The aim of the research is to identify the educational and psychological effects of the positive and negative aspects of using social networking websites. The researcher administered a number of questions to (250) users of different types of social networking websites. He analyzed his research results and obtained a number of results. The research has reached a number of recommendations and suggestion: Regulating the use of social media. Monitoring the parents of the sites used by children in a way that they do not feel they are observers. It is necessary to devote an hour daily to show the importance of real social life for children other than using social media. It is necessary to show the importance of choosing friends who have a good reputation. It is necessary to assign a little time each week to meet family outside the house or visit relatives that help children to communicate with other changing the electronic communication to the real social media. It is necessary to show television programs to alert young people to the dangers of addiction to the psychological and educational internet. It is necessary to prepare annual calendar posters that alert students in schools and universities to the type of risks, including the risks of incorrect use of the Internet. It is necessary to prepare an educational curriculum that is not intended for the exam and does not fall within the exams and grades in the schools and universities, as much as it aims to build psychological and educational values according to the customs and traditions of ancient Iraq.
RM Abbas, AA Abdulhameed, AI Salahaldin, International Conference on Geotechnical Engineering, 2010
This study focused on extracting the outer membrane nanovesicles (OMVs) from Escherichia coli BE2 (EC- OMVs) by ultracentrifugation, and the yield was 2.3mg/ml. This was followed by purification with gel filtration chromatography using Sephadex G-150, which was 2mg/ml. The morphology and size of purified EC-OMVs were confirmed by transmission electron microscopy (TEM) at 40-200 nm. The nature of functional groups in the vesicle vesicle was determined by Fourier transforms infrared spectroscopy (FT-IR) analysis. The antitumor activity of EC-OMVs was conducted in vitro by MTT assay in human ovarian (OV33) cancer cell line at 24,48 and 96hrs. The cytotoxicity test showed high susceptibility to the vesicles in ovarian compared to normal
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Forty eight isolates (41.02%) were obtained from 117 wound and burn samples. The isolates that showed high resistance for both antibiotic was two only that represent 4,1% from all isolates. The result of PCR product electrophoresis was referred that the gene is VIM gene. Lactose and raffinose showed double increasing in diameter of inhibition zone of imipenem with 1% that mean showed highest susceptibility that decreased with the concentration increasing, the same result were with meropenem. But no effect were detected on meropenem inhibition zone diameter. Mannose have no effect on the resistance in 1%, 3% and 7%. Results showed that only three case that increase the expression of gene, they were lactose at 1% concentration that increased
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Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in
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Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f
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