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Epidemics of influenza are major public health concerns. Since influenza prediction always relies on the weekly clinical or laboratory surveillance data, typically the weekly Influenza-like illness (ILI) rate series, accurate multi-step-ahead influenza predictions using ILI series is of great importance, especially, to the potential coming influenza outbreaks. This study proposes Comprehensive Learning Particle Swarm Optimization based Machine Learning (CLPSO-ML) framework incorporating support vector regression (SVR) and multilayer perceptron (MLP) for multi-step-ahead influenza prediction. A comprehensive examination and comparison of the performance and potential of three commonly used multi-step-ahead prediction modeling strategies, including iterated strategy, direct strategy and multiple-input multiple-output (MIMO) strategy, was conducted using the weekly ILI rate series from both the Southern and Northern China. The results show that: (1) The MIMO strategy achieves the best multi-step-ahead prediction, and is potentially more adaptive for longer horizon; (2) The iterated strategy demonstrates special potentials for deriving the least time difference between the occurrence of the predicted peak value and the true peak value of an influenza outbreak; (3) For ILI in the Northern China, SVR model implemented with MIMO strategy performs best, and SVR with iterated strategy also shows remarkable performance especially during outbreak periods; while for ILI in the Southern China, both SVR and MLP models with MIMO strategy have competitive prediction performance

States play a central role in systematic studies of agrarian changes in East Asia, South Asia and Southeast Asia. However, due to China’s belated agrarian change, agrarian studies on China have only begun recently, and the role of the state is still relatively undiscussed. First, we review the history of state intervention on agricultural development. Then we focus on fiscal policies of the state’s intervention that have been implemented since the taxes and fees reforms, which involved a large number of state agricultural projects. Such state intervention is aimed at promoting food security and agricultural modernization and, in practice, is typically accompanied by land transfer promoted by local government. The local governments’ intervention has directly resulted in the emergence of capitalized family farms and the flow of industrial/commercial capital to the countryside, both of which constitute main aspects of China’s agrarian transition. Based on a case study of a county in Hunan Province, focusing on examples of the food security project and the agricultural vertical integration project, combining with the process of land transfer promoted by local government, we analyse the role of the state in the emergence of capitalized family farms and capital flow to the countryside, as well as connections between state interventions and capital accumulation. Then, we present the general development of capitalized family farms as well as the flow of agro-capital to the countryside based on provincial data, and interpret how agrarian transition evolves at a different pace among regions against the backdrop of state intervention. We emphasize the internal mechanism between state intervention and agrarian transformation based on the operation of specific agricultural projects and the local governments’ promotion of land transfer.

Roughly a decade ago, the Chinese government implemented a green credit policy aimed at lowering emissions from highly polluting corporations through improving information disclosure quality during the loan process. According to policy guidelines, banks may provide financial support only for new projects that passed an environmental assessment or were explicitly designed to decrease pollution. This paper used panel data from 320 companies in heavy polluting industries listed on the Shanghai Stock Exchange from 2008 to 2016 and adopted a fixed effects regression model to examine whether collusion between local governments and Chinese listed companies has prevented the green credit policy from achieving its target. The results show that there is no significant positive correlation between CEID and corporate green financing, which means that the environmental information disclosure system does not send valuable signals to the market and has failed to become a decision-making tool for bank-risk management.

Recovery of acute insulin response (AIR) is shown to be associated with long-term outcomes of patients with early type 2 diabetes treated with short-term intensive insulin therapy (SIIT). However, the complexity of measuring an AIR limits its utility in a real-world clinical setting. The aim of the study was to assess fasting indicators that may estimate recovery of the AIR after SIIT. We enrolled 62 patients with type 2 diabetes mellitus (T2DM) of varying disease duration who had poor glycemic control. Participants were treated with SIIT using insulin pumps to achieve near normoglycemia for 7 days. The AIR before and after the therapy were measured by intravenous glucose tolerance tests. After the therapy, AIR increased from −16.7 (−117.4, 52.4) pmol/L·min to 178.7 (31.8, 390.7) pmol/L·min (P<0.001) while hyperglycemia was alleviated; this improvement was observed in all disease duration categories. AIR was almost absent when fasting plasma glucose (FPG) > 10 mmol/L, while both AIR (R=−0.53, P<0.001) and its improvement from baseline (△AIR, R=−0.52, P<0.001) were negatively associated with FPG after SIIT when FPG

Objective: In patients with early type 2 diabetes, short-term intensive insulin therapy (SIIT) reverses ß cell dysfunction measured by acute insulin response (AIR). However, the complicated procedures limit large-scale use of AIR. Also unclear is whether SIIT is effective in patients with longer duration. This study is performed to assess fasting indicators estimating recovery of AIR after SIIT for type 2 diabetes of various duration. Research Design and Methods: Patients with type 2 diabetes (n=62) who had poor glycemic control were enrolled. Near-nomoglycaemia was achieved and maintained for 7 days with insulin pump. AIR was measured by intravenous tolerance tests before and after SIIT. Results: Both fasting plasma glucose (FPG, 12.0 ± 3.0 vs. 7.71± 1.6 mmol/L, P6 years respectively, P=0.10). AIR was almost absent when FPG was over 10 mmol/L. However, when FPG after SIIT was less than 10 mmol/L it was negatively associated with AIR (R= -0.53, P Conclusions: Recovery of AIR could be obtained in patients with various duration of type 2 diabetes, and it could be estimated conveniently by FPG and other fasting indicators. Disclosure L. Liu: None. S. Yang: None. J. Liu: None. L. Hai: None. J. Liu: None. Y. Li: None.

Meme, as defined in Dawkins' 1976 book 'The Selfish Gene', is "an idea, behaviour or style that spreads from person to person within a culture". Internet meme is an extension of meme, with the defining characteristic being its spread via Internet. While online communities of all cultures generate their own memes, owing to the colossal amount of content in English and the long & widespread adoption of Internet across all strata of society in English-speaking countries, the vast majority of high-impact and well-documented memes have their origin in English-speaking communities. In addition to their spread in the original culture sphere, some of these prominent memes have also crossed the cultural boundaries and entered the parlance of Chinese Internet communities. This paper seeks to give a brief introduction to Internet memes in general, and explore the factors that control and/or facilitate a meme’s ability to enter Chinese communities.