Objective: to assess the predictive value of Doppler imaging of the uterine artery in the identification of early intrauterine abnormal pregnancy as compared to a normal intrauterine pregnancy.

Subjects and methods: one hundred and twenty pregnant ladies, at their 6-12 weeks of gestation, with a singleton pregnancy were included in this population-based case-control study. Thirty women with a missed miscarriage, 30 with hydatidiform mole, 30 with a blighted ovum, and 30 as a control group, without risk factors, underwent Doppler interrogation of the uterine arteries. Resistive index (RI), pulsatility index (PI), and the systolic/diastolic ratio (S/D) were measured for both sides. The t-test, or ANOVA test when a

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

The behavior of AC conductivity (σ_ac), loss tangent (tan δ), and relative permittivity (ε′) for composites of PVC-P/graphite electrode waste (GEW) was investigated, and a qualitative explanation was provided as a function of PVC-P weight fractions (0, 5, 10, 15, 20, and 25) wt. percent, temperature (30-90) °C, and frequency (100Hz-2MHz). The behaviors of the composites' ac. conductivity and impedance as a frequency function and temperature have been examined. The permittivity was shown to rise with increasing temperature (Tg). The relative permittivity increased as the GEW filler concentration increased and was highest in the low-frequency range; nevertheless decreased as the frequency increased.

                The electrical characteristics of polyvinyl alcohol PVA doped with different concentrations (0, 1, 2, 3 and 4wt%) of sodium  iodide NaI powder were studied. The films are prepared using solution casting technique, in order to investigate the effect of sodium iodide NaI additions on the electrical properties of PVA host. The D.C conductivity measured by measuring the D.C electrical resistance using the Keithly Electrometer type 616C, and for different temperatures ranging from 30 – 70^oC.

          The dielectric properties measured by measuring the capacitor and the loss

This search study the effect of particle size of graphite on the mechanical and thermal properties of epoxy composites, where graphite adopted with particle sizes (45,53,75) ?m, respectively, and the percentages by weight (0,1,3,5,7,9)% for each size of this three particle sizes.Mechanical properties represented by the bending (three-point bending) and through which the conclusion is bending stress and modulus of elasticity, thermal properties were either through thermal conductivity tests.The results showed that the ratio(1%) is the maximum value of bending stress at the three particle size and the (45 ?m) is the maximum.Thermal conductivity result show is the maximum value at ratio (1%) of particle size(53 ?m)

This work illustrates an enhanced visible light photocatalytic degradation of methyl orange dye (M.O.) by employing BiOI / BiOCl composites prepared under room temperature and without any organic precursors. Various experimental parameters have been studied, namely; composition of the composite, irradiation time and cell material. Composition D which implied 75% BiOI and 25% BiOCl has shown the highest bleaching of M.O. dye. This confirms the optimum photo-sensitization phenomenon for this composition in comparison to others. In the optimum photo-sensitized composite the electron of the conduction band reveals better reducing power and the hole of the valence band exhibits more oxidative power than those of pure BiOI electron and hole. Acco

The study is devoted to both static and earthquake response analysis of retaining structures acted upon by lateral earth pressure. Two main approaches were implemented in the analysis, namely, the Mononobe-Okabe analytical method and the numerical Finite element procedure as provided in the ready software ABAQUS with explicit dynamic method. A basic case study considered in the present work is the bridge approach retaining walls as a part of AL-Jadiriya bridge intersection to obtain the effects of the backfill and the ground water on the retaining wall response including displacement of the retaining structure in addition to the behavior of the fill material. Parametric studies were carried out to evaluate the effects of several factors

 The permeability determination in the reservoirs that are anisotropic and heterogeneous is a complicated problem due to the limited number of wells that contain core samples and well test data. This paper presents hydraulic flow units and flow zone indicator for predicting permeability of rock mass from core for Nahr-Umr reservoir/ Subba field. The Permeability measurement is better found in the laboratory work on the cored rock that taken from the formation. Nahr-Umr Formation is the main lower cretaceous sandstone reservoir in southern of Iraq. This formation is made up mainly of sandstone. Nahr-Umr formation was deposited on a gradually rising basin floor. The digenesis of Nahr-Umr sediments is very important du

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed