Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

This research presents a method of using MATLAB in analyzing a nonhomogeneous soil (Gibson-type) by
estimating the displacements and stresses under the strip footing during applied incremental loading
sequences. This paper presents a two-dimensional finite element method. In this method, the soil is divided into a number of triangle elements. A model soil (Gibson-type) with linearly increasing modulus of elasticity with depth is presented. The influences of modulus of elasticity, incremental loading, width of footing, and depth of footing are considered in this paper. The results are compared with authors' conclusions of previous studies.

   The present research was conducted to synthesis Y-Zeolite by sol-gel technique using MWCNT (multiwalled carbon nanotubes) as crystallization medium to get a narrow range of particle size distribution with small average size compared with ordinary methods. The phase pattern, chemical structure, particle size, and surface area were detected by XRD, FTIR, BET and AFM, respectively. Results shown that the average size of Zeolite with and without using MWCNT were (92.39) nm and (55.17) nm respectively .Particle size range reduced from (150-55) nm to (130-30) nm. The surface area enhanced to be (558) m²/g with slightly large pore volume (0.231) km³/g was obtained. Meanwhile, degree of crystallization decrease

Background: Determination of local bone mineral density (BMD) immediately after implant insertion play an important role in implant success rate, may offer comprehensive description of the bone, and give enough information to the surgeon prior to implant insertion and at follow up status. The aim of the present study is to evaluate the changes of local bone density in the dental implant recipient sites by using computerized tomography. Material and method: The sample consisted of (20) dental implants recipient sites, bone density assessment was done twice, immediately after implants insertion and after six months. Results: The mean HU of the bone around the implant insertion site, immediately after implant placement was 552.28 HU, and inc