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Land use controversies often dog the construction of hydroelectric projects. Many important projects are battling in the tribunals because of Geo-environmental concerns. The paucity of scientific studies objectively investigating the litigations further aggravates the unsolvability of the disputes. The Sawra-Kuddu Hydroelectric project, India, became a subject of litigation when project affected persons filed a suit in the National Green Tribunal questioning the sustainability of the built environment. The litigants petitioned that the additional adit's blasting vibrations can trigger the landslide of slip zone, and Thana village situated above it. The petitioners further claimed that vibrations had cracked the houses. They also asserted degradation in the apple cultivation due to tunnel construction. The tribunal took a stern note of the petition and banned the construction activities. The tribunal further ruled that a scientific investigation must be conducted to ascertain the cause of petitioners' claims. The study results revealed that the vibrations originating from adit excavation are insignificant and cannot destabilize the slip zone. The high fluctuation of annual rainfall and tectonic strain were deemed responsible for the differential settlement of foundations and cracks in the houses. The horticulture study indicated that the physiological processes of apple crops were normal. The study's findings convinced the tribunal, and construction activities were resumed, resulting in the disputed 111 MW project's commissioning. Many run-of-the-river hydroelectric projects in the world are battling similar litigations addressed in the present study. A similar objective methodology is a need for the hour to resolve other hydroelectric projects' sustainability issues. The study findings will pave the path for the swift resolution of land disputes related to similar projects.

The present study compares three different techniques (decision tree, artificial neural network and multivariate regression analysis) for predicting blast-induced ground vibrations in some Indian tunnelling projects. The performance of these models was also compared to site-specific conventional predictor equations. A database consisting of 137 vibration records was randomly divided into training and testing sets for model generation. Eight input parameters (total charge, tunnel cross-section, maximum charge per delay, number of holes, hole diameter, distance from blasting face, hole depth and charge per hole) were selected for model development using bivariate correlation analysis. Results indicated that the decision tree is best suited for predicting vibrations. The decision tree further suggested that the intensity of near-field ground vibrations is mainly affected by total charge fired in a round, whereas the intensity of far-field vibrations is governed by maximum charge per delay and charge per hole. Conventional ground vibration predictors and machine learning techniques such as neural networks do not depict the relationship between input and output parameters. However, the present study substantiates that the decision tree can be a good tool for precise prediction of ground vibrations. Further, the decision tree can classify and relate different blast design parameters for refining blast designs to control ground vibrations on sites.

Pyrazinamide (PZA) is an important first-line antituberculosis drug because of its sterilizing activity against semidormant tubercle bacilli. In spite of its very high in vivo activity, its in vitro activity is not apparent unless an acidic environment is available, which makes PZA susceptibility testing difficult by conventional methods. The present study was, therefore, planned to assess the performance of the colorimetric BacT/ALERT 3D system and compare the results with those from conventional tests, i.e., the Löwenstein-Jensen (LJ) proportion method (pH 4.85) and Wayne's pyrazinamidase (PZase) assay, using 107 clinical isolates. The concordance among all of these tests was 89.71% after the first round of testing and reached 92.52% after resolution of the discordant results by retesting. Prolonged incubation of the PZase tube for up to 10 days was found to increase the specificity of the PZase test. The concordances between LJ proportion and BacT/ALERT 3D, LJ proportion and the PZase assay, and BacT/ALERT 3D and the PZase assay were found to be 99.06%, 93.46%, and 92.52%, respectively. Using the LJ results as the gold standard, the sensitivities of BacT/ALERT 3D and the PZase assay were 100 and 82.85%, respectively, while the specificity was 98.61% for both of the tests. The difference between the sensitivities of BacT/ALERT 3D and the PZase assay was significant ( P = 0.025). The mean turnaround times for the detection of resistant and susceptible results by BacT/ALERT 3D were 8.04 and 11.32 days, respectively. While the major limitations associated with the PZase assay and the LJ proportion method are lower sensitivity in previously treated patients and a longer time requirement, respectively, the BacT/ALERT 3D system was found to be rapid, highly sensitive, and specific.