Several efforts have been made to study the behavior of Total Electron Content (TEC) with many types of geomagnetic storm, the purpose of this research is to study the disturbances of the ionosphere through the TEC parameter during strong, severe and great geomagnetic storms and the validity of International Reference Ionosphere IRI model during these kinds of storms. TEC data selected for years 2000-2013 (descending solar cycle 23 to ascending cycle 24), as available from koyota Japan wdc. To find out the type of geomagnetic storms the Disturbance storm time (Dst) index was selected for the years (2000-2013) from the same website. Data from UK WDC have been taken for the solar indices sunspots number (SSN), radio flux (F10.7) and ionosphere index parameter (IG12). The predicted TEC are calculated from IRI model. From data analysis, it is found that there are (132) events happened in the tested years for the strong, severe and great geomagnetic storms, a largest number of solar storms appeared in years 2000 to 2005 at solar maximum from solar cycle 23 and the number of storms increases with increasing the SSN. In general, there is a good proportionality between disturbance storm time index (Dst) and the total electron contents, the values of TEC in daytime greater than nighttime, but there is anomaly when the storm continued for several hours from the day, there is a highly a broad increasing in TEC started from sunrise to sunset. Also two peaks or more appeared when two types of storms occurred remaining for one event or the storm remains for more than one day. Finally there is approximately sharp peak at noon, when the storm started in early morning. Concerning the validity of the IRI model during strong, great, and severe geomagnetic storm shows that there is a weak correlation between the observed and predicted TEC values, so that the model must be corrected during major storms.
An anatomical study was carried out at the College of Agricultural Engineering Sciences, University of Baghdad, in 2017, on lupine crop (Lupinus albus) as a comparison guide of three seed weights of three lupine cultivars viz. ‘Giza-1’, ‘Giza-2’ and ‘Hamburg’. The nested design was used with four replications. The results showed that cultivars had a significant effect on stem anatomical traits. ‘Hamburg’ cultivar recorded the highest stem diameter, cortex thickness and xylem vascular diameter, while cultivar ‘Giza-1’ recorded the lowest values for the same traits as well as the highest collenchyma layer thickness, vascular bundle thickness, and xylem thickness. Cultivar ‘Giza-2’ recorded the lowest vascular bundle th
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To present a case of a previous complicated mandibular orthognathic surgery that aimed to setback the mandible in a female cleft lip and palate (CLP) patient, which led to bone necrosis on one side with subsequent severe mandibular deviation and facial asymmetry. We additionally reviewed the previous reports of similar complications, the pathophysiology and the factors that could lead to this dreadful result.
A 27-year-old female patient presented with a severe dentofacial deformity secondary to a complicated bilateral sagittal spli
The genetic diversity was studied in sixteen barley Hordeum vulgar L. species cultivated in Iraq , which are differ in their ability to drought stress tolerance by using random amplified polymorphic DNA polymerase chain reaction (RAPD - PCR ) .Barley species was evaluated to drought stress after treatment the plant seedling at germination stages to different concentration of polyethylene glycol (PEDG6000) . The results showed that the Broaq and Arefat species have the highest tolerance to drought stress in contrast the rest of Barly species like Alkhair, Alwarkaa, Ebaa99, Shoaa, Alrafidain,Sameer Rehana 3 , forat9 , jazeral ,and ebaa7 revealed sensitivity to drought stress . The primes which used RAPD technique
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreAn anatomical study was carried out at the College of Agricultural Engineering Sciences, University of Baghdad, in 2017, on lupine crop (Lupinus albus) as a comparison guide of three seed weights of three lupine cultivars viz. ‘Giza-1’, ‘Giza-2’ and ‘Hamburg’. The nested design was used with four replications. The results showed that cultivars had a significant effect on stem anatomical traits. ‘Hamburg’ cultivar recorded the highest stem diameter, cortex thickness and xylem vascular diameter, while cultivar ‘Giza-1’ recorded the lowest values for the same traits as well as the highest collenchyma layer thickness, vascular bundle thickness, and xylem thickness. Cultivar ‘Giza-2’ recorded the lowest vascular b
... Show MoreIn this study, Staphylococcus aureus was found to be the causative agent of furunculosis in 64 (27.5%) out of 233 Iraqi patients presented with furunculosis. 16SrRNA gene was located in all isolates. Nevertheless, mecA and lukS-lukF genes were located in 60% and 4% of S. aureus isolates, respectively. Interestingly, the lukS-lukF carrying S. aureus isolates were mecA positive as well.
The main object of this article is to study and introduce a subclass of meromorphic univalent functions with fixed second positive defined by q-differed operator. Coefficient bounds, distortion and Growth theorems, and various are the obtained results.