New Schiff-base ligands bearing tetrazole moiety and their polymeric metal complexes with Co(II), Ni(II) and Cd(II) ions are reported. Ligands were prepared in a multiple-step reaction. The reaction of sodium 2,6- diformylphenolate and cyclohexane-1,3-dione with 5-amino-2-fluorobenzonitrile resulted in the isolation of two precursors sodium 2,6-bis((E)-(3-cyano-4-fluorophenylimino)methyl)-4-methylphenolate 1 and 5,5'- (1E,1'E)-cyclohexane-1,3-diylidenebis- (azan-1-yl-1-ylidene)bis(2-fluorobenzonitrile) 2, respectively. The reaction of precursors with azide gave the required ligands; sodium 2,6-bis((E)-(4-fluoro-3-(1H-tetrazol-5- yl)phenylimino)methyl)-4-methylphenolate (NaL) and (N, N'E, N, N'E)-N, N'-(cyclohexane-1,3-diylidene)bis(4- fluoro-3-(1H-tetrazol-5-yl)aniline) (L1). The reaction of these ligands with the appropriate metal ions gave polymeric metal complexes of the formulae {[M2(L)]Cl}n and [M(L1)Cl2]n (where M = Co(II), Ni(II) and Cd(II)). A range of techniques were used to confirm the entity of ligands and their complexes. The formation of ligands and mode of complexation and geometrical structure of the title polymeric complexes were verified using FTIR, electronic spectra, NMR, ESMS, magnetic susceptibility, micro-elemental analysis, metal content, chloride content and conductance. The analytical and spectroscopic data indicated the formation of four-coordinate complexes, with a tetrahedral geometry for Co(II) and Cd(II), and square planer for Ni(II) in L- and L1 complexes. Biological evaluation of ligands and their polymeric complexes against gram-positive bacteria (G+), Bacillus stubtili, Staphylococcus aureus, and gram-negative bacteria (G-), Escherichia coli and Pseudomonas aeruginosa, showed ligands and their polymeric metal complexes have a good effect on the screened bacteria.
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 MoreSilymarin (SM) is a plant extract obtained from Silybum marianum( milk thistle) . It is class II type drug according to Biopharmaceutics Classification System with low bioavailability due to its low solubility.
Micro/nanonization during crystallization, surface modification and crystal structure modification may improve the dissolution rate of poorly water-soluble drugs.
The aim of this study was to increase the water solubility and dissolution rate of SM by in-situ micronization using solvent change either by stirring or ultrasonic method. Stabilizers like Gelatin, PVP-K30, HPMC15, Pulullan were used to stabilize the prepared ultrafine crystals. Effect of type and concentration of hydrophilic polymer, solv
... Show MoreA simple, sensitive and accurate spectrophotometric method has been developed for the determination of salbutamol sulphate (SAB) and isoxsuprine hydrochloride (ISX) in pure and pharmaceutical dosage. The method involved oxidation of (SAB) and (ISX) with a known excess of N-bromosuccinamid in acidic medium, and subsequent occupation of unreacted oxidant in decolorization of Evans blue dye (EB). This, in the presence of SAB or ISX was rectilinear over the ranges 1.0-12.0, 1.0-11.0 µg/mL, with molar absorptivity 4.21×104 and 2.58×104 l.mol-1.cm-1 respectively. The developed method had been successfully applied for the determination of the studied drugs in their pharmaceutical dosage resulting i
... Show MorePolymer electrolytes were prepared using the solution cast technology. Under some conditions, the electrolyte content of polymers was analyzed in constant percent of PVA/PVP (50:50), ethylene carbonate (EC), and propylene carbonate (PC) (1:1) with different proportions of potassium iodide (KI) (10, 20, 30, 40, 50 wt%) and iodine (I2) = 10 wt% of salt. Fourier Transmission Infrared (FTIR) studies confirmed the complex formation of polymer blends. Electrical conductivity was calculated with an impedance analyzer in the frequency range 50 Hz–1MHz and in the temperature range 293–343 K. The highest electrical conductivity value of 5.3 × 10-3 (S/cm) was observed for electrolytes with 50 wt% KI concentration at room
... Show MoreIn this paper, we study the incorporation of the commensalism interaction and harvesting on the Lotka–Volterra food chain model. The system provides one commensal prey, one harvested prey, and two predators. A set of preliminary results in local bifurcation analysis around each equilibrium point for the proposed model is discussed, such as saddle-node, transcritical and pitchfork. Some numerical analysis to confirm the accruing of local bifurcation is illustrated. To back up the conclusions of the mathematical study, a numerical simulation of the model is carried out with the help of the MATLAB program. It can be concluded that the system's coexistence can be achieved as long as the harvesting rate on the second prey population is
... Show MoreMagneto-rheological (MR) valve is one of the devices generally used to control the speed of Hydraulic actuator of MR fluid. The performance of valve depends on the magnetic circuit design. Present study deals with a new design of MR valve. A mathematical model for the MR valve is developed and the simulation is carried out to evaluate the newly developed MR valve. The design of the magnetic circuit is accomplished by magnetic finite element software such as Finite Element Method Magnetic (FEMMR). The model dimensions of MR valve, material properties are taken into account. The results of analysis are presented in terms of magnetic strength H and magnetic flux density B. The simulation results based on the proposed model indicate that the ef
... Show MoreText based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.
... Show MoreThe recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med
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