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In-silico design, molecular docking, molecular dynamic simulations, Molecular mechanics with generalised Born and surface area solvation study, and pharmacokinetic prediction of novel diclofenac as anti-inflammatory compounds
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The prostaglandins inside inflamed tissues are produced by cyclooxygenase-2 (COX-2), making it an important target for improving anti-inflammatory medications over a long period. Adverse effects have been related to the traditional usage of non-steroidal anti-inflammatory drugs (NSAIDs) for the treatment of inflammation, mainly centered around gastrointestinal (GI) complications. The current research involves the creation of a virtual library of innovative molecules showing similar drug properties via a structure-based drug design. A library that includes five novel derivatives of Diclofenac was designed. Subsequently, molecular docking through the Glide module and determining the binding free energy implementing the Prime-MMGBSA module by the Schrödinger software package was used to identify compounds that showed marked specificity towards the COX-2 isoform. In addition, the ligands are subject to evaluation of their drug-like properties and ADMET (absorption, distribution, metabolism, excretion, and toxicity) characteristics using the QikProp module. Finally, molecular dynamics simulation has been calculated for the best molecule. The docking results indicated that all compounds own a predictive capability for specific binding to the COX-2 enzyme compared to the standard drug with a docking score range from -10.07 to -10.66 Kcal/mole, thus potentially overcoming the limitations imposed previously by the drugs currently used in clinical use. The ADMET analysis of the virtually active compounds demonstrated an acceptable drug-like profile and desirable pharmacokinetics properties. MM/GBSA calculation revealed that all the suggested compounds exhibited favorable free binding energies (-49.150 to - 60.185 Kcal/mole), indicating their strong potential to fit well into the COX-2 receptor. Finally, the MD simulation study revealed that compound 1 had perfect alignment with COX-2 receptor. The findings indicated that the compounds possess a predictive capability for specific binding to the COX-2 enzyme, thus potentially surmounting the restrictions imposed by the drugs currently employed in clinical use.

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Ant Colony Optimization Algorithm for Design of Distribution System with Practical Application
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The Ant System Algorithm (ASA) is a member of the ant colony algorithms family in swarm intelligence methods (part of the Artificial Intelligence field), which is based on the behavior of ants seeking a path and a source of food in their colonies. The aim of This algorithm is to search for an optimal solution for Combinational Optimization Problems (COP) for which is extremely difficult to find solution using the classical methods like linear and non-linear programming methods. 

The Ant System Algorithm was used in the management of water resources field in Iraq, specifically for Haditha dam which is one of the most important dams in Iraq. The target is to find out an efficient management system for

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Publication Date
Wed Jun 19 2019
Journal Name
Scientific Reports
Environmental microcystin targets the microbiome and increases the risk of intestinal inflammatory pathology via NOX2 in underlying murine model of Nonalcoholic Fatty Liver Disease
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Abstract<p>With increased climate change pressures likely to influence harmful algal blooms, exposure to microcystin, a known hepatotoxin and a byproduct of cyanobacterial blooms can be a risk factor for NAFLD associated comorbidities. Using both <italic>in vivo</italic> and <italic>in vitro</italic> experiments we show that microcystin exposure in NAFLD mice cause rapid alteration of gut microbiome, rise in bacterial genus known for mediating gut inflammation and lactate production. Changes in the microbiome were strongly associated with inflammatory pathology in the intestine, gut leaching, tight junction protein alterations and increased oxidative tyrosyl radicals. Increased lactate produ</p> ... Show More
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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Thu Jan 07 2021
Journal Name
Indian Journal Of Forensic Medicine &amp; Toxicology
Effect of Dentifrices with Different Abrasives on the Surface Roughness of a Nano Composite Resins materials
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Background: to evaluate the effect of different dentifrices on the surface roughness of two composite resins (nanofilled-based and nanoceramic – based composite resins). Materials and methods: Forty specimens (diameter 12 mm and height of 2mm) prepared from different composite resin materials: Z350 (nanofilled composite, and Ceram-X (nanoceramic) .they were subjected to brushing simulation equivalent to the period of 1 year. The groups assessed were a control group brushed with distilled water (G1), Opalescence whitening toothpasteR (G2), Colgate sensitive pro-relief (G3) and Biomed Charcoal Toothpaste (G4). The initial and final roughness of each group was tested by surface roughness tester. The results were statistically analyzed using

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Publication Date
Sat Jan 23 2016
Journal Name
Computer Science &amp; Information Technology ( Cs &amp; It )
Modelling Dynamic Patterns Using Mobile Data
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Publication Date
Mon Apr 01 2019
Journal Name
Applied Water Science
Hydrochemistry as a tool for interpreting brine origin and chemical equilibrium in oilfields: Zubair reservoir southern Iraq case study
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Publication Date
Mon Mar 15 2021
Journal Name
Al-adab Journal
Alienation in Scapegoat novel by Elie Amir
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 تهدف هذه الدراسة إلى بحث ظاهرة الاغتراب في رواية " ديك الفداء " لايلي عامير ، لأن هذه الظاهرة تبدو أكثر وضوحا في هذه الرواية ، وتمثل تیارا مسيطرة على معطياتها واتجاهاتها الفكرية والفنية، خاصة أن الكاتب استطاع أن يجسد هذه الظاهرة المحورية تجسيدا فنيا متميزا ، وكشف عن طبيعة العلاقة بين عالم الواقع وعالم الحلم لدى الشخصيات، وعما تتسم به من تناقض و تعارض وتصادم و شعور بالإحباط والضياع والاغتراب. وقد اشتملت ال

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Performance Equations for Household Compressors Depending on Manufacturing Data for Refrigerators and Freezers
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Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm3.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

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