This aim of this study is to assess the Tigris River sediments and utilize them as a new abrasive for the preparation of polished surface of magnetite ore to be studied under reflected light ore microscope. Such polishing process was tested using 250, 125, 71, 45, 25 and 18μm grain sizes of the river sediments. For the completion of the polishing and to obtain a glossy perfect polished surface, the 7 and 2.5 μm sized standard diamond pastes were used. After each polishing stage, the reflectance and roughness of these surfaces were measured as an evaluation step for the polishing efficiency. The reflectance values (R%) of the magnetite surface were found to be reversely proportioned to the abrasive grain size; while the surface roughness values (Ra) showed positive relationship with the grain size. The polished surface showed gradual improvement with decreasing grain size of the abrasive. The reflectance increased at a rate of 0, 0, 0.3, 1.2, 2.5, 3.7, 9.3, 20% with reducing grain sizes from 250, 125, 70, 45, 25, 18, 7 and 2.5 µm; at the same time, the roughness reduced at a rate of 72.2, 51.8, 23.7, 17.2, 10.9, 7.5, 6, 3.8 with reducing grain size. The 18 µm abrasive grain size of river sediments was found to be the best. Buffing by 2.5 µm diamond paste as the last stage, improved the polishing efficiency and resulted in 20% reflectance. Based on the obtained results, the Tigris sediments can be considered as fine-grained granules with the ability of preparing a flat, homogeneous surface with little roughness and reasonable degree of reflectivity.
The beginning of COVID-19 in Wuhan, China in late December 2019 and its worldwide transmission has led the World Health Organization to formally address the pandemic. The pandemic has imposed influential impacts on different environmental, economic, social, health, and living aspects. Publishing in scholastic journals was not immune from these impacts.
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In this work, thiadiazole derivatives were prepared by taking advantage of active sites in (2-amino-5-mercapto-1, 3, 4-thiadiazole) as a starting material base. The main heterocyclic compounds (1, 3, 4-thiadiazole, oxazole) etc, 2-amino-5-mercapto-1,3,4-thiadiazole compound (1) was prepared by cyclic closure of thiosemicarbazide compound with anhydrous sodium carbonate and carbon disulfide. Oxidation of (1) via hydrogen peroxide, to have (2) which was treated with chloro acetyl chloride to get (3). Preparation of thiazole ring (4) was from reacting of (3) with thiourea. Synthesis of diazonium salts (5) from compound (4) using sodium nitrite and HCl. Compound (5) reacted with different ester compounds to prepare a new azo compounds (6–8).C
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A series of new 4-(((4-(5-(Aryl)-1,3,4-oxadiazol-2-yl)benzyl)oxy)methyl)-2,6-dimethoxy phenol (6a-i) were synthesized from cyclization of 4-(((4-hydroxy-3,5-dimethoxy benzyl)oxy)methyl)benzohydrazide with substituted carboxylic acid in the presences of phosphorusoxy chloride.The resulting compounds were characterized by IR, 1H-NMR, 13C-NMR, and HRMS data. 2,2-Diphenyl-1-picrylhydrazide (DPPH) and ferric reducing antioxidant power (FRAP) assays were used to screen their antioxidant properties. Compounds 6i and 6h exhibited significant antioxidant ability in both assay. Furthermore, type of substituent and their position of the aryl attached 1,3,4-oxadiazole ring at position five are play an important roles in enhancing or declining the antio
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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The theories and applications of speaker identification, recognition, and verification are among the well-established fields. Many publications and advances in the relevant products are still emerging. In this paper, research-related publications of the past 25 years (from 1996 to 2020) were studied and analysed. Our main focus was on speaker identification, speaker recognition, and speaker verification. The study was carried out using the Science Direct databases. Several references, such as review articles, research articles, encyclopaedia, book chapters, conference abstracts, and others, were categorized and investigated. Summary of these kinds of literature is presented in this paper, together with statistical analyses
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