In this study the prevalence of acute, sub-acute and chronic toxoplasmosis were monitored in a group of Iraqi pregnant women according to the anti-T.gondii antibodies (IgG and IgM), as well as the levels of both progesterone and estrogen hormones were measured using mini-VIDAS®technique. This study demonstrated that there was high prevalence of chronic toxoplasmosis (31.70%) when it compared with acute and sub-acute type, results also showed that the acute toxoplasmosis always related with low concentration of both progesterone and estrogen which were (5.35 ± 7.15 ng/ml) and (70.66 ± 51.08 pg/ml) respectively

Background: Hypothyroidism is a clinical syndrome prevalent in women, even those of reproductive age. Ovarian reserve can be defined as the number and quality of follicles in the ovary at any given time. Evaluation of ovarian reserve is recommended for patients at risk of decreased ovarian reserve. Objective: This study aims to evaluate the effect of hypothyroidism on ovarian reserve in Iraqi women by hormonal measurements of serum anti-mullerian hormones AMH, FSH, and LH. Subjects and methods: This case–control study was carried out at the Department of Biochemistry, College of Medicine, University of Baghdad, in collaboration with Endocrinology and Diabetes Clinic, Baghdad Teaching Hospital, and National Center for Teaching Labo

In this paper,we focus on the investigated and studied of transition rate in metal/organic semiconductor interface due to quantum postulate and continuum transition theory. A theoretical  model has been used to estimate  the transition rate cross the interface through estimation many parameters such that ;transition energy  ,driving electronic energy U(eV) ,Potential barrier ,electronic coupling  ,semiconductor volume ,density ,metal work function ,electronic affinity and temperature T. The transition energy  is critical facter of charge transfer through the interfaces of metal organic films device and itscontrol of charge injection and transport cross interface. However,the potential at interfa

This article aim to estimate the Return Stock Rate of the private banking sector, with two banks, by adopting a Partial Linear Model based on the Arbitrage Pricing Model (APT) theory, using Wavelet and Kernel Smoothers. The results have proved that the wavelet method is the best. Also, the results of the market portfolio impact and inflation rate have proved an adversely effectiveness on the rate of return, and direct impact of the money supply.

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

The holmium plasma induced by a 1064-nmQ-switched Nd:YAG laser in air was investigated. This work was done theoretically and experimentally.  Cowan code was used to get the emission spectra for different transition of the holmium target. In the experimental work, the evolution of the plasma was studied by acquiring spectral images at different laser pulse energies (600,650,700, 750, and 800 mJ). The repetition rates of (1Hz and 10Hz) in the UV region (200-400 nm). The results indicate that, the emission line intensities increase with increasing of the laser pulse energy and repetition rate. The strongest emission spectra appeared when the laser pulse energy is 800mJ and 10 Hz repetition rate at λ= 345.64nm, with the maximum intensi

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

In this study, nanocomposites have been prepared by adding
multiwall carbon nanotubes (MWCNTs) with weight ratios (0, 2, 3,
4, 5) wt% to epoxy resin. The samples were prepared by hand lay-up
method. Influence of an applied load before and after immersion in
sodium hydroxide (NaOH) of normality (0.3N) for (15 days) at
laboratory temperature on wear rate of Ep/MWCNTs
nanocomposites was studied. The results showed that wear rate
increases with increasing the applied load for the as prepared and
immersed samples and after immersion. It was also found that epoxy
resin reinforced with MWCNTs has wear rate less than neat epoxy.
The sample (Ep + 5wt% of MWCNTs) has lower wear rate. The
immersion effect in base so

Bilastine (BLS) is non-sedating new-brand H1 antihistamine that has selective peripheral effects, the drug has a problem of an insufficient aqueous solubility and accordingly low dissolution rate, and low bioavailability. Solid dispersion (SD) is one of the most effective techniques for improving the solubility and the dissolution rate of poorly soluble drugs by the dispersion of drug within an inert hydrophilic carrier.   The aim of this study is to increase the solubility and dissolution rate of the BLS using SD technique. Twenty-nine BLS SD formulas were prepared using different carrier polymers include Pluronic 407 (Poloxamer407), Poloxamer188, Urea, Polyethylene glycol 6000 (PEG6000) and Polyvinylpyrrolidone (PVP K30) and em

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T