Digital Commons Network^™

Preparer Penalties And Compliance, George A. Arzoo

Tax Adviser

No abstract provided.

The Whisper Web: A Mail Intelligence Framework For Semantic Coordination In Communication Systems, Johny Manuel-Devadoss, Joanna Johnson, Jayden Jack Johnson, Deepthi Prasad

Defensive Publications Series

This paper introduces The Whisper Web, a communication intelligence framework designed for post-static digital correspondence ecosystems operating under conditions of planetary-scale coordination complexity. Unlike conventional email systems that treat messages as isolated immutable payloads exchanged between endpoints, the Whisper Web reconceptualizes communication as a continuously evolving semantic biosphere composed of dynamic probabilistic entities known as Whisper Units. Each Whisper Unit functions as a compressed socio-semantic organism capable of propagating influence through adaptive trust topologies, negotiation-energy fields, obligation gradients, institutional resonance maps, and multi-agent predictive coordination networks.

The proposed framework abandons the traditional paradigms of inboxes, message queues, folders, labels, and …

3d Puzzle Generation Beyond Voxelized Parts, Iris Xia

Computer Science Theses

Burr puzzles are interlocking assemblies whose pieces must be inserted and removed through tightly constrained motions. Designing them is difficult because geometric fit, interlocking behavior, and disassembly order are tightly coupled, while existing computational methods remain largely limited to voxelized or template-based constructions.

This work presents a framework for 3D puzzle generation beyond voxelized parts. The method replaces local mobility heuristics with a certified search over geometry edits. Starting from a topological contact specification, it constructs signed distance fields for individual parts, applies complementary local edits, and validates each candidate using exact geometric checks and a kernel disassembly graph. The …

Node Differentially Private Algorithms For Survivable Networks And Graphs Analysis, Jinghua Sun

Computer Science Theses

This thesis studies two graph algorithmic settings where additional structure gives stronger guarantees than worst-case black-box methods. The paper considers higher order edge connectivity under node differential privacy. We study the minimum k-edge-connected spanning subgraph problem (k-ECSS) and the minimum k-edge-connected component problem (k-ECC). These objectives have large global sensitivity under node privacy, since adding or deleting one vertex and its incident edges can significantly change robust connectivity structure. To address this, we use Propose-Test-Release for locally stable k-ECC instances and a Lipschitz extension framework for k-ECSS, based on bounded-degree complement objectives and the Generalized Exponential Mechanism.

The second part …

Multi-Level Variable Selection Using A Bart-Enhanced Mixed-Effects Framework, Keming Zhang, Yaoyao Li, Jungang Zou, Sijian Wang, Bernadette A. Fausto, Liangyuan Hu

College of Health Professions Faculty Papers

Selecting important individual- and cluster-level predictors has become increasingly critical in healthcare research, where data often exhibit hierarchical structures due to collection from multiple clusters. Mixed-effects models, which account for within-cluster correlation and between-cluster heterogeneity, are a natural approach for multilevel variable selection. However, currently available variable selection methods for multilevel data are predominantly based on mixed-effects models that impose restrictive parametric assumptions, potentially limiting their utility when the underlying relationships are nonlinear or involve interactions. While nonparametric methods have shown promise for variable selection in non-clustered data, they have been much less studied in the multilevel setting. Moreover, nonparametric …

Robert, Powers; Unl Chemistry; Nmr-Assisted Drug Discovery, Mark Griep, Robert Powers

Department of Chemistry: Faculty Interviews

Dr. Robert Powers became a chemistry professor at the University of Nebraska-Lincoln in 2003 and is about to retire after 23 years. Prior to UNL, Bob was a drug discovery researcher for 11 years at American Cyanamid, which eventually became Wyeth and is now part of Pfizer. Bob was born in Jersey City, New Jersey. Something in his youth must have sparked an interest in chemistry because he earned a bachelor's in that subject from Rutgers University in New Brunswick. Then he traveled 1200 miles west to Purdue University in Indiana where he earned his doctorate. Next, he did postdoctoral …

A Formal Ontology Of Combat Feel, Grayson Julian Von Goetz Und Schwanenfliess

LMU Theses and Dissertations

Combat feel, the moment-to-moment subjective character of real-time melee combat in ac- tion games, is a central concern of game design and a recurring subject in design literature, but practitioners currently navigate it through intuition and reference to admired prior work, with no shared formal vocabulary for the design trade-o!s being made. This thesis presents a decision-theoretic framework that formalizes combat feel as a Bayesian network in which designer decisions act as interventions on measurable system variables, those variables drive latent perceptual states whose conditional distributions are grounded in the psychophysics literature on input-lag detection, duration discrimination, and audiovisual temporal …

Real-Time Instruction Internalization For Large Language Models, Brenden Smith

Theses and Dissertations

For the end user, Large Language Models (LLMs) are programs that process natural language inputs into natural language outputs. In popular usage, this tends to take the form of conversation: a user asks a question, provides information, or gives instructions, and the LLM (hopefully) replies in a manner we would expect of an informed and compliant person. While convenient and intuitive for users, this natural conversational format encourages the misconception that LLMs are learning from conversations, when they do not. This work presents the benefits and practicality of a language model paradigm that meets this user expectation -- that is, …

Spectral Classification Of Diverse Lithologies Using Multi- And Hyperspectral Satellite Data: A Comparative Study, Önder Gürsoy, Emre Özelkan, Rutkay Atun, Ayşe Betül Çalişkan, Ahmet Efe

Turkish Journal of Earth Sciences

Accurate lithological mapping requires selecting the appropriate remote sensing data and classification methods. This study evaluates the performance of four satellite datasets—Landsat 8 OLI, Sentinel-2A, ASTER, and Hyperion EO-1—using three spectral classification techniques: Matched Filtering (MF), Spectral Angle Mapper (SAM), and Spectral Information Divergence (SID). The study area is located between the Zara and Koyulhisar districts in eastern Türkiye and comprises diverse lithological units. A total of 49 rock samples collected in the field were used for validation. The results indicate that MF consistently outperformed the other methods, achieving the highest accuracy with Landsat 8 (Kappa = 94.2%). ASTER data …

Hyperspectral Image Classification Using Novel 1-D And 2-D Deep Neural Networks, Özlem Polat, Zümray Dokur, Tamer Ölmez

Turkish Journal of Earth Sciences

Hyperspectral image (HSI) classification is of critical importance in many fields including agriculture, geology, environmental monitoring, and urban planning. In recent years, many researchers have utilized deep neural networks (DNNs), known for their high performance in the classification of HSIs. When 2-D/3-D convolutional neural networks are used in HSI classification, filters are applied using input patches typically larger than 11 × 11. This allows spectral and spatial features to be evaluated together. However, this combination creates several problems. Because HSIs have low spatial resolution, they often do not contain strong texture details. Furthermore, features with little relevance to classification make …

Formation Mechanism Of High-Quality Reservoirs In The Shanxi Formation Of The Qingyang Gas Field In A Meandering River Delta Setting, Xingming Duan, Shu Liu, Meng Wang, Yecan Fan, Xiyu Wang, Xinan Yu, Zubing Li

Turkish Journal of Earth Sciences

As global energy demand rises, unconventional gas resources, particularly tight gas reservoirs, have become increasingly important for future energy supply. Located in the southwestern Ordos Basin, the Qingyang gas field is a newly discovered deep tightgas field with proven geological reserves exceeding 31.8 × 109 m3 and has become a strategic focus for deep-gas exploration in China. Despite rapid appraisal that delineated several stable gas-bearing zones, a comprehensive understanding of the sedimentary architecture, diagenetic transformation, and enrichment mechanisms of high-quality reservoirs in the Permian Shanxi Formation remains incomplete. Focusing on the Shan 1 Member (hereafter referred to as Shan 1), …

A Shallow Landslide Hazard Assessment Using A Probabilistic Approach: An Example From Northeastern Türkiye (Beşikdüzü, Trabzon), Kübra Tezel, Aykut Akgün

Turkish Journal of Earth Sciences

The objective of this study was to identify and assess shallow landslide hazard in both spatial and temporal terms within the boundaries of Beşikdüzü District in northeastern Türkiye. The workflow was initiated with the development of a detailed multitemporal mass‑movement inventory map derived from satellite imagery provided on the Google Earth platform,1 covering the period between 2000 and 2018. Inventory mapping was complemented by extensive field verification campaigns to identify discrepancies, confirm spatial accuracy, and document additional morphological details that could not be detected from imagery alone. A 10-m spatial resolution digital elevation model (DEM) was generated from 1:25,000-scale digital …

Improving Explainability And Interpretability Of Neural Networks Via Hyperparameter-Extended Influence Functions, William Breslin

Dissertations and Theses

Understanding how model predictions and training outcomes vary with changes in data, features, and modeling choices is central to explainable artificial intelligence. This dissertation introduces a unified framework for explainability by generalizing classical influence functions to encompass user-defined hyperparameters embedded in the training loss, model architecture, or data representation. By extending influence functions in this way, the framework broadens their applicability and integrates multiple explainability techniques into a single, coherent approach. It provides a common mathematical foundation linking data impact, feature importance, and model design analysis, and supports a broad class of additional explainability analyses beyond these settings. The demonstrated …

Applicability Of Machine Learning For Shear-Wave Velocity Prediction From Conventional Well Logs: The Lsboost Approach, Rahmat Catur Wibowo, Fadsyah Muhammad Arby, Bagus Sapto Mulyatno, Ordas Dewanto, Isti Nur Kumalasari, Muh Sarkowi

Turkish Journal of Earth Sciences

Shear-wave velocity (Vs) is one of the most critical parameters for determining geomechanical properties and basin overpressure. However, assessing Vs via techniques like core analysis requires considerable effort and expense. This study predicts Vs using several approaches and compares the accuracy levels of all models. For this objective, the multiple linear regression, multiple linear stepwise regression, support vector machine, and least-squares boost (LSBoost) methodologies were selected. The six well-logging data inputs of density (RHOB), gamma-ray (GR), deep resistivity (ILD), acoustic wave velocity (Vp), shale volume (VCL), and water saturation (SW) were selected as effective variables, whereas Vs was regarded as …

Geoelectrical Signatures Of The Giant Karaburun Pelitic-Mafic-Type Volcanogenic Massive Sulfide Mineralization In The Central Pontides (Türkiye), Kurtuluş Günay, Türker Yas, Buğra Çavdar, Ertan Pekşen

Turkish Journal of Earth Sciences

The Karaburun deposit, hosted in greenschist facies metamorphic rocks, is a newly discovered giant volcanogenic massive sulfide (VMS) deposit in Anatolia and provides an exceptional natural laboratory for geophysical monitoring. The main ore body is less affected by metamorphism than the surrounding wall-rocks, where metamorphic and metasomatic processes formed pyritemagnetite- sericite-quartz assemblages that significantly influence geoelectrical properties. In this study, the geometry and extent of mineralization within geologically defined target zones were investigated using direct current resistivity and two-dimensional timedomain induced polarization (2D-TDIP) methods and the results were compared with the geology. A pole–dipole electrode array was employed in the …

Electoral Threshold: Pros-Cons And Political Party Consensus In Indonesia, Azka Abdi Amrurobbi, Donis Daviska, Alam Mahadika

Jurnal Wacana Politik

The debates surrounding the parliamentary threshold and presidential threshold have become a recurring phenomenon, particularly in the period leading up to general elections in Indonesia. This paper aims to examine the pros and cons of the implementation and determination processes of both thresholds. Employing a qualitative research method and library research as the primary data collection technique, to validate the data then this research used data triangulation technique. In the Indonesian context, the thresholds applied constitute a form of formal threshold, namely thresholds determined through political and legislative processes in parliament. Consequently, threshold policies are heavily influenced by the configuration …

Beyond Pedagogical Inertia: Understanding And Overcoming The Barriers To Effective Faculty Work In Higher Education, Yoshihiko Ariizumi

Learning, Teaching, & Researching Optimization

Academic faculty are among the most educated professionals in the world. Yet a striking body of empirical research demonstrates that they face profound, systematic barriers to performing their own work effectively—barriers that are cognitive, institutional, cultural, and structural in origin. This paper extends the analysis of “pedagogical inertia” beyond the classroom to the full scope of faculty professional life: research, writing, service, advising, and self-directed learning. Drawing on evidence from organizational psychology, cognitive neuroscience, higher education research, and behavioral science, we identify six classes of barriers that consistently impede effective faculty work, and we analyze—with reference to documented successful cases—the …

Imbalance In Wnt: Retinoic Acid Signaling Dysregulates Hox Gene Expression: Implications For Cancer Stem Cell Heterogeneity And Crc Patient Survival, Brian Osmond, Chi Zhang, Pascal K. Kataboh, Caroline O. B. Facey, Lynn M. Opdenaker, Bruce M. Boman

Department of Pharmacology and Experimental Therapeutics Faculty Papers

How HOX transcription factors play a role in the stem cell (SC) origin of cancer is unclear. Our goal is to determine how dysregulation of HOX gene expression promotes colorectal cancer (CRC) development through aberrant SC regulatory mechanisms. We investigated retinoic acid (RA) and WNT signaling because they regulate HOX expression and both pathways are dysregulated in cancer. Previously, we reported WNT and RA pathways are functionally linked, and in CRC, APC mutation generates a WNT:RA imbalance leading to incomplete differentiation and SC overpopulation. We hypothesize that aberrant WNT- and RA-signaling dysregulates HOX expression that contributes to the SC origin …

Geometric Structure In High-Dimensional Representations: Theory And Applications To Language, Jiayi Chen

Dartmouth College Ph.D Dissertations

This thesis develops a geometric perspective on high-dimensional representations, motivated by applications to language. Rather than treating representations solely as inputs to predictive models, we view them as structured objects whose geometry encodes meaningful information. In particular, we argue that such representations exhibit organization at multiple scales: at a global level, metric and clustering structure capture relationships such as genre, authorship, and discourse; at a local level, geometric quantities such as intrinsic dimension and curvature describe how these relationships vary across the space.

To study these phenomena, we combine empirical analysis with theoretical development. On the empirical side, we examine …

Uneven Ranks: Geographic Deepening Of The All-Volunteer Force, Christine Hogestyn

Master in Public Policy Theses

Who is enlisting in Fiscal Year 2025, and what state-level characteristics are associated with military enlistment rates, service selection, and recruit quality? This study documents the geographic landscape of U.S. military accessions during a period of recruiting recovery, filling a gap in the literature by providing a current, empirical description of who enlists and from where in today’s All-Volunteer Force. Drawing on personnel data from the Department of War, the U.S. Census and Bureau of Labor Statistics estimates, and a federal dataset of military installations, I analyze 203,987 new accessions across the Army, Navy, Air Force, and Marine Corps from …

Draft Final 2024 Unreclaimed Sites Sampling: Ur-21 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Systematic Literature Review On Data-Efficient And Adaptive Learning Techniques For Encrypted Traffic Classification Under Modern Protocols, Muntakimur Rahaman, Azwan Mahmud, Azlan Abd Aziz, Osama M. S. Abujawa, Ji-Jian Chin

School of Engineering, Computing and Mathematics

Recent studies suggest that few-shot and zero-shot learning methods, drawing on meta-learning, self-supervised approaches and metric-learning ideas, can classify encrypted traffic (TLS 1.3 and QUIC) with competitive accuracy across different protocol conditions. This systematic literature review (SLR) investigates 22 studies selected from an initial pool of 500 papers using PRISMA 2020, focusing on current methodologies for non-stationary network traffic classification, with particular attention to few-shot, zero-shot, and meta-learning approaches. The research addresses four questions: (1) Which approaches have been employed for non-stationary network traffic classification and threat detection? (2) How do hybrid or cross-domain models improve adaptation, detection and overall …

Design And Implementation Of Error Estimators For Finite Element Eigenvalue Problems, Gabriel Esteban Pinochet Soto

Dissertations and Theses

We present three publications, all encompassed under the umbrella of a posteriori error estimation theory for eigenvalue problems for finite element discretizations. The central objective of the research is the development of a general framework for the study of reliable estimation of eigenvalues and eigenspaces. We introduce applications to problems of theoretical interest as well as problems arising in real-life scenarios, such as optical fibers. The first paper focuses on the implementation of a dual-weighted residual error estimator for a nonselfadjoint eigenvalue problems arising from the study of leaky modes in optical fibers---Maxwell's equations, Perfectly Matched Layers, and a conforming …

Unquaint Pigs’ Stakeholder Perspectives On Wild Swine In Central Western Florida, Tyler Koerner

USF Tampa Graduate Theses and Dissertations

The Anthropocene presents important questions for how to address the continuous transferal of new species into new spaces and the cascading impacts of environmental transformations. Novel ecosystems present one such outline for conservation that acknowledges the modification of historic ecosystems and the social entanglements that arrive with new species. I argue that novel ecosystems can benefit from further anthropological integrations that aid in describing the entanglements of introduced species and the pursuit of best managerial outcomes. For wild swine in Florida, the adoption of a novel approach is especially relevant because of entanglements with historic and modern Floridian stakeholders and …

The Heterogeneous Response Of Astrocytes In Different Brain Regions Under Metabolic Stress, Pawan Kumar Thapaliya

USF Tampa Graduate Theses and Dissertations

Astrocytes play a central role in maintaining ionic homeostasis, neurotransmitter clearance, and brain en-ergy metabolism. Their excitability, reflected in activity-evoked intracellular sodium (Na+, [Na+]i) and calcium (Ca2+,[Ca+]i) dynamics, is increasingly recognized as a critical determinant of neuronal function and vulnerability, particularly under metabolic stress. Despite their importance, the mechanisms underlying astrocytic ionic signaling and its regional heterogeneity remain incompletely understood. In this thesis, I developed detailed computational and biophysical models to investigate astrocytic Na+ and Ca2+ dynamics, their bioenergetic consequences, and the roles of key ion transporters under physiological and metabolically stressed conditions, validating the models against experi- mental data. …

Paired-Satellite Coordinated Laser Ablation For Torque-Cancelled Deorbit Of Uncontrolled Orbital Debris, Daniel Austin Harbison

Defensive Publications Series

A method is disclosed for active orbital debris removal in which two satellites operate in coordinated formation on opposite sides of a target debris object and direct continuous-wave or pulsed laser ablation beams onto opposing faces of the target. The bilateral geometry provides three simultaneous effects: (1) surface ablation gradually weakens the structural integrity of degraded fasteners, adhesives, and thermal blankets on the debris exterior; (2) symmetric ablation plumes produce opposing reaction-torque components that cancel each other, suppressing the spin-up that would otherwise destabilize a single-beam ablation push; and (3) the combined photon pressure and plume-thrust components add as decelerating …

Neuroscience-Based Intellectual Productivity: A Ten-Principle Methodology For Knowledge Workers, Yoshihiko Ariizumi

Learning, Teaching, & Researching Optimization

This paper presents a comprehensive, neuroscience-grounded methodology for enhancing intellectual productivity among knowledge workers—particularly academic faculty and researchers operating under conditions of chronic cognitive overload. Drawing on ten foundational principles derived from contemporary cognitive neuroscience, we argue that substantial gains in research output, creative ideation, and knowledge integration are achievable not by working harder, but by working in deliberate alignment with the brain’s native computational architecture.

The ten principles address: strategic activation of the Default Mode Network (DMN) for incubation and creative insight; prefrontal cortex (PFC) energy management through temporal task separation; externalization of cognitive load via AI-assisted working memory …

Working Smarter, Not Harder: A Practical Guide To Intellectual Productivity, Yoshihiko Ariizumi

Learning, Teaching, & Researching Optimization

This guide offers general suggestions drawn from recent research. Every person thinks, works, and recharges differently. Please treat what follows not as a checklist to follow slavishly, but as a menu of ideas — pick what resonates, adapt freely, and discard whatever does not fit your life.

181st University Of Notre Dame Commencement, University Of Notre Dame

Commencement Programs

• SCHEDULE OF EVENTS 4
• HEARING IMPAIRED INFORMATION 9
• GRADUATE SCHOOL 10
• MENDOZA COLLEGE OF BUSINESS GRADUATE BUSINESS 32
• GRADUATE ARCHITECTURE 38
• LAW SCHOOL 39
• UNIVERSITY COMMENCEMENT CEREMONY 42
• COLLEGE OF ARTS AND LETTERS 44
• COLLEGE OF SCIENCE 51
• COLLEGE OF ENGINEERING 55
• MENDOZA COLLEGE OF BUSINESS 61
• SCHOOL OF ARCHITECTURE 67
• KEOUGH SCHOOL OF GLOBAL AFFAIRS 67
• VALEDICTORIAN CANDIDATES 68
• EMERITI FACULTY 68
• HONOR SOCIETIES 69
• AWARDS AND PRIZES 77
• TASSELS 100

A Quantum Phase Space Description Of Local Noise In Atomic Ensembles, Andrew Kolmer Forbes

Physics & Astronomy ETDs

Nonclassicality in quantum sensors can improve sensitivity, but often increases susceptibility to noise. Thus, modeling physically relevant noise sources and analyzing their effect on quantum metrology are both of importance to the field of quantum sensing. In this dissertation, I demonstrate that local noise sources, which are present in almost all many-spin systems, can be tractably modeled when assuming permutation symmetry of the noise, and we show that many common local noise sources can be mapped to a Fokker-Planck equation on quantum phase space. We apply this description of noise to study quantum sensing using noisy probe states and establish …