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.

Uncontrolled economic development often leads to land degradation, a decline in ecosystem services, and negative impacts on community welfare. This study employs water yield (WY) modeling as a method for environmental management, aiming to provide a comprehensive understanding of the relationship between Land Use Land Cover (LULC), Land Use Intensity (LUI), and WY to support sustainable natural resource management in the Cisadane Watershed, Indonesia. The objectives include: (1) analyzing changes in WY for 2010, 2015, and 2021; (2) predicting WY for 2030 and 2050 under two scenarios—Business as Usual (BAU) and Protected Forest Area (PFA); (3) assessing the impacts of LULC and climate change on WY; and (4) exploring the relationship between LUI and WY. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model calculates actual and predicted WY conditions, while the Coupling Coordination Degree (CCD) analyzes the LULC-WY relationship. Results indicate that the annual WY in 2021 was 215.8 × 108 m³, reflecting a 30.42% increase from 2010. Predictions show an increasing trend in WY under both scenarios for 2030 and 2050 with different magnitudes. Rainfall contributes 88.99% more dominantly to WY than LULC. Additionally, around 50% of districts exhibited unbalanced coordination between LUI and WY in 2010 and 2020. This study reveals the importance of ESs in sustainable watershed management amidst increasing demand for natural resources due to population growth.

This article analyzes the modes of organizing the political realm of society in Aceh, especially after the signing of the Helsinki MoU in 2005 by representatives of the Indonesian government and GAM as the two parties most interested in the social organization of Acehnese society. The post-conflict social and political phenomenon in Aceh is the fragmentation between democratic and customary institutions that can be directly observed by the public through their competition in local government elections. Former GAM leaders have chosen to revive Majelis Wali Nanggroe and Gampong as customary and cultural institutions to help the government organize the lives of Acehnese people post-conflict. This paper contends that the various relationships and networks of relationships present in institutional formations are understood and explained through the different rules and frameworks that define and regulate them. Data sources were collected through in-depth interviews with several key informants, such as former GAM members, DPRA members, university rectors, local Aceh mass media editors, and socio-political observers, field observations for eighteen days (5–22 August 2018), and literature studies. This qualitative research uses a new institutionalism approach that focuses on the dynamics of the social structure of Acehnese society, which was largely controlled by GAM before the Helsinki MoU and began to loosen after the elections and even formed fragmentation among former combatants in the struggle for leadership in local government institutions. This article finds that GAM elite divisions and conflicts after the conflict for official government positions occurred due to the absence of imagination of modes of organizing society that was able to connect structurally and functionally formal and informal institutions. Pragmatically, GAM leaders and negotiators tend to maintain identity politics as a resistance movement against the central government and at the same time, they continue to run governance in a special autonomy model that gives them a lot of constitutional, institutional and symbolic freedom.

This study investigates how corruption impacts sustainability in African countries. Using public databases, the research draws on the African Development Bank’s corruption indicators and the World Bank’s financial inclusion metrics. The findings reveal that as financial inclusion increases, particularly through the use of digital financial services, perceptions of corruption decrease. However, economic growth paradoxically correlates with an increased perception of corruption due to rising consumption demands. The study concludes that promoting financial literacy, along with robust governance, is essential for combating corruption and fostering sustainable development.

The study aims to explore the role of artificial intelligence in enhancing the efficiency of public relations practitioners in Jordanian telecommunication companies. This study belongs to the category of descriptive research and adopted a survey methodology. The study surveyed (86) individuals representing the community of public relations practitioners and customer service personnel in the Jordanian telecommunication companies Zain and Orange.The study findings revealed that less experienced public relations personnel in Zain and Orange, with less than five years of experience, exhibit greater acceptance and enthusiasm for using artificial intelligence applications compared to their more experienced counterparts. The study also indicated that most public relations practitioners in Zain and Orange perceive artificial intelligence applications to have a moderate to significant contribution to achieving public relations functions and enhancing their work, reflecting technological advancement and the need to adapt to rapid changes in the business environment. Moreover, the study also discussed the limits, including that artificial intelligence can analyze large amounts of data related to the market and the audience, which provides further research and study.

This study fills a significant need in the literature by exploring the efficacy of wearable technologies as helpful aids for special needs students in Saudi Arabia. This 12-month quantitative study used a purposive sample of 150 kids representing a range of disability classifications. This study examines the effects of wearable technology, such as smartwatches and augmented reality goggles, on students’ concentration and performance in the classroom. Wearable technology offers great promise, as descriptive statistics show that the experimental group had better involvement and academic achievement. The experimental and control groups vary significantly in terms of academic performance and engagement, as shown by independent samples t-tests. Wearable technology’s distinct benefits are further shown by regression analysis, which shows a favorable correlation with academic achievement after the intervention. According to the results, wearable tech has great promise for inclusive education in Saudi Arabia. Strategic integration, teacher professional development, ongoing research, better accessibility, and wearable gadget customization are some of the suggestions. Stakeholders may use these recommendations as a road map to build a welcoming and technologically sophisticated classroom. This study adds to the growing body of knowledge on assistive technology, especially in Saudi Arabia, and has important implications for academics, politicians, and educators.

The article investigates trade flows between the Shanghai Cooperation Organization (SCO) member-states and Belarus before the upcoming Belarus’ joining the organization. The export flows of the countries are modeled using a power function based on the time data. The results of the qualitative and quantitative analysis of foreign trade between the organization and the Republic of Belarus are presented, as well as the quantitative forecast of the prospects open to Belarus in connection with its joining the organization based on three original scenarios using econometric models. The results of the study show that Belarus has certain promising sectors of foreign economic activity, which can contribute to an increase in income from trade. It was found that the integration of the country will have a positive effect on increasing the volume of trade turnover with the participating countries, while in order to maintain sustainable economic growth of the country, domestic development of production should remain a priority, as evidenced by the obtained parameter estimates for the factors. An assessment of potential economic effects can be used to make a decision on whether a country should join an international organization. In particular, based on the assessments in our study in trade with Russia the expected increase in Belarus exports upon joining the Shanghai Cooperation Organization will constitute an increase of nearly 5%, exports to Kazakhstan are expected to increase by almost 75%, and to India and China by almost 90%. In the context of reshaping of international associations and organizations, the problems and issues raised in the study become even more relevant.