Change the morphological characteristics with the change of the factors affecting it has been shown that the Tigris River has the characteristics of the morphology of the low values in terms of depth, width and perimeter wet and gradient which in turn affected the morphological and other characteristics in terms of the direction and pattern of runoff came through the study of 48 cross-section is taken of the Tigris River Year 2008 by section for each 1 km, it has been shown that the average width of the Tigris River does not exceed 221.1 meters and the average depth of 3.9 meters either wet ocean amounted to 268.9 meters and changed the cross-section area of the last section at a rate of 4594.3 square meters, and through the study turned

Introduction: Implant stability is usually measured with resonance frequency analysis (RFA) and damping capacity assessment (DCA). This study aimed to measure primary and secondary stabilities using 3 devices that are based on these methods, namely; RFA (Osstell^®) and DCA (Periotest^® and AnyCheck^®) to assess the correlations of the measurements obtained by these devices and the correlations between implant stability and insertion torque. Material and Methods: This observational prospective study included 35 dental implants. The implant stability was measured using the 3 devices. Mann–Whitney U

Poly-ether-ether-ketone (PEEK) was introduced in dentistry as an alternative to metal alloys.

Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural