Rice husk has tremendous potential as a remediation material for the removal of arsenic from groundwater. The present work investigates the possibility of the use of rice husk adsorption technology without any pretreatment in the removal of arsenic from aqueous media. Various conditions that affect the adsorption/ desorption of arsenic are investigated. Adsorption column methods show the complete removal of both As(III) and As(V) under the following conditions: initial As concentration, 100 µg/L; rice husk amount, 6 g; average particle size, 780 and 510 µm; treatment flow rate, 6.7 and 1.7 mL/min; and pH, 6.5 and 6.0, respectively. The desorption efficiencies with 1 M of KOH after the treatment of groundwater were in the range of 71-96%. The present study might provide new avenues to achieve the arsenic concentrations required for drinking water recommended by Bangladesh and the World Health Organization (WHO).
Objectives: This study aimed to clarify the performance of automatic detection of subsolid nodules by commercially available software on computed tomography (CT) images of various slice thicknesses and compare it with visualization on the accompanying vessel-suppression CT (VS-CT) images.Methods: A total of 95 subsolid nodules from 84 CT examinations of 84 patients were included. The reconstructed CT image series of each case with 3-, 2-, and 1-mm slice thicknesses were loaded into a commercially available software application (ClearRead CT) for automatic detection of subsolid nodules and generation of VS-CT images. Automatic nodule detection sensitivity was assessed for 95 nodules on each series of images acquired at 3 slice thicknesses. Four radiologists subjectively evaluated visual assessment of the nodules on VS-CT.Results: ClearRead CT automatically detected 69.5% (66/95 nodules), 68.4% (65/95 nodules), and 70.5% (67/95 nodules) of all subsolid nodules in 3-, 2-, and 1-mm slices, respectively. The detection rate was higher for part-solid nodules than for pure ground-glass nodules at all slice thicknesses. In the visualization assessment on VS-CT, 3 nodules at each slice thickness (3.2%) were judged as invisible, while 26 of 29 (89.7%), 27 of 30 (90.0%), and 25 of 28 (89.3%) nodules, which were missed by computer-aided detection, were judged as visible in 3-, 2-, and 1-mm slices, respectively.
Conclusions:The automatic detection rate of subsolid nodules by ClearRead CT was approximately 70% at all slice thicknesses. More than 95% of subsolid nodules were visualized on VS-CT, including nodules undetected by the automated software. Computed tomography acquisition at slices thinner than 3 mm did not confer any benefits.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.