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This paper precisely estimates the looming demand for hydrogen within the transportation sector, spanning 14 pivotal G20 nations from 2022 to 2050, anchored in the global vehicle hydrogen market penetration rate. Employing a robust techno-economic modeling methodology and leveraging Geographic Information System (GIS) for enriched visualization, it unveils distinct environmental dividends across three thoughtfully devised scenarios: Business- as -Usual, Moderate, and Aggressive. Findings herald India and China as pinnacles of hydrogen demand, with South Korea and Japan tailing closely. The study forecasts the energy consumption for solar hydrogen production in G20 countries to oscillate between 3.02 and 2.89 million GWh in 2022, while production costs are anticipated to range from $8.47/kg to $10.01/kg. In an assertive scenario, the paper illuminates a pathway towards achieving a significant CO 2 reduction, unmasking environmental savings of up to a staggering 48%, equivalent to 1.5 million mtCO 2 , by 2050. [Display omitted] • Hydrogen demand of G20 countries is analyzed using GIS and techno-economic models. • The projected adoption rates of hydrogen vary among the G20 countries. • Solar energy is crucial in determining each region's annual energy demand. • China, US, and India have the highest solar potential throughout the year. • The environmental analysis shows 850–1.5 million mtCO2 total emissions by 2050. [ABSTRACT FROM AUTHOR]

Urbanizing villages are erstwhile rural villages that are spatially enveloped and are characterized by their dual relation to the state, which expresses itself as an issue of citizenship; of land ownership; of governance; and building regulations. This paper transcends the current focus on villages in Southern China, by comparing village urbanization between China and India through four narratives of village extensions. Four parallel readings are offered, namely that urban villages are characterized by; shared tenure rooted in their rural past; inherited administrative boundaries that are re-imbued with new legal designations; emulation of traditional practices; and sustained modes of self-governance. [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]

• 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]

• To assess the trend of global income inequality, we must address the challenges of scarce and heterogeneous data and the diversity of opinions on what inequality means, which generates much uncertainty about the results. • This paper provides a new transparent and open-access dataset to facilitate a comprehensive analysis of global distributional changes since 1950 and their implications for inequality and overall welfare. • Inequality has unequivocally increased both between and within countries when considered in terms of dollar distances between people (absolute inequality). • When inequality is considered more as relative distances, the results are less robust. However, it can be said with a high degree of consensus that global inequality has declined since 2000, driven by strong growth in China, India, and other emerging countries, and will likely continue to do so for a few more years. • The main exceptions to the consensus on the decline in relative inequality after 2000 come from extreme sensitivity towards either end of the distribution (i.e., stagnation of the very poor or high concentration of income among the very rich). I analyze trends in global income distribution since 1950 using a new companion WIID dataset with standardized country income percentiles. I investigate the robustness of these trends with respect to key data choices, as well as the degree to which the inequality trend depends on specific distributional views (such as the use of absolute versus relative inequality, or relative emphasis at the bottom versus the top). The results show a robust increase in absolute inequality, along with a more nuanced trend in relative inequality, with a very robust decline after 2000 that was interrupted by the COVID crisis but is expected to continue at least until 2028. [ABSTRACT FROM AUTHOR]

• Reducing modifiable risk factors could prevent the onset of cognitive decline. • Physical multimorbidity–cognitive function association was mediated by depression. • Routine screening for depression in multimorbidity patient may delay dementia onset. This paper explores the role of depressive symptoms (mediator/moderator) in the association between physical multimorbidity (exposure) and cognitive function (outcome) among older adults in the three most populous middle-income countries. This study used cross-sectional data from China (2015 China Health and Retirement Longitudinal Study), India (2017/2018 Longitudinal Ageing Study in India), and Indonesia (2014/2015 Indonesian Family Life Survey), with a total sample of 73,199 respondents aged ≥ 45 years. Three domains of cognitive tests were harmonised across surveys, including time orientation, word recall, and numeracy. The four-way decomposition analysis assessed the mediation and interaction effects between exposure, mediator/moderator, and outcome, adjusted for covariates. The mean age of the respondents (in years) was slightly younger in Indonesia (56.0, SD = 8.8) than in China (59.5, SD = 9.3) and India (60.0, SD = 10.5). The proportion of male respondents was 49.3 % in China, 47.3 % in India, and 47.5 % in Indonesia. Respondents in China had the highest mean cognitive function z scores (54.7, SD = 19.9), followed by India (51.1, SD = 20.0) and Indonesia (51.0, SD = 18.4). Physical multimorbidity was associated with lower cognitive function in China and India (p < 0.0001), with 48.4 % and 40.0 % of the association explained by the mediating effect of depressive symptoms ('overall proportion due to mediation'). The association was not found in Indonesia. Cognitive functions were lower among individuals with physical multimorbidity, and depressive symptoms mainly explained the association. Addressing depressive symptoms among persons with physical multimorbidity is likely to have not only an impact on their mental health but could prevent cognitive decline. [ABSTRACT FROM AUTHOR]

Microgrid is a promising way to integrate renewable distributed generation into the electric power sector, which has received widespread attention. In this paper, a uniform capacity-constrained optimization model under different power purchase and sale price contracts is developed to explore the optimal green investment strategy for grid-connected microgrid (GCM) with three configuration types. The impact of renewable energy source endowment and incentive policy is focused when macrogrid's generators emit more pollution than GCM's non-renewable generators, such as in China and India. The results show that: (1) GCM with renewable generation can only be invested in a site with relatively abundant renewable endowment; (2) carbon tax effectively promotes the deployment of GCM with renewable generation and achieves carbon emission abatement, but excessive carbon tax cannot incentive investment in the most desired GCM type; (3) a subsidy trap is found under feed-in tariff (FIT) subsidy, which implies that the fade-out or exit of FIT subsidy is beneficial for microgrid's healthy development; (4) and the comparisons under different price contracts emphasize the importance of macrogrid providing non-discriminatory access to feed-in and feed-out services to microgrid. • Investment strategy is explored for grid-connected microgrid (GCM) with three types. • Renewable source endowment and incentive policy determine the investment for GCM. • Excessive carbon tax cannot incentive investment in the most desired renewable GCM. • The fade-out or exit of FIT subsidy is beneficial for healthy GCM deployment due to the subsidy trap. • Emphasizing the importance of macrogrid providing non-discriminatory services to GCM. [ABSTRACT FROM AUTHOR]