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.

Background: Denture relining is the process of resurfacing of the tissue side of the ill fitting denture, the bond strength at the relining-denture base interface is most important for denture durability.The aim of present study was to evaluate the shear bond strength between the thermosens as relining material and different denture base materials that bonded by thermo fusing liquid. As this corrective procedureis the common chair side procedure in the dental clinic. Material and method: Sixty samples were prepared and divided into three main groups according to the type of denture base materials.Group (A) referred to the heat cure acrylic samples which consisted of 20 samples. Group (B) referred to the high impact acrylic samples which con

In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th

Cubosomes are nanosized structures self-assembled nanostructured materials used for controlling the release of the entrapped drug molecule. Lornoxicam (LXM) is a potent analgesic nonsteroidal anti-inflammatory (NSAID) drug with a short half-life (3-4) hours. The present study aims to prepare LXM-loaded cubosomes with well-defined morphology, particle size, PDI, high entrapment efficiency, sustained drug release, and high zeta potential value, as a transdermal drug delivery system.

      Twelve formulas of LXM-loaded cubosomal dispersions were prepared by a solvent dilution method using Glyceryl monooleate ( GMO) as polar lipid with different stabilizers as Pluronic® F127 or tween 80 and different types o

Background: The aim of this in vitro study was to evaluate and compare the microleakage between Vertise Flow T M composite material and other conventional (Filtek Z250, riva light cure and SDR) composite materials when restoring CII mesial box only cavity at gingival margin through die penetration test Materials and methods: Forty maxillary first premolars were prepared with class II box design only cavities. Samples were divided into four groups of ten teeth according to material used: group I (FiltekZ250 only). Group II (SDR+FiltekZ250). Group III (Vertise Flow +FiltekZ250). Group IV (Riva light cure+ FiltekZ250). After 24 hrs. immersion in 2% in methylene blue, samples were sectioned and micro leakage was estimated. Results: None of the

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c