Background: different methods can be used to remove tissue during gingivectomy and produce a good gingival margin, the most common is the conventional gingivectomy which is done by the use of scalpel, now a day’s Laser is widely spread and can be used to perform surgeries. Materials and methods: 50 patients divided into two equal groups, Group 1 gingivectomy was done by Diode Laser, Group 2 gingivectomy was done by scalpel, plaque and gingival index were measured at 1st, 2nd and 3rd visit, swab were taken and sent foe detecting bacterial growth and biopsy were taken for histopathological examination. Group 1 show no significant differences in plaque and gingival means between the visits, the bacteriological examination showed no growth of

Different methods can be used to remove tissue during gingivectomy and produce a good gingival margin, the most common is the conventional gingivectomy which is done by the use of scalpel, now a day’s Laser is widely spread and can be used to perform surgeries. Materials and methods: 50 patients divided into two equal groups, Group 1 gingivectomy was done by Diode Laser, Group 2 gingivectomy was done by scalpel, plaque and gingival index were measured at 1st, 2nd and 3rd visit, swab were taken and sent foe detecting bacterial growth and biopsy were taken for histopathological examination. Group 1 show no significant differences in plaque and gingival means between the visits, the bacteriological examination showed no growth of bact

Abstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t

Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h

Let G be a graph, each edge e of which is given a weight w(e). The shortest path problem is a path of minimum weight connecting two specified vertices a and b, and from it we have a pre-topology. Furthermore, we study the restriction and separators in pre-topology generated by the shortest path problems. Finally, we study the rate of liaison in pre-topology between two subgraphs. It is formally shown that the new distance measure is a metric

Background: Fetal macrosomia is usually distressing to obstetricians and neonatologists. In the current study, involved mothers had poor social and medical circumstances, as they were migrated forcefully within the country borders due to war, from their original homeland to safer camps which had miserable situations. Objectives: To study rate, risk factors, and complications of macrosomia in people with low socio-economic living conditions and missed medical follow up. Methods: All internally displaced pregnant women who gave birth to neonates weighed ≥4000 g were involved in the study. All required history, examination, care, and investigations were practiced by the attending obstetrician and neonatologist. Cases of normal birth weight n

Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi