This paper analyzes the characteristics and influence mechanisms of financial support for China’s strategic emerging industries. Using a sample of 356 listed companies across nine major industries, we conduct an in-depth analysis of the efficiency of financial support and its influencing factors. In addition, this paper analyzes the influence mechanism of financial support for strategic emerging industries based on the relevant theory of financial support for industry development. It clarifies the internal and external influencing factors. Based on the theoretical analysis, a two-stage empirical investigation was conducted: The data of 356 listed companies in strategic emerging industries from 2010 to 2022 were selected as a sample, and the data envelopment analysis (DEA) method was applied to measure efficiency. The influencing factors were then analyzed using a Tobit regression and an intermediate effects test.

The last decades have offered new challenges to researchers worldwide through the problems our planet is facing both in the environment protection field and the need to replace fossil fuels with new environmentally friendly alternatives. Bioenergy as a form of renewable energy is an acceptable option from all points of view and biofuels due to their biological origin have the ability to satisfy the new needs of humanity. By releasing some non-polluting combustion products into the atmosphere, biofuels have already been adopted as additives in traditional liquid fuels, being intended mainly for internal combustion engines of automobiles. The current work proposes an extension of biofuels application in combustion processes specific to industrial furnaces. This technical concern is not found in the literature, except for achievements of the research team involved in this work, which has performed previous investigations. A 51.5 kW-burner was designed to operate with glycerine originating from triglycerides of plants and animals, mixed with ethanol, an alcohol produced by the chemical industry recently used as an additive in gasoline for automobile engines. Industrial oxygen was chosen as the oxidizing agent necessary for the liquid mixture combustion, allowing to obtain much higher flame temperatures compared to the usual combustion processes using air. Mixing glycerine with ethanol in 8.8 ratio allowed growing flame stability, accentuated also by creating swirl currents in the flame through the speed regime of fluids at the exit from the burner body. Results were excellent both through the flame stability and low level of polluting emissions.

Employee Engagement (EE) has become a crucial element for the success of any organization. While psychology has conducted extensive research on EE, accounting has yet to give it the attention it deserves. This systematic literature review (SLR) was conducted to explore the linkage between corporate governance (CG) practices and factors that drive employee engagement (EED) in greater detail. The review identified several key factors influencing EED: board composition, audit committees, top leadership expertise, network power, other stakeholders’ supervision, and above-board application. In particular, the study revealed that effective CG practices have positive EE consequences, such as increased staff morale, job satisfaction, and productivity, and decreased employee turnover rates. The study underlined the importance of an employee-centric culture that encourages empowerment and fosters a sense of belonging in achieving maximum business success. It suggests that companies must create a work environment that promotes EE, provides opportunities for growth and development, recognizes employee contributions, and fosters open communication and collaboration. By leveraging these insights, companies can enhance their business operations and achieve maximum success by fostering a culture of EE and empowerment. The study concludes that businesses prioritizing EE as a core value can create a sustainable competitive advantage, increase their reputation, and attract and retain top talent.

Vehicle detection stands out as a rapidly developing technology today and is further strengthened by deep learning algorithms. This technology is critical in traffic management, automated driving systems, security, urban planning, environmental impacts, transportation, and emergency response applications. Vehicle detection, which is used in many application areas such as monitoring traffic flow, assessing density, increasing security, and vehicle detection in automatic driving systems, makes an effective contribution to a wide range of areas, from urban planning to security measures. Moreover, the integration of this technology represents an important step for the development of smart cities and sustainable urban life. Deep learning models, especially algorithms such as You Only Look Once version 5 (YOLOv5) and You Only Look Once version 8 (YOLOv8), show effective vehicle detection results with satellite image data. According to the comparisons, the precision and recall values of the YOLOv5 model are 1.63% and 2.49% higher, respectively, than the YOLOv8 model. The reason for this difference is that the YOLOv8 model makes more sensitive vehicle detection than the YOLOv5. In the comparison based on the F1 score, the F1 score of YOLOv5 was measured as 0.958, while the F1 score of YOLOv8 was measured as 0.938. Ignoring sensitivity amounts, the increase in F1 score of YOLOv8 compared to YOLOv5 was found to be 0.06%.