Human Health Activity Recognition Algorithm in Wireless Sensor Networks Based on Metric Learning.

Wireless sensor network is an ad hoc network with sensing capability. Usually, a large number of sensor nodes are randomly deployed in an unreachable environment or complex area for data collection and transmission, which can realize the perception and monitoring of the target area or specific objects and transmit the obtained data to the remote end of the system. Human health activity recognition algorithm is a hot topic in the field of computer. Based on the small sample problem and the linear indivisibility of real samples encountered in metric learning, this paper proposes a human activity recognition algorithm for wireless sensor networks. Human activity recognition algorithm for wireless sensor networks uses human activity recognition algorithm to solve the singularity of intraclass divergence matrix, so as to reduce the impact of small sample problem. The algorithm maps two different feature spaces to the high-dimensional linearly separable kernel space through the corresponding kernel function, calculates the distance between samples in the two projected feature subspaces to obtain two distance measurement functions, and finally linearly combines them with weights to obtain the final distance measurement function.

Simultaneous determination of the novel tyrosine kinase inhibitor meditinib and its active metabolite demethylation meditinib in monkey plasma by liquid chromatography-tandem mass spectrometry and its application to pharmacokinetic studies.

Meditinib (ME) is a novel tyrosine kinase inhibitor used as an antichronic myeloid leukemia drug. A simple, sensitive and specific LC/MS/MS method was developed and validated for the analysis of ME and its metabolite demethylation meditinib (PI) in monkey plasma using naltrexone as the internal standard. Sample preparation involved protein precipitation with methanol. The analysis was carried out on an Agilent C8 column (3.5 µm, 2.1 × 50 mm). Elution was achieved with a mobile phase gradient varying the proportion of a water solution containing 0.1% formic acid (solvent A) and a 0.1% formic acid in methanol solution (solvent B) at a flow rate of 300 µL/min. The method had a linear calibration curve over the concentration range of 2-1000 ng/mL for ME and 2-1000 ng/mL for PI. The lower limits of quantification of ME and PI were 2 and 2 ng/mL, respectively. The intra- and inter-day precision values were <15% and accuracy values were within ±10.0%. The mean recoveries of ME and PI from plasma were >85%. The assay has been successfully used for pharmacokinetic evaluation of ME and PI using the monkey as an animal model, and those data are reported for the first time.