The meteorite with a single total mass of 630 gm as a visible meteorite has fallen on 22 March 2021, at 10:00 a.m. in Al-Sherqat subdistrict within Salah Al-Din, northern Iraq; and therefore, was named Al-Sherqat meteorite by the authors. It is characterized by a uniform structure of coherent and medium degree of malleability. It is of a well-crystalline structure and not homogeneous in composition. The Al-Sherqat meteorite is composed of metallic phases of 7.6 gm/cm3 density exhibiting an oriented intergrowth of kamacite (α-FeNi) with taenite showing a Widmanstätten pattern on an etched polished section with the finest octahedrite kamacite bandwidth of less than 0.2 mm. It is composed of Fe (86.9 wt%), Ni (9.63 wt%), P (1.31 wt%), S (0.628 wt%), Ti (0.623 wt%), Co (0.446 wt%), Mo (0.146 wt%), Cr (0.103 wt%), Cu (0.141 wt%), V (300 ppm), Nb (220 ppm), W (53 ppm), Ag (50 ppm), Pb (30 ppm), Zn (20 ppm), Sb (16 ppm), Sn (10 ppm) and As (3 ppm). Al-Sherqat meteorite was structurally classified as an iron meteorite belongs to the plessitic group (Opl)) with octahedrite finest bands (less than 0.2 mm) of the kamacite lamellae. Kamacite platelets in Al-Sherqat meteorite are almost not a continuous plate network. Chemically, it belongs to the IIC type of magmatic group based on the amount of nickel (9.63%), where IIC is typically octahedrites has 9.3 – 11.5% Ni. The presence of kamacite, taenite, schreibersite, daubréelites, pentlandite, chromite, and wusite in Al-Sherqat meteorite are in accordance with IIC group of the iron meteorites. Al-Sherqat meteorite belongs to M-type considering a metallic core fragmented by impact asteroid. The most probable source of this meteorite is the core of an asteroid that melted early in its history.
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
... Show MoreThis paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n
... Show MoreRecently, 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.
Allopurinol derivative were prepared by reacting the (1-chloroacetyl)-2-Hydropyrazolo{3,4-d}pyrimidine-4-oneiwith 5- methoxy- 2-aminoibenzothiazoleiunder certain conditions to obtain new compound ( N- (2-aminoacetyl (5-methoxy) benzothiazole -2yl) (A4), Reaction of 5-(P-dimethyl amine benzene)-2-amino-1,3,4- oxadiazole in the presence of potassium carbonate anhydrous to yield new compound (N-(2- aminoacetyl-5-(P-dimethyl amine benzene )-1,3,4-oxadiazoles-2-yl)(A30) and Azo compound (N-(5-(Azo-2-hydroxy-5-amino benzene)-1,3-Diazol-2yl)Allopurinol(A46). The structure of prepared compounds were confirmed by (FT-IR)
... Show MoreImage 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
... Show MoreThe 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
... Show More: Partial purification of phosphoenolpyruvate carboxykinase (PEPCK) from type 2 diabetic patients sera take place using some purification steps such as participation with ammonium sulphate (55-80%) and filtered through dialysis, then ion exchange chromatography by DEAE sepharose anion column, gel filtration chromatography by sephadex G-100 column. In ion exchange step, there are four peak are obtained, the highest enzyme activity obtained by (0.4 M Nacl) with purification fold (2.18), yield (44.3) of enzyme and specific activity (13.5) mg/ng, which obtained a single peak by gel filtration chromatography, the degree of purification (5.34) fold, yield of enzyme (20%) with specific activity (33.109mg/ng). The purified enzyme had an optimum tem
... Show More