Mangrove forests are vital to coastal protection, biodiversity support, and climate regulation. In the Niger Delta, these ecosystems are increasingly threatened by oil spill incidents linked to intensive petroleum activities. This study investigates the extent of mangrove degradation between 1986 and 2022 in the lower Niger Delta, specifically the region between the San Bartolomeo and Imo Rivers, using remote sensing and machine learning. Landsat 5 TM (1986) and Landsat 8 OLI (2022) imagery were classified using the Support Vector Machine (SVM) algorithm. Classification accuracy was high, with overall accuracies of 98% (1986) and 99% (2022) and Kappa coefficients of 0.97 and 0.98. Healthy mangrove cover declined from 2804.37 km² (58%) to 2509.18 km² (52%), while degraded mangroves increased from 72.03 km² (1%) to 327.35 km² (7%), reflecting a 354.46% rise. Water bodies expanded by 101.17 km² (5.61%), potentially due to dredging, erosion, and sea-level rise. Built-up areas declined from 131.85 km² to 61.14 km², possibly reflecting socio-environmental displacement. Statistical analyses, including Chi-square (χ² = 1091.33, p < 0.001) and Kendall’s Tau (τ = 1, p < 0.001), showed strong correlations between oil spills and mangrove degradation. From 2012 to 2022, over 21,914 barrels of oil were spilled, with only 38% recovered. Although paired t-tests and ANOVA results indicated no statistically significant changes at broad scales, localized ecological shifts remain severe. These findings highlight the urgent need for integrated environmental policies and restoration efforts to mitigate mangrove loss and enhance sustainability in the Niger Delta.

Finding the right technique to optimize a complex problem is not an easy task. There are hundreds of methods, especially in the field of metaheuristics suitable for solving NP-hard problems. Most metaheuristic research is characterized by developing a new algorithm for a task, modifying or improving an existing technique. The overall rate of reuse of metaheuristics is small. Many problems in the field of logistics are complex and NP-hard, so metaheuristics can adequately solve them. The purpose of this paper is to promote more frequent reuse of algorithms in the field of logistics. For this, a framework is presented, where tasks are analyzed and categorized in a new way in terms of variables or based on the type of task. A lot of emphasis is placed on whether the nature of a task is discrete or continuous. Metaheuristics are also analyzed from a new approach: the focus of the study is that, based on literature, an algorithm has already effectively solved mostly discrete or continuous problems. An algorithm is not modified and adapted to a problem, but methods that provide a possible good solution for a task type are collected. A kind of reverse optimization is presented, which can help the reuse and industrial application of metaheuristics. The paper also contributes to providing proof of the difficulties in the applicability of metaheuristics. The revealed research difficulties can help improve the quality of the field and, by initiating many additional research questions, it can improve the real application of metaheuristic algorithms to specific problems. The paper helps with decision support in logistics in the selection of applied optimization methods. We tested the effectiveness of the selection method on a specific task, and it was proven that the functional structure can help the decision when choosing the appropriate algorithm.

Background: Digital transformation in the sports industry has become increasingly crucial for sustainable development, yet comprehensive empirical evidence on policy effectiveness and risk management remains limited. Purpose: This study investigates the impact of policy support and risk factors on digital transformation in sports companies, examining heterogeneous effects across different firm characteristics and regional contexts. Methods: Using panel data from 168 sports companies listed on China’s A-shares markets and the New Third Board from 2019 to 2023, this study employs multiple regression analyses, including baseline models, instrumental variables estimation, and robustness tests. The digital transformation level is measured through a composite index incorporating digital infrastructure, capability, and innovation dimensions. Results: The findings reveal that policy support significantly enhances digital transformation levels (coefficient = 0.238, p < 0.01), while financial risks demonstrate the strongest negative impact (−0.162, p < 0.01). Large firms and state-owned enterprises show stronger responses to policy support (0.312 and 0.278, respectively, p < 0.01). Regional development levels significantly moderate the effectiveness of policy implementation. Conclusions: The study provides empirical evidence for the differential effects of policy support and risk factors on digital transformation across various firm characteristics. The findings suggest the need for differentiated policy approaches considering firm size, ownership structure, and regional development levels. Implications: Policy makers should develop targeted support mechanisms addressing specific challenges faced by different types of firms, while considering regional disparities in digital transformation capabilities.

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.

This study explores the impact of digital economy engagement and digital adoption on the entrepreneurship performance of Small and Medium Enterprises (SMEs) in Malaysia, with a specific focus on the PG Mall platform. Through an analysis of SMEs’ involvement in digital activities such as e-commerce, digital marketing, and data analytics, the research identifies key factors that enhance business performance. The main objective of this paper is to examines the mediating role of government policies in supporting digital adoption and fostering a conducive environment for digital entrepreneurship. This paper employed a quantitative method to examine the impact of digital economy engagement and digital adoption on the entrepreneurship performance of Small and Medium Enterprises (SMEs) in Malaysia, with a focus on the PG Mall platform. Through data analysis, this research assessed several hypotheses related to the relationship between digital engagement, adoption, and business performance. The findings revealed that the majority of the hypotheses were supported, confirming the positive influence of digital economy engagement and digital adoption on various aspects of entrepreneurship performance. Based on these findings, this paper also proposes a conceptual framework that highlights the elements of digital economy engagement and digital adoption that contribute to SME performance. This framework serves as a valuable guideline for government policymakers, practitioners, and scholars in shaping strategies to foster digital entrepreneurship. It underscores the importance of supportive government policies, such as financial incentives and training, in facilitating the digital transformation of SMEs. By providing a structured approach to understanding the role of digital tools in enhancing business outcomes, the framework offers a foundation for future research and policy development aimed at promoting digital entrepreneurship in an evolving economic landscape.

The aim of this study is to examine the contributions of the components of employee engagement on knowledge-sharing behavior alongside possible mediating effect of management support. This study collected data from 395 respondents purposively selected from pharmaceutical organizations in Bangladesh. For input and incorporation of sample data, SPSS version 26 was used, whereas the PLS-SEM (version-4) tool was used to test the hypotheses relationships. The findings reveal significant positive effects of adaptation, devotion, and vitality on both knowledge sharing behavior and management support. Adaptation to new technologies and processes enhances employees’ ability and intention to share knowledge, facilitated by robust management support. Similarly, devotion and vitality among employees fosters a supportive environment that is conducive for knowledge exchange. Management support emerges as a critical mediator, amplifying the positive impacts of adaptation, devotion, and vitality on organizational outcomes. These findings address a critical gap in understanding the conditions that enhance knowledge-sharing behaviors in highly regulated industries and provides a valuable framework for organizations to nurture knowledge-sharing cultures that will drive innovation and resilience within emerging markets.