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Amal G. Ramadan(Amal G. Ramadan ),Ahmed A. M. Yassein(Ahmed A. M. Yassein ),Eissa A. Eissa(Eissa A. Eissa ),Gamal M. Hassan(Gamal M. Hassan ) 한국축산식품학회 2022 Food and Life Vol.2022 No.3
Zinc oxide nanoparticles (ZnO-NPs) are regularly utilized in the food and fertilizers industries. In our investigation, rats received oral administration of ZnO NPs with a particle size of 30±5 nm once daily at doses of 100, 200, 300, 400, and 600 mg/kg for ten weeks in order to assess the genotoxic effect. Impacts on hematological markers, genotoxic impact, and growth were investigated. The findings showed that ZnO-NPs significantly reduced body weight gain, red blood cell count (RBC), hemoglobin concentration (Hb), hematocrit value (HCT), and platelet count (PLT), while increasing white blood cell (WBC), mean capsular volume (MCV), mean capsular hemoglobin (MCH), and mean capsular hemoglobin concentration (MCHC) in the treated rats. Our results for the comet assay and micronuclei test show a dosage-dependent increase in DNA fragmentation, which was supported by an increase in the percentage of DNA that is tailed, the length and intensity of DNA tails, and the tail moment, especially at the dose of 600 mg/kg. According to the findings, the frequency of micronucleated cells has increased.
Eissa Mohamed El-Moghawry Shokir,Emad Souliman Al-Homadhi,Osama Al-Mahdy,Ayman Abdel-Hamid El-Midany 한국화학공학회 2014 Korean Journal of Chemical Engineering Vol.31 No.8
This paper presents the application of artificial neural networks (ANN) to develop new models of liquidsolvent dissolution of supercritical fluids with solutes in the presence of cosolvents. The neural network model of theliquid solvent dissolution of CO2 was built as a function of pressure, temperature, and concentrations of the solutesand cosolvents. Different experimental measurements of liquid solvent dissolution of supercritical fluids (CO2) withsolutes in the presence of cosolvents were collected. The collected data are divided into two parts. The first part wasused in building the models, and the second part was used to test and validate the developed models against the Peng-Robinson equation of state. The developed ANN models showed high accuracy, within the studied variables range,in predicting the solubility of the 2-naphthol, anthracene, and aspirin in the supercritical fluid in the presence and absenceof co-solvents compared to (EoS). Therefore, the developed ANN models could be considered as a good tool in predictingthe solubility of tested solutes in supercritical fluid.
Eissa, Alaa E.,Zaki, Manal M.,Aziz, A. Abdel Korean Society for Bioinformatics 2010 Interdisciplinary Bio Central (IBC) Vol.2 No.2
Flavobacterium columnare (F. columnare), the dermotropic Gram negative yellow pigmented bacteria was isolated from different sites of skin ulcerations in the Nile tilapia (Oreochromis niloticus) and Nile catfish (Clarias gariepinus) collected from an earthen pond located at an aquaculture station in Sharkiya Province, Lower Egypt during an acute episode of mass kills during the early summer of 2009. An acute infection with F. columnare was behind the emergent event of mass mortalities among both populations. Many of the Nile tilapias exhibited typical signs of hole - in- the head like lesions from which F. columnare together with the myxosporean spore, Myxobolus tilapiae (M. tilapiae) were retrieved. Most of the cohabitating infected Nile catfishes exhibited severe form of saddle back like ulcer. The identities of the retrieved isolates were confirmed using morphological, biochemical and molecular tools. The research lead us to conclude that the two diverse etiological agents (F. columnare and M. tilapiae) under the triggering effect of the abrupt change in the water quality measures (abrupt rise in the water temperature, ammonia, pH, sharp decrease in dissolved oxygen) have synergized together to induce the above mentioned pathology with the consequent reemergence of fish mass mortalities.
Assessment of Wind Power Prediction Using Hybrid Method and Comparison with Different Models
Mohammed Eissa,Yu Jilai,Wang Songyan,Peng Liu 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.3
This study aims at developing and applying a hybrid model to the wind power prediction (WPP). The hybrid model for a very-short-term WPP (VSTWPP) is achieved through analytical data, multiple linear regressions and least square methods (MLR&LS). The data used in our hybrid model are based on the historical records of wind power from an offshore region. In this model, the WPP is achieved in four steps: 1) transforming historical data into ratios; 2) predicting the wind power using the ratios; 3) predicting rectification ratios by the total wind power; 4) predicting the wind power using the proposed rectification method. The proposed method includes one-step and multi-step predictions. The WPP is tested by applying different models, such as the autoregressive moving average (ARMA), support vector machine (SVM), and artificial neural network (ANN). The results of all these models confirmed the validity of the proposed hybrid model in terms of error as well as its effectiveness. Furthermore, forecasting errors are compared to depict a highly variable WPP, and the correlations between the actual and predicted wind powers are shown. Simulations are carried out to definitely prove the feasibility and excellent performance of the proposed method for the VSTWPP versus that of the SVM, ANN and ARMA models.
Mahmoud A. Eissa 장전수학회 2019 Proceedings of the Jangjeon mathematical society Vol.22 No.1
Recently, there is growing interest in developing new numerical methods for stochastic dierential equations (SDEs), in order to improve the stability of approximation solution. There are many numerical methods have been constructed based on a Milstein scheme for SDEs. However, there exists very little results on the stability analysis of Milstein type methods for SDEs. This paper is concerned with mean-square (MS) stability of the semi-implicit theta Milstein methods and drifting split-step theta Milstein methods for nonlinear stochastic dierential equations. Under a coupled condition on the drifting and diusion coecients, it is proved that, the methods with > 1 2 are unconditionally preserve the MS-stability of the SDEs. For 2 [0; 1 2 ], the methods are MS-stable for some small step-size. This work is dierent from the previous works such that we could get rid of the restrictions that existed on the step-size of two classes Milstein methods for a symptomatic mean-square stability of the non-linear stochastic dierential equations, under Local lipschitz condition. Numerical experiments are given to demonstrate the conclusions.
The Liquidity of Indian Firms: Empirical Evidence of 2154 Firms
AL-HOMAIDI, Eissa A.,TABASH, Mosab I.,AL-AHDAL, Waleed M.,FARHAN, Najib H.S.,KHAN, Samar H. Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.1
This paper aims to empirically study the determinants of liquidity of Indian listed firms. To account for profit persistence, we apply a (pooled, fixed and random) effect models to a panel of Indian listed firms that covers the time period from 2010 to 2016. This study consists of 2154 firms operating in Indian market. Liquidity (LQD) of Indian firms is measured by liquid assets to total assets, whereas bank size, capital adequacy, profitability, leverage, and firm age are used as internal determinants. Further, economic activity, inflation rate, exchange rate, and interest rate are the external factors considered. The findings reveal that leverage, return on assets, and firm age are the essential internal determinants that impact the liquidity of Indian listed firms. Furthermore, among the internal determinants, the results indicate that firm size, leverage ratio, return on assets ratio, and firm age are found to have a significant positive association with firms' LQD, except leverage ratio and firm age has a negative relationship with firms' LQD. From this result, this article has provides helpful ideas and empirical evidence on the inner and external determinants of the companies mentioned in India is very useful to bankers, analysts, regulators, investors and other stakeholders.
Multimodal Interaction Framework for Collaborative Augmented Reality in Education
Asiri, Dalia Mohammed Eissa,Allehaibi, Khalid Hamed,Basori, Ahmad Hoirul International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.7
One of the most important technologies today is augmented reality technology, it allows users to experience the real world using virtual objects that are combined with the real world. This technology is interesting and has become applied in many sectors such as the shopping and medicine, also it has been included in the sector of education. In the field of education, AR technology has become widely used due to its effectiveness. It has many benefits, such as arousing students' interest in learning imaginative concepts that are difficult to understand. On the other hand, studies have proven that collaborative between students increases learning opportunities by exchanging information, and this is known as Collaborative Learning. The use of multimodal creates a distinctive and interesting experience, especially for students, as it increases the interaction of users with the technologies. The research aims at developing collaborative framework for developing achievement of 6th graders through designing a framework that integrated a collaborative framework with a multimodal input "hand-gesture and touch", considering the development of an effective, fun and easy to use framework with a multimodal interaction in AR technology that was applied to reformulate the genetics and traits lesson from the science textbook for the 6th grade, the first semester, the second lesson, in an interactive manner by creating a video based on the science teachers' consultations and a puzzle game in which the game images were inserted. As well, the framework adopted the cooperative between students to solve the questions. The finding showed a significant difference between post-test and pre-test of the experimental group on the mean scores of the science course at the level of remembering, understanding, and applying. Which indicates the success of the framework, in addition to the fact that 43 students preferred to use the framework over traditional education.
E. Salam,M.M. Eissa,A.S. Tageldin 한국원자력학회 2019 Nuclear Engineering and Technology Vol.51 No.3
In the present study, a series of tungsten austenitic stainless steel alloys have been developed byinterchanging the molybdenum in standard SS316 by tungsten. This was done to minimize the long-liferesidual activation occurred in molybdenum and nickel after decommissioning of the power plant. Themicrostructure and mechanical properties of the prepared alloys are determined. For the sake ofincreasing multifunction property of such series of tungsten-based austenitic stainless steel alloys,gamma shielding properties were studied experimentally by means of NaI(Tl) detector and theoreticallycalculated by using the XCOM program. Moreover, fast neutrons macroscopic removal cross-section beencalculated. The obtained combined mechanical, structural and shielding properties indicated that themodified austenitic stainless steel sample containing 1.79% tungsten and 0.64% molybdenum has preferableproperties among all other investigated samples in comparison with the standard SS316. Theseproperties nominate this new composition in several nuclear application domains such as, nuclearshielding domain.