Physical Sciences and Engineering

This research paper comprehensively analysis how social media influencers impact tourism patterns in India. Through extensive data collection and analysis of 30 top tourism influencers, we developed machine learning models to quantify and predict the relationship between social media metrics and tourism outcomes. Our findings reveal that engagement metrics, content authenticity, and local cultural context strongly predict tourism impact. The ML models developed demonstrate up to 82% accuracy in predicting tourism trends based on social media data.

The aim of this work is to probe observable effects of vortex driven Superfluid-Mott insulator transition using the rotational Bose-Hubbard mode kept inhomogeneous by a Berry curvature, considering neutral bosons confined in a 1D confinement about the x-direction. The 1D model includes two-or-three-body onsite interaction in order to probe further into the interactions. Our theoretical results show notable effects.

Water is very important for our life. And it is abundantly available in nature. For the investigation we have collected four sample near Parichha thermal plant. Water samples are collecting in February, May, August, NovemberMonth. During physiochemical analysis fluoride have found in very excess amount in groundwater sample collected from resources of drinking water near Parichha thermal plant. While fluoride levels can vary greatly, some fluorides are found naturally in soil, air, and water. Fluoride is present in almost all water.

The majority of literature on machine learning for resting-state functional magnetic resonance imaging (RS-fMRI) is devoted to unsupervised learning approaches. Modelling resting-state activity is challenging due to the absence of controlled stimuli driving fluctuations. Early analytic approaches focused on decomposition or clustering techniques to better characterize data in spatial and temporal domains. Unsupervised learning methods like ICA catalysed the discovery of resting-state networks or RSNs, which describe functionally coherent spatial compartments within the brain.

Customer loyalty is one of the most important businesses KPI for managers of companies and organizations. In fact, making customers loyal is one of the solutions to reduce future advertising and marketing costs. The main objective of this study was to investigate the role of brand experience and relationship benefits on customer loyalty. In this article, a questionnaire was used to measure the research variables. Based on the research literature, relationship benefits were measured through three variables: confidence, social, and special treatment benefits.

The rising threat of antimicrobial resistance demands the development of novel therapeutic agents with broad-spectrum efficacy. In this study, a series of thiadiazolyl-pyridine derivatives (5a–5h) was synthesized using a one-pot multicomponent reaction involving acetylthiadiazole, substituted aromatic aldehydes, malononitrile, and ammonium acetate in refluxing acetic acid. This green and efficient synthetic route offered high yields and reduced environmental impact. The structures of the synthesized compounds were confirmed by ¹H NMR, LC-MS, and elemental analysis.

Rapid expansion of antimicrobial-resistant pathogens has intensified the demand for chemotypes that are both potent and environmentally sustainable. We describe a green one-pot strategy for constructing a small library of polyhydroquinoline derivatives (4a–4e) starting from 5-methyl-2-aminopyridine and aromatic aldehydes in ethanol under catalytic HCl. Antimicrobial activity was assessed by agar well diffusion against Staphylococcus aureus, Bacillus anthracis, Pseudomonas aeruginosa, Escherichia coli, Candida albicans and Aspergillus niger.

The ground support for the Ban Houayxai exploration decline project has been thoughtfully designed, leveraging a wealth of research alongside detailed geological and geotechnical mapping of the underground conditions. While the drilled holes presented some unexpected results in the decline area, our dedicated team has made remarkable strides in collecting valuable data through meticulous underground geotechnical mapping.

The electrical characterization of solar cells is essential to evaluate their performance and understand their behavior under different environmental conditions, including temperature. Charge carriers, under the influence of temperature, diffuse into the cell, a phenomenon quantified by the diffusion capacitance. These generated carriers do not contribute to the electric current; some recombine in specific areas, either on the surface or in the bulk. Bulk recombination mechanisms include Shockley-Read-Hall (SRH) recombination, radiative recombination, and Auger recombination.

The rapid industrialization and urbanization of the Uruan Local Government Area of Akwa Ibom State, Nigeria, have significantly contributed to heavy metal contamination in the Nwaniba River. This research assesses the ecological risks associated with contamination using advanced machine learning techniques. Water, sediment, and marine organism samples were analyzed using ICP-OES to quantify seven heavy metals: iron (Fe), copper (Cu), nickel (Ni), lead (Pb), zinc (Zn), chromium (Cr), and manganese (Mn).