Digital Commons Network^™

On Heat Engines Having Efficiencies That Degrade With Every Cycle That Are Nonetheless Reversible: The Wonders Of Hilbert Curves In The Pressure-Volume Plane, Daniel Graham

Chemistry: Faculty Publications and Other Works

Heat engines are cornerstones in classical thermodynamics, not to mention fixtures of everyday life. As everyone knows, real heat engines are rife with sources of irreversibility, and, in turn, have efficiencies that degrade over time. Here we chart a classical heat engine whose efficiency degrades with every cycle, but maintains perfect reversibility nonetheless. There are no paradoxes in play due to the inviolability of the thermodynamic laws. Rather the engine operates transparently according to Hilbert curves that fill the pressure-volume plane. The assembly of the curves is iterative and digital whereby no information is lost over every cycle.

Regulatory Reform For Agentic Ai: Addressing Governance Challenges In Federal Ai Adoption, Satyadhar Joshi

Harrisburg University Other Works

The rapid advancement of artificial intelligence (AI), particularly agentic AI systems capable of autonomous decision-making, has exposed significant gaps in existing federal regulatory frameworks. This paper examines the regulatory barriers inhibiting AI innovation and adoption identified in the Office of Science and Technology Policy's (OSTP) Request for Information (RFI) on regulatory reform. We analyze five categories of barriers—regulatory mismatches, structural incompatibility, lack of clarity, direct hindrance, and organizational factors—and propose a comprehensive governance framework integrating technical standards, risk management protocols, and policy recommendations. Drawing from extensive literature on AI governance tools and frameworks, we present actionable solutions for modernizing federal …

Neural Dynamics In The Cortico-Basal Ganglia-Thalamic-Cortical Loop Underlying Flexible Motor Timing, Zidan Yang

Electronic Theses and Dissertations 2020 - Present

The ability to flexibly time actions is a fundamental aspect of voluntary motor control. The frontal cortex and striatum exhibit ramping neural activity that predicts movement initiation, suggesting they function as a core timing circuit. However, the distinct computational roles of these highly interconnected regions and the specific cell types involved have remained elusive. This thesis investigates the neural mechanisms of motor timing by combining cell-type-specific perturbations, multi-regional electrophysiology, and computational modeling in mice. First, we demonstrate that the frontal cortex and striatum play complementary roles in an adjustable timing mechanism. Transiently silencing the frontal cortex effectively “pauses” the ramping …

On The Derivation Of The Ungerboeck Observation Model For Offset Qpsk, Michael Rice

Faculty Publications

This report derives maximum likelihood sequence estimator for Offset QPSK (OQPSK) operating over frequency selective channel. The maximum likelihood sequence estimator takes the form of the Viterbi Algorithm operating on a trellis defined intersymbol interference caused by the frequency selective channel. Because the distorted pulse shape does not satisfy the Nyquist no-ISI criterion, the matched filter output samples contain correleted noise. The derivation uses Ungerboeck’s method to create a recursive causal metric suitable for use with the Viterbi Algorithm.

Nanodiamonds In Advancing Biomedical Sciences, Ebenezer Owusu, Sofia Lerma, Jinhyeong Jang, Deepa Roy, Shizue Mito, Upal Roy, Elena A. Rozhkova

Health & Biomedical Sciences Faculty Publications

Nanodiamonds (NDs), tetrahedral carbon structures with a size ranging from 1 to 100 nm, have gained growing attention in recent years due to their distinct optical, thermal, and mechanical properties compared to other carbon nanomaterials (e.g., graphene, carbon nanotubes, carbon dots). Combined with a high surface-to-volume ratio and tunable and chemically versatile surfaces, these support broad applications across catalysis, electronics, and life sciences. Moreover, the biocompatible characteristics of NDs enable their controllable interfacial interactions with biological systems, positioning them as excellent candidates for advancing cutting-edge biomedical sciences, particularly through the engineering of efficient material biointerfaces that facilitate optimal interactions with …

On Univariate Process Capability Indices: Some Issues And Applications, Kuntal Bera

Doctoral Theses

Process capability indices (PCIs) are proposed to assess the performance of manufacturing processes. PCIs evaluate the process performance by comparing the manufacturing tolerance with the natural variability of the process. Since process parameters are unknown, therefore, PCIs are estimated based on a random sample. Assessment of performance of a process based on estimated PCI values may be unreliable due to sampling fluctuations. Hence, it is essential to study the statistical properties of the estimators of PCI. Thus far, most of the studies on PCIs have been done under the assumption that the quality characteristic under investigation follows an independent and …

Development And Initial Validation Of An Instrument To Measure Teachers’ Socioscientific Issues Instruction Perceptions, Michael Edward Mitchell

USF Tampa Graduate Theses and Dissertations

Little is known about how high school science teachers perceive Socioscientific Issues (SSI) on a broad scale, including what factors shape their views of a pedagogical shift to adopt SSI. To address this critical gap, I constructed the Teachers’ Socioscientific Issues (SSI) Perceptions Survey (TSPS), the first instrument specifically designed and initially validated to measure teacher perceptions of SSI integration. This study presents the development and validation of the TSPS, offering robust evidence for its reliability, fairness, and construct validity.

Survey development adhered to gold-standard psychometric protocols (Bandalos, 2018; Crocker & Algina, 1986; DeVellis, 2012; McCoach et al., 2013) and …

The Nurse's Role In Patient Preparation For Discharge To Optimize Patient Outcomes And Reduce Readmissions, Marie-Antoinette Chevrin

Walden Dissertations and Doctoral Studies

For this Doctor of Nursing Practice (DNP) project, I created a staff education initiative aimed at enhancing nurses’ understanding of heart failure (HF) and clarifying their role within clinical pathways for managing decompensated HF. HF is a common and complex condition, accounting for 1-2% of hospital admissions. In response to the rising 30-day readmission rate and lack of a standardized discharge protocol, an evidence-based staff education program was developed. According to the “ACC/AHA/HFSA 2022 HF guidelines”, effective prevention and management require nurses to understand causes, risk factors, and pathophysiology of HF, along with their role in patient-centered care. Nurses routinely …

Great Lakes Water Levels: Curve Fitting, Statistics, And The Unacceptable-Value Statistical Approach, Brian Barkdoll

Michigan Tech Publications

Water levels in the Great Lakes fluctuate over time. Excessively high levels can cause flooding, erosion, property damage, and loss of human life. Excessively low values inhibit shipping since boats cannot reach the ports and docks due to low draft, thereby causing loss of economic resources. Water level prediction has proven elusive, thereby requiring a new approach to analyzing the historical record of water level values. Methods attempted here include curve fitting, conventional statistics, and a newly introduced Unacceptable-Value Statistical Approach (UVSA). The UVSA comprises only analyzing flooding and drought events. All remaining values are acceptable and, therefore, are not …

Detecting Burned Vegetation Areas By Merging Spectral And Texture Features In A Resnet Deep Learning Architecture, Jiahui Fan, Yunjun Yao, Yajie Li, Xueyi Zhang, Jiquan Chen, Joshua B. Fisher, Xiaotong Zhang, Bo Jiang, Lu Liu, Zijing Xie, Luna Zhang, Fei Qiu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Timely and accurate detection of burned areas is crucial for assessing fire damage and contributing to ecosystem recovery efforts. In this study, we propose a framework for detecting fire-affected vegetation anomalies on the basis of a ResNet deep learning (DL) algorithm by merging spectral and textural features (ResNet-IST) and the vegetation abnormal spectral texture index (VASTI). To train the ResNet-IST, a vegetation anomaly dataset was constructed on high-resolution 30 m fire-affected remote sensing images selected from the Global Fire Atlas (GFA) to extract the spectral and textural features. We tested the model to detect fire-affected vegetation in ten study areas …

October 2025, Office Of Research

Research Update

No abstract provided.

A Robust And Energy-Efficient Federated Ids For Iiot Using Spiking Neural Networks And Differential Evolution With Adversarial Resilience, Mohammad Othman Nassar

Iraqi Journal for Computer Science and Mathematics

The Industrial Internet of Things (IIoT) is faced with increasing cybersecurity threats that require lightweight, fast, and resilient intrusion detection systems (IDS). This study presents a novel federated IDS framework that integrates federated learning (FL), Spiking Neural Networks (SNNs), and differential evolution (DE). The use of SNNs within a federated context is a rare and innovative contribution that enables effective temporal feature extraction from IIoT traffic. DE is employed as a global optimization mechanism, enhancing robustness and generalization beyond conventional federated aggregation. To further strengthen resilience, synthetic adversarial noise is injected during training, allowing evaluation in realistic poisoning scenarios. The …

Wagon Tracks Volume 39, Issue 3 (May 2025)

Wagon Tracks

Contents

2 On the Cover: Symposium Logo, Survey Chain

4 Trail Writings: Chris Day

5 Joanne’s Jottings

6 News along the Trail

7 New Wagon Tracks Editor Named

8 Letter to Editor: Steve Schmidt

9 The Importance of Funding, Josiah Gregg Society: Rich Lawson

10-14 Marking a Road to Santa Fe: Symposium 2025

15-20 Leitensdorfer Men and Women: Santa Fe Trail Travelers and Traders By Doyle Daves

21-27 In Search of Furs and Freedom: African Americans on the Santa Fe Trail By William W. Gwaltney

28 Chapter Reports

29 Membership Form

32 Calendar

Wagon Tracks Volume 39, Issue 2 (Feb 2025)

Wagon Tracks

Contents

2 On the Cover: Jicarillo Young Woman and Cowboy Edward S. Curtis

4 Trail Writings: Chris Day

5-7 Joanne’s Jottings

7 Letter to Editor: Mike Olsen

7-9 News along the Trail

10 Preservation Committee: Alexa Roberts

12-17 An 1859 Contract for Exporting Wool on the Santa Fe Trail By Mary Penner

18-21 White Men Now Living Amongst Us By Ronald D. Parks

22-24 Jicarillo Apache Resistance By Doug Hocking

7/24 SFTA and Chapter 2024 Highlights

25 Chapter Reports

25 Membership Form

28 Calendar

Conflict Clarity: How To Teach Students To Turn Disputes Into Growth Opportunities, Eileen Paige Petzold-Bradley

Learning and Educational Center Virtual Teaching and Learning Conference

Conflict is an unavoidable part of learning and working in today’s fast-changing industries. Faculty often observe students struggling with teamwork, communication breakdowns, and emotional self-management during group projects or internships. This session equips educators with practical strategies to help students build durable skills—conflict resolution, emotional intelligence, and self-awareness—that translate directly into professional success.

Drawing on research in conflict management, leadership, and organizational psychology, participants will explore the “Conflict Clarity” framework: a set of teaching tools, reflection prompts, and case scenarios designed for classroom use across disciplines. Faculty will learn how to integrate conflict styles, the CLEAR conversation framework, and role-play …

Think Piece: Urban Echoes: How The New Historiography On Cities Is Reframing Our Understanding Of Mao’S China, Taoyu Yang

Asia Pacific Perspectives

Despite the conventional portrayal of the Chinese revolution as a predominantly peasant-oriented movement, cities emerged as critical arenas for the Chinese Communist Party’s project of modernization and class restructuring during Maoist period (1949–1976). Over the past decade, scholarly attention has increasingly turned to the urban dimensions of the early years of the People’s Republic. This think piece addresses how recent scholarship on cities offers new analytical insights into our understanding of Maoist China by focusing on six recently published monographs. Themes to be discussed in this essay include the contested and evolving notion of socialist modernity, the transformative effects of …

Ethosai: An Architectural Paradigm For Security And Auditability In Hybrid Agentic Ai Systems, Hp Inc

Defensive Publications Series

This disclosure presents EthosAI, a security architecture for distributed AI agent systems combining mandatory communication interception with context-aware policy enforcement. The key innovation is the symbiosis between: (1) a transparent sidecar proxy that architecturally prevents bypass by intercepting all agent communications, and (2) a Policy Enforcement Engine (PEE) that makes real-time authorization decisions based on rich contextual metadata (data origin, geographic location, temporal constraints, interaction patterns) embedded in standardized MCP packets. This prevents agent collusion, enables complete audit trails across organizational boundaries, and enforces data sovereignty in hybrid cloud environments.

Ai-Powered Layout Generation For Dynamic Advertising Displays, Yang Zhao, Clyde Li, Parag Jain, Sam Terwilliger, Alan Ruthazer, Rachel Lavelle, Jiachen Wang, Haifeng Gong

Defensive Publications Series

This publication describes an approach for creating dynamic layouts in responsive advertising displays by utilizing artificial intelligence (AI) to extract comprehensive metadata from image assets. This methodology enhances presentation effectiveness by tailoring the arrangement and appearance of visual components based on the specific content of each image. Key information, such as saliency maps identifying visually important regions, extracted color data, and image quality signals, is leveraged during ad rendering to achieve dynamic layout adjustments, prevent component overlap, and ensure visual coherence for improved ad performance in responsive advertising.

Ai-Driven Dynamic Generation Of User Interfaces, Raviteja Govindaraju, Harshdeep Singh

Defensive Publications Series

The predominant mode of interaction with artificial intelligence (AI) models is text or speech queries. The reliance on such chat-centric interfaces requires users to formulate specific and detailed (series of) questions to elicit the desired response from the AI model. This disclosure describes techniques that dynamically generate interactive user interfaces in response to user queries directed at an AI model. The techniques augment conventional chat-based interactions by interpreting the context and the user’s intent to construct a relevant graphical user interface (GUI) that facilitates further exploration and action. The GUI can include mouse (e.g., click, drag-and-drop, etc.) or touch-driven commands, …

Analysis Of An Effective Training Curriculum: Solutions Toincrease Participants' Interest In Training Teachingmaterials, Maulidya Husnul Khatimah, Yoto Yoto

Jurnal Pendidikan Sains

This research is important because it analyzes the curriculum as a primary tool for generating and maintaining participant interest. Curricula that are irrelevant, monotonous, or misaligned with participant needs are often the main causes of low motivation and participation. Furthermore, this research encourages the exploration and implementation of more innovative teaching methods and materials in training curricula. External pressure in the form of demands or instructions, rather than internal motivation, drives most training activities. This can reduce engagement and learning effectiveness. To overcome this, training institutions need to design programs that are relevant, flexible, and able to encourage participants' intrinsic …

Augmented Reality-Assisted E-Module On Temperature Andheat Content (Emarks), Tetri Sabrina, Ika Mustika Sari, Dedi Sasmita

Jurnal Pendidikan Sains

Temperature and heat content (calor) material in physics often involves concepts and phenomena that are difficult to observe directly or are abstract (such as energy transfer, particle movement, and changes in state). EMARKS (AR-based E-modules) are important because Augmented Reality (AR) allows the visualization of these abstract concepts in the form of interactive 3D models in the user's real environment. This helps students understand the concepts more concretely and easily. The development of E-modules is an innovation in learning media that is relevant to the demands of the digital era and the needs of modern students. The use of advanced …

The Effect Of Guided Inquiry Model With Deep Learningapproach On Student’S Hots In Elements, Compounds,And Mixtures At Junior High School, Friska Pakpahana, Retno Dwi Suyanti

Jurnal Pendidikan Sains

The current education curriculum places a strong emphasis on developing HOTS skills (such as analyzing, evaluating, and creating) to prepare students for the challenges of the 21st century. School learning often focuses on lower-level cognitive domains (memorizing and understanding). This research seeks to address this gap by offering a potentially effective learning model. The guided inquiry model positions students as active participants in learning, encouraging them to investigate, discover, and formulate concepts independently with teacher guidance. This strongly supports the development of critical thinking and problem-solving skills. Therefore, this study aims to analyze the effect of the guided inquiry model …

Guided Inquiry Learning Assisted By Crossword Puzzlemedia: Student Scientific Literacy And Critical Thinkingability For Middle School, Agis Putri Niswa, Mariati Purnama Simanjuntak, Ramlan Silaban, Fauziyah Harahap, Ridwan Abdullah Sani

Jurnal Pendidikan Sains

Scientific literacy and critical thinking skills are two fundamental competencies that students need in the 21st century. Scientific literacy is essential for students to understand and use scientific knowledge to make informed decisions, while critical thinking trains students to analyze information, evaluate arguments, and solve problems logically. Therefore, the intent of this study was to determine the effect of the guided inquiry learning model assisted by crossword puzzle media on students’ scientific literacy and critical thinking skills. The type of research used was quasi-experimental with a two-group pretest-posttest design. The sample consisted of two classes: class VII-8 as the control …

Computer Organization With Arm64, Seth D. Bergmann

OER Textbooks

This book is intended to be used for a first course in computer organization, or computer architecture. It assumes that all digital components can be constructed from fundamental logic gates.

The book begins with number representation schemes and assembly language for the ARM-64 architecture, including assembler directives and floating point instructions. It then describes the machine language instruction formats, and shows the student how to translate an assembly language program to machine language.

There is then an introduction to boolean algebra and digital logic, followed by a description of the memory hierarchy, including cache memory, RAM, and virtual memory.

The …

November 6, 2025, James Madison University

The Breeze, 2020-

The Breeze is the student newspaper of James Madison University in Harrisonburg, Virginia.

Torso Synthetic Ct Generation By Integrating Deep Learning And Segmentation For Fdg-Pet/Mr Attenuation Correction, Jin Uk Heo, Robert S. Jones, Theodore Higgins Arsenault, Jennifer Dorth, Tithi Biswas, Raymond F. Muzic Jr

Faculty Scholarship

Introduction. Positron Emission Tomography/Magnetic Resonance (PET/MR) offers benefits over PET/CT including simultaneous PET and MR acquisition, intrinsic spatial registration accuracy, MR-based functional information, and superior soft tissue contrast. However, accurate attenuation correction (AC) for PET remains challenging as MR signals do not directly correspond to attenuation. Using deep learning algorithms that learn complex relationships, we generate synthetic CT (sCT) from MR for AC. Our novel method for AC, merges deep learning with threshold-based segmentation, to produce an AC map for the entire torso from Dixon MR images, which heretofore has not been demonstrated. Method. Twenty-nine prospectively collected, paired FDG-PET/CT and …

Military Manpower Policy And Women’S Labor Market Outcomes, Amy Burnett Cross

Dissertation Awards

This dissertation examines how U.S. military manpower policy, when used to alleviate recruitment shortfalls, has shaped women’s participation in the civilian labor market. Across two chapters, I study military policy changes during periods of high demand for active duty service members to evaluate their impact on women’s labor force participation and entry into male-dominated occupations.

Advancing Delirium Detection Through The Open Health Natural Language Processing Consortium And The Evolve To Next-Gen Accrual To Clinical Trials Network, Sunyang Fu, Min Ji Kwak, Jaerong Ahn, Zhiyi Yue, Shreyas Ranganath, Joseph R Applegate, Andrew Wen, Liwei Wang, Chenyu Li, Michele Morris, Kelly M Toth, Timothy D Girard, John D Osborne, Richard E Kennedy, Nelly-Estefanie Garduno-Rapp, Phillip Reeder, Justin F Rousseau, Chao Yan, You Chen, Mayur B Patel, Tyler J Murphy, Bradley A Malin, Chan Mi Park, Heling Jia, Sandeep Pagali, Allyson K Palmer, Jennifer St Sauver, Sunghwan Sohn, Elmer V Bernstam, Shyam Visweswaran, Yanshan Wang, Hongfang Liu

Faculty, Staff and Student Publications

Background: Delirium is often underdiagnosed in clinical practice and is not routinely coded for billing. While manual chart review can identify delirium, it is labor-intensive and impractical for large-scale studies. Natural language processing (NLP) can analyze unstructured text in electronic health records (EHRs) to extract meaningful clinical information.

Methods: To support national integration of NLP for EHR-based delirium identification across different institutions, we launched the Delirium Interest Group within the national Evolve to Next-Gen Accrual to Clinical Trials (ENACT) NLP Working Group. This paper outlines our initial efforts to standardize, evaluate, and translate an NLP-based delirium detection model into the …

Curriculum Subcommittee Minutes November 6, 2025, Utah State University

Educational Policies Committee

• Approval of Minutes - October 2, 2025
• Program Proposals
• Semester Course Approval Reviews
• Other Business
• Adjourn: 3:00 pm

General Education Subcommittee Minutes November 6, 2025, Utah State University

Educational Policies Committee

• Call to Order
• Approval of Minutes - October 2, 2025
• Course Approvals/Removals/Syllabi Approvals
• New Business
• Depth Discussion
• Additional Items
• Adjourn: 9:25 am