The Sebkha is considered the evaporative geomorphological features, where climate plays an active role. It forms part of the surface features in Mesopotamia plain of Iraqi, which is the most fertile lands, and because of complimentary natural and human factors turned most of the arable land to the territory of Sebkha lands. The use satellite image (Raw Data), Landsat 30M Mss for the year 1976 Landsat 7 ETM, and the Landsat 8 for year 2013 (LDCM) for the summer Landsat Data Continuity Mission and perform geometric correction, enhancements, and Subset image And a visual analysis Space visuals based on the analysis of spectral fingerprints earth's This study has shown that the best in the discrimination of Sebkha Remote sensing techniques a

Since the beginning of mankind, the view of the sky was present through observations with the naked eye, then it developed with time, and the sciences and tools of astronomical observations developed, including photometric measurements, which reached a high degree of accuracy in describing various cosmic phenomena, including the study of galaxies, their composition, and the differences between them, and from here the importance of this study emerged, to determine the differences between two distinct types of classification of galaxies, which are normal and barred spiral galaxies, where two galaxies NGC 4662 and NGC 2649 were chosen that represented certain types of galaxies to study the morphological structure of the two galaxies, a

For criminal investigations, fingerprints remain the most reliable form of personal identification despite developments in other fields like DNA profiling. The objective of this work is to compare the performance of both commercial charcoal and activated carbon powder derived from the Alhagi plant to reveal latent fingerprints from different non-porous surfaces (cardboard, plain glass, aluminum foil sheet, China Dish, Plastic, and Switch). The effect of three variables on activated carbon production was investigated. These variables were the impregnation ratio (the weight ratio of KOH: dried raw material), the activation temperature, and the activation time. The effect factors were investigated using Central Composite Design

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,

Background: Depression is a state of low mood and aversion to activity, it can affect a person's thoughts, behavior and sense of well-being. It can affect oral health and lead to an increased risk of dental caries. Dental caries is the most common oral infectious diseases that stresses the immune system and causes changes in cellular and molecular components of peripheral blood and C-Reactive Protein is one of these components, considered a key biomarker of inflammation. This study was conducted to assess the effect of depression status on dental caries among 17 years old secondary school female students in relation to salivary C-Reactive Protein. Materials and Methods: A cross sectional study was carried and the whole sample composed of