An effective Denial of Service Attack Detection Method in Wireless Mesh Networks

AbstractIn order to detect the DoS attack (Denial-of-Service attack) when wireless mesh networks adopt AODV routing protocol of Ad Hoc networks. Such technologies as an end-to-end authentication, utilization rate of cache memory, two pre-assumed threshold value and distributed voting are used in this paper to detect DoS attacker, which is on the basic of hierarchical topology structure in wireless mesh networks. Through performance analysis in theory and simulations experiment, the scheme would improve the flexibility and accuracy of DoS attack detection, and would obviously improve its security in wireless mesh networks

Interferon-alpha responsible EPN3 regulates hepatitis B virus replication

Hepatitis B virus (HBV) infection remains a major health problem worldwide, and the current antiviral therapy, including nucleoside analogs, cannot achieve life-long cure, and clarification of antiviral host immunity is necessary for eradication. Here, we found that a clathrin-binding membrane protein epsin3 (EPN3) negatively regulates the expression of HBV RNA. EPN3 expression was induced by transfection of an HBV replicon plasmid, and reduced HBV-RNA level in hepatic cell lines and murine livers hydrodynamically injected with the HBV replicon plasmid. Viral RNA reduction by EPN3 was dependent on transcription, and independent from epsilon structure of viral RNA. Viral RNA reduction by overexpression of p53 or IFN-α treatment, was attenuated by knockdown of EPN3, suggesting its role downstream of IFN-α and p53. Taken together, this study demonstrates the anti-HBV role of EPN3. The mechanism how it decreases HBV transcription is discussed

Zero-Shot and Few-Shot Learning for Lung Cancer Multi-Label Classification using Vision Transformer

Lung cancer is the leading cause of cancer-related death worldwide. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the most common histologic subtypes of non-small-cell lung cancer (NSCLC). Histology is an essential tool for lung cancer diagnosis. Pathologists make classifications according to the dominant subtypes. Although morphology remains the standard for diagnosis, significant tool needs to be developed to elucidate the diagnosis. In our study, we utilize the pre-trained Vision Transformer (ViT) model to classify multiple label lung cancer on histologic slices (from dataset LC25000), in both Zero-Shot and Few-Shot settings. Then we compare the performance of Zero-Shot and Few-Shot ViT on accuracy, precision, recall, sensitivity and specificity. Our study show that the pre-trained ViT model has a good performance in Zero-Shot setting, a competitive accuracy ($99.87\%$) in Few-Shot setting ({epoch = 1}) and an optimal result ($100.00\%$ on both validation set and test set) in Few-Shot seeting ({epoch = 5})

Damage Diagnosis of Frame Structure Based on Convolutional Neural Network with SE-Res2Net Module

The complex application environments of frame structures and the similar vibration signals between different locations make it difficult to accurately diagnose damage using traditional methods. Based on modifying the parameters and configuration of the convolution neural network with training interference (TICNN), this paper proposes a new model for damage diagnosis of frame structures by implanting a squeeze-and-excitation neural network (SENet) and Res2Net modules. Taking the frame structure model from the University of British Columbia as the research object, the proposed damage diagnosis model was used to diagnose its damage type. The proposed new model was compared with other models in terms of accuracy and anti-noise ability. The experimental results show that the accuracy of the proposed model was 99.44% when the training epoch was 30 and 99.78% when training epoch was 100. It is superior to other similar models in terms of convergence speed and accuracy. At the same time, the proposed model also has an excellent advantage in anti-noise ability. Therefore, the proposed damage diagnosis model has the advantages of fast convergence and higher damage diagnosis accuracy under a strong noise environment. It can realize the accurate damage diagnosis of structural frames

CYCLIN-DEPENDENT KINASE8 Differentially Regulates Plant Immunity to Fungal Pathogens through Kinase-Dependent and -Independent Functions in ArabidopsisC

CYCLIN-DEPENDENT KINASE8 (CDK8) is a widely studied component of eukaryotic Mediator complexes. However, the biological and molecular functions of plant CDK8 are not well understood. Here, we provide evidence for regulatory functions of Arabidopsis thaliana CDK8 in defense and demonstrate its functional and molecular interactions with other Mediator and non-Mediator subunits. The cdk8 mutant exhibits enhanced resistance to Botrytis cinerea but susceptibility to Alternaria brassicicola. The contributions of CDK8 to the transcriptional activation of defensin gene PDF1.2 and its interaction with MEDIATOR COMPLEX SUBUNIT25 (MED25) implicate CDK8 in jasmonate-mediated defense. Moreover, CDK8 associates with the promoter of AGMATINE COUMAROYLTRANSFERASE to promote its transcription and regulate the biosynthesis of the defense-active secondary metabolites hydroxycinnamic acid amides. CDK8 also interacts with the transcription factor WAX INDUCER1, implying its additional role in cuticle development. In addition, overlapping functions of CDK8 with MED12 and MED13 and interactions between CDK8 and C-type cyclins suggest the conserved configuration of the plant Mediator kinase module. In summary, while CDK8’s positive transcriptional regulation of target genes and its phosphorylation activities underpin its defense functions, the impaired defense responses in the mutant are masked by its altered cuticle, resulting in specific resistance to B. cinerea