Digital Commons Network^™

An Ion-Neutral Reaction To Form Cyanobenzene And Ethynylbenzene In Titan’S Atmosphere, Rachel M. Huchmala, Vincent J. Esposito

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The ion-neutral reaction between cyanoacetylene (HC₃N) and phenyl anion (C₆H₅^–) leads to the formation of cyanobenzene (C₆H₅CN) and the ethynyl anion (C₂H^–) via a submerged, exothermic pathway. Through a different mechanism, the same two reactants also form ethynylbenzene (C₆H₅C₂H) and CN^–. These new reactions can be a foundation for the production of substituted benzenes using molecules currently present on Saturn’s largest moon, Titan. Cyclic aromatic molecules like C₆H₅CN and C₆H_{5 …}

A Systematic Approach For Controlling Tem Sample Thicknesses, Monte Kozell

Physics Faculty Publications and Presentations

Historically, TEM prep has been an artisan craft without a systematic workflow that ensures quantified control over TEM sample thickness. Over- and under-thinning is a significant problem in the TEM prep process. A direct measurement process was demonstrated to control the final thickness of the TEM lamella. Final lamella thickness was controlled by directly measuring lamella thickness in real time using a 10–15 kV SEM while performing secondary electron imaging at the mill position, allowing for (human-mediated) closed-loop processing. We demonstrated the utility of this technique by systematically thinning five TEM samples to discretely target thicknesses ranging from 100 nm …

K 1-6 Is A Photoionised Interstellar Medium Nebula Shaped By A Fast-Moving Hot White Dwarf In A Triple System, Jaroslav Merc, David Jones, Ana Escorza, Henri M. J. Boffin, Nicole Reindl, Michael Abdul-Masih, Thomas Masseron, Paulina Sowicka, Jan Kára, Jorge Jorge García-Rojas

Physics & Astronomy Faculty Publications

Aims. K 1-6 has long been classified as a planetary nebula (PN) hosting a binary central star; however, it has remained poorly studied due to its faintness. The central star exhibits pronounced photometric variability whose origin is still unclear. We present a comprehensive characterisation of the K 1-6 system, including the physical properties of its stellar components and the nature of the surrounding nebulosity.

Methods. We conducted a multi-wavelength analysis combining optical and UV spectroscopy obtained with the Gran Telescopio Canarias, the Telescopio Nazionale Galileo, the Nordic Optical Telescope, and the Hubble Space Telescope. We also present long-term multi-band ground- …

Knowledge-Enhanced Feature Store For Operational Ml And Llm Workflows, Saurabh Suman

Master's Theses

Modern machine learning (ML) organizations rely on feature stores to manage training and production data, yet as catalogs grow to thousands of features, semantic management becomes the bottleneck: discovery, governance, and metric selection remain largely manual. This thesis proposes and evaluates a knowledge-enhanced feature store that augments a dual-plane store with a hybrid knowledge layer—relational provenance, a lineage graph, semantic vector retrieval, and an online cache—and an LLM-driven multi-agent layer for profiling, matching, grounded metric recommendation, and pipeline generation. A working prototype was evaluated across three task families—semantic profiling, feature-matching retrieval, and discovery—using classification, ranking, and operational metrics computed by …

Fully Anharmonic Infrared Spectra Of Neutral Polycyclic Aromatic Hydrocarbons With Up To 38 Carbons, Nolan J. H. White, Vincent J. Esposito, Christiaan Boersma, Louis J. Allamandola, Jesse D. Bregman, Alexandros Maragkoudakis, Pasquale Temi, Ryan Fortenberry

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Interstellar aromatic infrared band (AIB) spectra show agreement with presently computed anharmonic spectra for various types of polycyclic aromatic hydrocarbons (PAHs) determined using a novel semiempirical quantum chemical method. Since the AIB spectrum is a blend of emission spectra from a vast number of different PAHs, likely with an array of different molecular structures, the spectra for a sample set of 31 PAHs ranging in size from naphthalene (C₁₀H₈) up to circumbiphenyl (C₃₈H₁₆) are combined, giving consideration to almost all PAH structural motifs. The computed numerical quartic force fields coupled to second-order …

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Final 2026 Interim Site- Wide Surface Water Monitoring Quality Assurance Project Plan (Qapp) (Dated August 28, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Final 2026 Interim Site-Wide Groundwater Monitoring Quality Assurance Project Plan (Dated August 28, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Hands-On Ransomware: An Experiential Wannacry Case Study For Undergraduate Cybersecurity Education, Eli Creek Richmond, Thomas R. Devine

Military Cyber Affairs

Ransomware represents one of the most disruptive threats in the cyber landscape, yet hands-on malware analysis remains rare in undergraduate cybersecurity curricula. This paper presents the design, implementation, and evaluation of an experiential learning module centered on the WannaCry ransomware case study, deployed in a senior-level course at West Virginia University. Students performed static and dynamic analysis using industry-standard tools. Pre- and post-module assessments demonstrated measurable gains in self-reported competency across seven technical dimensions. The module's competencies align directly with DoD Cyber Workforce Framework Work Role 212, Cyber Defense Forensics Analyst, supporting education-to-workforce pipeline development.

From Framework To Toolchain: Implementing Zero Trust Architecture In Cloud-Native Environments For Dow Compliance, Shelby C. Snyder

Military Cyber Affairs

Federal agencies face a fiscal year 2027 target for enterprise-wide Zero Trust deployment, but NIST SP 800-207A defines logical components without identifying the Kubernetes technologies that implement them. This paper proposes a three-tier mapping of the Policy Engine, Policy Administrator, and Policy Enforcement Point to service mesh, microsegmentation, and perimeter tooling, stating the criteria by which each component is classified. It then applies a defined rubric to six Zero Trust vendors across component alignment, Kubernetes capability, federal authorization posture, and evidence quality, finding that no single vendor covers all three tiers. The mapping is a testable architectural proposition; a Stage …

Characterizing Advanced Persistent Threats With Cyber Attack Flow Metrics, Tyler Miller, Caleb Chang, Shouhuai Xu

Military Cyber Affairs

Cyber attack campaigns vary not only in scale but in structure, yet conventional characterizations often reduce them to a single dimension such as technique count or impact severity. In this paper we extend the concept of cyber attack flows by defining three new metrics, novelty, technique complexity and flow complexity. Then we characterize the attack flows of three advanced persistent threat campaigns using these metrics and draw insights regarding their capabilities. Our findings include that low novelty does not equate to low attack capabilities and that exploitation of an internet-facing appliance is a common initial attack vector.

Semantic Shields: Automating Critical Infrastructure Defense Via Nlp-Driven Ransomware Profiling, Henry Trowbridge, Ian Zalcberg, Ryan Schley, Carter Yagemann, Natasha Phan, Srikar Maduposu, Vimal Buck

Military Cyber Affairs

Ransomware poses a growing threat to critical infrastructure, where successful attacks can disrupt operational technology (OT) and industrial control systems (ICS) with significant public safety consequences. However, attributing ransomware incidents to specific threat actors remains challenging due to ransomware-as-a-service ecosystems, actor rebranding, and the obfuscation of traditional indicators of compromise. This paper presents Semantic Shields, an NLP-driven attribution framework that leverages BERT-generated semantic embeddings and DBSCAN clustering to profile ransomware actors through the linguistic characteristics of ransom notes. Using a dataset of 295 ransom notes from 189 distinct threat groups, the framework achieved an 87.2% true positive clustering rate and …

Closing The Interpretability Gap: Explainable Ml-Based Malware Detection For Defensive Cyberspace Operations, Tashi Stirewalt, Sean Hodgson, Puumaaya Tahiru, Assefaw Gebremedhin

Military Cyber Affairs

This paper presents an end-to-end, explainable malware triage pipeline designed for defense-oriented cyber operations. It combines high-performance static detection methods with analyst-centered interpretability. Utilizing the EMBER 2024 Windows PE subset, we train and evaluate four classifiers and select LightGBM as the production model based on its predictive performance, inference efficiency, and compatibility with exact tree-based attribution. The deployed system consists of four sequential components: PE feature extraction, malware probability scoring, dual explainability (using SHAP and LIME), and large language model (LLM) report generation, all integrated within a Flask web interface. On a temporal test set of 1,080,000 samples, LightGBM achieves …

Statistical Triangulation: Weighing Multiple Statistical Tools In Macro-Level Housing Research, Julio Montanez, Amy Donley, Jacquelyn Reiss

Journal of Applied Disciplines

Homelessness and housing research has a detection problem, in which understanding housing issues (e.g., substandard housing) is plagued by problems like undercounting and incomplete data. To partially compensate for these pitfalls, the current research engages in an exercise aiming to sharpen the statistical approach to homelessness and housing research. The macro-level sample included Florida’s 27 Continuums of Care geographies (composed of one or more Florida counties). The dependent variables were sheltered homelessness, energy-based substandard housing, and plumbing-based substandard housing. The independent variables were misdemeanor partner violence rates, felony partner violence rates, high school non-completion rates, urbanicity, and population burdens of …

The Fossil Pearls Of The Million-Pearls Flowstone, Fairgrounds Room, Fort Stanton Cave, New Mexico Usa, Victor J. Polyak, Paula P. Provencio, Yemane Asmerom

International Journal of Speleology

‘Fossil’ cave pearls in the Fairgrounds Room of Fort Stanton Cave form two distinct layers in a flowstone sample, FS-14-2. The flowstone in the Fairgrounds Room covers a mud-silt bank and the extinct streambed that extends across the room. Uranium-series dates of two pieces of flowstone from this room, one piece from the higher end of the flowstone (FS-14-1, devoid of pearls), and another piece from the lower end of the flowstone (FS-14-2, rich in pearls), show that the flowstone was deposited during the Last Glacial period (60,000 to 11,000 yr BP).  The two cave-pearl layers in FS-14-2 yielded U-series …

A Calibrated And Conformal Deep Learning Framework For Trustworthy Antinuclear Antibody Pattern Recognition With Selective Referral To Experts, Hussein Ali Hussein Al Naffakh, Ahmed Dheyaa Radhi, Raghdah Maytham Hameed, Muntaha Abdullah Reishaan, Fouad A. Majeed, Rozaida Ghazali

Karbala International Journal of Modern Science

Reading antinuclear antibody patterns on human epithelial cells by indirect immunofluorescence is the reference screen for systemic autoimmune rheumatic diseases, but it is slow, subjective, and variable between observers. Deep learning reaches high accuracy on this task, yet most systems return a single prediction without stating how reliable it is, which is unsafe in a diagnostic workflow. This paper presents an intelligent decision support framework built around a single calibrated uncertainty signal. That signal is the control variable for four reliability modules: confidence calibration, conformal prediction, error detection, and selective referral. A feature space out of distribution detector serves as …

Re: Approval Letter For The Uncontrolled Surface Flow Areas Drainage C 95% Design Remedial Action Work Plan, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Conditional Approval Letter For Butte Priority Soils Operable Unit (Bpsou) Final Diggings East Dewatering Treatability Study Pre-Design Investigation Work Plan (Pdiwp) (Dated September 8, 2026) And The 2026 Final Diggings East Dewatering Treatability Study Quality Assurance Project Plan (Qapp) (Dated September 8, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Challenges, Trends, And The Role Of Lstm In Ai-Based Predictive Maintenance Of Electrolyzers For Solar Hydrogen Systems: A Review, Yani Koerniawan Kuatno, Muhamad Zahim Sujod

Turkish Journal of Electrical Engineering and Computer Sciences

The transition toward low-carbon energy systems has increased interest in hydrogen as a clean energy carrier, with solar-driven water electrolysis emerging as a promising technology due to its high efficiency and compatibility with renewable energy sources. However, dynamic operating conditions and intermittent renewable input accelerate electrolyzer degradation, reducing reliability and system lifespan. Predictive maintenance (PdM), supported by artificial intelligence (AI), offers a data-driven approach to anticipate failures and improve operational durability. This review systematically investigates AI-based PdM approaches for electrolyzers, with an emphasis on long short-term memory (LSTM) networks and Internet of things (IoT) integration. Following PRISMA 2020 guidelines, 35 …

Cuip-X25: A Real-World Network Intrusion Dataset For Next-Generation Ai-Driven Security, Arshad Iqbal, Sohail Asghar

Turkish Journal of Electrical Engineering and Computer Sciences

The efficacy of artificial intelligence (AI) in intrusion detection systems (IDS) is critically dependent on high-fidelity training data. However, as detailed in the manuscript's literature review, existing benchmark datasets are predominantly synthetic, outdated, or imbalanced and fail to capture the complexity of the contemporary threat landscape. To bridge this gap, this study introduces CUIP-X25, a novel real-world cyber-attack dataset captured over a four-month period using a dionaea honeypot deployed on a public network. Unlike synthetic alternatives, this dataset provides an authentic representation of modern adversarial tactics, techniques, and procedures, encompassing 3.16 million real events across ten distinct attack categories, including …

Empowering Edge Intelligence Through Reparameterized Lightweight Transformers And Distributed Inference, Hosein Esmaeili, Mohammad Ali Afshar Kazemi, Reza Radfar, Nazanin Pilevari

Turkish Journal of Electrical Engineering and Computer Sciences

Deploying advanced transformer-based models on resource-constrained edge devices remains a significant challenge due to their high memory footprint and substantial compute requirements. In this paper, we propose a reparameterized transformer framework that integrates High-Rank Factorization (HRF) during training, layer merging at inference, and dynamic, load-balanced distributed inference across multiple devices. To further reduce resource usage, our framework supports mixed-precision quantization down to 4-bit, enabling flexible accuracy–latency–energy trade-offs. Experimental evaluations on the ESC-50 environmental sound dataset demonstrate that our method matches or exceeds the performance of larger baseline models while using 20–30% fewer parameters, achieving up to 48% latency reduction in …

Non-Gradient Quaternion Training Matrix Modifications For Color-Image Distillation, Tahsin Shahnewaz, Megdam Ahmed Chowdhury, Nikolay Metodiev Sirakov

Student Publications

This paper develops a new multi-stage image distillation method that combines two well known techniques. In the first stage, our method creates a matrix from all training images. In the next stage, it adapts a modified principal component analysis (M-PCA) approach to transform the training matrix. In the third stage, Singular Value Decomposition (SVD) fur ther refines the training-image matrix through low-rank reconstruction and controlled row selection. In the fourth stage, rotation of small 2 ×2 matrix blocks on the entire left singular matrix is conducted. The upper m (user-selected number) rows of the reconstructed matrix are selected and transformed …

Measurement-Aware Zero-Phase Iterative Learning Control For Robust Regulation Of Nonideal Boost Converters In Electric Vehicle Fast Charging, Aytaç Altan, Mohammed S. Alzaidi, Cağfer Yanarateş

Turkish Journal of Electrical Engineering and Computer Sciences

Integrating battery energy storage with DC-DC boost converters for electric vehicle fast charging exposes the regulator to ageing-induced parameter drift, periodic load pulses, and, critically, the nonidealities in the output-voltage sensing chain. This paper proposes a measurement-aware, zero-phase iterative learning control scheme for robust output-voltage regulation of a nonideal boost converter whose parameters are matched to those of a commercial Texas Instruments TPS6102x battery regulator. The controller combines an inner proportional-integral stabilizing loop with an outer zero-phase learning law that updates a feedforward correction based on the sensor-captured output trajectory; a forward-backward robustness filter suppresses the amplification of measurement noise …

Portrait: Holistic Data Visualization Using Neural Networks, Chayan Maitra

Doctoral Theses

With the exponential growth of complex data across domains, effective visualization has become increasingly crucial for understanding relationships hidden within high-dimensional spaces. However, existing visualization techniques often struggle to effectively capture and represent such high-dimensional data. Motivated by this challenge, we have developed NeuroDAVIS, a neural network model designed to visualize high-dimensional data by extracting meaningful latent representations through deep feature extraction. While NeuroDAVIS has successfully addressed the visualization aspect, we have soon recognized the necessity of identifying the most relevant features that contribute to the visualization and downstream analysis. To address this issue, we have extended our framework and …

From Detection To Segmentation: Adapting Yolo26 For Surface Crack Delineation, Mohammed Al-Mustafa, Israa H. Ali

Journal of Intelligent Informatics, Networking, and Cybersecurity

Surface crack delineation plays an important role in infrastructure inspection because accurate pixel-level mapping of cracks can support condition assessment, maintenance planning, and automated monitoring of roads and other civil surfaces. However, recent crack segmentation methods often depend on heavy network designs or prompt-based foundation models. It also remains unclear how a lightweight detection-oriented model behaves across different data organizations and unseen images. This study therefore investigates whether YOLO26m-seg, the medium segmentation variant of the recent YOLO26 family, can be adapted into an effective and practical pipeline for surface crack delineation. The proposed workflow has four main steps. First, binary …

Spatiotemporal Variations Of Tidal Asymmetry Along The Coast Of Taiwan: Characteristics And Implications, Ting-Chieh Lin, Tai-Wen Hsu, Tzu-Chun Huang, Chun-Yuan Lin

Journal of Marine Science and Technology–Taiwan

This study presents the first systematic investigation into the spatiotemporal characteristics and evolutionary trends of tidal asymmetry along the coast of Taiwan from 2003 to 2022, employing a moving window method combined with the S_TIDE toolbox.  By quantifying the skewness of the Main Tidal Asymmetry Combinations (MTAC) and their temporal variations, the study reveals significant regional disparities between the eastern and western coasts.  The western coast is primarily dominated by the M2-M4 combination, with the northwestern region exhibiting a flood dominance pattern and the southwestern region characterized by ebb dominance.  Conversely, the eastern coast, attributed to its open topography and …

Synchronous Deep Reinforcement Learning For Optimized Storage Assignment Of Ship Blocks, Gawon Lee, Jaehyeon Heo, Misung Kim, Hyerim Bae

Journal of Marine Science and Technology–Taiwan

This paper presents a deep reinforcement learning (RL) framework for optimizing block storage allocation in shipbuilding yards. During the shipbuilding process, vessels are constructed in block units to maximize the operational efficiency. Following assembly, these blocks must be stored in limited yard spaces, creating a complex variant of the binary packing problem. This storage allocation problem is further complicated by operational constraints, including the barge capacity and transportation time restrictions. Moreover, poor storage decisions can lead to redundant block movements, which can adversely affect downstream processes and increase operational costs. To resolve this problem, a policy-gradient-based synchronous RL model was …

Decision Support Tool For The Maintenance Of Meter Gauge Railway Permanent-Way Infrastructures: A Concept Paper, Hamisi J. Maulid, Beatus A.T Kundi, Juma M. Matindana, Ismail W. R. Taifa Dr

Tanzania Journal of Engineering and Technology (TJET)

A Decision Support Tool (DST) represents a transformative way of modernising maintenance practice on the permanent-way infrastructure of Meter Gauge Railway (MGR). Maintenance practice remains largely reactive, as the MGR plays a strategic role in transporting both freight and passengers, resulting in inefficient resource allocation, high operational risk, and growing Lifecycle expenses. This concept paper explores the potential and the design challenges for a DST that combines fuzzy analytic hierarchy process (Fuzzy-AHP) modelling, multi-criteria decision analysis (MCDA), Geographic Information Systems (GIS) and predictive machine learning (ML) analytics for evidence-based, future-oriented maintenance management. The paper draws on peer-reviewed studies from …

Hydrothermal Alteration Mapping Of The Northern Coongan Greenstone Belt Using Remote Sensing Imagery, Meaza Bogale, Elias Woldeyohanis

Journal of Sustainable Mining

Archean greenstone belts are well known for their ore deposits, diverse lithostratigraphy, and well-preserved evidence from the early Earth. The Northern Coongan Greenstone Belt is an Archean greenstone belt that is part of the Eastern Pilbara Craton of Western Australia. The rock units of this area have the potential to be sources of valuable mineral deposits, which could be economically beneficial for extraction. Studies have been conducted in the northern Coongan greenstone belt, mostly using geological field methods and geophysical interpretations, excluding remote sensing methods for mapping mineral indices. Therefore, this study aims at providing surface mineral distribution maps and …

From Data To Victory: The Race For Analytic Superiority In Warfare, Robert Grossman, Emily Goldman

Joint Force Quarterly

Artificial intelligence technologies have reached a tipping point after decades of development. They are diffusing widely across defense and national security applications. Twenty-first century warfighters rely on analytic models in all systems, at all echelons, and in all domains. As more powerful models built on ever larger data sets become ubiquitous, militaries are in a new competition to deploy artificial intelligence. Operational art must embrace “analytic superiority.” This is the operational advantage from collecting and ingesting data, building robust models and computing infrastructure, deploying the models into operational systems, and denying adversaries' ability to do the same

This article explains …

How Euler Could Have Done It: Euler And An Integral Of Ramanujan, Alexander Aycock

Euleriana

We present a derivation of a definite integral discovered by Ramanujan (1887–1920) in his 1915 paper "Some Definite Integrals," from formulas and ideas already developed by Euler (1707–1783). Additionally, it is argued why Euler did not discover Ramanujan's integral himself, although he had all tools required for this task at his disposal.