Digital Commons Network^™

Can Machines Testify? Llms And The Boundaries Of Testimonial Epistemology, Michael J. Cummins

Philosophy Summer Fellows

As Large Language Models and AI chatbots become increasingly prevalent, pressing questions are raised about whether beliefs formed through LLM interactions carry the same epistemic weight as beliefs formed through human testimony. How we answer this question depends on whether LLMs can function as testifiers, a role which is typically assumed to require a human or human-like agent. This assumption has gone largely unexamined, yet its consequences are significant: if LLM outputs cannot constitute testimony, then the justificatory tools of testimonial epistemology are unavailable to any beliefs formed through LLM interaction. This paper challenges that assumption. It first argues that …

Entity Labels Are Not Entity Signals: A Framework For Observable Relevance In Document Re-Ranking, Utshab Kumar Ghosh, Shubham Chatterjee

Computer Science Faculty Research & Creative Works

Entity-aware document retrieval uses query-associated entities as ranking signals, assuming that semantically relevant entities are also useful retrieval signals. We show this assumption is insufficient - and explain why. Unlike terms, which are ground-truth observations, entity links are hypotheses produced by an imperfect linker: an entity can be topically central yet provide no discriminative signal if the linker fires indiscriminately across relevant and non-relevant documents. We formalize this as a distinction between Conceptual Entity Relevance (CER) - whether an entity is topically related to a query - and Observable Entity Relevance (OER) - whether its observed presence in a collection …

Sustainable Consumer Behavior Modeling: A Complex-Systems Approach To Neuromarketing, Preethi Nanjundan, Nupoor Sanjay Bhute, Ragini Topre, Lijo Thomas

Northeast Journal of Complex Systems (NEJCS)

This study examines the application of complex-systems modeling to neuromarketing data for gaining deeper insights into the mechanisms underlying sustainable consumer behavior. It investigates how neural and biometric responses, interpreted through a systems-based perspective, can uncover dynamic interactions, feedback mechanisms, and emergent behavioral patterns influencing sustainable purchase decisions. The research explores the impact of sustainability-oriented marketing stimuli on long-term behavioral intentions by emphasizing the interconnected roles of cognitive processing, emotional engagement, implicit associations, and collective consumer dynamics. Through simulation-based modeling and structural analysis, the study demonstrates how subconscious neural responses and affective mechanisms mediate the relationship between marketing interventions, consumer …

Fundamental Solutions To The Fractional Heat Operator, Jacob Flores

Math Theses

In this thesis, we are interested in showing the existence of a fundamental solution to the fractional heat operator. The fractional heat operator is a nonlocal linear operator used to model the time evolution of anomalous diffusion processes whose applicability arises in a wide variety of fields in the physical sciences, engineering, economics, and finance. Fundamental solutions to a partial differential operator are a class of generalized solutions formulated with rich mathematical analysis grounded in classes of well-behaved smooth functions referred to as test functions and their continuous linear functionals referred to as distributions. A primary tool that we use …

Simulations Of Skyrmions And Merons, Ryan Friesen, Aidan Kirk, Tom Carroll, Xuemei Cheng

Physics and Astronomy Summer Fellows

Skyrmions and merons are particle-like spin structures that are found in specific magnetic materials. Due to their stability and nanoscale size, these quasiparticles have been proposed as promising candidates for qubits in quantum computing applications. Our goal is to design materials that can host and stabilize these quasiparticles. Skyrmions and merons exist only under specific conditions, and the parameter space for these materials is vast. Thus, we use the simulation package MuMax3 to run simulations to test the viability of potential materials to simplify this search. We present on our simulations of these skyrmions and merons. This work was supported …

Oregon State Rank Assessment For Ithuriel's Spear (Triteleia Laxa), Lindsey K. Wise

Institute for Natural Resources Publications

Oregon state conservation status assessment for Ithuriel's spear (Triteleia laxa)
 using NatureServe methodology, 2026.

Editorial: Participatory And Just Governance: Empowering Local And Indigenous Communities, Melissa Haeffner, Maiko Sakamoto, Jenia Mukherjee, Hong Quan Nguyen, Soyo Takahashi

Environmental Science and Management Faculty Publications and Presentations

The papers in this Research Topic (RT) extend insights on the roles of social relations, institutional arrangements, Indigenous ways of knowing, local knowledge, and decisionmaking participation in shaping water governance and practice. Despite efforts to predict flows and possible hazards, we continue to observe “unintended consequences” when humans interact with waterscapes. What we often learn, we argue, is that what appears “unintended” often reflects a deliberate architecture of exclusion; one that becomes legible only when social power relations are placed at the center of analysis alongside hydrological variables. Doing so may illuminate where injustice complicates intentions and what difference participatory …

Glassy Magnetic Freezing Of Interacting Clusters In Materials Related To The Lk-99 Family, Serafim Teknowijoyo, Domenico Napoletani, Vahan Nikoghosyan, Armen Gulian

Mathematics, Physics, and Computer Science Faculty Articles and Research

We report reproducible magnetization anomalies appearing below room temperature in copper-doped apatite materials belonging to the LK-99 family synthesized via hydrothermal methods. These anomalies are observed consistently across samples prepared under comparable conditions. Although the extracted Mydosh parameter lies within the range often associated with vortex-glass behavior in superconductors, a detailed analysis of DC magnetization, AC susceptibility, field dependence, and magnetic memory effects demonstrates that the observed phenomena are not related to superconductivity. Instead, the data are consistent with glassy magnetic freezing of interacting clusters. Compositional and structural analysis identifies covellite (CuS), one of the constituent phases in these multiphase …

Re: Conditional Approval Letter For The Draft Final 2024 Unreclaimed Sites Sampling: Ur-21 Site Evaluation Summary Report, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit Diggings East Final 100% Remedial Design Package Submittal, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Using A Cell Flux Model To Investigate Phytoplankton Growth And Macromolecular Allocation Under Iron Limitation, Margaret Bernish, Meng Gao, Jongsun Kim, Benoit Pasquier

School of Earth, Environmental, & Marine Sciences Faculty Publications

Global biogeochemical models are powerful tools used to interpret observations and empirical data, create hypotheses, and make predictions. Many of these models, however, represent marine microbes as static stoichiometric reactions that convert nutrients into biomass. To better constrain the biological processes that control nutrient cycling in the global ocean, we extend the Cell Flux Model of Phytoplankton to explore the impact of dissolved iron concentration on the allocation of macromolecules and elemental ratios within phytoplankton cells. This model is supported by data obtained from a range of incubation experiments conducted with phytoplankton of varying species and size categories. Model output …

2026 July 23 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites: Ur-27 Site Evaluation Summary Report (Sesr), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) 2025 Butte Reclamation Evaluation System (Bres) Field Evaluation Summary Report And Technical Recommendations Proposal, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites: Ur-46 Remedial Action Work Plan (Rawp), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites: Ur-46 Site Evaluation Summary Report (Sesr), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Revised Draft Final Unreclaimed Sites: Ur-07 Site Evaluation Summary Report (Sesr), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Stylometric And Formal Patterns In The Scholarly Impact Of Scientific Literature, Joshua Ange, Eric Godat, Rajani Sudan

SMU Journal of Undergraduate Research

Scientific communication is typically tied to promoting public engagement and interest in science, increasing scientific literacy, and playing an essential role in policymaking. The success of public communication of scientific findings is largely associated with secondary characteristics of research (e.g. the style of writing and presentation), rather than the primary content or research quality. But it is unclear to what extent the success of scientific literature intended for working scientists is influenced by those same secondary characteristics. Does the writing style of scientific articles impact their success in academic spheres? In this study, we explore the stylometric and formal characteristics …

Image Fusion Based On Deep Learning With Different Locations And Sizes Of Objects, Baneen Al-Kalabi, Tawfiq Al-Assadi

Journal of Intelligent Informatics, Networking, and Cybersecurity

Multi-focus image fusion combines partially focused images into a single all-in-focus composite. Existing object-based methods assume precise spatial and scale alignment across source images, an assumption that frequently fails in Misaligned Multi-Focus Dataset scenarios due to camera displacement and focal length variation. This paper proposes a novel training-free, object-aware fusion framework to address this limitation through a five-stage pipeline: YOLOv8x detection, SAM2-L segmentation, LoFTR correspondence matching, a novel Scale-Aware Area Resize Algorithm, and GLCM-guided MSB/LSB bit-level fusion. The framework was evaluated on the EDMF benchmark (20 image pairs, synthetically modified to simulate Misaligned Multi-Focus Dataset shifts) and a Misaligned Multi-Focus …

Lossless Medical Image Compression Using Integer Discrete Wavelet Transform With Adaptive Subband Differencing And Context-Adaptive Entropy Coding, Rasha F. Nadhim, Ibrahim Adel Ibrahim, Ashwaq T. Hashim

Journal of Intelligent Informatics, Networking, and Cybersecurity

From transform-domain decorrelation and adaptive entropy coding, we propose a method for efficient lossless compression of medical images in this work. We implement the Integer Discrete Wavelet Transform (IDWT) to decompose the input image into four subbands of LL, LH, HL, HH, encompassing approximation and directional detail elements, in the initial implementation. It also removes spatial redundancy in image information and decomposes image information into a less correlated and more sparsely distributed set of coefficients. To decrease redundancy further, it proposes a subband-dependent differencing scheme, which decorrelates neighbouring wavelet coefficients with directional prediction. So horizontal differencing is done on LH, …

A Blockchain-Integrated Federated Learning Model And Autoencoder-Based Feature Reduction For Improving Iot Intrusion Detection, Tahseen A. Wotaifi

Journal of Intelligent Informatics, Networking, and Cybersecurity

The rapid growth of Internet of Things (IoT) environments has brought forth a wealth of security challenges in detecting network intrusions in diverse and resource-restricted systems. Privacy, scalability, and single point of failure issues plague traditional centralized intrusion detection solutions. To address these challenges, the study proposes a secure and adaptive intrusion detection model using Federated Learning (FL) and Blockchain, augmented with autoencoder-based feature reduction. The ToN-IoT dataset is pre-processed, and then an unsupervised autoencoder is used to build informative low-dimensional feature representations. The processed data is deployed to various clients to mimic a real federated situation. Every client will …

A Dual- Task Hierarchical Graph Attention Network For Protein-Protein Interaction Sites Prediction, Oras A. Hussein, Eman S. Al-Shamery

Journal of Intelligent Informatics, Networking, and Cybersecurity

In computational structural biology, it is still very hard to accurately find protein-protein interaction (PPI) sites and estimate how strong the interaction would be. In this research, we provide an innovative two-stage deep learning framework that combines residue-level graph representation learning with protein-level regression to achieve a thorough modeling of protein interactions. Protein structures first encoded as residue graphs, with nodes that stand for amino acids and edges that show how close they are to each other in space. To find binding residues, a deep residual Graph Attention Network v2 (GATv2) uses multi-head attention, residual connections, and Jumping Knowledge aggregation …

Oregon State Rank Assessment For Thompson Mistmaiden (Romanzoffia Thompsonii), Nora Dunkirk, Gabriel Campbell, Sue Vrilakas

Institute for Natural Resources Publications

Oregon state conservation status assessment for Thompson mistmaiden (Romanzoffia thompsonii) using NatureServe methodology, 2026.

A Dynamics Viewpoint On The Approximation Capabilities Of Infinite-Depth Neural Networks, Andreus Brammer

Electronic Theses and Dissertations

Neural Ordinary differential equations(Neural ODEs) provide a continuous-time framework for learning dynamical systems by representing the evolution of a state variable through a parameterized differential equation. While most existing methods rely on numerical time stepping methods during training such as RK4, this work investigates an alternate spectral framework where both the solution and the time-dependent network parameters are represented by global polynomial expressions.

Two methods are employed: the first uses Taylor series representations, and the second approach uses Chebyshev polynomial expansions together with fast spectral transforms and efficient polynomial multiplication techniques. In each formulation, the Neural ODE is transformed into …

Re: Response To Comment Letter (Dated June 11, 2026) For The Butte Priority Soils Operable Unit (Bpsou) Draft 2025 Butte Reclamation Evaluation System (Bres) Corrective Action Plans For Reclaimed Sites (Dated January 30, 2026), Brandon Warner

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Professional Development Course On Data-Driven Dynamical Systems At A Primarily Undergraduate Institution - Part B: Professional Development Framework And Institutional Implementation, Alessandro M. Selvitella, Jeffrey R. Anderson

CODEE Journal

This paper presents the professional-development and institutional-implementation component of a three-paper program on introducing data-driven dynamical systems into undergraduate ordinary differential equations instruction at a primarily undergraduate institution. The companion paper \cite{SelvitellaAnderson2026} develops the mathematical and computational content, including regression, regularization, Dynamic Mode Decomposition, Sparse Identification of Nonlinear Dynamics, and a Van der Pol oscillator activity. The present paper asks a complementary implementation question: what departmental structures, graduate teaching assistant roles, professional-development activities, and course-support pathways are needed for such materials to become teachable within local undergraduate settings?

We describe a three-phase professional-development model for graduate teaching assistants in the …

Tile-Based Knot Assembly With Celtic!, Divya Bajaj, Ryan Knobel, Juan Manuel Perez, Rene Reyes, Ramiro Santos, Tim Wylie

Computer Science Faculty Publications

In this paper we focus on the intersection of tile assembling systems, edge-matching puzzles, combinatorial games, and knot construction and identity. As a basis, we utilize the game Celtic!, which is a 2-player board game where the goal of the game is to construct knots where one knot uses more of a player’s pieces than the other player over all knots. All pieces must build off an existing knot and a valid knot must be closed. We consider three variations: a 0-player self-assembly variation that deterministically places pieces to form a closed knot of some length, a 1-player puzzle variation …

Global Performance Of Remote Sensing-Based And Reanalysis-Driven Models To Estimate Open Water Evaporation, Júlia Brusso Rossi, Ayan Santos Fleischmann, Leonardo Laipelt, Bruno Comini De Andrade, Joshua B. Fisher, Justin L. Huntington, Christopher Pearson, R. Iestyn Woolway, Roseilson Vale, Júlio Tota, Gabriel B. Senay, Huilin Gao, Anderson Ruhoff

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, we analyze the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. We compare 3 remote sensing‐based …

Cultural Traits May Replace Human Mobility Data In Forecasting Covid-19 Mortality: A Deep Learning Approach, Saif Abbas, Tamer Oraby, Michael G. Tyshenko, Samit Bhattacharyya

School of Mathematical & Statistical Sciences Faculty Publications

The COVID-19 pandemic highlighted the need for accurate epidemic forecasting to support public health decision-making. Most existing approaches depend heavily on human mobility data, while largely neglecting population behavior shaped by socio-cultural norms. In this study, we analyze daily COVID-19 mortality and Google mobility data from 72 countries during the first 130 d of the pandemic, a period characterized by high uncertainty and behavioral heterogeneity. In particular, we examine whether Hofstede’s country-level cultural dimensions can serve as latent behavioral forecasters of mortality in lieu of dynamic mobility indicators. Using 100 d for training and 30 d for forecasting, we employ …

Global Time-Resolved Measurements Of Inlet/Isolator Unstart Induced By Mass Injection, Andrew N. Bustard, Benjamin L. Bemis, Aaron Marques, Matthew J. Zahr, Thomas J. Juliano

Publications

The inner surface pressure of an axisymmetric inlet/isolator model was measured using anodized-aluminum pressure-sensitive paint (PSP) viewing through cast acrylic. Temperaturesensitive paint was utilized to correct for the PSP’s temperature sensitivity. The model was tested under Mach 5.7 flow at 𝑹𝒆 = 7.1 ×106 /m under conventional noise conditions. Transverse jet injection with jet-to-inlet mass-flow ratios up to 0.8 was used to induce unstart in the inlet/isolator. Background-oriented schlieren visualization of the inlet shocks was collected simultaneously with the PSP to determine when the inlet unstarted. Computational fluid dynamics results were used to determine off-wall flow structures and quantify approach …