Background: Irrigation of the canal system permits removal of residual tissue in the canal anatomy that cannot be reached by instrumentation of the main canals so the aim of this study was to compare and evaluate the efficiency of conventional irrigation system, endoactivator sonic irrigation system,P5 Newtron Satelec passive ultrasonic irrigation and Endovac irrigation system in removing of dentin debris at three levels of root canals and to compare the percentage of dentin debris among the three levels for each irrigation system. Materials and methods: Forty extracted premolars with approximately straight single root canals were randomly distributed into 4 tested groups of 10 teeth each. All canals were prepared with Protaper Universal ha

The banking sector has a significant impact on the economic growth of the country, and the importance of this sector must assess its financial performance from time to time, to measure the situation related to money for each bank and how to put the supervision of the efficiency of the full. The research aims at evaluating the financial performance according to the elements of the CAMELS model, which including capital adequacy, asset quality, management efficiency, profitability, liquidity, and market risk sensitivity. The research included the study of Al-Mansour Investment Bank during the period from 2014 to 2018. The base capital ratio was used to total assets to measure capital adequacy The proportion of investments to total a

A sensitivity-turbidimetric method at (0-180^o) was used for detⁿ. of mebeverine in drugs by two solar cell and six source  with C.F.I.A.. The method was based on the formation  of  ion pair for the pinkish banana color  precipitate by the reaction of Mebeverine hydrochloride with Phosphotungstic acid. Turbidity was measured via the reflection of incident light that collides on the surface particles of   precipitated at 0-180^o. All variables were optimized. The linearity ranged of Mebeverine hydrochloride was 0.05-12.5mmol.L^-1, the L.D. (S/N= 3)(3S_B) was 521.92 ng/sample depending on dilution for the minimum concentration , with correlation coefficient r = 0.9966while was R.S.D%

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi