Osmania University

This paper examines the tension between archival silence and forensic memory in Anil’s Ghost by Michael Ondaatje, situating the novel within the violent socio-political landscape of postcolonial Sri Lanka. Archival silence is understood as the systematic erasure, omission, or suppression of marginalized voices within official state records, particularly in contexts marked by political conflict and institutional control. In contrast, forensic memory emerges as a counter-discursive practice that seeks to reconstruct suppressed histories through scientific investigation, material evidence, and interpretive recovery. The novel foregrounds this dynamic through its focus on forensic experts who attempt to identify victims of state violence, thereby challenging the authority of official narratives and exposing the fragility of institutional truth.

Groundwater constitutes the principal source of water for drinking and irrigation in semi-arid regions of Telangana State, particularly in limestone-dominated terrains affected by mining and intensive agriculture. The present study evaluates the hydrogeochemical characteristics of groundwater in and around the Tandur Limestone area, Vikarabad District, Telangana, with the objectives of assessing its suitability for drinking and irrigation and understanding the geochemical processes governing groundwater composition. Thirty-five groundwater samples were collected during pre-monsoon and post-monsoon seasons and analysed for major physico-chemical parameters and ions following standard procedures. Hydrochemical facies were identified using Piper diagrams, and irrigation suitability was assessed using indices such as SAR, RSC, Kelly’s Ratio, and per cent sodium. The results indicate that groundwater chemistry is predominantly controlled by carbonate weathering processes, resulting in Ca–Mg–HCO₃ type waters, with localized influence of anthropogenic activities reflected by elevated nitrate, fluoride, and chloride concentrations in certain locations. Seasonal variations suggest enhanced water–rock interaction during the post-monsoon period. While most samples are suitable for drinking and irrigation, a few exceed permissible limits, warranting continuous monitoring and groundwater management measures in this mining-dominated limestone terrain.

The Indian Summer Monsoon (June–September, JJAS) plays a critical role in regulating water resources, agriculture, and hydroclimatic extremes across India, yet projecting future changes in monsoon variability remains challenging due to the coarse spatial resolution and biases of earth system models (ESMs). In this study, we develop high-resolution (0.25°) projections of monsoon rainfall over India using a statistical downscaling framework that combines weather typing with transfer functions, and we demonstrate how Standardized Precipitation Index (SPI) projections can be used to diagnose future changes in monsoon characteristics. Downscaled simulations from five GCMs are analyzed for a historical period and for two future socioeconomic pathways (SSP2-4.5 and SSP5-8.5). SPI is computed at monthly scale for June, July, August, and September, as well as for the seasonal JJAS total, enabling assessment of both intra-seasonal and seasonal hydroclimatic variability. Evaluation against observations shows that the historical simulations reproduce observed rainfall statistics with high fidelity, capturing both the mean and standard deviation across most regions of India. Furthermore, the downscaled GCMs successfully represent historical extremes, with more than 70% of grid cells capturing observed extreme drought events and over 80% capturing extreme wet events, providing confidence in the robustness of the derived SPI projections. Our next objective is to test the hypothesis that SPI contains discernible signals of key monsoon characteristics, including onset, withdrawal, and intraseasonal variability. If such signals are evident, SPI can serve as a useful diagnostic tool for inferring these features, which are otherwise difficult to predict directly. This framework further enables a range of analyses, including assessment of future projections and evaluation of shifts in the frequency, duration, and intensity of dry and wet spells during the monsoon season under both moderate and high-emission scenarios, thereby revealing changes in intraseasonal variability that may not be captured by seasonal mean rainfall alone.

ABSTRACT A novel series of imidazole–pyrazole ‐ 1,2,3‐triazole hybrids ( 7a–b and 8c–j ) were synthesized and evaluated for their in vitro antidiabetic potential through inhibition of the aldose reductase (AR) enzyme. Sorbinil was used as the standard reference inhibitor (IC 50 = 2.01 ± 0.31 µM). Several hybrids exhibited superior inhibitory activity, particularly the fluoro‐substituted analogue 7a , the methoxy derivative 7b , and the methyl analogue 8c , with IC 50 values of 1.20 ± 0.39, 1.88 ± 0.19, and 1.93 ± 0.23 µM, respectively. The trimethoxy analogue 8h also demonstrated potent activity (IC 50 = 2.19 ± 0.36 µM), comparable to Sorbinil . Molecular docking studies were performed using the AR crystal structure (PDB ID: 1PWM), and the docking protocol was validated by re‐docking the co‐crystallized ligand Fidarestat (RMSD = 1.18 Å). All synthesized hybrids showed stronger binding affinities (–13.8—16.3 kcal/mol) compared to Sorbinil (–11.2 kcal/mol). Notably, compound 8c displayed the highest docking score (–16.3 kcal/mol) and formed key stabilizing interactions, including π–π stacking with Trp219 and π‐cation interactions with Leu301 and Ser302. The favorable binding energies and interaction profiles strongly correlate with the observed in vitro activities, highlighting these hybrids as promising AR inhibitors for antidiabetic drug development.