https://www.selleckchem.com/products/z-vad(oh)-fmk.html PCA confirmed the input source of nutrients in the river from both natural and anthropogenic sources. Moreover, the upstream WQ assessed was found to be good as compared to the severely polluted downstream region. Due to COVID-19 and shutdown in the country, reduction of pollution load in the river was observed due to the rejuvenation capability of river Ganga. This information can assist the environmentalist, policymaker, and water resources planners & managers to prepare strategic planning in advance to maintain the aesthetic and cultural value of Ganga river in future. The coronavirus disease 2019 (COVID-19) has evolved into a worldwide pandemic. CT although sensitive in detecting changes suffers from poor specificity in discrimination from other causes of ground glass opacities (GGOs). We aimed to develop and validate a CT-based radiomics model to differentiate COVID-19 from other causes of pulmonary GGOs. We retrospectively included COVID-19 patients between 24/01/2020 and 31/03/2020 as case group and patients with pulmonary GGOs between 04/02/2012 and 31/03/2020 as a control group. Radiomics features were extracted from contoured GGOs by PyRadiomics. The least absolute shrinkage and selection operator method was used to establish the radiomics model. We assessed the performance using the area under the curve of the receiver operating characteristic curve (AUC). A total of 301 patients (age mean ± SD 64 ± 15 years; male 52.8 %) from three hospitals were enrolled, including 33 COVID-19 patients in the case group and 268 patients with malignancies or pneumonia in the control group. Thirteen radiomics features out of 474 were selected to build the model. This model achieved an AUC of 0.905, accuracy of 89.5 %, sensitivity of 83.3 %, specificity of 90.0 % in the testing set. We developed a noninvasive radiomics model based on CT imaging for the diagnosis of COVID-19 based on GGO lesions, which could be a promi