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The performance of a continuously operated lab-scale rotating biological contactor (RBC) was assessed for the removal of heavy metals viz. Cu(II), Cd(II) and Pb(II) from synthetic wastewater using artificial neural networks (ANNs). The RBC was inoculated with Sulfate Reducing Bacteria consortium (predominantly Desulfovibrio species), and the performance was evaluated at different hydraulic retention times (HRTs), and inlet heavy metal concentrations. A feed-forward back-propagation neural network model was developed using 90 data sets obtained over a period of 3 months, to predict the removal of heavy metal (HMRE) and COD (CODRE). The predictive capability of the model was evaluated in terms of the coefficient of determination (R) and, mean absolute percentage error between the model fitted and actual experimental data, whereas sensitivity analysis was performed on the input parameters by determining the absolute average sensitivity (AAS) values. The higher AAS value of the HRT compared to that of inlet heavy metal concentration suggested that the change of HRT has a significant influence on HMRE and CODRE. Overall, the results obtained from this study demonstrated that ANNs can efficiently predict the RBC behaviour with regard to heavy metal and COD removal characteristics under the prevailing operational conditions.

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Nostoc muscorum was isolated from a coal mining pit in Chiehruphi, Meghalaya, India, and its potential to remove Zn(II) and Cu(II) from media and the various biochemical alterations it undergoes during metal stress were studied. Metal uptake measured as a function of the ions removed by N. muscorum from media supplemented independently with 20 μmol/L ZnSO4 and CuSO4 established the ability of this cyanobacterium to remove 66% of Zn(2+) and 71% of Cu(2+) within 24 h of contact time. Metal binding on the cell surface was found to be the primary mode of uptake, followed by internalization. Within 7 days of contact, Zn(2+) and Cu(2+) mediated dissimilar effects on the organism. For instance, although chlorophyll a synthesis was increased by 12% in Zn(2+)-treated cells, it was reduced by 26% in Cu(2+)-treated cells. Total protein content remained unaltered in Zn(2+)-supplemented medium; however, a 15% reduction was noticed upon Cu(2+) exposure. Copper enhanced both photosynthesis and respiration by 15% and 19%, respectively; in contrast, photosynthesis was unchanged and respiration dropped by 11% upon Zn(2+) treatment. Inoculum age also influenced metal removal ability. Experiments in the presence of 3-(3,4-dichlorophenyl)-1,1-dimethylurea (a photosynthetic inhibitor), carbonyl cyanide m-chlorophenyl hydrazone (an uncoupler), and exogenous ATP established that metal uptake was energy dependent, and photosynthesis contributed significantly towards the energy pool required to mediate metal removals.