Unsupervised Single-Scene Semantic Segmentation for Earth Observation

Earth observation data have huge potential to enrich our knowledge about our planet. An important step in many Earth observation tasks is semantic segmentation. Generally, a large number of pixelwise labeled images are required to train deep models for supervised semantic segmentation. On the contrary, strong intersensor and geographic variations impede the availability of annotated training data in Earth observation. In practice, most Earth observation tasks use only the target scene without assuming availability of any additional scene, labeled or unlabeled. Keeping in mind such constraints, we propose a semantic segmentation method that learns to segment from a single scene, without using any annotation. Earth observation scenes are generally larger than those encountered in typical computer vision datasets. Exploiting this, the proposed method samples smaller unlabeled patches from the scene. For each patch, an alternate view is generated by simple transformations, e.g., addition of noise. Both views are then processed through a two-stream network and weights are iteratively refined using deep clustering, spatial consistency, and contrastive learning in the pixel space. The proposed model automatically segregates the major classes present in the scene and produces the segmentation map. Extensive experiments on four Earth observation datasets collected by different sensors show the effectiveness of the proposed method. Implementation is available at https://gitlab.lrz.de/ai4eo/cd/-/tree/main/unsupContrastiveSemanticSeg

Hsp90 Interacts With Tm-22 and Is Essential for Tm-22-Mediated Resistance to Tobacco mosaic virus

The tomato resistance gene Tm-22 encodes a coiled coil-nucleotide binding site-leucine rich repeat type resistance protein and confers effective immune response against tobamoviruses by detecting the presence of viral movement proteins (MPs). In this study, we show that the Nicotiana benthamiana Heat shock protein 90-kD (Hsp90) interacts with Tm-22. Silencing of Hsp90 reduced Tm-22-mediated resistance to Tobacco mosaic virus (TMV) and the steady-state levels of Tm-22 protein. Further, Hsp90 associates with SGT1 in yeast and in plant cells. These results suggest that Hsp90-SGT1 complex takes part in Tm-22-mediated TMV resistance by functioning as chaperone to regulate Tm-22 stability

Association between Serum Ferritin and Blood Lipids: Influence of Diabetes and hs-CRP Levels

This study is aimed at exploring the relationship between serum ferritin and blood lipids and the influence of diabetes and different hs-CRP levels. A total of 8163 subjects were analyzed. Participators were classified according to serum ferritin, diabetes, and two hs-CRP levels. Blood lipids were determined using standardized methods and conditions. Except for HDL-C, there was a significant increase in blood lipids in the progressive ferritin group with normal hs-CRP levels (P0.05). After a sufficient adjustment, there was a positive correlation between serum TG and ferritin and a negative correlation between LDL-C and ferritin. Nonetheless, a negative correlation between LDL-C and ferritin is influenced by diabetes frailly. And, there was no change of relationship between lipids and ferritin in different hs-CRP levels. We found a real relationship between ferritin and lipids after sufficient adjustment for confounders