The synthesis, characterization and liquid crystalline properties of N4,N40-bis((1 H-benzo[d]imidazol-2- yl)methyl)-3,30-dimethyl-[1,10-biphenyl]-4,40-diamine and of their corresponding Mn(II), Fe(II), Ni (II), Cu(II), and Zn(II) complexes are described. The ligand and complexes have been characterized by elemental analysis, magnetic susceptibility measurements (meff), conductometric measurements and Fourier Transform Infrared (FTIR), Nuclear Magnetic Resonance (1H NMR), (13C-NMR) and UV–Vis spectroscopy. Spectral investigations suggested octahedral coordination geometrical arrangement for M(II) complexes. The phase transition temperatures were detected by differential scanning calorimetry (DSC) analysis and the phases are confirmed by op

The synthesis, characterization and liquid crystalline properties of N4,N40 -bis((1 H-benzo[d]imidazol-2- yl)methyl)-3,30 -dimethyl-[1,10 -biphenyl]-4,40 -diamine and of their corresponding Mn(II), Fe(II), Ni (II), Cu(II), and Zn(II) complexes are described. The ligand and complexes have been characterized by elemental analysis, magnetic susceptibility measurements (meff), conductometric measurements and Fourier Transform Infrared (FTIR), Nuclear Magnetic Resonance (1 H NMR), (13C-NMR) and UV–Vis spectroscopy. Spectral investigations suggested octahedral coordination geometrical arrangement for M(II) complexes. The phase transition temperatures were detected by differential scanning calorimetry (DSC) analysis and the phases are confirmed

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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Docetaxel is an effective treatment approved for many types of cancers, but its effectiveness in clinical practice can be compromised by significant occurrence of adverse drug reactions. The aim of the current study was to measure the distribution of adverse drug reactions of docetaxel reported in Iraq and to assess the causality, severity, seriousness, preventability, expectedness and outcome of these adverse reactions. A retrospective study conducted on individual case safety reports from the Iraqi Pharmacovigilance Center / Ministry of Health. The study included 118 individual case safety report containing 236 adverse drug reactions.
Most of the adverse drug reactions were related to skin and subcutaneous tissue disorders(26.7%), f

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

Laser is a powerful device that has a wide range of applications in fields ranging from materials science and manufacturing to medicine and fibre optic communications. One remarkable