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Soil contamination is emerging as a major threat to environment as well as human health. The major causes of contamination are due to the rapid growth in industrial development, intensive agriculture and anthropogenic activities releasing heavy metals, chemicals, salts and other disease causing agents. The heavy metals decreases the quality of soil by leaching into it and thereby causing groundwater contamination. Therefore, remediation of such soils is necessary. Various methods are employed to remove the contaminants from soil. The paper focuses on using biopolymers as remedial agent in cadmium contaminated soil. Biopolymers are the polymeric molecules that are harmless and eco-friendly which occurs in nature. In the present study, starch based and cellulose based biopolymers were used to remediate clayey soil which is artificially contaminated using cadmium chloride at different concentrations. The effectiveness of treatment and a comparative study upon addition of both biopolymers will be evaluated by means of atterberg limits, column leaching test, strength characteristics and micro structural analysis., {"references":["Xia, W. Y., Feng, Y. S., Jin, F., Zhang, L. M., & Du, Y. J. (2017). Stabilization and solidification of a heavy metal contaminated site soil using a hydroxyapatite based binder. Construction and Building Materials, 156, 199-207.","Chen, R., Ramey, D., Weiland, E., Lee, I., & Zhang, L. (2016). Experimental investigation on biopolymer strengthening of mine tailings. Journal of Geotechnical and Geoenvironmental Engineering, 142(12), 06016017.","Hataf, N., Ghadir, P., & Ranjbar, N. (2018). Investigation of soil stabilization using chitosan biopolymer. Journal of Cleaner Production, 170, 1493-1500.","Chen, C., Wu, L., Perdjon, M., Huang, X., & Peng, Y. (2019). The drying effect on xanthan gum biopolymer treated sandy soil shear strength. Construction and Building Materials, 197, 271-279.","Chang, I., & Cho, G. C. (2012). Strengthening of Korean residual soil with β-1, 3/1, 6-glucan biopolymer. Construction and Building Materials, 30, 30-35.","Latifi, N., Horpibulsuk, S., Meehan, C. L., Abd Majid, M. Z., Tahir, M. M., & Mohamad, E. T. (2017). Improvement of problematic soils with biopolymer—an environmentally friendly soil stabilizer. Journal of Materials in Civil Engineering, 29(2), 04016204."]}

Table S3. Year wise rotavirus genotype distribution across 7 sites. The file contains details of year wise distribution of rotavirus genotypes in children with acute gastroenteritis in India across 7 sites. (DOCX 19 kb)

Table S2. Association between rotavirus genotype and severity of diarrhoea. The file contains details of the six common rotavirus genotypes in this study, and their association with severity of diarrhoea in children

Table S1. List of excluded cases. The list contains details of reasons for site wise exclusion of cases from final analysis. (DOCX 16 kb)

Table S5. Rotavirus genotype distribution in south Indian sites. The file contains details of year wise distribution of rotavirus genotypes in the 5 south Indian sites from July 2012 to June 2016. (DOCX 20 kb)

Table S4. Rotavirus genotype distribution in north Indian sites. The file contains details of year wise distribution of rotavirus genotypes in the 2 north Indian sites from July 2012 to June 2016. (DOCX 20 kb)

In this study, the potential of RGB color imaging to detect fungal contamination in three varieties (Khalas, Fard and Naghal) of dates was investigated. The samples were treated as three groups: UC (untreated control), SC (surface sterilized, rinsed and air-dried) and IS (surface sterilized, rinsed, air-dried and fungal inoculated). Color images of control samples and A. flavus inoculated date fruits after every 48 h of inoculation for 10 days were acquired using an RGB color imaging system (n=3150). The classification accuracies for IS were compared with UC and SC separately using a two-class model (control vs. infected (all stages of infection together)), six-class model (control, infected day 2, day 4, day 6, day 8 and day 10) and pair-wise model (control vs. each stage of infection). In the two-class model, the highest accuracy obtained by Fard, Khalas and Naghal dates were 97, 100 and 99%, respectively. The developed algorithm was also tested on pooled dates (all three varieties were combined together: control vs infected), and 98% and 99% of infested samples were correctly classified from untreated control and sterile control, respectively in two class models. In six class models, highest classification accuracies of 99-100% were obtained for IS Day 10 in all three date varieties.