Solar energy is a reliable and abundant resource for both heating and power generation. The current research examines how the novel class of nano-embedded Bees wax phase change materials (NEBPCMs) improves heat storage qualities. The synthetic NEBPCMs were subjected to experimental testing using, XRD, Bees wax and Al2O3 FESEM. A typical solar water heating system features a flat plate collector unit incorporating Bees Wax phase change material (NEBPCM) combined with varying concentrations of Al2O3 (0.01%, 0.015%, and 0.02%). The absorber plate surface is coated with a Nano-hybrid coating consisting of Black Paint, Al2O3, and additional Fe3O4 at a 2% concentration. Pure water is frequently used in these solar water heaters (SWH), with performance evaluations conducted using different Bees Wax and Al2O3 concentrations of NEBPCM (Bees Wax + Al2O3). The system’s efficiency is assessed across different flow rates (60, 90, and 120 kg/hr) and tilt angles (15, 30, and 45 degrees). This study aims to examine the feasibility of using PCMs to store solar energy for night time water heating, ensuring a continuous supply of hot water maximum efficiency achieved by using NEBPCM in solar water heater 52.26% at a flow rate of 120 Kg/hr, at angle of 45 degrees and Concentration 0.015%.

This study aims to explore the mediating role of perceived organizational support(POS) in the relationship between university teachers' competence and job performance. Through a questionnaire survey of 968 undergraduate university teachers in China, 879 valid questionnaires were collected. The study employed quantitative methods, constructing a university teacher competence scale comprising foundational competence, teaching competence, research competence, and innovation competence, as well as a job performance scale encompassing task performance, relationship performance, and adaptive performance. Structural equation modeling and SOBEL tests were used for data analysis. The results showed that POS exhibited different mediating effect patterns between various competence dimensions and job performance dimensions: no significant mediating effect was found in task performance; partial mediating effects were observed in relational performance and adaptive performance; and a complete mediating effect was identified between foundational competence and adaptive performance. The study provides theoretical support and practical guidance for university teachers management, emphasizing the importance of establishing a competence-based human resources management system, strengthening teachers perceptions of organizational support, and establishing diverse evaluation standards. Future research could further explore the impact of different cultural backgrounds and organizational types on mediating effects.

Fog computing (FC) has been presented as a modern distributed technology that will overcome the different issues that Cloud computing faces and provide many services. It brings computation and data storage closer to data resources such as sensors, cameras, and mobile devices. The fog computing paradigm is instrumental in scenarios where low latency, real-time processing, and high bandwidth are critical, such as in smart cities, industrial IoT, and autonomous vehicles. However, the distributed nature of fog computing introduces complexities in managing and predicting the execution time of tasks across heterogeneous devices with varying computational capabilities. Neural network models have demonstrated exceptional capability in prediction tasks because of their capacity to extract insightful patterns from data. Neural networks can capture non-linear interactions and provide precise predictions in various fields by using numerous layers of linked nodes. In addition, choosing the right inputs is essential to forecasting the correct value since neural network models rely on the data fed into the network to make predictions. The scheduler may choose the appropriate resource and schedule for practical resource usage and decreased make-span based on the expected value. In this paper, we suggest a model Neural Network model for fog computing task time execution prediction and an input assessment of the Interpretive Structural Modeling (ISM) technique. The proposed model showed a 23.9% reduction in MRE compared to other methods in the state-of-arts.

The multifaceted nature of the skills required by new-age professions, reflecting the dynamic evolution of the global workforce, is the focal point of this study. The objective was to synthesize the existing academic literature on these skills, employing a scientometric approach . This involved a comprehensive analysis of 367 articles from the merged Scopus and Web of Science databases. Science. We observed a significant increase in annual scientific output, with an increase of 87.01% over the last six years. The United States emerged as the most prolific contributor, responsible for 21.61% of total publications and receiving 34.31% of all citations. Using the Tree algorithm of Science (ToS), we identified fundamental contributions within this domain. The ToS outlined three main research streams: the convergence of gender, technology, and automation; defining elements of future work; and the dualistic impact of AI on work, seen as both a threat and an opportunity. Furthermore, our study explored the effects of automation on quality of life, the evolving meaning of work, and the emergence of new skills. A critical analysis was also conducted on how to balance technology with humanism, addressing challenges and strategies in workforce automation. This study offers a comprehensive scientometric view of new-age professions, highlighting the most important trends, challenges, and opportunities in this rapidly evolving field.

This study evaluates the effectiveness of Indonesia's defense industry policy from 2018 to 2023, focusing on PT Pindad, a pivotal state-owned defense enterprise. Using a Balanced Scorecard (BSC) framework, the study assesses PT Pindad’s performance across financial, customer, internal process, and learning and growth perspectives. The findings reveal strengths in financial stability (Current Ratio at 115.57% in 2023) and customer satisfaction, but challenges in Return on Investment (ROI), which fell from 6% in 2022 to 5.46% in 2023, signaling a need for further internal improvements. A mediation analysis using Shape-Restricted Regression indicates that Research and Development (R&D) serves as a crucial mediator, enhancing the impact of strategic alliances and technology transfer on PT Pindad’s self-reliance, with R&D showing a positive coefficient of β = 0.53 (p < 0.01). The systematic literature review complements these findings, underscoring the role of technology transfer, human capital development, and strategic partnerships as essential components for strengthening PT Pindad’s self-reliance and global competitiveness. Recommendations are made to enhance policy effectiveness by fostering robust technology transfer mechanisms, increasing investment in human capital, and expanding strategic partnerships. This research contributes to the literature on defense industry policies by providing a comprehensive evaluation framework that informs future policy decisions.