No abstract

The ionic liquid [H3N+CH2CH2OH][CH3COO-] (HEAA) catalyzes a three-component, one-pot condensation of malononitrile/ethyl cyanoacetate, 1,3-dicarbonyl compound/enol, and quinone or ninhydrin in water to afford a spiropyran derivative. This method has advantages of mild reaction conditions, short reaction time, and environmental friendliness.

No abstract

This chapter presents a framework for studying the effect of national and international investments (which include the flow of germplasm between the international agricultural research centres and China's national agricultural research system) on research and extension in China, focusing on rice, wheat and maize, and discusses the impact of such investments on the development of productivity-increasing technology.

A model for predicting wax deposition rate in pipeline transportation is constructed to predict wax deposition in actual pipeline, which can provide decision support for the flow guarantee of waxy crude oil in pipeline transportation. This paper analyzes the working principle of Back Propagation Neural Networks (BPNN). Aiming at the problems of BPNN model, such as over learning, long training time, low generalization ability and easy to fall into local minimum, the paper proposes an improved scheme of using Whale Optimization Algorithm (WOA) to optimize BPNN model(WOA-BPNN).Taking 38 groups of crude oil wax deposition experimental data in Huachi operation area as an example, the simulation calculation is carried out in MATLAB, and the Genetic Algorithm optimized BPNN(GA-BPNN) and the non Optimized BP neural network are used as comparative models for comparative analysis. The results show that the Mean Relative Error (MRE) of WOA-BPNN model in predicting wax deposition rate is 2.72% and the coefficient of determination(R 2 ) is 0.9966, which are better than those of BPNN and GA-BPNN models. It is proved that WOA-BPNN model has higher accuracy and robustness in predicting wax deposition rate.