Background: Beta thalassemia major is an inherited disorder that may affect general and oral health.The purpose of this study was toassess the severity of dental caries in relation to oral cleanliness, mutans streptococciamong a group of boys with beta thalassemia majorin comparison with a control group. Materials and Methods: The study involved 30 boys with BTM aged 10-12 years compared to 30 healthy boys with the same age group. d1-4mfs and D1-4 MFS indices were applied (Muhlemann, 1976), the viable counts of mutans streptococci in stimulated saliva were also determined. Results: The entire thalassemic group was caries-active. For both dentitions, a higher dmfs/DMFS values were recorded for study compared to control group, difference was

Background: Blood group system and the ability to taste phenylthiocarbamide (PTC) are the most studied traits in human genetics which have been extensively used in describing genetic variations among human populations around the world that may had an effect on dental caries. The aims of present study were to investigate the caries experience among students with different bitter taste threshold in relation to blood type. Materials and Methods: The sample of present study includes dental students female aged19-21 years. The diagnosis of dental caries was done according to the criteria of Manjia et al, 1989 recording decayed lesion by severity (D1-4) MFS. Furthermore, bitter taste sensitivity was measured according to PTC (phenylthiocarbamid

ABSTRACT Purpose: the aim of this in vitro study was to compare the marginal gap and internal fitness between single crowns and the crowns within three-unit bridges of zirconium fabricated by CAD-CAM system. Materials and methods: A standard model from ivoclar company was used as a pattern to simulate three-units bridge (upper first molar and upper first premolar) as abutments used to fabricate stone models, eight single crowns for premolar and eight of three units bridges. Crowns and bridges fabricated by CAD-CAM system were cemented on their respective stone models then sectioned at the mid-point buccolingaully and misiodistaly and examined under stereomicroscope. Result: the marginal gap in premolar crowns and premolar within bridge we

      The Khor Mor gas-condensate processing plant in Iraq is currently facing operational challenges due to foaming issues in the sweetening tower caused by high-soluble hydrocarbon liquids entering the tower. The root cause of the problem could be liquid carry-over as the separation vessels within the plant fail to remove liquid droplets from the gas phase. This study employs Aspen HYSYS v.11 software to investigate the performance of the industrial three-phase horizontal separator, Bravo #2, located upstream of the Khor Mor sweetening tower, under both current and future operational conditions. The simulation results, regarding the size distribution of liquid droplets in the gas product and the efficiency gas/liquid separation, r

Channel estimation and synchronization are considered the most challenging issues in Orthogonal Frequency Division Multiplexing (OFDM) system. OFDM is highly affected by synchronization errors that cause reduction in subcarriers orthogonality, leading to significant performance degradation. The synchronization errors cause two issues: Symbol Time Offset (STO), which produces inter symbol interference (ISI) and Carrier Frequency Offset (CFO), which results in inter carrier interference (ICI). The aim of the research is to simulate Comb type pilot based channel estimation for OFDM system showing the effect of pilot numbers on the channel estimation performance and propose a modified estimation method for STO with less numb

The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model