Search Results (33,565)

Background/Objectives: Systemic lupus erythematosus (SLE) is an autoimmune disease affecting multiple organ systems, characterized by remissions and relapses. Musculoskeletal involvement occurs in up to 95% of patients and may present as the initial symptom in 50%. Such involvement is often subclinical, without obvious joint or tendon inflammation. Musculoskeletal ultrasound (US) has proven valuable for detecting pathological changes in joints and periarticular structures, including in SLE patients, and early detection, particularly in subclinical stages, supports optimal therapy, monitoring, and improved prognosis. This study aimed to determine the frequency of new clinical manifestations in patients with previously confirmed clinical and subclinical musculoskeletal inflammation after 2 and 5 years, and to evaluate associations with sex, age, BMI, smoking status, ESR, CRP, SLEDAI-2K, complement components C3 and C4, anti-dsDNA antibodies concentrations, and prior treatment. Methods: The study included 34 SLE patients with clinical and 22 with subclinical musculoskeletal inflammation, confirmed at baseline by history, examination, and US. Follow-up at 2 and 5 years recorded new clinical manifestations. Correlations with patient characteristics were assessed to identify predictors. Results: New clinical manifestations occurred in 34% of patients at 2 years and 48% at 5 years, most commonly cutaneous, musculoskeletal, and hematological. Summary analysis identified female sex, lower BMI, and lower baseline SLEDAI-2K scores as the strongest predictors. In the subclinical group, female sex, smoking, and lower SLEDAI-2K scores were predictive, while in the clinical group, female sex, lower SLEDAI-2K scores, lower ESR, and higher anti-ds DNA levels were associated with new manifestations. Conclusions: Female sex, lower BMI, and lower baseline SLEDAI-2K scores are key predictors of new clinical manifestations in SLE patients, highlighting the importance of early detection and individualized monitoring, particularly in patients with subclinical musculoskeletal inflammation. Full article

This study examines the ethical problems of using artificial intelligence (AI) applications in higher education, focusing on activities performed by university educators. Drawing on Slovak legislation that defines educators’ responsibilities, the study classifies their activities into three categories: teaching, scientific research, and other (academic management and self-directed professional development). From standpoint of methodology, a thematic review of 42 open-access, peer-reviewed articles published between 2022 and 2025 was conducted across the Web of Science and Scopus databases. Relevant AI applications and their associated ethical issues were identified and thematically categorized. Results of this study show that AI applications are extensively used across all analysed areas of university educators’ activities. Most notably used are applications that are generative language models, editing and paraphrasing tools, learning and assessment software, management and search tools, visualizing and design tools, and analysis and management systems. Their adoption raises ethical concerns which can be thematically grouped into six categories: privacy and data protection, bias and fairness, transparency and accountability, autonomy and oversight, governance gaps, and integrity and plagiarism. The results provide universities with a structured analytical framework to assess and address ethical risks related to AI use in specific academic activities. Although the study is limited to open-access literature, it offers a conceptual foundation for future empirical research and the development of ethical, institutionally grounded AI policies in higher education. Full article

Background: Immunisation remains one of the most effective and cost-efficient public health interventions for preventing infectious diseases in children. Despite global progress, Sub-Saharan Africa (SSA) continues to face challenges in achieving equitable immunisation coverage. Gender-related disparities, rooted in sociocultural and structural inequalities, significantly influence the prevalence of zero-dose and under-immunised children in the region. This review critically examines the gender-associated barriers to routine childhood immunisation in SSA to inform more inclusive and equitable health interventions. Methods: A critical literature review was conducted generally following some steps of the PRISMA-P and CRD guidelines. Using the Population–Concept–Context (PCC) framework, studies were selected that examined gender-related barriers to routine immunisation for children under five in Sub-Saharan Africa. Comprehensive searches were performed across PubMed, Google Scholar, and relevant organisational websites, targeting articles published between 2015 and 2025. A total of 3683 articles were retrieved, with 24 studies ultimately meeting the inclusion criteria. Thematic analysis was used to synthesise the findings. Results: Four major themes emerged: (1) women’s empowerment and autonomy, including limited decision-making power, financial control, and the impact of gender-based violence; (2) male involvement and prevailing gender norms, where patriarchal structures and low male engagement negatively influenced vaccine uptake; (3) socioeconomic and structural barriers, such as poverty, geographic inaccessibility, maternal workload, and service availability; and (4) education, awareness, and health system responsiveness. Conclusions: Gender dynamics have a significant impact on childhood immunisation outcomes in Sub-Saharan Africa. Future policies must integrate these insights to improve immunisation equity and reduce preventable child morbidity and mortality across the region. Full article

The adoption of artificial intelligence has risen, yet research on its impact on innovation processes between actual businesses remains sparse. This research fills the present gap by investigating ten workers from a tech startup who utilize artificial intelligence tools in operational and creative activities. The paper analyzes business-related AI functionality through a qualitative analysis of ten tech start-up employees. The examination reveals that AI produces significant enhancements in problem resolution by executing mundane actions while analyzing large datasets to deliver data-driven suggestions to users. The interview respondents mentioned that AI’s role in diminishing supply chains is 15%, while allowing AI to manage customer service without employee engagement in 80% of interactions. The implementation costs, along with data dependency and occasional contextual blindness in AI systems, represented some of the problems in this system. Analysis demonstrated that AI tools enable the development of innovative concepts and challenge established viewpoints, prompting participants to create a gamified loyalty system and dynamic content planning. Participants in the study emphasized the need for human involvement to refine AI-based insights, recognizing how human imagination complements AI capabilities effectively. The work enhances academic discussions about AI-related problem-solving and creativity while offering specific business-related recommendations for implementation. The recommendations begin with establishing initial experimental programs, while providing support for employee’s skills development, and fostering strong alliances between technical AI personnel and professional subject matter experts. Research topics focused on AI application fields and the anticipated impacts on company decision-making, as well as the ethical ramifications, need further exploration. This research confirms the revolutionary potential of artificial intelligence systems for problem-solving methods, but requires proper execution, along with human supervision, to fully realize their advantages. Full article

Cultural eutrophication caused by human activity significantly impacts benthic ecosystems. This study investigated how different phytobenthic components—rhodophyte germlings, mesoalgal and macroalgal assemblages, and Ulva cf. lactuca—respond to nutrient enrichment in a tidal channel system in San Antonio Bay, Argentina. Two experiments were conducted: one in spring examined the interaction between nutrient enrichment (N + P, N + P + Fe) and grazing pressure on early and established algal communities, and the other in autumn assessed nutrient effects on assemblages and Ulva cf. lactuca. Results showed that early successional stages, such as germlings and mesoalgae, responded most strongly to nutrient inputs, while mature macroalgae remained largely unaffected. Significant growth of mesoalgae, with increased pigment concentrations (chlorophyll a, c, and carotenoids), occurred at the eutrophied SAO Channel in spring. Nutrient additions increased rhodophyte germlings but eventually reduced diatom-dominated mesoalgal growth. Mature macroalgae showed site-specific differences but did not respond to fertilization. Grazing effects were evident in treatments with protective cages, suggesting herbivory influences early-stage algal development. Overall, the study emphasizes the importance of the successional stage, grazing pressure, and environmental nutrient history in shaping benthic algal responses to eutrophication, offering key insights into the dynamics of coastal ecosystems under increasing nutrient stress. Full article

Aim: This study analyzed the concurrent validity of the Optojump infrared photocell system for estimating lower limb peak power by comparing it with the 15 s Wingate anaerobic test (WAnT) and examining relationships with sprint performance indicators. Methods: Twelve physically active university students (ten males, two females; age: 23.39 ± 1.47 years; body mass: 73.08 ± 9.19 kg; height: 173.67 ± 6.97 cm; BMI: 24.17 ± 1.48 kg·m⁻²) completed a cross-sectional validation protocol. Participants performed WAnT on a calibrated Monark ergometer (7.5% body weight for males, 5.5% for females), 30 s continuous jump tests using the Optojump system (Microgate, Italy), and 30 m sprint assessments with 10 m and 20 m split times. Peak power was expressed in absolute (W), relative (W·kg⁻¹), and allometric (W·kg^−0.67) terms. Results: Thirty-second continuous jump testing produced systematically higher peak power values across all metrics (p < 0.001). Mean differences indicated large effect sizes: relative power (Cohen’s d = 0.99; 18.263 ± 4.243 vs. 10.99 ± 1.58 W·kg⁻¹), absolute power (d = 0.86; 1381.71 ± 393.44 vs. 807.28 ± 175.45 W), and allometric power (d = 0.79). Strong correlations emerged between protocols, with absolute power showing the strongest association (r = 0.842, p < 0.001). Linear regression analysis revealed that 30 s continuous jump-derived measurements explained 71% of the variance in Wingate outcomes (R² = 0.710, p < 0.001). Sprint performance showed equivalent predictive capacity for both tests (Wingate: R² = 0.66; 30 s continuous jump: R² = 0.67). Conclusions: The Optojump infrared photocell system provides a valid and practical alternative to laboratory-based ergometry for assessing lower limb anaerobic power. While it systematically overestimates absolute values compared with the Wingate anaerobic test, its strong concurrent validity (r > 0.80), large effect sizes, and equivalent predictive ability for sprint performance (R² = 0.66–0.71) confirm its reliability as a field-based assessment tool. These findings underscore the importance of sport-specific, weight-bearing assessment technologies in modern sports biomechanics, providing coaches, practitioners, and clinicians with a feasible method for monitoring performance, talent identification, and training optimization. The results further suggest that Optojump-based protocols can bridge the gap between laboratory precision and ecological validity, supporting both athletic performance enhancement and injury prevention strategies. Full article

The transition to electric mobility has intensified efforts to develop battery technologies that are not only high-performing but also environmentally sustainable. A critical element in battery system design is the structural housing, which must provide effective impact protection to ensure passenger safety and prevent catastrophic failures. This study examines the impact response of an innovative sheet molding compound (SMC) composite battery housing, manufactured from an Elium resin modified with Martinal ATH matrix, reinforced with glass fibers, that combines fire resistance and recyclability, unlike conventional thermoset and metallic housings. The material was characterized through standardized mechanical tests, and its impact performance was evaluated via drop-weight experiments on plates and a full-scale housing. The impact tests were conducted at varying energy levels to induce barely visible impact damage (BVID) and visible impact damage (VID). A finite element model was developed in LS-DYNA using the experimentally derived material properties and was validated against the impact tests. Parametric simulations of ground and pole collisions revealed the critical velocity thresholds at which housing deformation begins to affect the first battery cells, while lower-energy impacts were absorbed without compromising the pack. The study provides one of the first combined experimental and numerical assessments of Elium SMC in battery enclosures, emphasizing its potential as a sustainable alternative for next-generation battery systems for transport applications. Full article

Graduate students often experience difficulties in learning statistics, particularly those who have limited mathematical backgrounds. In recent years, Learning Management Systems (LMS) and Problem-Based Learning (PBL) have been widely adopted to support instruction, yet little research has explored how these tools relate to learning outcomes using mixed methods design. Limited studies have employed machine learning methods such as clustering analysis in Learning Analytics (LA) to explore different behavior of clusters based on students log data. This study followed an explanatory sequential mixed methods design to examine student engagement patterns on Canvas and learning outcomes of students in a graduate-level statistics course. LMS log data and surveys were collected from 31 students, followed by interviews with 19 participants. K-means clustering revealed two groups: a high-performing group with lower LMS engagement and a low-performing group with higher LMS engagement. Six themes emerged from a thematic analysis of interview transcripts: behavioral differences in engagement, the role of assessment, emotional struggle, self-efficacy, knowledge or skill gain, and structured instructional support. Results indicated that low-performing students engaged more frequently and benefited from structured guidance and repeated exposure. High-performing students showed more proactive and consistent engagement habits. These findings highlight the importance of intentional course design that combines PBL with LMS features to support diverse learners. Full article

This paper examines the role of architects in identifying and implementing design strategies that enhance labour skills, facilitate technology transfer, and support capacity building in developing economies. It examines whether specific design approaches can introduce technological robustness to address the social, cultural, and economic challenges of construction in fragmented industrial environments. The study develops a normative framework for ‘technological robustness,’ which counteracts socio-technical fragmentation and promotes resilient, adaptable building practices in low-resource settings. Through a practitioner-researcher case study of a community library project in Sri Lanka, the paper illustrates how design strategies can expand operational capacity, adjust to variations in workmanship, and encourage organic skill development on real construction sites. The research offers two main contributions: a scalable, structured design methodology that guarantees technical adaptability, cultural relevance, and economic resilience; and an empirical example demonstrating how design can actively generate opportunities for capacity building within fragmented socio-technical systems. Overall, the framework provides practical pathways to enhance construction outcomes in developing economies. Full article

This paper charts AI’s transformative path toward advancing sustainability within art museums, introducing a Human–AI compass as a conceptual framework for navigating its integration. It advocates for human-centric AI that optimizes operations, modernizes collection management, and deepens visitor engagement—anchored in meaningful human–technology synergy and thoughtful human oversight. Drawing on extensive literature review and real-world museum case studies, the paper explores AI’s multifaceted impact across three domains. Firstly, it examines how AI improves operations, from audience forecasting and resource optimization to refining marketing, supporting conservation, and reshaping curatorial practices. Secondly, it investigates AI’s influence on digital collection management, highlighting its ability to improve organization, searchability, analysis, and interpretation through automated metadata and advanced pattern recognition. Thirdly, the study analyzes how AI elevates the visitor experience via chatbots, audio guides, and interactive applications, leveraging personalization, recommendation systems, and co-creation opportunities. Crucially, this exploration acknowledges AI’s complex challenges—technical-operational, ethical-governance, socioeconomic-cultural, and environmental—underscoring the indispensable role of human judgment in steering its implementation. The Human-AI compass offers a balanced, strategic approach for aligning innovation with human values, ethical principles, museum mission, and sustainability. The study provides valuable insights for researchers, practitioners and policymakers, enriching the broader discourse on AI’s growing role in the art and cultural sector. Full article

Magnetohydrodynamic (MHD) flow and heat transfer in porous media are central to many engineering applications, including heat exchangers, MHD generators, and polymer processing. This study examines the boundary layer flow and thermal behavior of an electrically conducting viscous fluid over a porous stretching tube. The model accounts for nonlinear thermal radiation, internal heat generation/absorption, and Darcy–Forchheimer drag to capture porous medium resistance. Similarity transformations reduce the governing equations to a system of coupled nonlinear ordinary differential equations, which are solved numerically using the BVP4C technique with Response Surface Methodology (RSM) and sensitivity analysis. The effects of dimensionless parameters magnetic field strength (M), Reynolds number (Re), Darcy–Forchheimer parameter (Df), Brinkman number (Br), Prandtl number (Pr), nonlinear radiation parameter (Rd), wall-to-ambient temperature ratio (rw), and heat source/sink parameter (Q) are investigated. Results show that increasing M, Df, and Q suppresses velocity and enhances temperature due to Lorentz and porous drag effects. Higher Re raises pressure but reduces near-wall velocity, while rw, Rd, and internal heating intensify thermal layers. The entropy generation analysis highlights the competing roles of viscous, magnetic, and thermal irreversibility, while the Bejan number trends distinctly indicate which mechanism dominates under different parameter conditions. The RSM findings highlight that rw and Rd consistently reduce the Nusselt number (Nu), lowering thermal efficiency. These results provide practical guidance for optimizing energy efficiency and thermal management in MHD and porous media-based systems.: Full article

The escalating global crisis of antimicrobial resistance demands innovative therapeutic strategies that transcend conventional approaches. This comprehensive review examines the groundbreaking synergistic integration of silver nanoparticles (AgNPs) with silk proteins (fibroin and sericin from Bombyx mori) to create advanced nanocomposite materials for biomedical applications. While extensive literature exists for AgNPs and silk proteins individually, a limited number of studies have explored their synergistic combination. This review consolidates this fragmented knowledge to establish the foundational framework for an emerging field. The unique properties of silk proteins as natural reducing, stabilizing, and capping agents enable environmentally friendly AgNPs synthesis while creating intelligent therapeutic platforms with emergent properties. These hybrid materials demonstrate superior performance in terms of antimicrobial efficacy, biocompatibility, and accelerated wound healing compared to the individual components. The nanocomposites exhibit broad-spectrum activity against multidrug-resistant pathogens while maintaining exceptional biocompatibility and promoting tissue regeneration. This integration represents a promising evolution toward biomimetic therapeutic platforms that work in harmony with biological systems, offering sustainable solutions to contemporary healthcare challenges. Full article

Amid ongoing educational reforms and the rapid advancement of the knowledge economy, innovative teaching behaviors are not only closely related to teachers’ professional growth and students’ academic achievement but are also regarded as the key driving force for the evolution of the educational system. Consequently, identifying effective ways to foster teachers’ innovative teaching behaviors has become a central concern in educational psychology and management. Grounded in the Job Demands–Resources framework, this study developed and tested a chained mediation model using survey data from 1163 Chinese elementary and secondary school teachers. The model examines how teachers’ emotional competence fosters innovative teaching behaviors and elucidates the underlying mechanisms. The results revealed that (1) emotional competence significantly and positively predicted innovative teaching behaviors, and (2) teaching efficacy and work vitality served not only as independent mediators but also as sequential mediators in this relationship. These findings extend the understanding of the antecedents of teachers’ innovative behaviors from an emotional perspective, demonstrating that emotional competence, as a critical psychological resource, can be transformed into innovative teaching behaviors through dual “cognitive–motivational” and “energy–motivational” pathways. This study offers both theoretical insights and practical implications for advancing teaching innovation by strengthening teachers’ emotional competence, teaching efficacy, and work vitality. Full article

This study presents the modeling and analysis of a composite structure incorporating an embedded macro fiber composite (MFC) patch. MFC actuators are available in several variants, with types P1 and P2 being the most commonly used. In this paper, an electromechanical model of the hybrid structure is developed, and experimental procedures are outlined for identifying selected system parameters. In the first phase of the study, two separate cantilever beam specimens are investigated—one with an embedded P1 patch and the other with a P2 patch. Their behaviors are tested and compared to identify and critically assess the advantages and limitations associated with each MFC type. In the second phase, a more complex system—a bistable cantilever shell—is examined. The choice of the appropriate MFC type (P1 or P2) for this structure is based on the findings obtained in the first phase. For the system incorporating the selected MFC patch, the dynamic response is analyzed in the vicinity of both stable equilibrium states, which are characterized by significantly different levels of pre-strain and pre-stress. The study concludes with highlights for the design of smart composite structures with integrated MFC patches. Full article

A balance between support and independence in guardianship systems is of high concern, especially with those who need help in making decisions. The research presents a novel approach to evaluating voluntary models of guardianship, focusing on the preservation of individual autonomy and examining the underlying decision symmetry in assessing diverse guardianship options. The ultimate solution to the inherent uncertainty and lack of objectivity in expert evaluations is to apply the circular q-rung orthopair fuzzy (Cq-ROF) combined compromise for ideal solution (CoCoFISo) approach, an effective multi-criteria decision-making (MCDM) model that integrates ranking and sorting views using a Cq-ROF framework within a symmetry-oriented analytical perspective. These are five major assessment factors: how well autonomy is preserved, legal and ethical adherence, psychological health, social integration aid, and risk prevention. It explores ten alternative approaches to guardianship, ranging from complete legal guardianship to community-based self-management solutions, and the use of technology as an element of support. The suggested approach can facilitate more sophisticated modelling of expert opinions, rather than relying on simplistic and straightforward distinctions and diverse evaluations. The case study results indicate that the hybrid and supported forms of decision-making could offer opportunities to preserve a high degree of personal autonomy while ensuring safety and compliance. The research gives a coherent, adaptable, and explainable approach to managing ethical and policy-level judgment concerning voluntary guardianship systems. Full article