In this study, we introduce new a nanocomposite of functionalize graphene oxide FGO and functionalize multi wall carbon nanotube (F-MWCNT-FGO).The formation of nanocomposite was confirmed by FT-IR ,XRD and SEM. The magnitude of the dielectric permittivity of the (F-MWCNT-FGO) nanocomposite appears to be very high in the low frequency range and show a unique negative permittivity at frequencies range from 400 Hz to 4000Hz. The ac conductivity of nanocomposite reaches 23.8 S.m-1 at 100Hz.

In this research, the kinetic studies of four isoenzymes of Asprtate aminotransferase, which partially purified from the urine of chronic renal failure patients were carried out .The four isoenzymes were obeyed Michaelis-Menton's equation and the optimum concentration of their substrate (Aspartic acid) was (166.5x10-3) mole/liter,and their Km values were determined. Four isoenzymesI,II,III,IV have shown an optimum pH at 7.4.The four isoenzymes obeyed Arrhenius equation up to 37º C and their Ea and Q10 constants were determined .

This study was conducted to detect the relationship between organic content in the sediment of Rivers Tigris and Diyala, at two locations south of Baghdad, with some environmental factors and the benthic invertebrates and values of diversity indices. Monthly samples collected from the area for the period November 2007 to October 2008. Results showed differences in the physical and chemical characteristics of the two sites, Where the annual average in Tigris and Diyala were respectively for: water temperature (19, 20) C°, pH (8, 8), dissolved oxygen (4, 8) mg / l , Biochemical oxygen Demand BOD5 (3,44 ) mg/l, TDS (632,1585) mg / l, TSS (42, 44) mg / l, turbidity (28,74) NTU, and total hardness as CaCO3 (485,823) mg / l ,Sulfat

The current study aimed to assess the biological efficacy of the triple arbuscular mycorrhiza (AM) mixture of fungi Glomus etunicatum, G. leptotichum and Rhizophagus intraradices, and mix it with organic matter (O) and pathogenic fungi Fusarium oxysporum f.sp.lycopersici by using voyeurism in the plastic house in the growth of the tomato plant after four and eight weeks of cultivation. The results were shown after the treatment of the tomato plant in agriculture with the mixture of mycorrhiza and the pathogenic fungi and organic matter were treated with the mixture of mycorrhiza, organic matter and pathogenic fungi together. The effect of mycorrhiza and organic matter interference on the increase in the percentage of the lignin afte

Yeasts are distributed in all environments and have been reported as potential biocontrol agents against various phytopathogenic fungi. To investigate their enzymatic and biological activities, 32 yeasts were isolated from 15 date vinegar samples. Evaluation of the antagonistic activities of isolated yeasts against the plant pathogens Fusarium oxysporium, Sclerotinia sclerotiorum, and Macrophomina phaseolina indicated that there are two yeasts had the highest inhibitory effect against plant pathogens, these yeasts identified as Kluyveromyces marxianus and Torulaspora delbrueckii using traditional and molecular methods. These yeast isolates were tested for fungal cell wall degrading enzymes (in vitro), and results indicated that the

            The increase in population resulted in an increase in the consumption of water. The present work investigates the performance of a recycling solar- powered greywater treatment system for the purposes of irrigation, used to reduce the amount of waste grey water and reduce electricity consumption and reduce the costs of constructing large scale water treatment plants. The system consumes about 3814W per hour and provides water treatment about 1.4 m³ per day. The proposed system is designed to    residential, office and governmental buildings application. Tests are conducted in an office building at the Ministry of Science and Technology site in Baghdad. Laboratorial water samples testing analyses are co

The term of heterocyclic chemistry focuses only on heterocyclic compounds, which consider as a percentage of organic chemistry, they equal to greater than sixty-five. These compounds are widely founded in nature and most of them are important to life. In the past few years, scientist fused on 1,2,4-triazoles and their condensed heterocyclic ring due to their medicinal significance, 1,2,4-triazole containing Sulphur atom is one of the important heterocyclic moieties due to its broad range of biological activities also their derivatives can accommodate one of the alternatives as electronic effect as exchanges of the electronic density (electron donating or withdrawing) groups ; for all what mentioned above they are consider as a core

Background: Hyperthyroidism refers to overactive of thyroid gland leading to excessive synthesis of thyroid hormones and accelerated metabolism in the peripheral tissue. Objective: The aim of this study is to evaluate a new member of the IL-1 super family of cytokines interleukin-33(IL-33) levels in serum .in order to evaluate its utility as clinical bio marker of autoimmune disease (i.e. hyperthyroidism) Methods: The present study was conducted on 30 patients from the Iraqi female patients with hyperthyroidism attending Baghdad teaching hospital, in addition to 30 healthy controls. All subjects were (35-65) years old. Parameters measured in the sera of patients and healthy groups, were interleukin -33 (IL-33), Thyroxin (T4), Thyroxin (T3)

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class