Pure and doped TiO 2 with Bi films are obtained by pulse laser deposition technique at RT under vacume 10-3 mbar, and the influence of Bi content on the photocvoltaic properties of TiO 2 hetrojunctions is studied. All the films display photovoltaic in the near visible region. A broad double peaks are observed around λ= 300nm for pure TiO 2 at RT in the spectral response of the photocurrent, which corresponds approximately to the absorption edge and this peak shift to higher wavelength (600 nm) when Bi content increase by 7% then decrease by 9%. The result is confirmed with the decreasing of the energy gap in optical properties. Also, the increasing is due to an increase in the amount of Bi content, and shifted to 400nm when annealed at 523

In this paper, silicon carbonitried thin films were prepared by the method of photolysis of the silane (SiH4) and ethylene (C2H4) gases, with and without ammonia gas (NH3), which is represented by the ratio between the (PNH3) and (PSiH4 + PC2H4 + PNH3), (which assign by the letter X), X has the values (0, 0.13, 0.33). This method carried out by using TEA-CO2 laser, on glass substrate at (375 oC), deposition rate (0.416-0.833) nm/pulse thin film thickness of (500-1000) nm. The optical properties of the films were studied by using Absorbance and Transmittance spectrums in wavelength range of (400-1100) nm, the results showed that the electronic transitions is indirect and the energy gap for the SiCN films increase with increasing of nitrog

This investigation was carried out to examine the effect of replacing partial of flour by dried Lentils (Lens culinaris) to white flour in different percentages on the chemical, sensory and storage properties of the Laboratory bread. The results revealed that replacing 0% than wheat flour by lentil powder (1) control was high significan than the replacing 25 and 35% than wheat flour by lentil powder ( 4 and 5) in flavor and chewiness . The results of sensory evaluation showed that replacing 4 were high significan different than that of replacing 1 in external layer colour. Other replacing percentages, however, did not show significant differences of in comparison with control . In regards with chemical analysis of Iron and copper, i

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Filed experiment was conducted to test the effect of saline water and potassium fertilizers rate on proline and water potential of Pisum sativum L. (Var.Senador Cambados ) leaves . Treatments of the experiment included two levels of water salinity( 2, 7 dSm-1) as a main plot and fertilizer rates as a sub plot. Results indicated that irrigation of plant with saline water 7 dSm-1 and fertilization 150 kg/donum increased proline accumulation and water potential 0.31 mmol/g,-17.00 bar at 9 AM morning and 0.62 mmol/g , -21.00 bar at 3 PM afternoon ,Irrigating plant with a 2 dSm-1 and fertilization 300 kg/donum decreased proline accumulation and water potential of leaves 0.22 mmol/g, -16.00 bar at 9 A

The preparation and characterization of innovative nanocomposites based on zinc oxide nanorods (ZNR) encapsulated by graphene (Gr) nanosheets and decorated with silver (Ag), and cupper (Cu) nanoparticles (NP) were studied. The prepared nanocomposites (ZNR@Gr/Cu-Ag) were examined by different techniques including Field Emission Scanning Electron Microscope (FESEM), Transmission electron microscopy (TEM), Atomic force microscopy (AFM), UV-Vis spectrophotometer and fluorescence spectroscopy. The results showed that the ZNR has been good cover by five layers of graphene and decorated with Ag and Cu NPs with particles size of about 10-15 nm. The ZNR@Gr/Cu-Ag nanocomposites exhibit high absorption behavior in ultraviolet (UV) region of sp