Experimental study on the seismic behavior of coupled shear wall with concealed partitioned steel plates

To study the seismic behavior and post-earthquake repairability of coupled shear wall with concrete filled steel tube (CFST) frame and concealed partitioned steel plates (SPs), three 1/5 scaled coupled shear wall specimens were designed with different type of CFST column or core structure. Low-cycle reversed loading was adopted in the test. The test contained two stages. Load-carrying capacity, energy dissipation, ductility, stiffness and failure characteristic of the specimens were compared in pre-repair stages and post-repair stages. The conclusions are drawn that the core structure shows a good ductile yielding mechanism. The cross-section type of frame has an obvious effect on the seismic behavior of shear wall. After damage and strengthening, the new coupled shear wall still has enough seismic capacity and good energy dissipation capacity, and it is easy to be repaired after earthquake. Finite element analysis software ABAQUS has been used to simulate the behavior of coupled shear wall. Ultimate strength is obtained with the vibration of thickness of SPs

Bio-inspired functional surface fabricated by electrically assisted micro-embossing of AZ31 magnesium alloy

Developing bio-inspired functional surfaces on engineering metals is of extreme importance, involving different industrial sectors, like automotive or aeronautics. In particular, micro-embossing is one of the efficient and large-scale processes for manufacturing bio-inspired textures on metallic surfaces. However, this process faces some problems, such as filling defects and die breakage due tocsize effect, which restrict this technology for some components. Electrically assisted micro-forming has demonstrated the ability of reducing size effects, improving formability and decreasing flow stress, making it a promising hybrid process to control the filling quality of micro-scale features. This research focuses on the use of different current densities to perform embossed micro-channels of 7 um and sharklet patterns of 10 um in textured bulk metallic glass dies. These dies are prepared by thermoplastic forming based on the compression of photolithographic silicon molds. The results show that large areas of bio-inspired textures could be fabricated on magnesium alloy when current densities higher than 6 A/mm2 (threshold) are used. The optimal surface quality scenario is obtained for a current density of 13 A/mm2. Additionally, filling depth and depth–width ratio nonlinearly increases when higher current densities are used, where the temperature is a key parameter to control, keeping it below the temperature of the glass transition to avoid melting or an early breakage of the die.Peer ReviewedPostprint (published version

Dual-Neighborhood Deep Fusion Network for Point Cloud Analysis

Recently, deep neural networks have made remarkable achievements in 3D point cloud classification. However, existing classification methods are mainly implemented on idealized point clouds and suffer heavy degradation of per-formance on non-idealized scenarios. To handle this prob-lem, a feature representation learning method, named Dual-Neighborhood Deep Fusion Network (DNDFN), is proposed to serve as an improved point cloud encoder for the task of non-idealized point cloud classification. DNDFN utilizes a trainable neighborhood learning method called TN-Learning to capture the global key neighborhood. Then, the global neighborhood is fused with the local neighbor-hood to help the network achieve more powerful reasoning ability. Besides, an Information Transfer Convolution (IT-Conv) is proposed for DNDFN to learn the edge infor-mation between point-pairs and benefits the feature transfer procedure. The transmission of information in IT-Conv is similar to the propagation of information in the graph which makes DNDFN closer to the human reasoning mode. Extensive experiments on existing benchmarks especially non-idealized datasets verify the effectiveness of DNDFN and DNDFN achieves the state of the arts.Comment: ICMEW202

Adaptive Channel Encoding Transformer for Point Cloud Analysis

Transformer plays an increasingly important role in various computer vision areas and remarkable achievements have also been made in point cloud analysis. Since they mainly focus on point-wise transformer, an adaptive channel encoding transformer is proposed in this paper. Specifically, a channel convolution called Transformer-Conv is designed to encode the channel. It can encode feature channels by capturing the potential relationship between coordinates and features. Compared with simply assigning attention weight to each channel, our method aims to encode the channel adaptively. In addition, our network adopts the neighborhood search method of low-level and high-level dual semantic receptive fields to improve the performance. Extensive experiments show that our method is superior to state-of-the-art point cloud classification and segmentation methods on three benchmark datasets.Comment: ICANN202

Expediting the accuracy-improving process of SVMs for class imbalance learning

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ

Access Authentication Via Blockchain in Space Information Network

These authors contributed equally to this work. Abstract Space Information Network (SIN) has significant benefits of providing communication anywhere at any time. This feature offers an innovative way for conventional wireless customers to access enhanced internet services by using SIN. However, SIN's characteristics, such as naked links and maximum signal latency, make it difficult to design efficient security and routing protocols, etc. Similarly, existing SIN authentication techniques can't satisfy all of the essentials for secure communication, such as privacy leaks or rising authentication latency. The article aims to develop a novel blockchain-based access authentication mechanism for SIN. The proposed scheme uses a blockchain application, which has offered anonymity to mobile users while considering the satellites' limited processing capacity. The proposed scheme uses a blockchain application, which offers anonymity to mobile users while considering the satellites' limited processing capacity. The SIN gains the likelihood of far greater computational capacity devices as technology evolves. Since authenticating in SIN, the technique comprises three entities: low Earth orbit, mobile user, and network control centre. The proposed mutual authentication mechanism avoids the requirement of a ground station, resulting in less latency and overhead during mobile user authentication. Finally, the new blockchain-based authentication approach is being evaluated with AVISPA, a formal security tool. The simulation and performance study results illustrate that the proposed technique delivers efficient security characteristics such as low authentication latency, minimal signal overhead and less computational cost with group authentication

Identification of critical residues of influenza neuraminidase in viral particle release

BACKGROUND: Influenza neuraminidase (NA) is essential for virus release from its host cells and it is one of the targets for structure-based antiviral drug design. RESULTS: In this report, we established a pseudoviral particle release assay to study NA function, which is based on lentiviral particles pseudotyped with influenza glycoproteins HA and NA as a surrogate system. Through an extensive molecular analysis, we sought to characterize important residues governing NA function. We identified five residues of NA, 234, 241, 257, 286 and 345, four of which (except 345) map away from the active site of NA when projected onto the three-dimensional structure of avian influenza H5N1 NA, and substitutions of these residues adversely affected the NA-mediated viral particle release, suggesting that these residues are critical for NA enzymatic activity. CONCLUSION: Through extensive chimeric and mutational analyses, we have identified several residues, which map away from the active site and are critical for NA function. These findings provide new insights into NA-mediated pseudoviral particle release and may have important implications in drug design and therapeutics against influenza infection