Focusing on Shanghai Port, this in-depth study explores how government support can make port organizations more competitive. This study shall implement qualitative analysis based on in-depth interviews with key industry and government leaders to break down the complicated actions taken by the government and how they have changed the operational and strategic skills of the port industry. Seven factors were found in our study to be the most crucial support factors: Financial, regulatory, infrastructure growth, talent, market, policy, and organizational support. In their ways, each of these groups undermines the ability of port businesses to compete. For instance, finance can make ports more competitive in aspects such as tax cuts, lower interest rates, innovation and R&D funds, financing programs, venture capital funds, and putting up R&D sites. Supporting regulations makes sure that there is fair competition and smooth operations. This is done by protecting intellectual property, keeping the market going smoothly, improving the business environment, and monitoring market regulations. Building new infrastructure, such as innovation and updated buildings, enables the smooth running of the port businesses and minimizes wastage of time; thus, more time is spent on production. Supporting talent, the market, and policy all work together to make the human capital, international cooperation, and strategic regulatory framework that a company needs to stay ahead in the long run. It is clear from organizational support how important collaborative networks are for making ports more competitive. These networks, for instance, can be of assistance in helping schools and businesses work together, create new technologies, and find ways for companies and colleges to study together. This study examines these support systems to determine where the government should step in and how the systems can be made better to make ports more competitive. In terms of practical contribution, this in-depth study helps policymakers and port workers plan for the future. This study shows a fair way for the government to support the port business, which changes with its needs and stays competitive in the world of trade.

The aim of the research is to elucidate the features of the modern model of bioecomedicine and its components as a social determinant of sustainable societal development. The theoretical-methodological basis of the work was the complex use of scientific principles and a systematic approach, which determined the choice of research methods: general scientific and interdisciplinary. The concept generalized content is substantiated and the main lines of building the bioecomedicine model are characterized from the standpoint of information-structural modeling and sustainable development. Based on the structural-logical imperative, the object, subject, basic method and main concepts of this science sphere are characterized. The bioecomedicine principal idea as a social determinant of the sustainable development within a single information space is the unification of the knowledge information field of biology, ecology and medicine based on the use of the latest achievements in information technologies. It is proven that the algorithm for achieving the bioecomedicine global goal in the form of a set of principles reflects the essence of a systemic approach to solving the tasks of sustainable societal development by ensuring the system-environmental homeostasis of humans and the ecosystems that surround them.

Objective: As the scale and importance of official development assistance (ODA) continue to grow, the need to enhance the effectiveness of ODA policies has become more critical than ever before. In this context, it is essential to systematically classify recipient countries and establish tailored ODA policies based on these classifications. The objective of this study is to identify an appropriate methodology for categorizing developing countries using specific criteria, and to apply it to actual data, providing valuable insights for donor countries in formulating future ODA policies. Design/Methodology/Approach: The data used in this study are the basic statistics on the Sustainable Development Goals (SDGs) published annually in the SDGs Report. The analytical method employed is decision tree analysis. Results: The results indicate that the 167 countries analyzed were classified into 10 distinct nodes. The study further limited the scope to the five nodes representing the most disadvantaged developing countries and suggested future directions for aid policies for each of these nodes.

In the wake of the COVID-19 pandemic, the prevalence of online education in primary education has exhibited an upward trajectory. Relative to traditional learning environments, online instruction has evolved into a pivotal pedagogical modality for contemporary students. Thus, to comprehensively comprehend the repercussions of environmental changes on students’ psychological well-being in the backdrop of prolonged online education, this study employs an innovative methodology. Founded upon three elemental feature sequences—images, acoustics, and text extracted from online learning data—the model ingeniously amalgamates these facets. The fusion methodology aims to synergistically harness information from diverse perceptual channels to capture the students’ psychological states more comprehensively and accurately. To discern emotional features, the model leverages support vector machines (SVM), exhibiting commendable proficiency in handling emotional information. Moreover, to enhance the efficacy of psychological well-being prediction, this study incorporates an attention mechanism into the traditional Convolutional Neural Network (CNN) architecture. By innovatively introducing this attention mechanism in CNN, the study observes a significant improvement in accuracy in identifying six psychological features, demonstrating the effectiveness of attention mechanisms in deep learning models. Finally, beyond model performance validation, this study delves into a profound analysis of the impact of environmental changes on students’ psychological well-being. This analysis furnishes valuable insights for formulating pertinent instructional strategies in the protracted context of online education, aiding educational institutions in better addressing the challenges posed to students’ psychological well-being in novel learning environments.

Water physico-chemical parameters, such as pH and salinity, play an important role in the larval development of Aedes aegypti, the primary vector of dengue fever. although the role of these two factors is known, the interaction between pH and salinity in various aquatic habitats is still not fully understood, especially in the context of endemic areas. this study explored how the interaction between pH and salinity affects the development of Aedes aegypti larvae in dengue hemorrhagic fever (DHF) endemic areas. this study used a pure experimental design with a posttest-only control group approach. Aedes aegypti instar iv larvae were obtained from eggs collected in north kolaka regency, a dhf endemic area. the independent variables tested were pH (6 and 8) and salinity (0.4 gr/L and 0.6 gr/L), with the control group using pH 7 and no salinity. a two-way anova test was used to evaluate the interaction between pH and salinity, followed by tukey’s hsd post-hoc test to compare treatment groups. the results showed that, independently, pH and salinity had no significant effect on larval survival. however, the interaction between the two variables had a significant effect (p < 0.001). the combination of pH 8 and salinity 0.4 gr/L resulted in the highest survival rate, while pH 6 and salinity 0.6 gr/L caused a significant decrease in larval survival. the combination of alkaline pH (pH 8) and low salinity (0.4 gr/L) is the optimal condition for Aedes aegypti larval survival. the results of this study highlight the importance of considering the interaction between pH and salinity in environmental-based vector control strategies in endemic areas. further research is needed to explore other factors, such as aquatic microbiota and environmental variations, that may affect mosquito larval development.

The purpose of this research is to deeply examine the factors that support and hinder green economic growth in South Papua, with a specific focus on increasing awareness and capacity among local communities, developing sustainable infrastructure, and adopting clean technologies. This research utilizes a case study approach to uncover the dynamics and elements supporting the development of green economy in South Papua, particularly in Merauke Regency. Through surveys, in-depth interviews, and document analysis, data were gathered from various stakeholders, including government, communities, and the private sector. Sampling was done using purposive sampling method, ensuring the inclusion of respondents relevant to the research topic to provide a holistic understanding of the factors influencing green economy in the region. The research reveals that in Merauke Regency, the understanding of the concept of green economy among the community is still limited, highlighting the need for broader education and socialization. Factors such as government support, infrastructure availability, and community participation play a key role in driving green economic growth. However, challenges such as resource limitations and differences in perceptions among stakeholders highlight the complexity in implementing green economy. Therefore, holistic and collaborative policy recommendations need to be considered to strengthen support and effectiveness of sustainable development efforts in this region.