Two field experiments were conducted during the spring season 2020 in Karbala governorate to study the effect of irrigation systems, irrigation intervals, biofertilizers and polymers on some characteristics of vegetative growth and potato production. The results showed that there were significant differences in the values of the average plant height due to the effect of the double interference between the irrigation system and the improvers, The height of potato plant under any irrigation system was superior when adding conditioners compared to the control treatment, as it reached 48.56, 58.00 and 64.33cm when adding polymer, biofertilizer, and polymers+ biofertilizers, respectively compared with the control treatment of 44.64cm in the surf

Background: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized

Hepatitis C virus (HCV) is a liver disease that affects14 million people. Feasible research was conducted for identifying the genotypes and allele frequency of some single nucleotide polymorphisms (SNPs) of the IL-28β genes and their predictive role in disease incidence in Iraqi patients. The SNPs (rs28416813, rs4803219, rs11881222, and rs8103142) of IL-28β have been associated with susceptibility to several diseases. Ninety eight (98) HCV patients were included in this research; with average age ± SE (42.28 ± 3.44) years. Also, 80 healthy people (with average age ± SE (29.40 ± 2.84) years) were included as a control group. The SNPs were detected by allele-specific PCR (polymerase chain reaction) using specific primers. The re

Direct determination of trace metals Zn, Mn, Cu and Co were performed in serum
blood samples of two groups diabetic patient type 2 and non diabetes by ICP spectrometric
method. Results show the low levels of these elements Zn, Mn and Co while high level of Cu
detected compared with non diabetes according to these results good evidence can be made to
control these levels through a special diet containing these metals.

      The present study stresses two of the most significant aspects of linguistic approach: Pragmatics” and the “Speech Act Theory”, revealing its importance and the stages and levels of development through Hebrew language’s speech acts analysis including (political speech, the Holy Bible, Hebrew stories).

       Chronologically, Pragmatics has always been the center of linguists’ interests due to its importance in linguistic decryptions, particularly, through “Speech Act Theory” that has been initiated and developed by the most prominent philosophers and linguistics.

        The prese

A phytoremediation experiment was carried out with kerosene as a model for total petroleum hydrocarbons. A constructed wetland of barley was exposed to kerosene pollutants at varying concentrations (1, 2, and 3% v/v) in a subsurface flow (SSF) system. After a period of 42 days of exposure, it was found that the average ability to eliminate kerosene ranged from 56.5% to 61.2%, with the highest removal obtained at a kerosene concentration of 1% v/v. The analysis of kerosene at varying initial concentrations allowed the kinetics of kerosene to be fitted with the Grau model, which was closer than that with the zero order, first order, or second order kinetic models. The experimental study showed that the barley plant designed in a subsu

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F