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This paper presents a comprehensive analysis of the agriculture trade dynamic between India and China from 2002–2021. It employed the Revealed Comparative Advantage (RCA) and Revealed Symmetric Comparative Advantage (RSCA) indices and various statistical analyses to assess the trade performance and provide an enhanced comprehension of the specialization pattern. The study has selected 45 agricultural commodities, categorized into seven sections according to the HS Nomenclature 2017. The findings revealed that India boasts a more diversified export portfolio compared to China, with a more significant number of agriculture chapters demonstrating a comparative advantage. Conversely, China's export basket is more concentrated, featuring fewer chapters with a comparative advantage but higher values of RCA and RSCA. The paper also identified the prospective areas for agriculture-trade cooperation and collaboration between the two countries and put forward recommendations. This research aims to offer valuable insights for policymakers, researchers, and traders to enhance bilateral ties and mutual benefits in the agriculture sector. [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]

Rice (Oryza sativa L.) is thought to have been domesticated many times independently in China and India, and many modern cultivars are available. All rice tissues are rich in specialized metabolites (SPMs). To date, a total of 181 terpenoids, 199 phenolics, 41 alkaloids, and 26 other types of compounds have been detected in rice. Some volatile sesquiterpenoids released by rice are known to attract the natural enemies of rice herbivores, and play an indirect role in defense. Momilactone, phytocassane, and oryzalic acid are the most common diterpenoids found in rice, and are found at all growth stages. Indolamides, including serotonin, tryptamine, and N-benzoylserotonin, are the main rice alkaloids. The SPMs mainly exhibit defense functions with direct roles in resisting herbivory and pathogenic infections. In addition, phenolics are also important in indirect defense, and enhance wax deposition in leaves and promote the lignification of stems. Meanwhile, rice SPMs also have allelopathic effects and are crucial in the regulation of the relationships between different plants or between plants and microorganisms. In this study, we reviewed the various structures and functions of rice SPMs. This paper will provide useful information and methodological resources to inform the improvement of rice resistance and the promotion of the rice industry. [ABSTRACT FROM AUTHOR]

India's pharmaceutical sector has been one of the largest manufacturers of generic drugs globally. During the pandemic, most countries were dependent on imports of generic drugs from India. However, India has been relying on resources from China for Active Pharmaceutical Ingredients (APIs) which are the raw material for preparing generic drugs. We considered, in our analysis, branded product groups of Paracetamol and Amoxicillin due to their extensive use in the treatment of COVID-19. From a thorough market analysis of both the drugs, we conclude that firms have a monopoly over their brands but compete within the same product group and operate in their respective market under varying prices within certain bandwidths which resembles the feature of monopolistic competitive market. We have introduced compensating function a la Helpman (1981) in the pharmaceutical goods market with the assumption that an 'ideal product' exists among the pharmaceutical goods. Given the framework, this paper explores a general equilibrium model set in a monopolistic competitive product market for branded drugs. We concluded through our propositions that expanding the pharmaceutical sector will increase the employment of unskilled labor under no capacity constraint. We will observe an increase in wages of unskilled labor only under full employment conditions wherein we would observe that the expansion of pharmaceutical good will increase wages in the unskilled labor market. However we obtain an intriguing result wherein we obtain that despite instances of limiting trade dependence on China through implementation of policies like 'Aatmanirbhar Bharat' and 'profit linked incentive schemes', yet to maintain the status quo in the global market for generic drugs, India's dependence on China would increase, owing to API imports due to the pandemic crisis. While India can grab the opportunity in the form of increased demand for pharmaceutical goods to increase the employment level of the economy but this improvement in welfare is also dependent on the degree of dependency of API India has on China. The Indian government has recognized the same through the incorporation of 'Covid-Suraksha' and PLI schemes to minimize import dependency, and accelerate the development of APIs and the production of indigenous drugs. [ABSTRACT FROM AUTHOR]

This research paper investigates the evolving defense cooperation between India and Japan in the context of the strategic landscape in the Indo-Pacific region, particularly considering China's rise. The existing literature recognizes China's increasing influence as a significant factor in India-Japanese security cooperation, but tends to overlook the dynamics behind India's shifting stance. The study reveals that India initially hesitated to actively engage in anti-China security cooperation with Japan until the mid-2010s, but later adopted a more proactive partnership. An analysis of policy documents, political speeches, and government records attributes India's initial reluctance to its commitment to non-alignment and strategic autonomy, its desire to balance relations with both China and Japan, and its domestic political priorities favoring economic development over military expansion or strategic alliances. However, growing concerns over China's assertiveness, military modernization, a change in political leadership, and the Quad's development as a regional security platform have prompted India's attitude shift. The research's recommendations not only offer a roadmap for India, Japan, and other Indo-Pacific countries with deep economic ties to China, but also help combat China's military threats to contribute to regional stability and security, address common challenges, and foster a peaceful and prosperous Indo-Pacific region. [ABSTRACT FROM AUTHOR]

In the conditions of the spread of globalization processes, growing interdependence, and interconnectedness of countries, a significant intensification of the academic society efforts to ensure national energy security and independence is necessary. The purpose of the paper is to provide a systematic review of the scientific environment aimed at analysing the contents and features of scientific publications dealing with new trends and patterns in sustainable energy consumption. In order to create a semantic and definition basis and research the main trends of scientific publications on the subject of developing energy efficiency and sustainable consumption, the paper carried out a bibliometric analysis concerning the categories «energy efficient» and «energy consumption» using the Scopus and VOSviewer tools. The main question is, what are the main scientific and research trends and patterns in the field of energy efficiency and sustainable consumption? For this purpose, the quantity and quality tendencies of the scientific articles which are studying issues connected with energy efficiency and sustainable consumer behaviour were determined. A sample of more than 24000 scientific publications on this issue was generated from publications indexed by the Scopus database. The study period covers 2001-2021. On the global level, the analysed investigated area is represented by the countries: China, the USA, and India. VOS viewer tools were used to systemize 5 clusters of scientific articles that analysed sustainable energy consumption from different points of view. Identification of regularities in the developing of scientific approaches to energy-efficient consumption and developing sustainable energy sector was carried out using bibliometric analysis, which has made it possible to describe the dominant retrospective evolutionary and temporal tendencies in the development of this theory concerning the concepts of sustainable development, environmental management, and development of renewables. As a result, one of the most significant trends is a green brand and tendencies connected with developing green marketing and green consumer awareness. [ABSTRACT FROM AUTHOR]

• Study analyzes 1374 papers on sensitivity analysis in Scopus. • RStudio, CiteSpace, and VOSviewer are used. • China has most articles published; India leads in international cooperation. • Top three cited journals: J. Clean. Prod., Expert Syst. Appl., and Comput. Ind. Eng. • Most cited authors are Pamučar D, Kahraman C, and Zavadskas EK. In the present era, the implementation of scientifically grounded Multi-Criteria Decision Making (MCDM) has emerged as a pivotal solution to diverse decision-making challenges across various domains. Although a substantial body of exploratory, conceptual, and experimental studies exists, only 9.457% studies have incorporated sensitivity analyses to assess the robustness of MCDM methods. An exhaustive scientific exploration of sensitivity analysis within the scope of MCDM is thus lacking. This research aims to address this gap through Bibliometric Analysis while examining 1374 articles published between January 2000 and March 2023 from the Scopus database. Using RStudio (Biblioshiny), CiteSpace, and VOSviewer software, the study constructs a visual representation of the most prolific countries, institutions, and authors. Impressively, China takes the lead in article publications, while India excels in international collaboration. "An extended TODIM multi-criteria group decision-making method for green supplier selection in an interval type-2 fuzzy environment," featured in the Journal of Environmental Management, emerges as the most cited paper with a total citation of 455. The study also identifies the top three most cited journals, namely "Journal of Cleaner Production," "Expert Systems With Applications," and "Computers and Industrial Engineering." "North China Electric Power University" is the leading institute with the highest research outputs. "Pamučar D" is the most cited author, with 2594 citations and 39 articles, followed by "Kahraman C" and "Zavadskas EK. This study sheds light on trends in scientific developments and collaborations, providing a model for the application of sensitivity analysis in MCDM research and highlighting global trends. An understanding of the current state of sensitivity analysis research can assist researchers working in the entire domain of MCDM. Additionally, the visualization provides prescriptive data for future work and applications related to sensitivity analysis. [ABSTRACT FROM AUTHOR]

Diabetes mellitus is the main cause of diabetic retinopathy, the most common cause of blindness worldwide. In order to slow down or prevent vision loss and degeneration, early detection and treatment are essential. For the purpose of detecting and classifying diabetic retinopathy on fundus retina images, numerous artificial intelligence-based algorithms have been put forth by the scientific community. Due to its real-time relevance to everyone's lives, smart healthcare is attracting a lot of interest. With the convergence of IoT, this attention has increased. The leading cause of blindness among persons in their working years is diabetic eye disease. Millions of people live in the most populous Asian nations, including China and India, and the number of diabetics among them is on the rise. To provide medical screening and diagnosis for this rising population of diabetes patients, skilled clinicians faced significant challenges. Our objective is to use deep learning techniques to automatically detect blind spots in eyes and determine how serious they may be. We suggest an enhanced convolutional neural network (ECNN) utilizing a genetic algorithm in this paper. The ECNN technique's accuracy results are compared to those of existing approaches like the K-nearest neighbor approach, convolutional neural network, and support vector machine with the genetic algorithm. [ABSTRACT FROM AUTHOR]

Applying artificial intelligence in education is relevant to addressing the current educational crises. Many available solutions apply Convolutional Neural Networks (CNNs) to help improve educational outcomes. Therefore, a series of works have been developed integrating techniques in different educational contexts, for instance, in online teaching practices. Given the various studies and the relevance of CNNs for educational applications, this paper presents a systematic literature review to discuss the state-of-the-art. We reviewed 133 papers from the IEEE Xplore, ACM Digital Library, and Scopus databases. Based on our revision, we discuss characteristics of studies such as publication venues, educational context, datasets, types of CNNs models, and performance of models. We evidence that the literature regarding CNNs still misses more studies discussing educational problems faced by Global South students, considering both teaching and learning perspectives. Such a population cannot be neglected during experiments due to specific educational weaknesses (for example, basic skills) demanding personalized solutions. • A systematic literature review of 133 published papers. • China covered most publications, followed by India. • There is a research gap regarding using CNNs in some regions of the Global South. • The main educational context with CNN applications is students' performance. [ABSTRACT FROM AUTHOR]

China's hegemony in global fish production remains unquestioned. This paper tries to analyze the trend in the production of fish production in India and China giving emphasis to aquaculture fish production. In aqua production in the 2000s, India appears to have made a turnaround compared to the position of China. In the 2010s, India registered a growth rate of 78 percent almost the same as in the 2000s while China's decadal growth rate went down to a little over 50 percent. The variation difference in the growth trend of total fisheries production in India has been much more pronounced compared to that of China. The difference in variation of the growth has also been discernible in the Aquaculture production as well. While China's long-term growth has been steadier and steeper during the period under the study, India has shown relatively much-pronounced volatility, particularly in the second half of the 1990s and the first half of the 2000s. But in the later part of the 2010s, the volatility in the growth trend in respect of aqua production in India seems to have disappeared. [ABSTRACT FROM AUTHOR]

This paper re-examines the relationships between night-time light (NTL) and gross domestic product (GDP), population, road networks, and carbon emissions in China and India. Two treatments are carried out to those factors and NTL, which include simple summation in each administrative region (total data), and summation normalized by region area (density data). A series of univariate regression and multiple regression experiments are conducted in different countries and at different scales, in order to find the changes in the relationship between NTL and every parameter in different situations. Several statistical metrics, such as R2, Mean Relative Error (MRE), multiple regression weight coefficient, and Pearson's correlation coefficient are given special attention. We found that GDP, as a comprehensive indicator, is more representative of NTL when the administrative region is relatively comprehensive or highly developed. However, when these regions are unbalanced or undeveloped, the representation of GDP becomes weak and other factors can have a more important influence on the multiple regression. Differences in the relationship between NTL and GDP in China and India can also be reflected in some other factors. In many cases, regression after normalization with the administrative area has a higher R2 value than the total regression. But it is highly influenced by a few highly developed regions like Beijing in China or Chandigarh in India. After the scale of the administrative region becomes fragmented, it is necessary to adjust the model to make the regression more meaningful. The relationship between NTL and carbon emissions shows obvious difference between China and India, and among provinces and counties in China, which may be caused by the different electric power generation and transmission in China and India. From these results, we can know how the NTL is reflected by GDP and other factors in different situations, and then we can make some adjustments. [ABSTRACT FROM AUTHOR]

Cold-blooded Corona was infecting people severely and was causing death tolls across the whole world. Medical professionals did not have any full proof drug to treat pandemic with certainty. In this scenario, the curative modern treatments and drugs were explorative, empirical and trail- based. The Russian and the other vaccines have to prove the efficacy; however, it is a virtue in disguise in the way traditional Chinese medicines, herbs, Indian traditional systems of Ayurveda and Yoga have been making an impact in preventing the Covid pandemic. The integrative medical ethics using traditional treatments and modern drugs have been mitigating the severity of the Covid-19 in both India and China. The main objective of this paper is to research covid-19 impact on public health from the viewpoint of traditional medicines, integrative yoga philosophy and sustainability. It is to offer an integrative health perspective for the management of Covid pandemic and post-pandemic challenges. Keywords Integrative Medical Ethics, COVID-Pandemic, New-Normal, Social-Health, Holistic Health Management, Ayurveda and Yoga, Holistic, Environment and SDG's [ABSTRACT FROM AUTHOR]

Since the first fully homomorphic encryption scheme was published in 2009, many papers have been published on fully homomorphic encryption and its applications. Machine learning is one of the most interesting applications and has drawn a lot of attention from researchers. To better represent and understand the field of Homomorphic Encryption in Machine Learning (HEML), this paper utilizes automated citation and topic analysis to characterize the HEML research literature over the years and provide the bibliometrics assessments for this burgeoning field. This is conducted by using a bibliometric statistical analysis approach. We make use of web-based literature databases and automated tools to present the development of HEML. This allows us to target several popular topics for in-depth discussion. To achieve these goals, we have chosen the well-established Scopus literature database and analyzed them through keyword counts and Scopus relevance searches. The results show a relative increase in the number of papers published each year that involve both homomorphic cryptography and machine learning. Using text mining of articles titles, we have found that cloud computing is a popular topic in this field, which also includes neural networks, big data, and the Internet of Things. The analysis results show that China, the US, and India have generated almost half of all the research contributions in HEML. The citation statistics, keyword statistics, and topic analyses give us a quick overview of the development of the field, which can be of great help to new researchers. It is also possible to apply our methodology to other research areas, and we see great value in this approach. [ABSTRACT FROM AUTHOR]

Impact of heavy metal (HM) pollution and its understanding on environment as well as human beings has grown a lot during the last few decades. The goal of this study is to create a scientometric study on heavy metal contamination, in the period 1989 to 2020, in order to provide futuristic goals for the new researchers on wastewater treatment. For this, a search was conducted in the Web of Science (WoS) and Scopus databases, related to heavy metal pollution. Totally, 37,154 records were collected during the study period from 1989 to 2020. The findings revealed that China, the United States, and India has most referenced papers across a wide range of trans disciplinary issues such as toxicity, technology, and pollution. As a result, this study concludes that more research on various treatment methods is required in order to obtain high-quality water for consumption and routine activities, with the incorporation of various treatment tasks poses various challenges for the upcoming future studies. [Display omitted] • A bibliometric study is performed an heavy metal pollution between 1989 and 2020. • 37,154 records were critically analyzed to extract the bibliographic maps. • China, USA and India are the leading countries in heavy metal pollution research. • Advanced oxidation, coagulation-flocculation, adsorption, and membrane filtering technologies were focussed. [ABSTRACT FROM AUTHOR]

Energy storage ceramics is among the most discussed topics in the field of energy research. A bibliometric analysis was carried out to evaluate energy storage ceramic publications between 2000 and 2020, based on the Web of Science (WOS) databases. This paper presents a detailed overview of energy storage ceramics research from aspects of document types, paper citations, h-indices, publish time, publications, institutions, countries/regions, research areas, highly cited papers, and keywords. A total of 3177 publications were identified after retrieval in WOS. The results show that China takes the leading position in this research field, followed by the USA and India. Xi An Jiao Tong Univ has the most publications, with the highest h-index. J.W. Zhai is the most productive author in energy storage ceramics research. Ceramics International, Journal of Materials Science-Materials in Electronics, and the Journal of Alloys and Compounds are the most productive journals in this field, and materials science—multidisciplinary is the most frequently used subject category. Keywords, highly cited papers, and the analysis of popular papers indicate that, in recent years, lead-free ceramics are prevalent, and researchers focus on fields such as the microstructure, thin films, and phase transition of ceramics. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak has led to a substantial loss of human life throughout the world and has a tremendous impact on healthcare services. Industry 4.0 technologies have established effective supply chain management towards the fulfillment of customized demands in the healthcare field. In addition, the internet of things, artificial intelligence, big data analytics, and 3D printing have been extensively used to combat the COVID-19 pandemic and assist in providing value-added services in the healthcare sector. Henceforth, this paper presents a scientometric analysis on the literature of aforementioned Industry 4.0 technologies in the context of COVID-19. It provides extensive insights into co-citation and co-occurrence analysis of high cited publications, participating countries, influential authors, prolific journals, and keywords using the CiteSpace tool. The analyses reveal that China has produced the highest research outputs, although India is the most collaborative country in this field. The current research hotspots include supply chain, 4D printing, and social distancing technologies. Furthermore, it explores emerging trends, intellectual structure of publications, research frontiers, and potential research directions for further work in the Industry 4.0 assisted healthcare domain. [Display omitted] • Industry 4.0 technologies have emerged in the healthcare domain as an area of growing interest in academia and industry discipline. • Artificial intelligence, big data analytics, internet of things and 3D printing have been extensively used to control the COVID-19 spread and assist in providing value-added services in the healthcare sector. • It explores emerging trends, intellectual structure of publications, and potential research directions for further work in the Industry 4.0 assisted healthcare domain. [ABSTRACT FROM AUTHOR]

An extraction method for deep-seated thick seam deposits by underground mining with high resource recovery has remained a great challenge for Indian mining engineers, whereas the longwall top coal caving (LTCC) method has evolved as an effective method for various geo mining conditions in China and other counties. The percentage of top coal recovery (TCR) plays a predominant role in determining the feasibility of LTCC, which relies on the First Top Coal Caving Distance (FTCD). In this paper, the critical geotechnical parameters are identified, numerically simulated, and statistically analyzed, and the FTCD for Indian geo-mining conditions is developed and validated. A financial assessment is conducted, considering 70% top coal recovery at 85% performance level, cost of production escalated by 20% and fall in coal grade by two grades. The internal rate of return (IRR) for LTCC is 30.24% as per the sensitivity analysis where it is only 18% in single pass longwall method. This study contributes to evaluating both the technical and economic feasibility of introducing LTCC in Indian geo-mining conditions. [ABSTRACT FROM AUTHOR]