Abstract In the current contribution, a novel binuclear nickel(II) and zinc(II) complexes were prepared from a hexadentate ligand prepared via condensation of 3,3'-Bipyridine-6,6'-dicarbaldehyde , 2-amino-5-chlorobenzaldehyde and 2-Aminophenol .The symmetric ligand (H2DTPE) and its metal complexes were illustrated utilizing various techniques of physicochemical containing magnetic moment, analytical analysis and spectroscopy of mass, IR, 13C and 1H NMR, TGA and UV-Vis. The particles of MO Nanoscale were created from the labeled complex applying the ways of pyrolysis and utilizing methods of XRD, FT-IR, and FE-SEM, that specified close compatibility with the typical pattern for nanoparticles of NiO, ZnO and appeared the reasonable size in

Green synthesis of silver nanoparticles (AgNPs) using different plant parts has shown a great potential in medicinal and industrial applications. In this study, AgNPs were in vitro green synthesized using A. graecorum, and its antifungal and antitumoractivities were investigated. Scanning electron microscopy (SEM) image result indicated spherical shape of AgNPs with a size range of 22-36 nm indicated by using Image J program. The functional groups indicated by Fourier-transform infrared spectroscopy (FTIR) represented the groups involved in the reduction of silver ion into nanoparticles. Alhagi graecorum AgNPs inhibited MCF-7 breast cancer cell line growth in increased concentration depend manner, significant differences shown at

Global concerns are rising due to complications associated with the use of chemical agents and antibiotic resistance. Consequently, research focus has shifted towards the quest for effective agents of biological origin. The aim of the present study was to assess the antioxidant and antimicrobial potentials of aqueous and organic extracts derived from various parts of Alcea kurdica. Different parts of A. kurdica were obtained and prepared into leaf, flower and root powders. The powders were extracted with aqueous and organic solvents. The antimicrobial activity of these extracts was assessed against bacterial pathogens using the agar well-diffusion assay. Additionally, the antioxidant effects of the extracts were evaluated using the

Metal and metal oxide NPs have shown to be perfectly synthesized by using plant extracts with high efficiency, low cost and low toxicity. Our goal was to synthesize ZnO NPs by using an extract of pomegranate seeds and investigate the anticorrosion, antimicrobial and antioxidant properties of the synthesized ZnO NPs. The results have shown that the use of pomegranate in the green synthesis of ZnO NPs gave a good yield, with a low cost and non-toxic approach. The electrophoretic deposition (EPD) was used to coat stainless steel (S.S) by synthesized ZnO NPs in an alcoholic solution at room temperature producing a good coating against corrosion. The corrosion properties were investigated in a saline solution and a temperature range of (293–32

The antioxidant and antibacterial activities of ethanolic extract and phenolic compounds extract of Lemon balm (Melissa officinalis) and Oregano (Oreganum vulgare) plants were studied; the phenolic content and the relationship between these compounds and the above activities were also investigated. The results showed that the Lemon balm had the highest phenolic content (56.5% mg g) and the phenolic content of Oregano was twice lower than Lemon balm. Lemon balm has the highest antioxidant activity which causes lipid peroxidation inhibition activity of linoleic acid (90.5%), this activity was more than ?-tocopherole antioxidant activity (79.3 %). It was found that the main source of antioxidant activity o

In this research, the concentration of radon gas has been calculated in the classrooms of schools in Diyala Governorate by using the nuclear track detector (CR-39), which was one of the organic solid-state nuclear detectors (SSNTDs). After calculating the radon gas concentration, the lung cancer cases were calculated. The results showed that the lowest value was found in (Alshumue) school (4.753) people. In contrast, the highest value was found in (Habhib) school (20.421). The average values of lung cancer cases in Diyala governorate were equal to (9.319) per person. The results showed that the number of lung cancer cases per year per million persons in Diyala Governorate schools was below the allowed limit from (ICRP) agency (170-230) p

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a