Digital Commons Network^™

Codazzi Normalized Null Hypersurfaces, Théophile Kemajou Mbiakop, Cyriaque Atindogbe, Ferdinand Ngakeu

Turkish Journal of Mathematics

We introduce a class of null hypersurfaces of Lorentzian manifolds, namely Codazzi normalized null hyper surfaces, whose (screen) shape operator associated with the rigged vector field is a Codazzi tensor. Several examples are given to support our study. Moreover, we investigate conditions implying that the induced Riemannian screen structure on a Codazzi-type normalized null hypersurface of a Lorentzian space is locally a nontrivial warped product.

Interview With Orca Award Winner Reuben Rieke, Unl Chemistry; Discoverer Of Rieke Metals, Mark Griep, Reuben Rieke

UNL ORCA Interview Series

Emeritus Prof. Reuben Rieke was awarded the ORCA in 1995. Reuben was born in Fairfax, Minnesota. Something in his youth must have sparked an interest in science because he traveled 100 miles east to The University of Minnesota where he earned a bachelor’s in chemistry. Next, he earned a doctorate from the University of Wisconsin, and did postdoctoral work at the University of California Los Angeles. In 1977, after about 11 years as a faculty member in the chemistry department at the University of North Carolina, he joined UNL as a full professor of chemistry. I’ll share two remarkable facts …

Jwst Interferometric Imaging Reveals The Dusty Torus Obscuring The Supermassive Black Hole Of Circinus Galaxy, Enrique Lopez Rodriguez, Joel Sanchez-Bermudez, Omaira González-Martín, Robert Nikutta, Ryan M. Lau, Deepashri Thatte, Julien H. Girard, Ismael García-Bernete, Matthew J. Hankins

Faculty Publications

The dusty and molecular torus is an elusive structure surrounding supermassive black holes, yet its importance is unequivocal for understanding feedback and accretion mechanisms. The torus and accretion disk feed the inspiraling gas onto the active nucleus, launching outflows that fundamentally connect the active nucleus’s activity to the host galaxy. In this work, we utilize the aperture-masking interferometric mode onboard the JWST to achieve a resolution of 0.08" at 4.3 μm and bring out the fainter features in the central 10 pc of the Circinus galaxy. We show that most of the dust mass is located along the equatorial …

Evaluating Lunch Plan Data In The St. Charles School District (Scsd), Maddy Alexander, Guillermo Bilbao Olarreaga, Duncan Krige, Alyssa Schreiber, Nick Wintz, Wojciech Golik

The Confluence

The SCSD is a public school district in St. Charles, with, on average, 4500 students a year. The SCSD is subdivided into an early childhood center, six elementary schools, two intermediate (5-6,7-8) schools, and two high schools. Vocational schools are also within this district but were not included in this report. The SCSD is concerned with the impact of the Covid-19 pandemic on their district’s population and on the number of students that needed assistance with lunch. They have asked Lindenwood’s 2024-25 PIC Math group to analyze their data from the years 2020-25 and identify any trends. Identifying these trends …

A Review Of Routing Attacks In Routing Protocol Over Low-Power And Lossy-Based Iot Networks, Lanka Chris Sejaphala Mr., Vusimuzi Malele Prof, Francis Lugayizi Prof.

Journal of Cybersecurity Education, Research and Practice

Low-power and Lossy IoT Networks (LLNs) comprise physical sensors, processing capability, power, and other technologies to exchange information between systems and devices over the internet. However, these networks are susceptible to routing attacks affecting resources, traffic flow, and topology formation. In the related work, it has been discovered that many previous studies do not consider algorithms and implementation approaches for routing attacks. This research study provides a comprehensive in-depth synthesis insight into the description, effects, and algorithms & implementation of four routing attacks in LLNs i.e., rank, sinkhole, DIS-flooding, and worst parent attacks. The findings of this research study highlight …

Densest Subgraph Discovery On The Cpu, Hunter Gerard Gareau

Theses and Dissertations

The Densest Subgraph Discovery (DSD) problem is a prevalent problem in the field of graph mining, aiming to find the cohesive subgraph. Given a graph �� = (��,��) and an integer �� ≥ 2, the goal is to find a vertex sub- set �� ⊆ �� whose induced subgraph �� (��) maximizes the ��-clique density, defined as the number of ��-cliques per vertex. Larger val- ues of �� capture higher-order connectivity patterns beyond edges, enabling the discovery of more cohesive structures. There have been many solutions to this problem. However, one avenue that other graph mining problems have gone down …

Optimal Quantization Of Finite Uniform Data On The Sphere, Mrinal Kanti Roychowdhury

School of Mathematical & Statistical Sciences Faculty Publications

This paper develops a systematic and geometric theory of optimal quantization on the unit sphere 𝕊2, focusing on finite uniform probability distributions supported on the spherical surface—rather than on lower-dimensional geodesic subsets such as circles or arcs. We first establish the existence of optimal sets of n-means and characterize them through centroidal spherical Voronoi tessellations. Three fundamental structural results are obtained. First, a cluster-purity theorem shows that when the support consists of well-separated components, each optimal Voronoi region remains confined to a single component. Second, a ring allocation (discrete water-filling) theorem provides an explicit rule describing how optimal representatives are …

Wild@Fire2025: Overview Of Word-Level Code-Mixed Language Identification In Dravidian Languages, Ameeta Agrawal, Asha Hegde, Sharal Coelho, Sabur Butt, Fazlourrahman Balouchzahi, Sudha V, Shashirekha Hosahalli Lakshmaiah

Computer Science Faculty Publications and Presentations

Code-mixing is considered as a linguistic phenomenon that combines several languages into one text. It has now become very common in multilingual societies, especially in digital communication. Word-Level Identification of Languages in Dravidian Languages (WILD) - a Code-mixed Language Identification (CoLI) in Dravidian languages shared task, organized as a part of Forum for Information Retrieval and Evaluation (FIRE) 2025, put forward these challenges to the researchers by asking them to develop models capable of classifying words in code-mixed texts involving Dravidian languages - Tamil, Telugu, Malayalam, Kannada, and Tulu, which are interwoven with English. It poses significant challenges due to …

Jiving With Llms: Assessing First Year Students’ Computer Programming Self Efficacy After Reading Code With Llms, Michelle Jarvie-Eggart, Joseph Roy Teahen, Daniel T. Masker, Jose Padilla, Leo C. Ureel Ii, Laura E. Brown, Scott Pomerville, Jon Sticken

Michigan Tech Publications

This study investigated the impact of leveraging generative artificial intelligence (GenAI) to assist 1st-year engineering and computer science (CS) students in reading code in a new (to them) language. Students were asked to comment code in FORTRAN. They were then asked to run the code through ChatGPT-4.0 for its comments and reflect on what they learned from the experience. Participants completed survey items from Ramalingam and Wiedenbeck’s Computer Programming Self-Efficacy Scale (CPSES) prior to and after the intervention. Additional open-ended reflective (qualitative) questions were added to the quantitative questions in the postintervention questionnaire. This study documents increases in self-efficacy for …

Butte Priority Soils Operable Unit (Bpsou) 2025 Monthly Progress Report. Consent Decree For The Butte Priority Soils Operable Unit. Civil Action No. Cv 89-039-Bu-Seh, Atlantic Richfield Company

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Teaching Numeracy For Social Justice: Educational Equity, Esther Isabelle Wilder, Crystal C. Rodriguez, Caterina Shost, Eduardo Vianna, Frank Wang

Numeracy

The special collection, “Teaching Numeracy for Social Justice: Educational Equity,” focuses on how quantitative reasoning (QR) can function as a vehicle for equity, empowerment, and democratic participation. Building on a longstanding tradition that treats numeracy as inseparable from social justice, these contributions highlight how progressive pedagogies (e.g., active learning, authentic research, and equity-oriented assessment) have the potential to broaden access for students historically excluded from quantitative fields. The studies span a variety of conceptual frameworks, introductory and advanced quantitative instruction, and interdisciplinary applications, showcasing how inclusive QR practices can build confidence, agency, and real-world understanding. These articles demonstrate that when …

Animal Taxa Threatened By Adverse Fire Regimes In Western Australia: A Synthesis And Outlook, Tim S. Doherty, Mark G. Allen, Karlene Bain, Stephen Beatty, Allan H. Burbidge, Renee A. Catullo, Sarah Comer, Ben Corey, Saul J. Cowen, Robert A. Davis, Martin A. Dziminski, J. Anthony Friend, Bruce Greatwich, Mark S. Harvey, Hannah Killian, Michael E. Klunzinger, Damian C. Lettoof, Nicola J. Mitchell, Melinda Moir, Harry A. Moore, David L. Morgan, Ian J. Radford, Michael J. Rix, Tom Vigilante, Adrian F. Wayne, Corey Whisson, Nicole Willers, Matthew R. Williams

Natural Resources Research Articles

Adverse fire regimes threaten biodiversity, potentially leading to population declines and increased extinction risk. Understanding how varying fire regimes affect threatened species is essential for effective ecosystem management, including in Western Australia where diverse ecosystems are exposed to wildfires, Indigenous burning, and prescribed fire. We compiled and synthesised data on the threat of adverse fire regimes to threatened animal taxa in Western Australia. Using a threat classification scheme, we ranked adverse fire regimes as having either no, low, medium, high, or unknown impact on each taxon. A total of 212 taxa were reviewed, 153 (72%) of which are considered fire-threatened: …

Optimized Resnet-18 Architecture For Multi-Class Oral Diseases Classification, Ahmed Ahmed

Karbala International Journal of Modern Science

In recent years, the classification of oral diseases has gained significant attention due to its influence on public health and the necessity for early and accurate diagnosis. Traditional diagnosis depends on manual clinical assessment, which can be slow and subjective. An optimized and subsequently quantized model is required to provide a faster and more consistent diagnostic support tool. This paper proposes an optimized ResNet-18 architecture for the classification of six oral diseases. The optimization process is based on removing the Rectified Linear Unit (ReLU), Batch Normalization (BN), and convolutional layers from the base ResNet-18 blocks that contain 128 filters. This …

Appropriate Wireless Technology For Blue Data Communication To Enhance Artisanal Fishery, Abdi T. Abdalla, Eva Shayo, Angelina Misso, Baraka Maiseli, Kwame S. Ibwe, Narriman Jiddawi, Moses Ismail

Tanzania Journal of Science

The paper examines the development of a system architecture to support smart fishing. This includes the establishment of a blue data center, which would allow government agencies and research institutions to access fisheries data. The goal is to provide policymakers with the tools they need to efficiently manage artisanal fisheries resources. The architecture also incorporates wireless communication components that are suitable for small-scale fishers in remote areas. The study delves into the selection of appropriate wireless communication technology for transmitting fishing data to the communication center. Factors such as coverage range, data rates, and cost implications are taken into consideration. …

Qualitative And Numerical Observations Into The Career Trajectories Of Early Career Academics: A Mathematical Model Approach, Oluwatayo M. Ogunmiloro

Tanzania Journal of Science

This study develops and analyzes a mathematical model that describes the interplay among different researcher groups within academia by focusing on how variables such as mentorship, access to funding, and academic peer influence affect the career trajectories of early-career, experienced, redundant, and successful researchers. Using stability theory and relevant theorems of differential equations, this study ensures the existence, uniqueness, positivity, and boundedness of the model's solutions. Additionally, the model’s equilibrium states, are analyzed to determine the local asymptotic stability. Numerical simulations using the Runge-Kutta fourth-order (RK4) method, implemented in Python, are performed to illustrate issues related to career growth within …

Bridging The Gap: A Systematic Review Of Cyber Conflict Forecasting Models And The Case For Ai-Driven Dynamic Frameworks, Salim Arfaoui, Youssef Harrath, Omar El-Gayar

Research & Publications

Cyber conflict forecasting remains constrained by static models that overlook the integration of geopolitical context with technical indicators. This systematic literature review examines 58 studies (2010–2025) using PRISMA guidelines and an InputProcess-Output framework to classify approaches and identify key gaps. Quantitative methods dominate (67%), yet only 14% incorporate geopolitical variables, despite the political nature of cyber conflict. Major limitations include adversarial adaptation blindness (85% assume static behavior), coarse temporal granularity (72% use daily+ intervals), lack of uncertainty quantification (75%), and minimal modeling of cross-domain escalation (92% cyber-only focus). Strategic forecasting is rare, with just 14% providing long-term insights and 16% …

Datamut: Deterministic Algorithms For Time-Delay Attack Detection In Multi-Hop Uav Networks, Keiwan Soltani, Federico Corò, Punyasha Chatterjee, Sajal K. Das

Computer Science Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs), also known as drones, have gained popularity in various fields such as agriculture, emergency response, and search and rescue operations. UAV networks are susceptible to potential security threats, such as wormhole attacks, jamming, spoofing, and false data injection. Time-Delay Attack (TDA) is a unique attack in which malicious UAVs intentionally delay packet forwarding, posing significant threats, especially in time-sensitive applications. It is challenging to distinguish malicious delay from benign network delay due to the dynamic nature of UAV networks, intermittent wireless connectivity, or the Store-Carry-Forward (SCF) mechanism during multi-hop communication. Some existing works propose machine learning-based …

Pciafl: Personalized And Class Imbalance-Aware Federated Learning For Driver Behavior Classification, Osho Osho, Shubh Garg, Suchetana Chakraborty, Sajal K. Das

Computer Science Faculty Research & Creative Works

Automated understanding of driver behavior from vehicular kinematics is vital for safety-aware intelligent transportation systems. However, centralized cloud processing suffers from latency, scalability, and privacy issues. Federated Learning (FL) provides a decentralized alternative but faces two major challenges: (i) non-IID client data due to heterogeneous driving styles and sensors, and (ii) severe class imbalance, as risky behaviors are inherently rare. In this work, we propose a personalized FL framework that uses a shared CNN-LSTM backbone with client-adaptive classifiers and incorporates a cost-sensitive loss to address behavior skew. Evaluated on the UAH-DriveSet dataset, our method achieves 92.60% accuracy and 91.68% macro-F1, …

2026 Revised Draft Final Bpsou Backfill And Cover Material Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Statistics Of Glinting Clouds Observed By Dscovr And Geostationary Satellites, Tamás Várnai, Alexander Marshak, Alexander Kostinski

Michigan Tech Publications

This study examines how frequently the specular reflection of sunlight—that is, sun glint—reveals the presence of ice crystals that maintain a steady horizontal orientation. The study analyzes data from the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) spacecraft and from collocated images taken by geostationary satellites. The analysis of spatio-temporal variations in glint frequency over vegetated land surfaces reveals that (a) year-to-year variations are modest with no clear trends; (b) glints typically occur 7%–8% more frequently than previously estimated; (c) glints are most frequently observed during the May-August period, and over Asia. The results also …

Optimizing Proaftn Classifier With Ant Colony Algorithm: Enhanced Diabetes Detection Benchmarking, Feras Al-Obeidat

All Works

The increasing global prevalence of diabetes highlights the need for accurate diagnostic tools to improve early detection and effective treatment planning. Traditional classification models often struggle to achieve optimal performance due to limitations in parameter tuning and adaptability to complex datasets. To address these limitations, this article introduces PROAnt, an innovative learning approach designed to enhance the robustness and efficiency of the PROAFTN multicriteria classification method. PROAnt leverages the computational power of ant colony optimization (ACO) to dynamically fine-tune and optimize the key parameters, such as intervals and weights, at the core of the PROAFTN classification process. This learning methodology …

Inhomogeneous Branching Random Walks: Incorporating Genealogy And Density Effects, Lauren Ajax, Beatrice Durham, Pratima Hebbar, Cade Johnston, Jiayi Zhang

Spora: A Journal of Biomathematics

We introduce a novel framework using inhomogeneous branching random walks (BRWs) to model biological processes, specifically by introducing genealogy-dependence in branching rates and displacement distributions to model bacterial colony growth. Current stochastic models often either assume independent and identical behavior of individual agents or incorporate only spatiotemporal inhomogeneity, ignoring the effect of genealogy-based inhomogeneity on the long-time behavior of these processes. Such asymptotics are of independent mathematical interest and are crucial in understanding the emergence of patterns. We propose several inhomogeneous BRW models in 2D space where displacement distributions and branching rates vary with time, space, and genealogy. A combined …

The Sunday Math Circle, Nathan Pflueger

Journal of Math Circles

Bob and Ellen Kaplan envisioned and organized a style of math circle centered on the idea that children of all ages can work like mathematicians do: creatively, collaboratively, and ecstatically. This article surveys four sample topics covered during a Sunday morning math circle in the Boston area, based on Bob and Ellen's invaluable guidance. I also offer some reflections on what I learned from Bob and Ellen, and how it is reflected in these math circles.

Infinite Line, Infinite Knowledge: The 'Spera' And Organized Chaos In Lambert's Encyclopedia, The 'Liber Floridus', Ava Romano

Theses and Dissertations

The Liber Floridus is a medieval encyclopedia renowned for its program of circular diagrams, or sperae. Inside this manuscript of 190 chapters, these diagrams frame and embody written knowledge, revealing a connection between encyclopedism and life in the Benedictine monastery by creating a coherent visual organization of chapters.

Simulation Of Quantum Walks For Secure Data Access Patterns, Arslan Ahmad Janjua

Theses and Dissertations

Quantum computing is revolutionizing computational science, offering fundamentally new approaches to information processing that surpass classical limitations. One of the most versatile and powerful tools in this emerging field is quantum walks. Quantum walks are quantum analogs of classical random walks that leverage superposition and interference to explore complex spaces efficiently.

This thesis will explore how discrete-time scattering quantum walks can be simulated and analyzed to investigate patterns of secure data access. By modeling quantum walks on a variety of graph structures and studying the dynamics of marked vertices, the project aims to demonstrate how quantum interference and graph topology …

Structural Characterization Of Peptide Nanoaggregates At Varying Concentrations And Their Impact On Cellular Responses, Malika Rozmetova

Theses and Dissertations

Peptide nano-assemblies can regulate cellular pathways in a structure-dependent manner. Here, we show that the enzyme-responsive peptide NapFFK(NBD)Yp forms distinct nanoscale assemblies at different concentrations, triggering differential ER stress and extracellular vesicle release in MDA-MB231 cells. These results highlight the importance of supramolecular organization in peptide–cell interactions.

Ai In Society: A Regulatory Framework For Responsible Integration, Ziad Doughan, Sari Itani, Hadi Al Mubasher

BAU Journal - Science and Technology

This review paper studies the influence of Artificial Intelligence (AI) and Machine Learning (ML) on society in various categories in detail. AI and ML have developed rapidly in the past two decades, thus changing our lifestyles. These developments have various positive and negative impacts on society. This paper explores the many societal impacts of AI and ML, in economics, social aspects, ethics, and policy, shedding light on the opportunities and challenges that arise. An interdisciplinary insight is capable of understanding the challenges society faces when it uses AI and ML, locking opportunities that lie ahead and identifying promising paths towards …

Crystal Structure Of Methanococcus Jannaschii Dihydroorotase With Substrate Bound, Jacqueline Vitali, Jay C. Nix, Haley E. Newman, Michael J. Colaneri

Physics Faculty Publications

Here, we report the X-ray structural analysis of dihydroorotase from Methanococcus jannaschii co-crystallized with dihydroorotate at pH 6.5. The crystals are isomorphous with the crystals of the apoenzyme, with space group P3₂21 and unit-cell dimensions a = b = 111.4, c = 101.2 Å. The structure was refined to R = 0.169 and R_free = 0.186 at a resolution of 1.87 Å at room temperature. During crystallization the degradative reaction took place, and the electron density in the active site corresponds to the substrate carbamoyl aspartate. Carbamoyl aspartate interacts with the protein in the active site …

A. Vs. I In Ai: Is There A Threshold To "Engineered" Intelligence?, Joshit Mohanty

Engineering Management & Systems Engineering Faculty Publications

Despite artificial intelligence reshaping the world, its development generates uncertainties regarding future capabilities. AI simultaneously exists as an artifact of engineering design and as autonomous intelligence, creating an observer-participant feedback loop. This paper proposes that embodied AI faces a bandwidth-limited intelligence threshold T_h that it arises from B = min(C_sens,C_Act). However, Shannon capacity measures bits while intelligence operates on concepts, necessitating a dual-channel model separating physical bandwidth B_io from representational capacity B_rep. Intelligence emerges as multi-dimensional rather than scalar, with components exhibiting different bandwidth dependencies. Surpassing T_h requires either new sensing methods expanding B, enhanced representational frameworks, or reconceptualization within …

The Ai Revolution In Virtual Try-Ons: A Means-End Chain Model Perspective, Ju-Young M. Kang, Ji Young Lee, Dooyoung Choi, Sumin Helen Koo, Jeehyun Song, Youngjin Bahng

Educational Leadership & Workforce Development Faculty Publications

Leading brands have begun to implement artificial intelligence-driven virtual try-on (AI VTO) technology, which helps reduce returns and increase conversion rates, repeat purchases, and customer loyalty. This research aimed to examine how retail user experience with specific perceived quality factors of AI VTOs influences users’ value equity and downstream loyalty and to investigate the moderating effects of clothing in relation to the self as structure and concern for physical appearance, based on a Means–End Chain model. Data were collected from 509 U.S. online apparel shoppers using a consumer panel. Structural equation modeling and multigroup analysis were used for data analysis. …