This study examines the interaction between foreign direct investment (FDI), idiosyncratic risk, sectoral GDP, economic activity, and economic growth in ASEAN countries using structural equation modeling (SEM) performed using AMOS software. The analysis uses data from the ASEAN Statistics Database 2023 to distinguish the significant direct and indirect impacts of FDI on idiosyncratic risks, sectoral GDP, economic activity and aggregate economic growth can. ASEAN, which includes ten Southeast Asian countries, has experienced rapid economic growth and increasing integration in recent decades, making it an interesting area to study these relationships. The study covers a comprehensive period to capture trends and differences among ASEAN member states. Applying SEM with AMOS allows a detailed examination of complex relationships between important economic variables. The results show a clear link between FDI inflows, idiosyncratic risks, industry GDP performance, economic activity, and overall economic growth. More specifically, FDI inflows have a notable direct influence on idiosyncratic risks, which then impact GDP growth by sector, and the level of economic activity and ultimately contribute to economic growth trends. economy more broadly in ASEAN countries. These findings highlight the importance of understanding and effectively managing the dynamics between FDI and various economic indicators to promote sustainable economic development across ASEAN. This information can inform policymakers, investors, and stakeholders in developing targeted strategies and policies that maximize the benefits of FDI while minimizing related risks to promote strong and inclusive economic growth in the region. This study highlights the multifaceted relationships in the ASEAN economic context, emphasizing the need for strategic interventions and policy frameworks to exploit the potential of foreign investment directed at ASEAN, to the Sustainable Development Goals and long-term economic prosperity in the region.

Accurate drug-drug interaction (DDI) prediction is essential to prevent adverse effects, especially with the increased use of multiple medications during the COVID-19 pandemic. Traditional machine learning methods often miss the complex relationships necessary for effective DDI prediction. This study introduces a deep learning-based classification framework to assess adverse effects from interactions between Fluvoxamine and Curcumin. Our model integrates a wide range of drug-related data (e.g., molecular structures, targets, side effects) and synthesizes them into high-level features through a specialized deep neural network (DNN). This approach significantly outperforms traditional classifiers in accuracy, precision, recall, and F1-score. Additionally, our framework enables real-time DDI monitoring, which is particularly valuable in COVID-19 patient care. The model’s success in accurately predicting adverse effects demonstrates the potential of deep learning to enhance drug safety and support personalized medicine, paving the way for safer, data-driven treatment strategies.

Starting from the ‘90s, there has been a significant increase in PPP use in the public sector in Europe, benefiting the implementation of infrastructure projects. In Italy, PPP is still much more limited than in such countries as the UK and France: the projects funded are smaller and the sectors involved are less appropriate. Based on the economic literature, European initiatives and international comparisons, the paper examines aspects of regulations that could encourage the appropriate use of PPP and considers the problems with the Italian regulations, while proposing some corrective measures. The main limitations involve: i) the absence of adequate preliminary assessments about the advantages of using PPP rather than the traditional procurement, ii) the relative lack of attention to the contract terms, iii) inadequate safeguards to ensure the bankability of the projects, and iv) limited information transparency and accessibility.

Using a Global Trade Analysis Project (GTAP) model, and China as the base for analytical comparison, this paper shows that there are significant economic benefits to China and the participating countries along all six Belt and Road Initiative (BRI) economic corridors. However, to maximize these benefits, the social and environmental risks need to be well managed. The analysis shows a clear sequencing in terms of priority corridors. Two corridors have minimal investments and immediate returns, two corridors have significant investments with huge returns, and two corridors have high investments with lower returns. Overall, the paper demonstrates that to ensure the sustainability of any BRI corridor development, there is a need to consider its costs and benefits from the economic, social and environmental perspectives.

The design of effective flood risk mitigation strategies and their subsequent implementation is crucial for sustainable development in mountain areas. The assessment of the dynamic evolution of flood risk is the pillar of any subsequent planning process that is targeted at a reduction of the expected adverse consequences of the hazard impact. This study focuses on riverbed cities, aiming to analyze flood occurrences and their influencing factors. Through an extensive literature review, five key criteria commonly associated with flood events were identified: slope height, distance from rivers, topographic index, and runoff height. Utilizing the network analysis process within Super Decision software, these factors were weighted, and a final flood risk map was generated using the simple weighted sum method. 75% of the data was used for training, and 25% of it was used for testing. Additionally, vegetation changes were assessed using Landsat imagery from 2000 and 2022 and the normalized difference vegetation index (NDVI). The focus of this research is Qirokarzin city as a case study of riverbed cities, situated in Fars province, with Qir city serving as its central hub. Key rivers in Qirokarzin city include the Qara Aghaj River, traversing the plain from north to south; the primary Mubarak Abad River, originating from the east; and the Dutulghaz River, which enters the eastern part of the plain from the southwest of Qir, contributing to plain nourishment during flood events. The innovation of this paper is that along with the objective to produce a reliable delineation of hazard zones, a functional distinction between the loading and the response system (LS and RS, respectively) is made. Results indicate the topographic index as the most influential criterion, delineating Qirokarzin city into five flood risk zones: very low, low, moderate, high, and very high. Notably, a substantial portion of Qirokarzin city (1849.8 square kilometers, 8.54% of the area) falls within high- to very-high flood risk zones. Weighting analysis reveals that the topographic humidity index and runoff height are the most influential criteria, with weights of 0.27 and 0.229, respectively. Conversely, the height criterion carries the least weight at 0.122. Notably, 46.7% of the study area exhibits high flood intensity, potentially attributed to variations in elevation and runoff height. Flood potential findings show that the middle class covers 32.3%, indicating moderate flood risk due to changes in elevation and runoff height. The low-level risk is observed sporadically from the east to the west of the study area, comprising 12.4%. Analysis of vegetation changes revealed a significant decline in forest and pasture cover despite agricultural and horticultural development, exacerbating flood susceptibility. 

This article presents a comprehensive analysis and strategic framework for enhancing social welfare in Kazakhstan through the adoption of international social security standards. This article aims to formulate scientific and practical recommendations for enhancing the legal framework governing Kazakhstan’s social security system. It posits that integrating international social protection standards is pivotal for refining national legislation and charting future developmental courses. Employing a novel methodology, this study analyzes key documents from the International Labour Organization (ILO), the United Nations, the Commonwealth of Independent States (CIS), and the Eurasian Economic Union (EAEU). It also examines efforts to assimilate these international norms into Kazakhstan’s social security laws. The investigation reveals a stagnation in the evolution of the nation’s social sector, marked by a dearth of innovative ideas and initiatives to elevate the subpar social security standards. The adoption of international social standards emerges as a catalyst for rejuvenating the national social sphere, aiming to elevate the Kazakhstani social protection system to meet global benchmarks. This research outlines the pathways for Kazakhstan’s ratification of and accession to key social protection instruments and offers expert recommendations to support this endeavor. The conclusions and recommendations developed are poised for application in legislative reforms, aiming to amend and enhance existing laws to foster a more robust and inclusive social security framework. The findings suggest that the adoption of international social security standards not only contributes to the improvement of individual lives but also fosters social cohesion and economic stability. The article concludes with tailored recommendations for Kazakhstan, highlighting the role of stakeholder engagement, phased implementation, and continuous evaluation in the successful integration of global social security norms. This research contributes to the ongoing discourse on social security reform, offering a valuable perspective for scholars, policymakers, and practitioners involved in social welfare enhancement efforts in Kazakhstan and similar contexts.