Search results for: Taysir Soliman

Authors: A. A. Soliman

Abstract:

The Modified Regularized Long Wave (MRLW) equation is solved numerically by giving a new algorithm based on collocation method using quartic B-splines at the mid-knot points as element shape. Also, we use the fourth Runge-Kutta method for solving the system of first order ordinary differential equations instead of finite difference method. Our test problems, including the migration and interaction of solitary waves, are used to validate the algorithm which is found to be accurate and efficient. The three invariants of the motion are evaluated to determine the conservation properties of the algorithm. The temporal evaluation of a Maxwellian initial pulse is then studied.

Keywords: collocation method, MRLW equation, Quartic B-splines, solitons

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Authors: Abdel-Maksoud Abdel-Kader Soliman

Abstract:

The General Regularized Long Wave (GRLW) equation is solved numerically by giving a new algorithm based on collocation method using quartic B-splines at the mid-knot points as element shape. Also, we use the Fourth Runge-Kutta method for solving the system of first order ordinary differential equations instead of finite difference method. Our test problems, including the migration and interaction of solitary waves, are used to validate the algorithm which is found to be accurate and efficient. The three invariants of the motion are evaluated to determine the conservation properties of the algorithm.

Keywords: generalized RLW equation, solitons, quartic b-spline, nonlinear partial differential equations, difference equations

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Authors: Hanan A. Soliman, Mohamed A. El-Desouky, Walaa G. Hozayen, Rasha R. Ahmed, Amal K . Khaliefa

Abstract:

Aim: The objective of this study is to investigate the hypoglycemic, hypolipidemic, and hepatoprotective effects of the aqueous extract of parsley, basil, and chicory whole plant in normal and dexamethasone (Dex) rats. Materials and Methods: 50 female albino rats were used in this study and divided into 5 groups (for each 10). Group (1) fed basal diet and maintained as negative control group. Group (2) received Dex in a dose of (0.1 mg/kg b. wt.). Groups 3, 4, and 5 were treated with Dex along with three different plant extracts of parsley, basil, and chicory (2 g/kg b. wt.), (400 mg/kg b. wt.), and (100 mg/kg b. wt.), respectively. Results: All these groups were treated given three times per week for 8 consecutive weeks. Dex-induced alterations in the levels of serum glucose, triglyceride, cholesterol, low-density lipoprotein-cholesterol levels and cardiovascular indices and serum alanine aminotransferase, aspartate aminotransferase and lactate dehydrogenase activities, liver thiobarbituric acid (TBARS) levels increased, while high-density lipoprotein-cholesterol, total protein, albumin, and liver glutathione (GSH) levels decreased. On the other hand, plant extracts succeeded to modulate these observed abnormalities resulting from Dex as indicated by the reduction of glucose, cholesterol, TBARS, and the pronounced improvement of the investigated biochemical and antioxidant parameters. Conclusions: It was concluded that probably, due to its antioxidant property, parsley, basil, and chicory extracts have hepatoprotective effects in Dex-induced in rats.

Keywords: antioxidants, dexamethasone, hyperglycemia, hyperlipidemia

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Authors: M. E. Kolpakova, A. A. Jakovleva, L. S. Poliakova, H. El Amghari, S. Soliman, D. R. Faizullina, V. V. Sharoyko

Abstract:

Brain neuroplasticity is associated with blood-brain barrier vascular endothelial proteoglycans and post-stroke microglial activation. The study of the mechanisms of reperfusion injury limitation by remote ischemic postconditioning (RC) is of interest due to the effects on functional recovery after cerebral ischemia. The goal of the study is the assessment of the role of syndecan-1 (SDC-1) in restriction of ischemic-reperfusion injury on middle cerebral artery model in rats using RC protocol. Randomized controlled trials were conducted. Ischemia was performed by middle cerebral artery occlusion by Belayev L. (1996) on the Wistar rat-males (n= 87) weighting 250 ± 50 g. under general anesthesia (Zoletil 100 и Xylazine 2%). Syndecan-1 (SDC-1) concentration difference in plasma samples of false operated animals and animals with brain ischemia was 30% (30 min. МСАо: 41.4 * ± 1.3 ng/ml). SDC-1 concentration in animal plasma samples with ischemia + RC protocol was 112% (30 min МСАо+ RC): 67.8**± 5.8 ng/ml). Calculation of infarction volume in the ischemia group revealed brain injury in 31.97 ± 2.5%; the volume of infarction was 13.6 ± 1.3% in 30 min. МCАо + RC group. Swelling of tissue in the group 30 min. МCАо + RC was 16 ± 2.1%; it was 47 ± 3.3%. in 30 min. МCАо group. Correlation analysis showed a high direct correlation relationship between infarct area and muscle strength in the right forelimb (КК=0.72) in the 30 min. МCАо + RC group. Correlation analysis showed very high inverse correlation between infarct area and capillary blood flow in the 30 min. МCАо + RC group (p <0.01; r = -0.98). We believe the SDC-1 molecule in blood plasma may play role of potential messenger of ischemic-reperfusion injury restriction mechanisms. This leads to infarct-limiting effect of remote ischemic postconditioning and early functioning recovery.

Keywords: ischemia, МСАо, remote ischemic postconditioning, syndecan-1

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Authors: Hozaifa Zaki, Ghada Soliman

Abstract:

In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.

Keywords: computer vision, deep learning, image processing, character recognition

Procedia PDF Downloads 78