Aim of the study is to find any correlation between obesity (insulin resistance) and type I diabetes in children. Obesity and diabetes mellitus are the common health problems, and obesity is common cause of the insulin resistance. The results revealed marked increased in glucose, insulin, HbAlc and insulin resistance in obese diabetic type I patients comparing to control group they were obese and non-obese found to be within normal values for glucose, insulin, FIbAlc , and insulin resistance.

Abstract* Backgrounds The retention of the maxillary complete denture may be influenced by adequate recording in the patient’s mouth, marking, and carving of the post-dam on the maxillary cast. Failure to do so may lead to loss of retention. Successful denture construction with patient’s comfort could be achieved by effective methods of recording, marking, and carving of the post-dam. The aim of the study was to assess Iraqi dentists in their knowledge and application of the post-dam in maxillary complete dentures. Methods Questionnaires were distributed randomly through online Google Forms and 118 Iraqi dentists with different academic degree participated in the study. A multinomial logistic regression model was also used to ass

The study aims to identify the level of existential frustration and the level of recrimination among the students of universities, identify the statistical differences between the existential frustration and recrimination based on gender, and finally, identify the correlation between the existential frustration and recrimination. To do this, the researcher adopted the existential frustration scale of ( al-saaedi, 2009) that consisted of (43) item, he also adopted the recrimination scale of ( al-zugeibi,2008) which composed of (31) item. The total sample was (120) male and female student were chosen randomly from four colleges within the university of Baghdad for the academic year ( 2015-2016). The results revealed that the targeted sampl

Background: The rapid integration of Artificial Intelligence (AI) into healthcare necessitates that nursing education evolves to equip students with essential technological competencies. Objectives: To explore pediatric nursing students' perceptions of AI in nursing and analyze associations with sociodemographic factors and prior AI knowledge. Methods: A descriptive cross-sectional study was conducted from December 2024 to March 2025 across five universities in Baghdad. A non-probability sample of 500 pediatric nursing students completed the Shinners Artificial Intelligence Perception (SAIP) tool. Data were analyzed using descriptive statistics and inferential comparisons (t-tests/ANOVA) via SPSS. Results: Participants had a mean ag

In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water

These years Qatar has emerged as an important regional destination of foreign direct investment (FDI), which demonstrates the recent success of several smaller economies in attracting FDI. This paper aims to investigate the causal relationships between inward FDI and economic growth in the particular case of Qatar featured as oil production country. Vector Autoregressive (VAR) Impulse Responses and Granger Causality Tests were adopted as major research methods. Annual data set was used covering from 1990 to 2010. The main results demonstrated the bi-directional causality and long-run relationships between FDI inflows and economic growth in Qatar. And to attract FDI inflows into Qatar, the government shall continue its efforts in const

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k