ZnO thin films have been prepared by pulse laser deposition technique at room temperatures (RT). These films were deposited on GaAs substrate to form the ZnO/GaAs heterojunction solar cell. The effect of annealing temperatures at ( RT,100, 200)K on structural and optical properties of ZnO thin films has been investigated. The X-ray diffraction analysis indicated that all films have hexagonal polycrystalline structure. AFM shows that the grains uniformly distributed with homogeneous structure. The optical absorption spectra showed that all films have direct energy gap. The band gap energy of these films decreased with increasing annealing temperatures.  From the electrical properties, the carriers have n-type conductivity.  From

This paper reports the effect of Mg doping on structural and optical properties of ZnO prepared by pulse laser deposition (PLD). The films deposited on glass substrate using Nd:YAG laser (1064 nm) as the light source. The structure and optical properties were characterized by X-ray diffraction (XRD) and transmittance measurements. The films grown have a polycrystalline wurtzite structure and high transmission in the UV-Vis (300-900) nm. The optical energy gap of ZnO:Mg thin films could be controlled between (3.2eV and 3.9eV). The refractive index of ZnO:Mg thin films decreases with Mg doping. The extinction coefficient and the complex dielectric constant were also investigate.

Background: Osteoporosis is denoted by low bone mass and microarchitectural breakdown of bone tissue, directing to increased fracture risk and bone fragility. Fractures may lead to a decreased quality of life and increased medical costs. Thus, osteoporosis is widely considered a significant health concern.

Objective. This study aimed to compare quantitative computed tomography (QCT) and dual-energy X-Ray absorptiometry (DXA) to detect osteoporosis in postmenopausal women.

Subjects and Methods. We measured spinal volumetric bone mineral density (BMD) with QCT and areal spinal and hip BMD with DXA in 164 postmenopausal women. We calculated the osteo

Undoped and Co-doped zinc oxide (CZO) thin films have been prepared by spray pyrolysis technique using solution of zinc acetate and cobalt chloride. The effect of Co dopants on structural and optical properties has been investigated. The films were found to exhibit maximum transmittance (~90%) and low absorbance. The structural properties of the deposited films were examined by x-ray diffraction (XRD). These films, deposited on glass substrates at (400? C), have a polycrystalline texture with a wurtzite hexagonal structure, and the grain size was decreased with increasing Co concentration, and no change was observed in lattice constants while the optical band gap decreased from (3.18-3.02) eV for direct allowed transition. Other parameters

Structural and optical properties of CdO and CdO0.99Cu0.01 thin
films were prepared in this work. Cadmium Oxide (CdO) and
CdO0.99Cu0.01semiconducting films are deposited on glass substrates
by using pulsed laser deposition method (PLD) using SHG with Qswitched
Nd:YAG pulsed laser operation at 1064nm in 6x10-2 mbar
vacuum condition and frequency 6 Hz. CdO and CdO0.99Cu0.01 thin
films annealed at 550 C̊ for 12 min. The crystalline structure was
studied by X-ray diffraction (XRD) method and atomic force
microscope (AFM). It shows that the films are polycrystalline.
Optical properties of thin films were analyzed. The direct band gap
energy of CdO and CdO0.99Cu0.01 thin films were determined from
(αhυ)1/2 v

optical properties of pure poly(vinyl Alcohol) films and poly(vinyl Alcohol) doped with methyl red were study, different percentage prepared with constant thickness using casting technique. Absorption, Transmission spectra have been recorded in order to study the optical parameters such as absorption coefficient, energy gap, refractive index, Extinction coefficient and dispersion parameters were measured in the wavelength range (200-800)nm. This study reveals that the optical properties of PVA affect by increasing the impurity concentration.

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T