An observational study to discover the common conditions affecting the lumbosacral region that may affect lumbosacral position and tension. All the patients, underwent MRI exaamination (magnetic resonance imaging) in the supine position, were examined by the same consultant radiologist. The article was revised by the institutional ethical approval committee. The position of the nerve roots was observed, and the number of nerve roots was calculated anterior to a line passing between the mid-transvers process of L3(third lumbar vertebra). The number of nerve roots ahead of this line was calculated by the radiologist at the level of the right intervertebral foramen and at the left one. This procedure was applied to the normal group, an

Background: Neural tube defects (NTDs) are said to be inherited in a multifactorial fashion, i.e. genetic-environmental interaction. Maternal nutritional deficiencies had long been reported to cause NTDs, especially folate deficiency during early pregnancy. More attention had been paid to the exact mechanism by which this deficiency state causes these defects in the developing embryo. The most significant of all researches was that connecting reduced folate and increased homocysteine level in maternal serum on one hand and the risk of developing a NTD baby on the other hand. Objectives : to determine the significance of homocysteine level in Iraqi mothers who gave birth to babies with NTDs as compared to normal controls. Patients, Materials

The study employs Critical Discourse Analysis (CDA) to analyze how technological discourses are influenced by AI-generate d English texts. The research marries Fairclough’s three-dimensional discourse analysis, Van Dijk’s socio-cognitive approach, and Corpus-Assisted Discourse Studies (CADS) in the use of mixed-methods research, integrating primarily qualitative analysis with quantitative corpus-based data, to perform a thorough analysis of twenty AI-produced English texts. The findings identify the sophisticated linguistic mechanisms through which AI language employs modality, nominalization, passive voice, and interdiscursive blending to normalize and legitimize dominant contemporary ideologies. These mechanisms serve to legitimize te

Spatial Intelligence is a mental ability to understand and solve real-world problems. These visual-spatial representations are fundamental in learning various "STEM" topics, like digital drawing, art presentations, creating graphical representations, 2D designs. Opportunity to interact with real and/or virtual objects. It is a good opportunity in applying new techniques such as the augmenter, which is able to clarify mathematical tables, concepts and generalizations greatly to the visualization, understanding and mastery of concepts mathematically. The purpose of the research is to investigate impact of using AR technology in developing spatial intelligence for secondary school students, Baghdad. The quasi-experimental design was us

Background: Saliva is a specific bio-fluid with important biomarkers. Analyzing any alternation in these markers could give valuable information, in relation to oral health status parameters. The aim of this study was to investigate the level of α -amylase in unstimulated whole saliva of healthy, primary school children in relation to some oral health parameters. Materials and Methods: A questionnaires consisted of demography and medical histories of participants were filled by children families. Saliva samples were collected for 5- minutes between 9:00 -11:00 AM from 114 healthy students aged 6-13 years, divided into four age groups. Flow- rate, Plaque and Gingival Index were assessed and dentition status was investigated by DMFT/dmft

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le