In this paper, the Monte Carlo N-Particle extended  computer code (MCNP) were used to design a model of the European Sodium-cooled Fast Reactor. The multiplication factor, conversion factor, delayed neutrons fraction, doppler constant, control rod worth, sodium void worth, masses for major heavy nuclei, radial and axial power distribution at high burnup are studied. The results show that the reactor breeds fissile isotopes with a conversion ratio of 0.994 at fuel burnup 70 (GWd/T), and minor actinides are buildup inside the reactor core. The study aims to check the efficiency of the model on the calculation of the neutronic parameters of the core at high burnup.

The aim of this work presents the analytical studies of both the magnetohydrodynamic (MHD) flux and flow of the non-magnetohydro dynamic (MHD) for a fluid of generalized Burgers’ (GB) withinan annular pipe submitted under Sinusoidal  Pressure (SP)gradient. Closed beginning velocity's' solutions are taken by performing the finite Hankel transform (FHT) and Laplace transform (LT) of the successivefraction derivatives. Lastly, the figures were planned to exhibition the transformations effects of different fractional parameters (DFP) on the profile of velocity of both flows.

The study aimed to identify career engagement among school principals, the researcher used descriptive approach and reached the study sample (230) school, principals. The researcher instruments used: career engagement, has been checked and face validity, and construction and consistency of the instruments using internal consistency Cronbach's alpha The study came to the following findings: - The degree of career engagement among school principals was (29.0200) this refers to a higher level, compared with the theoretical average of (27) and the study showed that the results showed no significant statistical differences between school principals in the level of career engagement due to the variable sex.

Background: One of the most predominant periodontal diseases is the plaque induced gingivitis. For the past 20 years, super-oxidized solutions have be..

  This paper is concerned with Double Stage Shrinkage Bayesian (DSSB) Estimator for lowering the mean squared error of classical estimator ˆ q for the scale parameter (q) of an exponential distribution in a region (R) around available prior knowledge (q0) about the actual value (q) as initial estimate as well as to reduce the cost of experimentations.         In situation where the experimentations are time consuming or very costly, a Double Stage procedure can be used to reduce the expected sample size needed to obtain the estimator. This estimator is shown to have smaller mean squared error for certain choice of the shrinkage weight factor y( ) and for acceptance region R. Expression for

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

Introduction: Cutaneous leishmaniasis is considered a parasitic contagion resulting from the flagellated parasite belonging to the genus of Leishmania. Also, cutaneous leishmaniasis is a zoonotic ailment transmitted through the bloodsucking sand-flies bite (belonging to the Phlebotomus genus). The disease's reservoirs included wild or semi-domesticated animals, in general rodents and dogs. Tissue inhibitor metalloproteinase-1 (TIMP-1) is one of the extracellular matrix proteins that have a role in vessel wall degeneration and aneurysm development. In addition, it belongs to the zinc-dependent endopeptidases family that are involved in the degradation of connective tissues proteins which are included in vascular integrity maintenance. The Ge