Objectives: The study intends to identify the sources of work-related stress that might face the nurses working at
psychiatric wards in Baghdad psychiatric hospitals and to find out a relationship between the levels of stress and
some demographic characteristics.
Methodology: A descriptive study was achieved from the 10th of December, 2013 through the 10th of March, 2014.
Non-probability purposive samples of 94 nurses who work in psychiatric wards of Baghdad psychiatric hospitals
were recruited to meet the study objectives. Psychological Stress Inventory (PSI) the Arabic version, which was
modified by Abu Al-Hussein (2010) (20), was used. Data were analyzed by using the statistical analysis program of
SPSS 19th versi

Evaporation is one of the major components of the hydrological cycle in the nature, thus its accurate estimation is so important in the planning and management of the irrigation practices and to assess water availability and requirements. The aim of this study is to investigate the ability of fuzzy inference system for estimating monthly pan evaporation form meteorological data. The study has been carried out depending on 261 monthly measurements of each of temperature (T), relative humidity (RH), and wind speed (W) which have been available in Emara meteorological station, southern Iraq. Three different fuzzy models comprising various combinations of monthly climatic variables (temperature, wind speed, and relative humidity) were developed

     Biosurfactants have a wide-range of applications due to their unique properties like specificity, not toxicity (from LAB) and relative ease of preparation. These properties hold promise of biosurfactants to increase breast milk benefit were isolated and described into Lactobacillus plantarum, Lactobacillus fermentum ,Lactococcuslactis, and Leuconostocmesenteroides.The degree of microbial destruction of disease, which promotes  the effective remediation of disease spreading.This paper presents a review of available research, methods and publications regarding Biosurfactant extraction from Lactic Acid bacteria isolated from human breast milk. 3 samples of human breast milk was provid

The purpose of this study to synthesize and characterize silver nanoparticles using phenolic compounds obtained from Camellia sinensis, to test the antibacterial properties of biosynthesized nanoparticles on the formation of biofilms in multidrug-resistant Pseudomonas aeruginosa. Ten isolates of P. aeruginosa were obtained from the Genetic Engineering and Biotechnology Institute laboratories of the University of Baghdad. By using the VITEK-2 system and culturing the isolates on cetrimide agar, the diagnosis was confirmed. Camellia sinensis silver nanoparticles (CAgNPs) were created using an extract of the plant's aqueous and methanolic leaves. Based on the results of the nanoparticle synthesis, spherical nanoparticles that may be single or

Surface Plasmon Resonance (SPR)-based plastic optical fiber sensor for estimating the concentration and refractive index of sugar in human blood serum. The sensor is fabricated by a small part (10mm) of optical fiber in the middle is embedded in a resin block and then the polishing process is done, after that it is deposited with about (40nm) thickness of gold metal. The blood serum is placed on gold coated core of an Optical grade plastic optical fiber of 980 µm core diameter.

The aim of this research is to determine the uranium concentration in soil and water samples taken from different locations from the middle and south of Iraq using fission fragments track registration. Twelve samples of soil and water were taken from middle and South of Iraq. The nuclear reaction used as a source of nuclear fission fragments is U-235 (n.f) obtained by bombardment U-235with thermal neutrons from (Am-Be) neutron source with flux (5X103 n.cm-2.s-1). The concentration values were calculated by a comparison with standard samples recommended by IAEA.The results of the measurements show that the uranium concentration in soil samples were in Thekar (16.38 ppm), AL-Basra (16.1ppm) and (0.78 ppm) in Baghdad, from the results

It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i