The development of flexible, wearable electronic devices is one of the future directions of technology development. Flexible conductive materials are important supporting materials for wearable electronic devices. Polymer has excellent flexibility; it is an important way to prepare flexible conductors from polymer-based conductive composites. In this paper, the research progress of polymer-based flexible conductive composites is summarized in terms of preparation and characterization methods. The key factors to realize flexible conductors are put forward, namely, the maintenance of excellent polymer elasticity and the realization of stability. The design and preparation of the extensible conductor with high-elasticity matrix and nanofiller are introduced in detail, and the problems in the current research are summarized.

Benzoxazine resin, a new type of phenolic resin, has many advantages, such as a strong molecular design, no small molecular release in the curing process, excellent thermal stability and mechanical properties, and a high residual carbon ratio. Thus, it is important for electronic communication industry matrix material. To meet the needs of high-frequency and high-speed communication technology for low-dielectric polymer resin, the low-dielectric modification of benzoxazine resin is of great significance to the high frequency and high-speed propagation of the signal, which attracts a wide range of materials researchers’ attention. In this paper, we review a series of studies on the low dielectric modification of benzoxazine resin in recent years, including the synthesis of new monomers, inorganic - organic hybridization, copolymerization with other resins, and low molecular weight benzoxazine resin research trends.

In order to improve the quality and efficiency of heat treatment in welds of power stations, this paper summarizes the current situation of 600 MW supercritical power plant welding site heat treatment and puts forward the improved methods and measures accordingly. The heat treatment of welding holes in the construction site Play a certain guiding role.

This paper mainly uses the idea of pedigree clustering analysis, gray prediction and principal component analysis. The clustering analysis model, GM (1,1) model and principal component analysis model were established by using SPSS software to analyze the correlation matrices and principal component analysis. MATLAB software was used to calculate the correlation matrices. In January, The difference in price changes of major food prices in cities is calculated, and had forecasted the various food prices in June 2016. For the first issue, the main food is classified and the data are processed. After that, the SPSS software is used to classify the 27 kinds of food into four categories by using the pedigree cluster analysis model and the system clustering. The four categories are made by EXCEL. The price of food changes over time with a line chart that analyzes the characteristics of food price volatility. For the second issue, the gray prediction model is established based on the food classification of each kind of food price. First, the original data is cumulated, test and processed, so that the data have a strong regularity, and then establish a gray differential equation, and then use MATLAB software to solve the model. And then the residual test and post-check test, have C <0.35, the prediction accuracy is better. Finally, predict the price trend in June 2016 through the function. For the third issue, we analyzed the main components of 27 kinds of food types by celery, octopus, chicken (white striped chicken), duck and Chinese cabbage by using the data of principal given and analyzed by principal component analysis. It can be detected by measuring a small amount of food, this predict CPI value relatively accurate. Through the study of the characteristics of the region, select Shanghai and Shenyang, by looking for the relevant CPI and food price data, using spss software, principal component analysis, the impact of the CPI on several types of food, and then calculated by matlab algorithm weight, and then the data obtained by the analysis and comparison, different regions should be selected for different types of food for testing.

The project of returning farmland to forest is a new project of increasing farmers' income, ecological efficiency and

benefiting the country. The key to the success of returning farmland to forest project is to strictly control the key technologies such as regional planning, forest species selection, tree species selection, good seedling, structural configuration, meticulous soil preparation, serious planting, tending and management. According to the actual

situation of Yuanling County, suitable for the tree, choose the market prospects, fast-growing tree species afforestation,

reasonable adjustment of forest structure, ecological benefits and economic benefits simultaneously, take high-

quality high-yield and efficient forestry development. Returning farmland to forest project has played huge ecological benefits, economic and social benefits.

Nowadays, more and more cars have begun to enter into innumerable families; the family car has become a necessity for Chinese households who have certain purchasing power. However, the ups and downs of oil prices have brought some impact on people's automobile consumption activities. Therefore, after collecting the information of the oil price and family car consumer, carried on through in-depth analysis of the relevant data with reasonable relationship, and then developed a suitable for China's national conditions and finished oil pricing model, thereby the National Development and Reform Commission have proposed the suggestion for China's refined oil pricing mechanisms and promoting the healthy development of new energy vehicles with specific measures. For question 1, through the problem analysis and information access, combined with the past and current situation of the domestic refined oil prices, we analyze the following seven factors: international crude oil prices, China's annual crude oil imports, China's annual crude oil exports, crude oil output in China, China's annual GDP per capita, China's annual consumption of crude oil, the total annual energy consumption in China, all have influence on China's refined oil prices. By monadic linear regression analysis, annual average prices of domestic refined oil products have a certain correlation with the various influencing factors, and then by multiple linear regression way eventually concluded the final relationship between oil prices and the influence factors, which compared with the current price, and make reasonable evaluation model. Through the establishment of various influencing factors and function of time, and using the evaluation model for refined oil product price to make reasonable forecast. According to this model, in order to predict refined oil product price as $122.15 per barrel in 2016. For question two, we basically sums up three key factor which influence the quantity of family vehicle: China's oil product prices, the annual GDP per capita, total road mileage. Through Excel to make the relationship curves of different quantity of family cars against influencing factors, and use Grey Forecasting method to forecast the quantity of family cars. And carries on the residual error test, it is used to conclude that the rationality of the model is highly. The number of private cars of the city of xi 'an is predicts that to 8.302 million vehicles by 2020. For question three, we discussed the relationship between international crude oil prices and domestic exports of crude oil export with domestic refined oil prices, through its multiple linear regressions to get the final pricing model. For question four, according to three previous established models, we proposed China's refined oil pricing mechanism proposal to the national development and Reform Commission: perfect price controls, deeper product market, and integration of resources consideration and environmental protection class tax types, adjust the consumption tax collection and Administration links, and improve the production cost accounting.