Cooch Behar Panchanan Barma University

The green procedure has emerged as a promising technique for the synthesis of inorganic nanoparticles because of its eco-friendliness, simplicity, cost-effectiveness, and low toxicity. Taking into account all these unique characteristics, we have introduced the use of aqueous extract of Ananas Comosus and Murraya koenigii at ambient temperature for the preparation of iron oxide nanoparticles. The active organic alkaloid compounds present in the above-mentioned leaves act as reducing as well as capping agents during the synthesis procedure. The synthesized biogenic rhombohedral alpha-Fe2O3 (Hematite) NPs exhibit remarkable catalytic activity toward the degradation of noxious organic dyes, viz., methylene blue (MB) and methyl orange (MO), and they retain their catalytic activity up to five cycles. MB is degraded within 18 min, while MO becomes colorless within 28 min. The synthesized nanoparticles also exhibit antibacterial activity, which has been checked against E. coli and S. aureus bacterial strains. In a nutshell, this work emphasizes the sustainable approach of using A. Comosus and M. koenigii leaf extracts to synthesize catalytically active iron oxide nanoparticles. Such plant extracts can be used for the preparation of metal and metal oxide nanoparticles for their applications in different important fields, including biological applications.

Ranikhola River Sub-Basin features a complex topography and frequent landslides. Road construction and urban expansion exacerbate the situation. Multi-criteria decision-making (MCDM) and machine learning methods are used to assess spatial landslides in the Ranikhola River Sub-Basin, East Sikkim. Thirteen landslide conditioning factors were represented as GIS layers in the study area to construct landslide susceptibility maps. Parameters were assigned weights using the Analytic Hierarchy Process (AHP) and Entropy methods to balance subjective and objective influences. Random forests (RFs) and artificial neural networks (ANNs) were compared with two MCDM methods, TOPSIS and VIKOR, to map landslide susceptibility. The dataset was divided into training and testing, with a 70:30 ratio. As shown by accuracy assessments, ML approaches outperform MCDM. Slope (23.21

Rapid urbanization significantly influences the quantity and quality of natural water resources. This study investigates the impact of urban growth on the water quality of the Balason and Mahananda rivers in Siliguri. To evaluate the Water Quality Index (WQI), water samples for eleven physicochemical parameters were collected from seventeen selected sites. An upper - urban - downstream gradient approach was adopted, integrating statistical and GIS-based techniques for comprehensive analysis. WQI results indicated a marked decline in water quality during the lean season, particularly in densely populated urban stretches. Average WQI scores ranged from good to poor, with the most degraded sites located within the central urban zone. Statistical assessments revealed significant spatial variation in water quality across upstream, urban, and downstream segments. This research highlights that improving urban water quality aligns directly with SDG 6 (clean water and sanitation), suggesting the urgent need for integrated water resource management and sustainable urban planning.

We report a systematic investigation into the energy dependence of intermittent fluctuations and multifractal characteristics of primary charged hadrons ( h^± ) produced in pp collisions at center-of-mass energies √(s) = 0.9–13 TeV. The study is performed using the PYTHIA 8.3 Monash event generator, focusing on the influence of distinct color reconnection (CR) mechanisms—specifically the Multiple Parton Interaction-based (MPICR), QCD-based (QCDCR), and Gluon-Move (GMCR) schemes on local density fluctuations in one-dimensional pseudorapidity space. Using the method of scaled factorial moments, we observe clear power law scaling across the investigated energy spectrum, confirming the presence of self-similar cascading in small collision systems. To characterize the underlying dynamics, we evaluate several parameters, including the degree of multifractality (r), critical exponent ( ν ), anomalous fractal dimension ( d_q ), and Lévy index ( μ ). Furthermore, the degree of multifractality (r) and the multifractal specific heat (c) are found to be positive and sensitive to the CR topology. A significant finding of this work is that the critical exponent ( ν ), derived from the scaling of fractal dimensions, aligns most closely with the Ginzburg–Landau theoretical prediction of ν≈ 1.304 when the QCD-based CR scheme is employed. These results suggest that the inclusion of complex color string topologies, such as junctions, is essential for reproducing the critical fluctuations indicative of a quark-hadron phase transition in high-multiplicity pp collisions at Large Hadron Collider energies.

Landslides initiate when a geophysical mass, including rocks, mud, or debris, gets dislodged due to gravitational force, often triggered by various factors like rainfall, earthquakes, or anthropogenic activities. These events are particularly dangerous in mountainous areas, where they can cause significant harm to both human life and infrastructure. Detection of landslides is essential not only for diminishing damage but also for developing effective disaster management strategies. In this study, landslide susceptibility mapping was carried out in parts of the Kailash Mansarovar Pilgrimage road using multi-criteria decision-making methods like the Analytical Hierarchy Process (AHP) and the AHP-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). A landslide inventory was initially created by visual analysis of images sourced from Google Earth Pro, which resulted in the mapping of 100 landslide occurrences in 2024 along the road. Fourteen of the most important landslide causative/conditioning parameters, including Slope, Aspect, Stream Power Index (SPI), Drainage Density (DD), Lithology, Geomorphology, Distance from Lineament, Distance from Fault, Sediment Transport Index (STI), Topographic Wetness Index (TWI), Terrain Ruggedness Index (TRI), Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), and Land Use/Land Cover (LULC), were utilized as inputs in this study. The landslide susceptibility maps, thus generated using both the AHP-TOPSIS and AHP methods, indicated an increasing likelihood of landslides in the study area, thereby increasing knowledge and helping in disaster risk reduction. The AHP-TOPSIS method achieved a precision of 83.10