Madinat Sittah Uktubar, Egypt
Madinat Sittah Uktubar, Egypt

Modern science and Arts University is located in Cairo, Egypt .It was founded in 1996. Wikipedia.

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Arafa A.A.M.,South Valley University | Rida S.Z.,South Valley University | Khalil M.,Modern Sciences and Arts University
Nonlinear Biomedical Physics | Year: 2012

In this paper, we introduce fractional-order into a model of HIV-1 infection of CD4 +T cells. We study the effect of the changing the average number of viral particles N with different sets of initial conditions on the dynamics of the presented model. Generalized Euler method (GEM) will be used to find a numerical solution of the HIV-1 infection fractional order model. © 2012 Arafa et al; licensee BioMed Central Ltd.

Lotfy H.M.,Cairo University | Saleh S.S.,Modern Sciences and Arts University | Hassan N.Y.,Cairo University | Salem H.,Modern Sciences and Arts University
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy | Year: 2014

This work represents the application of the isosbestic points present in different absorption spectra. Three novel spectrophotometric methods were developed, the first method is the absorption subtraction method (AS) utilizing the isosbestic point in zero-order absorption spectra; the second method is the amplitude modulation method (AM) utilizing the isosbestic point in ratio spectra; and third method is the amplitude summation method (A-Sum) utilizing the isosbestic point in derivative spectra. The three methods were applied for the analysis of the ternary mixture of chloramphenicol (CHL), dexamethasone sodium phosphate (DXM) and tetryzoline hydrochloride (TZH) in eye drops in the presence of benzalkonium chloride as a preservative. The components at the isosbestic point were determined using the corresponding unified regression equation at this point with no need for a complementary method. The obtained results were statistically compared to each other and to that of the developed PLS model. The specificity of the developed methods was investigated by analyzing laboratory prepared mixtures and the combined dosage form. The methods were validated as per ICH guidelines where accuracy, repeatability, inter-day precision and robustness were found to be within the acceptable limits. The results obtained from the proposed methods were statistically compared with official ones where no significant difference was observed. © 2014 Elsevier B.V. All rights reserved.

Samir A.,Modern Sciences and Arts University | Lotfy H.M.,Cairo University | Salem H.,Modern Sciences and Arts University | Abdelkawy M.,Cairo University
Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy | Year: 2014

Spectrophotometric and TLC-spectrodensitometric methods were developed and validated for the simultaneous determination of beclomethasone dipropionate (BEC) and salbutamol (SAL). The spectrophotometric methods include dual wavelength, ratio difference, constant center coupled with a novel method namely, spectrum subtraction and mean centering with mean percentage recoveries and RSD 99.72 ± 1.07 and 99.70 ± 1.12, 100.25 ± 1.12 and 99.89 ± 1.12, 99.66 ± 1.85 and 99.19 ± 1.32, 100.74 ± 1.26 and 101.06 ± 0.90 for BEC and SAL respectively. The TLC-spectrodensitometric method was based on separation of both drugs on TLC aluminum plates of silica gel 60 F254, using benzene: methanol: triethylamine (10:1.5:0.5 v/v/v) as a mobile phase, followed by densitometric measurements of their bands at 230 nm. The mean percentage recoveries and RSD were 99.07 ± 1.25 and 101.35 ± 1.50 for BEC and SAL respectively. The proposed methods were validated according to ICH guidelines and were applied for the simultaneous analysis of the cited drugs in synthetic mixtures and pharmaceutical preparation. The methods were found to be rapid, specific, precise and accurate and can be successfully applied for the routine analysis of BEC and SAL in their pharmaceutical formulation with no need for prior separation. The results obtained were statistically compared to each other and to that of the reported HPLC method. The statistical comparison showed that there is no significant difference regarding both accuracy and precision. © 2014 Elsevier B.V. All rights reserved.

Azar A.T.,Modern Sciences and Arts University
International Journal of Industrial and Systems Engineering | Year: 2012

System dynamics (SD) is a powerful methodology and computer simulation modelling technique for framing, understanding and discussing complex issues and problems. It is widely used to analyse a range of systems in, e.g. business, ecology, medical and social systems as well as engineering. The methodology focuses on the way one quantity can affect others through the flow of physical entities and information. Often such flows come back to the original quantity causing a feedback loop. The behaviour of the system is governed by these feedback loops. There are two important advantages of taking systems dynamics approach. The interrelationship of the different elements of the systems can be easily seen in terms of cause and effects. Thus the true cause of the behaviour can be identified. The other advantage is that it possible to investigate which parameters or structures need to be changed in order to improve behaviour. This paper deals with the design of a framework for SD models and gives an overview of the current SD simulation packages. Copyright © 2012 Inderscience Enterprises Ltd.

Abdallah O.M.,Modern Sciences and Arts University
E-Journal of Chemistry | Year: 2011

Sensitive, simple and accurate high performance liquid chromatographic (HPLC) methods for the determination of atorvastatin (AT), fluvastatin (FL) and pravastatin (PV) have been developed. The proposed methods involve the use of a 150 mmx4.6 mm Zorbax Extend-C18 column (5 μm particle size) and different chromatographic conditions for the separation of the three statins. Linearity range was 5-40, 5-30 and 10-60 μg mL-1 for AT, FL and PV respectively. The developed methods proved to be successful in the determination of all studied drugs in spiked human plasma samples.

Azar A.T.,Modern Sciences and Arts University
International Journal of Intelligent Systems Technologies and Applications | Year: 2011

Total dialysis dose (Kt/V) is considered to be a major determinant of morbidity and mortality in haemodialysed patients. The continuous growth of the blood urea concentration over the 30-60-min period following dialysis, a phenomenon known as urea rebound, is a critical factor in determining the true dose of haemodialysis (HD). The misestimation of the equilibrated (true) postdialysis blood urea or equilibrated Kt/V results in an inadequate HD prescription, with predictably poor clinical outcomes for the patients. The estimation of the equilibrated post-dialysis blood urea (C eq) is therefore crucial in order to estimate the equilibrated (true) Kt/V. Measuring post-dialysis urea rebound (PDUR) requires a 30- or 60-min post-dialysis sampling, which is inconvenient. This paper presents a novel technique for predicting equilibrated urea concentration and PDUR in the form of a Takagi-Sugeno-Kang fuzzy inference system. The advantage of this neuro-fuzzy hybrid approach is that it does not require 30-60-min post-dialysis urea sample. Adaptive neuro-fuzzy inference system (ANFIS) was constructed to predict equilibrated urea (C eq) taken at 60 min after the end of the HD session in order to predict PDUR. The accuracy of the ANFIS was prospectively compared with other traditional methods for predicting equilibrated urea (C eq), PDUR and equilibrated dialysis dose ( eqKt/V). The results are highly promising, and a comparative analysis suggests that the proposed modelling approach outperforms other traditional urea kinetic models. © 2011 Inderscience Enterprises Ltd.

Azar A.T.,Modern Sciences and Arts University
International Journal of Modelling, Identification and Control | Year: 2011

The classification of the electrocardiogram (ECG) into different patho-physiological disease categories is a complex pattern recognition task. This paper presents an intelligent diagnosis system using hybrid approach of adaptive neuro-fuzzy inference system (ANFIS) model for classification of electrocardiogram (ECG) signals. Wavelet-transform is used for effective feature extraction and ANFIS is considered for the classifier model. It can parameterise the incoming ECG signals and then classify them into eight major types for health reference: left bundle branch block (LBBB), normal sinus rhythm (NSR), pre-ventricular contraction (PVC), atrial fibrillation (AF), ventricular fibrillation (VF), complete heart block (CHB), ischemic dilated cardiomyopathy (ISCH) and sick sinus syndrome (SSS). The inclusion of adaptive neuro-fuzzy interface system (ANFIS) in the complex investigating algorithms yields very interesting recognition and classification capabilities across a broad spectrum of biomedical problem domains. The performance of the ANFIS model is evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in classifying the ECG signals. Cross validation is used to measure the classifier performance. A testing classification accuracy of 95% is achieved which is a significant improvement. Copyright © 2011 Inderscience Enterprises Ltd.

Azar A.T.,Modern Sciences and Arts University
Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia | Year: 2011

Post-dialysis urea rebound (PDUR) is a cause of Kt/V overestimation when it is calculated from pre-dialysis and the immediate post-dialysis blood urea collections. Measuring PDUR requires a 30-or 60-min post-dialysis sampling, which is inconvenient. In this study, a supervised neural network was proposed to predict the equilibrated urea (C eq) at 60 min after the end of hemodialysis (HD). Data of 150 patients from a dialysis unit were analyzed. C eq was measured 60 min after each HD session to calculate PDUR, equilibrated urea reduction rate eq (URR), and ( eq Kt/V). The mean percentage of true urea rebound measured after 60 min of HD session was 19.6 ± 10.7. The mean urea rebound observed from the artificial neural network (ANN) was 18.6 ± 13.9%, while the means were 24.8 ± 14.1% and 21.3 ± 3.49% using Smye and Daugirdas methods, respectively. The ANN model achieved a correlation coefficient of 0.97 (P <0.0001), while the Smye and Daugirdas methods yielded R = 0.81 and 0.93, respectively (P <0.0001); the errors of the Smye method were larger than those of the other methods and resulted in a considerable bias in all cases, while the predictive accuracy for ( eq Kt/V) 60 was equally good by the Daugirdas' formula and the ANN . We conclude that the use of the ANN urea estimation yields accurate results when used to calculate ( eq Kt/V).

Labib S.S.,Modern Sciences and Arts University
2016 6th International Conference on Digital Information Processing and Communications, ICDIPC 2016 | Year: 2016

Brain computer interface (BCI) systems measure brain signal and translate it into control commands in an attempt to mimic specific human thinking activities. In recent years, many researchers have shown their interests in BCI systems, which has resulted in many experiments and applications. The main issue to build applicable Brain-Computer Interfaces is the capability to classify the Electroencephalograms (EEG). The purpose behind this research is to improve a model for brain signals analysis. We have used high pass filter to remove artifacts, discrete wavelet transform algorithms for feature extraction and statistical features like Mean Absolute Value, Root Mean Square, and Simple Square Integral are used, also we have used principle component analysis to reduce the size of feature vector and we used fuzzy Gaussian membership function to optimize the classification phase. It has been depicted from results that the proposed integrated techniques outperform a better performance than methods mentioned in literature. © 2016 IEEE.

Azar A.T.,Modern Sciences and Arts University
International Journal of Healthcare Technology and Management | Year: 2011

A novel system dynamics (simulation) model is developed to evaluate the effect of dialysis policies on session performance, quantify, optimise dialysis efficiency and monitor dialysis performance online. The developed system focuses on analysing and highlights factors which may alter the delivered dose and may lead to session degradation This will help increase the achievement of adequate haemodialysis to a level consistent with or higher than national adequacy statistics, in order to reduce the morbidity rate of the haemodialysis patient. The simulation results and the statistical analysis revealed that there is no statistically significant difference between the calculated results and the measured results. This system dynamics model is considered the novel system that calculates the dialysis session performance as a function of not only dialysis adequacy but also the intradialytic complications and overall equipment effectiveness. Copyright © 2011 Inderscience Enterprises Ltd.

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