<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

structural and electrical of CuIn (Sex Te1-x)2

Inthisstudy,FourierTransformInfraredSpectrophotometry(FTIR),XRay Diffraction(XRD)andlossonignition(LOI),comparativelyemployedtoprovideaquick,relativelyinexpensiveandefficientmethodforidentifyingandquantifyingcalcitecontentofphosphateoresamplestakenfromAkashatsiteinIraq.Acomprehensivespectroscopicstudyofphosphate-calcitesystemwasreportedfirstintheMid-IRspectra(4004000cm-1)usingShimadzuIRAffinity-1,fordifferentcutsofphosphatefieldgradeswithsamplesbeneficiatedusingcalcinationandleachingwithorganicacidatdifferenttemperatures.Thenusingtheresultedspectratocreateacalibrationcurverelatesmaterialconcentrationstotheintensity(peaks)ofFTIRabsorbanceandappliesthiscalibrationtospecifyphosphate-calcitecontentinIraqicalcareousphosphateore.Theirpeakswereass

Studying the past for its importance and connection with the present is reflected in a relative scale in the light of data and thought of the predecessors of a great nation like the Mesopotamia, where its civilization flourished and rose since the ancient times, which inspires the present with inherited meanings that might be an entity or recognized symbols in the establishment of a vision, system or architectural building. The researcher has crystallized the description of the past to enhance the vision of the present within what is required by the interior design specialty about the historical origins of education and the design of schools in the Mesopotamia, in addition to its ethnic and environmental specificity and the moral content

The research aims to identify the rates of hair loss during pregnancy and lactation and its relation to the rates get some elements motivator urged through the results of the continued failure to meet the need of daily assessments of these elements, which led to the continuation of Hair Loss

Applications of superconductor compounds were considered as modern and important topics, especially these which are exposures to one of the nuclear radiation kinds. So, we gone to investigate the influence of fast neutrons irradiation on electrical and structural characteristics of HgxSb1-xBa2Ca2Cu3O8+δ superconducting compound at (x = 0.7) in ratio. The superconducting specimens were synthesized using solid state technique. Specimens were exposure to the nuclear radiation using fast neutrons with doses (0, 9.06 x1010, 15.3 x 1010 and 18.17 x 1010) n/cm2 respectively. Electrical and X-ray diffraction properties of superconductor specimens before and after irradiation were investigated under standard conditions. Results of X-ray diffraction

In this study, the results of x-ray diffraction methods were used to determine the Crystallite size and Lattice strain of Cu2O nanoparticles then to compare the results obtained by using variance analysis method, Scherrer method and Williamson-Hall method. The results of these methods of the same powder which is cuprous oxide, using equations during the determination the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (28.302nm) and the lattice strain (0.03541) of the variance analysis method respectively and for the Williamson-Hall method were the results of the crystallite size (21.678nm) and lattice strain (0.00317) respectively, and Scherrer method which gives the value of c