This study was aimed to explore the impact of a practical program on supporting and reducing
symptoms of school bulling victims in a sample of student in the sixth grade. The study sample consisted of (18)
students that have been chosen from two schools (Al-Abass and Alataa’) it was an intended sample, because
there were enough student with high scores in bulling victims diagnostics test, the sample was divided into two
groups: the control group of (9) student from (Alataa’) school, and the experimental group consisted of (9)
student from Alabass) school keeping in mind to keep the two groups equivalent in maintaining equal controls.
The researcher applied the practical program which is based on cognitive behavioral therapy with the
individuals of the experimental group. The program consisted of 13 sessions, 50 minutes each. The control group did not receive any treatment. To achieve the purpose of the study, school bulling diagnosis have been applied to chose the sample of the study, a scale was also used on bulling victims to know the intensity or level of bulling the victims have been exposed to. Data was analyzed statistically based on tests of (Wilcoxon) and (Mann Witney) to measure the effect of the treatment in school bulling victims. Results show significant differences between the two tests pre and after in favor of the experiment group after applying the program, the other hand there wasn’t any differences in the pre and after test in the control group.
While conservative access preparations could increase fracture resistance of endodontically treated teeth, it may influence the shape of the prepared root canal. The aim of this study was to compare the prepared canal transportation and centering ability after continuous rotation or reciprocation instrumentation in teeth accessed through traditional or conservative endodontic cavities by using cone-beam computed tomography (CBCT).
Forty extracted intact, matured, and 2-rooted human maxillary first premolars were selected for this
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In this study, manganese dioxide (MnO₂) nanoparticles (NPs) were synthesized via the hydrothermal method and utilized for the adsorption of Janus green dye (JG) from aqueous solutions. The effects of MnO₂ NPs on kinetics and diffusion were also analyzed. The synthesized NPs were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray analysis (EDX), and Fourier-transform infrared spectroscopy (FT-IR), with XRD confirming the nanoparticle size of 6.23 nm. The adsorption kinetics were investigated using three models: pseudo-first-order (PFO), pseudo-second-order (PSO), and the intraparticle diffusion model. The PSO model provided the best fit (R² = 0.999), indicating that the adsorpti
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Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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