Aims: This study aimed to assess complications of caesarean section among pregnant women attending AL Diwaniyah Maternity and Pediatric Hospital; and find out relationship between complications of caesarean section and socio-demographic data of women. Methods: A descriptive cross-sectional study design is conducted for the period of December 26th 2020 to June 1st 2021. The validity of the questionnaire is determine through a panel of experts and reliability was achieved through a pilot study. By a purposive sample is selected among pregnant women who undergo caesarean section, data was collected through the use of questionnaire and interview techniques; and analyzed through the descriptive and inferential statistic. Results: Findings indica

Climate change is one of the global issues that is receiving wide attention due to its clear impact on all living organisms. This is essential for Iraq since it was classified as the fifth most vulnerable country to climate change. One of the manifestations of these changes in Iraq is the increasing frequency and severity of dust storms. In this study, the Normalized Difference Dust Index (NDDI) spectral index for Moderate Resolution Imaging Spectroradiometer (MODIS) sensor bands was used to measure and track the dust storm that occurred on May 16, 2022, as well as to test the validity of one of the daily products of this sensor, MOD11A1, to measure surface temperature and emissivity before and after the storm. It was found that the MOD0

Abstract Exotoxin A is the most lethal virulence factor produced by Pseudomonas aeruginosa. It inhibits elongation factor-2 by ADP-ribosylation of EF2. This causes stop of the elongation of polypeptides. In recent study, the effect of low concentration of exotoxin A on some important internal organs of mice was studied. Four groups white mice were injected intraperitonialy with pure exotoxin A in the following manner 0.1, 0.2, 0.3, 0.4 ng\ animals. One mouse receives normal saline inrtaperitonialy as a control. After 72 hours the mice were killed and four organs were taken, liver, spleen, lung and heart from each killed mice. Histological sections were made from each organ and stained with hematoxylin and eosin stain then examined under mic

This research is carried out to investigate the externally post-tensioning technique for strengthening RC beams. In this research, four T-section  RC beams having the same dimensions and material properties were casted and tested up to failure by applying two mid-third concentrated loads. Three of these beams are strengthened by using external tendons, while the remaining beam is kept without strengthening as a control beam. Two external strands of 12 mm diameter were fixed at each side of the web of the strengthened beams and located at depth of 200 mm from top fiber of the section (d_ps). So that the depth of strands to overall depth of the section ratio (d_ps

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,

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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