The present study aims to evaluate the effects of methotrexate (MTX) with and without vitamin A (Vit. A) on some biochemical parameters and histological structure in male rabbits liver. Twenty male rabbits weighing 1250-1480 gm were divided into four equal number groups. The first group was given 2 ml distilled water as control group. The second group was given MTX (20 mg/kg), the third group was given Vit. A (5000 IU), while the fourth group was given MTX (20 mg/kg) +Vit. A (5000 IU) in alternative days. Following four weeks of treatment, lipid profile total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL), [low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL)]; in addition to thyroid hormones tr

The present work aims to study the efficiency of coagulation/ flocculation as 1st stage, natural gravity water filter or microfiltration (MF) as 2nd stage and nanofiltration (NF) technology as final stage for treatment of water of main outfall drain (MOD) for injection in Nasiriyah oil field. Effects of operating parameters such as coagulant dosage, speed and time of slow mixing step and settling time in the 1st stage were studied. Also feed turbidity and total suspended solids (TSS) in the 2

A field experiment was carried out during the spring season 2019 and 2020 to obtain a fast, uniform, and high field emergence ratio of maize seeds under a wide range of environmental conditions. Randomize complete block design in the split-plot arrangement was used with three replications. The first factor in the main plots was cultivars (5018, Baghdad3 and Sumer). The second factor in the sub-plots was seeds soaking with ascorbic and citric acids (100 mg L−1) each and humic (1 ml L−1) in addition to control treatment (seeds soaking with distilled water only). Results showed the superiority of soaking with humic acid significantly, as means of characteristics of field emergence in both seasons, respectively, were as follows: Last day of

The estimation of the initial oil in place is a crucial topic in the period of exploration, appraisal, and development of the reservoir. In the current work, two conventional methods were used to determine the Initial Oil in Place. These two methods are a volumetric method and a reservoir simulation method. Moreover, each method requires a type of data whereet al the volumetric method depends on geological, core, well log and petrophysical properties data while the reservoir simulation method also needs capillary pressure versus water saturation, fluid production and static pressure data for all active wells at the Mishrif reservoir. The petrophysical properties for the studied reservoir is calculated using neural network technique

This paper presents a point multiplication processor over the binary field GF (2²³³) with internal registers integrated within the point-addition architecture to enhance the Performance Index (PI) of scalar multiplication. The proposed design uses one of two types of finite field multipliers, either the Montgomery multiplier or the interleaved multiplier supported by the additional layer of internal registers. Lopez Dahab coordinates are used for the computation of point multiplication on Koblitz Curve (K-233bit). In contrast, the metric used for comparison of the implementations of the design on different types of FPGA platforms is the Performance Index.

The first approach attains a performance index

Human identification is crucial in forensics for the investigation of large-scale disasters such as fires, epidemics, earthquakes, and tsunamis. Even though biometric identification using panoramic dental radiography (PDR) has been the subject of several studies in the literature, further study remains a necessary and challenging issue. In this research, a human identification system was developed based on a convolutional neural network (CNN) and contour transform (CT). The proposed system was implemented on a total of 1540 PDR from 302 individuals. The preprocessing applied to PDRs for enhancing and taking the Region of Interest (ROI). The features were extracted using CT transform. These features were fused with features extracted

 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat