Physical Sciences and Mathematics Commons^™

Natural Hydrogen Soil Gas Emissions Near Harvey, Perth Basin: A Comparative Study Of Survey Methods, Krista Davies, Peter W. Haines, Charmaine Thomas, Leon Normore

Research outputs 2022 to 2026

Quantifying natural hydrogen soil gas emissions and their controlling factors is critical for assessing hydrogen storage viability and improving exploration strategies. This study provides the first detailed comparison of hydrogen emissions near the DMP Harvey-2 well in the Perth Basin and compares the effectiveness of repeated point surveys and autonomous monitoring in capturing emission variability. Hydrogen concentrations ranged from 0 to >1000 ppm in point surveys, with transient pulses up to 598 ppm detected through continuous monitoring, indicating episodic release. Repeated point surveys successfully captured the overall range of emissions but failed to resolve dynamic processes, such as abrupt flux …

Cui-Derived Cuxo Thin Films Development Via Thermal Oxidation For Lead-Free Perovskite Solar Cells, Md Jakir Hossen, Md Shahinuzzaman, M. S. Jamal, Suhana Mohd Said, S. F.W.M. Hatta, Md Helal Miah, Mayeen Uddin Khandaker, Mohammad Nur-E-Alam, Mohammad Aminul Islam

Research outputs 2022 to 2026

The development of low-cost, stable, and efficient hole transport layers (HTLs) is crucial to the advancement of lead-free perovskite solar cells. In this work, a solution-based oxidation process is employed to convert spin-coated copper iodide (CuI) films into mixed-phase copper oxide (CuxO) thin films comprising Cu₂O and CuO. Oxidation occurs under moderate temperatures (200–300°C), leading to uniform, compact, and highly conductive p-type films with tunable bandgaps. Structural, morphological, and optical analysis confirms successful phase transformation, and measurements of Hall effect reveal maximum mobility of holes of 26.7 cm² V⁻¹ s⁻¹ for double-coated films annealed at 300°C. Device …

System Dynamics With Insight Maker, Steven D'Alessandro, Fons Wijnhoven

Research outputs 2022 to 2026

This book offers a practical, model-driven pathway for reasoning about uncertain futures in business and public policy using system dynamics with Insight Maker. It begins by motivating why historical data alone often fail to predict social change, and it introduces the core language of system dynamics—stocks, flows, feedbacks, delays, and auxiliary variables—alongside the complementary use of agent-based modeling. Through business-relevant cases (e.g., park management trade-offs, epidemic–economy interactions, and industry competition), the book demonstrates how non-linear structure generates counter-intuitive dynamics, why scenario analysis is essential, and how to translate causal loop diagrams into stock-and-flow simulations. Readers are guided step-by-step to build, …

On-Device Recommender Systems: A Comprehensive Survey, Hongzhi Yin, Liang Qu, Tong Chen, Wei Yuan, Ruiqi Zheng, Jing Long, Xin Xia, Yuhui Shi, Chengqi Zhang

Research outputs 2022 to 2026

Recommender systems have been widely deployed in various real-world applications to help users identify content of interest from massive amounts of information. Traditional recommender systems work by collecting user-item interaction data in a cloud-based data center and training a centralized model to perform the recommendation service. However, such cloud-based recommender systems (CloudRSs) inevitably suffer from excessive resource consumption, response latency, as well as privacy and security risks concerning both data and models. Recently, driven by the advances in storage, communication, and computation capabilities of edge devices, there has been a shift of focus from CloudRSs to on-device recommender systems (DeviceRSs), …

Quantifying The Performance Of The Sparta Toolkit For Use In Planetary Regolith Characterization Missions, Abigail S. Glover

Honors Undergraduate Theses

This research investigates the use of the Soil Properties Assessment, Resistance, and Thermal Analysis (SPARTA) Cone Penetration Tester (CPT) to quantify bulk density in lunar regolith simulant LHS-1E. Twenty-five penetration tests were conducted across five density profiles to derive slope parameters (G), which represent the rate of increase in resistance with depth. Results showed a consistent, nonlinear relationship between G and bulk density, validating the use of G slope as a diagnostic parameter and supporting the primary hypothesis that SPARTA CPT measurements vary meaningfully with density. Compared to prior work by Lucas et al. (2024), G values from SPARTA were …

Comparative Efficacy Of Hallucinogens In Treating Mood Disorders Through A Meta-Analysis Of Symptom Reduction, Dosage, And Duration, John Marco D.F. Muniz

Honors Undergraduate Theses

Background: Hallucinogens including psilocybin, lysergic acid diethylamide (LSD), ketamine, N,N-dimethyltryptamine (DMT) (as ayahuasca), have re-emerged as potential rapid-acting treatments for mood disorders. We conducted a meta-analysis of placebo-controlled trials evaluating their efficacy in depression and anxiety disorders. Methods: A systematic review identified 12 trials (Total ≈ 670) meeting inclusion criteria (randomized, placebo-controlled). Data on Cohen’s d and Hedges’ g effect sizes for depression- and anxiety-related outcomes were extracted. We computed pooled effect sizes (weighted by sample size and inverse variance), performed subgroup analyses by drug, diagnosis, follow-up duration, and outcome measure type, and assessed heterogeneity (I², Q …

Entangled Photoelectron Attosecond Spectroscopy, Jonathan Sar-Shalom

Honors Undergraduate Theses

In this thesis we propose an interferometric scheme to retrieve the dynamics of an electron wave packet emitted from two distinct residual photo-ion channels in the ionization of an atom by an ultra-short UV pulse. EPAS (Entangled-Photoelectron Attosecond Spectroscopy) works by having a non-overlapping UV and few-cycle IR pulse, where the IR is tuned near the transition frequency between two electronic bound states of the photo-ion. Using a time-dependent simulation based on a two-channel atomic model, supported by a perturbative approach, we were able to compute the resulting interference in the angular distribution of the photoelectron and retrieve the energy-dependent …

In Vitro Microfluidics System For Mechanobiologic Investigations, Michael A. Daanen

Honors Theses

Mechanobiology is an emerging field that aims to study the relationships between mechanical forces and cellular behavior. Such mechanobiological relationships are especially critical in the cardiovascular system, where endothelial cells lining the vasculature align in response to fluid shear stresses from blood flow (Sinha, 2016). Implanted flow devices, diabetes, chronic hypertension, and various other diseases and pathophysiologies alter vessel geometries and flow dynamics. Such alterations impact fluid shear stress and endothelial cell behavior, leading to microcirculatory dysfunction, vessel leakage, and organ failure (Poredos, 2021; Papadaki, 1999; Leitschuh, 1987). To simulate dysfunctional endothelial cell behavior in vitro and evaluate novel therapeutic …

On Linear Invariants Of Hypergraphs, Clara Chaplin

Honors Theses

We introduce linear invariants of hypergraphs as a way to study hypergraphs by their tensor representations. Our primary research goal is to determine what information linear invariants capture about the hypergraphs they arise from. We first investigate the centroid, which is shown to determine the connected components of a hypergraph. Next, we study the derivations of a hypergraph, and use this linear invariant to define a quotient operator $Q_\mathrm{Der}$ on the collection of all hypergraphs. This operator is shown to be a closure operator in that $Q_\mathrm{Der}(Q_\mathrm{Der}(\mathcal{H}))=Q_\mathrm{Der}(\mathcal{H})$ for any hypergraph $\mathcal{H}$. We apply the operator $Q_\mathrm{Der}$ to synthetically generated hypergraphs, …

One Peak, Two Peaks: On The Effects Of Enhanced Evaporation In An Ammonium Sulfate And Succinic Acid Aerosol System, Julia Reynolds

Honors Theses

Aerosols, defined as suspensions of liquid or solid particles in a gaseous medium, are ubiquitous in both indoor and outdoor environments. They have significant impacts ranging from public health concerns to climate dynamics. In laboratory settings, aerosols are most often generated through a technique known as atomization. The atomization or nebulization is from dilute, aqueous solutions of various chemical compositions. This process typically produces a unimodal, lognormal particle size distribution with exceedingly rare exceptions. Colleagues in a different laboratory (Dr. Freedman’s Group at Pennsylvania State University), however, mentioned they observed a bimodal size distribution, a distribution with more than one …

Theoretical Study Of Phase-Ordering Kinetics With An Anisotropic Surface Tension, Arjun Anand, Ben Vollmayr-Lee

Honors Theses

Coarsening describes the phase-separation dynamics that follows after a temperature quench from a stable to unstable region of the phase diagram in binary systems. Whereas binary systems with an isotropic surface tension have been thoroughly examined and modeled, the case of an anisotropic surface tension lacks the same degree of analysis and development. In this thesis, we demonstrate the self-consistency of the scaling hypothesis with an anisotropic surface tension in the dilute limit. We begin by assuming weak anisotropy in the surface tension and working only to first order in perturbation theory. Following a similar approach laid out in the …

Robust Text Input For Smartwatches: Compensating For Imprecise Tapping And Swiping, Jianwei Lai, Lina Zhou, Kanlun Wang, Dongsong Zhang

Faculty Publications - Information Technology

Entering text on a smartwatch is challenging due to the difficulty of tapping tiny keys. This study introduces a novel keyboard, Tap’nSwipe, to address the challenge. The keyboard features nine areas, each containing up to four characters. To enter a character, users swipe in a specific direction within the area containing the character, freeing them from precisely tapping on the target key. In addition, Tap’nSwipe leverages word predictions to enter words by allowing users to tap anywhere in the areas containing the target characters. The results of a user experiment show that Tap’nSwipe improves text entry accuracy and reduces error …

Scp 231 Dictionary + Example Problems [General Physics 1], Daniel Capic

Open Educational Resources

Student-written definitions of key physics concepts that appear in SCP 231. There are also student-written word problems with links to instructor-created video solutions.

Harnessing Electroosmotic Hybrid Nanofluid Dynamics In Curved Arteries: Insights Into Biomedical Flow Enhancement, M. A. El Kot, A. M. Alsharif, Y. Abd Elmaboud, Sara Abdelsalam

Basic Science Engineering

No abstract provided.

A Finite Difference Analysis Of Electroosmotic Flow Of A Two-Layer Jeffrey Fluid In A Vertical Porous Nanochannel, Y. Abdelmaboud, M. A. Elkot, Sara Abdelsalam

Basic Science Engineering

In this paper, we discuss the unsteady two-layer electroosmotic flow (EOF) of the Jeffrey fluid in a vertical porous nanochannel, taking into account the effect of the heat transfer and alternating current (AC) electric fields. In this model, the two layers have different densities and viscosities. The finite difference method is used to solve the governing equations of electrical potential, velocity, and temperature. The results show that the Debye-Hückel parameter is significant in managing electroosmotic flow (EOF) because it affects the electrical double layer (EDL) compression and velocity gradients on the wall. The higher the radiation parameter, the lower the …

Impacts Of Southern Pine Beetle (Dendroctonus Frontalis Zimmerman) On Loblolly Pine (Pinus Taeda L.) Canopy And Water Use In The Homochitto National Forest, Mississippi, Usa, Sasha Goodnow, Yun Yang, Hui Liu, Ashley Schulz

Endeavors: Mississippi State Undergraduate Research Journal

Abiotic and biotic forest disturbances can have many impacts to forest ecosystem services, including to forest water use. Studies on impacts to forest evapotranspiration have been conducted on the mountain pine beetle (Dendroctonus ponderosae) in western North America, but not on the southern pine beetle (Dendroctonus frontalis), which is a native pest of loblolly pine (Pinus taeda) and shortleaf pine (Pinus echinata), in the southeastern United States. Stressed pine trees produce pheromones that attract southern pine beetles and, with enough stressed trees, beetle populations can quickly grow to epidemic levels and attack healthy trees, which results in widespread tree mortality. …

Generative Ai And Finding The Law, Paul D. Callister

Faculty Works

Legal information science requires, among other things, principles and theories. The article states six principles or considerations that any discussion of generative AI large language models and their role in finding the law must include. The article concludes that law librarianship will increasingly become legal information science and require new paradigms. In addition to the six principles, the article applies ecological holistic media theory to understand the relationship of the legal community’s cognitive authority, institutions, techné (technology, medium and method), geopolitical factors, and the past and future to understand the changes in this information milieu. The article also explains generative …

Ai Lawyering Skills Trainers: Transforming Legal Education With Generative Ai, Alexandria Serra

Faculty Works

The integration of generative AI (GenAI) tools in legal education is not just an innovation—it's a transformative shift redefying how law students acquire and refine advocacy skills. This article examines AI’s critical role in modernizing legal education, emphasizing its potential to offer personalized, one-on-one coaching that enhances student learning and engagement. As AI reshapes the legal profession, law schools must evolve to prepare students for an AI-driven future. Serving as a practical guide, this article provides a step-by-step framework for educators and institutions to develop AI tools that simulate real-world courtroom scenarios and provide continuous, personalized feedback. It also highlights …

Three Essays On Sustainability Economics, Hélène Flore Nguemgaing

Graduate Theses, Dissertations, and Problem Reports (ETD)

As global economies face increasing resource dependencies and supply chain challenges, it becomes essential to understand the vulnerabilities that threaten economic stability. This dissertation investigates three empirical issues in agribusiness and critical minerals using econometric models to estimate the following: 1) the impact of supply chain disruptions on stock market returns during COVID-19; 2) the extraction of rare earth elements from acid mine drainage treatment by investigating the impacts of ownership and legislation in West Virginia and Pennsylvania; 3) China-to�FOBb (Free-on-Board) price transmission in rare earth elements markets: a copula-based dynamic tail dependence analysis.

The first essay evaluates how events …

Using Visual Prompts To Analyze Ejection Fraction In Echocardiograms, Kevin Reisch

Graduate Theses, Dissertations, and Problem Reports (ETD)

Left ventricular ejection fraction (LVEF) is a critical biomarker for heart failure, but manual estimation from echocardiograms is time-consuming. Artificial intelligence can be used to accelerate this process, allowing clinicians to focus on other critical tasks. Current methods typically train models from scratch on echocardiogram datasets; however, this approach is limited by the scarcity of large medical imaging datasets, which are expensive and difficult to acquire. We present a transfer learning approach that leverages pretrained models from massive datasets, enabling continuous improvement as foundation models advance. Our method employs visual prompting to generate trainable masks for echocardiogram videos, transforming the …

Ensemble Learning For Mri-Based Brain Tumor Classification: A Weighted Voting Approach, Ha Anh Vu

All Master's Theses

MRI is essential for detecting and diagnosing brain tumors, where accurately distinguishing glioma, meningioma, and pituitary tumors is vital for effective treatment planning. However, tumors' complex morphology and MRI imaging variations present significant challenges for reliable classification. Deep learning models, particularly Convolutional Neural Networks (CNN) and ResNet architectures, have demonstrated impressive performance in medical image analysis but often struggle with generalization across different datasets. On the other hand, traditional classifiers such as Support Vector Machines (SVM) and K-Nearest Neighbors (KNN) leverage handcrafted features like Histogram of Oriented Gradients (HOG), which can effectively capture structural details but may lack the adaptability …

Investigation Of Colorimetric Trends In Rare-Earth Co-Doped Ypo₄, Barit K. Essman

All Master's Theses

From detectors in scientific instrumentation to medical imaging devices and nuclear monitoring systems to LEDs seen in consumer products, phosphors are utilized in a myriad of applications experienced by both the general public and scientific community alike. For many phosphor applications, emission color and intensity are notably important features to consider. When phosphors are co-doped with rare-earth activators, the ability to predict emission intensity and color output becomes challenging due to competition kinetics and energy transfer between the dopants. During this study, correlation between trends in co-doped phosphor excitation and color output were analyzed to interpret optical behaviors originating from …

Hydrogeochemical Characterization Of The Ahtanum Alluvial Fan For Managed Aquifer Recharge, Yakima Basin, Washington, Brook M. Bauer

All Master's Theses

Overallocation of water resources in the Yakima River Basin, central Washington, has prompted investigation into facilitated aquifer recharge to enhance water supply during drought as part of the Yakima Basin Integrated Plan (YBIP). This study evaluates and characterizes the recharge potential of the Ahtanum Creek alluvial fan within the lower Ahtanum Sub-Basin by integrating geologic, hydraulic, and geochemical data.

Four main hydrogeologic units (unconsolidated, semi-consolidated, consolidated basin-fill deposits, and Columbia River Basalt aquifers) were identified from stratigraphic analysis of well logs across seven transects spanning the active fan and abandoned alluvial terrace portions of the alluvial fan study area. Stable …

Origins And Mechanisms Of Mobility Of Geogenic Arsenic Contamination In Toutle And Silver Lake, Wa, Usa, William A. Hays

All Master's Theses

Arsenic (As), a common contaminant in groundwater, is toxic to human health and has a maximum contaminant level of 10 ppb set by both the World Health Organization and the U.S. Environmental Protection Agency (ATSDR, 2007). In Toutle, WA, USA (30 km west of Mount Saint Helens), a private well, labelled TOU1, was previously identified with ~670 ppb of As and was the impetus of this study. This study targeted private wells in the vicinity of TOU1 to identify the extent of the arsenic contamination, identify the aquifer(s) of concern, and identify the mechanism(s) of mobility.

The wells were screened …

Scalable Parallel-In-Time Integration For Equations Of Motion, Nathan W. Chapman

All Master's Theses

Physical simulations always need to balance accuracy and run-time. This work implements the Parareal Algorithm using graphics processing units across a distributed system to accurately simulate time-dependent physics while attempting to minimize runtime. Data-transfer latency is identified as the primary bottleneck, for which mitigation methods are provided. Benchmarks comparing single-GPU and distributed implementations on a spectrum of coarse and fine discretizations are analyzed.

Macro-Ergonomic And Organizational Behavior Mapping For Organic Waste Management Using Hofstede Culture In Semarang, Indonesia : Pca & Sem Analysis Using Smart Pls, Ratih Setyaningrum, Sahana Pramukti, Ravindran Balasubramani

ASEAN Journal on Science and Technology for Development

Waste management has a very close and complex relationship with community behavior and culture . This relationship is two-way: community culture influences how waste is managed, and conversely, waste management practices can shape or change culture. This study to assess the organizational behavior related to organic waste management. Employing a quantitative methodology, data were gathered using the Hofstede Values Survey Module 13 (VSM 13) - closed questionnaire, with 109 Semarang city Community participants responding via a Google Form. The collected data were analyzed utilizing Hofstede's prescribed formula. The next stage is PCA (Principal Component Analysis) and SEM (Structural Equation Modeling) …

Understanding Detroit’S Local Food And Urban Agricultural Policy Subsystem Using The Advocacy Coalition Framework, Joann Marie Hennessey Ph.D.

Antioch University Dissertations & Theses

This explanatory qualitative case study applied the Advocacy Coalition Framework (ACF) to study Detroit’s local food policy changes from 2000 to 2022. The research question and sub-questions were framed using three ACF hypotheses that addressed advocacy coalitions, collective action, and policy change. My research showed how actors in the policy subsystem worked to promote policy change during the study period. Using this Advocacy Coalition Framework approach, I explored local food policy change in the context of community resilience and system changes. Since 2000, the local food movement in Detroit attempted system changes by experimenting with ways to provide local residents …

The Effect Of Polyethylene Glycol Surface Density Of Dense Brush Gold Nanoparticles On Insulin Fibrillation, Ethan Patrick Grier

Graduate Theses/Dissertations

The development of various neurodegenerative diseases such as Parkinson’s disease and Alzheimer’s disease has been linked to the fibrillation of various proteins within the brain. Parkinson’s disease is specifically linked to the fibrillation of α-Synuclein. During the fibrillation process, the proteins take the form of oligomers, and exposure to these oligomers has been linked to various cytotoxic and neurotoxic effects. Once the fibrillation process is complete, the fibrils made have been shown to be much less toxic than the oligomer stage. This fibrillation process is thermodynamically favorable and is largely irreversible, so one course of action for treatment of these …

Developing Mathematical Maturity By Solving A Given Quadratic Equation, Armando A. Amador, Nieves Angulo, Juan B. Lacay

Publications and Research

This article explores the instructional challenges faced by mathematics educators when addressing students’ limited background knowledge and underdeveloped mathematical maturity, two critical barriers to success in college-level algebra. Using the quadratic equation 2x2+x−3=0, which is reducible over the field of rational numbers ℚ ⊂ ℝ, we analyze how diverse solution methods—factoring, completing the square, and the quadratic formula—can support learning. An additional strategy, “Slide and Divide,” was introduced to promote procedural fluency and conceptual flexibility. To gain insight into students’ evolving mathematical maturity, an online survey was conducted to students at various levels of mathematics. The survey captured their perspectives …

Symbol-Temporal Consistency Self-Supervised Learning For Robust Time Series Classification, Kevin Garcia, Cassandra Garza, Brooklyn Berry, Yifeng Gao

Computer Science Faculty Publications

The surge in the significance of time series in digital health domains necessitates advanced methodologies for extracting meaningful patterns and representations. Self-supervised contrastive learning has emerged as a promising approach for learning directly from raw data. However, time series data in digital health is known to be highly noisy, inherently involves concept drifting, and poses a challenge for training a generalizable deep learning model. In this paper, we specifically focus on data distribution shift caused by different human behaviors and propose a self-supervised learning framework that is aware of the bag-of-symbol representation. The bag-of-symbol representation is known for its insensitivity …