The Ground Penetrating Radar (GPR) is frequently used in pavement engineering
for road pavement inspection. The main objective of this work is to validate
nondestructive, quick and powerful measurements using GPR for assessment of subgrade
and asphalt /concrete conditions. In the present study, two different antennas
(250, 500 MHz) were used. The case studies are presented was carried in University
of Baghdad over about 100m of paved road. After data acquisition and radar grams
collection, they have been processed using RadExplorer V1.4 software
implementing different filters with the most effective ones (time zero adjustment and
DC removal) in addition to other interpretation tool parameters.
The interpretatio

     The bound radial wave functions of Cosh potential which are the solutions to the radial part of Schrodinger equation are solved numerically and used to compute the size radii; i.e., the root-mean square proton, neutron, charge and matter radii, ground density distributions and elastic electron scattering charge form factors for nitrogen isotopes 14,16,18,20,22N. The parameters of such potential for the isotopes under study have been opted so as to regenerate the experimental last single nucleon binding energies on Fermi's level and available experimental size radii as well.

   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

Cilnidipine is a dihydropyridine class of calcium channel blockers, it is classified as a BCS class II drug, characterized by a low oral bioavailability of 13%. Consequently, the utilization of nanoparticle preparation is anticipated to enhance its bioavailability. The objective of the research is to integrate cilnidipine nanoparticles into oral films as a means of enhancing patient adherence. The optimal polymers for producing Cilnidipine films were PVA cold and or HPMC E5 at different concentrations using a casting technique with glycerol as a plasticizer. The Nano suspension-based preparation of Cilnidipine's oral film containing the combination of polymers exhibited a significant enhancement in vitro dissolution, with a percentage excee

Results of a study of alloys and films with various Pb content have been reported and discussed. Films of of thickness 1.5 μm have been deposited on glass substrates by flash thermal evaporation method at room temperature, under vacuum at constant deposition rate. These films were annealed under vacuum around 10⁻⁶Torr at different temperatures up to 523 K. The composition of the elements in alloys was determined by standard surfaces techniques such as atomic absorption spectroscopy (AAS) and X-ray fluorescence (XRF), and the results were found of high accuracy and in very good agreement with the theoretical values. The structure for alloys and films is determined by using X-ray

In this work, ZnO nanostructures for powder ZnO were synthesized by Hydrothermal Method. Size and shape of ZnO nanostructureas can be controlled by change ammonia concentration. In the preparation of ZnO nanostructure, zinc nitrate hexahydrate [Zn(NO₃)₂·6H2O] was used as a precursor. The structure and morphology of ZnO nanostructure have been characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffraction (XRD). The synthesized ZnO nanostructures have a hexagonal wurtzite structure. Also using Zeta potential and Particle Size Analyzers and size distribution of the ZnO powder

This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi