This review article concentrates the light about aetiology and treatment of the periimplantitis.

The purple pigment violacein is produced by Gram-negative bacteria, mainly from the Chromobacterium violaceum. Violacein is synthesized by fusing two Ltryptophan molecules using five different enzymes encoded by VioA, VioB, VioC, VioD, and VioE genes. These genes have transferred to genetically engineering microorganisms such as E.coli for high production of violacein. It is receiving greater interest because of its significant biological functions and therapeutic potential. The reviews outlining the biosynthesis, production, and biological significance of violacein are being published.

Blastocystosis is symptomatic infection caused by the protozoal parasite Blastocystis , which resides in the intestinal tract of its hosts and it is one of the most common parasites reported in humans. It’s prevalence ranges between (30 - 50%) of the population in developing countries. This genus has a worldwide distribution and often the most commonly reported human intestinal protozoan in children and adults, even infect infants

The poultry industry is developing continuously and rapidly, this development takes several trends in the poultry industry, such as searching for new alternatives feed additives. The research focused on finding new alternatives feed additives, among these alternatives is Synoptic, which used to maximize the benefit of the two important compounds (probiotics and prebiotics) as these two compounds are considered one of the most alternatives feed additives, which have been used a lot in poultry feeding to maximize the value of these compounds, they were combined into one compound called synbiotic. Several studies confirm that the synbiotic effect on the intestine morphology, which, the ratio villus height and villus: crypt ratio in the

Internet paths sharing the same congested link can be identified using several shared congestion detection techniques. The new detection technique which is proposed in this paper depends on the previous novel technique (delay correlation with wavelet denoising (DCW) with new denoising method called Discrete Multiwavelet Transform (DMWT) as signal denoising to separate between queuing delay caused by network congestion and delay caused by various other delay variations. The new detection technique provides faster convergence (3 to 5 seconds less than previous novel technique) while using fewer probe packets approximately half numbers than the previous novel technique, so it will reduce the overload on the network caused by probe packets.

<span>As a result of numerous applications and low installation costs, wireless sensor networks (WSNs) have expanded excessively. The main concern in the WSN environment is to lower energy consumption amidst nodes while preserving an acceptable level of service quality. Using multi-mobile sinks to reduce the nodes' energy consumption have been considered as an efficient strategy. In such networks, the dynamic network topology created by the sinks mobility makes it a challenging task to deliver the data to the sinks. Thus, in order to provide efficient data dissemination, the sensor nodes will have to readjust the routes to the current position of the mobile sinks. The route re-adjustment process could result in a significant m

<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

In this work, a simple and new method is proposed to simultaneously improve the physical layer security and the transmission performance of the optical orthogonal frequency division multiplexing system, by combining orthogonal frequency division multiplexing technique with chaotic theory principles. In the system, a 2-D chaotic map is employed. The introduced system replaces complex operations such as matrix multiplication with simple operations such as multiplexing and inverting. The system performance in terms of bit error rate (BER) and peak to average ratio (PAPR) is enhanced. The system is simulated using Optisystem15 with a MATLAB2016 and for different constellations. The simulation results showed that the  BE