Background: Tooth eruption is a localized process in the jaws which exhibits precise timing and bilateral symmetry. Develop within the jaws and their eruption is a complex infancy process during which they move through bone to their functional positions within the oral cavity. For species with more than one set of teeth, eruption of the second set also accomplishes. The key to the successful clinical management of tooth eruption consists of understanding that this process consists largely of the local regulation of alveolar bone metabolism to produce bone resorption in the direction of eruption and shift and formation of bone at the opposite side.The amniotic sac contains a considerable quantity of stem cells. These amniotic stem cells are

Anaerobic digestion (AD) is the most common process for dealing with primary and secondary wastewater sludge. In the present work, four pre-treatment methods (ultrasonic, chemical, thermal, and thermo-chemical) are investigated in Al-Rustumya Wastewater Treatment plant in order to find their effect on biogas production and volatile solid removal efficiency during anaerobic digestion.
Two frequencies of ultrasonic wave were used 30 KHz and 50 KHz during the pre-treatment. Sodium hydroxide was added in different amounts to give three pH values of 9, 10 and 11 in chemical pre-treating processes. The sludge was heated at 60oC and 80oC through thermal pre-treatment experiment. Also, the sludge was treated thermo-chemically at 80 oC and pH

An experimental and numerical study was carried out to investigate the heat transfer by natural convection in a three dimensional annulus enclosure filled with porous media (silica sand) between two inclined concentric cylinders with (and without) annular fins attached to the inner cylinder under steady state condition. The experiments were carried out for a range of modified Rayleigh number (0.2 ≤Ra*≤ 11) and extended to Ra*=500 for numerical study and for annulus inclination angle of (δ = 0˚, 30˚, 60˚ and 90˚). The numerical study was to give the governing equation under assumptions that used Darcy law and Boussinesq’s approximation and then it was solved numerically using finite difference approximation. It was found that t

Nurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Si

The rise in the general level of prices in Iraq makes the local commodity less able to compete with other commodities, which leads to an increase in the amount of imports and a decrease in the amount of exports, since it raises demand for foreign currencies while decreasing demand for the local currency, which leads to a decrease in the exchange rate of the local currency in exchange for an increase in the exchange rate of currencies. This is one of the most important factors affecting the determination of the exchange rate and its fluctuations. This research deals with the currency of the European Euro and its impact against the Iraqi dinar. To make an accurate prediction for any process, modern methods can be used through which

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