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Northeast China Produces An Abundance of Maize (Zea Mays L.), and Improvement of Maize Yield At This Region Correlates Closely With Ensure Food Supply Safely of China. in Recent Years, Deficiency Or Relative Deficiency of Potassium (K) in The Soil Is An Important Limitation To Maize Production. Maize inbred Lines Tolerant To K Deficiency (T) and Sensitive To K Deficiency (C) Were Hydroponically Grown in 1/2 Hoagland Solution To Study The Possible Mechanism of Maize Tolerance To Potassium Deficiency From Physiological Point of View. With The Reduction of K+ Concentration, Dw of The Plant Became Apparently Greater in T Than in C, The Symptom of Potassium Deficiency Advanced in C. Under K Deficiency, The Taproot Elongation increased and Root Top Ratio Decreased To A Greater Degree in C Than in T, C Had Fawer Lateral Roots. T Had A Stronger K+-Uptake Ability Than C, and The Difference Was More Obvious in Culture Solution With A Lower K+ Concentrations of Culture Solution. K+ Dependent H+ Extrusion From The Root Treated With K+ Deficiency Was Larger in T Than in C.

In order to further improve the automation setting of distribution system, this paper proposes an optimization research of distribution automation system based on artificial intelligence wireless network technology. This method uses artificial intelligence wireless network technology to optimize the automation of distribution system and improve the automation ability of distribution system. The experimental results show that when the number of iterations in the training process reaches 338, the mean square error is 0.001. Conclusion. The optimization research method of distribution automation system based on artificial intelligence wireless network technology can more effectively improve the automation level of distribution system. [ABSTRACT FROM AUTHOR]

Based on the working principle of high-speed electromagnetic repulsion mechanism, the main factors influencing the motion characteristics of the repulsion mechanism and their variation rules are analyzed and verified through calculation and simulation. Because of its fast moving speed and large kinetic energy of moving parts, it will produce large operating impact and bounce. Buffer performance is of great significance to the safe and reliable operation of high-voltage circuit breakers. Moreover, aiming at the above problems, this article studies the repulsive mechanism and its buffer problem. First, the mathematical model of the electromagnetic repulsive opening mechanism is established, and the electromagnetic repulsive force of the electromagnetic repulsive opening mechanism is deduced. The simplified model of the electromagnetic repulsive mechanism and the finite element simulation mesh are divided, and the discharge circuit model of the energy storage capacitor is designed. Then, the simulation results show that as the repulsion disk spacing, radius, storage, capacitor voltage, turn ratio, and other parameters adjust, the peak value of electromagnetic repulsion force increases, which can reach more than 60 kN, and the displacement of the mechanism can reach 84 mm within 5.5 ms. Finally, the drop weight contrast test is carried out. When the landing height is 300 mm, 500 mm, and 700 mm, respectively, the energy absorption rate of the buffer in the three groups of tests is higher than 85%. Through the speed curve simulation after the installation of buffer, it is verified that the elastic clay buffer is suitable for the buffer mode of fast switch, and a high-speed buffer device based on the elastic clay material is proposed. [ABSTRACT FROM AUTHOR]

In this article, we take a 126 kV single-break vacuum circuit breaker as the research object and study the application of high-energy-density PM motor in the high-voltage circuit breaker for the first time. The PM motor maintains maximum power density and torque density during the start-up phase. Note that most of the faults of high-voltage circuit breakers are mechanical faults. We designed a set of mechanical fault prediction systems for high-voltage circuit breakers. We present the prediction method of the opening and closing action curve of the high-voltage circuit breaker. It is inspired by Chaos Ant Colony Algorithm (CAS) and an optimized Long- and Short-Term Memory (LSTM) cycle neural network. We constructed the main structure of the neural network expert system and established the fault prediction model of the high-voltage circuit breaker, based on the LSTM cycle neural network, optimized by CAS. We used the improved least-square method to achieve the operation accuracy of the phase control switch. Finally, we completed the development and experiment of the prototype. [ABSTRACT FROM AUTHOR]