The purpose of this work is to present the model of a Parabolic Trough Solar Collector (PTC) using the Finite Element Method to predict the thermal behavior of the working fluid along the collector receiver tube. The thermal efficiency is estimated based on the governing equations involved in the heat transfer processes. To validate the model results, a thermal simulation of the fluid was performed using Solidworks software. The maximum error obtained from the comparison of the modeling with the simulation was 7.6% at a flow rate of 1 L/min. According to the results obtained from the statistical errors, the method can effectively predict the fluid temperature at high flow rates. The developed model can be useful as a design tool, in the optimization of the time spent in the simulations generated by the software and in the minimization of the manufacturing costs related to Parabolic Trough Solar Collectors.

The goal of this research is to focus on the impact of HR agility on Jordanian pharmaceutical manufacturing companies’ innovative performance. The study population of the study consists of managers at different levels of pharmaceutical companies listed on the Amman Stock Exchange. Convenience sample consists of 450 questionnaires was sent. PLS-SEM was employed in this work to assess the measurement model and to verify the study theories. The findings revealed that human resource agility has a positive impact on innovative performance. The implications of the research as this analysis have shown, a variety of factors influence the agility of human resources, allowing organizations to create and implement strategies that lead to better adaptability in a rapidly changing environment. Significant ramifications could arise from this review for organizations that prioritize fostering employee confidence, refining strategies to gain a competitive edge, enhancing employee skills, and adapting to both internal and external shifts in the work environment.

This paper utilizes an advanced Network Data Envelopment Analysis (DEA) model to examine the impact of mobile payment on the efficiency of Taiwan banking industry. Inheriting the literature, we separate the banking operation process into two stages, namely profitability and marketability. Mobile payment is then considered as the core factor in the second stage. Our paper discovers network DEA model can effectively enhance the analysis of banking industry’s efficiency, and mobile payment has a notable impact on Taiwan banking industry. Regarding the profitability stage, there is only one efficient bank in 2019 and 2022, respectively. These banks also perform better in terms of “mobile payment production”. In the marketability stage, there is also only one bank in 2021 and one bank in 2022, that can reach to unique efficiency score. This indicates many banks attempt to increase earnings per share through investing in mobile payment services. However, the achievement still needs more wait. This leads to the fact that no bank can reach the ultimate overall efficiency. Within our sample, we also find that regarding promoting mobile payment services, Private Banks outperform Government Banks.

In the current context of China’s vigorous development of its high-speed rail (HSR) network to accelerate the realization of connectivity, which is the aim of the “Belt and Road” initiative, it is crucial to study how the specific opening of HSR enhances enterprise human capital investment efficiency. Using a multiple-time-point difference-in-differences (DID) regression model, we empirically study data from listed Chinese companies. An HSR opening can promote the efficiency of an enterprise’s human capital investment. We further explore the relationship between HSR and a company’s human capital investment, by considering the moderating effects of firm property rights and foreign shareholding. Our findings indicate that these factors can enhance the impact of HSR on the efficiency of firms’ investments in human capital. Finally, to ensure the reliability of our experimental findings, we employed a combination of propensity score matching and the DID methodology. The findings of this study offer empirical evidence that can inform enterprise management strategies and provide valuable insights for policymakers seeking to promote economic growth.

Preserving roads involves regularly evaluating government policy through advanced assessments using vehicles with specialized capabilities and high-resolution scanning technology. However, the cost is often not affordable due to a limited budget. Road surface surveys are highly expected to use low-cost tools and methods capable of being carried out comprehensively. This research aims to create a road damage detection application system by identifying and qualifying precisely the type of damage that occurs using a single CNN to detect objects in real time. Especially for the type of pothole, further analysis is to measure the volume or dimensions of the hole with a LiDAR smartphone. The study area is 38 province’s representative area in Indonesia. This research resulted in the iRodd (intelligent-road damage detection) for detection and classification per type of road damage in real-time object detection. Especially for the type of pothole damage, further analysis is carried out to obtain a damage volume calculation model and 3D visualization. The resulting iRodd model contributes in terms of completion (analyzing the parameters needed to be related to the road damage detection process), accuracy (precision), reliability (the level of reliability has high precision and is still within the limits of cost-effective), correct prediction (four-fifths of all positive objects that should be identified), efficient (object detection models strike a good balance between being able to recognize objects with high precision and being able to capture most objects that would otherwise be detected-high sensitivity), meanwhile, in the calculation of pothole volume, where the precision level is established according to the volume error value, comparing the derived data to the reference data with an average error of 5.35% with an RMSE value of 6.47 mm. The advanced iRodd model with LiDAR smartphone devices can present visualization and precision in efficiently calculating the volume of asphalt damage (potholes).

In the process of English learning, primary school English is an important period of enlightenment. However, teachers’ old-fashioned teaching methods and obscure teaching contents make primary school students less interested in learning English, which will affect students’ entire English learning career. Under this educational background, the education department should analyze the existing problems in English teaching methods, teaching contents and teaching concepts based on the current situation of English teaching in primary schools, aiming to improve the interest of English teaching in primary schools through effective strategies.