Cobalt substituted nickel copper ferrite samples with general formula Ni0.95-xCoxCu0.05Fe2O4, where (x= 0.00, 0.01, 0.02, 0.03, 0.04 and 0.05) were prepared by solid-state reactions method at 1373 K for 4h. The samples prepared were examined by X-ray diffraction (XRD(, atomic force microscope (AFM), Fourier transform infra-red spectroscopy (FTIR) and Vickers hardness. X-ray diffraction patterns confirm the formation of a single phase of cubic spinel structure in all the prepared samples . XRD analysis showed that the increase in the cobalt concentration causes an increase in the lattice constant, bulk density (ρm) and the x-ray density (ρx), whereas porosity (p) and crystallite size (D) decrease. The Topography of the surface observed was found to be more uniform and homogeneous when the cobalt concentration increases, leading to a decrease in the roughness of the surface while average grains size increases. The FTIR spectra show two absorption bands, namely the high frequency band (υ1) in the range (1078-1081) cm-1 and the low frequency band (υ2) in the range (418–459) cm-1, which due to the vibrations of the tetrahedral and octahedral sites of Fe+3–O−2, respectively, these bands confirm the spinel structure of the prepared ferrite nanoparticles. Vickers hardness was found to increase with cobalt concentration increases.
The variation in wing morphological features was investigated using geometric morphometric technique of the Sand Fly from two Iraqi provinces Babylon and Diyala . We distributed eleven landmarks on the wings of Sand Fly species. By using the centroid size and shape together, all species were clearly distinguished. It is clear from these results that the wing analysis is an essential method for future geometric morphometry studies to distinguish the species of Sand Flies in Iraq.
Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreThe beet armyworm (BAW), Spodoptera exigua (Lepidoptera: Noctuidae) is a highly destructive pest of vegetables and field crops. Management of beet armyworm primarily relies on synthetic pesticides, which is threatening the beneficial community and environment. Most importantly, the BAW developed resistance to synthetic pesticides with making it difficult to manage. Therefore, alternative and environment-friendly pest management tactics are urgently required. The use of pesticidal plant extracts provides an effective way for a sustainable pest management program. To evaluate the use of pesticidal plant extracts against BAW, we selected six plant species (Lantana camara, Aloe vera, Azadirachta indica, Cymbopogon citratus, Nicotiana tabacum ,
... Show MoreBackground: Early detection of subclinical left ventricular (LV) systolic dysfunction is crucial and could influence patients' prognosis by aiding the clinician to candidate patients for better management.
Objective: To detect early LV systolic dysfunction in asymptomatic patient with chronic aortic regurgitation by two dimensional speckle tracking echocardiography.
Methods: Sixty one asymptomatic patients with chronic aortic regurgitation, with no ischemic heart diseases (by coronary angiography) or conductive heart diseases, no diabetes mellitus, no hypertension, and no other valvular heart diseases (group 1) and fifty age and sex-matched healthy subjects (
... Show MoreBreast cancer is the most common malignancy in female and the most registered cause of women’s mortality worldwide. BI-RADS 4 breast lesions are associated with an exceptionally high rate of benign breast pathology and breast cancer, so BI-RADS 4 is subdivided into 4A, 4B and 4C to standardize the risk estimation of breast lesions. The aim of the study: to evaluate the correlation between BI-RADS 4 subdivisions 4A, 4B & 4C and the categories of reporting FNA cytology results. A case series study was conducted in the Oncology Teaching Hospital in Baghdad from September 2018 to September 2019. Included patients had suspicious breast findings and given BI-RADS 4 (4A, 4B, or 4C) in the radiological report accordingly. Fine needle aspirati
... Show More