Background: Restoration of root canal treated teeth with a permanent restoration affect in the success of endodontically treated teeth. This in vitro study was performed to evaluate and compare the fracture strength of endodontically treated teeth restored by using custom made zirconium posts and cores, prefabricated carbon fiber, glass fiber and zirconium ceramic posts. Materials and method: Forty intact human mandibular second premolars were collected for this study and were divided into five groups. Each group contains 8 specimens: Group1: Teeth restored with Carbon Fiber Posts; Group2: Teeth restored with Glass Fiber Posts; Group3: Teeth restored with Zirconium Ceramic prefabricated Posts; Group4: Teeth restored with Zirconium Posts

In this work a model of a source generating truly random quadrature phase shift keying (QPSK) signal constellation required for quantum key distribution (QKD) system based on BB84 protocol using phase coding is implemented by using the software package OPTISYSTEM9. The randomness of the sequence generated is achieved by building an optical setup based on a weak laser source, beam splitters and single-photon avalanche photodiodes operating in Geiger mode. The random string obtained from the optical setup is used to generate the quadrature phase shift keying signal constellation required for phase coding in quantum key distribution system based on BB84 protocol with a bit rate of 2GHz/s.

All major organs may be impacted by the connective disease systemic lupus erythematosus, a separate risk factor for coronary artery disease (CAD). Adhesion molecules like intercellular adhesion molecules (ICAM) and vascular cell adhesion molecules (VCAM) can detect endothelial damage and dysfunction, which appear to play a crucial role. This study investigated whether people with SLE had elevated subclinical and clinical atherosclerosis risk factors. Traditional CAD risk factors such as smoking, hypertension, and hyperlipidemia cannot entirely explain this elevation. It is thought that immunological dysfunction also increases CAD risk in SLE patients. The study aimed to assess early endothelial changes in SLE Iraqi female patients w

Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr

This research aimed to evaluate the level of readiness to teach science in the light of the information, media, and technology skills among undergraduate students at the Faculty of Edu-cation, King Khalid University. To achieve this goal, a descriptive and analytical approach was used. A list of readiness to teach science was prepared in the light of Information, media, and technology skills, and in the light of this list, a cognitive test, observation sheet, and attitude scale were prepared to assess readiness to teach science in its three aspects, cognitive, behavioral, and emotional. The sample of the research consisted of (42) students enrolled in field training courses at the sixth, seventh and eighth levels. Research tools were app

The goal of this research is to find the effects of both the studying students groupwhich has various educational levels and the integration of the fragmented information through or during the study of history subjects for the female students of the fifth secondary literary section.
To achieve this study or case the researcher has chosen an experimental design or test by studying three groups: two are as mentioned above and the third is just ordinary team. In addition to that, there is a test after the experiment. The researcher chose on purpose female students of the literal section from two different secondary school Al Asil and Wahran both are secondary school for girls, and both are from directorate of education- Al Karkh 2nd dist

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data