BACKGROUND: Sickle cell nephropathy, a heterogeneous group of renal abnormalities resulting from complex interactions of sickle cell disease (SCD)-related factors and non-SCD phenotype characteristics, is associated with an increased risk for morbidity and mortality. AIMS: The aims of this study were to determine the frequency of microalbuminuria (MA) among pediatric patients with SCD and to determine risk factors for MA among those patients. SUBJECTS AND METHODS: A case–control study was carried out on 120 patients with SCD, 2–18 years old, registered at Basrah Center for Hereditary Blood Diseases, and 132 age-and sex-matched healthy children were included as a control group. Investigations included complete blood panel, blood urea, se

Atherosclerotic cardiovascular disease (ACVD) is an inflammatory disease of the coronary arteries associated with atheroma formation, which can cause disability and often death. Periodontitis is ranked as the sixth most prevalent disease affecting humans affecting 740 million people worldwide. In the last few decades, researchers have focused on the effect of periodontal disease (PD) on cardiovascular disease. The aim of this review was to investigate the association between these two diseases. PD is a potential risk factor that may initiate the development, maturation, and instability of atheroma in the arteries. Two mechanisms were proposed to explain such association, either periodontal pathogens directly invade bloodstream or in

Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of t

This paper  deals  to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th