Hybrid Pixel-Unshuffled Network for Lightweight Image Super-Resolution

Convolutional neural network (CNN) has achieved great success on image super-resolution (SR). However, most deep CNN-based SR models take massive computations to obtain high performance. Downsampling features for multi-resolution fusion is an efficient and effective way to improve the performance of visual recognition. Still, it is counter-intuitive in the SR task, which needs to project a low-resolution input to high-resolution. In this paper, we propose a novel Hybrid Pixel-Unshuffled Network (HPUN) by introducing an efficient and effective downsampling module into the SR task. The network contains pixel-unshuffled downsampling and Self-Residual Depthwise Separable Convolutions. Specifically, we utilize pixel-unshuffle operation to downsample the input features and use grouped convolution to reduce the channels. Besides, we enhance the depthwise convolution's performance by adding the input feature to its output. Experiments on benchmark datasets show that our HPUN achieves and surpasses the state-of-the-art reconstruction performance with fewer parameters and computation costs

The association between Toll-like receptor 2 single-nucleotide polymorphisms and hepatocellular carcinoma susceptibility

<p>Abstract</p> <p>Background</p> <p>Toll-like receptors (TLR) are key innate immunity receptors participating in an immune response. Growing evidence suggests that mutations of TLR2/TLR9 gene are associated with the progress of cancers. The present study aimed to investigate the temporal relationship of single nucleotide polymorphisms (SNP) of TLR2/TLR9 and the risk of hepatocellular carcinoma (HCC).</p> <p>Methods</p> <p>In this single center-based case-control study, SNaPshot method was used to genotype sequence variants of TLR2 and TLR9 in 211 patients with HCC and 232 subjects as controls.</p> <p>Results</p> <p>Two synonymous SNPs in the exon of TLR2 were closely associated with risk of HCC. Compared with those carrying wild-type homozygous genotypes (T/T), risk of HCC decreased significantly in individuals carrying the heterozygous genotypes (C/T) of the rs3804099 (adjusted odds ratio (OR), 0.493, 95% CI 0.331 - 0.736, <it>P </it>< 0.01) and rs3804100 (adjusted OR, 0.509, 95% CI 0.342 - 0.759, <it>P </it>< 0.01). There was no significant association found in two TLR9 SNPs concerning the risk of HCC. The haplotype TT for TLR2 was associated significantly with the decreased risk of HCC (OR 0.524, 95% CI 0.394 - 0.697, <it>P </it>= 0.000). Inversely, the risk of HCC increased significantly in patients with the haplotype CC (OR 2.743, 95% CI 1.915 - 3.930, <it>P </it>= 0.000).</p> <p>Conclusions</p> <p>These results suggested that TLR2 rs3804099 C/T and rs3804100 C/T polymorphisms were closely associated with HCC. In addition, the haplotypes composed of these two TLR2 synonymous SNPs have stronger effects on the susceptibility of HCC.</p

Single Nucleotide Polymorphisms of Toll-Like Receptor 4 Decrease the Risk of Development of Hepatocellular Carcinoma

BACKGROUND: Toll-like receptor 4 (TLR4) is a key innate immunity receptor that initiates an inflammatory response. Growing evidence suggests that mutation of TLR4 gene may play a role in the development of cancers. This study aimed to investigate the temporal relationship of single nucleotide polymorphisms of TLR4 and the risk of hepatocellular carcinoma, a single center-based case-control study was conducted. METHODS: A systematic genetic analysis of sequence variants of TLR4 by evaluating ten single-nucleotide polymorphisms was performed from 216 hepatocellular carcinoma cases and 228 controls. RESULTS: Six single nucleotide polymorphisms of the TLR4 in the 5'-untranslated region and intron were associated with risk of hepatocellular carcinoma. Individuals carrying the heterozygous genotypes for the rs10759930, rs2737190, rs10116253, rs1927914, rs12377632 and rs1927911 had significantly decreased risk of hepatocellular carcinoma (adjusted odds ratio [OR], from 0.527 to 0.578, P<0.01) comparing with those carrying wild-type homozygous genotypes. In haplotype analysis, one haplotype (GCCCTTAG) of TLR4 was associated significantly with decrease of the occurrence of hepatocellular carcinoma (OR, 0.556, 95% confidence interval [CI], 0.407-0.758, P = 0.000). CONCLUSIONS: Collectively, these results suggested that the risk of hepatocellular carcinoma was associated with TLR4 sequence variation. TLR4 single nucleotide polymorphisms may play an important protective role in the development of hepatocellular carcinoma

Examples-Rules Guided Deep Neural Network for Makeup Recommendation

In this paper, we consider a fully automatic makeup recommendation system and propose a novel examples-rules guided deep neural network approach. The framework consists of three stages. First, makeup-related facial traits are classified into structured coding. Second, these facial traits are fed in- to examples-rules guided deep neural recommendation model which makes use of the pairwise of Before-After images and the makeup artist knowledge jointly. Finally, to visualize the recommended makeup style, an automatic makeup synthesis system is developed as well. To this end, a new Before-After facial makeup database is collected and labeled manually, and the knowledge of makeup artist is modeled by knowledge base system. The performance of this framework is evaluated through extensive experimental analyses. The experiments validate the automatic facial traits classification, the recommendation effectiveness in statistical and perceptual ways and the makeup synthesis accuracy which outperforms the state of the art methods by large margin. It is also worthy to note that the proposed framework is a pioneering fully automatic makeup recommendation systems to our best knowledge