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Effects of iletamine-zolazepam-xylazine-tramadol combination on biochemical and haematological parameters in cats

100%

Li L. , Dong J. , Lu D. , Jiang S. , Lin D. , Fan H.

nr 3

Cats were injected with 2.4 mg/kg of tiletamine-zolazepam, 0.36 mg/kg of xylazine, and 0.8 mg/kg of tramadol, then blood was collected from their peripheral veins at 0.5, 1, 4, 8, 24, 48, 72, and 168 h after the injection. Before injection, the same cats were used as control group (0 h). Biochemical and haematological parameters were measured. The results revealed that the combination of the compounds produced good immobilisation, with minimal changes over time in biochemical and haematological parameters, which were within biologically acceptable limits.

A novel method for 3D measurement of RFID multi-tag network using a machine vision system

100%

Zhuang X. , Yu X. , Zhao Z. , Zhang W. , Liu Z. , Lu D. , Dong D.

tom Vol. 25, nr 3

475--486

The three-dimensional (3D) coordinate measurement of radio frequency identification (RFID) multi-tag networks is one of the important issues in the field of RFID, which affects the reading performance of RFID multi-tag networks. In this paper, a novel method for 3D coordinate measurement of RFID multi-tag networks is proposed. A dual-CCD system (vertical and horizontal cameras) is used to obtain images of RFID multi-tag networks from different angles. The iterative threshold segmentation and the morphological filtering method are used to process the images. The template matching method is respectively used to determine the two-dimensional (2D) coordinate and the vertical coordinate of each tag. After that, the 3D coordinate of each tag is obtained. Finally, a back-propagation (BP) neural network is used to model the nonlinear relationship between the RFID multi-tag network and the corresponding reading distance. The BP neural network can predict the reading distances of unknown tag groups and find out the optimal distribution structure of the tag groups corresponding to the maximum reading distance. In the future work, the corresponding in-depth research on the neural network to adjust the distribution of tags will be done.