This study aimed to assess orthodontic postgraduate students’ use of social media during the COVID-19 lockdown. Ninety-four postgraduate students (67 master’s students and 27 doctoral students) were enrolled in the study and asked to fill in an online questionnaire by answering questions regarding their use of social media during the COVID-19 lockdown. The frequency distributions and percentages were calculated using SPSS software. The results showed that 99% of the students used social media. The most frequently used type of social media was Facebook, 94%, followed by YouTube, 78%, and Instagram, 65%, while Twitter and Linkedin were used less, and no one used Blogger. About 63% of the students used elements of social media to l

In order to study the effect of inoculation with mycorrhiza and fertilization with plant residues on the growth of plants, we used two factors: the first two levels of mycorrhiza inoculation, Glumus mossea (0 and 10 g.pot-1) and the second factor, four levels of plant residues (10 g.pot-1) celery plant residues, 10 g pot-1 mint residues, and 10 g pot-1 black bean seed residues. Mychorrizal treatment (10 g pot-1) increased the number of mycorrhiza spores and the infection percentage of mycorrhizal by 917.44% and 13088.23%, respectively; celery treatment (10 g.pot-1) increased the chlorophyll index in the leaves and height of the chard plant by 31.34% and 94.04%, respectively; and black seed treatment (10 g.pot-1) increased the percen

The research aimed to identify “The impact of an instructional-learning design based on the brain- compatible model in systemic thinking among first intermediate grade female students in Mathematics”, in the day schools of the second Karkh Educational directorate.In order to achieve the research objective, the following null hypothesis was formulated:There is no statistically significant difference at the significance level (0.05) among the average scores of the experimental group students who will be taught by applying an (instructional- learning) design based to on the brain–compatible model and the average scores of the control group students who will be taught through the traditional method in the systemic thinking test.The resear

An experimental and numerical study has been carried out to investigate the heat transfer by natural convection and radiation in a two dimensional annulus enclosure filled with porous media (glass beads) between two horizontal concentric cylinders. The outer cylinders are of (100, 82 and70mm) outside diameters and the inner cylinder of 27 mm outside diameter with (or without) annular fins attached to it. Under steady state condition; the inner cylinder surface is maintained at a high temperature by applying a uniform heat flux and the outer cylinder surface at a low temperature inside a freezer. The experiments were carried out for an annulus filled with
glass beads at a range of modified Rayleigh number (4.9 ≤ Ra≤ 69), radiation

The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims