Search Results (39,628)

Social media influencers (SMIs) have become effective intermediaries that influence consumer perceptions, attitudes, and behavioral intentions through their online presence and persuasion skills; this has made it imperative to comprehend how buyer-related variables contribute to brand loyalty within contemporary marketing research. This study, therefore, examines the effect of social media influencer capability on brand loyalty in Saudi Arabia, using brand trust as a mediating variable and authentic leadership as a moderating variable. Utilizing Social Exchange Theory and Authentic Leadership Theory, the study applied a quantitative cross-sectional survey design. Data were purposively collected from 476 active social media users in three major commercial hubs in Saudi Arabia (Riyadh, Jeddah, and Dammam). The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that authenticity and communication skills have a positive and significant influence on brand trust and brand loyalty, but expertise and influence only have a significant and positive influence on brand trust, not on brand loyalty directly, which means that the two constructs are indirectly influencing brand loyalty. The study also finds that authentic leadership significantly moderates the relationship between expertise, influence, and communication skills and brand loyalty, while the interaction with authenticity is not significant. Moreover, the mediation analysis shows that brand trust plays a significant mediating role in the relationships between communication skills, expertise and influence and brand loyalty, implying that the antecedents play a leading role in fostering loyalty by first developing trust. The study contributes to theory by offering a process-based perspective on the concept of brand loyalty that positions brand trust as a fundamental mechanism and authentic leadership as a vital enabling context. The findings have practical implications for organizations that want to strengthen brand loyalty through authentic communication, trust-building strategies, and leadership practices in social media-based contexts. Full article

Cybersecurity operations in IoT and edge environments require fast, evidence-grounded decisions under strict resource and trust constraints. While large language models can support triage and incident analysis, their parametric knowledge may be outdated and prone to hallucination. Retrieval-augmented generation (RAG) improves grounding by conditioning responses on retrieved evidence, but also introduces new risks such as knowledge-base poisoning, indirect prompt injection, and embedding leakage. Federated learning enables collaborative adaptation without centralizing sensitive data, motivating federated RAG (FedRAG) architectures for distributed cybersecurity deployments. This study presents a deployment-oriented scoping review of FedRAG for cybersecurity. The review follows PRISMA-ScR reporting guidance and synthesizes 82 studies published between 2020 and 2026, identified through keyword search and citation snowballing over OpenAlex, arXiv, and Crossref. We develop a taxonomy that clarifies the components of federated systems, deployment locations, trust boundaries, and protected assets. We further map the combined RAG+FL attack surface, summarize practical defenses and system patterns, and distill actionable guidance for secure, privacy-preserving, and efficient FedRAG deployment in real-world IoT and edge scenarios. Our synthesis highlights recurring trade-offs among robustness, privacy, latency, communication overhead, and maintainability, and identifies open research priorities in benchmark design, governance mechanisms, and cross-silo evaluation protocols for practical deployment. Full article

Extracellular vesicles (EVs), as key mediators of intercellular communication, play multifaceted roles in the pathogenesis, treatment, drug resistance, and monitoring of B-cell non-Hodgkin lymphomas (B-NHLs), including diffuse large B-cell lymphoma (DLBCL), Burkitt lymphoma (BL), follicular lymphoma (FL), and mantle cell lymphoma (MCL). EVs derived from lymphoma cells or tumor microenvironment cells carry diverse cargoes such as proteins, microRNAs (miRNAs), and viral oncoproteins, which regulate tumor progression by modulating signaling pathways related to cell proliferation, invasion, apoptosis, autophagy, and immune suppression. In terms of treatment, accumulating evidence suggests that EVs may be associated with the efficacy of classical regimens such as R-CHOP, and they also hold potential as therapeutic targets and drug delivery vehicles for B-NHL. They contribute to drug resistance by altering the expression of key molecules or reshaping the tumor niche. Additionally, EV-derived biomarkers enable non-invasive diagnosis and monitoring of treatment response and prognosis. This review summarizes the latest research progress on the roles of EVs in major B-NHL subtypes, aiming to provide new insights for the development of innovative diagnostic and therapeutic strategies for B-NHL. Full article

Information visualization is a crucial yet often underdeveloped research skill in graduate education. This study examined how practice-based visualization instruction enhances graduate students’ conceptual understanding and procedural competence in scientific graph construction. Forty first-year graduate students participated in a ten-week instructional program combining diagnostic assessment, guided exercises, and a complex graph replication task. Conceptual and procedural competence were evaluated using validated analytic rubrics to ensure reliability and depth of analysis. Results showed substantial improvement in students’ ability to select suitable chart types, label axes accurately, and apply coherent color schemes. Consistent with the study’s hypotheses, significant gains were observed in conceptual understanding (H1) and technical execution (H2), and a moderate positive correlation between the two domains (H3) confirmed that stronger conceptual grasp aligned with higher visualization proficiency. Iterative feedback and guided reflection supported the integration of theory and practice. However, challenges in detailed annotation and multivariable coordination persisted. Overall, structured, practice-based visualization training enhanced methodological competence and communication clarity. Embedding such experiential learning within graduate curricula can strengthen visualization literacy and support the development of research independence. Full article

Although high-frequency electromagnetic methods, such as Radio Magnetotellurics (RMT) and Controlled-Source Radio Magnetotellurics (CSRMT), are highly effective for shallow-to-medium depth exploration, deploying traditional transmitter–receiver setups remains labor-intensive and significantly slows down large-scale surveys. To overcome these logistical bottlenecks, we developed a mobile Ultra-Audio Frequency Electromagnetic (UAEM) measurement system. While the hardware is designed with dual-mode capabilities supporting conventional controlled-source operations, this paper specifically focuses on its application in a Signals of Opportunity (SOOP) mode. By utilizing pre-existing, stable anthropogenic signals, including Amplitude Modulation (AM) broadcasts and naval very low frequency communications, the system effectively functions as a broadband RMT receiver. Technical evaluations demonstrate that the instrument operates across a 1 Hz to 1000 kHz bandwidth with a high sampling rate of 2.5 MHz. Furthermore, it achieves a dynamic range of 143 dB and maintains an apparent resistivity measurement accuracy of better than 3%. Thanks to its modular, vehicle-towed design, the UAEM system enables continuous, on-the-move data acquisition wherever ambient field sources are available. This approach eliminates the need for dedicated transmitter deployment, fundamentally reducing exploration costs and boosting overall survey efficiency. Full article

Master–slave bilateral teleoperation systems face several practical challenges, including model uncertainties, time-varying communication delays, and environment-induced force disturbances. To address these issues, this paper proposes an adaptive super-twisting sliding-mode control scheme to achieve high-precision position tracking and real-time force-feedback synchronization. First, joint-space dynamic models are established for both the master and the slave manipulators, and a passive impedance model is adopted to characterize the interaction dynamics at the operator–master and environment–slave interfaces. Second, to attenuate measurement noise in the environment interaction force, a first-order low-pass filter is used to preprocess the raw force measurements, and a radial basis function neural network (RBFNN) is employed to approximate the environment torque online. Furthermore, a super-twisting sliding-mode controller is developed and combined with an adaptive law to compensate online for system uncertainties, including dynamic parameter variations and environment-induced force disturbances. The stability of the resulting closed-loop system is rigorously analyzed using Lyapunov stability theory. Finally, the effectiveness of the proposed method is validated through numerical simulations, virtual experiments conducted in the MuJoCo physics engine, and real-world hardware experiments. The results show that the proposed strategy achieves accurate position synchronization and force tracking while maintaining stable haptic interaction in the presence of bounded time-varying delays, parameter uncertainties, and external disturbances. Full article

The school garden has a long-standing pedagogical tradition linked to active, experiential, and community-based education, represented by authors such as Montessori, Freinet, and Dewey. Currently, its role has been consolidated as a relevant educational resource used to address the challenges of sustainability education, pedagogical innovation, and student holistic development. This research takes a qualitative approach based on a multiple case study conducted in four educational centers in Spain and Portugal. Semi-structured interviews, documentary analysis, and reflective memoranda were used. Content analysis was performed using a deductive–inductive coding approach in ATLAS.ti software v. 25th, combining literature-derived categories with those emerging from the data, following a thematic analysis (TA) approach. The results suggest that school gardens promote meaningful learning, the development of transversal competencies, improved school climate, and community involvement. Pedagogical, social, and emotional benefits were identified, as well as high levels of satisfaction among all participants. However, obstacles were found to persist, mainly related to a lack of time and teacher coordination. The study confirms that the school garden serves as a pedagogical resource with a high transformative potential. Its effectiveness depends on intentional curricular integration, teacher commitment, and the engagement of the educational community, aligning with the principles of an active, sustainable, and contextualized pedagogy. Full article

Artificial Intelligence (AI)-based crack detection in buildings uses computer vision and deep learning to automatically identify structural cracks from inspection images. In recent years, many studies have explored this topic, but the overall development of the field, its methodological practices, and the remaining challenges are still not fully clear. Unlike most previous reviews that focus mainly on technical methods, this study combines a large-scale scientometric mapping of the research field with a focused technical analysis of recent AI-based crack detection methods specifically applied to building structures. This study therefore provides a dual-layer review covering research published between 2015 and 2025. A total of 146 Scopus-indexed publications were analysed using Visualization of Similarities viewer (VOSviewer) to examine publication growth, thematic evolution, collaboration patterns, and citation structures. In addition, a focused technical review of 36 highly relevant studies was carried out to analyse task formulations, model families, datasets, evaluation protocols, and methodological practices. The results show a rapid increase in research activity after 2020, largely driven by advances in deep-learning and Unmanned Aerial Vehicle (UAV)-based inspections. At the same time, collaboration networks remain uneven, and citation influence is concentrated in a limited number of research communities. The technical review further shows that most studies focus on detection-level tasks, particularly You Only Look Once (YOLO)-based models, while predictive diagnostics, automated inspection reporting, and decision-oriented Structural Health Monitoring (SHM) are still rarely addressed. Current datasets and evaluation protocols also remain mostly perception-oriented, which makes it difficult to assess robustness, generalisability and long-term predictive capability. Full article

This study examines how justice-oriented modeling lessons promote elementary students’ capacity to mathematize complex situations, develop civic empathy, and take action to address inequities and injustices in their communities. Through qualitative methods using multiple data sources including teacher interviews, lesson transcripts, student work, and classroom artifacts we share cases of modeling tasks that use mathematics as an empowerment tool to address empathy, representation, access, fairness and taking action. Findings illustrated critical moment-to-moment instructional decisions teachers made to elicit students’ justice-oriented reasoning. The modeling tasks involved addressing food waste in the school cafeteria, creating an inclusive play area, diversifying the school library collections, and choosing items for a sensory space to positively impact students’ individual and community well-being. Implications for teachers and teacher educators will be discussed. Full article

Arsenic (As) is a ubiquitous and highly toxic metalloid with well-established carcinogenicity. Its accumulation and secondary release from lake sediments pose potential risks to lake ecosystem integrity and human health. Meanwhile, the ongoing intensification of lake eutrophication at the global scale has altered the sources, composition, and environmental behavior of internally derived dissolved organic matter (DOM). These changes have profoundly influenced As mobilization and transformation at the sediment-water interface (SWI). To advance understanding of the regulatory roles and underlying mechanisms of algal dissolved organic matter (ADOM) and submerged macrophyte dissolved organic matter (SMDOM) in As biogeochemical cycling under lake ecosystem regime shifts, extensive findings from the international literature were synthesized. The characteristic properties and environmental behaviors of ADOM and SMDOM were systematically compared, and their distinct regulatory pathways in lacustrine systems were further summarized. Results indicate that ADOM is typically characterized by low molecular weight, weak aromaticity, and high bioavailability. It can enhance As dissolution and mobilization from sediments through direct complexation, competition for adsorption sites, and stimulation of microbial metabolism and Fe(III) reduction. In contrast, SMDOM exhibits higher molecular weight, greater aromaticity, and a higher degree of humification. It tends to form stable complexes with mineral phases. Under the influence of radial oxygen loss (ROL) from submerged macrophyte roots during the growth phase, its capacity to promote mineral reduction is relatively limited. This process favors stable As retention in sediments. The regulatory effects of ADOM and SMDOM on As behavior are strongly modulated by environmental factors such as pH, redox potential (Eh), temperature, and light conditions, as well as by microbial communities. ADOM is more sensitive to reducing environments and photochemical processes. SMDOM, in contrast, exerts more persistent control under oxidizing conditions and at mineral-water interfaces. In addition, ADOM more readily drives microbial community shifts toward assemblages with enhanced capacities for Fe(III) reduction and As reduction or methylation. SMDOM is less likely to trigger strongly reducing processes. Based on these mechanisms, the outbreak and decay phases in algal-dominated lakes often correspond to critical periods of enhanced As mobilization and elevated ecological risk. In submerged macrophyte-dominated lakes, the decay phase may represent an important window for sedimentary As release. Finally, a conceptual framework describing the differential regulation of As biogeochemical cycling by ADOM and SMDOM is proposed. This framework provides a theoretical basis for As risk identification, the determination of critical risk periods, and the development of management strategies across lakes with different trophic states. Full article

This study presents a comprehensive 35-year (1990–2025) shoreline change assessment along the southeast coast of Ireland, integrating multi-decadal Landsat satellite archives with GIS-based Digital Shoreline Analysis System (DSAS) metrics to quantify both spatial and temporal coastal dynamics. Unlike previous studies that focus on shorter timeframes or localized sectors, this research provides a regional-scale, orientation-specific comparison between the eastern-facing (SE1; County Wexford) and southern-facing (SE2; County Waterford) shorelines. Shoreline evolution was quantified using four complementary DSAS indicators—Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR), allowing robust discrimination between short-term variability and multi-decadal trends. The results reveal noticeable spatial variability in shoreline behavior with 57% accretion and 42% erosion across the eastern-facing coast (SE1) in County Wexford and the southern-facing coast (SE2) in County Waterford. SCE values ranging from 2.26 m to 663.83 m indicate considerable short-term shoreline variability, particularly within dynamic barrier and embayed systems. NSM values between −216.65 m and +663.83 m indicate erosional hotspots, particularly along soft-sediment coasts and exposed southern-facing sectors, whereas accretion is limited to embayments, sandy beaches, and zones of effective sediment trapping. Rate-based analyses show EPR values between −14.82 and +20.38 m/yr and LRR values between −5.27 and +20 m/yr, with LRR providing more reliable estimates of multi-decadal trends in highly dynamic environments. The findings highlight the strong influence of coastal orientation, sediment availability, geological controls, and human activities on shoreline change in southeastern Ireland. These findings provide valuable evidence to support coastal management, hazard mitigation, and climate adaptation planning, with the assistance of policymakers, to develop effective strategies that enhance the resilience and quality of life of coastal communities. Full article

Antibiotic therapy represents one of the strongest ecological perturbations of the human gut microbiota, inducing rapid and often prolonged alterations in community structure, metabolic activity, and functional resilience. While the use of probiotics to mitigate antibiotic-associated dysbiosis is widely adopted in clinical practice, probiotic selection is still largely empirical and insufficiently grounded in biological compatibility with specific antibiotic pressures. In this conceptual review, antibiotics are reframed not merely as antimicrobial agents, but as ecological forces that shape microbial survival, quiescence, and recolonization dynamics. We propose a biologically informed framework that distinguishes genetic antibiotic resistance from functional or ecological insensitivity, highlighting how microbial traits, such as the absence or inaccessibility of the antibiotic target, metabolic state, sporulation, and cellular architecture, influence the persistence of probiotics during antibiotic exposure. By integrating the mechanisms of action of antibiotics with key physiological and structural features of probiotic microorganisms, we develop a conceptual framework aimed at rationalizing the compatibility of probiotics and antibiotics. This framework does not imply clinical efficacy but provides an interpretative tool to guide hypothesis generation, experimental validation, and the design of future targeted probiotic strategies. A more ecologically grounded approach to probiotic selection may ultimately improve microbiota support during antibiotic therapy and advance personalized microbiome modulation. Full article

Speaking proficiency remains one of the most challenging skills for learners of English as a Foreign Language (EFL), particularly in contexts where sustained spoken interaction is limited. This systematic review synthesises 36 empirical studies (2015–2025) identified through a PRISMA-guided Scopus search to examine how artificial intelligence (AI)-mediated instruction supports EFL speaking development. The included studies were analysed according to AI modality, pedagogical integration, instructional input characteristics, and linguistic and affective outcomes. Findings indicate that AI tools—such as chatbots, automatic speech recognition systems, and large language models—consistently support affective outcomes, including reduced speaking anxiety and increased willingness to communicate. Improvements in fluency, pronunciation, and accuracy were frequently reported, particularly when AI tools were embedded within task-based and pedagogically structured instructional designs. However, evidence for sustained development of higher-order communicative competence was more variable. The review proposes a mediated input framework conceptualising AI as a design-sensitive instructional resource rather than an autonomous teaching agent. Full article

A wide range of Leishmania species, transmitted by phlebotomine, cause leishmaniasis, which presents diverse clinical manifestations. Leishmaniasis has a high impact on vulnerable communities, primarily affecting people suffering from malnutrition or poor housing. Because leishmaniasis is associated with poverty, access to treatment is limited. In addition, high drug toxicity and therapeutic failure, related to drug resistance, remain major challenges. Therefore, there is a need to develop new therapeutic approaches that are safer and more effective. Drug combinations and repurposing are two strategies used in the development of treatments. The combination of drugs with different mechanisms of action can minimise resistance and allow dose reduction, increasing the likelihood of successful drug repurposing. This study evaluated the antileishmanial effects of combining antitumoral agents (paclitaxel and docetaxel) with standard drugs (miltefosine and paromomycin). Results demonstrated synergistic effects at higher doses. Furthermore, the antitumoral compounds enhanced the host immune response by promoting macrophage polarisation toward the M1 phenotype, essential for parasite control. These findings highlight a promising approach that could improve efficacy and reduce resistance. Full article

Authentic, situated learning experiences which mirror the collaborative nature of healthcare practice are essential in preparing students for their future professions. Feedback literacy may be thought of as the understanding, capacity, and disposition needed to make sense of information and use it to enhance work or learning strategies. This study explored how feedback literacy can be developed through situated, interprofessional peer-to-peer feedback within a community-based paediatric health screening programme. Using an exploratory Action Research qualitative design, the planning activities stage explored current practice, gathering student insights via interviews, reflections, and a workshop to co-design an Interprofessional Feedback Conversation Guide (IPFCG). The IPFCG was piloted, integrating structured feedback tools and protected time for peer exchange, within the community screening activity. Feedback regarding use of the IPFCG contributed to the gathering data stage, which was followed by the evaluation and reflection stage. Evaluation revealed four key themes: value, engagement, optimising relationships, and structuring conversations. Students valued receiving feedback from peers outside their discipline, actively engaged with the process, emphasised the importance of building rapport, and utilised structured dialogue. These findings highlight how authentic, field-based learning can foster feedback literacy, enhancing the development of professional identity. The interprofessional nature of the program reflects the complexity of modern healthcare and demonstrates how curriculum-integrated models of authentic learning can enhance student engagement and workplace readiness. This study contributes to the evolving conversation about embedding authenticity in higher education and offers a practical model for building collaborative communication within situated learning experiences at scale. Full article