Abstract:          

                Interest in the topic of prediction has increased in recent years and appeared modern methods such as Artificial Neural Networks models, if these methods are able to learn and adapt self with any model, and does not require assumptions on the nature of the time series. On the other hand, the methods currently used to predict the classic method such as Box-Jenkins may be difficult to diagnose chain and modeling because they assume strict conditions.

The influence of silver doped n-type polycrystalline CdTe film with thickness of 200 nm and rate deposition of 0.3 nm.s -1 prepared under high vacuum using thermal co-evaporation technique on its some structural and electrical properties was reported. The X- ray analysis showed that all samples are polycrystalline and have the cubic zinc blend structure with preferential orientation in the [111] direction. Films doping with impurity percentages (2, 3, and 4) %Ag lead to a significant increase in the carrier concentration, so it is found to change from 23.493 108 cm -3 to 59.297 108 cm -3 for pure and doped CdTe thin films with 4%Ag respectively. But films doping with impurity percentages above lead to a significant decrease in the electrica

This research is concerned with the re-analysis of optical data (the imaginary part of the dielectric function as a function of photon energy E) of a-Si:H films prepared by Jackson et al. and Ferlauto et al. through using nonlinear regression fitting we estimated the optical energy gap and the deviation from the Tauc model by considering the parameter of energy photon-dependence of the momentum matrix element of the p as a free parameter by assuming that density of states distribution to be a square root function. It is observed for films prepared by Jackson et al. that the value of the parameter p for the photon energy range is is close to the value assumed by the Cody model and the optical gap energy is which is also close to the value

This work presents an experimental study of heat transfer and flow of distilled water and metal oxide nanofluid Fe₃O₄-distilled water at concentrations of (φ = 0.3, 0.6, 0.9 %) by volume in a horizontal pipe with constant magnetic field. All the tests are carried out with Reynolds number range (2900-9820) and uniform heat flux (11262-19562 W/m²). The results show that, the nanofluid concentration and magnetic intensity increase, the Nusselt number increases. The maximum enhancement in Nusselt number with magnetic nanofluid is (5.4 %, 26.4 %, 42.7 %) for volume concentration (0.3, 0.6, 0.9 %) respectively. The enhancement is maximized with magnetic intensity (0.1, 0.2, 0.3 tesla) respectively to (43.9, 44

The aim of this study is to identify the effect of particle size and to increase the concentration of Iraqi bentonite on rheological properties in order to evaluate its performance and to know if it can be used as drilling fluid without additives or not. In this study, Iraqi bentonite was carried out by mineral composition (XRD), chemical composition (XRF) and Particle size distribution (PSD), and its rheological properties were measured at different particle size and concentration. The results showed that when the particle size of Iraqi bentonite decreased, and the rheological properties were increased with increased concentration of Iraqi bentonite. Also, Iraqi bentonite was unable to use as drilling fluid without certain additives.

The aim of study is to identify the histological changes in ovaries of the albino mice exposed to silver nanoparticles. Sixty adult females were collected and exposures by 4000 p.p.m. and 50-150 nm in size, Females were divided into 3treated groups. The concentration dosage was (1, 1.5 and 2) p.p.m. of silver nanoparticles for 7, 14 and 21 days as exposure periods as well as control group which treated by normal saline. Treated groups appeared different histopathological changes, it is depending on the concentration of silver nanoparticles and the period of exposure. These changes were included congestion in the blood vessels, hemorrhage, hyaline degeneration, fatty degeneration, pyknosis, necrosis as well as fusion of cells in follicula