Digital Commons Network^™

Northern Rainstorm Belt And Response Strategies, Jianping Huang, Xiaodan Guan, Xiaohuang Liu, Xiaohan Shen, Xiaojie Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the summer of 2025, the Northern Rainstorm Belt stretching from eastern Northwest China to the Northeast region exhibited a significant increase in summer precipitation and rainfall frequency over northern China. Cities in the north were frequently struck by extreme rainstorms, resulting in prominent disasters such as “floods in drylands and urban waterlogging”. Northern China spans a vast territory, serving not only as a major grain-producing area and a densely populated region but also as an ecological security barrier that connects the farming-pastoral ecotone and the Loess Plateau. Its stability has nationwide implications. Therefore, comprehensively enhancing flood control capacity, strengthening …

Panoramic Analysis And Strategic Proposals Of Helium Research In China Based On Knowledge Graph, Huayang Li, Quanyou Liu, Dongya Zhu, Xiaoqi Wu, Chi Zhang, Zehui Shi

Bulletin of Chinese Academy of Sciences (Chinese Version)

Helium is a critical rare gas essential for aerospace, medical devices, and semiconductor production. With about 85% of its helium coming from imports, China’s advancement of exploration and development technologies is vital for national resource security. This study analyzes helium-related publications from CNKI (2000–2025) using advanced data visualization and statistical methods. It introduces a three-pronged approach–data-driven analysis, visual representation, and mechanistic explanation–to offer the first comprehensive examination of China’s helium exploration and development research, revealing its evolution and current state from multiple perspectives and providing fresh insights. By examining publication trends, institutional contributions, and evolving research priorities, the study maps …

Simulation And Projection Of Glaciers And Their Runoff In Xinjiang Based On Tgsgs, Zhongqin Li, Yefei Yang, Bowen Liu, Huilin Li, Zexin Zhan, Feiteng Wang, Chunhai Xu, Weibo Zhao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Glaciers are large flowing ice bodies formed from snowfall in cold regions. Due to the intrinsic physical properties of ice and the complexity of boundary conditions, physically based modelling of glacier change remains a global challenge. With support from the Chinese Academy of Sciences’ key science infrastructure program for the field station, the Tianshan Glaciological Station completed the Tianshan Glacier Station Glacier Simulator (TGSGS) in 2025. TGSGS features advanced representations of the physical mechanisms driving glacier change and multi-scale ensemble strategy, and is integrated with a reference glacier observation network based on terrestrial laser scanning (TLS), a low-temperature laboratory for …

Uptake And Fate Of Silver And Zinc Engineered Nanoparticles In Maize Under Single And Binary Dosing Soil Ecosystems, Lei Xu, Qingbo Yang, Xingmao Ma, Honglan Shi, John Yang, Hu Yang, Samira Mahdi, Ying Wang, Young Shin Jun

Chemistry Faculty Research & Creative Works

Recent agricultural applications of engineered metallic nanoparticles (ENPs) have raised concerns about their uptake and fate in plants. To understand this critical issue, this study investigated the fate and uptake of silver (Ag) and zinc oxide (ZnO) ENPs in maize (Zea mays L.) after single or binary ENP exposure in soil. Results indicated that both Zn and Ag elemental concentrations in roots increased with increasing ENP dosage. Ag NPs in the tissues were detected, but not Zn NPs. Ag NP concentration was 3 times higher in the roots than in the shoots at low Ag NP dosing, while Ag NP …

Fairhiveframes-1k: A Public Fair Dataset Of 1265 Annotated Hive Frame Images With Preliminary Yolov8 And Yolov11 Baselines, Vladimir Kulyukin, Reagan Hill, Aleksey Kulyukin

Computer Science Faculty and Staff Publications

In precision apiculture, the portable digital camera is a cost-effective sensor for capturing hive images or videos used to quantify different colony variables. Openly accessible, well-annotated, interoperable cell-level image datasets are still the exception rather than the norm. This shortage constitutes a major barrier to AI-driven approaches aimed at automating image-based comb analysis. In this article, we present FAIRHiveFrames-1K, a publicly available dataset of 1265 annotated hive frame images (1920 × 1080 PNG) designed to facilitate research in AI-intensive image-based comb analysis automation. The dataset, derived from a 2013–2022 U.S. Department of Agriculture–Agricultural Research Service multi-sensor research reservoir, includes 124,669 …

Phishing Restraint: University Simulated Phishing Campaigns, Alexander M. Abou Khir

Cybersecurity Undergraduate Research Showcase

Universities face heightened vulnerability to phishing attacks due to their open information-sharing culture and diverse user populations. This study examines how phishing exploits human factors within campus environments and evaluates three major training strategies: embedded phishing, microlearning, and role-based instruction to understand their individual and combined effectiveness. I explored studies that implement these strategies in pairs and use the strategies alone, identified trends in susceptibility reduction, behavioral reinforcement, and contextual relevance. I suggest that, while each method independently improves user awareness, multiple approaches offer stronger, more adaptable protection by addressing both psychological triggers and role-specific risks. The paper contributes a …

Leveraging Convolutional Neural Networks For Through-The-Wall Radar Imaging: Challenges, Impacts, And Future Directions, Tumaini Edgar, Abdulla F. Ally, Abdi T. Abdalla

Tanzania Journal of Engineering and Technology (TJET)

Through-the-wall radar imaging (TWRI) is an essential technology for military and rescue applications; however, its performance in detecting and visualizing high-quality images of targets behind walls is significantly degraded by multipath reflections and signal attenuation. This paper reviews the current state of TWRI and its challenges, and explores the transformative potential of deep learning, particularly convolutional neural networks (CNNs), in addressing these challenges. Peer-reviewed articles published from 2018 to 2024 were analysed to examine CNN applications in addressing TWRI challenges. The analysis reveals that using CNNs, TWRI systems can be more effective by filtering wall distortions, reducing noise, lowering computational …

The Texture Of A Threat: Adversarial Training, Cnns, And Obfuscated Malware Detection, Kaelyn Haynie

Senior Honors Theses

Accurately detecting malicious programs is an expanding field of research for machine learning (ML), with a novel approach incorporating a bytecode-to-image pipeline that produces images representative of software. These images are provided to convolutional neural networks (CNNs) to be examined for malicious pattern indicators. However, CNNs struggle to generalize these patterns effectively while still being robust against adversarial data, an issue which this research addresses with adversarial training. In this paper, three unique CNN architectures (a DBFS-MC-inspired baseline, MIRACLE, and PSP-CNN) are trained for binary classification with 15,000 benign and malicious software samples encoded into images for Android, Windows, and …

Tracing The Milky Way’S Evolution Through Its Star-Planet Systems, Rayna Rampalli

Dartmouth College Ph.D Dissertations

From individual planetary systems to the Milky Way's structure, stars are the linchpin connecting astrophysical scales. Through three complementary projects, my thesis leverages these connections and large stellar surveys to offer insight into the Galaxy's dynamical and chemical history and its role in shaping planet formation and evolution. (I) I developed Protify, an automated pipeline to measure stellar rotation periods in TESS light curves, enabling rotation-based ages for thousands of stars. Applying it to overdensities of stars in eccentric Galactic orbits, thought to be post-resonant signatures of spiral arm passages, revealed unexpectedly young rotators in dynamically old populations. Because such …

Bremsstrahlung Photons Emissions Measured At Different Rf Power In 28 Ghz Ecr Ion Source, Mwingereza John Kumwenda

Tanzania Journal of Engineering and Technology (TJET)

High-performance electron cyclotron resonance ion sources (ECRISs) generate large amounts of bremsstrahlung photons that affect the cryogenic systems due to the extra heat load that is produced. Thus, this study investigates the bremsstrahlung photons energy spectra at various RF powers, presenting some insight about the trends of the electron heating process inside the plasma. Bremsstrahlung photons from a 28 GHz ECRIS were measured at Busan center of Korean Basic Science Institute (KBSI). The gamma-ray detection system consists of three round-type NaI(Tl) scintillation detectors placed 620 mm radially from the beam axis at the extraction side of the ECRIS, and a …

Hijacking The Prompt: A Survey Of Prompt Injection Attacks, Detection, And Defense In Large Language Models, Edward J. Griggs

Cybersecurity Undergraduate Research Showcase

Prompt injection attacks, ranked the number-one vulnerability in AI systems by OWASP's 2025 Top 10 for Large Language Model Applications, remain largely unsolved, and this survey examines why. As large language models (LLMs) are deployed across enterprise workflows, agentic systems, and consumer tools, their fundamental inability to distinguish trusted instructions from untrusted user data has created a persistent and expanding attack surface. This paper presents a structured taxonomy of prompt injection attack vectors, including direct injection, indirect injection, multimodal attacks, tool and agent exploitation, hybrid chained techniques, and autonomous propagating threats. These vectors are mapped across five impact categories (data …

Emergent Dynamics In Multiplex Social Networks: Agent-Based Modeling Of Information Diffusion For Misinformation Control, Harshvardhan Prabhakar Ghongade, Anjali Ashokrao Bhadre, Shivani Agarwal, Harjitkumar Uttamrao Pawar, Harshal Subhash Rane

Northeast Journal of Complex Systems (NEJCS)

Information misrepresentation is widespread in multi-layered social networks which provide multiple avenues to communicate information. As such, it presents significant opportunities for both information integrity and public discourse to be undermined by disinformation. This paper outlines a new agent-based model, developed to capture emergent dynamics of multi-layered social networks and to help identify technical means to mitigate information misrepresentation in complex systems. A key component of this research includes a novel Multi-Layer Information Diffusion Model (MLIDM), integrating both cross-layer communication among agents, as well as heterogeneous agent behaviors and adaptive intervention strategies. Our methods employ a three-stage process to model …

Asymptotic Sensitivity And Adjoint Methods For Equation Discovery With Open-Source Implementation, Nathan Schill

Theses and Dissertations

The "on-the-fly" (OTF) method is a gradient-based approach to equation discovery. It makes use of (potentially limited) observational data, a data assimilation technique such as continuous data assimilation (also called nudging), and an error metric. From these it computes an asymptotic approximation of a simulated system's error sensitivity with respect to unknown parameters and utilizes any gradient-based optimization algorithm to perform parameter updates. These parameter updates may be done online or offline, and the model may be of a precisely specified form or simply a library of possible terms with potentially nonlinear parameters. We have applied the adjoint method to …

Recent Wetland Elevation Dynamics In Coastal Louisiana, Usa, Elizabeth Harris

LSU Master's Theses

Coastal marshes globally are increasingly vulnerable to accelerating relative sea-level rise (RSLR), which threatens their capacity to maintain elevation through feedbacks among sediment supply, vegetation productivity, hydrology, and soil processes. Although many marshes can persist under moderate rates of sea-level rise through vertical accretion and belowground biomass production, this resilience is strongly constrained by sediment availability and subsurface processes such as autocompaction and organic matter decomposition. High accretion is often assumed to confer marsh resilience; however, subsurface processes, particularly autocompaction driven by surface loading, can substantially offset elevation gains. Coastal Louisiana experiences among the highest rates of RSLR worldwide due …

Sonic Booms From Rockets: Measurements And Modeling, Mark Charles Anderson

Theses and Dissertations

Rocket sonic booms are produced when launch vehicles or boosters travel faster than the local speed of sound in the atmosphere, generating systems of conical shock waves. The purpose of this dissertation is to perform high-fidelity measurements of rocket sonic booms and to explain the physics behind the unique phenomena observed. After a thorough literature review on sonic booms produced during spaceflight operations, Part I of this dissertation deals with measurement and analysis challenges. One challenge is reducing contaminating noise effects on sonic boom perception metrics, addressed using a low-pass filtering method tied to the noise floor. A second challenge …

Characterizing The Unique Chemical Imprint Of On-Axis, Lower-Temperature Hydrothermal Flow To The Deep Ocean (Southern East Pacific Rise, 16.5°–18.0°S), Laura E. Moore, Randelle M. Bundy, Joseph A. Resing, Scott M. White, Tamara Baumberger, Peter N. Sedwick, Nathaniel J. Buck, Anson M. Antriasian, Isaac Keohane

Faculty Publications

In addition to high-temperature vents, lower-temperature flow (LTF) (< 300°C) is abundant along mid-ocean ridges and contributes globally-important fluxes of heat and water along with largely-unconstrained geochemical influences on the ocean. We examined the impact of on-axis LTF on the chemical composition of the overlying water column (< 40 m above seafloor) along the 16.5°–18.0°S sector of the ultrafast-spreading southern East Pacific Rise using autonomous underwater vehicle Sentry surveys and conductivity-temperature-depth rosette casts. LTF sites were typically spatially isolated from high-temperature systems and imparted unique chemical signatures to the overlying ocean. Water column samples impacted by LTF exhibited low particulate iron:sulfur ratios and high methane: total-dissolvable manganese ratios, whereas samples influenced by high-temperature venting exhibited opposite trends. We confirmed that LTF imparts a distinct and measurable chemical signature to the water column, independent from high-temperature vents. Isolated, on-axis LTF will be important to consider when assessing hydrothermal circulation impacts upon ocean biogeochemistry.

Real And Perceived Barriers To Effective Use Of Cataract Surgical Supplies, Caitlin Davie, Lindsay K. Cloud, Scott Burris, Shaina Shiwdin, Brooke Sherry, Christina R. Prescott, Joel Schuman, David Palmer, David Chang, Daniel Parra, Cordelia Kwon, Margaret A. Tharp, Cassandra L. Thiel

Wills Eye Hospital Papers

INTRODUCTION: Cataract surgery, among the most common procedures worldwide, significantly contributes to climate change through both solid waste and air pollution, highlighting the urgent need for targeted interventions. Implementation faces hurdles including legal constraints and concerns about infection risks and malpractice.

METHODS: This article examines federal and state regulatory structures around two key waste reduction strategies: reduction of multidose medications and distribution of partly-used operating room medication to patients post-surgery.

RESULTS: We find little-to-no legitimate regulatory barriers to either waste reduction practice. Dispensing and redistributing partly-used medication has been codified in law in some states. Evidence-based reports indicate minimal risks …

Modeling Flood-Induced Cascading Disruptions In The Indian Electronics Supply Chain Using Influence Network Analysis, Surendra Orupalli, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

This study investigates flood induced disruptions in the Indian electronics supply chain using influence network analysis. Monsoon floods are recurring hazards that significantly impact economic activities, logistics, and industrial productivity. This study integrates district-level rainfall data (2020 to 2025) with supply chain network models to quantify cascading failures. The methodology applies rainfall thresholds (≥ 300 mm/month) to identify flood-prone districts and constructs a stochastic influence matrix representing inter-firm dependencies. Flood propagation dynamics are modeled iteratively with a propagation coefficient (α = 0.6) and convergence threshold (ε = 10⁻⁴). The resulting disruption profiles are mapped onto company-level revenues calibrated to India-specific …

Unlocking Inexpensive Training Through Overcoming Weaknesses In Dataset Distillation, Connor Wilhelm

Theses and Dissertations

Dataset distillation is a nascent technique that promises accelerated neural network training. In particular, distillation produces a highly compressed dataset that can train a neural network in as little as a single optimization step. However, distillation has not been adopted for real-world use cases due to weaknesses, such as poor approximation of the original task, unclear interpretability, high costs of the initial distillation, and poorly elaborated use cases. Here, we present five papers that advance task distillation towards real-world adoption. The papers focus on: distilling reinforcement learning environments, interpreting distillation-produced datasets, improving distillation performance using ensembling, examining distillation's generalization to …

Umm (Ultimate Memory Manager): A Note–Taking App Built From Scratch, Caleb M. Early

ASPIRE 2026

For my honors project, I’m building UMM, an advanced note-taking application built entirely from scratch. I’m someone who takes many notes and primarily uses OneNote and Notion, but over time have found myself wanting something faster and more flexible than any note-taking application I could find. UMM is my attempt to create the note-taking app I wish I had, as well as learn how to create such a program.

Instead of relying on pre-made code, I built my own systems for how documents are structured, edited, saved, as well as how the cursor moves, text is formatted, and how selections …

Climate Change And Transportation, Paul J. Marchese

Open Educational Resources

This module examines how climate change is affecting transportation systems across multiple sectors, including roads, rail, air, maritime, and active transportation. It highlights key climate trends such as rising temperatures, sea level rise, and extreme weather, and explains how these factors disrupt infrastructure, operations, and safety. The module also explores the economic, operational, and policy challenges associated with maintaining resilient transportation systems under changing environmental conditions. Finally, it presents a range of adaptation and mitigation strategies, emphasizing engineering solutions, sustainable technologies, and data-driven decision-making.

Dimensionless Ratios And Processes Controlling Volumetric Bioretention Performance, Andrew Charles Hiestand

Master's Theses (2009 -)

Urbanization of previously natural land cover has spurred the innovation and implementation of green stormwater infrastructure (GSI) to combat increased surface runoff due to impermeable areas and a changing climate. Bioretention has been a popular choice in design due to its small footprint and proven effectiveness in retaining stormwater runoff and limiting discharges to receiving surface waters. However, their event-to-event performance variability is difficult to explain due to a number of confounding and interacting influences that distort cross-site analyses including inter-event drying and antecedent soil moisture conditions, geometric size and media properties, and event magnitude. This study applies and evaluates …

Cybersecurity Integration In Research Stage Connected Devices Within Healthcare Environments, Klemens Koszarek

Master's Theses (2009 -)

The rapid growth of connected devices in healthcare environments has significantly expanded the cybersecurity threat landscape, extending the potential risks beyond traditional hospital networks. Regulatory guidance from the FDA and risk management frameworks such as the NIST Cybersecurity Framework (NIST CSF) provide an approach for managing cybersecurity risk in connected systems. However, these principles are not always applied during early stages of device development. As a result, security consideration may be deferred until later stages of development, allowing for vulnerabilities to persist in systems as they move toward clinical or commercial deployment. This study presents a structured method for integrating …

Brown Pelican (Pelecanus Occidentalis) Groundings On A Four-Lane Divided Highway In South Texas: A Comparative Study Using Citizen Science, Bradley Evan Beer, Kevin W. Ryer, Md. Saydur Rahman, John H. Young Jr., Richard J. Kline

School of Integrative Biological & Chemical Sciences Faculty Publications

The population of the once-endangered brown pelican (Pelecanus occidentalis) has increased over the past several decades and is now considered fully recovered. However, in south Texas, the combined effects of weather patterns, transportation infrastructure, and brown pelican biology have led to road mortalities on State Highway 48 (SH 48) at the Carl “Joe” Gayman Bridge. To mitigate these mortalities, the Texas Department of Transportation modified traffic barriers on SH 48. We aimed to examine the effect of the barrier change and determine which weather variables influence brown pelican groundings on SH 48. Citizen scientists monitored sections of SH …

Understanding The Role Of Tiktok As A Source Of Support For Cyberbullying Victims, Saba Iqbal

Theses and Dissertations

Cyberbullying poses a significant threat to teenagers and young adults, who often seek support and advice online. Little is known about the support and advice shared online for victims of cyberbullying and whether it is helpful. In this study, we used qualitative thematic analysis to examine a sample of 150 TikTok videos that give support or advice for cyberbullying victims. We identify 33 unique pieces of support and advice across 5 categories, with differences in tone and delivery among different types of videos. We then evaluated the quality of 33 unique pieces of cyberbullying advice in a user study with …

Ownership Duration In The U.S. Business Jet Market, Yuchen Hu

SACAD: Scholarly Activities

This study analyzes ownership duration in the U.S. business jet market using FAA registry data as of February 16, 2026 (N=12,359). The analysis reveals a structured distribution with a mean of 5.86 years and a median of 5.00 years. Crucially, retention varies by acquisition status: new aircraft owners exhibit an average hold of 7.36 years, whereas pre-owned aircraft holders show a significantly higher turnover of 5.11 years, with most resales occurring within a 3–7-year window. These findings suggest that ownership behavior is driven by structured asset management and lifecycle planning, providing a predictive framework for identifying aircraft replacement and trade-in …

The Impact Of An Interactive Open Education Textbook For An Undergraduate Introductory Chemistry Course For Nonmajors, Erin Avram

Chemistry Faculty Publications

Reading informational text is a critical skill across most professions. Unfortunately, students are less likely to purchase the required course materials now compared to 2010. A free, interactive text was developed for an introductory chemistry course for non-STEM majors. This involved remixing existing texts and incorporating interactive activities to engage students during the learning process and provide opportunities for them to gauge their learning. Based on the results of a student survey, 82% of students reported that it was very important to them that the text was free and 80% of students who responded reported that they used the eText …

Modeling Bitcoin Dynamics Using Differential Equations, Boone M. Fleenor

Departmental Honors & Graduate Capstone Projects

In this thesis, we develop and analyze two nonlinear systems of ordinary differential equations to model Bitcoin price dynamics. Analytical techniques are used to obtain exact or approximate solutions where possible. Then, numerical simulations using a fourth-order Runge–Kutta method are employed to explore system behavior beyond analytically tractable regimes. Finally, model outputs are compared to historical Bitcoin price data using normalized and resampled time series. These results suggest that deterministic models can provide meaningful insight into the structural behavior of Bitcoin markets, while highlighting the need for stochastic or time-dependent extensions for more realistic modeling.

Engineering Ferrate(Vi) For Water And Wastewater Treatment: Translating Science Into Technology, Zepei Tang, Zhenli He, Yang Deng

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Over the past five decades, ferrate(VI) (FeO42–) for water and wastewater treatment has remained largely at the laboratory scale, with limited pilot- and full-scale implementation. This gap between sustained research and scarce real-world deployment places the technology in the Valley of Death─a high-risk stage of development─and highlights the need for an engineering-centric approach to enable practical application. This article presents an engineering framework to guide the development and translation of ferrate(VI) technology for water and wastewater treatment. From a system perspective, ferrate(VI) technology comprises three core subsystems: generation, treatment, and solid–liquid separation. Technology maturity depends on both the advancement of …

Integrating Multi-Source Data With Machine Learning Techniques To Upscale Wetland Carbon Dioxide Fluxes, Abdullah Sulaiman Abdullah Al Fazari

Electronic Theses and Dissertations 2020 - Present

Accurate quantification of atmospheric carbon dioxide (CO₂) fluxes in wetland ecosystems is essential for understanding their role in both regional and global carbon dynamics, particularly in the context of climate change. However, the spatial and temporal heterogeneity of wetlands presents major challenges for developing reliable upscaling models. This research developed and validated a comprehensive framework to upscale CO₂ fluxes across the Everglades National Park (ENP) and Big Cypress National Preserve (BCNP) in South Florida through the integration of multi-source datasets, including AmeriFlux eddy covariance (EC) tower measurements, NASA’s BlueFlux airborne CO₂ data, and multispectral satellite imagery from Landsat 8 OLI …