The problem of steady, laminar, natural convective flow in an square enclosure with and without partitions is considered for Rayleigh number (103-106) and Prandtl number (0.7). Vertical walls were maintained isothermal at different temperatures while horizontal walls and the partitions were insulated. The length of partition was taken constant. The number of partitions were placed on horizontal surface in staggered arrangement from (1– 3) and ratio of partition thickness (H/L= 0.033, 0.083, 0.124). The problem is formulated in terms of the vorticity-stream function procedure. A numerical solution based on a program in Fortran 90 with the finite difference method is obtained. Representative results illustrating the effects of the thickness and number of partitions on the contour maps of the streamlines and temperature are reported and discussed. In addition, the local Nusselt number is evaluated. Results show that the values of stream function (the strength of flow) in enclosure increases with the increasing Rayleigh number. As the number of partitions and thickness of partition increases, the strength of flow decreases. Mean Nusselt number increases with increasing Rayleigh number at different number of partitions. The numerical results are compared with available numerical results and experimental data and a good agreement is obtained.
A study were conducted to examinate the effect of organic and aqueous (Hot, Cold) Extracts from leaves of Duranta repens on the growth and activities of the following types of Bacteria:- Staphylococcus aureus,Streptococcus pyogens ,Escherichia coli,Klebsilla pneumonia, in addition to the yeast Candida albicans and the fungi Aspergullis niger ,Aspergulls flavus.The result showed that gram Positive Bacteria is more sensitive to the extracts than gram negative bacteria with Minimum inhibitory concentration (MIC) value (50,25,50,100)% and Minimum Bactericidal Concentration (MBC) value (100,50,200,100)% for all types Bacteria respectively . The most active extract against A.niger ,A,flavus was cold and hot aqueous extract from the leaves with d
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Fifty-four Sprague-Dawley albino adult male rats were classified into three main groups each of 18 rats treated for a particular duration (1,2, and 4) weeks respectively. Each group was subdivided into three subgroups each of six rats treated as follows; group (1) serve as normal control, group (2, and 3) intra-peritoneal treated with TiO2NPs (50,200) mg/kg respectively, body *weight of all rats was measured before and after the experiment, then rats were dissected at the end of each experiment and the weights of the thyroid was measured. The result showed a highly significant decrease (p<0.01) in thyroid gland weight, a highly significant increase (p<0.01) in body weights and TSH, while a highly significant decrease (p&
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In this study, gamma-ray spectrometry with an HPGe detector was used to measure the specific activity concentrations of 226Ra, 232Th, and 40K in soil samples collected from IT1 oil reservoirs in Kirkuk city, northeast Iraq. The “spectral line Gp” gamma analysis software package was used to analyze the spectral data. 226Ra specific activity varies from 9 0.34 Bq.kg-1 to 17 0.47 Bq.kg-1. 232Th specific activity varies from 6.2 0.08 Bq.kg-1 to 18 0.2 Bq.kg-1. 40K specific activity varies from 25 0.19 Bq.kg-1 to 118 0.41 Bq.kg-1. The radiological hazard due to the radiation emitted from natural r
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Liquefied petroleum gas (LPG), Natural gas (NG) and hydrogen were used to operate spark ignition internal combustion engine Ricardo E6, to compare NOx emissions emitted from the engine, with that emitted from engine fueled with gasoline as a fuel.
The study was done when engine operated at HUCR for gasoline, compared with its operation at HUCR for each fuel. Compression ratio, equivalence ratio and spark timing were studied at constant speed 25rps.
The results appeared that NOx concentrations will be at maximum value in the lean side near the stoichiometric ratio, and reduced with moving away from this ratio for mixture at both s
... Show MoreLung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c
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