It was founded by the Jesuits in 9 December 1953.
The structural, electrical, and optical characteristics of biopolymer electrolytes are derived from tamarind seed polysaccharide (TSP) and doped with sodium iodide (NaI) at various concentrations. TSP is highlighted as a biodegradable, renewable, nontoxic biopolymer with excellent film-forming ability, thermal stability, and functional groups that facilitate effective salt dissociation and ion transport. This justification aligns the material choice with the sustainability and performance objectives of the study. The films were fabricated by employing the solution casting method utilizing TSP:NaI ratios of 100:00, 90:10, 80:20, and 70:30. x-Ray diffraction analysis substantiated the presence of a predominantly amorphous structure in the 80:20 composite, which facilitated enhanced ionic mobility. Alternating-current (AC) impedance spectroscopy demonstrated the highest ionic conductivity (4.27 × 10−6 S cm−1) for this high composition. Investigations of dielectric properties and tangent loss illustrated significant energy storage capabilities along with minimal energy dissipation within the same composition. Optical evaluations revealed the peak absorbance, extinction coefficient, and refractive index, indicating its potential applicability in UV-blocking technologies. The optical bandgap exhibited a decrease with the increase in NaI concentration. The conductance and absorption coefficients further corroborated this improvement. Moreover, the membrane exhibited consistent electrochemical performance in sodium-ion battery discharge assessments, maintaining a plateau voltage of 1.52 V over 21 h.
The Eu3+-doped CaY2O4 phosphors were synthesised via high-temperature solid-state method. The XRD analysis suggests an Orthorhombic-like phase of the phosphor, with Eu3+ ions effectively substituting Y3+ sites, while the crystallite size analysis (Scherrer and W-H) reveals dopant-induced grain growth accompanied by strain relaxation. The photoluminescence spectra show an intense red-emission at 610 nm under a broad UV-to-blue excitation, with 466 nm emerging as the most efficient excitation wavelength, highlighting compatibility with blue LED sources. Concentration quenching behaviour suggests excitation-wavelength dependence, with optimum Eu3+ concentration at 1.5 mol% under deep UV-excitation (257 nm), and 2 mol% under near-UV/visible (393-532 nm) excitations. Dexter analysis indicates the dipole-dipole interactions dominated quenching in the visible region, while the unusually low Q value under deep UV-excitation suggests the host-activator transfer. The Judd-Ofelt analysis indicates a non-centrosymmetric Eu3+ environment, and CIE coordinates (x = 0.643, y = 0.356) with similar to 94 % high colour purity demonstrates the saturated red emission. Thermoluminescence study exhibits multiple traps with near-linear UV dose response, supporting dosimetric potential. The combined broad excitation, high emission intensity, and colour purity make the CaY2O4: Eu3+ a promising red phosphor for display and LED applications.
The advent of artificial intelligence (AI) has had a profound impact on the education sector, resulting in a transformative change in higher education worldwide. One such change is the usage of AI tools by teachers to enhance their teaching practices, including content creation, sharing, and personalized learning. Those certain obstacles persist for teachers while fully exploring the potential of AI and its adoption in teaching practices. An extensive review of the literature revealed a significant research gap in developing a comprehensive study to examine the influence of AI relevance and its readiness, performance expectancy (PE), and effort expectancy (EE) in shaping behavioral intention (BI) for AI adoption in teaching. Therefore, drawing cues from the unified theory of acceptance and use of technology a research framework was developed to examine these intricate relationships. We gathered data by administering a survey to higher education teachers across various educational organizations in India. Structural equation modeling (SEM) was employed to analyze the collected data and test the hypothesized relationships. The results uncovered a positive association between teacher's perceptions of AI's relevance and their readiness to adopt AI, with both factors positively influencing their BI. Furthermore, this study found that EE exhibited a significant positive effect on both BI and PE. This study discusses theoretical and practical implications, underscoring the importance of raising awareness about AI's relevance, and lays the groundwork for further exploration in this emerging area, intending to inform strategies and interventions to support successful AI adoption in educational organizations.
Bi4Ti3O12 (BIT) nanoparticles were successfully synthesized via a sol-gel method, with a well-defined orthorhombic Aurivillius structure and nanocrystallite sizes of 40-60 nm. Raman spectroscopy confirmed the presence of characteristic Ti-O and Bi-O vibrational modes, indicating octahedral distortion critical for functional properties. X-ray photoelectron spectroscopy (XPS) revealed Bi 4f peaks at 158.7 eV and 164.0 eV, confirming the Bi3+ oxidation state, Ti 2p doublets at 458.5 eV and 464.2 eV corresponding to Ti4+, and an O 1s peak at 529.6 eV associated with lattice oxygen. Field-emission scanning electron microscopy (FESEM) showed nanoplate-like morphology with an average particle size of similar to 270 nm and homogeneous elemental distribution. The BIT nanoparticles exhibited excellent visible-light photocatalytic activity, degrading similar to 90 % of methylene blue within 120 min. The degradation followed pseudo-first-order kinetics, with rate constants decreasing from 0.1414 to 0.0363 min-1 as dye concentration increased. The combination of high crystallinity, chemical purity, nanoscale morphology, and strong photocatalytic performance highlights BIT nanoparticles as promising candidates for multifunctional applications including wastewater treatment, environmental remediation, photovoltaic devices, and ferroelectric memory technologies.
Financial technology (FinTech) is fundamentally restructuring the monetary landscape through automation and enhanced global connectivity. This study examines consumer perceptions across five key FinTech domains like digital banking, digital payments, lending platforms, investments, and insurance. Utilizing a non-probability convenience sampling method, data were collected from 100 respondents in Vijayawada City via a standardized questionnaire and analysed using Analysis of Variance (ANOVA) to determine the impact of demographic variables on customer satisfaction, perceived complexity, and usage frequency. The empirical results indicate that while gender, occupation, and annual income do not significantly influence consumer satisfaction, age, educational attainment, and marital status are critical determinants. Regarding perceived complexity, age, education, and income emerged as significant factors, whereas gender and occupation showed no statistical bearing. Furthermore, usage frequency is significantly influenced by age, education, occupation, and marital status, but remains independent of gender and income. The findings suggest that younger and more educated consumers report superior FinTech experiences. Consequently, this study emphasizes the necessity of enhancing digital and financial literacy and developing user-centric platforms to mitigate perceived complexity. Such strategic improvements are vital for fostering broader adoption and advancing global financial inclusion.
