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  1. Awan MJ, Bilal MH, Yasin A, Nobanee H, Khan NS, Zain AM
    Int J Environ Res Public Health, 2021 Sep 27;18(19).
    PMID: 34639450 DOI: 10.3390/ijerph181910147
    Coronavirus disease (COVID-19) spreads from one person to another rapidly. A recently discovered coronavirus causes it. COVID-19 has proven to be challenging to detect and cure at an early stage all over the world. Patients showing symptoms of COVID-19 are resulting in hospitals becoming overcrowded, which is becoming a significant challenge. Deep learning's contribution to big data medical research has been enormously beneficial, offering new avenues and possibilities for illness diagnosis techniques. To counteract the COVID-19 outbreak, researchers must create a classifier distinguishing between positive and negative corona-positive X-ray pictures. In this paper, the Apache Spark system has been utilized as an extensive data framework and applied a Deep Transfer Learning (DTL) method using Convolutional Neural Network (CNN) three architectures -InceptionV3, ResNet50, and VGG19-on COVID-19 chest X-ray images. The three models are evaluated in two classes, COVID-19 and normal X-ray images, with 100 percent accuracy. But in COVID/Normal/pneumonia, detection accuracy was 97 percent for the inceptionV3 model, 98.55 percent for the ResNet50 Model, and 98.55 percent for the VGG19 model, respectively.
  2. Shahzad MK, Hussain S, Farooq MU, Laghari RA, Bilal MH, Khan SA, et al.
    Heliyon, 2023 Feb;9(2):e13687.
    PMID: 36873152 DOI: 10.1016/j.heliyon.2023.e13687
    Perovskite materials play a vital role in the field of material science via experimental as well as theoretical calculations. Radium semiconductor materials are considered the backbone of medical fields. These materials are considered in high technological fields to be used as controlling the decay ability. In this study, radium-based cubic fluoro-perovskite XRaF3 (where X = Rb and Na) are calculated using a DFT (density functional theory). These compounds are cubic nature with 221 space groups that construct on CASTEP (Cambridge-serial-total-energy-package) software with ultra-soft PPPW (pseudo-potential plane-wave) and GGA (Generalized-Gradient-approximation)-PBE (Perdew-Burke-Ernzerhof) exchange-correlation functional. The structural, optical, electronic, and mechanical properties of the compounds are calculated. According to the structural properties, NaRaF3 and RbRaF3 have a direct bandgap with 3.10eV and 4.187eV of NaRaF3 and RbRaF3, respectively. Total density of states (DOS) and partial density of states (PDOS) provide confirmation to the degree of electrons localized in distinct bands. NaRaF3 material is semiconductors and RbRaF3 is insulator, according to electronic results. The imaginary element dispersion of the dielectric function reveals its wide variety of energy transparency. In both compounds, the optical transitions are examined by fitting the damping ratio for the notional dielectric function scaling to the appropriate peaks. The absorption and the conductivity of NaRaF3 compound is better than the RbRaF3 compound which make it suitable for the solar cell applications increasing the efficiency and work function. We observed that both compounds are mechanically stable with cubic structure. The criteria for the mechanical stability of compounds are also met by the estimated elastic results. These compounds have potential application in field of solar cell and medical.

    OBJECTIVES: The band gap, absorption and the conductivity are necessary conditions for potential applications. Here, literature was reviewed to check computational translational insight into the relationships between absorption and conductivity for solar cell and medical applications of novel RbRaF3 and NaRaF3 compounds.

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