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Effectiveness of an Educational Program on Nurses- midwives' Knowledge about Pain Management during Labor in Baghdad Maternity Hospitals
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Objectives: To assess nurses-midwives' knowledge about pain management during labor before and after implementation of educational program and to determine the effectiveness of educational program on nurses-midwives' knowledge about pain management during labor in Baghdad Maternity Hospitals.

Methodology: A quasi-experimental design has been conducted during the period of (February 27th 2019 through 2nd June 2019) on non-probability sample (purposive) consists of (44 Nurses/midwives') who are work in delivery room, the sample was exposed to pretest, educational program, posttest. The study was conducted in three Directories, (Baghdad Teaching Hospital) at medical city health directorate, (Al-Elwia Maternity Teaching Hospital, Ibn Al -Balidy for Maternity and Pediatric Hospital, Fatima Al-Zahra for Maternity and Pediatric Hospital) at AL-Russafa/Health directorate, and (Al –Karckh Maternity Hospital and AL - Yarmouk Teaching Hospital - Maternity Department) at Akarkh/Health Directorate. Questionnaire has been used as a tool of data collection. Data were analyzed through the application of descriptive and inferential statistical data analysis approach through the use of (SSPS) version 22.0 and Excel system.

Results: The results of the study revealed that highest percentage (25%) of the nurses-midwives' are (20-24) years old, (77.3%) of the sample were skilled midwives and there is a  significant correlation between pretest and posttest periods after the implementation of education program for nurse- midwives regarding knowledge  about labor pain and non-pharmacological management in reducing labor pain in pregnant women.

Recommendations: The study recommended in-services education for the nurses- midwives' regarding knowledge of the current evidence, and provides experience in the skills necessary to fulfill their responsibility to support pain management during labor and  training primary health care nurses in improved pain management is important part of multi-faced approach towards improving and helping women's to reduce pain during labor.

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Thermophysical properties of [EMIM][BF<sub>4</sub>] and [HMIM][PF<sub>6</sub>] imidazolium ionic liquids with MWCNTs
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Abstract<p>In this study, several ionanofluids (INFs) were prepared in order to study their efficiency as a cooling medium at 25 °C. The two-step technique is used to prepare ionanofluid (INF) by dispersing multi-walled carbon nanotubes (MWCNTs) in two concentrations 0.5 and 1 wt% in ionic liquid (IL). Two types of ionic liquids (ILs) were used: hydrophilic represented by 1-ethyl-3-methylimidazolium tetrafluoroborate [EMIM][BF<sub>4</sub>] and hydrophobic represented by 1-hexyl-3-methylimidazolium hexafluorophosphate [HMIM][PF<sub>6</sub>]. The thermophysical properties of the prepared INFs including thermal conductivity (TC), density and viscosity were measured experimental</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Materials Today: Proceedings
Preparation, characterization and preliminary cytotoxic evaluation of 6-mercaptopurine-coated biotinylated carbon dots nanoparticles as a drug delivery system
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Publication Date
Thu Feb 06 2020
Journal Name
Scientific Reports
Waste foundry sand/MgFe-layered double hydroxides composite material for efficient removal of Congo red dye from aqueous solution
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Abstract<p>We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure</p> ... Show More
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Publication Date
Fri May 07 2021
Journal Name
Journal Of Evaluation In Clinical Practice
Exploring the acceptance of <scp>COVID</scp>‐19 vaccine among healthcare workers and general population using health belief model
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Abstract<sec><title>Rationale, aims and objectives

Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.

Methods

This was a cross‐sectional study based on electronic survey data that was collected in Iraq during December first‐19th, 2020. The electronic surve

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Publication Date
Sat Apr 30 2022
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Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Sat Jun 01 2024
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Optimization of photocatalytic process with SnO2 catalyst for COD reduction from petroleum refinery wastewater using a slurry bubble photoreactor
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