Background: Levetiracetam is a member of the new antiepileptic drugs and has a broad spectrum effect, used as an adjunctive therapy in addition to monotherapy in the treatment of partial onset-seizures. The effect of levetiracetam on the development of embryo nervous system after maternal exposure during pregnancy has not been identified. Objective: to evaluate the effect of antiepileptic drug, levetiracetam (LEV) within its therapeutic dose 350mg/Kg body weight on albino female rat to clarify its effect on the developing cerebral cortex histologically. Material And Methods: Ten pregnant female rats were separated into two groups, control group and experimental group. They were obtained from the animal house of the high institute of infertility diagnosis and assisted reproductive technologies/Al-Nahrain university. They were maintained in environmentally controlled room at a temperature of 21–28±4Cº, 40–60% humidity, 12 hours light-dark cycle, in a noise free environment. Oral administration of 350mg/Kg of LEV to the experiment group while physiologic saline was given to control group. Results: microscopic assessment of the cerebral cortex defects in the cerebrum of the treated group when compared with the control group. There was disorganization of the cortical layers where boundaries were dimmed, the depth of the six layers were overlapping, decreased proportion of the stellate cells in the external granular layer therefore, reducing layer outline, vascular congestion and hemorrhage. Furthermore, observation shows cellular degeneration, necrosis, and nucleus karyorrhexis. Conclusion: this study demonstrate that they must take care from giving Levetiracetam to pregnant female because it induces histological changes in the brain of the newborn rat.
The drones have become the focus of researchers’ attention because they enter into many details of life. The Tri-copter was chosen because it combines the advantages of the quadcopter in stability and manoeuvrability quickly. In this paper, the nonlinear Tri-copter model is entirely derived and applied three controllers; Proportional-Integral-Derivative (PID), Fractional Order PID (FOPID), and Nonlinear PID (NLPID). The tuning process for the controllers’ parameters had been tuned by using the Grey Wolf Optimization (GWO) algorithm. Then the results obtained had been compared. Where the improvement rate for the Tri-copter model of the nonlinear controller (NLPID) if compared with
A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video str
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac
... Show MoreIn this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.
This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio
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The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra
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