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bsj-5339
Antibacterial Activity of Silver Nanoparticles Synthesized by Aqueous Extract of Carthamus oxycantha M.Bieb. Against Antibiotics Resistant Bacteria
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Antibiotics resistant bacteria have become a global problem as a result of the unprogrammed use of antibiotics, resulting in bacterial strains resistant to many antibiotics, or to all available antibiotics. Plants are a good source of primary and secondary metabolites that have a major role in reducing silver nitrate to silver nanoparticles (AgNPs). The production of these nanoparticles were carried out by using aqueous extract of Carthamus oxycantha M.Bieb. This can be verified by color change of the reaction solution from yellow to dark brown because of the excitation of the surface plasmon resonance. AgNPs were characterized by UV-Vis spectroscopy, where they recorded the peak at 420 nm. Fourier Transformation-infrared (FTIR) was conducted to identify the effective plant group that contributes to the formation of AgNPs and it was found that proteins and phenols have the major role in the formation of those nanoparticles. Shapes and sizes of the synthesized AgNPs were characterized by Scanning Electron Microscope (SEM) with a range of 50-80nm in size and spherical in shapes. Antibacterial activity of AgNPs were tested against Multi-Drug Resistant bacteria (MDR), Extremely antibiotics Resistant (XDR), and Pan drug-resistant (PAN) bacteria, was done in concentrations ranging from 1000-63 µg/ml. The results showed that there were significant variations between the concentrations, the tested bacteria also showed significant differences in its sensitivity to AgNPs. The results recorded a proportional relation between the type of bacterial resistance to antibiotics and it's resistant to AgNPs, therefore the most resistant bacteria to AgNPs in this study Enterobacter cloacae EN2 was resistant to all antibiotics (PAN), while Escherichia coli E11 recorded was the most sensitive bacteria to AgNPs and its resistant only to 3 antibiotics.

unprogrammed use of antibiotics, resulting in bacterial strains resistant to many
antibiotics, or to all available antibiotics. Plants are a good source of primary and
secondary metabolites that have a major role in reducing silver nitrate to silver
nanoparticles (AgNPs). The production of these nanoparticles were carried out by using
aqueous extract of Carthamus oxycantha M.Bieb. This can be verified by color changed
of the reaction solution from yellow to dark brown because of the excitation of the
surface plasmon resonance. AgNPs were characterized by UV-Vis spectroscopy, where
recorded peak at 425 nm. Fourier Transformation-infrared (FTIR) was conducted to
identify the effective plant group that contributes to the formation of AgNPS and it was
found that proteins and phenols have the major role in the formation of those
nanoparticles. Shapes and sizes of synthesized AgNPs were characterized by Scanning
Electron Microscope (SEM) with a range of 50-80nm in size and spherical in shapes.
Antibacterial activity of AgNPs were tested against Multi-Drug Resistant bacteria
(MDR), Extremely antibiotics Resistant (XDR), and Pandrug-resistant (PAN) bacteria,
was done in concentrations ranging from 1000-63 µg/ml. The result showed that the
concentrations from 1000-125 µg/ml inhibited all tested bacterial strains except the S1
strain

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Natural Sciences Research
Isolation and Characterization of Lignin from Iraqi Date Palm Phoenix Dactylifera L. Frond Bases as a Good and Cheap Source of Lignin‏
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Publication Date
Sun Jan 01 2023
Journal Name
Chemical Engineering And Processing - Process Intensification
Optimization of a combined electrocoagulation-electro-oxidation process for the treatment of Al-Basra Majnoon Oil field wastewater: Adopting a new strategy
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Publication Date
Thu Feb 09 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of A cognitive Behavioral Counseling Program in Enhancing Self-Management in Reducing the Academic Procrastination of Tenth grade male Students
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This study aims to find out the effectiveness of a cognitive-behavioral counseling program in enhancing self-management in reducing the academic procrastination of tenth-grade male students. The sample consisted of (26) male students divided into an experimental group of (13) students and a control group of (13) students. Two scales of self-management and academic procrastination were used, prepared by the researcher. The counseling program was prepared by the researcher. The results showed the program's effectiveness in enhancing self-management and reducing academic procrastination in the posttest, as it showed the continuation of this enhancement in self-management and the increase in the reduction of procrastination in the follow-up

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation of banking performance according to the CAMELS model An applied study of Al-Mansour Investment Bank for the period 2014-2018.
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The banking sector has a significant impact on the economic growth of the country, and the importance of this sector must assess its financial performance from time to time, to measure the situation related to money for each bank and how to put the supervision of the efficiency of the full. The research aims at evaluating the financial performance according to the elements of the CAMELS model, which including capital adequacy, asset quality, management efficiency, profitability, liquidity, and market risk sensitivity. The research included the study of Al-Mansour Investment Bank during the period from 2014 to 2018. The base capital ratio was used to total assets to measure capital adequacy The proportion of investments to total a

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Assessment of Climate Change Impact on Water Productivity and Yield of Wheat Cultivated Using Developed Seasonal Schedule Irrigation in the Nineveh Province
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The agricultural lands that depend on supplementary irrigation methods for winter wheat cultivating in wide areas of the Nineveh province are most vulnerable to climate change concerns. Due to frequent rainfall shortages and the temperature increase recently noticed and predicted by the climate scenarios. Hence important to assess the climate effect on the crop response in terms of water consumption during the periods (2021-2040) and (2041-2060) by using high-resolution data extracted from 6 global climate data GCMs under SSP5-8.5 fossil fuel emission scenarios in changing and fixed CO2 concentration. And validate the Aqua-Crop model to estimate the yield and water productivity. And gives the RRSME of 7.1- 4.1

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Publication Date
Wed Jun 07 2023
Journal Name
Journal Of Educational And Psychological Researches
The impact of The Bransford and Stein Model on the Achievement of Fifth-Grade Literary Students for Geography and their Reflective Thinking
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The current research aims to identify the effect of the Bransford and Stein model on the achievement of fifth-grade literary students for geography and their reflective thinking. To achieve the objective of the research, the following two null hypotheses were formulated:

  • There is no statistically significant difference at the significance level (0.05) between the average scores of the experimental group students who studied geography using the Bransford and Stein model and the average scores of the control group students who studied the same subject in the usual way in the achievement test. 2- There is no statistically significant difference at the significance level (0.05) between the average scores of the experimental gr

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Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Engineering
Prediction of Raw Water Turbidity at the Intakes of the Water Treatment Plants along Tigris River in Baghdad, Iraq using Frequency Analysis
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Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit.  The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al-Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Clinical And Experimental Dentistry
Preventive effect of combined Er, Cr: YSGG and fluoride gel on acid resistance of the permanent tooth enamel: An in vitro study
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Publication Date
Fri Oct 10 2025
Journal Name
Natural And Life Sciences Communications
Influence of Sandblasting on Surface Roughness and Shear Bond Strength of Silicone Soft Liner Applied to 3D Printed Acrylic Denture Bases Material
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Removable dental prostheses remain a reliable treatment for edentulous patients. Conventional fabrication requires multiple steps, whereas computer-aided design and manufacturing (CAD-CAM), particularly 3D printing, offers faster and more cost-effective alternatives. This in vitro study aimed to evaluate the effect of sandblasting on surface roughness and shear bond strength of silicone soft liner bonded to 3D-printed and heat-cured acrylic denture base materials. Eighty specimens were divided into four groups: heat-cured control, 3D-printed control, heat-cured sandblasted, and 3D-printed sandblasted. Surface roughness was measured using a profilometer, while shear bond strength was tested with a universal testing machine. D

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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