Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzy

The study of surface hardness, wear resistance, adhesion strength, electrochemical corrosion resistance and thermal conductivity of coatings composed from sodium silicate was prepared using graphite micro-size particles and carbon nano particles as fillers respectively of concentration of (1-5%), for the purpose of covering and protecting the oil distillation towers. The results showed that the sodium silicate coating reinforced with carbon nano-powder has higher resistance to stitches, mechanical wear, adhesive and thermal conductivity than graphite/sodium silicate composite especially when the ratio 5% and 1%, the electrochemical corrosion test confirmed that the coating process of stainless steel 304 lead to increasin

Transportability refers to the ease with which people, goods, or services may be transferred. When transportability is high, distance becomes less of a limitation for activities. Transportation networks are frequently represented by a set of locations and a set of links that indicate the connections between those places which is usually called network topology. Hence, each transmission network has a unique topology that distinguishes its structure. The most essential components of such a framework are the network architecture and the connection level. This research aims to demonstrate the efficiency of the road network in the Al-Karrada area which is located in the Baghdad city. The analysis based on a quantitative evaluation using graph th

Mechanical degradation hampers the practical usage of polymers for turbulent drag reduction
application. Mechanical degradation refers to the chemical process in which the activation energy of
polymer chain scission is exceeded by mechanical action on the polymer chain, and bond rupture
occurs. When a water-soluble polymer and surfactant are mixed in water solution, the specific structures
(aggregates) are formed, in which polymer film is formed around micelle. In this work, Xanthan gum (XG) –
Sodium lauryl ether sulfate (SELS) complex formation and its effect on percentage viscosity reduction
(%VR) was studied. It was found that SELS surfactant reduced the mechanical degradation of XG much
more efficiently than th

Abstract The surface of kaolin was diagnosed by an AFM and the results were shown The height of the highest peak reached by a quantity of Kaolin ‎surface is 2.5 µm, the granules, and their diameter with an average diameter of 666.1nm. Using Kaolin's adsorption properties, erythrosine was removed of its aqueous solution. It was determined that the maximal dye adsorption ranged 36.53–40.61%. ‎‎‎‎The results of using the Freundlich, Langmuir, and Temkin adsorption isotherms revealed that at temperatures of (298,308,318) K, the Freundlich model was followed, the Langmuir model did not match, and the Temkin model could only be partially applied. There is also physical adsorption. One of the three kinetic models of the

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

In this paper we use Bernstein polynomials for deriving the modified Simpson's 3/8 , and the composite modified Simpson's 3/8 to solve one dimensional linear Volterra integral equations of the second kind , and we find that the solution computed by this procedure is very close to exact solution.