Browsing by Author "Hassan S.M."

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    Brain Cortical and Hippocampal Dopamine: A New Mechanistic Approach for Eurycoma longifolia Well-Known Aphrodisiac Activity and Its Chemical Characterization
    (Hindawi Limited, 2019) Ezzat, Shahira M; Ezzat M.I.; Okba M.M.; Hassan S.M.; Alkorashy A.I.; Karar M.M.; Ahmed S.H.; Mohamed S.O.; Fernandes G.; Pharmacognosy Department; Faculty of Pharmacy; Cairo University; Kasr El-Ainy Street; Cairo; 11562; Egypt; Pharmacognosy Department; Faculty of Pharmacy; October University for Modern Science and Arts (MSA); 6th of October 12566; Egypt; Department of Biochemistry; Faculty of Science; Ain Shams University; Cairo; Egypt; Department of Biochemistry; Faculty of Pharmacy; Al-Azhar University; Cairo; Egypt; Zewail City of Science and Technology; Cairo; Egypt; Department of Biochemistry; Faculty of Agriculture; Cairo University; Cairo; Egypt; School of Pharmaceutical Sciences; Universiti Sains Malaysia; Malaysia
    Eurycoma longifolia Jack (Fam.: Simaroubaceae), known as Tongkat Ali (TA), has been known as a symbol of virility and sexual power for men. Metabolic profiling of the aqueous extract of E. longifolia (AEEL) using UPLC-MS/MS in both positive and negative modes allowed the identification of seventeen metabolites. The identified compounds were classified into four groups: quassinoids, alkaloids, triterpenes, and biphenylneolignans. AEEL is considered safe with oral LD50 cut-off >5000 mg/kg. Oral administration of 50, 100, 200, 400, or 800 mg/kg of AEEL for 10 consecutive days to Sprague-Dawley male rats caused significant reductions in mounting, intromission, and ejaculation latencies and increased penile erection index. AEEL increased total body weight and relative weights of seminal vesicles and prostate. Total and free serum testosterone and brain cortical and hippocampal dopamine content was significantly elevated in treated groups with no significant effects on serotonin or noradrenaline content. 2019 Shahira M. Ezzat et al.
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    Rule-based approach for enhancing the motion trajectories in human activity recognition
    (2010) Hassan S.M.; Al-Sadek A.F.; Hemayed E.E.; Computer Science Dept.; October University for Modern Sciences and Arts; MSA; Egypt; Computer Engineering Dept.; Faculty of Engineering; Cairo University; Giza; Egypt
    In this paper, we propose a rule-based system for semantically understanding and analyzing the motion of the trajectories of the human activity. The proposed system can be used as a preprocessing phase for enhancing the object detection process. Detected trajectories are classified into three categories; normal, semi-normal and abnormal trajectories according to the distances between their adjacent points. Abnormal trajectories are removed from the trajectory space. Semi-normal trajectories are broken into small normal trajectories that are linked later to form a longer normal trajectory. The proposed system does not assume a specific trajectory length and hence is more generic than similar trajectory enhancement approaches. The effectiveness of the proposed approach is demonstrated through several experimental results using known human motion datasets. � 2010 IEEE.