Libraries underpin education, research, literacy and social development, yet the individuals who shaped Indian library development are seldom examined together. This historical and documentary study examines the contributions of Padma Shri awardees: S. R. Ranganathan (1957), B. S. Kesavan (1960), Iyyanki Venkata Ramanayya (1972), Syed Bashiruddin (1976), P. N. Kaula (2004), Palam Kalyanasundaram (2023) and Anke Gowda M. (2026). The study draws on official Padma Awards records, institutional profiles, scholarly articles, legislation and press reports. Information was extracted, cross-checked and grouped through thematic analysis. Four themes emerge: knowledge organisation and bibliographic control, public libraries and access to knowledge, library education and professional scholarship, and social responsibility. The seven contributions prove complementary: theoretical foundations, national bibliographic infrastructure, mass library mobilisation, formal professional training, scholarly communication, and philanthropic and community-based access. Two awardees were recognised in the field of social work, which separates their library service from their wider social contribution. The findings imply that public library services, information discovery, access, professional education and preservation remain central to library development. The study is limited by its dependence on available documentary evidence.

It is a quantitative cross-sectional study to examine the relationship between university level Kho-Kho participation and perceived local economic development in the state of Karnataka, India. Data were collected from 210 male university and college Kho-Kho players using a structured five-point Likertscale questionnaire on sports participation intensity, team cohesion, employment opportunities, local business growth, infrastructure development and perceived local economic development. Descriptive statistics, Pearson correlation, and multiple linear regression were used. All five explanatory constructs showed positive and statistically significant associations with perceived local economic development. Infrastructure development demonstrated the largest standardized regression coefficient (β = 0.34), followed by sports participation intensity (β = 0.31), employment opportunities (β = 0.28), team cohesion (β = 0.19), and local business growth (β = 0.17). The regression model accounted for 64% of the variance in perceived local economic development (R² = 0.64; adjusted R² ≈ 0.62; model p < 0.001). These findings indicate meaningful associative relationships between sports-related participation and perceived local economic development among the sampled players. Because the study is cross-sectional and relies on self-reported perceptions, the findings should not be interpreted as evidence of causal effects or objective changes in local economic output. The study contributes to discussion of grassroots indigenous sport as a potential component of local social and economic development planning while highlighting the need for longitudinal and objective economic measurement.

Dr Gourab Mukherjee is an Assistant Professor in the School of Mathematics and Natural Sciences at Chanakya University. Prior to his current appointment, he served as a DST-INSPIRE Faculty at CSIR–Indian Institute of Chemical Technology (IICT), Hyderabad, and as a MOPGA Visiting Researcher at iSm2-BiosCiences, Institut des Sciences Moléculaires de Marseille, France. He obtained his Ph.D. in Chemistry from IIT Guwahati and pursued postdoctoral research at the Tata Institute of Fundamental Research (TIFR), Mumbai, and the University of Edinburgh, UK. He also held a Visiting Research Fellowship at the University of Manchester. Dr Mukherjee’s research lies at the interface of inorganic and bioinorganic chemistry, with a focus on the design and mechanistic investigation of transition metal complexes relevant to biological and catalytic processes. Some of his works have been published in reputed international journals.

The knowledge of landscape dynamics aids in evolving strategies for the prudent management of natural resources to sustain ecosystem services. The availability of spatiotemporal remote sensing data with advancements in artificial intelligence (AI) and machine learning (ML) algorithms has aided in assessing the ecological status in urban environments, markedly revealing complex patterns and interactions. The current communication presents landscape dynamics in the Bengaluru Urban district from 1973 to 2022 using a supervised machine learning technique based on the Random Forest algorithm with temporal Landsat data, which showed a 51.86% increase in the built-up area and a 26.28% decrease in the green cover. Rapid unplanned urbanization after globalization and the opening up of Indian markets (in Bengaluru city) has witnessed erosion in the natural surface (waterbodies and green cover) in the neighborhood, which has been impacting the health of the environment and people. Computation of fragmentation indices showed a decline of the native green cover by 177.2 sq. km. in the southern part of the district. Likely land use changes are predicted using the Cellular Automata Markov model considering the base case scenario. The analyses revealed a further possible increase in built-up to 1536.08 sq. km, a decrease in green cover by 14.32 sq. km by 2038, and the disappearance of water bodies, which highlights the need to mitigate the adverse impacts of land use changes through planned urbanization considering the environment and livelihood of local communities. The decline of heat sinks such as water bodies and green cover would contribute to an increase in the land surface temperature (LST), which would affect the microclimate of Bengaluru, highlighting the need to sustain ecosystem services to support the livelihood of local communities. Understanding the ecological significance of diverse habitat characteristics of the urban region and the prediction of likely changes in a high degree of spatial heterogeneity would assist the decision-makers in framing appropriate policies.

Background: Studies have indicated that mothers are essential primary informants for adolescent girls regarding menstruation. Their knowledge and comfort levels regarding this subject considerably influence the information that their daughters receive. In addition to influencing the daughters’ initial experiences of menarche, maternal attitudes towards menstruation also affects their broader perceptions of menstruation throughout adolescence. This study aims to investigate mothers’ attitudes regarding menstruation, focusing on mother-daughter conversations and their influence on girls’ menstrual health education and experiences. Method: A phenomenological research design using the focus group discussion technique was employed to procure data. Fifty-three participants were recruited using organisational and advertisement techniques of purposive sampling. Six focus group discussions were conducted with participants’ spoken language. The audio recording was translated and transcribed verbatim into the English language. Using Atlas.ti software, a qualitative research analyst performed thematic analysis on verbatim transcripts from discussions in six focus groups. Outcome: The results of the study have unveiled thoughts and feelings of mothers anticipating their daughter’s onset of menstruation. It highlights that mothers’ perceptions are largely shaped by their personal feelings, especially surrounding issues of safety, protection, and the daughters’ ability to understand and manage their menstrual health. The findings offer a detailed insight into the mothers’ challenges, their support systems, and their psychological and emotional states as they navigate this significant transition for their daughter’s approaching puberty. Recommendations: A comprehensive instrument is necessary to assess attitudes around menstruation, enabling the identification of ways to provide mothers, women, and girls with vital information and assistance, thereby fostering positive body acceptance.