Unilaterally Aggregated Contrastive Learning with Hierarchical Augmentation for Anomaly Detection

Anomaly detection (AD), aiming to find samples that deviate from the training distribution, is essential in safety-critical applications. Though recent self-supervised learning based attempts achieve promising results by creating virtual outliers, their training objectives are less faithful to AD which requires a concentrated inlier distribution as well as a dispersive outlier distribution. In this paper, we propose Unilaterally Aggregated Contrastive Learning with Hierarchical Augmentation (UniCon-HA), taking into account both the requirements above. Specifically, we explicitly encourage the concentration of inliers and the dispersion of virtual outliers via supervised and unsupervised contrastive losses, respectively. Considering that standard contrastive data augmentation for generating positive views may induce outliers, we additionally introduce a soft mechanism to re-weight each augmented inlier according to its deviation from the inlier distribution, to ensure a purified concentration. Moreover, to prompt a higher concentration, inspired by curriculum learning, we adopt an easy-to-hard hierarchical augmentation strategy and perform contrastive aggregation at different depths of the network based on the strengths of data augmentation. Our method is evaluated under three AD settings including unlabeled one-class, unlabeled multi-class, and labeled multi-class, demonstrating its consistent superiority over other competitors.Comment: Accepted by ICCV'202

Video Anomaly Detection by Solving Decoupled Spatio-Temporal Jigsaw Puzzles

Video Anomaly Detection (VAD) is an important topic in computer vision. Motivated by the recent advances in self-supervised learning, this paper addresses VAD by solving an intuitive yet challenging pretext task, i.e., spatio-temporal jigsaw puzzles, which is cast as a multi-label fine-grained classification problem. Our method exhibits several advantages over existing works: 1) the spatio-temporal jigsaw puzzles are decoupled in terms of spatial and temporal dimensions, responsible for capturing highly discriminative appearance and motion features, respectively; 2) full permutations are used to provide abundant jigsaw puzzles covering various difficulty levels, allowing the network to distinguish subtle spatio-temporal differences between normal and abnormal events; and 3) the pretext task is tackled in an end-to-end manner without relying on any pre-trained models. Our method outperforms state-of-the-art counterparts on three public benchmarks. Especially on ShanghaiTech Campus, the result is superior to reconstruction and prediction-based methods by a large margin.Comment: Accepted by ECCV'2022; Code is available at https://github.com/gdwang08/Jigsaw-VA

Identification of genotype 4 Hepatitis E virus binding proteins on swine liver cells

Hepatitis E virus (HEV) is a zoonotic pathogen of which several species of animal were reported as reservoirs. Swine stands out as the major reservoir for HEV infection in humans, as suggested by the close genetic relationship of swine and human virus and cross-species infection of HEV. Up to now, the mechanism of cross-species infection of HEV from swine to humans is still unclear. This study sought to identify receptor element for genotype 4 HEV on swine liver cells using the viral overlay protein binding assay (VOPBA) technique and Mass Spectrometry fingerprinting. A single virus binding band with natural molecular weight about 55 kDa was observed, and mass spectrometry revealed that this virus binding band contained 31 different proteins. Infection inhibition assay suggested that this 55 kDa protein could prevent HEV from infecting its susceptible A549 cell line, which was further confirmed by the HEV genome detecting in the inoculated cells. Further research should be performed to elucidate the accurate receptor of HEV on the swine liver cells

Study of Ammonia Concentration Characteristics and Optimization in Broiler Chamber during Winter Based on Computational Fluid Dynamics

Poultry breeding is one of the most significant components of agriculture and an essential link of material exchange between humans and nature. Moreover, poultry breeding technology has a considerable impact on the life quality of human beings, and could even influence the survival of human beings. As one of the most popular poultry, broiler has a good economic benefit due to its excellent taste and fast growing cycle. This paper aims to improve the efficiency of raising broilers by understanding the impact of ammonia concentration distribution within a smart broiler breeding chamber, and the rationality of the system’s design. More specifically, we used computational fluid dynamics (CFD) technology to simulate the process of ammonia production and identify the characteristics of ammonia concentration. Based on the simulation results, the structure of the broiler chamber was reformed, and the ammonia uniformity was significantly improved after the structural modification of the broiler chamber and the ammonia concentration in the chamber had remained extremely low. In general, this study provides a reference for structural optimization of the design of broiler chambers and the environmental regulation of ammonia

Recombination analysis reveals a double recombination event in hepatitis E virus

Recombination of Hepatitis E Virus (HEV) has rarely been reported. In the present study, phylogenetic and recombination analyses were performed on 134 complete HEV genomes. Three potentially significant recombination events, including both intra-genotype and one inter-genotype, were identified by recombination detection analysis. Recombination events I and II occurred intra-genotype and inter-genotype, respectively, among three isolates, including the lineage represented by CHN-XJ-SW13 (GU119961, swine isolate), E067-SIJ05C (AB369690, human isolate), and JJT-Kan (AB091394, human isolate), and lead to the recombinant swine isolate swCH31 (DQ450072). Recombination event III occurred between the lineage represented by the NA1 (M73218) and K52-87 (L25595), which resulted in the recombinant Xingjiang-1 (D11092). Our analyses proved that that recombination could occur between human and swine HEV strains, double recombination events existed in HEV, and recombination event could happen within ORF2 region of HEV. These results will provide valuable hints for future research on HEV diversity