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Gadolinium-Doped CdZnS Nanocomposites with Improved Photocatalytic Activity and Stability Under Visible Light
No full textIn this study, a novel Gd-doped CdZnS nanocomposite was successfully synthesized via a simple aqueous co-precipitation method and evaluated for its structural, optical, and photocatalytic properties. The incorporation of Gd3+ ions into the CdZnS lattice significantly influenced the crystal structure, morphology, and defect density, as confirmed by XRD, Raman, and SEM analyses. The substitution of Cd2+ by Gd3+ induced compressive lattice strain, reduced crystallite size, and promoted defect-rich surface structures. Optical characterizations revealed a red-shifted absorption edge and Narrowed band gap from 2.16 to 2.01 eV upon doping, attributed to the formation of localized states and enhanced electron–phonon interactions. Photoluminescence (PL) spectroscopy further supported the presence of defect-assisted recombination and Gd-related energy levels. Most notably, the Gd-doped CdZnS exhibited superior photocatalytic efficiency, achieving 98% degradation of Rhodamine B under visible Light within 60 min-surpassing undoped and binary counterparts. Kinetic studies yielded a moderate activation energy of 29.77 kJ/mol, confirming thermally activated behavior. The catalyst also retained > 85% activity after five reuse cycles, demonstrating excellent stability. The synergistic effects of Gd doping on band structure modulation, defect engineering, and reusability underline the potential of Gd-doped CdZnS as a high-performance, reusable photocatalyst for environmental remediation applications
Sınırlar/Sınırlılıklar Arasında Göç: Adalet ve Küresel Eşitsizliğin Dilsel İnşasında Thilo Sarrazin’in Anlatısına Eleştirel Analiz
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Individual innovativeness levels and levels of medical artificial intelligence readiness among nursing students: a cross-sectional and correlational study
No full textAim: This study, aimed to determine the individual innovativeness levels of nursing students and their readiness levels for medical artificial intelligence and the relationship between these two variables. Background: A healthcare team with innovative personality traits is essential for the effective use of artificial intelligence in healthcare. It is important to determine the perspectives of nursing students, who are among the most crowded members of the team and whom we define as the nurses of the future, in this direction. Design: The research was designed as descriptive and correlational. Method: The research data were collected by the researcher between March 1 and May 1, 2023. The study included 1st, 2nd, 3rd and 4th year nursing students studying at two universities in Anatolia. Data were collected with a reliable online survey method. The sample selection procedure was based on the sampling of the known population method. The study was conducted with 781 nursing students using a cross-sectional and correlational study method. The data were collected using the Personal Information Form, Individual Innovativeness Scale and Medical Artificial Intelligence Readiness Scale. The conformity of the data to the normal distribution was made by using skewness and kurtosis values and the range of + 2 and − 2 was taken as reference. Significance level p <.05 was accepted in the tests. Results: The mean total score of the IIS, nursing students was 55.09 ± 9.22, and the mean total score of the MARS nursing students was 67.63 ± 12.83, and there was a weak positive correlation between the scales (r =.172, p <.001). Conclusion: In our study, it was determined that nursing students’ individual innovativeness levels positively affected their readiness for medical artificial intelligence. It was concluded in this study that the individual innovativeness level of the nursing students was low; in other words, they adopted a traditionalist attitude and approached artificial intelligence cautiously. It is recommended that the existing curricula be restructured to strengthen the innovative perspective of nursing students and to understand, use, and develop artificial intelligence technologies in nursing, and nursing educators should upskill themselves in this field
Investigation of the Interaction of ENT Drugs with Target Proteins Using a Molecular Docking Approach
No full textUnderstanding the interactions of drugs commonly used in the treatment of Ear, Nose and Throat (ENT) diseases at the molecular level is of great importance in terms of increasing treatment efficacy and identifying new therapeutic targets. In this study, five different active drug substances commonly used in the field of ENT (amoxicillin, loratadine, fluticasone and pseudoephedrine) were selected and the binding potentials of these molecules with the relevant biological target proteins (PDB IDs 1ZG4, 3RZE, 1M2Z, 4V7U, 2RH1) were investigated by molecular docking methods. The selected proteins are associated with bacterial resistance mechanisms, allergic responses, inflammation processes and sympathomimetic effects and play important roles in explaining the therapeutic effects of the relevant drugs. It is aimed that the molecular docking results will contribute to the optimization of drug design and current treatment approaches by revealing the structural basis of drug-protein interactions
