Charge transfer complex formation method has been applied for the spectrophotometric determination of erythromycin ethylsuccinate, in bulk sample and dosage form. The method was accurate, simple, rapid, inexpensive and sensitive depending on the formed charge- transfer complex between cited drug and, 2,3- Dichloro-5,6-dicyano-p- benzoquinone (DDQ) as a chromogenic reagent. The formed complex shows absorbance maxima at 587 nm against reagent blank. The calibration graph is linear in the ranges of (10 - 110) μg.mL-1 with detection limit of 0.351μg.mL-1. The results show the absence of interferences from the excipients on the determination of the drug. Therefore the proposed method has been successfully applied for the determination of eryth

     In this study, an efficient novel technique is presented to obtain a more accurate analytical solution to nonlinear pantograph differential equations. This technique combines the Adomian decomposition method (ADM) with the homotopy analysis method concepts (HAM). The whole integral part of HAM is used instead of an integral part of ADM approach to get higher accurate results. The main advantage of this technique is that it  gives a large and more extended convergent region of iterative approximate solutions for long time intervals that rapidly converge to the exact solution. Another advantage is capable of providing a continuous representation of the approximate solutions, which gives  better information over whole time interv

    The electronic properties (such as energy gap HOMO levels. LUMO levels, density of state and density of bonds in addition to spectroscopic properties like IR spectra, Raman spectra, force constant and reduced masses as a function of frequency) of coronene C₂₄ and reduced graphene oxide C₂₄O_X , where x=1-5, were studied.. The  methodology employed was  Density Functional Theory (DFT) with Hybrid function B3LYP and 6-311G** basis sets. The energy gap was calculated for C₂₄ to be 3.5 eV and for C₂₄O_x was from 0.89 to 1.6862 eV  for x=1-5 ,respectively.   These energy gaps values are comparable to the measured gap of Graphene (1-2.2 eV). The spectroscopic propertie

    The electronic properties (such as energy gap HOMO levels. LUMO levels, density of state and density of bonds in addition to spectroscopic properties like IR spectra, Raman spectra, force constant and reduced masses as a function of frequency) of coronene C24 and reduced graphene oxide C24OX , where x=1-5, were studied.. The  methodology employed was  Density Functional Theory (DFT) with Hybrid function B3LYP and 6-311G** basis sets. The energy gap was calculated for C24 to be 3.5 eV and for C24Ox was from 0.89 to 1.6862 eV  for x=1-5 ,respectively.   These energy gaps values are comparable to the measured gap of Graphene (1-2.2 eV). The spectroscopic properties were  compared with experimental measurements, specificall

The present study utilised date palm fibre (DPF) waste residues to adsorb Congo red (CR) dye from aqueous solutions. The features of the adsorbent, such as its surface shape, pore size, and chemical properties, were assessed with X-ray diffraction (XRD), BET, Fourier-transform infrared (FTIR), X-ray fluorescence (XRF), and field emission scanning electron microscope (FESEM). The current study employed the batch system to investigate the ideal pH to adsorb the CR dye and found that acidic pH decolourised the dye best. Extending the dye-DPF waste mixing period at 25°C reportedly removed more dye. Consequently, the influence of the starting dye and DPF waste quantity on dye removal was explored in this study. At 5 g/L dye concentration, 48% d

Information security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to

Background: Machine learning relies on a hybrid of analytics, including regression analyses. There have been no attempts to deploy a sinusoidal transformation of data to enhance linear regression models.
Objectives: We aim to optimize linear models by implementing sinusoidal transformation to minimize the sum of squared error.
Methods: We implemented non-Bayesian statistics using SPSS and MatLab. We used Excel to generate 30 trials of linear regression models, and each has 1,000 observations. We utilized SPSS linear regression, Wilcoxon signed-rank test, and Cronbach’s alpha statistics to evaluate the performance of the optimization model. Results: The sinusoidal