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Constructed wetlands (CWs) have great potential as low-cost natural wastewater treatment in developing countries. The present study appraises the performance of the vertical flow constructed wetland for domestic wastewater treatment. More specifically, the potential of Canna Indica in the removal of carbon, nitrogen, and phosphorus (CNP) from wastewater under tropical conditions. CW cell was fabricated with a vegetative layer of Canna Indica and tested with domestic wastewater. Based on the test results, Canna Indica shows a high Removal Efficiency (RE) of Chemical Oxygen Demand (COD), Biological Oxygen Demand (BOD5) on the order of 87% and 91%, respectively. Similarly, nutrients removal efficiency for total nitrogen (TN), total phosphorus (TP) was found to be 97% and 98%, respectively. The investigation also revealed that there is considerable removal of sulfates with efficiency equal to 78.4%. Overall, the Canna Indica based CWs were found to be suitable for wastewater treatment in the tropical regions, provided a viable medium for treating the wastewater in peri-urban and rural areas of developing countries. This study investigates the performance of Canna indica based vertical flow wetlands for greywater treatment. The study investigates the results at different hydraulic retention times and loading rates. There are no much studies reporting the performance of this variety of plant species under a tropical humid climate. The results from the study can encourage adoption of this plant variety, indigenous to this part of the country, for wastewater treatment It could emphasize the importance of familiarity with constructed wetlands to comprehend the RE of various climatic zones. It is possible to highlight the Canna-based CW's efficiency in removing organics and nutrients from domestic wastewater. The possibility for field-scale Canna-based CW to remove pollution in tropical climates was investigated, and Decentralization of wastewater treatment at the household level to apply CWs that will improve wastewater quality. [ABSTRACT FROM AUTHOR]

Objective To evaluate the accuracy of noninvasive imaging methods including gray-scale ultrasound, ultrasound shear wave elastography, unenhanced computed tomography (CT), and proton density fat fraction (PDFF) on magnetic resonance imaging (MRI) using three-dimensional (3D) multiecho multipoint chemical shift–encoded spoiled gradient echo (q-DIXON) sequence in the quantification of hepatic steatosis, with proton MR spectroscopy (H¹-MRS) as the reference standard in Indian population. Methods Our study included 100 consecutive adult patients referred to the department of radiology in our hospital for imaging of liver. Fat content of liver was recorded using MRI (H¹-MRS and q-DIXON), unenhanced CT (average liver attenuation [ALI] and liver attenuation index [LAI]) and ultrasonography (USG) (gray-scale grading and shear wave elastography [SWE]). Data were analyzed by linear regression and Bland–Altman analysis for each technique compared with H¹-MRS. The diagnostic performances of all the methods were compared using DeLong test, for detection of mild and moderate-to-severe hepatic steatosis, separately. Results MRI q-DIXON PDFF showed excellent correlation (r = 0.917, r² = 0.840) and strong agreement (1.48 ±3.01) with H¹-MRS-derived PDFF measurements. Unenhanced CT-based methods showed moderate correlation with modest agreement (r = −0.826, r² = 0.681, −40.18 ± 16.05 for ALI and r = −0.858, r² = 0.735, 13.4 ± 15.3 for LAI) whereas USG gray-scale assessment showed low correlation (weighted Kappa value 0.366) with H¹-MRS PDFF. No correlation was found between USG-SWE results and PDFF measured with H¹-MRS. Comparison of areas under curve (AUCs) using DeLong test revealed that MRI q-DIXON method performed the best for diagnosis of hepatic steatosis compared with rest. For moderate to severe steatosis, MRI q-DIXON and unenhanced CT-based methods had comparable diagnostic performance with AUCs not showing statistically significant differences. Conclusion MRI q-DIXON shows strongest correlation with MRS and should be preferred for estimation of hepatic fat, especially when MRS is not available. Unenhanced CT shows limited diagnostic performance in detecting mild steatosis; however, it certainly has a role in diagnosing moderate-to-severe hepatic steatosis, such as evaluating donor candidates for living donor liver transplantation. USG, using both the traditional four-grade visual assessment and elastography in the present form, appears to have limited role in liver fat quantification. [ABSTRACT FROM AUTHOR]

An accurate and timely forecast of extreme events can mitigate negative impacts and enhance preparedness. Real-time forecasting of extreme flood events with longer lead times is difficult for regions with sparse rain gauges, and in such situations, satellite precipitation could be a better alternative. Machine learning methods have shown promising results for flood forecasting with minimum variables indicating the underlying nonlinear complex hydrologic system. Integration of machine learning methods in extreme event forecasting motivates us to develop reliable flood forecasting models that are simple, accurate, and applicable in data scare regions. In this study, we develop a forecasting method using the satellite precipitation product and wavelet-based machine learning models. We test the proposed approach in the flood-prone Vamsadhara river basin, India. The validation results show that the proposed method is promising and has the potential to forecast extreme flood events with longer lead times in comparison with the other benchmark models.