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In recent years, with the rapid development of China's air transport industry and the change in market consumption structure, service quality has become one of the important factors affecting airline revenue. How to formulate a reasonable pricing strategy and maintain competitiveness in the fierce market competition has become an urgent problem for airlines. First, the impact factor of service quality level in the traditional pricing model is introduced and a static price competition model for multi-oligopoly airlines based on service quality is established in this paper. And then, a dynamic pricing model based on service quality of the multi-oligopoly airlines is established. The model incorporates the weight factor of service quality impact, which is used to indicate the weight of the service quality level in the process of airline dynamic pricing. The research results show that the service quality level of airlines has an indispensable influence on its development. Airlines should improve service quality as soon as possible to enhance market competitiveness and achieve sustainable development. [ABSTRACT FROM AUTHOR]

Abstract: We computed the daily AVHRR snow cover from all available AVHRR level1b raw data over central Asia (CA) with an aggregated rating based snow identification scheme. The daily AVHRR snow cover was further processed into an 8-day maximum-snow-extent data, and then went through a set of spatial and temporal filters to fill cloud or gap pixels. A correction method based on known long term snow probability in small sub-regions has been developed for computing corrected 8-day AVHRR snow cover, which is comparable to 8-day MODIS snow data. Validation of the daily AVHRR snow product against ground snow survey suggested a high accuracy of the snow identification scheme. Comparison of the daily AVHRR snow cover with the daily MODIS snow cover in Amu Dar'ya River basin within CA showed high accuracy of daily AVHRR snow, with a general accuracy of 99.60% and Kappa Coefficient of 0.92 in the basin. Comparison of the corrected 8-day AVHRR snow cover with 8-day MODIS cloud/gap free snow cover in the same basin also showed high comparability between both data, with a general accuracy of 95.61% and Kappa Coefficient of 0.84. Seasonal snow cover analysis in Amu Dar'ya River basin revealed the spatial and temporal patterns of snow distribution and negative trends in snow cover duration in 1986 to 2008 due to earlier snow melting dates. The newly developed long-term snow dataset from AVHRR and MODIS data over CA, with its high accuracy and internal comparability, is suitable for seasonal snow cover studies in mountainous regions over CA. [Copyright &y& Elsevier]

First discovered in rural areas of middle-eastern China in 2009, severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne zoonosis affecting hundreds of cases reported in China each year. Using the national surveillance data from 2010 to 2013, we conducted this retrospective epidemiological study and risk assessment of SFTS in China. We found that the incidence of SFTS and its epidemic areas are continuing to grow, but the case fatality rate (CFR) has steadily decreased. SFTS most commonly affected elderly farmers who acquired infection between May and July in middle-eastern China. However, other epidemiological characteristics such as incidence, sex ratio, CFR, and seasonality differ substantially across the affected provinces, which seem to be consistent with local agricultural activities and the seasonal abundance of ticks. Spatial scan statistics detected three hot spots of SFTS that accounted for 69.1% of SFTS cases in China. There was a strong association of SFTS incidence with temporal changes in the climate within the clusters. Multivariate modeling identified climate conditions, elevation, forest coverage, cattle density, and the presence of Haemaphysalis longicornis ticks as independent risk factors in the distribution of SFTS, based on which a predicted risk map of the disease was derived. [ABSTRACT FROM AUTHOR]