The possibility of using zero-valent iron as permeable reactive barrier in removing lead from a contaminated groundwater was investigated. In the batch tests, the effects of many parameters such as contact time between adsorbate and adsorbent (0-240 min), initial pH of the solution (4-8), sorbent dosage (1-12 g/100 mL), initial metal concentration (50-250 mg/L), and agitation speed
(0-250 rpm) were studied. The results proved that the best values of these parameters achieve the maximum removal efficiency of Pb+2 (=97%) were 2 hr, 5, 5 g/100 mL, 50 mg/L and 200 rpm respectively. The sorption data of Pb+2 ions on the zero-valent iron have been performed well by Langmuir isotherm model in compared with Freundlich model under the studied

The main objective of present work is to describe the feasibility of friction stir welding (FSW) for
joining of low carbon steel with dimensions (3 mm X 80 mm X 150 mm). A matrix (3×3) of welding
parameters (welding speed and tool rotational speed) was used to see influence of each parameter on
properties of welded joint .Series of (FSW) experiments were conducted using CNC milling machine
utilizing the wide range of rotational speed and transverse speed of the machine. Effect of welding
parameters on mechanical properties of weld joints were investigated using different mechanical tests
including (tensile and microhardness tests ). Micro structural change during (FSW) process was
studied and different welding zones

Iraqi siliceous rocks were chosen to be used as raw materials in this study which is concern with the linear shrinkage and their related parameters. They are porcelinite from Safra area (western desert) and Kaolin Duekla, their powders were mixed in certain percentage, to shape compacts and sintered. The study followed with thermal and chemical treatments, which are calcination and acid washing. The effects on final compact properties such as linear shrinkage were studied. Linear shrinkage was calculated for sintered compacts to study the effects of calcination processes, chemical washing, weight percentage, sintering processes, loading moment were studied on this property where the compacts for groups is insulating materials.
Linear

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

The aim of the current research is to verify the effect of the cognitive modeling strategy on the achievement of the chemistry course for the students of the first intermediate grade. To achieve the objective of the research, the null hypothesis was formulated via cognitive modeling strategy. The results showed that the experimental group's students performed better than the students in the control group. In the light of the results, the researchers concluded: The impact of the cognitive modeling strategy in the achievement of students of first intermediate grade in chemistry.

         This study attempts to determine the necessary teaching competencies for teachers and the level of their importance in the development of their performance professionally and scientifically, and the progress towards a better future to achieve an effective level. Accordingly, the research community consists of the morning-preparatory schools for boys at the General Directorate of Education of Baghdad \ Rusafa². The study sample included (68) teachers constituted 88.31% of the total community of teachers. As for the research tools, the researcher adopted the descriptive method by using the observation method in which the researcher prepared a list of teaching. For verifying the re

Cold plasma is a relatively low temperature gas, so this feature enables us to use cold plasma to treat thermally sensitive materials including polymers and biologic tissues. In this research, the non-thermal plasma system is designed with diameter (3 mm, 10 mm) Argon at atmospheric pressure as well as to be suitable for use in medical and biotechnological applications.
The thermal description of this system was studied and we observed the effect of the diameter of the plasma needle on the plasma, when the plasma needle slot is increased the plasma temperature decrease, as well as the effect of the voltages applied to the temperature of the plasma, where the temperature increasing with increasing the applied voltage . Results showed t

Increased downscaling of CMOS circuits with respect to feature size and threshold voltage has a result of dramatically increasing in leakage current. So, leakage power reduction is an important design issue for active and standby modes as long as the technology scaling increased. In this paper, a simultaneous active and standby energy optimization methodology is proposed for 22 nm sub-threshold CMOS circuits. In the first phase, we investigate the dual threshold voltage design for active energy per cycle minimization. A slack based genetic algorithm is proposed to find the optimal reverse body bias assignment to set of noncritical paths gates to ensure low active energy per cycle with the maximum allowable frequency at the optimal supply vo