High temperature superconductors with a nominal composition HgBa2Ca2Cu3O8+δ
for different values of pressure (0.2,0.3, 0.5, 0.6, 0.9, 1.0 & 1.1)GPa were prepared by
a solid state reaction method. It has been found that the samples were semiconductor
P=0.2GPa.while the behavior of the other samples are superconductor in the rang
(80-300) K. Also the transition temperature Tc=143K is the maximum at P is equal to
0.5GPa. X-ray diffraction showed a tetragonal structure with the decreasing of the
lattice constant c with the increasing of the pressure. Also we found an increasing of
the density with the pressure.

This paper deals with prediction the effect of soil re-moulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil re-moulding due to actual pile driving. The re

Nanomaterials have an excellent potential for improving the rheological and tribological properties of lubricating oil. In this study, oleic acid was used to surface-modify nanoparticles to enhance the dispersion and stability of Nanofluid. The surface modification was conducted for inorganic nanoparticles (NPs) TiO₂ and CuO with oleic acid (OA) surfactant, where oleic acid could render the surface of TiO₂-CuO hydrophobic. Fourier transform infrared spectroscopy (FTIR), and Scanning electron microscopy (SEM) were used to characterize the surface modification of NPs. The main objective of this study was to investigate the influence of adding modified TiO₂-CuO NPs with weight ratio 1:1 on thermal-physical propertie

A significant influence of temperature width found on the vanadium oxide properties, it plays a major role in highlighting the thermal limits of the three phases (metallic, semiconductor, and dielectric). Two values of the temperature width , and , had taken and studied their effect on both the dielectric constant and its two parts; refractive index, and extinction coefficient, and. It found that: as the temperature width is greater, the more the properties of the three phases for . In addition to increasing the thermal range for phases which can be reached to when , while it's at . Our results have achieved great compatibility with the published results globally. In addition to the effect of both ultraviolet, visible, and infrared

The research aims to know the influence of the intellectual capital on the internal control system in a sample of General Inspection Offices in Iraq. The research includes a sample of individuals who are working in these offices total sample (46) individuals distributed according to functional levels (General Inspector, Deputy Inspector General, and Director) , The data and information were collected by using questionnaire, which is done for this purpose, as well as personal interviews in order to reach to the results that achieve the aim of this research , Two hypotheses were formed , the first hypothesis consists of (4) secondary hypothesis , All these hypotheses were tested by using statistical tools such as (percentages, freq

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

In this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m³

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de