The research work was conducted to investigate the effect of oral administration of aqueous extract of turmeric at doses of (5, 10) mg/kg body weight for two weeks daily by determining the genotoxic effect (mitotic index), evaluation of immunological effect (IgG, IgM, IgA, C3, C4) and measuring fertility hormones (follicles stimulation hormone/FSH, lutenising hormone/LH) levels with histological examinations of female albino swiss mice ovaries in comparison with control (normal saline). A clear effect in increasing mitotic activity was reveled for both doses in comparison with control. Results also showed a significant increase in the value of all immunological parameters at both doses, in comparison with control. Also, obvious raise was se

The research work was conducted to investigate the effect of oral administration of aqueous extract of turmeric at doses of (5, 10) mg/kg body weight for two weeks daily by determining the genotoxic effect (mitotic index), evaluation of immunological effect (IgG, IgM, IgA, C3, C4) and measuring fertility hormones (follicles stimulation hormone/FSH, lutenising hormone/LH) levels with histological examinations of female albino swiss mice ovaries in comparison with control (normal saline). A clear effect in increasing mitotic activity was reveled for both doses in comparison with control. Results also showed a significant increase in the value of all immunological parameters at both doses, in comparison with control. Also, obvious rais

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Agricultural lands have great importance in people's lives, and their exploitation has a great impact on strengthening the national economy. Therefore, countries have given great importance to this sector, and because of the importance of this sector, the state has given large areas of these lands to the farmers to invest in agriculture, and among these farmers are those who died and left behind children who took up crafts. Agriculture, for fear that these agricultural lands would be abandoned and turned into waste lands, a land system was introduced called (regular distribu- tion), which corresponds to (legitimate inheritance). Under this system, these lands were trans- ferred to the children of farmers who died so that the process of inve

The present work presents a new experimental study of the enhancement of turbulent
convection heat transfer inside tubes for combined thermal and hydrodynamic entry length of one
popular “turbulator” (twisted tape with width slightly less than internal tube diameter) inserted for
fire tube boilers. Cylindrical combustion chamber was used to burn (1.6 to 7kg/h) fuel oil #2 to
deliver hot gases with ranges of Reynolds number (10500 to 21700), and (11400 to 24150) for both
empty and inserted tube respectively.A uniform wall temperature technique was used by keeping
approximately constant water temperature difference (25ºC) between inlet and exit cooling water in
parallel flow shell and tube heat exchanger. The test

The aim of this work is to learn the relationship of the stability of (β) emitter isobars with their shape for some isobaric elements with even mass number (A=152 - 162). To reach this goal firstly the most stable isobar have been determined by plotting mass parabola (plotting the binding energy (B.E) as a function of the atomic number (Z)) for each isobaric family. Then three-dimensional representation graphics for each nucleus in these isobaric families have been plotted to illustrate the deformation in the shape of a nucleus. These three-dimensional representation graphics prepared by calculating the values of semi-axis minor (a), major (b) and (c) ellipsoid axis’s. Our results show that the shape of nuclides which is represented the