Energy prices and energy intensity in China : a structural decomposition analysis and econometrics study

Since the start of its economic reforms in 1978, China's energy prices relative to other prices have increased. At the same time, its energy intensity, i.e., energy consumption per unit of Gross Domestic Product (GDP), has declined dramatically, by about 70%, in spite of increases in energy consumption. Is this just a coincidence? Or does a systematic relationship exist between energy prices and energy intensity? In this study, we examine whether and how China's energy price changes affect its energy intensity trend during 1980-2002 at a macro level. We conduct the research by using two complementary economic models: the input-output-based structural decomposition analysis (SDA) and econometric regression models and by using a decomposition method of own-price elasticity of energy intensity. Findings include a negative own-price elasticity of energy intensity, a price-inducement effect on energy efficiency improvement, and a greater sensitivity (in terms of the reaction of energy intensity towards changes in energy prices) of the industry sector, compared to the overall economy.(cont.) Analysts can use these results as a starting point for China's energy and carbon emission forecasts, which they traditionally conduct in China without accounting for energy-intensity changes. In addition, policy implications may initiate new thinking about energy policies that are needed to conserve China's energy resources and reduce carbon emissions

GROWTH ANALYSIS OF CHINESE LIQUOR LISTED COMPANIES BASED ON PRINCIPAL COMPONENT ANALYSIS

Online shopping has been increasingly popular in recent years due to the spread of the Internet, and the livestream sector has increased. Many traditional companies, such as Chinese liquor enterprises, tried to engage in livestreaming to keep pace with their new customers. The overall perceived value’s impact on user behavior has been examined in social commerce research, but the livestream context has received less attention. This study proposed and empirically tested a theoretical model, considering online word-of-mouth, and investigated the effect of consumer perceived value on livestream purchase intention of Chinese liquor. The findings demonstrate that online word-of-mouth serves as a mediator between the three dimensions of perceived value - functional, emotional, and social value - and livestream purchase intentions of Chinese liquor

Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks

The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA) is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN

MirrorDiffusion: Stabilizing Diffusion Process in Zero-shot Image Translation by Prompts Redescription and Beyond

Recently, text-to-image diffusion models become a new paradigm in image processing fields, including content generation, image restoration and image-to-image translation. Given a target prompt, Denoising Diffusion Probabilistic Models (DDPM) are able to generate realistic yet eligible images. With this appealing property, the image translation task has the potential to be free from target image samples for supervision. By using a target text prompt for domain adaption, the diffusion model is able to implement zero-shot image-to-image translation advantageously. However, the sampling and inversion processes of DDPM are stochastic, and thus the inversion process often fail to reconstruct the input content. Specifically, the displacement effect will gradually accumulated during the diffusion and inversion processes, which led to the reconstructed results deviating from the source domain. To make reconstruction explicit, we propose a prompt redescription strategy to realize a mirror effect between the source and reconstructed image in the diffusion model (MirrorDiffusion). More specifically, a prompt redescription mechanism is investigated to align the text prompts with latent code at each time step of the Denoising Diffusion Implicit Models (DDIM) inversion to pursue a structure-preserving reconstruction. With the revised DDIM inversion, MirrorDiffusion is able to realize accurate zero-shot image translation by editing optimized text prompts and latent code. Extensive experiments demonstrate that MirrorDiffusion achieves superior performance over the state-of-the-art methods on zero-shot image translation benchmarks by clear margins and practical model stability.Comment: A prompt re-description strategy is proposed for stabilizing the diffusion model in image-to-image translation. Code and dataset page: https://mirrordiffusion.github.io

Job Satisfaction by Chinese Primary Care Doctors Following Health Care Reform

The purpose of this study is to compare primary care doctors’ job satisfaction and factors associated with it before and after the latest health care reform in China. Data for the study were obtained from China Primary Care Workforce Surveys conducted in 2008 and 2011. Compared to results from the 2008 survey, primary care doctors (PCDs) in the 2011 survey were more satisfied with their jobs overall as well as work conditions and equipment, but less satisfied with their income. In both surveys rural CHC and village clinic doctors were less satisfied than their urban counterparts with their jobs overall, income, work condition, and equipment. Logistic regressions showed that practice setting (i.e. urban, rural, or village) and educational level were two important factors associated with job satisfaction. These findings demonstrated both significant achievements and further efforts to be made to strengthen primary care workforce and enhance their job satisfaction