A novel ruthenium(Ⅱ)?catalyzed C-H/C-N annulation of 1?phenyl?2?pyrazolin?5?one with ethylene carbonate was designed. In this transformation, the vinylene carbonate acts as an ethynol or alkyne surrogate without any external oxidant as well as bases involved. The reaction exhibits a broad substrate scope with excellent functional group compatibility, affording a series of 1H?pyrazolo[1,2?a]cinnolin?1?ones in 42%~87% yields. A possible mechanism involving a sequential C-H activation/intramolecular C-N bond formation/ CO₂ or CO {}_{\mathrm{3}}^{\mathrm{2}-} elimination is proposed. In addition, the reaction can also be carried out on a gram scale with satisfactory yield.

A mononuclear Cu complex Cu_0.5(4,4'?bipy)(H₂O)·L·0.5(4,4'?bipy)·2H₂O (1) was obtained by hydrothermal reaction with Cu²⁺ as the central ion and 4,4'?bipy as the nitrogen?containing auxiliary ligand. Its structure and composition were characterized by modern characterization methods, such as X?ray single crystal diffraction, elemental analysis and infrared spectrum. The results show that Cu²⁺ is six coordinated with four nitrogen atoms of 4,4'?bipy molecules and two oxygen atoms of H₂O molecules, showing a distorted octahedral coordination configuration. L^2- anion only balances the positive charges in compound 1 and does not participate in the coordination of metal Cu²⁺. Cu²⁺ coordinates with 4,4'?bipy and H₂O molecules to form a lattice layered structure [Cu(4,4'?bipy)₂(H₂O)₂]²⁺, the hydroxyl group of L^2- anion and free H₂O molecules form hydrogen bonds with H₂O molecules in the layered structure respectively, which increases the thermal stability of H₂O molecules in compound 1. The fluorescence emission of compound 1 is at 409 nm, which can be attributed to the intraligand emission state. Compared with the ligand, there is a slight red shift, which may be caused by the coordination between 4,4'? bipy ligand and Cu²⁺.

Taking advantage of its high?speed and high?precision characteristics, cooperative robots can improve production efficiency by imitating human creative and complex actions. At present, the simulation of human action mainly comes from the long?term debugging of the deployment personnel, which is lack of general solutions and can′t be deployed quickly. Based on this, an anchor?free RepVGG network?based Siamese network collaborative robot target tracking algorithm was proposed. The algorithm consists of a siamese network module, a classification regression module and a robot execution module. The siamese network module used the improved RepVGG network instead of ResNet as the backbone network to extract image features, which can improve the running speed of the whole network without losing accuracy，reduce the hardware requirements and is more friendly to special deep learning chips; the classification and regression module introduced the centrality branch to improve the prediction accuracy of the center point of the tracking frame; the robot execution module uses scale penalty and aspect ratio penalty to smooth the tracking boxes and ensure the smooth operation of the collaborative robots. Experimental results show that the average rate is 14 FPS higher than that before replacing the backbone network, which realizes real?time object tracking.