Background: Chronic myelogenous leukemia is a malignant hematological disease of hematopoietic stem cells. It is difficult to adapt treatment to each patient's risk level because there are currently few clinical tests and no molecular diagnostics that may predict a patient's clock for the advancement of CML at the time of chronic phase diagnosis. Biomarkers that can differentiate people based on the outcome at diagnosis are needed for blast crisis prevention and response improvement. Objective: This study is an effort to exploit the SLC25A3 gene as a potential biomarker for CML. Methods: RT-qPCR was applied to assess the expression levels of the SLC25A3 gene. Results: In comparison to the mean ΔCt of the control group, which was found to b

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

Objective: The evaluation of serum osteocalcin (OSN) for Iraqi infertile patients to see the effect of osteocalcin insufficiency, which may lead to a decreased level of testosterone production in males that may cause infertility. Methods: Forty two newly diagnosed infertile males age range (24–47) years and thirty two apparently healthy males as controls age range (25–58) years. Serum levels of testosterone (TEST), stimulating follicle hormone (FSH) and luteinizing hormone (LH), prolactin (PROL), osteocalcin OSN, and fasting blood sugar (FBS) were performed in both patients and controls. Estimation of serum OSN by Immulite1000 auto-analyzer, TEST, FSH, LH, PROL, and FBS by Immulite2000 auto-analyzer. Results: Infertile patients

A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

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.

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha