The - M ultiple mixing ratios of -transitions from levels of 56Fe populated in 56 56 Fe n n Fe ( , ) reactions are calculated by using const. S.T.M. This method has been used in other works [3,7] but with pure transition or with transitions that can be considered as pure transitions، in our work we used This method for mixed - transitions in addition to pure - transitions. The experimental angular distribution coefficients a2 was used from previous works [1] in order to calculet - values. It is clear from the results that the - values are in good agreement or consistent, within associated errors, with those reported previously [1]. The discrepancies that occur are due to inaccuracies existing in the experimental data of the previous works. The present work results confirm the validities of C.S.T.M. in calculating the -mixing ratios and their capabilities in predicting any inaccuracy in the experimental data and C.T.T.M. for mixed transition which are better than C.T.T.M. for pure transitions because it depends only on the experimental results while the 2nd method depends on pure and that which can be considered to be pure transitions.
Information on the scorpions' fauna of Iraq is limited especially in Thi Qar Province. The scorpion specimens of the present study were collected from the desert area which is located between the provinces of Thi Qar and Al-Muthana (Al-Kata'a region). The Scorpio kruglovi (Birula, 1910) redescribed in this study was found in this area. The diagnostic characters are given and the important features are figured.
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Piroxicam is a non-steroidal anti-inflammatory drug (NSAID) used in the treatment of musculo-skeletal and joint disorders. The problem with this drug is its poor solubility in water and hence poor bioavailability after oral administration. In order to improve its solubility and dissolution behavior, hydrophilic additives such as starch, lactose, superdisintegrants including crospovidone (C.P), cross carmellose sodium (CCS), and sodium starch glycolate (SSG) were physically dry mixed with the drug by simple trituration. The improvement in the solubility in 0.1 N HCl was obtained as the amount of starch or lactose increased in the physical mixture, while for superdisintegrants, they further improve the solubility when they are present in s
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A plant mixture containing indigenous Australian plants was examined for synergistic antimicrobial activity using selected test microorganisms. This study aims to investigate antibacterial activities, antioxidant potential and the content of phenolic compounds in aqueous, ethanolic and peptide extracts of plant mixture
Well diffusion, minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assays were used to test antibacterial activity against four pathogenic bacteria namely
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The isolation and characterization of
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The subject of the Internet of Things is very important, especially at present, which is why it has attracted the attention of researchers and scientists due to its importance in human life. Through it, a person can do several things easily, accurately, and in an organized manner. The research addressed important topics, the most important of which are the concept of the Internet of Things, the history of its emergence and development, the reasons for its interest and importance, and its most prominent advantages and characteristics. The research sheds light on the structure of the Internet of Things, its structural components, and its most important components. The research dealt with the most important search engines in the Intern
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.
Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
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