Diesel engine oil was subjected to thermal oxidization (TO) for six periods of time (0 h, 24 h, 48 h, 72 h, 96 h, and 120 h) and was subsequently characterized by terahertz time domain spectroscopy (THz-TDS). The THz refractive index generally increased with oxidation time. The measurement method illustrated the potential of THz-TDS when a fixed setup with a single cuvette is used. A future miniaturized setup installed in an engine would be an example of a fixed setup. For the refractive index, there were highly significant differences among the oxidation times across most of the 0.3–1.7 THz range.

<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi

The Gas Assisted Gravity Drainage (GAGD) process has become one of the most important processes to enhance oil recovery in both secondary and tertiary recovery stages and through immiscible and miscible modes.  Its advantages came from the ability to provide gravity-stable oil displacement for improving oil recovery, when compared with conventional gas injection methods such as Continuous Gas Injection (CGI) and Water – Alternative Gas (WAG). Vertical injectors for CO2   gas were placed at the top of the reservoir to form a gas cap which drives the oil towards the horizontal oil producing wells which are located above the oil-water-contact. The GAGD process was developed and tested in vertical wells to increase oil r

The permeable reactive barrier (PRB) is one of the promising innovative in situ groundwater remediation technologies, in removing of copper from a contaminated shallow aquifer. The 1:1- mixture of waste foundry sand (WFS) and Kerbala’s sand (KS) was used for PRB. The WFS was represented the reactivity material while KS used to increase the permeability of PRB only. However, Fourier-transform infrared (FTIR) analysis proved that the carboxylic and alkyl halides groups are responsible for the sorption of copper onto WFS. Batch tests have been performed to characterize the equilibrium sorption properties of the (WFS+KS) mix in copper- containing aqueous
solutions. The sorption data for Cu+2 ions, obtained by batch experiments, have be

This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others

         Allopurinol derivative were prepared by reacting the (1-chloroacetyl)-2-Hydropyrazolo{3,4-d}pyrimidine-4-oneiwith 5- methoxy- 2-aminoibenzothiazoleiunder certain conditions to obtain new compound  ( N- (2-aminoacetyl (5-methoxy) benzothiazole -2yl) (A₄), Reaction of 5-(P-dimethyl amine benzene)-2-amino-1,3,4- oxadiazole in the presence of potassium carbonate anhydrous to yield new  compound (N-(2- aminoacetyl-5-(P-dimethyl amine benzene )-1,3,4-oxadiazoles-2-yl)(A₃₀) and Azo compound (N-(5-(Azo-2-hydroxy-5-amino benzene)-1,3-Diazol-2yl)Allopurinol(A₄₆). The structure of prepared compounds were confirmed by (FT-IR)

Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R