University of West Florida

Digital literacy encompasses the skills needed to effectively navigate and use the digital tools and resources that are essential in today's educational landscape. Students with higher levels of digital literacy often demonstrate self-directed learning skills, enabling them to manage their study schedules and submit assignments in a timely and effective manner. Integrating digital literacy with preparation for self-directed learning is critical to fostering successful online learning experiences. Research into the impact of students' digital literacy and readiness for online learning on their self-directed learning is crucial to understanding the competencies and skills required for online education. Such competencies in learners may have unique effects, especially in specific online learning processes such as emergency remote teaching. Therefore, this study aimed to explore the potential impact of students' digital literacy on their self-directed online learning, with a particular focus on their online learning readiness. In line with the purpose of the study, a cross-sectional survey design was employed, using a structural equation modeling approach. The results showed that digital literacy has a direct and positive effect on online learning readiness. In addition, online learning readiness has a direct and positive influence on self-directed online learning. The results also highlighted that digital literacy indirectly and positively influences individuals' levels of self-directed online learning through their online learning readiness.

This paper presents a comprehensive comparative analysis of Singapore and France’s artificial intelligence (AI) governance models, examining how these distinct approaches interact with and are shaped by international organizations and global governance frameworks. Drawing on Zürn’s theory of global governance, focusing on authority, legitimacy, and contestation, and complementary theoretical perspectives, including policy diffusion and multi-level governance, this study explores the dichotomy between Singapore’s innovation-driven approach and France’s ethical-centric AI governance while analyzing the formative influence of European Union regulations and broader international standards. Through systematic qualitative content analysis of policy documents, regulatory frameworks, and implementation reports, this research uncovers the underlying political, economic, and cultural drivers that shape how these two countries navigate the complex terrain of AI governance amid global interdependencies. The findings suggest that effective global AI governance requires a polycentric approach that balances universal ethical principles with localized implementation strategies, offering important insights for policymakers and scholars working toward responsible global AI development.

The fashion supply chain is undergoing a transformation driven by AI, with significant implications for social sustainability and ethics. This study examines how AI‐powered innovations optimize supply chain operations, enhance transparency, and support ethical labor practices. Through a systematic literature review, we identify key challenges and opportunities, emphasizing the role of AI in fostering circular economy models, responsible sourcing, and stakeholder collaboration. Our findings propose a research agenda centered on policy frameworks, technological advancements, and ethical AI governance. This study contributes to the discourse on socially sustainable and ethical AI adoption in fashion supply chains, offering insights for researchers and industry leaders.

We analyze and test a simple-to-implement two-step iteration for the incompressible Navier-Stokes equations that consists of first applying the Picard iteration and then applying the Newton iteration to the Picard output. We prove that this composition of Picard and Newton converges quadratically, and our analysis (which covers both the unique solution and non-unique solution cases) also suggests that this solver has a larger convergence basin than usual Newton because of the improved stability properties of Picard-Newton over Newton. Numerical tests show that Picard-Newton converges more reliably for higher Reynolds numbers and worse initial conditions than Picard and Newton iterations. We also consider enhancing the Picard step with Anderson acceleration (AA), and find that the AAPicard-Newton iteration has even better convergence properties on several benchmark test problems.

Preventive patrol has been a cornerstone of modern policing since 1829, yet efficiently allocating patrol resources remains challenging. This study introduces a new approach, the Need for Patrol Presence Score (NPPS), to guide the design of patrol beat borders and coverage areas. Unlike traditional models, NPPS incorporates evidence-based policing by considering call types, urgency, and high-risk locations. Using Computer-Assisted Dispatch data, this method aims to create balanced patrol beats that can improve response times and workload distribution across the patrol beats. Implementation of NPPS can enhance police response, workload distribution, and community safety, providing a valuable tool for police departments seeking efficient patrol beat structures.

Background Resistance training with real-time movement velocity feedback enhances power training. Linear position transducers (LPTs) provide visual biofeedback and are commonly used to measure movement velocities in performance and research settings. However, the agreement between some commonly used LPTs, such as the Humac360, is unknown. Objective The purpose of this study was to determine the agreement of the Humac360 LPT between the Tendo Power Analyzer and the GymAware PowerTool. Methods Thirty participants (23.0 ± 5.6 years) completed 7 sets of 3 repetitions of the belt squat movement with loads ranging from 0–120% of their body weight. Mean velocity (MV) and peak velocity (PV) were collected and recorded simultaneously on all three LPTs. Agreement between devices was assessed using the ratio of half the limits of agreement and the mean of pairwise measurements, and the correlation between devices was determined using Pearson's r. Results Moderate agreement was seen at PV between the Humac360 and Tendo (0.5 LOA/MPM = 0.12–0.21), and between the Humac360 and GymAware (0.5 LOA/MPM = 0.16–0.27). Low agreement was observed when measuring MV between the Humac360 and Tendo (0.5 LOA/MPM = 0.23–0.31), and between the Humac360 and GymAware (0.5 LOA/MPM = 0.18–0.27). High to very high correlations were observed between the Humac360 and both the Tendo (r = 0.87–0.99) and GymAware (r = 0.87–0.96) at MV and PV. Conclusion The moderate agreement and high to very high positive correlations demonstrated by the Humac360 was comparable to the Tendo and GymAware devices, specifically at peak velocities, supporting its use by clinicians, therapists, and trainers, for the particular use of measuring peak velocity.

When personality psychologists examine political behaviour, including voting, they usually focus on a narrow range of variables, thereby undermining the breadth of our knowledge. We asked 280 participants who they voted for (or would have) in the 2020 US presidential election and inquired as to their ‘dark’ personality (i.e., psychopathy, sadism, narcissism, and Machiavellianism) and ‘light’ (i.e., Kantianism, humanism, and faith in humanity) personality traits, political attitudes (i.e., social dominance orientation, right‐wing authoritarianism, and left‐wing authoritarianism), and how many times people chose each of the six moral foundations (i.e., care, fairness, loyalty, purity, liberty, and hierarchy). We found that personality traits (as distal systems) were negligibly important in presidential choice, moral choices (as parallel‐yet‐related choices) had some utility especially in relation to voting for a third‐party candidate, and political attitudes (as proximal predictors) had the broadest and strongest associations. In addition, we found that third‐party voters showed stronger concerns for purity than Biden supporters, and greater concerns for fairness than Trump supporters. Our results focus on how dispositional measures can add to standard sociodemographic predictors used by pollsters, politicians, and pundits.

This study investigates ferroptosis in the context of peripheral artery disease (PAD), a vascular disease characterized by atherosclerosis of the lower extremities. Muscle atrophy and increased oxidative stress are hallmarks of PAD and correlate with worse clinical outcomes. Given ferroptosis’ association with oxidative stress, we explored its role in PAD myopathy by examining gene and protein markers related to metabolic pathways implicated in ferroptosis using both human PAD patients and cultured myotubes. Intermittent claudication (IC) PAD patients, critical limb ischemia (CLI) PAD patients, and non-PAD controls were recruited for this study. Calf muscle biopsies were analyzed for gene expression using qPCR, and protein levels were determined by Western blotting. Cultured myotubes treated with the ferroptosis inducer erastin provided an in vitro comparison. Results demonstrated upregulation of ferroptosis markers such as lipid peroxidation and PTGS2 gene expression in the muscle of CLI PAD patients compared to controls. Increased expression of ferroptosis-related genes HMOX1, ACSL4, ELAVL1, and Beclin-1 was also observed. Protein analysis showed trends consistent with gene expression in some ferroptosis markers. The increase in ferroptosis markers in CLI PAD patients, particularly in iron metabolism and autophagy pathways, suggests ferroptosis contributes to PAD myopathy.

This paper describes the creation of a new dataset, UWF-ZeekData24, aligned with the Enterprise MITRE ATT&CK Framework, that addresses critical shortcomings in existing network security datasets. Controlling the construction of attacks and meticulously labeling the data provides a more accurate and dynamic environment for testing of IDS/IPS systems and their machine learning algorithms. The outcomes of this research will assist in the development of cybersecurity solutions as well as increase the robustness and adaptability towards modern day cybersecurity threats. This new carefully engineered dataset will enhance cyber defense mechanisms that are responsible for safeguarding critical infrastructures and digital assets. Finally, this paper discusses the differences between crowd-sourced data and data collected in a more controlled environment. Dataset: datasets.uwf.edu Dataset License: CC-BY

Objectives This study aims to explore how health informaticists collaborate with multiple stakeholder groups, each possessing varying levels of comfort and competence with health technology and data. stakeholder engagement is highlighted as a crucial skill for health informaticists, necessitated by the differing competency levels among stakeholders. Methods The Competency Matrix Model was identified as a strategic tool to address the challenges faced by health informaticists in navigating the complexities of health information technology utilization. This framework was used to evaluate and enhance the technological competencies of various stakeholders within the health care domain. Results The application of the Competency Matrix Model provides health informaticists with a structured approach to improving stakeholders' technological competencies. This approach facilitates a better understanding and utilization of health information technologies, contributing to improved health care outcomes and operational efficiency. Conclusion This work demonstrates the applicability of the Competency Matrix Model in the health care domain by health informaticists to enhance the technological competencies of various stakeholders. Through strategic stakeholder engagement and competency development, health informaticists can effectively address the challenges of technology utilization in health care, ensuring a positive impact on health care delivery.

Despite concerns about methylmercury (MeHg) contamination in rice, the sources and transformation mechanisms of MeHg within paddy field water, the primary source of MeHg in rice, remain unclear. Determination of the isotopic composition of MeHg in paddy water is crucial to clarify these processes. However, there is a lack of sampling and analytical methods for quantifying MeHg isotopes in water samples. In this study, we use diffusive gradients in thin films (DGT) in-situ to collect MeHg from paddy water to determine the concentration of MeHg and the associated isotopic composition. This technique enables high collection efficiency of aqueous MeHg with limited Hg isotope mass-dependent fractionation (~ −0.2‰ δ202Hg) and mass-independent fractionation (< 0.1‰ Δ199Hg). Field applications using the developed DGT method suggest that in-situ methylation of soluble Hg(II) drives the generation of MeHg in paddy water. MeHg in overlying water exhibits a Δ199Hg/Δ201Hg ratio of 1.07 ± 0.09, indicating significant photoreduction of aqueous Hg(II) before methylation. The absence of photo-demethylation Δ199Hg/Δ201Hg ratio (~1.36) suggests limited MeHg demethylation in the overlying water. This study provides insights into the sources and transformation of MeHg in rice paddies and helps develop mitigation strategies to reduce MeHg exposure through rice consumption.

Blockchain technology has emerged as a transformative innovation, providing a transparent, immutable, and decentralized platform that underpins critical applications across industries such as cryptocurrencies, supply chain management, healthcare, and finance. Despite their promise of enhanced security and trust, the increasing sophistication of cyberattacks has exposed vulnerabilities within blockchain ecosystems, posing severe threats to their integrity, reliability, and adoption. This study presents a comprehensive and systematic review of blockchain vulnerabilities by categorizing and analyzing potential threats, including network-level attacks, consensus-based exploits, smart contract vulnerabilities, and user-centric risks. Furthermore, the research evaluates existing countermeasures and mitigation strategies by examining their effectiveness, scalability, and adaptability to diverse blockchain architectures and use cases. The study highlights the critical need for context-aware security solutions that address the unique requirements of various blockchain applications and proposes a framework for advancing proactive and resilient security designs. By bridging gaps in the existing literature, this research offers valuable insights for academics, industry practitioners, and policymakers, contributing to the ongoing development of robust and secure decentralized ecosystems.

The academic field of exercise science has experienced exponential growth in the past four decades, including in the number of degrees awarded, available job opportunities for graduates, amount of research conducted, and external funding for research. Typically, exercise science students are young, healthy adults, with an inherent interest in exercise science, making them “ideal” research participants for faculty-led research studies. However, these characteristics also make exercise science students particularly vulnerable to coercion and undue influence by faculty researchers aiming to use these students as research participants. Here, we will discuss ethical concerns related to recruiting exercise science students as research participants in faculty-led research related to power differentials, recruitment of female participants, and academic credit. We will provide recommendations to protect potential student participants from coercion, unjustifiable pressure, and undue influence that could undermine their voluntary informed consent.

Domestic cats have lived alongside human communities for thousands of years, hunting rats, mice, and other pests and serving as pets and a source of pelts and meat. Cats have received limited archaeological attention because their independence limits direct insight into human societies. An adult and juvenile cat recovered from the Emanuel Point wreck 2 (EP2) reflect what are, most likely, the earliest cats in what is now the United States. Zooarchaeological analyses of these and other archaeological cats in the Americas demonstrate that cats ranged substantially in size: some were comparable to modern house cats, and others were much smaller. Isotopic analyses of the adult cat from EP2 provides insight into early shipboard cat behavior and their diet, which appears to have focused on consumption of fish and possibly domestic meat. Cats accompanied sailors on ships where they were relied on to hunt rats and mice that were infesting ships’ holds. Interestingly, based on these isotopic results, the adult cat from EP2 does not seem to have relied heavily on rats as a source of food. These pests were unintentionally introduced to the New World, and cats would have followed, hunting both native and invasive pests.