One of the main environmental problems which affect extensively the areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Landsat satellite (TM & ETM+) images have been analyzed to study soil pollution (Exacerbation of salinity in the soil without the use of abandoned agricultural for a long time) at west of Baghdad city of Iraqi country for the years 1990, 2001 & 2007. All of the th

Background: Human semen contains high concentrations of fructose, zinc (Zn) and copper (Cu) in bound and ionic forms for Zn and Cu. The presence of abnormal levels of fructose and those trace elements may affect spermatogenesis with regard to production, maturation, motility and fertilizing capacity of the spermatozoa.Objective: To evaluate the levels of fructose, Zn and Cu in seminal plasma in different groups of male infertility and to correlate their concentrations with various sperm parameters.Methods: The concentrations of fructose, Zn and Cu were measured in 114 semen samples from normozoospermic, oligozoospermic, astheno-zoospermic, and azoospermic men using the electrothermal-atomic absorption spectrometry for Zn and Cu determinatio

Highly-fluorescent Carbon Quantum Dots (CQDs) are synthesized in simple step by hydrothermal carbonization method of natural precursor such as orange juice as a carbon source. Hydrothermal method for synthesized CQDs requires simple and inexpensive equipment and raw materials, thus this method are now common synthesis method. The prepared CQDs have ultrafine size up to few nanometers and   several features such as high solubility in water, low toxicity, high biocompatibility, photo-bleaching resistant, Chemical inertness and ease of functionalization which qualifies it for use in many applications such as bio-imaging, photo-labeling and photo-catalysis.

       This research demonstrates the

Pure grade II titanium disks were coated with a thin coating of polyetherketoneketone (PEKK) polymer by RF magnetron sputtering using either nitrogen or argon gas. Sputtering technique was employed at 50 W for one hour at 60°C with continuous flow of nitrogen or argon gas. Field-emission scanning electron microscopy (FE-SEM) showed a continuous, homogeneous, rough PEKK surface coating without cracks. In addition, cross-sectional FE-SEM revealed an average coat thickness of 1.86 μm with argon gas and 1.96 μm with nitrogen gas. There was homogenous adhesion between the coating layer and substrate. The elemental analysis of titanium substrate revealed the presence of carbon, titanium, and oxygen. The RF magnetron sputtering with argon or ni

Polycrystalline Cadmium Oxide (CdO) thin films were prepared
using pulsed laser deposition onto glass substrates at room
temperature with different thicknesses of (300, 350 and 400)nm,
these films were irradiated with cesium-137(Cs-137) radiation. The
thickness and irradiation effects on structural and optical properties
were studied. It is observed by XRD results that films are
polycrystalline before and after irradiation, with cubic structure and
show preferential growth along (111) and (200) directions. The
crystallite sizes increases with increasing of thickness, and decreases
with gamma radiation, which are found to be within the range
(23.84-4.52) nm and (41.44-4.974)nm before and after irradiation for

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s