This research presents a numerical study to simulate the heat transfer by forced convection as a result of fluid flow inside channel’s with one-sided semicircular sections and fully filled with porous media. The study assumes that the fluid were Laminar , Steady , Incompressible and inlet Temperature was less than Isotherm temperature of a Semicircular sections .Finite difference techniques were used to present the governing equations (Momentum, Energy and Continuity). Elliptical Grid is Generated using Poisson’s equations . The Algebraic equations were solved numerically by using (LSOR (.This research studied the effect of changing the channel shapes on fluid flow and heat transfer  in two cases ,the first: cha

A new Macrocyclic Schiff base ligand Bis[4-hydroxy(1,2-ethylene-dioxidebenzylidene) pheylenediamine] [H2L] and its complexes with (Co(II) , Ni(II) , Cu(II) , Zn(II) and Cd(II)) are reported . The ligand was prepared in two steps,in the first step a solution of (o-phenylene diamine) in methanol react under reflux with (2,4-dihydroxybenzylaldeyed) to give an (intermediatecompound) [Bis-1,2 (2,4-dihydroxybenzylediene)pheylinediamine] which react in the second step with (1,2- dichloro ethane) giving the mentioned ligand.Then the complexes were synthesis of adding of corresponding metal salts to the solution of the ligand in methanol under reflux with 1:1 metal to ligand ratio. On the basis of, molar conductance, I.R., UV-Vis, chloride content a

A novel Schiff base ligand [N1-benzylidenebenezene-1,2-diamine(L) = C20H16N2] was prepared through intensification of benzaldehyde (C6H5CHO) and O- amino aniline O-C6H4(NH2)2 in ethanol with 8-Hydroxyquinoline (8HQ) . Formed compounds were acquired of 1:1:2 molar proportion reactions for metal ions and ligands (L) and 2(8HQ) during reaction for MCl2 .nH2O salt products complexes conformable into the forms [M(L)(8HQ)2] ,where M = Mn(II),Co(II) and Ni(II). Whole the compounds were identified during the basis of their; FT-IR and U.V spectrum, melting point, molar conduct, identify of the percentage from the metal at the complexes via flame (AAS), C, H and N content of the Schiff base (L) and metal complexes were analysis and magnetic susceptib

A new ligand complexes have been synthesis from reaction of metal ions of Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II), Hg(II), Pd(II) and Pt(II) with schiff base LH. 5-[(2-Hydroxy-naphthalen-1-ylmethylene)-amino]-2-phenyl-2,4-dihydro-pyrazol-3-one, this ligand was characterized by Fourier transform infrared (FTIR), UV-vis, 1H, 13CNMR, and mass spectra. All complexes were characterized by techniques micro analysis C.H.N, UV-vis and FTIR spectral studies, atomic absorption, chloride content, molar conductivity measurements and magnetic susceptibility. The ligand acts as bidentate, coordination through nitrogen atom from azomethin group and deprotonated phenolic oxygen atom. The spectroscopic and analytical measurements showed that

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

<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation