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• Decoupling of GDP from all energy sources under multiple principles are examined. • World economy achieved weak energy decoupling in most years during 2000–2011. • World economy coupled with coal use and tended to couple with cleaner energy use. • None of studied economies achieved long-term GDP-embodied energy decoupling. • Decoupling delusions occurred when only considering direct and total energy use. Decoupling indicators are widely used to understand links between economic growth and energy use. However, traditional decoupling analyses mostly focus on domestic energy consumption (i.e., the production-based principle) and neglect off-site energy use across global supply chains to satisfy an economy's final consumption (i.e., the consumption-based principle). Moreover, analyses for total primary energy conceal an economy's preference for different energy sources. Therefore, this paper evaluates decoupling states of GDP from all types of primary energy use under consumption-based principle, for world economy and eight typical economies during 2000–2011. Regarding total primary energy, world economy witnessed weak decoupling in most years, and most economies studied (e.g., USA, Japan and China) achieved decoupling initially but performed negative decoupling finally. For EU, USA, Japan, Russia and India, production-based decoupling performances were generally better than consumption-based ones. Decoupling phenomena detected under production-based principle even became coupling or negative decoupling under consumption-based principle in some cases. As for each energy source, world economy decoupled from oil use, but still coupled with coal use, and gradually showed a trend to couple with natural gas and renewables use. Different energy sources showed distinct decoupling degrees from GDP, affected by individual embodied energy requirement structure. This paper uncovers potential energy decoupling delusions to deepen the understanding of relationships between energy use and economic growth. [ABSTRACT FROM AUTHOR]

• Sheltered natural carbonation can be similar between different climates. • Huge impact of curing on natural carbonation for very early age (i.e. 1 day) • Impact of curing is negligible for advanced curing age, regardless of cement type. • Strong impact of precipitation on natural carbonation. • The higher the number of rainy days, the lower the carbonation speed. This paper describes a unique international inter-laboratory study on the carbonation resistance of concrete prepared with different supplementary cementing materials. Concrete specimens – from 45 different concrete mixtures – prepared centrally in Lafarge Centre de Recherche (France) were shipped in a sealed condition to 4 other academia research laboratories (located in USA, Canada, India and China). The specimens were exposed to the ambient environments and atmospheric CO2 concentrations in the five locations, including Lafarge Centre de Recherche in France, in both sheltered and unsheltered condition for a period of 5 years. Measurements of carbonation depth were performed at periodic intervals, and the data was analyzed to assess the influence of climatic conditions on the resistance to carbonation. The results indicate that the general trend of carbonation is not much different irrespective of the macroclimate. Further, the number of rainy days seems to have a more significant influence on the progress of carbonation than the total rainfall in the region. [ABSTRACT FROM AUTHOR]

Abstract Wind speed and power forecast is an essential component to ensure grid stability and reliability. The traditional forecasting methods fail to address the non-linearity in the wind speed time-series, thus paving way for machine intelligent algorithms. This paper discusses a hybrid machine intelligent wind forecasting model utilizing different variants of Support Vector Regression (SVR) built on wavelet transform. Various performance indices are evaluated to identify the possible best one among four different machine learning regressors for wind forecasting application. Apart from standard ε-SVR and LS-SVR, two new regression models, namely, ε-Twin Support vector regression (ε-TSVR) and Twin Support vector regression (TSVR) are used to forecast short-term wind speed, and are compared with Persistence model for four wind farm sites. The effect of larger dataset on forecasting performance is evaluated for two wind farm sites from USA and India. Further, wind power ramp events are investigated at different hub heights and the forecasting performance of different variants of SVR is compared for five wind farm sites. Highlights • Machine intelligent SVR variants are discussed for short-term wind forecasting. • Overfitting and underfitting scenarios of variants of SVR are assessed. • Forecasting performance of SVR variants is assessed during wind power ramp event. • Wind power ramp events are analyzed at different hub heights for 5 wind farm sites. [ABSTRACT FROM AUTHOR]

Abstract Investigating the "physics" of food crises consists in identifying features which are common to all large-scale food crises. One element which stands out is the fact that during a food crisis there is not only a surge in deaths but also a correlative temporary decline in conceptions and therefore in subsequent births nine months later. This scenario is studied in three cases of large-scale food crises: Finland (1868), India (1867–1907 and 1942–1944), China (1960–1961). It turns out that between the regional amplitudes of death spikes on one hand and the amplitudes of birth troughs on the other hand there is a power law relationship. This confirms the same phenomenon already observed in the wake of the epidemic of 1918 in the United States (Richmond et al., 2018b). In the second part of the paper we explain and demonstrate on three case studies how this relationship can be used for the investigation of mass-mortality episodes in cases where direct death data are either uncertain, suspicious or nonexistent. Highlights • Mass mortality episodes are followed by birth troughs 9 months later. • There is a power law relationship between death and birth amplitudes. • It can give estimates for the death toll of major disasters. • The method is tested on 3 case studies. [ABSTRACT FROM AUTHOR]

Offshore wind is one of the most fascinating industries in the renewable energy sector and it is experiencing a remarkable growth. Offshore wind energy generation offers an opportunity in the race to decrease the dependence on fossil fuels, reduce green house emissions, increase energy security and create employment opportunities. UK has proven success in offshore wind and has been enjoying the economic benefits of offshore wind since over a decade. Offshore wind energy is an emergent renewable energy industry in the United States. The United States is coping up with the challenges and heading up fast to catch up with the industry. India is still in its infancy stage where the policy frameworks are framed by MNRE government and getting ready with the tools to enter into the offshore market. This paper researches the current situation and trend of offshore wind industries in UK and US, from aspects of policy, grid connections, operation and maintenance and cost reduction and analyses the proper direction and pathways of the industry to India. Therefore this paper highlights the scenario as to how these three countries UK, USA and India, respectively, are enabling offshore wind, to make a vital and sizeable contribution to the low carbon economy. [ABSTRACT FROM AUTHOR]

In this paper we use simulation to analyze how flight routing network structure may change in different world regions, and how this might impact future traffic growth and emissions. We compare models of the domestic Indian and US air transportation systems, representing developing and mature air transportation systems respectively. We explicitly model passenger and airline decision-making, capturing passenger demand effects and airline operational responses, including airline network change. The models are applied to simulate air transportation system growth for networks of 49 airports in each country from 2005 to 2050. In India, the percentage of connecting passengers simulated decreases significantly (from over 40% in 2005 to under 10% in 2050), indicating that a shift in network structure towards increased point-to-point routing can be expected. In contrast, very little network change is simulated for the US airport set modeled. The simulated impact of network change on system CO 2 emissions is very small, although in the case of India it could enable a large increase in demand, and therefore a significant reduction in emissions per passenger (by nearly 25%). NO x emissions at major hub airports are also estimated, and could initially reduce relative to a case in which network change is not simulated (by nearly 25% in the case of Mumbai in 2025). This effect, however, is significantly reduced by 2050 because of frequency competition effects. We conclude that network effects are important when estimating CO 2 emissions per passenger and local air quality effects at hub airports in developing air transportation systems. [ABSTRACT FROM AUTHOR]

This paper compares and contrasts the spread and impact of COVID-19 in the three countries most heavily impacted by the pandemic: the United States (US), India and Brazil. All three of these countries have a federal structure, in which the individual states have largely determined the response to the pandemic. Thus, we perform an extensive analysis of the individual states of these three countries to determine patterns of similarity within each. First, we analyse structural similarity and anomalies in the trajectories of cases and deaths as multivariate time series. Next, we study the lengths of the different waves of the virus outbreaks across the three countries and their states. Finally, we investigate suitable time offsets between cases and deaths as a function of the distinct outbreak waves. In all these analyses, we consistently reveal more characteristically distinct behaviour between US and Indian states, while Brazilian states exhibit less structure in their wave behaviour and changing progression between cases and deaths. • We compare and contrast the natural history of COVID-19 in the US, India and Brazil. • Case, death and mortality rate trajectories are analysed on a state-by-state basis. • We quantify heterogeneity and identify anomalous states therein within each country. • Wave behaviours are explored and clustered across the three countries states. • New mathematical methods quantify the lag in the progression from cases and deaths. [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]