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The Impact of using the Internet and Social Media on Sleep in a group of Secondary School Students from Baghdad
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Background: Insufficient sleep due to excessive media use is linked to decrease physical activity, poor nutrition, obesity, and decreased overall health-related quality of life.

Objectives: To assess the effect of using the internet and social media on the sleep of 4th-stage secondary school students.

Subjects and Methods: Cross-sectional study with the analytic element; for 500 secondary school students, obtained by choosing two schools randomly from each of the six educational directorates, by using a structured questionnaire.

Result: Secondary school students are involved in this study (n = 500). The study reveals that the majority of students 350 (69.7 %) were aged group (16) years old, Regarding the internet, used by the majority of the 454(90.4%), and 419 (83.5%) students had a mobile phone, 206(41.1%) of them using the internet more than 150 hours per month and concerning the students sleep; Unexplained tiredness in the morning 182(36.3%) was sometimes complained from it, about Nightmares, 187(37.3%) of students sometimes having it, 276(55%) of them wake up during sleep.

 Conclusion: students are using the internet more than one-fifth of their time per month, there is an association between the use of social media and short sleep duration among secondary school students that increases daytime sleepiness, unexplained tiredness in the morning, and nightmares.

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Publication Date
Fri Feb 20 2026
Journal Name
Journal Of Physical Education
Some Biomechanical Limitation During Acceleration Phase and Its Relationship With (110) m Hurdles Achievement for Advance Runners
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Publication Date
Mon Aug 08 2022
Journal Name
Egyptian Journal Of Chemistry
Synthesis, Characterization, Spectroscopic, Thermal and Biological Studies for New Complexes with N1, N2-bis(3-hydroxyphenyl) Oxalamide
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Publication Date
Mon Jun 30 2014
Journal Name
Al-kindy College Medical Journal
Relationship between very low birth weight neonates and increased neonatal mortality for age 0 to 7 days
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Background: Very low birth weight (VLBW) neonates constitute approximately 4–7 percent of all live births and their mortality is very high.
Objective: to find out if there is a relationship between Very Low Birth Weight Neonates and increased neonatal mortality for age 0 to 7 days.
Methods: A retrospective study of VLBW neonates admitted to NICU at Ibn Al- Baladi Pediatrics and Maternity hospital over one year (2012)were studied, The study period was from April till August 2013. Exclusion criteria were: (1) neonates weighing less than 700 g and with gestational age less than 24 weeks (abortion) (2) death in the delivery room (3) neonates weighing more than 1500 g. (4) Postnatal age more than 7 days. The outcome measure was in-hos

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Publication Date
Thu Jan 30 2014
Journal Name
Al-kindy College Medical Journal
Relationship between Very Low Birth Weight Neonates and increased Neonatal mortality for age 0 to 7 days
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B aa cc kk gg r oo uu nn dd : Very low birth weight (VLBW) neonates constitute approximately 4–7 percent of all live births and their mortality is very high. O bb j ee cc t i vv ee: to find out if there is a relationship between Very Low Birth Weight Neonates and increased neonatal mortality for age 0 to 7 days. M ee t hh oo dd ss A retrospective study of VLBW neonates admitted to NICU at Ibn Al- Baladi Pediatrics and Maternity hospital over one year (2012)were studied, study period was from April till August 2013. Exclusion criteria were: (1) neonates weighing less than 700 g and with gestational age less than 24 weeks (abortion) (2) death in the delivery room (3) neonates weighing more than 1500 g. (4) Postnatal age more than 7 days.

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Publication Date
Fri May 28 2021
Journal Name
Journal Of Microbiology And Biotechnology
Bioactive Levan-Type Exopolysaccharide Produced by <i>Pantoea agglomerans</i> ZMR7: Characterization and Optimization for Enhanced Production
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Publication Date
Thu May 05 2022
Journal Name
Karbala International Journal Of Modern Science
Nigella sativa Methanol Extract Inhibits PC-3 Cell Line Colonization, Induced Apoptosis, and Modulated LC3-based Autophagy
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Nigella sativa has various pharmacological properties and has been used throughout history for a variety of reasons. However, there is limited data about the effects of N. sativa (NS) on human cancer cells. This study aimed at observing the roles of methanolic extract of N. sativa on apoptosis and autophagy pathway in the Human PC3 (prostate cancer) cell line. The cell viability was checked by MTT assay. Clonogenic assay was performed to demonstrate clonogenicity and Western blot was used to check caspase-3, TIGAR, p53, and LC3 protein expression. The results demonstrated that PC3 cell proliferation was inhibited, caspase-3 and p53 protein expression was induced, and LC3 protein expression was modulated. The clonogenic assay showed that PC3

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Intelligent EMG Pattern Recognition Control Method for Upper-Limb Multifunctional Prostheses: Advances, Current Challenges, and Future Prospects
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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Solar ray tracing programs to find new types of solar
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Anew Solar concentrator have been designed in this paper, this concentrators Were based on the total internal reflection in a prism, the prism angles has been calculated by depending on the solar incident ray angle in baghdad for a year. The optical design consist ofa triangular presume, Where the solar cells on one side of the prism Wh?le the prism head towered the south. The results show that there is an increasing in the solar ray concentrators and the cell area is reduced.

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Publication Date
Sat Feb 01 2020
Journal Name
International Journal Of Computer Science And Mobile Computing
Hierarchical Fixed Prediction of Mixed based for Medical Image Compression.
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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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