Teachers are instrumental in advancing the cognitive and motor skills of children with autism. Despite their importance, the incorporation of both educators and robotic aids in the educational frameworks of specialized schools and centers is infrequent. Extensive research has been conducted to evaluate the impact of robotic assistance on the learning outcomes for children with autism. This study investigates the effects of the Furhat robot on the educational experiences of autistic children in schools, analyzing its utility both with and without the presence of teachers. Interviews with educators were carried out to gauge the effectiveness of implementing Furhat robots in these settings. Data collected from sessions with autistic children were analyzed using ANOVA tests, offering insights into the Furhat Social Robot’s potential as a significant tool for fostering engagement and interaction. The findings highlight the robot’s effectiveness in enhancing social interaction and engagement, thereby contributing to the ongoing discussion on how social robots can improve the developmental progress and well-being of children with autism. Moreover, this paper underlines the innovative aspects of our proposed model and its wider implications. By presenting specific quantitative outcomes, our aim is to extend the reach of our findings to a broader audience. Ultimately, this research delineates significant contributions to the understanding of social robots, such as Furhat, in improving the overall well-being and developmental trajectories of children with autism.

This study explores the determinants of control loss in eating behaviors, employing decision tree regression analysis on a sample of 558 participants. Guided by Self-Determination Theory, the findings highlight amotivation (β = 0.48, p < 0.001) and external regulation (β = 0.36, p < 0.01) as primary predictors of control loss, with introjected regulation also playing a significant role (β = 0.24, p < 0.05). Consistent with Self-Determination Theory, the results emphasize the critical role of autonomous motivation and its deficits in shaping self-regulation. Physical characteristics, such as age and weight, exhibited limited predictive power (β = 0.12, p = 0.08). The decision tree model demonstrated reliability in explaining eating behavior patterns, achieving an R² value of 0.39, with a standard deviation of 0.11. These results underline the importance of addressing motivational deficits in designing interventions aimed at improving self-regulation and promoting healthier eating behaviors.

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.

Rural tourism, which offers authentic cultural and nature-based experiences, is increasingly recognized as a vital tool for sustainable development. Ethiopia, with its rich rural landscapes and cultural heritage, holds immense potential for rural tourism, but the sector remains underdeveloped. This study assesses the facilitating conditions and challenges of rural tourism in Ethiopia using a mixed-methods approach. Results indicate that Ethiopia’s economic growth, improved rural infrastructure, large rural population, higher ethnic and religious diversity index, and 11 UNESCO World Heritage Sites provide strong foundations for rural tourism. However, significant challenges such as inadequate infrastructure, limited marketing, restricted access to financing, ethnic conflicts, environmental degradation, and insufficient stakeholder cooperation hinder its growth. To address these barriers, the study proposes a model encompassing strategic investments in infrastructure, enhancing marketing and promotion, access to finance initiatives, conflict resolution strategies, sustainable tourism practices, enhancing stakeholder coordination, and supportive policy frameworks. By employing these strategies, Ethiopia can harness the full potential of its rural tourism sector, contributing to economic development and community well-being while promoting cultural preservation and environmental sustainability. Also, the proposed model is highly applicable to other developing economies that share similar contexts. Besides, given the importance of the seven fundamental pillars of the model, it remains relevant across tourism types like coastal destinations.

The objective of this paper is to analyze the impact of infrastructure financing on economic growth in emerging markets through the application of both quantitative and qualitative research methodologies. In this study, the research will employ both primary and secondary data to investigate the impact of different structures of infrastructure financing on the performance of the economy through interviews with the stakeholders and policy documents alongside quantitative data from the World Bank and the IMF. The quantitative analysis employs the econometric models to establish the effect of infrastructure investment on the GDP growth of the selected countries, India, China, Brazil, and Nigeria. Additional secondary qualitative data obtained from interviews with policymakers and financial specialists from Brazil, India, and South Africa offer more practical information regarding the efficiency of the discussed financing approaches. This paper is therefore able to conclude that appropriate management of infrastructure investments, particularly those that involve the PPP, are central to the development of the economy. However, certain drawbacks such as the lack of regularity of data and the disparity in the effectiveness of financing instruments by the regions are pointed out. The research provides policy implications to policymakers and investors who wish to finance infrastructure in the emerging economy to enhance economic growth in the long run.

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.