Reaxys Chemistry database information SciVal Topics Metrics Abstract A novel CoO–ZnO nanocomposite was synthesized by the photo irradiation method using a solution of cobalt and zinc complexes and used as a coating applied by electrophoretic deposition (EPD) for corrosion protection of stainless steel (SS) in saline solution. The samples were characterized using powder XRD, scanning electron microscopy (SEM) and electrochemical polarization. It was also found that the coating was still stable after conducting the corrosion test: it contained no cracks and CoO–ZnO nanocomposites clearly appeared on the surface. SEM showed that the significant surface cracking disappeared. XRD confirmed that CoO–ZnO nanocomposites comprised CoO and Zn

Breast 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

The corrosion inhibiting properties of the new furan derivative 5-(furan-2-ylmethylsulfonyl-4-phenyl-2,4- dihydro [1,2,4] triazole-3-thione in acidic solution (1.0 M HCl) were explored utilizing electrochemical, surface morphology (AFM), and quantum chemical calculations approaches. The novel furan derivative 5-(furan-2-ylmethylsulfonyl-4-phenyl-2,4- dihydro [1,2,4] triazole-3-thione shows with an inhibitory efficiency value of 99.4 percent at 150 ppm, carbon steel corrosion in acidic medium is effectively inhibited, according to the results. The influence of temperature on corrosion prevention was studied using adsorption parameters and activation thermodynamics. The novel furan derivative creates a protective layer over the metallic surfa

Promoting the production of industrially important aromatic chloroamines over transition-metal nitrides catalysts has emerged as a prominent theme in catalysis. This contribution provides an insight into the reduction mechanism of p-chloronitrobenzene (p-CNB) to p-chloroaniline (p-CAN) over the γ-Mo2N(111) surface by means of density functional theory calculations. The adsorption energies of various molecularly adsorbed modes of p-CNB were computed. Our findings display that, p-CNB prefers to be adsorbed over two distinct adsorption sites, namely, Mo-hollow face-centered cubic (fcc) and N-hollow hexagonal close-packed (hcp) sites with adsorption energies of −32.1 and −38.5 kcal/mol, respectively. We establish that the activation of nit

The present study aimed to assess the potential impact of serum concentration of undercarboxylated osteocalcin (the active form of osteocalcin) and fibroblast growth factor-23 on the incidence of cardiovascular diseases in type 2 diabetics with carotid artery calcification and the possible association with metabolic changes in relation to glucose and minerals homeostasis.

This study included 52 men with carotid artery calcification type 2 diabetes mellitus. These patients were categorized; as follows: group A includes 30 patients who had cardiovascular disease and group B includes 22 patients who had no cardiovascular disease. These groups were compared with 25 apparently healthy control (Group C). 

It has been shown

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