Digital Commons Network^™

Model Unification: A Systematic Approach For The Cluster Expansion, Kolten Barfuss

Theses and Dissertations

A systematic approach for model unification of cluster expansion models is developed and demonstrated. The method builds on previous work with the Manifold Boundary Approximation Method (MBAM) to identify supremal models. The work is motivated by the exercise of unifying cluster expansion models – characterized by Π matrices – for two binary alloys that share one atomic species to form a model for the ternary alloy. The result is the Supremal Π Algorithm, a systematic unification algorithm that relies on an MBAM-informed understanding of models and on the singular value decomposition. The algorithm yields ΠΛ, a Π matrix for the …

Inc3vits Model: A Hybrid Architecture To Accelerate And Reduce Complexity For The Deepvariant Model For Variant Calling, Mustafa Al-Saffar, Sura Z. Al Rashid

Karbala International Journal of Modern Science

Deep learning has revolutionized genomic variant calling, yet the computational cost of current systems continues to limit scalability. We present a controlled efficiency study of DeepVariant-style pileup architectures under identical training and inference conditions, comparing architectural downsizing with a hybrid CNN–local attention design. Inc3ViTs pairs a streamlined InceptionV3 stem with a lightweight local attention head based on patch tokenization and windowed self-attention, enabling a direct comparison with a CNN-only reduced Inception baseline. Across whole-genome and whole-exome short-read datasets, Inc3ViTs reduces training time by ~40–50% and reduces inference runtime relative to the original DeepVariant. The CNN-only baseline indicates that most speedups …

Modelling Method Of Unmanned Vehicle Dynamics Based On Neural Network, Jun Wang, Min Liu, Xiaochuan Zhang, Yishan Ding, Juhui Feng, Ye Zhuang

Journal of System Simulation

Abstract: To address the challenges of high data acquisition costs of test data on dynamic characteristics between tires and soft terrain and low speed of numerical calculation for unmanned vehicles in complex terrestrial environments, a modeling method of unmanned vehicle dynamics based on a neural network was proposed. Tire-terrain contact dynamics models were built by using discrete element method (DEM) simulations for tire-terrain contact and experimental data, thereby creating a dataset of tire contact forces for various tire materials in terrestrial environments. The neural network was applied to regressively learn the dataset, and a nonlinear neural network tire model was …

Construction Of China’S Marine Protected Area System In 15th Five-Year Plan, Ke Duan, Danhong Chen, Keqiang Li, Limin Han, Zhengyan Liu, Dongliang Lu, Xiulin Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The establishment of the marine protected area (MPA) system constitutes a critical component of the national initiative to comprehensively advance the development of a nature reserve system centered on national parks. This study explores on domestic and international development trends from aspects such as conservation strategies, international policies, high seas protection, and development trends. It also sorts out and analyzes the construction status of marine protected area systems in China and the United States. Centering on issues in China related to spatial layout, management systems, policies and laws, scientific research support, high seas governance, and land-sea management, the study puts …

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 …

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 …

Techno-Enviro-Economic Analysis Of Precipitated Calcium Carbonate Production From Carbon Dioxide In Cement Industry Flue Gas And Calcium Hydroxide, Natalia Debora Panggabean, Widodo Wahyu Purwanto

Journal of Materials Exploration and Findings

CCUS is a technological solution to reduce emissions from the cement industry, which is the second largest CO2-intensive industry. This study aims to analyze technical, economic, and environmental performance of Precipitated Calcium Carbonate (PCC) synthesis in cement industry flue gas. The process simulation includes the CO2 capture system from cement plant, CO2 captured used as feedstock for PCC synthesis process through its reaction with calcium hydroxide. The simulation was carried out using ASPEN Plus software. Technical analysis was performed to determine the CO2 capture efficiency and PCC synthesis efficiency. Economic analysis was conducted to calculate CO2 capture cost and production …

Feasibility Analysis Of Thermal Oxidizer To Determine Remaining Life Using Fitness- For-Service Level 3 Method, Yudhi Yudistirawan, Donanta Dhaneswara, Wahyuaji Narottama Putra, Gama Widyaputra, Dewi Kurnia Suci, Agung Putra Mahardhika

Journal of Materials Exploration and Findings

An aged thermal oxidizer (TOX) in the oil and gas industry necessitates a comprehensive evaluation to ensure its continued safe operation. This study presents a Remaining Life Assessment (RLA) and a Fitness for Service (FFS) evaluation for the four main components of the TOX, in accordance with API 510, API 579/ASME FFS-1, and ASME BPVC Section VIII Div-1 standards. The investigation includes the determination of maximum stress and maximum temperature required to assess the operational viability of the reactor. The four components are radiant, convection, transition, and stack sections—were modeled using the finite element method (FEM). Following the geometric modeling, …

Organic Synthesis Of A Hydrazine Functionalized Ammonium Compound For Improved Capture Of Aldehyde Metabolites From Exhaled Breath, Po'iu N. Burgo

Undergraduate Theses

Breath analysis has emerged as a non-invasive and inexpensive way to screen for respiratory diseases. This technique involves measuring concentrations of specific metabolites found in exhaled breath that serve as a biomarkers for disease. A subclass of volatile organic compounds called α,β-Unsaturated aldehydes, products of the lipid peroxidation mechanism, are underrepresented as biomarkers of lung cancer. These have been found to have relatively increased concentrations in the exhaled breath of lung cancer patients compared to a healthy patient. One of the reasons that these metabolites have been underreported is that the techniques used to measure and characterized exhaled metabolites do …

Dynamics And Energetics Of Fast Waves From The Earth's Surface To The Lower Thermosphere, Richard L. Walterscheid, Michael P. Hickey Ph.D.

Publications

We use a Full Wave Model to examine the dynamics and energetics of waves that can be excited in the troposphere by a large explosive event. We find resonant structures in phase speed wavenumber space that can have substructures with distinct properties. The primary waves found are Lamb waves and fast deep waves (denoted 𝐿′) that have a hybrid internal-external wave nature and were recently identified in observations. Lamb waves and thermospherically ducted waves are branches of two continuous forms separated by a gap in which Lamb waves are preempted by Lamb speed waves oscillating with the buoyancy frequency. We …

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 …

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 …

Quantum Scattering Of Hc5n And Para-H2 On A New Potential Energy Surface, Shan Gao, François Lique, Ernesto Quintas-Sánchez, Richard Dawes, Jérôme Loreau

Chemistry Faculty Research & Creative Works

In the interstellar medium (ISM), non-local thermodynamic equilibrium situations are common due to low density, and one needs to consider the effect of molecular collisions in order to interpret the observations. Among the species detected in the ISM, cyanopolyynes, with the general molecular formula HC_2n+1N (n = 1, 2, …), are characterized by large dipole moments and small rotational constants and constitute an indispensable class of candidates for the sensitive tracers of local density and temperature. We present a study of the collisional (de-) excitation of HC₅N by para-H₂ (p-H₂) in its ground …

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 …

Drainage Proximity And Sinkhole Occurrence In Sivrihisar (Central Turkey): A Comparative Analysis Of Linear, Poisson, And Negative Binomial Regression Models, Bilge Bingül, Emrah Pekkan, Resul Çömert

International Journal of Speleology

This study investigates the relationship between sinkhole occurrence and distance to drainage in the Sivrihisar region (Central Turkey) and evaluates the suitability of different regression approaches for modeling clustered count data in karst terrains. A comprehensive inventory of 104 sinkholes developed within the Neogene lacustrine limestones of the Akpınar Formation was compiled using official records, remote sensing analyses, and detailed field surveys. Sinkhole occurrences were analyzed relative to a drainage network derived from a high-resolution Digital Surface Model and grouped by proximity to drainage lines. Linear Regression (LM), Poisson Regression (PR), and Negative Binomial Regression (NBR) models were comparatively applied …

Desialylation And Sialidase Secretion From Monocytes And Macrophages Upon Lps Activation, Yu Zhao, Majdi Aljohani, Morgan Pychowycz, Xue-Long Sun

Chemistry Faculty Publications

Introduction The cell surface expresses a dense layer of glycans often terminated with sialic acids (Sias), known as sialylation, which represents different cellular statuses. Meanwhile, the removal of Sias from the glycans catalyzed by sialidase (desialylation) is also involved in many biological processes, such as inflammatory responses. Previous studies demonstrated that desialylation is involved in LPS/TLR4 signaling pathway and pro-inflammatory cytokine production. In this report, we systematically profiled desialylation and sialidase activity, expression and secretion from monocytes and macrophages upon LPS activation.Methods THP-1 monocytes and THP-1 macrophages were activated by LPS (100 ng/mL) for 24 hours. The cellular Sia changes …

When Generative Ai Is Intimate, Sexy, And Violent: Examining Not-Safe-For-Work (Nsfw) Chatbots On Flowgpt, Xian Li, Yuanning Han, Di Liu, Pengcheng An, Shuo Niu

Computer Science

Content Warning: This paper contains sexually explicit and violent images and text. User-created chatbots powered by generative AI offer new ways to share and interact with Not-Safe-For-Work (NSFW) content. However, little is known about the characteristics of these GenAI-based chatbots and their user interactions. Drawing on the functional theory of NSFW on social media, this study analyzes 376 NSFW chatbots and 307 public conversation sessions on FlowGPT. Findings identify four chatbot types: roleplay characters, story generators, image generators, and do-anything-now bots. AI Characters portraying fantasy personas and enabling hangout-style interactions are most common, often using explicit avatar images to invite …

Advancing Cyclic Ion Mobility Mass Spectrometry For Structural Characterization, Isomer Discrimination And Gas-Phase Ion Chemistry, Sudam Shivaji Mane

Theses and Dissertations

This dissertation focuses on the development and application of high-resolution ion mobility-mass spectrometry (IMS-MS) methodologies for gas-phase separation and structural characterization of small molecules, with particular emphasis on epimers, positional isomers, and protomers. In addition to structural separations, this work investigates fundamental aspects of gas-phase ion chemistry using IMS-MS in combination with collision-induced ion activation and dissociation techniques. Advanced separations were performed using cyclic traveling-wave ion mobility spectrometry (cyclic TWIMS), implemented in a commercial cyclic ion mobility-mass spectrometry (cIMS) platform, to systematically evaluate both the capabilities and limitations of high-resolution IMS in resolving subtle structural differences. Initial studies demonstrated that, …

Characterizing User-Reported Risks Across Llm Chatbots, Lingyao Li, Renkai Ma, Zhaoqian Xue, Junjie Xiong

Computer Science Faculty Research & Creative Works

As Large Language Models (LLMs) become increasingly integral to daily life, users are engaging with multiple LLM chatbots for various needs; however, prior research on LLM risks often remains lab-based or focuses on single LLMs like ChatGPT or singular risks like privacy. To gain a multi-risk, cross-chatbot understanding of user experiences, we analyze Reddit discussions around seven major LLM chatbots using the NIST AI Risk Management Framework. We find that user-reported risks are unevenly distributed and chatbot-specific: ChatGPT is associated with safety and fairness concerns, Gemini with privacy, and Claude with security and resilience. Less frequent risks, such as explainability …

From Oversight To Insight: Transforming Cybersecurity Governance In Boardrooms, Tooba Aamir, Georgia Psaroulis, Marthie Grobler, Helge Janicke

Research outputs 2022 to 2026

Cybersecurity governance is increasingly critical in a digital economy, with board directors playing a central role in shaping organisational resilience. Directors are pivotal in setting cybersecurity strategies and carrying fiduciary obligations that extend to digital risk oversight. This study examines the cybersecurity literacy and governance practices of Australian board directors through a qualitative interview study with 13 participants. Findings reveal a substantial gap in directors' knowledge and confidence, undermining effective oversight and informed decision-making. This deficit limits their ability to interrogate risk reports, challenge assumptions, and steer investment in line with organisational resilience goals. In response, we propose a Board …

Coral Reef Hydrodynamics: A Critical Review Of Roughness Indices And Their Characteristic Complexity, Faisal Karim, N. A. K. Nandasena, Lujain Kuruvachalil, Mohamed M. Mohamed, James P. Terry

All Works

This study provides a systematic review of hydrodynamic roughness in coral reef systems, focusing on drag coefficient (Cd), Manning's roughness coefficient (n), friction factor, and rugosity metrics. A structured bibliometric analysis was conducted using Scopus and Web of Science databases, including field measurements, laboratory flume experiments, and numerical studies validated with physical data. Results show substantial variability in roughness parameters across scales and environments. Reported drag coefficients range from 0.002 for smooth sandy beds to values exceeding 7.0 in complex mangrove-reef systems, with typical reef crest values between 0.05 and 0.30. Manning's n varies from 0.01 in smooth channels to …

Pre-Experiential Constraint Reconstruction: A Structural Account Of The Prior Layer In Dialogue With Jung, Griselda Poe

Publications and Research

Experiences commonly described as pre-experiential memory—such as immediate recognition, familiarity without prior exposure, and the sense of "already knowing"—are typically interpreted as the retrieval of stored content. However, this storage-based account does not provide a structurally consistent explanation of how such content is preserved prior to experience or reactivated in a form that aligns with present input.

This paper extends the three-layer cognitive architecture developed in prior work in this series (Poe, 2026n), in which cognition operates across Core processing, Modulation, and an operationally inaccessible Prior layer that supplies constraints to all processing.

This paper proposes an alternative account in …

Dual History Enhancement With Hybrid Hypergraph-Graph Networks For Temporal Knowledge Graph Reasoning, Kailun Ye, Xiangjie Kong, Yuchao Zhang, Xuan Wang, Linan Zhu, Jiaxin Du, Guojiang Shen, Jianxin Li

Research outputs 2022 to 2026

Temporal Knowledge Graph (TKG) reasoning seeks to predict future events by analyzing historical data, where the effective leverage of both local and global historical facts proves crucial. Existing approaches employ graph neural networks (GNNs) and recurrent neural networks (RNNs) for local evolution patterns, complemented by statistical methods to enhance attention to global facts, demonstrating efficient predictive capabilities. However, traditional GNNs, constrained by their low-order neighborhood aggregation design, inherently fail to model potential high-order dependencies among facts. Furthermore, existing global history modeling approaches may introduce irrelevant historical information that interferes with prediction tasks. To address these limitations, we propose a Dual …

Does Culture Translate? A Case Study On Artificial Intelligencegenerated Text Concerning Japanese-Style Employment, Kanji Kitamura

Languages, Literatures, and Cultures Faculty Publications

Translation matters to international business when it has a discernible impact on firm performance or critical business processes. Current developments include machine translation, which is evolving in tandem with generative artificial intelligence (AI). On one hand, useful translation apps have become available to help the public communicate internationally. On the other hand, recent research concludes that even machine translation's best output still requires post-editing by a human. This argument implies that a machine-translated, grammatically accurate text may not always make sense to a human audience, possibly because of a semantic-pragmatic issue beyond the lexical level. This paper regards it as …

How To Effectively Trap Invasive Crayfish: A Discrete Life Stage Mathematical Model, Rini Pattison

Seaver College Research And Scholarly Achievement Symposium

The red swamp crayfish is an invasive species introduced into several streams within the Santa Monica Mountains (SMM). Crayfish predation decimates native aquatic species. The Mountains Restoration Trust (MRT) has worked to remove crayfish through regular trapping in Malibu Creek.

A prior student created a crayfish life cycle model with trapping, which we expand to better predict the efficacy of crayfish removal efforts in the SMM. We separate crayfish based upon life stages and sizes. We construct and parameterize this discrete crayfish population model with and without trapping. We use literature and crayfish removal data from MRT to fit the …

Two-Dimensional Inverse Scattering Solution Using Nurbs Expansion And A Deep Learning Method, Meisam Shafaee

Turkish Journal of Physics

This paper presents a novel framework for solving two-dimensional (2D) inverse scattering problems by integrating nonuniform rational B-spline (NURBS) parameterization with convolutional neural networks (CNNs). Tra ditional pixel/voxel-based deep learning methods often suffer from high dimensionality and discretization artifacts, while purely geometric approaches lack robust inversion mechanisms. To address these limitations, we propose a hybrid frame work where the relative permittivity profile of an unknown scatterer is compactly represented as a NURBS surface, parameterized by a sparse set of control points and weights. This approach reduces the problem dimensionality over 16 times. On the other hand, using NURBS expansion ensures …

Variability On M-Dwarf Stars And Its Effect On Exoplanet Detection, Aylin Garcia Soto

Dartmouth College Ph.D Dissertations

Understanding stellar magnetic activity is crucial for exoplanet research: activity can mask signatures from exoplanet detection and characterization, and impact planetary habitability. This is particularly important for M dwarf stars, which are highly magnetically active, displaying spectroscopic and photometric signatures of flares and rotational variability. In this thesis, I will present two complementary perspectives on M dwarf magnetic activity. First, I will discuss a study of short-term variability. I made new ground-based observations of 77 M dwarfs and tested the connection between chromospheric emission and photometric variability. I find a weak positive correlation between H$\alpha$ luminosity (tracing magnetic heating) and …

From Stability To Spintronics: A Comprehensive High-Throughput Investigation Of 2d Mf4 Lieb Lattices, Uğur Yorulmaz

Turkish Journal of Physics

The research on two-dimensional (2D) materials which have intrinsic magnetism and exotic electronic struc tures is an important quest in condensed matter physics. The Lieb lattice offers a unique platform for studying strongly correlated electron phenomena. In this work, we systematically investigated the structural, dynamical, mechanical, electronic, and magnetic properties of monolayer transition metal tetrafluorides (MF4, where M = Ag, Cd, Cr, Cu, Fe, Hf, Mn, Mo, Nb, Ni, Pd, Pt, Rh, Ru, Sc, Ta, Ti, V, W, and Y) arranged in a 2D Lieb lattice, using first-principles calculations based on density functional theory (DFT) with Hubbard (U) corrections. Our …

Analysis Of The Effects Of Magnetic Field, Heat Transfer, And Thermal Radiation On Blood Flow Through Bifurcated Artery To Enhance Tumor Treatments, Abdullahi Isah, Dauda Gulibur Yakubu, Ali Musa

Tanzania Journal of Science

The work presents the effects of some pertinent parameters on blood flow through bifurcated artery to enhance tumor treatments. Combining appropriately the basic equations, together with the fractionalized Maxwell fluid model allow us to determine the velocity, temperature and concentration of blood flow through bifurcated artery. The study adopted the Atangana-Baleanu fractional time derivative on fluid model to describe the non-Newtonian behavior of blood flow. The numerical simulations were performed using the combined Laplace transform and the method of undetermined coefficients and the results obtained with the aid of Mathcad software were simulated and presented graphically. From the graphical results, …

Ai Exposure And The Future Of Work: Tasks, Skill Demand, And Education, Erik Vasilauskas, Michael Horrigan

External Papers and Reports

No abstract provided.