In this publication, several six coordinate Co(III)-complexes are reported. The reaction of 2,3-butanedione monoxime with ethylenediamine or o-phenylenediamine in mole ratios of 2:1 gave the tetradentate imine-oxime ligands diaminoethane-N,N`-bis(2-butylidine-3-onedioxime) H2L1 and o-phenylenediamine-N,N`-bis(2-butylidine-3-onedioxime), respectively. The reaction of H2L1 and H2L2 with Co(NO3)2, and the amino acid co-ligands (glycine or serine) resulted in the formation of the required complexes. Upon complex formation, the ligands behave as a neutral tetradantate species, while the amino acid co-ligand acts as a monobasic species. The mode of bonding and overall geometry of the complexes were determined through physico-chemical and spectroscopic methods. These studies revealed octahedral geometry about Co(III) complexes in which the co-ligands bound through the amine and the carboxylate groups. Molecular structure for the complexes have been optimised by CS Chem 3D Ultra Molecular Modelling and Analysis Program and supported six coordinate geometry.
The hydrolysis of urea by the enzyme urease is significant for increasing the irroles in human pathogenicity, biocementation, soil fertilizer, and subsequently in soil improvement. This study devoted to the isolation of urease from urea-rich soil samples collected from seven different locations. Isolation of the various bacterial species was conducted using nutrient agar. The identity of isolated urease was based on morphological characteristics and standard microbiological and biochemical procedures. The urease producing strains of bacteria were obtained using the urease hydrolysis test. The bacterial isolates produced from soil samples collected from different environments and treat
Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the most effective parameter, particularly when Age<49.5. Whereas Ki67 appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu
... Show MoreNumeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a
... Show MoreThis work involves hard photon rate production from quark -gluon plasma QGP interaction in heavy ion collision. Using a quantum chromodynamic model to investigate and calculation of photons rate in 𝑐𝑔 → 𝑠𝑔𝛾 system due to strength coupling, photons rate, temperature of system, flavor number and critical. The photons rate production computed using the perturbative strength models for QGP interactions. The strength coupling was function of temperature of system, flavor number and critical temperature. Its influenced by force with temperature of system, its increased with decreased the temperature and vice versa. The strength coupling has used to examine the confinement and deconfinement of quarks in QGP properties and inf
... Show MoreIn this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in
Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal.
Darifenacin hydrobromide (DH) is the more recent uroselective M3 receptor antagonist for treating uncomplicated overactive bladder (OAB). This study was aimed to formulate DH as fast dissolving buccal films (FDBFs) using a solvent casting method to enhance patient’s compliance.
Films were prepared by using polyvinyl alcohol (PVA) as a film forming polymer. Different types and concentrations of superdisintegrants (croscarmellose sodium, sodium starch glycolate, indion 414) were used to select the best formula by studying the physicochemical properties of the films, disintegration time (DT) and percent drug release.
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