In this study, the physical, and mechanical properties of low-cost and biocomposites were evaluated. The walnut shell and date palm frond fibers were thermally treated in an oven at a temperature of 70°C and then chemically treated with NaOH and distilled water solution, after these treatments, the biocomposite materials will be thermally treated again at 50°C. This procedure was performed for three types of biocomposite; Walnut shell Fiber Reinforced Polymer (WFRP), Date palm Fiber Reinforced Polymer (DFRP), and Hybrid Fiber Reinforced Polymer (HFRP), whereas the biocomposite sheets consisting of 30% biofibers and 70% unsaturated polyester, the mechanical test specimens were cut by a CNC machine according to ASTM standards. The effect of fiber type was analyzed in terms of the mechanical properties (tensile, compression, and density). The tensile test results showed that the DFRP composite had the best results comparable with WFRP and HFRP, the ultimate tensile strength, was increased by 28.6%, and 12.5% respectively, furthermore, the compression strength of the WFRP composite was increased by 21.5%, and 10.3% compared with DFRP and HFRP composites respectively. The WFRP composite revealed the lowest value of density 4.60 g/cm3 rather than DFRP and HFRP composites.
Steps were taken to obtain the Kojic acid crystals from local fungal isolation A. flavus WJF81 by separating the fermentation products from the fungus mycelium from the production plant at the centrifuge at a speed of 5000 cycles for 10 minutes. The extraction was followed by ethyl acetate then supernatant concentrate by using rotary evaporator, and dried with heat oven 37ºC. Long, yellowish, pristine acid crystals were obtained that examined the optical microscope with a magnification force of 10x and 40x. The melting point of kojic acid was determined between 152.9-153.5 °C Results of the diagnosis of Kojic acid by applying High pressure liquid chromatography HPLC technique showed that the acid was at one peak, which was close to the
... Show MoreIn this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number determines the persistence or extinction of the COVID-19. If , one infected cell will transmit the virus to less than one cell, as a result, the person carrying the Coronavirus will get rid of the disease .If the infected cell will be able to infect all cells that contain ACE receptors. The stochastic model proves that if are sufficiently large then maybe give us ultimate disease extinction although , and this facts also proved by computer simulation.
The logistic regression model of the most important regression models a non-linear which aim getting estimators have a high of efficiency, taking character more advanced in the process of statistical analysis for being a models appropriate form of Binary Data.
Among the problems that appear as a result of the use of some statistical methods I
... Show MoreChannel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T
... Show MoreIn this work, excess properties (eg excess molar volume (VE), excess viscosity (ȠE), excess Gibbs free energy of activation of viscos flow (ΔG* E) and molar refraction changes (ΔnD) of binary solvent mixtures of tetrahydrofurfuryl alcohol (THFA) with aromatic hydrocarbons (benzene, toluene and p-xylene) have been calculated. This was achieved by determining the physical properties including density ρ, viscosity Ƞ and refraction index nD of liquid mixtures at 298.15 K. Results of the excess parameters and deviation functions for the binary solvent mixtures at 298.15 K have been discussed by molecular interactions that occur in these mixtures. Generally, parameters showed negative values and have been found to fit well to Redlich-Kister
... Show MoreAs tight gas reservoirs (TGRs) become more significant to the future of the gas industry, investigation into the best methods for the evaluation of field performance is critical. While hydraulic fractured well in TRGs are proven to be most viable options for economic recovery of gas, the interpretation of pressure transient or well test data from hydraulic fractured well in TGRs for the accurate estimation of important reservoirs and fracture properties (e.g. fracture length, fracture conductivity, skin and reservoir permeability) is rather very complex and difficult because of the existence of multiple flow profiles/regimes. The flow regimes are complex in TGRs due to the large hydraulic fractures n
The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri
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