Iraqi crude Atmospheric residual fraction supplied from al-Dura refinery was treated to remove metals contaminants by solvent extraction method, with various hydrocarbon solvents and concentrations. The extraction method using three different type solvent (n-hexane, n-heptane, and light naphtha) were found to be effective for removal of oil-soluble metals from heavy atmospheric residual fraction. Different solvents with using three different hydrocarbon solvents (n-hexane, n-heptane, and light naphtha) .different variables were studied solvent/oil ratios (4/1, 8/1, 10/1, 12/1, and 15/1), different intervals of perceptual (15, 30-60, 90 and 120 min) and different temperature (30, 45, 60 and 90 °C) were used. The metals removal perce

     Carbon Monoxide (CO) has a significant indirect effect on greenhouse gasses due to its ozone and carbon dioxide precursor, and its mechanism of degradation involving the hydroxyl radical (OH) which control the oxidizing ability of the tropospheric. To understand the effect of human activities on atmospheric composition, accurate estimates of the sources of atmospheric carbon monoxide (CO) are necessary. MOPITT (Measurements of Pollution in the Troposphere) is a NASA Terra satellite instrument designed to allow both Thermal-Infra-Red (TIR) and Near-Infra-Red (NIR) observations to be used to collect vertical CO profiles in the Troposphere via the concept of correlation spectroscopy. The objective of the current stu

Some microorganisms, including fungi, are characterized by their removal efficiency and reducing the concentrations of heavy metals such as Pb and Cr from industrial water. The present study aims to estimate the efficiency of Penicillium digitatum (Pers.) Sacc. as a low-cost biosorbent in reducing Pb and Cr from industrial water with optimum biosorption conditions (acidity of 1.5 , 4, and 5; temperature of 30 °C). The Fourier transform infrared spectroscopy (FTIR) analysis was also used for determining the roles of the functional groups in this biosorbent. The results indicated that the highest P. digitatum efficiency values for reducing the levels of Pb and Cr were 84% and 70% , respectively, at pH of 5 after 24 h.

Fourty three isolates ( 20.7%) characterized as Staphylococcus aureus , were isolated from 207 different clinical sources (blood , nose, , wound , urine , vaginal, ear and eye) in different percentages (30.23, 18.60, 16.28, 13.95, 15.15, 6.96 and 2.33 %), respectively. The staphyloxanthin (STX) production of S. aureus isolate was estimated 72.1% .The optimal conditions for pigment production by S. aureus AE36 , were detected and was noticed that the milk agar medium revealed the highest production of pigment which was estimated to be 165.21unit/cell, at pH 8 for 72 hr at 370C. The Staphyloxanthin pigment was extracted using methanol and was purified partially by organic solvents and Thin Layer Chromatography (TLC). The results revealed t

Two homopolymeric and three copolymeric additives for base oil were synthesized using octyl acrylate (OA) and tert-butyl acrylamide (TBA) monomers. The two additives named P1 and P2 are the homopolymers of TBA and OA, respectively, whereas copolymeric additives named Co1, Co2, and Co3 were synthesized by varying the ratios of TBA:OA as 1:3, 3:1 and 1:1, respectively. The prepared polymers were characterized by Fourier Transform Infrared (FTIR). Based on the solubility of synthesized polymers in base oil and reactivity ratios of TBA/OA copolymer (0.222, 0.434) calculated by Fineman-Ross method, P2, Co1, Co2 and Co3 were selected to evaluate their performance as pour point depressant (PPD), viscosity improver (VII), and anticorrosion addit

This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi

This work explores the designing a system of an automated unmanned aerial vehicles (UAV( for objects detection, labelling, and localization using deep learning. This system takes pictures with a low-cost camera and uses a GPS unit to specify the positions. The data is sent to the base station via Wi-Fi connection.

The proposed system consists of four main parts. First, the drone, which was assembled and installed, while a Raspberry Pi4 was added and the flight path was controlled. Second, various programs that were installed and downloaded to define the parts of the drone and its preparation for flight. In addition, this part included programs for both Raspberry Pi4 and servo, along with protocols for communication, video transmi