Digital Commons Network^™

Do Voters Understand The Benefits Of Taxes?, Benjamin Carter, Alessandro Del Ponte, Peter Discioli

Political Science Faculty Articles and Research

We use economic experiments to study a fundamental question in political economy: Do voters understand the benefits of taxes? Participants play an economic game as members of a virtual society composed of computer players. In each round, the players earn low or high income, see the distribution of income, and then vote for low or high taxes. We test whether participants vote rationally for high taxes when poor and low taxes when rich, following a classic model in political economy, or whether they focus on the burden of taxes more than the benefits. Across three experiments, poor players voted against …

Numerical Simulation Of Centrifugal Pump Performance Under Impeller Blade And Suction Diameter Variations, Gunawan Budi Santoso, Susanto -, Akhmad Nuriyanis, Anang Budhi Nugroho, Rizka Noor Miftakhul Ulum, Suyono -

Journal of Mechanical Engineering Science and Technology (JMEST)

The objective of this study is to model variations in pump geometry to obtain optimal performance under the effects of cavitation. The resulting geometric variation models were then simulated using ANSYS Fluent software. The first geometric variation model used a standard 5-blade impeller with suction pipe diameter variations of 2, 2 ½, 2 ¾, 3, 3 ¼, 3 ½, and 4 inches. The second geometric variation model for simulation used a standard 3-inch suction pipe with impeller blade variations of 3, 4, 5, 6, 7, 8, and 9. The simulation results indicated that the number of blades without changes in …

Privacy-Preserving Intrusion Detection For The Internet Of Medical Things Using Ensemble And Federated Learning, Theyab Alsolami

Electronic Theses and Dissertations 2020 - Present

The rapid proliferation of the Internet of Medical Things (IoMT) has transformed healthcare by enabling continuous monitoring, intelligent diagnostics, and data-driven clinical decision-making. However, this increased connectivity has significantly expanded the attack surface of healthcare systems, exposing sensitive patient data and critical medical devices to cyber threats such as intrusion and data exfiltration attacks. Ensuring both strong security and strict privacy preservation in IoMT environments remains a fundamental and unresolved challenge.

This dissertation investigates the design and evaluation of robust and privacy-preserving intrusion detection systems (IDS) for IoMT networks using advanced machine learning techniques. The research first examines the effectiveness …

Movement And Distribution Dynamics Of Predatory Fishes In The St. Lucie Estuary, Sarah Fae Leonowicz Torre

Electronic Theses and Dissertations 2020 - Present

Estuaries are productive but highly variable ecosystems that support recreationally and commercially valuable fisheries, as well as species of conservation concern. However, coastal development, habitat loss, altered freshwater inflow, and declining water quality can modify the environmental gradients that structure fish distributions. In the St. Lucie River and southern Indian River Lagoon, located in southeast Florida, managed freshwater discharges, watershed runoff, shoreline modification, and degradation of essential fish habitats (e.g., seagrass, oyster, and mangrove forests) have altered estuarine conditions.

This dissertation evaluates how four estuarine fish species with contrasting life histories respond to environmental variability, hydrologic disturbance, and habitat structure …

Beyond Immersion: A Stage-Based Framework For Cross-Modal Immersive Technologies In Medical Education, Christopher M. Ahmad, Ambrose Loc T. Ngo, Rae-Anne Kastle, Lance Rufino, Shantanu Amin, Brent Evan, Melissa Zolnierz

Student Publications

Background

Immersive technologies such as virtual reality (VR), augmented reality (AR), and point-of-care ultrasound are increasingly used in medical education, yet most studies evaluate these tools in isolation. As a result, the relationships among immersive experience, cognitive workload, technical performance, and downstream diagnostic assessment remain poorly understood. This exploratory secondary analysis applied the Immersive Learning Engagement-Performance (ILEP) conceptual framework to a staged multimodal dataset to examine whether selected immersive psychological variables were associated with downstream Extension Proficiency Composite and exploratory distal diagnostic performance.

Methods

This theory-informed secondary analysis used participant-level data from a prospective staged protocol involving VR, AR, and …

Depro: Understanding The Role Of Llms In Debugging Competitive Programming Code, Nabiha Parvez, Md Tanvin Sarkar Pallab, Mia Mohammad Imran, Tarannum Shaila Zaman

Computer Science Faculty Research & Creative Works

Debugging consumes a substantial portion of the software development lifecycle, yet researchers do not yet understand well the effectiveness of Large Language Models (LLMs) in this task. Competitive programming offers a rich benchmark for such evaluation, given its diverse problem domains and strict efficiency requirements. We present an empirical study of LLM-based debugging on competitive programming problems and introduce DePro, a test-case-driven approach that assists programmers by correcting existing code rather than generating new solutions. DePro combines brute-force reference generation, stress testing, and iterative LLM-guided refinement to efficiently identify and resolve errors. Experiments on 13 faulty user submissions from Codeforces …

Llm-Enabled Open-Source Systems In The Wild: An Empirical Study Of Vulnerabilities In Github Security Advisories, Fariha Tanjim Shifat, Hariswar Baburaj, Ce Zhou, Jaydeb Sarker, Mia Mohammad Imran

Computer Science Faculty Research & Creative Works

Large language models (LLMs) are increasingly embedded in open-source software (OSS) ecosystems, creating complex interactions among natural language prompts, probabilistic model outputs, and execution-capable components. However, it remains unclear whether traditional vulnerability disclosure frameworks adequately capture these model-mediated risks. To investigate this, we analyze 295 GitHub Security Advisories published between January 2025 and January 2026 that reference LLM-related components, and we manually annotate a sample of 100 advisories using the OWASP Top 10 for LLM Applications 2025.We find no evidence of new implementation-level weakness classes specific to LLM systems. Most advisories map to established CWEs, particularly injection and deserialization weaknesses. …

“Innocent” Electrolytes Can Influence Organic Electrosynthetic Selectivity, Zachary A. Nguyen, Nhu H. Quach, Mayank Tanwar, Joshua A. Beeler, Kevin Mcfadden, Dylan G. Boucher, Matthew Neurock, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Organic electrosynthesis has emerged as a powerful strategy for leveraging electricity in organic synthesis. Despite its growing popularity, the fundamental molecular interactions governing electrochemical systems remain poorly understood. Many electrosynthetic reactions show strong dependence on the identity of the allegedly inert supporting electrolyte, which can significantly impact yields and selectivity, yet the physical origins of these effects are largely unexplored. A mechanistic understanding of electrolyte effects would enable more rational reaction design for applications. Here, we use cyclic voltammetry to investigate cobalt-based metal–carbon bond homolysis and elucidate how common supporting electrolytes influence reaction rates. Bulk electrolysis experiments further reveal how …

Fort Hays State University Tiger Weekly, July 17, 2026, University Relations

Tiger Weekly Newsletters

No abstract provided.

Explainable Machine Learning For Biomedical Diagnostics: Optical Imaging And Eeg Signal Analysis, Fozia Rajbdad

LSU Doctoral Dissertations

The growing convenience of complex biomedical data begins new roads for better disease detection and functional identification via artificial intelligence (AI). Nevertheless, conventional analysis methods often rely on basic metrics that drop sensitive biotic differences, and various AI systems are difficult to infer, limiting their clinical reliability and practical use. There is a growing need for explainable, physiologically relevant computational models that can extract key biomarkers from diverse biomedical data sources. This dissertation addresses this problem by obtaining explainable machine learning and deep learning procedures for studying biomedical signals and optical imaging data.

This dissertation is divided into two parts; …

Nitrogen Management Strategies For Specialty Tea Production In Louisiana: Rate, Source Type, And Nutrient Dynamics, Autumn D. Hilderbrand

LSU Master's Theses

Tea (Camellia sinensis L.) is an emerging specialty crop in Louisiana and the southeastern United States; however, region-specific nitrogen (N) management recommendations remain limited. This research evaluated N fertilizer source, application rate, and nutrient leaching to identify management strategies that improve nitrogen use efficiency (NUE) and environmental sustainability during tea establishment.

Three complementary studies evaluated N source replacement, application rate, and fertilizer source effects on nutrient retention and movement. The first study evaluated the replacement of urea ammonium sulfate (UAS) with blood meal (BM) while maintaining a constant annual N application rate. Fertilizer replacement did not significantly affect leaf …

Improving Cancer Diagnosis And Patient Outcomes With Deep Learning Models, Mariana Arriz-Jorquiera

USF Tampa Graduate Theses and Dissertations

Cancer care depends on timely and reliable decisions, from detection and diagnosis to treatment planning and patient monitoring. These decisions are often made under uncertainty because medical images and healthcare data may be noisy, incomplete, or difficult to interpret. In breast cancer imaging, ultrasound is widely used because it is safe, accessible, and complementary to other imaging modalities. However, variations in image quality, acquisition conditions, and noise can obscure lesion boundaries and texture, affecting human interpretation and artificial intelligence reliability. This dissertation develops deep learning, image-analysis, and optimization methods to improve healthcare decisions under imperfect information. Its primary focus is …

The Association Between Ferritin Marker And Iron Deficiency Anemia In Peptic Ulcer Disease Patients: A Case-Control Approach, Sajjad Fadhil K. Abbas, Abeer Cheaid Yousif Al-Fatlawi, Ahmed Hashim Abbas Al-Janabi

Al-Ameed Journal for Medical Research and Health Sciences

Background: Peptic ulcer disease refers to deep erosions in the mucosal layer of the GIT and is highly associated with upper gut bleeding, which results in anaemia. Ferritin is a protein that stores iron in the body.

Aim: To estimate serum ferritin levels in relation to anaemia in peptic ulcer disease and assess its potential as a predictor of peptic ulcer bleeding.

Method: A case-control study in Kerbala, Iraq, measured ferritin by ELISA and anaemia by Hb levels on CBC, with ROC curves used to assess sensitivity and specificity.

Results: results show a significant difference in haemoglobin and ferritin levels …

The Implications Of Generative-Ai User Prompt Engineering Shaping The Absent Presence Of Latino Women Textual Rhetoric In Llms, Angely C. Suarez Dejesus

ELO (un)supervised 2026

This article examines how large language models (LLMs) generate text that affects underrepresented groups, particularly Latino women, due to limited cultural, contextual, and abstraction training rooted in biases. The research draws on Brock’s (2018) CTDA theory, White et al.’s (2023) prompt engineering framework, Klein’s (2015) computational spatiality, and Anzaldua’s (1987) concepts of cultural, emotional, and gendered borderlands to analyze the outputs. Using narrative prompt experiments, Chat GPT 3.5, 5, Claude AI, Gemini, and Microsoft Co-Pilot produced changes in their textual outputs as evidence of further algorithmic designs. Nevertheless, continual biases embedded in the algorithms’ linguistic representation and misrepresentation through the …

Cooperation, Collaboration, And Community In Horror And Suspense Games, Rachel Kerr, Monica Evans, Cameron Irby, Cheri Tang

ELO (un)supervised 2026

Cooperation has been a staple in video and analog games since their inception. From couch co-op to social deduction games, there are few games that cannot be enjoyed cooperatively in some way. Even games that are not inherently cooperative can be played collaboratively, from single-player games enjoyed by multiple people in the same room to PvP games where players opt for teamwork despite explicitly competitive mechanics. In horror and suspense games, cooperation tends to form strong communicative bonds between players. The four papers in this panel examine how communities form in and around horror and suspense games, and how those …

Complete Issue-Volume 35, Issue 3, Robert J. Bailey, Claude E. Fike, James T. Currie, Carl Butler, Joseph C. Kiger, Richard A. Mclemore, Robert E. Corlew, Bernarr Cresap, John Edmond Gonzales, James H. Dormon

Journal of Mississippi History

No abstract provided.

The Beginnings Of Congressional Reconstruction In Mississippi, James T. Currie

Journal of Mississippi History

No abstract provided.

The Gubernatorial Administration Of George Poindexter, 1820-1822, Robert J. Bailey

Journal of Mississippi History

No abstract provided.

Complete Issue-Volume 35, Issue 1, Robert Simpson, Clarice T. Campbell, Kit Mui L. Chan, Dawn Maddox, William G. Hartley, James H. Stone, Jerome C. Hafter, Willie D. Halsell, Tom W. Henderson, Laura D.S. Harrell, Daniel P. Jordan, John R. Skates Jr., Robert V. Haynes

Journal of Mississippi History

No abstract provided.

Exploring The Roots Of Tougaloo College, Clarice T. Campbell

Journal of Mississippi History

No abstract provided.

Complete Issue-Volume 35, Issue 2, Les Crocker, Joseph E. Fortenberry, Nancy T. Kondert, Elmo Howell, Matthew C. O'Brien, R. Halliburton Jr., John L. Thompson, William N. Thompson, Carl Butler, Patricia S. Currie, James T. Currie, David L. Porter, Jack D.L. Holmes, Robert E. Corlew, Harry P. Owens, John Ray Skates Jr.

Journal of Mississippi History

No abstract provided.

Marriages In Lowndes County, 1836-1845, Part I, Carl Butler

Journal of Mississippi History

No abstract provided.

Mississippi's Contribution To The Anti-Evolution Movement, R. Halliburton Jr.

Journal of Mississippi History

No abstract provided.

An Early Iron Foundry In Mississippi, Les Crocker

Journal of Mississippi History

No abstract provided.

Excerpts From "Estes And Rocky Mountain National Park: An Historical Reminiscence," Abner Sprague Collection, Stephan Hart Archives, History Of Colorado Collection, Abner Spague

Rocky Mountain National Park

Document is related to the way of life and the inhabitants of the Rocky Mountain National Park and Estes Park area. It discusses the way settlers would come in and establish cattle trade and homesteading within the park area and along the waterways. Fannie Fergison Seaton; Sallie Ferguson Reed; Homer E. James; Howard P. James; James McLaughlin; James Nugent; Windom Thomas; Willow Park; Moraine Park; A.Q. MacGregor, W. E. James; H. W. Ferguson; John Hupp, Abner Sprague; Hank Ferrar; George Bodde; Theodore Whyte; Alfred H. Hord; St. Mary's Lake; Mildred Fergison; Beaver Creek; James Daly; Henrry Hupp; Walter Jones; Elmer …

House Of Representatives, Rocky Mountain National Park Committee On The Public Lands Report, Rocky Mountain History & Legislation Dedications, File 101-01, Box 400, R. W. Dunlap, Hubert Work, William Jackson

Rocky Mountain National Park

A report was to establish the boundaries of the Rocky Mountain National Park. With this legislative report there are different sources included ranging from news clippings to expedition journal entries providing information of the area and the land features. N.J. Sinnott; R.W. Dunlap; Moraine Park; Arbuckle Reservoir; Hubert Work; Grand Lake; Big Thompson River; Little Thompson River; Colorado River; Shadow Mountain Lake; Gulf of California; Green Mountain Reservoir; Harold L. Ickes; Northern Colorado Water User's Association; Cha S. Hansen; Moses E. Smith; Thomas A. Nixon; Western Slope Protective Association; Silmon Smith; Clifford H. Stone; A. C. Sudan; Grand Lake; Don …

Rocky Mountain History & Legislation House Bills, File 120-01, Box 400, E. C. Finney, Hubert Work, Franklin K. Lane, Wm. Tyler Page

Rocky Mountain National Park

Document contain conversations and legislation of the land divided between Rocky Mountain National Park and the State National Parks. The legislation would eliminate some private land ownerships. Arno B. Cammerer; E.C. Finney; Glasier Basin; Arbuckle Reservoir Company; Hubert Work; N.J. Sinnett; Franklin K. Lane; Hennry L. Myers; Scott Ferris; Crow Creek; Aspen Brook; Arbuckle Number Two Reservoir; River and Harbor Appropriation Act 1917; WM. Tyler Page;

Ai To Ai Architecture: A Direct Latent-Space Tensor Routing Protocol & Immutable Neuromorphic Asic Architecture For Self-Regulating Milti-Agent Compute Networks, Christopher L. Eckes

Defensive Publications Series

Contemporary distributed Artificial Intelligence (AI) networks face critical limits in throughput, energy efficiency, and security due to their reliance on serialized -token interfaces (e.g., natural language, JSON, XML) for multi-agent cross-talk.

These traditional software-defined models introduce significant tokenization processing latency, suffer from compounding autoregressive gradient drift that causes runaway hallucination spirals over time, and present extensive vulnerability surfaces to adversarial prompt injections and gradient poisoning exploits.

This paper introduces a production-ready system architecture for a non-linguistic, machine-to-machine data routing engine and embedded cybersecurity shield, hardwired directly onto custom Neuromorphic Application-Specific Integrated Circuits (ASICs).

The Bounded Cognitive Accelerator (BCA) protocol bypasses …

A System And Method For Contextual Anomaly Detection Using Ai Agents For Large-Scale Data Streams, Ravi Shanker Kumar Sinha, Shashwat Mishra

Defensive Publications Series

The present disclosure provides systems and methods for contextual anomaly detection. The system includes a data ingestion module configured to receive data streams from a plurality of data sources within an enterprise environment. The system includes a feature extraction module configured to process the received data streams and determine anomaly indicators based on statistical analysis of the received data streams. The system includes a contextual reasoning module configured to determine contextual factors associated with the anomaly indicators and process the anomaly indicators and the contextual factors using a Large Language Model to classify the anomaly indicators as genuine anomalous events …

Anticipatory Action Fulfillment In Conversational Agents Via Speculative Native-Audio Llms And Streaming Latent Diarization, Tamar Yakar, Ilia Labzovsky

Defensive Publications Series

Current voice-activated conversational agents rely on sequential, text-based processing pipelines that introduce latency and fail during mid-utterance interruptions. A computational architecture is disclosed that replaces traditional speech recognition pipelines with a streaming native-audio large language model. Acoustic tokens are processed directly to maintain a real-time computational graph of an acoustic trajectory. Streaming latent diarization is employed natively within the model to mathematically segregate intersecting vocal trajectories. Parallel isolated execution branches are dynamically created when biometric shifts are detected, allowing background noise to be masked. Structured tool-calls are generated speculatively by an execution head before end-of-speech markers are reached. Conversational intent …