Two-dimensional hexagonal boron nitride nanosheets (h-BNNS) were synthesized on silver (Ag) substrates via a scalable, room-temperature atmospheric pressure plasma (APP) technique, employing borazine as a precursor. This approach overcomes the limitations of conventional chemical vapor deposition (CVD), which requires high temperatures (>800 °C) and low pressures (10−2 Pa). The h-BNNS were characterized using FT-IR spectroscopy, confirming the presence of BN functional groups (805 cm−1 and 1632 cm−1), while FESEM/EDS revealed uniform nanosheet morphology with reduced particle size (80.66 nm at 20 min plasma exposure) and pore size (28.6 nm). XRD analysis demonstrated high crystallinity, with prominent h-BN (002) and h-BN (100) peaks, and Scherrer calculations indicated a crystallite size of ~15 nm. The coatings exhibited minimal disruption to UV-VIS reflectivity, maintaining Ag's optical properties. Crucially, Vickers hardness tests showed a 39% improvement (38.3 HV vs. 27.6 HV for pristine Ag) due to plasma-induced cross-linking and interfacial adhesion. This work establishes APP as a cost-effective, eco-friendly alternative for growing h-BNNS on temperature-sensitive substrates, with applications in optical mirrors, corrosion-resistant coatings, energy devices and gas sensing.

Poly(methyl methacrylate) (PMMA) is a versatile and widely used polymer that has gained significant attention in various industries due to its unique combination of properties and ease of processing. PMMA, also known as acrylic or plexiglass, is a transparent thermoplastic with exceptional optical clarity, high-impact resistance, and excellent weatherability. This scholarly article endeavors to offer an exhaustive examination of the composition, characteristics, and broad utilization of poly(methyl methacrylate) (PMMA). This study aims to conduct an in-depth analysis of the molecular composition and chemical attributes inherent to PMMA. Furthermore, it intends to examine the mechanical and physical attributes exhibited by PMMA meticulously. Additionally, an exploration of varied methodologies employed in the processing and fabrication of PMMA will be undertaken. The extensive array of applications of PMMA spanning multiple industries will be underscored, followed by a comprehensive discourse on its merits, constraints, contemporary advancements, and prospective avenues. Understanding the properties and applications of PMMA is crucial for engineers, scientists, and professionals working in fields such as automotive, aerospace, medical, and signage, where PMMA finds extensive use.

Academic integrity has been at the centre of the discussion of the adoption of Chat GPT by academics in their research. This study explored how academic integrity mitigates the desire to use ChatGPT in academic tasks by EFL Pre-service teachers, in consideration of the time factor, perceived peer influence, academic self-effectiveness, and self-esteem. The study utilized web-based questionnaires to elicit data from 300 EFL Pre-service teachers across educational fields drawn from different schools across the world. Analysis was conducted using relevant statistical measures to test the projected four hypotheses. The findings provide evidence in support of Hypothesis 1, with a statistically significant path coefficient (β) of 0.442, a t-value of 3.728, and a p-value of 0.000. The hypothesis acceptance implies that when academic integrity improves, the impact of the time-saving aspect of the use of ChatGPT Across educational fields study decreases. This suggests that EFL Pre-service teachers who have a firm dedication to academic honesty are less influenced by the tempting appeal of ChatGPT’s time-saving features, highlighting the ethical factors that influence their decision-making. The data also provide support for Hypothesis 2, indicating a substantial inverse relationship with a path coefficient (β) of 0.369, a t-value of 5.629, and a p-value of 0.001. These findings indicate that stronger adherence to academic integrity is linked to a diminished effect of colleagues on the choice to use ChatGPT in Academic tasks. The results suggest that a firm dedication to academic honesty serves as a protective barrier against exogenous pressures or influences from colleagues when it comes to embracing cutting-edge technology. However, in general, these findings revealed there was a negative association between academically related factors (e.g., time factor, sense of peer pressure, language study self-confidence, and academic language competence), as well as an attitude toward adoption of ChatGPT and commitment towards academic integrity.

Adequate sanitation is crucial for human health and well-being, yet billions worldwide lack access to basic facilities. This comprehensive review examines the emerging field of intelligent sanitation systems, which leverage Internet of Things (IoT) and advanced Artificial Intelligence (AI) technologies to address global sanitation challenges. The existing intelligent sanitation systems and applications is still in their early stages, marked by inconsistencies and gaps. The paper consolidates fragmented research from both academic and industrial perspectives based on PRISMA protocol, exploring the historical development, current state, and future potential of intelligent sanitation solutions. The assessment of existing intelligent sanitation systems focuses on system detection, health monitoring, and AI enhancement. The paper examines how IoT-enabled data collection and AI-driven analytics can optimize sanitation facility performance, predict system failures, detect health risks, and inform decision-making for sanitation improvements. By synthesizing existing research, identifying knowledge gaps, and discussing opportunities and challenges, this review provides valuable insights for practitioners, academics, engineers, policymakers, and other stakeholders. It offers a foundation for understanding how advanced IoT and AI techniques can enhance the efficiency, sustainability, and safety of the sanitation industry.

Purpose: The major objective of this study is to measure the impact of various attributes, such as social attraction, physical attraction, and task attraction on para-social relationships. The study also seeks to measure how the para-social relationship mediates the association between the three attributes (above-mentioned) on perceived credibility and informational influence, and consumers’ intention to purchase banking products. Study design/methodology: PLS-SEM has been used as it is believed to be most suited for the study due to the multivariate non-normality in the data, and the small sample size. Data has been collected using the 5-point Likert scale from approximately 151 respondents, who were selected using the non-random sampling method based on purposive sampling coupled with convenience-based sampling. The data was collected from January 2023 to August 2023. Findings: Largely, the findings reveal that both social and physical attractions do have a positive impact on the para-social relationship, further leading to perceived credibility and informational influence. Notably, this perceived credibility and informational influence lead to consumers’ intentions to purchase banking products, albeit with the use of artificial intelligence-based chatbots and digital assistants. Originality: This is possibly among the first-ever studies extending the para-social theory for purchasing banking products and services using artificial intelligence-based chatbots and virtual assistants.