Digital Commons Network^™

Computer-Aided Molecular Design To Identify More Environmentally Friendly Pfas, Melvin M. Keita

Williams Honors College, Honors Research Projects

The goal of this project is to inversely design alternatives to per- and polyfluoroalkyl substances (PFAS) using Computer-Aided Molecular Design (CAMD). PFAS, also described as “forever chemicals”, have been used in industry and consumer products since the 1940s. PFAS can be found in drinking water, food, food packaging, waste sites, and other sources. Exposure to different PFAS can lead to increased risks of some cancers, immune effects, and reproductive effects. Pulling from existing data, this project will use quantitative structure-property relationships (QSPRs) to design PFAS alternatives that possess optimal properties to prevent adsorption into drinking water and other potential sources …

Machine Learning For Economists, John Luke Gallup

Economics Faculty Publications and Presentations

Explication of machine learning algorithms and their usefulness for economic research. The prediction algorithms of Random Forest, Gradient Boost Machines, Neural Networks and Support Vector Machines are built from simple steps applied at large scale to generate surprisingly precise nonlinear estimates. Although useful for processing and interpreting new forms of data, their application to economics research is limited because they do not provide readily interpretable evidence of the causes of outcomes.

Data And Code For: Combined Effects Of Forest Fire And Climate Warming On Seasonal Snow In The Western Oregon Cascades, Joseph D. Vigil

Environmental Science and Management Datasets

This dataset supports a study examining the combined effects of forest fire and climate warming on seasonal snow in the Breitenbush watershed of the western Oregon Cascades. The archive includes daily SnowModel snow water equivalent outputs for forested, current post-fire, mid-century, and end-century climate scenarios; field meteorological and manual snow observations; station metadata; modified SnowModel code used to represent post-fire snow-albedo decay; and R code used to calculate snow metrics and statistical comparisons reported in the associated manuscript. Derived results and documentation are included to support reproduction of the primary analyses.

Using Low-Cost Sensors For Source Attribution And Health Assessment: An Air Quality Study In Brownsville, Texas, Sai Deepak Pinakana, Kabir Bahadur Shah, Daniel Jaffe, Juan L. Gonzalez, Owen Temby, Gabriel Ibarra-Mejia, Amit U. Raysoni

School of Earth, Environmental, & Marine Sciences Faculty Publications

Air quality monitoring remains a challenge in areas lacking or having sparse federal monitoring infrastructure, posing significant barriers to public health research. This study demonstrates the usage of low-cost sensors in addressing gaps in air quality monitoring, source attribution, and health risk assessment in a Brownsville, TX neighborhood impacted by emissions from a barite and celestite mineral processing unit. PM2.5 concentrations were measured using PurpleAir sensors deployed across three residential locations, with the site nearest to the processing unit recording a 24-h averaged PM2.5 concentration of 25.12 μg/m3—approximately 2.79 times higher than the nearest Texas Commission of Environmental Quality (TCEQ) …

Handwriting Recognition In Vr, Dominique Mosley

EWU Masters Thesis Collection

Virtual Reality (VR) is slowly becoming more popular for more than just entertainment. VR can be found in educational, office, and even healthcare settings to help discover more intuitive ways to teach, collaborate, and treat patients. Outside of the virtual world, these environments typically rely on writing for communicating or note-taking. Currently, VR input forces users to rely on clunky on-screen keyboards which disrupts the user’s immersion and breaks the flow of natural interaction. This thesis explores the potential of VR as a learning platform by combining it with artificial intelligence (AI). It aims to develop a VR-enhanced handwriting practicing …

An Introduction To Field Excursions For The 2026 Geological Society Of America Cordilleran Section Meeting In Loreto, Baja California Sur, México, Scott E.K. Bennett, Michael H. Darin, Genaro Martínez Gutiérrez

Geology Faculty Publications and Presentations

The 122nd annual meeting of the Geological Society of America (GSA) Cordilleran Section will be held in Loreto, Baja California Sur, México, an idyllic and historic Sonoran Desert city nestled on the eastern shore of the Baja California peninsula. The 2026 Loreto meeting marks a milestone for GSA as it is the first time in the Section’s century-plus history that the meeting has been held on the Baja California peninsula and only the third time that the meeting has been held in México. Thus, the 2026 Loreto meeting and related field trips represent a meaningful expansion of the Section’s engagement …

Parametric Study Of Yields And Properties Of Corn Stover-Derived Hydrothermal Liquefaction Products By Using Statistical Approaches, Isamu Umeda, Meicen Liu, Jiefu Wang, Yi Zheng, Zhiwu Wang, Jaya Shankar Tumuluru, Sandeep Kumar

Civil & Environmental Engineering Faculty Publications

Hydrothermal liquefaction (HTL) of lignocellulosic biomass produces multiple product fractions, including solid residue (SR), heavy bio-oil (HBO), aqueous phase (AP), and light bio-oil (LBO). This study mainly applied principal component analysis (PCA) and regression modeling to predict AP solution weight, LBO weight and fuel characteristics, and HTL wastewater biodegradability, as well as to improve prediction accuracy for SR and HBO under various operating conditions (temperature: 250–350 °C, residence time: 5–60 min, and the combined solid loading of three batches: 15–45 g). A complementary relationship between SR and AP weights found in PCA enabled the estimation of AP weight based on …

Physics-Based Multi-Hazard Fragility Modeling Of Low-Rise Wood-Frame Buildings Under Hurricane-Induced Wind And Surge, Mumtasirun Nahar, Abdullah M. Braik, Mohammad Syed, Maria Koliou, Petros Sideris

Civil & Environmental Engineering Faculty Publications

Coastal buildings are exposed to concurrent hurricane-induced wind and storm surge, yet their vulnerability is commonly assessed using separate single-hazard models that neglect hazard interaction. This study developed a physics-based finite element framework to evaluate the performance of a low-rise light wood-frame building under simultaneous wind and surge-wave loading. A detailed three-dimensional model was constructed using a sub-assembly strategy that explicitly represented framing members, sheathing systems, and critical connections. Structural response was evaluated across a hazard space defined by wind speed, still-water depth, and flow velocity, and component- and system-level fragility functions were derived using Monte Carlo simulation and generalized …

Learning Weibull Loss Severity Models From Truncated And Censored Data, Majed Alkhasha

Graduate Studies Theses and Dissertations 2026

In modern actuarial science and risk management, due to various loss control mechanisms, observed severity losses are typically left-truncated at the deductible, right-censored at the policy limit, and scaled by a pre-specified co-insurance factor. This results in two types of actuarial payment random variables: payment-per-payment (PPP) and payment-per-loss (PPL). To learn ground-up Weibull loss severity models from PPP and PPL sample data, we implement two estimation techniques: Maximum Likelihood Estimation (MLE) and the dynamic Method of Trimmed Moments (MTM). MLE is employed to obtain efficient estimates of the Weibull shape and scale parameters. However, MLE may assign unnecessarily large point …

Connecting The Existing Fiber Infrastructure To The Future With Antiresonant Hollow Core Fibers, Timothy Bate

Graduate Studies Theses and Dissertations 2026

Optical fiber systems based on solid-core silica waveguides underpin modern telecommunications, high-power laser delivery, precision sensing, and coherent optical systems. However, nonlinear effects, material absorption, and thermal limitations within silica increasingly constrain further scaling in both optical power and transmission performance. Antiresonant hollow-core fibers provide a promising alternative by guiding light predominantly in air, substantially reducing nonlinear interactions, latency, and optical damage while enabling transmission regimes inaccessible to conventional solid-core fibers. Despite rapid advances in antiresonant hollow-core fiber attenuation and power handling, one of the largest remaining barriers to widespread adoption is reliable integration with the existing solid-core fiber ecosystem. …

Nebraska Test 2305: Claas Arion 660, Nebraska Tractor Test Lab

Nebraska Tractor Tests

ABOUT THE TEST REPORT AND USE OF THE DATA The test data contained in this report are a tabulation of the results of a series of tests. Due to the restricted format of these pages, only a limited amount of data and not all of the tractor specifications are included. The full OECD report contains usually about 30 pages of data and specifications. The test data were obtained for each tractor under similar conditions and therefore, provide a means of comparison of performance based on a limited set of reported data. EXPLANATION OF THE TEST PROCEDURES Purpose The purpose of …

Nebraska Test 2308: John Deere 9r 540 Single Turbo (Chassis Serial Numbers 1rw9540xxsx090001 And Higher), Nebraska Tractor Test Lab

Nebraska Tractor Tests

ABOUT THE TEST REPORT AND USE OF THE DATA The test data contained in this report are a tabulation of the results of a series of tests. Due to the restricted format of these pages, only a limited amount of data and not all of the tractor specifications are included. The full OECD report contains usually about 30 pages of data and specifications. The test data were obtained for each tractor under similar conditions and therefore, provide a means of comparison of performance based on a limited set of reported data. EXPLANATION OF THE TEST PROCEDURES Purpose The purpose of …

The Case For Friction In Ai-Mediated Information Seeking And Learning, Susan G. Archambault, Priya Kizhakkethil

Librarian Publications & Presentations

Introduction. This paper challenges the assumption that frictionless AI-mediated information seeking represents progress. We argue that AI systems eliminating productive friction, such as uncertainty, exploration, and reflective processes, undermine intellectual virtues essential for critical thinking in an AI-saturated information environment.

Method. This conceptual article employs a theory synthesis approach, drawing on library information science (LIS) theories of information behaviour, experience, and literacy, virtue epistemology, and human–computer interaction (HCI) friction design literature.

Analysis. We map intellectual virtues such as curiosity, thoroughness, and intellectual humility onto the Association of College and Research Libraries (ACRL) Framework for Information Literacy for Higher Education, building …

Gender Differences In The Association Between Adverse Childhood Experiences And Drug Use: Findings From A Community-Based Survey In China, Hongyun Fu, Elizabeth Monk-Turner, Xiushi Yang

Department of Pediatrics Faculty Publications

Background

While adverse childhood experiences (ACEs) are widely recognized risk factors for behavioral health problems, including drug use, prior research has largely been conducted in Western countries, focused primarily on males, and relied on convenience samples without comparison groups of nonusers. Limited work has examined the impact of ACEs on drug use in non-Western contexts. This study examines gender differences in the relationship between ACEs and drug use in China, using data from a population-based probability sample survey.

Methods:

Cross-sectional data were collected in 2019 from one city in Yunnan Province in Southwest China and one city in Guangdong Province …

1-D And 2-D Hadamard Transformations For Protein Sequence Analysis, Esraa A. Ahmed, Abed M. Nasr, Marwa A. Abd Elwahaab

Mansoura Engineering Journal

Similarity/dissimilarity studies follow alignment-based or alignment-free methods. Many alignment-free methods involve selecting physicochemical properties. Most previous articles don’t explain their criteria for choosing the properties used. These heuristic approaches have, by definition, undeterministic and unreliable performance. Hence, there is a need for a powerful proxy for similarity/dissimilarity by a deterministic, reliable approach.

In this study, a physicochemical property is selected by a multi-criteria sequential selection process. The amino acids composing any protein sequence are replaced with their values of the chosen property to produce a discrete signal in the time domain.  The one-dimensional discrete Hadamard transforms our signal from the …

High-Efficiency And Compact Virtual Reality Displays, Zhenyi Luo

Graduate Studies Theses and Dissertations 2026

Virtual reality (VR) and augmented reality (AR) technologies are revolutionizing the way humans interact with digital information. However, current near-eye display systems still face critical challenges regarding optical efficiency, image quality, and device weight. This dissertation focuses on addressing these limitations through innovative liquid-crystal (LC) optics and system-level design strategies to achieve high-efficiency and compact VR displays.

First, to solve the longstanding problem of severe chromatic aberrations in ultrathin LC optics, I proposed an achromatic diffractive LC device. By stacking three LC layers with specifically designed spectral responses and polarization selectivity, I successfully reduced the chromatic aberrations. This idea enables …

Nebraska Test 2304: Claas Arion 630, Nebraska Tractor Test Lab

Nebraska Tractor Tests

ABOUT THE TEST REPORT AND USE OF THE DATA The test data contained in this report are a tabulation of the results of a series of tests. Due to the restricted format of these pages, only a limited amount of data and not all of the tractor specifications are included. The full OECD report contains usually about 30 pages of data and specifications. The test data were obtained for each tractor under similar conditions and therefore, provide a means of comparison of performance based on a limited set of reported data. EXPLANATION OF THE TEST PROCEDURES Purpose The purpose of …

Nebraska Test 2310: John Deere 9rx 540 Single Turbo (Chassis Serial Numbers 1rw9540xxsx828001 And Higher), Nebraska Tractor Test Lab

Nebraska Tractor Tests

ABOUT THE TEST REPORT AND USE OF THE DATA The test data contained in this report are a tabulation of the results of a series of tests. Due to the restricted format of these pages, only a limited amount of data and not all of the tractor specifications are included. The full OECD report contains usually about 30 pages of data and specifications. The test data were obtained for each tractor under similar conditions and therefore, provide a means of comparison of performance based on a limited set of reported data. EXPLANATION OF THE TEST PROCEDURES Purpose The purpose of …

Nebraska Test 2309: John Deere 9rt 540 Single Turbo (Chassis Serial Numbers 1rw9540xxsx929001 And Higher), Nebraska Tractor Test Lab

Nebraska Tractor Tests

ABOUT THE TEST REPORT AND USE OF THE DATA The test data contained in this report are a tabulation of the results of a series of tests. Due to the restricted format of these pages, only a limited amount of data and not all of the tractor specifications are included. The full OECD report contains usually about 30 pages of data and specifications. The test data were obtained for each tractor under similar conditions and therefore, provide a means of comparison of performance based on a limited set of reported data. EXPLANATION OF THE TEST PROCEDURES Purpose The purpose of …

Structured Interactions With Llms To Support Ltl: Supplemental Information, Karenna Kung, Maanas Punuru, Alicia M. Grubb, Paola Spoletini

Computer Science: Faculty Publications

This repository contains the supplemental information for the paper: "Structured Interactions with LLMs to Support LTL", which investigates how students interact with and can be supported by LLM explanations while translating linear temporal logic formulae into English natural language.

Oompa 2025.08: A First Cut Of The Toolkit For Object-Oriented Modeling For Planning And Acting, Mark Roberts, David H. Chan, Dana S. Nau, Jamie C. Macbeth

Computer Science: Faculty Publications

OOMPA is a partially implemented Python 3.13+ toolkit for modeling hierarchical planning domains as annotated Python classes, without writing a separate PDDL or HDDL domain file. State properties, actions, and hierarchical methods attach to domain classes via decorator syntax; OOMPA projects the resulting model into a flat dictionary of dictionaries, like the Pyhop family of planners. We describe OOMPA’s motivation and architecture as we demonstrate its use in a restaurant planning domain. There are many unrealized features, so we end with a discussion of limitations and future work.

Explainable Physics-Based Constraints On Reinforcement Learning For Accelerator Optimization, Jonathan Colen, Malachi Schram, Kishansingh Rajput, Armen Kasparian

Data Science Faculty Publications

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at …

Applying Transfer Learning For Street-Scale Nuisance Flood Forecasting In Coastal-Urban Environments, Binata Roy, Jonathan L. Goodall, Diana Mcspadden, Chetan Kumar, Steven Goldenberg, Yidi Wang, Malachi Schram

Data Science Faculty Publications

An important challenge with Machine Learning (ML) is its transferability; that is, whether an ML model trained on one set of data can be applied to a second set of data without requiring full retraining of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether an ML model trained for …

Slm With Swarm Intelligence For Efficient Representation Of Medical Claims, Mohamed Ahmed Abo El-Enen, Ravi S. Sharma, Mustafa Abdulrazek, Amril Nazir, Reem Muhammad, Ahmed Talat Sahlol

All Works

Healthcare industry faces significant challenges due to fraudulent medical insurance claims, which result in substantial financial losses. We propose an automated system using domain-specific Small Language Models (SLMs) with a narrower scope and smaller parameter count than general-purpose Large Language Models (LLMs), combined with optimization algorithms to improve fraud detection. Our approach integrates numerical features, such as age and claim amount, with textual descriptions, including diagnoses and procedures, into a unified textual representation for each medical activity. This representation captures complex patterns, enhancing the model’s predictive ability. SLMs fine-tuned on medical corpora transform these textual inputs into fixed-dimensional numerical embeddings, …

Optimized Hybrid Beamforming For Ris-Assisted Multi-User Mimo In 6g Mmwave Networks: A Low-Complexity Approach To Spectral Efficiency And Interference Mitigation, Safiya Nasser Al-Jaradi, Mohammad Kamrul Hasan, Nabeel Al-Qirim, Shayla Islam, Thippa Reddy Gadekallu, Hana Mujlid, Hashim Elshafie, Rashid A. Saeed

All Works

The joint optimization of hybrid beamforming and reconfigurable intelligent surface (RIS) phase shifts in multi-user millimeter-wave (mmWave) MIMO systems is a challenging problem, mainly due to high computational complexity and the lack of adaptive interference management. Existing approaches typically rely on fixed Zero-Forcing (ZF) or Maximum-Ratio Transmission (MRT) designs or require iterative optimization with high overhead, limiting their practical use in dense 6G environments. To overcome these challenges, this research proposes a RIS-Aided Adaptive Zero-Forcing and Maximum-Ratio Transmission Hybrid Precoding (RA-ZMHP) framework for 6G mmWave multi-user MIMO systems. The main novelty of the method lies in an adaptive ZF–MRT mixing …

A Novel Bernstein Operational Matrix Approach For Tempered Fractional Differential Equations: Convergence And Stability Analysis, Jalal Al Hallak, Mohammed Alshbool, Ishak Hashim, Eddie Shahril Ismail, Shaher Momani

All Works

Tempered fractional differential equations (TFDEs) incorporate exponential decay into fractional operators to account for truncated memory and semi-long-range dependence in a variety of applications, including anomalous diffusion, viscoelasticity, transport phenomena, geophysical processes, and financial dynamics. In this work, a tempered fractional Bernstein method (TFBM) was proposed for the numerical solution of TFDEs involving Caputo-type derivatives. The proposed formulation combined a Bernstein polynomial approximation with an analytic representation of the Caputo–tempered fractional derivative through operational matrices. On this basis, two collocation-based variants were developed, namely, a Chebyshev-type method (TFBM-C) and a Legendre-type method (TFBM-L). For the linear setting, a convergence analysis …

Empirically Evaluating The Accessibility Of A Pon-Enable Feature Diagrams Notation By The Red-Green Colorblind Community, Mohamed El-Attar, Sarah Kohail, Rima Grati

All Works

In 2016, an enhanced version of a feature diagram notation developed using the Physics of Notations (PoN) framework was introduced. Empirical evidence demonstrated that this revised notation was more cognitively effective than the original. However, the new notation relies on color, specifically red, which poses accessibility challenges for individuals with red–green color vision deficiency, as they cannot perceive the notation as originally intended. Consequently, the cognitive effectiveness of a red–green–deficient (RGD) version of the new notation relative to the original notation remained unknown. Although the PoN framework specifies several principles that may be satisfied with or without the use of …

Leveraging Quantum Storage Mechanism For Digital Forensic Readiness Towards Smart City Security, Bashaer Aljeneibi, Richard Ikuesan

All Works

The increasing digitization of urban infrastructure has introduced advanced efficiency and connectivity in smart cities while exposing them to sophisticated cybersecurity threats. This study explores how Quantum Storage Mechanisms (QSM) can be integrated with digital forensic readiness systems to enhance smart city security and incident response. Through a simulated environment, the research evaluates the effectiveness of QSM against three critical cyberattack scenarios: Distributed Denial of Service (DDoS), sensor spoofing, and supply chain firmware attacks. The findings reveal that QSM-enabled systems outperform traditional cybersecurity tools by ensuring tamper-proof evidence collection, real-time threat detection, and secure long-term data retention. The study also …

The Deepfake Litmus Test: A Multimedia Authenticity Mechanism, Amna Alzaabi, Hessa Alqubaisi, Fatima Alzaabi, Richard Ikuesan

All Works

Deepfake technologies have made it increasingly difficult to distinguish authentic video content from manipulated media. This paper presents a forensic detection framework, referred to as the Litmus Test, which focuses on structural analysis of MP4 container files to detect signs of tampering. Unlike conventional AI-based approaches that operate as black boxes, this method examines the atomic composition of video containers to identify anomalies. The proposed method performs atom-level inspection of MP4 file hierarchies and structural markers to uncover anomalies indicative of synthetic manipulation. Evaluations using datasets such as CelebDF, UADFV, and DeeperForensics reveal that the framework can identify inconsistencies common …

Modelling Route-Level Interzonal Travel Time Using Gps Trajectories, Muhammad Faiq Ahmed, Tom Bellemans, Fatma Outay, Muhammad Ahmed, Afzal Ahmed, Feng Liu, Muhammad Adnan

All Works

Activity-based models (ABMs) require accurate travel-time estimates for accessibility calculations, yet many implementations rely on static routing outputs that fail to capture temporal congestion dynamics due to limited high-resolution data. This paper develops route-level travel-speed prediction models using GPS trajectory data from 48 vehicles in Flanders, Belgium. GPS trajectories are integrated with OpenStreetMap and land-use data through destination-based segmentation, in which trips from fixed origins are cumulatively segmented at zone crossings. To capture behavioural differences by trip length, separate Gamma regression models are estimated for short (≤5 km) and long (>5 km) trips using temporal, network, and spatial variables. …