Search

This paper explores the historical context and current dynamics of the transboundary water issues between India and China. Both countries share multiple transboundary river basins, with the Brahmaputra River being one of the most significant. The importance of the Brahmaputra River to both nations goes beyond just providing resources. It has implications for national security, regional stability, and human livelihoods. However, China's upstream control over the river and its extensive dam-building projects have raised concerns in downstream India and Bangladesh about potential impacts on water availability, agriculture, and livelihoods. The river system is critical for the socioeconomic well-being of millions of people, yet the competing demands for water resources have led to geopolitical tensions. The paper highlights China's strategic use of water resources, including plans for large-scale dams, which India views as a potential threat to its water security. It also underscores the importance of a nuanced understanding of hydropolitics, emphasizing the need for human security, particularly water security, in addressing these challenges. It argues that while "water wars" are unlikely, "water tensions" are significant and must be addressed through comprehensive bilateral agreements and collaborative efforts. [ABSTRACT FROM AUTHOR]

Introduction: The emergence of artificial intelligence (AI) chat programs has opened two distinct paths, one enhancing interaction and another potentially replacing personal understanding. Ethical and legal concerns arise due to the rapid development of these programs. This paper investigates academic discussions on AI in medicine, analyzing the context, frequency, and reasons behind these conversations. Methods: The study collected data from the Web of Science database on articles containing the keyword "ChatGPT" published from January to September 2023, resulting in 786 medically related journal articles. The inclusion criteria were peer-reviewed articles in English related to medicine. Results: The United States led in publications (38.1%), followed by India (15.5%) and China (7.0%). Keywords such as "patient" (16.7%), "research" (12%), and "performance" (10.6%) were prevalent. The Cureus Journal of Medical Science (11.8%) had the most publications, followed by the Annals of Biomedical Engineering (8.3%). August 2023 had the highest number of publications (29.3%), with significant growth between February to March and April to May. Medical General Internal (21.0%) was the most common category, followed by Surgery (15.4%) and Radiology (7.9%). Discussion: The prominence of India in ChatGPT research, despite lower research funding, indicates the platform's popularity and highlights the importance of monitoring its use for potential medical misinformation. China's interest in ChatGPT research suggests a focus on Natural Language Processing (NLP) AI applications, despite public bans on the platform. Cureus' success in publishing ChatGPT articles can be attributed to its open-access, rapid publication model. The study identifies research trends in plastic surgery, radiology, and obstetric gynecology, emphasizing the need for ethical considerations and reliability assessments in the application of ChatGPT in medical practice. Conclusion: ChatGPT's presence in medical literature is growing rapidly across various specialties, but concerns related to safety, privacy, and accuracy persist. More research is needed to assess its suitability for patient care and implications for non-medical use. Skepticism and thorough review of research are essential, as current studies may face retraction as more information emerges. [ABSTRACT FROM AUTHOR]

Biofloc technology (BFT) is an aquaculture technology that uses microbial communities to produce a balanced aquatic environment for fish and crustaceans. This study evaluated the global research trends and measured the performance of researchers, organizations or research centers, countries, and funding agencies participating in BFT research in the last decade. Scientific knowledge mapping was also performed to understand the social and conceptual structure of the research publications. The study was conducted based on journal article publications indexed in the Scopus database between 2013 and 2022. The analysis showed that BFT research was increasing steadily, with a total of 911 documents published in the past 10 years. Brazil, China, and India were the three most productive countries in the field. The most productive journals were Aquaculture, Aquaculture Research, and Aquaculture International. Regarding research topics, the largest share of documents was related to bioflocs and their technologies, followed by Litopenaeus vannamei, water quality, growth performance, shrimp, Nile tilapia, Oreochromis niloticus, etc. Co-authorship network analysis revealed that the largest cluster comprised researchers from Brazil, China, and India. Moreover, the study of societal attention revealed that the BFT research needs more public attention as the research was discussed and mentioned only a few social media platforms. However, the BFT research had significant readers on Mendeley. This study provides a comprehensive overview of the current state of BFT research and the research performance of scientific actors. It can serve as a valuable reference for researchers and policymakers. [ABSTRACT FROM AUTHOR]

Background & Aims: Diabetes and related metabolic syndromes represent a significant global health challenge, with the global burden of diabetes increasing considerably since 1990. In this article, we examined the trend of publications in Endocrinology, Diabetes and Metabolism between 1996 and 2021, focusing on Asian countries. Methods: We obtained and used the data from the Scopus database from the SCImago website (https://www.scimagojr.com/), on 1 April 2023, related to the subspecialty of Endocrinology, Diabetes and Metabolism for country rankings between 1996 and 2021. We did not include any data related to other medical specialties or other fields. Results: There has been a steady rise in global publications on these subspecialties over the past decade, with the number of publications from Asian countries increasing significantly. Western Europe recorded the highest number of publications, followed by North America and Asia. The COVID-19 pandemic also contributed to a surge in publications in this field. In Asian countries, China and India have notably increased their global contribution to publications, with China emerging as the top Asian nation in 2021. Conclusion: Our findings provide valuable insights into the research output from various countries and the productivity trends in Diabetes, Endocrinology and Metabolism-related research. [ABSTRACT FROM AUTHOR]

Crop yield predictions are important for crop monitoring and agronomic management. The traditional methods for yield predictions are complicated and resource consuming. With the availability of affordable handheld imaging and computing devices, the image processing-based yield prediction methods are gaining popularity. In this work, RGB images of rice panicles are captured using DSLR camera with simple background and processed to determine the panicle area in terms of number of pixels. A machine learning-based model is developed to make predictions for rice yield. The model is trained to make predictions on unseen data. Various machine learning-based regression algorithms including decision tree, random forest, support vector machine, and convolution neural network are tested. The experiments are performed on a publically available dataset from China as well as on a self-acquired dataset in India. The results have shown that image processing and machine learning-based methods can make yield predictions satisfactorily as evident from the coefficient of determination ( R 2 ) that ranges 0.80–0.97 for different cultivars. The prediction error is determined in terms of root mean square error (RMSE) and mean absolute error (MAE). RMSE for different methods lies between 0.14 and 0.40, whereas MAE varies from 0.11 to 0.30. Among the tested algorithms, linear regression achieved the best precision with R 2 = 0.97, RMSE = 0.14, and MAE = 0.11. [ABSTRACT FROM AUTHOR]