Abstract: Choosing suitable artificial teeth for partially edentulous patients and arranging these teeth in a way to look natural is difficult. An important factor in dentures construction is the mesiodistal width of anterior teeth, because a denture would not appearance natural if artificial teeth are of incorrect size. While for a successful orthodontic treatment, mesiodeistal width of teeth is important for space analysis and for establishing proper occlusion. The aim of this study is to determine the correlation between the average mesiodistal width of anterior and posterior teeth in male and female Iraqi population. 40 Iraqi subjects with normal occlusion participated in this study. Mesiodistal measurement of all teeth was carried out

Abstract The purpose of this paper is preparing exercises according to some biomechanical variables for women with low back pain and identifying the effect of exercise according to some biomechanical variables and relieving lower back pain for women. The researchers used the one-group experimental design. The sample was chosen by the intentional method to provide the necessary conditions for conducting the study, and they represent the research community and its sample. The researchers also excluded (2) of the injured women because they did not adhere to the rehabilitation sessions, and for the purpose of ensuring the homogeneity of the sample members, the researchers used the arithmetic mean, standard deviation, and the torsion coefficient

Objectives: To identify the impact of the brain consensus model on the acquisition of Arabic grammar concepts among students in the fourth grade, methodology: The pilot curriculum was used, and a partial control pilot design was adopted. There were 30 female students in the pilot group, 30 female students in the control group, and the two researchers were statistically rewarded among the two groups' students in some variables and used appropriate statistical means to analyse the results, including the test for two independent samples, the square (c2) and the Alpha Kronbach equation.Results: The pilot group outperformed the control group. The results showed that there is a significant statistical difference at the indicative level (0.05) for

While traditional energy sources such as oil, coal, and natural gas drive economic growth, they also seriously affect people’s health and the environment. Renewable energies (RE) are presently seen as an efficient choice for attaining long-term sustainability in development. They provide an adequate response to climate change and supply sufficient electricity. The current situation in Iraq results from a decades-long scarcity of reliable electricity, which has impacted various industries, including agriculture. There are diverse prospects for using renewable energy sources to address the present power crisis. The economic and environmental impacts of renewable energy systems were investigated in this study by using the solar pumpi

Purpose: To identify the size of the food gap for the main agricultural products and crops in Iraq, which reflects to us the extent to which agricultural production in particular and the agricultural sector in general have declined.Theoretical framework: The theoretical side of the research dealt with the definition of self-sufficiency and the food gap, as well as identifying the reality of agricultural production in Iraq during the study period, as well as the reality of the food gap for the most important agricultural, plant and animal products.Design/methodology/approach: In reviewing the research problem, the researcher adopted the method of deductive and descriptive analysis based on the presentation and detail of official data

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T