This research paper aims to examine the association between financial development and environmental quality in 31 European Union (EU) countries from 2001 to 2020. This study proposed an estimation model for the study by combining regression models. The regression model has a dependent variable, carbon emissions, and five independent variables, including Urbanization (URB), Total population (POP), Gross domestic product (GDP), Credit to the private sector (FDB), and Foreign direct investment (FDI). This research used regression methods such as the Fixed Effects Model, Random Effects Model, and Feasible generalized least squaresThe findings reveal that URB, POP, and GDP positively impact carbon emissions in EU countries, whereas the FDB variable exhibits a contrary effect. The remaining variable, FDI, is not statistically significant. In response to these findings, we advocate for adopting transformative green solutions that aim to enhance the quality of health, society, and the environment, offering comprehensive strategies to address Europe’s environmental challenges and pave the way for a sustainable future.
The usage of cybersecurity is growing steadily because it is beneficial to us. When people use cybersecurity, they can easily protect their valuable data. Today, everyone is connected through the internet. It’s much easier for a thief to connect important data through cyber-attacks. Everyone needs cybersecurity to protect their precious personal data and sustainable infrastructure development in data science. However, systems protecting our data using the existing cybersecurity systems is difficult. There are different types of cybersecurity threats. It can be phishing, malware, ransomware, and so on. To prevent these attacks, people need advanced cybersecurity systems. Many software helps to prevent cyber-attacks. However, these are not able to early detect suspicious internet threat exchanges. This research used machine learning models in cybersecurity to enhance threat detection. Reducing cyberattacks internet and enhancing data protection; this system makes it possible to browse anywhere through the internet securely. The Kaggle dataset was collected to build technology to detect untrustworthy online threat exchanges early. To obtain better results and accuracy, a few pre-processing approaches were applied. Feature engineering is applied to the dataset to improve the quality of data. Ultimately, the random forest, gradient boosting, XGBoost, and Light GBM were used to achieve our goal. Random forest obtained 96% accuracy, which is the best and helpful to get a good outcome for the social development in the cybersecurity system.
Economic growth is a pressing issue facing the global community transitioning to sustainable development. Sustainable development is impossible without rapid economic growth limited by imperfect technologies and social structure. Most often, the limit of economic growth is related not so much to the amount of natural resources as to the possibilities of the environment. The atmosphere, water reservoirs, and the earth are already at the limit of their capabilities. This forces us to look for ways to develop production in combination with the economic and environmental spheres. Advanced companies are the first environmentally oriented enterprises, because reducing the amount of primary raw and other materials and energy, switching to secondary raw materials, and processing them reduces the cost of production, and, most often, brings additional profit. This study evaluates socioeconomic approaches to the development of the environmental management system. The creation of an environmentally friendly enterprise’s field of activity is not only a solution to many economic and environmental issues but also one of the ways to transition to a normally functioning market system, given the financial capabilities of enterprises and the understanding of the necessity of state sustainable development by the company management and the population.
The article is dedicated to analyzing trends in the development of startup infrastructure in Ukraine, Latvia and Georgia. The article is based on concrete data, a comprehensive analysis of statistical and qualitative data on the development of startups in Ukraine, Latvia and Georgia. This provides a reliable basis for the arguments and conclusions. General patterns of startup infrastructure development in the three countries were identified. A PEST analysis of startup infrastructure development in Ukraine, Latvia and Georgia was conducted. Thus, the authors conduct a multidisciplinary analysis that includes not only economic, but also social and technological aspects of startup ecosystems and infrastructures. Suggestions for improving the startup infrastructure in these countries were developed.
The national park with Chinese characteristics is the highest level of protection of a kind of natural protection, its establishment marks the park will implement the strictest ecological protection means. It is of great value to construct the utilization system of national park resources under the new natural protected area system in the new era to avoid the misunderstanding of “ecological protection only” and explore how to carry out the sustainable utilization of resources in the reform of national park system and mechanism. According to the analytic hierarchy process (AHP) and Delphi method, the evaluation framework, indicators, reference standards and weights of resource utilization under the national park system were determined in combination with the requirements of constructing the protected natural area system and the total value of resource ecosystem services (including harvest value, existence value and future value). Based on the application research of Bawangling zone of Hainan Tropical Rainforest National Park, the optimal resource utilization system in the future was proposed, and two optimization strategies of ecological adjustment of resource utilization system and construction of suitable resource utilization system were put forward.
This study aims to explore the perceptions of the Scholarship of Teaching and Learning (SoTL) of primary and secondary school teachers in C City, China, as well as the challenges they face in developing these abilities. Through narrative inquiry involving five current teachers, the research collected their personal experiences in the development of teaching and academic abilities, with data gathered through semi-structured interviews. The findings reveal that teachers are primarily driven by external forces, professional identity, personal growth, and the need to improve teaching quality in their efforts to enhance teaching and academic abilities. However, they also encounter challenges such as teaching pressures, time management difficulties, insufficient school support, and declining energy. To overcome these obstacles, teachers have adopted strategies such as time management, task allocation, and cognitive enhancement. The study concludes by recommending that through the combined efforts of teachers, schools, and society, a strong professional belief system should be established, and a supportive environment should be created to collaboratively promote the development of teaching and academic abilities among primary and secondary school teachers, thereby fostering their professional growth.
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