An experiment was carried out in the vegetables field of Horticulture Department / College of Agriculture / Baghdad University , for the three seasons : spring and Autumn of 2005 , and spring of 2007 , to study the type of gene action in some traits of yield and its components in summer squash crosses (4 x 3 = cross 1 , 3 x 7 = cross 2 , 3 x 4 = cross 3 , 3 x 5 = cross 4 , 5 x 1 = cross 5 , 5 x 2 = cross 6). The study followed generation mean analysis method which included to each cross (P1 , P2 , F1 , F2 , Bc1P1 , Bc1P2) , and those populations obtained by hybridization during the first and second seasons. Experimental comparison was performed in the second (Two crosses only) and third seasons , (four crosses) by using RCBD with three repl

The present study aimed to evaluate the effect of lead exposure on hemopoetic system (through the index delta-Aminolevulinic acid dehydratase ?-ALAD activity & hemoglobin concentration (Hb) ) and on iron status (levels of iron Fe, Ferritin Fr, Total iron binding capacity TIBC, percentage of transferine saturation TF%) in 44 Iraqi worker at lead batteries factory. Workers divided into two groups: smokers(n=21) mean aged (37.33±4.82 year)and non smokers(n=23) mean aged(40.78±7.89 year) and 45 healthy subjects mean aged (33.97±5.08)as control group . Activity of ?-ALAD ratio shows significant decrease (p ? 0.05) ,while Hb and hematocrit Hct were non significant (p ? 0.05) in smoker workers more than non smoker as compared to control . The r

Magnetic nanoparticles (MNPs) of iron oxide (Fe₃O₄) represent the most promising materials in many applications. MNPs have been synthesized by co-precipitation of ferric and ferrous ions in alkaline solution. Two methods of synthesis were conducted with different parameters, such as temperature (25 and 80 ̊C), adding a base to the reactants and the opposite process, and using nitrogen as an inert gas. The product of the first method (MNPs-1) and the second method (MNPs-2) were characterized by x-ray diffractometer (XRD), Zeta Potential, atomic force microscope (AFM) and scanning electron microscope (SEM). AFM results showed convergent particle size of (MNPs-1) and (MNPs-2) with (86.01) and (74.14)

The meteorite with a single total mass of 630 gm as a visible meteorite has fallen on 22 March 2021, at 10:00 a.m. in Al-Sherqat subdistrict within Salah Al-Din, northern Iraq; and therefore, was named Al-Sherqat meteorite by the authors. It is characterized by a uniform structure of coherent and medium degree of malleability. It is of a well-crystalline structure and not homogeneous in composition. The Al-Sherqat meteorite is composed of metallic phases of 7.6 gm/cm3 density exhibiting an oriented intergrowth of kamacite (α-FeNi) with taenite showing a Widmanstätten pattern on an etched polished section with the finest octahedrite kamacite bandwidth of less than 0.2 mm. It is composed of Fe (86.9 wt%), Ni (9.63 wt%), P (1.31 wt%)

new, simple and fast solid-phase extraction method for separation and preconcentration of trace theophylline in aqueous solutions was developed using magnetite nanoparticles (MIONPs) coated with aluminium oxide (AMIONPs) and modified with palmitate (P) as an extractor (P@AMIONPs). It has shown that the developed method has a fast absorbent rate of the theophylline at room temperature. The parameters that affect the absorbent of theophylline in the aqueous solutions have been investigated such as the amount of magnetite nanoparticle, pH, standing time and the volume, concentration of desorption solution. The linear range, limit of quantification (LOQ) and limit of detection (LOD) for the determination of theophylline were 0.05-2.450 μg mL-

In this research the performance of 5G mobile system is evaluated through the Ergodic capacity metric. Today, in an­­y wireless communication system, many parameters have a significant role on system performance. Three main parameters are of concern here; the source power, number of antennas, and transmitter-receiver distance. User equipment’s (UEs) with equal and non-equal powers are used to evaluate the system performance in addition to using different antenna techniques to demonstrate the differences between SISO, MIMO, and massive MIMO. Using two mobile stations (MS) with different distances from the base station (BS), resulted in showing how using massive MIMO system will improve the performance than the standar

    The goal of this research is to use optical emission spectroscopy to investigate the parameters of exploding silver wire plasma. The silver discharge plasma's emission spectra were recorded and studied. For silver wire of diameter 0.4 mm and different currents 75,100, and 125A in deionized water, the plasma electron temperature ( ) was calculated by Boltzmann plot and container plasma medium temperature by thermal camera, and the electron density ( ) was computed by Stark broadening using the hydrogen (H line) at 656.279 nm With increasing current from 75 to 125 A, the electron density (n_e) increased from 3.160×  to 8.762×   , while electron temperatures increased from 0.571 to 1.334 eV under the same conditions. 

The permeable reactive barrier (PRB) is one of the promising innovative in situ groundwater remediation technologies, in removing of copper from a contaminated shallow aquifer. The 1:1- mixture of waste foundry sand (WFS) and Kerbala’s sand (KS) was used for PRB. The WFS was represented the reactivity material while KS used to increase the permeability of PRB only. However, Fourier-transform infrared (FTIR) analysis proved that the carboxylic and alkyl halides groups are responsible for the sorption of copper onto WFS. Batch tests have been performed to characterize the equilibrium sorption properties of the (WFS+KS) mix in copper- containing aqueous
solutions. The sorption data for Cu+2 ions, obtained by batch experiments, have be

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod