Protecting the environment and the Earth's natural resources is one of the most important tasks for modern societies, economies, and countries. Changes in the environment have made climate protection a key task of state policy implemented at the local, national, and international. They also have caused such negative social manifestations as environmental radicalism and terrorism. The purpose of this paper was to analyze the capacity of state institutions to prevent environmental terrorism and radicalism, particularly in the Russian context, by identifying and prioritizing key challenges and countermeasures. A mixed-methods approach was adopted, involving both qualitative and quantitative analyses. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 35 articles and reviews were selected to provide a foundation for understanding eco-terrorism trends. Additionally, an expert survey was conducted with 44 qualified participants to rank problems and recommended actions. The Kendall concordance coefficient was used to assess the consistency of expert opinions. The authors conclude that low environmental awareness and insufficient cooperation between state institutions and environmental organizations are the most significant challenges in preventing eco-terrorism. To adequately and competently prevent environmental terrorism and radicalism in society, the prevention system must be based on clear and thoughtful actions by state institutions.
This study aims to identify key strategies and tactics necessary to effectively implement national social security in a democratic Indonesia. Indonesia established the Law on the National Social Security System in 2004. However, the national social security programs did not commence until 2014. The national social security implementation has faced significant obstacles. These challenges include recurring delays, legal disputes, appeals, judicial reviews, and deviations from the original policy objectives, all threatening the long-term viability of the national social security programs. This article applies a qualitative approach by critically analyzing regulations, government reports, and publicly available data and observing open public meetings and hearings concerning implementing national social security programs. Our findings indicate that implementing national social security policies in a democratic Indonesia depends on effectively managing the dynamic processes involved in policy formulation and adoption. We propose a risk-based decision-making model to assist policymakers in mitigating policy-related risks and enhance the effectiveness of future policy agendas in social security.
The 2019 Social Enterprise Promotion Act in Thailand represents a pivotal step towards promoting social enterprises by fostering self-reliance and a fair and sustainable future for the country. Despite their significance, there is a noticeable research gap focusing on the factors that motivate Thai entrepreneurs to venture into social entrepreneurship. This study seeks to fill that gap by analyzing data from 2000 respondents in Thailand, utilizing linear regression to explore whether the awareness of the United Nations Sustainable Development Goals (SDGs), the adoption of digital technologies, extrinsic motivations, such as the overall societal view of entrepreneurs, social awareness, and perceptions of entrepreneurial capabilities influence the decision to start a social enterprise. In a gender comparison, our findings reveal that the societal context plays a crucial role for both genders, although in distinct ways: Male entrepreneurs are more influenced by individualistic extrinsic values, with motivations linked to power, respect, and societal recognition. In contrast, female entrepreneurs display a collectivistic orientation, being more likely to be inspired by intrinsic motivations, such as the success and visibility of other successful startups within their society. These findings underline the need for a gender-sensitive approach by government bodies, educational institutions, and other relevant organizations aiming to boost start-up rates of enterprises who “make a difference in the world”. Tailored support and educational programs to address the unique motivations and perspectives of male and female entrepreneurs could play a crucial role in enhancing the effectiveness of strategies designed to promote social entrepreneurship in Thailand and beyond.
Hospital performance possesses strategic significance in achieving an essential completive advantage for the public hospitals. This study aimed to examine the relationship between patient safety culture (PSC) and the performance of traditional Chinese medicine (TCM) public hospitals in Sichuan, China. To address the research purpose, this study analyses the hospital performance and Patient safety culture in traditional Chinese medicine public hospital in China. We examine the propose model by analyzing cross-sectional survey data from 194 clinical directors at 194 public traditional Chinese medicine hospitals using the Partial least squares structural equation model in Smart PLS 4.0. This study provides predictive evidence that PSC in unit management and management support can lead to better patient safety outcomes. The results revealed patient safety outcomes significantly and positively effects of patient safety related to unit management and management support on overall hospital performance (p-value: 0.000–0.003).
Since the Reform and Opening up, GDP of the cities on eastern bank of the Pearl River Estuary in Guangdong Province were higher than the eastern bank cities. Therefore, this article aims to modify the urban gravity model combines it with the entropy weight method to calculate urban quality and applies it to measure the degree of connectivity between cities over the past decades. The research aims to explore whether cities with higher economic output have a greater attraction for surrounding cities, and whether the eastern bank cities can also promote the development of the west. Through detailed data collection and analysis, this essay reveals the dynamic changes of the gravity among cities and its influence factors such as economic, transportation and urban development. The research results indicate that the strongest gravitational force between cities on the east and west banks is between Dongguan and Zhongshan, rather than between Shenzhen and cities on the west bank. This demonstrates that the connection between cities on the east and west banks is primarily constrained by geographical factors, and the geographical location of a city influences on surrounding cities significantly. In particular, Dongguan and Zhongshan play a key role in connecting the eastern and western bank of the Pearl River Estuary, rather than Shenzhen, which is traditionally considered to have the highest economic aggregate. In addition, the study also found that the COVID-19 epidemic has had a significant impact on inter-city communication, resulting in a decline in inter-city gravity in recent years.
This paper proposes a framework for highlighting the significance of cultural communication in Islamic thought, sociology, and law, areas deeply intertwined with human values. It examines how Islam presents a clear vision and noble conduct in establishing peace values and fostering principles of tolerance among all. Additionally, it explores the potential of virtual communication networks to promote a culture of peace.
This study aims at exploring the direct impact of positive mental health through 6 factors on quality of life among students with disabilities and diabetes at Saudi universities, as well as the moderating impact of physical fitness on all direct relationships among all variables of the study. Employing a quantitative research methodology, using self-administered surveys distributed to a sample of students with disabilities and diabetes at numerous Saudi Arabian universities. 468 completed surveys were received and subjected to statistical analysis, using PLS-SEM, and the study uncovered significant positive direct relationships between all positive mental health sub factors and quality of life among students. Additionally, the study revealed that physical fitness acts as a moderator in all direct relationships These findings offer valuable insights for universities, in order to develop and implement psychological support and academic adjustments policies ensuring students have access to health and wellness programs, and engage local communities in the creation of policies that can help students with disabilities.
The telecommunications services market faces essential challenges in an increasingly flexible and customer-adaptable environment. Research has highlighted that the monopolization of the spectrum by one operator reduces competition and negatively impacts users and the general dynamics of the sector. This article aims to present a proposal to predict the number of users, the level of traffic, and the operators’ income in the telecommunications market using artificial intelligence. Deep Learning (DL) is implemented through a Long-Short Term Memory (LSTM) as a prediction technique. The database used corresponds to the users, revenues, and traffic of 15 network operators obtained from the Communications Regulation Commission of the Republic of Colombia. The ability of LSTMs to handle temporal sequences, long-term dependencies, adaptability to changes, and complex data management makes them an excellent strategy for predicting and forecasting the telecom market. Various works involve LSTM and telecommunications. However, many questions remain in prediction. Various strategies can be proposed, and continued research should focus on providing cognitive engines to address further challenges. MATLAB is used for the design and subsequent implementation. The low Root Mean Squared Error (RMSE) values and the acceptable levels of Mean Absolute Percentage Error (MAPE), especially in an environment characterized by high variability in the number of users, support the conclusion that the implemented model exhibits excellent performance in terms of precision in the prediction process in both open-loop and closed-loop.
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