Background: Patients requiring renal biopsies have various glomerular diseases according to their demographic characteristics.
Objective: To study types of glomerular disease among adult Iraqi patients in a single center in Baghdad/Iraq
Material and Methods: A total of 120 native kidney biopsies were studied. All biopsies were adequate and were processed for Light Microscopy.
The age range of the study patients was 17-67 years, with a mean of 38.5 years. The mean follow up period was 28 weeks (4-52 weeks)
Indication for biopsy included: Nephrotic syndrome (N=72; 60%), Asymptomatic proteinuria (N=21; 17.5%), acute nephritic presentation (N=17; 14.16%), asymptomatic haematuria (N=10; 8.33%).
Results: Primary glomerulonephrit

Continuous escalation of the cost of generating energy is preceded by the fact of scary depletion of the energy reserve of the fossil fuels and pollution of the environment as developed and developing countries burn these fuels. To meet the challenge of the impending energy crisis, renewable energy has been growing rapidly in the last decade. Among the renewable energy sources, solar energy is the most extensively available energy, has the least effect on the environment, and is very efficient in terms of energy conversion. Thus, solar energy has become one of the preferred sources of renewable energy. Flat-plate solar collectors are one of the extensively-used and well-known types of solar collectors. However, the effectiveness of the coll

In this study, we focused on the random coefficient estimation of the general regression and Swamy models of panel data. By using this type of data, the data give a better chance of obtaining a better method and better indicators. Entropy's methods have been used to estimate random coefficients for the general regression and Swamy of the panel data which were presented in two ways: the first represents the maximum dual Entropy and the second is general maximum Entropy in which a comparison between them have been done by using simulation to choose the optimal methods.

The results have been compared by using mean squares error and mean absolute percentage error to different cases in term of correlation valu

The study is carried out by using personal dosimeters (film badge). The films are irradiated to absorbed dose of range (0.01-10000 rad). The calibration curves are drawn by using the ordinary method taking into account the filtration effects in three regions (D (Pb/Sn),D(Du),D(300). The calibration films are stored in ambient condition. It is found that the optical density increases, which is attributed to the photodegradation of the films may induce localized states in the energy gap causing increasing in optical absorption, but optical density decreases, which attributed to the photodegradation of the films may cause some cracks at the film surface during the first month, whereas at the rest months we see clear stability in optical d

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Many oil and gas processes, including oil recovery, oil transportation, and petroleum processing, are negatively impacted by the precipitation and deposition of asphaltene. Screening methods for determining the stability of asphaltenes in crude oil have been developed due to the high cost of remediating asphaltene deposition in crude oil production and processing. The colloidal instability index, the Asphaltene-resin ratio, the De Boer plot, and the modified colloidal instability index were used to predict the stability of asphaltene in crude oil in this study. The screening approaches were investigated in detail, as done for the experimental results obtained from them. The factors regulating the asphaltene precipitation are different fr