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Determination of the energy and kick velocity of Crab Nebula pulsar from the distribution morphology of the remnant
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The Plerion nebula is characterized by its pulsar that fills the center of the supernova remnant with radio and X-ray frequencies. In our galaxy there are nine naked plerionic systems known, of which the Crab Nebula is the best-known example. It has been studied this instance in order to investigate how the pulsar energy affect on the distribution and evolution of the remnant as well as study the pulsar kick velocity and its influence on the remnant. From the obtained results it's found that, the pulsar of the Crab Nebula injects about (2−3)𝑥 1047 erg of energy to the remnant, although this energy is small compared to the supernova explosion energy which is about 1051 erg but still plays a significant role in the distribution and the morphology as well as the dynamical expansion of the remnant. However, most of this energy is concentrate in the direction of the pulsar rotational dipole axis which makes the remnant expanding in this direction further than other regions and consequently has more density. Moreover, it's found that the pulsar kick velocity which is in order ≈110 km.s-1 also adds an expansion energy to the remnant in the direction of the kick (North West direction) added to its initial energy and due to this kick the pulsar will be shifts to the opposite direction of the kick the South East direction, which cause the pulsar to leave its birth position and finally leave the remnant itself.

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Publication Date
Wed Jun 07 2023
Journal Name
Journal Of Educational And Psychological Researches
Parental Treatment Styles and their Relationship to Self-Efficacy among Middle School Students
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The current research aims to identify the level of parental treatment methods tolerance, hostility, strictness, and warmth, as well as the level of self-efficacy among middle school students. Moreover, it aims to identify the correlation relationship between the variables of parental treatment methods and self-efficacy among middle school students. The research sample included (150) middle school students. For achieving the objectives of the current research, the researchers adopted a scale of parental treatment methods prepared by (Zughair, 2006), and a scale of self-efficacy prepared by (Youssef, 2016), which were applied in their final form to the research sample. The research reached the following results: parents use a low-level hos

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Publication Date
Mon Apr 04 2022
Journal Name
Journal Of Educational And Psychological Researches
Stressful Life Events and their Relationship to Life Skills in Middle School Students
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The current research aims to identify the stressful life events among middle school students in terms of gender (male-female), academic branch (scientific-literary), and the Life Skills of the students of the preparatory stage in terms of gender (male-female), and academic branch (scientific-literary). Additionally, the study aims to identify the relationship between stressful life events and life skills in middle school students. A sample of (200) students who were selected randomly from the Directorate of education of Baghdad Karkh/ III was used in this study. To achieve the objectives of the current research, the researcher has adopted two scales, the stressful life events scale for the researcher Al-Sultan (2008), and the life skills

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Sun Jul 04 2010
Journal Name
Journal Of Educational And Psychological Researches
guidance program Structured to address therapeutic cognitive emotional disorders (Anxiety and depression model)
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           Is one of the processes of educational guidance to help the individual to design educational plans that fit with the abilities and inclinations and goals.
And research aims the current instruction program heuristic therapeutic knowledge to deal with emotional disorders. And may the researcher instruct a program according to the theories of interested and competent guidance to education and has studied the large number of studies available in this field, as has been the program on a number of specialists in education and Psychology and took their views. And then was adopted the final version of the indicative program, consistent with the sample, which was built

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Composites Science
Sawdust-Based Concrete Composite-Filled Steel Tube Beams: An Experimental and Analytical Investigation
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Incorporating waste byproducts into concrete is an innovative and promising way to minimize the environmental impact of waste material while maintaining and/or improving concrete’s mechanical characteristics and strength. The proper application of sawdust as a pozzolan in the building industry remains a significant challenge. Consequently, this study conducted an experimental evaluation of sawdust as a fill material. In particular, sawdust as a fine aggregate in concrete offers a realistic structural and economical possibility for the construction of lightweight structural systems. Failure under four-point loads was investigated for six concrete-filled steel tube (CFST) specimens. The results indicated that recycled lightweight co

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Publication Date
Fri Jan 01 2021
Journal Name
Materials Today: Proceedings
Response surface methodology: A review on its applications and challenges in microbial cultures
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Publication Date
Sat Nov 01 2025
Journal Name
Journal Of Molecular Liquids
Chitosan salt as a dual-function agent for CO₂ sequestration and acidizing enhancement
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The utilization of carbon dioxide (CO₂) to enhance wellbore injectivity presents a cost-effective and sustainable strategy for mitigating greenhouse gas emissions while improving reservoir performance. This study introduces an environmentally friendly method employing a water-soluble chitosan salt (CS) that generates a carbonated-rich acid solution upon contact with dry CO₂ at 25 °C and 508 psi. CS solutions (100–2000 ppm) were prepared and evaluated for CO₂ uptake, acid generation, and rheological behavior. Results show that 1000 ppm achieves an optimal CO2 uptake (2612 mg/l), with moderate viscosity increase (from 1.52 to 3.37 cp), while higher concentrations exhibit a sharp rise due to polymer-like network formation. Core floodi

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Industrial And Engineering Chemistry
Petroleum refinery wastewater treatment using a novel combined electro-Fenton and photocatalytic process
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Publication Date
Tue Jun 23 2015
Journal Name
Nature Communications
A metabolic stress-inducible miR-34a-HNF4α pathway regulates lipid and lipoprotein metabolism
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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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