Application of HACCP in Producting Process of Tartary Buckwheat

Food safely has always been the focus of consumer＇s attention since the successful accession of China to the WTO ,and many Chinese food processing enterprises have transformed from small workshop into a large-scale modern enterprises capable of processing continuously ,which requires us to constantly update and improve a series of food safety control system,In this paper,we studied the application of HACCP system in the manufacturing process of tartary buchwheat tea and analyzed hazards in the process of bitter buckwheat tea,and concluded that purchase of raw material,screening and grading ,soaking,cooking ,drying and sterilization ,shelling,packaging and storage of ginished product are eight links as critical control points ,Based on this,corrective measures were proposed,and a detailed HACCP plan was developed.

Mapping scientific cooperation of the NSFC:A case study of Major International(Regional) Joint Research Program

International cooperations have played an important role in academic activities as more and more researchers endeavor to participate in joint research or exchange with partners aboard. Focused on projects of Major International(Regional) Joint Research Program of the Natural Science Foundation of China(NSFC) from 2003 to 2008, we have investigated the characteristics of the scientific cooperation by mapping the funded projects from the aspects of topics, affiliations and cooperative countries(regions), respectively.Moreover, it is demonstrated that issues related to nano technologies, genes and ecological environments have become the hot topics in the joint research of NSFC, and projects with issues of big science have been preferentially funded under the program’s guide posted every year. Moreover, most granted projects were undertaken by the minority of affiliations with the leading research capability, which is the same to partners abroad. The aggregation effect has been greatly improved with the bilateral or multilateral agreement signed with scientific organizations abroad, so has the competitive mechanism of scientific resources allocation.

The Threshold Effect of Rationalization of Industrial Structure on Air Quality in Shanxi Province

Shanxi Province is a typical resource-based region. After years of economic transformation, the air quality has been at a low level for a long time. The rationalization of industrial structure can measure the effect of economic transformation and whether it has an important impact on air quality. Therefore, it is necessary to study the non-linear impact that the rationalization of industrial structure has had on air quality at different stages, which is of positive significance for the continuing transformation and upgrading of resource-based regions. This study constructs a threshold regression model based on the panel data of 11 provincial cities in Shanxi Province from 2004 to 2016. The results show that the rationalization of industrial structure had a double threshold effect on air quality under different threshold variables. On the whole, optimizing the rationalization of industrial structure in Shanxi Province can improve air quality, and the improvement effect dropped first, and then began to rise. As a result, the current energy transformation and upgrading process should focus on the rationalization of industrial structure to solve the conflict between air quality and economic development.

Forecasting Gas Consumption Based on a Residual Auto-Regression Model and Kalman Filtering Algorithm

Consumption of clean energy has been increasing in China.Forecasting gas consumption is important to adjusting the energy consumption structure in the future.Based on historical data of gas consumption from 1980 to 2017,this paper presents a weight method of the inverse deviation of fitted value,and a combined forecast based on a residual auto-regression model and Kalman filtering algorithm is used to forecast gas consumption.Our results show that:(1)The combination forecast is of higher precision:the relative errors of the residual auto-regressive model,the Kalman filtering algorithm and the combination model are within the range(–0.08,0.09),(–0.09,0.32)and(–0.03,0.11),respectively.(2)The combination forecast is of greater stability:the variance of relative error of the residual auto-regressive model,the Kalman filtering algorithm and the combination model are 0.002,0.007 and 0.001,respectively.(3)Provided that other conditions are invariant,the predicted value of gas consumption in 2018 is 241.81×10~9 m^3.Compared to other time-series forecasting methods,this combined model is less restrictive,performs well and the result is more credible.