This study investigates the potential of developing a maritime tourism project within the blue economy of Pakistan and explores the factors influencing blue growth and maritime tourism. A quantitative research approach has been adopted. The research gathered primary data from diverse experts and stakeholders within the maritime sector and related industries. The study’s target population comprised on various entities involved in these sectors. A sample of around 250 individuals was selected using a convenient sampling technique. The collected data underwent analysis using the Statistical Package for the Social Sciences (SPSS) and the Partial Least Square (PLS) method. This approach was chosen to explore and understand the intricate relationships between variables in the context of the maritime industry. Structural Equation Modeling (SEM) and Confirmatory Factor Analysis (CFA) techniques were then employed to scrutinize the data further, allowing for a comprehensive examination of the interconnections among the variables identified in the study. This robust methodological approach enhances the study’s credibility and provides valuable insights into the dynamics of the maritime sector and its associated industries. The findings indicate that a balanced approach, valuing business sustainability, top management support, and enabling innovation structures positively impact blue growth. Additionally, uncertainty avoidance and promoting short-term goals have an appositive impact on the blue economy. Moreover, two potential barriers, Functional strategy, and weak competency, do not significantly affect the blue economy. This study lays the foundation for further exploration and implementation of strategies that promote sustainable growth and development in Pakistan’s blue economy. By integrating the insights gained from this study into policy and decision-making processes, stakeholders can work together to create a vibrant and sustainable maritime tourism sector that benefits both local communities and the environment.

This paper aims to investigate the impact of China’s central state-owned enterprises (SOEs) relocation policy from the capital city of Beijing on the economy and local fiscal revenue. We find that these enterprises play a critical role in implementing national strategies, promoting industrial upgrading, and enhancing the competitiveness of the industry chain. At the same time, their relocation has also dispersed the pressure of economic development in Beijing, promoted regional economic coordination and development, and increased local fiscal revenue. However, attention should be paid to the particularity and diversity of local areas in the process of policy formulation to avoid “one-size-fits-all” solutions. Therefore, when formulating corresponding policies, the central government should guide enterprises to handle relocation issues correctly and safeguard the legitimate rights and interests of employees and their families. Meanwhile, local governments should also formulate corresponding support policies to facilitate enterprise settlement. The ultimate goal is to solve problems and contradictions through development and achieve common prosperity. Therefore, we suggest that the government and enterprises work together to bring prosperity to everyone and jointly promote the sustainable development of the Chinese economy.

Background: The prevalence of anxiety among college students is a growing global concern, with a median prevalence of 32%. This study addresses the need for effective interventions within an educational policy framework to alleviate anxiety and promote mental health among college students. Objective: The study aims to evaluate the impact of breathing relaxation exercises and tactile art therapy on college students’ self-understanding and psychological well-being, providing reference information for policies and practices in mental health education. Methods: We enrolled 10 college students from X University in South Korea, dividing them into an experimental group and a control group. The experimental group underwent 10 sessions of breathing exercises and tactile art therapy, while the control group received standard psychological counseling. Pre- and post-tests assessed breathing function, self-understanding, and psychological well-being. Results: The experimental group demonstrated significant improvements in breathing function, particularly in forced vital capacity (FVC), and in psychological well-being, as measured by the Psychological Well-Being Scale (PWBS). Sub-factors such as safety, goal orientation, and self-acceptance within self-understanding, self-acceptance, positive relationships, purpose in life, and environmental mastery within psychological well-being, showed notable enhancements. In contrast, the control group did not show significant effects in terms of FVC and FEV1（p > 0.05）, and there were no statistically significant differences in the various sub-factors of self-understanding and psychological well-being. Conclusion: The study demonstrates that integrating breathing relaxation exercises and tactile art therapy into educational policy can significantly reduce anxiety and enhance the psychological well-being of college students. These findings suggest that such interventions can be effective components of a comprehensive educational policy aimed at improving student mental health.

Nigeria’s palm oil processing industry poses significant environmental pollution risks, jeopardizing the country’s ability to meet the UN’s 17 Sustainable Development Goals (SDGs) by 2030. Traditional processing methods generate palm oil mill effluent (POME), contaminating soil and shallow wells. This study investigated water samples from five locations (Edo, Akwa-Ibom, Cross River, Delta, and Imo states) with high effluent release. While some parameters met international and national standards (WHO guidelines, ASCE, NIS, and NSDWQ) others exceeded acceptable limits, detrimental to improved water quality. Results showed, pH values within acceptable ranges (6.5–8.5), high total conductivity and salinity (800–1150 µS/cm), acceptable hardness values (200–300 mg/L), nitrite concentrations (10–45 mg/L), excessive magnesium absorption (> 50 mg/L), biochemical oxygen demand (BOD) indicating significant pollution (75–290 mg/L), total dissolved solids (TDS) exceeding safe limits in four locations, total solids (TS) exceeding allowable limits for drinking water (310–845 mg/L), water quality index (WQI) values ranged from “poor” to “very poor”. POME contamination by metals like magnesium, nitrite, chloride, and sodium compromised shallow well water quality. Correlation analysis confirmed robust results, indicating strong positive correlations between conductivity and TDS (r = 0.85, p < 0.01) and pH and total hardness (r = 0.65, p < 0.05). The study emphasizes the need for environmentally friendly palm oil processing methods to mitigate pollution, ensure safe drinking water, and achieve Nigeria’s SDGs. Implementation of sustainable practices is crucial to protect public health and the environment.

This article focuses on studying how transportation connectivity affects Vietnam’s trade with Association of Southeast Asian Nations (ASEAN) countries. By using a gravity model, the article applies fixed effects (FE) and random effects (RE) to analyze panel data on trade, GDP, tariffs, border effects, and indicators. The number represents Vietnam’s transport connectivity with ASEAN countries from 2004 to 2021. Research results show that transport connectivity hurts Vietnam’s trade with other countries. ASEAN. The article proposes solutions for the Government and Vietnamese export enterprises to promote intra-ASEAN trade in the direction of increasing the added value of Vietnam’s imported and exported goods within ASEAN countries and balancing between Developing intra-ASEAN and foreign trade.

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.