The hydraulic behavior of the flow can be changed by using large-scale geometric roughness elements in open channels. This change can help in controlling erosions and sedimentations along the mainstream of the channel. Roughness elements can be large stone or concrete blocks placed at the channel's bed to impose more resistance in the bed. The geometry of the roughness elements, numbers used, and configuration are parameters that can affect the flow's hydraulic characteristics. In this paper, velocity distribution along the flume was theoretically investigated using a series of tests of T-shape roughness elements, fixed height, arranged in three different configurations, differ in the number of lines of roughness element

The avoidance strategy of prey to predation and the predation strategy for predators are important topics in evolutionary biology. Both prey and predators adjust their behaviors in order to obtain the maximal benefits and to raise their biomass for each. Therefore, this paper is aimed at studying the impact of prey’s fear and group defense against predation on the dynamics of the food-web model. Consequently, in this paper, a mathematical model that describes a tritrophic Leslie-Gower food-web system is formulated. Sokol-Howell type of function response is adapted to describe the predation process due to the prey’s group defensive capability. The effects of fear due to the predation process are considered in the first two levels

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

The success of endodontic therapy is relied on radicular system cleaning, shaping, elimination of micro-organisms, and three dimensional filling of the radicular complex.This study was conducted to develop and assess new root canal sealer incorporating nano-sized bioactive glass into Gutta Flow II. The following concentration was used depend on a pilot study included adding (3%) of 45S5 bioactive glass into the Gutta Flow II. These materials were tested through assessment bioactivity. bioactivity test was undertaken after immersion of the tested samples into PBS for three days, seven days, fourteen days, and twenty eight days using FTIR too. study was found that it’s peaks was appear at level 800-1000 cm-1. The results showed that GFII gr

This work involved the successful synthesis of three new Schiff base complexes, including Ni(II), Mn(II), and Cu(II) complexes. The Schiff base ligand was created by reacting the malonyldihydrazide molecule with naphthaldehyde, and the final step involved reacting the ligand with the corresponding metallic chloride yielding pure target complexes. FTIR, 1 H NMR, 13 C NMR, mass, and UV/Vis spectroscopies were used to comprehensively characterize the produced complexes. These substances have been employed in this study to photo-stabilize polystyrene (PS) and lessen the photo-degradation of its polymeric chains. Several methods, including FTIR, weight loss, viscosity average molecular weight, light and atomic force microscopy, and energy disper

In this paper, a microcontroller-based electronic circuit have been designed and implemented for dental curing system using 8-bit MCS-51 microcontroller. Also a new control card is designed while considering advantages of microcontroller systems the time of curing was controlled automatically by preset values which were input from a push-button switch. An ignition based on PWM technique was used to reduce the high starting current needed for the halogen lamp. This paper and through the test result will show a good performance of the proposed system.

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co