Digital Commons Network^™

Mumm Vs. Minium: A Tale Of Two Quarries, Kale Link, Amanda Peng

SACAD: Scholarly Activities

In 2025, a discrepancy was discovered in the field numbers of a selection of mammal fossils, which had been mistakenly catalogued as originating from the Minium Quarry in Graham County, KS instead of the Mumm Quarry in Rawlins County, KS. While both quarries belong to the Ogallala Formation, they demonstrate differing biostratigraphic ages, faunal assemblages, and taphonomic settings. Mumm is Clarendonian aged, while Minium is Hemphillian. To correct this issue, all the Mumm specimens were assigned to an updated locality with more precise geographic and biostratigraphic data.

David Berkowitz, Enzyme-Assisted Organic Synthesis & Nsf Officer, Mark A. Griep, David B. Berkowitz

Department of Chemistry: Faculty Interviews

Dr. Dave Berkowitz was born in Urbana, Illinois. He earned his bachelor's degree in chemistry from the University of Chicago, where he did undergraduate research. Next, he earned his doctorate from Harvard University. However, his advisor, Steve Benner, moved from Harvard to ETH Zurich, also called the Swiss Federal Institute of Technology. Dave accompanied him to Zurich, where he completed his dissertation work. When Dave returned to the U.S., he did a postdoc with the legendary Samuel Danishefsky at Yale University. In 1991, he joined UNL as an assistant professor of chemistry and quickly rose through the ranks. Dave is …

Mathematical Logic And Computer Language, Yueun Park

SACAD: Scholarly Activities

Fundamental principles of computer programming comes from mathematical logic. Mathematics enables programming languages to interpret and execute complex instructions. This project explores the possible application of mathematical logic within programming languages by developing a Boolean logic calculator in C++. The program implements a stack-based algorithm to convert infix notation (which we often use) to postfix notation (which computers can evaluate) and uses subsequent functions to evaluate the postfix notation. The program focuses on logic operators NOT, AND, and OR, classified with specific precedence hierarchies. Program analysis shows that the processes have linear time complexity, that is, O(n). The result suggests …

Application Identification With Pfsense, Snort, And Openappid In Academic Lab Networks, Minh-Khanh Vu

Journal of Cybersecurity Education, Research and Practice

This paper evaluates the practical capabilities and limitations of a widely used open-source network security stack—pfSense firewall, Snort Intrusion Detection System (IDS), and OpenAppID detectors—in academic cy- bersecurity laboratories and small-to-medium enterprise (SME)-like environments. In a controlled virtual testbed, we measure application-level and feature-level identifi- cation performance for major applications (Facebook, YouTube, Zoom) using the pfSense/Snort/OpenAppID configuration. The stack achieves 97% application-level identification accuracy for these applications in our lab dataset, drawing on a library of 3,374 OpenAppID detectors. However, our experiments reveal a substan- tial feature-level detection gap: specific functions such as Zoom file transfers and Facebook messaging can- …

Negotiating Digital Identities With Ai Companions: Motivations, Strategies, And Emotional Outcomes, Renkai Ma, Shuo Niu, Lingyao Li, Alexander Hirth, Ava Brehm, Rowajana Behterin Barbie

Computer Science

AI companions enable deep emotional relationships by engaging a user's sense of identity, but they also pose risks like unhealthy emotional dependence. Mitigating these risks requires first understanding the underlying process of identity construction and negotiation with AI companions. Focusing on Character.AI (C.AI), a popular AI companion, we conducted an LLM-assisted thematic analysis of 22,374 online discussions on its subreddit. Using Identity Negotiation Theory as an analytical lens, we identified a three-stage process: 1) five user motivations; 2) an identity negotiation process involving three communication expectations and four identity co-construction strategies; and 3) three emotional outcomes. Our findings surface the …

Creating Disability Story Videos With Generative Ai: Motivation, Expression, And Sharing, Shuo Niu, Dylan Clements, Hyungsin Kim

Computer Science

Generative AI (GenAI) is both promising and challenging in supporting people with disabilities (PwDs) in creating stories about disability. GenAI can reduce barriers to media production and inspire the creativity of PwDs, but it may also introduce biases and imperfections that hinder its adoption for personal expression. In this research, we examine how nine PwD from a disability advocacy group used GenAI to create videos sharing their disability experiences. Grounded in digital storytelling theory, we explore the motivations, expression, and sharing of PwD-created GenAI story videos. We conclude with a framework of momentous depiction, which highlights four core affordances of …

The Promises And Perils Of Using Llms For Effective Public Services, Erina Seh-Young Moon, Matthew Tamura, Angelina Zhai, Nuzaira Habib, Behnaz Shirazi, Altaf Kassam, Devansh Saxena, Shion Guha

Health Services and Informatics Research

Governments are the primary providers of essential public services and are responsible for delivering them effectively. In high-stakes decision-making domains such as child welfare (CW), agencies must protect children without unnecessarily prolonging a family’s engagement with the system. With growing optimism around AI, governments are pushing for its integration but concerns regarding feasibility and harms remain. Through collaborations with a large Canadian CW agency, we examined how LocalLLM and BERTopic models can track CW case progress. We demonstrate how the tools can potentially assist workers in opportunistically addressing gaps in their work by signaling case progress/deviations. And yet, we also …

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 …

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 …

Analysis And Study Of Telemetry Systems For Directional And Horizontal Well Drilling, Jahongir Abdiganiyev Erkin Ugli, Sherali Halloqovich Umedov

Technical science and innovation

The article discusses the issues of reducing non-productive drilling time during the construction of directional and horizontal wells. The main focus is on the analysis of drilling conditions in complex geological and high-temperature environments. Particular attention is paid to drilling conditions in the territory of the Republic of Uzbekistan, with a specific study of data from the Boysun and Ustyurt regions. An analysis and study of the performance of telemetry systems available on the market, as well as their main technical characteristics, have been conducted. Key factors affecting the accuracy of wellbore trajectory measurements under various geological and technical conditions …

Design Of Virtual Impedance Controller For Parallel-Connected Converters In A Microgrid, Manyanda Makoye, Francis Mwasilu, Peter M. Makolo, Jackson Justo

Tanzania Journal of Science

This paper addresses the significant challenge of inaccurate power sharing among Distributed Generators (DGs) in islanded microgrids, which is primarily caused by mismatched feeder and line impedances. Conventional decentralized control solutions often fail to ensure accurate power sharing, especially when line impedances are resistive. To overcome this, the paper proposes a robust, coordinated Virtual Impedance Control (VIC) strategy for DGs. This method implements fixed virtual resistance and virtual inductance to standardize the output impedance characteristics of parallel-connected inverters, thereby minimizing impedance discrepancies and enhancing system stability through increased damping. The theoretical analysis and design of the VIC were validated through …

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 …

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 …

Statistical Inference Is Not Moral Reasoning: The Case Against Ai On Hospital Ethics Boards, Elan J. Haronian

Seaver College Research And Scholarly Achievement Symposium

As generative AI becomes more integrated in healthcare, it seems inevitable that AI will eventually be used on hospital ethics committees. However, before implementation, their roles need careful consideration. Although AI promises to reduce costs, increase efficiency, and reduce human workloads, there are important ways in which it is limited, especially when human emotion and connection are crucial, as in clinical ethics boards.

In this paper, I highlight several problems preventing AI from being useful on hospital ethics boards. These include issues of opaque reasoning (the “black box” problem), liability, transparency, privacy, and consent. While there are proposed frameworks for …

The Core-Modulation Architecture (Cma): A Structural Overview Of Hallucination As Structural Mismatch, Griselda Poe

Publications and Research

Hallucination is defined not as factual error but as a structural failure of alignment across target, layer, and constraint.

Within the Core-Modulation Architecture (CMA), cognition proceeds through layered processing and requires layer-specific termination conditions. Hallucination arises when Modulation-level termination is registered as completion while Core-level resolution has not occurred, producing structurally ungrounded but locally coherent outputs.

Detection is therefore structural rather than content-based, focusing on layer mismatch and termination failure.

This document presents a minimal structural account of hallucination within the CMA framework.

Differentials As Models: Constructing A Differentials-Within-Limits Framework For First-Year Calculus And Examining Students' Understanding Of Limits, Differentials, And Derivatives Within It, Alexander A. Swindler

Theses and Dissertations

Work in first-year calculus has clearly shown the power that treating differentials (such as dx) as tiny quantities affords for first-year calculus learning, yet a traditional limits-based approach leaves no room for them. While some researchers have loosely described informal differentials and limits within the same paradigm, their actual conceptual definitions and relationships have not been explicitly constructed. Continued progress in this area could benefit from theoretical consideration of (a) providing clearer intuitive definitions for differentials inside a limits-based approach to calculus, and (b) defining more exactly the relationships between differentials and limits. In this study, I propose a theoretical …

Advice For Incorporating Ai Tools Into Your Legal Practice, Celia Bigoness, Robert A. Mackenzie, David J. Reiss

Cornell Law Faculty Publications

We have been speaking with many lawyers and law students about using generative artificial intelligence (AI) tools in their legal practice. We are struck by the fact that many of them have not been experimenting much, if at all, with the tools that are available to them - although many acknowledge that their clients are increasingly integrating generative AI into their businesses. We have been integrating a lot of these tools into our own professional lives, and here are some tips to help lawyers and law students get comfortable with AI tools that can help them, in big ways and …

Diffeomorphisms In Quantum Black Hole Interiors, Ian William Bornhoeft

Electronic Theses and Dissertations 2020 - Present

We begin with an introduction to canonical Loop Quantum Gravity. We then introduce a notion of residual diffeomorphism covariance in quantum Kantowski–Sachs (KS), describing the interior of a Schwarzschild black hole. We solve for the family of Hamiltonian constraint operators satisfying an associated covariance condition, as well as parity invariance, preservation of the Bohr Hilbert space of Loop Quantum KS and a correct (naive) classical limit. We further explore imposing minimality of the number of momentum shift terms, and compare the solution with other Hamiltonian constraints proposed for Loop Quantum KS in the literature. In particular, we discuss a lapse …

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 …

Escaping Isolation: An Analysis Of Virtual Machine And Container Breakout Vulnerabilities, Felix Iov

Cybersecurity Undergraduate Research Showcase

Cloud computing providers rely on multi-tenant architectures to maximize resource efficiency. This infrastructure depends on virtualization, which provides isolation between clients. This comes primarily in the form of Virtual Machines (VMs) and Containers. However, “breakout attacks” or “escapes” are a critical threat where attackers bypass these isolation layers to gain unauthorized access to the host system and neighboring environments. This paper surveys virtualization escape threats and analyzes three case studies: a runc container escape (Leaky Vessels), a VMware ESXi VM escape (VSOCKPuppet), and an NVIDIA GPU container escape (NVIDIAScape). Each demonstrates different attack surfaces, including file descriptor misuse, kernel driver …

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 …

Butte Priority Soils Operable Unit (Bpsou) 2026 Monthly Progress Report. Consent Decree For The Butte Priority Soils Operable Unit. Civil Action No. Cv 89-039-Bu-Seh, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Machine Learning Based Models For Simulation And Analysis Of Bulk Earth Melt System, Abin Shakya

LSU Doctoral Dissertations

Understanding the segregation of bulk Earth melt systems into metallic (core) and silicate (mantle) phases under high-pressure and high-temperature conditions is central to modeling Earth’s interior, yet relevant experimental and computational studies remain limited. This work develops a machine learning–based simulation pipeline that iteratively couples first-principles (quantum mechanical) calculations with neural network training to generate high-fidelity force fields. Using major-element Fe–Mg–Si–O melt systems, with and without H and N, as testbeds, we demonstrate that this framework enables large-scale molecular dynamics simulations at near first-principles accuracy. We further introduce a sequence of phase identification methods, progressing from statistical binning of elemental …

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 …

A Comprehensive Survey Of Agentic Ai: Design Principles, Security Risks, And Ethical Consideration, Md Shaba Sayeed

ATU Scholars Symposium

In the past several years, the world has managed to transition away from simple automation to independent AI systems. Agentic AI is an agent that can work independently, carrying out all essential plans and implementations without any kind of supervision from a human being. This review has tried to demonstrate the transformative impact that Agentic AI brings to contemporary models of intelligence by means of synthesis of perception, reasoning, and goal. We utilized the phrases Agentic AI, autonomous AI, multi agent systems as keywords in Google Scholar, ScienceDirect, arXiv, and other digital libraries. We have used these 38 main papers …

Computational Approaches To Laser Alignment And Phase Correction, Joseph E. Temple

ATU Scholars Symposium

The goal of our work is to automate the tedious and delicate process of optical alignment (rotating mirrors, shifting lenses by millimeters, and iterating endlessly) in the context of generating vortex beams from a Gaussian laser beam. We create vortex beams by illuminating a digital hologram displayed on a spatial light modulator (SLM). Two main issues arise: misalignment and phase imperfections in the input beam. If the beam does not pass directly through the center of the SLM, or if it deviates from an ideal Gaussian profile, the resulting vortex beam becomes distorted.

Last semester, we developed two methods to …

Creating A Floating Volumetric Display, Joy Skaggs, Hope Skinner

ATU Scholars Symposium

The public has long been interested in futuristic technology, especially ‘holograms’ and their possibilities, evidenced by pop culture icons such as Iron Man and the popularity of the Sci-Fi Genre. The popular term ‘hologram’ actually describes the phenomenon of a volumetric display, where light is directed to form 3D forms in the air. Attempts to create these volumetric displays began as early as 1988 with creators like Gregg Favelora and Alan Sullivan. As technology improved, so too did the ability to make the futuristic ‘hologram’ a reality.

Another common form of these interactive holograms is the floating display, which may …

Proactive Mental Health Assistance Via Agentic Llm Chatbots With Retrieval-Augmented Generation, Shaira Wajiha

ATU Scholars Symposium

Mental health challenges such as anxiety and depression are widespread, yet often remain unaddressed due to stigma, financial barriers, limited access to professionals, or personal reluctance. To address this gap, we present an accessible AI-powered chatbot that provides preliminary conversational support with empathetic, context-aware responses. The chatbot is trained and evaluated on two publicly available counseling conversation datasets from Huggingface, enabling it to learn and maintain therapeutic dialogue patterns. We compare three advanced LLMs, such as Llama3.1, Mistral 7b, and Qwen3, evaluating them on relevance, empathy, conciseness, and contextual understanding, and all models demonstrate high response quality. Incorporation of a …

Automatic Labeling Of Real-World Pmu Data: A Weakly Supervised Learning Approach, Yunchuan Liu

Research Days

This paper presents a weakly supervised learning framework for real-world event identification in transmission networks using phasor measurement unit (PMU) data. The growing integration of renewable energy sources has introduced greater variability in grid conditions, intensifying the need for accurate event detection. Although high-resolution PMU measurements enable event identification to be formulated as a classification problem, traditional supervised learning approaches are hindered by the scarcity of labeled data, and acquiring large-scale, high-quality labeled PMU datasets remains prohibitively expensive. To overcome this challenge, we propose an automated PMU data-labeling method that combines domain knowledge with machine learning techniques through the use …

Physics-Informed Neural Network Solution Of The 2d Helmholtz Equation With A Gaussian Source, Theodoros Panagiotakopoulos, Chris Velissaris, Aristotelis Nikolaos Rapsomanikis

Faculty Scholarship and Creative Works

We present a physics-informed neural network (PINN) framework for solving the complex-valued two-dimensional Helmholtz equation with a localized Gaussian source and spatially varying permittivity. Starting from Maxwell’s equations, the frequency-domain scalar Helmholtz formulation under transverse electric (TE) polarization is derived and enforced directly within the neural network loss function. The model employs a sinusoidal representation network (SIREN) architecture to capture the oscillatory nature of wave solutions and incorporates the Sommerfeld radiation condition to impose open boundary conditions. Training is performed using a hybrid collocation strategy combined with a two-stage optimization procedure consisting of Adam followed by L-BFGS. Numerical experiments in …