Digital Commons Network^™

Intersectional Inequalities In College Savings And Educational Outcomes Across Race/Ethnicity, Immigrant Status, And Gender: A Quant-Crit Analysis, Jason Jabbari, Ibrahim Habiba, Mat Despard, Somalis Chy

Journal of Student Financial Aid

As families use savings to further their children’s education, education serves as both a key driver of wealth and an artifact of wealth itself. Despite these cyclical relationships and the ways in which education and wealth are stratified across gender, race/ethnicity, and immigration, there is little intersectional research exploring these relationships. We employ a quantitative critical approach and leverage the first nationally representative longitudinal survey that includes information on high school achievement, college savings, borrowing, college enrollment, and major of study. We first demonstrate how race-gender and immigrant-gender intersectional groups experience disadvantages in college savings and in educational outcomes. We …

Can Technology Augment Order Writing Capacity At Regulators?, Natasha Aggarwal, Amrutha Desikan, Bhavin Patel, Satyavrat Bondre, Dipyaman Sanyal

Indian Journal of Law and Technology

This article critically examines the opportunities and challenges of using technology, in particular Large Language Models (‘LLMs’), to assist regulatory order writing in quasi-judicial settings in India. It proposes augmenting rather than replacing human decision-makers, aiming to improve regulatory order writing practice through responsible use of LLMs. This article identifies the core principles of administrative law that must be upheld in these settings and analyses how inherent limitations of LLMs may undermine these principles. The article reviews international frameworks and case studies from various jurisdictions, highlighting common design principles. It proposes a comprehensive Problem-Solution-Evaluation ('PSE') framework for responsibly integrating LLMs …

A Visual-Cultural Study Of The Paisley Motif And Its Application In Contemporary Scarf Design, Reham A. Sanad

Journal of Art, Design and Music

This study aimed to explore a significant source of inspiration in textile and fashion design, originating as an Indo-Persian design motif and becoming widespread through mass production in Europe, namely “Paisley”.  The paisley motif, in the shape of a teardrop, originating in Persia and popularised in 19th-century Scotland, represents life and eternity, showcasing a rich cultural legacy. This concept is investigated visually in the current study by examining its potential to sustain in the field of fashion and textiles. Historically, scarves symbolised status in ancient Egypt and were used in religious contexts in Eastern cultures, proving unique and deep roles …

Utilizing Deep Learning To Generate Biomorphic Furniture Design: A Generative Approach, Asmaa Medhat Abd El Aziz Mostafa, Doaa Abdelrahman Mohamed Goda, Dalia Mohamed Ezzat

Journal of Art, Design and Music

This research paper highlights the relatively unexplored potential of deep learning, a branch of artificial intelligence, to radically transform design in general, and specifically in the field of furniture design, by creating new design concepts inspired by living organisms such as marine biology. The main objective of this research is to explore the role of deep learning and artificial intelligence as tools for generating innovative and novel furniture designs inspired by marine organisms (marine biology). The research followed experimental methodology through a prompt engineering-based protocol, using ChatGPT-4 to produce an optimized prompt to be subsequently used on the (Prome AI) …

Recognizing And Rewarding Peer Review: Rethinking Research Assessment For Openness, Fairness, And Global Equity, Tung Tung Chan, Bernd Pulverer, Johan Rooryck

FORCE 2026

The Coalition for Advancing Research Assessment (CoARA) Working Group on Recognizing and Rewarding Peer Review has developed a comprehensive framework for reforming how scholarly review is valued within research careers. Our recommendations address a fundamental question: how can peer review, a critical yet often invisible scholarly contribution, be made visible, credited, and meaningfully integrated into research assessment?

Developed through a collaborative effort across 16 European organisations, the Working Group’s outputs offer targeted recommendations for four key stakeholder groups: research performing organizations, research funding bodies, publishers and editors, and individual researchers. These recommendations are structured across five key dimensions:
(1) Openness: …

Open Research Information - How To Support Publishers To Make Metadata Openly Availble, Bianca Kramer

FORCE 2026

Research information, or scholarly metadata, is important for decision making around strategic priorities, distribution of resources, and evaluation of researchers and institutions. It is also used to assess the effect of policies, and to find and assess research results. Open research information (free to access and free to (re)use) is increasingly valued for fair assessment and equitable decision making, and is also important in digital sovereignty.


The Barcelona Declaration on Open Research Information calls on organizations performing, funding and evaluating research to make openness of research information the default, work with services and systems that support and enable open research …

Fatigue Behavior Characterization Of Magnesium And Aluminum Alloys In Military Trainer Aircraft, Alysson Sousa Rabelo, José Aécio Gomes De Sousa, Feliciano José Ricardo Cangue, Luiz Leroy Thomé Vaughan

Journal of Aviation Technology and Engineering

The increasing demand for lightweight and durable materials in aviation industry necessitates continuous improvements in research into fatigue-resistant alloys to improve operational efficiency, safety, and cost-effectiveness. The estimation of the operational life of aeronautical structures is directly related to the study of their mechanical properties, particularly concerning fatigue behavior due to the constant exposure to cyclic loads. For this reason, the aeronautical sector often invests significant capital in research for the development of new alloys that enable high structural performance, lightness, low cost, high durability, and tolerance to environmental damage. Despite the advancements in composite materials, aluminum and magnesium alloys …

Into The Unknown: Ai Adoption And Job Satisfaction Of Christian Faculty, Hailey A. Manicone, Roger B. Bingham, Ireremena E. Felixotuorimuo, Linnaya M. Graf, Rachel A. Joseph, Erica Danielle Moore, Joshua E. Wilson

Journal for the Scholarship of Teaching & Learning

The purpose of this study was to capture the lived experiences of faculty members at Christian higher education institutions regarding the impact of artificial intelligence (AI) on faculty job satisfaction. The study addressed two primary research questions: (1) What are the perceptions of Christian higher education faculty regarding expectations related to their use of AI in teaching? (2) How do these perceptions influence their job satisfaction? A transcendental phenomenological approach was used to gather data from six participants from a faith-based institution in the southeastern United States through individual interviews, focus groups, and journal prompts. Analysis followed Moustakas’ (1994) four-step …

Safe By Construction, Personalized By Design: Formal Methods Meet Human Feedback For Safe And Adaptive Autonomous Systems Behavior, Ruya Karagulle, Necmiye Ozay

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Control Theories For Machine Learning Algorithms Analysis And Design (Ct4ml): An Overview Of A Short Course, Yangquan Chen

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Robustness Of Gradient-Based Optimization Under Perturbations: From Deterministic To Stochastic Noise, Leilei Cui

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Maximal State-Control Invariant Sets For Linear Systems, Ahmad Amine Mr., Nick-Marios T. Kokolakis, Ugo Rosolia, Truong X. Nghiem, Rahul Mangharam

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Fairness-Aware Management Of Electric Vehicle Charging Stations, Paulo Bessa Do Rego Monteiro, Ricardo Pinto De Castro

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Advances In Sampling-Based Uncertainty Quantification For Safe Learning-Based Control, Abdullah Tokmak, Thomas B. Schön, Dominik Baumann

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Blood Pressure Prediction During Hemorrhage And Blood Transfusion: A Population-Informed Sequential Inference Approach, Yi-Ming Kao, Parham Rezaei, Sina Masoumi Shahrbabak, Jeremy Alanano Pepino, Ian Sebastian Kirk Shogren, Yang Wang, Andrew Tomas Reisner, Jin-Oh Hahn

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Identifiability, Observability, Parameter Reduction, And State Estimation For Nonsmooth Dynamical Systems, Hesham Abdelfattah, Peter Stechlinski, Sameh Eisa

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Bilevel Convex Identification Of Autonomous Multi-Mode Switching Systems, Kaito Iwasaki

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

The General Polyak-Lojasiewicz Inequality And Its Connection To Neural Network Training, Arthur Castello B. De Oliveira, Eduardo Sontag

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Towards Adaptive Driver Training: Online Estimation Of Dual-Task Performance Model Parameters, Aleksandra Dudek, Patrick Linford, Zihan Yu, Scott James, Matthew Castanier, Chris Vermillion, Kira Barton

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

System Identification For An Impedance-Controlled Exoskeleton, Mason D. Mathias, Chad G. Rose, Rhet O. Hailey

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Rumor Propagation And Regulation: A Graphon Game Approach With Stackelberg Control, Huaning Liu, Gokce Dayanikli

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Entropy-Aware Model Predictive Control For Transient Quality Mitigation In Metal Additive Manufacturing, Md Shafikul Islam, Mahathir Mohamamd Bappy, Saifur Rahman Tushar

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Learning Hidden Control Laws For Gps Spoofing Via Unknown-Input Estimation And Reservoir Computing, Seif O. Elsabagh, Wenbin Wan

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Multiagent Social Influence: Modeling Persuasion In Contested Social Networks, Renukanandan Tumu, Cristian Ioan Vasile, Victor Preciado, Rahul Mangharam

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Gap Metrics For Model Fidelity Quantification In Dynamical Systems, Quintin Nelson, Manoranjan Majji

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

A Comparator-Free Architecture For Maximum Product-Exponent Detection Via Or-Bucketing, N/A, N/A

Defensive Publications Series

This publication describes a hardware architecture for floating-point dot-product arrays that performs exponent alignment using a comparator-free OR-bucketing topology. The architecture uses spatial unrolling to create a single-cycle, parallel-prefix logic tree that is purely combinational. The design exploits algebraic properties to cancel out exponent biases during alignment, which allows the primary timing path to remain completely unsigned and free of bias subtractors. By managing excess timing slack, the system supports various operating modes for artificial intelligence accelerators, including high-throughput and high-efficiency modes. Keywords: floating-point, dot-product array, exponent alignment, OR-bucketing, spatial unrolling, bias cancellation, parallel-prefix logic, artificial intelligence accelerator.

Mathematical Verification And Automated Translation Of Security Policies Across Container Orchestration Platforms, Utkarsh Bhardwaj, Shivank Awasthi

Defensive Publications Series

The described technology provides an automated platform for translating security policies from a source container orchestration system to a target container orchestration system. A universal intermediate representation, structured as a directed multigraph, captures security intents which are mapped to target-native primitives. Formal mathematical methods verify that the generated policies are equivalent to the original intents. Additional features include regulatory compliance validation utilizing a compliance knowledge graph, attack surface quantification across four distinct axes, the generation of cryptographic audit certificates, and parallel processing to avoid state explosion. Keywords: Automated Policy Translation, Formal Verification, Container Orchestration, Cloud Migration, Directed Multigraph, Satisfiability Modulo …

Rendering Live Data In Pre-Recorded Video Using Dynamic 3d Topology Extraction, Nikita Agarwal

Defensive Publications Series

This technology creates a way to show live, real-time information—such as current traffic or crowd sizes—directly inside a video that was recorded in the past.

The system works by following these steps:

• It analyzes a regular video to figure out the 3D shape of the environment.
• At the same time, it finds live data for the specific location shown in that video.
• It turns that live data into 3D images and places them into the video so they stay in the right spot, even if the camera moves.
• It uses depth sensing to make sure the live data is hidden …

Proactive Source-Weighted Routing For Stable Peer-To-Peer Mesh Networks With Predictive Handoff, Raghav Gupta

Defensive Publications Series

A system performs proactive routing for shared internet access in peer-to-peer (P2P) mesh networks. The system continuously monitors communication link quality by analyzing signal strength and its rate of change to compute a predictive link reliability score. When this score indicates an active link is degrading, the system proactively establishes a parallel connection to a new neighbor in the background before the original link fails. This process facilitates a handoff that avoids the latency associated with reactive route discovery. The system also uses a source-weighted path selection algorithm to evaluate multi-hop routes, calculating a path score that gives greater weight …

The Dual-Agent Architecture For Real-Time Correction Of Computational Model Outputs, Heena Piratiyath, Tanmay Kayande

Defensive Publications Series

The abstract describes a system designed to ensure AI models make fair and ethical decisions in real-time. This system uses two separate AI "agents" working together:

• The Proposer: The first agent suggests a specific action or decision.
• The Checker: The second agent (an "agentic ethicist") reviews that suggestion to make sure it follows set rules for fairness and legality.

If the suggestion is found to be unfair or biased, a "safety layer" immediately changes it to a better, more compliant alternative before the decision is finalized. This method aims to catch and fix biased AI recommendations while they are being …