SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation

We present SegNeXt, a simple convolutional network architecture for semantic segmentation. Recent transformer-based models have dominated the field of semantic segmentation due to the efficiency of self-attention in encoding spatial information. In this paper, we show that convolutional attention is a more efficient and effective way to encode contextual information than the self-attention mechanism in transformers. By re-examining the characteristics owned by successful segmentation models, we discover several key components leading to the performance improvement of segmentation models. This motivates us to design a novel convolutional attention network that uses cheap convolutional operations. Without bells and whistles, our SegNeXt significantly improves the performance of previous state-of-the-art methods on popular benchmarks, including ADE20K, Cityscapes, COCO-Stuff, Pascal VOC, Pascal Context, and iSAID. Notably, SegNeXt outperforms EfficientNet-L2 w/ NAS-FPN and achieves 90.6% mIoU on the Pascal VOC 2012 test leaderboard using only 1/10 parameters of it. On average, SegNeXt achieves about 2.0% mIoU improvements compared to the state-of-the-art methods on the ADE20K datasets with the same or fewer computations. Code is available at https://github.com/uyzhang/JSeg (Jittor) and https://github.com/Visual-Attention-Network/SegNeXt (Pytorch).Comment: SegNeXt, a simple CNN for semantic segmentation. Code is availabl

Reaction sintered Fe–Sialon ceramic composite: Processing, characterization and high temperature erosion wear behavior

AbstractFe–Sialon ceramic matrix composite has been newly developed from ferro-silicon alloy and commercial-grade industrial alumina powders by reaction sintering under a nitrogen atmosphere. The phase composition, mechanical properties and impact erosion wear behavior were investigated. The solid particle erosion tests have been conducted at elevated temperatures ranging from 25°C to 1200°C. Sharp SiC particles between 325 and 830μm in diameter were employed as impact abrasives. The results showed that Fe–Sialon ceramic consisted of β-Sialon and Fe3Si phases. The Z value of the as-formed β-Sialon varied from 0 to 3.2 with increasing the alumina content in the starting powders. The bending strength and Rockwell hardness gradually increased with raising the alumina addition. The erosion rate of Fe–Sialon ceramic is highly dependent on the testing temperature. The minor erosion took place at room temperature or 1200°C, while the major erosion occurred at 600–1000°C. Fe–Sialon composites showed better erosion wear resistance than the control material of alumina ceramic at 1200°C, although having much lower density and slightly lower bending strength

Homage to Professor Shinko Ogiwara

<p><b><i>Primula undulifolia</i> sp. nov.</b> (A) Habit in Flowering; (B) Type Locality; (C) Calyx; (D) Pin and Thrum Flowers; (E) Leaf. Photographed by Yuan XU.</p

Natural aromatic compounds as scaffolds to develop selective G-quadruplex ligands. From previously reported berberine derivatives to new palmatine analogues

In this paper, the selective interactions of synthetic derivatives of two natural compounds, berberine and palmatine,with DNA G-quadruplex structureswere reported. In particular, the previous works on this subject concerning berberine were further presented and discussed, whereas the results concerning palmatine are presented here for the first time. In detail, these palmatine derivatives were developed by inserting seven different small peptide basic chains, giving several new compounds that have never been reported before. The preliminary studies of the interactions of these compounds with various G-quadruplex-forming sequences were carried out by means of various structural and biochemical techniques, which showed that the presence of suitable side chains is very useful for improving the interaction of the ligands with G-quadruplex structures. Thus, these new palmatine derivatives might act as potential anticancer drugs