The research involves preparing gold nanoparticles (AuNPs) and studying the factors that influence the shape, sizes and distribution ratio of the prepared particles according to Turkevich method. These factors include (reaction temperature, initial heating, concentration of gold ions, concentration and quantity of added citrate, reaction time and order of reactant addition). Gold nanoparticles prepared were characterized by the following measurements: UV-Visible spectroscopy, X-ray diffraction and scanning electron microscopy. The average size of gold nanoparticles was formed in the range (20 -35) nm. The amount of added citrate was changed and studied. In addition, the concentration of added gold ions was changed and the calibration curve was calculated used to estimate Au ions in different samples. The effectiveness of gold nanoparticles prepared according to Turkevich method was studied as antibacterial agents against E. coli bacteria. The minimum inhibition concentration of gold nanoparticles that inhibit bacterial growth was calculated using the broth dilution method, which is based on several dilutions to determine the inhibition concentration.
Complexes of 1-phenyl-3-(2(-5-(phenyl amino)-1,3,4-thiadiazole-2-yl)phenyl) thiourea have been prepared and characteizedby elemental analysis, Ff-[R, and u.v./ visible spectra moreover,determination of metal content M%o by flame atomic absorptionspectroscopy, molar conductance in DMSO solution and magneticmoments (peffl.The result showed that the ligand (L) was coordinated to Mn+2, Ni+2,Ct+2,2n+2,Cd+2, and Hg+2 ions through the nitrogen atoms and sulpheratoms.From the result obtained, rhe following general formula [MLCl2] hasbeen given for the prepared complexes with an octahedral geometryaround the metal ions for all complexes.where M= Mn+2, Ni+2, cu+2, zn+2, cd+2, and Hg+2 l= l-phenyl-3-(2-(5-(phenyl amino
... Show MoreComplexes of 1-phenyl-3-(2(-5-(phenyl amino)-1,3,4- thiadiazole-2-yl)phenyl) thiourea have been prepared and characteized by elemental analysis, Ff-[R, and u.v./ visible spectra moreover, determination of metal content M%o by flame atomic absorption spectroscopy, molar conductance in DMSO solution and magnetic moments (peffl. The result showed that the ligand (L) was coordinated to Mn*2, Ni*2, Ct*2,2n*2,Cd*2, and Hg*2 ions through the nitrogen atoms and sulpher atoms. From the result obtained, rhe following general formula [MLClz] has been given for the prepared complexes with an octahedral geometry around the metal ions for all complexes. where M= Mn*2, Ni*2, cu*2, zn*z, cd*z, and Hg*2 l= l-phenyl-3-(2-(5-(phenyl amino)-1, 3,
... Show MoreThe present paper stresses the direct effect of the situational dimension termed as “reality” on the authors’ thoughts and attitudes. Every text is placed within a particular situation which has to be correctly identified by the translator as the first and the most important step for a good translation. Hence, the content of any word production reflects some part of reality. Comprehending any text includes comprehending the reality’s different dimensions as reflected in the text and, thus illuminating the connection of reality features.
Аннотация
Исследование под названием ((«Понимание реальности» средство полно
... Show MoreThis research presents a method for calculating stress ratio to predict fracture pressure gradient. It also, describes a correlation and list ideas about this correlation. Using the data collected from four wells, which are the deepest in southern Iraqi oil fields (3000 to 6000) m and belonged to four oil fields. These wells are passing through the following formations: Y, Su, G, N, Sa, Al, M, Ad, and B. A correlation method was applied to calculate fracture pressure gradient immediately in terms of both overburden and pore pressure gradient with an accurate results. Based on the results of our previous research , the data were used to calculate and plot the effective stresses. Many equations relating horizontal effective stress and vertica
... Show MoreThis paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,
... Show MoreIn data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me
Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
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