Because of the quick growth of electrical instruments used in noxious gas detection, the importance of gas sensors has increased. X-ray diffraction (XRD) can be used to examine the crystal phase structure of sensing materials, which affects the properties of gas sensing. This contributes to the study of the effect of electrochemical synthesis of titanium dioxide (TiO2) materials with various crystal phase shapes, such as rutile TiO2 (R-TiO2NTs) and anatase TiO2 (A-TiO2NTs). In this work, we have studied the effect of voltage on preparing TiO2 nanotube arrays via the anodization technique for gas sensor applications. The results acquired from XRD, energy dispersion spectroscopy (EDX), and field emission scanning electron microscopy

Because of the quick growth of electrical instruments used in noxious gas detection, the importance of gas sensors has increased. X-ray diffraction (XRD) can be used to examine the crystal phase structure of sensing materials, which affects the properties of gas sensing. This contributes to the study of the effect of electrochemical synthesis of titanium dioxide (TiO₂) materials with various crystal phase shapes, such as rutile TiO₂ (R-TiO₂NTs) and anatase TiO₂ (A-TiO₂NTs). In this work, we have studied the effect of voltage on preparing TiO₂ nanotube arrays via the anodization technique for gas sensor applications. The results acquired from XRD, energy dispersion spectro

Objective: Carbamazepine is typically used for the treatment of seizure disorders and neuropathic pain. One of the major problems with this drug is its low solubility in water; therefore the objective of this study was to enhance the solubility of carbamazepine by complexation with cyclodextrin to be formulated as effervescent and dispersible granules.Methods: Solvent evaporation method was used to prepare, binary (Carbamazepine/β-cyclodextrin) complex and ternary (Carbamazepine/β-cyclodextrin/hydroxypropyl methyl cellulose (HPMC E5). The more soluble complex will be further formulated as unit dose effervescent and dispersible granules. The complexes were evaluated for their solubility, drug content, percentage practical yield and

In this research, the results of x-ray diffraction method were used to determine the uniform stress deformation and microstructure parameters of CuO nanoparticles to determine the lattice strain obtained and crystallite size and then to compare the results obtained by two model Halder Wagner and Size Strain Plot with the results of these methods of the same powder using equations during which the calculation of the size of the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (19.81nm) and the lattice strain (0.004065) of the Halder-wagner model respectively and for the ssp method were the results of the crystallite size (17.20nm) and lattice strain (0.000305) respectively. The sa

HR Al-Hamamy, KE Sharquie, AA Noaimi, WN Hussein, Our Dermatology Online, 2014 - Cited by 6

This study was aimed to monitor oral zinc sulfate role on local cervical proinflammatory cytokines in HPV-infected women comparing with these cytokines before treatment application. A cervical secretion got from 28 infected women before and after treatment with zinc sulfate, these samples assessed various markers of inflammation including interleukin-1β, IL-8, and IL-12. Results manifested that improve and clear the cervical HPV infections after three months of zinc treatment 46.43% and 21.43%, respectively. Viral infections with single and multiple HPV high-risk types are raising of studied cytokines after 3-month compared with single HPV low-risk type. Moreover, this increasing was statistically significant only in IL-12 and IL-1. Women

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated