Digital Commons Network^™

Infestation By Phorid Flies Disrupts Behavior And Immune Function In Honey Bees Monitored By Radio-Frequency Identification, Gloria Ruiz-Guzmán, Oliverio Delgado-Carrillo, Francisco J. Balvino-Olvera, María De Jesús Aguilar-Aguilar, Violeta Patiño-Conde, Paulo De Souza, Ulises Olivares-Pinto, Mauricio Quesada

Research outputs 2022 to 2026

Honey bees (Apis mellifera Linnaeus) are important pollinators in natural and agricultural ecosystems and play a key role in global food production. However, colonies are increasingly affected by multiple stressors, including emerging parasites, which can compromise their health and performance. Among these, phorid flies (Diptera: Phoridae) have been observed in association with weak or collapsing honey bee colonies in various regions in Mexico, yet their effects on honey bee behavior and immune function under field conditions remain poorly understood. In this study, we investigated the impact of a phorid fly infestation on the behavior, survival, and immune defense of A. …

Analysis Of U.S. Army Body Composition Policies: Implementation Effectiveness And Recommendations For Policy Enhancement At Brooke Army Medical Center, Michael L. Rizzo

Doctor of Nursing Practice (DNP) Manuscripts

US Army body composition policies (AR 600-9 and recent directives) are essential for military readiness, injury prevention, and force health protection, yet implementation gaps persist, particularly with the 2026 Department of Defense (DoD)-mandated waist-to-height ratio (WHtR < 0.55) transition. This DNP project evaluated policy implementation effectiveness at Brooke Army Medical Center using the W.K. Kellogg Foundation Logic Model and CFIR 2.0 framework. Analysis of 2022–2025 de-identified administrative data and 16 stakeholder questionnaires identified ≥10 implementation gaps, including low awareness of new standards and workload impacts. The project developed 8 evidence-based recommendations and an implementation roadmap to improve compliance, optimize resources, reduce administrative burden, and strengthen military readiness.

Revisiting Ulam Stability For Boundary Value Problems, Martin Bohner, Snezhana Hristova, Agnieszka B. Malinowska, Ewa Girejko

Mathematics and Statistics Faculty Research & Creative Works

The main goal of this paper is to apply Ulam stability theory to boundary value problems for dynamic equations, while addressing several common misconceptions found in the existing literature. We identify the key issues that arise when applying Ulam stability to such problems and propose three distinct approaches to overcome them. To enhance clarity and accessibility, we begin with nonlinear ordinary differential equations and subsequently extend the analysis to nonlinear dynamic equations on time scales. Since a time scale is defined as any nonempty closed subset of the real numbers, our results are applicable to dynamic equations on continuous, discrete, …

Implementing Updated Npo Guidelines For Inpatient Procedures, Yasamin Ghanivand

Doctor of Nursing Practice (DNP) Projects

Background: Nil per os (NPO) guidelines are utilized for patient safety during procedures to reduce the risk of pulmonary aspiration. The American Society of Anesthesiologists (ASA) recommends clear liquids up to 2 hours before non-emergent procedures, although many facilities still implement the outdated practice of ordering NPO after midnight. This practice can lead to prolonged fasting, which may cause increased hunger, thirst, hypotension, nausea, and dizziness, ultimately resulting in patient dissatisfaction and discomfort.

Purpose: To review and assess current ASA NPO guidelines that describe best practice to enhance the patient experience without increasing perioperative risk of pulmonary aspiration.

Methods: A …

Wildfire And Fuel Treatments In Utah: A Practical Guide And Outcomes From An Oak-Maple Ecosystem, Annie E. Prescott

All Graduate Theses and Dissertations, Fall 2023 to Present

Wildfire is a natural part of Utah’s landscapes, but as wildfires become more extreme and communities continue to expand into wildland areas, it is increasingly important to understand how wildfires behave and how their negative effects can be mitigated. One way to reduce wildfire risks and protect life, property, and ecosystem services is through fuel treatments — actions that reduce the amount and arrangement of flammable vegetation through mechanical removal, wildland fire, or other methods.

Information on wildfire behavior and fuel treatments is abundant but often scattered, ecosystem-specific and difficult to access. In addition, most research in the Western U.S. …

The Effects Of Eps Level And Presentation Format Of Analysts’ Forecast Deviation On Non-Professional Investors’ Investment Judgments, Clarence Goh, Prasart Jongjaroenkamol, Poh-Sun Seow

Research Collection School Of Accountancy

We experimentally investigate how the presentation format of the extent to which a firm's earnings per share (EPS) diverges from analysts' EPS forecasts (i.e. deviation information) and a firm's EPS level affect the investment judgments of non-professional investors (referred to hereafter as “investors”). Our results suggest that investors' investment judgments are more positive when firms with low (high) EPS levels disclose deviation information in percentage (absolute) terms. Furthermore, when the percentage of forecast deviation is held constant, investment judgments are more positive when EPS levels are high versus low if the deviation information is expressed in absolute terms. By contrast, …

Soil-Science Expertise In An Ai-Exposed World: Competencies, Curricula, And Careers For Soil Security, Gian Franco Capra, Thiago Assis Rodrigues Nogueira, Arun Dilipkumar Jani

Biology, Agriculture and Chemistry Faculty Publications and Presentations

Generative artificial intelligence (AI) is reshaping the world of knowledge-based work, with highly qualified professions appearing more exposed to substitution than routine manual ones. Soil science occupies a hybrid position, being a field that requires extensive knowledge and at the same time a strong dependency on field and laboratory activities, time-consuming and intrinsically “embodied.” This review examines what AI entails for soil science, asking which competencies are more or less exposed, how curricula should respond, and what actions institutions should undertake in the current AI-dominant academic environment. The analysis rests on two axes, namely the AI exposure of a task …

Evaluating The Impact Of Research Equipment Availability On Scientific Rigor, Reproducibility, And Innovation Across Stem Disciplines, Lyndi G. Hraban

Honors Program: Senior Projects (Public)

Research infrastructure plays a central role in shaping the quality and innovative capacity of scientific research. This study evaluates how the availability of research equipment influences scientific rigor, reproducibility, and innovation across STEM disciplines. Drawing on literature from science-to-science research, policy studies, and discipline-specific analyses, this project synthesizes existing scholarship to explore the relationship between access to infrastructure and key research outcomes. Findings across the literature indicate that access to advanced and well-maintained equipment can strengthen scientific rigor by enabling more precise measurements, improved experimental control, and the implementation of standardized research protocols. Shared and centralized facilities are also associated …

In Adults Older Than 18 Years With Obesity Living In Massachusetts, Can Engaging In A Weight Loss Program Help Them Lose Weight After Insurance Stops Covering Their Weight Loss Medications?, Angel Nagawa

Capstones

Executive summary

The Problem

Obesity rates continue to rise sharply across the United States. Weight loss medications have high compliance but face major insurance restrictions. Strict clinical criteria leave many patients without accessible treatment options.

The Proposed Solution

Launch structured, lifestyle-focused clinical weight loss programs. Provide an effective, accessible alternative to restricted pharmaceutical therapies.

Supporting Evidence

Evaluated data from three distinct randomized controlled trials. Findings confirm successful long-term weight management for program participants. Results prove effective control over serious obesity-related comorbidities.

Policy recommendation

Implement structured lifestyle programs as a primary, frontline intervention modality. Improve broad-scale patient health outcomes across clinical …

Castor Canadensis Winter 2026, Jedediah Smith Society

Castor Canadensis - Jedediah Smith Society

Newsletter of the Jedediah Smith Society

Optimizing Inventory Management, William Hawkins

Agricultural Economics and Agribusiness Undergraduate Honors Theses

Inventory management is extremely important for businesses to maximize their profitability. Many factors go into the decision-making process for how much inventory to hold and when to restock this inventory. Through the process of an internship, I determined that some of the most important factors were the amount of a part that needed to be ordered at a time and what order quantities would allow for high levels of customer satisfaction. In this research, I compared these factors between the different models I studied, and the data I received from Riggs CAT to determine whether or not maximum efficiency and …

A Global High-Resolution Comprehensive Heat Indices Dataset From 1950 To 2024, Abdul Malik, Sateesh Masabathini, Mohsin Ahmed Shaikh, Qinqin Kong, Muhammad Usman, Dasari Hari Prasad, Ibrahim Hoteit

All Works

Heatwaves are becoming more intense and frequent as global temperatures rise, affecting vulnerable populations, particularly in low-income communities. Addressing the impacts of heatwaves requires high-resolution data to assess their influence on labour productivity, public health, and climate risk. We introduce the Comprehensive Heat Indices (CHI) dataset, a high-resolution (0.1° × 0.1°) hourly dataset from 1950 to 2024, derived from the ERA5 and ERA5-Land reanalyses. The CHI dataset encompasses thirteen heat stress indices, including wet-bulb temperature, universal thermal climate index, mean radiant temperature, wind chill, and lethal heat stress index (Ls). Thresholds for Ls are empirically linked to mortality, enabling the …

Quantifying Customer Sentiment For Automobile Brand Perception Analysis Using Machine Learning On Twitter, Sujith Samuel Mathew, Kadhim Hayawi, Neethu Venugopal, May El Barachi

All Works

Social networking sites provide a platform for individuals to express their opinions publicly. Brand managers actively use these platforms to gain insights into brand perceptions, as users often share their views on products and services. In this study, we use sentiment analysis to assess customer sentiment towards five leading automobile brands, analyzing text content shared on Twitter(or X). The research models the ’Brand Polarity Score’, which indicates whether customers perceive the brand positively or negatively. This score is further weighted based on the tweet’s influence, characterized by the engagement metrics of the tweet and the author’s follower count. We also …

Dblp: Noise Bridge Consistency Distillation For Efficient And Reliable Adversarial Purification, Chihan Huang, Belal Alsinglawi, Islam Al-Qudah

All Works

Recent advances in deep neural networks (DNNs) have led to remarkable success across a wide range of tasks. However, their susceptibility to adversarial perturbations remains a critical vulnerability. Existing diffusion-based adversarial purification methods often require intensive iterative denoising, severely limiting their practical deployment. In this paper, we propose Diffusion Bridge Distillation for Purification (DBLP), a novel and efficient diffusion-based framework for adversarial purification. Central to our approach is a new objective, noise bridge distillation, which constructs a principled alignment between the adversarial noise distribution and the clean data distribution within a latent consistency model (LCM). To further enhance semantic fidelity, …

X-Threat Framework For Adaptive And Explainable Deep Learning-Based Minority-Class And Zero-Day Cyber Threat Detection, Samina Naz Qaisarani, Sahar K. Badri, Asad Khattak, Daniyal M. Alghazzawi, Mohammed Yahya Alghamdi, Mona Alkhozae, Abeer Almakky, Rania M. Alhazmi, Muhammad Zubair Asghar

All Works

The dynamic nature of cyber threats—particularly minority-class and zero-day attacks—poses significant challenges to existing intrusion detection systems (IDS), which often lack adaptability, interpretability, and robustness. This paper presents X-THREAT, an adaptive and explainable deep learning framework designed to improve detection of rare and previously unseen cyber threats. Unlike prior approaches that treat detection, augmentation, and explainability separately, X-THREAT integrates these components within a unified pipeline. A hybrid VAE–GAN module enhances minority-class representation during training, while a CNN–BiLSTM–attention model performs threat detection, and a context-aware SHAP mechanism provides interpretable insights into model decisions. Experimental results on three benchmark datasets—CICIDS2017, UNSW-NB15, and …

Evolving Ai Integration In Complex Medical Decision-Making And Multidisciplinary Transplant Care: A Systematic Review Of Human-Ai Collaboration, Rachel L. Dzieran, Cihan H. Dagli, Robert J. Marley

Engineering Management and Systems Engineering Faculty Research & Creative Works

Purpose of Review: Artificial intelligence (AI) in healthcare has evolved dramatically from early expert systems, which were initially considered replacements for clinical judgment, to today's collaborative frameworks that aim to augment physician decision-making. This evolution is particularly crucial in domains such as transplant surgery, where decisions carry irreversible consequences and require the integration of complex, often ambiguous data. Drawing on peer-reviewed literature from 2019 to 2025, we conducted a systematic review that analyzed key elements distinguishing successful human-AI partnerships from those that fail. Recent Findings: The ideal balance incorporates human expertise into AI systems through weighted integration approaches, rather than …

The Airport And The City: Toward A Philosophy Of The Aerotropolis, Shane Ray Epting

Arts, Languages and Philosophy Faculty Research & Creative Works

As a city centered on its airport's vast influence, the aerotropolis's existence has an inherent tension: It is a stable city for people to stay put and dwell, with the notion of leaving at the foreground of urban life. As a conception, the aerotropolis requires investigation to reveal its significance for humankind and its place in an ontology of cities. When the aerotropolis is situated in such a manner, we see how it differs significantly from other kinds of cities throughout history that depend on travel, such as river and port cities. After unpacking these points, a view emerges illustrating …

Will Your Ai Turn Backers Away? Evidence From Kickstarter's Ai-Use Disclosure Policy, Sonika Singhal, Yeongin Kim, Seonjun Kang, Victoria Yoon

Business and Information Technology Faculty Research & Creative Works

Generative artificial intelligence (GenAI) is reshaping how creative work is produced, raising new questions about authenticity, originality, and human effort in entrepreneurial settings. We examine how platform-mandated AI-use disclosure is associated with crowdfunding outcomes, using Kickstarter's 2023 disclosure policy and a dataset of over 63,000 campaigns launched between 2022 and 2024. Drawing on signaling theory, we argue that an AI-use label functions as a platform-governed cue that backers may interpret as signaling reduced human effort, potentially shaping how they evaluate creators and campaigns. Empirically, we find that AI-use disclosure is associated with a significantly lower likelihood of campaign success, with …

Power At Sea Develop Phase, Jake Lauer, Isabella Heinemann, Bailey Gargasz, Zachery Boyer

Mechanical Engineering

This project develops a renewable, wave-powered charging system designed to extend the mission duration of Autonomous Underwater Vehicles by eliminating the need for frequent manual battery replacement. Building upon a prior oscillating water column prototype from the CONCEPT phase, the team redesigned and tested an improved system capable of converting wave-induced air motion into electrical power using a Wells turbine. Key enhancements include doubling the column diameter to increase displaced air volume, integrating a flared inlet and bi-directional nozzle to improve airflow, and selecting corrosion-resistant materials suitable for long-term deployment in marine environments. Multiple prototypes were constructed and evaluated through …

Reasserting Congressional Authority In National Security In The Post-Chadha Era, Jacob Shaffer

Hofstra Law Review

No abstract provided.

Providing Effective Student Feedback: Effects Of Sociotropy, Student-Teacher Connectedness, And Expressed Disappointment And Praise On Students' Self-Esteem And Motivation, Emily Davied

All Graduate Theses and Dissertations, Fall 2023 to Present

This study examined how different types of teacher feedback (i.e., expressed pride, expressed disappointment, and near-neutral feedback) impact students’ motivation to learn and self-esteem. It also explored whether such effects vary depending on students' personality and how connected they feel to their teacher. Undergraduate students (N = 221) imagined receiving feedback from a teacher and completed surveys assessing their motivation, self-esteem, sociotropy, and connectedness with the teacher. The results showed that feedback expressing disappointment lowered students' self esteem compared to expressing pride and lowered students' motivation compared to near neutral feedback. Although sociotropy (i.e., dependence on others' approval) and teacher …

Reduced Mediators Released By Cyanobacteria During Exoelectrogenesis Detected Using Differential Pulse Voltammetry, Laura T. Wey, Monica Brachi, Yagut Allahverdiyeva, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Cyanobacteria generate electrical current through exoelectrogenesis (extracellular electron transfer) downstream of photosynthesis, yet the identity of the endogenous redox mediator(s) responsible remains unresolved. Here, we apply differential pulse voltammetry (DPV) to detect and characterise redox-active species released by Synechocystis sp. PCC 6803 under illumination. To enable sensitive detection, we developed an electrolyte intermediate between BG11 (Blue-Green-11) growth medium and MOPS (3-(N-morpholino)propanesulfonic acid) buffer that minimises background electrochemical interference while maintaining short-term cellular functionality. DPV revealed multiple light-enhanced oxidation peaks (0.1–0.65 V vs. saturated calomel electrode (SCE)) that were not resolvable using cyclic voltammetry, providing evidence that cyanobacteria release reduced compounds …

Generative Ai Adoption And Solvers' Popularity On Supply-Driven Crowdsourcing Platforms: The Dual Role Of Price Signals, Zimeng Zhu, Carol Hsu, Fiona Fui-Hoon Nah, Na Liu

Research Collection School Of Computing and Information Systems

Purpose – We investigate the effect of solvers’ adoption of Generative AI (GenAI) on their popularity in a supply-driven crowdsourcing platform. We also examine the impact of price signals as well as their heterogeneous impact based on the solvers’ membership duration on the platform. Design/methodology/approach – Our analysis focuses on solvers who adopt GenAI for design-related gigs on the supply-driven crowdsourcing platform. By combining propensity score matching (PSM) with multi-period difference-in-differences (DID), we examine how GenAI adoption impacts solvers’ popularity and how price signals affect this main effect. Findings – Our findings reveal that solvers who adopt GenAI tend to …

Artificial Intelligence (Ai) For Social Innovation In Health Education: Promoting Health Literacy Through Personalized Ai-Driven Learning Tools – A Systematic Review, Dina Mansour Tbaishat, Maha Waleed Elfadel

All Works

Background: Artificial Intelligence (AI) is transforming health education by enabling personalized, adaptive, and scalable approaches that may enhance aspects of health literacy. Despite rapid adoption, comprehensive synthesis of AI tools’ impact on health literacy as social innovation is limited. Understanding these effects guides educators, developers, and policymakers in designing potentially effective, inclusive, and ethical AI interventions. This review examines generative AI models, chatbots, and adaptive learning systems in supporting health literacy globally. Methods: A systematic review was conducted following PRISMA guidelines. Literature was identified primarily through PubMed/Medline, Scopus, and ScienceDirect. Connectedpapers.com was used exclusively as a citation chasing tool, performing …

Radio Frequency Tagging–Enabled Patient Monitoring: Integrating Mobility Tracking With Early Warning Systems For Enhanced Safety, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Abhishek Dwivedi

All Works

Ensuring patient safety in healthcare environments requires continuous monitoring systems capable of identifying early warning signs of clinical risk. Traditional surveillance methods often fail to capture meaningful patterns in patient movement, limiting their ability to prevent incidents such as falls, prolonged immobility, or unnoticed health deterioration. Radio Frequency Tagging technology has been increasingly adopted for real-time patient tracking; however, existing systems are generally limited to location detection and lack predictive insights into patient behaviour. To overcome these limitations, this study presents a Radio Frequency Tagging-based patient monitoring framework that integrates mobility tracking with an early warning mechanism to enable proactive …

The Association Between Cyber Behaviors And Hedonic And Eudaimonic Well-Being: The Moderating Role Of Personality Traits, Areej Elsayary, Juan Calmaestra, Mercedes Gómez-López

All Works

The increasing integration of digital technologies into everyday life has intensified engagement in various cyber behaviors, raising important questions about their relationship with individuals' well-being. This study examined the associations between online moral disengagement, problematic internet use (compulsive internet use), benign and toxic disinhibition, cyberaggression, and cybervictimization with both hedonic and eudaimonic well-being among emerging adults in the United Arab Emirates. Furthermore, it explores the moderating role of personality traits in these associations. Data were collected from 671 emerging adults (46.8% women) aged 18–29 years (M = 22.56; SD = 3.04). Results showed that cybervictimization and cyberaggression exhibited the strongest …

Understanding Chatbot-Assisted Collaborative Learning Among Female Undergraduate Students, Mohammad Amin Kuhail, Ahmed Shuhaiber, Sinan Salman, Nazik Alturki

All Works

Computer programming can be daunting for beginners due to complex concepts and syntax. Traditional teaching methods, while engaging through gamification and active learning, often lack personalized approaches. Recent advancements in artificial intelligence (AI), particularly large language models (LLMs), present new possibilities for personalized and interactive learning environments. This study introduces a chatbot-assisted collaborative learning environment (CCLE) that leverages an LLM (GPT-4) to enhance collaborative programming education. The CCLE enables real-time guidance and collaboration through natural language interactions, allowing students to work together on programming tasks, edit code collaboratively, and engage with both peers and the educational chatbot. We conducted an …

Engineering Sulfur Concrete Mixes: A Data-Driven Approach To Aggregate Packing And Binder Efficiency, Vasilia Al Khaldi, Abdel Hamid I. Mourad, Maisa El Gamal

All Works

Processing window (mass loss < 3%). A first-order, order-of-magnitude carbon-footprint estimate—presented with explicit caveats rather than as a full life-cycle assessment—indicates that replacing Portland cement with by-product sulfur is the dominant contributor to a substantial reduction in embodied CO₂ per cubic metre relative to equivalent-strength Portland cement concrete. The valorization of steelmaking by-products aligns with circular economy principles, enabling high-performance, recyclable, and low-carbon construction materials without chemical binder modification.

An Advanced Healthcare System With An Automated Vit Model For Dermoscopic Skin Cancer Identification, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

All Works

Early and reliable diagnosis of skin cancer from dermoscopic images remains challenging due to class imbalance, subtle inter-class variations, lesion boundary ambiguity, and illumination inconsistency, which can degrade the robustness of conventional convolutional neural networks (CNNs). To address these limitations, this study proposes an automated smart healthcare framework for dermoscopic skin cancer diagnosis using an Enhanced Vision Transformer (E-ViT) that improves global-context modeling through self-attention while strengthening fine-grained lesion representation learning. Unlike standard ViT configurations, the proposed architecture integrates multi-scale patch embedding and attention refinement to better capture border irregularities and color–texture heterogeneity that are critical for melanoma discrimination. Furthermore, …

Fair And Explainable Educational Recommendations With A Hybrid Graph-Gru Framework, Edmund Evangelista, Syed M.Salman Bukhari

All Works

Artificial Intelligence (AI) recommender systems are increasingly used in education to personalize learning and help students navigate large collections of digital learning resources. However, many existing approaches emphasize predictive accuracy over fairness, robustness, diversity, and transparency. This creates an important educational challenge. The students with limited participation histories may receive less reliable support, while highly popular resources may dominate recommendation lists and limit access to other useful learning materials. To address this challenge, this study aims to develop and evaluate a responsible educational recommender framework that supports personalized learning resource navigation while making recommendation behavior more fair, stable, diverse, and …