Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

This thesis was aimed to study gas hydrates in terms of their equilibrium conditions in bulk and their effects on sedimentary rocks. The hydrate equilibrium measurements for different gas mixtures containing CH4, CO2 and N2 were determined experimentally using the PVT sapphire cell equipment. We imaged CO2 hydrate distribution in sandstone, and investigated the hydrate morphology and cluster characteristics via μCT. Moreover, the effect of hydrate formation on the P-wave velocities of sandstone was investigated experimentally.

CR-39 is a solid state nuclear track detector (SSNTD) that has been used in many research areas. In spite of the assumption that the CR-39 detectors are insensitive to beta and gamma rays, irradiation with these rays can have significant effects on the detector properties. In this study, beta and gamma rays mass attenuation coefficients μ/ρ (cm2 g-1) for the CR-39 detector have been measured using NaI(Tl) scintillation spectrometer along with a standard geometrical arrangement in the energy region of (0.546-2.274) MeV beta rays and standard gamma sources having energy 0.356, 0.5697, 0.6617 and 1.063 MeV. The total atomic cross-section (σtot), total electronic cross-section (σT E) and the effective atomic number (Zeff) of gamma rays a

Background: Most prevalent chronic liver disease in developed and developing nations is non-alcoholic fatty liver disease. From fatty liver, which often has benign, non-progressive clinical history, to non-alcoholic steatohepatitis, a more serious variant of fatty liver that can lead to cirrhosis and end-stage liver disease, non-alcoholic fatty liver disease encompasses broad spectrum of diseases. The gold standard for determining extent of hepatic fibrosis is still liver biopsy; however, number of noninvasive tests have been established to make diagnosis and assess effectiveness of treatment.

Objective: Aim of study was to assess effectiveness of the combination of fibroscan and

This paper aims to deal with the understanding of the properties of the molecular gas hydrogen in the extragalactic spirals sample. It is critical to make observations of CO (J = 1-0) line emission for spiral galaxies, particularly those with an energetic nucleus.  In the sample of spiral galaxies compiled, a carbon monoxide CO (1-0) emission line can be observed. This sample of galaxies' gas kinematics and star-forming should be analyzed statistically utilizing appropriate atomic gas HI, molecular gas H2, infrared (1μm-1000μm), visual (at λblue-optical=4400A0), and radio spectrum (at νradio=1.4 GHz and 5GHz) databases. STATISTICA is software that allows us to perform this statistical analysis. The presence of a high scale of s

Beta-irradiation effects on the microstructure of LDPE samples have been investigated
using Positron Annihilation Lifetime Technique (PALT). These effects on the orthopositronium
(o-Ps) Lifetime t3, the free positron annihilation lifetime 2 t , the free-volume
hole size (Vh) and the free volume fraction (fh) were measured as functions of Beta
irradiation - dose up to a total dose of 30.28 kGy.
The results show that the values of t3, Vh and fh increase gradually with increasing Beta
dose up to a total dose of 1.289 kGy, and reach a maximum increment of 17.4%, 32.8% and
5.86%, respectively, while t2 reachs maximum increment of 211.9% at a total dose of 1.59
kGy. Above these doses, the values show nonlinear changes u

Presupposition is the background belief that is known by both the speaker and the addressee, it is tied to particular words and aspects of the surface structure that act as linguistic triggers. The present study aims at investigating whether Iraqi fourth -year university students are able to recognize the English presuppositions through the meaning of these linguistic triggers .To fulfil the basic requirements of the study, the researcher has conducted a test . The results of the study have validated the hypothesis of the work and it is found that the linguistic triggers are important tools in recognizing presuppositions.    

The measurements of major and trace elements in different brands of milk powder selected from the Iraqis market via the X-ray fluorescence (XRF) Technique have been studied in the present work. The result of the measurements reveals the high concentrations of sodium, phosphorus, sulfur, chlorine, potassium, calcium and magnesium. Furthermore, low concentrations of aluminum, silicon, iron, bromine, molybdenum, iodine, barium, titanium, manganese, cobalt, chrome, nickel, copper, zinc and lead were detected. Neutron activation analysis (NAA) and Kjeldahl technique were also employed to determine the concentrations of nitrogen. It was found that the nitrogen concentration was in the range of (1.96 - 3.23) % which is within the permissible li

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To