Brain tumors are a primary factor causing cancer-related deaths globally, and their classification remains a significant research challenge due to the variability in tumor intensity, size, and shape, as well as the similar appearances of different tumor types. Accurate differentiation is further complicated by these factors, making diagnosis difficult even with advanced imaging techniques such as magnetic resonance imaging (MRI). Recent techniques in artificial intelligence (AI), in particular deep learning (DL), have improved the speed and accuracy of medical image analysis, but they still face challenges like overfitting and the need for large annotated datasets. This study addresses these challenges by presenting two approaches for brain tumor classification using MRI images. The first approach involves fine-tuning transfer learning cutting-edge models, including SEResNet, ConvNeXtBase, and ResNet101V2, with global average pooling 2D and dropout layers to minimize overfitting and reduce the need for extensive preprocessing. The second approach leverages the Vision Transformer (ViT), optimized with the AdamW optimizer and extensive data augmentation. Experiments on the BT-Large-4C dataset demonstrate that SEResNet achieves the highest accuracy of 97.96%, surpassing ViT’s 95.4%. These results suggest that fine-tuning and transfer learning models are more effective at addressing the challenges of overfitting and dataset limitations, ultimately outperforming the Vision Transformer and existing state-of-the-art techniques in brain tumor classification.

The global Testing, Inspection, and Certification (TIC) service market is experiencing significant growth, driven by rising demand for high-quality and safety-related TIC services across various industries. This research aims to redesign a position map and strategy for Indonesian TIC State-Owned Enterprises (SOEs) in the Red Ocean competition. This systematic literature review analyzed 17 journals. The results show that the Indonesian TIC SOEs are intensively competing in the Red Ocean competition. In designing the position map in the Red Ocean competition, the SOEs must use technology in their operational activities to implement good corporate governance, collaborative strategies, resource management, and leadership styles aligned with the organizational culture.

Indonesia, as a maritime country, has many coastal areas with fishing villages that have significant potential, especially in sociological, economic, and environmental aspects, to be developed as models for sustainable development. Indonesia, with its long-standing fishing traditions, showcases the abundant potential and traditional that could help address global challenges such as climate change, rapid urbanization, and environmental and economic issues. This study aims to develop a conceptual model for sustainable cities and communities based on local potential and Wisdom towards the establishment of a Blue Village in the fishing village of Mundu Pesisir, Cirebon, Indonesia. The urgency of this study lies in the importance of developing sustainable strategies to address these challenges in coastal towns. This study involves an interdisciplinary team, including experts in sociology, social welfare, architecture, law, economics, and information technology. Through the identification of local natural and sociocultural resources, as well as the formulation of sustainable development strategies, this study develops a conceptual Blue Village model that can be applied to other coastal villages. The method employed in this study is qualitative descriptive, involving the steps of conducting a literature review, analyzing local potential, organizing focus group discussions, conducting interviews, and finalizing the conceptual model. The study employed, a purposive sampling technique, involving 110 participants. The results of the study include the modeling of a sustainable city and community development based on local potential and Wisdom aimed at creating Blue Villages in Indonesia, and It is expected to make a significant contribution to the creation of competitive and sustainable coastal areas capable of addressing the challenges of climate change and socioeconomic dynamics in the future.

This article explores ethnomedicine or traditional medication written in palm-leaf manuscripts in Lombok, West Nusa Tenggara. Most of the manuscripts in Lombok are written on palm leaf or lontar. One genre of palm-leaf manuscripts is USADA or traditional medication. These USADA manuscripts, serving as guides for traditional healers (dukun and balian), contain valuable information on diseases, treatments, herbal remedies, and incantations. The study reveals that ethnomedicine remains a relevant and respected practice in Lombok, often considered on par with modern medicine. Many residents rely on traditional healers for healthcare, particularly for minor illnesses. The research also highlights the living nature of the manuscript tradition, with continued recitation, copying, and teaching of these texts to younger generations. However, challenges persist in preserving these manuscripts and promoting wider appreciation for this unique cultural heritage.

This study investigates the link between debt and political alignment in international relations between the People’s Republic of China (PRC) and African nations. Using recorded roll-call votes on United Nations General Assembly (UNGA) resolutions, we explore whether PRC investment in sovereign debt influences the voting behaviour of loan recipient countries. We compile voting data for African countries from 2000 to 2020 to calculate an annual voting affinity score as a proxy for political alignment. Concurrently, data on Chinese public and publicly guaranteed (PPG) loans to African governments are collected. A Two-Stage Least-Squares analysis is employed, using the ratio of Chinese PPG debt to GDP as an instrument to address endogeneity. Results reveal a negative impact of Chinese lending on African political support, while trade, foreign direct investment (FDI), and Chinese GDP positively influence political alignment. In high debt-risk African countries, interest rates have a negative impact, whereas loan maturity shows a positive effect. These findings suggest that Chinese loans, particularly under commercial terms, may have strained bilateral relations due to debt sustainability concerns. Nevertheless, the positive impacts of trade and FDI may enhance international relations, highlighting the limitations of China’s loan diplomacy in fostering long-term strategic alignment in Africa.

This study investigates the roles of government and non-governmental organizations (NGOs) in constructing permanent housing for disaster-affected communities in Cianjur Regency following the November 2022 earthquake. Employing a qualitative methodology, the research utilizes in-depth interviews and field observations involving local governments, NGOs, and disaster survivors. The findings highlight the government’s central role in policy formulation, budget allocation, and coordination of housing development, while NGOs contribute through community empowerment, logistical support, and ensuring participatory planning. Challenges in collaboration, such as differing objectives and resource constraints, underscore the need for enhanced synergy. The study concludes that effective partnerships among the government, NGOs, and the community can expedite the development of sustainable, safe housing tailored to local needs. Emphasis on community empowerment and integrated resource management enhances resilience to future disasters. Success hinges on strong coordination, proactive challenge management, and inclusive stakeholder engagement throughout the recovery process.