Background: asthma has an influence on craniofacial development. Recently evidences show that there is an association between oral health problems and chronic lung disease. The present study was designed to estimate the changes in arch dimension measurements among asthmatic children aged 12 years old who were collected from AL- Zahra Center Advisory for Allergy and Asthma and compare them with the non-asthmatic children of the same age and gender. Material and Methods: Fifty children (25 asthmatic and 25 non- asthmatic children) were included for the odontometric measurement. For both upper and lower study models, photographs were taken using special photographic apparatus for each child, and the statistical analysis were done by using SPSS

During the last quarter century, many changes have taken place in the tanks industry and also in the materials that used in its production، while concrete is the most suitable material where concrete tanks has the benefits of strength, long service life and cost effectiveness. So, it is necessary improvement the
conventional concrete in order to adapt the severe environment requirements and as a result high
performance concrete (HPC) was used. It is not fundamentally different from the concrete used in the past, although it usually contains fly ash, ground granulated blast furnace slag and silica fume, as well as
superplasticizer. So, the content of cementitious material is high and the water/cement ratio is low. In this
stu

Field experiment was conducted by using two fertilization systems (i.e.) biofertilizers (inoculation with Pseudomonas putida and with Azotobacter chroococcum and non - inoculation) and chemical fertilization (100%, 50% and 25% of recommended by Ministry of Agriculture) to study the influence of these system and interaction on water and grain yield productivity, some growth phytohorones and number of bacterial cells in soil rizosphere of root of wheat crop under water scarcity. The result showed that the integrate fertilization (inoculation with Pseudomonas putida and Azotobacter chroococcum bacterial + 50% of the recommended chemical fertilizer) recorded 5.70 and 5.55 t ha^-1, respectively with reducing the chemical fertilizer app

There have been many advances in the solar chimney power plant  since 1930 and the first pilot work was built in Spain (Manzanares) that produced 50 KW. The solar chimney power plant is considered of a clean power generation that needs to be investigated  to enhance the performance by studying the effect of changing the area of passage of air to enhance the velocity towards the chimney to maximize design velocity. In this experimental and numerical study, the reduction area of solar collector was investigated. The reduction area that mean changing the height of glass cover from the absorbing plate (h1=3.8cm, h2=2.6cm and h3=1.28cm). The numerical study was performed using ANSYS Fluent software package (version 14.0) to solve go

The antibacterial effect of (Eruca sativa) extract was evaluated by an in vitro study testing the growth of various Gram-Positive and Gram-Negative bacteria . The bactericidal activity of this extract was analyzed by serial dilution in tubes. This study,found that Gram-Negative and Gram-Positive bacteria susceptible to very low eruca concentrations. On the other hand, Gram-positive bacteria were more susceptible than Gram-negative bacteria, the minimal bactericidal concentration of Gram-positive bacteria was 5 mg ml-1 but minimal bactericidal concentration of Gram-negative bacteria was 10 mg ml-1 that mean duble inhibation concentration of Gram-positive bacteria . this study suggest that Eruca sativa leaves have inhibation effect on Gra

This paper details the process of designing, analysing, manufacturing, and testing an integrated solid-state hydrogen storage system. Analysis is performed to optimise flow distribution and pressure drop through the channels, and experimental investigations compare the effects of profile shape on the overall power output from the fuel cell. The storing of hydrogen is given much attention in the selection of a storage medium, and the effect of a cooling system to reduce the recharging time of the hydrogen storage vessel. The PTFE seal performed excellently, holding pressure over 60 bar, despite requiring changing each time the cell is opened. The assembly of the vessel was simple and straightforward, and there was no indication of pressure

Tin Oxide (SnO2) films have been deposited by spray pyrolysis technique at different substrate temperatures. The effects of substrate temperature on the structural, optical and electrical properties of SnO2 films have been investigated. The XRD result shows a polycrystalline structure for SnO2 films at substrate temperature of 673K. The thickness of the deposited film was of the order of 200 nm measured by Toulansky method. The energy gap increases from 2.58eV to 3.59 eV when substrate temperature increases from 473K to 673K .Electrical conductivity is 4.8*10-7(.cm)-1 for sample deposited at 473K while it increases to 8.7*10-3 when the film is deposited at 673K

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to