The aim of this work is to evaluate some mechanical and physical
properties (i.e. the impact strength, hardness, flexural strength,
thermal conductivity and diffusion coefficient) of
(epoxy/polyurethane) blend reinforced with nano silica powder (2%
wt.). Hand lay-up technique was used to manufacture the composite
and a magnetic stirrer for blending the components. Results showed
that water had affected the bending flexural strength and hardness,
while impact strength increased and thermal conductivity decreased.
In addition to the above mentioned tests, the diffusion coefficient
was calculated using Fick’s 2nd law.
Background: Waterpipe tobacco smoking has become common especially among young people, Waterpipe smoking misconcepted as a safer mean of smoking, so in this study we will highlight the effect of Waterpipe smoking ‎on periodontal and oral health.‎ Materials and method. The selected ‎‎‎100 male subjects of 30-40 years, ‎categorized into 4 groups (each group ‎‎25 subject): Waterpipe smoker ‎with ‎healthy periodontium, ‎Waterpipe smoker ‎‎with chronic periodontitis, Non-‎‎smoker ‎with healthy periodontium and Non-smoker ‎with chronic periodontitis. Whole ‎unstimulated ‎saliva was collected. Clinical measurements: plaque ‎index
... Show MoreAt a temperature of 300 K, a prepared thin film of Ag doped with different ratios of CdO (0.1, 0.3, 0.5) % were observed using pulse laser deposition (PLD). The laser, an Nd:YAG in ?=1064 nm, used a pulse, constant energy of 600 mJ ,with a repetition rate of 6 Hz and 400 pulses. The effect of CdO on the structural and optical properties of these films was studied. The structural tests showed that these films are of a polycrystalline structure with a preferred orientation in the (002) direction for Ag. The grain size is positively correlated with the concentration of CdO. The optical properties of the Ag :CdO thin film we observed included transmittance, absorption coefficient, and the energy gap in the wavelength range of 300-1100
... Show MoreSamarium ions (Sm +3), a rare-earth element, have a significant optical emission within the visible spectrum. PMMA samples, mixed with different ratios of SmCl3.6H2O, were prepared via the casting method. The composite was tested using UV-visible, photoluminescence and thermogravimetric analysis (TGA). The FTIR spectrometry of PMMA samples showed some changes, including variation in band intensity, location, and width. Mixed with samarium decreases the intensity of the CO and CH2 stretching bands and band position. A new band appeared corresponding to ionic bonds between samarium cations with negative branches in the polymer. These variations indicate complex links between the Sm +3 ion and oxygen in the ether group. The optical absorption
... Show MoreTight reservoirs have attracted the interest of the oil industry in recent years according to its significant impact on the global oil product. Several challenges are present when producing from these reservoirs due to its low to extra low permeability and very narrow pore throat radius. Development strategy selection for these reservoirs such as horizontal well placement, hydraulic fracture design, well completion, and smart production program, wellbore stability all need accurate characterizations of geomechanical parameters for these reservoirs. Geomechanical properties, including uniaxial compressive strength (UCS), static Young’s modulus (Es), and Poisson’s ratio (υs), were measured experimentally using both static and dynamic met
... Show MoreIn this article, the casting method was used to prepare poly(methyl methacrylate)/hydroxyapatite (PMMA/HA) nanocomposite films incorporated with different contents (0.5, 1, and 1.5 wt%) of graphene nanoplatelets (Gnp). The chemical properties and surface morphology of the PMMA/HA blend and PMMA/HA/Gnp nanocomposite were characterized using FTIR, and SEM analysis. Besides, the thermal conductivity, dielectric and electrical properties at (1–107 Hz) of the PMMA/HA blend and PMMA/HA/Gnp composites were investigated. The structural analysis showed that the synthesized composites had a low agglomerated state, with multiple wrinkles of graphene flakes in the PMMA/HA blend. The thermal conductivity was improved by more than 35-fold its value for
... Show MoreThis study was done to test the activity of some plant extracts as antioxidant agents. The plants were (Morus rubra, Hibiscus sabdariffa L ., Rhus coriaria L., Anethum graveolens and Petroselinum sativum).
Ethanolic 98% (24 hours/ 25˚c) and distilled water (30 minutes/ 25˚c have been used for extraction.The Total phenols, total flavonoids, total anthocyanin, antioxidant activities were studied.
The extract of Morus rubra was chosen because it has a higher antioxidant activity.
The phenolic extract of Morus rubra was prepare and examined by application it in burger . The antioxidant activity test of Morus rubra was made before and after 3,6 days of cold storage. The sensory evaluation of all treatments were done within 5,1
Most studies on deep beams have been made with reinforced concrete deep beams, only a few studies investigate the response of prestressed deep beams, while, to the best of our knowledge, there is not a study that investigates the response of full scale (T-section) prestressed deep beams with large web openings. An experimental and numerical study was conducted in order to investigate the shear strength of ordinary reinforced and partially prestressed full scale (T-section) deep beams that contain large web openings in order to investigate the prestressing existence effects on the deep beam responses and to better understand the effects of prestressing locations and opening depth to beam depth ratio on the deep beam performance and b
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for