Background: University students in Iraq face rising obesity risk linked to physical inactivity, prolonged sedentary behavior, insufficient sleep, and academic stress. Longitudinal evidence examining the combined influence of these behaviors on weight status in Iraqi universities remains limited. Objective: This study examined six-month longitudinal associations of physical activity, sedentary behavior, sleep duration, and perceived stress with body mass index and percentage body fat among Iraqi university students. Methods: A prospective multi-behavioral study was conducted at six public universities in Iraq. Six hundred undergraduate students aged 18–25 years were followed monthly during one academic semester. Validated questionn

Transportation and distribution are the most important elements in the work system for any company, which are of great importance in the success of the chain work. Al-Rabee factory is one of the largest ice cream factories in Iraq and it is considered one of the most productive and diversified factories with products where its products cover most areas of the capital Baghdad, however, it lacks a distribution system based on scientific and mathematical methods to work in the transportation and distribution processes, moreover, these processes need a set of important data that cannot in any way be separated from the reality of fuzziness industrial environment in Iraq, which led to use the fuzzy sets theory to reduce the levels of uncertainty.

In the present study, multi-walled carbon nanotubes (MWCNTs) with outside diameters of< 8 nm and 20−30 nm were covalently functionalized with β-Alanine using a novel synthesis procedure. The functionalization process was proved successful using Raman spectroscopy, FTIR, and TEM. Utilizing the two-step method with ultrasonication, the MWCNTs treated with β-Alanine (Ala-MWCNTs) with weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1% were dispersed in distilled water to prepare water-based nanofluids. The aqueous colloidal dispersions of pristine MWCNTs were unstable. While for Ala-MWCNTs and after> 50 days from preparation, higher colloidal stability was obtained up to relative concentration of 0.955 and 0.939 for the 0.075-wt% samp

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d