In the current paper, the effect of fear in three species Beddington–DeAngelis food chain model is investigated. A three species food chain model incorporating Beddington-DeAngelis functional response is proposed, where the growth rate in the first and second level decreases due to existence of predator in the upper level. The existence, uniqueness and boundedness of the solution of the model are studied. All the possible equilibrium points are determined. The local as well as global stability of the system are investigated. The persistence conditions of the system are established. The local bifurcation analysis of the system is carried out. Finally, numerical simulations are used to investigate the existence of chaos and understand the effect of varying the system parameters. It is observed that the existence of fear up to a critical value has a stabilizing effect on the system; otherwise it works as an extinction factor in the system.
The design studies, especially in their contemporary stages, have not been isolated from the subjects that underpin advanced ideas in the field of technical treatments that enrich and improve the social life of users through those technological innovations that have enhanced and changed life styles, Especially in the field of general institutional techniques, including cinemas, as the ideal places for people and visitors to this space, which can contribute to the promotion of cultural, social and technical aspects within this millennium. DONC as reflected on the positive communication and communication between the intellectual and cognitive develop individuals, including cultural and technical side of the individual. The first chapter co
... Show Moreأن الثورة الرقمية أصبحت اليوم واقع حتمي نعيشه من حيث القت بظلالها على مختلف جوانب الحياة، ولم يخل المسرح من هذا التأثير وخاصة في ظهور ملامح ما بعد الحداثة بكل ما تحملهُ من رؤى فكرية وفلسفية وجمالية، مع ذلك التطور التكنولوجي في هذا السياق يسعى المسرحيون والمخرجون والممثلون الى تأسيس علاقات فاعلة مع شبكات الانترنيت والوسائط الرقمية مما ظهر العديد من المواقع المهتمة بالمسرح. من هنا ظهرت اهمية الربط بين الث
... Show MoreIn this paper, a mathematical model for the oxidative desulfurization of kerosene had been developed. The mathematical model and simulation process is a very important process due to it provides a better understanding of a real process. The mathematical model in this study was based on experimental results which were taken from literature to calculate the optimal kinetic parameters where simulation and optimization were conducted using gPROMS software. The optimal kinetic parameters were Activation energy 18.63958 kJ/mol, Pre-exponential factor 2201.34 (wt)-0.76636. min-1 and the reaction order 1.76636. These optimal kinetic parameters were used to find the optimal reaction conditions which
... Show MoreIn this paper, we employ the maximum likelihood estimator in addition to the shrinkage estimation procedure to estimate the system reliability (
Methotrexate is a folate antimetabolite chemical used to treat many forms of cancer and cleared mainly by kidney which result in a nephrotoxicity as a major complication of methotrexate. Trivalent chromium complex, chromium picolinate (CrPic), is mostly utilized to regulate glucose and raise insulin sensitivity—particularly in diabetes. The objective of this study was to assess the renoprotective effects of Chromium in mitigating nephrotoxicity induced by Methotrexate in rats. Study conducted on 32 male rats divided into 4 groups; Group I (Control group) in which rats received distilled water orally for 8 days, Group II (Induction group) which received a single intraperitoneal injection of Methotrexate (20 mg/kg) on
... Show MoreIn this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.
After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
... Show MoreIn present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.