Background: Removal of bacteria from the pulp system by instrumentation of an infected root canal, will be significantly reduced the number of bacteria, but it is well documented that instrumentation alone can-not clean and kill all bacteria found on the root canal walls. Antibacterial irrigants are needed to kill the remaining microorganisms. The aims of this study was to assess antibacterial effect of titanium tetrafluoride (TiF4) solution and brewing green tea against root canal bacteria and to compare with sodium hypochlorite and normal saline through microbiological and molecular studies. Materials and methods: Microbiological study was carried out to determine the concentration of titanium tetrafluoride and brewing green tea at which

The study aimed to reveal the possibility of predicting academic procrastination through both Cognitive distortions and time management among students of Al-Aqsa Community College, as well as to reveal the level of both cognitive distortions, time management, and academic procrastination. Additionally, it aimed to identify the size of the correlation between cognitive distortions, time management, and academic procrastination. The study sample consisted of (250) students from Al-Aqsa community college students. The results of the study concluded that the mean for each level of cognitive distortions and academic procrastination is average. The mean level of time management is high. There is a statistically significant positive relationshi

Strategic Cost Management Tools Under Technological Development and Change in Customer Tastes Critical Studies

Reducing costs and protecting the environment surrounding economic unity has become the concern of many economic units and shifting their ideas towards preserving resources and protecting the environment by adopting strategies and techniques that take into account when applied reducing production costs and protecting the environment, including these strategies and techniques, the technical costs of the product life cycle and the strategy of cleaner production, as the application of the two concepts in local economic units helps to try to keep up with the countries that work to keep up with the success of their economic units by following the concepts that have been successful in  Developed countries by maintaining the sustainabilit

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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