Punjabi University

Purpose. Injuries are common in athletics and reduce athlete availability. While injury incidence is well described, less is known about rehabilitation burden – the time from injury onset to unrestricted sports participation – particularly in Indian athletes. Material & Methods. This prospective cohort study followed 95 national-level track-and-field athletes (56 men, 39 women) over one competitive season (November 2023 – October 2024). Injury surveillance was conducted by physiotherapists using International Olympic Committee (IOC) consensus definitions. Rehabilitation duration was measured from injury reporting until medical clearance for unrestricted participation. Descriptive statistics were used, and rehabilitation burden was calculated as days lost per 1000 athlete-days. Results. Seventy-seven injuries occurred in 71 athletes (74.7%). Muscle injuries were most frequent (n=25; mean rehabilitation 13 days), whereas tendon, bone stress, and joint injuries required longer recovery. Post-operative injuries (n=3) showed the longest rehabilitation duration (mean 260 days). Severe injuries accounted for 36.4% of cases and required a median of 60 days, compared with 20 days for moderate and 5.5 days for mild injuries. Overuse injuries resulted in substantially greater time loss than acute injuries (mean 87 vs. 12 days). Throwers sustained the highest number of injuries (n=30) and had the longest average rehabilitation duration (mean 70 days). Overall rehabilitation burden was 106 days per 1000 athlete-days, indicating approximately 10% athlete unavailability. Conclusions. Although muscle injuries are common and short-lived, severe, overuse, and post-operative injuries contribute disproportionately to rehabilitation burden in national-level athletics. Targeted prevention strategies, structured rehabilitation, and adequate physiotherapy resources are essential to reduce athlete unavailability.

This study examines the mechanisms by which cognitive diversity affects team performance in India’s banking sector, an industry characterized by digital transformation and hierarchical organizational norms. Grounded in the social cognitive theory, we propose a triadic model in which team efficacy mediates the relationship between cognitive diversity and performance, while team learning moderates the efficacy–performance pathway. Data were collected from 39 banking teams (392 respondents: 33 team leaders and 359 team members) using a three-wave, time-lagged survey design. Psychometric analyses confirmed strong internal consistency ( α = 0.869–0.905) and appropriate team-level aggregation (ICC (1) = 0.18–0.23; ICC (2) = 0.72–0.78). Covariance-based structural equation modelling revealed that cognitive diversity exhibited both a direct positive association with team performance ( β = 0.113, p < .01) and an indirect association mediated through team efficacy, with bootstrapped confidence intervals (0.071–0.152) confirming robustness. Team learning significantly strengthened the efficacy–performance relationship, with conditional indirect effects increasing from 0.034–0.104 under low-learning conditions to 0.099–0.208 under high learning conditions. These findings advance the social cognitive theory by establishing team efficacy as the psychological mechanism linking diverse cognitive inputs to coordinated action and team learning as a critical boundary condition in high-power-distance contexts. Practically, this study demonstrates that banking organizations must systematically cultivate collective efficacy and embed continuous learning routines to harness the performance benefits of cognitive diversity.

This study presents a robust and scalable method for automatic layout detection in digitized newspapers to facilitate efficient knowledge extraction and information retrieval. A custom dataset comprising annotated newspaper images in English, Hindi, and other languages was developed, with layout regions categorized into five primary classes. An enhanced YOLOv12 object detection model was trained on this dataset and evaluated using the mean Average Precision (mAP) metric across various Intersection over Union (IoU) thresholds. The model achieved a mAP@50 of 0.88, demonstrating strong detection performance and outperforming several stateof-the-art object detection models in the same task. The findings validate the effectiveness of the proposed approach in handling multilingual, structurally diverse newspaper formats. This research provides a practical framework for integrating automated layout analysis into digital archiving systems, OCR pipelines, and media monitoring applications. It also supports broader efforts to digitize historical print media and improve accessibility to regional content, thereby enabling enhanced research, journalism, and public engagement.

There is need to strengthen the barcode reference library of Indian butterfly species to better understand the genetic structure of these species. The present study addresses by generating barcodes for eight species of subtribe Polyommatina, including high altitude species Plebejus samudra which is barcoded for the first time globally. All the generated DNA barcodes submitted to the Genbank and accession numbers have been procured. The phylogenetic relationships were inferred using the maximum likelihood method. All the eight sequenced species grouped within the monophyletic clades along with other congeneric species. The Intergeneric, interspecific and intraspecific divergence values were also calculated.