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bsj-7405
Synthesis, characterization, molecular docking, ADMET prediction, and anti-inflammatory activity of some Schiff bases derived from salicylaldehyde as a potential cyclooxygenase inhibitor
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A series of Schiff base-bearing salicylaldehyde moiety compounds (1-4) had been designed, synthesized, subjected to insilico ADMET prediction, molecular docking, characterization by FT-IR, and CHNS analysis techniques, and finally to their Anti-inflammatory profile using cyclooxygenase fluorescence inhibitor screening assay methods along with standard drugs, celecoxib, and diclofenac. The ADMET studies were used to predict which compounds would be suitable for oral administration, as well as absorption sites, bioavailability, TPSA, and drug likeness. According to the results of ADME data, all of the produced chemicals can be absorbed through the GIT and have passed Lipinski’s rule of five. Through molecular docking with PyRx 0.8, these synthesized compounds were tested insilico selectivity toward COX-1 and COX-2 and in vitro for their anti-inflammatory efficacy . In vitro testing demonstrated that all of the produced compounds had significantly stronger activity against the COX-2 enzyme than COX-1. Among these, compound 1 displayed the most potent inhibitory activity with an IC50 value of 0.19 µM compared to standard drug celecoxib (IC50 = 0.29 µM). The most active derivative compound1 was oriented towards the active site and occupied the target enzyme based on the docking investigation against COX-1 and COX-2. In addition, insilico investigations found that COX-2 has a higher inhibitory activity than COX-1

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Tue Mar 30 2021
Journal Name
College Of Islamic Sciences
Taking Over The Judiciary By Women And The Position Of Law From That: مثالا
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لمقدمة

     الحمد لله رب العالمين والصلاة والسلام على سيد الأنبياء والمرسلين نبينا محمد صلى الله عليه وسلم وعلى  واصحابه أجمعين  ومن تبعهم وأهتدى بهداهم الى يوم الدين اما بعد :

        فوظيفة القضاء وظيفة سامية يراد منها اقامة العدل ولا يستقيم حالهم الا به دفعاّ للظلم ، ولقد اولى النبي صلى الله عليه وآله وسلم ومن بعده الخلفاء الراشدون

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Publication Date
Fri Aug 18 2023
Journal Name
مجلة الدراسات المستدامة
A Review article:Diversity of fish in Iraqi waters and some factors affecting them
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Rivers Tigris and Euphrates, as well as the wetlands in southern Iraq and the Diyala River, were all included in the evaluation of earlier studies on the variety and factors impacting fish in Iraqi waters. Different studies documented different types, and the number of species recorded varied between the studies, which could be explained by the registration of some species, synonyms, differs from the registration of some species with synonymous names By mistake, as well as recording new species in times that followed some previous studies, Also, the difference in some factors, including the pollution of some waterways, leads to a difference in the existing species, so we find the presence of species that are tolerant of pollution. There are

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
Detection of 16S rRNA Methylases and Co-Resistance with β-lactams among Klebsiella pneumoniae Isolates from Iraqi Patients
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Out of 150 clinical samples, 50 isolates of Klebsiella pneumoniae were identified according to morphological and biochemical properties. These isolates were collected from different clinical samples, including 15 (30%) urine, 12 (24%) blood, 9 (18%) sputum, 9 (18%) wound, and 5 (10%) burn. The minimum inhibitory concentrations (MICs) assay revealed that 25 (50%) of isolates were resistant to gentamicin (≥16µg/ml), 22 (44%) of isolates were resistant to amikacin (≥64 µg/ml), 21 (42%) of isolates were resistant to ertapenem (≥8 µg/ml), 18 (36%) of isolates were resistant to imipenem (4- ≥16µg/ml), 43 (86%) of isolates were resistant to ceftriaxone (4- ≥64 µg/ml), 42 (84%) of isolates were resistant to ceftazidime (1

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Publication Date
Sun Mar 13 2016
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
New Species of the Sub family Cerambycinae (Coleoptera, Cerambycidae) from Iraq: New Species of the Sub family Cerambycinae (Coleoptera, Cerambycidae) from Iraq
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A new Species of the Cerambycinae belonging to the genus Hesperophanes was found new to the fauna of Iraq and Science. H. testaceus was studied in details and the male genitalia were illustrated. Type's paratypes and the locality of this newly described Species were mentioned.

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology & Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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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
Sat Jan 01 2022
Journal Name
Journal Of Applied Engineering Science
Rutting prediction of hot mix asphalt mixtures reinforced by ceramic fibers
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One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to stu

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Travel Time Prediction Models and Reliability Indices for Palestine Urban Road in Baghdad City
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Abstract

     Travel Time estimation and reliability measurement is an important issues for improving operation efficiency and safety of traffic roads networks. The aim of this research is the estimation of total travel time and distribution analysis for three selected links in Palestine Arterial Street in Baghdad city. Buffer time index results in worse reliability conditions. Link (2) from Bab Al Mutham intersection to Al-Sakara intersection produced a buffer index of about 36%  and 26 % for Link (1) Al-Mawall intersection to Bab Al- Mutham intersection and finally for link (3) which presented a 24% buffer index. These illustrated that the reliability get worst for link

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Publication Date
Fri Apr 01 2016
Journal Name
Swift Journal Of Social Sciences And Humanity
Difficulties encountered in translating Some legal texts from Arabic into English
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Translation is both a social and cultural phenomenon, it can neither exist outside a social community and it is within society, nor it can be viewed as a medium of cross-cultural fertilization. This paper aims to investigate the difficulties that a translator may face when dealing with legal texts such as marriage and divorce contracts. These difficulties can be classified according to the present paper into syntactic, semantic, and cultural. The syntactic difficulties include word order, syntactic arrangement, unusual sentence structure, the use of model verbs in English, and difference in legal system. As to the semantic difficulties, they involve lack of established terminology, finding functional and lexical equivalence, word for word t

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