A scenario analysis of energy requirements and energy intensity for China's rapidly developing society in the year 2020

Both energy requirements and energy intensity are crucial to the development of a society. This article uses an input–output model to assess how social and economic changes will affect energy requirements and energy intensity for China's rapidly developing society. According to the proposed input–output model, six scenarios were sequentially developed by introducing major impact factors, such as technological advancement, population, income, and urbanization, in order to project China's energy requirements. Based on 1997 data, the impact of economic and social changes on China's energy requirements in 2010 and 2020 were quantitatively analyzed. The results show that technological advancement has the strongest impact on energy intensity. Based on these findings, some related conclusions and corresponding policy recommendations are proposed.     

Risk assessment of oil price from static and dynamic modelling approaches

The price gap between West Texas Intermediate (WTI) and Brent crude oil markets has been completely changed in the past several years. The price of WTI was always a little larger than that of Brent for a long time. However, the price of WTI has been surpassed by that of Brent since 2011. The new market circumstances and volatility of oil price require a comprehensive re-estimation of risk. Therefore, this study aims to explore an integrated approach to assess the price risk in the two crude oil markets through the value at risk (VaR) model. The VaR is estimated by the extreme value theory (EVT) and GARCH model on the basis of generalized error distribution (GED). The results show that EVT is a powerful approach to capture the risk in the oil markets. On the contrary, the traditional variance–covariance (VC) and Monte Carlo (MC) approaches tend to overestimate risk when the confidence level is 95%, but underestimate risk at the confidence level of 99%. The VaR of WTI returns is larger than that of Brent returns at identical confidence levels. Moreover, the GED-GARCH model can estimate the downside dynamic VaR accurately for WTI and Brent oil returns.     

Can China realise its energy-savings goal by adjusting its industrial structure?

To investigate whether China can realise its energy-savings goal by 2020 through adjustments to its industrial structure, this study proposes a dynamic input–output multi-objective optimisation model. According to this model, the objectives to be achieved include the maximum gross domestic product and employment, and the minimum energy consumption, where the constraints are the sectoral dynamic input–output balance, labour and energy supply, and sectoral production capacity. The four best solutions are screened from the Pareto-optimal front. The study findings show that the energy intensities in 2020 would decrease by 42.8%, 43.5%, 42.9%, and 43.4% in the four scenarios when compared to their 2002 levels. This means that China can fully achieve its planned energy-savings target for 2020. In order to ensure that the industrial structure is optimised for the future, sectoral capital investments should be regulated by China's government and efforts to improve energy efficiency should be maintained.     

依达拉奉联合阿托伐他汀钙治疗急性脑梗死患者的临床疗效

目的 探讨依达拉奉联合阿托伐他汀钙治疗急性脑梗死患者的疗效.方法 选取2019年1月至2020年1月于大连市中心医院神经内科住院治疗的急性脑梗死患者68例作为研究对象,据其住院病例号码随机分为他汀组与联合组,各34例.两组患者接受抗血小板聚集、改善循环、降低颅内压、改善脑水肿等基础治疗,并监测各项生命指征指标,如血压、...