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Summary: The daily practice requires the use of indirect calorimetry to define the energy requirements of intensive care patients. In the time of COVID-19 pandemic, this practice is challenging. The purpose of this methodology paper is to provide practical guidance to health professionals to perform this measurement safely, using various metabolic monitors.

Abstract Electric vehicle development is critical to achieve the sustainable goals, while the hit of COVID-19 strikes the market and brings challenges to the whole industry. China, among one of the earliest regions affected by COVID-19 and takes a great part in the global electric vehicle market, is attracting growing attention on its post-pandemic trends in the electric vehicle industry. This paper provides a comprehensive analysis of COVID-19 impacts on China's electric vehicle industry from both the demand side and the supply side. Both challenges and opportunities for China's electric vehicle development are revealed with emerging trend analysis. It is found that the COVID-19 outbreak has reduced electric vehicle sales in the short-term, but may also stimulate future electric vehicle demand especially for large electric cars with better performance. Meanwhile, travel restrictions caused by COVID-19 have interrupted electric vehicle material supplies that relying on imports, accelerating domestic substitute exploitation and inventory improvement for critical parts. Additionally, massive lockdowns for controlling COVID-19 have disrupted productions and operations, which tends to expel small brands out of the competitive market, concentrating China's electric vehicle industry to the leading brands. Finally, the social distancing trend after pandemic is bringing challenges to traditional EV distribution channels with dealers, pushing automakers to develop innovative online selling channels. These impacts are likely to lead to a reformation of China's electric vehicle industry towards a more advanced and reliable future.

Increasing economic and population growth has led to a rise in electricity consumption. Consequently, electrical utility firms must have a proper energy management strategy in place to improve citizens’ quality of life and ensure an organization’s seamless operation, particularly amid unanticipated circumstances such as coronavirus disease (COVID-19). There is a growing interest in the application of artificial intelligence models to electricity prediction during the COVID-19 pandemic, but the impacts of clustering methods and parameter selection have not been explored. Consequently, this study investigates the impacts of clustering techniques and different significant parameters of the adaptive neuro-fuzzy inference systems (ANFIS) model for predicting electricity consumption during the COVID-19 pandemic using districts of Lagos, Nigeria as a case study. The energy prediction of the dataset was examined in relation to three clustering techniques: grid partitioning (GP), subtractive clustering (SC), fuzzy c-means (FCM), and other key parameters such as clustering radius (CR), input and output membership functions, and the number of clusters. Using renowned statistical metrics, the best sub-models for each clustering technique were selected. The outcome showed that the ANFIS-based FCM technique produced the best results with five clusters, with the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Coefficient of Variation (RCoV), Coefficient of Variation of the Root Mean Square Error (CVRMSE), and Mean Absolute Percentage Error (MAPE) being 1137.6024, 898.5070, 0.0586, 11.5727, and 9.3122, respectively. The FCM clustering technique is recommended for usage in ANFIS models that employ similar time series data due to its accuracy and speed.

however, the environmental dimension has suffered a negative impact in prioritisation, regardless of organisation type, country where they are based, organisation size, or the time they have been working on sustainability. We are currently facing an environmental conundrum, where air quality has improved and pollution has decreased in societies, but organisations are starting to neglect such environmental issues. The COVID-19 outbreak is an opportunity for organisations to better contribute to sustainability by ensuring that the efforts that have been undertaken in the last three decades are not forgotten, and that societies and organisations are better coupled to face such crises and avert rebound effects. sustainability priorities. Prior to the COVID-19 outbreak, such priorities were on the economic dimension followed by the environmental and social dimensions. A survey was sent to 11,657 organisations to analyse such changes, with a 5.60% response rate. The results show that for organisations, the main priority is now on the social dimension, followed by the economic one The COVID-19 outbreak has affected societies and organisations in an unprecedented way. This has resulted in negative impacts to economic and social issues, but it is a &ldquo for environmental issues. This paper analyses how the outbreak has affected organisations&rsquo blessing in disguise&rdquo

Electricity consumption has been affected due to worldwide lockdown policies against COVID-19. Many countries have pointed out that electricity supply security during the epidemic is critical to ensuring people’s livelihood. Accurate prediction of electricity demand would act a more important role in ensuring energy security for all the countries. Although there have been many studies on electricity forecasting, they did not consider the pandemic, and many works only considered the prediction accuracy and ignored the stability. Driven by the above reasons, it is necessary to develop an electricity consumption prediction model that can be well applied in the pandemic. In this work, a hybrid prediction system is proposed with data processing, modelling, and optimization. An improved complete ensemble empirical mode decomposition with adaptive noise is used for data preprocessing, which overcomes the shortcomings of the original method; a multi-objective optimizer is adopted for ensuring the accuracy and stability; support vector machine is used as the prediction model. Taking daily electricity demand of US as an example, the results prove that the proposed hybrid models are superior to benchmark models in both prediction accuracy and stability. Moreover, selection of input parameters is discussed, and the results indicate that the model considering the daily infections has the highest prediction accuracy and stability, and it is proved that the proposed model has great potential in real-world applications. Highlights • A hybrid model is developed for predicting daily electricity demand during COVID-19. • The accuracy and stability of the new model are higher than those of benchmark models. • The proposed model also performs well in multi-step prediction. • The model that only considers daily infections has the best prediction performance.

One “silver lining” of the COVID-19 pandemic has been the reduction in air pollution that followed lockdowns. Unfortunately, this unintended air pollution decline will likely be short-lived. As regions begin to recover their economies, travel and industrial activity will increase the ambient pollutants quickly offsetting the improvement in air quality. Therefore, it is urgent to clarify the causal impact of reopening an economy on air quality during COVID-19. Based on city-level daily air quality data in China, this paper is the first to empirically analyze the causal effect of reopening the economy in the provincial capital Lanzhou on concentrations of four air pollutants using the synthetic control method. The results show that the reopening caused a significant increase in the concentration of NO2 by as much as 30 μg/m3 (an increase of 75% from the lockdown level) and a significant increase in O3 concentrations by 60μg/m3 (a 60% increase) which peaked on the 6th day after the restart. The reopening also led to significant fluctuations in SO2 and CO concentrations. This study contains useful conclusions by providing timely and reliable causal evidence on the lasting impact of COVID-19 on air quality.

We present a comprehensive analysis of the performance and flows of U.S. actively-managed equity mutual funds during the COVID-19 crisis of 2020. We find that most active funds underperform passive benchmarks during the crisis, contradicting a popular hypothesis. Funds with high sustainability ratings perform well, as do funds with high star ratings. Fund out ows surpass pre-crisis trends, but not dramatically. Investors favor funds that apply exclusion criteria and funds with high sustainability ratings, especially environmental ones. Our finding that investors remain focused on sustainability during this major crisis suggests they view sustainability as a necessity rather than a luxury good.

During the COVID-19 pandemic, educational mobile games may play a significant role to facilitate students’ learning. Several studies have indicated that these games using mobile phones may improve students’ learning motivation and effectiveness when they are equipped with appropriate learning strategies. However, investigating the impact of learning strategies in students’ utilization of educational mobile games has received little scholarly attention during the COVID-19 pandemic. Hence, this research proposed two learning games scenarios to fill this gap. In the first scenario, students were offered an educational mobile game with a learning strategy called ‘scaffolding strategy’; while in the second scenario, the same game was offered without the strategy. To achieve this objective, an experimental design with a research model was developed to examine the role of scaffolding learning strategy in students’ use of educational mobile games. In this experimental study, 43 students from two classes participated in the two learning scenarios. The results indicate that educational mobile gaming with the scaffolding learning strategy significantly influenced students’ utilization of the mobile game. In addition, the adoption of the learning strategy significantly affected students’ perceived enjoyment, perceived usefulness, perceived ease of use, and behavioural intention to use, compared with the same game without the learning strategy. The results also indicate that the introduction of the scaffolding learning strategy into the educational mobile game will increase students’ learning effectiveness and motivation.

Food security and energy transition are among the current major global environmental challenges. Although these issues individually are significant in their own right, they are connected to each other in a nexus with different interrelationships and dependencies. In the quest for non-fossil alternatives for energy, cultivation of bioenergy crops has become an important part of the energy policy in many countries. In this regard, the use of fertile agricultural land for growing crops for energy production rather than for food supply affects the global food security. Recent conflicts and the geopolitical crisis in Europe, leading to increased food, fuel, and fertiliser prices, the existing climate crisis, and the crisis caused due to the COVID-19 pandemic, have further reinforced the understanding of this nexus, with certain countries mulling limiting biofuel production from agricultural land and others banning food grain exports to safeguard food supply. The idea of growing non-food energy crops on marginal lands in general and closed landfill sites in particular is hence ever more relevant, to avoid land-use concurrence between food needs and energy needs. Landfilling has been the dominant waste management strategy until recently in European countries and is still the dominant mode of waste management in low-income regions like South Asia. This paper provides a review of the economic as well as environmental benefits of growing Ricinus communis L., Jatropha curcas L., and Populus deltoides as energy crops on closed landfill sites in the South Asian context. While as the cultivation of Miscanthus X Giganteus, Silphium perfoliatum L., and Panicum virgatum (Switchgrass) is reviewed in the European context. The cultivation of non-food energy crops like these on closed landfill sites and marginal lands is presented as a potential component of an integrated food-energy policy, with an increased relevance in the current times. In the current times of multiple crises, this measure is of increasing relevance as a part of the overall strategy to achieve resilience and environmental sustainability. Food security and energy transition are among the current major global environmental challenges. Although these issues individually are significant in their own right, they are connected to each other in a nexus with different interrelationships and dependencies. In the quest for non-fossil alternatives for energy, cultivation of bioenergy crops has become an important part of the energy policy in many countries. In this regard, the use of fertile agricultural land for growing crops for energy production rather than for food supply affects the global food security. Recent conflicts and the geopolitical crisis in Europe, leading to increased food, fuel, and fertiliser prices, the existing climate crisis, and the crisis caused due to the COVID-19 pandemic, have further reinforced the understanding of this nexus, with certain countries mulling limiting biofuel production from agricultural land and others banning food grain exports to safeguard food supply. The idea of growing non-food energy crops on marginal lands in general and closed landfill sites in particular is hence ever more relevant, to avoid land-use concurrence between food needs and energy needs. Landfilling has been the dominant waste management strategy until recently in European countries and is still the dominant mode of waste management in low-income regions like South Asia. This paper provides a review of the economic as well as environmental benefits of growing Ricinus communis L., Jatropha curcas L., and Populus deltoides as energy crops on closed landfill sites in the South Asian context. While as the cultivation of Miscanthus X Giganteus, Silphium perfoliatum L., and Panicum virgatum (Switchgrass) is reviewed in the European context. The cultivation of non-food energy crops like these on closed landfill sites and marginal lands is presented as a potential component of an integrated food-energy policy, with an increased relevance in the current times. In the current times of multiple crises, this measure is of increasing relevance as a part of the overall strategy to achieve resilience and environmental sustainability.