Abstract In the current contribution, a novel binuclear nickel(II) and zinc(II) complexes were prepared from a hexadentate ligand prepared via condensation of 3,3'-Bipyridine-6,6'-dicarbaldehyde , 2-amino-5-chlorobenzaldehyde and 2-Aminophenol .The symmetric ligand (H2DTPE) and its metal complexes were illustrated utilizing various techniques of physicochemical containing magnetic moment, analytical analysis and spectroscopy of mass, IR, 13C and 1H NMR, TGA and UV-Vis. The particles of MO Nanoscale were created from the labeled complex applying the ways of pyrolysis and utilizing methods of XRD, FT-IR, and FE-SEM, that specified close compatibility with the typical pattern for nanoparticles of NiO, ZnO and appeared the reasonable size in the nano reign ( 30 nm). In the efficacies of antimicrobial (In-vitro) for the compounds, some (+)ve Gram (Staphylococcus and Fecal enterococci) and Gram-negative bacteria (Enterococcus faecalis and Pseudomonas aeruginosa) were investigated and compared with each other. It was obtained that the Ni (II) and Zn(II) complexes exhibited higher efficacy.
As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Recently, numerous the generalizations of Hurwitz-Lerch zeta functions are investigated and introduced. In this paper, by using the extended generalized Hurwitz-Lerch zeta function, a new Salagean’s differential operator is studied. Based on this new operator, a new geometric class and yielded coefficient bounds, growth and distortion result, radii of convexity, star-likeness, close-to-convexity, as well as extreme points are discussed.
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop
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the bank sect for any country is very important because its represent a major nerve to feed a verity economic and finance activities .development any state measure by development banking sets and its represent important factor to investors attract . and because important of this subject ,teen accounting rule is a specialized for it .its related by Disclosures in the Financial Statements Of Banks and The Similar Institutions, its accredit by auditing and accounting standard consul in republic of Iraq.in date 10/28/1998. &
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يعد هذا النص أحد النصوص المسمارية المصادرة التي بحوزة المتحف العراقي، ويحمل الرقم المتحفي (235869)، قياساته )12،7x 6x 2،5سم). يتضمن مدخولات كميات من الشعير،أرخ النص الى عصر أور الثالثة (2012-2004 ق.م) و يعود الى السنة الثالثة من حكم الملك أبي-سين (2028-2004 ق.م)،أن الشخصية الرئيسة في هذا النص هو)با-اَ-كا مسمن الماشية( من مدينة أري-ساكرك، ومقارنته مع النصوص المسمارية المنشورة التي تعود الى أرشيفه يبلغ عددها (196) نصاً تضمنت نشاطاته م
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