BCN: Batch Channel Normalization for Image Classification

Normalization techniques have been widely used in the field of deep learning due to their capability of enabling higher learning rates and are less careful in initialization. However, the effectiveness of popular normalization technologies is typically limited to specific areas. Unlike the standard Batch Normalization (BN) and Layer Normalization (LN), where BN computes the mean and variance along the (N,H,W) dimensions and LN computes the mean and variance along the (C,H,W) dimensions (N, C, H and W are the batch, channel, spatial height and width dimension, respectively), this paper presents a novel normalization technique called Batch Channel Normalization (BCN). To exploit both the channel and batch dependence and adaptively and combine the advantages of BN and LN based on specific datasets or tasks, BCN separately normalizes inputs along the (N, H, W) and (C, H, W) axes, then combines the normalized outputs based on adaptive parameters. As a basic block, BCN can be easily integrated into existing models for various applications in the field of computer vision. Empirical results show that the proposed technique can be seamlessly applied to various versions of CNN or Vision Transformer architecture. The code is publicly available at https://github.com/AfifaKhaled/BatchChannel-Normalizatio

Anti-hepatitis B viral activity of Phyllanthus niruri L (Phyllanthaceae) in HepG2/C3A and SK-HEP-1 cells

Purpose: To investigate the effectiveness of an ethanol extract of Phyllanthus niruri against hepatitis B viral (HBV) infection in human HepG2/C3A cells.Methods: An ellagic acid-rich ethanol fraction was obtained from P. niruri (Euphorbiaceae) by extraction and thin-layer chromatography. The anti-HBV activity of the fraction was evaluated in vitro against HepG2/C3A cells. The physicochemical characteristics of the fraction were assessed by nuclear magnetic resonance (1H and 12C-NMR).Results: The isolated active compound showed a half-maximal inhibitory concentration (IC50) of 120 μg/mL. Ellagic acid had no effect on HBV DNA replication at the concentrations evaluated, and did not inhibit the reproduction of HBV. However, the ethanol fraction inhibited the growth of HBV-infected HepG2/C3A cells.Conclusion: The findings suggest that the ethanol fraction of P. niruri inhibits HBV, and that the active component is not ellagic acid.Keywords: Phyllanthus niruri, Anti-HBeAg, Hepatitis B viru

LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving

A map, as crucial information for downstream applications of an autonomous driving system, is usually represented in lanelines or centerlines. However, existing literature on map learning primarily focuses on either detecting geometry-based lanelines or perceiving topology relationships of centerlines. Both of these methods ignore the intrinsic relationship of lanelines and centerlines, that lanelines bind centerlines. While simply predicting both types of lane in one model is mutually excluded in learning objective, we advocate lane segment as a new representation that seamlessly incorporates both geometry and topology information. Thus, we introduce LaneSegNet, the first end-to-end mapping network generating lane segments to obtain a complete representation of the road structure. Our algorithm features two key modifications. One is a lane attention module to capture pivotal region details within the long-range feature space. Another is an identical initialization strategy for reference points, which enhances the learning of positional priors for lane attention. On the OpenLane-V2 dataset, LaneSegNet outperforms previous counterparts by a substantial gain across three tasks, \textit{i.e.}, map element detection (+4.8 mAP), centerline perception (+6.9 DET$_l$), and the newly defined one, lane segment perception (+5.6 mAP). Furthermore, it obtains a real-time inference speed of 14.7 FPS. Code is accessible at https://github.com/OpenDriveLab/LaneSegNet.Comment: Accepted in ICLR 202

Insights into high temperature pretreatment on cellulase processing of bamboo

Bamboo processing was performed with commercial cellulase. The properties of cellulase and the effect of high temperature pretreatment on cellulase hydrolysis of bamboo were investigated. Results indicated that cellulase hydrolysis performed fast and dramatically within 30 minutes, and then gradually reached its balance. It was found that pretreatment played an active role in cellulase processing, which enhanced the saccharification of bamboo and benefited high-molecular-weight lignin degradation and removal. Additionally, a better performance of bamboo processing was achieved under the cellulase concentration of 15IU in total reaction system of 100 ml at 50°C, pH 4.8, together with the high temperature pretreatment of 120°C for 15 minutes