Visual In-Context Learning for Few-Shot Eczema Segmentation.

Automated diagnosis of eczema from digital camera images is crucial for applications that allow patients to self-monitor their recovery. An important component of this is the segmentation of eczema region from such images. Current methods for eczema segmentation rely on deep neural networks such as convolutional (CNN)-based U-Net or transformer-based Swin U-Net.

Enhanced biodegradation of PAHs by microbial consortium with different amendment and their fate in in-situ condition.

Microbial degradation is a useful tool to prevent chemical pollution in soil. In the present study, in-situ bioremediation of polyaromatic hydrocarbons (PAHs) by microbial consortium consisting of Serratia marcescens L-11, Streptomyces rochei PAH-13 and Phanerochaete chrysosporium VV-18 has been reported. In preliminary studies, the consortium degraded nearly 60-70% of PAHs in broth within 7 days under controlled conditions.

Characterization of bacterial diversity in an atrazine degrading enrichment culture and degradation of atrazine, cyanuric acid and biuret in industrial wastewater.

An enrichment culture was used to study atrazine degradation in mineral salt medium (MSM) (T1), MSM+soil extract (1:1, v/v) (T2) and soil extract (T3). Results suggested that enrichment culture required soil extract to degrade atrazine, as after second sequential transfer only partial atrazine degradation was observed in T1 treatment while atrazine was completely degraded in T2 and T3 treatments even after fourth transfer. Culture independent polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) technique confirmed selective enrichment of genus Bacillus along with Pseudomonas and Burkholderia.