Vivekananda College for Women, established in 1961, is an undergraduate and postgraduate women's college in Barisha, Calcutta, West Bengal India. It is affiliated with the University of Calcutta.
Chromolaena odorata (L.), is a perennial shrub growing in the central and southern part of America that has spread to many other tropical Asian, Austrian, and West African countries. It usually creates dense thickets in the invaded ranges, which decrease the diversity and quantity of native species. It is included in the top 100 worst invasive alien species in the world and is regarded as a noxious weed in commercial plantations and agricultural fields. The ethnopharmacological qualities of this plant are observed against painful swelling, antioxidant, antimicrobial, analgesic action, wound healing, skin infections, stomach issues and many other pertinent therapeutic features, which have been documented in the literature on a significant scale. It has been found that the root and leaf extracts of plants contain a variety of active secondary metabolites, including phenolic, essential oils, flavonoid chemicals, saponins, and alkaloids. These metabolites can work alone or in concert to mediate the diverse biological activities. This article's objective is to give a summary to provide an overview of the phytochemical ingredients, bioactivities, and pharmacological properties of C. odorata , all of which are important for the potential future development of contemporary medications. This approach may unlock the full potential of C. odorata , creating new opportunities for modern drug discovery and practical applications in both medical and agricultural fields.
West Bengal has a unique diversity of geomorphological landscapes ranging from the Eastern Himalaya and Sub-Himalayan piedmont to plateau, fluvial, deltaic and coastal environments. However, comparative and spatially explicit assessment of geosites across these contrasting landscapes is limited. The present study employs the Modified Geosite Assessment Model (M-GAM) to assess and rank 42 representative geosites in the major geomorphic provinces of West Bengal. The evaluation comprises expert assessment of 27 standardised sub-indicators and visitor opinions collected through a structured survey of 202 respondents. The expert-based assessment incorporated visitor-derived importance factors (Im) to reflect the perceived importance of individual attributes. The visitor instrument demonstrated acceptable internal consistency for the Main Value (MV; Cronbach’s α = 0.79) and Additional Value (AV; Cronbach’s α = 0.84) subscales. The results show high variability among geosites in scientific/educational, scenic/aesthetic, protection, functional and touristic attributes. The mean AV score (11.90) was higher than the mean MV score (8.53), indicating the importance of functional and tourism-supporting attributes in the relative M-GAM scores. The 42 geosites were ranked into relatively high-13, moderate-18 and low-11 priority groups using quartile-based thresholds within the study inventory. Correlation analysis revealed positive correlations between some of the M-GAM components, for example, between accessibility and number of visitors (r = 0.74). The VTr – AV correlation (r = 0.81) is treated with caution since VTr is a component of AV itself. Further, a comparison of expert and visitor assessments identifies sites where geomorphological significance and visitor perceived importance are convergent or divergent. Overall, the study demonstrates the value of M-GAM as a comparative decision support framework for geosite prioritization across contrasting landscapes, whilst acknowledging the uncertainties associated with visitor sampling, expert scoring, weighting, aggregation and relative classification.
The fast rate of urban expansion in the ecologically fragile Northeastern Himalayas is related to the rise in anthropogenic pressure and the changes in vegetation composition, surface thermal conditions, atmospheric quality, and demographic intensity. However, the existing environmental indices are typically focused on individual environmental dimensions or provide a limited representation of the combined urban-ecological system. In this research, we developed an Urban-Ecological Impact Index (UEII) using Google Earth Engine and multi-source remote sensing and ancillary datasets to characterize the spatial-temporal co-occurrence of urban pressure and environmental stress across the Northeastern Himalayan region. Multi-temporal Landsat observations for 2005, 2015 and 2025 were used to derive the Normalised Difference Vegetation Index (NDVI), Normalised Difference Built-up Index (NDBI) and Land Surface Temperature (LST). Nighttime-light intensity, Air Quality Index (AQI) and population density were incorporated to represent additional anthropogenic and environmental pressures. Within the framework, these indicators are integrated into an Urbanization Index (UI) and an Ecological Degradation Index (EDI), and combined to produce values of UEII on a normalised 0–1 scale. The Getis-Ord Gi* hotspot analysis was used to assess spatial clustering, and the correlation analysis was used to investigate the relationships between the main environmental and anthropogenic indicators. Moreover, the revised assessment considers sensitivity to weighting, multicollinearity, spatial dependence, and uncertainty from heterogeneous spatial resolutions and temporal sensor differences. Results indicate that urban–ecological pressure is spatially significantly differentiated, and high UEII concentrations are particularly around major urban and fast-developing corridors such as Guwahati–Shillong and the Siliguri region. The temporal comparison also identifies the change of vegetation condition, built-up intensity, thermal environment, nighttime illumination, atmospheric quality and population pressure between 2005 and 2025. The temporal comparison also identifies the change of vegetation condition, built-up intensity, thermal environment, nighttime illumination, atmospheric quality and population pressure between 2005 and 2025. Importantly, the UEII is interpreted as a relative measure of combined urban pressure and environmental stress, rather than as a probabilistic ecological-risk metric or a causal measure of urbanisation-induced degradation. This study illustrates the potential of cloud-based geospatial analysis for integrated environmental assessment and decision support in fast-transforming and environmentally sensitive Himalayan landscapes.
The prevalence of stress and anxiety among undergraduate students is a growing concern worldwide, impacting academic performance, mental health, and overall well-being. Currently, an alarming number of adolescents and young adults are experiencing anxiety and depression. Mental tension is one of the primary causes. This research paper aims to investigate the psychometric educational stress and anxiety among undergraduate students, especially in engineering colleges using machine learning algorithms. Various psychometric scales like Perceived Stress Scale (PSS), General Anxiety Disorder 7-item (GAD-7) scale, Patient-Reported Outcomes Measurement Information System (PROMIS) three outcome variables like stress, anxiety, and depression are analyzed and few machine learning techniques, like Logistic Regression, K-NN Classifier, Decision Tree Classifier, Random Forest, and Stacking provides insights into the factors contributing to stress, anxiety and depression levels among undergraduates. Also, two machine learning models logistic and Support Vector Machine (SVM) are proposed to predict the stress level of the students.
Mixed spin- 1/2 states violating Bell-CHSH inequality is useful for teleportation. There exist states which do not violate Bell-inequality but is still useful as teleportation channels. Maximally entangled mixed states of Munro class and Ishizaka-Hiroshima class are such types which although satisfy Bell-CHSH inequality, yet can perform better as teleportation channels for a given degree of mixedness (Adhikari et al., Quant. Inf. Comp. 10, 039, 2010). In this work we construct class of mixed states of non-maximally entangled types whose efficacy as teleportation channels have been studied. For certain range of state parameters, these non-maximally entangled mixed states performs better as quantum teleportation channels than certain maximally entangled mixed states (such as Werner state). These constructed states, though entangled, satisfy Bell-CHSH inequality implying further that violation of local inequalities may not be good indicators of their ability to complete quantum processing tasks such as teleportation.
