This study was conducted in order to statement the effect of ginger (Zingiber officinale) extracts in reducing the presence of the bacterium Salmonella typhimurium in some foods products.
Qualitative disclosures effective chemical compounds (alkaloids, flavonoids, phenols, tannins, terpenes) showed that the extracts of ginger an effective compounds as follows: oil extract and fresh juice> aqueous extract warm> aqueous extract cold. And studied the impact extract of fresh ginger juice, hot water ,cold water and oil rates extracts (1,2,3)% in bacteria test has shown that all s of extracts clear impact inhibition has oily extract of ginger recorded the highest value to inhibition zone reaching 35 mm when the concentration of 3%, f

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

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

In this paper, the reliability and scheduling of maintenance of some medical devices were estimated by one variable, the time variable (failure times) on the assumption that the time variable for all devices has the same distribution as (Weibull distribution.

The method of estimating the distribution parameters for each device was the OLS method.

The main objective of this research is to determine the optimal time for preventive maintenance of medical devices. Two methods were adopted to estimate the optimal time of preventive maintenance. The first method depends on the maintenance schedule by relying on information on the cost of maintenance and the cost of stopping work and acc

This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

Multiple single-nucleotide polymorphisms (SNPs) located in the intergenic region between estrogen receptor 1 and CCDC170 (especially at rs3757318) are thought to be associated with breast cancer risk. additionally, the serum level of vitamin D is believed to be linked to different aspects of breast carcinogenesis.

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

Toxoplasmosis is regarded as one of the most important global life-threatening diseases in immune-compromised people. The intracellular protozoon Toxoplasma gondii is the causative pathogen of toxoplasmosis. Aim of this study is to investigate the possible association between T. gondii infection and breast cancer (BC) in Iraqi women, also to assess the effect of T. gondiion interleukin 10 (IL-10) of the immune response. By ELISA method, blood samples from 81 women with breast cancer and 60 apparently healthy women have been examined for presence of anti-toxoplasmaantibodies, also the levels of serum IL-10 were estimated in these subjects. Results showed that women with BC had the highest prevalence rate of toxoplasmosis. The anti- T.gondii

الخلفية: إن سمية الدواء والآثار الجانبية للعلاج الكيميائي تؤثر سلبا على مرضى سرطان الثدي. الأهداف: لتقييم فعالية التدخلات الصيدلانية في تحسين معرفة مرضى سرطان الثدي ومواقفهم وممارساتهم فيما يتعلق بالعلاج الكيميائي لسرطان الثدي.

Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete