A Few-Shot Learning-Based Siamese Capsule Network for Intrusion Detection with Imbalanced Training Data

Network intrusion detection remains one of the major challenges in cybersecurity. In recent years, many machine-learning-based methods have been designed to capture the dynamic and complex intrusion patterns to improve the performance of intrusion detection systems. However, two issues, including imbalanced training data and new unknown attacks, still hinder the development of a reliable network intrusion detection system. In this paper, we propose a novel few-shot learning-based Siamese capsule network to tackle the scarcity of abnormal network traffic training data and enhance the detection of unknown attacks. In specific, the well-designed deep learning network excels at capturing dynamic relationships across traffic features. In addition, an unsupervised subtype sampling scheme is seamlessly integrated with the Siamese network to improve the detection of network intrusion attacks under the circumstance of imbalanced training data. Experimental results have demonstrated that the metric learning framework is more suitable to extract subtle and distinctive features to identify both known and unknown attacks after the sampling scheme compared to other supervised learning methods. Compared to the state-of-the-art methods, our proposed method achieves superior performance to effectively detect both types of attacks

Australobius polyspinipes sp. n., a new species of Australobius Chamberlin, 1920 (Lithobiomorpha: Lithobiidae) from China

Australobius polyspinipes sp. n. (Lithobiomorpha: Lithobiidae) was recently discovered from Tianheshan Mountain, Hebei Province, China, and it is described here. Morphologically the new species is similar to A. nodulus Ma, Song &Zhu, 2008 and A. magnus (Trozina, 1894), both recorded from China. The new species can be easily distinguished from those by having 7+7–8+8 coxosternal teeth, 10–12 ocelli on each side of the cephalic plate, 5+5 spurs on the first article of the female gonopods and differences in plectrotaxy of legs. The main morphological characters and a key to the known Chinese species of genus Australobius based on adult specimens is presented

Emergence of Extensively Drug-Resistant Proteus mirabilis Harboring a Conjugative NDM-1 Plasmid and a Novel Salmonella Genomic Island 1 Variant, SGI1-Z

Acquisition of blaNDM-1 in bacterial species, such as Proteus mirabilis that is intrinsically resistant to tetracycline, tigecycline and colistin, will make clinical treatment extremely difficult. Here, we characterized an NDM-1-producing clinical isolate of P. mirabilis (PM58) that displayed an extensively drug-resistant (XDR) phenotype, susceptible only to aztreonam. Molecular analysis revealed that PM58 harbored both a conjugative NDM-1 plasmid and a novel Salmonella genomic island 1 variant on chromosome

SUN: Exploring Intrinsic Uncertainties in Text-to-SQL Parsers

This paper aims to improve the performance of text-to-SQL parsing by exploring the intrinsic uncertainties in the neural network based approaches (called SUN). From the data uncertainty perspective, it is indisputable that a single SQL can be learned from multiple semantically-equivalent questions.Different from previous methods that are limited to one-to-one mapping, we propose a data uncertainty constraint to explore the underlying complementary semantic information among multiple semantically-equivalent questions (many-to-one) and learn the robust feature representations with reduced spurious associations. In this way, we can reduce the sensitivity of the learned representations and improve the robustness of the parser. From the model uncertainty perspective, there is often structural information (dependence) among the weights of neural networks. To improve the generalizability and stability of neural text-to-SQL parsers, we propose a model uncertainty constraint to refine the query representations by enforcing the output representations of different perturbed encoding networks to be consistent with each other. Extensive experiments on five benchmark datasets demonstrate that our method significantly outperforms strong competitors and achieves new state-of-the-art results. For reproducibility, we release our code and data at https://github.com/AlibabaResearch/DAMO-ConvAI/tree/main/sunsql.Comment: Accepted at COLING 202

Large-scale phosphoproteome analysis in seedling leaves of Brachypodium distachyon L.

BACKGROUND: Protein phosphorylation is one of the most important post-translational modifications involved in the regulation of plant growth and development as well as diverse stress response. As a member of the Poaceae, Brachypodium distachyon L. is a new model plant for wheat and barley as well as several potential biofuel grasses such as switchgrass. Vegetative growth is vital for biomass accumulation of plants, but knowledge regarding the role of protein phosphorylation modification during vegetative growth, especially in biofuel plants, is far from comprehensive. RESULTS: In this study, we carried out the first large-scale phosphoproteome analysis of seedling leaves in Brachypodium accession Bd21 using TiO(2) microcolumns combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) and MaxQuant software. A total of 1470 phosphorylation sites in 950 phosphoproteins were identified, and these phosphoproteins were implicated in various molecular functions and basic cellular processes by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Among the 950 phosphoproteins identified, 127 contained 3 to 8 phosphorylation sites. Conservation analysis showed that 93.4% of the 950 phosphoproteins had phosphorylation orthologs in other plant species. Motif-X analysis of the phosphorylation sites identified 13 significantly enriched phosphorylation motifs, of which 3 were novel phosphorylation motifs. Meanwhile, there were 91 phosphoproteins with both multiple phosphorylation sites and multiple phosphorylation motifs. In addition, we identified 58 phosphorylated transcription factors across 21 families and found out 6 significantly over-represented transcription factor families (C3H, Trihelix, CAMTA, TALE, MYB_related and CPP). Eighty-four protein kinases (PKs), 8 protein phosphatases (PPs) and 6 CESAs were recognized as phosphoproteins. CONCLUSIONS: Through a large-scale bioinformatics analysis of the phosphorylation data in seedling leaves, a complicated PKs- and PPs- centered network related to rapid vegetative growth was deciphered in B. distachyon. We revealed a MAPK cascade network that might play the crucial roles during the phosphorylation signal transduction in leaf growth and development. The phosphoproteins and phosphosites identified from our study expanded our knowledge of protein phosphorylation modification in plants, especially in monocots. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-375) contains supplementary material, which is available to authorized users

Feline umbilical cord-derived mesenchymal stem cells: isolation, identification, and antioxidative stress role through NF-κB signaling pathway

At present, the differentiation potential and antioxidant activity of feline umbilical cord-derived mesenchymal stem cells (UC-MSCs) have not been clearly studied. In this study, feline UC-MSCs were isolated by tissue adhesion method, identified by flow cytometry detection of cell surface markers (CD44, CD90, CD34, and CD45), and induced differentiation toward osteogenesis and adipogenesis in vitro. Furthermore, the oxidative stress model was established with hydrogen peroxide (H2O2) (100 μM, 300 μM, 500 μM, 700 μM, and 900 μM). The antioxidant properties of feline UC-MSCs and feline fibroblasts were compared by morphological observation, ROS detection, cell viability via CCK-8 assay, as well as oxidative and antioxidative parameters via ELISA. The mRNA expression of genes related to NF-κB pathway was detected via quantitative real-time polymerase chain reaction, while the levels of NF-κB signaling cascade-related proteins were determined via Western Blot. The results showed that feline UC-MSCs highly expressed CD44 and CD90, while negative for CD34 and CD45 expression. Feline UC-MSCs cultured under osteogenic and adipogenic conditions showed good differentiation capacity. After being exposed to different concentrations of H2O2 for eight hours, feline UC-MSCs exhibited the significantly higher survival rate than feline fibroblasts. A certain concentration of H2O2 could up-regulate the activities of SOD2 and GSH-Px in feline UC-MSCs. The expression levels of p50, MnSOD, and FHC mRNA in feline UC-MSCs stimulated by 300 μM and 500 μM H2O2 significantly increased compared with the control group. Furthermore, it was observed that 500 μM H2O2 significantly enhanced the protein levels of p-IκB, IκB, p-p50, p50, MnSOD, and FHC, which could be reversed by BAY 11-7,082, a NF-κB signaling pathway inhibitor. In conclusion, it was confirmed that feline UC-MSCs, with good osteogenesis and adipogenesis abilities, had better antioxidant property which might be related to NF-κB signaling pathway. This study lays a foundation for the further application of feline UC-MSCs in treating the various inflammatory and oxidative injury diseases of pets

Regulation of LYRM1 Gene Expression by Free Fatty Acids, Adipokines, and Rosiglitazone in 3T3-L1 Adipocytes

LYR motif containing 1 (LYRM1) is a novel gene that is abundantly expressed in the adipose tissue of obese subjects and is involved in insulin resistance. In this study, free fatty acids (FFAs) and tumor necrosis factor-α (TNF-α) are shown to upregulate LYRM1 mRNA expression in 3T3-L1 adipocytes. Conversely, resistin and rosiglitazone exert an inhibitory effect on LYRM1 mRNA expression. These results suggest that the expression of LYRM1 mRNA is affected by a variety of factors that are related to insulin sensitivity. LYRM1 may be an important mediator in the development of obesity-related insulin resistance