Gypsiferous soil deposits (Gypcrete) are weakly consolidate earthy mixture of secondary gypsum, sand and clay. It is formed in arid and semi- arid area with annual precipitation rainfall less than 400mm. These sediments occur in surface and subsurface in region of little rainfall and rapid evaporation. This research deals with the study of gypcrete in Alexandria to improve the mineralogical and geochemical properties of the gypcrete. The gypcrete soil is used as raw material to produce the plaster for building purposes. Three samples of gypcrete were chemically and geochemically analyzed. The common mineral is howed in 0-0.5m Gypsum followed by Calcite in 0-1m and Quartz in 1-1.5m due to leaching and infiltration by rainfall as well as it

Background: The aim of the study was to investigate the effect of surface treatments of zirconia (grinding and sandblast with 50μm, 100 μm) on shear bond strength between zirconia core and veneering ceramic. Material and methods: Twenty-eight presintered Y-TZP ceramic specimens (IPS e.max ZirCAD, Ivoclar vivadent) were fabricated and sintered according to manufacturer’s instructions. The core specimens were divided randomly in to 4 groups, group 1: no surface treatment, group2: zirconia specimens were ground with silicon carbide paper up to1200 grit under water cooling, group3: zirconia specimens were ground and sandblast with 100 μm alumina, group 4: zirconia specimens were ground and sandblast with 50 μm alumina. Surfa

Introduction: The current study investigated the use of acid-treated rice husks to remove heavy metals and organic pollutants from water containing heavy metals (R2C and Cd2) and organic pollutants (phenol and atrazine). Methods: The adsorption effect of acid-treated rice husks was compared with other adsorbents such as activated carbon, chitosan, and bentonite clay. Result: both acid-treated rice husks and activated carbon were highly efficient materials, and thus, rice husks were established as a cost-effective alternative. It was revealed that acid treatment of rice husks enhanced adsorption capacity by half, and lead removal was nearly doubled. The most effective pH value for optimizing organic pollutants and heavy metals while

The study investigates the water quality of the Orontes River, which is considered one of the important water recourses in Syria, as it is used for drinking, irrigation, swimming and industrial needs. A database of 660 measurements for 13 parameters concentrations used, were taken from 11 monitoring points distributed along the Orontes River for a period of five years from 2015-2019, and to study the correlation between parameters and their impact on water quality, statistical analysis was applied using (SPSS) program. Cluster analysis was applied in order to classify the pollution areas along the river, and two groups were given: (low pollution - high pollution), where the areas were classified according to the sources of pollution to w

In this work, study the optical properties of composites consisting of poly Methyl Methacrylate and Berry Paper Mulberry. The samples of composites were prepared using casting method .The Berry Paper Mulberry (BPM) was added by different concentrations are (0, 2, 4 and 6)wt.%. The optical properties of composites have been studied in the wavelength range (200-800)nm. The absorption coefficient ,energy gap, refractive index, extinction coefficient and dielectric constants have been determined. The results show that the optical constants change with increase of BPM concentrations .

Cr2O3 thin films have been prepared by spray pyrolysis on a glass substrate. Absorbance and transmittance spectra were recorded in the wavelength range (300-900) nm before and after annealing. The effects of annealing temperature on absorption coefficient, refractive index, extinction coefficient, real and imaginary parts of dielectric constant and optical conductivity were expected. It was found that all these parameters increase as the annealing temperature increased to 550°C.

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d