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In this work, calcium (Ca)-modified titanium dioxide (TiO₂) nanoparticulate (NP) films were successfully prepared using sparking off Ca-electroplated Ti tips. Aqueous solution of calcium carbonate (CaCO₃) was used as electrolyte in the electroplating process. The experiment was carried out using electric current of 0.02mA applied to titanium electrodes for 10min. The NP films with small and uniform size were deposited on quartz substrate using the sparking process with a high DC voltage of 4kV in ambient air. The as-deposited NP films were then annealed at 800^∘C, 900^∘C and 1000^∘C for 3h under atmospheric pressure to improve their crystallinity. Morphology, structural and optical properties of the NP films were characterized by SEM, XRD, Raman, XPS and UV-Vis spectroscopy. The effects of annealing temperature on the properties of the as-deposited and annealed NP films were reported. Furthermore, photocatalytic activity against 10 $\mu$M of methylene blue (MB) under visible light region will be discussed.

Titanium dioxide (TiO₂) and iron oxide (Fe₂O₃) nanoparticles (NPs) were successfully deposited on multiwall carbon nanotubes (MWCNTs) films using a low-cost and simple sparking process. The as-deposited film was annealed at $350^{\circ }$C for 2h to improve their crystallinity. The results show the anatase TiO₂ and hematite Fe₂O₃ NPs with the size of 5–10nm are coated on MWCNTs. The bandgap energy of the as-prepared and the annealed films were 2.3eV and 2.7eV. Photocatalytic activity of the annealed films under visible irradiation is greater than the as-prepared films. Moreover, TiO₂:Fe₂O₃ with the ratio of 3:1 was the optimized condition. Interestingly, the relative current of the annealed films increased to 0.75 when increasing the irradiation time for 5h. This result confirmed that the excited electron from photocatalytic activity can be transferred through the MWCNTs. This is an alternative way to produce the electric current from photocatalysis in the future.

Acute lymphoblastic leukemia (ALL) is a serious hematological neoplasis that is characterized by the development of immature and abnormal growth of lymphoblasts. However, microscopic examination of bone marrow is the only way to achieve leukemia detection. Various methods are developed for automatic leukemia detection, but these methods are costly and time-consuming. Hence, an effective leukemia detection approach is designed using the proposed Taylor–monarch butterfly optimization-based support vector machine (Taylor–MBO-based SVM). However, the proposed Taylor–MBO is designed by integrating the Taylor series and MBO, respectively. The sparking process is designed to perform the automatic segmentation of blood smear images by estimating optimal threshold values. By extracting the features, such as texture features, statistical, and grid-based features from the segmented smear image, the performance of classification is increased with less training time. The kernel function of SVM is enabled to perform the leukemia classification such that the proposed Taylor–MBO algorithm accomplishes the training process of SVM. However, the proposed Taylor–MBO-based SVM obtained better performance using the metrics, such as accuracy, sensitivity, and specificity, with 94.5751, 95.526, and 94.570%, respectively.