In this paper, some series of new complexes of Mn(II), Co(II), Ni (II) Cu(II) and Hg(II) are prepared from the Schiff bases (L1,L2). (L1) derived from 4-aminoantipyrine and O-phenylene dia mine then (L2) derived from (L1) and 2-benzoyl benzoic acid. Structural features are obtained from their elemental microanalyses, molar conductance, IR, UV–Vis, 1H, 13CNMR spectra and magnetic susceptibility. The magnetic susceptibility and UV–Vis, IR spectral data of the ligand (L1) complexes get square–planar and tetrahedral geometries and the complexes oflig and (L2) get an octahedral geometry. Antimicrobial examinations show good results in the sharing complexes.

In this paper, some series of new complexes of Mn(II), Co(II), Ni (II) Cu(II) and Hg(II) are prepared from the Schiff bases (L1,L2). (L1) derived from 4-aminoantipyrine and O-phenylene dia mine then (L2) derived from (L1) and 2-benzoyl benzoic acid. Structural features are obtained from their elemental microanalyses, molar conductance, IR, UV–Vis, 1H, 13CNMR spectra and magnetic susceptibility. The magnetic susceptibility and UV–Vis, IR spectral data of the ligand (L1) complexes get square–planar and tetrahedral geometries and the complexes oflig and (L2) get an octahedral geometry. Antimicrobial examinations show good results in the sharing complexes.

    The  adsorption of cephalexin.H₂O from aqueous solution on attapulgite, bentonite and kaolin has been studied at the human body temperature (37.5ËšC) and at 5, 27, 47ËšC in 0.1M hydrochloric acid (pH 1.2). The value of pH 1.2 has been chosen to simulate the pH of stomach fluid. The clays show the following order: Bentonite > attapulgite > kaolin, for their activity to adsorb cephalexin.H₂O. The charged clay particles can attract molecules either by electrostatic forces, for the molecules of oppositely charged, or by inducing dipole formation in the neutral molecule. The L-shaped adsorption isotherm indicated that drug molecules arrangement in a flat geometry on the clay surface. The

This work describes the synthesis of novel ligand (H₂L²) (4-((2-hydroxy-5-nitrophenyl)imino)methyl)-5(hydroxymethyl)-2methylpyridin-3-ol)  type (NOO) donor atoms. When it coordinates with metal ions[V²⁺,Mn²⁺,Fe²⁺,Co²⁺,Ni²⁺,Cu²⁺and Pt⁴⁺] with the general formula K₂[M(L²)₂].XH₂O and K₂[VO(L²)(OSO₃)].H₂O . This ligand can form tridentate structures. The ligand was synthesized from the reaction of pyridoxal hydrochloride with 2-amino-4-nitrophenol in ethanol (as a solvent) at a mole ratio of 1:1 and thoroughly mixed and refluxed for 6-8  hrs . The reaction

The approach of green synthesis of bio-sorbent has become simple alternatives to chemical synths as they use for example plant extracts, plus green synthesis outperforms chemical methods because it is environmentally friendly besides has wide applications in environmental remediation. This paper investigates the removal of ciprofloxacin (CIP) using green tea nano zero-valent iron (GT-NZVI) in an aqueous solution. The synthesized GT-NZVI was categorized using SEM, AFM, BET, FTIR, and Zeta potentials techniques. The spherical nanoparticles were found to be nano zero-valent, with an average size of 85 nm and a surface area of 2.19m2/g. The results showed that the removal efficiency of ciprofloxacin depends on the initial pH (2.5-10),

Boltzmann mach ine neural network bas been used to recognize the Arabic speech.  Fast Fourier transl(>lmation algorithm has been used t() extract speciral 'features from an a caustic signal .

The  spectral  feature size is reduced by series of operations in

order to make it salable as input for a neural network which is used as a recogni zer by Boltzmann Machine Neural  network which has been used as a recognizer for phonemes . A training set consist of a number of Arabic phoneme repesentations, is used to train lhe neuntl network.

The neural network recognized Arabic. After Boltzmann Machine Neura l    network   training  the  system   with 

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas