A mobile robot path planning algorithm based on improved A*

Abstract Global path planning of mobile robot aims to provide a safe and smooth path for mobile robot navigation. Traditional A * algorithm is planning the path of more turns, and not smooth. Moreover, for the u-shaped terrain, the path stick to the obstacles. Aiming at the shortcomings of A* algorithm, cosine distance is selected as the heuristic function, and direction information is added and normalized. The 36-order neighborhood search matrix is selected to solve the problem of fitting u-bend. In addition, a post-processing method based on Bessel curve is proposed. Make the planned path curvature change continuously. Simulation results show the effectiveness of the improved algorithm.</jats:p

Metformin regulates the Th17/Treg balance by glycolysis with TIGAR in hepatic ischemia-reperfusion injury

The balance of Th17/Treg plays an important role in hepatic ischemia–reperfusion (I/R) injury. Glycolysis and glutaminolysis for energy metabolism governs the differentiate of CD 4+ T-cells to Th17/Treg. Metformin can regulate glucose metabolism in the liver, but its protective effect on I/R liver injury and its effect on Th17/Treg balancestill unknown. In this study, the I/R liver injury rat model and the primary hepatocyte hypoxia/reoxygenation injury model were established. The biochemical indexes, inflammatory factor indexes, Th17/Treg balance and energy metabolism were evaluated. RNA-seq and gene knockout cells were used to investigated the target protein of metformin. The results showed that metformin could effectively improve liver injury caused by I/R, significantly inhibit the glycolysis, improve the Th17/Treg balance, and inhibit the expression of inflammatory factors. RNA-seq results showed that TIGAR was a possible regulatory site of metformin. However, the protective effect and the regulating effect of Th17/Treg balance by metformin in TIGAR knock-out cells were disappeared. In conclusion, metformin could regulate TIGAR inhibit glycolysis then regulate Th17/Treg balance, inhibit the release of liver inflammatory factors, and finally play a role in inhibiting the occurrence of liver injury caused by ischemia-reperfusion

Convolutional neural network for real-time main transformer detection

Abstract For substation constructions, the main transformer is the dominant electrical equipment, and its arrival and operation affect the progress of project directly. In the context of smart grid construction, in order to improve the efficiency of real-time main transformer detection, this paper proposes an identification and detection method based on the SSD algorithm. The SSD algorithm is able to extract the target device (such as main transformer) accurately and the Lenet algorithm module can analyse the features contained in the image. To improve the accuracy of the detection method, the image migration algorithm of VGG-Net is used to expand the negative samples of main transformers to improve the generalisation of the algorithm. Finally, the image set collected in the real substation projects is used for validation, and result shows that the method identifies main transformers more accurately, with high effectiveness and feasibility.</jats:p