The rise of antimicrobial resistance caused by inappropriate use of these agents in various settings has become a global health threat. Nanotechnology offers the potential for the synthesis of nanoparticles (NPs) with antimicrobial activity, such as iron oxide nanoparticles (IONPs). The use of IONPs is a promising way to overcome antimicrobial resistance or pathogenicity because of their ability to interact with several biological molecules and to inhibit microbial growth. In this review, we outline the pivotal findings over the past decade concerning methods for the green synthesis of IONPs using bacteria, fungi, plants, and organic waste. Subsequently, we delve into the primary challenges encountered in green synthesis utilizing diverse organisms and organic materials. Furthermore, we compile the most common methods employed for the characterization of these IONPs. To conclude, we highlight the applications of these IONPs as promising antibacterial, antifungal, antiparasitic, and antiviral agents.

Pathogenic microorganisms can cause a range of infectious diseases and are often treated with antimicrobial agents. The rise of antimicrobial resistance caused by inappropriate use of these agents in various settings has become a global health threat. There is, therefore, a need to find new and effective agents to combat infections caused by resistant pathogens. Nanotechnology has seen significant growth and development in recent years and has a wide range of applications in various fields, including health, agriculture, and industry. This novel area offers the potential for the synthesis of nanoparticles (NPs) with antimicrobial activity, such as iron oxide nanoparticles (IONPs). The use of IONPs is a promising way to overcome antimicrobial resistance or pathogenicity because of their ability to interact with several biological molecules and to inhibit microbial growth. This review focuses on the most common green synthesis methods for producing IONPs using bacteria, fungi, plants, and organic waste, as well as the most common methods for the characterization of these IONPs. Finally, it summarizes their application as promising antibacterial, antifungal, antiparasitic, and antiviral agents.

Introduction: The study provided a comprehensive bibliometric analysis addressing the challenges for virtual distance education, primarily among populations facing significant barriers, such as individuals with disabilities, web accessibility constraints, and those affected by diverse socioeconomic or geopolitical factors.Methods: The analysis encompassed publications from the last ten years. A co-occurrence approach was employed to identify thematic trends, conceptual relationships, and geographic contributions. Data were filtered for relevance and subjected to quantitative indicators (e.g., publication counts by year) to track research evolution.Results: The findings indicated a marked increase in scholarly attention to enhancing accessibility in virtual education, as evidenced by rising annual publication volumes. The United States, China, and the United Kingdom emerged as the leading contributors to this scientific discourse. Key challenges identified included technological barriers, socio-economic disparities, and the need for inclusive pedagogical strategies targeting marginalized groups.Conclusions: The analysis underscored the importance of a multidimensional and inclusive approach to advancing digital education. By highlighting persistent obstacles and emerging solutions, the study informed policy, technological innovation, and instructional design aimed at fostering equitable participation in virtual distance education for underrepresented communities.

Digital internationalization has moved beyond “mobility-at-a-distance” toward course-embedded designs that can scale intercultural competence (IC) development. Using PRISMA, we mapped digital technologies and pedagogical strategies used to teach IC in higher education, outcome measures, direction of effects, and equity-related implementation conditions, and we added mechanism-oriented coding linking modality affordances to learning processes and IC outcomes. We searched Scopus, Web of Science, and ERIC and screened 133 records. Twenty-four studies (total n = 1,787) met eligibility criteria. We combined descriptive bibliometrics with an adapted JBI quality appraisal (median quality 78.6%, IQR 57.1–85.7), a SWiM synthesis of effect direction by strategy, and intervention-level mechanism coding. Evidence clusters around LMS/forums, videoconferencing and collaboration suites, immersive VR/360°, telepresence/telesimulation, MOOCs, and guided inquiry. Across modalities, the most consistent IC gains occur when interventions instantiate structured intercultural contact, facilitation and feedback, authentic co-production, and guided reflection/debriefing. Scenario-based and immersive formats are most effective when situated performance is paired with structured debriefing and feedback. By contrast, content-centric LMS/MOOC formats show mixed results unless instructors engineer dialogic tasks and active facilitation to convert exposure into interaction. Most studies rely on standardized self-report measures; performance or observational evidence is less common and concentrates in simulation and role-play contexts. Reported constraints include connectivity, language and time-zone barriers, and facilitation workload, underscoring the role of institutional support. Future research should strengthen comparative and longitudinal designs, report implementation fidelity and dosage, validate instruments across languages, and triangulate self-report with performance evidence and downstream academic/employability outcomes.

Introduction: The COVID-19 pandemic triggered unprecedented disruptions in education, catalyzing shifts in policy research worldwide. This study offers a comprehensive bibliometric analysis of educational policy scholarship from 2014 to 2024, focusing on changes in research output, thematic trends, and geographic patterns before and after the onset of COVID-19.Methods: A systematic search was conducted in Scopus and Web of Science using the keywords “educational legislation,” “educational law,” “educational policy,” and “education regulation” while excluding terms related to COVID-19 or the pandemic to avoid bias. Data were filtered by open-access status, exported, and deduplicated. Bibliometric indicators were calculated to examine publication volume and top publishing countries. VOSviewer was employed for keyword co-occurrence analysis.Results: The findings reveal a notable increase in publication output after 2020, particularly in countries like the United States, Spain, and emerging contributors like Chile and Brazil. Co-occurrence analysis indicates heightened attention to digital learning, equity, and public health dimensions in post-pandemic research.Conclusions: The pandemic has amplified existing themes of equity and curriculum reform and introduced new focal points, including distance education and socioemotional well-being. These insights inform policymakers and researchers seeking to develop resilient and inclusive educational frameworks in a rapidly changing global context.

This paper presents a physics-informed, tacholess pipeline for smartphone-grade Noise, Vibration, and Harshness (NVH) diagnosis in electric vehicle powertrains. A configurable generator synthesizes labeled signals with order components (1×/2×/3×), AM/FM modulation, sub-harmonics, impact-driven ring-down near resonance, and realistic white/pink/ambient noise at phone bandwidths. A ridge-guided harmonic comb recenters orders without a tachometer and splits tonal from residual content. Interpretable features—order-invariant ratios ($E_{2\times }/E_{1\times }$, ${\mathrm{S}\mathrm{B}}_1$/$E_{1\times }$, $E_{0.5\times }/E_{1\times }$) and residual descriptors (band-power, kurtosis, cepstrum/WPT)—feed light-compute models. A reproducible benchmark stresses SNR (−5…+10 dB), RPM profiles (ramp/steps/cycles), and simulated domain shift; parameter-to-feature analyses (with Sobol sensitivity and a delta-method identifiability proxy) quantify measurability under phone constraints. Across a five-fold CV, tacholess order tracking increases tonal SNR by ≥+6 dB and yields macro-F1 ≈ 0.86 with Random Forest, while ordinal severity achieves QWK ≈ 0.81 (ECE ≈ 0.06) and regression attains MAE ≈ 0.12 (R² ≈ 0.78). All code, datasets, figures, and tables regenerate from fixed seeds with one-command builds; a data card and a sim-to-real guide are included. The result is an open, low-compute standard that couples reproducibility with physics-aligned interpretability, providing a practical baseline for EV NVH diagnostics with smartphones and a common ground for future field validation.