Abstract: Disclosed in the present application are an anomaly recognition method and an anomaly recognition system for tracks of trucks. The method includes: obtaining a running track T according to global positioning system (GPS) data of running of a truck to be recognized; employing a track compression algorithm for the running track T to obtain a compressed track set C; employing a density-based clustering algorithm and performing grouping according to set time periods to obtain a network graph representing a motion track of each time period; inputting the network graph into a track embedding model established and trained in advance to obtain an explicit embedding vector corresponding to each network graph; and determining stability according to a distance between the vectors, and classifying points with the stability lower than a set threshold as abnormal tracks. The track embedding model is realized by employing a Skipgram model on the basis of a graph2vec algorithm.

Abstract: Described herein are methods and compositions for point of care droplet digital PCR (ddPCR) using large uniform droplets that can be visually analyzed for detection. In one embodiment, the ddPCR reaction is prepared by dispensing a plurality of large uniform droplets using a modified pipette tip having a specific aspect ratio and one or more surfactants in the aqueous phase.

Abstract: Methods for preparing electrolyte salts for alkaline earth metal-ion batteries (e.g., calcium and magnesium ion batteries) are described. The electrolyte salts comprise alkaline earth metal (e.g., Mg or Ca) salts of bis(fluorosulfonyl)imide (FSI) and 3,4-dicyano-2-trifluoromethylimidazole (TDI). The methods comprise contacting FSI or TDI with an alkaline earth metal bis(trifluoroacetate) salt in trifluoroacetic acid.