In this work, ZnO nanostructures for powder ZnO were synthesized by Hydrothermal Method. Size and shape of ZnO nanostructureas can be controlled by change ammonia concentration. In the preparation of ZnO nanostructure, zinc nitrate hexahydrate [Zn(NO₃)₂·6H2O] was used as a precursor. The structure and morphology of ZnO nanostructure have been characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffraction (XRD). The synthesized ZnO nanostructures have a hexagonal wurtzite structure. Also using Zeta potential and Particle Size Analyzers and size distribution of the ZnO powder

Series of new complexes of the type [M2 (L)Cl4 ] are prepared from the new ligand[N1 ,N4 -bis(benzo[d]thiazol-2- yl)succinamide (L) derived from ethan-1,2-dicarbonyl chloride and 2-aminobenzothiozole,where, M= Ni(ii), Cu(ii) and Zn(ii) alsocomplexes of mix-ligands, the type [M(L)(8-HQ)]Cl, where, M = Ni(ii), Cu(ii) and Zn(ii),8-HQ= 8-Hydroxyquinoline. Chemical forms are obtained from their 1 H, 13CNMR, Mass spectra (for (L)), FT-IR and U.V spectrum, melting point, molar conduct.Using flame (AA), % M is determined in the complexes.The content of C, H, N and S in the (L) and its complexes was specified. Magnetic susceptibility and thermal analysis (TGA) of prepared compounds were measured.The propose geometry for all complexes[M2 (L)Cl4 ] wa

Breast cancer (BC) is the most prevalent tract cancer in the world, including Iraq. The classified breast tumors to benign, malignant, and radiotherapy. Cancer treatment depends on certain stages such as mastectomy then chemotherapy alone or with radiation therapy or endocrine therapy according to the prognostic features obtained from the pathology report. The present study included 100 females. The women were split into two groups, control group that consisted of 50 apparently healthy females and 50 patients with BC group who undergo the radiotherapy. The current study highlighted on some of the anthropometric measurements, including the oxidative stress index malondialdehyde (MDA), the concentrations of total antioxidant capacity (TAC), s

Breast cancer (BC) is the most prevalent tract cancer in the world, including Iraq. The classified breast tumors to benign, malignant, and radiotherapy. Cancer treatment depends on certain stages such as mastectomy then chemotherapy alone or with radiation therapy or endocrine therapy according to the prognostic features obtained from the pathology report. The present study included 100 females. The women were split into two groups, control group that consisted of 50 apparently healthy females and 50 patients with BC group who undergo the radiotherapy. The current study highlighted on some of the anthropometric measurements, including the oxidative stress index malondialdehyde (MDA), the concentrations of total antioxidant capacity (TAC), s

In this research paper, two techniques were used to treat the drill cuttings resulting from the oil-based drilling fluid. The drill cuttings were taken from the southern Rumaila fields which prepared for testing and fixed with 100 gm per sample and contaminated with two types of crude oil, one from Rumaila oilfields with Sp.gr of 0.882 and the other from the eastern Baghdad oilfield with Sp.gr of 0.924 besides contamination levels of 10% ​​and 15% w/w in mass. Samples were treated first with microwave with a power applied of 540 & 180 watts as well as a time of 50 minutes. It was found that the results reached below 1% w/w in mass, except for two samples they reached below 1.5% w/w in mass. Then, the sample of 1.41% w/w in mass,

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