Search Results (485)

Kazakhstan is a major migration corridor for raptors in Central Asia, yet the migratory connectivity of these species remains poorly documented. We analysed 60 years of ringing data (1966–2025) for three species: Eurasian Sparrowhawk (Accipiter nisus), Northern Goshawk (Astur gentilis), and Shikra (Tachyspiza badia). In total, 5785 individuals were ringed, and 38 recoveries of Kazakhstan-ringed birds were obtained (0.66%). Because recoveries for Goshawk (n = 2) and Shikra (n = 1) are extremely limited, quantitative analyses were restricted to Sparrowhawk recoveries (n = 35), while the other two species are reported descriptively as case records. For Sparrowhawks, migration distances reached 1947 km (mean = 975 km) and did not differ detectably among age classes. Most ringing effort occurred at Shakpak Pass (94.7%), and recoveries indicate connectivity between Kazakhstan, Western Siberia and wintering areas in Central Asia and northern India. Among recovered dead birds (n = 25), shooting (n = 10) and powerline electrocution or collision (n = 3) were frequently reported causes. These long-term ring recoveries provide baseline information on movement connectivity and threats for Central Asian accipiters and highlight the value of sustained monitoring at migration bottlenecks. Full article

Effective crop monitoring during monsoon growing seasons in Central India faces challenges from persistent cloud cover that limits optical remote sensing during critical agricultural periods. This study presents the first attempt to develop a novel set of SAR-derived phenological metrics organized into five thematic categories for monsoon crop discrimination in smallholder agricultural systems. Five major monsoon crops (cotton, rice, maize, soybean, and urad) were analyzed across five different agroclimatic zones in Central India using Sentinel-1 data for the 2021 growing season. Phenological features were extracted from VV, VH polarizations, and their ratio, including seasonal extrema, threshold crossings, duration measures, curve shape descriptors, and area under the curve. Distinct crop-specific signatures were observed, with cotton showing extended phenology and cereal–legume crops displaying compressed, overlapping growth patterns. VV polarization achieved the highest statistical discrimination for intensity-based metrics, with 75% thresholds (VV_HP75V: F = 1287) providing higher separability than other thresholds by capturing near-peak biomass differences. VH performed best for duration and integration-based metrics, while VH/VV provided limited additional separability across metric types. For area-under-the-curve metrics, AUC25 outperformed AUC50 and AUC75 by capturing cumulative backscatter across the broader growing season while remaining robust to soil- and residue-dominated backscatter variability at sowing and harvest. Multiclass classification achieved 48.3% overall accuracy with systematic cereal–legume confusion, reflecting fundamental phenological convergence among monsoon-aligned crops. Cotton achieved the highest performance (F1: 0.79), with VH polarization dominating feature importance (65% of top 20 features). Binary classification revealed crop-specific discrimination patterns: cotton was best separated using VV intensity metrics, maize using the VH/VV ratio, and rice using timing-based features. Cross-district transferability showed the highest mean overall accuracy for rice (74%) and cotton (72%), while the remaining crops showed lower accuracy due to their phenological similarity. These findings highlight both the potential and limitations of SAR phenological metrics for monsoon crop discrimination, with effective results for structurally distinct crops but persistent cereal–legume confusion, requiring further investigation with multi-sensor approaches. Full article

Childhood stunting remains a major public health challenge in India and is influenced by multiple socioeconomic and environmental factors. This ecological study examined district-level correlates of childhood stunting, including Crimes Against Women (CAW), the Multidimensional Poverty Index (MPI), and drought severity, using data from NFHS-5, the National Crime Records Bureau, NITI Aayog’s MPI reports, and the Drought Atlas of India. Spatial autocorrelation and Spatial regression models were applied alongside machine learning approaches and SHAP-based Explainable AI (XAI) interpretation. Childhood stunting exhibited significant spatial clustering (Moran’s I = 0.520, p < 0.001), with hotspots in northern, central, and eastern India. Higher stunting was associated with higher birth order, low maternal BMI, child anaemia, and MPI, and negative associations with iodised salt usage, electricity access, and timely postnatal care. A significant spatial lag parameter (ρ = 0.348) indicated substantial spillover effects. Machine learning models consistently identified MPI, drought severity, and CAW as key predictors. The integrated spatial and machine learning framework identifies key correlates and spatial dependencies of childhood stunting, highlighting the need for region-specific, multisectoral interventions. Full article

Background/Objectives: Primary amoebic meningoencephalitis (PAM) is a rare, fulminant, and often fatal central nervous system infection caused by the opportunistic free-living amoeba Naegleria fowleri. Although Naegleria species are widely present in freshwater and soil worldwide, human disease is associated specifically with pathogenic N. fowleri rather than the many nonpathogenic environmental species, and virulence may vary across N. fowleri isolates. This systematic review aimed to synthesize contemporary global data from 2000 to 2024 to identify recent trends in epidemiology, clinical presentation, diagnosis, treatment, and outcomes. Methods: A systematic literature search was conducted across PubMed, Scopus, and the Cochrane Library, identifying 58 eligible publications encompassing 66 individual cases. Results: Most reports originated from the United States, India, and China. The median patient age was 14 years, with 78% of cases occurring in males. Annual case reports increased from one per year (2000–2005) to over four per year (2020–2024), reflecting either a true rise in incidence or improved detection. Common presenting symptoms included fever, headache, and altered mental status. Diagnosis was confirmed via polymerase chain reaction (PCR) testing or post-mortem biopsy in nearly one-third of cases. Treatment regimens varied, with amphotericin B and miltefosine being the most frequently used agents. Overall mortality was 83%, with survival strongly associated with early initiation of combination therapy. Pediatric patients had a higher survival rate (22%) compared to adults (7.1%). Conclusions: The findings highlight the need for heightened clinical awareness, especially in the context of climate-driven ecological changes that may expand N. fowleri’s geographic range. This review underscores critical gaps in surveillance and diagnostics and emphasizes the importance of a One Health approach to addressing emerging threats like PAM. Further research into novel therapeutics, rapid diagnostics, and global case reporting systems is urgently needed. Full article

Banks around the globe are rapidly progressing towards the adoption of digital currency. However, its adoption rate has been consistently low among both emerging and advanced economies. This study examines the user adoption of the Indian digital currency, the e-Rupee, based on a primary survey conducted between July 2025 and September 2025 of 751 respondents. The study adopted a blend of TAM and nudge theory for the first time in the digital currency domain, using the stated preference method in finance literature to understand the willingness to shift to the e-Rupee in India. Using binary logit regression, we test two hypotheses. The results show that apart from socioeconomic predictors, adoption of the e-Rupee is significantly influenced by digital financial literacy. With respect to the willingness to shift to the e-Rupee, the study found TAM constructs like perceived convenience and perceived belief in the study as the key predictors. Unlike the current literature, our study finds that trust is not a significant predictor of e-Rupee adoption. This highlights the credibility of the central bank of the country and the future growth of its digital currency. The findings highlight the importance of digital financial literacy and behavioral intentions, rather than technical viability, as the key factors in digital currency adoption in India. Full article

Urban blue-green spaces (UBGS) are crucial nature-based solutions for enhancing urban resilience and improving public health. This study examined the experiential relationships linking BGS use to human well-being among users of five urban parks in Delhi, India. Using an integrated experience-centered framework, we collected in-situ survey data (n = 411) to profile usage patterns, assess environmental quality, and quantify restorative outcomes grounded in Attention Restoration Theory (ART) and Stress Reduction Theory (SRT). Advanced analytical techniques, including ordinal logistic regression and interpretable machine learning (SHAP), were used to identify the key factors associated with user satisfaction. The results revealed that for these respondents, BGS appeared to function as an essential neighbourhood, with over 40% visiting three or more times per week. Although visual attractiveness was rated positively, deficits in noise buffering and amenities indicated a gap between aesthetic and functional qualities. Restorative benefits, including emotional calmness, mood refreshment, and fatigue recovery, were consistently reported among respondents. Analyses showed that embodied experiences, particularly post-visit relaxation and physical comfort, were more strongly associated with user satisfaction. SHAP interpretation highlighted seating adequacy, routine use, and thermal comfort as prominent contributors, suggesting somatic relief may be particularly salient. This study provides exploratory evidence from a Global South megacity and context-sensitive insights into how restorative processes operate under high-density urban conditions. The findings show that routine accessibility, basic amenities, and thermal comfort are central to the everyday functioning of blue-green spaces as urban infrastructure, underscoring the need for experience-responsive and equity-oriented urban greening policies in high-density cities. Full article

Over the past few decades, legume-based intercropping has emerged as a strategic agronomic practice to enhance the sustainability and resilience of agro-ecosystems, thanks to its ability to perform biological nitrogen fixation and store soil organic carbon. The present study, given the growing recognition of agroecological practices, aims to analyze through a global bibliometric analysis the research conducted between 1986 and 2025 on legume–non-legume intercropping, with particular emphasis on its ecological and agronomic benefits. The investigation, carried out according to the PRISMA protocol on the Scopus database, selected 167 original English-language articles, excluding reviews, conference proceedings, modeling studies, and meta-analyses. China and India are identified as the most productive countries. Co-occurrence and bibliographic coupling analyses highlight thematic clusters centered on soil fertility, microbial communities, productivity, and the mitigation of environmental impact. Furthermore, management practices such as integrated rotations, cover crops, and agroforestry systems amplify the benefits in terms of carbon accumulation and resilience to adverse climate conditions. The distribution of publications by journal highlights the centrality of journals such as Agriculture, Ecosystems & Environment and Plant and Soil. Overall, the data confirm the crucial role of intercropping as a pillar of the agroecological transition, underscoring the need for policies and research programs capable of amplifying its global adoption. The findings of this study may guide future interdisciplinary research and evidence-based policy decisions aimed at optimizing the design of resilient intercropping systems, tailored to address the challenges posed by climate change and the growing demands of global food security. Full article

This paper examines how Dushyant Kumar’s collection, sāye meṅ dhūp (lit. Sunlight in the Shadows), reinvented the classical ġhazal genre as a vernacular weapon of anti-authoritarian dissent—not by abandoning ambiguity, but by recalibrating it under conditions of constraint—during India’s Emergency. This study argues that Kumar’s work constitutes a radical departure from the genre’s traditional emphasis on the abstract longing of the lover for the beloved and other tropes which are peculiar to writing ġhazal in the Perso-Urdu world. Instead, Kumar systematically repurposed its conventions—its ambiguity, its metaphors of the beloved and the garden, its themes of sacrifice—to mount a sharp polemic against Indira Gandhi’s regime. Through an analysis of ġhazal-s selected for their range of polemical strategies—from direct satire and political allegory to the recasting of traditional themes like martyrdom—this paper demonstrates how Kumar’s conscious use of a blended Hindi–Urdu vernacular was central to his political project. By writing in “the language I speak,” he dragged the elite ġhazal into the public square, transforming it into a medium for articulating collective disillusionment, resistance, and a scathing critique of a democracy in crisis. Kumar’s work thus stands as a testament to the ġhazal’s potent, and often overlooked, capacity for explicit political engagement. Full article

Southern India and Sri Lanka (SISL) rainfall during January–April (JFMA) exhibits strong interannual variability and is influenced by the El Niño–Southern Oscillation (ENSO), yet the long-term evolution of this relationship and its physical drivers remain unclear. Based on multiple precipitation datasets and atmospheric reanalysis products for 1950–2024, this study reveals a pronounced strengthening of the negative correlation between JFMA-mean SISL rainfall and the Niño 3.4 index, shifting from a statistically insignificant relationship prior to the late 1970s to a more coherent association after the 1980s. This transition is accompanied by intensified ENSO-related circulation anomalies. The strengthened and westward-extended Northwest Pacific Anticyclone (NWPAC) plays a dominant role, whereas an enhanced cross-equatorial temperature gradient in the Indian Ocean contributes to a lesser extent. Composite analyses further indicate that, on average, Eastern Pacific (EP) ENSO events tend to produce stronger rainfall anomalies over SISL than Central Pacific (CP) events; however, the differences between EP and CP composites are not statistically significant, reflecting pronounced event-to-event variability, especially for CP events. These results highlight the complexity of ENSO–SISL teleconnections and underscore the importance of NWPAC as a key bridge linking Pacific SST variability to regional rainfall responses. Full article

This study examines the tourism value chain of the Cartagena de Indias–Santa Cruz de Mompox river corridor in Colombia. The objective is to analyze how the corridor’s territorial configuration, prioritized nodes, and inventory of attractions contribute to strengthening the sustainable integration of destinations. The research is based on three questions: (RQ1) How is the corridor’s territorial configuration structured and refined? (RQ2) Which locations should be prioritized according to the multi-criteria evaluation? (RQ3) How do the attractions and industry trends influence opportunities for strengthening the sustainable value chain? A case study design combined document review, mapping, field validation, expert consultation, multi-criteria scoring, and stakeholder surveys. The findings reveal a spatially continuous but functionally uneven system. Central nodes, such as Cartagena and Mompox, show greater integration of attractions and services, while intermediate municipalities show untapped potential, limited by insufficient promotion and training. While infrastructure and basic services are positively assessed, governance coordination and marketing remain critically deficient. Trend analysis indicates high viability for heritage and nature tourism, while eco-innovation and well-being require gradual institutional and capacity development. This study provides a replicable framework that integrates territorial mapping, prioritization matrices, and attraction-based value chain analysis for sustainable tourism in corridors. Full article

The U.S. dollar’s share in global central banks’ foreign reserves has declined slightly between 2015 and 2025. When gold is included as foreign reserves, the decline is significantly larger. We find that the average USD share in total reserves declines by 12 percent, while the gold share increases by 8 percent and other reserve assets by 4 percent. The rise in the share of gold is primarily explained by gold price appreciation. In the case of sanctioned Russia, appreciation is 78%, while physical gold accumulation accounts for 22% of the increase in the value of gold reserves. In China, 91% of the increase in the share of gold is due to gold appreciation, while only 9% is due to gold accumulation. In India, the respective proportions of active versus passive accumulation were 80% and 20%, while in Japan they were 96% and 4% respectively. Physical gold accumulation took place in China (538 metric tons), Russia (915 mt), India (322 mt) and Japan (81 mt). For Germany, France, Italy, Spain, England, and Switzerland, 100% of the share of gold reserves took place passively due to gold appreciation, with no change in physical gold held. Reserve de-dollarization takes place in all ten countries, except for Switzerland, whose USD assets rose by 2% of total reserves. In most cases, de-dollarization reflects valuation effects rather than substantial reductions in dollar asset holdings. Full article

Changes in land use patterns due to urbanisation impact local weather patterns by influencing Land Surface Temperatures (LSTs). Despite rapid urbanisation in the Delhi-NCR (National Capital Region), the peri-urban fringes of Haryana, such as the Central Circle Forest (CCF) region, in the past three decades, a comprehensive 30-year analysis that integrates LST, the Normalised Difference Vegetation Index (NDVI), the Normalised Difference Built-up Index (NDBI), and Land Use/Land Cover (LULC) is lacking. The current study on the decadal analysis covering the 1993 to 2023 time period shows an increase in built-up areas (14.6–38.4%), a decline in NDVI (−0.01 to −0.08), a 6 °C rise in summer LST, and weak correlations between LST and NDVI. A significant increase in summer mean LSTs was observed, with some regions reaching temperatures beyond 35 °C in the selected districts. The LST and LULC zonal statistics revealed that the open fields/agricultural land and floodplains of the Yamuna River have adversely affected the weather pattern with rising LST. The average NDVI declined from −0.01 in 1993 to −0.08 in 2023, indicating a loss of vegetative buffers. Meanwhile, NDBI trends from 2003 to 2023 showed that built-up areas have steadily grown, and LULC data highlighted 38.43% of the built-up area in 2023. Correlation analysis showed a weak negative relationship between LST and NDVI (r = −0.47), suggesting diminishing cooling effects of vegetation, while a weak positive correlation between LST and NDBI indicates that urban expansion is significantly contributing to the urban heat island effect. This study emphasises the need for green infrastructure, afforestation, and water conservation in urban planning frameworks to enhance climate resilience and ecological sustainability. Full article

A Dendrochronological study of teak (Tectona grandis) was conducted at two sites in northern Chhattisgarh, central India, and resulted in the development of two tree-ring width chronologies. We examined the relationships between tree-ring chronologies and gridded monthly and daily climate variables (mean temperature, total precipitation and drought indices) as well as monthly soil moisture. We performed spatial correlations using monthly climate data and used the nearest climate grid point for daily climate correlations. Both chronologies showed negative correlations with temperature and positive correlations with soil moisture, rainfall, and drought indices. These relationships highlight the dominant role of soil moisture availability in influencing teak growth in the monsoon-dominated climate of Chhattisgarh. Based on this relationship, we reconstructed average soil moisture from February to October, extending the gridded soil moisture record by 62 years (1920–1981 CE). This reconstruction represents the first tree-ring-based long-term soil moisture record from central India. Our findings provide a comprehensive hydroclimatic perspective for a region lacking historical tree-ring data and demonstrate the potential of teak as a proxy for investigating long-term soil moisture variability. Further research using older samples from this species will enhance understanding of past climate variability and hydroclimatic changes in central India. Full article

Buffaloes (Bubalus bubalis) are central to the dairy and agricultural economy, contributing high-quality milk, meat, draft power, and manure. Rich milk composition, the ability to utilize low-quality roughage, and strong disease resistance make buffaloes indispensable across diverse production systems. Among India’s major dairy breeds—Murrah, Nili-Ravi, Jaffarabadi, Surti, Bhadawari, Mehsana, and Nagpuri, none exhibit the distinctive trait of intermittent milking, which is uniquely observed in the Pandharpuri buffalo, a registered indigenous breed of Maharashtra. Despite coexisting with dominant dairy breeds such as Murrah, Pandharpuri buffalo is considered to possess primitive riverine ancestry and may represent one of the ancestral lineages from which several Indian breeds evolved. Its evolutionary relevance and unique intermittent milking capacity underscore the need to understand its genomic architecture. To address this, we applied whole-genome resequencing and the De-Correlated Composite of Multiple Signals (DCMS) approach to identify within-breed selection signatures. Our analyses identified 1337 candidate genes, including several linked to milk production, particularly those relevant to the physiological capacity for intermittent milking. Notable genes included ERBB4, ESR1, SYK, INSR, PTPN11, VAV3, MAPK3, and PRKG1. These signatures provide insights into genomic regions and biological pathways that may be involved in lactation-related processes relevant to intermittent milking. The identified genomic regions offer promising targets for functional validation and future genome-informed breeding strategies aimed at conserving this unique indigenous germplasm while improving lactation efficiency and resilience. Full article

Efficient irrigation planning in data-scarce regions remains challenging due to limited access to localized meteorological data, reliance on complex computer-based models, and the technical knowledge required to deploy them at the field scale. Hence, the need for accessible, smartphone-based tools that simplify soil water balance calculations using public data to support practical decision-making in resource-limited contexts. This smartphone-based application estimates Net and Gross Irrigation Requirements using a Soil Water Balance (SWB) framework. The app combines region-specific empirical formulations for Effective Rainfall (Pe) calculation. The application utilizes user-supplied crop and irrigation parameters and meteorological data available in the public domain and operates at multiple temporal scales (daily, 10-day, weekly, and monthly), thereby supporting flexible irrigation schedules. The performance of app was evaluated through simulation-based benchmarking against FAO-CROPWAT 8.0 using harmonized inputs across five representatives agro-climatic region: Central India, Southern Vietnam, Northern Thailand, Western Bangladesh, and Central Sri Lanka. Quantitative comparison showed deviations within ±5% for Effective Rainfall, crop evapotranspiration, Net Irrigation, and Gross Irrigation, and low mean bias values (−2.8% to +3.3%) show the absence of systematic over- or under-estimation compared to CROPWAT model. The application also demonstrated responsiveness to climatic variability. Although the validation is limited to few representative locations and assumed minimal runoff conditions, the results suggest that the proposed method is technically consistent and feasible in practice. This study demonstrates smartphone-based application as a decision support for field-level irrigation planning and water resource management, particularly in data-limited agricultural contexts. Full article