Background: Dental implants act as infrastructure for fixed restoration to look like as a natural tooth. Osseointegration is a biological events and considered as a base for success of dental implant. The aim of this study is to evaluate the bond strength between bone and Ti implant coated with mixture of nano hydroxyapatite-chitosan-collagen compared with Ti implants coated with nano hydroxyapatite implanted in rabbit tibia, after different period of implantation time (two and six weeks) by torque removal test. Material and methods: 36 screws of commercially pure titanium; 8mm in length and 3mm diameter , 18 screws coated with mixture of nano hydroxyapatite-chitosan-collagen and18 screws coated with nano hydroxyapatite by dip coating. St

These deposits take many forms like current acc, deposits in order to growth and serve national economy Various in varicose perspectives .

The problem of this paper its concern with un applied the mathematical models that used in profitability analysis of current acc , and deposits in view of risk, profit efficiency and financial leverage for this reason the paper discussion use the cumulate mathematical model to solve these problem, that content three variables that be used to measuring profitability by consequent replacement method by stable base and by moving base for 2007 – 2009 applied the data collect from Iraq middle east bank.           &nbs

Diabetic mellitus is one of the main risk factors of fungal infections because poor glycemic control is associated with a high level of glucose in blood and saliva which could be treated as nutrient to fungi. This study aimed to isolate and identification of pathogenic fungi from diabetic patient. 140 samples were taken from different places of human body from the national center of diabetic patients that related to Mustansiriyah University / college of medicine and Al-yarmuk Hospital in Baghdad. 84 sample (60%) tested positive to fungi and 56 sample (40%) tested negative to fungi. The most frequented fungi isolated have been chosen for molecular identification by PCR (Millerozyma farinosa and Candida orthopsilosis) using specific pri

In this paper waste natural material (date seed) and polymer particles(UF) were used for investigation of  removal dye of the potassium permanganate. Also study effect some variables such as pH, dye concentration and adsorbent concentration on dye removal. 15 experimental runs were done using  the itemized conditions designed established on the Box-Wilson design employed to optimize dye removal. The optimum conditions for the dye removal were found: (pH) 12, (dye con.) 2.38 ppm, (adsorbant con.) 0.0816 gm for date seed with 95.22% removal and for UF (pH) 12, (dye con.) 18 ppm, (adsorbant con.) 0.2235 gm with 91.43%. The value of R-square was 85.47%  for Date seed  and (88.77%) for UF.

Industrial effluents loaded with heavy metals are a cause of hazards to the humans and other forms of life. Conventional approaches, such as electroplating, ion exchange, and membrane processes, are used for removal of copper, cadmium, and lead and are often cost prohibitive with low efficiency at low metal ion concentration. Biosorption can be considered as an option which has been proven as more efficient and economical for removing the mentioned metal ions. Biosorbents used are fungi, yeasts, oil palm shells, coir pith carbon, peanut husks, and olive pulp. Recently, low cost and natural products have also been researched as biosorbent. This paper presents an attempt of the potential use of Iraqi date pits and Al-Khriet (i.e. substances l

CuO-ZnO-Al2O3 catalyst was prepared in the ratios of 20:30:50 respectively, using the coprecipitation method of Cu, Zn and Al carbonates from their nitrate solutions dissolved in distilled water by adding sodium bicarbonate as precipitant.The catalyst was identified by XRD and quantitatively analysis to determine the percentages of its components using flame atomic absorption technique. Also the surface area was measured by BET method. The activity of this prepared catalyst was examined through the oxidation of ethanol to acetaldehyde which was evaluated by gas chromatography.

In this research, the results of x-ray diffraction method were used to determine the uniform stress deformation and microstructure parameters of CuO nanoparticles to determine the lattice strain obtained and crystallite size and then to compare the results obtained by two model Halder Wagner and Size Strain Plot with the results of these methods of the same powder using equations during which the calculation of the size of the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (19.81nm) and the lattice strain (0.004065) of the Halder-wagner model respectively and for the ssp method were the results of the crystallite size (17.20nm) and lattice strain (0.000305) respectively. The sa

In this work copper nanopowder was created at different liquid
medias like DDDW, ethylene glycol and Polyvinylpyrrolidone
(PVP). Copper nanopowder prepared using explosion wire process
and investigated the effects of the exploding energy, wire diameter,
the type of liquid on the particle size, and the particles size
distribution. The nanoparticles are characterized by x-ray diffraction,
UV-visible absorption spectroscopy and transmission electron
microscopy (TEM). The x-ray diffraction results reveal that the
nanoparticles continue to routine lattice periodicity at reduced
particle size. The UV-Visible absorption spectrum of liquid solution
for copper nanoparticles shows sharp and single surface Plasmon
r

Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti