Search

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]

• 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]

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 and India are two major contributors to the growth of global energy demand. As energy is one central part of the geopolitics, the energy security for both countries get complicated by the political environment. The paper investigates the positions of China and India in the trading relationships with different regions of the world. The paper also examines recent events that affect the energy security of China and India. The conclusion is that during the past decade, China and India have diversified sources of energy, especially from the Middle East, though China demonstrates a higher level of diversification and occupies a less passive position in its trading relationships. Shale revolution, the US energy sanctions on Iran and Venezuela and the US-Chinese trade conflicts, can bring China, India and Russia closer to each other due to the shrinking market influence of Russia in Europe and the needs of India and China to further diversify import sources so that energy supplies will not be disrupted by political chaos. [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]

Microplastics (MPs) are non-biodegradable substances that can sustain our environment for up to a century. What is more worrying is the incapability of modern technologies to annihilate MPs from om environment. One ramification of MPs is their impact on every kind of life form on this planet, which has been discussed ahead; that is why these substances are surfacing in everyday discussions of scholars and researchers. This paper discusses the overview of the global occurrence, abundance, analysis, and remediation techniques of MPs in the environment. This paper primarily reviews the event and abundance of MPs in coastal sediments and agricultural soil of three major Asian countries, India, China, and Japan. A significant concentration of MPs has been recorded from these countries, which affirms its strong presence and subsequent environmental impacts. Concentrations such as 73,100 MPs/kg in Indian coastal sediments and 42,960 particles/kg in the agricultural soil of China is a solid testimony to prove their massive outbreak in our environment and require urgent attention towards this issue. Conclusions show that human activities, rivers, and plastic mulching on agricultural fields have majorly acted as carriers of MPs towards coastal and terrestrial soil and sediments. Later, based on recorded concentrations and gaps, future research studies are recommended in the concerned domain; a dearth of studies on MPs influencing Indian agricultural soil make a whole sector and its consumer vulnerable to the adverse effects of this emerging contaminant. [Display omitted] • Film & fibre shaped microplastics (MPs) are more abundant in India, China and Japan. • Plastic mulching is the root cause of major MPs pollution in soil and sediment. • Estuarian soil/sediment are more prone to MPs pollution than terrestrial and coastal. • FT-IR is highly used for MPs identification; mass spectrometry & microscopy are least. • MPs work as a vector for metals, PPCPs, surfactants and antibiotic resistance genes (ARGs). [ABSTRACT FROM AUTHOR]

• The co-authorship networks constructed from the bibliometric data of research published in the area of Artificial Intelligence and Machine Learning are investigated. • The dichotomous networks are highly assortative and the corresponding strength-coupled networks are highly cohesive. • The distribution profile, not for the degrees but for the weighted degrees, is smooth and well described by power-law with exponential cut-off. • Dominance of affiliations from domestic institutions of the authors with high closeness centrality is observed for highly productive cases. • This study suggests that the dominance of domestic affiliations for central authors influences and catalyses the collaborative research. Extant studies suggest that the proximity between the researchers and their structural positioning in the collaboration network may influence productivity and performance in collaboration research. In this paper, we analyze the co-authorship networks of the three countries, viz. the USA, China, and India, constructed in consecutive non-overlapping 5-year long time windows from bibliometric data of research papers published in the past decade in the rapidly evolving area of Artificial Intelligence and Machine Learning (AI&ML). Our analysis relies on the observations ensued from a comparison of the statistical properties of the evolving networks. We consider macro-level network properties which describe the global characteristics, such as degree distribution, assortativity, and large-scale cohesion etc., as well as micro-level properties associated with the actors who have assumed central positions, defining a core in the network assembly with respect to closeness centrality measure. For the analysis of the core actors, who are well connected with a large number of other actors, we consider share of their affiliations with domestic institutes. We find dominant representation of domestic affiliations of the core actors for high productivity cases, such as China in the second time window and the USA in the first and second both. Our study, therefore, suggests that the domestic affiliation of the core actors, who could access network resources more efficiently than other actors, influences and catalyzes the collaborative research. [ABSTRACT FROM AUTHOR]

Ethnopharmacological relevance Gastrodia elata Blume ( Orchidaceae ) is commonly called Tian ma in Chinese and mainly distributed in the mountainous areas of eastern Asia, such as China, Korea, Japan and India. It is an extensively used traditional Chinese herbal medicine in the clinical practice of traditional Chinese medicine, to treat headache, migraine, dizziness, epilepsy, infantile convulsion, tetany and so on. The present paper reviews the advancements in investigation of botany and ethnopharmacology, phytochemistry, pharmacology, toxicology and quality control of Gastrodia elata Blume. Finally, the possible tendency and perspective for future investigation of this plant are also put forward. Materials and methods The information on Gastrodia elata Blume was collected via piles of resources including classic books about Chinese herbal medicine, and scientific databases including Pubmed, Google Scholar, ACS, Web of science, ScienceDirect databases, CNKI and others. Plant taxonomy was validated by the databases “The Plant List”, and “Mansfeld’s Encyclopedia”. Results Over 81 compounds from this plant have been isolated and identified, phenolics and polysaccharides are generally considered as the characteristic and active constituents of Gastrodia elata Blume. Its active compounds possess wide-reaching biological activities, including sedative, hypnotic, antiepileptic, anticonvulsive, antianxietic, antidepressant, neuroprotective, antipsychotic, anti-vertigo, circulatory system modulating, anti-inflammationary, analgesic, antioxidative, memory-improving and antiaging, antivirus and antitumor effects. Conclusion Despite the publication of various papers on Gastrodia elata Blume, there is still, however, the need for definitive research and clarification of other bioactive compounds using bioactivity-guided isolation strategies, and the possible mechanism of action as well as potential synergistic or antagonistic effects of multi-component mixtures derived from Gastrodia elata Blume need to be evaluated. It is also necessary and important to do more quality control and toxicological study on human subjects in order to maintain its efficacy stable in the body and validate its safety in clinical uses. In addition, more investigations on other parts of this plant beyond the tubers are needed. Further studies on Gastrodia elata Blume will lead to the development of new drugs and therapeutics for various diseases, and how to utilize it better should be paid more attention to. [ABSTRACT FROM AUTHOR]

Access to medicines has become a major concern for countries worldwide during the COVID-19 pandemic, as pharmaceutical production and trade have been disrupted in the course of the crisis. Antibiotics are one group of medicines where worries about access have been raised. Access to the right antibiotic at the right time is important not only for curing infections of individual patients, but also for curbing antibiotic resistance globally. Reliable pharmaceutical supply is key to ensuring access to medicines. The global supply of generic medicines has over the last decades been transformed by the rise of India's pharmaceutical industry. In this paper, I trace the changing role of this industry for the global export of antibiotics, by mapping and describing changes in Indian antibiotic exports and discussing these in light of historical processes and events. The paper offers a novel approach to analyse global antibiotic trajectories by using international trade data from publicly available resources combined with a secondary literature review. I show that India's pharmaceutical industry today holds a key role as one of the world's biggest exporters of antibiotic medicines, but with an increasing dependency on China as a supplier of antibiotic ingredients. This produces both opportunities and concerns for access to antibiotics globally. • Offers a novel approach to trace antibiotic and pharmaceutical geographies. • Uses international trade data to map India's role for global antibiotics supply. • Describes that India has become one of the world's biggest exporters of antibiotics. • Shows that India is highly dependent on China for import of antibiotic ingredients. [ABSTRACT FROM AUTHOR]

China, India, and the USA are the world's biggest energy consumers and CO 2 emitters. Being the leading contributors to climate change, these economies are also at the core of environmental solutions. This paper investigates the causal relationship among solar and wind energy production, coal consumption, economic growth, and CO 2 emissions for these three countries. To do so, we use an advanced methodology in Machine Learning to verify the predictive causal linkages among variables. The Causal Direction from Dependency (D2C) algorithm set CO 2 emissions as the target variable. The obtained results were disaggregated and estimated in a supervised prediction model. The findings, confirmed by three different Machine Learning procedures, showed an interesting output. While a reduction in overall carbon emissions is predicted in China and the US (resulting from the intensive use of renewable sources of energy), India displays critical predictions of a rise in CO 2 emissions. This indicates that curbing CO 2 emissions cannot be achieved without conducting a comprehensive shift from fossil to renewable resources, although China and the U.S. present a more promising path to sustainability than India. Being an emerging renewable energy leader, India should further enhance the use of low-carbon sources in its power supply and limit its dependence on coal. • Renewable energies, coal consumption, economic growth, and CO 2 we examine. • We investigate the causal predicted relationship on China, India, and the USA. • An advanced methodology in Machine Learning is used. • India has a prediction of an increase in emissions of CO 2. • China and the U.S. present a more promising path to sustainability than India. [ABSTRACT FROM AUTHOR]

We aimed to examine the rate and characteristics of retracted articles in infectious diseases and clinical microbiology. Using the Retraction Watch Database, we conducted a cross-sectional study for retracted publications categorized as 'Infectious Disease' or 'Microbiology' until June 30 2022. We included publications for which citation information was available through the Web of Science database. Study characteristics, retraction trends and number of citations before and after the retraction year were analysed. Overall, 1004 retracted publications were included, retracted between August 1968 and June 2022. The number of retractions climbed through the years, peaking in 2020–2021. A total of 614 retractions originated from USA, China, and India, of total 183 736 PubMed publications from these countries. Overall, 378 (38%) were retracted because of errors; 182 (18%) because of plagiarism; and 142 (14%) because of falsification/fabrication. Specific reasons included 'concerns/issues about data' (158, 16%); 'duplication of image' (127, 13%); and 'unreliable results' (116, 12%). Of the 347 retractions during 2020 to June 2022, 91 (26%) were COVID-19 related. Fifty of 895 (5.6%) first authors had two retracted papers, and 14 (1.6%) had ≥2 retractions. Of 824 publications cited at least once, 466 (57%) were cited more often after retraction. Retractions of infectious diseases and clinical microbiology publications are increasing. Concerning reasons such as plagiarism, falsification/fabrication and errors are not uncommon. Nonetheless, these publications continue to be commonly cited after being retracted. [ABSTRACT FROM AUTHOR]

Aluminum demand has increased with modernization of our society. As the primary source of aluminum is bauxite ore, this has resulted in more accumulation of bauxite residue. A bauxite residue typically contains 15–25% of alumina depending on the origin of its ore and process conditions. Along with alumina, it also contains iron, titanium and rare earth elements (REEs) in considerable levels. There is still little effort for commercial use of bauxite residue with few exceptions like in cement production such as in India and China. However, high levels of soda and iron oxides in the residue can limit such applications too. For complete valorization of bauxite residue, iron content needs to be lowered by recovering it through smelting reduction followed by slag leaching for the recovery of other metals (e.g., Ti and REEs). Smelting reduction process becomes uneconomical with high alumina as it hinders efficient separation of metal and slag phases. One of the most promising options to circumvent that problem is alumina recovery before smelting to remove iron. The main focus of this paper is to give a comparative and comprehensive overview on the processes developed for aluminum recovery from bauxite residue. These processes are, namely, a second Bayer process, Pederson process, soda or soda-lime sintering, reduction alkali roasting, smelting and acid leaching, and calcification and carbonation processes. [Display omitted] [ABSTRACT FROM AUTHOR]

Many studies have suggested herbal medicines as alternatives or adjuvants to modern drugs for COVID-19. Their scientometric analyses can provide a scientific overview of this topic. Web of Science (WOS) and Scopus were searched for articles on the use of herbal medicines in COVID-19 published until 26 October 2020. Collected data were analyzed for document type, subject area, top journal, citation number, and authors' collaboration network using VOSviewer 1.6.15, ScientoPy 2.0.3, Gephi 0.9.2, and SPSS 15 statistical tools. After screening the 3185 retrieved records, 378 and 849 records, respectively from WOS and Scopus, remained for quantity analysis. Original and review articles were the two main types of papers in both databases. Top subject areas were drug and medicine, respectively in the WOS and Scopus databases. The top three productive countries in the field were China, the US, and India. The most cited article was a practice guideline in both databases. "Journal of Biomolecular Structure Dynamics" in WOS and "Chinese Traditional and Herbal Drugs" in Scopus were the top journals. Top keywords included "COVID-19″ and "Traditional Chinese Medicine". US authors had the highest collaboration with other authors. The current study provides a snapshot of the quantity and characteristics of published scholarly documents in recent months in the intersection of herbal medicines and COVID-19. Our findings help scientists to find the existing gaps, identify the active authors and scientific institutes to collaborate with and use their experience to produce new knowledge in the future. [Display omitted] • This scientometrics was propsed to show an overview of the published documents on herbal medicine therapy for COVID-19 in WOS and Scopus databases and compare their characteristics. • Quantity analysis showed original and review articles as the main types of papers, drug and medicine as top subject areas, and China as top productive country. • A practice guideline was the highest cited article "Journal of Biomolecular Structure Dynamics" and "Chinese Traditional and Herbal Drugs" were the toppest journals in WOS, and Scopus, respectively. • US authors had the highest collaboration with other authors. • The topic modeling could give an overview of issues that publications have been focused on whether it is clinical care, management, public heath, and pathogenesis. [ABSTRACT FROM AUTHOR]

Objective: This paper shall first investigate the informatics areas and applications of the four Traditional Medicine systems - Traditional Chinese Medicine (TCM), Ayurveda, Traditional Arabic and Islamic Medicine and Traditional Malay Medicine. Then, this paper shall examine the national informatics infrastructure initiatives in the four respective countries that support the Traditional Medicine systems. Challenges of implementing informatics in Traditional Medicine Systems shall also be discussed.Methods: The literature was sourced from four databases: Ebsco Host, IEEE Explore, Proquest and Google scholar. The search term used was "Traditional Medicine", "informatics", "informatics infrastructure", "traditional Chinese medicine", "Ayurveda", "traditional Arabic and Islamic medicine", and "traditional malay medicine". A combination of the search terms above was also executed to enhance the searching process. A search was also conducted in Google to identify miscellaneous books, publications, and organization websites using the same terms.Results: Amongst major advancements in TCM and Ayurveda are bioinformatics, development of Traditional Medicine databases for decision system support, data mining and image processing. Traditional Chinese Medicine differentiates itself from other Traditional Medicine systems with documented ISO Standards to support the standardization of TCM. Informatics applications in Traditional Arabic and Islamic Medicine are mostly ehealth applications that focus more on spiritual healing, Islamic obligations and prophetic traditions. Literature regarding development of health informatics to support Traditional Malay Medicine is still insufficient. Major informatics infrastructure that is common in China and India are automated insurance payment systems for Traditional Medicine treatment. National informatics infrastructure in Middle East and Malaysia mainly cater for modern medicine. Other infrastructure such as telemedicine and hospital information systems focus its implementation in modern medicine or are not implemented and strategized at a national level to support Traditional Medicine.Conclusion: Informatics may not be able to address all the emerging areas of Traditional Medicine because the concepts in Traditional Medicine system of medicine are different from modern system, though the aim may be same, i.e., to give relief to the patient. Thus, there is a need to synthesize Traditional Medicine systems and informatics with involvements from modern system of medicine. Future research works may include filling the gaps of informatics areas and integrate national informatics infrastructure with established Traditional Medicine systems. [ABSTRACT FROM AUTHOR]

For several decades the leading wind energy nations were European, while China and India were mainly the recipients of technology transfer. This paper aims to explore the role technology transfer/cooperation from Europe played in shaping firm-level wind energy technologies in China and India and to discuss whether the recent technology cooperation between the Chinese, Indian, and European wind firms challenges the classical North–South technology cooperation paradigm. The research finds that firm-level technology transfer/cooperation shaped the leading wind energy technologies in China and to a lesser extent in India. The paper also finds that several trends towards South–North technology cooperation have been observed between China, India and Europe, such as South–North flows of capital, drivers for market access, and R&D leadership, while the origins of innovation (e.g. patents) seem to remain predominantly in the global North. The paper concludes that the technology cooperation between China, India, and Europe has become more multi-faceted and increasingly Southern-led. [ABSTRACT FROM AUTHOR]

In view of the climate emergency, it is necessary to model and forecast road transport emissions for implementing more effective climate policy. This paper fills an important research gap by quantifying the challenges, barriers and remedies of achieving road transport emission reduction and air quality improvement in developing countries. It contributes to the debate on top-down and bottom-up approaches to reconcile carbon and other transport related emissions. China and India are chosen as case studies. Using various official statistics and proxy variables, we estimate and compare the road transport carbon emissions of the two countries systematically from 2009 to 2020. Insights from detailed mode-specific estimations of the bottom-up approach are valuable for targeted policies and measures. An analysis of the major components of road transport carbon emissions points to strategies of promoting electric vehicles, reducing transport demand, accelerating modal shift to low-carbon modes, and cleaner electricity to achieve climate policy. [ABSTRACT FROM AUTHOR]

Air pollution in the form of particulate matter (PM) is becoming one of the greatest current threats to human health on a global scale. This paper firstly presents a Bayesian space–time hierarch piecewise regression model (BSTHPRM) which can self-adaptively detect the transitions of local trends, accounting for spatial correlations. The spatiotemporal trends of the approximately anthropogenic PM 2.5 removed natural dust (PM 2.5_No Dust) concentrations and the corresponding population's PM 2.5_No Dust exposure (PPM 2.5 E) in the global continent from 1998 to 2016 were investigated by the presented BSTHPRM. The total areas of the high and higher PM 2.5_No Dust -polluted regions, whose spatial relative magnitude of PM 2.5_NoDust pollution to the global continental overall level was between 1.89 and 14.68, accounted for about 13.4% of the global land area, and the corresponding exposed populations accounted for 56.0% of the global total population. The spatial heterogeneity of the global PM 2.5_NoDust pollution increased generally from 1998 to 2016. The areas of hot, warm, and cold spots with increasing trends of PM 2.5_NoDust concentration initially contracted and then later expanded. The local trends of the global continental PM 2.5_NoDust concentrations and PPM 2.5 E can be parted into three changing stages, early, medium, and later stages, using the BSTHPRM. The area proportions of the regions experiencing a decreasing trend of PM 2.5_NoDust concentrations and PPM 2.5 E were greater in the medium stage than in the early and later stages. The local trends of PM 2.5_NoDust concentration and PPM 2.5 E in the two higher PM 2.5_NoDust polluted areas, northern India and eastern and southern China, increased in the early stage and then decreased in the medium stage. In the later stage (recent years), northern India displayed a stronger increasing trend; nevertheless, the follow-up decreasing trend still occurred in eastern and southern China. In the first two stages, more than half of the areas in Europe experienced a decreasing trend of PM 2.5_NoDust concentration and PPM 2.5 E; later, more than half of areas in Europe exhibited increasing trends in the later stage. North America and South America experienced a similar local trend of PPM 2.5 E to Europe. The PPM 2.5 E trend in Africa generally increased during the study period. • First presentation of a Bayesian space-time hierarchy piecewise regression model detecting self-adaptively transitions. • Firstly applies a developed Bayesian space-time model in investigating the global population's exposure to PM 2.5. • Deeply analyses the spatiotemporal trends of the global continental PM 2.5 pollution removed natural dust. • Details the spatiotemporal trends of the global population's exposure to anthropogenic PM 2.5. [ABSTRACT FROM AUTHOR]

Individuals in developing countries often engage in paid and unpaid work till late in life due to low household savings and limited welfare provisions. Yet, physical disabilities associated with aging can limit their ability to work. While work can be beneficial for economic and psychological well-being, this paper investigates whether engagement in paid and unpaid work mediates the impact of physical disabilities on quality of life for older adults. We exploit the different levels of health services and social security in rural and urban China and India to examine the effect of public provisions in the process. We use nationally representative data of individuals aged 50 and above from the World Health Organization Study on Global Ageing and Adult Health Wave 1, conducted in 2008–10 in China and in 2007–08 in India. Using a causal mediation analysis framework, we find that paid work plays a minor role in mediating the effect of physical disabilities on quality of life in all societies, and the mediated effect is smaller in urban China than in other societies. Unpaid work is beneficial only in urban China, and it does not mediate the impact of physical disabilities on quality of life elsewhere. The findings indicate that promoting productive engagement alone, without improving basic public provisions, will have limited impact on improving quality of life of the aging population in developing countries. • In developing countries, both paid and unpaid work is common out of necessity. • Older adults bear a double burden of paid and unpaid work in rural China and India. • Productive aging has limited impact on quality of life in developing countries. • Impact of productive aging on quality of life varies with public provisions. • Physical disabilities associated with aging is less consequential in urban China. [ABSTRACT FROM AUTHOR]

Highlights • There are sanukitoids and anatectic granites in the Bundelkhand Craton. • U-Pb zircon dating of a sanukitoid yielded a crystallization age of 2577 ± 16 Ma. • Sanukitoids are derived from a crustal source. • Sanukitoids and anatectic granites formed in a subduction-collision environment. Abstract In this paper, we present in situ zircon U–Pb ages as well as whole-rock elemental and Sm-Nd isotopic compositions for late Archean sanukitoids of the Bundelkhand Craton, India. The LA–ICP–MS zircon U–Pb dating results of the sanukitoids (s.l.) indicate that these rocks were emplaced at 2577 ± 16 Ma, with inherited zircon at an age of 2644 ± 25 Ma, and are coeval with high-K anatectic granites (2544–2583 Ma). The sanukitoids (s.l.) are characterized by high-alumina (15–16 wt.%), Mg# (27–50) and TiO 2 (0.31–0.87 wt.%). They have a strongly enriched signature in terms of incompatible trace elements (LREEs and LILE) pointing to a subduction-related or crustal source. The high-K anatectic granites are characterized by Al 2 O 3 (12–15 wt.%), Mg# (13–39) and TiO 2 (0.06–0.8 wt.%); they have enriched and variable concentrations of LILEs and REEs; and negative Eu anomalies (Eu/Eu* = 0.15–0.93). The whole-rock ε Nd (t) values (−3.64 to −1.66) indicate a crustal component. These isotopic and geochemical characteristics indicate that the sanukitoid plutons originated from the mixing of metasomatized mantle melts with anatectic melts and were followed by homogenization at shallow levels of emplacement, whereas the high-K anatectic granites indicate reworking of the pre-existing TTG crust during the cratonic stabilization ca. 2.5 Ga. This interpretation suggests a temporal evolution from TTG-domination through sanukitoids (s.l.) to anatectic leucogranites by an internal reworking of the continental crust, involving subduction-collision environments in the late Archean era. Such magmatic events and tectonics during the late-Archean in the Bundelkhand Craton resemble other Archean cratons, such as the Dharwar, North China, Karelian, Superior Province, Pilbara, Kaapvaal and Amazonian. [ABSTRACT FROM AUTHOR]

• We put forward a more holistic theoretical model of information seeking practices in everyday life. • We extend the context to the Global South, where there is less research on mobile platforms. • We link the variation in everyday information seeking practices to different groups. • We show the relation between information divides and social changes in China and India. • We apply a theory of digital divides in everyday information practices to the Global South contexts. The internet is becoming a major source of everyday information, yet existing research often focuses on specific information seeking contexts such as health, climate change, news, or hobbies. In this paper, we put forward a more holistic theoretical model of information seeking practices in everyday life that combines the social phenomenological perspective of everyday life information seeking practices and the domestication framework. We extend the cultural context to the Global South countries, where there is less research on "mobile first" societies centred on emerging mobile platforms. Based on extensive and mixed-methods fieldwork in rural and industrial China about everyday information seeking practices, the paper goes beyond previous research about digital divides in internet access and internet literacy. Instead, it focuses on divides in everyday information seeking practices. We argue that new divides are emerging between those with more restricted everyday internet uses and those with broader and more diverse ones. We compare everyday information practices and divides in China with those in India and show how a theory of digital divides in everyday information seeking practices can be applied beyond both countries to the Global South. Such a theory can also contribute to the design of informatisation policies. [ABSTRACT FROM AUTHOR]

COVID-19 is a buzz word nowadays. The deadly virus that started in China has spread worldwide. The fundamental principle is "if the disease can travel faster information has to travel even faster". The sequence of events reveals the upheaval need to strengthen the ability of the early warning system, risk reduction, and management of national and global risks. Digital contact tracing apps like Aarogya setu (India) and Pan-European privacy preserving proximity tracing (German) has somehow helped but they are more effective in the initial stage and less relevant in the community spread phase. Thus, there is a need to devise a Decision Support System (DSS) based on machine learning algorithms. In this paper, we have attempted to propose an Additive Utility Assumption Approach for Criterion Comparison in Multi-criterion Intelligent Decision Support system for COVID-19. The dataset of Covid-19 has been taken from government link for validating the results. In this paper, an additive utility assumption-based approach for multi-criterion decision support system (MCDSS) with an accurate prediction of identified risk factors on certain well-defined input parameters is proposed and validated empirically using the standard SEIR model approach (Susceptible, Exposed, Infected and Recovered). The results includes comparative analysis in tabular form with already existing approaches to illustrate the potential of the proposed approach including the parameters such as Precision, Recall and F-Score. Other advanced parameters such as, MCC (Matthews Correlation Coefficient), ROC (Receiver Operating Characteristics) and PRC (Precision Recall) have also been considered for validation and the graphs are illustrated using Jupyter notebook. The statistical analysis of the most affected top eight states of India is undertaken effectively using the Weka software tool and IBM Cognos software to correctly predict the outbreak of pandemic situation due to Covid-19. Finally, the article has immense potential to contribute to the COVID-19 situation and may prove to be instrumental in propelling the research interest of researchers and providing some useful insights for the current pandemic situation. • Proposing a Multi-criterion Intelligent DSS • Epidemiology modeling of data using a SEIFR Model • Our approach applies data to get trained using multiple parameters to handle and serve significant challenges existing especially in healthcare. [ABSTRACT FROM AUTHOR]

Recently, some high-skilled workers tend to escape from areas with severe air pollution. The phenomenon is more prominent in two emerging economies, China and India, and they are facing the brain drain caused by air pollution. This paper establishes a partial equilibrium model about the relationship of air pollution and the flow of technological innovative professionals (TIP), and for the first time, examines the effect of air pollution on the accumulation of technological innovative human capital based on cross-country data from China and India. We find that air pollution will reduce the stock of TIP in some regions. The estimation results show that a 1% increase in the PM 2.5 concentration of China's cities leads to an approximate 146 people decrease in the stock of TIP, while a 1% increase in the PM 10 concentration of Indian states leads to a 0.127% decrease in the stock of TIP. Further analysis of regional differences indicates that air pollution has a significant negative effect on the stock of TIP in economically developed areas of China, but has little effect on that in underdeveloped areas of China. Moreover, the results of robustness tests prove the stability of the findings in this study. This paper concludes with suggestions on how the country, local governments, enterprises, and research institutions could better deal with air pollution, attract and retain TIP, and effectively reduce brain drain. • Air pollution negatively affects the accumulation of innovative human capital. • Air pollution will reduce the stock of technological innovative professionals (TIP). • A 1% increase in PM 2.5 in China's cities decreases the stock of TIP by 146 people. • A 1% increase in PM 10 in Indian states reduces the stock of TIP by 0.127%. • TIP in economically developed areas are more sensitive to air pollution. [ABSTRACT FROM AUTHOR]

The aim of this research is to examine the link between CO 2 emissions, hydroelectricity consumption, urbanisation and real GDP in China and India during the period of 1965–2013. The long-run cointegration is investigated by the autoregressive distributed lag (ARDL) bounds testing approach, which is augmented with structural breaks. We employ the ARDL cointegration test to establish long run relationship in the variables. Furthermore, we use the ARDL to show that real GDP and urbanisation have long-run positive impact on emission, while hydroelectricity consumption exerts long-run negative impact on emission in both countries. The results support the existence of environmental Kuznets curve (EKC) hypothesis in China and India. Besides, the paper assesses the causal link between the variables by using Granger causality procedures and the results show that there is long-run bidirectional relationship between the variables in both countries. [ABSTRACT FROM AUTHOR]

• Groundwater related research papers from 1978 to 2017 were collected. • The number of published studies increased by >10% per year on average. • Institutions based in developed countries have led groundwater research output. • China and India have experienced strong growth in output in recent years. • Depletion and sustainability have increased as a percentage of groundwater studies. Long-term over-exploitation and unsustainable practices have caused severe groundwater depletion and deterioration across many regions throughout the world. This has triggered a series of negative impacts on human populations and the natural environment. To understand groundwater-related processes and explore ways to mitigate pertaining issues, large numbers of groundwater-related studies have been performed by the research community. In this study, all research papers published between 1978 and 2017 incorporating "groundwater" in the title, keywords, or abstract, were retrieved from the Web of Science Core Collection (WSCC). Of these, a total of 80,763 papers were identified as being groundwater-related publications. Our analysis revealed that groundwater research output increased significantly during this period, at average annual rate of 10.1%, exceeding the general trend for the WSCC (3.4%). Institutions based in developed countries have held predominance in publishing groundwater research, however, research output from developing countries, such as China and India, experienced much growth in recent years. Development trends were assessed among the research topics of groundwater depletion, contamination, remediation technology, and sustainable management, all of which experienced increased research output. Among sub-topics, groundwater depletion and sustainable management research have increased as a percentage of total groundwater studies, while studies of arsenic, chlorinated solvents, BTEX, bioremediation, and natural attenuation have dropped off in recent years. Additionally, as groundwater-related research output has increased rapidly, robust secondary analyses and meta -analyses are called for in order to make sense of the rapidly expanding body of groundwater research literature. Moreover, owing to the many complexities surround groundwater issues, greater interdisciplinary collaboration is also called for. [ABSTRACT FROM AUTHOR]

The aim of this paper is to test whether income inequality contributes to environmental degradation in China and India, where both countries are giving a great concern about the implications of their unsustainable energy consumption to the environment not only to themselves but also to the global environmental sustainability. By applying the bounds test approach to cointegration we found in both countries a long-run but not a statistically significant relationship between income inequality and CO 2 emissions both in the long-run and in the short-run. The robustness of our cointegration results is also ascertained by using three different long-run tests. Furthermore, applying the variance decomposition analysis to examine the dynamic causal relationship between the Gini coefficient of income distribution and CO 2 emissions, we found that income inequality was the least important factor in determining CO 2 emissions and that there was no causality running in any direction between CO 2 emissions and income inequality in both countries. Still income and energy consumption are the major determinants of CO 2 emissions in both countries. Nevertheless, even though the evidence is not statistically significant, in the case of China it indicates that reducing income inequality can have a positive impact on environmental quality, while in India redistributing income to improve environmental degradation may not be effective. [ABSTRACT FROM AUTHOR]

Since coal will be widely used in the next decades, mainly in the developing countries such as China and India, carbon capture and storage (CCS) technologies will have a key role in the containment of global warming. This paper presents a techno-economic comparison between the most promising power generation technologies for a CO 2 -free power generation in a short-term future. In particular, three different power generation technologies have been considered in their conventional (without CCS) and CO 2 -free configurations: (a) ultra supercritical (USC) pulverized coal combustion, (b) oxy-coal combustion (OCC) and (c) integrated gasification combined cycle (IGCC). Process simulation, based on Aspen Plus and Gate Cycle commercial tools, allows to calculate plant performance, including the energy penalty due to the CCS system (10.9% points for USC and 8.7% points for IGCC). In parallel, a detailed economic assessment shows that, among the commercial-ready technologies, USC could be the most convenient solution for power generation without CCS (presenting a levelized cost of electricity – LCOE – of 38.6 €/MW h, significantly lower than 43.7 €/MW h of IGCC), whereas IGCC becomes competitive for CO 2 -free systems (with a LCOE of 59.6 €/MW h, to be compared with 63.4 €/MW h of USC). Moreover, oxy-coal combustion, which is currently not mature enough for commercial-scale applications, promises to become strongly competitive for CCS applications due to its relatively low levelized cost of electricity (62.8 €/MW h). This kind of analysis typically presents strong uncertainties, due to the variability of several key parameters (e.g. fuel and CCS prices, determined by the fluctuation of the international markets, or an improvement of the technologies). Therefore, a sensitivity analysis has been done to determine the effects of these potential fluctuation or the improvement on the economic performance of the plant. [ABSTRACT FROM AUTHOR]

An airport network forms the backbone of any air transportation system. The relationships among the origins and destinations of flights result in a complex network of routes which can be complemented with information associated with the routes themselves, for instance, traffic load and distance. In this paper, we modeled the Australia's civil domestic airport infrastructure as a network and analyzed the resulting network structure and its features using complex network tool. This case study identifies and investigates complex network measures, such as the degree distribution, characteristics path length, clustering coefficient and centrality measure as well as the correlations among them to understand the topology of an airport network. This analysis of the Australian Airport Network (AAN) indicates that it has a cumulative degree distribution described by the power-law function. As it has an average path length of 2.90, it is considered to have small-world properties. It is also found that it has a clustering coefficient of 0.50 which is higher than that of a random network of the same size which indicates that the transitivity and cohesiveness of AAN is different from a random network. In contrast to the World-wide Airport Network (WAN), the AAN is found to have disassortative mixing similar to the airport networks of China and India. [ABSTRACT FROM AUTHOR]

The past decades have seen planning and implementation of built infrastructure in all over the developed and developing world growing in large scales. This has been influenced by economic and population growths, urbanization and industrialization, which in turn have put increasing stress in provision of services. The paper reviews the policy dimensions of water infrastructure development and financing in the two largest economies at present, China and India, including planning, implementation and decision-making processes. Findings indicate that main challenges for infrastructure development have been limited sources of financing, but also policies and their implementation. The high levels of investment in water infrastructure in the two countries have been impressive, mainly in China. However, they still have not necessarily addressed efficiency over the long term, supported more inclusive and higher economic growth or improve social and environmental conditions in all cases. [ABSTRACT FROM AUTHOR]

China and India accounted for two-thirds of the world׳s rise in energy use between 2000 and 2012. This paper aimed to calculate the P (population)– A (affluence)– T (technology) effects of energy use in China and India – the world׳s two most populous and largest developing countries. To this end, a combination of the IPAT method and the logarithmic mean divisia index technique, and annual time-series data on population, energy consumption, and gross domestic product during 1970–2012 are used. In China, a 12.53-fold growth of energy use emissions from 1970 to 2012 is driven by a combination of rapid growth in individual income and slow growth in population, with offset by technological advancement since 1980. The accelerating rise in energy use since 2000 is a result of accelerating growth rates in individual income and a reversal of earlier declining in energy intensity (technological advancement). Unlike China, the long-term rise in energy use exceeded the long-term rise in individual income in India. In addition, a strong trend of decline in energy intensity has not yet occurred in India. Thus, a 7.39-folds growth of Indian energy use for 1970–2012 was a result of relatively rapid increase in population and relatively slow increase in income, without effective offset by technological advancement. It suggests that market-oriented economic and energy reforms need to send the correct price signal to promote energy-efficient technologies thus improving energy efficiency, which is the key to a sustainable energy future in China and India. [ABSTRACT FROM AUTHOR]

The age of the giant Uragen sandstone-hosted Pb-Zn deposit in the western margin of the Tarim Basin in Northwest China has long been questioned due to the general paucity of minerals unequivocally linked to Pb-Zn deposition that can be precisely dated using conventional radiogenic isotopic techniques. This paper describes the petrographic characteristics of Pb-Zn ores and presents the results of in situ calcite U–Pb analysis using laser ablation sector field inductively coupled plasma mass spectrometry (LA-ICP-MS) for this deposit. Calcite from the early, main and late ore-forming stages yielded low intercept ages of 11.80 ± 0.4 Ma, 10.9 ± 0.3 Ma and 10.6 ± 0.2 Ma, respectively, which constrain the Uragen Pb-Zn mineralization to the Late Miocene. Combined with the existing isotopic ages in the region, these new ages lead us to propose that the Uragen deposit formed during two hydrothermal episodes. The first refers to the oil-gas migration that occurred during the Middle Eocene to Early Miocene, which may be associated with the India–Eurasia collision and subsequent activity of the Main Pamir Thrust. The second refers to the Pb-Zn mineralization that occurred in the Late Miocene, which may be associated with the activity of the foreland thrust fault belt of South Tianshan and the Pamir Frontal Thrust (PFT). This study demonstrates the potential of using LA-ICP–MS U–Pb dating on calcite to constrain the ages of sandstone-hosted Pb-Zn deposits. [ABSTRACT FROM AUTHOR]

This paper assesses comparable urban transport scenarios for China and India. The assessment methodology uses AIM/End-use model with a detailed characterization of technologies to analyze two scenarios for India and China till the year 2050. The first scenario assumes continuation and enhancement, in both countries, of policies under a typical business-as-usual dynamics, like constructing metros, implementing national fuel economy standards, promoting alternate fuel vehicles and implementing national air quality standards. The alternative, low carbon scenario assumes application, in both countries, of globally envisaged measures like fuel economy standards as well as imposition of carbon price derived from a global integrated assessment modeling exercise aiming to achieve global 2 °C temperature stabilization target. The modeling results for both countries show that decarbonizing transport sector shall need a wide array of measures including fuel economy, low carbon fuel mix including low carbon electricity supply. The comparison of China and India results provides important insights and lessons from their similarities and differences in the choice of urban transport options. India can benefit from China’s experiences as it lags China in urbanization and income. Modeling assessments show that both nations can contribute to, as well as benefit by aligning their transport plans with global climate stabilization regime. [ABSTRACT FROM AUTHOR]

Renewable energy has a critical role in limiting the greenhouse gas (GHG) emissions. This paper assesses the implication of aligning renewable energy deployment target with national emission reduction target for mitigation cost. The assessment methodology uses Asia-Pacific Integrated Assessment/computable general equilibrium (AIM/CGE) model to determine the mitigation cost in terms of GDP and welfare loss under alternative renewable targets in different climate-constrained scenarios. A range of country-specific emission constraints is taken to address the uncertainties related to global emission pathway and emission entitlement scheme. Comparative results show that China needs to increase its share of non-fossil fuel significantly in the primary energy mix to achieve the stringent emission reduction target compared to India. The mitigation cost in terms of economic and welfare loss can be reduced by increasing the penetration of the renewable energy to achieve the same emission reduction target. The modeling results show that coordinated national climate and renewable energy policies help to achieve the GHG emission reduction target in an efficient and cost-effective manner. [ABSTRACT FROM AUTHOR]

Global competition for crude oil has increased in the past decade with the entry of industrializing nations such as China and India. Yet we still do not know much about the spatial structure of crude oil commodity trade and its evolution over time. In this paper, we apply complex network analysis to examine the geography of global crude oil flows and its evolution based on the United Nations commodity trade database from 1988 to 2013. Attention is given to the geo-visualization of the networks that trace the rise and decline of oil hubs. The results show that world crude oil is characterized by network characteristics that capture both small world and flat world properties. [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]

• The IUSS in the B&R areas from 1992 to 2019 at a 1 km resolution was estimated. • Significant differences in the development of B&R in the north and south occurred. • The spatial autocorrelation of IUSS in the B&R area gradually solidified. • Wealth level is the main driving force for the evolution of IUSS. • China and India are potential hotspots for steel material flow in the future. Urban development has advanced the accumulation of steel resources from the natural environment to urban structures, thereby aggravating the deterioration of the natural environment and increasing concern for the circular economy. Accurately understanding the spatiotemporal evolution of urban steel stocks is necessary to better maintain sustainable socioeconomic development. This paper constructs the consistency and continuity of multisource nighttime light (NTL) data and the results of modelled in-use steel stock (IUSS) in the Belt and Road (B&R) areas at a 1 km resolution. The multiscale IUSS spatiotemporal evolution in the B&R areas was quantified using geographic information analysis methods. The results revealed that the evolution of IUSS in the southern and northern parts of the B&R has significant differences. From 1992 to 2004, the evolutionary state of the IUSS showed drastic changes, while an overall trend of balanced development was maintained from 2004 to 2019. High-intensity IUSS is mainly concentrated in China, Russia, and India, and wealth level is the primary factor driving the development of IUSS. Combining the results of the development state analysis and spatial correlation analysis shows that central India and central and western China are potential hotspot areas for the flow of steel resources in the future. The results of this study can help develop differentiated and refined management strategies for the flow of anthropogenic steel resources. [ABSTRACT FROM AUTHOR]

This paper presents a comparison of the changes in the energetic metabolic pattern of China and India, the two most populated countries in the world, with two economies undergoing an important economic transition. The comparison of the changes in the energetic metabolic pattern has the scope to characterize and explain a bifurcation in their evolutionary path in the recent years, using the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach. The analysis shows an impressive transformation of China׳s energy metabolism determined by the joining of the WTO in 2001. Since then, China became the largest factory of the world with a generalized capitalization of all sectors, especially the industrial sector, boosting economic labor productivity as well as total energy consumption. India, on the contrary, lags behind when considering these factors. Looking at changes in the household sector (energy metabolism associated with final consumption) in the case of China, the energetic metabolic rate (EMR) soared in the last decade, also thanks to a reduced growth of population, whereas in India it remained stagnant for the last 40 years. This analysis indicates a big challenge for India for the next decade. In the light of the data analyzed both countries will continue to require strong injections of technical capital requiring a continuous increase in their total energy consumption. When considering the size of these economies it is easy to guess that this may induce a dramatic increase in the price of energy, an event that at the moment will penalize much more the chance of a quick economic development of India. [ABSTRACT FROM AUTHOR]

China and India, with their huge populations (37% of the world total), have been experiencing high economic growth rates of 7 to 12% in the last two decades. This has led to major changes in the levels and patterns of their food consumption and food buying behavior. This paper examines the rise and transformation of food demand in these two large emerging economies and the possible implications for the food security challenge. Data from the latest consumer surveys of the Government of India covering about 100,000 households and similar data from China are used. Tabulation and econometric analysis indicate that food demand is undergoing a huge transformation and will undergo further change. Consumers are rapidly increasing their consumption of animal products, vegetables and fruits, and reducing their consumption of cereals. Results show high income elasticities of demand for many food products such as animal products, processed foods, and also eating-out-of-home in both rural and urban areas. In India, given the vegetarian diets, the biggest component emerges to be dairy products, but the consumption of vegetables, meat and eggs is also growing rapidly. Supply is frequently unable to keep pace with the demand, resulting in high food price inflation. In China, the demand for foods of higher value, such as meats, dairy products and aquatic products is growing strongly. Urbanization is also having a significant impact. The numerous challenges include not only managing the supply but also the food supply chain, marketing, food safety and food processing. The changes pose an opportunity as well as a new food security challenge for these countries and the world. [ABSTRACT FROM AUTHOR]

This paper presents an extensive review of experimental, numerical, and numerical-experimental studies focused on compiling different aspects that lead to improved PTSC performance using the different electronic base sources during the last four decades. Different applications and future research prospects have also been presented, guiding the researchers that focus on developing new working fluids, receiver configurations, applications, among other aspects for PTSC performance enhancement. Experimental studies reveal that the combination of nanofluids and turbulators leads to the best improvement in PTSC thermal efficiency, followed by the use of internal fins and nanofluids only. Numerical studies affirmed that fin inserts have a more significant influence on heat transfer than nanofluids, but its main drawback is that it has a cost increase of 5%. The dispersion of Cu and CuO in the base fluid showed a remarkable increase in the heat transfer coefficient than other nanoparticles. Therefore, they are the best options to improve the PTSC's performance. Numerical-experimental studies reveal that the tube with an internal annular porous combined with the nanofluid Al 2 O 3 /Synthetic oil showed the best increase in thermal efficiency with a value that varies from 8% to 15%. Electronic analysis of publications focused on improving the PTSC's performance shows that China participates with 25%, followed by India with 11%. The PTSC applications proved that it is ideal for electrical energy stability and less dependent on limited fossil fuel reserves. Furthermore, more experimental studies are required to mature nanofluids' application and new receiver tube configurations on an industrial scale. • Different ways to improve PTSC performance over the last 4 decades was reviewed. • Experimental and numerical studies to improve PTSC thermal performance are presented. • Nanofluids, PTSR, and numerical models are described with current challenges. • The use of nanofluids with turbulators is the best option to improve PTSC performance. • This review can help to identify the aspects to be considered in future developments. [ABSTRACT FROM AUTHOR]

An accurate and objective prediction of coal consumption is important for stabilizing the coal market, ensuring the operating results of coal enterprises. This paper starts with the background value of the traditional GM(1,1) model, extends the model by the extrapolation method, proposes an optimized grey prediction model, deduces the time response equation, studies the relationship between model parameters and model accuracy. Then the model is optimized by simulated annealing algorithm. Three cases verify the validity of model, the results show that its lowest prediction error percentage is 3.1286%, which is better than two classical grey prediction models, Finally, the model is applied to forecast the next five years' consumption of China, India and the United States, which are the world's top three coal consumers. The errors of the proposed models are all about 5%, which is obviously better than the comparison models. The results show that coal consumption in China and India will continue to rise over the next five years, while the United States will decline. These findings are consistent with the current development of the three countries; therefore, the optimized prediction model can effectively predict the coal consumption of the three countries. • The highlights of this article are as follows: • An optimized grey prediction model that can be applied to various data situations is proposed. • The traditional GM(1,1) model is optimized by a simulated annealing algorithm. • The validity of the model is verified by theoretical deduction and case analysis. • The generality and wide applicability of the proposed method are discussed. [ABSTRACT FROM AUTHOR]

Traditional Indian medicine is one of the oldest medical systems and remains popular worldwide. Traditional medicine systems in China and India have historical origins pertaining to mutual learning, reference, and development from medical theory to the drugs used. The exchange of traditional medicine between China and India began in the Qin and Han Dynasties (221 BC–220 AD), prospered in the Tang Dynasty (618–907 AD), and declined after the Song Dynasty (960–1279 AD). It was also directly related to the rise and fall of Buddhism. The traditional medicines of the two countries are highly complementary because of differences in geographical climate and the modernisation process of traditional medicine. This review aimed to understand the spread and development of traditional Indian medicine in China to further promote exchange and cooperation between China and India in the field of traditional medicine. We performed a systematic search of MEDLINE via PubMed, CNKI, Science Direct, Sci-Hub, and other databases using the terms 'traditional Indian medicine' or 'Indian medicine' or 'Ayurveda' or 'Yoga' or 'Unani', and limiting the search to articles published between 1958 and 2019. We analysed the sources, publication date, type, and topic of the retrieved articles/studies. Based on the results of research on traditional Indian medicine carried out by Chinese scholars, 518 academic papers and 60 classic works published in China and abroad were collected. The results showed the following. First, Chinese scholars have systematically investigated traditional Indian medicine including its composition, management, and education; the scale of medicinal and pharmaceutical plants; protective measures of intellectual property rights of traditional medicine; and international promotion of Yoga. Second, studies have examined the development status of traditional Indian medicine in China including the spread of Yoga in the country and the industrial scale of, education in, existing problems in, and clinical research on Yoga. In addition, Chinese scholars conducted research on and the translation of classic works and terms of Ayurveda, and studied the theory, treatment, and medicine thereof. Third, the historical exchange and trading status of traditional medicine between India and China have been discussed, including the exchange of traditional medicine between the two countries, effect of traditional Indian medicine on Chinese Buddhism, and minority medicine and trade in medicinal materials between the two countries. India attaches great importance to the management of, education in, and industry of traditional medicine, and has made various efforts to protect intellectual property rights. Indian Yoga is very popular in China, and Chinese scholars have conducted some clinical research thereon. However, regulatory systems and legislation for Yoga are lacking in China. At present, traditional Chinese medicine scholars have an enhanced understanding of the term Yoga and less knowledge of the terms Ayurveda, Siddha, Unani, and similar concepts. We suggest that Chinese scholars further study the classic works, basic theories, treatment of clinical diseases, medicinal materials, and prescriptions compounding traditional Indian medicine. The results of this study highlight directions for Chinese scholars to pursue in further studying traditional Indian medicine comprehensively, and will help promote exchange and cooperation between China and India in the field of traditional medicine. [Display omitted] [ABSTRACT FROM AUTHOR]

Eco-efficiency composite indicators are widely accepted as the ratio of environmental impact to created economic value. These indicators are realistic measures for assessing sustainability performance considering the economy and environment. The weights reflect the importance of indicators to the aggregated environmental impacts. Estimating the relative weight of indicators is highly subjective, and therefore the search for a single unique weighting method has been going on for years. The regression-based weights are one of the most recent trends in sustainability modeling. Since these methods are designed initially to investigate the impact of multiple variables on a response variable rather than to estimate weights, some drawbacks are associated with their potential to provide proper weights. This paper presents a novel weighting approach integrating linear mixed-effect models with Johnson's relative weights to address these drawbacks and provide meaningful relative weights for eco-efficiency composite indicators. The proposed approach's operational and computational procedures are illustrated using a real example, and the eco-efficiency of food consumption of 38 countries is estimated for the period between 1990 and 2012 using a consumption-based sustainability accounting method. The findings have shown that energy use and GHG indicators are the most critical contributor to global food consumption's environmental impacts. The country-based eco-efficiency performance in this work has shown that China, India, and Russia are located in the low eco-efficiency score class. The Spatio-temporal analysis downgraded the geographical location's significance on the trends of eco-efficiency behavior in time and space. On the other hand, it revealed the different types of emerging hot spots over the world. • Consumption-based environmental footprint analysis is conducted. • Dynamic ecoefficiency of food consumption is estimated for 38 countries. • A novel weighting approach integrating Johnson's relative weights is proposed. • China, India, and Russia are located in the low ecoefficiency-score cluster. [ABSTRACT FROM AUTHOR]

This paper contributes to the existing literature by investigating the impact of oil prices on real exchange rates in China and India. We employ the non-linear, autoregressive-distributed lag model advanced by Shin et al. (2014), which allows both short-run and long-run asymmetry pass-through to a variable of interest. Oil prices and exchange rates are frequently found to be noisy. In order to detect the accurate relationship between oil prices and exchange rates, the maximum overlap, discrete-wavelet transformation is used to remove noise from the original series. The dynamic relationship between the original and de-noised series is compared. Our empirical findings suggest only long-run asymmetric effects of oil prices on exchange rates for both countries; however, after time-series noise removal, the asymmetric long-run effect becomes symmetric for India. Policy implications also are included. [ABSTRACT FROM AUTHOR]

Accurately forecasting energy demand can better predict future changes in energy demand. This study is aimed to develop more accurate clean energy prediction model from two perspectives of the modeling mechanisms and improvements on the model structure. For this purpose, a novel Riccati–Bernoulli differential equation is established through social practice theory, supply–demand relationship, and the preference of consumption in the energy economy. Considering the limited information in observation data, this differential equation is then transformed into a grey Riccati–Bernoulli model (GRBM(1,1)) according to the differential information principle. With the response function solved on the basis of polynomial equation theory and the power exponent optimized combining the modified flower pollination algorithm, the main process of GRBM(1,1) can be summarized. The four validation examples are provided for confirming the effectiveness and reliability of the new model by comparing with other existing models. Finally, the proposed model is employed to estimate and forecast the clean energy consumption in China and India. The results show that the proposed model demonstrates better estimation in all cases and efficiency in short-term clean energy consumption forecasting. Therefore, by using this optimum model, China's preference coefficient in total energy consumption is 0.7103, lower than that of India (0.8799), and China's preference coefficient in clean energy consumption is 0.9665, higher than that of Indian (0.7155), which means China has less interest to increase total energy consumption but more interest in popularizing the clean energy. • This paper proposed a novel grey Riccati–Bernoulli model for energy consumption prediction. • A specific solution algorithm for this Riccati–Bernoulli equation is discussed in this research. • We compared the proposed novel grey model with other 12 exiting prediction models. • The novel model also reveals China's effort in popularizing the use of clean energy. [ABSTRACT FROM AUTHOR]

Developing more effective carbon mitigation strategies requires accurate forecasting of carbon emissions. This is especially true for China, the United States and India, which produce over half of the world's carbon emissions. China, the United States, and India represent three different types of carbon emissions data. The first data type is typical for China: rapid grows which is thereafter slowing down. The US carbon emissions data show volatile growth and decline. The third data type is common for India's data: accelerated growth. To deal with the volatility of the data and to improve the forecasting accuracy, this paper combines Metabolic Nonlinear Grey Model (MNGM) with Autoregressive Integrated Moving Average (ARIMA) to develop the combined MNGM-ARIMA model, and MNGM with Back Propagation Neural Network (BPNN) to develop the new combined MNGM-BPNN model. In this way, ARIMA and BPNN could correct the modelling residual error of MNGM, to decrease the forecasting error. Through the quantitative data study of the countries in focus, we have made the following findings: First, the mean relative percent errors of the proposed MNGM-ARIMA and MNGM-BPNN models are 1.35% and 1.57%, which are lower than the traditional MNGM, ARIMA, and BPNN models. Besides, it is projected that during the period of 2019–2030, the US′ carbon emissions will keep a downward trend, while carbon emissions in China and India will continue to grow. Finally yet importantly, in the future periods of time, the carbon emissions growth rate in India will be faster than that for China. The above findings have led us to the following conclusions: (1) Error values of those two proposed approaches have proven that the strategy of correcting the forecasting error of the previous models with the latter models can effectively improve the forecasting accuracy. (2) The proposed two combined forecasting techniques have shown sound performance for the three types of data. It is reasonable to believe that new approaches will help to improve insight into better forecasting carbon emissions in other countries and regions of the world. (3) China and India will remain the major sources of global carbon emissions, and should therefore continue their efforts on carbon emission reduction. Image 10221 • China, the United States and India contribute half of global carbon emissions. • Forecasting the carbon emissions is conducive to global carbon emission reduction. • Strategy of "error correction + quadratic modeling" and new models are proposed. • Mean relative errors of the two proposed models achieved 1.35% and 1.57%. • Future carbon emissions growth will be concentrated in developing countries. [ABSTRACT FROM AUTHOR]

Following India's efforts to mitigate the emission of greenhouse gases, there has been a transition from fossil fuels to clean energy sources, such as solar and wind, in the energy portfolio. The renewable energy sector is widely acknowledged as a fertile ground for employment creation, as it is labour-intensive. Against this backdrop, the main objective of this paper is to provide an empirical explanation of how the growth of renewable energy sources, particularly solar photovoltaic (PV) technology, affects employment creation in India. The findings reveal that, despite a substantial investment in India's solar PV technology, the number of jobs created by the sector declined marginally from 164000 in 2017–114000 in 2018. India's estimated employment elasticity is just 0.004, implying that the level of employment does not show a significant positive response to changes in installed capacity. Almost 60 per cent of the global solar PV workforce is in China, which has become the leading country both in terms of installed capacity of global solar PV technology and manufacturing of solar PV cells and modules. The wide disparity in solar PV employment between India and China is explained by the former's excessive dependence on China for solar PV cells. Alongside climate conservation, India should, therefore, place more emphasis on revitalising the domestic solar manufacturing industry to bring about efficient use of the nation's untapped resources. [ABSTRACT FROM AUTHOR]

• Experimental studies of the slotted-in dowelled bamboo-to-steel joint with/without infilling grout. • Failure behaviours and load-displacement curves for various specimens were predicted by FEM. • Analytical design models were proposed based on the results from test and FEM for the joints. Bamboo has been widely used for structural and non-structural purpose, for example as scaffolding and cladding for many centuries in South East Asian countries such as China and India, due to its high strength-to-weight ratio, low price and recyclability. In today's trend of sustainable development, there is a renewed interest in the use of bamboo for modern prefabricated structures. In this paper, dowel-type bamboo joints are introduced for prefabricated bamboo structures. An experimental study has been undertaken to investigate the structural behaviour and the failure mechanisms of the dowelled joints with varying configurations. Test results reveal that the ductile failure mode of the bamboo occurred when large end spacing was applied, and the infilling grout can significantly increase the load-carrying capacity of the dowelled joint. Three-dimensional finite element models were established and validated using available experimental data. Extensive parametric studies were carried out based on the simulation approach to investigate the effects of key influencing variables involved, i.e. hole clearance, friction coefficient, bolt strength, bamboo thickness, grout strength and end spacing. Moreover, analytical models for designing the dowelled joints are proposed and compared with the current codified approach. [ABSTRACT FROM AUTHOR]

The research into bioactive natural products originating from medicinal plants, fungi and other organisms has a long history, accumulating abundant and diverse publications. However no quantitative literature analysis has been conducted so far. Here we analyze the bibliometric data of ethnopharmacology literature and relate the semantic content to the publication and citation data so that the major research themes, contributors, and journals of different time periods could be identified and evaluated. Web of Science (WoS) was searched to identify relevant publications. The Analyze function of WoS and bibliometric software (VOSviewer) were utilized to perform the analyses. Until the end of November 2018, 59,576 publications -linked to 'ethnopharmacology' indexed by WoS, published since 1958 in more than 5600 journals, and contributed by over 20,600 institutions located in more than 200 countries/regions, were identified. The papers were published under four dominating WoS categories, namely pharmacology/pharmacy (34.4%), plant sciences (28.6%), medicinal chemistry (25.3%), and integrative complementary medicine (20.6%). India (14.6%) and China (13.2%) were dominating the publication space. The United States and Brazil also had more than 8.0% contribution each. The rest of the top ten countries/regions were mainly from Asia. There were around ten-fold more original articles (84.6%) than reviews (8.4%). Ethnopharmacological research has a consistent focus on food and plant sciences, (bio)chemistry, complementary medicine and pharmacology, with a more limited scientific acceptance in the socio-cultural sciences. Dynamic global contributions have been shifting from developed countries to economically and scientifically emerging countries in Asia, South America and the Middle East. Research on recording medicinal plant species used by traditional medicine continues, but the evaluation of specific properties or treatment effects of extracts and compounds has increased enormously. Moreover increasing attention is paid to some widely distributed natural products, such as curcumin, quercetin, and rutin. Image 1 [ABSTRACT FROM AUTHOR]

Taking Sino-Indian relations as a case-study, this paper examines a form of international relations that arises when emerging states share an inhabited borderland: "state-shadowing". Authority over people is crucial to effective sovereignty, yet international borderlands are often porous and heterogeneous. Borderlanders have the possibility to look across, observe and compare different state-making and nation-building projects. When neighboring states simultaneously seek to consolidate in such situations, physical closeness can become a contest to prove their superiority over the state next door—which constitutes an always discernible, readily available, and equally viable alternative political project—to local people. This fear of comparison is particularly high in post-colonial polities like China and India, struggling to transform into nations. The triangular relationship between states and non-state actors in borderland situations turns state-making and nation-building into emulative, mirroring, and competitive attempts at self-definition against the other polity. As China and India's Himalayan encounter in the 20th century attests, this fear of being compared can escalate into a destructive security dilemma. The concept of state-shadowing thus offers a framework to understand how proximity, mobility and governmentality structure the low politics between neighboring post-colonial states, and potentially contribute to conflict. [ABSTRACT FROM AUTHOR]