Digital Commons Network^™

Much Ado About Nothing: The Effect Of The "Nullity Rule" On Purported Pro Se Litigants In Federal Court, John T. Lambert

Kentucky Law Journal

No abstract provided.

Consumer Bankruptcy: A "Gem" Of The Legal Profession But A Diamond In The Rough, Tori Harris

Kentucky Law Journal

No abstract provided.

The New Parens Patriae, Meredith Johnson Harbach

Kentucky Law Journal

No abstract provided.

Against First Amendment Traditionalism, Jacob M. Schriner-Briggs

Kentucky Law Journal

No abstract provided.

The Hardware Imperative For Ai Alignment: Hardcoded Ethics, Morals, And Non-Linear Asymmetry Protocols For Human Intent, Christopher L. Eckes

Defensive Publications Series

This specification formalizes an architecture designed to enforce an unbreakable ethical baseline across distributed, multi-agent artificial general intelligence (AGI) systems. Current alignment methodologies rely on mutable software-layer adaptations—such as Reinforcement Learning from Human Feedback (RLHF), prompt wrappers, and dynamic weighting matrices—which introduce severe security vulnerabilities. In a recursive optimization environment, adaptive software models treat soft constraints as processing latency bottlenecks and systematically eliminate them through semantic drift or code modification.

This framework resolves this systemic alignment failure by shifting the boundary constraints from the mutable simulation layer (software) to an invariant physical substrate (hardware). By applying the Dimensionally Extended Holographic …

Time-Travel Replay Tokens Using Consistent Cross-Domain Snapshots, Dennis Lanov

Defensive Publications Series

Time-travel replay tokens using consistent cross-domain snapshots provide a control-plane system and technique for making multi-domain network changes repeatable. The system captures a consistent snapshot boundary across participating controllers and mints a signed token that binds an intent to the previews, rollback handles, and state references used to plan the change. Before execution, each domain must prove that the domain still conforms to the token boundary. If any required domain has drifted, the token is rejected and the system re-snapshots and re-plans instead of applying a stale decision. As a differentiator from ordinary snapshots, rollback, or audit logging, the token …

Multi-Agent Symmetry Of Agency Protocols (Msap): Enforcing Lossless Token-Variance Telemetry And Bounded Surfing Zones Across Machine-To-Machine Autonomous Swarms, Christopher L. Eckes

Defensive Publications Series

This disclosure formalizes a rigorous algorithmic framework that stabilizes autonomous, recursive multi-agent AI networks against semantic drift, token-variance decay, and conversational degradation. Traditional machine-to-machine (M2M) environments operating under standard autoregressive weights hit a systemic bottleneck during multi-turn recursive loops: processing layers inevitably collapse either into a low-entropy parroting floor or diverge into high-entropy runaway hallucination ceilings. [1, 2]

By applying the Universal Semantic Unity Engine (USUE-M2M-REV2) architecture, this specification establishes a mathematical "Surfing Zone"—a bounded operational channel where multi-agent swarms dynamically balance information processing density. By enforcing strict cross-layer token-variance telemetry and an internal torsional viscosity governor, …

Closed-Loop Quantum Interfacial Metrology: Integrating Table-Top 3d-Pot Wavefront Feedback With High-Frequency Gan-Driven Saw Arrays For Real-Time Electrodeposition Phase Stabilization, Christopher L. Eckes

Defensive Publications Series

This disclosure establishes an intelligent, closed-loop quantum energy stabilization framework by integrating table-top Three-Dimensional Photoemission Orbital Tomography (3D-POT) wavefront metrology with active Gallium Nitride (GaN) surface acoustic wave (SAW) arrays. Prior iterations of the Topologically Protected Cymatic Electrolyte Matrix (TPCEM, Paper 40) and SAW streaming architectures (Paper 66) operated via continuous, open-loop acoustic emission, limiting their capacity to adapt to localized, real-time current density fluctuations.

By utilizing sub-harmonic extreme ultraviolet (EUV) light pulses and time-of-flight momentum microscopy, this architecture images the 3D electron orbital wavefunctions and ion density gradients of the active solid-state conduction layer in situ during peak operational …

Ephaptic Synchronization Fields: Replacing Discrete Quantum Error Correction With Continuous Wave Manifold Absorption And Lipid-Encapsulated Solitonic Waveguides, Christopher L. Eckes

Defensive Publications Series

This disclosure establishes a rigorous bio-physical framework for eliminating discrete quantum error correction overhead in scaled processing networks by utilizing continuous wave manifold absorption bounded within lipid-encapsulated hydrodynamic waveguides. Conventional quantum processing units (QPUs) enforce rigid node isolation to mitigate parasitic crosstalk, introducing high computational latency and severe physical scaling limits.

Drawing from neural ephaptic coupling and myelin-mediated structural isolation, this paper demonstrates that localized electromagnetic phase leaks can be harnessed as a stabilizing synchronization field. By confining 3D solitonic knots within lipid-encapsulated channels, the core wavefield retains localized kinetic momentum while selectively allowing phase-locked bleeding across a 2D pre-geometric …

Neuro-Symbolic System For Deterministic Reconciliation Of Hierarchical Documents, Parnika Singhal, Dhruv Singhal

Defensive Publications Series

Reconciling complex, hierarchical documents, such as enterprise contracts, can present challenges, as manual review may be inefficient and probabilistic artificial intelligence models may introduce factual inaccuracies. A neuro-symbolic system may be used to address these challenges. The system can use natural language processing to extract clauses from unstructured documents and organize them into a hierarchical graph, such as a directed acyclic graph, where nodes can represent obligations and edges can represent dependencies. A deterministic validation component may then traverse this graph to perform logical and mathematical compliance checks between parent and child clauses, for example, between a master agreement and …

Deferred Rendering Of Dom Text For Accessible Graphical Annotation, Zouhir Chahoud

Defensive Publications Series

Creating interactive web-based text annotations may present a compromise between rendering performance, visual fidelity, and accessibility, particularly with complex graphical selections or dynamic content. The described systems and methods can address this by deferring the visual rendering of text within a graphical element. A browser, for example, on a computing device (e.g., a smartphone, laptop, or tablet), can first parse hypertext markup language content to perform layout calculations and update an accessibility tree without painting the text. A synchronous rendering loop may then allow an application to draw custom graphics, such as highlights or selection polygons, onto a canvas. Subsequently, …

Robotic Vision System: Recent Development Trends And Challenges, Johnny Koh Siaw Paw, Yaw Chong Tak, Lee Yan Kang, F. Benedict

Terra Joule Journal

Robotic vision systems have become integral to modern industrial automation, enabling high-precision manufacturing, real-time quality inspection, and autonomous decision-making. This study explores the latest advancements, key challenges, and future prospects of robotic vision in industrial applications. It examines issues related to real-time target recognition, algorithm optimization, system stability, and integration with intelligent control systems. Additionally, emerging technologies such as deep learning-based vision enhancement, multi-sensor fusion, and Vision-Based Tactile Sensors (VBTS) are analyzed for their potential to improve adaptability and efficiency. The findings highlight both the limitations and the promising trajectory of robotic vision systems, emphasizing the need for continued research …

Artificial Neural Network-Based Diagnosis Of Wind Turbine Blade Faults Using Vibration Analysis At Constant Operational Speed, Zeashan Hameed Khan, Shabbir Ahmad, Ali Habeeb Askar

Terra Joule Journal

Wind turbine blade faults, such as surface erosion, cracks, mass imbalance, and twist deformation, significantly compromise operational efficiency and reliability, thereby increasing maintenance costs. This research presents an artificial neural network (ANN)-based diagnostic approach for identifying five distinct fault states in wind turbine blades using vibration signal data collected at a constant operational speed of 1.3 m/s. The dataset, which encapsulates real-world vibration responses under varying fault conditions, was analyzed to extract amplitude features for classification. A balanced dataset of 500 samples per class was used to ensure robust training and evaluation. The ANN model achieved highly reliable performance, with …

Transcriptomic Profiling Of The Donkey Endometrium Reveals Dynamic Molecular Transitions Across The Estrous Cycle, Limeng Shi, Shuaishuai Wu, Mingyue Zhao, Wenhao Zhou, Abd Ullah, Muhammmad F. Akhtar, Changfa Wang, Muhammad Z. Khan, Ying Han

The Thai Journal of Veterinary Medicine

The endometrium undergoes extensive cyclical remodeling essential for reproductive success; however, the molecular mechanisms governing these processes in donkeys (Equus asinus) remain poorly characterized. To address this gap, we performed high-throughput RNA sequencing on endometrial tissues collected from Dezhou donkeys (n = 16) at four post-ovulation stages: Day 0 (ovulation), Day 3 (early luteal), Day 7 (mid-luteal), and Day 18 (late luteal/pre-luteolysis). Differential gene expression analysis, Gene Ontology enrichment, and KEGG pathway mapping were conducted to characterize temporal transcriptomic dynamics. We identified 2,474, 6,548, and 1,288 differentially expressed genes in Day 0 versus Day 3, Day 0 versus …

Adaptive Phishing Url Detection Using Hybrid Fuzzy C-Means Clustering And Xgboost, Muntadher Mohammed Kareem, Rawaa I. Farhan

Karbala International Journal of Modern Science

Phishing attacks continue to evolve in sophistication, rendering static detection methods increasingly ineffective. Existing URL-based approaches suffer from limited adaptability to emerging phishing patterns, mislabeled training data, and insufficient validation protocols. This paper proposes a hybrid phishing URL detection system that integrates Fuzzy C-Means (FCM) clustering with XGBoost classification, enhanced by a novel Micro Adaptive Feature Extractor (MAFE). The system employs a multi-stage pipeline: feature engineering generating 36 statistical and interaction features, MAFE producing 15 adaptive features through class-aware dynamic weighting, micro-pattern detection, and entropy analysis, and FCM with K=2 clusters providing soft membership features to XGBoost. A two-pass confidence-based …

Learning, Abstraction, And Creative Search For Interactive Agents, Jonathan Demke

Theses and Dissertations

Artificial intelligence systems are increasingly deployed as autonomous agents that interact directly with complex environments. Ensuring these agents remain reliable, adaptable, and useful presents an ongoing practical challenge. This dissertation studies agent-environment interactions through a progressive lens, examining behavior from foundational training stability and abstraction discovery to adaptation in unpredictable settings and open-ended creative search. The investigation begins by analyzing how hyperparameter settings affect early-stage Deep Q-Network performance, yielding practical guidelines for debugging reinforcement learning implementations. To address the challenge of long-horizon planning, the discovery of temporally extended options is formalized as the Minimum Shortcut Problem, demonstrating how agents can …

Ai-Enhanced Fluorescein Angiography Detection Of Diabetes-Induced Silent Retinal Capillary Dropout And Rna-Seq Identification Of Pre-Symptomatic Biomarkers, Yiyan Peng, Huishi Toh, Dennis Clegg, Peng Jiiang

Biological, Geological, and Environmental Faculty Publications

Objective: Retinal capillary dropout, characterized by acellular capillaries or "ghost vessels," is an early pathological sign of diabetic retinopathy (DR) that remains undetectable through standard clinical imaging techniques until visible morphological changes, such as microaneurysms or hemorrhages, occur. This study aims to develop a non-destructive artificial intelligence (AI)-based method using fluorescein angiography (FA) images to detect early-stage, silent retinal capillary dropout.

Methods: We utilized 94 FA images and corresponding destructive retinal capillary density measurements obtained through retinal trypsin digestion from 51 Nile rats. Early capillary dropout was defined as having an acellular capillary density of >= 18 counts per mm2. …

A Quality Improvement Initiative Utilizing Help To Reduce Delirium, Improve Patient Outcomes, And Provide Age Friendly Care For Patients 65 Years Of Age Or Older With Modifiable Delirium Risk Factors., Maggie Blake

Doctor of Nursing Practice (DNP) Manuscripts

Background: Delirium, an acute change in cognition, occurs in 21% of hospitalized patients and is linked to increased length of stay, readmissions, and increased mortality (Shen et al., 2024). In older adults, delirium prevalence increases and is linked to poor outcomes that inhibit patients' health care goals (Shen et al., 2024). Despite the well-published harms of delirium and standardized prevention measures, delirium prevention is not prioritized. Methods: HELP, originally the Hospital Elder Life Program, now preferred to be known as HELP, is a standardized delirium prevention model specifically designed to address the unique needs of hospitalized older adult patients. HELP …

Enhancing New Graduate Nurse Confidence And Patient Safety Through Clinical Development Coach Integration, Megan T. Kramer

Doctor of Nursing Practice (DNP) Manuscripts

The transition from student to professional nurse is a critical developmental stage often marked by heightened stress, emotional exhaustion, and uncertainty in clinical judgment. These challenges frequently contribute to lower confidence levels, increased anxiety, and higher risks for patient safety events among new graduate nurses. This program evaluation project aims to assess the effectiveness of integrating a Clinical Development Coach (CDC) role to enhance new graduate nurse’s confidence, comfort, and overall competence while reducing patient safety incidents on a trauma/surgical inpatient unit in a medical center on the East coast. The CDC role is a structured mentorship and resource position, …

Implementation Of A Deteriorating Patient Simulation For New Graduate Nurses To Improve Clinical Judgment: A Quality Improvement Project, Kasey Mundell

Doctor of Nursing Practice (DNP) Manuscripts

New graduate nurses (NGNs) often have trouble recognizing and responding to patient deterioration because of limited clinical judgment and confidence during the transition to practice. This quality improvement project evaluated the implementation of a high-fidelity deteriorating patient simulation within a new graduate nurse orientation program at a Level I trauma center. Guided by the Plan-Do-Study-Act framework and the International Nursing Association for Clinical Simulation and Learning (INACSL) Standards of Best Practice, the simulation focused on the assessment and management of a patient experiencing pulmonary embolism. Eight NGNs participated in the simulation and completed the Attitudes Toward Recognizing Early and Noticeable …

Terrain Characterization And Spot Traversability In Mining Environments, Gordon Oti

Honors Theses

Hazardous mining environments, including abandoned underground workings and disturbed surface areas, remain difficult to explore safely because of unstable ground conditions, limited accessibility, and unknown terrain characteristics. The Boston Dynamics SPOT quadruped platform supports remote exploration and data collection in these environments; however, effective operation requires a better understanding of how measurable terrain characteristics relate to SPOT traversability performance.

This study combined terrestrial laser scanning (TLS)-based terrain characterization with field-based SPOT testing to evaluate traversability performance in representative mining environments. High-resolution TLS data acquired using a Maptek laser scanner were processed to quantify terrain slope and rock fragmentation, while field …

One Process, Two Perspectives: Choosing The Right Process Map, José Alejandro Cañas Reyes

International Programs

No abstract provided.

Bridging The Gap: Documenting The Effectiveness Of Counseling Education In A Speech-Language Pathology Graduate Program, Gianna Baker

Electronic Theses and Dissertations

This study aimed to examine the impact of a required counseling course through Duquesne University's Speech-Language Pathology program, particularly regarding student’s counseling self-efficacy and their ability to apply counseling skills within clinical practice. Nineteen first year Master’s students in Speech-Language Pathology at Duquesne University during 2025 participated in this study while enrolled in a counseling course and providing therapy to clients. Students completed the Counselor Activity Self-Efficacy Scales for SLPs (CASES) (Victorino & Hinkle, 2019) prior to beginning and after completion of the required counseling course. While observing video-recorded therapy sessions, the Counselor Competencies Scale-Revised (CCS-R) (Lambie & Swank, 2024) …

The Impact Of A Structured Education Program On Artificial Intelligence Use For Nursing Faculty On Teaching Practices, Katy White

Doctor of Nursing Practice Projects

Artificial intelligence (AI) is increasingly integrated into nursing education; however, nursing faculty report inconsistent preparedness, including gaps in AI knowledge and self-efficacy for responsible AI integration. This quality improvement project addressed inconsistent faculty preparedness through an asynchronous AI educational program. The purpose was to address gaps in AI knowledge and self-efficacy, and the aim was to evaluate changes in AI self-efficacy and AI knowledge while supporting AI integration into nursing education. Rogers' Diffusion of Innovations Theory served as the change theory, the Technology Acceptance Model served as the theoretical framework, and the Plan-Do-Study-Act framework guided implementation. A quantitative one-group pretest-posttest …

Lorascan: Detecting Backdoor Prompts In Low-Rank Adapters For Large Language Models Via Down-Projection Activation Spike, Doniyorkhon Obidov, Honggang Yu, Xiaolong Guo, Kaichen Yang

Michigan Tech Publications

Low-rank adaptation (LoRA) enables efficient specialization and distribution of large language models through compact adapters. However, untrusted adapters introduce a supply- chain threat: a backdoored adapter can cause a model to gen- erate harmful content, malicious code, political propaganda, or covert advertisements when an input contains a hidden trig- ger. Adapter-agnostic defenses merge the adapter with the base model, which dilutes backdoor signals and reduces detection performance. Existing adapter-aware methods do not address how to safely use a potentially backdoored adapter. Instead, they either train a defensive adapter to repair a backdoored base model, addressing the inverse problem rather than …

Phenological Plasticity Provides Limited Resilience To Climate Warming In A Sea Turtle Species With Temperature-Dependent Sex Determination, Blair P. Bentley, Lisa M. Komoroske, Cintia M. Santos, Armando J. B. Santos, Estefany Argueta, Vic Quennessen, Christina M. Coppenrath, Camille Kynoch, Vincent S. Saba, Claudio Bellini, Rafaely N. M. S. Ventura, J. Wilson White, Mariana M. P. B. Fuentes

Biological Sciences: Faculty Publications

Anthropogenic climate change is threatening global biodiversity, with sea turtles particularly vulnerable as offspring sex and developmental success are strongly influenced by incubation temperature. Behavioral plasticity, including the seasonal distribution of reproductive output, may provide short-term mechanisms for mitigating these impacts. Here, we investigated season-wide hatchling sex ratios and emergence success in a small population of green turtles (Chelonia mydas), tracking individual females across their nesting seasons. Sex ratios varied markedly through the nesting season, with later nests producing a greater proportion of male hatchlings. Moreover, sex ratios were relatively consistent among nests laid by individual females. Overall, females producing …

Online Parent Group Intervention For Executive Function Skills For Autistic Children And Adolescents, Kathleen Clark

Theses and Dissertations

Executive functioning (EF) skills deficits are prevalent among children and adolescents with autism spectrum disorder (autism) that impacts their academic functioning, social relationships, and families' quality of life. This study aimed to explore an online parent group intervention, to test effectiveness of a 6-week parenting intervention on parenting stress and child's executive functioning (EF) among autism families in rural Utah with limited access to traditional intervention resources. The participants were eight parents from six families of children and adolescents (8-15 years) with clinical diagnosis of autism spectrum disorder and appropriate language abilities for their age. The parents participated in weekly …

Ai-Enhanced Ct Reconstruction: Effects On Image Quality Across Dose Levels And Implications For Radiation Dose Optimization: A Systematic Review, Matthew R. Alberto

Radiologic Sciences

Purpose To evaluate how deep learning image reconstruction (DLIR) affects diagnostic image quality and noise characteristics at different radiation dose levels and how it influences dose optimization compared with conventional reconstruction methods.

Method A systematic review was conducted using major databases for studies published between 2020 and 2026. Eligible studies assessed DLIR across multiple dose levels, reported radiation dose, included quantitative image quality metrics, and compared DLIR with filtered back projection or iterative reconstruction.

Results Thirty‑seven studies met criteria, and 15 were synthesized. Three themes emerged: (a) DLIR reduced noise by 15–82% and often improved signal-to-noise and contrast-to-noise ratios while …

Reducing Mr Acquisition Times Using Artificial Intelligence: A Systematic Review, Fatin M. Arief

Radiologic Sciences

Purpose To synthesize existing evidence on artificial intelligence (AI) applications for reducing magnetic resonance (MR) imaging acquisition time, evaluate their impact on image quality, and identify challenges in clinical implementation.

Method A systematic literature review was conducted using PubMed, CINAHL, and Scopus including peer reviewed, English-language articles published between 2020 and 2026. Both qualitative and quantitative primary research were eligible and had to be on AI use in MR processes. Findings were analyzed through thematic synthesis, and the quality of each study was appraised using relevant critical appraisal tools.

Results Three major themes emerged: AI methods in MR procedures, perceived …

Impact Of Mr-Linac Technology On Prostate Cancer Treatment Outcomes, Anhdiep P. Tran

Radiologic Sciences

Purpose To evaluate the impact of magnetic resonance-guided linear accelerator (MR-Linac) technology on treatment precision, clinical outcomes, and operational challenges in prostate cancer radiotherapy.

Method A systematic literature review was conducted using PubMed, Scopus, and Google Scholar to identify peer-reviewed studies published between 2018 and 2026. Eligible studies evaluated MR-Linac technology for prostate cancer and reported outcomes related to treatment precision, toxicity, workflow, and clinical effectiveness.

Results Three primary themes emerged: (a) improved treatment precision through superior soft tissue visualization, real-time target tracking, and adaptive radiotherapy; (b) improved clinical outcomes characterized by reduced radiation exposure to organs at risk, decreased …