Human Activity Recognition Based on R Transform

This paper addresses human activity recognition based on a new feature descriptor. For a binary human silhouette, an extended radon transform, transform, is employed to represent low-level features. The advantage of the trans-form lies in its low computational complexity and geomet-ric invariance. Then a set of HMMs based on the extracted features are trained to recognize activities. Compared with other commonly-used feature descriptors, transform is robust to frame loss in video, disjoint silhouettes and holes in the shape, and thus achieves better performance in rec-ognizing similar activities. Rich experiments have proved the efficiency of the proposed method. 1

Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks

Convolutional residual neural networks (ConvResNets), though overparameterized, can achieve remarkable prediction performance in practice, which cannot be well explained by conventional wisdom. To bridge this gap, we study the performance of ConvResNeXts, which cover ConvResNets as a special case, trained with weight decay from the perspective of nonparametric classification. Our analysis allows for infinitely many building blocks in ConvResNeXts, and shows that weight decay implicitly enforces sparsity on these blocks. Specifically, we consider a smooth target function supported on a low-dimensional manifold, then prove that ConvResNeXts can adapt to the function smoothness and low-dimensional structures and efficiently learn the function without suffering from the curse of dimensionality. Our findings partially justify the advantage of overparameterized ConvResNeXts over conventional machine learning models.Comment: 20 pages, 1 figur

Pharmacokinetics and tissue distribution of N-3- methoxybenzyl-palmitamide in rat: A macamide derived from Lepidium meyenii

Purpose: To study the pharmacokinetics and tissue distribution of N-3-methoxybenzyl-palmitamide (MPM) derived from Lepidium meyenii (Maca)Methods: MPM and N-benzylpalmitamide (BPM, as the internal standard, IS) were prepared by one-pot synthesis method and characterized. For the analysis of MPM in rat plasma and tissue samples, a rapid ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) method was developed and validated by optimizing sample preparation conditions and UPLC conditions. Finally, the pharmacokinetics and biodistribution of MPM after oral administration in rats were studied.Results: The lower limit of quantification (LLOQ) and limit of detection (LOD) of the UPLC-MS/MS method were 1.2 and 5.0 ng/mL, respectively. Good linear relationship of calibration curve (r > 0.9951) was achieved over the range of 5 – 5000 ng/mL. In pharmacokinetics, plasma concentration-time curve of MPM showed double peaks. The highest distribution of MPM after absorption was in the stomach, followed by lung. The absorption and eliminate rate of MPM were slow in rats. In fact, MPM displayed a lung targeting property.Conclusion: The developed UPLC-MS/MS method is suitable for plasma and tissue distribution studies of MPM in rats. The present study can provide guidance for the further development and utilization of Maca tuber.Keywords: Macamide, Maca tuber, Lepidium meyenii, Pharmacokinetics, Tissue distribution, UPLCMS/M