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A Comparative Study for the Accuracy of Three Molecular Docking Programs Using HIV-1 Protease Inhibitors as a Model
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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 enzyme. The tested sets are composed of eight receptor-ligand complexes with high resolution crystal structures downloaded from Protein Data Bank website. Molecular dockings were applied between approved HIV-1 protease inhibitors and the HIV-1 protease using AutoDock Vina, 1-Click Docking, and DOCK6. Then, docking poses of the top-ranked solution was realized using UCSF Chimera. Furthermore, Pearson correlation coefficient (r) and coefficient of determination (r2) between the experimental results and the top scored docking results of each program were calculated using Graphpad prism V9.2. After comparing saquinavir top scored binding poses of each docking program with the crystal structure, various conformational changes were observed. Moreover, according to the relative comparison between the top ranked calculated ?Gbinding values against the experimental results, r2 value of AutoDock Vina, 1-Click Docking, and DOCK6 were 0.65, 0.41, and 0.005, respectively. The outcome of this study shows that the top scored binding free energy could not produce the best pose prediction. In addition, AutoDock Vina results have the highest correlation with the experimental results.

 

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Publication Date
Thu Jul 25 2024
Journal Name
Metals
The Effects of Three Antibacterial Nanoparticle Coatings on the Surface Characteristics of Stainless Steel
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The aim of this study is to investigate the antibacterial capabilities of different coating durations of three nanoparticle (NP) coatings: molybdenum (Mo), tantalum (Ta), and zinc oxide (ZnO), and their effects on the surface characteristics of 316L stainless steel (SS). The coated substrates underwent characterization utilizing field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectrometry (EDX), and X-ray diffractometer (XRD) techniques. The antibacterial efficacy of NPs was evaluated using the agar diffusion method. The FE-SEM and EDX images confirmed the presence of nano-sized particles of Mo, Ta, and ZnO on the surface of the substrates with perfectly symmetrical spheres and a uniform distribution of

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Publication Date
Tue Oct 19 2021
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Object Tracking Using Adaptive Diffusion Flow Active Model
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Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Agile manufacturing assessment model using multi-grade evaluation
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In unpredicted industrial environment, being able to adapt quickly and effectively to the changing is key in gaining a competitive advantage in the global market. Agile manufacturing evolves new ways of running factories to react quickly and effectively to changing markets, driven by customized requirement. Agility in manufacturing can be successfully achieved via integration of information system, people, technologies, and business processes. This article presents the conceptual model of agility in three dimensions named: driving factor, enabling technologies and evaluation of agility in manufacturing system. The conceptual model was developed based on a review of the literature. Then, the paper demonstrates the agility

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Euro Dinar Trading Analysis Using WARIMA Hybrid Model
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The rise in the general level of prices in Iraq makes the local commodity less able to compete with other commodities, which leads to an increase in the amount of imports and a decrease in the amount of exports, since it raises demand for foreign currencies while decreasing demand for the local currency, which leads to a decrease in the exchange rate of the local currency in exchange for an increase in the exchange rate of currencies. This is one of the most important factors affecting the determination of the exchange rate and its fluctuations. This research deals with the currency of the European Euro and its impact against the Iraqi dinar. To make an accurate prediction for any process, modern methods can be used through which

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Publication Date
Thu Jan 21 2021
Journal Name
Recent Innovations In Chemical Engineering (formerly Recent Patents On Chemical Engineering)
Soap Production Using Vacuum Reactive Distillation: Batch Model
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Introduction: Although soap industry is known from hundreds of years, the development accompanied with this industry was little. The development implied the mechanical equipment and the additive materials necessary to produce soap with the best specifications of shape, physical and chemical properties. Objectives: This research studies the use of vacuum reactive distillation VRD technique for soap production. Methods: Olein and Palmitin in the ratio of 3 to 1 were mixed in a flask with NaOH solution in stoichiometric amount under different vacuum pressures from -0.35 to -0.5 bar. Total conversion was reached by using the VRD technique. The soap produced by the VRD method was compared with soap prepared by the reaction - only method which

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Publication Date
Fri Jul 28 2017
Journal Name
Iraqi Journal Of Science
3D Building Reconstruction Using DEM and Mosaic Model
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A digital elevation model (DEM) is a digital representation of ground surface topography or terrain. It can be represented as a raster (a grid of squares) and it is commonly estimated by utilizing remote sensing techniques, or from land surveying. In this research a 3D building of Baghdad university campus have been performed using DEM, where the easting, northing, and elevation of 400 locations have been obtained by field survey using global positioning system (GPS). The image of the investigated area has been extracted from QuickBird satellite sensor (with spatial resolution of 0.6 m). This image has been geo-referenced by selecting ground control points of the GPS. The rectification is running, using 1st order polynomial transformation.

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Publication Date
Sun Feb 10 2019
Journal Name
Drug Invention Today
Design, characterization, and in vitro evaluation of zaltoprofen solid dispersion as a hollow-type rectal suppository
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Aim: The present study aims to improve the poor water solubility of zaltoprofen which is a non-steroidal anti-inflammatory drug (NSAIDs) with a potent analgesic effect using solid dispersion then formulate it as a hollow type suppository to be more convenient for geriatric patients. Materials and Method: Zaltoprofen solid dispersions were prepared by solvent evaporation technique in different zaltoprofen: Soluplus® ratios. Results: Among the formulations tested, zaltoprofen solid dispersion preparation using 1:5 (zaltoprofen: Soluplus®) ratio showed the highest solubility and selected for further investigation. Solid dispersion characterization was evaluated by differential scanning calorimetry (DSC), X-ray diffraction study (XRD) and Fou

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Green synthesis of CdS:Sn NPs by Starch as a Covering Agent and Studying its Physical Properties
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The aim of this research is to employ starch as a stabilizing and reducing agent in the production of CdS nanoparticles with less environmental risk, easy scaling, stability, economical feasibility, and suitability for large-scale production. Nanoparticles of CdS have been successfully produced by employing starch as a reducing agent in a simple green synthesis technique and then doped with Sn in certain proportions (1%, 2%, 3%, 4%, and 5%).According to the XRD data, the samples were crystallized in a hexagonal pattern, because the average crystal size of pure CdS is 5.6nm and fluctuates in response to the changes in doping concentration 1, 2, 3, 4, 5 %wt Sn, to become   4.8, 3.9, 11.5, 13.1, 9.3 nm respectively. An increase in crystal

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