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The present study explained the effect of pretreatments on the biosorption of Cr (III) and Cr (VI) by Cassia fistula biomass from aqueous solutions. For this purpose Cassia fistula biomass was pretreated physically by heating, autoclaving, boiling and chemically with sodium hydroxide, formaldehyde, gluteraldehyde, acetic acid, hydrogen peroxide, commercial laundry detergent, orthophosphoric, sulphuric acid, nitric acid, and hydrochloric acid. The adsorption capacity of biomass for Cr (III) and Cr (VI) was found to be significantly improved by the treatments of gluteraldehyde (95.41 and 96.21 mg/g) and benzene (85.71 and 90.81 mg/g) respectively. The adsorption capacity was found to depend on pH, initial metal concentration, dose, size, kinetics, and temperature. Maximum adsorption of both the Cr (III) and Cr (VI) was observed at pH 5 and 2. When Freundlich and Langmuir isotherms were tested, the latter had a better fit with the experimental data. The kinetic studies showed that the sorption rates could be described better by a second order expression than by a more commonly applied Lagergren equation.

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Surveillance of the evolving SARS-COV-2 genome combined with epidemiological monitoring and emerging vaccination became paramount tasks to control the pandemic which is rapidly changing in time and space. Genomic surveillance must combine generation and sharing sequence data with appropriate bioinformatics monitoring and analysis methods. We applied molecular portrayal using self-organizing maps machine learning (SOM portrayal) to characterize the diversity of the virus genomes, their mutual relatedness and development since the beginning of the pandemic. The genetic landscape obtained visualizes the relevant mutations in a lineage-specific fashion and provides developmental paths in genetic state space from early lineages towards the variants of concern alpha, beta, gamma and delta. The different genes of the virus have specific footprints in the landscape reflecting their biological impact. SOM portrayal provides a novel option for ‘bioinformatics surveillance’ of the pandemic, with strong odds regarding visualization, intuitive perception and ‘personalization’ of the mutational patterns of the virus genomes.