Streptomyces sp. B-PNG23 was selected as a promising cellulolytic strain and tested for its ability to produce cellulases from agroindustrial residues. A pH value of 7 and temperature of 28°C were found to be optimal for maximum enzyme production. The highest endoglucanase activity was obtained in a medium comprised of wheat bran (2 g/l), yeast extract (2 g/l), NaCl (2 g/l), NH4Cl (2.5 g/l), and (0.4 g/l) of MgSO4. The enzyme was active at a broad range of pH (5-8) and temperatures (40-70°C). The optimum pH and temperature were 6 and 50°C, respectively. In the presence of metal ions Mn2+, Cu2+ and NH4 + the activity of the enzyme increased significantly. The enzyme retained 50% of its activity after heating at 50°C for 6 h. This enzyme could be considered as a thermotolerant biocatalyst that could be utilized in biotechnological applications

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Coronavirus disease has become a worldwide threat affecting almost every country in the world. The aim of this study is to identify the COVID-19 cases (positive, recovery and death) in Algeria using the Double Exponential Smoothing Method and an Autoregressive Integrated Moving Average (ARIMA) model for forecasting the COVID-19 cases.The data for this study were obtained from March 21st, 2020 to November 26th, 2020. The daily Algerian COVID-19 confirmed cases were sourced from The Ministry of Health, Population and Hospital Reform of Algeria. Based on the results of PACF, ACF, and estimated parameters of the ARIMA model in the COVID-19 case in Algeria following the ARIMA model (0,1,1). Observed cases during the forecast period were accurately predicted and were placed within the prediction intervals generated by the fitted model. This study shows that ARIMA models with optimally selected covariates are useful tools for monitoring and predicting trends of COVID-19 cases in Algeria.