Synthesis of new Fe+3, Co+2, Cu+2, Ru+3, and Rh+3 complexes of azo ligand; [5-((2-(3 H-1 indol-3-yl) ethyl) diazenyl) quinolin-8-ol], of 1:2 (M: L) and characterized through various techniques. The complexes exhibited octahedral geometries. Thermogravimetric (TGA and DSC) analysis is utilized to study the thermal properties of various compounds and reveal the presence of coordinated water molecules in the complexes. The multi-stage thermal decomposition mechanisms, where the thermal breakdown is ended by the formation of metal oxide as the final stable residue. The antioxidant activity of the ligand and its metal complexes was evaluated using the DPPH free radical scavenging assay and Gallic acid as a standard substance. Among the tested compounds, the Ru complex exhibited the strongest activity, whereas the free ligand (HL) showed the weakest. Finally, the anticancer potential of the synthesized complexes was evaluated against selected breast cancer cell lines. Experiments were carried out using five different concentrations, and absorbance was recorded at 570 nm to determine the mean percentage of cell viability. Results indicated that the highest tested concentration (524.70 µg / Ml ) produced the greatest reduction in cancer cell growth. Among the tested compounds, the Ru complex demonstrated the strongest inhibitory effect, showing superior anticancer activity as well as the most pronounced ability to suppress free radical activity.
In this article four samples of HgBa2Ca2Cu2.4Ag0.6O8+δ were prepared and irradiated with different doses of gamma radiation 6, 8 and 10 Mrad. The effects of gamma irradiation on structure of HgBa2Ca2Cu2.4Ag0.6O8+δ samples were characterized using X-ray diffraction. It was concluded that there effect on structure by gamma irradiation. Scherrer, crystallization, and Williamson equations were applied based on the X-ray diffraction diagram and for all gamma doses, to calculate crystal size, strain, and degree of crystallinity. I
... Show MoreLongitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.
In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.
The longitudinal balanced data profile was compiled into subgroup
... Show More