Titanium dioxide nanotubes were synthesized by anodizing Ti sheets in the ethylene glycol solution and were covered in Pt nanoparticles onto the surface of TiO2NTs using electrodeposition method from using five derivatives of Mannich base Pt complexes which have been used as precursor of platinum. The mean size, shape, elemental composition of the titanium dioxide nanotubes and platinum deposited on the template were evaluated by different techniques such as field emission scanning electron microscope (FE-SEM), transmission electron microscopy (TEM), X-ray diffraction pattern (XRD), and energy dispersive X-ray (EDX) technique. From all these analyses, the TiO2NTs prepared and Ptnanoparticles deposited on it were identified. The diagnoses pr

Nanoparticles (NPs) have been suggested for subsurface projects, including enhanced oil recovery (EOR), carbon capture and storage (CCS), and hydrogen storage, due to their small size, high surface energy, controlled surface properties, and significant effects on the underground formation properties. Silica is an excellent NP that efficiently modifies the surface properties of subsurface formations for incremental oil recovery and to derisk carbon and hydrogen leaks. However, the retention of injected NPs in a narrow area near the injection inlet can limit a project’s feasibility. In the present study, hydrophobic (hybrid) NPs were produced via silanization of silica NPs, and the mobility behavior of bare (hydrophilic) and hybrid

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: This study was conducted among diabetic persons to assess the sweet and salty taste sensitivity with its effect on gingival health in relation to salivary serotonin levels. Materials and methods: A cross-sectional comparative study design was used. All patients with diabetes aged 12-14 years that attend the Paediatric hospital at Baghdad medical city with specific inclusion criteria were involved in the sample of the present study (patients group 50 patients) compared with non-diabetic persons matched in age and gender of the study sample (control group 70 patients) who were attending dental unit in the college of dentistry/university of Baghdad. A two-alternative forced choice question including each component presented at f

Experimental investigations had been done in this study to demonstrate the effect of natural particles used as a reinforcement material to unsaturated polyester resin. The tensile test and water absorption were investigated according to (ASTM D638) and (ASTM D570), respectively. The influence of sunflower husk and pomegranate husk particles, used as a reinforcement material, on the tensile strength, Young's modulus and water absorption with different weight fraction (3%, 7% and 10%) and particle grain size (50µm, 100 µm and 150 µm), has been investigated. The water absorption of polymer composites was studied by measuring the specimen weight before and after immersion in water for one hundred days. In the experiments of tensile test,

            Density Functional Theory (DFT) method of the type (B3LYP) and a Gaussian basis set (6-311G) were applied for calculating the vibration frequencies and absorption intensities for normal coordinates (3N-6) at the equilibrium geometry of the Di and Tetra-rings layer (6, 0) zigzag single wall carbon nanotubes (SWCNTs) by using Gaussian-09 program. Both were found to have the same symmetry of D_6d point group with C--C bond alternation in all tube rings (for axial bonds, which are the vertical C--Ca bonds in rings layer and for circumferential bonds C—Cc in the outer and mid rings bonds). Assignments of the modes of vibration IR active and inactive vibration frequ

Hypertension is a cardiovascular problem with high rates of epidemiology and risks of morbidity and mortality in the global area. Nitric oxide (NO) is one of the reactive oxygen species (ROS) that produced from L-arginine by nitric oxide synthase (NOS) enzyme. NO involves in various vital processes in human health, one of which is the modulation of vasoconstriction and relaxation of the vascular system. We have aimed to investigate the link between NO and NOS with hypertension in women. The relationship between NO and NOS, as well as the usefulness of them as indicators of hypertension risks were subjects of study in this article. The results have revealed that hypertensive women had significant (P<0.05) lower levels of NO (15.07±3.41 IU/m

Polyacrylamide Solutions of different concentrations (0.2, 0.4, 0.6, 0.8, 1.0 %) of Ag nanoparticles and ZnO nanoparticles were prepared, the viscosities and surface tension were measured for all solutions, where measurements indicated an increase in these properties with increased concentration, where the relative viscosity of polyacrylamide/zinc nanoparticles increased from 1.275 to 2.243, and the relative viscosity of polyacrylamide/silver nanoparticles increased from 1.178 to 1.934. Viscosity is significant parameters during electrospinning process. While the surface tension of the polyacrylamide/zinc nanoparticles has changed from 0.0343 Nm-1 to .0.0.0 Nm-1 and changed from .0.000Nm-1 to.0.0.0 Nm-1. Also the constants KH and KK were