Government of West Bengal

Since the introduction of the Street Lighting National Programme (SLNP) in India in 2015, municipalities and local bodies have been upgrading and revamping existing discharge lamp-based street lighting systems with light-emitting diode (LED)-based ones for enhancing energy efficiency. In recent years, artificial neural networks (ANNs) have emerged as a potent machine learning tool for predictive modelling across major engineering disciplines. This study applied feedforward ANNs for street lighting planning for single-sided, opposite, and staggered layouts of LED luminaires of common power ratings (35–116 W). Extensive photometric simulations were performed, and the generated datasets were utilized to train, validate, and test ANN models for the prediction of average illuminance, overall uniformity of illuminance, and installation energy efficiency. All the ANN models demonstrated good performance, and the error margin for the prediction of pertinent photometric and energy efficiency parameters was satisfactory. This machine learning-based approach can assist municipal engineers in street lighting project planning and implementation.

Lifetimes for the 4(1)(+) and 6(1)(+) states have been measured using gamma - gamma fast timing technique for low lying states of Xe-130, populated from beta(- )decay of the parent I-130 produced through U-nat(a, f) reaction at E-a = 40 MeV. VENTURE array comprising of eight fast CeBr3 detectors is used for the measurement. The reduced transition probabilities deduced from the measured lifetimes have been compared with results from the large basis shell model calculation and the interacting boson model calculation.

Abstract. Setyawan AD, Sutarno, Sugiyarto, Sunarto, Nursamsi I, Budiharta S, Supriatna J, Pradhan P. 2025. Climate-induced habitat contraction and elevational redistribution of Selaginella willdenowii and S. intermedia in Southeast Asia. Asian J For 9: 440-455. Climate change is increasingly recognized as a major threat to tropical biodiversity, particularly for moisture-dependent cryptogams with narrow environmental requirements. This study assessed the current and future habitat suitability of Selaginella willdenowii and Selaginella intermedia across Southeast Asia using Maximum Entropy (MaxEnt) modeling. A total of 726 occurrence records for S. willdenowii and 679 records for S. intermedia were compiled from field surveys conducted across Java Island, Indonesia and verified records obtained from the Global Biodiversity Information Facility (GBIF). Models were developed using climatic, edaphic, topographic, and UV-B radiation variables and projected under four Representative Concentration Pathway (RCP) scenarios (RCP 2.6, 4.5, 6.0, and 8.5) for 2030, 2050, and 2080. The models showed high predictive performance, with AUC values exceeding 0.93 and TSS values exceeding 0.87. Annual precipitation, temperature, elevation, and UV-B radiation were identified as the most influential predictors of habitat suitability. Current suitable habitats were concentrated in mainland and maritime Southeast Asia, particularly in Indonesia, Peninsular Malaysia, and the Philippines. Java Island emerged as a major regional hotspot, supporting 57.7% and 48.9% suitable habitat coverage for S. willdenowii and S. intermedia, respectively. Future projections consistently indicated habitat contraction under all climate scenarios, with greater losses occurring under higher emission pathways and later projection periods. By 2080, suitable habitat was projected to decline by 16.9-23.4% for S. willdenowii and 27.3-33.2% for S. intermedia accompanied by pronounced upslope redistribution toward montane environments. The greater habitat loss predicted for S. intermedia reflects its stronger dependence on elevational gradients and narrower climatic niche. These findings identify montane landscapes as critical climate refugia and emphasize the importance of maintaining elevational connectivity to support the long-term persistence of tropical understory cryptogams under climate change.

INTRODUCTION:Pediatric trigger thumb is a developmental condition characterized by flexion deformity of the interphalangeal joint due to constriction at the A1 pulley. Although spontaneous resolution has been reported, optimal treatment timing remains controversial. This study aimed to compare outcomes between conservative and surgical management in children aged up to five years. METHODOLOGY:A prospective analytical cohort study was conducted at a tertiary care center in Kolkata over 18 months. Fifty-eight children with clinically diagnosed trigger thumb were enrolled. All participants initially underwent six months of conservative observation. Those who did not improve underwent open A1 pulley release. The primary outcome was complete resolution of deformity. Secondary outcomes included degree of improvement, recurrence, complications, and time to resolution. Statistical analyses included the chi-square test, the Mann-Whitney U test, the Cox proportional hazards model, and multivariable logistic regression. RESULTS:Nineteen children (32.8%) improved with conservative management, whereas 39 (67.2%) required surgery. Surgical intervention achieved 100% resolution with no recurrence or major complications. Mean improvement in deformity was significantly greater in the surgical group (50.8° ± 5.8°) compared with the conservative group (14.5° ± 3.7°; p < 0.001). The relative risk of complete resolution with surgery was 3.05 (95% confidence interval (CI): 2.05-4.55), with an absolute risk reduction of 67.2% and a number needed to treat of approximately two. Cox analysis demonstrated faster recovery with surgery (HR: 4.62; 95% CI: 2.71-7.88; p < 0.001). An initial deformity of >20° independently predicted conservative failure. CONCLUSION:Surgical release provides significantly superior and faster resolution compared to conservative management, particularly in children presenting with deformity greater than 20°.