New ligand of N-(pyrimidin-2-yl carbamothioyl)acetamide was synthesized and its complexes with (VO(II), Mn (II), Cu (II), Zn (II), Cd (II) and Hg (II) are formed with confirmation of their structures on the bases of spectroscopic analyses. Antimicrobial activity of new complexes are studied against Gram positive S. aureus and Gram negative E. coli, Proteus, Pseudomonas. The octahedral geometrical structures are proved depending on the outcomes from the preceding procedures. Keywords: pyrimidin-2-amine, acetyl isothiocyanate, complexes, Antimicrobial activity

A new Schiff base o-hydroxybenzylidene-1-phenyl-2,3-dimethyl-4-amino-3-pyrazolin-5-on (HL) ,have been prepared and characterization.(HL) has been used as a chelating ligand to prepare a number of metal complexes VO(II) ,Cr(III) ,Mn(II),Fe(II),Hg(II) and UO2(II) .and mixed ligands complexes have been prepared between o-hydroxybenzylidene-1-phenyl-2,3-dimethyl-4-amino-3-pyrazolin-5-on and 8- hydroxy quinoline with VO(II),Zn(II),Cd(II), Hg(II) and UO2(II) the prepared complexes were isolated and characterized by (FT-IR)and (UV-Vis) spectroscopy. Elemental analysis (C.H.N) Chloride contents, Flame atomic absorption technique. in addition to magnetic susceptibility and conductivity measurement. Molar ratio measurement in solution gave comparabl

New Schiff base ligand (E)-6-(2-(4-(dimethylamino)benzylideneamino)-2-(4-hydroxyphenyl)acetamido)-3,3- dimethyl-7-oxo-4-thia-1- azabicyclo[3.2.0]heptane-2-carboxylic acid = (HL) was synthesized via condensation of Amoxicillin and 4(dimethylamino)benzaldehyde in methanol. Figure -1 Polydentate mixed ligand complexes were obtained from 1:1:2 molar ratio reactions with metal ions and HL, 2NA on reaction with MCl2 .nH2O salt yields complexes corresponding to the formulas [M(L)(NA)2Cl],where M=Fe(II),Co(II),Ni(II),Cu(II),and Zn(II), A=nicotinamide .

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

Porosity plays an essential role in petroleum engineering. It controls fluid storage in aquifers, connectivity of the pore structure control fluid flow through reservoir formations. To quantify the relationships between porosity, storage, transport and rock properties, however, the pore structure must be measured and quantitatively described. Porosity estimation of digital image utilizing image processing essential for the reservoir rock analysis since the sample 2D porosity briefly described. The regular procedure utilizes the binarization process, which uses the pixel value threshold to convert the color and grayscale images to binary images. The idea is to accommodate the blue regions entirely with pores and transform it to white in r

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp