Pt. Ravishankar Shukla University is an institution of higher education located in Raipur, Chhattisgarh, India. It is one of the largest and oldest institutions of higher education in Chhattisgarh. It is a state university founded in 1964 by the Government of Madhya Pradesh. It is a teaching-cum-affiliating university which affiliates about 144 colleges and has 29 University Teaching Departments (UTDs).
Piezocatalysis has emerged as a promising and sustainable method for degrading hazardous contaminants in aqueous environments.
The escalation in the prevalence of antibiotic-resistant microbial strains, especially in Pseudomonas aeruginosa ocular infections, necessitates innovative therapeutic strategies. The contemporary investigation emphasizes the evolution and evaluation of a novel ophthalmic formulation comprising ciprofloxacin HCl-loaded chitosan nanoparticles coadministered with the quorum sensing inhibitor (QSI) quercetin to enhance antimicrobial efficacy and disrupt bacterial biofilms in keratitis. Chitosan nanoparticles were optimized using a Box-Behnken design to investigate the influence of chitosan concentration (X 1), STPP concentration (X 2), and stirring speed (X 3) on particle size, entrapment efficiency, and drug release and subjected to characterization for size distribution, surface potential, encapsulation rate, and morphology. Optimized nanoparticles exhibited a size of 53.24 +/- 1.26 nm, a positive charge of 34.9 +/- 0.96 mV, high EE% of 88.02% +/- 1.20% for ciprofloxacin HCl, along with sustained release profiles. The co-loaded system demonstrated a biphasic drug release pattern, ensuring sustained ocular delivery through diffusion- and erosion-mediated mechanisms, with ciprofloxacin HCl following Higuchi kinetics and quercetin fitting the Korsmeyer-Peppas model. In vitro assays, including biofilm inhibition (crystal violet assay), quorum sensing interference (violacein and pyocyanin assays), motility reduction, and minimum inhibitory concentration (MIC), confirmed the superior performance of the nanoparticle-based formulation over free drugs. Fluorescence microscopy revealed significant disruption of biofilm architecture, indicating enhanced antimicrobial penetration. The combined system offers promising potential in overcoming ocular biofilm-related resistance by integrating antimicrobial and anti-virulence strategies, thereby improving therapeutic outcomes and compliance.
Luminescent rare-earth oxide phosphors are of considerable interest for advanced lighting, anticounterfeiting, security applications, dosimetry, etc. because of their unique performance of sharp and distinct emission peaks, spectral tunability, long luminescence decay times, exceptional thermal stability, etc. In this work, the Eu3+-activated La2Zr2O7 (LZO) nanophosphors having a defect fluorite structure were synthesized by the nitrate-citrate gel combustion method, and the influence of monovalent alkali-ion co-doping (Li+/Na+/K+) on their defect chemistry and luminescence behavior was systematically studied. Among them, Li+ co-doped nanophosphor (La1.72Eu0.22Li0.06Zr2O7) showed a 1.5-fold increase in the PL emission intensity with better CIE chromaticity coordinates (0.6394, 0.3598), a higher correlated color temperature value (1973 K), and excellent color purity (89%), overcoming the shortcomings in the red component of LEDs. X-ray photoelectron spectroscopy analysis indicated oxygen vacancy-related defect centers in Li+ ion co-doped phosphor materials. Judd-Ofelt (J-O) analysis studied the increased asymmetric environment around the activator ion, Eu3+, upon co-doping. Furthermore, La1.72Eu0.22Li0.06Zr2O7 nanophosphor demonstrated latent fingerprint detection as well as dosimetry applications via gamma radiation. Hence, this Li+ co-doped Eu3+: LZO nanophosphor can be a plausible option for the red component in lasers, display devices, and solid-state lighting, latent fingerprint analysis, and dosimetry studies.
The present study was conducted to evaluate genetic variability, heritability, and trait associations among Indian mustard (Brassica juncea L.) genotypes under the agro-climatic conditions of Prayagraj during the Rabi season 2025–26. The experiment was laid out in a Randomized Block Design with 20 genotypes and three replications. Observations were recorded on thirteen quantitative traits including plant height at different growth stages, days to 50% flowering, biological yield, seed yield, number of branches, and siliqua-related traits. Analysis of variance revealed significant differences among genotypes for all characters, indicating the presence of substantial genetic variability. The mean performance showed wide variation, particularly for total siliqua per plant (172.27–353.33), seed yield per plot (825.33–1275.67 g), and number of branches (15.93–28.07). High phenotypic coefficient of variation (PCV) compared to genotypic coefficient of variation (GCV) for most traits suggested environmental influence. High heritability was observed for days to 50% flowering (84.54%) along with moderate genetic advance, indicating its reliability for selection. Correlation analysis revealed that biological yield, total siliqua per plant, and number of branches exhibited strong positive association with seed yield. Path coefficient analysis further confirmed that these traits had a direct positive effect on yield. Cluster analysis grouped genotypes into three clusters, with maximum genotypes in cluster I, indicating genetic diversity among lines. Overall, traits such as total siliqua per plant, number of branches, and biological yield were identified as important selection criteria for yield improvement. The study highlights the potential of these traits and genotypes for future breeding programs aimed at enhancing mustard productivity.
This work presents a novel decision-making framework based on the trapezoidal-valued intuitionistic fuzzy Hamacher weighted averaging aggregation operator, incorporating variations of the ELECTRE method. This operator is designed to manage the ambiguity and inherent uncertainty that characterize complex decision-making scenarios, especially when making qualitative judgments. We apply this operator to the problem of locating electric vehicle (EV) charging stations, demonstrating its practical application. The framework captures the degrees of hesitance among decision-makers and their inclinations toward membership and non-membership values. Utilizing the adaptability of trapezoidal-valued intuitionistic fuzzy sets, our objective is to enhance the accuracy and robustness of the Hamacher aggregation process for multi-criteria decision-making (MCDM) problems. An illustrative example is provided to evaluate potential EV charging station locations based on criteria such as price, accessibility, expected demand, and environmental impact. The outcomes demonstrate the effectiveness of the TrVIFHWAA operator in aggregating expert opinions to improve decision-making in uncertain environments. Finally, sensitivity and comparative analyses were conducted to validate the method’s efficacy and robustness.
