The multi-dentate Schiff base ligand (H2L), where H2L=2,2'-(((1,3,5,6)-1-(3-((l1-oxidaneyl)-l5-methyl)-4-hydroxyphenyl)-7-(4-hydroxy-3-methoxyphenyl)hepta-1,6-di ene-3,5-diylidene)bis(azaneylylidene))bis(3-(4-hydroxyphenyl)propanoic acid), has been prepared from curcumin and L- Tyrosine amino acid. The synthesized Schiff base ligand (H2L) and the second ligand 1,10-phenanthroline (phen) are used to prepare the new complexes [Al(L)(phen)]Cl, K[Ag(L)(phen)] and [Pb(L)(phen)]. The synthesized compounds are characterized by magnetic susceptibility measurements, micro elemental analysis (C.H.N), mass spectrometry, molar conductance, FT-infrared, UV-visible, atomic absorption (AA), 13C-NMR, and 1H-NMR spectral studies. The characterization of the

The presence of hydrocarbons in the soil is considered one of the main problems of pollution. In our current study, eight samples isolated from soil saturated with hydrocarbons were taken from different areas of Baghdad, Iraq. In this study, 5 isolates belonging to Pseudomonas aeruginosa by 99%, 4 isolates to Klebsiella pneumoniae by 98%, and 3 isolates to Enterobacter hormaechei by 97% were diagnosed in different ways. A molecular examination was also conducted by 16sRNA. We recorded P. aeruginosa, K. Pneumoniae and E. hormaechei as new local isolates in NCBI. In addition, a comparison was made between our isolates and the global isolates to determine the degree of convergence in the evolutionary line. The genes alkB and nahAc7 were diagno

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

Explain in this study, thickness has an inverse relationship with electrical resistivity and a linear relationship with Grain boundary scattering. According to the (Fuchs-Sondheier, Mayadas-Shatzkces) model, grain boundary scattering leads To an Increase in electrical Resistivity. The surface scattering Coefficient  of Ag, which Fuchs-Sondheier and Mayadas-Shatzkces measured at , Ag's grain boundary reflection coefficient , which Mayadas-Shatzkces measured at , If the concentration of material has an effect on metal's electrical properties, According to this silver is a good electrical conductor and is used frequently in electrical and electronic circuits.

Background:

Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time

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The main targets for using the edge detection techniques in image processing are to reduce the number of features and find the edge of image based-contents. In this paper, comparisons have been demonstrated between classical methods (Canny, Sobel, Roberts, and Prewitt) and Fuzzy Logic Technique to detect the edges of different samples of image's contents and patterns. These methods are tested to detect edges of images that are corrupted with different types of noise such as (Gaussian, and Salt and pepper). The performance indices are mean square error and peak signal to noise ratio (MSE and PSNR). Finally, experimental results show that the proposed Fuzzy rules and membership function provide better results for both noisy and noise-free

Malware represents one of the dangerous threats to computer security. Dynamic analysis has difficulties in detecting unknown malware. This paper developed an integrated multi – layer detection approach to provide more accuracy in detecting malware. User interface integrated with Virus Total was designed as a first layer which represented a warning system for malware infection, Malware data base within malware samples as a second layer, Cuckoo as a third layer, Bull guard as a fourth layer and IDA pro as a fifth layer. The results showed that the use of fifth layers was better than the use of a single detector without merging. For example, the efficiency of the proposed approach is 100% compared with 18% and 63% of Virus Total and Bel