This study was carried out to investigate the effects of magnetized water on accumulated infiltration depth. A test rig was designed and constructed for this purpose was installed at the water tests laboratory of the Department of Water Resources Engineering at the University of aghdad. The investigation was carried out by using two types of soil, different flow velocities throughout magnetizing device and different configuration of magnets over and under the water passage of the magnetizing device. The soils that were used in the experiments are clayey and sandy soils. Six different flow velocities throughout magnetizing device ranged between 0.29 to 1.19 cm/s and ten configurations of arranging the magnets over and under the water passage of the magnetizing device were used. The magnates are sintered neodymium-iron-boron type. Tests results obtained with magnetized water were compared with those of untreated water. Results showed that magnetizing water increases the accumulated infiltration depth for the two types of soil. The highest increase in the accumulated infiltration depth is achieved under low flow velocity throughout the magnetizing device and with ten magnets. This highest increase for the clayey and sandy soils was 98.2% and 34.2%, respectively.
The research aimed to investigate the level of Organizational Cynicism and Job Engagement of Government Schools teachers in Al Zubair district. To achieve this research was conducted on a random sample of (66) items. The statistical package for social sciences (SPSS) was used to analyze and examine the hypotheses. The researcher used many statistical methods to achieve the research objectives, such as simple, multi regression and the research results showed there is a significant impact to teacher's in the schools of the research sample between Organizational cynicism and Job Engagement
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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,
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A new class of biologically active nanocomposites and modified polymers based on poly (vinyl alcohol) (PVA) with some organic compounds [II, IV, V and VI] were synthesized using silver nanoparticles (Ag-NPs). All compounds were synthesized using nucleophilic substitution interactions and characterized by FTIR, DSC and TGA. The biological activity of the modified polymers was evaluated against: gram (+) (staphylococcus aureus) and gram (-): (Es cherichia coli bacteria). Antimicrobial films are developed based on modified poly (vinyl alcohol) MPVA and Ag-NPs nanoparticles. The nanocomposites and modified polymers showed better antibacterial activities against Escherichia coli (Gram negative) than against Staphyloc
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Iron slag is a byproduct generated in huge quantities from recycled remnants of iron and steel factories; therefore, the possibility of using this waste in the removal of benzaldehyde from contaminated water offers an excellent topic in sustainability field. Results reveal that the removal efficiency was equal to 85% for the interaction of slag and water contaminated with benzaldehyde at the best operational conditions of 0.3 g/100 mL, 6, 180 min, and 250 rpm for the sorbent dosage, initial pH, agitation time, and speed, respectively with 300 mg/L initial concentration. The maximum uptake capacity of iron slag was 118.25 mg/g which was calculated by the Langmuir model. Physical sorption may be the major mechanism for the removal of
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This study aims to know the degree of importance and the availability of the enhancing specifications of the educational process, and the way its objectives are achieved. Such a step involves using educational techniques, laying the selection foundations, knowing the methods of their employment and tracking the obstacles that limit this employment in teaching Arabic to non-native speakers. To achieve these objectives, the study followed a descriptive approach, and collected the necessary data through an integrated questionnaire prepared for the purpose of describing the phenomenon or topic. This approach was adopted, as it is characterized by being comprehensive, focuses on collecting data related and necessary to the topic under study.
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We studied the effect of certain environmental conditions for removing heavy metal elements from contaminated aqueous solutions (Cd, Cu, Pb, Fe, Zn, Ni, Cr) using the bacterium Bacillus subtilis to appoint the optimal conditions for removal ,The best optimum temperature range for two isolate was 30-35○C while the hydrogen number for the maximum mineral removal range was 6-7. The best primary mineral removal was 100 mg/L, while the maximum removal for all minerals was obtained after 6 hrs of Cu element time and the maximum removal efficiency was obtained after 24 hrs of Cu element. The results have proved that the best aeration for maximum removal was obtained at rotation speed of 150 rpm/minute. Inoculums of 5ml/100ml which contained 1
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