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Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international information network has showed that the error rate in the training and the testing process was about (10%) and that the results of the network query has given the results of acceptable accuracy statistically so that it was better than results obtained from multiple linear regression equation for the same data.

 

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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Molecular Docking, Synthesis, characterization and preliminary cytotoxic evaluation of new 1, 3,4-Thiadiazole derivatives as EGFR inhibitors
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of The Mechanical Behavior Of Materials
Transient response and performance of prestressed concrete deep T-beams with large web openings under impact loading
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Abstract<p>This study reports testing results of the transient response of T-shape concrete deep beams with large openings due to impact loading. Seven concrete deep beams with openings including two ordinary reinforced, four partially prestressed, and one solid ordinary reinforced as a reference beam were fabricated and tested. The effects of prestressing strand position and the intensity of the impact force were investigated. Two values for the opening’s depth relative to the beam cross-section dimensions were inspected under the effect of an impacting mass repeatedly dropped from different heights. The study revealed that the beam’s transient deflection was increased by about 50% with gre</p> ... Show More
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Publication Date
Fri Jun 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Autophagy or Apoptosis: Anticancer Molecular Mechanism of Epigallocatechin Gallate with Natural Polyphenol Effect on HepG2 Cells Viability
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Background: The anticancer impact of Epigallocatechin gallate (EGCG) the highly active polyphenol of green tea was abundantly studied.  Though, the exact mechanism of its cytotoxicity is still under investigation. Objectives: Hence, the current study designed to investigate the molecular target of EGCG in HepG2 cells on thirteen autophagy- and/or apoptosis- related genes. Methods: The apoptosis detection analyses such as flow cytometry and dual apoptosis assay were used. The genes expression profile was explored by the real-time quantitative-PCR. Results: EGCG increases G0/G1 cell cycle arrest and the real-time apoptosis markers proteins leading to stimulate apoptos

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Publication Date
Wed Oct 16 2019
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Depression, Anxiety and Stress Among a Sample of Chronic Hepatitis C Patients in AL-Najaf Province /Iraq
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Previous studies in Euro-American countries have shown that patients with chronic hepatitis C virus infection have increased levels of neuropsychiatric symptoms. While chronic hepatitis C virus infection has been reported in Arab countries such as Iraq, there is little studies about the neuropsychological burden associated with chronic hepatitis C among patients in the Arab region. The aim of the current study was to measure the prevalence and level of severity of depression, anxiety and stress among a sample of chronic hepatitis C patients in AL-Najaf province /Iraq. The current study was cross-sectional study carried out on (110) already diagnosed chronic viral hepatitis C patients who attended the Gastroenterology and Hepatology

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Publication Date
Mon Aug 01 2022
Journal Name
Archives Of Razi Institute
Antimicrobial Effect of Moringa Oleifera L. and Red Pomegranate against Clinically Isolated Porphyromonas gingivalis: in vitro Study
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Moringa oleifera L. and red pomegranate extracts have been reported to inhibit gram-positive facultative anaerobe growth and inhibit the formation of biofilm on tooth surfaces. The current study aimed to assess the antibacterial effect of M. oleifera L. and red pomegranate extracts and their combinations against Porphyromonas gingivalis. The antimicrobial sensitivity, minimum inhibition concentrations (MIC), and minimum bactericidal concentrations after treatment with the aqueous extracts of M. oleifera L. and red pomegranate as well as their combination against clinically isolated P. gingivalis were determined using agar well diffusion and two-fold serial dilution. The anti-biofilm activity of the extracts and their combination was evaluat

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Publication Date
Mon May 30 2022
Journal Name
Egyptian Journal Of Chemistry
Design ,Synthesis, Insilco Study and Biological Evaluation of New Coumarin-Oxadiazole Derivatives as Potent Histone Deacetylase Inhibitors
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Publication Date
Mon Jan 01 2024
Journal Name
Oral Health And Preventive Dentistry
Antioxidant and Antineoplastic Activities of Hibiscus sabdariffa Linn. Petal Extracts against Oral Squamous Cell Carcinoma Cell Line
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Purpose: To assess the antioxidant and antineoplastic effects of Hibiscus sabdariffa Linn. on oral squamous cell carcinoma cells. Materials and Methods: Human squamous cell carcinoma HSCC cells were tested for cytotoxicity by a methanol extract of Hibiscus sabdariffa (MEHSP). After 24, 48, and 72 ...

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Sat Jan 01 2022
Journal Name
Brazilian Dental Science
Association of matrix metalloproteinase-1-1607 1G/2G single nucleotide polymorphism genotypes with periodontitis in Iraqi population
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Publication Date
Tue Jan 01 2013
Journal Name
Advances In Physics Theories And Applications
Analysis and Assessment of Essential Toxic Heavy Metals, PH and EC in Ishaqi River and Adjacent Soil
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This research was conducted to determine content levels of heavy metal pollution. Samples taken from Ishaqi River bank and adjacent agricultural soils area, in ten sites, distributed along 48 km of the Ishaqi River, north Baghdad. The evaluated metals were Zinc, Copper, Manganese, Iron, Cobalt, Nickel, Chromium, Cadmium, Vanadium and Lead. PH and Electric Conductivity (EC) were measured to evaluate the acidity and (EC). Results showed that most site were contaminated with metals evaluated. Among these metals, Zn, Mn, Fe and Ni were consistently higher in all the samples (both river bank and adjacent soil) followed by PB, CU, V, Cd, Co and Cr. The level concentrations of river bank were almost higher than that of adjacent soil. As will be re

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