsequent forecasting, it cannot be estimated from market data and does not allow for any objective interpretation. The proposed approach does not have this shortcoming as it adopts a suitably designed unweighted function space. The HJM equation is …

Cross-Modal Proxy Evolving For Ood Detection With Vision-Language Models, Hao Tang, Yu Liu, Shuanglin Yan, Fei Shen, Shengfeng He, Jing Qin

Research Collection School Of Computing and Information Systems

Reliable zero-shot detection of out-of-distribution (OOD) inputs is critical for deploying vision-language models in open-world settings. However, the lack of labeled negatives in zero-shot OOD detection necessitates proxy signals that remain effective under distribution shift. Existing negative-label methods rely on a fixed set of textual proxies, which (i) sparsely sample the semantic space beyond in-distribution (ID) classes and (ii) remain static while only visual features drift, leading to cross-modal misalignment and unstable predictions. In this paper, we propose CoEvo, a training- and annotation-free test-time framework that performs bidirectional, sample-conditioned adaptation of both textual and visual proxies. Specifically, CoEvo introduces a …

Relationships Between Benthic Macroinvertebrate Communities And Environmental Conditions In Headwater Tributaries Of The Pend Oreille Lake Watershed, Idaho, Devlin Mee

EWU Masters Thesis Collection

Benthic macroinvertebrates are widely used indicators of stream condition, and their communities respond to thermal and land-use conditions in headwater streams. This study characterized macroinvertebrate biomass, community composition, and diversity across forested headwater tributaries of the Pend Oreille lake watershed in northern Idaho, and examined their relationships with summer temperature, land development, and road proximity. Samples from thirteen streams collected in 2024 were identified to genus, measured, and converted to estimated biomass using published length–mass regressions; ten streams had recovered temperature loggers. Because environmental variables were characterized once per stream, all analyses were conducted at the stream level.

Estimated total …