Digital Commons Network^™

In Situ Observations Of Thermal Ions In Perturbed Ionospheres: Techniques And Results, Magdalina Louise Moses

Dartmouth College Ph.D Dissertations

Prediction and mitigation of space weather events are active research topics that require knowledge of the physics governing the ionosphere. Sounding rockets can be used to make in situ observations. The Lynch Rocket Lab created the Petite-Ion-Probe (PIP), a small retarding potential analyzer, to measure thermal ion parameters (i.e., ion density and temperature). A PIP's raw data consists of a series of measured anode currents as a function of screen bias voltages, called IV curves. PIPs can be integrated onto a sounding rocket’s main payload and/or be deployed from the rocket on small platforms called ``PIP-Bobs''. Note that as the …

Basis Design For Electronic Structure And Beyond, Weishi Wang

Dartmouth College Ph.D Dissertations

At the intersection of quantum physics, quantum chemistry, and materials science, electronic structure is the study of electrons in solid-state and molecular systems. Electronic-structure computation relies on discretizing the many-electron Hamiltonian with a finite single-particle basis set. However, basis-set construction is conventionally treated as an ad hoc preprocessing step. This thesis develops an expressive and flexible framework for active, system-oriented basis-set design and numerical modeling strategies that treat basis functions as tunable representations to encode electronic ground-state information.

We first introduce a multi-layered, differentiable basis-construction framework that embeds a set of primitive parameters into mixed-contracted Gaussian-type orbitals. We then develop …

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 …

Sea-Level Rise Adaptation And Collaboration In Polycentric Governance: A Comparison Of Three Regions, Francesca Vantaggiato, Mark Lubell, Matthew C. Nowlin, Juita-Elena (Wie) Yusuf, Majid Shafiee-Jood

School of Public Service Faculty Publications

Adaptation to sea-level rise confronts coastal communities worldwide with a new set of collective action problems that require collaboration. When does collaboration result in concrete action for adaptation? To address this question, we combine the Ecology of Games and Collaborative Governance frameworks using a comparative analysis of three coastal regions in the United States. We leverage original survey data from the San Francisco Bay Area in California (2018, N = 878), the Tri-County (Charleston) Area in South Carolina (2022, N = 152), and the Hampton Roads region in Virginia (2023, N = 153), three regions that differ in terms of …

Hyena: An Observing System Simulation Experiment For Hypothetical Energetic Neutral Atom Imagers, Joel Tibbetts, Amy Keesee, Matina Gkioulidou, Robert Demajistre, Viacheslav Merkin

Faculty Publications

Mesoscale plasma sheet flows are widely understood to be a critical component of the overall picture of energy, particle, and magnetic flux transport during periods of geomagnetic activity. Without simultaneous measurements with true global coverage, the short lifetime (~10 min) and localized spatial extents (~1–3 R_E in azimuth) of these structures make obtaining a global picture of their contributions to stormtime magnetosphere dynamics difficult to characterize. Energetic neutral atom (ENA) imaging can enable remote mapping of plasma energization in the magnetosphere; however, its line-of-sight integrated nature, coupled with the challenging-to-characterize attributes of the target physical phenomena, means that numerous …

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. …

Removal And Monitoring Of Ammophila Arenaria In A Previously Restored Foredune Site In Humboldt Coastal Nature Center, Lucas Benjamin Griffin, Haylee Lynn Kimball, Maya Contreras, Ava Christenson

Environmental Science & Management Senior Capstones

Coastal dunes are important ecosystems that provide vital habitat for rare and endangered species as well as vital ecosystem services. However, since the late nineteenth century, coastal dune ecosystems have been invaded and altered by Ammophila arenaria, which is a beach grass species native to Europe. The dunes within the Humboldt Coastal Nature Center are one such example of this. This property is currently managed by the non-profit organization Friends of the Dunes, which has been working to restore the dunes' ecology and topography. Our project focuses on the monitoring and maintenance of a 2021 restoration project within a 17,794 …

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, …

Process Modeling, Operability Analysis, And Techno-Economic Optimization Of Soecs For Sustainable H2 Production, Krishna Murthy Busam

Graduate Theses, Dissertations, and Problem Reports (ETD)

The global imperative to decarbonize energy systems has intensified research into sustainable hydrogen production pathways, as hydrogen emerges as a critical energy carrier for sectors difficult to electrify directly. Among water electrolysis technologies, solid oxide electrolyzer cells operating at elevated temperatures offer the highest theoretical efficiency by utilizing thermal energy to reduce electrical energy requirements, yet comprehensive frameworks integrating electrochemical modeling with process operability analysis and techno-economic optimization remain scarce in the literature. This dissertation develops a process systems framework for proton-conducting solid oxide electrolyzer cells that bridges the gap between fundamental electrochemical phenomena and industrial-scale process economics. At the …

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 …

Maesa Ramentacea Leaf Extract Protects Against Gentamicin-Induced Nephrotoxicity In Wistar Rats By Modulating Renal Oxidative Stress, Inflammation And Apoptosis, Fahmida Akter, Md Shafiqul Islam Sovon, Baizid Hossain, Md Ariful Islam, Subrato Das, Anik Biswas, Md Sohorab Uddin, Md Mahmudul Hasan

Faculty Publications

Background: Gentamicin-induced nephrotoxicity continues to be a significant clinical concern, while effective and safe protective options remain limited. The nephroprotective potential of Maesa ramentacea has not yet been explored. To address this gap, the present study investigated the ethanolic leaf extract of M. ramentacea (MR-LEE) for its effects on gentamicin-induced kidney injury in Wistar rats. Methods: GC-MS profiling was employed to identify bioactive metabolites. Rats were categorised into five groups: control, gentamicin (100 mg/kg), gentamicin combined with silymarin (100 mg/kg), gentamicin combined with MR-LEE (200 mg/kg) and gentamicin combined with MR-LEE (400 mg/kg). Renal biomarkers, oxidative stress indicators, inflammatory and …

A Comprehensive Survey On Facial Expression Generation: From Gans To Llm-Guided Multimodal Models, Murad Hasan, Rabab Abdelfattah, Kareem Abdelfatah, Mostafa Fouda, Ahmed Sherif

Faculty Publications

Facial expression generation (FEG) has emerged as a vital area in human–computer interaction, virtual avatars, and affective computing, aiming to synthesize natural and expressive facial behaviors across diverse interaction contexts. This survey presents a comprehensive analysis of recent advances in FEG, organized into six key paradigms: speech-driven expression generation, facial reaction generation, face video generation, facial animation, avatar-based generation, and text-driven expression generation. We review a wide range of model architectures, including VQ-VAEs, Generative Adversarial Networks (GANs), 3D Morphable Models (3DMMs), Transformers, and diffusion-based approaches, and compare their performance using commonly adopted evaluation metrics such as Fréchet Distance (FD), Peak …

Success Coaching And Conditional Admit Student Success, Zachery Oliver Thayer

Graduate Theses, Dissertations, and Problem Reports (ETD)

Student success is a matter of critical importance to institutions of higher education, and to students. Colleges and universities exist in a current context of decreasing supply of potential students as a result of an impending demographic cliff and, therefore, increased competition for those remaining students, all while many institutions have become more tuition-dependent. This creates an incentive to decrease selectivity in order to meet enrollment goals as well as to focus university resources on student success measures that impact retention.  Some institutions have decreased selectivity to the point of admitting students conditionally or provisionally, even if those students do …

Creeping Alliances In Foreign Policy Choices: A World Of Clusters And The Outline Of A Fragmented World Order, Kerem Gülay

Case Western Reserve Journal of International Law

International cooperation and conflict has long been studied through formal institutions, namely, membership in international organizations and participation in bilateral or multilateral treaties. This hardly grasps the informal and contingent relationships and the tacit and pragmatic alliances reflected in countries’ joint positions on multilateral issues. While most theories of alliances were preoccupied with why such formal alliances were formed, this article offers a reconceptualization of international cooperation based on empirical data. It proposes “creeping alliances,” tentatively defined as gradual and often informal cooperation that develops over time characterized by increasing mutual foreign policy alignment, to explain an undertheorized domain of …

Maine Law Magazine - Issue No. 100, University Of Maine School Of Law

Maine Law Magazine

Features

• Maine Law’s Privacy Program Continues to Innovate
  How Maine Law’s privacy and innovation programs are preparing students for emerging legal challenges.

• New Business & Law Clinic
  Strengthening Maine’s economy one startup at a time.

• Global Experiential Learning
  From the Arctic Circle to U.N. climate negotiations, students engage with environmental law where it happens.

• Rural Access to Justice
  The Rural Practice Clinic’s impact on Maine’s growing justice gap.

• Law & Conservation Efforts
  How Maine Law alumni steward change and safeguard the future through environmental advocacy.

• Supporting Maine’s Vulnerable
  The Refugee & Human Rights Clinic expands access to justice across Maine. …

Body Mass Index Has No Impact On Complications And Mortality For Patients With Stage Iv Pancreatic Ductal Adenocarcinoma, Ren Bryant, Hannah Darnell, Megan Hall, Kelsey N. Karnik, Kristen J. Mcquerry, Ruben R. Plentz

Biostatistics Faculty Publications

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of United States (USA) cancer death. Overweight and obesity developing into a growing global medical and socio-economic problem, affecting approximately 42% of adults in the USA population. The aim of our analysis was to evaluate the influence of overweight and obesity on complications and clinical outcome in patients with stage IV PDAC.

Methods: We retrospectively reviewed electronic health records of patients diagnosed with stage IV PDAC (n=162) who followed with the University of Kentucky from January 2017–October 2024. Comparisons were based on the body mass index (BMI): low BMI …

Selling Ideals: Sexualization In Teen Girl Magazines, 2007-2017, Megan Coogan

Honors Theses - Providence Campus

Magazines are made to sell more than just a product; they sell lifestyles and ideals. Teen girl magazines target adolescents starting as young as twelve years old, but is the content in its pages appropriate and identifiable for that demographic? This study investigated how levels of perceived sexualization changed between 2007, 2012, and 2017, in Seventeen and Teen Vogue magazines. A decrease in perceived sexualization was expected across the ten-year period of time. This window of time reflects the last ten years of publication for both magazines. Research was conducted by creating and utilizing a grading system for non-explicit sexualized …

Flood Risk Prediction System For Irish River Networks, Fernando Adalberto Naatz Heringer, Hugo Rodrigues De Freitas

ICT

Flooding costs the Irish economy more than 300 million euros annually; however, the hydrometric and meteorological data needed to predict dangerous river rises is already collected and freely available. This project applies machine learning to a decade of hourly observations from OPW Station 09001 on the River Liffey at Leixlip and Met Eireann Casement Aerodrome to build a flood risk prediction system with a 72-hour forecast horizon.

A two-phase modelling pipeline was built following the CRISP-DM framework. Phase 1 compared LSTM and GRU recurrent neural networks on the task of forecasting the river level in metres 72 hours ahead. LSTM …

Machine Learning System For Cereal Yield Prediction In South America., Victor Gabriel Oliveira, Kelvin Henrique Ferreira Dumas

ICT

This project developed a machine learning solution to predict cereal yield in South America using FAOSTAT agricultural data. The objective was to estimate yield in kg/ha for rice, maize, and wheat based on variables such as country, crop type, year, harvested area, producer price, pesticide use, and nutrient indicators.

The project followed the CRISP-DM methodology, covering business understanding, data understanding, data preparation, modelling, evaluation, and deployment. Several regression models were tested, including Random Forest, Gradient Boosting, AdaBoost, XGBoost, KNN, and SVR.

The models were evaluated using MAE, MSE, RMSE, and R² score. The results showed that tree-based ensemble models performed …

A Comparative Analysis Of Supervised Machine Learning Techniques For Predicting It Incident Resolution Time, Ammad Hussain, Hussnain Yaqoob

ICT

IT support teams are facing the persistent challenge in estimating how long an incident will take to resolve. The lack of reliable predictions, planning decisions around staffing, escalation and user communication are largely guesswork. This project set out to address that gap by building a machine learning solution capable of predicting incident resolution time from details available at the point a ticket is logged.

Using the UCI IT Incident Event Log dataset, which contains 141,712 records from a real service management system, the project followed the CRISP-DM framework across six phases from business understanding through to deployment. After thorough data …

A Comprehensive Study Of Sarima And Xgboost Models For Short-Term Traffic Volume Forecasting At A Melbourne Intersection (Victoria), Australia, Douglas Vinicius Dierings, Felipe Fontanive Marques

ICT

Traffic congestion is an increasing challenge in modern cities, impacting transportation efficiency and urban sustainability. This project focuses on short-term traffic volume forecasting, using 15-minute Sydney Coordinated Adaptive Traffic System (SCATS) data collected from the State of Victoria, Australia. The study compares two forecasting approaches: SARIMA, a statistical time-series model, and XGBoost, a decision-tree machine-learning model. Historical traffic data from 2022 to 2024 was analysed to identify traffic patterns, seasonal trends, and peak traffic periods. The models were evaluated for their effectiveness in handling urban traffic behaviour. The results of this study aim to support smarter traffic management, infrastructure planning, …

Identifying New Programme Development Viability, Grant Goodwin

ICT

Higher Education Institutions (HEIs) face the challenge of developing programmes that respond to changing labour market needs while providing graduates with relevant employment opportunities and ensuring institutional financial viability. Rapid technological and economic changes make it increasingly important for HEIs to use reliable data to identify emerging skills and workforce demands. This project explores the use of machine learning and nationally collected employment data to support evidence-based decision-making in higher education programme development. By analysing patterns and relationships within labour market data, machine learning models can help identify areas of growing demand and provide insights into the potential alignment between …

Seasonal Dublin Airport Passenger Arrivals Forecast For The Economy Sector Of Dublin Airport, Roberto Tavares De Oliveira Neto

ICT

Dublin Airport plays a significant role in Ireland’s tourism and commercial sectors, with passenger demand directly influencing retail, hospitality, car rental and other airport-related businesses. Accurate forecasting of passenger numbers can support these sectors in planning marketing activities, managing stock levels and making evidence-based operational decisions. This project develops a monthly forecasting framework for passenger arrivals at Dublin Airport using data from the Central Statistics Office (CSO). Building on previous exploratory data analysis, the study evaluates five time series forecasting approaches: ARIMA, SARIMA, Holt-Winters Triple Exponential Smoothing, TBATS, and an automated model comparison pipeline using PyCaret. The models are assessed …

Machine Learning For Early Obesity Risk Prediction, Giuseppe Cutugno

ICT

Obesity is a major global public health concern, with significant implications for individual health, healthcare systems, and wider economic outcomes. Early identification of obesity risk can support preventive strategies and encourage healthier lifestyle choices before health conditions become more severe. This project develops a machine learning framework for estimating obesity levels using data relating to individuals’ physical characteristics, eating habits, lifestyle behaviours, and demographic factors. Following the CRISP-DM framework, the project examines the structure and limitations of the dataset, including its mixture of objective measurements, survey-based variables, and synthetically generated observations. Two modelling approaches are considered, one including BMI as …

Understanding Host Behaviour And Property Review Characteristics Using New York City Airbnb Dataset, Anna Szkwara

ICT

This project applies strategic thinking and the CRISP-DM methodology to analyse Airbnb listings in New York City and identify patterns associated with host performance and market vulnerability. Airbnb has become a major global accommodation platform, creating opportunities for individual hosts while also increasing competition within the short-term rental market. The project focuses on whether data-driven analysis can identify factors that may influence host success and provide useful insights for hosts with less experience or expertise than larger hospitality organisations. The dataset contains 85 variables, many of which require careful evaluation due to redundancy, high cardinality, sensitivity, or limited relevance to …

Predicting Product Returns In Online Retail, Mihaela Cristina Stefanache

ICT

Product returns are a significant challenge for online retailers, contributing to additional operational costs and affecting inventory management and profitability. This project develops and evaluates three machine learning models to predict product returns for a UK online retailer, building on the data understanding and preparation completed in the previous CA2 capstone project. Following the CRISP-DM framework, the study extends the analysis through enhanced exploratory data analysis, feature engineering, model development, hyperparameter optimisation, cross-validation, and model interpretability. Logistic Regression, a Tuned Random Forest, and XGBoost are evaluated, with the Tuned Random Forest achieving the strongest overall performance, obtaining an F1 score …

Design, Syntheses And Biological Applications Of Fluorescent Probes For Nad(P)H, Hsa And Cellular Microenvironment Sensing, Adenike M. Olowolagba

Dissertations, Master's Theses and Master's Reports

Fluorescent probes have emerged as powerful tools for investigating complex biological processes due to their high sensitivity, selectivity, and capability for real-time, non-invasive imaging. In particular, the detection of key biomolecules such as NAD(P)H, viscosity-related parameters, human serum albumin (HSA), and pH is essential for understanding cellular metabolism, redox homeostasis, and disease progression. In Chapter 2, three coumarin-based fluorescent probes (A–C) were designed, synthesized, and characterized for monitoring NAD(P)H levels in living cells. Probes A and B feature coumarin–cyanine hybrid structures linked via vinyl and thiophene bridges to 3-quinolinium acceptors, respectively, while probe C incorporates a dicyano moiety to replace …

Characterizing Cyber Intrusions In Critical Infrastructure Networks Using Discrete-Event Simulation, Lawrence M. Dilworth

Dissertations, Master's Theses and Master's Reports

Over the past two decades, cybersecurity compliance frameworks such as the North American Electric Reliability Corporation Critical Infrastructure Protection (CIP) have introduced prescriptive measures for protecting power system networks, emphasizing restricted access, segmentation, and minimizing routable exposure. While effective for baseline cyber hygiene, these approaches do not capture system-level risks or adversarial propagation across interconnected infrastructure. In contrast, Cyber-Informed Engineering (CIE), advanced by Idaho National Laboratory, embeds security in system design by considering threat vectors and physical constraints.

Despite CIP guidance, many deployments rely on IP-routable, bidirectional communication that enables handshaking, allowing adversaries to infer reachable targets. This work presents …