Two-stream network architecture has the ability to capture temporal and spatial features from videos simultaneously and has achieved excellent performance on video action recognition tasks. However, there is a fair amount of redundant information in both temporal and spatial dimensions in videos, which increases the complexity of network learning. To solve this problem, we propose residual spatial-temporal attention network (R-STAN), a feed-forward convolutional neural network using residual learning and spatial-temporal attention mechanism for video action recognition, which makes the network focus more on discriminative temporal and spatial features. In our R-STAN, each stream is constructed by stacking residual spatial-temporal attention blocks (R-STAB), the spatial-temporal attention modules integrated in the residual blocks have the ability to generate attention-aware features along temporal and spatial dimensions, which largely reduce the redundant information. Together with the specific characteristic of residual learning, we are able to construct a very deep network for learning spatial-temporal information in videos. With the layers going deeper, the attention-aware features from the different R-STABs can change adaptively. We validate our R-STAN through a large number of experiments on UCF101 and HMDB51 datasets. Our experiments show that our proposed network combined with residual learning and spatial-temporal attention mechanism contributes substantially to the performance of video action recognition.
This study used cellulose-and amylose-based chiral stationary phases to comparatively separate crufomate enantiomers on reverse-phase and normal-phase high performance liquid chromatography (RP-HPLC and NP-HPLC). The baseline separations were obtained on Phenomene Lux cellulose-1, Lux cellulose-2 and Lux amylose-2 with 2-propanol/hexane and on Lux cellulose-1 and Lux amylose-2 with acetonitrile/water as mobile phase. The results of optical rotation detections showed that (+)-enantiomer of crufomate was firstly eluted on Lux cellulose-1 and Lux amylose-2 both on NP-HPLC and RP-HPLC, while the (-)-enantiomer was firstly eluted on Lux cellulose-2 and Lux cellulose-3 on NP-HPLC. The influences of column temperature from 5-40 ºC on separation were investigated on three chiral stationary phases. The thermodynamic parameters were calculated using van't Hoff equations to study the enthalpy-driven and entropy-driven process. This work will be helpful to prepare optical pure enantiomers and establish efficient analytical method for study on enantioselective behaviours of crufomate.
Cucumber, Cucumis sativus is one of the most cultivated vegetables in the world, which is mostly consumed raw in China. The complete chloroplast genome of C. sativus was assembled and annotated in this study. Its size was 155,525 bp, containing a large single-copy region of 86,878 bp, a small singlecopy region of 18,269 bp and a pair of IR regions of 25,189 bp. Whole chloroplast genome of C. sativus contains 131 genes, including 77 protein-coding genes (PCGs), 46 transfer RNA genes (tRNAs), and 8 ribosome RNA genes (rRNAs). The overall nucleotide composition is: A of 31.1%, T of 31.9%, C of 18.8% and G of 18.2%, with a total GC content of the chloroplast genome 37.0% and AT of 63.0%. Genetic and phylogenetic analysis based on 10 plants species confirmed the position of C. sativus closely related to Cucurbitaceae species of Cucumis hystrix.
Using the information technology appropriately will positively affect the professional development of the teachers and, in turn, the educational reform towards the direction where we hope it to go. A survey about the teacher IT ability and training needs has been carried out from 2011-2013. More than 300 primary and middle school teachers are involved in our questionnaire and interview. Most of the teachers (76.84 percent) believe the improvement of the information literacy will be of great benefit their professional development.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.