This study offers numerical simulation results using the ABAQUS/CAE version 2019 finite element computer application to examine the performance, and residual strength of eight recycle aggregate RC one-way slabs. Six strengthened by NSM CFRP plates were presented to study the impact of several parameters on their structural behavior. The experimental results of four selected slabs under monotonic load, plus one slab under repeated load, were validated numerically. Then the numerical analysis was extended to different parameters investigation, such as the impact of added CFRP length on ultimate load capacity and load-deflection response and the impact of concrete compressive strength value on the structural performance of

  Reaction of Na2PdCl4 with benz-1,3-imidazole-2-thione or (bzimtH) benz-1,3-thiazoline2-thione (bztztH) in ethanol / NE3 afford complexes of the type [Pd(bzimt)2](1) and [Pd(bztzt)2](2) respectively. Treatment of [Pd(L)2] L= bzimt or bztzt with bidentate ligands (N^N) where N^N= bipyridine (Bipy) , phenanthroline (Phen) , ethylene diamine , or N,N′dimethylethylene diamine afford mononuclear complexes of the type [PdL2(N^N)]. The bzimt and bztzt ligands are coordinated as bidentate chelating ligands through the S and N in (1) and (2) whereas bonded as a monodentate fashion via the sulfur atom in other complexes. The prepared complexes were characterized by elemental CHN analysis, ir and 1H nmr spectra.
 

New tetradentate Schiff base [H2L] namely [2,2׳ -(ethane-1,2- diylbis (azan-1-ylylidene) diacetic acid)] was prepared from condensation of ethylenediamine with  glyoxylic acid  in ethanol as a solvent in presence of drops of 48% HBr .The structure of ligand (H2L) was characterized by,F-IR, U.V-Vis.,1H-,13C-NMR, pectrophotometer,melting point and elemental microanalysis C.H.N.  Metal complexes of the ligand (H2L) in general Molecular formula [M(L)(H2O)2], where M=  Co(II), Ni(II), Cu(II), Mn(II) and Hg(II); L=(C6H8N2O4) were synthesized were characterized by, Atomic absorption, F-IR, U.V-Vis. spectra, molar conductivity and magnetic susceptibility.It was found that all the complexes showed octahedral geometries.And

In this work, thiadiazole derivatives were prepared by taking advantage of active sites in (2-amino-5-mercapto-1, 3, 4-thiadiazole) as a starting material base. The main heterocyclic compounds (1, 3, 4-thiadiazole, oxazole) etc, 2-amino-5-mercapto-1,3,4-thiadiazole compound (1) was prepared by cyclic closure of thiosemicarbazide compound with anhydrous sodium carbonate and carbon disulfide. Oxidation of (1) via hydrogen peroxide, to have (2) which was treated with chloro acetyl chloride to get (3). Preparation of thiazole ring (4) was from reacting of (3) with thiourea. Synthesis of diazonium salts (5) from compound (4) using sodium nitrite and HCl. Compound (5) reacted with different ester compounds to prepare a new azo compounds (6–8).C

A series of new 4-(((4-(5-(Aryl)-1,3,4-oxadiazol-2-yl)benzyl)oxy)methyl)-2,6-dimethoxy phenol (6a-i) were synthesized from cyclization of 4-(((4-hydroxy-3,5-dimethoxy benzyl)oxy)methyl)benzohydrazide with substituted carboxylic acid in the presences of phosphorusoxy chloride.The resulting compounds were characterized by IR, 1H-NMR, 13C-NMR, and HRMS data. 2,2-Diphenyl-1-picrylhydrazide (DPPH) and ferric reducing antioxidant power (FRAP) assays were used to screen their antioxidant properties. Compounds 6i and 6h exhibited significant antioxidant ability in both assay. Furthermore, type of substituent and their position of the aryl attached 1,3,4-oxadiazole ring at position five are play an important roles in enhancing or declining the antio

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne