This paper presents the characterization of the microbial community responsible for the in-situ bioremediation of hexachlorocyclohexane (HCH). Microbial community structure and function was analyzed using 16S rRNA amplicon and shotgun metagenomic sequencing methods for three sets of soil samples. The three samples were collected from a HCH-dumpsite (450 mg HCH/g soil) and comprised of a HCH/soil ratio of 0.45, 0.0007, and 0.00003, respectively. Certain bacterial; (Chromohalobacter, Marinimicrobium, Idiomarina, Salinosphaera, Halomonas, Sphingopyxis, Novosphingobium, Sphingomonas and Pseudomonas), archaeal; (Halobacterium, Haloarcula and Halorhabdus) and fungal (Fusarium) genera were found to be more abundant in the soil sample from the HCH-dumpsite. Consistent with the phylogenetic shift, the dumpsite also exhibited a relatively higher abundance of genes coding for chemotaxis/motility, chloroaromatic and HCH degradation (lin genes). Reassembly of a draft pangenome of Chromohalobacter salaxigenes sp. (∼8X coverage) and 3 plasmids (pISP3, pISP4 and pLB1; 13X coverage) containing lin genes/clusters also provides an evidence for the horizontal transfer of HCH catabolism genes.

The contamination levels in ground and river water suggest significant run-off from the dumped HCH wastes and contamination of drinking water resources. The extent of dumping urgently needs to be assessed regarding the risks to human and ecosystem health. A plan for securing the waste isomers needs to be developed and implemented together with a plan for their final elimination. As part of the assessment, any polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/PCDF) generated during HCH recycling operations need to be monitored.

The unusual process of production of hexachlorocyclohexane (HCH) and extensive use of technical HCH and lindane has created a very serious problem of HCH contamination. While the use of technical HCH and lindane has been banned all over the world, India still continues producing lindane. Bacteria, especially Sphingomonads have been isolated that can degrade HCH isomers. Among all the bacterial strains isolated so far, Sphingobium indicum B90A that was isolated form HCH treated rhizosphere soil appears to have a better potential for HCH degradation. This conclusion is based on studies on the organization of lin genes and degradation ability of B90A. This strain perhaps can be used for HCH decontamination through bioaugmentation.

The taxonomic position of a Gram-negative, non-motile, oxidase negative and catalase positive strain, A648 T , isolated from a hexachlorocyclohexane (HCH) dump site located in Lucknow, India, was ascertained by using a polyphasic approach. A comparative analysis of a partial sequence of the rpoB gene and the 16S rRNA gene sequence revealed that strain A648T belonged to the , were found to be less than 8 %. The major cellular fatty acids of strain A648T were 18 : 1v9c (19.6 %), summed feature 3 (15.9 %), 16 : 0 (10.6 %) and 12 : 0 (6.4 %). The DNA G+C content was 40.4 mol%. The polar lipid profile of strain A648 T indicated the presence of diphosphatidylglycerol, phosphatidylethanolamine, followed by phosphatidylglycerol and phosphatidylcholine. The predominant polyamine of strain A648 T was 1,3-diaminopropane and moderate amounts of putrescine, spermidine and spermine were also detected. The respiratory quinone consisted of ubiquinone with nine isoprene units (Q-9). On the basis of DNA-DNA hybridization, phenotypic characteristics and chemotaxonomic and phylogenetic comparisons with other members of the genus Acinetobacter, strain A648 T is found to be a novel species of the genus Acinetobacter, for which the name Acinetobacter indicus sp. nov. is proposed. The type strain is A648 T (5DSM 25388 T 5CCM 7832 T ).

In current times, after the rapid expansion and spread of the COVID-19 outbreak globally, people have experienced severe disruption to their daily lives. One idea to manage the outbreak is to enforce people wear a face mask in public places. Therefore, automated and efficient face detection methods are essential for such enforcement. In this paper, a face mask detection model for static and real time videos has been presented which classifies the images as "with mask" and "without mask". The model is trained and evaluated using the Kaggle data-set. The gathered data-set comprises approximately about 4,000 pictures and attained a performance accuracy rate of 98%. The proposed model is computationally efficient and precise as compared to DenseNet-121, MobileNet-V2, VGG-19, and Inception-V3. This work can be utilized as a digitized scanning tool in schools, hospitals, banks, and airports, and many other public or commercial locations.