The Video effect on Youths Value

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

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

Titanium dioxide (TiO2) thin films were prepared under different pressures with values (15, 30, 60 and 120) Pa using the DC reactive magnetron homemade system with mixed gases of argon and oxygen in ratio (50:50). The result of X-ray diffraction patterns discovered that the structure of the deposited films was polycrystalline, including the phase of anatase. All the appeared peaks were matched to the planes (101), (004), (105), and (211) of diffracted states. Both the intensities and the number of the appeared peaks are declined according to the increased pressure, and the plane of (101) is be considered the preferential grown plane, it is taking a maximum texture factor. Both the lattice constant and the atomic inter-planer spacing take th

The primary aim of the present study was to prepare a set of exercises on the multi-resistor VertiMax device and to identify the effect of these exercises on the development of the endurance of discus throwers under 16 years old. The design of the present study was experimental. Participants were selected using purposive sampling method. A total of 5 discuss players constituted the sample of the study. The authors found a significant improvement in the levels of endurance and performance as a result of the training on the VertiMax device. Therefore, it is recommendable to use exercises on the VertiMax device to improve the endurance and performance of under 16-years of age discus throwers.

Background/Aim: Understanding how perinatal outcome variations affect dentition eruption can lead to healthcare providers monitoring and managing dental health in infants and children. This study aimed to evaluate the influence of gestational age, mode of delivery and birth weight on the stage of primary dentition eruption in children. Methods: A sample of 304 children aged 6-24 months from Baghdad City was studied. Information about gestational age, delivery method (vaginal vs Caesarean) and birth weight were evaluated through a parent-answered sheet. The stage of dental eruption was estimated based on the criteria established by Damodar P Swami. Statistical and descriptive analyses were utilised to compare the dental eruption stag

Nanomaterials have an excellent potential for improving the rheological and tribological properties of lubricating oil. In this study, oleic acid was used to surface-modify nanoparticles to enhance the dispersion and stability of Nanofluid. The surface modification was conducted for inorganic nanoparticles (NPs) TiO₂ and CuO with oleic acid (OA) surfactant, where oleic acid could render the surface of TiO₂-CuO hydrophobic. Fourier transform infrared spectroscopy (FTIR), and Scanning electron microscopy (SEM) were used to characterize the surface modification of NPs. The main objective of this study was to investigate the influence of adding modified TiO₂-CuO NPs with weight ratio 1:1 on thermal-physical propertie

 This research was to determine the effect of rare earth metal (REM) on the as-cast microstructure of Mg-4Al alloy. The rare earth metal used here is Lanthanum to produce Mg-4Al-1.5La alloy. The microstructure was characterized by optical microscopy. The phases of this alloy were identified by X-ray diffraction. The microstructure of Mg-4Al consists of α-Mg and grain boundaries with precipitated phase particles. With the addition of Lanthanum, three distinct phases were identified in the X-ray diffraction patterns of the as cast Mg-4Al-1.5La:  Mg, Al₁₁La₃, Al₄La. The Mg₁₇Al₁₂ phase was not detected. The addition of Lanthanium increases the hardness and dec

The present work aimed to study the SiO2μPs, and NPs effect on the biodegradability of St/PVA blends. The samples were prepared by casting method as PVA, St/PVA blends with different concentrations (30, 40, 50, and 60 %). FTIR test was carried out for the samples preparation. The results proved some changes which might be related to changing in crystallinity of St/PVA matrix as well as physical incorporation of SiO2 μPs, and NPs addition. The enzymatic test and water uptake results proved that increase in weight loss with increases of starch ratio. The lowest weight loss was PVA; the highest weight loss is 60% St/PVA whereas the lowest weight loss is 30%St/PVA for blends involved. SiO2μPs (753.7 nm), and NPs (263.1 nm) were added at d