Coherent Online Video Style Transfer

Training a feed-forward network for fast neural style transfer of images is proven to be successful. However, the naive extension to process video frame by frame is prone to producing flickering results. We propose the first end-to-end network for online video style transfer, which generates temporally coherent stylized video sequences in near real-time. Two key ideas include an efficient network by incorporating short-term coherence, and propagating short-term coherence to long-term, which ensures the consistency over larger period of time. Our network can incorporate different image stylization networks. We show that the proposed method clearly outperforms the per-frame baseline both qualitatively and quantitatively. Moreover, it can achieve visually comparable coherence to optimization-based video style transfer, but is three orders of magnitudes faster in runtime.Comment: Corrected typo

Оценка накопления изотопов плутония в ОЯТ при переходе на микротопливо в реакторе ВВЭР

The Selective Laser Melting (SLM) Rapid Manufacturing (RM) of the high-energy ball milled Ti-Si3N4 composite powder with the mol ratio of 9:1 was performed in the present work. The microstructural characterizations revealed the formation of TiN reinforced Ti5Si3 matrix composites after laser processing via the in-situ synthesis reaction 9Ti+Si3N4=4TiN+Ti5Si3. The in-situ presented TiN reinforcing phase possessed a refined granular morphology and a uniform distribution throughout the Ti5Si3 matrix, showing a clear and compatible interfacial structure with the matrix. The metallurgical mechanisms for the in-situ synthesis of TiN reinforced Ti5Si3 matrix composites by SLM were also proposed

Depth-Based Subgraph Convolutional Neural Networks

This paper proposes a new graph convolutional neural network architecture based on a depth-based representation of graph structure deriving from quantum walks, which we refer to as the quantum-based subgraph convolutional neural network (QS-CNNs). This new architecture captures both the global topological structure and the local connectivity structure within a graph. Specifically, we commence by establishing a family of K-layer expansion subgraphs for each vertex of a graph by quantum walks, which captures the global topological arrangement information for substructures contained within a graph. We then design a set of fixed-size convolution filters over the subgraphs, which helps to characterise multi-scale patterns residing in the data. The idea is to apply convolution filters sliding over the entire set of subgraphs rooted at a vertex to extract the local features analogous to the standard convolution operation on grid data. Experiments on eight graph-structured datasets demonstrate that QS-CNNs architecture is capable of outperforming fourteen state-of-the-art methods for the tasks of node classification and graph classification

Genome-wide analysis of plant nat-siRNAs reveals insights into their distribution, biogenesis and function

Background: Many eukaryotic genomes encode cis-natural antisense transcripts (cis-NATs). Sense and antisense transcripts may form double-stranded RNAs that are processed by the RNA interference machinery into small interfering RNAs (siRNAs). A few so-called nat-siRNAs have been reported in plants, mammals, Drosophila, and yeasts. However, many questions remain regarding the features and biogenesis of nat-siRNAs. Results: Through deep sequencing, we identified more than 17,000 unique siRNAs corresponding to cis-NATs from biotic and abiotic stress-challenged Arabidopsis thaliana and 56,000 from abiotic stress-treated rice. These siRNAs were enriched in the overlapping regions of NATs and exhibited either site-specific or distributed patterns, often with strand bias. Out of 1,439 and 767 cis-NAT pairs identified in Arabidopsis and rice, respectively, 84 and 119 could generate at least 10 siRNAs per million reads from the overlapping regions. Among them, 16 cis-NAT pairs from Arabidopsis and 34 from rice gave rise to nat-siRNAs exclusively in the overlap regions. Genetic analysis showed that the overlapping double-stranded RNAs could be processed by Dicer-like 1 (DCL1) and/or DCL3. The DCL3-dependent nat-siRNAs were also dependent on RNA-dependent RNA polymerase 2 (RDR2) and plant-specific RNA polymerase IV (PoIIV), whereas only a fraction of DCL1-dependent nat-siRNAs was RDR- and PoIIV-dependent. Furthermore, the levels of some nat-siRNAs were regulated by specific biotic or abiotic stress conditions in Arabidopsis and rice. Conclusions: Our results suggest that nat-siRNAs display distinct distribution patterns and are generated by DCL1 and/or DCL3. Our analysis further supported the existence of nat-siRNAs in plants and advanced our understanding of their characteristics.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000308544200005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Biotechnology & Applied MicrobiologyGenetics & HereditySCI(E)48ARTICLE3null1