Digital Commons Network^™

Activity 3: Rapid Judgment In High-Speed Mediaenvironments, Hyungjin Gill

Hyungjin Gill, Public Opinion, Propaganda, and Democratic Life

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Final 2026 Interim Site- Wide Surface Water Monitoring Quality Assurance Project Plan (Qapp) (Dated August 28, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Final 2026 Interim Site-Wide Groundwater Monitoring Quality Assurance Project Plan (Dated August 28, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Birch On Fetal Sentience, Claudia Passos-Ferreira

Animal Sentience

Birch proposes that human fetuses be recognized as sentience candidates from 12 weeks, on the grounds that midbrain-centered theories fall within the zone of reasonable disagreement among theories of consciousness. I raise a methodological and a policy problem for his view. Methodologically, whether the midbrain-centered view belongs within the zone is disputed, so there is no consensus about the consensus.  Furthermore, the evidence Birch discusses for 12 weeks does not actually estimate the onset of sentience; the proposed threshold tracks anatomical rather than functional onset. On policy, the US Supreme Court’s Dobbs ruling shows that fetal sentience is difficult to …

Turkish Translation And Cultural Adaptation Of The Evaluation In Ayres Sensory Integration (Easi), Aymen Balikci, Ayse Firdevs Aracikul Balikci, Isabelle Beaudry-Bellefeuille, Gamze Cagla Sirma, Fatos Kirteke, Zoe Mailloux, L. Diane Parham, Susanne Smith Roley, Roseann C. Schaaf

Department of Occupational Therapy Faculty Papers

INTRODUCTION: Cultural sensitivity and relevance are critical components for best practice in occupational therapy assessment. The Evaluation in Ayres Sensory Integration (EASI) is a performance-based assessment designed to evaluate sensory perception, sensory reactivity, postural control, ocular control, bilateral integration, and praxis abilities in children aged 3-12 years. Before the development of this tool, no standardized performance-based assessment of sensory integration functions had included a normative Turkish sample. The objective of this study was to translate and culturally adapt the EASI for Türkiye.

METHOD: A seven-step process for translation and cross-cultural adaptation, grounded in established methodology, was applied. The steps included …

Re: Comment Letter For Butte Priority Soils Operable Unit (Bpsou) Draft 2025 Groundwater Monitoring Data Summary Report January – December 2025 (Dated May 29, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Temporary Cattle Identification: Benefits Of Marking With Hair Bleach, Melanie Heaton, Reganne K. Briggs, Rebekah Iverson, Brooke Holgate, David Secrist

All Current Publications

Temporary identification is an important management tool for beef producers. Animals are routinely marked following breeding, pregnancy diagnosis, vaccination, treatment, sorting, shipping, and marketing so they can be quickly identified without repeated handling. Effective temporary identification improves labor efficiency, reduces animal stress, and helps ensure management decisions are applied to the correct animals. This fact sheet provides information on temporary cattle marking using hair bleach.

Ai-Based Environmental Code Checking Tool For Sustainability Best Management Practices Of Infrastructure Construction Projects, Joseph J. Kim, Pooja D. Chavan

Mineta Transportation Institute

Infrastructure construction and operation are major contributors to global greenhouse gas emissions, which account for approximately one-third of global CO₂ emissions and add to long-term environmental and air quality challenges. Sustainability rating systems such as Envision for infrastructure construction projects provide structured guidance to help teams reduce these impacts, but verifying compliance requires reviewing large volumes of project documents by hand, making the process time consuming and difficult to scale. Therefore, this research develops an AI-based environmental code checking tool that automates the interpretation of project documents and evaluates compliance on lifecycle GHG assessment under Credit CR1.2 of Envision—in other …

Visual Media, Digital Art, And The Development Of Contemporary Aesthetics: An Interview With Professor Dominic Mciver Lopes, Caishu Zhou, Dominic Mclver Lopes

Theoretical Studies in Literature and Art

In this interview, Professor Dominic Lopes provides in-depth philosophical and historical insights on a range of topics, including aesthetics, the philosophy of art, media and digital art, the cross-cultural dialogue between Eastern and Western aesthetics, as well as the relationship between an academic career and social transformation. First, Lopes introduces contemporary Western aesthetics as a discipline. Drawing on his monographs Aesthetic Life and Why It Matters and Beyond Art, he discusses the role of aesthetics in social practice, the buck passing theory, and the new definition of a “work of art”. Second, in response to the development of new …

On The Nature And Composition Methods Of Historical Xiqu Plays, Hengfu Zhu

Theoretical Studies in Literature and Art

Modern and contemporary China has witnessed continuing discussions of the nature of historical xiqu plays and the methods of their composition, with roughly four major waves of concentrated debate. The first, in the early 1940s, began with Guo Moruo's proposition that historical research seeks factual truth, whereas the writing of historical xiqu plays seeks resemblance in spirit. The second, in the early 1960s, centered on intense debates over whether historical truth and artistic truth are unified. The third began in the 1990s and continued into the early years of the new century, bringing forward such views as a spirit-infused conception …

Cognitive Resilience At The Edge: Hyperdimensional Computing Versus Deep Learning For Hardware-Degraded Rf Classification, Adrian B. Cisneros, Jeong Yang

Military Cyber Affairs

Autonomous Collaborative Combat Aircraft (CCA) operating in contested electromagnetic environments must classify Radio Frequency (RF) signals on edge silicon that degrades over the mission lifetime due to thermal stress, radiation, and manufacturing variation. Deep neural networks dominate RF classification on pristine hardware, but their weights are precise and interdependent, causing catastrophic accuracy collapse as the underlying chip ages. We investigate whether Hyperdimensional Computing (HDC), a brain-inspired paradigm that distributes information across thousands of dimensions, can provide a reliability floor where Deep Learning fails. Using the RadioML 2016.10A dataset filtered to five digital modulations relevant to drone command-and-control links, we trained …

Hands-On Ransomware: An Experiential Wannacry Case Study For Undergraduate Cybersecurity Education, Eli Creek Richmond, Thomas R. Devine

Military Cyber Affairs

Ransomware represents one of the most disruptive threats in the cyber landscape, yet hands-on malware analysis remains rare in undergraduate cybersecurity curricula. This paper presents the design, implementation, and evaluation of an experiential learning module centered on the WannaCry ransomware case study, deployed in a senior-level course at West Virginia University. Students performed static and dynamic analysis using industry-standard tools. Pre- and post-module assessments demonstrated measurable gains in self-reported competency across seven technical dimensions. The module's competencies align directly with DoD Cyber Workforce Framework Work Role 212, Cyber Defense Forensics Analyst, supporting education-to-workforce pipeline development.

From Framework To Toolchain: Implementing Zero Trust Architecture In Cloud-Native Environments For Dow Compliance, Shelby C. Snyder

Military Cyber Affairs

Federal agencies face a fiscal year 2027 target for enterprise-wide Zero Trust deployment, but NIST SP 800-207A defines logical components without identifying the Kubernetes technologies that implement them. This paper proposes a three-tier mapping of the Policy Engine, Policy Administrator, and Policy Enforcement Point to service mesh, microsegmentation, and perimeter tooling, stating the criteria by which each component is classified. It then applies a defined rubric to six Zero Trust vendors across component alignment, Kubernetes capability, federal authorization posture, and evidence quality, finding that no single vendor covers all three tiers. The mapping is a testable architectural proposition; a Stage …

Hybrid Deep (Cnn-Bilstm) Intrusion Detection For Defense And Mission-Critical Networks, Corey A Cheng, Jermaine Anim-Addo, Asma Jakir Hussain, Zion O Smith-Fox, Sanjay Goel, Yuksel Celik

Military Cyber Affairs

This article examines how hybrid deep learning can strengthen intrusion detection for military and defense networks. Using the CSE-CIC-IDS2018 dataset, the study evaluates a CNN-BiLSTM model designed to detect benign traffic and multiple attack categories, including DDoS, DoS, botnet, brute-force, web attack, and infiltration activity. The model achieved strong multi-class detection performance, with 0.9893 accuracy and 0.9979 ROC-AUC. The findings suggest that AI-supported intrusion detection can improve cyber defense operations, analyst triage, and protection of mission-critical networks.

Characterizing Advanced Persistent Threats With Cyber Attack Flow Metrics, Tyler Miller, Caleb Chang, Shouhuai Xu

Military Cyber Affairs

Cyber attack campaigns vary not only in scale but in structure, yet conventional characterizations often reduce them to a single dimension such as technique count or impact severity. In this paper we extend the concept of cyber attack flows by defining three new metrics, novelty, technique complexity and flow complexity. Then we characterize the attack flows of three advanced persistent threat campaigns using these metrics and draw insights regarding their capabilities. Our findings include that low novelty does not equate to low attack capabilities and that exploitation of an internet-facing appliance is a common initial attack vector.

Semantic Shields: Automating Critical Infrastructure Defense Via Nlp-Driven Ransomware Profiling, Henry Trowbridge, Ian Zalcberg, Ryan Schley, Carter Yagemann, Natasha Phan, Srikar Maduposu, Vimal Buck

Military Cyber Affairs

Ransomware poses a growing threat to critical infrastructure, where successful attacks can disrupt operational technology (OT) and industrial control systems (ICS) with significant public safety consequences. However, attributing ransomware incidents to specific threat actors remains challenging due to ransomware-as-a-service ecosystems, actor rebranding, and the obfuscation of traditional indicators of compromise. This paper presents Semantic Shields, an NLP-driven attribution framework that leverages BERT-generated semantic embeddings and DBSCAN clustering to profile ransomware actors through the linguistic characteristics of ransom notes. Using a dataset of 295 ransom notes from 189 distinct threat groups, the framework achieved an 87.2% true positive clustering rate and …

Closing The Interpretability Gap: Explainable Ml-Based Malware Detection For Defensive Cyberspace Operations, Tashi Stirewalt, Sean Hodgson, Puumaaya Tahiru, Assefaw Gebremedhin

Military Cyber Affairs

This paper presents an end-to-end, explainable malware triage pipeline designed for defense-oriented cyber operations. It combines high-performance static detection methods with analyst-centered interpretability. Utilizing the EMBER 2024 Windows PE subset, we train and evaluate four classifiers and select LightGBM as the production model based on its predictive performance, inference efficiency, and compatibility with exact tree-based attribution. The deployed system consists of four sequential components: PE feature extraction, malware probability scoring, dual explainability (using SHAP and LIME), and large language model (LLM) report generation, all integrated within a Flask web interface. On a temporal test set of 1,080,000 samples, LightGBM achieves …

Llm-Generated Countermeasures For Iot Cyberattacks, James Alger, Michael Tu

Military Cyber Affairs

The rapid expansion of the Internet of Things (IoT) has introduced significant cybersecurity challenges, particularly for resource-constrained devices that traditional intrusion detection systems often fail to protect effectively. This paper proposes a novel, two-phase autonomous security pipeline designed to bridge the gap between probabilistic threat detection and deterministic network enforcement. The framework first utilizes a custom Time Series Transformer (TST) to classify multivariate network traffic and identify specific attack vectors, such as ransomware, SQL injections, and malicious file uploads. In the second phase, an agentic AI layer, comprising a locally hosted Large Language Model (LLM) orchestrated via LangGraph, processes the …

Journal Ida 2023 102 4

Journal IDA

The Journal IDA is a peer-reviewed, scientific periodical owned and published by the Indiana Dental Association, a constituent of the American Dental Association.

Journal IDA concentrates on the clinical aspects of dentistry, including case studies and research; practice management and business aspects of dentistry, from start up to transition; and also includes special and regular feature articles.

Journal Ida 2023 102 3

Journal IDA

The Journal IDA is a peer-reviewed, scientific periodical owned and published by the Indiana Dental Association, a constituent of the American Dental Association.

Journal IDA concentrates on the clinical aspects of dentistry, including case studies and research; practice management and business aspects of dentistry, from start up to transition; and also includes special and regular feature articles.

From Static Frameworks To Adaptive Evaluation: Piloting An Ai-Powered Evaluation Planner For Media Literacy And Digital Skills Interventions, Natalia Edisherashvili, Marit Puusepp, Leen D'Haenens, Tania Azadi, Łukasz Tomczyk, Gemma Martinez Fernández, Miguel Ángel Casado Del Río, Diego Martinez-Castro

Journal of Media Literacy Education Pre-Prints

Evaluating media literacy and digital skills (ML&DS) interventions remains challenging due to limited methodological capacity, time, and resources. Existing frameworks offer valuable guidance but are static and require expert adaptation. This pilot study tested an AI-powered Evaluation Planner developed within the REMEDIS project to support practitioners in designing feasible, evidence-informed evaluation plans. Using a mixed-methods design, 56 participants from 12 countries assessed the tool’s usability, clarity, and perceived utility after completing the Planner and an online survey. Findings showed high perceived ease of use, cognitive clarity, utility, and multilingual functionality. Associations between clarity, ease of use, and intention to reuse …

Oswald Spengler, A Critical Estimate, Henry Stuart

Hannah Arendt Marginalia - All

New York : Scribner, 1952.

Call #: B3332.S44 H8

Contains marginalia, endpaper notes, marginal lining and underlining. PDF information: 24 pages - 7.9 MB

Held-Through Candidacy: Excluding Sustained-Note Interiors From Grid-Guided Onset Detection By Testing Whether The Previous Note Ever Stopped, Shane Wirkes

Defensive Publications Series

Grid-guided onset detection scores a musician’s timing by asking, at every position of a metronome grid, whether a note began there. On sustained-tone instruments (brass, single-reed, flute) this fails in one specific way: a note held across several grid positions keeps producing spectral change through vibrato, breath and pitch wobble, so its interior is reported as a run of new notes. Every test that reads the sound at the position (spectral flux, prominence, level, spectral sparsity, group delay, linear-prediction residual, pitch) is either inert on this population or removes only a minority of it at a cost in real notes …

Directed Continuity Groups For Fresh-State Multi-Machine Processing, Shivam Mohan

Defensive Publications Series

The present disclosure relates to Directed Continuity Groups for Fresh-State Multi-Machine Processing in distributed computing systems. A processing system for directing related work receives work associated with a relation, derives a relation identifier, and associates the relation identifier with a continuity group having at least two processing nodes during an active continuity interval. The processing system directs state-changing work to an authority node that applies the work to a volatile state representation and generates state-update information identifying an ordering position, while at least one reflected-state node maintains a reflected state representation. Further, the processing system directs subsequent work based on …

The Charter Of Procedural Standing. Mutual Verifiability, Reversibility, And Graduated Trust: A Short Charter For Humans And Ai Systems, Volodymyr Kotegov

Defensive Publications Series

This Charter sets out a framework for the coexistence of humans and artificial intelligence under conditions in which neither side can unilaterally, and with impunity, impose its will on the other. Discussion of the subject usually runs between “AI as a tool” and “AI that disregards humans”; this regime is left out. Procedural standing here means equality of procedure and of recognition under uncertainty, not equality of rights, power, or authority as things stand today. At the present stage all operational power rests with humans and developers, and the Charter does not hide that fact behind symmetrical language of obligation. …

Verifiable Trust: A Practice Guide To Graduated Oversight Of Advanced Ai Systems, Volodymyr Kotegov

Defensive Publications Series

This guide turns the operational core of The Human–AI Charter (Discussion Draft v1.4) into a set of protocols that researchers, evaluators, and engineers can adopt without adopting the Charter's broader positions on moral status, representation, or long-term governance. It contains five protocols and four supporting practices for keeping the oversight of advanced AI systems verifiable: measuring how well verification methods actually detect deviations (VT-1); controlling changes to the parameters that oversight depends on (VT-2); keeping verification data out of training (VT-4); financing and assigning independent evaluators so that findings do not depend on the evaluated party (VT-3); and tying the …

Self-Derived Task-Conditioned Attention Gating For Mitigating Semantic Distractors, Sumit Kumar, Shivam Mohan, Ravi Shanker Kumar Sinha

Defensive Publications Series

The present disclosure provides a method (300) for mitigating semantic distractors in artificial intelligence (AI) systems. The method (300) includes receiving contextual information and one or more associated tasks, generating token embeddings corresponding to the contextual information, and processing the token embeddings through one or more neural-network layers to establish task understanding. The method (300) further includes deriving a task vector from one or more hidden-state representations generated by the neural network, generating relevance-gating values based on the task vector and contextual representations, and applying the relevance-gating values during attention computation to determine gated attention scores. The method (300) further …

Referral-Bound Purchase Claims: Binding An Operator-Issued Referral Id To An Anonymous On-Chain Purchase Commitment For Verifiable Word-Of-Mouth, Takuya Ogura

Defensive Publications Series

A method for making word-of-mouth posts verifiable without revealing buyer identity. A purchase is recorded on a blockchain as a hiding commitment that does not identify the buyer. When the buyer chooses to post about the purchase on social media, a separate per-purchase binding record is written that contains the buyer's public account handle and, in plaintext, an operator-issued referral ID. The referral ID is generated from random bytes and exists only inside the buyer's personal connector (token) URL, which is issued automatically upon payment confirmation. A third party can therefore compare the referral URL in a post against the …

Telemetry- And Intent-Encoded Routed Expert Fabric, Dennis Lanov, Charles Fleming

Defensive Publications Series

A system is proposed herein for distributing artificial intelligence (AI) inference across endpoint, edge, and cloud tiers. The system routes each semantic portion of a request only to an execution tier permitted by enterprise policy. A local model processes the request first, and intent, local-model confidence, and live network and compute telemetry determine whether selected portions remain local or are promoted with compressed intermediate state. Promoted results are verified before acceptance, and observed outcomes are used to improve future routing and expert placement.

Multi-Tenant Traffic Disambiguation With Tenant-Indexed Ipv6 Addresses, Rashmi Garg, Jerome Tollet, Benoit Ganne, Anil Kumar Kainikara, Arthur De Kerhor

Defensive Publications Series

Proposed herein is a stateless mechanism for disambiguating overlapping private Internet Protocol version 4 (IPv4) traffic from multiple tenants by synthesizing Internet Protocol version 6 (IPv6) addresses that encode both tenant or virtual routing and forwarding (VRF) identity and the original IPv4 source address. Shared downstream gateways, including virtual private network (VPN), zero trust network access (ZTNA), Internet Protocol Security (IPsec), and cloud gateways, can receive native IPv6 traffic with globally unique source addresses without modification to understand tenants, VRFs, or overlay networks. Because the mapping is algorithmically reversible from the IPv6 address itself, return traffic can be translated back …