Utilizing of subsurface water retention technology is a modern technique to retain and save the application water for sustainability of agricultural production through scheduling and management the irrigation processes. The goal of this paper is to evaluate the effect of the supplementary irrigation and rainfed water on improvement of economic water productivity for winter wheat. The experiment was conducted in open field, within Joeybeh Township, located in east of the Ramadi City, in Anbar Province, for the growing season 2018-2019. Two plots were used for comparison process, the first plot where membrane trough below the root depth was installed and supplementary irrigation system was conducted beside the rainfed water and according to scheduling the irrigation process as checkbook method. While in second plot, the membrane trough was installed and only rainfed water was depend on. Cultivated date of winter wheat was December, 20th, 2018, and the harvest date was May, 10th, 2019. The obtained result was showed that the crop yield and economic water productivity from the first plot and the second plot were equaled to 0.52 kg/m2 and 0.35 kg/m2, and 930 ID/m3 and 800 ID/m3, respectively. The increasing value of crop yield and economic water productivity in the first plot was more than that in the second plot by 49 % and 16 %, respectively. The benefits of applying supplementary irrigation system with installing the new techniques of retaining the applied water were sufficient in improvement the crop yield and accordingly improved value of the economic water productivity.
Cosmetic surgery is more prevalent in the world in recent years. A beautiful and flawless face is everyone's dream. Aging, environmental factors, disease, or poor diet are among the factors that influence body wrinkles. Various methods are used to reduce these lines. It can be said that the simplest and most effective solution is to inject cosmetic fluids into these areas. But, due to the increase in facial injections using cosmetic fluids, which are considered toxins, the risk of injury to the surrounding facial nerves and injury to one of the main facial nerves is increasing, creating a catastrophe or deformation in the face irreversibly. Deep learning algorithms have been used to determine whether cosmetic fluids are injected or not. Deep Convolutional Neural Networks (CNNs), VGG16, ResNet....etc deep learning algorithms have demonstrated excellent performance in terms of object detection, picture classification, and semantic segmentation. all the suggested approach consists of three stages: feature extraction, training, and testing/validation. Deep learning technology is used to train and test the system with before and after photographs. Numerous investigations have been carried out using various deep learning algorithms and databases the main goal is to attain maximum accuracy to ensure that injected cosmetic fluids by specialists have been injected in safe areas in addition to facial recognition and determining whether or not the person received an injection. The most used databases are IIITD plastic surgery and HDA_Plastic surgery.