Objectives: The study aimed to assess the level of pediatric nurses' knowledge toward children with Guillain-Barre
syndrome (GBS) and to find out the relationships between nurses' knowledge and their demographic data.
Methodology: A purposive “non probability” sample of (30) nurses was selected from medical neurological wards and
Respiratory Care Units of Children Welfare Pediatric Teaching Hospital, Child’s Center Pediatric Teaching Hospital,
AL-Kadhemia Teaching Hospital, Baghdad Teaching Hospital, and Neurological Science Hospital which has started
from March 5
th 2009 to April 30th 2009. The study instrument consists of two parts. The first part is concerned with
nurses' demographical characteristic and the second one is concerned with nurses’ knowledge which is divided into two
sections. Section one consists of (20) items which are related to nurses’ knowledge about general information of
Guillain-Barre Syndrome, and section two (12) items concerning nurses’ knowledge in relation to nursing care of GBS.
Data were collected through a special constructed questionnaire format which includes multiple choice questions. A selfadministration
method was used. Data were analyzed by using SPSS packed version (10.0), a descriptive statistical
analysis (frequencies, percentage, quartile, and mean of scores), and inferential statistical analysis (chi-square) were
used.
The aim of the current study was to develop a nanostructured double-layer for hydrophobic molecules delivery system. The developed double-layer consisted of polyethylene glycol-based polymeric (PEG) followed by gelatin sub coating of the core hydrophobic molecules containing sodium citrate. The polymeric composition ratio of PEG and the amount of the sub coating gelatin were optimized using the two-level fractional method. The nanoparticles were characterized using AFM and FT-IR techniques. The size of these nano capsules was in the range of 39-76 nm depending on drug loading concentration. The drug was effectively loaded into PEG-Gelatin nanoparticles (≈47%). The hydrophobic molecules-release characteristics in terms of controlled-releas
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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Background: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized
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Abstract
The increasing of some traded Agricultural crops prices coincide with the increasing of crude oil prices in global market since the beginning of 21st century which indicate the possibility of short run and long run causality relation between the imported economic variables. The study aims to analysis the causality effects between some of Agricultural crops prices imported by Iraq and the prices of crude oil and Iraq dinar exchange rate in global markets for period (2004:1 -2016:4) theory for developing the adequate price and economic police for Iraqi economic sector. The results show the existence of short- run and long- run between the eco
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The current study used extracts from the aloe vera (AV) plant and the hibiscus sabdariffa flower to make Ag-ZnO nanoparticles (NPs) and Ag-ZnO nanocomposites (NCs). Ag/ZnO NCs were compared to Ag NPs and ZnO NPs. They exhibited unique properties against bacteria and fungi that aren't present in either of the individual parts. The Ag-ZnO NCs from AV showed the best performance against E. coli, with an inhibition zone of up to 27 mm, compared to the other samples. The maximum absorbance peaks were observed at 431 nm and 410 nm for Ag NPs, at 374 nm and 377 nm for ZnO NPs and at 384 nm and 391 nm for Ag-ZnO NCs using AV leaf extract and hibiscus sabdariffa flower extract, respectively. Using field emission-scanning electron microscopes (FE-
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An optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH and
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